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/-
Copyright (c) 2023 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne
-/
import Mathlib.MeasureTheory.Constructions.Pi
import Mathlib.Probability.Kernel.Basic
/-!
# Independence with respect to a kernel and a measure
A family of sets of sets `π : ι → Set (Set Ω)` is independent with respect to a kernel
`κ : kernel α Ω` and a measure `μ` on `α` if for any finite set of indices `s = {i_1, ..., i_n}`,
for any sets `f i_1 ∈ π i_1, ..., f i_n ∈ π i_n`, then for `μ`-almost every `a : α`,
`κ a (⋂ i in s, f i) = ∏ i ∈ s, κ a (f i)`.
This notion of independence is a generalization of both independence and conditional independence.
For conditional independence, `κ` is the conditional kernel `ProbabilityTheory.condexpKernel` and
`μ` is the ambiant measure. For (non-conditional) independence, `κ = kernel.const Unit μ` and the
measure is the Dirac measure on `Unit`.
The main purpose of this file is to prove only once the properties that hold for both conditional
and non-conditional independence.
## Main definitions
* `ProbabilityTheory.kernel.iIndepSets`: independence of a family of sets of sets.
Variant for two sets of sets: `ProbabilityTheory.kernel.IndepSets`.
* `ProbabilityTheory.kernel.iIndep`: independence of a family of σ-algebras. Variant for two
σ-algebras: `Indep`.
* `ProbabilityTheory.kernel.iIndepSet`: independence of a family of sets. Variant for two sets:
`ProbabilityTheory.kernel.IndepSet`.
* `ProbabilityTheory.kernel.iIndepFun`: independence of a family of functions (random variables).
Variant for two functions: `ProbabilityTheory.kernel.IndepFun`.
See the file `Mathlib/Probability/Kernel/Basic.lean` for a more detailed discussion of these
definitions in the particular case of the usual independence notion.
## Main statements
* `ProbabilityTheory.kernel.iIndepSets.iIndep`: if π-systems are independent as sets of sets,
then the measurable space structures they generate are independent.
* `ProbabilityTheory.kernel.IndepSets.Indep`: variant with two π-systems.
-/
open MeasureTheory MeasurableSpace
open scoped MeasureTheory ENNReal
namespace ProbabilityTheory.kernel
variable {α Ω ι : Type*}
section Definitions
variable {_mα : MeasurableSpace α}
/-- A family of sets of sets `π : ι → Set (Set Ω)` is independent with respect to a kernel `κ` and
a measure `μ` if for any finite set of indices `s = {i_1, ..., i_n}`, for any sets
`f i_1 ∈ π i_1, ..., f i_n ∈ π i_n`, then `∀ᵐ a ∂μ, κ a (⋂ i in s, f i) = ∏ i ∈ s, κ a (f i)`.
It will be used for families of pi_systems. -/
def iIndepSets {_mΩ : MeasurableSpace Ω}
(π : ι → Set (Set Ω)) (κ : kernel α Ω) (μ : Measure α := by volume_tac) : Prop :=
∀ (s : Finset ι) {f : ι → Set Ω} (_H : ∀ i, i ∈ s → f i ∈ π i),
∀ᵐ a ∂μ, κ a (⋂ i ∈ s, f i) = ∏ i ∈ s, κ a (f i)
/-- Two sets of sets `s₁, s₂` are independent with respect to a kernel `κ` and a measure `μ` if for
any sets `t₁ ∈ s₁, t₂ ∈ s₂`, then `∀ᵐ a ∂μ, κ a (t₁ ∩ t₂) = κ a (t₁) * κ a (t₂)` -/
def IndepSets {_mΩ : MeasurableSpace Ω}
(s1 s2 : Set (Set Ω)) (κ : kernel α Ω) (μ : Measure α := by volume_tac) : Prop :=
∀ t1 t2 : Set Ω, t1 ∈ s1 → t2 ∈ s2 → (∀ᵐ a ∂μ, κ a (t1 ∩ t2) = κ a t1 * κ a t2)
/-- A family of measurable space structures (i.e. of σ-algebras) is independent with respect to a
kernel `κ` and a measure `μ` if the family of sets of measurable sets they define is independent. -/
def iIndep (m : ι → MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω} (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
iIndepSets (fun x ↦ {s | MeasurableSet[m x] s}) κ μ
/-- Two measurable space structures (or σ-algebras) `m₁, m₂` are independent with respect to a
kernel `κ` and a measure `μ` if for any sets `t₁ ∈ m₁, t₂ ∈ m₂`,
`∀ᵐ a ∂μ, κ a (t₁ ∩ t₂) = κ a (t₁) * κ a (t₂)` -/
def Indep (m₁ m₂ : MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω} (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
IndepSets {s | MeasurableSet[m₁] s} {s | MeasurableSet[m₂] s} κ μ
/-- A family of sets is independent if the family of measurable space structures they generate is
independent. For a set `s`, the generated measurable space has measurable sets `∅, s, sᶜ, univ`. -/
def iIndepSet {_mΩ : MeasurableSpace Ω} (s : ι → Set Ω) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
iIndep (fun i ↦ generateFrom {s i}) κ μ
/-- Two sets are independent if the two measurable space structures they generate are independent.
For a set `s`, the generated measurable space structure has measurable sets `∅, s, sᶜ, univ`. -/
def IndepSet {_mΩ : MeasurableSpace Ω} (s t : Set Ω) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
Indep (generateFrom {s}) (generateFrom {t}) κ μ
/-- A family of functions defined on the same space `Ω` and taking values in possibly different
spaces, each with a measurable space structure, is independent if the family of measurable space
structures they generate on `Ω` is independent. For a function `g` with codomain having measurable
space structure `m`, the generated measurable space structure is `MeasurableSpace.comap g m`. -/
def iIndepFun {_mΩ : MeasurableSpace Ω} {β : ι → Type*} (m : ∀ x : ι, MeasurableSpace (β x))
(f : ∀ x : ι, Ω → β x) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
iIndep (fun x ↦ MeasurableSpace.comap (f x) (m x)) κ μ
/-- Two functions are independent if the two measurable space structures they generate are
independent. For a function `f` with codomain having measurable space structure `m`, the generated
measurable space structure is `MeasurableSpace.comap f m`. -/
def IndepFun {β γ} {_mΩ : MeasurableSpace Ω} [mβ : MeasurableSpace β] [mγ : MeasurableSpace γ]
(f : Ω → β) (g : Ω → γ) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
Indep (MeasurableSpace.comap f mβ) (MeasurableSpace.comap g mγ) κ μ
end Definitions
section ByDefinition
variable {β : ι → Type*} {mβ : ∀ i, MeasurableSpace (β i)}
{_mα : MeasurableSpace α} {m : ι → MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α}
{π : ι → Set (Set Ω)} {s : ι → Set Ω} {S : Finset ι} {f : ∀ x : ι, Ω → β x}
lemma iIndepSets.meas_biInter (h : iIndepSets π κ μ) (s : Finset ι)
{f : ι → Set Ω} (hf : ∀ i, i ∈ s → f i ∈ π i) :
∀ᵐ a ∂μ, κ a (⋂ i ∈ s, f i) = ∏ i ∈ s, κ a (f i) := h s hf
lemma iIndepSets.meas_iInter [Fintype ι] (h : iIndepSets π κ μ) (hs : ∀ i, s i ∈ π i) :
∀ᵐ a ∂μ, κ a (⋂ i, s i) = ∏ i, κ a (s i) := by
filter_upwards [h.meas_biInter Finset.univ (fun _i _ ↦ hs _)] with a ha using by simp [← ha]
lemma iIndep.iIndepSets' (hμ : iIndep m κ μ) :
iIndepSets (fun x ↦ {s | MeasurableSet[m x] s}) κ μ := hμ
lemma iIndep.meas_biInter (hμ : iIndep m κ μ) (hs : ∀ i, i ∈ S → MeasurableSet[m i] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i ∈ S, s i) = ∏ i ∈ S, κ a (s i) := hμ _ hs
lemma iIndep.meas_iInter [Fintype ι] (h : iIndep m κ μ) (hs : ∀ i, MeasurableSet[m i] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i, s i) = ∏ i, κ a (s i) := by
filter_upwards [h.meas_biInter (fun i (_ : i ∈ Finset.univ) ↦ hs _)] with a ha
simp [← ha]
protected lemma iIndepFun.iIndep (hf : iIndepFun mβ f κ μ) :
iIndep (fun x ↦ (mβ x).comap (f x)) κ μ := hf
lemma iIndepFun.meas_biInter (hf : iIndepFun mβ f κ μ)
(hs : ∀ i, i ∈ S → MeasurableSet[(mβ i).comap (f i)] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i ∈ S, s i) = ∏ i ∈ S, κ a (s i) := hf.iIndep.meas_biInter hs
lemma iIndepFun.meas_iInter [Fintype ι] (hf : iIndepFun mβ f κ μ)
(hs : ∀ i, MeasurableSet[(mβ i).comap (f i)] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i, s i) = ∏ i, κ a (s i) := hf.iIndep.meas_iInter hs
lemma IndepFun.meas_inter {β γ : Type*} [mβ : MeasurableSpace β] [mγ : MeasurableSpace γ]
{f : Ω → β} {g : Ω → γ} (hfg : IndepFun f g κ μ)
{s t : Set Ω} (hs : MeasurableSet[mβ.comap f] s) (ht : MeasurableSet[mγ.comap g] t) :
∀ᵐ a ∂μ, κ a (s ∩ t) = κ a s * κ a t := hfg _ _ hs ht
end ByDefinition
section Indep
variable {_mα : MeasurableSpace α}
@[symm]
theorem IndepSets.symm {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α}
{s₁ s₂ : Set (Set Ω)} (h : IndepSets s₁ s₂ κ μ) :
IndepSets s₂ s₁ κ μ := by
intros t1 t2 ht1 ht2
filter_upwards [h t2 t1 ht2 ht1] with a ha
rwa [Set.inter_comm, mul_comm]
@[symm]
theorem Indep.symm {m₁ m₂ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω}
{μ : Measure α} (h : Indep m₁ m₂ κ μ) :
Indep m₂ m₁ κ μ :=
IndepSets.symm h
theorem indep_bot_right (m' : MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] :
Indep m' ⊥ κ μ := by
intros s t _ ht
rw [Set.mem_setOf_eq, MeasurableSpace.measurableSet_bot_iff] at ht
refine Filter.eventually_of_forall (fun a ↦ ?_)
cases' ht with ht ht
· rw [ht, Set.inter_empty, measure_empty, mul_zero]
· rw [ht, Set.inter_univ, measure_univ, mul_one]
theorem indep_bot_left (m' : MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] :
Indep ⊥ m' κ μ := (indep_bot_right m').symm
theorem indepSet_empty_right {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] (s : Set Ω) :
IndepSet s ∅ κ μ := by
simp only [IndepSet, generateFrom_singleton_empty];
exact indep_bot_right _
theorem indepSet_empty_left {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω}
{μ : Measure α} [IsMarkovKernel κ] (s : Set Ω) :
IndepSet ∅ s κ μ :=
(indepSet_empty_right s).symm
theorem indepSets_of_indepSets_of_le_left {s₁ s₂ s₃ : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : IndepSets s₁ s₂ κ μ) (h31 : s₃ ⊆ s₁) :
IndepSets s₃ s₂ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 (Set.mem_of_subset_of_mem h31 ht1) ht2
theorem indepSets_of_indepSets_of_le_right {s₁ s₂ s₃ : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : IndepSets s₁ s₂ κ μ) (h32 : s₃ ⊆ s₂) :
IndepSets s₁ s₃ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 ht1 (Set.mem_of_subset_of_mem h32 ht2)
theorem indep_of_indep_of_le_left {m₁ m₂ m₃ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : Indep m₁ m₂ κ μ) (h31 : m₃ ≤ m₁) :
Indep m₃ m₂ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 (h31 _ ht1) ht2
theorem indep_of_indep_of_le_right {m₁ m₂ m₃ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : Indep m₁ m₂ κ μ) (h32 : m₃ ≤ m₂) :
Indep m₁ m₃ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 ht1 (h32 _ ht2)
theorem IndepSets.union {s₁ s₂ s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α}
(h₁ : IndepSets s₁ s' κ μ) (h₂ : IndepSets s₂ s' κ μ) :
IndepSets (s₁ ∪ s₂) s' κ μ := by
intro t1 t2 ht1 ht2
cases' (Set.mem_union _ _ _).mp ht1 with ht1₁ ht1₂
· exact h₁ t1 t2 ht1₁ ht2
· exact h₂ t1 t2 ht1₂ ht2
@[simp]
theorem IndepSets.union_iff {s₁ s₂ s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
IndepSets (s₁ ∪ s₂) s' κ μ ↔ IndepSets s₁ s' κ μ ∧ IndepSets s₂ s' κ μ :=
⟨fun h =>
⟨indepSets_of_indepSets_of_le_left h Set.subset_union_left,
indepSets_of_indepSets_of_le_left h Set.subset_union_right⟩,
fun h => IndepSets.union h.left h.right⟩
theorem IndepSets.iUnion {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (hyp : ∀ n, IndepSets (s n) s' κ μ) :
IndepSets (⋃ n, s n) s' κ μ := by
intro t1 t2 ht1 ht2
rw [Set.mem_iUnion] at ht1
cases' ht1 with n ht1
exact hyp n t1 t2 ht1 ht2
theorem IndepSets.bUnion {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {u : Set ι} (hyp : ∀ n ∈ u, IndepSets (s n) s' κ μ) :
IndepSets (⋃ n ∈ u, s n) s' κ μ := by
intro t1 t2 ht1 ht2
simp_rw [Set.mem_iUnion] at ht1
rcases ht1 with ⟨n, hpn, ht1⟩
exact hyp n hpn t1 t2 ht1 ht2
theorem IndepSets.inter {s₁ s' : Set (Set Ω)} (s₂ : Set (Set Ω)) {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h₁ : IndepSets s₁ s' κ μ) :
IndepSets (s₁ ∩ s₂) s' κ μ :=
fun t1 t2 ht1 ht2 => h₁ t1 t2 ((Set.mem_inter_iff _ _ _).mp ht1).left ht2
theorem IndepSets.iInter {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h : ∃ n, IndepSets (s n) s' κ μ) :
IndepSets (⋂ n, s n) s' κ μ := by
intro t1 t2 ht1 ht2; cases' h with n h; exact h t1 t2 (Set.mem_iInter.mp ht1 n) ht2
theorem IndepSets.bInter {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {u : Set ι} (h : ∃ n ∈ u, IndepSets (s n) s' κ μ) :
IndepSets (⋂ n ∈ u, s n) s' κ μ := by
intro t1 t2 ht1 ht2
rcases h with ⟨n, hn, h⟩
exact h t1 t2 (Set.biInter_subset_of_mem hn ht1) ht2
theorem iIndep_comap_mem_iff {f : ι → Set Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
iIndep (fun i => MeasurableSpace.comap (· ∈ f i) ⊤) κ μ ↔ iIndepSet f κ μ := by
simp_rw [← generateFrom_singleton, iIndepSet]
theorem iIndepSets_singleton_iff {s : ι → Set Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
iIndepSets (fun i ↦ {s i}) κ μ ↔
∀ S : Finset ι, ∀ᵐ a ∂μ, κ a (⋂ i ∈ S, s i) = ∏ i ∈ S, κ a (s i) := by
refine ⟨fun h S ↦ h S (fun i _ ↦ rfl), fun h S f hf ↦ ?_⟩
filter_upwards [h S] with a ha
have : ∀ i ∈ S, κ a (f i) = κ a (s i) := fun i hi ↦ by rw [hf i hi]
rwa [Finset.prod_congr rfl this, Set.iInter₂_congr hf]
theorem indepSets_singleton_iff {s t : Set Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
IndepSets {s} {t} κ μ ↔ ∀ᵐ a ∂μ, κ a (s ∩ t) = κ a s * κ a t :=
⟨fun h ↦ h s t rfl rfl,
fun h s1 t1 hs1 ht1 ↦ by rwa [Set.mem_singleton_iff.mp hs1, Set.mem_singleton_iff.mp ht1]⟩
end Indep
/-! ### Deducing `Indep` from `iIndep` -/
section FromiIndepToIndep
variable {_mα : MeasurableSpace α}
theorem iIndepSets.indepSets {s : ι → Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : iIndepSets s κ μ) {i j : ι} (hij : i ≠ j) :
IndepSets (s i) (s j) κ μ := by
classical
intro t₁ t₂ ht₁ ht₂
have hf_m : ∀ x : ι, x ∈ ({i, j} : Finset ι) → ite (x = i) t₁ t₂ ∈ s x := by
intro x hx
cases' Finset.mem_insert.mp hx with hx hx
· simp [hx, ht₁]
· simp [Finset.mem_singleton.mp hx, hij.symm, ht₂]
have h1 : t₁ = ite (i = i) t₁ t₂ := by simp only [if_true, eq_self_iff_true]
have h2 : t₂ = ite (j = i) t₁ t₂ := by simp only [hij.symm, if_false]
have h_inter : ⋂ (t : ι) (_ : t ∈ ({i, j} : Finset ι)), ite (t = i) t₁ t₂ =
ite (i = i) t₁ t₂ ∩ ite (j = i) t₁ t₂ := by
simp only [Finset.set_biInter_singleton, Finset.set_biInter_insert]
filter_upwards [h_indep {i, j} hf_m] with a h_indep'
have h_prod : (∏ t ∈ ({i, j} : Finset ι), κ a (ite (t = i) t₁ t₂))
= κ a (ite (i = i) t₁ t₂) * κ a (ite (j = i) t₁ t₂) := by
simp only [hij, Finset.prod_singleton, Finset.prod_insert, not_false_iff,
Finset.mem_singleton]
rw [h1]
nth_rw 2 [h2]
nth_rw 4 [h2]
rw [← h_inter, ← h_prod, h_indep']
theorem iIndep.indep {m : ι → MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α}
(h_indep : iIndep m κ μ) {i j : ι} (hij : i ≠ j) : Indep (m i) (m j) κ μ :=
iIndepSets.indepSets h_indep hij
theorem iIndepFun.indepFun {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {β : ι → Type*}
{m : ∀ x, MeasurableSpace (β x)} {f : ∀ i, Ω → β i} (hf_Indep : iIndepFun m f κ μ) {i j : ι}
(hij : i ≠ j) : IndepFun (f i) (f j) κ μ :=
hf_Indep.indep hij
end FromiIndepToIndep
/-!
## π-system lemma
Independence of measurable spaces is equivalent to independence of generating π-systems.
-/
section FromMeasurableSpacesToSetsOfSets
/-! ### Independence of measurable space structures implies independence of generating π-systems -/
variable {_mα : MeasurableSpace α}
theorem iIndep.iIndepSets {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {m : ι → MeasurableSpace Ω}
{s : ι → Set (Set Ω)} (hms : ∀ n, m n = generateFrom (s n)) (h_indep : iIndep m κ μ) :
iIndepSets s κ μ :=
fun S f hfs =>
h_indep S fun x hxS =>
((hms x).symm ▸ measurableSet_generateFrom (hfs x hxS) : MeasurableSet[m x] (f x))
theorem Indep.indepSets {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {s1 s2 : Set (Set Ω)}
(h_indep : Indep (generateFrom s1) (generateFrom s2) κ μ) :
IndepSets s1 s2 κ μ :=
fun t1 t2 ht1 ht2 =>
h_indep t1 t2 (measurableSet_generateFrom ht1) (measurableSet_generateFrom ht2)
end FromMeasurableSpacesToSetsOfSets
section FromPiSystemsToMeasurableSpaces
/-! ### Independence of generating π-systems implies independence of measurable space structures -/
variable {_mα : MeasurableSpace α}
theorem IndepSets.indep_aux {m₂ m : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] {p1 p2 : Set (Set Ω)} (h2 : m₂ ≤ m)
(hp2 : IsPiSystem p2) (hpm2 : m₂ = generateFrom p2) (hyp : IndepSets p1 p2 κ μ) {t1 t2 : Set Ω}
(ht1 : t1 ∈ p1) (ht1m : MeasurableSet[m] t1) (ht2m : MeasurableSet[m₂] t2) :
∀ᵐ a ∂μ, κ a (t1 ∩ t2) = κ a t1 * κ a t2 := by
refine @induction_on_inter _ (fun t ↦ ∀ᵐ a ∂μ, κ a (t1 ∩ t) = κ a t1 * κ a t) _
m₂ hpm2 hp2 ?_ ?_ ?_ ?_ t2 ht2m
· simp only [Set.inter_empty, measure_empty, mul_zero, eq_self_iff_true,
Filter.eventually_true]
· exact fun t ht_mem_p2 ↦ hyp t1 t ht1 ht_mem_p2
· intros t ht h
filter_upwards [h] with a ha
have : t1 ∩ tᶜ = t1 \ (t1 ∩ t) := by
rw [Set.diff_self_inter, Set.diff_eq_compl_inter, Set.inter_comm]
rw [this,
measure_diff Set.inter_subset_left (ht1m.inter (h2 _ ht)) (measure_ne_top (κ a) _),
measure_compl (h2 _ ht) (measure_ne_top (κ a) t), measure_univ,
ENNReal.mul_sub (fun _ _ ↦ measure_ne_top (κ a) _), mul_one, ha]
· intros f hf_disj hf_meas h
rw [← ae_all_iff] at h
filter_upwards [h] with a ha
rw [Set.inter_iUnion, measure_iUnion]
· rw [measure_iUnion hf_disj (fun i ↦ h2 _ (hf_meas i))]
rw [← ENNReal.tsum_mul_left]
congr with i
rw [ha i]
· intros i j hij
rw [Function.onFun, Set.inter_comm t1, Set.inter_comm t1]
exact Disjoint.inter_left _ (Disjoint.inter_right _ (hf_disj hij))
· exact fun i ↦ ht1m.inter (h2 _ (hf_meas i))
/-- The measurable space structures generated by independent pi-systems are independent. -/
theorem IndepSets.indep {m1 m2 m : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α}
[IsMarkovKernel κ] {p1 p2 : Set (Set Ω)} (h1 : m1 ≤ m) (h2 : m2 ≤ m) (hp1 : IsPiSystem p1)
(hp2 : IsPiSystem p2) (hpm1 : m1 = generateFrom p1) (hpm2 : m2 = generateFrom p2)
(hyp : IndepSets p1 p2 κ μ) :
Indep m1 m2 κ μ := by
intros t1 t2 ht1 ht2
refine @induction_on_inter _ (fun t ↦ ∀ᵐ (a : α) ∂μ, κ a (t ∩ t2) = κ a t * κ a t2) _ m1 hpm1 hp1
?_ ?_ ?_ ?_ _ ht1
· simp only [Set.empty_inter, measure_empty, zero_mul, eq_self_iff_true,
Filter.eventually_true]
· intros t ht_mem_p1
have ht1 : MeasurableSet[m] t := by
refine h1 _ ?_
rw [hpm1]
exact measurableSet_generateFrom ht_mem_p1
exact IndepSets.indep_aux h2 hp2 hpm2 hyp ht_mem_p1 ht1 ht2
· intros t ht h
filter_upwards [h] with a ha
have : tᶜ ∩ t2 = t2 \ (t ∩ t2) := by
rw [Set.inter_comm t, Set.diff_self_inter, Set.diff_eq_compl_inter]
rw [this, Set.inter_comm t t2,
measure_diff Set.inter_subset_left ((h2 _ ht2).inter (h1 _ ht))
(measure_ne_top (κ a) _),
Set.inter_comm, ha, measure_compl (h1 _ ht) (measure_ne_top (κ a) t), measure_univ,
mul_comm (1 - κ a t), ENNReal.mul_sub (fun _ _ ↦ measure_ne_top (κ a) _), mul_one, mul_comm]
· intros f hf_disj hf_meas h
rw [← ae_all_iff] at h
filter_upwards [h] with a ha
rw [Set.inter_comm, Set.inter_iUnion, measure_iUnion]
· rw [measure_iUnion hf_disj (fun i ↦ h1 _ (hf_meas i))]
rw [← ENNReal.tsum_mul_right]
congr 1 with i
rw [Set.inter_comm t2, ha i]
· intros i j hij
rw [Function.onFun, Set.inter_comm t2, Set.inter_comm t2]
exact Disjoint.inter_left _ (Disjoint.inter_right _ (hf_disj hij))
· exact fun i ↦ (h2 _ ht2).inter (h1 _ (hf_meas i))
theorem IndepSets.indep' {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ]
{p1 p2 : Set (Set Ω)} (hp1m : ∀ s ∈ p1, MeasurableSet s) (hp2m : ∀ s ∈ p2, MeasurableSet s)
(hp1 : IsPiSystem p1) (hp2 : IsPiSystem p2) (hyp : IndepSets p1 p2 κ μ) :
Indep (generateFrom p1) (generateFrom p2) κ μ :=
hyp.indep (generateFrom_le hp1m) (generateFrom_le hp2m) hp1 hp2 rfl rfl
variable {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α}
theorem indepSets_piiUnionInter_of_disjoint [IsMarkovKernel κ] {s : ι → Set (Set Ω)}
{S T : Set ι} (h_indep : iIndepSets s κ μ) (hST : Disjoint S T) :
IndepSets (piiUnionInter s S) (piiUnionInter s T) κ μ := by
rintro t1 t2 ⟨p1, hp1, f1, ht1_m, ht1_eq⟩ ⟨p2, hp2, f2, ht2_m, ht2_eq⟩
classical
let g i := ite (i ∈ p1) (f1 i) Set.univ ∩ ite (i ∈ p2) (f2 i) Set.univ
have h_P_inter : ∀ᵐ a ∂μ, κ a (t1 ∩ t2) = ∏ n ∈ p1 ∪ p2, κ a (g n) := by
have hgm : ∀ i ∈ p1 ∪ p2, g i ∈ s i := by
intro i hi_mem_union
rw [Finset.mem_union] at hi_mem_union
cases' hi_mem_union with hi1 hi2
· have hi2 : i ∉ p2 := fun hip2 => Set.disjoint_left.mp hST (hp1 hi1) (hp2 hip2)
simp_rw [g, if_pos hi1, if_neg hi2, Set.inter_univ]
exact ht1_m i hi1
· have hi1 : i ∉ p1 := fun hip1 => Set.disjoint_right.mp hST (hp2 hi2) (hp1 hip1)
simp_rw [g, if_neg hi1, if_pos hi2, Set.univ_inter]
exact ht2_m i hi2
have h_p1_inter_p2 :
((⋂ x ∈ p1, f1 x) ∩ ⋂ x ∈ p2, f2 x) =
⋂ i ∈ p1 ∪ p2, ite (i ∈ p1) (f1 i) Set.univ ∩ ite (i ∈ p2) (f2 i) Set.univ := by
ext1 x
simp only [Set.mem_ite_univ_right, Set.mem_inter_iff, Set.mem_iInter, Finset.mem_union]
exact
⟨fun h i _ => ⟨h.1 i, h.2 i⟩, fun h =>
⟨fun i hi => (h i (Or.inl hi)).1 hi, fun i hi => (h i (Or.inr hi)).2 hi⟩⟩
filter_upwards [h_indep _ hgm] with a ha
rw [ht1_eq, ht2_eq, h_p1_inter_p2, ← ha]
filter_upwards [h_P_inter, h_indep p1 ht1_m, h_indep p2 ht2_m] with a h_P_inter ha1 ha2
have h_μg : ∀ n, κ a (g n) = (ite (n ∈ p1) (κ a (f1 n)) 1) * (ite (n ∈ p2) (κ a (f2 n)) 1) := by
intro n
dsimp only [g]
split_ifs with h1 h2
· exact absurd rfl (Set.disjoint_iff_forall_ne.mp hST (hp1 h1) (hp2 h2))
all_goals simp only [measure_univ, one_mul, mul_one, Set.inter_univ, Set.univ_inter]
simp_rw [h_P_inter, h_μg, Finset.prod_mul_distrib,
Finset.prod_ite_mem (p1 ∪ p2) p1 (fun x ↦ κ a (f1 x)), Finset.union_inter_cancel_left,
Finset.prod_ite_mem (p1 ∪ p2) p2 (fun x => κ a (f2 x)), Finset.union_inter_cancel_right, ht1_eq,
← ha1, ht2_eq, ← ha2]
theorem iIndepSet.indep_generateFrom_of_disjoint [IsMarkovKernel κ] {s : ι → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (S T : Set ι) (hST : Disjoint S T) :
Indep (generateFrom { t | ∃ n ∈ S, s n = t }) (generateFrom { t | ∃ k ∈ T, s k = t }) κ μ := by
rw [← generateFrom_piiUnionInter_singleton_left, ← generateFrom_piiUnionInter_singleton_left]
refine
IndepSets.indep'
(fun t ht => generateFrom_piiUnionInter_le _ ?_ _ _ (measurableSet_generateFrom ht))
(fun t ht => generateFrom_piiUnionInter_le _ ?_ _ _ (measurableSet_generateFrom ht)) ?_ ?_ ?_
· exact fun k => generateFrom_le fun t ht => (Set.mem_singleton_iff.1 ht).symm ▸ hsm k
· exact fun k => generateFrom_le fun t ht => (Set.mem_singleton_iff.1 ht).symm ▸ hsm k
· exact isPiSystem_piiUnionInter _ (fun k => IsPiSystem.singleton _) _
· exact isPiSystem_piiUnionInter _ (fun k => IsPiSystem.singleton _) _
· classical exact indepSets_piiUnionInter_of_disjoint (iIndep.iIndepSets (fun n => rfl) hs) hST
theorem indep_iSup_of_disjoint [IsMarkovKernel κ] {m : ι → MeasurableSpace Ω}
(h_le : ∀ i, m i ≤ _mΩ) (h_indep : iIndep m κ μ) {S T : Set ι} (hST : Disjoint S T) :
Indep (⨆ i ∈ S, m i) (⨆ i ∈ T, m i) κ μ := by
refine
IndepSets.indep (iSup₂_le fun i _ => h_le i) (iSup₂_le fun i _ => h_le i) ?_ ?_
(generateFrom_piiUnionInter_measurableSet m S).symm
(generateFrom_piiUnionInter_measurableSet m T).symm ?_
· exact isPiSystem_piiUnionInter _ (fun n => @isPiSystem_measurableSet Ω (m n)) _
· exact isPiSystem_piiUnionInter _ (fun n => @isPiSystem_measurableSet Ω (m n)) _
· classical exact indepSets_piiUnionInter_of_disjoint h_indep hST
theorem indep_iSup_of_directed_le {Ω} {m : ι → MeasurableSpace Ω} {m' m0 : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] (h_indep : ∀ i, Indep (m i) m' κ μ)
(h_le : ∀ i, m i ≤ m0) (h_le' : m' ≤ m0) (hm : Directed (· ≤ ·) m) :
Indep (⨆ i, m i) m' κ μ := by
let p : ι → Set (Set Ω) := fun n => { t | MeasurableSet[m n] t }
have hp : ∀ n, IsPiSystem (p n) := fun n => @isPiSystem_measurableSet Ω (m n)
have h_gen_n : ∀ n, m n = generateFrom (p n) := fun n =>
(@generateFrom_measurableSet Ω (m n)).symm
have hp_supr_pi : IsPiSystem (⋃ n, p n) := isPiSystem_iUnion_of_directed_le p hp hm
let p' := { t : Set Ω | MeasurableSet[m'] t }
have hp'_pi : IsPiSystem p' := @isPiSystem_measurableSet Ω m'
have h_gen' : m' = generateFrom p' := (@generateFrom_measurableSet Ω m').symm
-- the π-systems defined are independent
have h_pi_system_indep : IndepSets (⋃ n, p n) p' κ μ := by
refine IndepSets.iUnion ?_
conv at h_indep =>
intro i
rw [h_gen_n i, h_gen']
exact fun n => (h_indep n).indepSets
-- now go from π-systems to σ-algebras
refine IndepSets.indep (iSup_le h_le) h_le' hp_supr_pi hp'_pi ?_ h_gen' h_pi_system_indep
exact (generateFrom_iUnion_measurableSet _).symm
theorem iIndepSet.indep_generateFrom_lt [Preorder ι] [IsMarkovKernel κ] {s : ι → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (i : ι) :
Indep (generateFrom {s i}) (generateFrom { t | ∃ j < i, s j = t }) κ μ := by
convert iIndepSet.indep_generateFrom_of_disjoint hsm hs {i} { j | j < i }
(Set.disjoint_singleton_left.mpr (lt_irrefl _))
simp only [Set.mem_singleton_iff, exists_prop, exists_eq_left, Set.setOf_eq_eq_singleton']
theorem iIndepSet.indep_generateFrom_le [LinearOrder ι] [IsMarkovKernel κ] {s : ι → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (i : ι) {k : ι} (hk : i < k) :
Indep (generateFrom {s k}) (generateFrom { t | ∃ j ≤ i, s j = t }) κ μ := by
convert iIndepSet.indep_generateFrom_of_disjoint hsm hs {k} { j | j ≤ i }
(Set.disjoint_singleton_left.mpr hk.not_le)
simp only [Set.mem_singleton_iff, exists_prop, exists_eq_left, Set.setOf_eq_eq_singleton']
theorem iIndepSet.indep_generateFrom_le_nat [IsMarkovKernel κ] {s : ℕ → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (n : ℕ) :
Indep (generateFrom {s (n + 1)}) (generateFrom { t | ∃ k ≤ n, s k = t }) κ μ :=
iIndepSet.indep_generateFrom_le hsm hs _ n.lt_succ_self
theorem indep_iSup_of_monotone [SemilatticeSup ι] {Ω} {m : ι → MeasurableSpace Ω}
{m' m0 : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ]
(h_indep : ∀ i, Indep (m i) m' κ μ) (h_le : ∀ i, m i ≤ m0) (h_le' : m' ≤ m0)
(hm : Monotone m) :
Indep (⨆ i, m i) m' κ μ :=
indep_iSup_of_directed_le h_indep h_le h_le' (Monotone.directed_le hm)
theorem indep_iSup_of_antitone [SemilatticeInf ι] {Ω} {m : ι → MeasurableSpace Ω}
{m' m0 : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ]
(h_indep : ∀ i, Indep (m i) m' κ μ) (h_le : ∀ i, m i ≤ m0) (h_le' : m' ≤ m0)
(hm : Antitone m) :
Indep (⨆ i, m i) m' κ μ :=
indep_iSup_of_directed_le h_indep h_le h_le' hm.directed_le
theorem iIndepSets.piiUnionInter_of_not_mem {π : ι → Set (Set Ω)} {a : ι} {S : Finset ι}
(hp_ind : iIndepSets π κ μ) (haS : a ∉ S) :
IndepSets (piiUnionInter π S) (π a) κ μ := by
rintro t1 t2 ⟨s, hs_mem, ft1, hft1_mem, ht1_eq⟩ ht2_mem_pia
rw [Finset.coe_subset] at hs_mem
classical
let f := fun n => ite (n = a) t2 (ite (n ∈ s) (ft1 n) Set.univ)
have h_f_mem : ∀ n ∈ insert a s, f n ∈ π n := by
intro n hn_mem_insert
dsimp only [f]
cases' Finset.mem_insert.mp hn_mem_insert with hn_mem hn_mem
· simp [hn_mem, ht2_mem_pia]
· have hn_ne_a : n ≠ a := by rintro rfl; exact haS (hs_mem hn_mem)
simp [hn_ne_a, hn_mem, hft1_mem n hn_mem]
have h_f_mem_pi : ∀ n ∈ s, f n ∈ π n := fun x hxS => h_f_mem x (by simp [hxS])
have h_t1 : t1 = ⋂ n ∈ s, f n := by
suffices h_forall : ∀ n ∈ s, f n = ft1 n by
rw [ht1_eq]
ext x
simp_rw [Set.mem_iInter]
conv => lhs; intro i hns; rw [← h_forall i hns]
intro n hnS
have hn_ne_a : n ≠ a := by rintro rfl; exact haS (hs_mem hnS)
simp_rw [f, if_pos hnS, if_neg hn_ne_a]
have h_μ_t1 : ∀ᵐ a' ∂μ, κ a' t1 = ∏ n ∈ s, κ a' (f n) := by
filter_upwards [hp_ind s h_f_mem_pi] with a' ha'
rw [h_t1, ← ha']
have h_t2 : t2 = f a := by simp [f]
have h_μ_inter : ∀ᵐ a' ∂μ, κ a' (t1 ∩ t2) = ∏ n ∈ insert a s, κ a' (f n) := by
have h_t1_inter_t2 : t1 ∩ t2 = ⋂ n ∈ insert a s, f n := by
rw [h_t1, h_t2, Finset.set_biInter_insert, Set.inter_comm]
filter_upwards [hp_ind (insert a s) h_f_mem] with a' ha'
rw [h_t1_inter_t2, ← ha']
have has : a ∉ s := fun has_mem => haS (hs_mem has_mem)
filter_upwards [h_μ_t1, h_μ_inter] with a' ha1 ha2
rw [ha2, Finset.prod_insert has, h_t2, mul_comm, ha1]
/-- The measurable space structures generated by independent pi-systems are independent. -/
theorem iIndepSets.iIndep [IsMarkovKernel κ] (m : ι → MeasurableSpace Ω)
(h_le : ∀ i, m i ≤ _mΩ) (π : ι → Set (Set Ω)) (h_pi : ∀ n, IsPiSystem (π n))
(h_generate : ∀ i, m i = generateFrom (π i)) (h_ind : iIndepSets π κ μ) :
iIndep m κ μ := by
classical
intro s f
refine Finset.induction ?_ ?_ s
· simp only [Finset.not_mem_empty, Set.mem_setOf_eq, IsEmpty.forall_iff, implies_true,
Set.iInter_of_empty, Set.iInter_univ, measure_univ, Finset.prod_empty,
Filter.eventually_true, forall_true_left]
· intro a S ha_notin_S h_rec hf_m
have hf_m_S : ∀ x ∈ S, MeasurableSet[m x] (f x) := fun x hx => hf_m x (by simp [hx])
let p := piiUnionInter π S
set m_p := generateFrom p with hS_eq_generate
have h_indep : Indep m_p (m a) κ μ := by
have hp : IsPiSystem p := isPiSystem_piiUnionInter π h_pi S
have h_le' : ∀ i, generateFrom (π i) ≤ _mΩ := fun i ↦ (h_generate i).symm.trans_le (h_le i)
have hm_p : m_p ≤ _mΩ := generateFrom_piiUnionInter_le π h_le' S
exact IndepSets.indep hm_p (h_le a) hp (h_pi a) hS_eq_generate (h_generate a)
(iIndepSets.piiUnionInter_of_not_mem h_ind ha_notin_S)
have h := h_indep.symm (f a) (⋂ n ∈ S, f n) (hf_m a (Finset.mem_insert_self a S)) ?_
· filter_upwards [h_rec hf_m_S, h] with a' ha' h'
rwa [Finset.set_biInter_insert, Finset.prod_insert ha_notin_S, ← ha']
· have h_le_p : ∀ i ∈ S, m i ≤ m_p := by
intros n hn
rw [hS_eq_generate, h_generate n]
exact le_generateFrom_piiUnionInter (S : Set ι) hn
have h_S_f : ∀ i ∈ S, MeasurableSet[m_p] (f i) :=
fun i hi ↦ (h_le_p i hi) (f i) (hf_m_S i hi)
exact S.measurableSet_biInter h_S_f
end FromPiSystemsToMeasurableSpaces
section IndepSet
/-! ### Independence of measurable sets
We prove the following equivalences on `IndepSet`, for measurable sets `s, t`.
* `IndepSet s t κ μ ↔ ∀ᵐ a ∂μ, κ a (s ∩ t) = κ a s * κ a t`,
* `IndepSet s t κ μ ↔ IndepSets {s} {t} κ μ`.
-/
variable {_mα : MeasurableSpace α}
theorem iIndepSet_iff_iIndepSets_singleton {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω}
[IsMarkovKernel κ] {μ : Measure α} {f : ι → Set Ω}
(hf : ∀ i, MeasurableSet (f i)) :
iIndepSet f κ μ ↔ iIndepSets (fun i ↦ {f i}) κ μ :=
⟨iIndep.iIndepSets fun _ ↦ rfl,
iIndepSets.iIndep _ (fun i ↦ generateFrom_le <| by rintro t (rfl : t = _); exact hf _) _
(fun _ ↦ IsPiSystem.singleton _) fun _ ↦ rfl⟩
theorem iIndepSet_iff_meas_biInter {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω}
[IsMarkovKernel κ] {μ : Measure α} {f : ι → Set Ω} (hf : ∀ i, MeasurableSet (f i)) :
iIndepSet f κ μ ↔ ∀ s, ∀ᵐ a ∂μ, κ a (⋂ i ∈ s, f i) = ∏ i ∈ s, κ a (f i) :=
(iIndepSet_iff_iIndepSets_singleton hf).trans iIndepSets_singleton_iff
theorem iIndepSets.iIndepSet_of_mem {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω}
[IsMarkovKernel κ] {μ : Measure α} {π : ι → Set (Set Ω)} {f : ι → Set Ω}
(hfπ : ∀ i, f i ∈ π i) (hf : ∀ i, MeasurableSet (f i))
(hπ : iIndepSets π κ μ) :
iIndepSet f κ μ :=
(iIndepSet_iff_meas_biInter hf).2 fun _t ↦ hπ.meas_biInter _ fun _i _ ↦ hfπ _
variable {s t : Set Ω} (S T : Set (Set Ω))
theorem indepSet_iff_indepSets_singleton {m0 : MeasurableSpace Ω} (hs_meas : MeasurableSet s)
(ht_meas : MeasurableSet t) (κ : kernel α Ω) (μ : Measure α)
[IsMarkovKernel κ] :
IndepSet s t κ μ ↔ IndepSets {s} {t} κ μ :=
⟨Indep.indepSets, fun h =>
IndepSets.indep
(generateFrom_le fun u hu => by rwa [Set.mem_singleton_iff.mp hu])
(generateFrom_le fun u hu => by rwa [Set.mem_singleton_iff.mp hu])
(IsPiSystem.singleton s) (IsPiSystem.singleton t) rfl rfl h⟩
theorem indepSet_iff_measure_inter_eq_mul {_m0 : MeasurableSpace Ω} (hs_meas : MeasurableSet s)
(ht_meas : MeasurableSet t) (κ : kernel α Ω) (μ : Measure α)
[IsMarkovKernel κ] :
IndepSet s t κ μ ↔ ∀ᵐ a ∂μ, κ a (s ∩ t) = κ a s * κ a t :=
(indepSet_iff_indepSets_singleton hs_meas ht_meas κ μ).trans indepSets_singleton_iff
theorem IndepSets.indepSet_of_mem {_m0 : MeasurableSpace Ω} (hs : s ∈ S) (ht : t ∈ T)
(hs_meas : MeasurableSet s) (ht_meas : MeasurableSet t)
(κ : kernel α Ω) (μ : Measure α) [IsMarkovKernel κ]
(h_indep : IndepSets S T κ μ) :
IndepSet s t κ μ :=
(indepSet_iff_measure_inter_eq_mul hs_meas ht_meas κ μ).mpr (h_indep s t hs ht)
theorem Indep.indepSet_of_measurableSet {m₁ m₂ m0 : MeasurableSpace Ω} {κ : kernel α Ω}
{μ : Measure α}
(h_indep : Indep m₁ m₂ κ μ) {s t : Set Ω} (hs : MeasurableSet[m₁] s)
(ht : MeasurableSet[m₂] t) :
IndepSet s t κ μ := by
refine fun s' t' hs' ht' => h_indep s' t' ?_ ?_
· refine @generateFrom_induction _ (fun u => MeasurableSet[m₁] u) {s} ?_ ?_ ?_ ?_ _ hs'
· simp only [Set.mem_singleton_iff, forall_eq, hs]
· exact @MeasurableSet.empty _ m₁
· exact fun u hu => hu.compl
· exact fun f hf => MeasurableSet.iUnion hf
· refine @generateFrom_induction _ (fun u => MeasurableSet[m₂] u) {t} ?_ ?_ ?_ ?_ _ ht'
· simp only [Set.mem_singleton_iff, forall_eq, ht]
· exact @MeasurableSet.empty _ m₂
· exact fun u hu => hu.compl
· exact fun f hf => MeasurableSet.iUnion hf
theorem indep_iff_forall_indepSet (m₁ m₂ : MeasurableSpace Ω) {_m0 : MeasurableSpace Ω}
(κ : kernel α Ω) (μ : Measure α) :
Indep m₁ m₂ κ μ ↔ ∀ s t, MeasurableSet[m₁] s → MeasurableSet[m₂] t → IndepSet s t κ μ :=
⟨fun h => fun _s _t hs ht => h.indepSet_of_measurableSet hs ht, fun h s t hs ht =>
h s t hs ht s t (measurableSet_generateFrom (Set.mem_singleton s))
(measurableSet_generateFrom (Set.mem_singleton t))⟩
end IndepSet
section IndepFun
/-! ### Independence of random variables
-/
variable {β β' γ γ' : Type*} {_mα : MeasurableSpace α} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {f : Ω → β} {g : Ω → β'}
theorem indepFun_iff_measure_inter_preimage_eq_mul {mβ : MeasurableSpace β}
{mβ' : MeasurableSpace β'} :
IndepFun f g κ μ ↔
∀ s t, MeasurableSet s → MeasurableSet t
→ ∀ᵐ a ∂μ, κ a (f ⁻¹' s ∩ g ⁻¹' t) = κ a (f ⁻¹' s) * κ a (g ⁻¹' t) := by
constructor <;> intro h
· refine fun s t hs ht => h (f ⁻¹' s) (g ⁻¹' t) ⟨s, hs, rfl⟩ ⟨t, ht, rfl⟩
· rintro _ _ ⟨s, hs, rfl⟩ ⟨t, ht, rfl⟩; exact h s t hs ht
theorem iIndepFun_iff_measure_inter_preimage_eq_mul {ι : Type*} {β : ι → Type*}
(m : ∀ x, MeasurableSpace (β x)) (f : ∀ i, Ω → β i) :
iIndepFun m f κ μ ↔
∀ (S : Finset ι) {sets : ∀ i : ι, Set (β i)} (_H : ∀ i, i ∈ S → MeasurableSet[m i] (sets i)),
∀ᵐ a ∂μ, κ a (⋂ i ∈ S, (f i) ⁻¹' (sets i)) = ∏ i ∈ S, κ a ((f i) ⁻¹' (sets i)) := by
refine ⟨fun h S sets h_meas => h _ fun i hi_mem => ⟨sets i, h_meas i hi_mem, rfl⟩, ?_⟩
intro h S setsΩ h_meas
classical
let setsβ : ∀ i : ι, Set (β i) := fun i =>
dite (i ∈ S) (fun hi_mem => (h_meas i hi_mem).choose) fun _ => Set.univ
have h_measβ : ∀ i ∈ S, MeasurableSet[m i] (setsβ i) := by
intro i hi_mem
simp_rw [setsβ, dif_pos hi_mem]
exact (h_meas i hi_mem).choose_spec.1
have h_preim : ∀ i ∈ S, setsΩ i = f i ⁻¹' setsβ i := by
intro i hi_mem
simp_rw [setsβ, dif_pos hi_mem]
exact (h_meas i hi_mem).choose_spec.2.symm
have h_left_eq : ∀ a, κ a (⋂ i ∈ S, setsΩ i) = κ a (⋂ i ∈ S, (f i) ⁻¹' (setsβ i)) := by
intro a
congr with x
simp_rw [Set.mem_iInter]
constructor <;> intro h i hi_mem <;> specialize h i hi_mem
· rwa [h_preim i hi_mem] at h
· rwa [h_preim i hi_mem]
have h_right_eq : ∀ a, (∏ i ∈ S, κ a (setsΩ i)) = ∏ i ∈ S, κ a ((f i) ⁻¹' (setsβ i)) := by
refine fun a ↦ Finset.prod_congr rfl fun i hi_mem => ?_
rw [h_preim i hi_mem]
filter_upwards [h S h_measβ] with a ha
rw [h_left_eq a, h_right_eq a, ha]
theorem indepFun_iff_indepSet_preimage {mβ : MeasurableSpace β} {mβ' : MeasurableSpace β'}
[IsMarkovKernel κ] (hf : Measurable f) (hg : Measurable g) :
IndepFun f g κ μ ↔
∀ s t, MeasurableSet s → MeasurableSet t → IndepSet (f ⁻¹' s) (g ⁻¹' t) κ μ := by
refine indepFun_iff_measure_inter_preimage_eq_mul.trans ?_
constructor <;> intro h s t hs ht <;> specialize h s t hs ht
· rwa [indepSet_iff_measure_inter_eq_mul (hf hs) (hg ht) κ μ]
· rwa [← indepSet_iff_measure_inter_eq_mul (hf hs) (hg ht) κ μ]
@[symm]
nonrec theorem IndepFun.symm {_ : MeasurableSpace β} {_ : MeasurableSpace β'}
(hfg : IndepFun f g κ μ) : IndepFun g f κ μ := hfg.symm
theorem IndepFun.ae_eq {mβ : MeasurableSpace β} {mβ' : MeasurableSpace β'}
{f' : Ω → β} {g' : Ω → β'} (hfg : IndepFun f g κ μ)
(hf : ∀ᵐ a ∂μ, f =ᵐ[κ a] f') (hg : ∀ᵐ a ∂μ, g =ᵐ[κ a] g') :
IndepFun f' g' κ μ := by
rintro _ _ ⟨A, hA, rfl⟩ ⟨B, hB, rfl⟩
filter_upwards [hf, hg, hfg _ _ ⟨_, hA, rfl⟩ ⟨_, hB, rfl⟩] with a hf' hg' hfg'
have h1 : f ⁻¹' A =ᵐ[κ a] f' ⁻¹' A := hf'.fun_comp A
have h2 : g ⁻¹' B =ᵐ[κ a] g' ⁻¹' B := hg'.fun_comp B
rwa [← measure_congr h1, ← measure_congr h2, ← measure_congr (h1.inter h2)]
| Mathlib/Probability/Independence/Kernel.lean | 803 | 810 | theorem IndepFun.comp {mβ : MeasurableSpace β} {mβ' : MeasurableSpace β'}
{mγ : MeasurableSpace γ} {mγ' : MeasurableSpace γ'} {φ : β → γ} {ψ : β' → γ'}
(hfg : IndepFun f g κ μ) (hφ : Measurable φ) (hψ : Measurable ψ) :
IndepFun (φ ∘ f) (ψ ∘ g) κ μ := by |
rintro _ _ ⟨A, hA, rfl⟩ ⟨B, hB, rfl⟩
apply hfg
· exact ⟨φ ⁻¹' A, hφ hA, Set.preimage_comp.symm⟩
· exact ⟨ψ ⁻¹' B, hψ hB, Set.preimage_comp.symm⟩
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Init.Control.Combinators
import Mathlib.Data.Option.Defs
import Mathlib.Logic.IsEmpty
import Mathlib.Logic.Relator
import Mathlib.Util.CompileInductive
import Aesop
#align_import data.option.basic from "leanprover-community/mathlib"@"f340f229b1f461aa1c8ee11e0a172d0a3b301a4a"
/-!
# Option of a type
This file develops the basic theory of option types.
If `α` is a type, then `Option α` can be understood as the type with one more element than `α`.
`Option α` has terms `some a`, where `a : α`, and `none`, which is the added element.
This is useful in multiple ways:
* It is the prototype of addition of terms to a type. See for example `WithBot α` which uses
`none` as an element smaller than all others.
* It can be used to define failsafe partial functions, which return `some the_result_we_expect`
if we can find `the_result_we_expect`, and `none` if there is no meaningful result. This forces
any subsequent use of the partial function to explicitly deal with the exceptions that make it
return `none`.
* `Option` is a monad. We love monads.
`Part` is an alternative to `Option` that can be seen as the type of `True`/`False` values
along with a term `a : α` if the value is `True`.
-/
universe u
namespace Option
variable {α β γ δ : Type*}
theorem coe_def : (fun a ↦ ↑a : α → Option α) = some :=
rfl
#align option.coe_def Option.coe_def
theorem mem_map {f : α → β} {y : β} {o : Option α} : y ∈ o.map f ↔ ∃ x ∈ o, f x = y := by simp
#align option.mem_map Option.mem_map
-- The simpNF linter says that the LHS can be simplified via `Option.mem_def`.
-- However this is a higher priority lemma.
-- https://github.com/leanprover/std4/issues/207
@[simp 1100, nolint simpNF]
theorem mem_map_of_injective {f : α → β} (H : Function.Injective f) {a : α} {o : Option α} :
f a ∈ o.map f ↔ a ∈ o := by
aesop
theorem forall_mem_map {f : α → β} {o : Option α} {p : β → Prop} :
(∀ y ∈ o.map f, p y) ↔ ∀ x ∈ o, p (f x) := by simp
#align option.forall_mem_map Option.forall_mem_map
theorem exists_mem_map {f : α → β} {o : Option α} {p : β → Prop} :
(∃ y ∈ o.map f, p y) ↔ ∃ x ∈ o, p (f x) := by simp
#align option.exists_mem_map Option.exists_mem_map
theorem coe_get {o : Option α} (h : o.isSome) : ((Option.get _ h : α) : Option α) = o :=
Option.some_get h
#align option.coe_get Option.coe_get
theorem eq_of_mem_of_mem {a : α} {o1 o2 : Option α} (h1 : a ∈ o1) (h2 : a ∈ o2) : o1 = o2 :=
h1.trans h2.symm
#align option.eq_of_mem_of_mem Option.eq_of_mem_of_mem
theorem Mem.leftUnique : Relator.LeftUnique ((· ∈ ·) : α → Option α → Prop) :=
fun _ _ _=> mem_unique
#align option.mem.left_unique Option.Mem.leftUnique
theorem some_injective (α : Type*) : Function.Injective (@some α) := fun _ _ ↦ some_inj.mp
#align option.some_injective Option.some_injective
/-- `Option.map f` is injective if `f` is injective. -/
theorem map_injective {f : α → β} (Hf : Function.Injective f) : Function.Injective (Option.map f)
| none, none, _ => rfl
| some a₁, some a₂, H => by rw [Hf (Option.some.inj H)]
#align option.map_injective Option.map_injective
@[simp]
theorem map_comp_some (f : α → β) : Option.map f ∘ some = some ∘ f :=
rfl
#align option.map_comp_some Option.map_comp_some
@[simp]
theorem none_bind' (f : α → Option β) : none.bind f = none :=
rfl
#align option.none_bind' Option.none_bind'
@[simp]
theorem some_bind' (a : α) (f : α → Option β) : (some a).bind f = f a :=
rfl
#align option.some_bind' Option.some_bind'
theorem bind_eq_some' {x : Option α} {f : α → Option β} {b : β} :
x.bind f = some b ↔ ∃ a, x = some a ∧ f a = some b := by
cases x <;> simp
#align option.bind_eq_some' Option.bind_eq_some'
#align option.bind_eq_none' Option.bind_eq_none'
theorem bind_congr {f g : α → Option β} {x : Option α}
(h : ∀ a ∈ x, f a = g a) : x.bind f = x.bind g := by
cases x <;> simp only [some_bind, none_bind, mem_def, h]
@[congr]
theorem bind_congr' {f g : α → Option β} {x y : Option α} (hx : x = y)
(hf : ∀ a ∈ y, f a = g a) : x.bind f = y.bind g :=
hx.symm ▸ bind_congr hf
theorem joinM_eq_join : joinM = @join α :=
funext fun _ ↦ rfl
#align option.join_eq_join Option.joinM_eq_join
theorem bind_eq_bind' {α β : Type u} {f : α → Option β} {x : Option α} : x >>= f = x.bind f :=
rfl
#align option.bind_eq_bind Option.bind_eq_bind'
theorem map_coe {α β} {a : α} {f : α → β} : f <$> (a : Option α) = ↑(f a) :=
rfl
#align option.map_coe Option.map_coe
@[simp]
theorem map_coe' {a : α} {f : α → β} : Option.map f (a : Option α) = ↑(f a) :=
rfl
#align option.map_coe' Option.map_coe'
/-- `Option.map` as a function between functions is injective. -/
theorem map_injective' : Function.Injective (@Option.map α β) := fun f g h ↦
funext fun x ↦ some_injective _ <| by simp only [← map_some', h]
#align option.map_injective' Option.map_injective'
@[simp]
theorem map_inj {f g : α → β} : Option.map f = Option.map g ↔ f = g :=
map_injective'.eq_iff
#align option.map_inj Option.map_inj
attribute [simp] map_id
@[simp]
theorem map_eq_id {f : α → α} : Option.map f = id ↔ f = id :=
map_injective'.eq_iff' map_id
#align option.map_eq_id Option.map_eq_id
theorem map_comm {f₁ : α → β} {f₂ : α → γ} {g₁ : β → δ} {g₂ : γ → δ} (h : g₁ ∘ f₁ = g₂ ∘ f₂)
(a : α) :
(Option.map f₁ a).map g₁ = (Option.map f₂ a).map g₂ := by rw [map_map, h, ← map_map]
#align option.map_comm Option.map_comm
section pmap
variable {p : α → Prop} (f : ∀ a : α, p a → β) (x : Option α)
-- Porting note: Can't simp tag this anymore because `pbind` simplifies
-- @[simp]
theorem pbind_eq_bind (f : α → Option β) (x : Option α) : (x.pbind fun a _ ↦ f a) = x.bind f := by
cases x <;> simp only [pbind, none_bind', some_bind']
#align option.pbind_eq_bind Option.pbind_eq_bind
theorem map_bind {α β γ} (f : β → γ) (x : Option α) (g : α → Option β) :
Option.map f (x >>= g) = x >>= fun a ↦ Option.map f (g a) := by
simp only [← map_eq_map, ← bind_pure_comp, LawfulMonad.bind_assoc]
#align option.map_bind Option.map_bind
theorem map_bind' (f : β → γ) (x : Option α) (g : α → Option β) :
Option.map f (x.bind g) = x.bind fun a ↦ Option.map f (g a) := by cases x <;> simp
#align option.map_bind' Option.map_bind'
theorem map_pbind (f : β → γ) (x : Option α) (g : ∀ a, a ∈ x → Option β) :
Option.map f (x.pbind g) = x.pbind fun a H ↦ Option.map f (g a H) := by
cases x <;> simp only [pbind, map_none']
#align option.map_pbind Option.map_pbind
theorem pbind_map (f : α → β) (x : Option α) (g : ∀ b : β, b ∈ x.map f → Option γ) :
pbind (Option.map f x) g = x.pbind fun a h ↦ g (f a) (mem_map_of_mem _ h) := by cases x <;> rfl
#align option.pbind_map Option.pbind_map
@[simp]
theorem pmap_none (f : ∀ a : α, p a → β) {H} : pmap f (@none α) H = none :=
rfl
#align option.pmap_none Option.pmap_none
@[simp]
theorem pmap_some (f : ∀ a : α, p a → β) {x : α} (h : p x) :
pmap f (some x) = fun _ ↦ some (f x h) :=
rfl
#align option.pmap_some Option.pmap_some
theorem mem_pmem {a : α} (h : ∀ a ∈ x, p a) (ha : a ∈ x) : f a (h a ha) ∈ pmap f x h := by
rw [mem_def] at ha ⊢
subst ha
rfl
#align option.mem_pmem Option.mem_pmem
theorem pmap_map (g : γ → α) (x : Option γ) (H) :
pmap f (x.map g) H = pmap (fun a h ↦ f (g a) h) x fun a h ↦ H _ (mem_map_of_mem _ h) := by
cases x <;> simp only [map_none', map_some', pmap]
#align option.pmap_map Option.pmap_map
theorem map_pmap (g : β → γ) (f : ∀ a, p a → β) (x H) :
Option.map g (pmap f x H) = pmap (fun a h ↦ g (f a h)) x H := by
cases x <;> simp only [map_none', map_some', pmap]
#align option.map_pmap Option.map_pmap
-- Porting note: Can't simp tag this anymore because `pmap` simplifies
-- @[simp]
theorem pmap_eq_map (p : α → Prop) (f : α → β) (x H) :
@pmap _ _ p (fun a _ ↦ f a) x H = Option.map f x := by
cases x <;> simp only [map_none', map_some', pmap]
#align option.pmap_eq_map Option.pmap_eq_map
theorem pmap_bind {α β γ} {x : Option α} {g : α → Option β} {p : β → Prop} {f : ∀ b, p b → γ} (H)
(H' : ∀ (a : α), ∀ b ∈ g a, b ∈ x >>= g) :
pmap f (x >>= g) H = x >>= fun a ↦ pmap f (g a) fun b h ↦ H _ (H' a _ h) := by
cases x <;> simp only [pmap, bind_eq_bind, none_bind, some_bind]
#align option.pmap_bind Option.pmap_bind
theorem bind_pmap {α β γ} {p : α → Prop} (f : ∀ a, p a → β) (x : Option α) (g : β → Option γ) (H) :
pmap f x H >>= g = x.pbind fun a h ↦ g (f a (H _ h)) := by
cases x <;> simp only [pmap, bind_eq_bind, none_bind, some_bind, pbind]
#align option.bind_pmap Option.bind_pmap
variable {f x}
theorem pbind_eq_none {f : ∀ a : α, a ∈ x → Option β}
(h' : ∀ a (H : a ∈ x), f a H = none → x = none) : x.pbind f = none ↔ x = none := by
cases x
· simp
· simp only [pbind, iff_false]
intro h
cases h' _ rfl h
#align option.pbind_eq_none Option.pbind_eq_none
theorem pbind_eq_some {f : ∀ a : α, a ∈ x → Option β} {y : β} :
x.pbind f = some y ↔ ∃ (z : α) (H : z ∈ x), f z H = some y := by
rcases x with (_|x)
· simp only [pbind, false_iff, not_exists]
intro z h
simp at h
· simp only [pbind]
refine ⟨fun h ↦ ⟨x, rfl, h⟩, ?_⟩
rintro ⟨z, H, hz⟩
simp only [mem_def, Option.some_inj] at H
simpa [H] using hz
#align option.pbind_eq_some Option.pbind_eq_some
-- Porting note: Can't simp tag this anymore because `pmap` simplifies
-- @[simp]
theorem pmap_eq_none_iff {h} : pmap f x h = none ↔ x = none := by cases x <;> simp
#align option.pmap_eq_none_iff Option.pmap_eq_none_iff
-- Porting note: Can't simp tag this anymore because `pmap` simplifies
-- @[simp]
theorem pmap_eq_some_iff {hf} {y : β} :
pmap f x hf = some y ↔ ∃ (a : α) (H : x = some a), f a (hf a H) = y := by
rcases x with (_|x)
· simp only [not_mem_none, exists_false, pmap, not_false_iff, exists_prop_of_false]
· constructor
· intro h
simp only [pmap, Option.some_inj] at h
exact ⟨x, rfl, h⟩
· rintro ⟨a, H, rfl⟩
simp only [mem_def, Option.some_inj] at H
simp only [H, pmap]
#align option.pmap_eq_some_iff Option.pmap_eq_some_iff
-- Porting note: Can't simp tag this anymore because `join` and `pmap` simplify
-- @[simp]
theorem join_pmap_eq_pmap_join {f : ∀ a, p a → β} {x : Option (Option α)} (H) :
(pmap (pmap f) x H).join = pmap f x.join fun a h ↦ H (some a) (mem_of_mem_join h) _ rfl := by
rcases x with (_ | _ | x) <;> simp
#align option.join_pmap_eq_pmap_join Option.join_pmap_eq_pmap_join
end pmap
@[simp]
theorem seq_some {α β} {a : α} {f : α → β} : some f <*> some a = some (f a) :=
rfl
#align option.seq_some Option.seq_some
@[simp]
theorem some_orElse' (a : α) (x : Option α) : (some a).orElse (fun _ ↦ x) = some a :=
rfl
#align option.some_orelse' Option.some_orElse'
#align option.some_orelse Option.some_orElse
@[simp]
theorem none_orElse' (x : Option α) : none.orElse (fun _ ↦ x) = x := by cases x <;> rfl
#align option.none_orelse' Option.none_orElse'
#align option.none_orelse Option.none_orElse
@[simp]
theorem orElse_none' (x : Option α) : x.orElse (fun _ ↦ none) = x := by cases x <;> rfl
#align option.orelse_none' Option.orElse_none'
#align option.orelse_none Option.orElse_none
#align option.is_some_none Option.isSome_none
#align option.is_some_some Option.isSome_some
#align option.is_some_iff_exists Option.isSome_iff_exists
#align option.is_none_none Option.isNone_none
#align option.is_none_some Option.isNone_some
#align option.not_is_some Option.not_isSome
#align option.not_is_some_iff_eq_none Option.not_isSome_iff_eq_none
#align option.ne_none_iff_is_some Option.ne_none_iff_isSome
theorem exists_ne_none {p : Option α → Prop} : (∃ x ≠ none, p x) ↔ (∃ x : α, p x) := by
simp only [← exists_prop, bex_ne_none]
@[simp]
| Mathlib/Data/Option/Basic.lean | 326 | 327 | theorem isSome_map (f : α → β) (o : Option α) : isSome (o.map f) = isSome o := by |
cases o <;> rfl
|
/-
Copyright (c) 2021 Christopher Hoskin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Christopher Hoskin
-/
import Mathlib.Algebra.Order.Group.PosPart
import Mathlib.Analysis.Normed.Group.Basic
import Mathlib.Topology.Order.Lattice
#align_import analysis.normed.order.lattice from "leanprover-community/mathlib"@"5dc275ec639221ca4d5f56938eb966f6ad9bc89f"
/-!
# Normed lattice ordered groups
Motivated by the theory of Banach Lattices, we then define `NormedLatticeAddCommGroup` as a
lattice with a covariant normed group addition satisfying the solid axiom.
## Main statements
We show that a normed lattice ordered group is a topological lattice with respect to the norm
topology.
## References
* [Meyer-Nieberg, Banach lattices][MeyerNieberg1991]
## Tags
normed, lattice, ordered, group
-/
/-!
### Normed lattice ordered groups
Motivated by the theory of Banach Lattices, this section introduces normed lattice ordered groups.
-/
-- Porting note: this now exists as a global notation
-- local notation "|" a "|" => abs a
section SolidNorm
/-- Let `α` be an `AddCommGroup` with a `Lattice` structure. A norm on `α` is *solid* if, for `a`
and `b` in `α`, with absolute values `|a|` and `|b|` respectively, `|a| ≤ |b|` implies `‖a‖ ≤ ‖b‖`.
-/
class HasSolidNorm (α : Type*) [NormedAddCommGroup α] [Lattice α] : Prop where
solid : ∀ ⦃x y : α⦄, |x| ≤ |y| → ‖x‖ ≤ ‖y‖
#align has_solid_norm HasSolidNorm
variable {α : Type*} [NormedAddCommGroup α] [Lattice α] [HasSolidNorm α]
theorem norm_le_norm_of_abs_le_abs {a b : α} (h : |a| ≤ |b|) : ‖a‖ ≤ ‖b‖ :=
HasSolidNorm.solid h
#align norm_le_norm_of_abs_le_abs norm_le_norm_of_abs_le_abs
/-- If `α` has a solid norm, then the balls centered at the origin of `α` are solid sets. -/
theorem LatticeOrderedAddCommGroup.isSolid_ball (r : ℝ) :
LatticeOrderedAddCommGroup.IsSolid (Metric.ball (0 : α) r) := fun _ hx _ hxy =>
mem_ball_zero_iff.mpr ((HasSolidNorm.solid hxy).trans_lt (mem_ball_zero_iff.mp hx))
#align lattice_ordered_add_comm_group.is_solid_ball LatticeOrderedAddCommGroup.isSolid_ball
instance : HasSolidNorm ℝ := ⟨fun _ _ => id⟩
instance : HasSolidNorm ℚ := ⟨fun _ _ _ => by simpa only [norm, ← Rat.cast_abs, Rat.cast_le]⟩
end SolidNorm
/--
Let `α` be a normed commutative group equipped with a partial order covariant with addition, with
respect which `α` forms a lattice. Suppose that `α` is *solid*, that is to say, for `a` and `b` in
`α`, with absolute values `|a|` and `|b|` respectively, `|a| ≤ |b|` implies `‖a‖ ≤ ‖b‖`. Then `α` is
said to be a normed lattice ordered group.
-/
class NormedLatticeAddCommGroup (α : Type*) extends
NormedAddCommGroup α, Lattice α, HasSolidNorm α where
add_le_add_left : ∀ a b : α, a ≤ b → ∀ c : α, c + a ≤ c + b
#align normed_lattice_add_comm_group NormedLatticeAddCommGroup
instance Real.normedLatticeAddCommGroup : NormedLatticeAddCommGroup ℝ where
add_le_add_left _ _ h _ := add_le_add le_rfl h
-- see Note [lower instance priority]
/-- A normed lattice ordered group is an ordered additive commutative group
-/
instance (priority := 100) NormedLatticeAddCommGroup.toOrderedAddCommGroup {α : Type*}
[h : NormedLatticeAddCommGroup α] : OrderedAddCommGroup α :=
{ h with }
#align normed_lattice_add_comm_group_to_ordered_add_comm_group NormedLatticeAddCommGroup.toOrderedAddCommGroup
variable {α : Type*} [NormedLatticeAddCommGroup α]
open HasSolidNorm
theorem dual_solid (a b : α) (h : b ⊓ -b ≤ a ⊓ -a) : ‖a‖ ≤ ‖b‖ := by
apply solid
rw [abs]
nth_rw 1 [← neg_neg a]
rw [← neg_inf]
rw [abs]
nth_rw 1 [← neg_neg b]
rwa [← neg_inf, neg_le_neg_iff, inf_comm _ b, inf_comm _ a]
#align dual_solid dual_solid
-- see Note [lower instance priority]
/-- Let `α` be a normed lattice ordered group, then the order dual is also a
normed lattice ordered group.
-/
instance (priority := 100) OrderDual.instNormedLatticeAddCommGroup :
NormedLatticeAddCommGroup αᵒᵈ :=
{ OrderDual.orderedAddCommGroup, OrderDual.normedAddCommGroup, OrderDual.instLattice α with
solid := dual_solid (α := α) }
theorem norm_abs_eq_norm (a : α) : ‖|a|‖ = ‖a‖ :=
(solid (abs_abs a).le).antisymm (solid (abs_abs a).symm.le)
#align norm_abs_eq_norm norm_abs_eq_norm
theorem norm_inf_sub_inf_le_add_norm (a b c d : α) : ‖a ⊓ b - c ⊓ d‖ ≤ ‖a - c‖ + ‖b - d‖ := by
rw [← norm_abs_eq_norm (a - c), ← norm_abs_eq_norm (b - d)]
refine le_trans (solid ?_) (norm_add_le |a - c| |b - d|)
rw [abs_of_nonneg (add_nonneg (abs_nonneg (a - c)) (abs_nonneg (b - d)))]
calc
|a ⊓ b - c ⊓ d| = |a ⊓ b - c ⊓ b + (c ⊓ b - c ⊓ d)| := by rw [sub_add_sub_cancel]
_ ≤ |a ⊓ b - c ⊓ b| + |c ⊓ b - c ⊓ d| := abs_add_le _ _
_ ≤ |a - c| + |b - d| := by
apply add_le_add
· exact abs_inf_sub_inf_le_abs _ _ _
· rw [inf_comm c, inf_comm c]
exact abs_inf_sub_inf_le_abs _ _ _
#align norm_inf_sub_inf_le_add_norm norm_inf_sub_inf_le_add_norm
| Mathlib/Analysis/Normed/Order/Lattice.lean | 133 | 144 | theorem norm_sup_sub_sup_le_add_norm (a b c d : α) : ‖a ⊔ b - c ⊔ d‖ ≤ ‖a - c‖ + ‖b - d‖ := by |
rw [← norm_abs_eq_norm (a - c), ← norm_abs_eq_norm (b - d)]
refine le_trans (solid ?_) (norm_add_le |a - c| |b - d|)
rw [abs_of_nonneg (add_nonneg (abs_nonneg (a - c)) (abs_nonneg (b - d)))]
calc
|a ⊔ b - c ⊔ d| = |a ⊔ b - c ⊔ b + (c ⊔ b - c ⊔ d)| := by rw [sub_add_sub_cancel]
_ ≤ |a ⊔ b - c ⊔ b| + |c ⊔ b - c ⊔ d| := abs_add_le _ _
_ ≤ |a - c| + |b - d| := by
apply add_le_add
· exact abs_sup_sub_sup_le_abs _ _ _
· rw [sup_comm c, sup_comm c]
exact abs_sup_sub_sup_le_abs _ _ _
|
/-
Copyright (c) 2019 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison
-/
import Mathlib.SetTheory.Game.State
#align_import set_theory.game.domineering from "leanprover-community/mathlib"@"b134b2f5cf6dd25d4bbfd3c498b6e36c11a17225"
/-!
# Domineering as a combinatorial game.
We define the game of Domineering, played on a chessboard of arbitrary shape
(possibly even disconnected).
Left moves by placing a domino vertically, while Right moves by placing a domino horizontally.
This is only a fragment of a full development;
in order to successfully analyse positions we would need some more theorems.
Most importantly, we need a general statement that allows us to discard irrelevant moves.
Specifically to domineering, we need the fact that
disjoint parts of the chessboard give sums of games.
-/
namespace SetTheory
namespace PGame
namespace Domineering
open Function
/-- The equivalence `(x, y) ↦ (x, y+1)`. -/
@[simps!]
def shiftUp : ℤ × ℤ ≃ ℤ × ℤ :=
(Equiv.refl ℤ).prodCongr (Equiv.addRight (1 : ℤ))
#align pgame.domineering.shift_up SetTheory.PGame.Domineering.shiftUp
/-- The equivalence `(x, y) ↦ (x+1, y)`. -/
@[simps!]
def shiftRight : ℤ × ℤ ≃ ℤ × ℤ :=
(Equiv.addRight (1 : ℤ)).prodCongr (Equiv.refl ℤ)
#align pgame.domineering.shift_right SetTheory.PGame.Domineering.shiftRight
/-- A Domineering board is an arbitrary finite subset of `ℤ × ℤ`. -/
-- Porting note: reducibility cannot be `local`. For now there are no dependents of this file so
-- being globally reducible is fine.
abbrev Board :=
Finset (ℤ × ℤ)
#align pgame.domineering.board SetTheory.PGame.Domineering.Board
/-- Left can play anywhere that a square and the square below it are open. -/
def left (b : Board) : Finset (ℤ × ℤ) :=
b ∩ b.map shiftUp
#align pgame.domineering.left SetTheory.PGame.Domineering.left
/-- Right can play anywhere that a square and the square to the left are open. -/
def right (b : Board) : Finset (ℤ × ℤ) :=
b ∩ b.map shiftRight
#align pgame.domineering.right SetTheory.PGame.Domineering.right
theorem mem_left {b : Board} (x : ℤ × ℤ) : x ∈ left b ↔ x ∈ b ∧ (x.1, x.2 - 1) ∈ b :=
Finset.mem_inter.trans (and_congr Iff.rfl Finset.mem_map_equiv)
#align pgame.domineering.mem_left SetTheory.PGame.Domineering.mem_left
theorem mem_right {b : Board} (x : ℤ × ℤ) : x ∈ right b ↔ x ∈ b ∧ (x.1 - 1, x.2) ∈ b :=
Finset.mem_inter.trans (and_congr Iff.rfl Finset.mem_map_equiv)
#align pgame.domineering.mem_right SetTheory.PGame.Domineering.mem_right
/-- After Left moves, two vertically adjacent squares are removed from the board. -/
def moveLeft (b : Board) (m : ℤ × ℤ) : Board :=
(b.erase m).erase (m.1, m.2 - 1)
#align pgame.domineering.move_left SetTheory.PGame.Domineering.moveLeft
/-- After Left moves, two horizontally adjacent squares are removed from the board. -/
def moveRight (b : Board) (m : ℤ × ℤ) : Board :=
(b.erase m).erase (m.1 - 1, m.2)
#align pgame.domineering.move_right SetTheory.PGame.Domineering.moveRight
theorem fst_pred_mem_erase_of_mem_right {b : Board} {m : ℤ × ℤ} (h : m ∈ right b) :
(m.1 - 1, m.2) ∈ b.erase m := by
rw [mem_right] at h
apply Finset.mem_erase_of_ne_of_mem _ h.2
exact ne_of_apply_ne Prod.fst (pred_ne_self m.1)
#align pgame.domineering.fst_pred_mem_erase_of_mem_right SetTheory.PGame.Domineering.fst_pred_mem_erase_of_mem_right
theorem snd_pred_mem_erase_of_mem_left {b : Board} {m : ℤ × ℤ} (h : m ∈ left b) :
(m.1, m.2 - 1) ∈ b.erase m := by
rw [mem_left] at h
apply Finset.mem_erase_of_ne_of_mem _ h.2
exact ne_of_apply_ne Prod.snd (pred_ne_self m.2)
#align pgame.domineering.snd_pred_mem_erase_of_mem_left SetTheory.PGame.Domineering.snd_pred_mem_erase_of_mem_left
theorem card_of_mem_left {b : Board} {m : ℤ × ℤ} (h : m ∈ left b) : 2 ≤ Finset.card b := by
have w₁ : m ∈ b := (Finset.mem_inter.1 h).1
have w₂ : (m.1, m.2 - 1) ∈ b.erase m := snd_pred_mem_erase_of_mem_left h
have i₁ := Finset.card_erase_lt_of_mem w₁
have i₂ := Nat.lt_of_le_of_lt (Nat.zero_le _) (Finset.card_erase_lt_of_mem w₂)
exact Nat.lt_of_le_of_lt i₂ i₁
#align pgame.domineering.card_of_mem_left SetTheory.PGame.Domineering.card_of_mem_left
theorem card_of_mem_right {b : Board} {m : ℤ × ℤ} (h : m ∈ right b) : 2 ≤ Finset.card b := by
have w₁ : m ∈ b := (Finset.mem_inter.1 h).1
have w₂ := fst_pred_mem_erase_of_mem_right h
have i₁ := Finset.card_erase_lt_of_mem w₁
have i₂ := Nat.lt_of_le_of_lt (Nat.zero_le _) (Finset.card_erase_lt_of_mem w₂)
exact Nat.lt_of_le_of_lt i₂ i₁
#align pgame.domineering.card_of_mem_right SetTheory.PGame.Domineering.card_of_mem_right
theorem moveLeft_card {b : Board} {m : ℤ × ℤ} (h : m ∈ left b) :
Finset.card (moveLeft b m) + 2 = Finset.card b := by
dsimp [moveLeft]
rw [Finset.card_erase_of_mem (snd_pred_mem_erase_of_mem_left h)]
rw [Finset.card_erase_of_mem (Finset.mem_of_mem_inter_left h)]
exact tsub_add_cancel_of_le (card_of_mem_left h)
#align pgame.domineering.move_left_card SetTheory.PGame.Domineering.moveLeft_card
theorem moveRight_card {b : Board} {m : ℤ × ℤ} (h : m ∈ right b) :
Finset.card (moveRight b m) + 2 = Finset.card b := by
dsimp [moveRight]
rw [Finset.card_erase_of_mem (fst_pred_mem_erase_of_mem_right h)]
rw [Finset.card_erase_of_mem (Finset.mem_of_mem_inter_left h)]
exact tsub_add_cancel_of_le (card_of_mem_right h)
#align pgame.domineering.move_right_card SetTheory.PGame.Domineering.moveRight_card
theorem moveLeft_smaller {b : Board} {m : ℤ × ℤ} (h : m ∈ left b) :
Finset.card (moveLeft b m) / 2 < Finset.card b / 2 := by simp [← moveLeft_card h, lt_add_one]
#align pgame.domineering.move_left_smaller SetTheory.PGame.Domineering.moveLeft_smaller
| Mathlib/SetTheory/Game/Domineering.lean | 129 | 130 | theorem moveRight_smaller {b : Board} {m : ℤ × ℤ} (h : m ∈ right b) :
Finset.card (moveRight b m) / 2 < Finset.card b / 2 := by | simp [← moveRight_card h, lt_add_one]
|
/-
Copyright (c) 2020 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov, Sébastien Gouëzel
-/
import Mathlib.Analysis.Calculus.Deriv.ZPow
import Mathlib.Analysis.SpecialFunctions.Sqrt
import Mathlib.Analysis.SpecialFunctions.Log.Deriv
import Mathlib.Analysis.SpecialFunctions.Trigonometric.Deriv
import Mathlib.Analysis.Convex.Deriv
#align_import analysis.convex.specific_functions.deriv from "leanprover-community/mathlib"@"a16665637b378379689c566204817ae792ac8b39"
/-!
# Collection of convex functions
In this file we prove that certain specific functions are strictly convex, including the following:
* `Even.strictConvexOn_pow` : For an even `n : ℕ` with `2 ≤ n`, `fun x => x ^ n` is strictly convex.
* `strictConvexOn_pow` : For `n : ℕ`, with `2 ≤ n`, `fun x => x ^ n` is strictly convex on $[0,+∞)$.
* `strictConvexOn_zpow` : For `m : ℤ` with `m ≠ 0, 1`, `fun x => x ^ m` is strictly convex on
$[0, +∞)$.
* `strictConcaveOn_sin_Icc` : `sin` is strictly concave on $[0, π]$
* `strictConcaveOn_cos_Icc` : `cos` is strictly concave on $[-π/2, π/2]$
## TODO
These convexity lemmas are proved by checking the sign of the second derivative. If desired, most
of these could also be switched to elementary proofs, like in
`Analysis.Convex.SpecificFunctions.Basic`.
-/
open Real Set
open scoped NNReal
/-- `x^n`, `n : ℕ` is strictly convex on `[0, +∞)` for all `n` greater than `2`. -/
| Mathlib/Analysis/Convex/SpecificFunctions/Deriv.lean | 40 | 44 | theorem strictConvexOn_pow {n : ℕ} (hn : 2 ≤ n) : StrictConvexOn ℝ (Ici 0) fun x : ℝ => x ^ n := by |
apply StrictMonoOn.strictConvexOn_of_deriv (convex_Ici _) (continuousOn_pow _)
rw [deriv_pow', interior_Ici]
exact fun x (hx : 0 < x) y _ hxy => mul_lt_mul_of_pos_left
(pow_lt_pow_left hxy hx.le <| Nat.sub_ne_zero_of_lt hn) (by positivity)
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Benjamin Davidson
-/
import Mathlib.Analysis.SpecialFunctions.Complex.Arg
import Mathlib.Analysis.SpecialFunctions.Log.Basic
#align_import analysis.special_functions.complex.log from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# The complex `log` function
Basic properties, relationship with `exp`.
-/
noncomputable section
namespace Complex
open Set Filter Bornology
open scoped Real Topology ComplexConjugate
/-- Inverse of the `exp` function. Returns values such that `(log x).im > - π` and `(log x).im ≤ π`.
`log 0 = 0`-/
-- Porting note: @[pp_nodot] does not exist in mathlib4
noncomputable def log (x : ℂ) : ℂ :=
x.abs.log + arg x * I
#align complex.log Complex.log
theorem log_re (x : ℂ) : x.log.re = x.abs.log := by simp [log]
#align complex.log_re Complex.log_re
theorem log_im (x : ℂ) : x.log.im = x.arg := by simp [log]
#align complex.log_im Complex.log_im
theorem neg_pi_lt_log_im (x : ℂ) : -π < (log x).im := by simp only [log_im, neg_pi_lt_arg]
#align complex.neg_pi_lt_log_im Complex.neg_pi_lt_log_im
theorem log_im_le_pi (x : ℂ) : (log x).im ≤ π := by simp only [log_im, arg_le_pi]
#align complex.log_im_le_pi Complex.log_im_le_pi
theorem exp_log {x : ℂ} (hx : x ≠ 0) : exp (log x) = x := by
rw [log, exp_add_mul_I, ← ofReal_sin, sin_arg, ← ofReal_cos, cos_arg hx, ← ofReal_exp,
Real.exp_log (abs.pos hx), mul_add, ofReal_div, ofReal_div,
mul_div_cancel₀ _ (ofReal_ne_zero.2 <| abs.ne_zero hx), ← mul_assoc,
mul_div_cancel₀ _ (ofReal_ne_zero.2 <| abs.ne_zero hx), re_add_im]
#align complex.exp_log Complex.exp_log
@[simp]
theorem range_exp : Set.range exp = {0}ᶜ :=
Set.ext fun x =>
⟨by
rintro ⟨x, rfl⟩
exact exp_ne_zero x, fun hx => ⟨log x, exp_log hx⟩⟩
#align complex.range_exp Complex.range_exp
theorem log_exp {x : ℂ} (hx₁ : -π < x.im) (hx₂ : x.im ≤ π) : log (exp x) = x := by
rw [log, abs_exp, Real.log_exp, exp_eq_exp_re_mul_sin_add_cos, ← ofReal_exp,
arg_mul_cos_add_sin_mul_I (Real.exp_pos _) ⟨hx₁, hx₂⟩, re_add_im]
#align complex.log_exp Complex.log_exp
| Mathlib/Analysis/SpecialFunctions/Complex/Log.lean | 65 | 67 | theorem exp_inj_of_neg_pi_lt_of_le_pi {x y : ℂ} (hx₁ : -π < x.im) (hx₂ : x.im ≤ π) (hy₁ : -π < y.im)
(hy₂ : y.im ≤ π) (hxy : exp x = exp y) : x = y := by |
rw [← log_exp hx₁ hx₂, ← log_exp hy₁ hy₂, hxy]
|
/-
Copyright (c) 2021 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Data.Matrix.Basis
import Mathlib.Data.Matrix.DMatrix
import Mathlib.LinearAlgebra.Matrix.Determinant.Basic
import Mathlib.LinearAlgebra.Matrix.Reindex
import Mathlib.Tactic.FieldSimp
#align_import linear_algebra.matrix.transvection from "leanprover-community/mathlib"@"0e2aab2b0d521f060f62a14d2cf2e2c54e8491d6"
/-!
# Transvections
Transvections are matrices of the form `1 + StdBasisMatrix i j c`, where `StdBasisMatrix i j c`
is the basic matrix with a `c` at position `(i, j)`. Multiplying by such a transvection on the left
(resp. on the right) amounts to adding `c` times the `j`-th row to the `i`-th row
(resp `c` times the `i`-th column to the `j`-th column). Therefore, they are useful to present
algorithms operating on rows and columns.
Transvections are a special case of *elementary matrices* (according to most references, these also
contain the matrices exchanging rows, and the matrices multiplying a row by a constant).
We show that, over a field, any matrix can be written as `L * D * L'`, where `L` and `L'` are
products of transvections and `D` is diagonal. In other words, one can reduce a matrix to diagonal
form by operations on its rows and columns, a variant of Gauss' pivot algorithm.
## Main definitions and results
* `Transvection i j c` is the matrix equal to `1 + StdBasisMatrix i j c`.
* `TransvectionStruct n R` is a structure containing the data of `i, j, c` and a proof that
`i ≠ j`. These are often easier to manipulate than straight matrices, especially in inductive
arguments.
* `exists_list_transvec_mul_diagonal_mul_list_transvec` states that any matrix `M` over a field can
be written in the form `t_1 * ... * t_k * D * t'_1 * ... * t'_l`, where `D` is diagonal and
the `t_i`, `t'_j` are transvections.
* `diagonal_transvection_induction` shows that a property which is true for diagonal matrices and
transvections, and invariant under product, is true for all matrices.
* `diagonal_transvection_induction_of_det_ne_zero` is the same statement over invertible matrices.
## Implementation details
The proof of the reduction results is done inductively on the size of the matrices, reducing an
`(r + 1) × (r + 1)` matrix to a matrix whose last row and column are zeroes, except possibly for
the last diagonal entry. This step is done as follows.
If all the coefficients on the last row and column are zero, there is nothing to do. Otherwise,
one can put a nonzero coefficient in the last diagonal entry by a row or column operation, and then
subtract this last diagonal entry from the other entries in the last row and column to make them
vanish.
This step is done in the type `Fin r ⊕ Unit`, where `Fin r` is useful to choose arbitrarily some
order in which we cancel the coefficients, and the sum structure is useful to use the formalism of
block matrices.
To proceed with the induction, we reindex our matrices to reduce to the above situation.
-/
universe u₁ u₂
namespace Matrix
open Matrix
variable (n p : Type*) (R : Type u₂) {𝕜 : Type*} [Field 𝕜]
variable [DecidableEq n] [DecidableEq p]
variable [CommRing R]
section Transvection
variable {R n} (i j : n)
/-- The transvection matrix `Transvection i j c` is equal to the identity plus `c` at position
`(i, j)`. Multiplying by it on the left (as in `Transvection i j c * M`) corresponds to adding
`c` times the `j`-th line of `M` to its `i`-th line. Multiplying by it on the right corresponds
to adding `c` times the `i`-th column to the `j`-th column. -/
def transvection (c : R) : Matrix n n R :=
1 + Matrix.stdBasisMatrix i j c
#align matrix.transvection Matrix.transvection
@[simp]
theorem transvection_zero : transvection i j (0 : R) = 1 := by simp [transvection]
#align matrix.transvection_zero Matrix.transvection_zero
section
/-- A transvection matrix is obtained from the identity by adding `c` times the `j`-th row to
the `i`-th row. -/
| Mathlib/LinearAlgebra/Matrix/Transvection.lean | 94 | 108 | theorem updateRow_eq_transvection [Finite n] (c : R) :
updateRow (1 : Matrix n n R) i ((1 : Matrix n n R) i + c • (1 : Matrix n n R) j) =
transvection i j c := by |
cases nonempty_fintype n
ext a b
by_cases ha : i = a
· by_cases hb : j = b
· simp only [updateRow_self, transvection, ha, hb, Pi.add_apply, StdBasisMatrix.apply_same,
one_apply_eq, Pi.smul_apply, mul_one, Algebra.id.smul_eq_mul, add_apply]
· simp only [updateRow_self, transvection, ha, hb, StdBasisMatrix.apply_of_ne, Pi.add_apply,
Ne, not_false_iff, Pi.smul_apply, and_false_iff, one_apply_ne, Algebra.id.smul_eq_mul,
mul_zero, add_apply]
· simp only [updateRow_ne, transvection, ha, Ne.symm ha, StdBasisMatrix.apply_of_ne, add_zero,
Algebra.id.smul_eq_mul, Ne, not_false_iff, DMatrix.add_apply, Pi.smul_apply,
mul_zero, false_and_iff, add_apply]
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Analysis.SpecificLimits.Basic
import Mathlib.Topology.MetricSpace.IsometricSMul
#align_import topology.metric_space.hausdorff_distance from "leanprover-community/mathlib"@"bc91ed7093bf098d253401e69df601fc33dde156"
/-!
# Hausdorff distance
The Hausdorff distance on subsets of a metric (or emetric) space.
Given two subsets `s` and `t` of a metric space, their Hausdorff distance is the smallest `d`
such that any point `s` is within `d` of a point in `t`, and conversely. This quantity
is often infinite (think of `s` bounded and `t` unbounded), and therefore better
expressed in the setting of emetric spaces.
## Main definitions
This files introduces:
* `EMetric.infEdist x s`, the infimum edistance of a point `x` to a set `s` in an emetric space
* `EMetric.hausdorffEdist s t`, the Hausdorff edistance of two sets in an emetric space
* Versions of these notions on metric spaces, called respectively `Metric.infDist`
and `Metric.hausdorffDist`
## Main results
* `infEdist_closure`: the edistance to a set and its closure coincide
* `EMetric.mem_closure_iff_infEdist_zero`: a point `x` belongs to the closure of `s` iff
`infEdist x s = 0`
* `IsCompact.exists_infEdist_eq_edist`: if `s` is compact and non-empty, there exists a point `y`
which attains this edistance
* `IsOpen.exists_iUnion_isClosed`: every open set `U` can be written as the increasing union
of countably many closed subsets of `U`
* `hausdorffEdist_closure`: replacing a set by its closure does not change the Hausdorff edistance
* `hausdorffEdist_zero_iff_closure_eq_closure`: two sets have Hausdorff edistance zero
iff their closures coincide
* the Hausdorff edistance is symmetric and satisfies the triangle inequality
* in particular, closed sets in an emetric space are an emetric space
(this is shown in `EMetricSpace.closeds.emetricspace`)
* versions of these notions on metric spaces
* `hausdorffEdist_ne_top_of_nonempty_of_bounded`: if two sets in a metric space
are nonempty and bounded in a metric space, they are at finite Hausdorff edistance.
## Tags
metric space, Hausdorff distance
-/
noncomputable section
open NNReal ENNReal Topology Set Filter Pointwise Bornology
universe u v w
variable {ι : Sort*} {α : Type u} {β : Type v}
namespace EMetric
section InfEdist
variable [PseudoEMetricSpace α] [PseudoEMetricSpace β] {x y : α} {s t : Set α} {Φ : α → β}
/-! ### Distance of a point to a set as a function into `ℝ≥0∞`. -/
/-- The minimal edistance of a point to a set -/
def infEdist (x : α) (s : Set α) : ℝ≥0∞ :=
⨅ y ∈ s, edist x y
#align emetric.inf_edist EMetric.infEdist
@[simp]
theorem infEdist_empty : infEdist x ∅ = ∞ :=
iInf_emptyset
#align emetric.inf_edist_empty EMetric.infEdist_empty
theorem le_infEdist {d} : d ≤ infEdist x s ↔ ∀ y ∈ s, d ≤ edist x y := by
simp only [infEdist, le_iInf_iff]
#align emetric.le_inf_edist EMetric.le_infEdist
/-- The edist to a union is the minimum of the edists -/
@[simp]
theorem infEdist_union : infEdist x (s ∪ t) = infEdist x s ⊓ infEdist x t :=
iInf_union
#align emetric.inf_edist_union EMetric.infEdist_union
@[simp]
theorem infEdist_iUnion (f : ι → Set α) (x : α) : infEdist x (⋃ i, f i) = ⨅ i, infEdist x (f i) :=
iInf_iUnion f _
#align emetric.inf_edist_Union EMetric.infEdist_iUnion
lemma infEdist_biUnion {ι : Type*} (f : ι → Set α) (I : Set ι) (x : α) :
infEdist x (⋃ i ∈ I, f i) = ⨅ i ∈ I, infEdist x (f i) := by simp only [infEdist_iUnion]
/-- The edist to a singleton is the edistance to the single point of this singleton -/
@[simp]
theorem infEdist_singleton : infEdist x {y} = edist x y :=
iInf_singleton
#align emetric.inf_edist_singleton EMetric.infEdist_singleton
/-- The edist to a set is bounded above by the edist to any of its points -/
theorem infEdist_le_edist_of_mem (h : y ∈ s) : infEdist x s ≤ edist x y :=
iInf₂_le y h
#align emetric.inf_edist_le_edist_of_mem EMetric.infEdist_le_edist_of_mem
/-- If a point `x` belongs to `s`, then its edist to `s` vanishes -/
theorem infEdist_zero_of_mem (h : x ∈ s) : infEdist x s = 0 :=
nonpos_iff_eq_zero.1 <| @edist_self _ _ x ▸ infEdist_le_edist_of_mem h
#align emetric.inf_edist_zero_of_mem EMetric.infEdist_zero_of_mem
/-- The edist is antitone with respect to inclusion. -/
theorem infEdist_anti (h : s ⊆ t) : infEdist x t ≤ infEdist x s :=
iInf_le_iInf_of_subset h
#align emetric.inf_edist_anti EMetric.infEdist_anti
/-- The edist to a set is `< r` iff there exists a point in the set at edistance `< r` -/
theorem infEdist_lt_iff {r : ℝ≥0∞} : infEdist x s < r ↔ ∃ y ∈ s, edist x y < r := by
simp_rw [infEdist, iInf_lt_iff, exists_prop]
#align emetric.inf_edist_lt_iff EMetric.infEdist_lt_iff
/-- The edist of `x` to `s` is bounded by the sum of the edist of `y` to `s` and
the edist from `x` to `y` -/
theorem infEdist_le_infEdist_add_edist : infEdist x s ≤ infEdist y s + edist x y :=
calc
⨅ z ∈ s, edist x z ≤ ⨅ z ∈ s, edist y z + edist x y :=
iInf₂_mono fun z _ => (edist_triangle _ _ _).trans_eq (add_comm _ _)
_ = (⨅ z ∈ s, edist y z) + edist x y := by simp only [ENNReal.iInf_add]
#align emetric.inf_edist_le_inf_edist_add_edist EMetric.infEdist_le_infEdist_add_edist
theorem infEdist_le_edist_add_infEdist : infEdist x s ≤ edist x y + infEdist y s := by
rw [add_comm]
exact infEdist_le_infEdist_add_edist
#align emetric.inf_edist_le_edist_add_inf_edist EMetric.infEdist_le_edist_add_infEdist
theorem edist_le_infEdist_add_ediam (hy : y ∈ s) : edist x y ≤ infEdist x s + diam s := by
simp_rw [infEdist, ENNReal.iInf_add]
refine le_iInf₂ fun i hi => ?_
calc
edist x y ≤ edist x i + edist i y := edist_triangle _ _ _
_ ≤ edist x i + diam s := add_le_add le_rfl (edist_le_diam_of_mem hi hy)
#align emetric.edist_le_inf_edist_add_ediam EMetric.edist_le_infEdist_add_ediam
/-- The edist to a set depends continuously on the point -/
@[continuity]
theorem continuous_infEdist : Continuous fun x => infEdist x s :=
continuous_of_le_add_edist 1 (by simp) <| by
simp only [one_mul, infEdist_le_infEdist_add_edist, forall₂_true_iff]
#align emetric.continuous_inf_edist EMetric.continuous_infEdist
/-- The edist to a set and to its closure coincide -/
theorem infEdist_closure : infEdist x (closure s) = infEdist x s := by
refine le_antisymm (infEdist_anti subset_closure) ?_
refine ENNReal.le_of_forall_pos_le_add fun ε εpos h => ?_
have ε0 : 0 < (ε / 2 : ℝ≥0∞) := by simpa [pos_iff_ne_zero] using εpos
have : infEdist x (closure s) < infEdist x (closure s) + ε / 2 :=
ENNReal.lt_add_right h.ne ε0.ne'
obtain ⟨y : α, ycs : y ∈ closure s, hy : edist x y < infEdist x (closure s) + ↑ε / 2⟩ :=
infEdist_lt_iff.mp this
obtain ⟨z : α, zs : z ∈ s, dyz : edist y z < ↑ε / 2⟩ := EMetric.mem_closure_iff.1 ycs (ε / 2) ε0
calc
infEdist x s ≤ edist x z := infEdist_le_edist_of_mem zs
_ ≤ edist x y + edist y z := edist_triangle _ _ _
_ ≤ infEdist x (closure s) + ε / 2 + ε / 2 := add_le_add (le_of_lt hy) (le_of_lt dyz)
_ = infEdist x (closure s) + ↑ε := by rw [add_assoc, ENNReal.add_halves]
#align emetric.inf_edist_closure EMetric.infEdist_closure
/-- A point belongs to the closure of `s` iff its infimum edistance to this set vanishes -/
theorem mem_closure_iff_infEdist_zero : x ∈ closure s ↔ infEdist x s = 0 :=
⟨fun h => by
rw [← infEdist_closure]
exact infEdist_zero_of_mem h,
fun h =>
EMetric.mem_closure_iff.2 fun ε εpos => infEdist_lt_iff.mp <| by rwa [h]⟩
#align emetric.mem_closure_iff_inf_edist_zero EMetric.mem_closure_iff_infEdist_zero
/-- Given a closed set `s`, a point belongs to `s` iff its infimum edistance to this set vanishes -/
theorem mem_iff_infEdist_zero_of_closed (h : IsClosed s) : x ∈ s ↔ infEdist x s = 0 := by
rw [← mem_closure_iff_infEdist_zero, h.closure_eq]
#align emetric.mem_iff_inf_edist_zero_of_closed EMetric.mem_iff_infEdist_zero_of_closed
/-- The infimum edistance of a point to a set is positive if and only if the point is not in the
closure of the set. -/
theorem infEdist_pos_iff_not_mem_closure {x : α} {E : Set α} :
0 < infEdist x E ↔ x ∉ closure E := by
rw [mem_closure_iff_infEdist_zero, pos_iff_ne_zero]
#align emetric.inf_edist_pos_iff_not_mem_closure EMetric.infEdist_pos_iff_not_mem_closure
theorem infEdist_closure_pos_iff_not_mem_closure {x : α} {E : Set α} :
0 < infEdist x (closure E) ↔ x ∉ closure E := by
rw [infEdist_closure, infEdist_pos_iff_not_mem_closure]
#align emetric.inf_edist_closure_pos_iff_not_mem_closure EMetric.infEdist_closure_pos_iff_not_mem_closure
theorem exists_real_pos_lt_infEdist_of_not_mem_closure {x : α} {E : Set α} (h : x ∉ closure E) :
∃ ε : ℝ, 0 < ε ∧ ENNReal.ofReal ε < infEdist x E := by
rw [← infEdist_pos_iff_not_mem_closure, ENNReal.lt_iff_exists_real_btwn] at h
rcases h with ⟨ε, ⟨_, ⟨ε_pos, ε_lt⟩⟩⟩
exact ⟨ε, ⟨ENNReal.ofReal_pos.mp ε_pos, ε_lt⟩⟩
#align emetric.exists_real_pos_lt_inf_edist_of_not_mem_closure EMetric.exists_real_pos_lt_infEdist_of_not_mem_closure
theorem disjoint_closedBall_of_lt_infEdist {r : ℝ≥0∞} (h : r < infEdist x s) :
Disjoint (closedBall x r) s := by
rw [disjoint_left]
intro y hy h'y
apply lt_irrefl (infEdist x s)
calc
infEdist x s ≤ edist x y := infEdist_le_edist_of_mem h'y
_ ≤ r := by rwa [mem_closedBall, edist_comm] at hy
_ < infEdist x s := h
#align emetric.disjoint_closed_ball_of_lt_inf_edist EMetric.disjoint_closedBall_of_lt_infEdist
/-- The infimum edistance is invariant under isometries -/
theorem infEdist_image (hΦ : Isometry Φ) : infEdist (Φ x) (Φ '' t) = infEdist x t := by
simp only [infEdist, iInf_image, hΦ.edist_eq]
#align emetric.inf_edist_image EMetric.infEdist_image
@[to_additive (attr := simp)]
theorem infEdist_smul {M} [SMul M α] [IsometricSMul M α] (c : M) (x : α) (s : Set α) :
infEdist (c • x) (c • s) = infEdist x s :=
infEdist_image (isometry_smul _ _)
#align emetric.inf_edist_smul EMetric.infEdist_smul
#align emetric.inf_edist_vadd EMetric.infEdist_vadd
theorem _root_.IsOpen.exists_iUnion_isClosed {U : Set α} (hU : IsOpen U) :
∃ F : ℕ → Set α, (∀ n, IsClosed (F n)) ∧ (∀ n, F n ⊆ U) ∧ ⋃ n, F n = U ∧ Monotone F := by
obtain ⟨a, a_pos, a_lt_one⟩ : ∃ a : ℝ≥0∞, 0 < a ∧ a < 1 := exists_between zero_lt_one
let F := fun n : ℕ => (fun x => infEdist x Uᶜ) ⁻¹' Ici (a ^ n)
have F_subset : ∀ n, F n ⊆ U := fun n x hx ↦ by
by_contra h
have : infEdist x Uᶜ ≠ 0 := ((ENNReal.pow_pos a_pos _).trans_le hx).ne'
exact this (infEdist_zero_of_mem h)
refine ⟨F, fun n => IsClosed.preimage continuous_infEdist isClosed_Ici, F_subset, ?_, ?_⟩
· show ⋃ n, F n = U
refine Subset.antisymm (by simp only [iUnion_subset_iff, F_subset, forall_const]) fun x hx => ?_
have : ¬x ∈ Uᶜ := by simpa using hx
rw [mem_iff_infEdist_zero_of_closed hU.isClosed_compl] at this
have B : 0 < infEdist x Uᶜ := by simpa [pos_iff_ne_zero] using this
have : Filter.Tendsto (fun n => a ^ n) atTop (𝓝 0) :=
ENNReal.tendsto_pow_atTop_nhds_zero_of_lt_one a_lt_one
rcases ((tendsto_order.1 this).2 _ B).exists with ⟨n, hn⟩
simp only [mem_iUnion, mem_Ici, mem_preimage]
exact ⟨n, hn.le⟩
show Monotone F
intro m n hmn x hx
simp only [F, mem_Ici, mem_preimage] at hx ⊢
apply le_trans (pow_le_pow_right_of_le_one' a_lt_one.le hmn) hx
#align is_open.exists_Union_is_closed IsOpen.exists_iUnion_isClosed
theorem _root_.IsCompact.exists_infEdist_eq_edist (hs : IsCompact s) (hne : s.Nonempty) (x : α) :
∃ y ∈ s, infEdist x s = edist x y := by
have A : Continuous fun y => edist x y := continuous_const.edist continuous_id
obtain ⟨y, ys, hy⟩ := hs.exists_isMinOn hne A.continuousOn
exact ⟨y, ys, le_antisymm (infEdist_le_edist_of_mem ys) (by rwa [le_infEdist])⟩
#align is_compact.exists_inf_edist_eq_edist IsCompact.exists_infEdist_eq_edist
theorem exists_pos_forall_lt_edist (hs : IsCompact s) (ht : IsClosed t) (hst : Disjoint s t) :
∃ r : ℝ≥0, 0 < r ∧ ∀ x ∈ s, ∀ y ∈ t, (r : ℝ≥0∞) < edist x y := by
rcases s.eq_empty_or_nonempty with (rfl | hne)
· use 1
simp
obtain ⟨x, hx, h⟩ := hs.exists_isMinOn hne continuous_infEdist.continuousOn
have : 0 < infEdist x t :=
pos_iff_ne_zero.2 fun H => hst.le_bot ⟨hx, (mem_iff_infEdist_zero_of_closed ht).mpr H⟩
rcases ENNReal.lt_iff_exists_nnreal_btwn.1 this with ⟨r, h₀, hr⟩
exact ⟨r, ENNReal.coe_pos.mp h₀, fun y hy z hz => hr.trans_le <| le_infEdist.1 (h hy) z hz⟩
#align emetric.exists_pos_forall_lt_edist EMetric.exists_pos_forall_lt_edist
end InfEdist
/-! ### The Hausdorff distance as a function into `ℝ≥0∞`. -/
/-- The Hausdorff edistance between two sets is the smallest `r` such that each set
is contained in the `r`-neighborhood of the other one -/
irreducible_def hausdorffEdist {α : Type u} [PseudoEMetricSpace α] (s t : Set α) : ℝ≥0∞ :=
(⨆ x ∈ s, infEdist x t) ⊔ ⨆ y ∈ t, infEdist y s
#align emetric.Hausdorff_edist EMetric.hausdorffEdist
#align emetric.Hausdorff_edist_def EMetric.hausdorffEdist_def
section HausdorffEdist
variable [PseudoEMetricSpace α] [PseudoEMetricSpace β] {x y : α} {s t u : Set α} {Φ : α → β}
/-- The Hausdorff edistance of a set to itself vanishes. -/
@[simp]
theorem hausdorffEdist_self : hausdorffEdist s s = 0 := by
simp only [hausdorffEdist_def, sup_idem, ENNReal.iSup_eq_zero]
exact fun x hx => infEdist_zero_of_mem hx
#align emetric.Hausdorff_edist_self EMetric.hausdorffEdist_self
/-- The Haudorff edistances of `s` to `t` and of `t` to `s` coincide. -/
theorem hausdorffEdist_comm : hausdorffEdist s t = hausdorffEdist t s := by
simp only [hausdorffEdist_def]; apply sup_comm
set_option linter.uppercaseLean3 false in
#align emetric.Hausdorff_edist_comm EMetric.hausdorffEdist_comm
/-- Bounding the Hausdorff edistance by bounding the edistance of any point
in each set to the other set -/
theorem hausdorffEdist_le_of_infEdist {r : ℝ≥0∞} (H1 : ∀ x ∈ s, infEdist x t ≤ r)
(H2 : ∀ x ∈ t, infEdist x s ≤ r) : hausdorffEdist s t ≤ r := by
simp only [hausdorffEdist_def, sup_le_iff, iSup_le_iff]
exact ⟨H1, H2⟩
#align emetric.Hausdorff_edist_le_of_inf_edist EMetric.hausdorffEdist_le_of_infEdist
/-- Bounding the Hausdorff edistance by exhibiting, for any point in each set,
another point in the other set at controlled distance -/
theorem hausdorffEdist_le_of_mem_edist {r : ℝ≥0∞} (H1 : ∀ x ∈ s, ∃ y ∈ t, edist x y ≤ r)
(H2 : ∀ x ∈ t, ∃ y ∈ s, edist x y ≤ r) : hausdorffEdist s t ≤ r := by
refine hausdorffEdist_le_of_infEdist (fun x xs ↦ ?_) (fun x xt ↦ ?_)
· rcases H1 x xs with ⟨y, yt, hy⟩
exact le_trans (infEdist_le_edist_of_mem yt) hy
· rcases H2 x xt with ⟨y, ys, hy⟩
exact le_trans (infEdist_le_edist_of_mem ys) hy
#align emetric.Hausdorff_edist_le_of_mem_edist EMetric.hausdorffEdist_le_of_mem_edist
/-- The distance to a set is controlled by the Hausdorff distance. -/
theorem infEdist_le_hausdorffEdist_of_mem (h : x ∈ s) : infEdist x t ≤ hausdorffEdist s t := by
rw [hausdorffEdist_def]
refine le_trans ?_ le_sup_left
exact le_iSup₂ (α := ℝ≥0∞) x h
#align emetric.inf_edist_le_Hausdorff_edist_of_mem EMetric.infEdist_le_hausdorffEdist_of_mem
/-- If the Hausdorff distance is `< r`, then any point in one of the sets has
a corresponding point at distance `< r` in the other set. -/
theorem exists_edist_lt_of_hausdorffEdist_lt {r : ℝ≥0∞} (h : x ∈ s) (H : hausdorffEdist s t < r) :
∃ y ∈ t, edist x y < r :=
infEdist_lt_iff.mp <|
calc
infEdist x t ≤ hausdorffEdist s t := infEdist_le_hausdorffEdist_of_mem h
_ < r := H
#align emetric.exists_edist_lt_of_Hausdorff_edist_lt EMetric.exists_edist_lt_of_hausdorffEdist_lt
/-- The distance from `x` to `s` or `t` is controlled in terms of the Hausdorff distance
between `s` and `t`. -/
theorem infEdist_le_infEdist_add_hausdorffEdist :
infEdist x t ≤ infEdist x s + hausdorffEdist s t :=
ENNReal.le_of_forall_pos_le_add fun ε εpos h => by
have ε0 : (ε / 2 : ℝ≥0∞) ≠ 0 := by simpa [pos_iff_ne_zero] using εpos
have : infEdist x s < infEdist x s + ε / 2 :=
ENNReal.lt_add_right (ENNReal.add_lt_top.1 h).1.ne ε0
obtain ⟨y : α, ys : y ∈ s, dxy : edist x y < infEdist x s + ↑ε / 2⟩ := infEdist_lt_iff.mp this
have : hausdorffEdist s t < hausdorffEdist s t + ε / 2 :=
ENNReal.lt_add_right (ENNReal.add_lt_top.1 h).2.ne ε0
obtain ⟨z : α, zt : z ∈ t, dyz : edist y z < hausdorffEdist s t + ↑ε / 2⟩ :=
exists_edist_lt_of_hausdorffEdist_lt ys this
calc
infEdist x t ≤ edist x z := infEdist_le_edist_of_mem zt
_ ≤ edist x y + edist y z := edist_triangle _ _ _
_ ≤ infEdist x s + ε / 2 + (hausdorffEdist s t + ε / 2) := add_le_add dxy.le dyz.le
_ = infEdist x s + hausdorffEdist s t + ε := by
simp [ENNReal.add_halves, add_comm, add_left_comm]
#align emetric.inf_edist_le_inf_edist_add_Hausdorff_edist EMetric.infEdist_le_infEdist_add_hausdorffEdist
/-- The Hausdorff edistance is invariant under isometries. -/
theorem hausdorffEdist_image (h : Isometry Φ) :
hausdorffEdist (Φ '' s) (Φ '' t) = hausdorffEdist s t := by
simp only [hausdorffEdist_def, iSup_image, infEdist_image h]
#align emetric.Hausdorff_edist_image EMetric.hausdorffEdist_image
/-- The Hausdorff distance is controlled by the diameter of the union. -/
theorem hausdorffEdist_le_ediam (hs : s.Nonempty) (ht : t.Nonempty) :
hausdorffEdist s t ≤ diam (s ∪ t) := by
rcases hs with ⟨x, xs⟩
rcases ht with ⟨y, yt⟩
refine hausdorffEdist_le_of_mem_edist ?_ ?_
· intro z hz
exact ⟨y, yt, edist_le_diam_of_mem (subset_union_left hz) (subset_union_right yt)⟩
· intro z hz
exact ⟨x, xs, edist_le_diam_of_mem (subset_union_right hz) (subset_union_left xs)⟩
#align emetric.Hausdorff_edist_le_ediam EMetric.hausdorffEdist_le_ediam
/-- The Hausdorff distance satisfies the triangle inequality. -/
theorem hausdorffEdist_triangle : hausdorffEdist s u ≤ hausdorffEdist s t + hausdorffEdist t u := by
rw [hausdorffEdist_def]
simp only [sup_le_iff, iSup_le_iff]
constructor
· show ∀ x ∈ s, infEdist x u ≤ hausdorffEdist s t + hausdorffEdist t u
exact fun x xs =>
calc
infEdist x u ≤ infEdist x t + hausdorffEdist t u :=
infEdist_le_infEdist_add_hausdorffEdist
_ ≤ hausdorffEdist s t + hausdorffEdist t u :=
add_le_add_right (infEdist_le_hausdorffEdist_of_mem xs) _
· show ∀ x ∈ u, infEdist x s ≤ hausdorffEdist s t + hausdorffEdist t u
exact fun x xu =>
calc
infEdist x s ≤ infEdist x t + hausdorffEdist t s :=
infEdist_le_infEdist_add_hausdorffEdist
_ ≤ hausdorffEdist u t + hausdorffEdist t s :=
add_le_add_right (infEdist_le_hausdorffEdist_of_mem xu) _
_ = hausdorffEdist s t + hausdorffEdist t u := by simp [hausdorffEdist_comm, add_comm]
#align emetric.Hausdorff_edist_triangle EMetric.hausdorffEdist_triangle
/-- Two sets are at zero Hausdorff edistance if and only if they have the same closure. -/
theorem hausdorffEdist_zero_iff_closure_eq_closure :
hausdorffEdist s t = 0 ↔ closure s = closure t := by
simp only [hausdorffEdist_def, ENNReal.sup_eq_zero, ENNReal.iSup_eq_zero, ← subset_def,
← mem_closure_iff_infEdist_zero, subset_antisymm_iff, isClosed_closure.closure_subset_iff]
#align emetric.Hausdorff_edist_zero_iff_closure_eq_closure EMetric.hausdorffEdist_zero_iff_closure_eq_closure
/-- The Hausdorff edistance between a set and its closure vanishes. -/
@[simp]
theorem hausdorffEdist_self_closure : hausdorffEdist s (closure s) = 0 := by
rw [hausdorffEdist_zero_iff_closure_eq_closure, closure_closure]
#align emetric.Hausdorff_edist_self_closure EMetric.hausdorffEdist_self_closure
/-- Replacing a set by its closure does not change the Hausdorff edistance. -/
@[simp]
theorem hausdorffEdist_closure₁ : hausdorffEdist (closure s) t = hausdorffEdist s t := by
refine le_antisymm ?_ ?_
· calc
_ ≤ hausdorffEdist (closure s) s + hausdorffEdist s t := hausdorffEdist_triangle
_ = hausdorffEdist s t := by simp [hausdorffEdist_comm]
· calc
_ ≤ hausdorffEdist s (closure s) + hausdorffEdist (closure s) t := hausdorffEdist_triangle
_ = hausdorffEdist (closure s) t := by simp
#align emetric.Hausdorff_edist_closure₁ EMetric.hausdorffEdist_closure₁
/-- Replacing a set by its closure does not change the Hausdorff edistance. -/
@[simp]
theorem hausdorffEdist_closure₂ : hausdorffEdist s (closure t) = hausdorffEdist s t := by
simp [@hausdorffEdist_comm _ _ s _]
#align emetric.Hausdorff_edist_closure₂ EMetric.hausdorffEdist_closure₂
/-- The Hausdorff edistance between sets or their closures is the same. -/
-- @[simp] -- Porting note (#10618): simp can prove this
theorem hausdorffEdist_closure : hausdorffEdist (closure s) (closure t) = hausdorffEdist s t := by
simp
#align emetric.Hausdorff_edist_closure EMetric.hausdorffEdist_closure
/-- Two closed sets are at zero Hausdorff edistance if and only if they coincide. -/
theorem hausdorffEdist_zero_iff_eq_of_closed (hs : IsClosed s) (ht : IsClosed t) :
hausdorffEdist s t = 0 ↔ s = t := by
rw [hausdorffEdist_zero_iff_closure_eq_closure, hs.closure_eq, ht.closure_eq]
#align emetric.Hausdorff_edist_zero_iff_eq_of_closed EMetric.hausdorffEdist_zero_iff_eq_of_closed
/-- The Haudorff edistance to the empty set is infinite. -/
theorem hausdorffEdist_empty (ne : s.Nonempty) : hausdorffEdist s ∅ = ∞ := by
rcases ne with ⟨x, xs⟩
have : infEdist x ∅ ≤ hausdorffEdist s ∅ := infEdist_le_hausdorffEdist_of_mem xs
simpa using this
#align emetric.Hausdorff_edist_empty EMetric.hausdorffEdist_empty
/-- If a set is at finite Hausdorff edistance of a nonempty set, it is nonempty. -/
theorem nonempty_of_hausdorffEdist_ne_top (hs : s.Nonempty) (fin : hausdorffEdist s t ≠ ⊤) :
t.Nonempty :=
t.eq_empty_or_nonempty.resolve_left fun ht ↦ fin (ht.symm ▸ hausdorffEdist_empty hs)
#align emetric.nonempty_of_Hausdorff_edist_ne_top EMetric.nonempty_of_hausdorffEdist_ne_top
theorem empty_or_nonempty_of_hausdorffEdist_ne_top (fin : hausdorffEdist s t ≠ ⊤) :
(s = ∅ ∧ t = ∅) ∨ (s.Nonempty ∧ t.Nonempty) := by
rcases s.eq_empty_or_nonempty with hs | hs
· rcases t.eq_empty_or_nonempty with ht | ht
· exact Or.inl ⟨hs, ht⟩
· rw [hausdorffEdist_comm] at fin
exact Or.inr ⟨nonempty_of_hausdorffEdist_ne_top ht fin, ht⟩
· exact Or.inr ⟨hs, nonempty_of_hausdorffEdist_ne_top hs fin⟩
#align emetric.empty_or_nonempty_of_Hausdorff_edist_ne_top EMetric.empty_or_nonempty_of_hausdorffEdist_ne_top
end HausdorffEdist
-- section
end EMetric
/-! Now, we turn to the same notions in metric spaces. To avoid the difficulties related to
`sInf` and `sSup` on `ℝ` (which is only conditionally complete), we use the notions in `ℝ≥0∞`
formulated in terms of the edistance, and coerce them to `ℝ`.
Then their properties follow readily from the corresponding properties in `ℝ≥0∞`,
modulo some tedious rewriting of inequalities from one to the other. -/
--namespace
namespace Metric
section
variable [PseudoMetricSpace α] [PseudoMetricSpace β] {s t u : Set α} {x y : α} {Φ : α → β}
open EMetric
/-! ### Distance of a point to a set as a function into `ℝ`. -/
/-- The minimal distance of a point to a set -/
def infDist (x : α) (s : Set α) : ℝ :=
ENNReal.toReal (infEdist x s)
#align metric.inf_dist Metric.infDist
theorem infDist_eq_iInf : infDist x s = ⨅ y : s, dist x y := by
rw [infDist, infEdist, iInf_subtype', ENNReal.toReal_iInf]
· simp only [dist_edist]
· exact fun _ ↦ edist_ne_top _ _
#align metric.inf_dist_eq_infi Metric.infDist_eq_iInf
/-- The minimal distance is always nonnegative -/
theorem infDist_nonneg : 0 ≤ infDist x s := toReal_nonneg
#align metric.inf_dist_nonneg Metric.infDist_nonneg
/-- The minimal distance to the empty set is 0 (if you want to have the more reasonable
value `∞` instead, use `EMetric.infEdist`, which takes values in `ℝ≥0∞`) -/
@[simp]
theorem infDist_empty : infDist x ∅ = 0 := by simp [infDist]
#align metric.inf_dist_empty Metric.infDist_empty
/-- In a metric space, the minimal edistance to a nonempty set is finite. -/
theorem infEdist_ne_top (h : s.Nonempty) : infEdist x s ≠ ⊤ := by
rcases h with ⟨y, hy⟩
exact ne_top_of_le_ne_top (edist_ne_top _ _) (infEdist_le_edist_of_mem hy)
#align metric.inf_edist_ne_top Metric.infEdist_ne_top
-- Porting note (#10756): new lemma;
-- Porting note (#11215): TODO: make it a `simp` lemma
theorem infEdist_eq_top_iff : infEdist x s = ∞ ↔ s = ∅ := by
rcases s.eq_empty_or_nonempty with rfl | hs <;> simp [*, Nonempty.ne_empty, infEdist_ne_top]
/-- The minimal distance of a point to a set containing it vanishes. -/
theorem infDist_zero_of_mem (h : x ∈ s) : infDist x s = 0 := by
simp [infEdist_zero_of_mem h, infDist]
#align metric.inf_dist_zero_of_mem Metric.infDist_zero_of_mem
/-- The minimal distance to a singleton is the distance to the unique point in this singleton. -/
@[simp]
theorem infDist_singleton : infDist x {y} = dist x y := by simp [infDist, dist_edist]
#align metric.inf_dist_singleton Metric.infDist_singleton
/-- The minimal distance to a set is bounded by the distance to any point in this set. -/
theorem infDist_le_dist_of_mem (h : y ∈ s) : infDist x s ≤ dist x y := by
rw [dist_edist, infDist]
exact ENNReal.toReal_mono (edist_ne_top _ _) (infEdist_le_edist_of_mem h)
#align metric.inf_dist_le_dist_of_mem Metric.infDist_le_dist_of_mem
/-- The minimal distance is monotone with respect to inclusion. -/
theorem infDist_le_infDist_of_subset (h : s ⊆ t) (hs : s.Nonempty) : infDist x t ≤ infDist x s :=
ENNReal.toReal_mono (infEdist_ne_top hs) (infEdist_anti h)
#align metric.inf_dist_le_inf_dist_of_subset Metric.infDist_le_infDist_of_subset
/-- The minimal distance to a set `s` is `< r` iff there exists a point in `s` at distance `< r`. -/
theorem infDist_lt_iff {r : ℝ} (hs : s.Nonempty) : infDist x s < r ↔ ∃ y ∈ s, dist x y < r := by
simp_rw [infDist, ← ENNReal.lt_ofReal_iff_toReal_lt (infEdist_ne_top hs), infEdist_lt_iff,
ENNReal.lt_ofReal_iff_toReal_lt (edist_ne_top _ _), ← dist_edist]
#align metric.inf_dist_lt_iff Metric.infDist_lt_iff
/-- The minimal distance from `x` to `s` is bounded by the distance from `y` to `s`, modulo
the distance between `x` and `y`. -/
theorem infDist_le_infDist_add_dist : infDist x s ≤ infDist y s + dist x y := by
rw [infDist, infDist, dist_edist]
refine ENNReal.toReal_le_add' infEdist_le_infEdist_add_edist ?_ (flip absurd (edist_ne_top _ _))
simp only [infEdist_eq_top_iff, imp_self]
#align metric.inf_dist_le_inf_dist_add_dist Metric.infDist_le_infDist_add_dist
theorem not_mem_of_dist_lt_infDist (h : dist x y < infDist x s) : y ∉ s := fun hy =>
h.not_le <| infDist_le_dist_of_mem hy
#align metric.not_mem_of_dist_lt_inf_dist Metric.not_mem_of_dist_lt_infDist
theorem disjoint_ball_infDist : Disjoint (ball x (infDist x s)) s :=
disjoint_left.2 fun _y hy => not_mem_of_dist_lt_infDist <| mem_ball'.1 hy
#align metric.disjoint_ball_inf_dist Metric.disjoint_ball_infDist
theorem ball_infDist_subset_compl : ball x (infDist x s) ⊆ sᶜ :=
(disjoint_ball_infDist (s := s)).subset_compl_right
#align metric.ball_inf_dist_subset_compl Metric.ball_infDist_subset_compl
theorem ball_infDist_compl_subset : ball x (infDist x sᶜ) ⊆ s :=
ball_infDist_subset_compl.trans_eq (compl_compl s)
#align metric.ball_inf_dist_compl_subset Metric.ball_infDist_compl_subset
theorem disjoint_closedBall_of_lt_infDist {r : ℝ} (h : r < infDist x s) :
Disjoint (closedBall x r) s :=
disjoint_ball_infDist.mono_left <| closedBall_subset_ball h
#align metric.disjoint_closed_ball_of_lt_inf_dist Metric.disjoint_closedBall_of_lt_infDist
theorem dist_le_infDist_add_diam (hs : IsBounded s) (hy : y ∈ s) :
dist x y ≤ infDist x s + diam s := by
rw [infDist, diam, dist_edist]
exact toReal_le_add (edist_le_infEdist_add_ediam hy) (infEdist_ne_top ⟨y, hy⟩) hs.ediam_ne_top
#align metric.dist_le_inf_dist_add_diam Metric.dist_le_infDist_add_diam
variable (s)
/-- The minimal distance to a set is Lipschitz in point with constant 1 -/
theorem lipschitz_infDist_pt : LipschitzWith 1 (infDist · s) :=
LipschitzWith.of_le_add fun _ _ => infDist_le_infDist_add_dist
#align metric.lipschitz_inf_dist_pt Metric.lipschitz_infDist_pt
/-- The minimal distance to a set is uniformly continuous in point -/
theorem uniformContinuous_infDist_pt : UniformContinuous (infDist · s) :=
(lipschitz_infDist_pt s).uniformContinuous
#align metric.uniform_continuous_inf_dist_pt Metric.uniformContinuous_infDist_pt
/-- The minimal distance to a set is continuous in point -/
@[continuity]
theorem continuous_infDist_pt : Continuous (infDist · s) :=
(uniformContinuous_infDist_pt s).continuous
#align metric.continuous_inf_dist_pt Metric.continuous_infDist_pt
variable {s}
/-- The minimal distances to a set and its closure coincide. -/
theorem infDist_closure : infDist x (closure s) = infDist x s := by
simp [infDist, infEdist_closure]
#align metric.inf_dist_eq_closure Metric.infDist_closure
/-- If a point belongs to the closure of `s`, then its infimum distance to `s` equals zero.
The converse is true provided that `s` is nonempty, see `Metric.mem_closure_iff_infDist_zero`. -/
theorem infDist_zero_of_mem_closure (hx : x ∈ closure s) : infDist x s = 0 := by
rw [← infDist_closure]
exact infDist_zero_of_mem hx
#align metric.inf_dist_zero_of_mem_closure Metric.infDist_zero_of_mem_closure
/-- A point belongs to the closure of `s` iff its infimum distance to this set vanishes. -/
theorem mem_closure_iff_infDist_zero (h : s.Nonempty) : x ∈ closure s ↔ infDist x s = 0 := by
simp [mem_closure_iff_infEdist_zero, infDist, ENNReal.toReal_eq_zero_iff, infEdist_ne_top h]
#align metric.mem_closure_iff_inf_dist_zero Metric.mem_closure_iff_infDist_zero
/-- Given a closed set `s`, a point belongs to `s` iff its infimum distance to this set vanishes -/
theorem _root_.IsClosed.mem_iff_infDist_zero (h : IsClosed s) (hs : s.Nonempty) :
x ∈ s ↔ infDist x s = 0 := by rw [← mem_closure_iff_infDist_zero hs, h.closure_eq]
#align is_closed.mem_iff_inf_dist_zero IsClosed.mem_iff_infDist_zero
/-- Given a closed set `s`, a point belongs to `s` iff its infimum distance to this set vanishes. -/
theorem _root_.IsClosed.not_mem_iff_infDist_pos (h : IsClosed s) (hs : s.Nonempty) :
x ∉ s ↔ 0 < infDist x s := by
simp [h.mem_iff_infDist_zero hs, infDist_nonneg.gt_iff_ne]
#align is_closed.not_mem_iff_inf_dist_pos IsClosed.not_mem_iff_infDist_pos
-- Porting note (#10756): new lemma
theorem continuousAt_inv_infDist_pt (h : x ∉ closure s) :
ContinuousAt (fun x ↦ (infDist x s)⁻¹) x := by
rcases s.eq_empty_or_nonempty with (rfl | hs)
· simp only [infDist_empty, continuousAt_const]
· refine (continuous_infDist_pt s).continuousAt.inv₀ ?_
rwa [Ne, ← mem_closure_iff_infDist_zero hs]
/-- The infimum distance is invariant under isometries. -/
theorem infDist_image (hΦ : Isometry Φ) : infDist (Φ x) (Φ '' t) = infDist x t := by
simp [infDist, infEdist_image hΦ]
#align metric.inf_dist_image Metric.infDist_image
theorem infDist_inter_closedBall_of_mem (h : y ∈ s) :
infDist x (s ∩ closedBall x (dist y x)) = infDist x s := by
replace h : y ∈ s ∩ closedBall x (dist y x) := ⟨h, mem_closedBall.2 le_rfl⟩
refine le_antisymm ?_ (infDist_le_infDist_of_subset inter_subset_left ⟨y, h⟩)
refine not_lt.1 fun hlt => ?_
rcases (infDist_lt_iff ⟨y, h.1⟩).mp hlt with ⟨z, hzs, hz⟩
rcases le_or_lt (dist z x) (dist y x) with hle | hlt
· exact hz.not_le (infDist_le_dist_of_mem ⟨hzs, hle⟩)
· rw [dist_comm z, dist_comm y] at hlt
exact (hlt.trans hz).not_le (infDist_le_dist_of_mem h)
#align metric.inf_dist_inter_closed_ball_of_mem Metric.infDist_inter_closedBall_of_mem
theorem _root_.IsCompact.exists_infDist_eq_dist (h : IsCompact s) (hne : s.Nonempty) (x : α) :
∃ y ∈ s, infDist x s = dist x y :=
let ⟨y, hys, hy⟩ := h.exists_infEdist_eq_edist hne x
⟨y, hys, by rw [infDist, dist_edist, hy]⟩
#align is_compact.exists_inf_dist_eq_dist IsCompact.exists_infDist_eq_dist
theorem _root_.IsClosed.exists_infDist_eq_dist [ProperSpace α] (h : IsClosed s) (hne : s.Nonempty)
(x : α) : ∃ y ∈ s, infDist x s = dist x y := by
rcases hne with ⟨z, hz⟩
rw [← infDist_inter_closedBall_of_mem hz]
set t := s ∩ closedBall x (dist z x)
have htc : IsCompact t := (isCompact_closedBall x (dist z x)).inter_left h
have htne : t.Nonempty := ⟨z, hz, mem_closedBall.2 le_rfl⟩
obtain ⟨y, ⟨hys, -⟩, hyd⟩ : ∃ y ∈ t, infDist x t = dist x y := htc.exists_infDist_eq_dist htne x
exact ⟨y, hys, hyd⟩
#align is_closed.exists_inf_dist_eq_dist IsClosed.exists_infDist_eq_dist
theorem exists_mem_closure_infDist_eq_dist [ProperSpace α] (hne : s.Nonempty) (x : α) :
∃ y ∈ closure s, infDist x s = dist x y := by
simpa only [infDist_closure] using isClosed_closure.exists_infDist_eq_dist hne.closure x
#align metric.exists_mem_closure_inf_dist_eq_dist Metric.exists_mem_closure_infDist_eq_dist
/-! ### Distance of a point to a set as a function into `ℝ≥0`. -/
/-- The minimal distance of a point to a set as a `ℝ≥0` -/
def infNndist (x : α) (s : Set α) : ℝ≥0 :=
ENNReal.toNNReal (infEdist x s)
#align metric.inf_nndist Metric.infNndist
@[simp]
theorem coe_infNndist : (infNndist x s : ℝ) = infDist x s :=
rfl
#align metric.coe_inf_nndist Metric.coe_infNndist
/-- The minimal distance to a set (as `ℝ≥0`) is Lipschitz in point with constant 1 -/
theorem lipschitz_infNndist_pt (s : Set α) : LipschitzWith 1 fun x => infNndist x s :=
LipschitzWith.of_le_add fun _ _ => infDist_le_infDist_add_dist
#align metric.lipschitz_inf_nndist_pt Metric.lipschitz_infNndist_pt
/-- The minimal distance to a set (as `ℝ≥0`) is uniformly continuous in point -/
theorem uniformContinuous_infNndist_pt (s : Set α) : UniformContinuous fun x => infNndist x s :=
(lipschitz_infNndist_pt s).uniformContinuous
#align metric.uniform_continuous_inf_nndist_pt Metric.uniformContinuous_infNndist_pt
/-- The minimal distance to a set (as `ℝ≥0`) is continuous in point -/
theorem continuous_infNndist_pt (s : Set α) : Continuous fun x => infNndist x s :=
(uniformContinuous_infNndist_pt s).continuous
#align metric.continuous_inf_nndist_pt Metric.continuous_infNndist_pt
/-! ### The Hausdorff distance as a function into `ℝ`. -/
/-- The Hausdorff distance between two sets is the smallest nonnegative `r` such that each set is
included in the `r`-neighborhood of the other. If there is no such `r`, it is defined to
be `0`, arbitrarily. -/
def hausdorffDist (s t : Set α) : ℝ :=
ENNReal.toReal (hausdorffEdist s t)
#align metric.Hausdorff_dist Metric.hausdorffDist
/-- The Hausdorff distance is nonnegative. -/
theorem hausdorffDist_nonneg : 0 ≤ hausdorffDist s t := by simp [hausdorffDist]
#align metric.Hausdorff_dist_nonneg Metric.hausdorffDist_nonneg
/-- If two sets are nonempty and bounded in a metric space, they are at finite Hausdorff
edistance. -/
theorem hausdorffEdist_ne_top_of_nonempty_of_bounded (hs : s.Nonempty) (ht : t.Nonempty)
(bs : IsBounded s) (bt : IsBounded t) : hausdorffEdist s t ≠ ⊤ := by
rcases hs with ⟨cs, hcs⟩
rcases ht with ⟨ct, hct⟩
rcases bs.subset_closedBall ct with ⟨rs, hrs⟩
rcases bt.subset_closedBall cs with ⟨rt, hrt⟩
have : hausdorffEdist s t ≤ ENNReal.ofReal (max rs rt) := by
apply hausdorffEdist_le_of_mem_edist
· intro x xs
exists ct, hct
have : dist x ct ≤ max rs rt := le_trans (hrs xs) (le_max_left _ _)
rwa [edist_dist, ENNReal.ofReal_le_ofReal_iff]
exact le_trans dist_nonneg this
· intro x xt
exists cs, hcs
have : dist x cs ≤ max rs rt := le_trans (hrt xt) (le_max_right _ _)
rwa [edist_dist, ENNReal.ofReal_le_ofReal_iff]
exact le_trans dist_nonneg this
exact ne_top_of_le_ne_top ENNReal.ofReal_ne_top this
#align metric.Hausdorff_edist_ne_top_of_nonempty_of_bounded Metric.hausdorffEdist_ne_top_of_nonempty_of_bounded
/-- The Hausdorff distance between a set and itself is zero. -/
@[simp]
theorem hausdorffDist_self_zero : hausdorffDist s s = 0 := by simp [hausdorffDist]
#align metric.Hausdorff_dist_self_zero Metric.hausdorffDist_self_zero
/-- The Hausdorff distances from `s` to `t` and from `t` to `s` coincide. -/
theorem hausdorffDist_comm : hausdorffDist s t = hausdorffDist t s := by
simp [hausdorffDist, hausdorffEdist_comm]
#align metric.Hausdorff_dist_comm Metric.hausdorffDist_comm
/-- The Hausdorff distance to the empty set vanishes (if you want to have the more reasonable
value `∞` instead, use `EMetric.hausdorffEdist`, which takes values in `ℝ≥0∞`). -/
@[simp]
theorem hausdorffDist_empty : hausdorffDist s ∅ = 0 := by
rcases s.eq_empty_or_nonempty with h | h
· simp [h]
· simp [hausdorffDist, hausdorffEdist_empty h]
#align metric.Hausdorff_dist_empty Metric.hausdorffDist_empty
/-- The Hausdorff distance to the empty set vanishes (if you want to have the more reasonable
value `∞` instead, use `EMetric.hausdorffEdist`, which takes values in `ℝ≥0∞`). -/
@[simp]
theorem hausdorffDist_empty' : hausdorffDist ∅ s = 0 := by simp [hausdorffDist_comm]
#align metric.Hausdorff_dist_empty' Metric.hausdorffDist_empty'
/-- Bounding the Hausdorff distance by bounding the distance of any point
in each set to the other set -/
theorem hausdorffDist_le_of_infDist {r : ℝ} (hr : 0 ≤ r) (H1 : ∀ x ∈ s, infDist x t ≤ r)
(H2 : ∀ x ∈ t, infDist x s ≤ r) : hausdorffDist s t ≤ r := by
by_cases h1 : hausdorffEdist s t = ⊤
· rwa [hausdorffDist, h1, ENNReal.top_toReal]
rcases s.eq_empty_or_nonempty with hs | hs
· rwa [hs, hausdorffDist_empty']
rcases t.eq_empty_or_nonempty with ht | ht
· rwa [ht, hausdorffDist_empty]
have : hausdorffEdist s t ≤ ENNReal.ofReal r := by
apply hausdorffEdist_le_of_infEdist _ _
· intro x hx
have I := H1 x hx
rwa [infDist, ← ENNReal.toReal_ofReal hr,
ENNReal.toReal_le_toReal (infEdist_ne_top ht) ENNReal.ofReal_ne_top] at I
· intro x hx
have I := H2 x hx
rwa [infDist, ← ENNReal.toReal_ofReal hr,
ENNReal.toReal_le_toReal (infEdist_ne_top hs) ENNReal.ofReal_ne_top] at I
rwa [hausdorffDist, ← ENNReal.toReal_ofReal hr,
ENNReal.toReal_le_toReal h1 ENNReal.ofReal_ne_top]
#align metric.Hausdorff_dist_le_of_inf_dist Metric.hausdorffDist_le_of_infDist
/-- Bounding the Hausdorff distance by exhibiting, for any point in each set,
another point in the other set at controlled distance -/
theorem hausdorffDist_le_of_mem_dist {r : ℝ} (hr : 0 ≤ r) (H1 : ∀ x ∈ s, ∃ y ∈ t, dist x y ≤ r)
(H2 : ∀ x ∈ t, ∃ y ∈ s, dist x y ≤ r) : hausdorffDist s t ≤ r := by
apply hausdorffDist_le_of_infDist hr
· intro x xs
rcases H1 x xs with ⟨y, yt, hy⟩
exact le_trans (infDist_le_dist_of_mem yt) hy
· intro x xt
rcases H2 x xt with ⟨y, ys, hy⟩
exact le_trans (infDist_le_dist_of_mem ys) hy
#align metric.Hausdorff_dist_le_of_mem_dist Metric.hausdorffDist_le_of_mem_dist
/-- The Hausdorff distance is controlled by the diameter of the union. -/
theorem hausdorffDist_le_diam (hs : s.Nonempty) (bs : IsBounded s) (ht : t.Nonempty)
(bt : IsBounded t) : hausdorffDist s t ≤ diam (s ∪ t) := by
rcases hs with ⟨x, xs⟩
rcases ht with ⟨y, yt⟩
refine hausdorffDist_le_of_mem_dist diam_nonneg ?_ ?_
· exact fun z hz => ⟨y, yt, dist_le_diam_of_mem (bs.union bt) (subset_union_left hz)
(subset_union_right yt)⟩
· exact fun z hz => ⟨x, xs, dist_le_diam_of_mem (bs.union bt) (subset_union_right hz)
(subset_union_left xs)⟩
#align metric.Hausdorff_dist_le_diam Metric.hausdorffDist_le_diam
/-- The distance to a set is controlled by the Hausdorff distance. -/
theorem infDist_le_hausdorffDist_of_mem (hx : x ∈ s) (fin : hausdorffEdist s t ≠ ⊤) :
infDist x t ≤ hausdorffDist s t :=
toReal_mono fin (infEdist_le_hausdorffEdist_of_mem hx)
#align metric.inf_dist_le_Hausdorff_dist_of_mem Metric.infDist_le_hausdorffDist_of_mem
/-- If the Hausdorff distance is `< r`, any point in one of the sets is at distance
`< r` of a point in the other set. -/
theorem exists_dist_lt_of_hausdorffDist_lt {r : ℝ} (h : x ∈ s) (H : hausdorffDist s t < r)
(fin : hausdorffEdist s t ≠ ⊤) : ∃ y ∈ t, dist x y < r := by
have r0 : 0 < r := lt_of_le_of_lt hausdorffDist_nonneg H
have : hausdorffEdist s t < ENNReal.ofReal r := by
rwa [hausdorffDist, ← ENNReal.toReal_ofReal (le_of_lt r0),
ENNReal.toReal_lt_toReal fin ENNReal.ofReal_ne_top] at H
rcases exists_edist_lt_of_hausdorffEdist_lt h this with ⟨y, hy, yr⟩
rw [edist_dist, ENNReal.ofReal_lt_ofReal_iff r0] at yr
exact ⟨y, hy, yr⟩
#align metric.exists_dist_lt_of_Hausdorff_dist_lt Metric.exists_dist_lt_of_hausdorffDist_lt
/-- If the Hausdorff distance is `< r`, any point in one of the sets is at distance
`< r` of a point in the other set. -/
theorem exists_dist_lt_of_hausdorffDist_lt' {r : ℝ} (h : y ∈ t) (H : hausdorffDist s t < r)
(fin : hausdorffEdist s t ≠ ⊤) : ∃ x ∈ s, dist x y < r := by
rw [hausdorffDist_comm] at H
rw [hausdorffEdist_comm] at fin
simpa [dist_comm] using exists_dist_lt_of_hausdorffDist_lt h H fin
#align metric.exists_dist_lt_of_Hausdorff_dist_lt' Metric.exists_dist_lt_of_hausdorffDist_lt'
/-- The infimum distance to `s` and `t` are the same, up to the Hausdorff distance
between `s` and `t` -/
theorem infDist_le_infDist_add_hausdorffDist (fin : hausdorffEdist s t ≠ ⊤) :
infDist x t ≤ infDist x s + hausdorffDist s t := by
refine toReal_le_add' infEdist_le_infEdist_add_hausdorffEdist (fun h ↦ ?_) (flip absurd fin)
rw [infEdist_eq_top_iff, ← not_nonempty_iff_eq_empty] at h ⊢
rw [hausdorffEdist_comm] at fin
exact mt (nonempty_of_hausdorffEdist_ne_top · fin) h
#align metric.inf_dist_le_inf_dist_add_Hausdorff_dist Metric.infDist_le_infDist_add_hausdorffDist
/-- The Hausdorff distance is invariant under isometries. -/
theorem hausdorffDist_image (h : Isometry Φ) :
hausdorffDist (Φ '' s) (Φ '' t) = hausdorffDist s t := by
simp [hausdorffDist, hausdorffEdist_image h]
#align metric.Hausdorff_dist_image Metric.hausdorffDist_image
/-- The Hausdorff distance satisfies the triangle inequality. -/
| Mathlib/Topology/MetricSpace/HausdorffDistance.lean | 854 | 858 | theorem hausdorffDist_triangle (fin : hausdorffEdist s t ≠ ⊤) :
hausdorffDist s u ≤ hausdorffDist s t + hausdorffDist t u := by |
refine toReal_le_add' hausdorffEdist_triangle (flip absurd fin) (not_imp_not.1 fun h ↦ ?_)
rw [hausdorffEdist_comm] at fin
exact ne_top_of_le_ne_top (add_ne_top.2 ⟨fin, h⟩) hausdorffEdist_triangle
|
/-
Copyright (c) 2019 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Polynomial.Expand
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.LinearAlgebra.Matrix.Charpoly.LinearMap
import Mathlib.RingTheory.Adjoin.FG
import Mathlib.RingTheory.FiniteType
import Mathlib.RingTheory.Polynomial.ScaleRoots
import Mathlib.RingTheory.Polynomial.Tower
import Mathlib.RingTheory.TensorProduct.Basic
#align_import ring_theory.integral_closure from "leanprover-community/mathlib"@"641b6a82006416ec431b2987b354af9311fed4f2"
/-!
# Integral closure of a subring.
If A is an R-algebra then `a : A` is integral over R if it is a root of a monic polynomial
with coefficients in R. Enough theory is developed to prove that integral elements
form a sub-R-algebra of A.
## Main definitions
Let `R` be a `CommRing` and let `A` be an R-algebra.
* `RingHom.IsIntegralElem (f : R →+* A) (x : A)` : `x` is integral with respect to the map `f`,
* `IsIntegral (x : A)` : `x` is integral over `R`, i.e., is a root of a monic polynomial with
coefficients in `R`.
* `integralClosure R A` : the integral closure of `R` in `A`, regarded as a sub-`R`-algebra of `A`.
-/
open scoped Classical
open Polynomial Submodule
section Ring
variable {R S A : Type*}
variable [CommRing R] [Ring A] [Ring S] (f : R →+* S)
/-- An element `x` of `A` is said to be integral over `R` with respect to `f`
if it is a root of a monic polynomial `p : R[X]` evaluated under `f` -/
def RingHom.IsIntegralElem (f : R →+* A) (x : A) :=
∃ p : R[X], Monic p ∧ eval₂ f x p = 0
#align ring_hom.is_integral_elem RingHom.IsIntegralElem
/-- A ring homomorphism `f : R →+* A` is said to be integral
if every element `A` is integral with respect to the map `f` -/
def RingHom.IsIntegral (f : R →+* A) :=
∀ x : A, f.IsIntegralElem x
#align ring_hom.is_integral RingHom.IsIntegral
variable [Algebra R A] (R)
/-- An element `x` of an algebra `A` over a commutative ring `R` is said to be *integral*,
if it is a root of some monic polynomial `p : R[X]`.
Equivalently, the element is integral over `R` with respect to the induced `algebraMap` -/
def IsIntegral (x : A) : Prop :=
(algebraMap R A).IsIntegralElem x
#align is_integral IsIntegral
variable (A)
/-- An algebra is integral if every element of the extension is integral over the base ring -/
protected class Algebra.IsIntegral : Prop :=
isIntegral : ∀ x : A, IsIntegral R x
#align algebra.is_integral Algebra.IsIntegral
variable {R A}
lemma Algebra.isIntegral_def : Algebra.IsIntegral R A ↔ ∀ x : A, IsIntegral R x :=
⟨fun ⟨h⟩ ↦ h, fun h ↦ ⟨h⟩⟩
theorem RingHom.isIntegralElem_map {x : R} : f.IsIntegralElem (f x) :=
⟨X - C x, monic_X_sub_C _, by simp⟩
#align ring_hom.is_integral_map RingHom.isIntegralElem_map
theorem isIntegral_algebraMap {x : R} : IsIntegral R (algebraMap R A x) :=
(algebraMap R A).isIntegralElem_map
#align is_integral_algebra_map isIntegral_algebraMap
end Ring
section
variable {R A B S : Type*}
variable [CommRing R] [CommRing A] [Ring B] [CommRing S]
variable [Algebra R A] [Algebra R B] (f : R →+* S)
theorem IsIntegral.map {B C F : Type*} [Ring B] [Ring C] [Algebra R B] [Algebra A B] [Algebra R C]
[IsScalarTower R A B] [Algebra A C] [IsScalarTower R A C] {b : B}
[FunLike F B C] [AlgHomClass F A B C] (f : F)
(hb : IsIntegral R b) : IsIntegral R (f b) := by
obtain ⟨P, hP⟩ := hb
refine ⟨P, hP.1, ?_⟩
rw [← aeval_def, ← aeval_map_algebraMap A,
aeval_algHom_apply, aeval_map_algebraMap, aeval_def, hP.2, _root_.map_zero]
#align map_is_integral IsIntegral.map
theorem IsIntegral.map_of_comp_eq {R S T U : Type*} [CommRing R] [Ring S]
[CommRing T] [Ring U] [Algebra R S] [Algebra T U] (φ : R →+* T) (ψ : S →+* U)
(h : (algebraMap T U).comp φ = ψ.comp (algebraMap R S)) {a : S} (ha : IsIntegral R a) :
IsIntegral T (ψ a) :=
let ⟨p, hp⟩ := ha
⟨p.map φ, hp.1.map _, by
rw [← eval_map, map_map, h, ← map_map, eval_map, eval₂_at_apply, eval_map, hp.2, ψ.map_zero]⟩
#align is_integral_map_of_comp_eq_of_is_integral IsIntegral.map_of_comp_eq
section
variable {A B : Type*} [Ring A] [Ring B] [Algebra R A] [Algebra R B]
variable (f : A →ₐ[R] B) (hf : Function.Injective f)
theorem isIntegral_algHom_iff {x : A} : IsIntegral R (f x) ↔ IsIntegral R x := by
refine ⟨fun ⟨p, hp, hx⟩ ↦ ⟨p, hp, ?_⟩, IsIntegral.map f⟩
rwa [← f.comp_algebraMap, ← AlgHom.coe_toRingHom, ← hom_eval₂, AlgHom.coe_toRingHom,
map_eq_zero_iff f hf] at hx
#align is_integral_alg_hom_iff isIntegral_algHom_iff
theorem Algebra.IsIntegral.of_injective [Algebra.IsIntegral R B] : Algebra.IsIntegral R A :=
⟨fun _ ↦ (isIntegral_algHom_iff f hf).mp (isIntegral _)⟩
end
@[simp]
theorem isIntegral_algEquiv {A B : Type*} [Ring A] [Ring B] [Algebra R A] [Algebra R B]
(f : A ≃ₐ[R] B) {x : A} : IsIntegral R (f x) ↔ IsIntegral R x :=
⟨fun h ↦ by simpa using h.map f.symm, IsIntegral.map f⟩
#align is_integral_alg_equiv isIntegral_algEquiv
/-- If `R → A → B` is an algebra tower,
then if the entire tower is an integral extension so is `A → B`. -/
theorem IsIntegral.tower_top [Algebra A B] [IsScalarTower R A B] {x : B}
(hx : IsIntegral R x) : IsIntegral A x :=
let ⟨p, hp, hpx⟩ := hx
⟨p.map <| algebraMap R A, hp.map _, by rw [← aeval_def, aeval_map_algebraMap, aeval_def, hpx]⟩
#align is_integral_of_is_scalar_tower IsIntegral.tower_top
#align is_integral_tower_top_of_is_integral IsIntegral.tower_top
theorem map_isIntegral_int {B C F : Type*} [Ring B] [Ring C] {b : B}
[FunLike F B C] [RingHomClass F B C] (f : F)
(hb : IsIntegral ℤ b) : IsIntegral ℤ (f b) :=
hb.map (f : B →+* C).toIntAlgHom
#align map_is_integral_int map_isIntegral_int
theorem IsIntegral.of_subring {x : B} (T : Subring R) (hx : IsIntegral T x) : IsIntegral R x :=
hx.tower_top
#align is_integral_of_subring IsIntegral.of_subring
protected theorem IsIntegral.algebraMap [Algebra A B] [IsScalarTower R A B] {x : A}
(h : IsIntegral R x) : IsIntegral R (algebraMap A B x) := by
rcases h with ⟨f, hf, hx⟩
use f, hf
rw [IsScalarTower.algebraMap_eq R A B, ← hom_eval₂, hx, RingHom.map_zero]
#align is_integral.algebra_map IsIntegral.algebraMap
theorem isIntegral_algebraMap_iff [Algebra A B] [IsScalarTower R A B] {x : A}
(hAB : Function.Injective (algebraMap A B)) :
IsIntegral R (algebraMap A B x) ↔ IsIntegral R x :=
isIntegral_algHom_iff (IsScalarTower.toAlgHom R A B) hAB
#align is_integral_algebra_map_iff isIntegral_algebraMap_iff
theorem isIntegral_iff_isIntegral_closure_finite {r : B} :
IsIntegral R r ↔ ∃ s : Set R, s.Finite ∧ IsIntegral (Subring.closure s) r := by
constructor <;> intro hr
· rcases hr with ⟨p, hmp, hpr⟩
refine ⟨_, Finset.finite_toSet _, p.restriction, monic_restriction.2 hmp, ?_⟩
rw [← aeval_def, ← aeval_map_algebraMap R r p.restriction, map_restriction, aeval_def, hpr]
rcases hr with ⟨s, _, hsr⟩
exact hsr.of_subring _
#align is_integral_iff_is_integral_closure_finite isIntegral_iff_isIntegral_closure_finite
theorem Submodule.span_range_natDegree_eq_adjoin {R A} [CommRing R] [Semiring A] [Algebra R A]
{x : A} {f : R[X]} (hf : f.Monic) (hfx : aeval x f = 0) :
span R (Finset.image (x ^ ·) (Finset.range (natDegree f))) =
Subalgebra.toSubmodule (Algebra.adjoin R {x}) := by
nontriviality A
have hf1 : f ≠ 1 := by rintro rfl; simp [one_ne_zero' A] at hfx
refine (span_le.mpr fun s hs ↦ ?_).antisymm fun r hr ↦ ?_
· rcases Finset.mem_image.1 hs with ⟨k, -, rfl⟩
exact (Algebra.adjoin R {x}).pow_mem (Algebra.subset_adjoin rfl) k
rw [Subalgebra.mem_toSubmodule, Algebra.adjoin_singleton_eq_range_aeval] at hr
rcases (aeval x).mem_range.mp hr with ⟨p, rfl⟩
rw [← modByMonic_add_div p hf, map_add, map_mul, hfx,
zero_mul, add_zero, ← sum_C_mul_X_pow_eq (p %ₘ f), aeval_def, eval₂_sum, sum_def]
refine sum_mem fun k hkq ↦ ?_
rw [C_mul_X_pow_eq_monomial, eval₂_monomial, ← Algebra.smul_def]
exact smul_mem _ _ (subset_span <| Finset.mem_image_of_mem _ <| Finset.mem_range.mpr <|
(le_natDegree_of_mem_supp _ hkq).trans_lt <| natDegree_modByMonic_lt p hf hf1)
| Mathlib/RingTheory/IntegralClosure.lean | 194 | 198 | theorem IsIntegral.fg_adjoin_singleton {x : B} (hx : IsIntegral R x) :
(Algebra.adjoin R {x}).toSubmodule.FG := by |
rcases hx with ⟨f, hfm, hfx⟩
use (Finset.range <| f.natDegree).image (x ^ ·)
exact span_range_natDegree_eq_adjoin hfm (by rwa [aeval_def])
|
/-
Copyright (c) 2018 Reid Barton. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Reid Barton
-/
import Mathlib.Topology.ContinuousFunction.Basic
#align_import topology.compact_open from "leanprover-community/mathlib"@"4c19a16e4b705bf135cf9a80ac18fcc99c438514"
/-!
# The compact-open topology
In this file, we define the compact-open topology on the set of continuous maps between two
topological spaces.
## Main definitions
* `ContinuousMap.compactOpen` is the compact-open topology on `C(X, Y)`.
It is declared as an instance.
* `ContinuousMap.coev` is the coevaluation map `Y → C(X, Y × X)`. It is always continuous.
* `ContinuousMap.curry` is the currying map `C(X × Y, Z) → C(X, C(Y, Z))`. This map always exists
and it is continuous as long as `X × Y` is locally compact.
* `ContinuousMap.uncurry` is the uncurrying map `C(X, C(Y, Z)) → C(X × Y, Z)`. For this map to
exist, we need `Y` to be locally compact. If `X` is also locally compact, then this map is
continuous.
* `Homeomorph.curry` combines the currying and uncurrying operations into a homeomorphism
`C(X × Y, Z) ≃ₜ C(X, C(Y, Z))`. This homeomorphism exists if `X` and `Y` are locally compact.
## Tags
compact-open, curry, function space
-/
open Set Filter TopologicalSpace
open scoped Topology
namespace ContinuousMap
section CompactOpen
variable {α X Y Z T : Type*}
variable [TopologicalSpace X] [TopologicalSpace Y] [TopologicalSpace Z] [TopologicalSpace T]
variable {K : Set X} {U : Set Y}
#noalign continuous_map.compact_open.gen
#noalign continuous_map.gen_empty
#noalign continuous_map.gen_univ
#noalign continuous_map.gen_inter
#noalign continuous_map.gen_union
#noalign continuous_map.gen_empty_right
/-- The compact-open topology on the space of continuous maps `C(X, Y)`. -/
instance compactOpen : TopologicalSpace C(X, Y) :=
.generateFrom <| image2 (fun K U ↦ {f | MapsTo f K U}) {K | IsCompact K} {U | IsOpen U}
#align continuous_map.compact_open ContinuousMap.compactOpen
/-- Definition of `ContinuousMap.compactOpen`. -/
theorem compactOpen_eq : @compactOpen X Y _ _ =
.generateFrom (image2 (fun K U ↦ {f | MapsTo f K U}) {K | IsCompact K} {t | IsOpen t}) :=
rfl
theorem isOpen_setOf_mapsTo (hK : IsCompact K) (hU : IsOpen U) :
IsOpen {f : C(X, Y) | MapsTo f K U} :=
isOpen_generateFrom_of_mem <| mem_image2_of_mem hK hU
#align continuous_map.is_open_gen ContinuousMap.isOpen_setOf_mapsTo
lemma eventually_mapsTo {f : C(X, Y)} (hK : IsCompact K) (hU : IsOpen U) (h : MapsTo f K U) :
∀ᶠ g : C(X, Y) in 𝓝 f, MapsTo g K U :=
(isOpen_setOf_mapsTo hK hU).mem_nhds h
lemma nhds_compactOpen (f : C(X, Y)) :
𝓝 f = ⨅ (K : Set X) (_ : IsCompact K) (U : Set Y) (_ : IsOpen U) (_ : MapsTo f K U),
𝓟 {g : C(X, Y) | MapsTo g K U} := by
simp_rw [compactOpen_eq, nhds_generateFrom, mem_setOf_eq, @and_comm (f ∈ _), iInf_and,
← image_prod, iInf_image, biInf_prod, mem_setOf_eq]
lemma tendsto_nhds_compactOpen {l : Filter α} {f : α → C(Y, Z)} {g : C(Y, Z)} :
Tendsto f l (𝓝 g) ↔
∀ K, IsCompact K → ∀ U, IsOpen U → MapsTo g K U → ∀ᶠ a in l, MapsTo (f a) K U := by
simp [nhds_compactOpen]
lemma continuous_compactOpen {f : X → C(Y, Z)} :
Continuous f ↔ ∀ K, IsCompact K → ∀ U, IsOpen U → IsOpen {x | MapsTo (f x) K U} :=
continuous_generateFrom_iff.trans forall_image2_iff
section Functorial
/-- `C(X, ·)` is a functor. -/
theorem continuous_comp (g : C(Y, Z)) : Continuous (ContinuousMap.comp g : C(X, Y) → C(X, Z)) :=
continuous_compactOpen.2 fun _K hK _U hU ↦ isOpen_setOf_mapsTo hK (hU.preimage g.2)
#align continuous_map.continuous_comp ContinuousMap.continuous_comp
/-- If `g : C(Y, Z)` is a topology inducing map,
then the composition `ContinuousMap.comp g : C(X, Y) → C(X, Z)` is a topology inducing map too. -/
theorem inducing_comp (g : C(Y, Z)) (hg : Inducing g) : Inducing (g.comp : C(X, Y) → C(X, Z)) where
induced := by
simp only [compactOpen_eq, induced_generateFrom_eq, image_image2, hg.setOf_isOpen,
image2_image_right, MapsTo, mem_preimage, preimage_setOf_eq, comp_apply]
/-- If `g : C(Y, Z)` is a topological embedding,
then the composition `ContinuousMap.comp g : C(X, Y) → C(X, Z)` is an embedding too. -/
theorem embedding_comp (g : C(Y, Z)) (hg : Embedding g) : Embedding (g.comp : C(X, Y) → C(X, Z)) :=
⟨inducing_comp g hg.1, fun _ _ ↦ (cancel_left hg.2).1⟩
/-- `C(·, Z)` is a functor. -/
theorem continuous_comp_left (f : C(X, Y)) : Continuous (fun g => g.comp f : C(Y, Z) → C(X, Z)) :=
continuous_compactOpen.2 fun K hK U hU ↦ by
simpa only [mapsTo_image_iff] using isOpen_setOf_mapsTo (hK.image f.2) hU
#align continuous_map.continuous_comp_left ContinuousMap.continuous_comp_left
/-- Any pair of homeomorphisms `X ≃ₜ Z` and `Y ≃ₜ T` gives rise to a homeomorphism
`C(X, Y) ≃ₜ C(Z, T)`. -/
protected def _root_.Homeomorph.arrowCongr (φ : X ≃ₜ Z) (ψ : Y ≃ₜ T) :
C(X, Y) ≃ₜ C(Z, T) where
toFun f := .comp ψ <| f.comp φ.symm
invFun f := .comp ψ.symm <| f.comp φ
left_inv f := ext fun _ ↦ ψ.left_inv (f _) |>.trans <| congrArg f <| φ.left_inv _
right_inv f := ext fun _ ↦ ψ.right_inv (f _) |>.trans <| congrArg f <| φ.right_inv _
continuous_toFun := continuous_comp _ |>.comp <| continuous_comp_left _
continuous_invFun := continuous_comp _ |>.comp <| continuous_comp_left _
variable [LocallyCompactPair Y Z]
/-- Composition is a continuous map from `C(X, Y) × C(Y, Z)` to `C(X, Z)`,
provided that `Y` is locally compact.
This is Prop. 9 of Chap. X, §3, №. 4 of Bourbaki's *Topologie Générale*. -/
theorem continuous_comp' : Continuous fun x : C(X, Y) × C(Y, Z) => x.2.comp x.1 := by
simp_rw [continuous_iff_continuousAt, ContinuousAt, tendsto_nhds_compactOpen]
intro ⟨f, g⟩ K hK U hU (hKU : MapsTo (g ∘ f) K U)
obtain ⟨L, hKL, hLc, hLU⟩ : ∃ L ∈ 𝓝ˢ (f '' K), IsCompact L ∧ MapsTo g L U :=
exists_mem_nhdsSet_isCompact_mapsTo g.continuous (hK.image f.continuous) hU
(mapsTo_image_iff.2 hKU)
rw [← subset_interior_iff_mem_nhdsSet, ← mapsTo'] at hKL
exact ((eventually_mapsTo hK isOpen_interior hKL).prod_nhds
(eventually_mapsTo hLc hU hLU)).mono fun ⟨f', g'⟩ ⟨hf', hg'⟩ ↦
hg'.comp <| hf'.mono_right interior_subset
#align continuous_map.continuous_comp' ContinuousMap.continuous_comp'
lemma _root_.Filter.Tendsto.compCM {α : Type*} {l : Filter α} {g : α → C(Y, Z)} {g₀ : C(Y, Z)}
{f : α → C(X, Y)} {f₀ : C(X, Y)} (hg : Tendsto g l (𝓝 g₀)) (hf : Tendsto f l (𝓝 f₀)) :
Tendsto (fun a ↦ (g a).comp (f a)) l (𝓝 (g₀.comp f₀)) :=
(continuous_comp'.tendsto (f₀, g₀)).comp (hf.prod_mk_nhds hg)
variable {X' : Type*} [TopologicalSpace X'] {a : X'} {g : X' → C(Y, Z)} {f : X' → C(X, Y)}
{s : Set X'}
nonrec lemma _root_.ContinuousAt.compCM (hg : ContinuousAt g a) (hf : ContinuousAt f a) :
ContinuousAt (fun x ↦ (g x).comp (f x)) a :=
hg.compCM hf
nonrec lemma _root_.ContinuousWithinAt.compCM (hg : ContinuousWithinAt g s a)
(hf : ContinuousWithinAt f s a) : ContinuousWithinAt (fun x ↦ (g x).comp (f x)) s a :=
hg.compCM hf
lemma _root_.ContinuousOn.compCM (hg : ContinuousOn g s) (hf : ContinuousOn f s) :
ContinuousOn (fun x ↦ (g x).comp (f x)) s := fun a ha ↦
(hg a ha).compCM (hf a ha)
lemma _root_.Continuous.compCM (hg : Continuous g) (hf : Continuous f) :
Continuous fun x => (g x).comp (f x) :=
continuous_comp'.comp (hf.prod_mk hg)
@[deprecated _root_.Continuous.compCM (since := "2024-01-30")]
lemma continuous.comp' (hf : Continuous f) (hg : Continuous g) :
Continuous fun x => (g x).comp (f x) :=
hg.compCM hf
#align continuous_map.continuous.comp' ContinuousMap.continuous.comp'
end Functorial
section Ev
/-- The evaluation map `C(X, Y) × X → Y` is continuous
if `X, Y` is a locally compact pair of spaces. -/
@[continuity]
theorem continuous_eval [LocallyCompactPair X Y] : Continuous fun p : C(X, Y) × X => p.1 p.2 := by
simp_rw [continuous_iff_continuousAt, ContinuousAt, (nhds_basis_opens _).tendsto_right_iff]
rintro ⟨f, x⟩ U ⟨hx : f x ∈ U, hU : IsOpen U⟩
rcases exists_mem_nhds_isCompact_mapsTo f.continuous (hU.mem_nhds hx) with ⟨K, hxK, hK, hKU⟩
filter_upwards [prod_mem_nhds (eventually_mapsTo hK hU hKU) hxK] using fun _ h ↦ h.1 h.2
#align continuous_map.continuous_eval' ContinuousMap.continuous_eval
#align continuous_map.continuous_eval ContinuousMap.continuous_eval
@[deprecated] alias continuous_eval' := continuous_eval
/-- Evaluation of a continuous map `f` at a point `x` is continuous in `f`.
Porting note: merged `continuous_eval_const` with `continuous_eval_const'` removing unneeded
assumptions. -/
@[continuity]
theorem continuous_eval_const (a : X) : Continuous fun f : C(X, Y) => f a :=
continuous_def.2 fun U hU ↦ by simpa using isOpen_setOf_mapsTo (isCompact_singleton (x := a)) hU
#align continuous_map.continuous_eval_const' ContinuousMap.continuous_eval_const
#align continuous_map.continuous_eval_const ContinuousMap.continuous_eval_const
/-- Coercion from `C(X, Y)` with compact-open topology to `X → Y` with pointwise convergence
topology is a continuous map.
Porting note: merged `continuous_coe` with `continuous_coe'` removing unneeded assumptions. -/
theorem continuous_coe : Continuous ((⇑) : C(X, Y) → (X → Y)) :=
continuous_pi continuous_eval_const
#align continuous_map.continuous_coe' ContinuousMap.continuous_coe
#align continuous_map.continuous_coe ContinuousMap.continuous_coe
lemma isClosed_setOf_mapsTo {t : Set Y} (ht : IsClosed t) (s : Set X) :
IsClosed {f : C(X, Y) | MapsTo f s t} :=
ht.setOf_mapsTo fun _ _ ↦ continuous_eval_const _
lemma isClopen_setOf_mapsTo (hK : IsCompact K) (hU : IsClopen U) :
IsClopen {f : C(X, Y) | MapsTo f K U} :=
⟨isClosed_setOf_mapsTo hU.isClosed K, isOpen_setOf_mapsTo hK hU.isOpen⟩
@[norm_cast]
lemma specializes_coe {f g : C(X, Y)} : ⇑f ⤳ ⇑g ↔ f ⤳ g := by
refine ⟨fun h ↦ ?_, fun h ↦ h.map continuous_coe⟩
suffices ∀ K, IsCompact K → ∀ U, IsOpen U → MapsTo g K U → MapsTo f K U by
simpa [specializes_iff_pure, nhds_compactOpen]
exact fun K _ U hU hg x hx ↦ (h.map (continuous_apply x)).mem_open hU (hg hx)
@[norm_cast]
lemma inseparable_coe {f g : C(X, Y)} : Inseparable (f : X → Y) g ↔ Inseparable f g := by
simp only [inseparable_iff_specializes_and, specializes_coe]
instance [T0Space Y] : T0Space C(X, Y) :=
t0Space_of_injective_of_continuous DFunLike.coe_injective continuous_coe
instance [R0Space Y] : R0Space C(X, Y) where
specializes_symmetric f g h := by
rw [← specializes_coe] at h ⊢
exact h.symm
instance [T1Space Y] : T1Space C(X, Y) :=
t1Space_of_injective_of_continuous DFunLike.coe_injective continuous_coe
instance [R1Space Y] : R1Space C(X, Y) :=
.of_continuous_specializes_imp continuous_coe fun _ _ ↦ specializes_coe.1
instance [T2Space Y] : T2Space C(X, Y) := inferInstance
instance [RegularSpace Y] : RegularSpace C(X, Y) :=
.of_lift'_closure_le fun f ↦ by
rw [← tendsto_id', tendsto_nhds_compactOpen]
intro K hK U hU hf
rcases (hK.image f.continuous).exists_isOpen_closure_subset (hU.mem_nhdsSet.2 hf.image_subset)
with ⟨V, hVo, hKV, hVU⟩
filter_upwards [mem_lift' (eventually_mapsTo hK hVo (mapsTo'.2 hKV))] with g hg
refine ((isClosed_setOf_mapsTo isClosed_closure K).closure_subset ?_).mono_right hVU
exact closure_mono (fun _ h ↦ h.mono_right subset_closure) hg
instance [T3Space Y] : T3Space C(X, Y) := inferInstance
end Ev
section InfInduced
/-- For any subset `s` of `X`, the restriction of continuous functions to `s` is continuous
as a function from `C(X, Y)` to `C(s, Y)` with their respective compact-open topologies. -/
theorem continuous_restrict (s : Set X) : Continuous fun F : C(X, Y) => F.restrict s :=
continuous_comp_left <| restrict s <| .id X
#align continuous_map.continuous_restrict ContinuousMap.continuous_restrict
theorem compactOpen_le_induced (s : Set X) :
(ContinuousMap.compactOpen : TopologicalSpace C(X, Y)) ≤
.induced (restrict s) ContinuousMap.compactOpen :=
(continuous_restrict s).le_induced
#align continuous_map.compact_open_le_induced ContinuousMap.compactOpen_le_induced
/-- The compact-open topology on `C(X, Y)`
is equal to the infimum of the compact-open topologies on `C(s, Y)` for `s` a compact subset of `X`.
The key point of the proof is that for every compact set `K`,
the universal set `Set.univ : Set K` is a compact set as well. -/
theorem compactOpen_eq_iInf_induced :
(ContinuousMap.compactOpen : TopologicalSpace C(X, Y)) =
⨅ (K : Set X) (_ : IsCompact K), .induced (.restrict K) ContinuousMap.compactOpen := by
refine le_antisymm (le_iInf₂ fun s _ ↦ compactOpen_le_induced s) ?_
refine le_generateFrom <| forall_image2_iff.2 fun K (hK : IsCompact K) U hU ↦ ?_
refine TopologicalSpace.le_def.1 (iInf₂_le K hK) _ ?_
convert isOpen_induced (isOpen_setOf_mapsTo (isCompact_iff_isCompact_univ.1 hK) hU)
simp only [mapsTo_univ_iff, Subtype.forall]
rfl
#align continuous_map.compact_open_eq_Inf_induced ContinuousMap.compactOpen_eq_iInf_induced
@[deprecated] alias compactOpen_eq_sInf_induced := compactOpen_eq_iInf_induced
theorem nhds_compactOpen_eq_iInf_nhds_induced (f : C(X, Y)) :
𝓝 f = ⨅ (s) (hs : IsCompact s), (𝓝 (f.restrict s)).comap (ContinuousMap.restrict s) := by
rw [compactOpen_eq_iInf_induced]
simp only [nhds_iInf, nhds_induced]
#align continuous_map.nhds_compact_open_eq_Inf_nhds_induced ContinuousMap.nhds_compactOpen_eq_iInf_nhds_induced
@[deprecated] alias nhds_compactOpen_eq_sInf_nhds_induced := nhds_compactOpen_eq_iInf_nhds_induced
theorem tendsto_compactOpen_restrict {ι : Type*} {l : Filter ι} {F : ι → C(X, Y)} {f : C(X, Y)}
(hFf : Filter.Tendsto F l (𝓝 f)) (s : Set X) :
Tendsto (fun i => (F i).restrict s) l (𝓝 (f.restrict s)) :=
(continuous_restrict s).continuousAt.tendsto.comp hFf
#align continuous_map.tendsto_compact_open_restrict ContinuousMap.tendsto_compactOpen_restrict
theorem tendsto_compactOpen_iff_forall {ι : Type*} {l : Filter ι} (F : ι → C(X, Y)) (f : C(X, Y)) :
Tendsto F l (𝓝 f) ↔
∀ K, IsCompact K → Tendsto (fun i => (F i).restrict K) l (𝓝 (f.restrict K)) := by
rw [compactOpen_eq_iInf_induced]
simp [nhds_iInf, nhds_induced, Filter.tendsto_comap_iff, Function.comp]
#align continuous_map.tendsto_compact_open_iff_forall ContinuousMap.tendsto_compactOpen_iff_forall
/-- A family `F` of functions in `C(X, Y)` converges in the compact-open topology, if and only if
it converges in the compact-open topology on each compact subset of `X`. -/
theorem exists_tendsto_compactOpen_iff_forall [WeaklyLocallyCompactSpace X] [T2Space Y]
{ι : Type*} {l : Filter ι} [Filter.NeBot l] (F : ι → C(X, Y)) :
(∃ f, Filter.Tendsto F l (𝓝 f)) ↔
∀ s : Set X, IsCompact s → ∃ f, Filter.Tendsto (fun i => (F i).restrict s) l (𝓝 f) := by
constructor
· rintro ⟨f, hf⟩ s _
exact ⟨f.restrict s, tendsto_compactOpen_restrict hf s⟩
· intro h
choose f hf using h
-- By uniqueness of limits in a `T2Space`, since `fun i ↦ F i x` tends to both `f s₁ hs₁ x` and
-- `f s₂ hs₂ x`, we have `f s₁ hs₁ x = f s₂ hs₂ x`
have h :
∀ (s₁) (hs₁ : IsCompact s₁) (s₂) (hs₂ : IsCompact s₂) (x : X) (hxs₁ : x ∈ s₁) (hxs₂ : x ∈ s₂),
f s₁ hs₁ ⟨x, hxs₁⟩ = f s₂ hs₂ ⟨x, hxs₂⟩ := by
rintro s₁ hs₁ s₂ hs₂ x hxs₁ hxs₂
haveI := isCompact_iff_compactSpace.mp hs₁
haveI := isCompact_iff_compactSpace.mp hs₂
have h₁ := (continuous_eval_const (⟨x, hxs₁⟩ : s₁)).continuousAt.tendsto.comp (hf s₁ hs₁)
have h₂ := (continuous_eval_const (⟨x, hxs₂⟩ : s₂)).continuousAt.tendsto.comp (hf s₂ hs₂)
exact tendsto_nhds_unique h₁ h₂
-- So glue the `f s hs` together and prove that this glued function `f₀` is a limit on each
-- compact set `s`
refine ⟨liftCover' _ _ h exists_compact_mem_nhds, ?_⟩
rw [tendsto_compactOpen_iff_forall]
intro s hs
rw [liftCover_restrict']
exact hf s hs
#align continuous_map.exists_tendsto_compact_open_iff_forall ContinuousMap.exists_tendsto_compactOpen_iff_forall
end InfInduced
section Coev
variable (X Y)
/-- The coevaluation map `Y → C(X, Y × X)` sending a point `x : Y` to the continuous function
on `X` sending `y` to `(x, y)`. -/
@[simps (config := .asFn)]
def coev (b : Y) : C(X, Y × X) :=
{ toFun := Prod.mk b }
#align continuous_map.coev ContinuousMap.coev
variable {X Y}
theorem image_coev {y : Y} (s : Set X) : coev X Y y '' s = {y} ×ˢ s := by simp
#align continuous_map.image_coev ContinuousMap.image_coev
/-- The coevaluation map `Y → C(X, Y × X)` is continuous (always). -/
theorem continuous_coev : Continuous (coev X Y) := by
have : ∀ {a K U}, MapsTo (coev X Y a) K U ↔ {a} ×ˢ K ⊆ U := by simp [mapsTo']
simp only [continuous_iff_continuousAt, ContinuousAt, tendsto_nhds_compactOpen, this]
intro x K hK U hU hKU
rcases generalized_tube_lemma isCompact_singleton hK hU hKU with ⟨V, W, hV, -, hxV, hKW, hVWU⟩
filter_upwards [hV.mem_nhds (hxV rfl)] with a ha
exact (prod_mono (singleton_subset_iff.mpr ha) hKW).trans hVWU
#align continuous_map.continuous_coev ContinuousMap.continuous_coev
end Coev
section Curry
/-- The curried form of a continuous map `α × β → γ` as a continuous map `α → C(β, γ)`.
If `a × β` is locally compact, this is continuous. If `α` and `β` are both locally
compact, then this is a homeomorphism, see `Homeomorph.curry`. -/
def curry (f : C(X × Y, Z)) : C(X, C(Y, Z)) where
toFun a := ⟨Function.curry f a, f.continuous.comp <| by continuity⟩
continuous_toFun := (continuous_comp f).comp continuous_coev
#align continuous_map.curry ContinuousMap.curry
@[simp]
theorem curry_apply (f : C(X × Y, Z)) (a : X) (b : Y) : f.curry a b = f (a, b) :=
rfl
#align continuous_map.curry_apply ContinuousMap.curry_apply
/-- Auxiliary definition, see `ContinuousMap.curry` and `Homeomorph.curry`. -/
@[deprecated ContinuousMap.curry]
def curry' (f : C(X × Y, Z)) (a : X) : C(Y, Z) := curry f a
#align continuous_map.curry' ContinuousMap.curry'
set_option linter.deprecated false in
/-- If a map `α × β → γ` is continuous, then its curried form `α → C(β, γ)` is continuous. -/
@[deprecated ContinuousMap.curry]
theorem continuous_curry' (f : C(X × Y, Z)) : Continuous (curry' f) := (curry f).continuous
#align continuous_map.continuous_curry' ContinuousMap.continuous_curry'
/-- To show continuity of a map `α → C(β, γ)`, it suffices to show that its uncurried form
`α × β → γ` is continuous. -/
theorem continuous_of_continuous_uncurry (f : X → C(Y, Z))
(h : Continuous (Function.uncurry fun x y => f x y)) : Continuous f :=
(curry ⟨_, h⟩).2
#align continuous_map.continuous_of_continuous_uncurry ContinuousMap.continuous_of_continuous_uncurry
/-- The currying process is a continuous map between function spaces. -/
theorem continuous_curry [LocallyCompactSpace (X × Y)] :
Continuous (curry : C(X × Y, Z) → C(X, C(Y, Z))) := by
apply continuous_of_continuous_uncurry
apply continuous_of_continuous_uncurry
rw [← (Homeomorph.prodAssoc _ _ _).symm.comp_continuous_iff']
exact continuous_eval
#align continuous_map.continuous_curry ContinuousMap.continuous_curry
/-- The uncurried form of a continuous map `X → C(Y, Z)` is a continuous map `X × Y → Z`. -/
theorem continuous_uncurry_of_continuous [LocallyCompactSpace Y] (f : C(X, C(Y, Z))) :
Continuous (Function.uncurry fun x y => f x y) :=
continuous_eval.comp <| f.continuous.prod_map continuous_id
#align continuous_map.continuous_uncurry_of_continuous ContinuousMap.continuous_uncurry_of_continuous
/-- The uncurried form of a continuous map `X → C(Y, Z)` as a continuous map `X × Y → Z` (if `Y` is
locally compact). If `X` is also locally compact, then this is a homeomorphism between the two
function spaces, see `Homeomorph.curry`. -/
@[simps]
def uncurry [LocallyCompactSpace Y] (f : C(X, C(Y, Z))) : C(X × Y, Z) :=
⟨_, continuous_uncurry_of_continuous f⟩
#align continuous_map.uncurry ContinuousMap.uncurry
/-- The uncurrying process is a continuous map between function spaces. -/
| Mathlib/Topology/CompactOpen.lean | 426 | 430 | theorem continuous_uncurry [LocallyCompactSpace X] [LocallyCompactSpace Y] :
Continuous (uncurry : C(X, C(Y, Z)) → C(X × Y, Z)) := by |
apply continuous_of_continuous_uncurry
rw [← (Homeomorph.prodAssoc _ _ _).comp_continuous_iff']
apply continuous_eval.comp (continuous_eval.prod_map continuous_id)
|
/-
Copyright (c) 2017 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Tim Baumann, Stephen Morgan, Scott Morrison, Floris van Doorn
-/
import Mathlib.Tactic.CategoryTheory.Reassoc
#align_import category_theory.isomorphism from "leanprover-community/mathlib"@"8350c34a64b9bc3fc64335df8006bffcadc7baa6"
/-!
# Isomorphisms
This file defines isomorphisms between objects of a category.
## Main definitions
- `structure Iso` : a bundled isomorphism between two objects of a category;
- `class IsIso` : an unbundled version of `iso`;
note that `IsIso f` is a `Prop`, and only asserts the existence of an inverse.
Of course, this inverse is unique, so it doesn't cost us much to use choice to retrieve it.
- `inv f`, for the inverse of a morphism with `[IsIso f]`
- `asIso` : convert from `IsIso` to `Iso` (noncomputable);
- `of_iso` : convert from `Iso` to `IsIso`;
- standard operations on isomorphisms (composition, inverse etc)
## Notations
- `X ≅ Y` : same as `Iso X Y`;
- `α ≪≫ β` : composition of two isomorphisms; it is called `Iso.trans`
## Tags
category, category theory, isomorphism
-/
universe v u
-- morphism levels before object levels. See note [CategoryTheory universes].
namespace CategoryTheory
open Category
/-- An isomorphism (a.k.a. an invertible morphism) between two objects of a category.
The inverse morphism is bundled.
See also `CategoryTheory.Core` for the category with the same objects and isomorphisms playing
the role of morphisms.
See <https://stacks.math.columbia.edu/tag/0017>.
-/
structure Iso {C : Type u} [Category.{v} C] (X Y : C) where
/-- The forward direction of an isomorphism. -/
hom : X ⟶ Y
/-- The backwards direction of an isomorphism. -/
inv : Y ⟶ X
/-- Composition of the two directions of an isomorphism is the identity on the source. -/
hom_inv_id : hom ≫ inv = 𝟙 X := by aesop_cat
/-- Composition of the two directions of an isomorphism in reverse order
is the identity on the target. -/
inv_hom_id : inv ≫ hom = 𝟙 Y := by aesop_cat
#align category_theory.iso CategoryTheory.Iso
#align category_theory.iso.hom CategoryTheory.Iso.hom
#align category_theory.iso.inv CategoryTheory.Iso.inv
#align category_theory.iso.inv_hom_id CategoryTheory.Iso.inv_hom_id
#align category_theory.iso.hom_inv_id CategoryTheory.Iso.hom_inv_id
attribute [reassoc (attr := simp)] Iso.hom_inv_id Iso.inv_hom_id
#align category_theory.iso.hom_inv_id_assoc CategoryTheory.Iso.hom_inv_id_assoc
#align category_theory.iso.inv_hom_id_assoc CategoryTheory.Iso.inv_hom_id_assoc
/-- Notation for an isomorphism in a category. -/
infixr:10 " ≅ " => Iso -- type as \cong or \iso
variable {C : Type u} [Category.{v} C] {X Y Z : C}
namespace Iso
@[ext]
theorem ext ⦃α β : X ≅ Y⦄ (w : α.hom = β.hom) : α = β :=
suffices α.inv = β.inv by
cases α
cases β
cases w
cases this
rfl
calc
α.inv = α.inv ≫ β.hom ≫ β.inv := by rw [Iso.hom_inv_id, Category.comp_id]
_ = (α.inv ≫ α.hom) ≫ β.inv := by rw [Category.assoc, ← w]
_ = β.inv := by rw [Iso.inv_hom_id, Category.id_comp]
#align category_theory.iso.ext CategoryTheory.Iso.ext
/-- Inverse isomorphism. -/
@[symm]
def symm (I : X ≅ Y) : Y ≅ X where
hom := I.inv
inv := I.hom
#align category_theory.iso.symm CategoryTheory.Iso.symm
@[simp]
theorem symm_hom (α : X ≅ Y) : α.symm.hom = α.inv :=
rfl
#align category_theory.iso.symm_hom CategoryTheory.Iso.symm_hom
@[simp]
theorem symm_inv (α : X ≅ Y) : α.symm.inv = α.hom :=
rfl
#align category_theory.iso.symm_inv CategoryTheory.Iso.symm_inv
@[simp]
theorem symm_mk {X Y : C} (hom : X ⟶ Y) (inv : Y ⟶ X) (hom_inv_id) (inv_hom_id) :
Iso.symm { hom, inv, hom_inv_id := hom_inv_id, inv_hom_id := inv_hom_id } =
{ hom := inv, inv := hom, hom_inv_id := inv_hom_id, inv_hom_id := hom_inv_id } :=
rfl
#align category_theory.iso.symm_mk CategoryTheory.Iso.symm_mk
@[simp]
theorem symm_symm_eq {X Y : C} (α : X ≅ Y) : α.symm.symm = α := by cases α; rfl
#align category_theory.iso.symm_symm_eq CategoryTheory.Iso.symm_symm_eq
@[simp]
theorem symm_eq_iff {X Y : C} {α β : X ≅ Y} : α.symm = β.symm ↔ α = β :=
⟨fun h => symm_symm_eq α ▸ symm_symm_eq β ▸ congr_arg symm h, congr_arg symm⟩
#align category_theory.iso.symm_eq_iff CategoryTheory.Iso.symm_eq_iff
theorem nonempty_iso_symm (X Y : C) : Nonempty (X ≅ Y) ↔ Nonempty (Y ≅ X) :=
⟨fun h => ⟨h.some.symm⟩, fun h => ⟨h.some.symm⟩⟩
#align category_theory.iso.nonempty_iso_symm CategoryTheory.Iso.nonempty_iso_symm
/-- Identity isomorphism. -/
@[refl, simps]
def refl (X : C) : X ≅ X where
hom := 𝟙 X
inv := 𝟙 X
#align category_theory.iso.refl CategoryTheory.Iso.refl
#align category_theory.iso.refl_inv CategoryTheory.Iso.refl_inv
#align category_theory.iso.refl_hom CategoryTheory.Iso.refl_hom
instance : Inhabited (X ≅ X) := ⟨Iso.refl X⟩
theorem nonempty_iso_refl (X : C) : Nonempty (X ≅ X) := ⟨default⟩
@[simp]
theorem refl_symm (X : C) : (Iso.refl X).symm = Iso.refl X := rfl
#align category_theory.iso.refl_symm CategoryTheory.Iso.refl_symm
-- Porting note: It seems that the trans `trans` attribute isn't working properly
-- in this case, so we have to manually add a `Trans` instance (with a `simps` tag).
/-- Composition of two isomorphisms -/
@[trans, simps]
def trans (α : X ≅ Y) (β : Y ≅ Z) : X ≅ Z where
hom := α.hom ≫ β.hom
inv := β.inv ≫ α.inv
#align category_theory.iso.trans CategoryTheory.Iso.trans
#align category_theory.iso.trans_hom CategoryTheory.Iso.trans_hom
#align category_theory.iso.trans_inv CategoryTheory.Iso.trans_inv
@[simps]
instance instTransIso : Trans (α := C) (· ≅ ·) (· ≅ ·) (· ≅ ·) where
trans := trans
/-- Notation for composition of isomorphisms. -/
infixr:80 " ≪≫ " => Iso.trans -- type as `\ll \gg`.
@[simp]
theorem trans_mk {X Y Z : C} (hom : X ⟶ Y) (inv : Y ⟶ X) (hom_inv_id) (inv_hom_id)
(hom' : Y ⟶ Z) (inv' : Z ⟶ Y) (hom_inv_id') (inv_hom_id') (hom_inv_id'') (inv_hom_id'') :
Iso.trans ⟨hom, inv, hom_inv_id, inv_hom_id⟩ ⟨hom', inv', hom_inv_id', inv_hom_id'⟩ =
⟨hom ≫ hom', inv' ≫ inv, hom_inv_id'', inv_hom_id''⟩ :=
rfl
#align category_theory.iso.trans_mk CategoryTheory.Iso.trans_mk
@[simp]
theorem trans_symm (α : X ≅ Y) (β : Y ≅ Z) : (α ≪≫ β).symm = β.symm ≪≫ α.symm :=
rfl
#align category_theory.iso.trans_symm CategoryTheory.Iso.trans_symm
@[simp]
theorem trans_assoc {Z' : C} (α : X ≅ Y) (β : Y ≅ Z) (γ : Z ≅ Z') :
(α ≪≫ β) ≪≫ γ = α ≪≫ β ≪≫ γ := by
ext; simp only [trans_hom, Category.assoc]
#align category_theory.iso.trans_assoc CategoryTheory.Iso.trans_assoc
@[simp]
theorem refl_trans (α : X ≅ Y) : Iso.refl X ≪≫ α = α := by ext; apply Category.id_comp
#align category_theory.iso.refl_trans CategoryTheory.Iso.refl_trans
@[simp]
theorem trans_refl (α : X ≅ Y) : α ≪≫ Iso.refl Y = α := by ext; apply Category.comp_id
#align category_theory.iso.trans_refl CategoryTheory.Iso.trans_refl
@[simp]
theorem symm_self_id (α : X ≅ Y) : α.symm ≪≫ α = Iso.refl Y :=
ext α.inv_hom_id
#align category_theory.iso.symm_self_id CategoryTheory.Iso.symm_self_id
@[simp]
theorem self_symm_id (α : X ≅ Y) : α ≪≫ α.symm = Iso.refl X :=
ext α.hom_inv_id
#align category_theory.iso.self_symm_id CategoryTheory.Iso.self_symm_id
@[simp]
theorem symm_self_id_assoc (α : X ≅ Y) (β : Y ≅ Z) : α.symm ≪≫ α ≪≫ β = β := by
rw [← trans_assoc, symm_self_id, refl_trans]
#align category_theory.iso.symm_self_id_assoc CategoryTheory.Iso.symm_self_id_assoc
@[simp]
theorem self_symm_id_assoc (α : X ≅ Y) (β : X ≅ Z) : α ≪≫ α.symm ≪≫ β = β := by
rw [← trans_assoc, self_symm_id, refl_trans]
#align category_theory.iso.self_symm_id_assoc CategoryTheory.Iso.self_symm_id_assoc
theorem inv_comp_eq (α : X ≅ Y) {f : X ⟶ Z} {g : Y ⟶ Z} : α.inv ≫ f = g ↔ f = α.hom ≫ g :=
⟨fun H => by simp [H.symm], fun H => by simp [H]⟩
#align category_theory.iso.inv_comp_eq CategoryTheory.Iso.inv_comp_eq
theorem eq_inv_comp (α : X ≅ Y) {f : X ⟶ Z} {g : Y ⟶ Z} : g = α.inv ≫ f ↔ α.hom ≫ g = f :=
(inv_comp_eq α.symm).symm
#align category_theory.iso.eq_inv_comp CategoryTheory.Iso.eq_inv_comp
theorem comp_inv_eq (α : X ≅ Y) {f : Z ⟶ Y} {g : Z ⟶ X} : f ≫ α.inv = g ↔ f = g ≫ α.hom :=
⟨fun H => by simp [H.symm], fun H => by simp [H]⟩
#align category_theory.iso.comp_inv_eq CategoryTheory.Iso.comp_inv_eq
theorem eq_comp_inv (α : X ≅ Y) {f : Z ⟶ Y} {g : Z ⟶ X} : g = f ≫ α.inv ↔ g ≫ α.hom = f :=
(comp_inv_eq α.symm).symm
#align category_theory.iso.eq_comp_inv CategoryTheory.Iso.eq_comp_inv
theorem inv_eq_inv (f g : X ≅ Y) : f.inv = g.inv ↔ f.hom = g.hom :=
have : ∀ {X Y : C} (f g : X ≅ Y), f.hom = g.hom → f.inv = g.inv := fun f g h => by rw [ext h]
⟨this f.symm g.symm, this f g⟩
#align category_theory.iso.inv_eq_inv CategoryTheory.Iso.inv_eq_inv
theorem hom_comp_eq_id (α : X ≅ Y) {f : Y ⟶ X} : α.hom ≫ f = 𝟙 X ↔ f = α.inv := by
rw [← eq_inv_comp, comp_id]
#align category_theory.iso.hom_comp_eq_id CategoryTheory.Iso.hom_comp_eq_id
theorem comp_hom_eq_id (α : X ≅ Y) {f : Y ⟶ X} : f ≫ α.hom = 𝟙 Y ↔ f = α.inv := by
rw [← eq_comp_inv, id_comp]
#align category_theory.iso.comp_hom_eq_id CategoryTheory.Iso.comp_hom_eq_id
theorem inv_comp_eq_id (α : X ≅ Y) {f : X ⟶ Y} : α.inv ≫ f = 𝟙 Y ↔ f = α.hom :=
hom_comp_eq_id α.symm
#align category_theory.iso.inv_comp_eq_id CategoryTheory.Iso.inv_comp_eq_id
theorem comp_inv_eq_id (α : X ≅ Y) {f : X ⟶ Y} : f ≫ α.inv = 𝟙 X ↔ f = α.hom :=
comp_hom_eq_id α.symm
#align category_theory.iso.comp_inv_eq_id CategoryTheory.Iso.comp_inv_eq_id
theorem hom_eq_inv (α : X ≅ Y) (β : Y ≅ X) : α.hom = β.inv ↔ β.hom = α.inv := by
erw [inv_eq_inv α.symm β, eq_comm]
rfl
#align category_theory.iso.hom_eq_inv CategoryTheory.Iso.hom_eq_inv
end Iso
/-- `IsIso` typeclass expressing that a morphism is invertible. -/
class IsIso (f : X ⟶ Y) : Prop where
/-- The existence of an inverse morphism. -/
out : ∃ inv : Y ⟶ X, f ≫ inv = 𝟙 X ∧ inv ≫ f = 𝟙 Y
#align category_theory.is_iso CategoryTheory.IsIso
/-- The inverse of a morphism `f` when we have `[IsIso f]`.
-/
noncomputable def inv (f : X ⟶ Y) [I : IsIso f] : Y ⟶ X :=
Classical.choose I.1
#align category_theory.inv CategoryTheory.inv
namespace IsIso
@[simp]
theorem hom_inv_id (f : X ⟶ Y) [I : IsIso f] : f ≫ inv f = 𝟙 X :=
(Classical.choose_spec I.1).left
#align category_theory.is_iso.hom_inv_id CategoryTheory.IsIso.hom_inv_id
@[simp]
theorem inv_hom_id (f : X ⟶ Y) [I : IsIso f] : inv f ≫ f = 𝟙 Y :=
(Classical.choose_spec I.1).right
#align category_theory.is_iso.inv_hom_id CategoryTheory.IsIso.inv_hom_id
-- FIXME putting @[reassoc] on the `hom_inv_id` above somehow unfolds `inv`
-- This happens even if we make `inv` irreducible!
-- I don't understand how this is happening: it is likely a bug.
-- attribute [reassoc] hom_inv_id inv_hom_id
-- #print hom_inv_id_assoc
-- theorem CategoryTheory.IsIso.hom_inv_id_assoc {X Y : C} (f : X ⟶ Y) [I : IsIso f]
-- {Z : C} (h : X ⟶ Z),
-- f ≫ Classical.choose (_ : Exists fun inv ↦ f ≫ inv = 𝟙 X ∧ inv ≫ f = 𝟙 Y) ≫ h = h := ...
@[simp]
theorem hom_inv_id_assoc (f : X ⟶ Y) [I : IsIso f] {Z} (g : X ⟶ Z) : f ≫ inv f ≫ g = g := by
simp [← Category.assoc]
#align category_theory.is_iso.hom_inv_id_assoc CategoryTheory.IsIso.hom_inv_id_assoc
@[simp]
theorem inv_hom_id_assoc (f : X ⟶ Y) [I : IsIso f] {Z} (g : Y ⟶ Z) : inv f ≫ f ≫ g = g := by
simp [← Category.assoc]
#align category_theory.is_iso.inv_hom_id_assoc CategoryTheory.IsIso.inv_hom_id_assoc
end IsIso
lemma Iso.isIso_hom (e : X ≅ Y) : IsIso e.hom :=
⟨e.inv, by simp, by simp⟩
#align category_theory.is_iso.of_iso CategoryTheory.Iso.isIso_hom
lemma Iso.isIso_inv (e : X ≅ Y) : IsIso e.inv := e.symm.isIso_hom
#align category_theory.is_iso.of_iso_inv CategoryTheory.Iso.isIso_inv
attribute [instance] Iso.isIso_hom Iso.isIso_inv
open IsIso
/-- Reinterpret a morphism `f` with an `IsIso f` instance as an `Iso`. -/
noncomputable def asIso (f : X ⟶ Y) [IsIso f] : X ≅ Y :=
⟨f, inv f, hom_inv_id f, inv_hom_id f⟩
#align category_theory.as_iso CategoryTheory.asIso
-- Porting note: the `IsIso f` argument had been instance implicit,
-- but we've changed it to implicit as a `rw` in `Mathlib.CategoryTheory.Closed.Functor`
-- was failing to generate it by typeclass search.
@[simp]
theorem asIso_hom (f : X ⟶ Y) {_ : IsIso f} : (asIso f).hom = f :=
rfl
#align category_theory.as_iso_hom CategoryTheory.asIso_hom
-- Porting note: the `IsIso f` argument had been instance implicit,
-- but we've changed it to implicit as a `rw` in `Mathlib.CategoryTheory.Closed.Functor`
-- was failing to generate it by typeclass search.
@[simp]
theorem asIso_inv (f : X ⟶ Y) {_ : IsIso f} : (asIso f).inv = inv f :=
rfl
#align category_theory.as_iso_inv CategoryTheory.asIso_inv
namespace IsIso
-- see Note [lower instance priority]
instance (priority := 100) epi_of_iso (f : X ⟶ Y) [IsIso f] : Epi f where
left_cancellation g h w := by
rw [← IsIso.inv_hom_id_assoc f g, w, IsIso.inv_hom_id_assoc f h]
#align category_theory.is_iso.epi_of_iso CategoryTheory.IsIso.epi_of_iso
-- see Note [lower instance priority]
instance (priority := 100) mono_of_iso (f : X ⟶ Y) [IsIso f] : Mono f where
right_cancellation g h w := by
rw [← Category.comp_id g, ← Category.comp_id h, ← IsIso.hom_inv_id f,
← Category.assoc, w, ← Category.assoc]
#align category_theory.is_iso.mono_of_iso CategoryTheory.IsIso.mono_of_iso
-- Porting note: `@[ext]` used to accept lemmas like this. Now we add an aesop rule
@[aesop apply safe (rule_sets := [CategoryTheory])]
theorem inv_eq_of_hom_inv_id {f : X ⟶ Y} [IsIso f] {g : Y ⟶ X} (hom_inv_id : f ≫ g = 𝟙 X) :
inv f = g := by
apply (cancel_epi f).mp
simp [hom_inv_id]
#align category_theory.is_iso.inv_eq_of_hom_inv_id CategoryTheory.IsIso.inv_eq_of_hom_inv_id
theorem inv_eq_of_inv_hom_id {f : X ⟶ Y} [IsIso f] {g : Y ⟶ X} (inv_hom_id : g ≫ f = 𝟙 Y) :
inv f = g := by
apply (cancel_mono f).mp
simp [inv_hom_id]
#align category_theory.is_iso.inv_eq_of_inv_hom_id CategoryTheory.IsIso.inv_eq_of_inv_hom_id
-- Porting note: `@[ext]` used to accept lemmas like this.
@[aesop apply safe (rule_sets := [CategoryTheory])]
theorem eq_inv_of_hom_inv_id {f : X ⟶ Y} [IsIso f] {g : Y ⟶ X} (hom_inv_id : f ≫ g = 𝟙 X) :
g = inv f :=
(inv_eq_of_hom_inv_id hom_inv_id).symm
#align category_theory.is_iso.eq_inv_of_hom_inv_id CategoryTheory.IsIso.eq_inv_of_hom_inv_id
theorem eq_inv_of_inv_hom_id {f : X ⟶ Y} [IsIso f] {g : Y ⟶ X} (inv_hom_id : g ≫ f = 𝟙 Y) :
g = inv f :=
(inv_eq_of_inv_hom_id inv_hom_id).symm
#align category_theory.is_iso.eq_inv_of_inv_hom_id CategoryTheory.IsIso.eq_inv_of_inv_hom_id
instance id (X : C) : IsIso (𝟙 X) := ⟨⟨𝟙 X, by simp⟩⟩
#align category_theory.is_iso.id CategoryTheory.IsIso.id
-- deprecated on 2024-05-15
@[deprecated] alias of_iso := CategoryTheory.Iso.isIso_hom
@[deprecated] alias of_iso_inv := CategoryTheory.Iso.isIso_inv
variable {f g : X ⟶ Y} {h : Y ⟶ Z}
instance inv_isIso [IsIso f] : IsIso (inv f) :=
(asIso f).isIso_inv
#align category_theory.is_iso.inv_is_iso CategoryTheory.IsIso.inv_isIso
/- The following instance has lower priority for the following reason:
Suppose we are given `f : X ≅ Y` with `X Y : Type u`.
Without the lower priority, typeclass inference cannot deduce `IsIso f.hom`
because `f.hom` is defeq to `(fun x ↦ x) ≫ f.hom`, triggering a loop. -/
instance (priority := 900) comp_isIso [IsIso f] [IsIso h] : IsIso (f ≫ h) :=
(asIso f ≪≫ asIso h).isIso_hom
#align category_theory.is_iso.comp_is_iso CategoryTheory.IsIso.comp_isIso
@[simp]
theorem inv_id : inv (𝟙 X) = 𝟙 X := by
apply inv_eq_of_hom_inv_id
simp
#align category_theory.is_iso.inv_id CategoryTheory.IsIso.inv_id
@[simp]
theorem inv_comp [IsIso f] [IsIso h] : inv (f ≫ h) = inv h ≫ inv f := by
apply inv_eq_of_hom_inv_id
simp
#align category_theory.is_iso.inv_comp CategoryTheory.IsIso.inv_comp
@[simp]
theorem inv_inv [IsIso f] : inv (inv f) = f := by
apply inv_eq_of_hom_inv_id
simp
#align category_theory.is_iso.inv_inv CategoryTheory.IsIso.inv_inv
@[simp]
theorem Iso.inv_inv (f : X ≅ Y) : inv f.inv = f.hom := by
apply inv_eq_of_hom_inv_id
simp
#align category_theory.is_iso.iso.inv_inv CategoryTheory.IsIso.Iso.inv_inv
@[simp]
theorem Iso.inv_hom (f : X ≅ Y) : inv f.hom = f.inv := by
apply inv_eq_of_hom_inv_id
simp
#align category_theory.is_iso.iso.inv_hom CategoryTheory.IsIso.Iso.inv_hom
@[simp]
theorem inv_comp_eq (α : X ⟶ Y) [IsIso α] {f : X ⟶ Z} {g : Y ⟶ Z} : inv α ≫ f = g ↔ f = α ≫ g :=
(asIso α).inv_comp_eq
#align category_theory.is_iso.inv_comp_eq CategoryTheory.IsIso.inv_comp_eq
@[simp]
theorem eq_inv_comp (α : X ⟶ Y) [IsIso α] {f : X ⟶ Z} {g : Y ⟶ Z} : g = inv α ≫ f ↔ α ≫ g = f :=
(asIso α).eq_inv_comp
#align category_theory.is_iso.eq_inv_comp CategoryTheory.IsIso.eq_inv_comp
@[simp]
theorem comp_inv_eq (α : X ⟶ Y) [IsIso α] {f : Z ⟶ Y} {g : Z ⟶ X} : f ≫ inv α = g ↔ f = g ≫ α :=
(asIso α).comp_inv_eq
#align category_theory.is_iso.comp_inv_eq CategoryTheory.IsIso.comp_inv_eq
@[simp]
theorem eq_comp_inv (α : X ⟶ Y) [IsIso α] {f : Z ⟶ Y} {g : Z ⟶ X} : g = f ≫ inv α ↔ g ≫ α = f :=
(asIso α).eq_comp_inv
#align category_theory.is_iso.eq_comp_inv CategoryTheory.IsIso.eq_comp_inv
theorem of_isIso_comp_left {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) [IsIso f] [IsIso (f ≫ g)] :
IsIso g := by
rw [← id_comp g, ← inv_hom_id f, assoc]
infer_instance
#align category_theory.is_iso.of_is_iso_comp_left CategoryTheory.IsIso.of_isIso_comp_left
theorem of_isIso_comp_right {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) [IsIso g] [IsIso (f ≫ g)] :
IsIso f := by
rw [← comp_id f, ← hom_inv_id g, ← assoc]
infer_instance
#align category_theory.is_iso.of_is_iso_comp_right CategoryTheory.IsIso.of_isIso_comp_right
theorem of_isIso_fac_left {X Y Z : C} {f : X ⟶ Y} {g : Y ⟶ Z} {h : X ⟶ Z} [IsIso f]
[hh : IsIso h] (w : f ≫ g = h) : IsIso g := by
rw [← w] at hh
haveI := hh
exact of_isIso_comp_left f g
#align category_theory.is_iso.of_is_iso_fac_left CategoryTheory.IsIso.of_isIso_fac_left
theorem of_isIso_fac_right {X Y Z : C} {f : X ⟶ Y} {g : Y ⟶ Z} {h : X ⟶ Z} [IsIso g]
[hh : IsIso h] (w : f ≫ g = h) : IsIso f := by
rw [← w] at hh
haveI := hh
exact of_isIso_comp_right f g
#align category_theory.is_iso.of_is_iso_fac_right CategoryTheory.IsIso.of_isIso_fac_right
end IsIso
open IsIso
theorem eq_of_inv_eq_inv {f g : X ⟶ Y} [IsIso f] [IsIso g] (p : inv f = inv g) : f = g := by
apply (cancel_epi (inv f)).1
erw [inv_hom_id, p, inv_hom_id]
#align category_theory.eq_of_inv_eq_inv CategoryTheory.eq_of_inv_eq_inv
theorem IsIso.inv_eq_inv {f g : X ⟶ Y} [IsIso f] [IsIso g] : inv f = inv g ↔ f = g :=
Iso.inv_eq_inv (asIso f) (asIso g)
#align category_theory.is_iso.inv_eq_inv CategoryTheory.IsIso.inv_eq_inv
theorem hom_comp_eq_id (g : X ⟶ Y) [IsIso g] {f : Y ⟶ X} : g ≫ f = 𝟙 X ↔ f = inv g :=
(asIso g).hom_comp_eq_id
#align category_theory.hom_comp_eq_id CategoryTheory.hom_comp_eq_id
theorem comp_hom_eq_id (g : X ⟶ Y) [IsIso g] {f : Y ⟶ X} : f ≫ g = 𝟙 Y ↔ f = inv g :=
(asIso g).comp_hom_eq_id
#align category_theory.comp_hom_eq_id CategoryTheory.comp_hom_eq_id
theorem inv_comp_eq_id (g : X ⟶ Y) [IsIso g] {f : X ⟶ Y} : inv g ≫ f = 𝟙 Y ↔ f = g :=
(asIso g).inv_comp_eq_id
#align category_theory.inv_comp_eq_id CategoryTheory.inv_comp_eq_id
theorem comp_inv_eq_id (g : X ⟶ Y) [IsIso g] {f : X ⟶ Y} : f ≫ inv g = 𝟙 X ↔ f = g :=
(asIso g).comp_inv_eq_id
#align category_theory.comp_inv_eq_id CategoryTheory.comp_inv_eq_id
theorem isIso_of_hom_comp_eq_id (g : X ⟶ Y) [IsIso g] {f : Y ⟶ X} (h : g ≫ f = 𝟙 X) : IsIso f := by
rw [(hom_comp_eq_id _).mp h]
infer_instance
#align category_theory.is_iso_of_hom_comp_eq_id CategoryTheory.isIso_of_hom_comp_eq_id
| Mathlib/CategoryTheory/Iso.lean | 505 | 507 | theorem isIso_of_comp_hom_eq_id (g : X ⟶ Y) [IsIso g] {f : Y ⟶ X} (h : f ≫ g = 𝟙 Y) : IsIso f := by |
rw [(comp_hom_eq_id _).mp h]
infer_instance
|
/-
Copyright (c) 2024 Thomas Browning, Junyan Xu. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Thomas Browning, Junyan Xu
-/
import Mathlib.Data.Set.Finite
import Mathlib.GroupTheory.GroupAction.FixedPoints
import Mathlib.GroupTheory.Perm.Support
/-!
# Subgroups generated by transpositions
This file studies subgroups generated by transpositions.
## Main results
- `swap_mem_closure_isSwap` : If a subgroup is generated by transpositions, then a transposition
`swap x y` lies in the subgroup if and only if `x` lies in the same orbit as `y`.
- `mem_closure_isSwap` : If a subgroup is generated by transpositions, then a permutation `f`
lies in the subgroup if and only if `f` has finite support and `f x` always lies in the same
orbit as `x`.
-/
open Equiv List MulAction Pointwise Set Subgroup
variable {G α : Type*} [Group G] [MulAction G α] [DecidableEq α]
/-- If the support of each element in a generating set of a permutation group is finite,
then the support of every element in the group is finite. -/
theorem finite_compl_fixedBy_closure_iff {S : Set G} :
(∀ g ∈ closure S, (fixedBy α g)ᶜ.Finite) ↔ ∀ g ∈ S, (fixedBy α g)ᶜ.Finite :=
⟨fun h g hg ↦ h g (subset_closure hg), fun h g hg ↦ by
refine closure_induction hg h (by simp) (fun g g' hg hg' ↦ (hg.union hg').subset ?_) (by simp)
simp_rw [← compl_inter, compl_subset_compl, fixedBy_mul]⟩
theorem finite_compl_fixedBy_swap {x y : α} : (fixedBy α (swap x y))ᶜ.Finite :=
Set.Finite.subset (s := {x, y}) (by simp)
(compl_subset_comm.mp fun z h ↦ by apply swap_apply_of_ne_of_ne <;> rintro rfl <;> simp at h)
theorem Equiv.Perm.IsSwap.finite_compl_fixedBy {σ : Perm α} (h : σ.IsSwap) :
(fixedBy α σ)ᶜ.Finite := by
obtain ⟨x, y, -, rfl⟩ := h
exact finite_compl_fixedBy_swap
-- this result cannot be moved to Perm/Basic since Perm/Basic is not allowed to import Submonoid
theorem SubmonoidClass.swap_mem_trans {a b c : α} {C} [SetLike C (Perm α)]
[SubmonoidClass C (Perm α)] (M : C) (hab : swap a b ∈ M) (hbc : swap b c ∈ M) :
swap a c ∈ M := by
obtain rfl | hab' := eq_or_ne a b
· exact hbc
obtain rfl | hac := eq_or_ne a c
· exact swap_self a ▸ one_mem M
rw [swap_comm, ← swap_mul_swap_mul_swap hab' hac]
exact mul_mem (mul_mem hbc hab) hbc
/-- Given a symmetric generating set of a permutation group, if T is a nonempty proper subset of
an orbit, then there exists a generator that sends some element of T into the complement of T. -/
theorem exists_smul_not_mem_of_subset_orbit_closure (S : Set G) (T : Set α) {a : α}
(hS : ∀ g ∈ S, g⁻¹ ∈ S) (subset : T ⊆ orbit (closure S) a) (not_mem : a ∉ T)
(nonempty : T.Nonempty) : ∃ σ ∈ S, ∃ a ∈ T, σ • a ∉ T := by
have key0 : ¬ closure S ≤ stabilizer G T := by
have ⟨b, hb⟩ := nonempty
obtain ⟨σ, rfl⟩ := subset hb
contrapose! not_mem with h
exact smul_mem_smul_set_iff.mp ((h σ.2).symm ▸ hb)
contrapose! key0
refine (closure_le _).mpr fun σ hσ ↦ ?_
simp_rw [SetLike.mem_coe, mem_stabilizer_iff, Set.ext_iff, mem_smul_set_iff_inv_smul_mem]
exact fun a ↦ ⟨fun h ↦ smul_inv_smul σ a ▸ key0 σ hσ (σ⁻¹ • a) h, key0 σ⁻¹ (hS σ hσ) a⟩
/-- If a subgroup is generated by transpositions, then a transposition `swap x y` lies in the
subgroup if and only if `x` lies in the same orbit as `y`. -/
theorem swap_mem_closure_isSwap {S : Set (Perm α)} (hS : ∀ f ∈ S, f.IsSwap) {x y : α} :
swap x y ∈ closure S ↔ x ∈ orbit (closure S) y := by
refine ⟨fun h ↦ ⟨⟨swap x y, h⟩, swap_apply_right x y⟩, fun hf ↦ ?_⟩
by_contra h
have := exists_smul_not_mem_of_subset_orbit_closure S {x | swap x y ∈ closure S}
(fun f hf ↦ ?_) (fun z hz ↦ ?_) h ⟨y, ?_⟩
· obtain ⟨σ, hσ, a, ha, hσa⟩ := this
obtain ⟨z, w, hzw, rfl⟩ := hS σ hσ
have := ne_of_mem_of_not_mem ha hσa
rw [Perm.smul_def, ne_comm, swap_apply_ne_self_iff, and_iff_right hzw] at this
refine hσa (SubmonoidClass.swap_mem_trans (closure S) ?_ ha)
obtain rfl | rfl := this <;> simpa [swap_comm] using subset_closure hσ
· obtain ⟨x, y, -, rfl⟩ := hS f hf; rwa [swap_inv]
· exact orbit_eq_iff.mpr hf ▸ ⟨⟨swap z y, hz⟩, swap_apply_right z y⟩
· rw [mem_setOf, swap_self]; apply one_mem
/-- If a subgroup is generated by transpositions, then a permutation `f` lies in the subgroup if
and only if `f` has finite support and `f x` always lies in the same orbit as `x`. -/
| Mathlib/GroupTheory/Perm/ClosureSwap.lean | 92 | 114 | theorem mem_closure_isSwap {S : Set (Perm α)} (hS : ∀ f ∈ S, f.IsSwap) {f : Perm α} :
f ∈ closure S ↔ (fixedBy α f)ᶜ.Finite ∧ ∀ x, f x ∈ orbit (closure S) x := by |
refine ⟨fun hf ↦ ⟨?_, fun x ↦ mem_orbit_iff.mpr ⟨⟨f, hf⟩, rfl⟩⟩, ?_⟩
· exact finite_compl_fixedBy_closure_iff.mpr (fun f hf ↦ (hS f hf).finite_compl_fixedBy) _ hf
rintro ⟨fin, hf⟩
set supp := (fixedBy α f)ᶜ with supp_eq
suffices h : (fixedBy α f)ᶜ ⊆ supp → f ∈ closure S from h supp_eq.symm.subset
clear_value supp; clear supp_eq; revert f
apply fin.induction_on ..
· rintro f - emp; convert (closure S).one_mem; ext; by_contra h; exact emp h
rintro a s - - ih f hf supp_subset
refine (mul_mem_cancel_left ((swap_mem_closure_isSwap hS).2 (hf a))).1
(ih (fun b ↦ ?_) fun b hb ↦ ?_)
· rw [Perm.mul_apply, swap_apply_def]; split_ifs with h1 h2
· rw [← orbit_eq_iff.mpr (hf b), h1, orbit_eq_iff.mpr (hf a)]; apply mem_orbit_self
· rw [← orbit_eq_iff.mpr (hf b), h2]; apply hf
· exact hf b
· contrapose! hb
simp_rw [not_mem_compl_iff, mem_fixedBy, Perm.smul_def, Perm.mul_apply, swap_apply_def,
apply_eq_iff_eq]
by_cases hb' : f b = b
· rw [hb']; split_ifs with h <;> simp only [h]
simp [show b = a by simpa [hb] using supp_subset hb']
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.RingTheory.Ideal.Over
import Mathlib.RingTheory.Ideal.Prod
import Mathlib.RingTheory.Ideal.MinimalPrime
import Mathlib.RingTheory.Localization.Away.Basic
import Mathlib.RingTheory.Nilpotent.Lemmas
import Mathlib.Topology.Sets.Closeds
import Mathlib.Topology.Sober
#align_import algebraic_geometry.prime_spectrum.basic from "leanprover-community/mathlib"@"a7c017d750512a352b623b1824d75da5998457d0"
/-!
# Prime spectrum of a commutative (semi)ring
The prime spectrum of a commutative (semi)ring is the type of all prime ideals.
It is naturally endowed with a topology: the Zariski topology.
(It is also naturally endowed with a sheaf of rings,
which is constructed in `AlgebraicGeometry.StructureSheaf`.)
## Main definitions
* `PrimeSpectrum R`: The prime spectrum of a commutative (semi)ring `R`,
i.e., the set of all prime ideals of `R`.
* `zeroLocus s`: The zero locus of a subset `s` of `R`
is the subset of `PrimeSpectrum R` consisting of all prime ideals that contain `s`.
* `vanishingIdeal t`: The vanishing ideal of a subset `t` of `PrimeSpectrum R`
is the intersection of points in `t` (viewed as prime ideals).
## Conventions
We denote subsets of (semi)rings with `s`, `s'`, etc...
whereas we denote subsets of prime spectra with `t`, `t'`, etc...
## Inspiration/contributors
The contents of this file draw inspiration from <https://github.com/ramonfmir/lean-scheme>
which has contributions from Ramon Fernandez Mir, Kevin Buzzard, Kenny Lau,
and Chris Hughes (on an earlier repository).
-/
noncomputable section
open scoped Classical
universe u v
variable (R : Type u) (S : Type v)
/-- The prime spectrum of a commutative (semi)ring `R` is the type of all prime ideals of `R`.
It is naturally endowed with a topology (the Zariski topology),
and a sheaf of commutative rings (see `AlgebraicGeometry.StructureSheaf`).
It is a fundamental building block in algebraic geometry. -/
@[ext]
structure PrimeSpectrum [CommSemiring R] where
asIdeal : Ideal R
IsPrime : asIdeal.IsPrime
#align prime_spectrum PrimeSpectrum
attribute [instance] PrimeSpectrum.IsPrime
namespace PrimeSpectrum
section CommSemiRing
variable [CommSemiring R] [CommSemiring S]
variable {R S}
instance [Nontrivial R] : Nonempty <| PrimeSpectrum R :=
let ⟨I, hI⟩ := Ideal.exists_maximal R
⟨⟨I, hI.isPrime⟩⟩
/-- The prime spectrum of the zero ring is empty. -/
instance [Subsingleton R] : IsEmpty (PrimeSpectrum R) :=
⟨fun x ↦ x.IsPrime.ne_top <| SetLike.ext' <| Subsingleton.eq_univ_of_nonempty x.asIdeal.nonempty⟩
#noalign prime_spectrum.punit
variable (R S)
/-- The map from the direct sum of prime spectra to the prime spectrum of a direct product. -/
@[simp]
def primeSpectrumProdOfSum : Sum (PrimeSpectrum R) (PrimeSpectrum S) → PrimeSpectrum (R × S)
| Sum.inl ⟨I, _⟩ => ⟨Ideal.prod I ⊤, Ideal.isPrime_ideal_prod_top⟩
| Sum.inr ⟨J, _⟩ => ⟨Ideal.prod ⊤ J, Ideal.isPrime_ideal_prod_top'⟩
#align prime_spectrum.prime_spectrum_prod_of_sum PrimeSpectrum.primeSpectrumProdOfSum
/-- The prime spectrum of `R × S` is in bijection with the disjoint unions of the prime spectrum of
`R` and the prime spectrum of `S`. -/
noncomputable def primeSpectrumProd :
PrimeSpectrum (R × S) ≃ Sum (PrimeSpectrum R) (PrimeSpectrum S) :=
Equiv.symm <|
Equiv.ofBijective (primeSpectrumProdOfSum R S) (by
constructor
· rintro (⟨I, hI⟩ | ⟨J, hJ⟩) (⟨I', hI'⟩ | ⟨J', hJ'⟩) h <;>
simp only [mk.injEq, Ideal.prod.ext_iff, primeSpectrumProdOfSum] at h
· simp only [h]
· exact False.elim (hI.ne_top h.left)
· exact False.elim (hJ.ne_top h.right)
· simp only [h]
· rintro ⟨I, hI⟩
rcases (Ideal.ideal_prod_prime I).mp hI with (⟨p, ⟨hp, rfl⟩⟩ | ⟨p, ⟨hp, rfl⟩⟩)
· exact ⟨Sum.inl ⟨p, hp⟩, rfl⟩
· exact ⟨Sum.inr ⟨p, hp⟩, rfl⟩)
#align prime_spectrum.prime_spectrum_prod PrimeSpectrum.primeSpectrumProd
variable {R S}
@[simp]
theorem primeSpectrumProd_symm_inl_asIdeal (x : PrimeSpectrum R) :
((primeSpectrumProd R S).symm <| Sum.inl x).asIdeal = Ideal.prod x.asIdeal ⊤ := by
cases x
rfl
#align prime_spectrum.prime_spectrum_prod_symm_inl_as_ideal PrimeSpectrum.primeSpectrumProd_symm_inl_asIdeal
@[simp]
theorem primeSpectrumProd_symm_inr_asIdeal (x : PrimeSpectrum S) :
((primeSpectrumProd R S).symm <| Sum.inr x).asIdeal = Ideal.prod ⊤ x.asIdeal := by
cases x
rfl
#align prime_spectrum.prime_spectrum_prod_symm_inr_as_ideal PrimeSpectrum.primeSpectrumProd_symm_inr_asIdeal
/-- The zero locus of a set `s` of elements of a commutative (semi)ring `R` is the set of all
prime ideals of the ring that contain the set `s`.
An element `f` of `R` can be thought of as a dependent function on the prime spectrum of `R`.
At a point `x` (a prime ideal) the function (i.e., element) `f` takes values in the quotient ring
`R` modulo the prime ideal `x`. In this manner, `zeroLocus s` is exactly the subset of
`PrimeSpectrum R` where all "functions" in `s` vanish simultaneously.
-/
def zeroLocus (s : Set R) : Set (PrimeSpectrum R) :=
{ x | s ⊆ x.asIdeal }
#align prime_spectrum.zero_locus PrimeSpectrum.zeroLocus
@[simp]
theorem mem_zeroLocus (x : PrimeSpectrum R) (s : Set R) : x ∈ zeroLocus s ↔ s ⊆ x.asIdeal :=
Iff.rfl
#align prime_spectrum.mem_zero_locus PrimeSpectrum.mem_zeroLocus
@[simp]
theorem zeroLocus_span (s : Set R) : zeroLocus (Ideal.span s : Set R) = zeroLocus s := by
ext x
exact (Submodule.gi R R).gc s x.asIdeal
#align prime_spectrum.zero_locus_span PrimeSpectrum.zeroLocus_span
/-- The vanishing ideal of a set `t` of points of the prime spectrum of a commutative ring `R` is
the intersection of all the prime ideals in the set `t`.
An element `f` of `R` can be thought of as a dependent function on the prime spectrum of `R`.
At a point `x` (a prime ideal) the function (i.e., element) `f` takes values in the quotient ring
`R` modulo the prime ideal `x`. In this manner, `vanishingIdeal t` is exactly the ideal of `R`
consisting of all "functions" that vanish on all of `t`.
-/
def vanishingIdeal (t : Set (PrimeSpectrum R)) : Ideal R :=
⨅ (x : PrimeSpectrum R) (_ : x ∈ t), x.asIdeal
#align prime_spectrum.vanishing_ideal PrimeSpectrum.vanishingIdeal
theorem coe_vanishingIdeal (t : Set (PrimeSpectrum R)) :
(vanishingIdeal t : Set R) = { f : R | ∀ x : PrimeSpectrum R, x ∈ t → f ∈ x.asIdeal } := by
ext f
rw [vanishingIdeal, SetLike.mem_coe, Submodule.mem_iInf]
apply forall_congr'; intro x
rw [Submodule.mem_iInf]
#align prime_spectrum.coe_vanishing_ideal PrimeSpectrum.coe_vanishingIdeal
theorem mem_vanishingIdeal (t : Set (PrimeSpectrum R)) (f : R) :
f ∈ vanishingIdeal t ↔ ∀ x : PrimeSpectrum R, x ∈ t → f ∈ x.asIdeal := by
rw [← SetLike.mem_coe, coe_vanishingIdeal, Set.mem_setOf_eq]
#align prime_spectrum.mem_vanishing_ideal PrimeSpectrum.mem_vanishingIdeal
@[simp]
theorem vanishingIdeal_singleton (x : PrimeSpectrum R) :
vanishingIdeal ({x} : Set (PrimeSpectrum R)) = x.asIdeal := by simp [vanishingIdeal]
#align prime_spectrum.vanishing_ideal_singleton PrimeSpectrum.vanishingIdeal_singleton
theorem subset_zeroLocus_iff_le_vanishingIdeal (t : Set (PrimeSpectrum R)) (I : Ideal R) :
t ⊆ zeroLocus I ↔ I ≤ vanishingIdeal t :=
⟨fun h _ k => (mem_vanishingIdeal _ _).mpr fun _ j => (mem_zeroLocus _ _).mpr (h j) k, fun h =>
fun x j => (mem_zeroLocus _ _).mpr (le_trans h fun _ h => ((mem_vanishingIdeal _ _).mp h) x j)⟩
#align prime_spectrum.subset_zero_locus_iff_le_vanishing_ideal PrimeSpectrum.subset_zeroLocus_iff_le_vanishingIdeal
section Gc
variable (R)
/-- `zeroLocus` and `vanishingIdeal` form a galois connection. -/
theorem gc :
@GaloisConnection (Ideal R) (Set (PrimeSpectrum R))ᵒᵈ _ _ (fun I => zeroLocus I) fun t =>
vanishingIdeal t :=
fun I t => subset_zeroLocus_iff_le_vanishingIdeal t I
#align prime_spectrum.gc PrimeSpectrum.gc
/-- `zeroLocus` and `vanishingIdeal` form a galois connection. -/
theorem gc_set :
@GaloisConnection (Set R) (Set (PrimeSpectrum R))ᵒᵈ _ _ (fun s => zeroLocus s) fun t =>
vanishingIdeal t := by
have ideal_gc : GaloisConnection Ideal.span _ := (Submodule.gi R R).gc
simpa [zeroLocus_span, Function.comp] using ideal_gc.compose (gc R)
#align prime_spectrum.gc_set PrimeSpectrum.gc_set
theorem subset_zeroLocus_iff_subset_vanishingIdeal (t : Set (PrimeSpectrum R)) (s : Set R) :
t ⊆ zeroLocus s ↔ s ⊆ vanishingIdeal t :=
(gc_set R) s t
#align prime_spectrum.subset_zero_locus_iff_subset_vanishing_ideal PrimeSpectrum.subset_zeroLocus_iff_subset_vanishingIdeal
end Gc
theorem subset_vanishingIdeal_zeroLocus (s : Set R) : s ⊆ vanishingIdeal (zeroLocus s) :=
(gc_set R).le_u_l s
#align prime_spectrum.subset_vanishing_ideal_zero_locus PrimeSpectrum.subset_vanishingIdeal_zeroLocus
theorem le_vanishingIdeal_zeroLocus (I : Ideal R) : I ≤ vanishingIdeal (zeroLocus I) :=
(gc R).le_u_l I
#align prime_spectrum.le_vanishing_ideal_zero_locus PrimeSpectrum.le_vanishingIdeal_zeroLocus
@[simp]
theorem vanishingIdeal_zeroLocus_eq_radical (I : Ideal R) :
vanishingIdeal (zeroLocus (I : Set R)) = I.radical :=
Ideal.ext fun f => by
rw [mem_vanishingIdeal, Ideal.radical_eq_sInf, Submodule.mem_sInf]
exact ⟨fun h x hx => h ⟨x, hx.2⟩ hx.1, fun h x hx => h x.1 ⟨hx, x.2⟩⟩
#align prime_spectrum.vanishing_ideal_zero_locus_eq_radical PrimeSpectrum.vanishingIdeal_zeroLocus_eq_radical
@[simp]
theorem zeroLocus_radical (I : Ideal R) : zeroLocus (I.radical : Set R) = zeroLocus I :=
vanishingIdeal_zeroLocus_eq_radical I ▸ (gc R).l_u_l_eq_l I
#align prime_spectrum.zero_locus_radical PrimeSpectrum.zeroLocus_radical
theorem subset_zeroLocus_vanishingIdeal (t : Set (PrimeSpectrum R)) :
t ⊆ zeroLocus (vanishingIdeal t) :=
(gc R).l_u_le t
#align prime_spectrum.subset_zero_locus_vanishing_ideal PrimeSpectrum.subset_zeroLocus_vanishingIdeal
theorem zeroLocus_anti_mono {s t : Set R} (h : s ⊆ t) : zeroLocus t ⊆ zeroLocus s :=
(gc_set R).monotone_l h
#align prime_spectrum.zero_locus_anti_mono PrimeSpectrum.zeroLocus_anti_mono
theorem zeroLocus_anti_mono_ideal {s t : Ideal R} (h : s ≤ t) :
zeroLocus (t : Set R) ⊆ zeroLocus (s : Set R) :=
(gc R).monotone_l h
#align prime_spectrum.zero_locus_anti_mono_ideal PrimeSpectrum.zeroLocus_anti_mono_ideal
theorem vanishingIdeal_anti_mono {s t : Set (PrimeSpectrum R)} (h : s ⊆ t) :
vanishingIdeal t ≤ vanishingIdeal s :=
(gc R).monotone_u h
#align prime_spectrum.vanishing_ideal_anti_mono PrimeSpectrum.vanishingIdeal_anti_mono
theorem zeroLocus_subset_zeroLocus_iff (I J : Ideal R) :
zeroLocus (I : Set R) ⊆ zeroLocus (J : Set R) ↔ J ≤ I.radical := by
rw [subset_zeroLocus_iff_le_vanishingIdeal, vanishingIdeal_zeroLocus_eq_radical]
#align prime_spectrum.zero_locus_subset_zero_locus_iff PrimeSpectrum.zeroLocus_subset_zeroLocus_iff
theorem zeroLocus_subset_zeroLocus_singleton_iff (f g : R) :
zeroLocus ({f} : Set R) ⊆ zeroLocus {g} ↔ g ∈ (Ideal.span ({f} : Set R)).radical := by
rw [← zeroLocus_span {f}, ← zeroLocus_span {g}, zeroLocus_subset_zeroLocus_iff, Ideal.span_le,
Set.singleton_subset_iff, SetLike.mem_coe]
#align prime_spectrum.zero_locus_subset_zero_locus_singleton_iff PrimeSpectrum.zeroLocus_subset_zeroLocus_singleton_iff
theorem zeroLocus_bot : zeroLocus ((⊥ : Ideal R) : Set R) = Set.univ :=
(gc R).l_bot
#align prime_spectrum.zero_locus_bot PrimeSpectrum.zeroLocus_bot
@[simp]
theorem zeroLocus_singleton_zero : zeroLocus ({0} : Set R) = Set.univ :=
zeroLocus_bot
#align prime_spectrum.zero_locus_singleton_zero PrimeSpectrum.zeroLocus_singleton_zero
@[simp]
theorem zeroLocus_empty : zeroLocus (∅ : Set R) = Set.univ :=
(gc_set R).l_bot
#align prime_spectrum.zero_locus_empty PrimeSpectrum.zeroLocus_empty
@[simp]
theorem vanishingIdeal_univ : vanishingIdeal (∅ : Set (PrimeSpectrum R)) = ⊤ := by
simpa using (gc R).u_top
#align prime_spectrum.vanishing_ideal_univ PrimeSpectrum.vanishingIdeal_univ
theorem zeroLocus_empty_of_one_mem {s : Set R} (h : (1 : R) ∈ s) : zeroLocus s = ∅ := by
rw [Set.eq_empty_iff_forall_not_mem]
intro x hx
rw [mem_zeroLocus] at hx
have x_prime : x.asIdeal.IsPrime := by infer_instance
have eq_top : x.asIdeal = ⊤ := by
rw [Ideal.eq_top_iff_one]
exact hx h
apply x_prime.ne_top eq_top
#align prime_spectrum.zero_locus_empty_of_one_mem PrimeSpectrum.zeroLocus_empty_of_one_mem
@[simp]
theorem zeroLocus_singleton_one : zeroLocus ({1} : Set R) = ∅ :=
zeroLocus_empty_of_one_mem (Set.mem_singleton (1 : R))
#align prime_spectrum.zero_locus_singleton_one PrimeSpectrum.zeroLocus_singleton_one
theorem zeroLocus_empty_iff_eq_top {I : Ideal R} : zeroLocus (I : Set R) = ∅ ↔ I = ⊤ := by
constructor
· contrapose!
intro h
rcases Ideal.exists_le_maximal I h with ⟨M, hM, hIM⟩
exact ⟨⟨M, hM.isPrime⟩, hIM⟩
· rintro rfl
apply zeroLocus_empty_of_one_mem
trivial
#align prime_spectrum.zero_locus_empty_iff_eq_top PrimeSpectrum.zeroLocus_empty_iff_eq_top
@[simp]
theorem zeroLocus_univ : zeroLocus (Set.univ : Set R) = ∅ :=
zeroLocus_empty_of_one_mem (Set.mem_univ 1)
#align prime_spectrum.zero_locus_univ PrimeSpectrum.zeroLocus_univ
theorem vanishingIdeal_eq_top_iff {s : Set (PrimeSpectrum R)} : vanishingIdeal s = ⊤ ↔ s = ∅ := by
rw [← top_le_iff, ← subset_zeroLocus_iff_le_vanishingIdeal, Submodule.top_coe, zeroLocus_univ,
Set.subset_empty_iff]
#align prime_spectrum.vanishing_ideal_eq_top_iff PrimeSpectrum.vanishingIdeal_eq_top_iff
theorem zeroLocus_sup (I J : Ideal R) :
zeroLocus ((I ⊔ J : Ideal R) : Set R) = zeroLocus I ∩ zeroLocus J :=
(gc R).l_sup
#align prime_spectrum.zero_locus_sup PrimeSpectrum.zeroLocus_sup
theorem zeroLocus_union (s s' : Set R) : zeroLocus (s ∪ s') = zeroLocus s ∩ zeroLocus s' :=
(gc_set R).l_sup
#align prime_spectrum.zero_locus_union PrimeSpectrum.zeroLocus_union
theorem vanishingIdeal_union (t t' : Set (PrimeSpectrum R)) :
vanishingIdeal (t ∪ t') = vanishingIdeal t ⊓ vanishingIdeal t' :=
(gc R).u_inf
#align prime_spectrum.vanishing_ideal_union PrimeSpectrum.vanishingIdeal_union
theorem zeroLocus_iSup {ι : Sort*} (I : ι → Ideal R) :
zeroLocus ((⨆ i, I i : Ideal R) : Set R) = ⋂ i, zeroLocus (I i) :=
(gc R).l_iSup
#align prime_spectrum.zero_locus_supr PrimeSpectrum.zeroLocus_iSup
theorem zeroLocus_iUnion {ι : Sort*} (s : ι → Set R) :
zeroLocus (⋃ i, s i) = ⋂ i, zeroLocus (s i) :=
(gc_set R).l_iSup
#align prime_spectrum.zero_locus_Union PrimeSpectrum.zeroLocus_iUnion
theorem zeroLocus_bUnion (s : Set (Set R)) :
zeroLocus (⋃ s' ∈ s, s' : Set R) = ⋂ s' ∈ s, zeroLocus s' := by simp only [zeroLocus_iUnion]
#align prime_spectrum.zero_locus_bUnion PrimeSpectrum.zeroLocus_bUnion
theorem vanishingIdeal_iUnion {ι : Sort*} (t : ι → Set (PrimeSpectrum R)) :
vanishingIdeal (⋃ i, t i) = ⨅ i, vanishingIdeal (t i) :=
(gc R).u_iInf
#align prime_spectrum.vanishing_ideal_Union PrimeSpectrum.vanishingIdeal_iUnion
theorem zeroLocus_inf (I J : Ideal R) :
zeroLocus ((I ⊓ J : Ideal R) : Set R) = zeroLocus I ∪ zeroLocus J :=
Set.ext fun x => x.2.inf_le
#align prime_spectrum.zero_locus_inf PrimeSpectrum.zeroLocus_inf
theorem union_zeroLocus (s s' : Set R) :
zeroLocus s ∪ zeroLocus s' = zeroLocus (Ideal.span s ⊓ Ideal.span s' : Ideal R) := by
rw [zeroLocus_inf]
simp
#align prime_spectrum.union_zero_locus PrimeSpectrum.union_zeroLocus
theorem zeroLocus_mul (I J : Ideal R) :
zeroLocus ((I * J : Ideal R) : Set R) = zeroLocus I ∪ zeroLocus J :=
Set.ext fun x => x.2.mul_le
#align prime_spectrum.zero_locus_mul PrimeSpectrum.zeroLocus_mul
theorem zeroLocus_singleton_mul (f g : R) :
zeroLocus ({f * g} : Set R) = zeroLocus {f} ∪ zeroLocus {g} :=
Set.ext fun x => by simpa using x.2.mul_mem_iff_mem_or_mem
#align prime_spectrum.zero_locus_singleton_mul PrimeSpectrum.zeroLocus_singleton_mul
@[simp]
theorem zeroLocus_pow (I : Ideal R) {n : ℕ} (hn : n ≠ 0) :
zeroLocus ((I ^ n : Ideal R) : Set R) = zeroLocus I :=
zeroLocus_radical (I ^ n) ▸ (I.radical_pow hn).symm ▸ zeroLocus_radical I
#align prime_spectrum.zero_locus_pow PrimeSpectrum.zeroLocus_pow
@[simp]
theorem zeroLocus_singleton_pow (f : R) (n : ℕ) (hn : 0 < n) :
zeroLocus ({f ^ n} : Set R) = zeroLocus {f} :=
Set.ext fun x => by simpa using x.2.pow_mem_iff_mem n hn
#align prime_spectrum.zero_locus_singleton_pow PrimeSpectrum.zeroLocus_singleton_pow
theorem sup_vanishingIdeal_le (t t' : Set (PrimeSpectrum R)) :
vanishingIdeal t ⊔ vanishingIdeal t' ≤ vanishingIdeal (t ∩ t') := by
intro r
rw [Submodule.mem_sup, mem_vanishingIdeal]
rintro ⟨f, hf, g, hg, rfl⟩ x ⟨hxt, hxt'⟩
rw [mem_vanishingIdeal] at hf hg
apply Submodule.add_mem <;> solve_by_elim
#align prime_spectrum.sup_vanishing_ideal_le PrimeSpectrum.sup_vanishingIdeal_le
theorem mem_compl_zeroLocus_iff_not_mem {f : R} {I : PrimeSpectrum R} :
I ∈ (zeroLocus {f} : Set (PrimeSpectrum R))ᶜ ↔ f ∉ I.asIdeal := by
rw [Set.mem_compl_iff, mem_zeroLocus, Set.singleton_subset_iff]; rfl
#align prime_spectrum.mem_compl_zero_locus_iff_not_mem PrimeSpectrum.mem_compl_zeroLocus_iff_not_mem
/-- The Zariski topology on the prime spectrum of a commutative (semi)ring is defined
via the closed sets of the topology: they are exactly those sets that are the zero locus
of a subset of the ring. -/
instance zariskiTopology : TopologicalSpace (PrimeSpectrum R) :=
TopologicalSpace.ofClosed (Set.range PrimeSpectrum.zeroLocus) ⟨Set.univ, by simp⟩
(by
intro Zs h
rw [Set.sInter_eq_iInter]
choose f hf using fun i : Zs => h i.prop
simp only [← hf]
exact ⟨_, zeroLocus_iUnion _⟩)
(by
rintro _ ⟨s, rfl⟩ _ ⟨t, rfl⟩
exact ⟨_, (union_zeroLocus s t).symm⟩)
#align prime_spectrum.zariski_topology PrimeSpectrum.zariskiTopology
theorem isOpen_iff (U : Set (PrimeSpectrum R)) : IsOpen U ↔ ∃ s, Uᶜ = zeroLocus s := by
simp only [@eq_comm _ Uᶜ]; rfl
#align prime_spectrum.is_open_iff PrimeSpectrum.isOpen_iff
theorem isClosed_iff_zeroLocus (Z : Set (PrimeSpectrum R)) : IsClosed Z ↔ ∃ s, Z = zeroLocus s := by
rw [← isOpen_compl_iff, isOpen_iff, compl_compl]
#align prime_spectrum.is_closed_iff_zero_locus PrimeSpectrum.isClosed_iff_zeroLocus
theorem isClosed_iff_zeroLocus_ideal (Z : Set (PrimeSpectrum R)) :
IsClosed Z ↔ ∃ I : Ideal R, Z = zeroLocus I :=
(isClosed_iff_zeroLocus _).trans
⟨fun ⟨s, hs⟩ => ⟨_, (zeroLocus_span s).substr hs⟩, fun ⟨I, hI⟩ => ⟨I, hI⟩⟩
#align prime_spectrum.is_closed_iff_zero_locus_ideal PrimeSpectrum.isClosed_iff_zeroLocus_ideal
theorem isClosed_iff_zeroLocus_radical_ideal (Z : Set (PrimeSpectrum R)) :
IsClosed Z ↔ ∃ I : Ideal R, I.IsRadical ∧ Z = zeroLocus I :=
(isClosed_iff_zeroLocus_ideal _).trans
⟨fun ⟨I, hI⟩ => ⟨_, I.radical_isRadical, (zeroLocus_radical I).substr hI⟩, fun ⟨I, _, hI⟩ =>
⟨I, hI⟩⟩
#align prime_spectrum.is_closed_iff_zero_locus_radical_ideal PrimeSpectrum.isClosed_iff_zeroLocus_radical_ideal
theorem isClosed_zeroLocus (s : Set R) : IsClosed (zeroLocus s) := by
rw [isClosed_iff_zeroLocus]
exact ⟨s, rfl⟩
#align prime_spectrum.is_closed_zero_locus PrimeSpectrum.isClosed_zeroLocus
theorem zeroLocus_vanishingIdeal_eq_closure (t : Set (PrimeSpectrum R)) :
zeroLocus (vanishingIdeal t : Set R) = closure t := by
rcases isClosed_iff_zeroLocus (closure t) |>.mp isClosed_closure with ⟨I, hI⟩
rw [subset_antisymm_iff, (isClosed_zeroLocus _).closure_subset_iff, hI,
subset_zeroLocus_iff_subset_vanishingIdeal, (gc R).u_l_u_eq_u,
← subset_zeroLocus_iff_subset_vanishingIdeal, ← hI]
exact ⟨subset_closure, subset_zeroLocus_vanishingIdeal t⟩
#align prime_spectrum.zero_locus_vanishing_ideal_eq_closure PrimeSpectrum.zeroLocus_vanishingIdeal_eq_closure
theorem vanishingIdeal_closure (t : Set (PrimeSpectrum R)) :
vanishingIdeal (closure t) = vanishingIdeal t :=
zeroLocus_vanishingIdeal_eq_closure t ▸ (gc R).u_l_u_eq_u t
#align prime_spectrum.vanishing_ideal_closure PrimeSpectrum.vanishingIdeal_closure
theorem closure_singleton (x) : closure ({x} : Set (PrimeSpectrum R)) = zeroLocus x.asIdeal := by
rw [← zeroLocus_vanishingIdeal_eq_closure, vanishingIdeal_singleton]
#align prime_spectrum.closure_singleton PrimeSpectrum.closure_singleton
theorem isClosed_singleton_iff_isMaximal (x : PrimeSpectrum R) :
IsClosed ({x} : Set (PrimeSpectrum R)) ↔ x.asIdeal.IsMaximal := by
rw [← closure_subset_iff_isClosed, ← zeroLocus_vanishingIdeal_eq_closure,
vanishingIdeal_singleton]
constructor <;> intro H
· rcases x.asIdeal.exists_le_maximal x.2.1 with ⟨m, hm, hxm⟩
exact (congr_arg asIdeal (@H ⟨m, hm.isPrime⟩ hxm)) ▸ hm
· exact fun p hp ↦ PrimeSpectrum.ext _ _ (H.eq_of_le p.2.1 hp).symm
#align prime_spectrum.is_closed_singleton_iff_is_maximal PrimeSpectrum.isClosed_singleton_iff_isMaximal
theorem isRadical_vanishingIdeal (s : Set (PrimeSpectrum R)) : (vanishingIdeal s).IsRadical := by
rw [← vanishingIdeal_closure, ← zeroLocus_vanishingIdeal_eq_closure,
vanishingIdeal_zeroLocus_eq_radical]
apply Ideal.radical_isRadical
#align prime_spectrum.is_radical_vanishing_ideal PrimeSpectrum.isRadical_vanishingIdeal
theorem vanishingIdeal_anti_mono_iff {s t : Set (PrimeSpectrum R)} (ht : IsClosed t) :
s ⊆ t ↔ vanishingIdeal t ≤ vanishingIdeal s :=
⟨vanishingIdeal_anti_mono, fun h => by
rw [← ht.closure_subset_iff, ← ht.closure_eq]
convert ← zeroLocus_anti_mono_ideal h <;> apply zeroLocus_vanishingIdeal_eq_closure⟩
#align prime_spectrum.vanishing_ideal_anti_mono_iff PrimeSpectrum.vanishingIdeal_anti_mono_iff
theorem vanishingIdeal_strict_anti_mono_iff {s t : Set (PrimeSpectrum R)} (hs : IsClosed s)
(ht : IsClosed t) : s ⊂ t ↔ vanishingIdeal t < vanishingIdeal s := by
rw [Set.ssubset_def, vanishingIdeal_anti_mono_iff hs, vanishingIdeal_anti_mono_iff ht,
lt_iff_le_not_le]
#align prime_spectrum.vanishing_ideal_strict_anti_mono_iff PrimeSpectrum.vanishingIdeal_strict_anti_mono_iff
/-- The antitone order embedding of closed subsets of `Spec R` into ideals of `R`. -/
def closedsEmbedding (R : Type*) [CommSemiring R] :
(TopologicalSpace.Closeds <| PrimeSpectrum R)ᵒᵈ ↪o Ideal R :=
OrderEmbedding.ofMapLEIff (fun s => vanishingIdeal ↑(OrderDual.ofDual s)) fun s _ =>
(vanishingIdeal_anti_mono_iff s.2).symm
#align prime_spectrum.closeds_embedding PrimeSpectrum.closedsEmbedding
theorem t1Space_iff_isField [IsDomain R] : T1Space (PrimeSpectrum R) ↔ IsField R := by
refine ⟨?_, fun h => ?_⟩
· intro h
have hbot : Ideal.IsPrime (⊥ : Ideal R) := Ideal.bot_prime
exact
Classical.not_not.1
(mt
(Ring.ne_bot_of_isMaximal_of_not_isField <|
(isClosed_singleton_iff_isMaximal _).1 (T1Space.t1 ⟨⊥, hbot⟩))
(by aesop))
· refine ⟨fun x => (isClosed_singleton_iff_isMaximal x).2 ?_⟩
by_cases hx : x.asIdeal = ⊥
· letI := h.toSemifield
exact hx.symm ▸ Ideal.bot_isMaximal
· exact absurd h (Ring.not_isField_iff_exists_prime.2 ⟨x.asIdeal, ⟨hx, x.2⟩⟩)
#align prime_spectrum.t1_space_iff_is_field PrimeSpectrum.t1Space_iff_isField
local notation "Z(" a ")" => zeroLocus (a : Set R)
theorem isIrreducible_zeroLocus_iff_of_radical (I : Ideal R) (hI : I.IsRadical) :
IsIrreducible (zeroLocus (I : Set R)) ↔ I.IsPrime := by
rw [Ideal.isPrime_iff, IsIrreducible]
apply and_congr
· rw [Set.nonempty_iff_ne_empty, Ne, zeroLocus_empty_iff_eq_top]
· trans ∀ x y : Ideal R, Z(I) ⊆ Z(x) ∪ Z(y) → Z(I) ⊆ Z(x) ∨ Z(I) ⊆ Z(y)
· simp_rw [isPreirreducible_iff_closed_union_closed, isClosed_iff_zeroLocus_ideal]
constructor
· rintro h x y
exact h _ _ ⟨x, rfl⟩ ⟨y, rfl⟩
· rintro h _ _ ⟨x, rfl⟩ ⟨y, rfl⟩
exact h x y
· simp_rw [← zeroLocus_inf, subset_zeroLocus_iff_le_vanishingIdeal,
vanishingIdeal_zeroLocus_eq_radical, hI.radical]
constructor
· simp_rw [← SetLike.mem_coe, ← Set.singleton_subset_iff, ← Ideal.span_le, ←
Ideal.span_singleton_mul_span_singleton]
refine fun h x y h' => h _ _ ?_
rw [← hI.radical_le_iff] at h' ⊢
simpa only [Ideal.radical_inf, Ideal.radical_mul] using h'
· simp_rw [or_iff_not_imp_left, SetLike.not_le_iff_exists]
rintro h s t h' ⟨x, hx, hx'⟩ y hy
exact h (h' ⟨Ideal.mul_mem_right _ _ hx, Ideal.mul_mem_left _ _ hy⟩) hx'
#align prime_spectrum.is_irreducible_zero_locus_iff_of_radical PrimeSpectrum.isIrreducible_zeroLocus_iff_of_radical
theorem isIrreducible_zeroLocus_iff (I : Ideal R) :
IsIrreducible (zeroLocus (I : Set R)) ↔ I.radical.IsPrime :=
zeroLocus_radical I ▸ isIrreducible_zeroLocus_iff_of_radical _ I.radical_isRadical
#align prime_spectrum.is_irreducible_zero_locus_iff PrimeSpectrum.isIrreducible_zeroLocus_iff
theorem isIrreducible_iff_vanishingIdeal_isPrime {s : Set (PrimeSpectrum R)} :
IsIrreducible s ↔ (vanishingIdeal s).IsPrime := by
rw [← isIrreducible_iff_closure, ← zeroLocus_vanishingIdeal_eq_closure,
isIrreducible_zeroLocus_iff_of_radical _ (isRadical_vanishingIdeal s)]
#align prime_spectrum.is_irreducible_iff_vanishing_ideal_is_prime PrimeSpectrum.isIrreducible_iff_vanishingIdeal_isPrime
lemma vanishingIdeal_isIrreducible :
vanishingIdeal (R := R) '' {s | IsIrreducible s} = {P | P.IsPrime} :=
Set.ext fun I ↦ ⟨fun ⟨_, hs, e⟩ ↦ e ▸ isIrreducible_iff_vanishingIdeal_isPrime.mp hs,
fun h ↦ ⟨zeroLocus I, (isIrreducible_zeroLocus_iff_of_radical _ h.isRadical).mpr h,
(vanishingIdeal_zeroLocus_eq_radical I).trans h.radical⟩⟩
lemma vanishingIdeal_isClosed_isIrreducible :
vanishingIdeal (R := R) '' {s | IsClosed s ∧ IsIrreducible s} = {P | P.IsPrime} := by
refine (subset_antisymm ?_ ?_).trans vanishingIdeal_isIrreducible
· exact Set.image_subset _ fun _ ↦ And.right
rintro _ ⟨s, hs, rfl⟩
exact ⟨closure s, ⟨isClosed_closure, hs.closure⟩, vanishingIdeal_closure s⟩
instance irreducibleSpace [IsDomain R] : IrreducibleSpace (PrimeSpectrum R) := by
rw [irreducibleSpace_def, Set.top_eq_univ, ← zeroLocus_bot, isIrreducible_zeroLocus_iff]
simpa using Ideal.bot_prime
instance quasiSober : QuasiSober (PrimeSpectrum R) :=
⟨fun {S} h₁ h₂ =>
⟨⟨_, isIrreducible_iff_vanishingIdeal_isPrime.1 h₁⟩, by
rw [IsGenericPoint, closure_singleton, zeroLocus_vanishingIdeal_eq_closure, h₂.closure_eq]⟩⟩
/-- The prime spectrum of a commutative (semi)ring is a compact topological space. -/
instance compactSpace : CompactSpace (PrimeSpectrum R) := by
refine compactSpace_of_finite_subfamily_closed fun S S_closed S_empty ↦ ?_
choose I hI using fun i ↦ (isClosed_iff_zeroLocus_ideal (S i)).mp (S_closed i)
simp_rw [hI, ← zeroLocus_iSup, zeroLocus_empty_iff_eq_top, ← top_le_iff] at S_empty ⊢
exact Ideal.isCompactElement_top.exists_finset_of_le_iSup _ _ S_empty
section Comap
variable {S' : Type*} [CommSemiring S']
theorem preimage_comap_zeroLocus_aux (f : R →+* S) (s : Set R) :
(fun y => ⟨Ideal.comap f y.asIdeal, inferInstance⟩ : PrimeSpectrum S → PrimeSpectrum R) ⁻¹'
zeroLocus s =
zeroLocus (f '' s) := by
ext x
simp only [mem_zeroLocus, Set.image_subset_iff, Set.mem_preimage, mem_zeroLocus, Ideal.coe_comap]
#align prime_spectrum.preimage_comap_zero_locus_aux PrimeSpectrum.preimage_comap_zeroLocus_aux
/-- The function between prime spectra of commutative (semi)rings induced by a ring homomorphism.
This function is continuous. -/
def comap (f : R →+* S) : C(PrimeSpectrum S, PrimeSpectrum R) where
toFun y := ⟨Ideal.comap f y.asIdeal, inferInstance⟩
continuous_toFun := by
simp only [continuous_iff_isClosed, isClosed_iff_zeroLocus]
rintro _ ⟨s, rfl⟩
exact ⟨_, preimage_comap_zeroLocus_aux f s⟩
#align prime_spectrum.comap PrimeSpectrum.comap
variable (f : R →+* S)
@[simp]
theorem comap_asIdeal (y : PrimeSpectrum S) : (comap f y).asIdeal = Ideal.comap f y.asIdeal :=
rfl
#align prime_spectrum.comap_as_ideal PrimeSpectrum.comap_asIdeal
@[simp]
theorem comap_id : comap (RingHom.id R) = ContinuousMap.id _ := by
ext
rfl
#align prime_spectrum.comap_id PrimeSpectrum.comap_id
@[simp]
theorem comap_comp (f : R →+* S) (g : S →+* S') : comap (g.comp f) = (comap f).comp (comap g) :=
rfl
#align prime_spectrum.comap_comp PrimeSpectrum.comap_comp
theorem comap_comp_apply (f : R →+* S) (g : S →+* S') (x : PrimeSpectrum S') :
PrimeSpectrum.comap (g.comp f) x = (PrimeSpectrum.comap f) (PrimeSpectrum.comap g x) :=
rfl
#align prime_spectrum.comap_comp_apply PrimeSpectrum.comap_comp_apply
@[simp]
theorem preimage_comap_zeroLocus (s : Set R) : comap f ⁻¹' zeroLocus s = zeroLocus (f '' s) :=
preimage_comap_zeroLocus_aux f s
#align prime_spectrum.preimage_comap_zero_locus PrimeSpectrum.preimage_comap_zeroLocus
theorem comap_injective_of_surjective (f : R →+* S) (hf : Function.Surjective f) :
Function.Injective (comap f) := fun x y h =>
PrimeSpectrum.ext _ _
(Ideal.comap_injective_of_surjective f hf
(congr_arg PrimeSpectrum.asIdeal h : (comap f x).asIdeal = (comap f y).asIdeal))
#align prime_spectrum.comap_injective_of_surjective PrimeSpectrum.comap_injective_of_surjective
variable (S)
theorem localization_comap_inducing [Algebra R S] (M : Submonoid R) [IsLocalization M S] :
Inducing (comap (algebraMap R S)) := by
refine ⟨TopologicalSpace.ext_isClosed fun Z ↦ ?_⟩
simp_rw [isClosed_induced_iff, isClosed_iff_zeroLocus, @eq_comm _ _ (zeroLocus _),
exists_exists_eq_and, preimage_comap_zeroLocus]
constructor
· rintro ⟨s, rfl⟩
refine ⟨(Ideal.span s).comap (algebraMap R S), ?_⟩
rw [← zeroLocus_span, ← zeroLocus_span s, ← Ideal.map, IsLocalization.map_comap M S]
· rintro ⟨s, rfl⟩
exact ⟨_, rfl⟩
#align prime_spectrum.localization_comap_inducing PrimeSpectrum.localization_comap_inducing
theorem localization_comap_injective [Algebra R S] (M : Submonoid R) [IsLocalization M S] :
Function.Injective (comap (algebraMap R S)) := by
intro p q h
replace h := congr_arg (fun x : PrimeSpectrum R => Ideal.map (algebraMap R S) x.asIdeal) h
dsimp only [comap, ContinuousMap.coe_mk] at h
rw [IsLocalization.map_comap M S, IsLocalization.map_comap M S] at h
ext1
exact h
#align prime_spectrum.localization_comap_injective PrimeSpectrum.localization_comap_injective
theorem localization_comap_embedding [Algebra R S] (M : Submonoid R) [IsLocalization M S] :
Embedding (comap (algebraMap R S)) :=
⟨localization_comap_inducing S M, localization_comap_injective S M⟩
#align prime_spectrum.localization_comap_embedding PrimeSpectrum.localization_comap_embedding
theorem localization_comap_range [Algebra R S] (M : Submonoid R) [IsLocalization M S] :
Set.range (comap (algebraMap R S)) = { p | Disjoint (M : Set R) p.asIdeal } := by
ext x
constructor
· simp_rw [disjoint_iff_inf_le]
rintro ⟨p, rfl⟩ x ⟨hx₁, hx₂⟩
exact (p.2.1 : ¬_) (p.asIdeal.eq_top_of_isUnit_mem hx₂ (IsLocalization.map_units S ⟨x, hx₁⟩))
· intro h
use ⟨x.asIdeal.map (algebraMap R S), IsLocalization.isPrime_of_isPrime_disjoint M S _ x.2 h⟩
ext1
exact IsLocalization.comap_map_of_isPrime_disjoint M S _ x.2 h
#align prime_spectrum.localization_comap_range PrimeSpectrum.localization_comap_range
open Function RingHom
theorem comap_inducing_of_surjective (hf : Surjective f) : Inducing (comap f) where
induced := by
set_option tactic.skipAssignedInstances false in
simp_rw [TopologicalSpace.ext_iff, ← isClosed_compl_iff,
← @isClosed_compl_iff (PrimeSpectrum S)
((TopologicalSpace.induced (comap f) zariskiTopology)), isClosed_induced_iff,
isClosed_iff_zeroLocus]
refine fun s =>
⟨fun ⟨F, hF⟩ =>
⟨zeroLocus (f ⁻¹' F), ⟨f ⁻¹' F, rfl⟩, by
rw [preimage_comap_zeroLocus, Function.Surjective.image_preimage hf, hF]⟩,
?_⟩
rintro ⟨-, ⟨F, rfl⟩, hF⟩
exact ⟨f '' F, hF.symm.trans (preimage_comap_zeroLocus f F)⟩
#align prime_spectrum.comap_inducing_of_surjective PrimeSpectrum.comap_inducing_of_surjective
end Comap
end CommSemiRing
section SpecOfSurjective
/-! The comap of a surjective ring homomorphism is a closed embedding between the prime spectra. -/
open Function RingHom
variable [CommRing R] [CommRing S]
variable (f : R →+* S)
variable {R}
theorem comap_singleton_isClosed_of_surjective (f : R →+* S) (hf : Function.Surjective f)
(x : PrimeSpectrum S) (hx : IsClosed ({x} : Set (PrimeSpectrum S))) :
IsClosed ({comap f x} : Set (PrimeSpectrum R)) :=
haveI : x.asIdeal.IsMaximal := (isClosed_singleton_iff_isMaximal x).1 hx
(isClosed_singleton_iff_isMaximal _).2 (Ideal.comap_isMaximal_of_surjective f hf)
#align prime_spectrum.comap_singleton_is_closed_of_surjective PrimeSpectrum.comap_singleton_isClosed_of_surjective
theorem comap_singleton_isClosed_of_isIntegral (f : R →+* S) (hf : f.IsIntegral)
(x : PrimeSpectrum S) (hx : IsClosed ({x} : Set (PrimeSpectrum S))) :
IsClosed ({comap f x} : Set (PrimeSpectrum R)) :=
have := (isClosed_singleton_iff_isMaximal x).1 hx
(isClosed_singleton_iff_isMaximal _).2
(Ideal.isMaximal_comap_of_isIntegral_of_isMaximal' f hf x.asIdeal)
#align prime_spectrum.comap_singleton_is_closed_of_is_integral PrimeSpectrum.comap_singleton_isClosed_of_isIntegral
theorem image_comap_zeroLocus_eq_zeroLocus_comap (hf : Surjective f) (I : Ideal S) :
comap f '' zeroLocus I = zeroLocus (I.comap f) := by
simp only [Set.ext_iff, Set.mem_image, mem_zeroLocus, SetLike.coe_subset_coe]
refine fun p => ⟨?_, fun h_I_p => ?_⟩
· rintro ⟨p, hp, rfl⟩ a ha
exact hp ha
· have hp : ker f ≤ p.asIdeal := (Ideal.comap_mono bot_le).trans h_I_p
refine ⟨⟨p.asIdeal.map f, Ideal.map_isPrime_of_surjective hf hp⟩, fun x hx => ?_, ?_⟩
· obtain ⟨x', rfl⟩ := hf x
exact Ideal.mem_map_of_mem f (h_I_p hx)
· ext x
rw [comap_asIdeal, Ideal.mem_comap, Ideal.mem_map_iff_of_surjective f hf]
refine ⟨?_, fun hx => ⟨x, hx, rfl⟩⟩
rintro ⟨x', hx', heq⟩
rw [← sub_sub_cancel x' x]
refine p.asIdeal.sub_mem hx' (hp ?_)
rwa [mem_ker, map_sub, sub_eq_zero]
#align prime_spectrum.image_comap_zero_locus_eq_zero_locus_comap PrimeSpectrum.image_comap_zeroLocus_eq_zeroLocus_comap
| Mathlib/AlgebraicGeometry/PrimeSpectrum/Basic.lean | 748 | 752 | theorem range_comap_of_surjective (hf : Surjective f) :
Set.range (comap f) = zeroLocus (ker f) := by |
rw [← Set.image_univ]
convert image_comap_zeroLocus_eq_zeroLocus_comap _ _ hf _
rw [zeroLocus_bot]
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Analysis.NormedSpace.Multilinear.Curry
#align_import analysis.calculus.formal_multilinear_series from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Formal multilinear series
In this file we define `FormalMultilinearSeries 𝕜 E F` to be a family of `n`-multilinear maps for
all `n`, designed to model the sequence of derivatives of a function. In other files we use this
notion to define `C^n` functions (called `contDiff` in `mathlib`) and analytic functions.
## Notations
We use the notation `E [×n]→L[𝕜] F` for the space of continuous multilinear maps on `E^n` with
values in `F`. This is the space in which the `n`-th derivative of a function from `E` to `F` lives.
## Tags
multilinear, formal series
-/
noncomputable section
open Set Fin Topology
-- Porting note: added explicit universes to fix compile
universe u u' v w x
variable {𝕜 : Type u} {𝕜' : Type u'} {E : Type v} {F : Type w} {G : Type x}
section
variable [Ring 𝕜] [AddCommGroup E] [Module 𝕜 E] [TopologicalSpace E] [TopologicalAddGroup E]
[ContinuousConstSMul 𝕜 E] [AddCommGroup F] [Module 𝕜 F] [TopologicalSpace F]
[TopologicalAddGroup F] [ContinuousConstSMul 𝕜 F] [AddCommGroup G] [Module 𝕜 G]
[TopologicalSpace G] [TopologicalAddGroup G] [ContinuousConstSMul 𝕜 G]
/-- A formal multilinear series over a field `𝕜`, from `E` to `F`, is given by a family of
multilinear maps from `E^n` to `F` for all `n`. -/
@[nolint unusedArguments]
def FormalMultilinearSeries (𝕜 : Type*) (E : Type*) (F : Type*) [Ring 𝕜] [AddCommGroup E]
[Module 𝕜 E] [TopologicalSpace E] [TopologicalAddGroup E] [ContinuousConstSMul 𝕜 E]
[AddCommGroup F] [Module 𝕜 F] [TopologicalSpace F] [TopologicalAddGroup F]
[ContinuousConstSMul 𝕜 F] :=
∀ n : ℕ, E[×n]→L[𝕜] F
#align formal_multilinear_series FormalMultilinearSeries
-- Porting note: was `deriving`
instance : AddCommGroup (FormalMultilinearSeries 𝕜 E F) :=
inferInstanceAs <| AddCommGroup <| ∀ n : ℕ, E[×n]→L[𝕜] F
instance : Inhabited (FormalMultilinearSeries 𝕜 E F) :=
⟨0⟩
section Module
instance (𝕜') [Semiring 𝕜'] [Module 𝕜' F] [ContinuousConstSMul 𝕜' F] [SMulCommClass 𝕜 𝕜' F] :
Module 𝕜' (FormalMultilinearSeries 𝕜 E F) :=
inferInstanceAs <| Module 𝕜' <| ∀ n : ℕ, E[×n]→L[𝕜] F
end Module
namespace FormalMultilinearSeries
@[simp] -- Porting note (#10756): new theorem; was not needed in Lean 3
theorem zero_apply (n : ℕ) : (0 : FormalMultilinearSeries 𝕜 E F) n = 0 := rfl
@[simp] -- Porting note (#10756): new theorem; was not needed in Lean 3
theorem neg_apply (f : FormalMultilinearSeries 𝕜 E F) (n : ℕ) : (-f) n = - f n := rfl
@[ext] -- Porting note (#10756): new theorem
protected theorem ext {p q : FormalMultilinearSeries 𝕜 E F} (h : ∀ n, p n = q n) : p = q :=
funext h
protected theorem ext_iff {p q : FormalMultilinearSeries 𝕜 E F} : p = q ↔ ∀ n, p n = q n :=
Function.funext_iff
#align formal_multilinear_series.ext_iff FormalMultilinearSeries.ext_iff
protected theorem ne_iff {p q : FormalMultilinearSeries 𝕜 E F} : p ≠ q ↔ ∃ n, p n ≠ q n :=
Function.ne_iff
#align formal_multilinear_series.ne_iff FormalMultilinearSeries.ne_iff
/-- Cartesian product of two formal multilinear series (with the same field `𝕜` and the same source
space, but possibly different target spaces). -/
def prod (p : FormalMultilinearSeries 𝕜 E F) (q : FormalMultilinearSeries 𝕜 E G) :
FormalMultilinearSeries 𝕜 E (F × G)
| n => (p n).prod (q n)
/-- Killing the zeroth coefficient in a formal multilinear series -/
def removeZero (p : FormalMultilinearSeries 𝕜 E F) : FormalMultilinearSeries 𝕜 E F
| 0 => 0
| n + 1 => p (n + 1)
#align formal_multilinear_series.remove_zero FormalMultilinearSeries.removeZero
@[simp]
theorem removeZero_coeff_zero (p : FormalMultilinearSeries 𝕜 E F) : p.removeZero 0 = 0 :=
rfl
#align formal_multilinear_series.remove_zero_coeff_zero FormalMultilinearSeries.removeZero_coeff_zero
@[simp]
theorem removeZero_coeff_succ (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
p.removeZero (n + 1) = p (n + 1) :=
rfl
#align formal_multilinear_series.remove_zero_coeff_succ FormalMultilinearSeries.removeZero_coeff_succ
theorem removeZero_of_pos (p : FormalMultilinearSeries 𝕜 E F) {n : ℕ} (h : 0 < n) :
p.removeZero n = p n := by
rw [← Nat.succ_pred_eq_of_pos h]
rfl
#align formal_multilinear_series.remove_zero_of_pos FormalMultilinearSeries.removeZero_of_pos
/-- Convenience congruence lemma stating in a dependent setting that, if the arguments to a formal
multilinear series are equal, then the values are also equal. -/
| Mathlib/Analysis/Calculus/FormalMultilinearSeries.lean | 119 | 124 | theorem congr (p : FormalMultilinearSeries 𝕜 E F) {m n : ℕ} {v : Fin m → E} {w : Fin n → E}
(h1 : m = n) (h2 : ∀ (i : ℕ) (him : i < m) (hin : i < n), v ⟨i, him⟩ = w ⟨i, hin⟩) :
p m v = p n w := by |
subst n
congr with ⟨i, hi⟩
exact h2 i hi hi
|
/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.AlgebraicGeometry.Morphisms.Basic
import Mathlib.RingTheory.LocalProperties
#align_import algebraic_geometry.morphisms.ring_hom_properties from "leanprover-community/mathlib"@"d39590fc8728fbf6743249802486f8c91ffe07bc"
/-!
# Properties of morphisms from properties of ring homs.
We provide the basic framework for talking about properties of morphisms that come from properties
of ring homs. For `P` a property of ring homs, we have two ways of defining a property of scheme
morphisms:
Let `f : X ⟶ Y`,
- `targetAffineLocally (affine_and P)`: the preimage of an affine open `U = Spec A` is affine
(`= Spec B`) and `A ⟶ B` satisfies `P`. (TODO)
- `affineLocally P`: For each pair of affine open `U = Spec A ⊆ X` and `V = Spec B ⊆ f ⁻¹' U`,
the ring hom `A ⟶ B` satisfies `P`.
For these notions to be well defined, we require `P` be a sufficient local property. For the former,
`P` should be local on the source (`RingHom.RespectsIso P`, `RingHom.LocalizationPreserves P`,
`RingHom.OfLocalizationSpan`), and `targetAffineLocally (affine_and P)` will be local on
the target. (TODO)
For the latter `P` should be local on the target (`RingHom.PropertyIsLocal P`), and
`affineLocally P` will be local on both the source and the target.
Further more, these properties are stable under compositions (resp. base change) if `P` is. (TODO)
-/
-- Explicit universe annotations were used in this file to improve perfomance #12737
universe u
open CategoryTheory Opposite TopologicalSpace CategoryTheory.Limits AlgebraicGeometry
variable (P : ∀ {R S : Type u} [CommRing R] [CommRing S], (R →+* S) → Prop)
namespace RingHom
variable {P}
theorem RespectsIso.basicOpen_iff (hP : RespectsIso @P) {X Y : Scheme.{u}} [IsAffine X] [IsAffine Y]
(f : X ⟶ Y) (r : Y.presheaf.obj (Opposite.op ⊤)) :
P (Scheme.Γ.map (f ∣_ Y.basicOpen r).op) ↔
P (@IsLocalization.Away.map (Y.presheaf.obj (Opposite.op ⊤)) _
(Y.presheaf.obj (Opposite.op <| Y.basicOpen r)) _ _ (X.presheaf.obj (Opposite.op ⊤)) _
(X.presheaf.obj (Opposite.op <| X.basicOpen (Scheme.Γ.map f.op r))) _ _
(Scheme.Γ.map f.op) r _ <| @isLocalization_away_of_isAffine X _ (Scheme.Γ.map f.op r)) := by
rw [Γ_map_morphismRestrict, hP.cancel_left_isIso, hP.cancel_right_isIso,
← hP.cancel_right_isIso (f.val.c.app (Opposite.op (Y.basicOpen r)))
(X.presheaf.map (eqToHom (Scheme.preimage_basicOpen f r).symm).op), ← eq_iff_iff]
congr
delta IsLocalization.Away.map
refine IsLocalization.ringHom_ext (Submonoid.powers r) ?_
generalize_proofs
haveI i1 := @isLocalization_away_of_isAffine X _ (Scheme.Γ.map f.op r)
-- Porting note: needs to be very explicit here
convert
(@IsLocalization.map_comp (hy := ‹_ ≤ _›) (Y.presheaf.obj <| Opposite.op (Scheme.basicOpen Y r))
_ _ (isLocalization_away_of_isAffine _) _ _ _ i1).symm using 1
change Y.presheaf.map _ ≫ _ = _ ≫ X.presheaf.map _
rw [f.val.c.naturality_assoc]
simp only [TopCat.Presheaf.pushforwardObj_map, ← X.presheaf.map_comp]
congr 1
#align ring_hom.respects_iso.basic_open_iff RingHom.RespectsIso.basicOpen_iff
theorem RespectsIso.basicOpen_iff_localization (hP : RespectsIso @P) {X Y : Scheme.{u}} [IsAffine X]
[IsAffine Y] (f : X ⟶ Y) (r : Y.presheaf.obj (Opposite.op ⊤)) :
P (Scheme.Γ.map (f ∣_ Y.basicOpen r).op) ↔ P (Localization.awayMap (Scheme.Γ.map f.op) r) := by
refine (hP.basicOpen_iff _ _).trans ?_
-- Porting note: was a one line term mode proof, but this `dsimp` is vital so the term mode
-- one liner is not possible
dsimp
rw [← hP.is_localization_away_iff]
#align ring_hom.respects_iso.basic_open_iff_localization RingHom.RespectsIso.basicOpen_iff_localization
@[deprecated (since := "2024-03-02")] alias
RespectsIso.ofRestrict_morphismRestrict_iff_of_isAffine := RespectsIso.basicOpen_iff_localization
theorem RespectsIso.ofRestrict_morphismRestrict_iff (hP : RingHom.RespectsIso @P) {X Y : Scheme.{u}}
[IsAffine Y] (f : X ⟶ Y) (r : Y.presheaf.obj (Opposite.op ⊤)) (U : Opens X.carrier)
(hU : IsAffineOpen U) {V : Opens _}
(e : V = (Scheme.ιOpens <| f ⁻¹ᵁ Y.basicOpen r) ⁻¹ᵁ U) :
P (Scheme.Γ.map (Scheme.ιOpens V ≫ f ∣_ Y.basicOpen r).op) ↔
P (Localization.awayMap (Scheme.Γ.map (Scheme.ιOpens U ≫ f).op) r) := by
subst e
refine (hP.cancel_right_isIso _
(Scheme.Γ.mapIso (Scheme.restrictRestrictComm _ _ _).op).inv).symm.trans ?_
haveI : IsAffine _ := hU
rw [← hP.basicOpen_iff_localization, iff_iff_eq]
congr 1
simp only [Functor.mapIso_inv, Iso.op_inv, ← Functor.map_comp, ← op_comp, morphismRestrict_comp]
rw [← Category.assoc]
congr 3
rw [← cancel_mono (Scheme.ιOpens _), Category.assoc, Scheme.restrictRestrictComm,
IsOpenImmersion.isoOfRangeEq_inv_fac, morphismRestrict_ι]
#align ring_hom.respects_iso.of_restrict_morphism_restrict_iff RingHom.RespectsIso.ofRestrict_morphismRestrict_iff
theorem StableUnderBaseChange.Γ_pullback_fst (hP : StableUnderBaseChange @P) (hP' : RespectsIso @P)
{X Y S : Scheme} [IsAffine X] [IsAffine Y] [IsAffine S] (f : X ⟶ S) (g : Y ⟶ S)
(H : P (Scheme.Γ.map g.op)) : P (Scheme.Γ.map (pullback.fst : pullback f g ⟶ _).op) := by
-- Porting note (#11224): change `rw` to `erw`
erw [← PreservesPullback.iso_inv_fst AffineScheme.forgetToScheme (AffineScheme.ofHom f)
(AffineScheme.ofHom g)]
rw [op_comp, Functor.map_comp, hP'.cancel_right_isIso, AffineScheme.forgetToScheme_map]
have :=
_root_.congr_arg Quiver.Hom.unop
(PreservesPullback.iso_hom_fst AffineScheme.Γ.rightOp (AffineScheme.ofHom f)
(AffineScheme.ofHom g))
simp only [Quiver.Hom.unop_op, Functor.rightOp_map, unop_comp] at this
delta AffineScheme.Γ at this
simp only [Quiver.Hom.unop_op, Functor.comp_map, AffineScheme.forgetToScheme_map,
Functor.op_map] at this
rw [← this, hP'.cancel_right_isIso,
← pushoutIsoUnopPullback_inl_hom (Quiver.Hom.unop _) (Quiver.Hom.unop _),
hP'.cancel_right_isIso]
exact hP.pushout_inl _ hP' _ _ H
#align ring_hom.stable_under_base_change.Γ_pullback_fst RingHom.StableUnderBaseChange.Γ_pullback_fst
end RingHom
namespace AlgebraicGeometry
/-- For `P` a property of ring homomorphisms, `sourceAffineLocally P` holds for `f : X ⟶ Y`
whenever `P` holds for the restriction of `f` on every affine open subset of `X`. -/
def sourceAffineLocally : AffineTargetMorphismProperty := fun X _ f _ =>
∀ U : X.affineOpens, P (Scheme.Γ.map (X.ofRestrict U.1.openEmbedding ≫ f).op)
#align algebraic_geometry.source_affine_locally AlgebraicGeometry.sourceAffineLocally
/-- For `P` a property of ring homomorphisms, `affineLocally P` holds for `f : X ⟶ Y` if for each
affine open `U = Spec A ⊆ Y` and `V = Spec B ⊆ f ⁻¹' U`, the ring hom `A ⟶ B` satisfies `P`.
Also see `affineLocally_iff_affineOpens_le`. -/
abbrev affineLocally : MorphismProperty Scheme.{u} :=
targetAffineLocally (sourceAffineLocally @P)
#align algebraic_geometry.affine_locally AlgebraicGeometry.affineLocally
variable {P}
theorem sourceAffineLocally_respectsIso (h₁ : RingHom.RespectsIso @P) :
(sourceAffineLocally @P).toProperty.RespectsIso := by
apply AffineTargetMorphismProperty.respectsIso_mk
· introv H U
rw [← h₁.cancel_right_isIso _ (Scheme.Γ.map (Scheme.restrictMapIso e.inv U.1).hom.op), ←
Functor.map_comp, ← op_comp]
convert H ⟨_, U.prop.map_isIso e.inv⟩ using 3
rw [IsOpenImmersion.isoOfRangeEq_hom_fac_assoc, Category.assoc,
e.inv_hom_id_assoc]
· introv H U
rw [← Category.assoc, op_comp, Functor.map_comp, h₁.cancel_left_isIso]
exact H U
#align algebraic_geometry.source_affine_locally_respects_iso AlgebraicGeometry.sourceAffineLocally_respectsIso
theorem affineLocally_respectsIso (h : RingHom.RespectsIso @P) : (affineLocally @P).RespectsIso :=
targetAffineLocally_respectsIso (sourceAffineLocally_respectsIso h)
#align algebraic_geometry.affine_locally_respects_iso AlgebraicGeometry.affineLocally_respectsIso
theorem affineLocally_iff_affineOpens_le
(hP : RingHom.RespectsIso @P) {X Y : Scheme.{u}} (f : X ⟶ Y) :
affineLocally.{u} (@P) f ↔
∀ (U : Y.affineOpens) (V : X.affineOpens) (e : V.1 ≤ (Opens.map f.1.base).obj U.1),
P (Scheme.Hom.appLe f e) := by
apply forall_congr'
intro U
delta sourceAffineLocally
simp_rw [op_comp, Scheme.Γ.map_comp, Γ_map_morphismRestrict, Category.assoc, Scheme.Γ_map_op,
hP.cancel_left_isIso (Y.presheaf.map (eqToHom _).op)]
constructor
· intro H V e
let U' := (Opens.map f.val.base).obj U.1
have e'' : (Scheme.Hom.opensFunctor (X.ofRestrict U'.openEmbedding)).obj
(X.ofRestrict U'.openEmbedding⁻¹ᵁ V) = V := by
ext1; refine Set.image_preimage_eq_inter_range.trans (Set.inter_eq_left.mpr ?_)
erw [Subtype.range_val]
exact e
have h : X.ofRestrict U'.openEmbedding ⁻¹ᵁ ↑V ∈ Scheme.affineOpens (X.restrict _) := by
apply (X.ofRestrict U'.openEmbedding).isAffineOpen_iff_of_isOpenImmersion.mp
-- Porting note: was convert V.2
rw [e'']
convert V.2
have := H ⟨(Opens.map (X.ofRestrict U'.openEmbedding).1.base).obj V.1, h⟩
rw [← hP.cancel_right_isIso _ (X.presheaf.map (eqToHom _)), Category.assoc,
← X.presheaf.map_comp]
· dsimp; convert this using 1
congr 1
rw [X.presheaf.map_comp]
swap
· dsimp only [Functor.op, unop_op]
rw [Opens.openEmbedding_obj_top]
congr 1
exact e''.symm
· simp only [Scheme.ofRestrict_val_c_app, Scheme.restrict_presheaf_map, ← X.presheaf.map_comp]
congr 1
· intro H V
specialize H ⟨_, V.2.imageIsOpenImmersion (X.ofRestrict _)⟩ (Subtype.coe_image_subset _ _)
rw [← hP.cancel_right_isIso _ (X.presheaf.map (eqToHom _)), Category.assoc]
· convert H
simp only [Scheme.ofRestrict_val_c_app, Scheme.restrict_presheaf_map, ← X.presheaf.map_comp]
congr 1
· dsimp only [Functor.op, unop_op]; rw [Opens.openEmbedding_obj_top]
#align algebraic_geometry.affine_locally_iff_affine_opens_le AlgebraicGeometry.affineLocally_iff_affineOpens_le
theorem scheme_restrict_basicOpen_of_localizationPreserves (h₁ : RingHom.RespectsIso @P)
(h₂ : RingHom.LocalizationPreserves @P) {X Y : Scheme.{u}} [IsAffine Y] (f : X ⟶ Y)
(r : Y.presheaf.obj (op ⊤)) (H : sourceAffineLocally (@P) f)
(U : (X.restrict ((Opens.map f.1.base).obj <| Y.basicOpen r).openEmbedding).affineOpens) :
P (Scheme.Γ.map ((X.restrict ((Opens.map f.1.base).obj <|
Y.basicOpen r).openEmbedding).ofRestrict U.1.openEmbedding ≫ f ∣_ Y.basicOpen r).op) := by
specialize H ⟨_, U.2.imageIsOpenImmersion (X.ofRestrict _)⟩
letI i1 : Algebra (Y.presheaf.obj <| Opposite.op ⊤) (Localization.Away r) := Localization.algebra
exact (h₁.ofRestrict_morphismRestrict_iff f r
((Scheme.Hom.opensFunctor
(X.ofRestrict ((Opens.map f.1.base).obj <| Y.basicOpen r).openEmbedding)).obj U.1)
(IsAffineOpen.imageIsOpenImmersion U.2
(X.ofRestrict ((Opens.map f.1.base).obj <| Y.basicOpen r).openEmbedding))
(Opens.ext (Set.preimage_image_eq _ Subtype.coe_injective).symm)).mpr (h₂.away r H)
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.Scheme_restrict_basic_open_of_localization_preserves AlgebraicGeometry.scheme_restrict_basicOpen_of_localizationPreserves
theorem sourceAffineLocally_isLocal (h₁ : RingHom.RespectsIso @P)
(h₂ : RingHom.LocalizationPreserves @P) (h₃ : RingHom.OfLocalizationSpan @P) :
(sourceAffineLocally @P).IsLocal := by
constructor
· exact sourceAffineLocally_respectsIso h₁
· introv H U
apply scheme_restrict_basicOpen_of_localizationPreserves h₁ h₂; assumption
· introv hs hs' U
apply h₃ _ _ hs
intro r
have := hs' r ⟨(Opens.map (X.ofRestrict _).1.base).obj U.1, ?_⟩
· rwa [h₁.ofRestrict_morphismRestrict_iff] at this
· exact U.2
· rfl
· suffices ∀ (V) (_ : V = (Opens.map f.val.base).obj (Y.basicOpen r.val)),
IsAffineOpen ((Opens.map (X.ofRestrict V.openEmbedding).1.base).obj U.1) by
exact this _ rfl
intro V hV
rw [Scheme.preimage_basicOpen] at hV
subst hV
exact U.2.mapRestrictBasicOpen (Scheme.Γ.map f.op r.1)
#align algebraic_geometry.source_affine_locally_is_local AlgebraicGeometry.sourceAffineLocally_isLocal
variable (hP : RingHom.PropertyIsLocal @P)
theorem sourceAffineLocally_of_source_open_cover_aux (h₁ : RingHom.RespectsIso @P)
(h₃ : RingHom.OfLocalizationSpanTarget @P) {X Y : Scheme.{u}} (f : X ⟶ Y) (U : X.affineOpens)
(s : Set (X.presheaf.obj (op U.1))) (hs : Ideal.span s = ⊤)
(hs' : ∀ r : s, P (Scheme.Γ.map (Scheme.ιOpens (X.basicOpen r.1) ≫ f).op)) :
P (Scheme.Γ.map (Scheme.ιOpens U ≫ f).op) := by
apply_fun Ideal.map (X.presheaf.map (eqToHom U.1.openEmbedding_obj_top).op) at hs
rw [Ideal.map_span, Ideal.map_top] at hs
apply h₃.ofIsLocalization h₁ _ _ hs
rintro ⟨s, r, hr, hs⟩
refine ⟨_, _, _, @AlgebraicGeometry.Γ_restrict_isLocalization (X ∣_ᵤ U.1) U.2 s, ?_⟩
rw [RingHom.algebraMap_toAlgebra, ← CommRingCat.comp_eq_ring_hom_comp, ← Functor.map_comp,
← op_comp, ← h₁.cancel_right_isIso _ (Scheme.Γ.mapIso (Scheme.restrictRestrict _ _ _).op).inv]
subst hs
rw [← h₁.cancel_right_isIso _
(Scheme.Γ.mapIso (Scheme.restrictIsoOfEq _ (Scheme.map_basicOpen_map _ _ _)).op).inv]
simp only [Functor.mapIso_inv, Iso.op_inv, ← Functor.map_comp, ← op_comp,
Scheme.restrictRestrict_inv_restrict_restrict_assoc, Scheme.restrictIsoOfEq,
IsOpenImmersion.isoOfRangeEq_inv_fac_assoc]
exact hs' ⟨r, hr⟩
#align algebraic_geometry.source_affine_locally_of_source_open_cover_aux AlgebraicGeometry.sourceAffineLocally_of_source_open_cover_aux
theorem isOpenImmersionCat_comp_of_sourceAffineLocally (h₁ : RingHom.RespectsIso @P)
{X Y Z : Scheme.{u}} [IsAffine X] [IsAffine Z] (f : X ⟶ Y) [IsOpenImmersion f] (g : Y ⟶ Z)
(h₂ : sourceAffineLocally (@P) g) : P (Scheme.Γ.map (f ≫ g).op) := by
rw [← h₁.cancel_right_isIso _
(Scheme.Γ.map (IsOpenImmersion.isoOfRangeEq (Y.ofRestrict _) f _).hom.op),
← Functor.map_comp, ← op_comp]
· convert h₂ ⟨_, rangeIsAffineOpenOfOpenImmersion f⟩ using 3
· rw [IsOpenImmersion.isoOfRangeEq_hom_fac_assoc]
exact Subtype.range_coe
#align algebraic_geometry.is_open_immersion_comp_of_source_affine_locally AlgebraicGeometry.isOpenImmersionCat_comp_of_sourceAffineLocally
end AlgebraicGeometry
open AlgebraicGeometry
namespace RingHom.PropertyIsLocal
variable {P} (hP : RingHom.PropertyIsLocal @P)
theorem sourceAffineLocally_of_source_openCover {X Y : Scheme.{u}} (f : X ⟶ Y) [IsAffine Y]
(𝒰 : X.OpenCover) [∀ i, IsAffine (𝒰.obj i)] (H : ∀ i, P (Scheme.Γ.map (𝒰.map i ≫ f).op)) :
sourceAffineLocally (@P) f := by
let S i := (⟨⟨Set.range (𝒰.map i).1.base, (𝒰.IsOpen i).base_open.isOpen_range⟩,
rangeIsAffineOpenOfOpenImmersion (𝒰.map i)⟩ : X.affineOpens)
intro U
-- Porting note: here is what we are eliminating into Lean
apply of_affine_open_cover
(P := fun V => P (Scheme.Γ.map (X.ofRestrict (Opens.openEmbedding V.val) ≫ f).op)) U
pick_goal 5
· exact Set.range S
· intro U r H
-- Porting note: failing on instance synthesis for an (unspecified) meta variable
-- made φ explicit and forced to use dsimp in the proof
convert hP.StableUnderComposition
(S := Scheme.Γ.obj (Opposite.op (X.restrict <| Opens.openEmbedding U.val)))
(T := Scheme.Γ.obj (Opposite.op (X.restrict <| Opens.openEmbedding (X.basicOpen r))))
?_ ?_ H ?_ using 1
swap
· refine X.presheaf.map
(@homOfLE _ _ ((IsOpenMap.functor _).obj _) ((IsOpenMap.functor _).obj _) ?_).op
dsimp
rw [Opens.openEmbedding_obj_top, Opens.openEmbedding_obj_top]
exact X.basicOpen_le _
· rw [op_comp, op_comp, Functor.map_comp, Functor.map_comp]
refine (Eq.trans ?_ (Category.assoc (obj := CommRingCat) _ _ _).symm : _)
congr 1
dsimp
refine Eq.trans ?_ (X.presheaf.map_comp _ _)
change X.presheaf.map _ = _
congr!
-- Porting note: need to pass Algebra through explicitly
convert @HoldsForLocalizationAway _ hP _
(Scheme.Γ.obj (Opposite.op (X.restrict (X.basicOpen r).openEmbedding))) _ _ ?_
(X.presheaf.map (eqToHom U.1.openEmbedding_obj_top).op r) ?_
· exact RingHom.algebraMap_toAlgebra
(R := Scheme.Γ.obj <| Opposite.op <| X.restrict (U.1.openEmbedding))
(S :=
Scheme.Γ.obj (Opposite.op <| X.restrict (X.affineBasicOpen r).1.openEmbedding)) _|>.symm
· dsimp [Scheme.Γ]
have := U.2
rw [← U.1.openEmbedding_obj_top] at this
-- Porting note: the second argument of `IsLocalization.Away` is a type, and we want
-- to generate an equality, so using `typeEqs := true` to force allowing type equalities.
convert (config := {typeEqs := true, transparency := .default})
this.isLocalization_basicOpen _ using 5
all_goals rw [Opens.openEmbedding_obj_top]; exact (Scheme.basicOpen_res_eq _ _ _).symm
· introv hs hs'
exact sourceAffineLocally_of_source_open_cover_aux hP.respectsIso hP.2 _ _ _ hs hs'
· rw [Set.eq_univ_iff_forall]
intro x
rw [Set.mem_iUnion]
exact ⟨⟨_, 𝒰.f x, rfl⟩, 𝒰.Covers x⟩
· rintro ⟨_, i, rfl⟩
specialize H i
rw [← hP.respectsIso.cancel_right_isIso _
(Scheme.Γ.map
(IsOpenImmersion.isoOfRangeEq (𝒰.map i) (X.ofRestrict (S i).1.openEmbedding)
Subtype.range_coe.symm).inv.op)] at H
rwa [← Scheme.Γ.map_comp, ← op_comp, IsOpenImmersion.isoOfRangeEq_inv_fac_assoc] at H
#align ring_hom.property_is_local.source_affine_locally_of_source_open_cover RingHom.PropertyIsLocal.sourceAffineLocally_of_source_openCover
theorem affine_openCover_TFAE {X Y : Scheme.{u}} [IsAffine Y] (f : X ⟶ Y) :
List.TFAE
[sourceAffineLocally (@P) f,
∃ (𝒰 : Scheme.OpenCover.{u} X) (_ : ∀ i, IsAffine (𝒰.obj i)),
∀ i : 𝒰.J, P (Scheme.Γ.map (𝒰.map i ≫ f).op),
∀ (𝒰 : Scheme.OpenCover.{u} X) [∀ i, IsAffine (𝒰.obj i)] (i : 𝒰.J),
P (Scheme.Γ.map (𝒰.map i ≫ f).op),
∀ {U : Scheme} (g : U ⟶ X) [IsAffine U] [IsOpenImmersion g],
P (Scheme.Γ.map (g ≫ f).op)] := by
tfae_have 1 → 4
· intro H U g _ hg
specialize H ⟨⟨_, hg.base_open.isOpen_range⟩, rangeIsAffineOpenOfOpenImmersion g⟩
rw [← hP.respectsIso.cancel_right_isIso _ (Scheme.Γ.map (IsOpenImmersion.isoOfRangeEq g
(X.ofRestrict (Opens.openEmbedding ⟨_, hg.base_open.isOpen_range⟩))
Subtype.range_coe.symm).hom.op),
← Scheme.Γ.map_comp, ← op_comp, IsOpenImmersion.isoOfRangeEq_hom_fac_assoc] at H
exact H
tfae_have 4 → 3
· intro H 𝒰 _ i; apply H
tfae_have 3 → 2
· intro H; exact ⟨X.affineCover, inferInstance, H _⟩
tfae_have 2 → 1
· rintro ⟨𝒰, _, h𝒰⟩
exact sourceAffineLocally_of_source_openCover hP f 𝒰 h𝒰
tfae_finish
#align ring_hom.property_is_local.affine_open_cover_tfae RingHom.PropertyIsLocal.affine_openCover_TFAE
theorem openCover_TFAE {X Y : Scheme.{u}} [IsAffine Y] (f : X ⟶ Y) :
List.TFAE
[sourceAffineLocally (@P) f,
∃ 𝒰 : Scheme.OpenCover.{u} X, ∀ i : 𝒰.J, sourceAffineLocally (@P) (𝒰.map i ≫ f),
∀ (𝒰 : Scheme.OpenCover.{u} X) (i : 𝒰.J), sourceAffineLocally (@P) (𝒰.map i ≫ f),
∀ {U : Scheme} (g : U ⟶ X) [IsOpenImmersion g], sourceAffineLocally (@P) (g ≫ f)] := by
tfae_have 1 → 4
· intro H U g hg V
-- Porting note: this has metavariable if I put it directly into rw
have := (hP.affine_openCover_TFAE f).out 0 3
rw [this] at H
haveI : IsAffine _ := V.2
rw [← Category.assoc]
-- Porting note: Lean could find this previously
have : IsOpenImmersion <| (Scheme.ofRestrict U (Opens.openEmbedding V.val)) ≫ g :=
LocallyRingedSpace.IsOpenImmersion.comp _ _
apply H
tfae_have 4 → 3
· intro H 𝒰 _ i; apply H
tfae_have 3 → 2
· intro H; exact ⟨X.affineCover, H _⟩
tfae_have 2 → 1
· rintro ⟨𝒰, h𝒰⟩
-- Porting note: this has metavariable if I put it directly into rw
have := (hP.affine_openCover_TFAE f).out 0 1
rw [this]
refine ⟨𝒰.bind fun _ => Scheme.affineCover _, ?_, ?_⟩
· intro i; dsimp; infer_instance
· intro i
specialize h𝒰 i.1
-- Porting note: this has metavariable if I put it directly into rw
have := (hP.affine_openCover_TFAE (𝒰.map i.fst ≫ f)).out 0 3
rw [this] at h𝒰
-- Porting note: this was discharged after the apply previously
have : IsAffine (Scheme.OpenCover.obj
(Scheme.OpenCover.bind 𝒰 fun x ↦ Scheme.affineCover (Scheme.OpenCover.obj 𝒰 x)) i) := by
dsimp; infer_instance
apply @h𝒰 _ (show _ from _)
tfae_finish
#align ring_hom.property_is_local.open_cover_tfae RingHom.PropertyIsLocal.openCover_TFAE
theorem sourceAffineLocally_comp_of_isOpenImmersion {X Y Z : Scheme.{u}} [IsAffine Z] (f : X ⟶ Y)
(g : Y ⟶ Z) [IsOpenImmersion f] (H : sourceAffineLocally (@P) g) :
sourceAffineLocally (@P) (f ≫ g) := by
-- Porting note: more tfae mis-behavior
have := (hP.openCover_TFAE g).out 0 3
apply this.mp H
#align ring_hom.property_is_local.source_affine_locally_comp_of_is_open_immersion RingHom.PropertyIsLocal.sourceAffineLocally_comp_of_isOpenImmersion
theorem source_affine_openCover_iff {X Y : Scheme.{u}} (f : X ⟶ Y) [IsAffine Y]
(𝒰 : Scheme.OpenCover.{u} X) [∀ i, IsAffine (𝒰.obj i)] :
sourceAffineLocally (@P) f ↔ ∀ i, P (Scheme.Γ.map (𝒰.map i ≫ f).op) := by
-- Porting note: seems like TFAE is misbehaving; this used to be pure term proof but
-- had strange failures where the output of TFAE turned into a metavariable when used despite
-- being correctly displayed in the infoview
refine ⟨fun H => ?_, fun H => ?_⟩
· have h := (hP.affine_openCover_TFAE f).out 0 2
apply h.mp
exact H
· have h := (hP.affine_openCover_TFAE f).out 1 0
apply h.mp
use 𝒰
#align ring_hom.property_is_local.source_affine_open_cover_iff RingHom.PropertyIsLocal.source_affine_openCover_iff
theorem isLocal_sourceAffineLocally : (sourceAffineLocally @P).IsLocal :=
sourceAffineLocally_isLocal hP.respectsIso hP.LocalizationPreserves
(@RingHom.PropertyIsLocal.ofLocalizationSpan _ hP)
#align ring_hom.property_is_local.is_local_source_affine_locally RingHom.PropertyIsLocal.isLocal_sourceAffineLocally
theorem is_local_affineLocally : PropertyIsLocalAtTarget (affineLocally @P) :=
hP.isLocal_sourceAffineLocally.targetAffineLocallyIsLocal
#align ring_hom.property_is_local.is_local_affine_locally RingHom.PropertyIsLocal.is_local_affineLocally
theorem affine_openCover_iff {X Y : Scheme.{u}} (f : X ⟶ Y) (𝒰 : Scheme.OpenCover.{u} Y)
[∀ i, IsAffine (𝒰.obj i)] (𝒰' : ∀ i, Scheme.OpenCover.{u} ((𝒰.pullbackCover f).obj i))
[∀ i j, IsAffine ((𝒰' i).obj j)] :
affineLocally (@P) f ↔ ∀ i j, P (Scheme.Γ.map ((𝒰' i).map j ≫ pullback.snd).op) :=
(hP.isLocal_sourceAffineLocally.affine_openCover_iff f 𝒰).trans
(forall_congr' fun i => hP.source_affine_openCover_iff _ (𝒰' i))
#align ring_hom.property_is_local.affine_open_cover_iff RingHom.PropertyIsLocal.affine_openCover_iff
| Mathlib/AlgebraicGeometry/Morphisms/RingHomProperties.lean | 460 | 479 | theorem source_openCover_iff {X Y : Scheme.{u}} (f : X ⟶ Y) (𝒰 : Scheme.OpenCover.{u} X) :
affineLocally (@P) f ↔ ∀ i, affineLocally (@P) (𝒰.map i ≫ f) := by |
constructor
· intro H i U
rw [morphismRestrict_comp]
apply hP.sourceAffineLocally_comp_of_isOpenImmersion
apply H
· intro H U
haveI : IsAffine _ := U.2
apply ((hP.openCover_TFAE (f ∣_ U.1)).out 1 0).mp
use 𝒰.pullbackCover (X.ofRestrict _)
intro i
specialize H i U
rw [morphismRestrict_comp] at H
delta morphismRestrict at H
have := sourceAffineLocally_respectsIso hP.respectsIso
rw [Category.assoc, affine_cancel_left_isIso this, ←
affine_cancel_left_isIso this (pullbackSymmetry _ _).hom,
pullbackSymmetry_hom_comp_snd_assoc] at H
exact H
|
/-
Copyright (c) 2022 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp
-/
import Mathlib.Analysis.InnerProductSpace.PiL2
import Mathlib.LinearAlgebra.Matrix.ZPow
#align_import linear_algebra.matrix.hermitian from "leanprover-community/mathlib"@"caa58cbf5bfb7f81ccbaca4e8b8ac4bc2b39cc1c"
/-! # Hermitian matrices
This file defines hermitian matrices and some basic results about them.
See also `IsSelfAdjoint`, which generalizes this definition to other star rings.
## Main definition
* `Matrix.IsHermitian` : a matrix `A : Matrix n n α` is hermitian if `Aᴴ = A`.
## Tags
self-adjoint matrix, hermitian matrix
-/
namespace Matrix
variable {α β : Type*} {m n : Type*} {A : Matrix n n α}
open scoped Matrix
local notation "⟪" x ", " y "⟫" => @inner α _ _ x y
section Star
variable [Star α] [Star β]
/-- A matrix is hermitian if it is equal to its conjugate transpose. On the reals, this definition
captures symmetric matrices. -/
def IsHermitian (A : Matrix n n α) : Prop := Aᴴ = A
#align matrix.is_hermitian Matrix.IsHermitian
instance (A : Matrix n n α) [Decidable (Aᴴ = A)] : Decidable (IsHermitian A) :=
inferInstanceAs <| Decidable (_ = _)
theorem IsHermitian.eq {A : Matrix n n α} (h : A.IsHermitian) : Aᴴ = A := h
#align matrix.is_hermitian.eq Matrix.IsHermitian.eq
protected theorem IsHermitian.isSelfAdjoint {A : Matrix n n α} (h : A.IsHermitian) :
IsSelfAdjoint A := h
#align matrix.is_hermitian.is_self_adjoint Matrix.IsHermitian.isSelfAdjoint
-- @[ext] -- Porting note: incorrect ext, not a structure or a lemma proving x = y
theorem IsHermitian.ext {A : Matrix n n α} : (∀ i j, star (A j i) = A i j) → A.IsHermitian := by
intro h; ext i j; exact h i j
#align matrix.is_hermitian.ext Matrix.IsHermitian.ext
theorem IsHermitian.apply {A : Matrix n n α} (h : A.IsHermitian) (i j : n) : star (A j i) = A i j :=
congr_fun (congr_fun h _) _
#align matrix.is_hermitian.apply Matrix.IsHermitian.apply
theorem IsHermitian.ext_iff {A : Matrix n n α} : A.IsHermitian ↔ ∀ i j, star (A j i) = A i j :=
⟨IsHermitian.apply, IsHermitian.ext⟩
#align matrix.is_hermitian.ext_iff Matrix.IsHermitian.ext_iff
@[simp]
theorem IsHermitian.map {A : Matrix n n α} (h : A.IsHermitian) (f : α → β)
(hf : Function.Semiconj f star star) : (A.map f).IsHermitian :=
(conjTranspose_map f hf).symm.trans <| h.eq.symm ▸ rfl
#align matrix.is_hermitian.map Matrix.IsHermitian.map
theorem IsHermitian.transpose {A : Matrix n n α} (h : A.IsHermitian) : Aᵀ.IsHermitian := by
rw [IsHermitian, conjTranspose, transpose_map]
exact congr_arg Matrix.transpose h
#align matrix.is_hermitian.transpose Matrix.IsHermitian.transpose
@[simp]
theorem isHermitian_transpose_iff (A : Matrix n n α) : Aᵀ.IsHermitian ↔ A.IsHermitian :=
⟨by intro h; rw [← transpose_transpose A]; exact IsHermitian.transpose h, IsHermitian.transpose⟩
#align matrix.is_hermitian_transpose_iff Matrix.isHermitian_transpose_iff
theorem IsHermitian.conjTranspose {A : Matrix n n α} (h : A.IsHermitian) : Aᴴ.IsHermitian :=
h.transpose.map _ fun _ => rfl
#align matrix.is_hermitian.conj_transpose Matrix.IsHermitian.conjTranspose
@[simp]
theorem IsHermitian.submatrix {A : Matrix n n α} (h : A.IsHermitian) (f : m → n) :
(A.submatrix f f).IsHermitian := (conjTranspose_submatrix _ _ _).trans (h.symm ▸ rfl)
#align matrix.is_hermitian.submatrix Matrix.IsHermitian.submatrix
@[simp]
theorem isHermitian_submatrix_equiv {A : Matrix n n α} (e : m ≃ n) :
(A.submatrix e e).IsHermitian ↔ A.IsHermitian :=
⟨fun h => by simpa using h.submatrix e.symm, fun h => h.submatrix _⟩
#align matrix.is_hermitian_submatrix_equiv Matrix.isHermitian_submatrix_equiv
end Star
section InvolutiveStar
variable [InvolutiveStar α]
@[simp]
theorem isHermitian_conjTranspose_iff (A : Matrix n n α) : Aᴴ.IsHermitian ↔ A.IsHermitian :=
IsSelfAdjoint.star_iff
#align matrix.is_hermitian_conj_transpose_iff Matrix.isHermitian_conjTranspose_iff
/-- A block matrix `A.from_blocks B C D` is hermitian,
if `A` and `D` are hermitian and `Bᴴ = C`. -/
theorem IsHermitian.fromBlocks {A : Matrix m m α} {B : Matrix m n α} {C : Matrix n m α}
{D : Matrix n n α} (hA : A.IsHermitian) (hBC : Bᴴ = C) (hD : D.IsHermitian) :
(A.fromBlocks B C D).IsHermitian := by
have hCB : Cᴴ = B := by rw [← hBC, conjTranspose_conjTranspose]
unfold Matrix.IsHermitian
rw [fromBlocks_conjTranspose, hBC, hCB, hA, hD]
#align matrix.is_hermitian.from_blocks Matrix.IsHermitian.fromBlocks
/-- This is the `iff` version of `Matrix.IsHermitian.fromBlocks`. -/
theorem isHermitian_fromBlocks_iff {A : Matrix m m α} {B : Matrix m n α} {C : Matrix n m α}
{D : Matrix n n α} :
(A.fromBlocks B C D).IsHermitian ↔ A.IsHermitian ∧ Bᴴ = C ∧ Cᴴ = B ∧ D.IsHermitian :=
⟨fun h =>
⟨congr_arg toBlocks₁₁ h, congr_arg toBlocks₂₁ h, congr_arg toBlocks₁₂ h,
congr_arg toBlocks₂₂ h⟩,
fun ⟨hA, hBC, _hCB, hD⟩ => IsHermitian.fromBlocks hA hBC hD⟩
#align matrix.is_hermitian_from_blocks_iff Matrix.isHermitian_fromBlocks_iff
end InvolutiveStar
section AddMonoid
variable [AddMonoid α] [StarAddMonoid α] [AddMonoid β] [StarAddMonoid β]
/-- A diagonal matrix is hermitian if the entries are self-adjoint (as a vector) -/
theorem isHermitian_diagonal_of_self_adjoint [DecidableEq n] (v : n → α) (h : IsSelfAdjoint v) :
(diagonal v).IsHermitian :=
(-- TODO: add a `pi.has_trivial_star` instance and remove the `funext`
diagonal_conjTranspose v).trans <| congr_arg _ h
#align matrix.is_hermitian_diagonal_of_self_adjoint Matrix.isHermitian_diagonal_of_self_adjoint
/-- A diagonal matrix is hermitian if each diagonal entry is self-adjoint -/
lemma isHermitian_diagonal_iff [DecidableEq n] {d : n → α} :
IsHermitian (diagonal d) ↔ (∀ i : n, IsSelfAdjoint (d i)) := by
simp [isSelfAdjoint_iff, IsHermitian, conjTranspose, diagonal_transpose, diagonal_map]
/-- A diagonal matrix is hermitian if the entries have the trivial `star` operation
(such as on the reals). -/
@[simp]
theorem isHermitian_diagonal [TrivialStar α] [DecidableEq n] (v : n → α) :
(diagonal v).IsHermitian :=
isHermitian_diagonal_of_self_adjoint _ (IsSelfAdjoint.all _)
#align matrix.is_hermitian_diagonal Matrix.isHermitian_diagonal
@[simp]
theorem isHermitian_zero : (0 : Matrix n n α).IsHermitian :=
isSelfAdjoint_zero _
#align matrix.is_hermitian_zero Matrix.isHermitian_zero
@[simp]
theorem IsHermitian.add {A B : Matrix n n α} (hA : A.IsHermitian) (hB : B.IsHermitian) :
(A + B).IsHermitian :=
IsSelfAdjoint.add hA hB
#align matrix.is_hermitian.add Matrix.IsHermitian.add
end AddMonoid
section AddCommMonoid
variable [AddCommMonoid α] [StarAddMonoid α]
theorem isHermitian_add_transpose_self (A : Matrix n n α) : (A + Aᴴ).IsHermitian :=
isSelfAdjoint_add_star_self A
#align matrix.is_hermitian_add_transpose_self Matrix.isHermitian_add_transpose_self
theorem isHermitian_transpose_add_self (A : Matrix n n α) : (Aᴴ + A).IsHermitian :=
isSelfAdjoint_star_add_self A
#align matrix.is_hermitian_transpose_add_self Matrix.isHermitian_transpose_add_self
end AddCommMonoid
section AddGroup
variable [AddGroup α] [StarAddMonoid α]
@[simp]
theorem IsHermitian.neg {A : Matrix n n α} (h : A.IsHermitian) : (-A).IsHermitian :=
IsSelfAdjoint.neg h
#align matrix.is_hermitian.neg Matrix.IsHermitian.neg
@[simp]
theorem IsHermitian.sub {A B : Matrix n n α} (hA : A.IsHermitian) (hB : B.IsHermitian) :
(A - B).IsHermitian :=
IsSelfAdjoint.sub hA hB
#align matrix.is_hermitian.sub Matrix.IsHermitian.sub
end AddGroup
section NonUnitalSemiring
variable [NonUnitalSemiring α] [StarRing α] [NonUnitalSemiring β] [StarRing β]
/-- Note this is more general than `IsSelfAdjoint.mul_star_self` as `B` can be rectangular. -/
theorem isHermitian_mul_conjTranspose_self [Fintype n] (A : Matrix m n α) :
(A * Aᴴ).IsHermitian := by rw [IsHermitian, conjTranspose_mul, conjTranspose_conjTranspose]
#align matrix.is_hermitian_mul_conj_transpose_self Matrix.isHermitian_mul_conjTranspose_self
/-- Note this is more general than `IsSelfAdjoint.star_mul_self` as `B` can be rectangular. -/
| Mathlib/LinearAlgebra/Matrix/Hermitian.lean | 210 | 211 | theorem isHermitian_transpose_mul_self [Fintype m] (A : Matrix m n α) : (Aᴴ * A).IsHermitian := by |
rw [IsHermitian, conjTranspose_mul, conjTranspose_conjTranspose]
|
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Sébastien Gouëzel, Frédéric Dupuis
-/
import Mathlib.Algebra.DirectSum.Module
import Mathlib.Analysis.Complex.Basic
import Mathlib.Analysis.Convex.Uniform
import Mathlib.Analysis.NormedSpace.Completion
import Mathlib.Analysis.NormedSpace.BoundedLinearMaps
#align_import analysis.inner_product_space.basic from "leanprover-community/mathlib"@"3f655f5297b030a87d641ad4e825af8d9679eb0b"
/-!
# Inner product space
This file defines inner product spaces and proves the basic properties. We do not formally
define Hilbert spaces, but they can be obtained using the set of assumptions
`[NormedAddCommGroup E] [InnerProductSpace 𝕜 E] [CompleteSpace E]`.
An inner product space is a vector space endowed with an inner product. It generalizes the notion of
dot product in `ℝ^n` and provides the means of defining the length of a vector and the angle between
two vectors. In particular vectors `x` and `y` are orthogonal if their inner product equals zero.
We define both the real and complex cases at the same time using the `RCLike` typeclass.
This file proves general results on inner product spaces. For the specific construction of an inner
product structure on `n → 𝕜` for `𝕜 = ℝ` or `ℂ`, see `EuclideanSpace` in
`Analysis.InnerProductSpace.PiL2`.
## Main results
- We define the class `InnerProductSpace 𝕜 E` extending `NormedSpace 𝕜 E` with a number of basic
properties, most notably the Cauchy-Schwarz inequality. Here `𝕜` is understood to be either `ℝ`
or `ℂ`, through the `RCLike` typeclass.
- We show that the inner product is continuous, `continuous_inner`, and bundle it as the
continuous sesquilinear map `innerSL` (see also `innerₛₗ` for the non-continuous version).
- We define `Orthonormal`, a predicate on a function `v : ι → E`, and prove the existence of a
maximal orthonormal set, `exists_maximal_orthonormal`. Bessel's inequality,
`Orthonormal.tsum_inner_products_le`, states that given an orthonormal set `v` and a vector `x`,
the sum of the norm-squares of the inner products `⟪v i, x⟫` is no more than the norm-square of
`x`. For the existence of orthonormal bases, Hilbert bases, etc., see the file
`Analysis.InnerProductSpace.projection`.
## Notation
We globally denote the real and complex inner products by `⟪·, ·⟫_ℝ` and `⟪·, ·⟫_ℂ` respectively.
We also provide two notation namespaces: `RealInnerProductSpace`, `ComplexInnerProductSpace`,
which respectively introduce the plain notation `⟪·, ·⟫` for the real and complex inner product.
## Implementation notes
We choose the convention that inner products are conjugate linear in the first argument and linear
in the second.
## Tags
inner product space, Hilbert space, norm
## References
* [Clément & Martin, *The Lax-Milgram Theorem. A detailed proof to be formalized in Coq*]
* [Clément & Martin, *A Coq formal proof of the Lax–Milgram theorem*]
The Coq code is available at the following address: <http://www.lri.fr/~sboldo/elfic/index.html>
-/
noncomputable section
open RCLike Real Filter
open Topology ComplexConjugate
open LinearMap (BilinForm)
variable {𝕜 E F : Type*} [RCLike 𝕜]
/-- Syntactic typeclass for types endowed with an inner product -/
class Inner (𝕜 E : Type*) where
/-- The inner product function. -/
inner : E → E → 𝕜
#align has_inner Inner
export Inner (inner)
/-- The inner product with values in `𝕜`. -/
notation3:max "⟪" x ", " y "⟫_" 𝕜:max => @inner 𝕜 _ _ x y
section Notations
/-- The inner product with values in `ℝ`. -/
scoped[RealInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℝ _ _ x y
/-- The inner product with values in `ℂ`. -/
scoped[ComplexInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℂ _ _ x y
end Notations
/-- An inner product space is a vector space with an additional operation called inner product.
The norm could be derived from the inner product, instead we require the existence of a norm and
the fact that `‖x‖^2 = re ⟪x, x⟫` to be able to put instances on `𝕂` or product
spaces.
To construct a norm from an inner product, see `InnerProductSpace.ofCore`.
-/
class InnerProductSpace (𝕜 : Type*) (E : Type*) [RCLike 𝕜] [NormedAddCommGroup E] extends
NormedSpace 𝕜 E, Inner 𝕜 E where
/-- The inner product induces the norm. -/
norm_sq_eq_inner : ∀ x : E, ‖x‖ ^ 2 = re (inner x x)
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space InnerProductSpace
/-!
### Constructing a normed space structure from an inner product
In the definition of an inner product space, we require the existence of a norm, which is equal
(but maybe not defeq) to the square root of the scalar product. This makes it possible to put
an inner product space structure on spaces with a preexisting norm (for instance `ℝ`), with good
properties. However, sometimes, one would like to define the norm starting only from a well-behaved
scalar product. This is what we implement in this paragraph, starting from a structure
`InnerProductSpace.Core` stating that we have a nice scalar product.
Our goal here is not to develop a whole theory with all the supporting API, as this will be done
below for `InnerProductSpace`. Instead, we implement the bare minimum to go as directly as
possible to the construction of the norm and the proof of the triangular inequality.
Warning: Do not use this `Core` structure if the space you are interested in already has a norm
instance defined on it, otherwise this will create a second non-defeq norm instance!
-/
/-- A structure requiring that a scalar product is positive definite and symmetric, from which one
can construct an `InnerProductSpace` instance in `InnerProductSpace.ofCore`. -/
-- @[nolint HasNonemptyInstance] porting note: I don't think we have this linter anymore
structure InnerProductSpace.Core (𝕜 : Type*) (F : Type*) [RCLike 𝕜] [AddCommGroup F]
[Module 𝕜 F] extends Inner 𝕜 F where
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is positive (semi)definite. -/
nonneg_re : ∀ x, 0 ≤ re (inner x x)
/-- The inner product is positive definite. -/
definite : ∀ x, inner x x = 0 → x = 0
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space.core InnerProductSpace.Core
/- We set `InnerProductSpace.Core` to be a class as we will use it as such in the construction
of the normed space structure that it produces. However, all the instances we will use will be
local to this proof. -/
attribute [class] InnerProductSpace.Core
/-- Define `InnerProductSpace.Core` from `InnerProductSpace`. Defined to reuse lemmas about
`InnerProductSpace.Core` for `InnerProductSpace`s. Note that the `Norm` instance provided by
`InnerProductSpace.Core.norm` is propositionally but not definitionally equal to the original
norm. -/
def InnerProductSpace.toCore [NormedAddCommGroup E] [c : InnerProductSpace 𝕜 E] :
InnerProductSpace.Core 𝕜 E :=
{ c with
nonneg_re := fun x => by
rw [← InnerProductSpace.norm_sq_eq_inner]
apply sq_nonneg
definite := fun x hx =>
norm_eq_zero.1 <| pow_eq_zero (n := 2) <| by
rw [InnerProductSpace.norm_sq_eq_inner (𝕜 := 𝕜) x, hx, map_zero] }
#align inner_product_space.to_core InnerProductSpace.toCore
namespace InnerProductSpace.Core
variable [AddCommGroup F] [Module 𝕜 F] [c : InnerProductSpace.Core 𝕜 F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 F _ x y
local notation "normSqK" => @RCLike.normSq 𝕜 _
local notation "reK" => @RCLike.re 𝕜 _
local notation "ext_iff" => @RCLike.ext_iff 𝕜 _
local postfix:90 "†" => starRingEnd _
/-- Inner product defined by the `InnerProductSpace.Core` structure. We can't reuse
`InnerProductSpace.Core.toInner` because it takes `InnerProductSpace.Core` as an explicit
argument. -/
def toInner' : Inner 𝕜 F :=
c.toInner
#align inner_product_space.core.to_has_inner' InnerProductSpace.Core.toInner'
attribute [local instance] toInner'
/-- The norm squared function for `InnerProductSpace.Core` structure. -/
def normSq (x : F) :=
reK ⟪x, x⟫
#align inner_product_space.core.norm_sq InnerProductSpace.Core.normSq
local notation "normSqF" => @normSq 𝕜 F _ _ _ _
theorem inner_conj_symm (x y : F) : ⟪y, x⟫† = ⟪x, y⟫ :=
c.conj_symm x y
#align inner_product_space.core.inner_conj_symm InnerProductSpace.Core.inner_conj_symm
theorem inner_self_nonneg {x : F} : 0 ≤ re ⟪x, x⟫ :=
c.nonneg_re _
#align inner_product_space.core.inner_self_nonneg InnerProductSpace.Core.inner_self_nonneg
theorem inner_self_im (x : F) : im ⟪x, x⟫ = 0 := by
rw [← @ofReal_inj 𝕜, im_eq_conj_sub]
simp [inner_conj_symm]
#align inner_product_space.core.inner_self_im InnerProductSpace.Core.inner_self_im
theorem inner_add_left (x y z : F) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
c.add_left _ _ _
#align inner_product_space.core.inner_add_left InnerProductSpace.Core.inner_add_left
theorem inner_add_right (x y z : F) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]; simp only [inner_conj_symm]
#align inner_product_space.core.inner_add_right InnerProductSpace.Core.inner_add_right
theorem ofReal_normSq_eq_inner_self (x : F) : (normSqF x : 𝕜) = ⟪x, x⟫ := by
rw [ext_iff]
exact ⟨by simp only [ofReal_re]; rfl, by simp only [inner_self_im, ofReal_im]⟩
#align inner_product_space.core.coe_norm_sq_eq_inner_self InnerProductSpace.Core.ofReal_normSq_eq_inner_self
theorem inner_re_symm (x y : F) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
#align inner_product_space.core.inner_re_symm InnerProductSpace.Core.inner_re_symm
theorem inner_im_symm (x y : F) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
#align inner_product_space.core.inner_im_symm InnerProductSpace.Core.inner_im_symm
theorem inner_smul_left (x y : F) {r : 𝕜} : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
c.smul_left _ _ _
#align inner_product_space.core.inner_smul_left InnerProductSpace.Core.inner_smul_left
theorem inner_smul_right (x y : F) {r : 𝕜} : ⟪x, r • y⟫ = r * ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left];
simp only [conj_conj, inner_conj_symm, RingHom.map_mul]
#align inner_product_space.core.inner_smul_right InnerProductSpace.Core.inner_smul_right
theorem inner_zero_left (x : F) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : F), inner_smul_left];
simp only [zero_mul, RingHom.map_zero]
#align inner_product_space.core.inner_zero_left InnerProductSpace.Core.inner_zero_left
theorem inner_zero_right (x : F) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left]; simp only [RingHom.map_zero]
#align inner_product_space.core.inner_zero_right InnerProductSpace.Core.inner_zero_right
theorem inner_self_eq_zero {x : F} : ⟪x, x⟫ = 0 ↔ x = 0 :=
⟨c.definite _, by
rintro rfl
exact inner_zero_left _⟩
#align inner_product_space.core.inner_self_eq_zero InnerProductSpace.Core.inner_self_eq_zero
theorem normSq_eq_zero {x : F} : normSqF x = 0 ↔ x = 0 :=
Iff.trans
(by simp only [normSq, ext_iff, map_zero, inner_self_im, eq_self_iff_true, and_true_iff])
(@inner_self_eq_zero 𝕜 _ _ _ _ _ x)
#align inner_product_space.core.norm_sq_eq_zero InnerProductSpace.Core.normSq_eq_zero
theorem inner_self_ne_zero {x : F} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
#align inner_product_space.core.inner_self_ne_zero InnerProductSpace.Core.inner_self_ne_zero
theorem inner_self_ofReal_re (x : F) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ := by
norm_num [ext_iff, inner_self_im]
set_option linter.uppercaseLean3 false in
#align inner_product_space.core.inner_self_re_to_K InnerProductSpace.Core.inner_self_ofReal_re
theorem norm_inner_symm (x y : F) : ‖⟪x, y⟫‖ = ‖⟪y, x⟫‖ := by rw [← inner_conj_symm, norm_conj]
#align inner_product_space.core.norm_inner_symm InnerProductSpace.Core.norm_inner_symm
theorem inner_neg_left (x y : F) : ⟪-x, y⟫ = -⟪x, y⟫ := by
rw [← neg_one_smul 𝕜 x, inner_smul_left]
simp
#align inner_product_space.core.inner_neg_left InnerProductSpace.Core.inner_neg_left
theorem inner_neg_right (x y : F) : ⟪x, -y⟫ = -⟪x, y⟫ := by
rw [← inner_conj_symm, inner_neg_left]; simp only [RingHom.map_neg, inner_conj_symm]
#align inner_product_space.core.inner_neg_right InnerProductSpace.Core.inner_neg_right
theorem inner_sub_left (x y z : F) : ⟪x - y, z⟫ = ⟪x, z⟫ - ⟪y, z⟫ := by
simp [sub_eq_add_neg, inner_add_left, inner_neg_left]
#align inner_product_space.core.inner_sub_left InnerProductSpace.Core.inner_sub_left
theorem inner_sub_right (x y z : F) : ⟪x, y - z⟫ = ⟪x, y⟫ - ⟪x, z⟫ := by
simp [sub_eq_add_neg, inner_add_right, inner_neg_right]
#align inner_product_space.core.inner_sub_right InnerProductSpace.Core.inner_sub_right
theorem inner_mul_symm_re_eq_norm (x y : F) : re (⟪x, y⟫ * ⟪y, x⟫) = ‖⟪x, y⟫ * ⟪y, x⟫‖ := by
rw [← inner_conj_symm, mul_comm]
exact re_eq_norm_of_mul_conj (inner y x)
#align inner_product_space.core.inner_mul_symm_re_eq_norm InnerProductSpace.Core.inner_mul_symm_re_eq_norm
/-- Expand `inner (x + y) (x + y)` -/
theorem inner_add_add_self (x y : F) : ⟪x + y, x + y⟫ = ⟪x, x⟫ + ⟪x, y⟫ + ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_add_left, inner_add_right]; ring
#align inner_product_space.core.inner_add_add_self InnerProductSpace.Core.inner_add_add_self
-- Expand `inner (x - y) (x - y)`
theorem inner_sub_sub_self (x y : F) : ⟪x - y, x - y⟫ = ⟪x, x⟫ - ⟪x, y⟫ - ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_sub_left, inner_sub_right]; ring
#align inner_product_space.core.inner_sub_sub_self InnerProductSpace.Core.inner_sub_sub_self
/-- An auxiliary equality useful to prove the **Cauchy–Schwarz inequality**: the square of the norm
of `⟪x, y⟫ • x - ⟪x, x⟫ • y` is equal to `‖x‖ ^ 2 * (‖x‖ ^ 2 * ‖y‖ ^ 2 - ‖⟪x, y⟫‖ ^ 2)`. We use
`InnerProductSpace.ofCore.normSq x` etc (defeq to `is_R_or_C.re ⟪x, x⟫`) instead of `‖x‖ ^ 2`
etc to avoid extra rewrites when applying it to an `InnerProductSpace`. -/
theorem cauchy_schwarz_aux (x y : F) :
normSqF (⟪x, y⟫ • x - ⟪x, x⟫ • y) = normSqF x * (normSqF x * normSqF y - ‖⟪x, y⟫‖ ^ 2) := by
rw [← @ofReal_inj 𝕜, ofReal_normSq_eq_inner_self]
simp only [inner_sub_sub_self, inner_smul_left, inner_smul_right, conj_ofReal, mul_sub, ←
ofReal_normSq_eq_inner_self x, ← ofReal_normSq_eq_inner_self y]
rw [← mul_assoc, mul_conj, RCLike.conj_mul, mul_left_comm, ← inner_conj_symm y, mul_conj]
push_cast
ring
#align inner_product_space.core.cauchy_schwarz_aux InnerProductSpace.Core.cauchy_schwarz_aux
/-- **Cauchy–Schwarz inequality**.
We need this for the `Core` structure to prove the triangle inequality below when
showing the core is a normed group.
-/
theorem inner_mul_inner_self_le (x y : F) : ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ := by
rcases eq_or_ne x 0 with (rfl | hx)
· simpa only [inner_zero_left, map_zero, zero_mul, norm_zero] using le_rfl
· have hx' : 0 < normSqF x := inner_self_nonneg.lt_of_ne' (mt normSq_eq_zero.1 hx)
rw [← sub_nonneg, ← mul_nonneg_iff_right_nonneg_of_pos hx', ← normSq, ← normSq,
norm_inner_symm y, ← sq, ← cauchy_schwarz_aux]
exact inner_self_nonneg
#align inner_product_space.core.inner_mul_inner_self_le InnerProductSpace.Core.inner_mul_inner_self_le
/-- Norm constructed from an `InnerProductSpace.Core` structure, defined to be the square root
of the scalar product. -/
def toNorm : Norm F where norm x := √(re ⟪x, x⟫)
#align inner_product_space.core.to_has_norm InnerProductSpace.Core.toNorm
attribute [local instance] toNorm
theorem norm_eq_sqrt_inner (x : F) : ‖x‖ = √(re ⟪x, x⟫) := rfl
#align inner_product_space.core.norm_eq_sqrt_inner InnerProductSpace.Core.norm_eq_sqrt_inner
theorem inner_self_eq_norm_mul_norm (x : F) : re ⟪x, x⟫ = ‖x‖ * ‖x‖ := by
rw [norm_eq_sqrt_inner, ← sqrt_mul inner_self_nonneg (re ⟪x, x⟫), sqrt_mul_self inner_self_nonneg]
#align inner_product_space.core.inner_self_eq_norm_mul_norm InnerProductSpace.Core.inner_self_eq_norm_mul_norm
theorem sqrt_normSq_eq_norm (x : F) : √(normSqF x) = ‖x‖ := rfl
#align inner_product_space.core.sqrt_norm_sq_eq_norm InnerProductSpace.Core.sqrt_normSq_eq_norm
/-- Cauchy–Schwarz inequality with norm -/
theorem norm_inner_le_norm (x y : F) : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ :=
nonneg_le_nonneg_of_sq_le_sq (mul_nonneg (sqrt_nonneg _) (sqrt_nonneg _)) <|
calc
‖⟪x, y⟫‖ * ‖⟪x, y⟫‖ = ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ := by rw [norm_inner_symm]
_ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ := inner_mul_inner_self_le x y
_ = ‖x‖ * ‖y‖ * (‖x‖ * ‖y‖) := by simp only [inner_self_eq_norm_mul_norm]; ring
#align inner_product_space.core.norm_inner_le_norm InnerProductSpace.Core.norm_inner_le_norm
/-- Normed group structure constructed from an `InnerProductSpace.Core` structure -/
def toNormedAddCommGroup : NormedAddCommGroup F :=
AddGroupNorm.toNormedAddCommGroup
{ toFun := fun x => √(re ⟪x, x⟫)
map_zero' := by simp only [sqrt_zero, inner_zero_right, map_zero]
neg' := fun x => by simp only [inner_neg_left, neg_neg, inner_neg_right]
add_le' := fun x y => by
have h₁ : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ := norm_inner_le_norm _ _
have h₂ : re ⟪x, y⟫ ≤ ‖⟪x, y⟫‖ := re_le_norm _
have h₃ : re ⟪x, y⟫ ≤ ‖x‖ * ‖y‖ := h₂.trans h₁
have h₄ : re ⟪y, x⟫ ≤ ‖x‖ * ‖y‖ := by rwa [← inner_conj_symm, conj_re]
have : ‖x + y‖ * ‖x + y‖ ≤ (‖x‖ + ‖y‖) * (‖x‖ + ‖y‖) := by
simp only [← inner_self_eq_norm_mul_norm, inner_add_add_self, mul_add, mul_comm, map_add]
linarith
exact nonneg_le_nonneg_of_sq_le_sq (add_nonneg (sqrt_nonneg _) (sqrt_nonneg _)) this
eq_zero_of_map_eq_zero' := fun x hx =>
normSq_eq_zero.1 <| (sqrt_eq_zero inner_self_nonneg).1 hx }
#align inner_product_space.core.to_normed_add_comm_group InnerProductSpace.Core.toNormedAddCommGroup
attribute [local instance] toNormedAddCommGroup
/-- Normed space structure constructed from an `InnerProductSpace.Core` structure -/
def toNormedSpace : NormedSpace 𝕜 F where
norm_smul_le r x := by
rw [norm_eq_sqrt_inner, inner_smul_left, inner_smul_right, ← mul_assoc]
rw [RCLike.conj_mul, ← ofReal_pow, re_ofReal_mul, sqrt_mul, ← ofReal_normSq_eq_inner_self,
ofReal_re]
· simp [sqrt_normSq_eq_norm, RCLike.sqrt_normSq_eq_norm]
· positivity
#align inner_product_space.core.to_normed_space InnerProductSpace.Core.toNormedSpace
end InnerProductSpace.Core
section
attribute [local instance] InnerProductSpace.Core.toNormedAddCommGroup
/-- Given an `InnerProductSpace.Core` structure on a space, one can use it to turn
the space into an inner product space. The `NormedAddCommGroup` structure is expected
to already be defined with `InnerProductSpace.ofCore.toNormedAddCommGroup`. -/
def InnerProductSpace.ofCore [AddCommGroup F] [Module 𝕜 F] (c : InnerProductSpace.Core 𝕜 F) :
InnerProductSpace 𝕜 F :=
letI : NormedSpace 𝕜 F := @InnerProductSpace.Core.toNormedSpace 𝕜 F _ _ _ c
{ c with
norm_sq_eq_inner := fun x => by
have h₁ : ‖x‖ ^ 2 = √(re (c.inner x x)) ^ 2 := rfl
have h₂ : 0 ≤ re (c.inner x x) := InnerProductSpace.Core.inner_self_nonneg
simp [h₁, sq_sqrt, h₂] }
#align inner_product_space.of_core InnerProductSpace.ofCore
end
/-! ### Properties of inner product spaces -/
variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [NormedAddCommGroup F] [InnerProductSpace ℝ F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
local notation "IK" => @RCLike.I 𝕜 _
local postfix:90 "†" => starRingEnd _
export InnerProductSpace (norm_sq_eq_inner)
section BasicProperties
@[simp]
theorem inner_conj_symm (x y : E) : ⟪y, x⟫† = ⟪x, y⟫ :=
InnerProductSpace.conj_symm _ _
#align inner_conj_symm inner_conj_symm
theorem real_inner_comm (x y : F) : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ :=
@inner_conj_symm ℝ _ _ _ _ x y
#align real_inner_comm real_inner_comm
theorem inner_eq_zero_symm {x y : E} : ⟪x, y⟫ = 0 ↔ ⟪y, x⟫ = 0 := by
rw [← inner_conj_symm]
exact star_eq_zero
#align inner_eq_zero_symm inner_eq_zero_symm
@[simp]
theorem inner_self_im (x : E) : im ⟪x, x⟫ = 0 := by rw [← @ofReal_inj 𝕜, im_eq_conj_sub]; simp
#align inner_self_im inner_self_im
theorem inner_add_left (x y z : E) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
InnerProductSpace.add_left _ _ _
#align inner_add_left inner_add_left
theorem inner_add_right (x y z : E) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]
simp only [inner_conj_symm]
#align inner_add_right inner_add_right
theorem inner_re_symm (x y : E) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
#align inner_re_symm inner_re_symm
theorem inner_im_symm (x y : E) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
#align inner_im_symm inner_im_symm
theorem inner_smul_left (x y : E) (r : 𝕜) : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
InnerProductSpace.smul_left _ _ _
#align inner_smul_left inner_smul_left
theorem real_inner_smul_left (x y : F) (r : ℝ) : ⟪r • x, y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_left _ _ _
#align real_inner_smul_left real_inner_smul_left
theorem inner_smul_real_left (x y : E) (r : ℝ) : ⟪(r : 𝕜) • x, y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_left, conj_ofReal, Algebra.smul_def]
rfl
#align inner_smul_real_left inner_smul_real_left
theorem inner_smul_right (x y : E) (r : 𝕜) : ⟪x, r • y⟫ = r * ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left, RingHom.map_mul, conj_conj, inner_conj_symm]
#align inner_smul_right inner_smul_right
theorem real_inner_smul_right (x y : F) (r : ℝ) : ⟪x, r • y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_right _ _ _
#align real_inner_smul_right real_inner_smul_right
theorem inner_smul_real_right (x y : E) (r : ℝ) : ⟪x, (r : 𝕜) • y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_right, Algebra.smul_def]
rfl
#align inner_smul_real_right inner_smul_real_right
/-- The inner product as a sesquilinear form.
Note that in the case `𝕜 = ℝ` this is a bilinear form. -/
@[simps!]
def sesqFormOfInner : E →ₗ[𝕜] E →ₗ⋆[𝕜] 𝕜 :=
LinearMap.mk₂'ₛₗ (RingHom.id 𝕜) (starRingEnd _) (fun x y => ⟪y, x⟫)
(fun _x _y _z => inner_add_right _ _ _) (fun _r _x _y => inner_smul_right _ _ _)
(fun _x _y _z => inner_add_left _ _ _) fun _r _x _y => inner_smul_left _ _ _
#align sesq_form_of_inner sesqFormOfInner
/-- The real inner product as a bilinear form.
Note that unlike `sesqFormOfInner`, this does not reverse the order of the arguments. -/
@[simps!]
def bilinFormOfRealInner : BilinForm ℝ F := sesqFormOfInner.flip
#align bilin_form_of_real_inner bilinFormOfRealInner
/-- An inner product with a sum on the left. -/
theorem sum_inner {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪∑ i ∈ s, f i, x⟫ = ∑ i ∈ s, ⟪f i, x⟫ :=
map_sum (sesqFormOfInner (𝕜 := 𝕜) (E := E) x) _ _
#align sum_inner sum_inner
/-- An inner product with a sum on the right. -/
theorem inner_sum {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪x, ∑ i ∈ s, f i⟫ = ∑ i ∈ s, ⟪x, f i⟫ :=
map_sum (LinearMap.flip sesqFormOfInner x) _ _
#align inner_sum inner_sum
/-- An inner product with a sum on the left, `Finsupp` version. -/
theorem Finsupp.sum_inner {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪l.sum fun (i : ι) (a : 𝕜) => a • v i, x⟫ = l.sum fun (i : ι) (a : 𝕜) => conj a • ⟪v i, x⟫ := by
convert _root_.sum_inner (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_left, Finsupp.sum, smul_eq_mul]
#align finsupp.sum_inner Finsupp.sum_inner
/-- An inner product with a sum on the right, `Finsupp` version. -/
theorem Finsupp.inner_sum {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪x, l.sum fun (i : ι) (a : 𝕜) => a • v i⟫ = l.sum fun (i : ι) (a : 𝕜) => a • ⟪x, v i⟫ := by
convert _root_.inner_sum (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_right, Finsupp.sum, smul_eq_mul]
#align finsupp.inner_sum Finsupp.inner_sum
theorem DFinsupp.sum_inner {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪l.sum f, x⟫ = l.sum fun i a => ⟪f i a, x⟫ := by
simp (config := { contextual := true }) only [DFinsupp.sum, _root_.sum_inner, smul_eq_mul]
#align dfinsupp.sum_inner DFinsupp.sum_inner
theorem DFinsupp.inner_sum {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪x, l.sum f⟫ = l.sum fun i a => ⟪x, f i a⟫ := by
simp (config := { contextual := true }) only [DFinsupp.sum, _root_.inner_sum, smul_eq_mul]
#align dfinsupp.inner_sum DFinsupp.inner_sum
@[simp]
theorem inner_zero_left (x : E) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : E), inner_smul_left, RingHom.map_zero, zero_mul]
#align inner_zero_left inner_zero_left
theorem inner_re_zero_left (x : E) : re ⟪0, x⟫ = 0 := by
simp only [inner_zero_left, AddMonoidHom.map_zero]
#align inner_re_zero_left inner_re_zero_left
@[simp]
theorem inner_zero_right (x : E) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left, RingHom.map_zero]
#align inner_zero_right inner_zero_right
theorem inner_re_zero_right (x : E) : re ⟪x, 0⟫ = 0 := by
simp only [inner_zero_right, AddMonoidHom.map_zero]
#align inner_re_zero_right inner_re_zero_right
theorem inner_self_nonneg {x : E} : 0 ≤ re ⟪x, x⟫ :=
InnerProductSpace.toCore.nonneg_re x
#align inner_self_nonneg inner_self_nonneg
theorem real_inner_self_nonneg {x : F} : 0 ≤ ⟪x, x⟫_ℝ :=
@inner_self_nonneg ℝ F _ _ _ x
#align real_inner_self_nonneg real_inner_self_nonneg
@[simp]
theorem inner_self_ofReal_re (x : E) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ :=
((RCLike.is_real_TFAE (⟪x, x⟫ : 𝕜)).out 2 3).2 (inner_self_im _)
set_option linter.uppercaseLean3 false in
#align inner_self_re_to_K inner_self_ofReal_re
theorem inner_self_eq_norm_sq_to_K (x : E) : ⟪x, x⟫ = (‖x‖ : 𝕜) ^ 2 := by
rw [← inner_self_ofReal_re, ← norm_sq_eq_inner, ofReal_pow]
set_option linter.uppercaseLean3 false in
#align inner_self_eq_norm_sq_to_K inner_self_eq_norm_sq_to_K
theorem inner_self_re_eq_norm (x : E) : re ⟪x, x⟫ = ‖⟪x, x⟫‖ := by
conv_rhs => rw [← inner_self_ofReal_re]
symm
exact norm_of_nonneg inner_self_nonneg
#align inner_self_re_eq_norm inner_self_re_eq_norm
theorem inner_self_ofReal_norm (x : E) : (‖⟪x, x⟫‖ : 𝕜) = ⟪x, x⟫ := by
rw [← inner_self_re_eq_norm]
exact inner_self_ofReal_re _
set_option linter.uppercaseLean3 false in
#align inner_self_norm_to_K inner_self_ofReal_norm
theorem real_inner_self_abs (x : F) : |⟪x, x⟫_ℝ| = ⟪x, x⟫_ℝ :=
@inner_self_ofReal_norm ℝ F _ _ _ x
#align real_inner_self_abs real_inner_self_abs
@[simp]
theorem inner_self_eq_zero {x : E} : ⟪x, x⟫ = 0 ↔ x = 0 := by
rw [inner_self_eq_norm_sq_to_K, sq_eq_zero_iff, ofReal_eq_zero, norm_eq_zero]
#align inner_self_eq_zero inner_self_eq_zero
theorem inner_self_ne_zero {x : E} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
#align inner_self_ne_zero inner_self_ne_zero
@[simp]
theorem inner_self_nonpos {x : E} : re ⟪x, x⟫ ≤ 0 ↔ x = 0 := by
rw [← norm_sq_eq_inner, (sq_nonneg _).le_iff_eq, sq_eq_zero_iff, norm_eq_zero]
#align inner_self_nonpos inner_self_nonpos
theorem real_inner_self_nonpos {x : F} : ⟪x, x⟫_ℝ ≤ 0 ↔ x = 0 :=
@inner_self_nonpos ℝ F _ _ _ x
#align real_inner_self_nonpos real_inner_self_nonpos
| Mathlib/Analysis/InnerProductSpace/Basic.lean | 615 | 615 | theorem norm_inner_symm (x y : E) : ‖⟪x, y⟫‖ = ‖⟪y, x⟫‖ := by | rw [← inner_conj_symm, norm_conj]
|
/-
Copyright (c) 2022 David Loeffler. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Loeffler
-/
import Mathlib.MeasureTheory.Integral.ExpDecay
import Mathlib.Analysis.MellinTransform
#align_import analysis.special_functions.gamma.basic from "leanprover-community/mathlib"@"cca40788df1b8755d5baf17ab2f27dacc2e17acb"
/-!
# The Gamma function
This file defines the `Γ` function (of a real or complex variable `s`). We define this by Euler's
integral `Γ(s) = ∫ x in Ioi 0, exp (-x) * x ^ (s - 1)` in the range where this integral converges
(i.e., for `0 < s` in the real case, and `0 < re s` in the complex case).
We show that this integral satisfies `Γ(1) = 1` and `Γ(s + 1) = s * Γ(s)`; hence we can define
`Γ(s)` for all `s` as the unique function satisfying this recurrence and agreeing with Euler's
integral in the convergence range. (If `s = -n` for `n ∈ ℕ`, then the function is undefined, and we
set it to be `0` by convention.)
## Gamma function: main statements (complex case)
* `Complex.Gamma`: the `Γ` function (of a complex variable).
* `Complex.Gamma_eq_integral`: for `0 < re s`, `Γ(s)` agrees with Euler's integral.
* `Complex.Gamma_add_one`: for all `s : ℂ` with `s ≠ 0`, we have `Γ (s + 1) = s Γ(s)`.
* `Complex.Gamma_nat_eq_factorial`: for all `n : ℕ` we have `Γ (n + 1) = n!`.
* `Complex.differentiableAt_Gamma`: `Γ` is complex-differentiable at all `s : ℂ` with
`s ∉ {-n : n ∈ ℕ}`.
## Gamma function: main statements (real case)
* `Real.Gamma`: the `Γ` function (of a real variable).
* Real counterparts of all the properties of the complex Gamma function listed above:
`Real.Gamma_eq_integral`, `Real.Gamma_add_one`, `Real.Gamma_nat_eq_factorial`,
`Real.differentiableAt_Gamma`.
## Tags
Gamma
-/
noncomputable section
set_option linter.uppercaseLean3 false
open Filter intervalIntegral Set Real MeasureTheory Asymptotics
open scoped Nat Topology ComplexConjugate
namespace Real
/-- Asymptotic bound for the `Γ` function integrand. -/
theorem Gamma_integrand_isLittleO (s : ℝ) :
(fun x : ℝ => exp (-x) * x ^ s) =o[atTop] fun x : ℝ => exp (-(1 / 2) * x) := by
refine isLittleO_of_tendsto (fun x hx => ?_) ?_
· exfalso; exact (exp_pos (-(1 / 2) * x)).ne' hx
have : (fun x : ℝ => exp (-x) * x ^ s / exp (-(1 / 2) * x)) =
(fun x : ℝ => exp (1 / 2 * x) / x ^ s)⁻¹ := by
ext1 x
field_simp [exp_ne_zero, exp_neg, ← Real.exp_add]
left
ring
rw [this]
exact (tendsto_exp_mul_div_rpow_atTop s (1 / 2) one_half_pos).inv_tendsto_atTop
#align real.Gamma_integrand_is_o Real.Gamma_integrand_isLittleO
/-- The Euler integral for the `Γ` function converges for positive real `s`. -/
theorem GammaIntegral_convergent {s : ℝ} (h : 0 < s) :
IntegrableOn (fun x : ℝ => exp (-x) * x ^ (s - 1)) (Ioi 0) := by
rw [← Ioc_union_Ioi_eq_Ioi (@zero_le_one ℝ _ _ _ _), integrableOn_union]
constructor
· rw [← integrableOn_Icc_iff_integrableOn_Ioc]
refine IntegrableOn.continuousOn_mul continuousOn_id.neg.rexp ?_ isCompact_Icc
refine (intervalIntegrable_iff_integrableOn_Icc_of_le zero_le_one).mp ?_
exact intervalIntegrable_rpow' (by linarith)
· refine integrable_of_isBigO_exp_neg one_half_pos ?_ (Gamma_integrand_isLittleO _).isBigO
refine continuousOn_id.neg.rexp.mul (continuousOn_id.rpow_const ?_)
intro x hx
exact Or.inl ((zero_lt_one : (0 : ℝ) < 1).trans_le hx).ne'
#align real.Gamma_integral_convergent Real.GammaIntegral_convergent
end Real
namespace Complex
/- Technical note: In defining the Gamma integrand exp (-x) * x ^ (s - 1) for s complex, we have to
make a choice between ↑(Real.exp (-x)), Complex.exp (↑(-x)), and Complex.exp (-↑x), all of which are
equal but not definitionally so. We use the first of these throughout. -/
/-- The integral defining the `Γ` function converges for complex `s` with `0 < re s`.
This is proved by reduction to the real case. -/
theorem GammaIntegral_convergent {s : ℂ} (hs : 0 < s.re) :
IntegrableOn (fun x => (-x).exp * x ^ (s - 1) : ℝ → ℂ) (Ioi 0) := by
constructor
· refine ContinuousOn.aestronglyMeasurable ?_ measurableSet_Ioi
apply (continuous_ofReal.comp continuous_neg.rexp).continuousOn.mul
apply ContinuousAt.continuousOn
intro x hx
have : ContinuousAt (fun x : ℂ => x ^ (s - 1)) ↑x :=
continuousAt_cpow_const <| ofReal_mem_slitPlane.2 hx
exact ContinuousAt.comp this continuous_ofReal.continuousAt
· rw [← hasFiniteIntegral_norm_iff]
refine HasFiniteIntegral.congr (Real.GammaIntegral_convergent hs).2 ?_
apply (ae_restrict_iff' measurableSet_Ioi).mpr
filter_upwards with x hx
rw [norm_eq_abs, map_mul, abs_of_nonneg <| le_of_lt <| exp_pos <| -x,
abs_cpow_eq_rpow_re_of_pos hx _]
simp
#align complex.Gamma_integral_convergent Complex.GammaIntegral_convergent
/-- Euler's integral for the `Γ` function (of a complex variable `s`), defined as
`∫ x in Ioi 0, exp (-x) * x ^ (s - 1)`.
See `Complex.GammaIntegral_convergent` for a proof of the convergence of the integral for
`0 < re s`. -/
def GammaIntegral (s : ℂ) : ℂ :=
∫ x in Ioi (0 : ℝ), ↑(-x).exp * ↑x ^ (s - 1)
#align complex.Gamma_integral Complex.GammaIntegral
theorem GammaIntegral_conj (s : ℂ) : GammaIntegral (conj s) = conj (GammaIntegral s) := by
rw [GammaIntegral, GammaIntegral, ← integral_conj]
refine setIntegral_congr measurableSet_Ioi fun x hx => ?_
dsimp only
rw [RingHom.map_mul, conj_ofReal, cpow_def_of_ne_zero (ofReal_ne_zero.mpr (ne_of_gt hx)),
cpow_def_of_ne_zero (ofReal_ne_zero.mpr (ne_of_gt hx)), ← exp_conj, RingHom.map_mul, ←
ofReal_log (le_of_lt hx), conj_ofReal, RingHom.map_sub, RingHom.map_one]
#align complex.Gamma_integral_conj Complex.GammaIntegral_conj
theorem GammaIntegral_ofReal (s : ℝ) :
GammaIntegral ↑s = ↑(∫ x : ℝ in Ioi 0, Real.exp (-x) * x ^ (s - 1)) := by
have : ∀ r : ℝ, Complex.ofReal' r = @RCLike.ofReal ℂ _ r := fun r => rfl
rw [GammaIntegral]
conv_rhs => rw [this, ← _root_.integral_ofReal]
refine setIntegral_congr measurableSet_Ioi ?_
intro x hx; dsimp only
conv_rhs => rw [← this]
rw [ofReal_mul, ofReal_cpow (mem_Ioi.mp hx).le]
simp
#align complex.Gamma_integral_of_real Complex.GammaIntegral_ofReal
@[simp]
theorem GammaIntegral_one : GammaIntegral 1 = 1 := by
simpa only [← ofReal_one, GammaIntegral_ofReal, ofReal_inj, sub_self, rpow_zero,
mul_one] using integral_exp_neg_Ioi_zero
#align complex.Gamma_integral_one Complex.GammaIntegral_one
end Complex
/-! Now we establish the recurrence relation `Γ(s + 1) = s * Γ(s)` using integration by parts. -/
namespace Complex
section GammaRecurrence
/-- The indefinite version of the `Γ` function, `Γ(s, X) = ∫ x ∈ 0..X, exp(-x) x ^ (s - 1)`. -/
def partialGamma (s : ℂ) (X : ℝ) : ℂ :=
∫ x in (0)..X, (-x).exp * x ^ (s - 1)
#align complex.partial_Gamma Complex.partialGamma
theorem tendsto_partialGamma {s : ℂ} (hs : 0 < s.re) :
Tendsto (fun X : ℝ => partialGamma s X) atTop (𝓝 <| GammaIntegral s) :=
intervalIntegral_tendsto_integral_Ioi 0 (GammaIntegral_convergent hs) tendsto_id
#align complex.tendsto_partial_Gamma Complex.tendsto_partialGamma
private theorem Gamma_integrand_interval_integrable (s : ℂ) {X : ℝ} (hs : 0 < s.re) (hX : 0 ≤ X) :
IntervalIntegrable (fun x => (-x).exp * x ^ (s - 1) : ℝ → ℂ) volume 0 X := by
rw [intervalIntegrable_iff_integrableOn_Ioc_of_le hX]
exact IntegrableOn.mono_set (GammaIntegral_convergent hs) Ioc_subset_Ioi_self
private theorem Gamma_integrand_deriv_integrable_A {s : ℂ} (hs : 0 < s.re) {X : ℝ} (hX : 0 ≤ X) :
IntervalIntegrable (fun x => -((-x).exp * x ^ s) : ℝ → ℂ) volume 0 X := by
convert (Gamma_integrand_interval_integrable (s + 1) _ hX).neg
· simp only [ofReal_exp, ofReal_neg, add_sub_cancel_right]; rfl
· simp only [add_re, one_re]; linarith
private theorem Gamma_integrand_deriv_integrable_B {s : ℂ} (hs : 0 < s.re) {Y : ℝ} (hY : 0 ≤ Y) :
IntervalIntegrable (fun x : ℝ => (-x).exp * (s * x ^ (s - 1)) : ℝ → ℂ) volume 0 Y := by
have : (fun x => (-x).exp * (s * x ^ (s - 1)) : ℝ → ℂ) =
(fun x => s * ((-x).exp * x ^ (s - 1)) : ℝ → ℂ) := by ext1; ring
rw [this, intervalIntegrable_iff_integrableOn_Ioc_of_le hY]
constructor
· refine (continuousOn_const.mul ?_).aestronglyMeasurable measurableSet_Ioc
apply (continuous_ofReal.comp continuous_neg.rexp).continuousOn.mul
apply ContinuousAt.continuousOn
intro x hx
refine (?_ : ContinuousAt (fun x : ℂ => x ^ (s - 1)) _).comp continuous_ofReal.continuousAt
exact continuousAt_cpow_const <| ofReal_mem_slitPlane.2 hx.1
rw [← hasFiniteIntegral_norm_iff]
simp_rw [norm_eq_abs, map_mul]
refine (((Real.GammaIntegral_convergent hs).mono_set
Ioc_subset_Ioi_self).hasFiniteIntegral.congr ?_).const_mul _
rw [EventuallyEq, ae_restrict_iff']
· filter_upwards with x hx
rw [abs_of_nonneg (exp_pos _).le, abs_cpow_eq_rpow_re_of_pos hx.1]
simp
· exact measurableSet_Ioc
/-- The recurrence relation for the indefinite version of the `Γ` function. -/
theorem partialGamma_add_one {s : ℂ} (hs : 0 < s.re) {X : ℝ} (hX : 0 ≤ X) :
partialGamma (s + 1) X = s * partialGamma s X - (-X).exp * X ^ s := by
rw [partialGamma, partialGamma, add_sub_cancel_right]
have F_der_I : ∀ x : ℝ, x ∈ Ioo 0 X → HasDerivAt (fun x => (-x).exp * x ^ s : ℝ → ℂ)
(-((-x).exp * x ^ s) + (-x).exp * (s * x ^ (s - 1))) x := by
intro x hx
have d1 : HasDerivAt (fun y : ℝ => (-y).exp) (-(-x).exp) x := by
simpa using (hasDerivAt_neg x).exp
have d2 : HasDerivAt (fun y : ℝ => (y : ℂ) ^ s) (s * x ^ (s - 1)) x := by
have t := @HasDerivAt.cpow_const _ _ _ s (hasDerivAt_id ↑x) ?_
· simpa only [mul_one] using t.comp_ofReal
· exact ofReal_mem_slitPlane.2 hx.1
simpa only [ofReal_neg, neg_mul] using d1.ofReal_comp.mul d2
have cont := (continuous_ofReal.comp continuous_neg.rexp).mul (continuous_ofReal_cpow_const hs)
have der_ible :=
(Gamma_integrand_deriv_integrable_A hs hX).add (Gamma_integrand_deriv_integrable_B hs hX)
have int_eval := integral_eq_sub_of_hasDerivAt_of_le hX cont.continuousOn F_der_I der_ible
-- We are basically done here but manipulating the output into the right form is fiddly.
apply_fun fun x : ℂ => -x at int_eval
rw [intervalIntegral.integral_add (Gamma_integrand_deriv_integrable_A hs hX)
(Gamma_integrand_deriv_integrable_B hs hX),
intervalIntegral.integral_neg, neg_add, neg_neg] at int_eval
rw [eq_sub_of_add_eq int_eval, sub_neg_eq_add, neg_sub, add_comm, add_sub]
have : (fun x => (-x).exp * (s * x ^ (s - 1)) : ℝ → ℂ) =
(fun x => s * (-x).exp * x ^ (s - 1) : ℝ → ℂ) := by ext1; ring
rw [this]
have t := @integral_const_mul 0 X volume _ _ s fun x : ℝ => (-x).exp * x ^ (s - 1)
rw [← t, ofReal_zero, zero_cpow]
· rw [mul_zero, add_zero]; congr 2; ext1; ring
· contrapose! hs; rw [hs, zero_re]
#align complex.partial_Gamma_add_one Complex.partialGamma_add_one
/-- The recurrence relation for the `Γ` integral. -/
theorem GammaIntegral_add_one {s : ℂ} (hs : 0 < s.re) :
GammaIntegral (s + 1) = s * GammaIntegral s := by
suffices Tendsto (s + 1).partialGamma atTop (𝓝 <| s * GammaIntegral s) by
refine tendsto_nhds_unique ?_ this
apply tendsto_partialGamma; rw [add_re, one_re]; linarith
have : (fun X : ℝ => s * partialGamma s X - X ^ s * (-X).exp) =ᶠ[atTop]
(s + 1).partialGamma := by
apply eventuallyEq_of_mem (Ici_mem_atTop (0 : ℝ))
intro X hX
rw [partialGamma_add_one hs (mem_Ici.mp hX)]
ring_nf
refine Tendsto.congr' this ?_
suffices Tendsto (fun X => -X ^ s * (-X).exp : ℝ → ℂ) atTop (𝓝 0) by
simpa using Tendsto.add (Tendsto.const_mul s (tendsto_partialGamma hs)) this
rw [tendsto_zero_iff_norm_tendsto_zero]
have :
(fun e : ℝ => ‖-(e : ℂ) ^ s * (-e).exp‖) =ᶠ[atTop] fun e : ℝ => e ^ s.re * (-1 * e).exp := by
refine eventuallyEq_of_mem (Ioi_mem_atTop 0) ?_
intro x hx; dsimp only
rw [norm_eq_abs, map_mul, abs.map_neg, abs_cpow_eq_rpow_re_of_pos hx,
abs_of_nonneg (exp_pos (-x)).le, neg_mul, one_mul]
exact (tendsto_congr' this).mpr (tendsto_rpow_mul_exp_neg_mul_atTop_nhds_zero _ _ zero_lt_one)
#align complex.Gamma_integral_add_one Complex.GammaIntegral_add_one
end GammaRecurrence
/-! Now we define `Γ(s)` on the whole complex plane, by recursion. -/
section GammaDef
/-- The `n`th function in this family is `Γ(s)` if `-n < s.re`, and junk otherwise. -/
noncomputable def GammaAux : ℕ → ℂ → ℂ
| 0 => GammaIntegral
| n + 1 => fun s : ℂ => GammaAux n (s + 1) / s
#align complex.Gamma_aux Complex.GammaAux
theorem GammaAux_recurrence1 (s : ℂ) (n : ℕ) (h1 : -s.re < ↑n) :
GammaAux n s = GammaAux n (s + 1) / s := by
induction' n with n hn generalizing s
· simp only [Nat.zero_eq, CharP.cast_eq_zero, Left.neg_neg_iff] at h1
dsimp only [GammaAux]; rw [GammaIntegral_add_one h1]
rw [mul_comm, mul_div_cancel_right₀]; contrapose! h1; rw [h1]
simp
· dsimp only [GammaAux]
have hh1 : -(s + 1).re < n := by
rw [Nat.cast_add, Nat.cast_one] at h1
rw [add_re, one_re]; linarith
rw [← hn (s + 1) hh1]
#align complex.Gamma_aux_recurrence1 Complex.GammaAux_recurrence1
theorem GammaAux_recurrence2 (s : ℂ) (n : ℕ) (h1 : -s.re < ↑n) :
GammaAux n s = GammaAux (n + 1) s := by
cases' n with n n
· simp only [Nat.zero_eq, CharP.cast_eq_zero, Left.neg_neg_iff] at h1
dsimp only [GammaAux]
rw [GammaIntegral_add_one h1, mul_div_cancel_left₀]
rintro rfl
rw [zero_re] at h1
exact h1.false
· dsimp only [GammaAux]
have : GammaAux n (s + 1 + 1) / (s + 1) = GammaAux n (s + 1) := by
have hh1 : -(s + 1).re < n := by
rw [Nat.cast_add, Nat.cast_one] at h1
rw [add_re, one_re]; linarith
rw [GammaAux_recurrence1 (s + 1) n hh1]
rw [this]
#align complex.Gamma_aux_recurrence2 Complex.GammaAux_recurrence2
/-- The `Γ` function (of a complex variable `s`). -/
-- @[pp_nodot] -- Porting note: removed
irreducible_def Gamma (s : ℂ) : ℂ :=
GammaAux ⌊1 - s.re⌋₊ s
#align complex.Gamma Complex.Gamma
theorem Gamma_eq_GammaAux (s : ℂ) (n : ℕ) (h1 : -s.re < ↑n) : Gamma s = GammaAux n s := by
have u : ∀ k : ℕ, GammaAux (⌊1 - s.re⌋₊ + k) s = Gamma s := by
intro k; induction' k with k hk
· simp [Gamma]
· rw [← hk, ← add_assoc]
refine (GammaAux_recurrence2 s (⌊1 - s.re⌋₊ + k) ?_).symm
rw [Nat.cast_add]
have i0 := Nat.sub_one_lt_floor (1 - s.re)
simp only [sub_sub_cancel_left] at i0
refine lt_add_of_lt_of_nonneg i0 ?_
rw [← Nat.cast_zero, Nat.cast_le]; exact Nat.zero_le k
convert (u <| n - ⌊1 - s.re⌋₊).symm; rw [Nat.add_sub_of_le]
by_cases h : 0 ≤ 1 - s.re
· apply Nat.le_of_lt_succ
exact_mod_cast lt_of_le_of_lt (Nat.floor_le h) (by linarith : 1 - s.re < n + 1)
· rw [Nat.floor_of_nonpos]
· omega
· linarith
#align complex.Gamma_eq_Gamma_aux Complex.Gamma_eq_GammaAux
/-- The recurrence relation for the `Γ` function. -/
theorem Gamma_add_one (s : ℂ) (h2 : s ≠ 0) : Gamma (s + 1) = s * Gamma s := by
let n := ⌊1 - s.re⌋₊
have t1 : -s.re < n := by simpa only [sub_sub_cancel_left] using Nat.sub_one_lt_floor (1 - s.re)
have t2 : -(s + 1).re < n := by rw [add_re, one_re]; linarith
rw [Gamma_eq_GammaAux s n t1, Gamma_eq_GammaAux (s + 1) n t2, GammaAux_recurrence1 s n t1]
field_simp
#align complex.Gamma_add_one Complex.Gamma_add_one
theorem Gamma_eq_integral {s : ℂ} (hs : 0 < s.re) : Gamma s = GammaIntegral s :=
Gamma_eq_GammaAux s 0 (by norm_cast; linarith)
#align complex.Gamma_eq_integral Complex.Gamma_eq_integral
@[simp]
theorem Gamma_one : Gamma 1 = 1 := by rw [Gamma_eq_integral] <;> simp
#align complex.Gamma_one Complex.Gamma_one
theorem Gamma_nat_eq_factorial (n : ℕ) : Gamma (n + 1) = n ! := by
induction' n with n hn
· simp
· rw [Gamma_add_one n.succ <| Nat.cast_ne_zero.mpr <| Nat.succ_ne_zero n]
simp only [Nat.cast_succ, Nat.factorial_succ, Nat.cast_mul]; congr
#align complex.Gamma_nat_eq_factorial Complex.Gamma_nat_eq_factorial
@[simp]
theorem Gamma_ofNat_eq_factorial (n : ℕ) [(n + 1).AtLeastTwo] :
Gamma (no_index (OfNat.ofNat (n + 1) : ℂ)) = n ! :=
mod_cast Gamma_nat_eq_factorial (n : ℕ)
/-- At `0` the Gamma function is undefined; by convention we assign it the value `0`. -/
@[simp]
theorem Gamma_zero : Gamma 0 = 0 := by
simp_rw [Gamma, zero_re, sub_zero, Nat.floor_one, GammaAux, div_zero]
#align complex.Gamma_zero Complex.Gamma_zero
/-- At `-n` for `n ∈ ℕ`, the Gamma function is undefined; by convention we assign it the value 0. -/
theorem Gamma_neg_nat_eq_zero (n : ℕ) : Gamma (-n) = 0 := by
induction' n with n IH
· rw [Nat.cast_zero, neg_zero, Gamma_zero]
· have A : -(n.succ : ℂ) ≠ 0 := by
rw [neg_ne_zero, Nat.cast_ne_zero]
apply Nat.succ_ne_zero
have : -(n : ℂ) = -↑n.succ + 1 := by simp
rw [this, Gamma_add_one _ A] at IH
contrapose! IH
exact mul_ne_zero A IH
#align complex.Gamma_neg_nat_eq_zero Complex.Gamma_neg_nat_eq_zero
theorem Gamma_conj (s : ℂ) : Gamma (conj s) = conj (Gamma s) := by
suffices ∀ (n : ℕ) (s : ℂ), GammaAux n (conj s) = conj (GammaAux n s) by
simp [Gamma, this]
intro n
induction' n with n IH
· rw [GammaAux]; exact GammaIntegral_conj
· intro s
rw [GammaAux]
dsimp only
rw [div_eq_mul_inv _ s, RingHom.map_mul, conj_inv, ← div_eq_mul_inv]
suffices conj s + 1 = conj (s + 1) by rw [this, IH]
rw [RingHom.map_add, RingHom.map_one]
#align complex.Gamma_conj Complex.Gamma_conj
/-- Expresses the integral over `Ioi 0` of `t ^ (a - 1) * exp (-(r * t))` in terms of the Gamma
function, for complex `a`. -/
lemma integral_cpow_mul_exp_neg_mul_Ioi {a : ℂ} {r : ℝ} (ha : 0 < a.re) (hr : 0 < r) :
∫ (t : ℝ) in Ioi 0, t ^ (a - 1) * exp (-(r * t)) = (1 / r) ^ a * Gamma a := by
have aux : (1 / r : ℂ) ^ a = 1 / r * (1 / r) ^ (a - 1) := by
nth_rewrite 2 [← cpow_one (1 / r : ℂ)]
rw [← cpow_add _ _ (one_div_ne_zero <| ofReal_ne_zero.mpr hr.ne'), add_sub_cancel]
calc
_ = ∫ (t : ℝ) in Ioi 0, (1 / r) ^ (a - 1) * (r * t) ^ (a - 1) * exp (-(r * t)) := by
refine MeasureTheory.setIntegral_congr measurableSet_Ioi (fun x hx ↦ ?_)
rw [mem_Ioi] at hx
rw [mul_cpow_ofReal_nonneg hr.le hx.le, ← mul_assoc, one_div, ← ofReal_inv,
← mul_cpow_ofReal_nonneg (inv_pos.mpr hr).le hr.le, ← ofReal_mul r⁻¹, inv_mul_cancel hr.ne',
ofReal_one, one_cpow, one_mul]
_ = 1 / r * ∫ (t : ℝ) in Ioi 0, (1 / r) ^ (a - 1) * t ^ (a - 1) * exp (-t) := by
simp_rw [← ofReal_mul]
rw [integral_comp_mul_left_Ioi (fun x ↦ _ * x ^ (a - 1) * exp (-x)) _ hr, mul_zero,
real_smul, ← one_div, ofReal_div, ofReal_one]
_ = 1 / r * (1 / r : ℂ) ^ (a - 1) * (∫ (t : ℝ) in Ioi 0, t ^ (a - 1) * exp (-t)) := by
simp_rw [← integral_mul_left, mul_assoc]
_ = (1 / r) ^ a * Gamma a := by
rw [aux, Gamma_eq_integral ha]
congr 2 with x
rw [ofReal_exp, ofReal_neg, mul_comm]
end GammaDef
/-! Now check that the `Γ` function is differentiable, wherever this makes sense. -/
section GammaHasDeriv
/-- Rewrite the Gamma integral as an example of a Mellin transform. -/
theorem GammaIntegral_eq_mellin : GammaIntegral = mellin fun x => ↑(Real.exp (-x)) :=
funext fun s => by simp only [mellin, GammaIntegral, smul_eq_mul, mul_comm]
#align complex.Gamma_integral_eq_mellin Complex.GammaIntegral_eq_mellin
/-- The derivative of the `Γ` integral, at any `s ∈ ℂ` with `1 < re s`, is given by the Mellin
transform of `log t * exp (-t)`. -/
theorem hasDerivAt_GammaIntegral {s : ℂ} (hs : 0 < s.re) :
HasDerivAt GammaIntegral (∫ t : ℝ in Ioi 0, t ^ (s - 1) * (Real.log t * Real.exp (-t))) s := by
rw [GammaIntegral_eq_mellin]
convert (mellin_hasDerivAt_of_isBigO_rpow (E := ℂ) _ _ (lt_add_one _) _ hs).2
· refine (Continuous.continuousOn ?_).locallyIntegrableOn measurableSet_Ioi
exact continuous_ofReal.comp (Real.continuous_exp.comp continuous_neg)
· rw [← isBigO_norm_left]
simp_rw [Complex.norm_eq_abs, abs_ofReal, ← Real.norm_eq_abs, isBigO_norm_left]
simpa only [neg_one_mul] using (isLittleO_exp_neg_mul_rpow_atTop zero_lt_one _).isBigO
· simp_rw [neg_zero, rpow_zero]
refine isBigO_const_of_tendsto (?_ : Tendsto _ _ (𝓝 (1 : ℂ))) one_ne_zero
rw [(by simp : (1 : ℂ) = Real.exp (-0))]
exact (continuous_ofReal.comp (Real.continuous_exp.comp continuous_neg)).continuousWithinAt
#align complex.has_deriv_at_Gamma_integral Complex.hasDerivAt_GammaIntegral
theorem differentiableAt_GammaAux (s : ℂ) (n : ℕ) (h1 : 1 - s.re < n) (h2 : ∀ m : ℕ, s ≠ -m) :
DifferentiableAt ℂ (GammaAux n) s := by
induction' n with n hn generalizing s
· refine (hasDerivAt_GammaIntegral ?_).differentiableAt
rw [Nat.cast_zero] at h1; linarith
· dsimp only [GammaAux]
specialize hn (s + 1)
have a : 1 - (s + 1).re < ↑n := by
rw [Nat.cast_succ] at h1; rw [Complex.add_re, Complex.one_re]; linarith
have b : ∀ m : ℕ, s + 1 ≠ -m := by
intro m; have := h2 (1 + m)
contrapose! this
rw [← eq_sub_iff_add_eq] at this
simpa using this
refine DifferentiableAt.div (DifferentiableAt.comp _ (hn a b) ?_) ?_ ?_
· rw [differentiableAt_add_const_iff (1 : ℂ)]; exact differentiableAt_id
· exact differentiableAt_id
· simpa using h2 0
#align complex.differentiable_at_Gamma_aux Complex.differentiableAt_GammaAux
| Mathlib/Analysis/SpecialFunctions/Gamma/Basic.lean | 467 | 481 | theorem differentiableAt_Gamma (s : ℂ) (hs : ∀ m : ℕ, s ≠ -m) : DifferentiableAt ℂ Gamma s := by |
let n := ⌊1 - s.re⌋₊ + 1
have hn : 1 - s.re < n := mod_cast Nat.lt_floor_add_one (1 - s.re)
apply (differentiableAt_GammaAux s n hn hs).congr_of_eventuallyEq
let S := {t : ℂ | 1 - t.re < n}
have : S ∈ 𝓝 s := by
rw [mem_nhds_iff]; use S
refine ⟨Subset.rfl, ?_, hn⟩
have : S = re ⁻¹' Ioi (1 - n : ℝ) := by
ext; rw [preimage, Ioi, mem_setOf_eq, mem_setOf_eq, mem_setOf_eq]; exact sub_lt_comm
rw [this]
exact Continuous.isOpen_preimage continuous_re _ isOpen_Ioi
apply eventuallyEq_of_mem this
intro t ht; rw [mem_setOf_eq] at ht
apply Gamma_eq_GammaAux; linarith
|
/-
Copyright (c) 2021 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.Algebra.Module.LinearMap.Basic
import Mathlib.RingTheory.HahnSeries.Basic
#align_import ring_theory.hahn_series from "leanprover-community/mathlib"@"a484a7d0eade4e1268f4fb402859b6686037f965"
/-!
# Additive properties of Hahn series
If `Γ` is ordered and `R` has zero, then `HahnSeries Γ R` consists of formal series over `Γ` with
coefficients in `R`, whose supports are partially well-ordered. With further structure on `R` and
`Γ`, we can add further structure on `HahnSeries Γ R`. When `R` has an addition operation,
`HahnSeries Γ R` also has addition by adding coefficients.
## Main Definitions
* If `R` is a (commutative) additive monoid or group, then so is `HahnSeries Γ R`.
## References
- [J. van der Hoeven, *Operators on Generalized Power Series*][van_der_hoeven]
-/
set_option linter.uppercaseLean3 false
open Finset Function
open scoped Classical
noncomputable section
variable {Γ R : Type*}
namespace HahnSeries
section Addition
variable [PartialOrder Γ]
section AddMonoid
variable [AddMonoid R]
instance : Add (HahnSeries Γ R) where
add x y :=
{ coeff := x.coeff + y.coeff
isPWO_support' := (x.isPWO_support.union y.isPWO_support).mono (Function.support_add _ _) }
instance : AddMonoid (HahnSeries Γ R) where
zero := 0
add := (· + ·)
nsmul := nsmulRec
add_assoc x y z := by
ext
apply add_assoc
zero_add x := by
ext
apply zero_add
add_zero x := by
ext
apply add_zero
@[simp]
theorem add_coeff' {x y : HahnSeries Γ R} : (x + y).coeff = x.coeff + y.coeff :=
rfl
#align hahn_series.add_coeff' HahnSeries.add_coeff'
theorem add_coeff {x y : HahnSeries Γ R} {a : Γ} : (x + y).coeff a = x.coeff a + y.coeff a :=
rfl
#align hahn_series.add_coeff HahnSeries.add_coeff
theorem support_add_subset {x y : HahnSeries Γ R} : support (x + y) ⊆ support x ∪ support y :=
fun a ha => by
rw [mem_support, add_coeff] at ha
rw [Set.mem_union, mem_support, mem_support]
contrapose! ha
rw [ha.1, ha.2, add_zero]
#align hahn_series.support_add_subset HahnSeries.support_add_subset
theorem min_order_le_order_add {Γ} [Zero Γ] [LinearOrder Γ] {x y : HahnSeries Γ R}
(hxy : x + y ≠ 0) : min x.order y.order ≤ (x + y).order := by
by_cases hx : x = 0; · simp [hx]
by_cases hy : y = 0; · simp [hy]
rw [order_of_ne hx, order_of_ne hy, order_of_ne hxy]
apply le_of_eq_of_le _ (Set.IsWF.min_le_min_of_subset (support_add_subset (x := x) (y := y)))
· simp
· simp [hy]
· exact (Set.IsWF.min_union _ _ _ _).symm
#align hahn_series.min_order_le_order_add HahnSeries.min_order_le_order_add
/-- `single` as an additive monoid/group homomorphism -/
@[simps!]
def single.addMonoidHom (a : Γ) : R →+ HahnSeries Γ R :=
{ single a with
map_add' := fun x y => by
ext b
by_cases h : b = a <;> simp [h] }
#align hahn_series.single.add_monoid_hom HahnSeries.single.addMonoidHom
/-- `coeff g` as an additive monoid/group homomorphism -/
@[simps]
def coeff.addMonoidHom (g : Γ) : HahnSeries Γ R →+ R where
toFun f := f.coeff g
map_zero' := zero_coeff
map_add' _ _ := add_coeff
#align hahn_series.coeff.add_monoid_hom HahnSeries.coeff.addMonoidHom
section Domain
variable {Γ' : Type*} [PartialOrder Γ']
theorem embDomain_add (f : Γ ↪o Γ') (x y : HahnSeries Γ R) :
embDomain f (x + y) = embDomain f x + embDomain f y := by
ext g
by_cases hg : g ∈ Set.range f
· obtain ⟨a, rfl⟩ := hg
simp
· simp [embDomain_notin_range hg]
#align hahn_series.emb_domain_add HahnSeries.embDomain_add
end Domain
end AddMonoid
instance [AddCommMonoid R] : AddCommMonoid (HahnSeries Γ R) :=
{ inferInstanceAs (AddMonoid (HahnSeries Γ R)) with
add_comm := fun x y => by
ext
apply add_comm }
section AddGroup
variable [AddGroup R]
instance : Neg (HahnSeries Γ R) where
neg x :=
{ coeff := fun a => -x.coeff a
isPWO_support' := by
rw [Function.support_neg]
exact x.isPWO_support }
instance : AddGroup (HahnSeries Γ R) :=
{ inferInstanceAs (AddMonoid (HahnSeries Γ R)) with
zsmul := zsmulRec
add_left_neg := fun x => by
ext
apply add_left_neg }
@[simp]
theorem neg_coeff' {x : HahnSeries Γ R} : (-x).coeff = -x.coeff :=
rfl
#align hahn_series.neg_coeff' HahnSeries.neg_coeff'
theorem neg_coeff {x : HahnSeries Γ R} {a : Γ} : (-x).coeff a = -x.coeff a :=
rfl
#align hahn_series.neg_coeff HahnSeries.neg_coeff
@[simp]
| Mathlib/RingTheory/HahnSeries/Addition.lean | 160 | 162 | theorem support_neg {x : HahnSeries Γ R} : (-x).support = x.support := by |
ext
simp
|
/-
Copyright (c) 2022 Markus Himmel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel
-/
import Mathlib.CategoryTheory.Limits.Shapes.Biproducts
import Mathlib.GroupTheory.EckmannHilton
import Mathlib.Tactic.CategoryTheory.Reassoc
#align_import category_theory.preadditive.of_biproducts from "leanprover-community/mathlib"@"061ea99a5610cfc72c286aa930d3c1f47f74f3d0"
/-!
# Constructing a semiadditive structure from binary biproducts
We show that any category with zero morphisms and binary biproducts is enriched over the category
of commutative monoids.
-/
noncomputable section
universe v u
open CategoryTheory
open CategoryTheory.Limits
namespace CategoryTheory.SemiadditiveOfBinaryBiproducts
variable {C : Type u} [Category.{v} C] [HasZeroMorphisms C] [HasBinaryBiproducts C]
section
variable (X Y : C)
/-- `f +ₗ g` is the composite `X ⟶ Y ⊞ Y ⟶ Y`, where the first map is `(f, g)` and the second map
is `(𝟙 𝟙)`. -/
@[simp]
def leftAdd (f g : X ⟶ Y) : X ⟶ Y :=
biprod.lift f g ≫ biprod.desc (𝟙 Y) (𝟙 Y)
#align category_theory.semiadditive_of_binary_biproducts.left_add CategoryTheory.SemiadditiveOfBinaryBiproducts.leftAdd
/-- `f +ᵣ g` is the composite `X ⟶ X ⊞ X ⟶ Y`, where the first map is `(𝟙, 𝟙)` and the second map
is `(f g)`. -/
@[simp]
def rightAdd (f g : X ⟶ Y) : X ⟶ Y :=
biprod.lift (𝟙 X) (𝟙 X) ≫ biprod.desc f g
#align category_theory.semiadditive_of_binary_biproducts.right_add CategoryTheory.SemiadditiveOfBinaryBiproducts.rightAdd
local infixr:65 " +ₗ " => leftAdd X Y
local infixr:65 " +ᵣ " => rightAdd X Y
| Mathlib/CategoryTheory/Preadditive/OfBiproducts.lean | 54 | 68 | theorem isUnital_leftAdd : EckmannHilton.IsUnital (· +ₗ ·) 0 := by |
have hr : ∀ f : X ⟶ Y, biprod.lift (0 : X ⟶ Y) f = f ≫ biprod.inr := by
intro f
ext
· aesop_cat
· simp [biprod.lift_fst, Category.assoc, biprod.inr_fst, comp_zero]
have hl : ∀ f : X ⟶ Y, biprod.lift f (0 : X ⟶ Y) = f ≫ biprod.inl := by
intro f
ext
· aesop_cat
· simp [biprod.lift_snd, Category.assoc, biprod.inl_snd, comp_zero]
exact {
left_id := fun f => by simp [hr f, leftAdd, Category.assoc, Category.comp_id, biprod.inr_desc],
right_id := fun f => by simp [hl f, leftAdd, Category.assoc, Category.comp_id, biprod.inl_desc]
}
|
/-
Copyright (c) 2018 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Reid Barton, Mario Carneiro, Scott Morrison, Floris van Doorn
-/
import Mathlib.CategoryTheory.Limits.IsLimit
import Mathlib.CategoryTheory.Category.ULift
import Mathlib.CategoryTheory.EssentiallySmall
import Mathlib.Logic.Equiv.Basic
#align_import category_theory.limits.has_limits from "leanprover-community/mathlib"@"2738d2ca56cbc63be80c3bd48e9ed90ad94e947d"
/-!
# Existence of limits and colimits
In `CategoryTheory.Limits.IsLimit` we defined `IsLimit c`,
the data showing that a cone `c` is a limit cone.
The two main structures defined in this file are:
* `LimitCone F`, which consists of a choice of cone for `F` and the fact it is a limit cone, and
* `HasLimit F`, asserting the mere existence of some limit cone for `F`.
`HasLimit` is a propositional typeclass
(it's important that it is a proposition merely asserting the existence of a limit,
as otherwise we would have non-defeq problems from incompatible instances).
While `HasLimit` only asserts the existence of a limit cone,
we happily use the axiom of choice in mathlib,
so there are convenience functions all depending on `HasLimit F`:
* `limit F : C`, producing some limit object (of course all such are isomorphic)
* `limit.π F j : limit F ⟶ F.obj j`, the morphisms out of the limit,
* `limit.lift F c : c.pt ⟶ limit F`, the universal morphism from any other `c : Cone F`, etc.
Key to using the `HasLimit` interface is that there is an `@[ext]` lemma stating that
to check `f = g`, for `f g : Z ⟶ limit F`, it suffices to check `f ≫ limit.π F j = g ≫ limit.π F j`
for every `j`.
This, combined with `@[simp]` lemmas, makes it possible to prove many easy facts about limits using
automation (e.g. `tidy`).
There are abbreviations `HasLimitsOfShape J C` and `HasLimits C`
asserting the existence of classes of limits.
Later more are introduced, for finite limits, special shapes of limits, etc.
Ideally, many results about limits should be stated first in terms of `IsLimit`,
and then a result in terms of `HasLimit` derived from this.
At this point, however, this is far from uniformly achieved in mathlib ---
often statements are only written in terms of `HasLimit`.
## Implementation
At present we simply say everything twice, in order to handle both limits and colimits.
It would be highly desirable to have some automation support,
e.g. a `@[dualize]` attribute that behaves similarly to `@[to_additive]`.
## References
* [Stacks: Limits and colimits](https://stacks.math.columbia.edu/tag/002D)
-/
noncomputable section
open CategoryTheory CategoryTheory.Category CategoryTheory.Functor Opposite
namespace CategoryTheory.Limits
-- morphism levels before object levels. See note [CategoryTheory universes].
universe v₁ u₁ v₂ u₂ v₃ u₃ v v' v'' u u' u''
variable {J : Type u₁} [Category.{v₁} J] {K : Type u₂} [Category.{v₂} K]
variable {C : Type u} [Category.{v} C]
variable {F : J ⥤ C}
section Limit
/-- `LimitCone F` contains a cone over `F` together with the information that it is a limit. -/
-- @[nolint has_nonempty_instance] -- Porting note(#5171): removed; linter not ported yet
structure LimitCone (F : J ⥤ C) where
/-- The cone itself -/
cone : Cone F
/-- The proof that is the limit cone -/
isLimit : IsLimit cone
#align category_theory.limits.limit_cone CategoryTheory.Limits.LimitCone
#align category_theory.limits.limit_cone.is_limit CategoryTheory.Limits.LimitCone.isLimit
/-- `HasLimit F` represents the mere existence of a limit for `F`. -/
class HasLimit (F : J ⥤ C) : Prop where mk' ::
/-- There is some limit cone for `F` -/
exists_limit : Nonempty (LimitCone F)
#align category_theory.limits.has_limit CategoryTheory.Limits.HasLimit
theorem HasLimit.mk {F : J ⥤ C} (d : LimitCone F) : HasLimit F :=
⟨Nonempty.intro d⟩
#align category_theory.limits.has_limit.mk CategoryTheory.Limits.HasLimit.mk
/-- Use the axiom of choice to extract explicit `LimitCone F` from `HasLimit F`. -/
def getLimitCone (F : J ⥤ C) [HasLimit F] : LimitCone F :=
Classical.choice <| HasLimit.exists_limit
#align category_theory.limits.get_limit_cone CategoryTheory.Limits.getLimitCone
variable (J C)
/-- `C` has limits of shape `J` if there exists a limit for every functor `F : J ⥤ C`. -/
class HasLimitsOfShape : Prop where
/-- All functors `F : J ⥤ C` from `J` have limits -/
has_limit : ∀ F : J ⥤ C, HasLimit F := by infer_instance
#align category_theory.limits.has_limits_of_shape CategoryTheory.Limits.HasLimitsOfShape
/-- `C` has all limits of size `v₁ u₁` (`HasLimitsOfSize.{v₁ u₁} C`)
if it has limits of every shape `J : Type u₁` with `[Category.{v₁} J]`.
-/
@[pp_with_univ]
class HasLimitsOfSize (C : Type u) [Category.{v} C] : Prop where
/-- All functors `F : J ⥤ C` from all small `J` have limits -/
has_limits_of_shape : ∀ (J : Type u₁) [Category.{v₁} J], HasLimitsOfShape J C := by
infer_instance
#align category_theory.limits.has_limits_of_size CategoryTheory.Limits.HasLimitsOfSize
/-- `C` has all (small) limits if it has limits of every shape that is as big as its hom-sets. -/
abbrev HasLimits (C : Type u) [Category.{v} C] : Prop :=
HasLimitsOfSize.{v, v} C
#align category_theory.limits.has_limits CategoryTheory.Limits.HasLimits
theorem HasLimits.has_limits_of_shape {C : Type u} [Category.{v} C] [HasLimits C] (J : Type v)
[Category.{v} J] : HasLimitsOfShape J C :=
HasLimitsOfSize.has_limits_of_shape J
#align category_theory.limits.has_limits.has_limits_of_shape CategoryTheory.Limits.HasLimits.has_limits_of_shape
variable {J C}
-- see Note [lower instance priority]
instance (priority := 100) hasLimitOfHasLimitsOfShape {J : Type u₁} [Category.{v₁} J]
[HasLimitsOfShape J C] (F : J ⥤ C) : HasLimit F :=
HasLimitsOfShape.has_limit F
#align category_theory.limits.has_limit_of_has_limits_of_shape CategoryTheory.Limits.hasLimitOfHasLimitsOfShape
-- see Note [lower instance priority]
instance (priority := 100) hasLimitsOfShapeOfHasLimits {J : Type u₁} [Category.{v₁} J]
[HasLimitsOfSize.{v₁, u₁} C] : HasLimitsOfShape J C :=
HasLimitsOfSize.has_limits_of_shape J
#align category_theory.limits.has_limits_of_shape_of_has_limits CategoryTheory.Limits.hasLimitsOfShapeOfHasLimits
-- Interface to the `HasLimit` class.
/-- An arbitrary choice of limit cone for a functor. -/
def limit.cone (F : J ⥤ C) [HasLimit F] : Cone F :=
(getLimitCone F).cone
#align category_theory.limits.limit.cone CategoryTheory.Limits.limit.cone
/-- An arbitrary choice of limit object of a functor. -/
def limit (F : J ⥤ C) [HasLimit F] :=
(limit.cone F).pt
#align category_theory.limits.limit CategoryTheory.Limits.limit
/-- The projection from the limit object to a value of the functor. -/
def limit.π (F : J ⥤ C) [HasLimit F] (j : J) : limit F ⟶ F.obj j :=
(limit.cone F).π.app j
#align category_theory.limits.limit.π CategoryTheory.Limits.limit.π
@[simp]
theorem limit.cone_x {F : J ⥤ C} [HasLimit F] : (limit.cone F).pt = limit F :=
rfl
set_option linter.uppercaseLean3 false in
#align category_theory.limits.limit.cone_X CategoryTheory.Limits.limit.cone_x
@[simp]
theorem limit.cone_π {F : J ⥤ C} [HasLimit F] : (limit.cone F).π.app = limit.π _ :=
rfl
#align category_theory.limits.limit.cone_π CategoryTheory.Limits.limit.cone_π
@[reassoc (attr := simp)]
theorem limit.w (F : J ⥤ C) [HasLimit F] {j j' : J} (f : j ⟶ j') :
limit.π F j ≫ F.map f = limit.π F j' :=
(limit.cone F).w f
#align category_theory.limits.limit.w CategoryTheory.Limits.limit.w
/-- Evidence that the arbitrary choice of cone provided by `limit.cone F` is a limit cone. -/
def limit.isLimit (F : J ⥤ C) [HasLimit F] : IsLimit (limit.cone F) :=
(getLimitCone F).isLimit
#align category_theory.limits.limit.is_limit CategoryTheory.Limits.limit.isLimit
/-- The morphism from the cone point of any other cone to the limit object. -/
def limit.lift (F : J ⥤ C) [HasLimit F] (c : Cone F) : c.pt ⟶ limit F :=
(limit.isLimit F).lift c
#align category_theory.limits.limit.lift CategoryTheory.Limits.limit.lift
@[simp]
theorem limit.isLimit_lift {F : J ⥤ C} [HasLimit F] (c : Cone F) :
(limit.isLimit F).lift c = limit.lift F c :=
rfl
#align category_theory.limits.limit.is_limit_lift CategoryTheory.Limits.limit.isLimit_lift
@[reassoc (attr := simp)]
theorem limit.lift_π {F : J ⥤ C} [HasLimit F] (c : Cone F) (j : J) :
limit.lift F c ≫ limit.π F j = c.π.app j :=
IsLimit.fac _ c j
#align category_theory.limits.limit.lift_π CategoryTheory.Limits.limit.lift_π
/-- Functoriality of limits.
Usually this morphism should be accessed through `lim.map`,
but may be needed separately when you have specified limits for the source and target functors,
but not necessarily for all functors of shape `J`.
-/
def limMap {F G : J ⥤ C} [HasLimit F] [HasLimit G] (α : F ⟶ G) : limit F ⟶ limit G :=
IsLimit.map _ (limit.isLimit G) α
#align category_theory.limits.lim_map CategoryTheory.Limits.limMap
@[reassoc (attr := simp)]
theorem limMap_π {F G : J ⥤ C} [HasLimit F] [HasLimit G] (α : F ⟶ G) (j : J) :
limMap α ≫ limit.π G j = limit.π F j ≫ α.app j :=
limit.lift_π _ j
#align category_theory.limits.lim_map_π CategoryTheory.Limits.limMap_π
/-- The cone morphism from any cone to the arbitrary choice of limit cone. -/
def limit.coneMorphism {F : J ⥤ C} [HasLimit F] (c : Cone F) : c ⟶ limit.cone F :=
(limit.isLimit F).liftConeMorphism c
#align category_theory.limits.limit.cone_morphism CategoryTheory.Limits.limit.coneMorphism
@[simp]
theorem limit.coneMorphism_hom {F : J ⥤ C} [HasLimit F] (c : Cone F) :
(limit.coneMorphism c).hom = limit.lift F c :=
rfl
#align category_theory.limits.limit.cone_morphism_hom CategoryTheory.Limits.limit.coneMorphism_hom
theorem limit.coneMorphism_π {F : J ⥤ C} [HasLimit F] (c : Cone F) (j : J) :
(limit.coneMorphism c).hom ≫ limit.π F j = c.π.app j := by simp
#align category_theory.limits.limit.cone_morphism_π CategoryTheory.Limits.limit.coneMorphism_π
@[reassoc (attr := simp)]
theorem limit.conePointUniqueUpToIso_hom_comp {F : J ⥤ C} [HasLimit F] {c : Cone F} (hc : IsLimit c)
(j : J) : (IsLimit.conePointUniqueUpToIso hc (limit.isLimit _)).hom ≫ limit.π F j = c.π.app j :=
IsLimit.conePointUniqueUpToIso_hom_comp _ _ _
#align category_theory.limits.limit.cone_point_unique_up_to_iso_hom_comp CategoryTheory.Limits.limit.conePointUniqueUpToIso_hom_comp
@[reassoc (attr := simp)]
theorem limit.conePointUniqueUpToIso_inv_comp {F : J ⥤ C} [HasLimit F] {c : Cone F} (hc : IsLimit c)
(j : J) : (IsLimit.conePointUniqueUpToIso (limit.isLimit _) hc).inv ≫ limit.π F j = c.π.app j :=
IsLimit.conePointUniqueUpToIso_inv_comp _ _ _
#align category_theory.limits.limit.cone_point_unique_up_to_iso_inv_comp CategoryTheory.Limits.limit.conePointUniqueUpToIso_inv_comp
theorem limit.existsUnique {F : J ⥤ C} [HasLimit F] (t : Cone F) :
∃! l : t.pt ⟶ limit F, ∀ j, l ≫ limit.π F j = t.π.app j :=
(limit.isLimit F).existsUnique _
#align category_theory.limits.limit.exists_unique CategoryTheory.Limits.limit.existsUnique
/-- Given any other limit cone for `F`, the chosen `limit F` is isomorphic to the cone point.
-/
def limit.isoLimitCone {F : J ⥤ C} [HasLimit F] (t : LimitCone F) : limit F ≅ t.cone.pt :=
IsLimit.conePointUniqueUpToIso (limit.isLimit F) t.isLimit
#align category_theory.limits.limit.iso_limit_cone CategoryTheory.Limits.limit.isoLimitCone
@[reassoc (attr := simp)]
theorem limit.isoLimitCone_hom_π {F : J ⥤ C} [HasLimit F] (t : LimitCone F) (j : J) :
(limit.isoLimitCone t).hom ≫ t.cone.π.app j = limit.π F j := by
dsimp [limit.isoLimitCone, IsLimit.conePointUniqueUpToIso]
aesop_cat
#align category_theory.limits.limit.iso_limit_cone_hom_π CategoryTheory.Limits.limit.isoLimitCone_hom_π
@[reassoc (attr := simp)]
theorem limit.isoLimitCone_inv_π {F : J ⥤ C} [HasLimit F] (t : LimitCone F) (j : J) :
(limit.isoLimitCone t).inv ≫ limit.π F j = t.cone.π.app j := by
dsimp [limit.isoLimitCone, IsLimit.conePointUniqueUpToIso]
aesop_cat
#align category_theory.limits.limit.iso_limit_cone_inv_π CategoryTheory.Limits.limit.isoLimitCone_inv_π
@[ext]
theorem limit.hom_ext {F : J ⥤ C} [HasLimit F] {X : C} {f f' : X ⟶ limit F}
(w : ∀ j, f ≫ limit.π F j = f' ≫ limit.π F j) : f = f' :=
(limit.isLimit F).hom_ext w
#align category_theory.limits.limit.hom_ext CategoryTheory.Limits.limit.hom_ext
@[simp]
theorem limit.lift_map {F G : J ⥤ C} [HasLimit F] [HasLimit G] (c : Cone F) (α : F ⟶ G) :
limit.lift F c ≫ limMap α = limit.lift G ((Cones.postcompose α).obj c) := by
ext
rw [assoc, limMap_π, limit.lift_π_assoc, limit.lift_π]
rfl
#align category_theory.limits.limit.lift_map CategoryTheory.Limits.limit.lift_map
@[simp]
theorem limit.lift_cone {F : J ⥤ C} [HasLimit F] : limit.lift F (limit.cone F) = 𝟙 (limit F) :=
(limit.isLimit _).lift_self
#align category_theory.limits.limit.lift_cone CategoryTheory.Limits.limit.lift_cone
/-- The isomorphism (in `Type`) between
morphisms from a specified object `W` to the limit object,
and cones with cone point `W`.
-/
def limit.homIso (F : J ⥤ C) [HasLimit F] (W : C) :
ULift.{u₁} (W ⟶ limit F : Type v) ≅ F.cones.obj (op W) :=
(limit.isLimit F).homIso W
#align category_theory.limits.limit.hom_iso CategoryTheory.Limits.limit.homIso
@[simp]
theorem limit.homIso_hom (F : J ⥤ C) [HasLimit F] {W : C} (f : ULift (W ⟶ limit F)) :
(limit.homIso F W).hom f = (const J).map f.down ≫ (limit.cone F).π :=
(limit.isLimit F).homIso_hom f
#align category_theory.limits.limit.hom_iso_hom CategoryTheory.Limits.limit.homIso_hom
/-- The isomorphism (in `Type`) between
morphisms from a specified object `W` to the limit object,
and an explicit componentwise description of cones with cone point `W`.
-/
def limit.homIso' (F : J ⥤ C) [HasLimit F] (W : C) :
ULift.{u₁} (W ⟶ limit F : Type v) ≅
{ p : ∀ j, W ⟶ F.obj j // ∀ {j j' : J} (f : j ⟶ j'), p j ≫ F.map f = p j' } :=
(limit.isLimit F).homIso' W
#align category_theory.limits.limit.hom_iso' CategoryTheory.Limits.limit.homIso'
theorem limit.lift_extend {F : J ⥤ C} [HasLimit F] (c : Cone F) {X : C} (f : X ⟶ c.pt) :
limit.lift F (c.extend f) = f ≫ limit.lift F c := by aesop_cat
#align category_theory.limits.limit.lift_extend CategoryTheory.Limits.limit.lift_extend
/-- If a functor `F` has a limit, so does any naturally isomorphic functor.
-/
theorem hasLimitOfIso {F G : J ⥤ C} [HasLimit F] (α : F ≅ G) : HasLimit G :=
HasLimit.mk
{ cone := (Cones.postcompose α.hom).obj (limit.cone F)
isLimit := (IsLimit.postcomposeHomEquiv _ _).symm (limit.isLimit F) }
#align category_theory.limits.has_limit_of_iso CategoryTheory.Limits.hasLimitOfIso
-- See the construction of limits from products and equalizers
-- for an example usage.
/-- If a functor `G` has the same collection of cones as a functor `F`
which has a limit, then `G` also has a limit. -/
theorem HasLimit.ofConesIso {J K : Type u₁} [Category.{v₁} J] [Category.{v₂} K] (F : J ⥤ C)
(G : K ⥤ C) (h : F.cones ≅ G.cones) [HasLimit F] : HasLimit G :=
HasLimit.mk ⟨_, IsLimit.ofNatIso (IsLimit.natIso (limit.isLimit F) ≪≫ h)⟩
#align category_theory.limits.has_limit.of_cones_iso CategoryTheory.Limits.HasLimit.ofConesIso
/-- The limits of `F : J ⥤ C` and `G : J ⥤ C` are isomorphic,
if the functors are naturally isomorphic.
-/
def HasLimit.isoOfNatIso {F G : J ⥤ C} [HasLimit F] [HasLimit G] (w : F ≅ G) : limit F ≅ limit G :=
IsLimit.conePointsIsoOfNatIso (limit.isLimit F) (limit.isLimit G) w
#align category_theory.limits.has_limit.iso_of_nat_iso CategoryTheory.Limits.HasLimit.isoOfNatIso
@[reassoc (attr := simp)]
theorem HasLimit.isoOfNatIso_hom_π {F G : J ⥤ C} [HasLimit F] [HasLimit G] (w : F ≅ G) (j : J) :
(HasLimit.isoOfNatIso w).hom ≫ limit.π G j = limit.π F j ≫ w.hom.app j :=
IsLimit.conePointsIsoOfNatIso_hom_comp _ _ _ _
#align category_theory.limits.has_limit.iso_of_nat_iso_hom_π CategoryTheory.Limits.HasLimit.isoOfNatIso_hom_π
@[reassoc (attr := simp)]
theorem HasLimit.isoOfNatIso_inv_π {F G : J ⥤ C} [HasLimit F] [HasLimit G] (w : F ≅ G) (j : J) :
(HasLimit.isoOfNatIso w).inv ≫ limit.π F j = limit.π G j ≫ w.inv.app j :=
IsLimit.conePointsIsoOfNatIso_inv_comp _ _ _ _
#align category_theory.limits.has_limit.iso_of_nat_iso_inv_π CategoryTheory.Limits.HasLimit.isoOfNatIso_inv_π
@[reassoc (attr := simp)]
theorem HasLimit.lift_isoOfNatIso_hom {F G : J ⥤ C} [HasLimit F] [HasLimit G] (t : Cone F)
(w : F ≅ G) :
limit.lift F t ≫ (HasLimit.isoOfNatIso w).hom =
limit.lift G ((Cones.postcompose w.hom).obj _) :=
IsLimit.lift_comp_conePointsIsoOfNatIso_hom _ _ _
#align category_theory.limits.has_limit.lift_iso_of_nat_iso_hom CategoryTheory.Limits.HasLimit.lift_isoOfNatIso_hom
@[reassoc (attr := simp)]
theorem HasLimit.lift_isoOfNatIso_inv {F G : J ⥤ C} [HasLimit F] [HasLimit G] (t : Cone G)
(w : F ≅ G) :
limit.lift G t ≫ (HasLimit.isoOfNatIso w).inv =
limit.lift F ((Cones.postcompose w.inv).obj _) :=
IsLimit.lift_comp_conePointsIsoOfNatIso_inv _ _ _
#align category_theory.limits.has_limit.lift_iso_of_nat_iso_inv CategoryTheory.Limits.HasLimit.lift_isoOfNatIso_inv
/-- The limits of `F : J ⥤ C` and `G : K ⥤ C` are isomorphic,
if there is an equivalence `e : J ≌ K` making the triangle commute up to natural isomorphism.
-/
def HasLimit.isoOfEquivalence {F : J ⥤ C} [HasLimit F] {G : K ⥤ C} [HasLimit G] (e : J ≌ K)
(w : e.functor ⋙ G ≅ F) : limit F ≅ limit G :=
IsLimit.conePointsIsoOfEquivalence (limit.isLimit F) (limit.isLimit G) e w
#align category_theory.limits.has_limit.iso_of_equivalence CategoryTheory.Limits.HasLimit.isoOfEquivalence
@[simp]
theorem HasLimit.isoOfEquivalence_hom_π {F : J ⥤ C} [HasLimit F] {G : K ⥤ C} [HasLimit G]
(e : J ≌ K) (w : e.functor ⋙ G ≅ F) (k : K) :
(HasLimit.isoOfEquivalence e w).hom ≫ limit.π G k =
limit.π F (e.inverse.obj k) ≫ w.inv.app (e.inverse.obj k) ≫ G.map (e.counit.app k) := by
simp only [HasLimit.isoOfEquivalence, IsLimit.conePointsIsoOfEquivalence_hom]
dsimp
simp
#align category_theory.limits.has_limit.iso_of_equivalence_hom_π CategoryTheory.Limits.HasLimit.isoOfEquivalence_hom_π
@[simp]
theorem HasLimit.isoOfEquivalence_inv_π {F : J ⥤ C} [HasLimit F] {G : K ⥤ C} [HasLimit G]
(e : J ≌ K) (w : e.functor ⋙ G ≅ F) (j : J) :
(HasLimit.isoOfEquivalence e w).inv ≫ limit.π F j =
limit.π G (e.functor.obj j) ≫ w.hom.app j := by
simp only [HasLimit.isoOfEquivalence, IsLimit.conePointsIsoOfEquivalence_hom]
dsimp
simp
#align category_theory.limits.has_limit.iso_of_equivalence_inv_π CategoryTheory.Limits.HasLimit.isoOfEquivalence_inv_π
section Pre
variable (F) [HasLimit F] (E : K ⥤ J) [HasLimit (E ⋙ F)]
/-- The canonical morphism from the limit of `F` to the limit of `E ⋙ F`.
-/
def limit.pre : limit F ⟶ limit (E ⋙ F) :=
limit.lift (E ⋙ F) ((limit.cone F).whisker E)
#align category_theory.limits.limit.pre CategoryTheory.Limits.limit.pre
@[reassoc (attr := simp)]
theorem limit.pre_π (k : K) : limit.pre F E ≫ limit.π (E ⋙ F) k = limit.π F (E.obj k) := by
erw [IsLimit.fac]
rfl
#align category_theory.limits.limit.pre_π CategoryTheory.Limits.limit.pre_π
@[simp]
theorem limit.lift_pre (c : Cone F) :
limit.lift F c ≫ limit.pre F E = limit.lift (E ⋙ F) (c.whisker E) := by ext; simp
#align category_theory.limits.limit.lift_pre CategoryTheory.Limits.limit.lift_pre
variable {L : Type u₃} [Category.{v₃} L]
variable (D : L ⥤ K) [HasLimit (D ⋙ E ⋙ F)]
@[simp]
theorem limit.pre_pre [h : HasLimit (D ⋙ E ⋙ F)] : haveI : HasLimit ((D ⋙ E) ⋙ F) := h;
limit.pre F E ≫ limit.pre (E ⋙ F) D = limit.pre F (D ⋙ E) := by
haveI : HasLimit ((D ⋙ E) ⋙ F) := h
ext j; erw [assoc, limit.pre_π, limit.pre_π, limit.pre_π]; rfl
#align category_theory.limits.limit.pre_pre CategoryTheory.Limits.limit.pre_pre
variable {E F}
/-- -
If we have particular limit cones available for `E ⋙ F` and for `F`,
we obtain a formula for `limit.pre F E`.
-/
theorem limit.pre_eq (s : LimitCone (E ⋙ F)) (t : LimitCone F) :
limit.pre F E = (limit.isoLimitCone t).hom ≫ s.isLimit.lift (t.cone.whisker E) ≫
(limit.isoLimitCone s).inv := by aesop_cat
#align category_theory.limits.limit.pre_eq CategoryTheory.Limits.limit.pre_eq
end Pre
section Post
variable {D : Type u'} [Category.{v'} D]
variable (F) [HasLimit F] (G : C ⥤ D) [HasLimit (F ⋙ G)]
/-- The canonical morphism from `G` applied to the limit of `F` to the limit of `F ⋙ G`.
-/
def limit.post : G.obj (limit F) ⟶ limit (F ⋙ G) :=
limit.lift (F ⋙ G) (G.mapCone (limit.cone F))
#align category_theory.limits.limit.post CategoryTheory.Limits.limit.post
@[reassoc (attr := simp)]
theorem limit.post_π (j : J) : limit.post F G ≫ limit.π (F ⋙ G) j = G.map (limit.π F j) := by
erw [IsLimit.fac]
rfl
#align category_theory.limits.limit.post_π CategoryTheory.Limits.limit.post_π
@[simp]
theorem limit.lift_post (c : Cone F) :
G.map (limit.lift F c) ≫ limit.post F G = limit.lift (F ⋙ G) (G.mapCone c) := by
ext
rw [assoc, limit.post_π, ← G.map_comp, limit.lift_π, limit.lift_π]
rfl
#align category_theory.limits.limit.lift_post CategoryTheory.Limits.limit.lift_post
@[simp]
theorem limit.post_post {E : Type u''} [Category.{v''} E] (H : D ⥤ E) [h : HasLimit ((F ⋙ G) ⋙ H)] :
-- H G (limit F) ⟶ H (limit (F ⋙ G)) ⟶ limit ((F ⋙ G) ⋙ H) equals
-- H G (limit F) ⟶ limit (F ⋙ (G ⋙ H))
haveI : HasLimit (F ⋙ G ⋙ H) := h
H.map (limit.post F G) ≫ limit.post (F ⋙ G) H = limit.post F (G ⋙ H) := by
haveI : HasLimit (F ⋙ G ⋙ H) := h
ext; erw [assoc, limit.post_π, ← H.map_comp, limit.post_π, limit.post_π]; rfl
#align category_theory.limits.limit.post_post CategoryTheory.Limits.limit.post_post
end Post
theorem limit.pre_post {D : Type u'} [Category.{v'} D] (E : K ⥤ J) (F : J ⥤ C) (G : C ⥤ D)
[HasLimit F] [HasLimit (E ⋙ F)] [HasLimit (F ⋙ G)]
[h : HasLimit ((E ⋙ F) ⋙ G)] :-- G (limit F) ⟶ G (limit (E ⋙ F)) ⟶ limit ((E ⋙ F) ⋙ G) vs
-- G (limit F) ⟶ limit F ⋙ G ⟶ limit (E ⋙ (F ⋙ G)) or
haveI : HasLimit (E ⋙ F ⋙ G) := h
G.map (limit.pre F E) ≫ limit.post (E ⋙ F) G = limit.post F G ≫ limit.pre (F ⋙ G) E := by
haveI : HasLimit (E ⋙ F ⋙ G) := h
ext; erw [assoc, limit.post_π, ← G.map_comp, limit.pre_π, assoc, limit.pre_π, limit.post_π]
#align category_theory.limits.limit.pre_post CategoryTheory.Limits.limit.pre_post
open CategoryTheory.Equivalence
instance hasLimitEquivalenceComp (e : K ≌ J) [HasLimit F] : HasLimit (e.functor ⋙ F) :=
HasLimit.mk
{ cone := Cone.whisker e.functor (limit.cone F)
isLimit := IsLimit.whiskerEquivalence (limit.isLimit F) e }
#align category_theory.limits.has_limit_equivalence_comp CategoryTheory.Limits.hasLimitEquivalenceComp
-- Porting note: testing whether this still needed
-- attribute [local elab_without_expected_type] inv_fun_id_assoc
-- not entirely sure why this is needed
/-- If a `E ⋙ F` has a limit, and `E` is an equivalence, we can construct a limit of `F`.
-/
theorem hasLimitOfEquivalenceComp (e : K ≌ J) [HasLimit (e.functor ⋙ F)] : HasLimit F := by
haveI : HasLimit (e.inverse ⋙ e.functor ⋙ F) := Limits.hasLimitEquivalenceComp e.symm
apply hasLimitOfIso (e.invFunIdAssoc F)
#align category_theory.limits.has_limit_of_equivalence_comp CategoryTheory.Limits.hasLimitOfEquivalenceComp
-- `hasLimitCompEquivalence` and `hasLimitOfCompEquivalence`
-- are proved in `CategoryTheory/Adjunction/Limits.lean`.
section LimFunctor
variable [HasLimitsOfShape J C]
section
/-- `limit F` is functorial in `F`, when `C` has all limits of shape `J`. -/
@[simps]
def lim : (J ⥤ C) ⥤ C where
obj F := limit F
map α := limMap α
map_id F := by
apply Limits.limit.hom_ext; intro j
erw [limMap_π, Category.id_comp, Category.comp_id]
map_comp α β := by
apply Limits.limit.hom_ext; intro j
erw [assoc, IsLimit.fac, IsLimit.fac, ← assoc, IsLimit.fac, assoc]; rfl
#align category_theory.limits.lim CategoryTheory.Limits.lim
#align category_theory.limits.lim_map_eq_lim_map CategoryTheory.Limits.lim_map
end
variable {G : J ⥤ C} (α : F ⟶ G)
theorem limit.map_pre [HasLimitsOfShape K C] (E : K ⥤ J) :
lim.map α ≫ limit.pre G E = limit.pre F E ≫ lim.map (whiskerLeft E α) := by
ext
simp
#align category_theory.limits.limit.map_pre CategoryTheory.Limits.limit.map_pre
theorem limit.map_pre' [HasLimitsOfShape K C] (F : J ⥤ C) {E₁ E₂ : K ⥤ J} (α : E₁ ⟶ E₂) :
limit.pre F E₂ = limit.pre F E₁ ≫ lim.map (whiskerRight α F) := by
ext1; simp [← category.assoc]
#align category_theory.limits.limit.map_pre' CategoryTheory.Limits.limit.map_pre'
theorem limit.id_pre (F : J ⥤ C) : limit.pre F (𝟭 _) = lim.map (Functor.leftUnitor F).inv := by
aesop_cat
#align category_theory.limits.limit.id_pre CategoryTheory.Limits.limit.id_pre
theorem limit.map_post {D : Type u'} [Category.{v'} D] [HasLimitsOfShape J D] (H : C ⥤ D) :
/- H (limit F) ⟶ H (limit G) ⟶ limit (G ⋙ H) vs
H (limit F) ⟶ limit (F ⋙ H) ⟶ limit (G ⋙ H) -/
H.map (limMap α) ≫ limit.post G H = limit.post F H ≫ limMap (whiskerRight α H) := by
ext
simp only [whiskerRight_app, limMap_π, assoc, limit.post_π_assoc, limit.post_π, ← H.map_comp]
#align category_theory.limits.limit.map_post CategoryTheory.Limits.limit.map_post
/-- The isomorphism between
morphisms from `W` to the cone point of the limit cone for `F`
and cones over `F` with cone point `W`
is natural in `F`.
-/
def limYoneda :
lim ⋙ yoneda ⋙ (whiskeringRight _ _ _).obj uliftFunctor.{u₁} ≅ CategoryTheory.cones J C :=
NatIso.ofComponents fun F => NatIso.ofComponents fun W => limit.homIso F (unop W)
#align category_theory.limits.lim_yoneda CategoryTheory.Limits.limYoneda
/-- The constant functor and limit functor are adjoint to each other-/
def constLimAdj : (const J : C ⥤ J ⥤ C) ⊣ lim where
homEquiv c g :=
{ toFun := fun f => limit.lift _ ⟨c, f⟩
invFun := fun f =>
{ app := fun j => f ≫ limit.π _ _ }
left_inv := by aesop_cat
right_inv := by aesop_cat }
unit := { app := fun c => limit.lift _ ⟨_, 𝟙 _⟩ }
counit := { app := fun g => { app := limit.π _ } }
-- This used to be automatic before leanprover/lean4#2644
homEquiv_unit := by
-- Sad that aesop can no longer do this!
intros
dsimp
ext
simp
#align category_theory.limits.const_lim_adj CategoryTheory.Limits.constLimAdj
instance : IsRightAdjoint (lim : (J ⥤ C) ⥤ C) :=
⟨_, ⟨constLimAdj⟩⟩
end LimFunctor
instance limMap_mono' {F G : J ⥤ C} [HasLimitsOfShape J C] (α : F ⟶ G) [Mono α] : Mono (limMap α) :=
(lim : (J ⥤ C) ⥤ C).map_mono α
#align category_theory.limits.lim_map_mono' CategoryTheory.Limits.limMap_mono'
instance limMap_mono {F G : J ⥤ C} [HasLimit F] [HasLimit G] (α : F ⟶ G) [∀ j, Mono (α.app j)] :
Mono (limMap α) :=
⟨fun {Z} u v h =>
limit.hom_ext fun j => (cancel_mono (α.app j)).1 <| by simpa using h =≫ limit.π _ j⟩
#align category_theory.limits.lim_map_mono CategoryTheory.Limits.limMap_mono
section Adjunction
variable {L : (J ⥤ C) ⥤ C} (adj : Functor.const _ ⊣ L)
/- The fact that the existence of limits of shape `J` is equivalent to the existence
of a right adjoint to the constant functor `C ⥤ (J ⥤ C)` is obtained in
the file `Mathlib.CategoryTheory.Limits.ConeCategory`: see the lemma
`hasLimitsOfShape_iff_isLeftAdjoint_const`. In the definitions below, given an
adjunction `adj : Functor.const _ ⊣ (L : (J ⥤ C) ⥤ C)`, we directly construct
a limit cone for any `F : J ⥤ C`. -/
/-- The limit cone obtained from a right adjoint of the constant functor. -/
@[simps]
noncomputable def coneOfAdj (F : J ⥤ C) : Cone F where
pt := L.obj F
π := adj.counit.app F
/-- The cones defined by `coneOfAdj` are limit cones. -/
@[simps]
def isLimitConeOfAdj (F : J ⥤ C) :
IsLimit (coneOfAdj adj F) where
lift s := adj.homEquiv _ _ s.π
fac s j := by
have eq := NatTrans.congr_app (adj.counit.naturality s.π) j
have eq' := NatTrans.congr_app (adj.left_triangle_components s.pt) j
dsimp at eq eq' ⊢
rw [Adjunction.homEquiv_unit, assoc, eq, reassoc_of% eq']
uniq s m hm := (adj.homEquiv _ _).symm.injective (by ext j; simpa using hm j)
end Adjunction
/-- We can transport limits of shape `J` along an equivalence `J ≌ J'`.
-/
theorem hasLimitsOfShape_of_equivalence {J' : Type u₂} [Category.{v₂} J'] (e : J ≌ J')
[HasLimitsOfShape J C] : HasLimitsOfShape J' C := by
constructor
intro F
apply hasLimitOfEquivalenceComp e
#align category_theory.limits.has_limits_of_shape_of_equivalence CategoryTheory.Limits.hasLimitsOfShape_of_equivalence
variable (C)
/-- A category that has larger limits also has smaller limits. -/
theorem hasLimitsOfSizeOfUnivLE [UnivLE.{v₂, v₁}] [UnivLE.{u₂, u₁}]
[HasLimitsOfSize.{v₁, u₁} C] : HasLimitsOfSize.{v₂, u₂} C where
has_limits_of_shape J {_} := hasLimitsOfShape_of_equivalence
((ShrinkHoms.equivalence J).trans <| Shrink.equivalence _).symm
/-- `hasLimitsOfSizeShrink.{v u} C` tries to obtain `HasLimitsOfSize.{v u} C`
from some other `HasLimitsOfSize C`.
-/
theorem hasLimitsOfSizeShrink [HasLimitsOfSize.{max v₁ v₂, max u₁ u₂} C] :
HasLimitsOfSize.{v₁, u₁} C := hasLimitsOfSizeOfUnivLE.{max v₁ v₂, max u₁ u₂} C
#align category_theory.limits.has_limits_of_size_shrink CategoryTheory.Limits.hasLimitsOfSizeShrink
instance (priority := 100) hasSmallestLimitsOfHasLimits [HasLimits C] : HasLimitsOfSize.{0, 0} C :=
hasLimitsOfSizeShrink.{0, 0} C
#align category_theory.limits.has_smallest_limits_of_has_limits CategoryTheory.Limits.hasSmallestLimitsOfHasLimits
end Limit
section Colimit
/-- `ColimitCocone F` contains a cocone over `F` together with the information that it is a
colimit. -/
-- @[nolint has_nonempty_instance] -- Porting note(#5171): removed; linter not ported yet
structure ColimitCocone (F : J ⥤ C) where
/-- The cocone itself -/
cocone : Cocone F
/-- The proof that it is the colimit cocone -/
isColimit : IsColimit cocone
#align category_theory.limits.colimit_cocone CategoryTheory.Limits.ColimitCocone
#align category_theory.limits.colimit_cocone.is_colimit CategoryTheory.Limits.ColimitCocone.isColimit
/-- `HasColimit F` represents the mere existence of a colimit for `F`. -/
class HasColimit (F : J ⥤ C) : Prop where mk' ::
/-- There exists a colimit for `F` -/
exists_colimit : Nonempty (ColimitCocone F)
#align category_theory.limits.has_colimit CategoryTheory.Limits.HasColimit
theorem HasColimit.mk {F : J ⥤ C} (d : ColimitCocone F) : HasColimit F :=
⟨Nonempty.intro d⟩
#align category_theory.limits.has_colimit.mk CategoryTheory.Limits.HasColimit.mk
/-- Use the axiom of choice to extract explicit `ColimitCocone F` from `HasColimit F`. -/
def getColimitCocone (F : J ⥤ C) [HasColimit F] : ColimitCocone F :=
Classical.choice <| HasColimit.exists_colimit
#align category_theory.limits.get_colimit_cocone CategoryTheory.Limits.getColimitCocone
variable (J C)
/-- `C` has colimits of shape `J` if there exists a colimit for every functor `F : J ⥤ C`. -/
class HasColimitsOfShape : Prop where
/-- All `F : J ⥤ C` have colimits for a fixed `J` -/
has_colimit : ∀ F : J ⥤ C, HasColimit F := by infer_instance
#align category_theory.limits.has_colimits_of_shape CategoryTheory.Limits.HasColimitsOfShape
/-- `C` has all colimits of size `v₁ u₁` (`HasColimitsOfSize.{v₁ u₁} C`)
if it has colimits of every shape `J : Type u₁` with `[Category.{v₁} J]`.
-/
@[pp_with_univ]
class HasColimitsOfSize (C : Type u) [Category.{v} C] : Prop where
/-- All `F : J ⥤ C` have colimits for all small `J` -/
has_colimits_of_shape : ∀ (J : Type u₁) [Category.{v₁} J], HasColimitsOfShape J C := by
infer_instance
#align category_theory.limits.has_colimits_of_size CategoryTheory.Limits.HasColimitsOfSize
/-- `C` has all (small) colimits if it has colimits of every shape that is as big as its hom-sets.
-/
abbrev HasColimits (C : Type u) [Category.{v} C] : Prop :=
HasColimitsOfSize.{v, v} C
#align category_theory.limits.has_colimits CategoryTheory.Limits.HasColimits
theorem HasColimits.hasColimitsOfShape {C : Type u} [Category.{v} C] [HasColimits C] (J : Type v)
[Category.{v} J] : HasColimitsOfShape J C :=
HasColimitsOfSize.has_colimits_of_shape J
#align category_theory.limits.has_colimits.has_colimits_of_shape CategoryTheory.Limits.HasColimits.hasColimitsOfShape
variable {J C}
-- see Note [lower instance priority]
instance (priority := 100) hasColimitOfHasColimitsOfShape {J : Type u₁} [Category.{v₁} J]
[HasColimitsOfShape J C] (F : J ⥤ C) : HasColimit F :=
HasColimitsOfShape.has_colimit F
#align category_theory.limits.has_colimit_of_has_colimits_of_shape CategoryTheory.Limits.hasColimitOfHasColimitsOfShape
-- see Note [lower instance priority]
instance (priority := 100) hasColimitsOfShapeOfHasColimitsOfSize {J : Type u₁} [Category.{v₁} J]
[HasColimitsOfSize.{v₁, u₁} C] : HasColimitsOfShape J C :=
HasColimitsOfSize.has_colimits_of_shape J
#align category_theory.limits.has_colimits_of_shape_of_has_colimits_of_size CategoryTheory.Limits.hasColimitsOfShapeOfHasColimitsOfSize
-- Interface to the `HasColimit` class.
/-- An arbitrary choice of colimit cocone of a functor. -/
def colimit.cocone (F : J ⥤ C) [HasColimit F] : Cocone F :=
(getColimitCocone F).cocone
#align category_theory.limits.colimit.cocone CategoryTheory.Limits.colimit.cocone
/-- An arbitrary choice of colimit object of a functor. -/
def colimit (F : J ⥤ C) [HasColimit F] :=
(colimit.cocone F).pt
#align category_theory.limits.colimit CategoryTheory.Limits.colimit
/-- The coprojection from a value of the functor to the colimit object. -/
def colimit.ι (F : J ⥤ C) [HasColimit F] (j : J) : F.obj j ⟶ colimit F :=
(colimit.cocone F).ι.app j
#align category_theory.limits.colimit.ι CategoryTheory.Limits.colimit.ι
@[simp]
theorem colimit.cocone_ι {F : J ⥤ C} [HasColimit F] (j : J) :
(colimit.cocone F).ι.app j = colimit.ι _ j :=
rfl
#align category_theory.limits.colimit.cocone_ι CategoryTheory.Limits.colimit.cocone_ι
@[simp]
theorem colimit.cocone_x {F : J ⥤ C} [HasColimit F] : (colimit.cocone F).pt = colimit F :=
rfl
set_option linter.uppercaseLean3 false in
#align category_theory.limits.colimit.cocone_X CategoryTheory.Limits.colimit.cocone_x
@[reassoc (attr := simp)]
theorem colimit.w (F : J ⥤ C) [HasColimit F] {j j' : J} (f : j ⟶ j') :
F.map f ≫ colimit.ι F j' = colimit.ι F j :=
(colimit.cocone F).w f
#align category_theory.limits.colimit.w CategoryTheory.Limits.colimit.w
/-- Evidence that the arbitrary choice of cocone is a colimit cocone. -/
def colimit.isColimit (F : J ⥤ C) [HasColimit F] : IsColimit (colimit.cocone F) :=
(getColimitCocone F).isColimit
#align category_theory.limits.colimit.is_colimit CategoryTheory.Limits.colimit.isColimit
/-- The morphism from the colimit object to the cone point of any other cocone. -/
def colimit.desc (F : J ⥤ C) [HasColimit F] (c : Cocone F) : colimit F ⟶ c.pt :=
(colimit.isColimit F).desc c
#align category_theory.limits.colimit.desc CategoryTheory.Limits.colimit.desc
@[simp]
theorem colimit.isColimit_desc {F : J ⥤ C} [HasColimit F] (c : Cocone F) :
(colimit.isColimit F).desc c = colimit.desc F c :=
rfl
#align category_theory.limits.colimit.is_colimit_desc CategoryTheory.Limits.colimit.isColimit_desc
/-- We have lots of lemmas describing how to simplify `colimit.ι F j ≫ _`,
and combined with `colimit.ext` we rely on these lemmas for many calculations.
However, since `Category.assoc` is a `@[simp]` lemma, often expressions are
right associated, and it's hard to apply these lemmas about `colimit.ι`.
We thus use `reassoc` to define additional `@[simp]` lemmas, with an arbitrary extra morphism.
(see `Tactic/reassoc_axiom.lean`)
-/
@[reassoc (attr := simp)]
theorem colimit.ι_desc {F : J ⥤ C} [HasColimit F] (c : Cocone F) (j : J) :
colimit.ι F j ≫ colimit.desc F c = c.ι.app j :=
IsColimit.fac _ c j
#align category_theory.limits.colimit.ι_desc CategoryTheory.Limits.colimit.ι_desc
/-- Functoriality of colimits.
Usually this morphism should be accessed through `colim.map`,
but may be needed separately when you have specified colimits for the source and target functors,
but not necessarily for all functors of shape `J`.
-/
def colimMap {F G : J ⥤ C} [HasColimit F] [HasColimit G] (α : F ⟶ G) : colimit F ⟶ colimit G :=
IsColimit.map (colimit.isColimit F) _ α
#align category_theory.limits.colim_map CategoryTheory.Limits.colimMap
@[reassoc (attr := simp)]
theorem ι_colimMap {F G : J ⥤ C} [HasColimit F] [HasColimit G] (α : F ⟶ G) (j : J) :
colimit.ι F j ≫ colimMap α = α.app j ≫ colimit.ι G j :=
colimit.ι_desc _ j
#align category_theory.limits.ι_colim_map CategoryTheory.Limits.ι_colimMap
/-- The cocone morphism from the arbitrary choice of colimit cocone to any cocone. -/
def colimit.coconeMorphism {F : J ⥤ C} [HasColimit F] (c : Cocone F) : colimit.cocone F ⟶ c :=
(colimit.isColimit F).descCoconeMorphism c
#align category_theory.limits.colimit.cocone_morphism CategoryTheory.Limits.colimit.coconeMorphism
@[simp]
theorem colimit.coconeMorphism_hom {F : J ⥤ C} [HasColimit F] (c : Cocone F) :
(colimit.coconeMorphism c).hom = colimit.desc F c :=
rfl
#align category_theory.limits.colimit.cocone_morphism_hom CategoryTheory.Limits.colimit.coconeMorphism_hom
theorem colimit.ι_coconeMorphism {F : J ⥤ C} [HasColimit F] (c : Cocone F) (j : J) :
colimit.ι F j ≫ (colimit.coconeMorphism c).hom = c.ι.app j := by simp
#align category_theory.limits.colimit.ι_cocone_morphism CategoryTheory.Limits.colimit.ι_coconeMorphism
@[reassoc (attr := simp)]
theorem colimit.comp_coconePointUniqueUpToIso_hom {F : J ⥤ C} [HasColimit F] {c : Cocone F}
(hc : IsColimit c) (j : J) :
colimit.ι F j ≫ (IsColimit.coconePointUniqueUpToIso (colimit.isColimit _) hc).hom = c.ι.app j :=
IsColimit.comp_coconePointUniqueUpToIso_hom _ _ _
#align category_theory.limits.colimit.comp_cocone_point_unique_up_to_iso_hom CategoryTheory.Limits.colimit.comp_coconePointUniqueUpToIso_hom
@[reassoc (attr := simp)]
theorem colimit.comp_coconePointUniqueUpToIso_inv {F : J ⥤ C} [HasColimit F] {c : Cocone F}
(hc : IsColimit c) (j : J) :
colimit.ι F j ≫ (IsColimit.coconePointUniqueUpToIso hc (colimit.isColimit _)).inv = c.ι.app j :=
IsColimit.comp_coconePointUniqueUpToIso_inv _ _ _
#align category_theory.limits.colimit.comp_cocone_point_unique_up_to_iso_inv CategoryTheory.Limits.colimit.comp_coconePointUniqueUpToIso_inv
theorem colimit.existsUnique {F : J ⥤ C} [HasColimit F] (t : Cocone F) :
∃! d : colimit F ⟶ t.pt, ∀ j, colimit.ι F j ≫ d = t.ι.app j :=
(colimit.isColimit F).existsUnique _
#align category_theory.limits.colimit.exists_unique CategoryTheory.Limits.colimit.existsUnique
/--
Given any other colimit cocone for `F`, the chosen `colimit F` is isomorphic to the cocone point.
-/
def colimit.isoColimitCocone {F : J ⥤ C} [HasColimit F] (t : ColimitCocone F) :
colimit F ≅ t.cocone.pt :=
IsColimit.coconePointUniqueUpToIso (colimit.isColimit F) t.isColimit
#align category_theory.limits.colimit.iso_colimit_cocone CategoryTheory.Limits.colimit.isoColimitCocone
@[reassoc (attr := simp)]
theorem colimit.isoColimitCocone_ι_hom {F : J ⥤ C} [HasColimit F] (t : ColimitCocone F) (j : J) :
colimit.ι F j ≫ (colimit.isoColimitCocone t).hom = t.cocone.ι.app j := by
dsimp [colimit.isoColimitCocone, IsColimit.coconePointUniqueUpToIso]
aesop_cat
#align category_theory.limits.colimit.iso_colimit_cocone_ι_hom CategoryTheory.Limits.colimit.isoColimitCocone_ι_hom
@[reassoc (attr := simp)]
theorem colimit.isoColimitCocone_ι_inv {F : J ⥤ C} [HasColimit F] (t : ColimitCocone F) (j : J) :
t.cocone.ι.app j ≫ (colimit.isoColimitCocone t).inv = colimit.ι F j := by
dsimp [colimit.isoColimitCocone, IsColimit.coconePointUniqueUpToIso]
aesop_cat
#align category_theory.limits.colimit.iso_colimit_cocone_ι_inv CategoryTheory.Limits.colimit.isoColimitCocone_ι_inv
@[ext]
theorem colimit.hom_ext {F : J ⥤ C} [HasColimit F] {X : C} {f f' : colimit F ⟶ X}
(w : ∀ j, colimit.ι F j ≫ f = colimit.ι F j ≫ f') : f = f' :=
(colimit.isColimit F).hom_ext w
#align category_theory.limits.colimit.hom_ext CategoryTheory.Limits.colimit.hom_ext
@[simp]
theorem colimit.desc_cocone {F : J ⥤ C} [HasColimit F] :
colimit.desc F (colimit.cocone F) = 𝟙 (colimit F) :=
(colimit.isColimit _).desc_self
#align category_theory.limits.colimit.desc_cocone CategoryTheory.Limits.colimit.desc_cocone
/-- The isomorphism (in `Type`) between
morphisms from the colimit object to a specified object `W`,
and cocones with cone point `W`.
-/
def colimit.homIso (F : J ⥤ C) [HasColimit F] (W : C) :
ULift.{u₁} (colimit F ⟶ W : Type v) ≅ F.cocones.obj W :=
(colimit.isColimit F).homIso W
#align category_theory.limits.colimit.hom_iso CategoryTheory.Limits.colimit.homIso
@[simp]
theorem colimit.homIso_hom (F : J ⥤ C) [HasColimit F] {W : C} (f : ULift (colimit F ⟶ W)) :
(colimit.homIso F W).hom f = (colimit.cocone F).ι ≫ (const J).map f.down :=
(colimit.isColimit F).homIso_hom f
#align category_theory.limits.colimit.hom_iso_hom CategoryTheory.Limits.colimit.homIso_hom
/-- The isomorphism (in `Type`) between
morphisms from the colimit object to a specified object `W`,
and an explicit componentwise description of cocones with cone point `W`.
-/
def colimit.homIso' (F : J ⥤ C) [HasColimit F] (W : C) :
ULift.{u₁} (colimit F ⟶ W : Type v) ≅
{ p : ∀ j, F.obj j ⟶ W // ∀ {j j'} (f : j ⟶ j'), F.map f ≫ p j' = p j } :=
(colimit.isColimit F).homIso' W
#align category_theory.limits.colimit.hom_iso' CategoryTheory.Limits.colimit.homIso'
theorem colimit.desc_extend (F : J ⥤ C) [HasColimit F] (c : Cocone F) {X : C} (f : c.pt ⟶ X) :
colimit.desc F (c.extend f) = colimit.desc F c ≫ f := by ext1; rw [← Category.assoc]; simp
#align category_theory.limits.colimit.desc_extend CategoryTheory.Limits.colimit.desc_extend
-- This has the isomorphism pointing in the opposite direction than in `has_limit_of_iso`.
-- This is intentional; it seems to help with elaboration.
/-- If `F` has a colimit, so does any naturally isomorphic functor.
-/
theorem hasColimitOfIso {F G : J ⥤ C} [HasColimit F] (α : G ≅ F) : HasColimit G :=
HasColimit.mk
{ cocone := (Cocones.precompose α.hom).obj (colimit.cocone F)
isColimit := (IsColimit.precomposeHomEquiv _ _).symm (colimit.isColimit F) }
#align category_theory.limits.has_colimit_of_iso CategoryTheory.Limits.hasColimitOfIso
/-- If a functor `G` has the same collection of cocones as a functor `F`
which has a colimit, then `G` also has a colimit. -/
theorem HasColimit.ofCoconesIso {K : Type u₁} [Category.{v₂} K] (F : J ⥤ C) (G : K ⥤ C)
(h : F.cocones ≅ G.cocones) [HasColimit F] : HasColimit G :=
HasColimit.mk ⟨_, IsColimit.ofNatIso (IsColimit.natIso (colimit.isColimit F) ≪≫ h)⟩
#align category_theory.limits.has_colimit.of_cocones_iso CategoryTheory.Limits.HasColimit.ofCoconesIso
/-- The colimits of `F : J ⥤ C` and `G : J ⥤ C` are isomorphic,
if the functors are naturally isomorphic.
-/
def HasColimit.isoOfNatIso {F G : J ⥤ C} [HasColimit F] [HasColimit G] (w : F ≅ G) :
colimit F ≅ colimit G :=
IsColimit.coconePointsIsoOfNatIso (colimit.isColimit F) (colimit.isColimit G) w
#align category_theory.limits.has_colimit.iso_of_nat_iso CategoryTheory.Limits.HasColimit.isoOfNatIso
@[reassoc (attr := simp)]
theorem HasColimit.isoOfNatIso_ι_hom {F G : J ⥤ C} [HasColimit F] [HasColimit G] (w : F ≅ G)
(j : J) : colimit.ι F j ≫ (HasColimit.isoOfNatIso w).hom = w.hom.app j ≫ colimit.ι G j :=
IsColimit.comp_coconePointsIsoOfNatIso_hom _ _ _ _
#align category_theory.limits.has_colimit.iso_of_nat_iso_ι_hom CategoryTheory.Limits.HasColimit.isoOfNatIso_ι_hom
@[reassoc (attr := simp)]
theorem HasColimit.isoOfNatIso_ι_inv {F G : J ⥤ C} [HasColimit F] [HasColimit G] (w : F ≅ G)
(j : J) : colimit.ι G j ≫ (HasColimit.isoOfNatIso w).inv = w.inv.app j ≫ colimit.ι F j :=
IsColimit.comp_coconePointsIsoOfNatIso_inv _ _ _ _
#align category_theory.limits.has_colimit.iso_of_nat_iso_ι_inv CategoryTheory.Limits.HasColimit.isoOfNatIso_ι_inv
@[reassoc (attr := simp)]
theorem HasColimit.isoOfNatIso_hom_desc {F G : J ⥤ C} [HasColimit F] [HasColimit G] (t : Cocone G)
(w : F ≅ G) :
(HasColimit.isoOfNatIso w).hom ≫ colimit.desc G t =
colimit.desc F ((Cocones.precompose w.hom).obj _) :=
IsColimit.coconePointsIsoOfNatIso_hom_desc _ _ _
#align category_theory.limits.has_colimit.iso_of_nat_iso_hom_desc CategoryTheory.Limits.HasColimit.isoOfNatIso_hom_desc
@[reassoc (attr := simp)]
theorem HasColimit.isoOfNatIso_inv_desc {F G : J ⥤ C} [HasColimit F] [HasColimit G] (t : Cocone F)
(w : F ≅ G) :
(HasColimit.isoOfNatIso w).inv ≫ colimit.desc F t =
colimit.desc G ((Cocones.precompose w.inv).obj _) :=
IsColimit.coconePointsIsoOfNatIso_inv_desc _ _ _
#align category_theory.limits.has_colimit.iso_of_nat_iso_inv_desc CategoryTheory.Limits.HasColimit.isoOfNatIso_inv_desc
/-- The colimits of `F : J ⥤ C` and `G : K ⥤ C` are isomorphic,
if there is an equivalence `e : J ≌ K` making the triangle commute up to natural isomorphism.
-/
def HasColimit.isoOfEquivalence {F : J ⥤ C} [HasColimit F] {G : K ⥤ C} [HasColimit G] (e : J ≌ K)
(w : e.functor ⋙ G ≅ F) : colimit F ≅ colimit G :=
IsColimit.coconePointsIsoOfEquivalence (colimit.isColimit F) (colimit.isColimit G) e w
#align category_theory.limits.has_colimit.iso_of_equivalence CategoryTheory.Limits.HasColimit.isoOfEquivalence
@[simp]
theorem HasColimit.isoOfEquivalence_hom_π {F : J ⥤ C} [HasColimit F] {G : K ⥤ C} [HasColimit G]
(e : J ≌ K) (w : e.functor ⋙ G ≅ F) (j : J) :
colimit.ι F j ≫ (HasColimit.isoOfEquivalence e w).hom =
F.map (e.unit.app j) ≫ w.inv.app _ ≫ colimit.ι G _ := by
simp [HasColimit.isoOfEquivalence, IsColimit.coconePointsIsoOfEquivalence_inv]
#align category_theory.limits.has_colimit.iso_of_equivalence_hom_π CategoryTheory.Limits.HasColimit.isoOfEquivalence_hom_π
@[simp]
theorem HasColimit.isoOfEquivalence_inv_π {F : J ⥤ C} [HasColimit F] {G : K ⥤ C} [HasColimit G]
(e : J ≌ K) (w : e.functor ⋙ G ≅ F) (k : K) :
colimit.ι G k ≫ (HasColimit.isoOfEquivalence e w).inv =
G.map (e.counitInv.app k) ≫ w.hom.app (e.inverse.obj k) ≫ colimit.ι F (e.inverse.obj k) := by
simp [HasColimit.isoOfEquivalence, IsColimit.coconePointsIsoOfEquivalence_inv]
#align category_theory.limits.has_colimit.iso_of_equivalence_inv_π CategoryTheory.Limits.HasColimit.isoOfEquivalence_inv_π
section Pre
variable (F) [HasColimit F] (E : K ⥤ J) [HasColimit (E ⋙ F)]
/-- The canonical morphism from the colimit of `E ⋙ F` to the colimit of `F`.
-/
def colimit.pre : colimit (E ⋙ F) ⟶ colimit F :=
colimit.desc (E ⋙ F) ((colimit.cocone F).whisker E)
#align category_theory.limits.colimit.pre CategoryTheory.Limits.colimit.pre
@[reassoc (attr := simp)]
theorem colimit.ι_pre (k : K) : colimit.ι (E ⋙ F) k ≫ colimit.pre F E = colimit.ι F (E.obj k) := by
erw [IsColimit.fac]
rfl
#align category_theory.limits.colimit.ι_pre CategoryTheory.Limits.colimit.ι_pre
@[reassoc (attr := simp)]
theorem colimit.pre_desc (c : Cocone F) :
colimit.pre F E ≫ colimit.desc F c = colimit.desc (E ⋙ F) (c.whisker E) := by
ext; rw [← assoc, colimit.ι_pre]; simp
#align category_theory.limits.colimit.pre_desc CategoryTheory.Limits.colimit.pre_desc
variable {L : Type u₃} [Category.{v₃} L]
variable (D : L ⥤ K) [HasColimit (D ⋙ E ⋙ F)]
@[simp]
theorem colimit.pre_pre [h : HasColimit (D ⋙ E ⋙ F)] :
haveI : HasColimit ((D ⋙ E) ⋙ F) := h
colimit.pre (E ⋙ F) D ≫ colimit.pre F E = colimit.pre F (D ⋙ E) := by
ext j
rw [← assoc, colimit.ι_pre, colimit.ι_pre]
haveI : HasColimit ((D ⋙ E) ⋙ F) := h
exact (colimit.ι_pre F (D ⋙ E) j).symm
#align category_theory.limits.colimit.pre_pre CategoryTheory.Limits.colimit.pre_pre
variable {E F}
/-- -
If we have particular colimit cocones available for `E ⋙ F` and for `F`,
we obtain a formula for `colimit.pre F E`.
-/
theorem colimit.pre_eq (s : ColimitCocone (E ⋙ F)) (t : ColimitCocone F) :
colimit.pre F E =
(colimit.isoColimitCocone s).hom ≫
s.isColimit.desc (t.cocone.whisker E) ≫ (colimit.isoColimitCocone t).inv := by
aesop_cat
#align category_theory.limits.colimit.pre_eq CategoryTheory.Limits.colimit.pre_eq
end Pre
section Post
variable {D : Type u'} [Category.{v'} D]
variable (F) [HasColimit F] (G : C ⥤ D) [HasColimit (F ⋙ G)]
/-- The canonical morphism from `G` applied to the colimit of `F ⋙ G`
to `G` applied to the colimit of `F`.
-/
def colimit.post : colimit (F ⋙ G) ⟶ G.obj (colimit F) :=
colimit.desc (F ⋙ G) (G.mapCocone (colimit.cocone F))
#align category_theory.limits.colimit.post CategoryTheory.Limits.colimit.post
@[reassoc (attr := simp)]
theorem colimit.ι_post (j : J) :
colimit.ι (F ⋙ G) j ≫ colimit.post F G = G.map (colimit.ι F j) := by
erw [IsColimit.fac]
rfl
#align category_theory.limits.colimit.ι_post CategoryTheory.Limits.colimit.ι_post
@[simp]
theorem colimit.post_desc (c : Cocone F) :
colimit.post F G ≫ G.map (colimit.desc F c) = colimit.desc (F ⋙ G) (G.mapCocone c) := by
ext
rw [← assoc, colimit.ι_post, ← G.map_comp, colimit.ι_desc, colimit.ι_desc]
rfl
#align category_theory.limits.colimit.post_desc CategoryTheory.Limits.colimit.post_desc
@[simp]
theorem colimit.post_post {E : Type u''} [Category.{v''} E] (H : D ⥤ E)
-- H G (colimit F) ⟶ H (colimit (F ⋙ G)) ⟶ colimit ((F ⋙ G) ⋙ H) equals
-- H G (colimit F) ⟶ colimit (F ⋙ (G ⋙ H))
[h : HasColimit ((F ⋙ G) ⋙ H)] : haveI : HasColimit (F ⋙ G ⋙ H) := h
colimit.post (F ⋙ G) H ≫ H.map (colimit.post F G) = colimit.post F (G ⋙ H) := by
ext j
rw [← assoc, colimit.ι_post, ← H.map_comp, colimit.ι_post]
haveI : HasColimit (F ⋙ G ⋙ H) := h
exact (colimit.ι_post F (G ⋙ H) j).symm
#align category_theory.limits.colimit.post_post CategoryTheory.Limits.colimit.post_post
end Post
theorem colimit.pre_post {D : Type u'} [Category.{v'} D] (E : K ⥤ J) (F : J ⥤ C) (G : C ⥤ D)
[HasColimit F] [HasColimit (E ⋙ F)] [HasColimit (F ⋙ G)] [h : HasColimit ((E ⋙ F) ⋙ G)] :
-- G (colimit F) ⟶ G (colimit (E ⋙ F)) ⟶ colimit ((E ⋙ F) ⋙ G) vs
-- G (colimit F) ⟶ colimit F ⋙ G ⟶ colimit (E ⋙ (F ⋙ G)) or
haveI : HasColimit (E ⋙ F ⋙ G) := h
colimit.post (E ⋙ F) G ≫ G.map (colimit.pre F E) =
colimit.pre (F ⋙ G) E ≫ colimit.post F G := by
ext j
rw [← assoc, colimit.ι_post, ← G.map_comp, colimit.ι_pre, ← assoc]
haveI : HasColimit (E ⋙ F ⋙ G) := h
erw [colimit.ι_pre (F ⋙ G) E j, colimit.ι_post]
#align category_theory.limits.colimit.pre_post CategoryTheory.Limits.colimit.pre_post
open CategoryTheory.Equivalence
instance hasColimit_equivalence_comp (e : K ≌ J) [HasColimit F] : HasColimit (e.functor ⋙ F) :=
HasColimit.mk
{ cocone := Cocone.whisker e.functor (colimit.cocone F)
isColimit := IsColimit.whiskerEquivalence (colimit.isColimit F) e }
#align category_theory.limits.has_colimit_equivalence_comp CategoryTheory.Limits.hasColimit_equivalence_comp
/-- If a `E ⋙ F` has a colimit, and `E` is an equivalence, we can construct a colimit of `F`.
-/
theorem hasColimit_of_equivalence_comp (e : K ≌ J) [HasColimit (e.functor ⋙ F)] : HasColimit F := by
haveI : HasColimit (e.inverse ⋙ e.functor ⋙ F) := Limits.hasColimit_equivalence_comp e.symm
apply hasColimitOfIso (e.invFunIdAssoc F).symm
#align category_theory.limits.has_colimit_of_equivalence_comp CategoryTheory.Limits.hasColimit_of_equivalence_comp
section ColimFunctor
variable [HasColimitsOfShape J C]
section
-- attribute [local simp] colimMap -- Porting note: errors out colim.map_id and map_comp now
/-- `colimit F` is functorial in `F`, when `C` has all colimits of shape `J`. -/
@[simps] -- Porting note: simps on all fields now
def colim : (J ⥤ C) ⥤ C where
obj F := colimit F
map α := colimMap α
#align category_theory.limits.colim CategoryTheory.Limits.colim
end
variable {G : J ⥤ C} (α : F ⟶ G)
-- @[reassoc (attr := simp)] Porting note: now simp can prove these
@[reassoc]
theorem colimit.ι_map (j : J) : colimit.ι F j ≫ colim.map α = α.app j ≫ colimit.ι G j := by simp
#align category_theory.limits.colimit.ι_map CategoryTheory.Limits.colimit.ι_map
@[simp] -- Porting note: proof adjusted to account for @[simps] on all fields of colim
theorem colimit.map_desc (c : Cocone G) :
colimMap α ≫ colimit.desc G c = colimit.desc F ((Cocones.precompose α).obj c) := by
ext j
simp [← assoc, colimit.ι_map, assoc, colimit.ι_desc, colimit.ι_desc]
#align category_theory.limits.colimit.map_desc CategoryTheory.Limits.colimit.map_desc
theorem colimit.pre_map [HasColimitsOfShape K C] (E : K ⥤ J) :
colimit.pre F E ≫ colim.map α = colim.map (whiskerLeft E α) ≫ colimit.pre G E := by
ext
rw [← assoc, colimit.ι_pre, colimit.ι_map, ← assoc, colimit.ι_map, assoc, colimit.ι_pre]
rfl
#align category_theory.limits.colimit.pre_map CategoryTheory.Limits.colimit.pre_map
theorem colimit.pre_map' [HasColimitsOfShape K C] (F : J ⥤ C) {E₁ E₂ : K ⥤ J} (α : E₁ ⟶ E₂) :
colimit.pre F E₁ = colim.map (whiskerRight α F) ≫ colimit.pre F E₂ := by
ext1
simp [← assoc, assoc]
#align category_theory.limits.colimit.pre_map' CategoryTheory.Limits.colimit.pre_map'
theorem colimit.pre_id (F : J ⥤ C) :
colimit.pre F (𝟭 _) = colim.map (Functor.leftUnitor F).hom := by aesop_cat
#align category_theory.limits.colimit.pre_id CategoryTheory.Limits.colimit.pre_id
theorem colimit.map_post {D : Type u'} [Category.{v'} D] [HasColimitsOfShape J D]
(H : C ⥤ D) :/- H (colimit F) ⟶ H (colimit G) ⟶ colimit (G ⋙ H) vs
H (colimit F) ⟶ colimit (F ⋙ H) ⟶ colimit (G ⋙ H) -/
colimit.post
F H ≫
H.map (colim.map α) =
colim.map (whiskerRight α H) ≫ colimit.post G H := by
ext
rw [← assoc, colimit.ι_post, ← H.map_comp, colimit.ι_map, H.map_comp]
rw [← assoc, colimit.ι_map, assoc, colimit.ι_post]
rfl
#align category_theory.limits.colimit.map_post CategoryTheory.Limits.colimit.map_post
/-- The isomorphism between
morphisms from the cone point of the colimit cocone for `F` to `W`
and cocones over `F` with cone point `W`
is natural in `F`.
-/
def colimCoyoneda : colim.op ⋙ coyoneda ⋙ (whiskeringRight _ _ _).obj uliftFunctor.{u₁}
≅ CategoryTheory.cocones J C :=
NatIso.ofComponents fun F => NatIso.ofComponents fun W => colimit.homIso (unop F) W
#align category_theory.limits.colim_coyoneda CategoryTheory.Limits.colimCoyoneda
/-- The colimit functor and constant functor are adjoint to each other
-/
def colimConstAdj : (colim : (J ⥤ C) ⥤ C) ⊣ const J where
homEquiv f c :=
{ toFun := fun g =>
{ app := fun _ => colimit.ι _ _ ≫ g }
invFun := fun g => colimit.desc _ ⟨_, g⟩
left_inv := by aesop_cat
right_inv := by aesop_cat }
unit := { app := fun g => { app := colimit.ι _ } }
counit := { app := fun c => colimit.desc _ ⟨_, 𝟙 _⟩ }
#align category_theory.limits.colim_const_adj CategoryTheory.Limits.colimConstAdj
instance : IsLeftAdjoint (colim : (J ⥤ C) ⥤ C) :=
⟨_, ⟨colimConstAdj⟩⟩
end ColimFunctor
instance colimMap_epi' {F G : J ⥤ C} [HasColimitsOfShape J C] (α : F ⟶ G) [Epi α] :
Epi (colimMap α) :=
(colim : (J ⥤ C) ⥤ C).map_epi α
#align category_theory.limits.colim_map_epi' CategoryTheory.Limits.colimMap_epi'
instance colimMap_epi {F G : J ⥤ C} [HasColimit F] [HasColimit G] (α : F ⟶ G) [∀ j, Epi (α.app j)] :
Epi (colimMap α) :=
⟨fun {Z} u v h =>
colimit.hom_ext fun j => (cancel_epi (α.app j)).1 <| by simpa using colimit.ι _ j ≫= h⟩
#align category_theory.limits.colim_map_epi CategoryTheory.Limits.colimMap_epi
/-- We can transport colimits of shape `J` along an equivalence `J ≌ J'`.
-/
| Mathlib/CategoryTheory/Limits/HasLimits.lean | 1,204 | 1,208 | theorem hasColimitsOfShape_of_equivalence {J' : Type u₂} [Category.{v₂} J'] (e : J ≌ J')
[HasColimitsOfShape J C] : HasColimitsOfShape J' C := by |
constructor
intro F
apply hasColimit_of_equivalence_comp e
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura, Jeremy Avigad, Mario Carneiro
-/
import Mathlib.Data.List.Count
import Mathlib.Data.List.Dedup
import Mathlib.Data.List.InsertNth
import Mathlib.Data.List.Lattice
import Mathlib.Data.List.Permutation
import Mathlib.Data.Nat.Factorial.Basic
#align_import data.list.perm from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# List Permutations
This file introduces the `List.Perm` relation, which is true if two lists are permutations of one
another.
## Notation
The notation `~` is used for permutation equivalence.
-/
-- Make sure we don't import algebra
assert_not_exists Monoid
open Nat
namespace List
variable {α β : Type*} {l l₁ l₂ : List α} {a : α}
#align list.perm List.Perm
instance : Trans (@List.Perm α) (@List.Perm α) List.Perm where
trans := @List.Perm.trans α
open Perm (swap)
attribute [refl] Perm.refl
#align list.perm.refl List.Perm.refl
lemma perm_rfl : l ~ l := Perm.refl _
-- Porting note: used rec_on in mathlib3; lean4 eqn compiler still doesn't like it
attribute [symm] Perm.symm
#align list.perm.symm List.Perm.symm
#align list.perm_comm List.perm_comm
#align list.perm.swap' List.Perm.swap'
attribute [trans] Perm.trans
#align list.perm.eqv List.Perm.eqv
#align list.is_setoid List.isSetoid
#align list.perm.mem_iff List.Perm.mem_iff
#align list.perm.subset List.Perm.subset
theorem Perm.subset_congr_left {l₁ l₂ l₃ : List α} (h : l₁ ~ l₂) : l₁ ⊆ l₃ ↔ l₂ ⊆ l₃ :=
⟨h.symm.subset.trans, h.subset.trans⟩
#align list.perm.subset_congr_left List.Perm.subset_congr_left
theorem Perm.subset_congr_right {l₁ l₂ l₃ : List α} (h : l₁ ~ l₂) : l₃ ⊆ l₁ ↔ l₃ ⊆ l₂ :=
⟨fun h' => h'.trans h.subset, fun h' => h'.trans h.symm.subset⟩
#align list.perm.subset_congr_right List.Perm.subset_congr_right
#align list.perm.append_right List.Perm.append_right
#align list.perm.append_left List.Perm.append_left
#align list.perm.append List.Perm.append
#align list.perm.append_cons List.Perm.append_cons
#align list.perm_middle List.perm_middle
#align list.perm_append_singleton List.perm_append_singleton
#align list.perm_append_comm List.perm_append_comm
#align list.concat_perm List.concat_perm
#align list.perm.length_eq List.Perm.length_eq
#align list.perm.eq_nil List.Perm.eq_nil
#align list.perm.nil_eq List.Perm.nil_eq
#align list.perm_nil List.perm_nil
#align list.nil_perm List.nil_perm
#align list.not_perm_nil_cons List.not_perm_nil_cons
#align list.reverse_perm List.reverse_perm
#align list.perm_cons_append_cons List.perm_cons_append_cons
#align list.perm_replicate List.perm_replicate
#align list.replicate_perm List.replicate_perm
#align list.perm_singleton List.perm_singleton
#align list.singleton_perm List.singleton_perm
#align list.singleton_perm_singleton List.singleton_perm_singleton
#align list.perm_cons_erase List.perm_cons_erase
#align list.perm_induction_on List.Perm.recOnSwap'
-- Porting note: used to be @[congr]
#align list.perm.filter_map List.Perm.filterMap
-- Porting note: used to be @[congr]
#align list.perm.map List.Perm.map
#align list.perm.pmap List.Perm.pmap
#align list.perm.filter List.Perm.filter
#align list.filter_append_perm List.filter_append_perm
#align list.exists_perm_sublist List.exists_perm_sublist
#align list.perm.sizeof_eq_sizeof List.Perm.sizeOf_eq_sizeOf
section Rel
open Relator
variable {γ : Type*} {δ : Type*} {r : α → β → Prop} {p : γ → δ → Prop}
local infixr:80 " ∘r " => Relation.Comp
theorem perm_comp_perm : (Perm ∘r Perm : List α → List α → Prop) = Perm := by
funext a c; apply propext
constructor
· exact fun ⟨b, hab, hba⟩ => Perm.trans hab hba
· exact fun h => ⟨a, Perm.refl a, h⟩
#align list.perm_comp_perm List.perm_comp_perm
theorem perm_comp_forall₂ {l u v} (hlu : Perm l u) (huv : Forall₂ r u v) :
(Forall₂ r ∘r Perm) l v := by
induction hlu generalizing v with
| nil => cases huv; exact ⟨[], Forall₂.nil, Perm.nil⟩
| cons u _hlu ih =>
cases' huv with _ b _ v hab huv'
rcases ih huv' with ⟨l₂, h₁₂, h₂₃⟩
exact ⟨b :: l₂, Forall₂.cons hab h₁₂, h₂₃.cons _⟩
| swap a₁ a₂ h₂₃ =>
cases' huv with _ b₁ _ l₂ h₁ hr₂₃
cases' hr₂₃ with _ b₂ _ l₂ h₂ h₁₂
exact ⟨b₂ :: b₁ :: l₂, Forall₂.cons h₂ (Forall₂.cons h₁ h₁₂), Perm.swap _ _ _⟩
| trans _ _ ih₁ ih₂ =>
rcases ih₂ huv with ⟨lb₂, hab₂, h₂₃⟩
rcases ih₁ hab₂ with ⟨lb₁, hab₁, h₁₂⟩
exact ⟨lb₁, hab₁, Perm.trans h₁₂ h₂₃⟩
#align list.perm_comp_forall₂ List.perm_comp_forall₂
theorem forall₂_comp_perm_eq_perm_comp_forall₂ : Forall₂ r ∘r Perm = Perm ∘r Forall₂ r := by
funext l₁ l₃; apply propext
constructor
· intro h
rcases h with ⟨l₂, h₁₂, h₂₃⟩
have : Forall₂ (flip r) l₂ l₁ := h₁₂.flip
rcases perm_comp_forall₂ h₂₃.symm this with ⟨l', h₁, h₂⟩
exact ⟨l', h₂.symm, h₁.flip⟩
· exact fun ⟨l₂, h₁₂, h₂₃⟩ => perm_comp_forall₂ h₁₂ h₂₃
#align list.forall₂_comp_perm_eq_perm_comp_forall₂ List.forall₂_comp_perm_eq_perm_comp_forall₂
theorem rel_perm_imp (hr : RightUnique r) : (Forall₂ r ⇒ Forall₂ r ⇒ (· → ·)) Perm Perm :=
fun a b h₁ c d h₂ h =>
have : (flip (Forall₂ r) ∘r Perm ∘r Forall₂ r) b d := ⟨a, h₁, c, h, h₂⟩
have : ((flip (Forall₂ r) ∘r Forall₂ r) ∘r Perm) b d := by
rwa [← forall₂_comp_perm_eq_perm_comp_forall₂, ← Relation.comp_assoc] at this
let ⟨b', ⟨c', hbc, hcb⟩, hbd⟩ := this
have : b' = b := right_unique_forall₂' hr hcb hbc
this ▸ hbd
#align list.rel_perm_imp List.rel_perm_imp
theorem rel_perm (hr : BiUnique r) : (Forall₂ r ⇒ Forall₂ r ⇒ (· ↔ ·)) Perm Perm :=
fun _a _b hab _c _d hcd =>
Iff.intro (rel_perm_imp hr.2 hab hcd) (rel_perm_imp hr.left.flip hab.flip hcd.flip)
#align list.rel_perm List.rel_perm
end Rel
section Subperm
#align list.nil_subperm List.nil_subperm
#align list.perm.subperm_left List.Perm.subperm_left
#align list.perm.subperm_right List.Perm.subperm_right
#align list.sublist.subperm List.Sublist.subperm
#align list.perm.subperm List.Perm.subperm
attribute [refl] Subperm.refl
#align list.subperm.refl List.Subperm.refl
attribute [trans] Subperm.trans
#align list.subperm.trans List.Subperm.trans
#align list.subperm.length_le List.Subperm.length_le
#align list.subperm.perm_of_length_le List.Subperm.perm_of_length_le
#align list.subperm.antisymm List.Subperm.antisymm
#align list.subperm.subset List.Subperm.subset
#align list.subperm.filter List.Subperm.filter
end Subperm
#align list.sublist.exists_perm_append List.Sublist.exists_perm_append
lemma subperm_iff : l₁ <+~ l₂ ↔ ∃ l, l ~ l₂ ∧ l₁ <+ l := by
refine ⟨?_, fun ⟨l, h₁, h₂⟩ ↦ h₂.subperm.trans h₁.subperm⟩
rintro ⟨l, h₁, h₂⟩
obtain ⟨l', h₂⟩ := h₂.exists_perm_append
exact ⟨l₁ ++ l', (h₂.trans (h₁.append_right _)).symm, (prefix_append _ _).sublist⟩
#align list.subperm_singleton_iff List.singleton_subperm_iff
@[simp] lemma subperm_singleton_iff : l <+~ [a] ↔ l = [] ∨ l = [a] := by
constructor
· rw [subperm_iff]
rintro ⟨s, hla, h⟩
rwa [perm_singleton.mp hla, sublist_singleton] at h
· rintro (rfl | rfl)
exacts [nil_subperm, Subperm.refl _]
attribute [simp] nil_subperm
@[simp]
theorem subperm_nil : List.Subperm l [] ↔ l = [] :=
match l with
| [] => by simp
| head :: tail => by
simp only [iff_false]
intro h
have := h.length_le
simp only [List.length_cons, List.length_nil, Nat.succ_ne_zero, ← Nat.not_lt, Nat.zero_lt_succ,
not_true_eq_false] at this
#align list.perm.countp_eq List.Perm.countP_eq
#align list.subperm.countp_le List.Subperm.countP_le
#align list.perm.countp_congr List.Perm.countP_congr
#align list.countp_eq_countp_filter_add List.countP_eq_countP_filter_add
lemma count_eq_count_filter_add [DecidableEq α] (P : α → Prop) [DecidablePred P]
(l : List α) (a : α) :
count a l = count a (l.filter P) + count a (l.filter (¬ P ·)) := by
convert countP_eq_countP_filter_add l _ P
simp only [decide_not]
#align list.perm.count_eq List.Perm.count_eq
#align list.subperm.count_le List.Subperm.count_le
#align list.perm.foldl_eq' List.Perm.foldl_eq'
theorem Perm.foldl_eq {f : β → α → β} {l₁ l₂ : List α} (rcomm : RightCommutative f) (p : l₁ ~ l₂) :
∀ b, foldl f b l₁ = foldl f b l₂ :=
p.foldl_eq' fun x _hx y _hy z => rcomm z x y
#align list.perm.foldl_eq List.Perm.foldl_eq
theorem Perm.foldr_eq {f : α → β → β} {l₁ l₂ : List α} (lcomm : LeftCommutative f) (p : l₁ ~ l₂) :
∀ b, foldr f b l₁ = foldr f b l₂ := by
intro b
induction p using Perm.recOnSwap' generalizing b with
| nil => rfl
| cons _ _ r => simp; rw [r b]
| swap' _ _ _ r => simp; rw [lcomm, r b]
| trans _ _ r₁ r₂ => exact Eq.trans (r₁ b) (r₂ b)
#align list.perm.foldr_eq List.Perm.foldr_eq
#align list.perm.rec_heq List.Perm.rec_heq
section
variable {op : α → α → α} [IA : Std.Associative op] [IC : Std.Commutative op]
local notation a " * " b => op a b
local notation l " <*> " a => foldl op a l
theorem Perm.fold_op_eq {l₁ l₂ : List α} {a : α} (h : l₁ ~ l₂) : (l₁ <*> a) = l₂ <*> a :=
h.foldl_eq (right_comm _ IC.comm IA.assoc) _
#align list.perm.fold_op_eq List.Perm.fold_op_eq
end
#align list.perm_inv_core List.perm_inv_core
#align list.perm.cons_inv List.Perm.cons_inv
#align list.perm_cons List.perm_cons
#align list.perm_append_left_iff List.perm_append_left_iff
#align list.perm_append_right_iff List.perm_append_right_iff
theorem perm_option_to_list {o₁ o₂ : Option α} : o₁.toList ~ o₂.toList ↔ o₁ = o₂ := by
refine ⟨fun p => ?_, fun e => e ▸ Perm.refl _⟩
cases' o₁ with a <;> cases' o₂ with b; · rfl
· cases p.length_eq
· cases p.length_eq
· exact Option.mem_toList.1 (p.symm.subset <| by simp)
#align list.perm_option_to_list List.perm_option_to_list
#align list.subperm_cons List.subperm_cons
alias ⟨subperm.of_cons, subperm.cons⟩ := subperm_cons
#align list.subperm.of_cons List.subperm.of_cons
#align list.subperm.cons List.subperm.cons
-- Porting note: commented out
--attribute [protected] subperm.cons
theorem cons_subperm_of_mem {a : α} {l₁ l₂ : List α} (d₁ : Nodup l₁) (h₁ : a ∉ l₁) (h₂ : a ∈ l₂)
(s : l₁ <+~ l₂) : a :: l₁ <+~ l₂ := by
rcases s with ⟨l, p, s⟩
induction s generalizing l₁ with
| slnil => cases h₂
| @cons r₁ r₂ b s' ih =>
simp? at h₂ says simp only [mem_cons] at h₂
cases' h₂ with e m
· subst b
exact ⟨a :: r₁, p.cons a, s'.cons₂ _⟩
· rcases ih d₁ h₁ m p with ⟨t, p', s'⟩
exact ⟨t, p', s'.cons _⟩
| @cons₂ r₁ r₂ b _ ih =>
have bm : b ∈ l₁ := p.subset <| mem_cons_self _ _
have am : a ∈ r₂ := by
simp only [find?, mem_cons] at h₂
exact h₂.resolve_left fun e => h₁ <| e.symm ▸ bm
rcases append_of_mem bm with ⟨t₁, t₂, rfl⟩
have st : t₁ ++ t₂ <+ t₁ ++ b :: t₂ := by simp
rcases ih (d₁.sublist st) (mt (fun x => st.subset x) h₁) am
(Perm.cons_inv <| p.trans perm_middle) with
⟨t, p', s'⟩
exact
⟨b :: t, (p'.cons b).trans <| (swap _ _ _).trans (perm_middle.symm.cons a), s'.cons₂ _⟩
#align list.cons_subperm_of_mem List.cons_subperm_of_mem
#align list.subperm_append_left List.subperm_append_left
#align list.subperm_append_right List.subperm_append_right
#align list.subperm.exists_of_length_lt List.Subperm.exists_of_length_lt
protected theorem Nodup.subperm (d : Nodup l₁) (H : l₁ ⊆ l₂) : l₁ <+~ l₂ :=
subperm_of_subset d H
#align list.nodup.subperm List.Nodup.subperm
#align list.perm_ext List.perm_ext_iff_of_nodup
#align list.nodup.sublist_ext List.Nodup.perm_iff_eq_of_sublist
section
variable [DecidableEq α]
-- attribute [congr]
#align list.perm.erase List.Perm.erase
#align list.subperm_cons_erase List.subperm_cons_erase
#align list.erase_subperm List.erase_subperm
#align list.subperm.erase List.Subperm.erase
#align list.perm.diff_right List.Perm.diff_right
#align list.perm.diff_left List.Perm.diff_left
#align list.perm.diff List.Perm.diff
#align list.subperm.diff_right List.Subperm.diff_right
#align list.erase_cons_subperm_cons_erase List.erase_cons_subperm_cons_erase
#align list.subperm_cons_diff List.subperm_cons_diff
#align list.subset_cons_diff List.subset_cons_diff
theorem Perm.bagInter_right {l₁ l₂ : List α} (t : List α) (h : l₁ ~ l₂) :
l₁.bagInter t ~ l₂.bagInter t := by
induction' h with x _ _ _ _ x y _ _ _ _ _ _ ih_1 ih_2 generalizing t; · simp
· by_cases x ∈ t <;> simp [*, Perm.cons]
· by_cases h : x = y
· simp [h]
by_cases xt : x ∈ t <;> by_cases yt : y ∈ t
· simp [xt, yt, mem_erase_of_ne h, mem_erase_of_ne (Ne.symm h), erase_comm, swap]
· simp [xt, yt, mt mem_of_mem_erase, Perm.cons]
· simp [xt, yt, mt mem_of_mem_erase, Perm.cons]
· simp [xt, yt]
· exact (ih_1 _).trans (ih_2 _)
#align list.perm.bag_inter_right List.Perm.bagInter_right
theorem Perm.bagInter_left (l : List α) {t₁ t₂ : List α} (p : t₁ ~ t₂) :
l.bagInter t₁ = l.bagInter t₂ := by
induction' l with a l IH generalizing t₁ t₂ p; · simp
by_cases h : a ∈ t₁
· simp [h, p.subset h, IH (p.erase _)]
· simp [h, mt p.mem_iff.2 h, IH p]
#align list.perm.bag_inter_left List.Perm.bagInter_left
theorem Perm.bagInter {l₁ l₂ t₁ t₂ : List α} (hl : l₁ ~ l₂) (ht : t₁ ~ t₂) :
l₁.bagInter t₁ ~ l₂.bagInter t₂ :=
ht.bagInter_left l₂ ▸ hl.bagInter_right _
#align list.perm.bag_inter List.Perm.bagInter
#align list.cons_perm_iff_perm_erase List.cons_perm_iff_perm_erase
#align list.perm_iff_count List.perm_iff_count
theorem perm_replicate_append_replicate {l : List α} {a b : α} {m n : ℕ} (h : a ≠ b) :
l ~ replicate m a ++ replicate n b ↔ count a l = m ∧ count b l = n ∧ l ⊆ [a, b] := by
rw [perm_iff_count, ← Decidable.and_forall_ne a, ← Decidable.and_forall_ne b]
suffices l ⊆ [a, b] ↔ ∀ c, c ≠ b → c ≠ a → c ∉ l by
simp (config := { contextual := true }) [count_replicate, h, h.symm, this, count_eq_zero]
trans ∀ c, c ∈ l → c = b ∨ c = a
· simp [subset_def, or_comm]
· exact forall_congr' fun _ => by rw [← and_imp, ← not_or, not_imp_not]
#align list.perm_replicate_append_replicate List.perm_replicate_append_replicate
#align list.subperm.cons_right List.Subperm.cons_right
#align list.subperm_append_diff_self_of_count_le List.subperm_append_diff_self_of_count_le
#align list.subperm_ext_iff List.subperm_ext_iff
#align list.decidable_subperm List.decidableSubperm
#align list.subperm.cons_left List.Subperm.cons_left
#align list.decidable_perm List.decidablePerm
-- @[congr]
theorem Perm.dedup {l₁ l₂ : List α} (p : l₁ ~ l₂) : dedup l₁ ~ dedup l₂ :=
perm_iff_count.2 fun a =>
if h : a ∈ l₁ then by simp [nodup_dedup, h, p.subset h] else by simp [h, mt p.mem_iff.2 h]
#align list.perm.dedup List.Perm.dedup
-- attribute [congr]
#align list.perm.insert List.Perm.insert
#align list.perm_insert_swap List.perm_insert_swap
#align list.perm_insert_nth List.perm_insertNth
#align list.perm.union_right List.Perm.union_right
#align list.perm.union_left List.Perm.union_left
-- @[congr]
#align list.perm.union List.Perm.union
#align list.perm.inter_right List.Perm.inter_right
#align list.perm.inter_left List.Perm.inter_left
-- @[congr]
#align list.perm.inter List.Perm.inter
theorem Perm.inter_append {l t₁ t₂ : List α} (h : Disjoint t₁ t₂) :
l ∩ (t₁ ++ t₂) ~ l ∩ t₁ ++ l ∩ t₂ := by
induction l with
| nil => simp
| cons x xs l_ih =>
by_cases h₁ : x ∈ t₁
· have h₂ : x ∉ t₂ := h h₁
simp [*]
by_cases h₂ : x ∈ t₂
· simp only [*, inter_cons_of_not_mem, false_or_iff, mem_append, inter_cons_of_mem,
not_false_iff]
refine Perm.trans (Perm.cons _ l_ih) ?_
change [x] ++ xs ∩ t₁ ++ xs ∩ t₂ ~ xs ∩ t₁ ++ ([x] ++ xs ∩ t₂)
rw [← List.append_assoc]
solve_by_elim [Perm.append_right, perm_append_comm]
· simp [*]
#align list.perm.inter_append List.Perm.inter_append
end
#align list.perm.pairwise_iff List.Perm.pairwise_iff
#align list.pairwise.perm List.Pairwise.perm
#align list.perm.pairwise List.Perm.pairwise
#align list.perm.nodup_iff List.Perm.nodup_iff
#align list.perm.join List.Perm.join
#align list.perm.bind_right List.Perm.bind_right
#align list.perm.join_congr List.Perm.join_congr
theorem Perm.bind_left (l : List α) {f g : α → List β} (h : ∀ a ∈ l, f a ~ g a) :
l.bind f ~ l.bind g :=
Perm.join_congr <| by
rwa [List.forall₂_map_right_iff, List.forall₂_map_left_iff, List.forall₂_same]
#align list.perm.bind_left List.Perm.bind_left
theorem bind_append_perm (l : List α) (f g : α → List β) :
l.bind f ++ l.bind g ~ l.bind fun x => f x ++ g x := by
induction' l with a l IH <;> simp
refine (Perm.trans ?_ (IH.append_left _)).append_left _
rw [← append_assoc, ← append_assoc]
exact perm_append_comm.append_right _
#align list.bind_append_perm List.bind_append_perm
theorem map_append_bind_perm (l : List α) (f : α → β) (g : α → List β) :
l.map f ++ l.bind g ~ l.bind fun x => f x :: g x := by
simpa [← map_eq_bind] using bind_append_perm l (fun x => [f x]) g
#align list.map_append_bind_perm List.map_append_bind_perm
theorem Perm.product_right {l₁ l₂ : List α} (t₁ : List β) (p : l₁ ~ l₂) :
product l₁ t₁ ~ product l₂ t₁ :=
p.bind_right _
#align list.perm.product_right List.Perm.product_right
theorem Perm.product_left (l : List α) {t₁ t₂ : List β} (p : t₁ ~ t₂) :
product l t₁ ~ product l t₂ :=
(Perm.bind_left _) fun _ _ => p.map _
#align list.perm.product_left List.Perm.product_left
-- @[congr]
theorem Perm.product {l₁ l₂ : List α} {t₁ t₂ : List β} (p₁ : l₁ ~ l₂) (p₂ : t₁ ~ t₂) :
product l₁ t₁ ~ product l₂ t₂ :=
(p₁.product_right t₁).trans (p₂.product_left l₂)
#align list.perm.product List.Perm.product
theorem perm_lookmap (f : α → Option α) {l₁ l₂ : List α}
(H : Pairwise (fun a b => ∀ c ∈ f a, ∀ d ∈ f b, a = b ∧ c = d) l₁) (p : l₁ ~ l₂) :
lookmap f l₁ ~ lookmap f l₂ := by
induction' p with a l₁ l₂ p IH a b l l₁ l₂ l₃ p₁ _ IH₁ IH₂; · simp
· cases h : f a
· simp [h]
exact IH (pairwise_cons.1 H).2
· simp [lookmap_cons_some _ _ h, p]
· cases' h₁ : f a with c <;> cases' h₂ : f b with d
· simp [h₁, h₂]
apply swap
· simp [h₁, lookmap_cons_some _ _ h₂]
apply swap
· simp [lookmap_cons_some _ _ h₁, h₂]
apply swap
· simp [lookmap_cons_some _ _ h₁, lookmap_cons_some _ _ h₂]
rcases (pairwise_cons.1 H).1 _ (mem_cons.2 (Or.inl rfl)) _ h₂ _ h₁ with ⟨rfl, rfl⟩
exact Perm.refl _
· refine (IH₁ H).trans (IH₂ ((p₁.pairwise_iff ?_).1 H))
intro x y h c hc d hd
rw [@eq_comm _ y, @eq_comm _ c]
apply h d hd c hc
#align list.perm_lookmap List.perm_lookmap
#align list.perm.erasep List.Perm.eraseP
theorem Perm.take_inter [DecidableEq α] {xs ys : List α} (n : ℕ) (h : xs ~ ys)
(h' : ys.Nodup) : xs.take n ~ ys.inter (xs.take n) := by
simp only [List.inter]
exact Perm.trans (show xs.take n ~ xs.filter (xs.take n).elem by
conv_lhs => rw [Nodup.take_eq_filter_mem ((Perm.nodup_iff h).2 h')])
(Perm.filter _ h)
#align list.perm.take_inter List.Perm.take_inter
theorem Perm.drop_inter [DecidableEq α] {xs ys : List α} (n : ℕ) (h : xs ~ ys) (h' : ys.Nodup) :
xs.drop n ~ ys.inter (xs.drop n) := by
by_cases h'' : n ≤ xs.length
· let n' := xs.length - n
have h₀ : n = xs.length - n' := by rwa [Nat.sub_sub_self]
have h₁ : n' ≤ xs.length := Nat.sub_le ..
have h₂ : xs.drop n = (xs.reverse.take n').reverse := by
rw [reverse_take _ h₁, h₀, reverse_reverse]
rw [h₂]
apply (reverse_perm _).trans
rw [inter_reverse]
apply Perm.take_inter _ _ h'
apply (reverse_perm _).trans; assumption
· have : drop n xs = [] := by
apply eq_nil_of_length_eq_zero
rw [length_drop, Nat.sub_eq_zero_iff_le]
apply le_of_not_ge h''
simp [this, List.inter]
#align list.perm.drop_inter List.Perm.drop_inter
theorem Perm.dropSlice_inter [DecidableEq α] {xs ys : List α} (n m : ℕ) (h : xs ~ ys)
(h' : ys.Nodup) : List.dropSlice n m xs ~ ys ∩ List.dropSlice n m xs := by
simp only [dropSlice_eq]
have : n ≤ n + m := Nat.le_add_right _ _
have h₂ := h.nodup_iff.2 h'
apply Perm.trans _ (Perm.inter_append _).symm
· exact Perm.append (Perm.take_inter _ h h') (Perm.drop_inter _ h h')
· exact disjoint_take_drop h₂ this
#align list.perm.slice_inter List.Perm.dropSlice_inter
-- enumerating permutations
section Permutations
theorem perm_of_mem_permutationsAux :
∀ {ts is l : List α}, l ∈ permutationsAux ts is → l ~ ts ++ is := by
show ∀ (ts is l : List α), l ∈ permutationsAux ts is → l ~ ts ++ is
refine permutationsAux.rec (by simp) ?_
introv IH1 IH2 m
rw [permutationsAux_cons, permutations, mem_foldr_permutationsAux2] at m
rcases m with (m | ⟨l₁, l₂, m, _, rfl⟩)
· exact (IH1 _ m).trans perm_middle
· have p : l₁ ++ l₂ ~ is := by
simp only [mem_cons] at m
cases' m with e m
· simp [e]
exact is.append_nil ▸ IH2 _ m
exact ((perm_middle.trans (p.cons _)).append_right _).trans (perm_append_comm.cons _)
#align list.perm_of_mem_permutations_aux List.perm_of_mem_permutationsAux
theorem perm_of_mem_permutations {l₁ l₂ : List α} (h : l₁ ∈ permutations l₂) : l₁ ~ l₂ :=
(eq_or_mem_of_mem_cons h).elim (fun e => e ▸ Perm.refl _) fun m =>
append_nil l₂ ▸ perm_of_mem_permutationsAux m
#align list.perm_of_mem_permutations List.perm_of_mem_permutations
theorem length_permutationsAux :
∀ ts is : List α, length (permutationsAux ts is) + is.length ! = (length ts + length is)! := by
refine permutationsAux.rec (by simp) ?_
intro t ts is IH1 IH2
have IH2 : length (permutationsAux is nil) + 1 = is.length ! := by simpa using IH2
simp only [factorial, Nat.mul_comm, add_eq] at IH1
rw [permutationsAux_cons,
length_foldr_permutationsAux2' _ _ _ _ _ fun l m => (perm_of_mem_permutations m).length_eq,
permutations, length, length, IH2, Nat.succ_add, Nat.factorial_succ, Nat.mul_comm (_ + 1),
← Nat.succ_eq_add_one, ← IH1, Nat.add_comm (_ * _), Nat.add_assoc, Nat.mul_succ, Nat.mul_comm]
#align list.length_permutations_aux List.length_permutationsAux
theorem length_permutations (l : List α) : length (permutations l) = (length l)! :=
length_permutationsAux l []
#align list.length_permutations List.length_permutations
theorem mem_permutations_of_perm_lemma {is l : List α}
(H : l ~ [] ++ is → (∃ (ts' : _) (_ : ts' ~ []), l = ts' ++ is) ∨ l ∈ permutationsAux is []) :
l ~ is → l ∈ permutations is := by simpa [permutations, perm_nil] using H
#align list.mem_permutations_of_perm_lemma List.mem_permutations_of_perm_lemma
theorem mem_permutationsAux_of_perm :
∀ {ts is l : List α},
l ~ is ++ ts → (∃ (is' : _) (_ : is' ~ is), l = is' ++ ts) ∨ l ∈ permutationsAux ts is := by
show ∀ (ts is l : List α),
l ~ is ++ ts → (∃ (is' : _) (_ : is' ~ is), l = is' ++ ts) ∨ l ∈ permutationsAux ts is
refine permutationsAux.rec (by simp) ?_
intro t ts is IH1 IH2 l p
rw [permutationsAux_cons, mem_foldr_permutationsAux2]
rcases IH1 _ (p.trans perm_middle) with (⟨is', p', e⟩ | m)
· clear p
subst e
rcases append_of_mem (p'.symm.subset (mem_cons_self _ _)) with ⟨l₁, l₂, e⟩
subst is'
have p := (perm_middle.symm.trans p').cons_inv
cases' l₂ with a l₂'
· exact Or.inl ⟨l₁, by simpa using p⟩
· exact Or.inr (Or.inr ⟨l₁, a :: l₂', mem_permutations_of_perm_lemma (IH2 _) p, by simp⟩)
· exact Or.inr (Or.inl m)
#align list.mem_permutations_aux_of_perm List.mem_permutationsAux_of_perm
@[simp]
theorem mem_permutations {s t : List α} : s ∈ permutations t ↔ s ~ t :=
⟨perm_of_mem_permutations, mem_permutations_of_perm_lemma mem_permutationsAux_of_perm⟩
#align list.mem_permutations List.mem_permutations
-- Porting note: temporary theorem to solve diamond issue
private theorem DecEq_eq [DecidableEq α] :
List.instBEq = @instBEqOfDecidableEq (List α) instDecidableEqList :=
congr_arg BEq.mk <| by
funext l₁ l₂
show (l₁ == l₂) = _
rw [Bool.eq_iff_iff, @beq_iff_eq _ (_), decide_eq_true_iff]
theorem perm_permutations'Aux_comm (a b : α) (l : List α) :
(permutations'Aux a l).bind (permutations'Aux b) ~
(permutations'Aux b l).bind (permutations'Aux a) := by
induction' l with c l ih
· simp [swap]
simp only [permutations'Aux, cons_bind, map_cons, map_map, cons_append]
apply Perm.swap'
have :
∀ a b,
(map (cons c) (permutations'Aux a l)).bind (permutations'Aux b) ~
map (cons b ∘ cons c) (permutations'Aux a l) ++
map (cons c) ((permutations'Aux a l).bind (permutations'Aux b)) := by
intros a' b'
simp only [map_bind, permutations'Aux]
show List.bind (permutations'Aux _ l) (fun a => ([b' :: c :: a] ++
map (cons c) (permutations'Aux _ a))) ~ _
refine (bind_append_perm _ (fun x => [b' :: c :: x]) _).symm.trans ?_
rw [← map_eq_bind, ← bind_map]
exact Perm.refl _
refine (((this _ _).append_left _).trans ?_).trans ((this _ _).append_left _).symm
rw [← append_assoc, ← append_assoc]
exact perm_append_comm.append (ih.map _)
#align list.perm_permutations'_aux_comm List.perm_permutations'Aux_comm
theorem Perm.permutations' {s t : List α} (p : s ~ t) : permutations' s ~ permutations' t := by
induction' p with a s t _ IH a b l s t u _ _ IH₁ IH₂; · simp
· exact IH.bind_right _
· dsimp
rw [bind_assoc, bind_assoc]
apply Perm.bind_left
intro l' _
apply perm_permutations'Aux_comm
· exact IH₁.trans IH₂
#align list.perm.permutations' List.Perm.permutations'
theorem permutations_perm_permutations' (ts : List α) : ts.permutations ~ ts.permutations' := by
obtain ⟨n, h⟩ : ∃ n, length ts < n := ⟨_, Nat.lt_succ_self _⟩
induction' n with n IH generalizing ts; · cases h
refine List.reverseRecOn ts (fun _ => ?_) (fun ts t _ h => ?_) h; · simp [permutations]
rw [← concat_eq_append, length_concat, Nat.succ_lt_succ_iff] at h
have IH₂ := (IH ts.reverse (by rwa [length_reverse])).trans (reverse_perm _).permutations'
simp only [permutations_append, foldr_permutationsAux2, permutationsAux_nil,
permutationsAux_cons, append_nil]
refine
(perm_append_comm.trans ((IH₂.bind_right _).append ((IH _ h).map _))).trans
(Perm.trans ?_ perm_append_comm.permutations')
rw [map_eq_bind, singleton_append, permutations']
refine (bind_append_perm _ _ _).trans ?_
refine Perm.of_eq ?_
congr
funext _
rw [permutations'Aux_eq_permutationsAux2, permutationsAux2_append]
#align list.permutations_perm_permutations' List.permutations_perm_permutations'
@[simp]
theorem mem_permutations' {s t : List α} : s ∈ permutations' t ↔ s ~ t :=
(permutations_perm_permutations' _).symm.mem_iff.trans mem_permutations
#align list.mem_permutations' List.mem_permutations'
theorem Perm.permutations {s t : List α} (h : s ~ t) : permutations s ~ permutations t :=
(permutations_perm_permutations' _).trans <|
h.permutations'.trans (permutations_perm_permutations' _).symm
#align list.perm.permutations List.Perm.permutations
@[simp]
theorem perm_permutations_iff {s t : List α} : permutations s ~ permutations t ↔ s ~ t :=
⟨fun h => mem_permutations.1 <| h.mem_iff.1 <| mem_permutations.2 (Perm.refl _),
Perm.permutations⟩
#align list.perm_permutations_iff List.perm_permutations_iff
@[simp]
theorem perm_permutations'_iff {s t : List α} : permutations' s ~ permutations' t ↔ s ~ t :=
⟨fun h => mem_permutations'.1 <| h.mem_iff.1 <| mem_permutations'.2 (Perm.refl _),
Perm.permutations'⟩
#align list.perm_permutations'_iff List.perm_permutations'_iff
theorem get_permutations'Aux (s : List α) (x : α) (n : ℕ)
(hn : n < length (permutations'Aux x s)) :
(permutations'Aux x s).get ⟨n, hn⟩ = s.insertNth n x := by
induction' s with y s IH generalizing n
· simp only [length, Nat.zero_add, Nat.lt_one_iff] at hn
simp [hn]
· cases n
· simp [get]
· simpa [get] using IH _ _
#align list.nth_le_permutations'_aux List.get_permutations'Aux
set_option linter.deprecated false in
@[deprecated get_permutations'Aux (since := "2024-04-23")]
theorem nthLe_permutations'Aux (s : List α) (x : α) (n : ℕ)
(hn : n < length (permutations'Aux x s)) :
(permutations'Aux x s).nthLe n hn = s.insertNth n x :=
get_permutations'Aux s x n hn
theorem count_permutations'Aux_self [DecidableEq α] (l : List α) (x : α) :
count (x :: l) (permutations'Aux x l) = length (takeWhile (x = ·) l) + 1 := by
induction' l with y l IH generalizing x
· simp [takeWhile, count]
· rw [permutations'Aux, DecEq_eq, count_cons_self]
by_cases hx : x = y
· subst hx
simpa [takeWhile, Nat.succ_inj', DecEq_eq] using IH _
· rw [takeWhile]
simp only [mem_map, cons.injEq, Ne.symm hx, false_and, and_false, exists_false,
not_false_iff, count_eq_zero_of_not_mem, Nat.zero_add, hx, decide_False, length_nil]
#align list.count_permutations'_aux_self List.count_permutations'Aux_self
@[simp]
theorem length_permutations'Aux (s : List α) (x : α) :
length (permutations'Aux x s) = length s + 1 := by
induction' s with y s IH
· simp
· simpa using IH
#align list.length_permutations'_aux List.length_permutations'Aux
@[simp]
theorem permutations'Aux_get_zero (s : List α) (x : α)
(hn : 0 < length (permutations'Aux x s) := (by simp)) :
(permutations'Aux x s).get ⟨0, hn⟩ = x :: s :=
get_permutations'Aux _ _ _ _
#align list.permutations'_aux_nth_le_zero List.permutations'Aux_get_zero
theorem injective_permutations'Aux (x : α) : Function.Injective (permutations'Aux x) := by
intro s t h
apply insertNth_injective s.length x
have hl : s.length = t.length := by simpa using congr_arg length h
rw [← get_permutations'Aux s x s.length (by simp),
← get_permutations'Aux t x s.length (by simp [hl])]
simp only [← getElem_eq_get, h, hl]
#align list.injective_permutations'_aux List.injective_permutations'Aux
theorem nodup_permutations'Aux_of_not_mem (s : List α) (x : α) (hx : x ∉ s) :
Nodup (permutations'Aux x s) := by
induction' s with y s IH
· simp
· simp only [not_or, mem_cons] at hx
simp only [permutations'Aux, nodup_cons, mem_map, cons.injEq, exists_eq_right_right, not_and]
refine ⟨fun _ => Ne.symm hx.left, ?_⟩
rw [nodup_map_iff]
· exact IH hx.right
· simp
#align list.nodup_permutations'_aux_of_not_mem List.nodup_permutations'Aux_of_not_mem
set_option linter.deprecated false in
theorem nodup_permutations'Aux_iff {s : List α} {x : α} : Nodup (permutations'Aux x s) ↔ x ∉ s := by
refine ⟨fun h => ?_, nodup_permutations'Aux_of_not_mem _ _⟩
intro H
obtain ⟨k, hk, hk'⟩ := nthLe_of_mem H
rw [nodup_iff_nthLe_inj] at h
refine k.succ_ne_self.symm $ h k (k + 1) ?_ ?_ ?_
· simpa [Nat.lt_succ_iff] using hk.le
· simpa using hk
rw [nthLe_permutations'Aux, nthLe_permutations'Aux]
have hl : length (insertNth k x s) = length (insertNth (k + 1) x s) := by
rw [length_insertNth _ _ hk.le, length_insertNth _ _ (Nat.succ_le_of_lt hk)]
refine ext_nthLe hl fun n hn hn' => ?_
rcases lt_trichotomy n k with (H | rfl | H)
· rw [nthLe_insertNth_of_lt _ _ _ _ H (H.trans hk),
nthLe_insertNth_of_lt _ _ _ _ (H.trans (Nat.lt_succ_self _))]
· rw [nthLe_insertNth_self _ _ _ hk.le, nthLe_insertNth_of_lt _ _ _ _ (Nat.lt_succ_self _) hk,
hk']
· rcases (Nat.succ_le_of_lt H).eq_or_lt with (rfl | H')
· rw [nthLe_insertNth_self _ _ _ (Nat.succ_le_of_lt hk)]
convert hk' using 1
exact nthLe_insertNth_add_succ _ _ _ 0 _
· obtain ⟨m, rfl⟩ := Nat.exists_eq_add_of_lt H'
erw [length_insertNth _ _ hk.le, Nat.succ_lt_succ_iff, Nat.succ_add] at hn
rw [nthLe_insertNth_add_succ]
· convert nthLe_insertNth_add_succ s x k m.succ (by simpa using hn) using 2
· simp [Nat.add_assoc, Nat.add_left_comm]
· simp [Nat.add_left_comm, Nat.add_comm]
· simpa [Nat.succ_add] using hn
#align list.nodup_permutations'_aux_iff List.nodup_permutations'Aux_iff
set_option linter.deprecated false in
| Mathlib/Data/List/Perm.lean | 869 | 905 | theorem nodup_permutations (s : List α) (hs : Nodup s) : Nodup s.permutations := by |
rw [(permutations_perm_permutations' s).nodup_iff]
induction' hs with x l h h' IH
· simp
· rw [permutations']
rw [nodup_bind]
constructor
· intro ys hy
rw [mem_permutations'] at hy
rw [nodup_permutations'Aux_iff, hy.mem_iff]
exact fun H => h x H rfl
· refine IH.pairwise_of_forall_ne fun as ha bs hb H => ?_
rw [disjoint_iff_ne]
rintro a ha' b hb' rfl
obtain ⟨⟨n, hn⟩, hn'⟩ := get_of_mem ha'
obtain ⟨⟨m, hm⟩, hm'⟩ := get_of_mem hb'
rw [mem_permutations'] at ha hb
have hl : as.length = bs.length := (ha.trans hb.symm).length_eq
simp only [Nat.lt_succ_iff, length_permutations'Aux] at hn hm
rw [← nthLe, nthLe_permutations'Aux] at hn' hm'
have hx :
nthLe (insertNth n x as) m (by rwa [length_insertNth _ _ hn, Nat.lt_succ_iff, hl]) = x := by
simp [hn', ← hm', hm]
have hx' :
nthLe (insertNth m x bs) n (by rwa [length_insertNth _ _ hm, Nat.lt_succ_iff, ← hl]) =
x := by
simp [hm', ← hn', hn]
rcases lt_trichotomy n m with (ht | ht | ht)
· suffices x ∈ bs by exact h x (hb.subset this) rfl
rw [← hx', nthLe_insertNth_of_lt _ _ _ _ ht (ht.trans_le hm)]
exact nthLe_mem _ _ _
· simp only [ht] at hm' hn'
rw [← hm'] at hn'
exact H (insertNth_injective _ _ hn')
· suffices x ∈ as by exact h x (ha.subset this) rfl
rw [← hx, nthLe_insertNth_of_lt _ _ _ _ ht (ht.trans_le hn)]
exact nthLe_mem _ _ _
|
/-
Copyright (c) 2020 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.Polynomial.Expand
import Mathlib.Algebra.Polynomial.Splits
import Mathlib.Algebra.Squarefree.Basic
import Mathlib.FieldTheory.Minpoly.Field
import Mathlib.RingTheory.PowerBasis
#align_import field_theory.separable from "leanprover-community/mathlib"@"92ca63f0fb391a9ca5f22d2409a6080e786d99f7"
/-!
# Separable polynomials
We define a polynomial to be separable if it is coprime with its derivative. We prove basic
properties about separable polynomials here.
## Main definitions
* `Polynomial.Separable f`: a polynomial `f` is separable iff it is coprime with its derivative.
-/
universe u v w
open scoped Classical
open Polynomial Finset
namespace Polynomial
section CommSemiring
variable {R : Type u} [CommSemiring R] {S : Type v} [CommSemiring S]
/-- A polynomial is separable iff it is coprime with its derivative. -/
def Separable (f : R[X]) : Prop :=
IsCoprime f (derivative f)
#align polynomial.separable Polynomial.Separable
theorem separable_def (f : R[X]) : f.Separable ↔ IsCoprime f (derivative f) :=
Iff.rfl
#align polynomial.separable_def Polynomial.separable_def
theorem separable_def' (f : R[X]) : f.Separable ↔ ∃ a b : R[X], a * f + b * (derivative f) = 1 :=
Iff.rfl
#align polynomial.separable_def' Polynomial.separable_def'
theorem not_separable_zero [Nontrivial R] : ¬Separable (0 : R[X]) := by
rintro ⟨x, y, h⟩
simp only [derivative_zero, mul_zero, add_zero, zero_ne_one] at h
#align polynomial.not_separable_zero Polynomial.not_separable_zero
theorem Separable.ne_zero [Nontrivial R] {f : R[X]} (h : f.Separable) : f ≠ 0 :=
(not_separable_zero <| · ▸ h)
@[simp]
theorem separable_one : (1 : R[X]).Separable :=
isCoprime_one_left
#align polynomial.separable_one Polynomial.separable_one
@[nontriviality]
theorem separable_of_subsingleton [Subsingleton R] (f : R[X]) : f.Separable := by
simp [Separable, IsCoprime, eq_iff_true_of_subsingleton]
#align polynomial.separable_of_subsingleton Polynomial.separable_of_subsingleton
theorem separable_X_add_C (a : R) : (X + C a).Separable := by
rw [separable_def, derivative_add, derivative_X, derivative_C, add_zero]
exact isCoprime_one_right
set_option linter.uppercaseLean3 false in
#align polynomial.separable_X_add_C Polynomial.separable_X_add_C
theorem separable_X : (X : R[X]).Separable := by
rw [separable_def, derivative_X]
exact isCoprime_one_right
set_option linter.uppercaseLean3 false in
#align polynomial.separable_X Polynomial.separable_X
theorem separable_C (r : R) : (C r).Separable ↔ IsUnit r := by
rw [separable_def, derivative_C, isCoprime_zero_right, isUnit_C]
set_option linter.uppercaseLean3 false in
#align polynomial.separable_C Polynomial.separable_C
theorem Separable.of_mul_left {f g : R[X]} (h : (f * g).Separable) : f.Separable := by
have := h.of_mul_left_left; rw [derivative_mul] at this
exact IsCoprime.of_mul_right_left (IsCoprime.of_add_mul_left_right this)
#align polynomial.separable.of_mul_left Polynomial.Separable.of_mul_left
theorem Separable.of_mul_right {f g : R[X]} (h : (f * g).Separable) : g.Separable := by
rw [mul_comm] at h
exact h.of_mul_left
#align polynomial.separable.of_mul_right Polynomial.Separable.of_mul_right
theorem Separable.of_dvd {f g : R[X]} (hf : f.Separable) (hfg : g ∣ f) : g.Separable := by
rcases hfg with ⟨f', rfl⟩
exact Separable.of_mul_left hf
#align polynomial.separable.of_dvd Polynomial.Separable.of_dvd
theorem separable_gcd_left {F : Type*} [Field F] {f : F[X]} (hf : f.Separable) (g : F[X]) :
(EuclideanDomain.gcd f g).Separable :=
Separable.of_dvd hf (EuclideanDomain.gcd_dvd_left f g)
#align polynomial.separable_gcd_left Polynomial.separable_gcd_left
theorem separable_gcd_right {F : Type*} [Field F] {g : F[X]} (f : F[X]) (hg : g.Separable) :
(EuclideanDomain.gcd f g).Separable :=
Separable.of_dvd hg (EuclideanDomain.gcd_dvd_right f g)
#align polynomial.separable_gcd_right Polynomial.separable_gcd_right
theorem Separable.isCoprime {f g : R[X]} (h : (f * g).Separable) : IsCoprime f g := by
have := h.of_mul_left_left; rw [derivative_mul] at this
exact IsCoprime.of_mul_right_right (IsCoprime.of_add_mul_left_right this)
#align polynomial.separable.is_coprime Polynomial.Separable.isCoprime
theorem Separable.of_pow' {f : R[X]} :
∀ {n : ℕ} (_h : (f ^ n).Separable), IsUnit f ∨ f.Separable ∧ n = 1 ∨ n = 0
| 0 => fun _h => Or.inr <| Or.inr rfl
| 1 => fun h => Or.inr <| Or.inl ⟨pow_one f ▸ h, rfl⟩
| n + 2 => fun h => by
rw [pow_succ, pow_succ] at h
exact Or.inl (isCoprime_self.1 h.isCoprime.of_mul_left_right)
#align polynomial.separable.of_pow' Polynomial.Separable.of_pow'
theorem Separable.of_pow {f : R[X]} (hf : ¬IsUnit f) {n : ℕ} (hn : n ≠ 0)
(hfs : (f ^ n).Separable) : f.Separable ∧ n = 1 :=
(hfs.of_pow'.resolve_left hf).resolve_right hn
#align polynomial.separable.of_pow Polynomial.Separable.of_pow
theorem Separable.map {p : R[X]} (h : p.Separable) {f : R →+* S} : (p.map f).Separable :=
let ⟨a, b, H⟩ := h
⟨a.map f, b.map f, by
rw [derivative_map, ← Polynomial.map_mul, ← Polynomial.map_mul, ← Polynomial.map_add, H,
Polynomial.map_one]⟩
#align polynomial.separable.map Polynomial.Separable.map
theorem _root_.Associated.separable {f g : R[X]}
(ha : Associated f g) (h : f.Separable) : g.Separable := by
obtain ⟨⟨u, v, h1, h2⟩, ha⟩ := ha
obtain ⟨a, b, h⟩ := h
refine ⟨a * v + b * derivative v, b * v, ?_⟩
replace h := congr($h * $(h1))
have h3 := congr(derivative $(h1))
simp only [← ha, derivative_mul, derivative_one] at h3 ⊢
calc
_ = (a * f + b * derivative f) * (u * v)
+ (b * f) * (derivative u * v + u * derivative v) := by ring1
_ = 1 := by rw [h, h3]; ring1
theorem _root_.Associated.separable_iff {f g : R[X]}
(ha : Associated f g) : f.Separable ↔ g.Separable := ⟨ha.separable, ha.symm.separable⟩
theorem Separable.mul_unit {f g : R[X]} (hf : f.Separable) (hg : IsUnit g) : (f * g).Separable :=
(associated_mul_unit_right f g hg).separable hf
theorem Separable.unit_mul {f g : R[X]} (hf : IsUnit f) (hg : g.Separable) : (f * g).Separable :=
(associated_unit_mul_right g f hf).separable hg
theorem Separable.eval₂_derivative_ne_zero [Nontrivial S] (f : R →+* S) {p : R[X]}
(h : p.Separable) {x : S} (hx : p.eval₂ f x = 0) :
(derivative p).eval₂ f x ≠ 0 := by
intro hx'
obtain ⟨a, b, e⟩ := h
apply_fun Polynomial.eval₂ f x at e
simp only [eval₂_add, eval₂_mul, hx, mul_zero, hx', add_zero, eval₂_one, zero_ne_one] at e
theorem Separable.aeval_derivative_ne_zero [Nontrivial S] [Algebra R S] {p : R[X]}
(h : p.Separable) {x : S} (hx : aeval x p = 0) :
aeval x (derivative p) ≠ 0 :=
h.eval₂_derivative_ne_zero (algebraMap R S) hx
variable (p q : ℕ)
theorem isUnit_of_self_mul_dvd_separable {p q : R[X]} (hp : p.Separable) (hq : q * q ∣ p) :
IsUnit q := by
obtain ⟨p, rfl⟩ := hq
apply isCoprime_self.mp
have : IsCoprime (q * (q * p))
(q * (derivative q * p + derivative q * p + q * derivative p)) := by
simp only [← mul_assoc, mul_add]
dsimp only [Separable] at hp
convert hp using 1
rw [derivative_mul, derivative_mul]
ring
exact IsCoprime.of_mul_right_left (IsCoprime.of_mul_left_left this)
#align polynomial.is_unit_of_self_mul_dvd_separable Polynomial.isUnit_of_self_mul_dvd_separable
theorem multiplicity_le_one_of_separable {p q : R[X]} (hq : ¬IsUnit q) (hsep : Separable p) :
multiplicity q p ≤ 1 := by
contrapose! hq
apply isUnit_of_self_mul_dvd_separable hsep
rw [← sq]
apply multiplicity.pow_dvd_of_le_multiplicity
have h : ⟨Part.Dom 1 ∧ Part.Dom 1, fun _ ↦ 2⟩ ≤ multiplicity q p := PartENat.add_one_le_of_lt hq
rw [and_self] at h
exact h
#align polynomial.multiplicity_le_one_of_separable Polynomial.multiplicity_le_one_of_separable
/-- A separable polynomial is square-free.
See `PerfectField.separable_iff_squarefree` for the converse when the coefficients are a perfect
field. -/
theorem Separable.squarefree {p : R[X]} (hsep : Separable p) : Squarefree p := by
rw [multiplicity.squarefree_iff_multiplicity_le_one p]
exact fun f => or_iff_not_imp_right.mpr fun hunit => multiplicity_le_one_of_separable hunit hsep
#align polynomial.separable.squarefree Polynomial.Separable.squarefree
end CommSemiring
section CommRing
variable {R : Type u} [CommRing R]
theorem separable_X_sub_C {x : R} : Separable (X - C x) := by
simpa only [sub_eq_add_neg, C_neg] using separable_X_add_C (-x)
set_option linter.uppercaseLean3 false in
#align polynomial.separable_X_sub_C Polynomial.separable_X_sub_C
theorem Separable.mul {f g : R[X]} (hf : f.Separable) (hg : g.Separable) (h : IsCoprime f g) :
(f * g).Separable := by
rw [separable_def, derivative_mul]
exact
((hf.mul_right h).add_mul_left_right _).mul_left ((h.symm.mul_right hg).mul_add_right_right _)
#align polynomial.separable.mul Polynomial.Separable.mul
theorem separable_prod' {ι : Sort _} {f : ι → R[X]} {s : Finset ι} :
(∀ x ∈ s, ∀ y ∈ s, x ≠ y → IsCoprime (f x) (f y)) →
(∀ x ∈ s, (f x).Separable) → (∏ x ∈ s, f x).Separable :=
Finset.induction_on s (fun _ _ => separable_one) fun a s has ih h1 h2 => by
simp_rw [Finset.forall_mem_insert, forall_and] at h1 h2; rw [prod_insert has]
exact
h2.1.mul (ih h1.2.2 h2.2)
(IsCoprime.prod_right fun i his => h1.1.2 i his <| Ne.symm <| ne_of_mem_of_not_mem his has)
#align polynomial.separable_prod' Polynomial.separable_prod'
theorem separable_prod {ι : Sort _} [Fintype ι] {f : ι → R[X]} (h1 : Pairwise (IsCoprime on f))
(h2 : ∀ x, (f x).Separable) : (∏ x, f x).Separable :=
separable_prod' (fun _x _hx _y _hy hxy => h1 hxy) fun x _hx => h2 x
#align polynomial.separable_prod Polynomial.separable_prod
theorem Separable.inj_of_prod_X_sub_C [Nontrivial R] {ι : Sort _} {f : ι → R} {s : Finset ι}
(hfs : (∏ i ∈ s, (X - C (f i))).Separable) {x y : ι} (hx : x ∈ s) (hy : y ∈ s)
(hfxy : f x = f y) : x = y := by
by_contra hxy
rw [← insert_erase hx, prod_insert (not_mem_erase _ _), ←
insert_erase (mem_erase_of_ne_of_mem (Ne.symm hxy) hy), prod_insert (not_mem_erase _ _), ←
mul_assoc, hfxy, ← sq] at hfs
cases (hfs.of_mul_left.of_pow (not_isUnit_X_sub_C _) two_ne_zero).2
set_option linter.uppercaseLean3 false in
#align polynomial.separable.inj_of_prod_X_sub_C Polynomial.Separable.inj_of_prod_X_sub_C
theorem Separable.injective_of_prod_X_sub_C [Nontrivial R] {ι : Sort _} [Fintype ι] {f : ι → R}
(hfs : (∏ i, (X - C (f i))).Separable) : Function.Injective f := fun _x _y hfxy =>
hfs.inj_of_prod_X_sub_C (mem_univ _) (mem_univ _) hfxy
set_option linter.uppercaseLean3 false in
#align polynomial.separable.injective_of_prod_X_sub_C Polynomial.Separable.injective_of_prod_X_sub_C
theorem nodup_of_separable_prod [Nontrivial R] {s : Multiset R}
(hs : Separable (Multiset.map (fun a => X - C a) s).prod) : s.Nodup := by
rw [Multiset.nodup_iff_ne_cons_cons]
rintro a t rfl
refine not_isUnit_X_sub_C a (isUnit_of_self_mul_dvd_separable hs ?_)
simpa only [Multiset.map_cons, Multiset.prod_cons] using mul_dvd_mul_left _ (dvd_mul_right _ _)
#align polynomial.nodup_of_separable_prod Polynomial.nodup_of_separable_prod
/-- If `IsUnit n` in a `CommRing R`, then `X ^ n - u` is separable for any unit `u`. -/
theorem separable_X_pow_sub_C_unit {n : ℕ} (u : Rˣ) (hn : IsUnit (n : R)) :
Separable (X ^ n - C (u : R)) := by
nontriviality R
rcases n.eq_zero_or_pos with (rfl | hpos)
· simp at hn
apply (separable_def' (X ^ n - C (u : R))).2
obtain ⟨n', hn'⟩ := hn.exists_left_inv
refine ⟨-C ↑u⁻¹, C (↑u⁻¹ : R) * C n' * X, ?_⟩
rw [derivative_sub, derivative_C, sub_zero, derivative_pow X n, derivative_X, mul_one]
calc
-C ↑u⁻¹ * (X ^ n - C ↑u) + C ↑u⁻¹ * C n' * X * (↑n * X ^ (n - 1)) =
C (↑u⁻¹ * ↑u) - C ↑u⁻¹ * X ^ n + C ↑u⁻¹ * C (n' * ↑n) * (X * X ^ (n - 1)) := by
simp only [C.map_mul, C_eq_natCast]
ring
_ = 1 := by
simp only [Units.inv_mul, hn', C.map_one, mul_one, ← pow_succ',
Nat.sub_add_cancel (show 1 ≤ n from hpos), sub_add_cancel]
set_option linter.uppercaseLean3 false in
#align polynomial.separable_X_pow_sub_C_unit Polynomial.separable_X_pow_sub_C_unit
theorem rootMultiplicity_le_one_of_separable [Nontrivial R] {p : R[X]} (hsep : Separable p)
(x : R) : rootMultiplicity x p ≤ 1 := by
by_cases hp : p = 0
· simp [hp]
rw [rootMultiplicity_eq_multiplicity, dif_neg hp, ← PartENat.coe_le_coe, PartENat.natCast_get,
Nat.cast_one]
exact multiplicity_le_one_of_separable (not_isUnit_X_sub_C _) hsep
#align polynomial.root_multiplicity_le_one_of_separable Polynomial.rootMultiplicity_le_one_of_separable
end CommRing
section IsDomain
variable {R : Type u} [CommRing R] [IsDomain R]
| Mathlib/FieldTheory/Separable.lean | 303 | 305 | theorem count_roots_le_one {p : R[X]} (hsep : Separable p) (x : R) : p.roots.count x ≤ 1 := by |
rw [count_roots p]
exact rootMultiplicity_le_one_of_separable hsep x
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Johannes Hölzl, Patrick Massot
-/
import Mathlib.Data.Set.Image
import Mathlib.Data.SProd
#align_import data.set.prod from "leanprover-community/mathlib"@"48fb5b5280e7c81672afc9524185ae994553ebf4"
/-!
# Sets in product and pi types
This file defines the product of sets in `α × β` and in `Π i, α i` along with the diagonal of a
type.
## Main declarations
* `Set.prod`: Binary product of sets. For `s : Set α`, `t : Set β`, we have
`s.prod t : Set (α × β)`.
* `Set.diagonal`: Diagonal of a type. `Set.diagonal α = {(x, x) | x : α}`.
* `Set.offDiag`: Off-diagonal. `s ×ˢ s` without the diagonal.
* `Set.pi`: Arbitrary product of sets.
-/
open Function
namespace Set
/-! ### Cartesian binary product of sets -/
section Prod
variable {α β γ δ : Type*} {s s₁ s₂ : Set α} {t t₁ t₂ : Set β} {a : α} {b : β}
theorem Subsingleton.prod (hs : s.Subsingleton) (ht : t.Subsingleton) :
(s ×ˢ t).Subsingleton := fun _x hx _y hy ↦
Prod.ext (hs hx.1 hy.1) (ht hx.2 hy.2)
noncomputable instance decidableMemProd [DecidablePred (· ∈ s)] [DecidablePred (· ∈ t)] :
DecidablePred (· ∈ s ×ˢ t) := fun _ => And.decidable
#align set.decidable_mem_prod Set.decidableMemProd
@[gcongr]
theorem prod_mono (hs : s₁ ⊆ s₂) (ht : t₁ ⊆ t₂) : s₁ ×ˢ t₁ ⊆ s₂ ×ˢ t₂ :=
fun _ ⟨h₁, h₂⟩ => ⟨hs h₁, ht h₂⟩
#align set.prod_mono Set.prod_mono
@[gcongr]
theorem prod_mono_left (hs : s₁ ⊆ s₂) : s₁ ×ˢ t ⊆ s₂ ×ˢ t :=
prod_mono hs Subset.rfl
#align set.prod_mono_left Set.prod_mono_left
@[gcongr]
theorem prod_mono_right (ht : t₁ ⊆ t₂) : s ×ˢ t₁ ⊆ s ×ˢ t₂ :=
prod_mono Subset.rfl ht
#align set.prod_mono_right Set.prod_mono_right
@[simp]
theorem prod_self_subset_prod_self : s₁ ×ˢ s₁ ⊆ s₂ ×ˢ s₂ ↔ s₁ ⊆ s₂ :=
⟨fun h _ hx => (h (mk_mem_prod hx hx)).1, fun h _ hx => ⟨h hx.1, h hx.2⟩⟩
#align set.prod_self_subset_prod_self Set.prod_self_subset_prod_self
@[simp]
theorem prod_self_ssubset_prod_self : s₁ ×ˢ s₁ ⊂ s₂ ×ˢ s₂ ↔ s₁ ⊂ s₂ :=
and_congr prod_self_subset_prod_self <| not_congr prod_self_subset_prod_self
#align set.prod_self_ssubset_prod_self Set.prod_self_ssubset_prod_self
theorem prod_subset_iff {P : Set (α × β)} : s ×ˢ t ⊆ P ↔ ∀ x ∈ s, ∀ y ∈ t, (x, y) ∈ P :=
⟨fun h _ hx _ hy => h (mk_mem_prod hx hy), fun h ⟨_, _⟩ hp => h _ hp.1 _ hp.2⟩
#align set.prod_subset_iff Set.prod_subset_iff
theorem forall_prod_set {p : α × β → Prop} : (∀ x ∈ s ×ˢ t, p x) ↔ ∀ x ∈ s, ∀ y ∈ t, p (x, y) :=
prod_subset_iff
#align set.forall_prod_set Set.forall_prod_set
theorem exists_prod_set {p : α × β → Prop} : (∃ x ∈ s ×ˢ t, p x) ↔ ∃ x ∈ s, ∃ y ∈ t, p (x, y) := by
simp [and_assoc]
#align set.exists_prod_set Set.exists_prod_set
@[simp]
theorem prod_empty : s ×ˢ (∅ : Set β) = ∅ := by
ext
exact and_false_iff _
#align set.prod_empty Set.prod_empty
@[simp]
theorem empty_prod : (∅ : Set α) ×ˢ t = ∅ := by
ext
exact false_and_iff _
#align set.empty_prod Set.empty_prod
@[simp, mfld_simps]
theorem univ_prod_univ : @univ α ×ˢ @univ β = univ := by
ext
exact true_and_iff _
#align set.univ_prod_univ Set.univ_prod_univ
theorem univ_prod {t : Set β} : (univ : Set α) ×ˢ t = Prod.snd ⁻¹' t := by simp [prod_eq]
#align set.univ_prod Set.univ_prod
theorem prod_univ {s : Set α} : s ×ˢ (univ : Set β) = Prod.fst ⁻¹' s := by simp [prod_eq]
#align set.prod_univ Set.prod_univ
@[simp] lemma prod_eq_univ [Nonempty α] [Nonempty β] : s ×ˢ t = univ ↔ s = univ ∧ t = univ := by
simp [eq_univ_iff_forall, forall_and]
@[simp]
theorem singleton_prod : ({a} : Set α) ×ˢ t = Prod.mk a '' t := by
ext ⟨x, y⟩
simp [and_left_comm, eq_comm]
#align set.singleton_prod Set.singleton_prod
@[simp]
theorem prod_singleton : s ×ˢ ({b} : Set β) = (fun a => (a, b)) '' s := by
ext ⟨x, y⟩
simp [and_left_comm, eq_comm]
#align set.prod_singleton Set.prod_singleton
theorem singleton_prod_singleton : ({a} : Set α) ×ˢ ({b} : Set β) = {(a, b)} := by simp
#align set.singleton_prod_singleton Set.singleton_prod_singleton
@[simp]
theorem union_prod : (s₁ ∪ s₂) ×ˢ t = s₁ ×ˢ t ∪ s₂ ×ˢ t := by
ext ⟨x, y⟩
simp [or_and_right]
#align set.union_prod Set.union_prod
@[simp]
theorem prod_union : s ×ˢ (t₁ ∪ t₂) = s ×ˢ t₁ ∪ s ×ˢ t₂ := by
ext ⟨x, y⟩
simp [and_or_left]
#align set.prod_union Set.prod_union
theorem inter_prod : (s₁ ∩ s₂) ×ˢ t = s₁ ×ˢ t ∩ s₂ ×ˢ t := by
ext ⟨x, y⟩
simp only [← and_and_right, mem_inter_iff, mem_prod]
#align set.inter_prod Set.inter_prod
theorem prod_inter : s ×ˢ (t₁ ∩ t₂) = s ×ˢ t₁ ∩ s ×ˢ t₂ := by
ext ⟨x, y⟩
simp only [← and_and_left, mem_inter_iff, mem_prod]
#align set.prod_inter Set.prod_inter
@[mfld_simps]
theorem prod_inter_prod : s₁ ×ˢ t₁ ∩ s₂ ×ˢ t₂ = (s₁ ∩ s₂) ×ˢ (t₁ ∩ t₂) := by
ext ⟨x, y⟩
simp [and_assoc, and_left_comm]
#align set.prod_inter_prod Set.prod_inter_prod
lemma compl_prod_eq_union {α β : Type*} (s : Set α) (t : Set β) :
(s ×ˢ t)ᶜ = (sᶜ ×ˢ univ) ∪ (univ ×ˢ tᶜ) := by
ext p
simp only [mem_compl_iff, mem_prod, not_and, mem_union, mem_univ, and_true, true_and]
constructor <;> intro h
· by_cases fst_in_s : p.fst ∈ s
· exact Or.inr (h fst_in_s)
· exact Or.inl fst_in_s
· intro fst_in_s
simpa only [fst_in_s, not_true, false_or] using h
@[simp]
theorem disjoint_prod : Disjoint (s₁ ×ˢ t₁) (s₂ ×ˢ t₂) ↔ Disjoint s₁ s₂ ∨ Disjoint t₁ t₂ := by
simp_rw [disjoint_left, mem_prod, not_and_or, Prod.forall, and_imp, ← @forall_or_right α, ←
@forall_or_left β, ← @forall_or_right (_ ∈ s₁), ← @forall_or_left (_ ∈ t₁)]
#align set.disjoint_prod Set.disjoint_prod
theorem Disjoint.set_prod_left (hs : Disjoint s₁ s₂) (t₁ t₂ : Set β) :
Disjoint (s₁ ×ˢ t₁) (s₂ ×ˢ t₂) :=
disjoint_left.2 fun ⟨_a, _b⟩ ⟨ha₁, _⟩ ⟨ha₂, _⟩ => disjoint_left.1 hs ha₁ ha₂
#align set.disjoint.set_prod_left Set.Disjoint.set_prod_left
theorem Disjoint.set_prod_right (ht : Disjoint t₁ t₂) (s₁ s₂ : Set α) :
Disjoint (s₁ ×ˢ t₁) (s₂ ×ˢ t₂) :=
disjoint_left.2 fun ⟨_a, _b⟩ ⟨_, hb₁⟩ ⟨_, hb₂⟩ => disjoint_left.1 ht hb₁ hb₂
#align set.disjoint.set_prod_right Set.Disjoint.set_prod_right
theorem insert_prod : insert a s ×ˢ t = Prod.mk a '' t ∪ s ×ˢ t := by
ext ⟨x, y⟩
simp (config := { contextual := true }) [image, iff_def, or_imp]
#align set.insert_prod Set.insert_prod
theorem prod_insert : s ×ˢ insert b t = (fun a => (a, b)) '' s ∪ s ×ˢ t := by
ext ⟨x, y⟩
-- porting note (#10745):
-- was `simp (config := { contextual := true }) [image, iff_def, or_imp, Imp.swap]`
simp only [mem_prod, mem_insert_iff, image, mem_union, mem_setOf_eq, Prod.mk.injEq]
refine ⟨fun h => ?_, fun h => ?_⟩
· obtain ⟨hx, rfl|hy⟩ := h
· exact Or.inl ⟨x, hx, rfl, rfl⟩
· exact Or.inr ⟨hx, hy⟩
· obtain ⟨x, hx, rfl, rfl⟩|⟨hx, hy⟩ := h
· exact ⟨hx, Or.inl rfl⟩
· exact ⟨hx, Or.inr hy⟩
#align set.prod_insert Set.prod_insert
theorem prod_preimage_eq {f : γ → α} {g : δ → β} :
(f ⁻¹' s) ×ˢ (g ⁻¹' t) = (fun p : γ × δ => (f p.1, g p.2)) ⁻¹' s ×ˢ t :=
rfl
#align set.prod_preimage_eq Set.prod_preimage_eq
theorem prod_preimage_left {f : γ → α} :
(f ⁻¹' s) ×ˢ t = (fun p : γ × β => (f p.1, p.2)) ⁻¹' s ×ˢ t :=
rfl
#align set.prod_preimage_left Set.prod_preimage_left
theorem prod_preimage_right {g : δ → β} :
s ×ˢ (g ⁻¹' t) = (fun p : α × δ => (p.1, g p.2)) ⁻¹' s ×ˢ t :=
rfl
#align set.prod_preimage_right Set.prod_preimage_right
theorem preimage_prod_map_prod (f : α → β) (g : γ → δ) (s : Set β) (t : Set δ) :
Prod.map f g ⁻¹' s ×ˢ t = (f ⁻¹' s) ×ˢ (g ⁻¹' t) :=
rfl
#align set.preimage_prod_map_prod Set.preimage_prod_map_prod
theorem mk_preimage_prod (f : γ → α) (g : γ → β) :
(fun x => (f x, g x)) ⁻¹' s ×ˢ t = f ⁻¹' s ∩ g ⁻¹' t :=
rfl
#align set.mk_preimage_prod Set.mk_preimage_prod
@[simp]
theorem mk_preimage_prod_left (hb : b ∈ t) : (fun a => (a, b)) ⁻¹' s ×ˢ t = s := by
ext a
simp [hb]
#align set.mk_preimage_prod_left Set.mk_preimage_prod_left
@[simp]
theorem mk_preimage_prod_right (ha : a ∈ s) : Prod.mk a ⁻¹' s ×ˢ t = t := by
ext b
simp [ha]
#align set.mk_preimage_prod_right Set.mk_preimage_prod_right
@[simp]
theorem mk_preimage_prod_left_eq_empty (hb : b ∉ t) : (fun a => (a, b)) ⁻¹' s ×ˢ t = ∅ := by
ext a
simp [hb]
#align set.mk_preimage_prod_left_eq_empty Set.mk_preimage_prod_left_eq_empty
@[simp]
theorem mk_preimage_prod_right_eq_empty (ha : a ∉ s) : Prod.mk a ⁻¹' s ×ˢ t = ∅ := by
ext b
simp [ha]
#align set.mk_preimage_prod_right_eq_empty Set.mk_preimage_prod_right_eq_empty
theorem mk_preimage_prod_left_eq_if [DecidablePred (· ∈ t)] :
(fun a => (a, b)) ⁻¹' s ×ˢ t = if b ∈ t then s else ∅ := by split_ifs with h <;> simp [h]
#align set.mk_preimage_prod_left_eq_if Set.mk_preimage_prod_left_eq_if
theorem mk_preimage_prod_right_eq_if [DecidablePred (· ∈ s)] :
Prod.mk a ⁻¹' s ×ˢ t = if a ∈ s then t else ∅ := by split_ifs with h <;> simp [h]
#align set.mk_preimage_prod_right_eq_if Set.mk_preimage_prod_right_eq_if
theorem mk_preimage_prod_left_fn_eq_if [DecidablePred (· ∈ t)] (f : γ → α) :
(fun a => (f a, b)) ⁻¹' s ×ˢ t = if b ∈ t then f ⁻¹' s else ∅ := by
rw [← mk_preimage_prod_left_eq_if, prod_preimage_left, preimage_preimage]
#align set.mk_preimage_prod_left_fn_eq_if Set.mk_preimage_prod_left_fn_eq_if
theorem mk_preimage_prod_right_fn_eq_if [DecidablePred (· ∈ s)] (g : δ → β) :
(fun b => (a, g b)) ⁻¹' s ×ˢ t = if a ∈ s then g ⁻¹' t else ∅ := by
rw [← mk_preimage_prod_right_eq_if, prod_preimage_right, preimage_preimage]
#align set.mk_preimage_prod_right_fn_eq_if Set.mk_preimage_prod_right_fn_eq_if
@[simp]
theorem preimage_swap_prod (s : Set α) (t : Set β) : Prod.swap ⁻¹' s ×ˢ t = t ×ˢ s := by
ext ⟨x, y⟩
simp [and_comm]
#align set.preimage_swap_prod Set.preimage_swap_prod
@[simp]
theorem image_swap_prod (s : Set α) (t : Set β) : Prod.swap '' s ×ˢ t = t ×ˢ s := by
rw [image_swap_eq_preimage_swap, preimage_swap_prod]
#align set.image_swap_prod Set.image_swap_prod
theorem prod_image_image_eq {m₁ : α → γ} {m₂ : β → δ} :
(m₁ '' s) ×ˢ (m₂ '' t) = (fun p : α × β => (m₁ p.1, m₂ p.2)) '' s ×ˢ t :=
ext <| by
simp [-exists_and_right, exists_and_right.symm, and_left_comm, and_assoc, and_comm]
#align set.prod_image_image_eq Set.prod_image_image_eq
theorem prod_range_range_eq {m₁ : α → γ} {m₂ : β → δ} :
range m₁ ×ˢ range m₂ = range fun p : α × β => (m₁ p.1, m₂ p.2) :=
ext <| by simp [range]
#align set.prod_range_range_eq Set.prod_range_range_eq
@[simp, mfld_simps]
theorem range_prod_map {m₁ : α → γ} {m₂ : β → δ} : range (Prod.map m₁ m₂) = range m₁ ×ˢ range m₂ :=
prod_range_range_eq.symm
#align set.range_prod_map Set.range_prod_map
theorem prod_range_univ_eq {m₁ : α → γ} :
range m₁ ×ˢ (univ : Set β) = range fun p : α × β => (m₁ p.1, p.2) :=
ext <| by simp [range]
#align set.prod_range_univ_eq Set.prod_range_univ_eq
theorem prod_univ_range_eq {m₂ : β → δ} :
(univ : Set α) ×ˢ range m₂ = range fun p : α × β => (p.1, m₂ p.2) :=
ext <| by simp [range]
#align set.prod_univ_range_eq Set.prod_univ_range_eq
theorem range_pair_subset (f : α → β) (g : α → γ) :
(range fun x => (f x, g x)) ⊆ range f ×ˢ range g := by
have : (fun x => (f x, g x)) = Prod.map f g ∘ fun x => (x, x) := funext fun x => rfl
rw [this, ← range_prod_map]
apply range_comp_subset_range
#align set.range_pair_subset Set.range_pair_subset
theorem Nonempty.prod : s.Nonempty → t.Nonempty → (s ×ˢ t).Nonempty := fun ⟨x, hx⟩ ⟨y, hy⟩ =>
⟨(x, y), ⟨hx, hy⟩⟩
#align set.nonempty.prod Set.Nonempty.prod
theorem Nonempty.fst : (s ×ˢ t).Nonempty → s.Nonempty := fun ⟨x, hx⟩ => ⟨x.1, hx.1⟩
#align set.nonempty.fst Set.Nonempty.fst
theorem Nonempty.snd : (s ×ˢ t).Nonempty → t.Nonempty := fun ⟨x, hx⟩ => ⟨x.2, hx.2⟩
#align set.nonempty.snd Set.Nonempty.snd
@[simp]
theorem prod_nonempty_iff : (s ×ˢ t).Nonempty ↔ s.Nonempty ∧ t.Nonempty :=
⟨fun h => ⟨h.fst, h.snd⟩, fun h => h.1.prod h.2⟩
#align set.prod_nonempty_iff Set.prod_nonempty_iff
@[simp]
theorem prod_eq_empty_iff : s ×ˢ t = ∅ ↔ s = ∅ ∨ t = ∅ := by
simp only [not_nonempty_iff_eq_empty.symm, prod_nonempty_iff, not_and_or]
#align set.prod_eq_empty_iff Set.prod_eq_empty_iff
theorem prod_sub_preimage_iff {W : Set γ} {f : α × β → γ} :
s ×ˢ t ⊆ f ⁻¹' W ↔ ∀ a b, a ∈ s → b ∈ t → f (a, b) ∈ W := by simp [subset_def]
#align set.prod_sub_preimage_iff Set.prod_sub_preimage_iff
theorem image_prod_mk_subset_prod {f : α → β} {g : α → γ} {s : Set α} :
(fun x => (f x, g x)) '' s ⊆ (f '' s) ×ˢ (g '' s) := by
rintro _ ⟨x, hx, rfl⟩
exact mk_mem_prod (mem_image_of_mem f hx) (mem_image_of_mem g hx)
#align set.image_prod_mk_subset_prod Set.image_prod_mk_subset_prod
theorem image_prod_mk_subset_prod_left (hb : b ∈ t) : (fun a => (a, b)) '' s ⊆ s ×ˢ t := by
rintro _ ⟨a, ha, rfl⟩
exact ⟨ha, hb⟩
#align set.image_prod_mk_subset_prod_left Set.image_prod_mk_subset_prod_left
theorem image_prod_mk_subset_prod_right (ha : a ∈ s) : Prod.mk a '' t ⊆ s ×ˢ t := by
rintro _ ⟨b, hb, rfl⟩
exact ⟨ha, hb⟩
#align set.image_prod_mk_subset_prod_right Set.image_prod_mk_subset_prod_right
theorem prod_subset_preimage_fst (s : Set α) (t : Set β) : s ×ˢ t ⊆ Prod.fst ⁻¹' s :=
inter_subset_left
#align set.prod_subset_preimage_fst Set.prod_subset_preimage_fst
theorem fst_image_prod_subset (s : Set α) (t : Set β) : Prod.fst '' s ×ˢ t ⊆ s :=
image_subset_iff.2 <| prod_subset_preimage_fst s t
#align set.fst_image_prod_subset Set.fst_image_prod_subset
theorem fst_image_prod (s : Set β) {t : Set α} (ht : t.Nonempty) : Prod.fst '' s ×ˢ t = s :=
(fst_image_prod_subset _ _).antisymm fun y hy =>
let ⟨x, hx⟩ := ht
⟨(y, x), ⟨hy, hx⟩, rfl⟩
#align set.fst_image_prod Set.fst_image_prod
theorem prod_subset_preimage_snd (s : Set α) (t : Set β) : s ×ˢ t ⊆ Prod.snd ⁻¹' t :=
inter_subset_right
#align set.prod_subset_preimage_snd Set.prod_subset_preimage_snd
theorem snd_image_prod_subset (s : Set α) (t : Set β) : Prod.snd '' s ×ˢ t ⊆ t :=
image_subset_iff.2 <| prod_subset_preimage_snd s t
#align set.snd_image_prod_subset Set.snd_image_prod_subset
theorem snd_image_prod {s : Set α} (hs : s.Nonempty) (t : Set β) : Prod.snd '' s ×ˢ t = t :=
(snd_image_prod_subset _ _).antisymm fun y y_in =>
let ⟨x, x_in⟩ := hs
⟨(x, y), ⟨x_in, y_in⟩, rfl⟩
#align set.snd_image_prod Set.snd_image_prod
theorem prod_diff_prod : s ×ˢ t \ s₁ ×ˢ t₁ = s ×ˢ (t \ t₁) ∪ (s \ s₁) ×ˢ t := by
ext x
by_cases h₁ : x.1 ∈ s₁ <;> by_cases h₂ : x.2 ∈ t₁ <;> simp [*]
#align set.prod_diff_prod Set.prod_diff_prod
/-- A product set is included in a product set if and only factors are included, or a factor of the
first set is empty. -/
theorem prod_subset_prod_iff : s ×ˢ t ⊆ s₁ ×ˢ t₁ ↔ s ⊆ s₁ ∧ t ⊆ t₁ ∨ s = ∅ ∨ t = ∅ := by
rcases (s ×ˢ t).eq_empty_or_nonempty with h | h
· simp [h, prod_eq_empty_iff.1 h]
have st : s.Nonempty ∧ t.Nonempty := by rwa [prod_nonempty_iff] at h
refine ⟨fun H => Or.inl ⟨?_, ?_⟩, ?_⟩
· have := image_subset (Prod.fst : α × β → α) H
rwa [fst_image_prod _ st.2, fst_image_prod _ (h.mono H).snd] at this
· have := image_subset (Prod.snd : α × β → β) H
rwa [snd_image_prod st.1, snd_image_prod (h.mono H).fst] at this
· intro H
simp only [st.1.ne_empty, st.2.ne_empty, or_false_iff] at H
exact prod_mono H.1 H.2
#align set.prod_subset_prod_iff Set.prod_subset_prod_iff
theorem prod_eq_prod_iff_of_nonempty (h : (s ×ˢ t).Nonempty) :
s ×ˢ t = s₁ ×ˢ t₁ ↔ s = s₁ ∧ t = t₁ := by
constructor
· intro heq
have h₁ : (s₁ ×ˢ t₁ : Set _).Nonempty := by rwa [← heq]
rw [prod_nonempty_iff] at h h₁
rw [← fst_image_prod s h.2, ← fst_image_prod s₁ h₁.2, heq, eq_self_iff_true, true_and_iff, ←
snd_image_prod h.1 t, ← snd_image_prod h₁.1 t₁, heq]
· rintro ⟨rfl, rfl⟩
rfl
#align set.prod_eq_prod_iff_of_nonempty Set.prod_eq_prod_iff_of_nonempty
theorem prod_eq_prod_iff :
s ×ˢ t = s₁ ×ˢ t₁ ↔ s = s₁ ∧ t = t₁ ∨ (s = ∅ ∨ t = ∅) ∧ (s₁ = ∅ ∨ t₁ = ∅) := by
symm
rcases eq_empty_or_nonempty (s ×ˢ t) with h | h
· simp_rw [h, @eq_comm _ ∅, prod_eq_empty_iff, prod_eq_empty_iff.mp h, true_and_iff,
or_iff_right_iff_imp]
rintro ⟨rfl, rfl⟩
exact prod_eq_empty_iff.mp h
rw [prod_eq_prod_iff_of_nonempty h]
rw [nonempty_iff_ne_empty, Ne, prod_eq_empty_iff] at h
simp_rw [h, false_and_iff, or_false_iff]
#align set.prod_eq_prod_iff Set.prod_eq_prod_iff
@[simp]
theorem prod_eq_iff_eq (ht : t.Nonempty) : s ×ˢ t = s₁ ×ˢ t ↔ s = s₁ := by
simp_rw [prod_eq_prod_iff, ht.ne_empty, and_true_iff, or_iff_left_iff_imp,
or_false_iff]
rintro ⟨rfl, rfl⟩
rfl
#align set.prod_eq_iff_eq Set.prod_eq_iff_eq
section Mono
variable [Preorder α] {f : α → Set β} {g : α → Set γ}
theorem _root_.Monotone.set_prod (hf : Monotone f) (hg : Monotone g) :
Monotone fun x => f x ×ˢ g x :=
fun _ _ h => prod_mono (hf h) (hg h)
#align monotone.set_prod Monotone.set_prod
theorem _root_.Antitone.set_prod (hf : Antitone f) (hg : Antitone g) :
Antitone fun x => f x ×ˢ g x :=
fun _ _ h => prod_mono (hf h) (hg h)
#align antitone.set_prod Antitone.set_prod
theorem _root_.MonotoneOn.set_prod (hf : MonotoneOn f s) (hg : MonotoneOn g s) :
MonotoneOn (fun x => f x ×ˢ g x) s := fun _ ha _ hb h => prod_mono (hf ha hb h) (hg ha hb h)
#align monotone_on.set_prod MonotoneOn.set_prod
theorem _root_.AntitoneOn.set_prod (hf : AntitoneOn f s) (hg : AntitoneOn g s) :
AntitoneOn (fun x => f x ×ˢ g x) s := fun _ ha _ hb h => prod_mono (hf ha hb h) (hg ha hb h)
#align antitone_on.set_prod AntitoneOn.set_prod
end Mono
end Prod
/-! ### Diagonal
In this section we prove some lemmas about the diagonal set `{p | p.1 = p.2}` and the diagonal map
`fun x ↦ (x, x)`.
-/
section Diagonal
variable {α : Type*} {s t : Set α}
lemma diagonal_nonempty [Nonempty α] : (diagonal α).Nonempty :=
Nonempty.elim ‹_› fun x => ⟨_, mem_diagonal x⟩
#align set.diagonal_nonempty Set.diagonal_nonempty
instance decidableMemDiagonal [h : DecidableEq α] (x : α × α) : Decidable (x ∈ diagonal α) :=
h x.1 x.2
#align set.decidable_mem_diagonal Set.decidableMemDiagonal
theorem preimage_coe_coe_diagonal (s : Set α) :
Prod.map (fun x : s => (x : α)) (fun x : s => (x : α)) ⁻¹' diagonal α = diagonal s := by
ext ⟨⟨x, hx⟩, ⟨y, hy⟩⟩
simp [Set.diagonal]
#align set.preimage_coe_coe_diagonal Set.preimage_coe_coe_diagonal
@[simp]
theorem range_diag : (range fun x => (x, x)) = diagonal α := by
ext ⟨x, y⟩
simp [diagonal, eq_comm]
#align set.range_diag Set.range_diag
theorem diagonal_subset_iff {s} : diagonal α ⊆ s ↔ ∀ x, (x, x) ∈ s := by
rw [← range_diag, range_subset_iff]
#align set.diagonal_subset_iff Set.diagonal_subset_iff
@[simp]
theorem prod_subset_compl_diagonal_iff_disjoint : s ×ˢ t ⊆ (diagonal α)ᶜ ↔ Disjoint s t :=
prod_subset_iff.trans disjoint_iff_forall_ne.symm
#align set.prod_subset_compl_diagonal_iff_disjoint Set.prod_subset_compl_diagonal_iff_disjoint
@[simp]
theorem diag_preimage_prod (s t : Set α) : (fun x => (x, x)) ⁻¹' s ×ˢ t = s ∩ t :=
rfl
#align set.diag_preimage_prod Set.diag_preimage_prod
theorem diag_preimage_prod_self (s : Set α) : (fun x => (x, x)) ⁻¹' s ×ˢ s = s :=
inter_self s
#align set.diag_preimage_prod_self Set.diag_preimage_prod_self
theorem diag_image (s : Set α) : (fun x => (x, x)) '' s = diagonal α ∩ s ×ˢ s := by
rw [← range_diag, ← image_preimage_eq_range_inter, diag_preimage_prod_self]
#align set.diag_image Set.diag_image
theorem diagonal_eq_univ_iff : diagonal α = univ ↔ Subsingleton α := by
simp only [subsingleton_iff, eq_univ_iff_forall, Prod.forall, mem_diagonal_iff]
theorem diagonal_eq_univ [Subsingleton α] : diagonal α = univ := diagonal_eq_univ_iff.2 ‹_›
end Diagonal
/-- A function is `Function.const α a` for some `a` if and only if `∀ x y, f x = f y`. -/
theorem range_const_eq_diagonal {α β : Type*} [hβ : Nonempty β] :
range (const α) = {f : α → β | ∀ x y, f x = f y} := by
refine (range_eq_iff _ _).mpr ⟨fun _ _ _ ↦ rfl, fun f hf ↦ ?_⟩
rcases isEmpty_or_nonempty α with h|⟨⟨a⟩⟩
· exact hβ.elim fun b ↦ ⟨b, Subsingleton.elim _ _⟩
· exact ⟨f a, funext fun x ↦ hf _ _⟩
end Set
section Pullback
open Set
variable {X Y Z}
/-- The fiber product $X \times_Y Z$. -/
abbrev Function.Pullback (f : X → Y) (g : Z → Y) := {p : X × Z // f p.1 = g p.2}
/-- The fiber product $X \times_Y X$. -/
abbrev Function.PullbackSelf (f : X → Y) := f.Pullback f
/-- The projection from the fiber product to the first factor. -/
def Function.Pullback.fst {f : X → Y} {g : Z → Y} (p : f.Pullback g) : X := p.val.1
/-- The projection from the fiber product to the second factor. -/
def Function.Pullback.snd {f : X → Y} {g : Z → Y} (p : f.Pullback g) : Z := p.val.2
open Function.Pullback in
lemma Function.pullback_comm_sq (f : X → Y) (g : Z → Y) :
f ∘ @fst X Y Z f g = g ∘ @snd X Y Z f g := funext fun p ↦ p.2
/-- The diagonal map $\Delta: X \to X \times_Y X$. -/
def toPullbackDiag (f : X → Y) (x : X) : f.Pullback f := ⟨(x, x), rfl⟩
/-- The diagonal $\Delta(X) \subseteq X \times_Y X$. -/
def Function.pullbackDiagonal (f : X → Y) : Set (f.Pullback f) := {p | p.fst = p.snd}
/-- Three functions between the three pairs of spaces $X_i, Y_i, Z_i$ that are compatible
induce a function $X_1 \times_{Y_1} Z_1 \to X_2 \times_{Y_2} Z_2$. -/
def Function.mapPullback {X₁ X₂ Y₁ Y₂ Z₁ Z₂}
{f₁ : X₁ → Y₁} {g₁ : Z₁ → Y₁} {f₂ : X₂ → Y₂} {g₂ : Z₂ → Y₂}
(mapX : X₁ → X₂) (mapY : Y₁ → Y₂) (mapZ : Z₁ → Z₂)
(commX : f₂ ∘ mapX = mapY ∘ f₁) (commZ : g₂ ∘ mapZ = mapY ∘ g₁)
(p : f₁.Pullback g₁) : f₂.Pullback g₂ :=
⟨(mapX p.fst, mapZ p.snd),
(congr_fun commX _).trans <| (congr_arg mapY p.2).trans <| congr_fun commZ.symm _⟩
open Function.Pullback in
/-- The projection $(X \times_Y Z) \times_Z (X \times_Y Z) \to X \times_Y X$. -/
def Function.PullbackSelf.map_fst {f : X → Y} {g : Z → Y} :
(@snd X Y Z f g).PullbackSelf → f.PullbackSelf :=
mapPullback fst g fst (pullback_comm_sq f g) (pullback_comm_sq f g)
open Function.Pullback in
/-- The projection $(X \times_Y Z) \times_X (X \times_Y Z) \to Z \times_Y Z$. -/
def Function.PullbackSelf.map_snd {f : X → Y} {g : Z → Y} :
(@fst X Y Z f g).PullbackSelf → g.PullbackSelf :=
mapPullback snd f snd (pullback_comm_sq f g).symm (pullback_comm_sq f g).symm
open Function.PullbackSelf Function.Pullback
theorem preimage_map_fst_pullbackDiagonal {f : X → Y} {g : Z → Y} :
@map_fst X Y Z f g ⁻¹' pullbackDiagonal f = pullbackDiagonal (@snd X Y Z f g) := by
ext ⟨⟨p₁, p₂⟩, he⟩
simp_rw [pullbackDiagonal, mem_setOf, Subtype.ext_iff, Prod.ext_iff]
exact (and_iff_left he).symm
theorem Function.Injective.preimage_pullbackDiagonal {f : X → Y} {g : Z → X} (inj : g.Injective) :
mapPullback g id g (by rfl) (by rfl) ⁻¹' pullbackDiagonal f = pullbackDiagonal (f ∘ g) :=
ext fun _ ↦ inj.eq_iff
theorem image_toPullbackDiag (f : X → Y) (s : Set X) :
toPullbackDiag f '' s = pullbackDiagonal f ∩ Subtype.val ⁻¹' s ×ˢ s := by
ext x
constructor
· rintro ⟨x, hx, rfl⟩
exact ⟨rfl, hx, hx⟩
· obtain ⟨⟨x, y⟩, h⟩ := x
rintro ⟨rfl : x = y, h2x⟩
exact mem_image_of_mem _ h2x.1
theorem range_toPullbackDiag (f : X → Y) : range (toPullbackDiag f) = pullbackDiagonal f := by
rw [← image_univ, image_toPullbackDiag, univ_prod_univ, preimage_univ, inter_univ]
theorem injective_toPullbackDiag (f : X → Y) : (toPullbackDiag f).Injective :=
fun _ _ h ↦ congr_arg Prod.fst (congr_arg Subtype.val h)
end Pullback
namespace Set
section OffDiag
variable {α : Type*} {s t : Set α} {x : α × α} {a : α}
theorem offDiag_mono : Monotone (offDiag : Set α → Set (α × α)) := fun _ _ h _ =>
And.imp (@h _) <| And.imp_left <| @h _
#align set.off_diag_mono Set.offDiag_mono
@[simp]
theorem offDiag_nonempty : s.offDiag.Nonempty ↔ s.Nontrivial := by
simp [offDiag, Set.Nonempty, Set.Nontrivial]
#align set.off_diag_nonempty Set.offDiag_nonempty
@[simp]
theorem offDiag_eq_empty : s.offDiag = ∅ ↔ s.Subsingleton := by
rw [← not_nonempty_iff_eq_empty, ← not_nontrivial_iff, offDiag_nonempty.not]
#align set.off_diag_eq_empty Set.offDiag_eq_empty
alias ⟨_, Nontrivial.offDiag_nonempty⟩ := offDiag_nonempty
#align set.nontrivial.off_diag_nonempty Set.Nontrivial.offDiag_nonempty
alias ⟨_, Subsingleton.offDiag_eq_empty⟩ := offDiag_nonempty
#align set.subsingleton.off_diag_eq_empty Set.Subsingleton.offDiag_eq_empty
variable (s t)
theorem offDiag_subset_prod : s.offDiag ⊆ s ×ˢ s := fun _ hx => ⟨hx.1, hx.2.1⟩
#align set.off_diag_subset_prod Set.offDiag_subset_prod
theorem offDiag_eq_sep_prod : s.offDiag = { x ∈ s ×ˢ s | x.1 ≠ x.2 } :=
ext fun _ => and_assoc.symm
#align set.off_diag_eq_sep_prod Set.offDiag_eq_sep_prod
@[simp]
theorem offDiag_empty : (∅ : Set α).offDiag = ∅ := by simp
#align set.off_diag_empty Set.offDiag_empty
@[simp]
theorem offDiag_singleton (a : α) : ({a} : Set α).offDiag = ∅ := by simp
#align set.off_diag_singleton Set.offDiag_singleton
@[simp]
theorem offDiag_univ : (univ : Set α).offDiag = (diagonal α)ᶜ :=
ext <| by simp
#align set.off_diag_univ Set.offDiag_univ
@[simp]
theorem prod_sdiff_diagonal : s ×ˢ s \ diagonal α = s.offDiag :=
ext fun _ => and_assoc
#align set.prod_sdiff_diagonal Set.prod_sdiff_diagonal
@[simp]
theorem disjoint_diagonal_offDiag : Disjoint (diagonal α) s.offDiag :=
disjoint_left.mpr fun _ hd ho => ho.2.2 hd
#align set.disjoint_diagonal_off_diag Set.disjoint_diagonal_offDiag
theorem offDiag_inter : (s ∩ t).offDiag = s.offDiag ∩ t.offDiag :=
ext fun x => by
simp only [mem_offDiag, mem_inter_iff]
tauto
#align set.off_diag_inter Set.offDiag_inter
variable {s t}
theorem offDiag_union (h : Disjoint s t) :
(s ∪ t).offDiag = s.offDiag ∪ t.offDiag ∪ s ×ˢ t ∪ t ×ˢ s := by
ext x
simp only [mem_offDiag, mem_union, ne_eq, mem_prod]
constructor
· rintro ⟨h0|h0, h1|h1, h2⟩ <;> simp [h0, h1, h2]
· rintro (((⟨h0, h1, h2⟩|⟨h0, h1, h2⟩)|⟨h0, h1⟩)|⟨h0, h1⟩) <;> simp [*]
· rintro h3
rw [h3] at h0
exact Set.disjoint_left.mp h h0 h1
· rintro h3
rw [h3] at h0
exact (Set.disjoint_right.mp h h0 h1).elim
#align set.off_diag_union Set.offDiag_union
theorem offDiag_insert (ha : a ∉ s) : (insert a s).offDiag = s.offDiag ∪ {a} ×ˢ s ∪ s ×ˢ {a} := by
rw [insert_eq, union_comm, offDiag_union, offDiag_singleton, union_empty, union_right_comm]
rw [disjoint_left]
rintro b hb (rfl : b = a)
exact ha hb
#align set.off_diag_insert Set.offDiag_insert
end OffDiag
/-! ### Cartesian set-indexed product of sets -/
section Pi
variable {ι : Type*} {α β : ι → Type*} {s s₁ s₂ : Set ι} {t t₁ t₂ : ∀ i, Set (α i)} {i : ι}
@[simp]
| Mathlib/Data/Set/Prod.lean | 705 | 707 | theorem empty_pi (s : ∀ i, Set (α i)) : pi ∅ s = univ := by |
ext
simp [pi]
|
/-
Copyright (c) 2022 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Analysis.InnerProductSpace.PiL2
import Mathlib.Combinatorics.Additive.AP.Three.Defs
import Mathlib.Combinatorics.Pigeonhole
import Mathlib.Data.Complex.ExponentialBounds
#align_import combinatorics.additive.behrend from "leanprover-community/mathlib"@"4fa54b337f7d52805480306db1b1439c741848c8"
/-!
# Behrend's bound on Roth numbers
This file proves Behrend's lower bound on Roth numbers. This says that we can find a subset of
`{1, ..., n}` of size `n / exp (O (sqrt (log n)))` which does not contain arithmetic progressions of
length `3`.
The idea is that the sphere (in the `n` dimensional Euclidean space) doesn't contain arithmetic
progressions (literally) because the corresponding ball is strictly convex. Thus we can take
integer points on that sphere and map them onto `ℕ` in a way that preserves arithmetic progressions
(`Behrend.map`).
## Main declarations
* `Behrend.sphere`: The intersection of the Euclidean sphere with the positive integer quadrant.
This is the set that we will map on `ℕ`.
* `Behrend.map`: Given a natural number `d`, `Behrend.map d : ℕⁿ → ℕ` reads off the coordinates as
digits in base `d`.
* `Behrend.card_sphere_le_rothNumberNat`: Implicit lower bound on Roth numbers in terms of
`Behrend.sphere`.
* `Behrend.roth_lower_bound`: Behrend's explicit lower bound on Roth numbers.
## References
* [Bryan Gillespie, *Behrend’s Construction*]
(http://www.epsilonsmall.com/resources/behrends-construction/behrend.pdf)
* Behrend, F. A., "On sets of integers which contain no three terms in arithmetical progression"
* [Wikipedia, *Salem-Spencer set*](https://en.wikipedia.org/wiki/Salem–Spencer_set)
## Tags
3AP-free, Salem-Spencer, Behrend construction, arithmetic progression, sphere, strictly convex
-/
open Nat hiding log
open Finset Metric Real
open scoped Pointwise
/-- The frontier of a closed strictly convex set only contains trivial arithmetic progressions.
The idea is that an arithmetic progression is contained on a line and the frontier of a strictly
convex set does not contain lines. -/
lemma threeAPFree_frontier {𝕜 E : Type*} [LinearOrderedField 𝕜] [TopologicalSpace E]
[AddCommMonoid E] [Module 𝕜 E] {s : Set E} (hs₀ : IsClosed s) (hs₁ : StrictConvex 𝕜 s) :
ThreeAPFree (frontier s) := by
intro a ha b hb c hc habc
obtain rfl : (1 / 2 : 𝕜) • a + (1 / 2 : 𝕜) • c = b := by
rwa [← smul_add, one_div, inv_smul_eq_iff₀ (show (2 : 𝕜) ≠ 0 by norm_num), two_smul]
have :=
hs₁.eq (hs₀.frontier_subset ha) (hs₀.frontier_subset hc) one_half_pos one_half_pos
(add_halves _) hb.2
simp [this, ← add_smul]
ring_nf
simp
#align add_salem_spencer_frontier threeAPFree_frontier
lemma threeAPFree_sphere {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[StrictConvexSpace ℝ E] (x : E) (r : ℝ) : ThreeAPFree (sphere x r) := by
obtain rfl | hr := eq_or_ne r 0
· rw [sphere_zero]
exact threeAPFree_singleton _
· convert threeAPFree_frontier isClosed_ball (strictConvex_closedBall ℝ x r)
exact (frontier_closedBall _ hr).symm
#align add_salem_spencer_sphere threeAPFree_sphere
namespace Behrend
variable {α β : Type*} {n d k N : ℕ} {x : Fin n → ℕ}
/-!
### Turning the sphere into 3AP-free set
We define `Behrend.sphere`, the intersection of the $L^2$ sphere with the positive quadrant of
integer points. Because the $L^2$ closed ball is strictly convex, the $L^2$ sphere and
`Behrend.sphere` are 3AP-free (`threeAPFree_sphere`). Then we can turn this set in
`Fin n → ℕ` into a set in `ℕ` using `Behrend.map`, which preserves `ThreeAPFree` because it is
an additive monoid homomorphism.
-/
/-- The box `{0, ..., d - 1}^n` as a `Finset`. -/
def box (n d : ℕ) : Finset (Fin n → ℕ) :=
Fintype.piFinset fun _ => range d
#align behrend.box Behrend.box
theorem mem_box : x ∈ box n d ↔ ∀ i, x i < d := by simp only [box, Fintype.mem_piFinset, mem_range]
#align behrend.mem_box Behrend.mem_box
@[simp]
theorem card_box : (box n d).card = d ^ n := by simp [box]
#align behrend.card_box Behrend.card_box
@[simp]
theorem box_zero : box (n + 1) 0 = ∅ := by simp [box]
#align behrend.box_zero Behrend.box_zero
/-- The intersection of the sphere of radius `√k` with the integer points in the positive
quadrant. -/
def sphere (n d k : ℕ) : Finset (Fin n → ℕ) :=
(box n d).filter fun x => ∑ i, x i ^ 2 = k
#align behrend.sphere Behrend.sphere
theorem sphere_zero_subset : sphere n d 0 ⊆ 0 := fun x => by simp [sphere, Function.funext_iff]
#align behrend.sphere_zero_subset Behrend.sphere_zero_subset
@[simp]
theorem sphere_zero_right (n k : ℕ) : sphere (n + 1) 0 k = ∅ := by simp [sphere]
#align behrend.sphere_zero_right Behrend.sphere_zero_right
theorem sphere_subset_box : sphere n d k ⊆ box n d :=
filter_subset _ _
#align behrend.sphere_subset_box Behrend.sphere_subset_box
theorem norm_of_mem_sphere {x : Fin n → ℕ} (hx : x ∈ sphere n d k) :
‖(WithLp.equiv 2 _).symm ((↑) ∘ x : Fin n → ℝ)‖ = √↑k := by
rw [EuclideanSpace.norm_eq]
dsimp
simp_rw [abs_cast, ← cast_pow, ← cast_sum, (mem_filter.1 hx).2]
#align behrend.norm_of_mem_sphere Behrend.norm_of_mem_sphere
theorem sphere_subset_preimage_metric_sphere : (sphere n d k : Set (Fin n → ℕ)) ⊆
(fun x : Fin n → ℕ => (WithLp.equiv 2 _).symm ((↑) ∘ x : Fin n → ℝ)) ⁻¹'
Metric.sphere (0 : PiLp 2 fun _ : Fin n => ℝ) (√↑k) :=
fun x hx => by rw [Set.mem_preimage, mem_sphere_zero_iff_norm, norm_of_mem_sphere hx]
#align behrend.sphere_subset_preimage_metric_sphere Behrend.sphere_subset_preimage_metric_sphere
/-- The map that appears in Behrend's bound on Roth numbers. -/
@[simps]
def map (d : ℕ) : (Fin n → ℕ) →+ ℕ where
toFun a := ∑ i, a i * d ^ (i : ℕ)
map_zero' := by simp_rw [Pi.zero_apply, zero_mul, sum_const_zero]
map_add' a b := by simp_rw [Pi.add_apply, add_mul, sum_add_distrib]
#align behrend.map Behrend.map
-- @[simp] -- Porting note (#10618): simp can prove this
theorem map_zero (d : ℕ) (a : Fin 0 → ℕ) : map d a = 0 := by simp [map]
#align behrend.map_zero Behrend.map_zero
theorem map_succ (a : Fin (n + 1) → ℕ) :
map d a = a 0 + (∑ x : Fin n, a x.succ * d ^ (x : ℕ)) * d := by
simp [map, Fin.sum_univ_succ, _root_.pow_succ, ← mul_assoc, ← sum_mul]
#align behrend.map_succ Behrend.map_succ
theorem map_succ' (a : Fin (n + 1) → ℕ) : map d a = a 0 + map d (a ∘ Fin.succ) * d :=
map_succ _
#align behrend.map_succ' Behrend.map_succ'
theorem map_monotone (d : ℕ) : Monotone (map d : (Fin n → ℕ) → ℕ) := fun x y h => by
dsimp; exact sum_le_sum fun i _ => Nat.mul_le_mul_right _ <| h i
#align behrend.map_monotone Behrend.map_monotone
theorem map_mod (a : Fin n.succ → ℕ) : map d a % d = a 0 % d := by
rw [map_succ, Nat.add_mul_mod_self_right]
#align behrend.map_mod Behrend.map_mod
theorem map_eq_iff {x₁ x₂ : Fin n.succ → ℕ} (hx₁ : ∀ i, x₁ i < d) (hx₂ : ∀ i, x₂ i < d) :
map d x₁ = map d x₂ ↔ x₁ 0 = x₂ 0 ∧ map d (x₁ ∘ Fin.succ) = map d (x₂ ∘ Fin.succ) := by
refine ⟨fun h => ?_, fun h => by rw [map_succ', map_succ', h.1, h.2]⟩
have : x₁ 0 = x₂ 0 := by
rw [← mod_eq_of_lt (hx₁ _), ← map_mod, ← mod_eq_of_lt (hx₂ _), ← map_mod, h]
rw [map_succ, map_succ, this, add_right_inj, mul_eq_mul_right_iff] at h
exact ⟨this, h.resolve_right (pos_of_gt (hx₁ 0)).ne'⟩
#align behrend.map_eq_iff Behrend.map_eq_iff
theorem map_injOn : {x : Fin n → ℕ | ∀ i, x i < d}.InjOn (map d) := by
intro x₁ hx₁ x₂ hx₂ h
induction' n with n ih
· simp [eq_iff_true_of_subsingleton]
rw [forall_const] at ih
ext i
have x := (map_eq_iff hx₁ hx₂).1 h
refine Fin.cases x.1 (congr_fun <| ih (fun _ => ?_) (fun _ => ?_) x.2) i
· exact hx₁ _
· exact hx₂ _
#align behrend.map_inj_on Behrend.map_injOn
theorem map_le_of_mem_box (hx : x ∈ box n d) :
map (2 * d - 1) x ≤ ∑ i : Fin n, (d - 1) * (2 * d - 1) ^ (i : ℕ) :=
map_monotone (2 * d - 1) fun _ => Nat.le_sub_one_of_lt <| mem_box.1 hx _
#align behrend.map_le_of_mem_box Behrend.map_le_of_mem_box
nonrec theorem threeAPFree_sphere : ThreeAPFree (sphere n d k : Set (Fin n → ℕ)) := by
set f : (Fin n → ℕ) →+ EuclideanSpace ℝ (Fin n) :=
{ toFun := fun f => ((↑) : ℕ → ℝ) ∘ f
map_zero' := funext fun _ => cast_zero
map_add' := fun _ _ => funext fun _ => cast_add _ _ }
refine ThreeAPFree.of_image (AddMonoidHomClass.isAddFreimanHom f (Set.mapsTo_image _ _))
cast_injective.comp_left.injOn (Set.subset_univ _) ?_
refine (threeAPFree_sphere 0 (√↑k)).mono (Set.image_subset_iff.2 fun x => ?_)
rw [Set.mem_preimage, mem_sphere_zero_iff_norm]
exact norm_of_mem_sphere
#align behrend.add_salem_spencer_sphere Behrend.threeAPFree_sphere
theorem threeAPFree_image_sphere :
ThreeAPFree ((sphere n d k).image (map (2 * d - 1)) : Set ℕ) := by
rw [coe_image]
apply ThreeAPFree.image' (α := Fin n → ℕ) (β := ℕ) (s := sphere n d k) (map (2 * d - 1))
(map_injOn.mono _) threeAPFree_sphere
· rw [Set.add_subset_iff]
rintro a ha b hb i
have hai := mem_box.1 (sphere_subset_box ha) i
have hbi := mem_box.1 (sphere_subset_box hb) i
rw [lt_tsub_iff_right, ← succ_le_iff, two_mul]
exact (add_add_add_comm _ _ 1 1).trans_le (_root_.add_le_add hai hbi)
· exact x
#align behrend.add_salem_spencer_image_sphere Behrend.threeAPFree_image_sphere
theorem sum_sq_le_of_mem_box (hx : x ∈ box n d) : ∑ i : Fin n, x i ^ 2 ≤ n * (d - 1) ^ 2 := by
rw [mem_box] at hx
have : ∀ i, x i ^ 2 ≤ (d - 1) ^ 2 := fun i =>
Nat.pow_le_pow_left (Nat.le_sub_one_of_lt (hx i)) _
exact (sum_le_card_nsmul univ _ _ fun i _ => this i).trans (by rw [card_fin, smul_eq_mul])
#align behrend.sum_sq_le_of_mem_box Behrend.sum_sq_le_of_mem_box
theorem sum_eq : (∑ i : Fin n, d * (2 * d + 1) ^ (i : ℕ)) = ((2 * d + 1) ^ n - 1) / 2 := by
refine (Nat.div_eq_of_eq_mul_left zero_lt_two ?_).symm
rw [← sum_range fun i => d * (2 * d + 1) ^ (i : ℕ), ← mul_sum, mul_right_comm, mul_comm d, ←
geom_sum_mul_add, add_tsub_cancel_right, mul_comm]
#align behrend.sum_eq Behrend.sum_eq
theorem sum_lt : (∑ i : Fin n, d * (2 * d + 1) ^ (i : ℕ)) < (2 * d + 1) ^ n :=
sum_eq.trans_lt <| (Nat.div_le_self _ 2).trans_lt <| pred_lt (pow_pos (succ_pos _) _).ne'
#align behrend.sum_lt Behrend.sum_lt
theorem card_sphere_le_rothNumberNat (n d k : ℕ) :
(sphere n d k).card ≤ rothNumberNat ((2 * d - 1) ^ n) := by
cases n
· dsimp; refine (card_le_univ _).trans_eq ?_; rfl
cases d
· simp
apply threeAPFree_image_sphere.le_rothNumberNat _ _ (card_image_of_injOn _)
· intro; assumption
· simp only [subset_iff, mem_image, and_imp, forall_exists_index, mem_range,
forall_apply_eq_imp_iff₂, sphere, mem_filter]
rintro _ x hx _ rfl
exact (map_le_of_mem_box hx).trans_lt sum_lt
apply map_injOn.mono fun x => ?_
· intro; assumption
simp only [mem_coe, sphere, mem_filter, mem_box, and_imp, two_mul]
exact fun h _ i => (h i).trans_le le_self_add
#align behrend.card_sphere_le_roth_number_nat Behrend.card_sphere_le_rothNumberNat
/-!
### Optimization
Now that we know how to turn the integer points of any sphere into a 3AP-free set, we find a
sphere containing many integer points by the pigeonhole principle. This gives us an implicit bound
that we then optimize by tweaking the parameters. The (almost) optimal parameters are
`Behrend.nValue` and `Behrend.dValue`.
-/
theorem exists_large_sphere_aux (n d : ℕ) : ∃ k ∈ range (n * (d - 1) ^ 2 + 1),
(↑(d ^ n) / ((n * (d - 1) ^ 2 :) + 1) : ℝ) ≤ (sphere n d k).card := by
refine exists_le_card_fiber_of_nsmul_le_card_of_maps_to (fun x hx => ?_) nonempty_range_succ ?_
· rw [mem_range, Nat.lt_succ_iff]
exact sum_sq_le_of_mem_box hx
· rw [card_range, _root_.nsmul_eq_mul, mul_div_assoc', cast_add_one, mul_div_cancel_left₀,
card_box]
exact (cast_add_one_pos _).ne'
#align behrend.exists_large_sphere_aux Behrend.exists_large_sphere_aux
theorem exists_large_sphere (n d : ℕ) :
∃ k, ((d ^ n :) / (n * d ^ 2 :) : ℝ) ≤ (sphere n d k).card := by
obtain ⟨k, -, hk⟩ := exists_large_sphere_aux n d
refine ⟨k, ?_⟩
obtain rfl | hn := n.eq_zero_or_pos
· simp
obtain rfl | hd := d.eq_zero_or_pos
· simp
refine (div_le_div_of_nonneg_left ?_ ?_ ?_).trans hk
· exact cast_nonneg _
· exact cast_add_one_pos _
simp only [← le_sub_iff_add_le', cast_mul, ← mul_sub, cast_pow, cast_sub hd, sub_sq, one_pow,
cast_one, mul_one, sub_add, sub_sub_self]
apply one_le_mul_of_one_le_of_one_le
· rwa [one_le_cast]
rw [_root_.le_sub_iff_add_le]
set_option tactic.skipAssignedInstances false in norm_num
exact one_le_cast.2 hd
#align behrend.exists_large_sphere Behrend.exists_large_sphere
theorem bound_aux' (n d : ℕ) : ((d ^ n :) / (n * d ^ 2 :) : ℝ) ≤ rothNumberNat ((2 * d - 1) ^ n) :=
let ⟨_, h⟩ := exists_large_sphere n d
h.trans <| cast_le.2 <| card_sphere_le_rothNumberNat _ _ _
#align behrend.bound_aux' Behrend.bound_aux'
theorem bound_aux (hd : d ≠ 0) (hn : 2 ≤ n) :
(d ^ (n - 2 :) / n : ℝ) ≤ rothNumberNat ((2 * d - 1) ^ n) := by
convert bound_aux' n d using 1
rw [cast_mul, cast_pow, mul_comm, ← div_div, pow_sub₀ _ _ hn, ← div_eq_mul_inv, cast_pow]
rwa [cast_ne_zero]
#align behrend.bound_aux Behrend.bound_aux
open scoped Filter Topology
open Real
section NumericalBounds
theorem log_two_mul_two_le_sqrt_log_eight : log 2 * 2 ≤ √(log 8) := by
have : (8 : ℝ) = 2 ^ ((3 : ℕ) : ℝ) := by rw [rpow_natCast]; norm_num
rw [this, log_rpow zero_lt_two (3 : ℕ)]
apply le_sqrt_of_sq_le
rw [mul_pow, sq (log 2), mul_assoc, mul_comm]
refine mul_le_mul_of_nonneg_right ?_ (log_nonneg one_le_two)
rw [← le_div_iff]
on_goal 1 => apply log_two_lt_d9.le.trans
all_goals norm_num1
#align behrend.log_two_mul_two_le_sqrt_log_eight Behrend.log_two_mul_two_le_sqrt_log_eight
theorem two_div_one_sub_two_div_e_le_eight : 2 / (1 - 2 / exp 1) ≤ 8 := by
rw [div_le_iff, mul_sub, mul_one, mul_div_assoc', le_sub_comm, div_le_iff (exp_pos _)]
· have : 16 < 6 * (2.7182818283 : ℝ) := by norm_num
linarith [exp_one_gt_d9]
rw [sub_pos, div_lt_one] <;> exact exp_one_gt_d9.trans' (by norm_num)
#align behrend.two_div_one_sub_two_div_e_le_eight Behrend.two_div_one_sub_two_div_e_le_eight
theorem le_sqrt_log (hN : 4096 ≤ N) : log (2 / (1 - 2 / exp 1)) * (69 / 50) ≤ √(log ↑N) := by
have : (12 : ℕ) * log 2 ≤ log N := by
rw [← log_rpow zero_lt_two, rpow_natCast]
exact log_le_log (by positivity) (mod_cast hN)
refine (mul_le_mul_of_nonneg_right (log_le_log ?_ two_div_one_sub_two_div_e_le_eight) <| by
norm_num1).trans ?_
· refine div_pos zero_lt_two ?_
rw [sub_pos, div_lt_one (exp_pos _)]
exact exp_one_gt_d9.trans_le' (by norm_num1)
have l8 : log 8 = (3 : ℕ) * log 2 := by
rw [← log_rpow zero_lt_two, rpow_natCast]
norm_num
rw [l8]
apply le_sqrt_of_sq_le (le_trans _ this)
rw [mul_right_comm, mul_pow, sq (log 2), ← mul_assoc]
apply mul_le_mul_of_nonneg_right _ (log_nonneg one_le_two)
rw [← le_div_iff']
· exact log_two_lt_d9.le.trans (by norm_num1)
exact sq_pos_of_ne_zero (by norm_num1)
#align behrend.le_sqrt_log Behrend.le_sqrt_log
theorem exp_neg_two_mul_le {x : ℝ} (hx : 0 < x) : exp (-2 * x) < exp (2 - ⌈x⌉₊) / ⌈x⌉₊ := by
have h₁ := ceil_lt_add_one hx.le
have h₂ : 1 - x ≤ 2 - ⌈x⌉₊ := by linarith
calc
_ ≤ exp (1 - x) / (x + 1) := ?_
_ ≤ exp (2 - ⌈x⌉₊) / (x + 1) := by gcongr
_ < _ := by gcongr
rw [le_div_iff (add_pos hx zero_lt_one), ← le_div_iff' (exp_pos _), ← exp_sub, neg_mul,
sub_neg_eq_add, two_mul, sub_add_add_cancel, add_comm _ x]
exact le_trans (le_add_of_nonneg_right zero_le_one) (add_one_le_exp _)
#align behrend.exp_neg_two_mul_le Behrend.exp_neg_two_mul_le
theorem div_lt_floor {x : ℝ} (hx : 2 / (1 - 2 / exp 1) ≤ x) : x / exp 1 < (⌊x / 2⌋₊ : ℝ) := by
apply lt_of_le_of_lt _ (sub_one_lt_floor _)
have : 0 < 1 - 2 / exp 1 := by
rw [sub_pos, div_lt_one (exp_pos _)]
exact lt_of_le_of_lt (by norm_num) exp_one_gt_d9
rwa [le_sub_comm, div_eq_mul_one_div x, div_eq_mul_one_div x, ← mul_sub, div_sub', ←
div_eq_mul_one_div, mul_div_assoc', one_le_div, ← div_le_iff this]
· exact zero_lt_two
· exact two_ne_zero
#align behrend.div_lt_floor Behrend.div_lt_floor
theorem ceil_lt_mul {x : ℝ} (hx : 50 / 19 ≤ x) : (⌈x⌉₊ : ℝ) < 1.38 * x := by
refine (ceil_lt_add_one <| hx.trans' <| by norm_num).trans_le ?_
rw [← le_sub_iff_add_le', ← sub_one_mul]
have : (1.38 : ℝ) = 69 / 50 := by norm_num
rwa [this, show (69 / 50 - 1 : ℝ) = (50 / 19)⁻¹ by norm_num1, ←
div_eq_inv_mul, one_le_div]
norm_num1
#align behrend.ceil_lt_mul Behrend.ceil_lt_mul
end NumericalBounds
/-- The (almost) optimal value of `n` in `Behrend.bound_aux`. -/
noncomputable def nValue (N : ℕ) : ℕ :=
⌈√(log N)⌉₊
#align behrend.n_value Behrend.nValue
/-- The (almost) optimal value of `d` in `Behrend.bound_aux`. -/
noncomputable def dValue (N : ℕ) : ℕ := ⌊(N : ℝ) ^ (nValue N : ℝ)⁻¹ / 2⌋₊
#align behrend.d_value Behrend.dValue
theorem nValue_pos (hN : 2 ≤ N) : 0 < nValue N :=
ceil_pos.2 <| Real.sqrt_pos.2 <| log_pos <| one_lt_cast.2 <| hN
#align behrend.n_value_pos Behrend.nValue_pos
#noalign behrend.two_le_n_value
theorem three_le_nValue (hN : 64 ≤ N) : 3 ≤ nValue N := by
rw [nValue, ← lt_iff_add_one_le, lt_ceil, cast_two]
apply lt_sqrt_of_sq_lt
have : (2 : ℝ) ^ ((6 : ℕ) : ℝ) ≤ N := by
rw [rpow_natCast]
exact (cast_le.2 hN).trans' (by norm_num1)
apply lt_of_lt_of_le _ (log_le_log (rpow_pos_of_pos zero_lt_two _) this)
rw [log_rpow zero_lt_two, ← div_lt_iff']
· exact log_two_gt_d9.trans_le' (by norm_num1)
· norm_num1
#align behrend.three_le_n_value Behrend.three_le_nValue
theorem dValue_pos (hN₃ : 8 ≤ N) : 0 < dValue N := by
have hN₀ : 0 < (N : ℝ) := cast_pos.2 (succ_pos'.trans_le hN₃)
rw [dValue, floor_pos, ← log_le_log_iff zero_lt_one, log_one, log_div _ two_ne_zero, log_rpow hN₀,
inv_mul_eq_div, sub_nonneg, le_div_iff]
· have : (nValue N : ℝ) ≤ 2 * √(log N) := by
apply (ceil_lt_add_one <| sqrt_nonneg _).le.trans
rw [two_mul, add_le_add_iff_left]
apply le_sqrt_of_sq_le
rw [one_pow, le_log_iff_exp_le hN₀]
exact (exp_one_lt_d9.le.trans <| by norm_num).trans (cast_le.2 hN₃)
apply (mul_le_mul_of_nonneg_left this <| log_nonneg one_le_two).trans _
rw [← mul_assoc, ← le_div_iff (Real.sqrt_pos.2 <| log_pos <| one_lt_cast.2 _), div_sqrt]
· apply log_two_mul_two_le_sqrt_log_eight.trans
apply Real.sqrt_le_sqrt
exact log_le_log (by norm_num) (mod_cast hN₃)
exact hN₃.trans_lt' (by norm_num)
· exact cast_pos.2 (nValue_pos <| hN₃.trans' <| by norm_num)
· exact (rpow_pos_of_pos hN₀ _).ne'
· exact div_pos (rpow_pos_of_pos hN₀ _) zero_lt_two
#align behrend.d_value_pos Behrend.dValue_pos
theorem le_N (hN : 2 ≤ N) : (2 * dValue N - 1) ^ nValue N ≤ N := by
have : (2 * dValue N - 1) ^ nValue N ≤ (2 * dValue N) ^ nValue N :=
Nat.pow_le_pow_left (Nat.sub_le _ _) _
apply this.trans
suffices ((2 * dValue N) ^ nValue N : ℝ) ≤ N from mod_cast this
suffices i : (2 * dValue N : ℝ) ≤ (N : ℝ) ^ (nValue N : ℝ)⁻¹ by
rw [← rpow_natCast]
apply (rpow_le_rpow (mul_nonneg zero_le_two (cast_nonneg _)) i (cast_nonneg _)).trans
rw [← rpow_mul (cast_nonneg _), inv_mul_cancel, rpow_one]
rw [cast_ne_zero]
apply (nValue_pos hN).ne'
rw [← le_div_iff']
· exact floor_le (div_nonneg (rpow_nonneg (cast_nonneg _) _) zero_le_two)
apply zero_lt_two
set_option linter.uppercaseLean3 false in
#align behrend.le_N Behrend.le_N
theorem bound (hN : 4096 ≤ N) : (N : ℝ) ^ (nValue N : ℝ)⁻¹ / exp 1 < dValue N := by
apply div_lt_floor _
rw [← log_le_log_iff, log_rpow, mul_comm, ← div_eq_mul_inv]
· apply le_trans _ (div_le_div_of_nonneg_left _ _ (ceil_lt_mul _).le)
· rw [mul_comm, ← div_div, div_sqrt, le_div_iff]
· set_option tactic.skipAssignedInstances false in norm_num; exact le_sqrt_log hN
· norm_num1
· apply log_nonneg
rw [one_le_cast]
exact hN.trans' (by norm_num1)
· rw [cast_pos, lt_ceil, cast_zero, Real.sqrt_pos]
refine log_pos ?_
rw [one_lt_cast]
exact hN.trans_lt' (by norm_num1)
apply le_sqrt_of_sq_le
have : (12 : ℕ) * log 2 ≤ log N := by
rw [← log_rpow zero_lt_two, rpow_natCast]
exact log_le_log (by positivity) (mod_cast hN)
refine le_trans ?_ this
rw [← div_le_iff']
· exact log_two_gt_d9.le.trans' (by norm_num1)
· norm_num1
· rw [cast_pos]
exact hN.trans_lt' (by norm_num1)
· refine div_pos zero_lt_two ?_
rw [sub_pos, div_lt_one (exp_pos _)]
exact lt_of_le_of_lt (by norm_num1) exp_one_gt_d9
positivity
#align behrend.bound Behrend.bound
theorem roth_lower_bound_explicit (hN : 4096 ≤ N) :
(N : ℝ) * exp (-4 * √(log N)) < rothNumberNat N := by
let n := nValue N
have hn : 0 < (n : ℝ) := cast_pos.2 (nValue_pos <| hN.trans' <| by norm_num1)
have hd : 0 < dValue N := dValue_pos (hN.trans' <| by norm_num1)
have hN₀ : 0 < (N : ℝ) := cast_pos.2 (hN.trans' <| by norm_num1)
have hn₂ : 2 < n := three_le_nValue <| hN.trans' <| by norm_num1
have : (2 * dValue N - 1) ^ n ≤ N := le_N (hN.trans' <| by norm_num1)
calc
_ ≤ (N ^ (nValue N : ℝ)⁻¹ / rexp 1 : ℝ) ^ (n - 2) / n := ?_
_ < _ := by gcongr; exacts [(tsub_pos_of_lt hn₂).ne', bound hN]
_ ≤ rothNumberNat ((2 * dValue N - 1) ^ n) := bound_aux hd.ne' hn₂.le
_ ≤ rothNumberNat N := mod_cast rothNumberNat.mono this
rw [← rpow_natCast, div_rpow (rpow_nonneg hN₀.le _) (exp_pos _).le, ← rpow_mul hN₀.le,
inv_mul_eq_div, cast_sub hn₂.le, cast_two, same_sub_div hn.ne', exp_one_rpow,
div_div, rpow_sub hN₀, rpow_one, div_div, div_eq_mul_inv]
refine mul_le_mul_of_nonneg_left ?_ (cast_nonneg _)
rw [mul_inv, mul_inv, ← exp_neg, ← rpow_neg (cast_nonneg _), neg_sub, ← div_eq_mul_inv]
have : exp (-4 * √(log N)) = exp (-2 * √(log N)) * exp (-2 * √(log N)) := by
rw [← exp_add, ← add_mul]
norm_num
rw [this]
refine mul_le_mul ?_ (exp_neg_two_mul_le <| Real.sqrt_pos.2 <| log_pos ?_).le (exp_pos _).le <|
rpow_nonneg (cast_nonneg _) _
· rw [← le_log_iff_exp_le (rpow_pos_of_pos hN₀ _), log_rpow hN₀, ← le_div_iff, mul_div_assoc,
div_sqrt, neg_mul, neg_le_neg_iff, div_mul_eq_mul_div, div_le_iff hn]
· exact mul_le_mul_of_nonneg_left (le_ceil _) zero_le_two
refine Real.sqrt_pos.2 (log_pos ?_)
rw [one_lt_cast]
exact hN.trans_lt' (by norm_num1)
· rw [one_lt_cast]
exact hN.trans_lt' (by norm_num1)
#align behrend.roth_lower_bound_explicit Behrend.roth_lower_bound_explicit
theorem exp_four_lt : exp 4 < 64 := by
rw [show (64 : ℝ) = 2 ^ ((6 : ℕ) : ℝ) by rw [rpow_natCast]; norm_num1,
← lt_log_iff_exp_lt (rpow_pos_of_pos zero_lt_two _), log_rpow zero_lt_two, ← div_lt_iff']
· exact log_two_gt_d9.trans_le' (by norm_num1)
· norm_num
#align behrend.exp_four_lt Behrend.exp_four_lt
theorem four_zero_nine_six_lt_exp_sixteen : 4096 < exp 16 := by
rw [← log_lt_iff_lt_exp (show (0 : ℝ) < 4096 by norm_num), show (4096 : ℝ) = 2 ^ 12 by norm_cast,
← rpow_natCast, log_rpow zero_lt_two, cast_ofNat]
have : 12 * (0.6931471808 : ℝ) < 16 := by norm_num
linarith [log_two_lt_d9]
#align behrend.four_zero_nine_six_lt_exp_sixteen Behrend.four_zero_nine_six_lt_exp_sixteen
theorem lower_bound_le_one' (hN : 2 ≤ N) (hN' : N ≤ 4096) :
(N : ℝ) * exp (-4 * √(log N)) ≤ 1 := by
rw [← log_le_log_iff (mul_pos (cast_pos.2 (zero_lt_two.trans_le hN)) (exp_pos _)) zero_lt_one,
log_one, log_mul (cast_pos.2 (zero_lt_two.trans_le hN)).ne' (exp_pos _).ne', log_exp, neg_mul, ←
sub_eq_add_neg, sub_nonpos, ←
div_le_iff (Real.sqrt_pos.2 <| log_pos <| one_lt_cast.2 <| one_lt_two.trans_le hN), div_sqrt,
sqrt_le_left zero_le_four, log_le_iff_le_exp (cast_pos.2 (zero_lt_two.trans_le hN))]
norm_num1
apply le_trans _ four_zero_nine_six_lt_exp_sixteen.le
exact mod_cast hN'
#align behrend.lower_bound_le_one' Behrend.lower_bound_le_one'
theorem lower_bound_le_one (hN : 1 ≤ N) (hN' : N ≤ 4096) :
(N : ℝ) * exp (-4 * √(log N)) ≤ 1 := by
obtain rfl | hN := hN.eq_or_lt
· norm_num
· exact lower_bound_le_one' hN hN'
#align behrend.lower_bound_le_one Behrend.lower_bound_le_one
| Mathlib/Combinatorics/Additive/AP/Three/Behrend.lean | 547 | 553 | theorem roth_lower_bound : (N : ℝ) * exp (-4 * √(log N)) ≤ rothNumberNat N := by |
obtain rfl | hN := Nat.eq_zero_or_pos N
· norm_num
obtain h₁ | h₁ := le_or_lt 4096 N
· exact (roth_lower_bound_explicit h₁).le
· apply (lower_bound_le_one hN h₁.le).trans
simpa using rothNumberNat.monotone hN
|
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne, Kexing Ying
-/
import Mathlib.Probability.Notation
import Mathlib.Probability.Process.Stopping
#align_import probability.martingale.basic from "leanprover-community/mathlib"@"ba074af83b6cf54c3104e59402b39410ddbd6dca"
/-!
# Martingales
A family of functions `f : ι → Ω → E` is a martingale with respect to a filtration `ℱ` if every
`f i` is integrable, `f` is adapted with respect to `ℱ` and for all `i ≤ j`,
`μ[f j | ℱ i] =ᵐ[μ] f i`. On the other hand, `f : ι → Ω → E` is said to be a supermartingale
with respect to the filtration `ℱ` if `f i` is integrable, `f` is adapted with resepct to `ℱ`
and for all `i ≤ j`, `μ[f j | ℱ i] ≤ᵐ[μ] f i`. Finally, `f : ι → Ω → E` is said to be a
submartingale with respect to the filtration `ℱ` if `f i` is integrable, `f` is adapted with
resepct to `ℱ` and for all `i ≤ j`, `f i ≤ᵐ[μ] μ[f j | ℱ i]`.
The definitions of filtration and adapted can be found in `Probability.Process.Stopping`.
### Definitions
* `MeasureTheory.Martingale f ℱ μ`: `f` is a martingale with respect to filtration `ℱ` and
measure `μ`.
* `MeasureTheory.Supermartingale f ℱ μ`: `f` is a supermartingale with respect to
filtration `ℱ` and measure `μ`.
* `MeasureTheory.Submartingale f ℱ μ`: `f` is a submartingale with respect to filtration `ℱ` and
measure `μ`.
### Results
* `MeasureTheory.martingale_condexp f ℱ μ`: the sequence `fun i => μ[f | ℱ i, ℱ.le i])` is a
martingale with respect to `ℱ` and `μ`.
-/
open TopologicalSpace Filter
open scoped NNReal ENNReal MeasureTheory ProbabilityTheory
namespace MeasureTheory
variable {Ω E ι : Type*} [Preorder ι] {m0 : MeasurableSpace Ω} {μ : Measure Ω}
[NormedAddCommGroup E] [NormedSpace ℝ E] [CompleteSpace E] {f g : ι → Ω → E} {ℱ : Filtration ι m0}
/-- A family of functions `f : ι → Ω → E` is a martingale with respect to a filtration `ℱ` if `f`
is adapted with respect to `ℱ` and for all `i ≤ j`, `μ[f j | ℱ i] =ᵐ[μ] f i`. -/
def Martingale (f : ι → Ω → E) (ℱ : Filtration ι m0) (μ : Measure Ω) : Prop :=
Adapted ℱ f ∧ ∀ i j, i ≤ j → μ[f j|ℱ i] =ᵐ[μ] f i
#align measure_theory.martingale MeasureTheory.Martingale
/-- A family of integrable functions `f : ι → Ω → E` is a supermartingale with respect to a
filtration `ℱ` if `f` is adapted with respect to `ℱ` and for all `i ≤ j`,
`μ[f j | ℱ.le i] ≤ᵐ[μ] f i`. -/
def Supermartingale [LE E] (f : ι → Ω → E) (ℱ : Filtration ι m0) (μ : Measure Ω) : Prop :=
Adapted ℱ f ∧ (∀ i j, i ≤ j → μ[f j|ℱ i] ≤ᵐ[μ] f i) ∧ ∀ i, Integrable (f i) μ
#align measure_theory.supermartingale MeasureTheory.Supermartingale
/-- A family of integrable functions `f : ι → Ω → E` is a submartingale with respect to a
filtration `ℱ` if `f` is adapted with respect to `ℱ` and for all `i ≤ j`,
`f i ≤ᵐ[μ] μ[f j | ℱ.le i]`. -/
def Submartingale [LE E] (f : ι → Ω → E) (ℱ : Filtration ι m0) (μ : Measure Ω) : Prop :=
Adapted ℱ f ∧ (∀ i j, i ≤ j → f i ≤ᵐ[μ] μ[f j|ℱ i]) ∧ ∀ i, Integrable (f i) μ
#align measure_theory.submartingale MeasureTheory.Submartingale
theorem martingale_const (ℱ : Filtration ι m0) (μ : Measure Ω) [IsFiniteMeasure μ] (x : E) :
Martingale (fun _ _ => x) ℱ μ :=
⟨adapted_const ℱ _, fun i j _ => by rw [condexp_const (ℱ.le _)]⟩
#align measure_theory.martingale_const MeasureTheory.martingale_const
theorem martingale_const_fun [OrderBot ι] (ℱ : Filtration ι m0) (μ : Measure Ω) [IsFiniteMeasure μ]
{f : Ω → E} (hf : StronglyMeasurable[ℱ ⊥] f) (hfint : Integrable f μ) :
Martingale (fun _ => f) ℱ μ := by
refine ⟨fun i => hf.mono <| ℱ.mono bot_le, fun i j _ => ?_⟩
rw [condexp_of_stronglyMeasurable (ℱ.le _) (hf.mono <| ℱ.mono bot_le) hfint]
#align measure_theory.martingale_const_fun MeasureTheory.martingale_const_fun
variable (E)
theorem martingale_zero (ℱ : Filtration ι m0) (μ : Measure Ω) : Martingale (0 : ι → Ω → E) ℱ μ :=
⟨adapted_zero E ℱ, fun i j _ => by rw [Pi.zero_apply, condexp_zero]; simp⟩
#align measure_theory.martingale_zero MeasureTheory.martingale_zero
variable {E}
namespace Martingale
protected theorem adapted (hf : Martingale f ℱ μ) : Adapted ℱ f :=
hf.1
#align measure_theory.martingale.adapted MeasureTheory.Martingale.adapted
protected theorem stronglyMeasurable (hf : Martingale f ℱ μ) (i : ι) :
StronglyMeasurable[ℱ i] (f i) :=
hf.adapted i
#align measure_theory.martingale.strongly_measurable MeasureTheory.Martingale.stronglyMeasurable
theorem condexp_ae_eq (hf : Martingale f ℱ μ) {i j : ι} (hij : i ≤ j) : μ[f j|ℱ i] =ᵐ[μ] f i :=
hf.2 i j hij
#align measure_theory.martingale.condexp_ae_eq MeasureTheory.Martingale.condexp_ae_eq
protected theorem integrable (hf : Martingale f ℱ μ) (i : ι) : Integrable (f i) μ :=
integrable_condexp.congr (hf.condexp_ae_eq (le_refl i))
#align measure_theory.martingale.integrable MeasureTheory.Martingale.integrable
theorem setIntegral_eq [SigmaFiniteFiltration μ ℱ] (hf : Martingale f ℱ μ) {i j : ι} (hij : i ≤ j)
{s : Set Ω} (hs : MeasurableSet[ℱ i] s) : ∫ ω in s, f i ω ∂μ = ∫ ω in s, f j ω ∂μ := by
rw [← @setIntegral_condexp _ _ _ _ _ (ℱ i) m0 _ _ _ (ℱ.le i) _ (hf.integrable j) hs]
refine setIntegral_congr_ae (ℱ.le i s hs) ?_
filter_upwards [hf.2 i j hij] with _ heq _ using heq.symm
#align measure_theory.martingale.set_integral_eq MeasureTheory.Martingale.setIntegral_eq
@[deprecated (since := "2024-04-17")]
alias set_integral_eq := setIntegral_eq
theorem add (hf : Martingale f ℱ μ) (hg : Martingale g ℱ μ) : Martingale (f + g) ℱ μ := by
refine ⟨hf.adapted.add hg.adapted, fun i j hij => ?_⟩
exact (condexp_add (hf.integrable j) (hg.integrable j)).trans ((hf.2 i j hij).add (hg.2 i j hij))
#align measure_theory.martingale.add MeasureTheory.Martingale.add
theorem neg (hf : Martingale f ℱ μ) : Martingale (-f) ℱ μ :=
⟨hf.adapted.neg, fun i j hij => (condexp_neg (f j)).trans (hf.2 i j hij).neg⟩
#align measure_theory.martingale.neg MeasureTheory.Martingale.neg
theorem sub (hf : Martingale f ℱ μ) (hg : Martingale g ℱ μ) : Martingale (f - g) ℱ μ := by
rw [sub_eq_add_neg]; exact hf.add hg.neg
#align measure_theory.martingale.sub MeasureTheory.Martingale.sub
theorem smul (c : ℝ) (hf : Martingale f ℱ μ) : Martingale (c • f) ℱ μ := by
refine ⟨hf.adapted.smul c, fun i j hij => ?_⟩
refine (condexp_smul c (f j)).trans ((hf.2 i j hij).mono fun x hx => ?_)
simp only [Pi.smul_apply, hx]
#align measure_theory.martingale.smul MeasureTheory.Martingale.smul
theorem supermartingale [Preorder E] (hf : Martingale f ℱ μ) : Supermartingale f ℱ μ :=
⟨hf.1, fun i j hij => (hf.2 i j hij).le, fun i => hf.integrable i⟩
#align measure_theory.martingale.supermartingale MeasureTheory.Martingale.supermartingale
theorem submartingale [Preorder E] (hf : Martingale f ℱ μ) : Submartingale f ℱ μ :=
⟨hf.1, fun i j hij => (hf.2 i j hij).symm.le, fun i => hf.integrable i⟩
#align measure_theory.martingale.submartingale MeasureTheory.Martingale.submartingale
end Martingale
theorem martingale_iff [PartialOrder E] :
Martingale f ℱ μ ↔ Supermartingale f ℱ μ ∧ Submartingale f ℱ μ :=
⟨fun hf => ⟨hf.supermartingale, hf.submartingale⟩, fun ⟨hf₁, hf₂⟩ =>
⟨hf₁.1, fun i j hij => (hf₁.2.1 i j hij).antisymm (hf₂.2.1 i j hij)⟩⟩
#align measure_theory.martingale_iff MeasureTheory.martingale_iff
theorem martingale_condexp (f : Ω → E) (ℱ : Filtration ι m0) (μ : Measure Ω)
[SigmaFiniteFiltration μ ℱ] : Martingale (fun i => μ[f|ℱ i]) ℱ μ :=
⟨fun _ => stronglyMeasurable_condexp, fun _ j hij => condexp_condexp_of_le (ℱ.mono hij) (ℱ.le j)⟩
#align measure_theory.martingale_condexp MeasureTheory.martingale_condexp
namespace Supermartingale
protected theorem adapted [LE E] (hf : Supermartingale f ℱ μ) : Adapted ℱ f :=
hf.1
#align measure_theory.supermartingale.adapted MeasureTheory.Supermartingale.adapted
protected theorem stronglyMeasurable [LE E] (hf : Supermartingale f ℱ μ) (i : ι) :
StronglyMeasurable[ℱ i] (f i) :=
hf.adapted i
#align measure_theory.supermartingale.strongly_measurable MeasureTheory.Supermartingale.stronglyMeasurable
protected theorem integrable [LE E] (hf : Supermartingale f ℱ μ) (i : ι) : Integrable (f i) μ :=
hf.2.2 i
#align measure_theory.supermartingale.integrable MeasureTheory.Supermartingale.integrable
theorem condexp_ae_le [LE E] (hf : Supermartingale f ℱ μ) {i j : ι} (hij : i ≤ j) :
μ[f j|ℱ i] ≤ᵐ[μ] f i :=
hf.2.1 i j hij
#align measure_theory.supermartingale.condexp_ae_le MeasureTheory.Supermartingale.condexp_ae_le
theorem setIntegral_le [SigmaFiniteFiltration μ ℱ] {f : ι → Ω → ℝ} (hf : Supermartingale f ℱ μ)
{i j : ι} (hij : i ≤ j) {s : Set Ω} (hs : MeasurableSet[ℱ i] s) :
∫ ω in s, f j ω ∂μ ≤ ∫ ω in s, f i ω ∂μ := by
rw [← setIntegral_condexp (ℱ.le i) (hf.integrable j) hs]
refine setIntegral_mono_ae integrable_condexp.integrableOn (hf.integrable i).integrableOn ?_
filter_upwards [hf.2.1 i j hij] with _ heq using heq
#align measure_theory.supermartingale.set_integral_le MeasureTheory.Supermartingale.setIntegral_le
@[deprecated (since := "2024-04-17")]
alias set_integral_le := setIntegral_le
theorem add [Preorder E] [CovariantClass E E (· + ·) (· ≤ ·)] (hf : Supermartingale f ℱ μ)
(hg : Supermartingale g ℱ μ) : Supermartingale (f + g) ℱ μ := by
refine ⟨hf.1.add hg.1, fun i j hij => ?_, fun i => (hf.2.2 i).add (hg.2.2 i)⟩
refine (condexp_add (hf.integrable j) (hg.integrable j)).le.trans ?_
filter_upwards [hf.2.1 i j hij, hg.2.1 i j hij]
intros
refine add_le_add ?_ ?_ <;> assumption
#align measure_theory.supermartingale.add MeasureTheory.Supermartingale.add
theorem add_martingale [Preorder E] [CovariantClass E E (· + ·) (· ≤ ·)]
(hf : Supermartingale f ℱ μ) (hg : Martingale g ℱ μ) : Supermartingale (f + g) ℱ μ :=
hf.add hg.supermartingale
#align measure_theory.supermartingale.add_martingale MeasureTheory.Supermartingale.add_martingale
theorem neg [Preorder E] [CovariantClass E E (· + ·) (· ≤ ·)] (hf : Supermartingale f ℱ μ) :
Submartingale (-f) ℱ μ := by
refine ⟨hf.1.neg, fun i j hij => ?_, fun i => (hf.2.2 i).neg⟩
refine EventuallyLE.trans ?_ (condexp_neg (f j)).symm.le
filter_upwards [hf.2.1 i j hij] with _ _
simpa
#align measure_theory.supermartingale.neg MeasureTheory.Supermartingale.neg
end Supermartingale
namespace Submartingale
protected theorem adapted [LE E] (hf : Submartingale f ℱ μ) : Adapted ℱ f :=
hf.1
#align measure_theory.submartingale.adapted MeasureTheory.Submartingale.adapted
protected theorem stronglyMeasurable [LE E] (hf : Submartingale f ℱ μ) (i : ι) :
StronglyMeasurable[ℱ i] (f i) :=
hf.adapted i
#align measure_theory.submartingale.strongly_measurable MeasureTheory.Submartingale.stronglyMeasurable
protected theorem integrable [LE E] (hf : Submartingale f ℱ μ) (i : ι) : Integrable (f i) μ :=
hf.2.2 i
#align measure_theory.submartingale.integrable MeasureTheory.Submartingale.integrable
theorem ae_le_condexp [LE E] (hf : Submartingale f ℱ μ) {i j : ι} (hij : i ≤ j) :
f i ≤ᵐ[μ] μ[f j|ℱ i] :=
hf.2.1 i j hij
#align measure_theory.submartingale.ae_le_condexp MeasureTheory.Submartingale.ae_le_condexp
theorem add [Preorder E] [CovariantClass E E (· + ·) (· ≤ ·)] (hf : Submartingale f ℱ μ)
(hg : Submartingale g ℱ μ) : Submartingale (f + g) ℱ μ := by
refine ⟨hf.1.add hg.1, fun i j hij => ?_, fun i => (hf.2.2 i).add (hg.2.2 i)⟩
refine EventuallyLE.trans ?_ (condexp_add (hf.integrable j) (hg.integrable j)).symm.le
filter_upwards [hf.2.1 i j hij, hg.2.1 i j hij]
intros
refine add_le_add ?_ ?_ <;> assumption
#align measure_theory.submartingale.add MeasureTheory.Submartingale.add
theorem add_martingale [Preorder E] [CovariantClass E E (· + ·) (· ≤ ·)] (hf : Submartingale f ℱ μ)
(hg : Martingale g ℱ μ) : Submartingale (f + g) ℱ μ :=
hf.add hg.submartingale
#align measure_theory.submartingale.add_martingale MeasureTheory.Submartingale.add_martingale
theorem neg [Preorder E] [CovariantClass E E (· + ·) (· ≤ ·)] (hf : Submartingale f ℱ μ) :
Supermartingale (-f) ℱ μ := by
refine ⟨hf.1.neg, fun i j hij => (condexp_neg (f j)).le.trans ?_, fun i => (hf.2.2 i).neg⟩
filter_upwards [hf.2.1 i j hij] with _ _
simpa
#align measure_theory.submartingale.neg MeasureTheory.Submartingale.neg
/-- The converse of this lemma is `MeasureTheory.submartingale_of_setIntegral_le`. -/
theorem setIntegral_le [SigmaFiniteFiltration μ ℱ] {f : ι → Ω → ℝ} (hf : Submartingale f ℱ μ)
{i j : ι} (hij : i ≤ j) {s : Set Ω} (hs : MeasurableSet[ℱ i] s) :
∫ ω in s, f i ω ∂μ ≤ ∫ ω in s, f j ω ∂μ := by
rw [← neg_le_neg_iff, ← integral_neg, ← integral_neg]
exact Supermartingale.setIntegral_le hf.neg hij hs
#align measure_theory.submartingale.set_integral_le MeasureTheory.Submartingale.setIntegral_le
@[deprecated (since := "2024-04-17")]
alias set_integral_le := setIntegral_le
theorem sub_supermartingale [Preorder E] [CovariantClass E E (· + ·) (· ≤ ·)]
(hf : Submartingale f ℱ μ) (hg : Supermartingale g ℱ μ) : Submartingale (f - g) ℱ μ := by
rw [sub_eq_add_neg]; exact hf.add hg.neg
#align measure_theory.submartingale.sub_supermartingale MeasureTheory.Submartingale.sub_supermartingale
theorem sub_martingale [Preorder E] [CovariantClass E E (· + ·) (· ≤ ·)] (hf : Submartingale f ℱ μ)
(hg : Martingale g ℱ μ) : Submartingale (f - g) ℱ μ :=
hf.sub_supermartingale hg.supermartingale
#align measure_theory.submartingale.sub_martingale MeasureTheory.Submartingale.sub_martingale
protected theorem sup {f g : ι → Ω → ℝ} (hf : Submartingale f ℱ μ) (hg : Submartingale g ℱ μ) :
Submartingale (f ⊔ g) ℱ μ := by
refine ⟨fun i => @StronglyMeasurable.sup _ _ _ _ (ℱ i) _ _ _ (hf.adapted i) (hg.adapted i),
fun i j hij => ?_, fun i => Integrable.sup (hf.integrable _) (hg.integrable _)⟩
refine EventuallyLE.sup_le ?_ ?_
· exact EventuallyLE.trans (hf.2.1 i j hij)
(condexp_mono (hf.integrable _) (Integrable.sup (hf.integrable j) (hg.integrable j))
(eventually_of_forall fun x => le_max_left _ _))
· exact EventuallyLE.trans (hg.2.1 i j hij)
(condexp_mono (hg.integrable _) (Integrable.sup (hf.integrable j) (hg.integrable j))
(eventually_of_forall fun x => le_max_right _ _))
#align measure_theory.submartingale.sup MeasureTheory.Submartingale.sup
protected theorem pos {f : ι → Ω → ℝ} (hf : Submartingale f ℱ μ) : Submartingale (f⁺) ℱ μ :=
hf.sup (martingale_zero _ _ _).submartingale
#align measure_theory.submartingale.pos MeasureTheory.Submartingale.pos
end Submartingale
section Submartingale
theorem submartingale_of_setIntegral_le [IsFiniteMeasure μ] {f : ι → Ω → ℝ} (hadp : Adapted ℱ f)
(hint : ∀ i, Integrable (f i) μ) (hf : ∀ i j : ι,
i ≤ j → ∀ s : Set Ω, MeasurableSet[ℱ i] s → ∫ ω in s, f i ω ∂μ ≤ ∫ ω in s, f j ω ∂μ) :
Submartingale f ℱ μ := by
refine ⟨hadp, fun i j hij => ?_, hint⟩
suffices f i ≤ᵐ[μ.trim (ℱ.le i)] μ[f j|ℱ i] by exact ae_le_of_ae_le_trim this
suffices 0 ≤ᵐ[μ.trim (ℱ.le i)] μ[f j|ℱ i] - f i by
filter_upwards [this] with x hx
rwa [← sub_nonneg]
refine ae_nonneg_of_forall_setIntegral_nonneg
((integrable_condexp.sub (hint i)).trim _ (stronglyMeasurable_condexp.sub <| hadp i))
fun s hs _ => ?_
specialize hf i j hij s hs
rwa [← setIntegral_trim _ (stronglyMeasurable_condexp.sub <| hadp i) hs,
integral_sub' integrable_condexp.integrableOn (hint i).integrableOn, sub_nonneg,
setIntegral_condexp (ℱ.le i) (hint j) hs]
#align measure_theory.submartingale_of_set_integral_le MeasureTheory.submartingale_of_setIntegral_le
@[deprecated (since := "2024-04-17")]
alias submartingale_of_set_integral_le := submartingale_of_setIntegral_le
| Mathlib/Probability/Martingale/Basic.lean | 318 | 323 | theorem submartingale_of_condexp_sub_nonneg [IsFiniteMeasure μ] {f : ι → Ω → ℝ} (hadp : Adapted ℱ f)
(hint : ∀ i, Integrable (f i) μ) (hf : ∀ i j, i ≤ j → 0 ≤ᵐ[μ] μ[f j - f i|ℱ i]) :
Submartingale f ℱ μ := by |
refine ⟨hadp, fun i j hij => ?_, hint⟩
rw [← condexp_of_stronglyMeasurable (ℱ.le _) (hadp _) (hint _), ← eventually_sub_nonneg]
exact EventuallyLE.trans (hf i j hij) (condexp_sub (hint _) (hint _)).le
|
/-
Copyright (c) 2022 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth
-/
import Mathlib.Analysis.InnerProductSpace.Dual
import Mathlib.Analysis.InnerProductSpace.Orientation
import Mathlib.Data.Complex.Orientation
import Mathlib.Tactic.LinearCombination
#align_import analysis.inner_product_space.two_dim from "leanprover-community/mathlib"@"cd8fafa2fac98e1a67097e8a91ad9901cfde48af"
/-!
# Oriented two-dimensional real inner product spaces
This file defines constructions specific to the geometry of an oriented two-dimensional real inner
product space `E`.
## Main declarations
* `Orientation.areaForm`: an antisymmetric bilinear form `E →ₗ[ℝ] E →ₗ[ℝ] ℝ` (usual notation `ω`).
Morally, when `ω` is evaluated on two vectors, it gives the oriented area of the parallelogram
they span. (But mathlib does not yet have a construction of oriented area, and in fact the
construction of oriented area should pass through `ω`.)
* `Orientation.rightAngleRotation`: an isometric automorphism `E ≃ₗᵢ[ℝ] E` (usual notation `J`).
This automorphism squares to -1. In a later file, rotations (`Orientation.rotation`) are defined,
in such a way that this automorphism is equal to rotation by 90 degrees.
* `Orientation.basisRightAngleRotation`: for a nonzero vector `x` in `E`, the basis `![x, J x]`
for `E`.
* `Orientation.kahler`: a complex-valued real-bilinear map `E →ₗ[ℝ] E →ₗ[ℝ] ℂ`. Its real part is the
inner product and its imaginary part is `Orientation.areaForm`. For vectors `x` and `y` in `E`,
the complex number `o.kahler x y` has modulus `‖x‖ * ‖y‖`. In a later file, oriented angles
(`Orientation.oangle`) are defined, in such a way that the argument of `o.kahler x y` is the
oriented angle from `x` to `y`.
## Main results
* `Orientation.rightAngleRotation_rightAngleRotation`: the identity `J (J x) = - x`
* `Orientation.nonneg_inner_and_areaForm_eq_zero_iff_sameRay`: `x`, `y` are in the same ray, if
and only if `0 ≤ ⟪x, y⟫` and `ω x y = 0`
* `Orientation.kahler_mul`: the identity `o.kahler x a * o.kahler a y = ‖a‖ ^ 2 * o.kahler x y`
* `Complex.areaForm`, `Complex.rightAngleRotation`, `Complex.kahler`: the concrete
interpretations of `areaForm`, `rightAngleRotation`, `kahler` for the oriented real inner
product space `ℂ`
* `Orientation.areaForm_map_complex`, `Orientation.rightAngleRotation_map_complex`,
`Orientation.kahler_map_complex`: given an orientation-preserving isometry from `E` to `ℂ`,
expressions for `areaForm`, `rightAngleRotation`, `kahler` as the pullback of their concrete
interpretations on `ℂ`
## Implementation notes
Notation `ω` for `Orientation.areaForm` and `J` for `Orientation.rightAngleRotation` should be
defined locally in each file which uses them, since otherwise one would need a more cumbersome
notation which mentions the orientation explicitly (something like `ω[o]`). Write
```
local notation "ω" => o.areaForm
local notation "J" => o.rightAngleRotation
```
-/
noncomputable section
open scoped RealInnerProductSpace ComplexConjugate
open FiniteDimensional
lemma FiniteDimensional.of_fact_finrank_eq_two {K V : Type*} [DivisionRing K]
[AddCommGroup V] [Module K V] [Fact (finrank K V = 2)] : FiniteDimensional K V :=
.of_fact_finrank_eq_succ 1
attribute [local instance] FiniteDimensional.of_fact_finrank_eq_two
@[deprecated (since := "2024-02-02")]
alias FiniteDimensional.finiteDimensional_of_fact_finrank_eq_two :=
FiniteDimensional.of_fact_finrank_eq_two
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E] [Fact (finrank ℝ E = 2)]
(o : Orientation ℝ E (Fin 2))
namespace Orientation
/-- An antisymmetric bilinear form on an oriented real inner product space of dimension 2 (usual
notation `ω`). When evaluated on two vectors, it gives the oriented area of the parallelogram they
span. -/
irreducible_def areaForm : E →ₗ[ℝ] E →ₗ[ℝ] ℝ := by
let z : E [⋀^Fin 0]→ₗ[ℝ] ℝ ≃ₗ[ℝ] ℝ :=
AlternatingMap.constLinearEquivOfIsEmpty.symm
let y : E [⋀^Fin 1]→ₗ[ℝ] ℝ →ₗ[ℝ] E →ₗ[ℝ] ℝ :=
LinearMap.llcomp ℝ E (E [⋀^Fin 0]→ₗ[ℝ] ℝ) ℝ z ∘ₗ AlternatingMap.curryLeftLinearMap
exact y ∘ₗ AlternatingMap.curryLeftLinearMap (R' := ℝ) o.volumeForm
#align orientation.area_form Orientation.areaForm
local notation "ω" => o.areaForm
theorem areaForm_to_volumeForm (x y : E) : ω x y = o.volumeForm ![x, y] := by simp [areaForm]
#align orientation.area_form_to_volume_form Orientation.areaForm_to_volumeForm
@[simp]
theorem areaForm_apply_self (x : E) : ω x x = 0 := by
rw [areaForm_to_volumeForm]
refine o.volumeForm.map_eq_zero_of_eq ![x, x] ?_ (?_ : (0 : Fin 2) ≠ 1)
· simp
· norm_num
#align orientation.area_form_apply_self Orientation.areaForm_apply_self
theorem areaForm_swap (x y : E) : ω x y = -ω y x := by
simp only [areaForm_to_volumeForm]
convert o.volumeForm.map_swap ![y, x] (_ : (0 : Fin 2) ≠ 1)
· ext i
fin_cases i <;> rfl
· norm_num
#align orientation.area_form_swap Orientation.areaForm_swap
@[simp]
theorem areaForm_neg_orientation : (-o).areaForm = -o.areaForm := by
ext x y
simp [areaForm_to_volumeForm]
#align orientation.area_form_neg_orientation Orientation.areaForm_neg_orientation
/-- Continuous linear map version of `Orientation.areaForm`, useful for calculus. -/
def areaForm' : E →L[ℝ] E →L[ℝ] ℝ :=
LinearMap.toContinuousLinearMap
(↑(LinearMap.toContinuousLinearMap : (E →ₗ[ℝ] ℝ) ≃ₗ[ℝ] E →L[ℝ] ℝ) ∘ₗ o.areaForm)
#align orientation.area_form' Orientation.areaForm'
@[simp]
theorem areaForm'_apply (x : E) :
o.areaForm' x = LinearMap.toContinuousLinearMap (o.areaForm x) :=
rfl
#align orientation.area_form'_apply Orientation.areaForm'_apply
theorem abs_areaForm_le (x y : E) : |ω x y| ≤ ‖x‖ * ‖y‖ := by
simpa [areaForm_to_volumeForm, Fin.prod_univ_succ] using o.abs_volumeForm_apply_le ![x, y]
#align orientation.abs_area_form_le Orientation.abs_areaForm_le
theorem areaForm_le (x y : E) : ω x y ≤ ‖x‖ * ‖y‖ := by
simpa [areaForm_to_volumeForm, Fin.prod_univ_succ] using o.volumeForm_apply_le ![x, y]
#align orientation.area_form_le Orientation.areaForm_le
theorem abs_areaForm_of_orthogonal {x y : E} (h : ⟪x, y⟫ = 0) : |ω x y| = ‖x‖ * ‖y‖ := by
rw [o.areaForm_to_volumeForm, o.abs_volumeForm_apply_of_pairwise_orthogonal]
· simp [Fin.prod_univ_succ]
intro i j hij
fin_cases i <;> fin_cases j
· simp_all
· simpa using h
· simpa [real_inner_comm] using h
· simp_all
#align orientation.abs_area_form_of_orthogonal Orientation.abs_areaForm_of_orthogonal
theorem areaForm_map {F : Type*} [NormedAddCommGroup F] [InnerProductSpace ℝ F]
[hF : Fact (finrank ℝ F = 2)] (φ : E ≃ₗᵢ[ℝ] F) (x y : F) :
(Orientation.map (Fin 2) φ.toLinearEquiv o).areaForm x y =
o.areaForm (φ.symm x) (φ.symm y) := by
have : φ.symm ∘ ![x, y] = ![φ.symm x, φ.symm y] := by
ext i
fin_cases i <;> rfl
simp [areaForm_to_volumeForm, volumeForm_map, this]
#align orientation.area_form_map Orientation.areaForm_map
/-- The area form is invariant under pullback by a positively-oriented isometric automorphism. -/
theorem areaForm_comp_linearIsometryEquiv (φ : E ≃ₗᵢ[ℝ] E)
(hφ : 0 < LinearMap.det (φ.toLinearEquiv : E →ₗ[ℝ] E)) (x y : E) :
o.areaForm (φ x) (φ y) = o.areaForm x y := by
convert o.areaForm_map φ (φ x) (φ y)
· symm
rwa [← o.map_eq_iff_det_pos φ.toLinearEquiv] at hφ
rw [@Fact.out (finrank ℝ E = 2), Fintype.card_fin]
· simp
· simp
#align orientation.area_form_comp_linear_isometry_equiv Orientation.areaForm_comp_linearIsometryEquiv
/-- Auxiliary construction for `Orientation.rightAngleRotation`, rotation by 90 degrees in an
oriented real inner product space of dimension 2. -/
irreducible_def rightAngleRotationAux₁ : E →ₗ[ℝ] E :=
let to_dual : E ≃ₗ[ℝ] E →ₗ[ℝ] ℝ :=
(InnerProductSpace.toDual ℝ E).toLinearEquiv ≪≫ₗ LinearMap.toContinuousLinearMap.symm
↑to_dual.symm ∘ₗ ω
#align orientation.right_angle_rotation_aux₁ Orientation.rightAngleRotationAux₁
@[simp]
theorem inner_rightAngleRotationAux₁_left (x y : E) : ⟪o.rightAngleRotationAux₁ x, y⟫ = ω x y := by
-- Porting note: split `simp only` for greater proof control
simp only [rightAngleRotationAux₁, LinearEquiv.trans_symm, LinearIsometryEquiv.toLinearEquiv_symm,
LinearMap.coe_comp, LinearEquiv.coe_coe, Function.comp_apply, LinearEquiv.trans_apply,
LinearIsometryEquiv.coe_toLinearEquiv]
rw [InnerProductSpace.toDual_symm_apply]
norm_cast
#align orientation.inner_right_angle_rotation_aux₁_left Orientation.inner_rightAngleRotationAux₁_left
@[simp]
theorem inner_rightAngleRotationAux₁_right (x y : E) :
⟪x, o.rightAngleRotationAux₁ y⟫ = -ω x y := by
rw [real_inner_comm]
simp [o.areaForm_swap y x]
#align orientation.inner_right_angle_rotation_aux₁_right Orientation.inner_rightAngleRotationAux₁_right
/-- Auxiliary construction for `Orientation.rightAngleRotation`, rotation by 90 degrees in an
oriented real inner product space of dimension 2. -/
def rightAngleRotationAux₂ : E →ₗᵢ[ℝ] E :=
{ o.rightAngleRotationAux₁ with
norm_map' := fun x => by
dsimp
refine le_antisymm ?_ ?_
· cases' eq_or_lt_of_le (norm_nonneg (o.rightAngleRotationAux₁ x)) with h h
· rw [← h]
positivity
refine le_of_mul_le_mul_right ?_ h
rw [← real_inner_self_eq_norm_mul_norm, o.inner_rightAngleRotationAux₁_left]
exact o.areaForm_le x (o.rightAngleRotationAux₁ x)
· let K : Submodule ℝ E := ℝ ∙ x
have : Nontrivial Kᗮ := by
apply @FiniteDimensional.nontrivial_of_finrank_pos ℝ
have : finrank ℝ K ≤ Finset.card {x} := by
rw [← Set.toFinset_singleton]
exact finrank_span_le_card ({x} : Set E)
have : Finset.card {x} = 1 := Finset.card_singleton x
have : finrank ℝ K + finrank ℝ Kᗮ = finrank ℝ E := K.finrank_add_finrank_orthogonal
have : finrank ℝ E = 2 := Fact.out
linarith
obtain ⟨w, hw₀⟩ : ∃ w : Kᗮ, w ≠ 0 := exists_ne 0
have hw' : ⟪x, (w : E)⟫ = 0 := Submodule.mem_orthogonal_singleton_iff_inner_right.mp w.2
have hw : (w : E) ≠ 0 := fun h => hw₀ (Submodule.coe_eq_zero.mp h)
refine le_of_mul_le_mul_right ?_ (by rwa [norm_pos_iff] : 0 < ‖(w : E)‖)
rw [← o.abs_areaForm_of_orthogonal hw']
rw [← o.inner_rightAngleRotationAux₁_left x w]
exact abs_real_inner_le_norm (o.rightAngleRotationAux₁ x) w }
#align orientation.right_angle_rotation_aux₂ Orientation.rightAngleRotationAux₂
@[simp]
theorem rightAngleRotationAux₁_rightAngleRotationAux₁ (x : E) :
o.rightAngleRotationAux₁ (o.rightAngleRotationAux₁ x) = -x := by
apply ext_inner_left ℝ
intro y
have : ⟪o.rightAngleRotationAux₁ y, o.rightAngleRotationAux₁ x⟫ = ⟪y, x⟫ :=
LinearIsometry.inner_map_map o.rightAngleRotationAux₂ y x
rw [o.inner_rightAngleRotationAux₁_right, ← o.inner_rightAngleRotationAux₁_left, this,
inner_neg_right]
#align orientation.right_angle_rotation_aux₁_right_angle_rotation_aux₁ Orientation.rightAngleRotationAux₁_rightAngleRotationAux₁
/-- An isometric automorphism of an oriented real inner product space of dimension 2 (usual notation
`J`). This automorphism squares to -1. We will define rotations in such a way that this
automorphism is equal to rotation by 90 degrees. -/
irreducible_def rightAngleRotation : E ≃ₗᵢ[ℝ] E :=
LinearIsometryEquiv.ofLinearIsometry o.rightAngleRotationAux₂ (-o.rightAngleRotationAux₁)
(by ext; simp [rightAngleRotationAux₂]) (by ext; simp [rightAngleRotationAux₂])
#align orientation.right_angle_rotation Orientation.rightAngleRotation
local notation "J" => o.rightAngleRotation
@[simp]
theorem inner_rightAngleRotation_left (x y : E) : ⟪J x, y⟫ = ω x y := by
rw [rightAngleRotation]
exact o.inner_rightAngleRotationAux₁_left x y
#align orientation.inner_right_angle_rotation_left Orientation.inner_rightAngleRotation_left
@[simp]
theorem inner_rightAngleRotation_right (x y : E) : ⟪x, J y⟫ = -ω x y := by
rw [rightAngleRotation]
exact o.inner_rightAngleRotationAux₁_right x y
#align orientation.inner_right_angle_rotation_right Orientation.inner_rightAngleRotation_right
@[simp]
theorem rightAngleRotation_rightAngleRotation (x : E) : J (J x) = -x := by
rw [rightAngleRotation]
exact o.rightAngleRotationAux₁_rightAngleRotationAux₁ x
#align orientation.right_angle_rotation_right_angle_rotation Orientation.rightAngleRotation_rightAngleRotation
@[simp]
theorem rightAngleRotation_symm :
LinearIsometryEquiv.symm J = LinearIsometryEquiv.trans J (LinearIsometryEquiv.neg ℝ) := by
rw [rightAngleRotation]
exact LinearIsometryEquiv.toLinearIsometry_injective rfl
#align orientation.right_angle_rotation_symm Orientation.rightAngleRotation_symm
-- @[simp] -- Porting note (#10618): simp already proves this
theorem inner_rightAngleRotation_self (x : E) : ⟪J x, x⟫ = 0 := by simp
#align orientation.inner_right_angle_rotation_self Orientation.inner_rightAngleRotation_self
theorem inner_rightAngleRotation_swap (x y : E) : ⟪x, J y⟫ = -⟪J x, y⟫ := by simp
#align orientation.inner_right_angle_rotation_swap Orientation.inner_rightAngleRotation_swap
theorem inner_rightAngleRotation_swap' (x y : E) : ⟪J x, y⟫ = -⟪x, J y⟫ := by
simp [o.inner_rightAngleRotation_swap x y]
#align orientation.inner_right_angle_rotation_swap' Orientation.inner_rightAngleRotation_swap'
theorem inner_comp_rightAngleRotation (x y : E) : ⟪J x, J y⟫ = ⟪x, y⟫ :=
LinearIsometryEquiv.inner_map_map J x y
#align orientation.inner_comp_right_angle_rotation Orientation.inner_comp_rightAngleRotation
@[simp]
theorem areaForm_rightAngleRotation_left (x y : E) : ω (J x) y = -⟪x, y⟫ := by
rw [← o.inner_comp_rightAngleRotation, o.inner_rightAngleRotation_right, neg_neg]
#align orientation.area_form_right_angle_rotation_left Orientation.areaForm_rightAngleRotation_left
@[simp]
theorem areaForm_rightAngleRotation_right (x y : E) : ω x (J y) = ⟪x, y⟫ := by
rw [← o.inner_rightAngleRotation_left, o.inner_comp_rightAngleRotation]
#align orientation.area_form_right_angle_rotation_right Orientation.areaForm_rightAngleRotation_right
-- @[simp] -- Porting note (#10618): simp already proves this
theorem areaForm_comp_rightAngleRotation (x y : E) : ω (J x) (J y) = ω x y := by simp
#align orientation.area_form_comp_right_angle_rotation Orientation.areaForm_comp_rightAngleRotation
@[simp]
theorem rightAngleRotation_trans_rightAngleRotation :
LinearIsometryEquiv.trans J J = LinearIsometryEquiv.neg ℝ := by ext; simp
#align orientation.right_angle_rotation_trans_right_angle_rotation Orientation.rightAngleRotation_trans_rightAngleRotation
theorem rightAngleRotation_neg_orientation (x : E) :
(-o).rightAngleRotation x = -o.rightAngleRotation x := by
apply ext_inner_right ℝ
intro y
rw [inner_rightAngleRotation_left]
simp
#align orientation.right_angle_rotation_neg_orientation Orientation.rightAngleRotation_neg_orientation
@[simp]
theorem rightAngleRotation_trans_neg_orientation :
(-o).rightAngleRotation = o.rightAngleRotation.trans (LinearIsometryEquiv.neg ℝ) :=
LinearIsometryEquiv.ext <| o.rightAngleRotation_neg_orientation
#align orientation.right_angle_rotation_trans_neg_orientation Orientation.rightAngleRotation_trans_neg_orientation
theorem rightAngleRotation_map {F : Type*} [NormedAddCommGroup F] [InnerProductSpace ℝ F]
[hF : Fact (finrank ℝ F = 2)] (φ : E ≃ₗᵢ[ℝ] F) (x : F) :
(Orientation.map (Fin 2) φ.toLinearEquiv o).rightAngleRotation x =
φ (o.rightAngleRotation (φ.symm x)) := by
apply ext_inner_right ℝ
intro y
rw [inner_rightAngleRotation_left]
trans ⟪J (φ.symm x), φ.symm y⟫
· simp [o.areaForm_map]
trans ⟪φ (J (φ.symm x)), φ (φ.symm y)⟫
· rw [φ.inner_map_map]
· simp
#align orientation.right_angle_rotation_map Orientation.rightAngleRotation_map
/-- `J` commutes with any positively-oriented isometric automorphism. -/
theorem linearIsometryEquiv_comp_rightAngleRotation (φ : E ≃ₗᵢ[ℝ] E)
(hφ : 0 < LinearMap.det (φ.toLinearEquiv : E →ₗ[ℝ] E)) (x : E) : φ (J x) = J (φ x) := by
convert (o.rightAngleRotation_map φ (φ x)).symm
· simp
· symm
rwa [← o.map_eq_iff_det_pos φ.toLinearEquiv] at hφ
rw [@Fact.out (finrank ℝ E = 2), Fintype.card_fin]
#align orientation.linear_isometry_equiv_comp_right_angle_rotation Orientation.linearIsometryEquiv_comp_rightAngleRotation
theorem rightAngleRotation_map' {F : Type*} [NormedAddCommGroup F] [InnerProductSpace ℝ F]
[Fact (finrank ℝ F = 2)] (φ : E ≃ₗᵢ[ℝ] F) :
(Orientation.map (Fin 2) φ.toLinearEquiv o).rightAngleRotation =
(φ.symm.trans o.rightAngleRotation).trans φ :=
LinearIsometryEquiv.ext <| o.rightAngleRotation_map φ
#align orientation.right_angle_rotation_map' Orientation.rightAngleRotation_map'
/-- `J` commutes with any positively-oriented isometric automorphism. -/
theorem linearIsometryEquiv_comp_rightAngleRotation' (φ : E ≃ₗᵢ[ℝ] E)
(hφ : 0 < LinearMap.det (φ.toLinearEquiv : E →ₗ[ℝ] E)) :
LinearIsometryEquiv.trans J φ = φ.trans J :=
LinearIsometryEquiv.ext <| o.linearIsometryEquiv_comp_rightAngleRotation φ hφ
#align orientation.linear_isometry_equiv_comp_right_angle_rotation' Orientation.linearIsometryEquiv_comp_rightAngleRotation'
/-- For a nonzero vector `x` in an oriented two-dimensional real inner product space `E`,
`![x, J x]` forms an (orthogonal) basis for `E`. -/
def basisRightAngleRotation (x : E) (hx : x ≠ 0) : Basis (Fin 2) ℝ E :=
@basisOfLinearIndependentOfCardEqFinrank ℝ _ _ _ _ _ _ _ ![x, J x]
(linearIndependent_of_ne_zero_of_inner_eq_zero (fun i => by fin_cases i <;> simp [hx])
(by
intro i j hij
fin_cases i <;> fin_cases j <;> simp_all))
(@Fact.out (finrank ℝ E = 2)).symm
#align orientation.basis_right_angle_rotation Orientation.basisRightAngleRotation
@[simp]
theorem coe_basisRightAngleRotation (x : E) (hx : x ≠ 0) :
⇑(o.basisRightAngleRotation x hx) = ![x, J x] :=
coe_basisOfLinearIndependentOfCardEqFinrank _ _
#align orientation.coe_basis_right_angle_rotation Orientation.coe_basisRightAngleRotation
/-- For vectors `a x y : E`, the identity `⟪a, x⟫ * ⟪a, y⟫ + ω a x * ω a y = ‖a‖ ^ 2 * ⟪x, y⟫`. (See
`Orientation.inner_mul_inner_add_areaForm_mul_areaForm` for the "applied" form.)-/
| Mathlib/Analysis/InnerProductSpace/TwoDim.lean | 391 | 407 | theorem inner_mul_inner_add_areaForm_mul_areaForm' (a x : E) :
⟪a, x⟫ • innerₛₗ ℝ a + ω a x • ω a = ‖a‖ ^ 2 • innerₛₗ ℝ x := by |
by_cases ha : a = 0
· simp [ha]
apply (o.basisRightAngleRotation a ha).ext
intro i
fin_cases i
· simp only [Fin.mk_zero, coe_basisRightAngleRotation, Matrix.cons_val_zero, LinearMap.add_apply,
LinearMap.smul_apply, innerₛₗ_apply, real_inner_self_eq_norm_sq, smul_eq_mul,
areaForm_apply_self, mul_zero, add_zero, Real.rpow_two, real_inner_comm]
ring
· simp only [Fin.mk_one, coe_basisRightAngleRotation, Matrix.cons_val_one, Matrix.head_cons,
LinearMap.add_apply, LinearMap.smul_apply, innerₛₗ_apply, inner_rightAngleRotation_right,
areaForm_apply_self, neg_zero, smul_eq_mul, mul_zero, areaForm_rightAngleRotation_right,
real_inner_self_eq_norm_sq, zero_add, Real.rpow_two, mul_neg]
rw [o.areaForm_swap]
ring
|
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Yury Kudryashov, Sébastien Gouëzel, Rémy Degenne
-/
import Mathlib.MeasureTheory.Function.SimpleFuncDenseLp
#align_import measure_theory.integral.set_to_l1 from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Extension of a linear function from indicators to L1
Let `T : Set α → E →L[ℝ] F` be additive for measurable sets with finite measure, in the sense that
for `s, t` two such sets, `s ∩ t = ∅ → T (s ∪ t) = T s + T t`. `T` is akin to a bilinear map on
`Set α × E`, or a linear map on indicator functions.
This file constructs an extension of `T` to integrable simple functions, which are finite sums of
indicators of measurable sets with finite measure, then to integrable functions, which are limits of
integrable simple functions.
The main result is a continuous linear map `(α →₁[μ] E) →L[ℝ] F`. This extension process is used to
define the Bochner integral in the `MeasureTheory.Integral.Bochner` file and the conditional
expectation of an integrable function in `MeasureTheory.Function.ConditionalExpectation`.
## Main Definitions
- `FinMeasAdditive μ T`: the property that `T` is additive on measurable sets with finite measure.
For two such sets, `s ∩ t = ∅ → T (s ∪ t) = T s + T t`.
- `DominatedFinMeasAdditive μ T C`: `FinMeasAdditive μ T ∧ ∀ s, ‖T s‖ ≤ C * (μ s).toReal`.
This is the property needed to perform the extension from indicators to L1.
- `setToL1 (hT : DominatedFinMeasAdditive μ T C) : (α →₁[μ] E) →L[ℝ] F`: the extension of `T`
from indicators to L1.
- `setToFun μ T (hT : DominatedFinMeasAdditive μ T C) (f : α → E) : F`: a version of the
extension which applies to functions (with value 0 if the function is not integrable).
## Properties
For most properties of `setToFun`, we provide two lemmas. One version uses hypotheses valid on
all sets, like `T = T'`, and a second version which uses a primed name uses hypotheses on
measurable sets with finite measure, like `∀ s, MeasurableSet s → μ s < ∞ → T s = T' s`.
The lemmas listed here don't show all hypotheses. Refer to the actual lemmas for details.
Linearity:
- `setToFun_zero_left : setToFun μ 0 hT f = 0`
- `setToFun_add_left : setToFun μ (T + T') _ f = setToFun μ T hT f + setToFun μ T' hT' f`
- `setToFun_smul_left : setToFun μ (fun s ↦ c • (T s)) (hT.smul c) f = c • setToFun μ T hT f`
- `setToFun_zero : setToFun μ T hT (0 : α → E) = 0`
- `setToFun_neg : setToFun μ T hT (-f) = - setToFun μ T hT f`
If `f` and `g` are integrable:
- `setToFun_add : setToFun μ T hT (f + g) = setToFun μ T hT f + setToFun μ T hT g`
- `setToFun_sub : setToFun μ T hT (f - g) = setToFun μ T hT f - setToFun μ T hT g`
If `T` is verifies `∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x`:
- `setToFun_smul : setToFun μ T hT (c • f) = c • setToFun μ T hT f`
Other:
- `setToFun_congr_ae (h : f =ᵐ[μ] g) : setToFun μ T hT f = setToFun μ T hT g`
- `setToFun_measure_zero (h : μ = 0) : setToFun μ T hT f = 0`
If the space is a `NormedLatticeAddCommGroup` and `T` is such that `0 ≤ T s x` for `0 ≤ x`, we
also prove order-related properties:
- `setToFun_mono_left (h : ∀ s x, T s x ≤ T' s x) : setToFun μ T hT f ≤ setToFun μ T' hT' f`
- `setToFun_nonneg (hf : 0 ≤ᵐ[μ] f) : 0 ≤ setToFun μ T hT f`
- `setToFun_mono (hfg : f ≤ᵐ[μ] g) : setToFun μ T hT f ≤ setToFun μ T hT g`
## Implementation notes
The starting object `T : Set α → E →L[ℝ] F` matters only through its restriction on measurable sets
with finite measure. Its value on other sets is ignored.
-/
noncomputable section
open scoped Classical Topology NNReal ENNReal MeasureTheory Pointwise
open Set Filter TopologicalSpace ENNReal EMetric
namespace MeasureTheory
variable {α E F F' G 𝕜 : Type*} {p : ℝ≥0∞} [NormedAddCommGroup E] [NormedSpace ℝ E]
[NormedAddCommGroup F] [NormedSpace ℝ F] [NormedAddCommGroup F'] [NormedSpace ℝ F']
[NormedAddCommGroup G] {m : MeasurableSpace α} {μ : Measure α}
local infixr:25 " →ₛ " => SimpleFunc
open Finset
section FinMeasAdditive
/-- A set function is `FinMeasAdditive` if its value on the union of two disjoint measurable
sets with finite measure is the sum of its values on each set. -/
def FinMeasAdditive {β} [AddMonoid β] {_ : MeasurableSpace α} (μ : Measure α) (T : Set α → β) :
Prop :=
∀ s t, MeasurableSet s → MeasurableSet t → μ s ≠ ∞ → μ t ≠ ∞ → s ∩ t = ∅ → T (s ∪ t) = T s + T t
#align measure_theory.fin_meas_additive MeasureTheory.FinMeasAdditive
namespace FinMeasAdditive
variable {β : Type*} [AddCommMonoid β] {T T' : Set α → β}
theorem zero : FinMeasAdditive μ (0 : Set α → β) := fun s t _ _ _ _ _ => by simp
#align measure_theory.fin_meas_additive.zero MeasureTheory.FinMeasAdditive.zero
theorem add (hT : FinMeasAdditive μ T) (hT' : FinMeasAdditive μ T') :
FinMeasAdditive μ (T + T') := by
intro s t hs ht hμs hμt hst
simp only [hT s t hs ht hμs hμt hst, hT' s t hs ht hμs hμt hst, Pi.add_apply]
abel
#align measure_theory.fin_meas_additive.add MeasureTheory.FinMeasAdditive.add
theorem smul [Monoid 𝕜] [DistribMulAction 𝕜 β] (hT : FinMeasAdditive μ T) (c : 𝕜) :
FinMeasAdditive μ fun s => c • T s := fun s t hs ht hμs hμt hst => by
simp [hT s t hs ht hμs hμt hst]
#align measure_theory.fin_meas_additive.smul MeasureTheory.FinMeasAdditive.smul
theorem of_eq_top_imp_eq_top {μ' : Measure α} (h : ∀ s, MeasurableSet s → μ s = ∞ → μ' s = ∞)
(hT : FinMeasAdditive μ T) : FinMeasAdditive μ' T := fun s t hs ht hμ's hμ't hst =>
hT s t hs ht (mt (h s hs) hμ's) (mt (h t ht) hμ't) hst
#align measure_theory.fin_meas_additive.of_eq_top_imp_eq_top MeasureTheory.FinMeasAdditive.of_eq_top_imp_eq_top
theorem of_smul_measure (c : ℝ≥0∞) (hc_ne_top : c ≠ ∞) (hT : FinMeasAdditive (c • μ) T) :
FinMeasAdditive μ T := by
refine of_eq_top_imp_eq_top (fun s _ hμs => ?_) hT
rw [Measure.smul_apply, smul_eq_mul, ENNReal.mul_eq_top] at hμs
simp only [hc_ne_top, or_false_iff, Ne, false_and_iff] at hμs
exact hμs.2
#align measure_theory.fin_meas_additive.of_smul_measure MeasureTheory.FinMeasAdditive.of_smul_measure
theorem smul_measure (c : ℝ≥0∞) (hc_ne_zero : c ≠ 0) (hT : FinMeasAdditive μ T) :
FinMeasAdditive (c • μ) T := by
refine of_eq_top_imp_eq_top (fun s _ hμs => ?_) hT
rw [Measure.smul_apply, smul_eq_mul, ENNReal.mul_eq_top]
simp only [hc_ne_zero, true_and_iff, Ne, not_false_iff]
exact Or.inl hμs
#align measure_theory.fin_meas_additive.smul_measure MeasureTheory.FinMeasAdditive.smul_measure
theorem smul_measure_iff (c : ℝ≥0∞) (hc_ne_zero : c ≠ 0) (hc_ne_top : c ≠ ∞) :
FinMeasAdditive (c • μ) T ↔ FinMeasAdditive μ T :=
⟨fun hT => of_smul_measure c hc_ne_top hT, fun hT => smul_measure c hc_ne_zero hT⟩
#align measure_theory.fin_meas_additive.smul_measure_iff MeasureTheory.FinMeasAdditive.smul_measure_iff
theorem map_empty_eq_zero {β} [AddCancelMonoid β] {T : Set α → β} (hT : FinMeasAdditive μ T) :
T ∅ = 0 := by
have h_empty : μ ∅ ≠ ∞ := (measure_empty.le.trans_lt ENNReal.coe_lt_top).ne
specialize hT ∅ ∅ MeasurableSet.empty MeasurableSet.empty h_empty h_empty (Set.inter_empty ∅)
rw [Set.union_empty] at hT
nth_rw 1 [← add_zero (T ∅)] at hT
exact (add_left_cancel hT).symm
#align measure_theory.fin_meas_additive.map_empty_eq_zero MeasureTheory.FinMeasAdditive.map_empty_eq_zero
theorem map_iUnion_fin_meas_set_eq_sum (T : Set α → β) (T_empty : T ∅ = 0)
(h_add : FinMeasAdditive μ T) {ι} (S : ι → Set α) (sι : Finset ι)
(hS_meas : ∀ i, MeasurableSet (S i)) (hSp : ∀ i ∈ sι, μ (S i) ≠ ∞)
(h_disj : ∀ᵉ (i ∈ sι) (j ∈ sι), i ≠ j → Disjoint (S i) (S j)) :
T (⋃ i ∈ sι, S i) = ∑ i ∈ sι, T (S i) := by
revert hSp h_disj
refine Finset.induction_on sι ?_ ?_
· simp only [Finset.not_mem_empty, IsEmpty.forall_iff, iUnion_false, iUnion_empty, sum_empty,
forall₂_true_iff, imp_true_iff, forall_true_left, not_false_iff, T_empty]
intro a s has h hps h_disj
rw [Finset.sum_insert has, ← h]
swap; · exact fun i hi => hps i (Finset.mem_insert_of_mem hi)
swap;
· exact fun i hi j hj hij =>
h_disj i (Finset.mem_insert_of_mem hi) j (Finset.mem_insert_of_mem hj) hij
rw [←
h_add (S a) (⋃ i ∈ s, S i) (hS_meas a) (measurableSet_biUnion _ fun i _ => hS_meas i)
(hps a (Finset.mem_insert_self a s))]
· congr; convert Finset.iSup_insert a s S
· exact
((measure_biUnion_finset_le _ _).trans_lt <|
ENNReal.sum_lt_top fun i hi => hps i <| Finset.mem_insert_of_mem hi).ne
· simp_rw [Set.inter_iUnion]
refine iUnion_eq_empty.mpr fun i => iUnion_eq_empty.mpr fun hi => ?_
rw [← Set.disjoint_iff_inter_eq_empty]
refine h_disj a (Finset.mem_insert_self a s) i (Finset.mem_insert_of_mem hi) fun hai => ?_
rw [← hai] at hi
exact has hi
#align measure_theory.fin_meas_additive.map_Union_fin_meas_set_eq_sum MeasureTheory.FinMeasAdditive.map_iUnion_fin_meas_set_eq_sum
end FinMeasAdditive
/-- A `FinMeasAdditive` set function whose norm on every set is less than the measure of the
set (up to a multiplicative constant). -/
def DominatedFinMeasAdditive {β} [SeminormedAddCommGroup β] {_ : MeasurableSpace α} (μ : Measure α)
(T : Set α → β) (C : ℝ) : Prop :=
FinMeasAdditive μ T ∧ ∀ s, MeasurableSet s → μ s < ∞ → ‖T s‖ ≤ C * (μ s).toReal
#align measure_theory.dominated_fin_meas_additive MeasureTheory.DominatedFinMeasAdditive
namespace DominatedFinMeasAdditive
variable {β : Type*} [SeminormedAddCommGroup β] {T T' : Set α → β} {C C' : ℝ}
theorem zero {m : MeasurableSpace α} (μ : Measure α) (hC : 0 ≤ C) :
DominatedFinMeasAdditive μ (0 : Set α → β) C := by
refine ⟨FinMeasAdditive.zero, fun s _ _ => ?_⟩
rw [Pi.zero_apply, norm_zero]
exact mul_nonneg hC toReal_nonneg
#align measure_theory.dominated_fin_meas_additive.zero MeasureTheory.DominatedFinMeasAdditive.zero
theorem eq_zero_of_measure_zero {β : Type*} [NormedAddCommGroup β] {T : Set α → β} {C : ℝ}
(hT : DominatedFinMeasAdditive μ T C) {s : Set α} (hs : MeasurableSet s) (hs_zero : μ s = 0) :
T s = 0 := by
refine norm_eq_zero.mp ?_
refine ((hT.2 s hs (by simp [hs_zero])).trans (le_of_eq ?_)).antisymm (norm_nonneg _)
rw [hs_zero, ENNReal.zero_toReal, mul_zero]
#align measure_theory.dominated_fin_meas_additive.eq_zero_of_measure_zero MeasureTheory.DominatedFinMeasAdditive.eq_zero_of_measure_zero
theorem eq_zero {β : Type*} [NormedAddCommGroup β] {T : Set α → β} {C : ℝ} {m : MeasurableSpace α}
(hT : DominatedFinMeasAdditive (0 : Measure α) T C) {s : Set α} (hs : MeasurableSet s) :
T s = 0 :=
eq_zero_of_measure_zero hT hs (by simp only [Measure.coe_zero, Pi.zero_apply])
#align measure_theory.dominated_fin_meas_additive.eq_zero MeasureTheory.DominatedFinMeasAdditive.eq_zero
theorem add (hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') :
DominatedFinMeasAdditive μ (T + T') (C + C') := by
refine ⟨hT.1.add hT'.1, fun s hs hμs => ?_⟩
rw [Pi.add_apply, add_mul]
exact (norm_add_le _ _).trans (add_le_add (hT.2 s hs hμs) (hT'.2 s hs hμs))
#align measure_theory.dominated_fin_meas_additive.add MeasureTheory.DominatedFinMeasAdditive.add
theorem smul [NormedField 𝕜] [NormedSpace 𝕜 β] (hT : DominatedFinMeasAdditive μ T C) (c : 𝕜) :
DominatedFinMeasAdditive μ (fun s => c • T s) (‖c‖ * C) := by
refine ⟨hT.1.smul c, fun s hs hμs => ?_⟩
dsimp only
rw [norm_smul, mul_assoc]
exact mul_le_mul le_rfl (hT.2 s hs hμs) (norm_nonneg _) (norm_nonneg _)
#align measure_theory.dominated_fin_meas_additive.smul MeasureTheory.DominatedFinMeasAdditive.smul
theorem of_measure_le {μ' : Measure α} (h : μ ≤ μ') (hT : DominatedFinMeasAdditive μ T C)
(hC : 0 ≤ C) : DominatedFinMeasAdditive μ' T C := by
have h' : ∀ s, μ s = ∞ → μ' s = ∞ := fun s hs ↦ top_unique <| hs.symm.trans_le (h _)
refine ⟨hT.1.of_eq_top_imp_eq_top fun s _ ↦ h' s, fun s hs hμ's ↦ ?_⟩
have hμs : μ s < ∞ := (h s).trans_lt hμ's
calc
‖T s‖ ≤ C * (μ s).toReal := hT.2 s hs hμs
_ ≤ C * (μ' s).toReal := by gcongr; exacts [hμ's.ne, h _]
#align measure_theory.dominated_fin_meas_additive.of_measure_le MeasureTheory.DominatedFinMeasAdditive.of_measure_le
theorem add_measure_right {_ : MeasurableSpace α} (μ ν : Measure α)
(hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C) : DominatedFinMeasAdditive (μ + ν) T C :=
of_measure_le (Measure.le_add_right le_rfl) hT hC
#align measure_theory.dominated_fin_meas_additive.add_measure_right MeasureTheory.DominatedFinMeasAdditive.add_measure_right
theorem add_measure_left {_ : MeasurableSpace α} (μ ν : Measure α)
(hT : DominatedFinMeasAdditive ν T C) (hC : 0 ≤ C) : DominatedFinMeasAdditive (μ + ν) T C :=
of_measure_le (Measure.le_add_left le_rfl) hT hC
#align measure_theory.dominated_fin_meas_additive.add_measure_left MeasureTheory.DominatedFinMeasAdditive.add_measure_left
theorem of_smul_measure (c : ℝ≥0∞) (hc_ne_top : c ≠ ∞) (hT : DominatedFinMeasAdditive (c • μ) T C) :
DominatedFinMeasAdditive μ T (c.toReal * C) := by
have h : ∀ s, MeasurableSet s → c • μ s = ∞ → μ s = ∞ := by
intro s _ hcμs
simp only [hc_ne_top, Algebra.id.smul_eq_mul, ENNReal.mul_eq_top, or_false_iff, Ne,
false_and_iff] at hcμs
exact hcμs.2
refine ⟨hT.1.of_eq_top_imp_eq_top (μ := c • μ) h, fun s hs hμs => ?_⟩
have hcμs : c • μ s ≠ ∞ := mt (h s hs) hμs.ne
rw [smul_eq_mul] at hcμs
simp_rw [DominatedFinMeasAdditive, Measure.smul_apply, smul_eq_mul, toReal_mul] at hT
refine (hT.2 s hs hcμs.lt_top).trans (le_of_eq ?_)
ring
#align measure_theory.dominated_fin_meas_additive.of_smul_measure MeasureTheory.DominatedFinMeasAdditive.of_smul_measure
theorem of_measure_le_smul {μ' : Measure α} (c : ℝ≥0∞) (hc : c ≠ ∞) (h : μ ≤ c • μ')
(hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C) :
DominatedFinMeasAdditive μ' T (c.toReal * C) :=
(hT.of_measure_le h hC).of_smul_measure c hc
#align measure_theory.dominated_fin_meas_additive.of_measure_le_smul MeasureTheory.DominatedFinMeasAdditive.of_measure_le_smul
end DominatedFinMeasAdditive
end FinMeasAdditive
namespace SimpleFunc
/-- Extend `Set α → (F →L[ℝ] F')` to `(α →ₛ F) → F'`. -/
def setToSimpleFunc {_ : MeasurableSpace α} (T : Set α → F →L[ℝ] F') (f : α →ₛ F) : F' :=
∑ x ∈ f.range, T (f ⁻¹' {x}) x
#align measure_theory.simple_func.set_to_simple_func MeasureTheory.SimpleFunc.setToSimpleFunc
@[simp]
theorem setToSimpleFunc_zero {m : MeasurableSpace α} (f : α →ₛ F) :
setToSimpleFunc (0 : Set α → F →L[ℝ] F') f = 0 := by simp [setToSimpleFunc]
#align measure_theory.simple_func.set_to_simple_func_zero MeasureTheory.SimpleFunc.setToSimpleFunc_zero
theorem setToSimpleFunc_zero' {T : Set α → E →L[ℝ] F'}
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →ₛ E) (hf : Integrable f μ) :
setToSimpleFunc T f = 0 := by
simp_rw [setToSimpleFunc]
refine sum_eq_zero fun x _ => ?_
by_cases hx0 : x = 0
· simp [hx0]
rw [h_zero (f ⁻¹' ({x} : Set E)) (measurableSet_fiber _ _)
(measure_preimage_lt_top_of_integrable f hf hx0),
ContinuousLinearMap.zero_apply]
#align measure_theory.simple_func.set_to_simple_func_zero' MeasureTheory.SimpleFunc.setToSimpleFunc_zero'
@[simp]
theorem setToSimpleFunc_zero_apply {m : MeasurableSpace α} (T : Set α → F →L[ℝ] F') :
setToSimpleFunc T (0 : α →ₛ F) = 0 := by
cases isEmpty_or_nonempty α <;> simp [setToSimpleFunc]
#align measure_theory.simple_func.set_to_simple_func_zero_apply MeasureTheory.SimpleFunc.setToSimpleFunc_zero_apply
theorem setToSimpleFunc_eq_sum_filter {m : MeasurableSpace α} (T : Set α → F →L[ℝ] F')
(f : α →ₛ F) :
setToSimpleFunc T f = ∑ x ∈ f.range.filter fun x => x ≠ 0, (T (f ⁻¹' {x})) x := by
symm
refine sum_filter_of_ne fun x _ => mt fun hx0 => ?_
rw [hx0]
exact ContinuousLinearMap.map_zero _
#align measure_theory.simple_func.set_to_simple_func_eq_sum_filter MeasureTheory.SimpleFunc.setToSimpleFunc_eq_sum_filter
theorem map_setToSimpleFunc (T : Set α → F →L[ℝ] F') (h_add : FinMeasAdditive μ T) {f : α →ₛ G}
(hf : Integrable f μ) {g : G → F} (hg : g 0 = 0) :
(f.map g).setToSimpleFunc T = ∑ x ∈ f.range, T (f ⁻¹' {x}) (g x) := by
have T_empty : T ∅ = 0 := h_add.map_empty_eq_zero
have hfp : ∀ x ∈ f.range, x ≠ 0 → μ (f ⁻¹' {x}) ≠ ∞ := fun x _ hx0 =>
(measure_preimage_lt_top_of_integrable f hf hx0).ne
simp only [setToSimpleFunc, range_map]
refine Finset.sum_image' _ fun b hb => ?_
rcases mem_range.1 hb with ⟨a, rfl⟩
by_cases h0 : g (f a) = 0
· simp_rw [h0]
rw [ContinuousLinearMap.map_zero, Finset.sum_eq_zero fun x hx => ?_]
rw [mem_filter] at hx
rw [hx.2, ContinuousLinearMap.map_zero]
have h_left_eq :
T (map g f ⁻¹' {g (f a)}) (g (f a)) =
T (f ⁻¹' (f.range.filter fun b => g b = g (f a))) (g (f a)) := by
congr; rw [map_preimage_singleton]
rw [h_left_eq]
have h_left_eq' :
T (f ⁻¹' (filter (fun b : G => g b = g (f a)) f.range)) (g (f a)) =
T (⋃ y ∈ filter (fun b : G => g b = g (f a)) f.range, f ⁻¹' {y}) (g (f a)) := by
congr; rw [← Finset.set_biUnion_preimage_singleton]
rw [h_left_eq']
rw [h_add.map_iUnion_fin_meas_set_eq_sum T T_empty]
· simp only [sum_apply, ContinuousLinearMap.coe_sum']
refine Finset.sum_congr rfl fun x hx => ?_
rw [mem_filter] at hx
rw [hx.2]
· exact fun i => measurableSet_fiber _ _
· intro i hi
rw [mem_filter] at hi
refine hfp i hi.1 fun hi0 => ?_
rw [hi0, hg] at hi
exact h0 hi.2.symm
· intro i _j hi _ hij
rw [Set.disjoint_iff]
intro x hx
rw [Set.mem_inter_iff, Set.mem_preimage, Set.mem_preimage, Set.mem_singleton_iff,
Set.mem_singleton_iff] at hx
rw [← hx.1, ← hx.2] at hij
exact absurd rfl hij
#align measure_theory.simple_func.map_set_to_simple_func MeasureTheory.SimpleFunc.map_setToSimpleFunc
theorem setToSimpleFunc_congr' (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T) {f g : α →ₛ E}
(hf : Integrable f μ) (hg : Integrable g μ)
(h : Pairwise fun x y => T (f ⁻¹' {x} ∩ g ⁻¹' {y}) = 0) :
f.setToSimpleFunc T = g.setToSimpleFunc T :=
show ((pair f g).map Prod.fst).setToSimpleFunc T = ((pair f g).map Prod.snd).setToSimpleFunc T by
have h_pair : Integrable (f.pair g) μ := integrable_pair hf hg
rw [map_setToSimpleFunc T h_add h_pair Prod.fst_zero]
rw [map_setToSimpleFunc T h_add h_pair Prod.snd_zero]
refine Finset.sum_congr rfl fun p hp => ?_
rcases mem_range.1 hp with ⟨a, rfl⟩
by_cases eq : f a = g a
· dsimp only [pair_apply]; rw [eq]
· have : T (pair f g ⁻¹' {(f a, g a)}) = 0 := by
have h_eq : T ((⇑(f.pair g)) ⁻¹' {(f a, g a)}) = T (f ⁻¹' {f a} ∩ g ⁻¹' {g a}) := by
congr; rw [pair_preimage_singleton f g]
rw [h_eq]
exact h eq
simp only [this, ContinuousLinearMap.zero_apply, pair_apply]
#align measure_theory.simple_func.set_to_simple_func_congr' MeasureTheory.SimpleFunc.setToSimpleFunc_congr'
theorem setToSimpleFunc_congr (T : Set α → E →L[ℝ] F)
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) {f g : α →ₛ E}
(hf : Integrable f μ) (h : f =ᵐ[μ] g) : f.setToSimpleFunc T = g.setToSimpleFunc T := by
refine setToSimpleFunc_congr' T h_add hf ((integrable_congr h).mp hf) ?_
refine fun x y hxy => h_zero _ ((measurableSet_fiber f x).inter (measurableSet_fiber g y)) ?_
rw [EventuallyEq, ae_iff] at h
refine measure_mono_null (fun z => ?_) h
simp_rw [Set.mem_inter_iff, Set.mem_setOf_eq, Set.mem_preimage, Set.mem_singleton_iff]
intro h
rwa [h.1, h.2]
#align measure_theory.simple_func.set_to_simple_func_congr MeasureTheory.SimpleFunc.setToSimpleFunc_congr
theorem setToSimpleFunc_congr_left (T T' : Set α → E →L[ℝ] F)
(h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →ₛ E) (hf : Integrable f μ) :
setToSimpleFunc T f = setToSimpleFunc T' f := by
simp_rw [setToSimpleFunc]
refine sum_congr rfl fun x _ => ?_
by_cases hx0 : x = 0
· simp [hx0]
· rw [h (f ⁻¹' {x}) (SimpleFunc.measurableSet_fiber _ _)
(SimpleFunc.measure_preimage_lt_top_of_integrable _ hf hx0)]
#align measure_theory.simple_func.set_to_simple_func_congr_left MeasureTheory.SimpleFunc.setToSimpleFunc_congr_left
theorem setToSimpleFunc_add_left {m : MeasurableSpace α} (T T' : Set α → F →L[ℝ] F') {f : α →ₛ F} :
setToSimpleFunc (T + T') f = setToSimpleFunc T f + setToSimpleFunc T' f := by
simp_rw [setToSimpleFunc, Pi.add_apply]
push_cast
simp_rw [Pi.add_apply, sum_add_distrib]
#align measure_theory.simple_func.set_to_simple_func_add_left MeasureTheory.SimpleFunc.setToSimpleFunc_add_left
theorem setToSimpleFunc_add_left' (T T' T'' : Set α → E →L[ℝ] F)
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) {f : α →ₛ E}
(hf : Integrable f μ) : setToSimpleFunc T'' f = setToSimpleFunc T f + setToSimpleFunc T' f := by
simp_rw [setToSimpleFunc_eq_sum_filter]
suffices
∀ x ∈ filter (fun x : E => x ≠ 0) f.range, T'' (f ⁻¹' {x}) = T (f ⁻¹' {x}) + T' (f ⁻¹' {x}) by
rw [← sum_add_distrib]
refine Finset.sum_congr rfl fun x hx => ?_
rw [this x hx]
push_cast
rw [Pi.add_apply]
intro x hx
refine
h_add (f ⁻¹' {x}) (measurableSet_preimage _ _) (measure_preimage_lt_top_of_integrable _ hf ?_)
rw [mem_filter] at hx
exact hx.2
#align measure_theory.simple_func.set_to_simple_func_add_left' MeasureTheory.SimpleFunc.setToSimpleFunc_add_left'
theorem setToSimpleFunc_smul_left {m : MeasurableSpace α} (T : Set α → F →L[ℝ] F') (c : ℝ)
(f : α →ₛ F) : setToSimpleFunc (fun s => c • T s) f = c • setToSimpleFunc T f := by
simp_rw [setToSimpleFunc, ContinuousLinearMap.smul_apply, smul_sum]
#align measure_theory.simple_func.set_to_simple_func_smul_left MeasureTheory.SimpleFunc.setToSimpleFunc_smul_left
theorem setToSimpleFunc_smul_left' (T T' : Set α → E →L[ℝ] F') (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) {f : α →ₛ E} (hf : Integrable f μ) :
setToSimpleFunc T' f = c • setToSimpleFunc T f := by
simp_rw [setToSimpleFunc_eq_sum_filter]
suffices ∀ x ∈ filter (fun x : E => x ≠ 0) f.range, T' (f ⁻¹' {x}) = c • T (f ⁻¹' {x}) by
rw [smul_sum]
refine Finset.sum_congr rfl fun x hx => ?_
rw [this x hx]
rfl
intro x hx
refine
h_smul (f ⁻¹' {x}) (measurableSet_preimage _ _) (measure_preimage_lt_top_of_integrable _ hf ?_)
rw [mem_filter] at hx
exact hx.2
#align measure_theory.simple_func.set_to_simple_func_smul_left' MeasureTheory.SimpleFunc.setToSimpleFunc_smul_left'
theorem setToSimpleFunc_add (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T) {f g : α →ₛ E}
(hf : Integrable f μ) (hg : Integrable g μ) :
setToSimpleFunc T (f + g) = setToSimpleFunc T f + setToSimpleFunc T g :=
have hp_pair : Integrable (f.pair g) μ := integrable_pair hf hg
calc
setToSimpleFunc T (f + g) = ∑ x ∈ (pair f g).range, T (pair f g ⁻¹' {x}) (x.fst + x.snd) := by
rw [add_eq_map₂, map_setToSimpleFunc T h_add hp_pair]; simp
_ = ∑ x ∈ (pair f g).range, (T (pair f g ⁻¹' {x}) x.fst + T (pair f g ⁻¹' {x}) x.snd) :=
(Finset.sum_congr rfl fun a _ => ContinuousLinearMap.map_add _ _ _)
_ = (∑ x ∈ (pair f g).range, T (pair f g ⁻¹' {x}) x.fst) +
∑ x ∈ (pair f g).range, T (pair f g ⁻¹' {x}) x.snd := by
rw [Finset.sum_add_distrib]
_ = ((pair f g).map Prod.fst).setToSimpleFunc T +
((pair f g).map Prod.snd).setToSimpleFunc T := by
rw [map_setToSimpleFunc T h_add hp_pair Prod.snd_zero,
map_setToSimpleFunc T h_add hp_pair Prod.fst_zero]
#align measure_theory.simple_func.set_to_simple_func_add MeasureTheory.SimpleFunc.setToSimpleFunc_add
theorem setToSimpleFunc_neg (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T) {f : α →ₛ E}
(hf : Integrable f μ) : setToSimpleFunc T (-f) = -setToSimpleFunc T f :=
calc
setToSimpleFunc T (-f) = setToSimpleFunc T (f.map Neg.neg) := rfl
_ = -setToSimpleFunc T f := by
rw [map_setToSimpleFunc T h_add hf neg_zero, setToSimpleFunc, ← sum_neg_distrib]
exact Finset.sum_congr rfl fun x _ => ContinuousLinearMap.map_neg _ _
#align measure_theory.simple_func.set_to_simple_func_neg MeasureTheory.SimpleFunc.setToSimpleFunc_neg
theorem setToSimpleFunc_sub (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T) {f g : α →ₛ E}
(hf : Integrable f μ) (hg : Integrable g μ) :
setToSimpleFunc T (f - g) = setToSimpleFunc T f - setToSimpleFunc T g := by
rw [sub_eq_add_neg, setToSimpleFunc_add T h_add hf, setToSimpleFunc_neg T h_add hg,
sub_eq_add_neg]
rw [integrable_iff] at hg ⊢
intro x hx_ne
change μ (Neg.neg ∘ g ⁻¹' {x}) < ∞
rw [preimage_comp, neg_preimage, Set.neg_singleton]
refine hg (-x) ?_
simp [hx_ne]
#align measure_theory.simple_func.set_to_simple_func_sub MeasureTheory.SimpleFunc.setToSimpleFunc_sub
theorem setToSimpleFunc_smul_real (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T) (c : ℝ)
{f : α →ₛ E} (hf : Integrable f μ) : setToSimpleFunc T (c • f) = c • setToSimpleFunc T f :=
calc
setToSimpleFunc T (c • f) = ∑ x ∈ f.range, T (f ⁻¹' {x}) (c • x) := by
rw [smul_eq_map c f, map_setToSimpleFunc T h_add hf]; dsimp only; rw [smul_zero]
_ = ∑ x ∈ f.range, c • T (f ⁻¹' {x}) x :=
(Finset.sum_congr rfl fun b _ => by rw [ContinuousLinearMap.map_smul (T (f ⁻¹' {b})) c b])
_ = c • setToSimpleFunc T f := by simp only [setToSimpleFunc, smul_sum, smul_smul, mul_comm]
#align measure_theory.simple_func.set_to_simple_func_smul_real MeasureTheory.SimpleFunc.setToSimpleFunc_smul_real
theorem setToSimpleFunc_smul {E} [NormedAddCommGroup E] [NormedField 𝕜] [NormedSpace 𝕜 E]
[NormedSpace ℝ E] [NormedSpace 𝕜 F] (T : Set α → E →L[ℝ] F) (h_add : FinMeasAdditive μ T)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜) {f : α →ₛ E} (hf : Integrable f μ) :
setToSimpleFunc T (c • f) = c • setToSimpleFunc T f :=
calc
setToSimpleFunc T (c • f) = ∑ x ∈ f.range, T (f ⁻¹' {x}) (c • x) := by
rw [smul_eq_map c f, map_setToSimpleFunc T h_add hf]; dsimp only; rw [smul_zero]
_ = ∑ x ∈ f.range, c • T (f ⁻¹' {x}) x := Finset.sum_congr rfl fun b _ => by rw [h_smul]
_ = c • setToSimpleFunc T f := by simp only [setToSimpleFunc, smul_sum, smul_smul, mul_comm]
#align measure_theory.simple_func.set_to_simple_func_smul MeasureTheory.SimpleFunc.setToSimpleFunc_smul
section Order
variable {G' G'' : Type*} [NormedLatticeAddCommGroup G''] [NormedSpace ℝ G'']
[NormedLatticeAddCommGroup G'] [NormedSpace ℝ G']
theorem setToSimpleFunc_mono_left {m : MeasurableSpace α} (T T' : Set α → F →L[ℝ] G'')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →ₛ F) : setToSimpleFunc T f ≤ setToSimpleFunc T' f := by
simp_rw [setToSimpleFunc]; exact sum_le_sum fun i _ => hTT' _ i
#align measure_theory.simple_func.set_to_simple_func_mono_left MeasureTheory.SimpleFunc.setToSimpleFunc_mono_left
theorem setToSimpleFunc_mono_left' (T T' : Set α → E →L[ℝ] G'')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →ₛ E)
(hf : Integrable f μ) : setToSimpleFunc T f ≤ setToSimpleFunc T' f := by
refine sum_le_sum fun i _ => ?_
by_cases h0 : i = 0
· simp [h0]
· exact hTT' _ (measurableSet_fiber _ _) (measure_preimage_lt_top_of_integrable _ hf h0) i
#align measure_theory.simple_func.set_to_simple_func_mono_left' MeasureTheory.SimpleFunc.setToSimpleFunc_mono_left'
theorem setToSimpleFunc_nonneg {m : MeasurableSpace α} (T : Set α → G' →L[ℝ] G'')
(hT_nonneg : ∀ s x, 0 ≤ x → 0 ≤ T s x) (f : α →ₛ G') (hf : 0 ≤ f) :
0 ≤ setToSimpleFunc T f := by
refine sum_nonneg fun i hi => hT_nonneg _ i ?_
rw [mem_range] at hi
obtain ⟨y, hy⟩ := Set.mem_range.mp hi
rw [← hy]
refine le_trans ?_ (hf y)
simp
#align measure_theory.simple_func.set_to_simple_func_nonneg MeasureTheory.SimpleFunc.setToSimpleFunc_nonneg
theorem setToSimpleFunc_nonneg' (T : Set α → G' →L[ℝ] G'')
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) (f : α →ₛ G') (hf : 0 ≤ f)
(hfi : Integrable f μ) : 0 ≤ setToSimpleFunc T f := by
refine sum_nonneg fun i hi => ?_
by_cases h0 : i = 0
· simp [h0]
refine
hT_nonneg _ (measurableSet_fiber _ _) (measure_preimage_lt_top_of_integrable _ hfi h0) i ?_
rw [mem_range] at hi
obtain ⟨y, hy⟩ := Set.mem_range.mp hi
rw [← hy]
convert hf y
#align measure_theory.simple_func.set_to_simple_func_nonneg' MeasureTheory.SimpleFunc.setToSimpleFunc_nonneg'
theorem setToSimpleFunc_mono {T : Set α → G' →L[ℝ] G''} (h_add : FinMeasAdditive μ T)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →ₛ G'}
(hfi : Integrable f μ) (hgi : Integrable g μ) (hfg : f ≤ g) :
setToSimpleFunc T f ≤ setToSimpleFunc T g := by
rw [← sub_nonneg, ← setToSimpleFunc_sub T h_add hgi hfi]
refine setToSimpleFunc_nonneg' T hT_nonneg _ ?_ (hgi.sub hfi)
intro x
simp only [coe_sub, sub_nonneg, coe_zero, Pi.zero_apply, Pi.sub_apply]
exact hfg x
#align measure_theory.simple_func.set_to_simple_func_mono MeasureTheory.SimpleFunc.setToSimpleFunc_mono
end Order
theorem norm_setToSimpleFunc_le_sum_opNorm {m : MeasurableSpace α} (T : Set α → F' →L[ℝ] F)
(f : α →ₛ F') : ‖f.setToSimpleFunc T‖ ≤ ∑ x ∈ f.range, ‖T (f ⁻¹' {x})‖ * ‖x‖ :=
calc
‖∑ x ∈ f.range, T (f ⁻¹' {x}) x‖ ≤ ∑ x ∈ f.range, ‖T (f ⁻¹' {x}) x‖ := norm_sum_le _ _
_ ≤ ∑ x ∈ f.range, ‖T (f ⁻¹' {x})‖ * ‖x‖ := by
refine Finset.sum_le_sum fun b _ => ?_; simp_rw [ContinuousLinearMap.le_opNorm]
#align measure_theory.simple_func.norm_set_to_simple_func_le_sum_op_norm MeasureTheory.SimpleFunc.norm_setToSimpleFunc_le_sum_opNorm
@[deprecated (since := "2024-02-02")]
alias norm_setToSimpleFunc_le_sum_op_norm := norm_setToSimpleFunc_le_sum_opNorm
theorem norm_setToSimpleFunc_le_sum_mul_norm (T : Set α → F →L[ℝ] F') {C : ℝ}
(hT_norm : ∀ s, MeasurableSet s → ‖T s‖ ≤ C * (μ s).toReal) (f : α →ₛ F) :
‖f.setToSimpleFunc T‖ ≤ C * ∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal * ‖x‖ :=
calc
‖f.setToSimpleFunc T‖ ≤ ∑ x ∈ f.range, ‖T (f ⁻¹' {x})‖ * ‖x‖ :=
norm_setToSimpleFunc_le_sum_opNorm T f
_ ≤ ∑ x ∈ f.range, C * (μ (f ⁻¹' {x})).toReal * ‖x‖ := by
gcongr
exact hT_norm _ <| SimpleFunc.measurableSet_fiber _ _
_ ≤ C * ∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal * ‖x‖ := by simp_rw [mul_sum, ← mul_assoc]; rfl
#align measure_theory.simple_func.norm_set_to_simple_func_le_sum_mul_norm MeasureTheory.SimpleFunc.norm_setToSimpleFunc_le_sum_mul_norm
theorem norm_setToSimpleFunc_le_sum_mul_norm_of_integrable (T : Set α → E →L[ℝ] F') {C : ℝ}
(hT_norm : ∀ s, MeasurableSet s → μ s < ∞ → ‖T s‖ ≤ C * (μ s).toReal) (f : α →ₛ E)
(hf : Integrable f μ) :
‖f.setToSimpleFunc T‖ ≤ C * ∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal * ‖x‖ :=
calc
‖f.setToSimpleFunc T‖ ≤ ∑ x ∈ f.range, ‖T (f ⁻¹' {x})‖ * ‖x‖ :=
norm_setToSimpleFunc_le_sum_opNorm T f
_ ≤ ∑ x ∈ f.range, C * (μ (f ⁻¹' {x})).toReal * ‖x‖ := by
refine Finset.sum_le_sum fun b hb => ?_
obtain rfl | hb := eq_or_ne b 0
· simp
gcongr
exact hT_norm _ (SimpleFunc.measurableSet_fiber _ _) <|
SimpleFunc.measure_preimage_lt_top_of_integrable _ hf hb
_ ≤ C * ∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal * ‖x‖ := by simp_rw [mul_sum, ← mul_assoc]; rfl
#align measure_theory.simple_func.norm_set_to_simple_func_le_sum_mul_norm_of_integrable MeasureTheory.SimpleFunc.norm_setToSimpleFunc_le_sum_mul_norm_of_integrable
theorem setToSimpleFunc_indicator (T : Set α → F →L[ℝ] F') (hT_empty : T ∅ = 0)
{m : MeasurableSpace α} {s : Set α} (hs : MeasurableSet s) (x : F) :
SimpleFunc.setToSimpleFunc T
(SimpleFunc.piecewise s hs (SimpleFunc.const α x) (SimpleFunc.const α 0)) =
T s x := by
obtain rfl | hs_empty := s.eq_empty_or_nonempty
· simp only [hT_empty, ContinuousLinearMap.zero_apply, piecewise_empty, const_zero,
setToSimpleFunc_zero_apply]
simp_rw [setToSimpleFunc]
obtain rfl | hs_univ := eq_or_ne s univ
· haveI hα := hs_empty.to_type
simp [← Function.const_def]
rw [range_indicator hs hs_empty hs_univ]
by_cases hx0 : x = 0
· simp_rw [hx0]; simp
rw [sum_insert]
swap; · rw [Finset.mem_singleton]; exact hx0
rw [sum_singleton, (T _).map_zero, add_zero]
congr
simp only [coe_piecewise, piecewise_eq_indicator, coe_const, Function.const_zero,
piecewise_eq_indicator]
rw [indicator_preimage, ← Function.const_def, preimage_const_of_mem]
swap; · exact Set.mem_singleton x
rw [← Function.const_zero, ← Function.const_def, preimage_const_of_not_mem]
swap; · rw [Set.mem_singleton_iff]; exact Ne.symm hx0
simp
#align measure_theory.simple_func.set_to_simple_func_indicator MeasureTheory.SimpleFunc.setToSimpleFunc_indicator
theorem setToSimpleFunc_const' [Nonempty α] (T : Set α → F →L[ℝ] F') (x : F)
{m : MeasurableSpace α} : SimpleFunc.setToSimpleFunc T (SimpleFunc.const α x) = T univ x := by
simp only [setToSimpleFunc, range_const, Set.mem_singleton, preimage_const_of_mem,
sum_singleton, ← Function.const_def, coe_const]
#align measure_theory.simple_func.set_to_simple_func_const' MeasureTheory.SimpleFunc.setToSimpleFunc_const'
theorem setToSimpleFunc_const (T : Set α → F →L[ℝ] F') (hT_empty : T ∅ = 0) (x : F)
{m : MeasurableSpace α} : SimpleFunc.setToSimpleFunc T (SimpleFunc.const α x) = T univ x := by
cases isEmpty_or_nonempty α
· have h_univ_empty : (univ : Set α) = ∅ := Subsingleton.elim _ _
rw [h_univ_empty, hT_empty]
simp only [setToSimpleFunc, ContinuousLinearMap.zero_apply, sum_empty,
range_eq_empty_of_isEmpty]
· exact setToSimpleFunc_const' T x
#align measure_theory.simple_func.set_to_simple_func_const MeasureTheory.SimpleFunc.setToSimpleFunc_const
end SimpleFunc
namespace L1
set_option linter.uppercaseLean3 false
open AEEqFun Lp.simpleFunc Lp
namespace SimpleFunc
theorem norm_eq_sum_mul (f : α →₁ₛ[μ] G) :
‖f‖ = ∑ x ∈ (toSimpleFunc f).range, (μ (toSimpleFunc f ⁻¹' {x})).toReal * ‖x‖ := by
rw [norm_toSimpleFunc, snorm_one_eq_lintegral_nnnorm]
have h_eq := SimpleFunc.map_apply (fun x => (‖x‖₊ : ℝ≥0∞)) (toSimpleFunc f)
simp_rw [← h_eq]
rw [SimpleFunc.lintegral_eq_lintegral, SimpleFunc.map_lintegral, ENNReal.toReal_sum]
· congr
ext1 x
rw [ENNReal.toReal_mul, mul_comm, ← ofReal_norm_eq_coe_nnnorm,
ENNReal.toReal_ofReal (norm_nonneg _)]
· intro x _
by_cases hx0 : x = 0
· rw [hx0]; simp
· exact
ENNReal.mul_ne_top ENNReal.coe_ne_top
(SimpleFunc.measure_preimage_lt_top_of_integrable _ (SimpleFunc.integrable f) hx0).ne
#align measure_theory.L1.simple_func.norm_eq_sum_mul MeasureTheory.L1.SimpleFunc.norm_eq_sum_mul
section SetToL1S
variable [NormedField 𝕜] [NormedSpace 𝕜 E]
attribute [local instance] Lp.simpleFunc.module
attribute [local instance] Lp.simpleFunc.normedSpace
/-- Extend `Set α → (E →L[ℝ] F')` to `(α →₁ₛ[μ] E) → F'`. -/
def setToL1S (T : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) : F :=
(toSimpleFunc f).setToSimpleFunc T
#align measure_theory.L1.simple_func.set_to_L1s MeasureTheory.L1.SimpleFunc.setToL1S
theorem setToL1S_eq_setToSimpleFunc (T : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) :
setToL1S T f = (toSimpleFunc f).setToSimpleFunc T :=
rfl
#align measure_theory.L1.simple_func.set_to_L1s_eq_set_to_simple_func MeasureTheory.L1.SimpleFunc.setToL1S_eq_setToSimpleFunc
@[simp]
theorem setToL1S_zero_left (f : α →₁ₛ[μ] E) : setToL1S (0 : Set α → E →L[ℝ] F) f = 0 :=
SimpleFunc.setToSimpleFunc_zero _
#align measure_theory.L1.simple_func.set_to_L1s_zero_left MeasureTheory.L1.SimpleFunc.setToL1S_zero_left
theorem setToL1S_zero_left' {T : Set α → E →L[ℝ] F}
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁ₛ[μ] E) : setToL1S T f = 0 :=
SimpleFunc.setToSimpleFunc_zero' h_zero _ (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_zero_left' MeasureTheory.L1.SimpleFunc.setToL1S_zero_left'
theorem setToL1S_congr (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) {f g : α →₁ₛ[μ] E} (h : toSimpleFunc f =ᵐ[μ] toSimpleFunc g) :
setToL1S T f = setToL1S T g :=
SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable f) h
#align measure_theory.L1.simple_func.set_to_L1s_congr MeasureTheory.L1.SimpleFunc.setToL1S_congr
theorem setToL1S_congr_left (T T' : Set α → E →L[ℝ] F)
(h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →₁ₛ[μ] E) :
setToL1S T f = setToL1S T' f :=
SimpleFunc.setToSimpleFunc_congr_left T T' h (simpleFunc.toSimpleFunc f) (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_congr_left MeasureTheory.L1.SimpleFunc.setToL1S_congr_left
/-- `setToL1S` does not change if we replace the measure `μ` by `μ'` with `μ ≪ μ'`. The statement
uses two functions `f` and `f'` because they have to belong to different types, but morally these
are the same function (we have `f =ᵐ[μ] f'`). -/
theorem setToL1S_congr_measure {μ' : Measure α} (T : Set α → E →L[ℝ] F)
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (hμ : μ ≪ μ')
(f : α →₁ₛ[μ] E) (f' : α →₁ₛ[μ'] E) (h : (f : α → E) =ᵐ[μ] f') :
setToL1S T f = setToL1S T f' := by
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable f) ?_
refine (toSimpleFunc_eq_toFun f).trans ?_
suffices (f' : α → E) =ᵐ[μ] simpleFunc.toSimpleFunc f' from h.trans this
have goal' : (f' : α → E) =ᵐ[μ'] simpleFunc.toSimpleFunc f' := (toSimpleFunc_eq_toFun f').symm
exact hμ.ae_eq goal'
#align measure_theory.L1.simple_func.set_to_L1s_congr_measure MeasureTheory.L1.SimpleFunc.setToL1S_congr_measure
theorem setToL1S_add_left (T T' : Set α → E →L[ℝ] F) (f : α →₁ₛ[μ] E) :
setToL1S (T + T') f = setToL1S T f + setToL1S T' f :=
SimpleFunc.setToSimpleFunc_add_left T T'
#align measure_theory.L1.simple_func.set_to_L1s_add_left MeasureTheory.L1.SimpleFunc.setToL1S_add_left
theorem setToL1S_add_left' (T T' T'' : Set α → E →L[ℝ] F)
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁ₛ[μ] E) :
setToL1S T'' f = setToL1S T f + setToL1S T' f :=
SimpleFunc.setToSimpleFunc_add_left' T T' T'' h_add (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_add_left' MeasureTheory.L1.SimpleFunc.setToL1S_add_left'
theorem setToL1S_smul_left (T : Set α → E →L[ℝ] F) (c : ℝ) (f : α →₁ₛ[μ] E) :
setToL1S (fun s => c • T s) f = c • setToL1S T f :=
SimpleFunc.setToSimpleFunc_smul_left T c _
#align measure_theory.L1.simple_func.set_to_L1s_smul_left MeasureTheory.L1.SimpleFunc.setToL1S_smul_left
theorem setToL1S_smul_left' (T T' : Set α → E →L[ℝ] F) (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁ₛ[μ] E) :
setToL1S T' f = c • setToL1S T f :=
SimpleFunc.setToSimpleFunc_smul_left' T T' c h_smul (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_smul_left' MeasureTheory.L1.SimpleFunc.setToL1S_smul_left'
theorem setToL1S_add (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f g : α →₁ₛ[μ] E) :
setToL1S T (f + g) = setToL1S T f + setToL1S T g := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_add T h_add (SimpleFunc.integrable f)
(SimpleFunc.integrable g)]
exact
SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _)
(add_toSimpleFunc f g)
#align measure_theory.L1.simple_func.set_to_L1s_add MeasureTheory.L1.SimpleFunc.setToL1S_add
theorem setToL1S_neg {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f : α →₁ₛ[μ] E) : setToL1S T (-f) = -setToL1S T f := by
simp_rw [setToL1S]
have : simpleFunc.toSimpleFunc (-f) =ᵐ[μ] ⇑(-simpleFunc.toSimpleFunc f) :=
neg_toSimpleFunc f
rw [SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) this]
exact SimpleFunc.setToSimpleFunc_neg T h_add (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_neg MeasureTheory.L1.SimpleFunc.setToL1S_neg
theorem setToL1S_sub {T : Set α → E →L[ℝ] F} (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (f g : α →₁ₛ[μ] E) :
setToL1S T (f - g) = setToL1S T f - setToL1S T g := by
rw [sub_eq_add_neg, setToL1S_add T h_zero h_add, setToL1S_neg h_zero h_add, sub_eq_add_neg]
#align measure_theory.L1.simple_func.set_to_L1s_sub MeasureTheory.L1.SimpleFunc.setToL1S_sub
theorem setToL1S_smul_real (T : Set α → E →L[ℝ] F)
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (c : ℝ)
(f : α →₁ₛ[μ] E) : setToL1S T (c • f) = c • setToL1S T f := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_smul_real T h_add c (SimpleFunc.integrable f)]
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact smul_toSimpleFunc c f
#align measure_theory.L1.simple_func.set_to_L1s_smul_real MeasureTheory.L1.SimpleFunc.setToL1S_smul_real
theorem setToL1S_smul {E} [NormedAddCommGroup E] [NormedSpace ℝ E] [NormedSpace 𝕜 E]
[NormedSpace 𝕜 F] (T : Set α → E →L[ℝ] F) (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜)
(f : α →₁ₛ[μ] E) : setToL1S T (c • f) = c • setToL1S T f := by
simp_rw [setToL1S]
rw [← SimpleFunc.setToSimpleFunc_smul T h_add h_smul c (SimpleFunc.integrable f)]
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact smul_toSimpleFunc c f
#align measure_theory.L1.simple_func.set_to_L1s_smul MeasureTheory.L1.SimpleFunc.setToL1S_smul
theorem norm_setToL1S_le (T : Set α → E →L[ℝ] F) {C : ℝ}
(hT_norm : ∀ s, MeasurableSet s → μ s < ∞ → ‖T s‖ ≤ C * (μ s).toReal) (f : α →₁ₛ[μ] E) :
‖setToL1S T f‖ ≤ C * ‖f‖ := by
rw [setToL1S, norm_eq_sum_mul f]
exact
SimpleFunc.norm_setToSimpleFunc_le_sum_mul_norm_of_integrable T hT_norm _
(SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.norm_set_to_L1s_le MeasureTheory.L1.SimpleFunc.norm_setToL1S_le
theorem setToL1S_indicatorConst {T : Set α → E →L[ℝ] F} {s : Set α}
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T)
(hs : MeasurableSet s) (hμs : μ s < ∞) (x : E) :
setToL1S T (simpleFunc.indicatorConst 1 hs hμs.ne x) = T s x := by
have h_empty : T ∅ = 0 := h_zero _ MeasurableSet.empty measure_empty
rw [setToL1S_eq_setToSimpleFunc]
refine Eq.trans ?_ (SimpleFunc.setToSimpleFunc_indicator T h_empty hs x)
refine SimpleFunc.setToSimpleFunc_congr T h_zero h_add (SimpleFunc.integrable _) ?_
exact toSimpleFunc_indicatorConst hs hμs.ne x
#align measure_theory.L1.simple_func.set_to_L1s_indicator_const MeasureTheory.L1.SimpleFunc.setToL1S_indicatorConst
theorem setToL1S_const [IsFiniteMeasure μ] {T : Set α → E →L[ℝ] F}
(h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0) (h_add : FinMeasAdditive μ T) (x : E) :
setToL1S T (simpleFunc.indicatorConst 1 MeasurableSet.univ (measure_ne_top μ _) x) = T univ x :=
setToL1S_indicatorConst h_zero h_add MeasurableSet.univ (measure_lt_top _ _) x
#align measure_theory.L1.simple_func.set_to_L1s_const MeasureTheory.L1.SimpleFunc.setToL1S_const
section Order
variable {G'' G' : Type*} [NormedLatticeAddCommGroup G'] [NormedSpace ℝ G']
[NormedLatticeAddCommGroup G''] [NormedSpace ℝ G''] {T : Set α → G'' →L[ℝ] G'}
theorem setToL1S_mono_left {T T' : Set α → E →L[ℝ] G''} (hTT' : ∀ s x, T s x ≤ T' s x)
(f : α →₁ₛ[μ] E) : setToL1S T f ≤ setToL1S T' f :=
SimpleFunc.setToSimpleFunc_mono_left T T' hTT' _
#align measure_theory.L1.simple_func.set_to_L1s_mono_left MeasureTheory.L1.SimpleFunc.setToL1S_mono_left
theorem setToL1S_mono_left' {T T' : Set α → E →L[ℝ] G''}
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1S T f ≤ setToL1S T' f :=
SimpleFunc.setToSimpleFunc_mono_left' T T' hTT' _ (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_mono_left' MeasureTheory.L1.SimpleFunc.setToL1S_mono_left'
theorem setToL1S_nonneg (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁ₛ[μ] G''}
(hf : 0 ≤ f) : 0 ≤ setToL1S T f := by
simp_rw [setToL1S]
obtain ⟨f', hf', hff'⟩ : ∃ f' : α →ₛ G'', 0 ≤ f' ∧ simpleFunc.toSimpleFunc f =ᵐ[μ] f' := by
obtain ⟨f'', hf'', hff''⟩ := exists_simpleFunc_nonneg_ae_eq hf
exact ⟨f'', hf'', (Lp.simpleFunc.toSimpleFunc_eq_toFun f).trans hff''⟩
rw [SimpleFunc.setToSimpleFunc_congr _ h_zero h_add (SimpleFunc.integrable _) hff']
exact
SimpleFunc.setToSimpleFunc_nonneg' T hT_nonneg _ hf' ((SimpleFunc.integrable f).congr hff')
#align measure_theory.L1.simple_func.set_to_L1s_nonneg MeasureTheory.L1.SimpleFunc.setToL1S_nonneg
theorem setToL1S_mono (h_zero : ∀ s, MeasurableSet s → μ s = 0 → T s = 0)
(h_add : FinMeasAdditive μ T)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁ₛ[μ] G''}
(hfg : f ≤ g) : setToL1S T f ≤ setToL1S T g := by
rw [← sub_nonneg] at hfg ⊢
rw [← setToL1S_sub h_zero h_add]
exact setToL1S_nonneg h_zero h_add hT_nonneg hfg
#align measure_theory.L1.simple_func.set_to_L1s_mono MeasureTheory.L1.SimpleFunc.setToL1S_mono
end Order
variable [NormedSpace 𝕜 F]
variable (α E μ 𝕜)
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁ₛ[μ] E) →L[𝕜] F`. -/
def setToL1SCLM' {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) : (α →₁ₛ[μ] E) →L[𝕜] F :=
LinearMap.mkContinuous
⟨⟨setToL1S T, setToL1S_add T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩,
setToL1S_smul T (fun _ => hT.eq_zero_of_measure_zero) hT.1 h_smul⟩
C fun f => norm_setToL1S_le T hT.2 f
#align measure_theory.L1.simple_func.set_to_L1s_clm' MeasureTheory.L1.SimpleFunc.setToL1SCLM'
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁ₛ[μ] E) →L[ℝ] F`. -/
def setToL1SCLM {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) :
(α →₁ₛ[μ] E) →L[ℝ] F :=
LinearMap.mkContinuous
⟨⟨setToL1S T, setToL1S_add T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩,
setToL1S_smul_real T (fun _ => hT.eq_zero_of_measure_zero) hT.1⟩
C fun f => norm_setToL1S_le T hT.2 f
#align measure_theory.L1.simple_func.set_to_L1s_clm MeasureTheory.L1.SimpleFunc.setToL1SCLM
variable {α E μ 𝕜}
variable {T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ}
@[simp]
theorem setToL1SCLM_zero_left (hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C)
(f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = 0 :=
setToL1S_zero_left _
#align measure_theory.L1.simple_func.set_to_L1s_clm_zero_left MeasureTheory.L1.SimpleFunc.setToL1SCLM_zero_left
theorem setToL1SCLM_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f = 0 :=
setToL1S_zero_left' h_zero f
#align measure_theory.L1.simple_func.set_to_L1s_clm_zero_left' MeasureTheory.L1.SimpleFunc.setToL1SCLM_zero_left'
theorem setToL1SCLM_congr_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : T = T') (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f = setToL1SCLM α E μ hT' f :=
setToL1S_congr_left T T' (fun _ _ _ => by rw [h]) f
#align measure_theory.L1.simple_func.set_to_L1s_clm_congr_left MeasureTheory.L1.SimpleFunc.setToL1SCLM_congr_left
theorem setToL1SCLM_congr_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s)
(f : α →₁ₛ[μ] E) : setToL1SCLM α E μ hT f = setToL1SCLM α E μ hT' f :=
setToL1S_congr_left T T' h f
#align measure_theory.L1.simple_func.set_to_L1s_clm_congr_left' MeasureTheory.L1.SimpleFunc.setToL1SCLM_congr_left'
theorem setToL1SCLM_congr_measure {μ' : Measure α} (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ' T C') (hμ : μ ≪ μ') (f : α →₁ₛ[μ] E) (f' : α →₁ₛ[μ'] E)
(h : (f : α → E) =ᵐ[μ] f') : setToL1SCLM α E μ hT f = setToL1SCLM α E μ' hT' f' :=
setToL1S_congr_measure T (fun _ => hT.eq_zero_of_measure_zero) hT.1 hμ _ _ h
#align measure_theory.L1.simple_func.set_to_L1s_clm_congr_measure MeasureTheory.L1.SimpleFunc.setToL1SCLM_congr_measure
theorem setToL1SCLM_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ (hT.add hT') f = setToL1SCLM α E μ hT f + setToL1SCLM α E μ hT' f :=
setToL1S_add_left T T' f
#align measure_theory.L1.simple_func.set_to_L1s_clm_add_left MeasureTheory.L1.SimpleFunc.setToL1SCLM_add_left
theorem setToL1SCLM_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT'' f = setToL1SCLM α E μ hT f + setToL1SCLM α E μ hT' f :=
setToL1S_add_left' T T' T'' h_add f
#align measure_theory.L1.simple_func.set_to_L1s_clm_add_left' MeasureTheory.L1.SimpleFunc.setToL1SCLM_add_left'
theorem setToL1SCLM_smul_left (c : ℝ) (hT : DominatedFinMeasAdditive μ T C) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ (hT.smul c) f = c • setToL1SCLM α E μ hT f :=
setToL1S_smul_left T c f
#align measure_theory.L1.simple_func.set_to_L1s_clm_smul_left MeasureTheory.L1.SimpleFunc.setToL1SCLM_smul_left
theorem setToL1SCLM_smul_left' (c : ℝ) (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C')
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT' f = c • setToL1SCLM α E μ hT f :=
setToL1S_smul_left' T T' c h_smul f
#align measure_theory.L1.simple_func.set_to_L1s_clm_smul_left' MeasureTheory.L1.SimpleFunc.setToL1SCLM_smul_left'
theorem norm_setToL1SCLM_le {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hC : 0 ≤ C) : ‖setToL1SCLM α E μ hT‖ ≤ C :=
LinearMap.mkContinuous_norm_le _ hC _
#align measure_theory.L1.simple_func.norm_set_to_L1s_clm_le MeasureTheory.L1.SimpleFunc.norm_setToL1SCLM_le
theorem norm_setToL1SCLM_le' {T : Set α → E →L[ℝ] F} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C) :
‖setToL1SCLM α E μ hT‖ ≤ max C 0 :=
LinearMap.mkContinuous_norm_le' _ _
#align measure_theory.L1.simple_func.norm_set_to_L1s_clm_le' MeasureTheory.L1.SimpleFunc.norm_setToL1SCLM_le'
theorem setToL1SCLM_const [IsFiniteMeasure μ] {T : Set α → E →L[ℝ] F} {C : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (x : E) :
setToL1SCLM α E μ hT (simpleFunc.indicatorConst 1 MeasurableSet.univ (measure_ne_top μ _) x) =
T univ x :=
setToL1S_const (fun _ => hT.eq_zero_of_measure_zero) hT.1 x
#align measure_theory.L1.simple_func.set_to_L1s_clm_const MeasureTheory.L1.SimpleFunc.setToL1SCLM_const
section Order
variable {G' G'' : Type*} [NormedLatticeAddCommGroup G''] [NormedSpace ℝ G'']
[NormedLatticeAddCommGroup G'] [NormedSpace ℝ G']
theorem setToL1SCLM_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f ≤ setToL1SCLM α E μ hT' f :=
SimpleFunc.setToSimpleFunc_mono_left T T' hTT' _
#align measure_theory.L1.simple_func.set_to_L1s_clm_mono_left MeasureTheory.L1.SimpleFunc.setToL1SCLM_mono_left
theorem setToL1SCLM_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁ₛ[μ] E) :
setToL1SCLM α E μ hT f ≤ setToL1SCLM α E μ hT' f :=
SimpleFunc.setToSimpleFunc_mono_left' T T' hTT' _ (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.set_to_L1s_clm_mono_left' MeasureTheory.L1.SimpleFunc.setToL1SCLM_mono_left'
theorem setToL1SCLM_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁ₛ[μ] G'}
(hf : 0 ≤ f) : 0 ≤ setToL1SCLM α G' μ hT f :=
setToL1S_nonneg (fun _ => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg hf
#align measure_theory.L1.simple_func.set_to_L1s_clm_nonneg MeasureTheory.L1.SimpleFunc.setToL1SCLM_nonneg
theorem setToL1SCLM_mono {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁ₛ[μ] G'}
(hfg : f ≤ g) : setToL1SCLM α G' μ hT f ≤ setToL1SCLM α G' μ hT g :=
setToL1S_mono (fun _ => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg hfg
#align measure_theory.L1.simple_func.set_to_L1s_clm_mono MeasureTheory.L1.SimpleFunc.setToL1SCLM_mono
end Order
end SetToL1S
end SimpleFunc
open SimpleFunc
section SetToL1
attribute [local instance] Lp.simpleFunc.module
attribute [local instance] Lp.simpleFunc.normedSpace
variable (𝕜) [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F] [CompleteSpace F]
{T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ}
/-- Extend `set α → (E →L[ℝ] F)` to `(α →₁[μ] E) →L[𝕜] F`. -/
def setToL1' (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) : (α →₁[μ] E) →L[𝕜] F :=
(setToL1SCLM' α E 𝕜 μ hT h_smul).extend (coeToLp α E 𝕜) (simpleFunc.denseRange one_ne_top)
simpleFunc.uniformInducing
#align measure_theory.L1.set_to_L1' MeasureTheory.L1.setToL1'
variable {𝕜}
/-- Extend `Set α → E →L[ℝ] F` to `(α →₁[μ] E) →L[ℝ] F`. -/
def setToL1 (hT : DominatedFinMeasAdditive μ T C) : (α →₁[μ] E) →L[ℝ] F :=
(setToL1SCLM α E μ hT).extend (coeToLp α E ℝ) (simpleFunc.denseRange one_ne_top)
simpleFunc.uniformInducing
#align measure_theory.L1.set_to_L1 MeasureTheory.L1.setToL1
theorem setToL1_eq_setToL1SCLM (hT : DominatedFinMeasAdditive μ T C) (f : α →₁ₛ[μ] E) :
setToL1 hT f = setToL1SCLM α E μ hT f :=
uniformly_extend_of_ind simpleFunc.uniformInducing (simpleFunc.denseRange one_ne_top)
(setToL1SCLM α E μ hT).uniformContinuous _
#align measure_theory.L1.set_to_L1_eq_set_to_L1s_clm MeasureTheory.L1.setToL1_eq_setToL1SCLM
theorem setToL1_eq_setToL1' (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (f : α →₁[μ] E) :
setToL1 hT f = setToL1' 𝕜 hT h_smul f :=
rfl
#align measure_theory.L1.set_to_L1_eq_set_to_L1' MeasureTheory.L1.setToL1_eq_setToL1'
@[simp]
theorem setToL1_zero_left (hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C)
(f : α →₁[μ] E) : setToL1 hT f = 0 := by
suffices setToL1 hT = 0 by rw [this]; simp
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
rw [setToL1SCLM_zero_left hT f, ContinuousLinearMap.zero_comp, ContinuousLinearMap.zero_apply]
#align measure_theory.L1.set_to_L1_zero_left MeasureTheory.L1.setToL1_zero_left
theorem setToL1_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) (f : α →₁[μ] E) : setToL1 hT f = 0 := by
suffices setToL1 hT = 0 by rw [this]; simp
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
rw [setToL1SCLM_zero_left' hT h_zero f, ContinuousLinearMap.zero_comp,
ContinuousLinearMap.zero_apply]
#align measure_theory.L1.set_to_L1_zero_left' MeasureTheory.L1.setToL1_zero_left'
theorem setToL1_congr_left (T T' : Set α → E →L[ℝ] F) {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C') (h : T = T')
(f : α →₁[μ] E) : setToL1 hT f = setToL1 hT' f := by
suffices setToL1 hT = setToL1 hT' by rw [this]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
suffices setToL1 hT' f = setToL1SCLM α E μ hT f by rw [← this]; rfl
rw [setToL1_eq_setToL1SCLM]
exact setToL1SCLM_congr_left hT' hT h.symm f
#align measure_theory.L1.set_to_L1_congr_left MeasureTheory.L1.setToL1_congr_left
theorem setToL1_congr_left' (T T' : Set α → E →L[ℝ] F) {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s) (f : α →₁[μ] E) :
setToL1 hT f = setToL1 hT' f := by
suffices setToL1 hT = setToL1 hT' by rw [this]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT) _ _ _ _ ?_
ext1 f
suffices setToL1 hT' f = setToL1SCLM α E μ hT f by rw [← this]; rfl
rw [setToL1_eq_setToL1SCLM]
exact (setToL1SCLM_congr_left' hT hT' h f).symm
#align measure_theory.L1.set_to_L1_congr_left' MeasureTheory.L1.setToL1_congr_left'
theorem setToL1_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α →₁[μ] E) :
setToL1 (hT.add hT') f = setToL1 hT f + setToL1 hT' f := by
suffices setToL1 (hT.add hT') = setToL1 hT + setToL1 hT' by
rw [this, ContinuousLinearMap.add_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ (hT.add hT')) _ _ _ _ ?_
ext1 f
suffices setToL1 hT f + setToL1 hT' f = setToL1SCLM α E μ (hT.add hT') f by
rw [← this]; rfl
rw [setToL1_eq_setToL1SCLM, setToL1_eq_setToL1SCLM, setToL1SCLM_add_left hT hT']
#align measure_theory.L1.set_to_L1_add_left MeasureTheory.L1.setToL1_add_left
theorem setToL1_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α →₁[μ] E) :
setToL1 hT'' f = setToL1 hT f + setToL1 hT' f := by
suffices setToL1 hT'' = setToL1 hT + setToL1 hT' by rw [this, ContinuousLinearMap.add_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT'') _ _ _ _ ?_
ext1 f
suffices setToL1 hT f + setToL1 hT' f = setToL1SCLM α E μ hT'' f by rw [← this]; congr
rw [setToL1_eq_setToL1SCLM, setToL1_eq_setToL1SCLM,
setToL1SCLM_add_left' hT hT' hT'' h_add]
#align measure_theory.L1.set_to_L1_add_left' MeasureTheory.L1.setToL1_add_left'
theorem setToL1_smul_left (hT : DominatedFinMeasAdditive μ T C) (c : ℝ) (f : α →₁[μ] E) :
setToL1 (hT.smul c) f = c • setToL1 hT f := by
suffices setToL1 (hT.smul c) = c • setToL1 hT by rw [this, ContinuousLinearMap.smul_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ (hT.smul c)) _ _ _ _ ?_
ext1 f
suffices c • setToL1 hT f = setToL1SCLM α E μ (hT.smul c) f by rw [← this]; congr
rw [setToL1_eq_setToL1SCLM, setToL1SCLM_smul_left c hT]
#align measure_theory.L1.set_to_L1_smul_left MeasureTheory.L1.setToL1_smul_left
theorem setToL1_smul_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α →₁[μ] E) :
setToL1 hT' f = c • setToL1 hT f := by
suffices setToL1 hT' = c • setToL1 hT by rw [this, ContinuousLinearMap.smul_apply]
refine ContinuousLinearMap.extend_unique (setToL1SCLM α E μ hT') _ _ _ _ ?_
ext1 f
suffices c • setToL1 hT f = setToL1SCLM α E μ hT' f by rw [← this]; congr
rw [setToL1_eq_setToL1SCLM, setToL1SCLM_smul_left' c hT hT' h_smul]
#align measure_theory.L1.set_to_L1_smul_left' MeasureTheory.L1.setToL1_smul_left'
theorem setToL1_smul (hT : DominatedFinMeasAdditive μ T C)
(h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜) (f : α →₁[μ] E) :
setToL1 hT (c • f) = c • setToL1 hT f := by
rw [setToL1_eq_setToL1' hT h_smul, setToL1_eq_setToL1' hT h_smul]
exact ContinuousLinearMap.map_smul _ _ _
#align measure_theory.L1.set_to_L1_smul MeasureTheory.L1.setToL1_smul
theorem setToL1_simpleFunc_indicatorConst (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s < ∞) (x : E) :
setToL1 hT (simpleFunc.indicatorConst 1 hs hμs.ne x) = T s x := by
rw [setToL1_eq_setToL1SCLM]
exact setToL1S_indicatorConst (fun s => hT.eq_zero_of_measure_zero) hT.1 hs hμs x
#align measure_theory.L1.set_to_L1_simple_func_indicator_const MeasureTheory.L1.setToL1_simpleFunc_indicatorConst
theorem setToL1_indicatorConstLp (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : E) :
setToL1 hT (indicatorConstLp 1 hs hμs x) = T s x := by
rw [← Lp.simpleFunc.coe_indicatorConst hs hμs x]
exact setToL1_simpleFunc_indicatorConst hT hs hμs.lt_top x
#align measure_theory.L1.set_to_L1_indicator_const_Lp MeasureTheory.L1.setToL1_indicatorConstLp
theorem setToL1_const [IsFiniteMeasure μ] (hT : DominatedFinMeasAdditive μ T C) (x : E) :
setToL1 hT (indicatorConstLp 1 MeasurableSet.univ (measure_ne_top _ _) x) = T univ x :=
setToL1_indicatorConstLp hT MeasurableSet.univ (measure_ne_top _ _) x
#align measure_theory.L1.set_to_L1_const MeasureTheory.L1.setToL1_const
section Order
variable {G' G'' : Type*} [NormedLatticeAddCommGroup G''] [NormedSpace ℝ G''] [CompleteSpace G'']
[NormedLatticeAddCommGroup G'] [NormedSpace ℝ G']
theorem setToL1_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α →₁[μ] E) :
setToL1 hT f ≤ setToL1 hT' f := by
induction f using Lp.induction (hp_ne_top := one_ne_top) with
| @h_ind c s hs hμs =>
rw [setToL1_simpleFunc_indicatorConst hT hs hμs, setToL1_simpleFunc_indicatorConst hT' hs hμs]
exact hTT' s hs hμs c
| @h_add f g hf hg _ hf_le hg_le =>
rw [(setToL1 hT).map_add, (setToL1 hT').map_add]
exact add_le_add hf_le hg_le
| h_closed => exact isClosed_le (setToL1 hT).continuous (setToL1 hT').continuous
#align measure_theory.L1.set_to_L1_mono_left' MeasureTheory.L1.setToL1_mono_left'
theorem setToL1_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁[μ] E) : setToL1 hT f ≤ setToL1 hT' f :=
setToL1_mono_left' hT hT' (fun s _ _ x => hTT' s x) f
#align measure_theory.L1.set_to_L1_mono_left MeasureTheory.L1.setToL1_mono_left
theorem setToL1_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α →₁[μ] G'}
(hf : 0 ≤ f) : 0 ≤ setToL1 hT f := by
suffices ∀ f : { g : α →₁[μ] G' // 0 ≤ g }, 0 ≤ setToL1 hT f from
this (⟨f, hf⟩ : { g : α →₁[μ] G' // 0 ≤ g })
refine fun g =>
@isClosed_property { g : α →₁ₛ[μ] G' // 0 ≤ g } { g : α →₁[μ] G' // 0 ≤ g } _ _
(fun g => 0 ≤ setToL1 hT g)
(denseRange_coeSimpleFuncNonnegToLpNonneg 1 μ G' one_ne_top) ?_ ?_ g
· exact isClosed_le continuous_zero ((setToL1 hT).continuous.comp continuous_induced_dom)
· intro g
have : (coeSimpleFuncNonnegToLpNonneg 1 μ G' g : α →₁[μ] G') = (g : α →₁ₛ[μ] G') := rfl
rw [this, setToL1_eq_setToL1SCLM]
exact setToL1S_nonneg (fun s => hT.eq_zero_of_measure_zero) hT.1 hT_nonneg g.2
#align measure_theory.L1.set_to_L1_nonneg MeasureTheory.L1.setToL1_nonneg
theorem setToL1_mono {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α →₁[μ] G'}
(hfg : f ≤ g) : setToL1 hT f ≤ setToL1 hT g := by
rw [← sub_nonneg] at hfg ⊢
rw [← (setToL1 hT).map_sub]
exact setToL1_nonneg hT hT_nonneg hfg
#align measure_theory.L1.set_to_L1_mono MeasureTheory.L1.setToL1_mono
end Order
theorem norm_setToL1_le_norm_setToL1SCLM (hT : DominatedFinMeasAdditive μ T C) :
‖setToL1 hT‖ ≤ ‖setToL1SCLM α E μ hT‖ :=
calc
‖setToL1 hT‖ ≤ (1 : ℝ≥0) * ‖setToL1SCLM α E μ hT‖ := by
refine
ContinuousLinearMap.opNorm_extend_le (setToL1SCLM α E μ hT) (coeToLp α E ℝ)
(simpleFunc.denseRange one_ne_top) fun x => le_of_eq ?_
rw [NNReal.coe_one, one_mul]
rfl
_ = ‖setToL1SCLM α E μ hT‖ := by rw [NNReal.coe_one, one_mul]
#align measure_theory.L1.norm_set_to_L1_le_norm_set_to_L1s_clm MeasureTheory.L1.norm_setToL1_le_norm_setToL1SCLM
theorem norm_setToL1_le_mul_norm (hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C)
(f : α →₁[μ] E) : ‖setToL1 hT f‖ ≤ C * ‖f‖ :=
calc
‖setToL1 hT f‖ ≤ ‖setToL1SCLM α E μ hT‖ * ‖f‖ :=
ContinuousLinearMap.le_of_opNorm_le _ (norm_setToL1_le_norm_setToL1SCLM hT) _
_ ≤ C * ‖f‖ := mul_le_mul (norm_setToL1SCLM_le hT hC) le_rfl (norm_nonneg _) hC
#align measure_theory.L1.norm_set_to_L1_le_mul_norm MeasureTheory.L1.norm_setToL1_le_mul_norm
theorem norm_setToL1_le_mul_norm' (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) :
‖setToL1 hT f‖ ≤ max C 0 * ‖f‖ :=
calc
‖setToL1 hT f‖ ≤ ‖setToL1SCLM α E μ hT‖ * ‖f‖ :=
ContinuousLinearMap.le_of_opNorm_le _ (norm_setToL1_le_norm_setToL1SCLM hT) _
_ ≤ max C 0 * ‖f‖ :=
mul_le_mul (norm_setToL1SCLM_le' hT) le_rfl (norm_nonneg _) (le_max_right _ _)
#align measure_theory.L1.norm_set_to_L1_le_mul_norm' MeasureTheory.L1.norm_setToL1_le_mul_norm'
theorem norm_setToL1_le (hT : DominatedFinMeasAdditive μ T C) (hC : 0 ≤ C) : ‖setToL1 hT‖ ≤ C :=
ContinuousLinearMap.opNorm_le_bound _ hC (norm_setToL1_le_mul_norm hT hC)
#align measure_theory.L1.norm_set_to_L1_le MeasureTheory.L1.norm_setToL1_le
theorem norm_setToL1_le' (hT : DominatedFinMeasAdditive μ T C) : ‖setToL1 hT‖ ≤ max C 0 :=
ContinuousLinearMap.opNorm_le_bound _ (le_max_right _ _) (norm_setToL1_le_mul_norm' hT)
#align measure_theory.L1.norm_set_to_L1_le' MeasureTheory.L1.norm_setToL1_le'
theorem setToL1_lipschitz (hT : DominatedFinMeasAdditive μ T C) :
LipschitzWith (Real.toNNReal C) (setToL1 hT) :=
(setToL1 hT).lipschitz.weaken (norm_setToL1_le' hT)
#align measure_theory.L1.set_to_L1_lipschitz MeasureTheory.L1.setToL1_lipschitz
/-- If `fs i → f` in `L1`, then `setToL1 hT (fs i) → setToL1 hT f`. -/
theorem tendsto_setToL1 (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) {ι}
(fs : ι → α →₁[μ] E) {l : Filter ι} (hfs : Tendsto fs l (𝓝 f)) :
Tendsto (fun i => setToL1 hT (fs i)) l (𝓝 <| setToL1 hT f) :=
((setToL1 hT).continuous.tendsto _).comp hfs
#align measure_theory.L1.tendsto_set_to_L1 MeasureTheory.L1.tendsto_setToL1
end SetToL1
end L1
section Function
set_option linter.uppercaseLean3 false
variable [CompleteSpace F] {T T' T'' : Set α → E →L[ℝ] F} {C C' C'' : ℝ} {f g : α → E}
variable (μ T)
/-- Extend `T : Set α → E →L[ℝ] F` to `(α → E) → F` (for integrable functions `α → E`). We set it to
0 if the function is not integrable. -/
def setToFun (hT : DominatedFinMeasAdditive μ T C) (f : α → E) : F :=
if hf : Integrable f μ then L1.setToL1 hT (hf.toL1 f) else 0
#align measure_theory.set_to_fun MeasureTheory.setToFun
variable {μ T}
theorem setToFun_eq (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) :
setToFun μ T hT f = L1.setToL1 hT (hf.toL1 f) :=
dif_pos hf
#align measure_theory.set_to_fun_eq MeasureTheory.setToFun_eq
theorem L1.setToFun_eq_setToL1 (hT : DominatedFinMeasAdditive μ T C) (f : α →₁[μ] E) :
setToFun μ T hT f = L1.setToL1 hT f := by
rw [setToFun_eq hT (L1.integrable_coeFn f), Integrable.toL1_coeFn]
#align measure_theory.L1.set_to_fun_eq_set_to_L1 MeasureTheory.L1.setToFun_eq_setToL1
theorem setToFun_undef (hT : DominatedFinMeasAdditive μ T C) (hf : ¬Integrable f μ) :
setToFun μ T hT f = 0 :=
dif_neg hf
#align measure_theory.set_to_fun_undef MeasureTheory.setToFun_undef
theorem setToFun_non_aEStronglyMeasurable (hT : DominatedFinMeasAdditive μ T C)
(hf : ¬AEStronglyMeasurable f μ) : setToFun μ T hT f = 0 :=
setToFun_undef hT (not_and_of_not_left _ hf)
#align measure_theory.set_to_fun_non_ae_strongly_measurable MeasureTheory.setToFun_non_aEStronglyMeasurable
theorem setToFun_congr_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : T = T') (f : α → E) :
setToFun μ T hT f = setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_congr_left T T' hT hT' h]
· simp_rw [setToFun_undef _ hf]
#align measure_theory.set_to_fun_congr_left MeasureTheory.setToFun_congr_left
theorem setToFun_congr_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (h : ∀ s, MeasurableSet s → μ s < ∞ → T s = T' s)
(f : α → E) : setToFun μ T hT f = setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_congr_left' T T' hT hT' h]
· simp_rw [setToFun_undef _ hf]
#align measure_theory.set_to_fun_congr_left' MeasureTheory.setToFun_congr_left'
theorem setToFun_add_left (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (f : α → E) :
setToFun μ (T + T') (hT.add hT') f = setToFun μ T hT f + setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_add_left hT hT']
· simp_rw [setToFun_undef _ hf, add_zero]
#align measure_theory.set_to_fun_add_left MeasureTheory.setToFun_add_left
theorem setToFun_add_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (hT'' : DominatedFinMeasAdditive μ T'' C'')
(h_add : ∀ s, MeasurableSet s → μ s < ∞ → T'' s = T s + T' s) (f : α → E) :
setToFun μ T'' hT'' f = setToFun μ T hT f + setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_add_left' hT hT' hT'' h_add]
· simp_rw [setToFun_undef _ hf, add_zero]
#align measure_theory.set_to_fun_add_left' MeasureTheory.setToFun_add_left'
theorem setToFun_smul_left (hT : DominatedFinMeasAdditive μ T C) (c : ℝ) (f : α → E) :
setToFun μ (fun s => c • T s) (hT.smul c) f = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_smul_left hT c]
· simp_rw [setToFun_undef _ hf, smul_zero]
#align measure_theory.set_to_fun_smul_left MeasureTheory.setToFun_smul_left
theorem setToFun_smul_left' (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ T' C') (c : ℝ)
(h_smul : ∀ s, MeasurableSet s → μ s < ∞ → T' s = c • T s) (f : α → E) :
setToFun μ T' hT' f = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf, L1.setToL1_smul_left' hT hT' c h_smul]
· simp_rw [setToFun_undef _ hf, smul_zero]
#align measure_theory.set_to_fun_smul_left' MeasureTheory.setToFun_smul_left'
@[simp]
theorem setToFun_zero (hT : DominatedFinMeasAdditive μ T C) : setToFun μ T hT (0 : α → E) = 0 := by
erw [setToFun_eq hT (integrable_zero _ _ _), Integrable.toL1_zero, ContinuousLinearMap.map_zero]
#align measure_theory.set_to_fun_zero MeasureTheory.setToFun_zero
@[simp]
theorem setToFun_zero_left {hT : DominatedFinMeasAdditive μ (0 : Set α → E →L[ℝ] F) C} :
setToFun μ 0 hT f = 0 := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf]; exact L1.setToL1_zero_left hT _
· exact setToFun_undef hT hf
#align measure_theory.set_to_fun_zero_left MeasureTheory.setToFun_zero_left
theorem setToFun_zero_left' (hT : DominatedFinMeasAdditive μ T C)
(h_zero : ∀ s, MeasurableSet s → μ s < ∞ → T s = 0) : setToFun μ T hT f = 0 := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf]; exact L1.setToL1_zero_left' hT h_zero _
· exact setToFun_undef hT hf
#align measure_theory.set_to_fun_zero_left' MeasureTheory.setToFun_zero_left'
theorem setToFun_add (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ)
(hg : Integrable g μ) : setToFun μ T hT (f + g) = setToFun μ T hT f + setToFun μ T hT g := by
rw [setToFun_eq hT (hf.add hg), setToFun_eq hT hf, setToFun_eq hT hg, Integrable.toL1_add,
(L1.setToL1 hT).map_add]
#align measure_theory.set_to_fun_add MeasureTheory.setToFun_add
theorem setToFun_finset_sum' (hT : DominatedFinMeasAdditive μ T C) {ι} (s : Finset ι)
{f : ι → α → E} (hf : ∀ i ∈ s, Integrable (f i) μ) :
setToFun μ T hT (∑ i ∈ s, f i) = ∑ i ∈ s, setToFun μ T hT (f i) := by
revert hf
refine Finset.induction_on s ?_ ?_
· intro _
simp only [setToFun_zero, Finset.sum_empty]
· intro i s his ih hf
simp only [his, Finset.sum_insert, not_false_iff]
rw [setToFun_add hT (hf i (Finset.mem_insert_self i s)) _]
· rw [ih fun i hi => hf i (Finset.mem_insert_of_mem hi)]
· convert integrable_finset_sum s fun i hi => hf i (Finset.mem_insert_of_mem hi) with x
simp
#align measure_theory.set_to_fun_finset_sum' MeasureTheory.setToFun_finset_sum'
theorem setToFun_finset_sum (hT : DominatedFinMeasAdditive μ T C) {ι} (s : Finset ι) {f : ι → α → E}
(hf : ∀ i ∈ s, Integrable (f i) μ) :
(setToFun μ T hT fun a => ∑ i ∈ s, f i a) = ∑ i ∈ s, setToFun μ T hT (f i) := by
convert setToFun_finset_sum' hT s hf with a; simp
#align measure_theory.set_to_fun_finset_sum MeasureTheory.setToFun_finset_sum
theorem setToFun_neg (hT : DominatedFinMeasAdditive μ T C) (f : α → E) :
setToFun μ T hT (-f) = -setToFun μ T hT f := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf, setToFun_eq hT hf.neg, Integrable.toL1_neg,
(L1.setToL1 hT).map_neg]
· rw [setToFun_undef hT hf, setToFun_undef hT, neg_zero]
rwa [← integrable_neg_iff] at hf
#align measure_theory.set_to_fun_neg MeasureTheory.setToFun_neg
theorem setToFun_sub (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ)
(hg : Integrable g μ) : setToFun μ T hT (f - g) = setToFun μ T hT f - setToFun μ T hT g := by
rw [sub_eq_add_neg, sub_eq_add_neg, setToFun_add hT hf hg.neg, setToFun_neg hT g]
#align measure_theory.set_to_fun_sub MeasureTheory.setToFun_sub
theorem setToFun_smul [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace 𝕜 F]
(hT : DominatedFinMeasAdditive μ T C) (h_smul : ∀ c : 𝕜, ∀ s x, T s (c • x) = c • T s x) (c : 𝕜)
(f : α → E) : setToFun μ T hT (c • f) = c • setToFun μ T hT f := by
by_cases hf : Integrable f μ
· rw [setToFun_eq hT hf, setToFun_eq hT, Integrable.toL1_smul',
L1.setToL1_smul hT h_smul c _]
· by_cases hr : c = 0
· rw [hr]; simp
· have hf' : ¬Integrable (c • f) μ := by rwa [integrable_smul_iff hr f]
rw [setToFun_undef hT hf, setToFun_undef hT hf', smul_zero]
#align measure_theory.set_to_fun_smul MeasureTheory.setToFun_smul
theorem setToFun_congr_ae (hT : DominatedFinMeasAdditive μ T C) (h : f =ᵐ[μ] g) :
setToFun μ T hT f = setToFun μ T hT g := by
by_cases hfi : Integrable f μ
· have hgi : Integrable g μ := hfi.congr h
rw [setToFun_eq hT hfi, setToFun_eq hT hgi, (Integrable.toL1_eq_toL1_iff f g hfi hgi).2 h]
· have hgi : ¬Integrable g μ := by rw [integrable_congr h] at hfi; exact hfi
rw [setToFun_undef hT hfi, setToFun_undef hT hgi]
#align measure_theory.set_to_fun_congr_ae MeasureTheory.setToFun_congr_ae
theorem setToFun_measure_zero (hT : DominatedFinMeasAdditive μ T C) (h : μ = 0) :
setToFun μ T hT f = 0 := by
have : f =ᵐ[μ] 0 := by simp [h, EventuallyEq]
rw [setToFun_congr_ae hT this, setToFun_zero]
#align measure_theory.set_to_fun_measure_zero MeasureTheory.setToFun_measure_zero
theorem setToFun_measure_zero' (hT : DominatedFinMeasAdditive μ T C)
(h : ∀ s, MeasurableSet s → μ s < ∞ → μ s = 0) : setToFun μ T hT f = 0 :=
setToFun_zero_left' hT fun s hs hμs => hT.eq_zero_of_measure_zero hs (h s hs hμs)
#align measure_theory.set_to_fun_measure_zero' MeasureTheory.setToFun_measure_zero'
theorem setToFun_toL1 (hT : DominatedFinMeasAdditive μ T C) (hf : Integrable f μ) :
setToFun μ T hT (hf.toL1 f) = setToFun μ T hT f :=
setToFun_congr_ae hT hf.coeFn_toL1
#align measure_theory.set_to_fun_to_L1 MeasureTheory.setToFun_toL1
theorem setToFun_indicator_const (hT : DominatedFinMeasAdditive μ T C) {s : Set α}
(hs : MeasurableSet s) (hμs : μ s ≠ ∞) (x : E) :
setToFun μ T hT (s.indicator fun _ => x) = T s x := by
rw [setToFun_congr_ae hT (@indicatorConstLp_coeFn _ _ _ 1 _ _ _ hs hμs x).symm]
rw [L1.setToFun_eq_setToL1 hT]
exact L1.setToL1_indicatorConstLp hT hs hμs x
#align measure_theory.set_to_fun_indicator_const MeasureTheory.setToFun_indicator_const
theorem setToFun_const [IsFiniteMeasure μ] (hT : DominatedFinMeasAdditive μ T C) (x : E) :
(setToFun μ T hT fun _ => x) = T univ x := by
have : (fun _ : α => x) = Set.indicator univ fun _ => x := (indicator_univ _).symm
rw [this]
exact setToFun_indicator_const hT MeasurableSet.univ (measure_ne_top _ _) x
#align measure_theory.set_to_fun_const MeasureTheory.setToFun_const
section Order
variable {G' G'' : Type*} [NormedLatticeAddCommGroup G''] [NormedSpace ℝ G''] [CompleteSpace G'']
[NormedLatticeAddCommGroup G'] [NormedSpace ℝ G']
theorem setToFun_mono_left' {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, T s x ≤ T' s x) (f : α → E) :
setToFun μ T hT f ≤ setToFun μ T' hT' f := by
by_cases hf : Integrable f μ
· simp_rw [setToFun_eq _ hf]; exact L1.setToL1_mono_left' hT hT' hTT' _
· simp_rw [setToFun_undef _ hf]; rfl
#align measure_theory.set_to_fun_mono_left' MeasureTheory.setToFun_mono_left'
theorem setToFun_mono_left {T T' : Set α → E →L[ℝ] G''} {C C' : ℝ}
(hT : DominatedFinMeasAdditive μ T C) (hT' : DominatedFinMeasAdditive μ T' C')
(hTT' : ∀ s x, T s x ≤ T' s x) (f : α →₁[μ] E) : setToFun μ T hT f ≤ setToFun μ T' hT' f :=
setToFun_mono_left' hT hT' (fun s _ _ x => hTT' s x) f
#align measure_theory.set_to_fun_mono_left MeasureTheory.setToFun_mono_left
theorem setToFun_nonneg {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f : α → G'}
(hf : 0 ≤ᵐ[μ] f) : 0 ≤ setToFun μ T hT f := by
by_cases hfi : Integrable f μ
· simp_rw [setToFun_eq _ hfi]
refine L1.setToL1_nonneg hT hT_nonneg ?_
rw [← Lp.coeFn_le]
have h0 := Lp.coeFn_zero G' 1 μ
have h := Integrable.coeFn_toL1 hfi
filter_upwards [h0, h, hf] with _ h0a ha hfa
rw [h0a, ha]
exact hfa
· simp_rw [setToFun_undef _ hfi]; rfl
#align measure_theory.set_to_fun_nonneg MeasureTheory.setToFun_nonneg
theorem setToFun_mono {T : Set α → G' →L[ℝ] G''} {C : ℝ} (hT : DominatedFinMeasAdditive μ T C)
(hT_nonneg : ∀ s, MeasurableSet s → μ s < ∞ → ∀ x, 0 ≤ x → 0 ≤ T s x) {f g : α → G'}
(hf : Integrable f μ) (hg : Integrable g μ) (hfg : f ≤ᵐ[μ] g) :
setToFun μ T hT f ≤ setToFun μ T hT g := by
rw [← sub_nonneg, ← setToFun_sub hT hg hf]
refine setToFun_nonneg hT hT_nonneg (hfg.mono fun a ha => ?_)
rw [Pi.sub_apply, Pi.zero_apply, sub_nonneg]
exact ha
#align measure_theory.set_to_fun_mono MeasureTheory.setToFun_mono
end Order
@[continuity]
theorem continuous_setToFun (hT : DominatedFinMeasAdditive μ T C) :
Continuous fun f : α →₁[μ] E => setToFun μ T hT f := by
simp_rw [L1.setToFun_eq_setToL1 hT]; exact ContinuousLinearMap.continuous _
#align measure_theory.continuous_set_to_fun MeasureTheory.continuous_setToFun
/-- If `F i → f` in `L1`, then `setToFun μ T hT (F i) → setToFun μ T hT f`. -/
theorem tendsto_setToFun_of_L1 (hT : DominatedFinMeasAdditive μ T C) {ι} (f : α → E)
(hfi : Integrable f μ) {fs : ι → α → E} {l : Filter ι} (hfsi : ∀ᶠ i in l, Integrable (fs i) μ)
(hfs : Tendsto (fun i => ∫⁻ x, ‖fs i x - f x‖₊ ∂μ) l (𝓝 0)) :
Tendsto (fun i => setToFun μ T hT (fs i)) l (𝓝 <| setToFun μ T hT f) := by
classical
let f_lp := hfi.toL1 f
let F_lp i := if hFi : Integrable (fs i) μ then hFi.toL1 (fs i) else 0
have tendsto_L1 : Tendsto F_lp l (𝓝 f_lp) := by
rw [Lp.tendsto_Lp_iff_tendsto_ℒp']
simp_rw [snorm_one_eq_lintegral_nnnorm, Pi.sub_apply]
refine (tendsto_congr' ?_).mp hfs
filter_upwards [hfsi] with i hi
refine lintegral_congr_ae ?_
filter_upwards [hi.coeFn_toL1, hfi.coeFn_toL1] with x hxi hxf
simp_rw [F_lp, dif_pos hi, hxi, hxf]
suffices Tendsto (fun i => setToFun μ T hT (F_lp i)) l (𝓝 (setToFun μ T hT f)) by
refine (tendsto_congr' ?_).mp this
filter_upwards [hfsi] with i hi
suffices h_ae_eq : F_lp i =ᵐ[μ] fs i from setToFun_congr_ae hT h_ae_eq
simp_rw [F_lp, dif_pos hi]
exact hi.coeFn_toL1
rw [setToFun_congr_ae hT hfi.coeFn_toL1.symm]
exact ((continuous_setToFun hT).tendsto f_lp).comp tendsto_L1
#align measure_theory.tendsto_set_to_fun_of_L1 MeasureTheory.tendsto_setToFun_of_L1
theorem tendsto_setToFun_approxOn_of_measurable (hT : DominatedFinMeasAdditive μ T C)
[MeasurableSpace E] [BorelSpace E] {f : α → E} {s : Set E} [SeparableSpace s]
(hfi : Integrable f μ) (hfm : Measurable f) (hs : ∀ᵐ x ∂μ, f x ∈ closure s) {y₀ : E}
(h₀ : y₀ ∈ s) (h₀i : Integrable (fun _ => y₀) μ) :
Tendsto (fun n => setToFun μ T hT (SimpleFunc.approxOn f hfm s y₀ h₀ n)) atTop
(𝓝 <| setToFun μ T hT f) :=
tendsto_setToFun_of_L1 hT _ hfi
(eventually_of_forall (SimpleFunc.integrable_approxOn hfm hfi h₀ h₀i))
(SimpleFunc.tendsto_approxOn_L1_nnnorm hfm _ hs (hfi.sub h₀i).2)
#align measure_theory.tendsto_set_to_fun_approx_on_of_measurable MeasureTheory.tendsto_setToFun_approxOn_of_measurable
theorem tendsto_setToFun_approxOn_of_measurable_of_range_subset
(hT : DominatedFinMeasAdditive μ T C) [MeasurableSpace E] [BorelSpace E] {f : α → E}
(fmeas : Measurable f) (hf : Integrable f μ) (s : Set E) [SeparableSpace s]
(hs : range f ∪ {0} ⊆ s) :
Tendsto (fun n => setToFun μ T hT (SimpleFunc.approxOn f fmeas s 0 (hs <| by simp) n)) atTop
(𝓝 <| setToFun μ T hT f) := by
refine tendsto_setToFun_approxOn_of_measurable hT hf fmeas ?_ _ (integrable_zero _ _ _)
exact eventually_of_forall fun x => subset_closure (hs (Set.mem_union_left _ (mem_range_self _)))
#align measure_theory.tendsto_set_to_fun_approx_on_of_measurable_of_range_subset MeasureTheory.tendsto_setToFun_approxOn_of_measurable_of_range_subset
/-- Auxiliary lemma for `setToFun_congr_measure`: the function sending `f : α →₁[μ] G` to
`f : α →₁[μ'] G` is continuous when `μ' ≤ c' • μ` for `c' ≠ ∞`. -/
theorem continuous_L1_toL1 {μ' : Measure α} (c' : ℝ≥0∞) (hc' : c' ≠ ∞) (hμ'_le : μ' ≤ c' • μ) :
Continuous fun f : α →₁[μ] G =>
(Integrable.of_measure_le_smul c' hc' hμ'_le (L1.integrable_coeFn f)).toL1 f := by
by_cases hc'0 : c' = 0
· have hμ'0 : μ' = 0 := by rw [← Measure.nonpos_iff_eq_zero']; refine hμ'_le.trans ?_; simp [hc'0]
have h_im_zero :
(fun f : α →₁[μ] G =>
(Integrable.of_measure_le_smul c' hc' hμ'_le (L1.integrable_coeFn f)).toL1 f) =
0 := by
ext1 f; ext1; simp_rw [hμ'0]; simp only [ae_zero, EventuallyEq, eventually_bot]
rw [h_im_zero]
exact continuous_zero
rw [Metric.continuous_iff]
intro f ε hε_pos
use ε / 2 / c'.toReal
refine ⟨div_pos (half_pos hε_pos) (toReal_pos hc'0 hc'), ?_⟩
intro g hfg
rw [Lp.dist_def] at hfg ⊢
let h_int := fun f' : α →₁[μ] G => (L1.integrable_coeFn f').of_measure_le_smul c' hc' hμ'_le
have :
snorm (⇑(Integrable.toL1 g (h_int g)) - ⇑(Integrable.toL1 f (h_int f))) 1 μ' =
snorm (⇑g - ⇑f) 1 μ' :=
snorm_congr_ae ((Integrable.coeFn_toL1 _).sub (Integrable.coeFn_toL1 _))
rw [this]
have h_snorm_ne_top : snorm (⇑g - ⇑f) 1 μ ≠ ∞ := by
rw [← snorm_congr_ae (Lp.coeFn_sub _ _)]; exact Lp.snorm_ne_top _
have h_snorm_ne_top' : snorm (⇑g - ⇑f) 1 μ' ≠ ∞ := by
refine ((snorm_mono_measure _ hμ'_le).trans_lt ?_).ne
rw [snorm_smul_measure_of_ne_zero hc'0, smul_eq_mul]
refine ENNReal.mul_lt_top ?_ h_snorm_ne_top
simp [hc', hc'0]
calc
(snorm (⇑g - ⇑f) 1 μ').toReal ≤ (c' * snorm (⇑g - ⇑f) 1 μ).toReal := by
rw [toReal_le_toReal h_snorm_ne_top' (ENNReal.mul_ne_top hc' h_snorm_ne_top)]
refine (snorm_mono_measure (⇑g - ⇑f) hμ'_le).trans ?_
rw [snorm_smul_measure_of_ne_zero hc'0, smul_eq_mul]
simp
_ = c'.toReal * (snorm (⇑g - ⇑f) 1 μ).toReal := toReal_mul
_ ≤ c'.toReal * (ε / 2 / c'.toReal) :=
(mul_le_mul le_rfl hfg.le toReal_nonneg toReal_nonneg)
_ = ε / 2 := by
refine mul_div_cancel₀ (ε / 2) ?_; rw [Ne, toReal_eq_zero_iff]; simp [hc', hc'0]
_ < ε := half_lt_self hε_pos
#align measure_theory.continuous_L1_to_L1 MeasureTheory.continuous_L1_toL1
theorem setToFun_congr_measure_of_integrable {μ' : Measure α} (c' : ℝ≥0∞) (hc' : c' ≠ ∞)
(hμ'_le : μ' ≤ c' • μ) (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ' T C') (f : α → E) (hfμ : Integrable f μ) :
setToFun μ T hT f = setToFun μ' T hT' f := by
-- integrability for `μ` implies integrability for `μ'`.
have h_int : ∀ g : α → E, Integrable g μ → Integrable g μ' := fun g hg =>
Integrable.of_measure_le_smul c' hc' hμ'_le hg
-- We use `Integrable.induction`
apply hfμ.induction (P := fun f => setToFun μ T hT f = setToFun μ' T hT' f)
· intro c s hs hμs
have hμ's : μ' s ≠ ∞ := by
refine ((hμ'_le s).trans_lt ?_).ne
rw [Measure.smul_apply, smul_eq_mul]
exact ENNReal.mul_lt_top hc' hμs.ne
rw [setToFun_indicator_const hT hs hμs.ne, setToFun_indicator_const hT' hs hμ's]
· intro f₂ g₂ _ hf₂ hg₂ h_eq_f h_eq_g
rw [setToFun_add hT hf₂ hg₂, setToFun_add hT' (h_int f₂ hf₂) (h_int g₂ hg₂), h_eq_f, h_eq_g]
· refine isClosed_eq (continuous_setToFun hT) ?_
have :
(fun f : α →₁[μ] E => setToFun μ' T hT' f) = fun f : α →₁[μ] E =>
setToFun μ' T hT' ((h_int f (L1.integrable_coeFn f)).toL1 f) := by
ext1 f; exact setToFun_congr_ae hT' (Integrable.coeFn_toL1 _).symm
rw [this]
exact (continuous_setToFun hT').comp (continuous_L1_toL1 c' hc' hμ'_le)
· intro f₂ g₂ hfg _ hf_eq
have hfg' : f₂ =ᵐ[μ'] g₂ := (Measure.absolutelyContinuous_of_le_smul hμ'_le).ae_eq hfg
rw [← setToFun_congr_ae hT hfg, hf_eq, setToFun_congr_ae hT' hfg']
#align measure_theory.set_to_fun_congr_measure_of_integrable MeasureTheory.setToFun_congr_measure_of_integrable
| Mathlib/MeasureTheory/Integral/SetToL1.lean | 1,624 | 1,633 | theorem setToFun_congr_measure {μ' : Measure α} (c c' : ℝ≥0∞) (hc : c ≠ ∞) (hc' : c' ≠ ∞)
(hμ_le : μ ≤ c • μ') (hμ'_le : μ' ≤ c' • μ) (hT : DominatedFinMeasAdditive μ T C)
(hT' : DominatedFinMeasAdditive μ' T C') (f : α → E) :
setToFun μ T hT f = setToFun μ' T hT' f := by |
by_cases hf : Integrable f μ
· exact setToFun_congr_measure_of_integrable c' hc' hμ'_le hT hT' f hf
· -- if `f` is not integrable, both `setToFun` are 0.
have h_int : ∀ g : α → E, ¬Integrable g μ → ¬Integrable g μ' := fun g =>
mt fun h => h.of_measure_le_smul _ hc hμ_le
simp_rw [setToFun_undef _ hf, setToFun_undef _ (h_int f hf)]
|
/-
Copyright (c) 2014 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura, Floris van Doorn, Yury Kudryashov, Neil Strickland
-/
import Mathlib.Algebra.Group.Semiconj.Defs
import Mathlib.Algebra.Ring.Defs
#align_import algebra.ring.semiconj from "leanprover-community/mathlib"@"70d50ecfd4900dd6d328da39ab7ebd516abe4025"
/-!
# Semirings and rings
This file gives lemmas about semirings, rings and domains.
This is analogous to `Mathlib.Algebra.Group.Basic`,
the difference being that the former is about `+` and `*` separately, while
the present file is about their interaction.
For the definitions of semirings and rings see `Mathlib.Algebra.Ring.Defs`.
-/
universe u v w x
variable {α : Type u} {β : Type v} {γ : Type w} {R : Type x}
open Function
namespace SemiconjBy
@[simp]
theorem add_right [Distrib R] {a x y x' y' : R} (h : SemiconjBy a x y) (h' : SemiconjBy a x' y') :
SemiconjBy a (x + x') (y + y') := by
simp only [SemiconjBy, left_distrib, right_distrib, h.eq, h'.eq]
#align semiconj_by.add_right SemiconjBy.add_right
@[simp]
| Mathlib/Algebra/Ring/Semiconj.lean | 39 | 41 | theorem add_left [Distrib R] {a b x y : R} (ha : SemiconjBy a x y) (hb : SemiconjBy b x y) :
SemiconjBy (a + b) x y := by |
simp only [SemiconjBy, left_distrib, right_distrib, ha.eq, hb.eq]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Jeremy Avigad
-/
import Mathlib.Algebra.Order.Ring.Defs
import Mathlib.Data.Set.Finite
#align_import order.filter.basic from "leanprover-community/mathlib"@"d4f691b9e5f94cfc64639973f3544c95f8d5d494"
/-!
# Theory of filters on sets
## Main definitions
* `Filter` : filters on a set;
* `Filter.principal` : filter of all sets containing a given set;
* `Filter.map`, `Filter.comap` : operations on filters;
* `Filter.Tendsto` : limit with respect to filters;
* `Filter.Eventually` : `f.eventually p` means `{x | p x} ∈ f`;
* `Filter.Frequently` : `f.frequently p` means `{x | ¬p x} ∉ f`;
* `filter_upwards [h₁, ..., hₙ]` :
a tactic that takes a list of proofs `hᵢ : sᵢ ∈ f`,
and replaces a goal `s ∈ f` with `∀ x, x ∈ s₁ → ... → x ∈ sₙ → x ∈ s`;
* `Filter.NeBot f` : a utility class stating that `f` is a non-trivial filter.
Filters on a type `X` are sets of sets of `X` satisfying three conditions. They are mostly used to
abstract two related kinds of ideas:
* *limits*, including finite or infinite limits of sequences, finite or infinite limits of functions
at a point or at infinity, etc...
* *things happening eventually*, including things happening for large enough `n : ℕ`, or near enough
a point `x`, or for close enough pairs of points, or things happening almost everywhere in the
sense of measure theory. Dually, filters can also express the idea of *things happening often*:
for arbitrarily large `n`, or at a point in any neighborhood of given a point etc...
In this file, we define the type `Filter X` of filters on `X`, and endow it with a complete lattice
structure. This structure is lifted from the lattice structure on `Set (Set X)` using the Galois
insertion which maps a filter to its elements in one direction, and an arbitrary set of sets to
the smallest filter containing it in the other direction.
We also prove `Filter` is a monadic functor, with a push-forward operation
`Filter.map` and a pull-back operation `Filter.comap` that form a Galois connections for the
order on filters.
The examples of filters appearing in the description of the two motivating ideas are:
* `(Filter.atTop : Filter ℕ)` : made of sets of `ℕ` containing `{n | n ≥ N}` for some `N`
* `𝓝 x` : made of neighborhoods of `x` in a topological space (defined in topology.basic)
* `𝓤 X` : made of entourages of a uniform space (those space are generalizations of metric spaces
defined in `Mathlib/Topology/UniformSpace/Basic.lean`)
* `MeasureTheory.ae` : made of sets whose complement has zero measure with respect to `μ`
(defined in `Mathlib/MeasureTheory/OuterMeasure/AE`)
The general notion of limit of a map with respect to filters on the source and target types
is `Filter.Tendsto`. It is defined in terms of the order and the push-forward operation.
The predicate "happening eventually" is `Filter.Eventually`, and "happening often" is
`Filter.Frequently`, whose definitions are immediate after `Filter` is defined (but they come
rather late in this file in order to immediately relate them to the lattice structure).
For instance, anticipating on Topology.Basic, the statement: "if a sequence `u` converges to
some `x` and `u n` belongs to a set `M` for `n` large enough then `x` is in the closure of
`M`" is formalized as: `Tendsto u atTop (𝓝 x) → (∀ᶠ n in atTop, u n ∈ M) → x ∈ closure M`,
which is a special case of `mem_closure_of_tendsto` from Topology.Basic.
## Notations
* `∀ᶠ x in f, p x` : `f.Eventually p`;
* `∃ᶠ x in f, p x` : `f.Frequently p`;
* `f =ᶠ[l] g` : `∀ᶠ x in l, f x = g x`;
* `f ≤ᶠ[l] g` : `∀ᶠ x in l, f x ≤ g x`;
* `𝓟 s` : `Filter.Principal s`, localized in `Filter`.
## References
* [N. Bourbaki, *General Topology*][bourbaki1966]
Important note: Bourbaki requires that a filter on `X` cannot contain all sets of `X`, which
we do *not* require. This gives `Filter X` better formal properties, in particular a bottom element
`⊥` for its lattice structure, at the cost of including the assumption
`[NeBot f]` in a number of lemmas and definitions.
-/
set_option autoImplicit true
open Function Set Order
open scoped Classical
universe u v w x y
/-- A filter `F` on a type `α` is a collection of sets of `α` which contains the whole `α`,
is upwards-closed, and is stable under intersection. We do not forbid this collection to be
all sets of `α`. -/
structure Filter (α : Type*) where
/-- The set of sets that belong to the filter. -/
sets : Set (Set α)
/-- The set `Set.univ` belongs to any filter. -/
univ_sets : Set.univ ∈ sets
/-- If a set belongs to a filter, then its superset belongs to the filter as well. -/
sets_of_superset {x y} : x ∈ sets → x ⊆ y → y ∈ sets
/-- If two sets belong to a filter, then their intersection belongs to the filter as well. -/
inter_sets {x y} : x ∈ sets → y ∈ sets → x ∩ y ∈ sets
#align filter Filter
/-- If `F` is a filter on `α`, and `U` a subset of `α` then we can write `U ∈ F` as on paper. -/
instance {α : Type*} : Membership (Set α) (Filter α) :=
⟨fun U F => U ∈ F.sets⟩
namespace Filter
variable {α : Type u} {f g : Filter α} {s t : Set α}
@[simp]
protected theorem mem_mk {t : Set (Set α)} {h₁ h₂ h₃} : s ∈ mk t h₁ h₂ h₃ ↔ s ∈ t :=
Iff.rfl
#align filter.mem_mk Filter.mem_mk
@[simp]
protected theorem mem_sets : s ∈ f.sets ↔ s ∈ f :=
Iff.rfl
#align filter.mem_sets Filter.mem_sets
instance inhabitedMem : Inhabited { s : Set α // s ∈ f } :=
⟨⟨univ, f.univ_sets⟩⟩
#align filter.inhabited_mem Filter.inhabitedMem
theorem filter_eq : ∀ {f g : Filter α}, f.sets = g.sets → f = g
| ⟨_, _, _, _⟩, ⟨_, _, _, _⟩, rfl => rfl
#align filter.filter_eq Filter.filter_eq
theorem filter_eq_iff : f = g ↔ f.sets = g.sets :=
⟨congr_arg _, filter_eq⟩
#align filter.filter_eq_iff Filter.filter_eq_iff
protected theorem ext_iff : f = g ↔ ∀ s, s ∈ f ↔ s ∈ g := by
simp only [filter_eq_iff, ext_iff, Filter.mem_sets]
#align filter.ext_iff Filter.ext_iff
@[ext]
protected theorem ext : (∀ s, s ∈ f ↔ s ∈ g) → f = g :=
Filter.ext_iff.2
#align filter.ext Filter.ext
/-- An extensionality lemma that is useful for filters with good lemmas about `sᶜ ∈ f` (e.g.,
`Filter.comap`, `Filter.coprod`, `Filter.Coprod`, `Filter.cofinite`). -/
protected theorem coext (h : ∀ s, sᶜ ∈ f ↔ sᶜ ∈ g) : f = g :=
Filter.ext <| compl_surjective.forall.2 h
#align filter.coext Filter.coext
@[simp]
theorem univ_mem : univ ∈ f :=
f.univ_sets
#align filter.univ_mem Filter.univ_mem
theorem mem_of_superset {x y : Set α} (hx : x ∈ f) (hxy : x ⊆ y) : y ∈ f :=
f.sets_of_superset hx hxy
#align filter.mem_of_superset Filter.mem_of_superset
instance : Trans (· ⊇ ·) ((· ∈ ·) : Set α → Filter α → Prop) (· ∈ ·) where
trans h₁ h₂ := mem_of_superset h₂ h₁
theorem inter_mem {s t : Set α} (hs : s ∈ f) (ht : t ∈ f) : s ∩ t ∈ f :=
f.inter_sets hs ht
#align filter.inter_mem Filter.inter_mem
@[simp]
theorem inter_mem_iff {s t : Set α} : s ∩ t ∈ f ↔ s ∈ f ∧ t ∈ f :=
⟨fun h => ⟨mem_of_superset h inter_subset_left, mem_of_superset h inter_subset_right⟩,
and_imp.2 inter_mem⟩
#align filter.inter_mem_iff Filter.inter_mem_iff
theorem diff_mem {s t : Set α} (hs : s ∈ f) (ht : tᶜ ∈ f) : s \ t ∈ f :=
inter_mem hs ht
#align filter.diff_mem Filter.diff_mem
theorem univ_mem' (h : ∀ a, a ∈ s) : s ∈ f :=
mem_of_superset univ_mem fun x _ => h x
#align filter.univ_mem' Filter.univ_mem'
theorem mp_mem (hs : s ∈ f) (h : { x | x ∈ s → x ∈ t } ∈ f) : t ∈ f :=
mem_of_superset (inter_mem hs h) fun _ ⟨h₁, h₂⟩ => h₂ h₁
#align filter.mp_mem Filter.mp_mem
theorem congr_sets (h : { x | x ∈ s ↔ x ∈ t } ∈ f) : s ∈ f ↔ t ∈ f :=
⟨fun hs => mp_mem hs (mem_of_superset h fun _ => Iff.mp), fun hs =>
mp_mem hs (mem_of_superset h fun _ => Iff.mpr)⟩
#align filter.congr_sets Filter.congr_sets
/-- Override `sets` field of a filter to provide better definitional equality. -/
protected def copy (f : Filter α) (S : Set (Set α)) (hmem : ∀ s, s ∈ S ↔ s ∈ f) : Filter α where
sets := S
univ_sets := (hmem _).2 univ_mem
sets_of_superset h hsub := (hmem _).2 <| mem_of_superset ((hmem _).1 h) hsub
inter_sets h₁ h₂ := (hmem _).2 <| inter_mem ((hmem _).1 h₁) ((hmem _).1 h₂)
lemma copy_eq {S} (hmem : ∀ s, s ∈ S ↔ s ∈ f) : f.copy S hmem = f := Filter.ext hmem
@[simp] lemma mem_copy {S hmem} : s ∈ f.copy S hmem ↔ s ∈ S := Iff.rfl
@[simp]
theorem biInter_mem {β : Type v} {s : β → Set α} {is : Set β} (hf : is.Finite) :
(⋂ i ∈ is, s i) ∈ f ↔ ∀ i ∈ is, s i ∈ f :=
Finite.induction_on hf (by simp) fun _ _ hs => by simp [hs]
#align filter.bInter_mem Filter.biInter_mem
@[simp]
theorem biInter_finset_mem {β : Type v} {s : β → Set α} (is : Finset β) :
(⋂ i ∈ is, s i) ∈ f ↔ ∀ i ∈ is, s i ∈ f :=
biInter_mem is.finite_toSet
#align filter.bInter_finset_mem Filter.biInter_finset_mem
alias _root_.Finset.iInter_mem_sets := biInter_finset_mem
#align finset.Inter_mem_sets Finset.iInter_mem_sets
-- attribute [protected] Finset.iInter_mem_sets porting note: doesn't work
@[simp]
theorem sInter_mem {s : Set (Set α)} (hfin : s.Finite) : ⋂₀ s ∈ f ↔ ∀ U ∈ s, U ∈ f := by
rw [sInter_eq_biInter, biInter_mem hfin]
#align filter.sInter_mem Filter.sInter_mem
@[simp]
theorem iInter_mem {β : Sort v} {s : β → Set α} [Finite β] : (⋂ i, s i) ∈ f ↔ ∀ i, s i ∈ f :=
(sInter_mem (finite_range _)).trans forall_mem_range
#align filter.Inter_mem Filter.iInter_mem
theorem exists_mem_subset_iff : (∃ t ∈ f, t ⊆ s) ↔ s ∈ f :=
⟨fun ⟨_, ht, ts⟩ => mem_of_superset ht ts, fun hs => ⟨s, hs, Subset.rfl⟩⟩
#align filter.exists_mem_subset_iff Filter.exists_mem_subset_iff
theorem monotone_mem {f : Filter α} : Monotone fun s => s ∈ f := fun _ _ hst h =>
mem_of_superset h hst
#align filter.monotone_mem Filter.monotone_mem
theorem exists_mem_and_iff {P : Set α → Prop} {Q : Set α → Prop} (hP : Antitone P)
(hQ : Antitone Q) : ((∃ u ∈ f, P u) ∧ ∃ u ∈ f, Q u) ↔ ∃ u ∈ f, P u ∧ Q u := by
constructor
· rintro ⟨⟨u, huf, hPu⟩, v, hvf, hQv⟩
exact
⟨u ∩ v, inter_mem huf hvf, hP inter_subset_left hPu, hQ inter_subset_right hQv⟩
· rintro ⟨u, huf, hPu, hQu⟩
exact ⟨⟨u, huf, hPu⟩, u, huf, hQu⟩
#align filter.exists_mem_and_iff Filter.exists_mem_and_iff
theorem forall_in_swap {β : Type*} {p : Set α → β → Prop} :
(∀ a ∈ f, ∀ (b), p a b) ↔ ∀ (b), ∀ a ∈ f, p a b :=
Set.forall_in_swap
#align filter.forall_in_swap Filter.forall_in_swap
end Filter
namespace Mathlib.Tactic
open Lean Meta Elab Tactic
/--
`filter_upwards [h₁, ⋯, hₙ]` replaces a goal of the form `s ∈ f` and terms
`h₁ : t₁ ∈ f, ⋯, hₙ : tₙ ∈ f` with `∀ x, x ∈ t₁ → ⋯ → x ∈ tₙ → x ∈ s`.
The list is an optional parameter, `[]` being its default value.
`filter_upwards [h₁, ⋯, hₙ] with a₁ a₂ ⋯ aₖ` is a short form for
`{ filter_upwards [h₁, ⋯, hₙ], intros a₁ a₂ ⋯ aₖ }`.
`filter_upwards [h₁, ⋯, hₙ] using e` is a short form for
`{ filter_upwards [h1, ⋯, hn], exact e }`.
Combining both shortcuts is done by writing `filter_upwards [h₁, ⋯, hₙ] with a₁ a₂ ⋯ aₖ using e`.
Note that in this case, the `aᵢ` terms can be used in `e`.
-/
syntax (name := filterUpwards) "filter_upwards" (" [" term,* "]")?
(" with" (ppSpace colGt term:max)*)? (" using " term)? : tactic
elab_rules : tactic
| `(tactic| filter_upwards $[[$[$args],*]]? $[with $wth*]? $[using $usingArg]?) => do
let config : ApplyConfig := {newGoals := ApplyNewGoals.nonDependentOnly}
for e in args.getD #[] |>.reverse do
let goal ← getMainGoal
replaceMainGoal <| ← goal.withContext <| runTermElab do
let m ← mkFreshExprMVar none
let lem ← Term.elabTermEnsuringType
(← ``(Filter.mp_mem $e $(← Term.exprToSyntax m))) (← goal.getType)
goal.assign lem
return [m.mvarId!]
liftMetaTactic fun goal => do
goal.apply (← mkConstWithFreshMVarLevels ``Filter.univ_mem') config
evalTactic <|← `(tactic| dsimp (config := {zeta := false}) only [Set.mem_setOf_eq])
if let some l := wth then
evalTactic <|← `(tactic| intro $[$l]*)
if let some e := usingArg then
evalTactic <|← `(tactic| exact $e)
end Mathlib.Tactic
namespace Filter
variable {α : Type u} {β : Type v} {γ : Type w} {δ : Type*} {ι : Sort x}
section Principal
/-- The principal filter of `s` is the collection of all supersets of `s`. -/
def principal (s : Set α) : Filter α where
sets := { t | s ⊆ t }
univ_sets := subset_univ s
sets_of_superset hx := Subset.trans hx
inter_sets := subset_inter
#align filter.principal Filter.principal
@[inherit_doc]
scoped notation "𝓟" => Filter.principal
@[simp] theorem mem_principal {s t : Set α} : s ∈ 𝓟 t ↔ t ⊆ s := Iff.rfl
#align filter.mem_principal Filter.mem_principal
theorem mem_principal_self (s : Set α) : s ∈ 𝓟 s := Subset.rfl
#align filter.mem_principal_self Filter.mem_principal_self
end Principal
open Filter
section Join
/-- The join of a filter of filters is defined by the relation `s ∈ join f ↔ {t | s ∈ t} ∈ f`. -/
def join (f : Filter (Filter α)) : Filter α where
sets := { s | { t : Filter α | s ∈ t } ∈ f }
univ_sets := by simp only [mem_setOf_eq, univ_sets, ← Filter.mem_sets, setOf_true]
sets_of_superset hx xy := mem_of_superset hx fun f h => mem_of_superset h xy
inter_sets hx hy := mem_of_superset (inter_mem hx hy) fun f ⟨h₁, h₂⟩ => inter_mem h₁ h₂
#align filter.join Filter.join
@[simp]
theorem mem_join {s : Set α} {f : Filter (Filter α)} : s ∈ join f ↔ { t | s ∈ t } ∈ f :=
Iff.rfl
#align filter.mem_join Filter.mem_join
end Join
section Lattice
variable {f g : Filter α} {s t : Set α}
instance : PartialOrder (Filter α) where
le f g := ∀ ⦃U : Set α⦄, U ∈ g → U ∈ f
le_antisymm a b h₁ h₂ := filter_eq <| Subset.antisymm h₂ h₁
le_refl a := Subset.rfl
le_trans a b c h₁ h₂ := Subset.trans h₂ h₁
theorem le_def : f ≤ g ↔ ∀ x ∈ g, x ∈ f :=
Iff.rfl
#align filter.le_def Filter.le_def
protected theorem not_le : ¬f ≤ g ↔ ∃ s ∈ g, s ∉ f := by simp_rw [le_def, not_forall, exists_prop]
#align filter.not_le Filter.not_le
/-- `GenerateSets g s`: `s` is in the filter closure of `g`. -/
inductive GenerateSets (g : Set (Set α)) : Set α → Prop
| basic {s : Set α} : s ∈ g → GenerateSets g s
| univ : GenerateSets g univ
| superset {s t : Set α} : GenerateSets g s → s ⊆ t → GenerateSets g t
| inter {s t : Set α} : GenerateSets g s → GenerateSets g t → GenerateSets g (s ∩ t)
#align filter.generate_sets Filter.GenerateSets
/-- `generate g` is the largest filter containing the sets `g`. -/
def generate (g : Set (Set α)) : Filter α where
sets := {s | GenerateSets g s}
univ_sets := GenerateSets.univ
sets_of_superset := GenerateSets.superset
inter_sets := GenerateSets.inter
#align filter.generate Filter.generate
lemma mem_generate_of_mem {s : Set <| Set α} {U : Set α} (h : U ∈ s) :
U ∈ generate s := GenerateSets.basic h
theorem le_generate_iff {s : Set (Set α)} {f : Filter α} : f ≤ generate s ↔ s ⊆ f.sets :=
Iff.intro (fun h _ hu => h <| GenerateSets.basic <| hu) fun h _ hu =>
hu.recOn (fun h' => h h') univ_mem (fun _ hxy hx => mem_of_superset hx hxy) fun _ _ hx hy =>
inter_mem hx hy
#align filter.sets_iff_generate Filter.le_generate_iff
theorem mem_generate_iff {s : Set <| Set α} {U : Set α} :
U ∈ generate s ↔ ∃ t ⊆ s, Set.Finite t ∧ ⋂₀ t ⊆ U := by
constructor <;> intro h
· induction h with
| @basic V V_in =>
exact ⟨{V}, singleton_subset_iff.2 V_in, finite_singleton _, (sInter_singleton _).subset⟩
| univ => exact ⟨∅, empty_subset _, finite_empty, subset_univ _⟩
| superset _ hVW hV =>
rcases hV with ⟨t, hts, ht, htV⟩
exact ⟨t, hts, ht, htV.trans hVW⟩
| inter _ _ hV hW =>
rcases hV, hW with ⟨⟨t, hts, ht, htV⟩, u, hus, hu, huW⟩
exact
⟨t ∪ u, union_subset hts hus, ht.union hu,
(sInter_union _ _).subset.trans <| inter_subset_inter htV huW⟩
· rcases h with ⟨t, hts, tfin, h⟩
exact mem_of_superset ((sInter_mem tfin).2 fun V hV => GenerateSets.basic <| hts hV) h
#align filter.mem_generate_iff Filter.mem_generate_iff
@[simp] lemma generate_singleton (s : Set α) : generate {s} = 𝓟 s :=
le_antisymm (fun _t ht ↦ mem_of_superset (mem_generate_of_mem <| mem_singleton _) ht) <|
le_generate_iff.2 <| singleton_subset_iff.2 Subset.rfl
/-- `mkOfClosure s hs` constructs a filter on `α` whose elements set is exactly
`s : Set (Set α)`, provided one gives the assumption `hs : (generate s).sets = s`. -/
protected def mkOfClosure (s : Set (Set α)) (hs : (generate s).sets = s) : Filter α where
sets := s
univ_sets := hs ▸ univ_mem
sets_of_superset := hs ▸ mem_of_superset
inter_sets := hs ▸ inter_mem
#align filter.mk_of_closure Filter.mkOfClosure
theorem mkOfClosure_sets {s : Set (Set α)} {hs : (generate s).sets = s} :
Filter.mkOfClosure s hs = generate s :=
Filter.ext fun u =>
show u ∈ (Filter.mkOfClosure s hs).sets ↔ u ∈ (generate s).sets from hs.symm ▸ Iff.rfl
#align filter.mk_of_closure_sets Filter.mkOfClosure_sets
/-- Galois insertion from sets of sets into filters. -/
def giGenerate (α : Type*) :
@GaloisInsertion (Set (Set α)) (Filter α)ᵒᵈ _ _ Filter.generate Filter.sets where
gc _ _ := le_generate_iff
le_l_u _ _ h := GenerateSets.basic h
choice s hs := Filter.mkOfClosure s (le_antisymm hs <| le_generate_iff.1 <| le_rfl)
choice_eq _ _ := mkOfClosure_sets
#align filter.gi_generate Filter.giGenerate
/-- The infimum of filters is the filter generated by intersections
of elements of the two filters. -/
instance : Inf (Filter α) :=
⟨fun f g : Filter α =>
{ sets := { s | ∃ a ∈ f, ∃ b ∈ g, s = a ∩ b }
univ_sets := ⟨_, univ_mem, _, univ_mem, by simp⟩
sets_of_superset := by
rintro x y ⟨a, ha, b, hb, rfl⟩ xy
refine
⟨a ∪ y, mem_of_superset ha subset_union_left, b ∪ y,
mem_of_superset hb subset_union_left, ?_⟩
rw [← inter_union_distrib_right, union_eq_self_of_subset_left xy]
inter_sets := by
rintro x y ⟨a, ha, b, hb, rfl⟩ ⟨c, hc, d, hd, rfl⟩
refine ⟨a ∩ c, inter_mem ha hc, b ∩ d, inter_mem hb hd, ?_⟩
ac_rfl }⟩
theorem mem_inf_iff {f g : Filter α} {s : Set α} : s ∈ f ⊓ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, s = t₁ ∩ t₂ :=
Iff.rfl
#align filter.mem_inf_iff Filter.mem_inf_iff
theorem mem_inf_of_left {f g : Filter α} {s : Set α} (h : s ∈ f) : s ∈ f ⊓ g :=
⟨s, h, univ, univ_mem, (inter_univ s).symm⟩
#align filter.mem_inf_of_left Filter.mem_inf_of_left
theorem mem_inf_of_right {f g : Filter α} {s : Set α} (h : s ∈ g) : s ∈ f ⊓ g :=
⟨univ, univ_mem, s, h, (univ_inter s).symm⟩
#align filter.mem_inf_of_right Filter.mem_inf_of_right
theorem inter_mem_inf {α : Type u} {f g : Filter α} {s t : Set α} (hs : s ∈ f) (ht : t ∈ g) :
s ∩ t ∈ f ⊓ g :=
⟨s, hs, t, ht, rfl⟩
#align filter.inter_mem_inf Filter.inter_mem_inf
theorem mem_inf_of_inter {f g : Filter α} {s t u : Set α} (hs : s ∈ f) (ht : t ∈ g)
(h : s ∩ t ⊆ u) : u ∈ f ⊓ g :=
mem_of_superset (inter_mem_inf hs ht) h
#align filter.mem_inf_of_inter Filter.mem_inf_of_inter
theorem mem_inf_iff_superset {f g : Filter α} {s : Set α} :
s ∈ f ⊓ g ↔ ∃ t₁ ∈ f, ∃ t₂ ∈ g, t₁ ∩ t₂ ⊆ s :=
⟨fun ⟨t₁, h₁, t₂, h₂, Eq⟩ => ⟨t₁, h₁, t₂, h₂, Eq ▸ Subset.rfl⟩, fun ⟨_, h₁, _, h₂, sub⟩ =>
mem_inf_of_inter h₁ h₂ sub⟩
#align filter.mem_inf_iff_superset Filter.mem_inf_iff_superset
instance : Top (Filter α) :=
⟨{ sets := { s | ∀ x, x ∈ s }
univ_sets := fun x => mem_univ x
sets_of_superset := fun hx hxy a => hxy (hx a)
inter_sets := fun hx hy _ => mem_inter (hx _) (hy _) }⟩
theorem mem_top_iff_forall {s : Set α} : s ∈ (⊤ : Filter α) ↔ ∀ x, x ∈ s :=
Iff.rfl
#align filter.mem_top_iff_forall Filter.mem_top_iff_forall
@[simp]
theorem mem_top {s : Set α} : s ∈ (⊤ : Filter α) ↔ s = univ := by
rw [mem_top_iff_forall, eq_univ_iff_forall]
#align filter.mem_top Filter.mem_top
section CompleteLattice
/- We lift the complete lattice along the Galois connection `generate` / `sets`. Unfortunately,
we want to have different definitional equalities for some lattice operations. So we define them
upfront and change the lattice operations for the complete lattice instance. -/
instance instCompleteLatticeFilter : CompleteLattice (Filter α) :=
{ @OrderDual.instCompleteLattice _ (giGenerate α).liftCompleteLattice with
le := (· ≤ ·)
top := ⊤
le_top := fun _ _s hs => (mem_top.1 hs).symm ▸ univ_mem
inf := (· ⊓ ·)
inf_le_left := fun _ _ _ => mem_inf_of_left
inf_le_right := fun _ _ _ => mem_inf_of_right
le_inf := fun _ _ _ h₁ h₂ _s ⟨_a, ha, _b, hb, hs⟩ => hs.symm ▸ inter_mem (h₁ ha) (h₂ hb)
sSup := join ∘ 𝓟
le_sSup := fun _ _f hf _s hs => hs hf
sSup_le := fun _ _f hf _s hs _g hg => hf _ hg hs }
instance : Inhabited (Filter α) := ⟨⊥⟩
end CompleteLattice
/-- A filter is `NeBot` if it is not equal to `⊥`, or equivalently the empty set does not belong to
the filter. Bourbaki include this assumption in the definition of a filter but we prefer to have a
`CompleteLattice` structure on `Filter _`, so we use a typeclass argument in lemmas instead. -/
class NeBot (f : Filter α) : Prop where
/-- The filter is nontrivial: `f ≠ ⊥` or equivalently, `∅ ∉ f`. -/
ne' : f ≠ ⊥
#align filter.ne_bot Filter.NeBot
theorem neBot_iff {f : Filter α} : NeBot f ↔ f ≠ ⊥ :=
⟨fun h => h.1, fun h => ⟨h⟩⟩
#align filter.ne_bot_iff Filter.neBot_iff
theorem NeBot.ne {f : Filter α} (hf : NeBot f) : f ≠ ⊥ := hf.ne'
#align filter.ne_bot.ne Filter.NeBot.ne
@[simp] theorem not_neBot {f : Filter α} : ¬f.NeBot ↔ f = ⊥ := neBot_iff.not_left
#align filter.not_ne_bot Filter.not_neBot
theorem NeBot.mono {f g : Filter α} (hf : NeBot f) (hg : f ≤ g) : NeBot g :=
⟨ne_bot_of_le_ne_bot hf.1 hg⟩
#align filter.ne_bot.mono Filter.NeBot.mono
theorem neBot_of_le {f g : Filter α} [hf : NeBot f] (hg : f ≤ g) : NeBot g :=
hf.mono hg
#align filter.ne_bot_of_le Filter.neBot_of_le
@[simp] theorem sup_neBot {f g : Filter α} : NeBot (f ⊔ g) ↔ NeBot f ∨ NeBot g := by
simp only [neBot_iff, not_and_or, Ne, sup_eq_bot_iff]
#align filter.sup_ne_bot Filter.sup_neBot
theorem not_disjoint_self_iff : ¬Disjoint f f ↔ f.NeBot := by rw [disjoint_self, neBot_iff]
#align filter.not_disjoint_self_iff Filter.not_disjoint_self_iff
theorem bot_sets_eq : (⊥ : Filter α).sets = univ := rfl
#align filter.bot_sets_eq Filter.bot_sets_eq
/-- Either `f = ⊥` or `Filter.NeBot f`. This is a version of `eq_or_ne` that uses `Filter.NeBot`
as the second alternative, to be used as an instance. -/
theorem eq_or_neBot (f : Filter α) : f = ⊥ ∨ NeBot f := (eq_or_ne f ⊥).imp_right NeBot.mk
theorem sup_sets_eq {f g : Filter α} : (f ⊔ g).sets = f.sets ∩ g.sets :=
(giGenerate α).gc.u_inf
#align filter.sup_sets_eq Filter.sup_sets_eq
theorem sSup_sets_eq {s : Set (Filter α)} : (sSup s).sets = ⋂ f ∈ s, (f : Filter α).sets :=
(giGenerate α).gc.u_sInf
#align filter.Sup_sets_eq Filter.sSup_sets_eq
theorem iSup_sets_eq {f : ι → Filter α} : (iSup f).sets = ⋂ i, (f i).sets :=
(giGenerate α).gc.u_iInf
#align filter.supr_sets_eq Filter.iSup_sets_eq
theorem generate_empty : Filter.generate ∅ = (⊤ : Filter α) :=
(giGenerate α).gc.l_bot
#align filter.generate_empty Filter.generate_empty
theorem generate_univ : Filter.generate univ = (⊥ : Filter α) :=
bot_unique fun _ _ => GenerateSets.basic (mem_univ _)
#align filter.generate_univ Filter.generate_univ
theorem generate_union {s t : Set (Set α)} :
Filter.generate (s ∪ t) = Filter.generate s ⊓ Filter.generate t :=
(giGenerate α).gc.l_sup
#align filter.generate_union Filter.generate_union
theorem generate_iUnion {s : ι → Set (Set α)} :
Filter.generate (⋃ i, s i) = ⨅ i, Filter.generate (s i) :=
(giGenerate α).gc.l_iSup
#align filter.generate_Union Filter.generate_iUnion
@[simp]
theorem mem_bot {s : Set α} : s ∈ (⊥ : Filter α) :=
trivial
#align filter.mem_bot Filter.mem_bot
@[simp]
theorem mem_sup {f g : Filter α} {s : Set α} : s ∈ f ⊔ g ↔ s ∈ f ∧ s ∈ g :=
Iff.rfl
#align filter.mem_sup Filter.mem_sup
theorem union_mem_sup {f g : Filter α} {s t : Set α} (hs : s ∈ f) (ht : t ∈ g) : s ∪ t ∈ f ⊔ g :=
⟨mem_of_superset hs subset_union_left, mem_of_superset ht subset_union_right⟩
#align filter.union_mem_sup Filter.union_mem_sup
@[simp]
theorem mem_sSup {x : Set α} {s : Set (Filter α)} : x ∈ sSup s ↔ ∀ f ∈ s, x ∈ (f : Filter α) :=
Iff.rfl
#align filter.mem_Sup Filter.mem_sSup
@[simp]
theorem mem_iSup {x : Set α} {f : ι → Filter α} : x ∈ iSup f ↔ ∀ i, x ∈ f i := by
simp only [← Filter.mem_sets, iSup_sets_eq, iff_self_iff, mem_iInter]
#align filter.mem_supr Filter.mem_iSup
@[simp]
theorem iSup_neBot {f : ι → Filter α} : (⨆ i, f i).NeBot ↔ ∃ i, (f i).NeBot := by
simp [neBot_iff]
#align filter.supr_ne_bot Filter.iSup_neBot
theorem iInf_eq_generate (s : ι → Filter α) : iInf s = generate (⋃ i, (s i).sets) :=
show generate _ = generate _ from congr_arg _ <| congr_arg sSup <| (range_comp _ _).symm
#align filter.infi_eq_generate Filter.iInf_eq_generate
theorem mem_iInf_of_mem {f : ι → Filter α} (i : ι) {s} (hs : s ∈ f i) : s ∈ ⨅ i, f i :=
iInf_le f i hs
#align filter.mem_infi_of_mem Filter.mem_iInf_of_mem
theorem mem_iInf_of_iInter {ι} {s : ι → Filter α} {U : Set α} {I : Set ι} (I_fin : I.Finite)
{V : I → Set α} (hV : ∀ i, V i ∈ s i) (hU : ⋂ i, V i ⊆ U) : U ∈ ⨅ i, s i := by
haveI := I_fin.fintype
refine mem_of_superset (iInter_mem.2 fun i => ?_) hU
exact mem_iInf_of_mem (i : ι) (hV _)
#align filter.mem_infi_of_Inter Filter.mem_iInf_of_iInter
theorem mem_iInf {ι} {s : ι → Filter α} {U : Set α} :
(U ∈ ⨅ i, s i) ↔ ∃ I : Set ι, I.Finite ∧ ∃ V : I → Set α, (∀ i, V i ∈ s i) ∧ U = ⋂ i, V i := by
constructor
· rw [iInf_eq_generate, mem_generate_iff]
rintro ⟨t, tsub, tfin, tinter⟩
rcases eq_finite_iUnion_of_finite_subset_iUnion tfin tsub with ⟨I, Ifin, σ, σfin, σsub, rfl⟩
rw [sInter_iUnion] at tinter
set V := fun i => U ∪ ⋂₀ σ i with hV
have V_in : ∀ i, V i ∈ s i := by
rintro i
have : ⋂₀ σ i ∈ s i := by
rw [sInter_mem (σfin _)]
apply σsub
exact mem_of_superset this subset_union_right
refine ⟨I, Ifin, V, V_in, ?_⟩
rwa [hV, ← union_iInter, union_eq_self_of_subset_right]
· rintro ⟨I, Ifin, V, V_in, rfl⟩
exact mem_iInf_of_iInter Ifin V_in Subset.rfl
#align filter.mem_infi Filter.mem_iInf
theorem mem_iInf' {ι} {s : ι → Filter α} {U : Set α} :
(U ∈ ⨅ i, s i) ↔
∃ I : Set ι, I.Finite ∧ ∃ V : ι → Set α, (∀ i, V i ∈ s i) ∧
(∀ i ∉ I, V i = univ) ∧ (U = ⋂ i ∈ I, V i) ∧ U = ⋂ i, V i := by
simp only [mem_iInf, SetCoe.forall', biInter_eq_iInter]
refine ⟨?_, fun ⟨I, If, V, hVs, _, hVU, _⟩ => ⟨I, If, fun i => V i, fun i => hVs i, hVU⟩⟩
rintro ⟨I, If, V, hV, rfl⟩
refine ⟨I, If, fun i => if hi : i ∈ I then V ⟨i, hi⟩ else univ, fun i => ?_, fun i hi => ?_, ?_⟩
· dsimp only
split_ifs
exacts [hV _, univ_mem]
· exact dif_neg hi
· simp only [iInter_dite, biInter_eq_iInter, dif_pos (Subtype.coe_prop _), Subtype.coe_eta,
iInter_univ, inter_univ, eq_self_iff_true, true_and_iff]
#align filter.mem_infi' Filter.mem_iInf'
theorem exists_iInter_of_mem_iInf {ι : Type*} {α : Type*} {f : ι → Filter α} {s}
(hs : s ∈ ⨅ i, f i) : ∃ t : ι → Set α, (∀ i, t i ∈ f i) ∧ s = ⋂ i, t i :=
let ⟨_, _, V, hVs, _, _, hVU'⟩ := mem_iInf'.1 hs; ⟨V, hVs, hVU'⟩
#align filter.exists_Inter_of_mem_infi Filter.exists_iInter_of_mem_iInf
theorem mem_iInf_of_finite {ι : Type*} [Finite ι] {α : Type*} {f : ι → Filter α} (s) :
(s ∈ ⨅ i, f i) ↔ ∃ t : ι → Set α, (∀ i, t i ∈ f i) ∧ s = ⋂ i, t i := by
refine ⟨exists_iInter_of_mem_iInf, ?_⟩
rintro ⟨t, ht, rfl⟩
exact iInter_mem.2 fun i => mem_iInf_of_mem i (ht i)
#align filter.mem_infi_of_finite Filter.mem_iInf_of_finite
@[simp]
theorem le_principal_iff {s : Set α} {f : Filter α} : f ≤ 𝓟 s ↔ s ∈ f :=
⟨fun h => h Subset.rfl, fun hs _ ht => mem_of_superset hs ht⟩
#align filter.le_principal_iff Filter.le_principal_iff
theorem Iic_principal (s : Set α) : Iic (𝓟 s) = { l | s ∈ l } :=
Set.ext fun _ => le_principal_iff
#align filter.Iic_principal Filter.Iic_principal
theorem principal_mono {s t : Set α} : 𝓟 s ≤ 𝓟 t ↔ s ⊆ t := by
simp only [le_principal_iff, iff_self_iff, mem_principal]
#align filter.principal_mono Filter.principal_mono
@[gcongr] alias ⟨_, _root_.GCongr.filter_principal_mono⟩ := principal_mono
@[mono]
theorem monotone_principal : Monotone (𝓟 : Set α → Filter α) := fun _ _ => principal_mono.2
#align filter.monotone_principal Filter.monotone_principal
@[simp] theorem principal_eq_iff_eq {s t : Set α} : 𝓟 s = 𝓟 t ↔ s = t := by
simp only [le_antisymm_iff, le_principal_iff, mem_principal]; rfl
#align filter.principal_eq_iff_eq Filter.principal_eq_iff_eq
@[simp] theorem join_principal_eq_sSup {s : Set (Filter α)} : join (𝓟 s) = sSup s := rfl
#align filter.join_principal_eq_Sup Filter.join_principal_eq_sSup
@[simp] theorem principal_univ : 𝓟 (univ : Set α) = ⊤ :=
top_unique <| by simp only [le_principal_iff, mem_top, eq_self_iff_true]
#align filter.principal_univ Filter.principal_univ
@[simp]
theorem principal_empty : 𝓟 (∅ : Set α) = ⊥ :=
bot_unique fun _ _ => empty_subset _
#align filter.principal_empty Filter.principal_empty
theorem generate_eq_biInf (S : Set (Set α)) : generate S = ⨅ s ∈ S, 𝓟 s :=
eq_of_forall_le_iff fun f => by simp [le_generate_iff, le_principal_iff, subset_def]
#align filter.generate_eq_binfi Filter.generate_eq_biInf
/-! ### Lattice equations -/
theorem empty_mem_iff_bot {f : Filter α} : ∅ ∈ f ↔ f = ⊥ :=
⟨fun h => bot_unique fun s _ => mem_of_superset h (empty_subset s), fun h => h.symm ▸ mem_bot⟩
#align filter.empty_mem_iff_bot Filter.empty_mem_iff_bot
theorem nonempty_of_mem {f : Filter α} [hf : NeBot f] {s : Set α} (hs : s ∈ f) : s.Nonempty :=
s.eq_empty_or_nonempty.elim (fun h => absurd hs (h.symm ▸ mt empty_mem_iff_bot.mp hf.1)) id
#align filter.nonempty_of_mem Filter.nonempty_of_mem
theorem NeBot.nonempty_of_mem {f : Filter α} (hf : NeBot f) {s : Set α} (hs : s ∈ f) : s.Nonempty :=
@Filter.nonempty_of_mem α f hf s hs
#align filter.ne_bot.nonempty_of_mem Filter.NeBot.nonempty_of_mem
@[simp]
theorem empty_not_mem (f : Filter α) [NeBot f] : ¬∅ ∈ f := fun h => (nonempty_of_mem h).ne_empty rfl
#align filter.empty_not_mem Filter.empty_not_mem
theorem nonempty_of_neBot (f : Filter α) [NeBot f] : Nonempty α :=
nonempty_of_exists <| nonempty_of_mem (univ_mem : univ ∈ f)
#align filter.nonempty_of_ne_bot Filter.nonempty_of_neBot
theorem compl_not_mem {f : Filter α} {s : Set α} [NeBot f] (h : s ∈ f) : sᶜ ∉ f := fun hsc =>
(nonempty_of_mem (inter_mem h hsc)).ne_empty <| inter_compl_self s
#align filter.compl_not_mem Filter.compl_not_mem
theorem filter_eq_bot_of_isEmpty [IsEmpty α] (f : Filter α) : f = ⊥ :=
empty_mem_iff_bot.mp <| univ_mem' isEmptyElim
#align filter.filter_eq_bot_of_is_empty Filter.filter_eq_bot_of_isEmpty
protected lemma disjoint_iff {f g : Filter α} : Disjoint f g ↔ ∃ s ∈ f, ∃ t ∈ g, Disjoint s t := by
simp only [disjoint_iff, ← empty_mem_iff_bot, mem_inf_iff, inf_eq_inter, bot_eq_empty,
@eq_comm _ ∅]
#align filter.disjoint_iff Filter.disjoint_iff
theorem disjoint_of_disjoint_of_mem {f g : Filter α} {s t : Set α} (h : Disjoint s t) (hs : s ∈ f)
(ht : t ∈ g) : Disjoint f g :=
Filter.disjoint_iff.mpr ⟨s, hs, t, ht, h⟩
#align filter.disjoint_of_disjoint_of_mem Filter.disjoint_of_disjoint_of_mem
theorem NeBot.not_disjoint (hf : f.NeBot) (hs : s ∈ f) (ht : t ∈ f) : ¬Disjoint s t := fun h =>
not_disjoint_self_iff.2 hf <| Filter.disjoint_iff.2 ⟨s, hs, t, ht, h⟩
#align filter.ne_bot.not_disjoint Filter.NeBot.not_disjoint
theorem inf_eq_bot_iff {f g : Filter α} : f ⊓ g = ⊥ ↔ ∃ U ∈ f, ∃ V ∈ g, U ∩ V = ∅ := by
simp only [← disjoint_iff, Filter.disjoint_iff, Set.disjoint_iff_inter_eq_empty]
#align filter.inf_eq_bot_iff Filter.inf_eq_bot_iff
theorem _root_.Pairwise.exists_mem_filter_of_disjoint {ι : Type*} [Finite ι] {l : ι → Filter α}
(hd : Pairwise (Disjoint on l)) :
∃ s : ι → Set α, (∀ i, s i ∈ l i) ∧ Pairwise (Disjoint on s) := by
have : Pairwise fun i j => ∃ (s : {s // s ∈ l i}) (t : {t // t ∈ l j}), Disjoint s.1 t.1 := by
simpa only [Pairwise, Function.onFun, Filter.disjoint_iff, exists_prop, Subtype.exists] using hd
choose! s t hst using this
refine ⟨fun i => ⋂ j, @s i j ∩ @t j i, fun i => ?_, fun i j hij => ?_⟩
exacts [iInter_mem.2 fun j => inter_mem (@s i j).2 (@t j i).2,
(hst hij).mono ((iInter_subset _ j).trans inter_subset_left)
((iInter_subset _ i).trans inter_subset_right)]
#align pairwise.exists_mem_filter_of_disjoint Pairwise.exists_mem_filter_of_disjoint
theorem _root_.Set.PairwiseDisjoint.exists_mem_filter {ι : Type*} {l : ι → Filter α} {t : Set ι}
(hd : t.PairwiseDisjoint l) (ht : t.Finite) :
∃ s : ι → Set α, (∀ i, s i ∈ l i) ∧ t.PairwiseDisjoint s := by
haveI := ht.to_subtype
rcases (hd.subtype _ _).exists_mem_filter_of_disjoint with ⟨s, hsl, hsd⟩
lift s to (i : t) → {s // s ∈ l i} using hsl
rcases @Subtype.exists_pi_extension ι (fun i => { s // s ∈ l i }) _ _ s with ⟨s, rfl⟩
exact ⟨fun i => s i, fun i => (s i).2, hsd.set_of_subtype _ _⟩
#align set.pairwise_disjoint.exists_mem_filter Set.PairwiseDisjoint.exists_mem_filter
/-- There is exactly one filter on an empty type. -/
instance unique [IsEmpty α] : Unique (Filter α) where
default := ⊥
uniq := filter_eq_bot_of_isEmpty
#align filter.unique Filter.unique
theorem NeBot.nonempty (f : Filter α) [hf : f.NeBot] : Nonempty α :=
not_isEmpty_iff.mp fun _ ↦ hf.ne (Subsingleton.elim _ _)
/-- There are only two filters on a `Subsingleton`: `⊥` and `⊤`. If the type is empty, then they are
equal. -/
theorem eq_top_of_neBot [Subsingleton α] (l : Filter α) [NeBot l] : l = ⊤ := by
refine top_unique fun s hs => ?_
obtain rfl : s = univ := Subsingleton.eq_univ_of_nonempty (nonempty_of_mem hs)
exact univ_mem
#align filter.eq_top_of_ne_bot Filter.eq_top_of_neBot
theorem forall_mem_nonempty_iff_neBot {f : Filter α} :
(∀ s : Set α, s ∈ f → s.Nonempty) ↔ NeBot f :=
⟨fun h => ⟨fun hf => not_nonempty_empty (h ∅ <| hf.symm ▸ mem_bot)⟩, @nonempty_of_mem _ _⟩
#align filter.forall_mem_nonempty_iff_ne_bot Filter.forall_mem_nonempty_iff_neBot
instance instNontrivialFilter [Nonempty α] : Nontrivial (Filter α) :=
⟨⟨⊤, ⊥, NeBot.ne <| forall_mem_nonempty_iff_neBot.1
fun s hs => by rwa [mem_top.1 hs, ← nonempty_iff_univ_nonempty]⟩⟩
theorem nontrivial_iff_nonempty : Nontrivial (Filter α) ↔ Nonempty α :=
⟨fun _ =>
by_contra fun h' =>
haveI := not_nonempty_iff.1 h'
not_subsingleton (Filter α) inferInstance,
@Filter.instNontrivialFilter α⟩
#align filter.nontrivial_iff_nonempty Filter.nontrivial_iff_nonempty
theorem eq_sInf_of_mem_iff_exists_mem {S : Set (Filter α)} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ f ∈ S, s ∈ f) : l = sInf S :=
le_antisymm (le_sInf fun f hf _ hs => h.2 ⟨f, hf, hs⟩)
fun _ hs => let ⟨_, hf, hs⟩ := h.1 hs; (sInf_le hf) hs
#align filter.eq_Inf_of_mem_iff_exists_mem Filter.eq_sInf_of_mem_iff_exists_mem
theorem eq_iInf_of_mem_iff_exists_mem {f : ι → Filter α} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ i, s ∈ f i) : l = iInf f :=
eq_sInf_of_mem_iff_exists_mem <| h.trans exists_range_iff.symm
#align filter.eq_infi_of_mem_iff_exists_mem Filter.eq_iInf_of_mem_iff_exists_mem
theorem eq_biInf_of_mem_iff_exists_mem {f : ι → Filter α} {p : ι → Prop} {l : Filter α}
(h : ∀ {s}, s ∈ l ↔ ∃ i, p i ∧ s ∈ f i) : l = ⨅ (i) (_ : p i), f i := by
rw [iInf_subtype']
exact eq_iInf_of_mem_iff_exists_mem fun {_} => by simp only [Subtype.exists, h, exists_prop]
#align filter.eq_binfi_of_mem_iff_exists_mem Filter.eq_biInf_of_mem_iff_exists_memₓ
theorem iInf_sets_eq {f : ι → Filter α} (h : Directed (· ≥ ·) f) [ne : Nonempty ι] :
(iInf f).sets = ⋃ i, (f i).sets :=
let ⟨i⟩ := ne
let u :=
{ sets := ⋃ i, (f i).sets
univ_sets := mem_iUnion.2 ⟨i, univ_mem⟩
sets_of_superset := by
simp only [mem_iUnion, exists_imp]
exact fun i hx hxy => ⟨i, mem_of_superset hx hxy⟩
inter_sets := by
simp only [mem_iUnion, exists_imp]
intro x y a hx b hy
rcases h a b with ⟨c, ha, hb⟩
exact ⟨c, inter_mem (ha hx) (hb hy)⟩ }
have : u = iInf f := eq_iInf_of_mem_iff_exists_mem mem_iUnion
-- Porting note: it was just `congr_arg filter.sets this.symm`
(congr_arg Filter.sets this.symm).trans <| by simp only
#align filter.infi_sets_eq Filter.iInf_sets_eq
theorem mem_iInf_of_directed {f : ι → Filter α} (h : Directed (· ≥ ·) f) [Nonempty ι] (s) :
s ∈ iInf f ↔ ∃ i, s ∈ f i := by
simp only [← Filter.mem_sets, iInf_sets_eq h, mem_iUnion]
#align filter.mem_infi_of_directed Filter.mem_iInf_of_directed
theorem mem_biInf_of_directed {f : β → Filter α} {s : Set β} (h : DirectedOn (f ⁻¹'o (· ≥ ·)) s)
(ne : s.Nonempty) {t : Set α} : (t ∈ ⨅ i ∈ s, f i) ↔ ∃ i ∈ s, t ∈ f i := by
haveI := ne.to_subtype
simp_rw [iInf_subtype', mem_iInf_of_directed h.directed_val, Subtype.exists, exists_prop]
#align filter.mem_binfi_of_directed Filter.mem_biInf_of_directed
theorem biInf_sets_eq {f : β → Filter α} {s : Set β} (h : DirectedOn (f ⁻¹'o (· ≥ ·)) s)
(ne : s.Nonempty) : (⨅ i ∈ s, f i).sets = ⋃ i ∈ s, (f i).sets :=
ext fun t => by simp [mem_biInf_of_directed h ne]
#align filter.binfi_sets_eq Filter.biInf_sets_eq
theorem iInf_sets_eq_finite {ι : Type*} (f : ι → Filter α) :
(⨅ i, f i).sets = ⋃ t : Finset ι, (⨅ i ∈ t, f i).sets := by
rw [iInf_eq_iInf_finset, iInf_sets_eq]
exact directed_of_isDirected_le fun _ _ => biInf_mono
#align filter.infi_sets_eq_finite Filter.iInf_sets_eq_finite
theorem iInf_sets_eq_finite' (f : ι → Filter α) :
(⨅ i, f i).sets = ⋃ t : Finset (PLift ι), (⨅ i ∈ t, f (PLift.down i)).sets := by
rw [← iInf_sets_eq_finite, ← Equiv.plift.surjective.iInf_comp, Equiv.plift_apply]
#align filter.infi_sets_eq_finite' Filter.iInf_sets_eq_finite'
theorem mem_iInf_finite {ι : Type*} {f : ι → Filter α} (s) :
s ∈ iInf f ↔ ∃ t : Finset ι, s ∈ ⨅ i ∈ t, f i :=
(Set.ext_iff.1 (iInf_sets_eq_finite f) s).trans mem_iUnion
#align filter.mem_infi_finite Filter.mem_iInf_finite
theorem mem_iInf_finite' {f : ι → Filter α} (s) :
s ∈ iInf f ↔ ∃ t : Finset (PLift ι), s ∈ ⨅ i ∈ t, f (PLift.down i) :=
(Set.ext_iff.1 (iInf_sets_eq_finite' f) s).trans mem_iUnion
#align filter.mem_infi_finite' Filter.mem_iInf_finite'
@[simp]
theorem sup_join {f₁ f₂ : Filter (Filter α)} : join f₁ ⊔ join f₂ = join (f₁ ⊔ f₂) :=
Filter.ext fun x => by simp only [mem_sup, mem_join]
#align filter.sup_join Filter.sup_join
@[simp]
theorem iSup_join {ι : Sort w} {f : ι → Filter (Filter α)} : ⨆ x, join (f x) = join (⨆ x, f x) :=
Filter.ext fun x => by simp only [mem_iSup, mem_join]
#align filter.supr_join Filter.iSup_join
instance : DistribLattice (Filter α) :=
{ Filter.instCompleteLatticeFilter with
le_sup_inf := by
intro x y z s
simp only [and_assoc, mem_inf_iff, mem_sup, exists_prop, exists_imp, and_imp]
rintro hs t₁ ht₁ t₂ ht₂ rfl
exact
⟨t₁, x.sets_of_superset hs inter_subset_left, ht₁, t₂,
x.sets_of_superset hs inter_subset_right, ht₂, rfl⟩ }
-- The dual version does not hold! `Filter α` is not a `CompleteDistribLattice`. -/
instance : Coframe (Filter α) :=
{ Filter.instCompleteLatticeFilter with
iInf_sup_le_sup_sInf := fun f s t ⟨h₁, h₂⟩ => by
rw [iInf_subtype']
rw [sInf_eq_iInf', iInf_sets_eq_finite, mem_iUnion] at h₂
obtain ⟨u, hu⟩ := h₂
rw [← Finset.inf_eq_iInf] at hu
suffices ⨅ i : s, f ⊔ ↑i ≤ f ⊔ u.inf fun i => ↑i from this ⟨h₁, hu⟩
refine Finset.induction_on u (le_sup_of_le_right le_top) ?_
rintro ⟨i⟩ u _ ih
rw [Finset.inf_insert, sup_inf_left]
exact le_inf (iInf_le _ _) ih }
theorem mem_iInf_finset {s : Finset α} {f : α → Filter β} {t : Set β} :
(t ∈ ⨅ a ∈ s, f a) ↔ ∃ p : α → Set β, (∀ a ∈ s, p a ∈ f a) ∧ t = ⋂ a ∈ s, p a := by
simp only [← Finset.set_biInter_coe, biInter_eq_iInter, iInf_subtype']
refine ⟨fun h => ?_, ?_⟩
· rcases (mem_iInf_of_finite _).1 h with ⟨p, hp, rfl⟩
refine ⟨fun a => if h : a ∈ s then p ⟨a, h⟩ else univ,
fun a ha => by simpa [ha] using hp ⟨a, ha⟩, ?_⟩
refine iInter_congr_of_surjective id surjective_id ?_
rintro ⟨a, ha⟩
simp [ha]
· rintro ⟨p, hpf, rfl⟩
exact iInter_mem.2 fun a => mem_iInf_of_mem a (hpf a a.2)
#align filter.mem_infi_finset Filter.mem_iInf_finset
/-- If `f : ι → Filter α` is directed, `ι` is not empty, and `∀ i, f i ≠ ⊥`, then `iInf f ≠ ⊥`.
See also `iInf_neBot_of_directed` for a version assuming `Nonempty α` instead of `Nonempty ι`. -/
theorem iInf_neBot_of_directed' {f : ι → Filter α} [Nonempty ι] (hd : Directed (· ≥ ·) f) :
(∀ i, NeBot (f i)) → NeBot (iInf f) :=
not_imp_not.1 <| by simpa only [not_forall, not_neBot, ← empty_mem_iff_bot,
mem_iInf_of_directed hd] using id
#align filter.infi_ne_bot_of_directed' Filter.iInf_neBot_of_directed'
/-- If `f : ι → Filter α` is directed, `α` is not empty, and `∀ i, f i ≠ ⊥`, then `iInf f ≠ ⊥`.
See also `iInf_neBot_of_directed'` for a version assuming `Nonempty ι` instead of `Nonempty α`. -/
theorem iInf_neBot_of_directed {f : ι → Filter α} [hn : Nonempty α] (hd : Directed (· ≥ ·) f)
(hb : ∀ i, NeBot (f i)) : NeBot (iInf f) := by
cases isEmpty_or_nonempty ι
· constructor
simp [iInf_of_empty f, top_ne_bot]
· exact iInf_neBot_of_directed' hd hb
#align filter.infi_ne_bot_of_directed Filter.iInf_neBot_of_directed
theorem sInf_neBot_of_directed' {s : Set (Filter α)} (hne : s.Nonempty) (hd : DirectedOn (· ≥ ·) s)
(hbot : ⊥ ∉ s) : NeBot (sInf s) :=
(sInf_eq_iInf' s).symm ▸
@iInf_neBot_of_directed' _ _ _ hne.to_subtype hd.directed_val fun ⟨_, hf⟩ =>
⟨ne_of_mem_of_not_mem hf hbot⟩
#align filter.Inf_ne_bot_of_directed' Filter.sInf_neBot_of_directed'
theorem sInf_neBot_of_directed [Nonempty α] {s : Set (Filter α)} (hd : DirectedOn (· ≥ ·) s)
(hbot : ⊥ ∉ s) : NeBot (sInf s) :=
(sInf_eq_iInf' s).symm ▸
iInf_neBot_of_directed hd.directed_val fun ⟨_, hf⟩ => ⟨ne_of_mem_of_not_mem hf hbot⟩
#align filter.Inf_ne_bot_of_directed Filter.sInf_neBot_of_directed
theorem iInf_neBot_iff_of_directed' {f : ι → Filter α} [Nonempty ι] (hd : Directed (· ≥ ·) f) :
NeBot (iInf f) ↔ ∀ i, NeBot (f i) :=
⟨fun H i => H.mono (iInf_le _ i), iInf_neBot_of_directed' hd⟩
#align filter.infi_ne_bot_iff_of_directed' Filter.iInf_neBot_iff_of_directed'
theorem iInf_neBot_iff_of_directed {f : ι → Filter α} [Nonempty α] (hd : Directed (· ≥ ·) f) :
NeBot (iInf f) ↔ ∀ i, NeBot (f i) :=
⟨fun H i => H.mono (iInf_le _ i), iInf_neBot_of_directed hd⟩
#align filter.infi_ne_bot_iff_of_directed Filter.iInf_neBot_iff_of_directed
@[elab_as_elim]
theorem iInf_sets_induct {f : ι → Filter α} {s : Set α} (hs : s ∈ iInf f) {p : Set α → Prop}
(uni : p univ) (ins : ∀ {i s₁ s₂}, s₁ ∈ f i → p s₂ → p (s₁ ∩ s₂)) : p s := by
rw [mem_iInf_finite'] at hs
simp only [← Finset.inf_eq_iInf] at hs
rcases hs with ⟨is, his⟩
induction is using Finset.induction_on generalizing s with
| empty => rwa [mem_top.1 his]
| insert _ ih =>
rw [Finset.inf_insert, mem_inf_iff] at his
rcases his with ⟨s₁, hs₁, s₂, hs₂, rfl⟩
exact ins hs₁ (ih hs₂)
#align filter.infi_sets_induct Filter.iInf_sets_induct
/-! #### `principal` equations -/
@[simp]
theorem inf_principal {s t : Set α} : 𝓟 s ⊓ 𝓟 t = 𝓟 (s ∩ t) :=
le_antisymm
(by simp only [le_principal_iff, mem_inf_iff]; exact ⟨s, Subset.rfl, t, Subset.rfl, rfl⟩)
(by simp [le_inf_iff, inter_subset_left, inter_subset_right])
#align filter.inf_principal Filter.inf_principal
@[simp]
theorem sup_principal {s t : Set α} : 𝓟 s ⊔ 𝓟 t = 𝓟 (s ∪ t) :=
Filter.ext fun u => by simp only [union_subset_iff, mem_sup, mem_principal]
#align filter.sup_principal Filter.sup_principal
@[simp]
theorem iSup_principal {ι : Sort w} {s : ι → Set α} : ⨆ x, 𝓟 (s x) = 𝓟 (⋃ i, s i) :=
Filter.ext fun x => by simp only [mem_iSup, mem_principal, iUnion_subset_iff]
#align filter.supr_principal Filter.iSup_principal
@[simp]
theorem principal_eq_bot_iff {s : Set α} : 𝓟 s = ⊥ ↔ s = ∅ :=
empty_mem_iff_bot.symm.trans <| mem_principal.trans subset_empty_iff
#align filter.principal_eq_bot_iff Filter.principal_eq_bot_iff
@[simp]
theorem principal_neBot_iff {s : Set α} : NeBot (𝓟 s) ↔ s.Nonempty :=
neBot_iff.trans <| (not_congr principal_eq_bot_iff).trans nonempty_iff_ne_empty.symm
#align filter.principal_ne_bot_iff Filter.principal_neBot_iff
alias ⟨_, _root_.Set.Nonempty.principal_neBot⟩ := principal_neBot_iff
#align set.nonempty.principal_ne_bot Set.Nonempty.principal_neBot
theorem isCompl_principal (s : Set α) : IsCompl (𝓟 s) (𝓟 sᶜ) :=
IsCompl.of_eq (by rw [inf_principal, inter_compl_self, principal_empty]) <| by
rw [sup_principal, union_compl_self, principal_univ]
#align filter.is_compl_principal Filter.isCompl_principal
theorem mem_inf_principal' {f : Filter α} {s t : Set α} : s ∈ f ⊓ 𝓟 t ↔ tᶜ ∪ s ∈ f := by
simp only [← le_principal_iff, (isCompl_principal s).le_left_iff, disjoint_assoc, inf_principal,
← (isCompl_principal (t ∩ sᶜ)).le_right_iff, compl_inter, compl_compl]
#align filter.mem_inf_principal' Filter.mem_inf_principal'
lemma mem_inf_principal {f : Filter α} {s t : Set α} : s ∈ f ⊓ 𝓟 t ↔ { x | x ∈ t → x ∈ s } ∈ f := by
simp only [mem_inf_principal', imp_iff_not_or, setOf_or, compl_def, setOf_mem_eq]
#align filter.mem_inf_principal Filter.mem_inf_principal
lemma iSup_inf_principal (f : ι → Filter α) (s : Set α) : ⨆ i, f i ⊓ 𝓟 s = (⨆ i, f i) ⊓ 𝓟 s := by
ext
simp only [mem_iSup, mem_inf_principal]
#align filter.supr_inf_principal Filter.iSup_inf_principal
theorem inf_principal_eq_bot {f : Filter α} {s : Set α} : f ⊓ 𝓟 s = ⊥ ↔ sᶜ ∈ f := by
rw [← empty_mem_iff_bot, mem_inf_principal]
simp only [mem_empty_iff_false, imp_false, compl_def]
#align filter.inf_principal_eq_bot Filter.inf_principal_eq_bot
theorem mem_of_eq_bot {f : Filter α} {s : Set α} (h : f ⊓ 𝓟 sᶜ = ⊥) : s ∈ f := by
rwa [inf_principal_eq_bot, compl_compl] at h
#align filter.mem_of_eq_bot Filter.mem_of_eq_bot
theorem diff_mem_inf_principal_compl {f : Filter α} {s : Set α} (hs : s ∈ f) (t : Set α) :
s \ t ∈ f ⊓ 𝓟 tᶜ :=
inter_mem_inf hs <| mem_principal_self tᶜ
#align filter.diff_mem_inf_principal_compl Filter.diff_mem_inf_principal_compl
theorem principal_le_iff {s : Set α} {f : Filter α} : 𝓟 s ≤ f ↔ ∀ V ∈ f, s ⊆ V := by
simp_rw [le_def, mem_principal]
#align filter.principal_le_iff Filter.principal_le_iff
@[simp]
theorem iInf_principal_finset {ι : Type w} (s : Finset ι) (f : ι → Set α) :
⨅ i ∈ s, 𝓟 (f i) = 𝓟 (⋂ i ∈ s, f i) := by
induction' s using Finset.induction_on with i s _ hs
· simp
· rw [Finset.iInf_insert, Finset.set_biInter_insert, hs, inf_principal]
#align filter.infi_principal_finset Filter.iInf_principal_finset
theorem iInf_principal {ι : Sort w} [Finite ι] (f : ι → Set α) : ⨅ i, 𝓟 (f i) = 𝓟 (⋂ i, f i) := by
cases nonempty_fintype (PLift ι)
rw [← iInf_plift_down, ← iInter_plift_down]
simpa using iInf_principal_finset Finset.univ (f <| PLift.down ·)
/-- A special case of `iInf_principal` that is safe to mark `simp`. -/
@[simp]
theorem iInf_principal' {ι : Type w} [Finite ι] (f : ι → Set α) : ⨅ i, 𝓟 (f i) = 𝓟 (⋂ i, f i) :=
iInf_principal _
#align filter.infi_principal Filter.iInf_principal
theorem iInf_principal_finite {ι : Type w} {s : Set ι} (hs : s.Finite) (f : ι → Set α) :
⨅ i ∈ s, 𝓟 (f i) = 𝓟 (⋂ i ∈ s, f i) := by
lift s to Finset ι using hs
exact mod_cast iInf_principal_finset s f
#align filter.infi_principal_finite Filter.iInf_principal_finite
end Lattice
@[mono, gcongr]
theorem join_mono {f₁ f₂ : Filter (Filter α)} (h : f₁ ≤ f₂) : join f₁ ≤ join f₂ := fun _ hs => h hs
#align filter.join_mono Filter.join_mono
/-! ### Eventually -/
/-- `f.Eventually p` or `∀ᶠ x in f, p x` mean that `{x | p x} ∈ f`. E.g., `∀ᶠ x in atTop, p x`
means that `p` holds true for sufficiently large `x`. -/
protected def Eventually (p : α → Prop) (f : Filter α) : Prop :=
{ x | p x } ∈ f
#align filter.eventually Filter.Eventually
@[inherit_doc Filter.Eventually]
notation3 "∀ᶠ "(...)" in "f", "r:(scoped p => Filter.Eventually p f) => r
theorem eventually_iff {f : Filter α} {P : α → Prop} : (∀ᶠ x in f, P x) ↔ { x | P x } ∈ f :=
Iff.rfl
#align filter.eventually_iff Filter.eventually_iff
@[simp]
theorem eventually_mem_set {s : Set α} {l : Filter α} : (∀ᶠ x in l, x ∈ s) ↔ s ∈ l :=
Iff.rfl
#align filter.eventually_mem_set Filter.eventually_mem_set
protected theorem ext' {f₁ f₂ : Filter α}
(h : ∀ p : α → Prop, (∀ᶠ x in f₁, p x) ↔ ∀ᶠ x in f₂, p x) : f₁ = f₂ :=
Filter.ext h
#align filter.ext' Filter.ext'
theorem Eventually.filter_mono {f₁ f₂ : Filter α} (h : f₁ ≤ f₂) {p : α → Prop}
(hp : ∀ᶠ x in f₂, p x) : ∀ᶠ x in f₁, p x :=
h hp
#align filter.eventually.filter_mono Filter.Eventually.filter_mono
theorem eventually_of_mem {f : Filter α} {P : α → Prop} {U : Set α} (hU : U ∈ f)
(h : ∀ x ∈ U, P x) : ∀ᶠ x in f, P x :=
mem_of_superset hU h
#align filter.eventually_of_mem Filter.eventually_of_mem
protected theorem Eventually.and {p q : α → Prop} {f : Filter α} :
f.Eventually p → f.Eventually q → ∀ᶠ x in f, p x ∧ q x :=
inter_mem
#align filter.eventually.and Filter.Eventually.and
@[simp] theorem eventually_true (f : Filter α) : ∀ᶠ _ in f, True := univ_mem
#align filter.eventually_true Filter.eventually_true
theorem eventually_of_forall {p : α → Prop} {f : Filter α} (hp : ∀ x, p x) : ∀ᶠ x in f, p x :=
univ_mem' hp
#align filter.eventually_of_forall Filter.eventually_of_forall
@[simp]
theorem eventually_false_iff_eq_bot {f : Filter α} : (∀ᶠ _ in f, False) ↔ f = ⊥ :=
empty_mem_iff_bot
#align filter.eventually_false_iff_eq_bot Filter.eventually_false_iff_eq_bot
@[simp]
theorem eventually_const {f : Filter α} [t : NeBot f] {p : Prop} : (∀ᶠ _ in f, p) ↔ p := by
by_cases h : p <;> simp [h, t.ne]
#align filter.eventually_const Filter.eventually_const
theorem eventually_iff_exists_mem {p : α → Prop} {f : Filter α} :
(∀ᶠ x in f, p x) ↔ ∃ v ∈ f, ∀ y ∈ v, p y :=
exists_mem_subset_iff.symm
#align filter.eventually_iff_exists_mem Filter.eventually_iff_exists_mem
theorem Eventually.exists_mem {p : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x) :
∃ v ∈ f, ∀ y ∈ v, p y :=
eventually_iff_exists_mem.1 hp
#align filter.eventually.exists_mem Filter.Eventually.exists_mem
theorem Eventually.mp {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∀ᶠ x in f, p x → q x) : ∀ᶠ x in f, q x :=
mp_mem hp hq
#align filter.eventually.mp Filter.Eventually.mp
theorem Eventually.mono {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∀ x, p x → q x) : ∀ᶠ x in f, q x :=
hp.mp (eventually_of_forall hq)
#align filter.eventually.mono Filter.Eventually.mono
theorem forall_eventually_of_eventually_forall {f : Filter α} {p : α → β → Prop}
(h : ∀ᶠ x in f, ∀ y, p x y) : ∀ y, ∀ᶠ x in f, p x y :=
fun y => h.mono fun _ h => h y
#align filter.forall_eventually_of_eventually_forall Filter.forall_eventually_of_eventually_forall
@[simp]
theorem eventually_and {p q : α → Prop} {f : Filter α} :
(∀ᶠ x in f, p x ∧ q x) ↔ (∀ᶠ x in f, p x) ∧ ∀ᶠ x in f, q x :=
inter_mem_iff
#align filter.eventually_and Filter.eventually_and
theorem Eventually.congr {f : Filter α} {p q : α → Prop} (h' : ∀ᶠ x in f, p x)
(h : ∀ᶠ x in f, p x ↔ q x) : ∀ᶠ x in f, q x :=
h'.mp (h.mono fun _ hx => hx.mp)
#align filter.eventually.congr Filter.Eventually.congr
theorem eventually_congr {f : Filter α} {p q : α → Prop} (h : ∀ᶠ x in f, p x ↔ q x) :
(∀ᶠ x in f, p x) ↔ ∀ᶠ x in f, q x :=
⟨fun hp => hp.congr h, fun hq => hq.congr <| by simpa only [Iff.comm] using h⟩
#align filter.eventually_congr Filter.eventually_congr
@[simp]
theorem eventually_all {ι : Sort*} [Finite ι] {l} {p : ι → α → Prop} :
(∀ᶠ x in l, ∀ i, p i x) ↔ ∀ i, ∀ᶠ x in l, p i x := by
simpa only [Filter.Eventually, setOf_forall] using iInter_mem
#align filter.eventually_all Filter.eventually_all
@[simp]
theorem eventually_all_finite {ι} {I : Set ι} (hI : I.Finite) {l} {p : ι → α → Prop} :
(∀ᶠ x in l, ∀ i ∈ I, p i x) ↔ ∀ i ∈ I, ∀ᶠ x in l, p i x := by
simpa only [Filter.Eventually, setOf_forall] using biInter_mem hI
#align filter.eventually_all_finite Filter.eventually_all_finite
alias _root_.Set.Finite.eventually_all := eventually_all_finite
#align set.finite.eventually_all Set.Finite.eventually_all
-- attribute [protected] Set.Finite.eventually_all
@[simp] theorem eventually_all_finset {ι} (I : Finset ι) {l} {p : ι → α → Prop} :
(∀ᶠ x in l, ∀ i ∈ I, p i x) ↔ ∀ i ∈ I, ∀ᶠ x in l, p i x :=
I.finite_toSet.eventually_all
#align filter.eventually_all_finset Filter.eventually_all_finset
alias _root_.Finset.eventually_all := eventually_all_finset
#align finset.eventually_all Finset.eventually_all
-- attribute [protected] Finset.eventually_all
@[simp]
theorem eventually_or_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∀ᶠ x in f, p ∨ q x) ↔ p ∨ ∀ᶠ x in f, q x :=
by_cases (fun h : p => by simp [h]) fun h => by simp [h]
#align filter.eventually_or_distrib_left Filter.eventually_or_distrib_left
@[simp]
theorem eventually_or_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∀ᶠ x in f, p x ∨ q) ↔ (∀ᶠ x in f, p x) ∨ q := by
simp only [@or_comm _ q, eventually_or_distrib_left]
#align filter.eventually_or_distrib_right Filter.eventually_or_distrib_right
theorem eventually_imp_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∀ᶠ x in f, p → q x) ↔ p → ∀ᶠ x in f, q x :=
eventually_all
#align filter.eventually_imp_distrib_left Filter.eventually_imp_distrib_left
@[simp]
theorem eventually_bot {p : α → Prop} : ∀ᶠ x in ⊥, p x :=
⟨⟩
#align filter.eventually_bot Filter.eventually_bot
@[simp]
theorem eventually_top {p : α → Prop} : (∀ᶠ x in ⊤, p x) ↔ ∀ x, p x :=
Iff.rfl
#align filter.eventually_top Filter.eventually_top
@[simp]
theorem eventually_sup {p : α → Prop} {f g : Filter α} :
(∀ᶠ x in f ⊔ g, p x) ↔ (∀ᶠ x in f, p x) ∧ ∀ᶠ x in g, p x :=
Iff.rfl
#align filter.eventually_sup Filter.eventually_sup
@[simp]
theorem eventually_sSup {p : α → Prop} {fs : Set (Filter α)} :
(∀ᶠ x in sSup fs, p x) ↔ ∀ f ∈ fs, ∀ᶠ x in f, p x :=
Iff.rfl
#align filter.eventually_Sup Filter.eventually_sSup
@[simp]
theorem eventually_iSup {p : α → Prop} {fs : ι → Filter α} :
(∀ᶠ x in ⨆ b, fs b, p x) ↔ ∀ b, ∀ᶠ x in fs b, p x :=
mem_iSup
#align filter.eventually_supr Filter.eventually_iSup
@[simp]
theorem eventually_principal {a : Set α} {p : α → Prop} : (∀ᶠ x in 𝓟 a, p x) ↔ ∀ x ∈ a, p x :=
Iff.rfl
#align filter.eventually_principal Filter.eventually_principal
theorem Eventually.forall_mem {α : Type*} {f : Filter α} {s : Set α} {P : α → Prop}
(hP : ∀ᶠ x in f, P x) (hf : 𝓟 s ≤ f) : ∀ x ∈ s, P x :=
Filter.eventually_principal.mp (hP.filter_mono hf)
theorem eventually_inf {f g : Filter α} {p : α → Prop} :
(∀ᶠ x in f ⊓ g, p x) ↔ ∃ s ∈ f, ∃ t ∈ g, ∀ x ∈ s ∩ t, p x :=
mem_inf_iff_superset
#align filter.eventually_inf Filter.eventually_inf
theorem eventually_inf_principal {f : Filter α} {p : α → Prop} {s : Set α} :
(∀ᶠ x in f ⊓ 𝓟 s, p x) ↔ ∀ᶠ x in f, x ∈ s → p x :=
mem_inf_principal
#align filter.eventually_inf_principal Filter.eventually_inf_principal
/-! ### Frequently -/
/-- `f.Frequently p` or `∃ᶠ x in f, p x` mean that `{x | ¬p x} ∉ f`. E.g., `∃ᶠ x in atTop, p x`
means that there exist arbitrarily large `x` for which `p` holds true. -/
protected def Frequently (p : α → Prop) (f : Filter α) : Prop :=
¬∀ᶠ x in f, ¬p x
#align filter.frequently Filter.Frequently
@[inherit_doc Filter.Frequently]
notation3 "∃ᶠ "(...)" in "f", "r:(scoped p => Filter.Frequently p f) => r
theorem Eventually.frequently {f : Filter α} [NeBot f] {p : α → Prop} (h : ∀ᶠ x in f, p x) :
∃ᶠ x in f, p x :=
compl_not_mem h
#align filter.eventually.frequently Filter.Eventually.frequently
theorem frequently_of_forall {f : Filter α} [NeBot f] {p : α → Prop} (h : ∀ x, p x) :
∃ᶠ x in f, p x :=
Eventually.frequently (eventually_of_forall h)
#align filter.frequently_of_forall Filter.frequently_of_forall
theorem Frequently.mp {p q : α → Prop} {f : Filter α} (h : ∃ᶠ x in f, p x)
(hpq : ∀ᶠ x in f, p x → q x) : ∃ᶠ x in f, q x :=
mt (fun hq => hq.mp <| hpq.mono fun _ => mt) h
#align filter.frequently.mp Filter.Frequently.mp
theorem Frequently.filter_mono {p : α → Prop} {f g : Filter α} (h : ∃ᶠ x in f, p x) (hle : f ≤ g) :
∃ᶠ x in g, p x :=
mt (fun h' => h'.filter_mono hle) h
#align filter.frequently.filter_mono Filter.Frequently.filter_mono
theorem Frequently.mono {p q : α → Prop} {f : Filter α} (h : ∃ᶠ x in f, p x)
(hpq : ∀ x, p x → q x) : ∃ᶠ x in f, q x :=
h.mp (eventually_of_forall hpq)
#align filter.frequently.mono Filter.Frequently.mono
theorem Frequently.and_eventually {p q : α → Prop} {f : Filter α} (hp : ∃ᶠ x in f, p x)
(hq : ∀ᶠ x in f, q x) : ∃ᶠ x in f, p x ∧ q x := by
refine mt (fun h => hq.mp <| h.mono ?_) hp
exact fun x hpq hq hp => hpq ⟨hp, hq⟩
#align filter.frequently.and_eventually Filter.Frequently.and_eventually
theorem Eventually.and_frequently {p q : α → Prop} {f : Filter α} (hp : ∀ᶠ x in f, p x)
(hq : ∃ᶠ x in f, q x) : ∃ᶠ x in f, p x ∧ q x := by
simpa only [and_comm] using hq.and_eventually hp
#align filter.eventually.and_frequently Filter.Eventually.and_frequently
theorem Frequently.exists {p : α → Prop} {f : Filter α} (hp : ∃ᶠ x in f, p x) : ∃ x, p x := by
by_contra H
replace H : ∀ᶠ x in f, ¬p x := eventually_of_forall (not_exists.1 H)
exact hp H
#align filter.frequently.exists Filter.Frequently.exists
theorem Eventually.exists {p : α → Prop} {f : Filter α} [NeBot f] (hp : ∀ᶠ x in f, p x) :
∃ x, p x :=
hp.frequently.exists
#align filter.eventually.exists Filter.Eventually.exists
lemma frequently_iff_neBot {p : α → Prop} : (∃ᶠ x in l, p x) ↔ NeBot (l ⊓ 𝓟 {x | p x}) := by
rw [neBot_iff, Ne, inf_principal_eq_bot]; rfl
lemma frequently_mem_iff_neBot {s : Set α} : (∃ᶠ x in l, x ∈ s) ↔ NeBot (l ⊓ 𝓟 s) :=
frequently_iff_neBot
theorem frequently_iff_forall_eventually_exists_and {p : α → Prop} {f : Filter α} :
(∃ᶠ x in f, p x) ↔ ∀ {q : α → Prop}, (∀ᶠ x in f, q x) → ∃ x, p x ∧ q x :=
⟨fun hp q hq => (hp.and_eventually hq).exists, fun H hp => by
simpa only [and_not_self_iff, exists_false] using H hp⟩
#align filter.frequently_iff_forall_eventually_exists_and Filter.frequently_iff_forall_eventually_exists_and
theorem frequently_iff {f : Filter α} {P : α → Prop} :
(∃ᶠ x in f, P x) ↔ ∀ {U}, U ∈ f → ∃ x ∈ U, P x := by
simp only [frequently_iff_forall_eventually_exists_and, @and_comm (P _)]
rfl
#align filter.frequently_iff Filter.frequently_iff
@[simp]
theorem not_eventually {p : α → Prop} {f : Filter α} : (¬∀ᶠ x in f, p x) ↔ ∃ᶠ x in f, ¬p x := by
simp [Filter.Frequently]
#align filter.not_eventually Filter.not_eventually
@[simp]
theorem not_frequently {p : α → Prop} {f : Filter α} : (¬∃ᶠ x in f, p x) ↔ ∀ᶠ x in f, ¬p x := by
simp only [Filter.Frequently, not_not]
#align filter.not_frequently Filter.not_frequently
@[simp]
theorem frequently_true_iff_neBot (f : Filter α) : (∃ᶠ _ in f, True) ↔ NeBot f := by
simp [frequently_iff_neBot]
#align filter.frequently_true_iff_ne_bot Filter.frequently_true_iff_neBot
@[simp]
theorem frequently_false (f : Filter α) : ¬∃ᶠ _ in f, False := by simp
#align filter.frequently_false Filter.frequently_false
@[simp]
theorem frequently_const {f : Filter α} [NeBot f] {p : Prop} : (∃ᶠ _ in f, p) ↔ p := by
by_cases p <;> simp [*]
#align filter.frequently_const Filter.frequently_const
@[simp]
theorem frequently_or_distrib {f : Filter α} {p q : α → Prop} :
(∃ᶠ x in f, p x ∨ q x) ↔ (∃ᶠ x in f, p x) ∨ ∃ᶠ x in f, q x := by
simp only [Filter.Frequently, ← not_and_or, not_or, eventually_and]
#align filter.frequently_or_distrib Filter.frequently_or_distrib
theorem frequently_or_distrib_left {f : Filter α} [NeBot f] {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p ∨ q x) ↔ p ∨ ∃ᶠ x in f, q x := by simp
#align filter.frequently_or_distrib_left Filter.frequently_or_distrib_left
theorem frequently_or_distrib_right {f : Filter α} [NeBot f] {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x ∨ q) ↔ (∃ᶠ x in f, p x) ∨ q := by simp
#align filter.frequently_or_distrib_right Filter.frequently_or_distrib_right
theorem frequently_imp_distrib {f : Filter α} {p q : α → Prop} :
(∃ᶠ x in f, p x → q x) ↔ (∀ᶠ x in f, p x) → ∃ᶠ x in f, q x := by
simp [imp_iff_not_or]
#align filter.frequently_imp_distrib Filter.frequently_imp_distrib
theorem frequently_imp_distrib_left {f : Filter α} [NeBot f] {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p → q x) ↔ p → ∃ᶠ x in f, q x := by simp [frequently_imp_distrib]
#align filter.frequently_imp_distrib_left Filter.frequently_imp_distrib_left
theorem frequently_imp_distrib_right {f : Filter α} [NeBot f] {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x → q) ↔ (∀ᶠ x in f, p x) → q := by
set_option tactic.skipAssignedInstances false in simp [frequently_imp_distrib]
#align filter.frequently_imp_distrib_right Filter.frequently_imp_distrib_right
theorem eventually_imp_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∀ᶠ x in f, p x → q) ↔ (∃ᶠ x in f, p x) → q := by
simp only [imp_iff_not_or, eventually_or_distrib_right, not_frequently]
#align filter.eventually_imp_distrib_right Filter.eventually_imp_distrib_right
@[simp]
theorem frequently_and_distrib_left {f : Filter α} {p : Prop} {q : α → Prop} :
(∃ᶠ x in f, p ∧ q x) ↔ p ∧ ∃ᶠ x in f, q x := by
simp only [Filter.Frequently, not_and, eventually_imp_distrib_left, Classical.not_imp]
#align filter.frequently_and_distrib_left Filter.frequently_and_distrib_left
@[simp]
theorem frequently_and_distrib_right {f : Filter α} {p : α → Prop} {q : Prop} :
(∃ᶠ x in f, p x ∧ q) ↔ (∃ᶠ x in f, p x) ∧ q := by
simp only [@and_comm _ q, frequently_and_distrib_left]
#align filter.frequently_and_distrib_right Filter.frequently_and_distrib_right
@[simp]
theorem frequently_bot {p : α → Prop} : ¬∃ᶠ x in ⊥, p x := by simp
#align filter.frequently_bot Filter.frequently_bot
@[simp]
theorem frequently_top {p : α → Prop} : (∃ᶠ x in ⊤, p x) ↔ ∃ x, p x := by simp [Filter.Frequently]
#align filter.frequently_top Filter.frequently_top
@[simp]
theorem frequently_principal {a : Set α} {p : α → Prop} : (∃ᶠ x in 𝓟 a, p x) ↔ ∃ x ∈ a, p x := by
simp [Filter.Frequently, not_forall]
#align filter.frequently_principal Filter.frequently_principal
theorem frequently_inf_principal {f : Filter α} {s : Set α} {p : α → Prop} :
(∃ᶠ x in f ⊓ 𝓟 s, p x) ↔ ∃ᶠ x in f, x ∈ s ∧ p x := by
simp only [Filter.Frequently, eventually_inf_principal, not_and]
alias ⟨Frequently.of_inf_principal, Frequently.inf_principal⟩ := frequently_inf_principal
theorem frequently_sup {p : α → Prop} {f g : Filter α} :
(∃ᶠ x in f ⊔ g, p x) ↔ (∃ᶠ x in f, p x) ∨ ∃ᶠ x in g, p x := by
simp only [Filter.Frequently, eventually_sup, not_and_or]
#align filter.frequently_sup Filter.frequently_sup
@[simp]
theorem frequently_sSup {p : α → Prop} {fs : Set (Filter α)} :
(∃ᶠ x in sSup fs, p x) ↔ ∃ f ∈ fs, ∃ᶠ x in f, p x := by
simp only [Filter.Frequently, not_forall, eventually_sSup, exists_prop]
#align filter.frequently_Sup Filter.frequently_sSup
@[simp]
theorem frequently_iSup {p : α → Prop} {fs : β → Filter α} :
(∃ᶠ x in ⨆ b, fs b, p x) ↔ ∃ b, ∃ᶠ x in fs b, p x := by
simp only [Filter.Frequently, eventually_iSup, not_forall]
#align filter.frequently_supr Filter.frequently_iSup
theorem Eventually.choice {r : α → β → Prop} {l : Filter α} [l.NeBot] (h : ∀ᶠ x in l, ∃ y, r x y) :
∃ f : α → β, ∀ᶠ x in l, r x (f x) := by
haveI : Nonempty β := let ⟨_, hx⟩ := h.exists; hx.nonempty
choose! f hf using fun x (hx : ∃ y, r x y) => hx
exact ⟨f, h.mono hf⟩
#align filter.eventually.choice Filter.Eventually.choice
/-!
### Relation “eventually equal”
-/
/-- Two functions `f` and `g` are *eventually equal* along a filter `l` if the set of `x` such that
`f x = g x` belongs to `l`. -/
def EventuallyEq (l : Filter α) (f g : α → β) : Prop :=
∀ᶠ x in l, f x = g x
#align filter.eventually_eq Filter.EventuallyEq
@[inherit_doc]
notation:50 f " =ᶠ[" l:50 "] " g:50 => EventuallyEq l f g
theorem EventuallyEq.eventually {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) :
∀ᶠ x in l, f x = g x :=
h
#align filter.eventually_eq.eventually Filter.EventuallyEq.eventually
theorem EventuallyEq.rw {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) (p : α → β → Prop)
(hf : ∀ᶠ x in l, p x (f x)) : ∀ᶠ x in l, p x (g x) :=
hf.congr <| h.mono fun _ hx => hx ▸ Iff.rfl
#align filter.eventually_eq.rw Filter.EventuallyEq.rw
theorem eventuallyEq_set {s t : Set α} {l : Filter α} : s =ᶠ[l] t ↔ ∀ᶠ x in l, x ∈ s ↔ x ∈ t :=
eventually_congr <| eventually_of_forall fun _ ↦ eq_iff_iff
#align filter.eventually_eq_set Filter.eventuallyEq_set
alias ⟨EventuallyEq.mem_iff, Eventually.set_eq⟩ := eventuallyEq_set
#align filter.eventually_eq.mem_iff Filter.EventuallyEq.mem_iff
#align filter.eventually.set_eq Filter.Eventually.set_eq
@[simp]
theorem eventuallyEq_univ {s : Set α} {l : Filter α} : s =ᶠ[l] univ ↔ s ∈ l := by
simp [eventuallyEq_set]
#align filter.eventually_eq_univ Filter.eventuallyEq_univ
theorem EventuallyEq.exists_mem {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) :
∃ s ∈ l, EqOn f g s :=
Eventually.exists_mem h
#align filter.eventually_eq.exists_mem Filter.EventuallyEq.exists_mem
theorem eventuallyEq_of_mem {l : Filter α} {f g : α → β} {s : Set α} (hs : s ∈ l) (h : EqOn f g s) :
f =ᶠ[l] g :=
eventually_of_mem hs h
#align filter.eventually_eq_of_mem Filter.eventuallyEq_of_mem
theorem eventuallyEq_iff_exists_mem {l : Filter α} {f g : α → β} :
f =ᶠ[l] g ↔ ∃ s ∈ l, EqOn f g s :=
eventually_iff_exists_mem
#align filter.eventually_eq_iff_exists_mem Filter.eventuallyEq_iff_exists_mem
theorem EventuallyEq.filter_mono {l l' : Filter α} {f g : α → β} (h₁ : f =ᶠ[l] g) (h₂ : l' ≤ l) :
f =ᶠ[l'] g :=
h₂ h₁
#align filter.eventually_eq.filter_mono Filter.EventuallyEq.filter_mono
@[refl, simp]
theorem EventuallyEq.refl (l : Filter α) (f : α → β) : f =ᶠ[l] f :=
eventually_of_forall fun _ => rfl
#align filter.eventually_eq.refl Filter.EventuallyEq.refl
protected theorem EventuallyEq.rfl {l : Filter α} {f : α → β} : f =ᶠ[l] f :=
EventuallyEq.refl l f
#align filter.eventually_eq.rfl Filter.EventuallyEq.rfl
@[symm]
theorem EventuallyEq.symm {f g : α → β} {l : Filter α} (H : f =ᶠ[l] g) : g =ᶠ[l] f :=
H.mono fun _ => Eq.symm
#align filter.eventually_eq.symm Filter.EventuallyEq.symm
@[trans]
theorem EventuallyEq.trans {l : Filter α} {f g h : α → β} (H₁ : f =ᶠ[l] g) (H₂ : g =ᶠ[l] h) :
f =ᶠ[l] h :=
H₂.rw (fun x y => f x = y) H₁
#align filter.eventually_eq.trans Filter.EventuallyEq.trans
instance : Trans ((· =ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· =ᶠ[l] ·) (· =ᶠ[l] ·) where
trans := EventuallyEq.trans
theorem EventuallyEq.prod_mk {l} {f f' : α → β} (hf : f =ᶠ[l] f') {g g' : α → γ} (hg : g =ᶠ[l] g') :
(fun x => (f x, g x)) =ᶠ[l] fun x => (f' x, g' x) :=
hf.mp <|
hg.mono <| by
intros
simp only [*]
#align filter.eventually_eq.prod_mk Filter.EventuallyEq.prod_mk
-- See `EventuallyEq.comp_tendsto` further below for a similar statement w.r.t.
-- composition on the right.
theorem EventuallyEq.fun_comp {f g : α → β} {l : Filter α} (H : f =ᶠ[l] g) (h : β → γ) :
h ∘ f =ᶠ[l] h ∘ g :=
H.mono fun _ hx => congr_arg h hx
#align filter.eventually_eq.fun_comp Filter.EventuallyEq.fun_comp
theorem EventuallyEq.comp₂ {δ} {f f' : α → β} {g g' : α → γ} {l} (Hf : f =ᶠ[l] f') (h : β → γ → δ)
(Hg : g =ᶠ[l] g') : (fun x => h (f x) (g x)) =ᶠ[l] fun x => h (f' x) (g' x) :=
(Hf.prod_mk Hg).fun_comp (uncurry h)
#align filter.eventually_eq.comp₂ Filter.EventuallyEq.comp₂
@[to_additive]
theorem EventuallyEq.mul [Mul β] {f f' g g' : α → β} {l : Filter α} (h : f =ᶠ[l] g)
(h' : f' =ᶠ[l] g') : (fun x => f x * f' x) =ᶠ[l] fun x => g x * g' x :=
h.comp₂ (· * ·) h'
#align filter.eventually_eq.mul Filter.EventuallyEq.mul
#align filter.eventually_eq.add Filter.EventuallyEq.add
@[to_additive const_smul]
theorem EventuallyEq.pow_const {γ} [Pow β γ] {f g : α → β} {l : Filter α} (h : f =ᶠ[l] g) (c : γ):
(fun x => f x ^ c) =ᶠ[l] fun x => g x ^ c :=
h.fun_comp (· ^ c)
#align filter.eventually_eq.const_smul Filter.EventuallyEq.const_smul
@[to_additive]
theorem EventuallyEq.inv [Inv β] {f g : α → β} {l : Filter α} (h : f =ᶠ[l] g) :
(fun x => (f x)⁻¹) =ᶠ[l] fun x => (g x)⁻¹ :=
h.fun_comp Inv.inv
#align filter.eventually_eq.inv Filter.EventuallyEq.inv
#align filter.eventually_eq.neg Filter.EventuallyEq.neg
@[to_additive]
theorem EventuallyEq.div [Div β] {f f' g g' : α → β} {l : Filter α} (h : f =ᶠ[l] g)
(h' : f' =ᶠ[l] g') : (fun x => f x / f' x) =ᶠ[l] fun x => g x / g' x :=
h.comp₂ (· / ·) h'
#align filter.eventually_eq.div Filter.EventuallyEq.div
#align filter.eventually_eq.sub Filter.EventuallyEq.sub
attribute [to_additive] EventuallyEq.const_smul
#align filter.eventually_eq.const_vadd Filter.EventuallyEq.const_vadd
@[to_additive]
theorem EventuallyEq.smul {𝕜} [SMul 𝕜 β] {l : Filter α} {f f' : α → 𝕜} {g g' : α → β}
(hf : f =ᶠ[l] f') (hg : g =ᶠ[l] g') : (fun x => f x • g x) =ᶠ[l] fun x => f' x • g' x :=
hf.comp₂ (· • ·) hg
#align filter.eventually_eq.smul Filter.EventuallyEq.smul
#align filter.eventually_eq.vadd Filter.EventuallyEq.vadd
theorem EventuallyEq.sup [Sup β] {l : Filter α} {f f' g g' : α → β} (hf : f =ᶠ[l] f')
(hg : g =ᶠ[l] g') : (fun x => f x ⊔ g x) =ᶠ[l] fun x => f' x ⊔ g' x :=
hf.comp₂ (· ⊔ ·) hg
#align filter.eventually_eq.sup Filter.EventuallyEq.sup
theorem EventuallyEq.inf [Inf β] {l : Filter α} {f f' g g' : α → β} (hf : f =ᶠ[l] f')
(hg : g =ᶠ[l] g') : (fun x => f x ⊓ g x) =ᶠ[l] fun x => f' x ⊓ g' x :=
hf.comp₂ (· ⊓ ·) hg
#align filter.eventually_eq.inf Filter.EventuallyEq.inf
theorem EventuallyEq.preimage {l : Filter α} {f g : α → β} (h : f =ᶠ[l] g) (s : Set β) :
f ⁻¹' s =ᶠ[l] g ⁻¹' s :=
h.fun_comp s
#align filter.eventually_eq.preimage Filter.EventuallyEq.preimage
theorem EventuallyEq.inter {s t s' t' : Set α} {l : Filter α} (h : s =ᶠ[l] t) (h' : s' =ᶠ[l] t') :
(s ∩ s' : Set α) =ᶠ[l] (t ∩ t' : Set α) :=
h.comp₂ (· ∧ ·) h'
#align filter.eventually_eq.inter Filter.EventuallyEq.inter
theorem EventuallyEq.union {s t s' t' : Set α} {l : Filter α} (h : s =ᶠ[l] t) (h' : s' =ᶠ[l] t') :
(s ∪ s' : Set α) =ᶠ[l] (t ∪ t' : Set α) :=
h.comp₂ (· ∨ ·) h'
#align filter.eventually_eq.union Filter.EventuallyEq.union
theorem EventuallyEq.compl {s t : Set α} {l : Filter α} (h : s =ᶠ[l] t) :
(sᶜ : Set α) =ᶠ[l] (tᶜ : Set α) :=
h.fun_comp Not
#align filter.eventually_eq.compl Filter.EventuallyEq.compl
theorem EventuallyEq.diff {s t s' t' : Set α} {l : Filter α} (h : s =ᶠ[l] t) (h' : s' =ᶠ[l] t') :
(s \ s' : Set α) =ᶠ[l] (t \ t' : Set α) :=
h.inter h'.compl
#align filter.eventually_eq.diff Filter.EventuallyEq.diff
theorem eventuallyEq_empty {s : Set α} {l : Filter α} : s =ᶠ[l] (∅ : Set α) ↔ ∀ᶠ x in l, x ∉ s :=
eventuallyEq_set.trans <| by simp
#align filter.eventually_eq_empty Filter.eventuallyEq_empty
theorem inter_eventuallyEq_left {s t : Set α} {l : Filter α} :
(s ∩ t : Set α) =ᶠ[l] s ↔ ∀ᶠ x in l, x ∈ s → x ∈ t := by
simp only [eventuallyEq_set, mem_inter_iff, and_iff_left_iff_imp]
#align filter.inter_eventually_eq_left Filter.inter_eventuallyEq_left
theorem inter_eventuallyEq_right {s t : Set α} {l : Filter α} :
(s ∩ t : Set α) =ᶠ[l] t ↔ ∀ᶠ x in l, x ∈ t → x ∈ s := by
rw [inter_comm, inter_eventuallyEq_left]
#align filter.inter_eventually_eq_right Filter.inter_eventuallyEq_right
@[simp]
theorem eventuallyEq_principal {s : Set α} {f g : α → β} : f =ᶠ[𝓟 s] g ↔ EqOn f g s :=
Iff.rfl
#align filter.eventually_eq_principal Filter.eventuallyEq_principal
theorem eventuallyEq_inf_principal_iff {F : Filter α} {s : Set α} {f g : α → β} :
f =ᶠ[F ⊓ 𝓟 s] g ↔ ∀ᶠ x in F, x ∈ s → f x = g x :=
eventually_inf_principal
#align filter.eventually_eq_inf_principal_iff Filter.eventuallyEq_inf_principal_iff
theorem EventuallyEq.sub_eq [AddGroup β] {f g : α → β} {l : Filter α} (h : f =ᶠ[l] g) :
f - g =ᶠ[l] 0 := by simpa using ((EventuallyEq.refl l f).sub h).symm
#align filter.eventually_eq.sub_eq Filter.EventuallyEq.sub_eq
theorem eventuallyEq_iff_sub [AddGroup β] {f g : α → β} {l : Filter α} :
f =ᶠ[l] g ↔ f - g =ᶠ[l] 0 :=
⟨fun h => h.sub_eq, fun h => by simpa using h.add (EventuallyEq.refl l g)⟩
#align filter.eventually_eq_iff_sub Filter.eventuallyEq_iff_sub
section LE
variable [LE β] {l : Filter α}
/-- A function `f` is eventually less than or equal to a function `g` at a filter `l`. -/
def EventuallyLE (l : Filter α) (f g : α → β) : Prop :=
∀ᶠ x in l, f x ≤ g x
#align filter.eventually_le Filter.EventuallyLE
@[inherit_doc]
notation:50 f " ≤ᶠ[" l:50 "] " g:50 => EventuallyLE l f g
theorem EventuallyLE.congr {f f' g g' : α → β} (H : f ≤ᶠ[l] g) (hf : f =ᶠ[l] f') (hg : g =ᶠ[l] g') :
f' ≤ᶠ[l] g' :=
H.mp <| hg.mp <| hf.mono fun x hf hg H => by rwa [hf, hg] at H
#align filter.eventually_le.congr Filter.EventuallyLE.congr
theorem eventuallyLE_congr {f f' g g' : α → β} (hf : f =ᶠ[l] f') (hg : g =ᶠ[l] g') :
f ≤ᶠ[l] g ↔ f' ≤ᶠ[l] g' :=
⟨fun H => H.congr hf hg, fun H => H.congr hf.symm hg.symm⟩
#align filter.eventually_le_congr Filter.eventuallyLE_congr
end LE
section Preorder
variable [Preorder β] {l : Filter α} {f g h : α → β}
theorem EventuallyEq.le (h : f =ᶠ[l] g) : f ≤ᶠ[l] g :=
h.mono fun _ => le_of_eq
#align filter.eventually_eq.le Filter.EventuallyEq.le
@[refl]
theorem EventuallyLE.refl (l : Filter α) (f : α → β) : f ≤ᶠ[l] f :=
EventuallyEq.rfl.le
#align filter.eventually_le.refl Filter.EventuallyLE.refl
theorem EventuallyLE.rfl : f ≤ᶠ[l] f :=
EventuallyLE.refl l f
#align filter.eventually_le.rfl Filter.EventuallyLE.rfl
@[trans]
theorem EventuallyLE.trans (H₁ : f ≤ᶠ[l] g) (H₂ : g ≤ᶠ[l] h) : f ≤ᶠ[l] h :=
H₂.mp <| H₁.mono fun _ => le_trans
#align filter.eventually_le.trans Filter.EventuallyLE.trans
instance : Trans ((· ≤ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· ≤ᶠ[l] ·) (· ≤ᶠ[l] ·) where
trans := EventuallyLE.trans
@[trans]
theorem EventuallyEq.trans_le (H₁ : f =ᶠ[l] g) (H₂ : g ≤ᶠ[l] h) : f ≤ᶠ[l] h :=
H₁.le.trans H₂
#align filter.eventually_eq.trans_le Filter.EventuallyEq.trans_le
instance : Trans ((· =ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· ≤ᶠ[l] ·) (· ≤ᶠ[l] ·) where
trans := EventuallyEq.trans_le
@[trans]
theorem EventuallyLE.trans_eq (H₁ : f ≤ᶠ[l] g) (H₂ : g =ᶠ[l] h) : f ≤ᶠ[l] h :=
H₁.trans H₂.le
#align filter.eventually_le.trans_eq Filter.EventuallyLE.trans_eq
instance : Trans ((· ≤ᶠ[l] ·) : (α → β) → (α → β) → Prop) (· =ᶠ[l] ·) (· ≤ᶠ[l] ·) where
trans := EventuallyLE.trans_eq
end Preorder
theorem EventuallyLE.antisymm [PartialOrder β] {l : Filter α} {f g : α → β} (h₁ : f ≤ᶠ[l] g)
(h₂ : g ≤ᶠ[l] f) : f =ᶠ[l] g :=
h₂.mp <| h₁.mono fun _ => le_antisymm
#align filter.eventually_le.antisymm Filter.EventuallyLE.antisymm
theorem eventuallyLE_antisymm_iff [PartialOrder β] {l : Filter α} {f g : α → β} :
f =ᶠ[l] g ↔ f ≤ᶠ[l] g ∧ g ≤ᶠ[l] f := by
simp only [EventuallyEq, EventuallyLE, le_antisymm_iff, eventually_and]
#align filter.eventually_le_antisymm_iff Filter.eventuallyLE_antisymm_iff
theorem EventuallyLE.le_iff_eq [PartialOrder β] {l : Filter α} {f g : α → β} (h : f ≤ᶠ[l] g) :
g ≤ᶠ[l] f ↔ g =ᶠ[l] f :=
⟨fun h' => h'.antisymm h, EventuallyEq.le⟩
#align filter.eventually_le.le_iff_eq Filter.EventuallyLE.le_iff_eq
theorem Eventually.ne_of_lt [Preorder β] {l : Filter α} {f g : α → β} (h : ∀ᶠ x in l, f x < g x) :
∀ᶠ x in l, f x ≠ g x :=
h.mono fun _ hx => hx.ne
#align filter.eventually.ne_of_lt Filter.Eventually.ne_of_lt
theorem Eventually.ne_top_of_lt [PartialOrder β] [OrderTop β] {l : Filter α} {f g : α → β}
(h : ∀ᶠ x in l, f x < g x) : ∀ᶠ x in l, f x ≠ ⊤ :=
h.mono fun _ hx => hx.ne_top
#align filter.eventually.ne_top_of_lt Filter.Eventually.ne_top_of_lt
theorem Eventually.lt_top_of_ne [PartialOrder β] [OrderTop β] {l : Filter α} {f : α → β}
(h : ∀ᶠ x in l, f x ≠ ⊤) : ∀ᶠ x in l, f x < ⊤ :=
h.mono fun _ hx => hx.lt_top
#align filter.eventually.lt_top_of_ne Filter.Eventually.lt_top_of_ne
theorem Eventually.lt_top_iff_ne_top [PartialOrder β] [OrderTop β] {l : Filter α} {f : α → β} :
(∀ᶠ x in l, f x < ⊤) ↔ ∀ᶠ x in l, f x ≠ ⊤ :=
⟨Eventually.ne_of_lt, Eventually.lt_top_of_ne⟩
#align filter.eventually.lt_top_iff_ne_top Filter.Eventually.lt_top_iff_ne_top
@[mono]
theorem EventuallyLE.inter {s t s' t' : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) (h' : s' ≤ᶠ[l] t') :
(s ∩ s' : Set α) ≤ᶠ[l] (t ∩ t' : Set α) :=
h'.mp <| h.mono fun _ => And.imp
#align filter.eventually_le.inter Filter.EventuallyLE.inter
@[mono]
theorem EventuallyLE.union {s t s' t' : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) (h' : s' ≤ᶠ[l] t') :
(s ∪ s' : Set α) ≤ᶠ[l] (t ∪ t' : Set α) :=
h'.mp <| h.mono fun _ => Or.imp
#align filter.eventually_le.union Filter.EventuallyLE.union
protected lemma EventuallyLE.iUnion [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i ≤ᶠ[l] t i) : (⋃ i, s i) ≤ᶠ[l] ⋃ i, t i :=
(eventually_all.2 h).mono fun _x hx hx' ↦
let ⟨i, hi⟩ := mem_iUnion.1 hx'; mem_iUnion.2 ⟨i, hx i hi⟩
protected lemma EventuallyEq.iUnion [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i =ᶠ[l] t i) : (⋃ i, s i) =ᶠ[l] ⋃ i, t i :=
(EventuallyLE.iUnion fun i ↦ (h i).le).antisymm <| .iUnion fun i ↦ (h i).symm.le
protected lemma EventuallyLE.iInter [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i ≤ᶠ[l] t i) : (⋂ i, s i) ≤ᶠ[l] ⋂ i, t i :=
(eventually_all.2 h).mono fun _x hx hx' ↦ mem_iInter.2 fun i ↦ hx i (mem_iInter.1 hx' i)
protected lemma EventuallyEq.iInter [Finite ι] {s t : ι → Set α}
(h : ∀ i, s i =ᶠ[l] t i) : (⋂ i, s i) =ᶠ[l] ⋂ i, t i :=
(EventuallyLE.iInter fun i ↦ (h i).le).antisymm <| .iInter fun i ↦ (h i).symm.le
lemma _root_.Set.Finite.eventuallyLE_iUnion {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋃ i ∈ s, f i) ≤ᶠ[l] (⋃ i ∈ s, g i) := by
have := hs.to_subtype
rw [biUnion_eq_iUnion, biUnion_eq_iUnion]
exact .iUnion fun i ↦ hle i.1 i.2
alias EventuallyLE.biUnion := Set.Finite.eventuallyLE_iUnion
lemma _root_.Set.Finite.eventuallyEq_iUnion {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋃ i ∈ s, f i) =ᶠ[l] (⋃ i ∈ s, g i) :=
(EventuallyLE.biUnion hs fun i hi ↦ (heq i hi).le).antisymm <|
.biUnion hs fun i hi ↦ (heq i hi).symm.le
alias EventuallyEq.biUnion := Set.Finite.eventuallyEq_iUnion
lemma _root_.Set.Finite.eventuallyLE_iInter {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋂ i ∈ s, f i) ≤ᶠ[l] (⋂ i ∈ s, g i) := by
have := hs.to_subtype
rw [biInter_eq_iInter, biInter_eq_iInter]
exact .iInter fun i ↦ hle i.1 i.2
alias EventuallyLE.biInter := Set.Finite.eventuallyLE_iInter
lemma _root_.Set.Finite.eventuallyEq_iInter {ι : Type*} {s : Set ι} (hs : s.Finite)
{f g : ι → Set α} (heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋂ i ∈ s, f i) =ᶠ[l] (⋂ i ∈ s, g i) :=
(EventuallyLE.biInter hs fun i hi ↦ (heq i hi).le).antisymm <|
.biInter hs fun i hi ↦ (heq i hi).symm.le
alias EventuallyEq.biInter := Set.Finite.eventuallyEq_iInter
lemma _root_.Finset.eventuallyLE_iUnion {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋃ i ∈ s, f i) ≤ᶠ[l] (⋃ i ∈ s, g i) :=
.biUnion s.finite_toSet hle
lemma _root_.Finset.eventuallyEq_iUnion {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋃ i ∈ s, f i) =ᶠ[l] (⋃ i ∈ s, g i) :=
.biUnion s.finite_toSet heq
lemma _root_.Finset.eventuallyLE_iInter {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(hle : ∀ i ∈ s, f i ≤ᶠ[l] g i) : (⋂ i ∈ s, f i) ≤ᶠ[l] (⋂ i ∈ s, g i) :=
.biInter s.finite_toSet hle
lemma _root_.Finset.eventuallyEq_iInter {ι : Type*} (s : Finset ι) {f g : ι → Set α}
(heq : ∀ i ∈ s, f i =ᶠ[l] g i) : (⋂ i ∈ s, f i) =ᶠ[l] (⋂ i ∈ s, g i) :=
.biInter s.finite_toSet heq
@[mono]
theorem EventuallyLE.compl {s t : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) :
(tᶜ : Set α) ≤ᶠ[l] (sᶜ : Set α) :=
h.mono fun _ => mt
#align filter.eventually_le.compl Filter.EventuallyLE.compl
@[mono]
theorem EventuallyLE.diff {s t s' t' : Set α} {l : Filter α} (h : s ≤ᶠ[l] t) (h' : t' ≤ᶠ[l] s') :
(s \ s' : Set α) ≤ᶠ[l] (t \ t' : Set α) :=
h.inter h'.compl
#align filter.eventually_le.diff Filter.EventuallyLE.diff
theorem set_eventuallyLE_iff_mem_inf_principal {s t : Set α} {l : Filter α} :
s ≤ᶠ[l] t ↔ t ∈ l ⊓ 𝓟 s :=
eventually_inf_principal.symm
#align filter.set_eventually_le_iff_mem_inf_principal Filter.set_eventuallyLE_iff_mem_inf_principal
theorem set_eventuallyLE_iff_inf_principal_le {s t : Set α} {l : Filter α} :
s ≤ᶠ[l] t ↔ l ⊓ 𝓟 s ≤ l ⊓ 𝓟 t :=
set_eventuallyLE_iff_mem_inf_principal.trans <| by
simp only [le_inf_iff, inf_le_left, true_and_iff, le_principal_iff]
#align filter.set_eventually_le_iff_inf_principal_le Filter.set_eventuallyLE_iff_inf_principal_le
theorem set_eventuallyEq_iff_inf_principal {s t : Set α} {l : Filter α} :
s =ᶠ[l] t ↔ l ⊓ 𝓟 s = l ⊓ 𝓟 t := by
simp only [eventuallyLE_antisymm_iff, le_antisymm_iff, set_eventuallyLE_iff_inf_principal_le]
#align filter.set_eventually_eq_iff_inf_principal Filter.set_eventuallyEq_iff_inf_principal
theorem EventuallyLE.mul_le_mul [MulZeroClass β] [PartialOrder β] [PosMulMono β] [MulPosMono β]
{l : Filter α} {f₁ f₂ g₁ g₂ : α → β} (hf : f₁ ≤ᶠ[l] f₂) (hg : g₁ ≤ᶠ[l] g₂) (hg₀ : 0 ≤ᶠ[l] g₁)
(hf₀ : 0 ≤ᶠ[l] f₂) : f₁ * g₁ ≤ᶠ[l] f₂ * g₂ := by
filter_upwards [hf, hg, hg₀, hf₀] with x using _root_.mul_le_mul
#align filter.eventually_le.mul_le_mul Filter.EventuallyLE.mul_le_mul
@[to_additive EventuallyLE.add_le_add]
theorem EventuallyLE.mul_le_mul' [Mul β] [Preorder β] [CovariantClass β β (· * ·) (· ≤ ·)]
[CovariantClass β β (swap (· * ·)) (· ≤ ·)] {l : Filter α} {f₁ f₂ g₁ g₂ : α → β}
(hf : f₁ ≤ᶠ[l] f₂) (hg : g₁ ≤ᶠ[l] g₂) : f₁ * g₁ ≤ᶠ[l] f₂ * g₂ := by
filter_upwards [hf, hg] with x hfx hgx using _root_.mul_le_mul' hfx hgx
#align filter.eventually_le.mul_le_mul' Filter.EventuallyLE.mul_le_mul'
#align filter.eventually_le.add_le_add Filter.EventuallyLE.add_le_add
theorem EventuallyLE.mul_nonneg [OrderedSemiring β] {l : Filter α} {f g : α → β} (hf : 0 ≤ᶠ[l] f)
(hg : 0 ≤ᶠ[l] g) : 0 ≤ᶠ[l] f * g := by filter_upwards [hf, hg] with x using _root_.mul_nonneg
#align filter.eventually_le.mul_nonneg Filter.EventuallyLE.mul_nonneg
theorem eventually_sub_nonneg [OrderedRing β] {l : Filter α} {f g : α → β} :
0 ≤ᶠ[l] g - f ↔ f ≤ᶠ[l] g :=
eventually_congr <| eventually_of_forall fun _ => sub_nonneg
#align filter.eventually_sub_nonneg Filter.eventually_sub_nonneg
theorem EventuallyLE.sup [SemilatticeSup β] {l : Filter α} {f₁ f₂ g₁ g₂ : α → β} (hf : f₁ ≤ᶠ[l] f₂)
(hg : g₁ ≤ᶠ[l] g₂) : f₁ ⊔ g₁ ≤ᶠ[l] f₂ ⊔ g₂ := by
filter_upwards [hf, hg] with x hfx hgx using sup_le_sup hfx hgx
#align filter.eventually_le.sup Filter.EventuallyLE.sup
theorem EventuallyLE.sup_le [SemilatticeSup β] {l : Filter α} {f g h : α → β} (hf : f ≤ᶠ[l] h)
(hg : g ≤ᶠ[l] h) : f ⊔ g ≤ᶠ[l] h := by
filter_upwards [hf, hg] with x hfx hgx using _root_.sup_le hfx hgx
#align filter.eventually_le.sup_le Filter.EventuallyLE.sup_le
theorem EventuallyLE.le_sup_of_le_left [SemilatticeSup β] {l : Filter α} {f g h : α → β}
(hf : h ≤ᶠ[l] f) : h ≤ᶠ[l] f ⊔ g :=
hf.mono fun _ => _root_.le_sup_of_le_left
#align filter.eventually_le.le_sup_of_le_left Filter.EventuallyLE.le_sup_of_le_left
theorem EventuallyLE.le_sup_of_le_right [SemilatticeSup β] {l : Filter α} {f g h : α → β}
(hg : h ≤ᶠ[l] g) : h ≤ᶠ[l] f ⊔ g :=
hg.mono fun _ => _root_.le_sup_of_le_right
#align filter.eventually_le.le_sup_of_le_right Filter.EventuallyLE.le_sup_of_le_right
theorem join_le {f : Filter (Filter α)} {l : Filter α} (h : ∀ᶠ m in f, m ≤ l) : join f ≤ l :=
fun _ hs => h.mono fun _ hm => hm hs
#align filter.join_le Filter.join_le
/-! ### Push-forwards, pull-backs, and the monad structure -/
section Map
/-- The forward map of a filter -/
def map (m : α → β) (f : Filter α) : Filter β where
sets := preimage m ⁻¹' f.sets
univ_sets := univ_mem
sets_of_superset hs st := mem_of_superset hs <| preimage_mono st
inter_sets hs ht := inter_mem hs ht
#align filter.map Filter.map
@[simp]
theorem map_principal {s : Set α} {f : α → β} : map f (𝓟 s) = 𝓟 (Set.image f s) :=
Filter.ext fun _ => image_subset_iff.symm
#align filter.map_principal Filter.map_principal
variable {f : Filter α} {m : α → β} {m' : β → γ} {s : Set α} {t : Set β}
@[simp]
theorem eventually_map {P : β → Prop} : (∀ᶠ b in map m f, P b) ↔ ∀ᶠ a in f, P (m a) :=
Iff.rfl
#align filter.eventually_map Filter.eventually_map
@[simp]
theorem frequently_map {P : β → Prop} : (∃ᶠ b in map m f, P b) ↔ ∃ᶠ a in f, P (m a) :=
Iff.rfl
#align filter.frequently_map Filter.frequently_map
@[simp]
theorem mem_map : t ∈ map m f ↔ m ⁻¹' t ∈ f :=
Iff.rfl
#align filter.mem_map Filter.mem_map
theorem mem_map' : t ∈ map m f ↔ { x | m x ∈ t } ∈ f :=
Iff.rfl
#align filter.mem_map' Filter.mem_map'
theorem image_mem_map (hs : s ∈ f) : m '' s ∈ map m f :=
f.sets_of_superset hs <| subset_preimage_image m s
#align filter.image_mem_map Filter.image_mem_map
-- The simpNF linter says that the LHS can be simplified via `Filter.mem_map`.
-- However this is a higher priority lemma.
-- https://github.com/leanprover/std4/issues/207
@[simp 1100, nolint simpNF]
theorem image_mem_map_iff (hf : Injective m) : m '' s ∈ map m f ↔ s ∈ f :=
⟨fun h => by rwa [← preimage_image_eq s hf], image_mem_map⟩
#align filter.image_mem_map_iff Filter.image_mem_map_iff
theorem range_mem_map : range m ∈ map m f := by
rw [← image_univ]
exact image_mem_map univ_mem
#align filter.range_mem_map Filter.range_mem_map
theorem mem_map_iff_exists_image : t ∈ map m f ↔ ∃ s ∈ f, m '' s ⊆ t :=
⟨fun ht => ⟨m ⁻¹' t, ht, image_preimage_subset _ _⟩, fun ⟨_, hs, ht⟩ =>
mem_of_superset (image_mem_map hs) ht⟩
#align filter.mem_map_iff_exists_image Filter.mem_map_iff_exists_image
@[simp]
theorem map_id : Filter.map id f = f :=
filter_eq <| rfl
#align filter.map_id Filter.map_id
@[simp]
theorem map_id' : Filter.map (fun x => x) f = f :=
map_id
#align filter.map_id' Filter.map_id'
@[simp]
theorem map_compose : Filter.map m' ∘ Filter.map m = Filter.map (m' ∘ m) :=
funext fun _ => filter_eq <| rfl
#align filter.map_compose Filter.map_compose
@[simp]
theorem map_map : Filter.map m' (Filter.map m f) = Filter.map (m' ∘ m) f :=
congr_fun Filter.map_compose f
#align filter.map_map Filter.map_map
/-- If functions `m₁` and `m₂` are eventually equal at a filter `f`, then
they map this filter to the same filter. -/
theorem map_congr {m₁ m₂ : α → β} {f : Filter α} (h : m₁ =ᶠ[f] m₂) : map m₁ f = map m₂ f :=
Filter.ext' fun _ => eventually_congr (h.mono fun _ hx => hx ▸ Iff.rfl)
#align filter.map_congr Filter.map_congr
end Map
section Comap
/-- The inverse map of a filter. A set `s` belongs to `Filter.comap m f` if either of the following
equivalent conditions hold.
1. There exists a set `t ∈ f` such that `m ⁻¹' t ⊆ s`. This is used as a definition.
2. The set `kernImage m s = {y | ∀ x, m x = y → x ∈ s}` belongs to `f`, see `Filter.mem_comap'`.
3. The set `(m '' sᶜ)ᶜ` belongs to `f`, see `Filter.mem_comap_iff_compl` and
`Filter.compl_mem_comap`. -/
def comap (m : α → β) (f : Filter β) : Filter α where
sets := { s | ∃ t ∈ f, m ⁻¹' t ⊆ s }
univ_sets := ⟨univ, univ_mem, by simp only [subset_univ, preimage_univ]⟩
sets_of_superset := fun ⟨a', ha', ma'a⟩ ab => ⟨a', ha', ma'a.trans ab⟩
inter_sets := fun ⟨a', ha₁, ha₂⟩ ⟨b', hb₁, hb₂⟩ =>
⟨a' ∩ b', inter_mem ha₁ hb₁, inter_subset_inter ha₂ hb₂⟩
#align filter.comap Filter.comap
variable {f : α → β} {l : Filter β} {p : α → Prop} {s : Set α}
theorem mem_comap' : s ∈ comap f l ↔ { y | ∀ ⦃x⦄, f x = y → x ∈ s } ∈ l :=
⟨fun ⟨t, ht, hts⟩ => mem_of_superset ht fun y hy x hx => hts <| mem_preimage.2 <| by rwa [hx],
fun h => ⟨_, h, fun x hx => hx rfl⟩⟩
#align filter.mem_comap' Filter.mem_comap'
-- TODO: it would be nice to use `kernImage` much more to take advantage of common name and API,
-- and then this would become `mem_comap'`
theorem mem_comap'' : s ∈ comap f l ↔ kernImage f s ∈ l :=
mem_comap'
/-- RHS form is used, e.g., in the definition of `UniformSpace`. -/
lemma mem_comap_prod_mk {x : α} {s : Set β} {F : Filter (α × β)} :
s ∈ comap (Prod.mk x) F ↔ {p : α × β | p.fst = x → p.snd ∈ s} ∈ F := by
simp_rw [mem_comap', Prod.ext_iff, and_imp, @forall_swap β (_ = _), forall_eq, eq_comm]
#align filter.mem_comap_prod_mk Filter.mem_comap_prod_mk
@[simp]
theorem eventually_comap : (∀ᶠ a in comap f l, p a) ↔ ∀ᶠ b in l, ∀ a, f a = b → p a :=
mem_comap'
#align filter.eventually_comap Filter.eventually_comap
@[simp]
theorem frequently_comap : (∃ᶠ a in comap f l, p a) ↔ ∃ᶠ b in l, ∃ a, f a = b ∧ p a := by
simp only [Filter.Frequently, eventually_comap, not_exists, _root_.not_and]
#align filter.frequently_comap Filter.frequently_comap
theorem mem_comap_iff_compl : s ∈ comap f l ↔ (f '' sᶜ)ᶜ ∈ l := by
simp only [mem_comap'', kernImage_eq_compl]
#align filter.mem_comap_iff_compl Filter.mem_comap_iff_compl
theorem compl_mem_comap : sᶜ ∈ comap f l ↔ (f '' s)ᶜ ∈ l := by rw [mem_comap_iff_compl, compl_compl]
#align filter.compl_mem_comap Filter.compl_mem_comap
end Comap
section KernMap
/-- The analog of `kernImage` for filters. A set `s` belongs to `Filter.kernMap m f` if either of
the following equivalent conditions hold.
1. There exists a set `t ∈ f` such that `s = kernImage m t`. This is used as a definition.
2. There exists a set `t` such that `tᶜ ∈ f` and `sᶜ = m '' t`, see `Filter.mem_kernMap_iff_compl`
and `Filter.compl_mem_kernMap`.
This definition because it gives a right adjoint to `Filter.comap`, and because it has a nice
interpretation when working with `co-` filters (`Filter.cocompact`, `Filter.cofinite`, ...).
For example, `kernMap m (cocompact α)` is the filter generated by the complements of the sets
`m '' K` where `K` is a compact subset of `α`. -/
def kernMap (m : α → β) (f : Filter α) : Filter β where
sets := (kernImage m) '' f.sets
univ_sets := ⟨univ, f.univ_sets, by simp [kernImage_eq_compl]⟩
sets_of_superset := by
rintro _ t ⟨s, hs, rfl⟩ hst
refine ⟨s ∪ m ⁻¹' t, mem_of_superset hs subset_union_left, ?_⟩
rw [kernImage_union_preimage, union_eq_right.mpr hst]
inter_sets := by
rintro _ _ ⟨s₁, h₁, rfl⟩ ⟨s₂, h₂, rfl⟩
exact ⟨s₁ ∩ s₂, f.inter_sets h₁ h₂, Set.preimage_kernImage.u_inf⟩
variable {m : α → β} {f : Filter α}
theorem mem_kernMap {s : Set β} : s ∈ kernMap m f ↔ ∃ t ∈ f, kernImage m t = s :=
Iff.rfl
theorem mem_kernMap_iff_compl {s : Set β} : s ∈ kernMap m f ↔ ∃ t, tᶜ ∈ f ∧ m '' t = sᶜ := by
rw [mem_kernMap, compl_surjective.exists]
refine exists_congr (fun x ↦ and_congr_right fun _ ↦ ?_)
rw [kernImage_compl, compl_eq_comm, eq_comm]
theorem compl_mem_kernMap {s : Set β} : sᶜ ∈ kernMap m f ↔ ∃ t, tᶜ ∈ f ∧ m '' t = s := by
simp_rw [mem_kernMap_iff_compl, compl_compl]
end KernMap
/-- The monadic bind operation on filter is defined the usual way in terms of `map` and `join`.
Unfortunately, this `bind` does not result in the expected applicative. See `Filter.seq` for the
applicative instance. -/
def bind (f : Filter α) (m : α → Filter β) : Filter β :=
join (map m f)
#align filter.bind Filter.bind
/-- The applicative sequentiation operation. This is not induced by the bind operation. -/
def seq (f : Filter (α → β)) (g : Filter α) : Filter β where
sets := { s | ∃ u ∈ f, ∃ t ∈ g, ∀ m ∈ u, ∀ x ∈ t, (m : α → β) x ∈ s }
univ_sets := ⟨univ, univ_mem, univ, univ_mem, fun _ _ _ _ => trivial⟩
sets_of_superset := fun ⟨t₀, t₁, h₀, h₁, h⟩ hst =>
⟨t₀, t₁, h₀, h₁, fun _ hx _ hy => hst <| h _ hx _ hy⟩
inter_sets := fun ⟨t₀, ht₀, t₁, ht₁, ht⟩ ⟨u₀, hu₀, u₁, hu₁, hu⟩ =>
⟨t₀ ∩ u₀, inter_mem ht₀ hu₀, t₁ ∩ u₁, inter_mem ht₁ hu₁, fun _ ⟨hx₀, hx₁⟩ _ ⟨hy₀, hy₁⟩ =>
⟨ht _ hx₀ _ hy₀, hu _ hx₁ _ hy₁⟩⟩
#align filter.seq Filter.seq
/-- `pure x` is the set of sets that contain `x`. It is equal to `𝓟 {x}` but
with this definition we have `s ∈ pure a` defeq `a ∈ s`. -/
instance : Pure Filter :=
⟨fun x =>
{ sets := { s | x ∈ s }
inter_sets := And.intro
sets_of_superset := fun hs hst => hst hs
univ_sets := trivial }⟩
instance : Bind Filter :=
⟨@Filter.bind⟩
instance : Functor Filter where map := @Filter.map
instance : LawfulFunctor (Filter : Type u → Type u) where
id_map _ := map_id
comp_map _ _ _ := map_map.symm
map_const := rfl
theorem pure_sets (a : α) : (pure a : Filter α).sets = { s | a ∈ s } :=
rfl
#align filter.pure_sets Filter.pure_sets
@[simp]
theorem mem_pure {a : α} {s : Set α} : s ∈ (pure a : Filter α) ↔ a ∈ s :=
Iff.rfl
#align filter.mem_pure Filter.mem_pure
@[simp]
theorem eventually_pure {a : α} {p : α → Prop} : (∀ᶠ x in pure a, p x) ↔ p a :=
Iff.rfl
#align filter.eventually_pure Filter.eventually_pure
@[simp]
theorem principal_singleton (a : α) : 𝓟 {a} = pure a :=
Filter.ext fun s => by simp only [mem_pure, mem_principal, singleton_subset_iff]
#align filter.principal_singleton Filter.principal_singleton
@[simp]
theorem map_pure (f : α → β) (a : α) : map f (pure a) = pure (f a) :=
rfl
#align filter.map_pure Filter.map_pure
theorem pure_le_principal (a : α) : pure a ≤ 𝓟 s ↔ a ∈ s := by
simp
@[simp] theorem join_pure (f : Filter α) : join (pure f) = f := rfl
#align filter.join_pure Filter.join_pure
@[simp]
theorem pure_bind (a : α) (m : α → Filter β) : bind (pure a) m = m a := by
simp only [Bind.bind, bind, map_pure, join_pure]
#align filter.pure_bind Filter.pure_bind
theorem map_bind {α β} (m : β → γ) (f : Filter α) (g : α → Filter β) :
map m (bind f g) = bind f (map m ∘ g) :=
rfl
theorem bind_map {α β} (m : α → β) (f : Filter α) (g : β → Filter γ) :
(bind (map m f) g) = bind f (g ∘ m) :=
rfl
/-!
### `Filter` as a `Monad`
In this section we define `Filter.monad`, a `Monad` structure on `Filter`s. This definition is not
an instance because its `Seq` projection is not equal to the `Filter.seq` function we use in the
`Applicative` instance on `Filter`.
-/
section
/-- The monad structure on filters. -/
protected def monad : Monad Filter where map := @Filter.map
#align filter.monad Filter.monad
attribute [local instance] Filter.monad
protected theorem lawfulMonad : LawfulMonad Filter where
map_const := rfl
id_map _ := rfl
seqLeft_eq _ _ := rfl
seqRight_eq _ _ := rfl
pure_seq _ _ := rfl
bind_pure_comp _ _ := rfl
bind_map _ _ := rfl
pure_bind _ _ := rfl
bind_assoc _ _ _ := rfl
#align filter.is_lawful_monad Filter.lawfulMonad
end
instance : Alternative Filter where
seq := fun x y => x.seq (y ())
failure := ⊥
orElse x y := x ⊔ y ()
@[simp]
theorem map_def {α β} (m : α → β) (f : Filter α) : m <$> f = map m f :=
rfl
#align filter.map_def Filter.map_def
@[simp]
theorem bind_def {α β} (f : Filter α) (m : α → Filter β) : f >>= m = bind f m :=
rfl
#align filter.bind_def Filter.bind_def
/-! #### `map` and `comap` equations -/
section Map
variable {f f₁ f₂ : Filter α} {g g₁ g₂ : Filter β} {m : α → β} {m' : β → γ} {s : Set α} {t : Set β}
@[simp] theorem mem_comap : s ∈ comap m g ↔ ∃ t ∈ g, m ⁻¹' t ⊆ s := Iff.rfl
#align filter.mem_comap Filter.mem_comap
theorem preimage_mem_comap (ht : t ∈ g) : m ⁻¹' t ∈ comap m g :=
⟨t, ht, Subset.rfl⟩
#align filter.preimage_mem_comap Filter.preimage_mem_comap
theorem Eventually.comap {p : β → Prop} (hf : ∀ᶠ b in g, p b) (f : α → β) :
∀ᶠ a in comap f g, p (f a) :=
preimage_mem_comap hf
#align filter.eventually.comap Filter.Eventually.comap
theorem comap_id : comap id f = f :=
le_antisymm (fun _ => preimage_mem_comap) fun _ ⟨_, ht, hst⟩ => mem_of_superset ht hst
#align filter.comap_id Filter.comap_id
theorem comap_id' : comap (fun x => x) f = f := comap_id
#align filter.comap_id' Filter.comap_id'
theorem comap_const_of_not_mem {x : β} (ht : t ∈ g) (hx : x ∉ t) : comap (fun _ : α => x) g = ⊥ :=
empty_mem_iff_bot.1 <| mem_comap'.2 <| mem_of_superset ht fun _ hx' _ h => hx <| h.symm ▸ hx'
#align filter.comap_const_of_not_mem Filter.comap_const_of_not_mem
theorem comap_const_of_mem {x : β} (h : ∀ t ∈ g, x ∈ t) : comap (fun _ : α => x) g = ⊤ :=
top_unique fun _ hs => univ_mem' fun _ => h _ (mem_comap'.1 hs) rfl
#align filter.comap_const_of_mem Filter.comap_const_of_mem
theorem map_const [NeBot f] {c : β} : (f.map fun _ => c) = pure c := by
ext s
by_cases h : c ∈ s <;> simp [h]
#align filter.map_const Filter.map_const
theorem comap_comap {m : γ → β} {n : β → α} : comap m (comap n f) = comap (n ∘ m) f :=
Filter.coext fun s => by simp only [compl_mem_comap, image_image, (· ∘ ·)]
#align filter.comap_comap Filter.comap_comap
section comm
/-!
The variables in the following lemmas are used as in this diagram:
```
φ
α → β
θ ↓ ↓ ψ
γ → δ
ρ
```
-/
variable {φ : α → β} {θ : α → γ} {ψ : β → δ} {ρ : γ → δ} (H : ψ ∘ φ = ρ ∘ θ)
theorem map_comm (F : Filter α) : map ψ (map φ F) = map ρ (map θ F) := by
rw [Filter.map_map, H, ← Filter.map_map]
#align filter.map_comm Filter.map_comm
theorem comap_comm (G : Filter δ) : comap φ (comap ψ G) = comap θ (comap ρ G) := by
rw [Filter.comap_comap, H, ← Filter.comap_comap]
#align filter.comap_comm Filter.comap_comm
end comm
theorem _root_.Function.Semiconj.filter_map {f : α → β} {ga : α → α} {gb : β → β}
(h : Function.Semiconj f ga gb) : Function.Semiconj (map f) (map ga) (map gb) :=
map_comm h.comp_eq
#align function.semiconj.filter_map Function.Semiconj.filter_map
theorem _root_.Function.Commute.filter_map {f g : α → α} (h : Function.Commute f g) :
Function.Commute (map f) (map g) :=
h.semiconj.filter_map
#align function.commute.filter_map Function.Commute.filter_map
theorem _root_.Function.Semiconj.filter_comap {f : α → β} {ga : α → α} {gb : β → β}
(h : Function.Semiconj f ga gb) : Function.Semiconj (comap f) (comap gb) (comap ga) :=
comap_comm h.comp_eq.symm
#align function.semiconj.filter_comap Function.Semiconj.filter_comap
theorem _root_.Function.Commute.filter_comap {f g : α → α} (h : Function.Commute f g) :
Function.Commute (comap f) (comap g) :=
h.semiconj.filter_comap
#align function.commute.filter_comap Function.Commute.filter_comap
section
open Filter
theorem _root_.Function.LeftInverse.filter_map {f : α → β} {g : β → α} (hfg : LeftInverse g f) :
LeftInverse (map g) (map f) := fun F ↦ by
rw [map_map, hfg.comp_eq_id, map_id]
theorem _root_.Function.LeftInverse.filter_comap {f : α → β} {g : β → α} (hfg : LeftInverse g f) :
RightInverse (comap g) (comap f) := fun F ↦ by
rw [comap_comap, hfg.comp_eq_id, comap_id]
nonrec theorem _root_.Function.RightInverse.filter_map {f : α → β} {g : β → α}
(hfg : RightInverse g f) : RightInverse (map g) (map f) :=
hfg.filter_map
nonrec theorem _root_.Function.RightInverse.filter_comap {f : α → β} {g : β → α}
(hfg : RightInverse g f) : LeftInverse (comap g) (comap f) :=
hfg.filter_comap
theorem _root_.Set.LeftInvOn.filter_map_Iic {f : α → β} {g : β → α} (hfg : LeftInvOn g f s) :
LeftInvOn (map g) (map f) (Iic <| 𝓟 s) := fun F (hF : F ≤ 𝓟 s) ↦ by
have : (g ∘ f) =ᶠ[𝓟 s] id := by simpa only [eventuallyEq_principal] using hfg
rw [map_map, map_congr (this.filter_mono hF), map_id]
nonrec theorem _root_.Set.RightInvOn.filter_map_Iic {f : α → β} {g : β → α}
(hfg : RightInvOn g f t) : RightInvOn (map g) (map f) (Iic <| 𝓟 t) :=
hfg.filter_map_Iic
end
@[simp]
theorem comap_principal {t : Set β} : comap m (𝓟 t) = 𝓟 (m ⁻¹' t) :=
Filter.ext fun _ => ⟨fun ⟨_u, hu, b⟩ => (preimage_mono hu).trans b,
fun h => ⟨t, Subset.rfl, h⟩⟩
#align filter.comap_principal Filter.comap_principal
theorem principal_subtype {α : Type*} (s : Set α) (t : Set s) :
𝓟 t = comap (↑) (𝓟 (((↑) : s → α) '' t)) := by
rw [comap_principal, preimage_image_eq _ Subtype.coe_injective]
#align principal_subtype Filter.principal_subtype
@[simp]
theorem comap_pure {b : β} : comap m (pure b) = 𝓟 (m ⁻¹' {b}) := by
rw [← principal_singleton, comap_principal]
#align filter.comap_pure Filter.comap_pure
theorem map_le_iff_le_comap : map m f ≤ g ↔ f ≤ comap m g :=
⟨fun h _ ⟨_, ht, hts⟩ => mem_of_superset (h ht) hts, fun h _ ht => h ⟨_, ht, Subset.rfl⟩⟩
#align filter.map_le_iff_le_comap Filter.map_le_iff_le_comap
theorem gc_map_comap (m : α → β) : GaloisConnection (map m) (comap m) :=
fun _ _ => map_le_iff_le_comap
#align filter.gc_map_comap Filter.gc_map_comap
theorem comap_le_iff_le_kernMap : comap m g ≤ f ↔ g ≤ kernMap m f := by
simp [Filter.le_def, mem_comap'', mem_kernMap, -mem_comap]
theorem gc_comap_kernMap (m : α → β) : GaloisConnection (comap m) (kernMap m) :=
fun _ _ ↦ comap_le_iff_le_kernMap
theorem kernMap_principal {s : Set α} : kernMap m (𝓟 s) = 𝓟 (kernImage m s) := by
refine eq_of_forall_le_iff (fun g ↦ ?_)
rw [← comap_le_iff_le_kernMap, le_principal_iff, le_principal_iff, mem_comap'']
@[mono]
theorem map_mono : Monotone (map m) :=
(gc_map_comap m).monotone_l
#align filter.map_mono Filter.map_mono
@[mono]
theorem comap_mono : Monotone (comap m) :=
(gc_map_comap m).monotone_u
#align filter.comap_mono Filter.comap_mono
/-- Temporary lemma that we can tag with `gcongr` -/
@[gcongr, deprecated] theorem map_le_map (h : F ≤ G) : map m F ≤ map m G := map_mono h
/-- Temporary lemma that we can tag with `gcongr` -/
@[gcongr, deprecated] theorem comap_le_comap (h : F ≤ G) : comap m F ≤ comap m G := comap_mono h
@[simp] theorem map_bot : map m ⊥ = ⊥ := (gc_map_comap m).l_bot
#align filter.map_bot Filter.map_bot
@[simp] theorem map_sup : map m (f₁ ⊔ f₂) = map m f₁ ⊔ map m f₂ := (gc_map_comap m).l_sup
#align filter.map_sup Filter.map_sup
@[simp]
theorem map_iSup {f : ι → Filter α} : map m (⨆ i, f i) = ⨆ i, map m (f i) :=
(gc_map_comap m).l_iSup
#align filter.map_supr Filter.map_iSup
@[simp]
theorem map_top (f : α → β) : map f ⊤ = 𝓟 (range f) := by
rw [← principal_univ, map_principal, image_univ]
#align filter.map_top Filter.map_top
@[simp] theorem comap_top : comap m ⊤ = ⊤ := (gc_map_comap m).u_top
#align filter.comap_top Filter.comap_top
@[simp] theorem comap_inf : comap m (g₁ ⊓ g₂) = comap m g₁ ⊓ comap m g₂ := (gc_map_comap m).u_inf
#align filter.comap_inf Filter.comap_inf
@[simp]
theorem comap_iInf {f : ι → Filter β} : comap m (⨅ i, f i) = ⨅ i, comap m (f i) :=
(gc_map_comap m).u_iInf
#align filter.comap_infi Filter.comap_iInf
theorem le_comap_top (f : α → β) (l : Filter α) : l ≤ comap f ⊤ := by
rw [comap_top]
exact le_top
#align filter.le_comap_top Filter.le_comap_top
theorem map_comap_le : map m (comap m g) ≤ g :=
(gc_map_comap m).l_u_le _
#align filter.map_comap_le Filter.map_comap_le
theorem le_comap_map : f ≤ comap m (map m f) :=
(gc_map_comap m).le_u_l _
#align filter.le_comap_map Filter.le_comap_map
@[simp]
theorem comap_bot : comap m ⊥ = ⊥ :=
bot_unique fun s _ => ⟨∅, mem_bot, by simp only [empty_subset, preimage_empty]⟩
#align filter.comap_bot Filter.comap_bot
theorem neBot_of_comap (h : (comap m g).NeBot) : g.NeBot := by
rw [neBot_iff] at *
contrapose! h
rw [h]
exact comap_bot
#align filter.ne_bot_of_comap Filter.neBot_of_comap
theorem comap_inf_principal_range : comap m (g ⊓ 𝓟 (range m)) = comap m g := by
simp
#align filter.comap_inf_principal_range Filter.comap_inf_principal_range
theorem disjoint_comap (h : Disjoint g₁ g₂) : Disjoint (comap m g₁) (comap m g₂) := by
simp only [disjoint_iff, ← comap_inf, h.eq_bot, comap_bot]
#align filter.disjoint_comap Filter.disjoint_comap
theorem comap_iSup {ι} {f : ι → Filter β} {m : α → β} : comap m (iSup f) = ⨆ i, comap m (f i) :=
(gc_comap_kernMap m).l_iSup
#align filter.comap_supr Filter.comap_iSup
theorem comap_sSup {s : Set (Filter β)} {m : α → β} : comap m (sSup s) = ⨆ f ∈ s, comap m f := by
simp only [sSup_eq_iSup, comap_iSup, eq_self_iff_true]
#align filter.comap_Sup Filter.comap_sSup
theorem comap_sup : comap m (g₁ ⊔ g₂) = comap m g₁ ⊔ comap m g₂ := by
rw [sup_eq_iSup, comap_iSup, iSup_bool_eq, Bool.cond_true, Bool.cond_false]
#align filter.comap_sup Filter.comap_sup
theorem map_comap (f : Filter β) (m : α → β) : (f.comap m).map m = f ⊓ 𝓟 (range m) := by
refine le_antisymm (le_inf map_comap_le <| le_principal_iff.2 range_mem_map) ?_
rintro t' ⟨t, ht, sub⟩
refine mem_inf_principal.2 (mem_of_superset ht ?_)
rintro _ hxt ⟨x, rfl⟩
exact sub hxt
#align filter.map_comap Filter.map_comap
theorem map_comap_setCoe_val (f : Filter β) (s : Set β) :
(f.comap ((↑) : s → β)).map (↑) = f ⊓ 𝓟 s := by
rw [map_comap, Subtype.range_val]
theorem map_comap_of_mem {f : Filter β} {m : α → β} (hf : range m ∈ f) : (f.comap m).map m = f := by
rw [map_comap, inf_eq_left.2 (le_principal_iff.2 hf)]
#align filter.map_comap_of_mem Filter.map_comap_of_mem
instance canLift (c) (p) [CanLift α β c p] :
CanLift (Filter α) (Filter β) (map c) fun f => ∀ᶠ x : α in f, p x where
prf f hf := ⟨comap c f, map_comap_of_mem <| hf.mono CanLift.prf⟩
#align filter.can_lift Filter.canLift
theorem comap_le_comap_iff {f g : Filter β} {m : α → β} (hf : range m ∈ f) :
comap m f ≤ comap m g ↔ f ≤ g :=
⟨fun h => map_comap_of_mem hf ▸ (map_mono h).trans map_comap_le, fun h => comap_mono h⟩
#align filter.comap_le_comap_iff Filter.comap_le_comap_iff
theorem map_comap_of_surjective {f : α → β} (hf : Surjective f) (l : Filter β) :
map f (comap f l) = l :=
map_comap_of_mem <| by simp only [hf.range_eq, univ_mem]
#align filter.map_comap_of_surjective Filter.map_comap_of_surjective
theorem comap_injective {f : α → β} (hf : Surjective f) : Injective (comap f) :=
LeftInverse.injective <| map_comap_of_surjective hf
theorem _root_.Function.Surjective.filter_map_top {f : α → β} (hf : Surjective f) : map f ⊤ = ⊤ :=
(congr_arg _ comap_top).symm.trans <| map_comap_of_surjective hf ⊤
#align function.surjective.filter_map_top Function.Surjective.filter_map_top
theorem subtype_coe_map_comap (s : Set α) (f : Filter α) :
map ((↑) : s → α) (comap ((↑) : s → α) f) = f ⊓ 𝓟 s := by rw [map_comap, Subtype.range_coe]
#align filter.subtype_coe_map_comap Filter.subtype_coe_map_comap
theorem image_mem_of_mem_comap {f : Filter α} {c : β → α} (h : range c ∈ f) {W : Set β}
(W_in : W ∈ comap c f) : c '' W ∈ f := by
rw [← map_comap_of_mem h]
exact image_mem_map W_in
#align filter.image_mem_of_mem_comap Filter.image_mem_of_mem_comap
theorem image_coe_mem_of_mem_comap {f : Filter α} {U : Set α} (h : U ∈ f) {W : Set U}
(W_in : W ∈ comap ((↑) : U → α) f) : (↑) '' W ∈ f :=
image_mem_of_mem_comap (by simp [h]) W_in
#align filter.image_coe_mem_of_mem_comap Filter.image_coe_mem_of_mem_comap
theorem comap_map {f : Filter α} {m : α → β} (h : Injective m) : comap m (map m f) = f :=
le_antisymm
(fun s hs =>
mem_of_superset (preimage_mem_comap <| image_mem_map hs) <| by
simp only [preimage_image_eq s h, Subset.rfl])
le_comap_map
#align filter.comap_map Filter.comap_map
theorem mem_comap_iff {f : Filter β} {m : α → β} (inj : Injective m) (large : Set.range m ∈ f)
{S : Set α} : S ∈ comap m f ↔ m '' S ∈ f := by
rw [← image_mem_map_iff inj, map_comap_of_mem large]
#align filter.mem_comap_iff Filter.mem_comap_iff
theorem map_le_map_iff_of_injOn {l₁ l₂ : Filter α} {f : α → β} {s : Set α} (h₁ : s ∈ l₁)
(h₂ : s ∈ l₂) (hinj : InjOn f s) : map f l₁ ≤ map f l₂ ↔ l₁ ≤ l₂ :=
⟨fun h _t ht =>
mp_mem h₁ <|
mem_of_superset (h <| image_mem_map (inter_mem h₂ ht)) fun _y ⟨_x, ⟨hxs, hxt⟩, hxy⟩ hys =>
hinj hxs hys hxy ▸ hxt,
fun h => map_mono h⟩
#align filter.map_le_map_iff_of_inj_on Filter.map_le_map_iff_of_injOn
theorem map_le_map_iff {f g : Filter α} {m : α → β} (hm : Injective m) :
map m f ≤ map m g ↔ f ≤ g := by rw [map_le_iff_le_comap, comap_map hm]
#align filter.map_le_map_iff Filter.map_le_map_iff
theorem map_eq_map_iff_of_injOn {f g : Filter α} {m : α → β} {s : Set α} (hsf : s ∈ f) (hsg : s ∈ g)
(hm : InjOn m s) : map m f = map m g ↔ f = g := by
simp only [le_antisymm_iff, map_le_map_iff_of_injOn hsf hsg hm,
map_le_map_iff_of_injOn hsg hsf hm]
#align filter.map_eq_map_iff_of_inj_on Filter.map_eq_map_iff_of_injOn
theorem map_inj {f g : Filter α} {m : α → β} (hm : Injective m) : map m f = map m g ↔ f = g :=
map_eq_map_iff_of_injOn univ_mem univ_mem hm.injOn
#align filter.map_inj Filter.map_inj
theorem map_injective {m : α → β} (hm : Injective m) : Injective (map m) := fun _ _ =>
(map_inj hm).1
#align filter.map_injective Filter.map_injective
theorem comap_neBot_iff {f : Filter β} {m : α → β} : NeBot (comap m f) ↔ ∀ t ∈ f, ∃ a, m a ∈ t := by
simp only [← forall_mem_nonempty_iff_neBot, mem_comap, forall_exists_index, and_imp]
exact ⟨fun h t t_in => h (m ⁻¹' t) t t_in Subset.rfl, fun h s t ht hst => (h t ht).imp hst⟩
#align filter.comap_ne_bot_iff Filter.comap_neBot_iff
theorem comap_neBot {f : Filter β} {m : α → β} (hm : ∀ t ∈ f, ∃ a, m a ∈ t) : NeBot (comap m f) :=
comap_neBot_iff.mpr hm
#align filter.comap_ne_bot Filter.comap_neBot
theorem comap_neBot_iff_frequently {f : Filter β} {m : α → β} :
NeBot (comap m f) ↔ ∃ᶠ y in f, y ∈ range m := by
simp only [comap_neBot_iff, frequently_iff, mem_range, @and_comm (_ ∈ _), exists_exists_eq_and]
#align filter.comap_ne_bot_iff_frequently Filter.comap_neBot_iff_frequently
theorem comap_neBot_iff_compl_range {f : Filter β} {m : α → β} :
NeBot (comap m f) ↔ (range m)ᶜ ∉ f :=
comap_neBot_iff_frequently
#align filter.comap_ne_bot_iff_compl_range Filter.comap_neBot_iff_compl_range
theorem comap_eq_bot_iff_compl_range {f : Filter β} {m : α → β} : comap m f = ⊥ ↔ (range m)ᶜ ∈ f :=
not_iff_not.mp <| neBot_iff.symm.trans comap_neBot_iff_compl_range
#align filter.comap_eq_bot_iff_compl_range Filter.comap_eq_bot_iff_compl_range
theorem comap_surjective_eq_bot {f : Filter β} {m : α → β} (hm : Surjective m) :
comap m f = ⊥ ↔ f = ⊥ := by
rw [comap_eq_bot_iff_compl_range, hm.range_eq, compl_univ, empty_mem_iff_bot]
#align filter.comap_surjective_eq_bot Filter.comap_surjective_eq_bot
theorem disjoint_comap_iff (h : Surjective m) :
Disjoint (comap m g₁) (comap m g₂) ↔ Disjoint g₁ g₂ := by
rw [disjoint_iff, disjoint_iff, ← comap_inf, comap_surjective_eq_bot h]
#align filter.disjoint_comap_iff Filter.disjoint_comap_iff
theorem NeBot.comap_of_range_mem {f : Filter β} {m : α → β} (_ : NeBot f) (hm : range m ∈ f) :
NeBot (comap m f) :=
comap_neBot_iff_frequently.2 <| Eventually.frequently hm
#align filter.ne_bot.comap_of_range_mem Filter.NeBot.comap_of_range_mem
@[simp]
theorem comap_fst_neBot_iff {f : Filter α} :
(f.comap (Prod.fst : α × β → α)).NeBot ↔ f.NeBot ∧ Nonempty β := by
cases isEmpty_or_nonempty β
· rw [filter_eq_bot_of_isEmpty (f.comap _), ← not_iff_not]; simp [*]
· simp [comap_neBot_iff_frequently, *]
#align filter.comap_fst_ne_bot_iff Filter.comap_fst_neBot_iff
@[instance]
theorem comap_fst_neBot [Nonempty β] {f : Filter α} [NeBot f] :
(f.comap (Prod.fst : α × β → α)).NeBot :=
comap_fst_neBot_iff.2 ⟨‹_›, ‹_›⟩
#align filter.comap_fst_ne_bot Filter.comap_fst_neBot
@[simp]
theorem comap_snd_neBot_iff {f : Filter β} :
(f.comap (Prod.snd : α × β → β)).NeBot ↔ Nonempty α ∧ f.NeBot := by
cases' isEmpty_or_nonempty α with hα hα
· rw [filter_eq_bot_of_isEmpty (f.comap _), ← not_iff_not]; simp
· simp [comap_neBot_iff_frequently, hα]
#align filter.comap_snd_ne_bot_iff Filter.comap_snd_neBot_iff
@[instance]
theorem comap_snd_neBot [Nonempty α] {f : Filter β} [NeBot f] :
(f.comap (Prod.snd : α × β → β)).NeBot :=
comap_snd_neBot_iff.2 ⟨‹_›, ‹_›⟩
#align filter.comap_snd_ne_bot Filter.comap_snd_neBot
theorem comap_eval_neBot_iff' {ι : Type*} {α : ι → Type*} {i : ι} {f : Filter (α i)} :
(comap (eval i) f).NeBot ↔ (∀ j, Nonempty (α j)) ∧ NeBot f := by
cases' isEmpty_or_nonempty (∀ j, α j) with H H
· rw [filter_eq_bot_of_isEmpty (f.comap _), ← not_iff_not]
simp [← Classical.nonempty_pi]
· have : ∀ j, Nonempty (α j) := Classical.nonempty_pi.1 H
simp [comap_neBot_iff_frequently, *]
#align filter.comap_eval_ne_bot_iff' Filter.comap_eval_neBot_iff'
@[simp]
theorem comap_eval_neBot_iff {ι : Type*} {α : ι → Type*} [∀ j, Nonempty (α j)] {i : ι}
{f : Filter (α i)} : (comap (eval i) f).NeBot ↔ NeBot f := by simp [comap_eval_neBot_iff', *]
#align filter.comap_eval_ne_bot_iff Filter.comap_eval_neBot_iff
@[instance]
theorem comap_eval_neBot {ι : Type*} {α : ι → Type*} [∀ j, Nonempty (α j)] (i : ι)
(f : Filter (α i)) [NeBot f] : (comap (eval i) f).NeBot :=
comap_eval_neBot_iff.2 ‹_›
#align filter.comap_eval_ne_bot Filter.comap_eval_neBot
theorem comap_inf_principal_neBot_of_image_mem {f : Filter β} {m : α → β} (hf : NeBot f) {s : Set α}
(hs : m '' s ∈ f) : NeBot (comap m f ⊓ 𝓟 s) := by
refine ⟨compl_compl s ▸ mt mem_of_eq_bot ?_⟩
rintro ⟨t, ht, hts⟩
rcases hf.nonempty_of_mem (inter_mem hs ht) with ⟨_, ⟨x, hxs, rfl⟩, hxt⟩
exact absurd hxs (hts hxt)
#align filter.comap_inf_principal_ne_bot_of_image_mem Filter.comap_inf_principal_neBot_of_image_mem
theorem comap_coe_neBot_of_le_principal {s : Set γ} {l : Filter γ} [h : NeBot l] (h' : l ≤ 𝓟 s) :
NeBot (comap ((↑) : s → γ) l) :=
h.comap_of_range_mem <| (@Subtype.range_coe γ s).symm ▸ h' (mem_principal_self s)
#align filter.comap_coe_ne_bot_of_le_principal Filter.comap_coe_neBot_of_le_principal
theorem NeBot.comap_of_surj {f : Filter β} {m : α → β} (hf : NeBot f) (hm : Surjective m) :
NeBot (comap m f) :=
hf.comap_of_range_mem <| univ_mem' hm
#align filter.ne_bot.comap_of_surj Filter.NeBot.comap_of_surj
theorem NeBot.comap_of_image_mem {f : Filter β} {m : α → β} (hf : NeBot f) {s : Set α}
(hs : m '' s ∈ f) : NeBot (comap m f) :=
hf.comap_of_range_mem <| mem_of_superset hs (image_subset_range _ _)
#align filter.ne_bot.comap_of_image_mem Filter.NeBot.comap_of_image_mem
@[simp]
theorem map_eq_bot_iff : map m f = ⊥ ↔ f = ⊥ :=
⟨by
rw [← empty_mem_iff_bot, ← empty_mem_iff_bot]
exact id, fun h => by simp only [h, map_bot]⟩
#align filter.map_eq_bot_iff Filter.map_eq_bot_iff
| Mathlib/Order/Filter/Basic.lean | 2,678 | 2,679 | theorem map_neBot_iff (f : α → β) {F : Filter α} : NeBot (map f F) ↔ NeBot F := by |
simp only [neBot_iff, Ne, map_eq_bot_iff]
|
/-
Copyright (c) 2020 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Andrew Yang
-/
import Mathlib.CategoryTheory.Monoidal.Functor
#align_import category_theory.monoidal.End from "leanprover-community/mathlib"@"85075bccb68ab7fa49fb05db816233fb790e4fe9"
/-!
# Endofunctors as a monoidal category.
We give the monoidal category structure on `C ⥤ C`,
and show that when `C` itself is monoidal, it embeds via a monoidal functor into `C ⥤ C`.
## TODO
Can we use this to show coherence results, e.g. a cheap proof that `λ_ (𝟙_ C) = ρ_ (𝟙_ C)`?
I suspect this is harder than is usually made out.
-/
universe v u
namespace CategoryTheory
variable (C : Type u) [Category.{v} C]
/-- The category of endofunctors of any category is a monoidal category,
with tensor product given by composition of functors
(and horizontal composition of natural transformations).
-/
def endofunctorMonoidalCategory : MonoidalCategory (C ⥤ C) where
tensorObj F G := F ⋙ G
whiskerLeft X _ _ F := whiskerLeft X F
whiskerRight F X := whiskerRight F X
tensorHom α β := α ◫ β
tensorUnit := 𝟭 C
associator F G H := Functor.associator F G H
leftUnitor F := Functor.leftUnitor F
rightUnitor F := Functor.rightUnitor F
#align category_theory.endofunctor_monoidal_category CategoryTheory.endofunctorMonoidalCategory
open CategoryTheory.MonoidalCategory
attribute [local instance] endofunctorMonoidalCategory
@[simp] theorem endofunctorMonoidalCategory_tensorUnit_obj (X : C) :
(𝟙_ (C ⥤ C)).obj X = X := rfl
@[simp] theorem endofunctorMonoidalCategory_tensorUnit_map {X Y : C} (f : X ⟶ Y) :
(𝟙_ (C ⥤ C)).map f = f := rfl
@[simp] theorem endofunctorMonoidalCategory_tensorObj_obj (F G : C ⥤ C) (X : C) :
(F ⊗ G).obj X = G.obj (F.obj X) := rfl
@[simp] theorem endofunctorMonoidalCategory_tensorObj_map (F G : C ⥤ C) {X Y : C} (f : X ⟶ Y) :
(F ⊗ G).map f = G.map (F.map f) := rfl
@[simp] theorem endofunctorMonoidalCategory_tensorMap_app
{F G H K : C ⥤ C} {α : F ⟶ G} {β : H ⟶ K} (X : C) :
(α ⊗ β).app X = β.app (F.obj X) ≫ K.map (α.app X) := rfl
@[simp] theorem endofunctorMonoidalCategory_whiskerLeft_app
{F H K : C ⥤ C} {β : H ⟶ K} (X : C) :
(F ◁ β).app X = β.app (F.obj X) := rfl
@[simp] theorem endofunctorMonoidalCategory_whiskerRight_app
{F G H : C ⥤ C} {α : F ⟶ G} (X : C) :
(α ▷ H).app X = H.map (α.app X) := rfl
@[simp] theorem endofunctorMonoidalCategory_associator_hom_app (F G H : C ⥤ C) (X : C) :
(α_ F G H).hom.app X = 𝟙 _ := rfl
@[simp] theorem endofunctorMonoidalCategory_associator_inv_app (F G H : C ⥤ C) (X : C) :
(α_ F G H).inv.app X = 𝟙 _ := rfl
@[simp] theorem endofunctorMonoidalCategory_leftUnitor_hom_app (F : C ⥤ C) (X : C) :
(λ_ F).hom.app X = 𝟙 _ := rfl
@[simp] theorem endofunctorMonoidalCategory_leftUnitor_inv_app (F : C ⥤ C) (X : C) :
(λ_ F).inv.app X = 𝟙 _ := rfl
@[simp] theorem endofunctorMonoidalCategory_rightUnitor_hom_app (F : C ⥤ C) (X : C) :
(ρ_ F).hom.app X = 𝟙 _ := rfl
@[simp] theorem endofunctorMonoidalCategory_rightUnitor_inv_app (F : C ⥤ C) (X : C) :
(ρ_ F).inv.app X = 𝟙 _ := rfl
/-- Tensoring on the right gives a monoidal functor from `C` into endofunctors of `C`.
-/
@[simps!]
def tensoringRightMonoidal [MonoidalCategory.{v} C] : MonoidalFunctor C (C ⥤ C) :=
{ tensoringRight C with
ε := (rightUnitorNatIso C).inv
μ := fun X Y => (isoWhiskerRight (curriedAssociatorNatIso C)
((evaluation C (C ⥤ C)).obj X ⋙ (evaluation C C).obj Y)).hom }
#align category_theory.tensoring_right_monoidal CategoryTheory.tensoringRightMonoidal
variable {C}
variable {M : Type*} [Category M] [MonoidalCategory M] (F : MonoidalFunctor M (C ⥤ C))
@[reassoc (attr := simp)]
theorem μ_hom_inv_app (i j : M) (X : C) : (F.μ i j).app X ≫ (F.μIso i j).inv.app X = 𝟙 _ :=
(F.μIso i j).hom_inv_id_app X
#align category_theory.μ_hom_inv_app CategoryTheory.μ_hom_inv_app
@[reassoc (attr := simp)]
theorem μ_inv_hom_app (i j : M) (X : C) : (F.μIso i j).inv.app X ≫ (F.μ i j).app X = 𝟙 _ :=
(F.μIso i j).inv_hom_id_app X
#align category_theory.μ_inv_hom_app CategoryTheory.μ_inv_hom_app
@[reassoc (attr := simp)]
theorem ε_hom_inv_app (X : C) : F.ε.app X ≫ F.εIso.inv.app X = 𝟙 _ :=
F.εIso.hom_inv_id_app X
#align category_theory.ε_hom_inv_app CategoryTheory.ε_hom_inv_app
@[reassoc (attr := simp)]
theorem ε_inv_hom_app (X : C) : F.εIso.inv.app X ≫ F.ε.app X = 𝟙 _ :=
F.εIso.inv_hom_id_app X
#align category_theory.ε_inv_hom_app CategoryTheory.ε_inv_hom_app
@[reassoc (attr := simp)]
theorem ε_naturality {X Y : C} (f : X ⟶ Y) : F.ε.app X ≫ (F.obj (𝟙_ M)).map f = f ≫ F.ε.app Y :=
(F.ε.naturality f).symm
#align category_theory.ε_naturality CategoryTheory.ε_naturality
@[reassoc (attr := simp)]
theorem ε_inv_naturality {X Y : C} (f : X ⟶ Y) :
(MonoidalFunctor.εIso F).inv.app X ≫ (𝟙_ (C ⥤ C)).map f = F.εIso.inv.app X ≫ f := by
aesop_cat
#align category_theory.ε_inv_naturality CategoryTheory.ε_inv_naturality
@[reassoc (attr := simp)]
theorem μ_naturality {m n : M} {X Y : C} (f : X ⟶ Y) :
(F.obj n).map ((F.obj m).map f) ≫ (F.μ m n).app Y = (F.μ m n).app X ≫ (F.obj _).map f :=
(F.toLaxMonoidalFunctor.μ m n).naturality f
#align category_theory.μ_naturality CategoryTheory.μ_naturality
-- This is a simp lemma in the reverse direction via `NatTrans.naturality`.
@[reassoc]
theorem μ_inv_naturality {m n : M} {X Y : C} (f : X ⟶ Y) :
(F.μIso m n).inv.app X ≫ (F.obj n).map ((F.obj m).map f) =
(F.obj _).map f ≫ (F.μIso m n).inv.app Y :=
((F.μIso m n).inv.naturality f).symm
#align category_theory.μ_inv_naturality CategoryTheory.μ_inv_naturality
-- This is not a simp lemma since it could be proved by the lemmas later.
@[reassoc]
theorem μ_naturality₂ {m n m' n' : M} (f : m ⟶ m') (g : n ⟶ n') (X : C) :
(F.map g).app ((F.obj m).obj X) ≫ (F.obj n').map ((F.map f).app X) ≫ (F.μ m' n').app X =
(F.μ m n).app X ≫ (F.map (f ⊗ g)).app X := by
have := congr_app (F.toLaxMonoidalFunctor.μ_natural f g) X
dsimp at this
simpa using this
#align category_theory.μ_naturality₂ CategoryTheory.μ_naturality₂
@[reassoc (attr := simp)]
theorem μ_naturalityₗ {m n m' : M} (f : m ⟶ m') (X : C) :
(F.obj n).map ((F.map f).app X) ≫ (F.μ m' n).app X =
(F.μ m n).app X ≫ (F.map (f ▷ n)).app X := by
rw [← tensorHom_id, ← μ_naturality₂ F f (𝟙 n) X]
simp
#align category_theory.μ_naturalityₗ CategoryTheory.μ_naturalityₗ
@[reassoc (attr := simp)]
theorem μ_naturalityᵣ {m n n' : M} (g : n ⟶ n') (X : C) :
(F.map g).app ((F.obj m).obj X) ≫ (F.μ m n').app X =
(F.μ m n).app X ≫ (F.map (m ◁ g)).app X := by
rw [← id_tensorHom, ← μ_naturality₂ F (𝟙 m) g X]
simp
#align category_theory.μ_naturalityᵣ CategoryTheory.μ_naturalityᵣ
@[reassoc (attr := simp)]
theorem μ_inv_naturalityₗ {m n m' : M} (f : m ⟶ m') (X : C) :
(F.μIso m n).inv.app X ≫ (F.obj n).map ((F.map f).app X) =
(F.map (f ▷ n)).app X ≫ (F.μIso m' n).inv.app X := by
rw [← IsIso.comp_inv_eq, Category.assoc, ← IsIso.eq_inv_comp]
simp
#align category_theory.μ_inv_naturalityₗ CategoryTheory.μ_inv_naturalityₗ
@[reassoc (attr := simp)]
theorem μ_inv_naturalityᵣ {m n n' : M} (g : n ⟶ n') (X : C) :
(F.μIso m n).inv.app X ≫ (F.map g).app ((F.obj m).obj X) =
(F.map (m ◁ g)).app X ≫ (F.μIso m n').inv.app X := by
rw [← IsIso.comp_inv_eq, Category.assoc, ← IsIso.eq_inv_comp]
simp
#align category_theory.μ_inv_naturalityᵣ CategoryTheory.μ_inv_naturalityᵣ
@[reassoc]
| Mathlib/CategoryTheory/Monoidal/End.lean | 191 | 195 | theorem left_unitality_app (n : M) (X : C) :
(F.obj n).map (F.ε.app X) ≫ (F.μ (𝟙_ M) n).app X ≫ (F.map (λ_ n).hom).app X = 𝟙 _ := by |
have := congr_app (F.toLaxMonoidalFunctor.left_unitality n) X
dsimp at this
simpa using this.symm
|
/-
Copyright (c) 2019 Jean Lo. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jean Lo, Yaël Dillies, Moritz Doll
-/
import Mathlib.Data.Real.Pointwise
import Mathlib.Analysis.Convex.Function
import Mathlib.Analysis.LocallyConvex.Basic
import Mathlib.Data.Real.Sqrt
#align_import analysis.seminorm from "leanprover-community/mathlib"@"09079525fd01b3dda35e96adaa08d2f943e1648c"
/-!
# Seminorms
This file defines seminorms.
A seminorm is a function to the reals which is positive-semidefinite, absolutely homogeneous, and
subadditive. They are closely related to convex sets, and a topological vector space is locally
convex if and only if its topology is induced by a family of seminorms.
## Main declarations
For a module over a normed ring:
* `Seminorm`: A function to the reals that is positive-semidefinite, absolutely homogeneous, and
subadditive.
* `normSeminorm 𝕜 E`: The norm on `E` as a seminorm.
## References
* [H. H. Schaefer, *Topological Vector Spaces*][schaefer1966]
## Tags
seminorm, locally convex, LCTVS
-/
open NormedField Set Filter
open scoped NNReal Pointwise Topology Uniformity
variable {R R' 𝕜 𝕜₂ 𝕜₃ 𝕝 E E₂ E₃ F G ι : Type*}
/-- A seminorm on a module over a normed ring is a function to the reals that is positive
semidefinite, positive homogeneous, and subadditive. -/
structure Seminorm (𝕜 : Type*) (E : Type*) [SeminormedRing 𝕜] [AddGroup E] [SMul 𝕜 E] extends
AddGroupSeminorm E where
/-- The seminorm of a scalar multiplication is the product of the absolute value of the scalar
and the original seminorm. -/
smul' : ∀ (a : 𝕜) (x : E), toFun (a • x) = ‖a‖ * toFun x
#align seminorm Seminorm
attribute [nolint docBlame] Seminorm.toAddGroupSeminorm
/-- `SeminormClass F 𝕜 E` states that `F` is a type of seminorms on the `𝕜`-module `E`.
You should extend this class when you extend `Seminorm`. -/
class SeminormClass (F : Type*) (𝕜 E : outParam Type*) [SeminormedRing 𝕜] [AddGroup E]
[SMul 𝕜 E] [FunLike F E ℝ] extends AddGroupSeminormClass F E ℝ : Prop where
/-- The seminorm of a scalar multiplication is the product of the absolute value of the scalar
and the original seminorm. -/
map_smul_eq_mul (f : F) (a : 𝕜) (x : E) : f (a • x) = ‖a‖ * f x
#align seminorm_class SeminormClass
export SeminormClass (map_smul_eq_mul)
-- Porting note: dangerous instances no longer exist
-- attribute [nolint dangerousInstance] SeminormClass.toAddGroupSeminormClass
section Of
/-- Alternative constructor for a `Seminorm` on an `AddCommGroup E` that is a module over a
`SeminormedRing 𝕜`. -/
def Seminorm.of [SeminormedRing 𝕜] [AddCommGroup E] [Module 𝕜 E] (f : E → ℝ)
(add_le : ∀ x y : E, f (x + y) ≤ f x + f y) (smul : ∀ (a : 𝕜) (x : E), f (a • x) = ‖a‖ * f x) :
Seminorm 𝕜 E where
toFun := f
map_zero' := by rw [← zero_smul 𝕜 (0 : E), smul, norm_zero, zero_mul]
add_le' := add_le
smul' := smul
neg' x := by rw [← neg_one_smul 𝕜, smul, norm_neg, ← smul, one_smul]
#align seminorm.of Seminorm.of
/-- Alternative constructor for a `Seminorm` over a normed field `𝕜` that only assumes `f 0 = 0`
and an inequality for the scalar multiplication. -/
def Seminorm.ofSMulLE [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] (f : E → ℝ) (map_zero : f 0 = 0)
(add_le : ∀ x y, f (x + y) ≤ f x + f y) (smul_le : ∀ (r : 𝕜) (x), f (r • x) ≤ ‖r‖ * f x) :
Seminorm 𝕜 E :=
Seminorm.of f add_le fun r x => by
refine le_antisymm (smul_le r x) ?_
by_cases h : r = 0
· simp [h, map_zero]
rw [← mul_le_mul_left (inv_pos.mpr (norm_pos_iff.mpr h))]
rw [inv_mul_cancel_left₀ (norm_ne_zero_iff.mpr h)]
specialize smul_le r⁻¹ (r • x)
rw [norm_inv] at smul_le
convert smul_le
simp [h]
#align seminorm.of_smul_le Seminorm.ofSMulLE
end Of
namespace Seminorm
section SeminormedRing
variable [SeminormedRing 𝕜]
section AddGroup
variable [AddGroup E]
section SMul
variable [SMul 𝕜 E]
instance instFunLike : FunLike (Seminorm 𝕜 E) E ℝ where
coe f := f.toFun
coe_injective' f g h := by
rcases f with ⟨⟨_⟩⟩
rcases g with ⟨⟨_⟩⟩
congr
instance instSeminormClass : SeminormClass (Seminorm 𝕜 E) 𝕜 E where
map_zero f := f.map_zero'
map_add_le_add f := f.add_le'
map_neg_eq_map f := f.neg'
map_smul_eq_mul f := f.smul'
#align seminorm.seminorm_class Seminorm.instSeminormClass
@[ext]
theorem ext {p q : Seminorm 𝕜 E} (h : ∀ x, (p : E → ℝ) x = q x) : p = q :=
DFunLike.ext p q h
#align seminorm.ext Seminorm.ext
instance instZero : Zero (Seminorm 𝕜 E) :=
⟨{ AddGroupSeminorm.instZeroAddGroupSeminorm.zero with
smul' := fun _ _ => (mul_zero _).symm }⟩
@[simp]
theorem coe_zero : ⇑(0 : Seminorm 𝕜 E) = 0 :=
rfl
#align seminorm.coe_zero Seminorm.coe_zero
@[simp]
theorem zero_apply (x : E) : (0 : Seminorm 𝕜 E) x = 0 :=
rfl
#align seminorm.zero_apply Seminorm.zero_apply
instance : Inhabited (Seminorm 𝕜 E) :=
⟨0⟩
variable (p : Seminorm 𝕜 E) (c : 𝕜) (x y : E) (r : ℝ)
/-- Any action on `ℝ` which factors through `ℝ≥0` applies to a seminorm. -/
instance instSMul [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] : SMul R (Seminorm 𝕜 E) where
smul r p :=
{ r • p.toAddGroupSeminorm with
toFun := fun x => r • p x
smul' := fun _ _ => by
simp only [← smul_one_smul ℝ≥0 r (_ : ℝ), NNReal.smul_def, smul_eq_mul]
rw [map_smul_eq_mul, mul_left_comm] }
instance [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] [SMul R' ℝ] [SMul R' ℝ≥0]
[IsScalarTower R' ℝ≥0 ℝ] [SMul R R'] [IsScalarTower R R' ℝ] :
IsScalarTower R R' (Seminorm 𝕜 E) where
smul_assoc r a p := ext fun x => smul_assoc r a (p x)
theorem coe_smul [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] (r : R) (p : Seminorm 𝕜 E) :
⇑(r • p) = r • ⇑p :=
rfl
#align seminorm.coe_smul Seminorm.coe_smul
@[simp]
theorem smul_apply [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] (r : R) (p : Seminorm 𝕜 E)
(x : E) : (r • p) x = r • p x :=
rfl
#align seminorm.smul_apply Seminorm.smul_apply
instance instAdd : Add (Seminorm 𝕜 E) where
add p q :=
{ p.toAddGroupSeminorm + q.toAddGroupSeminorm with
toFun := fun x => p x + q x
smul' := fun a x => by simp only [map_smul_eq_mul, map_smul_eq_mul, mul_add] }
theorem coe_add (p q : Seminorm 𝕜 E) : ⇑(p + q) = p + q :=
rfl
#align seminorm.coe_add Seminorm.coe_add
@[simp]
theorem add_apply (p q : Seminorm 𝕜 E) (x : E) : (p + q) x = p x + q x :=
rfl
#align seminorm.add_apply Seminorm.add_apply
instance instAddMonoid : AddMonoid (Seminorm 𝕜 E) :=
DFunLike.coe_injective.addMonoid _ rfl coe_add fun _ _ => by rfl
instance instOrderedCancelAddCommMonoid : OrderedCancelAddCommMonoid (Seminorm 𝕜 E) :=
DFunLike.coe_injective.orderedCancelAddCommMonoid _ rfl coe_add fun _ _ => rfl
instance instMulAction [Monoid R] [MulAction R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] :
MulAction R (Seminorm 𝕜 E) :=
DFunLike.coe_injective.mulAction _ (by intros; rfl)
variable (𝕜 E)
/-- `coeFn` as an `AddMonoidHom`. Helper definition for showing that `Seminorm 𝕜 E` is a module. -/
@[simps]
def coeFnAddMonoidHom : AddMonoidHom (Seminorm 𝕜 E) (E → ℝ) where
toFun := (↑)
map_zero' := coe_zero
map_add' := coe_add
#align seminorm.coe_fn_add_monoid_hom Seminorm.coeFnAddMonoidHom
theorem coeFnAddMonoidHom_injective : Function.Injective (coeFnAddMonoidHom 𝕜 E) :=
show @Function.Injective (Seminorm 𝕜 E) (E → ℝ) (↑) from DFunLike.coe_injective
#align seminorm.coe_fn_add_monoid_hom_injective Seminorm.coeFnAddMonoidHom_injective
variable {𝕜 E}
instance instDistribMulAction [Monoid R] [DistribMulAction R ℝ] [SMul R ℝ≥0]
[IsScalarTower R ℝ≥0 ℝ] : DistribMulAction R (Seminorm 𝕜 E) :=
(coeFnAddMonoidHom_injective 𝕜 E).distribMulAction _ (by intros; rfl)
instance instModule [Semiring R] [Module R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] :
Module R (Seminorm 𝕜 E) :=
(coeFnAddMonoidHom_injective 𝕜 E).module R _ (by intros; rfl)
instance instSup : Sup (Seminorm 𝕜 E) where
sup p q :=
{ p.toAddGroupSeminorm ⊔ q.toAddGroupSeminorm with
toFun := p ⊔ q
smul' := fun x v =>
(congr_arg₂ max (map_smul_eq_mul p x v) (map_smul_eq_mul q x v)).trans <|
(mul_max_of_nonneg _ _ <| norm_nonneg x).symm }
@[simp]
theorem coe_sup (p q : Seminorm 𝕜 E) : ⇑(p ⊔ q) = (p : E → ℝ) ⊔ (q : E → ℝ) :=
rfl
#align seminorm.coe_sup Seminorm.coe_sup
theorem sup_apply (p q : Seminorm 𝕜 E) (x : E) : (p ⊔ q) x = p x ⊔ q x :=
rfl
#align seminorm.sup_apply Seminorm.sup_apply
theorem smul_sup [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] (r : R) (p q : Seminorm 𝕜 E) :
r • (p ⊔ q) = r • p ⊔ r • q :=
have real.smul_max : ∀ x y : ℝ, r • max x y = max (r • x) (r • y) := fun x y => by
simpa only [← smul_eq_mul, ← NNReal.smul_def, smul_one_smul ℝ≥0 r (_ : ℝ)] using
mul_max_of_nonneg x y (r • (1 : ℝ≥0) : ℝ≥0).coe_nonneg
ext fun x => real.smul_max _ _
#align seminorm.smul_sup Seminorm.smul_sup
instance instPartialOrder : PartialOrder (Seminorm 𝕜 E) :=
PartialOrder.lift _ DFunLike.coe_injective
@[simp, norm_cast]
theorem coe_le_coe {p q : Seminorm 𝕜 E} : (p : E → ℝ) ≤ q ↔ p ≤ q :=
Iff.rfl
#align seminorm.coe_le_coe Seminorm.coe_le_coe
@[simp, norm_cast]
theorem coe_lt_coe {p q : Seminorm 𝕜 E} : (p : E → ℝ) < q ↔ p < q :=
Iff.rfl
#align seminorm.coe_lt_coe Seminorm.coe_lt_coe
theorem le_def {p q : Seminorm 𝕜 E} : p ≤ q ↔ ∀ x, p x ≤ q x :=
Iff.rfl
#align seminorm.le_def Seminorm.le_def
theorem lt_def {p q : Seminorm 𝕜 E} : p < q ↔ p ≤ q ∧ ∃ x, p x < q x :=
@Pi.lt_def _ _ _ p q
#align seminorm.lt_def Seminorm.lt_def
instance instSemilatticeSup : SemilatticeSup (Seminorm 𝕜 E) :=
Function.Injective.semilatticeSup _ DFunLike.coe_injective coe_sup
end SMul
end AddGroup
section Module
variable [SeminormedRing 𝕜₂] [SeminormedRing 𝕜₃]
variable {σ₁₂ : 𝕜 →+* 𝕜₂} [RingHomIsometric σ₁₂]
variable {σ₂₃ : 𝕜₂ →+* 𝕜₃} [RingHomIsometric σ₂₃]
variable {σ₁₃ : 𝕜 →+* 𝕜₃} [RingHomIsometric σ₁₃]
variable [AddCommGroup E] [AddCommGroup E₂] [AddCommGroup E₃]
variable [AddCommGroup F] [AddCommGroup G]
variable [Module 𝕜 E] [Module 𝕜₂ E₂] [Module 𝕜₃ E₃] [Module 𝕜 F] [Module 𝕜 G]
-- Porting note: even though this instance is found immediately by typeclass search,
-- it seems to be needed below!?
noncomputable instance smul_nnreal_real : SMul ℝ≥0 ℝ := inferInstance
variable [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ]
/-- Composition of a seminorm with a linear map is a seminorm. -/
def comp (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) : Seminorm 𝕜 E :=
{ p.toAddGroupSeminorm.comp f.toAddMonoidHom with
toFun := fun x => p (f x)
-- Porting note: the `simp only` below used to be part of the `rw`.
-- I'm not sure why this change was needed, and am worried by it!
-- Note: #8386 had to change `map_smulₛₗ` to `map_smulₛₗ _`
smul' := fun _ _ => by simp only [map_smulₛₗ _]; rw [map_smul_eq_mul, RingHomIsometric.is_iso] }
#align seminorm.comp Seminorm.comp
theorem coe_comp (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) : ⇑(p.comp f) = p ∘ f :=
rfl
#align seminorm.coe_comp Seminorm.coe_comp
@[simp]
theorem comp_apply (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (x : E) : (p.comp f) x = p (f x) :=
rfl
#align seminorm.comp_apply Seminorm.comp_apply
@[simp]
theorem comp_id (p : Seminorm 𝕜 E) : p.comp LinearMap.id = p :=
ext fun _ => rfl
#align seminorm.comp_id Seminorm.comp_id
@[simp]
theorem comp_zero (p : Seminorm 𝕜₂ E₂) : p.comp (0 : E →ₛₗ[σ₁₂] E₂) = 0 :=
ext fun _ => map_zero p
#align seminorm.comp_zero Seminorm.comp_zero
@[simp]
theorem zero_comp (f : E →ₛₗ[σ₁₂] E₂) : (0 : Seminorm 𝕜₂ E₂).comp f = 0 :=
ext fun _ => rfl
#align seminorm.zero_comp Seminorm.zero_comp
theorem comp_comp [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] (p : Seminorm 𝕜₃ E₃) (g : E₂ →ₛₗ[σ₂₃] E₃)
(f : E →ₛₗ[σ₁₂] E₂) : p.comp (g.comp f) = (p.comp g).comp f :=
ext fun _ => rfl
#align seminorm.comp_comp Seminorm.comp_comp
theorem add_comp (p q : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) :
(p + q).comp f = p.comp f + q.comp f :=
ext fun _ => rfl
#align seminorm.add_comp Seminorm.add_comp
theorem comp_add_le (p : Seminorm 𝕜₂ E₂) (f g : E →ₛₗ[σ₁₂] E₂) :
p.comp (f + g) ≤ p.comp f + p.comp g := fun _ => map_add_le_add p _ _
#align seminorm.comp_add_le Seminorm.comp_add_le
theorem smul_comp (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (c : R) :
(c • p).comp f = c • p.comp f :=
ext fun _ => rfl
#align seminorm.smul_comp Seminorm.smul_comp
theorem comp_mono {p q : Seminorm 𝕜₂ E₂} (f : E →ₛₗ[σ₁₂] E₂) (hp : p ≤ q) : p.comp f ≤ q.comp f :=
fun _ => hp _
#align seminorm.comp_mono Seminorm.comp_mono
/-- The composition as an `AddMonoidHom`. -/
@[simps]
def pullback (f : E →ₛₗ[σ₁₂] E₂) : Seminorm 𝕜₂ E₂ →+ Seminorm 𝕜 E where
toFun := fun p => p.comp f
map_zero' := zero_comp f
map_add' := fun p q => add_comp p q f
#align seminorm.pullback Seminorm.pullback
instance instOrderBot : OrderBot (Seminorm 𝕜 E) where
bot := 0
bot_le := apply_nonneg
@[simp]
theorem coe_bot : ⇑(⊥ : Seminorm 𝕜 E) = 0 :=
rfl
#align seminorm.coe_bot Seminorm.coe_bot
theorem bot_eq_zero : (⊥ : Seminorm 𝕜 E) = 0 :=
rfl
#align seminorm.bot_eq_zero Seminorm.bot_eq_zero
theorem smul_le_smul {p q : Seminorm 𝕜 E} {a b : ℝ≥0} (hpq : p ≤ q) (hab : a ≤ b) :
a • p ≤ b • q := by
simp_rw [le_def]
intro x
exact mul_le_mul hab (hpq x) (apply_nonneg p x) (NNReal.coe_nonneg b)
#align seminorm.smul_le_smul Seminorm.smul_le_smul
theorem finset_sup_apply (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) :
s.sup p x = ↑(s.sup fun i => ⟨p i x, apply_nonneg (p i) x⟩ : ℝ≥0) := by
induction' s using Finset.cons_induction_on with a s ha ih
· rw [Finset.sup_empty, Finset.sup_empty, coe_bot, _root_.bot_eq_zero, Pi.zero_apply]
norm_cast
· rw [Finset.sup_cons, Finset.sup_cons, coe_sup, sup_eq_max, Pi.sup_apply, sup_eq_max,
NNReal.coe_max, NNReal.coe_mk, ih]
#align seminorm.finset_sup_apply Seminorm.finset_sup_apply
theorem exists_apply_eq_finset_sup (p : ι → Seminorm 𝕜 E) {s : Finset ι} (hs : s.Nonempty) (x : E) :
∃ i ∈ s, s.sup p x = p i x := by
rcases Finset.exists_mem_eq_sup s hs (fun i ↦ (⟨p i x, apply_nonneg _ _⟩ : ℝ≥0)) with ⟨i, hi, hix⟩
rw [finset_sup_apply]
exact ⟨i, hi, congr_arg _ hix⟩
theorem zero_or_exists_apply_eq_finset_sup (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) :
s.sup p x = 0 ∨ ∃ i ∈ s, s.sup p x = p i x := by
rcases Finset.eq_empty_or_nonempty s with (rfl|hs)
· left; rfl
· right; exact exists_apply_eq_finset_sup p hs x
theorem finset_sup_smul (p : ι → Seminorm 𝕜 E) (s : Finset ι) (C : ℝ≥0) :
s.sup (C • p) = C • s.sup p := by
ext x
rw [smul_apply, finset_sup_apply, finset_sup_apply]
symm
exact congr_arg ((↑) : ℝ≥0 → ℝ) (NNReal.mul_finset_sup C s (fun i ↦ ⟨p i x, apply_nonneg _ _⟩))
theorem finset_sup_le_sum (p : ι → Seminorm 𝕜 E) (s : Finset ι) : s.sup p ≤ ∑ i ∈ s, p i := by
classical
refine Finset.sup_le_iff.mpr ?_
intro i hi
rw [Finset.sum_eq_sum_diff_singleton_add hi, le_add_iff_nonneg_left]
exact bot_le
#align seminorm.finset_sup_le_sum Seminorm.finset_sup_le_sum
theorem finset_sup_apply_le {p : ι → Seminorm 𝕜 E} {s : Finset ι} {x : E} {a : ℝ} (ha : 0 ≤ a)
(h : ∀ i, i ∈ s → p i x ≤ a) : s.sup p x ≤ a := by
lift a to ℝ≥0 using ha
rw [finset_sup_apply, NNReal.coe_le_coe]
exact Finset.sup_le h
#align seminorm.finset_sup_apply_le Seminorm.finset_sup_apply_le
theorem le_finset_sup_apply {p : ι → Seminorm 𝕜 E} {s : Finset ι} {x : E} {i : ι}
(hi : i ∈ s) : p i x ≤ s.sup p x :=
(Finset.le_sup hi : p i ≤ s.sup p) x
theorem finset_sup_apply_lt {p : ι → Seminorm 𝕜 E} {s : Finset ι} {x : E} {a : ℝ} (ha : 0 < a)
(h : ∀ i, i ∈ s → p i x < a) : s.sup p x < a := by
lift a to ℝ≥0 using ha.le
rw [finset_sup_apply, NNReal.coe_lt_coe, Finset.sup_lt_iff]
· exact h
· exact NNReal.coe_pos.mpr ha
#align seminorm.finset_sup_apply_lt Seminorm.finset_sup_apply_lt
theorem norm_sub_map_le_sub (p : Seminorm 𝕜 E) (x y : E) : ‖p x - p y‖ ≤ p (x - y) :=
abs_sub_map_le_sub p x y
#align seminorm.norm_sub_map_le_sub Seminorm.norm_sub_map_le_sub
end Module
end SeminormedRing
section SeminormedCommRing
variable [SeminormedRing 𝕜] [SeminormedCommRing 𝕜₂]
variable {σ₁₂ : 𝕜 →+* 𝕜₂} [RingHomIsometric σ₁₂]
variable [AddCommGroup E] [AddCommGroup E₂] [Module 𝕜 E] [Module 𝕜₂ E₂]
theorem comp_smul (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (c : 𝕜₂) :
p.comp (c • f) = ‖c‖₊ • p.comp f :=
ext fun _ => by
rw [comp_apply, smul_apply, LinearMap.smul_apply, map_smul_eq_mul, NNReal.smul_def, coe_nnnorm,
smul_eq_mul, comp_apply]
#align seminorm.comp_smul Seminorm.comp_smul
theorem comp_smul_apply (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (c : 𝕜₂) (x : E) :
p.comp (c • f) x = ‖c‖ * p (f x) :=
map_smul_eq_mul p _ _
#align seminorm.comp_smul_apply Seminorm.comp_smul_apply
end SeminormedCommRing
section NormedField
variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] {p q : Seminorm 𝕜 E} {x : E}
/-- Auxiliary lemma to show that the infimum of seminorms is well-defined. -/
theorem bddBelow_range_add : BddBelow (range fun u => p u + q (x - u)) :=
⟨0, by
rintro _ ⟨x, rfl⟩
dsimp; positivity⟩
#align seminorm.bdd_below_range_add Seminorm.bddBelow_range_add
noncomputable instance instInf : Inf (Seminorm 𝕜 E) where
inf p q :=
{ p.toAddGroupSeminorm ⊓ q.toAddGroupSeminorm with
toFun := fun x => ⨅ u : E, p u + q (x - u)
smul' := by
intro a x
obtain rfl | ha := eq_or_ne a 0
· rw [norm_zero, zero_mul, zero_smul]
refine
ciInf_eq_of_forall_ge_of_forall_gt_exists_lt
-- Porting note: the following was previously `fun i => by positivity`
(fun i => add_nonneg (apply_nonneg _ _) (apply_nonneg _ _))
fun x hx => ⟨0, by rwa [map_zero, sub_zero, map_zero, add_zero]⟩
simp_rw [Real.mul_iInf_of_nonneg (norm_nonneg a), mul_add, ← map_smul_eq_mul p, ←
map_smul_eq_mul q, smul_sub]
refine
Function.Surjective.iInf_congr ((a⁻¹ • ·) : E → E)
(fun u => ⟨a • u, inv_smul_smul₀ ha u⟩) fun u => ?_
rw [smul_inv_smul₀ ha] }
@[simp]
theorem inf_apply (p q : Seminorm 𝕜 E) (x : E) : (p ⊓ q) x = ⨅ u : E, p u + q (x - u) :=
rfl
#align seminorm.inf_apply Seminorm.inf_apply
noncomputable instance instLattice : Lattice (Seminorm 𝕜 E) :=
{ Seminorm.instSemilatticeSup with
inf := (· ⊓ ·)
inf_le_left := fun p q x =>
ciInf_le_of_le bddBelow_range_add x <| by
simp only [sub_self, map_zero, add_zero]; rfl
inf_le_right := fun p q x =>
ciInf_le_of_le bddBelow_range_add 0 <| by
simp only [sub_self, map_zero, zero_add, sub_zero]; rfl
le_inf := fun a b c hab hac x =>
le_ciInf fun u => (le_map_add_map_sub a _ _).trans <| add_le_add (hab _) (hac _) }
theorem smul_inf [SMul R ℝ] [SMul R ℝ≥0] [IsScalarTower R ℝ≥0 ℝ] (r : R) (p q : Seminorm 𝕜 E) :
r • (p ⊓ q) = r • p ⊓ r • q := by
ext
simp_rw [smul_apply, inf_apply, smul_apply, ← smul_one_smul ℝ≥0 r (_ : ℝ), NNReal.smul_def,
smul_eq_mul, Real.mul_iInf_of_nonneg (NNReal.coe_nonneg _), mul_add]
#align seminorm.smul_inf Seminorm.smul_inf
section Classical
open scoped Classical
/-- We define the supremum of an arbitrary subset of `Seminorm 𝕜 E` as follows:
* if `s` is `BddAbove` *as a set of functions `E → ℝ`* (that is, if `s` is pointwise bounded
above), we take the pointwise supremum of all elements of `s`, and we prove that it is indeed a
seminorm.
* otherwise, we take the zero seminorm `⊥`.
There are two things worth mentioning here:
* First, it is not trivial at first that `s` being bounded above *by a function* implies
being bounded above *as a seminorm*. We show this in `Seminorm.bddAbove_iff` by using
that the `Sup s` as defined here is then a bounding seminorm for `s`. So it is important to make
the case disjunction on `BddAbove ((↑) '' s : Set (E → ℝ))` and not `BddAbove s`.
* Since the pointwise `Sup` already gives `0` at points where a family of functions is
not bounded above, one could hope that just using the pointwise `Sup` would work here, without the
need for an additional case disjunction. As discussed on Zulip, this doesn't work because this can
give a function which does *not* satisfy the seminorm axioms (typically sub-additivity).
-/
noncomputable instance instSupSet : SupSet (Seminorm 𝕜 E) where
sSup s :=
if h : BddAbove ((↑) '' s : Set (E → ℝ)) then
{ toFun := ⨆ p : s, ((p : Seminorm 𝕜 E) : E → ℝ)
map_zero' := by
rw [iSup_apply, ← @Real.ciSup_const_zero s]
congr!
rename_i _ _ _ i
exact map_zero i.1
add_le' := fun x y => by
rcases h with ⟨q, hq⟩
obtain rfl | h := s.eq_empty_or_nonempty
· simp [Real.iSup_of_isEmpty]
haveI : Nonempty ↑s := h.coe_sort
simp only [iSup_apply]
refine ciSup_le fun i =>
((i : Seminorm 𝕜 E).add_le' x y).trans <| add_le_add
-- Porting note: `f` is provided to force `Subtype.val` to appear.
-- A type ascription on `_` would have also worked, but would have been more verbose.
(le_ciSup (f := fun i => (Subtype.val i : Seminorm 𝕜 E).toFun x) ⟨q x, ?_⟩ i)
(le_ciSup (f := fun i => (Subtype.val i : Seminorm 𝕜 E).toFun y) ⟨q y, ?_⟩ i)
<;> rw [mem_upperBounds, forall_mem_range]
<;> exact fun j => hq (mem_image_of_mem _ j.2) _
neg' := fun x => by
simp only [iSup_apply]
congr! 2
rename_i _ _ _ i
exact i.1.neg' _
smul' := fun a x => by
simp only [iSup_apply]
rw [← smul_eq_mul,
Real.smul_iSup_of_nonneg (norm_nonneg a) fun i : s => (i : Seminorm 𝕜 E) x]
congr!
rename_i _ _ _ i
exact i.1.smul' a x }
else ⊥
protected theorem coe_sSup_eq' {s : Set <| Seminorm 𝕜 E}
(hs : BddAbove ((↑) '' s : Set (E → ℝ))) : ↑(sSup s) = ⨆ p : s, ((p : Seminorm 𝕜 E) : E → ℝ) :=
congr_arg _ (dif_pos hs)
#align seminorm.coe_Sup_eq' Seminorm.coe_sSup_eq'
protected theorem bddAbove_iff {s : Set <| Seminorm 𝕜 E} :
BddAbove s ↔ BddAbove ((↑) '' s : Set (E → ℝ)) :=
⟨fun ⟨q, hq⟩ => ⟨q, forall_mem_image.2 fun p hp => hq hp⟩, fun H =>
⟨sSup s, fun p hp x => by
dsimp
rw [Seminorm.coe_sSup_eq' H, iSup_apply]
rcases H with ⟨q, hq⟩
exact
le_ciSup ⟨q x, forall_mem_range.mpr fun i : s => hq (mem_image_of_mem _ i.2) x⟩ ⟨p, hp⟩⟩⟩
#align seminorm.bdd_above_iff Seminorm.bddAbove_iff
protected theorem bddAbove_range_iff {ι : Sort*} {p : ι → Seminorm 𝕜 E} :
BddAbove (range p) ↔ ∀ x, BddAbove (range fun i ↦ p i x) := by
rw [Seminorm.bddAbove_iff, ← range_comp, bddAbove_range_pi]; rfl
protected theorem coe_sSup_eq {s : Set <| Seminorm 𝕜 E} (hs : BddAbove s) :
↑(sSup s) = ⨆ p : s, ((p : Seminorm 𝕜 E) : E → ℝ) :=
Seminorm.coe_sSup_eq' (Seminorm.bddAbove_iff.mp hs)
#align seminorm.coe_Sup_eq Seminorm.coe_sSup_eq
protected theorem coe_iSup_eq {ι : Sort*} {p : ι → Seminorm 𝕜 E} (hp : BddAbove (range p)) :
↑(⨆ i, p i) = ⨆ i, ((p i : Seminorm 𝕜 E) : E → ℝ) := by
rw [← sSup_range, Seminorm.coe_sSup_eq hp]
exact iSup_range' (fun p : Seminorm 𝕜 E => (p : E → ℝ)) p
#align seminorm.coe_supr_eq Seminorm.coe_iSup_eq
protected theorem sSup_apply {s : Set (Seminorm 𝕜 E)} (hp : BddAbove s) {x : E} :
(sSup s) x = ⨆ p : s, (p : E → ℝ) x := by
rw [Seminorm.coe_sSup_eq hp, iSup_apply]
protected theorem iSup_apply {ι : Sort*} {p : ι → Seminorm 𝕜 E}
(hp : BddAbove (range p)) {x : E} : (⨆ i, p i) x = ⨆ i, p i x := by
rw [Seminorm.coe_iSup_eq hp, iSup_apply]
protected theorem sSup_empty : sSup (∅ : Set (Seminorm 𝕜 E)) = ⊥ := by
ext
rw [Seminorm.sSup_apply bddAbove_empty, Real.iSup_of_isEmpty]
rfl
private theorem isLUB_sSup (s : Set (Seminorm 𝕜 E)) (hs₁ : BddAbove s) (hs₂ : s.Nonempty) :
IsLUB s (sSup s) := by
refine ⟨fun p hp x => ?_, fun p hp x => ?_⟩ <;> haveI : Nonempty ↑s := hs₂.coe_sort <;>
dsimp <;> rw [Seminorm.coe_sSup_eq hs₁, iSup_apply]
· rcases hs₁ with ⟨q, hq⟩
exact le_ciSup ⟨q x, forall_mem_range.mpr fun i : s => hq i.2 x⟩ ⟨p, hp⟩
· exact ciSup_le fun q => hp q.2 x
/-- `Seminorm 𝕜 E` is a conditionally complete lattice.
Note that, while `inf`, `sup` and `sSup` have good definitional properties (corresponding to
the instances given here for `Inf`, `Sup` and `SupSet` respectively), `sInf s` is just
defined as the supremum of the lower bounds of `s`, which is not really useful in practice. If you
need to use `sInf` on seminorms, then you should probably provide a more workable definition first,
but this is unlikely to happen so we keep the "bad" definition for now. -/
noncomputable instance instConditionallyCompleteLattice :
ConditionallyCompleteLattice (Seminorm 𝕜 E) :=
conditionallyCompleteLatticeOfLatticeOfsSup (Seminorm 𝕜 E) Seminorm.isLUB_sSup
end Classical
end NormedField
/-! ### Seminorm ball -/
section SeminormedRing
variable [SeminormedRing 𝕜]
section AddCommGroup
variable [AddCommGroup E]
section SMul
variable [SMul 𝕜 E] (p : Seminorm 𝕜 E)
/-- The ball of radius `r` at `x` with respect to seminorm `p` is the set of elements `y` with
`p (y - x) < r`. -/
def ball (x : E) (r : ℝ) :=
{ y : E | p (y - x) < r }
#align seminorm.ball Seminorm.ball
/-- The closed ball of radius `r` at `x` with respect to seminorm `p` is the set of elements `y`
with `p (y - x) ≤ r`. -/
def closedBall (x : E) (r : ℝ) :=
{ y : E | p (y - x) ≤ r }
#align seminorm.closed_ball Seminorm.closedBall
variable {x y : E} {r : ℝ}
@[simp]
theorem mem_ball : y ∈ ball p x r ↔ p (y - x) < r :=
Iff.rfl
#align seminorm.mem_ball Seminorm.mem_ball
@[simp]
theorem mem_closedBall : y ∈ closedBall p x r ↔ p (y - x) ≤ r :=
Iff.rfl
#align seminorm.mem_closed_ball Seminorm.mem_closedBall
theorem mem_ball_self (hr : 0 < r) : x ∈ ball p x r := by simp [hr]
#align seminorm.mem_ball_self Seminorm.mem_ball_self
theorem mem_closedBall_self (hr : 0 ≤ r) : x ∈ closedBall p x r := by simp [hr]
#align seminorm.mem_closed_ball_self Seminorm.mem_closedBall_self
theorem mem_ball_zero : y ∈ ball p 0 r ↔ p y < r := by rw [mem_ball, sub_zero]
#align seminorm.mem_ball_zero Seminorm.mem_ball_zero
theorem mem_closedBall_zero : y ∈ closedBall p 0 r ↔ p y ≤ r := by rw [mem_closedBall, sub_zero]
#align seminorm.mem_closed_ball_zero Seminorm.mem_closedBall_zero
theorem ball_zero_eq : ball p 0 r = { y : E | p y < r } :=
Set.ext fun _ => p.mem_ball_zero
#align seminorm.ball_zero_eq Seminorm.ball_zero_eq
theorem closedBall_zero_eq : closedBall p 0 r = { y : E | p y ≤ r } :=
Set.ext fun _ => p.mem_closedBall_zero
#align seminorm.closed_ball_zero_eq Seminorm.closedBall_zero_eq
theorem ball_subset_closedBall (x r) : ball p x r ⊆ closedBall p x r := fun _ h =>
(mem_closedBall _).mpr ((mem_ball _).mp h).le
#align seminorm.ball_subset_closed_ball Seminorm.ball_subset_closedBall
theorem closedBall_eq_biInter_ball (x r) : closedBall p x r = ⋂ ρ > r, ball p x ρ := by
ext y; simp_rw [mem_closedBall, mem_iInter₂, mem_ball, ← forall_lt_iff_le']
#align seminorm.closed_ball_eq_bInter_ball Seminorm.closedBall_eq_biInter_ball
@[simp]
theorem ball_zero' (x : E) (hr : 0 < r) : ball (0 : Seminorm 𝕜 E) x r = Set.univ := by
rw [Set.eq_univ_iff_forall, ball]
simp [hr]
#align seminorm.ball_zero' Seminorm.ball_zero'
@[simp]
theorem closedBall_zero' (x : E) (hr : 0 < r) : closedBall (0 : Seminorm 𝕜 E) x r = Set.univ :=
eq_univ_of_subset (ball_subset_closedBall _ _ _) (ball_zero' x hr)
#align seminorm.closed_ball_zero' Seminorm.closedBall_zero'
theorem ball_smul (p : Seminorm 𝕜 E) {c : NNReal} (hc : 0 < c) (r : ℝ) (x : E) :
(c • p).ball x r = p.ball x (r / c) := by
ext
rw [mem_ball, mem_ball, smul_apply, NNReal.smul_def, smul_eq_mul, mul_comm,
lt_div_iff (NNReal.coe_pos.mpr hc)]
#align seminorm.ball_smul Seminorm.ball_smul
theorem closedBall_smul (p : Seminorm 𝕜 E) {c : NNReal} (hc : 0 < c) (r : ℝ) (x : E) :
(c • p).closedBall x r = p.closedBall x (r / c) := by
ext
rw [mem_closedBall, mem_closedBall, smul_apply, NNReal.smul_def, smul_eq_mul, mul_comm,
le_div_iff (NNReal.coe_pos.mpr hc)]
#align seminorm.closed_ball_smul Seminorm.closedBall_smul
theorem ball_sup (p : Seminorm 𝕜 E) (q : Seminorm 𝕜 E) (e : E) (r : ℝ) :
ball (p ⊔ q) e r = ball p e r ∩ ball q e r := by
simp_rw [ball, ← Set.setOf_and, coe_sup, Pi.sup_apply, sup_lt_iff]
#align seminorm.ball_sup Seminorm.ball_sup
theorem closedBall_sup (p : Seminorm 𝕜 E) (q : Seminorm 𝕜 E) (e : E) (r : ℝ) :
closedBall (p ⊔ q) e r = closedBall p e r ∩ closedBall q e r := by
simp_rw [closedBall, ← Set.setOf_and, coe_sup, Pi.sup_apply, sup_le_iff]
#align seminorm.closed_ball_sup Seminorm.closedBall_sup
theorem ball_finset_sup' (p : ι → Seminorm 𝕜 E) (s : Finset ι) (H : s.Nonempty) (e : E) (r : ℝ) :
ball (s.sup' H p) e r = s.inf' H fun i => ball (p i) e r := by
induction H using Finset.Nonempty.cons_induction with
| singleton => simp
| cons _ _ _ hs ih =>
rw [Finset.sup'_cons hs, Finset.inf'_cons hs, ball_sup]
-- Porting note: `rw` can't use `inf_eq_inter` here, but `simp` can?
simp only [inf_eq_inter, ih]
#align seminorm.ball_finset_sup' Seminorm.ball_finset_sup'
theorem closedBall_finset_sup' (p : ι → Seminorm 𝕜 E) (s : Finset ι) (H : s.Nonempty) (e : E)
(r : ℝ) : closedBall (s.sup' H p) e r = s.inf' H fun i => closedBall (p i) e r := by
induction H using Finset.Nonempty.cons_induction with
| singleton => simp
| cons _ _ _ hs ih =>
rw [Finset.sup'_cons hs, Finset.inf'_cons hs, closedBall_sup]
-- Porting note: `rw` can't use `inf_eq_inter` here, but `simp` can?
simp only [inf_eq_inter, ih]
#align seminorm.closed_ball_finset_sup' Seminorm.closedBall_finset_sup'
theorem ball_mono {p : Seminorm 𝕜 E} {r₁ r₂ : ℝ} (h : r₁ ≤ r₂) : p.ball x r₁ ⊆ p.ball x r₂ :=
fun _ (hx : _ < _) => hx.trans_le h
#align seminorm.ball_mono Seminorm.ball_mono
theorem closedBall_mono {p : Seminorm 𝕜 E} {r₁ r₂ : ℝ} (h : r₁ ≤ r₂) :
p.closedBall x r₁ ⊆ p.closedBall x r₂ := fun _ (hx : _ ≤ _) => hx.trans h
#align seminorm.closed_ball_mono Seminorm.closedBall_mono
theorem ball_antitone {p q : Seminorm 𝕜 E} (h : q ≤ p) : p.ball x r ⊆ q.ball x r := fun _ =>
(h _).trans_lt
#align seminorm.ball_antitone Seminorm.ball_antitone
theorem closedBall_antitone {p q : Seminorm 𝕜 E} (h : q ≤ p) :
p.closedBall x r ⊆ q.closedBall x r := fun _ => (h _).trans
#align seminorm.closed_ball_antitone Seminorm.closedBall_antitone
theorem ball_add_ball_subset (p : Seminorm 𝕜 E) (r₁ r₂ : ℝ) (x₁ x₂ : E) :
p.ball (x₁ : E) r₁ + p.ball (x₂ : E) r₂ ⊆ p.ball (x₁ + x₂) (r₁ + r₂) := by
rintro x ⟨y₁, hy₁, y₂, hy₂, rfl⟩
rw [mem_ball, add_sub_add_comm]
exact (map_add_le_add p _ _).trans_lt (add_lt_add hy₁ hy₂)
#align seminorm.ball_add_ball_subset Seminorm.ball_add_ball_subset
theorem closedBall_add_closedBall_subset (p : Seminorm 𝕜 E) (r₁ r₂ : ℝ) (x₁ x₂ : E) :
p.closedBall (x₁ : E) r₁ + p.closedBall (x₂ : E) r₂ ⊆ p.closedBall (x₁ + x₂) (r₁ + r₂) := by
rintro x ⟨y₁, hy₁, y₂, hy₂, rfl⟩
rw [mem_closedBall, add_sub_add_comm]
exact (map_add_le_add p _ _).trans (add_le_add hy₁ hy₂)
#align seminorm.closed_ball_add_closed_ball_subset Seminorm.closedBall_add_closedBall_subset
theorem sub_mem_ball (p : Seminorm 𝕜 E) (x₁ x₂ y : E) (r : ℝ) :
x₁ - x₂ ∈ p.ball y r ↔ x₁ ∈ p.ball (x₂ + y) r := by simp_rw [mem_ball, sub_sub]
#align seminorm.sub_mem_ball Seminorm.sub_mem_ball
/-- The image of a ball under addition with a singleton is another ball. -/
theorem vadd_ball (p : Seminorm 𝕜 E) : x +ᵥ p.ball y r = p.ball (x +ᵥ y) r :=
letI := AddGroupSeminorm.toSeminormedAddCommGroup p.toAddGroupSeminorm
Metric.vadd_ball x y r
#align seminorm.vadd_ball Seminorm.vadd_ball
/-- The image of a closed ball under addition with a singleton is another closed ball. -/
theorem vadd_closedBall (p : Seminorm 𝕜 E) : x +ᵥ p.closedBall y r = p.closedBall (x +ᵥ y) r :=
letI := AddGroupSeminorm.toSeminormedAddCommGroup p.toAddGroupSeminorm
Metric.vadd_closedBall x y r
#align seminorm.vadd_closed_ball Seminorm.vadd_closedBall
end SMul
section Module
variable [Module 𝕜 E]
variable [SeminormedRing 𝕜₂] [AddCommGroup E₂] [Module 𝕜₂ E₂]
variable {σ₁₂ : 𝕜 →+* 𝕜₂} [RingHomIsometric σ₁₂]
theorem ball_comp (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (x : E) (r : ℝ) :
(p.comp f).ball x r = f ⁻¹' p.ball (f x) r := by
ext
simp_rw [ball, mem_preimage, comp_apply, Set.mem_setOf_eq, map_sub]
#align seminorm.ball_comp Seminorm.ball_comp
theorem closedBall_comp (p : Seminorm 𝕜₂ E₂) (f : E →ₛₗ[σ₁₂] E₂) (x : E) (r : ℝ) :
(p.comp f).closedBall x r = f ⁻¹' p.closedBall (f x) r := by
ext
simp_rw [closedBall, mem_preimage, comp_apply, Set.mem_setOf_eq, map_sub]
#align seminorm.closed_ball_comp Seminorm.closedBall_comp
variable (p : Seminorm 𝕜 E)
theorem preimage_metric_ball {r : ℝ} : p ⁻¹' Metric.ball 0 r = { x | p x < r } := by
ext x
simp only [mem_setOf, mem_preimage, mem_ball_zero_iff, Real.norm_of_nonneg (apply_nonneg p _)]
#align seminorm.preimage_metric_ball Seminorm.preimage_metric_ball
theorem preimage_metric_closedBall {r : ℝ} : p ⁻¹' Metric.closedBall 0 r = { x | p x ≤ r } := by
ext x
simp only [mem_setOf, mem_preimage, mem_closedBall_zero_iff,
Real.norm_of_nonneg (apply_nonneg p _)]
#align seminorm.preimage_metric_closed_ball Seminorm.preimage_metric_closedBall
theorem ball_zero_eq_preimage_ball {r : ℝ} : p.ball 0 r = p ⁻¹' Metric.ball 0 r := by
rw [ball_zero_eq, preimage_metric_ball]
#align seminorm.ball_zero_eq_preimage_ball Seminorm.ball_zero_eq_preimage_ball
theorem closedBall_zero_eq_preimage_closedBall {r : ℝ} :
p.closedBall 0 r = p ⁻¹' Metric.closedBall 0 r := by
rw [closedBall_zero_eq, preimage_metric_closedBall]
#align seminorm.closed_ball_zero_eq_preimage_closed_ball Seminorm.closedBall_zero_eq_preimage_closedBall
@[simp]
theorem ball_bot {r : ℝ} (x : E) (hr : 0 < r) : ball (⊥ : Seminorm 𝕜 E) x r = Set.univ :=
ball_zero' x hr
#align seminorm.ball_bot Seminorm.ball_bot
@[simp]
theorem closedBall_bot {r : ℝ} (x : E) (hr : 0 < r) :
closedBall (⊥ : Seminorm 𝕜 E) x r = Set.univ :=
closedBall_zero' x hr
#align seminorm.closed_ball_bot Seminorm.closedBall_bot
/-- Seminorm-balls at the origin are balanced. -/
theorem balanced_ball_zero (r : ℝ) : Balanced 𝕜 (ball p 0 r) := by
rintro a ha x ⟨y, hy, hx⟩
rw [mem_ball_zero, ← hx, map_smul_eq_mul]
calc
_ ≤ p y := mul_le_of_le_one_left (apply_nonneg p _) ha
_ < r := by rwa [mem_ball_zero] at hy
#align seminorm.balanced_ball_zero Seminorm.balanced_ball_zero
/-- Closed seminorm-balls at the origin are balanced. -/
theorem balanced_closedBall_zero (r : ℝ) : Balanced 𝕜 (closedBall p 0 r) := by
rintro a ha x ⟨y, hy, hx⟩
rw [mem_closedBall_zero, ← hx, map_smul_eq_mul]
calc
_ ≤ p y := mul_le_of_le_one_left (apply_nonneg p _) ha
_ ≤ r := by rwa [mem_closedBall_zero] at hy
#align seminorm.balanced_closed_ball_zero Seminorm.balanced_closedBall_zero
theorem ball_finset_sup_eq_iInter (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) {r : ℝ}
(hr : 0 < r) : ball (s.sup p) x r = ⋂ i ∈ s, ball (p i) x r := by
lift r to NNReal using hr.le
simp_rw [ball, iInter_setOf, finset_sup_apply, NNReal.coe_lt_coe,
Finset.sup_lt_iff (show ⊥ < r from hr), ← NNReal.coe_lt_coe, NNReal.coe_mk]
#align seminorm.ball_finset_sup_eq_Inter Seminorm.ball_finset_sup_eq_iInter
theorem closedBall_finset_sup_eq_iInter (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) {r : ℝ}
(hr : 0 ≤ r) : closedBall (s.sup p) x r = ⋂ i ∈ s, closedBall (p i) x r := by
lift r to NNReal using hr
simp_rw [closedBall, iInter_setOf, finset_sup_apply, NNReal.coe_le_coe, Finset.sup_le_iff, ←
NNReal.coe_le_coe, NNReal.coe_mk]
#align seminorm.closed_ball_finset_sup_eq_Inter Seminorm.closedBall_finset_sup_eq_iInter
theorem ball_finset_sup (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) {r : ℝ} (hr : 0 < r) :
ball (s.sup p) x r = s.inf fun i => ball (p i) x r := by
rw [Finset.inf_eq_iInf]
exact ball_finset_sup_eq_iInter _ _ _ hr
#align seminorm.ball_finset_sup Seminorm.ball_finset_sup
theorem closedBall_finset_sup (p : ι → Seminorm 𝕜 E) (s : Finset ι) (x : E) {r : ℝ} (hr : 0 ≤ r) :
closedBall (s.sup p) x r = s.inf fun i => closedBall (p i) x r := by
rw [Finset.inf_eq_iInf]
exact closedBall_finset_sup_eq_iInter _ _ _ hr
#align seminorm.closed_ball_finset_sup Seminorm.closedBall_finset_sup
@[simp]
| Mathlib/Analysis/Seminorm.lean | 911 | 914 | theorem ball_eq_emptyset (p : Seminorm 𝕜 E) {x : E} {r : ℝ} (hr : r ≤ 0) : p.ball x r = ∅ := by |
ext
rw [Seminorm.mem_ball, Set.mem_empty_iff_false, iff_false_iff, not_lt]
exact hr.trans (apply_nonneg p _)
|
/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.Algebra.Polynomial.Module.Basic
import Mathlib.Algebra.Ring.Idempotents
import Mathlib.RingTheory.Ideal.LocalRing
import Mathlib.RingTheory.Noetherian
import Mathlib.RingTheory.ReesAlgebra
import Mathlib.RingTheory.Finiteness
import Mathlib.Order.Basic
import Mathlib.Order.Hom.Lattice
#align_import ring_theory.filtration from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# `I`-filtrations of modules
This file contains the definitions and basic results around (stable) `I`-filtrations of modules.
## Main results
- `Ideal.Filtration`:
An `I`-filtration on the module `M` is a sequence of decreasing submodules `N i` such that
`∀ i, I • (N i) ≤ N (i + 1)`. Note that we do not require the filtration to start from `⊤`.
- `Ideal.Filtration.Stable`: An `I`-filtration is stable if `I • (N i) = N (i + 1)` for large
enough `i`.
- `Ideal.Filtration.submodule`: The associated module `⨁ Nᵢ` of a filtration, implemented as a
submodule of `M[X]`.
- `Ideal.Filtration.submodule_fg_iff_stable`: If `F.N i` are all finitely generated, then
`F.Stable` iff `F.submodule.FG`.
- `Ideal.Filtration.Stable.of_le`: In a finite module over a noetherian ring,
if `F' ≤ F`, then `F.Stable → F'.Stable`.
- `Ideal.exists_pow_inf_eq_pow_smul`: **Artin-Rees lemma**.
given `N ≤ M`, there exists a `k` such that `IⁿM ⊓ N = Iⁿ⁻ᵏ(IᵏM ⊓ N)` for all `n ≥ k`.
- `Ideal.iInf_pow_eq_bot_of_localRing`:
**Krull's intersection theorem** (`⨅ i, I ^ i = ⊥`) for noetherian local rings.
- `Ideal.iInf_pow_eq_bot_of_isDomain`:
**Krull's intersection theorem** (`⨅ i, I ^ i = ⊥`) for noetherian domains.
-/
universe u v
variable {R M : Type u} [CommRing R] [AddCommGroup M] [Module R M] (I : Ideal R)
open Polynomial
open scoped Polynomial
/-- An `I`-filtration on the module `M` is a sequence of decreasing submodules `N i` such that
`I • (N i) ≤ N (i + 1)`. Note that we do not require the filtration to start from `⊤`. -/
@[ext]
structure Ideal.Filtration (M : Type u) [AddCommGroup M] [Module R M] where
N : ℕ → Submodule R M
mono : ∀ i, N (i + 1) ≤ N i
smul_le : ∀ i, I • N i ≤ N (i + 1)
#align ideal.filtration Ideal.Filtration
variable (F F' : I.Filtration M) {I}
namespace Ideal.Filtration
theorem pow_smul_le (i j : ℕ) : I ^ i • F.N j ≤ F.N (i + j) := by
induction' i with _ ih
· simp
· rw [pow_succ', mul_smul, add_assoc, add_comm 1, ← add_assoc]
exact (smul_mono_right _ ih).trans (F.smul_le _)
#align ideal.filtration.pow_smul_le Ideal.Filtration.pow_smul_le
theorem pow_smul_le_pow_smul (i j k : ℕ) : I ^ (i + k) • F.N j ≤ I ^ k • F.N (i + j) := by
rw [add_comm, pow_add, mul_smul]
exact smul_mono_right _ (F.pow_smul_le i j)
#align ideal.filtration.pow_smul_le_pow_smul Ideal.Filtration.pow_smul_le_pow_smul
protected theorem antitone : Antitone F.N :=
antitone_nat_of_succ_le F.mono
#align ideal.filtration.antitone Ideal.Filtration.antitone
/-- The trivial `I`-filtration of `N`. -/
@[simps]
def _root_.Ideal.trivialFiltration (I : Ideal R) (N : Submodule R M) : I.Filtration M where
N _ := N
mono _ := le_rfl
smul_le _ := Submodule.smul_le_right
#align ideal.trivial_filtration Ideal.trivialFiltration
/-- The `sup` of two `I.Filtration`s is an `I.Filtration`. -/
instance : Sup (I.Filtration M) :=
⟨fun F F' =>
⟨F.N ⊔ F'.N, fun i => sup_le_sup (F.mono i) (F'.mono i), fun i =>
(Submodule.smul_sup _ _ _).trans_le <| sup_le_sup (F.smul_le i) (F'.smul_le i)⟩⟩
/-- The `sSup` of a family of `I.Filtration`s is an `I.Filtration`. -/
instance : SupSet (I.Filtration M) :=
⟨fun S =>
{ N := sSup (Ideal.Filtration.N '' S)
mono := fun i => by
apply sSup_le_sSup_of_forall_exists_le _
rintro _ ⟨⟨_, F, hF, rfl⟩, rfl⟩
exact ⟨_, ⟨⟨_, F, hF, rfl⟩, rfl⟩, F.mono i⟩
smul_le := fun i => by
rw [sSup_eq_iSup', iSup_apply, Submodule.smul_iSup, iSup_apply]
apply iSup_mono _
rintro ⟨_, F, hF, rfl⟩
exact F.smul_le i }⟩
/-- The `inf` of two `I.Filtration`s is an `I.Filtration`. -/
instance : Inf (I.Filtration M) :=
⟨fun F F' =>
⟨F.N ⊓ F'.N, fun i => inf_le_inf (F.mono i) (F'.mono i), fun i =>
(smul_inf_le _ _ _).trans <| inf_le_inf (F.smul_le i) (F'.smul_le i)⟩⟩
/-- The `sInf` of a family of `I.Filtration`s is an `I.Filtration`. -/
instance : InfSet (I.Filtration M) :=
⟨fun S =>
{ N := sInf (Ideal.Filtration.N '' S)
mono := fun i => by
apply sInf_le_sInf_of_forall_exists_le _
rintro _ ⟨⟨_, F, hF, rfl⟩, rfl⟩
exact ⟨_, ⟨⟨_, F, hF, rfl⟩, rfl⟩, F.mono i⟩
smul_le := fun i => by
rw [sInf_eq_iInf', iInf_apply, iInf_apply]
refine smul_iInf_le.trans ?_
apply iInf_mono _
rintro ⟨_, F, hF, rfl⟩
exact F.smul_le i }⟩
instance : Top (I.Filtration M) :=
⟨I.trivialFiltration ⊤⟩
instance : Bot (I.Filtration M) :=
⟨I.trivialFiltration ⊥⟩
@[simp]
theorem sup_N : (F ⊔ F').N = F.N ⊔ F'.N :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.sup_N Ideal.Filtration.sup_N
@[simp]
theorem sSup_N (S : Set (I.Filtration M)) : (sSup S).N = sSup (Ideal.Filtration.N '' S) :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.Sup_N Ideal.Filtration.sSup_N
@[simp]
theorem inf_N : (F ⊓ F').N = F.N ⊓ F'.N :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.inf_N Ideal.Filtration.inf_N
@[simp]
theorem sInf_N (S : Set (I.Filtration M)) : (sInf S).N = sInf (Ideal.Filtration.N '' S) :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.Inf_N Ideal.Filtration.sInf_N
@[simp]
theorem top_N : (⊤ : I.Filtration M).N = ⊤ :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.top_N Ideal.Filtration.top_N
@[simp]
theorem bot_N : (⊥ : I.Filtration M).N = ⊥ :=
rfl
set_option linter.uppercaseLean3 false in
#align ideal.filtration.bot_N Ideal.Filtration.bot_N
@[simp]
theorem iSup_N {ι : Sort*} (f : ι → I.Filtration M) : (iSup f).N = ⨆ i, (f i).N :=
congr_arg sSup (Set.range_comp _ _).symm
set_option linter.uppercaseLean3 false in
#align ideal.filtration.supr_N Ideal.Filtration.iSup_N
@[simp]
theorem iInf_N {ι : Sort*} (f : ι → I.Filtration M) : (iInf f).N = ⨅ i, (f i).N :=
congr_arg sInf (Set.range_comp _ _).symm
set_option linter.uppercaseLean3 false in
#align ideal.filtration.infi_N Ideal.Filtration.iInf_N
instance : CompleteLattice (I.Filtration M) :=
Function.Injective.completeLattice Ideal.Filtration.N Ideal.Filtration.ext sup_N inf_N
(fun _ => sSup_image) (fun _ => sInf_image) top_N bot_N
instance : Inhabited (I.Filtration M) :=
⟨⊥⟩
/-- An `I` filtration is stable if `I • F.N n = F.N (n+1)` for large enough `n`. -/
def Stable : Prop :=
∃ n₀, ∀ n ≥ n₀, I • F.N n = F.N (n + 1)
#align ideal.filtration.stable Ideal.Filtration.Stable
/-- The trivial stable `I`-filtration of `N`. -/
@[simps]
def _root_.Ideal.stableFiltration (I : Ideal R) (N : Submodule R M) : I.Filtration M where
N i := I ^ i • N
mono i := by dsimp only; rw [add_comm, pow_add, mul_smul]; exact Submodule.smul_le_right
smul_le i := by dsimp only; rw [add_comm, pow_add, mul_smul, pow_one]
#align ideal.stable_filtration Ideal.stableFiltration
theorem _root_.Ideal.stableFiltration_stable (I : Ideal R) (N : Submodule R M) :
(I.stableFiltration N).Stable := by
use 0
intro n _
dsimp
rw [add_comm, pow_add, mul_smul, pow_one]
#align ideal.stable_filtration_stable Ideal.stableFiltration_stable
variable {F F'} (h : F.Stable)
theorem Stable.exists_pow_smul_eq : ∃ n₀, ∀ k, F.N (n₀ + k) = I ^ k • F.N n₀ := by
obtain ⟨n₀, hn⟩ := h
use n₀
intro k
induction' k with _ ih
· simp
· rw [← add_assoc, ← hn, ih, add_comm, pow_add, mul_smul, pow_one]
omega
#align ideal.filtration.stable.exists_pow_smul_eq Ideal.Filtration.Stable.exists_pow_smul_eq
theorem Stable.exists_pow_smul_eq_of_ge : ∃ n₀, ∀ n ≥ n₀, F.N n = I ^ (n - n₀) • F.N n₀ := by
obtain ⟨n₀, hn₀⟩ := h.exists_pow_smul_eq
use n₀
intro n hn
convert hn₀ (n - n₀)
rw [add_comm, tsub_add_cancel_of_le hn]
#align ideal.filtration.stable.exists_pow_smul_eq_of_ge Ideal.Filtration.Stable.exists_pow_smul_eq_of_ge
theorem stable_iff_exists_pow_smul_eq_of_ge :
F.Stable ↔ ∃ n₀, ∀ n ≥ n₀, F.N n = I ^ (n - n₀) • F.N n₀ := by
refine ⟨Stable.exists_pow_smul_eq_of_ge, fun h => ⟨h.choose, fun n hn => ?_⟩⟩
rw [h.choose_spec n hn, h.choose_spec (n + 1) (by omega), smul_smul, ← pow_succ',
tsub_add_eq_add_tsub hn]
#align ideal.filtration.stable_iff_exists_pow_smul_eq_of_ge Ideal.Filtration.stable_iff_exists_pow_smul_eq_of_ge
theorem Stable.exists_forall_le (h : F.Stable) (e : F.N 0 ≤ F'.N 0) :
∃ n₀, ∀ n, F.N (n + n₀) ≤ F'.N n := by
obtain ⟨n₀, hF⟩ := h
use n₀
intro n
induction' n with n hn
· refine (F.antitone ?_).trans e; simp
· rw [add_right_comm, ← hF]
· exact (smul_mono_right _ hn).trans (F'.smul_le _)
simp
#align ideal.filtration.stable.exists_forall_le Ideal.Filtration.Stable.exists_forall_le
theorem Stable.bounded_difference (h : F.Stable) (h' : F'.Stable) (e : F.N 0 = F'.N 0) :
∃ n₀, ∀ n, F.N (n + n₀) ≤ F'.N n ∧ F'.N (n + n₀) ≤ F.N n := by
obtain ⟨n₁, h₁⟩ := h.exists_forall_le (le_of_eq e)
obtain ⟨n₂, h₂⟩ := h'.exists_forall_le (le_of_eq e.symm)
use max n₁ n₂
intro n
refine ⟨(F.antitone ?_).trans (h₁ n), (F'.antitone ?_).trans (h₂ n)⟩ <;> simp
#align ideal.filtration.stable.bounded_difference Ideal.Filtration.Stable.bounded_difference
open PolynomialModule
variable (F F')
/-- The `R[IX]`-submodule of `M[X]` associated with an `I`-filtration. -/
protected def submodule : Submodule (reesAlgebra I) (PolynomialModule R M) where
carrier := { f | ∀ i, f i ∈ F.N i }
add_mem' hf hg i := Submodule.add_mem _ (hf i) (hg i)
zero_mem' i := Submodule.zero_mem _
smul_mem' r f hf i := by
rw [Subalgebra.smul_def, PolynomialModule.smul_apply]
apply Submodule.sum_mem
rintro ⟨j, k⟩ e
rw [Finset.mem_antidiagonal] at e
subst e
exact F.pow_smul_le j k (Submodule.smul_mem_smul (r.2 j) (hf k))
#align ideal.filtration.submodule Ideal.Filtration.submodule
@[simp]
theorem mem_submodule (f : PolynomialModule R M) : f ∈ F.submodule ↔ ∀ i, f i ∈ F.N i :=
Iff.rfl
#align ideal.filtration.mem_submodule Ideal.Filtration.mem_submodule
theorem inf_submodule : (F ⊓ F').submodule = F.submodule ⊓ F'.submodule := by
ext
exact forall_and
#align ideal.filtration.inf_submodule Ideal.Filtration.inf_submodule
variable (I M)
/-- `Ideal.Filtration.submodule` as an `InfHom`. -/
def submoduleInfHom :
InfHom (I.Filtration M) (Submodule (reesAlgebra I) (PolynomialModule R M)) where
toFun := Ideal.Filtration.submodule
map_inf' := inf_submodule
#align ideal.filtration.submodule_inf_hom Ideal.Filtration.submoduleInfHom
variable {I M}
theorem submodule_closure_single :
AddSubmonoid.closure (⋃ i, single R i '' (F.N i : Set M)) = F.submodule.toAddSubmonoid := by
apply le_antisymm
· rw [AddSubmonoid.closure_le, Set.iUnion_subset_iff]
rintro i _ ⟨m, hm, rfl⟩ j
rw [single_apply]
split_ifs with h
· rwa [← h]
· exact (F.N j).zero_mem
· intro f hf
rw [← f.sum_single]
apply AddSubmonoid.sum_mem _ _
rintro c -
exact AddSubmonoid.subset_closure (Set.subset_iUnion _ c <| Set.mem_image_of_mem _ (hf c))
#align ideal.filtration.submodule_closure_single Ideal.Filtration.submodule_closure_single
theorem submodule_span_single :
Submodule.span (reesAlgebra I) (⋃ i, single R i '' (F.N i : Set M)) = F.submodule := by
rw [← Submodule.span_closure, submodule_closure_single, Submodule.coe_toAddSubmonoid]
exact Submodule.span_eq (Filtration.submodule F)
#align ideal.filtration.submodule_span_single Ideal.Filtration.submodule_span_single
theorem submodule_eq_span_le_iff_stable_ge (n₀ : ℕ) :
F.submodule = Submodule.span _ (⋃ i ≤ n₀, single R i '' (F.N i : Set M)) ↔
∀ n ≥ n₀, I • F.N n = F.N (n + 1) := by
rw [← submodule_span_single, ← LE.le.le_iff_eq, Submodule.span_le, Set.iUnion_subset_iff]
swap; · exact Submodule.span_mono (Set.iUnion₂_subset_iUnion _ _)
constructor
· intro H n hn
refine (F.smul_le n).antisymm ?_
intro x hx
obtain ⟨l, hl⟩ := (Finsupp.mem_span_iff_total _ _ _).mp (H _ ⟨x, hx, rfl⟩)
replace hl := congr_arg (fun f : ℕ →₀ M => f (n + 1)) hl
dsimp only at hl
erw [Finsupp.single_eq_same] at hl
rw [← hl, Finsupp.total_apply, Finsupp.sum_apply]
apply Submodule.sum_mem _ _
rintro ⟨_, _, ⟨n', rfl⟩, _, ⟨hn', rfl⟩, m, hm, rfl⟩ -
dsimp only [Subtype.coe_mk]
rw [Subalgebra.smul_def, smul_single_apply, if_pos (show n' ≤ n + 1 by omega)]
have e : n' ≤ n := by omega
have := F.pow_smul_le_pow_smul (n - n') n' 1
rw [tsub_add_cancel_of_le e, pow_one, add_comm _ 1, ← add_tsub_assoc_of_le e, add_comm] at this
exact this (Submodule.smul_mem_smul ((l _).2 <| n + 1 - n') hm)
· let F' := Submodule.span (reesAlgebra I) (⋃ i ≤ n₀, single R i '' (F.N i : Set M))
intro hF i
have : ∀ i ≤ n₀, single R i '' (F.N i : Set M) ⊆ F' := by
-- Porting note: Original proof was
-- `fun i hi => Set.Subset.trans (Set.subset_iUnion₂ i hi) Submodule.subset_span`
intro i hi
refine Set.Subset.trans ?_ Submodule.subset_span
refine @Set.subset_iUnion₂ _ _ _ (fun i => fun _ => ↑((single R i) '' ((N F i) : Set M))) i ?_
exact hi
induction' i with j hj
· exact this _ (zero_le _)
by_cases hj' : j.succ ≤ n₀
· exact this _ hj'
simp only [not_le, Nat.lt_succ_iff] at hj'
rw [← hF _ hj']
rintro _ ⟨m, hm, rfl⟩
refine Submodule.smul_induction_on hm (fun r hr m' hm' => ?_) (fun x y hx hy => ?_)
· rw [add_comm, ← monomial_smul_single]
exact F'.smul_mem
⟨_, reesAlgebra.monomial_mem.mpr (by rwa [pow_one])⟩ (hj <| Set.mem_image_of_mem _ hm')
· rw [map_add]
exact F'.add_mem hx hy
#align ideal.filtration.submodule_eq_span_le_iff_stable_ge Ideal.Filtration.submodule_eq_span_le_iff_stable_ge
/-- If the components of a filtration are finitely generated, then the filtration is stable iff
its associated submodule of is finitely generated. -/
theorem submodule_fg_iff_stable (hF' : ∀ i, (F.N i).FG) : F.submodule.FG ↔ F.Stable := by
classical
delta Ideal.Filtration.Stable
simp_rw [← F.submodule_eq_span_le_iff_stable_ge]
constructor
· rintro H
refine H.stabilizes_of_iSup_eq
⟨fun n₀ => Submodule.span _ (⋃ (i : ℕ) (_ : i ≤ n₀), single R i '' ↑(F.N i)), ?_⟩ ?_
· intro n m e
rw [Submodule.span_le, Set.iUnion₂_subset_iff]
intro i hi
refine Set.Subset.trans ?_ Submodule.subset_span
refine @Set.subset_iUnion₂ _ _ _ (fun i => fun _ => ↑((single R i) '' ((N F i) : Set M))) i ?_
exact hi.trans e
· dsimp
rw [← Submodule.span_iUnion, ← submodule_span_single]
congr 1
ext
simp only [Set.mem_iUnion, Set.mem_image, SetLike.mem_coe, exists_prop]
constructor
· rintro ⟨-, i, -, e⟩; exact ⟨i, e⟩
· rintro ⟨i, e⟩; exact ⟨i, i, le_refl i, e⟩
· rintro ⟨n, hn⟩
rw [hn]
simp_rw [Submodule.span_iUnion₂, ← Finset.mem_range_succ_iff, iSup_subtype']
apply Submodule.fg_iSup
rintro ⟨i, hi⟩
obtain ⟨s, hs⟩ := hF' i
have : Submodule.span (reesAlgebra I) (s.image (lsingle R i) : Set (PolynomialModule R M)) =
Submodule.span _ (single R i '' (F.N i : Set M)) := by
rw [Finset.coe_image, ← Submodule.span_span_of_tower R, ← Submodule.map_span, hs]; rfl
rw [Subtype.coe_mk, ← this]
exact ⟨_, rfl⟩
#align ideal.filtration.submodule_fg_iff_stable Ideal.Filtration.submodule_fg_iff_stable
variable {F}
theorem Stable.of_le [IsNoetherianRing R] [Module.Finite R M] (hF : F.Stable)
{F' : I.Filtration M} (hf : F' ≤ F) : F'.Stable := by
rw [← submodule_fg_iff_stable] at hF ⊢
any_goals intro i; exact IsNoetherian.noetherian _
have := isNoetherian_of_fg_of_noetherian _ hF
rw [isNoetherian_submodule] at this
exact this _ (OrderHomClass.mono (submoduleInfHom M I) hf)
#align ideal.filtration.stable.of_le Ideal.Filtration.Stable.of_le
theorem Stable.inter_right [IsNoetherianRing R] [Module.Finite R M] (hF : F.Stable) :
(F ⊓ F').Stable :=
hF.of_le inf_le_left
#align ideal.filtration.stable.inter_right Ideal.Filtration.Stable.inter_right
theorem Stable.inter_left [IsNoetherianRing R] [Module.Finite R M] (hF : F.Stable) :
(F' ⊓ F).Stable :=
hF.of_le inf_le_right
#align ideal.filtration.stable.inter_left Ideal.Filtration.Stable.inter_left
end Ideal.Filtration
variable (I)
/-- **Artin-Rees lemma** -/
theorem Ideal.exists_pow_inf_eq_pow_smul [IsNoetherianRing R] [Module.Finite R M]
(N : Submodule R M) : ∃ k : ℕ, ∀ n ≥ k, I ^ n • ⊤ ⊓ N = I ^ (n - k) • (I ^ k • ⊤ ⊓ N) :=
((I.stableFiltration_stable ⊤).inter_right (I.trivialFiltration N)).exists_pow_smul_eq_of_ge
#align ideal.exists_pow_inf_eq_pow_smul Ideal.exists_pow_inf_eq_pow_smul
theorem Ideal.mem_iInf_smul_pow_eq_bot_iff [IsNoetherianRing R] [Module.Finite R M] (x : M) :
x ∈ (⨅ i : ℕ, I ^ i • ⊤ : Submodule R M) ↔ ∃ r : I, (r : R) • x = x := by
let N := (⨅ i : ℕ, I ^ i • ⊤ : Submodule R M)
have hN : ∀ k, (I.stableFiltration ⊤ ⊓ I.trivialFiltration N).N k = N :=
fun k => inf_eq_right.mpr ((iInf_le _ k).trans <| le_of_eq <| by simp)
constructor
· obtain ⟨r, hr₁, hr₂⟩ :=
Submodule.exists_mem_and_smul_eq_self_of_fg_of_le_smul I N (IsNoetherian.noetherian N) (by
obtain ⟨k, hk⟩ := (I.stableFiltration_stable ⊤).inter_right (I.trivialFiltration N)
have := hk k (le_refl _)
rw [hN, hN] at this
exact le_of_eq this.symm)
intro H
exact ⟨⟨r, hr₁⟩, hr₂ _ H⟩
· rintro ⟨r, eq⟩
rw [Submodule.mem_iInf]
intro i
induction' i with i hi
· simp
· rw [add_comm, pow_add, ← smul_smul, pow_one, ← eq]
exact Submodule.smul_mem_smul r.prop hi
#align ideal.mem_infi_smul_pow_eq_bot_iff Ideal.mem_iInf_smul_pow_eq_bot_iff
theorem Ideal.iInf_pow_smul_eq_bot_of_localRing [IsNoetherianRing R] [LocalRing R]
[Module.Finite R M] (h : I ≠ ⊤) : (⨅ i : ℕ, I ^ i • ⊤ : Submodule R M) = ⊥ := by
rw [eq_bot_iff]
intro x hx
obtain ⟨r, hr⟩ := (I.mem_iInf_smul_pow_eq_bot_iff x).mp hx
have := LocalRing.isUnit_one_sub_self_of_mem_nonunits _ (LocalRing.le_maximalIdeal h r.prop)
apply this.smul_left_cancel.mp
simp [sub_smul, hr]
#align ideal.infi_pow_smul_eq_bot_of_local_ring Ideal.iInf_pow_smul_eq_bot_of_localRing
/-- **Krull's intersection theorem** for noetherian local rings. -/
| Mathlib/RingTheory/Filtration.lean | 471 | 475 | theorem Ideal.iInf_pow_eq_bot_of_localRing [IsNoetherianRing R] [LocalRing R] (h : I ≠ ⊤) :
⨅ i : ℕ, I ^ i = ⊥ := by |
convert I.iInf_pow_smul_eq_bot_of_localRing (M := R) h
ext i
rw [smul_eq_mul, ← Ideal.one_eq_top, mul_one]
|
/-
Copyright (c) 2021 Frédéric Dupuis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Frédéric Dupuis
-/
import Mathlib.Algebra.Group.Subgroup.Basic
import Mathlib.Algebra.Module.Defs
import Mathlib.Algebra.Star.Pi
#align_import algebra.star.self_adjoint from "leanprover-community/mathlib"@"a6ece35404f60597c651689c1b46ead86de5ac1b"
/-!
# Self-adjoint, skew-adjoint and normal elements of a star additive group
This file defines `selfAdjoint R` (resp. `skewAdjoint R`), where `R` is a star additive group,
as the additive subgroup containing the elements that satisfy `star x = x` (resp. `star x = -x`).
This includes, for instance, (skew-)Hermitian operators on Hilbert spaces.
We also define `IsStarNormal R`, a `Prop` that states that an element `x` satisfies
`star x * x = x * star x`.
## Implementation notes
* When `R` is a `StarModule R₂ R`, then `selfAdjoint R` has a natural
`Module (selfAdjoint R₂) (selfAdjoint R)` structure. However, doing this literally would be
undesirable since in the main case of interest (`R₂ = ℂ`) we want `Module ℝ (selfAdjoint R)`
and not `Module (selfAdjoint ℂ) (selfAdjoint R)`. We solve this issue by adding the typeclass
`[TrivialStar R₃]`, of which `ℝ` is an instance (registered in `Data/Real/Basic`), and then
add a `[Module R₃ (selfAdjoint R)]` instance whenever we have
`[Module R₃ R] [TrivialStar R₃]`. (Another approach would have been to define
`[StarInvariantScalars R₃ R]` to express the fact that `star (x • v) = x • star v`, but
this typeclass would have the disadvantage of taking two type arguments.)
## TODO
* Define `IsSkewAdjoint` to match `IsSelfAdjoint`.
* Define `fun z x => z * x * star z` (i.e. conjugation by `z`) as a monoid action of `R` on `R`
(similar to the existing `ConjAct` for groups), and then state the fact that `selfAdjoint R` is
invariant under it.
-/
open Function
variable {R A : Type*}
/-- An element is self-adjoint if it is equal to its star. -/
def IsSelfAdjoint [Star R] (x : R) : Prop :=
star x = x
#align is_self_adjoint IsSelfAdjoint
/-- An element of a star monoid is normal if it commutes with its adjoint. -/
@[mk_iff]
class IsStarNormal [Mul R] [Star R] (x : R) : Prop where
/-- A normal element of a star monoid commutes with its adjoint. -/
star_comm_self : Commute (star x) x
#align is_star_normal IsStarNormal
export IsStarNormal (star_comm_self)
theorem star_comm_self' [Mul R] [Star R] (x : R) [IsStarNormal x] : star x * x = x * star x :=
IsStarNormal.star_comm_self
#align star_comm_self' star_comm_self'
namespace IsSelfAdjoint
-- named to match `Commute.allₓ`
/-- All elements are self-adjoint when `star` is trivial. -/
theorem all [Star R] [TrivialStar R] (r : R) : IsSelfAdjoint r :=
star_trivial _
#align is_self_adjoint.all IsSelfAdjoint.all
theorem star_eq [Star R] {x : R} (hx : IsSelfAdjoint x) : star x = x :=
hx
#align is_self_adjoint.star_eq IsSelfAdjoint.star_eq
theorem _root_.isSelfAdjoint_iff [Star R] {x : R} : IsSelfAdjoint x ↔ star x = x :=
Iff.rfl
#align is_self_adjoint_iff isSelfAdjoint_iff
@[simp]
theorem star_iff [InvolutiveStar R] {x : R} : IsSelfAdjoint (star x) ↔ IsSelfAdjoint x := by
simpa only [IsSelfAdjoint, star_star] using eq_comm
#align is_self_adjoint.star_iff IsSelfAdjoint.star_iff
@[simp]
theorem star_mul_self [Mul R] [StarMul R] (x : R) : IsSelfAdjoint (star x * x) := by
simp only [IsSelfAdjoint, star_mul, star_star]
#align is_self_adjoint.star_mul_self IsSelfAdjoint.star_mul_self
@[simp]
theorem mul_star_self [Mul R] [StarMul R] (x : R) : IsSelfAdjoint (x * star x) := by
simpa only [star_star] using star_mul_self (star x)
#align is_self_adjoint.mul_star_self IsSelfAdjoint.mul_star_self
/-- Self-adjoint elements commute if and only if their product is self-adjoint. -/
lemma commute_iff {R : Type*} [Mul R] [StarMul R] {x y : R}
(hx : IsSelfAdjoint x) (hy : IsSelfAdjoint y) : Commute x y ↔ IsSelfAdjoint (x * y) := by
refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· rw [isSelfAdjoint_iff, star_mul, hx.star_eq, hy.star_eq, h.eq]
· simpa only [star_mul, hx.star_eq, hy.star_eq] using h.symm
/-- Functions in a `StarHomClass` preserve self-adjoint elements. -/
theorem starHom_apply {F R S : Type*} [Star R] [Star S] [FunLike F R S] [StarHomClass F R S]
{x : R} (hx : IsSelfAdjoint x) (f : F) : IsSelfAdjoint (f x) :=
show star (f x) = f x from map_star f x ▸ congr_arg f hx
#align is_self_adjoint.star_hom_apply IsSelfAdjoint.starHom_apply
/- note: this lemma is *not* marked as `simp` so that Lean doesn't look for a `[TrivialStar R]`
instance every time it sees `⊢ IsSelfAdjoint (f x)`, which will likely occur relatively often. -/
theorem _root_.isSelfAdjoint_starHom_apply {F R S : Type*} [Star R] [Star S] [FunLike F R S]
[StarHomClass F R S] [TrivialStar R] (f : F) (x : R) : IsSelfAdjoint (f x) :=
(IsSelfAdjoint.all x).starHom_apply f
section AddMonoid
variable [AddMonoid R] [StarAddMonoid R]
variable (R)
@[simp] theorem _root_.isSelfAdjoint_zero : IsSelfAdjoint (0 : R) := star_zero R
#align is_self_adjoint_zero isSelfAdjoint_zero
variable {R}
theorem add {x y : R} (hx : IsSelfAdjoint x) (hy : IsSelfAdjoint y) : IsSelfAdjoint (x + y) := by
simp only [isSelfAdjoint_iff, star_add, hx.star_eq, hy.star_eq]
#align is_self_adjoint.add IsSelfAdjoint.add
#noalign is_self_adjoint.bit0
end AddMonoid
section AddGroup
variable [AddGroup R] [StarAddMonoid R]
theorem neg {x : R} (hx : IsSelfAdjoint x) : IsSelfAdjoint (-x) := by
simp only [isSelfAdjoint_iff, star_neg, hx.star_eq]
#align is_self_adjoint.neg IsSelfAdjoint.neg
| Mathlib/Algebra/Star/SelfAdjoint.lean | 141 | 142 | theorem sub {x y : R} (hx : IsSelfAdjoint x) (hy : IsSelfAdjoint y) : IsSelfAdjoint (x - y) := by |
simp only [isSelfAdjoint_iff, star_sub, hx.star_eq, hy.star_eq]
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Mario Carneiro
-/
import Mathlib.Algebra.Module.Submodule.Bilinear
import Mathlib.GroupTheory.Congruence.Basic
import Mathlib.LinearAlgebra.Basic
import Mathlib.Tactic.SuppressCompilation
#align_import linear_algebra.tensor_product from "leanprover-community/mathlib"@"88fcdc3da43943f5b01925deddaa5bf0c0e85e4e"
/-!
# Tensor product of modules over commutative semirings.
This file constructs the tensor product of modules over commutative semirings. Given a semiring
`R` and modules over it `M` and `N`, the standard construction of the tensor product is
`TensorProduct R M N`. It is also a module over `R`.
It comes with a canonical bilinear map `M → N → TensorProduct R M N`.
Given any bilinear map `M → N → P`, there is a unique linear map `TensorProduct R M N → P` whose
composition with the canonical bilinear map `M → N → TensorProduct R M N` is the given bilinear
map `M → N → P`.
We start by proving basic lemmas about bilinear maps.
## Notations
This file uses the localized notation `M ⊗ N` and `M ⊗[R] N` for `TensorProduct R M N`, as well
as `m ⊗ₜ n` and `m ⊗ₜ[R] n` for `TensorProduct.tmul R m n`.
## Tags
bilinear, tensor, tensor product
-/
suppress_compilation
section Semiring
variable {R : Type*} [CommSemiring R]
variable {R' : Type*} [Monoid R']
variable {R'' : Type*} [Semiring R'']
variable {M : Type*} {N : Type*} {P : Type*} {Q : Type*} {S : Type*} {T : Type*}
variable [AddCommMonoid M] [AddCommMonoid N] [AddCommMonoid P]
variable [AddCommMonoid Q] [AddCommMonoid S] [AddCommMonoid T]
variable [Module R M] [Module R N] [Module R P] [Module R Q] [Module R S] [Module R T]
variable [DistribMulAction R' M]
variable [Module R'' M]
variable (M N)
namespace TensorProduct
section
variable (R)
/-- The relation on `FreeAddMonoid (M × N)` that generates a congruence whose quotient is
the tensor product. -/
inductive Eqv : FreeAddMonoid (M × N) → FreeAddMonoid (M × N) → Prop
| of_zero_left : ∀ n : N, Eqv (.of (0, n)) 0
| of_zero_right : ∀ m : M, Eqv (.of (m, 0)) 0
| of_add_left : ∀ (m₁ m₂ : M) (n : N), Eqv (.of (m₁, n) + .of (m₂, n)) (.of (m₁ + m₂, n))
| of_add_right : ∀ (m : M) (n₁ n₂ : N), Eqv (.of (m, n₁) + .of (m, n₂)) (.of (m, n₁ + n₂))
| of_smul : ∀ (r : R) (m : M) (n : N), Eqv (.of (r • m, n)) (.of (m, r • n))
| add_comm : ∀ x y, Eqv (x + y) (y + x)
#align tensor_product.eqv TensorProduct.Eqv
end
end TensorProduct
variable (R)
/-- The tensor product of two modules `M` and `N` over the same commutative semiring `R`.
The localized notations are `M ⊗ N` and `M ⊗[R] N`, accessed by `open scoped TensorProduct`. -/
def TensorProduct : Type _ :=
(addConGen (TensorProduct.Eqv R M N)).Quotient
#align tensor_product TensorProduct
variable {R}
set_option quotPrecheck false in
@[inherit_doc TensorProduct] scoped[TensorProduct] infixl:100 " ⊗ " => TensorProduct _
@[inherit_doc] scoped[TensorProduct] notation:100 M " ⊗[" R "] " N:100 => TensorProduct R M N
namespace TensorProduct
section Module
protected instance add : Add (M ⊗[R] N) :=
(addConGen (TensorProduct.Eqv R M N)).hasAdd
instance addZeroClass : AddZeroClass (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with
/- The `toAdd` field is given explicitly as `TensorProduct.add` for performance reasons.
This avoids any need to unfold `Con.addMonoid` when the type checker is checking
that instance diagrams commute -/
toAdd := TensorProduct.add _ _ }
instance addSemigroup : AddSemigroup (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with
toAdd := TensorProduct.add _ _ }
instance addCommSemigroup : AddCommSemigroup (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with
toAddSemigroup := TensorProduct.addSemigroup _ _
add_comm := fun x y =>
AddCon.induction_on₂ x y fun _ _ =>
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.add_comm _ _ }
instance : Inhabited (M ⊗[R] N) :=
⟨0⟩
variable (R) {M N}
/-- The canonical function `M → N → M ⊗ N`. The localized notations are `m ⊗ₜ n` and `m ⊗ₜ[R] n`,
accessed by `open scoped TensorProduct`. -/
def tmul (m : M) (n : N) : M ⊗[R] N :=
AddCon.mk' _ <| FreeAddMonoid.of (m, n)
#align tensor_product.tmul TensorProduct.tmul
variable {R}
/-- The canonical function `M → N → M ⊗ N`. -/
infixl:100 " ⊗ₜ " => tmul _
/-- The canonical function `M → N → M ⊗ N`. -/
notation:100 x " ⊗ₜ[" R "] " y:100 => tmul R x y
-- Porting note: make the arguments of induction_on explicit
@[elab_as_elim]
protected theorem induction_on {motive : M ⊗[R] N → Prop} (z : M ⊗[R] N)
(zero : motive 0)
(tmul : ∀ x y, motive <| x ⊗ₜ[R] y)
(add : ∀ x y, motive x → motive y → motive (x + y)) : motive z :=
AddCon.induction_on z fun x =>
FreeAddMonoid.recOn x zero fun ⟨m, n⟩ y ih => by
rw [AddCon.coe_add]
exact add _ _ (tmul ..) ih
#align tensor_product.induction_on TensorProduct.induction_on
/-- Lift an `R`-balanced map to the tensor product.
A map `f : M →+ N →+ P` additive in both components is `R`-balanced, or middle linear with respect
to `R`, if scalar multiplication in either argument is equivalent, `f (r • m) n = f m (r • n)`.
Note that strictly the first action should be a right-action by `R`, but for now `R` is commutative
so it doesn't matter. -/
-- TODO: use this to implement `lift` and `SMul.aux`. For now we do not do this as it causes
-- performance issues elsewhere.
def liftAddHom (f : M →+ N →+ P)
(hf : ∀ (r : R) (m : M) (n : N), f (r • m) n = f m (r • n)) :
M ⊗[R] N →+ P :=
(addConGen (TensorProduct.Eqv R M N)).lift (FreeAddMonoid.lift (fun mn : M × N => f mn.1 mn.2)) <|
AddCon.addConGen_le fun x y hxy =>
match x, y, hxy with
| _, _, .of_zero_left n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, FreeAddMonoid.lift_eval_of, map_zero,
AddMonoidHom.zero_apply]
| _, _, .of_zero_right m =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, FreeAddMonoid.lift_eval_of, map_zero]
| _, _, .of_add_left m₁ m₂ n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, FreeAddMonoid.lift_eval_of, map_add,
AddMonoidHom.add_apply]
| _, _, .of_add_right m n₁ n₂ =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, FreeAddMonoid.lift_eval_of, map_add]
| _, _, .of_smul s m n =>
(AddCon.ker_rel _).2 <| by rw [FreeAddMonoid.lift_eval_of, FreeAddMonoid.lift_eval_of, hf]
| _, _, .add_comm x y =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, add_comm]
@[simp]
theorem liftAddHom_tmul (f : M →+ N →+ P)
(hf : ∀ (r : R) (m : M) (n : N), f (r • m) n = f m (r • n)) (m : M) (n : N) :
liftAddHom f hf (m ⊗ₜ n) = f m n :=
rfl
variable (M)
@[simp]
theorem zero_tmul (n : N) : (0 : M) ⊗ₜ[R] n = 0 :=
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_zero_left _
#align tensor_product.zero_tmul TensorProduct.zero_tmul
variable {M}
theorem add_tmul (m₁ m₂ : M) (n : N) : (m₁ + m₂) ⊗ₜ n = m₁ ⊗ₜ n + m₂ ⊗ₜ[R] n :=
Eq.symm <| Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_add_left _ _ _
#align tensor_product.add_tmul TensorProduct.add_tmul
variable (N)
@[simp]
theorem tmul_zero (m : M) : m ⊗ₜ[R] (0 : N) = 0 :=
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_zero_right _
#align tensor_product.tmul_zero TensorProduct.tmul_zero
variable {N}
theorem tmul_add (m : M) (n₁ n₂ : N) : m ⊗ₜ (n₁ + n₂) = m ⊗ₜ n₁ + m ⊗ₜ[R] n₂ :=
Eq.symm <| Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_add_right _ _ _
#align tensor_product.tmul_add TensorProduct.tmul_add
instance uniqueLeft [Subsingleton M] : Unique (M ⊗[R] N) where
default := 0
uniq z := z.induction_on rfl (fun x y ↦ by rw [Subsingleton.elim x 0, zero_tmul]; rfl) <| by
rintro _ _ rfl rfl; apply add_zero
instance uniqueRight [Subsingleton N] : Unique (M ⊗[R] N) where
default := 0
uniq z := z.induction_on rfl (fun x y ↦ by rw [Subsingleton.elim y 0, tmul_zero]; rfl) <| by
rintro _ _ rfl rfl; apply add_zero
section
variable (R R' M N)
/-- A typeclass for `SMul` structures which can be moved across a tensor product.
This typeclass is generated automatically from an `IsScalarTower` instance, but exists so that
we can also add an instance for `AddCommGroup.intModule`, allowing `z •` to be moved even if
`R` does not support negation.
Note that `Module R' (M ⊗[R] N)` is available even without this typeclass on `R'`; it's only
needed if `TensorProduct.smul_tmul`, `TensorProduct.smul_tmul'`, or `TensorProduct.tmul_smul` is
used.
-/
class CompatibleSMul [DistribMulAction R' N] : Prop where
smul_tmul : ∀ (r : R') (m : M) (n : N), (r • m) ⊗ₜ n = m ⊗ₜ[R] (r • n)
#align tensor_product.compatible_smul TensorProduct.CompatibleSMul
end
/-- Note that this provides the default `compatible_smul R R M N` instance through
`IsScalarTower.left`. -/
instance (priority := 100) CompatibleSMul.isScalarTower [SMul R' R] [IsScalarTower R' R M]
[DistribMulAction R' N] [IsScalarTower R' R N] : CompatibleSMul R R' M N :=
⟨fun r m n => by
conv_lhs => rw [← one_smul R m]
conv_rhs => rw [← one_smul R n]
rw [← smul_assoc, ← smul_assoc]
exact Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_smul _ _ _⟩
#align tensor_product.compatible_smul.is_scalar_tower TensorProduct.CompatibleSMul.isScalarTower
/-- `smul` can be moved from one side of the product to the other . -/
theorem smul_tmul [DistribMulAction R' N] [CompatibleSMul R R' M N] (r : R') (m : M) (n : N) :
(r • m) ⊗ₜ n = m ⊗ₜ[R] (r • n) :=
CompatibleSMul.smul_tmul _ _ _
#align tensor_product.smul_tmul TensorProduct.smul_tmul
-- Porting note: This is added as a local instance for `SMul.aux`.
-- For some reason type-class inference in Lean 3 unfolded this definition.
private def addMonoidWithWrongNSMul : AddMonoid (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with }
attribute [local instance] addMonoidWithWrongNSMul in
/-- Auxiliary function to defining scalar multiplication on tensor product. -/
def SMul.aux {R' : Type*} [SMul R' M] (r : R') : FreeAddMonoid (M × N) →+ M ⊗[R] N :=
FreeAddMonoid.lift fun p : M × N => (r • p.1) ⊗ₜ p.2
#align tensor_product.smul.aux TensorProduct.SMul.aux
theorem SMul.aux_of {R' : Type*} [SMul R' M] (r : R') (m : M) (n : N) :
SMul.aux r (.of (m, n)) = (r • m) ⊗ₜ[R] n :=
rfl
#align tensor_product.smul.aux_of TensorProduct.SMul.aux_of
variable [SMulCommClass R R' M] [SMulCommClass R R'' M]
/-- Given two modules over a commutative semiring `R`, if one of the factors carries a
(distributive) action of a second type of scalars `R'`, which commutes with the action of `R`, then
the tensor product (over `R`) carries an action of `R'`.
This instance defines this `R'` action in the case that it is the left module which has the `R'`
action. Two natural ways in which this situation arises are:
* Extension of scalars
* A tensor product of a group representation with a module not carrying an action
Note that in the special case that `R = R'`, since `R` is commutative, we just get the usual scalar
action on a tensor product of two modules. This special case is important enough that, for
performance reasons, we define it explicitly below. -/
instance leftHasSMul : SMul R' (M ⊗[R] N) :=
⟨fun r =>
(addConGen (TensorProduct.Eqv R M N)).lift (SMul.aux r : _ →+ M ⊗[R] N) <|
AddCon.addConGen_le fun x y hxy =>
match x, y, hxy with
| _, _, .of_zero_left n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, SMul.aux_of, smul_zero, zero_tmul]
| _, _, .of_zero_right m =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, SMul.aux_of, tmul_zero]
| _, _, .of_add_left m₁ m₂ n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, SMul.aux_of, smul_add, add_tmul]
| _, _, .of_add_right m n₁ n₂ =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, SMul.aux_of, tmul_add]
| _, _, .of_smul s m n =>
(AddCon.ker_rel _).2 <| by rw [SMul.aux_of, SMul.aux_of, ← smul_comm, smul_tmul]
| _, _, .add_comm x y =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, add_comm]⟩
#align tensor_product.left_has_smul TensorProduct.leftHasSMul
instance : SMul R (M ⊗[R] N) :=
TensorProduct.leftHasSMul
protected theorem smul_zero (r : R') : r • (0 : M ⊗[R] N) = 0 :=
AddMonoidHom.map_zero _
#align tensor_product.smul_zero TensorProduct.smul_zero
protected theorem smul_add (r : R') (x y : M ⊗[R] N) : r • (x + y) = r • x + r • y :=
AddMonoidHom.map_add _ _ _
#align tensor_product.smul_add TensorProduct.smul_add
protected theorem zero_smul (x : M ⊗[R] N) : (0 : R'') • x = 0 :=
have : ∀ (r : R'') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
x.induction_on (by rw [TensorProduct.smul_zero])
(fun m n => by rw [this, zero_smul, zero_tmul]) fun x y ihx ihy => by
rw [TensorProduct.smul_add, ihx, ihy, add_zero]
#align tensor_product.zero_smul TensorProduct.zero_smul
protected theorem one_smul (x : M ⊗[R] N) : (1 : R') • x = x :=
have : ∀ (r : R') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
x.induction_on (by rw [TensorProduct.smul_zero])
(fun m n => by rw [this, one_smul])
fun x y ihx ihy => by rw [TensorProduct.smul_add, ihx, ihy]
#align tensor_product.one_smul TensorProduct.one_smul
protected theorem add_smul (r s : R'') (x : M ⊗[R] N) : (r + s) • x = r • x + s • x :=
have : ∀ (r : R'') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
x.induction_on (by simp_rw [TensorProduct.smul_zero, add_zero])
(fun m n => by simp_rw [this, add_smul, add_tmul]) fun x y ihx ihy => by
simp_rw [TensorProduct.smul_add]
rw [ihx, ihy, add_add_add_comm]
#align tensor_product.add_smul TensorProduct.add_smul
instance addMonoid : AddMonoid (M ⊗[R] N) :=
{ TensorProduct.addZeroClass _ _ with
toAddSemigroup := TensorProduct.addSemigroup _ _
toZero := (TensorProduct.addZeroClass _ _).toZero
nsmul := fun n v => n • v
nsmul_zero := by simp [TensorProduct.zero_smul]
nsmul_succ := by simp only [TensorProduct.one_smul, TensorProduct.add_smul, add_comm,
forall_const] }
instance addCommMonoid : AddCommMonoid (M ⊗[R] N) :=
{ TensorProduct.addCommSemigroup _ _ with
toAddMonoid := TensorProduct.addMonoid }
instance leftDistribMulAction : DistribMulAction R' (M ⊗[R] N) :=
have : ∀ (r : R') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
{ smul_add := fun r x y => TensorProduct.smul_add r x y
mul_smul := fun r s x =>
x.induction_on (by simp_rw [TensorProduct.smul_zero])
(fun m n => by simp_rw [this, mul_smul]) fun x y ihx ihy => by
simp_rw [TensorProduct.smul_add]
rw [ihx, ihy]
one_smul := TensorProduct.one_smul
smul_zero := TensorProduct.smul_zero }
#align tensor_product.left_distrib_mul_action TensorProduct.leftDistribMulAction
instance : DistribMulAction R (M ⊗[R] N) :=
TensorProduct.leftDistribMulAction
theorem smul_tmul' (r : R') (m : M) (n : N) : r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n :=
rfl
#align tensor_product.smul_tmul' TensorProduct.smul_tmul'
@[simp]
theorem tmul_smul [DistribMulAction R' N] [CompatibleSMul R R' M N] (r : R') (x : M) (y : N) :
x ⊗ₜ (r • y) = r • x ⊗ₜ[R] y :=
(smul_tmul _ _ _).symm
#align tensor_product.tmul_smul TensorProduct.tmul_smul
theorem smul_tmul_smul (r s : R) (m : M) (n : N) : (r • m) ⊗ₜ[R] (s • n) = (r * s) • m ⊗ₜ[R] n := by
simp_rw [smul_tmul, tmul_smul, mul_smul]
#align tensor_product.smul_tmul_smul TensorProduct.smul_tmul_smul
instance leftModule : Module R'' (M ⊗[R] N) :=
{ add_smul := TensorProduct.add_smul
zero_smul := TensorProduct.zero_smul }
#align tensor_product.left_module TensorProduct.leftModule
instance : Module R (M ⊗[R] N) :=
TensorProduct.leftModule
instance [Module R''ᵐᵒᵖ M] [IsCentralScalar R'' M] : IsCentralScalar R'' (M ⊗[R] N) where
op_smul_eq_smul r x :=
x.induction_on (by rw [smul_zero, smul_zero])
(fun x y => by rw [smul_tmul', smul_tmul', op_smul_eq_smul]) fun x y hx hy => by
rw [smul_add, smul_add, hx, hy]
section
-- Like `R'`, `R'₂` provides a `DistribMulAction R'₂ (M ⊗[R] N)`
variable {R'₂ : Type*} [Monoid R'₂] [DistribMulAction R'₂ M]
variable [SMulCommClass R R'₂ M]
/-- `SMulCommClass R' R'₂ M` implies `SMulCommClass R' R'₂ (M ⊗[R] N)` -/
instance smulCommClass_left [SMulCommClass R' R'₂ M] : SMulCommClass R' R'₂ (M ⊗[R] N) where
smul_comm r' r'₂ x :=
TensorProduct.induction_on x (by simp_rw [TensorProduct.smul_zero])
(fun m n => by simp_rw [smul_tmul', smul_comm]) fun x y ihx ihy => by
simp_rw [TensorProduct.smul_add]; rw [ihx, ihy]
#align tensor_product.smul_comm_class_left TensorProduct.smulCommClass_left
variable [SMul R'₂ R']
/-- `IsScalarTower R'₂ R' M` implies `IsScalarTower R'₂ R' (M ⊗[R] N)` -/
instance isScalarTower_left [IsScalarTower R'₂ R' M] : IsScalarTower R'₂ R' (M ⊗[R] N) :=
⟨fun s r x =>
x.induction_on (by simp)
(fun m n => by rw [smul_tmul', smul_tmul', smul_tmul', smul_assoc]) fun x y ihx ihy => by
rw [smul_add, smul_add, smul_add, ihx, ihy]⟩
#align tensor_product.is_scalar_tower_left TensorProduct.isScalarTower_left
variable [DistribMulAction R'₂ N] [DistribMulAction R' N]
variable [CompatibleSMul R R'₂ M N] [CompatibleSMul R R' M N]
/-- `IsScalarTower R'₂ R' N` implies `IsScalarTower R'₂ R' (M ⊗[R] N)` -/
instance isScalarTower_right [IsScalarTower R'₂ R' N] : IsScalarTower R'₂ R' (M ⊗[R] N) :=
⟨fun s r x =>
x.induction_on (by simp)
(fun m n => by rw [← tmul_smul, ← tmul_smul, ← tmul_smul, smul_assoc]) fun x y ihx ihy => by
rw [smul_add, smul_add, smul_add, ihx, ihy]⟩
#align tensor_product.is_scalar_tower_right TensorProduct.isScalarTower_right
end
/-- A short-cut instance for the common case, where the requirements for the `compatible_smul`
instances are sufficient. -/
instance isScalarTower [SMul R' R] [IsScalarTower R' R M] : IsScalarTower R' R (M ⊗[R] N) :=
TensorProduct.isScalarTower_left
#align tensor_product.is_scalar_tower TensorProduct.isScalarTower
-- or right
variable (R M N)
/-- The canonical bilinear map `M → N → M ⊗[R] N`. -/
def mk : M →ₗ[R] N →ₗ[R] M ⊗[R] N :=
LinearMap.mk₂ R (· ⊗ₜ ·) add_tmul (fun c m n => by simp_rw [smul_tmul, tmul_smul])
tmul_add tmul_smul
#align tensor_product.mk TensorProduct.mk
variable {R M N}
@[simp]
theorem mk_apply (m : M) (n : N) : mk R M N m n = m ⊗ₜ n :=
rfl
#align tensor_product.mk_apply TensorProduct.mk_apply
theorem ite_tmul (x₁ : M) (x₂ : N) (P : Prop) [Decidable P] :
(if P then x₁ else 0) ⊗ₜ[R] x₂ = if P then x₁ ⊗ₜ x₂ else 0 := by split_ifs <;> simp
#align tensor_product.ite_tmul TensorProduct.ite_tmul
| Mathlib/LinearAlgebra/TensorProduct/Basic.lean | 455 | 456 | theorem tmul_ite (x₁ : M) (x₂ : N) (P : Prop) [Decidable P] :
(x₁ ⊗ₜ[R] if P then x₂ else 0) = if P then x₁ ⊗ₜ x₂ else 0 := by | split_ifs <;> simp
|
/-
Copyright (c) 2020 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov, Patrick Massot, Eric Wieser, Yaël Dillies
-/
import Mathlib.Analysis.NormedSpace.Basic
import Mathlib.Topology.Algebra.Module.Basic
#align_import analysis.normed_space.basic from "leanprover-community/mathlib"@"bc91ed7093bf098d253401e69df601fc33dde156"
/-!
# Basic facts about real (semi)normed spaces
In this file we prove some theorems about (semi)normed spaces over real numberes.
## Main results
- `closure_ball`, `frontier_ball`, `interior_closedBall`, `frontier_closedBall`, `interior_sphere`,
`frontier_sphere`: formulas for the closure/interior/frontier
of nontrivial balls and spheres in a real seminormed space;
- `interior_closedBall'`, `frontier_closedBall'`, `interior_sphere'`, `frontier_sphere'`:
similar lemmas assuming that the ambient space is separated and nontrivial instead of `r ≠ 0`.
-/
open Metric Set Function Filter
open scoped NNReal Topology
/-- If `E` is a nontrivial topological module over `ℝ`, then `E` has no isolated points.
This is a particular case of `Module.punctured_nhds_neBot`. -/
instance Real.punctured_nhds_module_neBot {E : Type*} [AddCommGroup E] [TopologicalSpace E]
[ContinuousAdd E] [Nontrivial E] [Module ℝ E] [ContinuousSMul ℝ E] (x : E) : NeBot (𝓝[≠] x) :=
Module.punctured_nhds_neBot ℝ E x
#align real.punctured_nhds_module_ne_bot Real.punctured_nhds_module_neBot
section Seminormed
variable {E : Type*} [SeminormedAddCommGroup E] [NormedSpace ℝ E]
theorem inv_norm_smul_mem_closed_unit_ball (x : E) :
‖x‖⁻¹ • x ∈ closedBall (0 : E) 1 := by
simp only [mem_closedBall_zero_iff, norm_smul, norm_inv, norm_norm, ← div_eq_inv_mul,
div_self_le_one]
#align inv_norm_smul_mem_closed_unit_ball inv_norm_smul_mem_closed_unit_ball
theorem norm_smul_of_nonneg {t : ℝ} (ht : 0 ≤ t) (x : E) : ‖t • x‖ = t * ‖x‖ := by
rw [norm_smul, Real.norm_eq_abs, abs_of_nonneg ht]
#align norm_smul_of_nonneg norm_smul_of_nonneg
theorem dist_smul_add_one_sub_smul_le {r : ℝ} {x y : E} (h : r ∈ Icc 0 1) :
dist (r • x + (1 - r) • y) x ≤ dist y x :=
calc
dist (r • x + (1 - r) • y) x = ‖1 - r‖ * ‖x - y‖ := by
simp_rw [dist_eq_norm', ← norm_smul, sub_smul, one_smul, smul_sub, ← sub_sub, ← sub_add,
sub_right_comm]
_ = (1 - r) * dist y x := by
rw [Real.norm_eq_abs, abs_eq_self.mpr (sub_nonneg.mpr h.2), dist_eq_norm']
_ ≤ (1 - 0) * dist y x := by gcongr; exact h.1
_ = dist y x := by rw [sub_zero, one_mul]
theorem closure_ball (x : E) {r : ℝ} (hr : r ≠ 0) : closure (ball x r) = closedBall x r := by
refine Subset.antisymm closure_ball_subset_closedBall fun y hy => ?_
have : ContinuousWithinAt (fun c : ℝ => c • (y - x) + x) (Ico 0 1) 1 :=
((continuous_id.smul continuous_const).add continuous_const).continuousWithinAt
convert this.mem_closure _ _
· rw [one_smul, sub_add_cancel]
· simp [closure_Ico zero_ne_one, zero_le_one]
· rintro c ⟨hc0, hc1⟩
rw [mem_ball, dist_eq_norm, add_sub_cancel_right, norm_smul, Real.norm_eq_abs,
abs_of_nonneg hc0, mul_comm, ← mul_one r]
rw [mem_closedBall, dist_eq_norm] at hy
replace hr : 0 < r := ((norm_nonneg _).trans hy).lt_of_ne hr.symm
apply mul_lt_mul' <;> assumption
#align closure_ball closure_ball
theorem frontier_ball (x : E) {r : ℝ} (hr : r ≠ 0) :
frontier (ball x r) = sphere x r := by
rw [frontier, closure_ball x hr, isOpen_ball.interior_eq, closedBall_diff_ball]
#align frontier_ball frontier_ball
theorem interior_closedBall (x : E) {r : ℝ} (hr : r ≠ 0) :
interior (closedBall x r) = ball x r := by
cases' hr.lt_or_lt with hr hr
· rw [closedBall_eq_empty.2 hr, ball_eq_empty.2 hr.le, interior_empty]
refine Subset.antisymm ?_ ball_subset_interior_closedBall
intro y hy
rcases (mem_closedBall.1 <| interior_subset hy).lt_or_eq with (hr | rfl)
· exact hr
set f : ℝ → E := fun c : ℝ => c • (y - x) + x
suffices f ⁻¹' closedBall x (dist y x) ⊆ Icc (-1) 1 by
have hfc : Continuous f := (continuous_id.smul continuous_const).add continuous_const
have hf1 : (1 : ℝ) ∈ f ⁻¹' interior (closedBall x <| dist y x) := by simpa [f]
have h1 : (1 : ℝ) ∈ interior (Icc (-1 : ℝ) 1) :=
interior_mono this (preimage_interior_subset_interior_preimage hfc hf1)
simp at h1
intro c hc
rw [mem_Icc, ← abs_le, ← Real.norm_eq_abs, ← mul_le_mul_right hr]
simpa [f, dist_eq_norm, norm_smul] using hc
#align interior_closed_ball interior_closedBall
theorem frontier_closedBall (x : E) {r : ℝ} (hr : r ≠ 0) :
frontier (closedBall x r) = sphere x r := by
rw [frontier, closure_closedBall, interior_closedBall x hr, closedBall_diff_ball]
#align frontier_closed_ball frontier_closedBall
| Mathlib/Analysis/NormedSpace/Real.lean | 106 | 107 | theorem interior_sphere (x : E) {r : ℝ} (hr : r ≠ 0) : interior (sphere x r) = ∅ := by |
rw [← frontier_closedBall x hr, interior_frontier isClosed_ball]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Benjamin Davidson
-/
import Mathlib.Analysis.SpecialFunctions.Trigonometric.Angle
import Mathlib.Analysis.SpecialFunctions.Trigonometric.Inverse
#align_import analysis.special_functions.complex.arg from "leanprover-community/mathlib"@"2c1d8ca2812b64f88992a5294ea3dba144755cd1"
/-!
# The argument of a complex number.
We define `arg : ℂ → ℝ`, returning a real number in the range (-π, π],
such that for `x ≠ 0`, `sin (arg x) = x.im / x.abs` and `cos (arg x) = x.re / x.abs`,
while `arg 0` defaults to `0`
-/
open Filter Metric Set
open scoped ComplexConjugate Real Topology
namespace Complex
variable {a x z : ℂ}
/-- `arg` returns values in the range (-π, π], such that for `x ≠ 0`,
`sin (arg x) = x.im / x.abs` and `cos (arg x) = x.re / x.abs`,
`arg 0` defaults to `0` -/
noncomputable def arg (x : ℂ) : ℝ :=
if 0 ≤ x.re then Real.arcsin (x.im / abs x)
else if 0 ≤ x.im then Real.arcsin ((-x).im / abs x) + π else Real.arcsin ((-x).im / abs x) - π
#align complex.arg Complex.arg
theorem sin_arg (x : ℂ) : Real.sin (arg x) = x.im / abs x := by
unfold arg; split_ifs <;>
simp [sub_eq_add_neg, arg,
Real.sin_arcsin (abs_le.1 (abs_im_div_abs_le_one x)).1 (abs_le.1 (abs_im_div_abs_le_one x)).2,
Real.sin_add, neg_div, Real.arcsin_neg, Real.sin_neg]
#align complex.sin_arg Complex.sin_arg
theorem cos_arg {x : ℂ} (hx : x ≠ 0) : Real.cos (arg x) = x.re / abs x := by
rw [arg]
split_ifs with h₁ h₂
· rw [Real.cos_arcsin]
field_simp [Real.sqrt_sq, (abs.pos hx).le, *]
· rw [Real.cos_add_pi, Real.cos_arcsin]
field_simp [Real.sqrt_div (sq_nonneg _), Real.sqrt_sq_eq_abs,
_root_.abs_of_neg (not_le.1 h₁), *]
· rw [Real.cos_sub_pi, Real.cos_arcsin]
field_simp [Real.sqrt_div (sq_nonneg _), Real.sqrt_sq_eq_abs,
_root_.abs_of_neg (not_le.1 h₁), *]
#align complex.cos_arg Complex.cos_arg
@[simp]
theorem abs_mul_exp_arg_mul_I (x : ℂ) : ↑(abs x) * exp (arg x * I) = x := by
rcases eq_or_ne x 0 with (rfl | hx)
· simp
· have : abs x ≠ 0 := abs.ne_zero hx
apply Complex.ext <;> field_simp [sin_arg, cos_arg hx, this, mul_comm (abs x)]
set_option linter.uppercaseLean3 false in
#align complex.abs_mul_exp_arg_mul_I Complex.abs_mul_exp_arg_mul_I
@[simp]
theorem abs_mul_cos_add_sin_mul_I (x : ℂ) : (abs x * (cos (arg x) + sin (arg x) * I) : ℂ) = x := by
rw [← exp_mul_I, abs_mul_exp_arg_mul_I]
set_option linter.uppercaseLean3 false in
#align complex.abs_mul_cos_add_sin_mul_I Complex.abs_mul_cos_add_sin_mul_I
@[simp]
lemma abs_mul_cos_arg (x : ℂ) : abs x * Real.cos (arg x) = x.re := by
simpa [-abs_mul_cos_add_sin_mul_I] using congr_arg re (abs_mul_cos_add_sin_mul_I x)
@[simp]
lemma abs_mul_sin_arg (x : ℂ) : abs x * Real.sin (arg x) = x.im := by
simpa [-abs_mul_cos_add_sin_mul_I] using congr_arg im (abs_mul_cos_add_sin_mul_I x)
theorem abs_eq_one_iff (z : ℂ) : abs z = 1 ↔ ∃ θ : ℝ, exp (θ * I) = z := by
refine ⟨fun hz => ⟨arg z, ?_⟩, ?_⟩
· calc
exp (arg z * I) = abs z * exp (arg z * I) := by rw [hz, ofReal_one, one_mul]
_ = z := abs_mul_exp_arg_mul_I z
· rintro ⟨θ, rfl⟩
exact Complex.abs_exp_ofReal_mul_I θ
#align complex.abs_eq_one_iff Complex.abs_eq_one_iff
@[simp]
theorem range_exp_mul_I : (Set.range fun x : ℝ => exp (x * I)) = Metric.sphere 0 1 := by
ext x
simp only [mem_sphere_zero_iff_norm, norm_eq_abs, abs_eq_one_iff, Set.mem_range]
set_option linter.uppercaseLean3 false in
#align complex.range_exp_mul_I Complex.range_exp_mul_I
theorem arg_mul_cos_add_sin_mul_I {r : ℝ} (hr : 0 < r) {θ : ℝ} (hθ : θ ∈ Set.Ioc (-π) π) :
arg (r * (cos θ + sin θ * I)) = θ := by
simp only [arg, map_mul, abs_cos_add_sin_mul_I, abs_of_nonneg hr.le, mul_one]
simp only [re_ofReal_mul, im_ofReal_mul, neg_im, ← ofReal_cos, ← ofReal_sin, ←
mk_eq_add_mul_I, neg_div, mul_div_cancel_left₀ _ hr.ne', mul_nonneg_iff_right_nonneg_of_pos hr]
by_cases h₁ : θ ∈ Set.Icc (-(π / 2)) (π / 2)
· rw [if_pos]
exacts [Real.arcsin_sin' h₁, Real.cos_nonneg_of_mem_Icc h₁]
· rw [Set.mem_Icc, not_and_or, not_le, not_le] at h₁
cases' h₁ with h₁ h₁
· replace hθ := hθ.1
have hcos : Real.cos θ < 0 := by
rw [← neg_pos, ← Real.cos_add_pi]
refine Real.cos_pos_of_mem_Ioo ⟨?_, ?_⟩ <;> linarith
have hsin : Real.sin θ < 0 := Real.sin_neg_of_neg_of_neg_pi_lt (by linarith) hθ
rw [if_neg, if_neg, ← Real.sin_add_pi, Real.arcsin_sin, add_sub_cancel_right] <;> [linarith;
linarith; exact hsin.not_le; exact hcos.not_le]
· replace hθ := hθ.2
have hcos : Real.cos θ < 0 := Real.cos_neg_of_pi_div_two_lt_of_lt h₁ (by linarith)
have hsin : 0 ≤ Real.sin θ := Real.sin_nonneg_of_mem_Icc ⟨by linarith, hθ⟩
rw [if_neg, if_pos, ← Real.sin_sub_pi, Real.arcsin_sin, sub_add_cancel] <;> [linarith;
linarith; exact hsin; exact hcos.not_le]
set_option linter.uppercaseLean3 false in
#align complex.arg_mul_cos_add_sin_mul_I Complex.arg_mul_cos_add_sin_mul_I
theorem arg_cos_add_sin_mul_I {θ : ℝ} (hθ : θ ∈ Set.Ioc (-π) π) : arg (cos θ + sin θ * I) = θ := by
rw [← one_mul (_ + _), ← ofReal_one, arg_mul_cos_add_sin_mul_I zero_lt_one hθ]
set_option linter.uppercaseLean3 false in
#align complex.arg_cos_add_sin_mul_I Complex.arg_cos_add_sin_mul_I
lemma arg_exp_mul_I (θ : ℝ) :
arg (exp (θ * I)) = toIocMod (mul_pos two_pos Real.pi_pos) (-π) θ := by
convert arg_cos_add_sin_mul_I (θ := toIocMod (mul_pos two_pos Real.pi_pos) (-π) θ) _ using 2
· rw [← exp_mul_I, eq_sub_of_add_eq $ toIocMod_add_toIocDiv_zsmul _ _ θ, ofReal_sub,
ofReal_zsmul, ofReal_mul, ofReal_ofNat, exp_mul_I_periodic.sub_zsmul_eq]
· convert toIocMod_mem_Ioc _ _ _
ring
@[simp]
theorem arg_zero : arg 0 = 0 := by simp [arg, le_refl]
#align complex.arg_zero Complex.arg_zero
theorem ext_abs_arg {x y : ℂ} (h₁ : abs x = abs y) (h₂ : x.arg = y.arg) : x = y := by
rw [← abs_mul_exp_arg_mul_I x, ← abs_mul_exp_arg_mul_I y, h₁, h₂]
#align complex.ext_abs_arg Complex.ext_abs_arg
theorem ext_abs_arg_iff {x y : ℂ} : x = y ↔ abs x = abs y ∧ arg x = arg y :=
⟨fun h => h ▸ ⟨rfl, rfl⟩, and_imp.2 ext_abs_arg⟩
#align complex.ext_abs_arg_iff Complex.ext_abs_arg_iff
theorem arg_mem_Ioc (z : ℂ) : arg z ∈ Set.Ioc (-π) π := by
have hπ : 0 < π := Real.pi_pos
rcases eq_or_ne z 0 with (rfl | hz)
· simp [hπ, hπ.le]
rcases existsUnique_add_zsmul_mem_Ioc Real.two_pi_pos (arg z) (-π) with ⟨N, hN, -⟩
rw [two_mul, neg_add_cancel_left, ← two_mul, zsmul_eq_mul] at hN
rw [← abs_mul_cos_add_sin_mul_I z, ← cos_add_int_mul_two_pi _ N, ← sin_add_int_mul_two_pi _ N]
have := arg_mul_cos_add_sin_mul_I (abs.pos hz) hN
push_cast at this
rwa [this]
#align complex.arg_mem_Ioc Complex.arg_mem_Ioc
@[simp]
theorem range_arg : Set.range arg = Set.Ioc (-π) π :=
(Set.range_subset_iff.2 arg_mem_Ioc).antisymm fun _ hx => ⟨_, arg_cos_add_sin_mul_I hx⟩
#align complex.range_arg Complex.range_arg
theorem arg_le_pi (x : ℂ) : arg x ≤ π :=
(arg_mem_Ioc x).2
#align complex.arg_le_pi Complex.arg_le_pi
theorem neg_pi_lt_arg (x : ℂ) : -π < arg x :=
(arg_mem_Ioc x).1
#align complex.neg_pi_lt_arg Complex.neg_pi_lt_arg
theorem abs_arg_le_pi (z : ℂ) : |arg z| ≤ π :=
abs_le.2 ⟨(neg_pi_lt_arg z).le, arg_le_pi z⟩
#align complex.abs_arg_le_pi Complex.abs_arg_le_pi
@[simp]
theorem arg_nonneg_iff {z : ℂ} : 0 ≤ arg z ↔ 0 ≤ z.im := by
rcases eq_or_ne z 0 with (rfl | h₀); · simp
calc
0 ≤ arg z ↔ 0 ≤ Real.sin (arg z) :=
⟨fun h => Real.sin_nonneg_of_mem_Icc ⟨h, arg_le_pi z⟩, by
contrapose!
intro h
exact Real.sin_neg_of_neg_of_neg_pi_lt h (neg_pi_lt_arg _)⟩
_ ↔ _ := by rw [sin_arg, le_div_iff (abs.pos h₀), zero_mul]
#align complex.arg_nonneg_iff Complex.arg_nonneg_iff
@[simp]
theorem arg_neg_iff {z : ℂ} : arg z < 0 ↔ z.im < 0 :=
lt_iff_lt_of_le_iff_le arg_nonneg_iff
#align complex.arg_neg_iff Complex.arg_neg_iff
theorem arg_real_mul (x : ℂ) {r : ℝ} (hr : 0 < r) : arg (r * x) = arg x := by
rcases eq_or_ne x 0 with (rfl | hx); · rw [mul_zero]
conv_lhs =>
rw [← abs_mul_cos_add_sin_mul_I x, ← mul_assoc, ← ofReal_mul,
arg_mul_cos_add_sin_mul_I (mul_pos hr (abs.pos hx)) x.arg_mem_Ioc]
#align complex.arg_real_mul Complex.arg_real_mul
theorem arg_mul_real {r : ℝ} (hr : 0 < r) (x : ℂ) : arg (x * r) = arg x :=
mul_comm x r ▸ arg_real_mul x hr
theorem arg_eq_arg_iff {x y : ℂ} (hx : x ≠ 0) (hy : y ≠ 0) :
arg x = arg y ↔ (abs y / abs x : ℂ) * x = y := by
simp only [ext_abs_arg_iff, map_mul, map_div₀, abs_ofReal, abs_abs,
div_mul_cancel₀ _ (abs.ne_zero hx), eq_self_iff_true, true_and_iff]
rw [← ofReal_div, arg_real_mul]
exact div_pos (abs.pos hy) (abs.pos hx)
#align complex.arg_eq_arg_iff Complex.arg_eq_arg_iff
@[simp]
theorem arg_one : arg 1 = 0 := by simp [arg, zero_le_one]
#align complex.arg_one Complex.arg_one
@[simp]
| Mathlib/Analysis/SpecialFunctions/Complex/Arg.lean | 213 | 213 | theorem arg_neg_one : arg (-1) = π := by | simp [arg, le_refl, not_le.2 (zero_lt_one' ℝ)]
|
/-
Copyright (c) 2021 Adam Topaz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Adam Topaz
-/
import Mathlib.CategoryTheory.Limits.Shapes.Products
import Mathlib.CategoryTheory.Limits.Shapes.Equalizers
import Mathlib.CategoryTheory.Limits.ConeCategory
#align_import category_theory.limits.shapes.multiequalizer from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Multi-(co)equalizers
A *multiequalizer* is an equalizer of two morphisms between two products.
Since both products and equalizers are limits, such an object is again a limit.
This file provides the diagram whose limit is indeed such an object.
In fact, it is well-known that any limit can be obtained as a multiequalizer.
The dual construction (multicoequalizers) is also provided.
## Projects
Prove that a multiequalizer can be identified with
an equalizer between products (and analogously for multicoequalizers).
Prove that the limit of any diagram is a multiequalizer (and similarly for colimits).
-/
namespace CategoryTheory.Limits
open CategoryTheory
universe w v u
/-- The type underlying the multiequalizer diagram. -/
--@[nolint unused_arguments]
inductive WalkingMulticospan {L R : Type w} (fst snd : R → L) : Type w
| left : L → WalkingMulticospan fst snd
| right : R → WalkingMulticospan fst snd
#align category_theory.limits.walking_multicospan CategoryTheory.Limits.WalkingMulticospan
/-- The type underlying the multiecoqualizer diagram. -/
--@[nolint unused_arguments]
inductive WalkingMultispan {L R : Type w} (fst snd : L → R) : Type w
| left : L → WalkingMultispan fst snd
| right : R → WalkingMultispan fst snd
#align category_theory.limits.walking_multispan CategoryTheory.Limits.WalkingMultispan
namespace WalkingMulticospan
variable {L R : Type w} {fst snd : R → L}
instance [Inhabited L] : Inhabited (WalkingMulticospan fst snd) :=
⟨left default⟩
/-- Morphisms for `WalkingMulticospan`. -/
inductive Hom : ∀ _ _ : WalkingMulticospan fst snd, Type w
| id (A) : Hom A A
| fst (b) : Hom (left (fst b)) (right b)
| snd (b) : Hom (left (snd b)) (right b)
#align category_theory.limits.walking_multicospan.hom CategoryTheory.Limits.WalkingMulticospan.Hom
/- Porting note: simpNF says the LHS of this internal identifier simplifies
(which it does, using Hom.id_eq_id) -/
attribute [-simp, nolint simpNF] WalkingMulticospan.Hom.id.sizeOf_spec
instance {a : WalkingMulticospan fst snd} : Inhabited (Hom a a) :=
⟨Hom.id _⟩
/-- Composition of morphisms for `WalkingMulticospan`. -/
def Hom.comp : ∀ {A B C : WalkingMulticospan fst snd} (_ : Hom A B) (_ : Hom B C), Hom A C
| _, _, _, Hom.id X, f => f
| _, _, _, Hom.fst b, Hom.id _ => Hom.fst b
| _, _, _, Hom.snd b, Hom.id _ => Hom.snd b
#align category_theory.limits.walking_multicospan.hom.comp CategoryTheory.Limits.WalkingMulticospan.Hom.comp
instance : SmallCategory (WalkingMulticospan fst snd) where
Hom := Hom
id := Hom.id
comp := Hom.comp
id_comp := by
rintro (_ | _) (_ | _) (_ | _ | _) <;> rfl
comp_id := by
rintro (_ | _) (_ | _) (_ | _ | _) <;> rfl
assoc := by
rintro (_ | _) (_ | _) (_ | _) (_ | _) (_ | _ | _) (_ | _ | _) (_ | _ | _) <;> rfl
@[simp] -- Porting note (#10756): added simp lemma
lemma Hom.id_eq_id (X : WalkingMulticospan fst snd) :
Hom.id X = 𝟙 X := rfl
@[simp] -- Porting note (#10756): added simp lemma
lemma Hom.comp_eq_comp {X Y Z : WalkingMulticospan fst snd}
(f : X ⟶ Y) (g : Y ⟶ Z) : Hom.comp f g = f ≫ g := rfl
end WalkingMulticospan
namespace WalkingMultispan
variable {L R : Type v} {fst snd : L → R}
instance [Inhabited L] : Inhabited (WalkingMultispan fst snd) :=
⟨left default⟩
/-- Morphisms for `WalkingMultispan`. -/
inductive Hom : ∀ _ _ : WalkingMultispan fst snd, Type v
| id (A) : Hom A A
| fst (a) : Hom (left a) (right (fst a))
| snd (a) : Hom (left a) (right (snd a))
#align category_theory.limits.walking_multispan.hom CategoryTheory.Limits.WalkingMultispan.Hom
/- Porting note: simpNF says the LHS of this internal identifier simplifies
(which it does, using Hom.id_eq_id) -/
attribute [-simp, nolint simpNF] WalkingMultispan.Hom.id.sizeOf_spec
instance {a : WalkingMultispan fst snd} : Inhabited (Hom a a) :=
⟨Hom.id _⟩
/-- Composition of morphisms for `WalkingMultispan`. -/
def Hom.comp : ∀ {A B C : WalkingMultispan fst snd} (_ : Hom A B) (_ : Hom B C), Hom A C
| _, _, _, Hom.id X, f => f
| _, _, _, Hom.fst a, Hom.id _ => Hom.fst a
| _, _, _, Hom.snd a, Hom.id _ => Hom.snd a
#align category_theory.limits.walking_multispan.hom.comp CategoryTheory.Limits.WalkingMultispan.Hom.comp
instance : SmallCategory (WalkingMultispan fst snd) where
Hom := Hom
id := Hom.id
comp := Hom.comp
id_comp := by
rintro (_ | _) (_ | _) (_ | _ | _) <;> rfl
comp_id := by
rintro (_ | _) (_ | _) (_ | _ | _) <;> rfl
assoc := by
rintro (_ | _) (_ | _) (_ | _) (_ | _) (_ | _ | _) (_ | _ | _) (_ | _ | _) <;> rfl
@[simp] -- Porting note (#10756): added simp lemma
lemma Hom.id_eq_id (X : WalkingMultispan fst snd) : Hom.id X = 𝟙 X := rfl
@[simp] -- Porting note (#10756): added simp lemma
lemma Hom.comp_eq_comp {X Y Z : WalkingMultispan fst snd}
(f : X ⟶ Y) (g : Y ⟶ Z) : Hom.comp f g = f ≫ g := rfl
end WalkingMultispan
/-- This is a structure encapsulating the data necessary to define a `Multicospan`. -/
-- Porting note(#5171): linter not ported yet
-- @[nolint has_nonempty_instance]
structure MulticospanIndex (C : Type u) [Category.{v} C] where
(L R : Type w)
(fstTo sndTo : R → L)
left : L → C
right : R → C
fst : ∀ b, left (fstTo b) ⟶ right b
snd : ∀ b, left (sndTo b) ⟶ right b
#align category_theory.limits.multicospan_index CategoryTheory.Limits.MulticospanIndex
/-- This is a structure encapsulating the data necessary to define a `Multispan`. -/
-- Porting note(#5171): linter not ported yet
-- @[nolint has_nonempty_instance]
structure MultispanIndex (C : Type u) [Category.{v} C] where
(L R : Type w)
(fstFrom sndFrom : L → R)
left : L → C
right : R → C
fst : ∀ a, left a ⟶ right (fstFrom a)
snd : ∀ a, left a ⟶ right (sndFrom a)
#align category_theory.limits.multispan_index CategoryTheory.Limits.MultispanIndex
namespace MulticospanIndex
variable {C : Type u} [Category.{v} C] (I : MulticospanIndex.{w} C)
/-- The multicospan associated to `I : MulticospanIndex`. -/
def multicospan : WalkingMulticospan I.fstTo I.sndTo ⥤ C where
obj x :=
match x with
| WalkingMulticospan.left a => I.left a
| WalkingMulticospan.right b => I.right b
map {x y} f :=
match x, y, f with
| _, _, WalkingMulticospan.Hom.id x => 𝟙 _
| _, _, WalkingMulticospan.Hom.fst b => I.fst _
| _, _, WalkingMulticospan.Hom.snd b => I.snd _
map_id := by
rintro (_ | _) <;> rfl
map_comp := by
rintro (_ | _) (_ | _) (_ | _) (_ | _ | _) (_ | _ | _) <;> aesop_cat
#align category_theory.limits.multicospan_index.multicospan CategoryTheory.Limits.MulticospanIndex.multicospan
@[simp]
theorem multicospan_obj_left (a) : I.multicospan.obj (WalkingMulticospan.left a) = I.left a :=
rfl
#align category_theory.limits.multicospan_index.multicospan_obj_left CategoryTheory.Limits.MulticospanIndex.multicospan_obj_left
@[simp]
theorem multicospan_obj_right (b) : I.multicospan.obj (WalkingMulticospan.right b) = I.right b :=
rfl
#align category_theory.limits.multicospan_index.multicospan_obj_right CategoryTheory.Limits.MulticospanIndex.multicospan_obj_right
@[simp]
theorem multicospan_map_fst (b) : I.multicospan.map (WalkingMulticospan.Hom.fst b) = I.fst b :=
rfl
#align category_theory.limits.multicospan_index.multicospan_map_fst CategoryTheory.Limits.MulticospanIndex.multicospan_map_fst
@[simp]
theorem multicospan_map_snd (b) : I.multicospan.map (WalkingMulticospan.Hom.snd b) = I.snd b :=
rfl
#align category_theory.limits.multicospan_index.multicospan_map_snd CategoryTheory.Limits.MulticospanIndex.multicospan_map_snd
variable [HasProduct I.left] [HasProduct I.right]
/-- The induced map `∏ᶜ I.left ⟶ ∏ᶜ I.right` via `I.fst`. -/
noncomputable def fstPiMap : ∏ᶜ I.left ⟶ ∏ᶜ I.right :=
Pi.lift fun b => Pi.π I.left (I.fstTo b) ≫ I.fst b
#align category_theory.limits.multicospan_index.fst_pi_map CategoryTheory.Limits.MulticospanIndex.fstPiMap
/-- The induced map `∏ᶜ I.left ⟶ ∏ᶜ I.right` via `I.snd`. -/
noncomputable def sndPiMap : ∏ᶜ I.left ⟶ ∏ᶜ I.right :=
Pi.lift fun b => Pi.π I.left (I.sndTo b) ≫ I.snd b
#align category_theory.limits.multicospan_index.snd_pi_map CategoryTheory.Limits.MulticospanIndex.sndPiMap
@[reassoc (attr := simp)]
theorem fstPiMap_π (b) : I.fstPiMap ≫ Pi.π I.right b = Pi.π I.left _ ≫ I.fst b := by
simp [fstPiMap]
#align category_theory.limits.multicospan_index.fst_pi_map_π CategoryTheory.Limits.MulticospanIndex.fstPiMap_π
@[reassoc (attr := simp)]
theorem sndPiMap_π (b) : I.sndPiMap ≫ Pi.π I.right b = Pi.π I.left _ ≫ I.snd b := by
simp [sndPiMap]
#align category_theory.limits.multicospan_index.snd_pi_map_π CategoryTheory.Limits.MulticospanIndex.sndPiMap_π
/-- Taking the multiequalizer over the multicospan index is equivalent to taking the equalizer over
the two morphisms `∏ᶜ I.left ⇉ ∏ᶜ I.right`. This is the diagram of the latter.
-/
@[simps!]
protected noncomputable def parallelPairDiagram :=
parallelPair I.fstPiMap I.sndPiMap
#align category_theory.limits.multicospan_index.parallel_pair_diagram CategoryTheory.Limits.MulticospanIndex.parallelPairDiagram
end MulticospanIndex
namespace MultispanIndex
variable {C : Type u} [Category.{v} C] (I : MultispanIndex.{w} C)
/-- The multispan associated to `I : MultispanIndex`. -/
def multispan : WalkingMultispan I.fstFrom I.sndFrom ⥤ C where
obj x :=
match x with
| WalkingMultispan.left a => I.left a
| WalkingMultispan.right b => I.right b
map {x y} f :=
match x, y, f with
| _, _, WalkingMultispan.Hom.id x => 𝟙 _
| _, _, WalkingMultispan.Hom.fst b => I.fst _
| _, _, WalkingMultispan.Hom.snd b => I.snd _
map_id := by
rintro (_ | _) <;> rfl
map_comp := by
rintro (_ | _) (_ | _) (_ | _) (_ | _ | _) (_ | _ | _) <;> aesop_cat
#align category_theory.limits.multispan_index.multispan CategoryTheory.Limits.MultispanIndex.multispan
@[simp]
theorem multispan_obj_left (a) : I.multispan.obj (WalkingMultispan.left a) = I.left a :=
rfl
#align category_theory.limits.multispan_index.multispan_obj_left CategoryTheory.Limits.MultispanIndex.multispan_obj_left
@[simp]
theorem multispan_obj_right (b) : I.multispan.obj (WalkingMultispan.right b) = I.right b :=
rfl
#align category_theory.limits.multispan_index.multispan_obj_right CategoryTheory.Limits.MultispanIndex.multispan_obj_right
@[simp]
theorem multispan_map_fst (a) : I.multispan.map (WalkingMultispan.Hom.fst a) = I.fst a :=
rfl
#align category_theory.limits.multispan_index.multispan_map_fst CategoryTheory.Limits.MultispanIndex.multispan_map_fst
@[simp]
theorem multispan_map_snd (a) : I.multispan.map (WalkingMultispan.Hom.snd a) = I.snd a :=
rfl
#align category_theory.limits.multispan_index.multispan_map_snd CategoryTheory.Limits.MultispanIndex.multispan_map_snd
variable [HasCoproduct I.left] [HasCoproduct I.right]
/-- The induced map `∐ I.left ⟶ ∐ I.right` via `I.fst`. -/
noncomputable def fstSigmaMap : ∐ I.left ⟶ ∐ I.right :=
Sigma.desc fun b => I.fst b ≫ Sigma.ι _ (I.fstFrom b)
#align category_theory.limits.multispan_index.fst_sigma_map CategoryTheory.Limits.MultispanIndex.fstSigmaMap
/-- The induced map `∐ I.left ⟶ ∐ I.right` via `I.snd`. -/
noncomputable def sndSigmaMap : ∐ I.left ⟶ ∐ I.right :=
Sigma.desc fun b => I.snd b ≫ Sigma.ι _ (I.sndFrom b)
#align category_theory.limits.multispan_index.snd_sigma_map CategoryTheory.Limits.MultispanIndex.sndSigmaMap
@[reassoc (attr := simp)]
theorem ι_fstSigmaMap (b) : Sigma.ι I.left b ≫ I.fstSigmaMap = I.fst b ≫ Sigma.ι I.right _ := by
simp [fstSigmaMap]
#align category_theory.limits.multispan_index.ι_fst_sigma_map CategoryTheory.Limits.MultispanIndex.ι_fstSigmaMap
@[reassoc (attr := simp)]
theorem ι_sndSigmaMap (b) : Sigma.ι I.left b ≫ I.sndSigmaMap = I.snd b ≫ Sigma.ι I.right _ := by
simp [sndSigmaMap]
#align category_theory.limits.multispan_index.ι_snd_sigma_map CategoryTheory.Limits.MultispanIndex.ι_sndSigmaMap
/--
Taking the multicoequalizer over the multispan index is equivalent to taking the coequalizer over
the two morphsims `∐ I.left ⇉ ∐ I.right`. This is the diagram of the latter.
-/
protected noncomputable abbrev parallelPairDiagram :=
parallelPair I.fstSigmaMap I.sndSigmaMap
#align category_theory.limits.multispan_index.parallel_pair_diagram CategoryTheory.Limits.MultispanIndex.parallelPairDiagram
end MultispanIndex
variable {C : Type u} [Category.{v} C]
/-- A multifork is a cone over a multicospan. -/
-- Porting note(#5171): linter not ported yet
-- @[nolint has_nonempty_instance]
abbrev Multifork (I : MulticospanIndex.{w} C) :=
Cone I.multicospan
#align category_theory.limits.multifork CategoryTheory.Limits.Multifork
/-- A multicofork is a cocone over a multispan. -/
-- Porting note(#5171): linter not ported yet
-- @[nolint has_nonempty_instance]
abbrev Multicofork (I : MultispanIndex.{w} C) :=
Cocone I.multispan
#align category_theory.limits.multicofork CategoryTheory.Limits.Multicofork
namespace Multifork
variable {I : MulticospanIndex.{w} C} (K : Multifork I)
/-- The maps from the cone point of a multifork to the objects on the left. -/
def ι (a : I.L) : K.pt ⟶ I.left a :=
K.π.app (WalkingMulticospan.left _)
#align category_theory.limits.multifork.ι CategoryTheory.Limits.Multifork.ι
@[simp]
theorem app_left_eq_ι (a) : K.π.app (WalkingMulticospan.left a) = K.ι a :=
rfl
#align category_theory.limits.multifork.app_left_eq_ι CategoryTheory.Limits.Multifork.app_left_eq_ι
@[simp]
| Mathlib/CategoryTheory/Limits/Shapes/Multiequalizer.lean | 350 | 353 | theorem app_right_eq_ι_comp_fst (b) :
K.π.app (WalkingMulticospan.right b) = K.ι (I.fstTo b) ≫ I.fst b := by |
rw [← K.w (WalkingMulticospan.Hom.fst b)]
rfl
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.Algebra.Order.BigOperators.Group.Finset
import Mathlib.Data.Finset.Sort
import Mathlib.Data.Set.Subsingleton
#align_import combinatorics.composition from "leanprover-community/mathlib"@"92ca63f0fb391a9ca5f22d2409a6080e786d99f7"
/-!
# Compositions
A composition of a natural number `n` is a decomposition `n = i₀ + ... + i_{k-1}` of `n` into a sum
of positive integers. Combinatorially, it corresponds to a decomposition of `{0, ..., n-1}` into
non-empty blocks of consecutive integers, where the `iⱼ` are the lengths of the blocks.
This notion is closely related to that of a partition of `n`, but in a composition of `n` the
order of the `iⱼ`s matters.
We implement two different structures covering these two viewpoints on compositions. The first
one, made of a list of positive integers summing to `n`, is the main one and is called
`Composition n`. The second one is useful for combinatorial arguments (for instance to show that
the number of compositions of `n` is `2^(n-1)`). It is given by a subset of `{0, ..., n}`
containing `0` and `n`, where the elements of the subset (other than `n`) correspond to the leftmost
points of each block. The main API is built on `Composition n`, and we provide an equivalence
between the two types.
## Main functions
* `c : Composition n` is a structure, made of a list of integers which are all positive and
add up to `n`.
* `composition_card` states that the cardinality of `Composition n` is exactly
`2^(n-1)`, which is proved by constructing an equiv with `CompositionAsSet n` (see below), which
is itself in bijection with the subsets of `Fin (n-1)` (this holds even for `n = 0`, where `-` is
nat subtraction).
Let `c : Composition n` be a composition of `n`. Then
* `c.blocks` is the list of blocks in `c`.
* `c.length` is the number of blocks in the composition.
* `c.blocks_fun : Fin c.length → ℕ` is the realization of `c.blocks` as a function on
`Fin c.length`. This is the main object when using compositions to understand the composition of
analytic functions.
* `c.sizeUpTo : ℕ → ℕ` is the sum of the size of the blocks up to `i`.;
* `c.embedding i : Fin (c.blocks_fun i) → Fin n` is the increasing embedding of the `i`-th block in
`Fin n`;
* `c.index j`, for `j : Fin n`, is the index of the block containing `j`.
* `Composition.ones n` is the composition of `n` made of ones, i.e., `[1, ..., 1]`.
* `Composition.single n (hn : 0 < n)` is the composition of `n` made of a single block of size `n`.
Compositions can also be used to split lists. Let `l` be a list of length `n` and `c` a composition
of `n`.
* `l.splitWrtComposition c` is a list of lists, made of the slices of `l` corresponding to the
blocks of `c`.
* `join_splitWrtComposition` states that splitting a list and then joining it gives back the
original list.
* `joinSplitWrtComposition_join` states that joining a list of lists, and then splitting it back
according to the right composition, gives back the original list of lists.
We turn to the second viewpoint on compositions, that we realize as a finset of `Fin (n+1)`.
`c : CompositionAsSet n` is a structure made of a finset of `Fin (n+1)` called `c.boundaries`
and proofs that it contains `0` and `n`. (Taking a finset of `Fin n` containing `0` would not
make sense in the edge case `n = 0`, while the previous description works in all cases).
The elements of this set (other than `n`) correspond to leftmost points of blocks.
Thus, there is an equiv between `Composition n` and `CompositionAsSet n`. We
only construct basic API on `CompositionAsSet` (notably `c.length` and `c.blocks`) to be able
to construct this equiv, called `compositionEquiv n`. Since there is a straightforward equiv
between `CompositionAsSet n` and finsets of `{1, ..., n-1}` (obtained by removing `0` and `n`
from a `CompositionAsSet` and called `compositionAsSetEquiv n`), we deduce that
`CompositionAsSet n` and `Composition n` are both fintypes of cardinality `2^(n - 1)`
(see `compositionAsSet_card` and `composition_card`).
## Implementation details
The main motivation for this structure and its API is in the construction of the composition of
formal multilinear series, and the proof that the composition of analytic functions is analytic.
The representation of a composition as a list is very handy as lists are very flexible and already
have a well-developed API.
## Tags
Composition, partition
## References
<https://en.wikipedia.org/wiki/Composition_(combinatorics)>
-/
open List
variable {n : ℕ}
/-- A composition of `n` is a list of positive integers summing to `n`. -/
@[ext]
structure Composition (n : ℕ) where
/-- List of positive integers summing to `n`-/
blocks : List ℕ
/-- Proof of positivity for `blocks`-/
blocks_pos : ∀ {i}, i ∈ blocks → 0 < i
/-- Proof that `blocks` sums to `n`-/
blocks_sum : blocks.sum = n
#align composition Composition
/-- Combinatorial viewpoint on a composition of `n`, by seeing it as non-empty blocks of
consecutive integers in `{0, ..., n-1}`. We register every block by its left end-point, yielding
a finset containing `0`. As this does not make sense for `n = 0`, we add `n` to this finset, and
get a finset of `{0, ..., n}` containing `0` and `n`. This is the data in the structure
`CompositionAsSet n`. -/
@[ext]
structure CompositionAsSet (n : ℕ) where
/-- Combinatorial viewpoint on a composition of `n` as consecutive integers `{0, ..., n-1}`-/
boundaries : Finset (Fin n.succ)
/-- Proof that `0` is a member of `boundaries`-/
zero_mem : (0 : Fin n.succ) ∈ boundaries
/-- Last element of the composition-/
getLast_mem : Fin.last n ∈ boundaries
#align composition_as_set CompositionAsSet
instance {n : ℕ} : Inhabited (CompositionAsSet n) :=
⟨⟨Finset.univ, Finset.mem_univ _, Finset.mem_univ _⟩⟩
/-!
### Compositions
A composition of an integer `n` is a decomposition `n = i₀ + ... + i_{k-1}` of `n` into a sum of
positive integers.
-/
namespace Composition
variable (c : Composition n)
instance (n : ℕ) : ToString (Composition n) :=
⟨fun c => toString c.blocks⟩
/-- The length of a composition, i.e., the number of blocks in the composition. -/
abbrev length : ℕ :=
c.blocks.length
#align composition.length Composition.length
theorem blocks_length : c.blocks.length = c.length :=
rfl
#align composition.blocks_length Composition.blocks_length
/-- The blocks of a composition, seen as a function on `Fin c.length`. When composing analytic
functions using compositions, this is the main player. -/
def blocksFun : Fin c.length → ℕ := c.blocks.get
#align composition.blocks_fun Composition.blocksFun
theorem ofFn_blocksFun : ofFn c.blocksFun = c.blocks :=
ofFn_get _
#align composition.of_fn_blocks_fun Composition.ofFn_blocksFun
theorem sum_blocksFun : ∑ i, c.blocksFun i = n := by
conv_rhs => rw [← c.blocks_sum, ← ofFn_blocksFun, sum_ofFn]
#align composition.sum_blocks_fun Composition.sum_blocksFun
theorem blocksFun_mem_blocks (i : Fin c.length) : c.blocksFun i ∈ c.blocks :=
get_mem _ _ _
#align composition.blocks_fun_mem_blocks Composition.blocksFun_mem_blocks
@[simp]
theorem one_le_blocks {i : ℕ} (h : i ∈ c.blocks) : 1 ≤ i :=
c.blocks_pos h
#align composition.one_le_blocks Composition.one_le_blocks
@[simp]
theorem one_le_blocks' {i : ℕ} (h : i < c.length) : 1 ≤ c.blocks.get ⟨i, h⟩ :=
c.one_le_blocks (get_mem (blocks c) i h)
#align composition.one_le_blocks' Composition.one_le_blocks'
@[simp]
theorem blocks_pos' (i : ℕ) (h : i < c.length) : 0 < c.blocks.get ⟨i, h⟩ :=
c.one_le_blocks' h
#align composition.blocks_pos' Composition.blocks_pos'
theorem one_le_blocksFun (i : Fin c.length) : 1 ≤ c.blocksFun i :=
c.one_le_blocks (c.blocksFun_mem_blocks i)
#align composition.one_le_blocks_fun Composition.one_le_blocksFun
theorem length_le : c.length ≤ n := by
conv_rhs => rw [← c.blocks_sum]
exact length_le_sum_of_one_le _ fun i hi => c.one_le_blocks hi
#align composition.length_le Composition.length_le
theorem length_pos_of_pos (h : 0 < n) : 0 < c.length := by
apply length_pos_of_sum_pos
convert h
exact c.blocks_sum
#align composition.length_pos_of_pos Composition.length_pos_of_pos
/-- The sum of the sizes of the blocks in a composition up to `i`. -/
def sizeUpTo (i : ℕ) : ℕ :=
(c.blocks.take i).sum
#align composition.size_up_to Composition.sizeUpTo
@[simp]
theorem sizeUpTo_zero : c.sizeUpTo 0 = 0 := by simp [sizeUpTo]
#align composition.size_up_to_zero Composition.sizeUpTo_zero
theorem sizeUpTo_ofLength_le (i : ℕ) (h : c.length ≤ i) : c.sizeUpTo i = n := by
dsimp [sizeUpTo]
convert c.blocks_sum
exact take_all_of_le h
#align composition.size_up_to_of_length_le Composition.sizeUpTo_ofLength_le
@[simp]
theorem sizeUpTo_length : c.sizeUpTo c.length = n :=
c.sizeUpTo_ofLength_le c.length le_rfl
#align composition.size_up_to_length Composition.sizeUpTo_length
theorem sizeUpTo_le (i : ℕ) : c.sizeUpTo i ≤ n := by
conv_rhs => rw [← c.blocks_sum, ← sum_take_add_sum_drop _ i]
exact Nat.le_add_right _ _
#align composition.size_up_to_le Composition.sizeUpTo_le
theorem sizeUpTo_succ {i : ℕ} (h : i < c.length) :
c.sizeUpTo (i + 1) = c.sizeUpTo i + c.blocks.get ⟨i, h⟩ := by
simp only [sizeUpTo]
rw [sum_take_succ _ _ h]
#align composition.size_up_to_succ Composition.sizeUpTo_succ
theorem sizeUpTo_succ' (i : Fin c.length) :
c.sizeUpTo ((i : ℕ) + 1) = c.sizeUpTo i + c.blocksFun i :=
c.sizeUpTo_succ i.2
#align composition.size_up_to_succ' Composition.sizeUpTo_succ'
theorem sizeUpTo_strict_mono {i : ℕ} (h : i < c.length) : c.sizeUpTo i < c.sizeUpTo (i + 1) := by
rw [c.sizeUpTo_succ h]
simp
#align composition.size_up_to_strict_mono Composition.sizeUpTo_strict_mono
theorem monotone_sizeUpTo : Monotone c.sizeUpTo :=
monotone_sum_take _
#align composition.monotone_size_up_to Composition.monotone_sizeUpTo
/-- The `i`-th boundary of a composition, i.e., the leftmost point of the `i`-th block. We include
a virtual point at the right of the last block, to make for a nice equiv with
`CompositionAsSet n`. -/
def boundary : Fin (c.length + 1) ↪o Fin (n + 1) :=
(OrderEmbedding.ofStrictMono fun i => ⟨c.sizeUpTo i, Nat.lt_succ_of_le (c.sizeUpTo_le i)⟩) <|
Fin.strictMono_iff_lt_succ.2 fun ⟨_, hi⟩ => c.sizeUpTo_strict_mono hi
#align composition.boundary Composition.boundary
@[simp]
theorem boundary_zero : c.boundary 0 = 0 := by simp [boundary, Fin.ext_iff]
#align composition.boundary_zero Composition.boundary_zero
@[simp]
theorem boundary_last : c.boundary (Fin.last c.length) = Fin.last n := by
simp [boundary, Fin.ext_iff]
#align composition.boundary_last Composition.boundary_last
/-- The boundaries of a composition, i.e., the leftmost point of all the blocks. We include
a virtual point at the right of the last block, to make for a nice equiv with
`CompositionAsSet n`. -/
def boundaries : Finset (Fin (n + 1)) :=
Finset.univ.map c.boundary.toEmbedding
#align composition.boundaries Composition.boundaries
theorem card_boundaries_eq_succ_length : c.boundaries.card = c.length + 1 := by simp [boundaries]
#align composition.card_boundaries_eq_succ_length Composition.card_boundaries_eq_succ_length
/-- To `c : Composition n`, one can associate a `CompositionAsSet n` by registering the leftmost
point of each block, and adding a virtual point at the right of the last block. -/
def toCompositionAsSet : CompositionAsSet n where
boundaries := c.boundaries
zero_mem := by
simp only [boundaries, Finset.mem_univ, exists_prop_of_true, Finset.mem_map]
exact ⟨0, And.intro True.intro rfl⟩
getLast_mem := by
simp only [boundaries, Finset.mem_univ, exists_prop_of_true, Finset.mem_map]
exact ⟨Fin.last c.length, And.intro True.intro c.boundary_last⟩
#align composition.to_composition_as_set Composition.toCompositionAsSet
/-- The canonical increasing bijection between `Fin (c.length + 1)` and `c.boundaries` is
exactly `c.boundary`. -/
theorem orderEmbOfFin_boundaries :
c.boundaries.orderEmbOfFin c.card_boundaries_eq_succ_length = c.boundary := by
refine (Finset.orderEmbOfFin_unique' _ ?_).symm
exact fun i => (Finset.mem_map' _).2 (Finset.mem_univ _)
#align composition.order_emb_of_fin_boundaries Composition.orderEmbOfFin_boundaries
/-- Embedding the `i`-th block of a composition (identified with `Fin (c.blocks_fun i)`) into
`Fin n` at the relevant position. -/
def embedding (i : Fin c.length) : Fin (c.blocksFun i) ↪o Fin n :=
(Fin.natAddOrderEmb <| c.sizeUpTo i).trans <| Fin.castLEOrderEmb <|
calc
c.sizeUpTo i + c.blocksFun i = c.sizeUpTo (i + 1) := (c.sizeUpTo_succ _).symm
_ ≤ c.sizeUpTo c.length := monotone_sum_take _ i.2
_ = n := c.sizeUpTo_length
#align composition.embedding Composition.embedding
@[simp]
theorem coe_embedding (i : Fin c.length) (j : Fin (c.blocksFun i)) :
(c.embedding i j : ℕ) = c.sizeUpTo i + j :=
rfl
#align composition.coe_embedding Composition.coe_embedding
/-- `index_exists` asserts there is some `i` with `j < c.size_up_to (i+1)`.
In the next definition `index` we use `Nat.find` to produce the minimal such index.
-/
theorem index_exists {j : ℕ} (h : j < n) : ∃ i : ℕ, j < c.sizeUpTo (i + 1) ∧ i < c.length := by
have n_pos : 0 < n := lt_of_le_of_lt (zero_le j) h
have : 0 < c.blocks.sum := by rwa [← c.blocks_sum] at n_pos
have length_pos : 0 < c.blocks.length := length_pos_of_sum_pos (blocks c) this
refine ⟨c.length - 1, ?_, Nat.pred_lt (ne_of_gt length_pos)⟩
have : c.length - 1 + 1 = c.length := Nat.succ_pred_eq_of_pos length_pos
simp [this, h]
#align composition.index_exists Composition.index_exists
/-- `c.index j` is the index of the block in the composition `c` containing `j`. -/
def index (j : Fin n) : Fin c.length :=
⟨Nat.find (c.index_exists j.2), (Nat.find_spec (c.index_exists j.2)).2⟩
#align composition.index Composition.index
theorem lt_sizeUpTo_index_succ (j : Fin n) : (j : ℕ) < c.sizeUpTo (c.index j).succ :=
(Nat.find_spec (c.index_exists j.2)).1
#align composition.lt_size_up_to_index_succ Composition.lt_sizeUpTo_index_succ
theorem sizeUpTo_index_le (j : Fin n) : c.sizeUpTo (c.index j) ≤ j := by
by_contra H
set i := c.index j
push_neg at H
have i_pos : (0 : ℕ) < i := by
by_contra! i_pos
revert H
simp [nonpos_iff_eq_zero.1 i_pos, c.sizeUpTo_zero]
let i₁ := (i : ℕ).pred
have i₁_lt_i : i₁ < i := Nat.pred_lt (ne_of_gt i_pos)
have i₁_succ : i₁ + 1 = i := Nat.succ_pred_eq_of_pos i_pos
have := Nat.find_min (c.index_exists j.2) i₁_lt_i
simp [lt_trans i₁_lt_i (c.index j).2, i₁_succ] at this
exact Nat.lt_le_asymm H this
#align composition.size_up_to_index_le Composition.sizeUpTo_index_le
/-- Mapping an element `j` of `Fin n` to the element in the block containing it, identified with
`Fin (c.blocks_fun (c.index j))` through the canonical increasing bijection. -/
def invEmbedding (j : Fin n) : Fin (c.blocksFun (c.index j)) :=
⟨j - c.sizeUpTo (c.index j), by
rw [tsub_lt_iff_right, add_comm, ← sizeUpTo_succ']
· exact lt_sizeUpTo_index_succ _ _
· exact sizeUpTo_index_le _ _⟩
#align composition.inv_embedding Composition.invEmbedding
@[simp]
theorem coe_invEmbedding (j : Fin n) : (c.invEmbedding j : ℕ) = j - c.sizeUpTo (c.index j) :=
rfl
#align composition.coe_inv_embedding Composition.coe_invEmbedding
theorem embedding_comp_inv (j : Fin n) : c.embedding (c.index j) (c.invEmbedding j) = j := by
rw [Fin.ext_iff]
apply add_tsub_cancel_of_le (c.sizeUpTo_index_le j)
#align composition.embedding_comp_inv Composition.embedding_comp_inv
theorem mem_range_embedding_iff {j : Fin n} {i : Fin c.length} :
j ∈ Set.range (c.embedding i) ↔ c.sizeUpTo i ≤ j ∧ (j : ℕ) < c.sizeUpTo (i : ℕ).succ := by
constructor
· intro h
rcases Set.mem_range.2 h with ⟨k, hk⟩
rw [Fin.ext_iff] at hk
dsimp at hk
rw [← hk]
simp [sizeUpTo_succ', k.is_lt]
· intro h
apply Set.mem_range.2
refine ⟨⟨j - c.sizeUpTo i, ?_⟩, ?_⟩
· rw [tsub_lt_iff_left, ← sizeUpTo_succ']
· exact h.2
· exact h.1
· rw [Fin.ext_iff]
exact add_tsub_cancel_of_le h.1
#align composition.mem_range_embedding_iff Composition.mem_range_embedding_iff
/-- The embeddings of different blocks of a composition are disjoint. -/
theorem disjoint_range {i₁ i₂ : Fin c.length} (h : i₁ ≠ i₂) :
Disjoint (Set.range (c.embedding i₁)) (Set.range (c.embedding i₂)) := by
classical
wlog h' : i₁ < i₂
· exact (this c h.symm (h.lt_or_lt.resolve_left h')).symm
by_contra d
obtain ⟨x, hx₁, hx₂⟩ :
∃ x : Fin n, x ∈ Set.range (c.embedding i₁) ∧ x ∈ Set.range (c.embedding i₂) :=
Set.not_disjoint_iff.1 d
have A : (i₁ : ℕ).succ ≤ i₂ := Nat.succ_le_of_lt h'
apply lt_irrefl (x : ℕ)
calc
(x : ℕ) < c.sizeUpTo (i₁ : ℕ).succ := (c.mem_range_embedding_iff.1 hx₁).2
_ ≤ c.sizeUpTo (i₂ : ℕ) := monotone_sum_take _ A
_ ≤ x := (c.mem_range_embedding_iff.1 hx₂).1
#align composition.disjoint_range Composition.disjoint_range
theorem mem_range_embedding (j : Fin n) : j ∈ Set.range (c.embedding (c.index j)) := by
have : c.embedding (c.index j) (c.invEmbedding j) ∈ Set.range (c.embedding (c.index j)) :=
Set.mem_range_self _
rwa [c.embedding_comp_inv j] at this
#align composition.mem_range_embedding Composition.mem_range_embedding
theorem mem_range_embedding_iff' {j : Fin n} {i : Fin c.length} :
j ∈ Set.range (c.embedding i) ↔ i = c.index j := by
constructor
· rw [← not_imp_not]
intro h
exact Set.disjoint_right.1 (c.disjoint_range h) (c.mem_range_embedding j)
· intro h
rw [h]
exact c.mem_range_embedding j
#align composition.mem_range_embedding_iff' Composition.mem_range_embedding_iff'
theorem index_embedding (i : Fin c.length) (j : Fin (c.blocksFun i)) :
c.index (c.embedding i j) = i := by
symm
rw [← mem_range_embedding_iff']
apply Set.mem_range_self
#align composition.index_embedding Composition.index_embedding
theorem invEmbedding_comp (i : Fin c.length) (j : Fin (c.blocksFun i)) :
(c.invEmbedding (c.embedding i j) : ℕ) = j := by
simp_rw [coe_invEmbedding, index_embedding, coe_embedding, add_tsub_cancel_left]
#align composition.inv_embedding_comp Composition.invEmbedding_comp
/-- Equivalence between the disjoint union of the blocks (each of them seen as
`Fin (c.blocks_fun i)`) with `Fin n`. -/
def blocksFinEquiv : (Σi : Fin c.length, Fin (c.blocksFun i)) ≃ Fin n where
toFun x := c.embedding x.1 x.2
invFun j := ⟨c.index j, c.invEmbedding j⟩
left_inv x := by
rcases x with ⟨i, y⟩
dsimp
congr; · exact c.index_embedding _ _
rw [Fin.heq_ext_iff]
· exact c.invEmbedding_comp _ _
· rw [c.index_embedding]
right_inv j := c.embedding_comp_inv j
#align composition.blocks_fin_equiv Composition.blocksFinEquiv
theorem blocksFun_congr {n₁ n₂ : ℕ} (c₁ : Composition n₁) (c₂ : Composition n₂) (i₁ : Fin c₁.length)
(i₂ : Fin c₂.length) (hn : n₁ = n₂) (hc : c₁.blocks = c₂.blocks) (hi : (i₁ : ℕ) = i₂) :
c₁.blocksFun i₁ = c₂.blocksFun i₂ := by
cases hn
rw [← Composition.ext_iff] at hc
cases hc
congr
rwa [Fin.ext_iff]
#align composition.blocks_fun_congr Composition.blocksFun_congr
/-- Two compositions (possibly of different integers) coincide if and only if they have the
same sequence of blocks. -/
theorem sigma_eq_iff_blocks_eq {c : Σn, Composition n} {c' : Σn, Composition n} :
c = c' ↔ c.2.blocks = c'.2.blocks := by
refine ⟨fun H => by rw [H], fun H => ?_⟩
rcases c with ⟨n, c⟩
rcases c' with ⟨n', c'⟩
have : n = n' := by rw [← c.blocks_sum, ← c'.blocks_sum, H]
induction this
congr
ext1
exact H
#align composition.sigma_eq_iff_blocks_eq Composition.sigma_eq_iff_blocks_eq
/-! ### The composition `Composition.ones` -/
/-- The composition made of blocks all of size `1`. -/
def ones (n : ℕ) : Composition n :=
⟨replicate n (1 : ℕ), fun {i} hi => by simp [List.eq_of_mem_replicate hi], by simp⟩
#align composition.ones Composition.ones
instance {n : ℕ} : Inhabited (Composition n) :=
⟨Composition.ones n⟩
@[simp]
theorem ones_length (n : ℕ) : (ones n).length = n :=
List.length_replicate n 1
#align composition.ones_length Composition.ones_length
@[simp]
theorem ones_blocks (n : ℕ) : (ones n).blocks = replicate n (1 : ℕ) :=
rfl
#align composition.ones_blocks Composition.ones_blocks
@[simp]
theorem ones_blocksFun (n : ℕ) (i : Fin (ones n).length) : (ones n).blocksFun i = 1 := by
simp only [blocksFun, ones, blocks, i.2, List.get_replicate]
#align composition.ones_blocks_fun Composition.ones_blocksFun
@[simp]
theorem ones_sizeUpTo (n : ℕ) (i : ℕ) : (ones n).sizeUpTo i = min i n := by
simp [sizeUpTo, ones_blocks, take_replicate]
#align composition.ones_size_up_to Composition.ones_sizeUpTo
@[simp]
theorem ones_embedding (i : Fin (ones n).length) (h : 0 < (ones n).blocksFun i) :
(ones n).embedding i ⟨0, h⟩ = ⟨i, lt_of_lt_of_le i.2 (ones n).length_le⟩ := by
ext
simpa using i.2.le
#align composition.ones_embedding Composition.ones_embedding
theorem eq_ones_iff {c : Composition n} : c = ones n ↔ ∀ i ∈ c.blocks, i = 1 := by
constructor
· rintro rfl
exact fun i => eq_of_mem_replicate
· intro H
ext1
have A : c.blocks = replicate c.blocks.length 1 := eq_replicate_of_mem H
have : c.blocks.length = n := by
conv_rhs => rw [← c.blocks_sum, A]
simp
rw [A, this, ones_blocks]
#align composition.eq_ones_iff Composition.eq_ones_iff
theorem ne_ones_iff {c : Composition n} : c ≠ ones n ↔ ∃ i ∈ c.blocks, 1 < i := by
refine (not_congr eq_ones_iff).trans ?_
have : ∀ j ∈ c.blocks, j = 1 ↔ j ≤ 1 := fun j hj => by simp [le_antisymm_iff, c.one_le_blocks hj]
simp (config := { contextual := true }) [this]
#align composition.ne_ones_iff Composition.ne_ones_iff
theorem eq_ones_iff_length {c : Composition n} : c = ones n ↔ c.length = n := by
constructor
· rintro rfl
exact ones_length n
· contrapose
intro H length_n
apply lt_irrefl n
calc
n = ∑ i : Fin c.length, 1 := by simp [length_n]
_ < ∑ i : Fin c.length, c.blocksFun i := by
{
obtain ⟨i, hi, i_blocks⟩ : ∃ i ∈ c.blocks, 1 < i := ne_ones_iff.1 H
rw [← ofFn_blocksFun, mem_ofFn c.blocksFun, Set.mem_range] at hi
obtain ⟨j : Fin c.length, hj : c.blocksFun j = i⟩ := hi
rw [← hj] at i_blocks
exact Finset.sum_lt_sum (fun i _ => one_le_blocksFun c i) ⟨j, Finset.mem_univ _, i_blocks⟩
}
_ = n := c.sum_blocksFun
#align composition.eq_ones_iff_length Composition.eq_ones_iff_length
theorem eq_ones_iff_le_length {c : Composition n} : c = ones n ↔ n ≤ c.length := by
simp [eq_ones_iff_length, le_antisymm_iff, c.length_le]
#align composition.eq_ones_iff_le_length Composition.eq_ones_iff_le_length
/-! ### The composition `Composition.single` -/
/-- The composition made of a single block of size `n`. -/
def single (n : ℕ) (h : 0 < n) : Composition n :=
⟨[n], by simp [h], by simp⟩
#align composition.single Composition.single
@[simp]
theorem single_length {n : ℕ} (h : 0 < n) : (single n h).length = 1 :=
rfl
#align composition.single_length Composition.single_length
@[simp]
theorem single_blocks {n : ℕ} (h : 0 < n) : (single n h).blocks = [n] :=
rfl
#align composition.single_blocks Composition.single_blocks
@[simp]
theorem single_blocksFun {n : ℕ} (h : 0 < n) (i : Fin (single n h).length) :
(single n h).blocksFun i = n := by simp [blocksFun, single, blocks, i.2]
#align composition.single_blocks_fun Composition.single_blocksFun
@[simp]
theorem single_embedding {n : ℕ} (h : 0 < n) (i : Fin n) :
((single n h).embedding (0 : Fin 1)) i = i := by
ext
simp
#align composition.single_embedding Composition.single_embedding
theorem eq_single_iff_length {n : ℕ} (h : 0 < n) {c : Composition n} :
c = single n h ↔ c.length = 1 := by
constructor
· intro H
rw [H]
exact single_length h
· intro H
ext1
have A : c.blocks.length = 1 := H ▸ c.blocks_length
have B : c.blocks.sum = n := c.blocks_sum
rw [eq_cons_of_length_one A] at B ⊢
simpa [single_blocks] using B
#align composition.eq_single_iff_length Composition.eq_single_iff_length
theorem ne_single_iff {n : ℕ} (hn : 0 < n) {c : Composition n} :
c ≠ single n hn ↔ ∀ i, c.blocksFun i < n := by
rw [← not_iff_not]
push_neg
constructor
· rintro rfl
exact ⟨⟨0, by simp⟩, by simp⟩
· rintro ⟨i, hi⟩
rw [eq_single_iff_length]
have : ∀ j : Fin c.length, j = i := by
intro j
by_contra ji
apply lt_irrefl (∑ k, c.blocksFun k)
calc
∑ k, c.blocksFun k ≤ c.blocksFun i := by simp only [c.sum_blocksFun, hi]
_ < ∑ k, c.blocksFun k :=
Finset.single_lt_sum ji (Finset.mem_univ _) (Finset.mem_univ _) (c.one_le_blocksFun j)
fun _ _ _ => zero_le _
simpa using Fintype.card_eq_one_of_forall_eq this
#align composition.ne_single_iff Composition.ne_single_iff
end Composition
/-!
### Splitting a list
Given a list of length `n` and a composition `c` of `n`, one can split `l` into `c.length` sublists
of respective lengths `c.blocks_fun 0`, ..., `c.blocks_fun (c.length-1)`. This is inverse to the
join operation.
-/
namespace List
variable {α : Type*}
/-- Auxiliary for `List.splitWrtComposition`. -/
def splitWrtCompositionAux : List α → List ℕ → List (List α)
| _, [] => []
| l, n::ns =>
let (l₁, l₂) := l.splitAt n
l₁::splitWrtCompositionAux l₂ ns
#align list.split_wrt_composition_aux List.splitWrtCompositionAux
/-- Given a list of length `n` and a composition `[i₁, ..., iₖ]` of `n`, split `l` into a list of
`k` lists corresponding to the blocks of the composition, of respective lengths `i₁`, ..., `iₖ`.
This makes sense mostly when `n = l.length`, but this is not necessary for the definition. -/
def splitWrtComposition (l : List α) (c : Composition n) : List (List α) :=
splitWrtCompositionAux l c.blocks
#align list.split_wrt_composition List.splitWrtComposition
-- Porting note: can't refer to subeqn in Lean 4 this way, and seems to definitionally simp
--attribute [local simp] splitWrtCompositionAux.equations._eqn_1
@[local simp]
theorem splitWrtCompositionAux_cons (l : List α) (n ns) :
l.splitWrtCompositionAux (n::ns) = take n l::(drop n l).splitWrtCompositionAux ns := by
simp [splitWrtCompositionAux]
#align list.split_wrt_composition_aux_cons List.splitWrtCompositionAux_cons
theorem length_splitWrtCompositionAux (l : List α) (ns) :
length (l.splitWrtCompositionAux ns) = ns.length := by
induction ns generalizing l
· simp [splitWrtCompositionAux, *]
· simp [*]
#align list.length_split_wrt_composition_aux List.length_splitWrtCompositionAux
/-- When one splits a list along a composition `c`, the number of sublists thus created is
`c.length`. -/
@[simp]
theorem length_splitWrtComposition (l : List α) (c : Composition n) :
length (l.splitWrtComposition c) = c.length :=
length_splitWrtCompositionAux _ _
#align list.length_split_wrt_composition List.length_splitWrtComposition
theorem map_length_splitWrtCompositionAux {ns : List ℕ} :
∀ {l : List α}, ns.sum ≤ l.length → map length (l.splitWrtCompositionAux ns) = ns := by
induction' ns with n ns IH <;> intro l h <;> simp at h
· simp [splitWrtCompositionAux]
have := le_trans (Nat.le_add_right _ _) h
simp only [splitWrtCompositionAux_cons, this]; dsimp
rw [length_take, IH] <;> simp [length_drop]
· assumption
· exact le_tsub_of_add_le_left h
#align list.map_length_split_wrt_composition_aux List.map_length_splitWrtCompositionAux
/-- When one splits a list along a composition `c`, the lengths of the sublists thus created are
given by the block sizes in `c`. -/
theorem map_length_splitWrtComposition (l : List α) (c : Composition l.length) :
map length (l.splitWrtComposition c) = c.blocks :=
map_length_splitWrtCompositionAux (le_of_eq c.blocks_sum)
#align list.map_length_split_wrt_composition List.map_length_splitWrtComposition
theorem length_pos_of_mem_splitWrtComposition {l l' : List α} {c : Composition l.length}
(h : l' ∈ l.splitWrtComposition c) : 0 < length l' := by
have : l'.length ∈ (l.splitWrtComposition c).map List.length :=
List.mem_map_of_mem List.length h
rw [map_length_splitWrtComposition] at this
exact c.blocks_pos this
#align list.length_pos_of_mem_split_wrt_composition List.length_pos_of_mem_splitWrtComposition
theorem sum_take_map_length_splitWrtComposition (l : List α) (c : Composition l.length) (i : ℕ) :
(((l.splitWrtComposition c).map length).take i).sum = c.sizeUpTo i := by
congr
exact map_length_splitWrtComposition l c
#align list.sum_take_map_length_split_wrt_composition List.sum_take_map_length_splitWrtComposition
theorem get_splitWrtCompositionAux (l : List α) (ns : List ℕ) {i : ℕ} (hi) :
(l.splitWrtCompositionAux ns).get ⟨i, hi⟩ =
(l.take (ns.take (i + 1)).sum).drop (ns.take i).sum := by
induction' ns with n ns IH generalizing l i
· cases hi
cases' i with i
· rw [Nat.add_zero, List.take_zero, sum_nil]
simpa using get_mk_zero hi
· simp only [splitWrtCompositionAux, get_cons_succ, IH, take,
sum_cons, Nat.add_eq, add_zero, splitAt_eq_take_drop, drop_take, drop_drop]
rw [add_comm (sum _) n, Nat.add_sub_add_left]
#align list.nth_le_split_wrt_composition_aux List.get_splitWrtCompositionAux
/-- The `i`-th sublist in the splitting of a list `l` along a composition `c`, is the slice of `l`
between the indices `c.sizeUpTo i` and `c.sizeUpTo (i+1)`, i.e., the indices in the `i`-th
block of the composition. -/
theorem get_splitWrtComposition' (l : List α) (c : Composition n) {i : ℕ}
(hi : i < (l.splitWrtComposition c).length) :
(l.splitWrtComposition c).get ⟨i, hi⟩ = (l.take (c.sizeUpTo (i + 1))).drop (c.sizeUpTo i) :=
get_splitWrtCompositionAux _ _ _
#align list.nth_le_split_wrt_composition List.get_splitWrtComposition'
-- Porting note: restatement of `get_splitWrtComposition`
theorem get_splitWrtComposition (l : List α) (c : Composition n)
(i : Fin (l.splitWrtComposition c).length) :
get (l.splitWrtComposition c) i = (l.take (c.sizeUpTo (i + 1))).drop (c.sizeUpTo i) :=
get_splitWrtComposition' _ _ _
theorem join_splitWrtCompositionAux {ns : List ℕ} :
∀ {l : List α}, ns.sum = l.length → (l.splitWrtCompositionAux ns).join = l := by
induction' ns with n ns IH <;> intro l h <;> simp at h
· exact (length_eq_zero.1 h.symm).symm
simp only [splitWrtCompositionAux_cons]; dsimp
rw [IH]
· simp
· rw [length_drop, ← h, add_tsub_cancel_left]
#align list.join_split_wrt_composition_aux List.join_splitWrtCompositionAux
/-- If one splits a list along a composition, and then joins the sublists, one gets back the
original list. -/
@[simp]
theorem join_splitWrtComposition (l : List α) (c : Composition l.length) :
(l.splitWrtComposition c).join = l :=
join_splitWrtCompositionAux c.blocks_sum
#align list.join_split_wrt_composition List.join_splitWrtComposition
/-- If one joins a list of lists and then splits the join along the right composition, one gets
back the original list of lists. -/
@[simp]
theorem splitWrtComposition_join (L : List (List α)) (c : Composition L.join.length)
(h : map length L = c.blocks) : splitWrtComposition (join L) c = L := by
simp only [eq_self_iff_true, and_self_iff, eq_iff_join_eq, join_splitWrtComposition,
map_length_splitWrtComposition, h]
#align list.split_wrt_composition_join List.splitWrtComposition_join
end List
/-!
### Compositions as sets
Combinatorial viewpoints on compositions, seen as finite subsets of `Fin (n+1)` containing `0` and
`n`, where the points of the set (other than `n`) correspond to the leftmost points of each block.
-/
/-- Bijection between compositions of `n` and subsets of `{0, ..., n-2}`, defined by
considering the restriction of the subset to `{1, ..., n-1}` and shifting to the left by one. -/
def compositionAsSetEquiv (n : ℕ) : CompositionAsSet n ≃ Finset (Fin (n - 1)) where
toFun c :=
{ i : Fin (n - 1) |
(⟨1 + (i : ℕ), by
apply (add_lt_add_left i.is_lt 1).trans_le
rw [Nat.succ_eq_add_one, add_comm]
exact add_le_add (Nat.sub_le n 1) (le_refl 1)⟩ :
Fin n.succ) ∈
c.boundaries }.toFinset
invFun s :=
{ boundaries :=
{ i : Fin n.succ |
i = 0 ∨ i = Fin.last n ∨ ∃ (j : Fin (n - 1)) (_hj : j ∈ s), (i : ℕ) = j + 1 }.toFinset
zero_mem := by simp
getLast_mem := by simp }
left_inv := by
intro c
ext i
simp only [add_comm, Set.toFinset_setOf, Finset.mem_univ,
forall_true_left, Finset.mem_filter, true_and, exists_prop]
constructor
· rintro (rfl | rfl | ⟨j, hj1, hj2⟩)
· exact c.zero_mem
· exact c.getLast_mem
· convert hj1
· simp only [or_iff_not_imp_left]
intro i_mem i_ne_zero i_ne_last
simp? [Fin.ext_iff] at i_ne_zero i_ne_last says
simp only [Nat.succ_eq_add_one, Fin.ext_iff, Fin.val_zero, Fin.val_last]
at i_ne_zero i_ne_last
have A : (1 + (i - 1) : ℕ) = (i : ℕ) := by
rw [add_comm]
exact Nat.succ_pred_eq_of_pos (pos_iff_ne_zero.mpr i_ne_zero)
refine ⟨⟨i - 1, ?_⟩, ?_, ?_⟩
· have : (i : ℕ) < n + 1 := i.2
simp? [Nat.lt_succ_iff_lt_or_eq, i_ne_last] at this says
simp only [Nat.succ_eq_add_one, Nat.lt_succ_iff_lt_or_eq, i_ne_last, or_false] at this
exact Nat.pred_lt_pred i_ne_zero this
· convert i_mem
simp only [ge_iff_le]
rwa [add_comm]
· simp only [ge_iff_le]
symm
rwa [add_comm]
right_inv := by
intro s
ext i
have : 1 + (i : ℕ) ≠ n := by
apply ne_of_lt
convert add_lt_add_left i.is_lt 1
rw [add_comm]
apply (Nat.succ_pred_eq_of_pos _).symm
exact (zero_le i.val).trans_lt (i.2.trans_le (Nat.sub_le n 1))
simp only [add_comm, Fin.ext_iff, Fin.val_zero, Fin.val_last, exists_prop, Set.toFinset_setOf,
Finset.mem_univ, forall_true_left, Finset.mem_filter, add_eq_zero_iff, and_false,
add_left_inj, false_or, true_and]
erw [Set.mem_setOf_eq]
simp [this, false_or_iff, add_right_inj, add_eq_zero_iff, one_ne_zero, false_and_iff,
Fin.val_mk]
constructor
· intro h
cases' h with n h
· rw [add_comm] at this
contradiction
· cases' h with w h; cases' h with h₁ h₂
rw [← Fin.ext_iff] at h₂
rwa [h₂]
· intro h
apply Or.inr
use i, h
#align composition_as_set_equiv compositionAsSetEquiv
instance compositionAsSetFintype (n : ℕ) : Fintype (CompositionAsSet n) :=
Fintype.ofEquiv _ (compositionAsSetEquiv n).symm
#align composition_as_set_fintype compositionAsSetFintype
theorem compositionAsSet_card (n : ℕ) : Fintype.card (CompositionAsSet n) = 2 ^ (n - 1) := by
have : Fintype.card (Finset (Fin (n - 1))) = 2 ^ (n - 1) := by simp
rw [← this]
exact Fintype.card_congr (compositionAsSetEquiv n)
#align composition_as_set_card compositionAsSet_card
namespace CompositionAsSet
variable (c : CompositionAsSet n)
theorem boundaries_nonempty : c.boundaries.Nonempty :=
⟨0, c.zero_mem⟩
#align composition_as_set.boundaries_nonempty CompositionAsSet.boundaries_nonempty
theorem card_boundaries_pos : 0 < Finset.card c.boundaries :=
Finset.card_pos.mpr c.boundaries_nonempty
#align composition_as_set.card_boundaries_pos CompositionAsSet.card_boundaries_pos
/-- Number of blocks in a `CompositionAsSet`. -/
def length : ℕ :=
Finset.card c.boundaries - 1
#align composition_as_set.length CompositionAsSet.length
theorem card_boundaries_eq_succ_length : c.boundaries.card = c.length + 1 :=
(tsub_eq_iff_eq_add_of_le (Nat.succ_le_of_lt c.card_boundaries_pos)).mp rfl
#align composition_as_set.card_boundaries_eq_succ_length CompositionAsSet.card_boundaries_eq_succ_length
theorem length_lt_card_boundaries : c.length < c.boundaries.card := by
rw [c.card_boundaries_eq_succ_length]
exact lt_add_one _
#align composition_as_set.length_lt_card_boundaries CompositionAsSet.length_lt_card_boundaries
theorem lt_length (i : Fin c.length) : (i : ℕ) + 1 < c.boundaries.card :=
lt_tsub_iff_right.mp i.2
#align composition_as_set.lt_length CompositionAsSet.lt_length
theorem lt_length' (i : Fin c.length) : (i : ℕ) < c.boundaries.card :=
lt_of_le_of_lt (Nat.le_succ i) (c.lt_length i)
#align composition_as_set.lt_length' CompositionAsSet.lt_length'
/-- Canonical increasing bijection from `Fin c.boundaries.card` to `c.boundaries`. -/
def boundary : Fin c.boundaries.card ↪o Fin (n + 1) :=
c.boundaries.orderEmbOfFin rfl
#align composition_as_set.boundary CompositionAsSet.boundary
@[simp]
theorem boundary_zero : (c.boundary ⟨0, c.card_boundaries_pos⟩ : Fin (n + 1)) = 0 := by
rw [boundary, Finset.orderEmbOfFin_zero rfl c.card_boundaries_pos]
exact le_antisymm (Finset.min'_le _ _ c.zero_mem) (Fin.zero_le _)
#align composition_as_set.boundary_zero CompositionAsSet.boundary_zero
@[simp]
theorem boundary_length : c.boundary ⟨c.length, c.length_lt_card_boundaries⟩ = Fin.last n := by
convert Finset.orderEmbOfFin_last rfl c.card_boundaries_pos
exact le_antisymm (Finset.le_max' _ _ c.getLast_mem) (Fin.le_last _)
#align composition_as_set.boundary_length CompositionAsSet.boundary_length
/-- Size of the `i`-th block in a `CompositionAsSet`, seen as a function on `Fin c.length`. -/
def blocksFun (i : Fin c.length) : ℕ :=
c.boundary ⟨(i : ℕ) + 1, c.lt_length i⟩ - c.boundary ⟨i, c.lt_length' i⟩
#align composition_as_set.blocks_fun CompositionAsSet.blocksFun
theorem blocksFun_pos (i : Fin c.length) : 0 < c.blocksFun i :=
haveI : (⟨i, c.lt_length' i⟩ : Fin c.boundaries.card) < ⟨i + 1, c.lt_length i⟩ :=
Nat.lt_succ_self _
lt_tsub_iff_left.mpr ((c.boundaries.orderEmbOfFin rfl).strictMono this)
#align composition_as_set.blocks_fun_pos CompositionAsSet.blocksFun_pos
/-- List of the sizes of the blocks in a `CompositionAsSet`. -/
def blocks (c : CompositionAsSet n) : List ℕ :=
ofFn c.blocksFun
#align composition_as_set.blocks CompositionAsSet.blocks
@[simp]
theorem blocks_length : c.blocks.length = c.length :=
length_ofFn _
#align composition_as_set.blocks_length CompositionAsSet.blocks_length
theorem blocks_partial_sum {i : ℕ} (h : i < c.boundaries.card) :
(c.blocks.take i).sum = c.boundary ⟨i, h⟩ := by
induction' i with i IH
· simp
have A : i < c.blocks.length := by
rw [c.card_boundaries_eq_succ_length] at h
simp [blocks, Nat.lt_of_succ_lt_succ h]
have B : i < c.boundaries.card := lt_of_lt_of_le A (by simp [blocks, length, Nat.sub_le])
rw [sum_take_succ _ _ A, IH B]
simp [blocks, blocksFun, get_ofFn]
#align composition_as_set.blocks_partial_sum CompositionAsSet.blocks_partial_sum
| Mathlib/Combinatorics/Enumerative/Composition.lean | 933 | 946 | theorem mem_boundaries_iff_exists_blocks_sum_take_eq {j : Fin (n + 1)} :
j ∈ c.boundaries ↔ ∃ i < c.boundaries.card, (c.blocks.take i).sum = j := by |
constructor
· intro hj
rcases (c.boundaries.orderIsoOfFin rfl).surjective ⟨j, hj⟩ with ⟨i, hi⟩
rw [Subtype.ext_iff, Subtype.coe_mk] at hi
refine ⟨i.1, i.2, ?_⟩
dsimp at hi
rw [← hi, c.blocks_partial_sum i.2]
rfl
· rintro ⟨i, hi, H⟩
convert (c.boundaries.orderIsoOfFin rfl ⟨i, hi⟩).2
have : c.boundary ⟨i, hi⟩ = j := by rwa [Fin.ext_iff, ← c.blocks_partial_sum hi]
exact this.symm
|
/-
Copyright (c) 2024 Moritz Doll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Moritz Doll
-/
import Mathlib.Topology.ContinuousFunction.ZeroAtInfty
/-!
# ZeroAtInftyContinuousMapClass in normed additive groups
In this file we give a characterization of the predicate `zero_at_infty` from
`ZeroAtInftyContinuousMapClass`. A continuous map `f` is zero at infinity if and only if
for every `ε > 0` there exists a `r : ℝ` such that for all `x : E` with `r < ‖x‖` it holds that
`‖f x‖ < ε`.
-/
open Topology Filter
variable {E F 𝓕 : Type*}
variable [SeminormedAddGroup E] [SeminormedAddCommGroup F]
variable [FunLike 𝓕 E F] [ZeroAtInftyContinuousMapClass 𝓕 E F]
theorem ZeroAtInftyContinuousMapClass.norm_le (f : 𝓕) (ε : ℝ) (hε : 0 < ε) :
∃ (r : ℝ), ∀ (x : E) (_hx : r < ‖x‖), ‖f x‖ < ε := by
have h := zero_at_infty f
rw [tendsto_zero_iff_norm_tendsto_zero, tendsto_def] at h
specialize h (Metric.ball 0 ε) (Metric.ball_mem_nhds 0 hε)
rcases Metric.closedBall_compl_subset_of_mem_cocompact h 0 with ⟨r, hr⟩
use r
intro x hr'
suffices x ∈ (fun x ↦ ‖f x‖) ⁻¹' Metric.ball 0 ε by aesop
apply hr
aesop
variable [ProperSpace E]
| Mathlib/Analysis/Normed/Group/ZeroAtInfty.lean | 38 | 49 | theorem zero_at_infty_of_norm_le (f : E → F)
(h : ∀ (ε : ℝ) (_hε : 0 < ε), ∃ (r : ℝ), ∀ (x : E) (_hx : r < ‖x‖), ‖f x‖ < ε) :
Tendsto f (cocompact E) (𝓝 0) := by |
rw [tendsto_zero_iff_norm_tendsto_zero]
intro s hs
rw [mem_map, Metric.mem_cocompact_iff_closedBall_compl_subset 0]
rw [Metric.mem_nhds_iff] at hs
rcases hs with ⟨ε, hε, hs⟩
rcases h ε hε with ⟨r, hr⟩
use r
intro
aesop
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Jireh Loreaux
-/
import Mathlib.Analysis.MeanInequalities
import Mathlib.Data.Fintype.Order
import Mathlib.LinearAlgebra.Matrix.Basis
import Mathlib.Analysis.NormedSpace.WithLp
#align_import analysis.normed_space.pi_Lp from "leanprover-community/mathlib"@"9d013ad8430ddddd350cff5c3db830278ded3c79"
/-!
# `L^p` distance on finite products of metric spaces
Given finitely many metric spaces, one can put the max distance on their product, but there is also
a whole family of natural distances, indexed by a parameter `p : ℝ≥0∞`, that also induce
the product topology. We define them in this file. For `0 < p < ∞`, the distance on `Π i, α i`
is given by
$$
d(x, y) = \left(\sum d(x_i, y_i)^p\right)^{1/p}.
$$,
whereas for `p = 0` it is the cardinality of the set ${i | d (x_i, y_i) ≠ 0}$. For `p = ∞` the
distance is the supremum of the distances.
We give instances of this construction for emetric spaces, metric spaces, normed groups and normed
spaces.
To avoid conflicting instances, all these are defined on a copy of the original Π-type, named
`PiLp p α`. The assumption `[Fact (1 ≤ p)]` is required for the metric and normed space instances.
We ensure that the topology, bornology and uniform structure on `PiLp p α` are (defeq to) the
product topology, product bornology and product uniformity, to be able to use freely continuity
statements for the coordinate functions, for instance.
## Implementation notes
We only deal with the `L^p` distance on a product of finitely many metric spaces, which may be
distinct. A closely related construction is `lp`, the `L^p` norm on a product of (possibly
infinitely many) normed spaces, where the norm is
$$
\left(\sum ‖f (x)‖^p \right)^{1/p}.
$$
However, the topology induced by this construction is not the product topology, and some functions
have infinite `L^p` norm. These subtleties are not present in the case of finitely many metric
spaces, hence it is worth devoting a file to this specific case which is particularly well behaved.
Another related construction is `MeasureTheory.Lp`, the `L^p` norm on the space of functions from
a measure space to a normed space, where the norm is
$$
\left(\int ‖f (x)‖^p dμ\right)^{1/p}.
$$
This has all the same subtleties as `lp`, and the further subtlety that this only
defines a seminorm (as almost everywhere zero functions have zero `L^p` norm).
The construction `PiLp` corresponds to the special case of `MeasureTheory.Lp` in which the basis
is a finite space equipped with the counting measure.
To prove that the topology (and the uniform structure) on a finite product with the `L^p` distance
are the same as those coming from the `L^∞` distance, we could argue that the `L^p` and `L^∞` norms
are equivalent on `ℝ^n` for abstract (norm equivalence) reasons. Instead, we give a more explicit
(easy) proof which provides a comparison between these two norms with explicit constants.
We also set up the theory for `PseudoEMetricSpace` and `PseudoMetricSpace`.
-/
set_option linter.uppercaseLean3 false
open Real Set Filter RCLike Bornology Uniformity Topology NNReal ENNReal
noncomputable section
/-- A copy of a Pi type, on which we will put the `L^p` distance. Since the Pi type itself is
already endowed with the `L^∞` distance, we need the type synonym to avoid confusing typeclass
resolution. Also, we let it depend on `p`, to get a whole family of type on which we can put
different distances. -/
abbrev PiLp (p : ℝ≥0∞) {ι : Type*} (α : ι → Type*) : Type _ :=
WithLp p (∀ i : ι, α i)
#align pi_Lp PiLp
/-The following should not be a `FunLike` instance because then the coercion `⇑` would get
unfolded to `FunLike.coe` instead of `WithLp.equiv`. -/
instance (p : ℝ≥0∞) {ι : Type*} (α : ι → Type*) : CoeFun (PiLp p α) (fun _ ↦ (i : ι) → α i) where
coe := WithLp.equiv p _
instance (p : ℝ≥0∞) {ι : Type*} (α : ι → Type*) [∀ i, Inhabited (α i)] : Inhabited (PiLp p α) :=
⟨fun _ => default⟩
@[ext] -- Porting note (#10756): new lemma
protected theorem PiLp.ext {p : ℝ≥0∞} {ι : Type*} {α : ι → Type*} {x y : PiLp p α}
(h : ∀ i, x i = y i) : x = y := funext h
namespace PiLp
variable (p : ℝ≥0∞) (𝕜 : Type*) {ι : Type*} (α : ι → Type*) (β : ι → Type*)
section
/- Register simplification lemmas for the applications of `PiLp` elements, as the usual lemmas
for Pi types will not trigger. -/
variable {𝕜 p α}
variable [SeminormedRing 𝕜] [∀ i, SeminormedAddCommGroup (β i)]
variable [∀ i, Module 𝕜 (β i)] [∀ i, BoundedSMul 𝕜 (β i)] (c : 𝕜)
variable (x y : PiLp p β) (i : ι)
@[simp]
theorem zero_apply : (0 : PiLp p β) i = 0 :=
rfl
#align pi_Lp.zero_apply PiLp.zero_apply
@[simp]
theorem add_apply : (x + y) i = x i + y i :=
rfl
#align pi_Lp.add_apply PiLp.add_apply
@[simp]
theorem sub_apply : (x - y) i = x i - y i :=
rfl
#align pi_Lp.sub_apply PiLp.sub_apply
@[simp]
theorem smul_apply : (c • x) i = c • x i :=
rfl
#align pi_Lp.smul_apply PiLp.smul_apply
@[simp]
theorem neg_apply : (-x) i = -x i :=
rfl
#align pi_Lp.neg_apply PiLp.neg_apply
end
/-! Note that the unapplied versions of these lemmas are deliberately omitted, as they break
the use of the type synonym. -/
@[simp]
theorem _root_.WithLp.equiv_pi_apply (x : PiLp p α) (i : ι) : WithLp.equiv p _ x i = x i :=
rfl
#align pi_Lp.equiv_apply WithLp.equiv_pi_apply
@[simp]
theorem _root_.WithLp.equiv_symm_pi_apply (x : ∀ i, α i) (i : ι) :
(WithLp.equiv p _).symm x i = x i :=
rfl
#align pi_Lp.equiv_symm_apply WithLp.equiv_symm_pi_apply
section DistNorm
variable [Fintype ι]
/-!
### Definition of `edist`, `dist` and `norm` on `PiLp`
In this section we define the `edist`, `dist` and `norm` functions on `PiLp p α` without assuming
`[Fact (1 ≤ p)]` or metric properties of the spaces `α i`. This allows us to provide the rewrite
lemmas for each of three cases `p = 0`, `p = ∞` and `0 < p.to_real`.
-/
section Edist
variable [∀ i, EDist (β i)]
/-- Endowing the space `PiLp p β` with the `L^p` edistance. We register this instance
separate from `pi_Lp.pseudo_emetric` since the latter requires the type class hypothesis
`[Fact (1 ≤ p)]` in order to prove the triangle inequality.
Registering this separately allows for a future emetric-like structure on `PiLp p β` for `p < 1`
satisfying a relaxed triangle inequality. The terminology for this varies throughout the
literature, but it is sometimes called a *quasi-metric* or *semi-metric*. -/
instance : EDist (PiLp p β) where
edist f g :=
if p = 0 then {i | edist (f i) (g i) ≠ 0}.toFinite.toFinset.card
else
if p = ∞ then ⨆ i, edist (f i) (g i) else (∑ i, edist (f i) (g i) ^ p.toReal) ^ (1 / p.toReal)
variable {β}
theorem edist_eq_card (f g : PiLp 0 β) :
edist f g = {i | edist (f i) (g i) ≠ 0}.toFinite.toFinset.card :=
if_pos rfl
#align pi_Lp.edist_eq_card PiLp.edist_eq_card
theorem edist_eq_sum {p : ℝ≥0∞} (hp : 0 < p.toReal) (f g : PiLp p β) :
edist f g = (∑ i, edist (f i) (g i) ^ p.toReal) ^ (1 / p.toReal) :=
let hp' := ENNReal.toReal_pos_iff.mp hp
(if_neg hp'.1.ne').trans (if_neg hp'.2.ne)
#align pi_Lp.edist_eq_sum PiLp.edist_eq_sum
theorem edist_eq_iSup (f g : PiLp ∞ β) : edist f g = ⨆ i, edist (f i) (g i) := by
dsimp [edist]
exact if_neg ENNReal.top_ne_zero
#align pi_Lp.edist_eq_supr PiLp.edist_eq_iSup
end Edist
section EdistProp
variable {β}
variable [∀ i, PseudoEMetricSpace (β i)]
/-- This holds independent of `p` and does not require `[Fact (1 ≤ p)]`. We keep it separate
from `pi_Lp.pseudo_emetric_space` so it can be used also for `p < 1`. -/
protected theorem edist_self (f : PiLp p β) : edist f f = 0 := by
rcases p.trichotomy with (rfl | rfl | h)
· simp [edist_eq_card]
· simp [edist_eq_iSup]
· simp [edist_eq_sum h, ENNReal.zero_rpow_of_pos h, ENNReal.zero_rpow_of_pos (inv_pos.2 <| h)]
#align pi_Lp.edist_self PiLp.edist_self
/-- This holds independent of `p` and does not require `[Fact (1 ≤ p)]`. We keep it separate
from `pi_Lp.pseudo_emetric_space` so it can be used also for `p < 1`. -/
protected theorem edist_comm (f g : PiLp p β) : edist f g = edist g f := by
rcases p.trichotomy with (rfl | rfl | h)
· simp only [edist_eq_card, edist_comm]
· simp only [edist_eq_iSup, edist_comm]
· simp only [edist_eq_sum h, edist_comm]
#align pi_Lp.edist_comm PiLp.edist_comm
end EdistProp
section Dist
variable [∀ i, Dist (α i)]
/-- Endowing the space `PiLp p β` with the `L^p` distance. We register this instance
separate from `pi_Lp.pseudo_metric` since the latter requires the type class hypothesis
`[Fact (1 ≤ p)]` in order to prove the triangle inequality.
Registering this separately allows for a future metric-like structure on `PiLp p β` for `p < 1`
satisfying a relaxed triangle inequality. The terminology for this varies throughout the
literature, but it is sometimes called a *quasi-metric* or *semi-metric*. -/
instance : Dist (PiLp p α) where
dist f g :=
if p = 0 then {i | dist (f i) (g i) ≠ 0}.toFinite.toFinset.card
else
if p = ∞ then ⨆ i, dist (f i) (g i) else (∑ i, dist (f i) (g i) ^ p.toReal) ^ (1 / p.toReal)
variable {α}
theorem dist_eq_card (f g : PiLp 0 α) :
dist f g = {i | dist (f i) (g i) ≠ 0}.toFinite.toFinset.card :=
if_pos rfl
#align pi_Lp.dist_eq_card PiLp.dist_eq_card
theorem dist_eq_sum {p : ℝ≥0∞} (hp : 0 < p.toReal) (f g : PiLp p α) :
dist f g = (∑ i, dist (f i) (g i) ^ p.toReal) ^ (1 / p.toReal) :=
let hp' := ENNReal.toReal_pos_iff.mp hp
(if_neg hp'.1.ne').trans (if_neg hp'.2.ne)
#align pi_Lp.dist_eq_sum PiLp.dist_eq_sum
theorem dist_eq_iSup (f g : PiLp ∞ α) : dist f g = ⨆ i, dist (f i) (g i) := by
dsimp [dist]
exact if_neg ENNReal.top_ne_zero
#align pi_Lp.dist_eq_csupr PiLp.dist_eq_iSup
end Dist
section Norm
variable [∀ i, Norm (β i)]
/-- Endowing the space `PiLp p β` with the `L^p` norm. We register this instance
separate from `PiLp.seminormedAddCommGroup` since the latter requires the type class hypothesis
`[Fact (1 ≤ p)]` in order to prove the triangle inequality.
Registering this separately allows for a future norm-like structure on `PiLp p β` for `p < 1`
satisfying a relaxed triangle inequality. These are called *quasi-norms*. -/
instance instNorm : Norm (PiLp p β) where
norm f :=
if p = 0 then {i | ‖f i‖ ≠ 0}.toFinite.toFinset.card
else if p = ∞ then ⨆ i, ‖f i‖ else (∑ i, ‖f i‖ ^ p.toReal) ^ (1 / p.toReal)
#align pi_Lp.has_norm PiLp.instNorm
variable {p β}
theorem norm_eq_card (f : PiLp 0 β) : ‖f‖ = {i | ‖f i‖ ≠ 0}.toFinite.toFinset.card :=
if_pos rfl
#align pi_Lp.norm_eq_card PiLp.norm_eq_card
theorem norm_eq_ciSup (f : PiLp ∞ β) : ‖f‖ = ⨆ i, ‖f i‖ := by
dsimp [Norm.norm]
exact if_neg ENNReal.top_ne_zero
#align pi_Lp.norm_eq_csupr PiLp.norm_eq_ciSup
theorem norm_eq_sum (hp : 0 < p.toReal) (f : PiLp p β) :
‖f‖ = (∑ i, ‖f i‖ ^ p.toReal) ^ (1 / p.toReal) :=
let hp' := ENNReal.toReal_pos_iff.mp hp
(if_neg hp'.1.ne').trans (if_neg hp'.2.ne)
#align pi_Lp.norm_eq_sum PiLp.norm_eq_sum
end Norm
end DistNorm
section Aux
/-!
### The uniformity on finite `L^p` products is the product uniformity
In this section, we put the `L^p` edistance on `PiLp p α`, and we check that the uniformity
coming from this edistance coincides with the product uniformity, by showing that the canonical
map to the Pi type (with the `L^∞` distance) is a uniform embedding, as it is both Lipschitz and
antiLipschitz.
We only register this emetric space structure as a temporary instance, as the true instance (to be
registered later) will have as uniformity exactly the product uniformity, instead of the one coming
from the edistance (which is equal to it, but not defeq). See Note [forgetful inheritance]
explaining why having definitionally the right uniformity is often important.
-/
variable [Fact (1 ≤ p)] [∀ i, PseudoMetricSpace (α i)] [∀ i, PseudoEMetricSpace (β i)]
variable [Fintype ι]
/-- Endowing the space `PiLp p β` with the `L^p` pseudoemetric structure. This definition is not
satisfactory, as it does not register the fact that the topology and the uniform structure coincide
with the product one. Therefore, we do not register it as an instance. Using this as a temporary
pseudoemetric space instance, we will show that the uniform structure is equal (but not defeq) to
the product one, and then register an instance in which we replace the uniform structure by the
product one using this pseudoemetric space and `PseudoEMetricSpace.replaceUniformity`. -/
def pseudoEmetricAux : PseudoEMetricSpace (PiLp p β) where
edist_self := PiLp.edist_self p
edist_comm := PiLp.edist_comm p
edist_triangle f g h := by
rcases p.dichotomy with (rfl | hp)
· simp only [edist_eq_iSup]
cases isEmpty_or_nonempty ι
· simp only [ciSup_of_empty, ENNReal.bot_eq_zero, add_zero, nonpos_iff_eq_zero]
-- Porting note: `le_iSup` needed some help
refine
iSup_le fun i => (edist_triangle _ (g i) _).trans <| add_le_add
(le_iSup (fun k => edist (f k) (g k)) i) (le_iSup (fun k => edist (g k) (h k)) i)
· simp only [edist_eq_sum (zero_lt_one.trans_le hp)]
calc
(∑ i, edist (f i) (h i) ^ p.toReal) ^ (1 / p.toReal) ≤
(∑ i, (edist (f i) (g i) + edist (g i) (h i)) ^ p.toReal) ^ (1 / p.toReal) := by
gcongr
apply edist_triangle
_ ≤
(∑ i, edist (f i) (g i) ^ p.toReal) ^ (1 / p.toReal) +
(∑ i, edist (g i) (h i) ^ p.toReal) ^ (1 / p.toReal) :=
ENNReal.Lp_add_le _ _ _ hp
#align pi_Lp.pseudo_emetric_aux PiLp.pseudoEmetricAux
attribute [local instance] PiLp.pseudoEmetricAux
/-- An auxiliary lemma used twice in the proof of `PiLp.pseudoMetricAux` below. Not intended for
use outside this file. -/
theorem iSup_edist_ne_top_aux {ι : Type*} [Finite ι] {α : ι → Type*}
[∀ i, PseudoMetricSpace (α i)] (f g : PiLp ∞ α) : (⨆ i, edist (f i) (g i)) ≠ ⊤ := by
cases nonempty_fintype ι
obtain ⟨M, hM⟩ := Finite.exists_le fun i => (⟨dist (f i) (g i), dist_nonneg⟩ : ℝ≥0)
refine ne_of_lt ((iSup_le fun i => ?_).trans_lt (@ENNReal.coe_lt_top M))
simp only [edist, PseudoMetricSpace.edist_dist, ENNReal.ofReal_eq_coe_nnreal dist_nonneg]
exact mod_cast hM i
#align pi_Lp.supr_edist_ne_top_aux PiLp.iSup_edist_ne_top_aux
/-- Endowing the space `PiLp p α` with the `L^p` pseudometric structure. This definition is not
satisfactory, as it does not register the fact that the topology, the uniform structure, and the
bornology coincide with the product ones. Therefore, we do not register it as an instance. Using
this as a temporary pseudoemetric space instance, we will show that the uniform structure is equal
(but not defeq) to the product one, and then register an instance in which we replace the uniform
structure and the bornology by the product ones using this pseudometric space,
`PseudoMetricSpace.replaceUniformity`, and `PseudoMetricSpace.replaceBornology`.
See note [reducible non-instances] -/
abbrev pseudoMetricAux : PseudoMetricSpace (PiLp p α) :=
PseudoEMetricSpace.toPseudoMetricSpaceOfDist dist
(fun f g => by
rcases p.dichotomy with (rfl | h)
· exact iSup_edist_ne_top_aux f g
· rw [edist_eq_sum (zero_lt_one.trans_le h)]
exact
ENNReal.rpow_ne_top_of_nonneg (one_div_nonneg.2 (zero_le_one.trans h))
(ne_of_lt <|
ENNReal.sum_lt_top fun i hi =>
ENNReal.rpow_ne_top_of_nonneg (zero_le_one.trans h) (edist_ne_top _ _)))
fun f g => by
rcases p.dichotomy with (rfl | h)
· rw [edist_eq_iSup, dist_eq_iSup]
cases isEmpty_or_nonempty ι
· simp only [Real.iSup_of_isEmpty, ciSup_of_empty, ENNReal.bot_eq_zero, ENNReal.zero_toReal]
· refine le_antisymm (ciSup_le fun i => ?_) ?_
· rw [← ENNReal.ofReal_le_iff_le_toReal (iSup_edist_ne_top_aux f g), ←
PseudoMetricSpace.edist_dist]
-- Porting note: `le_iSup` needed some help
exact le_iSup (fun k => edist (f k) (g k)) i
· refine ENNReal.toReal_le_of_le_ofReal (Real.sSup_nonneg _ ?_) (iSup_le fun i => ?_)
· rintro - ⟨i, rfl⟩
exact dist_nonneg
· change PseudoMetricSpace.edist _ _ ≤ _
rw [PseudoMetricSpace.edist_dist]
-- Porting note: `le_ciSup` needed some help
exact ENNReal.ofReal_le_ofReal
(le_ciSup (Finite.bddAbove_range (fun k => dist (f k) (g k))) i)
· have A : ∀ i, edist (f i) (g i) ^ p.toReal ≠ ⊤ := fun i =>
ENNReal.rpow_ne_top_of_nonneg (zero_le_one.trans h) (edist_ne_top _ _)
simp only [edist_eq_sum (zero_lt_one.trans_le h), dist_edist, ENNReal.toReal_rpow,
dist_eq_sum (zero_lt_one.trans_le h), ← ENNReal.toReal_sum fun i _ => A i]
#align pi_Lp.pseudo_metric_aux PiLp.pseudoMetricAux
attribute [local instance] PiLp.pseudoMetricAux
theorem lipschitzWith_equiv_aux : LipschitzWith 1 (WithLp.equiv p (∀ i, β i)) := by
intro x y
simp_rw [ENNReal.coe_one, one_mul, edist_pi_def, Finset.sup_le_iff, Finset.mem_univ,
forall_true_left, WithLp.equiv_pi_apply]
rcases p.dichotomy with (rfl | h)
· simpa only [edist_eq_iSup] using le_iSup fun i => edist (x i) (y i)
· have cancel : p.toReal * (1 / p.toReal) = 1 := mul_div_cancel₀ 1 (zero_lt_one.trans_le h).ne'
rw [edist_eq_sum (zero_lt_one.trans_le h)]
intro i
calc
edist (x i) (y i) = (edist (x i) (y i) ^ p.toReal) ^ (1 / p.toReal) := by
simp [← ENNReal.rpow_mul, cancel, -one_div]
_ ≤ (∑ i, edist (x i) (y i) ^ p.toReal) ^ (1 / p.toReal) := by
gcongr
exact Finset.single_le_sum (fun i _ => (bot_le : (0 : ℝ≥0∞) ≤ _)) (Finset.mem_univ i)
#align pi_Lp.lipschitz_with_equiv_aux PiLp.lipschitzWith_equiv_aux
theorem antilipschitzWith_equiv_aux :
AntilipschitzWith ((Fintype.card ι : ℝ≥0) ^ (1 / p).toReal) (WithLp.equiv p (∀ i, β i)) := by
intro x y
rcases p.dichotomy with (rfl | h)
· simp only [edist_eq_iSup, ENNReal.div_top, ENNReal.zero_toReal, NNReal.rpow_zero,
ENNReal.coe_one, one_mul, iSup_le_iff]
-- Porting note: `Finset.le_sup` needed some help
exact fun i => Finset.le_sup (f := fun i => edist (x i) (y i)) (Finset.mem_univ i)
· have pos : 0 < p.toReal := zero_lt_one.trans_le h
have nonneg : 0 ≤ 1 / p.toReal := one_div_nonneg.2 (le_of_lt pos)
have cancel : p.toReal * (1 / p.toReal) = 1 := mul_div_cancel₀ 1 (ne_of_gt pos)
rw [edist_eq_sum pos, ENNReal.toReal_div 1 p]
simp only [edist, ← one_div, ENNReal.one_toReal]
calc
(∑ i, edist (x i) (y i) ^ p.toReal) ^ (1 / p.toReal) ≤
(∑ _i, edist (WithLp.equiv p _ x) (WithLp.equiv p _ y) ^ p.toReal) ^ (1 / p.toReal) := by
gcongr with i
exact Finset.le_sup (f := fun i => edist (x i) (y i)) (Finset.mem_univ i)
_ =
((Fintype.card ι : ℝ≥0) ^ (1 / p.toReal) : ℝ≥0) *
edist (WithLp.equiv p _ x) (WithLp.equiv p _ y) := by
simp only [nsmul_eq_mul, Finset.card_univ, ENNReal.rpow_one, Finset.sum_const,
ENNReal.mul_rpow_of_nonneg _ _ nonneg, ← ENNReal.rpow_mul, cancel]
have : (Fintype.card ι : ℝ≥0∞) = (Fintype.card ι : ℝ≥0) :=
(ENNReal.coe_natCast (Fintype.card ι)).symm
rw [this, ENNReal.coe_rpow_of_nonneg _ nonneg]
#align pi_Lp.antilipschitz_with_equiv_aux PiLp.antilipschitzWith_equiv_aux
theorem aux_uniformity_eq : 𝓤 (PiLp p β) = 𝓤[Pi.uniformSpace _] := by
have A : UniformInducing (WithLp.equiv p (∀ i, β i)) :=
(antilipschitzWith_equiv_aux p β).uniformInducing
(lipschitzWith_equiv_aux p β).uniformContinuous
have : (fun x : PiLp p β × PiLp p β => (WithLp.equiv p _ x.fst, WithLp.equiv p _ x.snd)) = id :=
by ext i <;> rfl
rw [← A.comap_uniformity, this, comap_id]
#align pi_Lp.aux_uniformity_eq PiLp.aux_uniformity_eq
theorem aux_cobounded_eq : cobounded (PiLp p α) = @cobounded _ Pi.instBornology :=
calc
cobounded (PiLp p α) = comap (WithLp.equiv p (∀ i, α i)) (cobounded _) :=
le_antisymm (antilipschitzWith_equiv_aux p α).tendsto_cobounded.le_comap
(lipschitzWith_equiv_aux p α).comap_cobounded_le
_ = _ := comap_id
#align pi_Lp.aux_cobounded_eq PiLp.aux_cobounded_eq
end Aux
/-! ### Instances on finite `L^p` products -/
instance uniformSpace [∀ i, UniformSpace (β i)] : UniformSpace (PiLp p β) :=
Pi.uniformSpace _
#align pi_Lp.uniform_space PiLp.uniformSpace
theorem uniformContinuous_equiv [∀ i, UniformSpace (β i)] :
UniformContinuous (WithLp.equiv p (∀ i, β i)) :=
uniformContinuous_id
#align pi_Lp.uniform_continuous_equiv PiLp.uniformContinuous_equiv
theorem uniformContinuous_equiv_symm [∀ i, UniformSpace (β i)] :
UniformContinuous (WithLp.equiv p (∀ i, β i)).symm :=
uniformContinuous_id
#align pi_Lp.uniform_continuous_equiv_symm PiLp.uniformContinuous_equiv_symm
@[continuity]
theorem continuous_equiv [∀ i, UniformSpace (β i)] : Continuous (WithLp.equiv p (∀ i, β i)) :=
continuous_id
#align pi_Lp.continuous_equiv PiLp.continuous_equiv
@[continuity]
theorem continuous_equiv_symm [∀ i, UniformSpace (β i)] :
Continuous (WithLp.equiv p (∀ i, β i)).symm :=
continuous_id
#align pi_Lp.continuous_equiv_symm PiLp.continuous_equiv_symm
instance bornology [∀ i, Bornology (β i)] : Bornology (PiLp p β) :=
Pi.instBornology
#align pi_Lp.bornology PiLp.bornology
-- throughout the rest of the file, we assume `1 ≤ p`
variable [Fact (1 ≤ p)]
section Fintype
variable [Fintype ι]
/-- pseudoemetric space instance on the product of finitely many pseudoemetric spaces, using the
`L^p` pseudoedistance, and having as uniformity the product uniformity. -/
instance [∀ i, PseudoEMetricSpace (β i)] : PseudoEMetricSpace (PiLp p β) :=
(pseudoEmetricAux p β).replaceUniformity (aux_uniformity_eq p β).symm
/-- emetric space instance on the product of finitely many emetric spaces, using the `L^p`
edistance, and having as uniformity the product uniformity. -/
instance [∀ i, EMetricSpace (α i)] : EMetricSpace (PiLp p α) :=
@EMetricSpace.ofT0PseudoEMetricSpace (PiLp p α) _ Pi.instT0Space
/-- pseudometric space instance on the product of finitely many pseudometric spaces, using the
`L^p` distance, and having as uniformity the product uniformity. -/
instance [∀ i, PseudoMetricSpace (β i)] : PseudoMetricSpace (PiLp p β) :=
((pseudoMetricAux p β).replaceUniformity (aux_uniformity_eq p β).symm).replaceBornology fun s =>
Filter.ext_iff.1 (aux_cobounded_eq p β).symm sᶜ
/-- metric space instance on the product of finitely many metric spaces, using the `L^p` distance,
and having as uniformity the product uniformity. -/
instance [∀ i, MetricSpace (α i)] : MetricSpace (PiLp p α) :=
MetricSpace.ofT0PseudoMetricSpace _
theorem nndist_eq_sum {p : ℝ≥0∞} [Fact (1 ≤ p)] {β : ι → Type*} [∀ i, PseudoMetricSpace (β i)]
(hp : p ≠ ∞) (x y : PiLp p β) :
nndist x y = (∑ i : ι, nndist (x i) (y i) ^ p.toReal) ^ (1 / p.toReal) :=
-- Porting note: was `Subtype.ext`
NNReal.eq <| by
push_cast
exact dist_eq_sum (p.toReal_pos_iff_ne_top.mpr hp) _ _
#align pi_Lp.nndist_eq_sum PiLp.nndist_eq_sum
theorem nndist_eq_iSup {β : ι → Type*} [∀ i, PseudoMetricSpace (β i)] (x y : PiLp ∞ β) :
nndist x y = ⨆ i, nndist (x i) (y i) :=
-- Porting note: was `Subtype.ext`
NNReal.eq <| by
push_cast
exact dist_eq_iSup _ _
#align pi_Lp.nndist_eq_supr PiLp.nndist_eq_iSup
theorem lipschitzWith_equiv [∀ i, PseudoEMetricSpace (β i)] :
LipschitzWith 1 (WithLp.equiv p (∀ i, β i)) :=
lipschitzWith_equiv_aux p β
#align pi_Lp.lipschitz_with_equiv PiLp.lipschitzWith_equiv
theorem antilipschitzWith_equiv [∀ i, PseudoEMetricSpace (β i)] :
AntilipschitzWith ((Fintype.card ι : ℝ≥0) ^ (1 / p).toReal) (WithLp.equiv p (∀ i, β i)) :=
antilipschitzWith_equiv_aux p β
#align pi_Lp.antilipschitz_with_equiv PiLp.antilipschitzWith_equiv
theorem infty_equiv_isometry [∀ i, PseudoEMetricSpace (β i)] :
Isometry (WithLp.equiv ∞ (∀ i, β i)) :=
fun x y =>
le_antisymm (by simpa only [ENNReal.coe_one, one_mul] using lipschitzWith_equiv ∞ β x y)
(by
simpa only [ENNReal.div_top, ENNReal.zero_toReal, NNReal.rpow_zero, ENNReal.coe_one,
one_mul] using antilipschitzWith_equiv ∞ β x y)
#align pi_Lp.infty_equiv_isometry PiLp.infty_equiv_isometry
/-- seminormed group instance on the product of finitely many normed groups, using the `L^p`
norm. -/
instance seminormedAddCommGroup [∀ i, SeminormedAddCommGroup (β i)] :
SeminormedAddCommGroup (PiLp p β) :=
{ Pi.addCommGroup with
dist_eq := fun x y => by
rcases p.dichotomy with (rfl | h)
· simp only [dist_eq_iSup, norm_eq_ciSup, dist_eq_norm, sub_apply]
· have : p ≠ ∞ := by
intro hp
rw [hp, ENNReal.top_toReal] at h
linarith
simp only [dist_eq_sum (zero_lt_one.trans_le h), norm_eq_sum (zero_lt_one.trans_le h),
dist_eq_norm, sub_apply] }
#align pi_Lp.seminormed_add_comm_group PiLp.seminormedAddCommGroup
/-- normed group instance on the product of finitely many normed groups, using the `L^p` norm. -/
instance normedAddCommGroup [∀ i, NormedAddCommGroup (α i)] : NormedAddCommGroup (PiLp p α) :=
{ PiLp.seminormedAddCommGroup p α with
eq_of_dist_eq_zero := eq_of_dist_eq_zero }
#align pi_Lp.normed_add_comm_group PiLp.normedAddCommGroup
theorem nnnorm_eq_sum {p : ℝ≥0∞} [Fact (1 ≤ p)] {β : ι → Type*} (hp : p ≠ ∞)
[∀ i, SeminormedAddCommGroup (β i)] (f : PiLp p β) :
‖f‖₊ = (∑ i, ‖f i‖₊ ^ p.toReal) ^ (1 / p.toReal) := by
ext
simp [NNReal.coe_sum, norm_eq_sum (p.toReal_pos_iff_ne_top.mpr hp)]
#align pi_Lp.nnnorm_eq_sum PiLp.nnnorm_eq_sum
section Linfty
variable {β}
variable [∀ i, SeminormedAddCommGroup (β i)]
theorem nnnorm_eq_ciSup (f : PiLp ∞ β) : ‖f‖₊ = ⨆ i, ‖f i‖₊ := by
ext
simp [NNReal.coe_iSup, norm_eq_ciSup]
#align pi_Lp.nnnorm_eq_csupr PiLp.nnnorm_eq_ciSup
@[simp] theorem nnnorm_equiv (f : PiLp ∞ β) : ‖WithLp.equiv ⊤ _ f‖₊ = ‖f‖₊ := by
rw [nnnorm_eq_ciSup, Pi.nnnorm_def, Finset.sup_univ_eq_ciSup]
dsimp only [WithLp.equiv_pi_apply]
@[simp] theorem nnnorm_equiv_symm (f : ∀ i, β i) : ‖(WithLp.equiv ⊤ _).symm f‖₊ = ‖f‖₊ :=
(nnnorm_equiv _).symm
@[simp] theorem norm_equiv (f : PiLp ∞ β) : ‖WithLp.equiv ⊤ _ f‖ = ‖f‖ :=
congr_arg NNReal.toReal <| nnnorm_equiv f
@[simp] theorem norm_equiv_symm (f : ∀ i, β i) : ‖(WithLp.equiv ⊤ _).symm f‖ = ‖f‖ :=
(norm_equiv _).symm
end Linfty
theorem norm_eq_of_nat {p : ℝ≥0∞} [Fact (1 ≤ p)] {β : ι → Type*}
[∀ i, SeminormedAddCommGroup (β i)] (n : ℕ) (h : p = n) (f : PiLp p β) :
‖f‖ = (∑ i, ‖f i‖ ^ n) ^ (1 / (n : ℝ)) := by
have := p.toReal_pos_iff_ne_top.mpr (ne_of_eq_of_ne h <| ENNReal.natCast_ne_top n)
simp only [one_div, h, Real.rpow_natCast, ENNReal.toReal_nat, eq_self_iff_true, Finset.sum_congr,
norm_eq_sum this]
#align pi_Lp.norm_eq_of_nat PiLp.norm_eq_of_nat
| Mathlib/Analysis/NormedSpace/PiLp.lean | 621 | 625 | theorem norm_eq_of_L2 {β : ι → Type*} [∀ i, SeminormedAddCommGroup (β i)] (x : PiLp 2 β) :
‖x‖ = √(∑ i : ι, ‖x i‖ ^ 2) := by |
rw [norm_eq_of_nat 2 (by norm_cast) _] -- Porting note: was `convert`
rw [Real.sqrt_eq_rpow]
norm_cast
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Alexander Bentkamp, Anne Baanen
-/
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.LinearAlgebra.Prod
import Mathlib.SetTheory.Cardinal.Basic
import Mathlib.Tactic.FinCases
import Mathlib.Tactic.LinearCombination
import Mathlib.Lean.Expr.ExtraRecognizers
import Mathlib.Data.Set.Subsingleton
#align_import linear_algebra.linear_independent from "leanprover-community/mathlib"@"9d684a893c52e1d6692a504a118bfccbae04feeb"
/-!
# Linear independence
This file defines linear independence in a module or vector space.
It is inspired by Isabelle/HOL's linear algebra, and hence indirectly by HOL Light.
We define `LinearIndependent R v` as `ker (Finsupp.total ι M R v) = ⊥`. Here `Finsupp.total` is the
linear map sending a function `f : ι →₀ R` with finite support to the linear combination of vectors
from `v` with these coefficients. Then we prove that several other statements are equivalent to this
one, including injectivity of `Finsupp.total ι M R v` and some versions with explicitly written
linear combinations.
## Main definitions
All definitions are given for families of vectors, i.e. `v : ι → M` where `M` is the module or
vector space and `ι : Type*` is an arbitrary indexing type.
* `LinearIndependent R v` states that the elements of the family `v` are linearly independent.
* `LinearIndependent.repr hv x` returns the linear combination representing `x : span R (range v)`
on the linearly independent vectors `v`, given `hv : LinearIndependent R v`
(using classical choice). `LinearIndependent.repr hv` is provided as a linear map.
## Main statements
We prove several specialized tests for linear independence of families of vectors and of sets of
vectors.
* `Fintype.linearIndependent_iff`: if `ι` is a finite type, then any function `f : ι → R` has
finite support, so we can reformulate the statement using `∑ i : ι, f i • v i` instead of a sum
over an auxiliary `s : Finset ι`;
* `linearIndependent_empty_type`: a family indexed by an empty type is linearly independent;
* `linearIndependent_unique_iff`: if `ι` is a singleton, then `LinearIndependent K v` is
equivalent to `v default ≠ 0`;
* `linearIndependent_option`, `linearIndependent_sum`, `linearIndependent_fin_cons`,
`linearIndependent_fin_succ`: type-specific tests for linear independence of families of vector
fields;
* `linearIndependent_insert`, `linearIndependent_union`, `linearIndependent_pair`,
`linearIndependent_singleton`: linear independence tests for set operations.
In many cases we additionally provide dot-style operations (e.g., `LinearIndependent.union`) to
make the linear independence tests usable as `hv.insert ha` etc.
We also prove that, when working over a division ring,
any family of vectors includes a linear independent subfamily spanning the same subspace.
## Implementation notes
We use families instead of sets because it allows us to say that two identical vectors are linearly
dependent.
If you want to use sets, use the family `(fun x ↦ x : s → M)` given a set `s : Set M`. The lemmas
`LinearIndependent.to_subtype_range` and `LinearIndependent.of_subtype_range` connect those two
worlds.
## Tags
linearly dependent, linear dependence, linearly independent, linear independence
-/
noncomputable section
open Function Set Submodule
open Cardinal
universe u' u
variable {ι : Type u'} {ι' : Type*} {R : Type*} {K : Type*}
variable {M : Type*} {M' M'' : Type*} {V : Type u} {V' : Type*}
section Module
variable {v : ι → M}
variable [Semiring R] [AddCommMonoid M] [AddCommMonoid M'] [AddCommMonoid M'']
variable [Module R M] [Module R M'] [Module R M'']
variable {a b : R} {x y : M}
variable (R) (v)
/-- `LinearIndependent R v` states the family of vectors `v` is linearly independent over `R`. -/
def LinearIndependent : Prop :=
LinearMap.ker (Finsupp.total ι M R v) = ⊥
#align linear_independent LinearIndependent
open Lean PrettyPrinter.Delaborator SubExpr in
/-- Delaborator for `LinearIndependent` that suggests pretty printing with type hints
in case the family of vectors is over a `Set`.
Type hints look like `LinearIndependent fun (v : ↑s) => ↑v` or `LinearIndependent (ι := ↑s) f`,
depending on whether the family is a lambda expression or not. -/
@[delab app.LinearIndependent]
def delabLinearIndependent : Delab :=
whenPPOption getPPNotation <|
whenNotPPOption getPPAnalysisSkip <|
withOptionAtCurrPos `pp.analysis.skip true do
let e ← getExpr
guard <| e.isAppOfArity ``LinearIndependent 7
let some _ := (e.getArg! 0).coeTypeSet? | failure
let optionsPerPos ← if (e.getArg! 3).isLambda then
withNaryArg 3 do return (← read).optionsPerPos.setBool (← getPos) pp.funBinderTypes.name true
else
withNaryArg 0 do return (← read).optionsPerPos.setBool (← getPos) `pp.analysis.namedArg true
withTheReader Context ({· with optionsPerPos}) delab
variable {R} {v}
theorem linearIndependent_iff :
LinearIndependent R v ↔ ∀ l, Finsupp.total ι M R v l = 0 → l = 0 := by
simp [LinearIndependent, LinearMap.ker_eq_bot']
#align linear_independent_iff linearIndependent_iff
theorem linearIndependent_iff' :
LinearIndependent R v ↔
∀ s : Finset ι, ∀ g : ι → R, ∑ i ∈ s, g i • v i = 0 → ∀ i ∈ s, g i = 0 :=
linearIndependent_iff.trans
⟨fun hf s g hg i his =>
have h :=
hf (∑ i ∈ s, Finsupp.single i (g i)) <| by
simpa only [map_sum, Finsupp.total_single] using hg
calc
g i = (Finsupp.lapply i : (ι →₀ R) →ₗ[R] R) (Finsupp.single i (g i)) := by
{ rw [Finsupp.lapply_apply, Finsupp.single_eq_same] }
_ = ∑ j ∈ s, (Finsupp.lapply i : (ι →₀ R) →ₗ[R] R) (Finsupp.single j (g j)) :=
Eq.symm <|
Finset.sum_eq_single i
(fun j _hjs hji => by rw [Finsupp.lapply_apply, Finsupp.single_eq_of_ne hji])
fun hnis => hnis.elim his
_ = (∑ j ∈ s, Finsupp.single j (g j)) i := (map_sum ..).symm
_ = 0 := DFunLike.ext_iff.1 h i,
fun hf l hl =>
Finsupp.ext fun i =>
_root_.by_contradiction fun hni => hni <| hf _ _ hl _ <| Finsupp.mem_support_iff.2 hni⟩
#align linear_independent_iff' linearIndependent_iff'
theorem linearIndependent_iff'' :
LinearIndependent R v ↔
∀ (s : Finset ι) (g : ι → R), (∀ i ∉ s, g i = 0) →
∑ i ∈ s, g i • v i = 0 → ∀ i, g i = 0 := by
classical
exact linearIndependent_iff'.trans
⟨fun H s g hg hv i => if his : i ∈ s then H s g hv i his else hg i his, fun H s g hg i hi => by
convert
H s (fun j => if j ∈ s then g j else 0) (fun j hj => if_neg hj)
(by simp_rw [ite_smul, zero_smul, Finset.sum_extend_by_zero, hg]) i
exact (if_pos hi).symm⟩
#align linear_independent_iff'' linearIndependent_iff''
theorem not_linearIndependent_iff :
¬LinearIndependent R v ↔
∃ s : Finset ι, ∃ g : ι → R, ∑ i ∈ s, g i • v i = 0 ∧ ∃ i ∈ s, g i ≠ 0 := by
rw [linearIndependent_iff']
simp only [exists_prop, not_forall]
#align not_linear_independent_iff not_linearIndependent_iff
theorem Fintype.linearIndependent_iff [Fintype ι] :
LinearIndependent R v ↔ ∀ g : ι → R, ∑ i, g i • v i = 0 → ∀ i, g i = 0 := by
refine
⟨fun H g => by simpa using linearIndependent_iff'.1 H Finset.univ g, fun H =>
linearIndependent_iff''.2 fun s g hg hs i => H _ ?_ _⟩
rw [← hs]
refine (Finset.sum_subset (Finset.subset_univ _) fun i _ hi => ?_).symm
rw [hg i hi, zero_smul]
#align fintype.linear_independent_iff Fintype.linearIndependent_iff
/-- A finite family of vectors `v i` is linear independent iff the linear map that sends
`c : ι → R` to `∑ i, c i • v i` has the trivial kernel. -/
theorem Fintype.linearIndependent_iff' [Fintype ι] [DecidableEq ι] :
LinearIndependent R v ↔
LinearMap.ker (LinearMap.lsum R (fun _ ↦ R) ℕ fun i ↦ LinearMap.id.smulRight (v i)) = ⊥ := by
simp [Fintype.linearIndependent_iff, LinearMap.ker_eq_bot', funext_iff]
#align fintype.linear_independent_iff' Fintype.linearIndependent_iff'
theorem Fintype.not_linearIndependent_iff [Fintype ι] :
¬LinearIndependent R v ↔ ∃ g : ι → R, ∑ i, g i • v i = 0 ∧ ∃ i, g i ≠ 0 := by
simpa using not_iff_not.2 Fintype.linearIndependent_iff
#align fintype.not_linear_independent_iff Fintype.not_linearIndependent_iff
theorem linearIndependent_empty_type [IsEmpty ι] : LinearIndependent R v :=
linearIndependent_iff.mpr fun v _hv => Subsingleton.elim v 0
#align linear_independent_empty_type linearIndependent_empty_type
theorem LinearIndependent.ne_zero [Nontrivial R] (i : ι) (hv : LinearIndependent R v) : v i ≠ 0 :=
fun h =>
zero_ne_one' R <|
Eq.symm
(by
suffices (Finsupp.single i 1 : ι →₀ R) i = 0 by simpa
rw [linearIndependent_iff.1 hv (Finsupp.single i 1)]
· simp
· simp [h])
#align linear_independent.ne_zero LinearIndependent.ne_zero
lemma LinearIndependent.eq_zero_of_pair {x y : M} (h : LinearIndependent R ![x, y])
{s t : R} (h' : s • x + t • y = 0) : s = 0 ∧ t = 0 := by
have := linearIndependent_iff'.1 h Finset.univ ![s, t]
simp only [Fin.sum_univ_two, Matrix.cons_val_zero, Matrix.cons_val_one, Matrix.head_cons, h',
Finset.mem_univ, forall_true_left] at this
exact ⟨this 0, this 1⟩
/-- Also see `LinearIndependent.pair_iff'` for a simpler version over fields. -/
lemma LinearIndependent.pair_iff {x y : M} :
LinearIndependent R ![x, y] ↔ ∀ (s t : R), s • x + t • y = 0 → s = 0 ∧ t = 0 := by
refine ⟨fun h s t hst ↦ h.eq_zero_of_pair hst, fun h ↦ ?_⟩
apply Fintype.linearIndependent_iff.2
intro g hg
simp only [Fin.sum_univ_two, Matrix.cons_val_zero, Matrix.cons_val_one, Matrix.head_cons] at hg
intro i
fin_cases i
exacts [(h _ _ hg).1, (h _ _ hg).2]
/-- A subfamily of a linearly independent family (i.e., a composition with an injective map) is a
linearly independent family. -/
theorem LinearIndependent.comp (h : LinearIndependent R v) (f : ι' → ι) (hf : Injective f) :
LinearIndependent R (v ∘ f) := by
rw [linearIndependent_iff, Finsupp.total_comp]
intro l hl
have h_map_domain : ∀ x, (Finsupp.mapDomain f l) (f x) = 0 := by
rw [linearIndependent_iff.1 h (Finsupp.mapDomain f l) hl]; simp
ext x
convert h_map_domain x
rw [Finsupp.mapDomain_apply hf]
#align linear_independent.comp LinearIndependent.comp
/-- A family is linearly independent if and only if all of its finite subfamily is
linearly independent. -/
theorem linearIndependent_iff_finset_linearIndependent :
LinearIndependent R v ↔ ∀ (s : Finset ι), LinearIndependent R (v ∘ (Subtype.val : s → ι)) :=
⟨fun H _ ↦ H.comp _ Subtype.val_injective, fun H ↦ linearIndependent_iff'.2 fun s g hg i hi ↦
Fintype.linearIndependent_iff.1 (H s) (g ∘ Subtype.val)
(hg ▸ Finset.sum_attach s fun j ↦ g j • v j) ⟨i, hi⟩⟩
theorem LinearIndependent.coe_range (i : LinearIndependent R v) :
LinearIndependent R ((↑) : range v → M) := by simpa using i.comp _ (rangeSplitting_injective v)
#align linear_independent.coe_range LinearIndependent.coe_range
/-- If `v` is a linearly independent family of vectors and the kernel of a linear map `f` is
disjoint with the submodule spanned by the vectors of `v`, then `f ∘ v` is a linearly independent
family of vectors. See also `LinearIndependent.map'` for a special case assuming `ker f = ⊥`. -/
theorem LinearIndependent.map (hv : LinearIndependent R v) {f : M →ₗ[R] M'}
(hf_inj : Disjoint (span R (range v)) (LinearMap.ker f)) : LinearIndependent R (f ∘ v) := by
rw [disjoint_iff_inf_le, ← Set.image_univ, Finsupp.span_image_eq_map_total,
map_inf_eq_map_inf_comap, map_le_iff_le_comap, comap_bot, Finsupp.supported_univ, top_inf_eq]
at hf_inj
unfold LinearIndependent at hv ⊢
rw [hv, le_bot_iff] at hf_inj
haveI : Inhabited M := ⟨0⟩
rw [Finsupp.total_comp, Finsupp.lmapDomain_total _ _ f, LinearMap.ker_comp,
hf_inj]
exact fun _ => rfl
#align linear_independent.map LinearIndependent.map
/-- If `v` is an injective family of vectors such that `f ∘ v` is linearly independent, then `v`
spans a submodule disjoint from the kernel of `f` -/
theorem Submodule.range_ker_disjoint {f : M →ₗ[R] M'}
(hv : LinearIndependent R (f ∘ v)) :
Disjoint (span R (range v)) (LinearMap.ker f) := by
rw [LinearIndependent, Finsupp.total_comp, Finsupp.lmapDomain_total R _ f (fun _ ↦ rfl),
LinearMap.ker_comp] at hv
rw [disjoint_iff_inf_le, ← Set.image_univ, Finsupp.span_image_eq_map_total,
map_inf_eq_map_inf_comap, hv, inf_bot_eq, map_bot]
/-- An injective linear map sends linearly independent families of vectors to linearly independent
families of vectors. See also `LinearIndependent.map` for a more general statement. -/
theorem LinearIndependent.map' (hv : LinearIndependent R v) (f : M →ₗ[R] M')
(hf_inj : LinearMap.ker f = ⊥) : LinearIndependent R (f ∘ v) :=
hv.map <| by simp [hf_inj]
#align linear_independent.map' LinearIndependent.map'
/-- If `M / R` and `M' / R'` are modules, `i : R' → R` is a map, `j : M →+ M'` is a monoid map,
such that they send non-zero elements to non-zero elements, and compatible with the scalar
multiplications on `M` and `M'`, then `j` sends linearly independent families of vectors to
linearly independent families of vectors. As a special case, taking `R = R'`
it is `LinearIndependent.map'`. -/
theorem LinearIndependent.map_of_injective_injective {R' : Type*} {M' : Type*}
[Semiring R'] [AddCommMonoid M'] [Module R' M'] (hv : LinearIndependent R v)
(i : R' → R) (j : M →+ M') (hi : ∀ r, i r = 0 → r = 0) (hj : ∀ m, j m = 0 → m = 0)
(hc : ∀ (r : R') (m : M), j (i r • m) = r • j m) : LinearIndependent R' (j ∘ v) := by
rw [linearIndependent_iff'] at hv ⊢
intro S r' H s hs
simp_rw [comp_apply, ← hc, ← map_sum] at H
exact hi _ <| hv _ _ (hj _ H) s hs
/-- If `M / R` and `M' / R'` are modules, `i : R → R'` is a surjective map which maps zero to zero,
`j : M →+ M'` is a monoid map which sends non-zero elements to non-zero elements, such that the
scalar multiplications on `M` and `M'` are compatible, then `j` sends linearly independent families
of vectors to linearly independent families of vectors. As a special case, taking `R = R'`
it is `LinearIndependent.map'`. -/
theorem LinearIndependent.map_of_surjective_injective {R' : Type*} {M' : Type*}
[Semiring R'] [AddCommMonoid M'] [Module R' M'] (hv : LinearIndependent R v)
(i : ZeroHom R R') (j : M →+ M') (hi : Surjective i) (hj : ∀ m, j m = 0 → m = 0)
(hc : ∀ (r : R) (m : M), j (r • m) = i r • j m) : LinearIndependent R' (j ∘ v) := by
obtain ⟨i', hi'⟩ := hi.hasRightInverse
refine hv.map_of_injective_injective i' j (fun _ h ↦ ?_) hj fun r m ↦ ?_
· apply_fun i at h
rwa [hi', i.map_zero] at h
rw [hc (i' r) m, hi']
/-- If the image of a family of vectors under a linear map is linearly independent, then so is
the original family. -/
theorem LinearIndependent.of_comp (f : M →ₗ[R] M') (hfv : LinearIndependent R (f ∘ v)) :
LinearIndependent R v :=
linearIndependent_iff'.2 fun s g hg i his =>
have : (∑ i ∈ s, g i • f (v i)) = 0 := by
simp_rw [← map_smul, ← map_sum, hg, f.map_zero]
linearIndependent_iff'.1 hfv s g this i his
#align linear_independent.of_comp LinearIndependent.of_comp
/-- If `f` is an injective linear map, then the family `f ∘ v` is linearly independent
if and only if the family `v` is linearly independent. -/
protected theorem LinearMap.linearIndependent_iff (f : M →ₗ[R] M') (hf_inj : LinearMap.ker f = ⊥) :
LinearIndependent R (f ∘ v) ↔ LinearIndependent R v :=
⟨fun h => h.of_comp f, fun h => h.map <| by simp only [hf_inj, disjoint_bot_right]⟩
#align linear_map.linear_independent_iff LinearMap.linearIndependent_iff
@[nontriviality]
theorem linearIndependent_of_subsingleton [Subsingleton R] : LinearIndependent R v :=
linearIndependent_iff.2 fun _l _hl => Subsingleton.elim _ _
#align linear_independent_of_subsingleton linearIndependent_of_subsingleton
theorem linearIndependent_equiv (e : ι ≃ ι') {f : ι' → M} :
LinearIndependent R (f ∘ e) ↔ LinearIndependent R f :=
⟨fun h => Function.comp_id f ▸ e.self_comp_symm ▸ h.comp _ e.symm.injective, fun h =>
h.comp _ e.injective⟩
#align linear_independent_equiv linearIndependent_equiv
theorem linearIndependent_equiv' (e : ι ≃ ι') {f : ι' → M} {g : ι → M} (h : f ∘ e = g) :
LinearIndependent R g ↔ LinearIndependent R f :=
h ▸ linearIndependent_equiv e
#align linear_independent_equiv' linearIndependent_equiv'
theorem linearIndependent_subtype_range {ι} {f : ι → M} (hf : Injective f) :
LinearIndependent R ((↑) : range f → M) ↔ LinearIndependent R f :=
Iff.symm <| linearIndependent_equiv' (Equiv.ofInjective f hf) rfl
#align linear_independent_subtype_range linearIndependent_subtype_range
alias ⟨LinearIndependent.of_subtype_range, _⟩ := linearIndependent_subtype_range
#align linear_independent.of_subtype_range LinearIndependent.of_subtype_range
theorem linearIndependent_image {ι} {s : Set ι} {f : ι → M} (hf : Set.InjOn f s) :
(LinearIndependent R fun x : s => f x) ↔ LinearIndependent R fun x : f '' s => (x : M) :=
linearIndependent_equiv' (Equiv.Set.imageOfInjOn _ _ hf) rfl
#align linear_independent_image linearIndependent_image
theorem linearIndependent_span (hs : LinearIndependent R v) :
LinearIndependent R (M := span R (range v))
(fun i : ι => ⟨v i, subset_span (mem_range_self i)⟩) :=
LinearIndependent.of_comp (span R (range v)).subtype hs
#align linear_independent_span linearIndependent_span
/-- See `LinearIndependent.fin_cons` for a family of elements in a vector space. -/
theorem LinearIndependent.fin_cons' {m : ℕ} (x : M) (v : Fin m → M) (hli : LinearIndependent R v)
(x_ortho : ∀ (c : R) (y : Submodule.span R (Set.range v)), c • x + y = (0 : M) → c = 0) :
LinearIndependent R (Fin.cons x v : Fin m.succ → M) := by
rw [Fintype.linearIndependent_iff] at hli ⊢
rintro g total_eq j
simp_rw [Fin.sum_univ_succ, Fin.cons_zero, Fin.cons_succ] at total_eq
have : g 0 = 0 := by
refine x_ortho (g 0) ⟨∑ i : Fin m, g i.succ • v i, ?_⟩ total_eq
exact sum_mem fun i _ => smul_mem _ _ (subset_span ⟨i, rfl⟩)
rw [this, zero_smul, zero_add] at total_eq
exact Fin.cases this (hli _ total_eq) j
#align linear_independent.fin_cons' LinearIndependent.fin_cons'
/-- A set of linearly independent vectors in a module `M` over a semiring `K` is also linearly
independent over a subring `R` of `K`.
The implementation uses minimal assumptions about the relationship between `R`, `K` and `M`.
The version where `K` is an `R`-algebra is `LinearIndependent.restrict_scalars_algebras`.
-/
theorem LinearIndependent.restrict_scalars [Semiring K] [SMulWithZero R K] [Module K M]
[IsScalarTower R K M] (hinj : Function.Injective fun r : R => r • (1 : K))
(li : LinearIndependent K v) : LinearIndependent R v := by
refine linearIndependent_iff'.mpr fun s g hg i hi => hinj ?_
dsimp only; rw [zero_smul]
refine (linearIndependent_iff'.mp li : _) _ (g · • (1:K)) ?_ i hi
simp_rw [smul_assoc, one_smul]
exact hg
#align linear_independent.restrict_scalars LinearIndependent.restrict_scalars
/-- Every finite subset of a linearly independent set is linearly independent. -/
theorem linearIndependent_finset_map_embedding_subtype (s : Set M)
(li : LinearIndependent R ((↑) : s → M)) (t : Finset s) :
LinearIndependent R ((↑) : Finset.map (Embedding.subtype s) t → M) := by
let f : t.map (Embedding.subtype s) → s := fun x =>
⟨x.1, by
obtain ⟨x, h⟩ := x
rw [Finset.mem_map] at h
obtain ⟨a, _ha, rfl⟩ := h
simp only [Subtype.coe_prop, Embedding.coe_subtype]⟩
convert LinearIndependent.comp li f ?_
rintro ⟨x, hx⟩ ⟨y, hy⟩
rw [Finset.mem_map] at hx hy
obtain ⟨a, _ha, rfl⟩ := hx
obtain ⟨b, _hb, rfl⟩ := hy
simp only [f, imp_self, Subtype.mk_eq_mk]
#align linear_independent_finset_map_embedding_subtype linearIndependent_finset_map_embedding_subtype
/-- If every finite set of linearly independent vectors has cardinality at most `n`,
then the same is true for arbitrary sets of linearly independent vectors.
-/
theorem linearIndependent_bounded_of_finset_linearIndependent_bounded {n : ℕ}
(H : ∀ s : Finset M, (LinearIndependent R fun i : s => (i : M)) → s.card ≤ n) :
∀ s : Set M, LinearIndependent R ((↑) : s → M) → #s ≤ n := by
intro s li
apply Cardinal.card_le_of
intro t
rw [← Finset.card_map (Embedding.subtype s)]
apply H
apply linearIndependent_finset_map_embedding_subtype _ li
#align linear_independent_bounded_of_finset_linear_independent_bounded linearIndependent_bounded_of_finset_linearIndependent_bounded
section Subtype
/-! The following lemmas use the subtype defined by a set in `M` as the index set `ι`. -/
theorem linearIndependent_comp_subtype {s : Set ι} :
LinearIndependent R (v ∘ (↑) : s → M) ↔
∀ l ∈ Finsupp.supported R R s, (Finsupp.total ι M R v) l = 0 → l = 0 := by
simp only [linearIndependent_iff, (· ∘ ·), Finsupp.mem_supported, Finsupp.total_apply,
Set.subset_def, Finset.mem_coe]
constructor
· intro h l hl₁ hl₂
have := h (l.subtypeDomain s) ((Finsupp.sum_subtypeDomain_index hl₁).trans hl₂)
exact (Finsupp.subtypeDomain_eq_zero_iff hl₁).1 this
· intro h l hl
refine Finsupp.embDomain_eq_zero.1 (h (l.embDomain <| Function.Embedding.subtype s) ?_ ?_)
· suffices ∀ i hi, ¬l ⟨i, hi⟩ = 0 → i ∈ s by simpa
intros
assumption
· rwa [Finsupp.embDomain_eq_mapDomain, Finsupp.sum_mapDomain_index]
exacts [fun _ => zero_smul _ _, fun _ _ _ => add_smul _ _ _]
#align linear_independent_comp_subtype linearIndependent_comp_subtype
theorem linearDependent_comp_subtype' {s : Set ι} :
¬LinearIndependent R (v ∘ (↑) : s → M) ↔
∃ f : ι →₀ R, f ∈ Finsupp.supported R R s ∧ Finsupp.total ι M R v f = 0 ∧ f ≠ 0 := by
simp [linearIndependent_comp_subtype, and_left_comm]
#align linear_dependent_comp_subtype' linearDependent_comp_subtype'
/-- A version of `linearDependent_comp_subtype'` with `Finsupp.total` unfolded. -/
theorem linearDependent_comp_subtype {s : Set ι} :
¬LinearIndependent R (v ∘ (↑) : s → M) ↔
∃ f : ι →₀ R, f ∈ Finsupp.supported R R s ∧ ∑ i ∈ f.support, f i • v i = 0 ∧ f ≠ 0 :=
linearDependent_comp_subtype'
#align linear_dependent_comp_subtype linearDependent_comp_subtype
theorem linearIndependent_subtype {s : Set M} :
LinearIndependent R (fun x => x : s → M) ↔
∀ l ∈ Finsupp.supported R R s, (Finsupp.total M M R id) l = 0 → l = 0 := by
apply linearIndependent_comp_subtype (v := id)
#align linear_independent_subtype linearIndependent_subtype
theorem linearIndependent_comp_subtype_disjoint {s : Set ι} :
LinearIndependent R (v ∘ (↑) : s → M) ↔
Disjoint (Finsupp.supported R R s) (LinearMap.ker <| Finsupp.total ι M R v) := by
rw [linearIndependent_comp_subtype, LinearMap.disjoint_ker]
#align linear_independent_comp_subtype_disjoint linearIndependent_comp_subtype_disjoint
theorem linearIndependent_subtype_disjoint {s : Set M} :
LinearIndependent R (fun x => x : s → M) ↔
Disjoint (Finsupp.supported R R s) (LinearMap.ker <| Finsupp.total M M R id) := by
apply linearIndependent_comp_subtype_disjoint (v := id)
#align linear_independent_subtype_disjoint linearIndependent_subtype_disjoint
theorem linearIndependent_iff_totalOn {s : Set M} :
LinearIndependent R (fun x => x : s → M) ↔
(LinearMap.ker <| Finsupp.totalOn M M R id s) = ⊥ := by
rw [Finsupp.totalOn, LinearMap.ker, LinearMap.comap_codRestrict, Submodule.map_bot, comap_bot,
LinearMap.ker_comp, linearIndependent_subtype_disjoint, disjoint_iff_inf_le, ←
map_comap_subtype, map_le_iff_le_comap, comap_bot, ker_subtype, le_bot_iff]
#align linear_independent_iff_total_on linearIndependent_iff_totalOn
theorem LinearIndependent.restrict_of_comp_subtype {s : Set ι}
(hs : LinearIndependent R (v ∘ (↑) : s → M)) : LinearIndependent R (s.restrict v) :=
hs
#align linear_independent.restrict_of_comp_subtype LinearIndependent.restrict_of_comp_subtype
variable (R M)
theorem linearIndependent_empty : LinearIndependent R (fun x => x : (∅ : Set M) → M) := by
simp [linearIndependent_subtype_disjoint]
#align linear_independent_empty linearIndependent_empty
variable {R M}
theorem LinearIndependent.mono {t s : Set M} (h : t ⊆ s) :
LinearIndependent R (fun x => x : s → M) → LinearIndependent R (fun x => x : t → M) := by
simp only [linearIndependent_subtype_disjoint]
exact Disjoint.mono_left (Finsupp.supported_mono h)
#align linear_independent.mono LinearIndependent.mono
theorem linearIndependent_of_finite (s : Set M)
(H : ∀ t ⊆ s, Set.Finite t → LinearIndependent R (fun x => x : t → M)) :
LinearIndependent R (fun x => x : s → M) :=
linearIndependent_subtype.2 fun l hl =>
linearIndependent_subtype.1 (H _ hl (Finset.finite_toSet _)) l (Subset.refl _)
#align linear_independent_of_finite linearIndependent_of_finite
| Mathlib/LinearAlgebra/LinearIndependent.lean | 518 | 528 | theorem linearIndependent_iUnion_of_directed {η : Type*} {s : η → Set M} (hs : Directed (· ⊆ ·) s)
(h : ∀ i, LinearIndependent R (fun x => x : s i → M)) :
LinearIndependent R (fun x => x : (⋃ i, s i) → M) := by |
by_cases hη : Nonempty η
· refine linearIndependent_of_finite (⋃ i, s i) fun t ht ft => ?_
rcases finite_subset_iUnion ft ht with ⟨I, fi, hI⟩
rcases hs.finset_le fi.toFinset with ⟨i, hi⟩
exact (h i).mono (Subset.trans hI <| iUnion₂_subset fun j hj => hi j (fi.mem_toFinset.2 hj))
· refine (linearIndependent_empty R M).mono (t := iUnion (s ·)) ?_
rintro _ ⟨_, ⟨i, _⟩, _⟩
exact hη ⟨i⟩
|
/-
Copyright (c) 2021 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Algebra.AddTorsor
import Mathlib.Topology.Algebra.Constructions
import Mathlib.GroupTheory.GroupAction.SubMulAction
import Mathlib.Topology.Algebra.ConstMulAction
#align_import topology.algebra.mul_action from "leanprover-community/mathlib"@"d90e4e186f1d18e375dcd4e5b5f6364b01cb3e46"
/-!
# Continuous monoid action
In this file we define class `ContinuousSMul`. We say `ContinuousSMul M X` if `M` acts on `X` and
the map `(c, x) ↦ c • x` is continuous on `M × X`. We reuse this class for topological
(semi)modules, vector spaces and algebras.
## Main definitions
* `ContinuousSMul M X` : typeclass saying that the map `(c, x) ↦ c • x` is continuous
on `M × X`;
* `Units.continuousSMul`: scalar multiplication by `Mˣ` is continuous when scalar
multiplication by `M` is continuous. This allows `Homeomorph.smul` to be used with on monoids
with `G = Mˣ`.
-- Porting note: These have all moved
* `Homeomorph.smul_of_ne_zero`: if a group with zero `G₀` (e.g., a field) acts on `X` and `c : G₀`
is a nonzero element of `G₀`, then scalar multiplication by `c` is a homeomorphism of `X`;
* `Homeomorph.smul`: scalar multiplication by an element of a group `G` acting on `X`
is a homeomorphism of `X`.
## Main results
Besides homeomorphisms mentioned above, in this file we provide lemmas like `Continuous.smul`
or `Filter.Tendsto.smul` that provide dot-syntax access to `ContinuousSMul`.
-/
open Topology Pointwise
open Filter
/-- Class `ContinuousSMul M X` says that the scalar multiplication `(•) : M → X → X`
is continuous in both arguments. We use the same class for all kinds of multiplicative actions,
including (semi)modules and algebras. -/
class ContinuousSMul (M X : Type*) [SMul M X] [TopologicalSpace M] [TopologicalSpace X] :
Prop where
/-- The scalar multiplication `(•)` is continuous. -/
continuous_smul : Continuous fun p : M × X => p.1 • p.2
#align has_continuous_smul ContinuousSMul
export ContinuousSMul (continuous_smul)
/-- Class `ContinuousVAdd M X` says that the additive action `(+ᵥ) : M → X → X`
is continuous in both arguments. We use the same class for all kinds of additive actions,
including (semi)modules and algebras. -/
class ContinuousVAdd (M X : Type*) [VAdd M X] [TopologicalSpace M] [TopologicalSpace X] :
Prop where
/-- The additive action `(+ᵥ)` is continuous. -/
continuous_vadd : Continuous fun p : M × X => p.1 +ᵥ p.2
#align has_continuous_vadd ContinuousVAdd
export ContinuousVAdd (continuous_vadd)
attribute [to_additive] ContinuousSMul
section Main
variable {M X Y α : Type*} [TopologicalSpace M] [TopologicalSpace X] [TopologicalSpace Y]
section SMul
variable [SMul M X] [ContinuousSMul M X]
@[to_additive]
instance : ContinuousSMul (ULift M) X :=
⟨(continuous_smul (M := M)).comp₂ (continuous_uLift_down.comp continuous_fst) continuous_snd⟩
@[to_additive]
instance (priority := 100) ContinuousSMul.continuousConstSMul : ContinuousConstSMul M X where
continuous_const_smul _ := continuous_smul.comp (continuous_const.prod_mk continuous_id)
#align has_continuous_smul.has_continuous_const_smul ContinuousSMul.continuousConstSMul
#align has_continuous_vadd.has_continuous_const_vadd ContinuousVAdd.continuousConstVAdd
@[to_additive]
theorem Filter.Tendsto.smul {f : α → M} {g : α → X} {l : Filter α} {c : M} {a : X}
(hf : Tendsto f l (𝓝 c)) (hg : Tendsto g l (𝓝 a)) :
Tendsto (fun x => f x • g x) l (𝓝 <| c • a) :=
(continuous_smul.tendsto _).comp (hf.prod_mk_nhds hg)
#align filter.tendsto.smul Filter.Tendsto.smul
#align filter.tendsto.vadd Filter.Tendsto.vadd
@[to_additive]
theorem Filter.Tendsto.smul_const {f : α → M} {l : Filter α} {c : M} (hf : Tendsto f l (𝓝 c))
(a : X) : Tendsto (fun x => f x • a) l (𝓝 (c • a)) :=
hf.smul tendsto_const_nhds
#align filter.tendsto.smul_const Filter.Tendsto.smul_const
#align filter.tendsto.vadd_const Filter.Tendsto.vadd_const
variable {f : Y → M} {g : Y → X} {b : Y} {s : Set Y}
@[to_additive]
theorem ContinuousWithinAt.smul (hf : ContinuousWithinAt f s b) (hg : ContinuousWithinAt g s b) :
ContinuousWithinAt (fun x => f x • g x) s b :=
Filter.Tendsto.smul hf hg
#align continuous_within_at.smul ContinuousWithinAt.smul
#align continuous_within_at.vadd ContinuousWithinAt.vadd
@[to_additive (attr := fun_prop)]
theorem ContinuousAt.smul (hf : ContinuousAt f b) (hg : ContinuousAt g b) :
ContinuousAt (fun x => f x • g x) b :=
Filter.Tendsto.smul hf hg
#align continuous_at.smul ContinuousAt.smul
#align continuous_at.vadd ContinuousAt.vadd
@[to_additive (attr := fun_prop)]
theorem ContinuousOn.smul (hf : ContinuousOn f s) (hg : ContinuousOn g s) :
ContinuousOn (fun x => f x • g x) s := fun x hx => (hf x hx).smul (hg x hx)
#align continuous_on.smul ContinuousOn.smul
#align continuous_on.vadd ContinuousOn.vadd
@[to_additive (attr := continuity, fun_prop)]
theorem Continuous.smul (hf : Continuous f) (hg : Continuous g) : Continuous fun x => f x • g x :=
continuous_smul.comp (hf.prod_mk hg)
#align continuous.smul Continuous.smul
#align continuous.vadd Continuous.vadd
/-- If a scalar action is central, then its right action is continuous when its left action is. -/
@[to_additive "If an additive action is central, then its right action is continuous when its left
action is."]
instance ContinuousSMul.op [SMul Mᵐᵒᵖ X] [IsCentralScalar M X] : ContinuousSMul Mᵐᵒᵖ X :=
⟨by
suffices Continuous fun p : M × X => MulOpposite.op p.fst • p.snd from
this.comp (MulOpposite.continuous_unop.prod_map continuous_id)
simpa only [op_smul_eq_smul] using (continuous_smul : Continuous fun p : M × X => _)⟩
#align has_continuous_smul.op ContinuousSMul.op
#align has_continuous_vadd.op ContinuousVAdd.op
@[to_additive]
instance MulOpposite.continuousSMul : ContinuousSMul M Xᵐᵒᵖ :=
⟨MulOpposite.continuous_op.comp <|
continuous_smul.comp <| continuous_id.prod_map MulOpposite.continuous_unop⟩
#align mul_opposite.has_continuous_smul MulOpposite.continuousSMul
#align add_opposite.has_continuous_vadd AddOpposite.continuousVAdd
@[to_additive]
protected theorem Specializes.smul {a b : M} {x y : X} (h₁ : a ⤳ b) (h₂ : x ⤳ y) :
(a • x) ⤳ (b • y) :=
(h₁.prod h₂).map continuous_smul
@[to_additive]
protected theorem Inseparable.smul {a b : M} {x y : X} (h₁ : Inseparable a b)
(h₂ : Inseparable x y) : Inseparable (a • x) (b • y) :=
(h₁.prod h₂).map continuous_smul
@[to_additive]
lemma IsCompact.smul_set {k : Set M} {u : Set X} (hk : IsCompact k) (hu : IsCompact u) :
IsCompact (k • u) := by
rw [← Set.image_smul_prod]
exact IsCompact.image (hk.prod hu) continuous_smul
@[to_additive]
lemma smul_set_closure_subset (K : Set M) (L : Set X) :
closure K • closure L ⊆ closure (K • L) :=
Set.smul_subset_iff.2 fun _x hx _y hy ↦ map_mem_closure₂ continuous_smul hx hy fun _a ha _b hb ↦
Set.smul_mem_smul ha hb
/-- Suppose that `N` acts on `X` and `M` continuously acts on `Y`.
Suppose that `g : Y → X` is an action homomorphism in the following sense:
there exists a continuous function `f : N → M` such that `g (c • x) = f c • g x`.
Then the action of `N` on `X` is continuous as well.
In many cases, `f = id` so that `g` is an action homomorphism in the sense of `MulActionHom`.
However, this version also works for semilinear maps and `f = Units.val`. -/
@[to_additive
"Suppose that `N` additively acts on `X` and `M` continuously additively acts on `Y`.
Suppose that `g : Y → X` is an additive action homomorphism in the following sense:
there exists a continuous function `f : N → M` such that `g (c +ᵥ x) = f c +ᵥ g x`.
Then the action of `N` on `X` is continuous as well.
In many cases, `f = id` so that `g` is an action homomorphism in the sense of `AddActionHom`.
However, this version also works for `f = AddUnits.val`."]
lemma Inducing.continuousSMul {N : Type*} [SMul N Y] [TopologicalSpace N] {f : N → M}
(hg : Inducing g) (hf : Continuous f) (hsmul : ∀ {c x}, g (c • x) = f c • g x) :
ContinuousSMul N Y where
continuous_smul := by
simpa only [hg.continuous_iff, Function.comp_def, hsmul]
using (hf.comp continuous_fst).smul <| hg.continuous.comp continuous_snd
@[to_additive]
instance SMulMemClass.continuousSMul {S : Type*} [SetLike S X] [SMulMemClass S M X] (s : S) :
ContinuousSMul M s :=
inducing_subtype_val.continuousSMul continuous_id rfl
end SMul
section Monoid
variable [Monoid M] [MulAction M X] [ContinuousSMul M X]
@[to_additive]
instance Units.continuousSMul : ContinuousSMul Mˣ X :=
inducing_id.continuousSMul Units.continuous_val rfl
#align units.has_continuous_smul Units.continuousSMul
#align add_units.has_continuous_vadd AddUnits.continuousVAdd
/-- If an action is continuous, then composing this action with a continuous homomorphism gives
again a continuous action. -/
@[to_additive]
| Mathlib/Topology/Algebra/MulAction.lean | 211 | 216 | theorem MulAction.continuousSMul_compHom
{N : Type*} [TopologicalSpace N] [Monoid N] {f : N →* M} (hf : Continuous f) :
letI : MulAction N X := MulAction.compHom _ f
ContinuousSMul N X := by |
let _ : MulAction N X := MulAction.compHom _ f
exact ⟨(hf.comp continuous_fst).smul continuous_snd⟩
|
/-
Copyright (c) 2020 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison
-/
import Mathlib.Algebra.Algebra.Hom
import Mathlib.RingTheory.Ideal.Quotient
#align_import algebra.ring_quot from "leanprover-community/mathlib"@"e5820f6c8fcf1b75bcd7738ae4da1c5896191f72"
/-!
# Quotients of non-commutative rings
Unfortunately, ideals have only been developed in the commutative case as `Ideal`,
and it's not immediately clear how one should formalise ideals in the non-commutative case.
In this file, we directly define the quotient of a semiring by any relation,
by building a bigger relation that represents the ideal generated by that relation.
We prove the universal properties of the quotient, and recommend avoiding relying on the actual
definition, which is made irreducible for this purpose.
Since everything runs in parallel for quotients of `R`-algebras, we do that case at the same time.
-/
universe uR uS uT uA u₄
variable {R : Type uR} [Semiring R]
variable {S : Type uS} [CommSemiring S]
variable {T : Type uT}
variable {A : Type uA} [Semiring A] [Algebra S A]
namespace RingCon
instance (c : RingCon A) : Algebra S c.Quotient where
smul := (· • ·)
toRingHom := c.mk'.comp (algebraMap S A)
commutes' _ := Quotient.ind' fun _ ↦ congr_arg Quotient.mk'' <| Algebra.commutes _ _
smul_def' _ := Quotient.ind' fun _ ↦ congr_arg Quotient.mk'' <| Algebra.smul_def _ _
@[simp, norm_cast]
theorem coe_algebraMap (c : RingCon A) (s : S) :
(algebraMap S A s : c.Quotient) = algebraMap S _ s :=
rfl
#align ring_con.coe_algebra_map RingCon.coe_algebraMap
end RingCon
namespace RingQuot
/-- Given an arbitrary relation `r` on a ring, we strengthen it to a relation `Rel r`,
such that the equivalence relation generated by `Rel r` has `x ~ y` if and only if
`x - y` is in the ideal generated by elements `a - b` such that `r a b`.
-/
inductive Rel (r : R → R → Prop) : R → R → Prop
| of ⦃x y : R⦄ (h : r x y) : Rel r x y
| add_left ⦃a b c⦄ : Rel r a b → Rel r (a + c) (b + c)
| mul_left ⦃a b c⦄ : Rel r a b → Rel r (a * c) (b * c)
| mul_right ⦃a b c⦄ : Rel r b c → Rel r (a * b) (a * c)
#align ring_quot.rel RingQuot.Rel
theorem Rel.add_right {r : R → R → Prop} ⦃a b c : R⦄ (h : Rel r b c) : Rel r (a + b) (a + c) := by
rw [add_comm a b, add_comm a c]
exact Rel.add_left h
#align ring_quot.rel.add_right RingQuot.Rel.add_right
theorem Rel.neg {R : Type uR} [Ring R] {r : R → R → Prop} ⦃a b : R⦄ (h : Rel r a b) :
Rel r (-a) (-b) := by simp only [neg_eq_neg_one_mul a, neg_eq_neg_one_mul b, Rel.mul_right h]
#align ring_quot.rel.neg RingQuot.Rel.neg
theorem Rel.sub_left {R : Type uR} [Ring R] {r : R → R → Prop} ⦃a b c : R⦄ (h : Rel r a b) :
Rel r (a - c) (b - c) := by simp only [sub_eq_add_neg, h.add_left]
#align ring_quot.rel.sub_left RingQuot.Rel.sub_left
theorem Rel.sub_right {R : Type uR} [Ring R] {r : R → R → Prop} ⦃a b c : R⦄ (h : Rel r b c) :
Rel r (a - b) (a - c) := by simp only [sub_eq_add_neg, h.neg.add_right]
#align ring_quot.rel.sub_right RingQuot.Rel.sub_right
theorem Rel.smul {r : A → A → Prop} (k : S) ⦃a b : A⦄ (h : Rel r a b) : Rel r (k • a) (k • b) := by
simp only [Algebra.smul_def, Rel.mul_right h]
#align ring_quot.rel.smul RingQuot.Rel.smul
/-- `EqvGen (RingQuot.Rel r)` is a ring congruence. -/
def ringCon (r : R → R → Prop) : RingCon R where
r := EqvGen (Rel r)
iseqv := EqvGen.is_equivalence _
add' {a b c d} hab hcd := by
induction hab generalizing c d with
| rel _ _ hab =>
refine (EqvGen.rel _ _ hab.add_left).trans _ _ _ ?_
induction hcd with
| rel _ _ hcd => exact EqvGen.rel _ _ hcd.add_right
| refl => exact EqvGen.refl _
| symm _ _ _ h => exact h.symm _ _
| trans _ _ _ _ _ h h' => exact h.trans _ _ _ h'
| refl => induction hcd with
| rel _ _ hcd => exact EqvGen.rel _ _ hcd.add_right
| refl => exact EqvGen.refl _
| symm _ _ _ h => exact h.symm _ _
| trans _ _ _ _ _ h h' => exact h.trans _ _ _ h'
| symm x y _ hxy => exact (hxy hcd.symm).symm
| trans x y z _ _ h h' => exact (h hcd).trans _ _ _ (h' <| EqvGen.refl _)
mul' {a b c d} hab hcd := by
induction hab generalizing c d with
| rel _ _ hab =>
refine (EqvGen.rel _ _ hab.mul_left).trans _ _ _ ?_
induction hcd with
| rel _ _ hcd => exact EqvGen.rel _ _ hcd.mul_right
| refl => exact EqvGen.refl _
| symm _ _ _ h => exact h.symm _ _
| trans _ _ _ _ _ h h' => exact h.trans _ _ _ h'
| refl => induction hcd with
| rel _ _ hcd => exact EqvGen.rel _ _ hcd.mul_right
| refl => exact EqvGen.refl _
| symm _ _ _ h => exact h.symm _ _
| trans _ _ _ _ _ h h' => exact h.trans _ _ _ h'
| symm x y _ hxy => exact (hxy hcd.symm).symm
| trans x y z _ _ h h' => exact (h hcd).trans _ _ _ (h' <| EqvGen.refl _)
#align ring_quot.ring_con RingQuot.ringCon
theorem eqvGen_rel_eq (r : R → R → Prop) : EqvGen (Rel r) = RingConGen.Rel r := by
ext x₁ x₂
constructor
· intro h
induction h with
| rel _ _ h => induction h with
| of => exact RingConGen.Rel.of _ _ ‹_›
| add_left _ h => exact h.add (RingConGen.Rel.refl _)
| mul_left _ h => exact h.mul (RingConGen.Rel.refl _)
| mul_right _ h => exact (RingConGen.Rel.refl _).mul h
| refl => exact RingConGen.Rel.refl _
| symm => exact RingConGen.Rel.symm ‹_›
| trans => exact RingConGen.Rel.trans ‹_› ‹_›
· intro h
induction h with
| of => exact EqvGen.rel _ _ (Rel.of ‹_›)
| refl => exact (RingQuot.ringCon r).refl _
| symm => exact (RingQuot.ringCon r).symm ‹_›
| trans => exact (RingQuot.ringCon r).trans ‹_› ‹_›
| add => exact (RingQuot.ringCon r).add ‹_› ‹_›
| mul => exact (RingQuot.ringCon r).mul ‹_› ‹_›
#align ring_quot.eqv_gen_rel_eq RingQuot.eqvGen_rel_eq
end RingQuot
/-- The quotient of a ring by an arbitrary relation. -/
structure RingQuot (r : R → R → Prop) where
toQuot : Quot (RingQuot.Rel r)
#align ring_quot RingQuot
namespace RingQuot
variable (r : R → R → Prop)
-- can't be irreducible, causes diamonds in ℕ-algebras
private def natCast (n : ℕ) : RingQuot r :=
⟨Quot.mk _ n⟩
private irreducible_def zero : RingQuot r :=
⟨Quot.mk _ 0⟩
private irreducible_def one : RingQuot r :=
⟨Quot.mk _ 1⟩
private irreducible_def add : RingQuot r → RingQuot r → RingQuot r
| ⟨a⟩, ⟨b⟩ => ⟨Quot.map₂ (· + ·) Rel.add_right Rel.add_left a b⟩
private irreducible_def mul : RingQuot r → RingQuot r → RingQuot r
| ⟨a⟩, ⟨b⟩ => ⟨Quot.map₂ (· * ·) Rel.mul_right Rel.mul_left a b⟩
private irreducible_def neg {R : Type uR} [Ring R] (r : R → R → Prop) : RingQuot r → RingQuot r
| ⟨a⟩ => ⟨Quot.map (fun a ↦ -a) Rel.neg a⟩
private irreducible_def sub {R : Type uR} [Ring R] (r : R → R → Prop) :
RingQuot r → RingQuot r → RingQuot r
| ⟨a⟩, ⟨b⟩ => ⟨Quot.map₂ Sub.sub Rel.sub_right Rel.sub_left a b⟩
private irreducible_def npow (n : ℕ) : RingQuot r → RingQuot r
| ⟨a⟩ =>
⟨Quot.lift (fun a ↦ Quot.mk (RingQuot.Rel r) (a ^ n))
(fun a b (h : Rel r a b) ↦ by
-- note we can't define a `Rel.pow` as `Rel` isn't reflexive so `Rel r 1 1` isn't true
dsimp only
induction n with
| zero => rw [pow_zero, pow_zero]
| succ n ih =>
rw [pow_succ, pow_succ]
-- Porting note:
-- `simpa [mul_def] using congr_arg₂ (fun x y ↦ mul r ⟨x⟩ ⟨y⟩) (Quot.sound h) ih`
-- mysteriously doesn't work
have := congr_arg₂ (fun x y ↦ mul r ⟨x⟩ ⟨y⟩) ih (Quot.sound h)
dsimp only at this
simp? [mul_def] at this says simp only [mul_def, Quot.map₂_mk, mk.injEq] at this
exact this)
a⟩
-- note: this cannot be irreducible, as otherwise diamonds don't commute.
private def smul [Algebra S R] (n : S) : RingQuot r → RingQuot r
| ⟨a⟩ => ⟨Quot.map (fun a ↦ n • a) (Rel.smul n) a⟩
instance : NatCast (RingQuot r) :=
⟨natCast r⟩
instance : Zero (RingQuot r) :=
⟨zero r⟩
instance : One (RingQuot r) :=
⟨one r⟩
instance : Add (RingQuot r) :=
⟨add r⟩
instance : Mul (RingQuot r) :=
⟨mul r⟩
instance : NatPow (RingQuot r) :=
⟨fun x n ↦ npow r n x⟩
instance {R : Type uR} [Ring R] (r : R → R → Prop) : Neg (RingQuot r) :=
⟨neg r⟩
instance {R : Type uR} [Ring R] (r : R → R → Prop) : Sub (RingQuot r) :=
⟨sub r⟩
instance [Algebra S R] : SMul S (RingQuot r) :=
⟨smul r⟩
theorem zero_quot : (⟨Quot.mk _ 0⟩ : RingQuot r) = 0 :=
show _ = zero r by rw [zero_def]
#align ring_quot.zero_quot RingQuot.zero_quot
theorem one_quot : (⟨Quot.mk _ 1⟩ : RingQuot r) = 1 :=
show _ = one r by rw [one_def]
#align ring_quot.one_quot RingQuot.one_quot
theorem add_quot {a b} : (⟨Quot.mk _ a⟩ + ⟨Quot.mk _ b⟩ : RingQuot r) = ⟨Quot.mk _ (a + b)⟩ := by
show add r _ _ = _
rw [add_def]
rfl
#align ring_quot.add_quot RingQuot.add_quot
theorem mul_quot {a b} : (⟨Quot.mk _ a⟩ * ⟨Quot.mk _ b⟩ : RingQuot r) = ⟨Quot.mk _ (a * b)⟩ := by
show mul r _ _ = _
rw [mul_def]
rfl
#align ring_quot.mul_quot RingQuot.mul_quot
| Mathlib/Algebra/RingQuot.lean | 248 | 250 | theorem pow_quot {a} {n : ℕ} : (⟨Quot.mk _ a⟩ ^ n : RingQuot r) = ⟨Quot.mk _ (a ^ n)⟩ := by |
show npow r _ _ = _
rw [npow_def]
|
/-
Copyright (c) 2021 Jakob von Raumer. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jakob von Raumer
-/
import Mathlib.CategoryTheory.Monoidal.Free.Coherence
import Mathlib.Tactic.CategoryTheory.Coherence
import Mathlib.CategoryTheory.Closed.Monoidal
import Mathlib.Tactic.ApplyFun
#align_import category_theory.monoidal.rigid.basic from "leanprover-community/mathlib"@"3d7987cda72abc473c7cdbbb075170e9ac620042"
/-!
# Rigid (autonomous) monoidal categories
This file defines rigid (autonomous) monoidal categories and the necessary theory about
exact pairings and duals.
## Main definitions
* `ExactPairing` of two objects of a monoidal category
* Type classes `HasLeftDual` and `HasRightDual` that capture that a pairing exists
* The `rightAdjointMate f` as a morphism `fᘁ : Yᘁ ⟶ Xᘁ` for a morphism `f : X ⟶ Y`
* The classes of `RightRigidCategory`, `LeftRigidCategory` and `RigidCategory`
## Main statements
* `comp_rightAdjointMate`: The adjoint mates of the composition is the composition of
adjoint mates.
## Notations
* `η_` and `ε_` denote the coevaluation and evaluation morphism of an exact pairing.
* `Xᘁ` and `ᘁX` denote the right and left dual of an object, as well as the adjoint
mate of a morphism.
## Future work
* Show that `X ⊗ Y` and `Yᘁ ⊗ Xᘁ` form an exact pairing.
* Show that the left adjoint mate of the right adjoint mate of a morphism is the morphism itself.
* Simplify constructions in the case where a symmetry or braiding is present.
* Show that `ᘁ` gives an equivalence of categories `C ≅ (Cᵒᵖ)ᴹᵒᵖ`.
* Define pivotal categories (rigid categories equipped with a natural isomorphism `ᘁᘁ ≅ 𝟙 C`).
## Notes
Although we construct the adjunction `tensorLeft Y ⊣ tensorLeft X` from `ExactPairing X Y`,
this is not a bijective correspondence.
I think the correct statement is that `tensorLeft Y` and `tensorLeft X` are
module endofunctors of `C` as a right `C` module category,
and `ExactPairing X Y` is in bijection with adjunctions compatible with this right `C` action.
## References
* <https://ncatlab.org/nlab/show/rigid+monoidal+category>
## Tags
rigid category, monoidal category
-/
open CategoryTheory MonoidalCategory
universe v v₁ v₂ v₃ u u₁ u₂ u₃
noncomputable section
namespace CategoryTheory
variable {C : Type u₁} [Category.{v₁} C] [MonoidalCategory C]
/-- An exact pairing is a pair of objects `X Y : C` which admit
a coevaluation and evaluation morphism which fulfill two triangle equalities. -/
class ExactPairing (X Y : C) where
/-- Coevaluation of an exact pairing.
Do not use directly. Use `ExactPairing.coevaluation` instead. -/
coevaluation' : 𝟙_ C ⟶ X ⊗ Y
/-- Evaluation of an exact pairing.
Do not use directly. Use `ExactPairing.evaluation` instead. -/
evaluation' : Y ⊗ X ⟶ 𝟙_ C
coevaluation_evaluation' :
Y ◁ coevaluation' ≫ (α_ _ _ _).inv ≫ evaluation' ▷ Y = (ρ_ Y).hom ≫ (λ_ Y).inv := by
aesop_cat
evaluation_coevaluation' :
coevaluation' ▷ X ≫ (α_ _ _ _).hom ≫ X ◁ evaluation' = (λ_ X).hom ≫ (ρ_ X).inv := by
aesop_cat
#align category_theory.exact_pairing CategoryTheory.ExactPairing
namespace ExactPairing
-- Porting note: as there is no mechanism equivalent to `[]` in Lean 3 to make
-- arguments for class fields explicit,
-- we now repeat all the fields without primes.
-- See https://leanprover.zulipchat.com/#narrow/stream/287929-mathlib4/topic/Making.20variable.20in.20class.20field.20explicit
variable (X Y : C)
variable [ExactPairing X Y]
/-- Coevaluation of an exact pairing. -/
def coevaluation : 𝟙_ C ⟶ X ⊗ Y := @coevaluation' _ _ _ X Y _
/-- Evaluation of an exact pairing. -/
def evaluation : Y ⊗ X ⟶ 𝟙_ C := @evaluation' _ _ _ X Y _
@[inherit_doc] notation "η_" => ExactPairing.coevaluation
@[inherit_doc] notation "ε_" => ExactPairing.evaluation
lemma coevaluation_evaluation :
Y ◁ η_ _ _ ≫ (α_ _ _ _).inv ≫ ε_ X _ ▷ Y = (ρ_ Y).hom ≫ (λ_ Y).inv :=
coevaluation_evaluation'
lemma evaluation_coevaluation :
η_ _ _ ▷ X ≫ (α_ _ _ _).hom ≫ X ◁ ε_ _ Y = (λ_ X).hom ≫ (ρ_ X).inv :=
evaluation_coevaluation'
lemma coevaluation_evaluation'' :
Y ◁ η_ X Y ⊗≫ ε_ X Y ▷ Y = ⊗𝟙 := by
convert coevaluation_evaluation X Y <;> simp [monoidalComp]
lemma evaluation_coevaluation'' :
η_ X Y ▷ X ⊗≫ X ◁ ε_ X Y = ⊗𝟙 := by
convert evaluation_coevaluation X Y <;> simp [monoidalComp]
end ExactPairing
attribute [reassoc (attr := simp)] ExactPairing.coevaluation_evaluation
attribute [reassoc (attr := simp)] ExactPairing.evaluation_coevaluation
instance exactPairingUnit : ExactPairing (𝟙_ C) (𝟙_ C) where
coevaluation' := (ρ_ _).inv
evaluation' := (ρ_ _).hom
coevaluation_evaluation' := by rw [← id_tensorHom, ← tensorHom_id]; coherence
evaluation_coevaluation' := by rw [← id_tensorHom, ← tensorHom_id]; coherence
#align category_theory.exact_pairing_unit CategoryTheory.exactPairingUnit
/-- A class of objects which have a right dual. -/
class HasRightDual (X : C) where
/-- The right dual of the object `X`. -/
rightDual : C
[exact : ExactPairing X rightDual]
#align category_theory.has_right_dual CategoryTheory.HasRightDual
/-- A class of objects which have a left dual. -/
class HasLeftDual (Y : C) where
/-- The left dual of the object `X`. -/
leftDual : C
[exact : ExactPairing leftDual Y]
#align category_theory.has_left_dual CategoryTheory.HasLeftDual
attribute [instance] HasRightDual.exact
attribute [instance] HasLeftDual.exact
open ExactPairing HasRightDual HasLeftDual MonoidalCategory
@[inherit_doc] prefix:1024 "ᘁ" => leftDual
@[inherit_doc] postfix:1024 "ᘁ" => rightDual
instance hasRightDualUnit : HasRightDual (𝟙_ C) where
rightDual := 𝟙_ C
#align category_theory.has_right_dual_unit CategoryTheory.hasRightDualUnit
instance hasLeftDualUnit : HasLeftDual (𝟙_ C) where
leftDual := 𝟙_ C
#align category_theory.has_left_dual_unit CategoryTheory.hasLeftDualUnit
instance hasRightDualLeftDual {X : C} [HasLeftDual X] : HasRightDual ᘁX where
rightDual := X
#align category_theory.has_right_dual_left_dual CategoryTheory.hasRightDualLeftDual
instance hasLeftDualRightDual {X : C} [HasRightDual X] : HasLeftDual Xᘁ where
leftDual := X
#align category_theory.has_left_dual_right_dual CategoryTheory.hasLeftDualRightDual
@[simp]
theorem leftDual_rightDual {X : C} [HasRightDual X] : ᘁXᘁ = X :=
rfl
#align category_theory.left_dual_right_dual CategoryTheory.leftDual_rightDual
@[simp]
theorem rightDual_leftDual {X : C} [HasLeftDual X] : (ᘁX)ᘁ = X :=
rfl
#align category_theory.right_dual_left_dual CategoryTheory.rightDual_leftDual
/-- The right adjoint mate `fᘁ : Xᘁ ⟶ Yᘁ` of a morphism `f : X ⟶ Y`. -/
def rightAdjointMate {X Y : C} [HasRightDual X] [HasRightDual Y] (f : X ⟶ Y) : Yᘁ ⟶ Xᘁ :=
(ρ_ _).inv ≫ _ ◁ η_ _ _ ≫ _ ◁ f ▷ _ ≫ (α_ _ _ _).inv ≫ ε_ _ _ ▷ _ ≫ (λ_ _).hom
#align category_theory.right_adjoint_mate CategoryTheory.rightAdjointMate
/-- The left adjoint mate `ᘁf : ᘁY ⟶ ᘁX` of a morphism `f : X ⟶ Y`. -/
def leftAdjointMate {X Y : C} [HasLeftDual X] [HasLeftDual Y] (f : X ⟶ Y) : ᘁY ⟶ ᘁX :=
(λ_ _).inv ≫ η_ (ᘁX) X ▷ _ ≫ (_ ◁ f) ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom
#align category_theory.left_adjoint_mate CategoryTheory.leftAdjointMate
@[inherit_doc] notation f "ᘁ" => rightAdjointMate f
@[inherit_doc] notation "ᘁ" f => leftAdjointMate f
@[simp]
theorem rightAdjointMate_id {X : C} [HasRightDual X] : (𝟙 X)ᘁ = 𝟙 (Xᘁ) := by
simp [rightAdjointMate]
#align category_theory.right_adjoint_mate_id CategoryTheory.rightAdjointMate_id
@[simp]
theorem leftAdjointMate_id {X : C} [HasLeftDual X] : (ᘁ(𝟙 X)) = 𝟙 (ᘁX) := by
simp [leftAdjointMate]
#align category_theory.left_adjoint_mate_id CategoryTheory.leftAdjointMate_id
theorem rightAdjointMate_comp {X Y Z : C} [HasRightDual X] [HasRightDual Y] {f : X ⟶ Y}
{g : Xᘁ ⟶ Z} :
fᘁ ≫ g =
(ρ_ (Yᘁ)).inv ≫
_ ◁ η_ X (Xᘁ) ≫ _ ◁ (f ⊗ g) ≫ (α_ (Yᘁ) Y Z).inv ≫ ε_ Y (Yᘁ) ▷ _ ≫ (λ_ Z).hom :=
calc
_ = 𝟙 _ ⊗≫ Yᘁ ◁ η_ X Xᘁ ≫ Yᘁ ◁ f ▷ Xᘁ ⊗≫ (ε_ Y Yᘁ ▷ Xᘁ ≫ 𝟙_ C ◁ g) ⊗≫ 𝟙 _ := by
dsimp only [rightAdjointMate]; coherence
_ = _ := by
rw [← whisker_exchange, tensorHom_def]; coherence
#align category_theory.right_adjoint_mate_comp CategoryTheory.rightAdjointMate_comp
theorem leftAdjointMate_comp {X Y Z : C} [HasLeftDual X] [HasLeftDual Y] {f : X ⟶ Y}
{g : (ᘁX) ⟶ Z} :
(ᘁf) ≫ g =
(λ_ _).inv ≫
η_ (ᘁX) X ▷ _ ≫ (g ⊗ f) ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom :=
calc
_ = 𝟙 _ ⊗≫ η_ (ᘁX) X ▷ (ᘁY) ⊗≫ (ᘁX) ◁ f ▷ (ᘁY) ⊗≫ ((ᘁX) ◁ ε_ (ᘁY) Y ≫ g ▷ 𝟙_ C) ⊗≫ 𝟙 _ := by
dsimp only [leftAdjointMate]; coherence
_ = _ := by
rw [whisker_exchange, tensorHom_def']; coherence
#align category_theory.left_adjoint_mate_comp CategoryTheory.leftAdjointMate_comp
/-- The composition of right adjoint mates is the adjoint mate of the composition. -/
@[reassoc]
theorem comp_rightAdjointMate {X Y Z : C} [HasRightDual X] [HasRightDual Y] [HasRightDual Z]
{f : X ⟶ Y} {g : Y ⟶ Z} : (f ≫ g)ᘁ = gᘁ ≫ fᘁ := by
rw [rightAdjointMate_comp]
simp only [rightAdjointMate, comp_whiskerRight]
simp only [← Category.assoc]; congr 3; simp only [Category.assoc]
simp only [← MonoidalCategory.whiskerLeft_comp]; congr 2
symm
calc
_ = 𝟙 _ ⊗≫ (η_ Y Yᘁ ▷ 𝟙_ C ≫ (Y ⊗ Yᘁ) ◁ η_ X Xᘁ) ⊗≫ Y ◁ Yᘁ ◁ f ▷ Xᘁ ⊗≫
Y ◁ ε_ Y Yᘁ ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by
rw [tensorHom_def']; coherence
_ = η_ X Xᘁ ⊗≫ (η_ Y Yᘁ ▷ (X ⊗ Xᘁ) ≫ (Y ⊗ Yᘁ) ◁ f ▷ Xᘁ) ⊗≫
Y ◁ ε_ Y Yᘁ ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by
rw [← whisker_exchange]; coherence
_ = η_ X Xᘁ ⊗≫ f ▷ Xᘁ ⊗≫ (η_ Y Yᘁ ▷ Y ⊗≫ Y ◁ ε_ Y Yᘁ) ▷ Xᘁ ⊗≫ g ▷ Xᘁ ⊗≫ 𝟙 _ := by
rw [← whisker_exchange]; coherence
_ = η_ X Xᘁ ≫ f ▷ Xᘁ ≫ g ▷ Xᘁ := by
rw [evaluation_coevaluation'']; coherence
#align category_theory.comp_right_adjoint_mate CategoryTheory.comp_rightAdjointMate
/-- The composition of left adjoint mates is the adjoint mate of the composition. -/
@[reassoc]
theorem comp_leftAdjointMate {X Y Z : C} [HasLeftDual X] [HasLeftDual Y] [HasLeftDual Z] {f : X ⟶ Y}
{g : Y ⟶ Z} : (ᘁf ≫ g) = (ᘁg) ≫ ᘁf := by
rw [leftAdjointMate_comp]
simp only [leftAdjointMate, MonoidalCategory.whiskerLeft_comp]
simp only [← Category.assoc]; congr 3; simp only [Category.assoc]
simp only [← comp_whiskerRight]; congr 2
symm
calc
_ = 𝟙 _ ⊗≫ ((𝟙_ C) ◁ η_ (ᘁY) Y ≫ η_ (ᘁX) X ▷ ((ᘁY) ⊗ Y)) ⊗≫ (ᘁX) ◁ f ▷ (ᘁY) ▷ Y ⊗≫
(ᘁX) ◁ ε_ (ᘁY) Y ▷ Y ⊗≫ (ᘁX) ◁ g := by
rw [tensorHom_def]; coherence
_ = η_ (ᘁX) X ⊗≫ (((ᘁX) ⊗ X) ◁ η_ (ᘁY) Y ≫ ((ᘁX) ◁ f) ▷ ((ᘁY) ⊗ Y)) ⊗≫
(ᘁX) ◁ ε_ (ᘁY) Y ▷ Y ⊗≫ (ᘁX) ◁ g := by
rw [whisker_exchange]; coherence
_ = η_ (ᘁX) X ⊗≫ ((ᘁX) ◁ f) ⊗≫ (ᘁX) ◁ (Y ◁ η_ (ᘁY) Y ⊗≫ ε_ (ᘁY) Y ▷ Y) ⊗≫ (ᘁX) ◁ g := by
rw [whisker_exchange]; coherence
_ = η_ (ᘁX) X ≫ (ᘁX) ◁ f ≫ (ᘁX) ◁ g := by
rw [coevaluation_evaluation'']; coherence
#align category_theory.comp_left_adjoint_mate CategoryTheory.comp_leftAdjointMate
/-- Given an exact pairing on `Y Y'`,
we get a bijection on hom-sets `(Y' ⊗ X ⟶ Z) ≃ (X ⟶ Y ⊗ Z)`
by "pulling the string on the left" up or down.
This gives the adjunction `tensorLeftAdjunction Y Y' : tensorLeft Y' ⊣ tensorLeft Y`.
This adjunction is often referred to as "Frobenius reciprocity" in the
fusion categories / planar algebras / subfactors literature.
-/
def tensorLeftHomEquiv (X Y Y' Z : C) [ExactPairing Y Y'] : (Y' ⊗ X ⟶ Z) ≃ (X ⟶ Y ⊗ Z) where
toFun f := (λ_ _).inv ≫ η_ _ _ ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ f
invFun f := Y' ◁ f ≫ (α_ _ _ _).inv ≫ ε_ _ _ ▷ _ ≫ (λ_ _).hom
left_inv f := by
calc
_ = 𝟙 _ ⊗≫ Y' ◁ η_ Y Y' ▷ X ⊗≫ ((Y' ⊗ Y) ◁ f ≫ ε_ Y Y' ▷ Z) ⊗≫ 𝟙 _ := by
coherence
_ = 𝟙 _ ⊗≫ (Y' ◁ η_ Y Y' ⊗≫ ε_ Y Y' ▷ Y') ▷ X ⊗≫ f := by
rw [whisker_exchange]; coherence
_ = f := by
rw [coevaluation_evaluation'']; coherence
right_inv f := by
calc
_ = 𝟙 _ ⊗≫ (η_ Y Y' ▷ X ≫ (Y ⊗ Y') ◁ f) ⊗≫ Y ◁ ε_ Y Y' ▷ Z ⊗≫ 𝟙 _ := by
coherence
_ = f ⊗≫ (η_ Y Y' ▷ Y ⊗≫ Y ◁ ε_ Y Y') ▷ Z ⊗≫ 𝟙 _ := by
rw [← whisker_exchange]; coherence
_ = f := by
rw [evaluation_coevaluation'']; coherence
#align category_theory.tensor_left_hom_equiv CategoryTheory.tensorLeftHomEquiv
/-- Given an exact pairing on `Y Y'`,
we get a bijection on hom-sets `(X ⊗ Y ⟶ Z) ≃ (X ⟶ Z ⊗ Y')`
by "pulling the string on the right" up or down.
-/
def tensorRightHomEquiv (X Y Y' Z : C) [ExactPairing Y Y'] : (X ⊗ Y ⟶ Z) ≃ (X ⟶ Z ⊗ Y') where
toFun f := (ρ_ _).inv ≫ _ ◁ η_ _ _ ≫ (α_ _ _ _).inv ≫ f ▷ _
invFun f := f ▷ _ ≫ (α_ _ _ _).hom ≫ _ ◁ ε_ _ _ ≫ (ρ_ _).hom
left_inv f := by
calc
_ = 𝟙 _ ⊗≫ X ◁ η_ Y Y' ▷ Y ⊗≫ (f ▷ (Y' ⊗ Y) ≫ Z ◁ ε_ Y Y') ⊗≫ 𝟙 _ := by
coherence
_ = 𝟙 _ ⊗≫ X ◁ (η_ Y Y' ▷ Y ⊗≫ Y ◁ ε_ Y Y') ⊗≫ f := by
rw [← whisker_exchange]; coherence
_ = f := by
rw [evaluation_coevaluation'']; coherence
right_inv f := by
calc
_ = 𝟙 _ ⊗≫ (X ◁ η_ Y Y' ≫ f ▷ (Y ⊗ Y')) ⊗≫ Z ◁ ε_ Y Y' ▷ Y' ⊗≫ 𝟙 _ := by
coherence
_ = f ⊗≫ Z ◁ (Y' ◁ η_ Y Y' ⊗≫ ε_ Y Y' ▷ Y') ⊗≫ 𝟙 _ := by
rw [whisker_exchange]; coherence
_ = f := by
rw [coevaluation_evaluation'']; coherence
#align category_theory.tensor_right_hom_equiv CategoryTheory.tensorRightHomEquiv
theorem tensorLeftHomEquiv_naturality {X Y Y' Z Z' : C} [ExactPairing Y Y'] (f : Y' ⊗ X ⟶ Z)
(g : Z ⟶ Z') :
(tensorLeftHomEquiv X Y Y' Z') (f ≫ g) = (tensorLeftHomEquiv X Y Y' Z) f ≫ Y ◁ g := by
simp [tensorLeftHomEquiv]
#align category_theory.tensor_left_hom_equiv_naturality CategoryTheory.tensorLeftHomEquiv_naturality
theorem tensorLeftHomEquiv_symm_naturality {X X' Y Y' Z : C} [ExactPairing Y Y'] (f : X ⟶ X')
(g : X' ⟶ Y ⊗ Z) :
(tensorLeftHomEquiv X Y Y' Z).symm (f ≫ g) =
_ ◁ f ≫ (tensorLeftHomEquiv X' Y Y' Z).symm g := by
simp [tensorLeftHomEquiv]
#align category_theory.tensor_left_hom_equiv_symm_naturality CategoryTheory.tensorLeftHomEquiv_symm_naturality
theorem tensorRightHomEquiv_naturality {X Y Y' Z Z' : C} [ExactPairing Y Y'] (f : X ⊗ Y ⟶ Z)
(g : Z ⟶ Z') :
(tensorRightHomEquiv X Y Y' Z') (f ≫ g) = (tensorRightHomEquiv X Y Y' Z) f ≫ g ▷ Y' := by
simp [tensorRightHomEquiv]
#align category_theory.tensor_right_hom_equiv_naturality CategoryTheory.tensorRightHomEquiv_naturality
| Mathlib/CategoryTheory/Monoidal/Rigid/Basic.lean | 352 | 356 | theorem tensorRightHomEquiv_symm_naturality {X X' Y Y' Z : C} [ExactPairing Y Y'] (f : X ⟶ X')
(g : X' ⟶ Z ⊗ Y') :
(tensorRightHomEquiv X Y Y' Z).symm (f ≫ g) =
f ▷ Y ≫ (tensorRightHomEquiv X' Y Y' Z).symm g := by |
simp [tensorRightHomEquiv]
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Floris van Doorn
-/
import Mathlib.Geometry.Manifold.SmoothManifoldWithCorners
import Mathlib.Geometry.Manifold.LocalInvariantProperties
#align_import geometry.manifold.cont_mdiff from "leanprover-community/mathlib"@"e5ab837fc252451f3eb9124ae6e7b6f57455e7b9"
/-!
# Smooth functions between smooth manifolds
We define `Cⁿ` functions between smooth manifolds, as functions which are `Cⁿ` in charts, and prove
basic properties of these notions.
## Main definitions and statements
Let `M` and `M'` be two smooth manifolds, with respect to model with corners `I` and `I'`. Let
`f : M → M'`.
* `ContMDiffWithinAt I I' n f s x` states that the function `f` is `Cⁿ` within the set `s`
around the point `x`.
* `ContMDiffAt I I' n f x` states that the function `f` is `Cⁿ` around `x`.
* `ContMDiffOn I I' n f s` states that the function `f` is `Cⁿ` on the set `s`
* `ContMDiff I I' n f` states that the function `f` is `Cⁿ`.
We also give some basic properties of smooth functions between manifolds, following the API of
smooth functions between vector spaces.
See `Basic.lean` for further basic properties of smooth functions between smooth manifolds,
`NormedSpace.lean` for the equivalence of manifold-smoothness to usual smoothness,
`Product.lean` for smoothness results related to the product of manifolds and
`Atlas.lean` for smoothness of atlas members and local structomorphisms.
## Implementation details
Many properties follow for free from the corresponding properties of functions in vector spaces,
as being `Cⁿ` is a local property invariant under the smooth groupoid. We take advantage of the
general machinery developed in `LocalInvariantProperties.lean` to get these properties
automatically. For instance, the fact that being `Cⁿ` does not depend on the chart one considers
is given by `liftPropWithinAt_indep_chart`.
For this to work, the definition of `ContMDiffWithinAt` and friends has to
follow definitionally the setup of local invariant properties. Still, we recast the definition
in terms of extended charts in `contMDiffOn_iff` and `contMDiff_iff`.
-/
open Set Function Filter ChartedSpace SmoothManifoldWithCorners
open scoped Topology Manifold
/-! ### Definition of smooth functions between manifolds -/
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜]
-- declare a smooth manifold `M` over the pair `(E, H)`.
{E : Type*}
[NormedAddCommGroup E] [NormedSpace 𝕜 E] {H : Type*} [TopologicalSpace H]
(I : ModelWithCorners 𝕜 E H) {M : Type*} [TopologicalSpace M] [ChartedSpace H M]
[SmoothManifoldWithCorners I M]
-- declare a smooth manifold `M'` over the pair `(E', H')`.
{E' : Type*}
[NormedAddCommGroup E'] [NormedSpace 𝕜 E'] {H' : Type*} [TopologicalSpace H']
(I' : ModelWithCorners 𝕜 E' H') {M' : Type*} [TopologicalSpace M'] [ChartedSpace H' M']
[SmoothManifoldWithCorners I' M']
-- declare a manifold `M''` over the pair `(E'', H'')`.
{E'' : Type*}
[NormedAddCommGroup E''] [NormedSpace 𝕜 E''] {H'' : Type*} [TopologicalSpace H'']
{I'' : ModelWithCorners 𝕜 E'' H''} {M'' : Type*} [TopologicalSpace M''] [ChartedSpace H'' M'']
-- declare a smooth manifold `N` over the pair `(F, G)`.
{F : Type*}
[NormedAddCommGroup F] [NormedSpace 𝕜 F] {G : Type*} [TopologicalSpace G]
{J : ModelWithCorners 𝕜 F G} {N : Type*} [TopologicalSpace N] [ChartedSpace G N]
[SmoothManifoldWithCorners J N]
-- declare a smooth manifold `N'` over the pair `(F', G')`.
{F' : Type*}
[NormedAddCommGroup F'] [NormedSpace 𝕜 F'] {G' : Type*} [TopologicalSpace G']
{J' : ModelWithCorners 𝕜 F' G'} {N' : Type*} [TopologicalSpace N'] [ChartedSpace G' N']
[SmoothManifoldWithCorners J' N']
-- F₁, F₂, F₃, F₄ are normed spaces
{F₁ : Type*}
[NormedAddCommGroup F₁] [NormedSpace 𝕜 F₁] {F₂ : Type*} [NormedAddCommGroup F₂]
[NormedSpace 𝕜 F₂] {F₃ : Type*} [NormedAddCommGroup F₃] [NormedSpace 𝕜 F₃] {F₄ : Type*}
[NormedAddCommGroup F₄] [NormedSpace 𝕜 F₄]
-- declare functions, sets, points and smoothness indices
{e : PartialHomeomorph M H}
{e' : PartialHomeomorph M' H'} {f f₁ : M → M'} {s s₁ t : Set M} {x : M} {m n : ℕ∞}
/-- Property in the model space of a model with corners of being `C^n` within at set at a point,
when read in the model vector space. This property will be lifted to manifolds to define smooth
functions between manifolds. -/
def ContDiffWithinAtProp (n : ℕ∞) (f : H → H') (s : Set H) (x : H) : Prop :=
ContDiffWithinAt 𝕜 n (I' ∘ f ∘ I.symm) (I.symm ⁻¹' s ∩ range I) (I x)
#align cont_diff_within_at_prop ContDiffWithinAtProp
theorem contDiffWithinAtProp_self_source {f : E → H'} {s : Set E} {x : E} :
ContDiffWithinAtProp 𝓘(𝕜, E) I' n f s x ↔ ContDiffWithinAt 𝕜 n (I' ∘ f) s x := by
simp_rw [ContDiffWithinAtProp, modelWithCornersSelf_coe, range_id, inter_univ,
modelWithCornersSelf_coe_symm, CompTriple.comp_eq, preimage_id_eq, id_eq]
#align cont_diff_within_at_prop_self_source contDiffWithinAtProp_self_source
theorem contDiffWithinAtProp_self {f : E → E'} {s : Set E} {x : E} :
ContDiffWithinAtProp 𝓘(𝕜, E) 𝓘(𝕜, E') n f s x ↔ ContDiffWithinAt 𝕜 n f s x :=
contDiffWithinAtProp_self_source 𝓘(𝕜, E')
#align cont_diff_within_at_prop_self contDiffWithinAtProp_self
theorem contDiffWithinAtProp_self_target {f : H → E'} {s : Set H} {x : H} :
ContDiffWithinAtProp I 𝓘(𝕜, E') n f s x ↔
ContDiffWithinAt 𝕜 n (f ∘ I.symm) (I.symm ⁻¹' s ∩ range I) (I x) :=
Iff.rfl
#align cont_diff_within_at_prop_self_target contDiffWithinAtProp_self_target
/-- Being `Cⁿ` in the model space is a local property, invariant under smooth maps. Therefore,
it will lift nicely to manifolds. -/
theorem contDiffWithinAt_localInvariantProp (n : ℕ∞) :
(contDiffGroupoid ∞ I).LocalInvariantProp (contDiffGroupoid ∞ I')
(ContDiffWithinAtProp I I' n) where
is_local {s x u f} u_open xu := by
have : I.symm ⁻¹' (s ∩ u) ∩ range I = I.symm ⁻¹' s ∩ range I ∩ I.symm ⁻¹' u := by
simp only [inter_right_comm, preimage_inter]
rw [ContDiffWithinAtProp, ContDiffWithinAtProp, this]
symm
apply contDiffWithinAt_inter
have : u ∈ 𝓝 (I.symm (I x)) := by
rw [ModelWithCorners.left_inv]
exact u_open.mem_nhds xu
apply ContinuousAt.preimage_mem_nhds I.continuous_symm.continuousAt this
right_invariance' {s x f e} he hx h := by
rw [ContDiffWithinAtProp] at h ⊢
have : I x = (I ∘ e.symm ∘ I.symm) (I (e x)) := by simp only [hx, mfld_simps]
rw [this] at h
have : I (e x) ∈ I.symm ⁻¹' e.target ∩ range I := by simp only [hx, mfld_simps]
have := (mem_groupoid_of_pregroupoid.2 he).2.contDiffWithinAt this
convert (h.comp' _ (this.of_le le_top)).mono_of_mem _ using 1
· ext y; simp only [mfld_simps]
refine mem_nhdsWithin.mpr
⟨I.symm ⁻¹' e.target, e.open_target.preimage I.continuous_symm, by
simp_rw [mem_preimage, I.left_inv, e.mapsTo hx], ?_⟩
mfld_set_tac
congr_of_forall {s x f g} h hx hf := by
apply hf.congr
· intro y hy
simp only [mfld_simps] at hy
simp only [h, hy, mfld_simps]
· simp only [hx, mfld_simps]
left_invariance' {s x f e'} he' hs hx h := by
rw [ContDiffWithinAtProp] at h ⊢
have A : (I' ∘ f ∘ I.symm) (I x) ∈ I'.symm ⁻¹' e'.source ∩ range I' := by
simp only [hx, mfld_simps]
have := (mem_groupoid_of_pregroupoid.2 he').1.contDiffWithinAt A
convert (this.of_le le_top).comp _ h _
· ext y; simp only [mfld_simps]
· intro y hy; simp only [mfld_simps] at hy; simpa only [hy, mfld_simps] using hs hy.1
#align cont_diff_within_at_local_invariant_prop contDiffWithinAt_localInvariantProp
theorem contDiffWithinAtProp_mono_of_mem (n : ℕ∞) ⦃s x t⦄ ⦃f : H → H'⦄ (hts : s ∈ 𝓝[t] x)
(h : ContDiffWithinAtProp I I' n f s x) : ContDiffWithinAtProp I I' n f t x := by
refine h.mono_of_mem ?_
refine inter_mem ?_ (mem_of_superset self_mem_nhdsWithin inter_subset_right)
rwa [← Filter.mem_map, ← I.image_eq, I.symm_map_nhdsWithin_image]
#align cont_diff_within_at_prop_mono_of_mem contDiffWithinAtProp_mono_of_mem
theorem contDiffWithinAtProp_id (x : H) : ContDiffWithinAtProp I I n id univ x := by
simp only [ContDiffWithinAtProp, id_comp, preimage_univ, univ_inter]
have : ContDiffWithinAt 𝕜 n id (range I) (I x) := contDiff_id.contDiffAt.contDiffWithinAt
refine this.congr (fun y hy => ?_) ?_
· simp only [ModelWithCorners.right_inv I hy, mfld_simps]
· simp only [mfld_simps]
#align cont_diff_within_at_prop_id contDiffWithinAtProp_id
/-- A function is `n` times continuously differentiable within a set at a point in a manifold if
it is continuous and it is `n` times continuously differentiable in this set around this point, when
read in the preferred chart at this point. -/
def ContMDiffWithinAt (n : ℕ∞) (f : M → M') (s : Set M) (x : M) :=
LiftPropWithinAt (ContDiffWithinAtProp I I' n) f s x
#align cont_mdiff_within_at ContMDiffWithinAt
/-- Abbreviation for `ContMDiffWithinAt I I' ⊤ f s x`. See also documentation for `Smooth`.
-/
abbrev SmoothWithinAt (f : M → M') (s : Set M) (x : M) :=
ContMDiffWithinAt I I' ⊤ f s x
#align smooth_within_at SmoothWithinAt
/-- A function is `n` times continuously differentiable at a point in a manifold if
it is continuous and it is `n` times continuously differentiable around this point, when
read in the preferred chart at this point. -/
def ContMDiffAt (n : ℕ∞) (f : M → M') (x : M) :=
ContMDiffWithinAt I I' n f univ x
#align cont_mdiff_at ContMDiffAt
theorem contMDiffAt_iff {n : ℕ∞} {f : M → M'} {x : M} :
ContMDiffAt I I' n f x ↔
ContinuousAt f x ∧
ContDiffWithinAt 𝕜 n (extChartAt I' (f x) ∘ f ∘ (extChartAt I x).symm) (range I)
(extChartAt I x x) :=
liftPropAt_iff.trans <| by rw [ContDiffWithinAtProp, preimage_univ, univ_inter]; rfl
#align cont_mdiff_at_iff contMDiffAt_iff
/-- Abbreviation for `ContMDiffAt I I' ⊤ f x`. See also documentation for `Smooth`. -/
abbrev SmoothAt (f : M → M') (x : M) :=
ContMDiffAt I I' ⊤ f x
#align smooth_at SmoothAt
/-- A function is `n` times continuously differentiable in a set of a manifold if it is continuous
and, for any pair of points, it is `n` times continuously differentiable on this set in the charts
around these points. -/
def ContMDiffOn (n : ℕ∞) (f : M → M') (s : Set M) :=
∀ x ∈ s, ContMDiffWithinAt I I' n f s x
#align cont_mdiff_on ContMDiffOn
/-- Abbreviation for `ContMDiffOn I I' ⊤ f s`. See also documentation for `Smooth`. -/
abbrev SmoothOn (f : M → M') (s : Set M) :=
ContMDiffOn I I' ⊤ f s
#align smooth_on SmoothOn
/-- A function is `n` times continuously differentiable in a manifold if it is continuous
and, for any pair of points, it is `n` times continuously differentiable in the charts
around these points. -/
def ContMDiff (n : ℕ∞) (f : M → M') :=
∀ x, ContMDiffAt I I' n f x
#align cont_mdiff ContMDiff
/-- Abbreviation for `ContMDiff I I' ⊤ f`.
Short note to work with these abbreviations: a lemma of the form `ContMDiffFoo.bar` will
apply fine to an assumption `SmoothFoo` using dot notation or normal notation.
If the consequence `bar` of the lemma involves `ContDiff`, it is still better to restate
the lemma replacing `ContDiff` with `Smooth` both in the assumption and in the conclusion,
to make it possible to use `Smooth` consistently.
This also applies to `SmoothAt`, `SmoothOn` and `SmoothWithinAt`. -/
abbrev Smooth (f : M → M') :=
ContMDiff I I' ⊤ f
#align smooth Smooth
variable {I I'}
/-! ### Deducing smoothness from higher smoothness -/
theorem ContMDiffWithinAt.of_le (hf : ContMDiffWithinAt I I' n f s x) (le : m ≤ n) :
ContMDiffWithinAt I I' m f s x := by
simp only [ContMDiffWithinAt, LiftPropWithinAt] at hf ⊢
exact ⟨hf.1, hf.2.of_le le⟩
#align cont_mdiff_within_at.of_le ContMDiffWithinAt.of_le
theorem ContMDiffAt.of_le (hf : ContMDiffAt I I' n f x) (le : m ≤ n) : ContMDiffAt I I' m f x :=
ContMDiffWithinAt.of_le hf le
#align cont_mdiff_at.of_le ContMDiffAt.of_le
theorem ContMDiffOn.of_le (hf : ContMDiffOn I I' n f s) (le : m ≤ n) : ContMDiffOn I I' m f s :=
fun x hx => (hf x hx).of_le le
#align cont_mdiff_on.of_le ContMDiffOn.of_le
theorem ContMDiff.of_le (hf : ContMDiff I I' n f) (le : m ≤ n) : ContMDiff I I' m f := fun x =>
(hf x).of_le le
#align cont_mdiff.of_le ContMDiff.of_le
/-! ### Basic properties of smooth functions between manifolds -/
theorem ContMDiff.smooth (h : ContMDiff I I' ⊤ f) : Smooth I I' f :=
h
#align cont_mdiff.smooth ContMDiff.smooth
theorem Smooth.contMDiff (h : Smooth I I' f) : ContMDiff I I' n f :=
h.of_le le_top
#align smooth.cont_mdiff Smooth.contMDiff
theorem ContMDiffOn.smoothOn (h : ContMDiffOn I I' ⊤ f s) : SmoothOn I I' f s :=
h
#align cont_mdiff_on.smooth_on ContMDiffOn.smoothOn
theorem SmoothOn.contMDiffOn (h : SmoothOn I I' f s) : ContMDiffOn I I' n f s :=
h.of_le le_top
#align smooth_on.cont_mdiff_on SmoothOn.contMDiffOn
theorem ContMDiffAt.smoothAt (h : ContMDiffAt I I' ⊤ f x) : SmoothAt I I' f x :=
h
#align cont_mdiff_at.smooth_at ContMDiffAt.smoothAt
theorem SmoothAt.contMDiffAt (h : SmoothAt I I' f x) : ContMDiffAt I I' n f x :=
h.of_le le_top
#align smooth_at.cont_mdiff_at SmoothAt.contMDiffAt
theorem ContMDiffWithinAt.smoothWithinAt (h : ContMDiffWithinAt I I' ⊤ f s x) :
SmoothWithinAt I I' f s x :=
h
#align cont_mdiff_within_at.smooth_within_at ContMDiffWithinAt.smoothWithinAt
theorem SmoothWithinAt.contMDiffWithinAt (h : SmoothWithinAt I I' f s x) :
ContMDiffWithinAt I I' n f s x :=
h.of_le le_top
#align smooth_within_at.cont_mdiff_within_at SmoothWithinAt.contMDiffWithinAt
theorem ContMDiff.contMDiffAt (h : ContMDiff I I' n f) : ContMDiffAt I I' n f x :=
h x
#align cont_mdiff.cont_mdiff_at ContMDiff.contMDiffAt
theorem Smooth.smoothAt (h : Smooth I I' f) : SmoothAt I I' f x :=
ContMDiff.contMDiffAt h
#align smooth.smooth_at Smooth.smoothAt
theorem contMDiffWithinAt_univ : ContMDiffWithinAt I I' n f univ x ↔ ContMDiffAt I I' n f x :=
Iff.rfl
#align cont_mdiff_within_at_univ contMDiffWithinAt_univ
theorem smoothWithinAt_univ : SmoothWithinAt I I' f univ x ↔ SmoothAt I I' f x :=
contMDiffWithinAt_univ
#align smooth_within_at_univ smoothWithinAt_univ
theorem contMDiffOn_univ : ContMDiffOn I I' n f univ ↔ ContMDiff I I' n f := by
simp only [ContMDiffOn, ContMDiff, contMDiffWithinAt_univ, forall_prop_of_true, mem_univ]
#align cont_mdiff_on_univ contMDiffOn_univ
theorem smoothOn_univ : SmoothOn I I' f univ ↔ Smooth I I' f :=
contMDiffOn_univ
#align smooth_on_univ smoothOn_univ
/-- One can reformulate smoothness within a set at a point as continuity within this set at this
point, and smoothness in the corresponding extended chart. -/
theorem contMDiffWithinAt_iff :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧
ContDiffWithinAt 𝕜 n (extChartAt I' (f x) ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).symm ⁻¹' s ∩ range I) (extChartAt I x x) := by
simp_rw [ContMDiffWithinAt, liftPropWithinAt_iff']; rfl
#align cont_mdiff_within_at_iff contMDiffWithinAt_iff
/-- One can reformulate smoothness within a set at a point as continuity within this set at this
point, and smoothness in the corresponding extended chart. This form states smoothness of `f`
written in such a way that the set is restricted to lie within the domain/codomain of the
corresponding charts.
Even though this expression is more complicated than the one in `contMDiffWithinAt_iff`, it is
a smaller set, but their germs at `extChartAt I x x` are equal. It is sometimes useful to rewrite
using this in the goal.
-/
theorem contMDiffWithinAt_iff' :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧
ContDiffWithinAt 𝕜 n (extChartAt I' (f x) ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).target ∩
(extChartAt I x).symm ⁻¹' (s ∩ f ⁻¹' (extChartAt I' (f x)).source))
(extChartAt I x x) := by
simp only [ContMDiffWithinAt, liftPropWithinAt_iff']
exact and_congr_right fun hc => contDiffWithinAt_congr_nhds <|
hc.nhdsWithin_extChartAt_symm_preimage_inter_range I I'
#align cont_mdiff_within_at_iff' contMDiffWithinAt_iff'
/-- One can reformulate smoothness within a set at a point as continuity within this set at this
point, and smoothness in the corresponding extended chart in the target. -/
theorem contMDiffWithinAt_iff_target :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧ ContMDiffWithinAt I 𝓘(𝕜, E') n (extChartAt I' (f x) ∘ f) s x := by
simp_rw [ContMDiffWithinAt, liftPropWithinAt_iff', ← and_assoc]
have cont :
ContinuousWithinAt f s x ∧ ContinuousWithinAt (extChartAt I' (f x) ∘ f) s x ↔
ContinuousWithinAt f s x :=
and_iff_left_of_imp <| (continuousAt_extChartAt _ _).comp_continuousWithinAt
simp_rw [cont, ContDiffWithinAtProp, extChartAt, PartialHomeomorph.extend, PartialEquiv.coe_trans,
ModelWithCorners.toPartialEquiv_coe, PartialHomeomorph.coe_coe, modelWithCornersSelf_coe,
chartAt_self_eq, PartialHomeomorph.refl_apply, id_comp]
rfl
#align cont_mdiff_within_at_iff_target contMDiffWithinAt_iff_target
theorem smoothWithinAt_iff :
SmoothWithinAt I I' f s x ↔
ContinuousWithinAt f s x ∧
ContDiffWithinAt 𝕜 ∞ (extChartAt I' (f x) ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).symm ⁻¹' s ∩ range I) (extChartAt I x x) :=
contMDiffWithinAt_iff
#align smooth_within_at_iff smoothWithinAt_iff
theorem smoothWithinAt_iff_target :
SmoothWithinAt I I' f s x ↔
ContinuousWithinAt f s x ∧ SmoothWithinAt I 𝓘(𝕜, E') (extChartAt I' (f x) ∘ f) s x :=
contMDiffWithinAt_iff_target
#align smooth_within_at_iff_target smoothWithinAt_iff_target
theorem contMDiffAt_iff_target {x : M} :
ContMDiffAt I I' n f x ↔
ContinuousAt f x ∧ ContMDiffAt I 𝓘(𝕜, E') n (extChartAt I' (f x) ∘ f) x := by
rw [ContMDiffAt, ContMDiffAt, contMDiffWithinAt_iff_target, continuousWithinAt_univ]
#align cont_mdiff_at_iff_target contMDiffAt_iff_target
theorem smoothAt_iff_target {x : M} :
SmoothAt I I' f x ↔ ContinuousAt f x ∧ SmoothAt I 𝓘(𝕜, E') (extChartAt I' (f x) ∘ f) x :=
contMDiffAt_iff_target
#align smooth_at_iff_target smoothAt_iff_target
theorem contMDiffWithinAt_iff_of_mem_maximalAtlas {x : M} (he : e ∈ maximalAtlas I M)
(he' : e' ∈ maximalAtlas I' M') (hx : x ∈ e.source) (hy : f x ∈ e'.source) :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧
ContDiffWithinAt 𝕜 n (e'.extend I' ∘ f ∘ (e.extend I).symm)
((e.extend I).symm ⁻¹' s ∩ range I) (e.extend I x) :=
(contDiffWithinAt_localInvariantProp I I' n).liftPropWithinAt_indep_chart he hx he' hy
#align cont_mdiff_within_at_iff_of_mem_maximal_atlas contMDiffWithinAt_iff_of_mem_maximalAtlas
/-- An alternative formulation of `contMDiffWithinAt_iff_of_mem_maximalAtlas`
if the set if `s` lies in `e.source`. -/
theorem contMDiffWithinAt_iff_image {x : M} (he : e ∈ maximalAtlas I M)
(he' : e' ∈ maximalAtlas I' M') (hs : s ⊆ e.source) (hx : x ∈ e.source) (hy : f x ∈ e'.source) :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧
ContDiffWithinAt 𝕜 n (e'.extend I' ∘ f ∘ (e.extend I).symm) (e.extend I '' s)
(e.extend I x) := by
rw [contMDiffWithinAt_iff_of_mem_maximalAtlas he he' hx hy, and_congr_right_iff]
refine fun _ => contDiffWithinAt_congr_nhds ?_
simp_rw [nhdsWithin_eq_iff_eventuallyEq, e.extend_symm_preimage_inter_range_eventuallyEq I hs hx]
#align cont_mdiff_within_at_iff_image contMDiffWithinAt_iff_image
/-- One can reformulate smoothness within a set at a point as continuity within this set at this
point, and smoothness in any chart containing that point. -/
theorem contMDiffWithinAt_iff_of_mem_source {x' : M} {y : M'} (hx : x' ∈ (chartAt H x).source)
(hy : f x' ∈ (chartAt H' y).source) :
ContMDiffWithinAt I I' n f s x' ↔
ContinuousWithinAt f s x' ∧
ContDiffWithinAt 𝕜 n (extChartAt I' y ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).symm ⁻¹' s ∩ range I) (extChartAt I x x') :=
contMDiffWithinAt_iff_of_mem_maximalAtlas (chart_mem_maximalAtlas _ x)
(chart_mem_maximalAtlas _ y) hx hy
#align cont_mdiff_within_at_iff_of_mem_source contMDiffWithinAt_iff_of_mem_source
theorem contMDiffWithinAt_iff_of_mem_source' {x' : M} {y : M'} (hx : x' ∈ (chartAt H x).source)
(hy : f x' ∈ (chartAt H' y).source) :
ContMDiffWithinAt I I' n f s x' ↔
ContinuousWithinAt f s x' ∧
ContDiffWithinAt 𝕜 n (extChartAt I' y ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).target ∩ (extChartAt I x).symm ⁻¹' (s ∩ f ⁻¹' (extChartAt I' y).source))
(extChartAt I x x') := by
refine (contMDiffWithinAt_iff_of_mem_source hx hy).trans ?_
rw [← extChartAt_source I] at hx
rw [← extChartAt_source I'] at hy
rw [and_congr_right_iff]
set e := extChartAt I x; set e' := extChartAt I' (f x)
refine fun hc => contDiffWithinAt_congr_nhds ?_
rw [← e.image_source_inter_eq', ← map_extChartAt_nhdsWithin_eq_image' I hx, ←
map_extChartAt_nhdsWithin' I hx, inter_comm, nhdsWithin_inter_of_mem]
exact hc (extChartAt_source_mem_nhds' _ hy)
#align cont_mdiff_within_at_iff_of_mem_source' contMDiffWithinAt_iff_of_mem_source'
theorem contMDiffAt_iff_of_mem_source {x' : M} {y : M'} (hx : x' ∈ (chartAt H x).source)
(hy : f x' ∈ (chartAt H' y).source) :
ContMDiffAt I I' n f x' ↔
ContinuousAt f x' ∧
ContDiffWithinAt 𝕜 n (extChartAt I' y ∘ f ∘ (extChartAt I x).symm) (range I)
(extChartAt I x x') :=
(contMDiffWithinAt_iff_of_mem_source hx hy).trans <| by
rw [continuousWithinAt_univ, preimage_univ, univ_inter]
#align cont_mdiff_at_iff_of_mem_source contMDiffAt_iff_of_mem_source
theorem contMDiffWithinAt_iff_target_of_mem_source {x : M} {y : M'}
(hy : f x ∈ (chartAt H' y).source) :
ContMDiffWithinAt I I' n f s x ↔
ContinuousWithinAt f s x ∧ ContMDiffWithinAt I 𝓘(𝕜, E') n (extChartAt I' y ∘ f) s x := by
simp_rw [ContMDiffWithinAt]
rw [(contDiffWithinAt_localInvariantProp I I' n).liftPropWithinAt_indep_chart_target
(chart_mem_maximalAtlas I' y) hy,
and_congr_right]
intro hf
simp_rw [StructureGroupoid.liftPropWithinAt_self_target]
simp_rw [((chartAt H' y).continuousAt hy).comp_continuousWithinAt hf]
rw [← extChartAt_source I'] at hy
simp_rw [(continuousAt_extChartAt' I' hy).comp_continuousWithinAt hf]
rfl
#align cont_mdiff_within_at_iff_target_of_mem_source contMDiffWithinAt_iff_target_of_mem_source
theorem contMDiffAt_iff_target_of_mem_source {x : M} {y : M'} (hy : f x ∈ (chartAt H' y).source) :
ContMDiffAt I I' n f x ↔
ContinuousAt f x ∧ ContMDiffAt I 𝓘(𝕜, E') n (extChartAt I' y ∘ f) x := by
rw [ContMDiffAt, contMDiffWithinAt_iff_target_of_mem_source hy, continuousWithinAt_univ,
ContMDiffAt]
#align cont_mdiff_at_iff_target_of_mem_source contMDiffAt_iff_target_of_mem_source
| Mathlib/Geometry/Manifold/ContMDiff/Defs.lean | 473 | 484 | theorem contMDiffWithinAt_iff_source_of_mem_maximalAtlas (he : e ∈ maximalAtlas I M)
(hx : x ∈ e.source) :
ContMDiffWithinAt I I' n f s x ↔
ContMDiffWithinAt 𝓘(𝕜, E) I' n (f ∘ (e.extend I).symm) ((e.extend I).symm ⁻¹' s ∩ range I)
(e.extend I x) := by |
have h2x := hx; rw [← e.extend_source I] at h2x
simp_rw [ContMDiffWithinAt,
(contDiffWithinAt_localInvariantProp I I' n).liftPropWithinAt_indep_chart_source he hx,
StructureGroupoid.liftPropWithinAt_self_source,
e.extend_symm_continuousWithinAt_comp_right_iff, contDiffWithinAtProp_self_source,
ContDiffWithinAtProp, Function.comp, e.left_inv hx, (e.extend I).left_inv h2x]
rfl
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel,
Rémy Degenne, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.Complex.Log
#align_import analysis.special_functions.pow.complex from "leanprover-community/mathlib"@"4fa54b337f7d52805480306db1b1439c741848c8"
/-! # Power function on `ℂ`
We construct the power functions `x ^ y`, where `x` and `y` are complex numbers.
-/
open scoped Classical
open Real Topology Filter ComplexConjugate Finset Set
namespace Complex
/-- The complex power function `x ^ y`, given by `x ^ y = exp(y log x)` (where `log` is the
principal determination of the logarithm), unless `x = 0` where one sets `0 ^ 0 = 1` and
`0 ^ y = 0` for `y ≠ 0`. -/
noncomputable def cpow (x y : ℂ) : ℂ :=
if x = 0 then if y = 0 then 1 else 0 else exp (log x * y)
#align complex.cpow Complex.cpow
noncomputable instance : Pow ℂ ℂ :=
⟨cpow⟩
@[simp]
theorem cpow_eq_pow (x y : ℂ) : cpow x y = x ^ y :=
rfl
#align complex.cpow_eq_pow Complex.cpow_eq_pow
theorem cpow_def (x y : ℂ) : x ^ y = if x = 0 then if y = 0 then 1 else 0 else exp (log x * y) :=
rfl
#align complex.cpow_def Complex.cpow_def
theorem cpow_def_of_ne_zero {x : ℂ} (hx : x ≠ 0) (y : ℂ) : x ^ y = exp (log x * y) :=
if_neg hx
#align complex.cpow_def_of_ne_zero Complex.cpow_def_of_ne_zero
@[simp]
theorem cpow_zero (x : ℂ) : x ^ (0 : ℂ) = 1 := by simp [cpow_def]
#align complex.cpow_zero Complex.cpow_zero
@[simp]
theorem cpow_eq_zero_iff (x y : ℂ) : x ^ y = 0 ↔ x = 0 ∧ y ≠ 0 := by
simp only [cpow_def]
split_ifs <;> simp [*, exp_ne_zero]
#align complex.cpow_eq_zero_iff Complex.cpow_eq_zero_iff
@[simp]
theorem zero_cpow {x : ℂ} (h : x ≠ 0) : (0 : ℂ) ^ x = 0 := by simp [cpow_def, *]
#align complex.zero_cpow Complex.zero_cpow
theorem zero_cpow_eq_iff {x : ℂ} {a : ℂ} : (0 : ℂ) ^ x = a ↔ x ≠ 0 ∧ a = 0 ∨ x = 0 ∧ a = 1 := by
constructor
· intro hyp
simp only [cpow_def, eq_self_iff_true, if_true] at hyp
by_cases h : x = 0
· subst h
simp only [if_true, eq_self_iff_true] at hyp
right
exact ⟨rfl, hyp.symm⟩
· rw [if_neg h] at hyp
left
exact ⟨h, hyp.symm⟩
· rintro (⟨h, rfl⟩ | ⟨rfl, rfl⟩)
· exact zero_cpow h
· exact cpow_zero _
#align complex.zero_cpow_eq_iff Complex.zero_cpow_eq_iff
theorem eq_zero_cpow_iff {x : ℂ} {a : ℂ} : a = (0 : ℂ) ^ x ↔ x ≠ 0 ∧ a = 0 ∨ x = 0 ∧ a = 1 := by
rw [← zero_cpow_eq_iff, eq_comm]
#align complex.eq_zero_cpow_iff Complex.eq_zero_cpow_iff
@[simp]
theorem cpow_one (x : ℂ) : x ^ (1 : ℂ) = x :=
if hx : x = 0 then by simp [hx, cpow_def]
else by rw [cpow_def, if_neg (one_ne_zero : (1 : ℂ) ≠ 0), if_neg hx, mul_one, exp_log hx]
#align complex.cpow_one Complex.cpow_one
@[simp]
theorem one_cpow (x : ℂ) : (1 : ℂ) ^ x = 1 := by
rw [cpow_def]
split_ifs <;> simp_all [one_ne_zero]
#align complex.one_cpow Complex.one_cpow
theorem cpow_add {x : ℂ} (y z : ℂ) (hx : x ≠ 0) : x ^ (y + z) = x ^ y * x ^ z := by
simp only [cpow_def, ite_mul, boole_mul, mul_ite, mul_boole]
simp_all [exp_add, mul_add]
#align complex.cpow_add Complex.cpow_add
theorem cpow_mul {x y : ℂ} (z : ℂ) (h₁ : -π < (log x * y).im) (h₂ : (log x * y).im ≤ π) :
x ^ (y * z) = (x ^ y) ^ z := by
simp only [cpow_def]
split_ifs <;> simp_all [exp_ne_zero, log_exp h₁ h₂, mul_assoc]
#align complex.cpow_mul Complex.cpow_mul
theorem cpow_neg (x y : ℂ) : x ^ (-y) = (x ^ y)⁻¹ := by
simp only [cpow_def, neg_eq_zero, mul_neg]
split_ifs <;> simp [exp_neg]
#align complex.cpow_neg Complex.cpow_neg
theorem cpow_sub {x : ℂ} (y z : ℂ) (hx : x ≠ 0) : x ^ (y - z) = x ^ y / x ^ z := by
rw [sub_eq_add_neg, cpow_add _ _ hx, cpow_neg, div_eq_mul_inv]
#align complex.cpow_sub Complex.cpow_sub
theorem cpow_neg_one (x : ℂ) : x ^ (-1 : ℂ) = x⁻¹ := by simpa using cpow_neg x 1
#align complex.cpow_neg_one Complex.cpow_neg_one
/-- See also `Complex.cpow_int_mul'`. -/
lemma cpow_int_mul (x : ℂ) (n : ℤ) (y : ℂ) : x ^ (n * y) = (x ^ y) ^ n := by
rcases eq_or_ne x 0 with rfl | hx
· rcases eq_or_ne n 0 with rfl | hn
· simp
· rcases eq_or_ne y 0 with rfl | hy <;> simp [*, zero_zpow]
· rw [cpow_def_of_ne_zero hx, cpow_def_of_ne_zero hx, mul_left_comm, exp_int_mul]
lemma cpow_mul_int (x y : ℂ) (n : ℤ) : x ^ (y * n) = (x ^ y) ^ n := by rw [mul_comm, cpow_int_mul]
lemma cpow_nat_mul (x : ℂ) (n : ℕ) (y : ℂ) : x ^ (n * y) = (x ^ y) ^ n :=
mod_cast cpow_int_mul x n y
/-- See Note [no_index around OfNat.ofNat] -/
lemma cpow_ofNat_mul (x : ℂ) (n : ℕ) [n.AtLeastTwo] (y : ℂ) :
x ^ (no_index (OfNat.ofNat n) * y) = (x ^ y) ^ (OfNat.ofNat n : ℕ) :=
cpow_nat_mul x n y
lemma cpow_mul_nat (x y : ℂ) (n : ℕ) : x ^ (y * n) = (x ^ y) ^ n := by
rw [mul_comm, cpow_nat_mul]
/-- See Note [no_index around OfNat.ofNat] -/
lemma cpow_mul_ofNat (x y : ℂ) (n : ℕ) [n.AtLeastTwo] :
x ^ (y * no_index (OfNat.ofNat n)) = (x ^ y) ^ (OfNat.ofNat n : ℕ) :=
cpow_mul_nat x y n
@[simp, norm_cast]
theorem cpow_natCast (x : ℂ) (n : ℕ) : x ^ (n : ℂ) = x ^ n := by simpa using cpow_nat_mul x n 1
#align complex.cpow_nat_cast Complex.cpow_natCast
@[deprecated (since := "2024-04-17")]
alias cpow_nat_cast := cpow_natCast
/-- See Note [no_index around OfNat.ofNat] -/
@[simp]
lemma cpow_ofNat (x : ℂ) (n : ℕ) [n.AtLeastTwo] :
x ^ (no_index (OfNat.ofNat n) : ℂ) = x ^ (OfNat.ofNat n : ℕ) :=
cpow_natCast x n
theorem cpow_two (x : ℂ) : x ^ (2 : ℂ) = x ^ (2 : ℕ) := cpow_ofNat x 2
#align complex.cpow_two Complex.cpow_two
@[simp, norm_cast]
theorem cpow_intCast (x : ℂ) (n : ℤ) : x ^ (n : ℂ) = x ^ n := by simpa using cpow_int_mul x n 1
#align complex.cpow_int_cast Complex.cpow_intCast
@[deprecated (since := "2024-04-17")]
alias cpow_int_cast := cpow_intCast
@[simp]
theorem cpow_nat_inv_pow (x : ℂ) {n : ℕ} (hn : n ≠ 0) : (x ^ (n⁻¹ : ℂ)) ^ n = x := by
rw [← cpow_nat_mul, mul_inv_cancel, cpow_one]
assumption_mod_cast
#align complex.cpow_nat_inv_pow Complex.cpow_nat_inv_pow
/-- See Note [no_index around OfNat.ofNat] -/
@[simp]
lemma cpow_ofNat_inv_pow (x : ℂ) (n : ℕ) [n.AtLeastTwo] :
(x ^ ((no_index (OfNat.ofNat n) : ℂ)⁻¹)) ^ (no_index (OfNat.ofNat n) : ℕ) = x :=
cpow_nat_inv_pow _ (NeZero.ne n)
/-- A version of `Complex.cpow_int_mul` with RHS that matches `Complex.cpow_mul`.
The assumptions on the arguments are needed
because the equality fails, e.g., for `x = -I`, `n = 2`, `y = 1/2`. -/
lemma cpow_int_mul' {x : ℂ} {n : ℤ} (hlt : -π < n * x.arg) (hle : n * x.arg ≤ π) (y : ℂ) :
x ^ (n * y) = (x ^ n) ^ y := by
rw [mul_comm] at hlt hle
rw [cpow_mul, cpow_intCast] <;> simpa [log_im]
/-- A version of `Complex.cpow_nat_mul` with RHS that matches `Complex.cpow_mul`.
The assumptions on the arguments are needed
because the equality fails, e.g., for `x = -I`, `n = 2`, `y = 1/2`. -/
lemma cpow_nat_mul' {x : ℂ} {n : ℕ} (hlt : -π < n * x.arg) (hle : n * x.arg ≤ π) (y : ℂ) :
x ^ (n * y) = (x ^ n) ^ y :=
cpow_int_mul' hlt hle y
lemma cpow_ofNat_mul' {x : ℂ} {n : ℕ} [n.AtLeastTwo] (hlt : -π < OfNat.ofNat n * x.arg)
(hle : OfNat.ofNat n * x.arg ≤ π) (y : ℂ) :
x ^ (OfNat.ofNat n * y) = (x ^ (OfNat.ofNat n : ℕ)) ^ y :=
cpow_nat_mul' hlt hle y
lemma pow_cpow_nat_inv {x : ℂ} {n : ℕ} (h₀ : n ≠ 0) (hlt : -(π / n) < x.arg) (hle : x.arg ≤ π / n) :
(x ^ n) ^ (n⁻¹ : ℂ) = x := by
rw [← cpow_nat_mul', mul_inv_cancel (Nat.cast_ne_zero.2 h₀), cpow_one]
· rwa [← div_lt_iff' (Nat.cast_pos.2 h₀.bot_lt), neg_div]
· rwa [← le_div_iff' (Nat.cast_pos.2 h₀.bot_lt)]
lemma pow_cpow_ofNat_inv {x : ℂ} {n : ℕ} [n.AtLeastTwo] (hlt : -(π / OfNat.ofNat n) < x.arg)
(hle : x.arg ≤ π / OfNat.ofNat n) :
(x ^ (OfNat.ofNat n : ℕ)) ^ ((OfNat.ofNat n : ℂ)⁻¹) = x :=
pow_cpow_nat_inv (NeZero.ne n) hlt hle
/-- See also `Complex.pow_cpow_ofNat_inv` for a version that also works for `x * I`, `0 ≤ x`. -/
lemma sq_cpow_two_inv {x : ℂ} (hx : 0 < x.re) : (x ^ (2 : ℕ)) ^ (2⁻¹ : ℂ) = x :=
pow_cpow_ofNat_inv (neg_pi_div_two_lt_arg_iff.2 <| .inl hx)
(arg_le_pi_div_two_iff.2 <| .inl hx.le)
theorem mul_cpow_ofReal_nonneg {a b : ℝ} (ha : 0 ≤ a) (hb : 0 ≤ b) (r : ℂ) :
((a : ℂ) * (b : ℂ)) ^ r = (a : ℂ) ^ r * (b : ℂ) ^ r := by
rcases eq_or_ne r 0 with (rfl | hr)
· simp only [cpow_zero, mul_one]
rcases eq_or_lt_of_le ha with (rfl | ha')
· rw [ofReal_zero, zero_mul, zero_cpow hr, zero_mul]
rcases eq_or_lt_of_le hb with (rfl | hb')
· rw [ofReal_zero, mul_zero, zero_cpow hr, mul_zero]
have ha'' : (a : ℂ) ≠ 0 := ofReal_ne_zero.mpr ha'.ne'
have hb'' : (b : ℂ) ≠ 0 := ofReal_ne_zero.mpr hb'.ne'
rw [cpow_def_of_ne_zero (mul_ne_zero ha'' hb''), log_ofReal_mul ha' hb'', ofReal_log ha,
add_mul, exp_add, ← cpow_def_of_ne_zero ha'', ← cpow_def_of_ne_zero hb'']
#align complex.mul_cpow_of_real_nonneg Complex.mul_cpow_ofReal_nonneg
lemma natCast_mul_natCast_cpow (m n : ℕ) (s : ℂ) : (m * n : ℂ) ^ s = m ^ s * n ^ s :=
ofReal_natCast m ▸ ofReal_natCast n ▸ mul_cpow_ofReal_nonneg m.cast_nonneg n.cast_nonneg s
lemma natCast_cpow_natCast_mul (n m : ℕ) (z : ℂ) : (n : ℂ) ^ (m * z) = ((n : ℂ) ^ m) ^ z := by
refine cpow_nat_mul' (x := n) (n := m) ?_ ?_ z
· simp only [natCast_arg, mul_zero, Left.neg_neg_iff, pi_pos]
· simp only [natCast_arg, mul_zero, pi_pos.le]
theorem inv_cpow_eq_ite (x : ℂ) (n : ℂ) :
x⁻¹ ^ n = if x.arg = π then conj (x ^ conj n)⁻¹ else (x ^ n)⁻¹ := by
simp_rw [Complex.cpow_def, log_inv_eq_ite, inv_eq_zero, map_eq_zero, ite_mul, neg_mul,
RCLike.conj_inv, apply_ite conj, apply_ite exp, apply_ite Inv.inv, map_zero, map_one, exp_neg,
inv_one, inv_zero, ← exp_conj, map_mul, conj_conj]
split_ifs with hx hn ha ha <;> rfl
#align complex.inv_cpow_eq_ite Complex.inv_cpow_eq_ite
theorem inv_cpow (x : ℂ) (n : ℂ) (hx : x.arg ≠ π) : x⁻¹ ^ n = (x ^ n)⁻¹ := by
rw [inv_cpow_eq_ite, if_neg hx]
#align complex.inv_cpow Complex.inv_cpow
/-- `Complex.inv_cpow_eq_ite` with the `ite` on the other side. -/
theorem inv_cpow_eq_ite' (x : ℂ) (n : ℂ) :
(x ^ n)⁻¹ = if x.arg = π then conj (x⁻¹ ^ conj n) else x⁻¹ ^ n := by
rw [inv_cpow_eq_ite, apply_ite conj, conj_conj, conj_conj]
split_ifs with h
· rfl
· rw [inv_cpow _ _ h]
#align complex.inv_cpow_eq_ite' Complex.inv_cpow_eq_ite'
| Mathlib/Analysis/SpecialFunctions/Pow/Complex.lean | 256 | 260 | theorem conj_cpow_eq_ite (x : ℂ) (n : ℂ) :
conj x ^ n = if x.arg = π then x ^ n else conj (x ^ conj n) := by |
simp_rw [cpow_def, map_eq_zero, apply_ite conj, map_one, map_zero, ← exp_conj, map_mul, conj_conj,
log_conj_eq_ite]
split_ifs with hcx hn hx <;> rfl
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.Algebra.Group.Units
import Mathlib.Algebra.GroupWithZero.Basic
import Mathlib.Logic.Equiv.Defs
import Mathlib.Tactic.Contrapose
import Mathlib.Tactic.Nontriviality
import Mathlib.Tactic.Spread
import Mathlib.Util.AssertExists
#align_import algebra.group_with_zero.units.basic from "leanprover-community/mathlib"@"df5e9937a06fdd349fc60106f54b84d47b1434f0"
/-!
# Lemmas about units in a `MonoidWithZero` or a `GroupWithZero`.
We also define `Ring.inverse`, a globally defined function on any ring
(in fact any `MonoidWithZero`), which inverts units and sends non-units to zero.
-/
-- Guard against import creep
assert_not_exists Multiplicative
assert_not_exists DenselyOrdered
variable {α M₀ G₀ M₀' G₀' F F' : Type*}
variable [MonoidWithZero M₀]
namespace Units
/-- An element of the unit group of a nonzero monoid with zero represented as an element
of the monoid is nonzero. -/
@[simp]
theorem ne_zero [Nontrivial M₀] (u : M₀ˣ) : (u : M₀) ≠ 0 :=
left_ne_zero_of_mul_eq_one u.mul_inv
#align units.ne_zero Units.ne_zero
-- We can't use `mul_eq_zero` + `Units.ne_zero` in the next two lemmas because we don't assume
-- `Nonzero M₀`.
@[simp]
theorem mul_left_eq_zero (u : M₀ˣ) {a : M₀} : a * u = 0 ↔ a = 0 :=
⟨fun h => by simpa using mul_eq_zero_of_left h ↑u⁻¹, fun h => mul_eq_zero_of_left h u⟩
#align units.mul_left_eq_zero Units.mul_left_eq_zero
@[simp]
theorem mul_right_eq_zero (u : M₀ˣ) {a : M₀} : ↑u * a = 0 ↔ a = 0 :=
⟨fun h => by simpa using mul_eq_zero_of_right (↑u⁻¹) h, mul_eq_zero_of_right (u : M₀)⟩
#align units.mul_right_eq_zero Units.mul_right_eq_zero
end Units
namespace IsUnit
theorem ne_zero [Nontrivial M₀] {a : M₀} (ha : IsUnit a) : a ≠ 0 :=
let ⟨u, hu⟩ := ha
hu ▸ u.ne_zero
#align is_unit.ne_zero IsUnit.ne_zero
theorem mul_right_eq_zero {a b : M₀} (ha : IsUnit a) : a * b = 0 ↔ b = 0 :=
let ⟨u, hu⟩ := ha
hu ▸ u.mul_right_eq_zero
#align is_unit.mul_right_eq_zero IsUnit.mul_right_eq_zero
theorem mul_left_eq_zero {a b : M₀} (hb : IsUnit b) : a * b = 0 ↔ a = 0 :=
let ⟨u, hu⟩ := hb
hu ▸ u.mul_left_eq_zero
#align is_unit.mul_left_eq_zero IsUnit.mul_left_eq_zero
end IsUnit
@[simp]
theorem isUnit_zero_iff : IsUnit (0 : M₀) ↔ (0 : M₀) = 1 :=
⟨fun ⟨⟨_, a, (a0 : 0 * a = 1), _⟩, rfl⟩ => by rwa [zero_mul] at a0, fun h =>
@isUnit_of_subsingleton _ _ (subsingleton_of_zero_eq_one h) 0⟩
#align is_unit_zero_iff isUnit_zero_iff
-- Porting note: removed `simp` tag because `simpNF` says it's redundant
theorem not_isUnit_zero [Nontrivial M₀] : ¬IsUnit (0 : M₀) :=
mt isUnit_zero_iff.1 zero_ne_one
#align not_is_unit_zero not_isUnit_zero
namespace Ring
open scoped Classical
/-- Introduce a function `inverse` on a monoid with zero `M₀`, which sends `x` to `x⁻¹` if `x` is
invertible and to `0` otherwise. This definition is somewhat ad hoc, but one needs a fully (rather
than partially) defined inverse function for some purposes, including for calculus.
Note that while this is in the `Ring` namespace for brevity, it requires the weaker assumption
`MonoidWithZero M₀` instead of `Ring M₀`. -/
noncomputable def inverse : M₀ → M₀ := fun x => if h : IsUnit x then ((h.unit⁻¹ : M₀ˣ) : M₀) else 0
#align ring.inverse Ring.inverse
/-- By definition, if `x` is invertible then `inverse x = x⁻¹`. -/
@[simp]
theorem inverse_unit (u : M₀ˣ) : inverse (u : M₀) = (u⁻¹ : M₀ˣ) := by
rw [inverse, dif_pos u.isUnit, IsUnit.unit_of_val_units]
#align ring.inverse_unit Ring.inverse_unit
/-- By definition, if `x` is not invertible then `inverse x = 0`. -/
@[simp]
theorem inverse_non_unit (x : M₀) (h : ¬IsUnit x) : inverse x = 0 :=
dif_neg h
#align ring.inverse_non_unit Ring.inverse_non_unit
theorem mul_inverse_cancel (x : M₀) (h : IsUnit x) : x * inverse x = 1 := by
rcases h with ⟨u, rfl⟩
rw [inverse_unit, Units.mul_inv]
#align ring.mul_inverse_cancel Ring.mul_inverse_cancel
theorem inverse_mul_cancel (x : M₀) (h : IsUnit x) : inverse x * x = 1 := by
rcases h with ⟨u, rfl⟩
rw [inverse_unit, Units.inv_mul]
#align ring.inverse_mul_cancel Ring.inverse_mul_cancel
theorem mul_inverse_cancel_right (x y : M₀) (h : IsUnit x) : y * x * inverse x = y := by
rw [mul_assoc, mul_inverse_cancel x h, mul_one]
#align ring.mul_inverse_cancel_right Ring.mul_inverse_cancel_right
theorem inverse_mul_cancel_right (x y : M₀) (h : IsUnit x) : y * inverse x * x = y := by
rw [mul_assoc, inverse_mul_cancel x h, mul_one]
#align ring.inverse_mul_cancel_right Ring.inverse_mul_cancel_right
| Mathlib/Algebra/GroupWithZero/Units/Basic.lean | 126 | 127 | theorem mul_inverse_cancel_left (x y : M₀) (h : IsUnit x) : x * (inverse x * y) = y := by |
rw [← mul_assoc, mul_inverse_cancel x h, one_mul]
|
/-
Copyright (c) 2014 Robert Lewis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Robert Lewis, Leonardo de Moura, Mario Carneiro, Floris van Doorn
-/
import Mathlib.Algebra.Field.Basic
import Mathlib.Algebra.GroupWithZero.Units.Equiv
import Mathlib.Algebra.Order.Field.Defs
import Mathlib.Algebra.Order.Ring.Abs
import Mathlib.Order.Bounds.OrderIso
import Mathlib.Tactic.Positivity.Core
#align_import algebra.order.field.basic from "leanprover-community/mathlib"@"84771a9f5f0bd5e5d6218811556508ddf476dcbd"
/-!
# Lemmas about linear ordered (semi)fields
-/
open Function OrderDual
variable {ι α β : Type*}
section LinearOrderedSemifield
variable [LinearOrderedSemifield α] {a b c d e : α} {m n : ℤ}
/-- `Equiv.mulLeft₀` as an order_iso. -/
@[simps! (config := { simpRhs := true })]
def OrderIso.mulLeft₀ (a : α) (ha : 0 < a) : α ≃o α :=
{ Equiv.mulLeft₀ a ha.ne' with map_rel_iff' := @fun _ _ => mul_le_mul_left ha }
#align order_iso.mul_left₀ OrderIso.mulLeft₀
#align order_iso.mul_left₀_symm_apply OrderIso.mulLeft₀_symm_apply
#align order_iso.mul_left₀_apply OrderIso.mulLeft₀_apply
/-- `Equiv.mulRight₀` as an order_iso. -/
@[simps! (config := { simpRhs := true })]
def OrderIso.mulRight₀ (a : α) (ha : 0 < a) : α ≃o α :=
{ Equiv.mulRight₀ a ha.ne' with map_rel_iff' := @fun _ _ => mul_le_mul_right ha }
#align order_iso.mul_right₀ OrderIso.mulRight₀
#align order_iso.mul_right₀_symm_apply OrderIso.mulRight₀_symm_apply
#align order_iso.mul_right₀_apply OrderIso.mulRight₀_apply
/-!
### Relating one division with another term.
-/
theorem le_div_iff (hc : 0 < c) : a ≤ b / c ↔ a * c ≤ b :=
⟨fun h => div_mul_cancel₀ b (ne_of_lt hc).symm ▸ mul_le_mul_of_nonneg_right h hc.le, fun h =>
calc
a = a * c * (1 / c) := mul_mul_div a (ne_of_lt hc).symm
_ ≤ b * (1 / c) := mul_le_mul_of_nonneg_right h (one_div_pos.2 hc).le
_ = b / c := (div_eq_mul_one_div b c).symm
⟩
#align le_div_iff le_div_iff
theorem le_div_iff' (hc : 0 < c) : a ≤ b / c ↔ c * a ≤ b := by rw [mul_comm, le_div_iff hc]
#align le_div_iff' le_div_iff'
theorem div_le_iff (hb : 0 < b) : a / b ≤ c ↔ a ≤ c * b :=
⟨fun h =>
calc
a = a / b * b := by rw [div_mul_cancel₀ _ (ne_of_lt hb).symm]
_ ≤ c * b := mul_le_mul_of_nonneg_right h hb.le
,
fun h =>
calc
a / b = a * (1 / b) := div_eq_mul_one_div a b
_ ≤ c * b * (1 / b) := mul_le_mul_of_nonneg_right h (one_div_pos.2 hb).le
_ = c * b / b := (div_eq_mul_one_div (c * b) b).symm
_ = c := by refine (div_eq_iff (ne_of_gt hb)).mpr rfl
⟩
#align div_le_iff div_le_iff
theorem div_le_iff' (hb : 0 < b) : a / b ≤ c ↔ a ≤ b * c := by rw [mul_comm, div_le_iff hb]
#align div_le_iff' div_le_iff'
lemma div_le_comm₀ (hb : 0 < b) (hc : 0 < c) : a / b ≤ c ↔ a / c ≤ b := by
rw [div_le_iff hb, div_le_iff' hc]
theorem lt_div_iff (hc : 0 < c) : a < b / c ↔ a * c < b :=
lt_iff_lt_of_le_iff_le <| div_le_iff hc
#align lt_div_iff lt_div_iff
theorem lt_div_iff' (hc : 0 < c) : a < b / c ↔ c * a < b := by rw [mul_comm, lt_div_iff hc]
#align lt_div_iff' lt_div_iff'
theorem div_lt_iff (hc : 0 < c) : b / c < a ↔ b < a * c :=
lt_iff_lt_of_le_iff_le (le_div_iff hc)
#align div_lt_iff div_lt_iff
theorem div_lt_iff' (hc : 0 < c) : b / c < a ↔ b < c * a := by rw [mul_comm, div_lt_iff hc]
#align div_lt_iff' div_lt_iff'
lemma div_lt_comm₀ (hb : 0 < b) (hc : 0 < c) : a / b < c ↔ a / c < b := by
rw [div_lt_iff hb, div_lt_iff' hc]
theorem inv_mul_le_iff (h : 0 < b) : b⁻¹ * a ≤ c ↔ a ≤ b * c := by
rw [inv_eq_one_div, mul_comm, ← div_eq_mul_one_div]
exact div_le_iff' h
#align inv_mul_le_iff inv_mul_le_iff
theorem inv_mul_le_iff' (h : 0 < b) : b⁻¹ * a ≤ c ↔ a ≤ c * b := by rw [inv_mul_le_iff h, mul_comm]
#align inv_mul_le_iff' inv_mul_le_iff'
theorem mul_inv_le_iff (h : 0 < b) : a * b⁻¹ ≤ c ↔ a ≤ b * c := by rw [mul_comm, inv_mul_le_iff h]
#align mul_inv_le_iff mul_inv_le_iff
theorem mul_inv_le_iff' (h : 0 < b) : a * b⁻¹ ≤ c ↔ a ≤ c * b := by rw [mul_comm, inv_mul_le_iff' h]
#align mul_inv_le_iff' mul_inv_le_iff'
theorem div_self_le_one (a : α) : a / a ≤ 1 :=
if h : a = 0 then by simp [h] else by simp [h]
#align div_self_le_one div_self_le_one
theorem inv_mul_lt_iff (h : 0 < b) : b⁻¹ * a < c ↔ a < b * c := by
rw [inv_eq_one_div, mul_comm, ← div_eq_mul_one_div]
exact div_lt_iff' h
#align inv_mul_lt_iff inv_mul_lt_iff
theorem inv_mul_lt_iff' (h : 0 < b) : b⁻¹ * a < c ↔ a < c * b := by rw [inv_mul_lt_iff h, mul_comm]
#align inv_mul_lt_iff' inv_mul_lt_iff'
theorem mul_inv_lt_iff (h : 0 < b) : a * b⁻¹ < c ↔ a < b * c := by rw [mul_comm, inv_mul_lt_iff h]
#align mul_inv_lt_iff mul_inv_lt_iff
theorem mul_inv_lt_iff' (h : 0 < b) : a * b⁻¹ < c ↔ a < c * b := by rw [mul_comm, inv_mul_lt_iff' h]
#align mul_inv_lt_iff' mul_inv_lt_iff'
theorem inv_pos_le_iff_one_le_mul (ha : 0 < a) : a⁻¹ ≤ b ↔ 1 ≤ b * a := by
rw [inv_eq_one_div]
exact div_le_iff ha
#align inv_pos_le_iff_one_le_mul inv_pos_le_iff_one_le_mul
theorem inv_pos_le_iff_one_le_mul' (ha : 0 < a) : a⁻¹ ≤ b ↔ 1 ≤ a * b := by
rw [inv_eq_one_div]
exact div_le_iff' ha
#align inv_pos_le_iff_one_le_mul' inv_pos_le_iff_one_le_mul'
theorem inv_pos_lt_iff_one_lt_mul (ha : 0 < a) : a⁻¹ < b ↔ 1 < b * a := by
rw [inv_eq_one_div]
exact div_lt_iff ha
#align inv_pos_lt_iff_one_lt_mul inv_pos_lt_iff_one_lt_mul
theorem inv_pos_lt_iff_one_lt_mul' (ha : 0 < a) : a⁻¹ < b ↔ 1 < a * b := by
rw [inv_eq_one_div]
exact div_lt_iff' ha
#align inv_pos_lt_iff_one_lt_mul' inv_pos_lt_iff_one_lt_mul'
/-- One direction of `div_le_iff` where `b` is allowed to be `0` (but `c` must be nonnegative) -/
theorem div_le_of_nonneg_of_le_mul (hb : 0 ≤ b) (hc : 0 ≤ c) (h : a ≤ c * b) : a / b ≤ c := by
rcases eq_or_lt_of_le hb with (rfl | hb')
· simp only [div_zero, hc]
· rwa [div_le_iff hb']
#align div_le_of_nonneg_of_le_mul div_le_of_nonneg_of_le_mul
/-- One direction of `div_le_iff` where `c` is allowed to be `0` (but `b` must be nonnegative) -/
lemma mul_le_of_nonneg_of_le_div (hb : 0 ≤ b) (hc : 0 ≤ c) (h : a ≤ b / c) : a * c ≤ b := by
obtain rfl | hc := hc.eq_or_lt
· simpa using hb
· rwa [le_div_iff hc] at h
#align mul_le_of_nonneg_of_le_div mul_le_of_nonneg_of_le_div
theorem div_le_one_of_le (h : a ≤ b) (hb : 0 ≤ b) : a / b ≤ 1 :=
div_le_of_nonneg_of_le_mul hb zero_le_one <| by rwa [one_mul]
#align div_le_one_of_le div_le_one_of_le
lemma mul_inv_le_one_of_le (h : a ≤ b) (hb : 0 ≤ b) : a * b⁻¹ ≤ 1 := by
simpa only [← div_eq_mul_inv] using div_le_one_of_le h hb
lemma inv_mul_le_one_of_le (h : a ≤ b) (hb : 0 ≤ b) : b⁻¹ * a ≤ 1 := by
simpa only [← div_eq_inv_mul] using div_le_one_of_le h hb
/-!
### Bi-implications of inequalities using inversions
-/
@[gcongr]
theorem inv_le_inv_of_le (ha : 0 < a) (h : a ≤ b) : b⁻¹ ≤ a⁻¹ := by
rwa [← one_div a, le_div_iff' ha, ← div_eq_mul_inv, div_le_iff (ha.trans_le h), one_mul]
#align inv_le_inv_of_le inv_le_inv_of_le
/-- See `inv_le_inv_of_le` for the implication from right-to-left with one fewer assumption. -/
theorem inv_le_inv (ha : 0 < a) (hb : 0 < b) : a⁻¹ ≤ b⁻¹ ↔ b ≤ a := by
rw [← one_div, div_le_iff ha, ← div_eq_inv_mul, le_div_iff hb, one_mul]
#align inv_le_inv inv_le_inv
/-- In a linear ordered field, for positive `a` and `b` we have `a⁻¹ ≤ b ↔ b⁻¹ ≤ a`.
See also `inv_le_of_inv_le` for a one-sided implication with one fewer assumption. -/
theorem inv_le (ha : 0 < a) (hb : 0 < b) : a⁻¹ ≤ b ↔ b⁻¹ ≤ a := by
rw [← inv_le_inv hb (inv_pos.2 ha), inv_inv]
#align inv_le inv_le
theorem inv_le_of_inv_le (ha : 0 < a) (h : a⁻¹ ≤ b) : b⁻¹ ≤ a :=
(inv_le ha ((inv_pos.2 ha).trans_le h)).1 h
#align inv_le_of_inv_le inv_le_of_inv_le
theorem le_inv (ha : 0 < a) (hb : 0 < b) : a ≤ b⁻¹ ↔ b ≤ a⁻¹ := by
rw [← inv_le_inv (inv_pos.2 hb) ha, inv_inv]
#align le_inv le_inv
/-- See `inv_lt_inv_of_lt` for the implication from right-to-left with one fewer assumption. -/
theorem inv_lt_inv (ha : 0 < a) (hb : 0 < b) : a⁻¹ < b⁻¹ ↔ b < a :=
lt_iff_lt_of_le_iff_le (inv_le_inv hb ha)
#align inv_lt_inv inv_lt_inv
@[gcongr]
theorem inv_lt_inv_of_lt (hb : 0 < b) (h : b < a) : a⁻¹ < b⁻¹ :=
(inv_lt_inv (hb.trans h) hb).2 h
#align inv_lt_inv_of_lt inv_lt_inv_of_lt
/-- In a linear ordered field, for positive `a` and `b` we have `a⁻¹ < b ↔ b⁻¹ < a`.
See also `inv_lt_of_inv_lt` for a one-sided implication with one fewer assumption. -/
theorem inv_lt (ha : 0 < a) (hb : 0 < b) : a⁻¹ < b ↔ b⁻¹ < a :=
lt_iff_lt_of_le_iff_le (le_inv hb ha)
#align inv_lt inv_lt
theorem inv_lt_of_inv_lt (ha : 0 < a) (h : a⁻¹ < b) : b⁻¹ < a :=
(inv_lt ha ((inv_pos.2 ha).trans h)).1 h
#align inv_lt_of_inv_lt inv_lt_of_inv_lt
theorem lt_inv (ha : 0 < a) (hb : 0 < b) : a < b⁻¹ ↔ b < a⁻¹ :=
lt_iff_lt_of_le_iff_le (inv_le hb ha)
#align lt_inv lt_inv
theorem inv_lt_one (ha : 1 < a) : a⁻¹ < 1 := by
rwa [inv_lt (zero_lt_one.trans ha) zero_lt_one, inv_one]
#align inv_lt_one inv_lt_one
theorem one_lt_inv (h₁ : 0 < a) (h₂ : a < 1) : 1 < a⁻¹ := by
rwa [lt_inv (@zero_lt_one α _ _ _ _ _) h₁, inv_one]
#align one_lt_inv one_lt_inv
theorem inv_le_one (ha : 1 ≤ a) : a⁻¹ ≤ 1 := by
rwa [inv_le (zero_lt_one.trans_le ha) zero_lt_one, inv_one]
#align inv_le_one inv_le_one
theorem one_le_inv (h₁ : 0 < a) (h₂ : a ≤ 1) : 1 ≤ a⁻¹ := by
rwa [le_inv (@zero_lt_one α _ _ _ _ _) h₁, inv_one]
#align one_le_inv one_le_inv
theorem inv_lt_one_iff_of_pos (h₀ : 0 < a) : a⁻¹ < 1 ↔ 1 < a :=
⟨fun h₁ => inv_inv a ▸ one_lt_inv (inv_pos.2 h₀) h₁, inv_lt_one⟩
#align inv_lt_one_iff_of_pos inv_lt_one_iff_of_pos
theorem inv_lt_one_iff : a⁻¹ < 1 ↔ a ≤ 0 ∨ 1 < a := by
rcases le_or_lt a 0 with ha | ha
· simp [ha, (inv_nonpos.2 ha).trans_lt zero_lt_one]
· simp only [ha.not_le, false_or_iff, inv_lt_one_iff_of_pos ha]
#align inv_lt_one_iff inv_lt_one_iff
theorem one_lt_inv_iff : 1 < a⁻¹ ↔ 0 < a ∧ a < 1 :=
⟨fun h => ⟨inv_pos.1 (zero_lt_one.trans h), inv_inv a ▸ inv_lt_one h⟩, and_imp.2 one_lt_inv⟩
#align one_lt_inv_iff one_lt_inv_iff
theorem inv_le_one_iff : a⁻¹ ≤ 1 ↔ a ≤ 0 ∨ 1 ≤ a := by
rcases em (a = 1) with (rfl | ha)
· simp [le_rfl]
· simp only [Ne.le_iff_lt (Ne.symm ha), Ne.le_iff_lt (mt inv_eq_one.1 ha), inv_lt_one_iff]
#align inv_le_one_iff inv_le_one_iff
theorem one_le_inv_iff : 1 ≤ a⁻¹ ↔ 0 < a ∧ a ≤ 1 :=
⟨fun h => ⟨inv_pos.1 (zero_lt_one.trans_le h), inv_inv a ▸ inv_le_one h⟩, and_imp.2 one_le_inv⟩
#align one_le_inv_iff one_le_inv_iff
/-!
### Relating two divisions.
-/
@[mono, gcongr]
lemma div_le_div_of_nonneg_right (hab : a ≤ b) (hc : 0 ≤ c) : a / c ≤ b / c := by
rw [div_eq_mul_one_div a c, div_eq_mul_one_div b c]
exact mul_le_mul_of_nonneg_right hab (one_div_nonneg.2 hc)
#align div_le_div_of_le_of_nonneg div_le_div_of_nonneg_right
@[gcongr]
lemma div_lt_div_of_pos_right (h : a < b) (hc : 0 < c) : a / c < b / c := by
rw [div_eq_mul_one_div a c, div_eq_mul_one_div b c]
exact mul_lt_mul_of_pos_right h (one_div_pos.2 hc)
#align div_lt_div_of_lt div_lt_div_of_pos_right
-- Not a `mono` lemma b/c `div_le_div` is strictly more general
@[gcongr]
lemma div_le_div_of_nonneg_left (ha : 0 ≤ a) (hc : 0 < c) (h : c ≤ b) : a / b ≤ a / c := by
rw [div_eq_mul_inv, div_eq_mul_inv]
exact mul_le_mul_of_nonneg_left ((inv_le_inv (hc.trans_le h) hc).mpr h) ha
#align div_le_div_of_le_left div_le_div_of_nonneg_left
@[gcongr]
lemma div_lt_div_of_pos_left (ha : 0 < a) (hc : 0 < c) (h : c < b) : a / b < a / c := by
simpa only [div_eq_mul_inv, mul_lt_mul_left ha, inv_lt_inv (hc.trans h) hc]
#align div_lt_div_of_lt_left div_lt_div_of_pos_left
-- 2024-02-16
@[deprecated] alias div_le_div_of_le_of_nonneg := div_le_div_of_nonneg_right
@[deprecated] alias div_lt_div_of_lt := div_lt_div_of_pos_right
@[deprecated] alias div_le_div_of_le_left := div_le_div_of_nonneg_left
@[deprecated] alias div_lt_div_of_lt_left := div_lt_div_of_pos_left
@[deprecated div_le_div_of_nonneg_right (since := "2024-02-16")]
lemma div_le_div_of_le (hc : 0 ≤ c) (hab : a ≤ b) : a / c ≤ b / c :=
div_le_div_of_nonneg_right hab hc
#align div_le_div_of_le div_le_div_of_le
theorem div_le_div_right (hc : 0 < c) : a / c ≤ b / c ↔ a ≤ b :=
⟨le_imp_le_of_lt_imp_lt fun hab ↦ div_lt_div_of_pos_right hab hc,
fun hab ↦ div_le_div_of_nonneg_right hab hc.le⟩
#align div_le_div_right div_le_div_right
theorem div_lt_div_right (hc : 0 < c) : a / c < b / c ↔ a < b :=
lt_iff_lt_of_le_iff_le <| div_le_div_right hc
#align div_lt_div_right div_lt_div_right
theorem div_lt_div_left (ha : 0 < a) (hb : 0 < b) (hc : 0 < c) : a / b < a / c ↔ c < b := by
simp only [div_eq_mul_inv, mul_lt_mul_left ha, inv_lt_inv hb hc]
#align div_lt_div_left div_lt_div_left
theorem div_le_div_left (ha : 0 < a) (hb : 0 < b) (hc : 0 < c) : a / b ≤ a / c ↔ c ≤ b :=
le_iff_le_iff_lt_iff_lt.2 (div_lt_div_left ha hc hb)
#align div_le_div_left div_le_div_left
theorem div_lt_div_iff (b0 : 0 < b) (d0 : 0 < d) : a / b < c / d ↔ a * d < c * b := by
rw [lt_div_iff d0, div_mul_eq_mul_div, div_lt_iff b0]
#align div_lt_div_iff div_lt_div_iff
theorem div_le_div_iff (b0 : 0 < b) (d0 : 0 < d) : a / b ≤ c / d ↔ a * d ≤ c * b := by
rw [le_div_iff d0, div_mul_eq_mul_div, div_le_iff b0]
#align div_le_div_iff div_le_div_iff
@[mono, gcongr]
theorem div_le_div (hc : 0 ≤ c) (hac : a ≤ c) (hd : 0 < d) (hbd : d ≤ b) : a / b ≤ c / d := by
rw [div_le_div_iff (hd.trans_le hbd) hd]
exact mul_le_mul hac hbd hd.le hc
#align div_le_div div_le_div
@[gcongr]
theorem div_lt_div (hac : a < c) (hbd : d ≤ b) (c0 : 0 ≤ c) (d0 : 0 < d) : a / b < c / d :=
(div_lt_div_iff (d0.trans_le hbd) d0).2 (mul_lt_mul hac hbd d0 c0)
#align div_lt_div div_lt_div
theorem div_lt_div' (hac : a ≤ c) (hbd : d < b) (c0 : 0 < c) (d0 : 0 < d) : a / b < c / d :=
(div_lt_div_iff (d0.trans hbd) d0).2 (mul_lt_mul' hac hbd d0.le c0)
#align div_lt_div' div_lt_div'
/-!
### Relating one division and involving `1`
-/
theorem div_le_self (ha : 0 ≤ a) (hb : 1 ≤ b) : a / b ≤ a := by
simpa only [div_one] using div_le_div_of_nonneg_left ha zero_lt_one hb
#align div_le_self div_le_self
theorem div_lt_self (ha : 0 < a) (hb : 1 < b) : a / b < a := by
simpa only [div_one] using div_lt_div_of_pos_left ha zero_lt_one hb
#align div_lt_self div_lt_self
theorem le_div_self (ha : 0 ≤ a) (hb₀ : 0 < b) (hb₁ : b ≤ 1) : a ≤ a / b := by
simpa only [div_one] using div_le_div_of_nonneg_left ha hb₀ hb₁
#align le_div_self le_div_self
theorem one_le_div (hb : 0 < b) : 1 ≤ a / b ↔ b ≤ a := by rw [le_div_iff hb, one_mul]
#align one_le_div one_le_div
theorem div_le_one (hb : 0 < b) : a / b ≤ 1 ↔ a ≤ b := by rw [div_le_iff hb, one_mul]
#align div_le_one div_le_one
theorem one_lt_div (hb : 0 < b) : 1 < a / b ↔ b < a := by rw [lt_div_iff hb, one_mul]
#align one_lt_div one_lt_div
theorem div_lt_one (hb : 0 < b) : a / b < 1 ↔ a < b := by rw [div_lt_iff hb, one_mul]
#align div_lt_one div_lt_one
theorem one_div_le (ha : 0 < a) (hb : 0 < b) : 1 / a ≤ b ↔ 1 / b ≤ a := by simpa using inv_le ha hb
#align one_div_le one_div_le
theorem one_div_lt (ha : 0 < a) (hb : 0 < b) : 1 / a < b ↔ 1 / b < a := by simpa using inv_lt ha hb
#align one_div_lt one_div_lt
theorem le_one_div (ha : 0 < a) (hb : 0 < b) : a ≤ 1 / b ↔ b ≤ 1 / a := by simpa using le_inv ha hb
#align le_one_div le_one_div
theorem lt_one_div (ha : 0 < a) (hb : 0 < b) : a < 1 / b ↔ b < 1 / a := by simpa using lt_inv ha hb
#align lt_one_div lt_one_div
/-!
### Relating two divisions, involving `1`
-/
theorem one_div_le_one_div_of_le (ha : 0 < a) (h : a ≤ b) : 1 / b ≤ 1 / a := by
simpa using inv_le_inv_of_le ha h
#align one_div_le_one_div_of_le one_div_le_one_div_of_le
theorem one_div_lt_one_div_of_lt (ha : 0 < a) (h : a < b) : 1 / b < 1 / a := by
rwa [lt_div_iff' ha, ← div_eq_mul_one_div, div_lt_one (ha.trans h)]
#align one_div_lt_one_div_of_lt one_div_lt_one_div_of_lt
theorem le_of_one_div_le_one_div (ha : 0 < a) (h : 1 / a ≤ 1 / b) : b ≤ a :=
le_imp_le_of_lt_imp_lt (one_div_lt_one_div_of_lt ha) h
#align le_of_one_div_le_one_div le_of_one_div_le_one_div
theorem lt_of_one_div_lt_one_div (ha : 0 < a) (h : 1 / a < 1 / b) : b < a :=
lt_imp_lt_of_le_imp_le (one_div_le_one_div_of_le ha) h
#align lt_of_one_div_lt_one_div lt_of_one_div_lt_one_div
/-- For the single implications with fewer assumptions, see `one_div_le_one_div_of_le` and
`le_of_one_div_le_one_div` -/
theorem one_div_le_one_div (ha : 0 < a) (hb : 0 < b) : 1 / a ≤ 1 / b ↔ b ≤ a :=
div_le_div_left zero_lt_one ha hb
#align one_div_le_one_div one_div_le_one_div
/-- For the single implications with fewer assumptions, see `one_div_lt_one_div_of_lt` and
`lt_of_one_div_lt_one_div` -/
theorem one_div_lt_one_div (ha : 0 < a) (hb : 0 < b) : 1 / a < 1 / b ↔ b < a :=
div_lt_div_left zero_lt_one ha hb
#align one_div_lt_one_div one_div_lt_one_div
theorem one_lt_one_div (h1 : 0 < a) (h2 : a < 1) : 1 < 1 / a := by
rwa [lt_one_div (@zero_lt_one α _ _ _ _ _) h1, one_div_one]
#align one_lt_one_div one_lt_one_div
theorem one_le_one_div (h1 : 0 < a) (h2 : a ≤ 1) : 1 ≤ 1 / a := by
rwa [le_one_div (@zero_lt_one α _ _ _ _ _) h1, one_div_one]
#align one_le_one_div one_le_one_div
/-!
### Results about halving.
The equalities also hold in semifields of characteristic `0`.
-/
/- TODO: Unify `add_halves` and `add_halves'` into a single lemma about
`DivisionSemiring` + `CharZero` -/
theorem add_halves (a : α) : a / 2 + a / 2 = a := by
rw [div_add_div_same, ← two_mul, mul_div_cancel_left₀ a two_ne_zero]
#align add_halves add_halves
-- TODO: Generalize to `DivisionSemiring`
theorem add_self_div_two (a : α) : (a + a) / 2 = a := by
rw [← mul_two, mul_div_cancel_right₀ a two_ne_zero]
#align add_self_div_two add_self_div_two
theorem half_pos (h : 0 < a) : 0 < a / 2 :=
div_pos h zero_lt_two
#align half_pos half_pos
theorem one_half_pos : (0 : α) < 1 / 2 :=
half_pos zero_lt_one
#align one_half_pos one_half_pos
@[simp]
theorem half_le_self_iff : a / 2 ≤ a ↔ 0 ≤ a := by
rw [div_le_iff (zero_lt_two' α), mul_two, le_add_iff_nonneg_left]
#align half_le_self_iff half_le_self_iff
@[simp]
theorem half_lt_self_iff : a / 2 < a ↔ 0 < a := by
rw [div_lt_iff (zero_lt_two' α), mul_two, lt_add_iff_pos_left]
#align half_lt_self_iff half_lt_self_iff
alias ⟨_, half_le_self⟩ := half_le_self_iff
#align half_le_self half_le_self
alias ⟨_, half_lt_self⟩ := half_lt_self_iff
#align half_lt_self half_lt_self
alias div_two_lt_of_pos := half_lt_self
#align div_two_lt_of_pos div_two_lt_of_pos
theorem one_half_lt_one : (1 / 2 : α) < 1 :=
half_lt_self zero_lt_one
#align one_half_lt_one one_half_lt_one
theorem two_inv_lt_one : (2⁻¹ : α) < 1 :=
(one_div _).symm.trans_lt one_half_lt_one
#align two_inv_lt_one two_inv_lt_one
theorem left_lt_add_div_two : a < (a + b) / 2 ↔ a < b := by simp [lt_div_iff, mul_two]
#align left_lt_add_div_two left_lt_add_div_two
theorem add_div_two_lt_right : (a + b) / 2 < b ↔ a < b := by simp [div_lt_iff, mul_two]
#align add_div_two_lt_right add_div_two_lt_right
theorem add_thirds (a : α) : a / 3 + a / 3 + a / 3 = a := by
rw [div_add_div_same, div_add_div_same, ← two_mul, ← add_one_mul 2 a, two_add_one_eq_three,
mul_div_cancel_left₀ a three_ne_zero]
/-!
### Miscellaneous lemmas
-/
@[simp] lemma div_pos_iff_of_pos_left (ha : 0 < a) : 0 < a / b ↔ 0 < b := by
simp only [div_eq_mul_inv, mul_pos_iff_of_pos_left ha, inv_pos]
@[simp] lemma div_pos_iff_of_pos_right (hb : 0 < b) : 0 < a / b ↔ 0 < a := by
simp only [div_eq_mul_inv, mul_pos_iff_of_pos_right (inv_pos.2 hb)]
theorem mul_le_mul_of_mul_div_le (h : a * (b / c) ≤ d) (hc : 0 < c) : b * a ≤ d * c := by
rw [← mul_div_assoc] at h
rwa [mul_comm b, ← div_le_iff hc]
#align mul_le_mul_of_mul_div_le mul_le_mul_of_mul_div_le
theorem div_mul_le_div_mul_of_div_le_div (h : a / b ≤ c / d) (he : 0 ≤ e) :
a / (b * e) ≤ c / (d * e) := by
rw [div_mul_eq_div_mul_one_div, div_mul_eq_div_mul_one_div]
exact mul_le_mul_of_nonneg_right h (one_div_nonneg.2 he)
#align div_mul_le_div_mul_of_div_le_div div_mul_le_div_mul_of_div_le_div
theorem exists_pos_mul_lt {a : α} (h : 0 < a) (b : α) : ∃ c : α, 0 < c ∧ b * c < a := by
have : 0 < a / max (b + 1) 1 := div_pos h (lt_max_iff.2 (Or.inr zero_lt_one))
refine ⟨a / max (b + 1) 1, this, ?_⟩
rw [← lt_div_iff this, div_div_cancel' h.ne']
exact lt_max_iff.2 (Or.inl <| lt_add_one _)
#align exists_pos_mul_lt exists_pos_mul_lt
theorem exists_pos_lt_mul {a : α} (h : 0 < a) (b : α) : ∃ c : α, 0 < c ∧ b < c * a :=
let ⟨c, hc₀, hc⟩ := exists_pos_mul_lt h b;
⟨c⁻¹, inv_pos.2 hc₀, by rwa [← div_eq_inv_mul, lt_div_iff hc₀]⟩
#align exists_pos_lt_mul exists_pos_lt_mul
lemma monotone_div_right_of_nonneg (ha : 0 ≤ a) : Monotone (· / a) :=
fun _b _c hbc ↦ div_le_div_of_nonneg_right hbc ha
lemma strictMono_div_right_of_pos (ha : 0 < a) : StrictMono (· / a) :=
fun _b _c hbc ↦ div_lt_div_of_pos_right hbc ha
theorem Monotone.div_const {β : Type*} [Preorder β] {f : β → α} (hf : Monotone f) {c : α}
(hc : 0 ≤ c) : Monotone fun x => f x / c := (monotone_div_right_of_nonneg hc).comp hf
#align monotone.div_const Monotone.div_const
theorem StrictMono.div_const {β : Type*} [Preorder β] {f : β → α} (hf : StrictMono f) {c : α}
(hc : 0 < c) : StrictMono fun x => f x / c := by
simpa only [div_eq_mul_inv] using hf.mul_const (inv_pos.2 hc)
#align strict_mono.div_const StrictMono.div_const
-- see Note [lower instance priority]
instance (priority := 100) LinearOrderedSemiField.toDenselyOrdered : DenselyOrdered α where
dense a₁ a₂ h :=
⟨(a₁ + a₂) / 2,
calc
a₁ = (a₁ + a₁) / 2 := (add_self_div_two a₁).symm
_ < (a₁ + a₂) / 2 := div_lt_div_of_pos_right (add_lt_add_left h _) zero_lt_two
,
calc
(a₁ + a₂) / 2 < (a₂ + a₂) / 2 := div_lt_div_of_pos_right (add_lt_add_right h _) zero_lt_two
_ = a₂ := add_self_div_two a₂
⟩
#align linear_ordered_field.to_densely_ordered LinearOrderedSemiField.toDenselyOrdered
theorem min_div_div_right {c : α} (hc : 0 ≤ c) (a b : α) : min (a / c) (b / c) = min a b / c :=
(monotone_div_right_of_nonneg hc).map_min.symm
#align min_div_div_right min_div_div_right
theorem max_div_div_right {c : α} (hc : 0 ≤ c) (a b : α) : max (a / c) (b / c) = max a b / c :=
(monotone_div_right_of_nonneg hc).map_max.symm
#align max_div_div_right max_div_div_right
theorem one_div_strictAntiOn : StrictAntiOn (fun x : α => 1 / x) (Set.Ioi 0) :=
fun _ x1 _ y1 xy => (one_div_lt_one_div (Set.mem_Ioi.mp y1) (Set.mem_Ioi.mp x1)).mpr xy
#align one_div_strict_anti_on one_div_strictAntiOn
theorem one_div_pow_le_one_div_pow_of_le (a1 : 1 ≤ a) {m n : ℕ} (mn : m ≤ n) :
1 / a ^ n ≤ 1 / a ^ m := by
refine (one_div_le_one_div ?_ ?_).mpr (pow_le_pow_right a1 mn) <;>
exact pow_pos (zero_lt_one.trans_le a1) _
#align one_div_pow_le_one_div_pow_of_le one_div_pow_le_one_div_pow_of_le
theorem one_div_pow_lt_one_div_pow_of_lt (a1 : 1 < a) {m n : ℕ} (mn : m < n) :
1 / a ^ n < 1 / a ^ m := by
refine (one_div_lt_one_div ?_ ?_).2 (pow_lt_pow_right a1 mn) <;>
exact pow_pos (zero_lt_one.trans a1) _
#align one_div_pow_lt_one_div_pow_of_lt one_div_pow_lt_one_div_pow_of_lt
theorem one_div_pow_anti (a1 : 1 ≤ a) : Antitone fun n : ℕ => 1 / a ^ n := fun _ _ =>
one_div_pow_le_one_div_pow_of_le a1
#align one_div_pow_anti one_div_pow_anti
theorem one_div_pow_strictAnti (a1 : 1 < a) : StrictAnti fun n : ℕ => 1 / a ^ n := fun _ _ =>
one_div_pow_lt_one_div_pow_of_lt a1
#align one_div_pow_strict_anti one_div_pow_strictAnti
theorem inv_strictAntiOn : StrictAntiOn (fun x : α => x⁻¹) (Set.Ioi 0) := fun _ hx _ hy xy =>
(inv_lt_inv hy hx).2 xy
#align inv_strict_anti_on inv_strictAntiOn
theorem inv_pow_le_inv_pow_of_le (a1 : 1 ≤ a) {m n : ℕ} (mn : m ≤ n) : (a ^ n)⁻¹ ≤ (a ^ m)⁻¹ := by
convert one_div_pow_le_one_div_pow_of_le a1 mn using 1 <;> simp
#align inv_pow_le_inv_pow_of_le inv_pow_le_inv_pow_of_le
theorem inv_pow_lt_inv_pow_of_lt (a1 : 1 < a) {m n : ℕ} (mn : m < n) : (a ^ n)⁻¹ < (a ^ m)⁻¹ := by
convert one_div_pow_lt_one_div_pow_of_lt a1 mn using 1 <;> simp
#align inv_pow_lt_inv_pow_of_lt inv_pow_lt_inv_pow_of_lt
theorem inv_pow_anti (a1 : 1 ≤ a) : Antitone fun n : ℕ => (a ^ n)⁻¹ := fun _ _ =>
inv_pow_le_inv_pow_of_le a1
#align inv_pow_anti inv_pow_anti
theorem inv_pow_strictAnti (a1 : 1 < a) : StrictAnti fun n : ℕ => (a ^ n)⁻¹ := fun _ _ =>
inv_pow_lt_inv_pow_of_lt a1
#align inv_pow_strict_anti inv_pow_strictAnti
/-! ### Results about `IsGLB` -/
theorem IsGLB.mul_left {s : Set α} (ha : 0 ≤ a) (hs : IsGLB s b) :
IsGLB ((fun b => a * b) '' s) (a * b) := by
rcases lt_or_eq_of_le ha with (ha | rfl)
· exact (OrderIso.mulLeft₀ _ ha).isGLB_image'.2 hs
· simp_rw [zero_mul]
rw [hs.nonempty.image_const]
exact isGLB_singleton
#align is_glb.mul_left IsGLB.mul_left
theorem IsGLB.mul_right {s : Set α} (ha : 0 ≤ a) (hs : IsGLB s b) :
IsGLB ((fun b => b * a) '' s) (b * a) := by simpa [mul_comm] using hs.mul_left ha
#align is_glb.mul_right IsGLB.mul_right
end LinearOrderedSemifield
section
variable [LinearOrderedField α] {a b c d : α} {n : ℤ}
/-! ### Lemmas about pos, nonneg, nonpos, neg -/
theorem div_pos_iff : 0 < a / b ↔ 0 < a ∧ 0 < b ∨ a < 0 ∧ b < 0 := by
simp only [division_def, mul_pos_iff, inv_pos, inv_lt_zero]
#align div_pos_iff div_pos_iff
theorem div_neg_iff : a / b < 0 ↔ 0 < a ∧ b < 0 ∨ a < 0 ∧ 0 < b := by
simp [division_def, mul_neg_iff]
#align div_neg_iff div_neg_iff
theorem div_nonneg_iff : 0 ≤ a / b ↔ 0 ≤ a ∧ 0 ≤ b ∨ a ≤ 0 ∧ b ≤ 0 := by
simp [division_def, mul_nonneg_iff]
#align div_nonneg_iff div_nonneg_iff
theorem div_nonpos_iff : a / b ≤ 0 ↔ 0 ≤ a ∧ b ≤ 0 ∨ a ≤ 0 ∧ 0 ≤ b := by
simp [division_def, mul_nonpos_iff]
#align div_nonpos_iff div_nonpos_iff
theorem div_nonneg_of_nonpos (ha : a ≤ 0) (hb : b ≤ 0) : 0 ≤ a / b :=
div_nonneg_iff.2 <| Or.inr ⟨ha, hb⟩
#align div_nonneg_of_nonpos div_nonneg_of_nonpos
theorem div_pos_of_neg_of_neg (ha : a < 0) (hb : b < 0) : 0 < a / b :=
div_pos_iff.2 <| Or.inr ⟨ha, hb⟩
#align div_pos_of_neg_of_neg div_pos_of_neg_of_neg
theorem div_neg_of_neg_of_pos (ha : a < 0) (hb : 0 < b) : a / b < 0 :=
div_neg_iff.2 <| Or.inr ⟨ha, hb⟩
#align div_neg_of_neg_of_pos div_neg_of_neg_of_pos
theorem div_neg_of_pos_of_neg (ha : 0 < a) (hb : b < 0) : a / b < 0 :=
div_neg_iff.2 <| Or.inl ⟨ha, hb⟩
#align div_neg_of_pos_of_neg div_neg_of_pos_of_neg
/-! ### Relating one division with another term -/
theorem div_le_iff_of_neg (hc : c < 0) : b / c ≤ a ↔ a * c ≤ b :=
⟨fun h => div_mul_cancel₀ b (ne_of_lt hc) ▸ mul_le_mul_of_nonpos_right h hc.le, fun h =>
calc
a = a * c * (1 / c) := mul_mul_div a (ne_of_lt hc)
_ ≥ b * (1 / c) := mul_le_mul_of_nonpos_right h (one_div_neg.2 hc).le
_ = b / c := (div_eq_mul_one_div b c).symm
⟩
#align div_le_iff_of_neg div_le_iff_of_neg
theorem div_le_iff_of_neg' (hc : c < 0) : b / c ≤ a ↔ c * a ≤ b := by
rw [mul_comm, div_le_iff_of_neg hc]
#align div_le_iff_of_neg' div_le_iff_of_neg'
theorem le_div_iff_of_neg (hc : c < 0) : a ≤ b / c ↔ b ≤ a * c := by
rw [← neg_neg c, mul_neg, div_neg, le_neg, div_le_iff (neg_pos.2 hc), neg_mul]
#align le_div_iff_of_neg le_div_iff_of_neg
theorem le_div_iff_of_neg' (hc : c < 0) : a ≤ b / c ↔ b ≤ c * a := by
rw [mul_comm, le_div_iff_of_neg hc]
#align le_div_iff_of_neg' le_div_iff_of_neg'
theorem div_lt_iff_of_neg (hc : c < 0) : b / c < a ↔ a * c < b :=
lt_iff_lt_of_le_iff_le <| le_div_iff_of_neg hc
#align div_lt_iff_of_neg div_lt_iff_of_neg
theorem div_lt_iff_of_neg' (hc : c < 0) : b / c < a ↔ c * a < b := by
rw [mul_comm, div_lt_iff_of_neg hc]
#align div_lt_iff_of_neg' div_lt_iff_of_neg'
theorem lt_div_iff_of_neg (hc : c < 0) : a < b / c ↔ b < a * c :=
lt_iff_lt_of_le_iff_le <| div_le_iff_of_neg hc
#align lt_div_iff_of_neg lt_div_iff_of_neg
theorem lt_div_iff_of_neg' (hc : c < 0) : a < b / c ↔ b < c * a := by
rw [mul_comm, lt_div_iff_of_neg hc]
#align lt_div_iff_of_neg' lt_div_iff_of_neg'
theorem div_le_one_of_ge (h : b ≤ a) (hb : b ≤ 0) : a / b ≤ 1 := by
simpa only [neg_div_neg_eq] using div_le_one_of_le (neg_le_neg h) (neg_nonneg_of_nonpos hb)
#align div_le_one_of_ge div_le_one_of_ge
/-! ### Bi-implications of inequalities using inversions -/
theorem inv_le_inv_of_neg (ha : a < 0) (hb : b < 0) : a⁻¹ ≤ b⁻¹ ↔ b ≤ a := by
rw [← one_div, div_le_iff_of_neg ha, ← div_eq_inv_mul, div_le_iff_of_neg hb, one_mul]
#align inv_le_inv_of_neg inv_le_inv_of_neg
theorem inv_le_of_neg (ha : a < 0) (hb : b < 0) : a⁻¹ ≤ b ↔ b⁻¹ ≤ a := by
rw [← inv_le_inv_of_neg hb (inv_lt_zero.2 ha), inv_inv]
#align inv_le_of_neg inv_le_of_neg
theorem le_inv_of_neg (ha : a < 0) (hb : b < 0) : a ≤ b⁻¹ ↔ b ≤ a⁻¹ := by
rw [← inv_le_inv_of_neg (inv_lt_zero.2 hb) ha, inv_inv]
#align le_inv_of_neg le_inv_of_neg
theorem inv_lt_inv_of_neg (ha : a < 0) (hb : b < 0) : a⁻¹ < b⁻¹ ↔ b < a :=
lt_iff_lt_of_le_iff_le (inv_le_inv_of_neg hb ha)
#align inv_lt_inv_of_neg inv_lt_inv_of_neg
theorem inv_lt_of_neg (ha : a < 0) (hb : b < 0) : a⁻¹ < b ↔ b⁻¹ < a :=
lt_iff_lt_of_le_iff_le (le_inv_of_neg hb ha)
#align inv_lt_of_neg inv_lt_of_neg
theorem lt_inv_of_neg (ha : a < 0) (hb : b < 0) : a < b⁻¹ ↔ b < a⁻¹ :=
lt_iff_lt_of_le_iff_le (inv_le_of_neg hb ha)
#align lt_inv_of_neg lt_inv_of_neg
/-!
### Monotonicity results involving inversion
-/
theorem sub_inv_antitoneOn_Ioi :
AntitoneOn (fun x ↦ (x-c)⁻¹) (Set.Ioi c) :=
antitoneOn_iff_forall_lt.mpr fun _ ha _ hb hab ↦
inv_le_inv (sub_pos.mpr hb) (sub_pos.mpr ha) |>.mpr <| sub_le_sub (le_of_lt hab) le_rfl
theorem sub_inv_antitoneOn_Iio :
AntitoneOn (fun x ↦ (x-c)⁻¹) (Set.Iio c) :=
antitoneOn_iff_forall_lt.mpr fun _ ha _ hb hab ↦
inv_le_inv_of_neg (sub_neg.mpr hb) (sub_neg.mpr ha) |>.mpr <| sub_le_sub (le_of_lt hab) le_rfl
theorem sub_inv_antitoneOn_Icc_right (ha : c < a) :
AntitoneOn (fun x ↦ (x-c)⁻¹) (Set.Icc a b) := by
by_cases hab : a ≤ b
· exact sub_inv_antitoneOn_Ioi.mono <| (Set.Icc_subset_Ioi_iff hab).mpr ha
· simp [hab, Set.Subsingleton.antitoneOn]
theorem sub_inv_antitoneOn_Icc_left (ha : b < c) :
AntitoneOn (fun x ↦ (x-c)⁻¹) (Set.Icc a b) := by
by_cases hab : a ≤ b
· exact sub_inv_antitoneOn_Iio.mono <| (Set.Icc_subset_Iio_iff hab).mpr ha
· simp [hab, Set.Subsingleton.antitoneOn]
theorem inv_antitoneOn_Ioi :
AntitoneOn (fun x:α ↦ x⁻¹) (Set.Ioi 0) := by
convert sub_inv_antitoneOn_Ioi
exact (sub_zero _).symm
theorem inv_antitoneOn_Iio :
AntitoneOn (fun x:α ↦ x⁻¹) (Set.Iio 0) := by
convert sub_inv_antitoneOn_Iio
exact (sub_zero _).symm
theorem inv_antitoneOn_Icc_right (ha : 0 < a) :
AntitoneOn (fun x:α ↦ x⁻¹) (Set.Icc a b) := by
convert sub_inv_antitoneOn_Icc_right ha
exact (sub_zero _).symm
theorem inv_antitoneOn_Icc_left (hb : b < 0) :
AntitoneOn (fun x:α ↦ x⁻¹) (Set.Icc a b) := by
convert sub_inv_antitoneOn_Icc_left hb
exact (sub_zero _).symm
/-! ### Relating two divisions -/
theorem div_le_div_of_nonpos_of_le (hc : c ≤ 0) (h : b ≤ a) : a / c ≤ b / c := by
rw [div_eq_mul_one_div a c, div_eq_mul_one_div b c]
exact mul_le_mul_of_nonpos_right h (one_div_nonpos.2 hc)
#align div_le_div_of_nonpos_of_le div_le_div_of_nonpos_of_le
theorem div_lt_div_of_neg_of_lt (hc : c < 0) (h : b < a) : a / c < b / c := by
rw [div_eq_mul_one_div a c, div_eq_mul_one_div b c]
exact mul_lt_mul_of_neg_right h (one_div_neg.2 hc)
#align div_lt_div_of_neg_of_lt div_lt_div_of_neg_of_lt
theorem div_le_div_right_of_neg (hc : c < 0) : a / c ≤ b / c ↔ b ≤ a :=
⟨le_imp_le_of_lt_imp_lt <| div_lt_div_of_neg_of_lt hc, div_le_div_of_nonpos_of_le <| hc.le⟩
#align div_le_div_right_of_neg div_le_div_right_of_neg
theorem div_lt_div_right_of_neg (hc : c < 0) : a / c < b / c ↔ b < a :=
lt_iff_lt_of_le_iff_le <| div_le_div_right_of_neg hc
#align div_lt_div_right_of_neg div_lt_div_right_of_neg
/-! ### Relating one division and involving `1` -/
theorem one_le_div_of_neg (hb : b < 0) : 1 ≤ a / b ↔ a ≤ b := by rw [le_div_iff_of_neg hb, one_mul]
#align one_le_div_of_neg one_le_div_of_neg
theorem div_le_one_of_neg (hb : b < 0) : a / b ≤ 1 ↔ b ≤ a := by rw [div_le_iff_of_neg hb, one_mul]
#align div_le_one_of_neg div_le_one_of_neg
theorem one_lt_div_of_neg (hb : b < 0) : 1 < a / b ↔ a < b := by rw [lt_div_iff_of_neg hb, one_mul]
#align one_lt_div_of_neg one_lt_div_of_neg
theorem div_lt_one_of_neg (hb : b < 0) : a / b < 1 ↔ b < a := by rw [div_lt_iff_of_neg hb, one_mul]
#align div_lt_one_of_neg div_lt_one_of_neg
theorem one_div_le_of_neg (ha : a < 0) (hb : b < 0) : 1 / a ≤ b ↔ 1 / b ≤ a := by
simpa using inv_le_of_neg ha hb
#align one_div_le_of_neg one_div_le_of_neg
theorem one_div_lt_of_neg (ha : a < 0) (hb : b < 0) : 1 / a < b ↔ 1 / b < a := by
simpa using inv_lt_of_neg ha hb
#align one_div_lt_of_neg one_div_lt_of_neg
theorem le_one_div_of_neg (ha : a < 0) (hb : b < 0) : a ≤ 1 / b ↔ b ≤ 1 / a := by
simpa using le_inv_of_neg ha hb
#align le_one_div_of_neg le_one_div_of_neg
theorem lt_one_div_of_neg (ha : a < 0) (hb : b < 0) : a < 1 / b ↔ b < 1 / a := by
simpa using lt_inv_of_neg ha hb
#align lt_one_div_of_neg lt_one_div_of_neg
theorem one_lt_div_iff : 1 < a / b ↔ 0 < b ∧ b < a ∨ b < 0 ∧ a < b := by
rcases lt_trichotomy b 0 with (hb | rfl | hb)
· simp [hb, hb.not_lt, one_lt_div_of_neg]
· simp [lt_irrefl, zero_le_one]
· simp [hb, hb.not_lt, one_lt_div]
#align one_lt_div_iff one_lt_div_iff
| Mathlib/Algebra/Order/Field/Basic.lean | 839 | 843 | theorem one_le_div_iff : 1 ≤ a / b ↔ 0 < b ∧ b ≤ a ∨ b < 0 ∧ a ≤ b := by |
rcases lt_trichotomy b 0 with (hb | rfl | hb)
· simp [hb, hb.not_lt, one_le_div_of_neg]
· simp [lt_irrefl, zero_lt_one.not_le, zero_lt_one]
· simp [hb, hb.not_lt, one_le_div]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot
-/
import Mathlib.GroupTheory.GroupAction.ConjAct
import Mathlib.GroupTheory.GroupAction.Quotient
import Mathlib.GroupTheory.QuotientGroup
import Mathlib.Topology.Algebra.Monoid
import Mathlib.Topology.Algebra.Constructions
#align_import topology.algebra.group.basic from "leanprover-community/mathlib"@"3b1890e71632be9e3b2086ab512c3259a7e9a3ef"
/-!
# Topological groups
This file defines the following typeclasses:
* `TopologicalGroup`, `TopologicalAddGroup`: multiplicative and additive topological groups,
i.e., groups with continuous `(*)` and `(⁻¹)` / `(+)` and `(-)`;
* `ContinuousSub G` means that `G` has a continuous subtraction operation.
There is an instance deducing `ContinuousSub` from `TopologicalGroup` but we use a separate
typeclass because, e.g., `ℕ` and `ℝ≥0` have continuous subtraction but are not additive groups.
We also define `Homeomorph` versions of several `Equiv`s: `Homeomorph.mulLeft`,
`Homeomorph.mulRight`, `Homeomorph.inv`, and prove a few facts about neighbourhood filters in
groups.
## Tags
topological space, group, topological group
-/
open scoped Classical
open Set Filter TopologicalSpace Function Topology Pointwise MulOpposite
universe u v w x
variable {G : Type w} {H : Type x} {α : Type u} {β : Type v}
section ContinuousMulGroup
/-!
### Groups with continuous multiplication
In this section we prove a few statements about groups with continuous `(*)`.
-/
variable [TopologicalSpace G] [Group G] [ContinuousMul G]
/-- Multiplication from the left in a topological group as a homeomorphism. -/
@[to_additive "Addition from the left in a topological additive group as a homeomorphism."]
protected def Homeomorph.mulLeft (a : G) : G ≃ₜ G :=
{ Equiv.mulLeft a with
continuous_toFun := continuous_const.mul continuous_id
continuous_invFun := continuous_const.mul continuous_id }
#align homeomorph.mul_left Homeomorph.mulLeft
#align homeomorph.add_left Homeomorph.addLeft
@[to_additive (attr := simp)]
theorem Homeomorph.coe_mulLeft (a : G) : ⇑(Homeomorph.mulLeft a) = (a * ·) :=
rfl
#align homeomorph.coe_mul_left Homeomorph.coe_mulLeft
#align homeomorph.coe_add_left Homeomorph.coe_addLeft
@[to_additive]
theorem Homeomorph.mulLeft_symm (a : G) : (Homeomorph.mulLeft a).symm = Homeomorph.mulLeft a⁻¹ := by
ext
rfl
#align homeomorph.mul_left_symm Homeomorph.mulLeft_symm
#align homeomorph.add_left_symm Homeomorph.addLeft_symm
@[to_additive]
lemma isOpenMap_mul_left (a : G) : IsOpenMap (a * ·) := (Homeomorph.mulLeft a).isOpenMap
#align is_open_map_mul_left isOpenMap_mul_left
#align is_open_map_add_left isOpenMap_add_left
@[to_additive IsOpen.left_addCoset]
theorem IsOpen.leftCoset {U : Set G} (h : IsOpen U) (x : G) : IsOpen (x • U) :=
isOpenMap_mul_left x _ h
#align is_open.left_coset IsOpen.leftCoset
#align is_open.left_add_coset IsOpen.left_addCoset
@[to_additive]
lemma isClosedMap_mul_left (a : G) : IsClosedMap (a * ·) := (Homeomorph.mulLeft a).isClosedMap
#align is_closed_map_mul_left isClosedMap_mul_left
#align is_closed_map_add_left isClosedMap_add_left
@[to_additive IsClosed.left_addCoset]
theorem IsClosed.leftCoset {U : Set G} (h : IsClosed U) (x : G) : IsClosed (x • U) :=
isClosedMap_mul_left x _ h
#align is_closed.left_coset IsClosed.leftCoset
#align is_closed.left_add_coset IsClosed.left_addCoset
/-- Multiplication from the right in a topological group as a homeomorphism. -/
@[to_additive "Addition from the right in a topological additive group as a homeomorphism."]
protected def Homeomorph.mulRight (a : G) : G ≃ₜ G :=
{ Equiv.mulRight a with
continuous_toFun := continuous_id.mul continuous_const
continuous_invFun := continuous_id.mul continuous_const }
#align homeomorph.mul_right Homeomorph.mulRight
#align homeomorph.add_right Homeomorph.addRight
@[to_additive (attr := simp)]
lemma Homeomorph.coe_mulRight (a : G) : ⇑(Homeomorph.mulRight a) = (· * a) := rfl
#align homeomorph.coe_mul_right Homeomorph.coe_mulRight
#align homeomorph.coe_add_right Homeomorph.coe_addRight
@[to_additive]
theorem Homeomorph.mulRight_symm (a : G) :
(Homeomorph.mulRight a).symm = Homeomorph.mulRight a⁻¹ := by
ext
rfl
#align homeomorph.mul_right_symm Homeomorph.mulRight_symm
#align homeomorph.add_right_symm Homeomorph.addRight_symm
@[to_additive]
theorem isOpenMap_mul_right (a : G) : IsOpenMap (· * a) :=
(Homeomorph.mulRight a).isOpenMap
#align is_open_map_mul_right isOpenMap_mul_right
#align is_open_map_add_right isOpenMap_add_right
@[to_additive IsOpen.right_addCoset]
theorem IsOpen.rightCoset {U : Set G} (h : IsOpen U) (x : G) : IsOpen (op x • U) :=
isOpenMap_mul_right x _ h
#align is_open.right_coset IsOpen.rightCoset
#align is_open.right_add_coset IsOpen.right_addCoset
@[to_additive]
theorem isClosedMap_mul_right (a : G) : IsClosedMap (· * a) :=
(Homeomorph.mulRight a).isClosedMap
#align is_closed_map_mul_right isClosedMap_mul_right
#align is_closed_map_add_right isClosedMap_add_right
@[to_additive IsClosed.right_addCoset]
theorem IsClosed.rightCoset {U : Set G} (h : IsClosed U) (x : G) : IsClosed (op x • U) :=
isClosedMap_mul_right x _ h
#align is_closed.right_coset IsClosed.rightCoset
#align is_closed.right_add_coset IsClosed.right_addCoset
@[to_additive]
theorem discreteTopology_of_isOpen_singleton_one (h : IsOpen ({1} : Set G)) :
DiscreteTopology G := by
rw [← singletons_open_iff_discrete]
intro g
suffices {g} = (g⁻¹ * ·) ⁻¹' {1} by
rw [this]
exact (continuous_mul_left g⁻¹).isOpen_preimage _ h
simp only [mul_one, Set.preimage_mul_left_singleton, eq_self_iff_true, inv_inv,
Set.singleton_eq_singleton_iff]
#align discrete_topology_of_open_singleton_one discreteTopology_of_isOpen_singleton_one
#align discrete_topology_of_open_singleton_zero discreteTopology_of_isOpen_singleton_zero
@[to_additive]
theorem discreteTopology_iff_isOpen_singleton_one : DiscreteTopology G ↔ IsOpen ({1} : Set G) :=
⟨fun h => forall_open_iff_discrete.mpr h {1}, discreteTopology_of_isOpen_singleton_one⟩
#align discrete_topology_iff_open_singleton_one discreteTopology_iff_isOpen_singleton_one
#align discrete_topology_iff_open_singleton_zero discreteTopology_iff_isOpen_singleton_zero
end ContinuousMulGroup
/-!
### `ContinuousInv` and `ContinuousNeg`
-/
/-- Basic hypothesis to talk about a topological additive group. A topological additive group
over `M`, for example, is obtained by requiring the instances `AddGroup M` and
`ContinuousAdd M` and `ContinuousNeg M`. -/
class ContinuousNeg (G : Type u) [TopologicalSpace G] [Neg G] : Prop where
continuous_neg : Continuous fun a : G => -a
#align has_continuous_neg ContinuousNeg
-- Porting note: added
attribute [continuity] ContinuousNeg.continuous_neg
/-- Basic hypothesis to talk about a topological group. A topological group over `M`, for example,
is obtained by requiring the instances `Group M` and `ContinuousMul M` and
`ContinuousInv M`. -/
@[to_additive (attr := continuity)]
class ContinuousInv (G : Type u) [TopologicalSpace G] [Inv G] : Prop where
continuous_inv : Continuous fun a : G => a⁻¹
#align has_continuous_inv ContinuousInv
--#align has_continuous_neg ContinuousNeg
-- Porting note: added
attribute [continuity] ContinuousInv.continuous_inv
export ContinuousInv (continuous_inv)
export ContinuousNeg (continuous_neg)
section ContinuousInv
variable [TopologicalSpace G] [Inv G] [ContinuousInv G]
@[to_additive]
protected theorem Specializes.inv {x y : G} (h : x ⤳ y) : (x⁻¹) ⤳ (y⁻¹) :=
h.map continuous_inv
@[to_additive]
protected theorem Inseparable.inv {x y : G} (h : Inseparable x y) : Inseparable (x⁻¹) (y⁻¹) :=
h.map continuous_inv
@[to_additive]
protected theorem Specializes.zpow {G : Type*} [DivInvMonoid G] [TopologicalSpace G]
[ContinuousMul G] [ContinuousInv G] {x y : G} (h : x ⤳ y) : ∀ m : ℤ, (x ^ m) ⤳ (y ^ m)
| .ofNat n => by simpa using h.pow n
| .negSucc n => by simpa using (h.pow (n + 1)).inv
@[to_additive]
protected theorem Inseparable.zpow {G : Type*} [DivInvMonoid G] [TopologicalSpace G]
[ContinuousMul G] [ContinuousInv G] {x y : G} (h : Inseparable x y) (m : ℤ) :
Inseparable (x ^ m) (y ^ m) :=
(h.specializes.zpow m).antisymm (h.specializes'.zpow m)
@[to_additive]
instance : ContinuousInv (ULift G) :=
⟨continuous_uLift_up.comp (continuous_inv.comp continuous_uLift_down)⟩
@[to_additive]
theorem continuousOn_inv {s : Set G} : ContinuousOn Inv.inv s :=
continuous_inv.continuousOn
#align continuous_on_inv continuousOn_inv
#align continuous_on_neg continuousOn_neg
@[to_additive]
theorem continuousWithinAt_inv {s : Set G} {x : G} : ContinuousWithinAt Inv.inv s x :=
continuous_inv.continuousWithinAt
#align continuous_within_at_inv continuousWithinAt_inv
#align continuous_within_at_neg continuousWithinAt_neg
@[to_additive]
theorem continuousAt_inv {x : G} : ContinuousAt Inv.inv x :=
continuous_inv.continuousAt
#align continuous_at_inv continuousAt_inv
#align continuous_at_neg continuousAt_neg
@[to_additive]
theorem tendsto_inv (a : G) : Tendsto Inv.inv (𝓝 a) (𝓝 a⁻¹) :=
continuousAt_inv
#align tendsto_inv tendsto_inv
#align tendsto_neg tendsto_neg
/-- If a function converges to a value in a multiplicative topological group, then its inverse
converges to the inverse of this value. For the version in normed fields assuming additionally
that the limit is nonzero, use `Tendsto.inv'`. -/
@[to_additive
"If a function converges to a value in an additive topological group, then its
negation converges to the negation of this value."]
theorem Filter.Tendsto.inv {f : α → G} {l : Filter α} {y : G} (h : Tendsto f l (𝓝 y)) :
Tendsto (fun x => (f x)⁻¹) l (𝓝 y⁻¹) :=
(continuous_inv.tendsto y).comp h
#align filter.tendsto.inv Filter.Tendsto.inv
#align filter.tendsto.neg Filter.Tendsto.neg
variable [TopologicalSpace α] {f : α → G} {s : Set α} {x : α}
@[to_additive (attr := continuity, fun_prop)]
theorem Continuous.inv (hf : Continuous f) : Continuous fun x => (f x)⁻¹ :=
continuous_inv.comp hf
#align continuous.inv Continuous.inv
#align continuous.neg Continuous.neg
@[to_additive (attr := fun_prop)]
theorem ContinuousAt.inv (hf : ContinuousAt f x) : ContinuousAt (fun x => (f x)⁻¹) x :=
continuousAt_inv.comp hf
#align continuous_at.inv ContinuousAt.inv
#align continuous_at.neg ContinuousAt.neg
@[to_additive (attr := fun_prop)]
theorem ContinuousOn.inv (hf : ContinuousOn f s) : ContinuousOn (fun x => (f x)⁻¹) s :=
continuous_inv.comp_continuousOn hf
#align continuous_on.inv ContinuousOn.inv
#align continuous_on.neg ContinuousOn.neg
@[to_additive]
theorem ContinuousWithinAt.inv (hf : ContinuousWithinAt f s x) :
ContinuousWithinAt (fun x => (f x)⁻¹) s x :=
Filter.Tendsto.inv hf
#align continuous_within_at.inv ContinuousWithinAt.inv
#align continuous_within_at.neg ContinuousWithinAt.neg
@[to_additive]
instance Prod.continuousInv [TopologicalSpace H] [Inv H] [ContinuousInv H] :
ContinuousInv (G × H) :=
⟨continuous_inv.fst'.prod_mk continuous_inv.snd'⟩
variable {ι : Type*}
@[to_additive]
instance Pi.continuousInv {C : ι → Type*} [∀ i, TopologicalSpace (C i)] [∀ i, Inv (C i)]
[∀ i, ContinuousInv (C i)] : ContinuousInv (∀ i, C i) where
continuous_inv := continuous_pi fun i => (continuous_apply i).inv
#align pi.has_continuous_inv Pi.continuousInv
#align pi.has_continuous_neg Pi.continuousNeg
/-- A version of `Pi.continuousInv` for non-dependent functions. It is needed because sometimes
Lean fails to use `Pi.continuousInv` for non-dependent functions. -/
@[to_additive
"A version of `Pi.continuousNeg` for non-dependent functions. It is needed
because sometimes Lean fails to use `Pi.continuousNeg` for non-dependent functions."]
instance Pi.has_continuous_inv' : ContinuousInv (ι → G) :=
Pi.continuousInv
#align pi.has_continuous_inv' Pi.has_continuous_inv'
#align pi.has_continuous_neg' Pi.has_continuous_neg'
@[to_additive]
instance (priority := 100) continuousInv_of_discreteTopology [TopologicalSpace H] [Inv H]
[DiscreteTopology H] : ContinuousInv H :=
⟨continuous_of_discreteTopology⟩
#align has_continuous_inv_of_discrete_topology continuousInv_of_discreteTopology
#align has_continuous_neg_of_discrete_topology continuousNeg_of_discreteTopology
section PointwiseLimits
variable (G₁ G₂ : Type*) [TopologicalSpace G₂] [T2Space G₂]
@[to_additive]
theorem isClosed_setOf_map_inv [Inv G₁] [Inv G₂] [ContinuousInv G₂] :
IsClosed { f : G₁ → G₂ | ∀ x, f x⁻¹ = (f x)⁻¹ } := by
simp only [setOf_forall]
exact isClosed_iInter fun i => isClosed_eq (continuous_apply _) (continuous_apply _).inv
#align is_closed_set_of_map_inv isClosed_setOf_map_inv
#align is_closed_set_of_map_neg isClosed_setOf_map_neg
end PointwiseLimits
instance [TopologicalSpace H] [Inv H] [ContinuousInv H] : ContinuousNeg (Additive H) where
continuous_neg := @continuous_inv H _ _ _
instance [TopologicalSpace H] [Neg H] [ContinuousNeg H] : ContinuousInv (Multiplicative H) where
continuous_inv := @continuous_neg H _ _ _
end ContinuousInv
section ContinuousInvolutiveInv
variable [TopologicalSpace G] [InvolutiveInv G] [ContinuousInv G] {s : Set G}
@[to_additive]
theorem IsCompact.inv (hs : IsCompact s) : IsCompact s⁻¹ := by
rw [← image_inv]
exact hs.image continuous_inv
#align is_compact.inv IsCompact.inv
#align is_compact.neg IsCompact.neg
variable (G)
/-- Inversion in a topological group as a homeomorphism. -/
@[to_additive "Negation in a topological group as a homeomorphism."]
protected def Homeomorph.inv (G : Type*) [TopologicalSpace G] [InvolutiveInv G]
[ContinuousInv G] : G ≃ₜ G :=
{ Equiv.inv G with
continuous_toFun := continuous_inv
continuous_invFun := continuous_inv }
#align homeomorph.inv Homeomorph.inv
#align homeomorph.neg Homeomorph.neg
@[to_additive (attr := simp)]
lemma Homeomorph.coe_inv {G : Type*} [TopologicalSpace G] [InvolutiveInv G] [ContinuousInv G] :
⇑(Homeomorph.inv G) = Inv.inv := rfl
@[to_additive]
theorem isOpenMap_inv : IsOpenMap (Inv.inv : G → G) :=
(Homeomorph.inv _).isOpenMap
#align is_open_map_inv isOpenMap_inv
#align is_open_map_neg isOpenMap_neg
@[to_additive]
theorem isClosedMap_inv : IsClosedMap (Inv.inv : G → G) :=
(Homeomorph.inv _).isClosedMap
#align is_closed_map_inv isClosedMap_inv
#align is_closed_map_neg isClosedMap_neg
variable {G}
@[to_additive]
theorem IsOpen.inv (hs : IsOpen s) : IsOpen s⁻¹ :=
hs.preimage continuous_inv
#align is_open.inv IsOpen.inv
#align is_open.neg IsOpen.neg
@[to_additive]
theorem IsClosed.inv (hs : IsClosed s) : IsClosed s⁻¹ :=
hs.preimage continuous_inv
#align is_closed.inv IsClosed.inv
#align is_closed.neg IsClosed.neg
@[to_additive]
theorem inv_closure : ∀ s : Set G, (closure s)⁻¹ = closure s⁻¹ :=
(Homeomorph.inv G).preimage_closure
#align inv_closure inv_closure
#align neg_closure neg_closure
end ContinuousInvolutiveInv
section LatticeOps
variable {ι' : Sort*} [Inv G]
@[to_additive]
theorem continuousInv_sInf {ts : Set (TopologicalSpace G)}
(h : ∀ t ∈ ts, @ContinuousInv G t _) : @ContinuousInv G (sInf ts) _ :=
letI := sInf ts
{ continuous_inv :=
continuous_sInf_rng.2 fun t ht =>
continuous_sInf_dom ht (@ContinuousInv.continuous_inv G t _ (h t ht)) }
#align has_continuous_inv_Inf continuousInv_sInf
#align has_continuous_neg_Inf continuousNeg_sInf
@[to_additive]
theorem continuousInv_iInf {ts' : ι' → TopologicalSpace G}
(h' : ∀ i, @ContinuousInv G (ts' i) _) : @ContinuousInv G (⨅ i, ts' i) _ := by
rw [← sInf_range]
exact continuousInv_sInf (Set.forall_mem_range.mpr h')
#align has_continuous_inv_infi continuousInv_iInf
#align has_continuous_neg_infi continuousNeg_iInf
@[to_additive]
theorem continuousInv_inf {t₁ t₂ : TopologicalSpace G} (h₁ : @ContinuousInv G t₁ _)
(h₂ : @ContinuousInv G t₂ _) : @ContinuousInv G (t₁ ⊓ t₂) _ := by
rw [inf_eq_iInf]
refine continuousInv_iInf fun b => ?_
cases b <;> assumption
#align has_continuous_inv_inf continuousInv_inf
#align has_continuous_neg_inf continuousNeg_inf
end LatticeOps
@[to_additive]
theorem Inducing.continuousInv {G H : Type*} [Inv G] [Inv H] [TopologicalSpace G]
[TopologicalSpace H] [ContinuousInv H] {f : G → H} (hf : Inducing f)
(hf_inv : ∀ x, f x⁻¹ = (f x)⁻¹) : ContinuousInv G :=
⟨hf.continuous_iff.2 <| by simpa only [(· ∘ ·), hf_inv] using hf.continuous.inv⟩
#align inducing.has_continuous_inv Inducing.continuousInv
#align inducing.has_continuous_neg Inducing.continuousNeg
section TopologicalGroup
/-!
### Topological groups
A topological group is a group in which the multiplication and inversion operations are
continuous. Topological additive groups are defined in the same way. Equivalently, we can require
that the division operation `x y ↦ x * y⁻¹` (resp., subtraction) is continuous.
-/
-- Porting note (#11215): TODO should this docstring be extended
-- to match the multiplicative version?
/-- A topological (additive) group is a group in which the addition and negation operations are
continuous. -/
class TopologicalAddGroup (G : Type u) [TopologicalSpace G] [AddGroup G] extends
ContinuousAdd G, ContinuousNeg G : Prop
#align topological_add_group TopologicalAddGroup
/-- A topological group is a group in which the multiplication and inversion operations are
continuous.
When you declare an instance that does not already have a `UniformSpace` instance,
you should also provide an instance of `UniformSpace` and `UniformGroup` using
`TopologicalGroup.toUniformSpace` and `topologicalCommGroup_isUniform`. -/
-- Porting note: check that these ↑ names exist once they've been ported in the future.
@[to_additive]
class TopologicalGroup (G : Type*) [TopologicalSpace G] [Group G] extends ContinuousMul G,
ContinuousInv G : Prop
#align topological_group TopologicalGroup
--#align topological_add_group TopologicalAddGroup
section Conj
instance ConjAct.units_continuousConstSMul {M} [Monoid M] [TopologicalSpace M]
[ContinuousMul M] : ContinuousConstSMul (ConjAct Mˣ) M :=
⟨fun _ => (continuous_const.mul continuous_id).mul continuous_const⟩
#align conj_act.units_has_continuous_const_smul ConjAct.units_continuousConstSMul
variable [TopologicalSpace G] [Inv G] [Mul G] [ContinuousMul G]
/-- Conjugation is jointly continuous on `G × G` when both `mul` and `inv` are continuous. -/
@[to_additive
"Conjugation is jointly continuous on `G × G` when both `add` and `neg` are continuous."]
theorem TopologicalGroup.continuous_conj_prod [ContinuousInv G] :
Continuous fun g : G × G => g.fst * g.snd * g.fst⁻¹ :=
continuous_mul.mul (continuous_inv.comp continuous_fst)
#align topological_group.continuous_conj_prod TopologicalGroup.continuous_conj_prod
#align topological_add_group.continuous_conj_sum TopologicalAddGroup.continuous_conj_sum
/-- Conjugation by a fixed element is continuous when `mul` is continuous. -/
@[to_additive (attr := continuity)
"Conjugation by a fixed element is continuous when `add` is continuous."]
theorem TopologicalGroup.continuous_conj (g : G) : Continuous fun h : G => g * h * g⁻¹ :=
(continuous_mul_right g⁻¹).comp (continuous_mul_left g)
#align topological_group.continuous_conj TopologicalGroup.continuous_conj
#align topological_add_group.continuous_conj TopologicalAddGroup.continuous_conj
/-- Conjugation acting on fixed element of the group is continuous when both `mul` and
`inv` are continuous. -/
@[to_additive (attr := continuity)
"Conjugation acting on fixed element of the additive group is continuous when both
`add` and `neg` are continuous."]
theorem TopologicalGroup.continuous_conj' [ContinuousInv G] (h : G) :
Continuous fun g : G => g * h * g⁻¹ :=
(continuous_mul_right h).mul continuous_inv
#align topological_group.continuous_conj' TopologicalGroup.continuous_conj'
#align topological_add_group.continuous_conj' TopologicalAddGroup.continuous_conj'
end Conj
variable [TopologicalSpace G] [Group G] [TopologicalGroup G] [TopologicalSpace α] {f : α → G}
{s : Set α} {x : α}
instance : TopologicalGroup (ULift G) where
section ZPow
@[to_additive (attr := continuity)]
theorem continuous_zpow : ∀ z : ℤ, Continuous fun a : G => a ^ z
| Int.ofNat n => by simpa using continuous_pow n
| Int.negSucc n => by simpa using (continuous_pow (n + 1)).inv
#align continuous_zpow continuous_zpow
#align continuous_zsmul continuous_zsmul
instance AddGroup.continuousConstSMul_int {A} [AddGroup A] [TopologicalSpace A]
[TopologicalAddGroup A] : ContinuousConstSMul ℤ A :=
⟨continuous_zsmul⟩
#align add_group.has_continuous_const_smul_int AddGroup.continuousConstSMul_int
instance AddGroup.continuousSMul_int {A} [AddGroup A] [TopologicalSpace A]
[TopologicalAddGroup A] : ContinuousSMul ℤ A :=
⟨continuous_prod_of_discrete_left.mpr continuous_zsmul⟩
#align add_group.has_continuous_smul_int AddGroup.continuousSMul_int
@[to_additive (attr := continuity, fun_prop)]
theorem Continuous.zpow {f : α → G} (h : Continuous f) (z : ℤ) : Continuous fun b => f b ^ z :=
(continuous_zpow z).comp h
#align continuous.zpow Continuous.zpow
#align continuous.zsmul Continuous.zsmul
@[to_additive]
theorem continuousOn_zpow {s : Set G} (z : ℤ) : ContinuousOn (fun x => x ^ z) s :=
(continuous_zpow z).continuousOn
#align continuous_on_zpow continuousOn_zpow
#align continuous_on_zsmul continuousOn_zsmul
@[to_additive]
theorem continuousAt_zpow (x : G) (z : ℤ) : ContinuousAt (fun x => x ^ z) x :=
(continuous_zpow z).continuousAt
#align continuous_at_zpow continuousAt_zpow
#align continuous_at_zsmul continuousAt_zsmul
@[to_additive]
theorem Filter.Tendsto.zpow {α} {l : Filter α} {f : α → G} {x : G} (hf : Tendsto f l (𝓝 x))
(z : ℤ) : Tendsto (fun x => f x ^ z) l (𝓝 (x ^ z)) :=
(continuousAt_zpow _ _).tendsto.comp hf
#align filter.tendsto.zpow Filter.Tendsto.zpow
#align filter.tendsto.zsmul Filter.Tendsto.zsmul
@[to_additive]
theorem ContinuousWithinAt.zpow {f : α → G} {x : α} {s : Set α} (hf : ContinuousWithinAt f s x)
(z : ℤ) : ContinuousWithinAt (fun x => f x ^ z) s x :=
Filter.Tendsto.zpow hf z
#align continuous_within_at.zpow ContinuousWithinAt.zpow
#align continuous_within_at.zsmul ContinuousWithinAt.zsmul
@[to_additive (attr := fun_prop)]
theorem ContinuousAt.zpow {f : α → G} {x : α} (hf : ContinuousAt f x) (z : ℤ) :
ContinuousAt (fun x => f x ^ z) x :=
Filter.Tendsto.zpow hf z
#align continuous_at.zpow ContinuousAt.zpow
#align continuous_at.zsmul ContinuousAt.zsmul
@[to_additive (attr := fun_prop)]
theorem ContinuousOn.zpow {f : α → G} {s : Set α} (hf : ContinuousOn f s) (z : ℤ) :
ContinuousOn (fun x => f x ^ z) s := fun x hx => (hf x hx).zpow z
#align continuous_on.zpow ContinuousOn.zpow
#align continuous_on.zsmul ContinuousOn.zsmul
end ZPow
section OrderedCommGroup
variable [TopologicalSpace H] [OrderedCommGroup H] [ContinuousInv H]
@[to_additive]
theorem tendsto_inv_nhdsWithin_Ioi {a : H} : Tendsto Inv.inv (𝓝[>] a) (𝓝[<] a⁻¹) :=
(continuous_inv.tendsto a).inf <| by simp [tendsto_principal_principal]
#align tendsto_inv_nhds_within_Ioi tendsto_inv_nhdsWithin_Ioi
#align tendsto_neg_nhds_within_Ioi tendsto_neg_nhdsWithin_Ioi
@[to_additive]
theorem tendsto_inv_nhdsWithin_Iio {a : H} : Tendsto Inv.inv (𝓝[<] a) (𝓝[>] a⁻¹) :=
(continuous_inv.tendsto a).inf <| by simp [tendsto_principal_principal]
#align tendsto_inv_nhds_within_Iio tendsto_inv_nhdsWithin_Iio
#align tendsto_neg_nhds_within_Iio tendsto_neg_nhdsWithin_Iio
@[to_additive]
theorem tendsto_inv_nhdsWithin_Ioi_inv {a : H} : Tendsto Inv.inv (𝓝[>] a⁻¹) (𝓝[<] a) := by
simpa only [inv_inv] using @tendsto_inv_nhdsWithin_Ioi _ _ _ _ a⁻¹
#align tendsto_inv_nhds_within_Ioi_inv tendsto_inv_nhdsWithin_Ioi_inv
#align tendsto_neg_nhds_within_Ioi_neg tendsto_neg_nhdsWithin_Ioi_neg
@[to_additive]
theorem tendsto_inv_nhdsWithin_Iio_inv {a : H} : Tendsto Inv.inv (𝓝[<] a⁻¹) (𝓝[>] a) := by
simpa only [inv_inv] using @tendsto_inv_nhdsWithin_Iio _ _ _ _ a⁻¹
#align tendsto_inv_nhds_within_Iio_inv tendsto_inv_nhdsWithin_Iio_inv
#align tendsto_neg_nhds_within_Iio_neg tendsto_neg_nhdsWithin_Iio_neg
@[to_additive]
theorem tendsto_inv_nhdsWithin_Ici {a : H} : Tendsto Inv.inv (𝓝[≥] a) (𝓝[≤] a⁻¹) :=
(continuous_inv.tendsto a).inf <| by simp [tendsto_principal_principal]
#align tendsto_inv_nhds_within_Ici tendsto_inv_nhdsWithin_Ici
#align tendsto_neg_nhds_within_Ici tendsto_neg_nhdsWithin_Ici
@[to_additive]
theorem tendsto_inv_nhdsWithin_Iic {a : H} : Tendsto Inv.inv (𝓝[≤] a) (𝓝[≥] a⁻¹) :=
(continuous_inv.tendsto a).inf <| by simp [tendsto_principal_principal]
#align tendsto_inv_nhds_within_Iic tendsto_inv_nhdsWithin_Iic
#align tendsto_neg_nhds_within_Iic tendsto_neg_nhdsWithin_Iic
@[to_additive]
theorem tendsto_inv_nhdsWithin_Ici_inv {a : H} : Tendsto Inv.inv (𝓝[≥] a⁻¹) (𝓝[≤] a) := by
simpa only [inv_inv] using @tendsto_inv_nhdsWithin_Ici _ _ _ _ a⁻¹
#align tendsto_inv_nhds_within_Ici_inv tendsto_inv_nhdsWithin_Ici_inv
#align tendsto_neg_nhds_within_Ici_neg tendsto_neg_nhdsWithin_Ici_neg
@[to_additive]
theorem tendsto_inv_nhdsWithin_Iic_inv {a : H} : Tendsto Inv.inv (𝓝[≤] a⁻¹) (𝓝[≥] a) := by
simpa only [inv_inv] using @tendsto_inv_nhdsWithin_Iic _ _ _ _ a⁻¹
#align tendsto_inv_nhds_within_Iic_inv tendsto_inv_nhdsWithin_Iic_inv
#align tendsto_neg_nhds_within_Iic_neg tendsto_neg_nhdsWithin_Iic_neg
end OrderedCommGroup
@[to_additive]
instance [TopologicalSpace H] [Group H] [TopologicalGroup H] : TopologicalGroup (G × H) where
continuous_inv := continuous_inv.prod_map continuous_inv
@[to_additive]
instance Pi.topologicalGroup {C : β → Type*} [∀ b, TopologicalSpace (C b)] [∀ b, Group (C b)]
[∀ b, TopologicalGroup (C b)] : TopologicalGroup (∀ b, C b) where
continuous_inv := continuous_pi fun i => (continuous_apply i).inv
#align pi.topological_group Pi.topologicalGroup
#align pi.topological_add_group Pi.topologicalAddGroup
open MulOpposite
@[to_additive]
instance [Inv α] [ContinuousInv α] : ContinuousInv αᵐᵒᵖ :=
opHomeomorph.symm.inducing.continuousInv unop_inv
/-- If multiplication is continuous in `α`, then it also is in `αᵐᵒᵖ`. -/
@[to_additive "If addition is continuous in `α`, then it also is in `αᵃᵒᵖ`."]
instance [Group α] [TopologicalGroup α] : TopologicalGroup αᵐᵒᵖ where
variable (G)
@[to_additive]
theorem nhds_one_symm : comap Inv.inv (𝓝 (1 : G)) = 𝓝 (1 : G) :=
((Homeomorph.inv G).comap_nhds_eq _).trans (congr_arg nhds inv_one)
#align nhds_one_symm nhds_one_symm
#align nhds_zero_symm nhds_zero_symm
@[to_additive]
theorem nhds_one_symm' : map Inv.inv (𝓝 (1 : G)) = 𝓝 (1 : G) :=
((Homeomorph.inv G).map_nhds_eq _).trans (congr_arg nhds inv_one)
#align nhds_one_symm' nhds_one_symm'
#align nhds_zero_symm' nhds_zero_symm'
@[to_additive]
theorem inv_mem_nhds_one {S : Set G} (hS : S ∈ (𝓝 1 : Filter G)) : S⁻¹ ∈ 𝓝 (1 : G) := by
rwa [← nhds_one_symm'] at hS
#align inv_mem_nhds_one inv_mem_nhds_one
#align neg_mem_nhds_zero neg_mem_nhds_zero
/-- The map `(x, y) ↦ (x, x * y)` as a homeomorphism. This is a shear mapping. -/
@[to_additive "The map `(x, y) ↦ (x, x + y)` as a homeomorphism. This is a shear mapping."]
protected def Homeomorph.shearMulRight : G × G ≃ₜ G × G :=
{ Equiv.prodShear (Equiv.refl _) Equiv.mulLeft with
continuous_toFun := continuous_fst.prod_mk continuous_mul
continuous_invFun := continuous_fst.prod_mk <| continuous_fst.inv.mul continuous_snd }
#align homeomorph.shear_mul_right Homeomorph.shearMulRight
#align homeomorph.shear_add_right Homeomorph.shearAddRight
@[to_additive (attr := simp)]
theorem Homeomorph.shearMulRight_coe :
⇑(Homeomorph.shearMulRight G) = fun z : G × G => (z.1, z.1 * z.2) :=
rfl
#align homeomorph.shear_mul_right_coe Homeomorph.shearMulRight_coe
#align homeomorph.shear_add_right_coe Homeomorph.shearAddRight_coe
@[to_additive (attr := simp)]
theorem Homeomorph.shearMulRight_symm_coe :
⇑(Homeomorph.shearMulRight G).symm = fun z : G × G => (z.1, z.1⁻¹ * z.2) :=
rfl
#align homeomorph.shear_mul_right_symm_coe Homeomorph.shearMulRight_symm_coe
#align homeomorph.shear_add_right_symm_coe Homeomorph.shearAddRight_symm_coe
variable {G}
@[to_additive]
protected theorem Inducing.topologicalGroup {F : Type*} [Group H] [TopologicalSpace H]
[FunLike F H G] [MonoidHomClass F H G] (f : F) (hf : Inducing f) : TopologicalGroup H :=
{ toContinuousMul := hf.continuousMul _
toContinuousInv := hf.continuousInv (map_inv f) }
#align inducing.topological_group Inducing.topologicalGroup
#align inducing.topological_add_group Inducing.topologicalAddGroup
@[to_additive]
-- Porting note: removed `protected` (needs to be in namespace)
theorem topologicalGroup_induced {F : Type*} [Group H] [FunLike F H G] [MonoidHomClass F H G]
(f : F) :
@TopologicalGroup H (induced f ‹_›) _ :=
letI := induced f ‹_›
Inducing.topologicalGroup f ⟨rfl⟩
#align topological_group_induced topologicalGroup_induced
#align topological_add_group_induced topologicalAddGroup_induced
namespace Subgroup
@[to_additive]
instance (S : Subgroup G) : TopologicalGroup S :=
Inducing.topologicalGroup S.subtype inducing_subtype_val
end Subgroup
/-- The (topological-space) closure of a subgroup of a topological group is
itself a subgroup. -/
@[to_additive
"The (topological-space) closure of an additive subgroup of an additive topological group is
itself an additive subgroup."]
def Subgroup.topologicalClosure (s : Subgroup G) : Subgroup G :=
{ s.toSubmonoid.topologicalClosure with
carrier := _root_.closure (s : Set G)
inv_mem' := fun {g} hg => by simpa only [← Set.mem_inv, inv_closure, inv_coe_set] using hg }
#align subgroup.topological_closure Subgroup.topologicalClosure
#align add_subgroup.topological_closure AddSubgroup.topologicalClosure
@[to_additive (attr := simp)]
theorem Subgroup.topologicalClosure_coe {s : Subgroup G} :
(s.topologicalClosure : Set G) = _root_.closure s :=
rfl
#align subgroup.topological_closure_coe Subgroup.topologicalClosure_coe
#align add_subgroup.topological_closure_coe AddSubgroup.topologicalClosure_coe
@[to_additive]
theorem Subgroup.le_topologicalClosure (s : Subgroup G) : s ≤ s.topologicalClosure :=
_root_.subset_closure
#align subgroup.le_topological_closure Subgroup.le_topologicalClosure
#align add_subgroup.le_topological_closure AddSubgroup.le_topologicalClosure
@[to_additive]
theorem Subgroup.isClosed_topologicalClosure (s : Subgroup G) :
IsClosed (s.topologicalClosure : Set G) := isClosed_closure
#align subgroup.is_closed_topological_closure Subgroup.isClosed_topologicalClosure
#align add_subgroup.is_closed_topological_closure AddSubgroup.isClosed_topologicalClosure
@[to_additive]
theorem Subgroup.topologicalClosure_minimal (s : Subgroup G) {t : Subgroup G} (h : s ≤ t)
(ht : IsClosed (t : Set G)) : s.topologicalClosure ≤ t :=
closure_minimal h ht
#align subgroup.topological_closure_minimal Subgroup.topologicalClosure_minimal
#align add_subgroup.topological_closure_minimal AddSubgroup.topologicalClosure_minimal
@[to_additive]
theorem DenseRange.topologicalClosure_map_subgroup [Group H] [TopologicalSpace H]
[TopologicalGroup H] {f : G →* H} (hf : Continuous f) (hf' : DenseRange f) {s : Subgroup G}
(hs : s.topologicalClosure = ⊤) : (s.map f).topologicalClosure = ⊤ := by
rw [SetLike.ext'_iff] at hs ⊢
simp only [Subgroup.topologicalClosure_coe, Subgroup.coe_top, ← dense_iff_closure_eq] at hs ⊢
exact hf'.dense_image hf hs
#align dense_range.topological_closure_map_subgroup DenseRange.topologicalClosure_map_subgroup
#align dense_range.topological_closure_map_add_subgroup DenseRange.topologicalClosure_map_addSubgroup
/-- The topological closure of a normal subgroup is normal. -/
@[to_additive "The topological closure of a normal additive subgroup is normal."]
theorem Subgroup.is_normal_topologicalClosure {G : Type*} [TopologicalSpace G] [Group G]
[TopologicalGroup G] (N : Subgroup G) [N.Normal] : (Subgroup.topologicalClosure N).Normal where
conj_mem n hn g := by
apply map_mem_closure (TopologicalGroup.continuous_conj g) hn
exact fun m hm => Subgroup.Normal.conj_mem inferInstance m hm g
#align subgroup.is_normal_topological_closure Subgroup.is_normal_topologicalClosure
#align add_subgroup.is_normal_topological_closure AddSubgroup.is_normal_topologicalClosure
@[to_additive]
theorem mul_mem_connectedComponent_one {G : Type*} [TopologicalSpace G] [MulOneClass G]
[ContinuousMul G] {g h : G} (hg : g ∈ connectedComponent (1 : G))
(hh : h ∈ connectedComponent (1 : G)) : g * h ∈ connectedComponent (1 : G) := by
rw [connectedComponent_eq hg]
have hmul : g ∈ connectedComponent (g * h) := by
apply Continuous.image_connectedComponent_subset (continuous_mul_left g)
rw [← connectedComponent_eq hh]
exact ⟨(1 : G), mem_connectedComponent, by simp only [mul_one]⟩
simpa [← connectedComponent_eq hmul] using mem_connectedComponent
#align mul_mem_connected_component_one mul_mem_connectedComponent_one
#align add_mem_connected_component_zero add_mem_connectedComponent_zero
@[to_additive]
theorem inv_mem_connectedComponent_one {G : Type*} [TopologicalSpace G] [Group G]
[TopologicalGroup G] {g : G} (hg : g ∈ connectedComponent (1 : G)) :
g⁻¹ ∈ connectedComponent (1 : G) := by
rw [← inv_one]
exact
Continuous.image_connectedComponent_subset continuous_inv _
((Set.mem_image _ _ _).mp ⟨g, hg, rfl⟩)
#align inv_mem_connected_component_one inv_mem_connectedComponent_one
#align neg_mem_connected_component_zero neg_mem_connectedComponent_zero
/-- The connected component of 1 is a subgroup of `G`. -/
@[to_additive "The connected component of 0 is a subgroup of `G`."]
def Subgroup.connectedComponentOfOne (G : Type*) [TopologicalSpace G] [Group G]
[TopologicalGroup G] : Subgroup G where
carrier := connectedComponent (1 : G)
one_mem' := mem_connectedComponent
mul_mem' hg hh := mul_mem_connectedComponent_one hg hh
inv_mem' hg := inv_mem_connectedComponent_one hg
#align subgroup.connected_component_of_one Subgroup.connectedComponentOfOne
#align add_subgroup.connected_component_of_zero AddSubgroup.connectedComponentOfZero
/-- If a subgroup of a topological group is commutative, then so is its topological closure. -/
@[to_additive
"If a subgroup of an additive topological group is commutative, then so is its
topological closure."]
def Subgroup.commGroupTopologicalClosure [T2Space G] (s : Subgroup G)
(hs : ∀ x y : s, x * y = y * x) : CommGroup s.topologicalClosure :=
{ s.topologicalClosure.toGroup, s.toSubmonoid.commMonoidTopologicalClosure hs with }
#align subgroup.comm_group_topological_closure Subgroup.commGroupTopologicalClosure
#align add_subgroup.add_comm_group_topological_closure AddSubgroup.addCommGroupTopologicalClosure
variable (G) in
@[to_additive]
lemma Subgroup.coe_topologicalClosure_bot :
((⊥ : Subgroup G).topologicalClosure : Set G) = _root_.closure ({1} : Set G) := by simp
@[to_additive exists_nhds_half_neg]
theorem exists_nhds_split_inv {s : Set G} (hs : s ∈ 𝓝 (1 : G)) :
∃ V ∈ 𝓝 (1 : G), ∀ v ∈ V, ∀ w ∈ V, v / w ∈ s := by
have : (fun p : G × G => p.1 * p.2⁻¹) ⁻¹' s ∈ 𝓝 ((1, 1) : G × G) :=
continuousAt_fst.mul continuousAt_snd.inv (by simpa)
simpa only [div_eq_mul_inv, nhds_prod_eq, mem_prod_self_iff, prod_subset_iff, mem_preimage] using
this
#align exists_nhds_split_inv exists_nhds_split_inv
#align exists_nhds_half_neg exists_nhds_half_neg
@[to_additive]
theorem nhds_translation_mul_inv (x : G) : comap (· * x⁻¹) (𝓝 1) = 𝓝 x :=
((Homeomorph.mulRight x⁻¹).comap_nhds_eq 1).trans <| show 𝓝 (1 * x⁻¹⁻¹) = 𝓝 x by simp
#align nhds_translation_mul_inv nhds_translation_mul_inv
#align nhds_translation_add_neg nhds_translation_add_neg
@[to_additive (attr := simp)]
theorem map_mul_left_nhds (x y : G) : map (x * ·) (𝓝 y) = 𝓝 (x * y) :=
(Homeomorph.mulLeft x).map_nhds_eq y
#align map_mul_left_nhds map_mul_left_nhds
#align map_add_left_nhds map_add_left_nhds
@[to_additive]
theorem map_mul_left_nhds_one (x : G) : map (x * ·) (𝓝 1) = 𝓝 x := by simp
#align map_mul_left_nhds_one map_mul_left_nhds_one
#align map_add_left_nhds_zero map_add_left_nhds_zero
@[to_additive (attr := simp)]
theorem map_mul_right_nhds (x y : G) : map (· * x) (𝓝 y) = 𝓝 (y * x) :=
(Homeomorph.mulRight x).map_nhds_eq y
#align map_mul_right_nhds map_mul_right_nhds
#align map_add_right_nhds map_add_right_nhds
@[to_additive]
theorem map_mul_right_nhds_one (x : G) : map (· * x) (𝓝 1) = 𝓝 x := by simp
#align map_mul_right_nhds_one map_mul_right_nhds_one
#align map_add_right_nhds_zero map_add_right_nhds_zero
@[to_additive]
theorem Filter.HasBasis.nhds_of_one {ι : Sort*} {p : ι → Prop} {s : ι → Set G}
(hb : HasBasis (𝓝 1 : Filter G) p s) (x : G) :
HasBasis (𝓝 x) p fun i => { y | y / x ∈ s i } := by
rw [← nhds_translation_mul_inv]
simp_rw [div_eq_mul_inv]
exact hb.comap _
#align filter.has_basis.nhds_of_one Filter.HasBasis.nhds_of_one
#align filter.has_basis.nhds_of_zero Filter.HasBasis.nhds_of_zero
@[to_additive]
theorem mem_closure_iff_nhds_one {x : G} {s : Set G} :
x ∈ closure s ↔ ∀ U ∈ (𝓝 1 : Filter G), ∃ y ∈ s, y / x ∈ U := by
rw [mem_closure_iff_nhds_basis ((𝓝 1 : Filter G).basis_sets.nhds_of_one x)]
simp_rw [Set.mem_setOf, id]
#align mem_closure_iff_nhds_one mem_closure_iff_nhds_one
#align mem_closure_iff_nhds_zero mem_closure_iff_nhds_zero
/-- A monoid homomorphism (a bundled morphism of a type that implements `MonoidHomClass`) from a
topological group to a topological monoid is continuous provided that it is continuous at one. See
also `uniformContinuous_of_continuousAt_one`. -/
@[to_additive
"An additive monoid homomorphism (a bundled morphism of a type that implements
`AddMonoidHomClass`) from an additive topological group to an additive topological monoid is
continuous provided that it is continuous at zero. See also
`uniformContinuous_of_continuousAt_zero`."]
theorem continuous_of_continuousAt_one {M hom : Type*} [MulOneClass M] [TopologicalSpace M]
[ContinuousMul M] [FunLike hom G M] [MonoidHomClass hom G M] (f : hom)
(hf : ContinuousAt f 1) :
Continuous f :=
continuous_iff_continuousAt.2 fun x => by
simpa only [ContinuousAt, ← map_mul_left_nhds_one x, tendsto_map'_iff, (· ∘ ·), map_mul,
map_one, mul_one] using hf.tendsto.const_mul (f x)
#align continuous_of_continuous_at_one continuous_of_continuousAt_one
#align continuous_of_continuous_at_zero continuous_of_continuousAt_zero
-- Porting note (#10756): new theorem
@[to_additive continuous_of_continuousAt_zero₂]
theorem continuous_of_continuousAt_one₂ {H M : Type*} [CommMonoid M] [TopologicalSpace M]
[ContinuousMul M] [Group H] [TopologicalSpace H] [TopologicalGroup H] (f : G →* H →* M)
(hf : ContinuousAt (fun x : G × H ↦ f x.1 x.2) (1, 1))
(hl : ∀ x, ContinuousAt (f x) 1) (hr : ∀ y, ContinuousAt (f · y) 1) :
Continuous (fun x : G × H ↦ f x.1 x.2) := continuous_iff_continuousAt.2 fun (x, y) => by
simp only [ContinuousAt, nhds_prod_eq, ← map_mul_left_nhds_one x, ← map_mul_left_nhds_one y,
prod_map_map_eq, tendsto_map'_iff, (· ∘ ·), map_mul, MonoidHom.mul_apply] at *
refine ((tendsto_const_nhds.mul ((hr y).comp tendsto_fst)).mul
(((hl x).comp tendsto_snd).mul hf)).mono_right (le_of_eq ?_)
simp only [map_one, mul_one, MonoidHom.one_apply]
@[to_additive]
theorem TopologicalGroup.ext {G : Type*} [Group G] {t t' : TopologicalSpace G}
(tg : @TopologicalGroup G t _) (tg' : @TopologicalGroup G t' _)
(h : @nhds G t 1 = @nhds G t' 1) : t = t' :=
TopologicalSpace.ext_nhds fun x ↦ by
rw [← @nhds_translation_mul_inv G t _ _ x, ← @nhds_translation_mul_inv G t' _ _ x, ← h]
#align topological_group.ext TopologicalGroup.ext
#align topological_add_group.ext TopologicalAddGroup.ext
@[to_additive]
theorem TopologicalGroup.ext_iff {G : Type*} [Group G] {t t' : TopologicalSpace G}
(tg : @TopologicalGroup G t _) (tg' : @TopologicalGroup G t' _) :
t = t' ↔ @nhds G t 1 = @nhds G t' 1 :=
⟨fun h => h ▸ rfl, tg.ext tg'⟩
#align topological_group.ext_iff TopologicalGroup.ext_iff
#align topological_add_group.ext_iff TopologicalAddGroup.ext_iff
@[to_additive]
theorem ContinuousInv.of_nhds_one {G : Type*} [Group G] [TopologicalSpace G]
(hinv : Tendsto (fun x : G => x⁻¹) (𝓝 1) (𝓝 1))
(hleft : ∀ x₀ : G, 𝓝 x₀ = map (fun x : G => x₀ * x) (𝓝 1))
(hconj : ∀ x₀ : G, Tendsto (fun x : G => x₀ * x * x₀⁻¹) (𝓝 1) (𝓝 1)) : ContinuousInv G := by
refine ⟨continuous_iff_continuousAt.2 fun x₀ => ?_⟩
have : Tendsto (fun x => x₀⁻¹ * (x₀ * x⁻¹ * x₀⁻¹)) (𝓝 1) (map (x₀⁻¹ * ·) (𝓝 1)) :=
(tendsto_map.comp <| hconj x₀).comp hinv
simpa only [ContinuousAt, hleft x₀, hleft x₀⁻¹, tendsto_map'_iff, (· ∘ ·), mul_assoc, mul_inv_rev,
inv_mul_cancel_left] using this
#align has_continuous_inv.of_nhds_one ContinuousInv.of_nhds_one
#align has_continuous_neg.of_nhds_zero ContinuousNeg.of_nhds_zero
@[to_additive]
theorem TopologicalGroup.of_nhds_one' {G : Type u} [Group G] [TopologicalSpace G]
(hmul : Tendsto (uncurry ((· * ·) : G → G → G)) (𝓝 1 ×ˢ 𝓝 1) (𝓝 1))
(hinv : Tendsto (fun x : G => x⁻¹) (𝓝 1) (𝓝 1))
(hleft : ∀ x₀ : G, 𝓝 x₀ = map (fun x => x₀ * x) (𝓝 1))
(hright : ∀ x₀ : G, 𝓝 x₀ = map (fun x => x * x₀) (𝓝 1)) : TopologicalGroup G :=
{ toContinuousMul := ContinuousMul.of_nhds_one hmul hleft hright
toContinuousInv :=
ContinuousInv.of_nhds_one hinv hleft fun x₀ =>
le_of_eq
(by
rw [show (fun x => x₀ * x * x₀⁻¹) = (fun x => x * x₀⁻¹) ∘ fun x => x₀ * x from rfl, ←
map_map, ← hleft, hright, map_map]
simp [(· ∘ ·)]) }
#align topological_group.of_nhds_one' TopologicalGroup.of_nhds_one'
#align topological_add_group.of_nhds_zero' TopologicalAddGroup.of_nhds_zero'
@[to_additive]
theorem TopologicalGroup.of_nhds_one {G : Type u} [Group G] [TopologicalSpace G]
(hmul : Tendsto (uncurry ((· * ·) : G → G → G)) (𝓝 1 ×ˢ 𝓝 1) (𝓝 1))
(hinv : Tendsto (fun x : G => x⁻¹) (𝓝 1) (𝓝 1))
(hleft : ∀ x₀ : G, 𝓝 x₀ = map (x₀ * ·) (𝓝 1))
(hconj : ∀ x₀ : G, Tendsto (x₀ * · * x₀⁻¹) (𝓝 1) (𝓝 1)) : TopologicalGroup G := by
refine TopologicalGroup.of_nhds_one' hmul hinv hleft fun x₀ => ?_
replace hconj : ∀ x₀ : G, map (x₀ * · * x₀⁻¹) (𝓝 1) = 𝓝 1 :=
fun x₀ => map_eq_of_inverse (x₀⁻¹ * · * x₀⁻¹⁻¹) (by ext; simp [mul_assoc]) (hconj _) (hconj _)
rw [← hconj x₀]
simpa [(· ∘ ·)] using hleft _
#align topological_group.of_nhds_one TopologicalGroup.of_nhds_one
#align topological_add_group.of_nhds_zero TopologicalAddGroup.of_nhds_zero
@[to_additive]
theorem TopologicalGroup.of_comm_of_nhds_one {G : Type u} [CommGroup G] [TopologicalSpace G]
(hmul : Tendsto (uncurry ((· * ·) : G → G → G)) (𝓝 1 ×ˢ 𝓝 1) (𝓝 1))
(hinv : Tendsto (fun x : G => x⁻¹) (𝓝 1) (𝓝 1))
(hleft : ∀ x₀ : G, 𝓝 x₀ = map (x₀ * ·) (𝓝 1)) : TopologicalGroup G :=
TopologicalGroup.of_nhds_one hmul hinv hleft (by simpa using tendsto_id)
#align topological_group.of_comm_of_nhds_one TopologicalGroup.of_comm_of_nhds_one
#align topological_add_group.of_comm_of_nhds_zero TopologicalAddGroup.of_comm_of_nhds_zero
end TopologicalGroup
section QuotientTopologicalGroup
variable [TopologicalSpace G] [Group G] [TopologicalGroup G] (N : Subgroup G) (n : N.Normal)
@[to_additive]
instance QuotientGroup.Quotient.topologicalSpace {G : Type*} [Group G] [TopologicalSpace G]
(N : Subgroup G) : TopologicalSpace (G ⧸ N) :=
instTopologicalSpaceQuotient
#align quotient_group.quotient.topological_space QuotientGroup.Quotient.topologicalSpace
#align quotient_add_group.quotient.topological_space QuotientAddGroup.Quotient.topologicalSpace
open QuotientGroup
@[to_additive]
theorem QuotientGroup.isOpenMap_coe : IsOpenMap ((↑) : G → G ⧸ N) := by
intro s s_op
change IsOpen (((↑) : G → G ⧸ N) ⁻¹' ((↑) '' s))
rw [QuotientGroup.preimage_image_mk N s]
exact isOpen_iUnion fun n => (continuous_mul_right _).isOpen_preimage s s_op
#align quotient_group.is_open_map_coe QuotientGroup.isOpenMap_coe
#align quotient_add_group.is_open_map_coe QuotientAddGroup.isOpenMap_coe
@[to_additive]
instance topologicalGroup_quotient [N.Normal] : TopologicalGroup (G ⧸ N) where
continuous_mul := by
have cont : Continuous (((↑) : G → G ⧸ N) ∘ fun p : G × G ↦ p.fst * p.snd) :=
continuous_quot_mk.comp continuous_mul
have quot : QuotientMap fun p : G × G ↦ ((p.1 : G ⧸ N), (p.2 : G ⧸ N)) := by
apply IsOpenMap.to_quotientMap
· exact (QuotientGroup.isOpenMap_coe N).prod (QuotientGroup.isOpenMap_coe N)
· exact continuous_quot_mk.prod_map continuous_quot_mk
· exact (surjective_quot_mk _).prodMap (surjective_quot_mk _)
exact quot.continuous_iff.2 cont
continuous_inv := by
have quot := IsOpenMap.to_quotientMap
(QuotientGroup.isOpenMap_coe N) continuous_quot_mk (surjective_quot_mk _)
rw [quot.continuous_iff]
exact continuous_quot_mk.comp continuous_inv
#align topological_group_quotient topologicalGroup_quotient
#align topological_add_group_quotient topologicalAddGroup_quotient
/-- Neighborhoods in the quotient are precisely the map of neighborhoods in the prequotient. -/
@[to_additive
"Neighborhoods in the quotient are precisely the map of neighborhoods in the prequotient."]
theorem QuotientGroup.nhds_eq (x : G) : 𝓝 (x : G ⧸ N) = Filter.map (↑) (𝓝 x) :=
le_antisymm ((QuotientGroup.isOpenMap_coe N).nhds_le x) continuous_quot_mk.continuousAt
#align quotient_group.nhds_eq QuotientGroup.nhds_eq
#align quotient_add_group.nhds_eq QuotientAddGroup.nhds_eq
variable (G)
variable [FirstCountableTopology G]
/-- Any first countable topological group has an antitone neighborhood basis `u : ℕ → Set G` for
which `(u (n + 1)) ^ 2 ⊆ u n`. The existence of such a neighborhood basis is a key tool for
`QuotientGroup.completeSpace` -/
@[to_additive
"Any first countable topological additive group has an antitone neighborhood basis
`u : ℕ → set G` for which `u (n + 1) + u (n + 1) ⊆ u n`.
The existence of such a neighborhood basis is a key tool for `QuotientAddGroup.completeSpace`"]
theorem TopologicalGroup.exists_antitone_basis_nhds_one :
∃ u : ℕ → Set G, (𝓝 1).HasAntitoneBasis u ∧ ∀ n, u (n + 1) * u (n + 1) ⊆ u n := by
rcases (𝓝 (1 : G)).exists_antitone_basis with ⟨u, hu, u_anti⟩
have :=
((hu.prod_nhds hu).tendsto_iff hu).mp
(by simpa only [mul_one] using continuous_mul.tendsto ((1, 1) : G × G))
simp only [and_self_iff, mem_prod, and_imp, Prod.forall, exists_true_left, Prod.exists,
forall_true_left] at this
have event_mul : ∀ n : ℕ, ∀ᶠ m in atTop, u m * u m ⊆ u n := by
intro n
rcases this n with ⟨j, k, -, h⟩
refine atTop_basis.eventually_iff.mpr ⟨max j k, True.intro, fun m hm => ?_⟩
rintro - ⟨a, ha, b, hb, rfl⟩
exact h a b (u_anti ((le_max_left _ _).trans hm) ha) (u_anti ((le_max_right _ _).trans hm) hb)
obtain ⟨φ, -, hφ, φ_anti_basis⟩ := HasAntitoneBasis.subbasis_with_rel ⟨hu, u_anti⟩ event_mul
exact ⟨u ∘ φ, φ_anti_basis, fun n => hφ n.lt_succ_self⟩
#align topological_group.exists_antitone_basis_nhds_one TopologicalGroup.exists_antitone_basis_nhds_one
#align topological_add_group.exists_antitone_basis_nhds_zero TopologicalAddGroup.exists_antitone_basis_nhds_zero
/-- In a first countable topological group `G` with normal subgroup `N`, `1 : G ⧸ N` has a
countable neighborhood basis. -/
@[to_additive
"In a first countable topological additive group `G` with normal additive subgroup
`N`, `0 : G ⧸ N` has a countable neighborhood basis."]
instance QuotientGroup.nhds_one_isCountablyGenerated : (𝓝 (1 : G ⧸ N)).IsCountablyGenerated :=
(QuotientGroup.nhds_eq N 1).symm ▸ map.isCountablyGenerated _ _
#align quotient_group.nhds_one_is_countably_generated QuotientGroup.nhds_one_isCountablyGenerated
#align quotient_add_group.nhds_zero_is_countably_generated QuotientAddGroup.nhds_zero_isCountablyGenerated
end QuotientTopologicalGroup
/-- A typeclass saying that `p : G × G ↦ p.1 - p.2` is a continuous function. This property
automatically holds for topological additive groups but it also holds, e.g., for `ℝ≥0`. -/
class ContinuousSub (G : Type*) [TopologicalSpace G] [Sub G] : Prop where
continuous_sub : Continuous fun p : G × G => p.1 - p.2
#align has_continuous_sub ContinuousSub
/-- A typeclass saying that `p : G × G ↦ p.1 / p.2` is a continuous function. This property
automatically holds for topological groups. Lemmas using this class have primes.
The unprimed version is for `GroupWithZero`. -/
@[to_additive existing]
class ContinuousDiv (G : Type*) [TopologicalSpace G] [Div G] : Prop where
continuous_div' : Continuous fun p : G × G => p.1 / p.2
#align has_continuous_div ContinuousDiv
-- see Note [lower instance priority]
@[to_additive]
instance (priority := 100) TopologicalGroup.to_continuousDiv [TopologicalSpace G] [Group G]
[TopologicalGroup G] : ContinuousDiv G :=
⟨by
simp only [div_eq_mul_inv]
exact continuous_fst.mul continuous_snd.inv⟩
#align topological_group.to_has_continuous_div TopologicalGroup.to_continuousDiv
#align topological_add_group.to_has_continuous_sub TopologicalAddGroup.to_continuousSub
export ContinuousSub (continuous_sub)
export ContinuousDiv (continuous_div')
section ContinuousDiv
variable [TopologicalSpace G] [Div G] [ContinuousDiv G]
@[to_additive sub]
theorem Filter.Tendsto.div' {f g : α → G} {l : Filter α} {a b : G} (hf : Tendsto f l (𝓝 a))
(hg : Tendsto g l (𝓝 b)) : Tendsto (fun x => f x / g x) l (𝓝 (a / b)) :=
(continuous_div'.tendsto (a, b)).comp (hf.prod_mk_nhds hg)
#align filter.tendsto.div' Filter.Tendsto.div'
#align filter.tendsto.sub Filter.Tendsto.sub
@[to_additive const_sub]
theorem Filter.Tendsto.const_div' (b : G) {c : G} {f : α → G} {l : Filter α}
(h : Tendsto f l (𝓝 c)) : Tendsto (fun k : α => b / f k) l (𝓝 (b / c)) :=
tendsto_const_nhds.div' h
#align filter.tendsto.const_div' Filter.Tendsto.const_div'
#align filter.tendsto.const_sub Filter.Tendsto.const_sub
@[to_additive]
lemma Filter.tendsto_const_div_iff {G : Type*} [CommGroup G] [TopologicalSpace G] [ContinuousDiv G]
(b : G) {c : G} {f : α → G} {l : Filter α} :
Tendsto (fun k : α ↦ b / f k) l (𝓝 (b / c)) ↔ Tendsto f l (𝓝 c) := by
refine ⟨fun h ↦ ?_, Filter.Tendsto.const_div' b⟩
convert h.const_div' b with k <;> rw [div_div_cancel]
@[to_additive sub_const]
theorem Filter.Tendsto.div_const' {c : G} {f : α → G} {l : Filter α} (h : Tendsto f l (𝓝 c))
(b : G) : Tendsto (f · / b) l (𝓝 (c / b)) :=
h.div' tendsto_const_nhds
#align filter.tendsto.div_const' Filter.Tendsto.div_const'
#align filter.tendsto.sub_const Filter.Tendsto.sub_const
lemma Filter.tendsto_div_const_iff {G : Type*}
[CommGroupWithZero G] [TopologicalSpace G] [ContinuousDiv G]
{b : G} (hb : b ≠ 0) {c : G} {f : α → G} {l : Filter α} :
Tendsto (f · / b) l (𝓝 (c / b)) ↔ Tendsto f l (𝓝 c) := by
refine ⟨fun h ↦ ?_, fun h ↦ Filter.Tendsto.div_const' h b⟩
convert h.div_const' b⁻¹ with k <;> rw [div_div, mul_inv_cancel hb, div_one]
lemma Filter.tendsto_sub_const_iff {G : Type*}
[AddCommGroup G] [TopologicalSpace G] [ContinuousSub G]
(b : G) {c : G} {f : α → G} {l : Filter α} :
Tendsto (f · - b) l (𝓝 (c - b)) ↔ Tendsto f l (𝓝 c) := by
refine ⟨fun h ↦ ?_, fun h ↦ Filter.Tendsto.sub_const h b⟩
convert h.sub_const (-b) with k <;> rw [sub_sub, ← sub_eq_add_neg, sub_self, sub_zero]
variable [TopologicalSpace α] {f g : α → G} {s : Set α} {x : α}
@[to_additive (attr := continuity, fun_prop) sub]
theorem Continuous.div' (hf : Continuous f) (hg : Continuous g) : Continuous fun x => f x / g x :=
continuous_div'.comp (hf.prod_mk hg : _)
#align continuous.div' Continuous.div'
#align continuous.sub Continuous.sub
@[to_additive (attr := continuity) continuous_sub_left]
lemma continuous_div_left' (a : G) : Continuous (a / ·) := continuous_const.div' continuous_id
#align continuous_div_left' continuous_div_left'
#align continuous_sub_left continuous_sub_left
@[to_additive (attr := continuity) continuous_sub_right]
lemma continuous_div_right' (a : G) : Continuous (· / a) := continuous_id.div' continuous_const
#align continuous_div_right' continuous_div_right'
#align continuous_sub_right continuous_sub_right
@[to_additive (attr := fun_prop) sub]
theorem ContinuousAt.div' {f g : α → G} {x : α} (hf : ContinuousAt f x) (hg : ContinuousAt g x) :
ContinuousAt (fun x => f x / g x) x :=
Filter.Tendsto.div' hf hg
#align continuous_at.div' ContinuousAt.div'
#align continuous_at.sub ContinuousAt.sub
@[to_additive sub]
theorem ContinuousWithinAt.div' (hf : ContinuousWithinAt f s x) (hg : ContinuousWithinAt g s x) :
ContinuousWithinAt (fun x => f x / g x) s x :=
Filter.Tendsto.div' hf hg
#align continuous_within_at.div' ContinuousWithinAt.div'
#align continuous_within_at.sub ContinuousWithinAt.sub
@[to_additive (attr := fun_prop) sub]
theorem ContinuousOn.div' (hf : ContinuousOn f s) (hg : ContinuousOn g s) :
ContinuousOn (fun x => f x / g x) s := fun x hx => (hf x hx).div' (hg x hx)
#align continuous_on.div' ContinuousOn.div'
#align continuous_on.sub ContinuousOn.sub
end ContinuousDiv
section DivInvTopologicalGroup
variable [Group G] [TopologicalSpace G] [TopologicalGroup G]
/-- A version of `Homeomorph.mulLeft a b⁻¹` that is defeq to `a / b`. -/
@[to_additive (attr := simps! (config := { simpRhs := true }))
" A version of `Homeomorph.addLeft a (-b)` that is defeq to `a - b`. "]
def Homeomorph.divLeft (x : G) : G ≃ₜ G :=
{ Equiv.divLeft x with
continuous_toFun := continuous_const.div' continuous_id
continuous_invFun := continuous_inv.mul continuous_const }
#align homeomorph.div_left Homeomorph.divLeft
#align homeomorph.sub_left Homeomorph.subLeft
@[to_additive]
theorem isOpenMap_div_left (a : G) : IsOpenMap (a / ·) :=
(Homeomorph.divLeft _).isOpenMap
#align is_open_map_div_left isOpenMap_div_left
#align is_open_map_sub_left isOpenMap_sub_left
@[to_additive]
theorem isClosedMap_div_left (a : G) : IsClosedMap (a / ·) :=
(Homeomorph.divLeft _).isClosedMap
#align is_closed_map_div_left isClosedMap_div_left
#align is_closed_map_sub_left isClosedMap_sub_left
/-- A version of `Homeomorph.mulRight a⁻¹ b` that is defeq to `b / a`. -/
@[to_additive (attr := simps! (config := { simpRhs := true }))
"A version of `Homeomorph.addRight (-a) b` that is defeq to `b - a`. "]
def Homeomorph.divRight (x : G) : G ≃ₜ G :=
{ Equiv.divRight x with
continuous_toFun := continuous_id.div' continuous_const
continuous_invFun := continuous_id.mul continuous_const }
#align homeomorph.div_right Homeomorph.divRight
#align homeomorph.sub_right Homeomorph.subRight
@[to_additive]
lemma isOpenMap_div_right (a : G) : IsOpenMap (· / a) := (Homeomorph.divRight a).isOpenMap
#align is_open_map_div_right isOpenMap_div_right
#align is_open_map_sub_right isOpenMap_sub_right
@[to_additive]
lemma isClosedMap_div_right (a : G) : IsClosedMap (· / a) := (Homeomorph.divRight a).isClosedMap
#align is_closed_map_div_right isClosedMap_div_right
#align is_closed_map_sub_right isClosedMap_sub_right
@[to_additive]
theorem tendsto_div_nhds_one_iff {α : Type*} {l : Filter α} {x : G} {u : α → G} :
Tendsto (u · / x) l (𝓝 1) ↔ Tendsto u l (𝓝 x) :=
haveI A : Tendsto (fun _ : α => x) l (𝓝 x) := tendsto_const_nhds
⟨fun h => by simpa using h.mul A, fun h => by simpa using h.div' A⟩
#align tendsto_div_nhds_one_iff tendsto_div_nhds_one_iff
#align tendsto_sub_nhds_zero_iff tendsto_sub_nhds_zero_iff
@[to_additive]
theorem nhds_translation_div (x : G) : comap (· / x) (𝓝 1) = 𝓝 x := by
simpa only [div_eq_mul_inv] using nhds_translation_mul_inv x
#align nhds_translation_div nhds_translation_div
#align nhds_translation_sub nhds_translation_sub
end DivInvTopologicalGroup
/-!
### Topological operations on pointwise sums and products
A few results about interior and closure of the pointwise addition/multiplication of sets in groups
with continuous addition/multiplication. See also `Submonoid.top_closure_mul_self_eq` in
`Topology.Algebra.Monoid`.
-/
section ContinuousConstSMul
variable [TopologicalSpace β] [Group α] [MulAction α β] [ContinuousConstSMul α β] {s : Set α}
{t : Set β}
@[to_additive]
theorem IsOpen.smul_left (ht : IsOpen t) : IsOpen (s • t) := by
rw [← iUnion_smul_set]
exact isOpen_biUnion fun a _ => ht.smul _
#align is_open.smul_left IsOpen.smul_left
#align is_open.vadd_left IsOpen.vadd_left
@[to_additive]
theorem subset_interior_smul_right : s • interior t ⊆ interior (s • t) :=
interior_maximal (Set.smul_subset_smul_left interior_subset) isOpen_interior.smul_left
#align subset_interior_smul_right subset_interior_smul_right
#align subset_interior_vadd_right subset_interior_vadd_right
@[to_additive]
theorem smul_mem_nhds (a : α) {x : β} (ht : t ∈ 𝓝 x) : a • t ∈ 𝓝 (a • x) := by
rcases mem_nhds_iff.1 ht with ⟨u, ut, u_open, hu⟩
exact mem_nhds_iff.2 ⟨a • u, smul_set_mono ut, u_open.smul a, smul_mem_smul_set hu⟩
#align smul_mem_nhds smul_mem_nhds
#align vadd_mem_nhds vadd_mem_nhds
variable [TopologicalSpace α]
@[to_additive]
theorem subset_interior_smul : interior s • interior t ⊆ interior (s • t) :=
(Set.smul_subset_smul_right interior_subset).trans subset_interior_smul_right
#align subset_interior_smul subset_interior_smul
#align subset_interior_vadd subset_interior_vadd
end ContinuousConstSMul
section ContinuousSMul
variable [TopologicalSpace α] [TopologicalSpace β] [Group α] [MulAction α β] [ContinuousInv α]
[ContinuousSMul α β] {s : Set α} {t : Set β}
@[to_additive]
theorem IsClosed.smul_left_of_isCompact (ht : IsClosed t) (hs : IsCompact s) :
IsClosed (s • t) := by
have : ∀ x ∈ s • t, ∃ g ∈ s, g⁻¹ • x ∈ t := by
rintro x ⟨g, hgs, y, hyt, rfl⟩
refine ⟨g, hgs, ?_⟩
rwa [inv_smul_smul]
choose! f hf using this
refine isClosed_of_closure_subset (fun x hx ↦ ?_)
rcases mem_closure_iff_ultrafilter.mp hx with ⟨u, hust, hux⟩
have : Ultrafilter.map f u ≤ 𝓟 s :=
calc Ultrafilter.map f u ≤ map f (𝓟 (s • t)) := map_mono (le_principal_iff.mpr hust)
_ = 𝓟 (f '' (s • t)) := map_principal
_ ≤ 𝓟 s := principal_mono.mpr (image_subset_iff.mpr (fun x hx ↦ (hf x hx).1))
rcases hs.ultrafilter_le_nhds (Ultrafilter.map f u) this with ⟨g, hg, hug⟩
suffices g⁻¹ • x ∈ t from
⟨g, hg, g⁻¹ • x, this, smul_inv_smul _ _⟩
exact ht.mem_of_tendsto ((Tendsto.inv hug).smul hux)
(Eventually.mono hust (fun y hy ↦ (hf y hy).2))
/-! One may expect a version of `IsClosed.smul_left_of_isCompact` where `t` is compact and `s` is
closed, but such a lemma can't be true in this level of generality. For a counterexample, consider
`ℚ` acting on `ℝ` by translation, and let `s : Set ℚ := univ`, `t : set ℝ := {0}`. Then `s` is
closed and `t` is compact, but `s +ᵥ t` is the set of all rationals, which is definitely not
closed in `ℝ`.
To fix the proof, we would need to make two additional assumptions:
- for any `x ∈ t`, `s • {x}` is closed
- for any `x ∈ t`, there is a continuous function `g : s • {x} → s` such that, for all
`y ∈ s • {x}`, we have `y = (g y) • x`
These are fairly specific hypotheses so we don't state this version of the lemmas, but an
interesting fact is that these two assumptions are verified in the case of a `NormedAddTorsor`
(or really, any `AddTorsor` with continuous `-ᵥ`). We prove this special case in
`IsClosed.vadd_right_of_isCompact`. -/
@[to_additive]
theorem MulAction.isClosedMap_quotient [CompactSpace α] :
letI := orbitRel α β
IsClosedMap (Quotient.mk' : β → Quotient (orbitRel α β)) := by
intro t ht
rw [← quotientMap_quotient_mk'.isClosed_preimage, MulAction.quotient_preimage_image_eq_union_mul]
convert ht.smul_left_of_isCompact (isCompact_univ (X := α))
rw [← biUnion_univ, ← iUnion_smul_left_image]
rfl
end ContinuousSMul
section ContinuousConstSMul
variable [TopologicalSpace α] [Group α] [ContinuousConstSMul α α] {s t : Set α}
@[to_additive]
theorem IsOpen.mul_left : IsOpen t → IsOpen (s * t) :=
IsOpen.smul_left
#align is_open.mul_left IsOpen.mul_left
#align is_open.add_left IsOpen.add_left
@[to_additive]
theorem subset_interior_mul_right : s * interior t ⊆ interior (s * t) :=
subset_interior_smul_right
#align subset_interior_mul_right subset_interior_mul_right
#align subset_interior_add_right subset_interior_add_right
@[to_additive]
theorem subset_interior_mul : interior s * interior t ⊆ interior (s * t) :=
subset_interior_smul
#align subset_interior_mul subset_interior_mul
#align subset_interior_add subset_interior_add
@[to_additive]
theorem singleton_mul_mem_nhds (a : α) {b : α} (h : s ∈ 𝓝 b) : {a} * s ∈ 𝓝 (a * b) := by
have := smul_mem_nhds a h
rwa [← singleton_smul] at this
#align singleton_mul_mem_nhds singleton_mul_mem_nhds
#align singleton_add_mem_nhds singleton_add_mem_nhds
@[to_additive]
theorem singleton_mul_mem_nhds_of_nhds_one (a : α) (h : s ∈ 𝓝 (1 : α)) : {a} * s ∈ 𝓝 a := by
simpa only [mul_one] using singleton_mul_mem_nhds a h
#align singleton_mul_mem_nhds_of_nhds_one singleton_mul_mem_nhds_of_nhds_one
#align singleton_add_mem_nhds_of_nhds_zero singleton_add_mem_nhds_of_nhds_zero
end ContinuousConstSMul
section ContinuousConstSMulOp
variable [TopologicalSpace α] [Group α] [ContinuousConstSMul αᵐᵒᵖ α] {s t : Set α}
@[to_additive]
theorem IsOpen.mul_right (hs : IsOpen s) : IsOpen (s * t) := by
rw [← iUnion_op_smul_set]
exact isOpen_biUnion fun a _ => hs.smul _
#align is_open.mul_right IsOpen.mul_right
#align is_open.add_right IsOpen.add_right
@[to_additive]
theorem subset_interior_mul_left : interior s * t ⊆ interior (s * t) :=
interior_maximal (Set.mul_subset_mul_right interior_subset) isOpen_interior.mul_right
#align subset_interior_mul_left subset_interior_mul_left
#align subset_interior_add_left subset_interior_add_left
@[to_additive]
theorem subset_interior_mul' : interior s * interior t ⊆ interior (s * t) :=
(Set.mul_subset_mul_left interior_subset).trans subset_interior_mul_left
#align subset_interior_mul' subset_interior_mul'
#align subset_interior_add' subset_interior_add'
@[to_additive]
theorem mul_singleton_mem_nhds (a : α) {b : α} (h : s ∈ 𝓝 b) : s * {a} ∈ 𝓝 (b * a) := by
simp only [← iUnion_op_smul_set, mem_singleton_iff, iUnion_iUnion_eq_left]
exact smul_mem_nhds _ h
#align mul_singleton_mem_nhds mul_singleton_mem_nhds
#align add_singleton_mem_nhds add_singleton_mem_nhds
@[to_additive]
theorem mul_singleton_mem_nhds_of_nhds_one (a : α) (h : s ∈ 𝓝 (1 : α)) : s * {a} ∈ 𝓝 a := by
simpa only [one_mul] using mul_singleton_mem_nhds a h
#align mul_singleton_mem_nhds_of_nhds_one mul_singleton_mem_nhds_of_nhds_one
#align add_singleton_mem_nhds_of_nhds_zero add_singleton_mem_nhds_of_nhds_zero
end ContinuousConstSMulOp
section TopologicalGroup
variable [TopologicalSpace G] [Group G] [TopologicalGroup G] {s t : Set G}
@[to_additive]
theorem IsOpen.div_left (ht : IsOpen t) : IsOpen (s / t) := by
rw [← iUnion_div_left_image]
exact isOpen_biUnion fun a _ => isOpenMap_div_left a t ht
#align is_open.div_left IsOpen.div_left
#align is_open.sub_left IsOpen.sub_left
@[to_additive]
theorem IsOpen.div_right (hs : IsOpen s) : IsOpen (s / t) := by
rw [← iUnion_div_right_image]
exact isOpen_biUnion fun a _ => isOpenMap_div_right a s hs
#align is_open.div_right IsOpen.div_right
#align is_open.sub_right IsOpen.sub_right
@[to_additive]
theorem subset_interior_div_left : interior s / t ⊆ interior (s / t) :=
interior_maximal (div_subset_div_right interior_subset) isOpen_interior.div_right
#align subset_interior_div_left subset_interior_div_left
#align subset_interior_sub_left subset_interior_sub_left
@[to_additive]
theorem subset_interior_div_right : s / interior t ⊆ interior (s / t) :=
interior_maximal (div_subset_div_left interior_subset) isOpen_interior.div_left
#align subset_interior_div_right subset_interior_div_right
#align subset_interior_sub_right subset_interior_sub_right
@[to_additive]
theorem subset_interior_div : interior s / interior t ⊆ interior (s / t) :=
(div_subset_div_left interior_subset).trans subset_interior_div_left
#align subset_interior_div subset_interior_div
#align subset_interior_sub subset_interior_sub
@[to_additive]
theorem IsOpen.mul_closure (hs : IsOpen s) (t : Set G) : s * closure t = s * t := by
refine (mul_subset_iff.2 fun a ha b hb => ?_).antisymm (mul_subset_mul_left subset_closure)
rw [mem_closure_iff] at hb
have hbU : b ∈ s⁻¹ * {a * b} := ⟨a⁻¹, Set.inv_mem_inv.2 ha, a * b, rfl, inv_mul_cancel_left _ _⟩
obtain ⟨_, ⟨c, hc, d, rfl : d = _, rfl⟩, hcs⟩ := hb _ hs.inv.mul_right hbU
exact ⟨c⁻¹, hc, _, hcs, inv_mul_cancel_left _ _⟩
#align is_open.mul_closure IsOpen.mul_closure
#align is_open.add_closure IsOpen.add_closure
@[to_additive]
theorem IsOpen.closure_mul (ht : IsOpen t) (s : Set G) : closure s * t = s * t := by
rw [← inv_inv (closure s * t), mul_inv_rev, inv_closure, ht.inv.mul_closure, mul_inv_rev, inv_inv,
inv_inv]
#align is_open.closure_mul IsOpen.closure_mul
#align is_open.closure_add IsOpen.closure_add
@[to_additive]
theorem IsOpen.div_closure (hs : IsOpen s) (t : Set G) : s / closure t = s / t := by
simp_rw [div_eq_mul_inv, inv_closure, hs.mul_closure]
#align is_open.div_closure IsOpen.div_closure
#align is_open.sub_closure IsOpen.sub_closure
@[to_additive]
theorem IsOpen.closure_div (ht : IsOpen t) (s : Set G) : closure s / t = s / t := by
simp_rw [div_eq_mul_inv, ht.inv.closure_mul]
#align is_open.closure_div IsOpen.closure_div
#align is_open.closure_sub IsOpen.closure_sub
@[to_additive]
theorem IsClosed.mul_left_of_isCompact (ht : IsClosed t) (hs : IsCompact s) : IsClosed (s * t) :=
ht.smul_left_of_isCompact hs
@[to_additive]
theorem IsClosed.mul_right_of_isCompact (ht : IsClosed t) (hs : IsCompact s) :
IsClosed (t * s) := by
rw [← image_op_smul]
exact IsClosed.smul_left_of_isCompact ht (hs.image continuous_op)
@[to_additive]
theorem QuotientGroup.isClosedMap_coe {H : Subgroup G} (hH : IsCompact (H : Set G)) :
IsClosedMap ((↑) : G → G ⧸ H) := by
intro t ht
rw [← quotientMap_quotient_mk'.isClosed_preimage]
convert ht.mul_right_of_isCompact hH
refine (QuotientGroup.preimage_image_mk_eq_iUnion_image _ _).trans ?_
rw [iUnion_subtype, ← iUnion_mul_right_image]
rfl
@[to_additive]
lemma subset_mul_closure_one (s : Set G) : s ⊆ s * (closure {1} : Set G) := by
have : s ⊆ s * ({1} : Set G) := by simpa using Subset.rfl
exact this.trans (smul_subset_smul_left subset_closure)
@[to_additive]
lemma IsCompact.mul_closure_one_eq_closure {K : Set G} (hK : IsCompact K) :
K * (closure {1} : Set G) = closure K := by
apply Subset.antisymm ?_ ?_
· calc
K * (closure {1} : Set G) ⊆ closure K * (closure {1} : Set G) :=
smul_subset_smul_right subset_closure
_ ⊆ closure (K * ({1} : Set G)) := smul_set_closure_subset _ _
_ = closure K := by simp
· have : IsClosed (K * (closure {1} : Set G)) :=
IsClosed.smul_left_of_isCompact isClosed_closure hK
rw [IsClosed.closure_subset_iff this]
exact subset_mul_closure_one K
@[to_additive]
lemma IsClosed.mul_closure_one_eq {F : Set G} (hF : IsClosed F) :
F * (closure {1} : Set G) = F := by
refine Subset.antisymm ?_ (subset_mul_closure_one F)
calc
F * (closure {1} : Set G) = closure F * closure ({1} : Set G) := by rw [hF.closure_eq]
_ ⊆ closure (F * ({1} : Set G)) := smul_set_closure_subset _ _
_ = F := by simp [hF.closure_eq]
@[to_additive]
lemma compl_mul_closure_one_eq {t : Set G} (ht : t * (closure {1} : Set G) = t) :
tᶜ * (closure {1} : Set G) = tᶜ := by
refine Subset.antisymm ?_ (subset_mul_closure_one tᶜ)
rintro - ⟨x, hx, g, hg, rfl⟩
by_contra H
have : x ∈ t * (closure {1} : Set G) := by
rw [← Subgroup.coe_topologicalClosure_bot G] at hg ⊢
simp only [smul_eq_mul, mem_compl_iff, not_not] at H
exact ⟨x * g, H, g⁻¹, Subgroup.inv_mem _ hg, by simp⟩
rw [ht] at this
exact hx this
@[to_additive]
lemma compl_mul_closure_one_eq_iff {t : Set G} :
tᶜ * (closure {1} : Set G) = tᶜ ↔ t * (closure {1} : Set G) = t :=
⟨fun h ↦ by simpa using compl_mul_closure_one_eq h, fun h ↦ compl_mul_closure_one_eq h⟩
@[to_additive]
lemma IsOpen.mul_closure_one_eq {U : Set G} (hU : IsOpen U) :
U * (closure {1} : Set G) = U :=
compl_mul_closure_one_eq_iff.1 (hU.isClosed_compl.mul_closure_one_eq)
end TopologicalGroup
section FilterMul
section
variable (G) [TopologicalSpace G] [Group G] [ContinuousMul G]
@[to_additive]
theorem TopologicalGroup.t1Space (h : @IsClosed G _ {1}) : T1Space G :=
⟨fun x => by simpa using isClosedMap_mul_right x _ h⟩
#align topological_group.t1_space TopologicalGroup.t1Space
#align topological_add_group.t1_space TopologicalAddGroup.t1Space
end
section
variable (G) [TopologicalSpace G] [Group G] [TopologicalGroup G]
@[to_additive]
instance (priority := 100) TopologicalGroup.regularSpace : RegularSpace G := by
refine .of_exists_mem_nhds_isClosed_subset fun a s hs ↦ ?_
have : Tendsto (fun p : G × G => p.1 * p.2) (𝓝 (a, 1)) (𝓝 a) :=
continuous_mul.tendsto' _ _ (mul_one a)
rcases mem_nhds_prod_iff.mp (this hs) with ⟨U, hU, V, hV, hUV⟩
rw [← image_subset_iff, image_prod] at hUV
refine ⟨closure U, mem_of_superset hU subset_closure, isClosed_closure, ?_⟩
calc
closure U ⊆ closure U * interior V := subset_mul_left _ (mem_interior_iff_mem_nhds.2 hV)
_ = U * interior V := isOpen_interior.closure_mul U
_ ⊆ U * V := mul_subset_mul_left interior_subset
_ ⊆ s := hUV
#align topological_group.regular_space TopologicalGroup.regularSpace
#align topological_add_group.regular_space TopologicalAddGroup.regularSpace
-- `inferInstance` can find these instances now
#align topological_group.t3_space inferInstance
#align topological_add_group.t3_space inferInstance
#align topological_group.t2_space inferInstance
#align topological_add_group.t2_space inferInstance
variable {G}
@[to_additive]
theorem group_inseparable_iff {x y : G} : Inseparable x y ↔ x / y ∈ closure (1 : Set G) := by
rw [← singleton_one, ← specializes_iff_mem_closure, specializes_comm, specializes_iff_inseparable,
← (Homeomorph.mulRight y⁻¹).embedding.inseparable_iff]
simp [div_eq_mul_inv]
#align group_separation_rel group_inseparable_iff
#align add_group_separation_rel addGroup_inseparable_iff
@[to_additive]
theorem TopologicalGroup.t2Space_iff_one_closed : T2Space G ↔ IsClosed ({1} : Set G) :=
⟨fun _ ↦ isClosed_singleton, fun h ↦
have := TopologicalGroup.t1Space G h; inferInstance⟩
#align topological_group.t2_space_iff_one_closed TopologicalGroup.t2Space_iff_one_closed
#align topological_add_group.t2_space_iff_zero_closed TopologicalAddGroup.t2Space_iff_zero_closed
@[to_additive]
theorem TopologicalGroup.t2Space_of_one_sep (H : ∀ x : G, x ≠ 1 → ∃ U ∈ 𝓝 (1 : G), x ∉ U) :
T2Space G := by
suffices T1Space G from inferInstance
refine t1Space_iff_specializes_imp_eq.2 fun x y hspec ↦ by_contra fun hne ↦ ?_
rcases H (x * y⁻¹) (by rwa [Ne, mul_inv_eq_one]) with ⟨U, hU₁, hU⟩
exact hU <| mem_of_mem_nhds <| hspec.map (continuous_mul_right y⁻¹) (by rwa [mul_inv_self])
#align topological_group.t2_space_of_one_sep TopologicalGroup.t2Space_of_one_sep
#align topological_add_group.t2_space_of_zero_sep TopologicalAddGroup.t2Space_of_zero_sep
/-- Given a neighborhood `U` of the identity, one may find a neighborhood `V` of the identity which
is closed, symmetric, and satisfies `V * V ⊆ U`. -/
@[to_additive "Given a neighborhood `U` of the identity, one may find a neighborhood `V` of the
identity which is closed, symmetric, and satisfies `V + V ⊆ U`."]
theorem exists_closed_nhds_one_inv_eq_mul_subset {U : Set G} (hU : U ∈ 𝓝 1) :
∃ V ∈ 𝓝 1, IsClosed V ∧ V⁻¹ = V ∧ V * V ⊆ U := by
rcases exists_open_nhds_one_mul_subset hU with ⟨V, V_open, V_mem, hV⟩
rcases exists_mem_nhds_isClosed_subset (V_open.mem_nhds V_mem) with ⟨W, W_mem, W_closed, hW⟩
refine ⟨W ∩ W⁻¹, Filter.inter_mem W_mem (inv_mem_nhds_one G W_mem), W_closed.inter W_closed.inv,
by simp [inter_comm], ?_⟩
calc
W ∩ W⁻¹ * (W ∩ W⁻¹)
⊆ W * W := mul_subset_mul inter_subset_left inter_subset_left
_ ⊆ V * V := mul_subset_mul hW hW
_ ⊆ U := hV
variable (S : Subgroup G) [Subgroup.Normal S] [IsClosed (S : Set G)]
@[to_additive]
instance Subgroup.t3_quotient_of_isClosed (S : Subgroup G) [Subgroup.Normal S]
[hS : IsClosed (S : Set G)] : T3Space (G ⧸ S) := by
rw [← QuotientGroup.ker_mk' S] at hS
haveI := TopologicalGroup.t1Space (G ⧸ S) (quotientMap_quotient_mk'.isClosed_preimage.mp hS)
infer_instance
#align subgroup.t3_quotient_of_is_closed Subgroup.t3_quotient_of_isClosed
#align add_subgroup.t3_quotient_of_is_closed AddSubgroup.t3_quotient_of_isClosed
/-- A subgroup `S` of a topological group `G` acts on `G` properly discontinuously on the left, if
it is discrete in the sense that `S ∩ K` is finite for all compact `K`. (See also
`DiscreteTopology`.) -/
@[to_additive
"A subgroup `S` of an additive topological group `G` acts on `G` properly
discontinuously on the left, if it is discrete in the sense that `S ∩ K` is finite for all compact
`K`. (See also `DiscreteTopology`."]
theorem Subgroup.properlyDiscontinuousSMul_of_tendsto_cofinite (S : Subgroup G)
(hS : Tendsto S.subtype cofinite (cocompact G)) : ProperlyDiscontinuousSMul S G :=
{ finite_disjoint_inter_image := by
intro K L hK hL
have H : Set.Finite _ := hS ((hL.prod hK).image continuous_div').compl_mem_cocompact
rw [preimage_compl, compl_compl] at H
convert H
ext x
simp only [image_smul, mem_setOf_eq, coeSubtype, mem_preimage, mem_image, Prod.exists]
exact Set.smul_inter_ne_empty_iff' }
#align subgroup.properly_discontinuous_smul_of_tendsto_cofinite Subgroup.properlyDiscontinuousSMul_of_tendsto_cofinite
#align add_subgroup.properly_discontinuous_vadd_of_tendsto_cofinite AddSubgroup.properlyDiscontinuousVAdd_of_tendsto_cofinite
-- attribute [local semireducible] MulOpposite -- Porting note: doesn't work in Lean 4
/-- A subgroup `S` of a topological group `G` acts on `G` properly discontinuously on the right, if
it is discrete in the sense that `S ∩ K` is finite for all compact `K`. (See also
`DiscreteTopology`.)
If `G` is Hausdorff, this can be combined with `t2Space_of_properlyDiscontinuousSMul_of_t2Space`
to show that the quotient group `G ⧸ S` is Hausdorff. -/
@[to_additive
"A subgroup `S` of an additive topological group `G` acts on `G` properly discontinuously
on the right, if it is discrete in the sense that `S ∩ K` is finite for all compact `K`.
(See also `DiscreteTopology`.)
If `G` is Hausdorff, this can be combined with `t2Space_of_properlyDiscontinuousVAdd_of_t2Space`
to show that the quotient group `G ⧸ S` is Hausdorff."]
theorem Subgroup.properlyDiscontinuousSMul_opposite_of_tendsto_cofinite (S : Subgroup G)
(hS : Tendsto S.subtype cofinite (cocompact G)) : ProperlyDiscontinuousSMul S.op G :=
{ finite_disjoint_inter_image := by
intro K L hK hL
have : Continuous fun p : G × G => (p.1⁻¹, p.2) := continuous_inv.prod_map continuous_id
have H : Set.Finite _ :=
hS ((hK.prod hL).image (continuous_mul.comp this)).compl_mem_cocompact
simp only [preimage_compl, compl_compl, coeSubtype, comp_apply] at H
apply Finite.of_preimage _ (equivOp S).surjective
convert H using 1
ext x
simp only [image_smul, mem_setOf_eq, coeSubtype, mem_preimage, mem_image, Prod.exists]
exact Set.op_smul_inter_ne_empty_iff }
#align subgroup.properly_discontinuous_smul_opposite_of_tendsto_cofinite Subgroup.properlyDiscontinuousSMul_opposite_of_tendsto_cofinite
#align add_subgroup.properly_discontinuous_vadd_opposite_of_tendsto_cofinite AddSubgroup.properlyDiscontinuousVAdd_opposite_of_tendsto_cofinite
end
section
/-! Some results about an open set containing the product of two sets in a topological group. -/
variable [TopologicalSpace G] [MulOneClass G] [ContinuousMul G]
/-- Given a compact set `K` inside an open set `U`, there is an open neighborhood `V` of `1`
such that `K * V ⊆ U`. -/
@[to_additive
"Given a compact set `K` inside an open set `U`, there is an open neighborhood `V` of
`0` such that `K + V ⊆ U`."]
theorem compact_open_separated_mul_right {K U : Set G} (hK : IsCompact K) (hU : IsOpen U)
(hKU : K ⊆ U) : ∃ V ∈ 𝓝 (1 : G), K * V ⊆ U := by
refine hK.induction_on ?_ ?_ ?_ ?_
· exact ⟨univ, by simp⟩
· rintro s t hst ⟨V, hV, hV'⟩
exact ⟨V, hV, (mul_subset_mul_right hst).trans hV'⟩
· rintro s t ⟨V, V_in, hV'⟩ ⟨W, W_in, hW'⟩
use V ∩ W, inter_mem V_in W_in
rw [union_mul]
exact
union_subset ((mul_subset_mul_left V.inter_subset_left).trans hV')
((mul_subset_mul_left V.inter_subset_right).trans hW')
· intro x hx
have := tendsto_mul (show U ∈ 𝓝 (x * 1) by simpa using hU.mem_nhds (hKU hx))
rw [nhds_prod_eq, mem_map, mem_prod_iff] at this
rcases this with ⟨t, ht, s, hs, h⟩
rw [← image_subset_iff, image_mul_prod] at h
exact ⟨t, mem_nhdsWithin_of_mem_nhds ht, s, hs, h⟩
#align compact_open_separated_mul_right compact_open_separated_mul_right
#align compact_open_separated_add_right compact_open_separated_add_right
open MulOpposite
/-- Given a compact set `K` inside an open set `U`, there is an open neighborhood `V` of `1`
such that `V * K ⊆ U`. -/
@[to_additive
"Given a compact set `K` inside an open set `U`, there is an open neighborhood `V` of
`0` such that `V + K ⊆ U`."]
theorem compact_open_separated_mul_left {K U : Set G} (hK : IsCompact K) (hU : IsOpen U)
(hKU : K ⊆ U) : ∃ V ∈ 𝓝 (1 : G), V * K ⊆ U := by
rcases compact_open_separated_mul_right (hK.image continuous_op) (opHomeomorph.isOpenMap U hU)
(image_subset op hKU) with
⟨V, hV : V ∈ 𝓝 (op (1 : G)), hV' : op '' K * V ⊆ op '' U⟩
refine ⟨op ⁻¹' V, continuous_op.continuousAt hV, ?_⟩
rwa [← image_preimage_eq V op_surjective, ← image_op_mul, image_subset_iff,
preimage_image_eq _ op_injective] at hV'
#align compact_open_separated_mul_left compact_open_separated_mul_left
#align compact_open_separated_add_left compact_open_separated_add_left
end
section
variable [TopologicalSpace G] [Group G] [TopologicalGroup G]
/-- A compact set is covered by finitely many left multiplicative translates of a set
with non-empty interior. -/
@[to_additive
"A compact set is covered by finitely many left additive translates of a set
with non-empty interior."]
theorem compact_covered_by_mul_left_translates {K V : Set G} (hK : IsCompact K)
(hV : (interior V).Nonempty) : ∃ t : Finset G, K ⊆ ⋃ g ∈ t, (g * ·) ⁻¹' V := by
obtain ⟨t, ht⟩ : ∃ t : Finset G, K ⊆ ⋃ x ∈ t, interior ((x * ·) ⁻¹' V) := by
refine
hK.elim_finite_subcover (fun x => interior <| (x * ·) ⁻¹' V) (fun x => isOpen_interior) ?_
cases' hV with g₀ hg₀
refine fun g _ => mem_iUnion.2 ⟨g₀ * g⁻¹, ?_⟩
refine preimage_interior_subset_interior_preimage (continuous_const.mul continuous_id) ?_
rwa [mem_preimage, Function.id_def, inv_mul_cancel_right]
exact ⟨t, Subset.trans ht <| iUnion₂_mono fun g _ => interior_subset⟩
#align compact_covered_by_mul_left_translates compact_covered_by_mul_left_translates
#align compact_covered_by_add_left_translates compact_covered_by_add_left_translates
/-- Every weakly locally compact separable topological group is σ-compact.
Note: this is not true if we drop the topological group hypothesis. -/
@[to_additive SeparableWeaklyLocallyCompactAddGroup.sigmaCompactSpace
"Every weakly locally compact separable topological additive group is σ-compact.
Note: this is not true if we drop the topological group hypothesis."]
instance (priority := 100) SeparableWeaklyLocallyCompactGroup.sigmaCompactSpace [SeparableSpace G]
[WeaklyLocallyCompactSpace G] : SigmaCompactSpace G := by
obtain ⟨L, hLc, hL1⟩ := exists_compact_mem_nhds (1 : G)
refine ⟨⟨fun n => (fun x => x * denseSeq G n) ⁻¹' L, ?_, ?_⟩⟩
· intro n
exact (Homeomorph.mulRight _).isCompact_preimage.mpr hLc
· refine iUnion_eq_univ_iff.2 fun x => ?_
obtain ⟨_, ⟨n, rfl⟩, hn⟩ : (range (denseSeq G) ∩ (fun y => x * y) ⁻¹' L).Nonempty := by
rw [← (Homeomorph.mulLeft x).apply_symm_apply 1] at hL1
exact (denseRange_denseSeq G).inter_nhds_nonempty
((Homeomorph.mulLeft x).continuous.continuousAt <| hL1)
exact ⟨n, hn⟩
#align separable_locally_compact_group.sigma_compact_space SeparableWeaklyLocallyCompactGroup.sigmaCompactSpace
#align separable_locally_compact_add_group.sigma_compact_space SeparableWeaklyLocallyCompactAddGroup.sigmaCompactSpace
/-- Given two compact sets in a noncompact topological group, there is a translate of the second
one that is disjoint from the first one. -/
@[to_additive
"Given two compact sets in a noncompact additive topological group, there is a
translate of the second one that is disjoint from the first one."]
theorem exists_disjoint_smul_of_isCompact [NoncompactSpace G] {K L : Set G} (hK : IsCompact K)
(hL : IsCompact L) : ∃ g : G, Disjoint K (g • L) := by
have A : ¬K * L⁻¹ = univ := (hK.mul hL.inv).ne_univ
obtain ⟨g, hg⟩ : ∃ g, g ∉ K * L⁻¹ := by
contrapose! A
exact eq_univ_iff_forall.2 A
refine ⟨g, ?_⟩
refine disjoint_left.2 fun a ha h'a => hg ?_
rcases h'a with ⟨b, bL, rfl⟩
refine ⟨g * b, ha, b⁻¹, by simpa only [Set.mem_inv, inv_inv] using bL, ?_⟩
simp only [smul_eq_mul, mul_inv_cancel_right]
#align exists_disjoint_smul_of_is_compact exists_disjoint_smul_of_isCompact
#align exists_disjoint_vadd_of_is_compact exists_disjoint_vadd_of_isCompact
/-- A compact neighborhood of `1` in a topological group admits a closed compact subset
that is a neighborhood of `1`. -/
@[to_additive (attr := deprecated IsCompact.isCompact_isClosed_basis_nhds (since := "2024-01-28"))
"A compact neighborhood of `0` in a topological additive group
admits a closed compact subset that is a neighborhood of `0`."]
theorem exists_isCompact_isClosed_subset_isCompact_nhds_one
{L : Set G} (Lcomp : IsCompact L) (L1 : L ∈ 𝓝 (1 : G)) :
∃ K : Set G, IsCompact K ∧ IsClosed K ∧ K ⊆ L ∧ K ∈ 𝓝 (1 : G) :=
let ⟨K, ⟨hK, hK₁, hK₂⟩, hKL⟩ := (Lcomp.isCompact_isClosed_basis_nhds L1).mem_iff.1 L1
⟨K, hK₁, hK₂, hKL, hK⟩
/-- If a point in a topological group has a compact neighborhood, then the group is
locally compact. -/
@[to_additive]
| Mathlib/Topology/Algebra/Group/Basic.lean | 1,844 | 1,850 | theorem IsCompact.locallyCompactSpace_of_mem_nhds_of_group {K : Set G} (hK : IsCompact K) {x : G}
(h : K ∈ 𝓝 x) : LocallyCompactSpace G := by |
suffices WeaklyLocallyCompactSpace G from inferInstance
refine ⟨fun y ↦ ⟨(y * x⁻¹) • K, ?_, ?_⟩⟩
· exact hK.smul _
· rw [← preimage_smul_inv]
exact (continuous_const_smul _).continuousAt.preimage_mem_nhds (by simpa using h)
|
/-
Copyright (c) 2023 Dagur Asgeirsson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Dagur Asgeirsson
-/
import Mathlib.Algebra.Category.ModuleCat.Free
import Mathlib.Topology.Category.Profinite.CofilteredLimit
import Mathlib.Topology.Category.Profinite.Product
import Mathlib.Topology.LocallyConstant.Algebra
import Mathlib.Init.Data.Bool.Lemmas
/-!
# Nöbeling's theorem
This file proves Nöbeling's theorem.
## Main result
* `LocallyConstant.freeOfProfinite`: Nöbeling's theorem.
For `S : Profinite`, the `ℤ`-module `LocallyConstant S ℤ` is free.
## Proof idea
We follow the proof of theorem 5.4 in [scholze2019condensed], in which the idea is to embed `S` in
a product of `I` copies of `Bool` for some sufficiently large `I`, and then to choose a
well-ordering on `I` and use ordinal induction over that well-order. Here we can let `I` be
the set of clopen subsets of `S` since `S` is totally separated.
The above means it suffices to prove the following statement: For a closed subset `C` of `I → Bool`,
the `ℤ`-module `LocallyConstant C ℤ` is free.
For `i : I`, let `e C i : LocallyConstant C ℤ` denote the map `fun f ↦ (if f.val i then 1 else 0)`.
The basis will consist of products `e C iᵣ * ⋯ * e C i₁` with `iᵣ > ⋯ > i₁` which cannot be written
as linear combinations of lexicographically smaller products. We call this set `GoodProducts C`
What is proved by ordinal induction is that this set is linearly independent. The fact that it
spans can be proved directly.
## References
- [scholze2019condensed], Theorem 5.4.
-/
universe u
namespace Profinite
namespace NobelingProof
variable {I : Type u} [LinearOrder I] [IsWellOrder I (·<·)] (C : Set (I → Bool))
open Profinite ContinuousMap CategoryTheory Limits Opposite Submodule
section Projections
/-!
## Projection maps
The purpose of this section is twofold.
Firstly, in the proof that the set `GoodProducts C` spans the whole module `LocallyConstant C ℤ`,
we need to project `C` down to finite discrete subsets and write `C` as a cofiltered limit of those.
Secondly, in the inductive argument, we need to project `C` down to "smaller" sets satisfying the
inductive hypothesis.
In this section we define the relevant projection maps and prove some compatibility results.
### Main definitions
* Let `J : I → Prop`. Then `Proj J : (I → Bool) → (I → Bool)` is the projection mapping everything
that satisfies `J i` to itself, and everything else to `false`.
* The image of `C` under `Proj J` is denoted `π C J` and the corresponding map `C → π C J` is called
`ProjRestrict`. If `J` implies `K` we have a map `ProjRestricts : π C K → π C J`.
* `spanCone_isLimit` establishes that when `C` is compact, it can be written as a limit of its
images under the maps `Proj (· ∈ s)` where `s : Finset I`.
-/
variable (J K L : I → Prop) [∀ i, Decidable (J i)] [∀ i, Decidable (K i)] [∀ i, Decidable (L i)]
/--
The projection mapping everything that satisfies `J i` to itself, and everything else to `false`
-/
def Proj : (I → Bool) → (I → Bool) :=
fun c i ↦ if J i then c i else false
@[simp]
theorem continuous_proj :
Continuous (Proj J : (I → Bool) → (I → Bool)) := by
dsimp (config := { unfoldPartialApp := true }) [Proj]
apply continuous_pi
intro i
split
· apply continuous_apply
· apply continuous_const
/-- The image of `Proj π J` -/
def π : Set (I → Bool) := (Proj J) '' C
/-- The restriction of `Proj π J` to a subset, mapping to its image. -/
@[simps!]
def ProjRestrict : C → π C J :=
Set.MapsTo.restrict (Proj J) _ _ (Set.mapsTo_image _ _)
@[simp]
theorem continuous_projRestrict : Continuous (ProjRestrict C J) :=
Continuous.restrict _ (continuous_proj _)
theorem proj_eq_self {x : I → Bool} (h : ∀ i, x i ≠ false → J i) : Proj J x = x := by
ext i
simp only [Proj, ite_eq_left_iff]
contrapose!
simpa only [ne_comm] using h i
theorem proj_prop_eq_self (hh : ∀ i x, x ∈ C → x i ≠ false → J i) : π C J = C := by
ext x
refine ⟨fun ⟨y, hy, h⟩ ↦ ?_, fun h ↦ ⟨x, h, ?_⟩⟩
· rwa [← h, proj_eq_self]; exact (hh · y hy)
· rw [proj_eq_self]; exact (hh · x h)
theorem proj_comp_of_subset (h : ∀ i, J i → K i) : (Proj J ∘ Proj K) =
(Proj J : (I → Bool) → (I → Bool)) := by
ext x i; dsimp [Proj]; aesop
theorem proj_eq_of_subset (h : ∀ i, J i → K i) : π (π C K) J = π C J := by
ext x
refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· obtain ⟨y, ⟨z, hz, rfl⟩, rfl⟩ := h
refine ⟨z, hz, (?_ : _ = (Proj J ∘ Proj K) z)⟩
rw [proj_comp_of_subset J K h]
· obtain ⟨y, hy, rfl⟩ := h
dsimp [π]
rw [← Set.image_comp]
refine ⟨y, hy, ?_⟩
rw [proj_comp_of_subset J K h]
variable {J K L}
/-- A variant of `ProjRestrict` with domain of the form `π C K` -/
@[simps!]
def ProjRestricts (h : ∀ i, J i → K i) : π C K → π C J :=
Homeomorph.setCongr (proj_eq_of_subset C J K h) ∘ ProjRestrict (π C K) J
@[simp]
theorem continuous_projRestricts (h : ∀ i, J i → K i) : Continuous (ProjRestricts C h) :=
Continuous.comp (Homeomorph.continuous _) (continuous_projRestrict _ _)
theorem surjective_projRestricts (h : ∀ i, J i → K i) : Function.Surjective (ProjRestricts C h) :=
(Homeomorph.surjective _).comp (Set.surjective_mapsTo_image_restrict _ _)
variable (J) in
theorem projRestricts_eq_id : ProjRestricts C (fun i (h : J i) ↦ h) = id := by
ext ⟨x, y, hy, rfl⟩ i
simp (config := { contextual := true }) only [π, Proj, ProjRestricts_coe, id_eq, if_true]
theorem projRestricts_eq_comp (hJK : ∀ i, J i → K i) (hKL : ∀ i, K i → L i) :
ProjRestricts C hJK ∘ ProjRestricts C hKL = ProjRestricts C (fun i ↦ hKL i ∘ hJK i) := by
ext x i
simp only [π, Proj, Function.comp_apply, ProjRestricts_coe]
aesop
theorem projRestricts_comp_projRestrict (h : ∀ i, J i → K i) :
ProjRestricts C h ∘ ProjRestrict C K = ProjRestrict C J := by
ext x i
simp only [π, Proj, Function.comp_apply, ProjRestricts_coe, ProjRestrict_coe]
aesop
variable (J)
/-- The objectwise map in the isomorphism `spanFunctor ≅ Profinite.indexFunctor`. -/
def iso_map : C(π C J, (IndexFunctor.obj C J)) :=
⟨fun x ↦ ⟨fun i ↦ x.val i.val, by
rcases x with ⟨x, y, hy, rfl⟩
refine ⟨y, hy, ?_⟩
ext ⟨i, hi⟩
simp [precomp, Proj, hi]⟩, by
refine Continuous.subtype_mk (continuous_pi fun i ↦ ?_) _
exact (continuous_apply i.val).comp continuous_subtype_val⟩
lemma iso_map_bijective : Function.Bijective (iso_map C J) := by
refine ⟨fun a b h ↦ ?_, fun a ↦ ?_⟩
· ext i
rw [Subtype.ext_iff] at h
by_cases hi : J i
· exact congr_fun h ⟨i, hi⟩
· rcases a with ⟨_, c, hc, rfl⟩
rcases b with ⟨_, d, hd, rfl⟩
simp only [Proj, if_neg hi]
· refine ⟨⟨fun i ↦ if hi : J i then a.val ⟨i, hi⟩ else false, ?_⟩, ?_⟩
· rcases a with ⟨_, y, hy, rfl⟩
exact ⟨y, hy, rfl⟩
· ext i
exact dif_pos i.prop
variable {C} (hC : IsCompact C)
/--
For a given compact subset `C` of `I → Bool`, `spanFunctor` is the functor from the poset of finsets
of `I` to `Profinite`, sending a finite subset set `J` to the image of `C` under the projection
`Proj J`.
-/
noncomputable
def spanFunctor [∀ (s : Finset I) (i : I), Decidable (i ∈ s)] :
(Finset I)ᵒᵖ ⥤ Profinite.{u} where
obj s := @Profinite.of (π C (· ∈ (unop s))) _
(by rw [← isCompact_iff_compactSpace]; exact hC.image (continuous_proj _)) _ _
map h := ⟨(ProjRestricts C (leOfHom h.unop)), continuous_projRestricts _ _⟩
map_id J := by simp only [projRestricts_eq_id C (· ∈ (unop J))]; rfl
map_comp _ _ := by dsimp; congr; dsimp; rw [projRestricts_eq_comp]
/-- The limit cone on `spanFunctor` with point `C`. -/
noncomputable
def spanCone [∀ (s : Finset I) (i : I), Decidable (i ∈ s)] : Cone (spanFunctor hC) where
pt := @Profinite.of C _ (by rwa [← isCompact_iff_compactSpace]) _ _
π :=
{ app := fun s ↦ ⟨ProjRestrict C (· ∈ unop s), continuous_projRestrict _ _⟩
naturality := by
intro X Y h
simp only [Functor.const_obj_obj, Homeomorph.setCongr, Homeomorph.homeomorph_mk_coe,
Functor.const_obj_map, Category.id_comp, ← projRestricts_comp_projRestrict C
(leOfHom h.unop)]
rfl }
/-- `spanCone` is a limit cone. -/
noncomputable
def spanCone_isLimit [∀ (s : Finset I) (i : I), Decidable (i ∈ s)] :
CategoryTheory.Limits.IsLimit (spanCone hC) := by
refine (IsLimit.postcomposeHomEquiv (NatIso.ofComponents
(fun s ↦ (Profinite.isoOfBijective _ (iso_map_bijective C (· ∈ unop s)))) ?_) (spanCone hC))
(IsLimit.ofIsoLimit (indexCone_isLimit hC) (Cones.ext (Iso.refl _) ?_))
· intro ⟨s⟩ ⟨t⟩ ⟨⟨⟨f⟩⟩⟩
ext x
have : iso_map C (· ∈ t) ∘ ProjRestricts C f = IndexFunctor.map C f ∘ iso_map C (· ∈ s) := by
ext _ i; exact dif_pos i.prop
exact congr_fun this x
· intro ⟨s⟩
ext x
have : iso_map C (· ∈ s) ∘ ProjRestrict C (· ∈ s) = IndexFunctor.π_app C (· ∈ s) := by
ext _ i; exact dif_pos i.prop
erw [← this]
rfl
end Projections
section Products
/-!
## Defining the basis
Our proposed basis consists of products `e C iᵣ * ⋯ * e C i₁` with `iᵣ > ⋯ > i₁` which cannot be
written as linear combinations of lexicographically smaller products. See below for the definition
of `e`.
### Main definitions
* For `i : I`, we let `e C i : LocallyConstant C ℤ` denote the map
`fun f ↦ (if f.val i then 1 else 0)`.
* `Products I` is the type of lists of decreasing elements of `I`, so a typical element is
`[i₁, i₂,..., iᵣ]` with `i₁ > i₂ > ... > iᵣ`.
* `Products.eval C` is the `C`-evaluation of a list. It takes a term `[i₁, i₂,..., iᵣ] : Products I`
and returns the actual product `e C i₁ ··· e C iᵣ : LocallyConstant C ℤ`.
* `GoodProducts C` is the set of `Products I` such that their `C`-evaluation cannot be written as
a linear combination of evaluations of lexicographically smaller lists.
### Main results
* `Products.evalFacProp` and `Products.evalFacProps` establish the fact that `Products.eval`
interacts nicely with the projection maps from the previous section.
* `GoodProducts.span_iff_products`: the good products span `LocallyConstant C ℤ` iff all the
products span `LocallyConstant C ℤ`.
-/
/--
`e C i` is the locally constant map from `C : Set (I → Bool)` to `ℤ` sending `f` to 1 if
`f.val i = true`, and 0 otherwise.
-/
def e (i : I) : LocallyConstant C ℤ where
toFun := fun f ↦ (if f.val i then 1 else 0)
isLocallyConstant := by
rw [IsLocallyConstant.iff_continuous]
exact (continuous_of_discreteTopology (f := fun (a : Bool) ↦ (if a then (1 : ℤ) else 0))).comp
((continuous_apply i).comp continuous_subtype_val)
/--
`Products I` is the type of lists of decreasing elements of `I`, so a typical element is
`[i₁, i₂, ...]` with `i₁ > i₂ > ...`. We order `Products I` lexicographically, so `[] < [i₁, ...]`,
and `[i₁, i₂, ...] < [j₁, j₂, ...]` if either `i₁ < j₁`, or `i₁ = j₁` and `[i₂, ...] < [j₂, ...]`.
Terms `m = [i₁, i₂, ..., iᵣ]` of this type will be used to represent products of the form
`e C i₁ ··· e C iᵣ : LocallyConstant C ℤ` . The function associated to `m` is `m.eval`.
-/
def Products (I : Type*) [LinearOrder I] := {l : List I // l.Chain' (·>·)}
namespace Products
instance : LinearOrder (Products I) :=
inferInstanceAs (LinearOrder {l : List I // l.Chain' (·>·)})
@[simp]
theorem lt_iff_lex_lt (l m : Products I) : l < m ↔ List.Lex (·<·) l.val m.val := by
cases l; cases m; rw [Subtype.mk_lt_mk]; exact Iff.rfl
instance : IsWellFounded (Products I) (·<·) := by
have : (· < · : Products I → _ → _) = (fun l m ↦ List.Lex (·<·) l.val m.val) := by
ext; exact lt_iff_lex_lt _ _
rw [this]
dsimp [Products]
rw [(by rfl : (·>· : I → _) = flip (·<·))]
infer_instance
/-- The evaluation `e C i₁ ··· e C iᵣ : C → ℤ` of a formal product `[i₁, i₂, ..., iᵣ]`. -/
def eval (l : Products I) := (l.1.map (e C)).prod
/--
The predicate on products which we prove picks out a basis of `LocallyConstant C ℤ`. We call such a
product "good".
-/
def isGood (l : Products I) : Prop :=
l.eval C ∉ Submodule.span ℤ ((Products.eval C) '' {m | m < l})
theorem rel_head!_of_mem [Inhabited I] {i : I} {l : Products I} (hi : i ∈ l.val) :
i ≤ l.val.head! :=
List.Sorted.le_head! (List.chain'_iff_pairwise.mp l.prop) hi
theorem head!_le_of_lt [Inhabited I] {q l : Products I} (h : q < l) (hq : q.val ≠ []) :
q.val.head! ≤ l.val.head! :=
List.head!_le_of_lt l.val q.val h hq
end Products
/-- The set of good products. -/
def GoodProducts := {l : Products I | l.isGood C}
namespace GoodProducts
/-- Evaluation of good products. -/
def eval (l : {l : Products I // l.isGood C}) : LocallyConstant C ℤ :=
Products.eval C l.1
theorem injective : Function.Injective (eval C) := by
intro ⟨a, ha⟩ ⟨b, hb⟩ h
dsimp [eval] at h
rcases lt_trichotomy a b with (h'|rfl|h')
· exfalso; apply hb; rw [← h]
exact Submodule.subset_span ⟨a, h', rfl⟩
· rfl
· exfalso; apply ha; rw [h]
exact Submodule.subset_span ⟨b, ⟨h',rfl⟩⟩
/-- The image of the good products in the module `LocallyConstant C ℤ`. -/
def range := Set.range (GoodProducts.eval C)
/-- The type of good products is equivalent to its image. -/
noncomputable
def equiv_range : GoodProducts C ≃ range C :=
Equiv.ofInjective (eval C) (injective C)
theorem equiv_toFun_eq_eval : (equiv_range C).toFun = Set.rangeFactorization (eval C) := rfl
theorem linearIndependent_iff_range : LinearIndependent ℤ (GoodProducts.eval C) ↔
LinearIndependent ℤ (fun (p : range C) ↦ p.1) := by
rw [← @Set.rangeFactorization_eq _ _ (GoodProducts.eval C), ← equiv_toFun_eq_eval C]
exact linearIndependent_equiv (equiv_range C)
end GoodProducts
namespace Products
theorem eval_eq (l : Products I) (x : C) :
l.eval C x = if ∀ i, i ∈ l.val → (x.val i = true) then 1 else 0 := by
change LocallyConstant.evalMonoidHom x (l.eval C) = _
rw [eval, map_list_prod]
split_ifs with h
· simp only [List.map_map]
apply List.prod_eq_one
simp only [List.mem_map, Function.comp_apply]
rintro _ ⟨i, hi, rfl⟩
exact if_pos (h i hi)
· simp only [List.map_map, List.prod_eq_zero_iff, List.mem_map, Function.comp_apply]
push_neg at h
convert h with i
dsimp [LocallyConstant.evalMonoidHom, e]
simp only [ite_eq_right_iff, one_ne_zero]
theorem evalFacProp {l : Products I} (J : I → Prop)
(h : ∀ a, a ∈ l.val → J a) [∀ j, Decidable (J j)] :
l.eval (π C J) ∘ ProjRestrict C J = l.eval C := by
ext x
dsimp [ProjRestrict]
rw [Products.eval_eq, Products.eval_eq]
congr
apply forall_congr; intro i
apply forall_congr; intro hi
simp [h i hi, Proj]
theorem evalFacProps {l : Products I} (J K : I → Prop)
(h : ∀ a, a ∈ l.val → J a) [∀ j, Decidable (J j)] [∀ j, Decidable (K j)]
(hJK : ∀ i, J i → K i) :
l.eval (π C J) ∘ ProjRestricts C hJK = l.eval (π C K) := by
have : l.eval (π C J) ∘ Homeomorph.setCongr (proj_eq_of_subset C J K hJK) =
l.eval (π (π C K) J) := by
ext; simp [Homeomorph.setCongr, Products.eval_eq]
rw [ProjRestricts, ← Function.comp.assoc, this, ← evalFacProp (π C K) J h]
theorem prop_of_isGood {l : Products I} (J : I → Prop) [∀ j, Decidable (J j)]
(h : l.isGood (π C J)) : ∀ a, a ∈ l.val → J a := by
intro i hi
by_contra h'
apply h
suffices eval (π C J) l = 0 by
rw [this]
exact Submodule.zero_mem _
ext ⟨_, _, _, rfl⟩
rw [eval_eq, if_neg fun h ↦ ?_, LocallyConstant.zero_apply]
simpa [Proj, h'] using h i hi
end Products
/-- The good products span `LocallyConstant C ℤ` if and only all the products do. -/
theorem GoodProducts.span_iff_products : ⊤ ≤ span ℤ (Set.range (eval C)) ↔
⊤ ≤ span ℤ (Set.range (Products.eval C)) := by
refine ⟨fun h ↦ le_trans h (span_mono (fun a ⟨b, hb⟩ ↦ ⟨b.val, hb⟩)), fun h ↦ le_trans h ?_⟩
rw [span_le]
rintro f ⟨l, rfl⟩
let L : Products I → Prop := fun m ↦ m.eval C ∈ span ℤ (Set.range (GoodProducts.eval C))
suffices L l by assumption
apply IsWellFounded.induction (·<· : Products I → Products I → Prop)
intro l h
dsimp
by_cases hl : l.isGood C
· apply subset_span
exact ⟨⟨l, hl⟩, rfl⟩
· simp only [Products.isGood, not_not] at hl
suffices Products.eval C '' {m | m < l} ⊆ span ℤ (Set.range (GoodProducts.eval C)) by
rw [← span_le] at this
exact this hl
rintro a ⟨m, hm, rfl⟩
exact h m hm
end Products
section Span
/-!
## The good products span
Most of the argument is developing an API for `π C (· ∈ s)` when `s : Finset I`; then the image
of `C` is finite with the discrete topology. In this case, there is a direct argument that the good
products span. The general result is deduced from this.
### Main theorems
* `GoodProducts.spanFin` : The good products span the locally constant functions on `π C (· ∈ s)`
if `s` is finite.
* `GoodProducts.span` : The good products span `LocallyConstant C ℤ` for every closed subset `C`.
-/
section Fin
variable (s : Finset I)
/-- The `ℤ`-linear map induced by precomposition of the projection `C → π C (· ∈ s)`. -/
noncomputable
def πJ : LocallyConstant (π C (· ∈ s)) ℤ →ₗ[ℤ] LocallyConstant C ℤ :=
LocallyConstant.comapₗ ℤ ⟨_, (continuous_projRestrict C (· ∈ s))⟩
theorem eval_eq_πJ (l : Products I) (hl : l.isGood (π C (· ∈ s))) :
l.eval C = πJ C s (l.eval (π C (· ∈ s))) := by
ext f
simp only [πJ, LocallyConstant.comapₗ, LinearMap.coe_mk, AddHom.coe_mk,
(continuous_projRestrict C (· ∈ s)), LocallyConstant.coe_comap, Function.comp_apply]
exact (congr_fun (Products.evalFacProp C (· ∈ s) (Products.prop_of_isGood C (· ∈ s) hl)) _).symm
/-- `π C (· ∈ s)` is finite for a finite set `s`. -/
noncomputable
instance : Fintype (π C (· ∈ s)) := by
let f : π C (· ∈ s) → (s → Bool) := fun x j ↦ x.val j.val
refine Fintype.ofInjective f ?_
intro ⟨_, x, hx, rfl⟩ ⟨_, y, hy, rfl⟩ h
ext i
by_cases hi : i ∈ s
· exact congrFun h ⟨i, hi⟩
· simp only [Proj, if_neg hi]
open scoped Classical in
/-- The Kronecker delta as a locally constant map from `π C (· ∈ s)` to `ℤ`. -/
noncomputable
def spanFinBasis (x : π C (· ∈ s)) : LocallyConstant (π C (· ∈ s)) ℤ where
toFun := fun y ↦ if y = x then 1 else 0
isLocallyConstant :=
haveI : DiscreteTopology (π C (· ∈ s)) := discrete_of_t1_of_finite
IsLocallyConstant.of_discrete _
open scoped Classical in
theorem spanFinBasis.span : ⊤ ≤ Submodule.span ℤ (Set.range (spanFinBasis C s)) := by
intro f _
rw [Finsupp.mem_span_range_iff_exists_finsupp]
use Finsupp.onFinset (Finset.univ) f.toFun (fun _ _ ↦ Finset.mem_univ _)
ext x
change LocallyConstant.evalₗ ℤ x _ = _
simp only [zsmul_eq_mul, map_finsupp_sum, LocallyConstant.evalₗ_apply,
LocallyConstant.coe_mul, Pi.mul_apply, spanFinBasis, LocallyConstant.coe_mk, mul_ite, mul_one,
mul_zero, Finsupp.sum_ite_eq, Finsupp.mem_support_iff, ne_eq, ite_not]
split_ifs with h <;> [exact h.symm; rfl]
/--
A certain explicit list of locally constant maps. The theorem `factors_prod_eq_basis` shows that the
product of the elements in this list is the delta function `spanFinBasis C s x`.
-/
def factors (x : π C (· ∈ s)) : List (LocallyConstant (π C (· ∈ s)) ℤ) :=
List.map (fun i ↦ if x.val i = true then e (π C (· ∈ s)) i else (1 - (e (π C (· ∈ s)) i)))
(s.sort (·≥·))
theorem list_prod_apply (x : C) (l : List (LocallyConstant C ℤ)) :
l.prod x = (l.map (LocallyConstant.evalMonoidHom x)).prod := by
rw [← map_list_prod (LocallyConstant.evalMonoidHom x) l]
rfl
theorem factors_prod_eq_basis_of_eq {x y : (π C fun x ↦ x ∈ s)} (h : y = x) :
(factors C s x).prod y = 1 := by
rw [list_prod_apply (π C (· ∈ s)) y _]
apply List.prod_eq_one
simp only [h, List.mem_map, LocallyConstant.evalMonoidHom, factors]
rintro _ ⟨a, ⟨b, _, rfl⟩, rfl⟩
dsimp
split_ifs with hh
· rw [e, LocallyConstant.coe_mk, if_pos hh]
· rw [LocallyConstant.sub_apply, e, LocallyConstant.coe_mk, LocallyConstant.coe_mk, if_neg hh]
simp only [LocallyConstant.toFun_eq_coe, LocallyConstant.coe_one, Pi.one_apply, sub_zero]
theorem e_mem_of_eq_true {x : (π C (· ∈ s))} {a : I} (hx : x.val a = true) :
e (π C (· ∈ s)) a ∈ factors C s x := by
rcases x with ⟨_, z, hz, rfl⟩
simp only [factors, List.mem_map, Finset.mem_sort]
refine ⟨a, ?_, if_pos hx⟩
aesop (add simp Proj)
theorem one_sub_e_mem_of_false {x y : (π C (· ∈ s))} {a : I} (ha : y.val a = true)
(hx : x.val a = false) : 1 - e (π C (· ∈ s)) a ∈ factors C s x := by
simp only [factors, List.mem_map, Finset.mem_sort]
use a
simp only [hx, ite_false, and_true]
rcases y with ⟨_, z, hz, rfl⟩
aesop (add simp Proj)
theorem factors_prod_eq_basis_of_ne {x y : (π C (· ∈ s))} (h : y ≠ x) :
(factors C s x).prod y = 0 := by
rw [list_prod_apply (π C (· ∈ s)) y _]
apply List.prod_eq_zero
simp only [List.mem_map]
obtain ⟨a, ha⟩ : ∃ a, y.val a ≠ x.val a := by contrapose! h; ext; apply h
cases hx : x.val a
· rw [hx, ne_eq, Bool.not_eq_false] at ha
refine ⟨1 - (e (π C (· ∈ s)) a), ⟨one_sub_e_mem_of_false _ _ ha hx, ?_⟩⟩
rw [e, LocallyConstant.evalMonoidHom_apply, LocallyConstant.sub_apply,
LocallyConstant.coe_one, Pi.one_apply, LocallyConstant.coe_mk, if_pos ha, sub_self]
· refine ⟨e (π C (· ∈ s)) a, ⟨e_mem_of_eq_true _ _ hx, ?_⟩⟩
rw [hx] at ha
rw [LocallyConstant.evalMonoidHom_apply, e, LocallyConstant.coe_mk, if_neg ha]
/-- If `s` is finite, the product of the elements of the list `factors C s x`
is the delta function at `x`. -/
theorem factors_prod_eq_basis (x : π C (· ∈ s)) :
(factors C s x).prod = spanFinBasis C s x := by
ext y
dsimp [spanFinBasis]
split_ifs with h <;> [exact factors_prod_eq_basis_of_eq _ _ h;
exact factors_prod_eq_basis_of_ne _ _ h]
theorem GoodProducts.finsupp_sum_mem_span_eval {a : I} {as : List I}
(ha : List.Chain' (· > ·) (a :: as)) {c : Products I →₀ ℤ}
(hc : (c.support : Set (Products I)) ⊆ {m | m.val ≤ as}) :
(Finsupp.sum c fun a_1 b ↦ e (π C (· ∈ s)) a * b • Products.eval (π C (· ∈ s)) a_1) ∈
Submodule.span ℤ (Products.eval (π C (· ∈ s)) '' {m | m.val ≤ a :: as}) := by
apply Submodule.finsupp_sum_mem
intro m hm
have hsm := (LinearMap.mulLeft ℤ (e (π C (· ∈ s)) a)).map_smul
dsimp at hsm
rw [hsm]
apply Submodule.smul_mem
apply Submodule.subset_span
have hmas : m.val ≤ as := by
apply hc
simpa only [Finset.mem_coe, Finsupp.mem_support_iff] using hm
refine ⟨⟨a :: m.val, ha.cons_of_le m.prop hmas⟩, ⟨List.cons_le_cons a hmas, ?_⟩⟩
simp only [Products.eval, List.map, List.prod_cons]
/-- If `s` is a finite subset of `I`, then the good products span. -/
theorem GoodProducts.spanFin : ⊤ ≤ Submodule.span ℤ (Set.range (eval (π C (· ∈ s)))) := by
rw [span_iff_products]
refine le_trans (spanFinBasis.span C s) ?_
rw [Submodule.span_le]
rintro _ ⟨x, rfl⟩
rw [← factors_prod_eq_basis]
let l := s.sort (·≥·)
dsimp [factors]
suffices l.Chain' (·>·) → (l.map (fun i ↦ if x.val i = true then e (π C (· ∈ s)) i
else (1 - (e (π C (· ∈ s)) i)))).prod ∈
Submodule.span ℤ ((Products.eval (π C (· ∈ s))) '' {m | m.val ≤ l}) from
Submodule.span_mono (Set.image_subset_range _ _) (this (Finset.sort_sorted_gt _).chain')
induction l with
| nil =>
intro _
apply Submodule.subset_span
exact ⟨⟨[], List.chain'_nil⟩,⟨Or.inl rfl, rfl⟩⟩
| cons a as ih =>
rw [List.map_cons, List.prod_cons]
intro ha
specialize ih (by rw [List.chain'_cons'] at ha; exact ha.2)
rw [Finsupp.mem_span_image_iff_total] at ih
simp only [Finsupp.mem_supported, Finsupp.total_apply] at ih
obtain ⟨c, hc, hc'⟩ := ih
rw [← hc']; clear hc'
have hmap := fun g ↦ map_finsupp_sum (LinearMap.mulLeft ℤ (e (π C (· ∈ s)) a)) c g
dsimp at hmap ⊢
split_ifs
· rw [hmap]
exact finsupp_sum_mem_span_eval _ _ ha hc
· ring_nf
rw [hmap]
apply Submodule.add_mem
· apply Submodule.neg_mem
exact finsupp_sum_mem_span_eval _ _ ha hc
· apply Submodule.finsupp_sum_mem
intro m hm
apply Submodule.smul_mem
apply Submodule.subset_span
refine ⟨m, ⟨?_, rfl⟩⟩
simp only [Set.mem_setOf_eq]
have hmas : m.val ≤ as :=
hc (by simpa only [Finset.mem_coe, Finsupp.mem_support_iff] using hm)
refine le_trans hmas ?_
cases as with
| nil => exact (List.nil_lt_cons a []).le
| cons b bs =>
apply le_of_lt
rw [List.chain'_cons] at ha
have hlex := List.lt.head bs (b :: bs) ha.1
exact (List.lt_iff_lex_lt _ _).mp hlex
end Fin
theorem fin_comap_jointlySurjective
(hC : IsClosed C)
(f : LocallyConstant C ℤ) : ∃ (s : Finset I)
(g : LocallyConstant (π C (· ∈ s)) ℤ), f = g.comap ⟨(ProjRestrict C (· ∈ s)),
continuous_projRestrict _ _⟩ := by
obtain ⟨J, g, h⟩ := @Profinite.exists_locallyConstant.{0, u, u} (Finset I)ᵒᵖ _ _ _
(spanCone hC.isCompact) ℤ
(spanCone_isLimit hC.isCompact) f
exact ⟨(Opposite.unop J), g, h⟩
/-- The good products span all of `LocallyConstant C ℤ` if `C` is closed. -/
theorem GoodProducts.span (hC : IsClosed C) :
⊤ ≤ Submodule.span ℤ (Set.range (eval C)) := by
rw [span_iff_products]
intro f _
obtain ⟨K, f', rfl⟩ : ∃ K f', f = πJ C K f' := fin_comap_jointlySurjective C hC f
refine Submodule.span_mono ?_ <| Submodule.apply_mem_span_image_of_mem_span (πJ C K) <|
spanFin C K (Submodule.mem_top : f' ∈ ⊤)
rintro l ⟨y, ⟨m, rfl⟩, rfl⟩
exact ⟨m.val, eval_eq_πJ C K m.val m.prop⟩
end Span
section Ordinal
/-!
## Relating elements of the well-order `I` with ordinals
We choose a well-ordering on `I`. This amounts to regarding `I` as an ordinal, and as such it
can be regarded as the set of all strictly smaller ordinals, allowing to apply ordinal induction.
### Main definitions
* `ord I i` is the term `i` of `I` regarded as an ordinal.
* `term I ho` is a sufficiently small ordinal regarded as a term of `I`.
* `contained C o` is a predicate saying that `C` is "small" enough in relation to the ordinal `o`
to satisfy the inductive hypothesis.
* `P I` is the predicate on ordinals about linear independence of good products, which the rest of
this file is spent on proving by induction.
-/
variable (I)
/-- A term of `I` regarded as an ordinal. -/
def ord (i : I) : Ordinal := Ordinal.typein ((·<·) : I → I → Prop) i
/-- An ordinal regarded as a term of `I`. -/
noncomputable
def term {o : Ordinal} (ho : o < Ordinal.type ((·<·) : I → I → Prop)) : I :=
Ordinal.enum ((·<·) : I → I → Prop) o ho
variable {I}
theorem term_ord_aux {i : I} (ho : ord I i < Ordinal.type ((·<·) : I → I → Prop)) :
term I ho = i := by
simp only [term, ord, Ordinal.enum_typein]
@[simp]
theorem ord_term_aux {o : Ordinal} (ho : o < Ordinal.type ((·<·) : I → I → Prop)) :
ord I (term I ho) = o := by
simp only [ord, term, Ordinal.typein_enum]
theorem ord_term {o : Ordinal} (ho : o < Ordinal.type ((·<·) : I → I → Prop)) (i : I) :
ord I i = o ↔ term I ho = i := by
refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· subst h
exact term_ord_aux ho
· subst h
exact ord_term_aux ho
/-- A predicate saying that `C` is "small" enough to satisfy the inductive hypothesis. -/
def contained (o : Ordinal) : Prop := ∀ f, f ∈ C → ∀ (i : I), f i = true → ord I i < o
variable (I) in
/--
The predicate on ordinals which we prove by induction, see `GoodProducts.P0`,
`GoodProducts.Plimit` and `GoodProducts.linearIndependentAux` in the section `Induction` below
-/
def P (o : Ordinal) : Prop :=
o ≤ Ordinal.type (·<· : I → I → Prop) →
(∀ (C : Set (I → Bool)), IsClosed C → contained C o →
LinearIndependent ℤ (GoodProducts.eval C))
theorem Products.prop_of_isGood_of_contained {l : Products I} (o : Ordinal) (h : l.isGood C)
(hsC : contained C o) (i : I) (hi : i ∈ l.val) : ord I i < o := by
by_contra h'
apply h
suffices eval C l = 0 by simp [this, Submodule.zero_mem]
ext x
simp only [eval_eq, LocallyConstant.coe_zero, Pi.zero_apply, ite_eq_right_iff, one_ne_zero]
contrapose! h'
exact hsC x.val x.prop i (h'.1 i hi)
end Ordinal
section Zero
/-!
## The zero case of the induction
In this case, we have `contained C 0` which means that `C` is either empty or a singleton.
-/
instance : Subsingleton (LocallyConstant (∅ : Set (I → Bool)) ℤ) :=
subsingleton_iff.mpr (fun _ _ ↦ LocallyConstant.ext isEmptyElim)
instance : IsEmpty { l // Products.isGood (∅ : Set (I → Bool)) l } :=
isEmpty_iff.mpr fun ⟨l, hl⟩ ↦ hl <| by
rw [subsingleton_iff.mp inferInstance (Products.eval ∅ l) 0]
exact Submodule.zero_mem _
theorem GoodProducts.linearIndependentEmpty :
LinearIndependent ℤ (eval (∅ : Set (I → Bool))) := linearIndependent_empty_type
/-- The empty list as a `Products` -/
def Products.nil : Products I := ⟨[], by simp only [List.chain'_nil]⟩
theorem Products.lt_nil_empty : { m : Products I | m < Products.nil } = ∅ := by
ext ⟨m, hm⟩
refine ⟨fun h ↦ ?_, by tauto⟩
simp only [Set.mem_setOf_eq, lt_iff_lex_lt, nil, List.Lex.not_nil_right] at h
instance {α : Type*} [TopologicalSpace α] [Nonempty α] : Nontrivial (LocallyConstant α ℤ) :=
⟨0, 1, ne_of_apply_ne DFunLike.coe <| (Function.const_injective (β := ℤ)).ne zero_ne_one⟩
set_option backward.synthInstance.canonInstances false in -- See https://github.com/leanprover-community/mathlib4/issues/12532
theorem Products.isGood_nil : Products.isGood ({fun _ ↦ false} : Set (I → Bool)) Products.nil := by
intro h
simp only [Products.lt_nil_empty, Products.eval, List.map, List.prod_nil, Set.image_empty,
Submodule.span_empty, Submodule.mem_bot, one_ne_zero] at h
set_option backward.synthInstance.canonInstances false in -- See https://github.com/leanprover-community/mathlib4/issues/12532
theorem Products.span_nil_eq_top :
Submodule.span ℤ (eval ({fun _ ↦ false} : Set (I → Bool)) '' {nil}) = ⊤ := by
rw [Set.image_singleton, eq_top_iff]
intro f _
rw [Submodule.mem_span_singleton]
refine ⟨f default, ?_⟩
simp only [eval, List.map, List.prod_nil, zsmul_eq_mul, mul_one]
ext x
obtain rfl : x = default := by simp only [Set.default_coe_singleton, eq_iff_true_of_subsingleton]
rfl
/-- There is a unique `GoodProducts` for the singleton `{fun _ ↦ false}`. -/
noncomputable
instance : Unique { l // Products.isGood ({fun _ ↦ false} : Set (I → Bool)) l } where
default := ⟨Products.nil, Products.isGood_nil⟩
uniq := by
intro ⟨⟨l, hl⟩, hll⟩
ext
apply Subtype.ext
apply (List.Lex.nil_left_or_eq_nil l (r := (·<·))).resolve_left
intro _
apply hll
have he : {Products.nil} ⊆ {m | m < ⟨l,hl⟩} := by
simpa only [Products.nil, Products.lt_iff_lex_lt, Set.singleton_subset_iff, Set.mem_setOf_eq]
apply Submodule.span_mono (Set.image_subset _ he)
rw [Products.span_nil_eq_top]
exact Submodule.mem_top
instance (α : Type*) [TopologicalSpace α] : NoZeroSMulDivisors ℤ (LocallyConstant α ℤ) := by
constructor
intro c f h
rw [or_iff_not_imp_left]
intro hc
ext x
apply mul_right_injective₀ hc
simp [LocallyConstant.ext_iff] at h ⊢
exact h x
set_option backward.synthInstance.canonInstances false in -- See https://github.com/leanprover-community/mathlib4/issues/12532
theorem GoodProducts.linearIndependentSingleton :
LinearIndependent ℤ (eval ({fun _ ↦ false} : Set (I → Bool))) := by
refine linearIndependent_unique (eval ({fun _ ↦ false} : Set (I → Bool))) ?_
simp only [eval, Products.eval, List.map, List.prod_nil, ne_eq, one_ne_zero, not_false_eq_true]
end Zero
section Maps
/-!
## `ℤ`-linear maps induced by projections
We define injective `ℤ`-linear maps between modules of the form `LocallyConstant C ℤ` induced by
precomposition with the projections defined in the section `Projections`.
### Main definitions
* `πs` and `πs'` are the `ℤ`-linear maps corresponding to `ProjRestrict` and `ProjRestricts`
respectively.
### Main result
* We prove that `πs` and `πs'` interact well with `Products.eval` and the main application is the
theorem `isGood_mono` which says that the property `isGood` is "monotone" on ordinals.
-/
theorem contained_eq_proj (o : Ordinal) (h : contained C o) :
C = π C (ord I · < o) := by
have := proj_prop_eq_self C (ord I · < o)
simp [π, Bool.not_eq_false] at this
exact (this (fun i x hx ↦ h x hx i)).symm
theorem isClosed_proj (o : Ordinal) (hC : IsClosed C) : IsClosed (π C (ord I · < o)) :=
(continuous_proj (ord I · < o)).isClosedMap C hC
theorem contained_proj (o : Ordinal) : contained (π C (ord I · < o)) o := by
intro x ⟨_, _, h⟩ j hj
aesop (add simp Proj)
/-- The `ℤ`-linear map induced by precomposition of the projection `C → π C (ord I · < o)`. -/
@[simps!]
noncomputable
def πs (o : Ordinal) : LocallyConstant (π C (ord I · < o)) ℤ →ₗ[ℤ] LocallyConstant C ℤ :=
LocallyConstant.comapₗ ℤ ⟨(ProjRestrict C (ord I · < o)), (continuous_projRestrict _ _)⟩
theorem coe_πs (o : Ordinal) (f : LocallyConstant (π C (ord I · < o)) ℤ) :
πs C o f = f ∘ ProjRestrict C (ord I · < o) := by
rfl
theorem injective_πs (o : Ordinal) : Function.Injective (πs C o) :=
LocallyConstant.comap_injective ⟨_, (continuous_projRestrict _ _)⟩
(Set.surjective_mapsTo_image_restrict _ _)
/-- The `ℤ`-linear map induced by precomposition of the projection
`π C (ord I · < o₂) → π C (ord I · < o₁)` for `o₁ ≤ o₂`. -/
@[simps!]
noncomputable
def πs' {o₁ o₂ : Ordinal} (h : o₁ ≤ o₂) :
LocallyConstant (π C (ord I · < o₁)) ℤ →ₗ[ℤ] LocallyConstant (π C (ord I · < o₂)) ℤ :=
LocallyConstant.comapₗ ℤ ⟨(ProjRestricts C (fun _ hh ↦ lt_of_lt_of_le hh h)),
(continuous_projRestricts _ _)⟩
theorem coe_πs' {o₁ o₂ : Ordinal} (h : o₁ ≤ o₂) (f : LocallyConstant (π C (ord I · < o₁)) ℤ) :
(πs' C h f).toFun = f.toFun ∘ (ProjRestricts C (fun _ hh ↦ lt_of_lt_of_le hh h)) := by
rfl
theorem injective_πs' {o₁ o₂ : Ordinal} (h : o₁ ≤ o₂) : Function.Injective (πs' C h) :=
LocallyConstant.comap_injective ⟨_, (continuous_projRestricts _ _)⟩
(surjective_projRestricts _ fun _ hi ↦ lt_of_lt_of_le hi h)
namespace Products
theorem lt_ord_of_lt {l m : Products I} {o : Ordinal} (h₁ : m < l)
(h₂ : ∀ i ∈ l.val, ord I i < o) : ∀ i ∈ m.val, ord I i < o :=
List.Sorted.lt_ord_of_lt (List.chain'_iff_pairwise.mp l.2) (List.chain'_iff_pairwise.mp m.2) h₁ h₂
theorem eval_πs {l : Products I} {o : Ordinal} (hlt : ∀ i ∈ l.val, ord I i < o) :
πs C o (l.eval (π C (ord I · < o))) = l.eval C := by
simpa only [← LocallyConstant.coe_inj] using evalFacProp C (ord I · < o) hlt
theorem eval_πs' {l : Products I} {o₁ o₂ : Ordinal} (h : o₁ ≤ o₂)
(hlt : ∀ i ∈ l.val, ord I i < o₁) :
πs' C h (l.eval (π C (ord I · < o₁))) = l.eval (π C (ord I · < o₂)) := by
rw [← LocallyConstant.coe_inj, ← LocallyConstant.toFun_eq_coe]
exact evalFacProps C (fun (i : I) ↦ ord I i < o₁) (fun (i : I) ↦ ord I i < o₂) hlt
(fun _ hh ↦ lt_of_lt_of_le hh h)
theorem eval_πs_image {l : Products I} {o : Ordinal}
(hl : ∀ i ∈ l.val, ord I i < o) : eval C '' { m | m < l } =
(πs C o) '' (eval (π C (ord I · < o)) '' { m | m < l }) := by
ext f
simp only [Set.mem_image, Set.mem_setOf_eq, exists_exists_and_eq_and]
apply exists_congr; intro m
apply and_congr_right; intro hm
rw [eval_πs C (lt_ord_of_lt hm hl)]
theorem eval_πs_image' {l : Products I} {o₁ o₂ : Ordinal} (h : o₁ ≤ o₂)
(hl : ∀ i ∈ l.val, ord I i < o₁) : eval (π C (ord I · < o₂)) '' { m | m < l } =
(πs' C h) '' (eval (π C (ord I · < o₁)) '' { m | m < l }) := by
ext f
simp only [Set.mem_image, Set.mem_setOf_eq, exists_exists_and_eq_and]
apply exists_congr; intro m
apply and_congr_right; intro hm
rw [eval_πs' C h (lt_ord_of_lt hm hl)]
theorem head_lt_ord_of_isGood [Inhabited I] {l : Products I} {o : Ordinal}
(h : l.isGood (π C (ord I · < o))) (hn : l.val ≠ []) : ord I (l.val.head!) < o :=
prop_of_isGood C (ord I · < o) h l.val.head! (List.head!_mem_self hn)
/--
If `l` is good w.r.t. `π C (ord I · < o₁)` and `o₁ ≤ o₂`, then it is good w.r.t.
`π C (ord I · < o₂)`
-/
| Mathlib/Topology/Category/Profinite/Nobeling.lean | 940 | 945 | theorem isGood_mono {l : Products I} {o₁ o₂ : Ordinal} (h : o₁ ≤ o₂)
(hl : l.isGood (π C (ord I · < o₁))) : l.isGood (π C (ord I · < o₂)) := by |
intro hl'
apply hl
rwa [eval_πs_image' C h (prop_of_isGood C _ hl), ← eval_πs' C h (prop_of_isGood C _ hl),
Submodule.apply_mem_span_image_iff_mem_span (injective_πs' C h)] at hl'
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro
-/
import Mathlib.Topology.Constructions
import Mathlib.Topology.ContinuousOn
#align_import topology.bases from "leanprover-community/mathlib"@"bcfa726826abd57587355b4b5b7e78ad6527b7e4"
/-!
# Bases of topologies. Countability axioms.
A topological basis on a topological space `t` is a collection of sets,
such that all open sets can be generated as unions of these sets, without the need to take
finite intersections of them. This file introduces a framework for dealing with these collections,
and also what more we can say under certain countability conditions on bases,
which are referred to as first- and second-countable.
We also briefly cover the theory of separable spaces, which are those with a countable, dense
subset. If a space is second-countable, and also has a countably generated uniformity filter
(for example, if `t` is a metric space), it will automatically be separable (and indeed, these
conditions are equivalent in this case).
## Main definitions
* `TopologicalSpace.IsTopologicalBasis s`: The topological space `t` has basis `s`.
* `TopologicalSpace.SeparableSpace α`: The topological space `t` has a countable, dense subset.
* `TopologicalSpace.IsSeparable s`: The set `s` is contained in the closure of a countable set.
* `FirstCountableTopology α`: A topology in which `𝓝 x` is countably generated for
every `x`.
* `SecondCountableTopology α`: A topology which has a topological basis which is
countable.
## Main results
* `TopologicalSpace.FirstCountableTopology.tendsto_subseq`: In a first-countable space,
cluster points are limits of subsequences.
* `TopologicalSpace.SecondCountableTopology.isOpen_iUnion_countable`: In a second-countable space,
the union of arbitrarily-many open sets is equal to a sub-union of only countably many of these
sets.
* `TopologicalSpace.SecondCountableTopology.countable_cover_nhds`: Consider `f : α → Set α` with the
property that `f x ∈ 𝓝 x` for all `x`. Then there is some countable set `s` whose image covers
the space.
## Implementation Notes
For our applications we are interested that there exists a countable basis, but we do not need the
concrete basis itself. This allows us to declare these type classes as `Prop` to use them as mixins.
### TODO:
More fine grained instances for `FirstCountableTopology`,
`TopologicalSpace.SeparableSpace`, and more.
-/
open Set Filter Function Topology
noncomputable section
namespace TopologicalSpace
universe u
variable {α : Type u} {β : Type*} [t : TopologicalSpace α] {B : Set (Set α)} {s : Set α}
/-- A topological basis is one that satisfies the necessary conditions so that
it suffices to take unions of the basis sets to get a topology (without taking
finite intersections as well). -/
structure IsTopologicalBasis (s : Set (Set α)) : Prop where
/-- For every point `x`, the set of `t ∈ s` such that `x ∈ t` is directed downwards. -/
exists_subset_inter : ∀ t₁ ∈ s, ∀ t₂ ∈ s, ∀ x ∈ t₁ ∩ t₂, ∃ t₃ ∈ s, x ∈ t₃ ∧ t₃ ⊆ t₁ ∩ t₂
/-- The sets from `s` cover the whole space. -/
sUnion_eq : ⋃₀ s = univ
/-- The topology is generated by sets from `s`. -/
eq_generateFrom : t = generateFrom s
#align topological_space.is_topological_basis TopologicalSpace.IsTopologicalBasis
theorem IsTopologicalBasis.insert_empty {s : Set (Set α)} (h : IsTopologicalBasis s) :
IsTopologicalBasis (insert ∅ s) := by
refine ⟨?_, by rw [sUnion_insert, empty_union, h.sUnion_eq], ?_⟩
· rintro t₁ (rfl | h₁) t₂ (rfl | h₂) x ⟨hx₁, hx₂⟩
· cases hx₁
· cases hx₁
· cases hx₂
· obtain ⟨t₃, h₃, hs⟩ := h.exists_subset_inter _ h₁ _ h₂ x ⟨hx₁, hx₂⟩
exact ⟨t₃, .inr h₃, hs⟩
· rw [h.eq_generateFrom]
refine le_antisymm (le_generateFrom fun t => ?_) (generateFrom_anti <| subset_insert ∅ s)
rintro (rfl | ht)
· exact @isOpen_empty _ (generateFrom s)
· exact .basic t ht
#align topological_space.is_topological_basis.insert_empty TopologicalSpace.IsTopologicalBasis.insert_empty
theorem IsTopologicalBasis.diff_empty {s : Set (Set α)} (h : IsTopologicalBasis s) :
IsTopologicalBasis (s \ {∅}) := by
refine ⟨?_, by rw [sUnion_diff_singleton_empty, h.sUnion_eq], ?_⟩
· rintro t₁ ⟨h₁, -⟩ t₂ ⟨h₂, -⟩ x hx
obtain ⟨t₃, h₃, hs⟩ := h.exists_subset_inter _ h₁ _ h₂ x hx
exact ⟨t₃, ⟨h₃, Nonempty.ne_empty ⟨x, hs.1⟩⟩, hs⟩
· rw [h.eq_generateFrom]
refine le_antisymm (generateFrom_anti diff_subset) (le_generateFrom fun t ht => ?_)
obtain rfl | he := eq_or_ne t ∅
· exact @isOpen_empty _ (generateFrom _)
· exact .basic t ⟨ht, he⟩
#align topological_space.is_topological_basis.diff_empty TopologicalSpace.IsTopologicalBasis.diff_empty
/-- If a family of sets `s` generates the topology, then intersections of finite
subcollections of `s` form a topological basis. -/
theorem isTopologicalBasis_of_subbasis {s : Set (Set α)} (hs : t = generateFrom s) :
IsTopologicalBasis ((fun f => ⋂₀ f) '' { f : Set (Set α) | f.Finite ∧ f ⊆ s }) := by
subst t; letI := generateFrom s
refine ⟨?_, ?_, le_antisymm (le_generateFrom ?_) <| generateFrom_anti fun t ht => ?_⟩
· rintro _ ⟨t₁, ⟨hft₁, ht₁b⟩, rfl⟩ _ ⟨t₂, ⟨hft₂, ht₂b⟩, rfl⟩ x h
exact ⟨_, ⟨_, ⟨hft₁.union hft₂, union_subset ht₁b ht₂b⟩, sInter_union t₁ t₂⟩, h, Subset.rfl⟩
· rw [sUnion_image, iUnion₂_eq_univ_iff]
exact fun x => ⟨∅, ⟨finite_empty, empty_subset _⟩, sInter_empty.substr <| mem_univ x⟩
· rintro _ ⟨t, ⟨hft, htb⟩, rfl⟩
exact hft.isOpen_sInter fun s hs ↦ GenerateOpen.basic _ <| htb hs
· rw [← sInter_singleton t]
exact ⟨{t}, ⟨finite_singleton t, singleton_subset_iff.2 ht⟩, rfl⟩
#align topological_space.is_topological_basis_of_subbasis TopologicalSpace.isTopologicalBasis_of_subbasis
theorem IsTopologicalBasis.of_hasBasis_nhds {s : Set (Set α)}
(h_nhds : ∀ a, (𝓝 a).HasBasis (fun t ↦ t ∈ s ∧ a ∈ t) id) : IsTopologicalBasis s where
exists_subset_inter t₁ ht₁ t₂ ht₂ x hx := by
simpa only [and_assoc, (h_nhds x).mem_iff]
using (inter_mem ((h_nhds _).mem_of_mem ⟨ht₁, hx.1⟩) ((h_nhds _).mem_of_mem ⟨ht₂, hx.2⟩))
sUnion_eq := sUnion_eq_univ_iff.2 fun x ↦ (h_nhds x).ex_mem
eq_generateFrom := ext_nhds fun x ↦ by
simpa only [nhds_generateFrom, and_comm] using (h_nhds x).eq_biInf
/-- If a family of open sets `s` is such that every open neighbourhood contains some
member of `s`, then `s` is a topological basis. -/
theorem isTopologicalBasis_of_isOpen_of_nhds {s : Set (Set α)} (h_open : ∀ u ∈ s, IsOpen u)
(h_nhds : ∀ (a : α) (u : Set α), a ∈ u → IsOpen u → ∃ v ∈ s, a ∈ v ∧ v ⊆ u) :
IsTopologicalBasis s :=
.of_hasBasis_nhds <| fun a ↦
(nhds_basis_opens a).to_hasBasis' (by simpa [and_assoc] using h_nhds a)
fun t ⟨hts, hat⟩ ↦ (h_open _ hts).mem_nhds hat
#align topological_space.is_topological_basis_of_open_of_nhds TopologicalSpace.isTopologicalBasis_of_isOpen_of_nhds
/-- A set `s` is in the neighbourhood of `a` iff there is some basis set `t`, which
contains `a` and is itself contained in `s`. -/
theorem IsTopologicalBasis.mem_nhds_iff {a : α} {s : Set α} {b : Set (Set α)}
(hb : IsTopologicalBasis b) : s ∈ 𝓝 a ↔ ∃ t ∈ b, a ∈ t ∧ t ⊆ s := by
change s ∈ (𝓝 a).sets ↔ ∃ t ∈ b, a ∈ t ∧ t ⊆ s
rw [hb.eq_generateFrom, nhds_generateFrom, biInf_sets_eq]
· simp [and_assoc, and_left_comm]
· rintro s ⟨hs₁, hs₂⟩ t ⟨ht₁, ht₂⟩
let ⟨u, hu₁, hu₂, hu₃⟩ := hb.1 _ hs₂ _ ht₂ _ ⟨hs₁, ht₁⟩
exact ⟨u, ⟨hu₂, hu₁⟩, le_principal_iff.2 (hu₃.trans inter_subset_left),
le_principal_iff.2 (hu₃.trans inter_subset_right)⟩
· rcases eq_univ_iff_forall.1 hb.sUnion_eq a with ⟨i, h1, h2⟩
exact ⟨i, h2, h1⟩
#align topological_space.is_topological_basis.mem_nhds_iff TopologicalSpace.IsTopologicalBasis.mem_nhds_iff
theorem IsTopologicalBasis.isOpen_iff {s : Set α} {b : Set (Set α)} (hb : IsTopologicalBasis b) :
IsOpen s ↔ ∀ a ∈ s, ∃ t ∈ b, a ∈ t ∧ t ⊆ s := by simp [isOpen_iff_mem_nhds, hb.mem_nhds_iff]
#align topological_space.is_topological_basis.is_open_iff TopologicalSpace.IsTopologicalBasis.isOpen_iff
theorem IsTopologicalBasis.nhds_hasBasis {b : Set (Set α)} (hb : IsTopologicalBasis b) {a : α} :
(𝓝 a).HasBasis (fun t : Set α => t ∈ b ∧ a ∈ t) fun t => t :=
⟨fun s => hb.mem_nhds_iff.trans <| by simp only [and_assoc]⟩
#align topological_space.is_topological_basis.nhds_has_basis TopologicalSpace.IsTopologicalBasis.nhds_hasBasis
protected theorem IsTopologicalBasis.isOpen {s : Set α} {b : Set (Set α)}
(hb : IsTopologicalBasis b) (hs : s ∈ b) : IsOpen s := by
rw [hb.eq_generateFrom]
exact .basic s hs
#align topological_space.is_topological_basis.is_open TopologicalSpace.IsTopologicalBasis.isOpen
protected theorem IsTopologicalBasis.mem_nhds {a : α} {s : Set α} {b : Set (Set α)}
(hb : IsTopologicalBasis b) (hs : s ∈ b) (ha : a ∈ s) : s ∈ 𝓝 a :=
(hb.isOpen hs).mem_nhds ha
#align topological_space.is_topological_basis.mem_nhds TopologicalSpace.IsTopologicalBasis.mem_nhds
theorem IsTopologicalBasis.exists_subset_of_mem_open {b : Set (Set α)} (hb : IsTopologicalBasis b)
{a : α} {u : Set α} (au : a ∈ u) (ou : IsOpen u) : ∃ v ∈ b, a ∈ v ∧ v ⊆ u :=
hb.mem_nhds_iff.1 <| IsOpen.mem_nhds ou au
#align topological_space.is_topological_basis.exists_subset_of_mem_open TopologicalSpace.IsTopologicalBasis.exists_subset_of_mem_open
/-- Any open set is the union of the basis sets contained in it. -/
theorem IsTopologicalBasis.open_eq_sUnion' {B : Set (Set α)} (hB : IsTopologicalBasis B) {u : Set α}
(ou : IsOpen u) : u = ⋃₀ { s ∈ B | s ⊆ u } :=
ext fun _a =>
⟨fun ha =>
let ⟨b, hb, ab, bu⟩ := hB.exists_subset_of_mem_open ha ou
⟨b, ⟨hb, bu⟩, ab⟩,
fun ⟨_b, ⟨_, bu⟩, ab⟩ => bu ab⟩
#align topological_space.is_topological_basis.open_eq_sUnion' TopologicalSpace.IsTopologicalBasis.open_eq_sUnion'
theorem IsTopologicalBasis.open_eq_sUnion {B : Set (Set α)} (hB : IsTopologicalBasis B) {u : Set α}
(ou : IsOpen u) : ∃ S ⊆ B, u = ⋃₀ S :=
⟨{ s ∈ B | s ⊆ u }, fun _ h => h.1, hB.open_eq_sUnion' ou⟩
#align topological_space.is_topological_basis.open_eq_sUnion TopologicalSpace.IsTopologicalBasis.open_eq_sUnion
theorem IsTopologicalBasis.open_iff_eq_sUnion {B : Set (Set α)} (hB : IsTopologicalBasis B)
{u : Set α} : IsOpen u ↔ ∃ S ⊆ B, u = ⋃₀ S :=
⟨hB.open_eq_sUnion, fun ⟨_S, hSB, hu⟩ => hu.symm ▸ isOpen_sUnion fun _s hs => hB.isOpen (hSB hs)⟩
#align topological_space.is_topological_basis.open_iff_eq_sUnion TopologicalSpace.IsTopologicalBasis.open_iff_eq_sUnion
theorem IsTopologicalBasis.open_eq_iUnion {B : Set (Set α)} (hB : IsTopologicalBasis B) {u : Set α}
(ou : IsOpen u) : ∃ (β : Type u) (f : β → Set α), (u = ⋃ i, f i) ∧ ∀ i, f i ∈ B :=
⟨↥({ s ∈ B | s ⊆ u }), (↑), by
rw [← sUnion_eq_iUnion]
apply hB.open_eq_sUnion' ou, fun s => And.left s.2⟩
#align topological_space.is_topological_basis.open_eq_Union TopologicalSpace.IsTopologicalBasis.open_eq_iUnion
lemma IsTopologicalBasis.subset_of_forall_subset {t : Set α} (hB : IsTopologicalBasis B)
(hs : IsOpen s) (h : ∀ U ∈ B, U ⊆ s → U ⊆ t) : s ⊆ t := by
rw [hB.open_eq_sUnion' hs]; simpa [sUnion_subset_iff]
lemma IsTopologicalBasis.eq_of_forall_subset_iff {t : Set α} (hB : IsTopologicalBasis B)
(hs : IsOpen s) (ht : IsOpen t) (h : ∀ U ∈ B, U ⊆ s ↔ U ⊆ t) : s = t := by
rw [hB.open_eq_sUnion' hs, hB.open_eq_sUnion' ht]
exact congr_arg _ (Set.ext fun U ↦ and_congr_right <| h _)
/-- A point `a` is in the closure of `s` iff all basis sets containing `a` intersect `s`. -/
theorem IsTopologicalBasis.mem_closure_iff {b : Set (Set α)} (hb : IsTopologicalBasis b) {s : Set α}
{a : α} : a ∈ closure s ↔ ∀ o ∈ b, a ∈ o → (o ∩ s).Nonempty :=
(mem_closure_iff_nhds_basis' hb.nhds_hasBasis).trans <| by simp only [and_imp]
#align topological_space.is_topological_basis.mem_closure_iff TopologicalSpace.IsTopologicalBasis.mem_closure_iff
/-- A set is dense iff it has non-trivial intersection with all basis sets. -/
theorem IsTopologicalBasis.dense_iff {b : Set (Set α)} (hb : IsTopologicalBasis b) {s : Set α} :
Dense s ↔ ∀ o ∈ b, Set.Nonempty o → (o ∩ s).Nonempty := by
simp only [Dense, hb.mem_closure_iff]
exact ⟨fun h o hb ⟨a, ha⟩ => h a o hb ha, fun h a o hb ha => h o hb ⟨a, ha⟩⟩
#align topological_space.is_topological_basis.dense_iff TopologicalSpace.IsTopologicalBasis.dense_iff
theorem IsTopologicalBasis.isOpenMap_iff {β} [TopologicalSpace β] {B : Set (Set α)}
(hB : IsTopologicalBasis B) {f : α → β} : IsOpenMap f ↔ ∀ s ∈ B, IsOpen (f '' s) := by
refine ⟨fun H o ho => H _ (hB.isOpen ho), fun hf o ho => ?_⟩
rw [hB.open_eq_sUnion' ho, sUnion_eq_iUnion, image_iUnion]
exact isOpen_iUnion fun s => hf s s.2.1
#align topological_space.is_topological_basis.is_open_map_iff TopologicalSpace.IsTopologicalBasis.isOpenMap_iff
theorem IsTopologicalBasis.exists_nonempty_subset {B : Set (Set α)} (hb : IsTopologicalBasis B)
{u : Set α} (hu : u.Nonempty) (ou : IsOpen u) : ∃ v ∈ B, Set.Nonempty v ∧ v ⊆ u :=
let ⟨x, hx⟩ := hu
let ⟨v, vB, xv, vu⟩ := hb.exists_subset_of_mem_open hx ou
⟨v, vB, ⟨x, xv⟩, vu⟩
#align topological_space.is_topological_basis.exists_nonempty_subset TopologicalSpace.IsTopologicalBasis.exists_nonempty_subset
theorem isTopologicalBasis_opens : IsTopologicalBasis { U : Set α | IsOpen U } :=
isTopologicalBasis_of_isOpen_of_nhds (by tauto) (by tauto)
#align topological_space.is_topological_basis_opens TopologicalSpace.isTopologicalBasis_opens
protected theorem IsTopologicalBasis.inducing {β} [TopologicalSpace β] {f : α → β} {T : Set (Set β)}
(hf : Inducing f) (h : IsTopologicalBasis T) : IsTopologicalBasis ((preimage f) '' T) :=
.of_hasBasis_nhds fun a ↦ by
convert (hf.basis_nhds (h.nhds_hasBasis (a := f a))).to_image_id with s
aesop
#align topological_space.is_topological_basis.inducing TopologicalSpace.IsTopologicalBasis.inducing
protected theorem IsTopologicalBasis.induced [s : TopologicalSpace β] (f : α → β)
{T : Set (Set β)} (h : IsTopologicalBasis T) :
IsTopologicalBasis (t := induced f s) ((preimage f) '' T) :=
h.inducing (t := induced f s) (inducing_induced f)
protected theorem IsTopologicalBasis.inf {t₁ t₂ : TopologicalSpace β} {B₁ B₂ : Set (Set β)}
(h₁ : IsTopologicalBasis (t := t₁) B₁) (h₂ : IsTopologicalBasis (t := t₂) B₂) :
IsTopologicalBasis (t := t₁ ⊓ t₂) (image2 (· ∩ ·) B₁ B₂) := by
refine .of_hasBasis_nhds (t := ?_) fun a ↦ ?_
rw [nhds_inf (t₁ := t₁)]
convert ((h₁.nhds_hasBasis (t := t₁)).inf (h₂.nhds_hasBasis (t := t₂))).to_image_id
aesop
theorem IsTopologicalBasis.inf_induced {γ} [s : TopologicalSpace β] {B₁ : Set (Set α)}
{B₂ : Set (Set β)} (h₁ : IsTopologicalBasis B₁) (h₂ : IsTopologicalBasis B₂) (f₁ : γ → α)
(f₂ : γ → β) :
IsTopologicalBasis (t := induced f₁ t ⊓ induced f₂ s) (image2 (f₁ ⁻¹' · ∩ f₂ ⁻¹' ·) B₁ B₂) := by
simpa only [image2_image_left, image2_image_right] using (h₁.induced f₁).inf (h₂.induced f₂)
protected theorem IsTopologicalBasis.prod {β} [TopologicalSpace β] {B₁ : Set (Set α)}
{B₂ : Set (Set β)} (h₁ : IsTopologicalBasis B₁) (h₂ : IsTopologicalBasis B₂) :
IsTopologicalBasis (image2 (· ×ˢ ·) B₁ B₂) :=
h₁.inf_induced h₂ Prod.fst Prod.snd
#align topological_space.is_topological_basis.prod TopologicalSpace.IsTopologicalBasis.prod
theorem isTopologicalBasis_of_cover {ι} {U : ι → Set α} (Uo : ∀ i, IsOpen (U i))
(Uc : ⋃ i, U i = univ) {b : ∀ i, Set (Set (U i))} (hb : ∀ i, IsTopologicalBasis (b i)) :
IsTopologicalBasis (⋃ i : ι, image ((↑) : U i → α) '' b i) := by
refine isTopologicalBasis_of_isOpen_of_nhds (fun u hu => ?_) ?_
· simp only [mem_iUnion, mem_image] at hu
rcases hu with ⟨i, s, sb, rfl⟩
exact (Uo i).isOpenMap_subtype_val _ ((hb i).isOpen sb)
· intro a u ha uo
rcases iUnion_eq_univ_iff.1 Uc a with ⟨i, hi⟩
lift a to ↥(U i) using hi
rcases (hb i).exists_subset_of_mem_open ha (uo.preimage continuous_subtype_val) with
⟨v, hvb, hav, hvu⟩
exact ⟨(↑) '' v, mem_iUnion.2 ⟨i, mem_image_of_mem _ hvb⟩, mem_image_of_mem _ hav,
image_subset_iff.2 hvu⟩
#align topological_space.is_topological_basis_of_cover TopologicalSpace.isTopologicalBasis_of_cover
protected theorem IsTopologicalBasis.continuous_iff {β : Type*} [TopologicalSpace β]
{B : Set (Set β)} (hB : IsTopologicalBasis B) {f : α → β} :
Continuous f ↔ ∀ s ∈ B, IsOpen (f ⁻¹' s) := by
rw [hB.eq_generateFrom, continuous_generateFrom_iff]
@[deprecated]
protected theorem IsTopologicalBasis.continuous {β : Type*} [TopologicalSpace β] {B : Set (Set β)}
(hB : IsTopologicalBasis B) (f : α → β) (hf : ∀ s ∈ B, IsOpen (f ⁻¹' s)) : Continuous f :=
hB.continuous_iff.2 hf
#align topological_space.is_topological_basis.continuous TopologicalSpace.IsTopologicalBasis.continuous
variable (α)
/-- A separable space is one with a countable dense subset, available through
`TopologicalSpace.exists_countable_dense`. If `α` is also known to be nonempty, then
`TopologicalSpace.denseSeq` provides a sequence `ℕ → α` with dense range, see
`TopologicalSpace.denseRange_denseSeq`.
If `α` is a uniform space with countably generated uniformity filter (e.g., an `EMetricSpace`), then
this condition is equivalent to `SecondCountableTopology α`. In this case the
latter should be used as a typeclass argument in theorems because Lean can automatically deduce
`TopologicalSpace.SeparableSpace` from `SecondCountableTopology` but it can't
deduce `SecondCountableTopology` from `TopologicalSpace.SeparableSpace`.
Porting note (#11215): TODO: the previous paragraph describes the state of the art in Lean 3.
We can have instance cycles in Lean 4 but we might want to
postpone adding them till after the port. -/
@[mk_iff] class SeparableSpace : Prop where
/-- There exists a countable dense set. -/
exists_countable_dense : ∃ s : Set α, s.Countable ∧ Dense s
#align topological_space.separable_space TopologicalSpace.SeparableSpace
theorem exists_countable_dense [SeparableSpace α] : ∃ s : Set α, s.Countable ∧ Dense s :=
SeparableSpace.exists_countable_dense
#align topological_space.exists_countable_dense TopologicalSpace.exists_countable_dense
/-- A nonempty separable space admits a sequence with dense range. Instead of running `cases` on the
conclusion of this lemma, you might want to use `TopologicalSpace.denseSeq` and
`TopologicalSpace.denseRange_denseSeq`.
If `α` might be empty, then `TopologicalSpace.exists_countable_dense` is the main way to use
separability of `α`. -/
theorem exists_dense_seq [SeparableSpace α] [Nonempty α] : ∃ u : ℕ → α, DenseRange u := by
obtain ⟨s : Set α, hs, s_dense⟩ := exists_countable_dense α
cases' Set.countable_iff_exists_subset_range.mp hs with u hu
exact ⟨u, s_dense.mono hu⟩
#align topological_space.exists_dense_seq TopologicalSpace.exists_dense_seq
/-- A dense sequence in a non-empty separable topological space.
If `α` might be empty, then `TopologicalSpace.exists_countable_dense` is the main way to use
separability of `α`. -/
def denseSeq [SeparableSpace α] [Nonempty α] : ℕ → α :=
Classical.choose (exists_dense_seq α)
#align topological_space.dense_seq TopologicalSpace.denseSeq
/-- The sequence `TopologicalSpace.denseSeq α` has dense range. -/
@[simp]
theorem denseRange_denseSeq [SeparableSpace α] [Nonempty α] : DenseRange (denseSeq α) :=
Classical.choose_spec (exists_dense_seq α)
#align topological_space.dense_range_dense_seq TopologicalSpace.denseRange_denseSeq
variable {α}
instance (priority := 100) Countable.to_separableSpace [Countable α] : SeparableSpace α where
exists_countable_dense := ⟨Set.univ, Set.countable_univ, dense_univ⟩
#align topological_space.countable.to_separable_space TopologicalSpace.Countable.to_separableSpace
/-- If `f` has a dense range and its domain is countable, then its codomain is a separable space.
See also `DenseRange.separableSpace`. -/
theorem SeparableSpace.of_denseRange {ι : Sort _} [Countable ι] (u : ι → α) (hu : DenseRange u) :
SeparableSpace α :=
⟨⟨range u, countable_range u, hu⟩⟩
#align topological_space.separable_space_of_dense_range TopologicalSpace.SeparableSpace.of_denseRange
alias _root_.DenseRange.separableSpace' := SeparableSpace.of_denseRange
/-- If `α` is a separable space and `f : α → β` is a continuous map with dense range, then `β` is
a separable space as well. E.g., the completion of a separable uniform space is separable. -/
protected theorem _root_.DenseRange.separableSpace [SeparableSpace α] [TopologicalSpace β]
{f : α → β} (h : DenseRange f) (h' : Continuous f) : SeparableSpace β :=
let ⟨s, s_cnt, s_dense⟩ := exists_countable_dense α
⟨⟨f '' s, Countable.image s_cnt f, h.dense_image h' s_dense⟩⟩
#align dense_range.separable_space DenseRange.separableSpace
theorem _root_.QuotientMap.separableSpace [SeparableSpace α] [TopologicalSpace β] {f : α → β}
(hf : QuotientMap f) : SeparableSpace β :=
hf.surjective.denseRange.separableSpace hf.continuous
/-- The product of two separable spaces is a separable space. -/
instance [TopologicalSpace β] [SeparableSpace α] [SeparableSpace β] : SeparableSpace (α × β) := by
rcases exists_countable_dense α with ⟨s, hsc, hsd⟩
rcases exists_countable_dense β with ⟨t, htc, htd⟩
exact ⟨⟨s ×ˢ t, hsc.prod htc, hsd.prod htd⟩⟩
/-- The product of a countable family of separable spaces is a separable space. -/
instance {ι : Type*} {X : ι → Type*} [∀ i, TopologicalSpace (X i)] [∀ i, SeparableSpace (X i)]
[Countable ι] : SeparableSpace (∀ i, X i) := by
choose t htc htd using (exists_countable_dense <| X ·)
haveI := fun i ↦ (htc i).to_subtype
nontriviality ∀ i, X i; inhabit ∀ i, X i
classical
set f : (Σ I : Finset ι, ∀ i : I, t i) → ∀ i, X i := fun ⟨I, g⟩ i ↦
if hi : i ∈ I then g ⟨i, hi⟩ else (default : ∀ i, X i) i
refine ⟨⟨range f, countable_range f, dense_iff_inter_open.2 fun U hU ⟨g, hg⟩ ↦ ?_⟩⟩
rcases isOpen_pi_iff.1 hU g hg with ⟨I, u, huo, huU⟩
have : ∀ i : I, ∃ y ∈ t i, y ∈ u i := fun i ↦
(htd i).exists_mem_open (huo i i.2).1 ⟨_, (huo i i.2).2⟩
choose y hyt hyu using this
lift y to ∀ i : I, t i using hyt
refine ⟨f ⟨I, y⟩, huU fun i (hi : i ∈ I) ↦ ?_, mem_range_self _⟩
simp only [f, dif_pos hi]
exact hyu _
instance [SeparableSpace α] {r : α → α → Prop} : SeparableSpace (Quot r) :=
quotientMap_quot_mk.separableSpace
instance [SeparableSpace α] {s : Setoid α} : SeparableSpace (Quotient s) :=
quotientMap_quot_mk.separableSpace
/-- A topological space with discrete topology is separable iff it is countable. -/
theorem separableSpace_iff_countable [DiscreteTopology α] : SeparableSpace α ↔ Countable α := by
simp [separableSpace_iff, countable_univ_iff]
/-- In a separable space, a family of nonempty disjoint open sets is countable. -/
theorem _root_.Pairwise.countable_of_isOpen_disjoint [SeparableSpace α] {ι : Type*}
{s : ι → Set α} (hd : Pairwise (Disjoint on s)) (ho : ∀ i, IsOpen (s i))
(hne : ∀ i, (s i).Nonempty) : Countable ι := by
rcases exists_countable_dense α with ⟨u, u_countable, u_dense⟩
choose f hfu hfs using fun i ↦ u_dense.exists_mem_open (ho i) (hne i)
have f_inj : Injective f := fun i j hij ↦
hd.eq <| not_disjoint_iff.2 ⟨f i, hfs i, hij.symm ▸ hfs j⟩
have := u_countable.to_subtype
exact (f_inj.codRestrict hfu).countable
/-- In a separable space, a family of nonempty disjoint open sets is countable. -/
theorem _root_.Set.PairwiseDisjoint.countable_of_isOpen [SeparableSpace α] {ι : Type*}
{s : ι → Set α} {a : Set ι} (h : a.PairwiseDisjoint s) (ho : ∀ i ∈ a, IsOpen (s i))
(hne : ∀ i ∈ a, (s i).Nonempty) : a.Countable :=
(h.subtype _ _).countable_of_isOpen_disjoint (Subtype.forall.2 ho) (Subtype.forall.2 hne)
#align set.pairwise_disjoint.countable_of_is_open Set.PairwiseDisjoint.countable_of_isOpen
/-- In a separable space, a family of disjoint sets with nonempty interiors is countable. -/
theorem _root_.Set.PairwiseDisjoint.countable_of_nonempty_interior [SeparableSpace α] {ι : Type*}
{s : ι → Set α} {a : Set ι} (h : a.PairwiseDisjoint s)
(ha : ∀ i ∈ a, (interior (s i)).Nonempty) : a.Countable :=
(h.mono fun _ => interior_subset).countable_of_isOpen (fun _ _ => isOpen_interior) ha
#align set.pairwise_disjoint.countable_of_nonempty_interior Set.PairwiseDisjoint.countable_of_nonempty_interior
/-- A set `s` in a topological space is separable if it is contained in the closure of a countable
set `c`. Beware that this definition does not require that `c` is contained in `s` (to express the
latter, use `TopologicalSpace.SeparableSpace s` or
`TopologicalSpace.IsSeparable (univ : Set s))`. In metric spaces, the two definitions are
equivalent, see `TopologicalSpace.IsSeparable.separableSpace`. -/
def IsSeparable (s : Set α) :=
∃ c : Set α, c.Countable ∧ s ⊆ closure c
#align topological_space.is_separable TopologicalSpace.IsSeparable
theorem IsSeparable.mono {s u : Set α} (hs : IsSeparable s) (hu : u ⊆ s) : IsSeparable u := by
rcases hs with ⟨c, c_count, hs⟩
exact ⟨c, c_count, hu.trans hs⟩
#align topological_space.is_separable.mono TopologicalSpace.IsSeparable.mono
theorem IsSeparable.iUnion {ι : Sort*} [Countable ι] {s : ι → Set α}
(hs : ∀ i, IsSeparable (s i)) : IsSeparable (⋃ i, s i) := by
choose c hc h'c using hs
refine ⟨⋃ i, c i, countable_iUnion hc, iUnion_subset_iff.2 fun i => ?_⟩
exact (h'c i).trans (closure_mono (subset_iUnion _ i))
#align topological_space.is_separable_Union TopologicalSpace.IsSeparable.iUnion
@[simp]
theorem isSeparable_iUnion {ι : Sort*} [Countable ι] {s : ι → Set α} :
IsSeparable (⋃ i, s i) ↔ ∀ i, IsSeparable (s i) :=
⟨fun h i ↦ h.mono <| subset_iUnion s i, .iUnion⟩
@[simp]
theorem isSeparable_union {s t : Set α} : IsSeparable (s ∪ t) ↔ IsSeparable s ∧ IsSeparable t := by
simp [union_eq_iUnion, and_comm]
theorem IsSeparable.union {s u : Set α} (hs : IsSeparable s) (hu : IsSeparable u) :
IsSeparable (s ∪ u) :=
isSeparable_union.2 ⟨hs, hu⟩
#align topological_space.is_separable.union TopologicalSpace.IsSeparable.union
@[simp]
theorem isSeparable_closure : IsSeparable (closure s) ↔ IsSeparable s := by
simp only [IsSeparable, isClosed_closure.closure_subset_iff]
protected alias ⟨_, IsSeparable.closure⟩ := isSeparable_closure
#align topological_space.is_separable.closure TopologicalSpace.IsSeparable.closure
theorem _root_.Set.Countable.isSeparable {s : Set α} (hs : s.Countable) : IsSeparable s :=
⟨s, hs, subset_closure⟩
#align set.countable.is_separable Set.Countable.isSeparable
theorem _root_.Set.Finite.isSeparable {s : Set α} (hs : s.Finite) : IsSeparable s :=
hs.countable.isSeparable
#align set.finite.is_separable Set.Finite.isSeparable
theorem IsSeparable.univ_pi {ι : Type*} [Countable ι] {X : ι → Type*} {s : ∀ i, Set (X i)}
[∀ i, TopologicalSpace (X i)] (h : ∀ i, IsSeparable (s i)) :
IsSeparable (univ.pi s) := by
classical
rcases eq_empty_or_nonempty (univ.pi s) with he | ⟨f₀, -⟩
· rw [he]
exact countable_empty.isSeparable
· choose c c_count hc using h
haveI := fun i ↦ (c_count i).to_subtype
set g : (I : Finset ι) × ((i : I) → c i) → (i : ι) → X i := fun ⟨I, f⟩ i ↦
if hi : i ∈ I then f ⟨i, hi⟩ else f₀ i
refine ⟨range g, countable_range g, fun f hf ↦ mem_closure_iff.2 fun o ho hfo ↦ ?_⟩
rcases isOpen_pi_iff.1 ho f hfo with ⟨I, u, huo, hI⟩
rsuffices ⟨f, hf⟩ : ∃ f : (i : I) → c i, g ⟨I, f⟩ ∈ Set.pi I u
· exact ⟨g ⟨I, f⟩, hI hf, mem_range_self _⟩
suffices H : ∀ i ∈ I, (u i ∩ c i).Nonempty by
choose f hfu hfc using H
refine ⟨fun i ↦ ⟨f i i.2, hfc i i.2⟩, fun i (hi : i ∈ I) ↦ ?_⟩
simpa only [g, dif_pos hi] using hfu i hi
intro i hi
exact mem_closure_iff.1 (hc i <| hf _ trivial) _ (huo i hi).1 (huo i hi).2
lemma isSeparable_pi {ι : Type*} [Countable ι] {α : ι → Type*} {s : ∀ i, Set (α i)}
[∀ i, TopologicalSpace (α i)] (h : ∀ i, IsSeparable (s i)) :
IsSeparable {f : ∀ i, α i | ∀ i, f i ∈ s i} := by
simpa only [← mem_univ_pi] using IsSeparable.univ_pi h
lemma IsSeparable.prod {β : Type*} [TopologicalSpace β]
{s : Set α} {t : Set β} (hs : IsSeparable s) (ht : IsSeparable t) :
IsSeparable (s ×ˢ t) := by
rcases hs with ⟨cs, cs_count, hcs⟩
rcases ht with ⟨ct, ct_count, hct⟩
refine ⟨cs ×ˢ ct, cs_count.prod ct_count, ?_⟩
rw [closure_prod_eq]
gcongr
theorem IsSeparable.image {β : Type*} [TopologicalSpace β] {s : Set α} (hs : IsSeparable s)
{f : α → β} (hf : Continuous f) : IsSeparable (f '' s) := by
rcases hs with ⟨c, c_count, hc⟩
refine ⟨f '' c, c_count.image _, ?_⟩
rw [image_subset_iff]
exact hc.trans (closure_subset_preimage_closure_image hf)
#align topological_space.is_separable.image TopologicalSpace.IsSeparable.image
theorem _root_.Dense.isSeparable_iff (hs : Dense s) :
IsSeparable s ↔ SeparableSpace α := by
simp_rw [IsSeparable, separableSpace_iff, dense_iff_closure_eq, ← univ_subset_iff,
← hs.closure_eq, isClosed_closure.closure_subset_iff]
theorem isSeparable_univ_iff : IsSeparable (univ : Set α) ↔ SeparableSpace α :=
dense_univ.isSeparable_iff
#align topological_space.is_separable_univ_iff TopologicalSpace.isSeparable_univ_iff
theorem isSeparable_range [TopologicalSpace β] [SeparableSpace α] {f : α → β} (hf : Continuous f) :
IsSeparable (range f) :=
image_univ (f := f) ▸ (isSeparable_univ_iff.2 ‹_›).image hf
theorem IsSeparable.of_subtype (s : Set α) [SeparableSpace s] : IsSeparable s := by
simpa using isSeparable_range (continuous_subtype_val (p := (· ∈ s)))
#align topological_space.is_separable_of_separable_space_subtype TopologicalSpace.IsSeparable.of_subtype
@[deprecated (since := "2024-02-05")]
alias isSeparable_of_separableSpace_subtype := IsSeparable.of_subtype
theorem IsSeparable.of_separableSpace [h : SeparableSpace α] (s : Set α) : IsSeparable s :=
IsSeparable.mono (isSeparable_univ_iff.2 h) (subset_univ _)
#align topological_space.is_separable_of_separable_space TopologicalSpace.IsSeparable.of_separableSpace
@[deprecated (since := "2024-02-05")]
alias isSeparable_of_separableSpace := IsSeparable.of_separableSpace
end TopologicalSpace
open TopologicalSpace
protected theorem IsTopologicalBasis.iInf {β : Type*} {ι : Type*} {t : ι → TopologicalSpace β}
{T : ι → Set (Set β)} (h_basis : ∀ i, IsTopologicalBasis (t := t i) (T i)) :
IsTopologicalBasis (t := ⨅ i, t i)
{ S | ∃ (U : ι → Set β) (F : Finset ι), (∀ i, i ∈ F → U i ∈ T i) ∧ S = ⋂ i ∈ F, U i } := by
let _ := ⨅ i, t i
refine isTopologicalBasis_of_isOpen_of_nhds ?_ ?_
· rintro - ⟨U, F, hU, rfl⟩
refine isOpen_biInter_finset fun i hi ↦
(h_basis i).isOpen (t := t i) (hU i hi) |>.mono (iInf_le _ _)
· intro a u ha hu
rcases (nhds_iInf (t := t) (a := a)).symm ▸ hasBasis_iInf'
(fun i ↦ (h_basis i).nhds_hasBasis (t := t i)) |>.mem_iff.1 (hu.mem_nhds ha)
with ⟨⟨F, U⟩, ⟨hF, hU⟩, hUu⟩
refine ⟨_, ⟨U, hF.toFinset, ?_, rfl⟩, ?_, ?_⟩ <;> simp only [Finite.mem_toFinset, mem_iInter]
· exact fun i hi ↦ (hU i hi).1
· exact fun i hi ↦ (hU i hi).2
· exact hUu
theorem IsTopologicalBasis.iInf_induced {β : Type*} {ι : Type*} {X : ι → Type*}
[t : Π i, TopologicalSpace (X i)] {T : Π i, Set (Set (X i))}
(cond : ∀ i, IsTopologicalBasis (T i)) (f : Π i, β → X i) :
IsTopologicalBasis (t := ⨅ i, induced (f i) (t i))
{ S | ∃ (U : ∀ i, Set (X i)) (F : Finset ι),
(∀ i, i ∈ F → U i ∈ T i) ∧ S = ⋂ (i) (_ : i ∈ F), f i ⁻¹' U i } := by
convert IsTopologicalBasis.iInf (fun i ↦ (cond i).induced (f i)) with S
constructor <;> rintro ⟨U, F, hUT, hSU⟩
· exact ⟨fun i ↦ (f i) ⁻¹' (U i), F, fun i hi ↦ mem_image_of_mem _ (hUT i hi), hSU⟩
· choose! U' hU' hUU' using hUT
exact ⟨U', F, hU', hSU ▸ (.symm <| iInter₂_congr hUU')⟩
#align is_topological_basis_infi IsTopologicalBasis.iInf_induced
theorem isTopologicalBasis_pi {ι : Type*} {X : ι → Type*} [∀ i, TopologicalSpace (X i)]
{T : ∀ i, Set (Set (X i))} (cond : ∀ i, IsTopologicalBasis (T i)) :
IsTopologicalBasis { S | ∃ (U : ∀ i, Set (X i)) (F : Finset ι),
(∀ i, i ∈ F → U i ∈ T i) ∧ S = (F : Set ι).pi U } := by
simpa only [Set.pi_def] using IsTopologicalBasis.iInf_induced cond eval
#align is_topological_basis_pi isTopologicalBasis_pi
theorem isTopologicalBasis_singletons (α : Type*) [TopologicalSpace α] [DiscreteTopology α] :
IsTopologicalBasis { s | ∃ x : α, (s : Set α) = {x} } :=
isTopologicalBasis_of_isOpen_of_nhds (fun _ _ => isOpen_discrete _) fun x _ hx _ =>
⟨{x}, ⟨x, rfl⟩, mem_singleton x, singleton_subset_iff.2 hx⟩
#align is_topological_basis_singletons isTopologicalBasis_singletons
theorem isTopologicalBasis_subtype
{α : Type*} [TopologicalSpace α] {B : Set (Set α)}
(h : TopologicalSpace.IsTopologicalBasis B) (p : α → Prop) :
IsTopologicalBasis (Set.preimage (Subtype.val (p := p)) '' B) :=
h.inducing ⟨rfl⟩
-- Porting note: moved `DenseRange.separableSpace` up
theorem Dense.exists_countable_dense_subset {α : Type*} [TopologicalSpace α] {s : Set α}
[SeparableSpace s] (hs : Dense s) : ∃ t ⊆ s, t.Countable ∧ Dense t :=
let ⟨t, htc, htd⟩ := exists_countable_dense s
⟨(↑) '' t, Subtype.coe_image_subset s t, htc.image Subtype.val,
hs.denseRange_val.dense_image continuous_subtype_val htd⟩
#align dense.exists_countable_dense_subset Dense.exists_countable_dense_subsetₓ
/-- Let `s` be a dense set in a topological space `α` with partial order structure. If `s` is a
separable space (e.g., if `α` has a second countable topology), then there exists a countable
dense subset `t ⊆ s` such that `t` contains bottom/top element of `α` when they exist and belong
to `s`. For a dense subset containing neither bot nor top elements, see
`Dense.exists_countable_dense_subset_no_bot_top`. -/
theorem Dense.exists_countable_dense_subset_bot_top {α : Type*} [TopologicalSpace α]
[PartialOrder α] {s : Set α} [SeparableSpace s] (hs : Dense s) :
∃ t ⊆ s, t.Countable ∧ Dense t ∧ (∀ x, IsBot x → x ∈ s → x ∈ t) ∧
∀ x, IsTop x → x ∈ s → x ∈ t := by
rcases hs.exists_countable_dense_subset with ⟨t, hts, htc, htd⟩
refine ⟨(t ∪ ({ x | IsBot x } ∪ { x | IsTop x })) ∩ s, ?_, ?_, ?_, ?_, ?_⟩
exacts [inter_subset_right,
(htc.union ((countable_isBot α).union (countable_isTop α))).mono inter_subset_left,
htd.mono (subset_inter subset_union_left hts), fun x hx hxs => ⟨Or.inr <| Or.inl hx, hxs⟩,
fun x hx hxs => ⟨Or.inr <| Or.inr hx, hxs⟩]
#align dense.exists_countable_dense_subset_bot_top Dense.exists_countable_dense_subset_bot_top
instance separableSpace_univ {α : Type*} [TopologicalSpace α] [SeparableSpace α] :
SeparableSpace (univ : Set α) :=
(Equiv.Set.univ α).symm.surjective.denseRange.separableSpace (continuous_id.subtype_mk _)
#align separable_space_univ separableSpace_univ
/-- If `α` is a separable topological space with a partial order, then there exists a countable
dense set `s : Set α` that contains those of both bottom and top elements of `α` that actually
exist. For a dense set containing neither bot nor top elements, see
`exists_countable_dense_no_bot_top`. -/
theorem exists_countable_dense_bot_top (α : Type*) [TopologicalSpace α] [SeparableSpace α]
[PartialOrder α] :
∃ s : Set α, s.Countable ∧ Dense s ∧ (∀ x, IsBot x → x ∈ s) ∧ ∀ x, IsTop x → x ∈ s := by
simpa using dense_univ.exists_countable_dense_subset_bot_top
#align exists_countable_dense_bot_top exists_countable_dense_bot_top
namespace TopologicalSpace
universe u
variable (α : Type u) [t : TopologicalSpace α]
/-- A first-countable space is one in which every point has a
countable neighborhood basis. -/
class _root_.FirstCountableTopology : Prop where
/-- The filter `𝓝 a` is countably generated for all points `a`. -/
nhds_generated_countable : ∀ a : α, (𝓝 a).IsCountablyGenerated
#align topological_space.first_countable_topology FirstCountableTopology
attribute [instance] FirstCountableTopology.nhds_generated_countable
/-- If `β` is a first-countable space, then its induced topology via `f` on `α` is also
first-countable. -/
theorem firstCountableTopology_induced (α β : Type*) [t : TopologicalSpace β]
[FirstCountableTopology β] (f : α → β) : @FirstCountableTopology α (t.induced f) :=
let _ := t.induced f;
⟨fun x ↦ nhds_induced f x ▸ inferInstance⟩
variable {α}
instance Subtype.firstCountableTopology (s : Set α) [FirstCountableTopology α] :
FirstCountableTopology s :=
firstCountableTopology_induced s α (↑)
protected theorem _root_.Inducing.firstCountableTopology {β : Type*}
[TopologicalSpace β] [FirstCountableTopology β] {f : α → β} (hf : Inducing f) :
FirstCountableTopology α := by
rw [hf.1]
exact firstCountableTopology_induced α β f
protected theorem _root_.Embedding.firstCountableTopology {β : Type*}
[TopologicalSpace β] [FirstCountableTopology β] {f : α → β} (hf : Embedding f) :
FirstCountableTopology α :=
hf.1.firstCountableTopology
namespace FirstCountableTopology
/-- In a first-countable space, a cluster point `x` of a sequence
is the limit of some subsequence. -/
theorem tendsto_subseq [FirstCountableTopology α] {u : ℕ → α} {x : α}
(hx : MapClusterPt x atTop u) : ∃ ψ : ℕ → ℕ, StrictMono ψ ∧ Tendsto (u ∘ ψ) atTop (𝓝 x) :=
subseq_tendsto_of_neBot hx
#align topological_space.first_countable_topology.tendsto_subseq TopologicalSpace.FirstCountableTopology.tendsto_subseq
end FirstCountableTopology
instance {β} [TopologicalSpace β] [FirstCountableTopology α] [FirstCountableTopology β] :
FirstCountableTopology (α × β) :=
⟨fun ⟨x, y⟩ => by rw [nhds_prod_eq]; infer_instance⟩
section Pi
instance {ι : Type*} {π : ι → Type*} [Countable ι] [∀ i, TopologicalSpace (π i)]
[∀ i, FirstCountableTopology (π i)] : FirstCountableTopology (∀ i, π i) :=
⟨fun f => by rw [nhds_pi]; infer_instance⟩
end Pi
instance isCountablyGenerated_nhdsWithin (x : α) [IsCountablyGenerated (𝓝 x)] (s : Set α) :
IsCountablyGenerated (𝓝[s] x) :=
Inf.isCountablyGenerated _ _
#align topological_space.is_countably_generated_nhds_within TopologicalSpace.isCountablyGenerated_nhdsWithin
variable (α)
/-- A second-countable space is one with a countable basis. -/
class _root_.SecondCountableTopology : Prop where
/-- There exists a countable set of sets that generates the topology. -/
is_open_generated_countable : ∃ b : Set (Set α), b.Countable ∧ t = TopologicalSpace.generateFrom b
#align topological_space.second_countable_topology SecondCountableTopology
variable {α}
protected theorem IsTopologicalBasis.secondCountableTopology {b : Set (Set α)}
(hb : IsTopologicalBasis b) (hc : b.Countable) : SecondCountableTopology α :=
⟨⟨b, hc, hb.eq_generateFrom⟩⟩
#align topological_space.is_topological_basis.second_countable_topology TopologicalSpace.IsTopologicalBasis.secondCountableTopology
lemma SecondCountableTopology.mk' {b : Set (Set α)} (hc : b.Countable) :
@SecondCountableTopology α (generateFrom b) :=
@SecondCountableTopology.mk α (generateFrom b) ⟨b, hc, rfl⟩
instance _root_.Finite.toSecondCountableTopology [Finite α] : SecondCountableTopology α where
is_open_generated_countable :=
⟨_, {U | IsOpen U}.to_countable, TopologicalSpace.isTopologicalBasis_opens.eq_generateFrom⟩
variable (α)
theorem exists_countable_basis [SecondCountableTopology α] :
∃ b : Set (Set α), b.Countable ∧ ∅ ∉ b ∧ IsTopologicalBasis b := by
obtain ⟨b, hb₁, hb₂⟩ := @SecondCountableTopology.is_open_generated_countable α _ _
refine ⟨_, ?_, not_mem_diff_of_mem ?_, (isTopologicalBasis_of_subbasis hb₂).diff_empty⟩
exacts [((countable_setOf_finite_subset hb₁).image _).mono diff_subset, rfl]
#align topological_space.exists_countable_basis TopologicalSpace.exists_countable_basis
/-- A countable topological basis of `α`. -/
def countableBasis [SecondCountableTopology α] : Set (Set α) :=
(exists_countable_basis α).choose
#align topological_space.countable_basis TopologicalSpace.countableBasis
theorem countable_countableBasis [SecondCountableTopology α] : (countableBasis α).Countable :=
(exists_countable_basis α).choose_spec.1
#align topological_space.countable_countable_basis TopologicalSpace.countable_countableBasis
instance encodableCountableBasis [SecondCountableTopology α] : Encodable (countableBasis α) :=
(countable_countableBasis α).toEncodable
#align topological_space.encodable_countable_basis TopologicalSpace.encodableCountableBasis
theorem empty_nmem_countableBasis [SecondCountableTopology α] : ∅ ∉ countableBasis α :=
(exists_countable_basis α).choose_spec.2.1
#align topological_space.empty_nmem_countable_basis TopologicalSpace.empty_nmem_countableBasis
theorem isBasis_countableBasis [SecondCountableTopology α] :
IsTopologicalBasis (countableBasis α) :=
(exists_countable_basis α).choose_spec.2.2
#align topological_space.is_basis_countable_basis TopologicalSpace.isBasis_countableBasis
theorem eq_generateFrom_countableBasis [SecondCountableTopology α] :
‹TopologicalSpace α› = generateFrom (countableBasis α) :=
(isBasis_countableBasis α).eq_generateFrom
#align topological_space.eq_generate_from_countable_basis TopologicalSpace.eq_generateFrom_countableBasis
variable {α}
theorem isOpen_of_mem_countableBasis [SecondCountableTopology α] {s : Set α}
(hs : s ∈ countableBasis α) : IsOpen s :=
(isBasis_countableBasis α).isOpen hs
#align topological_space.is_open_of_mem_countable_basis TopologicalSpace.isOpen_of_mem_countableBasis
theorem nonempty_of_mem_countableBasis [SecondCountableTopology α] {s : Set α}
(hs : s ∈ countableBasis α) : s.Nonempty :=
nonempty_iff_ne_empty.2 <| ne_of_mem_of_not_mem hs <| empty_nmem_countableBasis α
#align topological_space.nonempty_of_mem_countable_basis TopologicalSpace.nonempty_of_mem_countableBasis
variable (α)
-- see Note [lower instance priority]
instance (priority := 100) SecondCountableTopology.to_firstCountableTopology
[SecondCountableTopology α] : FirstCountableTopology α :=
⟨fun _ => HasCountableBasis.isCountablyGenerated <|
⟨(isBasis_countableBasis α).nhds_hasBasis,
(countable_countableBasis α).mono inter_subset_left⟩⟩
#align topological_space.second_countable_topology.to_first_countable_topology TopologicalSpace.SecondCountableTopology.to_firstCountableTopology
/-- If `β` is a second-countable space, then its induced topology via
`f` on `α` is also second-countable. -/
theorem secondCountableTopology_induced (β) [t : TopologicalSpace β] [SecondCountableTopology β]
(f : α → β) : @SecondCountableTopology α (t.induced f) := by
rcases @SecondCountableTopology.is_open_generated_countable β _ _ with ⟨b, hb, eq⟩
letI := t.induced f
refine { is_open_generated_countable := ⟨preimage f '' b, hb.image _, ?_⟩ }
rw [eq, induced_generateFrom_eq]
#align topological_space.second_countable_topology_induced TopologicalSpace.secondCountableTopology_induced
variable {α}
instance Subtype.secondCountableTopology (s : Set α) [SecondCountableTopology α] :
SecondCountableTopology s :=
secondCountableTopology_induced s α (↑)
#align topological_space.subtype.second_countable_topology TopologicalSpace.Subtype.secondCountableTopology
lemma secondCountableTopology_iInf {ι} [Countable ι] {t : ι → TopologicalSpace α}
(ht : ∀ i, @SecondCountableTopology α (t i)) : @SecondCountableTopology α (⨅ i, t i) := by
rw [funext fun i => @eq_generateFrom_countableBasis α (t i) (ht i), ← generateFrom_iUnion]
exact SecondCountableTopology.mk' <|
countable_iUnion fun i => @countable_countableBasis _ (t i) (ht i)
-- TODO: more fine grained instances for `FirstCountableTopology`, `SeparableSpace`, `T2Space`, ...
instance {β : Type*} [TopologicalSpace β] [SecondCountableTopology α] [SecondCountableTopology β] :
SecondCountableTopology (α × β) :=
((isBasis_countableBasis α).prod (isBasis_countableBasis β)).secondCountableTopology <|
(countable_countableBasis α).image2 (countable_countableBasis β) _
instance {ι : Type*} {π : ι → Type*} [Countable ι] [∀ a, TopologicalSpace (π a)]
[∀ a, SecondCountableTopology (π a)] : SecondCountableTopology (∀ a, π a) :=
secondCountableTopology_iInf fun _ => secondCountableTopology_induced _ _ _
-- see Note [lower instance priority]
instance (priority := 100) SecondCountableTopology.to_separableSpace [SecondCountableTopology α] :
SeparableSpace α := by
choose p hp using fun s : countableBasis α => nonempty_of_mem_countableBasis s.2
exact
⟨⟨range p, countable_range _,
(isBasis_countableBasis α).dense_iff.2 fun o ho _ => ⟨p ⟨o, ho⟩, hp _, mem_range_self _⟩⟩⟩
#align topological_space.second_countable_topology.to_separable_space TopologicalSpace.SecondCountableTopology.to_separableSpace
/-- A countable open cover induces a second-countable topology if all open covers
are themselves second countable. -/
theorem secondCountableTopology_of_countable_cover {ι} [Countable ι] {U : ι → Set α}
[∀ i, SecondCountableTopology (U i)] (Uo : ∀ i, IsOpen (U i)) (hc : ⋃ i, U i = univ) :
SecondCountableTopology α :=
haveI : IsTopologicalBasis (⋃ i, image ((↑) : U i → α) '' countableBasis (U i)) :=
isTopologicalBasis_of_cover Uo hc fun i => isBasis_countableBasis (U i)
this.secondCountableTopology (countable_iUnion fun _ => (countable_countableBasis _).image _)
#align topological_space.second_countable_topology_of_countable_cover TopologicalSpace.secondCountableTopology_of_countable_cover
/-- In a second-countable space, an open set, given as a union of open sets,
is equal to the union of countably many of those sets.
In particular, any open covering of `α` has a countable subcover: α is a Lindelöf space. -/
theorem isOpen_iUnion_countable [SecondCountableTopology α] {ι} (s : ι → Set α)
(H : ∀ i, IsOpen (s i)) : ∃ T : Set ι, T.Countable ∧ ⋃ i ∈ T, s i = ⋃ i, s i := by
let B := { b ∈ countableBasis α | ∃ i, b ⊆ s i }
choose f hf using fun b : B => b.2.2
haveI : Countable B := ((countable_countableBasis α).mono (sep_subset _ _)).to_subtype
refine ⟨_, countable_range f, (iUnion₂_subset_iUnion _ _).antisymm (sUnion_subset ?_)⟩
rintro _ ⟨i, rfl⟩ x xs
rcases (isBasis_countableBasis α).exists_subset_of_mem_open xs (H _) with ⟨b, hb, xb, bs⟩
exact ⟨_, ⟨_, rfl⟩, _, ⟨⟨⟨_, hb, _, bs⟩, rfl⟩, rfl⟩, hf _ xb⟩
#align topological_space.is_open_Union_countable TopologicalSpace.isOpen_iUnion_countable
theorem isOpen_biUnion_countable [SecondCountableTopology α] {ι : Type*} (I : Set ι) (s : ι → Set α)
(H : ∀ i ∈ I, IsOpen (s i)) : ∃ T ⊆ I, T.Countable ∧ ⋃ i ∈ T, s i = ⋃ i ∈ I, s i := by
simp_rw [← Subtype.exists_set_subtype, biUnion_image]
rcases isOpen_iUnion_countable (fun i : I ↦ s i) fun i ↦ H i i.2 with ⟨T, hTc, hU⟩
exact ⟨T, hTc.image _, hU.trans <| iUnion_subtype ..⟩
theorem isOpen_sUnion_countable [SecondCountableTopology α] (S : Set (Set α))
(H : ∀ s ∈ S, IsOpen s) : ∃ T : Set (Set α), T.Countable ∧ T ⊆ S ∧ ⋃₀ T = ⋃₀ S := by
simpa only [and_left_comm, sUnion_eq_biUnion] using isOpen_biUnion_countable S id H
#align topological_space.is_open_sUnion_countable TopologicalSpace.isOpen_sUnion_countable
/-- In a topological space with second countable topology, if `f` is a function that sends each
point `x` to a neighborhood of `x`, then for some countable set `s`, the neighborhoods `f x`,
`x ∈ s`, cover the whole space. -/
theorem countable_cover_nhds [SecondCountableTopology α] {f : α → Set α} (hf : ∀ x, f x ∈ 𝓝 x) :
∃ s : Set α, s.Countable ∧ ⋃ x ∈ s, f x = univ := by
rcases isOpen_iUnion_countable (fun x => interior (f x)) fun x => isOpen_interior with
⟨s, hsc, hsU⟩
suffices ⋃ x ∈ s, interior (f x) = univ from
⟨s, hsc, flip eq_univ_of_subset this <| iUnion₂_mono fun _ _ => interior_subset⟩
simp only [hsU, eq_univ_iff_forall, mem_iUnion]
exact fun x => ⟨x, mem_interior_iff_mem_nhds.2 (hf x)⟩
#align topological_space.countable_cover_nhds TopologicalSpace.countable_cover_nhds
theorem countable_cover_nhdsWithin [SecondCountableTopology α] {f : α → Set α} {s : Set α}
(hf : ∀ x ∈ s, f x ∈ 𝓝[s] x) : ∃ t ⊆ s, t.Countable ∧ s ⊆ ⋃ x ∈ t, f x := by
have : ∀ x : s, (↑) ⁻¹' f x ∈ 𝓝 x := fun x => preimage_coe_mem_nhds_subtype.2 (hf x x.2)
rcases countable_cover_nhds this with ⟨t, htc, htU⟩
refine ⟨(↑) '' t, Subtype.coe_image_subset _ _, htc.image _, fun x hx => ?_⟩
simp only [biUnion_image, eq_univ_iff_forall, ← preimage_iUnion, mem_preimage] at htU ⊢
exact htU ⟨x, hx⟩
#align topological_space.countable_cover_nhds_within TopologicalSpace.countable_cover_nhdsWithin
section Sigma
variable {ι : Type*} {E : ι → Type*} [∀ i, TopologicalSpace (E i)]
/-- In a disjoint union space `Σ i, E i`, one can form a topological basis by taking the union of
topological bases on each of the parts of the space. -/
theorem IsTopologicalBasis.sigma {s : ∀ i : ι, Set (Set (E i))}
(hs : ∀ i, IsTopologicalBasis (s i)) :
IsTopologicalBasis (⋃ i : ι, (fun u => (Sigma.mk i '' u : Set (Σi, E i))) '' s i) := by
refine .of_hasBasis_nhds fun a ↦ ?_
rw [Sigma.nhds_eq]
convert (((hs a.1).nhds_hasBasis).map _).to_image_id
aesop
#align topological_space.is_topological_basis.sigma TopologicalSpace.IsTopologicalBasis.sigma
/-- A countable disjoint union of second countable spaces is second countable. -/
instance [Countable ι] [∀ i, SecondCountableTopology (E i)] :
SecondCountableTopology (Σi, E i) := by
let b := ⋃ i : ι, (fun u => (Sigma.mk i '' u : Set (Σi, E i))) '' countableBasis (E i)
have A : IsTopologicalBasis b := IsTopologicalBasis.sigma fun i => isBasis_countableBasis _
have B : b.Countable := countable_iUnion fun i => (countable_countableBasis _).image _
exact A.secondCountableTopology B
end Sigma
section Sum
variable {β : Type*} [TopologicalSpace α] [TopologicalSpace β]
/-- In a sum space `α ⊕ β`, one can form a topological basis by taking the union of
topological bases on each of the two components. -/
| Mathlib/Topology/Bases.lean | 939 | 954 | theorem IsTopologicalBasis.sum {s : Set (Set α)} (hs : IsTopologicalBasis s) {t : Set (Set β)}
(ht : IsTopologicalBasis t) :
IsTopologicalBasis ((fun u => Sum.inl '' u) '' s ∪ (fun u => Sum.inr '' u) '' t) := by |
apply isTopologicalBasis_of_isOpen_of_nhds
· rintro u (⟨w, hw, rfl⟩ | ⟨w, hw, rfl⟩)
· exact openEmbedding_inl.isOpenMap w (hs.isOpen hw)
· exact openEmbedding_inr.isOpenMap w (ht.isOpen hw)
· rintro (x | x) u hxu u_open
· obtain ⟨v, vs, xv, vu⟩ : ∃ v ∈ s, x ∈ v ∧ v ⊆ Sum.inl ⁻¹' u :=
hs.exists_subset_of_mem_open hxu (isOpen_sum_iff.1 u_open).1
exact ⟨Sum.inl '' v, mem_union_left _ (mem_image_of_mem _ vs), mem_image_of_mem _ xv,
image_subset_iff.2 vu⟩
· obtain ⟨v, vs, xv, vu⟩ : ∃ v ∈ t, x ∈ v ∧ v ⊆ Sum.inr ⁻¹' u :=
ht.exists_subset_of_mem_open hxu (isOpen_sum_iff.1 u_open).2
exact ⟨Sum.inr '' v, mem_union_right _ (mem_image_of_mem _ vs), mem_image_of_mem _ xv,
image_subset_iff.2 vu⟩
|
/-
Copyright (c) 2022 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Patrick Massot
-/
import Mathlib.Topology.Basic
#align_import topology.nhds_set from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Neighborhoods of a set
In this file we define the filter `𝓝ˢ s` or `nhdsSet s` consisting of all neighborhoods of a set
`s`.
## Main Properties
There are a couple different notions equivalent to `s ∈ 𝓝ˢ t`:
* `s ⊆ interior t` using `subset_interior_iff_mem_nhdsSet`
* `∀ x : X, x ∈ t → s ∈ 𝓝 x` using `mem_nhdsSet_iff_forall`
* `∃ U : Set X, IsOpen U ∧ t ⊆ U ∧ U ⊆ s` using `mem_nhdsSet_iff_exists`
Furthermore, we have the following results:
* `monotone_nhdsSet`: `𝓝ˢ` is monotone
* In T₁-spaces, `𝓝ˢ`is strictly monotone and hence injective:
`strict_mono_nhdsSet`/`injective_nhdsSet`. These results are in `Mathlib.Topology.Separation`.
-/
open Set Filter Topology
variable {X Y : Type*} [TopologicalSpace X] [TopologicalSpace Y] {f : Filter X}
{s t s₁ s₂ t₁ t₂ : Set X} {x : X}
theorem nhdsSet_diagonal (X) [TopologicalSpace (X × X)] :
𝓝ˢ (diagonal X) = ⨆ (x : X), 𝓝 (x, x) := by
rw [nhdsSet, ← range_diag, ← range_comp]
rfl
#align nhds_set_diagonal nhdsSet_diagonal
theorem mem_nhdsSet_iff_forall : s ∈ 𝓝ˢ t ↔ ∀ x : X, x ∈ t → s ∈ 𝓝 x := by
simp_rw [nhdsSet, Filter.mem_sSup, forall_mem_image]
#align mem_nhds_set_iff_forall mem_nhdsSet_iff_forall
lemma nhdsSet_le : 𝓝ˢ s ≤ f ↔ ∀ x ∈ s, 𝓝 x ≤ f := by simp [nhdsSet]
theorem bUnion_mem_nhdsSet {t : X → Set X} (h : ∀ x ∈ s, t x ∈ 𝓝 x) : (⋃ x ∈ s, t x) ∈ 𝓝ˢ s :=
mem_nhdsSet_iff_forall.2 fun x hx => mem_of_superset (h x hx) <|
subset_iUnion₂ (s := fun x _ => t x) x hx -- Porting note: fails to find `s`
#align bUnion_mem_nhds_set bUnion_mem_nhdsSet
theorem subset_interior_iff_mem_nhdsSet : s ⊆ interior t ↔ t ∈ 𝓝ˢ s := by
simp_rw [mem_nhdsSet_iff_forall, subset_interior_iff_nhds]
#align subset_interior_iff_mem_nhds_set subset_interior_iff_mem_nhdsSet
theorem disjoint_principal_nhdsSet : Disjoint (𝓟 s) (𝓝ˢ t) ↔ Disjoint (closure s) t := by
rw [disjoint_principal_left, ← subset_interior_iff_mem_nhdsSet, interior_compl,
subset_compl_iff_disjoint_left]
theorem disjoint_nhdsSet_principal : Disjoint (𝓝ˢ s) (𝓟 t) ↔ Disjoint s (closure t) := by
rw [disjoint_comm, disjoint_principal_nhdsSet, disjoint_comm]
theorem mem_nhdsSet_iff_exists : s ∈ 𝓝ˢ t ↔ ∃ U : Set X, IsOpen U ∧ t ⊆ U ∧ U ⊆ s := by
rw [← subset_interior_iff_mem_nhdsSet, subset_interior_iff]
#align mem_nhds_set_iff_exists mem_nhdsSet_iff_exists
/-- A proposition is true on a set neighborhood of `s` iff it is true on a larger open set -/
theorem eventually_nhdsSet_iff_exists {p : X → Prop} :
(∀ᶠ x in 𝓝ˢ s, p x) ↔ ∃ t, IsOpen t ∧ s ⊆ t ∧ ∀ x, x ∈ t → p x :=
mem_nhdsSet_iff_exists
/-- A proposition is true on a set neighborhood of `s`
iff it is eventually true near each point in the set. -/
theorem eventually_nhdsSet_iff_forall {p : X → Prop} :
(∀ᶠ x in 𝓝ˢ s, p x) ↔ ∀ x, x ∈ s → ∀ᶠ y in 𝓝 x, p y :=
mem_nhdsSet_iff_forall
theorem hasBasis_nhdsSet (s : Set X) : (𝓝ˢ s).HasBasis (fun U => IsOpen U ∧ s ⊆ U) fun U => U :=
⟨fun t => by simp [mem_nhdsSet_iff_exists, and_assoc]⟩
#align has_basis_nhds_set hasBasis_nhdsSet
@[simp]
lemma lift'_nhdsSet_interior (s : Set X) : (𝓝ˢ s).lift' interior = 𝓝ˢ s :=
(hasBasis_nhdsSet s).lift'_interior_eq_self fun _ ↦ And.left
lemma Filter.HasBasis.nhdsSet_interior {ι : Sort*} {p : ι → Prop} {s : ι → Set X} {t : Set X}
(h : (𝓝ˢ t).HasBasis p s) : (𝓝ˢ t).HasBasis p (interior <| s ·) :=
lift'_nhdsSet_interior t ▸ h.lift'_interior
theorem IsOpen.mem_nhdsSet (hU : IsOpen s) : s ∈ 𝓝ˢ t ↔ t ⊆ s := by
rw [← subset_interior_iff_mem_nhdsSet, hU.interior_eq]
#align is_open.mem_nhds_set IsOpen.mem_nhdsSet
/-- An open set belongs to its own set neighborhoods filter. -/
theorem IsOpen.mem_nhdsSet_self (ho : IsOpen s) : s ∈ 𝓝ˢ s := ho.mem_nhdsSet.mpr Subset.rfl
theorem principal_le_nhdsSet : 𝓟 s ≤ 𝓝ˢ s := fun _s hs =>
(subset_interior_iff_mem_nhdsSet.mpr hs).trans interior_subset
#align principal_le_nhds_set principal_le_nhdsSet
theorem subset_of_mem_nhdsSet (h : t ∈ 𝓝ˢ s) : s ⊆ t := principal_le_nhdsSet h
theorem Filter.Eventually.self_of_nhdsSet {p : X → Prop} (h : ∀ᶠ x in 𝓝ˢ s, p x) : ∀ x ∈ s, p x :=
principal_le_nhdsSet h
nonrec theorem Filter.EventuallyEq.self_of_nhdsSet {f g : X → Y} (h : f =ᶠ[𝓝ˢ s] g) : EqOn f g s :=
h.self_of_nhdsSet
@[simp]
theorem nhdsSet_eq_principal_iff : 𝓝ˢ s = 𝓟 s ↔ IsOpen s := by
rw [← principal_le_nhdsSet.le_iff_eq, le_principal_iff, mem_nhdsSet_iff_forall,
isOpen_iff_mem_nhds]
#align nhds_set_eq_principal_iff nhdsSet_eq_principal_iff
alias ⟨_, IsOpen.nhdsSet_eq⟩ := nhdsSet_eq_principal_iff
#align is_open.nhds_set_eq IsOpen.nhdsSet_eq
@[simp]
theorem nhdsSet_interior : 𝓝ˢ (interior s) = 𝓟 (interior s) :=
isOpen_interior.nhdsSet_eq
#align nhds_set_interior nhdsSet_interior
@[simp]
theorem nhdsSet_singleton : 𝓝ˢ {x} = 𝓝 x := by simp [nhdsSet]
#align nhds_set_singleton nhdsSet_singleton
theorem mem_nhdsSet_interior : s ∈ 𝓝ˢ (interior s) :=
subset_interior_iff_mem_nhdsSet.mp Subset.rfl
#align mem_nhds_set_interior mem_nhdsSet_interior
@[simp]
theorem nhdsSet_empty : 𝓝ˢ (∅ : Set X) = ⊥ := by rw [isOpen_empty.nhdsSet_eq, principal_empty]
#align nhds_set_empty nhdsSet_empty
theorem mem_nhdsSet_empty : s ∈ 𝓝ˢ (∅ : Set X) := by simp
#align mem_nhds_set_empty mem_nhdsSet_empty
@[simp]
theorem nhdsSet_univ : 𝓝ˢ (univ : Set X) = ⊤ := by rw [isOpen_univ.nhdsSet_eq, principal_univ]
#align nhds_set_univ nhdsSet_univ
@[mono]
theorem nhdsSet_mono (h : s ⊆ t) : 𝓝ˢ s ≤ 𝓝ˢ t :=
sSup_le_sSup <| image_subset _ h
#align nhds_set_mono nhdsSet_mono
theorem monotone_nhdsSet : Monotone (𝓝ˢ : Set X → Filter X) := fun _ _ => nhdsSet_mono
#align monotone_nhds_set monotone_nhdsSet
theorem nhds_le_nhdsSet (h : x ∈ s) : 𝓝 x ≤ 𝓝ˢ s :=
le_sSup <| mem_image_of_mem _ h
#align nhds_le_nhds_set nhds_le_nhdsSet
@[simp]
theorem nhdsSet_union (s t : Set X) : 𝓝ˢ (s ∪ t) = 𝓝ˢ s ⊔ 𝓝ˢ t := by
simp only [nhdsSet, image_union, sSup_union]
#align nhds_set_union nhdsSet_union
theorem union_mem_nhdsSet (h₁ : s₁ ∈ 𝓝ˢ t₁) (h₂ : s₂ ∈ 𝓝ˢ t₂) : s₁ ∪ s₂ ∈ 𝓝ˢ (t₁ ∪ t₂) := by
rw [nhdsSet_union]
exact union_mem_sup h₁ h₂
#align union_mem_nhds_set union_mem_nhdsSet
@[simp]
theorem nhdsSet_insert (x : X) (s : Set X) : 𝓝ˢ (insert x s) = 𝓝 x ⊔ 𝓝ˢ s := by
rw [insert_eq, nhdsSet_union, nhdsSet_singleton]
/-- Preimage of a set neighborhood of `t` under a continuous map `f` is a set neighborhood of `s`
provided that `f` maps `s` to `t`. -/
theorem Continuous.tendsto_nhdsSet {f : X → Y} {t : Set Y} (hf : Continuous f)
(hst : MapsTo f s t) : Tendsto f (𝓝ˢ s) (𝓝ˢ t) :=
((hasBasis_nhdsSet s).tendsto_iff (hasBasis_nhdsSet t)).mpr fun U hU =>
⟨f ⁻¹' U, ⟨hU.1.preimage hf, hst.mono Subset.rfl hU.2⟩, fun _ => id⟩
#align continuous.tendsto_nhds_set Continuous.tendsto_nhdsSet
lemma Continuous.tendsto_nhdsSet_nhds
{y : Y} {f : X → Y} (h : Continuous f) (h' : EqOn f (fun _ ↦ y) s) :
Tendsto f (𝓝ˢ s) (𝓝 y) := by
rw [← nhdsSet_singleton]
exact h.tendsto_nhdsSet h'
/- This inequality cannot be improved to an equality. For instance,
if `X` has two elements and the coarse topology and `s` and `t` are distinct singletons then
`𝓝ˢ (s ∩ t) = ⊥` while `𝓝ˢ s ⊓ 𝓝ˢ t = ⊤` and those are different. -/
theorem nhdsSet_inter_le (s t : Set X) : 𝓝ˢ (s ∩ t) ≤ 𝓝ˢ s ⊓ 𝓝ˢ t :=
(monotone_nhdsSet (X := X)).map_inf_le s t
variable (s) in
theorem IsClosed.nhdsSet_le_sup (h : IsClosed t) : 𝓝ˢ s ≤ 𝓝ˢ (s ∩ t) ⊔ 𝓟 (tᶜ) :=
calc
𝓝ˢ s = 𝓝ˢ (s ∩ t ∪ s ∩ tᶜ) := by rw [Set.inter_union_compl s t]
_ = 𝓝ˢ (s ∩ t) ⊔ 𝓝ˢ (s ∩ tᶜ) := by rw [nhdsSet_union]
_ ≤ 𝓝ˢ (s ∩ t) ⊔ 𝓝ˢ (tᶜ) := sup_le_sup_left (monotone_nhdsSet inter_subset_right) _
_ = 𝓝ˢ (s ∩ t) ⊔ 𝓟 (tᶜ) := by rw [h.isOpen_compl.nhdsSet_eq]
variable (s) in
theorem IsClosed.nhdsSet_le_sup' (h : IsClosed t) :
𝓝ˢ s ≤ 𝓝ˢ (t ∩ s) ⊔ 𝓟 (tᶜ) := by rw [Set.inter_comm]; exact h.nhdsSet_le_sup s
theorem Filter.Eventually.eventually_nhdsSet {p : X → Prop} (h : ∀ᶠ y in 𝓝ˢ s, p y) :
∀ᶠ y in 𝓝ˢ s, ∀ᶠ x in 𝓝 y, p x :=
eventually_nhdsSet_iff_forall.mpr fun x x_in ↦
(eventually_nhdsSet_iff_forall.mp h x x_in).eventually_nhds
theorem Filter.Eventually.union_nhdsSet {p : X → Prop} :
(∀ᶠ x in 𝓝ˢ (s ∪ t), p x) ↔ (∀ᶠ x in 𝓝ˢ s, p x) ∧ ∀ᶠ x in 𝓝ˢ t, p x := by
rw [nhdsSet_union, eventually_sup]
theorem Filter.Eventually.union {p : X → Prop} (hs : ∀ᶠ x in 𝓝ˢ s, p x) (ht : ∀ᶠ x in 𝓝ˢ t, p x) :
∀ᶠ x in 𝓝ˢ (s ∪ t), p x :=
Filter.Eventually.union_nhdsSet.mpr ⟨hs, ht⟩
theorem nhdsSet_iUnion {ι : Sort*} (s : ι → Set X) : 𝓝ˢ (⋃ i, s i) = ⨆ i, 𝓝ˢ (s i) := by
simp only [nhdsSet, image_iUnion, sSup_iUnion (β := Filter X)]
theorem eventually_nhdsSet_iUnion₂ {ι : Sort*} {p : ι → Prop} {s : ι → Set X} {P : X → Prop} :
(∀ᶠ x in 𝓝ˢ (⋃ (i) (_ : p i), s i), P x) ↔ ∀ i, p i → ∀ᶠ x in 𝓝ˢ (s i), P x := by
simp only [nhdsSet_iUnion, eventually_iSup]
| Mathlib/Topology/NhdsSet.lean | 220 | 222 | theorem eventually_nhdsSet_iUnion {ι : Sort*} {s : ι → Set X} {P : X → Prop} :
(∀ᶠ x in 𝓝ˢ (⋃ i, s i), P x) ↔ ∀ i, ∀ᶠ x in 𝓝ˢ (s i), P x := by |
simp only [nhdsSet_iUnion, eventually_iSup]
|
/-
Copyright (c) 2019 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Reid Barton, Mario Carneiro, Isabel Longbottom, Scott Morrison
-/
import Mathlib.Algebra.Order.ZeroLEOne
import Mathlib.Data.List.InsertNth
import Mathlib.Logic.Relation
import Mathlib.Logic.Small.Defs
import Mathlib.Order.GameAdd
#align_import set_theory.game.pgame from "leanprover-community/mathlib"@"8900d545017cd21961daa2a1734bb658ef52c618"
/-!
# Combinatorial (pre-)games.
The basic theory of combinatorial games, following Conway's book `On Numbers and Games`. We
construct "pregames", define an ordering and arithmetic operations on them, then show that the
operations descend to "games", defined via the equivalence relation `p ≈ q ↔ p ≤ q ∧ q ≤ p`.
The surreal numbers will be built as a quotient of a subtype of pregames.
A pregame (`SetTheory.PGame` below) is axiomatised via an inductive type, whose sole constructor
takes two types (thought of as indexing the possible moves for the players Left and Right), and a
pair of functions out of these types to `SetTheory.PGame` (thought of as describing the resulting
game after making a move).
Combinatorial games themselves, as a quotient of pregames, are constructed in `Game.lean`.
## Conway induction
By construction, the induction principle for pregames is exactly "Conway induction". That is, to
prove some predicate `SetTheory.PGame → Prop` holds for all pregames, it suffices to prove
that for every pregame `g`, if the predicate holds for every game resulting from making a move,
then it also holds for `g`.
While it is often convenient to work "by induction" on pregames, in some situations this becomes
awkward, so we also define accessor functions `SetTheory.PGame.LeftMoves`,
`SetTheory.PGame.RightMoves`, `SetTheory.PGame.moveLeft` and `SetTheory.PGame.moveRight`.
There is a relation `PGame.Subsequent p q`, saying that
`p` can be reached by playing some non-empty sequence of moves starting from `q`, an instance
`WellFounded Subsequent`, and a local tactic `pgame_wf_tac` which is helpful for discharging proof
obligations in inductive proofs relying on this relation.
## Order properties
Pregames have both a `≤` and a `<` relation, satisfying the usual properties of a `Preorder`. The
relation `0 < x` means that `x` can always be won by Left, while `0 ≤ x` means that `x` can be won
by Left as the second player.
It turns out to be quite convenient to define various relations on top of these. We define the "less
or fuzzy" relation `x ⧏ y` as `¬ y ≤ x`, the equivalence relation `x ≈ y` as `x ≤ y ∧ y ≤ x`, and
the fuzzy relation `x ‖ y` as `x ⧏ y ∧ y ⧏ x`. If `0 ⧏ x`, then `x` can be won by Left as the
first player. If `x ≈ 0`, then `x` can be won by the second player. If `x ‖ 0`, then `x` can be won
by the first player.
Statements like `zero_le_lf`, `zero_lf_le`, etc. unfold these definitions. The theorems `le_def` and
`lf_def` give a recursive characterisation of each relation in terms of themselves two moves later.
The theorems `zero_le`, `zero_lf`, etc. also take into account that `0` has no moves.
Later, games will be defined as the quotient by the `≈` relation; that is to say, the
`Antisymmetrization` of `SetTheory.PGame`.
## Algebraic structures
We next turn to defining the operations necessary to make games into a commutative additive group.
Addition is defined for $x = \{xL | xR\}$ and $y = \{yL | yR\}$ by $x + y = \{xL + y, x + yL | xR +
y, x + yR\}$. Negation is defined by $\{xL | xR\} = \{-xR | -xL\}$.
The order structures interact in the expected way with addition, so we have
```
theorem le_iff_sub_nonneg {x y : PGame} : x ≤ y ↔ 0 ≤ y - x := sorry
theorem lt_iff_sub_pos {x y : PGame} : x < y ↔ 0 < y - x := sorry
```
We show that these operations respect the equivalence relation, and hence descend to games. At the
level of games, these operations satisfy all the laws of a commutative group. To prove the necessary
equivalence relations at the level of pregames, we introduce the notion of a `Relabelling` of a
game, and show, for example, that there is a relabelling between `x + (y + z)` and `(x + y) + z`.
## Future work
* The theory of dominated and reversible positions, and unique normal form for short games.
* Analysis of basic domineering positions.
* Hex.
* Temperature.
* The development of surreal numbers, based on this development of combinatorial games, is still
quite incomplete.
## References
The material here is all drawn from
* [Conway, *On numbers and games*][conway2001]
An interested reader may like to formalise some of the material from
* [Andreas Blass, *A game semantics for linear logic*][MR1167694]
* [André Joyal, *Remarques sur la théorie des jeux à deux personnes*][joyal1997]
-/
set_option autoImplicit true
namespace SetTheory
open Function Relation
-- We'd like to be able to use multi-character auto-implicits in this file.
set_option relaxedAutoImplicit true
/-! ### Pre-game moves -/
/-- The type of pre-games, before we have quotiented
by equivalence (`PGame.Setoid`). In ZFC, a combinatorial game is constructed from
two sets of combinatorial games that have been constructed at an earlier
stage. To do this in type theory, we say that a pre-game is built
inductively from two families of pre-games indexed over any type
in Type u. The resulting type `PGame.{u}` lives in `Type (u+1)`,
reflecting that it is a proper class in ZFC. -/
inductive PGame : Type (u + 1)
| mk : ∀ α β : Type u, (α → PGame) → (β → PGame) → PGame
#align pgame SetTheory.PGame
compile_inductive% PGame
namespace PGame
/-- The indexing type for allowable moves by Left. -/
def LeftMoves : PGame → Type u
| mk l _ _ _ => l
#align pgame.left_moves SetTheory.PGame.LeftMoves
/-- The indexing type for allowable moves by Right. -/
def RightMoves : PGame → Type u
| mk _ r _ _ => r
#align pgame.right_moves SetTheory.PGame.RightMoves
/-- The new game after Left makes an allowed move. -/
def moveLeft : ∀ g : PGame, LeftMoves g → PGame
| mk _l _ L _ => L
#align pgame.move_left SetTheory.PGame.moveLeft
/-- The new game after Right makes an allowed move. -/
def moveRight : ∀ g : PGame, RightMoves g → PGame
| mk _ _r _ R => R
#align pgame.move_right SetTheory.PGame.moveRight
@[simp]
theorem leftMoves_mk {xl xr xL xR} : (⟨xl, xr, xL, xR⟩ : PGame).LeftMoves = xl :=
rfl
#align pgame.left_moves_mk SetTheory.PGame.leftMoves_mk
@[simp]
theorem moveLeft_mk {xl xr xL xR} : (⟨xl, xr, xL, xR⟩ : PGame).moveLeft = xL :=
rfl
#align pgame.move_left_mk SetTheory.PGame.moveLeft_mk
@[simp]
theorem rightMoves_mk {xl xr xL xR} : (⟨xl, xr, xL, xR⟩ : PGame).RightMoves = xr :=
rfl
#align pgame.right_moves_mk SetTheory.PGame.rightMoves_mk
@[simp]
theorem moveRight_mk {xl xr xL xR} : (⟨xl, xr, xL, xR⟩ : PGame).moveRight = xR :=
rfl
#align pgame.move_right_mk SetTheory.PGame.moveRight_mk
-- TODO define this at the level of games, as well, and perhaps also for finsets of games.
/-- Construct a pre-game from list of pre-games describing the available moves for Left and Right.
-/
def ofLists (L R : List PGame.{u}) : PGame.{u} :=
mk (ULift (Fin L.length)) (ULift (Fin R.length)) (fun i => L.get i.down) fun j ↦ R.get j.down
#align pgame.of_lists SetTheory.PGame.ofLists
theorem leftMoves_ofLists (L R : List PGame) : (ofLists L R).LeftMoves = ULift (Fin L.length) :=
rfl
#align pgame.left_moves_of_lists SetTheory.PGame.leftMoves_ofLists
theorem rightMoves_ofLists (L R : List PGame) : (ofLists L R).RightMoves = ULift (Fin R.length) :=
rfl
#align pgame.right_moves_of_lists SetTheory.PGame.rightMoves_ofLists
/-- Converts a number into a left move for `ofLists`. -/
def toOfListsLeftMoves {L R : List PGame} : Fin L.length ≃ (ofLists L R).LeftMoves :=
((Equiv.cast (leftMoves_ofLists L R).symm).trans Equiv.ulift).symm
#align pgame.to_of_lists_left_moves SetTheory.PGame.toOfListsLeftMoves
/-- Converts a number into a right move for `ofLists`. -/
def toOfListsRightMoves {L R : List PGame} : Fin R.length ≃ (ofLists L R).RightMoves :=
((Equiv.cast (rightMoves_ofLists L R).symm).trans Equiv.ulift).symm
#align pgame.to_of_lists_right_moves SetTheory.PGame.toOfListsRightMoves
theorem ofLists_moveLeft {L R : List PGame} (i : Fin L.length) :
(ofLists L R).moveLeft (toOfListsLeftMoves i) = L.get i :=
rfl
#align pgame.of_lists_move_left SetTheory.PGame.ofLists_moveLeft
@[simp]
theorem ofLists_moveLeft' {L R : List PGame} (i : (ofLists L R).LeftMoves) :
(ofLists L R).moveLeft i = L.get (toOfListsLeftMoves.symm i) :=
rfl
#align pgame.of_lists_move_left' SetTheory.PGame.ofLists_moveLeft'
theorem ofLists_moveRight {L R : List PGame} (i : Fin R.length) :
(ofLists L R).moveRight (toOfListsRightMoves i) = R.get i :=
rfl
#align pgame.of_lists_move_right SetTheory.PGame.ofLists_moveRight
@[simp]
theorem ofLists_moveRight' {L R : List PGame} (i : (ofLists L R).RightMoves) :
(ofLists L R).moveRight i = R.get (toOfListsRightMoves.symm i) :=
rfl
#align pgame.of_lists_move_right' SetTheory.PGame.ofLists_moveRight'
/-- A variant of `PGame.recOn` expressed in terms of `PGame.moveLeft` and `PGame.moveRight`.
Both this and `PGame.recOn` describe Conway induction on games. -/
@[elab_as_elim]
def moveRecOn {C : PGame → Sort*} (x : PGame)
(IH : ∀ y : PGame, (∀ i, C (y.moveLeft i)) → (∀ j, C (y.moveRight j)) → C y) : C x :=
x.recOn fun yl yr yL yR => IH (mk yl yr yL yR)
#align pgame.move_rec_on SetTheory.PGame.moveRecOn
/-- `IsOption x y` means that `x` is either a left or right option for `y`. -/
@[mk_iff]
inductive IsOption : PGame → PGame → Prop
| moveLeft {x : PGame} (i : x.LeftMoves) : IsOption (x.moveLeft i) x
| moveRight {x : PGame} (i : x.RightMoves) : IsOption (x.moveRight i) x
#align pgame.is_option SetTheory.PGame.IsOption
theorem IsOption.mk_left {xl xr : Type u} (xL : xl → PGame) (xR : xr → PGame) (i : xl) :
(xL i).IsOption (mk xl xr xL xR) :=
@IsOption.moveLeft (mk _ _ _ _) i
#align pgame.is_option.mk_left SetTheory.PGame.IsOption.mk_left
theorem IsOption.mk_right {xl xr : Type u} (xL : xl → PGame) (xR : xr → PGame) (i : xr) :
(xR i).IsOption (mk xl xr xL xR) :=
@IsOption.moveRight (mk _ _ _ _) i
#align pgame.is_option.mk_right SetTheory.PGame.IsOption.mk_right
theorem wf_isOption : WellFounded IsOption :=
⟨fun x =>
moveRecOn x fun x IHl IHr =>
Acc.intro x fun y h => by
induction' h with _ i _ j
· exact IHl i
· exact IHr j⟩
#align pgame.wf_is_option SetTheory.PGame.wf_isOption
/-- `Subsequent x y` says that `x` can be obtained by playing some nonempty sequence of moves from
`y`. It is the transitive closure of `IsOption`. -/
def Subsequent : PGame → PGame → Prop :=
TransGen IsOption
#align pgame.subsequent SetTheory.PGame.Subsequent
instance : IsTrans _ Subsequent :=
inferInstanceAs <| IsTrans _ (TransGen _)
@[trans]
theorem Subsequent.trans {x y z} : Subsequent x y → Subsequent y z → Subsequent x z :=
TransGen.trans
#align pgame.subsequent.trans SetTheory.PGame.Subsequent.trans
theorem wf_subsequent : WellFounded Subsequent :=
wf_isOption.transGen
#align pgame.wf_subsequent SetTheory.PGame.wf_subsequent
instance : WellFoundedRelation PGame :=
⟨_, wf_subsequent⟩
@[simp]
theorem Subsequent.moveLeft {x : PGame} (i : x.LeftMoves) : Subsequent (x.moveLeft i) x :=
TransGen.single (IsOption.moveLeft i)
#align pgame.subsequent.move_left SetTheory.PGame.Subsequent.moveLeft
@[simp]
theorem Subsequent.moveRight {x : PGame} (j : x.RightMoves) : Subsequent (x.moveRight j) x :=
TransGen.single (IsOption.moveRight j)
#align pgame.subsequent.move_right SetTheory.PGame.Subsequent.moveRight
@[simp]
theorem Subsequent.mk_left {xl xr} (xL : xl → PGame) (xR : xr → PGame) (i : xl) :
Subsequent (xL i) (mk xl xr xL xR) :=
@Subsequent.moveLeft (mk _ _ _ _) i
#align pgame.subsequent.mk_left SetTheory.PGame.Subsequent.mk_left
@[simp]
theorem Subsequent.mk_right {xl xr} (xL : xl → PGame) (xR : xr → PGame) (j : xr) :
Subsequent (xR j) (mk xl xr xL xR) :=
@Subsequent.moveRight (mk _ _ _ _) j
#align pgame.subsequent.mk_right SetTheory.PGame.Subsequent.mk_right
/--
Discharges proof obligations of the form `⊢ Subsequent ..` arising in termination proofs
of definitions using well-founded recursion on `PGame`.
-/
macro "pgame_wf_tac" : tactic =>
`(tactic| solve_by_elim (config := { maxDepth := 8 })
[Prod.Lex.left, Prod.Lex.right, PSigma.Lex.left, PSigma.Lex.right,
Subsequent.moveLeft, Subsequent.moveRight, Subsequent.mk_left, Subsequent.mk_right,
Subsequent.trans] )
-- Register some consequences of pgame_wf_tac as simp-lemmas for convenience
-- (which are applied by default for WF goals)
-- This is different from mk_right from the POV of the simplifier,
-- because the unifier can't solve `xr =?= RightMoves (mk xl xr xL xR)` at reducible transparency.
@[simp]
theorem Subsequent.mk_right' (xL : xl → PGame) (xR : xr → PGame) (j : RightMoves (mk xl xr xL xR)) :
Subsequent (xR j) (mk xl xr xL xR) := by
pgame_wf_tac
@[simp] theorem Subsequent.moveRight_mk_left (xL : xl → PGame) (j) :
Subsequent ((xL i).moveRight j) (mk xl xr xL xR) := by
pgame_wf_tac
@[simp] theorem Subsequent.moveRight_mk_right (xR : xr → PGame) (j) :
Subsequent ((xR i).moveRight j) (mk xl xr xL xR) := by
pgame_wf_tac
@[simp] theorem Subsequent.moveLeft_mk_left (xL : xl → PGame) (j) :
Subsequent ((xL i).moveLeft j) (mk xl xr xL xR) := by
pgame_wf_tac
@[simp] theorem Subsequent.moveLeft_mk_right (xR : xr → PGame) (j) :
Subsequent ((xR i).moveLeft j) (mk xl xr xL xR) := by
pgame_wf_tac
-- Porting note: linter claims these lemmas don't simplify?
open Subsequent in attribute [nolint simpNF] mk_left mk_right mk_right'
moveRight_mk_left moveRight_mk_right moveLeft_mk_left moveLeft_mk_right
/-! ### Basic pre-games -/
/-- The pre-game `Zero` is defined by `0 = { | }`. -/
instance : Zero PGame :=
⟨⟨PEmpty, PEmpty, PEmpty.elim, PEmpty.elim⟩⟩
@[simp]
theorem zero_leftMoves : LeftMoves 0 = PEmpty :=
rfl
#align pgame.zero_left_moves SetTheory.PGame.zero_leftMoves
@[simp]
theorem zero_rightMoves : RightMoves 0 = PEmpty :=
rfl
#align pgame.zero_right_moves SetTheory.PGame.zero_rightMoves
instance isEmpty_zero_leftMoves : IsEmpty (LeftMoves 0) :=
instIsEmptyPEmpty
#align pgame.is_empty_zero_left_moves SetTheory.PGame.isEmpty_zero_leftMoves
instance isEmpty_zero_rightMoves : IsEmpty (RightMoves 0) :=
instIsEmptyPEmpty
#align pgame.is_empty_zero_right_moves SetTheory.PGame.isEmpty_zero_rightMoves
instance : Inhabited PGame :=
⟨0⟩
/-- The pre-game `One` is defined by `1 = { 0 | }`. -/
instance instOnePGame : One PGame :=
⟨⟨PUnit, PEmpty, fun _ => 0, PEmpty.elim⟩⟩
@[simp]
theorem one_leftMoves : LeftMoves 1 = PUnit :=
rfl
#align pgame.one_left_moves SetTheory.PGame.one_leftMoves
@[simp]
theorem one_moveLeft (x) : moveLeft 1 x = 0 :=
rfl
#align pgame.one_move_left SetTheory.PGame.one_moveLeft
@[simp]
theorem one_rightMoves : RightMoves 1 = PEmpty :=
rfl
#align pgame.one_right_moves SetTheory.PGame.one_rightMoves
instance uniqueOneLeftMoves : Unique (LeftMoves 1) :=
PUnit.unique
#align pgame.unique_one_left_moves SetTheory.PGame.uniqueOneLeftMoves
instance isEmpty_one_rightMoves : IsEmpty (RightMoves 1) :=
instIsEmptyPEmpty
#align pgame.is_empty_one_right_moves SetTheory.PGame.isEmpty_one_rightMoves
/-! ### Pre-game order relations -/
/-- The less or equal relation on pre-games.
If `0 ≤ x`, then Left can win `x` as the second player. -/
instance le : LE PGame :=
⟨Sym2.GameAdd.fix wf_isOption fun x y le =>
(∀ i, ¬le y (x.moveLeft i) (Sym2.GameAdd.snd_fst <| IsOption.moveLeft i)) ∧
∀ j, ¬le (y.moveRight j) x (Sym2.GameAdd.fst_snd <| IsOption.moveRight j)⟩
/-- The less or fuzzy relation on pre-games.
If `0 ⧏ x`, then Left can win `x` as the first player. -/
def LF (x y : PGame) : Prop :=
¬y ≤ x
#align pgame.lf SetTheory.PGame.LF
@[inherit_doc]
scoped infixl:50 " ⧏ " => PGame.LF
@[simp]
protected theorem not_le {x y : PGame} : ¬x ≤ y ↔ y ⧏ x :=
Iff.rfl
#align pgame.not_le SetTheory.PGame.not_le
@[simp]
theorem not_lf {x y : PGame} : ¬x ⧏ y ↔ y ≤ x :=
Classical.not_not
#align pgame.not_lf SetTheory.PGame.not_lf
theorem _root_.LE.le.not_gf {x y : PGame} : x ≤ y → ¬y ⧏ x :=
not_lf.2
#align has_le.le.not_gf LE.le.not_gf
theorem LF.not_ge {x y : PGame} : x ⧏ y → ¬y ≤ x :=
id
#align pgame.lf.not_ge SetTheory.PGame.LF.not_ge
/-- Definition of `x ≤ y` on pre-games, in terms of `⧏`.
The ordering here is chosen so that `And.left` refer to moves by Left, and `And.right` refer to
moves by Right. -/
theorem le_iff_forall_lf {x y : PGame} :
x ≤ y ↔ (∀ i, x.moveLeft i ⧏ y) ∧ ∀ j, x ⧏ y.moveRight j := by
unfold LE.le le
simp only
rw [Sym2.GameAdd.fix_eq]
rfl
#align pgame.le_iff_forall_lf SetTheory.PGame.le_iff_forall_lf
/-- Definition of `x ≤ y` on pre-games built using the constructor. -/
@[simp]
theorem mk_le_mk {xl xr xL xR yl yr yL yR} :
mk xl xr xL xR ≤ mk yl yr yL yR ↔ (∀ i, xL i ⧏ mk yl yr yL yR) ∧ ∀ j, mk xl xr xL xR ⧏ yR j :=
le_iff_forall_lf
#align pgame.mk_le_mk SetTheory.PGame.mk_le_mk
theorem le_of_forall_lf {x y : PGame} (h₁ : ∀ i, x.moveLeft i ⧏ y) (h₂ : ∀ j, x ⧏ y.moveRight j) :
x ≤ y :=
le_iff_forall_lf.2 ⟨h₁, h₂⟩
#align pgame.le_of_forall_lf SetTheory.PGame.le_of_forall_lf
/-- Definition of `x ⧏ y` on pre-games, in terms of `≤`.
The ordering here is chosen so that `or.inl` refer to moves by Left, and `or.inr` refer to
moves by Right. -/
theorem lf_iff_exists_le {x y : PGame} :
x ⧏ y ↔ (∃ i, x ≤ y.moveLeft i) ∨ ∃ j, x.moveRight j ≤ y := by
rw [LF, le_iff_forall_lf, not_and_or]
simp
#align pgame.lf_iff_exists_le SetTheory.PGame.lf_iff_exists_le
/-- Definition of `x ⧏ y` on pre-games built using the constructor. -/
@[simp]
theorem mk_lf_mk {xl xr xL xR yl yr yL yR} :
mk xl xr xL xR ⧏ mk yl yr yL yR ↔ (∃ i, mk xl xr xL xR ≤ yL i) ∨ ∃ j, xR j ≤ mk yl yr yL yR :=
lf_iff_exists_le
#align pgame.mk_lf_mk SetTheory.PGame.mk_lf_mk
theorem le_or_gf (x y : PGame) : x ≤ y ∨ y ⧏ x := by
rw [← PGame.not_le]
apply em
#align pgame.le_or_gf SetTheory.PGame.le_or_gf
theorem moveLeft_lf_of_le {x y : PGame} (h : x ≤ y) (i) : x.moveLeft i ⧏ y :=
(le_iff_forall_lf.1 h).1 i
#align pgame.move_left_lf_of_le SetTheory.PGame.moveLeft_lf_of_le
alias _root_.LE.le.moveLeft_lf := moveLeft_lf_of_le
#align has_le.le.move_left_lf LE.le.moveLeft_lf
theorem lf_moveRight_of_le {x y : PGame} (h : x ≤ y) (j) : x ⧏ y.moveRight j :=
(le_iff_forall_lf.1 h).2 j
#align pgame.lf_move_right_of_le SetTheory.PGame.lf_moveRight_of_le
alias _root_.LE.le.lf_moveRight := lf_moveRight_of_le
#align has_le.le.lf_move_right LE.le.lf_moveRight
theorem lf_of_moveRight_le {x y : PGame} {j} (h : x.moveRight j ≤ y) : x ⧏ y :=
lf_iff_exists_le.2 <| Or.inr ⟨j, h⟩
#align pgame.lf_of_move_right_le SetTheory.PGame.lf_of_moveRight_le
theorem lf_of_le_moveLeft {x y : PGame} {i} (h : x ≤ y.moveLeft i) : x ⧏ y :=
lf_iff_exists_le.2 <| Or.inl ⟨i, h⟩
#align pgame.lf_of_le_move_left SetTheory.PGame.lf_of_le_moveLeft
theorem lf_of_le_mk {xl xr xL xR y} : mk xl xr xL xR ≤ y → ∀ i, xL i ⧏ y :=
moveLeft_lf_of_le
#align pgame.lf_of_le_mk SetTheory.PGame.lf_of_le_mk
theorem lf_of_mk_le {x yl yr yL yR} : x ≤ mk yl yr yL yR → ∀ j, x ⧏ yR j :=
lf_moveRight_of_le
#align pgame.lf_of_mk_le SetTheory.PGame.lf_of_mk_le
theorem mk_lf_of_le {xl xr y j} (xL) {xR : xr → PGame} : xR j ≤ y → mk xl xr xL xR ⧏ y :=
@lf_of_moveRight_le (mk _ _ _ _) y j
#align pgame.mk_lf_of_le SetTheory.PGame.mk_lf_of_le
theorem lf_mk_of_le {x yl yr} {yL : yl → PGame} (yR) {i} : x ≤ yL i → x ⧏ mk yl yr yL yR :=
@lf_of_le_moveLeft x (mk _ _ _ _) i
#align pgame.lf_mk_of_le SetTheory.PGame.lf_mk_of_le
/- We prove that `x ≤ y → y ≤ z → x ≤ z` inductively, by also simultaneously proving its cyclic
reorderings. This auxiliary lemma is used during said induction. -/
private theorem le_trans_aux {x y z : PGame}
(h₁ : ∀ {i}, y ≤ z → z ≤ x.moveLeft i → y ≤ x.moveLeft i)
(h₂ : ∀ {j}, z.moveRight j ≤ x → x ≤ y → z.moveRight j ≤ y) (hxy : x ≤ y) (hyz : y ≤ z) :
x ≤ z :=
le_of_forall_lf (fun i => PGame.not_le.1 fun h => (h₁ hyz h).not_gf <| hxy.moveLeft_lf i)
fun j => PGame.not_le.1 fun h => (h₂ h hxy).not_gf <| hyz.lf_moveRight j
instance : Preorder PGame :=
{ PGame.le with
le_refl := fun x => by
induction' x with _ _ _ _ IHl IHr
exact
le_of_forall_lf (fun i => lf_of_le_moveLeft (IHl i)) fun i => lf_of_moveRight_le (IHr i)
le_trans := by
suffices
∀ {x y z : PGame},
(x ≤ y → y ≤ z → x ≤ z) ∧ (y ≤ z → z ≤ x → y ≤ x) ∧ (z ≤ x → x ≤ y → z ≤ y) from
fun x y z => this.1
intro x y z
induction' x with xl xr xL xR IHxl IHxr generalizing y z
induction' y with yl yr yL yR IHyl IHyr generalizing z
induction' z with zl zr zL zR IHzl IHzr
exact
⟨le_trans_aux (fun {i} => (IHxl i).2.1) fun {j} => (IHzr j).2.2,
le_trans_aux (fun {i} => (IHyl i).2.2) fun {j} => (IHxr j).1,
le_trans_aux (fun {i} => (IHzl i).1) fun {j} => (IHyr j).2.1⟩
lt := fun x y => x ≤ y ∧ x ⧏ y }
theorem lt_iff_le_and_lf {x y : PGame} : x < y ↔ x ≤ y ∧ x ⧏ y :=
Iff.rfl
#align pgame.lt_iff_le_and_lf SetTheory.PGame.lt_iff_le_and_lf
theorem lt_of_le_of_lf {x y : PGame} (h₁ : x ≤ y) (h₂ : x ⧏ y) : x < y :=
⟨h₁, h₂⟩
#align pgame.lt_of_le_of_lf SetTheory.PGame.lt_of_le_of_lf
theorem lf_of_lt {x y : PGame} (h : x < y) : x ⧏ y :=
h.2
#align pgame.lf_of_lt SetTheory.PGame.lf_of_lt
alias _root_.LT.lt.lf := lf_of_lt
#align has_lt.lt.lf LT.lt.lf
theorem lf_irrefl (x : PGame) : ¬x ⧏ x :=
le_rfl.not_gf
#align pgame.lf_irrefl SetTheory.PGame.lf_irrefl
instance : IsIrrefl _ (· ⧏ ·) :=
⟨lf_irrefl⟩
@[trans]
theorem lf_of_le_of_lf {x y z : PGame} (h₁ : x ≤ y) (h₂ : y ⧏ z) : x ⧏ z := by
rw [← PGame.not_le] at h₂ ⊢
exact fun h₃ => h₂ (h₃.trans h₁)
#align pgame.lf_of_le_of_lf SetTheory.PGame.lf_of_le_of_lf
-- Porting note (#10754): added instance
instance : Trans (· ≤ ·) (· ⧏ ·) (· ⧏ ·) := ⟨lf_of_le_of_lf⟩
@[trans]
theorem lf_of_lf_of_le {x y z : PGame} (h₁ : x ⧏ y) (h₂ : y ≤ z) : x ⧏ z := by
rw [← PGame.not_le] at h₁ ⊢
exact fun h₃ => h₁ (h₂.trans h₃)
#align pgame.lf_of_lf_of_le SetTheory.PGame.lf_of_lf_of_le
-- Porting note (#10754): added instance
instance : Trans (· ⧏ ·) (· ≤ ·) (· ⧏ ·) := ⟨lf_of_lf_of_le⟩
alias _root_.LE.le.trans_lf := lf_of_le_of_lf
#align has_le.le.trans_lf LE.le.trans_lf
alias LF.trans_le := lf_of_lf_of_le
#align pgame.lf.trans_le SetTheory.PGame.LF.trans_le
@[trans]
theorem lf_of_lt_of_lf {x y z : PGame} (h₁ : x < y) (h₂ : y ⧏ z) : x ⧏ z :=
h₁.le.trans_lf h₂
#align pgame.lf_of_lt_of_lf SetTheory.PGame.lf_of_lt_of_lf
@[trans]
theorem lf_of_lf_of_lt {x y z : PGame} (h₁ : x ⧏ y) (h₂ : y < z) : x ⧏ z :=
h₁.trans_le h₂.le
#align pgame.lf_of_lf_of_lt SetTheory.PGame.lf_of_lf_of_lt
alias _root_.LT.lt.trans_lf := lf_of_lt_of_lf
#align has_lt.lt.trans_lf LT.lt.trans_lf
alias LF.trans_lt := lf_of_lf_of_lt
#align pgame.lf.trans_lt SetTheory.PGame.LF.trans_lt
theorem moveLeft_lf {x : PGame} : ∀ i, x.moveLeft i ⧏ x :=
le_rfl.moveLeft_lf
#align pgame.move_left_lf SetTheory.PGame.moveLeft_lf
theorem lf_moveRight {x : PGame} : ∀ j, x ⧏ x.moveRight j :=
le_rfl.lf_moveRight
#align pgame.lf_move_right SetTheory.PGame.lf_moveRight
theorem lf_mk {xl xr} (xL : xl → PGame) (xR : xr → PGame) (i) : xL i ⧏ mk xl xr xL xR :=
@moveLeft_lf (mk _ _ _ _) i
#align pgame.lf_mk SetTheory.PGame.lf_mk
theorem mk_lf {xl xr} (xL : xl → PGame) (xR : xr → PGame) (j) : mk xl xr xL xR ⧏ xR j :=
@lf_moveRight (mk _ _ _ _) j
#align pgame.mk_lf SetTheory.PGame.mk_lf
/-- This special case of `PGame.le_of_forall_lf` is useful when dealing with surreals, where `<` is
preferred over `⧏`. -/
theorem le_of_forall_lt {x y : PGame} (h₁ : ∀ i, x.moveLeft i < y) (h₂ : ∀ j, x < y.moveRight j) :
x ≤ y :=
le_of_forall_lf (fun i => (h₁ i).lf) fun i => (h₂ i).lf
#align pgame.le_of_forall_lt SetTheory.PGame.le_of_forall_lt
/-- The definition of `x ≤ y` on pre-games, in terms of `≤` two moves later. -/
theorem le_def {x y : PGame} :
x ≤ y ↔
(∀ i, (∃ i', x.moveLeft i ≤ y.moveLeft i') ∨ ∃ j, (x.moveLeft i).moveRight j ≤ y) ∧
∀ j, (∃ i, x ≤ (y.moveRight j).moveLeft i) ∨ ∃ j', x.moveRight j' ≤ y.moveRight j := by
rw [le_iff_forall_lf]
conv =>
lhs
simp only [lf_iff_exists_le]
#align pgame.le_def SetTheory.PGame.le_def
/-- The definition of `x ⧏ y` on pre-games, in terms of `⧏` two moves later. -/
theorem lf_def {x y : PGame} :
x ⧏ y ↔
(∃ i, (∀ i', x.moveLeft i' ⧏ y.moveLeft i) ∧ ∀ j, x ⧏ (y.moveLeft i).moveRight j) ∨
∃ j, (∀ i, (x.moveRight j).moveLeft i ⧏ y) ∧ ∀ j', x.moveRight j ⧏ y.moveRight j' := by
rw [lf_iff_exists_le]
conv =>
lhs
simp only [le_iff_forall_lf]
#align pgame.lf_def SetTheory.PGame.lf_def
/-- The definition of `0 ≤ x` on pre-games, in terms of `0 ⧏`. -/
theorem zero_le_lf {x : PGame} : 0 ≤ x ↔ ∀ j, 0 ⧏ x.moveRight j := by
rw [le_iff_forall_lf]
simp
#align pgame.zero_le_lf SetTheory.PGame.zero_le_lf
/-- The definition of `x ≤ 0` on pre-games, in terms of `⧏ 0`. -/
theorem le_zero_lf {x : PGame} : x ≤ 0 ↔ ∀ i, x.moveLeft i ⧏ 0 := by
rw [le_iff_forall_lf]
simp
#align pgame.le_zero_lf SetTheory.PGame.le_zero_lf
/-- The definition of `0 ⧏ x` on pre-games, in terms of `0 ≤`. -/
theorem zero_lf_le {x : PGame} : 0 ⧏ x ↔ ∃ i, 0 ≤ x.moveLeft i := by
rw [lf_iff_exists_le]
simp
#align pgame.zero_lf_le SetTheory.PGame.zero_lf_le
/-- The definition of `x ⧏ 0` on pre-games, in terms of `≤ 0`. -/
theorem lf_zero_le {x : PGame} : x ⧏ 0 ↔ ∃ j, x.moveRight j ≤ 0 := by
rw [lf_iff_exists_le]
simp
#align pgame.lf_zero_le SetTheory.PGame.lf_zero_le
/-- The definition of `0 ≤ x` on pre-games, in terms of `0 ≤` two moves later. -/
theorem zero_le {x : PGame} : 0 ≤ x ↔ ∀ j, ∃ i, 0 ≤ (x.moveRight j).moveLeft i := by
rw [le_def]
simp
#align pgame.zero_le SetTheory.PGame.zero_le
/-- The definition of `x ≤ 0` on pre-games, in terms of `≤ 0` two moves later. -/
theorem le_zero {x : PGame} : x ≤ 0 ↔ ∀ i, ∃ j, (x.moveLeft i).moveRight j ≤ 0 := by
rw [le_def]
simp
#align pgame.le_zero SetTheory.PGame.le_zero
/-- The definition of `0 ⧏ x` on pre-games, in terms of `0 ⧏` two moves later. -/
theorem zero_lf {x : PGame} : 0 ⧏ x ↔ ∃ i, ∀ j, 0 ⧏ (x.moveLeft i).moveRight j := by
rw [lf_def]
simp
#align pgame.zero_lf SetTheory.PGame.zero_lf
/-- The definition of `x ⧏ 0` on pre-games, in terms of `⧏ 0` two moves later. -/
theorem lf_zero {x : PGame} : x ⧏ 0 ↔ ∃ j, ∀ i, (x.moveRight j).moveLeft i ⧏ 0 := by
rw [lf_def]
simp
#align pgame.lf_zero SetTheory.PGame.lf_zero
@[simp]
theorem zero_le_of_isEmpty_rightMoves (x : PGame) [IsEmpty x.RightMoves] : 0 ≤ x :=
zero_le.2 isEmptyElim
#align pgame.zero_le_of_is_empty_right_moves SetTheory.PGame.zero_le_of_isEmpty_rightMoves
@[simp]
theorem le_zero_of_isEmpty_leftMoves (x : PGame) [IsEmpty x.LeftMoves] : x ≤ 0 :=
le_zero.2 isEmptyElim
#align pgame.le_zero_of_is_empty_left_moves SetTheory.PGame.le_zero_of_isEmpty_leftMoves
/-- Given a game won by the right player when they play second, provide a response to any move by
left. -/
noncomputable def rightResponse {x : PGame} (h : x ≤ 0) (i : x.LeftMoves) :
(x.moveLeft i).RightMoves :=
Classical.choose <| (le_zero.1 h) i
#align pgame.right_response SetTheory.PGame.rightResponse
/-- Show that the response for right provided by `rightResponse` preserves the right-player-wins
condition. -/
theorem rightResponse_spec {x : PGame} (h : x ≤ 0) (i : x.LeftMoves) :
(x.moveLeft i).moveRight (rightResponse h i) ≤ 0 :=
Classical.choose_spec <| (le_zero.1 h) i
#align pgame.right_response_spec SetTheory.PGame.rightResponse_spec
/-- Given a game won by the left player when they play second, provide a response to any move by
right. -/
noncomputable def leftResponse {x : PGame} (h : 0 ≤ x) (j : x.RightMoves) :
(x.moveRight j).LeftMoves :=
Classical.choose <| (zero_le.1 h) j
#align pgame.left_response SetTheory.PGame.leftResponse
/-- Show that the response for left provided by `leftResponse` preserves the left-player-wins
condition. -/
theorem leftResponse_spec {x : PGame} (h : 0 ≤ x) (j : x.RightMoves) :
0 ≤ (x.moveRight j).moveLeft (leftResponse h j) :=
Classical.choose_spec <| (zero_le.1 h) j
#align pgame.left_response_spec SetTheory.PGame.leftResponse_spec
#noalign pgame.upper_bound
#noalign pgame.upper_bound_right_moves_empty
#noalign pgame.le_upper_bound
#noalign pgame.upper_bound_mem_upper_bounds
/-- A small family of pre-games is bounded above. -/
lemma bddAbove_range_of_small [Small.{u} ι] (f : ι → PGame.{u}) : BddAbove (Set.range f) := by
let x : PGame.{u} := ⟨Σ i, (f $ (equivShrink.{u} ι).symm i).LeftMoves, PEmpty,
fun x ↦ moveLeft _ x.2, PEmpty.elim⟩
refine ⟨x, Set.forall_mem_range.2 fun i ↦ ?_⟩
rw [← (equivShrink ι).symm_apply_apply i, le_iff_forall_lf]
simpa [x] using fun j ↦ @moveLeft_lf x ⟨equivShrink ι i, j⟩
/-- A small set of pre-games is bounded above. -/
lemma bddAbove_of_small (s : Set PGame.{u}) [Small.{u} s] : BddAbove s := by
simpa using bddAbove_range_of_small (Subtype.val : s → PGame.{u})
#align pgame.bdd_above_of_small SetTheory.PGame.bddAbove_of_small
#noalign pgame.lower_bound
#noalign pgame.lower_bound_left_moves_empty
#noalign pgame.lower_bound_le
#noalign pgame.lower_bound_mem_lower_bounds
/-- A small family of pre-games is bounded below. -/
lemma bddBelow_range_of_small [Small.{u} ι] (f : ι → PGame.{u}) : BddBelow (Set.range f) := by
let x : PGame.{u} := ⟨PEmpty, Σ i, (f $ (equivShrink.{u} ι).symm i).RightMoves, PEmpty.elim,
fun x ↦ moveRight _ x.2⟩
refine ⟨x, Set.forall_mem_range.2 fun i ↦ ?_⟩
rw [← (equivShrink ι).symm_apply_apply i, le_iff_forall_lf]
simpa [x] using fun j ↦ @lf_moveRight x ⟨equivShrink ι i, j⟩
/-- A small set of pre-games is bounded below. -/
lemma bddBelow_of_small (s : Set PGame.{u}) [Small.{u} s] : BddBelow s := by
simpa using bddBelow_range_of_small (Subtype.val : s → PGame.{u})
#align pgame.bdd_below_of_small SetTheory.PGame.bddBelow_of_small
/-- The equivalence relation on pre-games. Two pre-games `x`, `y` are equivalent if `x ≤ y` and
`y ≤ x`.
If `x ≈ 0`, then the second player can always win `x`. -/
def Equiv (x y : PGame) : Prop :=
x ≤ y ∧ y ≤ x
#align pgame.equiv SetTheory.PGame.Equiv
-- Porting note: deleted the scoped notation due to notation overloading with the setoid
-- instance and this causes the PGame.equiv docstring to not show up on hover.
instance : IsEquiv _ PGame.Equiv where
refl _ := ⟨le_rfl, le_rfl⟩
trans := fun _ _ _ ⟨xy, yx⟩ ⟨yz, zy⟩ => ⟨xy.trans yz, zy.trans yx⟩
symm _ _ := And.symm
-- Porting note: moved the setoid instance from Basic.lean to here
instance setoid : Setoid PGame :=
⟨Equiv, refl, symm, Trans.trans⟩
#align pgame.setoid SetTheory.PGame.setoid
theorem Equiv.le {x y : PGame} (h : x ≈ y) : x ≤ y :=
h.1
#align pgame.equiv.le SetTheory.PGame.Equiv.le
theorem Equiv.ge {x y : PGame} (h : x ≈ y) : y ≤ x :=
h.2
#align pgame.equiv.ge SetTheory.PGame.Equiv.ge
@[refl, simp]
theorem equiv_rfl {x : PGame} : x ≈ x :=
refl x
#align pgame.equiv_rfl SetTheory.PGame.equiv_rfl
theorem equiv_refl (x : PGame) : x ≈ x :=
refl x
#align pgame.equiv_refl SetTheory.PGame.equiv_refl
@[symm]
protected theorem Equiv.symm {x y : PGame} : (x ≈ y) → (y ≈ x) :=
symm
#align pgame.equiv.symm SetTheory.PGame.Equiv.symm
@[trans]
protected theorem Equiv.trans {x y z : PGame} : (x ≈ y) → (y ≈ z) → (x ≈ z) :=
_root_.trans
#align pgame.equiv.trans SetTheory.PGame.Equiv.trans
protected theorem equiv_comm {x y : PGame} : (x ≈ y) ↔ (y ≈ x) :=
comm
#align pgame.equiv_comm SetTheory.PGame.equiv_comm
theorem equiv_of_eq {x y : PGame} (h : x = y) : x ≈ y := by subst h; rfl
#align pgame.equiv_of_eq SetTheory.PGame.equiv_of_eq
@[trans]
theorem le_of_le_of_equiv {x y z : PGame} (h₁ : x ≤ y) (h₂ : y ≈ z) : x ≤ z :=
h₁.trans h₂.1
#align pgame.le_of_le_of_equiv SetTheory.PGame.le_of_le_of_equiv
instance : Trans
((· ≤ ·) : PGame → PGame → Prop)
((· ≈ ·) : PGame → PGame → Prop)
((· ≤ ·) : PGame → PGame → Prop) where
trans := le_of_le_of_equiv
@[trans]
theorem le_of_equiv_of_le {x y z : PGame} (h₁ : x ≈ y) : y ≤ z → x ≤ z :=
h₁.1.trans
#align pgame.le_of_equiv_of_le SetTheory.PGame.le_of_equiv_of_le
instance : Trans
((· ≈ ·) : PGame → PGame → Prop)
((· ≤ ·) : PGame → PGame → Prop)
((· ≤ ·) : PGame → PGame → Prop) where
trans := le_of_equiv_of_le
theorem LF.not_equiv {x y : PGame} (h : x ⧏ y) : ¬(x ≈ y) := fun h' => h.not_ge h'.2
#align pgame.lf.not_equiv SetTheory.PGame.LF.not_equiv
theorem LF.not_equiv' {x y : PGame} (h : x ⧏ y) : ¬(y ≈ x) := fun h' => h.not_ge h'.1
#align pgame.lf.not_equiv' SetTheory.PGame.LF.not_equiv'
theorem LF.not_gt {x y : PGame} (h : x ⧏ y) : ¬y < x := fun h' => h.not_ge h'.le
#align pgame.lf.not_gt SetTheory.PGame.LF.not_gt
theorem le_congr_imp {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) (h : x₁ ≤ y₁) : x₂ ≤ y₂ :=
hx.2.trans (h.trans hy.1)
#align pgame.le_congr_imp SetTheory.PGame.le_congr_imp
theorem le_congr {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ ≤ y₁ ↔ x₂ ≤ y₂ :=
⟨le_congr_imp hx hy, le_congr_imp (Equiv.symm hx) (Equiv.symm hy)⟩
#align pgame.le_congr SetTheory.PGame.le_congr
theorem le_congr_left {x₁ x₂ y : PGame} (hx : x₁ ≈ x₂) : x₁ ≤ y ↔ x₂ ≤ y :=
le_congr hx equiv_rfl
#align pgame.le_congr_left SetTheory.PGame.le_congr_left
theorem le_congr_right {x y₁ y₂ : PGame} (hy : y₁ ≈ y₂) : x ≤ y₁ ↔ x ≤ y₂ :=
le_congr equiv_rfl hy
#align pgame.le_congr_right SetTheory.PGame.le_congr_right
theorem lf_congr {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ ⧏ y₁ ↔ x₂ ⧏ y₂ :=
PGame.not_le.symm.trans <| (not_congr (le_congr hy hx)).trans PGame.not_le
#align pgame.lf_congr SetTheory.PGame.lf_congr
theorem lf_congr_imp {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ ⧏ y₁ → x₂ ⧏ y₂ :=
(lf_congr hx hy).1
#align pgame.lf_congr_imp SetTheory.PGame.lf_congr_imp
theorem lf_congr_left {x₁ x₂ y : PGame} (hx : x₁ ≈ x₂) : x₁ ⧏ y ↔ x₂ ⧏ y :=
lf_congr hx equiv_rfl
#align pgame.lf_congr_left SetTheory.PGame.lf_congr_left
theorem lf_congr_right {x y₁ y₂ : PGame} (hy : y₁ ≈ y₂) : x ⧏ y₁ ↔ x ⧏ y₂ :=
lf_congr equiv_rfl hy
#align pgame.lf_congr_right SetTheory.PGame.lf_congr_right
@[trans]
theorem lf_of_lf_of_equiv {x y z : PGame} (h₁ : x ⧏ y) (h₂ : y ≈ z) : x ⧏ z :=
lf_congr_imp equiv_rfl h₂ h₁
#align pgame.lf_of_lf_of_equiv SetTheory.PGame.lf_of_lf_of_equiv
@[trans]
theorem lf_of_equiv_of_lf {x y z : PGame} (h₁ : x ≈ y) : y ⧏ z → x ⧏ z :=
lf_congr_imp (Equiv.symm h₁) equiv_rfl
#align pgame.lf_of_equiv_of_lf SetTheory.PGame.lf_of_equiv_of_lf
@[trans]
theorem lt_of_lt_of_equiv {x y z : PGame} (h₁ : x < y) (h₂ : y ≈ z) : x < z :=
h₁.trans_le h₂.1
#align pgame.lt_of_lt_of_equiv SetTheory.PGame.lt_of_lt_of_equiv
@[trans]
theorem lt_of_equiv_of_lt {x y z : PGame} (h₁ : x ≈ y) : y < z → x < z :=
h₁.1.trans_lt
#align pgame.lt_of_equiv_of_lt SetTheory.PGame.lt_of_equiv_of_lt
instance : Trans
((· ≈ ·) : PGame → PGame → Prop)
((· < ·) : PGame → PGame → Prop)
((· < ·) : PGame → PGame → Prop) where
trans := lt_of_equiv_of_lt
theorem lt_congr_imp {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) (h : x₁ < y₁) : x₂ < y₂ :=
hx.2.trans_lt (h.trans_le hy.1)
#align pgame.lt_congr_imp SetTheory.PGame.lt_congr_imp
theorem lt_congr {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ < y₁ ↔ x₂ < y₂ :=
⟨lt_congr_imp hx hy, lt_congr_imp (Equiv.symm hx) (Equiv.symm hy)⟩
#align pgame.lt_congr SetTheory.PGame.lt_congr
theorem lt_congr_left {x₁ x₂ y : PGame} (hx : x₁ ≈ x₂) : x₁ < y ↔ x₂ < y :=
lt_congr hx equiv_rfl
#align pgame.lt_congr_left SetTheory.PGame.lt_congr_left
theorem lt_congr_right {x y₁ y₂ : PGame} (hy : y₁ ≈ y₂) : x < y₁ ↔ x < y₂ :=
lt_congr equiv_rfl hy
#align pgame.lt_congr_right SetTheory.PGame.lt_congr_right
theorem lt_or_equiv_of_le {x y : PGame} (h : x ≤ y) : x < y ∨ (x ≈ y) :=
and_or_left.mp ⟨h, (em <| y ≤ x).symm.imp_left PGame.not_le.1⟩
#align pgame.lt_or_equiv_of_le SetTheory.PGame.lt_or_equiv_of_le
theorem lf_or_equiv_or_gf (x y : PGame) : x ⧏ y ∨ (x ≈ y) ∨ y ⧏ x := by
by_cases h : x ⧏ y
· exact Or.inl h
· right
cases' lt_or_equiv_of_le (PGame.not_lf.1 h) with h' h'
· exact Or.inr h'.lf
· exact Or.inl (Equiv.symm h')
#align pgame.lf_or_equiv_or_gf SetTheory.PGame.lf_or_equiv_or_gf
theorem equiv_congr_left {y₁ y₂ : PGame} : (y₁ ≈ y₂) ↔ ∀ x₁, (x₁ ≈ y₁) ↔ (x₁ ≈ y₂) :=
⟨fun h _ => ⟨fun h' => Equiv.trans h' h, fun h' => Equiv.trans h' (Equiv.symm h)⟩,
fun h => (h y₁).1 <| equiv_rfl⟩
#align pgame.equiv_congr_left SetTheory.PGame.equiv_congr_left
theorem equiv_congr_right {x₁ x₂ : PGame} : (x₁ ≈ x₂) ↔ ∀ y₁, (x₁ ≈ y₁) ↔ (x₂ ≈ y₁) :=
⟨fun h _ => ⟨fun h' => Equiv.trans (Equiv.symm h) h', fun h' => Equiv.trans h h'⟩,
fun h => (h x₂).2 <| equiv_rfl⟩
#align pgame.equiv_congr_right SetTheory.PGame.equiv_congr_right
theorem equiv_of_mk_equiv {x y : PGame} (L : x.LeftMoves ≃ y.LeftMoves)
(R : x.RightMoves ≃ y.RightMoves) (hl : ∀ i, x.moveLeft i ≈ y.moveLeft (L i))
(hr : ∀ j, x.moveRight j ≈ y.moveRight (R j)) : x ≈ y := by
constructor <;> rw [le_def]
· exact ⟨fun i => Or.inl ⟨_, (hl i).1⟩, fun j => Or.inr ⟨_, by simpa using (hr (R.symm j)).1⟩⟩
· exact ⟨fun i => Or.inl ⟨_, by simpa using (hl (L.symm i)).2⟩, fun j => Or.inr ⟨_, (hr j).2⟩⟩
#align pgame.equiv_of_mk_equiv SetTheory.PGame.equiv_of_mk_equiv
/-- The fuzzy, confused, or incomparable relation on pre-games.
If `x ‖ 0`, then the first player can always win `x`. -/
def Fuzzy (x y : PGame) : Prop :=
x ⧏ y ∧ y ⧏ x
#align pgame.fuzzy SetTheory.PGame.Fuzzy
@[inherit_doc]
scoped infixl:50 " ‖ " => PGame.Fuzzy
@[symm]
theorem Fuzzy.swap {x y : PGame} : x ‖ y → y ‖ x :=
And.symm
#align pgame.fuzzy.swap SetTheory.PGame.Fuzzy.swap
instance : IsSymm _ (· ‖ ·) :=
⟨fun _ _ => Fuzzy.swap⟩
theorem Fuzzy.swap_iff {x y : PGame} : x ‖ y ↔ y ‖ x :=
⟨Fuzzy.swap, Fuzzy.swap⟩
#align pgame.fuzzy.swap_iff SetTheory.PGame.Fuzzy.swap_iff
theorem fuzzy_irrefl (x : PGame) : ¬x ‖ x := fun h => lf_irrefl x h.1
#align pgame.fuzzy_irrefl SetTheory.PGame.fuzzy_irrefl
instance : IsIrrefl _ (· ‖ ·) :=
⟨fuzzy_irrefl⟩
theorem lf_iff_lt_or_fuzzy {x y : PGame} : x ⧏ y ↔ x < y ∨ x ‖ y := by
simp only [lt_iff_le_and_lf, Fuzzy, ← PGame.not_le]
tauto
#align pgame.lf_iff_lt_or_fuzzy SetTheory.PGame.lf_iff_lt_or_fuzzy
theorem lf_of_fuzzy {x y : PGame} (h : x ‖ y) : x ⧏ y :=
lf_iff_lt_or_fuzzy.2 (Or.inr h)
#align pgame.lf_of_fuzzy SetTheory.PGame.lf_of_fuzzy
alias Fuzzy.lf := lf_of_fuzzy
#align pgame.fuzzy.lf SetTheory.PGame.Fuzzy.lf
theorem lt_or_fuzzy_of_lf {x y : PGame} : x ⧏ y → x < y ∨ x ‖ y :=
lf_iff_lt_or_fuzzy.1
#align pgame.lt_or_fuzzy_of_lf SetTheory.PGame.lt_or_fuzzy_of_lf
theorem Fuzzy.not_equiv {x y : PGame} (h : x ‖ y) : ¬(x ≈ y) := fun h' => h'.1.not_gf h.2
#align pgame.fuzzy.not_equiv SetTheory.PGame.Fuzzy.not_equiv
theorem Fuzzy.not_equiv' {x y : PGame} (h : x ‖ y) : ¬(y ≈ x) := fun h' => h'.2.not_gf h.2
#align pgame.fuzzy.not_equiv' SetTheory.PGame.Fuzzy.not_equiv'
theorem not_fuzzy_of_le {x y : PGame} (h : x ≤ y) : ¬x ‖ y := fun h' => h'.2.not_ge h
#align pgame.not_fuzzy_of_le SetTheory.PGame.not_fuzzy_of_le
theorem not_fuzzy_of_ge {x y : PGame} (h : y ≤ x) : ¬x ‖ y := fun h' => h'.1.not_ge h
#align pgame.not_fuzzy_of_ge SetTheory.PGame.not_fuzzy_of_ge
theorem Equiv.not_fuzzy {x y : PGame} (h : x ≈ y) : ¬x ‖ y :=
not_fuzzy_of_le h.1
#align pgame.equiv.not_fuzzy SetTheory.PGame.Equiv.not_fuzzy
theorem Equiv.not_fuzzy' {x y : PGame} (h : x ≈ y) : ¬y ‖ x :=
not_fuzzy_of_le h.2
#align pgame.equiv.not_fuzzy' SetTheory.PGame.Equiv.not_fuzzy'
theorem fuzzy_congr {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ ‖ y₁ ↔ x₂ ‖ y₂ :=
show _ ∧ _ ↔ _ ∧ _ by rw [lf_congr hx hy, lf_congr hy hx]
#align pgame.fuzzy_congr SetTheory.PGame.fuzzy_congr
theorem fuzzy_congr_imp {x₁ y₁ x₂ y₂ : PGame} (hx : x₁ ≈ x₂) (hy : y₁ ≈ y₂) : x₁ ‖ y₁ → x₂ ‖ y₂ :=
(fuzzy_congr hx hy).1
#align pgame.fuzzy_congr_imp SetTheory.PGame.fuzzy_congr_imp
theorem fuzzy_congr_left {x₁ x₂ y : PGame} (hx : x₁ ≈ x₂) : x₁ ‖ y ↔ x₂ ‖ y :=
fuzzy_congr hx equiv_rfl
#align pgame.fuzzy_congr_left SetTheory.PGame.fuzzy_congr_left
theorem fuzzy_congr_right {x y₁ y₂ : PGame} (hy : y₁ ≈ y₂) : x ‖ y₁ ↔ x ‖ y₂ :=
fuzzy_congr equiv_rfl hy
#align pgame.fuzzy_congr_right SetTheory.PGame.fuzzy_congr_right
@[trans]
theorem fuzzy_of_fuzzy_of_equiv {x y z : PGame} (h₁ : x ‖ y) (h₂ : y ≈ z) : x ‖ z :=
(fuzzy_congr_right h₂).1 h₁
#align pgame.fuzzy_of_fuzzy_of_equiv SetTheory.PGame.fuzzy_of_fuzzy_of_equiv
@[trans]
theorem fuzzy_of_equiv_of_fuzzy {x y z : PGame} (h₁ : x ≈ y) (h₂ : y ‖ z) : x ‖ z :=
(fuzzy_congr_left h₁).2 h₂
#align pgame.fuzzy_of_equiv_of_fuzzy SetTheory.PGame.fuzzy_of_equiv_of_fuzzy
/-- Exactly one of the following is true (although we don't prove this here). -/
theorem lt_or_equiv_or_gt_or_fuzzy (x y : PGame) : x < y ∨ (x ≈ y) ∨ y < x ∨ x ‖ y := by
cases' le_or_gf x y with h₁ h₁ <;> cases' le_or_gf y x with h₂ h₂
· right
left
exact ⟨h₁, h₂⟩
· left
exact ⟨h₁, h₂⟩
· right
right
left
exact ⟨h₂, h₁⟩
· right
right
right
exact ⟨h₂, h₁⟩
#align pgame.lt_or_equiv_or_gt_or_fuzzy SetTheory.PGame.lt_or_equiv_or_gt_or_fuzzy
theorem lt_or_equiv_or_gf (x y : PGame) : x < y ∨ (x ≈ y) ∨ y ⧏ x := by
rw [lf_iff_lt_or_fuzzy, Fuzzy.swap_iff]
exact lt_or_equiv_or_gt_or_fuzzy x y
#align pgame.lt_or_equiv_or_gf SetTheory.PGame.lt_or_equiv_or_gf
/-! ### Relabellings -/
/-- `Relabelling x y` says that `x` and `y` are really the same game, just dressed up differently.
Specifically, there is a bijection between the moves for Left in `x` and in `y`, and similarly
for Right, and under these bijections we inductively have `Relabelling`s for the consequent games.
-/
inductive Relabelling : PGame.{u} → PGame.{u} → Type (u + 1)
|
mk :
∀ {x y : PGame} (L : x.LeftMoves ≃ y.LeftMoves) (R : x.RightMoves ≃ y.RightMoves),
(∀ i, Relabelling (x.moveLeft i) (y.moveLeft (L i))) →
(∀ j, Relabelling (x.moveRight j) (y.moveRight (R j))) → Relabelling x y
#align pgame.relabelling SetTheory.PGame.Relabelling
@[inherit_doc]
scoped infixl:50 " ≡r " => PGame.Relabelling
namespace Relabelling
variable {x y : PGame.{u}}
/-- A constructor for relabellings swapping the equivalences. -/
def mk' (L : y.LeftMoves ≃ x.LeftMoves) (R : y.RightMoves ≃ x.RightMoves)
(hL : ∀ i, x.moveLeft (L i) ≡r y.moveLeft i) (hR : ∀ j, x.moveRight (R j) ≡r y.moveRight j) :
x ≡r y :=
⟨L.symm, R.symm, fun i => by simpa using hL (L.symm i), fun j => by simpa using hR (R.symm j)⟩
#align pgame.relabelling.mk' SetTheory.PGame.Relabelling.mk'
/-- The equivalence between left moves of `x` and `y` given by the relabelling. -/
def leftMovesEquiv : x ≡r y → x.LeftMoves ≃ y.LeftMoves
| ⟨L,_, _,_⟩ => L
#align pgame.relabelling.left_moves_equiv SetTheory.PGame.Relabelling.leftMovesEquiv
@[simp]
theorem mk_leftMovesEquiv {x y L R hL hR} : (@Relabelling.mk x y L R hL hR).leftMovesEquiv = L :=
rfl
#align pgame.relabelling.mk_left_moves_equiv SetTheory.PGame.Relabelling.mk_leftMovesEquiv
@[simp]
theorem mk'_leftMovesEquiv {x y L R hL hR} :
(@Relabelling.mk' x y L R hL hR).leftMovesEquiv = L.symm :=
rfl
#align pgame.relabelling.mk'_left_moves_equiv SetTheory.PGame.Relabelling.mk'_leftMovesEquiv
/-- The equivalence between right moves of `x` and `y` given by the relabelling. -/
def rightMovesEquiv : x ≡r y → x.RightMoves ≃ y.RightMoves
| ⟨_, R, _, _⟩ => R
#align pgame.relabelling.right_moves_equiv SetTheory.PGame.Relabelling.rightMovesEquiv
@[simp]
theorem mk_rightMovesEquiv {x y L R hL hR} : (@Relabelling.mk x y L R hL hR).rightMovesEquiv = R :=
rfl
#align pgame.relabelling.mk_right_moves_equiv SetTheory.PGame.Relabelling.mk_rightMovesEquiv
@[simp]
theorem mk'_rightMovesEquiv {x y L R hL hR} :
(@Relabelling.mk' x y L R hL hR).rightMovesEquiv = R.symm :=
rfl
#align pgame.relabelling.mk'_right_moves_equiv SetTheory.PGame.Relabelling.mk'_rightMovesEquiv
/-- A left move of `x` is a relabelling of a left move of `y`. -/
def moveLeft : ∀ (r : x ≡r y) (i : x.LeftMoves), x.moveLeft i ≡r y.moveLeft (r.leftMovesEquiv i)
| ⟨_, _, hL, _⟩ => hL
#align pgame.relabelling.move_left SetTheory.PGame.Relabelling.moveLeft
/-- A left move of `y` is a relabelling of a left move of `x`. -/
def moveLeftSymm :
∀ (r : x ≡r y) (i : y.LeftMoves), x.moveLeft (r.leftMovesEquiv.symm i) ≡r y.moveLeft i
| ⟨L, R, hL, hR⟩, i => by simpa using hL (L.symm i)
#align pgame.relabelling.move_left_symm SetTheory.PGame.Relabelling.moveLeftSymm
/-- A right move of `x` is a relabelling of a right move of `y`. -/
def moveRight :
∀ (r : x ≡r y) (i : x.RightMoves), x.moveRight i ≡r y.moveRight (r.rightMovesEquiv i)
| ⟨_, _, _, hR⟩ => hR
#align pgame.relabelling.move_right SetTheory.PGame.Relabelling.moveRight
/-- A right move of `y` is a relabelling of a right move of `x`. -/
def moveRightSymm :
∀ (r : x ≡r y) (i : y.RightMoves), x.moveRight (r.rightMovesEquiv.symm i) ≡r y.moveRight i
| ⟨L, R, hL, hR⟩, i => by simpa using hR (R.symm i)
#align pgame.relabelling.move_right_symm SetTheory.PGame.Relabelling.moveRightSymm
/-- The identity relabelling. -/
@[refl]
def refl (x : PGame) : x ≡r x :=
⟨Equiv.refl _, Equiv.refl _, fun i => refl _, fun j => refl _⟩
termination_by x
#align pgame.relabelling.refl SetTheory.PGame.Relabelling.refl
instance (x : PGame) : Inhabited (x ≡r x) :=
⟨refl _⟩
/-- Flip a relabelling. -/
@[symm]
def symm : ∀ {x y : PGame}, x ≡r y → y ≡r x
| _, _, ⟨L, R, hL, hR⟩ => mk' L R (fun i => (hL i).symm) fun j => (hR j).symm
#align pgame.relabelling.symm SetTheory.PGame.Relabelling.symm
theorem le {x y : PGame} (r : x ≡r y) : x ≤ y :=
le_def.2
⟨fun i => Or.inl ⟨_, (r.moveLeft i).le⟩, fun j =>
Or.inr ⟨_, (r.moveRightSymm j).le⟩⟩
termination_by x
#align pgame.relabelling.le SetTheory.PGame.Relabelling.le
theorem ge {x y : PGame} (r : x ≡r y) : y ≤ x :=
r.symm.le
#align pgame.relabelling.ge SetTheory.PGame.Relabelling.ge
/-- A relabelling lets us prove equivalence of games. -/
theorem equiv (r : x ≡r y) : x ≈ y :=
⟨r.le, r.ge⟩
#align pgame.relabelling.equiv SetTheory.PGame.Relabelling.equiv
/-- Transitivity of relabelling. -/
@[trans]
def trans : ∀ {x y z : PGame}, x ≡r y → y ≡r z → x ≡r z
| _, _, _, ⟨L₁, R₁, hL₁, hR₁⟩, ⟨L₂, R₂, hL₂, hR₂⟩ =>
⟨L₁.trans L₂, R₁.trans R₂, fun i => (hL₁ i).trans (hL₂ _), fun j => (hR₁ j).trans (hR₂ _)⟩
#align pgame.relabelling.trans SetTheory.PGame.Relabelling.trans
/-- Any game without left or right moves is a relabelling of 0. -/
def isEmpty (x : PGame) [IsEmpty x.LeftMoves] [IsEmpty x.RightMoves] : x ≡r 0 :=
⟨Equiv.equivPEmpty _, Equiv.equivOfIsEmpty _ _, isEmptyElim, isEmptyElim⟩
#align pgame.relabelling.is_empty SetTheory.PGame.Relabelling.isEmpty
end Relabelling
theorem Equiv.isEmpty (x : PGame) [IsEmpty x.LeftMoves] [IsEmpty x.RightMoves] : x ≈ 0 :=
(Relabelling.isEmpty x).equiv
#align pgame.equiv.is_empty SetTheory.PGame.Equiv.isEmpty
instance {x y : PGame} : Coe (x ≡r y) (x ≈ y) :=
⟨Relabelling.equiv⟩
/-- Replace the types indexing the next moves for Left and Right by equivalent types. -/
def relabel {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves) : PGame :=
⟨xl', xr', x.moveLeft ∘ el, x.moveRight ∘ er⟩
#align pgame.relabel SetTheory.PGame.relabel
@[simp]
theorem relabel_moveLeft' {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves)
(i : xl') : moveLeft (relabel el er) i = x.moveLeft (el i) :=
rfl
#align pgame.relabel_move_left' SetTheory.PGame.relabel_moveLeft'
theorem relabel_moveLeft {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves)
(i : x.LeftMoves) : moveLeft (relabel el er) (el.symm i) = x.moveLeft i := by simp
#align pgame.relabel_move_left SetTheory.PGame.relabel_moveLeft
@[simp]
theorem relabel_moveRight' {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves)
(j : xr') : moveRight (relabel el er) j = x.moveRight (er j) :=
rfl
#align pgame.relabel_move_right' SetTheory.PGame.relabel_moveRight'
theorem relabel_moveRight {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves)
(j : x.RightMoves) : moveRight (relabel el er) (er.symm j) = x.moveRight j := by simp
#align pgame.relabel_move_right SetTheory.PGame.relabel_moveRight
/-- The game obtained by relabelling the next moves is a relabelling of the original game. -/
def relabelRelabelling {x : PGame} {xl' xr'} (el : xl' ≃ x.LeftMoves) (er : xr' ≃ x.RightMoves) :
x ≡r relabel el er :=
-- Porting note: needed to add `rfl`
Relabelling.mk' el er (fun i => by simp; rfl) (fun j => by simp; rfl)
#align pgame.relabel_relabelling SetTheory.PGame.relabelRelabelling
/-! ### Negation -/
/-- The negation of `{L | R}` is `{-R | -L}`. -/
def neg : PGame → PGame
| ⟨l, r, L, R⟩ => ⟨r, l, fun i => neg (R i), fun i => neg (L i)⟩
#align pgame.neg SetTheory.PGame.neg
instance : Neg PGame :=
⟨neg⟩
@[simp]
theorem neg_def {xl xr xL xR} : -mk xl xr xL xR = mk xr xl (fun j => -xR j) fun i => -xL i :=
rfl
#align pgame.neg_def SetTheory.PGame.neg_def
instance : InvolutiveNeg PGame :=
{ inferInstanceAs (Neg PGame) with
neg_neg := fun x => by
induction' x with xl xr xL xR ihL ihR
simp_rw [neg_def, ihL, ihR] }
instance : NegZeroClass PGame :=
{ inferInstanceAs (Zero PGame), inferInstanceAs (Neg PGame) with
neg_zero := by
dsimp [Zero.zero, Neg.neg, neg]
congr <;> funext i <;> cases i }
@[simp]
theorem neg_ofLists (L R : List PGame) :
-ofLists L R = ofLists (R.map fun x => -x) (L.map fun x => -x) := by
simp only [ofLists, neg_def, List.get_map, mk.injEq, List.length_map, true_and]
constructor
all_goals
apply hfunext
· simp
· rintro ⟨⟨a, ha⟩⟩ ⟨⟨b, hb⟩⟩ h
have :
∀ {m n} (_ : m = n) {b : ULift (Fin m)} {c : ULift (Fin n)} (_ : HEq b c),
(b.down : ℕ) = ↑c.down := by
rintro m n rfl b c
simp only [heq_eq_eq]
rintro rfl
rfl
congr 5
exact this (List.length_map _ _).symm h
#align pgame.neg_of_lists SetTheory.PGame.neg_ofLists
theorem isOption_neg {x y : PGame} : IsOption x (-y) ↔ IsOption (-x) y := by
rw [isOption_iff, isOption_iff, or_comm]
cases y;
apply or_congr <;>
· apply exists_congr
intro
rw [neg_eq_iff_eq_neg]
rfl
#align pgame.is_option_neg SetTheory.PGame.isOption_neg
@[simp]
theorem isOption_neg_neg {x y : PGame} : IsOption (-x) (-y) ↔ IsOption x y := by
rw [isOption_neg, neg_neg]
#align pgame.is_option_neg_neg SetTheory.PGame.isOption_neg_neg
theorem leftMoves_neg : ∀ x : PGame, (-x).LeftMoves = x.RightMoves
| ⟨_, _, _, _⟩ => rfl
#align pgame.left_moves_neg SetTheory.PGame.leftMoves_neg
theorem rightMoves_neg : ∀ x : PGame, (-x).RightMoves = x.LeftMoves
| ⟨_, _, _, _⟩ => rfl
#align pgame.right_moves_neg SetTheory.PGame.rightMoves_neg
/-- Turns a right move for `x` into a left move for `-x` and vice versa.
Even though these types are the same (not definitionally so), this is the preferred way to convert
between them. -/
def toLeftMovesNeg {x : PGame} : x.RightMoves ≃ (-x).LeftMoves :=
Equiv.cast (leftMoves_neg x).symm
#align pgame.to_left_moves_neg SetTheory.PGame.toLeftMovesNeg
/-- Turns a left move for `x` into a right move for `-x` and vice versa.
Even though these types are the same (not definitionally so), this is the preferred way to convert
between them. -/
def toRightMovesNeg {x : PGame} : x.LeftMoves ≃ (-x).RightMoves :=
Equiv.cast (rightMoves_neg x).symm
#align pgame.to_right_moves_neg SetTheory.PGame.toRightMovesNeg
theorem moveLeft_neg {x : PGame} (i) : (-x).moveLeft (toLeftMovesNeg i) = -x.moveRight i := by
cases x
rfl
#align pgame.move_left_neg SetTheory.PGame.moveLeft_neg
@[simp]
theorem moveLeft_neg' {x : PGame} (i) : (-x).moveLeft i = -x.moveRight (toLeftMovesNeg.symm i) := by
cases x
rfl
#align pgame.move_left_neg' SetTheory.PGame.moveLeft_neg'
theorem moveRight_neg {x : PGame} (i) : (-x).moveRight (toRightMovesNeg i) = -x.moveLeft i := by
cases x
rfl
#align pgame.move_right_neg SetTheory.PGame.moveRight_neg
@[simp]
theorem moveRight_neg' {x : PGame} (i) :
(-x).moveRight i = -x.moveLeft (toRightMovesNeg.symm i) := by
cases x
rfl
#align pgame.move_right_neg' SetTheory.PGame.moveRight_neg'
theorem moveLeft_neg_symm {x : PGame} (i) :
x.moveLeft (toRightMovesNeg.symm i) = -(-x).moveRight i := by simp
#align pgame.move_left_neg_symm SetTheory.PGame.moveLeft_neg_symm
theorem moveLeft_neg_symm' {x : PGame} (i) :
x.moveLeft i = -(-x).moveRight (toRightMovesNeg i) := by simp
#align pgame.move_left_neg_symm' SetTheory.PGame.moveLeft_neg_symm'
theorem moveRight_neg_symm {x : PGame} (i) :
x.moveRight (toLeftMovesNeg.symm i) = -(-x).moveLeft i := by simp
#align pgame.move_right_neg_symm SetTheory.PGame.moveRight_neg_symm
theorem moveRight_neg_symm' {x : PGame} (i) :
x.moveRight i = -(-x).moveLeft (toLeftMovesNeg i) := by simp
#align pgame.move_right_neg_symm' SetTheory.PGame.moveRight_neg_symm'
/-- If `x` has the same moves as `y`, then `-x` has the same moves as `-y`. -/
def Relabelling.negCongr : ∀ {x y : PGame}, x ≡r y → -x ≡r -y
| ⟨_, _, _, _⟩, ⟨_, _, _, _⟩, ⟨L, R, hL, hR⟩ =>
⟨R, L, fun j => (hR j).negCongr, fun i => (hL i).negCongr⟩
#align pgame.relabelling.neg_congr SetTheory.PGame.Relabelling.negCongr
private theorem neg_le_lf_neg_iff : ∀ {x y : PGame.{u}}, (-y ≤ -x ↔ x ≤ y) ∧ (-y ⧏ -x ↔ x ⧏ y)
| mk xl xr xL xR, mk yl yr yL yR => by
simp_rw [neg_def, mk_le_mk, mk_lf_mk, ← neg_def]
constructor
· rw [and_comm]
apply and_congr <;> exact forall_congr' fun _ => neg_le_lf_neg_iff.2
· rw [or_comm]
apply or_congr <;> exact exists_congr fun _ => neg_le_lf_neg_iff.1
termination_by x y => (x, y)
@[simp]
theorem neg_le_neg_iff {x y : PGame} : -y ≤ -x ↔ x ≤ y :=
neg_le_lf_neg_iff.1
#align pgame.neg_le_neg_iff SetTheory.PGame.neg_le_neg_iff
@[simp]
theorem neg_lf_neg_iff {x y : PGame} : -y ⧏ -x ↔ x ⧏ y :=
neg_le_lf_neg_iff.2
#align pgame.neg_lf_neg_iff SetTheory.PGame.neg_lf_neg_iff
@[simp]
theorem neg_lt_neg_iff {x y : PGame} : -y < -x ↔ x < y := by
rw [lt_iff_le_and_lf, lt_iff_le_and_lf, neg_le_neg_iff, neg_lf_neg_iff]
#align pgame.neg_lt_neg_iff SetTheory.PGame.neg_lt_neg_iff
@[simp]
theorem neg_equiv_neg_iff {x y : PGame} : (-x ≈ -y) ↔ (x ≈ y) := by
show Equiv (-x) (-y) ↔ Equiv x y
rw [Equiv, Equiv, neg_le_neg_iff, neg_le_neg_iff, and_comm]
#align pgame.neg_equiv_neg_iff SetTheory.PGame.neg_equiv_neg_iff
@[simp]
theorem neg_fuzzy_neg_iff {x y : PGame} : -x ‖ -y ↔ x ‖ y := by
rw [Fuzzy, Fuzzy, neg_lf_neg_iff, neg_lf_neg_iff, and_comm]
#align pgame.neg_fuzzy_neg_iff SetTheory.PGame.neg_fuzzy_neg_iff
theorem neg_le_iff {x y : PGame} : -y ≤ x ↔ -x ≤ y := by rw [← neg_neg x, neg_le_neg_iff, neg_neg]
#align pgame.neg_le_iff SetTheory.PGame.neg_le_iff
theorem neg_lf_iff {x y : PGame} : -y ⧏ x ↔ -x ⧏ y := by rw [← neg_neg x, neg_lf_neg_iff, neg_neg]
#align pgame.neg_lf_iff SetTheory.PGame.neg_lf_iff
theorem neg_lt_iff {x y : PGame} : -y < x ↔ -x < y := by rw [← neg_neg x, neg_lt_neg_iff, neg_neg]
#align pgame.neg_lt_iff SetTheory.PGame.neg_lt_iff
theorem neg_equiv_iff {x y : PGame} : (-x ≈ y) ↔ (x ≈ -y) := by
rw [← neg_neg y, neg_equiv_neg_iff, neg_neg]
#align pgame.neg_equiv_iff SetTheory.PGame.neg_equiv_iff
theorem neg_fuzzy_iff {x y : PGame} : -x ‖ y ↔ x ‖ -y := by
rw [← neg_neg y, neg_fuzzy_neg_iff, neg_neg]
#align pgame.neg_fuzzy_iff SetTheory.PGame.neg_fuzzy_iff
theorem le_neg_iff {x y : PGame} : y ≤ -x ↔ x ≤ -y := by rw [← neg_neg x, neg_le_neg_iff, neg_neg]
#align pgame.le_neg_iff SetTheory.PGame.le_neg_iff
theorem lf_neg_iff {x y : PGame} : y ⧏ -x ↔ x ⧏ -y := by rw [← neg_neg x, neg_lf_neg_iff, neg_neg]
#align pgame.lf_neg_iff SetTheory.PGame.lf_neg_iff
theorem lt_neg_iff {x y : PGame} : y < -x ↔ x < -y := by rw [← neg_neg x, neg_lt_neg_iff, neg_neg]
#align pgame.lt_neg_iff SetTheory.PGame.lt_neg_iff
@[simp]
theorem neg_le_zero_iff {x : PGame} : -x ≤ 0 ↔ 0 ≤ x := by rw [neg_le_iff, neg_zero]
#align pgame.neg_le_zero_iff SetTheory.PGame.neg_le_zero_iff
@[simp]
theorem zero_le_neg_iff {x : PGame} : 0 ≤ -x ↔ x ≤ 0 := by rw [le_neg_iff, neg_zero]
#align pgame.zero_le_neg_iff SetTheory.PGame.zero_le_neg_iff
@[simp]
theorem neg_lf_zero_iff {x : PGame} : -x ⧏ 0 ↔ 0 ⧏ x := by rw [neg_lf_iff, neg_zero]
#align pgame.neg_lf_zero_iff SetTheory.PGame.neg_lf_zero_iff
@[simp]
theorem zero_lf_neg_iff {x : PGame} : 0 ⧏ -x ↔ x ⧏ 0 := by rw [lf_neg_iff, neg_zero]
#align pgame.zero_lf_neg_iff SetTheory.PGame.zero_lf_neg_iff
@[simp]
theorem neg_lt_zero_iff {x : PGame} : -x < 0 ↔ 0 < x := by rw [neg_lt_iff, neg_zero]
#align pgame.neg_lt_zero_iff SetTheory.PGame.neg_lt_zero_iff
@[simp]
theorem zero_lt_neg_iff {x : PGame} : 0 < -x ↔ x < 0 := by rw [lt_neg_iff, neg_zero]
#align pgame.zero_lt_neg_iff SetTheory.PGame.zero_lt_neg_iff
@[simp]
theorem neg_equiv_zero_iff {x : PGame} : (-x ≈ 0) ↔ (x ≈ 0) := by rw [neg_equiv_iff, neg_zero]
#align pgame.neg_equiv_zero_iff SetTheory.PGame.neg_equiv_zero_iff
@[simp]
theorem neg_fuzzy_zero_iff {x : PGame} : -x ‖ 0 ↔ x ‖ 0 := by rw [neg_fuzzy_iff, neg_zero]
#align pgame.neg_fuzzy_zero_iff SetTheory.PGame.neg_fuzzy_zero_iff
@[simp]
| Mathlib/SetTheory/Game/PGame.lean | 1,469 | 1,469 | theorem zero_equiv_neg_iff {x : PGame} : (0 ≈ -x) ↔ (0 ≈ x) := by | rw [← neg_equiv_iff, neg_zero]
|
/-
Copyright (c) 2016 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura
-/
import Mathlib.Init.Data.List.Lemmas
import Mathlib.Tactic.Common
#align_import data.vector from "leanprover-community/lean"@"855e5b74e3a52a40552e8f067169d747d48743fd"
/-!
The type `Vector` represents lists with fixed length.
-/
assert_not_exists Monoid
universe u v w
/-- `Vector α n` is the type of lists of length `n` with elements of type `α`. -/
def Vector (α : Type u) (n : ℕ) :=
{ l : List α // l.length = n }
#align vector Vector
namespace Vector
variable {α : Type u} {β : Type v} {φ : Type w}
variable {n : ℕ}
instance [DecidableEq α] : DecidableEq (Vector α n) :=
inferInstanceAs (DecidableEq {l : List α // l.length = n})
/-- The empty vector with elements of type `α` -/
@[match_pattern]
def nil : Vector α 0 :=
⟨[], rfl⟩
#align vector.nil Vector.nil
/-- If `a : α` and `l : Vector α n`, then `cons a l`, is the vector of length `n + 1`
whose first element is a and with l as the rest of the list. -/
@[match_pattern]
def cons : α → Vector α n → Vector α (Nat.succ n)
| a, ⟨v, h⟩ => ⟨a :: v, congrArg Nat.succ h⟩
#align vector.cons Vector.cons
/-- The length of a vector. -/
@[reducible, nolint unusedArguments]
def length (_ : Vector α n) : ℕ :=
n
#align vector.length Vector.length
open Nat
/-- The first element of a vector with length at least `1`. -/
def head : Vector α (Nat.succ n) → α
| ⟨a :: _, _⟩ => a
#align vector.head Vector.head
/-- The head of a vector obtained by prepending is the element prepended. -/
theorem head_cons (a : α) : ∀ v : Vector α n, head (cons a v) = a
| ⟨_, _⟩ => rfl
#align vector.head_cons Vector.head_cons
/-- The tail of a vector, with an empty vector having empty tail. -/
def tail : Vector α n → Vector α (n - 1)
| ⟨[], h⟩ => ⟨[], congrArg pred h⟩
| ⟨_ :: v, h⟩ => ⟨v, congrArg pred h⟩
#align vector.tail Vector.tail
/-- The tail of a vector obtained by prepending is the vector prepended. to -/
theorem tail_cons (a : α) : ∀ v : Vector α n, tail (cons a v) = v
| ⟨_, _⟩ => rfl
#align vector.tail_cons Vector.tail_cons
/-- Prepending the head of a vector to its tail gives the vector. -/
@[simp]
theorem cons_head_tail : ∀ v : Vector α (succ n), cons (head v) (tail v) = v
| ⟨[], h⟩ => by contradiction
| ⟨a :: v, h⟩ => rfl
#align vector.cons_head_tail Vector.cons_head_tail
/-- The list obtained from a vector. -/
def toList (v : Vector α n) : List α :=
v.1
#align vector.to_list Vector.toList
/-- nth element of a vector, indexed by a `Fin` type. -/
def get (l : Vector α n) (i : Fin n) : α :=
l.1.get <| i.cast l.2.symm
#align vector.nth Vector.get
/-- Appending a vector to another. -/
def append {n m : Nat} : Vector α n → Vector α m → Vector α (n + m)
| ⟨l₁, h₁⟩, ⟨l₂, h₂⟩ => ⟨l₁ ++ l₂, by simp [*]⟩
#align vector.append Vector.append
/- warning: vector.elim -> Vector.elim is a dubious translation:
lean 3 declaration is
forall {α : Type.{u_1}} {C : forall {n : ℕ},
(Vector.{u_1} α n) -> Sort.{u}}, (forall (l : List.{u_1} α),
C (List.length.{u_1} α l) (Subtype.mk.{succ u_1} (List.{u_1} α)
(fun (l_1 : List.{u_1} α) => Eq.{1} ℕ (List.length.{u_1} α l_1)
(List.length.{u_1} α l)) l (Vector.Elim._proof_1.{u_1} α l))) ->
(forall {n : ℕ} (v : Vector.{u_1} α n), C n v)
but is expected to have type
forall {α : Type.{_aux_param_0}} {C : forall {n : ℕ}, (Vector.{_aux_param_0} α n) -> Sort.{u}},
(forall (l : List.{_aux_param_0} α),
C (List.length.{_aux_param_0} α l) (Subtype.mk.{succ _aux_param_0} (List.{_aux_param_0} α)
(fun (l_1 : List.{_aux_param_0} α) => Eq.{1} ℕ (List.length.{_aux_param_0} α l_1)
(List.length.{_aux_param_0} α l)) l (rfl.{1} ℕ (List.length.{_aux_param_0} α l)))) ->
(forall {n : ℕ} (v : Vector.{_aux_param_0} α n), C n v)
Case conversion may be inaccurate. Consider using '#align vector.elim Vector.elimₓ'. -/
/-- Elimination rule for `Vector`. -/
@[elab_as_elim]
def elim {α} {C : ∀ {n}, Vector α n → Sort u}
(H : ∀ l : List α, C ⟨l, rfl⟩) {n : ℕ} : ∀ v : Vector α n, C v
| ⟨l, h⟩ =>
match n, h with
| _, rfl => H l
#align vector.elim Vector.elim
/-- Map a vector under a function. -/
def map (f : α → β) : Vector α n → Vector β n
| ⟨l, h⟩ => ⟨List.map f l, by simp [*]⟩
#align vector.map Vector.map
/-- A `nil` vector maps to a `nil` vector. -/
@[simp]
theorem map_nil (f : α → β) : map f nil = nil :=
rfl
#align vector.map_nil Vector.map_nil
/-- `map` is natural with respect to `cons`. -/
@[simp]
theorem map_cons (f : α → β) (a : α) : ∀ v : Vector α n, map f (cons a v) = cons (f a) (map f v)
| ⟨_, _⟩ => rfl
#align vector.map_cons Vector.map_cons
/-- Mapping two vectors under a curried function of two variables. -/
def map₂ (f : α → β → φ) : Vector α n → Vector β n → Vector φ n
| ⟨x, _⟩, ⟨y, _⟩ => ⟨List.zipWith f x y, by simp [*]⟩
#align vector.map₂ Vector.map₂
/-- Vector obtained by repeating an element. -/
def replicate (n : ℕ) (a : α) : Vector α n :=
⟨List.replicate n a, List.length_replicate n a⟩
#align vector.replicate Vector.replicate
/-- Drop `i` elements from a vector of length `n`; we can have `i > n`. -/
def drop (i : ℕ) : Vector α n → Vector α (n - i)
| ⟨l, p⟩ => ⟨List.drop i l, by simp [*]⟩
#align vector.drop Vector.drop
/-- Take `i` elements from a vector of length `n`; we can have `i > n`. -/
def take (i : ℕ) : Vector α n → Vector α (min i n)
| ⟨l, p⟩ => ⟨List.take i l, by simp [*]⟩
#align vector.take Vector.take
/-- Remove the element at position `i` from a vector of length `n`. -/
def eraseIdx (i : Fin n) : Vector α n → Vector α (n - 1)
| ⟨l, p⟩ => ⟨List.eraseIdx l i.1, by rw [l.length_eraseIdx] <;> rw [p]; exact i.2⟩
#align vector.remove_nth Vector.eraseIdx
@[deprecated (since := "2024-05-04")] alias removeNth := eraseIdx
/-- Vector of length `n` from a function on `Fin n`. -/
def ofFn : ∀ {n}, (Fin n → α) → Vector α n
| 0, _ => nil
| _ + 1, f => cons (f 0) (ofFn fun i ↦ f i.succ)
/-- Create a vector from another with a provably equal length. -/
protected def congr {n m : ℕ} (h : n = m) : Vector α n → Vector α m
| ⟨x, p⟩ => ⟨x, h ▸ p⟩
#align vector.of_fn Vector.ofFn
section Accum
open Prod
variable {σ : Type}
/-- Runs a function over a vector returning the intermediate results and a
final result.
-/
def mapAccumr (f : α → σ → σ × β) : Vector α n → σ → σ × Vector β n
| ⟨x, px⟩, c =>
let res := List.mapAccumr f x c
⟨res.1, res.2, by simp [*, res]⟩
#align vector.map_accumr Vector.mapAccumr
/-- Runs a function over a pair of vectors returning the intermediate results and a
final result.
-/
def mapAccumr₂ {α β σ φ : Type} (f : α → β → σ → σ × φ) :
Vector α n → Vector β n → σ → σ × Vector φ n
| ⟨x, px⟩, ⟨y, py⟩, c =>
let res := List.mapAccumr₂ f x y c
⟨res.1, res.2, by simp [*, res]⟩
#align vector.map_accumr₂ Vector.mapAccumr₂
end Accum
/-! ### Shift Primitives-/
section Shift
/-- `shiftLeftFill v i` is the vector obtained by left-shifting `v` `i` times and padding with the
`fill` argument. If `v.length < i` then this will return `replicate n fill`. -/
def shiftLeftFill (v : Vector α n) (i : ℕ) (fill : α) : Vector α n :=
Vector.congr (by simp) <|
append (drop i v) (replicate (min n i) fill)
/-- `shiftRightFill v i` is the vector obtained by right-shifting `v` `i` times and padding with the
`fill` argument. If `v.length < i` then this will return `replicate n fill`. -/
def shiftRightFill (v : Vector α n) (i : ℕ) (fill : α) : Vector α n :=
Vector.congr (by omega) <| append (replicate (min n i) fill) (take (n - i) v)
end Shift
/-! ### Basic Theorems -/
/-- Vector is determined by the underlying list. -/
protected theorem eq {n : ℕ} : ∀ a1 a2 : Vector α n, toList a1 = toList a2 → a1 = a2
| ⟨_, _⟩, ⟨_, _⟩, rfl => rfl
#align vector.eq Vector.eq
/-- A vector of length `0` is a `nil` vector. -/
protected theorem eq_nil (v : Vector α 0) : v = nil :=
v.eq nil (List.eq_nil_of_length_eq_zero v.2)
#align vector.eq_nil Vector.eq_nil
/-- Vector of length from a list `v`
with witness that `v` has length `n` maps to `v` under `toList`. -/
@[simp]
theorem toList_mk (v : List α) (P : List.length v = n) : toList (Subtype.mk v P) = v :=
rfl
#align vector.to_list_mk Vector.toList_mk
/-- A nil vector maps to a nil list. -/
@[simp, nolint simpNF] -- Porting note (#10618): simp can prove this in the future
theorem toList_nil : toList nil = @List.nil α :=
rfl
#align vector.to_list_nil Vector.toList_nil
/-- The length of the list to which a vector of length `n` maps is `n`. -/
@[simp]
theorem toList_length (v : Vector α n) : (toList v).length = n :=
v.2
#align vector.to_list_length Vector.toList_length
/-- `toList` of `cons` of a vector and an element is
the `cons` of the list obtained by `toList` and the element -/
@[simp]
theorem toList_cons (a : α) (v : Vector α n) : toList (cons a v) = a :: toList v := by
cases v; rfl
#align vector.to_list_cons Vector.toList_cons
/-- Appending of vectors corresponds under `toList` to appending of lists. -/
@[simp]
theorem toList_append {n m : ℕ} (v : Vector α n) (w : Vector α m) :
toList (append v w) = toList v ++ toList w := by
cases v
cases w
rfl
#align vector.to_list_append Vector.toList_append
/-- `drop` of vectors corresponds under `toList` to `drop` of lists. -/
@[simp]
| Mathlib/Data/Vector/Defs.lean | 268 | 270 | theorem toList_drop {n m : ℕ} (v : Vector α m) : toList (drop n v) = List.drop n (toList v) := by |
cases v
rfl
|
/-
Copyright (c) 2023 Markus Himmel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel
-/
import Mathlib.CategoryTheory.Filtered.Final
/-!
# Finally small categories
A category given by `(J : Type u) [Category.{v} J]` is `w`-finally small if there exists a
`FinalModel J : Type w` equipped with `[SmallCategory (FinalModel J)]` and a final functor
`FinalModel J ⥤ J`.
This means that if a category `C` has colimits of size `w` and `J` is `w`-finally small, then
`C` has colimits of shape `J`. In this way, the notion of "finally small" can be seen of a
generalization of the notion of "essentially small" for indexing categories of colimits.
Dually, we have a notion of initially small category.
We show that a finally small category admits a small weakly terminal set, i.e., a small set `s` of
objects such that from every object there a morphism to a member of `s`. We also show that the
converse holds if `J` is filtered.
-/
universe w v v₁ u u₁
open CategoryTheory Functor
namespace CategoryTheory
section FinallySmall
variable (J : Type u) [Category.{v} J]
/-- A category is `FinallySmall.{w}` if there is a final functor from a `w`-small category. -/
class FinallySmall : Prop where
/-- There is a final functor from a small category. -/
final_smallCategory : ∃ (S : Type w) (_ : SmallCategory S) (F : S ⥤ J), Final F
/-- Constructor for `FinallySmall C` from an explicit small category witness. -/
theorem FinallySmall.mk' {J : Type u} [Category.{v} J] {S : Type w} [SmallCategory S]
(F : S ⥤ J) [Final F] : FinallySmall.{w} J :=
⟨S, _, F, inferInstance⟩
/-- An arbitrarily chosen small model for a finally small category. -/
def FinalModel [FinallySmall.{w} J] : Type w :=
Classical.choose (@FinallySmall.final_smallCategory J _ _)
noncomputable instance smallCategoryFinalModel [FinallySmall.{w} J] :
SmallCategory (FinalModel J) :=
Classical.choose (Classical.choose_spec (@FinallySmall.final_smallCategory J _ _))
/-- An arbitrarily chosen final functor `FinalModel J ⥤ J`. -/
noncomputable def fromFinalModel [FinallySmall.{w} J] : FinalModel J ⥤ J :=
Classical.choose (Classical.choose_spec (Classical.choose_spec
(@FinallySmall.final_smallCategory J _ _)))
instance final_fromFinalModel [FinallySmall.{w} J] : Final (fromFinalModel J) :=
Classical.choose_spec (Classical.choose_spec (Classical.choose_spec
(@FinallySmall.final_smallCategory J _ _)))
theorem finallySmall_of_essentiallySmall [EssentiallySmall.{w} J] : FinallySmall.{w} J :=
FinallySmall.mk' (equivSmallModel.{w} J).inverse
variable {J}
variable {K : Type u₁} [Category.{v₁} K] (F : K ⥤ J) [Final F]
theorem finallySmall_of_final_of_finallySmall [FinallySmall.{w} K] : FinallySmall.{w} J :=
suffices Final ((fromFinalModel K) ⋙ F) from .mk' ((fromFinalModel K) ⋙ F)
final_comp _ _
theorem finallySmall_of_final_of_essentiallySmall [EssentiallySmall.{w} K] : FinallySmall.{w} J :=
have := finallySmall_of_essentiallySmall K
finallySmall_of_final_of_finallySmall F
end FinallySmall
section InitiallySmall
variable (J : Type u) [Category.{v} J]
/-- A category is `InitiallySmall.{w}` if there is an initial functor from a `w`-small category. -/
class InitiallySmall : Prop where
/-- There is an initial functor from a small category. -/
initial_smallCategory : ∃ (S : Type w) (_ : SmallCategory S) (F : S ⥤ J), Initial F
/-- Constructor for `InitialSmall C` from an explicit small category witness. -/
theorem InitiallySmall.mk' {J : Type u} [Category.{v} J] {S : Type w} [SmallCategory S]
(F : S ⥤ J) [Initial F] : InitiallySmall.{w} J :=
⟨S, _, F, inferInstance⟩
/-- An arbitrarily chosen small model for an initially small category. -/
def InitialModel [InitiallySmall.{w} J] : Type w :=
Classical.choose (@InitiallySmall.initial_smallCategory J _ _)
noncomputable instance smallCategoryInitialModel [InitiallySmall.{w} J] :
SmallCategory (InitialModel J) :=
Classical.choose (Classical.choose_spec (@InitiallySmall.initial_smallCategory J _ _))
/-- An arbitrarily chosen initial functor `InitialModel J ⥤ J`. -/
noncomputable def fromInitialModel [InitiallySmall.{w} J] : InitialModel J ⥤ J :=
Classical.choose (Classical.choose_spec (Classical.choose_spec
(@InitiallySmall.initial_smallCategory J _ _)))
instance initial_fromInitialModel [InitiallySmall.{w} J] : Initial (fromInitialModel J) :=
Classical.choose_spec (Classical.choose_spec (Classical.choose_spec
(@InitiallySmall.initial_smallCategory J _ _)))
theorem initiallySmall_of_essentiallySmall [EssentiallySmall.{w} J] : InitiallySmall.{w} J :=
InitiallySmall.mk' (equivSmallModel.{w} J).inverse
variable {J}
variable {K : Type u₁} [Category.{v₁} K] (F : K ⥤ J) [Initial F]
theorem initiallySmall_of_initial_of_initiallySmall [InitiallySmall.{w} K] : InitiallySmall.{w} J :=
suffices Initial ((fromInitialModel K) ⋙ F) from .mk' ((fromInitialModel K) ⋙ F)
initial_comp _ _
theorem initiallySmall_of_initial_of_essentiallySmall [EssentiallySmall.{w} K] :
InitiallySmall.{w} J :=
have := initiallySmall_of_essentiallySmall K
initiallySmall_of_initial_of_initiallySmall F
end InitiallySmall
section WeaklyTerminal
variable (J : Type u) [Category.{v} J]
/-- The converse is true if `J` is filtered, see `finallySmall_of_small_weakly_terminal_set`. -/
theorem FinallySmall.exists_small_weakly_terminal_set [FinallySmall.{w} J] :
∃ (s : Set J) (_ : Small.{w} s), ∀ i, ∃ j ∈ s, Nonempty (i ⟶ j) := by
refine ⟨Set.range (fromFinalModel J).obj, inferInstance, fun i => ?_⟩
obtain ⟨f⟩ : Nonempty (StructuredArrow i (fromFinalModel J)) := IsConnected.is_nonempty
exact ⟨(fromFinalModel J).obj f.right, Set.mem_range_self _, ⟨f.hom⟩⟩
variable {J} in
| Mathlib/CategoryTheory/Limits/FinallySmall.lean | 139 | 145 | theorem finallySmall_of_small_weakly_terminal_set [IsFilteredOrEmpty J] (s : Set J) [Small.{v} s]
(hs : ∀ i, ∃ j ∈ s, Nonempty (i ⟶ j)) : FinallySmall.{v} J := by |
suffices Functor.Final (fullSubcategoryInclusion (· ∈ s)) from
finallySmall_of_final_of_essentiallySmall (fullSubcategoryInclusion (· ∈ s))
refine Functor.final_of_exists_of_isFiltered_of_fullyFaithful _ (fun i => ?_)
obtain ⟨j, hj₁, hj₂⟩ := hs i
exact ⟨⟨j, hj₁⟩, hj₂⟩
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Kevin Buzzard, Yury Kudryashov, Eric Wieser
-/
import Mathlib.Algebra.Algebra.Prod
import Mathlib.LinearAlgebra.Basic
import Mathlib.LinearAlgebra.Span
import Mathlib.Order.PartialSups
#align_import linear_algebra.prod from "leanprover-community/mathlib"@"cd391184c85986113f8c00844cfe6dda1d34be3d"
/-! ### Products of modules
This file defines constructors for linear maps whose domains or codomains are products.
It contains theorems relating these to each other, as well as to `Submodule.prod`, `Submodule.map`,
`Submodule.comap`, `LinearMap.range`, and `LinearMap.ker`.
## Main definitions
- products in the domain:
- `LinearMap.fst`
- `LinearMap.snd`
- `LinearMap.coprod`
- `LinearMap.prod_ext`
- products in the codomain:
- `LinearMap.inl`
- `LinearMap.inr`
- `LinearMap.prod`
- products in both domain and codomain:
- `LinearMap.prodMap`
- `LinearEquiv.prodMap`
- `LinearEquiv.skewProd`
-/
universe u v w x y z u' v' w' y'
variable {R : Type u} {K : Type u'} {M : Type v} {V : Type v'} {M₂ : Type w} {V₂ : Type w'}
variable {M₃ : Type y} {V₃ : Type y'} {M₄ : Type z} {ι : Type x}
variable {M₅ M₆ : Type*}
section Prod
namespace LinearMap
variable (S : Type*) [Semiring R] [Semiring S]
variable [AddCommMonoid M] [AddCommMonoid M₂] [AddCommMonoid M₃] [AddCommMonoid M₄]
variable [AddCommMonoid M₅] [AddCommMonoid M₆]
variable [Module R M] [Module R M₂] [Module R M₃] [Module R M₄]
variable [Module R M₅] [Module R M₆]
variable (f : M →ₗ[R] M₂)
section
variable (R M M₂)
/-- The first projection of a product is a linear map. -/
def fst : M × M₂ →ₗ[R] M where
toFun := Prod.fst
map_add' _x _y := rfl
map_smul' _x _y := rfl
#align linear_map.fst LinearMap.fst
/-- The second projection of a product is a linear map. -/
def snd : M × M₂ →ₗ[R] M₂ where
toFun := Prod.snd
map_add' _x _y := rfl
map_smul' _x _y := rfl
#align linear_map.snd LinearMap.snd
end
@[simp]
theorem fst_apply (x : M × M₂) : fst R M M₂ x = x.1 :=
rfl
#align linear_map.fst_apply LinearMap.fst_apply
@[simp]
theorem snd_apply (x : M × M₂) : snd R M M₂ x = x.2 :=
rfl
#align linear_map.snd_apply LinearMap.snd_apply
theorem fst_surjective : Function.Surjective (fst R M M₂) := fun x => ⟨(x, 0), rfl⟩
#align linear_map.fst_surjective LinearMap.fst_surjective
theorem snd_surjective : Function.Surjective (snd R M M₂) := fun x => ⟨(0, x), rfl⟩
#align linear_map.snd_surjective LinearMap.snd_surjective
/-- The prod of two linear maps is a linear map. -/
@[simps]
def prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : M →ₗ[R] M₂ × M₃ where
toFun := Pi.prod f g
map_add' x y := by simp only [Pi.prod, Prod.mk_add_mk, map_add]
map_smul' c x := by simp only [Pi.prod, Prod.smul_mk, map_smul, RingHom.id_apply]
#align linear_map.prod LinearMap.prod
theorem coe_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : ⇑(f.prod g) = Pi.prod f g :=
rfl
#align linear_map.coe_prod LinearMap.coe_prod
@[simp]
theorem fst_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : (fst R M₂ M₃).comp (prod f g) = f := rfl
#align linear_map.fst_prod LinearMap.fst_prod
@[simp]
theorem snd_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : (snd R M₂ M₃).comp (prod f g) = g := rfl
#align linear_map.snd_prod LinearMap.snd_prod
@[simp]
theorem pair_fst_snd : prod (fst R M M₂) (snd R M M₂) = LinearMap.id := rfl
#align linear_map.pair_fst_snd LinearMap.pair_fst_snd
theorem prod_comp (f : M₂ →ₗ[R] M₃) (g : M₂ →ₗ[R] M₄)
(h : M →ₗ[R] M₂) : (f.prod g).comp h = (f.comp h).prod (g.comp h) :=
rfl
/-- Taking the product of two maps with the same domain is equivalent to taking the product of
their codomains.
See note [bundled maps over different rings] for why separate `R` and `S` semirings are used. -/
@[simps]
def prodEquiv [Module S M₂] [Module S M₃] [SMulCommClass R S M₂] [SMulCommClass R S M₃] :
((M →ₗ[R] M₂) × (M →ₗ[R] M₃)) ≃ₗ[S] M →ₗ[R] M₂ × M₃ where
toFun f := f.1.prod f.2
invFun f := ((fst _ _ _).comp f, (snd _ _ _).comp f)
left_inv f := by ext <;> rfl
right_inv f := by ext <;> rfl
map_add' a b := rfl
map_smul' r a := rfl
#align linear_map.prod_equiv LinearMap.prodEquiv
section
variable (R M M₂)
/-- The left injection into a product is a linear map. -/
def inl : M →ₗ[R] M × M₂ :=
prod LinearMap.id 0
#align linear_map.inl LinearMap.inl
/-- The right injection into a product is a linear map. -/
def inr : M₂ →ₗ[R] M × M₂ :=
prod 0 LinearMap.id
#align linear_map.inr LinearMap.inr
theorem range_inl : range (inl R M M₂) = ker (snd R M M₂) := by
ext x
simp only [mem_ker, mem_range]
constructor
· rintro ⟨y, rfl⟩
rfl
· intro h
exact ⟨x.fst, Prod.ext rfl h.symm⟩
#align linear_map.range_inl LinearMap.range_inl
theorem ker_snd : ker (snd R M M₂) = range (inl R M M₂) :=
Eq.symm <| range_inl R M M₂
#align linear_map.ker_snd LinearMap.ker_snd
theorem range_inr : range (inr R M M₂) = ker (fst R M M₂) := by
ext x
simp only [mem_ker, mem_range]
constructor
· rintro ⟨y, rfl⟩
rfl
· intro h
exact ⟨x.snd, Prod.ext h.symm rfl⟩
#align linear_map.range_inr LinearMap.range_inr
theorem ker_fst : ker (fst R M M₂) = range (inr R M M₂) :=
Eq.symm <| range_inr R M M₂
#align linear_map.ker_fst LinearMap.ker_fst
@[simp] theorem fst_comp_inl : fst R M M₂ ∘ₗ inl R M M₂ = id := rfl
@[simp] theorem snd_comp_inl : snd R M M₂ ∘ₗ inl R M M₂ = 0 := rfl
@[simp] theorem fst_comp_inr : fst R M M₂ ∘ₗ inr R M M₂ = 0 := rfl
@[simp] theorem snd_comp_inr : snd R M M₂ ∘ₗ inr R M M₂ = id := rfl
end
@[simp]
theorem coe_inl : (inl R M M₂ : M → M × M₂) = fun x => (x, 0) :=
rfl
#align linear_map.coe_inl LinearMap.coe_inl
theorem inl_apply (x : M) : inl R M M₂ x = (x, 0) :=
rfl
#align linear_map.inl_apply LinearMap.inl_apply
@[simp]
theorem coe_inr : (inr R M M₂ : M₂ → M × M₂) = Prod.mk 0 :=
rfl
#align linear_map.coe_inr LinearMap.coe_inr
theorem inr_apply (x : M₂) : inr R M M₂ x = (0, x) :=
rfl
#align linear_map.inr_apply LinearMap.inr_apply
theorem inl_eq_prod : inl R M M₂ = prod LinearMap.id 0 :=
rfl
#align linear_map.inl_eq_prod LinearMap.inl_eq_prod
theorem inr_eq_prod : inr R M M₂ = prod 0 LinearMap.id :=
rfl
#align linear_map.inr_eq_prod LinearMap.inr_eq_prod
theorem inl_injective : Function.Injective (inl R M M₂) := fun _ => by simp
#align linear_map.inl_injective LinearMap.inl_injective
theorem inr_injective : Function.Injective (inr R M M₂) := fun _ => by simp
#align linear_map.inr_injective LinearMap.inr_injective
/-- The coprod function `x : M × M₂ ↦ f x.1 + g x.2` is a linear map. -/
def coprod (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) : M × M₂ →ₗ[R] M₃ :=
f.comp (fst _ _ _) + g.comp (snd _ _ _)
#align linear_map.coprod LinearMap.coprod
@[simp]
theorem coprod_apply (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) (x : M × M₂) :
coprod f g x = f x.1 + g x.2 :=
rfl
#align linear_map.coprod_apply LinearMap.coprod_apply
@[simp]
theorem coprod_inl (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) : (coprod f g).comp (inl R M M₂) = f := by
ext; simp only [map_zero, add_zero, coprod_apply, inl_apply, comp_apply]
#align linear_map.coprod_inl LinearMap.coprod_inl
@[simp]
theorem coprod_inr (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) : (coprod f g).comp (inr R M M₂) = g := by
ext; simp only [map_zero, coprod_apply, inr_apply, zero_add, comp_apply]
#align linear_map.coprod_inr LinearMap.coprod_inr
@[simp]
theorem coprod_inl_inr : coprod (inl R M M₂) (inr R M M₂) = LinearMap.id := by
ext <;>
simp only [Prod.mk_add_mk, add_zero, id_apply, coprod_apply, inl_apply, inr_apply, zero_add]
#align linear_map.coprod_inl_inr LinearMap.coprod_inl_inr
theorem coprod_zero_left (g : M₂ →ₗ[R] M₃) : (0 : M →ₗ[R] M₃).coprod g = g.comp (snd R M M₂) :=
zero_add _
theorem coprod_zero_right (f : M →ₗ[R] M₃) : f.coprod (0 : M₂ →ₗ[R] M₃) = f.comp (fst R M M₂) :=
add_zero _
theorem comp_coprod (f : M₃ →ₗ[R] M₄) (g₁ : M →ₗ[R] M₃) (g₂ : M₂ →ₗ[R] M₃) :
f.comp (g₁.coprod g₂) = (f.comp g₁).coprod (f.comp g₂) :=
ext fun x => f.map_add (g₁ x.1) (g₂ x.2)
#align linear_map.comp_coprod LinearMap.comp_coprod
theorem fst_eq_coprod : fst R M M₂ = coprod LinearMap.id 0 := by ext; simp
#align linear_map.fst_eq_coprod LinearMap.fst_eq_coprod
theorem snd_eq_coprod : snd R M M₂ = coprod 0 LinearMap.id := by ext; simp
#align linear_map.snd_eq_coprod LinearMap.snd_eq_coprod
@[simp]
theorem coprod_comp_prod (f : M₂ →ₗ[R] M₄) (g : M₃ →ₗ[R] M₄) (f' : M →ₗ[R] M₂) (g' : M →ₗ[R] M₃) :
(f.coprod g).comp (f'.prod g') = f.comp f' + g.comp g' :=
rfl
#align linear_map.coprod_comp_prod LinearMap.coprod_comp_prod
@[simp]
theorem coprod_map_prod (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) (S : Submodule R M)
(S' : Submodule R M₂) : (Submodule.prod S S').map (LinearMap.coprod f g) = S.map f ⊔ S'.map g :=
SetLike.coe_injective <| by
simp only [LinearMap.coprod_apply, Submodule.coe_sup, Submodule.map_coe]
rw [← Set.image2_add, Set.image2_image_left, Set.image2_image_right]
exact Set.image_prod fun m m₂ => f m + g m₂
#align linear_map.coprod_map_prod LinearMap.coprod_map_prod
/-- Taking the product of two maps with the same codomain is equivalent to taking the product of
their domains.
See note [bundled maps over different rings] for why separate `R` and `S` semirings are used. -/
@[simps]
def coprodEquiv [Module S M₃] [SMulCommClass R S M₃] :
((M →ₗ[R] M₃) × (M₂ →ₗ[R] M₃)) ≃ₗ[S] M × M₂ →ₗ[R] M₃ where
toFun f := f.1.coprod f.2
invFun f := (f.comp (inl _ _ _), f.comp (inr _ _ _))
left_inv f := by simp only [coprod_inl, coprod_inr]
right_inv f := by simp only [← comp_coprod, comp_id, coprod_inl_inr]
map_add' a b := by
ext
simp only [Prod.snd_add, add_apply, coprod_apply, Prod.fst_add, add_add_add_comm]
map_smul' r a := by
dsimp
ext
simp only [smul_add, smul_apply, Prod.smul_snd, Prod.smul_fst, coprod_apply]
#align linear_map.coprod_equiv LinearMap.coprodEquiv
theorem prod_ext_iff {f g : M × M₂ →ₗ[R] M₃} :
f = g ↔ f.comp (inl _ _ _) = g.comp (inl _ _ _) ∧ f.comp (inr _ _ _) = g.comp (inr _ _ _) :=
(coprodEquiv ℕ).symm.injective.eq_iff.symm.trans Prod.ext_iff
#align linear_map.prod_ext_iff LinearMap.prod_ext_iff
/--
Split equality of linear maps from a product into linear maps over each component, to allow `ext`
to apply lemmas specific to `M →ₗ M₃` and `M₂ →ₗ M₃`.
See note [partially-applied ext lemmas]. -/
@[ext 1100]
theorem prod_ext {f g : M × M₂ →ₗ[R] M₃} (hl : f.comp (inl _ _ _) = g.comp (inl _ _ _))
(hr : f.comp (inr _ _ _) = g.comp (inr _ _ _)) : f = g :=
prod_ext_iff.2 ⟨hl, hr⟩
#align linear_map.prod_ext LinearMap.prod_ext
/-- `prod.map` of two linear maps. -/
def prodMap (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₄) : M × M₂ →ₗ[R] M₃ × M₄ :=
(f.comp (fst R M M₂)).prod (g.comp (snd R M M₂))
#align linear_map.prod_map LinearMap.prodMap
theorem coe_prodMap (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₄) : ⇑(f.prodMap g) = Prod.map f g :=
rfl
#align linear_map.coe_prod_map LinearMap.coe_prodMap
@[simp]
theorem prodMap_apply (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₄) (x) : f.prodMap g x = (f x.1, g x.2) :=
rfl
#align linear_map.prod_map_apply LinearMap.prodMap_apply
theorem prodMap_comap_prod (f : M →ₗ[R] M₂) (g : M₃ →ₗ[R] M₄) (S : Submodule R M₂)
(S' : Submodule R M₄) :
(Submodule.prod S S').comap (LinearMap.prodMap f g) = (S.comap f).prod (S'.comap g) :=
SetLike.coe_injective <| Set.preimage_prod_map_prod f g _ _
#align linear_map.prod_map_comap_prod LinearMap.prodMap_comap_prod
theorem ker_prodMap (f : M →ₗ[R] M₂) (g : M₃ →ₗ[R] M₄) :
ker (LinearMap.prodMap f g) = Submodule.prod (ker f) (ker g) := by
dsimp only [ker]
rw [← prodMap_comap_prod, Submodule.prod_bot]
#align linear_map.ker_prod_map LinearMap.ker_prodMap
@[simp]
theorem prodMap_id : (id : M →ₗ[R] M).prodMap (id : M₂ →ₗ[R] M₂) = id :=
rfl
#align linear_map.prod_map_id LinearMap.prodMap_id
@[simp]
theorem prodMap_one : (1 : M →ₗ[R] M).prodMap (1 : M₂ →ₗ[R] M₂) = 1 :=
rfl
#align linear_map.prod_map_one LinearMap.prodMap_one
theorem prodMap_comp (f₁₂ : M →ₗ[R] M₂) (f₂₃ : M₂ →ₗ[R] M₃) (g₁₂ : M₄ →ₗ[R] M₅)
(g₂₃ : M₅ →ₗ[R] M₆) :
f₂₃.prodMap g₂₃ ∘ₗ f₁₂.prodMap g₁₂ = (f₂₃ ∘ₗ f₁₂).prodMap (g₂₃ ∘ₗ g₁₂) :=
rfl
#align linear_map.prod_map_comp LinearMap.prodMap_comp
theorem prodMap_mul (f₁₂ : M →ₗ[R] M) (f₂₃ : M →ₗ[R] M) (g₁₂ : M₂ →ₗ[R] M₂) (g₂₃ : M₂ →ₗ[R] M₂) :
f₂₃.prodMap g₂₃ * f₁₂.prodMap g₁₂ = (f₂₃ * f₁₂).prodMap (g₂₃ * g₁₂) :=
rfl
#align linear_map.prod_map_mul LinearMap.prodMap_mul
theorem prodMap_add (f₁ : M →ₗ[R] M₃) (f₂ : M →ₗ[R] M₃) (g₁ : M₂ →ₗ[R] M₄) (g₂ : M₂ →ₗ[R] M₄) :
(f₁ + f₂).prodMap (g₁ + g₂) = f₁.prodMap g₁ + f₂.prodMap g₂ :=
rfl
#align linear_map.prod_map_add LinearMap.prodMap_add
@[simp]
theorem prodMap_zero : (0 : M →ₗ[R] M₂).prodMap (0 : M₃ →ₗ[R] M₄) = 0 :=
rfl
#align linear_map.prod_map_zero LinearMap.prodMap_zero
@[simp]
theorem prodMap_smul [Module S M₃] [Module S M₄] [SMulCommClass R S M₃] [SMulCommClass R S M₄]
(s : S) (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₄) : prodMap (s • f) (s • g) = s • prodMap f g :=
rfl
#align linear_map.prod_map_smul LinearMap.prodMap_smul
variable (R M M₂ M₃ M₄)
/-- `LinearMap.prodMap` as a `LinearMap` -/
@[simps]
def prodMapLinear [Module S M₃] [Module S M₄] [SMulCommClass R S M₃] [SMulCommClass R S M₄] :
(M →ₗ[R] M₃) × (M₂ →ₗ[R] M₄) →ₗ[S] M × M₂ →ₗ[R] M₃ × M₄ where
toFun f := prodMap f.1 f.2
map_add' _ _ := rfl
map_smul' _ _ := rfl
#align linear_map.prod_map_linear LinearMap.prodMapLinear
/-- `LinearMap.prodMap` as a `RingHom` -/
@[simps]
def prodMapRingHom : (M →ₗ[R] M) × (M₂ →ₗ[R] M₂) →+* M × M₂ →ₗ[R] M × M₂ where
toFun f := prodMap f.1 f.2
map_one' := prodMap_one
map_zero' := rfl
map_add' _ _ := rfl
map_mul' _ _ := rfl
#align linear_map.prod_map_ring_hom LinearMap.prodMapRingHom
variable {R M M₂ M₃ M₄}
section map_mul
variable {A : Type*} [NonUnitalNonAssocSemiring A] [Module R A]
variable {B : Type*} [NonUnitalNonAssocSemiring B] [Module R B]
theorem inl_map_mul (a₁ a₂ : A) :
LinearMap.inl R A B (a₁ * a₂) = LinearMap.inl R A B a₁ * LinearMap.inl R A B a₂ :=
Prod.ext rfl (by simp)
#align linear_map.inl_map_mul LinearMap.inl_map_mul
theorem inr_map_mul (b₁ b₂ : B) :
LinearMap.inr R A B (b₁ * b₂) = LinearMap.inr R A B b₁ * LinearMap.inr R A B b₂ :=
Prod.ext (by simp) rfl
#align linear_map.inr_map_mul LinearMap.inr_map_mul
end map_mul
end LinearMap
end Prod
namespace LinearMap
variable (R M M₂)
variable [CommSemiring R]
variable [AddCommMonoid M] [AddCommMonoid M₂]
variable [Module R M] [Module R M₂]
/-- `LinearMap.prodMap` as an `AlgHom` -/
@[simps!]
def prodMapAlgHom : Module.End R M × Module.End R M₂ →ₐ[R] Module.End R (M × M₂) :=
{ prodMapRingHom R M M₂ with commutes' := fun _ => rfl }
#align linear_map.prod_map_alg_hom LinearMap.prodMapAlgHom
end LinearMap
namespace LinearMap
open Submodule
variable [Semiring R] [AddCommMonoid M] [AddCommMonoid M₂] [AddCommMonoid M₃] [AddCommMonoid M₄]
[Module R M] [Module R M₂] [Module R M₃] [Module R M₄]
theorem range_coprod (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) : range (f.coprod g) = range f ⊔ range g :=
Submodule.ext fun x => by simp [mem_sup]
#align linear_map.range_coprod LinearMap.range_coprod
theorem isCompl_range_inl_inr : IsCompl (range <| inl R M M₂) (range <| inr R M M₂) := by
constructor
· rw [disjoint_def]
rintro ⟨_, _⟩ ⟨x, hx⟩ ⟨y, hy⟩
simp only [Prod.ext_iff, inl_apply, inr_apply, mem_bot] at hx hy ⊢
exact ⟨hy.1.symm, hx.2.symm⟩
· rw [codisjoint_iff_le_sup]
rintro ⟨x, y⟩ -
simp only [mem_sup, mem_range, exists_prop]
refine ⟨(x, 0), ⟨x, rfl⟩, (0, y), ⟨y, rfl⟩, ?_⟩
simp
#align linear_map.is_compl_range_inl_inr LinearMap.isCompl_range_inl_inr
theorem sup_range_inl_inr : (range <| inl R M M₂) ⊔ (range <| inr R M M₂) = ⊤ :=
IsCompl.sup_eq_top isCompl_range_inl_inr
#align linear_map.sup_range_inl_inr LinearMap.sup_range_inl_inr
theorem disjoint_inl_inr : Disjoint (range <| inl R M M₂) (range <| inr R M M₂) := by
simp (config := { contextual := true }) [disjoint_def, @eq_comm M 0, @eq_comm M₂ 0]
#align linear_map.disjoint_inl_inr LinearMap.disjoint_inl_inr
theorem map_coprod_prod (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) (p : Submodule R M)
(q : Submodule R M₂) : map (coprod f g) (p.prod q) = map f p ⊔ map g q := by
refine le_antisymm ?_ (sup_le (map_le_iff_le_comap.2 ?_) (map_le_iff_le_comap.2 ?_))
· rw [SetLike.le_def]
rintro _ ⟨x, ⟨h₁, h₂⟩, rfl⟩
exact mem_sup.2 ⟨_, ⟨_, h₁, rfl⟩, _, ⟨_, h₂, rfl⟩, rfl⟩
· exact fun x hx => ⟨(x, 0), by simp [hx]⟩
· exact fun x hx => ⟨(0, x), by simp [hx]⟩
#align linear_map.map_coprod_prod LinearMap.map_coprod_prod
theorem comap_prod_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) (p : Submodule R M₂)
(q : Submodule R M₃) : comap (prod f g) (p.prod q) = comap f p ⊓ comap g q :=
Submodule.ext fun _x => Iff.rfl
#align linear_map.comap_prod_prod LinearMap.comap_prod_prod
theorem prod_eq_inf_comap (p : Submodule R M) (q : Submodule R M₂) :
p.prod q = p.comap (LinearMap.fst R M M₂) ⊓ q.comap (LinearMap.snd R M M₂) :=
Submodule.ext fun _x => Iff.rfl
#align linear_map.prod_eq_inf_comap LinearMap.prod_eq_inf_comap
theorem prod_eq_sup_map (p : Submodule R M) (q : Submodule R M₂) :
p.prod q = p.map (LinearMap.inl R M M₂) ⊔ q.map (LinearMap.inr R M M₂) := by
rw [← map_coprod_prod, coprod_inl_inr, map_id]
#align linear_map.prod_eq_sup_map LinearMap.prod_eq_sup_map
theorem span_inl_union_inr {s : Set M} {t : Set M₂} :
span R (inl R M M₂ '' s ∪ inr R M M₂ '' t) = (span R s).prod (span R t) := by
rw [span_union, prod_eq_sup_map, ← span_image, ← span_image]
#align linear_map.span_inl_union_inr LinearMap.span_inl_union_inr
@[simp]
theorem ker_prod (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) : ker (prod f g) = ker f ⊓ ker g := by
rw [ker, ← prod_bot, comap_prod_prod]; rfl
#align linear_map.ker_prod LinearMap.ker_prod
theorem range_prod_le (f : M →ₗ[R] M₂) (g : M →ₗ[R] M₃) :
range (prod f g) ≤ (range f).prod (range g) := by
simp only [SetLike.le_def, prod_apply, mem_range, SetLike.mem_coe, mem_prod, exists_imp]
rintro _ x rfl
exact ⟨⟨x, rfl⟩, ⟨x, rfl⟩⟩
#align linear_map.range_prod_le LinearMap.range_prod_le
theorem ker_prod_ker_le_ker_coprod {M₂ : Type*} [AddCommGroup M₂] [Module R M₂] {M₃ : Type*}
[AddCommGroup M₃] [Module R M₃] (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃) :
(ker f).prod (ker g) ≤ ker (f.coprod g) := by
rintro ⟨y, z⟩
simp (config := { contextual := true })
#align linear_map.ker_prod_ker_le_ker_coprod LinearMap.ker_prod_ker_le_ker_coprod
theorem ker_coprod_of_disjoint_range {M₂ : Type*} [AddCommGroup M₂] [Module R M₂] {M₃ : Type*}
[AddCommGroup M₃] [Module R M₃] (f : M →ₗ[R] M₃) (g : M₂ →ₗ[R] M₃)
(hd : Disjoint (range f) (range g)) : ker (f.coprod g) = (ker f).prod (ker g) := by
apply le_antisymm _ (ker_prod_ker_le_ker_coprod f g)
rintro ⟨y, z⟩ h
simp only [mem_ker, mem_prod, coprod_apply] at h ⊢
have : f y ∈ (range f) ⊓ (range g) := by
simp only [true_and_iff, mem_range, mem_inf, exists_apply_eq_apply]
use -z
rwa [eq_comm, map_neg, ← sub_eq_zero, sub_neg_eq_add]
rw [hd.eq_bot, mem_bot] at this
rw [this] at h
simpa [this] using h
#align linear_map.ker_coprod_of_disjoint_range LinearMap.ker_coprod_of_disjoint_range
end LinearMap
namespace Submodule
open LinearMap
variable [Semiring R]
variable [AddCommMonoid M] [AddCommMonoid M₂]
variable [Module R M] [Module R M₂]
theorem sup_eq_range (p q : Submodule R M) : p ⊔ q = range (p.subtype.coprod q.subtype) :=
Submodule.ext fun x => by simp [Submodule.mem_sup, SetLike.exists]
#align submodule.sup_eq_range Submodule.sup_eq_range
variable (p : Submodule R M) (q : Submodule R M₂)
@[simp]
theorem map_inl : p.map (inl R M M₂) = prod p ⊥ := by
ext ⟨x, y⟩
simp only [and_left_comm, eq_comm, mem_map, Prod.mk.inj_iff, inl_apply, mem_bot, exists_eq_left',
mem_prod]
#align submodule.map_inl Submodule.map_inl
@[simp]
theorem map_inr : q.map (inr R M M₂) = prod ⊥ q := by
ext ⟨x, y⟩; simp [and_left_comm, eq_comm, and_comm]
#align submodule.map_inr Submodule.map_inr
@[simp]
theorem comap_fst : p.comap (fst R M M₂) = prod p ⊤ := by ext ⟨x, y⟩; simp
#align submodule.comap_fst Submodule.comap_fst
@[simp]
theorem comap_snd : q.comap (snd R M M₂) = prod ⊤ q := by ext ⟨x, y⟩; simp
#align submodule.comap_snd Submodule.comap_snd
@[simp]
theorem prod_comap_inl : (prod p q).comap (inl R M M₂) = p := by ext; simp
#align submodule.prod_comap_inl Submodule.prod_comap_inl
@[simp]
theorem prod_comap_inr : (prod p q).comap (inr R M M₂) = q := by ext; simp
#align submodule.prod_comap_inr Submodule.prod_comap_inr
@[simp]
theorem prod_map_fst : (prod p q).map (fst R M M₂) = p := by
ext x; simp [(⟨0, zero_mem _⟩ : ∃ x, x ∈ q)]
#align submodule.prod_map_fst Submodule.prod_map_fst
@[simp]
theorem prod_map_snd : (prod p q).map (snd R M M₂) = q := by
ext x; simp [(⟨0, zero_mem _⟩ : ∃ x, x ∈ p)]
#align submodule.prod_map_snd Submodule.prod_map_snd
@[simp]
theorem ker_inl : ker (inl R M M₂) = ⊥ := by rw [ker, ← prod_bot, prod_comap_inl]
#align submodule.ker_inl Submodule.ker_inl
@[simp]
theorem ker_inr : ker (inr R M M₂) = ⊥ := by rw [ker, ← prod_bot, prod_comap_inr]
#align submodule.ker_inr Submodule.ker_inr
@[simp]
theorem range_fst : range (fst R M M₂) = ⊤ := by rw [range_eq_map, ← prod_top, prod_map_fst]
#align submodule.range_fst Submodule.range_fst
@[simp]
theorem range_snd : range (snd R M M₂) = ⊤ := by rw [range_eq_map, ← prod_top, prod_map_snd]
#align submodule.range_snd Submodule.range_snd
variable (R M M₂)
/-- `M` as a submodule of `M × N`. -/
def fst : Submodule R (M × M₂) :=
(⊥ : Submodule R M₂).comap (LinearMap.snd R M M₂)
#align submodule.fst Submodule.fst
/-- `M` as a submodule of `M × N` is isomorphic to `M`. -/
@[simps]
def fstEquiv : Submodule.fst R M M₂ ≃ₗ[R] M where
-- Porting note: proofs were `tidy` or `simp`
toFun x := x.1.1
invFun m := ⟨⟨m, 0⟩, by simp only [fst, comap_bot, mem_ker, snd_apply]⟩
map_add' := by simp only [AddSubmonoid.coe_add, coe_toAddSubmonoid, Prod.fst_add, Subtype.forall,
implies_true, Prod.forall, forall_const]
map_smul' := by simp only [SetLike.val_smul, Prod.smul_fst, RingHom.id_apply, Subtype.forall,
implies_true, Prod.forall, forall_const]
left_inv := by
rintro ⟨⟨x, y⟩, hy⟩
simp only [fst, comap_bot, mem_ker, snd_apply] at hy
simpa only [Subtype.mk.injEq, Prod.mk.injEq, true_and] using hy.symm
right_inv := by rintro x; rfl
#align submodule.fst_equiv Submodule.fstEquiv
theorem fst_map_fst : (Submodule.fst R M M₂).map (LinearMap.fst R M M₂) = ⊤ := by
-- Porting note (#10936): was `tidy`
rw [eq_top_iff]; rintro x -
simp only [fst, comap_bot, mem_map, mem_ker, snd_apply, fst_apply,
Prod.exists, exists_eq_left, exists_eq]
#align submodule.fst_map_fst Submodule.fst_map_fst
theorem fst_map_snd : (Submodule.fst R M M₂).map (LinearMap.snd R M M₂) = ⊥ := by
-- Porting note (#10936): was `tidy`
rw [eq_bot_iff]; intro x
simp only [fst, comap_bot, mem_map, mem_ker, snd_apply, eq_comm, Prod.exists, exists_eq_left,
exists_const, mem_bot, imp_self]
#align submodule.fst_map_snd Submodule.fst_map_snd
/-- `N` as a submodule of `M × N`. -/
def snd : Submodule R (M × M₂) :=
(⊥ : Submodule R M).comap (LinearMap.fst R M M₂)
#align submodule.snd Submodule.snd
/-- `N` as a submodule of `M × N` is isomorphic to `N`. -/
@[simps]
def sndEquiv : Submodule.snd R M M₂ ≃ₗ[R] M₂ where
-- Porting note: proofs were `tidy` or `simp`
toFun x := x.1.2
invFun n := ⟨⟨0, n⟩, by simp only [snd, comap_bot, mem_ker, fst_apply]⟩
map_add' := by simp only [AddSubmonoid.coe_add, coe_toAddSubmonoid, Prod.snd_add, Subtype.forall,
implies_true, Prod.forall, forall_const]
map_smul' := by simp only [SetLike.val_smul, Prod.smul_snd, RingHom.id_apply, Subtype.forall,
implies_true, Prod.forall, forall_const]
left_inv := by
rintro ⟨⟨x, y⟩, hx⟩
simp only [snd, comap_bot, mem_ker, fst_apply] at hx
simpa only [Subtype.mk.injEq, Prod.mk.injEq, and_true] using hx.symm
right_inv := by rintro x; rfl
#align submodule.snd_equiv Submodule.sndEquiv
theorem snd_map_fst : (Submodule.snd R M M₂).map (LinearMap.fst R M M₂) = ⊥ := by
-- Porting note (#10936): was `tidy`
rw [eq_bot_iff]; intro x
simp only [snd, comap_bot, mem_map, mem_ker, fst_apply, eq_comm, Prod.exists, exists_eq_left,
exists_const, mem_bot, imp_self]
#align submodule.snd_map_fst Submodule.snd_map_fst
theorem snd_map_snd : (Submodule.snd R M M₂).map (LinearMap.snd R M M₂) = ⊤ := by
-- Porting note (#10936): was `tidy`
rw [eq_top_iff]; rintro x -
simp only [snd, comap_bot, mem_map, mem_ker, snd_apply, fst_apply,
Prod.exists, exists_eq_right, exists_eq]
#align submodule.snd_map_snd Submodule.snd_map_snd
theorem fst_sup_snd : Submodule.fst R M M₂ ⊔ Submodule.snd R M M₂ = ⊤ := by
rw [eq_top_iff]
rintro ⟨m, n⟩ -
rw [show (m, n) = (m, 0) + (0, n) by simp]
apply Submodule.add_mem (Submodule.fst R M M₂ ⊔ Submodule.snd R M M₂)
· exact Submodule.mem_sup_left (Submodule.mem_comap.mpr (by simp))
· exact Submodule.mem_sup_right (Submodule.mem_comap.mpr (by simp))
#align submodule.fst_sup_snd Submodule.fst_sup_snd
theorem fst_inf_snd : Submodule.fst R M M₂ ⊓ Submodule.snd R M M₂ = ⊥ := by
-- Porting note (#10936): was `tidy`
rw [eq_bot_iff]; rintro ⟨x, y⟩
simp only [fst, comap_bot, snd, ge_iff_le, mem_inf, mem_ker, snd_apply, fst_apply, mem_bot,
Prod.mk_eq_zero, and_comm, imp_self]
#align submodule.fst_inf_snd Submodule.fst_inf_snd
theorem le_prod_iff {p₁ : Submodule R M} {p₂ : Submodule R M₂} {q : Submodule R (M × M₂)} :
q ≤ p₁.prod p₂ ↔ map (LinearMap.fst R M M₂) q ≤ p₁ ∧ map (LinearMap.snd R M M₂) q ≤ p₂ := by
constructor
· intro h
constructor
· rintro x ⟨⟨y1, y2⟩, ⟨hy1, rfl⟩⟩
exact (h hy1).1
· rintro x ⟨⟨y1, y2⟩, ⟨hy1, rfl⟩⟩
exact (h hy1).2
· rintro ⟨hH, hK⟩ ⟨x1, x2⟩ h
exact ⟨hH ⟨_, h, rfl⟩, hK ⟨_, h, rfl⟩⟩
#align submodule.le_prod_iff Submodule.le_prod_iff
| Mathlib/LinearAlgebra/Prod.lean | 704 | 722 | theorem prod_le_iff {p₁ : Submodule R M} {p₂ : Submodule R M₂} {q : Submodule R (M × M₂)} :
p₁.prod p₂ ≤ q ↔ map (LinearMap.inl R M M₂) p₁ ≤ q ∧ map (LinearMap.inr R M M₂) p₂ ≤ q := by |
constructor
· intro h
constructor
· rintro _ ⟨x, hx, rfl⟩
apply h
exact ⟨hx, zero_mem p₂⟩
· rintro _ ⟨x, hx, rfl⟩
apply h
exact ⟨zero_mem p₁, hx⟩
· rintro ⟨hH, hK⟩ ⟨x1, x2⟩ ⟨h1, h2⟩
have h1' : (LinearMap.inl R _ _) x1 ∈ q := by
apply hH
simpa using h1
have h2' : (LinearMap.inr R _ _) x2 ∈ q := by
apply hK
simpa using h2
simpa using add_mem h1' h2'
|
/-
Copyright (c) 2024 Markus Himmel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Markus Himmel
-/
import Mathlib.CategoryTheory.Limits.FinallySmall
import Mathlib.CategoryTheory.Limits.Presheaf
import Mathlib.CategoryTheory.Filtered.Small
/-!
# Ind-objects
For a presheaf `A : Cᵒᵖ ⥤ Type v` we define the type `IndObjectPresentation A` of presentations
of `A` as a small filtered colimit of representable presheaves and define the predicate
`IsIndObject A` asserting that there is at least one such presentation.
A presheaf is an ind-object if and only if the category `CostructuredArrow yoneda A` is filtered
and finally small. In this way, `CostructuredArrow yoneda A` can be thought of the universal
indexing category for the representation of `A` as a small filtered colimit of representable
presheaves.
## Future work
There are various useful ways to understand natural transformations between ind-objects in terms
of their presentations.
The ind-objects form a locally `v`-small category `IndCategory C` which has numerous interesting
properties.
## Implementation notes
One might be tempted to introduce another universe parameter and consider being a `w`-ind-object
as a property of presheaves `C ⥤ TypeMax.{v, w}`. This comes with significant technical hurdles.
The recommended alternative is to consider ind-objects over `ULiftHom.{w} C` instead.
## References
* [M. Kashiwara, P. Schapira, *Categories and Sheaves*][Kashiwara2006], Chapter 6
-/
universe v u
namespace CategoryTheory.Limits
variable {C : Type u} [Category.{v} C]
/-- The data that witnesses that a presheaf `A` is an ind-object. It consists of a small
filtered indexing category `I`, a diagram `F : I ⥤ C` and the data for a colimit cocone on
`F ⋙ yoneda : I ⥤ Cᵒᵖ ⥤ Type v` with cocone point `A`. -/
structure IndObjectPresentation (A : Cᵒᵖ ⥤ Type v) where
/-- The indexing category of the filtered colimit presentation -/
I : Type v
/-- The indexing category of the filtered colimit presentation -/
[ℐ : SmallCategory I]
[hI : IsFiltered I]
/-- The diagram of the filtered colimit presentation -/
F : I ⥤ C
/-- Use `IndObjectPresentation.cocone` instead. -/
ι : F ⋙ yoneda ⟶ (Functor.const I).obj A
/-- Use `IndObjectPresenation.coconeIsColimit` instead. -/
isColimit : IsColimit (Cocone.mk A ι)
namespace IndObjectPresentation
/-- Alternative constructor for `IndObjectPresentation` taking a cocone instead of its defining
natural transformation. -/
@[simps]
def ofCocone {I : Type v} [SmallCategory I] [IsFiltered I] {F : I ⥤ C}
(c : Cocone (F ⋙ yoneda)) (hc : IsColimit c) : IndObjectPresentation c.pt where
I := I
F := F
ι := c.ι
isColimit := hc
variable {A : Cᵒᵖ ⥤ Type v} (P : IndObjectPresentation A)
instance : SmallCategory P.I := P.ℐ
instance : IsFiltered P.I := P.hI
/-- The (colimit) cocone with cocone point `A`. -/
@[simps pt]
def cocone : Cocone (P.F ⋙ yoneda) where
pt := A
ι := P.ι
/-- `P.cocone` is a colimit cocone. -/
def coconeIsColimit : IsColimit P.cocone :=
P.isColimit
/-- If `A` and `B` are isomorphic, then an ind-object presentation of `A` can be extended to an
ind-object presentation of `B`. -/
@[simps!]
noncomputable def extend {A B : Cᵒᵖ ⥤ Type v} (P : IndObjectPresentation A) (η : A ⟶ B) [IsIso η] :
IndObjectPresentation B :=
.ofCocone (P.cocone.extend η) (P.coconeIsColimit.extendIso (by exact η))
/-- The canonical comparison functor between the indexing category of the presentation and the
comma category `CostructuredArrow yoneda A`. This functor is always final. -/
@[simps! obj_left obj_right_as obj_hom map_left]
def toCostructuredArrow : P.I ⥤ CostructuredArrow yoneda A :=
P.cocone.toCostructuredArrow ⋙ CostructuredArrow.pre _ _ _
instance : P.toCostructuredArrow.Final :=
final_toCostructuredArrow_comp_pre _ P.coconeIsColimit
/-- Representable presheaves are (trivially) ind-objects. -/
@[simps]
def yoneda (X : C) : IndObjectPresentation (yoneda.obj X) where
I := Discrete PUnit.{v + 1}
F := Functor.fromPUnit X
ι := { app := fun s => 𝟙 _ }
isColimit :=
{ desc := fun s => s.ι.app ⟨PUnit.unit⟩
uniq := fun s m h => h ⟨PUnit.unit⟩ }
end IndObjectPresentation
/-- A presheaf is called an ind-object if it can be written as a filtered colimit of representable
presheaves. -/
structure IsIndObject (A : Cᵒᵖ ⥤ Type v) : Prop where
mk' :: nonempty_presentation : Nonempty (IndObjectPresentation A)
theorem IsIndObject.mk {A : Cᵒᵖ ⥤ Type v} (P : IndObjectPresentation A) : IsIndObject A :=
⟨⟨P⟩⟩
/-- Representable presheaves are (trivially) ind-objects. -/
theorem isIndObject_yoneda (X : C) : IsIndObject (yoneda.obj X) :=
.mk <| IndObjectPresentation.yoneda X
namespace IsIndObject
variable {A : Cᵒᵖ ⥤ Type v}
theorem map {A B : Cᵒᵖ ⥤ Type v} (η : A ⟶ B) [IsIso η] : IsIndObject A → IsIndObject B
| ⟨⟨P⟩⟩ => ⟨⟨P.extend η⟩⟩
theorem iff_of_iso {A B : Cᵒᵖ ⥤ Type v} (η : A ⟶ B) [IsIso η] : IsIndObject A ↔ IsIndObject B :=
⟨.map η, .map (inv η)⟩
/-- Pick a presentation for an ind-object using choice. -/
noncomputable def presentation : IsIndObject A → IndObjectPresentation A
| ⟨P⟩ => P.some
theorem isFiltered (h : IsIndObject A) : IsFiltered (CostructuredArrow yoneda A) :=
IsFiltered.of_final h.presentation.toCostructuredArrow
theorem finallySmall (h : IsIndObject A) : FinallySmall.{v} (CostructuredArrow yoneda A) :=
FinallySmall.mk' h.presentation.toCostructuredArrow
end IsIndObject
open IsFiltered.SmallFilteredIntermediate
| Mathlib/CategoryTheory/Limits/Indization/IndObject.lean | 153 | 166 | theorem isIndObject_of_isFiltered_of_finallySmall (A : Cᵒᵖ ⥤ Type v)
[IsFiltered (CostructuredArrow yoneda A)] [FinallySmall.{v} (CostructuredArrow yoneda A)] :
IsIndObject A := by |
have h₁ : (factoring (fromFinalModel (CostructuredArrow yoneda A)) ⋙
inclusion (fromFinalModel (CostructuredArrow yoneda A))).Final := Functor.final_of_natIso
(factoringCompInclusion (fromFinalModel <| CostructuredArrow yoneda A)).symm
have h₂ : Functor.Final (inclusion (fromFinalModel (CostructuredArrow yoneda A))) :=
Functor.final_of_comp_full_faithful' (factoring _) (inclusion _)
let c := (tautologicalCocone A).whisker (inclusion (fromFinalModel (CostructuredArrow yoneda A)))
let hc : IsColimit c := (Functor.Final.isColimitWhiskerEquiv _ _).symm
(isColimitTautologicalCocone A)
have hq : Nonempty (FinalModel (CostructuredArrow yoneda A)) := Nonempty.map
(Functor.Final.lift (fromFinalModel (CostructuredArrow yoneda A))) IsFiltered.nonempty
exact ⟨_, inclusion (fromFinalModel _) ⋙ CostructuredArrow.proj yoneda A, c.ι, hc⟩
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau
-/
import Mathlib.Algebra.DirectSum.Basic
import Mathlib.LinearAlgebra.DFinsupp
import Mathlib.LinearAlgebra.Basis
#align_import algebra.direct_sum.module from "leanprover-community/mathlib"@"6623e6af705e97002a9054c1c05a980180276fc1"
/-!
# Direct sum of modules
The first part of the file provides constructors for direct sums of modules. It provides a
construction of the direct sum using the universal property and proves its uniqueness
(`DirectSum.toModule.unique`).
The second part of the file covers the special case of direct sums of submodules of a fixed module
`M`. There is a canonical linear map from this direct sum to `M` (`DirectSum.coeLinearMap`), and
the construction is of particular importance when this linear map is an equivalence; that is, when
the submodules provide an internal decomposition of `M`. The property is defined more generally
elsewhere as `DirectSum.IsInternal`, but its basic consequences on `Submodule`s are established
in this file.
-/
universe u v w u₁
namespace DirectSum
open DirectSum
section General
variable {R : Type u} [Semiring R]
variable {ι : Type v} [dec_ι : DecidableEq ι]
variable {M : ι → Type w} [∀ i, AddCommMonoid (M i)] [∀ i, Module R (M i)]
instance : Module R (⨁ i, M i) :=
DFinsupp.module
instance {S : Type*} [Semiring S] [∀ i, Module S (M i)] [∀ i, SMulCommClass R S (M i)] :
SMulCommClass R S (⨁ i, M i) :=
DFinsupp.smulCommClass
instance {S : Type*} [Semiring S] [SMul R S] [∀ i, Module S (M i)] [∀ i, IsScalarTower R S (M i)] :
IsScalarTower R S (⨁ i, M i) :=
DFinsupp.isScalarTower
instance [∀ i, Module Rᵐᵒᵖ (M i)] [∀ i, IsCentralScalar R (M i)] : IsCentralScalar R (⨁ i, M i) :=
DFinsupp.isCentralScalar
theorem smul_apply (b : R) (v : ⨁ i, M i) (i : ι) : (b • v) i = b • v i :=
DFinsupp.smul_apply _ _ _
#align direct_sum.smul_apply DirectSum.smul_apply
variable (R ι M)
/-- Create the direct sum given a family `M` of `R` modules indexed over `ι`. -/
def lmk : ∀ s : Finset ι, (∀ i : (↑s : Set ι), M i.val) →ₗ[R] ⨁ i, M i :=
DFinsupp.lmk
#align direct_sum.lmk DirectSum.lmk
/-- Inclusion of each component into the direct sum. -/
def lof : ∀ i : ι, M i →ₗ[R] ⨁ i, M i :=
DFinsupp.lsingle
#align direct_sum.lof DirectSum.lof
theorem lof_eq_of (i : ι) (b : M i) : lof R ι M i b = of M i b := rfl
#align direct_sum.lof_eq_of DirectSum.lof_eq_of
variable {ι M}
theorem single_eq_lof (i : ι) (b : M i) : DFinsupp.single i b = lof R ι M i b := rfl
#align direct_sum.single_eq_lof DirectSum.single_eq_lof
/-- Scalar multiplication commutes with direct sums. -/
theorem mk_smul (s : Finset ι) (c : R) (x) : mk M s (c • x) = c • mk M s x :=
(lmk R ι M s).map_smul c x
#align direct_sum.mk_smul DirectSum.mk_smul
/-- Scalar multiplication commutes with the inclusion of each component into the direct sum. -/
theorem of_smul (i : ι) (c : R) (x) : of M i (c • x) = c • of M i x :=
(lof R ι M i).map_smul c x
#align direct_sum.of_smul DirectSum.of_smul
variable {R}
theorem support_smul [∀ (i : ι) (x : M i), Decidable (x ≠ 0)] (c : R) (v : ⨁ i, M i) :
(c • v).support ⊆ v.support :=
DFinsupp.support_smul _ _
#align direct_sum.support_smul DirectSum.support_smul
variable {N : Type u₁} [AddCommMonoid N] [Module R N]
variable (φ : ∀ i, M i →ₗ[R] N)
variable (R ι N)
/-- The linear map constructed using the universal property of the coproduct. -/
def toModule : (⨁ i, M i) →ₗ[R] N :=
DFunLike.coe (DFinsupp.lsum ℕ) φ
#align direct_sum.to_module DirectSum.toModule
/-- Coproducts in the categories of modules and additive monoids commute with the forgetful functor
from modules to additive monoids. -/
theorem coe_toModule_eq_coe_toAddMonoid :
(toModule R ι N φ : (⨁ i, M i) → N) = toAddMonoid fun i ↦ (φ i).toAddMonoidHom := rfl
#align direct_sum.coe_to_module_eq_coe_to_add_monoid DirectSum.coe_toModule_eq_coe_toAddMonoid
variable {ι N φ}
/-- The map constructed using the universal property gives back the original maps when
restricted to each component. -/
@[simp]
theorem toModule_lof (i) (x : M i) : toModule R ι N φ (lof R ι M i x) = φ i x :=
toAddMonoid_of (fun i ↦ (φ i).toAddMonoidHom) i x
#align direct_sum.to_module_lof DirectSum.toModule_lof
variable (ψ : (⨁ i, M i) →ₗ[R] N)
/-- Every linear map from a direct sum agrees with the one obtained by applying
the universal property to each of its components. -/
theorem toModule.unique (f : ⨁ i, M i) : ψ f = toModule R ι N (fun i ↦ ψ.comp <| lof R ι M i) f :=
toAddMonoid.unique ψ.toAddMonoidHom f
#align direct_sum.to_module.unique DirectSum.toModule.unique
variable {ψ} {ψ' : (⨁ i, M i) →ₗ[R] N}
/-- Two `LinearMap`s out of a direct sum are equal if they agree on the generators.
See note [partially-applied ext lemmas]. -/
@[ext]
theorem linearMap_ext ⦃ψ ψ' : (⨁ i, M i) →ₗ[R] N⦄
(H : ∀ i, ψ.comp (lof R ι M i) = ψ'.comp (lof R ι M i)) : ψ = ψ' :=
DFinsupp.lhom_ext' H
#align direct_sum.linear_map_ext DirectSum.linearMap_ext
/-- The inclusion of a subset of the direct summands
into a larger subset of the direct summands, as a linear map. -/
def lsetToSet (S T : Set ι) (H : S ⊆ T) : (⨁ i : S, M i) →ₗ[R] ⨁ i : T, M i :=
toModule R _ _ fun i ↦ lof R T (fun i : Subtype T ↦ M i) ⟨i, H i.prop⟩
#align direct_sum.lset_to_set DirectSum.lsetToSet
variable (ι M)
/-- Given `Fintype α`, `linearEquivFunOnFintype R` is the natural `R`-linear equivalence
between `⨁ i, M i` and `∀ i, M i`. -/
@[simps apply]
def linearEquivFunOnFintype [Fintype ι] : (⨁ i, M i) ≃ₗ[R] ∀ i, M i :=
{ DFinsupp.equivFunOnFintype with
toFun := (↑)
map_add' := fun f g ↦ by
ext
rw [add_apply, Pi.add_apply]
map_smul' := fun c f ↦ by
simp_rw [RingHom.id_apply]
rw [DFinsupp.coe_smul] }
#align direct_sum.linear_equiv_fun_on_fintype DirectSum.linearEquivFunOnFintype
variable {ι M}
@[simp]
theorem linearEquivFunOnFintype_lof [Fintype ι] [DecidableEq ι] (i : ι) (m : M i) :
(linearEquivFunOnFintype R ι M) (lof R ι M i m) = Pi.single i m := by
ext a
change (DFinsupp.equivFunOnFintype (lof R ι M i m)) a = _
convert _root_.congr_fun (DFinsupp.equivFunOnFintype_single i m) a
#align direct_sum.linear_equiv_fun_on_fintype_lof DirectSum.linearEquivFunOnFintype_lof
@[simp]
theorem linearEquivFunOnFintype_symm_single [Fintype ι] [DecidableEq ι] (i : ι) (m : M i) :
(linearEquivFunOnFintype R ι M).symm (Pi.single i m) = lof R ι M i m := by
change (DFinsupp.equivFunOnFintype.symm (Pi.single i m)) = _
rw [DFinsupp.equivFunOnFintype_symm_single i m]
rfl
#align direct_sum.linear_equiv_fun_on_fintype_symm_single DirectSum.linearEquivFunOnFintype_symm_single
@[simp]
| Mathlib/Algebra/DirectSum/Module.lean | 180 | 182 | theorem linearEquivFunOnFintype_symm_coe [Fintype ι] (f : ⨁ i, M i) :
(linearEquivFunOnFintype R ι M).symm f = f := by |
simp [linearEquivFunOnFintype]
|
/-
Copyright (c) 2022 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alex Best, Riccardo Brasca, Eric Rodriguez
-/
import Mathlib.Data.PNat.Prime
import Mathlib.Algebra.IsPrimePow
import Mathlib.NumberTheory.Cyclotomic.Basic
import Mathlib.RingTheory.Adjoin.PowerBasis
import Mathlib.RingTheory.Polynomial.Cyclotomic.Eval
import Mathlib.RingTheory.Norm
import Mathlib.RingTheory.Polynomial.Cyclotomic.Expand
#align_import number_theory.cyclotomic.primitive_roots from "leanprover-community/mathlib"@"5bfbcca0a7ffdd21cf1682e59106d6c942434a32"
/-!
# Primitive roots in cyclotomic fields
If `IsCyclotomicExtension {n} A B`, we define an element `zeta n A B : B` that is a primitive
`n`th-root of unity in `B` and we study its properties. We also prove related theorems under the
more general assumption of just being a primitive root, for reasons described in the implementation
details section.
## Main definitions
* `IsCyclotomicExtension.zeta n A B`: if `IsCyclotomicExtension {n} A B`, than `zeta n A B`
is a primitive `n`-th root of unity in `B`.
* `IsPrimitiveRoot.powerBasis`: if `K` and `L` are fields such that
`IsCyclotomicExtension {n} K L`, then `IsPrimitiveRoot.powerBasis`
gives a `K`-power basis for `L` given a primitive root `ζ`.
* `IsPrimitiveRoot.embeddingsEquivPrimitiveRoots`: the equivalence between `L →ₐ[K] A`
and `primitiveroots n A` given by the choice of `ζ`.
## Main results
* `IsCyclotomicExtension.zeta_spec`: `zeta n A B` is a primitive `n`-th root of unity.
* `IsCyclotomicExtension.finrank`: if `Irreducible (cyclotomic n K)` (in particular for
`K = ℚ`), then the `finrank` of a cyclotomic extension is `n.totient`.
* `IsPrimitiveRoot.norm_eq_one`: if `Irreducible (cyclotomic n K)` (in particular for `K = ℚ`),
the norm of a primitive root is `1` if `n ≠ 2`.
* `IsPrimitiveRoot.sub_one_norm_eq_eval_cyclotomic`: if `Irreducible (cyclotomic n K)`
(in particular for `K = ℚ`), then the norm of `ζ - 1` is `eval 1 (cyclotomic n ℤ)`, for a
primitive root `ζ`. We also prove the analogous of this result for `zeta`.
* `IsPrimitiveRoot.norm_pow_sub_one_of_prime_pow_ne_two` : if
`Irreducible (cyclotomic (p ^ (k + 1)) K)` (in particular for `K = ℚ`) and `p` is a prime,
then the norm of `ζ ^ (p ^ s) - 1` is `p ^ (p ^ s)` `p ^ (k - s + 1) ≠ 2`. See the following
lemmas for similar results. We also prove the analogous of this result for `zeta`.
* `IsPrimitiveRoot.norm_sub_one_of_prime_ne_two` : if `Irreducible (cyclotomic (p ^ (k + 1)) K)`
(in particular for `K = ℚ`) and `p` is an odd prime, then the norm of `ζ - 1` is `p`. We also
prove the analogous of this result for `zeta`.
* `IsPrimitiveRoot.embeddingsEquivPrimitiveRoots`: the equivalence between `L →ₐ[K] A`
and `primitiveRoots n A` given by the choice of `ζ`.
## Implementation details
`zeta n A B` is defined as any primitive root of unity in `B`, - this must exist, by definition of
`IsCyclotomicExtension`. It is not true in general that it is a root of `cyclotomic n B`,
but this holds if `isDomain B` and `NeZero (↑n : B)`.
`zeta n A B` is defined using `Exists.choose`, which means we cannot control it.
For example, in normal mathematics, we can demand that `(zeta p ℤ ℤ[ζₚ] : ℚ(ζₚ))` is equal to
`zeta p ℚ ℚ(ζₚ)`, as we are just choosing "an arbitrary primitive root" and we can internally
specify that our choices agree. This is not the case here, and it is indeed impossible to prove that
these two are equal. Therefore, whenever possible, we prove our results for any primitive root,
and only at the "final step", when we need to provide an "explicit" primitive root, we use `zeta`.
-/
open Polynomial Algebra Finset FiniteDimensional IsCyclotomicExtension Nat PNat Set
open scoped IntermediateField
universe u v w z
variable {p n : ℕ+} (A : Type w) (B : Type z) (K : Type u) {L : Type v} (C : Type w)
variable [CommRing A] [CommRing B] [Algebra A B] [IsCyclotomicExtension {n} A B]
section Zeta
namespace IsCyclotomicExtension
variable (n)
/-- If `B` is an `n`-th cyclotomic extension of `A`, then `zeta n A B` is a primitive root of
unity in `B`. -/
noncomputable def zeta : B :=
(exists_prim_root A <| Set.mem_singleton n : ∃ r : B, IsPrimitiveRoot r n).choose
#align is_cyclotomic_extension.zeta IsCyclotomicExtension.zeta
/-- `zeta n A B` is a primitive `n`-th root of unity. -/
@[simp]
theorem zeta_spec : IsPrimitiveRoot (zeta n A B) n :=
Classical.choose_spec (exists_prim_root A (Set.mem_singleton n) : ∃ r : B, IsPrimitiveRoot r n)
#align is_cyclotomic_extension.zeta_spec IsCyclotomicExtension.zeta_spec
theorem aeval_zeta [IsDomain B] [NeZero ((n : ℕ) : B)] :
aeval (zeta n A B) (cyclotomic n A) = 0 := by
rw [aeval_def, ← eval_map, ← IsRoot.def, map_cyclotomic, isRoot_cyclotomic_iff]
exact zeta_spec n A B
#align is_cyclotomic_extension.aeval_zeta IsCyclotomicExtension.aeval_zeta
theorem zeta_isRoot [IsDomain B] [NeZero ((n : ℕ) : B)] : IsRoot (cyclotomic n B) (zeta n A B) := by
convert aeval_zeta n A B using 0
rw [IsRoot.def, aeval_def, eval₂_eq_eval_map, map_cyclotomic]
#align is_cyclotomic_extension.zeta_is_root IsCyclotomicExtension.zeta_isRoot
theorem zeta_pow : zeta n A B ^ (n : ℕ) = 1 :=
(zeta_spec n A B).pow_eq_one
#align is_cyclotomic_extension.zeta_pow IsCyclotomicExtension.zeta_pow
end IsCyclotomicExtension
end Zeta
section NoOrder
variable [Field K] [CommRing L] [IsDomain L] [Algebra K L] [IsCyclotomicExtension {n} K L] {ζ : L}
(hζ : IsPrimitiveRoot ζ n)
namespace IsPrimitiveRoot
variable {C}
/-- The `PowerBasis` given by a primitive root `η`. -/
@[simps!]
protected noncomputable def powerBasis : PowerBasis K L :=
PowerBasis.map (Algebra.adjoin.powerBasis <| (integral {n} K L).isIntegral ζ) <|
(Subalgebra.equivOfEq _ _ (IsCyclotomicExtension.adjoin_primitive_root_eq_top hζ)).trans
Subalgebra.topEquiv
#align is_primitive_root.power_basis IsPrimitiveRoot.powerBasis
theorem powerBasis_gen_mem_adjoin_zeta_sub_one :
(hζ.powerBasis K).gen ∈ adjoin K ({ζ - 1} : Set L) := by
rw [powerBasis_gen, adjoin_singleton_eq_range_aeval, AlgHom.mem_range]
exact ⟨X + 1, by simp⟩
#align is_primitive_root.power_basis_gen_mem_adjoin_zeta_sub_one IsPrimitiveRoot.powerBasis_gen_mem_adjoin_zeta_sub_one
/-- The `PowerBasis` given by `η - 1`. -/
@[simps!]
noncomputable def subOnePowerBasis : PowerBasis K L :=
(hζ.powerBasis K).ofGenMemAdjoin
(((integral {n} K L).isIntegral ζ).sub isIntegral_one)
(hζ.powerBasis_gen_mem_adjoin_zeta_sub_one _)
#align is_primitive_root.sub_one_power_basis IsPrimitiveRoot.subOnePowerBasis
variable {K} (C)
-- We are not using @[simps] to avoid a timeout.
/-- The equivalence between `L →ₐ[K] C` and `primitiveRoots n C` given by a primitive root `ζ`. -/
noncomputable def embeddingsEquivPrimitiveRoots (C : Type*) [CommRing C] [IsDomain C] [Algebra K C]
(hirr : Irreducible (cyclotomic n K)) : (L →ₐ[K] C) ≃ primitiveRoots n C :=
(hζ.powerBasis K).liftEquiv.trans
{ toFun := fun x => by
haveI := IsCyclotomicExtension.neZero' n K L
haveI hn := NeZero.of_noZeroSMulDivisors K C n
refine ⟨x.1, ?_⟩
cases x
rwa [mem_primitiveRoots n.pos, ← isRoot_cyclotomic_iff, IsRoot.def,
← map_cyclotomic _ (algebraMap K C), hζ.minpoly_eq_cyclotomic_of_irreducible hirr,
← eval₂_eq_eval_map, ← aeval_def]
invFun := fun x => by
haveI := IsCyclotomicExtension.neZero' n K L
haveI hn := NeZero.of_noZeroSMulDivisors K C n
refine ⟨x.1, ?_⟩
cases x
rwa [aeval_def, eval₂_eq_eval_map, hζ.powerBasis_gen K, ←
hζ.minpoly_eq_cyclotomic_of_irreducible hirr, map_cyclotomic, ← IsRoot.def,
isRoot_cyclotomic_iff, ← mem_primitiveRoots n.pos]
left_inv := fun x => Subtype.ext rfl
right_inv := fun x => Subtype.ext rfl }
#align is_primitive_root.embeddings_equiv_primitive_roots IsPrimitiveRoot.embeddingsEquivPrimitiveRoots
-- Porting note: renamed argument `φ`: "expected '_' or identifier"
@[simp]
theorem embeddingsEquivPrimitiveRoots_apply_coe (C : Type*) [CommRing C] [IsDomain C] [Algebra K C]
(hirr : Irreducible (cyclotomic n K)) (φ' : L →ₐ[K] C) :
(hζ.embeddingsEquivPrimitiveRoots C hirr φ' : C) = φ' ζ :=
rfl
#align is_primitive_root.embeddings_equiv_primitive_roots_apply_coe IsPrimitiveRoot.embeddingsEquivPrimitiveRoots_apply_coe
end IsPrimitiveRoot
namespace IsCyclotomicExtension
variable {K} (L)
/-- If `Irreducible (cyclotomic n K)` (in particular for `K = ℚ`), then the `finrank` of a
cyclotomic extension is `n.totient`. -/
theorem finrank (hirr : Irreducible (cyclotomic n K)) : finrank K L = (n : ℕ).totient := by
haveI := IsCyclotomicExtension.neZero' n K L
rw [((zeta_spec n K L).powerBasis K).finrank, IsPrimitiveRoot.powerBasis_dim, ←
(zeta_spec n K L).minpoly_eq_cyclotomic_of_irreducible hirr, natDegree_cyclotomic]
#align is_cyclotomic_extension.finrank IsCyclotomicExtension.finrank
variable {L} in
/-- If `L` contains both a primitive `p`-th root of unity and `q`-th root of unity, and
`Irreducible (cyclotomic (lcm p q) K)` (in particular for `K = ℚ`), then the `finrank K L` is at
least `(lcm p q).totient`. -/
theorem _root_.IsPrimitiveRoot.lcm_totient_le_finrank [FiniteDimensional K L] {p q : ℕ} {x y : L}
(hx : IsPrimitiveRoot x p) (hy : IsPrimitiveRoot y q)
(hirr : Irreducible (cyclotomic (Nat.lcm p q) K)) :
(Nat.lcm p q).totient ≤ FiniteDimensional.finrank K L := by
rcases Nat.eq_zero_or_pos p with (rfl | hppos)
· simp
rcases Nat.eq_zero_or_pos q with (rfl | hqpos)
· simp
let z := x ^ (p / factorizationLCMLeft p q) * y ^ (q / factorizationLCMRight p q)
let k := PNat.lcm ⟨p, hppos⟩ ⟨q, hqpos⟩
have : IsPrimitiveRoot z k := hx.pow_mul_pow_lcm hy hppos.ne' hqpos.ne'
haveI := IsPrimitiveRoot.adjoin_isCyclotomicExtension K this
convert Submodule.finrank_le (Subalgebra.toSubmodule (adjoin K {z}))
rw [show Nat.lcm p q = (k : ℕ) from rfl] at hirr
simpa using (IsCyclotomicExtension.finrank (Algebra.adjoin K {z}) hirr).symm
end IsCyclotomicExtension
end NoOrder
section Norm
namespace IsPrimitiveRoot
section Field
variable {K} [Field K] [NumberField K]
variable (n) in
/-- If a `n`-th cyclotomic extension of `ℚ` contains a primitive `l`-th root of unity, then
`l ∣ 2 * n`. -/
theorem dvd_of_isCyclotomicExtension [NumberField K] [IsCyclotomicExtension {n} ℚ K] {ζ : K}
{l : ℕ} (hζ : IsPrimitiveRoot ζ l) (hl : l ≠ 0) : l ∣ 2 * n := by
have hl : NeZero l := ⟨hl⟩
have hroot := IsCyclotomicExtension.zeta_spec n ℚ K
have key := IsPrimitiveRoot.lcm_totient_le_finrank hζ hroot
(cyclotomic.irreducible_rat <| Nat.lcm_pos (Nat.pos_of_ne_zero hl.1) n.2)
rw [IsCyclotomicExtension.finrank K (cyclotomic.irreducible_rat n.2)] at key
rcases _root_.dvd_lcm_right l n with ⟨r, hr⟩
have ineq := Nat.totient_super_multiplicative n r
rw [← hr] at ineq
replace key := (mul_le_iff_le_one_right (Nat.totient_pos.2 n.2)).mp (le_trans ineq key)
have rpos : 0 < r := by
refine Nat.pos_of_ne_zero (fun h ↦ ?_)
simp only [h, mul_zero, _root_.lcm_eq_zero_iff, PNat.ne_zero, or_false] at hr
exact hl.1 hr
replace key := (Nat.dvd_prime Nat.prime_two).1 (Nat.dvd_two_of_totient_le_one rpos key)
rcases key with (key | key)
· rw [key, mul_one] at hr
rw [← hr]
exact dvd_mul_of_dvd_right (_root_.dvd_lcm_left l ↑n) 2
· rw [key, mul_comm] at hr
simpa [← hr] using _root_.dvd_lcm_left _ _
/-- If `x` is a root of unity (spelled as `IsOfFinOrder x`) in an `n`-th cyclotomic extension of
`ℚ`, where `n` is odd, and `ζ` is a primitive `n`-th root of unity, then there exist `r`
such that `x = (-ζ)^r`. -/
theorem exists_neg_pow_of_isOfFinOrder [NumberField K] [IsCyclotomicExtension {n} ℚ K]
(hno : Odd (n : ℕ)) {ζ x : K} (hζ : IsPrimitiveRoot ζ n) (hx : IsOfFinOrder x) :
∃ r : ℕ, x = (-ζ) ^ r := by
have hnegζ : IsPrimitiveRoot (-ζ) (2 * n) := by
convert IsPrimitiveRoot.orderOf (-ζ)
rw [neg_eq_neg_one_mul, (Commute.all _ _).orderOf_mul_eq_mul_orderOf_of_coprime]
· simp [hζ.eq_orderOf]
· simp [← hζ.eq_orderOf, Nat.odd_iff_not_even.1 hno]
obtain ⟨k, hkpos, hkn⟩ := isOfFinOrder_iff_pow_eq_one.1 hx
obtain ⟨l, hl, hlroot⟩ := (isRoot_of_unity_iff hkpos _).1 hkn
have hlzero : NeZero l := ⟨fun h ↦ by simp [h] at hl⟩
have : NeZero (l : K) := ⟨NeZero.natCast_ne l K⟩
rw [isRoot_cyclotomic_iff] at hlroot
obtain ⟨a, ha⟩ := hlroot.dvd_of_isCyclotomicExtension n hlzero.1
replace hlroot : x ^ (2 * (n : ℕ)) = 1 := by rw [ha, pow_mul, hlroot.pow_eq_one, one_pow]
obtain ⟨s, -, hs⟩ := hnegζ.eq_pow_of_pow_eq_one hlroot (by simp)
exact ⟨s, hs.symm⟩
/-- If `x` is a root of unity (spelled as `IsOfFinOrder x`) in an `n`-th cyclotomic extension of
`ℚ`, where `n` is odd, and `ζ` is a primitive `n`-th root of unity, then there exists `r < n`
such that `x = ζ^r` or `x = -ζ^r`. -/
theorem exists_pow_or_neg_mul_pow_of_isOfFinOrder [NumberField K] [IsCyclotomicExtension {n} ℚ K]
(hno : Odd (n : ℕ)) {ζ x : K} (hζ : IsPrimitiveRoot ζ n) (hx : IsOfFinOrder x) :
∃ r : ℕ, r < n ∧ (x = ζ ^ r ∨ x = -ζ ^ r) := by
obtain ⟨r, hr⟩ := hζ.exists_neg_pow_of_isOfFinOrder hno hx
refine ⟨r % n, Nat.mod_lt _ n.2, ?_⟩
rw [show ζ ^ (r % ↑n) = ζ ^ r from (IsPrimitiveRoot.eq_orderOf hζ).symm ▸ pow_mod_orderOf .., hr]
rcases Nat.even_or_odd r with (h | h) <;> simp [neg_pow, h.neg_one_pow]
end Field
section CommRing
variable [CommRing L] {ζ : L} (hζ : IsPrimitiveRoot ζ n)
variable {K} [Field K] [Algebra K L]
/-- This mathematically trivial result is complementary to `norm_eq_one` below. -/
theorem norm_eq_neg_one_pow (hζ : IsPrimitiveRoot ζ 2) [IsDomain L] :
norm K ζ = (-1 : K) ^ finrank K L := by
rw [hζ.eq_neg_one_of_two_right, show -1 = algebraMap K L (-1) by simp, Algebra.norm_algebraMap]
#align is_primitive_root.norm_eq_neg_one_pow IsPrimitiveRoot.norm_eq_neg_one_pow
/-- If `Irreducible (cyclotomic n K)` (in particular for `K = ℚ`), the norm of a primitive root is
`1` if `n ≠ 2`. -/
theorem norm_eq_one [IsDomain L] [IsCyclotomicExtension {n} K L] (hn : n ≠ 2)
(hirr : Irreducible (cyclotomic n K)) : norm K ζ = 1 := by
haveI := IsCyclotomicExtension.neZero' n K L
by_cases h1 : n = 1
· rw [h1, one_coe, one_right_iff] at hζ
rw [hζ, show 1 = algebraMap K L 1 by simp, Algebra.norm_algebraMap, one_pow]
· replace h1 : 2 ≤ n := by
by_contra! h
exact h1 (PNat.eq_one_of_lt_two h)
-- Porting note: specyfing the type of `cyclotomic_coeff_zero K h1` was not needed.
rw [← hζ.powerBasis_gen K, PowerBasis.norm_gen_eq_coeff_zero_minpoly, hζ.powerBasis_gen K, ←
hζ.minpoly_eq_cyclotomic_of_irreducible hirr,
(cyclotomic_coeff_zero K h1 : coeff (cyclotomic n K) 0 = 1), mul_one,
hζ.powerBasis_dim K, ← hζ.minpoly_eq_cyclotomic_of_irreducible hirr, natDegree_cyclotomic]
exact (totient_even <| h1.lt_of_ne hn.symm).neg_one_pow
#align is_primitive_root.norm_eq_one IsPrimitiveRoot.norm_eq_one
/-- If `K` is linearly ordered, the norm of a primitive root is `1` if `n` is odd. -/
theorem norm_eq_one_of_linearly_ordered {K : Type*} [LinearOrderedField K] [Algebra K L]
(hodd : Odd (n : ℕ)) : norm K ζ = 1 := by
have hz := congr_arg (norm K) ((IsPrimitiveRoot.iff_def _ n).1 hζ).1
rw [← (algebraMap K L).map_one, Algebra.norm_algebraMap, one_pow, map_pow, ← one_pow ↑n] at hz
exact StrictMono.injective hodd.strictMono_pow hz
#align is_primitive_root.norm_eq_one_of_linearly_ordered IsPrimitiveRoot.norm_eq_one_of_linearly_ordered
theorem norm_of_cyclotomic_irreducible [IsDomain L] [IsCyclotomicExtension {n} K L]
(hirr : Irreducible (cyclotomic n K)) : norm K ζ = ite (n = 2) (-1) 1 := by
split_ifs with hn
· subst hn
convert norm_eq_neg_one_pow (K := K) hζ
erw [IsCyclotomicExtension.finrank _ hirr, totient_two, pow_one]
· exact hζ.norm_eq_one hn hirr
#align is_primitive_root.norm_of_cyclotomic_irreducible IsPrimitiveRoot.norm_of_cyclotomic_irreducible
end CommRing
section Field
variable [Field L] {ζ : L} (hζ : IsPrimitiveRoot ζ n)
variable {K} [Field K] [Algebra K L]
/-- If `Irreducible (cyclotomic n K)` (in particular for `K = ℚ`), then the norm of
`ζ - 1` is `eval 1 (cyclotomic n ℤ)`. -/
theorem sub_one_norm_eq_eval_cyclotomic [IsCyclotomicExtension {n} K L] (h : 2 < (n : ℕ))
(hirr : Irreducible (cyclotomic n K)) : norm K (ζ - 1) = ↑(eval 1 (cyclotomic n ℤ)) := by
haveI := IsCyclotomicExtension.neZero' n K L
let E := AlgebraicClosure L
obtain ⟨z, hz⟩ := IsAlgClosed.exists_root _ (degree_cyclotomic_pos n E n.pos).ne.symm
apply (algebraMap K E).injective
letI := IsCyclotomicExtension.finiteDimensional {n} K L
letI := IsCyclotomicExtension.isGalois n K L
rw [norm_eq_prod_embeddings]
conv_lhs =>
congr
rfl
ext
rw [← neg_sub, AlgHom.map_neg, AlgHom.map_sub, AlgHom.map_one, neg_eq_neg_one_mul]
rw [prod_mul_distrib, prod_const, card_univ, AlgHom.card, IsCyclotomicExtension.finrank L hirr,
(totient_even h).neg_one_pow, one_mul]
have Hprod : (Finset.univ.prod fun σ : L →ₐ[K] E => 1 - σ ζ) = eval 1 (cyclotomic' n E) := by
rw [cyclotomic', eval_prod, ← @Finset.prod_attach E E, ← univ_eq_attach]
refine Fintype.prod_equiv (hζ.embeddingsEquivPrimitiveRoots E hirr) _ _ fun σ => ?_
simp
haveI : NeZero ((n : ℕ) : E) := NeZero.of_noZeroSMulDivisors K _ (n : ℕ)
rw [Hprod, cyclotomic', ← cyclotomic_eq_prod_X_sub_primitiveRoots (isRoot_cyclotomic_iff.1 hz),
← map_cyclotomic_int, _root_.map_intCast, ← Int.cast_one, eval_intCast_map, eq_intCast,
Int.cast_id]
#align is_primitive_root.sub_one_norm_eq_eval_cyclotomic IsPrimitiveRoot.sub_one_norm_eq_eval_cyclotomic
/-- If `IsPrimePow (n : ℕ)`, `n ≠ 2` and `Irreducible (cyclotomic n K)` (in particular for
`K = ℚ`), then the norm of `ζ - 1` is `(n : ℕ).minFac`. -/
| Mathlib/NumberTheory/Cyclotomic/PrimitiveRoots.lean | 367 | 381 | theorem sub_one_norm_isPrimePow (hn : IsPrimePow (n : ℕ)) [IsCyclotomicExtension {n} K L]
(hirr : Irreducible (cyclotomic (n : ℕ) K)) (h : n ≠ 2) : norm K (ζ - 1) = (n : ℕ).minFac := by |
have :=
(coe_lt_coe 2 _).1
(lt_of_le_of_ne (succ_le_of_lt (IsPrimePow.one_lt hn))
(Function.Injective.ne PNat.coe_injective h).symm)
letI hprime : Fact (n : ℕ).minFac.Prime := ⟨minFac_prime (IsPrimePow.ne_one hn)⟩
rw [sub_one_norm_eq_eval_cyclotomic hζ this hirr]
nth_rw 1 [← IsPrimePow.minFac_pow_factorization_eq hn]
obtain ⟨k, hk⟩ : ∃ k, (n : ℕ).factorization (n : ℕ).minFac = k + 1 :=
exists_eq_succ_of_ne_zero
(((n : ℕ).factorization.mem_support_toFun (n : ℕ).minFac).1 <|
mem_primeFactors_iff_mem_factors.2 <|
(mem_factors (IsPrimePow.ne_zero hn)).2 ⟨hprime.out, minFac_dvd _⟩)
simp [hk, sub_one_norm_eq_eval_cyclotomic hζ this hirr]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Sébastien Gouëzel,
Rémy Degenne, David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.Pow.Real
#align_import analysis.special_functions.pow.nnreal from "leanprover-community/mathlib"@"4fa54b337f7d52805480306db1b1439c741848c8"
/-!
# Power function on `ℝ≥0` and `ℝ≥0∞`
We construct the power functions `x ^ y` where
* `x` is a nonnegative real number and `y` is a real number;
* `x` is a number from `[0, +∞]` (a.k.a. `ℝ≥0∞`) and `y` is a real number.
We also prove basic properties of these functions.
-/
noncomputable section
open scoped Classical
open Real NNReal ENNReal ComplexConjugate
open Finset Function Set
namespace NNReal
variable {w x y z : ℝ}
/-- The nonnegative real power function `x^y`, defined for `x : ℝ≥0` and `y : ℝ` as the
restriction of the real power function. For `x > 0`, it is equal to `exp (y log x)`. For `x = 0`,
one sets `0 ^ 0 = 1` and `0 ^ y = 0` for `y ≠ 0`. -/
noncomputable def rpow (x : ℝ≥0) (y : ℝ) : ℝ≥0 :=
⟨(x : ℝ) ^ y, Real.rpow_nonneg x.2 y⟩
#align nnreal.rpow NNReal.rpow
noncomputable instance : Pow ℝ≥0 ℝ :=
⟨rpow⟩
@[simp]
theorem rpow_eq_pow (x : ℝ≥0) (y : ℝ) : rpow x y = x ^ y :=
rfl
#align nnreal.rpow_eq_pow NNReal.rpow_eq_pow
@[simp, norm_cast]
theorem coe_rpow (x : ℝ≥0) (y : ℝ) : ((x ^ y : ℝ≥0) : ℝ) = (x : ℝ) ^ y :=
rfl
#align nnreal.coe_rpow NNReal.coe_rpow
@[simp]
theorem rpow_zero (x : ℝ≥0) : x ^ (0 : ℝ) = 1 :=
NNReal.eq <| Real.rpow_zero _
#align nnreal.rpow_zero NNReal.rpow_zero
@[simp]
theorem rpow_eq_zero_iff {x : ℝ≥0} {y : ℝ} : x ^ y = 0 ↔ x = 0 ∧ y ≠ 0 := by
rw [← NNReal.coe_inj, coe_rpow, ← NNReal.coe_eq_zero]
exact Real.rpow_eq_zero_iff_of_nonneg x.2
#align nnreal.rpow_eq_zero_iff NNReal.rpow_eq_zero_iff
@[simp]
theorem zero_rpow {x : ℝ} (h : x ≠ 0) : (0 : ℝ≥0) ^ x = 0 :=
NNReal.eq <| Real.zero_rpow h
#align nnreal.zero_rpow NNReal.zero_rpow
@[simp]
theorem rpow_one (x : ℝ≥0) : x ^ (1 : ℝ) = x :=
NNReal.eq <| Real.rpow_one _
#align nnreal.rpow_one NNReal.rpow_one
@[simp]
theorem one_rpow (x : ℝ) : (1 : ℝ≥0) ^ x = 1 :=
NNReal.eq <| Real.one_rpow _
#align nnreal.one_rpow NNReal.one_rpow
theorem rpow_add {x : ℝ≥0} (hx : x ≠ 0) (y z : ℝ) : x ^ (y + z) = x ^ y * x ^ z :=
NNReal.eq <| Real.rpow_add (pos_iff_ne_zero.2 hx) _ _
#align nnreal.rpow_add NNReal.rpow_add
theorem rpow_add' (x : ℝ≥0) {y z : ℝ} (h : y + z ≠ 0) : x ^ (y + z) = x ^ y * x ^ z :=
NNReal.eq <| Real.rpow_add' x.2 h
#align nnreal.rpow_add' NNReal.rpow_add'
/-- Variant of `NNReal.rpow_add'` that avoids having to prove `y + z = w` twice. -/
lemma rpow_of_add_eq (x : ℝ≥0) (hw : w ≠ 0) (h : y + z = w) : x ^ w = x ^ y * x ^ z := by
rw [← h, rpow_add']; rwa [h]
theorem rpow_mul (x : ℝ≥0) (y z : ℝ) : x ^ (y * z) = (x ^ y) ^ z :=
NNReal.eq <| Real.rpow_mul x.2 y z
#align nnreal.rpow_mul NNReal.rpow_mul
theorem rpow_neg (x : ℝ≥0) (y : ℝ) : x ^ (-y) = (x ^ y)⁻¹ :=
NNReal.eq <| Real.rpow_neg x.2 _
#align nnreal.rpow_neg NNReal.rpow_neg
theorem rpow_neg_one (x : ℝ≥0) : x ^ (-1 : ℝ) = x⁻¹ := by simp [rpow_neg]
#align nnreal.rpow_neg_one NNReal.rpow_neg_one
theorem rpow_sub {x : ℝ≥0} (hx : x ≠ 0) (y z : ℝ) : x ^ (y - z) = x ^ y / x ^ z :=
NNReal.eq <| Real.rpow_sub (pos_iff_ne_zero.2 hx) y z
#align nnreal.rpow_sub NNReal.rpow_sub
theorem rpow_sub' (x : ℝ≥0) {y z : ℝ} (h : y - z ≠ 0) : x ^ (y - z) = x ^ y / x ^ z :=
NNReal.eq <| Real.rpow_sub' x.2 h
#align nnreal.rpow_sub' NNReal.rpow_sub'
theorem rpow_inv_rpow_self {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ y) ^ (1 / y) = x := by
field_simp [← rpow_mul]
#align nnreal.rpow_inv_rpow_self NNReal.rpow_inv_rpow_self
theorem rpow_self_rpow_inv {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ (1 / y)) ^ y = x := by
field_simp [← rpow_mul]
#align nnreal.rpow_self_rpow_inv NNReal.rpow_self_rpow_inv
theorem inv_rpow (x : ℝ≥0) (y : ℝ) : x⁻¹ ^ y = (x ^ y)⁻¹ :=
NNReal.eq <| Real.inv_rpow x.2 y
#align nnreal.inv_rpow NNReal.inv_rpow
theorem div_rpow (x y : ℝ≥0) (z : ℝ) : (x / y) ^ z = x ^ z / y ^ z :=
NNReal.eq <| Real.div_rpow x.2 y.2 z
#align nnreal.div_rpow NNReal.div_rpow
theorem sqrt_eq_rpow (x : ℝ≥0) : sqrt x = x ^ (1 / (2 : ℝ)) := by
refine NNReal.eq ?_
push_cast
exact Real.sqrt_eq_rpow x.1
#align nnreal.sqrt_eq_rpow NNReal.sqrt_eq_rpow
@[simp, norm_cast]
theorem rpow_natCast (x : ℝ≥0) (n : ℕ) : x ^ (n : ℝ) = x ^ n :=
NNReal.eq <| by simpa only [coe_rpow, coe_pow] using Real.rpow_natCast x n
#align nnreal.rpow_nat_cast NNReal.rpow_natCast
@[deprecated (since := "2024-04-17")]
alias rpow_nat_cast := rpow_natCast
@[simp]
lemma rpow_ofNat (x : ℝ≥0) (n : ℕ) [n.AtLeastTwo] :
x ^ (no_index (OfNat.ofNat n) : ℝ) = x ^ (OfNat.ofNat n : ℕ) :=
rpow_natCast x n
theorem rpow_two (x : ℝ≥0) : x ^ (2 : ℝ) = x ^ 2 := rpow_ofNat x 2
#align nnreal.rpow_two NNReal.rpow_two
theorem mul_rpow {x y : ℝ≥0} {z : ℝ} : (x * y) ^ z = x ^ z * y ^ z :=
NNReal.eq <| Real.mul_rpow x.2 y.2
#align nnreal.mul_rpow NNReal.mul_rpow
/-- `rpow` as a `MonoidHom`-/
@[simps]
def rpowMonoidHom (r : ℝ) : ℝ≥0 →* ℝ≥0 where
toFun := (· ^ r)
map_one' := one_rpow _
map_mul' _x _y := mul_rpow
/-- `rpow` variant of `List.prod_map_pow` for `ℝ≥0`-/
theorem list_prod_map_rpow (l : List ℝ≥0) (r : ℝ) :
(l.map (· ^ r)).prod = l.prod ^ r :=
l.prod_hom (rpowMonoidHom r)
theorem list_prod_map_rpow' {ι} (l : List ι) (f : ι → ℝ≥0) (r : ℝ) :
(l.map (f · ^ r)).prod = (l.map f).prod ^ r := by
rw [← list_prod_map_rpow, List.map_map]; rfl
/-- `rpow` version of `Multiset.prod_map_pow` for `ℝ≥0`. -/
lemma multiset_prod_map_rpow {ι} (s : Multiset ι) (f : ι → ℝ≥0) (r : ℝ) :
(s.map (f · ^ r)).prod = (s.map f).prod ^ r :=
s.prod_hom' (rpowMonoidHom r) _
/-- `rpow` version of `Finset.prod_pow` for `ℝ≥0`. -/
lemma finset_prod_rpow {ι} (s : Finset ι) (f : ι → ℝ≥0) (r : ℝ) :
(∏ i ∈ s, f i ^ r) = (∏ i ∈ s, f i) ^ r :=
multiset_prod_map_rpow _ _ _
-- note: these don't really belong here, but they're much easier to prove in terms of the above
section Real
/-- `rpow` version of `List.prod_map_pow` for `Real`. -/
theorem _root_.Real.list_prod_map_rpow (l : List ℝ) (hl : ∀ x ∈ l, (0 : ℝ) ≤ x) (r : ℝ) :
(l.map (· ^ r)).prod = l.prod ^ r := by
lift l to List ℝ≥0 using hl
have := congr_arg ((↑) : ℝ≥0 → ℝ) (NNReal.list_prod_map_rpow l r)
push_cast at this
rw [List.map_map] at this ⊢
exact mod_cast this
theorem _root_.Real.list_prod_map_rpow' {ι} (l : List ι) (f : ι → ℝ)
(hl : ∀ i ∈ l, (0 : ℝ) ≤ f i) (r : ℝ) :
(l.map (f · ^ r)).prod = (l.map f).prod ^ r := by
rw [← Real.list_prod_map_rpow (l.map f) _ r, List.map_map]
· rfl
simpa using hl
/-- `rpow` version of `Multiset.prod_map_pow`. -/
theorem _root_.Real.multiset_prod_map_rpow {ι} (s : Multiset ι) (f : ι → ℝ)
(hs : ∀ i ∈ s, (0 : ℝ) ≤ f i) (r : ℝ) :
(s.map (f · ^ r)).prod = (s.map f).prod ^ r := by
induction' s using Quotient.inductionOn with l
simpa using Real.list_prod_map_rpow' l f hs r
/-- `rpow` version of `Finset.prod_pow`. -/
theorem _root_.Real.finset_prod_rpow
{ι} (s : Finset ι) (f : ι → ℝ) (hs : ∀ i ∈ s, 0 ≤ f i) (r : ℝ) :
(∏ i ∈ s, f i ^ r) = (∏ i ∈ s, f i) ^ r :=
Real.multiset_prod_map_rpow s.val f hs r
end Real
@[gcongr] theorem rpow_le_rpow {x y : ℝ≥0} {z : ℝ} (h₁ : x ≤ y) (h₂ : 0 ≤ z) : x ^ z ≤ y ^ z :=
Real.rpow_le_rpow x.2 h₁ h₂
#align nnreal.rpow_le_rpow NNReal.rpow_le_rpow
@[gcongr] theorem rpow_lt_rpow {x y : ℝ≥0} {z : ℝ} (h₁ : x < y) (h₂ : 0 < z) : x ^ z < y ^ z :=
Real.rpow_lt_rpow x.2 h₁ h₂
#align nnreal.rpow_lt_rpow NNReal.rpow_lt_rpow
theorem rpow_lt_rpow_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ^ z < y ^ z ↔ x < y :=
Real.rpow_lt_rpow_iff x.2 y.2 hz
#align nnreal.rpow_lt_rpow_iff NNReal.rpow_lt_rpow_iff
theorem rpow_le_rpow_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ^ z ≤ y ^ z ↔ x ≤ y :=
Real.rpow_le_rpow_iff x.2 y.2 hz
#align nnreal.rpow_le_rpow_iff NNReal.rpow_le_rpow_iff
theorem le_rpow_one_div_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ≤ y ^ (1 / z) ↔ x ^ z ≤ y := by
rw [← rpow_le_rpow_iff hz, rpow_self_rpow_inv hz.ne']
#align nnreal.le_rpow_one_div_iff NNReal.le_rpow_one_div_iff
theorem rpow_one_div_le_iff {x y : ℝ≥0} {z : ℝ} (hz : 0 < z) : x ^ (1 / z) ≤ y ↔ x ≤ y ^ z := by
rw [← rpow_le_rpow_iff hz, rpow_self_rpow_inv hz.ne']
#align nnreal.rpow_one_div_le_iff NNReal.rpow_one_div_le_iff
@[gcongr] theorem rpow_lt_rpow_of_exponent_lt {x : ℝ≥0} {y z : ℝ} (hx : 1 < x) (hyz : y < z) :
x ^ y < x ^ z :=
Real.rpow_lt_rpow_of_exponent_lt hx hyz
#align nnreal.rpow_lt_rpow_of_exponent_lt NNReal.rpow_lt_rpow_of_exponent_lt
@[gcongr] theorem rpow_le_rpow_of_exponent_le {x : ℝ≥0} {y z : ℝ} (hx : 1 ≤ x) (hyz : y ≤ z) :
x ^ y ≤ x ^ z :=
Real.rpow_le_rpow_of_exponent_le hx hyz
#align nnreal.rpow_le_rpow_of_exponent_le NNReal.rpow_le_rpow_of_exponent_le
theorem rpow_lt_rpow_of_exponent_gt {x : ℝ≥0} {y z : ℝ} (hx0 : 0 < x) (hx1 : x < 1) (hyz : z < y) :
x ^ y < x ^ z :=
Real.rpow_lt_rpow_of_exponent_gt hx0 hx1 hyz
#align nnreal.rpow_lt_rpow_of_exponent_gt NNReal.rpow_lt_rpow_of_exponent_gt
theorem rpow_le_rpow_of_exponent_ge {x : ℝ≥0} {y z : ℝ} (hx0 : 0 < x) (hx1 : x ≤ 1) (hyz : z ≤ y) :
x ^ y ≤ x ^ z :=
Real.rpow_le_rpow_of_exponent_ge hx0 hx1 hyz
#align nnreal.rpow_le_rpow_of_exponent_ge NNReal.rpow_le_rpow_of_exponent_ge
theorem rpow_pos {p : ℝ} {x : ℝ≥0} (hx_pos : 0 < x) : 0 < x ^ p := by
have rpow_pos_of_nonneg : ∀ {p : ℝ}, 0 < p → 0 < x ^ p := by
intro p hp_pos
rw [← zero_rpow hp_pos.ne']
exact rpow_lt_rpow hx_pos hp_pos
rcases lt_trichotomy (0 : ℝ) p with (hp_pos | rfl | hp_neg)
· exact rpow_pos_of_nonneg hp_pos
· simp only [zero_lt_one, rpow_zero]
· rw [← neg_neg p, rpow_neg, inv_pos]
exact rpow_pos_of_nonneg (neg_pos.mpr hp_neg)
#align nnreal.rpow_pos NNReal.rpow_pos
theorem rpow_lt_one {x : ℝ≥0} {z : ℝ} (hx1 : x < 1) (hz : 0 < z) : x ^ z < 1 :=
Real.rpow_lt_one (coe_nonneg x) hx1 hz
#align nnreal.rpow_lt_one NNReal.rpow_lt_one
theorem rpow_le_one {x : ℝ≥0} {z : ℝ} (hx2 : x ≤ 1) (hz : 0 ≤ z) : x ^ z ≤ 1 :=
Real.rpow_le_one x.2 hx2 hz
#align nnreal.rpow_le_one NNReal.rpow_le_one
theorem rpow_lt_one_of_one_lt_of_neg {x : ℝ≥0} {z : ℝ} (hx : 1 < x) (hz : z < 0) : x ^ z < 1 :=
Real.rpow_lt_one_of_one_lt_of_neg hx hz
#align nnreal.rpow_lt_one_of_one_lt_of_neg NNReal.rpow_lt_one_of_one_lt_of_neg
theorem rpow_le_one_of_one_le_of_nonpos {x : ℝ≥0} {z : ℝ} (hx : 1 ≤ x) (hz : z ≤ 0) : x ^ z ≤ 1 :=
Real.rpow_le_one_of_one_le_of_nonpos hx hz
#align nnreal.rpow_le_one_of_one_le_of_nonpos NNReal.rpow_le_one_of_one_le_of_nonpos
theorem one_lt_rpow {x : ℝ≥0} {z : ℝ} (hx : 1 < x) (hz : 0 < z) : 1 < x ^ z :=
Real.one_lt_rpow hx hz
#align nnreal.one_lt_rpow NNReal.one_lt_rpow
theorem one_le_rpow {x : ℝ≥0} {z : ℝ} (h : 1 ≤ x) (h₁ : 0 ≤ z) : 1 ≤ x ^ z :=
Real.one_le_rpow h h₁
#align nnreal.one_le_rpow NNReal.one_le_rpow
theorem one_lt_rpow_of_pos_of_lt_one_of_neg {x : ℝ≥0} {z : ℝ} (hx1 : 0 < x) (hx2 : x < 1)
(hz : z < 0) : 1 < x ^ z :=
Real.one_lt_rpow_of_pos_of_lt_one_of_neg hx1 hx2 hz
#align nnreal.one_lt_rpow_of_pos_of_lt_one_of_neg NNReal.one_lt_rpow_of_pos_of_lt_one_of_neg
theorem one_le_rpow_of_pos_of_le_one_of_nonpos {x : ℝ≥0} {z : ℝ} (hx1 : 0 < x) (hx2 : x ≤ 1)
(hz : z ≤ 0) : 1 ≤ x ^ z :=
Real.one_le_rpow_of_pos_of_le_one_of_nonpos hx1 hx2 hz
#align nnreal.one_le_rpow_of_pos_of_le_one_of_nonpos NNReal.one_le_rpow_of_pos_of_le_one_of_nonpos
theorem rpow_le_self_of_le_one {x : ℝ≥0} {z : ℝ} (hx : x ≤ 1) (h_one_le : 1 ≤ z) : x ^ z ≤ x := by
rcases eq_bot_or_bot_lt x with (rfl | (h : 0 < x))
· have : z ≠ 0 := by linarith
simp [this]
nth_rw 2 [← NNReal.rpow_one x]
exact NNReal.rpow_le_rpow_of_exponent_ge h hx h_one_le
#align nnreal.rpow_le_self_of_le_one NNReal.rpow_le_self_of_le_one
theorem rpow_left_injective {x : ℝ} (hx : x ≠ 0) : Function.Injective fun y : ℝ≥0 => y ^ x :=
fun y z hyz => by simpa only [rpow_inv_rpow_self hx] using congr_arg (fun y => y ^ (1 / x)) hyz
#align nnreal.rpow_left_injective NNReal.rpow_left_injective
theorem rpow_eq_rpow_iff {x y : ℝ≥0} {z : ℝ} (hz : z ≠ 0) : x ^ z = y ^ z ↔ x = y :=
(rpow_left_injective hz).eq_iff
#align nnreal.rpow_eq_rpow_iff NNReal.rpow_eq_rpow_iff
theorem rpow_left_surjective {x : ℝ} (hx : x ≠ 0) : Function.Surjective fun y : ℝ≥0 => y ^ x :=
fun y => ⟨y ^ x⁻¹, by simp_rw [← rpow_mul, _root_.inv_mul_cancel hx, rpow_one]⟩
#align nnreal.rpow_left_surjective NNReal.rpow_left_surjective
theorem rpow_left_bijective {x : ℝ} (hx : x ≠ 0) : Function.Bijective fun y : ℝ≥0 => y ^ x :=
⟨rpow_left_injective hx, rpow_left_surjective hx⟩
#align nnreal.rpow_left_bijective NNReal.rpow_left_bijective
theorem eq_rpow_one_div_iff {x y : ℝ≥0} {z : ℝ} (hz : z ≠ 0) : x = y ^ (1 / z) ↔ x ^ z = y := by
rw [← rpow_eq_rpow_iff hz, rpow_self_rpow_inv hz]
#align nnreal.eq_rpow_one_div_iff NNReal.eq_rpow_one_div_iff
theorem rpow_one_div_eq_iff {x y : ℝ≥0} {z : ℝ} (hz : z ≠ 0) : x ^ (1 / z) = y ↔ x = y ^ z := by
rw [← rpow_eq_rpow_iff hz, rpow_self_rpow_inv hz]
#align nnreal.rpow_one_div_eq_iff NNReal.rpow_one_div_eq_iff
@[simp] lemma rpow_rpow_inv {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ y) ^ y⁻¹ = x := by
rw [← rpow_mul, mul_inv_cancel hy, rpow_one]
@[simp] lemma rpow_inv_rpow {y : ℝ} (hy : y ≠ 0) (x : ℝ≥0) : (x ^ y⁻¹) ^ y = x := by
rw [← rpow_mul, inv_mul_cancel hy, rpow_one]
theorem pow_rpow_inv_natCast (x : ℝ≥0) {n : ℕ} (hn : n ≠ 0) : (x ^ n) ^ (n⁻¹ : ℝ) = x := by
rw [← NNReal.coe_inj, coe_rpow, NNReal.coe_pow]
exact Real.pow_rpow_inv_natCast x.2 hn
#align nnreal.pow_nat_rpow_nat_inv NNReal.pow_rpow_inv_natCast
theorem rpow_inv_natCast_pow (x : ℝ≥0) {n : ℕ} (hn : n ≠ 0) : (x ^ (n⁻¹ : ℝ)) ^ n = x := by
rw [← NNReal.coe_inj, NNReal.coe_pow, coe_rpow]
exact Real.rpow_inv_natCast_pow x.2 hn
#align nnreal.rpow_nat_inv_pow_nat NNReal.rpow_inv_natCast_pow
theorem _root_.Real.toNNReal_rpow_of_nonneg {x y : ℝ} (hx : 0 ≤ x) :
Real.toNNReal (x ^ y) = Real.toNNReal x ^ y := by
nth_rw 1 [← Real.coe_toNNReal x hx]
rw [← NNReal.coe_rpow, Real.toNNReal_coe]
#align real.to_nnreal_rpow_of_nonneg Real.toNNReal_rpow_of_nonneg
theorem strictMono_rpow_of_pos {z : ℝ} (h : 0 < z) : StrictMono fun x : ℝ≥0 => x ^ z :=
fun x y hxy => by simp only [NNReal.rpow_lt_rpow hxy h, coe_lt_coe]
theorem monotone_rpow_of_nonneg {z : ℝ} (h : 0 ≤ z) : Monotone fun x : ℝ≥0 => x ^ z :=
h.eq_or_lt.elim (fun h0 => h0 ▸ by simp only [rpow_zero, monotone_const]) fun h0 =>
(strictMono_rpow_of_pos h0).monotone
/-- Bundles `fun x : ℝ≥0 => x ^ y` into an order isomorphism when `y : ℝ` is positive,
where the inverse is `fun x : ℝ≥0 => x ^ (1 / y)`. -/
@[simps! apply]
def orderIsoRpow (y : ℝ) (hy : 0 < y) : ℝ≥0 ≃o ℝ≥0 :=
(strictMono_rpow_of_pos hy).orderIsoOfRightInverse (fun x => x ^ y) (fun x => x ^ (1 / y))
fun x => by
dsimp
rw [← rpow_mul, one_div_mul_cancel hy.ne.symm, rpow_one]
theorem orderIsoRpow_symm_eq (y : ℝ) (hy : 0 < y) :
(orderIsoRpow y hy).symm = orderIsoRpow (1 / y) (one_div_pos.2 hy) := by
simp only [orderIsoRpow, one_div_one_div]; rfl
end NNReal
namespace ENNReal
/-- The real power function `x^y` on extended nonnegative reals, defined for `x : ℝ≥0∞` and
`y : ℝ` as the restriction of the real power function if `0 < x < ⊤`, and with the natural values
for `0` and `⊤` (i.e., `0 ^ x = 0` for `x > 0`, `1` for `x = 0` and `⊤` for `x < 0`, and
`⊤ ^ x = 1 / 0 ^ x`). -/
noncomputable def rpow : ℝ≥0∞ → ℝ → ℝ≥0∞
| some x, y => if x = 0 ∧ y < 0 then ⊤ else (x ^ y : ℝ≥0)
| none, y => if 0 < y then ⊤ else if y = 0 then 1 else 0
#align ennreal.rpow ENNReal.rpow
noncomputable instance : Pow ℝ≥0∞ ℝ :=
⟨rpow⟩
@[simp]
theorem rpow_eq_pow (x : ℝ≥0∞) (y : ℝ) : rpow x y = x ^ y :=
rfl
#align ennreal.rpow_eq_pow ENNReal.rpow_eq_pow
@[simp]
theorem rpow_zero {x : ℝ≥0∞} : x ^ (0 : ℝ) = 1 := by
cases x <;>
· dsimp only [(· ^ ·), Pow.pow, rpow]
simp [lt_irrefl]
#align ennreal.rpow_zero ENNReal.rpow_zero
theorem top_rpow_def (y : ℝ) : (⊤ : ℝ≥0∞) ^ y = if 0 < y then ⊤ else if y = 0 then 1 else 0 :=
rfl
#align ennreal.top_rpow_def ENNReal.top_rpow_def
@[simp]
theorem top_rpow_of_pos {y : ℝ} (h : 0 < y) : (⊤ : ℝ≥0∞) ^ y = ⊤ := by simp [top_rpow_def, h]
#align ennreal.top_rpow_of_pos ENNReal.top_rpow_of_pos
@[simp]
theorem top_rpow_of_neg {y : ℝ} (h : y < 0) : (⊤ : ℝ≥0∞) ^ y = 0 := by
simp [top_rpow_def, asymm h, ne_of_lt h]
#align ennreal.top_rpow_of_neg ENNReal.top_rpow_of_neg
@[simp]
theorem zero_rpow_of_pos {y : ℝ} (h : 0 < y) : (0 : ℝ≥0∞) ^ y = 0 := by
rw [← ENNReal.coe_zero, ← ENNReal.some_eq_coe]
dsimp only [(· ^ ·), rpow, Pow.pow]
simp [h, asymm h, ne_of_gt h]
#align ennreal.zero_rpow_of_pos ENNReal.zero_rpow_of_pos
@[simp]
theorem zero_rpow_of_neg {y : ℝ} (h : y < 0) : (0 : ℝ≥0∞) ^ y = ⊤ := by
rw [← ENNReal.coe_zero, ← ENNReal.some_eq_coe]
dsimp only [(· ^ ·), rpow, Pow.pow]
simp [h, ne_of_gt h]
#align ennreal.zero_rpow_of_neg ENNReal.zero_rpow_of_neg
theorem zero_rpow_def (y : ℝ) : (0 : ℝ≥0∞) ^ y = if 0 < y then 0 else if y = 0 then 1 else ⊤ := by
rcases lt_trichotomy (0 : ℝ) y with (H | rfl | H)
· simp [H, ne_of_gt, zero_rpow_of_pos, lt_irrefl]
· simp [lt_irrefl]
· simp [H, asymm H, ne_of_lt, zero_rpow_of_neg]
#align ennreal.zero_rpow_def ENNReal.zero_rpow_def
@[simp]
theorem zero_rpow_mul_self (y : ℝ) : (0 : ℝ≥0∞) ^ y * (0 : ℝ≥0∞) ^ y = (0 : ℝ≥0∞) ^ y := by
rw [zero_rpow_def]
split_ifs
exacts [zero_mul _, one_mul _, top_mul_top]
#align ennreal.zero_rpow_mul_self ENNReal.zero_rpow_mul_self
@[norm_cast]
theorem coe_rpow_of_ne_zero {x : ℝ≥0} (h : x ≠ 0) (y : ℝ) : (x : ℝ≥0∞) ^ y = (x ^ y : ℝ≥0) := by
rw [← ENNReal.some_eq_coe]
dsimp only [(· ^ ·), Pow.pow, rpow]
simp [h]
#align ennreal.coe_rpow_of_ne_zero ENNReal.coe_rpow_of_ne_zero
@[norm_cast]
theorem coe_rpow_of_nonneg (x : ℝ≥0) {y : ℝ} (h : 0 ≤ y) : (x : ℝ≥0∞) ^ y = (x ^ y : ℝ≥0) := by
by_cases hx : x = 0
· rcases le_iff_eq_or_lt.1 h with (H | H)
· simp [hx, H.symm]
· simp [hx, zero_rpow_of_pos H, NNReal.zero_rpow (ne_of_gt H)]
· exact coe_rpow_of_ne_zero hx _
#align ennreal.coe_rpow_of_nonneg ENNReal.coe_rpow_of_nonneg
theorem coe_rpow_def (x : ℝ≥0) (y : ℝ) :
(x : ℝ≥0∞) ^ y = if x = 0 ∧ y < 0 then ⊤ else ↑(x ^ y) :=
rfl
#align ennreal.coe_rpow_def ENNReal.coe_rpow_def
@[simp]
theorem rpow_one (x : ℝ≥0∞) : x ^ (1 : ℝ) = x := by
cases x
· exact dif_pos zero_lt_one
· change ite _ _ _ = _
simp only [NNReal.rpow_one, some_eq_coe, ite_eq_right_iff, top_ne_coe, and_imp]
exact fun _ => zero_le_one.not_lt
#align ennreal.rpow_one ENNReal.rpow_one
@[simp]
theorem one_rpow (x : ℝ) : (1 : ℝ≥0∞) ^ x = 1 := by
rw [← coe_one, coe_rpow_of_ne_zero one_ne_zero]
simp
#align ennreal.one_rpow ENNReal.one_rpow
@[simp]
theorem rpow_eq_zero_iff {x : ℝ≥0∞} {y : ℝ} : x ^ y = 0 ↔ x = 0 ∧ 0 < y ∨ x = ⊤ ∧ y < 0 := by
cases' x with x
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [H, top_rpow_of_neg, top_rpow_of_pos, le_of_lt]
· by_cases h : x = 0
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [h, H, zero_rpow_of_neg, zero_rpow_of_pos, le_of_lt]
· simp [coe_rpow_of_ne_zero h, h]
#align ennreal.rpow_eq_zero_iff ENNReal.rpow_eq_zero_iff
lemma rpow_eq_zero_iff_of_pos {x : ℝ≥0∞} {y : ℝ} (hy : 0 < y) : x ^ y = 0 ↔ x = 0 := by
simp [hy, hy.not_lt]
@[simp]
theorem rpow_eq_top_iff {x : ℝ≥0∞} {y : ℝ} : x ^ y = ⊤ ↔ x = 0 ∧ y < 0 ∨ x = ⊤ ∧ 0 < y := by
cases' x with x
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [H, top_rpow_of_neg, top_rpow_of_pos, le_of_lt]
· by_cases h : x = 0
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [h, H, zero_rpow_of_neg, zero_rpow_of_pos, le_of_lt]
· simp [coe_rpow_of_ne_zero h, h]
#align ennreal.rpow_eq_top_iff ENNReal.rpow_eq_top_iff
theorem rpow_eq_top_iff_of_pos {x : ℝ≥0∞} {y : ℝ} (hy : 0 < y) : x ^ y = ⊤ ↔ x = ⊤ := by
simp [rpow_eq_top_iff, hy, asymm hy]
#align ennreal.rpow_eq_top_iff_of_pos ENNReal.rpow_eq_top_iff_of_pos
lemma rpow_lt_top_iff_of_pos {x : ℝ≥0∞} {y : ℝ} (hy : 0 < y) : x ^ y < ∞ ↔ x < ∞ := by
simp only [lt_top_iff_ne_top, Ne, rpow_eq_top_iff_of_pos hy]
theorem rpow_eq_top_of_nonneg (x : ℝ≥0∞) {y : ℝ} (hy0 : 0 ≤ y) : x ^ y = ⊤ → x = ⊤ := by
rw [ENNReal.rpow_eq_top_iff]
rintro (h|h)
· exfalso
rw [lt_iff_not_ge] at h
exact h.right hy0
· exact h.left
#align ennreal.rpow_eq_top_of_nonneg ENNReal.rpow_eq_top_of_nonneg
theorem rpow_ne_top_of_nonneg {x : ℝ≥0∞} {y : ℝ} (hy0 : 0 ≤ y) (h : x ≠ ⊤) : x ^ y ≠ ⊤ :=
mt (ENNReal.rpow_eq_top_of_nonneg x hy0) h
#align ennreal.rpow_ne_top_of_nonneg ENNReal.rpow_ne_top_of_nonneg
theorem rpow_lt_top_of_nonneg {x : ℝ≥0∞} {y : ℝ} (hy0 : 0 ≤ y) (h : x ≠ ⊤) : x ^ y < ⊤ :=
lt_top_iff_ne_top.mpr (ENNReal.rpow_ne_top_of_nonneg hy0 h)
#align ennreal.rpow_lt_top_of_nonneg ENNReal.rpow_lt_top_of_nonneg
theorem rpow_add {x : ℝ≥0∞} (y z : ℝ) (hx : x ≠ 0) (h'x : x ≠ ⊤) : x ^ (y + z) = x ^ y * x ^ z := by
cases' x with x
· exact (h'x rfl).elim
have : x ≠ 0 := fun h => by simp [h] at hx
simp [coe_rpow_of_ne_zero this, NNReal.rpow_add this]
#align ennreal.rpow_add ENNReal.rpow_add
theorem rpow_neg (x : ℝ≥0∞) (y : ℝ) : x ^ (-y) = (x ^ y)⁻¹ := by
cases' x with x
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [top_rpow_of_pos, top_rpow_of_neg, H, neg_pos.mpr]
· by_cases h : x = 0
· rcases lt_trichotomy y 0 with (H | H | H) <;>
simp [h, zero_rpow_of_pos, zero_rpow_of_neg, H, neg_pos.mpr]
· have A : x ^ y ≠ 0 := by simp [h]
simp [coe_rpow_of_ne_zero h, ← coe_inv A, NNReal.rpow_neg]
#align ennreal.rpow_neg ENNReal.rpow_neg
theorem rpow_sub {x : ℝ≥0∞} (y z : ℝ) (hx : x ≠ 0) (h'x : x ≠ ⊤) : x ^ (y - z) = x ^ y / x ^ z := by
rw [sub_eq_add_neg, rpow_add _ _ hx h'x, rpow_neg, div_eq_mul_inv]
#align ennreal.rpow_sub ENNReal.rpow_sub
theorem rpow_neg_one (x : ℝ≥0∞) : x ^ (-1 : ℝ) = x⁻¹ := by simp [rpow_neg]
#align ennreal.rpow_neg_one ENNReal.rpow_neg_one
theorem rpow_mul (x : ℝ≥0∞) (y z : ℝ) : x ^ (y * z) = (x ^ y) ^ z := by
cases' x with x
· rcases lt_trichotomy y 0 with (Hy | Hy | Hy) <;>
rcases lt_trichotomy z 0 with (Hz | Hz | Hz) <;>
simp [Hy, Hz, zero_rpow_of_neg, zero_rpow_of_pos, top_rpow_of_neg, top_rpow_of_pos,
mul_pos_of_neg_of_neg, mul_neg_of_neg_of_pos, mul_neg_of_pos_of_neg]
· by_cases h : x = 0
· rcases lt_trichotomy y 0 with (Hy | Hy | Hy) <;>
rcases lt_trichotomy z 0 with (Hz | Hz | Hz) <;>
simp [h, Hy, Hz, zero_rpow_of_neg, zero_rpow_of_pos, top_rpow_of_neg, top_rpow_of_pos,
mul_pos_of_neg_of_neg, mul_neg_of_neg_of_pos, mul_neg_of_pos_of_neg]
· have : x ^ y ≠ 0 := by simp [h]
simp [coe_rpow_of_ne_zero h, coe_rpow_of_ne_zero this, NNReal.rpow_mul]
#align ennreal.rpow_mul ENNReal.rpow_mul
@[simp, norm_cast]
theorem rpow_natCast (x : ℝ≥0∞) (n : ℕ) : x ^ (n : ℝ) = x ^ n := by
cases x
· cases n <;> simp [top_rpow_of_pos (Nat.cast_add_one_pos _), top_pow (Nat.succ_pos _)]
· simp [coe_rpow_of_nonneg _ (Nat.cast_nonneg n)]
#align ennreal.rpow_nat_cast ENNReal.rpow_natCast
@[deprecated (since := "2024-04-17")]
alias rpow_nat_cast := rpow_natCast
@[simp]
lemma rpow_ofNat (x : ℝ≥0∞) (n : ℕ) [n.AtLeastTwo] :
x ^ (no_index (OfNat.ofNat n) : ℝ) = x ^ (OfNat.ofNat n) :=
rpow_natCast x n
@[simp, norm_cast]
lemma rpow_intCast (x : ℝ≥0∞) (n : ℤ) : x ^ (n : ℝ) = x ^ n := by
cases n <;> simp only [Int.ofNat_eq_coe, Int.cast_natCast, rpow_natCast, zpow_natCast,
Int.cast_negSucc, rpow_neg, zpow_negSucc]
@[deprecated (since := "2024-04-17")]
alias rpow_int_cast := rpow_intCast
theorem rpow_two (x : ℝ≥0∞) : x ^ (2 : ℝ) = x ^ 2 := rpow_ofNat x 2
#align ennreal.rpow_two ENNReal.rpow_two
theorem mul_rpow_eq_ite (x y : ℝ≥0∞) (z : ℝ) :
(x * y) ^ z = if (x = 0 ∧ y = ⊤ ∨ x = ⊤ ∧ y = 0) ∧ z < 0 then ⊤ else x ^ z * y ^ z := by
rcases eq_or_ne z 0 with (rfl | hz); · simp
replace hz := hz.lt_or_lt
wlog hxy : x ≤ y
· convert this y x z hz (le_of_not_le hxy) using 2 <;> simp only [mul_comm, and_comm, or_comm]
rcases eq_or_ne x 0 with (rfl | hx0)
· induction y <;> cases' hz with hz hz <;> simp [*, hz.not_lt]
rcases eq_or_ne y 0 with (rfl | hy0)
· exact (hx0 (bot_unique hxy)).elim
induction x
· cases' hz with hz hz <;> simp [hz, top_unique hxy]
induction y
· rw [ne_eq, coe_eq_zero] at hx0
cases' hz with hz hz <;> simp [*]
simp only [*, false_and_iff, and_false_iff, false_or_iff, if_false]
norm_cast at *
rw [coe_rpow_of_ne_zero (mul_ne_zero hx0 hy0), NNReal.mul_rpow]
norm_cast
#align ennreal.mul_rpow_eq_ite ENNReal.mul_rpow_eq_ite
theorem mul_rpow_of_ne_top {x y : ℝ≥0∞} (hx : x ≠ ⊤) (hy : y ≠ ⊤) (z : ℝ) :
(x * y) ^ z = x ^ z * y ^ z := by simp [*, mul_rpow_eq_ite]
#align ennreal.mul_rpow_of_ne_top ENNReal.mul_rpow_of_ne_top
@[norm_cast]
theorem coe_mul_rpow (x y : ℝ≥0) (z : ℝ) : ((x : ℝ≥0∞) * y) ^ z = (x : ℝ≥0∞) ^ z * (y : ℝ≥0∞) ^ z :=
mul_rpow_of_ne_top coe_ne_top coe_ne_top z
#align ennreal.coe_mul_rpow ENNReal.coe_mul_rpow
theorem prod_coe_rpow {ι} (s : Finset ι) (f : ι → ℝ≥0) (r : ℝ) :
∏ i ∈ s, (f i : ℝ≥0∞) ^ r = ((∏ i ∈ s, f i : ℝ≥0) : ℝ≥0∞) ^ r := by
induction s using Finset.induction with
| empty => simp
| insert hi ih => simp_rw [prod_insert hi, ih, ← coe_mul_rpow, coe_mul]
theorem mul_rpow_of_ne_zero {x y : ℝ≥0∞} (hx : x ≠ 0) (hy : y ≠ 0) (z : ℝ) :
(x * y) ^ z = x ^ z * y ^ z := by simp [*, mul_rpow_eq_ite]
#align ennreal.mul_rpow_of_ne_zero ENNReal.mul_rpow_of_ne_zero
theorem mul_rpow_of_nonneg (x y : ℝ≥0∞) {z : ℝ} (hz : 0 ≤ z) : (x * y) ^ z = x ^ z * y ^ z := by
simp [hz.not_lt, mul_rpow_eq_ite]
#align ennreal.mul_rpow_of_nonneg ENNReal.mul_rpow_of_nonneg
theorem prod_rpow_of_ne_top {ι} {s : Finset ι} {f : ι → ℝ≥0∞} (hf : ∀ i ∈ s, f i ≠ ∞) (r : ℝ) :
∏ i ∈ s, f i ^ r = (∏ i ∈ s, f i) ^ r := by
induction s using Finset.induction with
| empty => simp
| @insert i s hi ih =>
have h2f : ∀ i ∈ s, f i ≠ ∞ := fun i hi ↦ hf i <| mem_insert_of_mem hi
rw [prod_insert hi, prod_insert hi, ih h2f, ← mul_rpow_of_ne_top <| hf i <| mem_insert_self ..]
apply prod_lt_top h2f |>.ne
theorem prod_rpow_of_nonneg {ι} {s : Finset ι} {f : ι → ℝ≥0∞} {r : ℝ} (hr : 0 ≤ r) :
∏ i ∈ s, f i ^ r = (∏ i ∈ s, f i) ^ r := by
induction s using Finset.induction with
| empty => simp
| insert hi ih => simp_rw [prod_insert hi, ih, ← mul_rpow_of_nonneg _ _ hr]
theorem inv_rpow (x : ℝ≥0∞) (y : ℝ) : x⁻¹ ^ y = (x ^ y)⁻¹ := by
rcases eq_or_ne y 0 with (rfl | hy); · simp only [rpow_zero, inv_one]
replace hy := hy.lt_or_lt
rcases eq_or_ne x 0 with (rfl | h0); · cases hy <;> simp [*]
rcases eq_or_ne x ⊤ with (rfl | h_top); · cases hy <;> simp [*]
apply ENNReal.eq_inv_of_mul_eq_one_left
rw [← mul_rpow_of_ne_zero (ENNReal.inv_ne_zero.2 h_top) h0, ENNReal.inv_mul_cancel h0 h_top,
one_rpow]
#align ennreal.inv_rpow ENNReal.inv_rpow
theorem div_rpow_of_nonneg (x y : ℝ≥0∞) {z : ℝ} (hz : 0 ≤ z) : (x / y) ^ z = x ^ z / y ^ z := by
rw [div_eq_mul_inv, mul_rpow_of_nonneg _ _ hz, inv_rpow, div_eq_mul_inv]
#align ennreal.div_rpow_of_nonneg ENNReal.div_rpow_of_nonneg
theorem strictMono_rpow_of_pos {z : ℝ} (h : 0 < z) : StrictMono fun x : ℝ≥0∞ => x ^ z := by
intro x y hxy
lift x to ℝ≥0 using ne_top_of_lt hxy
rcases eq_or_ne y ∞ with (rfl | hy)
· simp only [top_rpow_of_pos h, coe_rpow_of_nonneg _ h.le, coe_lt_top]
· lift y to ℝ≥0 using hy
simp only [coe_rpow_of_nonneg _ h.le, NNReal.rpow_lt_rpow (coe_lt_coe.1 hxy) h, coe_lt_coe]
#align ennreal.strict_mono_rpow_of_pos ENNReal.strictMono_rpow_of_pos
theorem monotone_rpow_of_nonneg {z : ℝ} (h : 0 ≤ z) : Monotone fun x : ℝ≥0∞ => x ^ z :=
h.eq_or_lt.elim (fun h0 => h0 ▸ by simp only [rpow_zero, monotone_const]) fun h0 =>
(strictMono_rpow_of_pos h0).monotone
#align ennreal.monotone_rpow_of_nonneg ENNReal.monotone_rpow_of_nonneg
/-- Bundles `fun x : ℝ≥0∞ => x ^ y` into an order isomorphism when `y : ℝ` is positive,
where the inverse is `fun x : ℝ≥0∞ => x ^ (1 / y)`. -/
@[simps! apply]
def orderIsoRpow (y : ℝ) (hy : 0 < y) : ℝ≥0∞ ≃o ℝ≥0∞ :=
(strictMono_rpow_of_pos hy).orderIsoOfRightInverse (fun x => x ^ y) (fun x => x ^ (1 / y))
fun x => by
dsimp
rw [← rpow_mul, one_div_mul_cancel hy.ne.symm, rpow_one]
#align ennreal.order_iso_rpow ENNReal.orderIsoRpow
theorem orderIsoRpow_symm_apply (y : ℝ) (hy : 0 < y) :
(orderIsoRpow y hy).symm = orderIsoRpow (1 / y) (one_div_pos.2 hy) := by
simp only [orderIsoRpow, one_div_one_div]
rfl
#align ennreal.order_iso_rpow_symm_apply ENNReal.orderIsoRpow_symm_apply
@[gcongr] theorem rpow_le_rpow {x y : ℝ≥0∞} {z : ℝ} (h₁ : x ≤ y) (h₂ : 0 ≤ z) : x ^ z ≤ y ^ z :=
monotone_rpow_of_nonneg h₂ h₁
#align ennreal.rpow_le_rpow ENNReal.rpow_le_rpow
@[gcongr] theorem rpow_lt_rpow {x y : ℝ≥0∞} {z : ℝ} (h₁ : x < y) (h₂ : 0 < z) : x ^ z < y ^ z :=
strictMono_rpow_of_pos h₂ h₁
#align ennreal.rpow_lt_rpow ENNReal.rpow_lt_rpow
theorem rpow_le_rpow_iff {x y : ℝ≥0∞} {z : ℝ} (hz : 0 < z) : x ^ z ≤ y ^ z ↔ x ≤ y :=
(strictMono_rpow_of_pos hz).le_iff_le
#align ennreal.rpow_le_rpow_iff ENNReal.rpow_le_rpow_iff
theorem rpow_lt_rpow_iff {x y : ℝ≥0∞} {z : ℝ} (hz : 0 < z) : x ^ z < y ^ z ↔ x < y :=
(strictMono_rpow_of_pos hz).lt_iff_lt
#align ennreal.rpow_lt_rpow_iff ENNReal.rpow_lt_rpow_iff
theorem le_rpow_one_div_iff {x y : ℝ≥0∞} {z : ℝ} (hz : 0 < z) : x ≤ y ^ (1 / z) ↔ x ^ z ≤ y := by
nth_rw 1 [← rpow_one x]
nth_rw 1 [← @_root_.mul_inv_cancel _ _ z hz.ne']
rw [rpow_mul, ← one_div, @rpow_le_rpow_iff _ _ (1 / z) (by simp [hz])]
#align ennreal.le_rpow_one_div_iff ENNReal.le_rpow_one_div_iff
theorem lt_rpow_one_div_iff {x y : ℝ≥0∞} {z : ℝ} (hz : 0 < z) : x < y ^ (1 / z) ↔ x ^ z < y := by
nth_rw 1 [← rpow_one x]
nth_rw 1 [← @_root_.mul_inv_cancel _ _ z (ne_of_lt hz).symm]
rw [rpow_mul, ← one_div, @rpow_lt_rpow_iff _ _ (1 / z) (by simp [hz])]
#align ennreal.lt_rpow_one_div_iff ENNReal.lt_rpow_one_div_iff
theorem rpow_one_div_le_iff {x y : ℝ≥0∞} {z : ℝ} (hz : 0 < z) : x ^ (1 / z) ≤ y ↔ x ≤ y ^ z := by
nth_rw 1 [← ENNReal.rpow_one y]
nth_rw 2 [← @_root_.mul_inv_cancel _ _ z hz.ne.symm]
rw [ENNReal.rpow_mul, ← one_div, ENNReal.rpow_le_rpow_iff (one_div_pos.2 hz)]
#align ennreal.rpow_one_div_le_iff ENNReal.rpow_one_div_le_iff
theorem rpow_lt_rpow_of_exponent_lt {x : ℝ≥0∞} {y z : ℝ} (hx : 1 < x) (hx' : x ≠ ⊤) (hyz : y < z) :
x ^ y < x ^ z := by
lift x to ℝ≥0 using hx'
rw [one_lt_coe_iff] at hx
simp [coe_rpow_of_ne_zero (ne_of_gt (lt_trans zero_lt_one hx)),
NNReal.rpow_lt_rpow_of_exponent_lt hx hyz]
#align ennreal.rpow_lt_rpow_of_exponent_lt ENNReal.rpow_lt_rpow_of_exponent_lt
@[gcongr] theorem rpow_le_rpow_of_exponent_le {x : ℝ≥0∞} {y z : ℝ} (hx : 1 ≤ x) (hyz : y ≤ z) :
x ^ y ≤ x ^ z := by
cases x
· rcases lt_trichotomy y 0 with (Hy | Hy | Hy) <;>
rcases lt_trichotomy z 0 with (Hz | Hz | Hz) <;>
simp [Hy, Hz, top_rpow_of_neg, top_rpow_of_pos, le_refl] <;>
linarith
· simp only [one_le_coe_iff, some_eq_coe] at hx
simp [coe_rpow_of_ne_zero (ne_of_gt (lt_of_lt_of_le zero_lt_one hx)),
NNReal.rpow_le_rpow_of_exponent_le hx hyz]
#align ennreal.rpow_le_rpow_of_exponent_le ENNReal.rpow_le_rpow_of_exponent_le
theorem rpow_lt_rpow_of_exponent_gt {x : ℝ≥0∞} {y z : ℝ} (hx0 : 0 < x) (hx1 : x < 1) (hyz : z < y) :
x ^ y < x ^ z := by
lift x to ℝ≥0 using ne_of_lt (lt_of_lt_of_le hx1 le_top)
simp only [coe_lt_one_iff, coe_pos] at hx0 hx1
simp [coe_rpow_of_ne_zero (ne_of_gt hx0), NNReal.rpow_lt_rpow_of_exponent_gt hx0 hx1 hyz]
#align ennreal.rpow_lt_rpow_of_exponent_gt ENNReal.rpow_lt_rpow_of_exponent_gt
theorem rpow_le_rpow_of_exponent_ge {x : ℝ≥0∞} {y z : ℝ} (hx1 : x ≤ 1) (hyz : z ≤ y) :
x ^ y ≤ x ^ z := by
lift x to ℝ≥0 using ne_of_lt (lt_of_le_of_lt hx1 coe_lt_top)
by_cases h : x = 0
· rcases lt_trichotomy y 0 with (Hy | Hy | Hy) <;>
rcases lt_trichotomy z 0 with (Hz | Hz | Hz) <;>
simp [Hy, Hz, h, zero_rpow_of_neg, zero_rpow_of_pos, le_refl] <;>
linarith
· rw [coe_le_one_iff] at hx1
simp [coe_rpow_of_ne_zero h,
NNReal.rpow_le_rpow_of_exponent_ge (bot_lt_iff_ne_bot.mpr h) hx1 hyz]
#align ennreal.rpow_le_rpow_of_exponent_ge ENNReal.rpow_le_rpow_of_exponent_ge
theorem rpow_le_self_of_le_one {x : ℝ≥0∞} {z : ℝ} (hx : x ≤ 1) (h_one_le : 1 ≤ z) : x ^ z ≤ x := by
nth_rw 2 [← ENNReal.rpow_one x]
exact ENNReal.rpow_le_rpow_of_exponent_ge hx h_one_le
#align ennreal.rpow_le_self_of_le_one ENNReal.rpow_le_self_of_le_one
theorem le_rpow_self_of_one_le {x : ℝ≥0∞} {z : ℝ} (hx : 1 ≤ x) (h_one_le : 1 ≤ z) : x ≤ x ^ z := by
nth_rw 1 [← ENNReal.rpow_one x]
exact ENNReal.rpow_le_rpow_of_exponent_le hx h_one_le
#align ennreal.le_rpow_self_of_one_le ENNReal.le_rpow_self_of_one_le
| Mathlib/Analysis/SpecialFunctions/Pow/NNReal.lean | 782 | 788 | theorem rpow_pos_of_nonneg {p : ℝ} {x : ℝ≥0∞} (hx_pos : 0 < x) (hp_nonneg : 0 ≤ p) : 0 < x ^ p := by |
by_cases hp_zero : p = 0
· simp [hp_zero, zero_lt_one]
· rw [← Ne] at hp_zero
have hp_pos := lt_of_le_of_ne hp_nonneg hp_zero.symm
rw [← zero_rpow_of_pos hp_pos]
exact rpow_lt_rpow hx_pos hp_pos
|
/-
Copyright (c) 2021 Kyle Miller. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kyle Miller
-/
import Mathlib.Combinatorics.SimpleGraph.Subgraph
import Mathlib.Data.List.Rotate
#align_import combinatorics.simple_graph.connectivity from "leanprover-community/mathlib"@"b99e2d58a5e6861833fa8de11e51a81144258db4"
/-!
# Graph connectivity
In a simple graph,
* A *walk* is a finite sequence of adjacent vertices, and can be
thought of equally well as a sequence of directed edges.
* A *trail* is a walk whose edges each appear no more than once.
* A *path* is a trail whose vertices appear no more than once.
* A *cycle* is a nonempty trail whose first and last vertices are the
same and whose vertices except for the first appear no more than once.
**Warning:** graph theorists mean something different by "path" than
do homotopy theorists. A "walk" in graph theory is a "path" in
homotopy theory. Another warning: some graph theorists use "path" and
"simple path" for "walk" and "path."
Some definitions and theorems have inspiration from multigraph
counterparts in [Chou1994].
## Main definitions
* `SimpleGraph.Walk` (with accompanying pattern definitions
`SimpleGraph.Walk.nil'` and `SimpleGraph.Walk.cons'`)
* `SimpleGraph.Walk.IsTrail`, `SimpleGraph.Walk.IsPath`, and `SimpleGraph.Walk.IsCycle`.
* `SimpleGraph.Path`
* `SimpleGraph.Walk.map` and `SimpleGraph.Path.map` for the induced map on walks,
given an (injective) graph homomorphism.
* `SimpleGraph.Reachable` for the relation of whether there exists
a walk between a given pair of vertices
* `SimpleGraph.Preconnected` and `SimpleGraph.Connected` are predicates
on simple graphs for whether every vertex can be reached from every other,
and in the latter case, whether the vertex type is nonempty.
* `SimpleGraph.ConnectedComponent` is the type of connected components of
a given graph.
* `SimpleGraph.IsBridge` for whether an edge is a bridge edge
## Main statements
* `SimpleGraph.isBridge_iff_mem_and_forall_cycle_not_mem` characterizes bridge edges in terms of
there being no cycle containing them.
## Tags
walks, trails, paths, circuits, cycles, bridge edges
-/
open Function
universe u v w
namespace SimpleGraph
variable {V : Type u} {V' : Type v} {V'' : Type w}
variable (G : SimpleGraph V) (G' : SimpleGraph V') (G'' : SimpleGraph V'')
/-- A walk is a sequence of adjacent vertices. For vertices `u v : V`,
the type `walk u v` consists of all walks starting at `u` and ending at `v`.
We say that a walk *visits* the vertices it contains. The set of vertices a
walk visits is `SimpleGraph.Walk.support`.
See `SimpleGraph.Walk.nil'` and `SimpleGraph.Walk.cons'` for patterns that
can be useful in definitions since they make the vertices explicit. -/
inductive Walk : V → V → Type u
| nil {u : V} : Walk u u
| cons {u v w : V} (h : G.Adj u v) (p : Walk v w) : Walk u w
deriving DecidableEq
#align simple_graph.walk SimpleGraph.Walk
attribute [refl] Walk.nil
@[simps]
instance Walk.instInhabited (v : V) : Inhabited (G.Walk v v) := ⟨Walk.nil⟩
#align simple_graph.walk.inhabited SimpleGraph.Walk.instInhabited
/-- The one-edge walk associated to a pair of adjacent vertices. -/
@[match_pattern, reducible]
def Adj.toWalk {G : SimpleGraph V} {u v : V} (h : G.Adj u v) : G.Walk u v :=
Walk.cons h Walk.nil
#align simple_graph.adj.to_walk SimpleGraph.Adj.toWalk
namespace Walk
variable {G}
/-- Pattern to get `Walk.nil` with the vertex as an explicit argument. -/
@[match_pattern]
abbrev nil' (u : V) : G.Walk u u := Walk.nil
#align simple_graph.walk.nil' SimpleGraph.Walk.nil'
/-- Pattern to get `Walk.cons` with the vertices as explicit arguments. -/
@[match_pattern]
abbrev cons' (u v w : V) (h : G.Adj u v) (p : G.Walk v w) : G.Walk u w := Walk.cons h p
#align simple_graph.walk.cons' SimpleGraph.Walk.cons'
/-- Change the endpoints of a walk using equalities. This is helpful for relaxing
definitional equality constraints and to be able to state otherwise difficult-to-state
lemmas. While this is a simple wrapper around `Eq.rec`, it gives a canonical way to write it.
The simp-normal form is for the `copy` to be pushed outward. That way calculations can
occur within the "copy context." -/
protected def copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') : G.Walk u' v' :=
hu ▸ hv ▸ p
#align simple_graph.walk.copy SimpleGraph.Walk.copy
@[simp]
theorem copy_rfl_rfl {u v} (p : G.Walk u v) : p.copy rfl rfl = p := rfl
#align simple_graph.walk.copy_rfl_rfl SimpleGraph.Walk.copy_rfl_rfl
@[simp]
theorem copy_copy {u v u' v' u'' v''} (p : G.Walk u v)
(hu : u = u') (hv : v = v') (hu' : u' = u'') (hv' : v' = v'') :
(p.copy hu hv).copy hu' hv' = p.copy (hu.trans hu') (hv.trans hv') := by
subst_vars
rfl
#align simple_graph.walk.copy_copy SimpleGraph.Walk.copy_copy
@[simp]
theorem copy_nil {u u'} (hu : u = u') : (Walk.nil : G.Walk u u).copy hu hu = Walk.nil := by
subst_vars
rfl
#align simple_graph.walk.copy_nil SimpleGraph.Walk.copy_nil
theorem copy_cons {u v w u' w'} (h : G.Adj u v) (p : G.Walk v w) (hu : u = u') (hw : w = w') :
(Walk.cons h p).copy hu hw = Walk.cons (hu ▸ h) (p.copy rfl hw) := by
subst_vars
rfl
#align simple_graph.walk.copy_cons SimpleGraph.Walk.copy_cons
@[simp]
theorem cons_copy {u v w v' w'} (h : G.Adj u v) (p : G.Walk v' w') (hv : v' = v) (hw : w' = w) :
Walk.cons h (p.copy hv hw) = (Walk.cons (hv ▸ h) p).copy rfl hw := by
subst_vars
rfl
#align simple_graph.walk.cons_copy SimpleGraph.Walk.cons_copy
theorem exists_eq_cons_of_ne {u v : V} (hne : u ≠ v) :
∀ (p : G.Walk u v), ∃ (w : V) (h : G.Adj u w) (p' : G.Walk w v), p = cons h p'
| nil => (hne rfl).elim
| cons h p' => ⟨_, h, p', rfl⟩
#align simple_graph.walk.exists_eq_cons_of_ne SimpleGraph.Walk.exists_eq_cons_of_ne
/-- The length of a walk is the number of edges/darts along it. -/
def length {u v : V} : G.Walk u v → ℕ
| nil => 0
| cons _ q => q.length.succ
#align simple_graph.walk.length SimpleGraph.Walk.length
/-- The concatenation of two compatible walks. -/
@[trans]
def append {u v w : V} : G.Walk u v → G.Walk v w → G.Walk u w
| nil, q => q
| cons h p, q => cons h (p.append q)
#align simple_graph.walk.append SimpleGraph.Walk.append
/-- The reversed version of `SimpleGraph.Walk.cons`, concatenating an edge to
the end of a walk. -/
def concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) : G.Walk u w := p.append (cons h nil)
#align simple_graph.walk.concat SimpleGraph.Walk.concat
theorem concat_eq_append {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
p.concat h = p.append (cons h nil) := rfl
#align simple_graph.walk.concat_eq_append SimpleGraph.Walk.concat_eq_append
/-- The concatenation of the reverse of the first walk with the second walk. -/
protected def reverseAux {u v w : V} : G.Walk u v → G.Walk u w → G.Walk v w
| nil, q => q
| cons h p, q => Walk.reverseAux p (cons (G.symm h) q)
#align simple_graph.walk.reverse_aux SimpleGraph.Walk.reverseAux
/-- The walk in reverse. -/
@[symm]
def reverse {u v : V} (w : G.Walk u v) : G.Walk v u := w.reverseAux nil
#align simple_graph.walk.reverse SimpleGraph.Walk.reverse
/-- Get the `n`th vertex from a walk, where `n` is generally expected to be
between `0` and `p.length`, inclusive.
If `n` is greater than or equal to `p.length`, the result is the path's endpoint. -/
def getVert {u v : V} : G.Walk u v → ℕ → V
| nil, _ => u
| cons _ _, 0 => u
| cons _ q, n + 1 => q.getVert n
#align simple_graph.walk.get_vert SimpleGraph.Walk.getVert
@[simp]
theorem getVert_zero {u v} (w : G.Walk u v) : w.getVert 0 = u := by cases w <;> rfl
#align simple_graph.walk.get_vert_zero SimpleGraph.Walk.getVert_zero
theorem getVert_of_length_le {u v} (w : G.Walk u v) {i : ℕ} (hi : w.length ≤ i) :
w.getVert i = v := by
induction w generalizing i with
| nil => rfl
| cons _ _ ih =>
cases i
· cases hi
· exact ih (Nat.succ_le_succ_iff.1 hi)
#align simple_graph.walk.get_vert_of_length_le SimpleGraph.Walk.getVert_of_length_le
@[simp]
theorem getVert_length {u v} (w : G.Walk u v) : w.getVert w.length = v :=
w.getVert_of_length_le rfl.le
#align simple_graph.walk.get_vert_length SimpleGraph.Walk.getVert_length
theorem adj_getVert_succ {u v} (w : G.Walk u v) {i : ℕ} (hi : i < w.length) :
G.Adj (w.getVert i) (w.getVert (i + 1)) := by
induction w generalizing i with
| nil => cases hi
| cons hxy _ ih =>
cases i
· simp [getVert, hxy]
· exact ih (Nat.succ_lt_succ_iff.1 hi)
#align simple_graph.walk.adj_get_vert_succ SimpleGraph.Walk.adj_getVert_succ
@[simp]
theorem cons_append {u v w x : V} (h : G.Adj u v) (p : G.Walk v w) (q : G.Walk w x) :
(cons h p).append q = cons h (p.append q) := rfl
#align simple_graph.walk.cons_append SimpleGraph.Walk.cons_append
@[simp]
theorem cons_nil_append {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h nil).append p = cons h p := rfl
#align simple_graph.walk.cons_nil_append SimpleGraph.Walk.cons_nil_append
@[simp]
theorem append_nil {u v : V} (p : G.Walk u v) : p.append nil = p := by
induction p with
| nil => rfl
| cons _ _ ih => rw [cons_append, ih]
#align simple_graph.walk.append_nil SimpleGraph.Walk.append_nil
@[simp]
theorem nil_append {u v : V} (p : G.Walk u v) : nil.append p = p :=
rfl
#align simple_graph.walk.nil_append SimpleGraph.Walk.nil_append
theorem append_assoc {u v w x : V} (p : G.Walk u v) (q : G.Walk v w) (r : G.Walk w x) :
p.append (q.append r) = (p.append q).append r := by
induction p with
| nil => rfl
| cons h p' ih =>
dsimp only [append]
rw [ih]
#align simple_graph.walk.append_assoc SimpleGraph.Walk.append_assoc
@[simp]
theorem append_copy_copy {u v w u' v' w'} (p : G.Walk u v) (q : G.Walk v w)
(hu : u = u') (hv : v = v') (hw : w = w') :
(p.copy hu hv).append (q.copy hv hw) = (p.append q).copy hu hw := by
subst_vars
rfl
#align simple_graph.walk.append_copy_copy SimpleGraph.Walk.append_copy_copy
theorem concat_nil {u v : V} (h : G.Adj u v) : nil.concat h = cons h nil := rfl
#align simple_graph.walk.concat_nil SimpleGraph.Walk.concat_nil
@[simp]
theorem concat_cons {u v w x : V} (h : G.Adj u v) (p : G.Walk v w) (h' : G.Adj w x) :
(cons h p).concat h' = cons h (p.concat h') := rfl
#align simple_graph.walk.concat_cons SimpleGraph.Walk.concat_cons
theorem append_concat {u v w x : V} (p : G.Walk u v) (q : G.Walk v w) (h : G.Adj w x) :
p.append (q.concat h) = (p.append q).concat h := append_assoc _ _ _
#align simple_graph.walk.append_concat SimpleGraph.Walk.append_concat
theorem concat_append {u v w x : V} (p : G.Walk u v) (h : G.Adj v w) (q : G.Walk w x) :
(p.concat h).append q = p.append (cons h q) := by
rw [concat_eq_append, ← append_assoc, cons_nil_append]
#align simple_graph.walk.concat_append SimpleGraph.Walk.concat_append
/-- A non-trivial `cons` walk is representable as a `concat` walk. -/
theorem exists_cons_eq_concat {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
∃ (x : V) (q : G.Walk u x) (h' : G.Adj x w), cons h p = q.concat h' := by
induction p generalizing u with
| nil => exact ⟨_, nil, h, rfl⟩
| cons h' p ih =>
obtain ⟨y, q, h'', hc⟩ := ih h'
refine ⟨y, cons h q, h'', ?_⟩
rw [concat_cons, hc]
#align simple_graph.walk.exists_cons_eq_concat SimpleGraph.Walk.exists_cons_eq_concat
/-- A non-trivial `concat` walk is representable as a `cons` walk. -/
theorem exists_concat_eq_cons {u v w : V} :
∀ (p : G.Walk u v) (h : G.Adj v w),
∃ (x : V) (h' : G.Adj u x) (q : G.Walk x w), p.concat h = cons h' q
| nil, h => ⟨_, h, nil, rfl⟩
| cons h' p, h => ⟨_, h', Walk.concat p h, concat_cons _ _ _⟩
#align simple_graph.walk.exists_concat_eq_cons SimpleGraph.Walk.exists_concat_eq_cons
@[simp]
theorem reverse_nil {u : V} : (nil : G.Walk u u).reverse = nil := rfl
#align simple_graph.walk.reverse_nil SimpleGraph.Walk.reverse_nil
theorem reverse_singleton {u v : V} (h : G.Adj u v) : (cons h nil).reverse = cons (G.symm h) nil :=
rfl
#align simple_graph.walk.reverse_singleton SimpleGraph.Walk.reverse_singleton
@[simp]
theorem cons_reverseAux {u v w x : V} (p : G.Walk u v) (q : G.Walk w x) (h : G.Adj w u) :
(cons h p).reverseAux q = p.reverseAux (cons (G.symm h) q) := rfl
#align simple_graph.walk.cons_reverse_aux SimpleGraph.Walk.cons_reverseAux
@[simp]
protected theorem append_reverseAux {u v w x : V}
(p : G.Walk u v) (q : G.Walk v w) (r : G.Walk u x) :
(p.append q).reverseAux r = q.reverseAux (p.reverseAux r) := by
induction p with
| nil => rfl
| cons h _ ih => exact ih q (cons (G.symm h) r)
#align simple_graph.walk.append_reverse_aux SimpleGraph.Walk.append_reverseAux
@[simp]
protected theorem reverseAux_append {u v w x : V}
(p : G.Walk u v) (q : G.Walk u w) (r : G.Walk w x) :
(p.reverseAux q).append r = p.reverseAux (q.append r) := by
induction p with
| nil => rfl
| cons h _ ih => simp [ih (cons (G.symm h) q)]
#align simple_graph.walk.reverse_aux_append SimpleGraph.Walk.reverseAux_append
protected theorem reverseAux_eq_reverse_append {u v w : V} (p : G.Walk u v) (q : G.Walk u w) :
p.reverseAux q = p.reverse.append q := by simp [reverse]
#align simple_graph.walk.reverse_aux_eq_reverse_append SimpleGraph.Walk.reverseAux_eq_reverse_append
@[simp]
theorem reverse_cons {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).reverse = p.reverse.append (cons (G.symm h) nil) := by simp [reverse]
#align simple_graph.walk.reverse_cons SimpleGraph.Walk.reverse_cons
@[simp]
theorem reverse_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).reverse = p.reverse.copy hv hu := by
subst_vars
rfl
#align simple_graph.walk.reverse_copy SimpleGraph.Walk.reverse_copy
@[simp]
theorem reverse_append {u v w : V} (p : G.Walk u v) (q : G.Walk v w) :
(p.append q).reverse = q.reverse.append p.reverse := by simp [reverse]
#align simple_graph.walk.reverse_append SimpleGraph.Walk.reverse_append
@[simp]
theorem reverse_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
(p.concat h).reverse = cons (G.symm h) p.reverse := by simp [concat_eq_append]
#align simple_graph.walk.reverse_concat SimpleGraph.Walk.reverse_concat
@[simp]
theorem reverse_reverse {u v : V} (p : G.Walk u v) : p.reverse.reverse = p := by
induction p with
| nil => rfl
| cons _ _ ih => simp [ih]
#align simple_graph.walk.reverse_reverse SimpleGraph.Walk.reverse_reverse
@[simp]
theorem length_nil {u : V} : (nil : G.Walk u u).length = 0 := rfl
#align simple_graph.walk.length_nil SimpleGraph.Walk.length_nil
@[simp]
theorem length_cons {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).length = p.length + 1 := rfl
#align simple_graph.walk.length_cons SimpleGraph.Walk.length_cons
@[simp]
theorem length_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).length = p.length := by
subst_vars
rfl
#align simple_graph.walk.length_copy SimpleGraph.Walk.length_copy
@[simp]
theorem length_append {u v w : V} (p : G.Walk u v) (q : G.Walk v w) :
(p.append q).length = p.length + q.length := by
induction p with
| nil => simp
| cons _ _ ih => simp [ih, add_comm, add_left_comm, add_assoc]
#align simple_graph.walk.length_append SimpleGraph.Walk.length_append
@[simp]
theorem length_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
(p.concat h).length = p.length + 1 := length_append _ _
#align simple_graph.walk.length_concat SimpleGraph.Walk.length_concat
@[simp]
protected theorem length_reverseAux {u v w : V} (p : G.Walk u v) (q : G.Walk u w) :
(p.reverseAux q).length = p.length + q.length := by
induction p with
| nil => simp!
| cons _ _ ih => simp [ih, Nat.succ_add, Nat.add_assoc]
#align simple_graph.walk.length_reverse_aux SimpleGraph.Walk.length_reverseAux
@[simp]
theorem length_reverse {u v : V} (p : G.Walk u v) : p.reverse.length = p.length := by simp [reverse]
#align simple_graph.walk.length_reverse SimpleGraph.Walk.length_reverse
theorem eq_of_length_eq_zero {u v : V} : ∀ {p : G.Walk u v}, p.length = 0 → u = v
| nil, _ => rfl
#align simple_graph.walk.eq_of_length_eq_zero SimpleGraph.Walk.eq_of_length_eq_zero
theorem adj_of_length_eq_one {u v : V} : ∀ {p : G.Walk u v}, p.length = 1 → G.Adj u v
| cons h nil, _ => h
@[simp]
theorem exists_length_eq_zero_iff {u v : V} : (∃ p : G.Walk u v, p.length = 0) ↔ u = v := by
constructor
· rintro ⟨p, hp⟩
exact eq_of_length_eq_zero hp
· rintro rfl
exact ⟨nil, rfl⟩
#align simple_graph.walk.exists_length_eq_zero_iff SimpleGraph.Walk.exists_length_eq_zero_iff
@[simp]
theorem length_eq_zero_iff {u : V} {p : G.Walk u u} : p.length = 0 ↔ p = nil := by cases p <;> simp
#align simple_graph.walk.length_eq_zero_iff SimpleGraph.Walk.length_eq_zero_iff
theorem getVert_append {u v w : V} (p : G.Walk u v) (q : G.Walk v w) (i : ℕ) :
(p.append q).getVert i = if i < p.length then p.getVert i else q.getVert (i - p.length) := by
induction p generalizing i with
| nil => simp
| cons h p ih => cases i <;> simp [getVert, ih, Nat.succ_lt_succ_iff]
theorem getVert_reverse {u v : V} (p : G.Walk u v) (i : ℕ) :
p.reverse.getVert i = p.getVert (p.length - i) := by
induction p with
| nil => rfl
| cons h p ih =>
simp only [reverse_cons, getVert_append, length_reverse, ih, length_cons]
split_ifs
next hi =>
rw [Nat.succ_sub hi.le]
simp [getVert]
next hi =>
obtain rfl | hi' := Nat.eq_or_lt_of_not_lt hi
· simp [getVert]
· rw [Nat.eq_add_of_sub_eq (Nat.sub_pos_of_lt hi') rfl, Nat.sub_eq_zero_of_le hi']
simp [getVert]
section ConcatRec
variable {motive : ∀ u v : V, G.Walk u v → Sort*} (Hnil : ∀ {u : V}, motive u u nil)
(Hconcat : ∀ {u v w : V} (p : G.Walk u v) (h : G.Adj v w), motive u v p → motive u w (p.concat h))
/-- Auxiliary definition for `SimpleGraph.Walk.concatRec` -/
def concatRecAux {u v : V} : (p : G.Walk u v) → motive v u p.reverse
| nil => Hnil
| cons h p => reverse_cons h p ▸ Hconcat p.reverse h.symm (concatRecAux p)
#align simple_graph.walk.concat_rec_aux SimpleGraph.Walk.concatRecAux
/-- Recursor on walks by inducting on `SimpleGraph.Walk.concat`.
This is inducting from the opposite end of the walk compared
to `SimpleGraph.Walk.rec`, which inducts on `SimpleGraph.Walk.cons`. -/
@[elab_as_elim]
def concatRec {u v : V} (p : G.Walk u v) : motive u v p :=
reverse_reverse p ▸ concatRecAux @Hnil @Hconcat p.reverse
#align simple_graph.walk.concat_rec SimpleGraph.Walk.concatRec
@[simp]
theorem concatRec_nil (u : V) :
@concatRec _ _ motive @Hnil @Hconcat _ _ (nil : G.Walk u u) = Hnil := rfl
#align simple_graph.walk.concat_rec_nil SimpleGraph.Walk.concatRec_nil
@[simp]
theorem concatRec_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
@concatRec _ _ motive @Hnil @Hconcat _ _ (p.concat h) =
Hconcat p h (concatRec @Hnil @Hconcat p) := by
simp only [concatRec]
apply eq_of_heq
apply rec_heq_of_heq
trans concatRecAux @Hnil @Hconcat (cons h.symm p.reverse)
· congr
simp
· rw [concatRecAux, rec_heq_iff_heq]
congr <;> simp [heq_rec_iff_heq]
#align simple_graph.walk.concat_rec_concat SimpleGraph.Walk.concatRec_concat
end ConcatRec
theorem concat_ne_nil {u v : V} (p : G.Walk u v) (h : G.Adj v u) : p.concat h ≠ nil := by
cases p <;> simp [concat]
#align simple_graph.walk.concat_ne_nil SimpleGraph.Walk.concat_ne_nil
theorem concat_inj {u v v' w : V} {p : G.Walk u v} {h : G.Adj v w} {p' : G.Walk u v'}
{h' : G.Adj v' w} (he : p.concat h = p'.concat h') : ∃ hv : v = v', p.copy rfl hv = p' := by
induction p with
| nil =>
cases p'
· exact ⟨rfl, rfl⟩
· exfalso
simp only [concat_nil, concat_cons, cons.injEq] at he
obtain ⟨rfl, he⟩ := he
simp only [heq_iff_eq] at he
exact concat_ne_nil _ _ he.symm
| cons _ _ ih =>
rw [concat_cons] at he
cases p'
· exfalso
simp only [concat_nil, cons.injEq] at he
obtain ⟨rfl, he⟩ := he
rw [heq_iff_eq] at he
exact concat_ne_nil _ _ he
· rw [concat_cons, cons.injEq] at he
obtain ⟨rfl, he⟩ := he
rw [heq_iff_eq] at he
obtain ⟨rfl, rfl⟩ := ih he
exact ⟨rfl, rfl⟩
#align simple_graph.walk.concat_inj SimpleGraph.Walk.concat_inj
/-- The `support` of a walk is the list of vertices it visits in order. -/
def support {u v : V} : G.Walk u v → List V
| nil => [u]
| cons _ p => u :: p.support
#align simple_graph.walk.support SimpleGraph.Walk.support
/-- The `darts` of a walk is the list of darts it visits in order. -/
def darts {u v : V} : G.Walk u v → List G.Dart
| nil => []
| cons h p => ⟨(u, _), h⟩ :: p.darts
#align simple_graph.walk.darts SimpleGraph.Walk.darts
/-- The `edges` of a walk is the list of edges it visits in order.
This is defined to be the list of edges underlying `SimpleGraph.Walk.darts`. -/
def edges {u v : V} (p : G.Walk u v) : List (Sym2 V) := p.darts.map Dart.edge
#align simple_graph.walk.edges SimpleGraph.Walk.edges
@[simp]
theorem support_nil {u : V} : (nil : G.Walk u u).support = [u] := rfl
#align simple_graph.walk.support_nil SimpleGraph.Walk.support_nil
@[simp]
theorem support_cons {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).support = u :: p.support := rfl
#align simple_graph.walk.support_cons SimpleGraph.Walk.support_cons
@[simp]
theorem support_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
(p.concat h).support = p.support.concat w := by
induction p <;> simp [*, concat_nil]
#align simple_graph.walk.support_concat SimpleGraph.Walk.support_concat
@[simp]
theorem support_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).support = p.support := by
subst_vars
rfl
#align simple_graph.walk.support_copy SimpleGraph.Walk.support_copy
theorem support_append {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
(p.append p').support = p.support ++ p'.support.tail := by
induction p <;> cases p' <;> simp [*]
#align simple_graph.walk.support_append SimpleGraph.Walk.support_append
@[simp]
theorem support_reverse {u v : V} (p : G.Walk u v) : p.reverse.support = p.support.reverse := by
induction p <;> simp [support_append, *]
#align simple_graph.walk.support_reverse SimpleGraph.Walk.support_reverse
@[simp]
theorem support_ne_nil {u v : V} (p : G.Walk u v) : p.support ≠ [] := by cases p <;> simp
#align simple_graph.walk.support_ne_nil SimpleGraph.Walk.support_ne_nil
theorem tail_support_append {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
(p.append p').support.tail = p.support.tail ++ p'.support.tail := by
rw [support_append, List.tail_append_of_ne_nil _ _ (support_ne_nil _)]
#align simple_graph.walk.tail_support_append SimpleGraph.Walk.tail_support_append
theorem support_eq_cons {u v : V} (p : G.Walk u v) : p.support = u :: p.support.tail := by
cases p <;> simp
#align simple_graph.walk.support_eq_cons SimpleGraph.Walk.support_eq_cons
@[simp]
theorem start_mem_support {u v : V} (p : G.Walk u v) : u ∈ p.support := by cases p <;> simp
#align simple_graph.walk.start_mem_support SimpleGraph.Walk.start_mem_support
@[simp]
theorem end_mem_support {u v : V} (p : G.Walk u v) : v ∈ p.support := by induction p <;> simp [*]
#align simple_graph.walk.end_mem_support SimpleGraph.Walk.end_mem_support
@[simp]
theorem support_nonempty {u v : V} (p : G.Walk u v) : { w | w ∈ p.support }.Nonempty :=
⟨u, by simp⟩
#align simple_graph.walk.support_nonempty SimpleGraph.Walk.support_nonempty
theorem mem_support_iff {u v w : V} (p : G.Walk u v) :
w ∈ p.support ↔ w = u ∨ w ∈ p.support.tail := by cases p <;> simp
#align simple_graph.walk.mem_support_iff SimpleGraph.Walk.mem_support_iff
theorem mem_support_nil_iff {u v : V} : u ∈ (nil : G.Walk v v).support ↔ u = v := by simp
#align simple_graph.walk.mem_support_nil_iff SimpleGraph.Walk.mem_support_nil_iff
@[simp]
theorem mem_tail_support_append_iff {t u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
t ∈ (p.append p').support.tail ↔ t ∈ p.support.tail ∨ t ∈ p'.support.tail := by
rw [tail_support_append, List.mem_append]
#align simple_graph.walk.mem_tail_support_append_iff SimpleGraph.Walk.mem_tail_support_append_iff
@[simp]
theorem end_mem_tail_support_of_ne {u v : V} (h : u ≠ v) (p : G.Walk u v) : v ∈ p.support.tail := by
obtain ⟨_, _, _, rfl⟩ := exists_eq_cons_of_ne h p
simp
#align simple_graph.walk.end_mem_tail_support_of_ne SimpleGraph.Walk.end_mem_tail_support_of_ne
@[simp, nolint unusedHavesSuffices]
theorem mem_support_append_iff {t u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
t ∈ (p.append p').support ↔ t ∈ p.support ∨ t ∈ p'.support := by
simp only [mem_support_iff, mem_tail_support_append_iff]
obtain rfl | h := eq_or_ne t v <;> obtain rfl | h' := eq_or_ne t u <;>
-- this `have` triggers the unusedHavesSuffices linter:
(try have := h'.symm) <;> simp [*]
#align simple_graph.walk.mem_support_append_iff SimpleGraph.Walk.mem_support_append_iff
@[simp]
theorem subset_support_append_left {V : Type u} {G : SimpleGraph V} {u v w : V}
(p : G.Walk u v) (q : G.Walk v w) : p.support ⊆ (p.append q).support := by
simp only [Walk.support_append, List.subset_append_left]
#align simple_graph.walk.subset_support_append_left SimpleGraph.Walk.subset_support_append_left
@[simp]
theorem subset_support_append_right {V : Type u} {G : SimpleGraph V} {u v w : V}
(p : G.Walk u v) (q : G.Walk v w) : q.support ⊆ (p.append q).support := by
intro h
simp (config := { contextual := true }) only [mem_support_append_iff, or_true_iff, imp_true_iff]
#align simple_graph.walk.subset_support_append_right SimpleGraph.Walk.subset_support_append_right
theorem coe_support {u v : V} (p : G.Walk u v) :
(p.support : Multiset V) = {u} + p.support.tail := by cases p <;> rfl
#align simple_graph.walk.coe_support SimpleGraph.Walk.coe_support
theorem coe_support_append {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
((p.append p').support : Multiset V) = {u} + p.support.tail + p'.support.tail := by
rw [support_append, ← Multiset.coe_add, coe_support]
#align simple_graph.walk.coe_support_append SimpleGraph.Walk.coe_support_append
theorem coe_support_append' [DecidableEq V] {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
((p.append p').support : Multiset V) = p.support + p'.support - {v} := by
rw [support_append, ← Multiset.coe_add]
simp only [coe_support]
rw [add_comm ({v} : Multiset V)]
simp only [← add_assoc, add_tsub_cancel_right]
#align simple_graph.walk.coe_support_append' SimpleGraph.Walk.coe_support_append'
theorem chain_adj_support {u v w : V} (h : G.Adj u v) :
∀ (p : G.Walk v w), List.Chain G.Adj u p.support
| nil => List.Chain.cons h List.Chain.nil
| cons h' p => List.Chain.cons h (chain_adj_support h' p)
#align simple_graph.walk.chain_adj_support SimpleGraph.Walk.chain_adj_support
theorem chain'_adj_support {u v : V} : ∀ (p : G.Walk u v), List.Chain' G.Adj p.support
| nil => List.Chain.nil
| cons h p => chain_adj_support h p
#align simple_graph.walk.chain'_adj_support SimpleGraph.Walk.chain'_adj_support
theorem chain_dartAdj_darts {d : G.Dart} {v w : V} (h : d.snd = v) (p : G.Walk v w) :
List.Chain G.DartAdj d p.darts := by
induction p generalizing d with
| nil => exact List.Chain.nil
-- Porting note: needed to defer `h` and `rfl` to help elaboration
| cons h' p ih => exact List.Chain.cons (by exact h) (ih (by rfl))
#align simple_graph.walk.chain_dart_adj_darts SimpleGraph.Walk.chain_dartAdj_darts
theorem chain'_dartAdj_darts {u v : V} : ∀ (p : G.Walk u v), List.Chain' G.DartAdj p.darts
| nil => trivial
-- Porting note: needed to defer `rfl` to help elaboration
| cons h p => chain_dartAdj_darts (by rfl) p
#align simple_graph.walk.chain'_dart_adj_darts SimpleGraph.Walk.chain'_dartAdj_darts
/-- Every edge in a walk's edge list is an edge of the graph.
It is written in this form (rather than using `⊆`) to avoid unsightly coercions. -/
theorem edges_subset_edgeSet {u v : V} :
∀ (p : G.Walk u v) ⦃e : Sym2 V⦄, e ∈ p.edges → e ∈ G.edgeSet
| cons h' p', e, h => by
cases h
· exact h'
next h' => exact edges_subset_edgeSet p' h'
#align simple_graph.walk.edges_subset_edge_set SimpleGraph.Walk.edges_subset_edgeSet
theorem adj_of_mem_edges {u v x y : V} (p : G.Walk u v) (h : s(x, y) ∈ p.edges) : G.Adj x y :=
edges_subset_edgeSet p h
#align simple_graph.walk.adj_of_mem_edges SimpleGraph.Walk.adj_of_mem_edges
@[simp]
theorem darts_nil {u : V} : (nil : G.Walk u u).darts = [] := rfl
#align simple_graph.walk.darts_nil SimpleGraph.Walk.darts_nil
@[simp]
theorem darts_cons {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).darts = ⟨(u, v), h⟩ :: p.darts := rfl
#align simple_graph.walk.darts_cons SimpleGraph.Walk.darts_cons
@[simp]
theorem darts_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
(p.concat h).darts = p.darts.concat ⟨(v, w), h⟩ := by
induction p <;> simp [*, concat_nil]
#align simple_graph.walk.darts_concat SimpleGraph.Walk.darts_concat
@[simp]
theorem darts_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).darts = p.darts := by
subst_vars
rfl
#align simple_graph.walk.darts_copy SimpleGraph.Walk.darts_copy
@[simp]
theorem darts_append {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
(p.append p').darts = p.darts ++ p'.darts := by
induction p <;> simp [*]
#align simple_graph.walk.darts_append SimpleGraph.Walk.darts_append
@[simp]
theorem darts_reverse {u v : V} (p : G.Walk u v) :
p.reverse.darts = (p.darts.map Dart.symm).reverse := by
induction p <;> simp [*, Sym2.eq_swap]
#align simple_graph.walk.darts_reverse SimpleGraph.Walk.darts_reverse
theorem mem_darts_reverse {u v : V} {d : G.Dart} {p : G.Walk u v} :
d ∈ p.reverse.darts ↔ d.symm ∈ p.darts := by simp
#align simple_graph.walk.mem_darts_reverse SimpleGraph.Walk.mem_darts_reverse
theorem cons_map_snd_darts {u v : V} (p : G.Walk u v) : (u :: p.darts.map (·.snd)) = p.support := by
induction p <;> simp! [*]
#align simple_graph.walk.cons_map_snd_darts SimpleGraph.Walk.cons_map_snd_darts
theorem map_snd_darts {u v : V} (p : G.Walk u v) : p.darts.map (·.snd) = p.support.tail := by
simpa using congr_arg List.tail (cons_map_snd_darts p)
#align simple_graph.walk.map_snd_darts SimpleGraph.Walk.map_snd_darts
theorem map_fst_darts_append {u v : V} (p : G.Walk u v) :
p.darts.map (·.fst) ++ [v] = p.support := by
induction p <;> simp! [*]
#align simple_graph.walk.map_fst_darts_append SimpleGraph.Walk.map_fst_darts_append
theorem map_fst_darts {u v : V} (p : G.Walk u v) : p.darts.map (·.fst) = p.support.dropLast := by
simpa! using congr_arg List.dropLast (map_fst_darts_append p)
#align simple_graph.walk.map_fst_darts SimpleGraph.Walk.map_fst_darts
@[simp]
theorem edges_nil {u : V} : (nil : G.Walk u u).edges = [] := rfl
#align simple_graph.walk.edges_nil SimpleGraph.Walk.edges_nil
@[simp]
theorem edges_cons {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).edges = s(u, v) :: p.edges := rfl
#align simple_graph.walk.edges_cons SimpleGraph.Walk.edges_cons
@[simp]
theorem edges_concat {u v w : V} (p : G.Walk u v) (h : G.Adj v w) :
(p.concat h).edges = p.edges.concat s(v, w) := by simp [edges]
#align simple_graph.walk.edges_concat SimpleGraph.Walk.edges_concat
@[simp]
theorem edges_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).edges = p.edges := by
subst_vars
rfl
#align simple_graph.walk.edges_copy SimpleGraph.Walk.edges_copy
@[simp]
theorem edges_append {u v w : V} (p : G.Walk u v) (p' : G.Walk v w) :
(p.append p').edges = p.edges ++ p'.edges := by simp [edges]
#align simple_graph.walk.edges_append SimpleGraph.Walk.edges_append
@[simp]
theorem edges_reverse {u v : V} (p : G.Walk u v) : p.reverse.edges = p.edges.reverse := by
simp [edges, List.map_reverse]
#align simple_graph.walk.edges_reverse SimpleGraph.Walk.edges_reverse
@[simp]
theorem length_support {u v : V} (p : G.Walk u v) : p.support.length = p.length + 1 := by
induction p <;> simp [*]
#align simple_graph.walk.length_support SimpleGraph.Walk.length_support
@[simp]
theorem length_darts {u v : V} (p : G.Walk u v) : p.darts.length = p.length := by
induction p <;> simp [*]
#align simple_graph.walk.length_darts SimpleGraph.Walk.length_darts
@[simp]
theorem length_edges {u v : V} (p : G.Walk u v) : p.edges.length = p.length := by simp [edges]
#align simple_graph.walk.length_edges SimpleGraph.Walk.length_edges
theorem dart_fst_mem_support_of_mem_darts {u v : V} :
∀ (p : G.Walk u v) {d : G.Dart}, d ∈ p.darts → d.fst ∈ p.support
| cons h p', d, hd => by
simp only [support_cons, darts_cons, List.mem_cons] at hd ⊢
rcases hd with (rfl | hd)
· exact Or.inl rfl
· exact Or.inr (dart_fst_mem_support_of_mem_darts _ hd)
#align simple_graph.walk.dart_fst_mem_support_of_mem_darts SimpleGraph.Walk.dart_fst_mem_support_of_mem_darts
theorem dart_snd_mem_support_of_mem_darts {u v : V} (p : G.Walk u v) {d : G.Dart}
(h : d ∈ p.darts) : d.snd ∈ p.support := by
simpa using p.reverse.dart_fst_mem_support_of_mem_darts (by simp [h] : d.symm ∈ p.reverse.darts)
#align simple_graph.walk.dart_snd_mem_support_of_mem_darts SimpleGraph.Walk.dart_snd_mem_support_of_mem_darts
theorem fst_mem_support_of_mem_edges {t u v w : V} (p : G.Walk v w) (he : s(t, u) ∈ p.edges) :
t ∈ p.support := by
obtain ⟨d, hd, he⟩ := List.mem_map.mp he
rw [dart_edge_eq_mk'_iff'] at he
rcases he with (⟨rfl, rfl⟩ | ⟨rfl, rfl⟩)
· exact dart_fst_mem_support_of_mem_darts _ hd
· exact dart_snd_mem_support_of_mem_darts _ hd
#align simple_graph.walk.fst_mem_support_of_mem_edges SimpleGraph.Walk.fst_mem_support_of_mem_edges
theorem snd_mem_support_of_mem_edges {t u v w : V} (p : G.Walk v w) (he : s(t, u) ∈ p.edges) :
u ∈ p.support := by
rw [Sym2.eq_swap] at he
exact p.fst_mem_support_of_mem_edges he
#align simple_graph.walk.snd_mem_support_of_mem_edges SimpleGraph.Walk.snd_mem_support_of_mem_edges
theorem darts_nodup_of_support_nodup {u v : V} {p : G.Walk u v} (h : p.support.Nodup) :
p.darts.Nodup := by
induction p with
| nil => simp
| cons _ p' ih =>
simp only [darts_cons, support_cons, List.nodup_cons] at h ⊢
exact ⟨fun h' => h.1 (dart_fst_mem_support_of_mem_darts p' h'), ih h.2⟩
#align simple_graph.walk.darts_nodup_of_support_nodup SimpleGraph.Walk.darts_nodup_of_support_nodup
theorem edges_nodup_of_support_nodup {u v : V} {p : G.Walk u v} (h : p.support.Nodup) :
p.edges.Nodup := by
induction p with
| nil => simp
| cons _ p' ih =>
simp only [edges_cons, support_cons, List.nodup_cons] at h ⊢
exact ⟨fun h' => h.1 (fst_mem_support_of_mem_edges p' h'), ih h.2⟩
#align simple_graph.walk.edges_nodup_of_support_nodup SimpleGraph.Walk.edges_nodup_of_support_nodup
/-- Predicate for the empty walk.
Solves the dependent type problem where `p = G.Walk.nil` typechecks
only if `p` has defeq endpoints. -/
inductive Nil : {v w : V} → G.Walk v w → Prop
| nil {u : V} : Nil (nil : G.Walk u u)
variable {u v w : V}
@[simp] lemma nil_nil : (nil : G.Walk u u).Nil := Nil.nil
@[simp] lemma not_nil_cons {h : G.Adj u v} {p : G.Walk v w} : ¬ (cons h p).Nil := nofun
instance (p : G.Walk v w) : Decidable p.Nil :=
match p with
| nil => isTrue .nil
| cons _ _ => isFalse nofun
protected lemma Nil.eq {p : G.Walk v w} : p.Nil → v = w | .nil => rfl
lemma not_nil_of_ne {p : G.Walk v w} : v ≠ w → ¬ p.Nil := mt Nil.eq
lemma nil_iff_support_eq {p : G.Walk v w} : p.Nil ↔ p.support = [v] := by
cases p <;> simp
lemma nil_iff_length_eq {p : G.Walk v w} : p.Nil ↔ p.length = 0 := by
cases p <;> simp
lemma not_nil_iff {p : G.Walk v w} :
¬ p.Nil ↔ ∃ (u : V) (h : G.Adj v u) (q : G.Walk u w), p = cons h q := by
cases p <;> simp [*]
/-- A walk with its endpoints defeq is `Nil` if and only if it is equal to `nil`. -/
lemma nil_iff_eq_nil : ∀ {p : G.Walk v v}, p.Nil ↔ p = nil
| .nil | .cons _ _ => by simp
alias ⟨Nil.eq_nil, _⟩ := nil_iff_eq_nil
@[elab_as_elim]
def notNilRec {motive : {u w : V} → (p : G.Walk u w) → (h : ¬ p.Nil) → Sort*}
(cons : {u v w : V} → (h : G.Adj u v) → (q : G.Walk v w) → motive (cons h q) not_nil_cons)
(p : G.Walk u w) : (hp : ¬ p.Nil) → motive p hp :=
match p with
| nil => fun hp => absurd .nil hp
| .cons h q => fun _ => cons h q
/-- The second vertex along a non-nil walk. -/
def sndOfNotNil (p : G.Walk v w) (hp : ¬ p.Nil) : V :=
p.notNilRec (@fun _ u _ _ _ => u) hp
@[simp] lemma adj_sndOfNotNil {p : G.Walk v w} (hp : ¬ p.Nil) :
G.Adj v (p.sndOfNotNil hp) :=
p.notNilRec (fun h _ => h) hp
/-- The walk obtained by removing the first dart of a non-nil walk. -/
def tail (p : G.Walk u v) (hp : ¬ p.Nil) : G.Walk (p.sndOfNotNil hp) v :=
p.notNilRec (fun _ q => q) hp
/-- The first dart of a walk. -/
@[simps]
def firstDart (p : G.Walk v w) (hp : ¬ p.Nil) : G.Dart where
fst := v
snd := p.sndOfNotNil hp
adj := p.adj_sndOfNotNil hp
lemma edge_firstDart (p : G.Walk v w) (hp : ¬ p.Nil) :
(p.firstDart hp).edge = s(v, p.sndOfNotNil hp) := rfl
variable {x y : V} -- TODO: rename to u, v, w instead?
@[simp] lemma cons_tail_eq (p : G.Walk x y) (hp : ¬ p.Nil) :
cons (p.adj_sndOfNotNil hp) (p.tail hp) = p :=
p.notNilRec (fun _ _ => rfl) hp
@[simp] lemma cons_support_tail (p : G.Walk x y) (hp : ¬p.Nil) :
x :: (p.tail hp).support = p.support := by
rw [← support_cons, cons_tail_eq]
@[simp] lemma length_tail_add_one {p : G.Walk x y} (hp : ¬ p.Nil) :
(p.tail hp).length + 1 = p.length := by
rw [← length_cons, cons_tail_eq]
@[simp] lemma nil_copy {x' y' : V} {p : G.Walk x y} (hx : x = x') (hy : y = y') :
(p.copy hx hy).Nil = p.Nil := by
subst_vars; rfl
@[simp] lemma support_tail (p : G.Walk v v) (hp) :
(p.tail hp).support = p.support.tail := by
rw [← cons_support_tail p hp, List.tail_cons]
/-! ### Trails, paths, circuits, cycles -/
/-- A *trail* is a walk with no repeating edges. -/
@[mk_iff isTrail_def]
structure IsTrail {u v : V} (p : G.Walk u v) : Prop where
edges_nodup : p.edges.Nodup
#align simple_graph.walk.is_trail SimpleGraph.Walk.IsTrail
#align simple_graph.walk.is_trail_def SimpleGraph.Walk.isTrail_def
/-- A *path* is a walk with no repeating vertices.
Use `SimpleGraph.Walk.IsPath.mk'` for a simpler constructor. -/
structure IsPath {u v : V} (p : G.Walk u v) extends IsTrail p : Prop where
support_nodup : p.support.Nodup
#align simple_graph.walk.is_path SimpleGraph.Walk.IsPath
-- Porting note: used to use `extends to_trail : is_trail p` in structure
protected lemma IsPath.isTrail {p : Walk G u v}(h : IsPath p) : IsTrail p := h.toIsTrail
#align simple_graph.walk.is_path.to_trail SimpleGraph.Walk.IsPath.isTrail
/-- A *circuit* at `u : V` is a nonempty trail beginning and ending at `u`. -/
@[mk_iff isCircuit_def]
structure IsCircuit {u : V} (p : G.Walk u u) extends IsTrail p : Prop where
ne_nil : p ≠ nil
#align simple_graph.walk.is_circuit SimpleGraph.Walk.IsCircuit
#align simple_graph.walk.is_circuit_def SimpleGraph.Walk.isCircuit_def
-- Porting note: used to use `extends to_trail : is_trail p` in structure
protected lemma IsCircuit.isTrail {p : Walk G u u} (h : IsCircuit p) : IsTrail p := h.toIsTrail
#align simple_graph.walk.is_circuit.to_trail SimpleGraph.Walk.IsCircuit.isTrail
/-- A *cycle* at `u : V` is a circuit at `u` whose only repeating vertex
is `u` (which appears exactly twice). -/
structure IsCycle {u : V} (p : G.Walk u u) extends IsCircuit p : Prop where
support_nodup : p.support.tail.Nodup
#align simple_graph.walk.is_cycle SimpleGraph.Walk.IsCycle
-- Porting note: used to use `extends to_circuit : is_circuit p` in structure
protected lemma IsCycle.isCircuit {p : Walk G u u} (h : IsCycle p) : IsCircuit p := h.toIsCircuit
#align simple_graph.walk.is_cycle.to_circuit SimpleGraph.Walk.IsCycle.isCircuit
@[simp]
theorem isTrail_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).IsTrail ↔ p.IsTrail := by
subst_vars
rfl
#align simple_graph.walk.is_trail_copy SimpleGraph.Walk.isTrail_copy
theorem IsPath.mk' {u v : V} {p : G.Walk u v} (h : p.support.Nodup) : p.IsPath :=
⟨⟨edges_nodup_of_support_nodup h⟩, h⟩
#align simple_graph.walk.is_path.mk' SimpleGraph.Walk.IsPath.mk'
theorem isPath_def {u v : V} (p : G.Walk u v) : p.IsPath ↔ p.support.Nodup :=
⟨IsPath.support_nodup, IsPath.mk'⟩
#align simple_graph.walk.is_path_def SimpleGraph.Walk.isPath_def
@[simp]
theorem isPath_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).IsPath ↔ p.IsPath := by
subst_vars
rfl
#align simple_graph.walk.is_path_copy SimpleGraph.Walk.isPath_copy
@[simp]
theorem isCircuit_copy {u u'} (p : G.Walk u u) (hu : u = u') :
(p.copy hu hu).IsCircuit ↔ p.IsCircuit := by
subst_vars
rfl
#align simple_graph.walk.is_circuit_copy SimpleGraph.Walk.isCircuit_copy
lemma IsCircuit.not_nil {p : G.Walk v v} (hp : IsCircuit p) : ¬ p.Nil := (hp.ne_nil ·.eq_nil)
theorem isCycle_def {u : V} (p : G.Walk u u) :
p.IsCycle ↔ p.IsTrail ∧ p ≠ nil ∧ p.support.tail.Nodup :=
Iff.intro (fun h => ⟨h.1.1, h.1.2, h.2⟩) fun h => ⟨⟨h.1, h.2.1⟩, h.2.2⟩
#align simple_graph.walk.is_cycle_def SimpleGraph.Walk.isCycle_def
@[simp]
theorem isCycle_copy {u u'} (p : G.Walk u u) (hu : u = u') :
(p.copy hu hu).IsCycle ↔ p.IsCycle := by
subst_vars
rfl
#align simple_graph.walk.is_cycle_copy SimpleGraph.Walk.isCycle_copy
lemma IsCycle.not_nil {p : G.Walk v v} (hp : IsCycle p) : ¬ p.Nil := (hp.ne_nil ·.eq_nil)
@[simp]
theorem IsTrail.nil {u : V} : (nil : G.Walk u u).IsTrail :=
⟨by simp [edges]⟩
#align simple_graph.walk.is_trail.nil SimpleGraph.Walk.IsTrail.nil
theorem IsTrail.of_cons {u v w : V} {h : G.Adj u v} {p : G.Walk v w} :
(cons h p).IsTrail → p.IsTrail := by simp [isTrail_def]
#align simple_graph.walk.is_trail.of_cons SimpleGraph.Walk.IsTrail.of_cons
@[simp]
theorem cons_isTrail_iff {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).IsTrail ↔ p.IsTrail ∧ s(u, v) ∉ p.edges := by simp [isTrail_def, and_comm]
#align simple_graph.walk.cons_is_trail_iff SimpleGraph.Walk.cons_isTrail_iff
theorem IsTrail.reverse {u v : V} (p : G.Walk u v) (h : p.IsTrail) : p.reverse.IsTrail := by
simpa [isTrail_def] using h
#align simple_graph.walk.is_trail.reverse SimpleGraph.Walk.IsTrail.reverse
@[simp]
theorem reverse_isTrail_iff {u v : V} (p : G.Walk u v) : p.reverse.IsTrail ↔ p.IsTrail := by
constructor <;>
· intro h
convert h.reverse _
try rw [reverse_reverse]
#align simple_graph.walk.reverse_is_trail_iff SimpleGraph.Walk.reverse_isTrail_iff
theorem IsTrail.of_append_left {u v w : V} {p : G.Walk u v} {q : G.Walk v w}
(h : (p.append q).IsTrail) : p.IsTrail := by
rw [isTrail_def, edges_append, List.nodup_append] at h
exact ⟨h.1⟩
#align simple_graph.walk.is_trail.of_append_left SimpleGraph.Walk.IsTrail.of_append_left
theorem IsTrail.of_append_right {u v w : V} {p : G.Walk u v} {q : G.Walk v w}
(h : (p.append q).IsTrail) : q.IsTrail := by
rw [isTrail_def, edges_append, List.nodup_append] at h
exact ⟨h.2.1⟩
#align simple_graph.walk.is_trail.of_append_right SimpleGraph.Walk.IsTrail.of_append_right
theorem IsTrail.count_edges_le_one [DecidableEq V] {u v : V} {p : G.Walk u v} (h : p.IsTrail)
(e : Sym2 V) : p.edges.count e ≤ 1 :=
List.nodup_iff_count_le_one.mp h.edges_nodup e
#align simple_graph.walk.is_trail.count_edges_le_one SimpleGraph.Walk.IsTrail.count_edges_le_one
theorem IsTrail.count_edges_eq_one [DecidableEq V] {u v : V} {p : G.Walk u v} (h : p.IsTrail)
{e : Sym2 V} (he : e ∈ p.edges) : p.edges.count e = 1 :=
List.count_eq_one_of_mem h.edges_nodup he
#align simple_graph.walk.is_trail.count_edges_eq_one SimpleGraph.Walk.IsTrail.count_edges_eq_one
theorem IsPath.nil {u : V} : (nil : G.Walk u u).IsPath := by constructor <;> simp
#align simple_graph.walk.is_path.nil SimpleGraph.Walk.IsPath.nil
theorem IsPath.of_cons {u v w : V} {h : G.Adj u v} {p : G.Walk v w} :
(cons h p).IsPath → p.IsPath := by simp [isPath_def]
#align simple_graph.walk.is_path.of_cons SimpleGraph.Walk.IsPath.of_cons
@[simp]
theorem cons_isPath_iff {u v w : V} (h : G.Adj u v) (p : G.Walk v w) :
(cons h p).IsPath ↔ p.IsPath ∧ u ∉ p.support := by
constructor <;> simp (config := { contextual := true }) [isPath_def]
#align simple_graph.walk.cons_is_path_iff SimpleGraph.Walk.cons_isPath_iff
protected lemma IsPath.cons {p : Walk G v w} (hp : p.IsPath) (hu : u ∉ p.support) {h : G.Adj u v} :
(cons h p).IsPath :=
(cons_isPath_iff _ _).2 ⟨hp, hu⟩
@[simp]
theorem isPath_iff_eq_nil {u : V} (p : G.Walk u u) : p.IsPath ↔ p = nil := by
cases p <;> simp [IsPath.nil]
#align simple_graph.walk.is_path_iff_eq_nil SimpleGraph.Walk.isPath_iff_eq_nil
theorem IsPath.reverse {u v : V} {p : G.Walk u v} (h : p.IsPath) : p.reverse.IsPath := by
simpa [isPath_def] using h
#align simple_graph.walk.is_path.reverse SimpleGraph.Walk.IsPath.reverse
@[simp]
theorem isPath_reverse_iff {u v : V} (p : G.Walk u v) : p.reverse.IsPath ↔ p.IsPath := by
constructor <;> intro h <;> convert h.reverse; simp
#align simple_graph.walk.is_path_reverse_iff SimpleGraph.Walk.isPath_reverse_iff
theorem IsPath.of_append_left {u v w : V} {p : G.Walk u v} {q : G.Walk v w} :
(p.append q).IsPath → p.IsPath := by
simp only [isPath_def, support_append]
exact List.Nodup.of_append_left
#align simple_graph.walk.is_path.of_append_left SimpleGraph.Walk.IsPath.of_append_left
theorem IsPath.of_append_right {u v w : V} {p : G.Walk u v} {q : G.Walk v w}
(h : (p.append q).IsPath) : q.IsPath := by
rw [← isPath_reverse_iff] at h ⊢
rw [reverse_append] at h
apply h.of_append_left
#align simple_graph.walk.is_path.of_append_right SimpleGraph.Walk.IsPath.of_append_right
@[simp]
theorem IsCycle.not_of_nil {u : V} : ¬(nil : G.Walk u u).IsCycle := fun h => h.ne_nil rfl
#align simple_graph.walk.is_cycle.not_of_nil SimpleGraph.Walk.IsCycle.not_of_nil
lemma IsCycle.ne_bot : ∀ {p : G.Walk u u}, p.IsCycle → G ≠ ⊥
| nil, hp => by cases hp.ne_nil rfl
| cons h _, hp => by rintro rfl; exact h
lemma IsCycle.three_le_length {v : V} {p : G.Walk v v} (hp : p.IsCycle) : 3 ≤ p.length := by
have ⟨⟨hp, hp'⟩, _⟩ := hp
match p with
| .nil => simp at hp'
| .cons h .nil => simp at h
| .cons _ (.cons _ .nil) => simp at hp
| .cons _ (.cons _ (.cons _ _)) => simp_rw [SimpleGraph.Walk.length_cons]; omega
theorem cons_isCycle_iff {u v : V} (p : G.Walk v u) (h : G.Adj u v) :
(Walk.cons h p).IsCycle ↔ p.IsPath ∧ ¬s(u, v) ∈ p.edges := by
simp only [Walk.isCycle_def, Walk.isPath_def, Walk.isTrail_def, edges_cons, List.nodup_cons,
support_cons, List.tail_cons]
have : p.support.Nodup → p.edges.Nodup := edges_nodup_of_support_nodup
tauto
#align simple_graph.walk.cons_is_cycle_iff SimpleGraph.Walk.cons_isCycle_iff
lemma IsPath.tail {p : G.Walk u v} (hp : p.IsPath) (hp' : ¬ p.Nil) : (p.tail hp').IsPath := by
rw [Walk.isPath_def] at hp ⊢
rw [← cons_support_tail _ hp', List.nodup_cons] at hp
exact hp.2
/-! ### About paths -/
instance [DecidableEq V] {u v : V} (p : G.Walk u v) : Decidable p.IsPath := by
rw [isPath_def]
infer_instance
theorem IsPath.length_lt [Fintype V] {u v : V} {p : G.Walk u v} (hp : p.IsPath) :
p.length < Fintype.card V := by
rw [Nat.lt_iff_add_one_le, ← length_support]
exact hp.support_nodup.length_le_card
#align simple_graph.walk.is_path.length_lt SimpleGraph.Walk.IsPath.length_lt
/-! ### Walk decompositions -/
section WalkDecomp
variable [DecidableEq V]
/-- Given a vertex in the support of a path, give the path up until (and including) that vertex. -/
def takeUntil {v w : V} : ∀ (p : G.Walk v w) (u : V), u ∈ p.support → G.Walk v u
| nil, u, h => by rw [mem_support_nil_iff.mp h]
| cons r p, u, h =>
if hx : v = u then
by subst u; exact Walk.nil
else
cons r (takeUntil p u <| by
cases h
· exact (hx rfl).elim
· assumption)
#align simple_graph.walk.take_until SimpleGraph.Walk.takeUntil
/-- Given a vertex in the support of a path, give the path from (and including) that vertex to
the end. In other words, drop vertices from the front of a path until (and not including)
that vertex. -/
def dropUntil {v w : V} : ∀ (p : G.Walk v w) (u : V), u ∈ p.support → G.Walk u w
| nil, u, h => by rw [mem_support_nil_iff.mp h]
| cons r p, u, h =>
if hx : v = u then by
subst u
exact cons r p
else dropUntil p u <| by
cases h
· exact (hx rfl).elim
· assumption
#align simple_graph.walk.drop_until SimpleGraph.Walk.dropUntil
/-- The `takeUntil` and `dropUntil` functions split a walk into two pieces.
The lemma `SimpleGraph.Walk.count_support_takeUntil_eq_one` specifies where this split occurs. -/
@[simp]
theorem take_spec {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).append (p.dropUntil u h) = p := by
induction p
· rw [mem_support_nil_iff] at h
subst u
rfl
· cases h
· simp!
· simp! only
split_ifs with h' <;> subst_vars <;> simp [*]
#align simple_graph.walk.take_spec SimpleGraph.Walk.take_spec
theorem mem_support_iff_exists_append {V : Type u} {G : SimpleGraph V} {u v w : V}
{p : G.Walk u v} : w ∈ p.support ↔ ∃ (q : G.Walk u w) (r : G.Walk w v), p = q.append r := by
classical
constructor
· exact fun h => ⟨_, _, (p.take_spec h).symm⟩
· rintro ⟨q, r, rfl⟩
simp only [mem_support_append_iff, end_mem_support, start_mem_support, or_self_iff]
#align simple_graph.walk.mem_support_iff_exists_append SimpleGraph.Walk.mem_support_iff_exists_append
@[simp]
theorem count_support_takeUntil_eq_one {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).support.count u = 1 := by
induction p
· rw [mem_support_nil_iff] at h
subst u
simp!
· cases h
· simp!
· simp! only
split_ifs with h' <;> rw [eq_comm] at h' <;> subst_vars <;> simp! [*, List.count_cons]
#align simple_graph.walk.count_support_take_until_eq_one SimpleGraph.Walk.count_support_takeUntil_eq_one
theorem count_edges_takeUntil_le_one {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) (x : V) :
(p.takeUntil u h).edges.count s(u, x) ≤ 1 := by
induction' p with u' u' v' w' ha p' ih
· rw [mem_support_nil_iff] at h
subst u
simp!
· cases h
· simp!
· simp! only
split_ifs with h'
· subst h'
simp
· rw [edges_cons, List.count_cons]
split_ifs with h''
· rw [Sym2.eq_iff] at h''
obtain ⟨rfl, rfl⟩ | ⟨rfl, rfl⟩ := h''
· exact (h' rfl).elim
· cases p' <;> simp!
· apply ih
#align simple_graph.walk.count_edges_take_until_le_one SimpleGraph.Walk.count_edges_takeUntil_le_one
@[simp]
theorem takeUntil_copy {u v w v' w'} (p : G.Walk v w) (hv : v = v') (hw : w = w')
(h : u ∈ (p.copy hv hw).support) :
(p.copy hv hw).takeUntil u h = (p.takeUntil u (by subst_vars; exact h)).copy hv rfl := by
subst_vars
rfl
#align simple_graph.walk.take_until_copy SimpleGraph.Walk.takeUntil_copy
@[simp]
theorem dropUntil_copy {u v w v' w'} (p : G.Walk v w) (hv : v = v') (hw : w = w')
(h : u ∈ (p.copy hv hw).support) :
(p.copy hv hw).dropUntil u h = (p.dropUntil u (by subst_vars; exact h)).copy rfl hw := by
subst_vars
rfl
#align simple_graph.walk.drop_until_copy SimpleGraph.Walk.dropUntil_copy
theorem support_takeUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).support ⊆ p.support := fun x hx => by
rw [← take_spec p h, mem_support_append_iff]
exact Or.inl hx
#align simple_graph.walk.support_take_until_subset SimpleGraph.Walk.support_takeUntil_subset
theorem support_dropUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.dropUntil u h).support ⊆ p.support := fun x hx => by
rw [← take_spec p h, mem_support_append_iff]
exact Or.inr hx
#align simple_graph.walk.support_drop_until_subset SimpleGraph.Walk.support_dropUntil_subset
theorem darts_takeUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).darts ⊆ p.darts := fun x hx => by
rw [← take_spec p h, darts_append, List.mem_append]
exact Or.inl hx
#align simple_graph.walk.darts_take_until_subset SimpleGraph.Walk.darts_takeUntil_subset
theorem darts_dropUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.dropUntil u h).darts ⊆ p.darts := fun x hx => by
rw [← take_spec p h, darts_append, List.mem_append]
exact Or.inr hx
#align simple_graph.walk.darts_drop_until_subset SimpleGraph.Walk.darts_dropUntil_subset
theorem edges_takeUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).edges ⊆ p.edges :=
List.map_subset _ (p.darts_takeUntil_subset h)
#align simple_graph.walk.edges_take_until_subset SimpleGraph.Walk.edges_takeUntil_subset
theorem edges_dropUntil_subset {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.dropUntil u h).edges ⊆ p.edges :=
List.map_subset _ (p.darts_dropUntil_subset h)
#align simple_graph.walk.edges_drop_until_subset SimpleGraph.Walk.edges_dropUntil_subset
theorem length_takeUntil_le {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.takeUntil u h).length ≤ p.length := by
have := congr_arg Walk.length (p.take_spec h)
rw [length_append] at this
exact Nat.le.intro this
#align simple_graph.walk.length_take_until_le SimpleGraph.Walk.length_takeUntil_le
theorem length_dropUntil_le {u v w : V} (p : G.Walk v w) (h : u ∈ p.support) :
(p.dropUntil u h).length ≤ p.length := by
have := congr_arg Walk.length (p.take_spec h)
rw [length_append, add_comm] at this
exact Nat.le.intro this
#align simple_graph.walk.length_drop_until_le SimpleGraph.Walk.length_dropUntil_le
protected theorem IsTrail.takeUntil {u v w : V} {p : G.Walk v w} (hc : p.IsTrail)
(h : u ∈ p.support) : (p.takeUntil u h).IsTrail :=
IsTrail.of_append_left (by rwa [← take_spec _ h] at hc)
#align simple_graph.walk.is_trail.take_until SimpleGraph.Walk.IsTrail.takeUntil
protected theorem IsTrail.dropUntil {u v w : V} {p : G.Walk v w} (hc : p.IsTrail)
(h : u ∈ p.support) : (p.dropUntil u h).IsTrail :=
IsTrail.of_append_right (by rwa [← take_spec _ h] at hc)
#align simple_graph.walk.is_trail.drop_until SimpleGraph.Walk.IsTrail.dropUntil
protected theorem IsPath.takeUntil {u v w : V} {p : G.Walk v w} (hc : p.IsPath)
(h : u ∈ p.support) : (p.takeUntil u h).IsPath :=
IsPath.of_append_left (by rwa [← take_spec _ h] at hc)
#align simple_graph.walk.is_path.take_until SimpleGraph.Walk.IsPath.takeUntil
-- Porting note: p was previously accidentally an explicit argument
protected theorem IsPath.dropUntil {u v w : V} {p : G.Walk v w} (hc : p.IsPath)
(h : u ∈ p.support) : (p.dropUntil u h).IsPath :=
IsPath.of_append_right (by rwa [← take_spec _ h] at hc)
#align simple_graph.walk.is_path.drop_until SimpleGraph.Walk.IsPath.dropUntil
/-- Rotate a loop walk such that it is centered at the given vertex. -/
def rotate {u v : V} (c : G.Walk v v) (h : u ∈ c.support) : G.Walk u u :=
(c.dropUntil u h).append (c.takeUntil u h)
#align simple_graph.walk.rotate SimpleGraph.Walk.rotate
@[simp]
theorem support_rotate {u v : V} (c : G.Walk v v) (h : u ∈ c.support) :
(c.rotate h).support.tail ~r c.support.tail := by
simp only [rotate, tail_support_append]
apply List.IsRotated.trans List.isRotated_append
rw [← tail_support_append, take_spec]
#align simple_graph.walk.support_rotate SimpleGraph.Walk.support_rotate
theorem rotate_darts {u v : V} (c : G.Walk v v) (h : u ∈ c.support) :
(c.rotate h).darts ~r c.darts := by
simp only [rotate, darts_append]
apply List.IsRotated.trans List.isRotated_append
rw [← darts_append, take_spec]
#align simple_graph.walk.rotate_darts SimpleGraph.Walk.rotate_darts
theorem rotate_edges {u v : V} (c : G.Walk v v) (h : u ∈ c.support) :
(c.rotate h).edges ~r c.edges :=
(rotate_darts c h).map _
#align simple_graph.walk.rotate_edges SimpleGraph.Walk.rotate_edges
protected theorem IsTrail.rotate {u v : V} {c : G.Walk v v} (hc : c.IsTrail) (h : u ∈ c.support) :
(c.rotate h).IsTrail := by
rw [isTrail_def, (c.rotate_edges h).perm.nodup_iff]
exact hc.edges_nodup
#align simple_graph.walk.is_trail.rotate SimpleGraph.Walk.IsTrail.rotate
protected theorem IsCircuit.rotate {u v : V} {c : G.Walk v v} (hc : c.IsCircuit)
(h : u ∈ c.support) : (c.rotate h).IsCircuit := by
refine ⟨hc.isTrail.rotate _, ?_⟩
cases c
· exact (hc.ne_nil rfl).elim
· intro hn
have hn' := congr_arg length hn
rw [rotate, length_append, add_comm, ← length_append, take_spec] at hn'
simp at hn'
#align simple_graph.walk.is_circuit.rotate SimpleGraph.Walk.IsCircuit.rotate
protected theorem IsCycle.rotate {u v : V} {c : G.Walk v v} (hc : c.IsCycle) (h : u ∈ c.support) :
(c.rotate h).IsCycle := by
refine ⟨hc.isCircuit.rotate _, ?_⟩
rw [List.IsRotated.nodup_iff (support_rotate _ _)]
exact hc.support_nodup
#align simple_graph.walk.is_cycle.rotate SimpleGraph.Walk.IsCycle.rotate
end WalkDecomp
/-- Given a set `S` and a walk `w` from `u` to `v` such that `u ∈ S` but `v ∉ S`,
there exists a dart in the walk whose start is in `S` but whose end is not. -/
theorem exists_boundary_dart {u v : V} (p : G.Walk u v) (S : Set V) (uS : u ∈ S) (vS : v ∉ S) :
∃ d : G.Dart, d ∈ p.darts ∧ d.fst ∈ S ∧ d.snd ∉ S := by
induction' p with _ x y w a p' ih
· cases vS uS
· by_cases h : y ∈ S
· obtain ⟨d, hd, hcd⟩ := ih h vS
exact ⟨d, List.Mem.tail _ hd, hcd⟩
· exact ⟨⟨(x, y), a⟩, List.Mem.head _, uS, h⟩
#align simple_graph.walk.exists_boundary_dart SimpleGraph.Walk.exists_boundary_dart
end Walk
/-! ### Type of paths -/
/-- The type for paths between two vertices. -/
abbrev Path (u v : V) := { p : G.Walk u v // p.IsPath }
#align simple_graph.path SimpleGraph.Path
namespace Path
variable {G G'}
@[simp]
protected theorem isPath {u v : V} (p : G.Path u v) : (p : G.Walk u v).IsPath := p.property
#align simple_graph.path.is_path SimpleGraph.Path.isPath
@[simp]
protected theorem isTrail {u v : V} (p : G.Path u v) : (p : G.Walk u v).IsTrail :=
p.property.isTrail
#align simple_graph.path.is_trail SimpleGraph.Path.isTrail
/-- The length-0 path at a vertex. -/
@[refl, simps]
protected def nil {u : V} : G.Path u u :=
⟨Walk.nil, Walk.IsPath.nil⟩
#align simple_graph.path.nil SimpleGraph.Path.nil
/-- The length-1 path between a pair of adjacent vertices. -/
@[simps]
def singleton {u v : V} (h : G.Adj u v) : G.Path u v :=
⟨Walk.cons h Walk.nil, by simp [h.ne]⟩
#align simple_graph.path.singleton SimpleGraph.Path.singleton
theorem mk'_mem_edges_singleton {u v : V} (h : G.Adj u v) :
s(u, v) ∈ (singleton h : G.Walk u v).edges := by simp [singleton]
#align simple_graph.path.mk_mem_edges_singleton SimpleGraph.Path.mk'_mem_edges_singleton
/-- The reverse of a path is another path. See also `SimpleGraph.Walk.reverse`. -/
@[symm, simps]
def reverse {u v : V} (p : G.Path u v) : G.Path v u :=
⟨Walk.reverse p, p.property.reverse⟩
#align simple_graph.path.reverse SimpleGraph.Path.reverse
theorem count_support_eq_one [DecidableEq V] {u v w : V} {p : G.Path u v}
(hw : w ∈ (p : G.Walk u v).support) : (p : G.Walk u v).support.count w = 1 :=
List.count_eq_one_of_mem p.property.support_nodup hw
#align simple_graph.path.count_support_eq_one SimpleGraph.Path.count_support_eq_one
theorem count_edges_eq_one [DecidableEq V] {u v : V} {p : G.Path u v} (e : Sym2 V)
(hw : e ∈ (p : G.Walk u v).edges) : (p : G.Walk u v).edges.count e = 1 :=
List.count_eq_one_of_mem p.property.isTrail.edges_nodup hw
#align simple_graph.path.count_edges_eq_one SimpleGraph.Path.count_edges_eq_one
@[simp]
theorem nodup_support {u v : V} (p : G.Path u v) : (p : G.Walk u v).support.Nodup :=
(Walk.isPath_def _).mp p.property
#align simple_graph.path.nodup_support SimpleGraph.Path.nodup_support
theorem loop_eq {v : V} (p : G.Path v v) : p = Path.nil := by
obtain ⟨_ | _, h⟩ := p
· rfl
· simp at h
#align simple_graph.path.loop_eq SimpleGraph.Path.loop_eq
theorem not_mem_edges_of_loop {v : V} {e : Sym2 V} {p : G.Path v v} :
¬e ∈ (p : G.Walk v v).edges := by simp [p.loop_eq]
#align simple_graph.path.not_mem_edges_of_loop SimpleGraph.Path.not_mem_edges_of_loop
theorem cons_isCycle {u v : V} (p : G.Path v u) (h : G.Adj u v)
(he : ¬s(u, v) ∈ (p : G.Walk v u).edges) : (Walk.cons h ↑p).IsCycle := by
simp [Walk.isCycle_def, Walk.cons_isTrail_iff, he]
#align simple_graph.path.cons_is_cycle SimpleGraph.Path.cons_isCycle
end Path
/-! ### Walks to paths -/
namespace Walk
variable {G} [DecidableEq V]
/-- Given a walk, produces a walk from it by bypassing subwalks between repeated vertices.
The result is a path, as shown in `SimpleGraph.Walk.bypass_isPath`.
This is packaged up in `SimpleGraph.Walk.toPath`. -/
def bypass {u v : V} : G.Walk u v → G.Walk u v
| nil => nil
| cons ha p =>
let p' := p.bypass
if hs : u ∈ p'.support then
p'.dropUntil u hs
else
cons ha p'
#align simple_graph.walk.bypass SimpleGraph.Walk.bypass
@[simp]
theorem bypass_copy {u v u' v'} (p : G.Walk u v) (hu : u = u') (hv : v = v') :
(p.copy hu hv).bypass = p.bypass.copy hu hv := by
subst_vars
rfl
#align simple_graph.walk.bypass_copy SimpleGraph.Walk.bypass_copy
theorem bypass_isPath {u v : V} (p : G.Walk u v) : p.bypass.IsPath := by
induction p with
| nil => simp!
| cons _ p' ih =>
simp only [bypass]
split_ifs with hs
· exact ih.dropUntil hs
· simp [*, cons_isPath_iff]
#align simple_graph.walk.bypass_is_path SimpleGraph.Walk.bypass_isPath
theorem length_bypass_le {u v : V} (p : G.Walk u v) : p.bypass.length ≤ p.length := by
induction p with
| nil => rfl
| cons _ _ ih =>
simp only [bypass]
split_ifs
· trans
· apply length_dropUntil_le
rw [length_cons]
omega
· rw [length_cons, length_cons]
exact Nat.add_le_add_right ih 1
#align simple_graph.walk.length_bypass_le SimpleGraph.Walk.length_bypass_le
lemma bypass_eq_self_of_length_le {u v : V} (p : G.Walk u v) (h : p.length ≤ p.bypass.length) :
p.bypass = p := by
induction p with
| nil => rfl
| cons h p ih =>
simp only [Walk.bypass]
split_ifs with hb
· exfalso
simp only [hb, Walk.bypass, Walk.length_cons, dif_pos] at h
apply Nat.not_succ_le_self p.length
calc p.length + 1
_ ≤ (p.bypass.dropUntil _ _).length := h
_ ≤ p.bypass.length := Walk.length_dropUntil_le p.bypass hb
_ ≤ p.length := Walk.length_bypass_le _
· simp only [hb, Walk.bypass, Walk.length_cons, not_false_iff, dif_neg,
Nat.add_le_add_iff_right] at h
rw [ih h]
/-- Given a walk, produces a path with the same endpoints using `SimpleGraph.Walk.bypass`. -/
def toPath {u v : V} (p : G.Walk u v) : G.Path u v :=
⟨p.bypass, p.bypass_isPath⟩
#align simple_graph.walk.to_path SimpleGraph.Walk.toPath
theorem support_bypass_subset {u v : V} (p : G.Walk u v) : p.bypass.support ⊆ p.support := by
induction p with
| nil => simp!
| cons _ _ ih =>
simp! only
split_ifs
· apply List.Subset.trans (support_dropUntil_subset _ _)
apply List.subset_cons_of_subset
assumption
· rw [support_cons]
apply List.cons_subset_cons
assumption
#align simple_graph.walk.support_bypass_subset SimpleGraph.Walk.support_bypass_subset
theorem support_toPath_subset {u v : V} (p : G.Walk u v) :
(p.toPath : G.Walk u v).support ⊆ p.support :=
support_bypass_subset _
#align simple_graph.walk.support_to_path_subset SimpleGraph.Walk.support_toPath_subset
theorem darts_bypass_subset {u v : V} (p : G.Walk u v) : p.bypass.darts ⊆ p.darts := by
induction p with
| nil => simp!
| cons _ _ ih =>
simp! only
split_ifs
· apply List.Subset.trans (darts_dropUntil_subset _ _)
apply List.subset_cons_of_subset _ ih
· rw [darts_cons]
exact List.cons_subset_cons _ ih
#align simple_graph.walk.darts_bypass_subset SimpleGraph.Walk.darts_bypass_subset
theorem edges_bypass_subset {u v : V} (p : G.Walk u v) : p.bypass.edges ⊆ p.edges :=
List.map_subset _ p.darts_bypass_subset
#align simple_graph.walk.edges_bypass_subset SimpleGraph.Walk.edges_bypass_subset
theorem darts_toPath_subset {u v : V} (p : G.Walk u v) : (p.toPath : G.Walk u v).darts ⊆ p.darts :=
darts_bypass_subset _
#align simple_graph.walk.darts_to_path_subset SimpleGraph.Walk.darts_toPath_subset
theorem edges_toPath_subset {u v : V} (p : G.Walk u v) : (p.toPath : G.Walk u v).edges ⊆ p.edges :=
edges_bypass_subset _
#align simple_graph.walk.edges_to_path_subset SimpleGraph.Walk.edges_toPath_subset
end Walk
/-! ### Mapping paths -/
namespace Walk
variable {G G' G''}
/-- Given a graph homomorphism, map walks to walks. -/
protected def map (f : G →g G') {u v : V} : G.Walk u v → G'.Walk (f u) (f v)
| nil => nil
| cons h p => cons (f.map_adj h) (p.map f)
#align simple_graph.walk.map SimpleGraph.Walk.map
variable (f : G →g G') (f' : G' →g G'') {u v u' v' : V} (p : G.Walk u v)
@[simp]
theorem map_nil : (nil : G.Walk u u).map f = nil := rfl
#align simple_graph.walk.map_nil SimpleGraph.Walk.map_nil
@[simp]
theorem map_cons {w : V} (h : G.Adj w u) : (cons h p).map f = cons (f.map_adj h) (p.map f) := rfl
#align simple_graph.walk.map_cons SimpleGraph.Walk.map_cons
@[simp]
theorem map_copy (hu : u = u') (hv : v = v') :
(p.copy hu hv).map f = (p.map f).copy (hu ▸ rfl) (hv ▸ rfl) := by
subst_vars
rfl
#align simple_graph.walk.map_copy SimpleGraph.Walk.map_copy
@[simp]
theorem map_id (p : G.Walk u v) : p.map Hom.id = p := by
induction p with
| nil => rfl
| cons _ p' ih => simp [ih p']
#align simple_graph.walk.map_id SimpleGraph.Walk.map_id
@[simp]
theorem map_map : (p.map f).map f' = p.map (f'.comp f) := by
induction p with
| nil => rfl
| cons _ _ ih => simp [ih]
#align simple_graph.walk.map_map SimpleGraph.Walk.map_map
/-- Unlike categories, for graphs vertex equality is an important notion, so needing to be able to
work with equality of graph homomorphisms is a necessary evil. -/
theorem map_eq_of_eq {f : G →g G'} (f' : G →g G') (h : f = f') :
p.map f = (p.map f').copy (h ▸ rfl) (h ▸ rfl) := by
subst_vars
rfl
#align simple_graph.walk.map_eq_of_eq SimpleGraph.Walk.map_eq_of_eq
@[simp]
theorem map_eq_nil_iff {p : G.Walk u u} : p.map f = nil ↔ p = nil := by cases p <;> simp
#align simple_graph.walk.map_eq_nil_iff SimpleGraph.Walk.map_eq_nil_iff
@[simp]
theorem length_map : (p.map f).length = p.length := by induction p <;> simp [*]
#align simple_graph.walk.length_map SimpleGraph.Walk.length_map
theorem map_append {u v w : V} (p : G.Walk u v) (q : G.Walk v w) :
(p.append q).map f = (p.map f).append (q.map f) := by induction p <;> simp [*]
#align simple_graph.walk.map_append SimpleGraph.Walk.map_append
@[simp]
theorem reverse_map : (p.map f).reverse = p.reverse.map f := by induction p <;> simp [map_append, *]
#align simple_graph.walk.reverse_map SimpleGraph.Walk.reverse_map
@[simp]
theorem support_map : (p.map f).support = p.support.map f := by induction p <;> simp [*]
#align simple_graph.walk.support_map SimpleGraph.Walk.support_map
@[simp]
theorem darts_map : (p.map f).darts = p.darts.map f.mapDart := by induction p <;> simp [*]
#align simple_graph.walk.darts_map SimpleGraph.Walk.darts_map
@[simp]
theorem edges_map : (p.map f).edges = p.edges.map (Sym2.map f) := by
induction p with
| nil => rfl
| cons _ _ ih =>
simp only [Walk.map_cons, edges_cons, List.map_cons, Sym2.map_pair_eq, List.cons.injEq,
true_and, ih]
#align simple_graph.walk.edges_map SimpleGraph.Walk.edges_map
variable {p f}
theorem map_isPath_of_injective (hinj : Function.Injective f) (hp : p.IsPath) :
(p.map f).IsPath := by
induction p with
| nil => simp
| cons _ _ ih =>
rw [Walk.cons_isPath_iff] at hp
simp only [map_cons, cons_isPath_iff, ih hp.1, support_map, List.mem_map, not_exists, not_and,
true_and]
intro x hx hf
cases hinj hf
exact hp.2 hx
#align simple_graph.walk.map_is_path_of_injective SimpleGraph.Walk.map_isPath_of_injective
protected theorem IsPath.of_map {f : G →g G'} (hp : (p.map f).IsPath) : p.IsPath := by
induction p with
| nil => simp
| cons _ _ ih =>
rw [map_cons, Walk.cons_isPath_iff, support_map] at hp
rw [Walk.cons_isPath_iff]
cases' hp with hp1 hp2
refine ⟨ih hp1, ?_⟩
contrapose! hp2
exact List.mem_map_of_mem f hp2
#align simple_graph.walk.is_path.of_map SimpleGraph.Walk.IsPath.of_map
theorem map_isPath_iff_of_injective (hinj : Function.Injective f) : (p.map f).IsPath ↔ p.IsPath :=
⟨IsPath.of_map, map_isPath_of_injective hinj⟩
#align simple_graph.walk.map_is_path_iff_of_injective SimpleGraph.Walk.map_isPath_iff_of_injective
theorem map_isTrail_iff_of_injective (hinj : Function.Injective f) :
(p.map f).IsTrail ↔ p.IsTrail := by
induction p with
| nil => simp
| cons _ _ ih =>
rw [map_cons, cons_isTrail_iff, ih, cons_isTrail_iff]
apply and_congr_right'
rw [← Sym2.map_pair_eq, edges_map, ← List.mem_map_of_injective (Sym2.map.injective hinj)]
#align simple_graph.walk.map_is_trail_iff_of_injective SimpleGraph.Walk.map_isTrail_iff_of_injective
alias ⟨_, map_isTrail_of_injective⟩ := map_isTrail_iff_of_injective
#align simple_graph.walk.map_is_trail_of_injective SimpleGraph.Walk.map_isTrail_of_injective
theorem map_isCycle_iff_of_injective {p : G.Walk u u} (hinj : Function.Injective f) :
(p.map f).IsCycle ↔ p.IsCycle := by
rw [isCycle_def, isCycle_def, map_isTrail_iff_of_injective hinj, Ne, map_eq_nil_iff,
support_map, ← List.map_tail, List.nodup_map_iff hinj]
#align simple_graph.walk.map_is_cycle_iff_of_injective SimpleGraph.Walk.map_isCycle_iff_of_injective
alias ⟨_, IsCycle.map⟩ := map_isCycle_iff_of_injective
#align simple_graph.walk.map_is_cycle_of_injective SimpleGraph.Walk.IsCycle.map
variable (p f)
theorem map_injective_of_injective {f : G →g G'} (hinj : Function.Injective f) (u v : V) :
Function.Injective (Walk.map f : G.Walk u v → G'.Walk (f u) (f v)) := by
intro p p' h
induction p with
| nil =>
cases p'
· rfl
· simp at h
| cons _ _ ih =>
cases p' with
| nil => simp at h
| cons _ _ =>
simp only [map_cons, cons.injEq] at h
cases hinj h.1
simp only [cons.injEq, heq_iff_eq, true_and_iff]
apply ih
simpa using h.2
#align simple_graph.walk.map_injective_of_injective SimpleGraph.Walk.map_injective_of_injective
/-- The specialization of `SimpleGraph.Walk.map` for mapping walks to supergraphs. -/
abbrev mapLe {G G' : SimpleGraph V} (h : G ≤ G') {u v : V} (p : G.Walk u v) : G'.Walk u v :=
p.map (Hom.mapSpanningSubgraphs h)
#align simple_graph.walk.map_le SimpleGraph.Walk.mapLe
@[simp]
theorem mapLe_isTrail {G G' : SimpleGraph V} (h : G ≤ G') {u v : V} {p : G.Walk u v} :
(p.mapLe h).IsTrail ↔ p.IsTrail :=
map_isTrail_iff_of_injective Function.injective_id
#align simple_graph.walk.map_le_is_trail SimpleGraph.Walk.mapLe_isTrail
alias ⟨IsTrail.of_mapLe, IsTrail.mapLe⟩ := mapLe_isTrail
#align simple_graph.walk.is_trail.of_map_le SimpleGraph.Walk.IsTrail.of_mapLe
#align simple_graph.walk.is_trail.map_le SimpleGraph.Walk.IsTrail.mapLe
@[simp]
theorem mapLe_isPath {G G' : SimpleGraph V} (h : G ≤ G') {u v : V} {p : G.Walk u v} :
(p.mapLe h).IsPath ↔ p.IsPath :=
map_isPath_iff_of_injective Function.injective_id
#align simple_graph.walk.map_le_is_path SimpleGraph.Walk.mapLe_isPath
alias ⟨IsPath.of_mapLe, IsPath.mapLe⟩ := mapLe_isPath
#align simple_graph.walk.is_path.of_map_le SimpleGraph.Walk.IsPath.of_mapLe
#align simple_graph.walk.is_path.map_le SimpleGraph.Walk.IsPath.mapLe
@[simp]
theorem mapLe_isCycle {G G' : SimpleGraph V} (h : G ≤ G') {u : V} {p : G.Walk u u} :
(p.mapLe h).IsCycle ↔ p.IsCycle :=
map_isCycle_iff_of_injective Function.injective_id
#align simple_graph.walk.map_le_is_cycle SimpleGraph.Walk.mapLe_isCycle
alias ⟨IsCycle.of_mapLe, IsCycle.mapLe⟩ := mapLe_isCycle
#align simple_graph.walk.is_cycle.of_map_le SimpleGraph.Walk.IsCycle.of_mapLe
#align simple_graph.walk.is_cycle.map_le SimpleGraph.Walk.IsCycle.mapLe
end Walk
namespace Path
variable {G G'}
/-- Given an injective graph homomorphism, map paths to paths. -/
@[simps]
protected def map (f : G →g G') (hinj : Function.Injective f) {u v : V} (p : G.Path u v) :
G'.Path (f u) (f v) :=
⟨Walk.map f p, Walk.map_isPath_of_injective hinj p.2⟩
#align simple_graph.path.map SimpleGraph.Path.map
theorem map_injective {f : G →g G'} (hinj : Function.Injective f) (u v : V) :
Function.Injective (Path.map f hinj : G.Path u v → G'.Path (f u) (f v)) := by
rintro ⟨p, hp⟩ ⟨p', hp'⟩ h
simp only [Path.map, Subtype.coe_mk, Subtype.mk.injEq] at h
simp [Walk.map_injective_of_injective hinj u v h]
#align simple_graph.path.map_injective SimpleGraph.Path.map_injective
/-- Given a graph embedding, map paths to paths. -/
@[simps!]
protected def mapEmbedding (f : G ↪g G') {u v : V} (p : G.Path u v) : G'.Path (f u) (f v) :=
Path.map f.toHom f.injective p
#align simple_graph.path.map_embedding SimpleGraph.Path.mapEmbedding
theorem mapEmbedding_injective (f : G ↪g G') (u v : V) :
Function.Injective (Path.mapEmbedding f : G.Path u v → G'.Path (f u) (f v)) :=
map_injective f.injective u v
#align simple_graph.path.map_embedding_injective SimpleGraph.Path.mapEmbedding_injective
end Path
/-! ### Transferring between graphs -/
namespace Walk
variable {G}
/-- The walk `p` transferred to lie in `H`, given that `H` contains its edges. -/
@[simp]
protected def transfer {u v : V} (p : G.Walk u v)
(H : SimpleGraph V) (h : ∀ e, e ∈ p.edges → e ∈ H.edgeSet) : H.Walk u v :=
match p with
| nil => nil
| cons' u v w _ p =>
cons (h s(u, v) (by simp)) (p.transfer H fun e he => h e (by simp [he]))
#align simple_graph.walk.transfer SimpleGraph.Walk.transfer
variable {u v : V} (p : G.Walk u v)
theorem transfer_self : p.transfer G p.edges_subset_edgeSet = p := by
induction p <;> simp [*]
#align simple_graph.walk.transfer_self SimpleGraph.Walk.transfer_self
variable {H : SimpleGraph V}
theorem transfer_eq_map_of_le (hp) (GH : G ≤ H) :
p.transfer H hp = p.map (SimpleGraph.Hom.mapSpanningSubgraphs GH) := by
induction p <;> simp [*]
#align simple_graph.walk.transfer_eq_map_of_le SimpleGraph.Walk.transfer_eq_map_of_le
@[simp]
theorem edges_transfer (hp) : (p.transfer H hp).edges = p.edges := by
induction p <;> simp [*]
#align simple_graph.walk.edges_transfer SimpleGraph.Walk.edges_transfer
@[simp]
theorem support_transfer (hp) : (p.transfer H hp).support = p.support := by
induction p <;> simp [*]
#align simple_graph.walk.support_transfer SimpleGraph.Walk.support_transfer
@[simp]
theorem length_transfer (hp) : (p.transfer H hp).length = p.length := by
induction p <;> simp [*]
#align simple_graph.walk.length_transfer SimpleGraph.Walk.length_transfer
variable {p}
protected theorem IsPath.transfer (hp) (pp : p.IsPath) :
(p.transfer H hp).IsPath := by
induction p with
| nil => simp
| cons _ _ ih =>
simp only [Walk.transfer, cons_isPath_iff, support_transfer _ ] at pp ⊢
exact ⟨ih _ pp.1, pp.2⟩
#align simple_graph.walk.is_path.transfer SimpleGraph.Walk.IsPath.transfer
protected theorem IsCycle.transfer {q : G.Walk u u} (qc : q.IsCycle) (hq) :
(q.transfer H hq).IsCycle := by
cases q with
| nil => simp at qc
| cons _ q =>
simp only [edges_cons, List.find?, List.mem_cons, forall_eq_or_imp, mem_edgeSet] at hq
simp only [Walk.transfer, cons_isCycle_iff, edges_transfer q hq.2] at qc ⊢
exact ⟨qc.1.transfer hq.2, qc.2⟩
#align simple_graph.walk.is_cycle.transfer SimpleGraph.Walk.IsCycle.transfer
variable (p)
-- Porting note: this failed the simpNF linter since it was originally of the form
-- `(p.transfer H hp).transfer K hp' = p.transfer K hp''` with `hp'` a function of `hp` and `hp'`.
-- This was a mistake and it's corrected here.
@[simp]
theorem transfer_transfer (hp) {K : SimpleGraph V} (hp') :
(p.transfer H hp).transfer K hp' = p.transfer K (p.edges_transfer hp ▸ hp') := by
induction p with
| nil => simp
| cons _ _ ih =>
simp only [Walk.transfer, cons.injEq, heq_eq_eq, true_and]
apply ih
#align simple_graph.walk.transfer_transfer SimpleGraph.Walk.transfer_transfer
@[simp]
theorem transfer_append {w : V} (q : G.Walk v w) (hpq) :
(p.append q).transfer H hpq =
(p.transfer H fun e he => hpq _ (by simp [he])).append
(q.transfer H fun e he => hpq _ (by simp [he])) := by
induction p with
| nil => simp
| cons _ _ ih => simp only [Walk.transfer, cons_append, cons.injEq, heq_eq_eq, true_and, ih]
#align simple_graph.walk.transfer_append SimpleGraph.Walk.transfer_append
@[simp]
theorem reverse_transfer (hp) :
(p.transfer H hp).reverse =
p.reverse.transfer H (by simp only [edges_reverse, List.mem_reverse]; exact hp) := by
induction p with
| nil => simp
| cons _ _ ih => simp only [transfer_append, Walk.transfer, reverse_nil, reverse_cons, ih]
#align simple_graph.walk.reverse_transfer SimpleGraph.Walk.reverse_transfer
end Walk
/-! ## Deleting edges -/
namespace Walk
variable {G}
/-- Given a walk that avoids a set of edges, produce a walk in the graph
with those edges deleted. -/
abbrev toDeleteEdges (s : Set (Sym2 V)) {v w : V} (p : G.Walk v w)
(hp : ∀ e, e ∈ p.edges → ¬e ∈ s) : (G.deleteEdges s).Walk v w :=
p.transfer _ <| by
simp only [edgeSet_deleteEdges, Set.mem_diff]
exact fun e ep => ⟨edges_subset_edgeSet p ep, hp e ep⟩
#align simple_graph.walk.to_delete_edges SimpleGraph.Walk.toDeleteEdges
@[simp]
theorem toDeleteEdges_nil (s : Set (Sym2 V)) {v : V} (hp) :
(Walk.nil : G.Walk v v).toDeleteEdges s hp = Walk.nil := rfl
#align simple_graph.walk.to_delete_edges_nil SimpleGraph.Walk.toDeleteEdges_nil
@[simp]
theorem toDeleteEdges_cons (s : Set (Sym2 V)) {u v w : V} (h : G.Adj u v) (p : G.Walk v w) (hp) :
(Walk.cons h p).toDeleteEdges s hp =
Walk.cons (deleteEdges_adj.mpr ⟨h, hp _ (List.Mem.head _)⟩)
(p.toDeleteEdges s fun _ he => hp _ <| List.Mem.tail _ he) :=
rfl
#align simple_graph.walk.to_delete_edges_cons SimpleGraph.Walk.toDeleteEdges_cons
variable {v w : V}
/-- Given a walk that avoids an edge, create a walk in the subgraph with that edge deleted.
This is an abbreviation for `SimpleGraph.Walk.toDeleteEdges`. -/
abbrev toDeleteEdge (e : Sym2 V) (p : G.Walk v w) (hp : e ∉ p.edges) :
(G.deleteEdges {e}).Walk v w :=
p.toDeleteEdges {e} (fun e' => by contrapose!; simp (config := { contextual := true }) [hp])
#align simple_graph.walk.to_delete_edge SimpleGraph.Walk.toDeleteEdge
@[simp]
theorem map_toDeleteEdges_eq (s : Set (Sym2 V)) {p : G.Walk v w} (hp) :
Walk.map (Hom.mapSpanningSubgraphs (G.deleteEdges_le s)) (p.toDeleteEdges s hp) = p := by
rw [← transfer_eq_map_of_le, transfer_transfer, transfer_self]
intros e
rw [edges_transfer]
apply edges_subset_edgeSet p
#align simple_graph.walk.map_to_delete_edges_eq SimpleGraph.Walk.map_toDeleteEdges_eq
protected theorem IsPath.toDeleteEdges (s : Set (Sym2 V))
{p : G.Walk v w} (h : p.IsPath) (hp) : (p.toDeleteEdges s hp).IsPath :=
h.transfer _
#align simple_graph.walk.is_path.to_delete_edges SimpleGraph.Walk.IsPath.toDeleteEdges
protected theorem IsCycle.toDeleteEdges (s : Set (Sym2 V))
{p : G.Walk v v} (h : p.IsCycle) (hp) : (p.toDeleteEdges s hp).IsCycle :=
h.transfer _
#align simple_graph.walk.is_cycle.to_delete_edges SimpleGraph.Walk.IsCycle.toDeleteEdges
@[simp]
theorem toDeleteEdges_copy {v u u' v' : V} (s : Set (Sym2 V))
(p : G.Walk u v) (hu : u = u') (hv : v = v') (h) :
(p.copy hu hv).toDeleteEdges s h =
(p.toDeleteEdges s (by subst_vars; exact h)).copy hu hv := by
subst_vars
rfl
#align simple_graph.walk.to_delete_edges_copy SimpleGraph.Walk.toDeleteEdges_copy
end Walk
/-! ## `Reachable` and `Connected` -/
/-- Two vertices are *reachable* if there is a walk between them.
This is equivalent to `Relation.ReflTransGen` of `G.Adj`.
See `SimpleGraph.reachable_iff_reflTransGen`. -/
def Reachable (u v : V) : Prop := Nonempty (G.Walk u v)
#align simple_graph.reachable SimpleGraph.Reachable
variable {G}
theorem reachable_iff_nonempty_univ {u v : V} :
G.Reachable u v ↔ (Set.univ : Set (G.Walk u v)).Nonempty :=
Set.nonempty_iff_univ_nonempty
#align simple_graph.reachable_iff_nonempty_univ SimpleGraph.reachable_iff_nonempty_univ
protected theorem Reachable.elim {p : Prop} {u v : V} (h : G.Reachable u v)
(hp : G.Walk u v → p) : p :=
Nonempty.elim h hp
#align simple_graph.reachable.elim SimpleGraph.Reachable.elim
protected theorem Reachable.elim_path {p : Prop} {u v : V} (h : G.Reachable u v)
(hp : G.Path u v → p) : p := by classical exact h.elim fun q => hp q.toPath
#align simple_graph.reachable.elim_path SimpleGraph.Reachable.elim_path
protected theorem Walk.reachable {G : SimpleGraph V} {u v : V} (p : G.Walk u v) : G.Reachable u v :=
⟨p⟩
#align simple_graph.walk.reachable SimpleGraph.Walk.reachable
protected theorem Adj.reachable {u v : V} (h : G.Adj u v) : G.Reachable u v :=
h.toWalk.reachable
#align simple_graph.adj.reachable SimpleGraph.Adj.reachable
@[refl]
protected theorem Reachable.refl (u : V) : G.Reachable u u := ⟨Walk.nil⟩
#align simple_graph.reachable.refl SimpleGraph.Reachable.refl
protected theorem Reachable.rfl {u : V} : G.Reachable u u := Reachable.refl _
#align simple_graph.reachable.rfl SimpleGraph.Reachable.rfl
@[symm]
protected theorem Reachable.symm {u v : V} (huv : G.Reachable u v) : G.Reachable v u :=
huv.elim fun p => ⟨p.reverse⟩
#align simple_graph.reachable.symm SimpleGraph.Reachable.symm
theorem reachable_comm {u v : V} : G.Reachable u v ↔ G.Reachable v u :=
⟨Reachable.symm, Reachable.symm⟩
#align simple_graph.reachable_comm SimpleGraph.reachable_comm
@[trans]
protected theorem Reachable.trans {u v w : V} (huv : G.Reachable u v) (hvw : G.Reachable v w) :
G.Reachable u w :=
huv.elim fun puv => hvw.elim fun pvw => ⟨puv.append pvw⟩
#align simple_graph.reachable.trans SimpleGraph.Reachable.trans
theorem reachable_iff_reflTransGen (u v : V) :
G.Reachable u v ↔ Relation.ReflTransGen G.Adj u v := by
constructor
· rintro ⟨h⟩
induction h with
| nil => rfl
| cons h' _ ih => exact (Relation.ReflTransGen.single h').trans ih
· intro h
induction h with
| refl => rfl
| tail _ ha hr => exact Reachable.trans hr ⟨Walk.cons ha Walk.nil⟩
#align simple_graph.reachable_iff_refl_trans_gen SimpleGraph.reachable_iff_reflTransGen
protected theorem Reachable.map {u v : V} {G : SimpleGraph V} {G' : SimpleGraph V'} (f : G →g G')
(h : G.Reachable u v) : G'.Reachable (f u) (f v) :=
h.elim fun p => ⟨p.map f⟩
#align simple_graph.reachable.map SimpleGraph.Reachable.map
@[mono]
protected lemma Reachable.mono {u v : V} {G G' : SimpleGraph V}
(h : G ≤ G') (Guv : G.Reachable u v) : G'.Reachable u v :=
Guv.map (SimpleGraph.Hom.mapSpanningSubgraphs h)
theorem Iso.reachable_iff {G : SimpleGraph V} {G' : SimpleGraph V'} {φ : G ≃g G'} {u v : V} :
G'.Reachable (φ u) (φ v) ↔ G.Reachable u v :=
⟨fun r => φ.left_inv u ▸ φ.left_inv v ▸ r.map φ.symm.toHom, Reachable.map φ.toHom⟩
#align simple_graph.iso.reachable_iff SimpleGraph.Iso.reachable_iff
theorem Iso.symm_apply_reachable {G : SimpleGraph V} {G' : SimpleGraph V'} {φ : G ≃g G'} {u : V}
{v : V'} : G.Reachable (φ.symm v) u ↔ G'.Reachable v (φ u) := by
rw [← Iso.reachable_iff, RelIso.apply_symm_apply]
#align simple_graph.iso.symm_apply_reachable SimpleGraph.Iso.symm_apply_reachable
variable (G)
theorem reachable_is_equivalence : Equivalence G.Reachable :=
Equivalence.mk (@Reachable.refl _ G) (@Reachable.symm _ G) (@Reachable.trans _ G)
#align simple_graph.reachable_is_equivalence SimpleGraph.reachable_is_equivalence
/-- The equivalence relation on vertices given by `SimpleGraph.Reachable`. -/
def reachableSetoid : Setoid V := Setoid.mk _ G.reachable_is_equivalence
#align simple_graph.reachable_setoid SimpleGraph.reachableSetoid
/-- A graph is preconnected if every pair of vertices is reachable from one another. -/
def Preconnected : Prop := ∀ u v : V, G.Reachable u v
#align simple_graph.preconnected SimpleGraph.Preconnected
theorem Preconnected.map {G : SimpleGraph V} {H : SimpleGraph V'} (f : G →g H) (hf : Surjective f)
(hG : G.Preconnected) : H.Preconnected :=
hf.forall₂.2 fun _ _ => Nonempty.map (Walk.map _) <| hG _ _
#align simple_graph.preconnected.map SimpleGraph.Preconnected.map
@[mono]
protected lemma Preconnected.mono {G G' : SimpleGraph V} (h : G ≤ G') (hG : G.Preconnected) :
G'.Preconnected := fun u v => (hG u v).mono h
lemma top_preconnected : (⊤ : SimpleGraph V).Preconnected := fun x y => by
if h : x = y then rw [h] else exact Adj.reachable h
theorem Iso.preconnected_iff {G : SimpleGraph V} {H : SimpleGraph V'} (e : G ≃g H) :
G.Preconnected ↔ H.Preconnected :=
⟨Preconnected.map e.toHom e.toEquiv.surjective,
Preconnected.map e.symm.toHom e.symm.toEquiv.surjective⟩
#align simple_graph.iso.preconnected_iff SimpleGraph.Iso.preconnected_iff
/-- A graph is connected if it's preconnected and contains at least one vertex.
This follows the convention observed by mathlib that something is connected iff it has
exactly one connected component.
There is a `CoeFun` instance so that `h u v` can be used instead of `h.Preconnected u v`. -/
@[mk_iff]
structure Connected : Prop where
protected preconnected : G.Preconnected
protected [nonempty : Nonempty V]
#align simple_graph.connected SimpleGraph.Connected
lemma connected_iff_exists_forall_reachable : G.Connected ↔ ∃ v, ∀ w, G.Reachable v w := by
rw [connected_iff]
constructor
· rintro ⟨hp, ⟨v⟩⟩
exact ⟨v, fun w => hp v w⟩
· rintro ⟨v, h⟩
exact ⟨fun u w => (h u).symm.trans (h w), ⟨v⟩⟩
instance : CoeFun G.Connected fun _ => ∀ u v : V, G.Reachable u v := ⟨fun h => h.preconnected⟩
theorem Connected.map {G : SimpleGraph V} {H : SimpleGraph V'} (f : G →g H) (hf : Surjective f)
(hG : G.Connected) : H.Connected :=
haveI := hG.nonempty.map f
⟨hG.preconnected.map f hf⟩
#align simple_graph.connected.map SimpleGraph.Connected.map
@[mono]
protected lemma Connected.mono {G G' : SimpleGraph V} (h : G ≤ G')
(hG : G.Connected) : G'.Connected where
preconnected := hG.preconnected.mono h
nonempty := hG.nonempty
lemma top_connected [Nonempty V] : (⊤ : SimpleGraph V).Connected where
preconnected := top_preconnected
theorem Iso.connected_iff {G : SimpleGraph V} {H : SimpleGraph V'} (e : G ≃g H) :
G.Connected ↔ H.Connected :=
⟨Connected.map e.toHom e.toEquiv.surjective, Connected.map e.symm.toHom e.symm.toEquiv.surjective⟩
#align simple_graph.iso.connected_iff SimpleGraph.Iso.connected_iff
/-- The quotient of `V` by the `SimpleGraph.Reachable` relation gives the connected
components of a graph. -/
def ConnectedComponent := Quot G.Reachable
#align simple_graph.connected_component SimpleGraph.ConnectedComponent
/-- Gives the connected component containing a particular vertex. -/
def connectedComponentMk (v : V) : G.ConnectedComponent := Quot.mk G.Reachable v
#align simple_graph.connected_component_mk SimpleGraph.connectedComponentMk
variable {G G' G''}
namespace ConnectedComponent
@[simps]
instance inhabited [Inhabited V] : Inhabited G.ConnectedComponent :=
⟨G.connectedComponentMk default⟩
#align simple_graph.connected_component.inhabited SimpleGraph.ConnectedComponent.inhabited
@[elab_as_elim]
protected theorem ind {β : G.ConnectedComponent → Prop}
(h : ∀ v : V, β (G.connectedComponentMk v)) (c : G.ConnectedComponent) : β c :=
Quot.ind h c
#align simple_graph.connected_component.ind SimpleGraph.ConnectedComponent.ind
@[elab_as_elim]
protected theorem ind₂ {β : G.ConnectedComponent → G.ConnectedComponent → Prop}
(h : ∀ v w : V, β (G.connectedComponentMk v) (G.connectedComponentMk w))
(c d : G.ConnectedComponent) : β c d :=
Quot.induction_on₂ c d h
#align simple_graph.connected_component.ind₂ SimpleGraph.ConnectedComponent.ind₂
protected theorem sound {v w : V} :
G.Reachable v w → G.connectedComponentMk v = G.connectedComponentMk w :=
Quot.sound
#align simple_graph.connected_component.sound SimpleGraph.ConnectedComponent.sound
protected theorem exact {v w : V} :
G.connectedComponentMk v = G.connectedComponentMk w → G.Reachable v w :=
@Quotient.exact _ G.reachableSetoid _ _
#align simple_graph.connected_component.exact SimpleGraph.ConnectedComponent.exact
@[simp]
protected theorem eq {v w : V} :
G.connectedComponentMk v = G.connectedComponentMk w ↔ G.Reachable v w :=
@Quotient.eq' _ G.reachableSetoid _ _
#align simple_graph.connected_component.eq SimpleGraph.ConnectedComponent.eq
theorem connectedComponentMk_eq_of_adj {v w : V} (a : G.Adj v w) :
G.connectedComponentMk v = G.connectedComponentMk w :=
ConnectedComponent.sound a.reachable
#align simple_graph.connected_component.connected_component_mk_eq_of_adj SimpleGraph.ConnectedComponent.connectedComponentMk_eq_of_adj
/-- The `ConnectedComponent` specialization of `Quot.lift`. Provides the stronger
assumption that the vertices are connected by a path. -/
protected def lift {β : Sort*} (f : V → β)
(h : ∀ (v w : V) (p : G.Walk v w), p.IsPath → f v = f w) : G.ConnectedComponent → β :=
Quot.lift f fun v w (h' : G.Reachable v w) => h'.elim_path fun hp => h v w hp hp.2
#align simple_graph.connected_component.lift SimpleGraph.ConnectedComponent.lift
@[simp]
protected theorem lift_mk {β : Sort*} {f : V → β}
{h : ∀ (v w : V) (p : G.Walk v w), p.IsPath → f v = f w} {v : V} :
ConnectedComponent.lift f h (G.connectedComponentMk v) = f v :=
rfl
#align simple_graph.connected_component.lift_mk SimpleGraph.ConnectedComponent.lift_mk
protected theorem «exists» {p : G.ConnectedComponent → Prop} :
(∃ c : G.ConnectedComponent, p c) ↔ ∃ v, p (G.connectedComponentMk v) :=
(surjective_quot_mk G.Reachable).exists
#align simple_graph.connected_component.exists SimpleGraph.ConnectedComponent.exists
protected theorem «forall» {p : G.ConnectedComponent → Prop} :
(∀ c : G.ConnectedComponent, p c) ↔ ∀ v, p (G.connectedComponentMk v) :=
(surjective_quot_mk G.Reachable).forall
#align simple_graph.connected_component.forall SimpleGraph.ConnectedComponent.forall
theorem _root_.SimpleGraph.Preconnected.subsingleton_connectedComponent (h : G.Preconnected) :
Subsingleton G.ConnectedComponent :=
⟨ConnectedComponent.ind₂ fun v w => ConnectedComponent.sound (h v w)⟩
#align simple_graph.preconnected.subsingleton_connected_component SimpleGraph.Preconnected.subsingleton_connectedComponent
/-- The map on connected components induced by a graph homomorphism. -/
def map (φ : G →g G') (C : G.ConnectedComponent) : G'.ConnectedComponent :=
C.lift (fun v => G'.connectedComponentMk (φ v)) fun _ _ p _ =>
ConnectedComponent.eq.mpr (p.map φ).reachable
#align simple_graph.connected_component.map SimpleGraph.ConnectedComponent.map
@[simp]
theorem map_mk (φ : G →g G') (v : V) :
(G.connectedComponentMk v).map φ = G'.connectedComponentMk (φ v) :=
rfl
#align simple_graph.connected_component.map_mk SimpleGraph.ConnectedComponent.map_mk
@[simp]
theorem map_id (C : ConnectedComponent G) : C.map Hom.id = C := by
refine C.ind ?_
exact fun _ => rfl
#align simple_graph.connected_component.map_id SimpleGraph.ConnectedComponent.map_id
@[simp]
theorem map_comp (C : G.ConnectedComponent) (φ : G →g G') (ψ : G' →g G'') :
(C.map φ).map ψ = C.map (ψ.comp φ) := by
refine C.ind ?_
exact fun _ => rfl
#align simple_graph.connected_component.map_comp SimpleGraph.ConnectedComponent.map_comp
variable {φ : G ≃g G'} {v : V} {v' : V'}
@[simp]
theorem iso_image_comp_eq_map_iff_eq_comp {C : G.ConnectedComponent} :
G'.connectedComponentMk (φ v) = C.map ↑(↑φ : G ↪g G') ↔ G.connectedComponentMk v = C := by
refine C.ind fun u => ?_
simp only [Iso.reachable_iff, ConnectedComponent.map_mk, RelEmbedding.coe_toRelHom,
RelIso.coe_toRelEmbedding, ConnectedComponent.eq]
#align simple_graph.connected_component.iso_image_comp_eq_map_iff_eq_comp SimpleGraph.ConnectedComponent.iso_image_comp_eq_map_iff_eq_comp
@[simp]
theorem iso_inv_image_comp_eq_iff_eq_map {C : G.ConnectedComponent} :
G.connectedComponentMk (φ.symm v') = C ↔ G'.connectedComponentMk v' = C.map φ := by
refine C.ind fun u => ?_
simp only [Iso.symm_apply_reachable, ConnectedComponent.eq, ConnectedComponent.map_mk,
RelEmbedding.coe_toRelHom, RelIso.coe_toRelEmbedding]
#align simple_graph.connected_component.iso_inv_image_comp_eq_iff_eq_map SimpleGraph.ConnectedComponent.iso_inv_image_comp_eq_iff_eq_map
end ConnectedComponent
namespace Iso
/-- An isomorphism of graphs induces a bijection of connected components. -/
@[simps]
def connectedComponentEquiv (φ : G ≃g G') : G.ConnectedComponent ≃ G'.ConnectedComponent where
toFun := ConnectedComponent.map φ
invFun := ConnectedComponent.map φ.symm
left_inv C := ConnectedComponent.ind
(fun v => congr_arg G.connectedComponentMk (Equiv.left_inv φ.toEquiv v)) C
right_inv C := ConnectedComponent.ind
(fun v => congr_arg G'.connectedComponentMk (Equiv.right_inv φ.toEquiv v)) C
#align simple_graph.iso.connected_component_equiv SimpleGraph.Iso.connectedComponentEquiv
@[simp]
theorem connectedComponentEquiv_refl :
(Iso.refl : G ≃g G).connectedComponentEquiv = Equiv.refl _ := by
ext ⟨v⟩
rfl
#align simple_graph.iso.connected_component_equiv_refl SimpleGraph.Iso.connectedComponentEquiv_refl
@[simp]
theorem connectedComponentEquiv_symm (φ : G ≃g G') :
φ.symm.connectedComponentEquiv = φ.connectedComponentEquiv.symm := by
ext ⟨_⟩
rfl
#align simple_graph.iso.connected_component_equiv_symm SimpleGraph.Iso.connectedComponentEquiv_symm
@[simp]
theorem connectedComponentEquiv_trans (φ : G ≃g G') (φ' : G' ≃g G'') :
connectedComponentEquiv (φ.trans φ') =
φ.connectedComponentEquiv.trans φ'.connectedComponentEquiv := by
ext ⟨_⟩
rfl
#align simple_graph.iso.connected_component_equiv_trans SimpleGraph.Iso.connectedComponentEquiv_trans
end Iso
namespace ConnectedComponent
/-- The set of vertices in a connected component of a graph. -/
def supp (C : G.ConnectedComponent) :=
{ v | G.connectedComponentMk v = C }
#align simple_graph.connected_component.supp SimpleGraph.ConnectedComponent.supp
@[ext]
theorem supp_injective :
Function.Injective (ConnectedComponent.supp : G.ConnectedComponent → Set V) := by
refine ConnectedComponent.ind₂ ?_
intro v w
simp only [ConnectedComponent.supp, Set.ext_iff, ConnectedComponent.eq, Set.mem_setOf_eq]
intro h
rw [reachable_comm, h]
#align simple_graph.connected_component.supp_injective SimpleGraph.ConnectedComponent.supp_injective
@[simp]
theorem supp_inj {C D : G.ConnectedComponent} : C.supp = D.supp ↔ C = D :=
ConnectedComponent.supp_injective.eq_iff
#align simple_graph.connected_component.supp_inj SimpleGraph.ConnectedComponent.supp_inj
instance : SetLike G.ConnectedComponent V where
coe := ConnectedComponent.supp
coe_injective' := ConnectedComponent.supp_injective
@[simp]
theorem mem_supp_iff (C : G.ConnectedComponent) (v : V) :
v ∈ C.supp ↔ G.connectedComponentMk v = C :=
Iff.rfl
#align simple_graph.connected_component.mem_supp_iff SimpleGraph.ConnectedComponent.mem_supp_iff
theorem connectedComponentMk_mem {v : V} : v ∈ G.connectedComponentMk v :=
rfl
#align simple_graph.connected_component.connected_component_mk_mem SimpleGraph.ConnectedComponent.connectedComponentMk_mem
/-- The equivalence between connected components, induced by an isomorphism of graphs,
itself defines an equivalence on the supports of each connected component.
-/
def isoEquivSupp (φ : G ≃g G') (C : G.ConnectedComponent) :
C.supp ≃ (φ.connectedComponentEquiv C).supp where
toFun v := ⟨φ v, ConnectedComponent.iso_image_comp_eq_map_iff_eq_comp.mpr v.prop⟩
invFun v' := ⟨φ.symm v', ConnectedComponent.iso_inv_image_comp_eq_iff_eq_map.mpr v'.prop⟩
left_inv v := Subtype.ext_val (φ.toEquiv.left_inv ↑v)
right_inv v := Subtype.ext_val (φ.toEquiv.right_inv ↑v)
#align simple_graph.connected_component.iso_equiv_supp SimpleGraph.ConnectedComponent.isoEquivSupp
end ConnectedComponent
theorem Preconnected.set_univ_walk_nonempty (hconn : G.Preconnected) (u v : V) :
(Set.univ : Set (G.Walk u v)).Nonempty := by
rw [← Set.nonempty_iff_univ_nonempty]
exact hconn u v
#align simple_graph.preconnected.set_univ_walk_nonempty SimpleGraph.Preconnected.set_univ_walk_nonempty
theorem Connected.set_univ_walk_nonempty (hconn : G.Connected) (u v : V) :
(Set.univ : Set (G.Walk u v)).Nonempty :=
hconn.preconnected.set_univ_walk_nonempty u v
#align simple_graph.connected.set_univ_walk_nonempty SimpleGraph.Connected.set_univ_walk_nonempty
/-! ### Walks as subgraphs -/
namespace Walk
variable {u v w : V}
/-- The subgraph consisting of the vertices and edges of the walk. -/
@[simp]
protected def toSubgraph {u v : V} : G.Walk u v → G.Subgraph
| nil => G.singletonSubgraph u
| cons h p => G.subgraphOfAdj h ⊔ p.toSubgraph
#align simple_graph.walk.to_subgraph SimpleGraph.Walk.toSubgraph
theorem toSubgraph_cons_nil_eq_subgraphOfAdj (h : G.Adj u v) :
(cons h nil).toSubgraph = G.subgraphOfAdj h := by simp
#align simple_graph.walk.to_subgraph_cons_nil_eq_subgraph_of_adj SimpleGraph.Walk.toSubgraph_cons_nil_eq_subgraphOfAdj
theorem mem_verts_toSubgraph (p : G.Walk u v) : w ∈ p.toSubgraph.verts ↔ w ∈ p.support := by
induction' p with _ x y z h p' ih
· simp
· have : w = y ∨ w ∈ p'.support ↔ w ∈ p'.support :=
⟨by rintro (rfl | h) <;> simp [*], by simp (config := { contextual := true })⟩
simp [ih, or_assoc, this]
#align simple_graph.walk.mem_verts_to_subgraph SimpleGraph.Walk.mem_verts_toSubgraph
lemma start_mem_verts_toSubgraph (p : G.Walk u v) : u ∈ p.toSubgraph.verts := by
simp [mem_verts_toSubgraph]
lemma end_mem_verts_toSubgraph (p : G.Walk u v) : v ∈ p.toSubgraph.verts := by
simp [mem_verts_toSubgraph]
@[simp]
theorem verts_toSubgraph (p : G.Walk u v) : p.toSubgraph.verts = { w | w ∈ p.support } :=
Set.ext fun _ => p.mem_verts_toSubgraph
#align simple_graph.walk.verts_to_subgraph SimpleGraph.Walk.verts_toSubgraph
theorem mem_edges_toSubgraph (p : G.Walk u v) {e : Sym2 V} :
e ∈ p.toSubgraph.edgeSet ↔ e ∈ p.edges := by induction p <;> simp [*]
#align simple_graph.walk.mem_edges_to_subgraph SimpleGraph.Walk.mem_edges_toSubgraph
@[simp]
theorem edgeSet_toSubgraph (p : G.Walk u v) : p.toSubgraph.edgeSet = { e | e ∈ p.edges } :=
Set.ext fun _ => p.mem_edges_toSubgraph
#align simple_graph.walk.edge_set_to_subgraph SimpleGraph.Walk.edgeSet_toSubgraph
@[simp]
theorem toSubgraph_append (p : G.Walk u v) (q : G.Walk v w) :
(p.append q).toSubgraph = p.toSubgraph ⊔ q.toSubgraph := by induction p <;> simp [*, sup_assoc]
#align simple_graph.walk.to_subgraph_append SimpleGraph.Walk.toSubgraph_append
@[simp]
theorem toSubgraph_reverse (p : G.Walk u v) : p.reverse.toSubgraph = p.toSubgraph := by
induction p with
| nil => simp
| cons _ _ _ =>
simp only [*, Walk.toSubgraph, reverse_cons, toSubgraph_append, subgraphOfAdj_symm]
rw [sup_comm]
congr
ext <;> simp [-Set.bot_eq_empty]
#align simple_graph.walk.to_subgraph_reverse SimpleGraph.Walk.toSubgraph_reverse
@[simp]
theorem toSubgraph_rotate [DecidableEq V] (c : G.Walk v v) (h : u ∈ c.support) :
(c.rotate h).toSubgraph = c.toSubgraph := by
rw [rotate, toSubgraph_append, sup_comm, ← toSubgraph_append, take_spec]
#align simple_graph.walk.to_subgraph_rotate SimpleGraph.Walk.toSubgraph_rotate
@[simp]
theorem toSubgraph_map (f : G →g G') (p : G.Walk u v) :
(p.map f).toSubgraph = p.toSubgraph.map f := by induction p <;> simp [*, Subgraph.map_sup]
#align simple_graph.walk.to_subgraph_map SimpleGraph.Walk.toSubgraph_map
@[simp]
theorem finite_neighborSet_toSubgraph (p : G.Walk u v) : (p.toSubgraph.neighborSet w).Finite := by
induction p with
| nil =>
rw [Walk.toSubgraph, neighborSet_singletonSubgraph]
apply Set.toFinite
| cons ha _ ih =>
rw [Walk.toSubgraph, Subgraph.neighborSet_sup]
refine Set.Finite.union ?_ ih
refine Set.Finite.subset ?_ (neighborSet_subgraphOfAdj_subset ha)
apply Set.toFinite
#align simple_graph.walk.finite_neighbor_set_to_subgraph SimpleGraph.Walk.finite_neighborSet_toSubgraph
lemma toSubgraph_le_induce_support (p : G.Walk u v) :
p.toSubgraph ≤ (⊤ : G.Subgraph).induce {v | v ∈ p.support} := by
convert Subgraph.le_induce_top_verts
exact p.verts_toSubgraph.symm
end Walk
/-! ### Walks of a given length -/
section WalkCounting
theorem set_walk_self_length_zero_eq (u : V) : {p : G.Walk u u | p.length = 0} = {Walk.nil} := by
ext p
simp
#align simple_graph.set_walk_self_length_zero_eq SimpleGraph.set_walk_self_length_zero_eq
theorem set_walk_length_zero_eq_of_ne {u v : V} (h : u ≠ v) :
{p : G.Walk u v | p.length = 0} = ∅ := by
ext p
simp only [Set.mem_setOf_eq, Set.mem_empty_iff_false, iff_false_iff]
exact fun h' => absurd (Walk.eq_of_length_eq_zero h') h
#align simple_graph.set_walk_length_zero_eq_of_ne SimpleGraph.set_walk_length_zero_eq_of_ne
theorem set_walk_length_succ_eq (u v : V) (n : ℕ) :
{p : G.Walk u v | p.length = n.succ} =
⋃ (w : V) (h : G.Adj u w), Walk.cons h '' {p' : G.Walk w v | p'.length = n} := by
ext p
cases' p with _ _ w _ huw pwv
· simp [eq_comm]
· simp only [Nat.succ_eq_add_one, Set.mem_setOf_eq, Walk.length_cons, add_left_inj,
Set.mem_iUnion, Set.mem_image, exists_prop]
constructor
· rintro rfl
exact ⟨w, huw, pwv, rfl, rfl⟩
· rintro ⟨w, huw, pwv, rfl, rfl, rfl⟩
rfl
#align simple_graph.set_walk_length_succ_eq SimpleGraph.set_walk_length_succ_eq
variable (G) [DecidableEq V]
/-- Walks of length two from `u` to `v` correspond bijectively to common neighbours of `u` and `v`.
Note that `u` and `v` may be the same. -/
@[simps]
def walkLengthTwoEquivCommonNeighbors (u v : V) :
{p : G.Walk u v // p.length = 2} ≃ G.commonNeighbors u v where
toFun p := ⟨p.val.getVert 1, match p with
| ⟨.cons _ (.cons _ .nil), hp⟩ => ⟨‹G.Adj u _›, ‹G.Adj _ v›.symm⟩⟩
invFun w := ⟨w.prop.1.toWalk.concat w.prop.2.symm, rfl⟩
left_inv | ⟨.cons _ (.cons _ .nil), hp⟩ => by rfl
right_inv _ := rfl
section LocallyFinite
variable [LocallyFinite G]
/-- The `Finset` of length-`n` walks from `u` to `v`.
This is used to give `{p : G.walk u v | p.length = n}` a `Fintype` instance, and it
can also be useful as a recursive description of this set when `V` is finite.
See `SimpleGraph.coe_finsetWalkLength_eq` for the relationship between this `Finset` and
the set of length-`n` walks. -/
def finsetWalkLength (n : ℕ) (u v : V) : Finset (G.Walk u v) :=
match n with
| 0 =>
if h : u = v then by
subst u
exact {Walk.nil}
else ∅
| n + 1 =>
Finset.univ.biUnion fun (w : G.neighborSet u) =>
(finsetWalkLength n w v).map ⟨fun p => Walk.cons w.property p, fun _ _ => by simp⟩
#align simple_graph.finset_walk_length SimpleGraph.finsetWalkLength
theorem coe_finsetWalkLength_eq (n : ℕ) (u v : V) :
(G.finsetWalkLength n u v : Set (G.Walk u v)) = {p : G.Walk u v | p.length = n} := by
induction' n with n ih generalizing u v
· obtain rfl | huv := eq_or_ne u v <;> simp [finsetWalkLength, set_walk_length_zero_eq_of_ne, *]
· simp only [finsetWalkLength, set_walk_length_succ_eq, Finset.coe_biUnion, Finset.mem_coe,
Finset.mem_univ, Set.iUnion_true]
ext p
simp only [mem_neighborSet, Finset.coe_map, Embedding.coeFn_mk, Set.iUnion_coe_set,
Set.mem_iUnion, Set.mem_image, Finset.mem_coe, Set.mem_setOf_eq]
congr!
rename_i w _ q
have := Set.ext_iff.mp (ih w v) q
simp only [Finset.mem_coe, Set.mem_setOf_eq] at this
rw [← this]
#align simple_graph.coe_finset_walk_length_eq SimpleGraph.coe_finsetWalkLength_eq
variable {G}
theorem Walk.mem_finsetWalkLength_iff_length_eq {n : ℕ} {u v : V} (p : G.Walk u v) :
p ∈ G.finsetWalkLength n u v ↔ p.length = n :=
Set.ext_iff.mp (G.coe_finsetWalkLength_eq n u v) p
#align simple_graph.walk.mem_finset_walk_length_iff_length_eq SimpleGraph.Walk.mem_finsetWalkLength_iff_length_eq
variable (G)
instance fintypeSetWalkLength (u v : V) (n : ℕ) : Fintype {p : G.Walk u v | p.length = n} :=
Fintype.ofFinset (G.finsetWalkLength n u v) fun p => by
rw [← Finset.mem_coe, coe_finsetWalkLength_eq]
#align simple_graph.fintype_set_walk_length SimpleGraph.fintypeSetWalkLength
instance fintypeSubtypeWalkLength (u v : V) (n : ℕ) : Fintype {p : G.Walk u v // p.length = n} :=
fintypeSetWalkLength G u v n
theorem set_walk_length_toFinset_eq (n : ℕ) (u v : V) :
{p : G.Walk u v | p.length = n}.toFinset = G.finsetWalkLength n u v := by
ext p
simp [← coe_finsetWalkLength_eq]
#align simple_graph.set_walk_length_to_finset_eq SimpleGraph.set_walk_length_toFinset_eq
/- See `SimpleGraph.adjMatrix_pow_apply_eq_card_walk` for the cardinality in terms of the `n`th
power of the adjacency matrix. -/
theorem card_set_walk_length_eq (u v : V) (n : ℕ) :
Fintype.card {p : G.Walk u v | p.length = n} = (G.finsetWalkLength n u v).card :=
Fintype.card_ofFinset (G.finsetWalkLength n u v) fun p => by
rw [← Finset.mem_coe, coe_finsetWalkLength_eq]
#align simple_graph.card_set_walk_length_eq SimpleGraph.card_set_walk_length_eq
instance fintypeSetPathLength (u v : V) (n : ℕ) :
Fintype {p : G.Walk u v | p.IsPath ∧ p.length = n} :=
Fintype.ofFinset ((G.finsetWalkLength n u v).filter Walk.IsPath) <| by
simp [Walk.mem_finsetWalkLength_iff_length_eq, and_comm]
#align simple_graph.fintype_set_path_length SimpleGraph.fintypeSetPathLength
end LocallyFinite
section Finite
variable [Fintype V] [DecidableRel G.Adj]
| Mathlib/Combinatorics/SimpleGraph/Connectivity.lean | 2,591 | 2,599 | theorem reachable_iff_exists_finsetWalkLength_nonempty (u v : V) :
G.Reachable u v ↔ ∃ n : Fin (Fintype.card V), (G.finsetWalkLength n u v).Nonempty := by |
constructor
· intro r
refine r.elim_path fun p => ?_
refine ⟨⟨_, p.isPath.length_lt⟩, p, ?_⟩
simp [Walk.mem_finsetWalkLength_iff_length_eq]
· rintro ⟨_, p, _⟩
exact ⟨p⟩
|
/-
Copyright (c) 2019 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, Yury Kudriashov
-/
import Mathlib.Analysis.Convex.Combination
import Mathlib.Analysis.Convex.Function
import Mathlib.Tactic.FieldSimp
#align_import analysis.convex.jensen from "leanprover-community/mathlib"@"bfad3f455b388fbcc14c49d0cac884f774f14d20"
/-!
# Jensen's inequality and maximum principle for convex functions
In this file, we prove the finite Jensen inequality and the finite maximum principle for convex
functions. The integral versions are to be found in `Analysis.Convex.Integral`.
## Main declarations
Jensen's inequalities:
* `ConvexOn.map_centerMass_le`, `ConvexOn.map_sum_le`: Convex Jensen's inequality. The image of a
convex combination of points under a convex function is less than the convex combination of the
images.
* `ConcaveOn.le_map_centerMass`, `ConcaveOn.le_map_sum`: Concave Jensen's inequality.
* `StrictConvexOn.map_sum_lt`: Convex strict Jensen inequality.
* `StrictConcaveOn.lt_map_sum`: Concave strict Jensen inequality.
As corollaries, we get:
* `StrictConvexOn.map_sum_eq_iff`: Equality case of the convex Jensen inequality.
* `StrictConcaveOn.map_sum_eq_iff`: Equality case of the concave Jensen inequality.
* `ConvexOn.exists_ge_of_mem_convexHull`: Maximum principle for convex functions.
* `ConcaveOn.exists_le_of_mem_convexHull`: Minimum principle for concave functions.
-/
open Finset LinearMap Set
open scoped Classical
open Convex Pointwise
variable {𝕜 E F β ι : Type*}
/-! ### Jensen's inequality -/
section Jensen
variable [LinearOrderedField 𝕜] [AddCommGroup E] [OrderedAddCommGroup β] [Module 𝕜 E] [Module 𝕜 β]
[OrderedSMul 𝕜 β] {s : Set E} {f : E → β} {t : Finset ι} {w : ι → 𝕜} {p : ι → E} {v : 𝕜} {q : E}
/-- Convex **Jensen's inequality**, `Finset.centerMass` version. -/
theorem ConvexOn.map_centerMass_le (hf : ConvexOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 ≤ w i)
(h₁ : 0 < ∑ i ∈ t, w i) (hmem : ∀ i ∈ t, p i ∈ s) :
f (t.centerMass w p) ≤ t.centerMass w (f ∘ p) := by
have hmem' : ∀ i ∈ t, (p i, (f ∘ p) i) ∈ { p : E × β | p.1 ∈ s ∧ f p.1 ≤ p.2 } := fun i hi =>
⟨hmem i hi, le_rfl⟩
convert (hf.convex_epigraph.centerMass_mem h₀ h₁ hmem').2 <;>
simp only [centerMass, Function.comp, Prod.smul_fst, Prod.fst_sum, Prod.smul_snd, Prod.snd_sum]
#align convex_on.map_center_mass_le ConvexOn.map_centerMass_le
/-- Concave **Jensen's inequality**, `Finset.centerMass` version. -/
theorem ConcaveOn.le_map_centerMass (hf : ConcaveOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 ≤ w i)
(h₁ : 0 < ∑ i ∈ t, w i) (hmem : ∀ i ∈ t, p i ∈ s) :
t.centerMass w (f ∘ p) ≤ f (t.centerMass w p) :=
ConvexOn.map_centerMass_le (β := βᵒᵈ) hf h₀ h₁ hmem
#align concave_on.le_map_center_mass ConcaveOn.le_map_centerMass
/-- Convex **Jensen's inequality**, `Finset.sum` version. -/
theorem ConvexOn.map_sum_le (hf : ConvexOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 ≤ w i) (h₁ : ∑ i ∈ t, w i = 1)
(hmem : ∀ i ∈ t, p i ∈ s) : f (∑ i ∈ t, w i • p i) ≤ ∑ i ∈ t, w i • f (p i) := by
simpa only [centerMass, h₁, inv_one, one_smul] using
hf.map_centerMass_le h₀ (h₁.symm ▸ zero_lt_one) hmem
#align convex_on.map_sum_le ConvexOn.map_sum_le
/-- Concave **Jensen's inequality**, `Finset.sum` version. -/
theorem ConcaveOn.le_map_sum (hf : ConcaveOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 ≤ w i)
(h₁ : ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s) :
(∑ i ∈ t, w i • f (p i)) ≤ f (∑ i ∈ t, w i • p i) :=
ConvexOn.map_sum_le (β := βᵒᵈ) hf h₀ h₁ hmem
#align concave_on.le_map_sum ConcaveOn.le_map_sum
/-- Convex **Jensen's inequality** where an element plays a distinguished role. -/
lemma ConvexOn.map_add_sum_le (hf : ConvexOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 ≤ w i)
(h₁ : v + ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s) (hv : 0 ≤ v) (hq : q ∈ s) :
f (v • q + ∑ i ∈ t, w i • p i) ≤ v • f q + ∑ i ∈ t, w i • f (p i) := by
let W j := Option.elim j v w
let P j := Option.elim j q p
have : f (∑ j ∈ insertNone t, W j • P j) ≤ ∑ j ∈ insertNone t, W j • f (P j) :=
hf.map_sum_le (forall_mem_insertNone.2 ⟨hv, h₀⟩) (by simpa using h₁)
(forall_mem_insertNone.2 ⟨hq, hmem⟩)
simpa using this
/-- Concave **Jensen's inequality** where an element plays a distinguished role. -/
lemma ConcaveOn.map_add_sum_le (hf : ConcaveOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 ≤ w i)
(h₁ : v + ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s) (hv : 0 ≤ v) (hq : q ∈ s) :
v • f q + ∑ i ∈ t, w i • f (p i) ≤ f (v • q + ∑ i ∈ t, w i • p i) :=
hf.dual.map_add_sum_le h₀ h₁ hmem hv hq
/-! ### Strict Jensen inequality -/
/-- Convex **strict Jensen inequality**.
If the function is strictly convex, the weights are strictly positive and the indexed family of
points is non-constant, then Jensen's inequality is strict.
See also `StrictConvexOn.map_sum_eq_iff`. -/
lemma StrictConvexOn.map_sum_lt (hf : StrictConvexOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 < w i)
(h₁ : ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s) (hp : ∃ j ∈ t, ∃ k ∈ t, p j ≠ p k) :
f (∑ i ∈ t, w i • p i) < ∑ i ∈ t, w i • f (p i) := by
classical
obtain ⟨j, hj, k, hk, hjk⟩ := hp
-- We replace `t` by `t \ {j, k}`
have : k ∈ t.erase j := mem_erase.2 ⟨ne_of_apply_ne _ hjk.symm, hk⟩
let u := (t.erase j).erase k
have hj : j ∉ u := by simp [u]
have hk : k ∉ u := by simp [u]
have ht :
t = (u.cons k hk).cons j (mem_cons.not.2 <| not_or_intro (ne_of_apply_ne _ hjk) hj) := by
simp [insert_erase this, insert_erase ‹j ∈ t›, *]
clear_value u
subst ht
simp only [sum_cons]
have := h₀ j <| by simp
have := h₀ k <| by simp
let c := w j + w k
have hc : w j / c + w k / c = 1 := by field_simp
have hcj : c * (w j / c) = w j := by field_simp
have hck : c * (w k / c) = w k := by field_simp
calc f (w j • p j + (w k • p k + ∑ x ∈ u, w x • p x))
_ = f (c • ((w j / c) • p j + (w k / c) • p k) + ∑ x ∈ u, w x • p x) := by
rw [smul_add, ← mul_smul, ← mul_smul, hcj, hck, add_assoc]
_ ≤ c • f ((w j / c) • p j + (w k / c) • p k) + ∑ x ∈ u, w x • f (p x) :=
-- apply the usual Jensen's inequality wrt the weighted average of the two distinguished
-- points and all the other points
hf.convexOn.map_add_sum_le (fun i hi ↦ (h₀ _ <| by simp [hi]).le)
(by simpa [-cons_eq_insert, ← add_assoc] using h₁)
(forall_of_forall_cons <| forall_of_forall_cons hmem) (by positivity) <| by
refine hf.1 (hmem _ <| by simp) (hmem _ <| by simp) ?_ ?_ hc <;> positivity
_ < c • ((w j / c) • f (p j) + (w k / c) • f (p k)) + ∑ x ∈ u, w x • f (p x) := by
-- then apply the definition of strict convexity for the two distinguished points
gcongr; refine hf.2 (hmem _ <| by simp) (hmem _ <| by simp) hjk ?_ ?_ hc <;> positivity
_ = (w j • f (p j) + w k • f (p k)) + ∑ x ∈ u, w x • f (p x) := by
rw [smul_add, ← mul_smul, ← mul_smul, hcj, hck]
_ = w j • f (p j) + (w k • f (p k) + ∑ x ∈ u, w x • f (p x)) := by abel_nf
/-- Concave **strict Jensen inequality**.
If the function is strictly concave, the weights are strictly positive and the indexed family of
points is non-constant, then Jensen's inequality is strict.
See also `StrictConcaveOn.map_sum_eq_iff`. -/
lemma StrictConcaveOn.lt_map_sum (hf : StrictConcaveOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 < w i)
(h₁ : ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s) (hp : ∃ j ∈ t, ∃ k ∈ t, p j ≠ p k) :
∑ i ∈ t, w i • f (p i) < f (∑ i ∈ t, w i • p i) := hf.dual.map_sum_lt h₀ h₁ hmem hp
/-! ### Equality case of Jensen's inequality -/
/-- A form of the **equality case of Jensen's equality**.
For a strictly convex function `f` and positive weights `w`, if
`f (∑ i ∈ t, w i • p i) = ∑ i ∈ t, w i • f (p i)`, then the points `p` are all equal.
See also `StrictConvexOn.map_sum_eq_iff`. -/
lemma StrictConvexOn.eq_of_le_map_sum (hf : StrictConvexOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 < w i)
(h₁ : ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s)
(h_eq : ∑ i ∈ t, w i • f (p i) ≤ f (∑ i ∈ t, w i • p i)) :
∀ ⦃j⦄, j ∈ t → ∀ ⦃k⦄, k ∈ t → p j = p k := by
by_contra!; exact h_eq.not_lt <| hf.map_sum_lt h₀ h₁ hmem this
/-- A form of the **equality case of Jensen's equality**.
For a strictly concave function `f` and positive weights `w`, if
`f (∑ i ∈ t, w i • p i) = ∑ i ∈ t, w i • f (p i)`, then the points `p` are all equal.
See also `StrictConcaveOn.map_sum_eq_iff`. -/
lemma StrictConcaveOn.eq_of_map_sum_eq (hf : StrictConcaveOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 < w i)
(h₁ : ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s)
(h_eq : f (∑ i ∈ t, w i • p i) ≤ ∑ i ∈ t, w i • f (p i)) :
∀ ⦃j⦄, j ∈ t → ∀ ⦃k⦄, k ∈ t → p j = p k := by
by_contra!; exact h_eq.not_lt <| hf.lt_map_sum h₀ h₁ hmem this
/-- Canonical form of the **equality case of Jensen's equality**.
For a strictly convex function `f` and positive weights `w`, we have
`f (∑ i ∈ t, w i • p i) = ∑ i ∈ t, w i • f (p i)` if and only if the points `p` are all equal
(and in fact all equal to their center of mass wrt `w`). -/
lemma StrictConvexOn.map_sum_eq_iff {w : ι → 𝕜} {p : ι → E} (hf : StrictConvexOn 𝕜 s f)
(h₀ : ∀ i ∈ t, 0 < w i) (h₁ : ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s) :
f (∑ i ∈ t, w i • p i) = ∑ i ∈ t, w i • f (p i) ↔ ∀ j ∈ t, p j = ∑ i ∈ t, w i • p i := by
constructor
· obtain rfl | ⟨i₀, hi₀⟩ := t.eq_empty_or_nonempty
· simp
intro h_eq i hi
have H : ∀ j ∈ t, p j = p i₀ := by
intro j hj
apply hf.eq_of_le_map_sum h₀ h₁ hmem h_eq.ge hj hi₀
calc p i = p i₀ := by rw [H _ hi]
_ = (1:𝕜) • p i₀ := by simp
_ = (∑ j ∈ t, w j) • p i₀ := by rw [h₁]
_ = ∑ j ∈ t, (w j • p i₀) := by rw [sum_smul]
_ = ∑ j ∈ t, (w j • p j) := by congr! 2 with j hj; rw [← H _ hj]
· intro h
have H : ∀ j ∈ t, w j • f (p j) = w j • f (∑ i ∈ t, w i • p i) := by
intro j hj
simp [h j hj]
rw [sum_congr rfl H, ← sum_smul, h₁, one_smul]
/-- Canonical form of the **equality case of Jensen's equality**.
For a strictly concave function `f` and positive weights `w`, we have
`f (∑ i ∈ t, w i • p i) = ∑ i ∈ t, w i • f (p i)` if and only if the points `p` are all equal
(and in fact all equal to their center of mass wrt `w`). -/
lemma StrictConcaveOn.map_sum_eq_iff (hf : StrictConcaveOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 < w i)
(h₁ : ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s) :
f (∑ i ∈ t, w i • p i) = ∑ i ∈ t, w i • f (p i) ↔ ∀ j ∈ t, p j = ∑ i ∈ t, w i • p i := by
simpa using hf.neg.map_sum_eq_iff h₀ h₁ hmem
/-- Canonical form of the **equality case of Jensen's equality**.
For a strictly convex function `f` and nonnegative weights `w`, we have
`f (∑ i ∈ t, w i • p i) = ∑ i ∈ t, w i • f (p i)` if and only if the points `p` with nonzero
weight are all equal (and in fact all equal to their center of mass wrt `w`). -/
lemma StrictConvexOn.map_sum_eq_iff' (hf : StrictConvexOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 ≤ w i)
(h₁ : ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s) :
f (∑ i ∈ t, w i • p i) = ∑ i ∈ t, w i • f (p i) ↔
∀ j ∈ t, w j ≠ 0 → p j = ∑ i ∈ t, w i • p i := by
have hw (i) (_ : i ∈ t) : w i • p i ≠ 0 → w i ≠ 0 := by aesop
have hw' (i) (_ : i ∈ t) : w i • f (p i) ≠ 0 → w i ≠ 0 := by aesop
rw [← sum_filter_of_ne hw, ← sum_filter_of_ne hw', hf.map_sum_eq_iff]
· simp
· simp (config := { contextual := true }) [(h₀ _ _).gt_iff_ne]
· rwa [sum_filter_ne_zero]
· simp (config := { contextual := true }) [hmem _ _]
/-- Canonical form of the **equality case of Jensen's equality**.
For a strictly concave function `f` and nonnegative weights `w`, we have
`f (∑ i ∈ t, w i • p i) = ∑ i ∈ t, w i • f (p i)` if and only if the points `p` with nonzero
weight are all equal (and in fact all equal to their center of mass wrt `w`). -/
lemma StrictConcaveOn.map_sum_eq_iff' (hf : StrictConcaveOn 𝕜 s f) (h₀ : ∀ i ∈ t, 0 ≤ w i)
(h₁ : ∑ i ∈ t, w i = 1) (hmem : ∀ i ∈ t, p i ∈ s) :
f (∑ i ∈ t, w i • p i) = ∑ i ∈ t, w i • f (p i) ↔
∀ j ∈ t, w j ≠ 0 → p j = ∑ i ∈ t, w i • p i := hf.dual.map_sum_eq_iff' h₀ h₁ hmem
end Jensen
/-! ### Maximum principle -/
section MaximumPrinciple
variable [LinearOrderedField 𝕜] [AddCommGroup E] [LinearOrderedAddCommGroup β] [Module 𝕜 E]
[Module 𝕜 β] [OrderedSMul 𝕜 β] {s : Set E} {f : E → β} {t : Finset ι} {w : ι → 𝕜} {p : ι → E}
{x y z : E}
| Mathlib/Analysis/Convex/Jensen.lean | 256 | 261 | theorem le_sup_of_mem_convexHull {s : Finset E} (hf : ConvexOn 𝕜 (convexHull 𝕜 (s : Set E)) f)
(hx : x ∈ convexHull 𝕜 (s : Set E)) :
f x ≤ s.sup' (coe_nonempty.1 <| convexHull_nonempty_iff.1 ⟨x, hx⟩) f := by |
obtain ⟨w, hw₀, hw₁, rfl⟩ := mem_convexHull.1 hx
exact (hf.map_centerMass_le hw₀ (by positivity) <| subset_convexHull _ _).trans
(centerMass_le_sup hw₀ <| by positivity)
|
/-
Copyright (c) 2019 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca, Paul Lezeau, Junyan Xu
-/
import Mathlib.RingTheory.AdjoinRoot
import Mathlib.FieldTheory.Minpoly.Field
import Mathlib.RingTheory.Polynomial.GaussLemma
#align_import field_theory.minpoly.is_integrally_closed from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Minimal polynomials over a GCD monoid
This file specializes the theory of minpoly to the case of an algebra over a GCD monoid.
## Main results
* `minpoly.isIntegrallyClosed_eq_field_fractions`: For integrally closed domains, the minimal
polynomial over the ring is the same as the minimal polynomial over the fraction field.
* `minpoly.isIntegrallyClosed_dvd` : For integrally closed domains, the minimal polynomial divides
any primitive polynomial that has the integral element as root.
* `IsIntegrallyClosed.Minpoly.unique` : The minimal polynomial of an element `x` is
uniquely characterized by its defining property: if there is another monic polynomial of minimal
degree that has `x` as a root, then this polynomial is equal to the minimal polynomial of `x`.
-/
open scoped Classical Polynomial
open Polynomial Set Function minpoly
namespace minpoly
variable {R S : Type*} [CommRing R] [CommRing S] [IsDomain R] [Algebra R S]
section
variable (K L : Type*) [Field K] [Algebra R K] [IsFractionRing R K] [CommRing L] [Nontrivial L]
[Algebra R L] [Algebra S L] [Algebra K L] [IsScalarTower R K L] [IsScalarTower R S L]
variable [IsIntegrallyClosed R]
/-- For integrally closed domains, the minimal polynomial over the ring is the same as the minimal
polynomial over the fraction field. See `minpoly.isIntegrallyClosed_eq_field_fractions'` if
`S` is already a `K`-algebra. -/
theorem isIntegrallyClosed_eq_field_fractions [IsDomain S] {s : S} (hs : IsIntegral R s) :
minpoly K (algebraMap S L s) = (minpoly R s).map (algebraMap R K) := by
refine (eq_of_irreducible_of_monic ?_ ?_ ?_).symm
· exact ((monic hs).irreducible_iff_irreducible_map_fraction_map).1 (irreducible hs)
· rw [aeval_map_algebraMap, aeval_algebraMap_apply, aeval, map_zero]
· exact (monic hs).map _
#align minpoly.is_integrally_closed_eq_field_fractions minpoly.isIntegrallyClosed_eq_field_fractions
/-- For integrally closed domains, the minimal polynomial over the ring is the same as the minimal
polynomial over the fraction field. Compared to `minpoly.isIntegrallyClosed_eq_field_fractions`,
this version is useful if the element is in a ring that is already a `K`-algebra. -/
theorem isIntegrallyClosed_eq_field_fractions' [IsDomain S] [Algebra K S] [IsScalarTower R K S]
{s : S} (hs : IsIntegral R s) : minpoly K s = (minpoly R s).map (algebraMap R K) := by
let L := FractionRing S
rw [← isIntegrallyClosed_eq_field_fractions K L hs, algebraMap_eq (IsFractionRing.injective S L)]
#align minpoly.is_integrally_closed_eq_field_fractions' minpoly.isIntegrallyClosed_eq_field_fractions'
end
variable [IsDomain S] [NoZeroSMulDivisors R S]
variable [IsIntegrallyClosed R]
/-- For integrally closed rings, the minimal polynomial divides any polynomial that has the
integral element as root. See also `minpoly.dvd` which relaxes the assumptions on `S`
in exchange for stronger assumptions on `R`. -/
| Mathlib/FieldTheory/Minpoly/IsIntegrallyClosed.lean | 75 | 92 | theorem isIntegrallyClosed_dvd {s : S} (hs : IsIntegral R s) {p : R[X]}
(hp : Polynomial.aeval s p = 0) : minpoly R s ∣ p := by |
let K := FractionRing R
let L := FractionRing S
let _ : Algebra K L := FractionRing.liftAlgebra R L
have := FractionRing.isScalarTower_liftAlgebra R L
have : minpoly K (algebraMap S L s) ∣ map (algebraMap R K) (p %ₘ minpoly R s) := by
rw [map_modByMonic _ (minpoly.monic hs), modByMonic_eq_sub_mul_div]
· refine dvd_sub (minpoly.dvd K (algebraMap S L s) ?_) ?_
· rw [← map_aeval_eq_aeval_map, hp, map_zero]
rw [← IsScalarTower.algebraMap_eq, ← IsScalarTower.algebraMap_eq]
apply dvd_mul_of_dvd_left
rw [isIntegrallyClosed_eq_field_fractions K L hs]
exact Monic.map _ (minpoly.monic hs)
rw [isIntegrallyClosed_eq_field_fractions _ _ hs,
map_dvd_map (algebraMap R K) (IsFractionRing.injective R K) (minpoly.monic hs)] at this
rw [← modByMonic_eq_zero_iff_dvd (minpoly.monic hs)]
exact Polynomial.eq_zero_of_dvd_of_degree_lt this (degree_modByMonic_lt p <| minpoly.monic hs)
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Algebra.Group.Indicator
import Mathlib.Data.Finset.Piecewise
import Mathlib.Data.Finset.Preimage
#align_import algebra.big_operators.basic from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# Big operators
In this file we define products and sums indexed by finite sets (specifically, `Finset`).
## Notation
We introduce the following notation.
Let `s` be a `Finset α`, and `f : α → β` a function.
* `∏ x ∈ s, f x` is notation for `Finset.prod s f` (assuming `β` is a `CommMonoid`)
* `∑ x ∈ s, f x` is notation for `Finset.sum s f` (assuming `β` is an `AddCommMonoid`)
* `∏ x, f x` is notation for `Finset.prod Finset.univ f`
(assuming `α` is a `Fintype` and `β` is a `CommMonoid`)
* `∑ x, f x` is notation for `Finset.sum Finset.univ f`
(assuming `α` is a `Fintype` and `β` is an `AddCommMonoid`)
## Implementation Notes
The first arguments in all definitions and lemmas is the codomain of the function of the big
operator. This is necessary for the heuristic in `@[to_additive]`.
See the documentation of `to_additive.attr` for more information.
-/
-- TODO
-- assert_not_exists AddCommMonoidWithOne
assert_not_exists MonoidWithZero
assert_not_exists MulAction
variable {ι κ α β γ : Type*}
open Fin Function
namespace Finset
/-- `∏ x ∈ s, f x` is the product of `f x`
as `x` ranges over the elements of the finite set `s`.
-/
@[to_additive "`∑ x ∈ s, f x` is the sum of `f x` as `x` ranges over the elements
of the finite set `s`."]
protected def prod [CommMonoid β] (s : Finset α) (f : α → β) : β :=
(s.1.map f).prod
#align finset.prod Finset.prod
#align finset.sum Finset.sum
@[to_additive (attr := simp)]
theorem prod_mk [CommMonoid β] (s : Multiset α) (hs : s.Nodup) (f : α → β) :
(⟨s, hs⟩ : Finset α).prod f = (s.map f).prod :=
rfl
#align finset.prod_mk Finset.prod_mk
#align finset.sum_mk Finset.sum_mk
@[to_additive (attr := simp)]
theorem prod_val [CommMonoid α] (s : Finset α) : s.1.prod = s.prod id := by
rw [Finset.prod, Multiset.map_id]
#align finset.prod_val Finset.prod_val
#align finset.sum_val Finset.sum_val
end Finset
library_note "operator precedence of big operators"/--
There is no established mathematical convention
for the operator precedence of big operators like `∏` and `∑`.
We will have to make a choice.
Online discussions, such as https://math.stackexchange.com/q/185538/30839
seem to suggest that `∏` and `∑` should have the same precedence,
and that this should be somewhere between `*` and `+`.
The latter have precedence levels `70` and `65` respectively,
and we therefore choose the level `67`.
In practice, this means that parentheses should be placed as follows:
```lean
∑ k ∈ K, (a k + b k) = ∑ k ∈ K, a k + ∑ k ∈ K, b k →
∏ k ∈ K, a k * b k = (∏ k ∈ K, a k) * (∏ k ∈ K, b k)
```
(Example taken from page 490 of Knuth's *Concrete Mathematics*.)
-/
namespace BigOperators
open Batteries.ExtendedBinder Lean Meta
-- TODO: contribute this modification back to `extBinder`
/-- A `bigOpBinder` is like an `extBinder` and has the form `x`, `x : ty`, or `x pred`
where `pred` is a `binderPred` like `< 2`.
Unlike `extBinder`, `x` is a term. -/
syntax bigOpBinder := term:max ((" : " term) <|> binderPred)?
/-- A BigOperator binder in parentheses -/
syntax bigOpBinderParenthesized := " (" bigOpBinder ")"
/-- A list of parenthesized binders -/
syntax bigOpBinderCollection := bigOpBinderParenthesized+
/-- A single (unparenthesized) binder, or a list of parenthesized binders -/
syntax bigOpBinders := bigOpBinderCollection <|> (ppSpace bigOpBinder)
/-- Collects additional binder/Finset pairs for the given `bigOpBinder`.
Note: this is not extensible at the moment, unlike the usual `bigOpBinder` expansions. -/
def processBigOpBinder (processed : (Array (Term × Term)))
(binder : TSyntax ``bigOpBinder) : MacroM (Array (Term × Term)) :=
set_option hygiene false in
withRef binder do
match binder with
| `(bigOpBinder| $x:term) =>
match x with
| `(($a + $b = $n)) => -- Maybe this is too cute.
return processed |>.push (← `(⟨$a, $b⟩), ← `(Finset.Nat.antidiagonal $n))
| _ => return processed |>.push (x, ← ``(Finset.univ))
| `(bigOpBinder| $x : $t) => return processed |>.push (x, ← ``((Finset.univ : Finset $t)))
| `(bigOpBinder| $x ∈ $s) => return processed |>.push (x, ← `(finset% $s))
| `(bigOpBinder| $x < $n) => return processed |>.push (x, ← `(Finset.Iio $n))
| `(bigOpBinder| $x ≤ $n) => return processed |>.push (x, ← `(Finset.Iic $n))
| `(bigOpBinder| $x > $n) => return processed |>.push (x, ← `(Finset.Ioi $n))
| `(bigOpBinder| $x ≥ $n) => return processed |>.push (x, ← `(Finset.Ici $n))
| _ => Macro.throwUnsupported
/-- Collects the binder/Finset pairs for the given `bigOpBinders`. -/
def processBigOpBinders (binders : TSyntax ``bigOpBinders) :
MacroM (Array (Term × Term)) :=
match binders with
| `(bigOpBinders| $b:bigOpBinder) => processBigOpBinder #[] b
| `(bigOpBinders| $[($bs:bigOpBinder)]*) => bs.foldlM processBigOpBinder #[]
| _ => Macro.throwUnsupported
/-- Collect the binderIdents into a `⟨...⟩` expression. -/
def bigOpBindersPattern (processed : (Array (Term × Term))) :
MacroM Term := do
let ts := processed.map Prod.fst
if ts.size == 1 then
return ts[0]!
else
`(⟨$ts,*⟩)
/-- Collect the terms into a product of sets. -/
def bigOpBindersProd (processed : (Array (Term × Term))) :
MacroM Term := do
if processed.isEmpty then
`((Finset.univ : Finset Unit))
else if processed.size == 1 then
return processed[0]!.2
else
processed.foldrM (fun s p => `(SProd.sprod $(s.2) $p)) processed.back.2
(start := processed.size - 1)
/--
- `∑ x, f x` is notation for `Finset.sum Finset.univ f`. It is the sum of `f x`,
where `x` ranges over the finite domain of `f`.
- `∑ x ∈ s, f x` is notation for `Finset.sum s f`. It is the sum of `f x`,
where `x` ranges over the finite set `s` (either a `Finset` or a `Set` with a `Fintype` instance).
- `∑ x ∈ s with p x, f x` is notation for `Finset.sum (Finset.filter p s) f`.
- `∑ (x ∈ s) (y ∈ t), f x y` is notation for `Finset.sum (s ×ˢ t) (fun ⟨x, y⟩ ↦ f x y)`.
These support destructuring, for example `∑ ⟨x, y⟩ ∈ s ×ˢ t, f x y`.
Notation: `"∑" bigOpBinders* ("with" term)? "," term` -/
syntax (name := bigsum) "∑ " bigOpBinders ("with " term)? ", " term:67 : term
/--
- `∏ x, f x` is notation for `Finset.prod Finset.univ f`. It is the product of `f x`,
where `x` ranges over the finite domain of `f`.
- `∏ x ∈ s, f x` is notation for `Finset.prod s f`. It is the product of `f x`,
where `x` ranges over the finite set `s` (either a `Finset` or a `Set` with a `Fintype` instance).
- `∏ x ∈ s with p x, f x` is notation for `Finset.prod (Finset.filter p s) f`.
- `∏ (x ∈ s) (y ∈ t), f x y` is notation for `Finset.prod (s ×ˢ t) (fun ⟨x, y⟩ ↦ f x y)`.
These support destructuring, for example `∏ ⟨x, y⟩ ∈ s ×ˢ t, f x y`.
Notation: `"∏" bigOpBinders* ("with" term)? "," term` -/
syntax (name := bigprod) "∏ " bigOpBinders ("with " term)? ", " term:67 : term
macro_rules (kind := bigsum)
| `(∑ $bs:bigOpBinders $[with $p?]?, $v) => do
let processed ← processBigOpBinders bs
let x ← bigOpBindersPattern processed
let s ← bigOpBindersProd processed
match p? with
| some p => `(Finset.sum (Finset.filter (fun $x ↦ $p) $s) (fun $x ↦ $v))
| none => `(Finset.sum $s (fun $x ↦ $v))
macro_rules (kind := bigprod)
| `(∏ $bs:bigOpBinders $[with $p?]?, $v) => do
let processed ← processBigOpBinders bs
let x ← bigOpBindersPattern processed
let s ← bigOpBindersProd processed
match p? with
| some p => `(Finset.prod (Finset.filter (fun $x ↦ $p) $s) (fun $x ↦ $v))
| none => `(Finset.prod $s (fun $x ↦ $v))
/-- (Deprecated, use `∑ x ∈ s, f x`)
`∑ x in s, f x` is notation for `Finset.sum s f`. It is the sum of `f x`,
where `x` ranges over the finite set `s`. -/
syntax (name := bigsumin) "∑ " extBinder " in " term ", " term:67 : term
macro_rules (kind := bigsumin)
| `(∑ $x:ident in $s, $r) => `(∑ $x:ident ∈ $s, $r)
| `(∑ $x:ident : $t in $s, $r) => `(∑ $x:ident ∈ ($s : Finset $t), $r)
/-- (Deprecated, use `∏ x ∈ s, f x`)
`∏ x in s, f x` is notation for `Finset.prod s f`. It is the product of `f x`,
where `x` ranges over the finite set `s`. -/
syntax (name := bigprodin) "∏ " extBinder " in " term ", " term:67 : term
macro_rules (kind := bigprodin)
| `(∏ $x:ident in $s, $r) => `(∏ $x:ident ∈ $s, $r)
| `(∏ $x:ident : $t in $s, $r) => `(∏ $x:ident ∈ ($s : Finset $t), $r)
open Lean Meta Parser.Term PrettyPrinter.Delaborator SubExpr
open Batteries.ExtendedBinder
/-- Delaborator for `Finset.prod`. The `pp.piBinderTypes` option controls whether
to show the domain type when the product is over `Finset.univ`. -/
@[delab app.Finset.prod] def delabFinsetProd : Delab :=
whenPPOption getPPNotation <| withOverApp 5 <| do
let #[_, _, _, s, f] := (← getExpr).getAppArgs | failure
guard <| f.isLambda
let ppDomain ← getPPOption getPPPiBinderTypes
let (i, body) ← withAppArg <| withBindingBodyUnusedName fun i => do
return (i, ← delab)
if s.isAppOfArity ``Finset.univ 2 then
let binder ←
if ppDomain then
let ty ← withNaryArg 0 delab
`(bigOpBinder| $(.mk i):ident : $ty)
else
`(bigOpBinder| $(.mk i):ident)
`(∏ $binder:bigOpBinder, $body)
else
let ss ← withNaryArg 3 <| delab
`(∏ $(.mk i):ident ∈ $ss, $body)
/-- Delaborator for `Finset.sum`. The `pp.piBinderTypes` option controls whether
to show the domain type when the sum is over `Finset.univ`. -/
@[delab app.Finset.sum] def delabFinsetSum : Delab :=
whenPPOption getPPNotation <| withOverApp 5 <| do
let #[_, _, _, s, f] := (← getExpr).getAppArgs | failure
guard <| f.isLambda
let ppDomain ← getPPOption getPPPiBinderTypes
let (i, body) ← withAppArg <| withBindingBodyUnusedName fun i => do
return (i, ← delab)
if s.isAppOfArity ``Finset.univ 2 then
let binder ←
if ppDomain then
let ty ← withNaryArg 0 delab
`(bigOpBinder| $(.mk i):ident : $ty)
else
`(bigOpBinder| $(.mk i):ident)
`(∑ $binder:bigOpBinder, $body)
else
let ss ← withNaryArg 3 <| delab
`(∑ $(.mk i):ident ∈ $ss, $body)
end BigOperators
namespace Finset
variable {s s₁ s₂ : Finset α} {a : α} {f g : α → β}
@[to_additive]
theorem prod_eq_multiset_prod [CommMonoid β] (s : Finset α) (f : α → β) :
∏ x ∈ s, f x = (s.1.map f).prod :=
rfl
#align finset.prod_eq_multiset_prod Finset.prod_eq_multiset_prod
#align finset.sum_eq_multiset_sum Finset.sum_eq_multiset_sum
@[to_additive (attr := simp)]
lemma prod_map_val [CommMonoid β] (s : Finset α) (f : α → β) : (s.1.map f).prod = ∏ a ∈ s, f a :=
rfl
#align finset.prod_map_val Finset.prod_map_val
#align finset.sum_map_val Finset.sum_map_val
@[to_additive]
theorem prod_eq_fold [CommMonoid β] (s : Finset α) (f : α → β) :
∏ x ∈ s, f x = s.fold ((· * ·) : β → β → β) 1 f :=
rfl
#align finset.prod_eq_fold Finset.prod_eq_fold
#align finset.sum_eq_fold Finset.sum_eq_fold
@[simp]
theorem sum_multiset_singleton (s : Finset α) : (s.sum fun x => {x}) = s.val := by
simp only [sum_eq_multiset_sum, Multiset.sum_map_singleton]
#align finset.sum_multiset_singleton Finset.sum_multiset_singleton
end Finset
@[to_additive (attr := simp)]
theorem map_prod [CommMonoid β] [CommMonoid γ] {G : Type*} [FunLike G β γ] [MonoidHomClass G β γ]
(g : G) (f : α → β) (s : Finset α) : g (∏ x ∈ s, f x) = ∏ x ∈ s, g (f x) := by
simp only [Finset.prod_eq_multiset_prod, map_multiset_prod, Multiset.map_map]; rfl
#align map_prod map_prod
#align map_sum map_sum
@[to_additive]
theorem MonoidHom.coe_finset_prod [MulOneClass β] [CommMonoid γ] (f : α → β →* γ) (s : Finset α) :
⇑(∏ x ∈ s, f x) = ∏ x ∈ s, ⇑(f x) :=
map_prod (MonoidHom.coeFn β γ) _ _
#align monoid_hom.coe_finset_prod MonoidHom.coe_finset_prod
#align add_monoid_hom.coe_finset_sum AddMonoidHom.coe_finset_sum
/-- See also `Finset.prod_apply`, with the same conclusion but with the weaker hypothesis
`f : α → β → γ` -/
@[to_additive (attr := simp)
"See also `Finset.sum_apply`, with the same conclusion but with the weaker hypothesis
`f : α → β → γ`"]
theorem MonoidHom.finset_prod_apply [MulOneClass β] [CommMonoid γ] (f : α → β →* γ) (s : Finset α)
(b : β) : (∏ x ∈ s, f x) b = ∏ x ∈ s, f x b :=
map_prod (MonoidHom.eval b) _ _
#align monoid_hom.finset_prod_apply MonoidHom.finset_prod_apply
#align add_monoid_hom.finset_sum_apply AddMonoidHom.finset_sum_apply
variable {s s₁ s₂ : Finset α} {a : α} {f g : α → β}
namespace Finset
section CommMonoid
variable [CommMonoid β]
@[to_additive (attr := simp)]
theorem prod_empty : ∏ x ∈ ∅, f x = 1 :=
rfl
#align finset.prod_empty Finset.prod_empty
#align finset.sum_empty Finset.sum_empty
@[to_additive]
theorem prod_of_empty [IsEmpty α] (s : Finset α) : ∏ i ∈ s, f i = 1 := by
rw [eq_empty_of_isEmpty s, prod_empty]
#align finset.prod_of_empty Finset.prod_of_empty
#align finset.sum_of_empty Finset.sum_of_empty
@[to_additive (attr := simp)]
theorem prod_cons (h : a ∉ s) : ∏ x ∈ cons a s h, f x = f a * ∏ x ∈ s, f x :=
fold_cons h
#align finset.prod_cons Finset.prod_cons
#align finset.sum_cons Finset.sum_cons
@[to_additive (attr := simp)]
theorem prod_insert [DecidableEq α] : a ∉ s → ∏ x ∈ insert a s, f x = f a * ∏ x ∈ s, f x :=
fold_insert
#align finset.prod_insert Finset.prod_insert
#align finset.sum_insert Finset.sum_insert
/-- The product of `f` over `insert a s` is the same as
the product over `s`, as long as `a` is in `s` or `f a = 1`. -/
@[to_additive (attr := simp) "The sum of `f` over `insert a s` is the same as
the sum over `s`, as long as `a` is in `s` or `f a = 0`."]
theorem prod_insert_of_eq_one_if_not_mem [DecidableEq α] (h : a ∉ s → f a = 1) :
∏ x ∈ insert a s, f x = ∏ x ∈ s, f x := by
by_cases hm : a ∈ s
· simp_rw [insert_eq_of_mem hm]
· rw [prod_insert hm, h hm, one_mul]
#align finset.prod_insert_of_eq_one_if_not_mem Finset.prod_insert_of_eq_one_if_not_mem
#align finset.sum_insert_of_eq_zero_if_not_mem Finset.sum_insert_of_eq_zero_if_not_mem
/-- The product of `f` over `insert a s` is the same as
the product over `s`, as long as `f a = 1`. -/
@[to_additive (attr := simp) "The sum of `f` over `insert a s` is the same as
the sum over `s`, as long as `f a = 0`."]
theorem prod_insert_one [DecidableEq α] (h : f a = 1) : ∏ x ∈ insert a s, f x = ∏ x ∈ s, f x :=
prod_insert_of_eq_one_if_not_mem fun _ => h
#align finset.prod_insert_one Finset.prod_insert_one
#align finset.sum_insert_zero Finset.sum_insert_zero
@[to_additive]
theorem prod_insert_div {M : Type*} [CommGroup M] [DecidableEq α] (ha : a ∉ s) {f : α → M} :
(∏ x ∈ insert a s, f x) / f a = ∏ x ∈ s, f x := by simp [ha]
@[to_additive (attr := simp)]
theorem prod_singleton (f : α → β) (a : α) : ∏ x ∈ singleton a, f x = f a :=
Eq.trans fold_singleton <| mul_one _
#align finset.prod_singleton Finset.prod_singleton
#align finset.sum_singleton Finset.sum_singleton
@[to_additive]
theorem prod_pair [DecidableEq α] {a b : α} (h : a ≠ b) :
(∏ x ∈ ({a, b} : Finset α), f x) = f a * f b := by
rw [prod_insert (not_mem_singleton.2 h), prod_singleton]
#align finset.prod_pair Finset.prod_pair
#align finset.sum_pair Finset.sum_pair
@[to_additive (attr := simp)]
theorem prod_const_one : (∏ _x ∈ s, (1 : β)) = 1 := by
simp only [Finset.prod, Multiset.map_const', Multiset.prod_replicate, one_pow]
#align finset.prod_const_one Finset.prod_const_one
#align finset.sum_const_zero Finset.sum_const_zero
@[to_additive (attr := simp)]
theorem prod_image [DecidableEq α] {s : Finset γ} {g : γ → α} :
(∀ x ∈ s, ∀ y ∈ s, g x = g y → x = y) → ∏ x ∈ s.image g, f x = ∏ x ∈ s, f (g x) :=
fold_image
#align finset.prod_image Finset.prod_image
#align finset.sum_image Finset.sum_image
@[to_additive (attr := simp)]
theorem prod_map (s : Finset α) (e : α ↪ γ) (f : γ → β) :
∏ x ∈ s.map e, f x = ∏ x ∈ s, f (e x) := by
rw [Finset.prod, Finset.map_val, Multiset.map_map]; rfl
#align finset.prod_map Finset.prod_map
#align finset.sum_map Finset.sum_map
@[to_additive]
lemma prod_attach (s : Finset α) (f : α → β) : ∏ x ∈ s.attach, f x = ∏ x ∈ s, f x := by
classical rw [← prod_image Subtype.coe_injective.injOn, attach_image_val]
#align finset.prod_attach Finset.prod_attach
#align finset.sum_attach Finset.sum_attach
@[to_additive (attr := congr)]
theorem prod_congr (h : s₁ = s₂) : (∀ x ∈ s₂, f x = g x) → s₁.prod f = s₂.prod g := by
rw [h]; exact fold_congr
#align finset.prod_congr Finset.prod_congr
#align finset.sum_congr Finset.sum_congr
@[to_additive]
theorem prod_eq_one {f : α → β} {s : Finset α} (h : ∀ x ∈ s, f x = 1) : ∏ x ∈ s, f x = 1 :=
calc
∏ x ∈ s, f x = ∏ _x ∈ s, 1 := Finset.prod_congr rfl h
_ = 1 := Finset.prod_const_one
#align finset.prod_eq_one Finset.prod_eq_one
#align finset.sum_eq_zero Finset.sum_eq_zero
@[to_additive]
theorem prod_disjUnion (h) :
∏ x ∈ s₁.disjUnion s₂ h, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x := by
refine Eq.trans ?_ (fold_disjUnion h)
rw [one_mul]
rfl
#align finset.prod_disj_union Finset.prod_disjUnion
#align finset.sum_disj_union Finset.sum_disjUnion
@[to_additive]
theorem prod_disjiUnion (s : Finset ι) (t : ι → Finset α) (h) :
∏ x ∈ s.disjiUnion t h, f x = ∏ i ∈ s, ∏ x ∈ t i, f x := by
refine Eq.trans ?_ (fold_disjiUnion h)
dsimp [Finset.prod, Multiset.prod, Multiset.fold, Finset.disjUnion, Finset.fold]
congr
exact prod_const_one.symm
#align finset.prod_disj_Union Finset.prod_disjiUnion
#align finset.sum_disj_Union Finset.sum_disjiUnion
@[to_additive]
theorem prod_union_inter [DecidableEq α] :
(∏ x ∈ s₁ ∪ s₂, f x) * ∏ x ∈ s₁ ∩ s₂, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x :=
fold_union_inter
#align finset.prod_union_inter Finset.prod_union_inter
#align finset.sum_union_inter Finset.sum_union_inter
@[to_additive]
theorem prod_union [DecidableEq α] (h : Disjoint s₁ s₂) :
∏ x ∈ s₁ ∪ s₂, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x := by
rw [← prod_union_inter, disjoint_iff_inter_eq_empty.mp h]; exact (mul_one _).symm
#align finset.prod_union Finset.prod_union
#align finset.sum_union Finset.sum_union
@[to_additive]
theorem prod_filter_mul_prod_filter_not
(s : Finset α) (p : α → Prop) [DecidablePred p] [∀ x, Decidable (¬p x)] (f : α → β) :
(∏ x ∈ s.filter p, f x) * ∏ x ∈ s.filter fun x => ¬p x, f x = ∏ x ∈ s, f x := by
have := Classical.decEq α
rw [← prod_union (disjoint_filter_filter_neg s s p), filter_union_filter_neg_eq]
#align finset.prod_filter_mul_prod_filter_not Finset.prod_filter_mul_prod_filter_not
#align finset.sum_filter_add_sum_filter_not Finset.sum_filter_add_sum_filter_not
section ToList
@[to_additive (attr := simp)]
theorem prod_to_list (s : Finset α) (f : α → β) : (s.toList.map f).prod = s.prod f := by
rw [Finset.prod, ← Multiset.prod_coe, ← Multiset.map_coe, Finset.coe_toList]
#align finset.prod_to_list Finset.prod_to_list
#align finset.sum_to_list Finset.sum_to_list
end ToList
@[to_additive]
theorem _root_.Equiv.Perm.prod_comp (σ : Equiv.Perm α) (s : Finset α) (f : α → β)
(hs : { a | σ a ≠ a } ⊆ s) : (∏ x ∈ s, f (σ x)) = ∏ x ∈ s, f x := by
convert (prod_map s σ.toEmbedding f).symm
exact (map_perm hs).symm
#align equiv.perm.prod_comp Equiv.Perm.prod_comp
#align equiv.perm.sum_comp Equiv.Perm.sum_comp
@[to_additive]
theorem _root_.Equiv.Perm.prod_comp' (σ : Equiv.Perm α) (s : Finset α) (f : α → α → β)
(hs : { a | σ a ≠ a } ⊆ s) : (∏ x ∈ s, f (σ x) x) = ∏ x ∈ s, f x (σ.symm x) := by
convert σ.prod_comp s (fun x => f x (σ.symm x)) hs
rw [Equiv.symm_apply_apply]
#align equiv.perm.prod_comp' Equiv.Perm.prod_comp'
#align equiv.perm.sum_comp' Equiv.Perm.sum_comp'
/-- A product over all subsets of `s ∪ {x}` is obtained by multiplying the product over all subsets
of `s`, and over all subsets of `s` to which one adds `x`. -/
@[to_additive "A sum over all subsets of `s ∪ {x}` is obtained by summing the sum over all subsets
of `s`, and over all subsets of `s` to which one adds `x`."]
lemma prod_powerset_insert [DecidableEq α] (ha : a ∉ s) (f : Finset α → β) :
∏ t ∈ (insert a s).powerset, f t =
(∏ t ∈ s.powerset, f t) * ∏ t ∈ s.powerset, f (insert a t) := by
rw [powerset_insert, prod_union, prod_image]
· exact insert_erase_invOn.2.injOn.mono fun t ht ↦ not_mem_mono (mem_powerset.1 ht) ha
· aesop (add simp [disjoint_left, insert_subset_iff])
#align finset.prod_powerset_insert Finset.prod_powerset_insert
#align finset.sum_powerset_insert Finset.sum_powerset_insert
/-- A product over all subsets of `s ∪ {x}` is obtained by multiplying the product over all subsets
of `s`, and over all subsets of `s` to which one adds `x`. -/
@[to_additive "A sum over all subsets of `s ∪ {x}` is obtained by summing the sum over all subsets
of `s`, and over all subsets of `s` to which one adds `x`."]
lemma prod_powerset_cons (ha : a ∉ s) (f : Finset α → β) :
∏ t ∈ (s.cons a ha).powerset, f t = (∏ t ∈ s.powerset, f t) *
∏ t ∈ s.powerset.attach, f (cons a t $ not_mem_mono (mem_powerset.1 t.2) ha) := by
classical
simp_rw [cons_eq_insert]
rw [prod_powerset_insert ha, prod_attach _ fun t ↦ f (insert a t)]
/-- A product over `powerset s` is equal to the double product over sets of subsets of `s` with
`card s = k`, for `k = 1, ..., card s`. -/
@[to_additive "A sum over `powerset s` is equal to the double sum over sets of subsets of `s` with
`card s = k`, for `k = 1, ..., card s`"]
lemma prod_powerset (s : Finset α) (f : Finset α → β) :
∏ t ∈ powerset s, f t = ∏ j ∈ range (card s + 1), ∏ t ∈ powersetCard j s, f t := by
rw [powerset_card_disjiUnion, prod_disjiUnion]
#align finset.prod_powerset Finset.prod_powerset
#align finset.sum_powerset Finset.sum_powerset
end CommMonoid
end Finset
section
open Finset
variable [Fintype α] [CommMonoid β]
@[to_additive]
theorem IsCompl.prod_mul_prod {s t : Finset α} (h : IsCompl s t) (f : α → β) :
(∏ i ∈ s, f i) * ∏ i ∈ t, f i = ∏ i, f i :=
(Finset.prod_disjUnion h.disjoint).symm.trans <| by
classical rw [Finset.disjUnion_eq_union, ← Finset.sup_eq_union, h.sup_eq_top]; rfl
#align is_compl.prod_mul_prod IsCompl.prod_mul_prod
#align is_compl.sum_add_sum IsCompl.sum_add_sum
end
namespace Finset
section CommMonoid
variable [CommMonoid β]
/-- Multiplying the products of a function over `s` and over `sᶜ` gives the whole product.
For a version expressed with subtypes, see `Fintype.prod_subtype_mul_prod_subtype`. -/
@[to_additive "Adding the sums of a function over `s` and over `sᶜ` gives the whole sum.
For a version expressed with subtypes, see `Fintype.sum_subtype_add_sum_subtype`. "]
theorem prod_mul_prod_compl [Fintype α] [DecidableEq α] (s : Finset α) (f : α → β) :
(∏ i ∈ s, f i) * ∏ i ∈ sᶜ, f i = ∏ i, f i :=
IsCompl.prod_mul_prod isCompl_compl f
#align finset.prod_mul_prod_compl Finset.prod_mul_prod_compl
#align finset.sum_add_sum_compl Finset.sum_add_sum_compl
@[to_additive]
theorem prod_compl_mul_prod [Fintype α] [DecidableEq α] (s : Finset α) (f : α → β) :
(∏ i ∈ sᶜ, f i) * ∏ i ∈ s, f i = ∏ i, f i :=
(@isCompl_compl _ s _).symm.prod_mul_prod f
#align finset.prod_compl_mul_prod Finset.prod_compl_mul_prod
#align finset.sum_compl_add_sum Finset.sum_compl_add_sum
@[to_additive]
theorem prod_sdiff [DecidableEq α] (h : s₁ ⊆ s₂) :
(∏ x ∈ s₂ \ s₁, f x) * ∏ x ∈ s₁, f x = ∏ x ∈ s₂, f x := by
rw [← prod_union sdiff_disjoint, sdiff_union_of_subset h]
#align finset.prod_sdiff Finset.prod_sdiff
#align finset.sum_sdiff Finset.sum_sdiff
@[to_additive]
theorem prod_subset_one_on_sdiff [DecidableEq α] (h : s₁ ⊆ s₂) (hg : ∀ x ∈ s₂ \ s₁, g x = 1)
(hfg : ∀ x ∈ s₁, f x = g x) : ∏ i ∈ s₁, f i = ∏ i ∈ s₂, g i := by
rw [← prod_sdiff h, prod_eq_one hg, one_mul]
exact prod_congr rfl hfg
#align finset.prod_subset_one_on_sdiff Finset.prod_subset_one_on_sdiff
#align finset.sum_subset_zero_on_sdiff Finset.sum_subset_zero_on_sdiff
@[to_additive]
theorem prod_subset (h : s₁ ⊆ s₂) (hf : ∀ x ∈ s₂, x ∉ s₁ → f x = 1) :
∏ x ∈ s₁, f x = ∏ x ∈ s₂, f x :=
haveI := Classical.decEq α
prod_subset_one_on_sdiff h (by simpa) fun _ _ => rfl
#align finset.prod_subset Finset.prod_subset
#align finset.sum_subset Finset.sum_subset
@[to_additive (attr := simp)]
theorem prod_disj_sum (s : Finset α) (t : Finset γ) (f : Sum α γ → β) :
∏ x ∈ s.disjSum t, f x = (∏ x ∈ s, f (Sum.inl x)) * ∏ x ∈ t, f (Sum.inr x) := by
rw [← map_inl_disjUnion_map_inr, prod_disjUnion, prod_map, prod_map]
rfl
#align finset.prod_disj_sum Finset.prod_disj_sum
#align finset.sum_disj_sum Finset.sum_disj_sum
@[to_additive]
theorem prod_sum_elim (s : Finset α) (t : Finset γ) (f : α → β) (g : γ → β) :
∏ x ∈ s.disjSum t, Sum.elim f g x = (∏ x ∈ s, f x) * ∏ x ∈ t, g x := by simp
#align finset.prod_sum_elim Finset.prod_sum_elim
#align finset.sum_sum_elim Finset.sum_sum_elim
@[to_additive]
theorem prod_biUnion [DecidableEq α] {s : Finset γ} {t : γ → Finset α}
(hs : Set.PairwiseDisjoint (↑s) t) : ∏ x ∈ s.biUnion t, f x = ∏ x ∈ s, ∏ i ∈ t x, f i := by
rw [← disjiUnion_eq_biUnion _ _ hs, prod_disjiUnion]
#align finset.prod_bUnion Finset.prod_biUnion
#align finset.sum_bUnion Finset.sum_biUnion
/-- Product over a sigma type equals the product of fiberwise products. For rewriting
in the reverse direction, use `Finset.prod_sigma'`. -/
@[to_additive "Sum over a sigma type equals the sum of fiberwise sums. For rewriting
in the reverse direction, use `Finset.sum_sigma'`"]
theorem prod_sigma {σ : α → Type*} (s : Finset α) (t : ∀ a, Finset (σ a)) (f : Sigma σ → β) :
∏ x ∈ s.sigma t, f x = ∏ a ∈ s, ∏ s ∈ t a, f ⟨a, s⟩ := by
simp_rw [← disjiUnion_map_sigma_mk, prod_disjiUnion, prod_map, Function.Embedding.sigmaMk_apply]
#align finset.prod_sigma Finset.prod_sigma
#align finset.sum_sigma Finset.sum_sigma
@[to_additive]
theorem prod_sigma' {σ : α → Type*} (s : Finset α) (t : ∀ a, Finset (σ a)) (f : ∀ a, σ a → β) :
(∏ a ∈ s, ∏ s ∈ t a, f a s) = ∏ x ∈ s.sigma t, f x.1 x.2 :=
Eq.symm <| prod_sigma s t fun x => f x.1 x.2
#align finset.prod_sigma' Finset.prod_sigma'
#align finset.sum_sigma' Finset.sum_sigma'
section bij
variable {ι κ α : Type*} [CommMonoid α] {s : Finset ι} {t : Finset κ} {f : ι → α} {g : κ → α}
/-- Reorder a product.
The difference with `Finset.prod_bij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.prod_nbij` is that the bijection is allowed to use membership of the
domain of the product, rather than being a non-dependent function. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_bij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.sum_nbij` is that the bijection is allowed to use membership of the
domain of the sum, rather than being a non-dependent function."]
theorem prod_bij (i : ∀ a ∈ s, κ) (hi : ∀ a ha, i a ha ∈ t)
(i_inj : ∀ a₁ ha₁ a₂ ha₂, i a₁ ha₁ = i a₂ ha₂ → a₁ = a₂)
(i_surj : ∀ b ∈ t, ∃ a ha, i a ha = b) (h : ∀ a ha, f a = g (i a ha)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x :=
congr_arg Multiset.prod (Multiset.map_eq_map_of_bij_of_nodup f g s.2 t.2 i hi i_inj i_surj h)
#align finset.prod_bij Finset.prod_bij
#align finset.sum_bij Finset.sum_bij
/-- Reorder a product.
The difference with `Finset.prod_bij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.prod_nbij'` is that the bijection and its inverse are allowed to use
membership of the domains of the products, rather than being non-dependent functions. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_bij` is that the bijection is specified with an inverse, rather than
as a surjective injection.
The difference with `Finset.sum_nbij'` is that the bijection and its inverse are allowed to use
membership of the domains of the sums, rather than being non-dependent functions."]
theorem prod_bij' (i : ∀ a ∈ s, κ) (j : ∀ a ∈ t, ι) (hi : ∀ a ha, i a ha ∈ t)
(hj : ∀ a ha, j a ha ∈ s) (left_inv : ∀ a ha, j (i a ha) (hi a ha) = a)
(right_inv : ∀ a ha, i (j a ha) (hj a ha) = a) (h : ∀ a ha, f a = g (i a ha)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x := by
refine prod_bij i hi (fun a1 h1 a2 h2 eq ↦ ?_) (fun b hb ↦ ⟨_, hj b hb, right_inv b hb⟩) h
rw [← left_inv a1 h1, ← left_inv a2 h2]
simp only [eq]
#align finset.prod_bij' Finset.prod_bij'
#align finset.sum_bij' Finset.sum_bij'
/-- Reorder a product.
The difference with `Finset.prod_nbij'` is that the bijection is specified as a surjective
injection, rather than by an inverse function.
The difference with `Finset.prod_bij` is that the bijection is a non-dependent function, rather than
being allowed to use membership of the domain of the product. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_nbij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.sum_bij` is that the bijection is a non-dependent function, rather than
being allowed to use membership of the domain of the sum."]
lemma prod_nbij (i : ι → κ) (hi : ∀ a ∈ s, i a ∈ t) (i_inj : (s : Set ι).InjOn i)
(i_surj : (s : Set ι).SurjOn i t) (h : ∀ a ∈ s, f a = g (i a)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x :=
prod_bij (fun a _ ↦ i a) hi i_inj (by simpa using i_surj) h
/-- Reorder a product.
The difference with `Finset.prod_nbij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.prod_bij'` is that the bijection and its inverse are non-dependent
functions, rather than being allowed to use membership of the domains of the products.
The difference with `Finset.prod_equiv` is that bijectivity is only required to hold on the domains
of the products, rather than on the entire types.
-/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_nbij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.sum_bij'` is that the bijection and its inverse are non-dependent
functions, rather than being allowed to use membership of the domains of the sums.
The difference with `Finset.sum_equiv` is that bijectivity is only required to hold on the domains
of the sums, rather than on the entire types."]
lemma prod_nbij' (i : ι → κ) (j : κ → ι) (hi : ∀ a ∈ s, i a ∈ t) (hj : ∀ a ∈ t, j a ∈ s)
(left_inv : ∀ a ∈ s, j (i a) = a) (right_inv : ∀ a ∈ t, i (j a) = a)
(h : ∀ a ∈ s, f a = g (i a)) : ∏ x ∈ s, f x = ∏ x ∈ t, g x :=
prod_bij' (fun a _ ↦ i a) (fun b _ ↦ j b) hi hj left_inv right_inv h
/-- Specialization of `Finset.prod_nbij'` that automatically fills in most arguments.
See `Fintype.prod_equiv` for the version where `s` and `t` are `univ`. -/
@[to_additive "`Specialization of `Finset.sum_nbij'` that automatically fills in most arguments.
See `Fintype.sum_equiv` for the version where `s` and `t` are `univ`."]
lemma prod_equiv (e : ι ≃ κ) (hst : ∀ i, i ∈ s ↔ e i ∈ t) (hfg : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ i ∈ t, g i := by refine prod_nbij' e e.symm ?_ ?_ ?_ ?_ hfg <;> simp [hst]
#align finset.equiv.prod_comp_finset Finset.prod_equiv
#align finset.equiv.sum_comp_finset Finset.sum_equiv
/-- Specialization of `Finset.prod_bij` that automatically fills in most arguments.
See `Fintype.prod_bijective` for the version where `s` and `t` are `univ`. -/
@[to_additive "`Specialization of `Finset.sum_bij` that automatically fills in most arguments.
See `Fintype.sum_bijective` for the version where `s` and `t` are `univ`."]
lemma prod_bijective (e : ι → κ) (he : e.Bijective) (hst : ∀ i, i ∈ s ↔ e i ∈ t)
(hfg : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ i ∈ t, g i := prod_equiv (.ofBijective e he) hst hfg
@[to_additive]
lemma prod_of_injOn (e : ι → κ) (he : Set.InjOn e s) (hest : Set.MapsTo e s t)
(h' : ∀ i ∈ t, i ∉ e '' s → g i = 1) (h : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ j ∈ t, g j := by
classical
exact (prod_nbij e (fun a ↦ mem_image_of_mem e) he (by simp [Set.surjOn_image]) h).trans <|
prod_subset (image_subset_iff.2 hest) <| by simpa using h'
variable [DecidableEq κ]
@[to_additive]
lemma prod_fiberwise_eq_prod_filter (s : Finset ι) (t : Finset κ) (g : ι → κ) (f : ι → α) :
∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s.filter fun i ↦ g i ∈ t, f i := by
rw [← prod_disjiUnion, disjiUnion_filter_eq]
@[to_additive]
lemma prod_fiberwise_eq_prod_filter' (s : Finset ι) (t : Finset κ) (g : ι → κ) (f : κ → α) :
∏ j ∈ t, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s.filter fun i ↦ g i ∈ t, f (g i) := by
calc
_ = ∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f (g i) :=
prod_congr rfl fun j _ ↦ prod_congr rfl fun i hi ↦ by rw [(mem_filter.1 hi).2]
_ = _ := prod_fiberwise_eq_prod_filter _ _ _ _
@[to_additive]
lemma prod_fiberwise_of_maps_to {g : ι → κ} (h : ∀ i ∈ s, g i ∈ t) (f : ι → α) :
∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s, f i := by
rw [← prod_disjiUnion, disjiUnion_filter_eq_of_maps_to h]
#align finset.prod_fiberwise_of_maps_to Finset.prod_fiberwise_of_maps_to
#align finset.sum_fiberwise_of_maps_to Finset.sum_fiberwise_of_maps_to
@[to_additive]
lemma prod_fiberwise_of_maps_to' {g : ι → κ} (h : ∀ i ∈ s, g i ∈ t) (f : κ → α) :
∏ j ∈ t, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s, f (g i) := by
calc
_ = ∏ y ∈ t, ∏ x ∈ s.filter fun x ↦ g x = y, f (g x) :=
prod_congr rfl fun y _ ↦ prod_congr rfl fun x hx ↦ by rw [(mem_filter.1 hx).2]
_ = _ := prod_fiberwise_of_maps_to h _
variable [Fintype κ]
@[to_additive]
lemma prod_fiberwise (s : Finset ι) (g : ι → κ) (f : ι → α) :
∏ j, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s, f i :=
prod_fiberwise_of_maps_to (fun _ _ ↦ mem_univ _) _
#align finset.prod_fiberwise Finset.prod_fiberwise
#align finset.sum_fiberwise Finset.sum_fiberwise
@[to_additive]
lemma prod_fiberwise' (s : Finset ι) (g : ι → κ) (f : κ → α) :
∏ j, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s, f (g i) :=
prod_fiberwise_of_maps_to' (fun _ _ ↦ mem_univ _) _
end bij
/-- Taking a product over `univ.pi t` is the same as taking the product over `Fintype.piFinset t`.
`univ.pi t` and `Fintype.piFinset t` are essentially the same `Finset`, but differ
in the type of their element, `univ.pi t` is a `Finset (Π a ∈ univ, t a)` and
`Fintype.piFinset t` is a `Finset (Π a, t a)`. -/
@[to_additive "Taking a sum over `univ.pi t` is the same as taking the sum over
`Fintype.piFinset t`. `univ.pi t` and `Fintype.piFinset t` are essentially the same `Finset`,
but differ in the type of their element, `univ.pi t` is a `Finset (Π a ∈ univ, t a)` and
`Fintype.piFinset t` is a `Finset (Π a, t a)`."]
lemma prod_univ_pi [DecidableEq ι] [Fintype ι] {κ : ι → Type*} (t : ∀ i, Finset (κ i))
(f : (∀ i ∈ (univ : Finset ι), κ i) → β) :
∏ x ∈ univ.pi t, f x = ∏ x ∈ Fintype.piFinset t, f fun a _ ↦ x a := by
apply prod_nbij' (fun x i ↦ x i $ mem_univ _) (fun x i _ ↦ x i) <;> simp
#align finset.prod_univ_pi Finset.prod_univ_pi
#align finset.sum_univ_pi Finset.sum_univ_pi
@[to_additive (attr := simp)]
lemma prod_diag [DecidableEq α] (s : Finset α) (f : α × α → β) :
∏ i ∈ s.diag, f i = ∏ i ∈ s, f (i, i) := by
apply prod_nbij' Prod.fst (fun i ↦ (i, i)) <;> simp
@[to_additive]
theorem prod_finset_product (r : Finset (γ × α)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : γ × α, p ∈ r ↔ p.1 ∈ s ∧ p.2 ∈ t p.1) {f : γ × α → β} :
∏ p ∈ r, f p = ∏ c ∈ s, ∏ a ∈ t c, f (c, a) := by
refine Eq.trans ?_ (prod_sigma s t fun p => f (p.1, p.2))
apply prod_equiv (Equiv.sigmaEquivProd _ _).symm <;> simp [h]
#align finset.prod_finset_product Finset.prod_finset_product
#align finset.sum_finset_product Finset.sum_finset_product
@[to_additive]
theorem prod_finset_product' (r : Finset (γ × α)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : γ × α, p ∈ r ↔ p.1 ∈ s ∧ p.2 ∈ t p.1) {f : γ → α → β} :
∏ p ∈ r, f p.1 p.2 = ∏ c ∈ s, ∏ a ∈ t c, f c a :=
prod_finset_product r s t h
#align finset.prod_finset_product' Finset.prod_finset_product'
#align finset.sum_finset_product' Finset.sum_finset_product'
@[to_additive]
theorem prod_finset_product_right (r : Finset (α × γ)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : α × γ, p ∈ r ↔ p.2 ∈ s ∧ p.1 ∈ t p.2) {f : α × γ → β} :
∏ p ∈ r, f p = ∏ c ∈ s, ∏ a ∈ t c, f (a, c) := by
refine Eq.trans ?_ (prod_sigma s t fun p => f (p.2, p.1))
apply prod_equiv ((Equiv.prodComm _ _).trans (Equiv.sigmaEquivProd _ _).symm) <;> simp [h]
#align finset.prod_finset_product_right Finset.prod_finset_product_right
#align finset.sum_finset_product_right Finset.sum_finset_product_right
@[to_additive]
theorem prod_finset_product_right' (r : Finset (α × γ)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : α × γ, p ∈ r ↔ p.2 ∈ s ∧ p.1 ∈ t p.2) {f : α → γ → β} :
∏ p ∈ r, f p.1 p.2 = ∏ c ∈ s, ∏ a ∈ t c, f a c :=
prod_finset_product_right r s t h
#align finset.prod_finset_product_right' Finset.prod_finset_product_right'
#align finset.sum_finset_product_right' Finset.sum_finset_product_right'
@[to_additive]
theorem prod_image' [DecidableEq α] {s : Finset γ} {g : γ → α} (h : γ → β)
(eq : ∀ c ∈ s, f (g c) = ∏ x ∈ s.filter fun c' => g c' = g c, h x) :
∏ x ∈ s.image g, f x = ∏ x ∈ s, h x :=
calc
∏ x ∈ s.image g, f x = ∏ x ∈ s.image g, ∏ x ∈ s.filter fun c' => g c' = x, h x :=
(prod_congr rfl) fun _x hx =>
let ⟨c, hcs, hc⟩ := mem_image.1 hx
hc ▸ eq c hcs
_ = ∏ x ∈ s, h x := prod_fiberwise_of_maps_to (fun _x => mem_image_of_mem g) _
#align finset.prod_image' Finset.prod_image'
#align finset.sum_image' Finset.sum_image'
@[to_additive]
theorem prod_mul_distrib : ∏ x ∈ s, f x * g x = (∏ x ∈ s, f x) * ∏ x ∈ s, g x :=
Eq.trans (by rw [one_mul]; rfl) fold_op_distrib
#align finset.prod_mul_distrib Finset.prod_mul_distrib
#align finset.sum_add_distrib Finset.sum_add_distrib
@[to_additive]
lemma prod_mul_prod_comm (f g h i : α → β) :
(∏ a ∈ s, f a * g a) * ∏ a ∈ s, h a * i a = (∏ a ∈ s, f a * h a) * ∏ a ∈ s, g a * i a := by
simp_rw [prod_mul_distrib, mul_mul_mul_comm]
@[to_additive]
theorem prod_product {s : Finset γ} {t : Finset α} {f : γ × α → β} :
∏ x ∈ s ×ˢ t, f x = ∏ x ∈ s, ∏ y ∈ t, f (x, y) :=
prod_finset_product (s ×ˢ t) s (fun _a => t) fun _p => mem_product
#align finset.prod_product Finset.prod_product
#align finset.sum_product Finset.sum_product
/-- An uncurried version of `Finset.prod_product`. -/
@[to_additive "An uncurried version of `Finset.sum_product`"]
theorem prod_product' {s : Finset γ} {t : Finset α} {f : γ → α → β} :
∏ x ∈ s ×ˢ t, f x.1 x.2 = ∏ x ∈ s, ∏ y ∈ t, f x y :=
prod_product
#align finset.prod_product' Finset.prod_product'
#align finset.sum_product' Finset.sum_product'
@[to_additive]
theorem prod_product_right {s : Finset γ} {t : Finset α} {f : γ × α → β} :
∏ x ∈ s ×ˢ t, f x = ∏ y ∈ t, ∏ x ∈ s, f (x, y) :=
prod_finset_product_right (s ×ˢ t) t (fun _a => s) fun _p => mem_product.trans and_comm
#align finset.prod_product_right Finset.prod_product_right
#align finset.sum_product_right Finset.sum_product_right
/-- An uncurried version of `Finset.prod_product_right`. -/
@[to_additive "An uncurried version of `Finset.sum_product_right`"]
theorem prod_product_right' {s : Finset γ} {t : Finset α} {f : γ → α → β} :
∏ x ∈ s ×ˢ t, f x.1 x.2 = ∏ y ∈ t, ∏ x ∈ s, f x y :=
prod_product_right
#align finset.prod_product_right' Finset.prod_product_right'
#align finset.sum_product_right' Finset.sum_product_right'
/-- Generalization of `Finset.prod_comm` to the case when the inner `Finset`s depend on the outer
variable. -/
@[to_additive "Generalization of `Finset.sum_comm` to the case when the inner `Finset`s depend on
the outer variable."]
theorem prod_comm' {s : Finset γ} {t : γ → Finset α} {t' : Finset α} {s' : α → Finset γ}
(h : ∀ x y, x ∈ s ∧ y ∈ t x ↔ x ∈ s' y ∧ y ∈ t') {f : γ → α → β} :
(∏ x ∈ s, ∏ y ∈ t x, f x y) = ∏ y ∈ t', ∏ x ∈ s' y, f x y := by
classical
have : ∀ z : γ × α, (z ∈ s.biUnion fun x => (t x).map <| Function.Embedding.sectr x _) ↔
z.1 ∈ s ∧ z.2 ∈ t z.1 := by
rintro ⟨x, y⟩
simp only [mem_biUnion, mem_map, Function.Embedding.sectr_apply, Prod.mk.injEq,
exists_eq_right, ← and_assoc]
exact
(prod_finset_product' _ _ _ this).symm.trans
((prod_finset_product_right' _ _ _) fun ⟨x, y⟩ => (this _).trans ((h x y).trans and_comm))
#align finset.prod_comm' Finset.prod_comm'
#align finset.sum_comm' Finset.sum_comm'
@[to_additive]
theorem prod_comm {s : Finset γ} {t : Finset α} {f : γ → α → β} :
(∏ x ∈ s, ∏ y ∈ t, f x y) = ∏ y ∈ t, ∏ x ∈ s, f x y :=
prod_comm' fun _ _ => Iff.rfl
#align finset.prod_comm Finset.prod_comm
#align finset.sum_comm Finset.sum_comm
@[to_additive]
theorem prod_hom_rel [CommMonoid γ] {r : β → γ → Prop} {f : α → β} {g : α → γ} {s : Finset α}
(h₁ : r 1 1) (h₂ : ∀ a b c, r b c → r (f a * b) (g a * c)) :
r (∏ x ∈ s, f x) (∏ x ∈ s, g x) := by
delta Finset.prod
apply Multiset.prod_hom_rel <;> assumption
#align finset.prod_hom_rel Finset.prod_hom_rel
#align finset.sum_hom_rel Finset.sum_hom_rel
@[to_additive]
theorem prod_filter_of_ne {p : α → Prop} [DecidablePred p] (hp : ∀ x ∈ s, f x ≠ 1 → p x) :
∏ x ∈ s.filter p, f x = ∏ x ∈ s, f x :=
(prod_subset (filter_subset _ _)) fun x => by
classical
rw [not_imp_comm, mem_filter]
exact fun h₁ h₂ => ⟨h₁, by simpa using hp _ h₁ h₂⟩
#align finset.prod_filter_of_ne Finset.prod_filter_of_ne
#align finset.sum_filter_of_ne Finset.sum_filter_of_ne
-- If we use `[DecidableEq β]` here, some rewrites fail because they find a wrong `Decidable`
-- instance first; `{∀ x, Decidable (f x ≠ 1)}` doesn't work with `rw ← prod_filter_ne_one`
@[to_additive]
theorem prod_filter_ne_one (s : Finset α) [∀ x, Decidable (f x ≠ 1)] :
∏ x ∈ s.filter fun x => f x ≠ 1, f x = ∏ x ∈ s, f x :=
prod_filter_of_ne fun _ _ => id
#align finset.prod_filter_ne_one Finset.prod_filter_ne_one
#align finset.sum_filter_ne_zero Finset.sum_filter_ne_zero
@[to_additive]
theorem prod_filter (p : α → Prop) [DecidablePred p] (f : α → β) :
∏ a ∈ s.filter p, f a = ∏ a ∈ s, if p a then f a else 1 :=
calc
∏ a ∈ s.filter p, f a = ∏ a ∈ s.filter p, if p a then f a else 1 :=
prod_congr rfl fun a h => by rw [if_pos]; simpa using (mem_filter.1 h).2
_ = ∏ a ∈ s, if p a then f a else 1 := by
{ refine prod_subset (filter_subset _ s) fun x hs h => ?_
rw [mem_filter, not_and] at h
exact if_neg (by simpa using h hs) }
#align finset.prod_filter Finset.prod_filter
#align finset.sum_filter Finset.sum_filter
@[to_additive]
theorem prod_eq_single_of_mem {s : Finset α} {f : α → β} (a : α) (h : a ∈ s)
(h₀ : ∀ b ∈ s, b ≠ a → f b = 1) : ∏ x ∈ s, f x = f a := by
haveI := Classical.decEq α
calc
∏ x ∈ s, f x = ∏ x ∈ {a}, f x := by
{ refine (prod_subset ?_ ?_).symm
· intro _ H
rwa [mem_singleton.1 H]
· simpa only [mem_singleton] }
_ = f a := prod_singleton _ _
#align finset.prod_eq_single_of_mem Finset.prod_eq_single_of_mem
#align finset.sum_eq_single_of_mem Finset.sum_eq_single_of_mem
@[to_additive]
theorem prod_eq_single {s : Finset α} {f : α → β} (a : α) (h₀ : ∀ b ∈ s, b ≠ a → f b = 1)
(h₁ : a ∉ s → f a = 1) : ∏ x ∈ s, f x = f a :=
haveI := Classical.decEq α
by_cases (prod_eq_single_of_mem a · h₀) fun this =>
(prod_congr rfl fun b hb => h₀ b hb <| by rintro rfl; exact this hb).trans <|
prod_const_one.trans (h₁ this).symm
#align finset.prod_eq_single Finset.prod_eq_single
#align finset.sum_eq_single Finset.sum_eq_single
@[to_additive]
lemma prod_union_eq_left [DecidableEq α] (hs : ∀ a ∈ s₂, a ∉ s₁ → f a = 1) :
∏ a ∈ s₁ ∪ s₂, f a = ∏ a ∈ s₁, f a :=
Eq.symm <|
prod_subset subset_union_left fun _a ha ha' ↦ hs _ ((mem_union.1 ha).resolve_left ha') ha'
@[to_additive]
lemma prod_union_eq_right [DecidableEq α] (hs : ∀ a ∈ s₁, a ∉ s₂ → f a = 1) :
∏ a ∈ s₁ ∪ s₂, f a = ∏ a ∈ s₂, f a := by rw [union_comm, prod_union_eq_left hs]
@[to_additive]
theorem prod_eq_mul_of_mem {s : Finset α} {f : α → β} (a b : α) (ha : a ∈ s) (hb : b ∈ s)
(hn : a ≠ b) (h₀ : ∀ c ∈ s, c ≠ a ∧ c ≠ b → f c = 1) : ∏ x ∈ s, f x = f a * f b := by
haveI := Classical.decEq α; let s' := ({a, b} : Finset α)
have hu : s' ⊆ s := by
refine insert_subset_iff.mpr ?_
apply And.intro ha
apply singleton_subset_iff.mpr hb
have hf : ∀ c ∈ s, c ∉ s' → f c = 1 := by
intro c hc hcs
apply h₀ c hc
apply not_or.mp
intro hab
apply hcs
rw [mem_insert, mem_singleton]
exact hab
rw [← prod_subset hu hf]
exact Finset.prod_pair hn
#align finset.prod_eq_mul_of_mem Finset.prod_eq_mul_of_mem
#align finset.sum_eq_add_of_mem Finset.sum_eq_add_of_mem
@[to_additive]
theorem prod_eq_mul {s : Finset α} {f : α → β} (a b : α) (hn : a ≠ b)
(h₀ : ∀ c ∈ s, c ≠ a ∧ c ≠ b → f c = 1) (ha : a ∉ s → f a = 1) (hb : b ∉ s → f b = 1) :
∏ x ∈ s, f x = f a * f b := by
haveI := Classical.decEq α; by_cases h₁ : a ∈ s <;> by_cases h₂ : b ∈ s
· exact prod_eq_mul_of_mem a b h₁ h₂ hn h₀
· rw [hb h₂, mul_one]
apply prod_eq_single_of_mem a h₁
exact fun c hc hca => h₀ c hc ⟨hca, ne_of_mem_of_not_mem hc h₂⟩
· rw [ha h₁, one_mul]
apply prod_eq_single_of_mem b h₂
exact fun c hc hcb => h₀ c hc ⟨ne_of_mem_of_not_mem hc h₁, hcb⟩
· rw [ha h₁, hb h₂, mul_one]
exact
_root_.trans
(prod_congr rfl fun c hc =>
h₀ c hc ⟨ne_of_mem_of_not_mem hc h₁, ne_of_mem_of_not_mem hc h₂⟩)
prod_const_one
#align finset.prod_eq_mul Finset.prod_eq_mul
#align finset.sum_eq_add Finset.sum_eq_add
-- Porting note: simpNF linter complains that LHS doesn't simplify, but it does
/-- A product over `s.subtype p` equals one over `s.filter p`. -/
@[to_additive (attr := simp, nolint simpNF)
"A sum over `s.subtype p` equals one over `s.filter p`."]
theorem prod_subtype_eq_prod_filter (f : α → β) {p : α → Prop} [DecidablePred p] :
∏ x ∈ s.subtype p, f x = ∏ x ∈ s.filter p, f x := by
conv_lhs => erw [← prod_map (s.subtype p) (Function.Embedding.subtype _) f]
exact prod_congr (subtype_map _) fun x _hx => rfl
#align finset.prod_subtype_eq_prod_filter Finset.prod_subtype_eq_prod_filter
#align finset.sum_subtype_eq_sum_filter Finset.sum_subtype_eq_sum_filter
/-- If all elements of a `Finset` satisfy the predicate `p`, a product
over `s.subtype p` equals that product over `s`. -/
@[to_additive "If all elements of a `Finset` satisfy the predicate `p`, a sum
over `s.subtype p` equals that sum over `s`."]
theorem prod_subtype_of_mem (f : α → β) {p : α → Prop} [DecidablePred p] (h : ∀ x ∈ s, p x) :
∏ x ∈ s.subtype p, f x = ∏ x ∈ s, f x := by
rw [prod_subtype_eq_prod_filter, filter_true_of_mem]
simpa using h
#align finset.prod_subtype_of_mem Finset.prod_subtype_of_mem
#align finset.sum_subtype_of_mem Finset.sum_subtype_of_mem
/-- A product of a function over a `Finset` in a subtype equals a
product in the main type of a function that agrees with the first
function on that `Finset`. -/
@[to_additive "A sum of a function over a `Finset` in a subtype equals a
sum in the main type of a function that agrees with the first
function on that `Finset`."]
theorem prod_subtype_map_embedding {p : α → Prop} {s : Finset { x // p x }} {f : { x // p x } → β}
{g : α → β} (h : ∀ x : { x // p x }, x ∈ s → g x = f x) :
(∏ x ∈ s.map (Function.Embedding.subtype _), g x) = ∏ x ∈ s, f x := by
rw [Finset.prod_map]
exact Finset.prod_congr rfl h
#align finset.prod_subtype_map_embedding Finset.prod_subtype_map_embedding
#align finset.sum_subtype_map_embedding Finset.sum_subtype_map_embedding
variable (f s)
@[to_additive]
theorem prod_coe_sort_eq_attach (f : s → β) : ∏ i : s, f i = ∏ i ∈ s.attach, f i :=
rfl
#align finset.prod_coe_sort_eq_attach Finset.prod_coe_sort_eq_attach
#align finset.sum_coe_sort_eq_attach Finset.sum_coe_sort_eq_attach
@[to_additive]
theorem prod_coe_sort : ∏ i : s, f i = ∏ i ∈ s, f i := prod_attach _ _
#align finset.prod_coe_sort Finset.prod_coe_sort
#align finset.sum_coe_sort Finset.sum_coe_sort
@[to_additive]
theorem prod_finset_coe (f : α → β) (s : Finset α) : (∏ i : (s : Set α), f i) = ∏ i ∈ s, f i :=
prod_coe_sort s f
#align finset.prod_finset_coe Finset.prod_finset_coe
#align finset.sum_finset_coe Finset.sum_finset_coe
variable {f s}
@[to_additive]
theorem prod_subtype {p : α → Prop} {F : Fintype (Subtype p)} (s : Finset α) (h : ∀ x, x ∈ s ↔ p x)
(f : α → β) : ∏ a ∈ s, f a = ∏ a : Subtype p, f a := by
have : (· ∈ s) = p := Set.ext h
subst p
rw [← prod_coe_sort]
congr!
#align finset.prod_subtype Finset.prod_subtype
#align finset.sum_subtype Finset.sum_subtype
@[to_additive]
lemma prod_preimage' (f : ι → κ) [DecidablePred (· ∈ Set.range f)] (s : Finset κ) (hf) (g : κ → β) :
∏ x ∈ s.preimage f hf, g (f x) = ∏ x ∈ s.filter (· ∈ Set.range f), g x := by
classical
calc
∏ x ∈ preimage s f hf, g (f x) = ∏ x ∈ image f (preimage s f hf), g x :=
Eq.symm <| prod_image <| by simpa only [mem_preimage, Set.InjOn] using hf
_ = ∏ x ∈ s.filter fun x => x ∈ Set.range f, g x := by rw [image_preimage]
#align finset.prod_preimage' Finset.prod_preimage'
#align finset.sum_preimage' Finset.sum_preimage'
@[to_additive]
lemma prod_preimage (f : ι → κ) (s : Finset κ) (hf) (g : κ → β)
(hg : ∀ x ∈ s, x ∉ Set.range f → g x = 1) :
∏ x ∈ s.preimage f hf, g (f x) = ∏ x ∈ s, g x := by
classical rw [prod_preimage', prod_filter_of_ne]; exact fun x hx ↦ Not.imp_symm (hg x hx)
#align finset.prod_preimage Finset.prod_preimage
#align finset.sum_preimage Finset.sum_preimage
@[to_additive]
lemma prod_preimage_of_bij (f : ι → κ) (s : Finset κ) (hf : Set.BijOn f (f ⁻¹' ↑s) ↑s) (g : κ → β) :
∏ x ∈ s.preimage f hf.injOn, g (f x) = ∏ x ∈ s, g x :=
prod_preimage _ _ hf.injOn g fun _ hs h_f ↦ (h_f <| hf.subset_range hs).elim
#align finset.prod_preimage_of_bij Finset.prod_preimage_of_bij
#align finset.sum_preimage_of_bij Finset.sum_preimage_of_bij
@[to_additive]
theorem prod_set_coe (s : Set α) [Fintype s] : (∏ i : s, f i) = ∏ i ∈ s.toFinset, f i :=
(Finset.prod_subtype s.toFinset (fun _ ↦ Set.mem_toFinset) f).symm
/-- The product of a function `g` defined only on a set `s` is equal to
the product of a function `f` defined everywhere,
as long as `f` and `g` agree on `s`, and `f = 1` off `s`. -/
@[to_additive "The sum of a function `g` defined only on a set `s` is equal to
the sum of a function `f` defined everywhere,
as long as `f` and `g` agree on `s`, and `f = 0` off `s`."]
theorem prod_congr_set {α : Type*} [CommMonoid α] {β : Type*} [Fintype β] (s : Set β)
[DecidablePred (· ∈ s)] (f : β → α) (g : s → α) (w : ∀ (x : β) (h : x ∈ s), f x = g ⟨x, h⟩)
(w' : ∀ x : β, x ∉ s → f x = 1) : Finset.univ.prod f = Finset.univ.prod g := by
rw [← @Finset.prod_subset _ _ s.toFinset Finset.univ f _ (by simp)]
· rw [Finset.prod_subtype]
· apply Finset.prod_congr rfl
exact fun ⟨x, h⟩ _ => w x h
· simp
· rintro x _ h
exact w' x (by simpa using h)
#align finset.prod_congr_set Finset.prod_congr_set
#align finset.sum_congr_set Finset.sum_congr_set
@[to_additive]
theorem prod_apply_dite {s : Finset α} {p : α → Prop} {hp : DecidablePred p}
[DecidablePred fun x => ¬p x] (f : ∀ x : α, p x → γ) (g : ∀ x : α, ¬p x → γ) (h : γ → β) :
(∏ x ∈ s, h (if hx : p x then f x hx else g x hx)) =
(∏ x ∈ (s.filter p).attach, h (f x.1 <| by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter fun x => ¬p x).attach, h (g x.1 <| by simpa using (mem_filter.mp x.2).2) :=
calc
(∏ x ∈ s, h (if hx : p x then f x hx else g x hx)) =
(∏ x ∈ s.filter p, h (if hx : p x then f x hx else g x hx)) *
∏ x ∈ s.filter (¬p ·), h (if hx : p x then f x hx else g x hx) :=
(prod_filter_mul_prod_filter_not s p _).symm
_ = (∏ x ∈ (s.filter p).attach, h (if hx : p x.1 then f x.1 hx else g x.1 hx)) *
∏ x ∈ (s.filter (¬p ·)).attach, h (if hx : p x.1 then f x.1 hx else g x.1 hx) :=
congr_arg₂ _ (prod_attach _ _).symm (prod_attach _ _).symm
_ = (∏ x ∈ (s.filter p).attach, h (f x.1 <| by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter (¬p ·)).attach, h (g x.1 <| by simpa using (mem_filter.mp x.2).2) :=
congr_arg₂ _ (prod_congr rfl fun x _hx ↦
congr_arg h (dif_pos <| by simpa using (mem_filter.mp x.2).2))
(prod_congr rfl fun x _hx => congr_arg h (dif_neg <| by simpa using (mem_filter.mp x.2).2))
#align finset.prod_apply_dite Finset.prod_apply_dite
#align finset.sum_apply_dite Finset.sum_apply_dite
@[to_additive]
theorem prod_apply_ite {s : Finset α} {p : α → Prop} {_hp : DecidablePred p} (f g : α → γ)
(h : γ → β) :
(∏ x ∈ s, h (if p x then f x else g x)) =
(∏ x ∈ s.filter p, h (f x)) * ∏ x ∈ s.filter fun x => ¬p x, h (g x) :=
(prod_apply_dite _ _ _).trans <| congr_arg₂ _ (prod_attach _ (h ∘ f)) (prod_attach _ (h ∘ g))
#align finset.prod_apply_ite Finset.prod_apply_ite
#align finset.sum_apply_ite Finset.sum_apply_ite
@[to_additive]
theorem prod_dite {s : Finset α} {p : α → Prop} {hp : DecidablePred p} (f : ∀ x : α, p x → β)
(g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) =
(∏ x ∈ (s.filter p).attach, f x.1 (by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter fun x => ¬p x).attach, g x.1 (by simpa using (mem_filter.mp x.2).2) := by
simp [prod_apply_dite _ _ fun x => x]
#align finset.prod_dite Finset.prod_dite
#align finset.sum_dite Finset.sum_dite
@[to_additive]
theorem prod_ite {s : Finset α} {p : α → Prop} {hp : DecidablePred p} (f g : α → β) :
∏ x ∈ s, (if p x then f x else g x) =
(∏ x ∈ s.filter p, f x) * ∏ x ∈ s.filter fun x => ¬p x, g x := by
simp [prod_apply_ite _ _ fun x => x]
#align finset.prod_ite Finset.prod_ite
#align finset.sum_ite Finset.sum_ite
@[to_additive]
theorem prod_ite_of_false {p : α → Prop} {hp : DecidablePred p} (f g : α → β) (h : ∀ x ∈ s, ¬p x) :
∏ x ∈ s, (if p x then f x else g x) = ∏ x ∈ s, g x := by
rw [prod_ite, filter_false_of_mem, filter_true_of_mem]
· simp only [prod_empty, one_mul]
all_goals intros; apply h; assumption
#align finset.prod_ite_of_false Finset.prod_ite_of_false
#align finset.sum_ite_of_false Finset.sum_ite_of_false
@[to_additive]
theorem prod_ite_of_true {p : α → Prop} {hp : DecidablePred p} (f g : α → β) (h : ∀ x ∈ s, p x) :
∏ x ∈ s, (if p x then f x else g x) = ∏ x ∈ s, f x := by
simp_rw [← ite_not (p _)]
apply prod_ite_of_false
simpa
#align finset.prod_ite_of_true Finset.prod_ite_of_true
#align finset.sum_ite_of_true Finset.sum_ite_of_true
@[to_additive]
theorem prod_apply_ite_of_false {p : α → Prop} {hp : DecidablePred p} (f g : α → γ) (k : γ → β)
(h : ∀ x ∈ s, ¬p x) : (∏ x ∈ s, k (if p x then f x else g x)) = ∏ x ∈ s, k (g x) := by
simp_rw [apply_ite k]
exact prod_ite_of_false _ _ h
#align finset.prod_apply_ite_of_false Finset.prod_apply_ite_of_false
#align finset.sum_apply_ite_of_false Finset.sum_apply_ite_of_false
@[to_additive]
theorem prod_apply_ite_of_true {p : α → Prop} {hp : DecidablePred p} (f g : α → γ) (k : γ → β)
(h : ∀ x ∈ s, p x) : (∏ x ∈ s, k (if p x then f x else g x)) = ∏ x ∈ s, k (f x) := by
simp_rw [apply_ite k]
exact prod_ite_of_true _ _ h
#align finset.prod_apply_ite_of_true Finset.prod_apply_ite_of_true
#align finset.sum_apply_ite_of_true Finset.sum_apply_ite_of_true
@[to_additive]
theorem prod_extend_by_one [DecidableEq α] (s : Finset α) (f : α → β) :
∏ i ∈ s, (if i ∈ s then f i else 1) = ∏ i ∈ s, f i :=
(prod_congr rfl) fun _i hi => if_pos hi
#align finset.prod_extend_by_one Finset.prod_extend_by_one
#align finset.sum_extend_by_zero Finset.sum_extend_by_zero
@[to_additive (attr := simp)]
theorem prod_ite_mem [DecidableEq α] (s t : Finset α) (f : α → β) :
∏ i ∈ s, (if i ∈ t then f i else 1) = ∏ i ∈ s ∩ t, f i := by
rw [← Finset.prod_filter, Finset.filter_mem_eq_inter]
#align finset.prod_ite_mem Finset.prod_ite_mem
#align finset.sum_ite_mem Finset.sum_ite_mem
@[to_additive (attr := simp)]
theorem prod_dite_eq [DecidableEq α] (s : Finset α) (a : α) (b : ∀ x : α, a = x → β) :
∏ x ∈ s, (if h : a = x then b x h else 1) = ite (a ∈ s) (b a rfl) 1 := by
split_ifs with h
· rw [Finset.prod_eq_single a, dif_pos rfl]
· intros _ _ h
rw [dif_neg]
exact h.symm
· simp [h]
· rw [Finset.prod_eq_one]
intros
rw [dif_neg]
rintro rfl
contradiction
#align finset.prod_dite_eq Finset.prod_dite_eq
#align finset.sum_dite_eq Finset.sum_dite_eq
@[to_additive (attr := simp)]
theorem prod_dite_eq' [DecidableEq α] (s : Finset α) (a : α) (b : ∀ x : α, x = a → β) :
∏ x ∈ s, (if h : x = a then b x h else 1) = ite (a ∈ s) (b a rfl) 1 := by
split_ifs with h
· rw [Finset.prod_eq_single a, dif_pos rfl]
· intros _ _ h
rw [dif_neg]
exact h
· simp [h]
· rw [Finset.prod_eq_one]
intros
rw [dif_neg]
rintro rfl
contradiction
#align finset.prod_dite_eq' Finset.prod_dite_eq'
#align finset.sum_dite_eq' Finset.sum_dite_eq'
@[to_additive (attr := simp)]
theorem prod_ite_eq [DecidableEq α] (s : Finset α) (a : α) (b : α → β) :
(∏ x ∈ s, ite (a = x) (b x) 1) = ite (a ∈ s) (b a) 1 :=
prod_dite_eq s a fun x _ => b x
#align finset.prod_ite_eq Finset.prod_ite_eq
#align finset.sum_ite_eq Finset.sum_ite_eq
/-- A product taken over a conditional whose condition is an equality test on the index and whose
alternative is `1` has value either the term at that index or `1`.
The difference with `Finset.prod_ite_eq` is that the arguments to `Eq` are swapped. -/
@[to_additive (attr := simp) "A sum taken over a conditional whose condition is an equality
test on the index and whose alternative is `0` has value either the term at that index or `0`.
The difference with `Finset.sum_ite_eq` is that the arguments to `Eq` are swapped."]
theorem prod_ite_eq' [DecidableEq α] (s : Finset α) (a : α) (b : α → β) :
(∏ x ∈ s, ite (x = a) (b x) 1) = ite (a ∈ s) (b a) 1 :=
prod_dite_eq' s a fun x _ => b x
#align finset.prod_ite_eq' Finset.prod_ite_eq'
#align finset.sum_ite_eq' Finset.sum_ite_eq'
@[to_additive]
theorem prod_ite_index (p : Prop) [Decidable p] (s t : Finset α) (f : α → β) :
∏ x ∈ if p then s else t, f x = if p then ∏ x ∈ s, f x else ∏ x ∈ t, f x :=
apply_ite (fun s => ∏ x ∈ s, f x) _ _ _
#align finset.prod_ite_index Finset.prod_ite_index
#align finset.sum_ite_index Finset.sum_ite_index
@[to_additive (attr := simp)]
theorem prod_ite_irrel (p : Prop) [Decidable p] (s : Finset α) (f g : α → β) :
∏ x ∈ s, (if p then f x else g x) = if p then ∏ x ∈ s, f x else ∏ x ∈ s, g x := by
split_ifs with h <;> rfl
#align finset.prod_ite_irrel Finset.prod_ite_irrel
#align finset.sum_ite_irrel Finset.sum_ite_irrel
@[to_additive (attr := simp)]
theorem prod_dite_irrel (p : Prop) [Decidable p] (s : Finset α) (f : p → α → β) (g : ¬p → α → β) :
∏ x ∈ s, (if h : p then f h x else g h x) =
if h : p then ∏ x ∈ s, f h x else ∏ x ∈ s, g h x := by
split_ifs with h <;> rfl
#align finset.prod_dite_irrel Finset.prod_dite_irrel
#align finset.sum_dite_irrel Finset.sum_dite_irrel
@[to_additive (attr := simp)]
theorem prod_pi_mulSingle' [DecidableEq α] (a : α) (x : β) (s : Finset α) :
∏ a' ∈ s, Pi.mulSingle a x a' = if a ∈ s then x else 1 :=
prod_dite_eq' _ _ _
#align finset.prod_pi_mul_single' Finset.prod_pi_mulSingle'
#align finset.sum_pi_single' Finset.sum_pi_single'
@[to_additive (attr := simp)]
theorem prod_pi_mulSingle {β : α → Type*} [DecidableEq α] [∀ a, CommMonoid (β a)] (a : α)
(f : ∀ a, β a) (s : Finset α) :
(∏ a' ∈ s, Pi.mulSingle a' (f a') a) = if a ∈ s then f a else 1 :=
prod_dite_eq _ _ _
#align finset.prod_pi_mul_single Finset.prod_pi_mulSingle
@[to_additive]
lemma mulSupport_prod (s : Finset ι) (f : ι → α → β) :
mulSupport (fun x ↦ ∏ i ∈ s, f i x) ⊆ ⋃ i ∈ s, mulSupport (f i) := by
simp only [mulSupport_subset_iff', Set.mem_iUnion, not_exists, nmem_mulSupport]
exact fun x ↦ prod_eq_one
#align function.mul_support_prod Finset.mulSupport_prod
#align function.support_sum Finset.support_sum
section indicator
open Set
variable {κ : Type*}
/-- Consider a product of `g i (f i)` over a finset. Suppose `g` is a function such as
`n ↦ (· ^ n)`, which maps a second argument of `1` to `1`. Then if `f` is replaced by the
corresponding multiplicative indicator function, the finset may be replaced by a possibly larger
finset without changing the value of the product. -/
@[to_additive "Consider a sum of `g i (f i)` over a finset. Suppose `g` is a function such as
`n ↦ (n • ·)`, which maps a second argument of `0` to `0` (or a weighted sum of `f i * h i` or
`f i • h i`, where `f` gives the weights that are multiplied by some other function `h`). Then if
`f` is replaced by the corresponding indicator function, the finset may be replaced by a possibly
larger finset without changing the value of the sum."]
lemma prod_mulIndicator_subset_of_eq_one [One α] (f : ι → α) (g : ι → α → β) {s t : Finset ι}
(h : s ⊆ t) (hg : ∀ a, g a 1 = 1) :
∏ i ∈ t, g i (mulIndicator ↑s f i) = ∏ i ∈ s, g i (f i) := by
calc
_ = ∏ i ∈ s, g i (mulIndicator ↑s f i) := by rw [prod_subset h fun i _ hn ↦ by simp [hn, hg]]
-- Porting note: This did not use to need the implicit argument
_ = _ := prod_congr rfl fun i hi ↦ congr_arg _ <| mulIndicator_of_mem (α := ι) hi f
#align set.prod_mul_indicator_subset_of_eq_one Finset.prod_mulIndicator_subset_of_eq_one
#align set.sum_indicator_subset_of_eq_zero Finset.sum_indicator_subset_of_eq_zero
/-- Taking the product of an indicator function over a possibly larger finset is the same as
taking the original function over the original finset. -/
@[to_additive "Summing an indicator function over a possibly larger `Finset` is the same as summing
the original function over the original finset."]
lemma prod_mulIndicator_subset (f : ι → β) {s t : Finset ι} (h : s ⊆ t) :
∏ i ∈ t, mulIndicator (↑s) f i = ∏ i ∈ s, f i :=
prod_mulIndicator_subset_of_eq_one _ (fun _ ↦ id) h fun _ ↦ rfl
#align set.prod_mul_indicator_subset Finset.prod_mulIndicator_subset
#align set.sum_indicator_subset Finset.sum_indicator_subset
@[to_additive]
lemma prod_mulIndicator_eq_prod_filter (s : Finset ι) (f : ι → κ → β) (t : ι → Set κ) (g : ι → κ)
[DecidablePred fun i ↦ g i ∈ t i] :
∏ i ∈ s, mulIndicator (t i) (f i) (g i) = ∏ i ∈ s.filter fun i ↦ g i ∈ t i, f i (g i) := by
refine (prod_filter_mul_prod_filter_not s (fun i ↦ g i ∈ t i) _).symm.trans <|
Eq.trans (congr_arg₂ (· * ·) ?_ ?_) (mul_one _)
· exact prod_congr rfl fun x hx ↦ mulIndicator_of_mem (mem_filter.1 hx).2 _
· exact prod_eq_one fun x hx ↦ mulIndicator_of_not_mem (mem_filter.1 hx).2 _
#align finset.prod_mul_indicator_eq_prod_filter Finset.prod_mulIndicator_eq_prod_filter
#align finset.sum_indicator_eq_sum_filter Finset.sum_indicator_eq_sum_filter
@[to_additive]
lemma prod_mulIndicator_eq_prod_inter [DecidableEq ι] (s t : Finset ι) (f : ι → β) :
∏ i ∈ s, (t : Set ι).mulIndicator f i = ∏ i ∈ s ∩ t, f i := by
rw [← filter_mem_eq_inter, prod_mulIndicator_eq_prod_filter]; rfl
@[to_additive]
lemma mulIndicator_prod (s : Finset ι) (t : Set κ) (f : ι → κ → β) :
mulIndicator t (∏ i ∈ s, f i) = ∏ i ∈ s, mulIndicator t (f i) :=
map_prod (mulIndicatorHom _ _) _ _
#align set.mul_indicator_finset_prod Finset.mulIndicator_prod
#align set.indicator_finset_sum Finset.indicator_sum
variable {κ : Type*}
@[to_additive]
lemma mulIndicator_biUnion (s : Finset ι) (t : ι → Set κ) {f : κ → β} :
((s : Set ι).PairwiseDisjoint t) →
mulIndicator (⋃ i ∈ s, t i) f = fun a ↦ ∏ i ∈ s, mulIndicator (t i) f a := by
classical
refine Finset.induction_on s (by simp) fun i s hi ih hs ↦ funext fun j ↦ ?_
rw [prod_insert hi, set_biUnion_insert, mulIndicator_union_of_not_mem_inter,
ih (hs.subset <| subset_insert _ _)]
simp only [not_exists, exists_prop, mem_iUnion, mem_inter_iff, not_and]
exact fun hji i' hi' hji' ↦ (ne_of_mem_of_not_mem hi' hi).symm <|
hs.elim_set (mem_insert_self _ _) (mem_insert_of_mem hi') _ hji hji'
#align set.mul_indicator_finset_bUnion Finset.mulIndicator_biUnion
#align set.indicator_finset_bUnion Finset.indicator_biUnion
@[to_additive]
lemma mulIndicator_biUnion_apply (s : Finset ι) (t : ι → Set κ) {f : κ → β}
(h : (s : Set ι).PairwiseDisjoint t) (x : κ) :
mulIndicator (⋃ i ∈ s, t i) f x = ∏ i ∈ s, mulIndicator (t i) f x := by
rw [mulIndicator_biUnion s t h]
#align set.mul_indicator_finset_bUnion_apply Finset.mulIndicator_biUnion_apply
#align set.indicator_finset_bUnion_apply Finset.indicator_biUnion_apply
end indicator
@[to_additive]
theorem prod_bij_ne_one {s : Finset α} {t : Finset γ} {f : α → β} {g : γ → β}
(i : ∀ a ∈ s, f a ≠ 1 → γ) (hi : ∀ a h₁ h₂, i a h₁ h₂ ∈ t)
(i_inj : ∀ a₁ h₁₁ h₁₂ a₂ h₂₁ h₂₂, i a₁ h₁₁ h₁₂ = i a₂ h₂₁ h₂₂ → a₁ = a₂)
(i_surj : ∀ b ∈ t, g b ≠ 1 → ∃ a h₁ h₂, i a h₁ h₂ = b) (h : ∀ a h₁ h₂, f a = g (i a h₁ h₂)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x := by
classical
calc
∏ x ∈ s, f x = ∏ x ∈ s.filter fun x => f x ≠ 1, f x := by rw [prod_filter_ne_one]
_ = ∏ x ∈ t.filter fun x => g x ≠ 1, g x :=
prod_bij (fun a ha => i a (mem_filter.mp ha).1 <| by simpa using (mem_filter.mp ha).2)
?_ ?_ ?_ ?_
_ = ∏ x ∈ t, g x := prod_filter_ne_one _
· intros a ha
refine (mem_filter.mp ha).elim ?_
intros h₁ h₂
refine (mem_filter.mpr ⟨hi a h₁ _, ?_⟩)
specialize h a h₁ fun H ↦ by rw [H] at h₂; simp at h₂
rwa [← h]
· intros a₁ ha₁ a₂ ha₂
refine (mem_filter.mp ha₁).elim fun _ha₁₁ _ha₁₂ ↦ ?_
refine (mem_filter.mp ha₂).elim fun _ha₂₁ _ha₂₂ ↦ ?_
apply i_inj
· intros b hb
refine (mem_filter.mp hb).elim fun h₁ h₂ ↦ ?_
obtain ⟨a, ha₁, ha₂, eq⟩ := i_surj b h₁ fun H ↦ by rw [H] at h₂; simp at h₂
exact ⟨a, mem_filter.mpr ⟨ha₁, ha₂⟩, eq⟩
· refine (fun a ha => (mem_filter.mp ha).elim fun h₁ h₂ ↦ ?_)
exact h a h₁ fun H ↦ by rw [H] at h₂; simp at h₂
#align finset.prod_bij_ne_one Finset.prod_bij_ne_one
#align finset.sum_bij_ne_zero Finset.sum_bij_ne_zero
@[to_additive]
theorem prod_dite_of_false {p : α → Prop} {hp : DecidablePred p} (h : ∀ x ∈ s, ¬p x)
(f : ∀ x : α, p x → β) (g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) = ∏ x : s, g x.val (h x.val x.property) := by
refine prod_bij' (fun x hx => ⟨x, hx⟩) (fun x _ ↦ x) ?_ ?_ ?_ ?_ ?_ <;> aesop
#align finset.prod_dite_of_false Finset.prod_dite_of_false
#align finset.sum_dite_of_false Finset.sum_dite_of_false
@[to_additive]
theorem prod_dite_of_true {p : α → Prop} {hp : DecidablePred p} (h : ∀ x ∈ s, p x)
(f : ∀ x : α, p x → β) (g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) = ∏ x : s, f x.val (h x.val x.property) := by
refine prod_bij' (fun x hx => ⟨x, hx⟩) (fun x _ ↦ x) ?_ ?_ ?_ ?_ ?_ <;> aesop
#align finset.prod_dite_of_true Finset.prod_dite_of_true
#align finset.sum_dite_of_true Finset.sum_dite_of_true
@[to_additive]
theorem nonempty_of_prod_ne_one (h : ∏ x ∈ s, f x ≠ 1) : s.Nonempty :=
s.eq_empty_or_nonempty.elim (fun H => False.elim <| h <| H.symm ▸ prod_empty) id
#align finset.nonempty_of_prod_ne_one Finset.nonempty_of_prod_ne_one
#align finset.nonempty_of_sum_ne_zero Finset.nonempty_of_sum_ne_zero
@[to_additive]
theorem exists_ne_one_of_prod_ne_one (h : ∏ x ∈ s, f x ≠ 1) : ∃ a ∈ s, f a ≠ 1 := by
classical
rw [← prod_filter_ne_one] at h
rcases nonempty_of_prod_ne_one h with ⟨x, hx⟩
exact ⟨x, (mem_filter.1 hx).1, by simpa using (mem_filter.1 hx).2⟩
#align finset.exists_ne_one_of_prod_ne_one Finset.exists_ne_one_of_prod_ne_one
#align finset.exists_ne_zero_of_sum_ne_zero Finset.exists_ne_zero_of_sum_ne_zero
@[to_additive]
theorem prod_range_succ_comm (f : ℕ → β) (n : ℕ) :
(∏ x ∈ range (n + 1), f x) = f n * ∏ x ∈ range n, f x := by
rw [range_succ, prod_insert not_mem_range_self]
#align finset.prod_range_succ_comm Finset.prod_range_succ_comm
#align finset.sum_range_succ_comm Finset.sum_range_succ_comm
@[to_additive]
theorem prod_range_succ (f : ℕ → β) (n : ℕ) :
(∏ x ∈ range (n + 1), f x) = (∏ x ∈ range n, f x) * f n := by
simp only [mul_comm, prod_range_succ_comm]
#align finset.prod_range_succ Finset.prod_range_succ
#align finset.sum_range_succ Finset.sum_range_succ
@[to_additive]
theorem prod_range_succ' (f : ℕ → β) :
∀ n : ℕ, (∏ k ∈ range (n + 1), f k) = (∏ k ∈ range n, f (k + 1)) * f 0
| 0 => prod_range_succ _ _
| n + 1 => by rw [prod_range_succ _ n, mul_right_comm, ← prod_range_succ' _ n, prod_range_succ]
#align finset.prod_range_succ' Finset.prod_range_succ'
#align finset.sum_range_succ' Finset.sum_range_succ'
@[to_additive]
theorem eventually_constant_prod {u : ℕ → β} {N : ℕ} (hu : ∀ n ≥ N, u n = 1) {n : ℕ} (hn : N ≤ n) :
(∏ k ∈ range n, u k) = ∏ k ∈ range N, u k := by
obtain ⟨m, rfl : n = N + m⟩ := Nat.exists_eq_add_of_le hn
clear hn
induction' m with m hm
· simp
· simp [← add_assoc, prod_range_succ, hm, hu]
#align finset.eventually_constant_prod Finset.eventually_constant_prod
#align finset.eventually_constant_sum Finset.eventually_constant_sum
@[to_additive]
theorem prod_range_add (f : ℕ → β) (n m : ℕ) :
(∏ x ∈ range (n + m), f x) = (∏ x ∈ range n, f x) * ∏ x ∈ range m, f (n + x) := by
induction' m with m hm
· simp
· erw [Nat.add_succ, prod_range_succ, prod_range_succ, hm, mul_assoc]
#align finset.prod_range_add Finset.prod_range_add
#align finset.sum_range_add Finset.sum_range_add
@[to_additive]
theorem prod_range_add_div_prod_range {α : Type*} [CommGroup α] (f : ℕ → α) (n m : ℕ) :
(∏ k ∈ range (n + m), f k) / ∏ k ∈ range n, f k = ∏ k ∈ Finset.range m, f (n + k) :=
div_eq_of_eq_mul' (prod_range_add f n m)
#align finset.prod_range_add_div_prod_range Finset.prod_range_add_div_prod_range
#align finset.sum_range_add_sub_sum_range Finset.sum_range_add_sub_sum_range
@[to_additive]
theorem prod_range_zero (f : ℕ → β) : ∏ k ∈ range 0, f k = 1 := by rw [range_zero, prod_empty]
#align finset.prod_range_zero Finset.prod_range_zero
#align finset.sum_range_zero Finset.sum_range_zero
@[to_additive sum_range_one]
theorem prod_range_one (f : ℕ → β) : ∏ k ∈ range 1, f k = f 0 := by
rw [range_one, prod_singleton]
#align finset.prod_range_one Finset.prod_range_one
#align finset.sum_range_one Finset.sum_range_one
open List
@[to_additive]
theorem prod_list_map_count [DecidableEq α] (l : List α) {M : Type*} [CommMonoid M] (f : α → M) :
(l.map f).prod = ∏ m ∈ l.toFinset, f m ^ l.count m := by
induction' l with a s IH; · simp only [map_nil, prod_nil, count_nil, pow_zero, prod_const_one]
simp only [List.map, List.prod_cons, toFinset_cons, IH]
by_cases has : a ∈ s.toFinset
· rw [insert_eq_of_mem has, ← insert_erase has, prod_insert (not_mem_erase _ _),
prod_insert (not_mem_erase _ _), ← mul_assoc, count_cons_self, pow_succ']
congr 1
refine prod_congr rfl fun x hx => ?_
rw [count_cons_of_ne (ne_of_mem_erase hx)]
rw [prod_insert has, count_cons_self, count_eq_zero_of_not_mem (mt mem_toFinset.2 has), pow_one]
congr 1
refine prod_congr rfl fun x hx => ?_
rw [count_cons_of_ne]
rintro rfl
exact has hx
#align finset.prod_list_map_count Finset.prod_list_map_count
#align finset.sum_list_map_count Finset.sum_list_map_count
@[to_additive]
theorem prod_list_count [DecidableEq α] [CommMonoid α] (s : List α) :
s.prod = ∏ m ∈ s.toFinset, m ^ s.count m := by simpa using prod_list_map_count s id
#align finset.prod_list_count Finset.prod_list_count
#align finset.sum_list_count Finset.sum_list_count
@[to_additive]
theorem prod_list_count_of_subset [DecidableEq α] [CommMonoid α] (m : List α) (s : Finset α)
(hs : m.toFinset ⊆ s) : m.prod = ∏ i ∈ s, i ^ m.count i := by
rw [prod_list_count]
refine prod_subset hs fun x _ hx => ?_
rw [mem_toFinset] at hx
rw [count_eq_zero_of_not_mem hx, pow_zero]
#align finset.prod_list_count_of_subset Finset.prod_list_count_of_subset
#align finset.sum_list_count_of_subset Finset.sum_list_count_of_subset
theorem sum_filter_count_eq_countP [DecidableEq α] (p : α → Prop) [DecidablePred p] (l : List α) :
∑ x ∈ l.toFinset.filter p, l.count x = l.countP p := by
simp [Finset.sum, sum_map_count_dedup_filter_eq_countP p l]
#align finset.sum_filter_count_eq_countp Finset.sum_filter_count_eq_countP
open Multiset
@[to_additive]
theorem prod_multiset_map_count [DecidableEq α] (s : Multiset α) {M : Type*} [CommMonoid M]
(f : α → M) : (s.map f).prod = ∏ m ∈ s.toFinset, f m ^ s.count m := by
refine Quot.induction_on s fun l => ?_
simp [prod_list_map_count l f]
#align finset.prod_multiset_map_count Finset.prod_multiset_map_count
#align finset.sum_multiset_map_count Finset.sum_multiset_map_count
@[to_additive]
theorem prod_multiset_count [DecidableEq α] [CommMonoid α] (s : Multiset α) :
s.prod = ∏ m ∈ s.toFinset, m ^ s.count m := by
convert prod_multiset_map_count s id
rw [Multiset.map_id]
#align finset.prod_multiset_count Finset.prod_multiset_count
#align finset.sum_multiset_count Finset.sum_multiset_count
@[to_additive]
theorem prod_multiset_count_of_subset [DecidableEq α] [CommMonoid α] (m : Multiset α) (s : Finset α)
(hs : m.toFinset ⊆ s) : m.prod = ∏ i ∈ s, i ^ m.count i := by
revert hs
refine Quot.induction_on m fun l => ?_
simp only [quot_mk_to_coe'', prod_coe, coe_count]
apply prod_list_count_of_subset l s
#align finset.prod_multiset_count_of_subset Finset.prod_multiset_count_of_subset
#align finset.sum_multiset_count_of_subset Finset.sum_multiset_count_of_subset
@[to_additive]
theorem prod_mem_multiset [DecidableEq α] (m : Multiset α) (f : { x // x ∈ m } → β) (g : α → β)
(hfg : ∀ x, f x = g x) : ∏ x : { x // x ∈ m }, f x = ∏ x ∈ m.toFinset, g x := by
refine prod_bij' (fun x _ ↦ x) (fun x hx ↦ ⟨x, Multiset.mem_toFinset.1 hx⟩) ?_ ?_ ?_ ?_ ?_ <;>
simp [hfg]
#align finset.prod_mem_multiset Finset.prod_mem_multiset
#align finset.sum_mem_multiset Finset.sum_mem_multiset
/-- To prove a property of a product, it suffices to prove that
the property is multiplicative and holds on factors. -/
@[to_additive "To prove a property of a sum, it suffices to prove that
the property is additive and holds on summands."]
theorem prod_induction {M : Type*} [CommMonoid M] (f : α → M) (p : M → Prop)
(hom : ∀ a b, p a → p b → p (a * b)) (unit : p 1) (base : ∀ x ∈ s, p <| f x) :
p <| ∏ x ∈ s, f x :=
Multiset.prod_induction _ _ hom unit (Multiset.forall_mem_map_iff.mpr base)
#align finset.prod_induction Finset.prod_induction
#align finset.sum_induction Finset.sum_induction
/-- To prove a property of a product, it suffices to prove that
the property is multiplicative and holds on factors. -/
@[to_additive "To prove a property of a sum, it suffices to prove that
the property is additive and holds on summands."]
theorem prod_induction_nonempty {M : Type*} [CommMonoid M] (f : α → M) (p : M → Prop)
(hom : ∀ a b, p a → p b → p (a * b)) (nonempty : s.Nonempty) (base : ∀ x ∈ s, p <| f x) :
p <| ∏ x ∈ s, f x :=
Multiset.prod_induction_nonempty p hom (by simp [nonempty_iff_ne_empty.mp nonempty])
(Multiset.forall_mem_map_iff.mpr base)
#align finset.prod_induction_nonempty Finset.prod_induction_nonempty
#align finset.sum_induction_nonempty Finset.sum_induction_nonempty
/-- For any product along `{0, ..., n - 1}` of a commutative-monoid-valued function, we can verify
that it's equal to a different function just by checking ratios of adjacent terms.
This is a multiplicative discrete analogue of the fundamental theorem of calculus. -/
@[to_additive "For any sum along `{0, ..., n - 1}` of a commutative-monoid-valued function, we can
verify that it's equal to a different function just by checking differences of adjacent terms.
This is a discrete analogue of the fundamental theorem of calculus."]
theorem prod_range_induction (f s : ℕ → β) (base : s 0 = 1)
(step : ∀ n, s (n + 1) = s n * f n) (n : ℕ) :
∏ k ∈ Finset.range n, f k = s n := by
induction' n with k hk
· rw [Finset.prod_range_zero, base]
· simp only [hk, Finset.prod_range_succ, step, mul_comm]
#align finset.prod_range_induction Finset.prod_range_induction
#align finset.sum_range_induction Finset.sum_range_induction
/-- A telescoping product along `{0, ..., n - 1}` of a commutative group valued function reduces to
the ratio of the last and first factors. -/
@[to_additive "A telescoping sum along `{0, ..., n - 1}` of an additive commutative group valued
function reduces to the difference of the last and first terms."]
theorem prod_range_div {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
(∏ i ∈ range n, f (i + 1) / f i) = f n / f 0 := by apply prod_range_induction <;> simp
#align finset.prod_range_div Finset.prod_range_div
#align finset.sum_range_sub Finset.sum_range_sub
@[to_additive]
theorem prod_range_div' {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
(∏ i ∈ range n, f i / f (i + 1)) = f 0 / f n := by apply prod_range_induction <;> simp
#align finset.prod_range_div' Finset.prod_range_div'
#align finset.sum_range_sub' Finset.sum_range_sub'
@[to_additive]
theorem eq_prod_range_div {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
f n = f 0 * ∏ i ∈ range n, f (i + 1) / f i := by rw [prod_range_div, mul_div_cancel]
#align finset.eq_prod_range_div Finset.eq_prod_range_div
#align finset.eq_sum_range_sub Finset.eq_sum_range_sub
@[to_additive]
theorem eq_prod_range_div' {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
f n = ∏ i ∈ range (n + 1), if i = 0 then f 0 else f i / f (i - 1) := by
conv_lhs => rw [Finset.eq_prod_range_div f]
simp [Finset.prod_range_succ', mul_comm]
#align finset.eq_prod_range_div' Finset.eq_prod_range_div'
#align finset.eq_sum_range_sub' Finset.eq_sum_range_sub'
/-- A telescoping sum along `{0, ..., n-1}` of an `ℕ`-valued function
reduces to the difference of the last and first terms
when the function we are summing is monotone.
-/
theorem sum_range_tsub [CanonicallyOrderedAddCommMonoid α] [Sub α] [OrderedSub α]
[ContravariantClass α α (· + ·) (· ≤ ·)] {f : ℕ → α} (h : Monotone f) (n : ℕ) :
∑ i ∈ range n, (f (i + 1) - f i) = f n - f 0 := by
apply sum_range_induction
case base => apply tsub_self
case step =>
intro n
have h₁ : f n ≤ f (n + 1) := h (Nat.le_succ _)
have h₂ : f 0 ≤ f n := h (Nat.zero_le _)
rw [tsub_add_eq_add_tsub h₂, add_tsub_cancel_of_le h₁]
#align finset.sum_range_tsub Finset.sum_range_tsub
@[to_additive (attr := simp)]
theorem prod_const (b : β) : ∏ _x ∈ s, b = b ^ s.card :=
(congr_arg _ <| s.val.map_const b).trans <| Multiset.prod_replicate s.card b
#align finset.prod_const Finset.prod_const
#align finset.sum_const Finset.sum_const
@[to_additive sum_eq_card_nsmul]
theorem prod_eq_pow_card {b : β} (hf : ∀ a ∈ s, f a = b) : ∏ a ∈ s, f a = b ^ s.card :=
(prod_congr rfl hf).trans <| prod_const _
#align finset.prod_eq_pow_card Finset.prod_eq_pow_card
#align finset.sum_eq_card_nsmul Finset.sum_eq_card_nsmul
@[to_additive card_nsmul_add_sum]
theorem pow_card_mul_prod {b : β} : b ^ s.card * ∏ a ∈ s, f a = ∏ a ∈ s, b * f a :=
(Finset.prod_const b).symm ▸ prod_mul_distrib.symm
@[to_additive sum_add_card_nsmul]
theorem prod_mul_pow_card {b : β} : (∏ a ∈ s, f a) * b ^ s.card = ∏ a ∈ s, f a * b :=
(Finset.prod_const b).symm ▸ prod_mul_distrib.symm
@[to_additive]
theorem pow_eq_prod_const (b : β) : ∀ n, b ^ n = ∏ _k ∈ range n, b := by simp
#align finset.pow_eq_prod_const Finset.pow_eq_prod_const
#align finset.nsmul_eq_sum_const Finset.nsmul_eq_sum_const
@[to_additive]
theorem prod_pow (s : Finset α) (n : ℕ) (f : α → β) : ∏ x ∈ s, f x ^ n = (∏ x ∈ s, f x) ^ n :=
Multiset.prod_map_pow
#align finset.prod_pow Finset.prod_pow
#align finset.sum_nsmul Finset.sum_nsmul
@[to_additive sum_nsmul_assoc]
lemma prod_pow_eq_pow_sum (s : Finset ι) (f : ι → ℕ) (a : β) :
∏ i ∈ s, a ^ f i = a ^ ∑ i ∈ s, f i :=
cons_induction (by simp) (fun _ _ _ _ ↦ by simp [prod_cons, sum_cons, pow_add, *]) s
#align finset.prod_pow_eq_pow_sum Finset.prod_pow_eq_pow_sum
/-- A product over `Finset.powersetCard` which only depends on the size of the sets is constant. -/
@[to_additive
"A sum over `Finset.powersetCard` which only depends on the size of the sets is constant."]
lemma prod_powersetCard (n : ℕ) (s : Finset α) (f : ℕ → β) :
∏ t ∈ powersetCard n s, f t.card = f n ^ s.card.choose n := by
rw [prod_eq_pow_card, card_powersetCard]; rintro a ha; rw [(mem_powersetCard.1 ha).2]
@[to_additive]
theorem prod_flip {n : ℕ} (f : ℕ → β) :
(∏ r ∈ range (n + 1), f (n - r)) = ∏ k ∈ range (n + 1), f k := by
induction' n with n ih
· rw [prod_range_one, prod_range_one]
· rw [prod_range_succ', prod_range_succ _ (Nat.succ n)]
simp [← ih]
#align finset.prod_flip Finset.prod_flip
#align finset.sum_flip Finset.sum_flip
@[to_additive]
theorem prod_involution {s : Finset α} {f : α → β} :
∀ (g : ∀ a ∈ s, α) (_ : ∀ a ha, f a * f (g a ha) = 1) (_ : ∀ a ha, f a ≠ 1 → g a ha ≠ a)
(g_mem : ∀ a ha, g a ha ∈ s) (_ : ∀ a ha, g (g a ha) (g_mem a ha) = a),
∏ x ∈ s, f x = 1 := by
haveI := Classical.decEq α; haveI := Classical.decEq β
exact
Finset.strongInductionOn s fun s ih g h g_ne g_mem g_inv =>
s.eq_empty_or_nonempty.elim (fun hs => hs.symm ▸ rfl) fun ⟨x, hx⟩ =>
have hmem : ∀ y ∈ (s.erase x).erase (g x hx), y ∈ s := fun y hy =>
mem_of_mem_erase (mem_of_mem_erase hy)
have g_inj : ∀ {x hx y hy}, g x hx = g y hy → x = y := fun {x hx y hy} h => by
rw [← g_inv x hx, ← g_inv y hy]; simp [h]
have ih' : (∏ y ∈ erase (erase s x) (g x hx), f y) = (1 : β) :=
ih ((s.erase x).erase (g x hx))
⟨Subset.trans (erase_subset _ _) (erase_subset _ _), fun h =>
not_mem_erase (g x hx) (s.erase x) (h (g_mem x hx))⟩
(fun y hy => g y (hmem y hy)) (fun y hy => h y (hmem y hy))
(fun y hy => g_ne y (hmem y hy))
(fun y hy =>
mem_erase.2
⟨fun h : g y _ = g x hx => by simp [g_inj h] at hy,
mem_erase.2
⟨fun h : g y _ = x => by
have : y = g x hx := g_inv y (hmem y hy) ▸ by simp [h]
simp [this] at hy, g_mem y (hmem y hy)⟩⟩)
fun y hy => g_inv y (hmem y hy)
if hx1 : f x = 1 then
ih' ▸
Eq.symm
(prod_subset hmem fun y hy hy₁ =>
have : y = x ∨ y = g x hx := by
simpa [hy, -not_and, mem_erase, not_and_or, or_comm] using hy₁
this.elim (fun hy => hy.symm ▸ hx1) fun hy =>
h x hx ▸ hy ▸ hx1.symm ▸ (one_mul _).symm)
else by
rw [← insert_erase hx, prod_insert (not_mem_erase _ _), ←
insert_erase (mem_erase.2 ⟨g_ne x hx hx1, g_mem x hx⟩),
prod_insert (not_mem_erase _ _), ih', mul_one, h x hx]
#align finset.prod_involution Finset.prod_involution
#align finset.sum_involution Finset.sum_involution
/-- The product of the composition of functions `f` and `g`, is the product over `b ∈ s.image g` of
`f b` to the power of the cardinality of the fibre of `b`. See also `Finset.prod_image`. -/
@[to_additive "The sum of the composition of functions `f` and `g`, is the sum over `b ∈ s.image g`
of `f b` times of the cardinality of the fibre of `b`. See also `Finset.sum_image`."]
theorem prod_comp [DecidableEq γ] (f : γ → β) (g : α → γ) :
∏ a ∈ s, f (g a) = ∏ b ∈ s.image g, f b ^ (s.filter fun a => g a = b).card := by
simp_rw [← prod_const, prod_fiberwise_of_maps_to' fun _ ↦ mem_image_of_mem _]
#align finset.prod_comp Finset.prod_comp
#align finset.sum_comp Finset.sum_comp
@[to_additive]
theorem prod_piecewise [DecidableEq α] (s t : Finset α) (f g : α → β) :
(∏ x ∈ s, (t.piecewise f g) x) = (∏ x ∈ s ∩ t, f x) * ∏ x ∈ s \ t, g x := by
erw [prod_ite, filter_mem_eq_inter, ← sdiff_eq_filter]
#align finset.prod_piecewise Finset.prod_piecewise
#align finset.sum_piecewise Finset.sum_piecewise
@[to_additive]
theorem prod_inter_mul_prod_diff [DecidableEq α] (s t : Finset α) (f : α → β) :
(∏ x ∈ s ∩ t, f x) * ∏ x ∈ s \ t, f x = ∏ x ∈ s, f x := by
convert (s.prod_piecewise t f f).symm
simp (config := { unfoldPartialApp := true }) [Finset.piecewise]
#align finset.prod_inter_mul_prod_diff Finset.prod_inter_mul_prod_diff
#align finset.sum_inter_add_sum_diff Finset.sum_inter_add_sum_diff
@[to_additive]
theorem prod_eq_mul_prod_diff_singleton [DecidableEq α] {s : Finset α} {i : α} (h : i ∈ s)
(f : α → β) : ∏ x ∈ s, f x = f i * ∏ x ∈ s \ {i}, f x := by
convert (s.prod_inter_mul_prod_diff {i} f).symm
simp [h]
#align finset.prod_eq_mul_prod_diff_singleton Finset.prod_eq_mul_prod_diff_singleton
#align finset.sum_eq_add_sum_diff_singleton Finset.sum_eq_add_sum_diff_singleton
@[to_additive]
theorem prod_eq_prod_diff_singleton_mul [DecidableEq α] {s : Finset α} {i : α} (h : i ∈ s)
(f : α → β) : ∏ x ∈ s, f x = (∏ x ∈ s \ {i}, f x) * f i := by
rw [prod_eq_mul_prod_diff_singleton h, mul_comm]
#align finset.prod_eq_prod_diff_singleton_mul Finset.prod_eq_prod_diff_singleton_mul
#align finset.sum_eq_sum_diff_singleton_add Finset.sum_eq_sum_diff_singleton_add
@[to_additive]
theorem _root_.Fintype.prod_eq_mul_prod_compl [DecidableEq α] [Fintype α] (a : α) (f : α → β) :
∏ i, f i = f a * ∏ i ∈ {a}ᶜ, f i :=
prod_eq_mul_prod_diff_singleton (mem_univ a) f
#align fintype.prod_eq_mul_prod_compl Fintype.prod_eq_mul_prod_compl
#align fintype.sum_eq_add_sum_compl Fintype.sum_eq_add_sum_compl
@[to_additive]
theorem _root_.Fintype.prod_eq_prod_compl_mul [DecidableEq α] [Fintype α] (a : α) (f : α → β) :
∏ i, f i = (∏ i ∈ {a}ᶜ, f i) * f a :=
prod_eq_prod_diff_singleton_mul (mem_univ a) f
#align fintype.prod_eq_prod_compl_mul Fintype.prod_eq_prod_compl_mul
#align fintype.sum_eq_sum_compl_add Fintype.sum_eq_sum_compl_add
theorem dvd_prod_of_mem (f : α → β) {a : α} {s : Finset α} (ha : a ∈ s) : f a ∣ ∏ i ∈ s, f i := by
classical
rw [Finset.prod_eq_mul_prod_diff_singleton ha]
exact dvd_mul_right _ _
#align finset.dvd_prod_of_mem Finset.dvd_prod_of_mem
/-- A product can be partitioned into a product of products, each equivalent under a setoid. -/
@[to_additive "A sum can be partitioned into a sum of sums, each equivalent under a setoid."]
theorem prod_partition (R : Setoid α) [DecidableRel R.r] :
∏ x ∈ s, f x = ∏ xbar ∈ s.image Quotient.mk'', ∏ y ∈ s.filter (⟦·⟧ = xbar), f y := by
refine (Finset.prod_image' f fun x _hx => ?_).symm
rfl
#align finset.prod_partition Finset.prod_partition
#align finset.sum_partition Finset.sum_partition
/-- If we can partition a product into subsets that cancel out, then the whole product cancels. -/
@[to_additive "If we can partition a sum into subsets that cancel out, then the whole sum cancels."]
theorem prod_cancels_of_partition_cancels (R : Setoid α) [DecidableRel R.r]
(h : ∀ x ∈ s, ∏ a ∈ s.filter fun y => y ≈ x, f a = 1) : ∏ x ∈ s, f x = 1 := by
rw [prod_partition R, ← Finset.prod_eq_one]
intro xbar xbar_in_s
obtain ⟨x, x_in_s, rfl⟩ := mem_image.mp xbar_in_s
simp only [← Quotient.eq] at h
exact h x x_in_s
#align finset.prod_cancels_of_partition_cancels Finset.prod_cancels_of_partition_cancels
#align finset.sum_cancels_of_partition_cancels Finset.sum_cancels_of_partition_cancels
@[to_additive]
theorem prod_update_of_not_mem [DecidableEq α] {s : Finset α} {i : α} (h : i ∉ s) (f : α → β)
(b : β) : ∏ x ∈ s, Function.update f i b x = ∏ x ∈ s, f x := by
apply prod_congr rfl
intros j hj
have : j ≠ i := by
rintro rfl
exact h hj
simp [this]
#align finset.prod_update_of_not_mem Finset.prod_update_of_not_mem
#align finset.sum_update_of_not_mem Finset.sum_update_of_not_mem
@[to_additive]
theorem prod_update_of_mem [DecidableEq α] {s : Finset α} {i : α} (h : i ∈ s) (f : α → β) (b : β) :
∏ x ∈ s, Function.update f i b x = b * ∏ x ∈ s \ singleton i, f x := by
rw [update_eq_piecewise, prod_piecewise]
simp [h]
#align finset.prod_update_of_mem Finset.prod_update_of_mem
#align finset.sum_update_of_mem Finset.sum_update_of_mem
/-- If a product of a `Finset` of size at most 1 has a given value, so
do the terms in that product. -/
@[to_additive eq_of_card_le_one_of_sum_eq "If a sum of a `Finset` of size at most 1 has a given
value, so do the terms in that sum."]
theorem eq_of_card_le_one_of_prod_eq {s : Finset α} (hc : s.card ≤ 1) {f : α → β} {b : β}
(h : ∏ x ∈ s, f x = b) : ∀ x ∈ s, f x = b := by
intro x hx
by_cases hc0 : s.card = 0
· exact False.elim (card_ne_zero_of_mem hx hc0)
· have h1 : s.card = 1 := le_antisymm hc (Nat.one_le_of_lt (Nat.pos_of_ne_zero hc0))
rw [card_eq_one] at h1
cases' h1 with x2 hx2
rw [hx2, mem_singleton] at hx
simp_rw [hx2] at h
rw [hx]
rw [prod_singleton] at h
exact h
#align finset.eq_of_card_le_one_of_prod_eq Finset.eq_of_card_le_one_of_prod_eq
#align finset.eq_of_card_le_one_of_sum_eq Finset.eq_of_card_le_one_of_sum_eq
/-- Taking a product over `s : Finset α` is the same as multiplying the value on a single element
`f a` by the product of `s.erase a`.
See `Multiset.prod_map_erase` for the `Multiset` version. -/
@[to_additive "Taking a sum over `s : Finset α` is the same as adding the value on a single element
`f a` to the sum over `s.erase a`.
See `Multiset.sum_map_erase` for the `Multiset` version."]
theorem mul_prod_erase [DecidableEq α] (s : Finset α) (f : α → β) {a : α} (h : a ∈ s) :
(f a * ∏ x ∈ s.erase a, f x) = ∏ x ∈ s, f x := by
rw [← prod_insert (not_mem_erase a s), insert_erase h]
#align finset.mul_prod_erase Finset.mul_prod_erase
#align finset.add_sum_erase Finset.add_sum_erase
/-- A variant of `Finset.mul_prod_erase` with the multiplication swapped. -/
@[to_additive "A variant of `Finset.add_sum_erase` with the addition swapped."]
theorem prod_erase_mul [DecidableEq α] (s : Finset α) (f : α → β) {a : α} (h : a ∈ s) :
(∏ x ∈ s.erase a, f x) * f a = ∏ x ∈ s, f x := by rw [mul_comm, mul_prod_erase s f h]
#align finset.prod_erase_mul Finset.prod_erase_mul
#align finset.sum_erase_add Finset.sum_erase_add
/-- If a function applied at a point is 1, a product is unchanged by
removing that point, if present, from a `Finset`. -/
@[to_additive "If a function applied at a point is 0, a sum is unchanged by
removing that point, if present, from a `Finset`."]
theorem prod_erase [DecidableEq α] (s : Finset α) {f : α → β} {a : α} (h : f a = 1) :
∏ x ∈ s.erase a, f x = ∏ x ∈ s, f x := by
rw [← sdiff_singleton_eq_erase]
refine prod_subset sdiff_subset fun x hx hnx => ?_
rw [sdiff_singleton_eq_erase] at hnx
rwa [eq_of_mem_of_not_mem_erase hx hnx]
#align finset.prod_erase Finset.prod_erase
#align finset.sum_erase Finset.sum_erase
/-- See also `Finset.prod_boole`. -/
@[to_additive "See also `Finset.sum_boole`."]
theorem prod_ite_one (s : Finset α) (p : α → Prop) [DecidablePred p]
(h : ∀ i ∈ s, ∀ j ∈ s, p i → p j → i = j) (a : β) :
∏ i ∈ s, ite (p i) a 1 = ite (∃ i ∈ s, p i) a 1 := by
split_ifs with h
· obtain ⟨i, hi, hpi⟩ := h
rw [prod_eq_single_of_mem _ hi, if_pos hpi]
exact fun j hj hji ↦ if_neg fun hpj ↦ hji <| h _ hj _ hi hpj hpi
· push_neg at h
rw [prod_eq_one]
exact fun i hi => if_neg (h i hi)
#align finset.prod_ite_one Finset.prod_ite_one
#align finset.sum_ite_zero Finset.sum_ite_zero
@[to_additive]
theorem prod_erase_lt_of_one_lt {γ : Type*} [DecidableEq α] [OrderedCommMonoid γ]
[CovariantClass γ γ (· * ·) (· < ·)] {s : Finset α} {d : α} (hd : d ∈ s) {f : α → γ}
(hdf : 1 < f d) : ∏ m ∈ s.erase d, f m < ∏ m ∈ s, f m := by
conv in ∏ m ∈ s, f m => rw [← Finset.insert_erase hd]
rw [Finset.prod_insert (Finset.not_mem_erase d s)]
exact lt_mul_of_one_lt_left' _ hdf
#align finset.prod_erase_lt_of_one_lt Finset.prod_erase_lt_of_one_lt
#align finset.sum_erase_lt_of_pos Finset.sum_erase_lt_of_pos
/-- If a product is 1 and the function is 1 except possibly at one
point, it is 1 everywhere on the `Finset`. -/
@[to_additive "If a sum is 0 and the function is 0 except possibly at one
point, it is 0 everywhere on the `Finset`."]
theorem eq_one_of_prod_eq_one {s : Finset α} {f : α → β} {a : α} (hp : ∏ x ∈ s, f x = 1)
(h1 : ∀ x ∈ s, x ≠ a → f x = 1) : ∀ x ∈ s, f x = 1 := by
intro x hx
classical
by_cases h : x = a
· rw [h]
rw [h] at hx
rw [← prod_subset (singleton_subset_iff.2 hx) fun t ht ha => h1 t ht (not_mem_singleton.1 ha),
prod_singleton] at hp
exact hp
· exact h1 x hx h
#align finset.eq_one_of_prod_eq_one Finset.eq_one_of_prod_eq_one
#align finset.eq_zero_of_sum_eq_zero Finset.eq_zero_of_sum_eq_zero
@[to_additive sum_boole_nsmul]
theorem prod_pow_boole [DecidableEq α] (s : Finset α) (f : α → β) (a : α) :
(∏ x ∈ s, f x ^ ite (a = x) 1 0) = ite (a ∈ s) (f a) 1 := by simp
#align finset.prod_pow_boole Finset.prod_pow_boole
theorem prod_dvd_prod_of_dvd {S : Finset α} (g1 g2 : α → β) (h : ∀ a ∈ S, g1 a ∣ g2 a) :
S.prod g1 ∣ S.prod g2 := by
classical
induction' S using Finset.induction_on' with a T _haS _hTS haT IH
· simp
· rw [Finset.prod_insert haT, prod_insert haT]
exact mul_dvd_mul (h a <| T.mem_insert_self a) <| IH fun b hb ↦ h b <| mem_insert_of_mem hb
#align finset.prod_dvd_prod_of_dvd Finset.prod_dvd_prod_of_dvd
theorem prod_dvd_prod_of_subset {ι M : Type*} [CommMonoid M] (s t : Finset ι) (f : ι → M)
(h : s ⊆ t) : (∏ i ∈ s, f i) ∣ ∏ i ∈ t, f i :=
Multiset.prod_dvd_prod_of_le <| Multiset.map_le_map <| by simpa
#align finset.prod_dvd_prod_of_subset Finset.prod_dvd_prod_of_subset
end CommMonoid
section CancelCommMonoid
variable [DecidableEq ι] [CancelCommMonoid α] {s t : Finset ι} {f : ι → α}
@[to_additive]
lemma prod_sdiff_eq_prod_sdiff_iff :
∏ i ∈ s \ t, f i = ∏ i ∈ t \ s, f i ↔ ∏ i ∈ s, f i = ∏ i ∈ t, f i :=
eq_comm.trans $ eq_iff_eq_of_mul_eq_mul $ by
rw [← prod_union disjoint_sdiff_self_left, ← prod_union disjoint_sdiff_self_left,
sdiff_union_self_eq_union, sdiff_union_self_eq_union, union_comm]
@[to_additive]
lemma prod_sdiff_ne_prod_sdiff_iff :
∏ i ∈ s \ t, f i ≠ ∏ i ∈ t \ s, f i ↔ ∏ i ∈ s, f i ≠ ∏ i ∈ t, f i :=
prod_sdiff_eq_prod_sdiff_iff.not
end CancelCommMonoid
theorem card_eq_sum_ones (s : Finset α) : s.card = ∑ x ∈ s, 1 := by simp
#align finset.card_eq_sum_ones Finset.card_eq_sum_ones
theorem sum_const_nat {m : ℕ} {f : α → ℕ} (h₁ : ∀ x ∈ s, f x = m) :
∑ x ∈ s, f x = card s * m := by
rw [← Nat.nsmul_eq_mul, ← sum_const]
apply sum_congr rfl h₁
#align finset.sum_const_nat Finset.sum_const_nat
lemma sum_card_fiberwise_eq_card_filter {κ : Type*} [DecidableEq κ] (s : Finset ι) (t : Finset κ)
(g : ι → κ) : ∑ j ∈ t, (s.filter fun i ↦ g i = j).card = (s.filter fun i ↦ g i ∈ t).card := by
simpa only [card_eq_sum_ones] using sum_fiberwise_eq_sum_filter _ _ _ _
lemma card_filter (p) [DecidablePred p] (s : Finset α) :
(filter p s).card = ∑ a ∈ s, ite (p a) 1 0 := by simp [sum_ite]
#align finset.card_filter Finset.card_filter
section Opposite
open MulOpposite
/-- Moving to the opposite additive commutative monoid commutes with summing. -/
@[simp]
theorem op_sum [AddCommMonoid β] {s : Finset α} (f : α → β) :
op (∑ x ∈ s, f x) = ∑ x ∈ s, op (f x) :=
map_sum (opAddEquiv : β ≃+ βᵐᵒᵖ) _ _
#align finset.op_sum Finset.op_sum
@[simp]
theorem unop_sum [AddCommMonoid β] {s : Finset α} (f : α → βᵐᵒᵖ) :
unop (∑ x ∈ s, f x) = ∑ x ∈ s, unop (f x) :=
map_sum (opAddEquiv : β ≃+ βᵐᵒᵖ).symm _ _
#align finset.unop_sum Finset.unop_sum
end Opposite
section DivisionCommMonoid
variable [DivisionCommMonoid β]
@[to_additive (attr := simp)]
theorem prod_inv_distrib : (∏ x ∈ s, (f x)⁻¹) = (∏ x ∈ s, f x)⁻¹ :=
Multiset.prod_map_inv
#align finset.prod_inv_distrib Finset.prod_inv_distrib
#align finset.sum_neg_distrib Finset.sum_neg_distrib
@[to_additive (attr := simp)]
theorem prod_div_distrib : ∏ x ∈ s, f x / g x = (∏ x ∈ s, f x) / ∏ x ∈ s, g x :=
Multiset.prod_map_div
#align finset.prod_div_distrib Finset.prod_div_distrib
#align finset.sum_sub_distrib Finset.sum_sub_distrib
@[to_additive]
theorem prod_zpow (f : α → β) (s : Finset α) (n : ℤ) : ∏ a ∈ s, f a ^ n = (∏ a ∈ s, f a) ^ n :=
Multiset.prod_map_zpow
#align finset.prod_zpow Finset.prod_zpow
#align finset.sum_zsmul Finset.sum_zsmul
end DivisionCommMonoid
section CommGroup
variable [CommGroup β] [DecidableEq α]
@[to_additive (attr := simp)]
theorem prod_sdiff_eq_div (h : s₁ ⊆ s₂) :
∏ x ∈ s₂ \ s₁, f x = (∏ x ∈ s₂, f x) / ∏ x ∈ s₁, f x := by
rw [eq_div_iff_mul_eq', prod_sdiff h]
#align finset.prod_sdiff_eq_div Finset.prod_sdiff_eq_div
#align finset.sum_sdiff_eq_sub Finset.sum_sdiff_eq_sub
@[to_additive]
theorem prod_sdiff_div_prod_sdiff :
(∏ x ∈ s₂ \ s₁, f x) / ∏ x ∈ s₁ \ s₂, f x = (∏ x ∈ s₂, f x) / ∏ x ∈ s₁, f x := by
simp [← Finset.prod_sdiff (@inf_le_left _ _ s₁ s₂), ← Finset.prod_sdiff (@inf_le_right _ _ s₁ s₂)]
#align finset.prod_sdiff_div_prod_sdiff Finset.prod_sdiff_div_prod_sdiff
#align finset.sum_sdiff_sub_sum_sdiff Finset.sum_sdiff_sub_sum_sdiff
@[to_additive (attr := simp)]
theorem prod_erase_eq_div {a : α} (h : a ∈ s) :
∏ x ∈ s.erase a, f x = (∏ x ∈ s, f x) / f a := by
rw [eq_div_iff_mul_eq', prod_erase_mul _ _ h]
#align finset.prod_erase_eq_div Finset.prod_erase_eq_div
#align finset.sum_erase_eq_sub Finset.sum_erase_eq_sub
end CommGroup
@[simp]
theorem card_sigma {σ : α → Type*} (s : Finset α) (t : ∀ a, Finset (σ a)) :
card (s.sigma t) = ∑ a ∈ s, card (t a) :=
Multiset.card_sigma _ _
#align finset.card_sigma Finset.card_sigma
@[simp]
theorem card_disjiUnion (s : Finset α) (t : α → Finset β) (h) :
(s.disjiUnion t h).card = s.sum fun i => (t i).card :=
Multiset.card_bind _ _
#align finset.card_disj_Union Finset.card_disjiUnion
theorem card_biUnion [DecidableEq β] {s : Finset α} {t : α → Finset β}
(h : ∀ x ∈ s, ∀ y ∈ s, x ≠ y → Disjoint (t x) (t y)) :
(s.biUnion t).card = ∑ u ∈ s, card (t u) :=
calc
(s.biUnion t).card = ∑ i ∈ s.biUnion t, 1 := card_eq_sum_ones _
_ = ∑ a ∈ s, ∑ _i ∈ t a, 1 := Finset.sum_biUnion h
_ = ∑ u ∈ s, card (t u) := by simp_rw [card_eq_sum_ones]
#align finset.card_bUnion Finset.card_biUnion
theorem card_biUnion_le [DecidableEq β] {s : Finset α} {t : α → Finset β} :
(s.biUnion t).card ≤ ∑ a ∈ s, (t a).card :=
haveI := Classical.decEq α
Finset.induction_on s (by simp) fun a s has ih =>
calc
((insert a s).biUnion t).card ≤ (t a).card + (s.biUnion t).card := by
{ rw [biUnion_insert]; exact Finset.card_union_le _ _ }
_ ≤ ∑ a ∈ insert a s, card (t a) := by rw [sum_insert has]; exact Nat.add_le_add_left ih _
#align finset.card_bUnion_le Finset.card_biUnion_le
theorem card_eq_sum_card_fiberwise [DecidableEq β] {f : α → β} {s : Finset α} {t : Finset β}
(H : ∀ x ∈ s, f x ∈ t) : s.card = ∑ a ∈ t, (s.filter fun x => f x = a).card := by
simp only [card_eq_sum_ones, sum_fiberwise_of_maps_to H]
#align finset.card_eq_sum_card_fiberwise Finset.card_eq_sum_card_fiberwise
theorem card_eq_sum_card_image [DecidableEq β] (f : α → β) (s : Finset α) :
s.card = ∑ a ∈ s.image f, (s.filter fun x => f x = a).card :=
card_eq_sum_card_fiberwise fun _ => mem_image_of_mem _
#align finset.card_eq_sum_card_image Finset.card_eq_sum_card_image
theorem mem_sum {f : α → Multiset β} (s : Finset α) (b : β) :
(b ∈ ∑ x ∈ s, f x) ↔ ∃ a ∈ s, b ∈ f a := by
classical
refine s.induction_on (by simp) ?_
intro a t hi ih
simp [sum_insert hi, ih, or_and_right, exists_or]
#align finset.mem_sum Finset.mem_sum
@[to_additive]
theorem prod_unique_nonempty {α β : Type*} [CommMonoid β] [Unique α] (s : Finset α) (f : α → β)
(h : s.Nonempty) : ∏ x ∈ s, f x = f default := by
rw [h.eq_singleton_default, Finset.prod_singleton]
#align finset.prod_unique_nonempty Finset.prod_unique_nonempty
#align finset.sum_unique_nonempty Finset.sum_unique_nonempty
theorem sum_nat_mod (s : Finset α) (n : ℕ) (f : α → ℕ) :
(∑ i ∈ s, f i) % n = (∑ i ∈ s, f i % n) % n :=
(Multiset.sum_nat_mod _ _).trans <| by rw [Finset.sum, Multiset.map_map]; rfl
#align finset.sum_nat_mod Finset.sum_nat_mod
theorem prod_nat_mod (s : Finset α) (n : ℕ) (f : α → ℕ) :
(∏ i ∈ s, f i) % n = (∏ i ∈ s, f i % n) % n :=
(Multiset.prod_nat_mod _ _).trans <| by rw [Finset.prod, Multiset.map_map]; rfl
#align finset.prod_nat_mod Finset.prod_nat_mod
theorem sum_int_mod (s : Finset α) (n : ℤ) (f : α → ℤ) :
(∑ i ∈ s, f i) % n = (∑ i ∈ s, f i % n) % n :=
(Multiset.sum_int_mod _ _).trans <| by rw [Finset.sum, Multiset.map_map]; rfl
#align finset.sum_int_mod Finset.sum_int_mod
theorem prod_int_mod (s : Finset α) (n : ℤ) (f : α → ℤ) :
(∏ i ∈ s, f i) % n = (∏ i ∈ s, f i % n) % n :=
(Multiset.prod_int_mod _ _).trans <| by rw [Finset.prod, Multiset.map_map]; rfl
#align finset.prod_int_mod Finset.prod_int_mod
end Finset
namespace Fintype
variable {ι κ α : Type*} [Fintype ι] [Fintype κ]
open Finset
section CommMonoid
variable [CommMonoid α]
/-- `Fintype.prod_bijective` is a variant of `Finset.prod_bij` that accepts `Function.Bijective`.
See `Function.Bijective.prod_comp` for a version without `h`. -/
@[to_additive "`Fintype.sum_bijective` is a variant of `Finset.sum_bij` that accepts
`Function.Bijective`.
See `Function.Bijective.sum_comp` for a version without `h`. "]
lemma prod_bijective (e : ι → κ) (he : e.Bijective) (f : ι → α) (g : κ → α)
(h : ∀ x, f x = g (e x)) : ∏ x, f x = ∏ x, g x :=
prod_equiv (.ofBijective e he) (by simp) (by simp [h])
#align fintype.prod_bijective Fintype.prod_bijective
#align fintype.sum_bijective Fintype.sum_bijective
@[to_additive] alias _root_.Function.Bijective.finset_prod := prod_bijective
/-- `Fintype.prod_equiv` is a specialization of `Finset.prod_bij` that
automatically fills in most arguments.
See `Equiv.prod_comp` for a version without `h`.
-/
@[to_additive "`Fintype.sum_equiv` is a specialization of `Finset.sum_bij` that
automatically fills in most arguments.
See `Equiv.sum_comp` for a version without `h`."]
lemma prod_equiv (e : ι ≃ κ) (f : ι → α) (g : κ → α) (h : ∀ x, f x = g (e x)) :
∏ x, f x = ∏ x, g x := prod_bijective _ e.bijective _ _ h
#align fintype.prod_equiv Fintype.prod_equiv
#align fintype.sum_equiv Fintype.sum_equiv
@[to_additive]
lemma _root_.Function.Bijective.prod_comp {e : ι → κ} (he : e.Bijective) (g : κ → α) :
∏ i, g (e i) = ∏ i, g i := prod_bijective _ he _ _ fun _ ↦ rfl
#align function.bijective.prod_comp Function.Bijective.prod_comp
#align function.bijective.sum_comp Function.Bijective.sum_comp
@[to_additive]
lemma _root_.Equiv.prod_comp (e : ι ≃ κ) (g : κ → α) : ∏ i, g (e i) = ∏ i, g i :=
prod_equiv e _ _ fun _ ↦ rfl
#align equiv.prod_comp Equiv.prod_comp
#align equiv.sum_comp Equiv.sum_comp
@[to_additive]
lemma prod_of_injective (e : ι → κ) (he : Injective e) (f : ι → α) (g : κ → α)
(h' : ∀ i ∉ Set.range e, g i = 1) (h : ∀ i, f i = g (e i)) : ∏ i, f i = ∏ j, g j :=
prod_of_injOn e he.injOn (by simp) (by simpa using h') (fun i _ ↦ h i)
@[to_additive]
lemma prod_fiberwise [DecidableEq κ] (g : ι → κ) (f : ι → α) :
∏ j, ∏ i : {i // g i = j}, f i = ∏ i, f i := by
rw [← Finset.prod_fiberwise _ g f]
congr with j
exact (prod_subtype _ (by simp) _).symm
#align fintype.prod_fiberwise Fintype.prod_fiberwise
#align fintype.sum_fiberwise Fintype.sum_fiberwise
@[to_additive]
lemma prod_fiberwise' [DecidableEq κ] (g : ι → κ) (f : κ → α) :
∏ j, ∏ _i : {i // g i = j}, f j = ∏ i, f (g i) := by
rw [← Finset.prod_fiberwise' _ g f]
congr with j
exact (prod_subtype _ (by simp) fun _ ↦ _).symm
@[to_additive]
theorem prod_unique {α β : Type*} [CommMonoid β] [Unique α] [Fintype α] (f : α → β) :
∏ x : α, f x = f default := by rw [univ_unique, prod_singleton]
#align fintype.prod_unique Fintype.prod_unique
#align fintype.sum_unique Fintype.sum_unique
@[to_additive]
theorem prod_empty {α β : Type*} [CommMonoid β] [IsEmpty α] [Fintype α] (f : α → β) :
∏ x : α, f x = 1 :=
Finset.prod_of_empty _
#align fintype.prod_empty Fintype.prod_empty
#align fintype.sum_empty Fintype.sum_empty
@[to_additive]
theorem prod_subsingleton {α β : Type*} [CommMonoid β] [Subsingleton α] [Fintype α] (f : α → β)
(a : α) : ∏ x : α, f x = f a := by
haveI : Unique α := uniqueOfSubsingleton a
rw [prod_unique f, Subsingleton.elim default a]
#align fintype.prod_subsingleton Fintype.prod_subsingleton
#align fintype.sum_subsingleton Fintype.sum_subsingleton
@[to_additive]
theorem prod_subtype_mul_prod_subtype {α β : Type*} [Fintype α] [CommMonoid β] (p : α → Prop)
(f : α → β) [DecidablePred p] :
(∏ i : { x // p x }, f i) * ∏ i : { x // ¬p x }, f i = ∏ i, f i := by
classical
let s := { x | p x }.toFinset
rw [← Finset.prod_subtype s, ← Finset.prod_subtype sᶜ]
· exact Finset.prod_mul_prod_compl _ _
· simp [s]
· simp [s]
#align fintype.prod_subtype_mul_prod_subtype Fintype.prod_subtype_mul_prod_subtype
#align fintype.sum_subtype_add_sum_subtype Fintype.sum_subtype_add_sum_subtype
@[to_additive] lemma prod_subset {s : Finset ι} {f : ι → α} (h : ∀ i, f i ≠ 1 → i ∈ s) :
∏ i ∈ s, f i = ∏ i, f i :=
Finset.prod_subset s.subset_univ $ by simpa [not_imp_comm (a := _ ∈ s)]
@[to_additive]
lemma prod_ite_eq_ite_exists (p : ι → Prop) [DecidablePred p] (h : ∀ i j, p i → p j → i = j)
(a : α) : ∏ i, ite (p i) a 1 = ite (∃ i, p i) a 1 := by
simp [prod_ite_one univ p (by simpa using h)]
variable [DecidableEq ι]
/-- See also `Finset.prod_dite_eq`. -/
@[to_additive "See also `Finset.sum_dite_eq`."] lemma prod_dite_eq (i : ι) (f : ∀ j, i = j → α) :
∏ j, (if h : i = j then f j h else 1) = f i rfl := by
rw [Finset.prod_dite_eq, if_pos (mem_univ _)]
/-- See also `Finset.prod_dite_eq'`. -/
@[to_additive "See also `Finset.sum_dite_eq'`."] lemma prod_dite_eq' (i : ι) (f : ∀ j, j = i → α) :
∏ j, (if h : j = i then f j h else 1) = f i rfl := by
rw [Finset.prod_dite_eq', if_pos (mem_univ _)]
/-- See also `Finset.prod_ite_eq`. -/
@[to_additive "See also `Finset.sum_ite_eq`."]
lemma prod_ite_eq (i : ι) (f : ι → α) : ∏ j, (if i = j then f j else 1) = f i := by
rw [Finset.prod_ite_eq, if_pos (mem_univ _)]
/-- See also `Finset.prod_ite_eq'`. -/
@[to_additive "See also `Finset.sum_ite_eq'`."]
lemma prod_ite_eq' (i : ι) (f : ι → α) : ∏ j, (if j = i then f j else 1) = f i := by
rw [Finset.prod_ite_eq', if_pos (mem_univ _)]
/-- See also `Finset.prod_pi_mulSingle`. -/
@[to_additive "See also `Finset.sum_pi_single`."]
lemma prod_pi_mulSingle {α : ι → Type*} [∀ i, CommMonoid (α i)] (i : ι) (f : ∀ i, α i) :
∏ j, Pi.mulSingle j (f j) i = f i := prod_dite_eq _ _
/-- See also `Finset.prod_pi_mulSingle'`. -/
@[to_additive "See also `Finset.sum_pi_single'`."]
lemma prod_pi_mulSingle' (i : ι) (a : α) : ∏ j, Pi.mulSingle i a j = a := prod_dite_eq' _ _
end CommMonoid
end Fintype
namespace Finset
variable [CommMonoid α]
@[to_additive (attr := simp)]
lemma prod_attach_univ [Fintype ι] (f : {i // i ∈ @univ ι _} → α) :
∏ i ∈ univ.attach, f i = ∏ i, f ⟨i, mem_univ _⟩ :=
Fintype.prod_equiv (Equiv.subtypeUnivEquiv mem_univ) _ _ $ by simp
#align finset.prod_attach_univ Finset.prod_attach_univ
#align finset.sum_attach_univ Finset.sum_attach_univ
@[to_additive]
theorem prod_erase_attach [DecidableEq ι] {s : Finset ι} (f : ι → α) (i : ↑s) :
∏ j ∈ s.attach.erase i, f ↑j = ∏ j ∈ s.erase ↑i, f j := by
rw [← Function.Embedding.coe_subtype, ← prod_map]
simp [attach_map_val]
end Finset
namespace List
@[to_additive]
theorem prod_toFinset {M : Type*} [DecidableEq α] [CommMonoid M] (f : α → M) :
∀ {l : List α} (_hl : l.Nodup), l.toFinset.prod f = (l.map f).prod
| [], _ => by simp
| a :: l, hl => by
let ⟨not_mem, hl⟩ := List.nodup_cons.mp hl
simp [Finset.prod_insert (mt List.mem_toFinset.mp not_mem), prod_toFinset _ hl]
#align list.prod_to_finset List.prod_toFinset
#align list.sum_to_finset List.sum_toFinset
@[simp]
theorem sum_toFinset_count_eq_length [DecidableEq α] (l : List α) :
∑ a in l.toFinset, l.count a = l.length := by
simpa using (Finset.sum_list_map_count l fun _ => (1 : ℕ)).symm
end List
namespace Multiset
theorem disjoint_list_sum_left {a : Multiset α} {l : List (Multiset α)} :
Multiset.Disjoint l.sum a ↔ ∀ b ∈ l, Multiset.Disjoint b a := by
induction' l with b bs ih
· simp only [zero_disjoint, List.not_mem_nil, IsEmpty.forall_iff, forall_const, List.sum_nil]
· simp_rw [List.sum_cons, disjoint_add_left, List.mem_cons, forall_eq_or_imp]
simp [and_congr_left_iff, iff_self_iff, ih]
#align multiset.disjoint_list_sum_left Multiset.disjoint_list_sum_left
theorem disjoint_list_sum_right {a : Multiset α} {l : List (Multiset α)} :
Multiset.Disjoint a l.sum ↔ ∀ b ∈ l, Multiset.Disjoint a b := by
simpa only [@disjoint_comm _ a] using disjoint_list_sum_left
#align multiset.disjoint_list_sum_right Multiset.disjoint_list_sum_right
theorem disjoint_sum_left {a : Multiset α} {i : Multiset (Multiset α)} :
Multiset.Disjoint i.sum a ↔ ∀ b ∈ i, Multiset.Disjoint b a :=
Quotient.inductionOn i fun l => by
rw [quot_mk_to_coe, Multiset.sum_coe]
exact disjoint_list_sum_left
#align multiset.disjoint_sum_left Multiset.disjoint_sum_left
theorem disjoint_sum_right {a : Multiset α} {i : Multiset (Multiset α)} :
Multiset.Disjoint a i.sum ↔ ∀ b ∈ i, Multiset.Disjoint a b := by
simpa only [@disjoint_comm _ a] using disjoint_sum_left
#align multiset.disjoint_sum_right Multiset.disjoint_sum_right
theorem disjoint_finset_sum_left {β : Type*} {i : Finset β} {f : β → Multiset α} {a : Multiset α} :
Multiset.Disjoint (i.sum f) a ↔ ∀ b ∈ i, Multiset.Disjoint (f b) a := by
convert @disjoint_sum_left _ a (map f i.val)
simp [and_congr_left_iff, iff_self_iff]
#align multiset.disjoint_finset_sum_left Multiset.disjoint_finset_sum_left
theorem disjoint_finset_sum_right {β : Type*} {i : Finset β} {f : β → Multiset α}
{a : Multiset α} : Multiset.Disjoint a (i.sum f) ↔ ∀ b ∈ i, Multiset.Disjoint a (f b) := by
simpa only [disjoint_comm] using disjoint_finset_sum_left
#align multiset.disjoint_finset_sum_right Multiset.disjoint_finset_sum_right
variable [DecidableEq α]
@[simp]
theorem toFinset_sum_count_eq (s : Multiset α) : ∑ a in s.toFinset, s.count a = card s := by
simpa using (Finset.sum_multiset_map_count s (fun _ => (1 : ℕ))).symm
#align multiset.to_finset_sum_count_eq Multiset.toFinset_sum_count_eq
@[simp]
theorem sum_count_eq [Fintype α] (s : Multiset α) : ∑ a, s.count a = Multiset.card s := by
rw [← toFinset_sum_count_eq, ← Finset.sum_filter_ne_zero]
congr
ext
simp
theorem count_sum' {s : Finset β} {a : α} {f : β → Multiset α} :
count a (∑ x ∈ s, f x) = ∑ x ∈ s, count a (f x) := by
dsimp only [Finset.sum]
rw [count_sum]
#align multiset.count_sum' Multiset.count_sum'
@[simp]
theorem toFinset_sum_count_nsmul_eq (s : Multiset α) :
∑ a ∈ s.toFinset, s.count a • {a} = s := by
rw [← Finset.sum_multiset_map_count, Multiset.sum_map_singleton]
#align multiset.to_finset_sum_count_nsmul_eq Multiset.toFinset_sum_count_nsmul_eq
theorem exists_smul_of_dvd_count (s : Multiset α) {k : ℕ}
(h : ∀ a : α, a ∈ s → k ∣ Multiset.count a s) : ∃ u : Multiset α, s = k • u := by
use ∑ a ∈ s.toFinset, (s.count a / k) • {a}
have h₂ :
(∑ x ∈ s.toFinset, k • (count x s / k) • ({x} : Multiset α)) =
∑ x ∈ s.toFinset, count x s • {x} := by
apply Finset.sum_congr rfl
intro x hx
rw [← mul_nsmul', Nat.mul_div_cancel' (h x (mem_toFinset.mp hx))]
rw [← Finset.sum_nsmul, h₂, toFinset_sum_count_nsmul_eq]
#align multiset.exists_smul_of_dvd_count Multiset.exists_smul_of_dvd_count
theorem toFinset_prod_dvd_prod [CommMonoid α] (S : Multiset α) : S.toFinset.prod id ∣ S.prod := by
rw [Finset.prod_eq_multiset_prod]
refine Multiset.prod_dvd_prod_of_le ?_
simp [Multiset.dedup_le S]
#align multiset.to_finset_prod_dvd_prod Multiset.toFinset_prod_dvd_prod
@[to_additive]
theorem prod_sum {α : Type*} {ι : Type*} [CommMonoid α] (f : ι → Multiset α) (s : Finset ι) :
(∑ x ∈ s, f x).prod = ∏ x ∈ s, (f x).prod := by
classical
induction' s using Finset.induction_on with a t hat ih
· rw [Finset.sum_empty, Finset.prod_empty, Multiset.prod_zero]
· rw [Finset.sum_insert hat, Finset.prod_insert hat, Multiset.prod_add, ih]
#align multiset.prod_sum Multiset.prod_sum
#align multiset.sum_sum Multiset.sum_sum
end Multiset
@[simp, norm_cast]
theorem Units.coe_prod {M : Type*} [CommMonoid M] (f : α → Mˣ) (s : Finset α) :
(↑(∏ i ∈ s, f i) : M) = ∏ i ∈ s, (f i : M) :=
map_prod (Units.coeHom M) _ _
#align units.coe_prod Units.coe_prod
theorem nat_abs_sum_le {ι : Type*} (s : Finset ι) (f : ι → ℤ) :
(∑ i ∈ s, f i).natAbs ≤ ∑ i ∈ s, (f i).natAbs := by
classical
induction' s using Finset.induction_on with i s his IH
· simp only [Finset.sum_empty, Int.natAbs_zero, le_refl]
· simp only [his, Finset.sum_insert, not_false_iff]
exact (Int.natAbs_add_le _ _).trans (Nat.add_le_add_left IH _)
#align nat_abs_sum_le nat_abs_sum_le
/-! ### `Additive`, `Multiplicative` -/
open Additive Multiplicative
section Monoid
variable [Monoid α]
@[simp]
theorem ofMul_list_prod (s : List α) : ofMul s.prod = (s.map ofMul).sum := by simp [ofMul]; rfl
#align of_mul_list_prod ofMul_list_prod
@[simp]
theorem toMul_list_sum (s : List (Additive α)) : toMul s.sum = (s.map toMul).prod := by
simp [toMul, ofMul]; rfl
#align to_mul_list_sum toMul_list_sum
end Monoid
section AddMonoid
variable [AddMonoid α]
@[simp]
theorem ofAdd_list_prod (s : List α) : ofAdd s.sum = (s.map ofAdd).prod := by simp [ofAdd]; rfl
#align of_add_list_prod ofAdd_list_prod
@[simp]
theorem toAdd_list_sum (s : List (Multiplicative α)) : toAdd s.prod = (s.map toAdd).sum := by
simp [toAdd, ofAdd]; rfl
#align to_add_list_sum toAdd_list_sum
end AddMonoid
section CommMonoid
variable [CommMonoid α]
@[simp]
theorem ofMul_multiset_prod (s : Multiset α) : ofMul s.prod = (s.map ofMul).sum := by
simp [ofMul]; rfl
#align of_mul_multiset_prod ofMul_multiset_prod
@[simp]
| Mathlib/Algebra/BigOperators/Group/Finset.lean | 2,571 | 2,572 | theorem toMul_multiset_sum (s : Multiset (Additive α)) : toMul s.sum = (s.map toMul).prod := by |
simp [toMul, ofMul]; rfl
|
/-
Copyright (c) 2022 Adam Topaz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Adam Topaz, Junyan Xu, Jack McKoen
-/
import Mathlib.RingTheory.Valuation.ValuationRing
import Mathlib.RingTheory.Localization.AsSubring
import Mathlib.Algebra.Ring.Subring.Pointwise
import Mathlib.AlgebraicGeometry.PrimeSpectrum.Basic
#align_import ring_theory.valuation.valuation_subring from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2"
/-!
# Valuation subrings of a field
## Projects
The order structure on `ValuationSubring K`.
-/
universe u
open scoped Classical
noncomputable section
variable (K : Type u) [Field K]
/-- A valuation subring of a field `K` is a subring `A` such that for every `x : K`,
either `x ∈ A` or `x⁻¹ ∈ A`. -/
structure ValuationSubring extends Subring K where
mem_or_inv_mem' : ∀ x : K, x ∈ carrier ∨ x⁻¹ ∈ carrier
#align valuation_subring ValuationSubring
namespace ValuationSubring
variable {K}
variable (A : ValuationSubring K)
instance : SetLike (ValuationSubring K) K where
coe A := A.toSubring
coe_injective' := by
intro ⟨_, _⟩ ⟨_, _⟩ h
replace h := SetLike.coe_injective' h
congr
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove that
theorem mem_carrier (x : K) : x ∈ A.carrier ↔ x ∈ A := Iff.refl _
#align valuation_subring.mem_carrier ValuationSubring.mem_carrier
@[simp]
theorem mem_toSubring (x : K) : x ∈ A.toSubring ↔ x ∈ A := Iff.refl _
#align valuation_subring.mem_to_subring ValuationSubring.mem_toSubring
@[ext]
theorem ext (A B : ValuationSubring K) (h : ∀ x, x ∈ A ↔ x ∈ B) : A = B := SetLike.ext h
#align valuation_subring.ext ValuationSubring.ext
theorem zero_mem : (0 : K) ∈ A := A.toSubring.zero_mem
#align valuation_subring.zero_mem ValuationSubring.zero_mem
theorem one_mem : (1 : K) ∈ A := A.toSubring.one_mem
#align valuation_subring.one_mem ValuationSubring.one_mem
theorem add_mem (x y : K) : x ∈ A → y ∈ A → x + y ∈ A := A.toSubring.add_mem
#align valuation_subring.add_mem ValuationSubring.add_mem
theorem mul_mem (x y : K) : x ∈ A → y ∈ A → x * y ∈ A := A.toSubring.mul_mem
#align valuation_subring.mul_mem ValuationSubring.mul_mem
theorem neg_mem (x : K) : x ∈ A → -x ∈ A := A.toSubring.neg_mem
#align valuation_subring.neg_mem ValuationSubring.neg_mem
theorem mem_or_inv_mem (x : K) : x ∈ A ∨ x⁻¹ ∈ A := A.mem_or_inv_mem' _
#align valuation_subring.mem_or_inv_mem ValuationSubring.mem_or_inv_mem
instance : SubringClass (ValuationSubring K) K where
zero_mem := zero_mem
add_mem {_} a b := add_mem _ a b
one_mem := one_mem
mul_mem {_} a b := mul_mem _ a b
neg_mem {_} x := neg_mem _ x
theorem toSubring_injective : Function.Injective (toSubring : ValuationSubring K → Subring K) :=
fun x y h => by cases x; cases y; congr
#align valuation_subring.to_subring_injective ValuationSubring.toSubring_injective
instance : CommRing A :=
show CommRing A.toSubring by infer_instance
instance : IsDomain A :=
show IsDomain A.toSubring by infer_instance
instance : Top (ValuationSubring K) :=
Top.mk <| { (⊤ : Subring K) with mem_or_inv_mem' := fun _ => Or.inl trivial }
theorem mem_top (x : K) : x ∈ (⊤ : ValuationSubring K) :=
trivial
#align valuation_subring.mem_top ValuationSubring.mem_top
theorem le_top : A ≤ ⊤ := fun _a _ha => mem_top _
#align valuation_subring.le_top ValuationSubring.le_top
instance : OrderTop (ValuationSubring K) where
top := ⊤
le_top := le_top
instance : Inhabited (ValuationSubring K) :=
⟨⊤⟩
instance : ValuationRing A where
cond' a b := by
by_cases h : (b : K) = 0
· use 0
left
ext
simp [h]
by_cases h : (a : K) = 0
· use 0; right
ext
simp [h]
cases' A.mem_or_inv_mem (a / b) with hh hh
· use ⟨a / b, hh⟩
right
ext
field_simp
· rw [show (a / b : K)⁻¹ = b / a by field_simp] at hh
use ⟨b / a, hh⟩;
left
ext
field_simp
instance : Algebra A K :=
show Algebra A.toSubring K by infer_instance
-- Porting note: Somehow it cannot find this instance and I'm too lazy to debug. wrong prio?
instance localRing : LocalRing A := ValuationRing.localRing A
@[simp]
theorem algebraMap_apply (a : A) : algebraMap A K a = a := rfl
#align valuation_subring.algebra_map_apply ValuationSubring.algebraMap_apply
instance : IsFractionRing A K where
map_units' := fun ⟨y, hy⟩ =>
(Units.mk0 (y : K) fun c => nonZeroDivisors.ne_zero hy <| Subtype.ext c).isUnit
surj' z := by
by_cases h : z = 0; · use (0, 1); simp [h]
cases' A.mem_or_inv_mem z with hh hh
· use (⟨z, hh⟩, 1); simp
· refine ⟨⟨1, ⟨⟨_, hh⟩, ?_⟩⟩, mul_inv_cancel h⟩
exact mem_nonZeroDivisors_iff_ne_zero.2 fun c => h (inv_eq_zero.mp (congr_arg Subtype.val c))
exists_of_eq {a b} h := ⟨1, by ext; simpa using h⟩
/-- The value group of the valuation associated to `A`. Note: it is actually a group with zero. -/
def ValueGroup :=
ValuationRing.ValueGroup A K
-- deriving LinearOrderedCommGroupWithZero
#align valuation_subring.value_group ValuationSubring.ValueGroup
-- Porting note: see https://github.com/leanprover-community/mathlib4/issues/5020
instance : LinearOrderedCommGroupWithZero (ValueGroup A) := by
unfold ValueGroup
infer_instance
/-- Any valuation subring of `K` induces a natural valuation on `K`. -/
def valuation : Valuation K A.ValueGroup :=
ValuationRing.valuation A K
#align valuation_subring.valuation ValuationSubring.valuation
instance inhabitedValueGroup : Inhabited A.ValueGroup := ⟨A.valuation 0⟩
#align valuation_subring.inhabited_value_group ValuationSubring.inhabitedValueGroup
theorem valuation_le_one (a : A) : A.valuation a ≤ 1 :=
(ValuationRing.mem_integer_iff A K _).2 ⟨a, rfl⟩
#align valuation_subring.valuation_le_one ValuationSubring.valuation_le_one
theorem mem_of_valuation_le_one (x : K) (h : A.valuation x ≤ 1) : x ∈ A :=
let ⟨a, ha⟩ := (ValuationRing.mem_integer_iff A K x).1 h
ha ▸ a.2
#align valuation_subring.mem_of_valuation_le_one ValuationSubring.mem_of_valuation_le_one
theorem valuation_le_one_iff (x : K) : A.valuation x ≤ 1 ↔ x ∈ A :=
⟨mem_of_valuation_le_one _ _, fun ha => A.valuation_le_one ⟨x, ha⟩⟩
#align valuation_subring.valuation_le_one_iff ValuationSubring.valuation_le_one_iff
theorem valuation_eq_iff (x y : K) : A.valuation x = A.valuation y ↔ ∃ a : Aˣ, (a : K) * y = x :=
Quotient.eq''
#align valuation_subring.valuation_eq_iff ValuationSubring.valuation_eq_iff
theorem valuation_le_iff (x y : K) : A.valuation x ≤ A.valuation y ↔ ∃ a : A, (a : K) * y = x :=
Iff.rfl
#align valuation_subring.valuation_le_iff ValuationSubring.valuation_le_iff
theorem valuation_surjective : Function.Surjective A.valuation := surjective_quot_mk _
#align valuation_subring.valuation_surjective ValuationSubring.valuation_surjective
theorem valuation_unit (a : Aˣ) : A.valuation a = 1 := by
rw [← A.valuation.map_one, valuation_eq_iff]; use a; simp
#align valuation_subring.valuation_unit ValuationSubring.valuation_unit
theorem valuation_eq_one_iff (a : A) : IsUnit a ↔ A.valuation a = 1 :=
⟨fun h => A.valuation_unit h.unit, fun h => by
have ha : (a : K) ≠ 0 := by
intro c
rw [c, A.valuation.map_zero] at h
exact zero_ne_one h
have ha' : (a : K)⁻¹ ∈ A := by rw [← valuation_le_one_iff, map_inv₀, h, inv_one]
apply isUnit_of_mul_eq_one a ⟨a⁻¹, ha'⟩; ext; field_simp⟩
#align valuation_subring.valuation_eq_one_iff ValuationSubring.valuation_eq_one_iff
theorem valuation_lt_one_or_eq_one (a : A) : A.valuation a < 1 ∨ A.valuation a = 1 :=
lt_or_eq_of_le (A.valuation_le_one a)
#align valuation_subring.valuation_lt_one_or_eq_one ValuationSubring.valuation_lt_one_or_eq_one
theorem valuation_lt_one_iff (a : A) : a ∈ LocalRing.maximalIdeal A ↔ A.valuation a < 1 := by
rw [LocalRing.mem_maximalIdeal]
dsimp [nonunits]; rw [valuation_eq_one_iff]
exact (A.valuation_le_one a).lt_iff_ne.symm
#align valuation_subring.valuation_lt_one_iff ValuationSubring.valuation_lt_one_iff
/-- A subring `R` of `K` such that for all `x : K` either `x ∈ R` or `x⁻¹ ∈ R` is
a valuation subring of `K`. -/
def ofSubring (R : Subring K) (hR : ∀ x : K, x ∈ R ∨ x⁻¹ ∈ R) : ValuationSubring K :=
{ R with mem_or_inv_mem' := hR }
#align valuation_subring.of_subring ValuationSubring.ofSubring
@[simp]
theorem mem_ofSubring (R : Subring K) (hR : ∀ x : K, x ∈ R ∨ x⁻¹ ∈ R) (x : K) :
x ∈ ofSubring R hR ↔ x ∈ R :=
Iff.refl _
#align valuation_subring.mem_of_subring ValuationSubring.mem_ofSubring
/-- An overring of a valuation ring is a valuation ring. -/
def ofLE (R : ValuationSubring K) (S : Subring K) (h : R.toSubring ≤ S) : ValuationSubring K :=
{ S with mem_or_inv_mem' := fun x => (R.mem_or_inv_mem x).imp (@h x) (@h _) }
#align valuation_subring.of_le ValuationSubring.ofLE
section Order
instance : SemilatticeSup (ValuationSubring K) :=
{ (inferInstance : PartialOrder (ValuationSubring K)) with
sup := fun R S => ofLE R (R.toSubring ⊔ S.toSubring) <| le_sup_left
le_sup_left := fun R S _ hx => (le_sup_left : R.toSubring ≤ R.toSubring ⊔ S.toSubring) hx
le_sup_right := fun R S _ hx => (le_sup_right : S.toSubring ≤ R.toSubring ⊔ S.toSubring) hx
sup_le := fun R S T hR hT _ hx => (sup_le hR hT : R.toSubring ⊔ S.toSubring ≤ T.toSubring) hx }
/-- The ring homomorphism induced by the partial order. -/
def inclusion (R S : ValuationSubring K) (h : R ≤ S) : R →+* S :=
Subring.inclusion h
#align valuation_subring.inclusion ValuationSubring.inclusion
/-- The canonical ring homomorphism from a valuation ring to its field of fractions. -/
def subtype (R : ValuationSubring K) : R →+* K :=
Subring.subtype R.toSubring
#align valuation_subring.subtype ValuationSubring.subtype
/-- The canonical map on value groups induced by a coarsening of valuation rings. -/
def mapOfLE (R S : ValuationSubring K) (h : R ≤ S) : R.ValueGroup →*₀ S.ValueGroup where
toFun := Quotient.map' id fun x y ⟨u, hu⟩ => ⟨Units.map (R.inclusion S h).toMonoidHom u, hu⟩
map_zero' := rfl
map_one' := rfl
map_mul' := by rintro ⟨⟩ ⟨⟩; rfl
#align valuation_subring.map_of_le ValuationSubring.mapOfLE
@[mono]
theorem monotone_mapOfLE (R S : ValuationSubring K) (h : R ≤ S) : Monotone (R.mapOfLE S h) := by
rintro ⟨⟩ ⟨⟩ ⟨a, ha⟩; exact ⟨R.inclusion S h a, ha⟩
#align valuation_subring.monotone_map_of_le ValuationSubring.monotone_mapOfLE
@[simp]
theorem mapOfLE_comp_valuation (R S : ValuationSubring K) (h : R ≤ S) :
R.mapOfLE S h ∘ R.valuation = S.valuation := by ext; rfl
#align valuation_subring.map_of_le_comp_valuation ValuationSubring.mapOfLE_comp_valuation
@[simp]
theorem mapOfLE_valuation_apply (R S : ValuationSubring K) (h : R ≤ S) (x : K) :
R.mapOfLE S h (R.valuation x) = S.valuation x := rfl
#align valuation_subring.map_of_le_valuation_apply ValuationSubring.mapOfLE_valuation_apply
/-- The ideal corresponding to a coarsening of a valuation ring. -/
def idealOfLE (R S : ValuationSubring K) (h : R ≤ S) : Ideal R :=
(LocalRing.maximalIdeal S).comap (R.inclusion S h)
#align valuation_subring.ideal_of_le ValuationSubring.idealOfLE
instance prime_idealOfLE (R S : ValuationSubring K) (h : R ≤ S) : (idealOfLE R S h).IsPrime :=
(LocalRing.maximalIdeal S).comap_isPrime _
#align valuation_subring.prime_ideal_of_le ValuationSubring.prime_idealOfLE
/-- The coarsening of a valuation ring associated to a prime ideal. -/
def ofPrime (A : ValuationSubring K) (P : Ideal A) [P.IsPrime] : ValuationSubring K :=
ofLE A (Localization.subalgebra.ofField K _ P.primeCompl_le_nonZeroDivisors).toSubring
-- Porting note: added `Subalgebra.mem_toSubring.mpr`
fun a ha => Subalgebra.mem_toSubring.mpr <|
Subalgebra.algebraMap_mem
(Localization.subalgebra.ofField K _ P.primeCompl_le_nonZeroDivisors) (⟨a, ha⟩ : A)
#align valuation_subring.of_prime ValuationSubring.ofPrime
instance ofPrimeAlgebra (A : ValuationSubring K) (P : Ideal A) [P.IsPrime] :
Algebra A (A.ofPrime P) :=
-- Porting note: filled in the argument
Subalgebra.algebra (Localization.subalgebra.ofField K _ P.primeCompl_le_nonZeroDivisors)
#align valuation_subring.of_prime_algebra ValuationSubring.ofPrimeAlgebra
instance ofPrime_scalar_tower (A : ValuationSubring K) (P : Ideal A) [P.IsPrime] :
-- porting note (#10754): added instance
letI : SMul A (A.ofPrime P) := SMulZeroClass.toSMul
IsScalarTower A (A.ofPrime P) K :=
IsScalarTower.subalgebra' A K K
-- Porting note: filled in the argument
(Localization.subalgebra.ofField K _ P.primeCompl_le_nonZeroDivisors)
#align valuation_subring.of_prime_scalar_tower ValuationSubring.ofPrime_scalar_tower
instance ofPrime_localization (A : ValuationSubring K) (P : Ideal A) [P.IsPrime] :
IsLocalization.AtPrime (A.ofPrime P) P := by
apply
Localization.subalgebra.isLocalization_ofField K P.primeCompl
P.primeCompl_le_nonZeroDivisors
#align valuation_subring.of_prime_localization ValuationSubring.ofPrime_localization
theorem le_ofPrime (A : ValuationSubring K) (P : Ideal A) [P.IsPrime] : A ≤ ofPrime A P :=
-- Porting note: added `Subalgebra.mem_toSubring.mpr`
fun a ha => Subalgebra.mem_toSubring.mpr <| Subalgebra.algebraMap_mem _ (⟨a, ha⟩ : A)
#align valuation_subring.le_of_prime ValuationSubring.le_ofPrime
theorem ofPrime_valuation_eq_one_iff_mem_primeCompl (A : ValuationSubring K) (P : Ideal A)
[P.IsPrime] (x : A) : (ofPrime A P).valuation x = 1 ↔ x ∈ P.primeCompl := by
rw [← IsLocalization.AtPrime.isUnit_to_map_iff (A.ofPrime P) P x, valuation_eq_one_iff]; rfl
#align valuation_subring.of_prime_valuation_eq_one_iff_mem_prime_compl ValuationSubring.ofPrime_valuation_eq_one_iff_mem_primeCompl
@[simp]
theorem idealOfLE_ofPrime (A : ValuationSubring K) (P : Ideal A) [P.IsPrime] :
idealOfLE A (ofPrime A P) (le_ofPrime A P) = P := by
refine Ideal.ext (fun x => ?_)
apply IsLocalization.AtPrime.to_map_mem_maximal_iff
exact localRing (ofPrime A P)
#align valuation_subring.ideal_of_le_of_prime ValuationSubring.idealOfLE_ofPrime
@[simp]
theorem ofPrime_idealOfLE (R S : ValuationSubring K) (h : R ≤ S) :
ofPrime R (idealOfLE R S h) = S := by
ext x; constructor
· rintro ⟨a, r, hr, rfl⟩; apply mul_mem; · exact h a.2
· rw [← valuation_le_one_iff, map_inv₀, ← inv_one, inv_le_inv₀]
· exact not_lt.1 ((not_iff_not.2 <| valuation_lt_one_iff S _).1 hr)
· intro hh; erw [Valuation.zero_iff, Subring.coe_eq_zero_iff] at hh
apply hr; rw [hh]; apply Ideal.zero_mem (R.idealOfLE S h)
· exact one_ne_zero
· intro hx; by_cases hr : x ∈ R; · exact R.le_ofPrime _ hr
have : x ≠ 0 := fun h => hr (by rw [h]; exact R.zero_mem)
replace hr := (R.mem_or_inv_mem x).resolve_left hr
-- Porting note: added `⟨⟩` brackets and reordered goals
use 1, ⟨x⁻¹, hr⟩; constructor
· field_simp
· change (⟨x⁻¹, h hr⟩ : S) ∉ nonunits S
rw [mem_nonunits_iff, Classical.not_not]
apply isUnit_of_mul_eq_one _ (⟨x, hx⟩ : S)
ext; field_simp
#align valuation_subring.of_prime_ideal_of_le ValuationSubring.ofPrime_idealOfLE
theorem ofPrime_le_of_le (P Q : Ideal A) [P.IsPrime] [Q.IsPrime] (h : P ≤ Q) :
ofPrime A Q ≤ ofPrime A P := fun _x ⟨a, s, hs, he⟩ => ⟨a, s, fun c => hs (h c), he⟩
#align valuation_subring.of_prime_le_of_le ValuationSubring.ofPrime_le_of_le
theorem idealOfLE_le_of_le (R S : ValuationSubring K) (hR : A ≤ R) (hS : A ≤ S) (h : R ≤ S) :
idealOfLE A S hS ≤ idealOfLE A R hR := fun x hx =>
(valuation_lt_one_iff R _).2
(by
by_contra c; push_neg at c; replace c := monotone_mapOfLE R S h c
rw [(mapOfLE _ _ _).map_one, mapOfLE_valuation_apply] at c
apply not_le_of_lt ((valuation_lt_one_iff S _).1 hx) c)
#align valuation_subring.ideal_of_le_le_of_le ValuationSubring.idealOfLE_le_of_le
/-- The equivalence between coarsenings of a valuation ring and its prime ideals. -/
@[simps]
def primeSpectrumEquiv : PrimeSpectrum A ≃ {S // A ≤ S} where
toFun P := ⟨ofPrime A P.asIdeal, le_ofPrime _ _⟩
invFun S := ⟨idealOfLE _ S S.2, inferInstance⟩
left_inv P := by ext1; simp
right_inv S := by ext1; simp
#align valuation_subring.prime_spectrum_equiv ValuationSubring.primeSpectrumEquiv
/-- An ordered variant of `primeSpectrumEquiv`. -/
@[simps!]
def primeSpectrumOrderEquiv : (PrimeSpectrum A)ᵒᵈ ≃o {S // A ≤ S} :=
{ primeSpectrumEquiv A with
map_rel_iff' :=
⟨fun h => by
dsimp at h
have := idealOfLE_le_of_le A _ _ ?_ ?_ h
iterate 2 erw [idealOfLE_ofPrime] at this
· exact this
all_goals exact le_ofPrime A (PrimeSpectrum.asIdeal _),
fun h => by apply ofPrime_le_of_le; exact h⟩ }
#align valuation_subring.prime_spectrum_order_equiv ValuationSubring.primeSpectrumOrderEquiv
instance linearOrderOverring : LinearOrder {S // A ≤ S} :=
{ (inferInstance : PartialOrder _) with
le_total :=
let i : IsTotal (PrimeSpectrum A) (· ≤ ·) := ⟨fun ⟨x, _⟩ ⟨y, _⟩ => LE.isTotal.total x y⟩
(primeSpectrumOrderEquiv A).symm.toRelEmbedding.isTotal.total
decidableLE := inferInstance }
#align valuation_subring.linear_order_overring ValuationSubring.linearOrderOverring
end Order
end ValuationSubring
namespace Valuation
variable {K}
variable {Γ Γ₁ Γ₂ : Type*} [LinearOrderedCommGroupWithZero Γ]
[LinearOrderedCommGroupWithZero Γ₁] [LinearOrderedCommGroupWithZero Γ₂] (v : Valuation K Γ)
(v₁ : Valuation K Γ₁) (v₂ : Valuation K Γ₂)
/-- The valuation subring associated to a valuation. -/
def valuationSubring : ValuationSubring K :=
{ v.integer with
mem_or_inv_mem' := by
intro x
rcases le_or_lt (v x) 1 with h | h
· left; exact h
· right; change v x⁻¹ ≤ 1
rw [map_inv₀ v, ← inv_one, inv_le_inv₀]
· exact le_of_lt h
· intro c; simp [c] at h
· exact one_ne_zero }
#align valuation.valuation_subring Valuation.valuationSubring
@[simp]
theorem mem_valuationSubring_iff (x : K) : x ∈ v.valuationSubring ↔ v x ≤ 1 := Iff.refl _
#align valuation.mem_valuation_subring_iff Valuation.mem_valuationSubring_iff
| Mathlib/RingTheory/Valuation/ValuationSubring.lean | 436 | 443 | theorem isEquiv_iff_valuationSubring :
v₁.IsEquiv v₂ ↔ v₁.valuationSubring = v₂.valuationSubring := by |
constructor
· intro h; ext x; specialize h x 1; simpa using h
· intro h; apply isEquiv_of_val_le_one
intro x
have : x ∈ v₁.valuationSubring ↔ x ∈ v₂.valuationSubring := by rw [h]
simpa using this
|
/-
Copyright (c) 2021 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Joël Riou
-/
import Mathlib.Algebra.Homology.Homotopy
import Mathlib.Algebra.Homology.SingleHomology
import Mathlib.CategoryTheory.Abelian.Homology
#align_import algebra.homology.quasi_iso from "leanprover-community/mathlib"@"956af7c76589f444f2e1313911bad16366ea476d"
/-!
# Quasi-isomorphisms
A chain map is a quasi-isomorphism if it induces isomorphisms on homology.
## Future work
Define the derived category as the localization at quasi-isomorphisms? (TODO @joelriou)
-/
open CategoryTheory Limits
universe v u
variable {ι : Type*}
section
variable {V : Type u} [Category.{v} V] [HasZeroMorphisms V] [HasZeroObject V]
variable [HasEqualizers V] [HasImages V] [HasImageMaps V] [HasCokernels V]
variable {c : ComplexShape ι} {C D E : HomologicalComplex V c}
/-- A chain map is a quasi-isomorphism if it induces isomorphisms on homology.
-/
class QuasiIso' (f : C ⟶ D) : Prop where
isIso : ∀ i, IsIso ((homology'Functor V c i).map f)
#align quasi_iso QuasiIso'
attribute [instance] QuasiIso'.isIso
instance (priority := 100) quasiIso'_of_iso (f : C ⟶ D) [IsIso f] : QuasiIso' f where
isIso i := by
change IsIso ((homology'Functor V c i).mapIso (asIso f)).hom
infer_instance
#align quasi_iso_of_iso quasiIso'_of_iso
instance quasiIso'_comp (f : C ⟶ D) [QuasiIso' f] (g : D ⟶ E) [QuasiIso' g] :
QuasiIso' (f ≫ g) where
isIso i := by
rw [Functor.map_comp]
infer_instance
#align quasi_iso_comp quasiIso'_comp
theorem quasiIso'_of_comp_left (f : C ⟶ D) [QuasiIso' f] (g : D ⟶ E) [QuasiIso' (f ≫ g)] :
QuasiIso' g :=
{ isIso := fun i => IsIso.of_isIso_fac_left ((homology'Functor V c i).map_comp f g).symm }
#align quasi_iso_of_comp_left quasiIso'_of_comp_left
theorem quasiIso'_of_comp_right (f : C ⟶ D) (g : D ⟶ E) [QuasiIso' g] [QuasiIso' (f ≫ g)] :
QuasiIso' f :=
{ isIso := fun i => IsIso.of_isIso_fac_right ((homology'Functor V c i).map_comp f g).symm }
#align quasi_iso_of_comp_right quasiIso'_of_comp_right
namespace HomotopyEquiv
section
variable {W : Type*} [Category W] [Preadditive W] [HasCokernels W] [HasImages W] [HasEqualizers W]
[HasZeroObject W] [HasImageMaps W]
/-- A homotopy equivalence is a quasi-isomorphism. -/
theorem toQuasiIso' {C D : HomologicalComplex W c} (e : HomotopyEquiv C D) : QuasiIso' e.hom :=
⟨fun i => by
refine ⟨⟨(homology'Functor W c i).map e.inv, ?_⟩⟩
simp only [← Functor.map_comp, ← (homology'Functor W c i).map_id]
constructor <;> apply homology'_map_eq_of_homotopy
exacts [e.homotopyHomInvId, e.homotopyInvHomId]⟩
#align homotopy_equiv.to_quasi_iso HomotopyEquiv.toQuasiIso'
theorem toQuasiIso'_inv {C D : HomologicalComplex W c} (e : HomotopyEquiv C D) (i : ι) :
(@asIso _ _ _ _ _ (e.toQuasiIso'.1 i)).inv = (homology'Functor W c i).map e.inv := by
symm
haveI := e.toQuasiIso'.1 i -- Porting note: Added this to get `asIso_hom` to work.
simp only [← Iso.hom_comp_eq_id, asIso_hom, ← Functor.map_comp,
← (homology'Functor W c i).map_id, homology'_map_eq_of_homotopy e.homotopyHomInvId _]
#align homotopy_equiv.to_quasi_iso_inv HomotopyEquiv.toQuasiIso'_inv
end
end HomotopyEquiv
namespace HomologicalComplex.Hom
section ToSingle₀
variable {W : Type*} [Category W] [Abelian W]
section
variable {X : ChainComplex W ℕ} {Y : W} (f : X ⟶ (ChainComplex.single₀ _).obj Y) [hf : QuasiIso' f]
/-- If a chain map `f : X ⟶ Y[0]` is a quasi-isomorphism, then the cokernel of the differential
`d : X₁ → X₀` is isomorphic to `Y`. -/
noncomputable def toSingle₀CokernelAtZeroIso : cokernel (X.d 1 0) ≅ Y :=
X.homology'ZeroIso.symm.trans
((@asIso _ _ _ _ _ (hf.1 0)).trans ((ChainComplex.homology'Functor0Single₀ W).app Y))
#align homological_complex.hom.to_single₀_cokernel_at_zero_iso HomologicalComplex.Hom.toSingle₀CokernelAtZeroIso
theorem toSingle₀CokernelAtZeroIso_hom_eq [hf : QuasiIso' f] :
f.toSingle₀CokernelAtZeroIso.hom =
cokernel.desc (X.d 1 0) (f.f 0) (by rw [← f.2 1 0 rfl]; exact comp_zero) := by
ext
dsimp only [toSingle₀CokernelAtZeroIso, ChainComplex.homology'ZeroIso, homology'OfZeroRight,
homology'.mapIso, ChainComplex.homology'Functor0Single₀, cokernel.map]
dsimp [asIso]
simp only [cokernel.π_desc, Category.assoc, homology'.map_desc, cokernel.π_desc_assoc]
simp [homology'.desc, Iso.refl_inv (X.X 0)]
#align homological_complex.hom.to_single₀_cokernel_at_zero_iso_hom_eq HomologicalComplex.Hom.toSingle₀CokernelAtZeroIso_hom_eq
theorem to_single₀_epi_at_zero [hf : QuasiIso' f] : Epi (f.f 0) := by
constructor
intro Z g h Hgh
rw [← cokernel.π_desc (X.d 1 0) (f.f 0) (by rw [← f.2 1 0 rfl]; exact comp_zero),
← toSingle₀CokernelAtZeroIso_hom_eq] at Hgh
rw [(@cancel_epi _ _ _ _ _ _ (epi_comp _ _) _ _).1 Hgh]
#align homological_complex.hom.to_single₀_epi_at_zero HomologicalComplex.Hom.to_single₀_epi_at_zero
theorem to_single₀_exact_d_f_at_zero [hf : QuasiIso' f] : Exact (X.d 1 0) (f.f 0) := by
rw [Preadditive.exact_iff_homology'_zero]
have h : X.d 1 0 ≫ f.f 0 = 0 := by simp only [← f.comm 1 0, single_obj_d, comp_zero]
refine ⟨h, Nonempty.intro (homology'IsoKernelDesc _ _ _ ≪≫ ?_)⟩
suffices IsIso (cokernel.desc _ _ h) by apply kernel.ofMono
rw [← toSingle₀CokernelAtZeroIso_hom_eq]
infer_instance
#align homological_complex.hom.to_single₀_exact_d_f_at_zero HomologicalComplex.Hom.to_single₀_exact_d_f_at_zero
theorem to_single₀_exact_at_succ [hf : QuasiIso' f] (n : ℕ) :
Exact (X.d (n + 2) (n + 1)) (X.d (n + 1) n) :=
(Preadditive.exact_iff_homology'_zero _ _).2
⟨X.d_comp_d _ _ _,
⟨(ChainComplex.homology'SuccIso _ _).symm.trans
((@asIso _ _ _ _ _ (hf.1 (n + 1))).trans homology'ZeroZero)⟩⟩
#align homological_complex.hom.to_single₀_exact_at_succ HomologicalComplex.Hom.to_single₀_exact_at_succ
end
section
variable {X : CochainComplex W ℕ} {Y : W} (f : (CochainComplex.single₀ _).obj Y ⟶ X)
/-- If a cochain map `f : Y[0] ⟶ X` is a quasi-isomorphism, then the kernel of the differential
`d : X₀ → X₁` is isomorphic to `Y`. -/
noncomputable def fromSingle₀KernelAtZeroIso [hf : QuasiIso' f] : kernel (X.d 0 1) ≅ Y :=
X.homology'ZeroIso.symm.trans
((@asIso _ _ _ _ _ (hf.1 0)).symm.trans ((CochainComplex.homologyFunctor0Single₀ W).app Y))
#align homological_complex.hom.from_single₀_kernel_at_zero_iso HomologicalComplex.Hom.fromSingle₀KernelAtZeroIso
theorem fromSingle₀KernelAtZeroIso_inv_eq [hf : QuasiIso' f] :
f.fromSingle₀KernelAtZeroIso.inv =
kernel.lift (X.d 0 1) (f.f 0) (by rw [f.2 0 1 rfl]; exact zero_comp) := by
ext
dsimp only [fromSingle₀KernelAtZeroIso, CochainComplex.homology'ZeroIso, homology'OfZeroLeft,
homology'.mapIso, CochainComplex.homologyFunctor0Single₀, kernel.map]
simp only [Iso.trans_inv, Iso.app_inv, Iso.symm_inv, Category.assoc, equalizer_as_kernel,
kernel.lift_ι]
dsimp [asIso]
simp only [Category.assoc, homology'.π_map, cokernelZeroIsoTarget_hom,
cokernelIsoOfEq_hom_comp_desc, kernelSubobject_arrow, homology'.π_map_assoc, IsIso.inv_comp_eq]
simp [homology'.π, kernelSubobjectMap_comp, Iso.refl_hom (X.X 0), Category.comp_id]
#align homological_complex.hom.from_single₀_kernel_at_zero_iso_inv_eq HomologicalComplex.Hom.fromSingle₀KernelAtZeroIso_inv_eq
theorem from_single₀_mono_at_zero [hf : QuasiIso' f] : Mono (f.f 0) := by
constructor
intro Z g h Hgh
rw [← kernel.lift_ι (X.d 0 1) (f.f 0) (by rw [f.2 0 1 rfl]; exact zero_comp),
← fromSingle₀KernelAtZeroIso_inv_eq] at Hgh
rw [(@cancel_mono _ _ _ _ _ _ (mono_comp _ _) _ _).1 Hgh]
#align homological_complex.hom.from_single₀_mono_at_zero HomologicalComplex.Hom.from_single₀_mono_at_zero
| Mathlib/Algebra/Homology/QuasiIso.lean | 182 | 188 | theorem from_single₀_exact_f_d_at_zero [hf : QuasiIso' f] : Exact (f.f 0) (X.d 0 1) := by |
rw [Preadditive.exact_iff_homology'_zero]
have h : f.f 0 ≫ X.d 0 1 = 0 := by simp
refine ⟨h, Nonempty.intro (homology'IsoCokernelLift _ _ _ ≪≫ ?_)⟩
suffices IsIso (kernel.lift (X.d 0 1) (f.f 0) h) by apply cokernel.ofEpi
rw [← fromSingle₀KernelAtZeroIso_inv_eq f]
infer_instance
|
/-
Copyright (c) 2021 Bryan Gin-ge Chen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Adam Topaz, Bryan Gin-ge Chen, Yaël Dillies
-/
import Mathlib.Order.BooleanAlgebra
import Mathlib.Logic.Equiv.Basic
#align_import order.symm_diff from "leanprover-community/mathlib"@"6eb334bd8f3433d5b08ba156b8ec3e6af47e1904"
/-!
# Symmetric difference and bi-implication
This file defines the symmetric difference and bi-implication operators in (co-)Heyting algebras.
## Examples
Some examples are
* The symmetric difference of two sets is the set of elements that are in either but not both.
* The symmetric difference on propositions is `Xor'`.
* The symmetric difference on `Bool` is `Bool.xor`.
* The equivalence of propositions. Two propositions are equivalent if they imply each other.
* The symmetric difference translates to addition when considering a Boolean algebra as a Boolean
ring.
## Main declarations
* `symmDiff`: The symmetric difference operator, defined as `(a \ b) ⊔ (b \ a)`
* `bihimp`: The bi-implication operator, defined as `(b ⇨ a) ⊓ (a ⇨ b)`
In generalized Boolean algebras, the symmetric difference operator is:
* `symmDiff_comm`: commutative, and
* `symmDiff_assoc`: associative.
## Notations
* `a ∆ b`: `symmDiff a b`
* `a ⇔ b`: `bihimp a b`
## References
The proof of associativity follows the note "Associativity of the Symmetric Difference of Sets: A
Proof from the Book" by John McCuan:
* <https://people.math.gatech.edu/~mccuan/courses/4317/symmetricdifference.pdf>
## Tags
boolean ring, generalized boolean algebra, boolean algebra, symmetric difference, bi-implication,
Heyting
-/
open Function OrderDual
variable {ι α β : Type*} {π : ι → Type*}
/-- The symmetric difference operator on a type with `⊔` and `\` is `(A \ B) ⊔ (B \ A)`. -/
def symmDiff [Sup α] [SDiff α] (a b : α) : α :=
a \ b ⊔ b \ a
#align symm_diff symmDiff
/-- The Heyting bi-implication is `(b ⇨ a) ⊓ (a ⇨ b)`. This generalizes equivalence of
propositions. -/
def bihimp [Inf α] [HImp α] (a b : α) : α :=
(b ⇨ a) ⊓ (a ⇨ b)
#align bihimp bihimp
/-- Notation for symmDiff -/
scoped[symmDiff] infixl:100 " ∆ " => symmDiff
/-- Notation for bihimp -/
scoped[symmDiff] infixl:100 " ⇔ " => bihimp
open scoped symmDiff
theorem symmDiff_def [Sup α] [SDiff α] (a b : α) : a ∆ b = a \ b ⊔ b \ a :=
rfl
#align symm_diff_def symmDiff_def
theorem bihimp_def [Inf α] [HImp α] (a b : α) : a ⇔ b = (b ⇨ a) ⊓ (a ⇨ b) :=
rfl
#align bihimp_def bihimp_def
theorem symmDiff_eq_Xor' (p q : Prop) : p ∆ q = Xor' p q :=
rfl
#align symm_diff_eq_xor symmDiff_eq_Xor'
@[simp]
theorem bihimp_iff_iff {p q : Prop} : p ⇔ q ↔ (p ↔ q) :=
(iff_iff_implies_and_implies _ _).symm.trans Iff.comm
#align bihimp_iff_iff bihimp_iff_iff
@[simp]
theorem Bool.symmDiff_eq_xor : ∀ p q : Bool, p ∆ q = xor p q := by decide
#align bool.symm_diff_eq_bxor Bool.symmDiff_eq_xor
section GeneralizedCoheytingAlgebra
variable [GeneralizedCoheytingAlgebra α] (a b c d : α)
@[simp]
theorem toDual_symmDiff : toDual (a ∆ b) = toDual a ⇔ toDual b :=
rfl
#align to_dual_symm_diff toDual_symmDiff
@[simp]
theorem ofDual_bihimp (a b : αᵒᵈ) : ofDual (a ⇔ b) = ofDual a ∆ ofDual b :=
rfl
#align of_dual_bihimp ofDual_bihimp
theorem symmDiff_comm : a ∆ b = b ∆ a := by simp only [symmDiff, sup_comm]
#align symm_diff_comm symmDiff_comm
instance symmDiff_isCommutative : Std.Commutative (α := α) (· ∆ ·) :=
⟨symmDiff_comm⟩
#align symm_diff_is_comm symmDiff_isCommutative
@[simp]
theorem symmDiff_self : a ∆ a = ⊥ := by rw [symmDiff, sup_idem, sdiff_self]
#align symm_diff_self symmDiff_self
@[simp]
theorem symmDiff_bot : a ∆ ⊥ = a := by rw [symmDiff, sdiff_bot, bot_sdiff, sup_bot_eq]
#align symm_diff_bot symmDiff_bot
@[simp]
theorem bot_symmDiff : ⊥ ∆ a = a := by rw [symmDiff_comm, symmDiff_bot]
#align bot_symm_diff bot_symmDiff
@[simp]
theorem symmDiff_eq_bot {a b : α} : a ∆ b = ⊥ ↔ a = b := by
simp_rw [symmDiff, sup_eq_bot_iff, sdiff_eq_bot_iff, le_antisymm_iff]
#align symm_diff_eq_bot symmDiff_eq_bot
theorem symmDiff_of_le {a b : α} (h : a ≤ b) : a ∆ b = b \ a := by
rw [symmDiff, sdiff_eq_bot_iff.2 h, bot_sup_eq]
#align symm_diff_of_le symmDiff_of_le
theorem symmDiff_of_ge {a b : α} (h : b ≤ a) : a ∆ b = a \ b := by
rw [symmDiff, sdiff_eq_bot_iff.2 h, sup_bot_eq]
#align symm_diff_of_ge symmDiff_of_ge
theorem symmDiff_le {a b c : α} (ha : a ≤ b ⊔ c) (hb : b ≤ a ⊔ c) : a ∆ b ≤ c :=
sup_le (sdiff_le_iff.2 ha) <| sdiff_le_iff.2 hb
#align symm_diff_le symmDiff_le
theorem symmDiff_le_iff {a b c : α} : a ∆ b ≤ c ↔ a ≤ b ⊔ c ∧ b ≤ a ⊔ c := by
simp_rw [symmDiff, sup_le_iff, sdiff_le_iff]
#align symm_diff_le_iff symmDiff_le_iff
@[simp]
theorem symmDiff_le_sup {a b : α} : a ∆ b ≤ a ⊔ b :=
sup_le_sup sdiff_le sdiff_le
#align symm_diff_le_sup symmDiff_le_sup
theorem symmDiff_eq_sup_sdiff_inf : a ∆ b = (a ⊔ b) \ (a ⊓ b) := by simp [sup_sdiff, symmDiff]
#align symm_diff_eq_sup_sdiff_inf symmDiff_eq_sup_sdiff_inf
theorem Disjoint.symmDiff_eq_sup {a b : α} (h : Disjoint a b) : a ∆ b = a ⊔ b := by
rw [symmDiff, h.sdiff_eq_left, h.sdiff_eq_right]
#align disjoint.symm_diff_eq_sup Disjoint.symmDiff_eq_sup
theorem symmDiff_sdiff : a ∆ b \ c = a \ (b ⊔ c) ⊔ b \ (a ⊔ c) := by
rw [symmDiff, sup_sdiff_distrib, sdiff_sdiff_left, sdiff_sdiff_left]
#align symm_diff_sdiff symmDiff_sdiff
@[simp]
theorem symmDiff_sdiff_inf : a ∆ b \ (a ⊓ b) = a ∆ b := by
rw [symmDiff_sdiff]
simp [symmDiff]
#align symm_diff_sdiff_inf symmDiff_sdiff_inf
@[simp]
theorem symmDiff_sdiff_eq_sup : a ∆ (b \ a) = a ⊔ b := by
rw [symmDiff, sdiff_idem]
exact
le_antisymm (sup_le_sup sdiff_le sdiff_le)
(sup_le le_sdiff_sup <| le_sdiff_sup.trans <| sup_le le_sup_right le_sdiff_sup)
#align symm_diff_sdiff_eq_sup symmDiff_sdiff_eq_sup
@[simp]
theorem sdiff_symmDiff_eq_sup : (a \ b) ∆ b = a ⊔ b := by
rw [symmDiff_comm, symmDiff_sdiff_eq_sup, sup_comm]
#align sdiff_symm_diff_eq_sup sdiff_symmDiff_eq_sup
@[simp]
theorem symmDiff_sup_inf : a ∆ b ⊔ a ⊓ b = a ⊔ b := by
refine le_antisymm (sup_le symmDiff_le_sup inf_le_sup) ?_
rw [sup_inf_left, symmDiff]
refine sup_le (le_inf le_sup_right ?_) (le_inf ?_ le_sup_right)
· rw [sup_right_comm]
exact le_sup_of_le_left le_sdiff_sup
· rw [sup_assoc]
exact le_sup_of_le_right le_sdiff_sup
#align symm_diff_sup_inf symmDiff_sup_inf
@[simp]
theorem inf_sup_symmDiff : a ⊓ b ⊔ a ∆ b = a ⊔ b := by rw [sup_comm, symmDiff_sup_inf]
#align inf_sup_symm_diff inf_sup_symmDiff
@[simp]
theorem symmDiff_symmDiff_inf : a ∆ b ∆ (a ⊓ b) = a ⊔ b := by
rw [← symmDiff_sdiff_inf a, sdiff_symmDiff_eq_sup, symmDiff_sup_inf]
#align symm_diff_symm_diff_inf symmDiff_symmDiff_inf
@[simp]
theorem inf_symmDiff_symmDiff : (a ⊓ b) ∆ (a ∆ b) = a ⊔ b := by
rw [symmDiff_comm, symmDiff_symmDiff_inf]
#align inf_symm_diff_symm_diff inf_symmDiff_symmDiff
theorem symmDiff_triangle : a ∆ c ≤ a ∆ b ⊔ b ∆ c := by
refine (sup_le_sup (sdiff_triangle a b c) <| sdiff_triangle _ b _).trans_eq ?_
rw [sup_comm (c \ b), sup_sup_sup_comm, symmDiff, symmDiff]
#align symm_diff_triangle symmDiff_triangle
theorem le_symmDiff_sup_right (a b : α) : a ≤ (a ∆ b) ⊔ b := by
convert symmDiff_triangle a b ⊥ <;> rw [symmDiff_bot]
theorem le_symmDiff_sup_left (a b : α) : b ≤ (a ∆ b) ⊔ a :=
symmDiff_comm a b ▸ le_symmDiff_sup_right ..
end GeneralizedCoheytingAlgebra
section GeneralizedHeytingAlgebra
variable [GeneralizedHeytingAlgebra α] (a b c d : α)
@[simp]
theorem toDual_bihimp : toDual (a ⇔ b) = toDual a ∆ toDual b :=
rfl
#align to_dual_bihimp toDual_bihimp
@[simp]
theorem ofDual_symmDiff (a b : αᵒᵈ) : ofDual (a ∆ b) = ofDual a ⇔ ofDual b :=
rfl
#align of_dual_symm_diff ofDual_symmDiff
theorem bihimp_comm : a ⇔ b = b ⇔ a := by simp only [(· ⇔ ·), inf_comm]
#align bihimp_comm bihimp_comm
instance bihimp_isCommutative : Std.Commutative (α := α) (· ⇔ ·) :=
⟨bihimp_comm⟩
#align bihimp_is_comm bihimp_isCommutative
@[simp]
theorem bihimp_self : a ⇔ a = ⊤ := by rw [bihimp, inf_idem, himp_self]
#align bihimp_self bihimp_self
@[simp]
theorem bihimp_top : a ⇔ ⊤ = a := by rw [bihimp, himp_top, top_himp, inf_top_eq]
#align bihimp_top bihimp_top
@[simp]
theorem top_bihimp : ⊤ ⇔ a = a := by rw [bihimp_comm, bihimp_top]
#align top_bihimp top_bihimp
@[simp]
theorem bihimp_eq_top {a b : α} : a ⇔ b = ⊤ ↔ a = b :=
@symmDiff_eq_bot αᵒᵈ _ _ _
#align bihimp_eq_top bihimp_eq_top
theorem bihimp_of_le {a b : α} (h : a ≤ b) : a ⇔ b = b ⇨ a := by
rw [bihimp, himp_eq_top_iff.2 h, inf_top_eq]
#align bihimp_of_le bihimp_of_le
theorem bihimp_of_ge {a b : α} (h : b ≤ a) : a ⇔ b = a ⇨ b := by
rw [bihimp, himp_eq_top_iff.2 h, top_inf_eq]
#align bihimp_of_ge bihimp_of_ge
theorem le_bihimp {a b c : α} (hb : a ⊓ b ≤ c) (hc : a ⊓ c ≤ b) : a ≤ b ⇔ c :=
le_inf (le_himp_iff.2 hc) <| le_himp_iff.2 hb
#align le_bihimp le_bihimp
theorem le_bihimp_iff {a b c : α} : a ≤ b ⇔ c ↔ a ⊓ b ≤ c ∧ a ⊓ c ≤ b := by
simp_rw [bihimp, le_inf_iff, le_himp_iff, and_comm]
#align le_bihimp_iff le_bihimp_iff
@[simp]
theorem inf_le_bihimp {a b : α} : a ⊓ b ≤ a ⇔ b :=
inf_le_inf le_himp le_himp
#align inf_le_bihimp inf_le_bihimp
theorem bihimp_eq_inf_himp_inf : a ⇔ b = a ⊔ b ⇨ a ⊓ b := by simp [himp_inf_distrib, bihimp]
#align bihimp_eq_inf_himp_inf bihimp_eq_inf_himp_inf
theorem Codisjoint.bihimp_eq_inf {a b : α} (h : Codisjoint a b) : a ⇔ b = a ⊓ b := by
rw [bihimp, h.himp_eq_left, h.himp_eq_right]
#align codisjoint.bihimp_eq_inf Codisjoint.bihimp_eq_inf
theorem himp_bihimp : a ⇨ b ⇔ c = (a ⊓ c ⇨ b) ⊓ (a ⊓ b ⇨ c) := by
rw [bihimp, himp_inf_distrib, himp_himp, himp_himp]
#align himp_bihimp himp_bihimp
@[simp]
theorem sup_himp_bihimp : a ⊔ b ⇨ a ⇔ b = a ⇔ b := by
rw [himp_bihimp]
simp [bihimp]
#align sup_himp_bihimp sup_himp_bihimp
@[simp]
theorem bihimp_himp_eq_inf : a ⇔ (a ⇨ b) = a ⊓ b :=
@symmDiff_sdiff_eq_sup αᵒᵈ _ _ _
#align bihimp_himp_eq_inf bihimp_himp_eq_inf
@[simp]
theorem himp_bihimp_eq_inf : (b ⇨ a) ⇔ b = a ⊓ b :=
@sdiff_symmDiff_eq_sup αᵒᵈ _ _ _
#align himp_bihimp_eq_inf himp_bihimp_eq_inf
@[simp]
theorem bihimp_inf_sup : a ⇔ b ⊓ (a ⊔ b) = a ⊓ b :=
@symmDiff_sup_inf αᵒᵈ _ _ _
#align bihimp_inf_sup bihimp_inf_sup
@[simp]
theorem sup_inf_bihimp : (a ⊔ b) ⊓ a ⇔ b = a ⊓ b :=
@inf_sup_symmDiff αᵒᵈ _ _ _
#align sup_inf_bihimp sup_inf_bihimp
@[simp]
theorem bihimp_bihimp_sup : a ⇔ b ⇔ (a ⊔ b) = a ⊓ b :=
@symmDiff_symmDiff_inf αᵒᵈ _ _ _
#align bihimp_bihimp_sup bihimp_bihimp_sup
@[simp]
theorem sup_bihimp_bihimp : (a ⊔ b) ⇔ (a ⇔ b) = a ⊓ b :=
@inf_symmDiff_symmDiff αᵒᵈ _ _ _
#align sup_bihimp_bihimp sup_bihimp_bihimp
theorem bihimp_triangle : a ⇔ b ⊓ b ⇔ c ≤ a ⇔ c :=
@symmDiff_triangle αᵒᵈ _ _ _ _
#align bihimp_triangle bihimp_triangle
end GeneralizedHeytingAlgebra
section CoheytingAlgebra
variable [CoheytingAlgebra α] (a : α)
@[simp]
theorem symmDiff_top' : a ∆ ⊤ = ￢a := by simp [symmDiff]
#align symm_diff_top' symmDiff_top'
@[simp]
theorem top_symmDiff' : ⊤ ∆ a = ￢a := by simp [symmDiff]
#align top_symm_diff' top_symmDiff'
@[simp]
theorem hnot_symmDiff_self : (￢a) ∆ a = ⊤ := by
rw [eq_top_iff, symmDiff, hnot_sdiff, sup_sdiff_self]
exact Codisjoint.top_le codisjoint_hnot_left
#align hnot_symm_diff_self hnot_symmDiff_self
@[simp]
theorem symmDiff_hnot_self : a ∆ (￢a) = ⊤ := by rw [symmDiff_comm, hnot_symmDiff_self]
#align symm_diff_hnot_self symmDiff_hnot_self
theorem IsCompl.symmDiff_eq_top {a b : α} (h : IsCompl a b) : a ∆ b = ⊤ := by
rw [h.eq_hnot, hnot_symmDiff_self]
#align is_compl.symm_diff_eq_top IsCompl.symmDiff_eq_top
end CoheytingAlgebra
section HeytingAlgebra
variable [HeytingAlgebra α] (a : α)
@[simp]
theorem bihimp_bot : a ⇔ ⊥ = aᶜ := by simp [bihimp]
#align bihimp_bot bihimp_bot
@[simp]
theorem bot_bihimp : ⊥ ⇔ a = aᶜ := by simp [bihimp]
#align bot_bihimp bot_bihimp
@[simp]
theorem compl_bihimp_self : aᶜ ⇔ a = ⊥ :=
@hnot_symmDiff_self αᵒᵈ _ _
#align compl_bihimp_self compl_bihimp_self
@[simp]
theorem bihimp_hnot_self : a ⇔ aᶜ = ⊥ :=
@symmDiff_hnot_self αᵒᵈ _ _
#align bihimp_hnot_self bihimp_hnot_self
theorem IsCompl.bihimp_eq_bot {a b : α} (h : IsCompl a b) : a ⇔ b = ⊥ := by
rw [h.eq_compl, compl_bihimp_self]
#align is_compl.bihimp_eq_bot IsCompl.bihimp_eq_bot
end HeytingAlgebra
section GeneralizedBooleanAlgebra
variable [GeneralizedBooleanAlgebra α] (a b c d : α)
@[simp]
theorem sup_sdiff_symmDiff : (a ⊔ b) \ a ∆ b = a ⊓ b :=
sdiff_eq_symm inf_le_sup (by rw [symmDiff_eq_sup_sdiff_inf])
#align sup_sdiff_symm_diff sup_sdiff_symmDiff
theorem disjoint_symmDiff_inf : Disjoint (a ∆ b) (a ⊓ b) := by
rw [symmDiff_eq_sup_sdiff_inf]
exact disjoint_sdiff_self_left
#align disjoint_symm_diff_inf disjoint_symmDiff_inf
theorem inf_symmDiff_distrib_left : a ⊓ b ∆ c = (a ⊓ b) ∆ (a ⊓ c) := by
rw [symmDiff_eq_sup_sdiff_inf, inf_sdiff_distrib_left, inf_sup_left, inf_inf_distrib_left,
symmDiff_eq_sup_sdiff_inf]
#align inf_symm_diff_distrib_left inf_symmDiff_distrib_left
theorem inf_symmDiff_distrib_right : a ∆ b ⊓ c = (a ⊓ c) ∆ (b ⊓ c) := by
simp_rw [inf_comm _ c, inf_symmDiff_distrib_left]
#align inf_symm_diff_distrib_right inf_symmDiff_distrib_right
theorem sdiff_symmDiff : c \ a ∆ b = c ⊓ a ⊓ b ⊔ c \ a ⊓ c \ b := by
simp only [(· ∆ ·), sdiff_sdiff_sup_sdiff']
#align sdiff_symm_diff sdiff_symmDiff
theorem sdiff_symmDiff' : c \ a ∆ b = c ⊓ a ⊓ b ⊔ c \ (a ⊔ b) := by
rw [sdiff_symmDiff, sdiff_sup]
#align sdiff_symm_diff' sdiff_symmDiff'
@[simp]
theorem symmDiff_sdiff_left : a ∆ b \ a = b \ a := by
rw [symmDiff_def, sup_sdiff, sdiff_idem, sdiff_sdiff_self, bot_sup_eq]
#align symm_diff_sdiff_left symmDiff_sdiff_left
@[simp]
theorem symmDiff_sdiff_right : a ∆ b \ b = a \ b := by rw [symmDiff_comm, symmDiff_sdiff_left]
#align symm_diff_sdiff_right symmDiff_sdiff_right
@[simp]
theorem sdiff_symmDiff_left : a \ a ∆ b = a ⊓ b := by simp [sdiff_symmDiff]
#align sdiff_symm_diff_left sdiff_symmDiff_left
@[simp]
| Mathlib/Order/SymmDiff.lean | 439 | 440 | theorem sdiff_symmDiff_right : b \ a ∆ b = a ⊓ b := by |
rw [symmDiff_comm, inf_comm, sdiff_symmDiff_left]
|
/-
Copyright (c) 2020 Yury G. Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury G. Kudryashov, Patrick Massot, Sébastien Gouëzel
-/
import Mathlib.Analysis.Calculus.FDeriv.Measurable
import Mathlib.Analysis.Calculus.Deriv.Comp
import Mathlib.Analysis.Calculus.Deriv.Add
import Mathlib.Analysis.Calculus.Deriv.Slope
import Mathlib.Analysis.Calculus.Deriv.Mul
import Mathlib.Analysis.NormedSpace.Dual
import Mathlib.MeasureTheory.Integral.DominatedConvergence
import Mathlib.MeasureTheory.Integral.VitaliCaratheodory
#align_import measure_theory.integral.fund_thm_calculus from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# Fundamental Theorem of Calculus
We prove various versions of the
[fundamental theorem of calculus](https://en.wikipedia.org/wiki/Fundamental_theorem_of_calculus)
for interval integrals in `ℝ`.
Recall that its first version states that the function `(u, v) ↦ ∫ x in u..v, f x` has derivative
`(δu, δv) ↦ δv • f b - δu • f a` at `(a, b)` provided that `f` is continuous at `a` and `b`,
and its second version states that, if `f` has an integrable derivative on `[a, b]`, then
`∫ x in a..b, f' x = f b - f a`.
## Main statements
### FTC-1 for Lebesgue measure
We prove several versions of FTC-1, all in the `intervalIntegral` namespace. Many of them follow
the naming scheme `integral_has(Strict?)(F?)Deriv(Within?)At(_of_tendsto_ae?)(_right|_left?)`.
They formulate FTC in terms of `Has(Strict?)(F?)Deriv(Within?)At`.
Let us explain the meaning of each part of the name:
* `Strict` means that the theorem is about strict differentiability, see `HasStrictDerivAt` and
`HasStrictFDerivAt`;
* `F` means that the theorem is about differentiability in both endpoints; incompatible with
`_right|_left`;
* `Within` means that the theorem is about one-sided derivatives, see below for details;
* `_of_tendsto_ae` means that instead of continuity the theorem assumes that `f` has a finite limit
almost surely as `x` tends to `a` and/or `b`;
* `_right` or `_left` mean that the theorem is about differentiability in the right (resp., left)
endpoint.
We also reformulate these theorems in terms of `(f?)deriv(Within?)`. These theorems are named
`(f?)deriv(Within?)_integral(_of_tendsto_ae?)(_right|_left?)` with the same meaning of parts of the
name.
### One-sided derivatives
Theorem `intervalIntegral.integral_hasFDerivWithinAt_of_tendsto_ae` states that
`(u, v) ↦ ∫ x in u..v, f x` has a derivative `(δu, δv) ↦ δv • cb - δu • ca` within the set `s × t`
at `(a, b)` provided that `f` tends to `ca` (resp., `cb`) almost surely at `la` (resp., `lb`), where
possible values of `s`, `t`, and corresponding filters `la`, `lb` are given in the following table.
| `s` | `la` | `t` | `lb` |
| ------- | ---- | --- | ---- |
| `Iic a` | `𝓝[≤] a` | `Iic b` | `𝓝[≤] b` |
| `Ici a` | `𝓝[>] a` | `Ici b` | `𝓝[>] b` |
| `{a}` | `⊥` | `{b}` | `⊥` |
| `univ` | `𝓝 a` | `univ` | `𝓝 b` |
We use a typeclass `intervalIntegral.FTCFilter` to make Lean automatically find `la`/`lb` based on
`s`/`t`. This way we can formulate one theorem instead of `16` (or `8` if we leave only non-trivial
ones not covered by `integral_hasDerivWithinAt_of_tendsto_ae_(left|right)` and
`integral_hasFDerivAt_of_tendsto_ae`). Similarly, `integral_hasDerivWithinAt_of_tendsto_ae_right`
works for both one-sided derivatives using the same typeclass to find an appropriate filter.
### FTC for a locally finite measure
Before proving FTC for the Lebesgue measure, we prove a few statements that can be seen as FTC for
any measure. The most general of them,
`measure_integral_sub_integral_sub_linear_isLittleO_of_tendsto_ae`, states the following.
Let `(la, la')` be an `intervalIntegral.FTCFilter` pair of filters around `a` (i.e.,
`intervalIntegral.FTCFilter a la la'`) and let `(lb, lb')` be an `intervalIntegral.FTCFilter` pair
of filters around `b`. If `f` has finite limits `ca` and `cb` almost surely at `la'` and `lb'`,
respectively, then
$$
\int_{va}^{vb} f ∂μ - \int_{ua}^{ub} f ∂μ =
\int_{ub}^{vb} cb ∂μ - \int_{ua}^{va} ca ∂μ + o(‖∫_{ua}^{va} 1 ∂μ‖ + ‖∫_{ub}^{vb} (1:ℝ) ∂μ‖)
$$
as `ua` and `va` tend to `la` while `ub` and `vb` tend to `lb`.
### FTC-2 and corollaries
We use FTC-1 to prove several versions of FTC-2 for the Lebesgue measure, using a similar naming
scheme as for the versions of FTC-1. They include:
* `intervalIntegral.integral_eq_sub_of_hasDeriv_right_of_le` - most general version, for functions
with a right derivative
* `intervalIntegral.integral_eq_sub_of_hasDerivAt` - version for functions with a derivative on
an open set
* `intervalIntegral.integral_deriv_eq_sub'` - version that is easiest to use when computing the
integral of a specific function
We then derive additional integration techniques from FTC-2:
* `intervalIntegral.integral_mul_deriv_eq_deriv_mul` - integration by parts
* `intervalIntegral.integral_comp_mul_deriv''` - integration by substitution
Many applications of these theorems can be found in the file
`Mathlib/Analysis/SpecialFunctions/Integrals.lean`.
Note that the assumptions of FTC-2 are formulated in the form that `f'` is integrable. To use it in
a context with the stronger assumption that `f'` is continuous, one can use
`ContinuousOn.intervalIntegrable` or `ContinuousOn.integrableOn_Icc` or
`ContinuousOn.integrableOn_uIcc`.
### `intervalIntegral.FTCFilter` class
As explained above, many theorems in this file rely on the typeclass
`intervalIntegral.FTCFilter (a : ℝ) (l l' : Filter ℝ)` to avoid code duplication. This typeclass
combines four assumptions:
- `pure a ≤ l`;
- `l' ≤ 𝓝 a`;
- `l'` has a basis of measurable sets;
- if `u n` and `v n` tend to `l`, then for any `s ∈ l'`, `Ioc (u n) (v n)` is eventually included
in `s`.
This typeclass has the following “real” instances: `(a, pure a, ⊥)`, `(a, 𝓝[≥] a, 𝓝[>] a)`,
`(a, 𝓝[≤] a, 𝓝[≤] a)`, `(a, 𝓝 a, 𝓝 a)`.
Furthermore, we have the following instances that are equal to the previously mentioned instances:
`(a, 𝓝[{a}] a, ⊥)` and `(a, 𝓝[univ] a, 𝓝[univ] a)`.
While the difference between `Ici a` and `Ioi a` doesn't matter for theorems about Lebesgue measure,
it becomes important in the versions of FTC about any locally finite measure if this measure has an
atom at one of the endpoints.
### Combining one-sided and two-sided derivatives
There are some `intervalIntegral.FTCFilter` instances where the fact that it is one-sided or
two-sided depends on the point, namely `(x, 𝓝[Set.Icc a b] x, 𝓝[Set.Icc a b] x)` (resp.
`(x, 𝓝[Set.uIcc a b] x, 𝓝[Set.uIcc a b] x)`, with `x ∈ Icc a b` (resp. `x ∈ uIcc a b`). This results
in a two-sided derivatives for `x ∈ Set.Ioo a b` and one-sided derivatives for `x ∈ {a, b}`. Other
instances could be added when needed (in that case, one also needs to add instances for
`Filter.IsMeasurablyGenerated` and `Filter.TendstoIxxClass`).
## Tags
integral, fundamental theorem of calculus, FTC-1, FTC-2, change of variables in integrals
-/
set_option autoImplicit true
noncomputable section
open scoped Classical
open MeasureTheory Set Filter Function
open scoped Classical Topology Filter ENNReal Interval NNReal
variable {ι 𝕜 E F A : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
namespace intervalIntegral
section FTC1
/-!
### Fundamental theorem of calculus, part 1, for any measure
In this section we prove a few lemmas that can be seen as versions of FTC-1 for interval integrals
w.r.t. any measure. Many theorems are formulated for one or two pairs of filters related by
`intervalIntegral.FTCFilter a l l'`. This typeclass has exactly four “real” instances:
`(a, pure a, ⊥)`, `(a, 𝓝[≥] a, 𝓝[>] a)`, `(a, 𝓝[≤] a, 𝓝[≤] a)`, `(a, 𝓝 a, 𝓝 a)`, and two instances
that are equal to the first and last “real” instances: `(a, 𝓝[{a}] a, ⊥)` and
`(a, 𝓝[univ] a, 𝓝[univ] a)`. We use this approach to avoid repeating arguments in many very similar
cases. Lean can automatically find both `a` and `l'` based on `l`.
The most general theorem `measure_integral_sub_integral_sub_linear_isLittleO_of_tendsto_ae` can be
seen as a generalization of lemma `integral_hasStrictFDerivAt` below which states strict
differentiability of `∫ x in u..v, f x` in `(u, v)` at `(a, b)` for a measurable function `f` that
is integrable on `a..b` and is continuous at `a` and `b`. The lemma is generalized in three
directions: first, `measure_integral_sub_integral_sub_linear_isLittleO_of_tendsto_ae` deals with any
locally finite measure `μ`; second, it works for one-sided limits/derivatives; third, it assumes
only that `f` has finite limits almost surely at `a` and `b`.
Namely, let `f` be a measurable function integrable on `a..b`. Let `(la, la')` be a pair of
`intervalIntegral.FTCFilter`s around `a`; let `(lb, lb')` be a pair of `intervalIntegral.FTCFilter`s
around `b`. Suppose that `f` has finite limits `ca` and `cb` at `la' ⊓ ae μ` and `lb' ⊓ ae μ`,
respectively. Then
`∫ x in va..vb, f x ∂μ - ∫ x in ua..ub, f x ∂μ = ∫ x in ub..vb, cb ∂μ - ∫ x in ua..va, ca ∂μ +
o(‖∫ x in ua..va, (1:ℝ) ∂μ‖ + ‖∫ x in ub..vb, (1:ℝ) ∂μ‖)`
as `ua` and `va` tend to `la` while `ub` and `vb` tend to `lb`.
This theorem is formulated with integral of constants instead of measures in the right hand sides
for two reasons: first, this way we avoid `min`/`max` in the statements; second, often it is
possible to write better `simp` lemmas for these integrals, see `integral_const` and
`integral_const_of_cdf`.
In the next subsection we apply this theorem to prove various theorems about differentiability
of the integral w.r.t. Lebesgue measure. -/
/-- An auxiliary typeclass for the Fundamental theorem of calculus, part 1. It is used to formulate
theorems that work simultaneously for left and right one-sided derivatives of `∫ x in u..v, f x`. -/
class FTCFilter (a : outParam ℝ) (outer : Filter ℝ) (inner : outParam <| Filter ℝ) extends
TendstoIxxClass Ioc outer inner : Prop where
pure_le : pure a ≤ outer
le_nhds : inner ≤ 𝓝 a
[meas_gen : IsMeasurablyGenerated inner]
set_option linter.uppercaseLean3 false in
#align interval_integral.FTC_filter intervalIntegral.FTCFilter
namespace FTCFilter
set_option linter.uppercaseLean3 false -- `FTC` in every name
instance pure (a : ℝ) : FTCFilter a (pure a) ⊥ where
pure_le := le_rfl
le_nhds := bot_le
#align interval_integral.FTC_filter.pure intervalIntegral.FTCFilter.pure
instance nhdsWithinSingleton (a : ℝ) : FTCFilter a (𝓝[{a}] a) ⊥ := by
rw [nhdsWithin, principal_singleton, inf_eq_right.2 (pure_le_nhds a)]; infer_instance
#align interval_integral.FTC_filter.nhds_within_singleton intervalIntegral.FTCFilter.nhdsWithinSingleton
theorem finiteAt_inner {a : ℝ} (l : Filter ℝ) {l'} [h : FTCFilter a l l'] {μ : Measure ℝ}
[IsLocallyFiniteMeasure μ] : μ.FiniteAtFilter l' :=
(μ.finiteAt_nhds a).filter_mono h.le_nhds
#align interval_integral.FTC_filter.finite_at_inner intervalIntegral.FTCFilter.finiteAt_inner
instance nhds (a : ℝ) : FTCFilter a (𝓝 a) (𝓝 a) where
pure_le := pure_le_nhds a
le_nhds := le_rfl
#align interval_integral.FTC_filter.nhds intervalIntegral.FTCFilter.nhds
instance nhdsUniv (a : ℝ) : FTCFilter a (𝓝[univ] a) (𝓝 a) := by rw [nhdsWithin_univ]; infer_instance
#align interval_integral.FTC_filter.nhds_univ intervalIntegral.FTCFilter.nhdsUniv
instance nhdsLeft (a : ℝ) : FTCFilter a (𝓝[≤] a) (𝓝[≤] a) where
pure_le := pure_le_nhdsWithin right_mem_Iic
le_nhds := inf_le_left
#align interval_integral.FTC_filter.nhds_left intervalIntegral.FTCFilter.nhdsLeft
instance nhdsRight (a : ℝ) : FTCFilter a (𝓝[≥] a) (𝓝[>] a) where
pure_le := pure_le_nhdsWithin left_mem_Ici
le_nhds := inf_le_left
#align interval_integral.FTC_filter.nhds_right intervalIntegral.FTCFilter.nhdsRight
instance nhdsIcc {x a b : ℝ} [h : Fact (x ∈ Icc a b)] :
FTCFilter x (𝓝[Icc a b] x) (𝓝[Icc a b] x) where
pure_le := pure_le_nhdsWithin h.out
le_nhds := inf_le_left
#align interval_integral.FTC_filter.nhds_Icc intervalIntegral.FTCFilter.nhdsIcc
instance nhdsUIcc {x a b : ℝ} [h : Fact (x ∈ [[a, b]])] :
FTCFilter x (𝓝[[[a, b]]] x) (𝓝[[[a, b]]] x) :=
.nhdsIcc (h := h)
#align interval_integral.FTC_filter.nhds_uIcc intervalIntegral.FTCFilter.nhdsUIcc
end FTCFilter
open Asymptotics
section
variable {f : ℝ → E} {a b : ℝ} {c ca cb : E} {l l' la la' lb lb' : Filter ℝ} {lt : Filter ι}
{μ : Measure ℝ} {u v ua va ub vb : ι → ℝ}
/-- **Fundamental theorem of calculus-1**, local version for any measure.
Let filters `l` and `l'` be related by `TendstoIxxClass Ioc`.
If `f` has a finite limit `c` at `l' ⊓ ae μ`, where `μ` is a measure
finite at `l'`, then `∫ x in u..v, f x ∂μ = ∫ x in u..v, c ∂μ + o(∫ x in u..v, 1 ∂μ)` as both
`u` and `v` tend to `l`.
See also `measure_integral_sub_linear_isLittleO_of_tendsto_ae` for a version assuming
`[intervalIntegral.FTCFilter a l l']` and `[MeasureTheory.IsLocallyFiniteMeasure μ]`. If `l` is one
of `𝓝[≥] a`, `𝓝[≤] a`, `𝓝 a`, then it's easier to apply the non-primed version. The primed version
also works, e.g., for `l = l' = atTop`.
We use integrals of constants instead of measures because this way it is easier to formulate
a statement that works in both cases `u ≤ v` and `v ≤ u`. -/
theorem measure_integral_sub_linear_isLittleO_of_tendsto_ae' [IsMeasurablyGenerated l']
[TendstoIxxClass Ioc l l'] (hfm : StronglyMeasurableAtFilter f l' μ)
(hf : Tendsto f (l' ⊓ ae μ) (𝓝 c)) (hl : μ.FiniteAtFilter l') (hu : Tendsto u lt l)
(hv : Tendsto v lt l) :
(fun t => (∫ x in u t..v t, f x ∂μ) - ∫ _ in u t..v t, c ∂μ) =o[lt] fun t =>
∫ _ in u t..v t, (1 : ℝ) ∂μ := by
by_cases hE : CompleteSpace E; swap
· simp [intervalIntegral, integral, hE]
have A := hf.integral_sub_linear_isLittleO_ae hfm hl (hu.Ioc hv)
have B := hf.integral_sub_linear_isLittleO_ae hfm hl (hv.Ioc hu)
simp_rw [integral_const', sub_smul]
refine ((A.trans_le fun t ↦ ?_).sub (B.trans_le fun t ↦ ?_)).congr_left fun t ↦ ?_
· cases le_total (u t) (v t) <;> simp [*]
· cases le_total (u t) (v t) <;> simp [*]
· simp_rw [intervalIntegral]
abel
#align interval_integral.measure_integral_sub_linear_is_o_of_tendsto_ae' intervalIntegral.measure_integral_sub_linear_isLittleO_of_tendsto_ae'
variable [CompleteSpace E]
/-- **Fundamental theorem of calculus-1**, local version for any measure.
Let filters `l` and `l'` be related by `TendstoIxxClass Ioc`.
If `f` has a finite limit `c` at `l ⊓ ae μ`, where `μ` is a measure
finite at `l`, then `∫ x in u..v, f x ∂μ = μ (Ioc u v) • c + o(μ(Ioc u v))` as both
`u` and `v` tend to `l` so that `u ≤ v`.
See also `measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_le` for a version assuming
`[intervalIntegral.FTCFilter a l l']` and `[MeasureTheory.IsLocallyFiniteMeasure μ]`. If `l` is one
of `𝓝[≥] a`, `𝓝[≤] a`, `𝓝 a`, then it's easier to apply the non-primed version. The primed version
also works, e.g., for `l = l' = Filter.atTop`. -/
theorem measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_le' [IsMeasurablyGenerated l']
[TendstoIxxClass Ioc l l'] (hfm : StronglyMeasurableAtFilter f l' μ)
(hf : Tendsto f (l' ⊓ ae μ) (𝓝 c)) (hl : μ.FiniteAtFilter l') (hu : Tendsto u lt l)
(hv : Tendsto v lt l) (huv : u ≤ᶠ[lt] v) :
(fun t => (∫ x in u t..v t, f x ∂μ) - (μ (Ioc (u t) (v t))).toReal • c) =o[lt] fun t =>
(μ <| Ioc (u t) (v t)).toReal :=
(measure_integral_sub_linear_isLittleO_of_tendsto_ae' hfm hf hl hu hv).congr'
(huv.mono fun x hx => by simp [integral_const', hx])
(huv.mono fun x hx => by simp [integral_const', hx])
#align interval_integral.measure_integral_sub_linear_is_o_of_tendsto_ae_of_le' intervalIntegral.measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_le'
/-- **Fundamental theorem of calculus-1**, local version for any measure.
Let filters `l` and `l'` be related by `TendstoIxxClass Ioc`.
If `f` has a finite limit `c` at `l ⊓ ae μ`, where `μ` is a measure
finite at `l`, then `∫ x in u..v, f x ∂μ = -μ (Ioc v u) • c + o(μ(Ioc v u))` as both
`u` and `v` tend to `l` so that `v ≤ u`.
See also `measure_integral_sub_linear_is_o_of_tendsto_ae_of_ge` for a version assuming
`[intervalIntegral.FTCFilter a l l']` and `[MeasureTheory.IsLocallyFiniteMeasure μ]`. If `l` is one
of `𝓝[≥] a`, `𝓝[≤] a`, `𝓝 a`, then it's easier to apply the non-primed version. The primed version
also works, e.g., for `l = l' = Filter.atTop`. -/
theorem measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_ge' [IsMeasurablyGenerated l']
[TendstoIxxClass Ioc l l'] (hfm : StronglyMeasurableAtFilter f l' μ)
(hf : Tendsto f (l' ⊓ ae μ) (𝓝 c)) (hl : μ.FiniteAtFilter l') (hu : Tendsto u lt l)
(hv : Tendsto v lt l) (huv : v ≤ᶠ[lt] u) :
(fun t => (∫ x in u t..v t, f x ∂μ) + (μ (Ioc (v t) (u t))).toReal • c) =o[lt] fun t =>
(μ <| Ioc (v t) (u t)).toReal :=
(measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_le' hfm hf hl hv hu
huv).neg_left.congr_left
fun t => by simp [integral_symm (u t), add_comm]
#align interval_integral.measure_integral_sub_linear_is_o_of_tendsto_ae_of_ge' intervalIntegral.measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_ge'
section
variable [IsLocallyFiniteMeasure μ] [FTCFilter a l l']
/-- **Fundamental theorem of calculus-1**, local version for any measure.
Let filters `l` and `l'` be related by `[intervalIntegral.FTCFilter a l l']`; let `μ` be a locally
finite measure. If `f` has a finite limit `c` at `l' ⊓ ae μ`, then
`∫ x in u..v, f x ∂μ = ∫ x in u..v, c ∂μ + o(∫ x in u..v, 1 ∂μ)` as both `u` and `v` tend to `l`.
See also `measure_integral_sub_linear_isLittleO_of_tendsto_ae'` for a version that also works, e.g.,
for `l = l' = Filter.atTop`.
We use integrals of constants instead of measures because this way it is easier to formulate
a statement that works in both cases `u ≤ v` and `v ≤ u`. -/
theorem measure_integral_sub_linear_isLittleO_of_tendsto_ae
(hfm : StronglyMeasurableAtFilter f l' μ) (hf : Tendsto f (l' ⊓ ae μ) (𝓝 c))
(hu : Tendsto u lt l) (hv : Tendsto v lt l) :
(fun t => (∫ x in u t..v t, f x ∂μ) - ∫ _ in u t..v t, c ∂μ) =o[lt] fun t =>
∫ _ in u t..v t, (1 : ℝ) ∂μ :=
haveI := FTCFilter.meas_gen l
measure_integral_sub_linear_isLittleO_of_tendsto_ae' hfm hf (FTCFilter.finiteAt_inner l) hu hv
#align interval_integral.measure_integral_sub_linear_is_o_of_tendsto_ae intervalIntegral.measure_integral_sub_linear_isLittleO_of_tendsto_ae
/-- **Fundamental theorem of calculus-1**, local version for any measure.
Let filters `l` and `l'` be related by `[intervalIntegral.FTCFilter a l l']`; let `μ` be a locally
finite measure. If `f` has a finite limit `c` at `l' ⊓ ae μ`, then
`∫ x in u..v, f x ∂μ = μ (Ioc u v) • c + o(μ(Ioc u v))` as both `u` and `v` tend to `l`.
See also `measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_le'` for a version that also works,
e.g., for `l = l' = Filter.atTop`. -/
theorem measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_le
(hfm : StronglyMeasurableAtFilter f l' μ) (hf : Tendsto f (l' ⊓ ae μ) (𝓝 c))
(hu : Tendsto u lt l) (hv : Tendsto v lt l) (huv : u ≤ᶠ[lt] v) :
(fun t => (∫ x in u t..v t, f x ∂μ) - (μ (Ioc (u t) (v t))).toReal • c) =o[lt] fun t =>
(μ <| Ioc (u t) (v t)).toReal :=
haveI := FTCFilter.meas_gen l
measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_le' hfm hf (FTCFilter.finiteAt_inner l) hu
hv huv
#align interval_integral.measure_integral_sub_linear_is_o_of_tendsto_ae_of_le intervalIntegral.measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_le
/-- **Fundamental theorem of calculus-1**, local version for any measure.
Let filters `l` and `l'` be related by `[intervalIntegral.FTCFilter a l l']`; let `μ` be a locally
finite measure. If `f` has a finite limit `c` at `l' ⊓ ae μ`, then
`∫ x in u..v, f x ∂μ = -μ (Set.Ioc v u) • c + o(μ(Set.Ioc v u))` as both `u` and `v` tend to `l`.
See also `measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_ge'` for a version that also works,
e.g., for `l = l' = Filter.atTop`. -/
theorem measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_ge
(hfm : StronglyMeasurableAtFilter f l' μ) (hf : Tendsto f (l' ⊓ ae μ) (𝓝 c))
(hu : Tendsto u lt l) (hv : Tendsto v lt l) (huv : v ≤ᶠ[lt] u) :
(fun t => (∫ x in u t..v t, f x ∂μ) + (μ (Ioc (v t) (u t))).toReal • c) =o[lt] fun t =>
(μ <| Ioc (v t) (u t)).toReal :=
haveI := FTCFilter.meas_gen l
measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_ge' hfm hf (FTCFilter.finiteAt_inner l) hu
hv huv
#align interval_integral.measure_integral_sub_linear_is_o_of_tendsto_ae_of_ge intervalIntegral.measure_integral_sub_linear_isLittleO_of_tendsto_ae_of_ge
end
variable [FTCFilter a la la'] [FTCFilter b lb lb'] [IsLocallyFiniteMeasure μ]
/-- **Fundamental theorem of calculus-1**, strict derivative in both limits for a locally finite
measure.
Let `f` be a measurable function integrable on `a..b`. Let `(la, la')` be a pair of
`intervalIntegral.FTCFilter`s around `a`; let `(lb, lb')` be a pair of `intervalIntegral.FTCFilter`s
around `b`. Suppose that `f` has finite limits `ca` and `cb` at `la' ⊓ ae μ` and `lb' ⊓ ae μ`,
respectively.
Then `∫ x in va..vb, f x ∂μ - ∫ x in ua..ub, f x ∂μ =
∫ x in ub..vb, cb ∂μ - ∫ x in ua..va, ca ∂μ +
o(‖∫ x in ua..va, (1:ℝ) ∂μ‖ + ‖∫ x in ub..vb, (1:ℝ) ∂μ‖)`
as `ua` and `va` tend to `la` while `ub` and `vb` tend to `lb`.
-/
theorem measure_integral_sub_integral_sub_linear_isLittleO_of_tendsto_ae
(hab : IntervalIntegrable f μ a b) (hmeas_a : StronglyMeasurableAtFilter f la' μ)
(hmeas_b : StronglyMeasurableAtFilter f lb' μ) (ha_lim : Tendsto f (la' ⊓ ae μ) (𝓝 ca))
(hb_lim : Tendsto f (lb' ⊓ ae μ) (𝓝 cb)) (hua : Tendsto ua lt la) (hva : Tendsto va lt la)
(hub : Tendsto ub lt lb) (hvb : Tendsto vb lt lb) :
(fun t =>
((∫ x in va t..vb t, f x ∂μ) - ∫ x in ua t..ub t, f x ∂μ) -
((∫ _ in ub t..vb t, cb ∂μ) - ∫ _ in ua t..va t, ca ∂μ)) =o[lt]
fun t => ‖∫ _ in ua t..va t, (1 : ℝ) ∂μ‖ + ‖∫ _ in ub t..vb t, (1 : ℝ) ∂μ‖ := by
haveI := FTCFilter.meas_gen la; haveI := FTCFilter.meas_gen lb
refine
((measure_integral_sub_linear_isLittleO_of_tendsto_ae hmeas_a ha_lim hua hva).neg_left.add_add
(measure_integral_sub_linear_isLittleO_of_tendsto_ae hmeas_b hb_lim hub hvb)).congr'
?_ EventuallyEq.rfl
have A : ∀ᶠ t in lt, IntervalIntegrable f μ (ua t) (va t) :=
ha_lim.eventually_intervalIntegrable_ae hmeas_a (FTCFilter.finiteAt_inner la) hua hva
have A' : ∀ᶠ t in lt, IntervalIntegrable f μ a (ua t) :=
ha_lim.eventually_intervalIntegrable_ae hmeas_a (FTCFilter.finiteAt_inner la)
(tendsto_const_pure.mono_right FTCFilter.pure_le) hua
have B : ∀ᶠ t in lt, IntervalIntegrable f μ (ub t) (vb t) :=
hb_lim.eventually_intervalIntegrable_ae hmeas_b (FTCFilter.finiteAt_inner lb) hub hvb
have B' : ∀ᶠ t in lt, IntervalIntegrable f μ b (ub t) :=
hb_lim.eventually_intervalIntegrable_ae hmeas_b (FTCFilter.finiteAt_inner lb)
(tendsto_const_pure.mono_right FTCFilter.pure_le) hub
filter_upwards [A, A', B, B'] with _ ua_va a_ua ub_vb b_ub
rw [← integral_interval_sub_interval_comm']
· abel
exacts [ub_vb, ua_va, b_ub.symm.trans <| hab.symm.trans a_ua]
#align interval_integral.measure_integral_sub_integral_sub_linear_is_o_of_tendsto_ae intervalIntegral.measure_integral_sub_integral_sub_linear_isLittleO_of_tendsto_ae
/-- **Fundamental theorem of calculus-1**, strict derivative in right endpoint for a locally finite
measure.
Let `f` be a measurable function integrable on `a..b`. Let `(lb, lb')` be a pair of
`intervalIntegral.FTCFilter`s around `b`. Suppose that `f` has a finite limit `c` at `lb' ⊓ ae μ`.
Then `∫ x in a..v, f x ∂μ - ∫ x in a..u, f x ∂μ = ∫ x in u..v, c ∂μ + o(∫ x in u..v, (1:ℝ) ∂μ)` as
`u` and `v` tend to `lb`.
-/
| Mathlib/MeasureTheory/Integral/FundThmCalculus.lean | 450 | 458 | theorem measure_integral_sub_integral_sub_linear_isLittleO_of_tendsto_ae_right
(hab : IntervalIntegrable f μ a b) (hmeas : StronglyMeasurableAtFilter f lb' μ)
(hf : Tendsto f (lb' ⊓ ae μ) (𝓝 c)) (hu : Tendsto u lt lb) (hv : Tendsto v lt lb) :
(fun t => ((∫ x in a..v t, f x ∂μ) - ∫ x in a..u t, f x ∂μ) - ∫ _ in u t..v t, c ∂μ) =o[lt]
fun t => ∫ _ in u t..v t, (1 : ℝ) ∂μ := by |
simpa using
measure_integral_sub_integral_sub_linear_isLittleO_of_tendsto_ae hab stronglyMeasurableAt_bot
hmeas ((tendsto_bot : Tendsto _ ⊥ (𝓝 (0 : E))).mono_left inf_le_left) hf
(tendsto_const_pure : Tendsto _ _ (pure a)) tendsto_const_pure hu hv
|
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Yury Kudryashov, Sébastien Gouëzel, Rémy Degenne
-/
import Mathlib.MeasureTheory.Integral.SetToL1
#align_import measure_theory.integral.bochner from "leanprover-community/mathlib"@"48fb5b5280e7c81672afc9524185ae994553ebf4"
/-!
# Bochner integral
The Bochner integral extends the definition of the Lebesgue integral to functions that map from a
measure space into a Banach space (complete normed vector space). It is constructed here by
extending the integral on simple functions.
## Main definitions
The Bochner integral is defined through the extension process described in the file `SetToL1`,
which follows these steps:
1. Define the integral of the indicator of a set. This is `weightedSMul μ s x = (μ s).toReal * x`.
`weightedSMul μ` is shown to be linear in the value `x` and `DominatedFinMeasAdditive`
(defined in the file `SetToL1`) with respect to the set `s`.
2. Define the integral on simple functions of the type `SimpleFunc α E` (notation : `α →ₛ E`)
where `E` is a real normed space. (See `SimpleFunc.integral` for details.)
3. Transfer this definition to define the integral on `L1.simpleFunc α E` (notation :
`α →₁ₛ[μ] E`), see `L1.simpleFunc.integral`. Show that this integral is a continuous linear
map from `α →₁ₛ[μ] E` to `E`.
4. Define the Bochner integral on L1 functions by extending the integral on integrable simple
functions `α →₁ₛ[μ] E` using `ContinuousLinearMap.extend` and the fact that the embedding of
`α →₁ₛ[μ] E` into `α →₁[μ] E` is dense.
5. Define the Bochner integral on functions as the Bochner integral of its equivalence class in L1
space, if it is in L1, and 0 otherwise.
The result of that construction is `∫ a, f a ∂μ`, which is definitionally equal to
`setToFun (dominatedFinMeasAdditive_weightedSMul μ) f`. Some basic properties of the integral
(like linearity) are particular cases of the properties of `setToFun` (which are described in the
file `SetToL1`).
## Main statements
1. Basic properties of the Bochner integral on functions of type `α → E`, where `α` is a measure
space and `E` is a real normed space.
* `integral_zero` : `∫ 0 ∂μ = 0`
* `integral_add` : `∫ x, f x + g x ∂μ = ∫ x, f ∂μ + ∫ x, g x ∂μ`
* `integral_neg` : `∫ x, - f x ∂μ = - ∫ x, f x ∂μ`
* `integral_sub` : `∫ x, f x - g x ∂μ = ∫ x, f x ∂μ - ∫ x, g x ∂μ`
* `integral_smul` : `∫ x, r • f x ∂μ = r • ∫ x, f x ∂μ`
* `integral_congr_ae` : `f =ᵐ[μ] g → ∫ x, f x ∂μ = ∫ x, g x ∂μ`
* `norm_integral_le_integral_norm` : `‖∫ x, f x ∂μ‖ ≤ ∫ x, ‖f x‖ ∂μ`
2. Basic properties of the Bochner integral on functions of type `α → ℝ`, where `α` is a measure
space.
* `integral_nonneg_of_ae` : `0 ≤ᵐ[μ] f → 0 ≤ ∫ x, f x ∂μ`
* `integral_nonpos_of_ae` : `f ≤ᵐ[μ] 0 → ∫ x, f x ∂μ ≤ 0`
* `integral_mono_ae` : `f ≤ᵐ[μ] g → ∫ x, f x ∂μ ≤ ∫ x, g x ∂μ`
* `integral_nonneg` : `0 ≤ f → 0 ≤ ∫ x, f x ∂μ`
* `integral_nonpos` : `f ≤ 0 → ∫ x, f x ∂μ ≤ 0`
* `integral_mono` : `f ≤ᵐ[μ] g → ∫ x, f x ∂μ ≤ ∫ x, g x ∂μ`
3. Propositions connecting the Bochner integral with the integral on `ℝ≥0∞`-valued functions,
which is called `lintegral` and has the notation `∫⁻`.
* `integral_eq_lintegral_pos_part_sub_lintegral_neg_part` :
`∫ x, f x ∂μ = ∫⁻ x, f⁺ x ∂μ - ∫⁻ x, f⁻ x ∂μ`,
where `f⁺` is the positive part of `f` and `f⁻` is the negative part of `f`.
* `integral_eq_lintegral_of_nonneg_ae` : `0 ≤ᵐ[μ] f → ∫ x, f x ∂μ = ∫⁻ x, f x ∂μ`
4. (In the file `DominatedConvergence`)
`tendsto_integral_of_dominated_convergence` : the Lebesgue dominated convergence theorem
5. (In the file `SetIntegral`) integration commutes with continuous linear maps.
* `ContinuousLinearMap.integral_comp_comm`
* `LinearIsometry.integral_comp_comm`
## Notes
Some tips on how to prove a proposition if the API for the Bochner integral is not enough so that
you need to unfold the definition of the Bochner integral and go back to simple functions.
One method is to use the theorem `Integrable.induction` in the file `SimpleFuncDenseLp` (or one
of the related results, like `Lp.induction` for functions in `Lp`), which allows you to prove
something for an arbitrary integrable function.
Another method is using the following steps.
See `integral_eq_lintegral_pos_part_sub_lintegral_neg_part` for a complicated example, which proves
that `∫ f = ∫⁻ f⁺ - ∫⁻ f⁻`, with the first integral sign being the Bochner integral of a real-valued
function `f : α → ℝ`, and second and third integral sign being the integral on `ℝ≥0∞`-valued
functions (called `lintegral`). The proof of `integral_eq_lintegral_pos_part_sub_lintegral_neg_part`
is scattered in sections with the name `posPart`.
Here are the usual steps of proving that a property `p`, say `∫ f = ∫⁻ f⁺ - ∫⁻ f⁻`, holds for all
functions :
1. First go to the `L¹` space.
For example, if you see `ENNReal.toReal (∫⁻ a, ENNReal.ofReal <| ‖f a‖)`, that is the norm of
`f` in `L¹` space. Rewrite using `L1.norm_of_fun_eq_lintegral_norm`.
2. Show that the set `{f ∈ L¹ | ∫ f = ∫⁻ f⁺ - ∫⁻ f⁻}` is closed in `L¹` using `isClosed_eq`.
3. Show that the property holds for all simple functions `s` in `L¹` space.
Typically, you need to convert various notions to their `SimpleFunc` counterpart, using lemmas
like `L1.integral_coe_eq_integral`.
4. Since simple functions are dense in `L¹`,
```
univ = closure {s simple}
= closure {s simple | ∫ s = ∫⁻ s⁺ - ∫⁻ s⁻} : the property holds for all simple functions
⊆ closure {f | ∫ f = ∫⁻ f⁺ - ∫⁻ f⁻}
= {f | ∫ f = ∫⁻ f⁺ - ∫⁻ f⁻} : closure of a closed set is itself
```
Use `isClosed_property` or `DenseRange.induction_on` for this argument.
## Notations
* `α →ₛ E` : simple functions (defined in `MeasureTheory/Integration`)
* `α →₁[μ] E` : functions in L1 space, i.e., equivalence classes of integrable functions (defined in
`MeasureTheory/LpSpace`)
* `α →₁ₛ[μ] E` : simple functions in L1 space, i.e., equivalence classes of integrable simple
functions (defined in `MeasureTheory/SimpleFuncDense`)
* `∫ a, f a ∂μ` : integral of `f` with respect to a measure `μ`
* `∫ a, f a` : integral of `f` with respect to `volume`, the default measure on the ambient type
We also define notations for integral on a set, which are described in the file
`MeasureTheory/SetIntegral`.
Note : `ₛ` is typed using `\_s`. Sometimes it shows as a box if the font is missing.
## Tags
Bochner integral, simple function, function space, Lebesgue dominated convergence theorem
-/
assert_not_exists Differentiable
noncomputable section
open scoped Topology NNReal ENNReal MeasureTheory
open Set Filter TopologicalSpace ENNReal EMetric
namespace MeasureTheory
variable {α E F 𝕜 : Type*}
section WeightedSMul
open ContinuousLinearMap
variable [NormedAddCommGroup F] [NormedSpace ℝ F] {m : MeasurableSpace α} {μ : Measure α}
/-- Given a set `s`, return the continuous linear map `fun x => (μ s).toReal • x`. The extension
of that set function through `setToL1` gives the Bochner integral of L1 functions. -/
def weightedSMul {_ : MeasurableSpace α} (μ : Measure α) (s : Set α) : F →L[ℝ] F :=
(μ s).toReal • ContinuousLinearMap.id ℝ F
#align measure_theory.weighted_smul MeasureTheory.weightedSMul
theorem weightedSMul_apply {m : MeasurableSpace α} (μ : Measure α) (s : Set α) (x : F) :
weightedSMul μ s x = (μ s).toReal • x := by simp [weightedSMul]
#align measure_theory.weighted_smul_apply MeasureTheory.weightedSMul_apply
@[simp]
theorem weightedSMul_zero_measure {m : MeasurableSpace α} :
weightedSMul (0 : Measure α) = (0 : Set α → F →L[ℝ] F) := by ext1; simp [weightedSMul]
#align measure_theory.weighted_smul_zero_measure MeasureTheory.weightedSMul_zero_measure
@[simp]
theorem weightedSMul_empty {m : MeasurableSpace α} (μ : Measure α) :
weightedSMul μ ∅ = (0 : F →L[ℝ] F) := by ext1 x; rw [weightedSMul_apply]; simp
#align measure_theory.weighted_smul_empty MeasureTheory.weightedSMul_empty
theorem weightedSMul_add_measure {m : MeasurableSpace α} (μ ν : Measure α) {s : Set α}
(hμs : μ s ≠ ∞) (hνs : ν s ≠ ∞) :
(weightedSMul (μ + ν) s : F →L[ℝ] F) = weightedSMul μ s + weightedSMul ν s := by
ext1 x
push_cast
simp_rw [Pi.add_apply, weightedSMul_apply]
push_cast
rw [Pi.add_apply, ENNReal.toReal_add hμs hνs, add_smul]
#align measure_theory.weighted_smul_add_measure MeasureTheory.weightedSMul_add_measure
theorem weightedSMul_smul_measure {m : MeasurableSpace α} (μ : Measure α) (c : ℝ≥0∞) {s : Set α} :
(weightedSMul (c • μ) s : F →L[ℝ] F) = c.toReal • weightedSMul μ s := by
ext1 x
push_cast
simp_rw [Pi.smul_apply, weightedSMul_apply]
push_cast
simp_rw [Pi.smul_apply, smul_eq_mul, toReal_mul, smul_smul]
#align measure_theory.weighted_smul_smul_measure MeasureTheory.weightedSMul_smul_measure
theorem weightedSMul_congr (s t : Set α) (hst : μ s = μ t) :
(weightedSMul μ s : F →L[ℝ] F) = weightedSMul μ t := by
ext1 x; simp_rw [weightedSMul_apply]; congr 2
#align measure_theory.weighted_smul_congr MeasureTheory.weightedSMul_congr
theorem weightedSMul_null {s : Set α} (h_zero : μ s = 0) : (weightedSMul μ s : F →L[ℝ] F) = 0 := by
ext1 x; rw [weightedSMul_apply, h_zero]; simp
#align measure_theory.weighted_smul_null MeasureTheory.weightedSMul_null
theorem weightedSMul_union' (s t : Set α) (ht : MeasurableSet t) (hs_finite : μ s ≠ ∞)
(ht_finite : μ t ≠ ∞) (h_inter : s ∩ t = ∅) :
(weightedSMul μ (s ∪ t) : F →L[ℝ] F) = weightedSMul μ s + weightedSMul μ t := by
ext1 x
simp_rw [add_apply, weightedSMul_apply,
measure_union (Set.disjoint_iff_inter_eq_empty.mpr h_inter) ht,
ENNReal.toReal_add hs_finite ht_finite, add_smul]
#align measure_theory.weighted_smul_union' MeasureTheory.weightedSMul_union'
@[nolint unusedArguments]
theorem weightedSMul_union (s t : Set α) (_hs : MeasurableSet s) (ht : MeasurableSet t)
(hs_finite : μ s ≠ ∞) (ht_finite : μ t ≠ ∞) (h_inter : s ∩ t = ∅) :
(weightedSMul μ (s ∪ t) : F →L[ℝ] F) = weightedSMul μ s + weightedSMul μ t :=
weightedSMul_union' s t ht hs_finite ht_finite h_inter
#align measure_theory.weighted_smul_union MeasureTheory.weightedSMul_union
theorem weightedSMul_smul [NormedField 𝕜] [NormedSpace 𝕜 F] [SMulCommClass ℝ 𝕜 F] (c : 𝕜)
(s : Set α) (x : F) : weightedSMul μ s (c • x) = c • weightedSMul μ s x := by
simp_rw [weightedSMul_apply, smul_comm]
#align measure_theory.weighted_smul_smul MeasureTheory.weightedSMul_smul
theorem norm_weightedSMul_le (s : Set α) : ‖(weightedSMul μ s : F →L[ℝ] F)‖ ≤ (μ s).toReal :=
calc
‖(weightedSMul μ s : F →L[ℝ] F)‖ = ‖(μ s).toReal‖ * ‖ContinuousLinearMap.id ℝ F‖ :=
norm_smul (μ s).toReal (ContinuousLinearMap.id ℝ F)
_ ≤ ‖(μ s).toReal‖ :=
((mul_le_mul_of_nonneg_left norm_id_le (norm_nonneg _)).trans (mul_one _).le)
_ = abs (μ s).toReal := Real.norm_eq_abs _
_ = (μ s).toReal := abs_eq_self.mpr ENNReal.toReal_nonneg
#align measure_theory.norm_weighted_smul_le MeasureTheory.norm_weightedSMul_le
theorem dominatedFinMeasAdditive_weightedSMul {_ : MeasurableSpace α} (μ : Measure α) :
DominatedFinMeasAdditive μ (weightedSMul μ : Set α → F →L[ℝ] F) 1 :=
⟨weightedSMul_union, fun s _ _ => (norm_weightedSMul_le s).trans (one_mul _).symm.le⟩
#align measure_theory.dominated_fin_meas_additive_weighted_smul MeasureTheory.dominatedFinMeasAdditive_weightedSMul
theorem weightedSMul_nonneg (s : Set α) (x : ℝ) (hx : 0 ≤ x) : 0 ≤ weightedSMul μ s x := by
simp only [weightedSMul, Algebra.id.smul_eq_mul, coe_smul', _root_.id, coe_id', Pi.smul_apply]
exact mul_nonneg toReal_nonneg hx
#align measure_theory.weighted_smul_nonneg MeasureTheory.weightedSMul_nonneg
end WeightedSMul
local infixr:25 " →ₛ " => SimpleFunc
namespace SimpleFunc
section PosPart
variable [LinearOrder E] [Zero E] [MeasurableSpace α]
/-- Positive part of a simple function. -/
def posPart (f : α →ₛ E) : α →ₛ E :=
f.map fun b => max b 0
#align measure_theory.simple_func.pos_part MeasureTheory.SimpleFunc.posPart
/-- Negative part of a simple function. -/
def negPart [Neg E] (f : α →ₛ E) : α →ₛ E :=
posPart (-f)
#align measure_theory.simple_func.neg_part MeasureTheory.SimpleFunc.negPart
theorem posPart_map_norm (f : α →ₛ ℝ) : (posPart f).map norm = posPart f := by
ext; rw [map_apply, Real.norm_eq_abs, abs_of_nonneg]; exact le_max_right _ _
#align measure_theory.simple_func.pos_part_map_norm MeasureTheory.SimpleFunc.posPart_map_norm
theorem negPart_map_norm (f : α →ₛ ℝ) : (negPart f).map norm = negPart f := by
rw [negPart]; exact posPart_map_norm _
#align measure_theory.simple_func.neg_part_map_norm MeasureTheory.SimpleFunc.negPart_map_norm
theorem posPart_sub_negPart (f : α →ₛ ℝ) : f.posPart - f.negPart = f := by
simp only [posPart, negPart]
ext a
rw [coe_sub]
exact max_zero_sub_eq_self (f a)
#align measure_theory.simple_func.pos_part_sub_neg_part MeasureTheory.SimpleFunc.posPart_sub_negPart
end PosPart
section Integral
/-!
### The Bochner integral of simple functions
Define the Bochner integral of simple functions of the type `α →ₛ β` where `β` is a normed group,
and prove basic property of this integral.
-/
open Finset
variable [NormedAddCommGroup E] [NormedAddCommGroup F] [NormedSpace ℝ F] {p : ℝ≥0∞} {G F' : Type*}
[NormedAddCommGroup G] [NormedAddCommGroup F'] [NormedSpace ℝ F'] {m : MeasurableSpace α}
{μ : Measure α}
/-- Bochner integral of simple functions whose codomain is a real `NormedSpace`.
This is equal to `∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal • x` (see `integral_eq`). -/
def integral {_ : MeasurableSpace α} (μ : Measure α) (f : α →ₛ F) : F :=
f.setToSimpleFunc (weightedSMul μ)
#align measure_theory.simple_func.integral MeasureTheory.SimpleFunc.integral
theorem integral_def {_ : MeasurableSpace α} (μ : Measure α) (f : α →ₛ F) :
f.integral μ = f.setToSimpleFunc (weightedSMul μ) := rfl
#align measure_theory.simple_func.integral_def MeasureTheory.SimpleFunc.integral_def
theorem integral_eq {m : MeasurableSpace α} (μ : Measure α) (f : α →ₛ F) :
f.integral μ = ∑ x ∈ f.range, (μ (f ⁻¹' {x})).toReal • x := by
simp [integral, setToSimpleFunc, weightedSMul_apply]
#align measure_theory.simple_func.integral_eq MeasureTheory.SimpleFunc.integral_eq
theorem integral_eq_sum_filter [DecidablePred fun x : F => x ≠ 0] {m : MeasurableSpace α}
(f : α →ₛ F) (μ : Measure α) :
f.integral μ = ∑ x ∈ f.range.filter fun x => x ≠ 0, (μ (f ⁻¹' {x})).toReal • x := by
rw [integral_def, setToSimpleFunc_eq_sum_filter]; simp_rw [weightedSMul_apply]; congr
#align measure_theory.simple_func.integral_eq_sum_filter MeasureTheory.SimpleFunc.integral_eq_sum_filter
/-- The Bochner integral is equal to a sum over any set that includes `f.range` (except `0`). -/
theorem integral_eq_sum_of_subset [DecidablePred fun x : F => x ≠ 0] {f : α →ₛ F} {s : Finset F}
(hs : (f.range.filter fun x => x ≠ 0) ⊆ s) :
f.integral μ = ∑ x ∈ s, (μ (f ⁻¹' {x})).toReal • x := by
rw [SimpleFunc.integral_eq_sum_filter, Finset.sum_subset hs]
rintro x - hx; rw [Finset.mem_filter, not_and_or, Ne, Classical.not_not] at hx
-- Porting note: reordered for clarity
rcases hx.symm with (rfl | hx)
· simp
rw [SimpleFunc.mem_range] at hx
-- Porting note: added
simp only [Set.mem_range, not_exists] at hx
rw [preimage_eq_empty] <;> simp [Set.disjoint_singleton_left, hx]
#align measure_theory.simple_func.integral_eq_sum_of_subset MeasureTheory.SimpleFunc.integral_eq_sum_of_subset
@[simp]
theorem integral_const {m : MeasurableSpace α} (μ : Measure α) (y : F) :
(const α y).integral μ = (μ univ).toReal • y := by
classical
calc
(const α y).integral μ = ∑ z ∈ {y}, (μ (const α y ⁻¹' {z})).toReal • z :=
integral_eq_sum_of_subset <| (filter_subset _ _).trans (range_const_subset _ _)
_ = (μ univ).toReal • y := by simp [Set.preimage] -- Porting note: added `Set.preimage`
#align measure_theory.simple_func.integral_const MeasureTheory.SimpleFunc.integral_const
@[simp]
theorem integral_piecewise_zero {m : MeasurableSpace α} (f : α →ₛ F) (μ : Measure α) {s : Set α}
(hs : MeasurableSet s) : (piecewise s hs f 0).integral μ = f.integral (μ.restrict s) := by
classical
refine (integral_eq_sum_of_subset ?_).trans
((sum_congr rfl fun y hy => ?_).trans (integral_eq_sum_filter _ _).symm)
· intro y hy
simp only [mem_filter, mem_range, coe_piecewise, coe_zero, piecewise_eq_indicator,
mem_range_indicator] at *
rcases hy with ⟨⟨rfl, -⟩ | ⟨x, -, rfl⟩, h₀⟩
exacts [(h₀ rfl).elim, ⟨Set.mem_range_self _, h₀⟩]
· dsimp
rw [Set.piecewise_eq_indicator, indicator_preimage_of_not_mem,
Measure.restrict_apply (f.measurableSet_preimage _)]
exact fun h₀ => (mem_filter.1 hy).2 (Eq.symm h₀)
#align measure_theory.simple_func.integral_piecewise_zero MeasureTheory.SimpleFunc.integral_piecewise_zero
/-- Calculate the integral of `g ∘ f : α →ₛ F`, where `f` is an integrable function from `α` to `E`
and `g` is a function from `E` to `F`. We require `g 0 = 0` so that `g ∘ f` is integrable. -/
theorem map_integral (f : α →ₛ E) (g : E → F) (hf : Integrable f μ) (hg : g 0 = 0) :
(f.map g).integral μ = ∑ x ∈ f.range, ENNReal.toReal (μ (f ⁻¹' {x})) • g x :=
map_setToSimpleFunc _ weightedSMul_union hf hg
#align measure_theory.simple_func.map_integral MeasureTheory.SimpleFunc.map_integral
/-- `SimpleFunc.integral` and `SimpleFunc.lintegral` agree when the integrand has type
`α →ₛ ℝ≥0∞`. But since `ℝ≥0∞` is not a `NormedSpace`, we need some form of coercion.
See `integral_eq_lintegral` for a simpler version. -/
theorem integral_eq_lintegral' {f : α →ₛ E} {g : E → ℝ≥0∞} (hf : Integrable f μ) (hg0 : g 0 = 0)
(ht : ∀ b, g b ≠ ∞) :
(f.map (ENNReal.toReal ∘ g)).integral μ = ENNReal.toReal (∫⁻ a, g (f a) ∂μ) := by
have hf' : f.FinMeasSupp μ := integrable_iff_finMeasSupp.1 hf
simp only [← map_apply g f, lintegral_eq_lintegral]
rw [map_integral f _ hf, map_lintegral, ENNReal.toReal_sum]
· refine Finset.sum_congr rfl fun b _ => ?_
-- Porting note: added `Function.comp_apply`
rw [smul_eq_mul, toReal_mul, mul_comm, Function.comp_apply]
· rintro a -
by_cases a0 : a = 0
· rw [a0, hg0, zero_mul]; exact WithTop.zero_ne_top
· apply mul_ne_top (ht a) (hf'.meas_preimage_singleton_ne_zero a0).ne
· simp [hg0]
#align measure_theory.simple_func.integral_eq_lintegral' MeasureTheory.SimpleFunc.integral_eq_lintegral'
variable [NormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace ℝ E] [SMulCommClass ℝ 𝕜 E]
theorem integral_congr {f g : α →ₛ E} (hf : Integrable f μ) (h : f =ᵐ[μ] g) :
f.integral μ = g.integral μ :=
setToSimpleFunc_congr (weightedSMul μ) (fun _ _ => weightedSMul_null) weightedSMul_union hf h
#align measure_theory.simple_func.integral_congr MeasureTheory.SimpleFunc.integral_congr
/-- `SimpleFunc.bintegral` and `SimpleFunc.integral` agree when the integrand has type
`α →ₛ ℝ≥0∞`. But since `ℝ≥0∞` is not a `NormedSpace`, we need some form of coercion. -/
theorem integral_eq_lintegral {f : α →ₛ ℝ} (hf : Integrable f μ) (h_pos : 0 ≤ᵐ[μ] f) :
f.integral μ = ENNReal.toReal (∫⁻ a, ENNReal.ofReal (f a) ∂μ) := by
have : f =ᵐ[μ] f.map (ENNReal.toReal ∘ ENNReal.ofReal) :=
h_pos.mono fun a h => (ENNReal.toReal_ofReal h).symm
rw [← integral_eq_lintegral' hf]
exacts [integral_congr hf this, ENNReal.ofReal_zero, fun b => ENNReal.ofReal_ne_top]
#align measure_theory.simple_func.integral_eq_lintegral MeasureTheory.SimpleFunc.integral_eq_lintegral
theorem integral_add {f g : α →ₛ E} (hf : Integrable f μ) (hg : Integrable g μ) :
integral μ (f + g) = integral μ f + integral μ g :=
setToSimpleFunc_add _ weightedSMul_union hf hg
#align measure_theory.simple_func.integral_add MeasureTheory.SimpleFunc.integral_add
theorem integral_neg {f : α →ₛ E} (hf : Integrable f μ) : integral μ (-f) = -integral μ f :=
setToSimpleFunc_neg _ weightedSMul_union hf
#align measure_theory.simple_func.integral_neg MeasureTheory.SimpleFunc.integral_neg
theorem integral_sub {f g : α →ₛ E} (hf : Integrable f μ) (hg : Integrable g μ) :
integral μ (f - g) = integral μ f - integral μ g :=
setToSimpleFunc_sub _ weightedSMul_union hf hg
#align measure_theory.simple_func.integral_sub MeasureTheory.SimpleFunc.integral_sub
theorem integral_smul (c : 𝕜) {f : α →ₛ E} (hf : Integrable f μ) :
integral μ (c • f) = c • integral μ f :=
setToSimpleFunc_smul _ weightedSMul_union weightedSMul_smul c hf
#align measure_theory.simple_func.integral_smul MeasureTheory.SimpleFunc.integral_smul
theorem norm_setToSimpleFunc_le_integral_norm (T : Set α → E →L[ℝ] F) {C : ℝ}
(hT_norm : ∀ s, MeasurableSet s → μ s < ∞ → ‖T s‖ ≤ C * (μ s).toReal) {f : α →ₛ E}
(hf : Integrable f μ) : ‖f.setToSimpleFunc T‖ ≤ C * (f.map norm).integral μ :=
calc
‖f.setToSimpleFunc T‖ ≤ C * ∑ x ∈ f.range, ENNReal.toReal (μ (f ⁻¹' {x})) * ‖x‖ :=
norm_setToSimpleFunc_le_sum_mul_norm_of_integrable T hT_norm f hf
_ = C * (f.map norm).integral μ := by
rw [map_integral f norm hf norm_zero]; simp_rw [smul_eq_mul]
#align measure_theory.simple_func.norm_set_to_simple_func_le_integral_norm MeasureTheory.SimpleFunc.norm_setToSimpleFunc_le_integral_norm
theorem norm_integral_le_integral_norm (f : α →ₛ E) (hf : Integrable f μ) :
‖f.integral μ‖ ≤ (f.map norm).integral μ := by
refine (norm_setToSimpleFunc_le_integral_norm _ (fun s _ _ => ?_) hf).trans (one_mul _).le
exact (norm_weightedSMul_le s).trans (one_mul _).symm.le
#align measure_theory.simple_func.norm_integral_le_integral_norm MeasureTheory.SimpleFunc.norm_integral_le_integral_norm
theorem integral_add_measure {ν} (f : α →ₛ E) (hf : Integrable f (μ + ν)) :
f.integral (μ + ν) = f.integral μ + f.integral ν := by
simp_rw [integral_def]
refine setToSimpleFunc_add_left'
(weightedSMul μ) (weightedSMul ν) (weightedSMul (μ + ν)) (fun s _ hμνs => ?_) hf
rw [lt_top_iff_ne_top, Measure.coe_add, Pi.add_apply, ENNReal.add_ne_top] at hμνs
rw [weightedSMul_add_measure _ _ hμνs.1 hμνs.2]
#align measure_theory.simple_func.integral_add_measure MeasureTheory.SimpleFunc.integral_add_measure
end Integral
end SimpleFunc
namespace L1
set_option linter.uppercaseLean3 false -- `L1`
open AEEqFun Lp.simpleFunc Lp
variable [NormedAddCommGroup E] [NormedAddCommGroup F] {m : MeasurableSpace α} {μ : Measure α}
namespace SimpleFunc
theorem norm_eq_integral (f : α →₁ₛ[μ] E) : ‖f‖ = ((toSimpleFunc f).map norm).integral μ := by
rw [norm_eq_sum_mul f, (toSimpleFunc f).map_integral norm (SimpleFunc.integrable f) norm_zero]
simp_rw [smul_eq_mul]
#align measure_theory.L1.simple_func.norm_eq_integral MeasureTheory.L1.SimpleFunc.norm_eq_integral
section PosPart
/-- Positive part of a simple function in L1 space. -/
nonrec def posPart (f : α →₁ₛ[μ] ℝ) : α →₁ₛ[μ] ℝ :=
⟨Lp.posPart (f : α →₁[μ] ℝ), by
rcases f with ⟨f, s, hsf⟩
use s.posPart
simp only [Subtype.coe_mk, Lp.coe_posPart, ← hsf, AEEqFun.posPart_mk,
SimpleFunc.coe_map, mk_eq_mk]
-- Porting note: added
simp [SimpleFunc.posPart, Function.comp, EventuallyEq.rfl] ⟩
#align measure_theory.L1.simple_func.pos_part MeasureTheory.L1.SimpleFunc.posPart
/-- Negative part of a simple function in L1 space. -/
def negPart (f : α →₁ₛ[μ] ℝ) : α →₁ₛ[μ] ℝ :=
posPart (-f)
#align measure_theory.L1.simple_func.neg_part MeasureTheory.L1.SimpleFunc.negPart
@[norm_cast]
theorem coe_posPart (f : α →₁ₛ[μ] ℝ) : (posPart f : α →₁[μ] ℝ) = Lp.posPart (f : α →₁[μ] ℝ) := rfl
#align measure_theory.L1.simple_func.coe_pos_part MeasureTheory.L1.SimpleFunc.coe_posPart
@[norm_cast]
theorem coe_negPart (f : α →₁ₛ[μ] ℝ) : (negPart f : α →₁[μ] ℝ) = Lp.negPart (f : α →₁[μ] ℝ) := rfl
#align measure_theory.L1.simple_func.coe_neg_part MeasureTheory.L1.SimpleFunc.coe_negPart
end PosPart
section SimpleFuncIntegral
/-!
### The Bochner integral of `L1`
Define the Bochner integral on `α →₁ₛ[μ] E` by extension from the simple functions `α →₁ₛ[μ] E`,
and prove basic properties of this integral. -/
variable [NormedField 𝕜] [NormedSpace 𝕜 E] [NormedSpace ℝ E] [SMulCommClass ℝ 𝕜 E] {F' : Type*}
[NormedAddCommGroup F'] [NormedSpace ℝ F']
attribute [local instance] simpleFunc.normedSpace
/-- The Bochner integral over simple functions in L1 space. -/
def integral (f : α →₁ₛ[μ] E) : E :=
(toSimpleFunc f).integral μ
#align measure_theory.L1.simple_func.integral MeasureTheory.L1.SimpleFunc.integral
theorem integral_eq_integral (f : α →₁ₛ[μ] E) : integral f = (toSimpleFunc f).integral μ := rfl
#align measure_theory.L1.simple_func.integral_eq_integral MeasureTheory.L1.SimpleFunc.integral_eq_integral
nonrec theorem integral_eq_lintegral {f : α →₁ₛ[μ] ℝ} (h_pos : 0 ≤ᵐ[μ] toSimpleFunc f) :
integral f = ENNReal.toReal (∫⁻ a, ENNReal.ofReal ((toSimpleFunc f) a) ∂μ) := by
rw [integral, SimpleFunc.integral_eq_lintegral (SimpleFunc.integrable f) h_pos]
#align measure_theory.L1.simple_func.integral_eq_lintegral MeasureTheory.L1.SimpleFunc.integral_eq_lintegral
theorem integral_eq_setToL1S (f : α →₁ₛ[μ] E) : integral f = setToL1S (weightedSMul μ) f := rfl
#align measure_theory.L1.simple_func.integral_eq_set_to_L1s MeasureTheory.L1.SimpleFunc.integral_eq_setToL1S
nonrec theorem integral_congr {f g : α →₁ₛ[μ] E} (h : toSimpleFunc f =ᵐ[μ] toSimpleFunc g) :
integral f = integral g :=
SimpleFunc.integral_congr (SimpleFunc.integrable f) h
#align measure_theory.L1.simple_func.integral_congr MeasureTheory.L1.SimpleFunc.integral_congr
theorem integral_add (f g : α →₁ₛ[μ] E) : integral (f + g) = integral f + integral g :=
setToL1S_add _ (fun _ _ => weightedSMul_null) weightedSMul_union _ _
#align measure_theory.L1.simple_func.integral_add MeasureTheory.L1.SimpleFunc.integral_add
theorem integral_smul (c : 𝕜) (f : α →₁ₛ[μ] E) : integral (c • f) = c • integral f :=
setToL1S_smul _ (fun _ _ => weightedSMul_null) weightedSMul_union weightedSMul_smul c f
#align measure_theory.L1.simple_func.integral_smul MeasureTheory.L1.SimpleFunc.integral_smul
theorem norm_integral_le_norm (f : α →₁ₛ[μ] E) : ‖integral f‖ ≤ ‖f‖ := by
rw [integral, norm_eq_integral]
exact (toSimpleFunc f).norm_integral_le_integral_norm (SimpleFunc.integrable f)
#align measure_theory.L1.simple_func.norm_integral_le_norm MeasureTheory.L1.SimpleFunc.norm_integral_le_norm
variable {E' : Type*} [NormedAddCommGroup E'] [NormedSpace ℝ E'] [NormedSpace 𝕜 E']
variable (α E μ 𝕜)
/-- The Bochner integral over simple functions in L1 space as a continuous linear map. -/
def integralCLM' : (α →₁ₛ[μ] E) →L[𝕜] E :=
LinearMap.mkContinuous ⟨⟨integral, integral_add⟩, integral_smul⟩ 1 fun f =>
le_trans (norm_integral_le_norm _) <| by rw [one_mul]
#align measure_theory.L1.simple_func.integral_clm' MeasureTheory.L1.SimpleFunc.integralCLM'
/-- The Bochner integral over simple functions in L1 space as a continuous linear map over ℝ. -/
def integralCLM : (α →₁ₛ[μ] E) →L[ℝ] E :=
integralCLM' α E ℝ μ
#align measure_theory.L1.simple_func.integral_clm MeasureTheory.L1.SimpleFunc.integralCLM
variable {α E μ 𝕜}
local notation "Integral" => integralCLM α E μ
open ContinuousLinearMap
theorem norm_Integral_le_one : ‖Integral‖ ≤ 1 :=
-- Porting note: Old proof was `LinearMap.mkContinuous_norm_le _ zero_le_one _`
LinearMap.mkContinuous_norm_le _ zero_le_one (fun f => by
rw [one_mul]
exact norm_integral_le_norm f)
#align measure_theory.L1.simple_func.norm_Integral_le_one MeasureTheory.L1.SimpleFunc.norm_Integral_le_one
section PosPart
theorem posPart_toSimpleFunc (f : α →₁ₛ[μ] ℝ) :
toSimpleFunc (posPart f) =ᵐ[μ] (toSimpleFunc f).posPart := by
have eq : ∀ a, (toSimpleFunc f).posPart a = max ((toSimpleFunc f) a) 0 := fun a => rfl
have ae_eq : ∀ᵐ a ∂μ, toSimpleFunc (posPart f) a = max ((toSimpleFunc f) a) 0 := by
filter_upwards [toSimpleFunc_eq_toFun (posPart f), Lp.coeFn_posPart (f : α →₁[μ] ℝ),
toSimpleFunc_eq_toFun f] with _ _ h₂ h₃
convert h₂ using 1
-- Porting note: added
rw [h₃]
refine ae_eq.mono fun a h => ?_
rw [h, eq]
#align measure_theory.L1.simple_func.pos_part_to_simple_func MeasureTheory.L1.SimpleFunc.posPart_toSimpleFunc
theorem negPart_toSimpleFunc (f : α →₁ₛ[μ] ℝ) :
toSimpleFunc (negPart f) =ᵐ[μ] (toSimpleFunc f).negPart := by
rw [SimpleFunc.negPart, MeasureTheory.SimpleFunc.negPart]
filter_upwards [posPart_toSimpleFunc (-f), neg_toSimpleFunc f]
intro a h₁ h₂
rw [h₁]
show max _ _ = max _ _
rw [h₂]
rfl
#align measure_theory.L1.simple_func.neg_part_to_simple_func MeasureTheory.L1.SimpleFunc.negPart_toSimpleFunc
theorem integral_eq_norm_posPart_sub (f : α →₁ₛ[μ] ℝ) : integral f = ‖posPart f‖ - ‖negPart f‖ := by
-- Convert things in `L¹` to their `SimpleFunc` counterpart
have ae_eq₁ : (toSimpleFunc f).posPart =ᵐ[μ] (toSimpleFunc (posPart f)).map norm := by
filter_upwards [posPart_toSimpleFunc f] with _ h
rw [SimpleFunc.map_apply, h]
conv_lhs => rw [← SimpleFunc.posPart_map_norm, SimpleFunc.map_apply]
-- Convert things in `L¹` to their `SimpleFunc` counterpart
have ae_eq₂ : (toSimpleFunc f).negPart =ᵐ[μ] (toSimpleFunc (negPart f)).map norm := by
filter_upwards [negPart_toSimpleFunc f] with _ h
rw [SimpleFunc.map_apply, h]
conv_lhs => rw [← SimpleFunc.negPart_map_norm, SimpleFunc.map_apply]
rw [integral, norm_eq_integral, norm_eq_integral, ← SimpleFunc.integral_sub]
· show (toSimpleFunc f).integral μ =
((toSimpleFunc (posPart f)).map norm - (toSimpleFunc (negPart f)).map norm).integral μ
apply MeasureTheory.SimpleFunc.integral_congr (SimpleFunc.integrable f)
filter_upwards [ae_eq₁, ae_eq₂] with _ h₁ h₂
show _ = _ - _
rw [← h₁, ← h₂]
have := (toSimpleFunc f).posPart_sub_negPart
conv_lhs => rw [← this]
rfl
· exact (SimpleFunc.integrable f).pos_part.congr ae_eq₁
· exact (SimpleFunc.integrable f).neg_part.congr ae_eq₂
#align measure_theory.L1.simple_func.integral_eq_norm_pos_part_sub MeasureTheory.L1.SimpleFunc.integral_eq_norm_posPart_sub
end PosPart
end SimpleFuncIntegral
end SimpleFunc
open SimpleFunc
local notation "Integral" => @integralCLM α E _ _ _ _ _ μ _
variable [NormedSpace ℝ E] [NontriviallyNormedField 𝕜] [NormedSpace 𝕜 E] [SMulCommClass ℝ 𝕜 E]
[NormedSpace ℝ F] [CompleteSpace E]
section IntegrationInL1
attribute [local instance] simpleFunc.normedSpace
open ContinuousLinearMap
variable (𝕜)
/-- The Bochner integral in L1 space as a continuous linear map. -/
nonrec def integralCLM' : (α →₁[μ] E) →L[𝕜] E :=
(integralCLM' α E 𝕜 μ).extend (coeToLp α E 𝕜) (simpleFunc.denseRange one_ne_top)
simpleFunc.uniformInducing
#align measure_theory.L1.integral_clm' MeasureTheory.L1.integralCLM'
variable {𝕜}
/-- The Bochner integral in L1 space as a continuous linear map over ℝ. -/
def integralCLM : (α →₁[μ] E) →L[ℝ] E :=
integralCLM' ℝ
#align measure_theory.L1.integral_clm MeasureTheory.L1.integralCLM
-- Porting note: added `(E := E)` in several places below.
/-- The Bochner integral in L1 space -/
irreducible_def integral (f : α →₁[μ] E) : E :=
integralCLM (E := E) f
#align measure_theory.L1.integral MeasureTheory.L1.integral
theorem integral_eq (f : α →₁[μ] E) : integral f = integralCLM (E := E) f := by
simp only [integral]
#align measure_theory.L1.integral_eq MeasureTheory.L1.integral_eq
theorem integral_eq_setToL1 (f : α →₁[μ] E) :
integral f = setToL1 (E := E) (dominatedFinMeasAdditive_weightedSMul μ) f := by
simp only [integral]; rfl
#align measure_theory.L1.integral_eq_set_to_L1 MeasureTheory.L1.integral_eq_setToL1
@[norm_cast]
theorem SimpleFunc.integral_L1_eq_integral (f : α →₁ₛ[μ] E) :
L1.integral (f : α →₁[μ] E) = SimpleFunc.integral f := by
simp only [integral, L1.integral]
exact setToL1_eq_setToL1SCLM (dominatedFinMeasAdditive_weightedSMul μ) f
#align measure_theory.L1.simple_func.integral_L1_eq_integral MeasureTheory.L1.SimpleFunc.integral_L1_eq_integral
variable (α E)
@[simp]
theorem integral_zero : integral (0 : α →₁[μ] E) = 0 := by
simp only [integral]
exact map_zero integralCLM
#align measure_theory.L1.integral_zero MeasureTheory.L1.integral_zero
variable {α E}
@[integral_simps]
theorem integral_add (f g : α →₁[μ] E) : integral (f + g) = integral f + integral g := by
simp only [integral]
exact map_add integralCLM f g
#align measure_theory.L1.integral_add MeasureTheory.L1.integral_add
@[integral_simps]
theorem integral_neg (f : α →₁[μ] E) : integral (-f) = -integral f := by
simp only [integral]
exact map_neg integralCLM f
#align measure_theory.L1.integral_neg MeasureTheory.L1.integral_neg
@[integral_simps]
theorem integral_sub (f g : α →₁[μ] E) : integral (f - g) = integral f - integral g := by
simp only [integral]
exact map_sub integralCLM f g
#align measure_theory.L1.integral_sub MeasureTheory.L1.integral_sub
@[integral_simps]
theorem integral_smul (c : 𝕜) (f : α →₁[μ] E) : integral (c • f) = c • integral f := by
simp only [integral]
show (integralCLM' (E := E) 𝕜) (c • f) = c • (integralCLM' (E := E) 𝕜) f
exact map_smul (integralCLM' (E := E) 𝕜) c f
#align measure_theory.L1.integral_smul MeasureTheory.L1.integral_smul
local notation "Integral" => @integralCLM α E _ _ μ _ _
local notation "sIntegral" => @SimpleFunc.integralCLM α E _ _ μ _
theorem norm_Integral_le_one : ‖integralCLM (α := α) (E := E) (μ := μ)‖ ≤ 1 :=
norm_setToL1_le (dominatedFinMeasAdditive_weightedSMul μ) zero_le_one
#align measure_theory.L1.norm_Integral_le_one MeasureTheory.L1.norm_Integral_le_one
theorem nnnorm_Integral_le_one : ‖integralCLM (α := α) (E := E) (μ := μ)‖₊ ≤ 1 :=
norm_Integral_le_one
theorem norm_integral_le (f : α →₁[μ] E) : ‖integral f‖ ≤ ‖f‖ :=
calc
‖integral f‖ = ‖integralCLM (E := E) f‖ := by simp only [integral]
_ ≤ ‖integralCLM (α := α) (E := E) (μ := μ)‖ * ‖f‖ := le_opNorm _ _
_ ≤ 1 * ‖f‖ := mul_le_mul_of_nonneg_right norm_Integral_le_one <| norm_nonneg _
_ = ‖f‖ := one_mul _
#align measure_theory.L1.norm_integral_le MeasureTheory.L1.norm_integral_le
theorem nnnorm_integral_le (f : α →₁[μ] E) : ‖integral f‖₊ ≤ ‖f‖₊ :=
norm_integral_le f
@[continuity]
theorem continuous_integral : Continuous fun f : α →₁[μ] E => integral f := by
simp only [integral]
exact L1.integralCLM.continuous
#align measure_theory.L1.continuous_integral MeasureTheory.L1.continuous_integral
section PosPart
theorem integral_eq_norm_posPart_sub (f : α →₁[μ] ℝ) :
integral f = ‖Lp.posPart f‖ - ‖Lp.negPart f‖ := by
-- Use `isClosed_property` and `isClosed_eq`
refine @isClosed_property _ _ _ ((↑) : (α →₁ₛ[μ] ℝ) → α →₁[μ] ℝ)
(fun f : α →₁[μ] ℝ => integral f = ‖Lp.posPart f‖ - ‖Lp.negPart f‖)
(simpleFunc.denseRange one_ne_top) (isClosed_eq ?_ ?_) ?_ f
· simp only [integral]
exact cont _
· refine Continuous.sub (continuous_norm.comp Lp.continuous_posPart)
(continuous_norm.comp Lp.continuous_negPart)
-- Show that the property holds for all simple functions in the `L¹` space.
· intro s
norm_cast
exact SimpleFunc.integral_eq_norm_posPart_sub _
#align measure_theory.L1.integral_eq_norm_pos_part_sub MeasureTheory.L1.integral_eq_norm_posPart_sub
end PosPart
end IntegrationInL1
end L1
/-!
## The Bochner integral on functions
Define the Bochner integral on functions generally to be the `L1` Bochner integral, for integrable
functions, and 0 otherwise; prove its basic properties.
-/
variable [NormedAddCommGroup E] [NormedSpace ℝ E] [hE : CompleteSpace E] [NontriviallyNormedField 𝕜]
[NormedSpace 𝕜 E] [SMulCommClass ℝ 𝕜 E] [NormedAddCommGroup F] [NormedSpace ℝ F] [CompleteSpace F]
{G : Type*} [NormedAddCommGroup G] [NormedSpace ℝ G]
section
open scoped Classical
/-- The Bochner integral -/
irreducible_def integral {_ : MeasurableSpace α} (μ : Measure α) (f : α → G) : G :=
if _ : CompleteSpace G then
if hf : Integrable f μ then L1.integral (hf.toL1 f) else 0
else 0
#align measure_theory.integral MeasureTheory.integral
end
/-! In the notation for integrals, an expression like `∫ x, g ‖x‖ ∂μ` will not be parsed correctly,
and needs parentheses. We do not set the binding power of `r` to `0`, because then
`∫ x, f x = 0` will be parsed incorrectly. -/
@[inherit_doc MeasureTheory.integral]
notation3 "∫ "(...)", "r:60:(scoped f => f)" ∂"μ:70 => integral μ r
@[inherit_doc MeasureTheory.integral]
notation3 "∫ "(...)", "r:60:(scoped f => integral volume f) => r
@[inherit_doc MeasureTheory.integral]
notation3 "∫ "(...)" in "s", "r:60:(scoped f => f)" ∂"μ:70 => integral (Measure.restrict μ s) r
@[inherit_doc MeasureTheory.integral]
notation3 "∫ "(...)" in "s", "r:60:(scoped f => integral (Measure.restrict volume s) f) => r
section Properties
open ContinuousLinearMap MeasureTheory.SimpleFunc
variable {f g : α → E} {m : MeasurableSpace α} {μ : Measure α}
theorem integral_eq (f : α → E) (hf : Integrable f μ) : ∫ a, f a ∂μ = L1.integral (hf.toL1 f) := by
simp [integral, hE, hf]
#align measure_theory.integral_eq MeasureTheory.integral_eq
theorem integral_eq_setToFun (f : α → E) :
∫ a, f a ∂μ = setToFun μ (weightedSMul μ) (dominatedFinMeasAdditive_weightedSMul μ) f := by
simp only [integral, hE, L1.integral]; rfl
#align measure_theory.integral_eq_set_to_fun MeasureTheory.integral_eq_setToFun
theorem L1.integral_eq_integral (f : α →₁[μ] E) : L1.integral f = ∫ a, f a ∂μ := by
simp only [integral, L1.integral, integral_eq_setToFun]
exact (L1.setToFun_eq_setToL1 (dominatedFinMeasAdditive_weightedSMul μ) f).symm
set_option linter.uppercaseLean3 false in
#align measure_theory.L1.integral_eq_integral MeasureTheory.L1.integral_eq_integral
theorem integral_undef {f : α → G} (h : ¬Integrable f μ) : ∫ a, f a ∂μ = 0 := by
by_cases hG : CompleteSpace G
· simp [integral, hG, h]
· simp [integral, hG]
#align measure_theory.integral_undef MeasureTheory.integral_undef
theorem Integrable.of_integral_ne_zero {f : α → G} (h : ∫ a, f a ∂μ ≠ 0) : Integrable f μ :=
Not.imp_symm integral_undef h
theorem integral_non_aestronglyMeasurable {f : α → G} (h : ¬AEStronglyMeasurable f μ) :
∫ a, f a ∂μ = 0 :=
integral_undef <| not_and_of_not_left _ h
#align measure_theory.integral_non_ae_strongly_measurable MeasureTheory.integral_non_aestronglyMeasurable
variable (α G)
@[simp]
theorem integral_zero : ∫ _ : α, (0 : G) ∂μ = 0 := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact setToFun_zero (dominatedFinMeasAdditive_weightedSMul μ)
· simp [integral, hG]
#align measure_theory.integral_zero MeasureTheory.integral_zero
@[simp]
theorem integral_zero' : integral μ (0 : α → G) = 0 :=
integral_zero α G
#align measure_theory.integral_zero' MeasureTheory.integral_zero'
variable {α G}
theorem integrable_of_integral_eq_one {f : α → ℝ} (h : ∫ x, f x ∂μ = 1) : Integrable f μ :=
.of_integral_ne_zero <| h ▸ one_ne_zero
#align measure_theory.integrable_of_integral_eq_one MeasureTheory.integrable_of_integral_eq_one
theorem integral_add {f g : α → G} (hf : Integrable f μ) (hg : Integrable g μ) :
∫ a, f a + g a ∂μ = ∫ a, f a ∂μ + ∫ a, g a ∂μ := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact setToFun_add (dominatedFinMeasAdditive_weightedSMul μ) hf hg
· simp [integral, hG]
#align measure_theory.integral_add MeasureTheory.integral_add
theorem integral_add' {f g : α → G} (hf : Integrable f μ) (hg : Integrable g μ) :
∫ a, (f + g) a ∂μ = ∫ a, f a ∂μ + ∫ a, g a ∂μ :=
integral_add hf hg
#align measure_theory.integral_add' MeasureTheory.integral_add'
theorem integral_finset_sum {ι} (s : Finset ι) {f : ι → α → G} (hf : ∀ i ∈ s, Integrable (f i) μ) :
∫ a, ∑ i ∈ s, f i a ∂μ = ∑ i ∈ s, ∫ a, f i a ∂μ := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact setToFun_finset_sum (dominatedFinMeasAdditive_weightedSMul _) s hf
· simp [integral, hG]
#align measure_theory.integral_finset_sum MeasureTheory.integral_finset_sum
@[integral_simps]
theorem integral_neg (f : α → G) : ∫ a, -f a ∂μ = -∫ a, f a ∂μ := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact setToFun_neg (dominatedFinMeasAdditive_weightedSMul μ) f
· simp [integral, hG]
#align measure_theory.integral_neg MeasureTheory.integral_neg
theorem integral_neg' (f : α → G) : ∫ a, (-f) a ∂μ = -∫ a, f a ∂μ :=
integral_neg f
#align measure_theory.integral_neg' MeasureTheory.integral_neg'
theorem integral_sub {f g : α → G} (hf : Integrable f μ) (hg : Integrable g μ) :
∫ a, f a - g a ∂μ = ∫ a, f a ∂μ - ∫ a, g a ∂μ := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact setToFun_sub (dominatedFinMeasAdditive_weightedSMul μ) hf hg
· simp [integral, hG]
#align measure_theory.integral_sub MeasureTheory.integral_sub
theorem integral_sub' {f g : α → G} (hf : Integrable f μ) (hg : Integrable g μ) :
∫ a, (f - g) a ∂μ = ∫ a, f a ∂μ - ∫ a, g a ∂μ :=
integral_sub hf hg
#align measure_theory.integral_sub' MeasureTheory.integral_sub'
@[integral_simps]
theorem integral_smul [NormedSpace 𝕜 G] [SMulCommClass ℝ 𝕜 G] (c : 𝕜) (f : α → G) :
∫ a, c • f a ∂μ = c • ∫ a, f a ∂μ := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact setToFun_smul (dominatedFinMeasAdditive_weightedSMul μ) weightedSMul_smul c f
· simp [integral, hG]
#align measure_theory.integral_smul MeasureTheory.integral_smul
theorem integral_mul_left {L : Type*} [RCLike L] (r : L) (f : α → L) :
∫ a, r * f a ∂μ = r * ∫ a, f a ∂μ :=
integral_smul r f
#align measure_theory.integral_mul_left MeasureTheory.integral_mul_left
theorem integral_mul_right {L : Type*} [RCLike L] (r : L) (f : α → L) :
∫ a, f a * r ∂μ = (∫ a, f a ∂μ) * r := by
simp only [mul_comm]; exact integral_mul_left r f
#align measure_theory.integral_mul_right MeasureTheory.integral_mul_right
theorem integral_div {L : Type*} [RCLike L] (r : L) (f : α → L) :
∫ a, f a / r ∂μ = (∫ a, f a ∂μ) / r := by
simpa only [← div_eq_mul_inv] using integral_mul_right r⁻¹ f
#align measure_theory.integral_div MeasureTheory.integral_div
theorem integral_congr_ae {f g : α → G} (h : f =ᵐ[μ] g) : ∫ a, f a ∂μ = ∫ a, g a ∂μ := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact setToFun_congr_ae (dominatedFinMeasAdditive_weightedSMul μ) h
· simp [integral, hG]
#align measure_theory.integral_congr_ae MeasureTheory.integral_congr_ae
-- Porting note: `nolint simpNF` added because simplify fails on left-hand side
@[simp, nolint simpNF]
theorem L1.integral_of_fun_eq_integral {f : α → G} (hf : Integrable f μ) :
∫ a, (hf.toL1 f) a ∂μ = ∫ a, f a ∂μ := by
by_cases hG : CompleteSpace G
· simp only [MeasureTheory.integral, hG, L1.integral]
exact setToFun_toL1 (dominatedFinMeasAdditive_weightedSMul μ) hf
· simp [MeasureTheory.integral, hG]
set_option linter.uppercaseLean3 false in
#align measure_theory.L1.integral_of_fun_eq_integral MeasureTheory.L1.integral_of_fun_eq_integral
@[continuity]
theorem continuous_integral : Continuous fun f : α →₁[μ] G => ∫ a, f a ∂μ := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact continuous_setToFun (dominatedFinMeasAdditive_weightedSMul μ)
· simp [integral, hG, continuous_const]
#align measure_theory.continuous_integral MeasureTheory.continuous_integral
theorem norm_integral_le_lintegral_norm (f : α → G) :
‖∫ a, f a ∂μ‖ ≤ ENNReal.toReal (∫⁻ a, ENNReal.ofReal ‖f a‖ ∂μ) := by
by_cases hG : CompleteSpace G
· by_cases hf : Integrable f μ
· rw [integral_eq f hf, ← Integrable.norm_toL1_eq_lintegral_norm f hf]
exact L1.norm_integral_le _
· rw [integral_undef hf, norm_zero]; exact toReal_nonneg
· simp [integral, hG]
#align measure_theory.norm_integral_le_lintegral_norm MeasureTheory.norm_integral_le_lintegral_norm
theorem ennnorm_integral_le_lintegral_ennnorm (f : α → G) :
(‖∫ a, f a ∂μ‖₊ : ℝ≥0∞) ≤ ∫⁻ a, ‖f a‖₊ ∂μ := by
simp_rw [← ofReal_norm_eq_coe_nnnorm]
apply ENNReal.ofReal_le_of_le_toReal
exact norm_integral_le_lintegral_norm f
#align measure_theory.ennnorm_integral_le_lintegral_ennnorm MeasureTheory.ennnorm_integral_le_lintegral_ennnorm
theorem integral_eq_zero_of_ae {f : α → G} (hf : f =ᵐ[μ] 0) : ∫ a, f a ∂μ = 0 := by
simp [integral_congr_ae hf, integral_zero]
#align measure_theory.integral_eq_zero_of_ae MeasureTheory.integral_eq_zero_of_ae
/-- If `f` has finite integral, then `∫ x in s, f x ∂μ` is absolutely continuous in `s`: it tends
to zero as `μ s` tends to zero. -/
theorem HasFiniteIntegral.tendsto_setIntegral_nhds_zero {ι} {f : α → G}
(hf : HasFiniteIntegral f μ) {l : Filter ι} {s : ι → Set α} (hs : Tendsto (μ ∘ s) l (𝓝 0)) :
Tendsto (fun i => ∫ x in s i, f x ∂μ) l (𝓝 0) := by
rw [tendsto_zero_iff_norm_tendsto_zero]
simp_rw [← coe_nnnorm, ← NNReal.coe_zero, NNReal.tendsto_coe, ← ENNReal.tendsto_coe,
ENNReal.coe_zero]
exact tendsto_of_tendsto_of_tendsto_of_le_of_le tendsto_const_nhds
(tendsto_set_lintegral_zero (ne_of_lt hf) hs) (fun i => zero_le _)
fun i => ennnorm_integral_le_lintegral_ennnorm _
#align measure_theory.has_finite_integral.tendsto_set_integral_nhds_zero MeasureTheory.HasFiniteIntegral.tendsto_setIntegral_nhds_zero
@[deprecated (since := "2024-04-17")]
alias HasFiniteIntegral.tendsto_set_integral_nhds_zero :=
HasFiniteIntegral.tendsto_setIntegral_nhds_zero
/-- If `f` is integrable, then `∫ x in s, f x ∂μ` is absolutely continuous in `s`: it tends
to zero as `μ s` tends to zero. -/
theorem Integrable.tendsto_setIntegral_nhds_zero {ι} {f : α → G} (hf : Integrable f μ)
{l : Filter ι} {s : ι → Set α} (hs : Tendsto (μ ∘ s) l (𝓝 0)) :
Tendsto (fun i => ∫ x in s i, f x ∂μ) l (𝓝 0) :=
hf.2.tendsto_setIntegral_nhds_zero hs
#align measure_theory.integrable.tendsto_set_integral_nhds_zero MeasureTheory.Integrable.tendsto_setIntegral_nhds_zero
@[deprecated (since := "2024-04-17")]
alias Integrable.tendsto_set_integral_nhds_zero :=
Integrable.tendsto_setIntegral_nhds_zero
/-- If `F i → f` in `L1`, then `∫ x, F i x ∂μ → ∫ x, f x ∂μ`. -/
theorem tendsto_integral_of_L1 {ι} (f : α → G) (hfi : Integrable f μ) {F : ι → α → G} {l : Filter ι}
(hFi : ∀ᶠ i in l, Integrable (F i) μ)
(hF : Tendsto (fun i => ∫⁻ x, ‖F i x - f x‖₊ ∂μ) l (𝓝 0)) :
Tendsto (fun i => ∫ x, F i x ∂μ) l (𝓝 <| ∫ x, f x ∂μ) := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact tendsto_setToFun_of_L1 (dominatedFinMeasAdditive_weightedSMul μ) f hfi hFi hF
· simp [integral, hG, tendsto_const_nhds]
set_option linter.uppercaseLean3 false in
#align measure_theory.tendsto_integral_of_L1 MeasureTheory.tendsto_integral_of_L1
/-- If `F i → f` in `L1`, then `∫ x, F i x ∂μ → ∫ x, f x ∂μ`. -/
lemma tendsto_integral_of_L1' {ι} (f : α → G) (hfi : Integrable f μ) {F : ι → α → G} {l : Filter ι}
(hFi : ∀ᶠ i in l, Integrable (F i) μ) (hF : Tendsto (fun i ↦ snorm (F i - f) 1 μ) l (𝓝 0)) :
Tendsto (fun i ↦ ∫ x, F i x ∂μ) l (𝓝 (∫ x, f x ∂μ)) := by
refine tendsto_integral_of_L1 f hfi hFi ?_
simp_rw [snorm_one_eq_lintegral_nnnorm, Pi.sub_apply] at hF
exact hF
/-- If `F i → f` in `L1`, then `∫ x in s, F i x ∂μ → ∫ x in s, f x ∂μ`. -/
lemma tendsto_setIntegral_of_L1 {ι} (f : α → G) (hfi : Integrable f μ) {F : ι → α → G}
{l : Filter ι}
(hFi : ∀ᶠ i in l, Integrable (F i) μ) (hF : Tendsto (fun i ↦ ∫⁻ x, ‖F i x - f x‖₊ ∂μ) l (𝓝 0))
(s : Set α) :
Tendsto (fun i ↦ ∫ x in s, F i x ∂μ) l (𝓝 (∫ x in s, f x ∂μ)) := by
refine tendsto_integral_of_L1 f hfi.restrict ?_ ?_
· filter_upwards [hFi] with i hi using hi.restrict
· simp_rw [← snorm_one_eq_lintegral_nnnorm] at hF ⊢
exact tendsto_of_tendsto_of_tendsto_of_le_of_le tendsto_const_nhds hF (fun _ ↦ zero_le')
(fun _ ↦ snorm_mono_measure _ Measure.restrict_le_self)
@[deprecated (since := "2024-04-17")]
alias tendsto_set_integral_of_L1 := tendsto_setIntegral_of_L1
/-- If `F i → f` in `L1`, then `∫ x in s, F i x ∂μ → ∫ x in s, f x ∂μ`. -/
lemma tendsto_setIntegral_of_L1' {ι} (f : α → G) (hfi : Integrable f μ) {F : ι → α → G}
{l : Filter ι}
(hFi : ∀ᶠ i in l, Integrable (F i) μ) (hF : Tendsto (fun i ↦ snorm (F i - f) 1 μ) l (𝓝 0))
(s : Set α) :
Tendsto (fun i ↦ ∫ x in s, F i x ∂μ) l (𝓝 (∫ x in s, f x ∂μ)) := by
refine tendsto_setIntegral_of_L1 f hfi hFi ?_ s
simp_rw [snorm_one_eq_lintegral_nnnorm, Pi.sub_apply] at hF
exact hF
@[deprecated (since := "2024-04-17")]
alias tendsto_set_integral_of_L1' := tendsto_setIntegral_of_L1'
variable {X : Type*} [TopologicalSpace X] [FirstCountableTopology X]
theorem continuousWithinAt_of_dominated {F : X → α → G} {x₀ : X} {bound : α → ℝ} {s : Set X}
(hF_meas : ∀ᶠ x in 𝓝[s] x₀, AEStronglyMeasurable (F x) μ)
(h_bound : ∀ᶠ x in 𝓝[s] x₀, ∀ᵐ a ∂μ, ‖F x a‖ ≤ bound a) (bound_integrable : Integrable bound μ)
(h_cont : ∀ᵐ a ∂μ, ContinuousWithinAt (fun x => F x a) s x₀) :
ContinuousWithinAt (fun x => ∫ a, F x a ∂μ) s x₀ := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact continuousWithinAt_setToFun_of_dominated (dominatedFinMeasAdditive_weightedSMul μ)
hF_meas h_bound bound_integrable h_cont
· simp [integral, hG, continuousWithinAt_const]
#align measure_theory.continuous_within_at_of_dominated MeasureTheory.continuousWithinAt_of_dominated
theorem continuousAt_of_dominated {F : X → α → G} {x₀ : X} {bound : α → ℝ}
(hF_meas : ∀ᶠ x in 𝓝 x₀, AEStronglyMeasurable (F x) μ)
(h_bound : ∀ᶠ x in 𝓝 x₀, ∀ᵐ a ∂μ, ‖F x a‖ ≤ bound a) (bound_integrable : Integrable bound μ)
(h_cont : ∀ᵐ a ∂μ, ContinuousAt (fun x => F x a) x₀) :
ContinuousAt (fun x => ∫ a, F x a ∂μ) x₀ := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact continuousAt_setToFun_of_dominated (dominatedFinMeasAdditive_weightedSMul μ)
hF_meas h_bound bound_integrable h_cont
· simp [integral, hG, continuousAt_const]
#align measure_theory.continuous_at_of_dominated MeasureTheory.continuousAt_of_dominated
theorem continuousOn_of_dominated {F : X → α → G} {bound : α → ℝ} {s : Set X}
(hF_meas : ∀ x ∈ s, AEStronglyMeasurable (F x) μ)
(h_bound : ∀ x ∈ s, ∀ᵐ a ∂μ, ‖F x a‖ ≤ bound a) (bound_integrable : Integrable bound μ)
(h_cont : ∀ᵐ a ∂μ, ContinuousOn (fun x => F x a) s) :
ContinuousOn (fun x => ∫ a, F x a ∂μ) s := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact continuousOn_setToFun_of_dominated (dominatedFinMeasAdditive_weightedSMul μ)
hF_meas h_bound bound_integrable h_cont
· simp [integral, hG, continuousOn_const]
#align measure_theory.continuous_on_of_dominated MeasureTheory.continuousOn_of_dominated
theorem continuous_of_dominated {F : X → α → G} {bound : α → ℝ}
(hF_meas : ∀ x, AEStronglyMeasurable (F x) μ) (h_bound : ∀ x, ∀ᵐ a ∂μ, ‖F x a‖ ≤ bound a)
(bound_integrable : Integrable bound μ) (h_cont : ∀ᵐ a ∂μ, Continuous fun x => F x a) :
Continuous fun x => ∫ a, F x a ∂μ := by
by_cases hG : CompleteSpace G
· simp only [integral, hG, L1.integral]
exact continuous_setToFun_of_dominated (dominatedFinMeasAdditive_weightedSMul μ)
hF_meas h_bound bound_integrable h_cont
· simp [integral, hG, continuous_const]
#align measure_theory.continuous_of_dominated MeasureTheory.continuous_of_dominated
/-- The Bochner integral of a real-valued function `f : α → ℝ` is the difference between the
integral of the positive part of `f` and the integral of the negative part of `f`. -/
theorem integral_eq_lintegral_pos_part_sub_lintegral_neg_part {f : α → ℝ} (hf : Integrable f μ) :
∫ a, f a ∂μ =
ENNReal.toReal (∫⁻ a, .ofReal (f a) ∂μ) - ENNReal.toReal (∫⁻ a, .ofReal (-f a) ∂μ) := by
let f₁ := hf.toL1 f
-- Go to the `L¹` space
have eq₁ : ENNReal.toReal (∫⁻ a, ENNReal.ofReal (f a) ∂μ) = ‖Lp.posPart f₁‖ := by
rw [L1.norm_def]
congr 1
apply lintegral_congr_ae
filter_upwards [Lp.coeFn_posPart f₁, hf.coeFn_toL1] with _ h₁ h₂
rw [h₁, h₂, ENNReal.ofReal]
congr 1
apply NNReal.eq
rw [Real.nnnorm_of_nonneg (le_max_right _ _)]
rw [Real.coe_toNNReal', NNReal.coe_mk]
-- Go to the `L¹` space
have eq₂ : ENNReal.toReal (∫⁻ a, ENNReal.ofReal (-f a) ∂μ) = ‖Lp.negPart f₁‖ := by
rw [L1.norm_def]
congr 1
apply lintegral_congr_ae
filter_upwards [Lp.coeFn_negPart f₁, hf.coeFn_toL1] with _ h₁ h₂
rw [h₁, h₂, ENNReal.ofReal]
congr 1
apply NNReal.eq
simp only [Real.coe_toNNReal', coe_nnnorm, nnnorm_neg]
rw [Real.norm_of_nonpos (min_le_right _ _), ← max_neg_neg, neg_zero]
rw [eq₁, eq₂, integral, dif_pos, dif_pos]
exact L1.integral_eq_norm_posPart_sub _
#align measure_theory.integral_eq_lintegral_pos_part_sub_lintegral_neg_part MeasureTheory.integral_eq_lintegral_pos_part_sub_lintegral_neg_part
theorem integral_eq_lintegral_of_nonneg_ae {f : α → ℝ} (hf : 0 ≤ᵐ[μ] f)
(hfm : AEStronglyMeasurable f μ) :
∫ a, f a ∂μ = ENNReal.toReal (∫⁻ a, ENNReal.ofReal (f a) ∂μ) := by
by_cases hfi : Integrable f μ
· rw [integral_eq_lintegral_pos_part_sub_lintegral_neg_part hfi]
have h_min : ∫⁻ a, ENNReal.ofReal (-f a) ∂μ = 0 := by
rw [lintegral_eq_zero_iff']
· refine hf.mono ?_
simp only [Pi.zero_apply]
intro a h
simp only [h, neg_nonpos, ofReal_eq_zero]
· exact measurable_ofReal.comp_aemeasurable hfm.aemeasurable.neg
rw [h_min, zero_toReal, _root_.sub_zero]
· rw [integral_undef hfi]
simp_rw [Integrable, hfm, hasFiniteIntegral_iff_norm, lt_top_iff_ne_top, Ne, true_and_iff,
Classical.not_not] at hfi
have : ∫⁻ a : α, ENNReal.ofReal (f a) ∂μ = ∫⁻ a, ENNReal.ofReal ‖f a‖ ∂μ := by
refine lintegral_congr_ae (hf.mono fun a h => ?_)
dsimp only
rw [Real.norm_eq_abs, abs_of_nonneg h]
rw [this, hfi]; rfl
#align measure_theory.integral_eq_lintegral_of_nonneg_ae MeasureTheory.integral_eq_lintegral_of_nonneg_ae
theorem integral_norm_eq_lintegral_nnnorm {P : Type*} [NormedAddCommGroup P] {f : α → P}
(hf : AEStronglyMeasurable f μ) : ∫ x, ‖f x‖ ∂μ = ENNReal.toReal (∫⁻ x, ‖f x‖₊ ∂μ) := by
rw [integral_eq_lintegral_of_nonneg_ae _ hf.norm]
· simp_rw [ofReal_norm_eq_coe_nnnorm]
· filter_upwards; simp_rw [Pi.zero_apply, norm_nonneg, imp_true_iff]
#align measure_theory.integral_norm_eq_lintegral_nnnorm MeasureTheory.integral_norm_eq_lintegral_nnnorm
theorem ofReal_integral_norm_eq_lintegral_nnnorm {P : Type*} [NormedAddCommGroup P] {f : α → P}
(hf : Integrable f μ) : ENNReal.ofReal (∫ x, ‖f x‖ ∂μ) = ∫⁻ x, ‖f x‖₊ ∂μ := by
rw [integral_norm_eq_lintegral_nnnorm hf.aestronglyMeasurable,
ENNReal.ofReal_toReal (lt_top_iff_ne_top.mp hf.2)]
#align measure_theory.of_real_integral_norm_eq_lintegral_nnnorm MeasureTheory.ofReal_integral_norm_eq_lintegral_nnnorm
theorem integral_eq_integral_pos_part_sub_integral_neg_part {f : α → ℝ} (hf : Integrable f μ) :
∫ a, f a ∂μ = ∫ a, (Real.toNNReal (f a) : ℝ) ∂μ - ∫ a, (Real.toNNReal (-f a) : ℝ) ∂μ := by
rw [← integral_sub hf.real_toNNReal]
· simp
· exact hf.neg.real_toNNReal
#align measure_theory.integral_eq_integral_pos_part_sub_integral_neg_part MeasureTheory.integral_eq_integral_pos_part_sub_integral_neg_part
theorem integral_nonneg_of_ae {f : α → ℝ} (hf : 0 ≤ᵐ[μ] f) : 0 ≤ ∫ a, f a ∂μ := by
have A : CompleteSpace ℝ := by infer_instance
simp only [integral_def, A, L1.integral_def, dite_true, ge_iff_le]
exact setToFun_nonneg (dominatedFinMeasAdditive_weightedSMul μ)
(fun s _ _ => weightedSMul_nonneg s) hf
#align measure_theory.integral_nonneg_of_ae MeasureTheory.integral_nonneg_of_ae
theorem lintegral_coe_eq_integral (f : α → ℝ≥0) (hfi : Integrable (fun x => (f x : ℝ)) μ) :
∫⁻ a, f a ∂μ = ENNReal.ofReal (∫ a, f a ∂μ) := by
simp_rw [integral_eq_lintegral_of_nonneg_ae (eventually_of_forall fun x => (f x).coe_nonneg)
hfi.aestronglyMeasurable, ← ENNReal.coe_nnreal_eq]
rw [ENNReal.ofReal_toReal]
rw [← lt_top_iff_ne_top]
convert hfi.hasFiniteIntegral
-- Porting note: `convert` no longer unfolds `HasFiniteIntegral`
simp_rw [HasFiniteIntegral, NNReal.nnnorm_eq]
#align measure_theory.lintegral_coe_eq_integral MeasureTheory.lintegral_coe_eq_integral
theorem ofReal_integral_eq_lintegral_ofReal {f : α → ℝ} (hfi : Integrable f μ) (f_nn : 0 ≤ᵐ[μ] f) :
ENNReal.ofReal (∫ x, f x ∂μ) = ∫⁻ x, ENNReal.ofReal (f x) ∂μ := by
have : f =ᵐ[μ] (‖f ·‖) := f_nn.mono fun _x hx ↦ (abs_of_nonneg hx).symm
simp_rw [integral_congr_ae this, ofReal_integral_norm_eq_lintegral_nnnorm hfi,
← ofReal_norm_eq_coe_nnnorm]
exact lintegral_congr_ae (this.symm.fun_comp ENNReal.ofReal)
#align measure_theory.of_real_integral_eq_lintegral_of_real MeasureTheory.ofReal_integral_eq_lintegral_ofReal
| Mathlib/MeasureTheory/Integral/Bochner.lean | 1,212 | 1,216 | theorem integral_toReal {f : α → ℝ≥0∞} (hfm : AEMeasurable f μ) (hf : ∀ᵐ x ∂μ, f x < ∞) :
∫ a, (f a).toReal ∂μ = (∫⁻ a, f a ∂μ).toReal := by |
rw [integral_eq_lintegral_of_nonneg_ae _ hfm.ennreal_toReal.aestronglyMeasurable,
lintegral_congr_ae (ofReal_toReal_ae_eq hf)]
exact eventually_of_forall fun x => ENNReal.toReal_nonneg
|
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Julian Kuelshammer
-/
import Mathlib.Algebra.CharP.Defs
import Mathlib.Algebra.GroupPower.IterateHom
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Data.Int.ModEq
import Mathlib.Data.Set.Pointwise.Basic
import Mathlib.Dynamics.PeriodicPts
import Mathlib.GroupTheory.Index
import Mathlib.Order.Interval.Finset.Nat
import Mathlib.Order.Interval.Set.Infinite
#align_import group_theory.order_of_element from "leanprover-community/mathlib"@"d07245fd37786daa997af4f1a73a49fa3b748408"
/-!
# Order of an element
This file defines the order of an element of a finite group. For a finite group `G` the order of
`x ∈ G` is the minimal `n ≥ 1` such that `x ^ n = 1`.
## Main definitions
* `IsOfFinOrder` is a predicate on an element `x` of a monoid `G` saying that `x` is of finite
order.
* `IsOfFinAddOrder` is the additive analogue of `IsOfFinOrder`.
* `orderOf x` defines the order of an element `x` of a monoid `G`, by convention its value is `0`
if `x` has infinite order.
* `addOrderOf` is the additive analogue of `orderOf`.
## Tags
order of an element
-/
open Function Fintype Nat Pointwise Subgroup Submonoid
variable {G H A α β : Type*}
section Monoid
variable [Monoid G] {a b x y : G} {n m : ℕ}
section IsOfFinOrder
-- Porting note(#12129): additional beta reduction needed
@[to_additive]
theorem isPeriodicPt_mul_iff_pow_eq_one (x : G) : IsPeriodicPt (x * ·) n 1 ↔ x ^ n = 1 := by
rw [IsPeriodicPt, IsFixedPt, mul_left_iterate]; beta_reduce; rw [mul_one]
#align is_periodic_pt_mul_iff_pow_eq_one isPeriodicPt_mul_iff_pow_eq_one
#align is_periodic_pt_add_iff_nsmul_eq_zero isPeriodicPt_add_iff_nsmul_eq_zero
/-- `IsOfFinOrder` is a predicate on an element `x` of a monoid to be of finite order, i.e. there
exists `n ≥ 1` such that `x ^ n = 1`. -/
@[to_additive "`IsOfFinAddOrder` is a predicate on an element `a` of an
additive monoid to be of finite order, i.e. there exists `n ≥ 1` such that `n • a = 0`."]
def IsOfFinOrder (x : G) : Prop :=
(1 : G) ∈ periodicPts (x * ·)
#align is_of_fin_order IsOfFinOrder
#align is_of_fin_add_order IsOfFinAddOrder
theorem isOfFinAddOrder_ofMul_iff : IsOfFinAddOrder (Additive.ofMul x) ↔ IsOfFinOrder x :=
Iff.rfl
#align is_of_fin_add_order_of_mul_iff isOfFinAddOrder_ofMul_iff
theorem isOfFinOrder_ofAdd_iff {α : Type*} [AddMonoid α] {x : α} :
IsOfFinOrder (Multiplicative.ofAdd x) ↔ IsOfFinAddOrder x := Iff.rfl
#align is_of_fin_order_of_add_iff isOfFinOrder_ofAdd_iff
@[to_additive]
theorem isOfFinOrder_iff_pow_eq_one : IsOfFinOrder x ↔ ∃ n, 0 < n ∧ x ^ n = 1 := by
simp [IsOfFinOrder, mem_periodicPts, isPeriodicPt_mul_iff_pow_eq_one]
#align is_of_fin_order_iff_pow_eq_one isOfFinOrder_iff_pow_eq_one
#align is_of_fin_add_order_iff_nsmul_eq_zero isOfFinAddOrder_iff_nsmul_eq_zero
@[to_additive] alias ⟨IsOfFinOrder.exists_pow_eq_one, _⟩ := isOfFinOrder_iff_pow_eq_one
@[to_additive]
lemma isOfFinOrder_iff_zpow_eq_one {G} [Group G] {x : G} :
IsOfFinOrder x ↔ ∃ (n : ℤ), n ≠ 0 ∧ x ^ n = 1 := by
rw [isOfFinOrder_iff_pow_eq_one]
refine ⟨fun ⟨n, hn, hn'⟩ ↦ ⟨n, Int.natCast_ne_zero_iff_pos.mpr hn, zpow_natCast x n ▸ hn'⟩,
fun ⟨n, hn, hn'⟩ ↦ ⟨n.natAbs, Int.natAbs_pos.mpr hn, ?_⟩⟩
cases' (Int.natAbs_eq_iff (a := n)).mp rfl with h h
· rwa [h, zpow_natCast] at hn'
· rwa [h, zpow_neg, inv_eq_one, zpow_natCast] at hn'
/-- See also `injective_pow_iff_not_isOfFinOrder`. -/
@[to_additive "See also `injective_nsmul_iff_not_isOfFinAddOrder`."]
theorem not_isOfFinOrder_of_injective_pow {x : G} (h : Injective fun n : ℕ => x ^ n) :
¬IsOfFinOrder x := by
simp_rw [isOfFinOrder_iff_pow_eq_one, not_exists, not_and]
intro n hn_pos hnx
rw [← pow_zero x] at hnx
rw [h hnx] at hn_pos
exact irrefl 0 hn_pos
#align not_is_of_fin_order_of_injective_pow not_isOfFinOrder_of_injective_pow
#align not_is_of_fin_add_order_of_injective_nsmul not_isOfFinAddOrder_of_injective_nsmul
lemma IsOfFinOrder.pow {n : ℕ} : IsOfFinOrder a → IsOfFinOrder (a ^ n) := by
simp_rw [isOfFinOrder_iff_pow_eq_one]
rintro ⟨m, hm, ha⟩
exact ⟨m, hm, by simp [pow_right_comm _ n, ha]⟩
/-- Elements of finite order are of finite order in submonoids. -/
@[to_additive "Elements of finite order are of finite order in submonoids."]
theorem Submonoid.isOfFinOrder_coe {H : Submonoid G} {x : H} :
IsOfFinOrder (x : G) ↔ IsOfFinOrder x := by
rw [isOfFinOrder_iff_pow_eq_one, isOfFinOrder_iff_pow_eq_one]
norm_cast
#align is_of_fin_order_iff_coe Submonoid.isOfFinOrder_coe
#align is_of_fin_add_order_iff_coe AddSubmonoid.isOfFinAddOrder_coe
/-- The image of an element of finite order has finite order. -/
@[to_additive "The image of an element of finite additive order has finite additive order."]
theorem MonoidHom.isOfFinOrder [Monoid H] (f : G →* H) {x : G} (h : IsOfFinOrder x) :
IsOfFinOrder <| f x :=
isOfFinOrder_iff_pow_eq_one.mpr <| by
obtain ⟨n, npos, hn⟩ := h.exists_pow_eq_one
exact ⟨n, npos, by rw [← f.map_pow, hn, f.map_one]⟩
#align monoid_hom.is_of_fin_order MonoidHom.isOfFinOrder
#align add_monoid_hom.is_of_fin_order AddMonoidHom.isOfFinAddOrder
/-- If a direct product has finite order then so does each component. -/
@[to_additive "If a direct product has finite additive order then so does each component."]
theorem IsOfFinOrder.apply {η : Type*} {Gs : η → Type*} [∀ i, Monoid (Gs i)] {x : ∀ i, Gs i}
(h : IsOfFinOrder x) : ∀ i, IsOfFinOrder (x i) := by
obtain ⟨n, npos, hn⟩ := h.exists_pow_eq_one
exact fun _ => isOfFinOrder_iff_pow_eq_one.mpr ⟨n, npos, (congr_fun hn.symm _).symm⟩
#align is_of_fin_order.apply IsOfFinOrder.apply
#align is_of_fin_add_order.apply IsOfFinAddOrder.apply
/-- 1 is of finite order in any monoid. -/
@[to_additive "0 is of finite order in any additive monoid."]
theorem isOfFinOrder_one : IsOfFinOrder (1 : G) :=
isOfFinOrder_iff_pow_eq_one.mpr ⟨1, Nat.one_pos, one_pow 1⟩
#align is_of_fin_order_one isOfFinOrder_one
#align is_of_fin_order_zero isOfFinAddOrder_zero
/-- The submonoid generated by an element is a group if that element has finite order. -/
@[to_additive "The additive submonoid generated by an element is
an additive group if that element has finite order."]
noncomputable abbrev IsOfFinOrder.groupPowers (hx : IsOfFinOrder x) :
Group (Submonoid.powers x) := by
obtain ⟨hpos, hx⟩ := hx.exists_pow_eq_one.choose_spec
exact Submonoid.groupPowers hpos hx
end IsOfFinOrder
/-- `orderOf x` is the order of the element `x`, i.e. the `n ≥ 1`, s.t. `x ^ n = 1` if it exists.
Otherwise, i.e. if `x` is of infinite order, then `orderOf x` is `0` by convention. -/
@[to_additive
"`addOrderOf a` is the order of the element `a`, i.e. the `n ≥ 1`, s.t. `n • a = 0` if it
exists. Otherwise, i.e. if `a` is of infinite order, then `addOrderOf a` is `0` by convention."]
noncomputable def orderOf (x : G) : ℕ :=
minimalPeriod (x * ·) 1
#align order_of orderOf
#align add_order_of addOrderOf
@[simp]
theorem addOrderOf_ofMul_eq_orderOf (x : G) : addOrderOf (Additive.ofMul x) = orderOf x :=
rfl
#align add_order_of_of_mul_eq_order_of addOrderOf_ofMul_eq_orderOf
@[simp]
lemma orderOf_ofAdd_eq_addOrderOf {α : Type*} [AddMonoid α] (a : α) :
orderOf (Multiplicative.ofAdd a) = addOrderOf a := rfl
#align order_of_of_add_eq_add_order_of orderOf_ofAdd_eq_addOrderOf
@[to_additive]
protected lemma IsOfFinOrder.orderOf_pos (h : IsOfFinOrder x) : 0 < orderOf x :=
minimalPeriod_pos_of_mem_periodicPts h
#align order_of_pos' IsOfFinOrder.orderOf_pos
#align add_order_of_pos' IsOfFinAddOrder.addOrderOf_pos
@[to_additive addOrderOf_nsmul_eq_zero]
theorem pow_orderOf_eq_one (x : G) : x ^ orderOf x = 1 := by
convert Eq.trans _ (isPeriodicPt_minimalPeriod (x * ·) 1)
-- Porting note(#12129): additional beta reduction needed in the middle of the rewrite
rw [orderOf, mul_left_iterate]; beta_reduce; rw [mul_one]
#align pow_order_of_eq_one pow_orderOf_eq_one
#align add_order_of_nsmul_eq_zero addOrderOf_nsmul_eq_zero
@[to_additive]
theorem orderOf_eq_zero (h : ¬IsOfFinOrder x) : orderOf x = 0 := by
rwa [orderOf, minimalPeriod, dif_neg]
#align order_of_eq_zero orderOf_eq_zero
#align add_order_of_eq_zero addOrderOf_eq_zero
@[to_additive]
theorem orderOf_eq_zero_iff : orderOf x = 0 ↔ ¬IsOfFinOrder x :=
⟨fun h H ↦ H.orderOf_pos.ne' h, orderOf_eq_zero⟩
#align order_of_eq_zero_iff orderOf_eq_zero_iff
#align add_order_of_eq_zero_iff addOrderOf_eq_zero_iff
@[to_additive]
theorem orderOf_eq_zero_iff' : orderOf x = 0 ↔ ∀ n : ℕ, 0 < n → x ^ n ≠ 1 := by
simp_rw [orderOf_eq_zero_iff, isOfFinOrder_iff_pow_eq_one, not_exists, not_and]
#align order_of_eq_zero_iff' orderOf_eq_zero_iff'
#align add_order_of_eq_zero_iff' addOrderOf_eq_zero_iff'
@[to_additive]
theorem orderOf_eq_iff {n} (h : 0 < n) :
orderOf x = n ↔ x ^ n = 1 ∧ ∀ m, m < n → 0 < m → x ^ m ≠ 1 := by
simp_rw [Ne, ← isPeriodicPt_mul_iff_pow_eq_one, orderOf, minimalPeriod]
split_ifs with h1
· classical
rw [find_eq_iff]
simp only [h, true_and]
push_neg
rfl
· rw [iff_false_left h.ne]
rintro ⟨h', -⟩
exact h1 ⟨n, h, h'⟩
#align order_of_eq_iff orderOf_eq_iff
#align add_order_of_eq_iff addOrderOf_eq_iff
/-- A group element has finite order iff its order is positive. -/
@[to_additive
"A group element has finite additive order iff its order is positive."]
theorem orderOf_pos_iff : 0 < orderOf x ↔ IsOfFinOrder x := by
rw [iff_not_comm.mp orderOf_eq_zero_iff, pos_iff_ne_zero]
#align order_of_pos_iff orderOf_pos_iff
#align add_order_of_pos_iff addOrderOf_pos_iff
@[to_additive]
theorem IsOfFinOrder.mono [Monoid β] {y : β} (hx : IsOfFinOrder x) (h : orderOf y ∣ orderOf x) :
IsOfFinOrder y := by rw [← orderOf_pos_iff] at hx ⊢; exact Nat.pos_of_dvd_of_pos h hx
#align is_of_fin_order.mono IsOfFinOrder.mono
#align is_of_fin_add_order.mono IsOfFinAddOrder.mono
@[to_additive]
theorem pow_ne_one_of_lt_orderOf' (n0 : n ≠ 0) (h : n < orderOf x) : x ^ n ≠ 1 := fun j =>
not_isPeriodicPt_of_pos_of_lt_minimalPeriod n0 h ((isPeriodicPt_mul_iff_pow_eq_one x).mpr j)
#align pow_ne_one_of_lt_order_of' pow_ne_one_of_lt_orderOf'
#align nsmul_ne_zero_of_lt_add_order_of' nsmul_ne_zero_of_lt_addOrderOf'
@[to_additive]
theorem orderOf_le_of_pow_eq_one (hn : 0 < n) (h : x ^ n = 1) : orderOf x ≤ n :=
IsPeriodicPt.minimalPeriod_le hn (by rwa [isPeriodicPt_mul_iff_pow_eq_one])
#align order_of_le_of_pow_eq_one orderOf_le_of_pow_eq_one
#align add_order_of_le_of_nsmul_eq_zero addOrderOf_le_of_nsmul_eq_zero
@[to_additive (attr := simp)]
theorem orderOf_one : orderOf (1 : G) = 1 := by
rw [orderOf, ← minimalPeriod_id (x := (1:G)), ← one_mul_eq_id]
#align order_of_one orderOf_one
#align order_of_zero addOrderOf_zero
@[to_additive (attr := simp) AddMonoid.addOrderOf_eq_one_iff]
theorem orderOf_eq_one_iff : orderOf x = 1 ↔ x = 1 := by
rw [orderOf, minimalPeriod_eq_one_iff_isFixedPt, IsFixedPt, mul_one]
#align order_of_eq_one_iff orderOf_eq_one_iff
#align add_monoid.order_of_eq_one_iff AddMonoid.addOrderOf_eq_one_iff
@[to_additive (attr := simp) mod_addOrderOf_nsmul]
lemma pow_mod_orderOf (x : G) (n : ℕ) : x ^ (n % orderOf x) = x ^ n :=
calc
x ^ (n % orderOf x) = x ^ (n % orderOf x + orderOf x * (n / orderOf x)) := by
simp [pow_add, pow_mul, pow_orderOf_eq_one]
_ = x ^ n := by rw [Nat.mod_add_div]
#align pow_eq_mod_order_of pow_mod_orderOf
#align nsmul_eq_mod_add_order_of mod_addOrderOf_nsmul
@[to_additive]
theorem orderOf_dvd_of_pow_eq_one (h : x ^ n = 1) : orderOf x ∣ n :=
IsPeriodicPt.minimalPeriod_dvd ((isPeriodicPt_mul_iff_pow_eq_one _).mpr h)
#align order_of_dvd_of_pow_eq_one orderOf_dvd_of_pow_eq_one
#align add_order_of_dvd_of_nsmul_eq_zero addOrderOf_dvd_of_nsmul_eq_zero
@[to_additive]
theorem orderOf_dvd_iff_pow_eq_one {n : ℕ} : orderOf x ∣ n ↔ x ^ n = 1 :=
⟨fun h => by rw [← pow_mod_orderOf, Nat.mod_eq_zero_of_dvd h, _root_.pow_zero],
orderOf_dvd_of_pow_eq_one⟩
#align order_of_dvd_iff_pow_eq_one orderOf_dvd_iff_pow_eq_one
#align add_order_of_dvd_iff_nsmul_eq_zero addOrderOf_dvd_iff_nsmul_eq_zero
@[to_additive addOrderOf_smul_dvd]
theorem orderOf_pow_dvd (n : ℕ) : orderOf (x ^ n) ∣ orderOf x := by
rw [orderOf_dvd_iff_pow_eq_one, pow_right_comm, pow_orderOf_eq_one, one_pow]
#align order_of_pow_dvd orderOf_pow_dvd
#align add_order_of_smul_dvd addOrderOf_smul_dvd
@[to_additive]
lemma pow_injOn_Iio_orderOf : (Set.Iio <| orderOf x).InjOn (x ^ ·) := by
simpa only [mul_left_iterate, mul_one]
using iterate_injOn_Iio_minimalPeriod (f := (x * ·)) (x := 1)
#align pow_injective_of_lt_order_of pow_injOn_Iio_orderOf
#align nsmul_injective_of_lt_add_order_of nsmul_injOn_Iio_addOrderOf
@[to_additive]
protected lemma IsOfFinOrder.mem_powers_iff_mem_range_orderOf [DecidableEq G]
(hx : IsOfFinOrder x) :
y ∈ Submonoid.powers x ↔ y ∈ (Finset.range (orderOf x)).image (x ^ ·) :=
Finset.mem_range_iff_mem_finset_range_of_mod_eq' hx.orderOf_pos <| pow_mod_orderOf _
#align mem_powers_iff_mem_range_order_of' IsOfFinOrder.mem_powers_iff_mem_range_orderOf
#align mem_multiples_iff_mem_range_add_order_of' IsOfFinAddOrder.mem_multiples_iff_mem_range_addOrderOf
@[to_additive]
protected lemma IsOfFinOrder.powers_eq_image_range_orderOf [DecidableEq G] (hx : IsOfFinOrder x) :
(Submonoid.powers x : Set G) = (Finset.range (orderOf x)).image (x ^ ·) :=
Set.ext fun _ ↦ hx.mem_powers_iff_mem_range_orderOf
@[deprecated (since := "2024-02-21")]
alias IsOfFinAddOrder.powers_eq_image_range_orderOf :=
IsOfFinAddOrder.multiples_eq_image_range_addOrderOf
@[to_additive]
theorem pow_eq_one_iff_modEq : x ^ n = 1 ↔ n ≡ 0 [MOD orderOf x] := by
rw [modEq_zero_iff_dvd, orderOf_dvd_iff_pow_eq_one]
#align pow_eq_one_iff_modeq pow_eq_one_iff_modEq
#align nsmul_eq_zero_iff_modeq nsmul_eq_zero_iff_modEq
@[to_additive]
theorem orderOf_map_dvd {H : Type*} [Monoid H] (ψ : G →* H) (x : G) :
orderOf (ψ x) ∣ orderOf x := by
apply orderOf_dvd_of_pow_eq_one
rw [← map_pow, pow_orderOf_eq_one]
apply map_one
#align order_of_map_dvd orderOf_map_dvd
#align add_order_of_map_dvd addOrderOf_map_dvd
@[to_additive]
theorem exists_pow_eq_self_of_coprime (h : n.Coprime (orderOf x)) : ∃ m : ℕ, (x ^ n) ^ m = x := by
by_cases h0 : orderOf x = 0
· rw [h0, coprime_zero_right] at h
exact ⟨1, by rw [h, pow_one, pow_one]⟩
by_cases h1 : orderOf x = 1
· exact ⟨0, by rw [orderOf_eq_one_iff.mp h1, one_pow, one_pow]⟩
obtain ⟨m, h⟩ := exists_mul_emod_eq_one_of_coprime h (one_lt_iff_ne_zero_and_ne_one.mpr ⟨h0, h1⟩)
exact ⟨m, by rw [← pow_mul, ← pow_mod_orderOf, h, pow_one]⟩
#align exists_pow_eq_self_of_coprime exists_pow_eq_self_of_coprime
#align exists_nsmul_eq_self_of_coprime exists_nsmul_eq_self_of_coprime
/-- If `x^n = 1`, but `x^(n/p) ≠ 1` for all prime factors `p` of `n`,
then `x` has order `n` in `G`. -/
@[to_additive addOrderOf_eq_of_nsmul_and_div_prime_nsmul "If `n * x = 0`, but `n/p * x ≠ 0` for
all prime factors `p` of `n`, then `x` has order `n` in `G`."]
theorem orderOf_eq_of_pow_and_pow_div_prime (hn : 0 < n) (hx : x ^ n = 1)
(hd : ∀ p : ℕ, p.Prime → p ∣ n → x ^ (n / p) ≠ 1) : orderOf x = n := by
-- Let `a` be `n/(orderOf x)`, and show `a = 1`
cases' exists_eq_mul_right_of_dvd (orderOf_dvd_of_pow_eq_one hx) with a ha
suffices a = 1 by simp [this, ha]
-- Assume `a` is not one...
by_contra h
have a_min_fac_dvd_p_sub_one : a.minFac ∣ n := by
obtain ⟨b, hb⟩ : ∃ b : ℕ, a = b * a.minFac := exists_eq_mul_left_of_dvd a.minFac_dvd
rw [hb, ← mul_assoc] at ha
exact Dvd.intro_left (orderOf x * b) ha.symm
-- Use the minimum prime factor of `a` as `p`.
refine hd a.minFac (Nat.minFac_prime h) a_min_fac_dvd_p_sub_one ?_
rw [← orderOf_dvd_iff_pow_eq_one, Nat.dvd_div_iff a_min_fac_dvd_p_sub_one, ha, mul_comm,
Nat.mul_dvd_mul_iff_left (IsOfFinOrder.orderOf_pos _)]
· exact Nat.minFac_dvd a
· rw [isOfFinOrder_iff_pow_eq_one]
exact Exists.intro n (id ⟨hn, hx⟩)
#align order_of_eq_of_pow_and_pow_div_prime orderOf_eq_of_pow_and_pow_div_prime
#align add_order_of_eq_of_nsmul_and_div_prime_nsmul addOrderOf_eq_of_nsmul_and_div_prime_nsmul
@[to_additive]
theorem orderOf_eq_orderOf_iff {H : Type*} [Monoid H] {y : H} :
orderOf x = orderOf y ↔ ∀ n : ℕ, x ^ n = 1 ↔ y ^ n = 1 := by
simp_rw [← isPeriodicPt_mul_iff_pow_eq_one, ← minimalPeriod_eq_minimalPeriod_iff, orderOf]
#align order_of_eq_order_of_iff orderOf_eq_orderOf_iff
#align add_order_of_eq_add_order_of_iff addOrderOf_eq_addOrderOf_iff
/-- An injective homomorphism of monoids preserves orders of elements. -/
@[to_additive "An injective homomorphism of additive monoids preserves orders of elements."]
theorem orderOf_injective {H : Type*} [Monoid H] (f : G →* H) (hf : Function.Injective f) (x : G) :
orderOf (f x) = orderOf x := by
simp_rw [orderOf_eq_orderOf_iff, ← f.map_pow, ← f.map_one, hf.eq_iff, forall_const]
#align order_of_injective orderOf_injective
#align add_order_of_injective addOrderOf_injective
/-- A multiplicative equivalence preserves orders of elements. -/
@[to_additive (attr := simp) "An additive equivalence preserves orders of elements."]
lemma MulEquiv.orderOf_eq {H : Type*} [Monoid H] (e : G ≃* H) (x : G) :
orderOf (e x) = orderOf x :=
orderOf_injective e e.injective x
@[to_additive]
theorem Function.Injective.isOfFinOrder_iff [Monoid H] {f : G →* H} (hf : Injective f) :
IsOfFinOrder (f x) ↔ IsOfFinOrder x := by
rw [← orderOf_pos_iff, orderOf_injective f hf x, ← orderOf_pos_iff]
@[to_additive (attr := norm_cast, simp)]
theorem orderOf_submonoid {H : Submonoid G} (y : H) : orderOf (y : G) = orderOf y :=
orderOf_injective H.subtype Subtype.coe_injective y
#align order_of_submonoid orderOf_submonoid
#align order_of_add_submonoid addOrderOf_addSubmonoid
@[to_additive]
theorem orderOf_units {y : Gˣ} : orderOf (y : G) = orderOf y :=
orderOf_injective (Units.coeHom G) Units.ext y
#align order_of_units orderOf_units
#align order_of_add_units addOrderOf_addUnits
/-- If the order of `x` is finite, then `x` is a unit with inverse `x ^ (orderOf x - 1)`. -/
@[simps]
noncomputable
def IsOfFinOrder.unit {M} [Monoid M] {x : M} (hx : IsOfFinOrder x) : Mˣ :=
⟨x, x ^ (orderOf x - 1),
by rw [← _root_.pow_succ', tsub_add_cancel_of_le (by exact hx.orderOf_pos), pow_orderOf_eq_one],
by rw [← _root_.pow_succ, tsub_add_cancel_of_le (by exact hx.orderOf_pos), pow_orderOf_eq_one]⟩
lemma IsOfFinOrder.isUnit {M} [Monoid M] {x : M} (hx : IsOfFinOrder x) : IsUnit x := ⟨hx.unit, rfl⟩
variable (x)
@[to_additive]
theorem orderOf_pow' (h : n ≠ 0) : orderOf (x ^ n) = orderOf x / gcd (orderOf x) n := by
unfold orderOf
rw [← minimalPeriod_iterate_eq_div_gcd h, mul_left_iterate]
#align order_of_pow' orderOf_pow'
#align add_order_of_nsmul' addOrderOf_nsmul'
@[to_additive]
lemma orderOf_pow_of_dvd {x : G} {n : ℕ} (hn : n ≠ 0) (dvd : n ∣ orderOf x) :
orderOf (x ^ n) = orderOf x / n := by rw [orderOf_pow' _ hn, Nat.gcd_eq_right dvd]
@[to_additive]
lemma orderOf_pow_orderOf_div {x : G} {n : ℕ} (hx : orderOf x ≠ 0) (hn : n ∣ orderOf x) :
orderOf (x ^ (orderOf x / n)) = n := by
rw [orderOf_pow_of_dvd _ (Nat.div_dvd_of_dvd hn), Nat.div_div_self hn hx]
rw [← Nat.div_mul_cancel hn] at hx; exact left_ne_zero_of_mul hx
variable (n)
@[to_additive]
protected lemma IsOfFinOrder.orderOf_pow (h : IsOfFinOrder x) :
orderOf (x ^ n) = orderOf x / gcd (orderOf x) n := by
unfold orderOf
rw [← minimalPeriod_iterate_eq_div_gcd' h, mul_left_iterate]
#align order_of_pow'' IsOfFinOrder.orderOf_pow
#align add_order_of_nsmul'' IsOfFinAddOrder.addOrderOf_nsmul
@[to_additive]
lemma Nat.Coprime.orderOf_pow (h : (orderOf y).Coprime m) : orderOf (y ^ m) = orderOf y := by
by_cases hg : IsOfFinOrder y
· rw [hg.orderOf_pow y m , h.gcd_eq_one, Nat.div_one]
· rw [m.coprime_zero_left.1 (orderOf_eq_zero hg ▸ h), pow_one]
#align order_of_pow_coprime Nat.Coprime.orderOf_pow
#align add_order_of_nsmul_coprime Nat.Coprime.addOrderOf_nsmul
@[to_additive]
lemma IsOfFinOrder.natCard_powers_le_orderOf (ha : IsOfFinOrder a) :
Nat.card (powers a : Set G) ≤ orderOf a := by
classical
simpa [ha.powers_eq_image_range_orderOf, Finset.card_range, Nat.Iio_eq_range]
using Finset.card_image_le (s := Finset.range (orderOf a))
@[to_additive]
lemma IsOfFinOrder.finite_powers (ha : IsOfFinOrder a) : (powers a : Set G).Finite := by
classical rw [ha.powers_eq_image_range_orderOf]; exact Finset.finite_toSet _
namespace Commute
variable {x} (h : Commute x y)
@[to_additive]
theorem orderOf_mul_dvd_lcm : orderOf (x * y) ∣ Nat.lcm (orderOf x) (orderOf y) := by
rw [orderOf, ← comp_mul_left]
exact Function.Commute.minimalPeriod_of_comp_dvd_lcm h.function_commute_mul_left
#align commute.order_of_mul_dvd_lcm Commute.orderOf_mul_dvd_lcm
#align add_commute.order_of_add_dvd_lcm AddCommute.addOrderOf_add_dvd_lcm
@[to_additive]
theorem orderOf_dvd_lcm_mul : orderOf y ∣ Nat.lcm (orderOf x) (orderOf (x * y)) := by
by_cases h0 : orderOf x = 0
· rw [h0, lcm_zero_left]
apply dvd_zero
conv_lhs =>
rw [← one_mul y, ← pow_orderOf_eq_one x, ← succ_pred_eq_of_pos (Nat.pos_of_ne_zero h0),
_root_.pow_succ, mul_assoc]
exact
(((Commute.refl x).mul_right h).pow_left _).orderOf_mul_dvd_lcm.trans
(lcm_dvd_iff.2 ⟨(orderOf_pow_dvd _).trans (dvd_lcm_left _ _), dvd_lcm_right _ _⟩)
#align commute.order_of_dvd_lcm_mul Commute.orderOf_dvd_lcm_mul
#align add_commute.order_of_dvd_lcm_add AddCommute.addOrderOf_dvd_lcm_add
@[to_additive addOrderOf_add_dvd_mul_addOrderOf]
theorem orderOf_mul_dvd_mul_orderOf : orderOf (x * y) ∣ orderOf x * orderOf y :=
dvd_trans h.orderOf_mul_dvd_lcm (lcm_dvd_mul _ _)
#align commute.order_of_mul_dvd_mul_order_of Commute.orderOf_mul_dvd_mul_orderOf
#align add_commute.add_order_of_add_dvd_mul_add_order_of AddCommute.addOrderOf_add_dvd_mul_addOrderOf
@[to_additive addOrderOf_add_eq_mul_addOrderOf_of_coprime]
theorem orderOf_mul_eq_mul_orderOf_of_coprime (hco : (orderOf x).Coprime (orderOf y)) :
orderOf (x * y) = orderOf x * orderOf y := by
rw [orderOf, ← comp_mul_left]
exact h.function_commute_mul_left.minimalPeriod_of_comp_eq_mul_of_coprime hco
#align commute.order_of_mul_eq_mul_order_of_of_coprime Commute.orderOf_mul_eq_mul_orderOf_of_coprime
#align add_commute.add_order_of_add_eq_mul_add_order_of_of_coprime AddCommute.addOrderOf_add_eq_mul_addOrderOf_of_coprime
/-- Commuting elements of finite order are closed under multiplication. -/
@[to_additive "Commuting elements of finite additive order are closed under addition."]
theorem isOfFinOrder_mul (hx : IsOfFinOrder x) (hy : IsOfFinOrder y) : IsOfFinOrder (x * y) :=
orderOf_pos_iff.mp <|
pos_of_dvd_of_pos h.orderOf_mul_dvd_mul_orderOf <| mul_pos hx.orderOf_pos hy.orderOf_pos
#align commute.is_of_fin_order_mul Commute.isOfFinOrder_mul
#align add_commute.is_of_fin_order_add AddCommute.isOfFinAddOrder_add
/-- If each prime factor of `orderOf x` has higher multiplicity in `orderOf y`, and `x` commutes
with `y`, then `x * y` has the same order as `y`. -/
@[to_additive addOrderOf_add_eq_right_of_forall_prime_mul_dvd
"If each prime factor of
`addOrderOf x` has higher multiplicity in `addOrderOf y`, and `x` commutes with `y`,
then `x + y` has the same order as `y`."]
theorem orderOf_mul_eq_right_of_forall_prime_mul_dvd (hy : IsOfFinOrder y)
(hdvd : ∀ p : ℕ, p.Prime → p ∣ orderOf x → p * orderOf x ∣ orderOf y) :
orderOf (x * y) = orderOf y := by
have hoy := hy.orderOf_pos
have hxy := dvd_of_forall_prime_mul_dvd hdvd
apply orderOf_eq_of_pow_and_pow_div_prime hoy <;> simp only [Ne, ← orderOf_dvd_iff_pow_eq_one]
· exact h.orderOf_mul_dvd_lcm.trans (lcm_dvd hxy dvd_rfl)
refine fun p hp hpy hd => hp.ne_one ?_
rw [← Nat.dvd_one, ← mul_dvd_mul_iff_right hoy.ne', one_mul, ← dvd_div_iff hpy]
refine (orderOf_dvd_lcm_mul h).trans (lcm_dvd ((dvd_div_iff hpy).2 ?_) hd)
by_cases h : p ∣ orderOf x
exacts [hdvd p hp h, (hp.coprime_iff_not_dvd.2 h).mul_dvd_of_dvd_of_dvd hpy hxy]
#align commute.order_of_mul_eq_right_of_forall_prime_mul_dvd Commute.orderOf_mul_eq_right_of_forall_prime_mul_dvd
#align add_commute.add_order_of_add_eq_right_of_forall_prime_mul_dvd AddCommute.addOrderOf_add_eq_right_of_forall_prime_mul_dvd
end Commute
section PPrime
variable {x n} {p : ℕ} [hp : Fact p.Prime]
@[to_additive]
theorem orderOf_eq_prime (hg : x ^ p = 1) (hg1 : x ≠ 1) : orderOf x = p :=
minimalPeriod_eq_prime ((isPeriodicPt_mul_iff_pow_eq_one _).mpr hg)
(by rwa [IsFixedPt, mul_one])
#align order_of_eq_prime orderOf_eq_prime
#align add_order_of_eq_prime addOrderOf_eq_prime
@[to_additive addOrderOf_eq_prime_pow]
theorem orderOf_eq_prime_pow (hnot : ¬x ^ p ^ n = 1) (hfin : x ^ p ^ (n + 1) = 1) :
orderOf x = p ^ (n + 1) := by
apply minimalPeriod_eq_prime_pow <;> rwa [isPeriodicPt_mul_iff_pow_eq_one]
#align order_of_eq_prime_pow orderOf_eq_prime_pow
#align add_order_of_eq_prime_pow addOrderOf_eq_prime_pow
@[to_additive exists_addOrderOf_eq_prime_pow_iff]
theorem exists_orderOf_eq_prime_pow_iff :
(∃ k : ℕ, orderOf x = p ^ k) ↔ ∃ m : ℕ, x ^ (p : ℕ) ^ m = 1 :=
⟨fun ⟨k, hk⟩ => ⟨k, by rw [← hk, pow_orderOf_eq_one]⟩, fun ⟨_, hm⟩ => by
obtain ⟨k, _, hk⟩ := (Nat.dvd_prime_pow hp.elim).mp (orderOf_dvd_of_pow_eq_one hm)
exact ⟨k, hk⟩⟩
#align exists_order_of_eq_prime_pow_iff exists_orderOf_eq_prime_pow_iff
#align exists_add_order_of_eq_prime_pow_iff exists_addOrderOf_eq_prime_pow_iff
end PPrime
end Monoid
section CancelMonoid
variable [LeftCancelMonoid G] {x y : G} {a : G} {m n : ℕ}
@[to_additive]
theorem pow_eq_pow_iff_modEq : x ^ n = x ^ m ↔ n ≡ m [MOD orderOf x] := by
wlog hmn : m ≤ n generalizing m n
· rw [eq_comm, ModEq.comm, this (le_of_not_le hmn)]
obtain ⟨k, rfl⟩ := Nat.exists_eq_add_of_le hmn
rw [← mul_one (x ^ m), pow_add, mul_left_cancel_iff, pow_eq_one_iff_modEq]
exact ⟨fun h => Nat.ModEq.add_left _ h, fun h => Nat.ModEq.add_left_cancel' _ h⟩
#align pow_eq_pow_iff_modeq pow_eq_pow_iff_modEq
#align nsmul_eq_nsmul_iff_modeq nsmul_eq_nsmul_iff_modEq
@[to_additive (attr := simp)]
lemma injective_pow_iff_not_isOfFinOrder : Injective (fun n : ℕ ↦ x ^ n) ↔ ¬IsOfFinOrder x := by
refine ⟨fun h => not_isOfFinOrder_of_injective_pow h, fun h n m hnm => ?_⟩
rwa [pow_eq_pow_iff_modEq, orderOf_eq_zero_iff.mpr h, modEq_zero_iff] at hnm
#align injective_pow_iff_not_is_of_fin_order injective_pow_iff_not_isOfFinOrder
#align injective_nsmul_iff_not_is_of_fin_add_order injective_nsmul_iff_not_isOfFinAddOrder
@[to_additive]
lemma pow_inj_mod {n m : ℕ} : x ^ n = x ^ m ↔ n % orderOf x = m % orderOf x := pow_eq_pow_iff_modEq
#align pow_inj_mod pow_inj_mod
#align nsmul_inj_mod nsmul_inj_mod
@[to_additive]
theorem pow_inj_iff_of_orderOf_eq_zero (h : orderOf x = 0) {n m : ℕ} : x ^ n = x ^ m ↔ n = m := by
rw [pow_eq_pow_iff_modEq, h, modEq_zero_iff]
#align pow_inj_iff_of_order_of_eq_zero pow_inj_iff_of_orderOf_eq_zero
#align nsmul_inj_iff_of_add_order_of_eq_zero nsmul_inj_iff_of_addOrderOf_eq_zero
@[to_additive]
theorem infinite_not_isOfFinOrder {x : G} (h : ¬IsOfFinOrder x) :
{ y : G | ¬IsOfFinOrder y }.Infinite := by
let s := { n | 0 < n }.image fun n : ℕ => x ^ n
have hs : s ⊆ { y : G | ¬IsOfFinOrder y } := by
rintro - ⟨n, hn : 0 < n, rfl⟩ (contra : IsOfFinOrder (x ^ n))
apply h
rw [isOfFinOrder_iff_pow_eq_one] at contra ⊢
obtain ⟨m, hm, hm'⟩ := contra
exact ⟨n * m, mul_pos hn hm, by rwa [pow_mul]⟩
suffices s.Infinite by exact this.mono hs
contrapose! h
have : ¬Injective fun n : ℕ => x ^ n := by
have := Set.not_injOn_infinite_finite_image (Set.Ioi_infinite 0) (Set.not_infinite.mp h)
contrapose! this
exact Set.injOn_of_injective this
rwa [injective_pow_iff_not_isOfFinOrder, Classical.not_not] at this
#align infinite_not_is_of_fin_order infinite_not_isOfFinOrder
#align infinite_not_is_of_fin_add_order infinite_not_isOfFinAddOrder
@[to_additive (attr := simp)]
lemma finite_powers : (powers a : Set G).Finite ↔ IsOfFinOrder a := by
refine ⟨fun h ↦ ?_, IsOfFinOrder.finite_powers⟩
obtain ⟨m, n, hmn, ha⟩ := h.exists_lt_map_eq_of_forall_mem (f := fun n : ℕ ↦ a ^ n)
(fun n ↦ by simp [mem_powers_iff])
refine isOfFinOrder_iff_pow_eq_one.2 ⟨n - m, tsub_pos_iff_lt.2 hmn, ?_⟩
rw [← mul_left_cancel_iff (a := a ^ m), ← pow_add, add_tsub_cancel_of_le hmn.le, ha, mul_one]
@[to_additive (attr := simp)]
lemma infinite_powers : (powers a : Set G).Infinite ↔ ¬ IsOfFinOrder a := finite_powers.not
/-- The equivalence between `Fin (orderOf x)` and `Submonoid.powers x`, sending `i` to `x ^ i`."-/
@[to_additive "The equivalence between `Fin (addOrderOf a)` and
`AddSubmonoid.multiples a`, sending `i` to `i • a`."]
noncomputable def finEquivPowers (x : G) (hx : IsOfFinOrder x) : Fin (orderOf x) ≃ powers x :=
Equiv.ofBijective (fun n ↦ ⟨x ^ (n : ℕ), ⟨n, rfl⟩⟩) ⟨fun ⟨_, h₁⟩ ⟨_, h₂⟩ ij ↦
Fin.ext (pow_injOn_Iio_orderOf h₁ h₂ (Subtype.mk_eq_mk.1 ij)), fun ⟨_, i, rfl⟩ ↦
⟨⟨i % orderOf x, mod_lt _ hx.orderOf_pos⟩, Subtype.eq <| pow_mod_orderOf _ _⟩⟩
#align fin_equiv_powers finEquivPowers
#align fin_equiv_multiples finEquivMultiples
-- This lemma has always been bad, but the linter only noticed after leanprover/lean4#2644.
@[to_additive (attr := simp, nolint simpNF)]
lemma finEquivPowers_apply (x : G) (hx) {n : Fin (orderOf x)} :
finEquivPowers x hx n = ⟨x ^ (n : ℕ), n, rfl⟩ := rfl
#align fin_equiv_powers_apply finEquivPowers_apply
#align fin_equiv_multiples_apply finEquivMultiples_apply
-- This lemma has always been bad, but the linter only noticed after leanprover/lean4#2644.
@[to_additive (attr := simp, nolint simpNF)]
lemma finEquivPowers_symm_apply (x : G) (hx) (n : ℕ) {hn : ∃ m : ℕ, x ^ m = x ^ n} :
(finEquivPowers x hx).symm ⟨x ^ n, hn⟩ = ⟨n % orderOf x, Nat.mod_lt _ hx.orderOf_pos⟩ := by
rw [Equiv.symm_apply_eq, finEquivPowers_apply, Subtype.mk_eq_mk, ← pow_mod_orderOf, Fin.val_mk]
#align fin_equiv_powers_symm_apply finEquivPowers_symm_apply
#align fin_equiv_multiples_symm_apply finEquivMultiples_symm_apply
/-- See also `orderOf_eq_card_powers`. -/
@[to_additive "See also `addOrder_eq_card_multiples`."]
lemma Nat.card_submonoidPowers : Nat.card (powers a) = orderOf a := by
classical
by_cases ha : IsOfFinOrder a
· exact (Nat.card_congr (finEquivPowers _ ha).symm).trans <| by simp
· have := (infinite_powers.2 ha).to_subtype
rw [orderOf_eq_zero ha, Nat.card_eq_zero_of_infinite]
end CancelMonoid
section Group
variable [Group G] {x y : G} {i : ℤ}
/-- Inverses of elements of finite order have finite order. -/
@[to_additive (attr := simp) "Inverses of elements of finite additive order
have finite additive order."]
theorem isOfFinOrder_inv_iff {x : G} : IsOfFinOrder x⁻¹ ↔ IsOfFinOrder x := by
simp [isOfFinOrder_iff_pow_eq_one]
#align is_of_fin_order_inv_iff isOfFinOrder_inv_iff
#align is_of_fin_order_neg_iff isOfFinAddOrder_neg_iff
@[to_additive] alias ⟨IsOfFinOrder.of_inv, IsOfFinOrder.inv⟩ := isOfFinOrder_inv_iff
#align is_of_fin_order.inv IsOfFinOrder.inv
#align is_of_fin_add_order.neg IsOfFinAddOrder.neg
@[to_additive]
theorem orderOf_dvd_iff_zpow_eq_one : (orderOf x : ℤ) ∣ i ↔ x ^ i = 1 := by
rcases Int.eq_nat_or_neg i with ⟨i, rfl | rfl⟩
· rw [Int.natCast_dvd_natCast, orderOf_dvd_iff_pow_eq_one, zpow_natCast]
· rw [dvd_neg, Int.natCast_dvd_natCast, zpow_neg, inv_eq_one, zpow_natCast,
orderOf_dvd_iff_pow_eq_one]
#align order_of_dvd_iff_zpow_eq_one orderOf_dvd_iff_zpow_eq_one
#align add_order_of_dvd_iff_zsmul_eq_zero addOrderOf_dvd_iff_zsmul_eq_zero
@[to_additive (attr := simp)]
theorem orderOf_inv (x : G) : orderOf x⁻¹ = orderOf x := by simp [orderOf_eq_orderOf_iff]
#align order_of_inv orderOf_inv
#align order_of_neg addOrderOf_neg
namespace Subgroup
variable {H : Subgroup G}
@[to_additive (attr := norm_cast)] -- Porting note (#10618): simp can prove this (so removed simp)
lemma orderOf_coe (a : H) : orderOf (a : G) = orderOf a :=
orderOf_injective H.subtype Subtype.coe_injective _
#align order_of_subgroup Subgroup.orderOf_coe
#align order_of_add_subgroup AddSubgroup.addOrderOf_coe
@[to_additive (attr := simp)]
lemma orderOf_mk (a : G) (ha) : orderOf (⟨a, ha⟩ : H) = orderOf a := (orderOf_coe _).symm
end Subgroup
@[to_additive mod_addOrderOf_zsmul]
lemma zpow_mod_orderOf (x : G) (z : ℤ) : x ^ (z % (orderOf x : ℤ)) = x ^ z :=
calc
x ^ (z % (orderOf x : ℤ)) = x ^ (z % orderOf x + orderOf x * (z / orderOf x) : ℤ) := by
simp [zpow_add, zpow_mul, pow_orderOf_eq_one]
_ = x ^ z := by rw [Int.emod_add_ediv]
#align zpow_eq_mod_order_of zpow_mod_orderOf
#align zsmul_eq_mod_add_order_of mod_addOrderOf_zsmul
@[to_additive (attr := simp) zsmul_smul_addOrderOf]
theorem zpow_pow_orderOf : (x ^ i) ^ orderOf x = 1 := by
by_cases h : IsOfFinOrder x
· rw [← zpow_natCast, ← zpow_mul, mul_comm, zpow_mul, zpow_natCast, pow_orderOf_eq_one, one_zpow]
· rw [orderOf_eq_zero h, _root_.pow_zero]
#align zpow_pow_order_of zpow_pow_orderOf
#align zsmul_smul_order_of zsmul_smul_addOrderOf
@[to_additive]
theorem IsOfFinOrder.zpow (h : IsOfFinOrder x) {i : ℤ} : IsOfFinOrder (x ^ i) :=
isOfFinOrder_iff_pow_eq_one.mpr ⟨orderOf x, h.orderOf_pos, zpow_pow_orderOf⟩
#align is_of_fin_order.zpow IsOfFinOrder.zpow
#align is_of_fin_add_order.zsmul IsOfFinAddOrder.zsmul
@[to_additive]
theorem IsOfFinOrder.of_mem_zpowers (h : IsOfFinOrder x) (h' : y ∈ Subgroup.zpowers x) :
IsOfFinOrder y := by
obtain ⟨k, rfl⟩ := Subgroup.mem_zpowers_iff.mp h'
exact h.zpow
#align is_of_fin_order.of_mem_zpowers IsOfFinOrder.of_mem_zpowers
#align is_of_fin_add_order.of_mem_zmultiples IsOfFinAddOrder.of_mem_zmultiples
@[to_additive]
theorem orderOf_dvd_of_mem_zpowers (h : y ∈ Subgroup.zpowers x) : orderOf y ∣ orderOf x := by
obtain ⟨k, rfl⟩ := Subgroup.mem_zpowers_iff.mp h
rw [orderOf_dvd_iff_pow_eq_one]
exact zpow_pow_orderOf
#align order_of_dvd_of_mem_zpowers orderOf_dvd_of_mem_zpowers
#align add_order_of_dvd_of_mem_zmultiples addOrderOf_dvd_of_mem_zmultiples
theorem smul_eq_self_of_mem_zpowers {α : Type*} [MulAction G α] (hx : x ∈ Subgroup.zpowers y)
{a : α} (hs : y • a = a) : x • a = a := by
obtain ⟨k, rfl⟩ := Subgroup.mem_zpowers_iff.mp hx
rw [← MulAction.toPerm_apply, ← MulAction.toPermHom_apply, MonoidHom.map_zpow _ y k,
MulAction.toPermHom_apply]
exact Function.IsFixedPt.perm_zpow (by exact hs) k -- Porting note: help elab'n with `by exact`
#align smul_eq_self_of_mem_zpowers smul_eq_self_of_mem_zpowers
theorem vadd_eq_self_of_mem_zmultiples {α G : Type*} [AddGroup G] [AddAction G α] {x y : G}
(hx : x ∈ AddSubgroup.zmultiples y) {a : α} (hs : y +ᵥ a = a) : x +ᵥ a = a :=
@smul_eq_self_of_mem_zpowers (Multiplicative G) _ _ _ α _ hx a hs
#align vadd_eq_self_of_mem_zmultiples vadd_eq_self_of_mem_zmultiples
attribute [to_additive existing] smul_eq_self_of_mem_zpowers
@[to_additive]
lemma IsOfFinOrder.mem_powers_iff_mem_zpowers (hx : IsOfFinOrder x) :
y ∈ powers x ↔ y ∈ zpowers x :=
⟨fun ⟨n, hn⟩ ↦ ⟨n, by simp_all⟩, fun ⟨i, hi⟩ ↦ ⟨(i % orderOf x).natAbs, by
dsimp only
rwa [← zpow_natCast, Int.natAbs_of_nonneg <| Int.emod_nonneg _ <|
Int.natCast_ne_zero_iff_pos.2 <| hx.orderOf_pos, zpow_mod_orderOf]⟩⟩
@[to_additive]
lemma IsOfFinOrder.powers_eq_zpowers (hx : IsOfFinOrder x) : (powers x : Set G) = zpowers x :=
Set.ext fun _ ↦ hx.mem_powers_iff_mem_zpowers
@[to_additive]
lemma IsOfFinOrder.mem_zpowers_iff_mem_range_orderOf [DecidableEq G] (hx : IsOfFinOrder x) :
y ∈ zpowers x ↔ y ∈ (Finset.range (orderOf x)).image (x ^ ·) :=
hx.mem_powers_iff_mem_zpowers.symm.trans hx.mem_powers_iff_mem_range_orderOf
/-- The equivalence between `Fin (orderOf x)` and `Subgroup.zpowers x`, sending `i` to `x ^ i`. -/
@[to_additive "The equivalence between `Fin (addOrderOf a)` and
`Subgroup.zmultiples a`, sending `i` to `i • a`."]
noncomputable def finEquivZPowers (x : G) (hx : IsOfFinOrder x) :
Fin (orderOf x) ≃ (zpowers x : Set G) :=
(finEquivPowers x hx).trans <| Equiv.Set.ofEq hx.powers_eq_zpowers
#align fin_equiv_zpowers finEquivZPowers
#align fin_equiv_zmultiples finEquivZMultiples
-- This lemma has always been bad, but the linter only noticed after leaprover/lean4#2644.
@[to_additive (attr := simp, nolint simpNF)]
lemma finEquivZPowers_apply (hx) {n : Fin (orderOf x)} :
finEquivZPowers x hx n = ⟨x ^ (n : ℕ), n, zpow_natCast x n⟩ := rfl
#align fin_equiv_zpowers_apply finEquivZPowers_apply
#align fin_equiv_zmultiples_apply finEquivZMultiples_apply
-- This lemma has always been bad, but the linter only noticed after leanprover/lean4#2644.
@[to_additive (attr := simp, nolint simpNF)]
lemma finEquivZPowers_symm_apply (x : G) (hx) (n : ℕ) :
(finEquivZPowers x hx).symm ⟨x ^ n, ⟨n, by simp⟩⟩ =
⟨n % orderOf x, Nat.mod_lt _ hx.orderOf_pos⟩ := by
rw [finEquivZPowers, Equiv.symm_trans_apply]; exact finEquivPowers_symm_apply x _ n
#align fin_equiv_zpowers_symm_apply finEquivZPowers_symm_apply
#align fin_equiv_zmultiples_symm_apply finEquivZMultiples_symm_apply
end Group
section CommMonoid
variable [CommMonoid G] {x y : G}
/-- Elements of finite order are closed under multiplication. -/
@[to_additive "Elements of finite additive order are closed under addition."]
theorem IsOfFinOrder.mul (hx : IsOfFinOrder x) (hy : IsOfFinOrder y) : IsOfFinOrder (x * y) :=
(Commute.all x y).isOfFinOrder_mul hx hy
#align is_of_fin_order.mul IsOfFinOrder.mul
#align is_of_fin_add_order.add IsOfFinAddOrder.add
end CommMonoid
section FiniteMonoid
variable [Monoid G] {x : G} {n : ℕ}
@[to_additive]
theorem sum_card_orderOf_eq_card_pow_eq_one [Fintype G] [DecidableEq G] (hn : n ≠ 0) :
(∑ m ∈ (Finset.range n.succ).filter (· ∣ n),
(Finset.univ.filter fun x : G => orderOf x = m).card) =
(Finset.univ.filter fun x : G => x ^ n = 1).card :=
calc
(∑ m ∈ (Finset.range n.succ).filter (· ∣ n),
(Finset.univ.filter fun x : G => orderOf x = m).card) = _ :=
(Finset.card_biUnion
(by
intros
apply Finset.disjoint_filter.2
rintro _ _ rfl; assumption)).symm
_ = _ :=
congr_arg Finset.card
(Finset.ext
(by
intro x
suffices orderOf x ≤ n ∧ orderOf x ∣ n ↔ x ^ n = 1 by simpa [Nat.lt_succ_iff]
exact
⟨fun h => by
let ⟨m, hm⟩ := h.2
rw [hm, pow_mul, pow_orderOf_eq_one, one_pow], fun h =>
⟨orderOf_le_of_pow_eq_one hn.bot_lt h, orderOf_dvd_of_pow_eq_one h⟩⟩))
#align sum_card_order_of_eq_card_pow_eq_one sum_card_orderOf_eq_card_pow_eq_one
#align sum_card_add_order_of_eq_card_nsmul_eq_zero sum_card_addOrderOf_eq_card_nsmul_eq_zero
@[to_additive]
theorem orderOf_le_card_univ [Fintype G] : orderOf x ≤ Fintype.card G :=
Finset.le_card_of_inj_on_range (x ^ ·) (fun _ _ ↦ Finset.mem_univ _) pow_injOn_Iio_orderOf
#align order_of_le_card_univ orderOf_le_card_univ
#align add_order_of_le_card_univ addOrderOf_le_card_univ
end FiniteMonoid
section FiniteCancelMonoid
variable [LeftCancelMonoid G]
-- TODO: Of course everything also works for `RightCancelMonoid`.
section Finite
variable [Finite G] {x y : G} {n : ℕ}
-- TODO: Use this to show that a finite left cancellative monoid is a group.
@[to_additive]
lemma isOfFinOrder_of_finite (x : G) : IsOfFinOrder x := by
by_contra h; exact infinite_not_isOfFinOrder h <| Set.toFinite _
#align exists_pow_eq_one isOfFinOrder_of_finite
#align exists_nsmul_eq_zero isOfFinAddOrder_of_finite
/-- This is the same as `IsOfFinOrder.orderOf_pos` but with one fewer explicit assumption since this
is automatic in case of a finite cancellative monoid. -/
@[to_additive "This is the same as `IsOfFinAddOrder.addOrderOf_pos` but with one fewer explicit
assumption since this is automatic in case of a finite cancellative additive monoid."]
lemma orderOf_pos (x : G) : 0 < orderOf x := (isOfFinOrder_of_finite x).orderOf_pos
#align order_of_pos orderOf_pos
#align add_order_of_pos addOrderOf_pos
/-- This is the same as `orderOf_pow'` and `orderOf_pow''` but with one assumption less which is
automatic in the case of a finite cancellative monoid. -/
@[to_additive "This is the same as `addOrderOf_nsmul'` and
`addOrderOf_nsmul` but with one assumption less which is automatic in the case of a
finite cancellative additive monoid."]
theorem orderOf_pow (x : G) : orderOf (x ^ n) = orderOf x / gcd (orderOf x) n :=
(isOfFinOrder_of_finite _).orderOf_pow _
#align order_of_pow orderOf_pow
#align add_order_of_nsmul addOrderOf_nsmul
@[to_additive]
theorem mem_powers_iff_mem_range_orderOf [DecidableEq G] :
y ∈ powers x ↔ y ∈ (Finset.range (orderOf x)).image (x ^ ·) :=
Finset.mem_range_iff_mem_finset_range_of_mod_eq' (orderOf_pos x) <| pow_mod_orderOf _
#align mem_powers_iff_mem_range_order_of mem_powers_iff_mem_range_orderOf
#align mem_multiples_iff_mem_range_add_order_of mem_multiples_iff_mem_range_addOrderOf
/-- The equivalence between `Submonoid.powers` of two elements `x, y` of the same order, mapping
`x ^ i` to `y ^ i`. -/
@[to_additive
"The equivalence between `Submonoid.multiples` of two elements `a, b` of the same additive order,
mapping `i • a` to `i • b`."]
noncomputable def powersEquivPowers (h : orderOf x = orderOf y) : powers x ≃ powers y :=
(finEquivPowers x <| isOfFinOrder_of_finite _).symm.trans <|
(finCongr h).trans <| finEquivPowers y <| isOfFinOrder_of_finite _
#align powers_equiv_powers powersEquivPowers
#align multiples_equiv_multiples multiplesEquivMultiples
-- Porting note: the simpNF linter complains that simp can change the LHS to something
-- that looks the same as the current LHS even with `pp.explicit`
@[to_additive (attr := simp, nolint simpNF)]
theorem powersEquivPowers_apply (h : orderOf x = orderOf y) (n : ℕ) :
powersEquivPowers h ⟨x ^ n, n, rfl⟩ = ⟨y ^ n, n, rfl⟩ := by
rw [powersEquivPowers, Equiv.trans_apply, Equiv.trans_apply, finEquivPowers_symm_apply, ←
Equiv.eq_symm_apply, finEquivPowers_symm_apply]
simp [h]
#align powers_equiv_powers_apply powersEquivPowers_apply
#align multiples_equiv_multiples_apply multiplesEquivMultiples_apply
end Finite
variable [Fintype G] {x : G}
@[to_additive]
lemma orderOf_eq_card_powers : orderOf x = Fintype.card (powers x : Set G) :=
(Fintype.card_fin (orderOf x)).symm.trans <|
Fintype.card_eq.2 ⟨finEquivPowers x <| isOfFinOrder_of_finite _⟩
#align order_eq_card_powers orderOf_eq_card_powers
#align add_order_of_eq_card_multiples addOrderOf_eq_card_multiples
end FiniteCancelMonoid
section FiniteGroup
variable [Group G]
section Finite
variable [Finite G] {x y : G}
@[to_additive]
theorem exists_zpow_eq_one (x : G) : ∃ (i : ℤ) (_ : i ≠ 0), x ^ (i : ℤ) = 1 := by
obtain ⟨w, hw1, hw2⟩ := isOfFinOrder_of_finite x
refine ⟨w, Int.natCast_ne_zero.mpr (_root_.ne_of_gt hw1), ?_⟩
rw [zpow_natCast]
exact (isPeriodicPt_mul_iff_pow_eq_one _).mp hw2
#align exists_zpow_eq_one exists_zpow_eq_one
#align exists_zsmul_eq_zero exists_zsmul_eq_zero
@[to_additive]
lemma mem_powers_iff_mem_zpowers : y ∈ powers x ↔ y ∈ zpowers x :=
(isOfFinOrder_of_finite _).mem_powers_iff_mem_zpowers
#align mem_powers_iff_mem_zpowers mem_powers_iff_mem_zpowers
#align mem_multiples_iff_mem_zmultiples mem_multiples_iff_mem_zmultiples
@[to_additive]
lemma powers_eq_zpowers (x : G) : (powers x : Set G) = zpowers x :=
(isOfFinOrder_of_finite _).powers_eq_zpowers
#align powers_eq_zpowers powers_eq_zpowers
#align multiples_eq_zmultiples multiples_eq_zmultiples
@[to_additive]
lemma mem_zpowers_iff_mem_range_orderOf [DecidableEq G] :
y ∈ zpowers x ↔ y ∈ (Finset.range (orderOf x)).image (x ^ ·) :=
(isOfFinOrder_of_finite _).mem_zpowers_iff_mem_range_orderOf
#align mem_zpowers_iff_mem_range_order_of mem_zpowers_iff_mem_range_orderOf
#align mem_zmultiples_iff_mem_range_add_order_of mem_zmultiples_iff_mem_range_addOrderOf
@[to_additive]
theorem zpow_eq_one_iff_modEq {n : ℤ} : x ^ n = 1 ↔ n ≡ 0 [ZMOD orderOf x] := by
rw [Int.modEq_zero_iff_dvd, orderOf_dvd_iff_zpow_eq_one]
#align zpow_eq_one_iff_modeq zpow_eq_one_iff_modEq
#align zsmul_eq_zero_iff_modeq zsmul_eq_zero_iff_modEq
@[to_additive]
theorem zpow_eq_zpow_iff_modEq {m n : ℤ} : x ^ m = x ^ n ↔ m ≡ n [ZMOD orderOf x] := by
rw [← mul_inv_eq_one, ← zpow_sub, zpow_eq_one_iff_modEq, Int.modEq_iff_dvd, Int.modEq_iff_dvd,
zero_sub, neg_sub]
#align zpow_eq_zpow_iff_modeq zpow_eq_zpow_iff_modEq
#align zsmul_eq_zsmul_iff_modeq zsmul_eq_zsmul_iff_modEq
@[to_additive (attr := simp)]
theorem injective_zpow_iff_not_isOfFinOrder : (Injective fun n : ℤ => x ^ n) ↔ ¬IsOfFinOrder x := by
refine ⟨?_, fun h n m hnm => ?_⟩
· simp_rw [isOfFinOrder_iff_pow_eq_one]
rintro h ⟨n, hn, hx⟩
exact Nat.cast_ne_zero.2 hn.ne' (h <| by simpa using hx)
rwa [zpow_eq_zpow_iff_modEq, orderOf_eq_zero_iff.2 h, Nat.cast_zero, Int.modEq_zero_iff] at hnm
#align injective_zpow_iff_not_is_of_fin_order injective_zpow_iff_not_isOfFinOrder
#align injective_zsmul_iff_not_is_of_fin_order injective_zsmul_iff_not_isOfFinAddOrder
/-- The equivalence between `Subgroup.zpowers` of two elements `x, y` of the same order, mapping
`x ^ i` to `y ^ i`. -/
@[to_additive
"The equivalence between `Subgroup.zmultiples` of two elements `a, b` of the same additive order,
mapping `i • a` to `i • b`."]
noncomputable def zpowersEquivZPowers (h : orderOf x = orderOf y) :
(Subgroup.zpowers x : Set G) ≃ (Subgroup.zpowers y : Set G) :=
(finEquivZPowers x <| isOfFinOrder_of_finite _).symm.trans <| (finCongr h).trans <|
finEquivZPowers y <| isOfFinOrder_of_finite _
#align zpowers_equiv_zpowers zpowersEquivZPowers
#align zmultiples_equiv_zmultiples zmultiplesEquivZMultiples
-- Porting note: the simpNF linter complains that simp can change the LHS to something
-- that looks the same as the current LHS even with `pp.explicit`
@[to_additive (attr := simp, nolint simpNF) zmultiples_equiv_zmultiples_apply]
theorem zpowersEquivZPowers_apply (h : orderOf x = orderOf y) (n : ℕ) :
zpowersEquivZPowers h ⟨x ^ n, n, zpow_natCast x n⟩ = ⟨y ^ n, n, zpow_natCast y n⟩ := by
rw [zpowersEquivZPowers, Equiv.trans_apply, Equiv.trans_apply, finEquivZPowers_symm_apply, ←
Equiv.eq_symm_apply, finEquivZPowers_symm_apply]
simp [h]
#align zpowers_equiv_zpowers_apply zpowersEquivZPowers_apply
#align zmultiples_equiv_zmultiples_apply zmultiples_equiv_zmultiples_apply
end Finite
variable [Fintype G] {x : G} {n : ℕ}
/-- See also `Nat.card_addSubgroupZPowers`. -/
@[to_additive "See also `Nat.card_subgroup`."]
theorem Fintype.card_zpowers : Fintype.card (zpowers x) = orderOf x :=
(Fintype.card_eq.2 ⟨finEquivZPowers x <| isOfFinOrder_of_finite _⟩).symm.trans <|
Fintype.card_fin (orderOf x)
#align order_eq_card_zpowers Fintype.card_zpowers
#align add_order_eq_card_zmultiples Fintype.card_zmultiples
@[to_additive]
theorem card_zpowers_le (a : G) {k : ℕ} (k_pos : k ≠ 0)
(ha : a ^ k = 1) : Fintype.card (Subgroup.zpowers a) ≤ k := by
rw [Fintype.card_zpowers]
apply orderOf_le_of_pow_eq_one k_pos.bot_lt ha
open QuotientGroup
@[to_additive]
theorem orderOf_dvd_card : orderOf x ∣ Fintype.card G := by
classical
have ft_prod : Fintype ((G ⧸ zpowers x) × zpowers x) :=
Fintype.ofEquiv G groupEquivQuotientProdSubgroup
have ft_s : Fintype (zpowers x) := @Fintype.prodRight _ _ _ ft_prod _
have ft_cosets : Fintype (G ⧸ zpowers x) :=
@Fintype.prodLeft _ _ _ ft_prod ⟨⟨1, (zpowers x).one_mem⟩⟩
have eq₁ : Fintype.card G = @Fintype.card _ ft_cosets * @Fintype.card _ ft_s :=
calc
Fintype.card G = @Fintype.card _ ft_prod :=
@Fintype.card_congr _ _ _ ft_prod groupEquivQuotientProdSubgroup
_ = @Fintype.card _ (@instFintypeProd _ _ ft_cosets ft_s) :=
congr_arg (@Fintype.card _) <| Subsingleton.elim _ _
_ = @Fintype.card _ ft_cosets * @Fintype.card _ ft_s :=
@Fintype.card_prod _ _ ft_cosets ft_s
have eq₂ : orderOf x = @Fintype.card _ ft_s :=
calc
orderOf x = _ := Fintype.card_zpowers.symm
_ = _ := congr_arg (@Fintype.card _) <| Subsingleton.elim _ _
exact Dvd.intro (@Fintype.card (G ⧸ Subgroup.zpowers x) ft_cosets) (by rw [eq₁, eq₂, mul_comm])
#align order_of_dvd_card_univ orderOf_dvd_card
#align add_order_of_dvd_card_univ addOrderOf_dvd_card
@[to_additive]
theorem orderOf_dvd_natCard {G : Type*} [Group G] (x : G) : orderOf x ∣ Nat.card G := by
cases' fintypeOrInfinite G with h h
· simp only [Nat.card_eq_fintype_card, orderOf_dvd_card]
· simp only [card_eq_zero_of_infinite, dvd_zero]
#align order_of_dvd_nat_card orderOf_dvd_natCard
#align add_order_of_dvd_nat_card addOrderOf_dvd_natCard
@[to_additive]
nonrec lemma Subgroup.orderOf_dvd_natCard (s : Subgroup G) (hx : x ∈ s) :
orderOf x ∣ Nat.card s := by simpa using orderOf_dvd_natCard (⟨x, hx⟩ : s)
@[to_additive]
lemma Subgroup.orderOf_le_card (s : Subgroup G) (hs : (s : Set G).Finite) (hx : x ∈ s) :
orderOf x ≤ Nat.card s :=
le_of_dvd (Nat.card_pos_iff.2 <| ⟨s.coe_nonempty.to_subtype, hs.to_subtype⟩) <|
s.orderOf_dvd_natCard hx
@[to_additive]
lemma Submonoid.orderOf_le_card (s : Submonoid G) (hs : (s : Set G).Finite) (hx : x ∈ s) :
orderOf x ≤ Nat.card s := by
rw [← Nat.card_submonoidPowers]; exact Nat.card_mono hs <| powers_le.2 hx
@[to_additive (attr := simp) card_nsmul_eq_zero']
theorem pow_card_eq_one' {G : Type*} [Group G] {x : G} : x ^ Nat.card G = 1 :=
orderOf_dvd_iff_pow_eq_one.mp <| orderOf_dvd_natCard _
#align pow_card_eq_one' pow_card_eq_one'
#align card_nsmul_eq_zero' card_nsmul_eq_zero'
@[to_additive (attr := simp) card_nsmul_eq_zero]
theorem pow_card_eq_one : x ^ Fintype.card G = 1 := by
rw [← Nat.card_eq_fintype_card, pow_card_eq_one']
#align pow_card_eq_one pow_card_eq_one
#align card_nsmul_eq_zero card_nsmul_eq_zero
@[to_additive]
theorem Subgroup.pow_index_mem {G : Type*} [Group G] (H : Subgroup G) [Normal H] (g : G) :
g ^ index H ∈ H := by rw [← eq_one_iff, QuotientGroup.mk_pow H, index, pow_card_eq_one']
#align subgroup.pow_index_mem Subgroup.pow_index_mem
#align add_subgroup.nsmul_index_mem AddSubgroup.nsmul_index_mem
@[to_additive (attr := simp) mod_card_nsmul]
lemma pow_mod_card (a : G) (n : ℕ) : a ^ (n % card G) = a ^ n := by
rw [eq_comm, ← pow_mod_orderOf, ← Nat.mod_mod_of_dvd n orderOf_dvd_card, pow_mod_orderOf]
#align pow_eq_mod_card pow_mod_card
#align nsmul_eq_mod_card mod_card_nsmul
@[to_additive (attr := simp) mod_card_zsmul]
theorem zpow_mod_card (a : G) (n : ℤ) : a ^ (n % Fintype.card G : ℤ) = a ^ n := by
rw [eq_comm, ← zpow_mod_orderOf, ← Int.emod_emod_of_dvd n
(Int.natCast_dvd_natCast.2 orderOf_dvd_card), zpow_mod_orderOf]
#align zpow_eq_mod_card zpow_mod_card
#align zsmul_eq_mod_card mod_card_zsmul
@[to_additive (attr := simp) mod_natCard_nsmul]
lemma pow_mod_natCard (a : G) (n : ℕ) : a ^ (n % Nat.card G) = a ^ n := by
rw [eq_comm, ← pow_mod_orderOf, ← Nat.mod_mod_of_dvd n $ orderOf_dvd_natCard _, pow_mod_orderOf]
@[to_additive (attr := simp) mod_natCard_zsmul]
lemma zpow_mod_natCard (a : G) (n : ℤ) : a ^ (n % Nat.card G : ℤ) = a ^ n := by
rw [eq_comm, ← zpow_mod_orderOf,
← Int.emod_emod_of_dvd n $ Int.natCast_dvd_natCast.2 $ orderOf_dvd_natCard _, zpow_mod_orderOf]
/-- If `gcd(|G|,n)=1` then the `n`th power map is a bijection -/
@[to_additive (attr := simps) "If `gcd(|G|,n)=1` then the smul by `n` is a bijection"]
noncomputable def powCoprime {G : Type*} [Group G] (h : (Nat.card G).Coprime n) : G ≃ G where
toFun g := g ^ n
invFun g := g ^ (Nat.card G).gcdB n
left_inv g := by
have key := congr_arg (g ^ ·) ((Nat.card G).gcd_eq_gcd_ab n)
dsimp only at key
rwa [zpow_add, zpow_mul, zpow_mul, zpow_natCast, zpow_natCast, zpow_natCast, h.gcd_eq_one,
pow_one, pow_card_eq_one', one_zpow, one_mul, eq_comm] at key
right_inv g := by
have key := congr_arg (g ^ ·) ((Nat.card G).gcd_eq_gcd_ab n)
dsimp only at key
rwa [zpow_add, zpow_mul, zpow_mul', zpow_natCast, zpow_natCast, zpow_natCast, h.gcd_eq_one,
pow_one, pow_card_eq_one', one_zpow, one_mul, eq_comm] at key
#align pow_coprime powCoprime
#align nsmul_coprime nsmulCoprime
@[to_additive] -- Porting note (#10618): simp can prove this (so removed simp)
theorem powCoprime_one {G : Type*} [Group G] (h : (Nat.card G).Coprime n) : powCoprime h 1 = 1 :=
one_pow n
#align pow_coprime_one powCoprime_one
#align nsmul_coprime_zero nsmulCoprime_zero
@[to_additive] -- Porting note (#10618): simp can prove this (so removed simp)
theorem powCoprime_inv {G : Type*} [Group G] (h : (Nat.card G).Coprime n) {g : G} :
powCoprime h g⁻¹ = (powCoprime h g)⁻¹ :=
inv_pow g n
#align pow_coprime_inv powCoprime_inv
#align nsmul_coprime_neg nsmulCoprime_neg
@[to_additive Nat.Coprime.nsmul_right_bijective]
lemma Nat.Coprime.pow_left_bijective (hn : (Nat.card G).Coprime n) : Bijective (· ^ n : G → G) :=
(powCoprime hn).bijective
@[to_additive add_inf_eq_bot_of_coprime]
theorem inf_eq_bot_of_coprime {G : Type*} [Group G] {H K : Subgroup G} [Fintype H] [Fintype K]
(h : Nat.Coprime (Fintype.card H) (Fintype.card K)) : H ⊓ K = ⊥ := by
refine (H ⊓ K).eq_bot_iff_forall.mpr fun x hx => ?_
rw [← orderOf_eq_one_iff, ← Nat.dvd_one, ← h.gcd_eq_one, Nat.dvd_gcd_iff]
exact
⟨(congr_arg (· ∣ Fintype.card H) (orderOf_coe ⟨x, hx.1⟩)).mpr orderOf_dvd_card,
(congr_arg (· ∣ Fintype.card K) (orderOf_coe ⟨x, hx.2⟩)).mpr orderOf_dvd_card⟩
#align inf_eq_bot_of_coprime inf_eq_bot_of_coprime
#align add_inf_eq_bot_of_coprime add_inf_eq_bot_of_coprime
/- TODO: Generalise to `Submonoid.powers`. -/
@[to_additive]
theorem image_range_orderOf [DecidableEq G] :
Finset.image (fun i => x ^ i) (Finset.range (orderOf x)) = (zpowers x : Set G).toFinset := by
ext x
rw [Set.mem_toFinset, SetLike.mem_coe, mem_zpowers_iff_mem_range_orderOf]
#align image_range_order_of image_range_orderOf
#align image_range_add_order_of image_range_addOrderOf
/- TODO: Generalise to `Finite` + `CancelMonoid`. -/
@[to_additive gcd_nsmul_card_eq_zero_iff]
theorem pow_gcd_card_eq_one_iff : x ^ n = 1 ↔ x ^ gcd n (Fintype.card G) = 1 :=
⟨fun h => pow_gcd_eq_one _ h <| pow_card_eq_one, fun h => by
let ⟨m, hm⟩ := gcd_dvd_left n (Fintype.card G)
rw [hm, pow_mul, h, one_pow]⟩
#align pow_gcd_card_eq_one_iff pow_gcd_card_eq_one_iff
#align gcd_nsmul_card_eq_zero_iff gcd_nsmul_card_eq_zero_iff
end FiniteGroup
section PowIsSubgroup
/-- A nonempty idempotent subset of a finite cancellative monoid is a submonoid -/
@[to_additive "A nonempty idempotent subset of a finite cancellative add monoid is a submonoid"]
def submonoidOfIdempotent {M : Type*} [LeftCancelMonoid M] [Finite M] (S : Set M)
(hS1 : S.Nonempty) (hS2 : S * S = S) : Submonoid M :=
have pow_mem : ∀ a : M, a ∈ S → ∀ n : ℕ, a ^ (n + 1) ∈ S := fun a ha =>
Nat.rec (by rwa [Nat.zero_eq, zero_add, pow_one]) fun n ih =>
(congr_arg₂ (· ∈ ·) (pow_succ a (n + 1)).symm hS2).mp (Set.mul_mem_mul ih ha)
{ carrier := S
one_mem' := by
obtain ⟨a, ha⟩ := hS1
rw [← pow_orderOf_eq_one a, ← tsub_add_cancel_of_le (succ_le_of_lt (orderOf_pos a))]
exact pow_mem a ha (orderOf a - 1)
mul_mem' := fun ha hb => (congr_arg₂ (· ∈ ·) rfl hS2).mp (Set.mul_mem_mul ha hb) }
#align submonoid_of_idempotent submonoidOfIdempotent
#align add_submonoid_of_idempotent addSubmonoidOfIdempotent
/-- A nonempty idempotent subset of a finite group is a subgroup -/
@[to_additive "A nonempty idempotent subset of a finite add group is a subgroup"]
def subgroupOfIdempotent {G : Type*} [Group G] [Finite G] (S : Set G) (hS1 : S.Nonempty)
(hS2 : S * S = S) : Subgroup G :=
{ submonoidOfIdempotent S hS1 hS2 with
carrier := S
inv_mem' := fun {a} ha => show a⁻¹ ∈ submonoidOfIdempotent S hS1 hS2 by
rw [← one_mul a⁻¹, ← pow_one a, ← pow_orderOf_eq_one a, ← pow_sub a (orderOf_pos a)]
exact pow_mem ha (orderOf a - 1) }
#align subgroup_of_idempotent subgroupOfIdempotent
#align add_subgroup_of_idempotent addSubgroupOfIdempotent
/-- If `S` is a nonempty subset of a finite group `G`, then `S ^ |G|` is a subgroup -/
@[to_additive (attr := simps!) smulCardAddSubgroup
"If `S` is a nonempty subset of a finite add group `G`, then `|G| • S` is a subgroup"]
def powCardSubgroup {G : Type*} [Group G] [Fintype G] (S : Set G) (hS : S.Nonempty) : Subgroup G :=
have one_mem : (1 : G) ∈ S ^ Fintype.card G := by
obtain ⟨a, ha⟩ := hS
rw [← pow_card_eq_one]
exact Set.pow_mem_pow ha (Fintype.card G)
subgroupOfIdempotent (S ^ Fintype.card G) ⟨1, one_mem⟩ <| by
classical
apply (Set.eq_of_subset_of_card_le (Set.subset_mul_left _ one_mem) (ge_of_eq _)).symm
simp_rw [← pow_add,
Group.card_pow_eq_card_pow_card_univ S (Fintype.card G + Fintype.card G) le_add_self]
#align pow_card_subgroup powCardSubgroup
#align smul_card_add_subgroup smulCardAddSubgroup
end PowIsSubgroup
section LinearOrderedSemiring
variable [LinearOrderedSemiring G] {a : G}
protected lemma IsOfFinOrder.eq_one (ha₀ : 0 ≤ a) (ha : IsOfFinOrder a) : a = 1 := by
obtain ⟨n, hn, ha⟩ := ha.exists_pow_eq_one
exact (pow_eq_one_iff_of_nonneg ha₀ hn.ne').1 ha
end LinearOrderedSemiring
section LinearOrderedRing
variable [LinearOrderedRing G] {a x : G}
protected lemma IsOfFinOrder.eq_neg_one (ha₀ : a ≤ 0) (ha : IsOfFinOrder a) : a = -1 :=
(sq_eq_one_iff.1 <| ha.pow.eq_one <| sq_nonneg a).resolve_left <| by
rintro rfl; exact one_pos.not_le ha₀
theorem orderOf_abs_ne_one (h : |x| ≠ 1) : orderOf x = 0 := by
rw [orderOf_eq_zero_iff']
intro n hn hx
replace hx : |x| ^ n = 1 := by simpa only [abs_one, abs_pow] using congr_arg abs hx
cases' h.lt_or_lt with h h
· exact ((pow_lt_one (abs_nonneg x) h hn.ne').ne hx).elim
· exact ((one_lt_pow h hn.ne').ne' hx).elim
#align order_of_abs_ne_one orderOf_abs_ne_one
theorem LinearOrderedRing.orderOf_le_two : orderOf x ≤ 2 := by
cases' ne_or_eq |x| 1 with h h
· simp [orderOf_abs_ne_one h]
rcases eq_or_eq_neg_of_abs_eq h with (rfl | rfl)
· simp
apply orderOf_le_of_pow_eq_one <;> norm_num
#align linear_ordered_ring.order_of_le_two LinearOrderedRing.orderOf_le_two
end LinearOrderedRing
section Prod
variable [Monoid α] [Monoid β] {x : α × β} {a : α} {b : β}
@[to_additive]
protected theorem Prod.orderOf (x : α × β) : orderOf x = (orderOf x.1).lcm (orderOf x.2) :=
minimalPeriod_prod_map _ _ _
#align prod.order_of Prod.orderOf
#align prod.add_order_of Prod.addOrderOf
@[deprecated (since := "2024-02-21")] alias Prod.add_orderOf := Prod.addOrderOf
@[to_additive]
theorem orderOf_fst_dvd_orderOf : orderOf x.1 ∣ orderOf x :=
minimalPeriod_fst_dvd
#align order_of_fst_dvd_order_of orderOf_fst_dvd_orderOf
#align add_order_of_fst_dvd_add_order_of addOrderOf_fst_dvd_addOrderOf
@[deprecated (since := "2024-02-21")]
alias add_orderOf_fst_dvd_add_orderOf := addOrderOf_fst_dvd_addOrderOf
@[to_additive]
theorem orderOf_snd_dvd_orderOf : orderOf x.2 ∣ orderOf x :=
minimalPeriod_snd_dvd
#align order_of_snd_dvd_order_of orderOf_snd_dvd_orderOf
#align add_order_of_snd_dvd_add_order_of addOrderOf_snd_dvd_addOrderOf
@[deprecated (since := "2024-02-21")] alias
add_orderOf_snd_dvd_add_orderOf := addOrderOf_snd_dvd_addOrderOf
@[to_additive]
theorem IsOfFinOrder.fst {x : α × β} (hx : IsOfFinOrder x) : IsOfFinOrder x.1 :=
hx.mono orderOf_fst_dvd_orderOf
#align is_of_fin_order.fst IsOfFinOrder.fst
#align is_of_fin_add_order.fst IsOfFinAddOrder.fst
@[to_additive]
theorem IsOfFinOrder.snd {x : α × β} (hx : IsOfFinOrder x) : IsOfFinOrder x.2 :=
hx.mono orderOf_snd_dvd_orderOf
#align is_of_fin_order.snd IsOfFinOrder.snd
#align is_of_fin_add_order.snd IsOfFinAddOrder.snd
@[to_additive IsOfFinAddOrder.prod_mk]
| Mathlib/GroupTheory/OrderOfElement.lean | 1,301 | 1,302 | theorem IsOfFinOrder.prod_mk : IsOfFinOrder a → IsOfFinOrder b → IsOfFinOrder (a, b) := by |
simpa only [← orderOf_pos_iff, Prod.orderOf] using Nat.lcm_pos
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Algebra.Group.Indicator
import Mathlib.Data.Finset.Piecewise
import Mathlib.Data.Finset.Preimage
#align_import algebra.big_operators.basic from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# Big operators
In this file we define products and sums indexed by finite sets (specifically, `Finset`).
## Notation
We introduce the following notation.
Let `s` be a `Finset α`, and `f : α → β` a function.
* `∏ x ∈ s, f x` is notation for `Finset.prod s f` (assuming `β` is a `CommMonoid`)
* `∑ x ∈ s, f x` is notation for `Finset.sum s f` (assuming `β` is an `AddCommMonoid`)
* `∏ x, f x` is notation for `Finset.prod Finset.univ f`
(assuming `α` is a `Fintype` and `β` is a `CommMonoid`)
* `∑ x, f x` is notation for `Finset.sum Finset.univ f`
(assuming `α` is a `Fintype` and `β` is an `AddCommMonoid`)
## Implementation Notes
The first arguments in all definitions and lemmas is the codomain of the function of the big
operator. This is necessary for the heuristic in `@[to_additive]`.
See the documentation of `to_additive.attr` for more information.
-/
-- TODO
-- assert_not_exists AddCommMonoidWithOne
assert_not_exists MonoidWithZero
assert_not_exists MulAction
variable {ι κ α β γ : Type*}
open Fin Function
namespace Finset
/-- `∏ x ∈ s, f x` is the product of `f x`
as `x` ranges over the elements of the finite set `s`.
-/
@[to_additive "`∑ x ∈ s, f x` is the sum of `f x` as `x` ranges over the elements
of the finite set `s`."]
protected def prod [CommMonoid β] (s : Finset α) (f : α → β) : β :=
(s.1.map f).prod
#align finset.prod Finset.prod
#align finset.sum Finset.sum
@[to_additive (attr := simp)]
theorem prod_mk [CommMonoid β] (s : Multiset α) (hs : s.Nodup) (f : α → β) :
(⟨s, hs⟩ : Finset α).prod f = (s.map f).prod :=
rfl
#align finset.prod_mk Finset.prod_mk
#align finset.sum_mk Finset.sum_mk
@[to_additive (attr := simp)]
theorem prod_val [CommMonoid α] (s : Finset α) : s.1.prod = s.prod id := by
rw [Finset.prod, Multiset.map_id]
#align finset.prod_val Finset.prod_val
#align finset.sum_val Finset.sum_val
end Finset
library_note "operator precedence of big operators"/--
There is no established mathematical convention
for the operator precedence of big operators like `∏` and `∑`.
We will have to make a choice.
Online discussions, such as https://math.stackexchange.com/q/185538/30839
seem to suggest that `∏` and `∑` should have the same precedence,
and that this should be somewhere between `*` and `+`.
The latter have precedence levels `70` and `65` respectively,
and we therefore choose the level `67`.
In practice, this means that parentheses should be placed as follows:
```lean
∑ k ∈ K, (a k + b k) = ∑ k ∈ K, a k + ∑ k ∈ K, b k →
∏ k ∈ K, a k * b k = (∏ k ∈ K, a k) * (∏ k ∈ K, b k)
```
(Example taken from page 490 of Knuth's *Concrete Mathematics*.)
-/
namespace BigOperators
open Batteries.ExtendedBinder Lean Meta
-- TODO: contribute this modification back to `extBinder`
/-- A `bigOpBinder` is like an `extBinder` and has the form `x`, `x : ty`, or `x pred`
where `pred` is a `binderPred` like `< 2`.
Unlike `extBinder`, `x` is a term. -/
syntax bigOpBinder := term:max ((" : " term) <|> binderPred)?
/-- A BigOperator binder in parentheses -/
syntax bigOpBinderParenthesized := " (" bigOpBinder ")"
/-- A list of parenthesized binders -/
syntax bigOpBinderCollection := bigOpBinderParenthesized+
/-- A single (unparenthesized) binder, or a list of parenthesized binders -/
syntax bigOpBinders := bigOpBinderCollection <|> (ppSpace bigOpBinder)
/-- Collects additional binder/Finset pairs for the given `bigOpBinder`.
Note: this is not extensible at the moment, unlike the usual `bigOpBinder` expansions. -/
def processBigOpBinder (processed : (Array (Term × Term)))
(binder : TSyntax ``bigOpBinder) : MacroM (Array (Term × Term)) :=
set_option hygiene false in
withRef binder do
match binder with
| `(bigOpBinder| $x:term) =>
match x with
| `(($a + $b = $n)) => -- Maybe this is too cute.
return processed |>.push (← `(⟨$a, $b⟩), ← `(Finset.Nat.antidiagonal $n))
| _ => return processed |>.push (x, ← ``(Finset.univ))
| `(bigOpBinder| $x : $t) => return processed |>.push (x, ← ``((Finset.univ : Finset $t)))
| `(bigOpBinder| $x ∈ $s) => return processed |>.push (x, ← `(finset% $s))
| `(bigOpBinder| $x < $n) => return processed |>.push (x, ← `(Finset.Iio $n))
| `(bigOpBinder| $x ≤ $n) => return processed |>.push (x, ← `(Finset.Iic $n))
| `(bigOpBinder| $x > $n) => return processed |>.push (x, ← `(Finset.Ioi $n))
| `(bigOpBinder| $x ≥ $n) => return processed |>.push (x, ← `(Finset.Ici $n))
| _ => Macro.throwUnsupported
/-- Collects the binder/Finset pairs for the given `bigOpBinders`. -/
def processBigOpBinders (binders : TSyntax ``bigOpBinders) :
MacroM (Array (Term × Term)) :=
match binders with
| `(bigOpBinders| $b:bigOpBinder) => processBigOpBinder #[] b
| `(bigOpBinders| $[($bs:bigOpBinder)]*) => bs.foldlM processBigOpBinder #[]
| _ => Macro.throwUnsupported
/-- Collect the binderIdents into a `⟨...⟩` expression. -/
def bigOpBindersPattern (processed : (Array (Term × Term))) :
MacroM Term := do
let ts := processed.map Prod.fst
if ts.size == 1 then
return ts[0]!
else
`(⟨$ts,*⟩)
/-- Collect the terms into a product of sets. -/
def bigOpBindersProd (processed : (Array (Term × Term))) :
MacroM Term := do
if processed.isEmpty then
`((Finset.univ : Finset Unit))
else if processed.size == 1 then
return processed[0]!.2
else
processed.foldrM (fun s p => `(SProd.sprod $(s.2) $p)) processed.back.2
(start := processed.size - 1)
/--
- `∑ x, f x` is notation for `Finset.sum Finset.univ f`. It is the sum of `f x`,
where `x` ranges over the finite domain of `f`.
- `∑ x ∈ s, f x` is notation for `Finset.sum s f`. It is the sum of `f x`,
where `x` ranges over the finite set `s` (either a `Finset` or a `Set` with a `Fintype` instance).
- `∑ x ∈ s with p x, f x` is notation for `Finset.sum (Finset.filter p s) f`.
- `∑ (x ∈ s) (y ∈ t), f x y` is notation for `Finset.sum (s ×ˢ t) (fun ⟨x, y⟩ ↦ f x y)`.
These support destructuring, for example `∑ ⟨x, y⟩ ∈ s ×ˢ t, f x y`.
Notation: `"∑" bigOpBinders* ("with" term)? "," term` -/
syntax (name := bigsum) "∑ " bigOpBinders ("with " term)? ", " term:67 : term
/--
- `∏ x, f x` is notation for `Finset.prod Finset.univ f`. It is the product of `f x`,
where `x` ranges over the finite domain of `f`.
- `∏ x ∈ s, f x` is notation for `Finset.prod s f`. It is the product of `f x`,
where `x` ranges over the finite set `s` (either a `Finset` or a `Set` with a `Fintype` instance).
- `∏ x ∈ s with p x, f x` is notation for `Finset.prod (Finset.filter p s) f`.
- `∏ (x ∈ s) (y ∈ t), f x y` is notation for `Finset.prod (s ×ˢ t) (fun ⟨x, y⟩ ↦ f x y)`.
These support destructuring, for example `∏ ⟨x, y⟩ ∈ s ×ˢ t, f x y`.
Notation: `"∏" bigOpBinders* ("with" term)? "," term` -/
syntax (name := bigprod) "∏ " bigOpBinders ("with " term)? ", " term:67 : term
macro_rules (kind := bigsum)
| `(∑ $bs:bigOpBinders $[with $p?]?, $v) => do
let processed ← processBigOpBinders bs
let x ← bigOpBindersPattern processed
let s ← bigOpBindersProd processed
match p? with
| some p => `(Finset.sum (Finset.filter (fun $x ↦ $p) $s) (fun $x ↦ $v))
| none => `(Finset.sum $s (fun $x ↦ $v))
macro_rules (kind := bigprod)
| `(∏ $bs:bigOpBinders $[with $p?]?, $v) => do
let processed ← processBigOpBinders bs
let x ← bigOpBindersPattern processed
let s ← bigOpBindersProd processed
match p? with
| some p => `(Finset.prod (Finset.filter (fun $x ↦ $p) $s) (fun $x ↦ $v))
| none => `(Finset.prod $s (fun $x ↦ $v))
/-- (Deprecated, use `∑ x ∈ s, f x`)
`∑ x in s, f x` is notation for `Finset.sum s f`. It is the sum of `f x`,
where `x` ranges over the finite set `s`. -/
syntax (name := bigsumin) "∑ " extBinder " in " term ", " term:67 : term
macro_rules (kind := bigsumin)
| `(∑ $x:ident in $s, $r) => `(∑ $x:ident ∈ $s, $r)
| `(∑ $x:ident : $t in $s, $r) => `(∑ $x:ident ∈ ($s : Finset $t), $r)
/-- (Deprecated, use `∏ x ∈ s, f x`)
`∏ x in s, f x` is notation for `Finset.prod s f`. It is the product of `f x`,
where `x` ranges over the finite set `s`. -/
syntax (name := bigprodin) "∏ " extBinder " in " term ", " term:67 : term
macro_rules (kind := bigprodin)
| `(∏ $x:ident in $s, $r) => `(∏ $x:ident ∈ $s, $r)
| `(∏ $x:ident : $t in $s, $r) => `(∏ $x:ident ∈ ($s : Finset $t), $r)
open Lean Meta Parser.Term PrettyPrinter.Delaborator SubExpr
open Batteries.ExtendedBinder
/-- Delaborator for `Finset.prod`. The `pp.piBinderTypes` option controls whether
to show the domain type when the product is over `Finset.univ`. -/
@[delab app.Finset.prod] def delabFinsetProd : Delab :=
whenPPOption getPPNotation <| withOverApp 5 <| do
let #[_, _, _, s, f] := (← getExpr).getAppArgs | failure
guard <| f.isLambda
let ppDomain ← getPPOption getPPPiBinderTypes
let (i, body) ← withAppArg <| withBindingBodyUnusedName fun i => do
return (i, ← delab)
if s.isAppOfArity ``Finset.univ 2 then
let binder ←
if ppDomain then
let ty ← withNaryArg 0 delab
`(bigOpBinder| $(.mk i):ident : $ty)
else
`(bigOpBinder| $(.mk i):ident)
`(∏ $binder:bigOpBinder, $body)
else
let ss ← withNaryArg 3 <| delab
`(∏ $(.mk i):ident ∈ $ss, $body)
/-- Delaborator for `Finset.sum`. The `pp.piBinderTypes` option controls whether
to show the domain type when the sum is over `Finset.univ`. -/
@[delab app.Finset.sum] def delabFinsetSum : Delab :=
whenPPOption getPPNotation <| withOverApp 5 <| do
let #[_, _, _, s, f] := (← getExpr).getAppArgs | failure
guard <| f.isLambda
let ppDomain ← getPPOption getPPPiBinderTypes
let (i, body) ← withAppArg <| withBindingBodyUnusedName fun i => do
return (i, ← delab)
if s.isAppOfArity ``Finset.univ 2 then
let binder ←
if ppDomain then
let ty ← withNaryArg 0 delab
`(bigOpBinder| $(.mk i):ident : $ty)
else
`(bigOpBinder| $(.mk i):ident)
`(∑ $binder:bigOpBinder, $body)
else
let ss ← withNaryArg 3 <| delab
`(∑ $(.mk i):ident ∈ $ss, $body)
end BigOperators
namespace Finset
variable {s s₁ s₂ : Finset α} {a : α} {f g : α → β}
@[to_additive]
theorem prod_eq_multiset_prod [CommMonoid β] (s : Finset α) (f : α → β) :
∏ x ∈ s, f x = (s.1.map f).prod :=
rfl
#align finset.prod_eq_multiset_prod Finset.prod_eq_multiset_prod
#align finset.sum_eq_multiset_sum Finset.sum_eq_multiset_sum
@[to_additive (attr := simp)]
lemma prod_map_val [CommMonoid β] (s : Finset α) (f : α → β) : (s.1.map f).prod = ∏ a ∈ s, f a :=
rfl
#align finset.prod_map_val Finset.prod_map_val
#align finset.sum_map_val Finset.sum_map_val
@[to_additive]
theorem prod_eq_fold [CommMonoid β] (s : Finset α) (f : α → β) :
∏ x ∈ s, f x = s.fold ((· * ·) : β → β → β) 1 f :=
rfl
#align finset.prod_eq_fold Finset.prod_eq_fold
#align finset.sum_eq_fold Finset.sum_eq_fold
@[simp]
theorem sum_multiset_singleton (s : Finset α) : (s.sum fun x => {x}) = s.val := by
simp only [sum_eq_multiset_sum, Multiset.sum_map_singleton]
#align finset.sum_multiset_singleton Finset.sum_multiset_singleton
end Finset
@[to_additive (attr := simp)]
theorem map_prod [CommMonoid β] [CommMonoid γ] {G : Type*} [FunLike G β γ] [MonoidHomClass G β γ]
(g : G) (f : α → β) (s : Finset α) : g (∏ x ∈ s, f x) = ∏ x ∈ s, g (f x) := by
simp only [Finset.prod_eq_multiset_prod, map_multiset_prod, Multiset.map_map]; rfl
#align map_prod map_prod
#align map_sum map_sum
@[to_additive]
theorem MonoidHom.coe_finset_prod [MulOneClass β] [CommMonoid γ] (f : α → β →* γ) (s : Finset α) :
⇑(∏ x ∈ s, f x) = ∏ x ∈ s, ⇑(f x) :=
map_prod (MonoidHom.coeFn β γ) _ _
#align monoid_hom.coe_finset_prod MonoidHom.coe_finset_prod
#align add_monoid_hom.coe_finset_sum AddMonoidHom.coe_finset_sum
/-- See also `Finset.prod_apply`, with the same conclusion but with the weaker hypothesis
`f : α → β → γ` -/
@[to_additive (attr := simp)
"See also `Finset.sum_apply`, with the same conclusion but with the weaker hypothesis
`f : α → β → γ`"]
theorem MonoidHom.finset_prod_apply [MulOneClass β] [CommMonoid γ] (f : α → β →* γ) (s : Finset α)
(b : β) : (∏ x ∈ s, f x) b = ∏ x ∈ s, f x b :=
map_prod (MonoidHom.eval b) _ _
#align monoid_hom.finset_prod_apply MonoidHom.finset_prod_apply
#align add_monoid_hom.finset_sum_apply AddMonoidHom.finset_sum_apply
variable {s s₁ s₂ : Finset α} {a : α} {f g : α → β}
namespace Finset
section CommMonoid
variable [CommMonoid β]
@[to_additive (attr := simp)]
theorem prod_empty : ∏ x ∈ ∅, f x = 1 :=
rfl
#align finset.prod_empty Finset.prod_empty
#align finset.sum_empty Finset.sum_empty
@[to_additive]
theorem prod_of_empty [IsEmpty α] (s : Finset α) : ∏ i ∈ s, f i = 1 := by
rw [eq_empty_of_isEmpty s, prod_empty]
#align finset.prod_of_empty Finset.prod_of_empty
#align finset.sum_of_empty Finset.sum_of_empty
@[to_additive (attr := simp)]
theorem prod_cons (h : a ∉ s) : ∏ x ∈ cons a s h, f x = f a * ∏ x ∈ s, f x :=
fold_cons h
#align finset.prod_cons Finset.prod_cons
#align finset.sum_cons Finset.sum_cons
@[to_additive (attr := simp)]
theorem prod_insert [DecidableEq α] : a ∉ s → ∏ x ∈ insert a s, f x = f a * ∏ x ∈ s, f x :=
fold_insert
#align finset.prod_insert Finset.prod_insert
#align finset.sum_insert Finset.sum_insert
/-- The product of `f` over `insert a s` is the same as
the product over `s`, as long as `a` is in `s` or `f a = 1`. -/
@[to_additive (attr := simp) "The sum of `f` over `insert a s` is the same as
the sum over `s`, as long as `a` is in `s` or `f a = 0`."]
theorem prod_insert_of_eq_one_if_not_mem [DecidableEq α] (h : a ∉ s → f a = 1) :
∏ x ∈ insert a s, f x = ∏ x ∈ s, f x := by
by_cases hm : a ∈ s
· simp_rw [insert_eq_of_mem hm]
· rw [prod_insert hm, h hm, one_mul]
#align finset.prod_insert_of_eq_one_if_not_mem Finset.prod_insert_of_eq_one_if_not_mem
#align finset.sum_insert_of_eq_zero_if_not_mem Finset.sum_insert_of_eq_zero_if_not_mem
/-- The product of `f` over `insert a s` is the same as
the product over `s`, as long as `f a = 1`. -/
@[to_additive (attr := simp) "The sum of `f` over `insert a s` is the same as
the sum over `s`, as long as `f a = 0`."]
theorem prod_insert_one [DecidableEq α] (h : f a = 1) : ∏ x ∈ insert a s, f x = ∏ x ∈ s, f x :=
prod_insert_of_eq_one_if_not_mem fun _ => h
#align finset.prod_insert_one Finset.prod_insert_one
#align finset.sum_insert_zero Finset.sum_insert_zero
@[to_additive]
theorem prod_insert_div {M : Type*} [CommGroup M] [DecidableEq α] (ha : a ∉ s) {f : α → M} :
(∏ x ∈ insert a s, f x) / f a = ∏ x ∈ s, f x := by simp [ha]
@[to_additive (attr := simp)]
theorem prod_singleton (f : α → β) (a : α) : ∏ x ∈ singleton a, f x = f a :=
Eq.trans fold_singleton <| mul_one _
#align finset.prod_singleton Finset.prod_singleton
#align finset.sum_singleton Finset.sum_singleton
@[to_additive]
theorem prod_pair [DecidableEq α] {a b : α} (h : a ≠ b) :
(∏ x ∈ ({a, b} : Finset α), f x) = f a * f b := by
rw [prod_insert (not_mem_singleton.2 h), prod_singleton]
#align finset.prod_pair Finset.prod_pair
#align finset.sum_pair Finset.sum_pair
@[to_additive (attr := simp)]
theorem prod_const_one : (∏ _x ∈ s, (1 : β)) = 1 := by
simp only [Finset.prod, Multiset.map_const', Multiset.prod_replicate, one_pow]
#align finset.prod_const_one Finset.prod_const_one
#align finset.sum_const_zero Finset.sum_const_zero
@[to_additive (attr := simp)]
theorem prod_image [DecidableEq α] {s : Finset γ} {g : γ → α} :
(∀ x ∈ s, ∀ y ∈ s, g x = g y → x = y) → ∏ x ∈ s.image g, f x = ∏ x ∈ s, f (g x) :=
fold_image
#align finset.prod_image Finset.prod_image
#align finset.sum_image Finset.sum_image
@[to_additive (attr := simp)]
theorem prod_map (s : Finset α) (e : α ↪ γ) (f : γ → β) :
∏ x ∈ s.map e, f x = ∏ x ∈ s, f (e x) := by
rw [Finset.prod, Finset.map_val, Multiset.map_map]; rfl
#align finset.prod_map Finset.prod_map
#align finset.sum_map Finset.sum_map
@[to_additive]
lemma prod_attach (s : Finset α) (f : α → β) : ∏ x ∈ s.attach, f x = ∏ x ∈ s, f x := by
classical rw [← prod_image Subtype.coe_injective.injOn, attach_image_val]
#align finset.prod_attach Finset.prod_attach
#align finset.sum_attach Finset.sum_attach
@[to_additive (attr := congr)]
theorem prod_congr (h : s₁ = s₂) : (∀ x ∈ s₂, f x = g x) → s₁.prod f = s₂.prod g := by
rw [h]; exact fold_congr
#align finset.prod_congr Finset.prod_congr
#align finset.sum_congr Finset.sum_congr
@[to_additive]
theorem prod_eq_one {f : α → β} {s : Finset α} (h : ∀ x ∈ s, f x = 1) : ∏ x ∈ s, f x = 1 :=
calc
∏ x ∈ s, f x = ∏ _x ∈ s, 1 := Finset.prod_congr rfl h
_ = 1 := Finset.prod_const_one
#align finset.prod_eq_one Finset.prod_eq_one
#align finset.sum_eq_zero Finset.sum_eq_zero
@[to_additive]
theorem prod_disjUnion (h) :
∏ x ∈ s₁.disjUnion s₂ h, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x := by
refine Eq.trans ?_ (fold_disjUnion h)
rw [one_mul]
rfl
#align finset.prod_disj_union Finset.prod_disjUnion
#align finset.sum_disj_union Finset.sum_disjUnion
@[to_additive]
theorem prod_disjiUnion (s : Finset ι) (t : ι → Finset α) (h) :
∏ x ∈ s.disjiUnion t h, f x = ∏ i ∈ s, ∏ x ∈ t i, f x := by
refine Eq.trans ?_ (fold_disjiUnion h)
dsimp [Finset.prod, Multiset.prod, Multiset.fold, Finset.disjUnion, Finset.fold]
congr
exact prod_const_one.symm
#align finset.prod_disj_Union Finset.prod_disjiUnion
#align finset.sum_disj_Union Finset.sum_disjiUnion
@[to_additive]
theorem prod_union_inter [DecidableEq α] :
(∏ x ∈ s₁ ∪ s₂, f x) * ∏ x ∈ s₁ ∩ s₂, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x :=
fold_union_inter
#align finset.prod_union_inter Finset.prod_union_inter
#align finset.sum_union_inter Finset.sum_union_inter
@[to_additive]
theorem prod_union [DecidableEq α] (h : Disjoint s₁ s₂) :
∏ x ∈ s₁ ∪ s₂, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x := by
rw [← prod_union_inter, disjoint_iff_inter_eq_empty.mp h]; exact (mul_one _).symm
#align finset.prod_union Finset.prod_union
#align finset.sum_union Finset.sum_union
@[to_additive]
theorem prod_filter_mul_prod_filter_not
(s : Finset α) (p : α → Prop) [DecidablePred p] [∀ x, Decidable (¬p x)] (f : α → β) :
(∏ x ∈ s.filter p, f x) * ∏ x ∈ s.filter fun x => ¬p x, f x = ∏ x ∈ s, f x := by
have := Classical.decEq α
rw [← prod_union (disjoint_filter_filter_neg s s p), filter_union_filter_neg_eq]
#align finset.prod_filter_mul_prod_filter_not Finset.prod_filter_mul_prod_filter_not
#align finset.sum_filter_add_sum_filter_not Finset.sum_filter_add_sum_filter_not
section ToList
@[to_additive (attr := simp)]
theorem prod_to_list (s : Finset α) (f : α → β) : (s.toList.map f).prod = s.prod f := by
rw [Finset.prod, ← Multiset.prod_coe, ← Multiset.map_coe, Finset.coe_toList]
#align finset.prod_to_list Finset.prod_to_list
#align finset.sum_to_list Finset.sum_to_list
end ToList
@[to_additive]
theorem _root_.Equiv.Perm.prod_comp (σ : Equiv.Perm α) (s : Finset α) (f : α → β)
(hs : { a | σ a ≠ a } ⊆ s) : (∏ x ∈ s, f (σ x)) = ∏ x ∈ s, f x := by
convert (prod_map s σ.toEmbedding f).symm
exact (map_perm hs).symm
#align equiv.perm.prod_comp Equiv.Perm.prod_comp
#align equiv.perm.sum_comp Equiv.Perm.sum_comp
@[to_additive]
theorem _root_.Equiv.Perm.prod_comp' (σ : Equiv.Perm α) (s : Finset α) (f : α → α → β)
(hs : { a | σ a ≠ a } ⊆ s) : (∏ x ∈ s, f (σ x) x) = ∏ x ∈ s, f x (σ.symm x) := by
convert σ.prod_comp s (fun x => f x (σ.symm x)) hs
rw [Equiv.symm_apply_apply]
#align equiv.perm.prod_comp' Equiv.Perm.prod_comp'
#align equiv.perm.sum_comp' Equiv.Perm.sum_comp'
/-- A product over all subsets of `s ∪ {x}` is obtained by multiplying the product over all subsets
of `s`, and over all subsets of `s` to which one adds `x`. -/
@[to_additive "A sum over all subsets of `s ∪ {x}` is obtained by summing the sum over all subsets
of `s`, and over all subsets of `s` to which one adds `x`."]
lemma prod_powerset_insert [DecidableEq α] (ha : a ∉ s) (f : Finset α → β) :
∏ t ∈ (insert a s).powerset, f t =
(∏ t ∈ s.powerset, f t) * ∏ t ∈ s.powerset, f (insert a t) := by
rw [powerset_insert, prod_union, prod_image]
· exact insert_erase_invOn.2.injOn.mono fun t ht ↦ not_mem_mono (mem_powerset.1 ht) ha
· aesop (add simp [disjoint_left, insert_subset_iff])
#align finset.prod_powerset_insert Finset.prod_powerset_insert
#align finset.sum_powerset_insert Finset.sum_powerset_insert
/-- A product over all subsets of `s ∪ {x}` is obtained by multiplying the product over all subsets
of `s`, and over all subsets of `s` to which one adds `x`. -/
@[to_additive "A sum over all subsets of `s ∪ {x}` is obtained by summing the sum over all subsets
of `s`, and over all subsets of `s` to which one adds `x`."]
lemma prod_powerset_cons (ha : a ∉ s) (f : Finset α → β) :
∏ t ∈ (s.cons a ha).powerset, f t = (∏ t ∈ s.powerset, f t) *
∏ t ∈ s.powerset.attach, f (cons a t $ not_mem_mono (mem_powerset.1 t.2) ha) := by
classical
simp_rw [cons_eq_insert]
rw [prod_powerset_insert ha, prod_attach _ fun t ↦ f (insert a t)]
/-- A product over `powerset s` is equal to the double product over sets of subsets of `s` with
`card s = k`, for `k = 1, ..., card s`. -/
@[to_additive "A sum over `powerset s` is equal to the double sum over sets of subsets of `s` with
`card s = k`, for `k = 1, ..., card s`"]
lemma prod_powerset (s : Finset α) (f : Finset α → β) :
∏ t ∈ powerset s, f t = ∏ j ∈ range (card s + 1), ∏ t ∈ powersetCard j s, f t := by
rw [powerset_card_disjiUnion, prod_disjiUnion]
#align finset.prod_powerset Finset.prod_powerset
#align finset.sum_powerset Finset.sum_powerset
end CommMonoid
end Finset
section
open Finset
variable [Fintype α] [CommMonoid β]
@[to_additive]
theorem IsCompl.prod_mul_prod {s t : Finset α} (h : IsCompl s t) (f : α → β) :
(∏ i ∈ s, f i) * ∏ i ∈ t, f i = ∏ i, f i :=
(Finset.prod_disjUnion h.disjoint).symm.trans <| by
classical rw [Finset.disjUnion_eq_union, ← Finset.sup_eq_union, h.sup_eq_top]; rfl
#align is_compl.prod_mul_prod IsCompl.prod_mul_prod
#align is_compl.sum_add_sum IsCompl.sum_add_sum
end
namespace Finset
section CommMonoid
variable [CommMonoid β]
/-- Multiplying the products of a function over `s` and over `sᶜ` gives the whole product.
For a version expressed with subtypes, see `Fintype.prod_subtype_mul_prod_subtype`. -/
@[to_additive "Adding the sums of a function over `s` and over `sᶜ` gives the whole sum.
For a version expressed with subtypes, see `Fintype.sum_subtype_add_sum_subtype`. "]
theorem prod_mul_prod_compl [Fintype α] [DecidableEq α] (s : Finset α) (f : α → β) :
(∏ i ∈ s, f i) * ∏ i ∈ sᶜ, f i = ∏ i, f i :=
IsCompl.prod_mul_prod isCompl_compl f
#align finset.prod_mul_prod_compl Finset.prod_mul_prod_compl
#align finset.sum_add_sum_compl Finset.sum_add_sum_compl
@[to_additive]
theorem prod_compl_mul_prod [Fintype α] [DecidableEq α] (s : Finset α) (f : α → β) :
(∏ i ∈ sᶜ, f i) * ∏ i ∈ s, f i = ∏ i, f i :=
(@isCompl_compl _ s _).symm.prod_mul_prod f
#align finset.prod_compl_mul_prod Finset.prod_compl_mul_prod
#align finset.sum_compl_add_sum Finset.sum_compl_add_sum
@[to_additive]
theorem prod_sdiff [DecidableEq α] (h : s₁ ⊆ s₂) :
(∏ x ∈ s₂ \ s₁, f x) * ∏ x ∈ s₁, f x = ∏ x ∈ s₂, f x := by
rw [← prod_union sdiff_disjoint, sdiff_union_of_subset h]
#align finset.prod_sdiff Finset.prod_sdiff
#align finset.sum_sdiff Finset.sum_sdiff
@[to_additive]
theorem prod_subset_one_on_sdiff [DecidableEq α] (h : s₁ ⊆ s₂) (hg : ∀ x ∈ s₂ \ s₁, g x = 1)
(hfg : ∀ x ∈ s₁, f x = g x) : ∏ i ∈ s₁, f i = ∏ i ∈ s₂, g i := by
rw [← prod_sdiff h, prod_eq_one hg, one_mul]
exact prod_congr rfl hfg
#align finset.prod_subset_one_on_sdiff Finset.prod_subset_one_on_sdiff
#align finset.sum_subset_zero_on_sdiff Finset.sum_subset_zero_on_sdiff
@[to_additive]
theorem prod_subset (h : s₁ ⊆ s₂) (hf : ∀ x ∈ s₂, x ∉ s₁ → f x = 1) :
∏ x ∈ s₁, f x = ∏ x ∈ s₂, f x :=
haveI := Classical.decEq α
prod_subset_one_on_sdiff h (by simpa) fun _ _ => rfl
#align finset.prod_subset Finset.prod_subset
#align finset.sum_subset Finset.sum_subset
@[to_additive (attr := simp)]
theorem prod_disj_sum (s : Finset α) (t : Finset γ) (f : Sum α γ → β) :
∏ x ∈ s.disjSum t, f x = (∏ x ∈ s, f (Sum.inl x)) * ∏ x ∈ t, f (Sum.inr x) := by
rw [← map_inl_disjUnion_map_inr, prod_disjUnion, prod_map, prod_map]
rfl
#align finset.prod_disj_sum Finset.prod_disj_sum
#align finset.sum_disj_sum Finset.sum_disj_sum
@[to_additive]
theorem prod_sum_elim (s : Finset α) (t : Finset γ) (f : α → β) (g : γ → β) :
∏ x ∈ s.disjSum t, Sum.elim f g x = (∏ x ∈ s, f x) * ∏ x ∈ t, g x := by simp
#align finset.prod_sum_elim Finset.prod_sum_elim
#align finset.sum_sum_elim Finset.sum_sum_elim
@[to_additive]
theorem prod_biUnion [DecidableEq α] {s : Finset γ} {t : γ → Finset α}
(hs : Set.PairwiseDisjoint (↑s) t) : ∏ x ∈ s.biUnion t, f x = ∏ x ∈ s, ∏ i ∈ t x, f i := by
rw [← disjiUnion_eq_biUnion _ _ hs, prod_disjiUnion]
#align finset.prod_bUnion Finset.prod_biUnion
#align finset.sum_bUnion Finset.sum_biUnion
/-- Product over a sigma type equals the product of fiberwise products. For rewriting
in the reverse direction, use `Finset.prod_sigma'`. -/
@[to_additive "Sum over a sigma type equals the sum of fiberwise sums. For rewriting
in the reverse direction, use `Finset.sum_sigma'`"]
theorem prod_sigma {σ : α → Type*} (s : Finset α) (t : ∀ a, Finset (σ a)) (f : Sigma σ → β) :
∏ x ∈ s.sigma t, f x = ∏ a ∈ s, ∏ s ∈ t a, f ⟨a, s⟩ := by
simp_rw [← disjiUnion_map_sigma_mk, prod_disjiUnion, prod_map, Function.Embedding.sigmaMk_apply]
#align finset.prod_sigma Finset.prod_sigma
#align finset.sum_sigma Finset.sum_sigma
@[to_additive]
theorem prod_sigma' {σ : α → Type*} (s : Finset α) (t : ∀ a, Finset (σ a)) (f : ∀ a, σ a → β) :
(∏ a ∈ s, ∏ s ∈ t a, f a s) = ∏ x ∈ s.sigma t, f x.1 x.2 :=
Eq.symm <| prod_sigma s t fun x => f x.1 x.2
#align finset.prod_sigma' Finset.prod_sigma'
#align finset.sum_sigma' Finset.sum_sigma'
section bij
variable {ι κ α : Type*} [CommMonoid α] {s : Finset ι} {t : Finset κ} {f : ι → α} {g : κ → α}
/-- Reorder a product.
The difference with `Finset.prod_bij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.prod_nbij` is that the bijection is allowed to use membership of the
domain of the product, rather than being a non-dependent function. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_bij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.sum_nbij` is that the bijection is allowed to use membership of the
domain of the sum, rather than being a non-dependent function."]
theorem prod_bij (i : ∀ a ∈ s, κ) (hi : ∀ a ha, i a ha ∈ t)
(i_inj : ∀ a₁ ha₁ a₂ ha₂, i a₁ ha₁ = i a₂ ha₂ → a₁ = a₂)
(i_surj : ∀ b ∈ t, ∃ a ha, i a ha = b) (h : ∀ a ha, f a = g (i a ha)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x :=
congr_arg Multiset.prod (Multiset.map_eq_map_of_bij_of_nodup f g s.2 t.2 i hi i_inj i_surj h)
#align finset.prod_bij Finset.prod_bij
#align finset.sum_bij Finset.sum_bij
/-- Reorder a product.
The difference with `Finset.prod_bij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.prod_nbij'` is that the bijection and its inverse are allowed to use
membership of the domains of the products, rather than being non-dependent functions. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_bij` is that the bijection is specified with an inverse, rather than
as a surjective injection.
The difference with `Finset.sum_nbij'` is that the bijection and its inverse are allowed to use
membership of the domains of the sums, rather than being non-dependent functions."]
theorem prod_bij' (i : ∀ a ∈ s, κ) (j : ∀ a ∈ t, ι) (hi : ∀ a ha, i a ha ∈ t)
(hj : ∀ a ha, j a ha ∈ s) (left_inv : ∀ a ha, j (i a ha) (hi a ha) = a)
(right_inv : ∀ a ha, i (j a ha) (hj a ha) = a) (h : ∀ a ha, f a = g (i a ha)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x := by
refine prod_bij i hi (fun a1 h1 a2 h2 eq ↦ ?_) (fun b hb ↦ ⟨_, hj b hb, right_inv b hb⟩) h
rw [← left_inv a1 h1, ← left_inv a2 h2]
simp only [eq]
#align finset.prod_bij' Finset.prod_bij'
#align finset.sum_bij' Finset.sum_bij'
/-- Reorder a product.
The difference with `Finset.prod_nbij'` is that the bijection is specified as a surjective
injection, rather than by an inverse function.
The difference with `Finset.prod_bij` is that the bijection is a non-dependent function, rather than
being allowed to use membership of the domain of the product. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_nbij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.sum_bij` is that the bijection is a non-dependent function, rather than
being allowed to use membership of the domain of the sum."]
lemma prod_nbij (i : ι → κ) (hi : ∀ a ∈ s, i a ∈ t) (i_inj : (s : Set ι).InjOn i)
(i_surj : (s : Set ι).SurjOn i t) (h : ∀ a ∈ s, f a = g (i a)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x :=
prod_bij (fun a _ ↦ i a) hi i_inj (by simpa using i_surj) h
/-- Reorder a product.
The difference with `Finset.prod_nbij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.prod_bij'` is that the bijection and its inverse are non-dependent
functions, rather than being allowed to use membership of the domains of the products.
The difference with `Finset.prod_equiv` is that bijectivity is only required to hold on the domains
of the products, rather than on the entire types.
-/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_nbij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.sum_bij'` is that the bijection and its inverse are non-dependent
functions, rather than being allowed to use membership of the domains of the sums.
The difference with `Finset.sum_equiv` is that bijectivity is only required to hold on the domains
of the sums, rather than on the entire types."]
lemma prod_nbij' (i : ι → κ) (j : κ → ι) (hi : ∀ a ∈ s, i a ∈ t) (hj : ∀ a ∈ t, j a ∈ s)
(left_inv : ∀ a ∈ s, j (i a) = a) (right_inv : ∀ a ∈ t, i (j a) = a)
(h : ∀ a ∈ s, f a = g (i a)) : ∏ x ∈ s, f x = ∏ x ∈ t, g x :=
prod_bij' (fun a _ ↦ i a) (fun b _ ↦ j b) hi hj left_inv right_inv h
/-- Specialization of `Finset.prod_nbij'` that automatically fills in most arguments.
See `Fintype.prod_equiv` for the version where `s` and `t` are `univ`. -/
@[to_additive "`Specialization of `Finset.sum_nbij'` that automatically fills in most arguments.
See `Fintype.sum_equiv` for the version where `s` and `t` are `univ`."]
lemma prod_equiv (e : ι ≃ κ) (hst : ∀ i, i ∈ s ↔ e i ∈ t) (hfg : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ i ∈ t, g i := by refine prod_nbij' e e.symm ?_ ?_ ?_ ?_ hfg <;> simp [hst]
#align finset.equiv.prod_comp_finset Finset.prod_equiv
#align finset.equiv.sum_comp_finset Finset.sum_equiv
/-- Specialization of `Finset.prod_bij` that automatically fills in most arguments.
See `Fintype.prod_bijective` for the version where `s` and `t` are `univ`. -/
@[to_additive "`Specialization of `Finset.sum_bij` that automatically fills in most arguments.
See `Fintype.sum_bijective` for the version where `s` and `t` are `univ`."]
lemma prod_bijective (e : ι → κ) (he : e.Bijective) (hst : ∀ i, i ∈ s ↔ e i ∈ t)
(hfg : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ i ∈ t, g i := prod_equiv (.ofBijective e he) hst hfg
@[to_additive]
lemma prod_of_injOn (e : ι → κ) (he : Set.InjOn e s) (hest : Set.MapsTo e s t)
(h' : ∀ i ∈ t, i ∉ e '' s → g i = 1) (h : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ j ∈ t, g j := by
classical
exact (prod_nbij e (fun a ↦ mem_image_of_mem e) he (by simp [Set.surjOn_image]) h).trans <|
prod_subset (image_subset_iff.2 hest) <| by simpa using h'
variable [DecidableEq κ]
@[to_additive]
lemma prod_fiberwise_eq_prod_filter (s : Finset ι) (t : Finset κ) (g : ι → κ) (f : ι → α) :
∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s.filter fun i ↦ g i ∈ t, f i := by
rw [← prod_disjiUnion, disjiUnion_filter_eq]
@[to_additive]
lemma prod_fiberwise_eq_prod_filter' (s : Finset ι) (t : Finset κ) (g : ι → κ) (f : κ → α) :
∏ j ∈ t, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s.filter fun i ↦ g i ∈ t, f (g i) := by
calc
_ = ∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f (g i) :=
prod_congr rfl fun j _ ↦ prod_congr rfl fun i hi ↦ by rw [(mem_filter.1 hi).2]
_ = _ := prod_fiberwise_eq_prod_filter _ _ _ _
@[to_additive]
lemma prod_fiberwise_of_maps_to {g : ι → κ} (h : ∀ i ∈ s, g i ∈ t) (f : ι → α) :
∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s, f i := by
rw [← prod_disjiUnion, disjiUnion_filter_eq_of_maps_to h]
#align finset.prod_fiberwise_of_maps_to Finset.prod_fiberwise_of_maps_to
#align finset.sum_fiberwise_of_maps_to Finset.sum_fiberwise_of_maps_to
@[to_additive]
lemma prod_fiberwise_of_maps_to' {g : ι → κ} (h : ∀ i ∈ s, g i ∈ t) (f : κ → α) :
∏ j ∈ t, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s, f (g i) := by
calc
_ = ∏ y ∈ t, ∏ x ∈ s.filter fun x ↦ g x = y, f (g x) :=
prod_congr rfl fun y _ ↦ prod_congr rfl fun x hx ↦ by rw [(mem_filter.1 hx).2]
_ = _ := prod_fiberwise_of_maps_to h _
variable [Fintype κ]
@[to_additive]
lemma prod_fiberwise (s : Finset ι) (g : ι → κ) (f : ι → α) :
∏ j, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s, f i :=
prod_fiberwise_of_maps_to (fun _ _ ↦ mem_univ _) _
#align finset.prod_fiberwise Finset.prod_fiberwise
#align finset.sum_fiberwise Finset.sum_fiberwise
@[to_additive]
lemma prod_fiberwise' (s : Finset ι) (g : ι → κ) (f : κ → α) :
∏ j, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s, f (g i) :=
prod_fiberwise_of_maps_to' (fun _ _ ↦ mem_univ _) _
end bij
/-- Taking a product over `univ.pi t` is the same as taking the product over `Fintype.piFinset t`.
`univ.pi t` and `Fintype.piFinset t` are essentially the same `Finset`, but differ
in the type of their element, `univ.pi t` is a `Finset (Π a ∈ univ, t a)` and
`Fintype.piFinset t` is a `Finset (Π a, t a)`. -/
@[to_additive "Taking a sum over `univ.pi t` is the same as taking the sum over
`Fintype.piFinset t`. `univ.pi t` and `Fintype.piFinset t` are essentially the same `Finset`,
but differ in the type of their element, `univ.pi t` is a `Finset (Π a ∈ univ, t a)` and
`Fintype.piFinset t` is a `Finset (Π a, t a)`."]
lemma prod_univ_pi [DecidableEq ι] [Fintype ι] {κ : ι → Type*} (t : ∀ i, Finset (κ i))
(f : (∀ i ∈ (univ : Finset ι), κ i) → β) :
∏ x ∈ univ.pi t, f x = ∏ x ∈ Fintype.piFinset t, f fun a _ ↦ x a := by
apply prod_nbij' (fun x i ↦ x i $ mem_univ _) (fun x i _ ↦ x i) <;> simp
#align finset.prod_univ_pi Finset.prod_univ_pi
#align finset.sum_univ_pi Finset.sum_univ_pi
@[to_additive (attr := simp)]
lemma prod_diag [DecidableEq α] (s : Finset α) (f : α × α → β) :
∏ i ∈ s.diag, f i = ∏ i ∈ s, f (i, i) := by
apply prod_nbij' Prod.fst (fun i ↦ (i, i)) <;> simp
@[to_additive]
theorem prod_finset_product (r : Finset (γ × α)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : γ × α, p ∈ r ↔ p.1 ∈ s ∧ p.2 ∈ t p.1) {f : γ × α → β} :
∏ p ∈ r, f p = ∏ c ∈ s, ∏ a ∈ t c, f (c, a) := by
refine Eq.trans ?_ (prod_sigma s t fun p => f (p.1, p.2))
apply prod_equiv (Equiv.sigmaEquivProd _ _).symm <;> simp [h]
#align finset.prod_finset_product Finset.prod_finset_product
#align finset.sum_finset_product Finset.sum_finset_product
@[to_additive]
theorem prod_finset_product' (r : Finset (γ × α)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : γ × α, p ∈ r ↔ p.1 ∈ s ∧ p.2 ∈ t p.1) {f : γ → α → β} :
∏ p ∈ r, f p.1 p.2 = ∏ c ∈ s, ∏ a ∈ t c, f c a :=
prod_finset_product r s t h
#align finset.prod_finset_product' Finset.prod_finset_product'
#align finset.sum_finset_product' Finset.sum_finset_product'
@[to_additive]
theorem prod_finset_product_right (r : Finset (α × γ)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : α × γ, p ∈ r ↔ p.2 ∈ s ∧ p.1 ∈ t p.2) {f : α × γ → β} :
∏ p ∈ r, f p = ∏ c ∈ s, ∏ a ∈ t c, f (a, c) := by
refine Eq.trans ?_ (prod_sigma s t fun p => f (p.2, p.1))
apply prod_equiv ((Equiv.prodComm _ _).trans (Equiv.sigmaEquivProd _ _).symm) <;> simp [h]
#align finset.prod_finset_product_right Finset.prod_finset_product_right
#align finset.sum_finset_product_right Finset.sum_finset_product_right
@[to_additive]
theorem prod_finset_product_right' (r : Finset (α × γ)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : α × γ, p ∈ r ↔ p.2 ∈ s ∧ p.1 ∈ t p.2) {f : α → γ → β} :
∏ p ∈ r, f p.1 p.2 = ∏ c ∈ s, ∏ a ∈ t c, f a c :=
prod_finset_product_right r s t h
#align finset.prod_finset_product_right' Finset.prod_finset_product_right'
#align finset.sum_finset_product_right' Finset.sum_finset_product_right'
@[to_additive]
theorem prod_image' [DecidableEq α] {s : Finset γ} {g : γ → α} (h : γ → β)
(eq : ∀ c ∈ s, f (g c) = ∏ x ∈ s.filter fun c' => g c' = g c, h x) :
∏ x ∈ s.image g, f x = ∏ x ∈ s, h x :=
calc
∏ x ∈ s.image g, f x = ∏ x ∈ s.image g, ∏ x ∈ s.filter fun c' => g c' = x, h x :=
(prod_congr rfl) fun _x hx =>
let ⟨c, hcs, hc⟩ := mem_image.1 hx
hc ▸ eq c hcs
_ = ∏ x ∈ s, h x := prod_fiberwise_of_maps_to (fun _x => mem_image_of_mem g) _
#align finset.prod_image' Finset.prod_image'
#align finset.sum_image' Finset.sum_image'
@[to_additive]
theorem prod_mul_distrib : ∏ x ∈ s, f x * g x = (∏ x ∈ s, f x) * ∏ x ∈ s, g x :=
Eq.trans (by rw [one_mul]; rfl) fold_op_distrib
#align finset.prod_mul_distrib Finset.prod_mul_distrib
#align finset.sum_add_distrib Finset.sum_add_distrib
@[to_additive]
lemma prod_mul_prod_comm (f g h i : α → β) :
(∏ a ∈ s, f a * g a) * ∏ a ∈ s, h a * i a = (∏ a ∈ s, f a * h a) * ∏ a ∈ s, g a * i a := by
simp_rw [prod_mul_distrib, mul_mul_mul_comm]
@[to_additive]
theorem prod_product {s : Finset γ} {t : Finset α} {f : γ × α → β} :
∏ x ∈ s ×ˢ t, f x = ∏ x ∈ s, ∏ y ∈ t, f (x, y) :=
prod_finset_product (s ×ˢ t) s (fun _a => t) fun _p => mem_product
#align finset.prod_product Finset.prod_product
#align finset.sum_product Finset.sum_product
/-- An uncurried version of `Finset.prod_product`. -/
@[to_additive "An uncurried version of `Finset.sum_product`"]
theorem prod_product' {s : Finset γ} {t : Finset α} {f : γ → α → β} :
∏ x ∈ s ×ˢ t, f x.1 x.2 = ∏ x ∈ s, ∏ y ∈ t, f x y :=
prod_product
#align finset.prod_product' Finset.prod_product'
#align finset.sum_product' Finset.sum_product'
@[to_additive]
theorem prod_product_right {s : Finset γ} {t : Finset α} {f : γ × α → β} :
∏ x ∈ s ×ˢ t, f x = ∏ y ∈ t, ∏ x ∈ s, f (x, y) :=
prod_finset_product_right (s ×ˢ t) t (fun _a => s) fun _p => mem_product.trans and_comm
#align finset.prod_product_right Finset.prod_product_right
#align finset.sum_product_right Finset.sum_product_right
/-- An uncurried version of `Finset.prod_product_right`. -/
@[to_additive "An uncurried version of `Finset.sum_product_right`"]
theorem prod_product_right' {s : Finset γ} {t : Finset α} {f : γ → α → β} :
∏ x ∈ s ×ˢ t, f x.1 x.2 = ∏ y ∈ t, ∏ x ∈ s, f x y :=
prod_product_right
#align finset.prod_product_right' Finset.prod_product_right'
#align finset.sum_product_right' Finset.sum_product_right'
/-- Generalization of `Finset.prod_comm` to the case when the inner `Finset`s depend on the outer
variable. -/
@[to_additive "Generalization of `Finset.sum_comm` to the case when the inner `Finset`s depend on
the outer variable."]
theorem prod_comm' {s : Finset γ} {t : γ → Finset α} {t' : Finset α} {s' : α → Finset γ}
(h : ∀ x y, x ∈ s ∧ y ∈ t x ↔ x ∈ s' y ∧ y ∈ t') {f : γ → α → β} :
(∏ x ∈ s, ∏ y ∈ t x, f x y) = ∏ y ∈ t', ∏ x ∈ s' y, f x y := by
classical
have : ∀ z : γ × α, (z ∈ s.biUnion fun x => (t x).map <| Function.Embedding.sectr x _) ↔
z.1 ∈ s ∧ z.2 ∈ t z.1 := by
rintro ⟨x, y⟩
simp only [mem_biUnion, mem_map, Function.Embedding.sectr_apply, Prod.mk.injEq,
exists_eq_right, ← and_assoc]
exact
(prod_finset_product' _ _ _ this).symm.trans
((prod_finset_product_right' _ _ _) fun ⟨x, y⟩ => (this _).trans ((h x y).trans and_comm))
#align finset.prod_comm' Finset.prod_comm'
#align finset.sum_comm' Finset.sum_comm'
@[to_additive]
theorem prod_comm {s : Finset γ} {t : Finset α} {f : γ → α → β} :
(∏ x ∈ s, ∏ y ∈ t, f x y) = ∏ y ∈ t, ∏ x ∈ s, f x y :=
prod_comm' fun _ _ => Iff.rfl
#align finset.prod_comm Finset.prod_comm
#align finset.sum_comm Finset.sum_comm
@[to_additive]
theorem prod_hom_rel [CommMonoid γ] {r : β → γ → Prop} {f : α → β} {g : α → γ} {s : Finset α}
(h₁ : r 1 1) (h₂ : ∀ a b c, r b c → r (f a * b) (g a * c)) :
r (∏ x ∈ s, f x) (∏ x ∈ s, g x) := by
delta Finset.prod
apply Multiset.prod_hom_rel <;> assumption
#align finset.prod_hom_rel Finset.prod_hom_rel
#align finset.sum_hom_rel Finset.sum_hom_rel
@[to_additive]
theorem prod_filter_of_ne {p : α → Prop} [DecidablePred p] (hp : ∀ x ∈ s, f x ≠ 1 → p x) :
∏ x ∈ s.filter p, f x = ∏ x ∈ s, f x :=
(prod_subset (filter_subset _ _)) fun x => by
classical
rw [not_imp_comm, mem_filter]
exact fun h₁ h₂ => ⟨h₁, by simpa using hp _ h₁ h₂⟩
#align finset.prod_filter_of_ne Finset.prod_filter_of_ne
#align finset.sum_filter_of_ne Finset.sum_filter_of_ne
-- If we use `[DecidableEq β]` here, some rewrites fail because they find a wrong `Decidable`
-- instance first; `{∀ x, Decidable (f x ≠ 1)}` doesn't work with `rw ← prod_filter_ne_one`
@[to_additive]
theorem prod_filter_ne_one (s : Finset α) [∀ x, Decidable (f x ≠ 1)] :
∏ x ∈ s.filter fun x => f x ≠ 1, f x = ∏ x ∈ s, f x :=
prod_filter_of_ne fun _ _ => id
#align finset.prod_filter_ne_one Finset.prod_filter_ne_one
#align finset.sum_filter_ne_zero Finset.sum_filter_ne_zero
@[to_additive]
theorem prod_filter (p : α → Prop) [DecidablePred p] (f : α → β) :
∏ a ∈ s.filter p, f a = ∏ a ∈ s, if p a then f a else 1 :=
calc
∏ a ∈ s.filter p, f a = ∏ a ∈ s.filter p, if p a then f a else 1 :=
prod_congr rfl fun a h => by rw [if_pos]; simpa using (mem_filter.1 h).2
_ = ∏ a ∈ s, if p a then f a else 1 := by
{ refine prod_subset (filter_subset _ s) fun x hs h => ?_
rw [mem_filter, not_and] at h
exact if_neg (by simpa using h hs) }
#align finset.prod_filter Finset.prod_filter
#align finset.sum_filter Finset.sum_filter
@[to_additive]
theorem prod_eq_single_of_mem {s : Finset α} {f : α → β} (a : α) (h : a ∈ s)
(h₀ : ∀ b ∈ s, b ≠ a → f b = 1) : ∏ x ∈ s, f x = f a := by
haveI := Classical.decEq α
calc
∏ x ∈ s, f x = ∏ x ∈ {a}, f x := by
{ refine (prod_subset ?_ ?_).symm
· intro _ H
rwa [mem_singleton.1 H]
· simpa only [mem_singleton] }
_ = f a := prod_singleton _ _
#align finset.prod_eq_single_of_mem Finset.prod_eq_single_of_mem
#align finset.sum_eq_single_of_mem Finset.sum_eq_single_of_mem
@[to_additive]
theorem prod_eq_single {s : Finset α} {f : α → β} (a : α) (h₀ : ∀ b ∈ s, b ≠ a → f b = 1)
(h₁ : a ∉ s → f a = 1) : ∏ x ∈ s, f x = f a :=
haveI := Classical.decEq α
by_cases (prod_eq_single_of_mem a · h₀) fun this =>
(prod_congr rfl fun b hb => h₀ b hb <| by rintro rfl; exact this hb).trans <|
prod_const_one.trans (h₁ this).symm
#align finset.prod_eq_single Finset.prod_eq_single
#align finset.sum_eq_single Finset.sum_eq_single
@[to_additive]
lemma prod_union_eq_left [DecidableEq α] (hs : ∀ a ∈ s₂, a ∉ s₁ → f a = 1) :
∏ a ∈ s₁ ∪ s₂, f a = ∏ a ∈ s₁, f a :=
Eq.symm <|
prod_subset subset_union_left fun _a ha ha' ↦ hs _ ((mem_union.1 ha).resolve_left ha') ha'
@[to_additive]
lemma prod_union_eq_right [DecidableEq α] (hs : ∀ a ∈ s₁, a ∉ s₂ → f a = 1) :
∏ a ∈ s₁ ∪ s₂, f a = ∏ a ∈ s₂, f a := by rw [union_comm, prod_union_eq_left hs]
@[to_additive]
theorem prod_eq_mul_of_mem {s : Finset α} {f : α → β} (a b : α) (ha : a ∈ s) (hb : b ∈ s)
(hn : a ≠ b) (h₀ : ∀ c ∈ s, c ≠ a ∧ c ≠ b → f c = 1) : ∏ x ∈ s, f x = f a * f b := by
haveI := Classical.decEq α; let s' := ({a, b} : Finset α)
have hu : s' ⊆ s := by
refine insert_subset_iff.mpr ?_
apply And.intro ha
apply singleton_subset_iff.mpr hb
have hf : ∀ c ∈ s, c ∉ s' → f c = 1 := by
intro c hc hcs
apply h₀ c hc
apply not_or.mp
intro hab
apply hcs
rw [mem_insert, mem_singleton]
exact hab
rw [← prod_subset hu hf]
exact Finset.prod_pair hn
#align finset.prod_eq_mul_of_mem Finset.prod_eq_mul_of_mem
#align finset.sum_eq_add_of_mem Finset.sum_eq_add_of_mem
@[to_additive]
theorem prod_eq_mul {s : Finset α} {f : α → β} (a b : α) (hn : a ≠ b)
(h₀ : ∀ c ∈ s, c ≠ a ∧ c ≠ b → f c = 1) (ha : a ∉ s → f a = 1) (hb : b ∉ s → f b = 1) :
∏ x ∈ s, f x = f a * f b := by
haveI := Classical.decEq α; by_cases h₁ : a ∈ s <;> by_cases h₂ : b ∈ s
· exact prod_eq_mul_of_mem a b h₁ h₂ hn h₀
· rw [hb h₂, mul_one]
apply prod_eq_single_of_mem a h₁
exact fun c hc hca => h₀ c hc ⟨hca, ne_of_mem_of_not_mem hc h₂⟩
· rw [ha h₁, one_mul]
apply prod_eq_single_of_mem b h₂
exact fun c hc hcb => h₀ c hc ⟨ne_of_mem_of_not_mem hc h₁, hcb⟩
· rw [ha h₁, hb h₂, mul_one]
exact
_root_.trans
(prod_congr rfl fun c hc =>
h₀ c hc ⟨ne_of_mem_of_not_mem hc h₁, ne_of_mem_of_not_mem hc h₂⟩)
prod_const_one
#align finset.prod_eq_mul Finset.prod_eq_mul
#align finset.sum_eq_add Finset.sum_eq_add
-- Porting note: simpNF linter complains that LHS doesn't simplify, but it does
/-- A product over `s.subtype p` equals one over `s.filter p`. -/
@[to_additive (attr := simp, nolint simpNF)
"A sum over `s.subtype p` equals one over `s.filter p`."]
theorem prod_subtype_eq_prod_filter (f : α → β) {p : α → Prop} [DecidablePred p] :
∏ x ∈ s.subtype p, f x = ∏ x ∈ s.filter p, f x := by
conv_lhs => erw [← prod_map (s.subtype p) (Function.Embedding.subtype _) f]
exact prod_congr (subtype_map _) fun x _hx => rfl
#align finset.prod_subtype_eq_prod_filter Finset.prod_subtype_eq_prod_filter
#align finset.sum_subtype_eq_sum_filter Finset.sum_subtype_eq_sum_filter
/-- If all elements of a `Finset` satisfy the predicate `p`, a product
over `s.subtype p` equals that product over `s`. -/
@[to_additive "If all elements of a `Finset` satisfy the predicate `p`, a sum
over `s.subtype p` equals that sum over `s`."]
theorem prod_subtype_of_mem (f : α → β) {p : α → Prop} [DecidablePred p] (h : ∀ x ∈ s, p x) :
∏ x ∈ s.subtype p, f x = ∏ x ∈ s, f x := by
rw [prod_subtype_eq_prod_filter, filter_true_of_mem]
simpa using h
#align finset.prod_subtype_of_mem Finset.prod_subtype_of_mem
#align finset.sum_subtype_of_mem Finset.sum_subtype_of_mem
/-- A product of a function over a `Finset` in a subtype equals a
product in the main type of a function that agrees with the first
function on that `Finset`. -/
@[to_additive "A sum of a function over a `Finset` in a subtype equals a
sum in the main type of a function that agrees with the first
function on that `Finset`."]
theorem prod_subtype_map_embedding {p : α → Prop} {s : Finset { x // p x }} {f : { x // p x } → β}
{g : α → β} (h : ∀ x : { x // p x }, x ∈ s → g x = f x) :
(∏ x ∈ s.map (Function.Embedding.subtype _), g x) = ∏ x ∈ s, f x := by
rw [Finset.prod_map]
exact Finset.prod_congr rfl h
#align finset.prod_subtype_map_embedding Finset.prod_subtype_map_embedding
#align finset.sum_subtype_map_embedding Finset.sum_subtype_map_embedding
variable (f s)
@[to_additive]
theorem prod_coe_sort_eq_attach (f : s → β) : ∏ i : s, f i = ∏ i ∈ s.attach, f i :=
rfl
#align finset.prod_coe_sort_eq_attach Finset.prod_coe_sort_eq_attach
#align finset.sum_coe_sort_eq_attach Finset.sum_coe_sort_eq_attach
@[to_additive]
theorem prod_coe_sort : ∏ i : s, f i = ∏ i ∈ s, f i := prod_attach _ _
#align finset.prod_coe_sort Finset.prod_coe_sort
#align finset.sum_coe_sort Finset.sum_coe_sort
@[to_additive]
theorem prod_finset_coe (f : α → β) (s : Finset α) : (∏ i : (s : Set α), f i) = ∏ i ∈ s, f i :=
prod_coe_sort s f
#align finset.prod_finset_coe Finset.prod_finset_coe
#align finset.sum_finset_coe Finset.sum_finset_coe
variable {f s}
@[to_additive]
theorem prod_subtype {p : α → Prop} {F : Fintype (Subtype p)} (s : Finset α) (h : ∀ x, x ∈ s ↔ p x)
(f : α → β) : ∏ a ∈ s, f a = ∏ a : Subtype p, f a := by
have : (· ∈ s) = p := Set.ext h
subst p
rw [← prod_coe_sort]
congr!
#align finset.prod_subtype Finset.prod_subtype
#align finset.sum_subtype Finset.sum_subtype
@[to_additive]
lemma prod_preimage' (f : ι → κ) [DecidablePred (· ∈ Set.range f)] (s : Finset κ) (hf) (g : κ → β) :
∏ x ∈ s.preimage f hf, g (f x) = ∏ x ∈ s.filter (· ∈ Set.range f), g x := by
classical
calc
∏ x ∈ preimage s f hf, g (f x) = ∏ x ∈ image f (preimage s f hf), g x :=
Eq.symm <| prod_image <| by simpa only [mem_preimage, Set.InjOn] using hf
_ = ∏ x ∈ s.filter fun x => x ∈ Set.range f, g x := by rw [image_preimage]
#align finset.prod_preimage' Finset.prod_preimage'
#align finset.sum_preimage' Finset.sum_preimage'
@[to_additive]
lemma prod_preimage (f : ι → κ) (s : Finset κ) (hf) (g : κ → β)
(hg : ∀ x ∈ s, x ∉ Set.range f → g x = 1) :
∏ x ∈ s.preimage f hf, g (f x) = ∏ x ∈ s, g x := by
classical rw [prod_preimage', prod_filter_of_ne]; exact fun x hx ↦ Not.imp_symm (hg x hx)
#align finset.prod_preimage Finset.prod_preimage
#align finset.sum_preimage Finset.sum_preimage
@[to_additive]
lemma prod_preimage_of_bij (f : ι → κ) (s : Finset κ) (hf : Set.BijOn f (f ⁻¹' ↑s) ↑s) (g : κ → β) :
∏ x ∈ s.preimage f hf.injOn, g (f x) = ∏ x ∈ s, g x :=
prod_preimage _ _ hf.injOn g fun _ hs h_f ↦ (h_f <| hf.subset_range hs).elim
#align finset.prod_preimage_of_bij Finset.prod_preimage_of_bij
#align finset.sum_preimage_of_bij Finset.sum_preimage_of_bij
@[to_additive]
theorem prod_set_coe (s : Set α) [Fintype s] : (∏ i : s, f i) = ∏ i ∈ s.toFinset, f i :=
(Finset.prod_subtype s.toFinset (fun _ ↦ Set.mem_toFinset) f).symm
/-- The product of a function `g` defined only on a set `s` is equal to
the product of a function `f` defined everywhere,
as long as `f` and `g` agree on `s`, and `f = 1` off `s`. -/
@[to_additive "The sum of a function `g` defined only on a set `s` is equal to
the sum of a function `f` defined everywhere,
as long as `f` and `g` agree on `s`, and `f = 0` off `s`."]
theorem prod_congr_set {α : Type*} [CommMonoid α] {β : Type*} [Fintype β] (s : Set β)
[DecidablePred (· ∈ s)] (f : β → α) (g : s → α) (w : ∀ (x : β) (h : x ∈ s), f x = g ⟨x, h⟩)
(w' : ∀ x : β, x ∉ s → f x = 1) : Finset.univ.prod f = Finset.univ.prod g := by
rw [← @Finset.prod_subset _ _ s.toFinset Finset.univ f _ (by simp)]
· rw [Finset.prod_subtype]
· apply Finset.prod_congr rfl
exact fun ⟨x, h⟩ _ => w x h
· simp
· rintro x _ h
exact w' x (by simpa using h)
#align finset.prod_congr_set Finset.prod_congr_set
#align finset.sum_congr_set Finset.sum_congr_set
@[to_additive]
theorem prod_apply_dite {s : Finset α} {p : α → Prop} {hp : DecidablePred p}
[DecidablePred fun x => ¬p x] (f : ∀ x : α, p x → γ) (g : ∀ x : α, ¬p x → γ) (h : γ → β) :
(∏ x ∈ s, h (if hx : p x then f x hx else g x hx)) =
(∏ x ∈ (s.filter p).attach, h (f x.1 <| by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter fun x => ¬p x).attach, h (g x.1 <| by simpa using (mem_filter.mp x.2).2) :=
calc
(∏ x ∈ s, h (if hx : p x then f x hx else g x hx)) =
(∏ x ∈ s.filter p, h (if hx : p x then f x hx else g x hx)) *
∏ x ∈ s.filter (¬p ·), h (if hx : p x then f x hx else g x hx) :=
(prod_filter_mul_prod_filter_not s p _).symm
_ = (∏ x ∈ (s.filter p).attach, h (if hx : p x.1 then f x.1 hx else g x.1 hx)) *
∏ x ∈ (s.filter (¬p ·)).attach, h (if hx : p x.1 then f x.1 hx else g x.1 hx) :=
congr_arg₂ _ (prod_attach _ _).symm (prod_attach _ _).symm
_ = (∏ x ∈ (s.filter p).attach, h (f x.1 <| by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter (¬p ·)).attach, h (g x.1 <| by simpa using (mem_filter.mp x.2).2) :=
congr_arg₂ _ (prod_congr rfl fun x _hx ↦
congr_arg h (dif_pos <| by simpa using (mem_filter.mp x.2).2))
(prod_congr rfl fun x _hx => congr_arg h (dif_neg <| by simpa using (mem_filter.mp x.2).2))
#align finset.prod_apply_dite Finset.prod_apply_dite
#align finset.sum_apply_dite Finset.sum_apply_dite
@[to_additive]
theorem prod_apply_ite {s : Finset α} {p : α → Prop} {_hp : DecidablePred p} (f g : α → γ)
(h : γ → β) :
(∏ x ∈ s, h (if p x then f x else g x)) =
(∏ x ∈ s.filter p, h (f x)) * ∏ x ∈ s.filter fun x => ¬p x, h (g x) :=
(prod_apply_dite _ _ _).trans <| congr_arg₂ _ (prod_attach _ (h ∘ f)) (prod_attach _ (h ∘ g))
#align finset.prod_apply_ite Finset.prod_apply_ite
#align finset.sum_apply_ite Finset.sum_apply_ite
@[to_additive]
theorem prod_dite {s : Finset α} {p : α → Prop} {hp : DecidablePred p} (f : ∀ x : α, p x → β)
(g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) =
(∏ x ∈ (s.filter p).attach, f x.1 (by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter fun x => ¬p x).attach, g x.1 (by simpa using (mem_filter.mp x.2).2) := by
simp [prod_apply_dite _ _ fun x => x]
#align finset.prod_dite Finset.prod_dite
#align finset.sum_dite Finset.sum_dite
@[to_additive]
theorem prod_ite {s : Finset α} {p : α → Prop} {hp : DecidablePred p} (f g : α → β) :
∏ x ∈ s, (if p x then f x else g x) =
(∏ x ∈ s.filter p, f x) * ∏ x ∈ s.filter fun x => ¬p x, g x := by
simp [prod_apply_ite _ _ fun x => x]
#align finset.prod_ite Finset.prod_ite
#align finset.sum_ite Finset.sum_ite
@[to_additive]
theorem prod_ite_of_false {p : α → Prop} {hp : DecidablePred p} (f g : α → β) (h : ∀ x ∈ s, ¬p x) :
∏ x ∈ s, (if p x then f x else g x) = ∏ x ∈ s, g x := by
rw [prod_ite, filter_false_of_mem, filter_true_of_mem]
· simp only [prod_empty, one_mul]
all_goals intros; apply h; assumption
#align finset.prod_ite_of_false Finset.prod_ite_of_false
#align finset.sum_ite_of_false Finset.sum_ite_of_false
@[to_additive]
theorem prod_ite_of_true {p : α → Prop} {hp : DecidablePred p} (f g : α → β) (h : ∀ x ∈ s, p x) :
∏ x ∈ s, (if p x then f x else g x) = ∏ x ∈ s, f x := by
simp_rw [← ite_not (p _)]
apply prod_ite_of_false
simpa
#align finset.prod_ite_of_true Finset.prod_ite_of_true
#align finset.sum_ite_of_true Finset.sum_ite_of_true
@[to_additive]
theorem prod_apply_ite_of_false {p : α → Prop} {hp : DecidablePred p} (f g : α → γ) (k : γ → β)
(h : ∀ x ∈ s, ¬p x) : (∏ x ∈ s, k (if p x then f x else g x)) = ∏ x ∈ s, k (g x) := by
simp_rw [apply_ite k]
exact prod_ite_of_false _ _ h
#align finset.prod_apply_ite_of_false Finset.prod_apply_ite_of_false
#align finset.sum_apply_ite_of_false Finset.sum_apply_ite_of_false
@[to_additive]
theorem prod_apply_ite_of_true {p : α → Prop} {hp : DecidablePred p} (f g : α → γ) (k : γ → β)
(h : ∀ x ∈ s, p x) : (∏ x ∈ s, k (if p x then f x else g x)) = ∏ x ∈ s, k (f x) := by
simp_rw [apply_ite k]
exact prod_ite_of_true _ _ h
#align finset.prod_apply_ite_of_true Finset.prod_apply_ite_of_true
#align finset.sum_apply_ite_of_true Finset.sum_apply_ite_of_true
@[to_additive]
theorem prod_extend_by_one [DecidableEq α] (s : Finset α) (f : α → β) :
∏ i ∈ s, (if i ∈ s then f i else 1) = ∏ i ∈ s, f i :=
(prod_congr rfl) fun _i hi => if_pos hi
#align finset.prod_extend_by_one Finset.prod_extend_by_one
#align finset.sum_extend_by_zero Finset.sum_extend_by_zero
@[to_additive (attr := simp)]
theorem prod_ite_mem [DecidableEq α] (s t : Finset α) (f : α → β) :
∏ i ∈ s, (if i ∈ t then f i else 1) = ∏ i ∈ s ∩ t, f i := by
rw [← Finset.prod_filter, Finset.filter_mem_eq_inter]
#align finset.prod_ite_mem Finset.prod_ite_mem
#align finset.sum_ite_mem Finset.sum_ite_mem
@[to_additive (attr := simp)]
theorem prod_dite_eq [DecidableEq α] (s : Finset α) (a : α) (b : ∀ x : α, a = x → β) :
∏ x ∈ s, (if h : a = x then b x h else 1) = ite (a ∈ s) (b a rfl) 1 := by
split_ifs with h
· rw [Finset.prod_eq_single a, dif_pos rfl]
· intros _ _ h
rw [dif_neg]
exact h.symm
· simp [h]
· rw [Finset.prod_eq_one]
intros
rw [dif_neg]
rintro rfl
contradiction
#align finset.prod_dite_eq Finset.prod_dite_eq
#align finset.sum_dite_eq Finset.sum_dite_eq
@[to_additive (attr := simp)]
theorem prod_dite_eq' [DecidableEq α] (s : Finset α) (a : α) (b : ∀ x : α, x = a → β) :
∏ x ∈ s, (if h : x = a then b x h else 1) = ite (a ∈ s) (b a rfl) 1 := by
split_ifs with h
· rw [Finset.prod_eq_single a, dif_pos rfl]
· intros _ _ h
rw [dif_neg]
exact h
· simp [h]
· rw [Finset.prod_eq_one]
intros
rw [dif_neg]
rintro rfl
contradiction
#align finset.prod_dite_eq' Finset.prod_dite_eq'
#align finset.sum_dite_eq' Finset.sum_dite_eq'
@[to_additive (attr := simp)]
theorem prod_ite_eq [DecidableEq α] (s : Finset α) (a : α) (b : α → β) :
(∏ x ∈ s, ite (a = x) (b x) 1) = ite (a ∈ s) (b a) 1 :=
prod_dite_eq s a fun x _ => b x
#align finset.prod_ite_eq Finset.prod_ite_eq
#align finset.sum_ite_eq Finset.sum_ite_eq
/-- A product taken over a conditional whose condition is an equality test on the index and whose
alternative is `1` has value either the term at that index or `1`.
The difference with `Finset.prod_ite_eq` is that the arguments to `Eq` are swapped. -/
@[to_additive (attr := simp) "A sum taken over a conditional whose condition is an equality
test on the index and whose alternative is `0` has value either the term at that index or `0`.
The difference with `Finset.sum_ite_eq` is that the arguments to `Eq` are swapped."]
theorem prod_ite_eq' [DecidableEq α] (s : Finset α) (a : α) (b : α → β) :
(∏ x ∈ s, ite (x = a) (b x) 1) = ite (a ∈ s) (b a) 1 :=
prod_dite_eq' s a fun x _ => b x
#align finset.prod_ite_eq' Finset.prod_ite_eq'
#align finset.sum_ite_eq' Finset.sum_ite_eq'
@[to_additive]
theorem prod_ite_index (p : Prop) [Decidable p] (s t : Finset α) (f : α → β) :
∏ x ∈ if p then s else t, f x = if p then ∏ x ∈ s, f x else ∏ x ∈ t, f x :=
apply_ite (fun s => ∏ x ∈ s, f x) _ _ _
#align finset.prod_ite_index Finset.prod_ite_index
#align finset.sum_ite_index Finset.sum_ite_index
@[to_additive (attr := simp)]
theorem prod_ite_irrel (p : Prop) [Decidable p] (s : Finset α) (f g : α → β) :
∏ x ∈ s, (if p then f x else g x) = if p then ∏ x ∈ s, f x else ∏ x ∈ s, g x := by
split_ifs with h <;> rfl
#align finset.prod_ite_irrel Finset.prod_ite_irrel
#align finset.sum_ite_irrel Finset.sum_ite_irrel
@[to_additive (attr := simp)]
theorem prod_dite_irrel (p : Prop) [Decidable p] (s : Finset α) (f : p → α → β) (g : ¬p → α → β) :
∏ x ∈ s, (if h : p then f h x else g h x) =
if h : p then ∏ x ∈ s, f h x else ∏ x ∈ s, g h x := by
split_ifs with h <;> rfl
#align finset.prod_dite_irrel Finset.prod_dite_irrel
#align finset.sum_dite_irrel Finset.sum_dite_irrel
@[to_additive (attr := simp)]
theorem prod_pi_mulSingle' [DecidableEq α] (a : α) (x : β) (s : Finset α) :
∏ a' ∈ s, Pi.mulSingle a x a' = if a ∈ s then x else 1 :=
prod_dite_eq' _ _ _
#align finset.prod_pi_mul_single' Finset.prod_pi_mulSingle'
#align finset.sum_pi_single' Finset.sum_pi_single'
@[to_additive (attr := simp)]
theorem prod_pi_mulSingle {β : α → Type*} [DecidableEq α] [∀ a, CommMonoid (β a)] (a : α)
(f : ∀ a, β a) (s : Finset α) :
(∏ a' ∈ s, Pi.mulSingle a' (f a') a) = if a ∈ s then f a else 1 :=
prod_dite_eq _ _ _
#align finset.prod_pi_mul_single Finset.prod_pi_mulSingle
@[to_additive]
lemma mulSupport_prod (s : Finset ι) (f : ι → α → β) :
mulSupport (fun x ↦ ∏ i ∈ s, f i x) ⊆ ⋃ i ∈ s, mulSupport (f i) := by
simp only [mulSupport_subset_iff', Set.mem_iUnion, not_exists, nmem_mulSupport]
exact fun x ↦ prod_eq_one
#align function.mul_support_prod Finset.mulSupport_prod
#align function.support_sum Finset.support_sum
section indicator
open Set
variable {κ : Type*}
/-- Consider a product of `g i (f i)` over a finset. Suppose `g` is a function such as
`n ↦ (· ^ n)`, which maps a second argument of `1` to `1`. Then if `f` is replaced by the
corresponding multiplicative indicator function, the finset may be replaced by a possibly larger
finset without changing the value of the product. -/
@[to_additive "Consider a sum of `g i (f i)` over a finset. Suppose `g` is a function such as
`n ↦ (n • ·)`, which maps a second argument of `0` to `0` (or a weighted sum of `f i * h i` or
`f i • h i`, where `f` gives the weights that are multiplied by some other function `h`). Then if
`f` is replaced by the corresponding indicator function, the finset may be replaced by a possibly
larger finset without changing the value of the sum."]
lemma prod_mulIndicator_subset_of_eq_one [One α] (f : ι → α) (g : ι → α → β) {s t : Finset ι}
(h : s ⊆ t) (hg : ∀ a, g a 1 = 1) :
∏ i ∈ t, g i (mulIndicator ↑s f i) = ∏ i ∈ s, g i (f i) := by
calc
_ = ∏ i ∈ s, g i (mulIndicator ↑s f i) := by rw [prod_subset h fun i _ hn ↦ by simp [hn, hg]]
-- Porting note: This did not use to need the implicit argument
_ = _ := prod_congr rfl fun i hi ↦ congr_arg _ <| mulIndicator_of_mem (α := ι) hi f
#align set.prod_mul_indicator_subset_of_eq_one Finset.prod_mulIndicator_subset_of_eq_one
#align set.sum_indicator_subset_of_eq_zero Finset.sum_indicator_subset_of_eq_zero
/-- Taking the product of an indicator function over a possibly larger finset is the same as
taking the original function over the original finset. -/
@[to_additive "Summing an indicator function over a possibly larger `Finset` is the same as summing
the original function over the original finset."]
lemma prod_mulIndicator_subset (f : ι → β) {s t : Finset ι} (h : s ⊆ t) :
∏ i ∈ t, mulIndicator (↑s) f i = ∏ i ∈ s, f i :=
prod_mulIndicator_subset_of_eq_one _ (fun _ ↦ id) h fun _ ↦ rfl
#align set.prod_mul_indicator_subset Finset.prod_mulIndicator_subset
#align set.sum_indicator_subset Finset.sum_indicator_subset
@[to_additive]
lemma prod_mulIndicator_eq_prod_filter (s : Finset ι) (f : ι → κ → β) (t : ι → Set κ) (g : ι → κ)
[DecidablePred fun i ↦ g i ∈ t i] :
∏ i ∈ s, mulIndicator (t i) (f i) (g i) = ∏ i ∈ s.filter fun i ↦ g i ∈ t i, f i (g i) := by
refine (prod_filter_mul_prod_filter_not s (fun i ↦ g i ∈ t i) _).symm.trans <|
Eq.trans (congr_arg₂ (· * ·) ?_ ?_) (mul_one _)
· exact prod_congr rfl fun x hx ↦ mulIndicator_of_mem (mem_filter.1 hx).2 _
· exact prod_eq_one fun x hx ↦ mulIndicator_of_not_mem (mem_filter.1 hx).2 _
#align finset.prod_mul_indicator_eq_prod_filter Finset.prod_mulIndicator_eq_prod_filter
#align finset.sum_indicator_eq_sum_filter Finset.sum_indicator_eq_sum_filter
@[to_additive]
lemma prod_mulIndicator_eq_prod_inter [DecidableEq ι] (s t : Finset ι) (f : ι → β) :
∏ i ∈ s, (t : Set ι).mulIndicator f i = ∏ i ∈ s ∩ t, f i := by
rw [← filter_mem_eq_inter, prod_mulIndicator_eq_prod_filter]; rfl
@[to_additive]
lemma mulIndicator_prod (s : Finset ι) (t : Set κ) (f : ι → κ → β) :
mulIndicator t (∏ i ∈ s, f i) = ∏ i ∈ s, mulIndicator t (f i) :=
map_prod (mulIndicatorHom _ _) _ _
#align set.mul_indicator_finset_prod Finset.mulIndicator_prod
#align set.indicator_finset_sum Finset.indicator_sum
variable {κ : Type*}
@[to_additive]
lemma mulIndicator_biUnion (s : Finset ι) (t : ι → Set κ) {f : κ → β} :
((s : Set ι).PairwiseDisjoint t) →
mulIndicator (⋃ i ∈ s, t i) f = fun a ↦ ∏ i ∈ s, mulIndicator (t i) f a := by
classical
refine Finset.induction_on s (by simp) fun i s hi ih hs ↦ funext fun j ↦ ?_
rw [prod_insert hi, set_biUnion_insert, mulIndicator_union_of_not_mem_inter,
ih (hs.subset <| subset_insert _ _)]
simp only [not_exists, exists_prop, mem_iUnion, mem_inter_iff, not_and]
exact fun hji i' hi' hji' ↦ (ne_of_mem_of_not_mem hi' hi).symm <|
hs.elim_set (mem_insert_self _ _) (mem_insert_of_mem hi') _ hji hji'
#align set.mul_indicator_finset_bUnion Finset.mulIndicator_biUnion
#align set.indicator_finset_bUnion Finset.indicator_biUnion
@[to_additive]
lemma mulIndicator_biUnion_apply (s : Finset ι) (t : ι → Set κ) {f : κ → β}
(h : (s : Set ι).PairwiseDisjoint t) (x : κ) :
mulIndicator (⋃ i ∈ s, t i) f x = ∏ i ∈ s, mulIndicator (t i) f x := by
rw [mulIndicator_biUnion s t h]
#align set.mul_indicator_finset_bUnion_apply Finset.mulIndicator_biUnion_apply
#align set.indicator_finset_bUnion_apply Finset.indicator_biUnion_apply
end indicator
@[to_additive]
theorem prod_bij_ne_one {s : Finset α} {t : Finset γ} {f : α → β} {g : γ → β}
(i : ∀ a ∈ s, f a ≠ 1 → γ) (hi : ∀ a h₁ h₂, i a h₁ h₂ ∈ t)
(i_inj : ∀ a₁ h₁₁ h₁₂ a₂ h₂₁ h₂₂, i a₁ h₁₁ h₁₂ = i a₂ h₂₁ h₂₂ → a₁ = a₂)
(i_surj : ∀ b ∈ t, g b ≠ 1 → ∃ a h₁ h₂, i a h₁ h₂ = b) (h : ∀ a h₁ h₂, f a = g (i a h₁ h₂)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x := by
classical
calc
∏ x ∈ s, f x = ∏ x ∈ s.filter fun x => f x ≠ 1, f x := by rw [prod_filter_ne_one]
_ = ∏ x ∈ t.filter fun x => g x ≠ 1, g x :=
prod_bij (fun a ha => i a (mem_filter.mp ha).1 <| by simpa using (mem_filter.mp ha).2)
?_ ?_ ?_ ?_
_ = ∏ x ∈ t, g x := prod_filter_ne_one _
· intros a ha
refine (mem_filter.mp ha).elim ?_
intros h₁ h₂
refine (mem_filter.mpr ⟨hi a h₁ _, ?_⟩)
specialize h a h₁ fun H ↦ by rw [H] at h₂; simp at h₂
rwa [← h]
· intros a₁ ha₁ a₂ ha₂
refine (mem_filter.mp ha₁).elim fun _ha₁₁ _ha₁₂ ↦ ?_
refine (mem_filter.mp ha₂).elim fun _ha₂₁ _ha₂₂ ↦ ?_
apply i_inj
· intros b hb
refine (mem_filter.mp hb).elim fun h₁ h₂ ↦ ?_
obtain ⟨a, ha₁, ha₂, eq⟩ := i_surj b h₁ fun H ↦ by rw [H] at h₂; simp at h₂
exact ⟨a, mem_filter.mpr ⟨ha₁, ha₂⟩, eq⟩
· refine (fun a ha => (mem_filter.mp ha).elim fun h₁ h₂ ↦ ?_)
exact h a h₁ fun H ↦ by rw [H] at h₂; simp at h₂
#align finset.prod_bij_ne_one Finset.prod_bij_ne_one
#align finset.sum_bij_ne_zero Finset.sum_bij_ne_zero
@[to_additive]
theorem prod_dite_of_false {p : α → Prop} {hp : DecidablePred p} (h : ∀ x ∈ s, ¬p x)
(f : ∀ x : α, p x → β) (g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) = ∏ x : s, g x.val (h x.val x.property) := by
refine prod_bij' (fun x hx => ⟨x, hx⟩) (fun x _ ↦ x) ?_ ?_ ?_ ?_ ?_ <;> aesop
#align finset.prod_dite_of_false Finset.prod_dite_of_false
#align finset.sum_dite_of_false Finset.sum_dite_of_false
@[to_additive]
theorem prod_dite_of_true {p : α → Prop} {hp : DecidablePred p} (h : ∀ x ∈ s, p x)
(f : ∀ x : α, p x → β) (g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) = ∏ x : s, f x.val (h x.val x.property) := by
refine prod_bij' (fun x hx => ⟨x, hx⟩) (fun x _ ↦ x) ?_ ?_ ?_ ?_ ?_ <;> aesop
#align finset.prod_dite_of_true Finset.prod_dite_of_true
#align finset.sum_dite_of_true Finset.sum_dite_of_true
@[to_additive]
theorem nonempty_of_prod_ne_one (h : ∏ x ∈ s, f x ≠ 1) : s.Nonempty :=
s.eq_empty_or_nonempty.elim (fun H => False.elim <| h <| H.symm ▸ prod_empty) id
#align finset.nonempty_of_prod_ne_one Finset.nonempty_of_prod_ne_one
#align finset.nonempty_of_sum_ne_zero Finset.nonempty_of_sum_ne_zero
@[to_additive]
theorem exists_ne_one_of_prod_ne_one (h : ∏ x ∈ s, f x ≠ 1) : ∃ a ∈ s, f a ≠ 1 := by
classical
rw [← prod_filter_ne_one] at h
rcases nonempty_of_prod_ne_one h with ⟨x, hx⟩
exact ⟨x, (mem_filter.1 hx).1, by simpa using (mem_filter.1 hx).2⟩
#align finset.exists_ne_one_of_prod_ne_one Finset.exists_ne_one_of_prod_ne_one
#align finset.exists_ne_zero_of_sum_ne_zero Finset.exists_ne_zero_of_sum_ne_zero
@[to_additive]
theorem prod_range_succ_comm (f : ℕ → β) (n : ℕ) :
(∏ x ∈ range (n + 1), f x) = f n * ∏ x ∈ range n, f x := by
rw [range_succ, prod_insert not_mem_range_self]
#align finset.prod_range_succ_comm Finset.prod_range_succ_comm
#align finset.sum_range_succ_comm Finset.sum_range_succ_comm
@[to_additive]
theorem prod_range_succ (f : ℕ → β) (n : ℕ) :
(∏ x ∈ range (n + 1), f x) = (∏ x ∈ range n, f x) * f n := by
simp only [mul_comm, prod_range_succ_comm]
#align finset.prod_range_succ Finset.prod_range_succ
#align finset.sum_range_succ Finset.sum_range_succ
@[to_additive]
theorem prod_range_succ' (f : ℕ → β) :
∀ n : ℕ, (∏ k ∈ range (n + 1), f k) = (∏ k ∈ range n, f (k + 1)) * f 0
| 0 => prod_range_succ _ _
| n + 1 => by rw [prod_range_succ _ n, mul_right_comm, ← prod_range_succ' _ n, prod_range_succ]
#align finset.prod_range_succ' Finset.prod_range_succ'
#align finset.sum_range_succ' Finset.sum_range_succ'
@[to_additive]
theorem eventually_constant_prod {u : ℕ → β} {N : ℕ} (hu : ∀ n ≥ N, u n = 1) {n : ℕ} (hn : N ≤ n) :
(∏ k ∈ range n, u k) = ∏ k ∈ range N, u k := by
obtain ⟨m, rfl : n = N + m⟩ := Nat.exists_eq_add_of_le hn
clear hn
induction' m with m hm
· simp
· simp [← add_assoc, prod_range_succ, hm, hu]
#align finset.eventually_constant_prod Finset.eventually_constant_prod
#align finset.eventually_constant_sum Finset.eventually_constant_sum
@[to_additive]
theorem prod_range_add (f : ℕ → β) (n m : ℕ) :
(∏ x ∈ range (n + m), f x) = (∏ x ∈ range n, f x) * ∏ x ∈ range m, f (n + x) := by
induction' m with m hm
· simp
· erw [Nat.add_succ, prod_range_succ, prod_range_succ, hm, mul_assoc]
#align finset.prod_range_add Finset.prod_range_add
#align finset.sum_range_add Finset.sum_range_add
@[to_additive]
theorem prod_range_add_div_prod_range {α : Type*} [CommGroup α] (f : ℕ → α) (n m : ℕ) :
(∏ k ∈ range (n + m), f k) / ∏ k ∈ range n, f k = ∏ k ∈ Finset.range m, f (n + k) :=
div_eq_of_eq_mul' (prod_range_add f n m)
#align finset.prod_range_add_div_prod_range Finset.prod_range_add_div_prod_range
#align finset.sum_range_add_sub_sum_range Finset.sum_range_add_sub_sum_range
@[to_additive]
theorem prod_range_zero (f : ℕ → β) : ∏ k ∈ range 0, f k = 1 := by rw [range_zero, prod_empty]
#align finset.prod_range_zero Finset.prod_range_zero
#align finset.sum_range_zero Finset.sum_range_zero
@[to_additive sum_range_one]
theorem prod_range_one (f : ℕ → β) : ∏ k ∈ range 1, f k = f 0 := by
rw [range_one, prod_singleton]
#align finset.prod_range_one Finset.prod_range_one
#align finset.sum_range_one Finset.sum_range_one
open List
@[to_additive]
theorem prod_list_map_count [DecidableEq α] (l : List α) {M : Type*} [CommMonoid M] (f : α → M) :
(l.map f).prod = ∏ m ∈ l.toFinset, f m ^ l.count m := by
induction' l with a s IH; · simp only [map_nil, prod_nil, count_nil, pow_zero, prod_const_one]
simp only [List.map, List.prod_cons, toFinset_cons, IH]
by_cases has : a ∈ s.toFinset
· rw [insert_eq_of_mem has, ← insert_erase has, prod_insert (not_mem_erase _ _),
prod_insert (not_mem_erase _ _), ← mul_assoc, count_cons_self, pow_succ']
congr 1
refine prod_congr rfl fun x hx => ?_
rw [count_cons_of_ne (ne_of_mem_erase hx)]
rw [prod_insert has, count_cons_self, count_eq_zero_of_not_mem (mt mem_toFinset.2 has), pow_one]
congr 1
refine prod_congr rfl fun x hx => ?_
rw [count_cons_of_ne]
rintro rfl
exact has hx
#align finset.prod_list_map_count Finset.prod_list_map_count
#align finset.sum_list_map_count Finset.sum_list_map_count
@[to_additive]
theorem prod_list_count [DecidableEq α] [CommMonoid α] (s : List α) :
s.prod = ∏ m ∈ s.toFinset, m ^ s.count m := by simpa using prod_list_map_count s id
#align finset.prod_list_count Finset.prod_list_count
#align finset.sum_list_count Finset.sum_list_count
@[to_additive]
theorem prod_list_count_of_subset [DecidableEq α] [CommMonoid α] (m : List α) (s : Finset α)
(hs : m.toFinset ⊆ s) : m.prod = ∏ i ∈ s, i ^ m.count i := by
rw [prod_list_count]
refine prod_subset hs fun x _ hx => ?_
rw [mem_toFinset] at hx
rw [count_eq_zero_of_not_mem hx, pow_zero]
#align finset.prod_list_count_of_subset Finset.prod_list_count_of_subset
#align finset.sum_list_count_of_subset Finset.sum_list_count_of_subset
theorem sum_filter_count_eq_countP [DecidableEq α] (p : α → Prop) [DecidablePred p] (l : List α) :
∑ x ∈ l.toFinset.filter p, l.count x = l.countP p := by
simp [Finset.sum, sum_map_count_dedup_filter_eq_countP p l]
#align finset.sum_filter_count_eq_countp Finset.sum_filter_count_eq_countP
open Multiset
@[to_additive]
theorem prod_multiset_map_count [DecidableEq α] (s : Multiset α) {M : Type*} [CommMonoid M]
(f : α → M) : (s.map f).prod = ∏ m ∈ s.toFinset, f m ^ s.count m := by
refine Quot.induction_on s fun l => ?_
simp [prod_list_map_count l f]
#align finset.prod_multiset_map_count Finset.prod_multiset_map_count
#align finset.sum_multiset_map_count Finset.sum_multiset_map_count
@[to_additive]
theorem prod_multiset_count [DecidableEq α] [CommMonoid α] (s : Multiset α) :
s.prod = ∏ m ∈ s.toFinset, m ^ s.count m := by
convert prod_multiset_map_count s id
rw [Multiset.map_id]
#align finset.prod_multiset_count Finset.prod_multiset_count
#align finset.sum_multiset_count Finset.sum_multiset_count
@[to_additive]
theorem prod_multiset_count_of_subset [DecidableEq α] [CommMonoid α] (m : Multiset α) (s : Finset α)
(hs : m.toFinset ⊆ s) : m.prod = ∏ i ∈ s, i ^ m.count i := by
revert hs
refine Quot.induction_on m fun l => ?_
simp only [quot_mk_to_coe'', prod_coe, coe_count]
apply prod_list_count_of_subset l s
#align finset.prod_multiset_count_of_subset Finset.prod_multiset_count_of_subset
#align finset.sum_multiset_count_of_subset Finset.sum_multiset_count_of_subset
@[to_additive]
theorem prod_mem_multiset [DecidableEq α] (m : Multiset α) (f : { x // x ∈ m } → β) (g : α → β)
(hfg : ∀ x, f x = g x) : ∏ x : { x // x ∈ m }, f x = ∏ x ∈ m.toFinset, g x := by
refine prod_bij' (fun x _ ↦ x) (fun x hx ↦ ⟨x, Multiset.mem_toFinset.1 hx⟩) ?_ ?_ ?_ ?_ ?_ <;>
simp [hfg]
#align finset.prod_mem_multiset Finset.prod_mem_multiset
#align finset.sum_mem_multiset Finset.sum_mem_multiset
/-- To prove a property of a product, it suffices to prove that
the property is multiplicative and holds on factors. -/
@[to_additive "To prove a property of a sum, it suffices to prove that
the property is additive and holds on summands."]
theorem prod_induction {M : Type*} [CommMonoid M] (f : α → M) (p : M → Prop)
(hom : ∀ a b, p a → p b → p (a * b)) (unit : p 1) (base : ∀ x ∈ s, p <| f x) :
p <| ∏ x ∈ s, f x :=
Multiset.prod_induction _ _ hom unit (Multiset.forall_mem_map_iff.mpr base)
#align finset.prod_induction Finset.prod_induction
#align finset.sum_induction Finset.sum_induction
/-- To prove a property of a product, it suffices to prove that
the property is multiplicative and holds on factors. -/
@[to_additive "To prove a property of a sum, it suffices to prove that
the property is additive and holds on summands."]
theorem prod_induction_nonempty {M : Type*} [CommMonoid M] (f : α → M) (p : M → Prop)
(hom : ∀ a b, p a → p b → p (a * b)) (nonempty : s.Nonempty) (base : ∀ x ∈ s, p <| f x) :
p <| ∏ x ∈ s, f x :=
Multiset.prod_induction_nonempty p hom (by simp [nonempty_iff_ne_empty.mp nonempty])
(Multiset.forall_mem_map_iff.mpr base)
#align finset.prod_induction_nonempty Finset.prod_induction_nonempty
#align finset.sum_induction_nonempty Finset.sum_induction_nonempty
/-- For any product along `{0, ..., n - 1}` of a commutative-monoid-valued function, we can verify
that it's equal to a different function just by checking ratios of adjacent terms.
This is a multiplicative discrete analogue of the fundamental theorem of calculus. -/
@[to_additive "For any sum along `{0, ..., n - 1}` of a commutative-monoid-valued function, we can
verify that it's equal to a different function just by checking differences of adjacent terms.
This is a discrete analogue of the fundamental theorem of calculus."]
theorem prod_range_induction (f s : ℕ → β) (base : s 0 = 1)
(step : ∀ n, s (n + 1) = s n * f n) (n : ℕ) :
∏ k ∈ Finset.range n, f k = s n := by
induction' n with k hk
· rw [Finset.prod_range_zero, base]
· simp only [hk, Finset.prod_range_succ, step, mul_comm]
#align finset.prod_range_induction Finset.prod_range_induction
#align finset.sum_range_induction Finset.sum_range_induction
/-- A telescoping product along `{0, ..., n - 1}` of a commutative group valued function reduces to
the ratio of the last and first factors. -/
@[to_additive "A telescoping sum along `{0, ..., n - 1}` of an additive commutative group valued
function reduces to the difference of the last and first terms."]
theorem prod_range_div {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
(∏ i ∈ range n, f (i + 1) / f i) = f n / f 0 := by apply prod_range_induction <;> simp
#align finset.prod_range_div Finset.prod_range_div
#align finset.sum_range_sub Finset.sum_range_sub
@[to_additive]
theorem prod_range_div' {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
(∏ i ∈ range n, f i / f (i + 1)) = f 0 / f n := by apply prod_range_induction <;> simp
#align finset.prod_range_div' Finset.prod_range_div'
#align finset.sum_range_sub' Finset.sum_range_sub'
@[to_additive]
theorem eq_prod_range_div {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
f n = f 0 * ∏ i ∈ range n, f (i + 1) / f i := by rw [prod_range_div, mul_div_cancel]
#align finset.eq_prod_range_div Finset.eq_prod_range_div
#align finset.eq_sum_range_sub Finset.eq_sum_range_sub
@[to_additive]
theorem eq_prod_range_div' {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
f n = ∏ i ∈ range (n + 1), if i = 0 then f 0 else f i / f (i - 1) := by
conv_lhs => rw [Finset.eq_prod_range_div f]
simp [Finset.prod_range_succ', mul_comm]
#align finset.eq_prod_range_div' Finset.eq_prod_range_div'
#align finset.eq_sum_range_sub' Finset.eq_sum_range_sub'
/-- A telescoping sum along `{0, ..., n-1}` of an `ℕ`-valued function
reduces to the difference of the last and first terms
when the function we are summing is monotone.
-/
theorem sum_range_tsub [CanonicallyOrderedAddCommMonoid α] [Sub α] [OrderedSub α]
[ContravariantClass α α (· + ·) (· ≤ ·)] {f : ℕ → α} (h : Monotone f) (n : ℕ) :
∑ i ∈ range n, (f (i + 1) - f i) = f n - f 0 := by
apply sum_range_induction
case base => apply tsub_self
case step =>
intro n
have h₁ : f n ≤ f (n + 1) := h (Nat.le_succ _)
have h₂ : f 0 ≤ f n := h (Nat.zero_le _)
rw [tsub_add_eq_add_tsub h₂, add_tsub_cancel_of_le h₁]
#align finset.sum_range_tsub Finset.sum_range_tsub
@[to_additive (attr := simp)]
theorem prod_const (b : β) : ∏ _x ∈ s, b = b ^ s.card :=
(congr_arg _ <| s.val.map_const b).trans <| Multiset.prod_replicate s.card b
#align finset.prod_const Finset.prod_const
#align finset.sum_const Finset.sum_const
@[to_additive sum_eq_card_nsmul]
theorem prod_eq_pow_card {b : β} (hf : ∀ a ∈ s, f a = b) : ∏ a ∈ s, f a = b ^ s.card :=
(prod_congr rfl hf).trans <| prod_const _
#align finset.prod_eq_pow_card Finset.prod_eq_pow_card
#align finset.sum_eq_card_nsmul Finset.sum_eq_card_nsmul
@[to_additive card_nsmul_add_sum]
theorem pow_card_mul_prod {b : β} : b ^ s.card * ∏ a ∈ s, f a = ∏ a ∈ s, b * f a :=
(Finset.prod_const b).symm ▸ prod_mul_distrib.symm
@[to_additive sum_add_card_nsmul]
theorem prod_mul_pow_card {b : β} : (∏ a ∈ s, f a) * b ^ s.card = ∏ a ∈ s, f a * b :=
(Finset.prod_const b).symm ▸ prod_mul_distrib.symm
@[to_additive]
theorem pow_eq_prod_const (b : β) : ∀ n, b ^ n = ∏ _k ∈ range n, b := by simp
#align finset.pow_eq_prod_const Finset.pow_eq_prod_const
#align finset.nsmul_eq_sum_const Finset.nsmul_eq_sum_const
@[to_additive]
theorem prod_pow (s : Finset α) (n : ℕ) (f : α → β) : ∏ x ∈ s, f x ^ n = (∏ x ∈ s, f x) ^ n :=
Multiset.prod_map_pow
#align finset.prod_pow Finset.prod_pow
#align finset.sum_nsmul Finset.sum_nsmul
@[to_additive sum_nsmul_assoc]
lemma prod_pow_eq_pow_sum (s : Finset ι) (f : ι → ℕ) (a : β) :
∏ i ∈ s, a ^ f i = a ^ ∑ i ∈ s, f i :=
cons_induction (by simp) (fun _ _ _ _ ↦ by simp [prod_cons, sum_cons, pow_add, *]) s
#align finset.prod_pow_eq_pow_sum Finset.prod_pow_eq_pow_sum
/-- A product over `Finset.powersetCard` which only depends on the size of the sets is constant. -/
@[to_additive
"A sum over `Finset.powersetCard` which only depends on the size of the sets is constant."]
lemma prod_powersetCard (n : ℕ) (s : Finset α) (f : ℕ → β) :
∏ t ∈ powersetCard n s, f t.card = f n ^ s.card.choose n := by
rw [prod_eq_pow_card, card_powersetCard]; rintro a ha; rw [(mem_powersetCard.1 ha).2]
@[to_additive]
theorem prod_flip {n : ℕ} (f : ℕ → β) :
(∏ r ∈ range (n + 1), f (n - r)) = ∏ k ∈ range (n + 1), f k := by
induction' n with n ih
· rw [prod_range_one, prod_range_one]
· rw [prod_range_succ', prod_range_succ _ (Nat.succ n)]
simp [← ih]
#align finset.prod_flip Finset.prod_flip
#align finset.sum_flip Finset.sum_flip
@[to_additive]
theorem prod_involution {s : Finset α} {f : α → β} :
∀ (g : ∀ a ∈ s, α) (_ : ∀ a ha, f a * f (g a ha) = 1) (_ : ∀ a ha, f a ≠ 1 → g a ha ≠ a)
(g_mem : ∀ a ha, g a ha ∈ s) (_ : ∀ a ha, g (g a ha) (g_mem a ha) = a),
∏ x ∈ s, f x = 1 := by
haveI := Classical.decEq α; haveI := Classical.decEq β
exact
Finset.strongInductionOn s fun s ih g h g_ne g_mem g_inv =>
s.eq_empty_or_nonempty.elim (fun hs => hs.symm ▸ rfl) fun ⟨x, hx⟩ =>
have hmem : ∀ y ∈ (s.erase x).erase (g x hx), y ∈ s := fun y hy =>
mem_of_mem_erase (mem_of_mem_erase hy)
have g_inj : ∀ {x hx y hy}, g x hx = g y hy → x = y := fun {x hx y hy} h => by
rw [← g_inv x hx, ← g_inv y hy]; simp [h]
have ih' : (∏ y ∈ erase (erase s x) (g x hx), f y) = (1 : β) :=
ih ((s.erase x).erase (g x hx))
⟨Subset.trans (erase_subset _ _) (erase_subset _ _), fun h =>
not_mem_erase (g x hx) (s.erase x) (h (g_mem x hx))⟩
(fun y hy => g y (hmem y hy)) (fun y hy => h y (hmem y hy))
(fun y hy => g_ne y (hmem y hy))
(fun y hy =>
mem_erase.2
⟨fun h : g y _ = g x hx => by simp [g_inj h] at hy,
mem_erase.2
⟨fun h : g y _ = x => by
have : y = g x hx := g_inv y (hmem y hy) ▸ by simp [h]
simp [this] at hy, g_mem y (hmem y hy)⟩⟩)
fun y hy => g_inv y (hmem y hy)
if hx1 : f x = 1 then
ih' ▸
Eq.symm
(prod_subset hmem fun y hy hy₁ =>
have : y = x ∨ y = g x hx := by
simpa [hy, -not_and, mem_erase, not_and_or, or_comm] using hy₁
this.elim (fun hy => hy.symm ▸ hx1) fun hy =>
h x hx ▸ hy ▸ hx1.symm ▸ (one_mul _).symm)
else by
rw [← insert_erase hx, prod_insert (not_mem_erase _ _), ←
insert_erase (mem_erase.2 ⟨g_ne x hx hx1, g_mem x hx⟩),
prod_insert (not_mem_erase _ _), ih', mul_one, h x hx]
#align finset.prod_involution Finset.prod_involution
#align finset.sum_involution Finset.sum_involution
/-- The product of the composition of functions `f` and `g`, is the product over `b ∈ s.image g` of
`f b` to the power of the cardinality of the fibre of `b`. See also `Finset.prod_image`. -/
@[to_additive "The sum of the composition of functions `f` and `g`, is the sum over `b ∈ s.image g`
of `f b` times of the cardinality of the fibre of `b`. See also `Finset.sum_image`."]
theorem prod_comp [DecidableEq γ] (f : γ → β) (g : α → γ) :
∏ a ∈ s, f (g a) = ∏ b ∈ s.image g, f b ^ (s.filter fun a => g a = b).card := by
simp_rw [← prod_const, prod_fiberwise_of_maps_to' fun _ ↦ mem_image_of_mem _]
#align finset.prod_comp Finset.prod_comp
#align finset.sum_comp Finset.sum_comp
@[to_additive]
theorem prod_piecewise [DecidableEq α] (s t : Finset α) (f g : α → β) :
(∏ x ∈ s, (t.piecewise f g) x) = (∏ x ∈ s ∩ t, f x) * ∏ x ∈ s \ t, g x := by
erw [prod_ite, filter_mem_eq_inter, ← sdiff_eq_filter]
#align finset.prod_piecewise Finset.prod_piecewise
#align finset.sum_piecewise Finset.sum_piecewise
@[to_additive]
theorem prod_inter_mul_prod_diff [DecidableEq α] (s t : Finset α) (f : α → β) :
(∏ x ∈ s ∩ t, f x) * ∏ x ∈ s \ t, f x = ∏ x ∈ s, f x := by
convert (s.prod_piecewise t f f).symm
simp (config := { unfoldPartialApp := true }) [Finset.piecewise]
#align finset.prod_inter_mul_prod_diff Finset.prod_inter_mul_prod_diff
#align finset.sum_inter_add_sum_diff Finset.sum_inter_add_sum_diff
@[to_additive]
theorem prod_eq_mul_prod_diff_singleton [DecidableEq α] {s : Finset α} {i : α} (h : i ∈ s)
(f : α → β) : ∏ x ∈ s, f x = f i * ∏ x ∈ s \ {i}, f x := by
convert (s.prod_inter_mul_prod_diff {i} f).symm
simp [h]
#align finset.prod_eq_mul_prod_diff_singleton Finset.prod_eq_mul_prod_diff_singleton
#align finset.sum_eq_add_sum_diff_singleton Finset.sum_eq_add_sum_diff_singleton
@[to_additive]
theorem prod_eq_prod_diff_singleton_mul [DecidableEq α] {s : Finset α} {i : α} (h : i ∈ s)
(f : α → β) : ∏ x ∈ s, f x = (∏ x ∈ s \ {i}, f x) * f i := by
rw [prod_eq_mul_prod_diff_singleton h, mul_comm]
#align finset.prod_eq_prod_diff_singleton_mul Finset.prod_eq_prod_diff_singleton_mul
#align finset.sum_eq_sum_diff_singleton_add Finset.sum_eq_sum_diff_singleton_add
@[to_additive]
theorem _root_.Fintype.prod_eq_mul_prod_compl [DecidableEq α] [Fintype α] (a : α) (f : α → β) :
∏ i, f i = f a * ∏ i ∈ {a}ᶜ, f i :=
prod_eq_mul_prod_diff_singleton (mem_univ a) f
#align fintype.prod_eq_mul_prod_compl Fintype.prod_eq_mul_prod_compl
#align fintype.sum_eq_add_sum_compl Fintype.sum_eq_add_sum_compl
@[to_additive]
theorem _root_.Fintype.prod_eq_prod_compl_mul [DecidableEq α] [Fintype α] (a : α) (f : α → β) :
∏ i, f i = (∏ i ∈ {a}ᶜ, f i) * f a :=
prod_eq_prod_diff_singleton_mul (mem_univ a) f
#align fintype.prod_eq_prod_compl_mul Fintype.prod_eq_prod_compl_mul
#align fintype.sum_eq_sum_compl_add Fintype.sum_eq_sum_compl_add
theorem dvd_prod_of_mem (f : α → β) {a : α} {s : Finset α} (ha : a ∈ s) : f a ∣ ∏ i ∈ s, f i := by
classical
rw [Finset.prod_eq_mul_prod_diff_singleton ha]
exact dvd_mul_right _ _
#align finset.dvd_prod_of_mem Finset.dvd_prod_of_mem
/-- A product can be partitioned into a product of products, each equivalent under a setoid. -/
@[to_additive "A sum can be partitioned into a sum of sums, each equivalent under a setoid."]
theorem prod_partition (R : Setoid α) [DecidableRel R.r] :
∏ x ∈ s, f x = ∏ xbar ∈ s.image Quotient.mk'', ∏ y ∈ s.filter (⟦·⟧ = xbar), f y := by
refine (Finset.prod_image' f fun x _hx => ?_).symm
rfl
#align finset.prod_partition Finset.prod_partition
#align finset.sum_partition Finset.sum_partition
/-- If we can partition a product into subsets that cancel out, then the whole product cancels. -/
@[to_additive "If we can partition a sum into subsets that cancel out, then the whole sum cancels."]
theorem prod_cancels_of_partition_cancels (R : Setoid α) [DecidableRel R.r]
(h : ∀ x ∈ s, ∏ a ∈ s.filter fun y => y ≈ x, f a = 1) : ∏ x ∈ s, f x = 1 := by
rw [prod_partition R, ← Finset.prod_eq_one]
intro xbar xbar_in_s
obtain ⟨x, x_in_s, rfl⟩ := mem_image.mp xbar_in_s
simp only [← Quotient.eq] at h
exact h x x_in_s
#align finset.prod_cancels_of_partition_cancels Finset.prod_cancels_of_partition_cancels
#align finset.sum_cancels_of_partition_cancels Finset.sum_cancels_of_partition_cancels
@[to_additive]
theorem prod_update_of_not_mem [DecidableEq α] {s : Finset α} {i : α} (h : i ∉ s) (f : α → β)
(b : β) : ∏ x ∈ s, Function.update f i b x = ∏ x ∈ s, f x := by
apply prod_congr rfl
intros j hj
have : j ≠ i := by
rintro rfl
exact h hj
simp [this]
#align finset.prod_update_of_not_mem Finset.prod_update_of_not_mem
#align finset.sum_update_of_not_mem Finset.sum_update_of_not_mem
@[to_additive]
theorem prod_update_of_mem [DecidableEq α] {s : Finset α} {i : α} (h : i ∈ s) (f : α → β) (b : β) :
∏ x ∈ s, Function.update f i b x = b * ∏ x ∈ s \ singleton i, f x := by
rw [update_eq_piecewise, prod_piecewise]
simp [h]
#align finset.prod_update_of_mem Finset.prod_update_of_mem
#align finset.sum_update_of_mem Finset.sum_update_of_mem
/-- If a product of a `Finset` of size at most 1 has a given value, so
do the terms in that product. -/
@[to_additive eq_of_card_le_one_of_sum_eq "If a sum of a `Finset` of size at most 1 has a given
value, so do the terms in that sum."]
theorem eq_of_card_le_one_of_prod_eq {s : Finset α} (hc : s.card ≤ 1) {f : α → β} {b : β}
(h : ∏ x ∈ s, f x = b) : ∀ x ∈ s, f x = b := by
intro x hx
by_cases hc0 : s.card = 0
· exact False.elim (card_ne_zero_of_mem hx hc0)
· have h1 : s.card = 1 := le_antisymm hc (Nat.one_le_of_lt (Nat.pos_of_ne_zero hc0))
rw [card_eq_one] at h1
cases' h1 with x2 hx2
rw [hx2, mem_singleton] at hx
simp_rw [hx2] at h
rw [hx]
rw [prod_singleton] at h
exact h
#align finset.eq_of_card_le_one_of_prod_eq Finset.eq_of_card_le_one_of_prod_eq
#align finset.eq_of_card_le_one_of_sum_eq Finset.eq_of_card_le_one_of_sum_eq
/-- Taking a product over `s : Finset α` is the same as multiplying the value on a single element
`f a` by the product of `s.erase a`.
See `Multiset.prod_map_erase` for the `Multiset` version. -/
@[to_additive "Taking a sum over `s : Finset α` is the same as adding the value on a single element
`f a` to the sum over `s.erase a`.
See `Multiset.sum_map_erase` for the `Multiset` version."]
theorem mul_prod_erase [DecidableEq α] (s : Finset α) (f : α → β) {a : α} (h : a ∈ s) :
(f a * ∏ x ∈ s.erase a, f x) = ∏ x ∈ s, f x := by
rw [← prod_insert (not_mem_erase a s), insert_erase h]
#align finset.mul_prod_erase Finset.mul_prod_erase
#align finset.add_sum_erase Finset.add_sum_erase
/-- A variant of `Finset.mul_prod_erase` with the multiplication swapped. -/
@[to_additive "A variant of `Finset.add_sum_erase` with the addition swapped."]
theorem prod_erase_mul [DecidableEq α] (s : Finset α) (f : α → β) {a : α} (h : a ∈ s) :
(∏ x ∈ s.erase a, f x) * f a = ∏ x ∈ s, f x := by rw [mul_comm, mul_prod_erase s f h]
#align finset.prod_erase_mul Finset.prod_erase_mul
#align finset.sum_erase_add Finset.sum_erase_add
/-- If a function applied at a point is 1, a product is unchanged by
removing that point, if present, from a `Finset`. -/
@[to_additive "If a function applied at a point is 0, a sum is unchanged by
removing that point, if present, from a `Finset`."]
theorem prod_erase [DecidableEq α] (s : Finset α) {f : α → β} {a : α} (h : f a = 1) :
∏ x ∈ s.erase a, f x = ∏ x ∈ s, f x := by
rw [← sdiff_singleton_eq_erase]
refine prod_subset sdiff_subset fun x hx hnx => ?_
rw [sdiff_singleton_eq_erase] at hnx
rwa [eq_of_mem_of_not_mem_erase hx hnx]
#align finset.prod_erase Finset.prod_erase
#align finset.sum_erase Finset.sum_erase
/-- See also `Finset.prod_boole`. -/
@[to_additive "See also `Finset.sum_boole`."]
theorem prod_ite_one (s : Finset α) (p : α → Prop) [DecidablePred p]
(h : ∀ i ∈ s, ∀ j ∈ s, p i → p j → i = j) (a : β) :
∏ i ∈ s, ite (p i) a 1 = ite (∃ i ∈ s, p i) a 1 := by
split_ifs with h
· obtain ⟨i, hi, hpi⟩ := h
rw [prod_eq_single_of_mem _ hi, if_pos hpi]
exact fun j hj hji ↦ if_neg fun hpj ↦ hji <| h _ hj _ hi hpj hpi
· push_neg at h
rw [prod_eq_one]
exact fun i hi => if_neg (h i hi)
#align finset.prod_ite_one Finset.prod_ite_one
#align finset.sum_ite_zero Finset.sum_ite_zero
@[to_additive]
theorem prod_erase_lt_of_one_lt {γ : Type*} [DecidableEq α] [OrderedCommMonoid γ]
[CovariantClass γ γ (· * ·) (· < ·)] {s : Finset α} {d : α} (hd : d ∈ s) {f : α → γ}
(hdf : 1 < f d) : ∏ m ∈ s.erase d, f m < ∏ m ∈ s, f m := by
conv in ∏ m ∈ s, f m => rw [← Finset.insert_erase hd]
rw [Finset.prod_insert (Finset.not_mem_erase d s)]
exact lt_mul_of_one_lt_left' _ hdf
#align finset.prod_erase_lt_of_one_lt Finset.prod_erase_lt_of_one_lt
#align finset.sum_erase_lt_of_pos Finset.sum_erase_lt_of_pos
/-- If a product is 1 and the function is 1 except possibly at one
point, it is 1 everywhere on the `Finset`. -/
@[to_additive "If a sum is 0 and the function is 0 except possibly at one
point, it is 0 everywhere on the `Finset`."]
theorem eq_one_of_prod_eq_one {s : Finset α} {f : α → β} {a : α} (hp : ∏ x ∈ s, f x = 1)
(h1 : ∀ x ∈ s, x ≠ a → f x = 1) : ∀ x ∈ s, f x = 1 := by
intro x hx
classical
by_cases h : x = a
· rw [h]
rw [h] at hx
rw [← prod_subset (singleton_subset_iff.2 hx) fun t ht ha => h1 t ht (not_mem_singleton.1 ha),
prod_singleton] at hp
exact hp
· exact h1 x hx h
#align finset.eq_one_of_prod_eq_one Finset.eq_one_of_prod_eq_one
#align finset.eq_zero_of_sum_eq_zero Finset.eq_zero_of_sum_eq_zero
@[to_additive sum_boole_nsmul]
theorem prod_pow_boole [DecidableEq α] (s : Finset α) (f : α → β) (a : α) :
(∏ x ∈ s, f x ^ ite (a = x) 1 0) = ite (a ∈ s) (f a) 1 := by simp
#align finset.prod_pow_boole Finset.prod_pow_boole
theorem prod_dvd_prod_of_dvd {S : Finset α} (g1 g2 : α → β) (h : ∀ a ∈ S, g1 a ∣ g2 a) :
S.prod g1 ∣ S.prod g2 := by
classical
induction' S using Finset.induction_on' with a T _haS _hTS haT IH
· simp
· rw [Finset.prod_insert haT, prod_insert haT]
exact mul_dvd_mul (h a <| T.mem_insert_self a) <| IH fun b hb ↦ h b <| mem_insert_of_mem hb
#align finset.prod_dvd_prod_of_dvd Finset.prod_dvd_prod_of_dvd
theorem prod_dvd_prod_of_subset {ι M : Type*} [CommMonoid M] (s t : Finset ι) (f : ι → M)
(h : s ⊆ t) : (∏ i ∈ s, f i) ∣ ∏ i ∈ t, f i :=
Multiset.prod_dvd_prod_of_le <| Multiset.map_le_map <| by simpa
#align finset.prod_dvd_prod_of_subset Finset.prod_dvd_prod_of_subset
end CommMonoid
section CancelCommMonoid
variable [DecidableEq ι] [CancelCommMonoid α] {s t : Finset ι} {f : ι → α}
@[to_additive]
lemma prod_sdiff_eq_prod_sdiff_iff :
∏ i ∈ s \ t, f i = ∏ i ∈ t \ s, f i ↔ ∏ i ∈ s, f i = ∏ i ∈ t, f i :=
eq_comm.trans $ eq_iff_eq_of_mul_eq_mul $ by
rw [← prod_union disjoint_sdiff_self_left, ← prod_union disjoint_sdiff_self_left,
sdiff_union_self_eq_union, sdiff_union_self_eq_union, union_comm]
@[to_additive]
lemma prod_sdiff_ne_prod_sdiff_iff :
∏ i ∈ s \ t, f i ≠ ∏ i ∈ t \ s, f i ↔ ∏ i ∈ s, f i ≠ ∏ i ∈ t, f i :=
prod_sdiff_eq_prod_sdiff_iff.not
end CancelCommMonoid
theorem card_eq_sum_ones (s : Finset α) : s.card = ∑ x ∈ s, 1 := by simp
#align finset.card_eq_sum_ones Finset.card_eq_sum_ones
theorem sum_const_nat {m : ℕ} {f : α → ℕ} (h₁ : ∀ x ∈ s, f x = m) :
∑ x ∈ s, f x = card s * m := by
rw [← Nat.nsmul_eq_mul, ← sum_const]
apply sum_congr rfl h₁
#align finset.sum_const_nat Finset.sum_const_nat
lemma sum_card_fiberwise_eq_card_filter {κ : Type*} [DecidableEq κ] (s : Finset ι) (t : Finset κ)
(g : ι → κ) : ∑ j ∈ t, (s.filter fun i ↦ g i = j).card = (s.filter fun i ↦ g i ∈ t).card := by
simpa only [card_eq_sum_ones] using sum_fiberwise_eq_sum_filter _ _ _ _
lemma card_filter (p) [DecidablePred p] (s : Finset α) :
(filter p s).card = ∑ a ∈ s, ite (p a) 1 0 := by simp [sum_ite]
#align finset.card_filter Finset.card_filter
section Opposite
open MulOpposite
/-- Moving to the opposite additive commutative monoid commutes with summing. -/
@[simp]
theorem op_sum [AddCommMonoid β] {s : Finset α} (f : α → β) :
op (∑ x ∈ s, f x) = ∑ x ∈ s, op (f x) :=
map_sum (opAddEquiv : β ≃+ βᵐᵒᵖ) _ _
#align finset.op_sum Finset.op_sum
@[simp]
theorem unop_sum [AddCommMonoid β] {s : Finset α} (f : α → βᵐᵒᵖ) :
unop (∑ x ∈ s, f x) = ∑ x ∈ s, unop (f x) :=
map_sum (opAddEquiv : β ≃+ βᵐᵒᵖ).symm _ _
#align finset.unop_sum Finset.unop_sum
end Opposite
section DivisionCommMonoid
variable [DivisionCommMonoid β]
@[to_additive (attr := simp)]
theorem prod_inv_distrib : (∏ x ∈ s, (f x)⁻¹) = (∏ x ∈ s, f x)⁻¹ :=
Multiset.prod_map_inv
#align finset.prod_inv_distrib Finset.prod_inv_distrib
#align finset.sum_neg_distrib Finset.sum_neg_distrib
@[to_additive (attr := simp)]
theorem prod_div_distrib : ∏ x ∈ s, f x / g x = (∏ x ∈ s, f x) / ∏ x ∈ s, g x :=
Multiset.prod_map_div
#align finset.prod_div_distrib Finset.prod_div_distrib
#align finset.sum_sub_distrib Finset.sum_sub_distrib
@[to_additive]
theorem prod_zpow (f : α → β) (s : Finset α) (n : ℤ) : ∏ a ∈ s, f a ^ n = (∏ a ∈ s, f a) ^ n :=
Multiset.prod_map_zpow
#align finset.prod_zpow Finset.prod_zpow
#align finset.sum_zsmul Finset.sum_zsmul
end DivisionCommMonoid
section CommGroup
variable [CommGroup β] [DecidableEq α]
@[to_additive (attr := simp)]
theorem prod_sdiff_eq_div (h : s₁ ⊆ s₂) :
∏ x ∈ s₂ \ s₁, f x = (∏ x ∈ s₂, f x) / ∏ x ∈ s₁, f x := by
rw [eq_div_iff_mul_eq', prod_sdiff h]
#align finset.prod_sdiff_eq_div Finset.prod_sdiff_eq_div
#align finset.sum_sdiff_eq_sub Finset.sum_sdiff_eq_sub
@[to_additive]
theorem prod_sdiff_div_prod_sdiff :
(∏ x ∈ s₂ \ s₁, f x) / ∏ x ∈ s₁ \ s₂, f x = (∏ x ∈ s₂, f x) / ∏ x ∈ s₁, f x := by
simp [← Finset.prod_sdiff (@inf_le_left _ _ s₁ s₂), ← Finset.prod_sdiff (@inf_le_right _ _ s₁ s₂)]
#align finset.prod_sdiff_div_prod_sdiff Finset.prod_sdiff_div_prod_sdiff
#align finset.sum_sdiff_sub_sum_sdiff Finset.sum_sdiff_sub_sum_sdiff
@[to_additive (attr := simp)]
theorem prod_erase_eq_div {a : α} (h : a ∈ s) :
∏ x ∈ s.erase a, f x = (∏ x ∈ s, f x) / f a := by
rw [eq_div_iff_mul_eq', prod_erase_mul _ _ h]
#align finset.prod_erase_eq_div Finset.prod_erase_eq_div
#align finset.sum_erase_eq_sub Finset.sum_erase_eq_sub
end CommGroup
@[simp]
theorem card_sigma {σ : α → Type*} (s : Finset α) (t : ∀ a, Finset (σ a)) :
card (s.sigma t) = ∑ a ∈ s, card (t a) :=
Multiset.card_sigma _ _
#align finset.card_sigma Finset.card_sigma
@[simp]
theorem card_disjiUnion (s : Finset α) (t : α → Finset β) (h) :
(s.disjiUnion t h).card = s.sum fun i => (t i).card :=
Multiset.card_bind _ _
#align finset.card_disj_Union Finset.card_disjiUnion
| Mathlib/Algebra/BigOperators/Group/Finset.lean | 2,167 | 2,173 | theorem card_biUnion [DecidableEq β] {s : Finset α} {t : α → Finset β}
(h : ∀ x ∈ s, ∀ y ∈ s, x ≠ y → Disjoint (t x) (t y)) :
(s.biUnion t).card = ∑ u ∈ s, card (t u) :=
calc
(s.biUnion t).card = ∑ i ∈ s.biUnion t, 1 := card_eq_sum_ones _
_ = ∑ a ∈ s, ∑ _i ∈ t a, 1 := Finset.sum_biUnion h
_ = ∑ u ∈ s, card (t u) := by | simp_rw [card_eq_sum_ones]
|
/-
Copyright (c) 2022 Eric Wieser. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Eric Wieser
-/
import Mathlib.Data.DFinsupp.Order
#align_import data.dfinsupp.multiset from "leanprover-community/mathlib"@"442a83d738cb208d3600056c489be16900ba701d"
/-!
# Equivalence between `Multiset` and `ℕ`-valued finitely supported functions
This defines `DFinsupp.toMultiset` the equivalence between `Π₀ a : α, ℕ` and `Multiset α`, along
with `Multiset.toDFinsupp` the reverse equivalence.
-/
open Function
variable {α : Type*} {β : α → Type*}
namespace DFinsupp
/-- Non-dependent special case of `DFinsupp.addZeroClass` to help typeclass search. -/
instance addZeroClass' {β} [AddZeroClass β] : AddZeroClass (Π₀ _ : α, β) :=
@DFinsupp.addZeroClass α (fun _ ↦ β) _
#align dfinsupp.add_zero_class' DFinsupp.addZeroClass'
variable [DecidableEq α] {s t : Multiset α}
/-- A DFinsupp version of `Finsupp.toMultiset`. -/
def toMultiset : (Π₀ _ : α, ℕ) →+ Multiset α :=
DFinsupp.sumAddHom fun a : α ↦ Multiset.replicateAddMonoidHom a
#align dfinsupp.to_multiset DFinsupp.toMultiset
@[simp]
theorem toMultiset_single (a : α) (n : ℕ) :
toMultiset (DFinsupp.single a n) = Multiset.replicate n a :=
DFinsupp.sumAddHom_single _ _ _
#align dfinsupp.to_multiset_single DFinsupp.toMultiset_single
end DFinsupp
namespace Multiset
variable [DecidableEq α] {s t : Multiset α}
/-- A DFinsupp version of `Multiset.toFinsupp`. -/
def toDFinsupp : Multiset α →+ Π₀ _ : α, ℕ where
toFun s :=
{ toFun := fun n ↦ s.count n
support' := Trunc.mk ⟨s, fun i ↦ (em (i ∈ s)).imp_right Multiset.count_eq_zero_of_not_mem⟩ }
map_zero' := rfl
map_add' _ _ := DFinsupp.ext fun _ ↦ Multiset.count_add _ _ _
#align multiset.to_dfinsupp Multiset.toDFinsupp
@[simp]
theorem toDFinsupp_apply (s : Multiset α) (a : α) : Multiset.toDFinsupp s a = s.count a :=
rfl
#align multiset.to_dfinsupp_apply Multiset.toDFinsupp_apply
@[simp]
theorem toDFinsupp_support (s : Multiset α) : s.toDFinsupp.support = s.toFinset :=
Finset.filter_true_of_mem fun _ hx ↦ count_ne_zero.mpr <| Multiset.mem_toFinset.1 hx
#align multiset.to_dfinsupp_support Multiset.toDFinsupp_support
@[simp]
theorem toDFinsupp_replicate (a : α) (n : ℕ) :
toDFinsupp (Multiset.replicate n a) = DFinsupp.single a n := by
ext i
dsimp [toDFinsupp]
simp [count_replicate, eq_comm]
#align multiset.to_dfinsupp_replicate Multiset.toDFinsupp_replicate
@[simp]
theorem toDFinsupp_singleton (a : α) : toDFinsupp {a} = DFinsupp.single a 1 := by
rw [← replicate_one, toDFinsupp_replicate]
#align multiset.to_dfinsupp_singleton Multiset.toDFinsupp_singleton
/-- `Multiset.toDFinsupp` as an `AddEquiv`. -/
@[simps! apply symm_apply]
def equivDFinsupp : Multiset α ≃+ Π₀ _ : α, ℕ :=
AddMonoidHom.toAddEquiv Multiset.toDFinsupp DFinsupp.toMultiset (by ext; simp) (by ext; simp)
#align multiset.equiv_dfinsupp Multiset.equivDFinsupp
@[simp]
theorem toDFinsupp_toMultiset (s : Multiset α) : DFinsupp.toMultiset (Multiset.toDFinsupp s) = s :=
equivDFinsupp.symm_apply_apply s
#align multiset.to_dfinsupp_to_multiset Multiset.toDFinsupp_toMultiset
theorem toDFinsupp_injective : Injective (toDFinsupp : Multiset α → Π₀ _a, ℕ) :=
equivDFinsupp.injective
#align multiset.to_dfinsupp_injective Multiset.toDFinsupp_injective
@[simp]
theorem toDFinsupp_inj : toDFinsupp s = toDFinsupp t ↔ s = t :=
toDFinsupp_injective.eq_iff
#align multiset.to_dfinsupp_inj Multiset.toDFinsupp_inj
@[simp]
theorem toDFinsupp_le_toDFinsupp : toDFinsupp s ≤ toDFinsupp t ↔ s ≤ t := by
simp [Multiset.le_iff_count, DFinsupp.le_def]
#align multiset.to_dfinsupp_le_to_dfinsupp Multiset.toDFinsupp_le_toDFinsupp
@[simp]
theorem toDFinsupp_lt_toDFinsupp : toDFinsupp s < toDFinsupp t ↔ s < t :=
lt_iff_lt_of_le_iff_le' toDFinsupp_le_toDFinsupp toDFinsupp_le_toDFinsupp
#align multiset.to_dfinsupp_lt_to_dfinsupp Multiset.toDFinsupp_lt_toDFinsupp
@[simp]
theorem toDFinsupp_inter (s t : Multiset α) : toDFinsupp (s ∩ t) = toDFinsupp s ⊓ toDFinsupp t := by
ext i; simp [inf_eq_min]
#align multiset.to_dfinsupp_inter Multiset.toDFinsupp_inter
@[simp]
theorem toDFinsupp_union (s t : Multiset α) : toDFinsupp (s ∪ t) = toDFinsupp s ⊔ toDFinsupp t := by
ext i; simp [sup_eq_max]
#align multiset.to_dfinsupp_union Multiset.toDFinsupp_union
end Multiset
namespace DFinsupp
variable [DecidableEq α] {f g : Π₀ _a : α, ℕ}
@[simp]
theorem toMultiset_toDFinsupp (f : Π₀ _ : α, ℕ) :
Multiset.toDFinsupp (DFinsupp.toMultiset f) = f :=
Multiset.equivDFinsupp.apply_symm_apply f
#align dfinsupp.to_multiset_to_dfinsupp DFinsupp.toMultiset_toDFinsupp
theorem toMultiset_injective : Injective (toMultiset : (Π₀ _a, ℕ) → Multiset α) :=
Multiset.equivDFinsupp.symm.injective
#align dfinsupp.to_multiset_injective DFinsupp.toMultiset_injective
@[simp]
theorem toMultiset_inj : toMultiset f = toMultiset g ↔ f = g :=
toMultiset_injective.eq_iff
#align dfinsupp.to_multiset_inj DFinsupp.toMultiset_inj
@[simp]
theorem toMultiset_le_toMultiset : toMultiset f ≤ toMultiset g ↔ f ≤ g := by
simp_rw [← Multiset.toDFinsupp_le_toDFinsupp, toMultiset_toDFinsupp]
#align dfinsupp.to_multiset_le_to_multiset DFinsupp.toMultiset_le_toMultiset
@[simp]
| Mathlib/Data/DFinsupp/Multiset.lean | 147 | 148 | theorem toMultiset_lt_toMultiset : toMultiset f < toMultiset g ↔ f < g := by |
simp_rw [← Multiset.toDFinsupp_lt_toDFinsupp, toMultiset_toDFinsupp]
|
/-
Copyright (c) 2021 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Analysis.Convex.Hull
import Mathlib.LinearAlgebra.AffineSpace.Independent
#align_import analysis.convex.simplicial_complex.basic from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Simplicial complexes
In this file, we define simplicial complexes in `𝕜`-modules. A simplicial complex is a collection
of simplices closed by inclusion (of vertices) and intersection (of underlying sets).
We model them by a downward-closed set of affine independent finite sets whose convex hulls "glue
nicely", each finite set and its convex hull corresponding respectively to the vertices and the
underlying set of a simplex.
## Main declarations
* `SimplicialComplex 𝕜 E`: A simplicial complex in the `𝕜`-module `E`.
* `SimplicialComplex.vertices`: The zero dimensional faces of a simplicial complex.
* `SimplicialComplex.facets`: The maximal faces of a simplicial complex.
## Notation
`s ∈ K` means that `s` is a face of `K`.
`K ≤ L` means that the faces of `K` are faces of `L`.
## Implementation notes
"glue nicely" usually means that the intersection of two faces (as sets in the ambient space) is a
face. Given that we store the vertices, not the faces, this would be a bit awkward to spell.
Instead, `SimplicialComplex.inter_subset_convexHull` is an equivalent condition which works on the
vertices.
## TODO
Simplicial complexes can be generalized to affine spaces once `ConvexHull` has been ported.
-/
open Finset Set
variable (𝕜 E : Type*) {ι : Type*} [OrderedRing 𝕜] [AddCommGroup E] [Module 𝕜 E]
namespace Geometry
-- TODO: update to new binder order? not sure what binder order is correct for `down_closed`.
/-- A simplicial complex in a `𝕜`-module is a collection of simplices which glue nicely together.
Note that the textbook meaning of "glue nicely" is given in
`Geometry.SimplicialComplex.disjoint_or_exists_inter_eq_convexHull`. It is mostly useless, as
`Geometry.SimplicialComplex.convexHull_inter_convexHull` is enough for all purposes. -/
@[ext]
structure SimplicialComplex where
/-- the faces of this simplicial complex: currently, given by their spanning vertices -/
faces : Set (Finset E)
/-- the empty set is not a face: hence, all faces are non-empty -/
not_empty_mem : ∅ ∉ faces
/-- the vertices in each face are affine independent: this is an implementation detail -/
indep : ∀ {s}, s ∈ faces → AffineIndependent 𝕜 ((↑) : s → E)
/-- faces are downward closed: a non-empty subset of its spanning vertices spans another face -/
down_closed : ∀ {s t}, s ∈ faces → t ⊆ s → t ≠ ∅ → t ∈ faces
inter_subset_convexHull : ∀ {s t}, s ∈ faces → t ∈ faces →
convexHull 𝕜 ↑s ∩ convexHull 𝕜 ↑t ⊆ convexHull 𝕜 (s ∩ t : Set E)
#align geometry.simplicial_complex Geometry.SimplicialComplex
namespace SimplicialComplex
variable {𝕜 E}
variable {K : SimplicialComplex 𝕜 E} {s t : Finset E} {x : E}
/-- A `Finset` belongs to a `SimplicialComplex` if it's a face of it. -/
instance : Membership (Finset E) (SimplicialComplex 𝕜 E) :=
⟨fun s K => s ∈ K.faces⟩
/-- The underlying space of a simplicial complex is the union of its faces. -/
def space (K : SimplicialComplex 𝕜 E) : Set E :=
⋃ s ∈ K.faces, convexHull 𝕜 (s : Set E)
#align geometry.simplicial_complex.space Geometry.SimplicialComplex.space
-- Porting note: Expanded `∃ s ∈ K.faces` to get the type to match more closely with Lean 3
theorem mem_space_iff : x ∈ K.space ↔ ∃ s ∈ K.faces, x ∈ convexHull 𝕜 (s : Set E) := by
simp [space]
#align geometry.simplicial_complex.mem_space_iff Geometry.SimplicialComplex.mem_space_iff
-- Porting note: Original proof was `:= subset_biUnion_of_mem hs`
| Mathlib/Analysis/Convex/SimplicialComplex/Basic.lean | 91 | 93 | theorem convexHull_subset_space (hs : s ∈ K.faces) : convexHull 𝕜 ↑s ⊆ K.space := by |
convert subset_biUnion_of_mem hs
rfl
|
/-
Copyright (c) 2023 Dagur Asgeirsson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Dagur Asgeirsson
-/
import Mathlib.Algebra.Category.ModuleCat.Free
import Mathlib.Topology.Category.Profinite.CofilteredLimit
import Mathlib.Topology.Category.Profinite.Product
import Mathlib.Topology.LocallyConstant.Algebra
import Mathlib.Init.Data.Bool.Lemmas
/-!
# Nöbeling's theorem
This file proves Nöbeling's theorem.
## Main result
* `LocallyConstant.freeOfProfinite`: Nöbeling's theorem.
For `S : Profinite`, the `ℤ`-module `LocallyConstant S ℤ` is free.
## Proof idea
We follow the proof of theorem 5.4 in [scholze2019condensed], in which the idea is to embed `S` in
a product of `I` copies of `Bool` for some sufficiently large `I`, and then to choose a
well-ordering on `I` and use ordinal induction over that well-order. Here we can let `I` be
the set of clopen subsets of `S` since `S` is totally separated.
The above means it suffices to prove the following statement: For a closed subset `C` of `I → Bool`,
the `ℤ`-module `LocallyConstant C ℤ` is free.
For `i : I`, let `e C i : LocallyConstant C ℤ` denote the map `fun f ↦ (if f.val i then 1 else 0)`.
The basis will consist of products `e C iᵣ * ⋯ * e C i₁` with `iᵣ > ⋯ > i₁` which cannot be written
as linear combinations of lexicographically smaller products. We call this set `GoodProducts C`
What is proved by ordinal induction is that this set is linearly independent. The fact that it
spans can be proved directly.
## References
- [scholze2019condensed], Theorem 5.4.
-/
universe u
namespace Profinite
namespace NobelingProof
variable {I : Type u} [LinearOrder I] [IsWellOrder I (·<·)] (C : Set (I → Bool))
open Profinite ContinuousMap CategoryTheory Limits Opposite Submodule
section Projections
/-!
## Projection maps
The purpose of this section is twofold.
Firstly, in the proof that the set `GoodProducts C` spans the whole module `LocallyConstant C ℤ`,
we need to project `C` down to finite discrete subsets and write `C` as a cofiltered limit of those.
Secondly, in the inductive argument, we need to project `C` down to "smaller" sets satisfying the
inductive hypothesis.
In this section we define the relevant projection maps and prove some compatibility results.
### Main definitions
* Let `J : I → Prop`. Then `Proj J : (I → Bool) → (I → Bool)` is the projection mapping everything
that satisfies `J i` to itself, and everything else to `false`.
* The image of `C` under `Proj J` is denoted `π C J` and the corresponding map `C → π C J` is called
`ProjRestrict`. If `J` implies `K` we have a map `ProjRestricts : π C K → π C J`.
* `spanCone_isLimit` establishes that when `C` is compact, it can be written as a limit of its
images under the maps `Proj (· ∈ s)` where `s : Finset I`.
-/
variable (J K L : I → Prop) [∀ i, Decidable (J i)] [∀ i, Decidable (K i)] [∀ i, Decidable (L i)]
/--
The projection mapping everything that satisfies `J i` to itself, and everything else to `false`
-/
def Proj : (I → Bool) → (I → Bool) :=
fun c i ↦ if J i then c i else false
@[simp]
theorem continuous_proj :
Continuous (Proj J : (I → Bool) → (I → Bool)) := by
dsimp (config := { unfoldPartialApp := true }) [Proj]
apply continuous_pi
intro i
split
· apply continuous_apply
· apply continuous_const
/-- The image of `Proj π J` -/
def π : Set (I → Bool) := (Proj J) '' C
/-- The restriction of `Proj π J` to a subset, mapping to its image. -/
@[simps!]
def ProjRestrict : C → π C J :=
Set.MapsTo.restrict (Proj J) _ _ (Set.mapsTo_image _ _)
@[simp]
theorem continuous_projRestrict : Continuous (ProjRestrict C J) :=
Continuous.restrict _ (continuous_proj _)
theorem proj_eq_self {x : I → Bool} (h : ∀ i, x i ≠ false → J i) : Proj J x = x := by
ext i
simp only [Proj, ite_eq_left_iff]
contrapose!
simpa only [ne_comm] using h i
theorem proj_prop_eq_self (hh : ∀ i x, x ∈ C → x i ≠ false → J i) : π C J = C := by
ext x
refine ⟨fun ⟨y, hy, h⟩ ↦ ?_, fun h ↦ ⟨x, h, ?_⟩⟩
· rwa [← h, proj_eq_self]; exact (hh · y hy)
· rw [proj_eq_self]; exact (hh · x h)
theorem proj_comp_of_subset (h : ∀ i, J i → K i) : (Proj J ∘ Proj K) =
(Proj J : (I → Bool) → (I → Bool)) := by
ext x i; dsimp [Proj]; aesop
theorem proj_eq_of_subset (h : ∀ i, J i → K i) : π (π C K) J = π C J := by
ext x
refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· obtain ⟨y, ⟨z, hz, rfl⟩, rfl⟩ := h
refine ⟨z, hz, (?_ : _ = (Proj J ∘ Proj K) z)⟩
rw [proj_comp_of_subset J K h]
· obtain ⟨y, hy, rfl⟩ := h
dsimp [π]
rw [← Set.image_comp]
refine ⟨y, hy, ?_⟩
rw [proj_comp_of_subset J K h]
variable {J K L}
/-- A variant of `ProjRestrict` with domain of the form `π C K` -/
@[simps!]
def ProjRestricts (h : ∀ i, J i → K i) : π C K → π C J :=
Homeomorph.setCongr (proj_eq_of_subset C J K h) ∘ ProjRestrict (π C K) J
@[simp]
theorem continuous_projRestricts (h : ∀ i, J i → K i) : Continuous (ProjRestricts C h) :=
Continuous.comp (Homeomorph.continuous _) (continuous_projRestrict _ _)
theorem surjective_projRestricts (h : ∀ i, J i → K i) : Function.Surjective (ProjRestricts C h) :=
(Homeomorph.surjective _).comp (Set.surjective_mapsTo_image_restrict _ _)
variable (J) in
theorem projRestricts_eq_id : ProjRestricts C (fun i (h : J i) ↦ h) = id := by
ext ⟨x, y, hy, rfl⟩ i
simp (config := { contextual := true }) only [π, Proj, ProjRestricts_coe, id_eq, if_true]
theorem projRestricts_eq_comp (hJK : ∀ i, J i → K i) (hKL : ∀ i, K i → L i) :
ProjRestricts C hJK ∘ ProjRestricts C hKL = ProjRestricts C (fun i ↦ hKL i ∘ hJK i) := by
ext x i
simp only [π, Proj, Function.comp_apply, ProjRestricts_coe]
aesop
theorem projRestricts_comp_projRestrict (h : ∀ i, J i → K i) :
ProjRestricts C h ∘ ProjRestrict C K = ProjRestrict C J := by
ext x i
simp only [π, Proj, Function.comp_apply, ProjRestricts_coe, ProjRestrict_coe]
aesop
variable (J)
/-- The objectwise map in the isomorphism `spanFunctor ≅ Profinite.indexFunctor`. -/
def iso_map : C(π C J, (IndexFunctor.obj C J)) :=
⟨fun x ↦ ⟨fun i ↦ x.val i.val, by
rcases x with ⟨x, y, hy, rfl⟩
refine ⟨y, hy, ?_⟩
ext ⟨i, hi⟩
simp [precomp, Proj, hi]⟩, by
refine Continuous.subtype_mk (continuous_pi fun i ↦ ?_) _
exact (continuous_apply i.val).comp continuous_subtype_val⟩
lemma iso_map_bijective : Function.Bijective (iso_map C J) := by
refine ⟨fun a b h ↦ ?_, fun a ↦ ?_⟩
· ext i
rw [Subtype.ext_iff] at h
by_cases hi : J i
· exact congr_fun h ⟨i, hi⟩
· rcases a with ⟨_, c, hc, rfl⟩
rcases b with ⟨_, d, hd, rfl⟩
simp only [Proj, if_neg hi]
· refine ⟨⟨fun i ↦ if hi : J i then a.val ⟨i, hi⟩ else false, ?_⟩, ?_⟩
· rcases a with ⟨_, y, hy, rfl⟩
exact ⟨y, hy, rfl⟩
· ext i
exact dif_pos i.prop
variable {C} (hC : IsCompact C)
/--
For a given compact subset `C` of `I → Bool`, `spanFunctor` is the functor from the poset of finsets
of `I` to `Profinite`, sending a finite subset set `J` to the image of `C` under the projection
`Proj J`.
-/
noncomputable
def spanFunctor [∀ (s : Finset I) (i : I), Decidable (i ∈ s)] :
(Finset I)ᵒᵖ ⥤ Profinite.{u} where
obj s := @Profinite.of (π C (· ∈ (unop s))) _
(by rw [← isCompact_iff_compactSpace]; exact hC.image (continuous_proj _)) _ _
map h := ⟨(ProjRestricts C (leOfHom h.unop)), continuous_projRestricts _ _⟩
map_id J := by simp only [projRestricts_eq_id C (· ∈ (unop J))]; rfl
map_comp _ _ := by dsimp; congr; dsimp; rw [projRestricts_eq_comp]
/-- The limit cone on `spanFunctor` with point `C`. -/
noncomputable
def spanCone [∀ (s : Finset I) (i : I), Decidable (i ∈ s)] : Cone (spanFunctor hC) where
pt := @Profinite.of C _ (by rwa [← isCompact_iff_compactSpace]) _ _
π :=
{ app := fun s ↦ ⟨ProjRestrict C (· ∈ unop s), continuous_projRestrict _ _⟩
naturality := by
intro X Y h
simp only [Functor.const_obj_obj, Homeomorph.setCongr, Homeomorph.homeomorph_mk_coe,
Functor.const_obj_map, Category.id_comp, ← projRestricts_comp_projRestrict C
(leOfHom h.unop)]
rfl }
/-- `spanCone` is a limit cone. -/
noncomputable
def spanCone_isLimit [∀ (s : Finset I) (i : I), Decidable (i ∈ s)] :
CategoryTheory.Limits.IsLimit (spanCone hC) := by
refine (IsLimit.postcomposeHomEquiv (NatIso.ofComponents
(fun s ↦ (Profinite.isoOfBijective _ (iso_map_bijective C (· ∈ unop s)))) ?_) (spanCone hC))
(IsLimit.ofIsoLimit (indexCone_isLimit hC) (Cones.ext (Iso.refl _) ?_))
· intro ⟨s⟩ ⟨t⟩ ⟨⟨⟨f⟩⟩⟩
ext x
have : iso_map C (· ∈ t) ∘ ProjRestricts C f = IndexFunctor.map C f ∘ iso_map C (· ∈ s) := by
ext _ i; exact dif_pos i.prop
exact congr_fun this x
· intro ⟨s⟩
ext x
have : iso_map C (· ∈ s) ∘ ProjRestrict C (· ∈ s) = IndexFunctor.π_app C (· ∈ s) := by
ext _ i; exact dif_pos i.prop
erw [← this]
rfl
end Projections
section Products
/-!
## Defining the basis
Our proposed basis consists of products `e C iᵣ * ⋯ * e C i₁` with `iᵣ > ⋯ > i₁` which cannot be
written as linear combinations of lexicographically smaller products. See below for the definition
of `e`.
### Main definitions
* For `i : I`, we let `e C i : LocallyConstant C ℤ` denote the map
`fun f ↦ (if f.val i then 1 else 0)`.
* `Products I` is the type of lists of decreasing elements of `I`, so a typical element is
`[i₁, i₂,..., iᵣ]` with `i₁ > i₂ > ... > iᵣ`.
* `Products.eval C` is the `C`-evaluation of a list. It takes a term `[i₁, i₂,..., iᵣ] : Products I`
and returns the actual product `e C i₁ ··· e C iᵣ : LocallyConstant C ℤ`.
* `GoodProducts C` is the set of `Products I` such that their `C`-evaluation cannot be written as
a linear combination of evaluations of lexicographically smaller lists.
### Main results
* `Products.evalFacProp` and `Products.evalFacProps` establish the fact that `Products.eval`
interacts nicely with the projection maps from the previous section.
* `GoodProducts.span_iff_products`: the good products span `LocallyConstant C ℤ` iff all the
products span `LocallyConstant C ℤ`.
-/
/--
`e C i` is the locally constant map from `C : Set (I → Bool)` to `ℤ` sending `f` to 1 if
`f.val i = true`, and 0 otherwise.
-/
def e (i : I) : LocallyConstant C ℤ where
toFun := fun f ↦ (if f.val i then 1 else 0)
isLocallyConstant := by
rw [IsLocallyConstant.iff_continuous]
exact (continuous_of_discreteTopology (f := fun (a : Bool) ↦ (if a then (1 : ℤ) else 0))).comp
((continuous_apply i).comp continuous_subtype_val)
/--
`Products I` is the type of lists of decreasing elements of `I`, so a typical element is
`[i₁, i₂, ...]` with `i₁ > i₂ > ...`. We order `Products I` lexicographically, so `[] < [i₁, ...]`,
and `[i₁, i₂, ...] < [j₁, j₂, ...]` if either `i₁ < j₁`, or `i₁ = j₁` and `[i₂, ...] < [j₂, ...]`.
Terms `m = [i₁, i₂, ..., iᵣ]` of this type will be used to represent products of the form
`e C i₁ ··· e C iᵣ : LocallyConstant C ℤ` . The function associated to `m` is `m.eval`.
-/
def Products (I : Type*) [LinearOrder I] := {l : List I // l.Chain' (·>·)}
namespace Products
instance : LinearOrder (Products I) :=
inferInstanceAs (LinearOrder {l : List I // l.Chain' (·>·)})
@[simp]
theorem lt_iff_lex_lt (l m : Products I) : l < m ↔ List.Lex (·<·) l.val m.val := by
cases l; cases m; rw [Subtype.mk_lt_mk]; exact Iff.rfl
instance : IsWellFounded (Products I) (·<·) := by
have : (· < · : Products I → _ → _) = (fun l m ↦ List.Lex (·<·) l.val m.val) := by
ext; exact lt_iff_lex_lt _ _
rw [this]
dsimp [Products]
rw [(by rfl : (·>· : I → _) = flip (·<·))]
infer_instance
/-- The evaluation `e C i₁ ··· e C iᵣ : C → ℤ` of a formal product `[i₁, i₂, ..., iᵣ]`. -/
def eval (l : Products I) := (l.1.map (e C)).prod
/--
The predicate on products which we prove picks out a basis of `LocallyConstant C ℤ`. We call such a
product "good".
-/
def isGood (l : Products I) : Prop :=
l.eval C ∉ Submodule.span ℤ ((Products.eval C) '' {m | m < l})
theorem rel_head!_of_mem [Inhabited I] {i : I} {l : Products I} (hi : i ∈ l.val) :
i ≤ l.val.head! :=
List.Sorted.le_head! (List.chain'_iff_pairwise.mp l.prop) hi
theorem head!_le_of_lt [Inhabited I] {q l : Products I} (h : q < l) (hq : q.val ≠ []) :
q.val.head! ≤ l.val.head! :=
List.head!_le_of_lt l.val q.val h hq
end Products
/-- The set of good products. -/
def GoodProducts := {l : Products I | l.isGood C}
namespace GoodProducts
/-- Evaluation of good products. -/
def eval (l : {l : Products I // l.isGood C}) : LocallyConstant C ℤ :=
Products.eval C l.1
theorem injective : Function.Injective (eval C) := by
intro ⟨a, ha⟩ ⟨b, hb⟩ h
dsimp [eval] at h
rcases lt_trichotomy a b with (h'|rfl|h')
· exfalso; apply hb; rw [← h]
exact Submodule.subset_span ⟨a, h', rfl⟩
· rfl
· exfalso; apply ha; rw [h]
exact Submodule.subset_span ⟨b, ⟨h',rfl⟩⟩
/-- The image of the good products in the module `LocallyConstant C ℤ`. -/
def range := Set.range (GoodProducts.eval C)
/-- The type of good products is equivalent to its image. -/
noncomputable
def equiv_range : GoodProducts C ≃ range C :=
Equiv.ofInjective (eval C) (injective C)
theorem equiv_toFun_eq_eval : (equiv_range C).toFun = Set.rangeFactorization (eval C) := rfl
theorem linearIndependent_iff_range : LinearIndependent ℤ (GoodProducts.eval C) ↔
LinearIndependent ℤ (fun (p : range C) ↦ p.1) := by
rw [← @Set.rangeFactorization_eq _ _ (GoodProducts.eval C), ← equiv_toFun_eq_eval C]
exact linearIndependent_equiv (equiv_range C)
end GoodProducts
namespace Products
theorem eval_eq (l : Products I) (x : C) :
l.eval C x = if ∀ i, i ∈ l.val → (x.val i = true) then 1 else 0 := by
change LocallyConstant.evalMonoidHom x (l.eval C) = _
rw [eval, map_list_prod]
split_ifs with h
· simp only [List.map_map]
apply List.prod_eq_one
simp only [List.mem_map, Function.comp_apply]
rintro _ ⟨i, hi, rfl⟩
exact if_pos (h i hi)
· simp only [List.map_map, List.prod_eq_zero_iff, List.mem_map, Function.comp_apply]
push_neg at h
convert h with i
dsimp [LocallyConstant.evalMonoidHom, e]
simp only [ite_eq_right_iff, one_ne_zero]
theorem evalFacProp {l : Products I} (J : I → Prop)
(h : ∀ a, a ∈ l.val → J a) [∀ j, Decidable (J j)] :
l.eval (π C J) ∘ ProjRestrict C J = l.eval C := by
ext x
dsimp [ProjRestrict]
rw [Products.eval_eq, Products.eval_eq]
congr
apply forall_congr; intro i
apply forall_congr; intro hi
simp [h i hi, Proj]
theorem evalFacProps {l : Products I} (J K : I → Prop)
(h : ∀ a, a ∈ l.val → J a) [∀ j, Decidable (J j)] [∀ j, Decidable (K j)]
(hJK : ∀ i, J i → K i) :
l.eval (π C J) ∘ ProjRestricts C hJK = l.eval (π C K) := by
have : l.eval (π C J) ∘ Homeomorph.setCongr (proj_eq_of_subset C J K hJK) =
l.eval (π (π C K) J) := by
ext; simp [Homeomorph.setCongr, Products.eval_eq]
rw [ProjRestricts, ← Function.comp.assoc, this, ← evalFacProp (π C K) J h]
theorem prop_of_isGood {l : Products I} (J : I → Prop) [∀ j, Decidable (J j)]
(h : l.isGood (π C J)) : ∀ a, a ∈ l.val → J a := by
intro i hi
by_contra h'
apply h
suffices eval (π C J) l = 0 by
rw [this]
exact Submodule.zero_mem _
ext ⟨_, _, _, rfl⟩
rw [eval_eq, if_neg fun h ↦ ?_, LocallyConstant.zero_apply]
simpa [Proj, h'] using h i hi
end Products
/-- The good products span `LocallyConstant C ℤ` if and only all the products do. -/
theorem GoodProducts.span_iff_products : ⊤ ≤ span ℤ (Set.range (eval C)) ↔
⊤ ≤ span ℤ (Set.range (Products.eval C)) := by
refine ⟨fun h ↦ le_trans h (span_mono (fun a ⟨b, hb⟩ ↦ ⟨b.val, hb⟩)), fun h ↦ le_trans h ?_⟩
rw [span_le]
rintro f ⟨l, rfl⟩
let L : Products I → Prop := fun m ↦ m.eval C ∈ span ℤ (Set.range (GoodProducts.eval C))
suffices L l by assumption
apply IsWellFounded.induction (·<· : Products I → Products I → Prop)
intro l h
dsimp
by_cases hl : l.isGood C
· apply subset_span
exact ⟨⟨l, hl⟩, rfl⟩
· simp only [Products.isGood, not_not] at hl
suffices Products.eval C '' {m | m < l} ⊆ span ℤ (Set.range (GoodProducts.eval C)) by
rw [← span_le] at this
exact this hl
rintro a ⟨m, hm, rfl⟩
exact h m hm
end Products
section Span
/-!
## The good products span
Most of the argument is developing an API for `π C (· ∈ s)` when `s : Finset I`; then the image
of `C` is finite with the discrete topology. In this case, there is a direct argument that the good
products span. The general result is deduced from this.
### Main theorems
* `GoodProducts.spanFin` : The good products span the locally constant functions on `π C (· ∈ s)`
if `s` is finite.
* `GoodProducts.span` : The good products span `LocallyConstant C ℤ` for every closed subset `C`.
-/
section Fin
variable (s : Finset I)
/-- The `ℤ`-linear map induced by precomposition of the projection `C → π C (· ∈ s)`. -/
noncomputable
def πJ : LocallyConstant (π C (· ∈ s)) ℤ →ₗ[ℤ] LocallyConstant C ℤ :=
LocallyConstant.comapₗ ℤ ⟨_, (continuous_projRestrict C (· ∈ s))⟩
theorem eval_eq_πJ (l : Products I) (hl : l.isGood (π C (· ∈ s))) :
l.eval C = πJ C s (l.eval (π C (· ∈ s))) := by
ext f
simp only [πJ, LocallyConstant.comapₗ, LinearMap.coe_mk, AddHom.coe_mk,
(continuous_projRestrict C (· ∈ s)), LocallyConstant.coe_comap, Function.comp_apply]
exact (congr_fun (Products.evalFacProp C (· ∈ s) (Products.prop_of_isGood C (· ∈ s) hl)) _).symm
/-- `π C (· ∈ s)` is finite for a finite set `s`. -/
noncomputable
instance : Fintype (π C (· ∈ s)) := by
let f : π C (· ∈ s) → (s → Bool) := fun x j ↦ x.val j.val
refine Fintype.ofInjective f ?_
intro ⟨_, x, hx, rfl⟩ ⟨_, y, hy, rfl⟩ h
ext i
by_cases hi : i ∈ s
· exact congrFun h ⟨i, hi⟩
· simp only [Proj, if_neg hi]
open scoped Classical in
/-- The Kronecker delta as a locally constant map from `π C (· ∈ s)` to `ℤ`. -/
noncomputable
def spanFinBasis (x : π C (· ∈ s)) : LocallyConstant (π C (· ∈ s)) ℤ where
toFun := fun y ↦ if y = x then 1 else 0
isLocallyConstant :=
haveI : DiscreteTopology (π C (· ∈ s)) := discrete_of_t1_of_finite
IsLocallyConstant.of_discrete _
open scoped Classical in
theorem spanFinBasis.span : ⊤ ≤ Submodule.span ℤ (Set.range (spanFinBasis C s)) := by
intro f _
rw [Finsupp.mem_span_range_iff_exists_finsupp]
use Finsupp.onFinset (Finset.univ) f.toFun (fun _ _ ↦ Finset.mem_univ _)
ext x
change LocallyConstant.evalₗ ℤ x _ = _
simp only [zsmul_eq_mul, map_finsupp_sum, LocallyConstant.evalₗ_apply,
LocallyConstant.coe_mul, Pi.mul_apply, spanFinBasis, LocallyConstant.coe_mk, mul_ite, mul_one,
mul_zero, Finsupp.sum_ite_eq, Finsupp.mem_support_iff, ne_eq, ite_not]
split_ifs with h <;> [exact h.symm; rfl]
/--
A certain explicit list of locally constant maps. The theorem `factors_prod_eq_basis` shows that the
product of the elements in this list is the delta function `spanFinBasis C s x`.
-/
def factors (x : π C (· ∈ s)) : List (LocallyConstant (π C (· ∈ s)) ℤ) :=
List.map (fun i ↦ if x.val i = true then e (π C (· ∈ s)) i else (1 - (e (π C (· ∈ s)) i)))
(s.sort (·≥·))
theorem list_prod_apply (x : C) (l : List (LocallyConstant C ℤ)) :
l.prod x = (l.map (LocallyConstant.evalMonoidHom x)).prod := by
rw [← map_list_prod (LocallyConstant.evalMonoidHom x) l]
rfl
theorem factors_prod_eq_basis_of_eq {x y : (π C fun x ↦ x ∈ s)} (h : y = x) :
(factors C s x).prod y = 1 := by
rw [list_prod_apply (π C (· ∈ s)) y _]
apply List.prod_eq_one
simp only [h, List.mem_map, LocallyConstant.evalMonoidHom, factors]
rintro _ ⟨a, ⟨b, _, rfl⟩, rfl⟩
dsimp
split_ifs with hh
· rw [e, LocallyConstant.coe_mk, if_pos hh]
· rw [LocallyConstant.sub_apply, e, LocallyConstant.coe_mk, LocallyConstant.coe_mk, if_neg hh]
simp only [LocallyConstant.toFun_eq_coe, LocallyConstant.coe_one, Pi.one_apply, sub_zero]
theorem e_mem_of_eq_true {x : (π C (· ∈ s))} {a : I} (hx : x.val a = true) :
e (π C (· ∈ s)) a ∈ factors C s x := by
rcases x with ⟨_, z, hz, rfl⟩
simp only [factors, List.mem_map, Finset.mem_sort]
refine ⟨a, ?_, if_pos hx⟩
aesop (add simp Proj)
theorem one_sub_e_mem_of_false {x y : (π C (· ∈ s))} {a : I} (ha : y.val a = true)
(hx : x.val a = false) : 1 - e (π C (· ∈ s)) a ∈ factors C s x := by
simp only [factors, List.mem_map, Finset.mem_sort]
use a
simp only [hx, ite_false, and_true]
rcases y with ⟨_, z, hz, rfl⟩
aesop (add simp Proj)
| Mathlib/Topology/Category/Profinite/Nobeling.lean | 556 | 569 | theorem factors_prod_eq_basis_of_ne {x y : (π C (· ∈ s))} (h : y ≠ x) :
(factors C s x).prod y = 0 := by |
rw [list_prod_apply (π C (· ∈ s)) y _]
apply List.prod_eq_zero
simp only [List.mem_map]
obtain ⟨a, ha⟩ : ∃ a, y.val a ≠ x.val a := by contrapose! h; ext; apply h
cases hx : x.val a
· rw [hx, ne_eq, Bool.not_eq_false] at ha
refine ⟨1 - (e (π C (· ∈ s)) a), ⟨one_sub_e_mem_of_false _ _ ha hx, ?_⟩⟩
rw [e, LocallyConstant.evalMonoidHom_apply, LocallyConstant.sub_apply,
LocallyConstant.coe_one, Pi.one_apply, LocallyConstant.coe_mk, if_pos ha, sub_self]
· refine ⟨e (π C (· ∈ s)) a, ⟨e_mem_of_eq_true _ _ hx, ?_⟩⟩
rw [hx] at ha
rw [LocallyConstant.evalMonoidHom_apply, e, LocallyConstant.coe_mk, if_neg ha]
|
/-
Copyright (c) 2021 Kalle Kytölä. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kalle Kytölä
-/
import Mathlib.MeasureTheory.Measure.FiniteMeasure
import Mathlib.MeasureTheory.Integral.Average
#align_import measure_theory.measure.probability_measure from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Probability measures
This file defines the type of probability measures on a given measurable space. When the underlying
space has a topology and the measurable space structure (sigma algebra) is finer than the Borel
sigma algebra, then the type of probability measures is equipped with the topology of convergence
in distribution (weak convergence of measures). The topology of convergence in distribution is the
coarsest topology w.r.t. which for every bounded continuous `ℝ≥0`-valued random variable `X`, the
expected value of `X` depends continuously on the choice of probability measure. This is a special
case of the topology of weak convergence of finite measures.
## Main definitions
The main definitions are
* the type `MeasureTheory.ProbabilityMeasure Ω` with the topology of convergence in
distribution (a.k.a. convergence in law, weak convergence of measures);
* `MeasureTheory.ProbabilityMeasure.toFiniteMeasure`: Interpret a probability measure as
a finite measure;
* `MeasureTheory.FiniteMeasure.normalize`: Normalize a finite measure to a probability measure
(returns junk for the zero measure).
* `MeasureTheory.ProbabilityMeasure.map`: The push-forward `f* μ` of a probability measure
`μ` on `Ω` along a measurable function `f : Ω → Ω'`.
## Main results
* `MeasureTheory.ProbabilityMeasure.tendsto_iff_forall_integral_tendsto`: Convergence of
probability measures is characterized by the convergence of expected values of all bounded
continuous random variables. This shows that the chosen definition of topology coincides with
the common textbook definition of convergence in distribution, i.e., weak convergence of
measures. A similar characterization by the convergence of expected values (in the
`MeasureTheory.lintegral` sense) of all bounded continuous nonnegative random variables is
`MeasureTheory.ProbabilityMeasure.tendsto_iff_forall_lintegral_tendsto`.
* `MeasureTheory.FiniteMeasure.tendsto_normalize_iff_tendsto`: The convergence of finite
measures to a nonzero limit is characterized by the convergence of the probability-normalized
versions and of the total masses.
* `MeasureTheory.ProbabilityMeasure.continuous_map`: For a continuous function `f : Ω → Ω'`, the
push-forward of probability measures `f* : ProbabilityMeasure Ω → ProbabilityMeasure Ω'` is
continuous.
* `MeasureTheory.ProbabilityMeasure.t2Space`: The topology of convergence in distribution is
Hausdorff on Borel spaces where indicators of closed sets have continuous decreasing
approximating sequences (in particular on any pseudo-metrizable spaces).
TODO:
* Probability measures form a convex space.
## Implementation notes
The topology of convergence in distribution on `MeasureTheory.ProbabilityMeasure Ω` is inherited
weak convergence of finite measures via the mapping
`MeasureTheory.ProbabilityMeasure.toFiniteMeasure`.
Like `MeasureTheory.FiniteMeasure Ω`, the implementation of `MeasureTheory.ProbabilityMeasure Ω`
is directly as a subtype of `MeasureTheory.Measure Ω`, and the coercion to a function is the
composition `ENNReal.toNNReal` and the coercion to function of `MeasureTheory.Measure Ω`.
## References
* [Billingsley, *Convergence of probability measures*][billingsley1999]
## Tags
convergence in distribution, convergence in law, weak convergence of measures, probability measure
-/
noncomputable section
open MeasureTheory
open Set
open Filter
open BoundedContinuousFunction
open scoped Topology ENNReal NNReal BoundedContinuousFunction
namespace MeasureTheory
section ProbabilityMeasure
/-! ### Probability measures
In this section we define the type of probability measures on a measurable space `Ω`, denoted by
`MeasureTheory.ProbabilityMeasure Ω`.
If `Ω` is moreover a topological space and the sigma algebra on `Ω` is finer than the Borel sigma
algebra (i.e. `[OpensMeasurableSpace Ω]`), then `MeasureTheory.ProbabilityMeasure Ω` is
equipped with the topology of weak convergence of measures. Since every probability measure is a
finite measure, this is implemented as the induced topology from the mapping
`MeasureTheory.ProbabilityMeasure.toFiniteMeasure`.
-/
/-- Probability measures are defined as the subtype of measures that have the property of being
probability measures (i.e., their total mass is one). -/
def ProbabilityMeasure (Ω : Type*) [MeasurableSpace Ω] : Type _ :=
{ μ : Measure Ω // IsProbabilityMeasure μ }
#align measure_theory.probability_measure MeasureTheory.ProbabilityMeasure
namespace ProbabilityMeasure
variable {Ω : Type*} [MeasurableSpace Ω]
instance [Inhabited Ω] : Inhabited (ProbabilityMeasure Ω) :=
⟨⟨Measure.dirac default, Measure.dirac.isProbabilityMeasure⟩⟩
-- Porting note: as with other subtype synonyms (e.g., `ℝ≥0`), we need a new function for the
-- coercion instead of relying on `Subtype.val`.
/-- Coercion from `MeasureTheory.ProbabilityMeasure Ω` to `MeasureTheory.Measure Ω`. -/
@[coe]
def toMeasure : ProbabilityMeasure Ω → Measure Ω := Subtype.val
/-- A probability measure can be interpreted as a measure. -/
instance : Coe (ProbabilityMeasure Ω) (MeasureTheory.Measure Ω) where
coe := toMeasure
instance (μ : ProbabilityMeasure Ω) : IsProbabilityMeasure (μ : Measure Ω) :=
μ.prop
@[simp, norm_cast] lemma coe_mk (μ : Measure Ω) (hμ) : toMeasure ⟨μ, hμ⟩ = μ := rfl
@[simp]
theorem val_eq_to_measure (ν : ProbabilityMeasure Ω) : ν.val = (ν : Measure Ω) :=
rfl
#align measure_theory.probability_measure.val_eq_to_measure MeasureTheory.ProbabilityMeasure.val_eq_to_measure
theorem toMeasure_injective : Function.Injective ((↑) : ProbabilityMeasure Ω → Measure Ω) :=
Subtype.coe_injective
#align measure_theory.probability_measure.coe_injective MeasureTheory.ProbabilityMeasure.toMeasure_injective
instance instFunLike : FunLike (ProbabilityMeasure Ω) (Set Ω) ℝ≥0 where
coe μ s := ((μ : Measure Ω) s).toNNReal
coe_injective' μ ν h := toMeasure_injective $ Measure.ext fun s _ ↦ by
simpa [ENNReal.toNNReal_eq_toNNReal_iff, measure_ne_top] using congr_fun h s
lemma coeFn_def (μ : ProbabilityMeasure Ω) : μ = fun s ↦ ((μ : Measure Ω) s).toNNReal := rfl
#align measure_theory.probability_measure.coe_fn_eq_to_nnreal_coe_fn_to_measure MeasureTheory.ProbabilityMeasure.coeFn_def
lemma coeFn_mk (μ : Measure Ω) (hμ) :
DFunLike.coe (F := ProbabilityMeasure Ω) ⟨μ, hμ⟩ = fun s ↦ (μ s).toNNReal := rfl
@[simp, norm_cast]
lemma mk_apply (μ : Measure Ω) (hμ) (s : Set Ω) :
DFunLike.coe (F := ProbabilityMeasure Ω) ⟨μ, hμ⟩ s = (μ s).toNNReal := rfl
@[simp, norm_cast]
theorem coeFn_univ (ν : ProbabilityMeasure Ω) : ν univ = 1 :=
congr_arg ENNReal.toNNReal ν.prop.measure_univ
#align measure_theory.probability_measure.coe_fn_univ MeasureTheory.ProbabilityMeasure.coeFn_univ
theorem coeFn_univ_ne_zero (ν : ProbabilityMeasure Ω) : ν univ ≠ 0 := by
simp only [coeFn_univ, Ne, one_ne_zero, not_false_iff]
#align measure_theory.probability_measure.coe_fn_univ_ne_zero MeasureTheory.ProbabilityMeasure.coeFn_univ_ne_zero
/-- A probability measure can be interpreted as a finite measure. -/
def toFiniteMeasure (μ : ProbabilityMeasure Ω) : FiniteMeasure Ω :=
⟨μ, inferInstance⟩
#align measure_theory.probability_measure.to_finite_measure MeasureTheory.ProbabilityMeasure.toFiniteMeasure
@[simp] lemma coeFn_toFiniteMeasure (μ : ProbabilityMeasure Ω) : ⇑μ.toFiniteMeasure = μ := rfl
lemma toFiniteMeasure_apply (μ : ProbabilityMeasure Ω) (s : Set Ω) :
μ.toFiniteMeasure s = μ s := rfl
@[simp]
theorem toMeasure_comp_toFiniteMeasure_eq_toMeasure (ν : ProbabilityMeasure Ω) :
(ν.toFiniteMeasure : Measure Ω) = (ν : Measure Ω) :=
rfl
#align measure_theory.probability_measure.coe_comp_to_finite_measure_eq_coe MeasureTheory.ProbabilityMeasure.toMeasure_comp_toFiniteMeasure_eq_toMeasure
@[simp]
theorem coeFn_comp_toFiniteMeasure_eq_coeFn (ν : ProbabilityMeasure Ω) :
(ν.toFiniteMeasure : Set Ω → ℝ≥0) = (ν : Set Ω → ℝ≥0) :=
rfl
#align measure_theory.probability_measure.coe_fn_comp_to_finite_measure_eq_coe_fn MeasureTheory.ProbabilityMeasure.coeFn_comp_toFiniteMeasure_eq_coeFn
@[simp]
theorem toFiniteMeasure_apply_eq_apply (ν : ProbabilityMeasure Ω) (s : Set Ω) :
ν.toFiniteMeasure s = ν s := rfl
@[simp]
theorem ennreal_coeFn_eq_coeFn_toMeasure (ν : ProbabilityMeasure Ω) (s : Set Ω) :
(ν s : ℝ≥0∞) = (ν : Measure Ω) s := by
rw [← coeFn_comp_toFiniteMeasure_eq_coeFn, FiniteMeasure.ennreal_coeFn_eq_coeFn_toMeasure,
toMeasure_comp_toFiniteMeasure_eq_toMeasure]
#align measure_theory.probability_measure.ennreal_coe_fn_eq_coe_fn_to_measure MeasureTheory.ProbabilityMeasure.ennreal_coeFn_eq_coeFn_toMeasure
theorem apply_mono (μ : ProbabilityMeasure Ω) {s₁ s₂ : Set Ω} (h : s₁ ⊆ s₂) : μ s₁ ≤ μ s₂ := by
rw [← coeFn_comp_toFiniteMeasure_eq_coeFn]
exact MeasureTheory.FiniteMeasure.apply_mono _ h
#align measure_theory.probability_measure.apply_mono MeasureTheory.ProbabilityMeasure.apply_mono
@[simp] theorem apply_le_one (μ : ProbabilityMeasure Ω) (s : Set Ω) : μ s ≤ 1 := by
simpa using apply_mono μ (subset_univ s)
theorem nonempty (μ : ProbabilityMeasure Ω) : Nonempty Ω := by
by_contra maybe_empty
have zero : (μ : Measure Ω) univ = 0 := by
rw [univ_eq_empty_iff.mpr (not_nonempty_iff.mp maybe_empty), measure_empty]
rw [measure_univ] at zero
exact zero_ne_one zero.symm
#align measure_theory.probability_measure.nonempty_of_probability_measure MeasureTheory.ProbabilityMeasure.nonempty
@[ext]
theorem eq_of_forall_toMeasure_apply_eq (μ ν : ProbabilityMeasure Ω)
(h : ∀ s : Set Ω, MeasurableSet s → (μ : Measure Ω) s = (ν : Measure Ω) s) : μ = ν := by
apply toMeasure_injective
ext1 s s_mble
exact h s s_mble
#align measure_theory.probability_measure.eq_of_forall_measure_apply_eq MeasureTheory.ProbabilityMeasure.eq_of_forall_toMeasure_apply_eq
theorem eq_of_forall_apply_eq (μ ν : ProbabilityMeasure Ω)
(h : ∀ s : Set Ω, MeasurableSet s → μ s = ν s) : μ = ν := by
ext1 s s_mble
simpa [ennreal_coeFn_eq_coeFn_toMeasure] using congr_arg ((↑) : ℝ≥0 → ℝ≥0∞) (h s s_mble)
#align measure_theory.probability_measure.eq_of_forall_apply_eq MeasureTheory.ProbabilityMeasure.eq_of_forall_apply_eq
@[simp]
theorem mass_toFiniteMeasure (μ : ProbabilityMeasure Ω) : μ.toFiniteMeasure.mass = 1 :=
μ.coeFn_univ
#align measure_theory.probability_measure.mass_to_finite_measure MeasureTheory.ProbabilityMeasure.mass_toFiniteMeasure
theorem toFiniteMeasure_nonzero (μ : ProbabilityMeasure Ω) : μ.toFiniteMeasure ≠ 0 := by
rw [← FiniteMeasure.mass_nonzero_iff, μ.mass_toFiniteMeasure]
exact one_ne_zero
#align measure_theory.probability_measure.to_finite_measure_nonzero MeasureTheory.ProbabilityMeasure.toFiniteMeasure_nonzero
section convergence_in_distribution
variable [TopologicalSpace Ω] [OpensMeasurableSpace Ω]
theorem testAgainstNN_lipschitz (μ : ProbabilityMeasure Ω) :
LipschitzWith 1 fun f : Ω →ᵇ ℝ≥0 => μ.toFiniteMeasure.testAgainstNN f :=
μ.mass_toFiniteMeasure ▸ μ.toFiniteMeasure.testAgainstNN_lipschitz
#align measure_theory.probability_measure.test_against_nn_lipschitz MeasureTheory.ProbabilityMeasure.testAgainstNN_lipschitz
/-- The topology of weak convergence on `MeasureTheory.ProbabilityMeasure Ω`. This is inherited
(induced) from the topology of weak convergence of finite measures via the inclusion
`MeasureTheory.ProbabilityMeasure.toFiniteMeasure`. -/
instance : TopologicalSpace (ProbabilityMeasure Ω) :=
TopologicalSpace.induced toFiniteMeasure inferInstance
theorem toFiniteMeasure_continuous :
Continuous (toFiniteMeasure : ProbabilityMeasure Ω → FiniteMeasure Ω) :=
continuous_induced_dom
#align measure_theory.probability_measure.to_finite_measure_continuous MeasureTheory.ProbabilityMeasure.toFiniteMeasure_continuous
/-- Probability measures yield elements of the `WeakDual` of bounded continuous nonnegative
functions via `MeasureTheory.FiniteMeasure.testAgainstNN`, i.e., integration. -/
def toWeakDualBCNN : ProbabilityMeasure Ω → WeakDual ℝ≥0 (Ω →ᵇ ℝ≥0) :=
FiniteMeasure.toWeakDualBCNN ∘ toFiniteMeasure
#align measure_theory.probability_measure.to_weak_dual_bcnn MeasureTheory.ProbabilityMeasure.toWeakDualBCNN
@[simp]
theorem coe_toWeakDualBCNN (μ : ProbabilityMeasure Ω) :
⇑μ.toWeakDualBCNN = μ.toFiniteMeasure.testAgainstNN :=
rfl
#align measure_theory.probability_measure.coe_to_weak_dual_bcnn MeasureTheory.ProbabilityMeasure.coe_toWeakDualBCNN
@[simp]
theorem toWeakDualBCNN_apply (μ : ProbabilityMeasure Ω) (f : Ω →ᵇ ℝ≥0) :
μ.toWeakDualBCNN f = (∫⁻ ω, f ω ∂(μ : Measure Ω)).toNNReal :=
rfl
#align measure_theory.probability_measure.to_weak_dual_bcnn_apply MeasureTheory.ProbabilityMeasure.toWeakDualBCNN_apply
theorem toWeakDualBCNN_continuous : Continuous fun μ : ProbabilityMeasure Ω => μ.toWeakDualBCNN :=
FiniteMeasure.toWeakDualBCNN_continuous.comp toFiniteMeasure_continuous
#align measure_theory.probability_measure.to_weak_dual_bcnn_continuous MeasureTheory.ProbabilityMeasure.toWeakDualBCNN_continuous
/- Integration of (nonnegative bounded continuous) test functions against Borel probability
measures depends continuously on the measure. -/
theorem continuous_testAgainstNN_eval (f : Ω →ᵇ ℝ≥0) :
Continuous fun μ : ProbabilityMeasure Ω => μ.toFiniteMeasure.testAgainstNN f :=
(FiniteMeasure.continuous_testAgainstNN_eval f).comp toFiniteMeasure_continuous
#align measure_theory.probability_measure.continuous_test_against_nn_eval MeasureTheory.ProbabilityMeasure.continuous_testAgainstNN_eval
-- The canonical mapping from probability measures to finite measures is an embedding.
theorem toFiniteMeasure_embedding (Ω : Type*) [MeasurableSpace Ω] [TopologicalSpace Ω]
[OpensMeasurableSpace Ω] :
Embedding (toFiniteMeasure : ProbabilityMeasure Ω → FiniteMeasure Ω) :=
{ induced := rfl
inj := fun _μ _ν h => Subtype.eq <| congr_arg FiniteMeasure.toMeasure h }
#align measure_theory.probability_measure.to_finite_measure_embedding MeasureTheory.ProbabilityMeasure.toFiniteMeasure_embedding
theorem tendsto_nhds_iff_toFiniteMeasure_tendsto_nhds {δ : Type*} (F : Filter δ)
{μs : δ → ProbabilityMeasure Ω} {μ₀ : ProbabilityMeasure Ω} :
Tendsto μs F (𝓝 μ₀) ↔ Tendsto (toFiniteMeasure ∘ μs) F (𝓝 μ₀.toFiniteMeasure) :=
Embedding.tendsto_nhds_iff (toFiniteMeasure_embedding Ω)
#align measure_theory.probability_measure.tendsto_nhds_iff_to_finite_measures_tendsto_nhds MeasureTheory.ProbabilityMeasure.tendsto_nhds_iff_toFiniteMeasure_tendsto_nhds
/-- A characterization of weak convergence of probability measures by the condition that the
integrals of every continuous bounded nonnegative function converge to the integral of the function
against the limit measure. -/
theorem tendsto_iff_forall_lintegral_tendsto {γ : Type*} {F : Filter γ}
{μs : γ → ProbabilityMeasure Ω} {μ : ProbabilityMeasure Ω} :
Tendsto μs F (𝓝 μ) ↔
∀ f : Ω →ᵇ ℝ≥0,
Tendsto (fun i => ∫⁻ ω, f ω ∂(μs i : Measure Ω)) F (𝓝 (∫⁻ ω, f ω ∂(μ : Measure Ω))) := by
rw [tendsto_nhds_iff_toFiniteMeasure_tendsto_nhds]
exact FiniteMeasure.tendsto_iff_forall_lintegral_tendsto
#align measure_theory.probability_measure.tendsto_iff_forall_lintegral_tendsto MeasureTheory.ProbabilityMeasure.tendsto_iff_forall_lintegral_tendsto
/-- The characterization of weak convergence of probability measures by the usual (defining)
condition that the integrals of every continuous bounded function converge to the integral of the
function against the limit measure. -/
theorem tendsto_iff_forall_integral_tendsto {γ : Type*} {F : Filter γ}
{μs : γ → ProbabilityMeasure Ω} {μ : ProbabilityMeasure Ω} :
Tendsto μs F (𝓝 μ) ↔
∀ f : Ω →ᵇ ℝ,
Tendsto (fun i => ∫ ω, f ω ∂(μs i : Measure Ω)) F (𝓝 (∫ ω, f ω ∂(μ : Measure Ω))) := by
rw [tendsto_nhds_iff_toFiniteMeasure_tendsto_nhds]
rw [FiniteMeasure.tendsto_iff_forall_integral_tendsto]
rfl
#align measure_theory.probability_measure.tendsto_iff_forall_integral_tendsto MeasureTheory.ProbabilityMeasure.tendsto_iff_forall_integral_tendsto
end convergence_in_distribution -- section
section Hausdorff
variable [TopologicalSpace Ω] [HasOuterApproxClosed Ω] [BorelSpace Ω]
variable (Ω)
/-- On topological spaces where indicators of closed sets have decreasing approximating sequences of
continuous functions (`HasOuterApproxClosed`), the topology of convergence in distribution of Borel
probability measures is Hausdorff (`T2Space`). -/
instance t2Space : T2Space (ProbabilityMeasure Ω) :=
Embedding.t2Space (toFiniteMeasure_embedding Ω)
end Hausdorff -- section
end ProbabilityMeasure
-- namespace
end ProbabilityMeasure
-- section
section NormalizeFiniteMeasure
/-! ### Normalization of finite measures to probability measures
This section is about normalizing finite measures to probability measures.
The weak convergence of finite measures to nonzero limit measures is characterized by
the convergence of the total mass and the convergence of the normalized probability
measures.
-/
namespace FiniteMeasure
variable {Ω : Type*} [Nonempty Ω] {m0 : MeasurableSpace Ω} (μ : FiniteMeasure Ω)
/-- Normalize a finite measure so that it becomes a probability measure, i.e., divide by the
total mass. -/
def normalize : ProbabilityMeasure Ω :=
if zero : μ.mass = 0 then ⟨Measure.dirac ‹Nonempty Ω›.some, Measure.dirac.isProbabilityMeasure⟩
else
{ val := ↑(μ.mass⁻¹ • μ)
property := by
refine ⟨?_⟩
-- Porting note: paying the price that this isn't `simp` lemma now.
rw [FiniteMeasure.toMeasure_smul]
simp only [Measure.coe_smul, Pi.smul_apply, Measure.nnreal_smul_coe_apply, ne_eq,
mass_zero_iff, ENNReal.coe_inv zero, ennreal_mass]
rw [← Ne, ← ENNReal.coe_ne_zero, ennreal_mass] at zero
exact ENNReal.inv_mul_cancel zero μ.prop.measure_univ_lt_top.ne }
#align measure_theory.finite_measure.normalize MeasureTheory.FiniteMeasure.normalize
@[simp]
theorem self_eq_mass_mul_normalize (s : Set Ω) : μ s = μ.mass * μ.normalize s := by
obtain rfl | h := eq_or_ne μ 0
· simp
have mass_nonzero : μ.mass ≠ 0 := by rwa [μ.mass_nonzero_iff]
simp only [normalize, dif_neg mass_nonzero]
simp [ProbabilityMeasure.coe_mk, toMeasure_smul, mul_inv_cancel_left₀ mass_nonzero, coeFn_def]
#align measure_theory.finite_measure.self_eq_mass_mul_normalize MeasureTheory.FiniteMeasure.self_eq_mass_mul_normalize
theorem self_eq_mass_smul_normalize : μ = μ.mass • μ.normalize.toFiniteMeasure := by
apply eq_of_forall_apply_eq
intro s _s_mble
rw [μ.self_eq_mass_mul_normalize s, smul_apply, smul_eq_mul,
ProbabilityMeasure.coeFn_comp_toFiniteMeasure_eq_coeFn]
#align measure_theory.finite_measure.self_eq_mass_smul_normalize MeasureTheory.FiniteMeasure.self_eq_mass_smul_normalize
theorem normalize_eq_of_nonzero (nonzero : μ ≠ 0) (s : Set Ω) : μ.normalize s = μ.mass⁻¹ * μ s := by
simp only [μ.self_eq_mass_mul_normalize, μ.mass_nonzero_iff.mpr nonzero, inv_mul_cancel_left₀,
Ne, not_false_iff]
#align measure_theory.finite_measure.normalize_eq_of_nonzero MeasureTheory.FiniteMeasure.normalize_eq_of_nonzero
theorem normalize_eq_inv_mass_smul_of_nonzero (nonzero : μ ≠ 0) :
μ.normalize.toFiniteMeasure = μ.mass⁻¹ • μ := by
nth_rw 3 [μ.self_eq_mass_smul_normalize]
rw [← smul_assoc]
simp only [μ.mass_nonzero_iff.mpr nonzero, Algebra.id.smul_eq_mul, inv_mul_cancel, Ne,
not_false_iff, one_smul]
#align measure_theory.finite_measure.normalize_eq_inv_mass_smul_of_nonzero MeasureTheory.FiniteMeasure.normalize_eq_inv_mass_smul_of_nonzero
theorem toMeasure_normalize_eq_of_nonzero (nonzero : μ ≠ 0) :
(μ.normalize : Measure Ω) = μ.mass⁻¹ • μ := by
ext1 s _s_mble
rw [← μ.normalize.ennreal_coeFn_eq_coeFn_toMeasure s, μ.normalize_eq_of_nonzero nonzero s,
ENNReal.coe_mul, ennreal_coeFn_eq_coeFn_toMeasure]
exact Measure.coe_nnreal_smul_apply _ _ _
#align measure_theory.finite_measure.coe_normalize_eq_of_nonzero MeasureTheory.FiniteMeasure.toMeasure_normalize_eq_of_nonzero
@[simp]
theorem _root_.ProbabilityMeasure.toFiniteMeasure_normalize_eq_self {m0 : MeasurableSpace Ω}
(μ : ProbabilityMeasure Ω) : μ.toFiniteMeasure.normalize = μ := by
apply ProbabilityMeasure.eq_of_forall_apply_eq
intro s _s_mble
rw [μ.toFiniteMeasure.normalize_eq_of_nonzero μ.toFiniteMeasure_nonzero s]
simp only [ProbabilityMeasure.mass_toFiniteMeasure, inv_one, one_mul, μ.coeFn_toFiniteMeasure]
#align probability_measure.to_finite_measure_normalize_eq_self ProbabilityMeasure.toFiniteMeasure_normalize_eq_self
/-- Averaging with respect to a finite measure is the same as integrating against
`MeasureTheory.FiniteMeasure.normalize`. -/
theorem average_eq_integral_normalize {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
(nonzero : μ ≠ 0) (f : Ω → E) :
average (μ : Measure Ω) f = ∫ ω, f ω ∂(μ.normalize : Measure Ω) := by
rw [μ.toMeasure_normalize_eq_of_nonzero nonzero, average]
congr
simp [ENNReal.coe_inv (μ.mass_nonzero_iff.mpr nonzero), ennreal_mass]
#align measure_theory.finite_measure.average_eq_integral_normalize MeasureTheory.FiniteMeasure.average_eq_integral_normalize
variable [TopologicalSpace Ω]
theorem testAgainstNN_eq_mass_mul (f : Ω →ᵇ ℝ≥0) :
μ.testAgainstNN f = μ.mass * μ.normalize.toFiniteMeasure.testAgainstNN f := by
nth_rw 1 [μ.self_eq_mass_smul_normalize]
rw [μ.normalize.toFiniteMeasure.smul_testAgainstNN_apply μ.mass f, smul_eq_mul]
#align measure_theory.finite_measure.test_against_nn_eq_mass_mul MeasureTheory.FiniteMeasure.testAgainstNN_eq_mass_mul
theorem normalize_testAgainstNN (nonzero : μ ≠ 0) (f : Ω →ᵇ ℝ≥0) :
μ.normalize.toFiniteMeasure.testAgainstNN f = μ.mass⁻¹ * μ.testAgainstNN f := by
simp [μ.testAgainstNN_eq_mass_mul, inv_mul_cancel_left₀ <| μ.mass_nonzero_iff.mpr nonzero]
#align measure_theory.finite_measure.normalize_test_against_nn MeasureTheory.FiniteMeasure.normalize_testAgainstNN
variable [OpensMeasurableSpace Ω]
variable {μ}
theorem tendsto_testAgainstNN_of_tendsto_normalize_testAgainstNN_of_tendsto_mass {γ : Type*}
{F : Filter γ} {μs : γ → FiniteMeasure Ω}
(μs_lim : Tendsto (fun i => (μs i).normalize) F (𝓝 μ.normalize))
(mass_lim : Tendsto (fun i => (μs i).mass) F (𝓝 μ.mass)) (f : Ω →ᵇ ℝ≥0) :
Tendsto (fun i => (μs i).testAgainstNN f) F (𝓝 (μ.testAgainstNN f)) := by
by_cases h_mass : μ.mass = 0
· simp only [μ.mass_zero_iff.mp h_mass, zero_testAgainstNN_apply, zero_mass,
eq_self_iff_true] at *
exact tendsto_zero_testAgainstNN_of_tendsto_zero_mass mass_lim f
simp_rw [fun i => (μs i).testAgainstNN_eq_mass_mul f, μ.testAgainstNN_eq_mass_mul f]
rw [ProbabilityMeasure.tendsto_nhds_iff_toFiniteMeasure_tendsto_nhds] at μs_lim
rw [tendsto_iff_forall_testAgainstNN_tendsto] at μs_lim
have lim_pair :
Tendsto (fun i => (⟨(μs i).mass, (μs i).normalize.toFiniteMeasure.testAgainstNN f⟩ : ℝ≥0 × ℝ≥0))
F (𝓝 ⟨μ.mass, μ.normalize.toFiniteMeasure.testAgainstNN f⟩) :=
(Prod.tendsto_iff _ _).mpr ⟨mass_lim, μs_lim f⟩
exact tendsto_mul.comp lim_pair
#align measure_theory.finite_measure.tendsto_test_against_nn_of_tendsto_normalize_test_against_nn_of_tendsto_mass MeasureTheory.FiniteMeasure.tendsto_testAgainstNN_of_tendsto_normalize_testAgainstNN_of_tendsto_mass
theorem tendsto_normalize_testAgainstNN_of_tendsto {γ : Type*} {F : Filter γ}
{μs : γ → FiniteMeasure Ω} (μs_lim : Tendsto μs F (𝓝 μ)) (nonzero : μ ≠ 0) (f : Ω →ᵇ ℝ≥0) :
Tendsto (fun i => (μs i).normalize.toFiniteMeasure.testAgainstNN f) F
(𝓝 (μ.normalize.toFiniteMeasure.testAgainstNN f)) := by
have lim_mass := μs_lim.mass
have aux : {(0 : ℝ≥0)}ᶜ ∈ 𝓝 μ.mass :=
isOpen_compl_singleton.mem_nhds (μ.mass_nonzero_iff.mpr nonzero)
have eventually_nonzero : ∀ᶠ i in F, μs i ≠ 0 := by
simp_rw [← mass_nonzero_iff]
exact lim_mass aux
have eve : ∀ᶠ i in F,
(μs i).normalize.toFiniteMeasure.testAgainstNN f =
(μs i).mass⁻¹ * (μs i).testAgainstNN f := by
filter_upwards [eventually_iff.mp eventually_nonzero]
intro i hi
apply normalize_testAgainstNN _ hi
simp_rw [tendsto_congr' eve, μ.normalize_testAgainstNN nonzero]
have lim_pair :
Tendsto (fun i => (⟨(μs i).mass⁻¹, (μs i).testAgainstNN f⟩ : ℝ≥0 × ℝ≥0)) F
(𝓝 ⟨μ.mass⁻¹, μ.testAgainstNN f⟩) := by
refine (Prod.tendsto_iff _ _).mpr ⟨?_, ?_⟩
· exact (continuousOn_inv₀.continuousAt aux).tendsto.comp lim_mass
· exact tendsto_iff_forall_testAgainstNN_tendsto.mp μs_lim f
exact tendsto_mul.comp lim_pair
#align measure_theory.finite_measure.tendsto_normalize_test_against_nn_of_tendsto MeasureTheory.FiniteMeasure.tendsto_normalize_testAgainstNN_of_tendsto
/-- If the normalized versions of finite measures converge weakly and their total masses
also converge, then the finite measures themselves converge weakly. -/
| Mathlib/MeasureTheory/Measure/ProbabilityMeasure.lean | 498 | 503 | theorem tendsto_of_tendsto_normalize_testAgainstNN_of_tendsto_mass {γ : Type*} {F : Filter γ}
{μs : γ → FiniteMeasure Ω} (μs_lim : Tendsto (fun i => (μs i).normalize) F (𝓝 μ.normalize))
(mass_lim : Tendsto (fun i => (μs i).mass) F (𝓝 μ.mass)) : Tendsto μs F (𝓝 μ) := by |
rw [tendsto_iff_forall_testAgainstNN_tendsto]
exact fun f =>
tendsto_testAgainstNN_of_tendsto_normalize_testAgainstNN_of_tendsto_mass μs_lim mass_lim f
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.Data.Fin.Tuple.Basic
import Mathlib.Data.List.Range
#align_import data.fin.vec_notation from "leanprover-community/mathlib"@"2445c98ae4b87eabebdde552593519b9b6dc350c"
/-!
# Matrix and vector notation
This file defines notation for vectors and matrices. Given `a b c d : α`,
the notation allows us to write `![a, b, c, d] : Fin 4 → α`.
Nesting vectors gives coefficients of a matrix, so `![![a, b], ![c, d]] : Fin 2 → Fin 2 → α`.
In later files we introduce `!![a, b; c, d]` as notation for `Matrix.of ![![a, b], ![c, d]]`.
## Main definitions
* `vecEmpty` is the empty vector (or `0` by `n` matrix) `![]`
* `vecCons` prepends an entry to a vector, so `![a, b]` is `vecCons a (vecCons b vecEmpty)`
## Implementation notes
The `simp` lemmas require that one of the arguments is of the form `vecCons _ _`.
This ensures `simp` works with entries only when (some) entries are already given.
In other words, this notation will only appear in the output of `simp` if it
already appears in the input.
## Notations
The main new notation is `![a, b]`, which gets expanded to `vecCons a (vecCons b vecEmpty)`.
## Examples
Examples of usage can be found in the `test/matrix.lean` file.
-/
namespace Matrix
universe u
variable {α : Type u}
section MatrixNotation
/-- `![]` is the vector with no entries. -/
def vecEmpty : Fin 0 → α :=
Fin.elim0
#align matrix.vec_empty Matrix.vecEmpty
/-- `vecCons h t` prepends an entry `h` to a vector `t`.
The inverse functions are `vecHead` and `vecTail`.
The notation `![a, b, ...]` expands to `vecCons a (vecCons b ...)`.
-/
def vecCons {n : ℕ} (h : α) (t : Fin n → α) : Fin n.succ → α :=
Fin.cons h t
#align matrix.vec_cons Matrix.vecCons
/-- `![...]` notation is used to construct a vector `Fin n → α` using `Matrix.vecEmpty` and
`Matrix.vecCons`.
For instance, `![a, b, c] : Fin 3` is syntax for `vecCons a (vecCons b (vecCons c vecEmpty))`.
Note that this should not be used as syntax for `Matrix` as it generates a term with the wrong type.
The `!![a, b; c, d]` syntax (provided by `Matrix.matrixNotation`) should be used instead.
-/
syntax (name := vecNotation) "![" term,* "]" : term
macro_rules
| `(![$term:term, $terms:term,*]) => `(vecCons $term ![$terms,*])
| `(![$term:term]) => `(vecCons $term ![])
| `(![]) => `(vecEmpty)
/-- Unexpander for the `![x, y, ...]` notation. -/
@[app_unexpander vecCons]
def vecConsUnexpander : Lean.PrettyPrinter.Unexpander
| `($_ $term ![$term2, $terms,*]) => `(![$term, $term2, $terms,*])
| `($_ $term ![$term2]) => `(![$term, $term2])
| `($_ $term ![]) => `(![$term])
| _ => throw ()
/-- Unexpander for the `![]` notation. -/
@[app_unexpander vecEmpty]
def vecEmptyUnexpander : Lean.PrettyPrinter.Unexpander
| `($_:ident) => `(![])
| _ => throw ()
/-- `vecHead v` gives the first entry of the vector `v` -/
def vecHead {n : ℕ} (v : Fin n.succ → α) : α :=
v 0
#align matrix.vec_head Matrix.vecHead
/-- `vecTail v` gives a vector consisting of all entries of `v` except the first -/
def vecTail {n : ℕ} (v : Fin n.succ → α) : Fin n → α :=
v ∘ Fin.succ
#align matrix.vec_tail Matrix.vecTail
variable {m n : ℕ}
/-- Use `![...]` notation for displaying a vector `Fin n → α`, for example:
```
#eval ![1, 2] + ![3, 4] -- ![4, 6]
```
-/
instance _root_.PiFin.hasRepr [Repr α] : Repr (Fin n → α) where
reprPrec f _ :=
Std.Format.bracket "![" (Std.Format.joinSep
((List.finRange n).map fun n => repr (f n)) ("," ++ Std.Format.line)) "]"
#align pi_fin.has_repr PiFin.hasRepr
end MatrixNotation
variable {m n o : ℕ} {m' n' o' : Type*}
theorem empty_eq (v : Fin 0 → α) : v = ![] :=
Subsingleton.elim _ _
#align matrix.empty_eq Matrix.empty_eq
section Val
@[simp]
theorem head_fin_const (a : α) : (vecHead fun _ : Fin (n + 1) => a) = a :=
rfl
#align matrix.head_fin_const Matrix.head_fin_const
@[simp]
theorem cons_val_zero (x : α) (u : Fin m → α) : vecCons x u 0 = x :=
rfl
#align matrix.cons_val_zero Matrix.cons_val_zero
theorem cons_val_zero' (h : 0 < m.succ) (x : α) (u : Fin m → α) : vecCons x u ⟨0, h⟩ = x :=
rfl
#align matrix.cons_val_zero' Matrix.cons_val_zero'
@[simp]
theorem cons_val_succ (x : α) (u : Fin m → α) (i : Fin m) : vecCons x u i.succ = u i := by
simp [vecCons]
#align matrix.cons_val_succ Matrix.cons_val_succ
@[simp]
theorem cons_val_succ' {i : ℕ} (h : i.succ < m.succ) (x : α) (u : Fin m → α) :
vecCons x u ⟨i.succ, h⟩ = u ⟨i, Nat.lt_of_succ_lt_succ h⟩ := by
simp only [vecCons, Fin.cons, Fin.cases_succ']
#align matrix.cons_val_succ' Matrix.cons_val_succ'
@[simp]
theorem head_cons (x : α) (u : Fin m → α) : vecHead (vecCons x u) = x :=
rfl
#align matrix.head_cons Matrix.head_cons
@[simp]
theorem tail_cons (x : α) (u : Fin m → α) : vecTail (vecCons x u) = u := by
ext
simp [vecTail]
#align matrix.tail_cons Matrix.tail_cons
@[simp]
theorem empty_val' {n' : Type*} (j : n') : (fun i => (![] : Fin 0 → n' → α) i j) = ![] :=
empty_eq _
#align matrix.empty_val' Matrix.empty_val'
@[simp]
theorem cons_head_tail (u : Fin m.succ → α) : vecCons (vecHead u) (vecTail u) = u :=
Fin.cons_self_tail _
#align matrix.cons_head_tail Matrix.cons_head_tail
@[simp]
theorem range_cons (x : α) (u : Fin n → α) : Set.range (vecCons x u) = {x} ∪ Set.range u :=
Set.ext fun y => by simp [Fin.exists_fin_succ, eq_comm]
#align matrix.range_cons Matrix.range_cons
@[simp]
theorem range_empty (u : Fin 0 → α) : Set.range u = ∅ :=
Set.range_eq_empty _
#align matrix.range_empty Matrix.range_empty
-- @[simp] -- Porting note (#10618): simp can prove this
theorem range_cons_empty (x : α) (u : Fin 0 → α) : Set.range (Matrix.vecCons x u) = {x} := by
rw [range_cons, range_empty, Set.union_empty]
#align matrix.range_cons_empty Matrix.range_cons_empty
-- @[simp] -- Porting note (#10618): simp can prove this (up to commutativity)
theorem range_cons_cons_empty (x y : α) (u : Fin 0 → α) :
Set.range (vecCons x <| vecCons y u) = {x, y} := by
rw [range_cons, range_cons_empty, Set.singleton_union]
#align matrix.range_cons_cons_empty Matrix.range_cons_cons_empty
@[simp]
theorem vecCons_const (a : α) : (vecCons a fun _ : Fin n => a) = fun _ => a :=
funext <| Fin.forall_fin_succ.2 ⟨rfl, cons_val_succ _ _⟩
#align matrix.vec_cons_const Matrix.vecCons_const
theorem vec_single_eq_const (a : α) : ![a] = fun _ => a :=
let _ : Unique (Fin 1) := inferInstance
funext <| Unique.forall_iff.2 rfl
#align matrix.vec_single_eq_const Matrix.vec_single_eq_const
/-- `![a, b, ...] 1` is equal to `b`.
The simplifier needs a special lemma for length `≥ 2`, in addition to
`cons_val_succ`, because `1 : Fin 1 = 0 : Fin 1`.
-/
@[simp]
theorem cons_val_one (x : α) (u : Fin m.succ → α) : vecCons x u 1 = vecHead u :=
rfl
#align matrix.cons_val_one Matrix.cons_val_one
@[simp]
theorem cons_val_two (x : α) (u : Fin m.succ.succ → α) : vecCons x u 2 = vecHead (vecTail u) :=
rfl
@[simp]
lemma cons_val_three (x : α) (u : Fin m.succ.succ.succ → α) :
vecCons x u 3 = vecHead (vecTail (vecTail u)) :=
rfl
@[simp]
lemma cons_val_four (x : α) (u : Fin m.succ.succ.succ.succ → α) :
vecCons x u 4 = vecHead (vecTail (vecTail (vecTail u))) :=
rfl
@[simp]
theorem cons_val_fin_one (x : α) (u : Fin 0 → α) : ∀ (i : Fin 1), vecCons x u i = x := by
rw [Fin.forall_fin_one]
rfl
#align matrix.cons_val_fin_one Matrix.cons_val_fin_one
theorem cons_fin_one (x : α) (u : Fin 0 → α) : vecCons x u = fun _ => x :=
funext (cons_val_fin_one x u)
#align matrix.cons_fin_one Matrix.cons_fin_one
open Lean in
open Qq in
protected instance _root_.PiFin.toExpr [ToLevel.{u}] [ToExpr α] (n : ℕ) : ToExpr (Fin n → α) :=
have lu := toLevel.{u}
have eα : Q(Type $lu) := toTypeExpr α
have toTypeExpr := q(Fin $n → $eα)
match n with
| 0 => { toTypeExpr, toExpr := fun _ => q(@vecEmpty $eα) }
| n + 1 =>
{ toTypeExpr, toExpr := fun v =>
have := PiFin.toExpr n
have eh : Q($eα) := toExpr (vecHead v)
have et : Q(Fin $n → $eα) := toExpr (vecTail v)
q(vecCons $eh $et) }
#align pi_fin.reflect PiFin.toExpr
-- Porting note: the next decl is commented out. TODO(eric-wieser)
-- /-- Convert a vector of pexprs to the pexpr constructing that vector. -/
-- unsafe def _root_.pi_fin.to_pexpr : ∀ {n}, (Fin n → pexpr) → pexpr
-- | 0, v => ``(![])
-- | n + 1, v => ``(vecCons $(v 0) $(_root_.pi_fin.to_pexpr <| vecTail v))
-- #align pi_fin.to_pexpr pi_fin.to_pexpr
/-! ### `bit0` and `bit1` indices
The following definitions and `simp` lemmas are used to allow
numeral-indexed element of a vector given with matrix notation to
be extracted by `simp` in Lean 3 (even when the numeral is larger than the
number of elements in the vector, which is taken modulo that number
of elements by virtue of the semantics of `bit0` and `bit1` and of
addition on `Fin n`).
-/
/-- `vecAppend ho u v` appends two vectors of lengths `m` and `n` to produce
one of length `o = m + n`. This is a variant of `Fin.append` with an additional `ho` argument,
which provides control of definitional equality for the vector length.
This turns out to be helpful when providing simp lemmas to reduce `![a, b, c] n`, and also means
that `vecAppend ho u v 0` is valid. `Fin.append u v 0` is not valid in this case because there is
no `Zero (Fin (m + n))` instance. -/
def vecAppend {α : Type*} {o : ℕ} (ho : o = m + n) (u : Fin m → α) (v : Fin n → α) : Fin o → α :=
Fin.append u v ∘ Fin.cast ho
#align matrix.vec_append Matrix.vecAppend
theorem vecAppend_eq_ite {α : Type*} {o : ℕ} (ho : o = m + n) (u : Fin m → α) (v : Fin n → α) :
vecAppend ho u v = fun i : Fin o =>
if h : (i : ℕ) < m then u ⟨i, h⟩ else v ⟨(i : ℕ) - m, by omega⟩ := by
ext i
rw [vecAppend, Fin.append, Function.comp_apply, Fin.addCases]
congr with hi
simp only [eq_rec_constant]
rfl
#align matrix.vec_append_eq_ite Matrix.vecAppend_eq_ite
-- Porting note: proof was `rfl`, so this is no longer a `dsimp`-lemma
-- Could become one again with change to `Nat.ble`:
-- https://github.com/leanprover-community/mathlib4/pull/1741/files/#r1083902351
@[simp]
theorem vecAppend_apply_zero {α : Type*} {o : ℕ} (ho : o + 1 = m + 1 + n) (u : Fin (m + 1) → α)
(v : Fin n → α) : vecAppend ho u v 0 = u 0 :=
dif_pos _
#align matrix.vec_append_apply_zero Matrix.vecAppend_apply_zero
@[simp]
theorem empty_vecAppend (v : Fin n → α) : vecAppend n.zero_add.symm ![] v = v := by
ext
simp [vecAppend_eq_ite]
#align matrix.empty_vec_append Matrix.empty_vecAppend
@[simp]
theorem cons_vecAppend (ho : o + 1 = m + 1 + n) (x : α) (u : Fin m → α) (v : Fin n → α) :
vecAppend ho (vecCons x u) v = vecCons x (vecAppend (by omega) u v) := by
ext i
simp_rw [vecAppend_eq_ite]
split_ifs with h
· rcases i with ⟨⟨⟩ | i, hi⟩
· simp
· simp only [Nat.add_lt_add_iff_right, Fin.val_mk] at h
simp [h]
· rcases i with ⟨⟨⟩ | i, hi⟩
· simp at h
· rw [not_lt, Fin.val_mk, Nat.add_le_add_iff_right] at h
simp [h, not_lt.2 h]
#align matrix.cons_vec_append Matrix.cons_vecAppend
/-- `vecAlt0 v` gives a vector with half the length of `v`, with
only alternate elements (even-numbered). -/
def vecAlt0 (hm : m = n + n) (v : Fin m → α) (k : Fin n) : α := v ⟨(k : ℕ) + k, by omega⟩
#align matrix.vec_alt0 Matrix.vecAlt0
/-- `vecAlt1 v` gives a vector with half the length of `v`, with
only alternate elements (odd-numbered). -/
def vecAlt1 (hm : m = n + n) (v : Fin m → α) (k : Fin n) : α :=
v ⟨(k : ℕ) + k + 1, hm.symm ▸ Nat.add_succ_lt_add k.2 k.2⟩
#align matrix.vec_alt1 Matrix.vecAlt1
section bits
set_option linter.deprecated false
theorem vecAlt0_vecAppend (v : Fin n → α) : vecAlt0 rfl (vecAppend rfl v v) = v ∘ bit0 := by
ext i
simp_rw [Function.comp, bit0, vecAlt0, vecAppend_eq_ite]
split_ifs with h <;> congr
· rw [Fin.val_mk] at h
exact (Nat.mod_eq_of_lt h).symm
· rw [Fin.val_mk, not_lt] at h
simp only [Fin.ext_iff, Fin.val_add, Fin.val_mk, Nat.mod_eq_sub_mod h]
refine (Nat.mod_eq_of_lt ?_).symm
omega
#align matrix.vec_alt0_vec_append Matrix.vecAlt0_vecAppend
theorem vecAlt1_vecAppend (v : Fin (n + 1) → α) : vecAlt1 rfl (vecAppend rfl v v) = v ∘ bit1 := by
ext i
simp_rw [Function.comp, vecAlt1, vecAppend_eq_ite]
cases n with
| zero =>
cases' i with i hi
simp only [Nat.zero_eq, Nat.zero_add, Nat.lt_one_iff] at hi; subst i; rfl
| succ n =>
split_ifs with h <;> simp_rw [bit1, bit0] <;> congr
· simp [Nat.mod_eq_of_lt, h]
· rw [Fin.val_mk, not_lt] at h
simp only [Fin.ext_iff, Fin.val_add, Fin.val_mk, Nat.mod_add_mod, Fin.val_one,
Nat.mod_eq_sub_mod h, show 1 % (n + 2) = 1 from Nat.mod_eq_of_lt (by omega)]
refine (Nat.mod_eq_of_lt ?_).symm
omega
#align matrix.vec_alt1_vec_append Matrix.vecAlt1_vecAppend
@[simp]
theorem vecHead_vecAlt0 (hm : m + 2 = n + 1 + (n + 1)) (v : Fin (m + 2) → α) :
vecHead (vecAlt0 hm v) = v 0 :=
rfl
#align matrix.vec_head_vec_alt0 Matrix.vecHead_vecAlt0
@[simp]
theorem vecHead_vecAlt1 (hm : m + 2 = n + 1 + (n + 1)) (v : Fin (m + 2) → α) :
vecHead (vecAlt1 hm v) = v 1 := by simp [vecHead, vecAlt1]
#align matrix.vec_head_vec_alt1 Matrix.vecHead_vecAlt1
@[simp]
theorem cons_vec_bit0_eq_alt0 (x : α) (u : Fin n → α) (i : Fin (n + 1)) :
vecCons x u (bit0 i) = vecAlt0 rfl (vecAppend rfl (vecCons x u) (vecCons x u)) i := by
rw [vecAlt0_vecAppend]; rfl
#align matrix.cons_vec_bit0_eq_alt0 Matrix.cons_vec_bit0_eq_alt0
@[simp]
theorem cons_vec_bit1_eq_alt1 (x : α) (u : Fin n → α) (i : Fin (n + 1)) :
vecCons x u (bit1 i) = vecAlt1 rfl (vecAppend rfl (vecCons x u) (vecCons x u)) i := by
rw [vecAlt1_vecAppend]; rfl
#align matrix.cons_vec_bit1_eq_alt1 Matrix.cons_vec_bit1_eq_alt1
end bits
@[simp]
theorem cons_vecAlt0 (h : m + 1 + 1 = n + 1 + (n + 1)) (x y : α) (u : Fin m → α) :
vecAlt0 h (vecCons x (vecCons y u)) = vecCons x (vecAlt0 (by omega) u) := by
ext i
simp_rw [vecAlt0]
rcases i with ⟨⟨⟩ | i, hi⟩
· rfl
· simp [vecAlt0, Nat.add_right_comm, ← Nat.add_assoc]
#align matrix.cons_vec_alt0 Matrix.cons_vecAlt0
-- Although proved by simp, extracting element 8 of a five-element
-- vector does not work by simp unless this lemma is present.
@[simp]
theorem empty_vecAlt0 (α) {h} : vecAlt0 h (![] : Fin 0 → α) = ![] := by
simp [eq_iff_true_of_subsingleton]
#align matrix.empty_vec_alt0 Matrix.empty_vecAlt0
@[simp]
theorem cons_vecAlt1 (h : m + 1 + 1 = n + 1 + (n + 1)) (x y : α) (u : Fin m → α) :
vecAlt1 h (vecCons x (vecCons y u)) = vecCons y (vecAlt1 (by omega) u) := by
ext i
simp_rw [vecAlt1]
rcases i with ⟨⟨⟩ | i, hi⟩
· rfl
· simp [vecAlt1, Nat.add_right_comm, ← Nat.add_assoc]
#align matrix.cons_vec_alt1 Matrix.cons_vecAlt1
-- Although proved by simp, extracting element 9 of a five-element
-- vector does not work by simp unless this lemma is present.
@[simp]
theorem empty_vecAlt1 (α) {h} : vecAlt1 h (![] : Fin 0 → α) = ![] := by
simp [eq_iff_true_of_subsingleton]
#align matrix.empty_vec_alt1 Matrix.empty_vecAlt1
end Val
section SMul
variable {M : Type*} [SMul M α]
@[simp]
theorem smul_empty (x : M) (v : Fin 0 → α) : x • v = ![] :=
empty_eq _
#align matrix.smul_empty Matrix.smul_empty
@[simp]
theorem smul_cons (x : M) (y : α) (v : Fin n → α) : x • vecCons y v = vecCons (x • y) (x • v) := by
ext i
refine Fin.cases ?_ ?_ i <;> simp
#align matrix.smul_cons Matrix.smul_cons
end SMul
section Add
variable [Add α]
@[simp]
theorem empty_add_empty (v w : Fin 0 → α) : v + w = ![] :=
empty_eq _
#align matrix.empty_add_empty Matrix.empty_add_empty
@[simp]
theorem cons_add (x : α) (v : Fin n → α) (w : Fin n.succ → α) :
vecCons x v + w = vecCons (x + vecHead w) (v + vecTail w) := by
ext i
refine Fin.cases ?_ ?_ i <;> simp [vecHead, vecTail]
#align matrix.cons_add Matrix.cons_add
@[simp]
theorem add_cons (v : Fin n.succ → α) (y : α) (w : Fin n → α) :
v + vecCons y w = vecCons (vecHead v + y) (vecTail v + w) := by
ext i
refine Fin.cases ?_ ?_ i <;> simp [vecHead, vecTail]
#align matrix.add_cons Matrix.add_cons
-- @[simp] -- Porting note (#10618): simp can prove this
theorem cons_add_cons (x : α) (v : Fin n → α) (y : α) (w : Fin n → α) :
vecCons x v + vecCons y w = vecCons (x + y) (v + w) := by simp
#align matrix.cons_add_cons Matrix.cons_add_cons
@[simp]
theorem head_add (a b : Fin n.succ → α) : vecHead (a + b) = vecHead a + vecHead b :=
rfl
#align matrix.head_add Matrix.head_add
@[simp]
theorem tail_add (a b : Fin n.succ → α) : vecTail (a + b) = vecTail a + vecTail b :=
rfl
#align matrix.tail_add Matrix.tail_add
end Add
section Sub
variable [Sub α]
@[simp]
theorem empty_sub_empty (v w : Fin 0 → α) : v - w = ![] :=
empty_eq _
#align matrix.empty_sub_empty Matrix.empty_sub_empty
@[simp]
theorem cons_sub (x : α) (v : Fin n → α) (w : Fin n.succ → α) :
vecCons x v - w = vecCons (x - vecHead w) (v - vecTail w) := by
ext i
refine Fin.cases ?_ ?_ i <;> simp [vecHead, vecTail]
#align matrix.cons_sub Matrix.cons_sub
@[simp]
theorem sub_cons (v : Fin n.succ → α) (y : α) (w : Fin n → α) :
v - vecCons y w = vecCons (vecHead v - y) (vecTail v - w) := by
ext i
refine Fin.cases ?_ ?_ i <;> simp [vecHead, vecTail]
#align matrix.sub_cons Matrix.sub_cons
-- @[simp] -- Porting note (#10618): simp can prove this
theorem cons_sub_cons (x : α) (v : Fin n → α) (y : α) (w : Fin n → α) :
vecCons x v - vecCons y w = vecCons (x - y) (v - w) := by simp
#align matrix.cons_sub_cons Matrix.cons_sub_cons
@[simp]
theorem head_sub (a b : Fin n.succ → α) : vecHead (a - b) = vecHead a - vecHead b :=
rfl
#align matrix.head_sub Matrix.head_sub
@[simp]
theorem tail_sub (a b : Fin n.succ → α) : vecTail (a - b) = vecTail a - vecTail b :=
rfl
#align matrix.tail_sub Matrix.tail_sub
end Sub
section Zero
variable [Zero α]
@[simp]
theorem zero_empty : (0 : Fin 0 → α) = ![] :=
empty_eq _
#align matrix.zero_empty Matrix.zero_empty
@[simp]
| Mathlib/Data/Fin/VecNotation.lean | 535 | 539 | theorem cons_zero_zero : vecCons (0 : α) (0 : Fin n → α) = 0 := by |
ext i
refine Fin.cases ?_ ?_ i
· rfl
simp
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Analysis.NormedSpace.Multilinear.Curry
#align_import analysis.calculus.formal_multilinear_series from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Formal multilinear series
In this file we define `FormalMultilinearSeries 𝕜 E F` to be a family of `n`-multilinear maps for
all `n`, designed to model the sequence of derivatives of a function. In other files we use this
notion to define `C^n` functions (called `contDiff` in `mathlib`) and analytic functions.
## Notations
We use the notation `E [×n]→L[𝕜] F` for the space of continuous multilinear maps on `E^n` with
values in `F`. This is the space in which the `n`-th derivative of a function from `E` to `F` lives.
## Tags
multilinear, formal series
-/
noncomputable section
open Set Fin Topology
-- Porting note: added explicit universes to fix compile
universe u u' v w x
variable {𝕜 : Type u} {𝕜' : Type u'} {E : Type v} {F : Type w} {G : Type x}
section
variable [Ring 𝕜] [AddCommGroup E] [Module 𝕜 E] [TopologicalSpace E] [TopologicalAddGroup E]
[ContinuousConstSMul 𝕜 E] [AddCommGroup F] [Module 𝕜 F] [TopologicalSpace F]
[TopologicalAddGroup F] [ContinuousConstSMul 𝕜 F] [AddCommGroup G] [Module 𝕜 G]
[TopologicalSpace G] [TopologicalAddGroup G] [ContinuousConstSMul 𝕜 G]
/-- A formal multilinear series over a field `𝕜`, from `E` to `F`, is given by a family of
multilinear maps from `E^n` to `F` for all `n`. -/
@[nolint unusedArguments]
def FormalMultilinearSeries (𝕜 : Type*) (E : Type*) (F : Type*) [Ring 𝕜] [AddCommGroup E]
[Module 𝕜 E] [TopologicalSpace E] [TopologicalAddGroup E] [ContinuousConstSMul 𝕜 E]
[AddCommGroup F] [Module 𝕜 F] [TopologicalSpace F] [TopologicalAddGroup F]
[ContinuousConstSMul 𝕜 F] :=
∀ n : ℕ, E[×n]→L[𝕜] F
#align formal_multilinear_series FormalMultilinearSeries
-- Porting note: was `deriving`
instance : AddCommGroup (FormalMultilinearSeries 𝕜 E F) :=
inferInstanceAs <| AddCommGroup <| ∀ n : ℕ, E[×n]→L[𝕜] F
instance : Inhabited (FormalMultilinearSeries 𝕜 E F) :=
⟨0⟩
section Module
instance (𝕜') [Semiring 𝕜'] [Module 𝕜' F] [ContinuousConstSMul 𝕜' F] [SMulCommClass 𝕜 𝕜' F] :
Module 𝕜' (FormalMultilinearSeries 𝕜 E F) :=
inferInstanceAs <| Module 𝕜' <| ∀ n : ℕ, E[×n]→L[𝕜] F
end Module
namespace FormalMultilinearSeries
@[simp] -- Porting note (#10756): new theorem; was not needed in Lean 3
theorem zero_apply (n : ℕ) : (0 : FormalMultilinearSeries 𝕜 E F) n = 0 := rfl
@[simp] -- Porting note (#10756): new theorem; was not needed in Lean 3
theorem neg_apply (f : FormalMultilinearSeries 𝕜 E F) (n : ℕ) : (-f) n = - f n := rfl
@[ext] -- Porting note (#10756): new theorem
protected theorem ext {p q : FormalMultilinearSeries 𝕜 E F} (h : ∀ n, p n = q n) : p = q :=
funext h
protected theorem ext_iff {p q : FormalMultilinearSeries 𝕜 E F} : p = q ↔ ∀ n, p n = q n :=
Function.funext_iff
#align formal_multilinear_series.ext_iff FormalMultilinearSeries.ext_iff
protected theorem ne_iff {p q : FormalMultilinearSeries 𝕜 E F} : p ≠ q ↔ ∃ n, p n ≠ q n :=
Function.ne_iff
#align formal_multilinear_series.ne_iff FormalMultilinearSeries.ne_iff
/-- Cartesian product of two formal multilinear series (with the same field `𝕜` and the same source
space, but possibly different target spaces). -/
def prod (p : FormalMultilinearSeries 𝕜 E F) (q : FormalMultilinearSeries 𝕜 E G) :
FormalMultilinearSeries 𝕜 E (F × G)
| n => (p n).prod (q n)
/-- Killing the zeroth coefficient in a formal multilinear series -/
def removeZero (p : FormalMultilinearSeries 𝕜 E F) : FormalMultilinearSeries 𝕜 E F
| 0 => 0
| n + 1 => p (n + 1)
#align formal_multilinear_series.remove_zero FormalMultilinearSeries.removeZero
@[simp]
theorem removeZero_coeff_zero (p : FormalMultilinearSeries 𝕜 E F) : p.removeZero 0 = 0 :=
rfl
#align formal_multilinear_series.remove_zero_coeff_zero FormalMultilinearSeries.removeZero_coeff_zero
@[simp]
theorem removeZero_coeff_succ (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ) :
p.removeZero (n + 1) = p (n + 1) :=
rfl
#align formal_multilinear_series.remove_zero_coeff_succ FormalMultilinearSeries.removeZero_coeff_succ
theorem removeZero_of_pos (p : FormalMultilinearSeries 𝕜 E F) {n : ℕ} (h : 0 < n) :
p.removeZero n = p n := by
rw [← Nat.succ_pred_eq_of_pos h]
rfl
#align formal_multilinear_series.remove_zero_of_pos FormalMultilinearSeries.removeZero_of_pos
/-- Convenience congruence lemma stating in a dependent setting that, if the arguments to a formal
multilinear series are equal, then the values are also equal. -/
theorem congr (p : FormalMultilinearSeries 𝕜 E F) {m n : ℕ} {v : Fin m → E} {w : Fin n → E}
(h1 : m = n) (h2 : ∀ (i : ℕ) (him : i < m) (hin : i < n), v ⟨i, him⟩ = w ⟨i, hin⟩) :
p m v = p n w := by
subst n
congr with ⟨i, hi⟩
exact h2 i hi hi
#align formal_multilinear_series.congr FormalMultilinearSeries.congr
/-- Composing each term `pₙ` in a formal multilinear series with `(u, ..., u)` where `u` is a fixed
continuous linear map, gives a new formal multilinear series `p.compContinuousLinearMap u`. -/
def compContinuousLinearMap (p : FormalMultilinearSeries 𝕜 F G) (u : E →L[𝕜] F) :
FormalMultilinearSeries 𝕜 E G := fun n => (p n).compContinuousLinearMap fun _ : Fin n => u
#align formal_multilinear_series.comp_continuous_linear_map FormalMultilinearSeries.compContinuousLinearMap
@[simp]
theorem compContinuousLinearMap_apply (p : FormalMultilinearSeries 𝕜 F G) (u : E →L[𝕜] F) (n : ℕ)
(v : Fin n → E) : (p.compContinuousLinearMap u) n v = p n (u ∘ v) :=
rfl
#align formal_multilinear_series.comp_continuous_linear_map_apply FormalMultilinearSeries.compContinuousLinearMap_apply
variable (𝕜) [Ring 𝕜'] [SMul 𝕜 𝕜']
variable [Module 𝕜' E] [ContinuousConstSMul 𝕜' E] [IsScalarTower 𝕜 𝕜' E]
variable [Module 𝕜' F] [ContinuousConstSMul 𝕜' F] [IsScalarTower 𝕜 𝕜' F]
/-- Reinterpret a formal `𝕜'`-multilinear series as a formal `𝕜`-multilinear series. -/
@[simp]
protected def restrictScalars (p : FormalMultilinearSeries 𝕜' E F) :
FormalMultilinearSeries 𝕜 E F := fun n => (p n).restrictScalars 𝕜
#align formal_multilinear_series.restrict_scalars FormalMultilinearSeries.restrictScalars
end FormalMultilinearSeries
end
namespace FormalMultilinearSeries
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E] [NormedAddCommGroup F]
[NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
variable (p : FormalMultilinearSeries 𝕜 E F)
/-- Forgetting the zeroth term in a formal multilinear series, and interpreting the following terms
as multilinear maps into `E →L[𝕜] F`. If `p` is the Taylor series (`HasFTaylorSeriesUpTo`) of a
function, then `p.shift` is the Taylor series of the derivative of the function. Note that the
`p.sum` of a Taylor series `p` does not give the original function; for a formal multilinear
series that sums to the derivative of `p.sum`, see `HasFPowerSeriesOnBall.fderiv`. -/
def shift : FormalMultilinearSeries 𝕜 E (E →L[𝕜] F) := fun n => (p n.succ).curryRight
#align formal_multilinear_series.shift FormalMultilinearSeries.shift
/-- Adding a zeroth term to a formal multilinear series taking values in `E →L[𝕜] F`. This
corresponds to starting from a Taylor series (`HasFTaylorSeriesUpTo`) for the derivative of a
function, and building a Taylor series for the function itself. -/
def unshift (q : FormalMultilinearSeries 𝕜 E (E →L[𝕜] F)) (z : F) : FormalMultilinearSeries 𝕜 E F
| 0 => (continuousMultilinearCurryFin0 𝕜 E F).symm z
| n + 1 => -- Porting note: added type hint here and explicit universes to fix compile
(continuousMultilinearCurryRightEquiv' 𝕜 n E F :
(E [×n]→L[𝕜] E →L[𝕜] F) → (E [×n.succ]→L[𝕜] F)) (q n)
#align formal_multilinear_series.unshift FormalMultilinearSeries.unshift
end FormalMultilinearSeries
section
variable [Ring 𝕜] [AddCommGroup E] [Module 𝕜 E] [TopologicalSpace E] [TopologicalAddGroup E]
[ContinuousConstSMul 𝕜 E] [AddCommGroup F] [Module 𝕜 F] [TopologicalSpace F]
[TopologicalAddGroup F] [ContinuousConstSMul 𝕜 F] [AddCommGroup G] [Module 𝕜 G]
[TopologicalSpace G] [TopologicalAddGroup G] [ContinuousConstSMul 𝕜 G]
namespace ContinuousLinearMap
/-- Composing each term `pₙ` in a formal multilinear series with a continuous linear map `f` on the
left gives a new formal multilinear series `f.compFormalMultilinearSeries p` whose general term
is `f ∘ pₙ`. -/
def compFormalMultilinearSeries (f : F →L[𝕜] G) (p : FormalMultilinearSeries 𝕜 E F) :
FormalMultilinearSeries 𝕜 E G := fun n => f.compContinuousMultilinearMap (p n)
#align continuous_linear_map.comp_formal_multilinear_series ContinuousLinearMap.compFormalMultilinearSeries
@[simp]
theorem compFormalMultilinearSeries_apply (f : F →L[𝕜] G) (p : FormalMultilinearSeries 𝕜 E F)
(n : ℕ) : (f.compFormalMultilinearSeries p) n = f.compContinuousMultilinearMap (p n) :=
rfl
#align continuous_linear_map.comp_formal_multilinear_series_apply ContinuousLinearMap.compFormalMultilinearSeries_apply
theorem compFormalMultilinearSeries_apply' (f : F →L[𝕜] G) (p : FormalMultilinearSeries 𝕜 E F)
(n : ℕ) (v : Fin n → E) : (f.compFormalMultilinearSeries p) n v = f (p n v) :=
rfl
#align continuous_linear_map.comp_formal_multilinear_series_apply' ContinuousLinearMap.compFormalMultilinearSeries_apply'
end ContinuousLinearMap
namespace ContinuousMultilinearMap
variable {ι : Type*} {E : ι → Type*} [∀ i, AddCommGroup (E i)] [∀ i, Module 𝕜 (E i)]
[∀ i, TopologicalSpace (E i)] [∀ i, TopologicalAddGroup (E i)]
[∀ i, ContinuousConstSMul 𝕜 (E i)] [Fintype ι] (f : ContinuousMultilinearMap 𝕜 E F)
/-- Realize a ContinuousMultilinearMap on `∀ i : ι, E i` as the evaluation of a
FormalMultilinearSeries by choosing an arbitrary identification `ι ≃ Fin (Fintype.card ι)`. -/
noncomputable def toFormalMultilinearSeries : FormalMultilinearSeries 𝕜 (∀ i, E i) F :=
fun n ↦ if h : Fintype.card ι = n then
(f.compContinuousLinearMap .proj).domDomCongr (Fintype.equivFinOfCardEq h)
else 0
end ContinuousMultilinearMap
end
namespace FormalMultilinearSeries
section Order
variable [Ring 𝕜] {n : ℕ} [AddCommGroup E] [Module 𝕜 E] [TopologicalSpace E]
[TopologicalAddGroup E] [ContinuousConstSMul 𝕜 E] [AddCommGroup F] [Module 𝕜 F]
[TopologicalSpace F] [TopologicalAddGroup F] [ContinuousConstSMul 𝕜 F]
{p : FormalMultilinearSeries 𝕜 E F}
/-- The index of the first non-zero coefficient in `p` (or `0` if all coefficients are zero). This
is the order of the isolated zero of an analytic function `f` at a point if `p` is the Taylor
series of `f` at that point. -/
noncomputable def order (p : FormalMultilinearSeries 𝕜 E F) : ℕ :=
sInf { n | p n ≠ 0 }
#align formal_multilinear_series.order FormalMultilinearSeries.order
@[simp]
theorem order_zero : (0 : FormalMultilinearSeries 𝕜 E F).order = 0 := by simp [order]
#align formal_multilinear_series.order_zero FormalMultilinearSeries.order_zero
theorem ne_zero_of_order_ne_zero (hp : p.order ≠ 0) : p ≠ 0 := fun h => by simp [h] at hp
#align formal_multilinear_series.ne_zero_of_order_ne_zero FormalMultilinearSeries.ne_zero_of_order_ne_zero
| Mathlib/Analysis/Calculus/FormalMultilinearSeries.lean | 249 | 250 | theorem order_eq_find [DecidablePred fun n => p n ≠ 0] (hp : ∃ n, p n ≠ 0) :
p.order = Nat.find hp := by | convert Nat.sInf_def hp
|
/-
Copyright (c) 2019 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Fabian Glöckle, Kyle Miller
-/
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.LinearAlgebra.FreeModule.Finite.Basic
import Mathlib.LinearAlgebra.FreeModule.StrongRankCondition
import Mathlib.LinearAlgebra.Projection
import Mathlib.LinearAlgebra.SesquilinearForm
import Mathlib.RingTheory.TensorProduct.Basic
import Mathlib.RingTheory.Ideal.LocalRing
#align_import linear_algebra.dual from "leanprover-community/mathlib"@"b1c017582e9f18d8494e5c18602a8cb4a6f843ac"
/-!
# Dual vector spaces
The dual space of an $R$-module $M$ is the $R$-module of $R$-linear maps $M \to R$.
## Main definitions
* Duals and transposes:
* `Module.Dual R M` defines the dual space of the `R`-module `M`, as `M →ₗ[R] R`.
* `Module.dualPairing R M` is the canonical pairing between `Dual R M` and `M`.
* `Module.Dual.eval R M : M →ₗ[R] Dual R (Dual R)` is the canonical map to the double dual.
* `Module.Dual.transpose` is the linear map from `M →ₗ[R] M'` to `Dual R M' →ₗ[R] Dual R M`.
* `LinearMap.dualMap` is `Module.Dual.transpose` of a given linear map, for dot notation.
* `LinearEquiv.dualMap` is for the dual of an equivalence.
* Bases:
* `Basis.toDual` produces the map `M →ₗ[R] Dual R M` associated to a basis for an `R`-module `M`.
* `Basis.toDual_equiv` is the equivalence `M ≃ₗ[R] Dual R M` associated to a finite basis.
* `Basis.dualBasis` is a basis for `Dual R M` given a finite basis for `M`.
* `Module.dual_bases e ε` is the proposition that the families `e` of vectors and `ε` of dual
vectors have the characteristic properties of a basis and a dual.
* Submodules:
* `Submodule.dualRestrict W` is the transpose `Dual R M →ₗ[R] Dual R W` of the inclusion map.
* `Submodule.dualAnnihilator W` is the kernel of `W.dualRestrict`. That is, it is the submodule
of `dual R M` whose elements all annihilate `W`.
* `Submodule.dualRestrict_comap W'` is the dual annihilator of `W' : Submodule R (Dual R M)`,
pulled back along `Module.Dual.eval R M`.
* `Submodule.dualCopairing W` is the canonical pairing between `W.dualAnnihilator` and `M ⧸ W`.
It is nondegenerate for vector spaces (`subspace.dualCopairing_nondegenerate`).
* `Submodule.dualPairing W` is the canonical pairing between `Dual R M ⧸ W.dualAnnihilator`
and `W`. It is nondegenerate for vector spaces (`Subspace.dualPairing_nondegenerate`).
* Vector spaces:
* `Subspace.dualLift W` is an arbitrary section (using choice) of `Submodule.dualRestrict W`.
## Main results
* Bases:
* `Module.dualBasis.basis` and `Module.dualBasis.coe_basis`: if `e` and `ε` form a dual pair,
then `e` is a basis.
* `Module.dualBasis.coe_dualBasis`: if `e` and `ε` form a dual pair,
then `ε` is a basis.
* Annihilators:
* `Module.dualAnnihilator_gc R M` is the antitone Galois correspondence between
`Submodule.dualAnnihilator` and `Submodule.dualConnihilator`.
* `LinearMap.ker_dual_map_eq_dualAnnihilator_range` says that
`f.dual_map.ker = f.range.dualAnnihilator`
* `LinearMap.range_dual_map_eq_dualAnnihilator_ker_of_subtype_range_surjective` says that
`f.dual_map.range = f.ker.dualAnnihilator`; this is specialized to vector spaces in
`LinearMap.range_dual_map_eq_dualAnnihilator_ker`.
* `Submodule.dualQuotEquivDualAnnihilator` is the equivalence
`Dual R (M ⧸ W) ≃ₗ[R] W.dualAnnihilator`
* `Submodule.quotDualCoannihilatorToDual` is the nondegenerate pairing
`M ⧸ W.dualCoannihilator →ₗ[R] Dual R W`.
It is an perfect pairing when `R` is a field and `W` is finite-dimensional.
* Vector spaces:
* `Subspace.dualAnnihilator_dualConnihilator_eq` says that the double dual annihilator,
pulled back ground `Module.Dual.eval`, is the original submodule.
* `Subspace.dualAnnihilator_gci` says that `module.dualAnnihilator_gc R M` is an
antitone Galois coinsertion.
* `Subspace.quotAnnihilatorEquiv` is the equivalence
`Dual K V ⧸ W.dualAnnihilator ≃ₗ[K] Dual K W`.
* `LinearMap.dualPairing_nondegenerate` says that `Module.dualPairing` is nondegenerate.
* `Subspace.is_compl_dualAnnihilator` says that the dual annihilator carries complementary
subspaces to complementary subspaces.
* Finite-dimensional vector spaces:
* `Module.evalEquiv` is the equivalence `V ≃ₗ[K] Dual K (Dual K V)`
* `Module.mapEvalEquiv` is the order isomorphism between subspaces of `V` and
subspaces of `Dual K (Dual K V)`.
* `Subspace.orderIsoFiniteCodimDim` is the antitone order isomorphism between
finite-codimensional subspaces of `V` and finite-dimensional subspaces of `Dual K V`.
* `Subspace.orderIsoFiniteDimensional` is the antitone order isomorphism between
subspaces of a finite-dimensional vector space `V` and subspaces of its dual.
* `Subspace.quotDualEquivAnnihilator W` is the equivalence
`(Dual K V ⧸ W.dualLift.range) ≃ₗ[K] W.dualAnnihilator`, where `W.dualLift.range` is a copy
of `Dual K W` inside `Dual K V`.
* `Subspace.quotEquivAnnihilator W` is the equivalence `(V ⧸ W) ≃ₗ[K] W.dualAnnihilator`
* `Subspace.dualQuotDistrib W` is an equivalence
`Dual K (V₁ ⧸ W) ≃ₗ[K] Dual K V₁ ⧸ W.dualLift.range` from an arbitrary choice of
splitting of `V₁`.
-/
noncomputable section
namespace Module
-- Porting note: max u v universe issues so name and specific below
universe uR uA uM uM' uM''
variable (R : Type uR) (A : Type uA) (M : Type uM)
variable [CommSemiring R] [AddCommMonoid M] [Module R M]
/-- The dual space of an R-module M is the R-module of linear maps `M → R`. -/
abbrev Dual :=
M →ₗ[R] R
#align module.dual Module.Dual
/-- The canonical pairing of a vector space and its algebraic dual. -/
def dualPairing (R M) [CommSemiring R] [AddCommMonoid M] [Module R M] :
Module.Dual R M →ₗ[R] M →ₗ[R] R :=
LinearMap.id
#align module.dual_pairing Module.dualPairing
@[simp]
theorem dualPairing_apply (v x) : dualPairing R M v x = v x :=
rfl
#align module.dual_pairing_apply Module.dualPairing_apply
namespace Dual
instance : Inhabited (Dual R M) := ⟨0⟩
/-- Maps a module M to the dual of the dual of M. See `Module.erange_coe` and
`Module.evalEquiv`. -/
def eval : M →ₗ[R] Dual R (Dual R M) :=
LinearMap.flip LinearMap.id
#align module.dual.eval Module.Dual.eval
@[simp]
theorem eval_apply (v : M) (a : Dual R M) : eval R M v a = a v :=
rfl
#align module.dual.eval_apply Module.Dual.eval_apply
variable {R M} {M' : Type uM'}
variable [AddCommMonoid M'] [Module R M']
/-- The transposition of linear maps, as a linear map from `M →ₗ[R] M'` to
`Dual R M' →ₗ[R] Dual R M`. -/
def transpose : (M →ₗ[R] M') →ₗ[R] Dual R M' →ₗ[R] Dual R M :=
(LinearMap.llcomp R M M' R).flip
#align module.dual.transpose Module.Dual.transpose
-- Porting note: with reducible def need to specify some parameters to transpose explicitly
theorem transpose_apply (u : M →ₗ[R] M') (l : Dual R M') : transpose (R := R) u l = l.comp u :=
rfl
#align module.dual.transpose_apply Module.Dual.transpose_apply
variable {M'' : Type uM''} [AddCommMonoid M''] [Module R M'']
-- Porting note: with reducible def need to specify some parameters to transpose explicitly
theorem transpose_comp (u : M' →ₗ[R] M'') (v : M →ₗ[R] M') :
transpose (R := R) (u.comp v) = (transpose (R := R) v).comp (transpose (R := R) u) :=
rfl
#align module.dual.transpose_comp Module.Dual.transpose_comp
end Dual
section Prod
variable (M' : Type uM') [AddCommMonoid M'] [Module R M']
/-- Taking duals distributes over products. -/
@[simps!]
def dualProdDualEquivDual : (Module.Dual R M × Module.Dual R M') ≃ₗ[R] Module.Dual R (M × M') :=
LinearMap.coprodEquiv R
#align module.dual_prod_dual_equiv_dual Module.dualProdDualEquivDual
@[simp]
theorem dualProdDualEquivDual_apply (φ : Module.Dual R M) (ψ : Module.Dual R M') :
dualProdDualEquivDual R M M' (φ, ψ) = φ.coprod ψ :=
rfl
#align module.dual_prod_dual_equiv_dual_apply Module.dualProdDualEquivDual_apply
end Prod
end Module
section DualMap
open Module
universe u v v'
variable {R : Type u} [CommSemiring R] {M₁ : Type v} {M₂ : Type v'}
variable [AddCommMonoid M₁] [Module R M₁] [AddCommMonoid M₂] [Module R M₂]
/-- Given a linear map `f : M₁ →ₗ[R] M₂`, `f.dualMap` is the linear map between the dual of
`M₂` and `M₁` such that it maps the functional `φ` to `φ ∘ f`. -/
def LinearMap.dualMap (f : M₁ →ₗ[R] M₂) : Dual R M₂ →ₗ[R] Dual R M₁ :=
-- Porting note: with reducible def need to specify some parameters to transpose explicitly
Module.Dual.transpose (R := R) f
#align linear_map.dual_map LinearMap.dualMap
lemma LinearMap.dualMap_eq_lcomp (f : M₁ →ₗ[R] M₂) : f.dualMap = f.lcomp R := rfl
-- Porting note: with reducible def need to specify some parameters to transpose explicitly
theorem LinearMap.dualMap_def (f : M₁ →ₗ[R] M₂) : f.dualMap = Module.Dual.transpose (R := R) f :=
rfl
#align linear_map.dual_map_def LinearMap.dualMap_def
theorem LinearMap.dualMap_apply' (f : M₁ →ₗ[R] M₂) (g : Dual R M₂) : f.dualMap g = g.comp f :=
rfl
#align linear_map.dual_map_apply' LinearMap.dualMap_apply'
@[simp]
theorem LinearMap.dualMap_apply (f : M₁ →ₗ[R] M₂) (g : Dual R M₂) (x : M₁) :
f.dualMap g x = g (f x) :=
rfl
#align linear_map.dual_map_apply LinearMap.dualMap_apply
@[simp]
theorem LinearMap.dualMap_id : (LinearMap.id : M₁ →ₗ[R] M₁).dualMap = LinearMap.id := by
ext
rfl
#align linear_map.dual_map_id LinearMap.dualMap_id
theorem LinearMap.dualMap_comp_dualMap {M₃ : Type*} [AddCommGroup M₃] [Module R M₃]
(f : M₁ →ₗ[R] M₂) (g : M₂ →ₗ[R] M₃) : f.dualMap.comp g.dualMap = (g.comp f).dualMap :=
rfl
#align linear_map.dual_map_comp_dual_map LinearMap.dualMap_comp_dualMap
/-- If a linear map is surjective, then its dual is injective. -/
theorem LinearMap.dualMap_injective_of_surjective {f : M₁ →ₗ[R] M₂} (hf : Function.Surjective f) :
Function.Injective f.dualMap := by
intro φ ψ h
ext x
obtain ⟨y, rfl⟩ := hf x
exact congr_arg (fun g : Module.Dual R M₁ => g y) h
#align linear_map.dual_map_injective_of_surjective LinearMap.dualMap_injective_of_surjective
/-- The `Linear_equiv` version of `LinearMap.dualMap`. -/
def LinearEquiv.dualMap (f : M₁ ≃ₗ[R] M₂) : Dual R M₂ ≃ₗ[R] Dual R M₁ where
__ := f.toLinearMap.dualMap
invFun := f.symm.toLinearMap.dualMap
left_inv φ := LinearMap.ext fun x ↦ congr_arg φ (f.right_inv x)
right_inv φ := LinearMap.ext fun x ↦ congr_arg φ (f.left_inv x)
#align linear_equiv.dual_map LinearEquiv.dualMap
@[simp]
theorem LinearEquiv.dualMap_apply (f : M₁ ≃ₗ[R] M₂) (g : Dual R M₂) (x : M₁) :
f.dualMap g x = g (f x) :=
rfl
#align linear_equiv.dual_map_apply LinearEquiv.dualMap_apply
@[simp]
theorem LinearEquiv.dualMap_refl :
(LinearEquiv.refl R M₁).dualMap = LinearEquiv.refl R (Dual R M₁) := by
ext
rfl
#align linear_equiv.dual_map_refl LinearEquiv.dualMap_refl
@[simp]
theorem LinearEquiv.dualMap_symm {f : M₁ ≃ₗ[R] M₂} :
(LinearEquiv.dualMap f).symm = LinearEquiv.dualMap f.symm :=
rfl
#align linear_equiv.dual_map_symm LinearEquiv.dualMap_symm
theorem LinearEquiv.dualMap_trans {M₃ : Type*} [AddCommGroup M₃] [Module R M₃] (f : M₁ ≃ₗ[R] M₂)
(g : M₂ ≃ₗ[R] M₃) : g.dualMap.trans f.dualMap = (f.trans g).dualMap :=
rfl
#align linear_equiv.dual_map_trans LinearEquiv.dualMap_trans
@[simp]
lemma Dual.apply_one_mul_eq (f : Dual R R) (r : R) :
f 1 * r = f r := by
conv_rhs => rw [← mul_one r, ← smul_eq_mul]
rw [map_smul, smul_eq_mul, mul_comm]
@[simp]
lemma LinearMap.range_dualMap_dual_eq_span_singleton (f : Dual R M₁) :
range f.dualMap = R ∙ f := by
ext m
rw [Submodule.mem_span_singleton]
refine ⟨fun ⟨r, hr⟩ ↦ ⟨r 1, ?_⟩, fun ⟨r, hr⟩ ↦ ⟨r • LinearMap.id, ?_⟩⟩
· ext; simp [dualMap_apply', ← hr]
· ext; simp [dualMap_apply', ← hr]
end DualMap
namespace Basis
universe u v w
open Module Module.Dual Submodule LinearMap Cardinal Function
universe uR uM uK uV uι
variable {R : Type uR} {M : Type uM} {K : Type uK} {V : Type uV} {ι : Type uι}
section CommSemiring
variable [CommSemiring R] [AddCommMonoid M] [Module R M] [DecidableEq ι]
variable (b : Basis ι R M)
/-- The linear map from a vector space equipped with basis to its dual vector space,
taking basis elements to corresponding dual basis elements. -/
def toDual : M →ₗ[R] Module.Dual R M :=
b.constr ℕ fun v => b.constr ℕ fun w => if w = v then (1 : R) else 0
#align basis.to_dual Basis.toDual
theorem toDual_apply (i j : ι) : b.toDual (b i) (b j) = if i = j then 1 else 0 := by
erw [constr_basis b, constr_basis b]
simp only [eq_comm]
#align basis.to_dual_apply Basis.toDual_apply
@[simp]
theorem toDual_total_left (f : ι →₀ R) (i : ι) :
b.toDual (Finsupp.total ι M R b f) (b i) = f i := by
rw [Finsupp.total_apply, Finsupp.sum, _root_.map_sum, LinearMap.sum_apply]
simp_rw [LinearMap.map_smul, LinearMap.smul_apply, toDual_apply, smul_eq_mul, mul_boole,
Finset.sum_ite_eq']
split_ifs with h
· rfl
· rw [Finsupp.not_mem_support_iff.mp h]
#align basis.to_dual_total_left Basis.toDual_total_left
@[simp]
theorem toDual_total_right (f : ι →₀ R) (i : ι) :
b.toDual (b i) (Finsupp.total ι M R b f) = f i := by
rw [Finsupp.total_apply, Finsupp.sum, _root_.map_sum]
simp_rw [LinearMap.map_smul, toDual_apply, smul_eq_mul, mul_boole, Finset.sum_ite_eq]
split_ifs with h
· rfl
· rw [Finsupp.not_mem_support_iff.mp h]
#align basis.to_dual_total_right Basis.toDual_total_right
theorem toDual_apply_left (m : M) (i : ι) : b.toDual m (b i) = b.repr m i := by
rw [← b.toDual_total_left, b.total_repr]
#align basis.to_dual_apply_left Basis.toDual_apply_left
theorem toDual_apply_right (i : ι) (m : M) : b.toDual (b i) m = b.repr m i := by
rw [← b.toDual_total_right, b.total_repr]
#align basis.to_dual_apply_right Basis.toDual_apply_right
theorem coe_toDual_self (i : ι) : b.toDual (b i) = b.coord i := by
ext
apply toDual_apply_right
#align basis.coe_to_dual_self Basis.coe_toDual_self
/-- `h.toDual_flip v` is the linear map sending `w` to `h.toDual w v`. -/
def toDualFlip (m : M) : M →ₗ[R] R :=
b.toDual.flip m
#align basis.to_dual_flip Basis.toDualFlip
theorem toDualFlip_apply (m₁ m₂ : M) : b.toDualFlip m₁ m₂ = b.toDual m₂ m₁ :=
rfl
#align basis.to_dual_flip_apply Basis.toDualFlip_apply
theorem toDual_eq_repr (m : M) (i : ι) : b.toDual m (b i) = b.repr m i :=
b.toDual_apply_left m i
#align basis.to_dual_eq_repr Basis.toDual_eq_repr
theorem toDual_eq_equivFun [Finite ι] (m : M) (i : ι) : b.toDual m (b i) = b.equivFun m i := by
rw [b.equivFun_apply, toDual_eq_repr]
#align basis.to_dual_eq_equiv_fun Basis.toDual_eq_equivFun
theorem toDual_injective : Injective b.toDual := fun x y h ↦ b.ext_elem_iff.mpr fun i ↦ by
simp_rw [← toDual_eq_repr]; exact DFunLike.congr_fun h _
theorem toDual_inj (m : M) (a : b.toDual m = 0) : m = 0 :=
b.toDual_injective (by rwa [_root_.map_zero])
#align basis.to_dual_inj Basis.toDual_inj
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.ker
theorem toDual_ker : LinearMap.ker b.toDual = ⊥ :=
ker_eq_bot'.mpr b.toDual_inj
#align basis.to_dual_ker Basis.toDual_ker
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.range
theorem toDual_range [Finite ι] : LinearMap.range b.toDual = ⊤ := by
refine eq_top_iff'.2 fun f => ?_
let lin_comb : ι →₀ R := Finsupp.equivFunOnFinite.symm fun i => f (b i)
refine ⟨Finsupp.total ι M R b lin_comb, b.ext fun i => ?_⟩
rw [b.toDual_eq_repr _ i, repr_total b]
rfl
#align basis.to_dual_range Basis.toDual_range
end CommSemiring
section
variable [CommSemiring R] [AddCommMonoid M] [Module R M] [Fintype ι]
variable (b : Basis ι R M)
@[simp]
theorem sum_dual_apply_smul_coord (f : Module.Dual R M) :
(∑ x, f (b x) • b.coord x) = f := by
ext m
simp_rw [LinearMap.sum_apply, LinearMap.smul_apply, smul_eq_mul, mul_comm (f _), ← smul_eq_mul, ←
f.map_smul, ← _root_.map_sum, Basis.coord_apply, Basis.sum_repr]
#align basis.sum_dual_apply_smul_coord Basis.sum_dual_apply_smul_coord
end
section CommRing
variable [CommRing R] [AddCommGroup M] [Module R M] [DecidableEq ι]
variable (b : Basis ι R M)
section Finite
variable [Finite ι]
/-- A vector space is linearly equivalent to its dual space. -/
def toDualEquiv : M ≃ₗ[R] Dual R M :=
LinearEquiv.ofBijective b.toDual ⟨ker_eq_bot.mp b.toDual_ker, range_eq_top.mp b.toDual_range⟩
#align basis.to_dual_equiv Basis.toDualEquiv
-- `simps` times out when generating this
@[simp]
theorem toDualEquiv_apply (m : M) : b.toDualEquiv m = b.toDual m :=
rfl
#align basis.to_dual_equiv_apply Basis.toDualEquiv_apply
-- Not sure whether this is true for free modules over a commutative ring
/-- A vector space over a field is isomorphic to its dual if and only if it is finite-dimensional:
a consequence of the Erdős-Kaplansky theorem. -/
theorem linearEquiv_dual_iff_finiteDimensional [Field K] [AddCommGroup V] [Module K V] :
Nonempty (V ≃ₗ[K] Dual K V) ↔ FiniteDimensional K V := by
refine ⟨fun ⟨e⟩ ↦ ?_, fun h ↦ ⟨(Module.Free.chooseBasis K V).toDualEquiv⟩⟩
rw [FiniteDimensional, ← Module.rank_lt_alpeh0_iff]
by_contra!
apply (lift_rank_lt_rank_dual this).ne
have := e.lift_rank_eq
rwa [lift_umax.{uV,uK}, lift_id'.{uV,uK}] at this
/-- Maps a basis for `V` to a basis for the dual space. -/
def dualBasis : Basis ι R (Dual R M) :=
b.map b.toDualEquiv
#align basis.dual_basis Basis.dualBasis
-- We use `j = i` to match `Basis.repr_self`
theorem dualBasis_apply_self (i j : ι) : b.dualBasis i (b j) =
if j = i then 1 else 0 := by
convert b.toDual_apply i j using 2
rw [@eq_comm _ j i]
#align basis.dual_basis_apply_self Basis.dualBasis_apply_self
theorem total_dualBasis (f : ι →₀ R) (i : ι) :
Finsupp.total ι (Dual R M) R b.dualBasis f (b i) = f i := by
cases nonempty_fintype ι
rw [Finsupp.total_apply, Finsupp.sum_fintype, LinearMap.sum_apply]
· simp_rw [LinearMap.smul_apply, smul_eq_mul, dualBasis_apply_self, mul_boole,
Finset.sum_ite_eq, if_pos (Finset.mem_univ i)]
· intro
rw [zero_smul]
#align basis.total_dual_basis Basis.total_dualBasis
theorem dualBasis_repr (l : Dual R M) (i : ι) : b.dualBasis.repr l i = l (b i) := by
rw [← total_dualBasis b, Basis.total_repr b.dualBasis l]
#align basis.dual_basis_repr Basis.dualBasis_repr
theorem dualBasis_apply (i : ι) (m : M) : b.dualBasis i m = b.repr m i :=
b.toDual_apply_right i m
#align basis.dual_basis_apply Basis.dualBasis_apply
@[simp]
theorem coe_dualBasis : ⇑b.dualBasis = b.coord := by
ext i x
apply dualBasis_apply
#align basis.coe_dual_basis Basis.coe_dualBasis
@[simp]
theorem toDual_toDual : b.dualBasis.toDual.comp b.toDual = Dual.eval R M := by
refine b.ext fun i => b.dualBasis.ext fun j => ?_
rw [LinearMap.comp_apply, toDual_apply_left, coe_toDual_self, ← coe_dualBasis,
Dual.eval_apply, Basis.repr_self, Finsupp.single_apply, dualBasis_apply_self]
#align basis.to_dual_to_dual Basis.toDual_toDual
end Finite
theorem dualBasis_equivFun [Finite ι] (l : Dual R M) (i : ι) :
b.dualBasis.equivFun l i = l (b i) := by rw [Basis.equivFun_apply, dualBasis_repr]
#align basis.dual_basis_equiv_fun Basis.dualBasis_equivFun
theorem eval_ker {ι : Type*} (b : Basis ι R M) :
LinearMap.ker (Dual.eval R M) = ⊥ := by
rw [ker_eq_bot']
intro m hm
simp_rw [LinearMap.ext_iff, Dual.eval_apply, zero_apply] at hm
exact (Basis.forall_coord_eq_zero_iff _).mp fun i => hm (b.coord i)
#align basis.eval_ker Basis.eval_ker
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.range
theorem eval_range {ι : Type*} [Finite ι] (b : Basis ι R M) :
LinearMap.range (Dual.eval R M) = ⊤ := by
classical
cases nonempty_fintype ι
rw [← b.toDual_toDual, range_comp, b.toDual_range, Submodule.map_top, toDual_range _]
#align basis.eval_range Basis.eval_range
section
variable [Finite R M] [Free R M]
instance dual_free : Free R (Dual R M) :=
Free.of_basis (Free.chooseBasis R M).dualBasis
#align basis.dual_free Basis.dual_free
instance dual_finite : Finite R (Dual R M) :=
Finite.of_basis (Free.chooseBasis R M).dualBasis
#align basis.dual_finite Basis.dual_finite
end
end CommRing
/-- `simp` normal form version of `total_dualBasis` -/
@[simp]
theorem total_coord [CommRing R] [AddCommGroup M] [Module R M] [Finite ι] (b : Basis ι R M)
(f : ι →₀ R) (i : ι) : Finsupp.total ι (Dual R M) R b.coord f (b i) = f i := by
haveI := Classical.decEq ι
rw [← coe_dualBasis, total_dualBasis]
#align basis.total_coord Basis.total_coord
theorem dual_rank_eq [CommRing K] [AddCommGroup V] [Module K V] [Finite ι] (b : Basis ι K V) :
Cardinal.lift.{uK,uV} (Module.rank K V) = Module.rank K (Dual K V) := by
classical rw [← lift_umax.{uV,uK}, b.toDualEquiv.lift_rank_eq, lift_id'.{uV,uK}]
#align basis.dual_rank_eq Basis.dual_rank_eq
end Basis
namespace Module
universe uK uV
variable {K : Type uK} {V : Type uV}
variable [CommRing K] [AddCommGroup V] [Module K V] [Module.Free K V]
open Module Module.Dual Submodule LinearMap Cardinal Basis FiniteDimensional
section
variable (K) (V)
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.ker
theorem eval_ker : LinearMap.ker (eval K V) = ⊥ := by
classical exact (Module.Free.chooseBasis K V).eval_ker
#align module.eval_ker Module.eval_ker
theorem map_eval_injective : (Submodule.map (eval K V)).Injective := by
apply Submodule.map_injective_of_injective
rw [← LinearMap.ker_eq_bot]
exact eval_ker K V
#align module.map_eval_injective Module.map_eval_injective
theorem comap_eval_surjective : (Submodule.comap (eval K V)).Surjective := by
apply Submodule.comap_surjective_of_injective
rw [← LinearMap.ker_eq_bot]
exact eval_ker K V
#align module.comap_eval_surjective Module.comap_eval_surjective
end
section
variable (K)
theorem eval_apply_eq_zero_iff (v : V) : (eval K V) v = 0 ↔ v = 0 := by
simpa only using SetLike.ext_iff.mp (eval_ker K V) v
#align module.eval_apply_eq_zero_iff Module.eval_apply_eq_zero_iff
theorem eval_apply_injective : Function.Injective (eval K V) :=
(injective_iff_map_eq_zero' (eval K V)).mpr (eval_apply_eq_zero_iff K)
#align module.eval_apply_injective Module.eval_apply_injective
theorem forall_dual_apply_eq_zero_iff (v : V) : (∀ φ : Module.Dual K V, φ v = 0) ↔ v = 0 := by
rw [← eval_apply_eq_zero_iff K v, LinearMap.ext_iff]
rfl
#align module.forall_dual_apply_eq_zero_iff Module.forall_dual_apply_eq_zero_iff
@[simp]
theorem subsingleton_dual_iff :
Subsingleton (Dual K V) ↔ Subsingleton V := by
refine ⟨fun h ↦ ⟨fun v w ↦ ?_⟩, fun h ↦ ⟨fun f g ↦ ?_⟩⟩
· rw [← sub_eq_zero, ← forall_dual_apply_eq_zero_iff K (v - w)]
intros f
simp [Subsingleton.elim f 0]
· ext v
simp [Subsingleton.elim v 0]
instance instSubsingletonDual [Subsingleton V] : Subsingleton (Dual K V) :=
(subsingleton_dual_iff K).mp inferInstance
@[simp]
theorem nontrivial_dual_iff :
Nontrivial (Dual K V) ↔ Nontrivial V := by
rw [← not_iff_not, not_nontrivial_iff_subsingleton, not_nontrivial_iff_subsingleton,
subsingleton_dual_iff]
instance instNontrivialDual [Nontrivial V] : Nontrivial (Dual K V) :=
(nontrivial_dual_iff K).mpr inferInstance
theorem finite_dual_iff : Finite K (Dual K V) ↔ Finite K V := by
constructor <;> intro h
· obtain ⟨⟨ι, b⟩⟩ := Module.Free.exists_basis (R := K) (M := V)
nontriviality K
obtain ⟨⟨s, span_s⟩⟩ := h
classical
haveI := (b.linearIndependent.map' _ b.toDual_ker).finite_of_le_span_finite _ s ?_
· exact Finite.of_basis b
· rw [span_s]; apply le_top
· infer_instance
end
theorem dual_rank_eq [Module.Finite K V] :
Cardinal.lift.{uK,uV} (Module.rank K V) = Module.rank K (Dual K V) :=
(Module.Free.chooseBasis K V).dual_rank_eq
#align module.dual_rank_eq Module.dual_rank_eq
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.range
theorem erange_coe [Module.Finite K V] : LinearMap.range (eval K V) = ⊤ :=
(Module.Free.chooseBasis K V).eval_range
#align module.erange_coe Module.erange_coe
section IsReflexive
open Function
variable (R M N : Type*) [CommRing R] [AddCommGroup M] [AddCommGroup N] [Module R M] [Module R N]
/-- A reflexive module is one for which the natural map to its double dual is a bijection.
Any finitely-generated free module (and thus any finite-dimensional vector space) is reflexive.
See `Module.IsReflexive.of_finite_of_free`. -/
class IsReflexive : Prop where
/-- A reflexive module is one for which the natural map to its double dual is a bijection. -/
bijective_dual_eval' : Bijective (Dual.eval R M)
lemma bijective_dual_eval [IsReflexive R M] : Bijective (Dual.eval R M) :=
IsReflexive.bijective_dual_eval'
instance IsReflexive.of_finite_of_free [Finite R M] [Free R M] : IsReflexive R M where
bijective_dual_eval' := ⟨LinearMap.ker_eq_bot.mp (Free.chooseBasis R M).eval_ker,
LinearMap.range_eq_top.mp (Free.chooseBasis R M).eval_range⟩
variable [IsReflexive R M]
/-- The bijection between a reflexive module and its double dual, bundled as a `LinearEquiv`. -/
def evalEquiv : M ≃ₗ[R] Dual R (Dual R M) :=
LinearEquiv.ofBijective _ (bijective_dual_eval R M)
#align module.eval_equiv Module.evalEquiv
@[simp] lemma evalEquiv_toLinearMap : evalEquiv R M = Dual.eval R M := rfl
#align module.eval_equiv_to_linear_map Module.evalEquiv_toLinearMap
@[simp] lemma evalEquiv_apply (m : M) : evalEquiv R M m = Dual.eval R M m := rfl
@[simp] lemma apply_evalEquiv_symm_apply (f : Dual R M) (g : Dual R (Dual R M)) :
f ((evalEquiv R M).symm g) = g f := by
set m := (evalEquiv R M).symm g
rw [← (evalEquiv R M).apply_symm_apply g, evalEquiv_apply, Dual.eval_apply]
@[simp] lemma symm_dualMap_evalEquiv :
(evalEquiv R M).symm.dualMap = Dual.eval R (Dual R M) := by
ext; simp
/-- The dual of a reflexive module is reflexive. -/
instance Dual.instIsReflecive : IsReflexive R (Dual R M) :=
⟨by simpa only [← symm_dualMap_evalEquiv] using (evalEquiv R M).dualMap.symm.bijective⟩
/-- The isomorphism `Module.evalEquiv` induces an order isomorphism on subspaces. -/
def mapEvalEquiv : Submodule R M ≃o Submodule R (Dual R (Dual R M)) :=
Submodule.orderIsoMapComap (evalEquiv R M)
#align module.map_eval_equiv Module.mapEvalEquiv
@[simp]
theorem mapEvalEquiv_apply (W : Submodule R M) :
mapEvalEquiv R M W = W.map (Dual.eval R M) :=
rfl
#align module.map_eval_equiv_apply Module.mapEvalEquiv_apply
@[simp]
theorem mapEvalEquiv_symm_apply (W'' : Submodule R (Dual R (Dual R M))) :
(mapEvalEquiv R M).symm W'' = W''.comap (Dual.eval R M) :=
rfl
#align module.map_eval_equiv_symm_apply Module.mapEvalEquiv_symm_apply
instance _root_.Prod.instModuleIsReflexive [IsReflexive R N] :
IsReflexive R (M × N) where
bijective_dual_eval' := by
let e : Dual R (Dual R (M × N)) ≃ₗ[R] Dual R (Dual R M) × Dual R (Dual R N) :=
(dualProdDualEquivDual R M N).dualMap.trans
(dualProdDualEquivDual R (Dual R M) (Dual R N)).symm
have : Dual.eval R (M × N) = e.symm.comp ((Dual.eval R M).prodMap (Dual.eval R N)) := by
ext m f <;> simp [e]
simp only [this, LinearEquiv.trans_symm, LinearEquiv.symm_symm, LinearEquiv.dualMap_symm,
coe_comp, LinearEquiv.coe_coe, EquivLike.comp_bijective]
exact (bijective_dual_eval R M).prodMap (bijective_dual_eval R N)
variable {R M N} in
lemma equiv (e : M ≃ₗ[R] N) : IsReflexive R N where
bijective_dual_eval' := by
let ed : Dual R (Dual R N) ≃ₗ[R] Dual R (Dual R M) := e.symm.dualMap.dualMap
have : Dual.eval R N = ed.symm.comp ((Dual.eval R M).comp e.symm.toLinearMap) := by
ext m f
exact DFunLike.congr_arg f (e.apply_symm_apply m).symm
simp only [this, LinearEquiv.trans_symm, LinearEquiv.symm_symm, LinearEquiv.dualMap_symm,
coe_comp, LinearEquiv.coe_coe, EquivLike.comp_bijective]
exact Bijective.comp (bijective_dual_eval R M) (LinearEquiv.bijective _)
instance _root_.MulOpposite.instModuleIsReflexive : IsReflexive R (MulOpposite M) :=
equiv <| MulOpposite.opLinearEquiv _
instance _root_.ULift.instModuleIsReflexive.{w} : IsReflexive R (ULift.{w} M) :=
equiv ULift.moduleEquiv.symm
end IsReflexive
end Module
namespace Submodule
open Module
variable {R M : Type*} [CommRing R] [AddCommGroup M] [Module R M] {p : Submodule R M}
theorem exists_dual_map_eq_bot_of_nmem {x : M} (hx : x ∉ p) (hp' : Free R (M ⧸ p)) :
∃ f : Dual R M, f x ≠ 0 ∧ p.map f = ⊥ := by
suffices ∃ f : Dual R (M ⧸ p), f (p.mkQ x) ≠ 0 by
obtain ⟨f, hf⟩ := this; exact ⟨f.comp p.mkQ, hf, by simp [Submodule.map_comp]⟩
rwa [← Submodule.Quotient.mk_eq_zero, ← Submodule.mkQ_apply,
← forall_dual_apply_eq_zero_iff (K := R), not_forall] at hx
theorem exists_dual_map_eq_bot_of_lt_top (hp : p < ⊤) (hp' : Free R (M ⧸ p)) :
∃ f : Dual R M, f ≠ 0 ∧ p.map f = ⊥ := by
obtain ⟨x, hx⟩ : ∃ x : M, x ∉ p := by rw [lt_top_iff_ne_top] at hp; contrapose! hp; ext; simp [hp]
obtain ⟨f, hf, hf'⟩ := p.exists_dual_map_eq_bot_of_nmem hx hp'
exact ⟨f, by aesop, hf'⟩
end Submodule
section DualBases
open Module
variable {R M ι : Type*}
variable [CommSemiring R] [AddCommMonoid M] [Module R M] [DecidableEq ι]
-- Porting note: replace use_finite_instance tactic
open Lean.Elab.Tactic in
/-- Try using `Set.to_finite` to dispatch a `Set.finite` goal. -/
def evalUseFiniteInstance : TacticM Unit := do
evalTactic (← `(tactic| intros; apply Set.toFinite))
elab "use_finite_instance" : tactic => evalUseFiniteInstance
/-- `e` and `ε` have characteristic properties of a basis and its dual -/
-- @[nolint has_nonempty_instance] Porting note (#5171): removed
structure Module.DualBases (e : ι → M) (ε : ι → Dual R M) : Prop where
eval : ∀ i j : ι, ε i (e j) = if i = j then 1 else 0
protected total : ∀ {m : M}, (∀ i, ε i m = 0) → m = 0
protected finite : ∀ m : M, { i | ε i m ≠ 0 }.Finite := by
use_finite_instance
#align module.dual_bases Module.DualBases
end DualBases
namespace Module.DualBases
open Module Module.Dual LinearMap Function
variable {R M ι : Type*}
variable [CommRing R] [AddCommGroup M] [Module R M]
variable {e : ι → M} {ε : ι → Dual R M}
/-- The coefficients of `v` on the basis `e` -/
def coeffs [DecidableEq ι] (h : DualBases e ε) (m : M) : ι →₀ R where
toFun i := ε i m
support := (h.finite m).toFinset
mem_support_toFun i := by rw [Set.Finite.mem_toFinset, Set.mem_setOf_eq]
#align module.dual_bases.coeffs Module.DualBases.coeffs
@[simp]
theorem coeffs_apply [DecidableEq ι] (h : DualBases e ε) (m : M) (i : ι) : h.coeffs m i = ε i m :=
rfl
#align module.dual_bases.coeffs_apply Module.DualBases.coeffs_apply
/-- linear combinations of elements of `e`.
This is a convenient abbreviation for `Finsupp.total _ M R e l` -/
def lc {ι} (e : ι → M) (l : ι →₀ R) : M :=
l.sum fun (i : ι) (a : R) => a • e i
#align module.dual_bases.lc Module.DualBases.lc
theorem lc_def (e : ι → M) (l : ι →₀ R) : lc e l = Finsupp.total _ _ R e l :=
rfl
#align module.dual_bases.lc_def Module.DualBases.lc_def
open Module
variable [DecidableEq ι] (h : DualBases e ε)
theorem dual_lc (l : ι →₀ R) (i : ι) : ε i (DualBases.lc e l) = l i := by
rw [lc, _root_.map_finsupp_sum, Finsupp.sum_eq_single i (g := fun a b ↦ (ε i) (b • e a))]
-- Porting note: cannot get at •
-- simp only [h.eval, map_smul, smul_eq_mul]
· simp [h.eval, smul_eq_mul]
· intro q _ q_ne
simp [q_ne.symm, h.eval, smul_eq_mul]
· simp
#align module.dual_bases.dual_lc Module.DualBases.dual_lc
@[simp]
theorem coeffs_lc (l : ι →₀ R) : h.coeffs (DualBases.lc e l) = l := by
ext i
rw [h.coeffs_apply, h.dual_lc]
#align module.dual_bases.coeffs_lc Module.DualBases.coeffs_lc
/-- For any m : M n, \sum_{p ∈ Q n} (ε p m) • e p = m -/
@[simp]
theorem lc_coeffs (m : M) : DualBases.lc e (h.coeffs m) = m := by
refine eq_of_sub_eq_zero <| h.total fun i ↦ ?_
simp [LinearMap.map_sub, h.dual_lc, sub_eq_zero]
#align module.dual_bases.lc_coeffs Module.DualBases.lc_coeffs
/-- `(h : DualBases e ε).basis` shows the family of vectors `e` forms a basis. -/
@[simps]
def basis : Basis ι R M :=
Basis.ofRepr
{ toFun := coeffs h
invFun := lc e
left_inv := lc_coeffs h
right_inv := coeffs_lc h
map_add' := fun v w => by
ext i
exact (ε i).map_add v w
map_smul' := fun c v => by
ext i
exact (ε i).map_smul c v }
#align module.dual_bases.basis Module.DualBases.basis
-- Porting note: from simpNF the LHS simplifies; it yields lc_def.symm
-- probably not a useful simp lemma; nolint simpNF since it cannot see this removal
attribute [-simp, nolint simpNF] basis_repr_symm_apply
@[simp]
theorem coe_basis : ⇑h.basis = e := by
ext i
rw [Basis.apply_eq_iff]
ext j
rw [h.basis_repr_apply, coeffs_apply, h.eval, Finsupp.single_apply]
convert if_congr (eq_comm (a := j) (b := i)) rfl rfl
#align module.dual_bases.coe_basis Module.DualBases.coe_basis
-- `convert` to get rid of a `DecidableEq` mismatch
theorem mem_of_mem_span {H : Set ι} {x : M} (hmem : x ∈ Submodule.span R (e '' H)) :
∀ i : ι, ε i x ≠ 0 → i ∈ H := by
intro i hi
rcases (Finsupp.mem_span_image_iff_total _).mp hmem with ⟨l, supp_l, rfl⟩
apply not_imp_comm.mp ((Finsupp.mem_supported' _ _).mp supp_l i)
rwa [← lc_def, h.dual_lc] at hi
#align module.dual_bases.mem_of_mem_span Module.DualBases.mem_of_mem_span
theorem coe_dualBasis [_root_.Finite ι] : ⇑h.basis.dualBasis = ε :=
funext fun i =>
h.basis.ext fun j => by
rw [h.basis.dualBasis_apply_self, h.coe_basis, h.eval, if_congr eq_comm rfl rfl]
#align module.dual_bases.coe_dual_basis Module.DualBases.coe_dualBasis
end Module.DualBases
namespace Submodule
universe u v w
variable {R : Type u} {M : Type v} [CommSemiring R] [AddCommMonoid M] [Module R M]
variable {W : Submodule R M}
/-- The `dualRestrict` of a submodule `W` of `M` is the linear map from the
dual of `M` to the dual of `W` such that the domain of each linear map is
restricted to `W`. -/
def dualRestrict (W : Submodule R M) : Module.Dual R M →ₗ[R] Module.Dual R W :=
LinearMap.domRestrict' W
#align submodule.dual_restrict Submodule.dualRestrict
theorem dualRestrict_def (W : Submodule R M) : W.dualRestrict = W.subtype.dualMap :=
rfl
#align submodule.dual_restrict_def Submodule.dualRestrict_def
@[simp]
theorem dualRestrict_apply (W : Submodule R M) (φ : Module.Dual R M) (x : W) :
W.dualRestrict φ x = φ (x : M) :=
rfl
#align submodule.dual_restrict_apply Submodule.dualRestrict_apply
/-- The `dualAnnihilator` of a submodule `W` is the set of linear maps `φ` such
that `φ w = 0` for all `w ∈ W`. -/
def dualAnnihilator {R : Type u} {M : Type v} [CommSemiring R] [AddCommMonoid M] [Module R M]
(W : Submodule R M) : Submodule R <| Module.Dual R M :=
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.ker
LinearMap.ker W.dualRestrict
#align submodule.dual_annihilator Submodule.dualAnnihilator
@[simp]
theorem mem_dualAnnihilator (φ : Module.Dual R M) : φ ∈ W.dualAnnihilator ↔ ∀ w ∈ W, φ w = 0 := by
refine LinearMap.mem_ker.trans ?_
simp_rw [LinearMap.ext_iff, dualRestrict_apply]
exact ⟨fun h w hw => h ⟨w, hw⟩, fun h w => h w.1 w.2⟩
#align submodule.mem_dual_annihilator Submodule.mem_dualAnnihilator
/-- That $\operatorname{ker}(\iota^* : V^* \to W^*) = \operatorname{ann}(W)$.
This is the definition of the dual annihilator of the submodule $W$. -/
theorem dualRestrict_ker_eq_dualAnnihilator (W : Submodule R M) :
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.ker
LinearMap.ker W.dualRestrict = W.dualAnnihilator :=
rfl
#align submodule.dual_restrict_ker_eq_dual_annihilator Submodule.dualRestrict_ker_eq_dualAnnihilator
/-- The `dualAnnihilator` of a submodule of the dual space pulled back along the evaluation map
`Module.Dual.eval`. -/
def dualCoannihilator (Φ : Submodule R (Module.Dual R M)) : Submodule R M :=
Φ.dualAnnihilator.comap (Module.Dual.eval R M)
#align submodule.dual_coannihilator Submodule.dualCoannihilator
@[simp]
theorem mem_dualCoannihilator {Φ : Submodule R (Module.Dual R M)} (x : M) :
x ∈ Φ.dualCoannihilator ↔ ∀ φ ∈ Φ, (φ x : R) = 0 := by
simp_rw [dualCoannihilator, mem_comap, mem_dualAnnihilator, Module.Dual.eval_apply]
#align submodule.mem_dual_coannihilator Submodule.mem_dualCoannihilator
theorem comap_dualAnnihilator (Φ : Submodule R (Module.Dual R M)) :
Φ.dualAnnihilator.comap (Module.Dual.eval R M) = Φ.dualCoannihilator := rfl
theorem map_dualCoannihilator_le (Φ : Submodule R (Module.Dual R M)) :
Φ.dualCoannihilator.map (Module.Dual.eval R M) ≤ Φ.dualAnnihilator :=
map_le_iff_le_comap.mpr (comap_dualAnnihilator Φ).le
variable (R M) in
theorem dualAnnihilator_gc :
GaloisConnection
(OrderDual.toDual ∘ (dualAnnihilator : Submodule R M → Submodule R (Module.Dual R M)))
(dualCoannihilator ∘ OrderDual.ofDual) := by
intro a b
induction b using OrderDual.rec
simp only [Function.comp_apply, OrderDual.toDual_le_toDual, OrderDual.ofDual_toDual]
constructor <;>
· intro h x hx
simp only [mem_dualAnnihilator, mem_dualCoannihilator]
intro y hy
have := h hy
simp only [mem_dualAnnihilator, mem_dualCoannihilator] at this
exact this x hx
#align submodule.dual_annihilator_gc Submodule.dualAnnihilator_gc
theorem le_dualAnnihilator_iff_le_dualCoannihilator {U : Submodule R (Module.Dual R M)}
{V : Submodule R M} : U ≤ V.dualAnnihilator ↔ V ≤ U.dualCoannihilator :=
(dualAnnihilator_gc R M).le_iff_le
#align submodule.le_dual_annihilator_iff_le_dual_coannihilator Submodule.le_dualAnnihilator_iff_le_dualCoannihilator
@[simp]
theorem dualAnnihilator_bot : (⊥ : Submodule R M).dualAnnihilator = ⊤ :=
(dualAnnihilator_gc R M).l_bot
#align submodule.dual_annihilator_bot Submodule.dualAnnihilator_bot
@[simp]
theorem dualAnnihilator_top : (⊤ : Submodule R M).dualAnnihilator = ⊥ := by
rw [eq_bot_iff]
intro v
simp_rw [mem_dualAnnihilator, mem_bot, mem_top, forall_true_left]
exact fun h => LinearMap.ext h
#align submodule.dual_annihilator_top Submodule.dualAnnihilator_top
@[simp]
theorem dualCoannihilator_bot : (⊥ : Submodule R (Module.Dual R M)).dualCoannihilator = ⊤ :=
(dualAnnihilator_gc R M).u_top
#align submodule.dual_coannihilator_bot Submodule.dualCoannihilator_bot
@[mono]
theorem dualAnnihilator_anti {U V : Submodule R M} (hUV : U ≤ V) :
V.dualAnnihilator ≤ U.dualAnnihilator :=
(dualAnnihilator_gc R M).monotone_l hUV
#align submodule.dual_annihilator_anti Submodule.dualAnnihilator_anti
@[mono]
theorem dualCoannihilator_anti {U V : Submodule R (Module.Dual R M)} (hUV : U ≤ V) :
V.dualCoannihilator ≤ U.dualCoannihilator :=
(dualAnnihilator_gc R M).monotone_u hUV
#align submodule.dual_coannihilator_anti Submodule.dualCoannihilator_anti
theorem le_dualAnnihilator_dualCoannihilator (U : Submodule R M) :
U ≤ U.dualAnnihilator.dualCoannihilator :=
(dualAnnihilator_gc R M).le_u_l U
#align submodule.le_dual_annihilator_dual_coannihilator Submodule.le_dualAnnihilator_dualCoannihilator
theorem le_dualCoannihilator_dualAnnihilator (U : Submodule R (Module.Dual R M)) :
U ≤ U.dualCoannihilator.dualAnnihilator :=
(dualAnnihilator_gc R M).l_u_le U
#align submodule.le_dual_coannihilator_dual_annihilator Submodule.le_dualCoannihilator_dualAnnihilator
theorem dualAnnihilator_dualCoannihilator_dualAnnihilator (U : Submodule R M) :
U.dualAnnihilator.dualCoannihilator.dualAnnihilator = U.dualAnnihilator :=
(dualAnnihilator_gc R M).l_u_l_eq_l U
#align submodule.dual_annihilator_dual_coannihilator_dual_annihilator Submodule.dualAnnihilator_dualCoannihilator_dualAnnihilator
theorem dualCoannihilator_dualAnnihilator_dualCoannihilator (U : Submodule R (Module.Dual R M)) :
U.dualCoannihilator.dualAnnihilator.dualCoannihilator = U.dualCoannihilator :=
(dualAnnihilator_gc R M).u_l_u_eq_u U
#align submodule.dual_coannihilator_dual_annihilator_dual_coannihilator Submodule.dualCoannihilator_dualAnnihilator_dualCoannihilator
theorem dualAnnihilator_sup_eq (U V : Submodule R M) :
(U ⊔ V).dualAnnihilator = U.dualAnnihilator ⊓ V.dualAnnihilator :=
(dualAnnihilator_gc R M).l_sup
#align submodule.dual_annihilator_sup_eq Submodule.dualAnnihilator_sup_eq
theorem dualCoannihilator_sup_eq (U V : Submodule R (Module.Dual R M)) :
(U ⊔ V).dualCoannihilator = U.dualCoannihilator ⊓ V.dualCoannihilator :=
(dualAnnihilator_gc R M).u_inf
#align submodule.dual_coannihilator_sup_eq Submodule.dualCoannihilator_sup_eq
theorem dualAnnihilator_iSup_eq {ι : Sort*} (U : ι → Submodule R M) :
(⨆ i : ι, U i).dualAnnihilator = ⨅ i : ι, (U i).dualAnnihilator :=
(dualAnnihilator_gc R M).l_iSup
#align submodule.dual_annihilator_supr_eq Submodule.dualAnnihilator_iSup_eq
theorem dualCoannihilator_iSup_eq {ι : Sort*} (U : ι → Submodule R (Module.Dual R M)) :
(⨆ i : ι, U i).dualCoannihilator = ⨅ i : ι, (U i).dualCoannihilator :=
(dualAnnihilator_gc R M).u_iInf
#align submodule.dual_coannihilator_supr_eq Submodule.dualCoannihilator_iSup_eq
/-- See also `Subspace.dualAnnihilator_inf_eq` for vector subspaces. -/
theorem sup_dualAnnihilator_le_inf (U V : Submodule R M) :
U.dualAnnihilator ⊔ V.dualAnnihilator ≤ (U ⊓ V).dualAnnihilator := by
rw [le_dualAnnihilator_iff_le_dualCoannihilator, dualCoannihilator_sup_eq]
apply inf_le_inf <;> exact le_dualAnnihilator_dualCoannihilator _
#align submodule.sup_dual_annihilator_le_inf Submodule.sup_dualAnnihilator_le_inf
/-- See also `Subspace.dualAnnihilator_iInf_eq` for vector subspaces when `ι` is finite. -/
theorem iSup_dualAnnihilator_le_iInf {ι : Sort*} (U : ι → Submodule R M) :
⨆ i : ι, (U i).dualAnnihilator ≤ (⨅ i : ι, U i).dualAnnihilator := by
rw [le_dualAnnihilator_iff_le_dualCoannihilator, dualCoannihilator_iSup_eq]
apply iInf_mono
exact fun i : ι => le_dualAnnihilator_dualCoannihilator (U i)
#align submodule.supr_dual_annihilator_le_infi Submodule.iSup_dualAnnihilator_le_iInf
end Submodule
namespace Subspace
open Submodule LinearMap
universe u v w
-- We work in vector spaces because `exists_is_compl` only hold for vector spaces
variable {K : Type u} {V : Type v} [Field K] [AddCommGroup V] [Module K V]
@[simp]
theorem dualCoannihilator_top (W : Subspace K V) :
(⊤ : Subspace K (Module.Dual K W)).dualCoannihilator = ⊥ := by
rw [dualCoannihilator, dualAnnihilator_top, comap_bot, Module.eval_ker]
#align subspace.dual_coannihilator_top Subspace.dualCoannihilator_top
@[simp]
theorem dualAnnihilator_dualCoannihilator_eq {W : Subspace K V} :
W.dualAnnihilator.dualCoannihilator = W := by
refine le_antisymm (fun v ↦ Function.mtr ?_) (le_dualAnnihilator_dualCoannihilator _)
simp only [mem_dualAnnihilator, mem_dualCoannihilator]
rw [← Quotient.mk_eq_zero W, ← Module.forall_dual_apply_eq_zero_iff K]
push_neg
refine fun ⟨φ, hφ⟩ ↦ ⟨φ.comp W.mkQ, fun w hw ↦ ?_, hφ⟩
rw [comp_apply, mkQ_apply, (Quotient.mk_eq_zero W).mpr hw, φ.map_zero]
#align subspace.dual_annihilator_dual_coannihilator_eq Subspace.dualAnnihilator_dualCoannihilator_eq
-- exact elaborates slowly
theorem forall_mem_dualAnnihilator_apply_eq_zero_iff (W : Subspace K V) (v : V) :
(∀ φ : Module.Dual K V, φ ∈ W.dualAnnihilator → φ v = 0) ↔ v ∈ W := by
rw [← SetLike.ext_iff.mp dualAnnihilator_dualCoannihilator_eq v, mem_dualCoannihilator]
#align subspace.forall_mem_dual_annihilator_apply_eq_zero_iff Subspace.forall_mem_dualAnnihilator_apply_eq_zero_iff
theorem comap_dualAnnihilator_dualAnnihilator (W : Subspace K V) :
W.dualAnnihilator.dualAnnihilator.comap (Module.Dual.eval K V) = W := by
ext; rw [Iff.comm, ← forall_mem_dualAnnihilator_apply_eq_zero_iff]; simp
theorem map_le_dualAnnihilator_dualAnnihilator (W : Subspace K V) :
W.map (Module.Dual.eval K V) ≤ W.dualAnnihilator.dualAnnihilator :=
map_le_iff_le_comap.mpr (comap_dualAnnihilator_dualAnnihilator W).ge
/-- `Submodule.dualAnnihilator` and `Submodule.dualCoannihilator` form a Galois coinsertion. -/
def dualAnnihilatorGci (K V : Type*) [Field K] [AddCommGroup V] [Module K V] :
GaloisCoinsertion
(OrderDual.toDual ∘ (dualAnnihilator : Subspace K V → Subspace K (Module.Dual K V)))
(dualCoannihilator ∘ OrderDual.ofDual) where
choice W _ := dualCoannihilator W
gc := dualAnnihilator_gc K V
u_l_le _ := dualAnnihilator_dualCoannihilator_eq.le
choice_eq _ _ := rfl
#align subspace.dual_annihilator_gci Subspace.dualAnnihilatorGci
theorem dualAnnihilator_le_dualAnnihilator_iff {W W' : Subspace K V} :
W.dualAnnihilator ≤ W'.dualAnnihilator ↔ W' ≤ W :=
(dualAnnihilatorGci K V).l_le_l_iff
#align subspace.dual_annihilator_le_dual_annihilator_iff Subspace.dualAnnihilator_le_dualAnnihilator_iff
theorem dualAnnihilator_inj {W W' : Subspace K V} :
W.dualAnnihilator = W'.dualAnnihilator ↔ W = W' :=
⟨fun h ↦ (dualAnnihilatorGci K V).l_injective h, congr_arg _⟩
#align subspace.dual_annihilator_inj Subspace.dualAnnihilator_inj
/-- Given a subspace `W` of `V` and an element of its dual `φ`, `dualLift W φ` is
an arbitrary extension of `φ` to an element of the dual of `V`.
That is, `dualLift W φ` sends `w ∈ W` to `φ x` and `x` in a chosen complement of `W` to `0`. -/
noncomputable def dualLift (W : Subspace K V) : Module.Dual K W →ₗ[K] Module.Dual K V :=
(Classical.choose <| W.subtype.exists_leftInverse_of_injective W.ker_subtype).dualMap
#align subspace.dual_lift Subspace.dualLift
variable {W : Subspace K V}
@[simp]
theorem dualLift_of_subtype {φ : Module.Dual K W} (w : W) : W.dualLift φ (w : V) = φ w :=
congr_arg φ <| DFunLike.congr_fun
(Classical.choose_spec <| W.subtype.exists_leftInverse_of_injective W.ker_subtype) w
#align subspace.dual_lift_of_subtype Subspace.dualLift_of_subtype
theorem dualLift_of_mem {φ : Module.Dual K W} {w : V} (hw : w ∈ W) : W.dualLift φ w = φ ⟨w, hw⟩ :=
dualLift_of_subtype ⟨w, hw⟩
#align subspace.dual_lift_of_mem Subspace.dualLift_of_mem
@[simp]
theorem dualRestrict_comp_dualLift (W : Subspace K V) : W.dualRestrict.comp W.dualLift = 1 := by
ext φ x
simp
#align subspace.dual_restrict_comp_dual_lift Subspace.dualRestrict_comp_dualLift
theorem dualRestrict_leftInverse (W : Subspace K V) :
Function.LeftInverse W.dualRestrict W.dualLift := fun x =>
show W.dualRestrict.comp W.dualLift x = x by
rw [dualRestrict_comp_dualLift]
rfl
#align subspace.dual_restrict_left_inverse Subspace.dualRestrict_leftInverse
theorem dualLift_rightInverse (W : Subspace K V) :
Function.RightInverse W.dualLift W.dualRestrict :=
W.dualRestrict_leftInverse
#align subspace.dual_lift_right_inverse Subspace.dualLift_rightInverse
theorem dualRestrict_surjective : Function.Surjective W.dualRestrict :=
W.dualLift_rightInverse.surjective
#align subspace.dual_restrict_surjective Subspace.dualRestrict_surjective
theorem dualLift_injective : Function.Injective W.dualLift :=
W.dualRestrict_leftInverse.injective
#align subspace.dual_lift_injective Subspace.dualLift_injective
/-- The quotient by the `dualAnnihilator` of a subspace is isomorphic to the
dual of that subspace. -/
noncomputable def quotAnnihilatorEquiv (W : Subspace K V) :
(Module.Dual K V ⧸ W.dualAnnihilator) ≃ₗ[K] Module.Dual K W :=
(quotEquivOfEq _ _ W.dualRestrict_ker_eq_dualAnnihilator).symm.trans <|
W.dualRestrict.quotKerEquivOfSurjective dualRestrict_surjective
#align subspace.quot_annihilator_equiv Subspace.quotAnnihilatorEquiv
@[simp]
theorem quotAnnihilatorEquiv_apply (W : Subspace K V) (φ : Module.Dual K V) :
W.quotAnnihilatorEquiv (Submodule.Quotient.mk φ) = W.dualRestrict φ := by
ext
rfl
#align subspace.quot_annihilator_equiv_apply Subspace.quotAnnihilatorEquiv_apply
/-- The natural isomorphism from the dual of a subspace `W` to `W.dualLift.range`. -/
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.range
noncomputable def dualEquivDual (W : Subspace K V) :
Module.Dual K W ≃ₗ[K] LinearMap.range W.dualLift :=
LinearEquiv.ofInjective _ dualLift_injective
#align subspace.dual_equiv_dual Subspace.dualEquivDual
theorem dualEquivDual_def (W : Subspace K V) :
W.dualEquivDual.toLinearMap = W.dualLift.rangeRestrict :=
rfl
#align subspace.dual_equiv_dual_def Subspace.dualEquivDual_def
@[simp]
theorem dualEquivDual_apply (φ : Module.Dual K W) :
W.dualEquivDual φ = ⟨W.dualLift φ, mem_range.2 ⟨φ, rfl⟩⟩ :=
rfl
#align subspace.dual_equiv_dual_apply Subspace.dualEquivDual_apply
section
open FiniteDimensional
instance instModuleDualFiniteDimensional [FiniteDimensional K V] :
FiniteDimensional K (Module.Dual K V) := by
infer_instance
#align subspace.module.dual.finite_dimensional Subspace.instModuleDualFiniteDimensional
@[simp]
theorem dual_finrank_eq : finrank K (Module.Dual K V) = finrank K V := by
by_cases h : FiniteDimensional K V
· classical exact LinearEquiv.finrank_eq (Basis.ofVectorSpace K V).toDualEquiv.symm
rw [finrank_eq_zero_of_basis_imp_false, finrank_eq_zero_of_basis_imp_false]
· exact fun _ b ↦ h (Module.Finite.of_basis b)
· exact fun _ b ↦ h ((Module.finite_dual_iff K).mp <| Module.Finite.of_basis b)
#align subspace.dual_finrank_eq Subspace.dual_finrank_eq
variable [FiniteDimensional K V]
theorem dualAnnihilator_dualAnnihilator_eq (W : Subspace K V) :
W.dualAnnihilator.dualAnnihilator = Module.mapEvalEquiv K V W := by
have : _ = W := Subspace.dualAnnihilator_dualCoannihilator_eq
rw [dualCoannihilator, ← Module.mapEvalEquiv_symm_apply] at this
rwa [← OrderIso.symm_apply_eq]
#align subspace.dual_annihilator_dual_annihilator_eq Subspace.dualAnnihilator_dualAnnihilator_eq
/-- The quotient by the dual is isomorphic to its dual annihilator. -/
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.range
noncomputable def quotDualEquivAnnihilator (W : Subspace K V) :
(Module.Dual K V ⧸ LinearMap.range W.dualLift) ≃ₗ[K] W.dualAnnihilator :=
LinearEquiv.quotEquivOfQuotEquiv <| LinearEquiv.trans W.quotAnnihilatorEquiv W.dualEquivDual
#align subspace.quot_dual_equiv_annihilator Subspace.quotDualEquivAnnihilator
open scoped Classical in
/-- The quotient by a subspace is isomorphic to its dual annihilator. -/
noncomputable def quotEquivAnnihilator (W : Subspace K V) : (V ⧸ W) ≃ₗ[K] W.dualAnnihilator :=
let φ := (Basis.ofVectorSpace K W).toDualEquiv.trans W.dualEquivDual
let ψ := LinearEquiv.quotEquivOfEquiv φ (Basis.ofVectorSpace K V).toDualEquiv
ψ ≪≫ₗ W.quotDualEquivAnnihilator
-- Porting note: this prevents the timeout; ML3 proof preserved below
-- refine' _ ≪≫ₗ W.quotDualEquivAnnihilator
-- refine' LinearEquiv.quot_equiv_of_equiv _ (Basis.ofVectorSpace K V).toDualEquiv
-- exact (Basis.ofVectorSpace K W).toDualEquiv.trans W.dual_equiv_dual
#align subspace.quot_equiv_annihilator Subspace.quotEquivAnnihilator
open FiniteDimensional
@[simp]
theorem finrank_dualCoannihilator_eq {Φ : Subspace K (Module.Dual K V)} :
finrank K Φ.dualCoannihilator = finrank K Φ.dualAnnihilator := by
rw [Submodule.dualCoannihilator, ← Module.evalEquiv_toLinearMap]
exact LinearEquiv.finrank_eq (LinearEquiv.ofSubmodule' _ _)
#align subspace.finrank_dual_coannihilator_eq Subspace.finrank_dualCoannihilator_eq
theorem finrank_add_finrank_dualCoannihilator_eq (W : Subspace K (Module.Dual K V)) :
finrank K W + finrank K W.dualCoannihilator = finrank K V := by
rw [finrank_dualCoannihilator_eq]
-- Porting note: LinearEquiv.finrank_eq needs help
let equiv := W.quotEquivAnnihilator
have eq := LinearEquiv.finrank_eq (R := K) (M := (Module.Dual K V) ⧸ W)
(M₂ := { x // x ∈ dualAnnihilator W }) equiv
rw [eq.symm, add_comm, Submodule.finrank_quotient_add_finrank, Subspace.dual_finrank_eq]
#align subspace.finrank_add_finrank_dual_coannihilator_eq Subspace.finrank_add_finrank_dualCoannihilator_eq
end
end Subspace
open Module
namespace LinearMap
universe uR uM₁ uM₂
variable {R : Type uR} [CommSemiring R] {M₁ : Type uM₁} {M₂ : Type uM₂}
variable [AddCommMonoid M₁] [Module R M₁] [AddCommMonoid M₂] [Module R M₂]
variable (f : M₁ →ₗ[R] M₂)
-- Porting note (#11036): broken dot notation lean4#1910 LinearMap.ker
| Mathlib/LinearAlgebra/Dual.lean | 1,257 | 1,262 | theorem ker_dualMap_eq_dualAnnihilator_range :
LinearMap.ker f.dualMap = f.range.dualAnnihilator := by |
ext
simp_rw [mem_ker, ext_iff, Submodule.mem_dualAnnihilator,
← SetLike.mem_coe, range_coe, Set.forall_mem_range]
rfl
|
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Kenny Lau, Johan Commelin, Mario Carneiro, Kevin Buzzard,
Amelia Livingston, Yury Kudryashov
-/
import Mathlib.Algebra.Group.Submonoid.Basic
import Mathlib.Algebra.Group.Subsemigroup.Operations
import Mathlib.Algebra.Group.Nat
import Mathlib.GroupTheory.GroupAction.Defs
#align_import group_theory.submonoid.operations from "leanprover-community/mathlib"@"cf8e77c636317b059a8ce20807a29cf3772a0640"
/-!
# Operations on `Submonoid`s
In this file we define various operations on `Submonoid`s and `MonoidHom`s.
## Main definitions
### Conversion between multiplicative and additive definitions
* `Submonoid.toAddSubmonoid`, `Submonoid.toAddSubmonoid'`, `AddSubmonoid.toSubmonoid`,
`AddSubmonoid.toSubmonoid'`: convert between multiplicative and additive submonoids of `M`,
`Multiplicative M`, and `Additive M`. These are stated as `OrderIso`s.
### (Commutative) monoid structure on a submonoid
* `Submonoid.toMonoid`, `Submonoid.toCommMonoid`: a submonoid inherits a (commutative) monoid
structure.
### Group actions by submonoids
* `Submonoid.MulAction`, `Submonoid.DistribMulAction`: a submonoid inherits (distributive)
multiplicative actions.
### Operations on submonoids
* `Submonoid.comap`: preimage of a submonoid under a monoid homomorphism as a submonoid of the
domain;
* `Submonoid.map`: image of a submonoid under a monoid homomorphism as a submonoid of the codomain;
* `Submonoid.prod`: product of two submonoids `s : Submonoid M` and `t : Submonoid N` as a submonoid
of `M × N`;
### Monoid homomorphisms between submonoid
* `Submonoid.subtype`: embedding of a submonoid into the ambient monoid.
* `Submonoid.inclusion`: given two submonoids `S`, `T` such that `S ≤ T`, `S.inclusion T` is the
inclusion of `S` into `T` as a monoid homomorphism;
* `MulEquiv.submonoidCongr`: converts a proof of `S = T` into a monoid isomorphism between `S`
and `T`.
* `Submonoid.prodEquiv`: monoid isomorphism between `s.prod t` and `s × t`;
### Operations on `MonoidHom`s
* `MonoidHom.mrange`: range of a monoid homomorphism as a submonoid of the codomain;
* `MonoidHom.mker`: kernel of a monoid homomorphism as a submonoid of the domain;
* `MonoidHom.restrict`: restrict a monoid homomorphism to a submonoid;
* `MonoidHom.codRestrict`: restrict the codomain of a monoid homomorphism to a submonoid;
* `MonoidHom.mrangeRestrict`: restrict a monoid homomorphism to its range;
## Tags
submonoid, range, product, map, comap
-/
assert_not_exists MonoidWithZero
variable {M N P : Type*} [MulOneClass M] [MulOneClass N] [MulOneClass P] (S : Submonoid M)
/-!
### Conversion to/from `Additive`/`Multiplicative`
-/
section
/-- Submonoids of monoid `M` are isomorphic to additive submonoids of `Additive M`. -/
@[simps]
def Submonoid.toAddSubmonoid : Submonoid M ≃o AddSubmonoid (Additive M) where
toFun S :=
{ carrier := Additive.toMul ⁻¹' S
zero_mem' := S.one_mem'
add_mem' := fun ha hb => S.mul_mem' ha hb }
invFun S :=
{ carrier := Additive.ofMul ⁻¹' S
one_mem' := S.zero_mem'
mul_mem' := fun ha hb => S.add_mem' ha hb}
left_inv x := by cases x; rfl
right_inv x := by cases x; rfl
map_rel_iff' := Iff.rfl
#align submonoid.to_add_submonoid Submonoid.toAddSubmonoid
#align submonoid.to_add_submonoid_symm_apply_coe Submonoid.toAddSubmonoid_symm_apply_coe
#align submonoid.to_add_submonoid_apply_coe Submonoid.toAddSubmonoid_apply_coe
/-- Additive submonoids of an additive monoid `Additive M` are isomorphic to submonoids of `M`. -/
abbrev AddSubmonoid.toSubmonoid' : AddSubmonoid (Additive M) ≃o Submonoid M :=
Submonoid.toAddSubmonoid.symm
#align add_submonoid.to_submonoid' AddSubmonoid.toSubmonoid'
theorem Submonoid.toAddSubmonoid_closure (S : Set M) :
Submonoid.toAddSubmonoid (Submonoid.closure S)
= AddSubmonoid.closure (Additive.toMul ⁻¹' S) :=
le_antisymm
(Submonoid.toAddSubmonoid.le_symm_apply.1 <|
Submonoid.closure_le.2 (AddSubmonoid.subset_closure (M := Additive M)))
(AddSubmonoid.closure_le.2 <| Submonoid.subset_closure (M := M))
#align submonoid.to_add_submonoid_closure Submonoid.toAddSubmonoid_closure
theorem AddSubmonoid.toSubmonoid'_closure (S : Set (Additive M)) :
AddSubmonoid.toSubmonoid' (AddSubmonoid.closure S)
= Submonoid.closure (Multiplicative.ofAdd ⁻¹' S) :=
le_antisymm
(AddSubmonoid.toSubmonoid'.le_symm_apply.1 <|
AddSubmonoid.closure_le.2 (Submonoid.subset_closure (M := M)))
(Submonoid.closure_le.2 <| AddSubmonoid.subset_closure (M := Additive M))
#align add_submonoid.to_submonoid'_closure AddSubmonoid.toSubmonoid'_closure
end
section
variable {A : Type*} [AddZeroClass A]
/-- Additive submonoids of an additive monoid `A` are isomorphic to
multiplicative submonoids of `Multiplicative A`. -/
@[simps]
def AddSubmonoid.toSubmonoid : AddSubmonoid A ≃o Submonoid (Multiplicative A) where
toFun S :=
{ carrier := Multiplicative.toAdd ⁻¹' S
one_mem' := S.zero_mem'
mul_mem' := fun ha hb => S.add_mem' ha hb }
invFun S :=
{ carrier := Multiplicative.ofAdd ⁻¹' S
zero_mem' := S.one_mem'
add_mem' := fun ha hb => S.mul_mem' ha hb}
left_inv x := by cases x; rfl
right_inv x := by cases x; rfl
map_rel_iff' := Iff.rfl
#align add_submonoid.to_submonoid AddSubmonoid.toSubmonoid
#align add_submonoid.to_submonoid_symm_apply_coe AddSubmonoid.toSubmonoid_symm_apply_coe
#align add_submonoid.to_submonoid_apply_coe AddSubmonoid.toSubmonoid_apply_coe
/-- Submonoids of a monoid `Multiplicative A` are isomorphic to additive submonoids of `A`. -/
abbrev Submonoid.toAddSubmonoid' : Submonoid (Multiplicative A) ≃o AddSubmonoid A :=
AddSubmonoid.toSubmonoid.symm
#align submonoid.to_add_submonoid' Submonoid.toAddSubmonoid'
theorem AddSubmonoid.toSubmonoid_closure (S : Set A) :
(AddSubmonoid.toSubmonoid) (AddSubmonoid.closure S)
= Submonoid.closure (Multiplicative.toAdd ⁻¹' S) :=
le_antisymm
(AddSubmonoid.toSubmonoid.to_galoisConnection.l_le <|
AddSubmonoid.closure_le.2 <| Submonoid.subset_closure (M := Multiplicative A))
(Submonoid.closure_le.2 <| AddSubmonoid.subset_closure (M := A))
#align add_submonoid.to_submonoid_closure AddSubmonoid.toSubmonoid_closure
theorem Submonoid.toAddSubmonoid'_closure (S : Set (Multiplicative A)) :
Submonoid.toAddSubmonoid' (Submonoid.closure S)
= AddSubmonoid.closure (Additive.ofMul ⁻¹' S) :=
le_antisymm
(Submonoid.toAddSubmonoid'.to_galoisConnection.l_le <|
Submonoid.closure_le.2 <| AddSubmonoid.subset_closure (M := A))
(AddSubmonoid.closure_le.2 <| Submonoid.subset_closure (M := Multiplicative A))
#align submonoid.to_add_submonoid'_closure Submonoid.toAddSubmonoid'_closure
end
namespace Submonoid
variable {F : Type*} [FunLike F M N] [mc : MonoidHomClass F M N]
open Set
/-!
### `comap` and `map`
-/
/-- The preimage of a submonoid along a monoid homomorphism is a submonoid. -/
@[to_additive
"The preimage of an `AddSubmonoid` along an `AddMonoid` homomorphism is an `AddSubmonoid`."]
def comap (f : F) (S : Submonoid N) :
Submonoid M where
carrier := f ⁻¹' S
one_mem' := show f 1 ∈ S by rw [map_one]; exact S.one_mem
mul_mem' ha hb := show f (_ * _) ∈ S by rw [map_mul]; exact S.mul_mem ha hb
#align submonoid.comap Submonoid.comap
#align add_submonoid.comap AddSubmonoid.comap
@[to_additive (attr := simp)]
theorem coe_comap (S : Submonoid N) (f : F) : (S.comap f : Set M) = f ⁻¹' S :=
rfl
#align submonoid.coe_comap Submonoid.coe_comap
#align add_submonoid.coe_comap AddSubmonoid.coe_comap
@[to_additive (attr := simp)]
theorem mem_comap {S : Submonoid N} {f : F} {x : M} : x ∈ S.comap f ↔ f x ∈ S :=
Iff.rfl
#align submonoid.mem_comap Submonoid.mem_comap
#align add_submonoid.mem_comap AddSubmonoid.mem_comap
@[to_additive]
theorem comap_comap (S : Submonoid P) (g : N →* P) (f : M →* N) :
(S.comap g).comap f = S.comap (g.comp f) :=
rfl
#align submonoid.comap_comap Submonoid.comap_comap
#align add_submonoid.comap_comap AddSubmonoid.comap_comap
@[to_additive (attr := simp)]
theorem comap_id (S : Submonoid P) : S.comap (MonoidHom.id P) = S :=
ext (by simp)
#align submonoid.comap_id Submonoid.comap_id
#align add_submonoid.comap_id AddSubmonoid.comap_id
/-- The image of a submonoid along a monoid homomorphism is a submonoid. -/
@[to_additive
"The image of an `AddSubmonoid` along an `AddMonoid` homomorphism is an `AddSubmonoid`."]
def map (f : F) (S : Submonoid M) :
Submonoid N where
carrier := f '' S
one_mem' := ⟨1, S.one_mem, map_one f⟩
mul_mem' := by
rintro _ _ ⟨x, hx, rfl⟩ ⟨y, hy, rfl⟩;
exact ⟨x * y, S.mul_mem hx hy, by rw [map_mul]⟩
#align submonoid.map Submonoid.map
#align add_submonoid.map AddSubmonoid.map
@[to_additive (attr := simp)]
theorem coe_map (f : F) (S : Submonoid M) : (S.map f : Set N) = f '' S :=
rfl
#align submonoid.coe_map Submonoid.coe_map
#align add_submonoid.coe_map AddSubmonoid.coe_map
@[to_additive (attr := simp)]
theorem mem_map {f : F} {S : Submonoid M} {y : N} : y ∈ S.map f ↔ ∃ x ∈ S, f x = y := Iff.rfl
#align submonoid.mem_map Submonoid.mem_map
#align add_submonoid.mem_map AddSubmonoid.mem_map
@[to_additive]
theorem mem_map_of_mem (f : F) {S : Submonoid M} {x : M} (hx : x ∈ S) : f x ∈ S.map f :=
mem_image_of_mem f hx
#align submonoid.mem_map_of_mem Submonoid.mem_map_of_mem
#align add_submonoid.mem_map_of_mem AddSubmonoid.mem_map_of_mem
@[to_additive]
theorem apply_coe_mem_map (f : F) (S : Submonoid M) (x : S) : f x ∈ S.map f :=
mem_map_of_mem f x.2
#align submonoid.apply_coe_mem_map Submonoid.apply_coe_mem_map
#align add_submonoid.apply_coe_mem_map AddSubmonoid.apply_coe_mem_map
@[to_additive]
theorem map_map (g : N →* P) (f : M →* N) : (S.map f).map g = S.map (g.comp f) :=
SetLike.coe_injective <| image_image _ _ _
#align submonoid.map_map Submonoid.map_map
#align add_submonoid.map_map AddSubmonoid.map_map
-- The simpNF linter says that the LHS can be simplified via `Submonoid.mem_map`.
-- However this is a higher priority lemma.
-- https://github.com/leanprover/std4/issues/207
@[to_additive (attr := simp 1100, nolint simpNF)]
theorem mem_map_iff_mem {f : F} (hf : Function.Injective f) {S : Submonoid M} {x : M} :
f x ∈ S.map f ↔ x ∈ S :=
hf.mem_set_image
#align submonoid.mem_map_iff_mem Submonoid.mem_map_iff_mem
#align add_submonoid.mem_map_iff_mem AddSubmonoid.mem_map_iff_mem
@[to_additive]
theorem map_le_iff_le_comap {f : F} {S : Submonoid M} {T : Submonoid N} :
S.map f ≤ T ↔ S ≤ T.comap f :=
image_subset_iff
#align submonoid.map_le_iff_le_comap Submonoid.map_le_iff_le_comap
#align add_submonoid.map_le_iff_le_comap AddSubmonoid.map_le_iff_le_comap
@[to_additive]
theorem gc_map_comap (f : F) : GaloisConnection (map f) (comap f) := fun _ _ => map_le_iff_le_comap
#align submonoid.gc_map_comap Submonoid.gc_map_comap
#align add_submonoid.gc_map_comap AddSubmonoid.gc_map_comap
@[to_additive]
theorem map_le_of_le_comap {T : Submonoid N} {f : F} : S ≤ T.comap f → S.map f ≤ T :=
(gc_map_comap f).l_le
#align submonoid.map_le_of_le_comap Submonoid.map_le_of_le_comap
#align add_submonoid.map_le_of_le_comap AddSubmonoid.map_le_of_le_comap
@[to_additive]
theorem le_comap_of_map_le {T : Submonoid N} {f : F} : S.map f ≤ T → S ≤ T.comap f :=
(gc_map_comap f).le_u
#align submonoid.le_comap_of_map_le Submonoid.le_comap_of_map_le
#align add_submonoid.le_comap_of_map_le AddSubmonoid.le_comap_of_map_le
@[to_additive]
theorem le_comap_map {f : F} : S ≤ (S.map f).comap f :=
(gc_map_comap f).le_u_l _
#align submonoid.le_comap_map Submonoid.le_comap_map
#align add_submonoid.le_comap_map AddSubmonoid.le_comap_map
@[to_additive]
theorem map_comap_le {S : Submonoid N} {f : F} : (S.comap f).map f ≤ S :=
(gc_map_comap f).l_u_le _
#align submonoid.map_comap_le Submonoid.map_comap_le
#align add_submonoid.map_comap_le AddSubmonoid.map_comap_le
@[to_additive]
theorem monotone_map {f : F} : Monotone (map f) :=
(gc_map_comap f).monotone_l
#align submonoid.monotone_map Submonoid.monotone_map
#align add_submonoid.monotone_map AddSubmonoid.monotone_map
@[to_additive]
theorem monotone_comap {f : F} : Monotone (comap f) :=
(gc_map_comap f).monotone_u
#align submonoid.monotone_comap Submonoid.monotone_comap
#align add_submonoid.monotone_comap AddSubmonoid.monotone_comap
@[to_additive (attr := simp)]
theorem map_comap_map {f : F} : ((S.map f).comap f).map f = S.map f :=
(gc_map_comap f).l_u_l_eq_l _
#align submonoid.map_comap_map Submonoid.map_comap_map
#align add_submonoid.map_comap_map AddSubmonoid.map_comap_map
@[to_additive (attr := simp)]
theorem comap_map_comap {S : Submonoid N} {f : F} : ((S.comap f).map f).comap f = S.comap f :=
(gc_map_comap f).u_l_u_eq_u _
#align submonoid.comap_map_comap Submonoid.comap_map_comap
#align add_submonoid.comap_map_comap AddSubmonoid.comap_map_comap
@[to_additive]
theorem map_sup (S T : Submonoid M) (f : F) : (S ⊔ T).map f = S.map f ⊔ T.map f :=
(gc_map_comap f : GaloisConnection (map f) (comap f)).l_sup
#align submonoid.map_sup Submonoid.map_sup
#align add_submonoid.map_sup AddSubmonoid.map_sup
@[to_additive]
theorem map_iSup {ι : Sort*} (f : F) (s : ι → Submonoid M) : (iSup s).map f = ⨆ i, (s i).map f :=
(gc_map_comap f : GaloisConnection (map f) (comap f)).l_iSup
#align submonoid.map_supr Submonoid.map_iSup
#align add_submonoid.map_supr AddSubmonoid.map_iSup
@[to_additive]
theorem comap_inf (S T : Submonoid N) (f : F) : (S ⊓ T).comap f = S.comap f ⊓ T.comap f :=
(gc_map_comap f : GaloisConnection (map f) (comap f)).u_inf
#align submonoid.comap_inf Submonoid.comap_inf
#align add_submonoid.comap_inf AddSubmonoid.comap_inf
@[to_additive]
theorem comap_iInf {ι : Sort*} (f : F) (s : ι → Submonoid N) :
(iInf s).comap f = ⨅ i, (s i).comap f :=
(gc_map_comap f : GaloisConnection (map f) (comap f)).u_iInf
#align submonoid.comap_infi Submonoid.comap_iInf
#align add_submonoid.comap_infi AddSubmonoid.comap_iInf
@[to_additive (attr := simp)]
theorem map_bot (f : F) : (⊥ : Submonoid M).map f = ⊥ :=
(gc_map_comap f).l_bot
#align submonoid.map_bot Submonoid.map_bot
#align add_submonoid.map_bot AddSubmonoid.map_bot
@[to_additive (attr := simp)]
theorem comap_top (f : F) : (⊤ : Submonoid N).comap f = ⊤ :=
(gc_map_comap f).u_top
#align submonoid.comap_top Submonoid.comap_top
#align add_submonoid.comap_top AddSubmonoid.comap_top
@[to_additive (attr := simp)]
theorem map_id (S : Submonoid M) : S.map (MonoidHom.id M) = S :=
ext fun _ => ⟨fun ⟨_, h, rfl⟩ => h, fun h => ⟨_, h, rfl⟩⟩
#align submonoid.map_id Submonoid.map_id
#align add_submonoid.map_id AddSubmonoid.map_id
section GaloisCoinsertion
variable {ι : Type*} {f : F} (hf : Function.Injective f)
/-- `map f` and `comap f` form a `GaloisCoinsertion` when `f` is injective. -/
@[to_additive " `map f` and `comap f` form a `GaloisCoinsertion` when `f` is injective. "]
def gciMapComap : GaloisCoinsertion (map f) (comap f) :=
(gc_map_comap f).toGaloisCoinsertion fun S x => by simp [mem_comap, mem_map, hf.eq_iff]
#align submonoid.gci_map_comap Submonoid.gciMapComap
#align add_submonoid.gci_map_comap AddSubmonoid.gciMapComap
@[to_additive]
theorem comap_map_eq_of_injective (S : Submonoid M) : (S.map f).comap f = S :=
(gciMapComap hf).u_l_eq _
#align submonoid.comap_map_eq_of_injective Submonoid.comap_map_eq_of_injective
#align add_submonoid.comap_map_eq_of_injective AddSubmonoid.comap_map_eq_of_injective
@[to_additive]
theorem comap_surjective_of_injective : Function.Surjective (comap f) :=
(gciMapComap hf).u_surjective
#align submonoid.comap_surjective_of_injective Submonoid.comap_surjective_of_injective
#align add_submonoid.comap_surjective_of_injective AddSubmonoid.comap_surjective_of_injective
@[to_additive]
theorem map_injective_of_injective : Function.Injective (map f) :=
(gciMapComap hf).l_injective
#align submonoid.map_injective_of_injective Submonoid.map_injective_of_injective
#align add_submonoid.map_injective_of_injective AddSubmonoid.map_injective_of_injective
@[to_additive]
theorem comap_inf_map_of_injective (S T : Submonoid M) : (S.map f ⊓ T.map f).comap f = S ⊓ T :=
(gciMapComap hf).u_inf_l _ _
#align submonoid.comap_inf_map_of_injective Submonoid.comap_inf_map_of_injective
#align add_submonoid.comap_inf_map_of_injective AddSubmonoid.comap_inf_map_of_injective
@[to_additive]
theorem comap_iInf_map_of_injective (S : ι → Submonoid M) : (⨅ i, (S i).map f).comap f = iInf S :=
(gciMapComap hf).u_iInf_l _
#align submonoid.comap_infi_map_of_injective Submonoid.comap_iInf_map_of_injective
#align add_submonoid.comap_infi_map_of_injective AddSubmonoid.comap_iInf_map_of_injective
@[to_additive]
theorem comap_sup_map_of_injective (S T : Submonoid M) : (S.map f ⊔ T.map f).comap f = S ⊔ T :=
(gciMapComap hf).u_sup_l _ _
#align submonoid.comap_sup_map_of_injective Submonoid.comap_sup_map_of_injective
#align add_submonoid.comap_sup_map_of_injective AddSubmonoid.comap_sup_map_of_injective
@[to_additive]
theorem comap_iSup_map_of_injective (S : ι → Submonoid M) : (⨆ i, (S i).map f).comap f = iSup S :=
(gciMapComap hf).u_iSup_l _
#align submonoid.comap_supr_map_of_injective Submonoid.comap_iSup_map_of_injective
#align add_submonoid.comap_supr_map_of_injective AddSubmonoid.comap_iSup_map_of_injective
@[to_additive]
theorem map_le_map_iff_of_injective {S T : Submonoid M} : S.map f ≤ T.map f ↔ S ≤ T :=
(gciMapComap hf).l_le_l_iff
#align submonoid.map_le_map_iff_of_injective Submonoid.map_le_map_iff_of_injective
#align add_submonoid.map_le_map_iff_of_injective AddSubmonoid.map_le_map_iff_of_injective
@[to_additive]
theorem map_strictMono_of_injective : StrictMono (map f) :=
(gciMapComap hf).strictMono_l
#align submonoid.map_strict_mono_of_injective Submonoid.map_strictMono_of_injective
#align add_submonoid.map_strict_mono_of_injective AddSubmonoid.map_strictMono_of_injective
end GaloisCoinsertion
section GaloisInsertion
variable {ι : Type*} {f : F} (hf : Function.Surjective f)
/-- `map f` and `comap f` form a `GaloisInsertion` when `f` is surjective. -/
@[to_additive " `map f` and `comap f` form a `GaloisInsertion` when `f` is surjective. "]
def giMapComap : GaloisInsertion (map f) (comap f) :=
(gc_map_comap f).toGaloisInsertion fun S x h =>
let ⟨y, hy⟩ := hf x
mem_map.2 ⟨y, by simp [hy, h]⟩
#align submonoid.gi_map_comap Submonoid.giMapComap
#align add_submonoid.gi_map_comap AddSubmonoid.giMapComap
@[to_additive]
theorem map_comap_eq_of_surjective (S : Submonoid N) : (S.comap f).map f = S :=
(giMapComap hf).l_u_eq _
#align submonoid.map_comap_eq_of_surjective Submonoid.map_comap_eq_of_surjective
#align add_submonoid.map_comap_eq_of_surjective AddSubmonoid.map_comap_eq_of_surjective
@[to_additive]
theorem map_surjective_of_surjective : Function.Surjective (map f) :=
(giMapComap hf).l_surjective
#align submonoid.map_surjective_of_surjective Submonoid.map_surjective_of_surjective
#align add_submonoid.map_surjective_of_surjective AddSubmonoid.map_surjective_of_surjective
@[to_additive]
theorem comap_injective_of_surjective : Function.Injective (comap f) :=
(giMapComap hf).u_injective
#align submonoid.comap_injective_of_surjective Submonoid.comap_injective_of_surjective
#align add_submonoid.comap_injective_of_surjective AddSubmonoid.comap_injective_of_surjective
@[to_additive]
theorem map_inf_comap_of_surjective (S T : Submonoid N) : (S.comap f ⊓ T.comap f).map f = S ⊓ T :=
(giMapComap hf).l_inf_u _ _
#align submonoid.map_inf_comap_of_surjective Submonoid.map_inf_comap_of_surjective
#align add_submonoid.map_inf_comap_of_surjective AddSubmonoid.map_inf_comap_of_surjective
@[to_additive]
theorem map_iInf_comap_of_surjective (S : ι → Submonoid N) : (⨅ i, (S i).comap f).map f = iInf S :=
(giMapComap hf).l_iInf_u _
#align submonoid.map_infi_comap_of_surjective Submonoid.map_iInf_comap_of_surjective
#align add_submonoid.map_infi_comap_of_surjective AddSubmonoid.map_iInf_comap_of_surjective
@[to_additive]
theorem map_sup_comap_of_surjective (S T : Submonoid N) : (S.comap f ⊔ T.comap f).map f = S ⊔ T :=
(giMapComap hf).l_sup_u _ _
#align submonoid.map_sup_comap_of_surjective Submonoid.map_sup_comap_of_surjective
#align add_submonoid.map_sup_comap_of_surjective AddSubmonoid.map_sup_comap_of_surjective
@[to_additive]
theorem map_iSup_comap_of_surjective (S : ι → Submonoid N) : (⨆ i, (S i).comap f).map f = iSup S :=
(giMapComap hf).l_iSup_u _
#align submonoid.map_supr_comap_of_surjective Submonoid.map_iSup_comap_of_surjective
#align add_submonoid.map_supr_comap_of_surjective AddSubmonoid.map_iSup_comap_of_surjective
@[to_additive]
theorem comap_le_comap_iff_of_surjective {S T : Submonoid N} : S.comap f ≤ T.comap f ↔ S ≤ T :=
(giMapComap hf).u_le_u_iff
#align submonoid.comap_le_comap_iff_of_surjective Submonoid.comap_le_comap_iff_of_surjective
#align add_submonoid.comap_le_comap_iff_of_surjective AddSubmonoid.comap_le_comap_iff_of_surjective
@[to_additive]
theorem comap_strictMono_of_surjective : StrictMono (comap f) :=
(giMapComap hf).strictMono_u
#align submonoid.comap_strict_mono_of_surjective Submonoid.comap_strictMono_of_surjective
#align add_submonoid.comap_strict_mono_of_surjective AddSubmonoid.comap_strictMono_of_surjective
end GaloisInsertion
end Submonoid
namespace OneMemClass
variable {A M₁ : Type*} [SetLike A M₁] [One M₁] [hA : OneMemClass A M₁] (S' : A)
/-- A submonoid of a monoid inherits a 1. -/
@[to_additive "An `AddSubmonoid` of an `AddMonoid` inherits a zero."]
instance one : One S' :=
⟨⟨1, OneMemClass.one_mem S'⟩⟩
#align one_mem_class.has_one OneMemClass.one
#align zero_mem_class.has_zero ZeroMemClass.zero
@[to_additive (attr := simp, norm_cast)]
theorem coe_one : ((1 : S') : M₁) = 1 :=
rfl
#align one_mem_class.coe_one OneMemClass.coe_one
#align zero_mem_class.coe_zero ZeroMemClass.coe_zero
variable {S'}
@[to_additive (attr := simp, norm_cast)]
theorem coe_eq_one {x : S'} : (↑x : M₁) = 1 ↔ x = 1 :=
(Subtype.ext_iff.symm : (x : M₁) = (1 : S') ↔ x = 1)
#align one_mem_class.coe_eq_one OneMemClass.coe_eq_one
#align zero_mem_class.coe_eq_zero ZeroMemClass.coe_eq_zero
variable (S')
@[to_additive]
theorem one_def : (1 : S') = ⟨1, OneMemClass.one_mem S'⟩ :=
rfl
#align one_mem_class.one_def OneMemClass.one_def
#align zero_mem_class.zero_def ZeroMemClass.zero_def
end OneMemClass
variable {A : Type*} [SetLike A M] [hA : SubmonoidClass A M] (S' : A)
/-- An `AddSubmonoid` of an `AddMonoid` inherits a scalar multiplication. -/
instance AddSubmonoidClass.nSMul {M} [AddMonoid M] {A : Type*} [SetLike A M]
[AddSubmonoidClass A M] (S : A) : SMul ℕ S :=
⟨fun n a => ⟨n • a.1, nsmul_mem a.2 n⟩⟩
#align add_submonoid_class.has_nsmul AddSubmonoidClass.nSMul
namespace SubmonoidClass
/-- A submonoid of a monoid inherits a power operator. -/
instance nPow {M} [Monoid M] {A : Type*} [SetLike A M] [SubmonoidClass A M] (S : A) : Pow S ℕ :=
⟨fun a n => ⟨a.1 ^ n, pow_mem a.2 n⟩⟩
#align submonoid_class.has_pow SubmonoidClass.nPow
attribute [to_additive existing nSMul] nPow
@[to_additive (attr := simp, norm_cast)]
theorem coe_pow {M} [Monoid M] {A : Type*} [SetLike A M] [SubmonoidClass A M] {S : A} (x : S)
(n : ℕ) : ↑(x ^ n) = (x : M) ^ n :=
rfl
#align submonoid_class.coe_pow SubmonoidClass.coe_pow
#align add_submonoid_class.coe_nsmul AddSubmonoidClass.coe_nsmul
@[to_additive (attr := simp)]
theorem mk_pow {M} [Monoid M] {A : Type*} [SetLike A M] [SubmonoidClass A M] {S : A} (x : M)
(hx : x ∈ S) (n : ℕ) : (⟨x, hx⟩ : S) ^ n = ⟨x ^ n, pow_mem hx n⟩ :=
rfl
#align submonoid_class.mk_pow SubmonoidClass.mk_pow
#align add_submonoid_class.mk_nsmul AddSubmonoidClass.mk_nsmul
-- Prefer subclasses of `Monoid` over subclasses of `SubmonoidClass`.
/-- A submonoid of a unital magma inherits a unital magma structure. -/
@[to_additive
"An `AddSubmonoid` of a unital additive magma inherits a unital additive magma structure."]
instance (priority := 75) toMulOneClass {M : Type*} [MulOneClass M] {A : Type*} [SetLike A M]
[SubmonoidClass A M] (S : A) : MulOneClass S :=
Subtype.coe_injective.mulOneClass (↑) rfl (fun _ _ => rfl)
#align submonoid_class.to_mul_one_class SubmonoidClass.toMulOneClass
#align add_submonoid_class.to_add_zero_class AddSubmonoidClass.toAddZeroClass
-- Prefer subclasses of `Monoid` over subclasses of `SubmonoidClass`.
/-- A submonoid of a monoid inherits a monoid structure. -/
@[to_additive "An `AddSubmonoid` of an `AddMonoid` inherits an `AddMonoid` structure."]
instance (priority := 75) toMonoid {M : Type*} [Monoid M] {A : Type*} [SetLike A M]
[SubmonoidClass A M] (S : A) : Monoid S :=
Subtype.coe_injective.monoid (↑) rfl (fun _ _ => rfl) (fun _ _ => rfl)
#align submonoid_class.to_monoid SubmonoidClass.toMonoid
#align add_submonoid_class.to_add_monoid AddSubmonoidClass.toAddMonoid
-- Prefer subclasses of `Monoid` over subclasses of `SubmonoidClass`.
/-- A submonoid of a `CommMonoid` is a `CommMonoid`. -/
@[to_additive "An `AddSubmonoid` of an `AddCommMonoid` is an `AddCommMonoid`."]
instance (priority := 75) toCommMonoid {M} [CommMonoid M] {A : Type*} [SetLike A M]
[SubmonoidClass A M] (S : A) : CommMonoid S :=
Subtype.coe_injective.commMonoid (↑) rfl (fun _ _ => rfl) fun _ _ => rfl
#align submonoid_class.to_comm_monoid SubmonoidClass.toCommMonoid
#align add_submonoid_class.to_add_comm_monoid AddSubmonoidClass.toAddCommMonoid
/-- The natural monoid hom from a submonoid of monoid `M` to `M`. -/
@[to_additive "The natural monoid hom from an `AddSubmonoid` of `AddMonoid` `M` to `M`."]
def subtype : S' →* M where
toFun := Subtype.val; map_one' := rfl; map_mul' _ _ := by simp
#align submonoid_class.subtype SubmonoidClass.subtype
#align add_submonoid_class.subtype AddSubmonoidClass.subtype
@[to_additive (attr := simp)]
theorem coe_subtype : (SubmonoidClass.subtype S' : S' → M) = Subtype.val :=
rfl
#align submonoid_class.coe_subtype SubmonoidClass.coe_subtype
#align add_submonoid_class.coe_subtype AddSubmonoidClass.coe_subtype
end SubmonoidClass
namespace Submonoid
/-- A submonoid of a monoid inherits a multiplication. -/
@[to_additive "An `AddSubmonoid` of an `AddMonoid` inherits an addition."]
instance mul : Mul S :=
⟨fun a b => ⟨a.1 * b.1, S.mul_mem a.2 b.2⟩⟩
#align submonoid.has_mul Submonoid.mul
#align add_submonoid.has_add AddSubmonoid.add
/-- A submonoid of a monoid inherits a 1. -/
@[to_additive "An `AddSubmonoid` of an `AddMonoid` inherits a zero."]
instance one : One S :=
⟨⟨_, S.one_mem⟩⟩
#align submonoid.has_one Submonoid.one
#align add_submonoid.has_zero AddSubmonoid.zero
@[to_additive (attr := simp, norm_cast)]
theorem coe_mul (x y : S) : (↑(x * y) : M) = ↑x * ↑y :=
rfl
#align submonoid.coe_mul Submonoid.coe_mul
#align add_submonoid.coe_add AddSubmonoid.coe_add
@[to_additive (attr := simp, norm_cast)]
theorem coe_one : ((1 : S) : M) = 1 :=
rfl
#align submonoid.coe_one Submonoid.coe_one
#align add_submonoid.coe_zero AddSubmonoid.coe_zero
@[to_additive (attr := simp)]
lemma mk_eq_one {a : M} {ha} : (⟨a, ha⟩ : S) = 1 ↔ a = 1 := by simp [← SetLike.coe_eq_coe]
@[to_additive (attr := simp)]
theorem mk_mul_mk (x y : M) (hx : x ∈ S) (hy : y ∈ S) :
(⟨x, hx⟩ : S) * ⟨y, hy⟩ = ⟨x * y, S.mul_mem hx hy⟩ :=
rfl
#align submonoid.mk_mul_mk Submonoid.mk_mul_mk
#align add_submonoid.mk_add_mk AddSubmonoid.mk_add_mk
@[to_additive]
theorem mul_def (x y : S) : x * y = ⟨x * y, S.mul_mem x.2 y.2⟩ :=
rfl
#align submonoid.mul_def Submonoid.mul_def
#align add_submonoid.add_def AddSubmonoid.add_def
@[to_additive]
theorem one_def : (1 : S) = ⟨1, S.one_mem⟩ :=
rfl
#align submonoid.one_def Submonoid.one_def
#align add_submonoid.zero_def AddSubmonoid.zero_def
/-- A submonoid of a unital magma inherits a unital magma structure. -/
@[to_additive
"An `AddSubmonoid` of a unital additive magma inherits a unital additive magma structure."]
instance toMulOneClass {M : Type*} [MulOneClass M] (S : Submonoid M) : MulOneClass S :=
Subtype.coe_injective.mulOneClass (↑) rfl fun _ _ => rfl
#align submonoid.to_mul_one_class Submonoid.toMulOneClass
#align add_submonoid.to_add_zero_class AddSubmonoid.toAddZeroClass
@[to_additive]
protected theorem pow_mem {M : Type*} [Monoid M] (S : Submonoid M) {x : M} (hx : x ∈ S) (n : ℕ) :
x ^ n ∈ S :=
pow_mem hx n
#align submonoid.pow_mem Submonoid.pow_mem
#align add_submonoid.nsmul_mem AddSubmonoid.nsmul_mem
-- Porting note: coe_pow removed, syntactic tautology
#noalign submonoid.coe_pow
#noalign add_submonoid.coe_smul
/-- A submonoid of a monoid inherits a monoid structure. -/
@[to_additive "An `AddSubmonoid` of an `AddMonoid` inherits an `AddMonoid` structure."]
instance toMonoid {M : Type*} [Monoid M] (S : Submonoid M) : Monoid S :=
Subtype.coe_injective.monoid (↑) rfl (fun _ _ => rfl) fun _ _ => rfl
#align submonoid.to_monoid Submonoid.toMonoid
#align add_submonoid.to_add_monoid AddSubmonoid.toAddMonoid
/-- A submonoid of a `CommMonoid` is a `CommMonoid`. -/
@[to_additive "An `AddSubmonoid` of an `AddCommMonoid` is an `AddCommMonoid`."]
instance toCommMonoid {M} [CommMonoid M] (S : Submonoid M) : CommMonoid S :=
Subtype.coe_injective.commMonoid (↑) rfl (fun _ _ => rfl) fun _ _ => rfl
#align submonoid.to_comm_monoid Submonoid.toCommMonoid
#align add_submonoid.to_add_comm_monoid AddSubmonoid.toAddCommMonoid
/-- The natural monoid hom from a submonoid of monoid `M` to `M`. -/
@[to_additive "The natural monoid hom from an `AddSubmonoid` of `AddMonoid` `M` to `M`."]
def subtype : S →* M where
toFun := Subtype.val; map_one' := rfl; map_mul' _ _ := by simp
#align submonoid.subtype Submonoid.subtype
#align add_submonoid.subtype AddSubmonoid.subtype
@[to_additive (attr := simp)]
theorem coe_subtype : ⇑S.subtype = Subtype.val :=
rfl
#align submonoid.coe_subtype Submonoid.coe_subtype
#align add_submonoid.coe_subtype AddSubmonoid.coe_subtype
/-- The top submonoid is isomorphic to the monoid. -/
@[to_additive (attr := simps) "The top additive submonoid is isomorphic to the additive monoid."]
def topEquiv : (⊤ : Submonoid M) ≃* M where
toFun x := x
invFun x := ⟨x, mem_top x⟩
left_inv x := x.eta _
right_inv _ := rfl
map_mul' _ _ := rfl
#align submonoid.top_equiv Submonoid.topEquiv
#align add_submonoid.top_equiv AddSubmonoid.topEquiv
#align submonoid.top_equiv_apply Submonoid.topEquiv_apply
#align submonoid.top_equiv_symm_apply_coe Submonoid.topEquiv_symm_apply_coe
@[to_additive (attr := simp)]
theorem topEquiv_toMonoidHom : ((topEquiv : _ ≃* M) : _ →* M) = (⊤ : Submonoid M).subtype :=
rfl
#align submonoid.top_equiv_to_monoid_hom Submonoid.topEquiv_toMonoidHom
#align add_submonoid.top_equiv_to_add_monoid_hom AddSubmonoid.topEquiv_toAddMonoidHom
/-- A subgroup is isomorphic to its image under an injective function. If you have an isomorphism,
use `MulEquiv.submonoidMap` for better definitional equalities. -/
@[to_additive "An additive subgroup is isomorphic to its image under an injective function. If you
have an isomorphism, use `AddEquiv.addSubmonoidMap` for better definitional equalities."]
noncomputable def equivMapOfInjective (f : M →* N) (hf : Function.Injective f) : S ≃* S.map f :=
{ Equiv.Set.image f S hf with map_mul' := fun _ _ => Subtype.ext (f.map_mul _ _) }
#align submonoid.equiv_map_of_injective Submonoid.equivMapOfInjective
#align add_submonoid.equiv_map_of_injective AddSubmonoid.equivMapOfInjective
@[to_additive (attr := simp)]
theorem coe_equivMapOfInjective_apply (f : M →* N) (hf : Function.Injective f) (x : S) :
(equivMapOfInjective S f hf x : N) = f x :=
rfl
#align submonoid.coe_equiv_map_of_injective_apply Submonoid.coe_equivMapOfInjective_apply
#align add_submonoid.coe_equiv_map_of_injective_apply AddSubmonoid.coe_equivMapOfInjective_apply
@[to_additive (attr := simp)]
theorem closure_closure_coe_preimage {s : Set M} : closure (((↑) : closure s → M) ⁻¹' s) = ⊤ :=
eq_top_iff.2 fun x =>
Subtype.recOn x fun x hx _ => by
refine closure_induction' (p := fun y hy ↦ ⟨y, hy⟩ ∈ closure (((↑) : closure s → M) ⁻¹' s))
(fun g hg => subset_closure hg) ?_ (fun g₁ g₂ hg₁ hg₂ => ?_) hx
· exact Submonoid.one_mem _
· exact Submonoid.mul_mem _
#align submonoid.closure_closure_coe_preimage Submonoid.closure_closure_coe_preimage
#align add_submonoid.closure_closure_coe_preimage AddSubmonoid.closure_closure_coe_preimage
/-- Given submonoids `s`, `t` of monoids `M`, `N` respectively, `s × t` as a submonoid
of `M × N`. -/
@[to_additive prod
"Given `AddSubmonoid`s `s`, `t` of `AddMonoid`s `A`, `B` respectively, `s × t`
as an `AddSubmonoid` of `A × B`."]
def prod (s : Submonoid M) (t : Submonoid N) :
Submonoid (M × N) where
carrier := s ×ˢ t
one_mem' := ⟨s.one_mem, t.one_mem⟩
mul_mem' hp hq := ⟨s.mul_mem hp.1 hq.1, t.mul_mem hp.2 hq.2⟩
#align submonoid.prod Submonoid.prod
#align add_submonoid.prod AddSubmonoid.prod
@[to_additive coe_prod]
theorem coe_prod (s : Submonoid M) (t : Submonoid N) :
(s.prod t : Set (M × N)) = (s : Set M) ×ˢ (t : Set N) :=
rfl
#align submonoid.coe_prod Submonoid.coe_prod
#align add_submonoid.coe_prod AddSubmonoid.coe_prod
@[to_additive mem_prod]
theorem mem_prod {s : Submonoid M} {t : Submonoid N} {p : M × N} :
p ∈ s.prod t ↔ p.1 ∈ s ∧ p.2 ∈ t :=
Iff.rfl
#align submonoid.mem_prod Submonoid.mem_prod
#align add_submonoid.mem_prod AddSubmonoid.mem_prod
@[to_additive prod_mono]
theorem prod_mono {s₁ s₂ : Submonoid M} {t₁ t₂ : Submonoid N} (hs : s₁ ≤ s₂) (ht : t₁ ≤ t₂) :
s₁.prod t₁ ≤ s₂.prod t₂ :=
Set.prod_mono hs ht
#align submonoid.prod_mono Submonoid.prod_mono
#align add_submonoid.prod_mono AddSubmonoid.prod_mono
@[to_additive prod_top]
theorem prod_top (s : Submonoid M) : s.prod (⊤ : Submonoid N) = s.comap (MonoidHom.fst M N) :=
ext fun x => by simp [mem_prod, MonoidHom.coe_fst]
#align submonoid.prod_top Submonoid.prod_top
#align add_submonoid.prod_top AddSubmonoid.prod_top
@[to_additive top_prod]
theorem top_prod (s : Submonoid N) : (⊤ : Submonoid M).prod s = s.comap (MonoidHom.snd M N) :=
ext fun x => by simp [mem_prod, MonoidHom.coe_snd]
#align submonoid.top_prod Submonoid.top_prod
#align add_submonoid.top_prod AddSubmonoid.top_prod
@[to_additive (attr := simp) top_prod_top]
theorem top_prod_top : (⊤ : Submonoid M).prod (⊤ : Submonoid N) = ⊤ :=
(top_prod _).trans <| comap_top _
#align submonoid.top_prod_top Submonoid.top_prod_top
#align add_submonoid.top_prod_top AddSubmonoid.top_prod_top
@[to_additive bot_prod_bot]
theorem bot_prod_bot : (⊥ : Submonoid M).prod (⊥ : Submonoid N) = ⊥ :=
SetLike.coe_injective <| by simp [coe_prod, Prod.one_eq_mk]
#align submonoid.bot_prod_bot Submonoid.bot_prod_bot
-- Porting note: to_additive translated the name incorrectly in mathlib 3.
#align add_submonoid.bot_sum_bot AddSubmonoid.bot_prod_bot
/-- The product of submonoids is isomorphic to their product as monoids. -/
@[to_additive prodEquiv
"The product of additive submonoids is isomorphic to their product as additive monoids"]
def prodEquiv (s : Submonoid M) (t : Submonoid N) : s.prod t ≃* s × t :=
{ (Equiv.Set.prod (s : Set M) (t : Set N)) with
map_mul' := fun _ _ => rfl }
#align submonoid.prod_equiv Submonoid.prodEquiv
#align add_submonoid.prod_equiv AddSubmonoid.prodEquiv
open MonoidHom
@[to_additive]
theorem map_inl (s : Submonoid M) : s.map (inl M N) = s.prod ⊥ :=
ext fun p =>
⟨fun ⟨_, hx, hp⟩ => hp ▸ ⟨hx, Set.mem_singleton 1⟩, fun ⟨hps, hp1⟩ =>
⟨p.1, hps, Prod.ext rfl <| (Set.eq_of_mem_singleton hp1).symm⟩⟩
#align submonoid.map_inl Submonoid.map_inl
#align add_submonoid.map_inl AddSubmonoid.map_inl
@[to_additive]
theorem map_inr (s : Submonoid N) : s.map (inr M N) = prod ⊥ s :=
ext fun p =>
⟨fun ⟨_, hx, hp⟩ => hp ▸ ⟨Set.mem_singleton 1, hx⟩, fun ⟨hp1, hps⟩ =>
⟨p.2, hps, Prod.ext (Set.eq_of_mem_singleton hp1).symm rfl⟩⟩
#align submonoid.map_inr Submonoid.map_inr
#align add_submonoid.map_inr AddSubmonoid.map_inr
@[to_additive (attr := simp) prod_bot_sup_bot_prod]
theorem prod_bot_sup_bot_prod (s : Submonoid M) (t : Submonoid N) :
(prod s ⊥) ⊔ (prod ⊥ t) = prod s t :=
(le_antisymm (sup_le (prod_mono (le_refl s) bot_le) (prod_mono bot_le (le_refl t))))
fun p hp => Prod.fst_mul_snd p ▸ mul_mem
((le_sup_left : prod s ⊥ ≤ prod s ⊥ ⊔ prod ⊥ t) ⟨hp.1, Set.mem_singleton 1⟩)
((le_sup_right : prod ⊥ t ≤ prod s ⊥ ⊔ prod ⊥ t) ⟨Set.mem_singleton 1, hp.2⟩)
#align submonoid.prod_bot_sup_bot_prod Submonoid.prod_bot_sup_bot_prod
#align add_submonoid.prod_bot_sup_bot_prod AddSubmonoid.prod_bot_sup_bot_prod
@[to_additive]
theorem mem_map_equiv {f : M ≃* N} {K : Submonoid M} {x : N} :
x ∈ K.map f.toMonoidHom ↔ f.symm x ∈ K :=
Set.mem_image_equiv
#align submonoid.mem_map_equiv Submonoid.mem_map_equiv
#align add_submonoid.mem_map_equiv AddSubmonoid.mem_map_equiv
@[to_additive]
theorem map_equiv_eq_comap_symm (f : M ≃* N) (K : Submonoid M) :
K.map f.toMonoidHom = K.comap f.symm.toMonoidHom :=
SetLike.coe_injective (f.toEquiv.image_eq_preimage K)
#align submonoid.map_equiv_eq_comap_symm Submonoid.map_equiv_eq_comap_symm
#align add_submonoid.map_equiv_eq_comap_symm AddSubmonoid.map_equiv_eq_comap_symm
@[to_additive]
theorem comap_equiv_eq_map_symm (f : N ≃* M) (K : Submonoid M) :
K.comap f = K.map f.symm :=
(map_equiv_eq_comap_symm f.symm K).symm
#align submonoid.comap_equiv_eq_map_symm Submonoid.comap_equiv_eq_map_symm
#align add_submonoid.comap_equiv_eq_map_symm AddSubmonoid.comap_equiv_eq_map_symm
@[to_additive (attr := simp)]
theorem map_equiv_top (f : M ≃* N) : (⊤ : Submonoid M).map f = ⊤ :=
SetLike.coe_injective <| Set.image_univ.trans f.surjective.range_eq
#align submonoid.map_equiv_top Submonoid.map_equiv_top
#align add_submonoid.map_equiv_top AddSubmonoid.map_equiv_top
@[to_additive le_prod_iff]
theorem le_prod_iff {s : Submonoid M} {t : Submonoid N} {u : Submonoid (M × N)} :
u ≤ s.prod t ↔ u.map (fst M N) ≤ s ∧ u.map (snd M N) ≤ t := by
constructor
· intro h
constructor
· rintro x ⟨⟨y1, y2⟩, ⟨hy1, rfl⟩⟩
exact (h hy1).1
· rintro x ⟨⟨y1, y2⟩, ⟨hy1, rfl⟩⟩
exact (h hy1).2
· rintro ⟨hH, hK⟩ ⟨x1, x2⟩ h
exact ⟨hH ⟨_, h, rfl⟩, hK ⟨_, h, rfl⟩⟩
#align submonoid.le_prod_iff Submonoid.le_prod_iff
#align add_submonoid.le_prod_iff AddSubmonoid.le_prod_iff
@[to_additive prod_le_iff]
theorem prod_le_iff {s : Submonoid M} {t : Submonoid N} {u : Submonoid (M × N)} :
s.prod t ≤ u ↔ s.map (inl M N) ≤ u ∧ t.map (inr M N) ≤ u := by
constructor
· intro h
constructor
· rintro _ ⟨x, hx, rfl⟩
apply h
exact ⟨hx, Submonoid.one_mem _⟩
· rintro _ ⟨x, hx, rfl⟩
apply h
exact ⟨Submonoid.one_mem _, hx⟩
· rintro ⟨hH, hK⟩ ⟨x1, x2⟩ ⟨h1, h2⟩
have h1' : inl M N x1 ∈ u := by
apply hH
simpa using h1
have h2' : inr M N x2 ∈ u := by
apply hK
simpa using h2
simpa using Submonoid.mul_mem _ h1' h2'
#align submonoid.prod_le_iff Submonoid.prod_le_iff
#align add_submonoid.prod_le_iff AddSubmonoid.prod_le_iff
end Submonoid
namespace MonoidHom
variable {F : Type*} [FunLike F M N] [mc : MonoidHomClass F M N]
open Submonoid
library_note "range copy pattern"/--
For many categories (monoids, modules, rings, ...) the set-theoretic image of a morphism `f` is
a subobject of the codomain. When this is the case, it is useful to define the range of a morphism
in such a way that the underlying carrier set of the range subobject is definitionally
`Set.range f`. In particular this means that the types `↥(Set.range f)` and `↥f.range` are
interchangeable without proof obligations.
A convenient candidate definition for range which is mathematically correct is `map ⊤ f`, just as
`Set.range` could have been defined as `f '' Set.univ`. However, this lacks the desired definitional
convenience, in that it both does not match `Set.range`, and that it introduces a redundant `x ∈ ⊤`
term which clutters proofs. In such a case one may resort to the `copy`
pattern. A `copy` function converts the definitional problem for the carrier set of a subobject
into a one-off propositional proof obligation which one discharges while writing the definition of
the definitionally convenient range (the parameter `hs` in the example below).
A good example is the case of a morphism of monoids. A convenient definition for
`MonoidHom.mrange` would be `(⊤ : Submonoid M).map f`. However since this lacks the required
definitional convenience, we first define `Submonoid.copy` as follows:
```lean
protected def copy (S : Submonoid M) (s : Set M) (hs : s = S) : Submonoid M :=
{ carrier := s,
one_mem' := hs.symm ▸ S.one_mem',
mul_mem' := hs.symm ▸ S.mul_mem' }
```
and then finally define:
```lean
def mrange (f : M →* N) : Submonoid N :=
((⊤ : Submonoid M).map f).copy (Set.range f) Set.image_univ.symm
```
-/
/-- The range of a monoid homomorphism is a submonoid. See Note [range copy pattern]. -/
@[to_additive "The range of an `AddMonoidHom` is an `AddSubmonoid`."]
def mrange (f : F) : Submonoid N :=
((⊤ : Submonoid M).map f).copy (Set.range f) Set.image_univ.symm
#align monoid_hom.mrange MonoidHom.mrange
#align add_monoid_hom.mrange AddMonoidHom.mrange
@[to_additive (attr := simp)]
theorem coe_mrange (f : F) : (mrange f : Set N) = Set.range f :=
rfl
#align monoid_hom.coe_mrange MonoidHom.coe_mrange
#align add_monoid_hom.coe_mrange AddMonoidHom.coe_mrange
@[to_additive (attr := simp)]
theorem mem_mrange {f : F} {y : N} : y ∈ mrange f ↔ ∃ x, f x = y :=
Iff.rfl
#align monoid_hom.mem_mrange MonoidHom.mem_mrange
#align add_monoid_hom.mem_mrange AddMonoidHom.mem_mrange
@[to_additive]
theorem mrange_eq_map (f : F) : mrange f = (⊤ : Submonoid M).map f :=
Submonoid.copy_eq _
#align monoid_hom.mrange_eq_map MonoidHom.mrange_eq_map
#align add_monoid_hom.mrange_eq_map AddMonoidHom.mrange_eq_map
@[to_additive (attr := simp)]
theorem mrange_id : mrange (MonoidHom.id M) = ⊤ := by
simp [mrange_eq_map]
@[to_additive]
theorem map_mrange (g : N →* P) (f : M →* N) : f.mrange.map g = mrange (comp g f) := by
simpa only [mrange_eq_map] using (⊤ : Submonoid M).map_map g f
#align monoid_hom.map_mrange MonoidHom.map_mrange
#align add_monoid_hom.map_mrange AddMonoidHom.map_mrange
@[to_additive]
theorem mrange_top_iff_surjective {f : F} : mrange f = (⊤ : Submonoid N) ↔ Function.Surjective f :=
SetLike.ext'_iff.trans <| Iff.trans (by rw [coe_mrange, coe_top]) Set.range_iff_surjective
#align monoid_hom.mrange_top_iff_surjective MonoidHom.mrange_top_iff_surjective
#align add_monoid_hom.mrange_top_iff_surjective AddMonoidHom.mrange_top_iff_surjective
/-- The range of a surjective monoid hom is the whole of the codomain. -/
@[to_additive (attr := simp)
"The range of a surjective `AddMonoid` hom is the whole of the codomain."]
theorem mrange_top_of_surjective (f : F) (hf : Function.Surjective f) :
mrange f = (⊤ : Submonoid N) :=
mrange_top_iff_surjective.2 hf
#align monoid_hom.mrange_top_of_surjective MonoidHom.mrange_top_of_surjective
#align add_monoid_hom.mrange_top_of_surjective AddMonoidHom.mrange_top_of_surjective
@[to_additive]
theorem mclosure_preimage_le (f : F) (s : Set N) : closure (f ⁻¹' s) ≤ (closure s).comap f :=
closure_le.2 fun _ hx => SetLike.mem_coe.2 <| mem_comap.2 <| subset_closure hx
#align monoid_hom.mclosure_preimage_le MonoidHom.mclosure_preimage_le
#align add_monoid_hom.mclosure_preimage_le AddMonoidHom.mclosure_preimage_le
/-- The image under a monoid hom of the submonoid generated by a set equals the submonoid generated
by the image of the set. -/
@[to_additive
"The image under an `AddMonoid` hom of the `AddSubmonoid` generated by a set equals
the `AddSubmonoid` generated by the image of the set."]
theorem map_mclosure (f : F) (s : Set M) : (closure s).map f = closure (f '' s) :=
le_antisymm
(map_le_iff_le_comap.2 <|
le_trans (closure_mono <| Set.subset_preimage_image _ _) (mclosure_preimage_le _ _))
(closure_le.2 <| Set.image_subset _ subset_closure)
#align monoid_hom.map_mclosure MonoidHom.map_mclosure
#align add_monoid_hom.map_mclosure AddMonoidHom.map_mclosure
@[to_additive (attr := simp)]
theorem mclosure_range (f : F) : closure (Set.range f) = mrange f := by
rw [← Set.image_univ, ← map_mclosure, mrange_eq_map, closure_univ]
/-- Restriction of a monoid hom to a submonoid of the domain. -/
@[to_additive "Restriction of an `AddMonoid` hom to an `AddSubmonoid` of the domain."]
def restrict {N S : Type*} [MulOneClass N] [SetLike S M] [SubmonoidClass S M] (f : M →* N)
(s : S) : s →* N :=
f.comp (SubmonoidClass.subtype _)
#align monoid_hom.restrict MonoidHom.restrict
#align add_monoid_hom.restrict AddMonoidHom.restrict
@[to_additive (attr := simp)]
theorem restrict_apply {N S : Type*} [MulOneClass N] [SetLike S M] [SubmonoidClass S M]
(f : M →* N) (s : S) (x : s) : f.restrict s x = f x :=
rfl
#align monoid_hom.restrict_apply MonoidHom.restrict_apply
#align add_monoid_hom.restrict_apply AddMonoidHom.restrict_apply
@[to_additive (attr := simp)]
theorem restrict_mrange (f : M →* N) : mrange (f.restrict S) = S.map f := by
simp [SetLike.ext_iff]
#align monoid_hom.restrict_mrange MonoidHom.restrict_mrange
#align add_monoid_hom.restrict_mrange AddMonoidHom.restrict_mrange
/-- Restriction of a monoid hom to a submonoid of the codomain. -/
@[to_additive (attr := simps apply)
"Restriction of an `AddMonoid` hom to an `AddSubmonoid` of the codomain."]
def codRestrict {S} [SetLike S N] [SubmonoidClass S N] (f : M →* N) (s : S) (h : ∀ x, f x ∈ s) :
M →* s where
toFun n := ⟨f n, h n⟩
map_one' := Subtype.eq f.map_one
map_mul' x y := Subtype.eq (f.map_mul x y)
#align monoid_hom.cod_restrict MonoidHom.codRestrict
#align add_monoid_hom.cod_restrict AddMonoidHom.codRestrict
#align monoid_hom.cod_restrict_apply MonoidHom.codRestrict_apply
/-- Restriction of a monoid hom to its range interpreted as a submonoid. -/
@[to_additive "Restriction of an `AddMonoid` hom to its range interpreted as a submonoid."]
def mrangeRestrict {N} [MulOneClass N] (f : M →* N) : M →* (mrange f) :=
(f.codRestrict (mrange f)) fun x => ⟨x, rfl⟩
#align monoid_hom.mrange_restrict MonoidHom.mrangeRestrict
#align add_monoid_hom.mrange_restrict AddMonoidHom.mrangeRestrict
@[to_additive (attr := simp)]
theorem coe_mrangeRestrict {N} [MulOneClass N] (f : M →* N) (x : M) :
(f.mrangeRestrict x : N) = f x :=
rfl
#align monoid_hom.coe_mrange_restrict MonoidHom.coe_mrangeRestrict
#align add_monoid_hom.coe_mrange_restrict AddMonoidHom.coe_mrangeRestrict
@[to_additive]
theorem mrangeRestrict_surjective (f : M →* N) : Function.Surjective f.mrangeRestrict :=
fun ⟨_, ⟨x, rfl⟩⟩ => ⟨x, rfl⟩
#align monoid_hom.mrange_restrict_surjective MonoidHom.mrangeRestrict_surjective
#align add_monoid_hom.mrange_restrict_surjective AddMonoidHom.mrangeRestrict_surjective
/-- The multiplicative kernel of a monoid hom is the submonoid of elements `x : G` such
that `f x = 1` -/
@[to_additive
"The additive kernel of an `AddMonoid` hom is the `AddSubmonoid` of
elements such that `f x = 0`"]
def mker (f : F) : Submonoid M :=
(⊥ : Submonoid N).comap f
#align monoid_hom.mker MonoidHom.mker
#align add_monoid_hom.mker AddMonoidHom.mker
@[to_additive]
theorem mem_mker (f : F) {x : M} : x ∈ mker f ↔ f x = 1 :=
Iff.rfl
#align monoid_hom.mem_mker MonoidHom.mem_mker
#align add_monoid_hom.mem_mker AddMonoidHom.mem_mker
@[to_additive]
theorem coe_mker (f : F) : (mker f : Set M) = (f : M → N) ⁻¹' {1} :=
rfl
#align monoid_hom.coe_mker MonoidHom.coe_mker
#align add_monoid_hom.coe_mker AddMonoidHom.coe_mker
@[to_additive]
instance decidableMemMker [DecidableEq N] (f : F) : DecidablePred (· ∈ mker f) := fun x =>
decidable_of_iff (f x = 1) (mem_mker f)
#align monoid_hom.decidable_mem_mker MonoidHom.decidableMemMker
#align add_monoid_hom.decidable_mem_mker AddMonoidHom.decidableMemMker
@[to_additive]
theorem comap_mker (g : N →* P) (f : M →* N) : g.mker.comap f = mker (comp g f) :=
rfl
#align monoid_hom.comap_mker MonoidHom.comap_mker
#align add_monoid_hom.comap_mker AddMonoidHom.comap_mker
@[to_additive (attr := simp)]
theorem comap_bot' (f : F) : (⊥ : Submonoid N).comap f = mker f :=
rfl
#align monoid_hom.comap_bot' MonoidHom.comap_bot'
#align add_monoid_hom.comap_bot' AddMonoidHom.comap_bot'
@[to_additive (attr := simp)]
theorem restrict_mker (f : M →* N) : mker (f.restrict S) = f.mker.comap S.subtype :=
rfl
#align monoid_hom.restrict_mker MonoidHom.restrict_mker
#align add_monoid_hom.restrict_mker AddMonoidHom.restrict_mker
@[to_additive]
theorem mrangeRestrict_mker (f : M →* N) : mker (mrangeRestrict f) = mker f := by
ext x
change (⟨f x, _⟩ : mrange f) = ⟨1, _⟩ ↔ f x = 1
simp
#align monoid_hom.range_restrict_mker MonoidHom.mrangeRestrict_mker
#align add_monoid_hom.range_restrict_mker AddMonoidHom.mrangeRestrict_mker
@[to_additive (attr := simp)]
theorem mker_one : mker (1 : M →* N) = ⊤ := by
ext
simp [mem_mker]
#align monoid_hom.mker_one MonoidHom.mker_one
#align add_monoid_hom.mker_zero AddMonoidHom.mker_zero
@[to_additive prod_map_comap_prod']
theorem prod_map_comap_prod' {M' : Type*} {N' : Type*} [MulOneClass M'] [MulOneClass N']
(f : M →* N) (g : M' →* N') (S : Submonoid N) (S' : Submonoid N') :
(S.prod S').comap (prodMap f g) = (S.comap f).prod (S'.comap g) :=
SetLike.coe_injective <| Set.preimage_prod_map_prod f g _ _
#align monoid_hom.prod_map_comap_prod' MonoidHom.prod_map_comap_prod'
-- Porting note: to_additive translated the name incorrectly in mathlib 3.
#align add_monoid_hom.sum_map_comap_sum' AddMonoidHom.prod_map_comap_prod'
@[to_additive mker_prod_map]
theorem mker_prod_map {M' : Type*} {N' : Type*} [MulOneClass M'] [MulOneClass N'] (f : M →* N)
(g : M' →* N') : mker (prodMap f g) = f.mker.prod (mker g) := by
rw [← comap_bot', ← comap_bot', ← comap_bot', ← prod_map_comap_prod', bot_prod_bot]
#align monoid_hom.mker_prod_map MonoidHom.mker_prod_map
-- Porting note: to_additive translated the name incorrectly in mathlib 3.
#align add_monoid_hom.mker_sum_map AddMonoidHom.mker_prod_map
@[to_additive (attr := simp)]
theorem mker_inl : mker (inl M N) = ⊥ := by
ext x
simp [mem_mker]
#align monoid_hom.mker_inl MonoidHom.mker_inl
#align add_monoid_hom.mker_inl AddMonoidHom.mker_inl
@[to_additive (attr := simp)]
theorem mker_inr : mker (inr M N) = ⊥ := by
ext x
simp [mem_mker]
#align monoid_hom.mker_inr MonoidHom.mker_inr
#align add_monoid_hom.mker_inr AddMonoidHom.mker_inr
@[to_additive (attr := simp)]
lemma mker_fst : mker (fst M N) = .prod ⊥ ⊤ := SetLike.ext fun _ => (and_true_iff _).symm
@[to_additive (attr := simp)]
lemma mker_snd : mker (snd M N) = .prod ⊤ ⊥ := SetLike.ext fun _ => (true_and_iff _).symm
/-- The `MonoidHom` from the preimage of a submonoid to itself. -/
@[to_additive (attr := simps)
"the `AddMonoidHom` from the preimage of an additive submonoid to itself."]
def submonoidComap (f : M →* N) (N' : Submonoid N) :
N'.comap f →* N' where
toFun x := ⟨f x, x.2⟩
map_one' := Subtype.eq f.map_one
map_mul' x y := Subtype.eq (f.map_mul x y)
#align monoid_hom.submonoid_comap MonoidHom.submonoidComap
#align add_monoid_hom.add_submonoid_comap AddMonoidHom.addSubmonoidComap
#align monoid_hom.submonoid_comap_apply_coe MonoidHom.submonoidComap_apply_coe
#align add_monoid_hom.submonoid_comap_apply_coe AddMonoidHom.addSubmonoidComap_apply_coe
/-- The `MonoidHom` from a submonoid to its image.
See `MulEquiv.SubmonoidMap` for a variant for `MulEquiv`s. -/
@[to_additive (attr := simps)
"the `AddMonoidHom` from an additive submonoid to its image. See
`AddEquiv.AddSubmonoidMap` for a variant for `AddEquiv`s."]
def submonoidMap (f : M →* N) (M' : Submonoid M) : M' →* M'.map f where
toFun x := ⟨f x, ⟨x, x.2, rfl⟩⟩
map_one' := Subtype.eq <| f.map_one
map_mul' x y := Subtype.eq <| f.map_mul x y
#align monoid_hom.submonoid_map MonoidHom.submonoidMap
#align add_monoid_hom.add_submonoid_map AddMonoidHom.addSubmonoidMap
#align monoid_hom.submonoid_map_apply_coe MonoidHom.submonoidMap_apply_coe
#align add_monoid_hom.submonoid_map_apply_coe AddMonoidHom.addSubmonoidMap_apply_coe
@[to_additive]
theorem submonoidMap_surjective (f : M →* N) (M' : Submonoid M) :
Function.Surjective (f.submonoidMap M') := by
rintro ⟨_, x, hx, rfl⟩
exact ⟨⟨x, hx⟩, rfl⟩
#align monoid_hom.submonoid_map_surjective MonoidHom.submonoidMap_surjective
#align add_monoid_hom.add_submonoid_map_surjective AddMonoidHom.addSubmonoidMap_surjective
end MonoidHom
namespace Submonoid
open MonoidHom
@[to_additive]
theorem mrange_inl : mrange (inl M N) = prod ⊤ ⊥ := by simpa only [mrange_eq_map] using map_inl ⊤
#align submonoid.mrange_inl Submonoid.mrange_inl
#align add_submonoid.mrange_inl AddSubmonoid.mrange_inl
@[to_additive]
theorem mrange_inr : mrange (inr M N) = prod ⊥ ⊤ := by simpa only [mrange_eq_map] using map_inr ⊤
#align submonoid.mrange_inr Submonoid.mrange_inr
#align add_submonoid.mrange_inr AddSubmonoid.mrange_inr
@[to_additive]
theorem mrange_inl' : mrange (inl M N) = comap (snd M N) ⊥ :=
mrange_inl.trans (top_prod _)
#align submonoid.mrange_inl' Submonoid.mrange_inl'
#align add_submonoid.mrange_inl' AddSubmonoid.mrange_inl'
@[to_additive]
theorem mrange_inr' : mrange (inr M N) = comap (fst M N) ⊥ :=
mrange_inr.trans (prod_top _)
#align submonoid.mrange_inr' Submonoid.mrange_inr'
#align add_submonoid.mrange_inr' AddSubmonoid.mrange_inr'
@[to_additive (attr := simp)]
theorem mrange_fst : mrange (fst M N) = ⊤ :=
mrange_top_of_surjective (fst M N) <| @Prod.fst_surjective _ _ ⟨1⟩
#align submonoid.mrange_fst Submonoid.mrange_fst
#align add_submonoid.mrange_fst AddSubmonoid.mrange_fst
@[to_additive (attr := simp)]
theorem mrange_snd : mrange (snd M N) = ⊤ :=
mrange_top_of_surjective (snd M N) <| @Prod.snd_surjective _ _ ⟨1⟩
#align submonoid.mrange_snd Submonoid.mrange_snd
#align add_submonoid.mrange_snd AddSubmonoid.mrange_snd
@[to_additive prod_eq_bot_iff]
theorem prod_eq_bot_iff {s : Submonoid M} {t : Submonoid N} : s.prod t = ⊥ ↔ s = ⊥ ∧ t = ⊥ := by
simp only [eq_bot_iff, prod_le_iff, (gc_map_comap _).le_iff_le, comap_bot', mker_inl, mker_inr]
#align submonoid.prod_eq_bot_iff Submonoid.prod_eq_bot_iff
-- Porting note: to_additive translated the name incorrectly in mathlib 3.
#align add_submonoid.sum_eq_bot_iff AddSubmonoid.prod_eq_bot_iff
@[to_additive prod_eq_top_iff]
theorem prod_eq_top_iff {s : Submonoid M} {t : Submonoid N} : s.prod t = ⊤ ↔ s = ⊤ ∧ t = ⊤ := by
simp only [eq_top_iff, le_prod_iff, ← (gc_map_comap _).le_iff_le, ← mrange_eq_map, mrange_fst,
mrange_snd]
#align submonoid.prod_eq_top_iff Submonoid.prod_eq_top_iff
-- Porting note: to_additive translated the name incorrectly in mathlib 3.
#align add_submonoid.sum_eq_top_iff AddSubmonoid.prod_eq_top_iff
@[to_additive (attr := simp)]
theorem mrange_inl_sup_mrange_inr : mrange (inl M N) ⊔ mrange (inr M N) = ⊤ := by
simp only [mrange_inl, mrange_inr, prod_bot_sup_bot_prod, top_prod_top]
#align submonoid.mrange_inl_sup_mrange_inr Submonoid.mrange_inl_sup_mrange_inr
#align add_submonoid.mrange_inl_sup_mrange_inr AddSubmonoid.mrange_inl_sup_mrange_inr
/-- The monoid hom associated to an inclusion of submonoids. -/
@[to_additive
"The `AddMonoid` hom associated to an inclusion of submonoids."]
def inclusion {S T : Submonoid M} (h : S ≤ T) : S →* T :=
S.subtype.codRestrict _ fun x => h x.2
#align submonoid.inclusion Submonoid.inclusion
#align add_submonoid.inclusion AddSubmonoid.inclusion
@[to_additive (attr := simp)]
theorem range_subtype (s : Submonoid M) : mrange s.subtype = s :=
SetLike.coe_injective <| (coe_mrange _).trans <| Subtype.range_coe
#align submonoid.range_subtype Submonoid.range_subtype
#align add_submonoid.range_subtype AddSubmonoid.range_subtype
@[to_additive]
theorem eq_top_iff' : S = ⊤ ↔ ∀ x : M, x ∈ S :=
eq_top_iff.trans ⟨fun h m => h <| mem_top m, fun h m _ => h m⟩
#align submonoid.eq_top_iff' Submonoid.eq_top_iff'
#align add_submonoid.eq_top_iff' AddSubmonoid.eq_top_iff'
@[to_additive]
theorem eq_bot_iff_forall : S = ⊥ ↔ ∀ x ∈ S, x = (1 : M) :=
SetLike.ext_iff.trans <| by simp (config := { contextual := true }) [iff_def, S.one_mem]
#align submonoid.eq_bot_iff_forall Submonoid.eq_bot_iff_forall
#align add_submonoid.eq_bot_iff_forall AddSubmonoid.eq_bot_iff_forall
@[to_additive]
| Mathlib/Algebra/Group/Submonoid/Operations.lean | 1,306 | 1,309 | theorem eq_bot_of_subsingleton [Subsingleton S] : S = ⊥ := by |
rw [eq_bot_iff_forall]
intro y hy
simpa using _root_.congr_arg ((↑) : S → M) <| Subsingleton.elim (⟨y, hy⟩ : S) 1
|
/-
Copyright (c) 2021 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Algebra.MvPolynomial.Equiv
import Mathlib.Algebra.MvPolynomial.Supported
import Mathlib.LinearAlgebra.LinearIndependent
import Mathlib.RingTheory.Adjoin.Basic
import Mathlib.RingTheory.Algebraic
import Mathlib.RingTheory.MvPolynomial.Basic
#align_import ring_theory.algebraic_independent from "leanprover-community/mathlib"@"949dc57e616a621462062668c9f39e4e17b64b69"
/-!
# Algebraic Independence
This file defines algebraic independence of a family of element of an `R` algebra.
## Main definitions
* `AlgebraicIndependent` - `AlgebraicIndependent R x` states the family of elements `x`
is algebraically independent over `R`, meaning that the canonical map out of the multivariable
polynomial ring is injective.
* `AlgebraicIndependent.repr` - The canonical map from the subalgebra generated by an
algebraic independent family into the polynomial ring.
## References
* [Stacks: Transcendence](https://stacks.math.columbia.edu/tag/030D)
## TODO
Define the transcendence degree and show it is independent of the choice of a
transcendence basis.
## Tags
transcendence basis, transcendence degree, transcendence
-/
noncomputable section
open Function Set Subalgebra MvPolynomial Algebra
open scoped Classical
universe x u v w
variable {ι : Type*} {ι' : Type*} (R : Type*) {K : Type*}
variable {A : Type*} {A' A'' : Type*} {V : Type u} {V' : Type*}
variable (x : ι → A)
variable [CommRing R] [CommRing A] [CommRing A'] [CommRing A'']
variable [Algebra R A] [Algebra R A'] [Algebra R A'']
variable {a b : R}
/-- `AlgebraicIndependent R x` states the family of elements `x`
is algebraically independent over `R`, meaning that the canonical
map out of the multivariable polynomial ring is injective. -/
def AlgebraicIndependent : Prop :=
Injective (MvPolynomial.aeval x : MvPolynomial ι R →ₐ[R] A)
#align algebraic_independent AlgebraicIndependent
variable {R} {x}
theorem algebraicIndependent_iff_ker_eq_bot :
AlgebraicIndependent R x ↔
RingHom.ker (MvPolynomial.aeval x : MvPolynomial ι R →ₐ[R] A).toRingHom = ⊥ :=
RingHom.injective_iff_ker_eq_bot _
#align algebraic_independent_iff_ker_eq_bot algebraicIndependent_iff_ker_eq_bot
theorem algebraicIndependent_iff :
AlgebraicIndependent R x ↔
∀ p : MvPolynomial ι R, MvPolynomial.aeval (x : ι → A) p = 0 → p = 0 :=
injective_iff_map_eq_zero _
#align algebraic_independent_iff algebraicIndependent_iff
theorem AlgebraicIndependent.eq_zero_of_aeval_eq_zero (h : AlgebraicIndependent R x) :
∀ p : MvPolynomial ι R, MvPolynomial.aeval (x : ι → A) p = 0 → p = 0 :=
algebraicIndependent_iff.1 h
#align algebraic_independent.eq_zero_of_aeval_eq_zero AlgebraicIndependent.eq_zero_of_aeval_eq_zero
theorem algebraicIndependent_iff_injective_aeval :
AlgebraicIndependent R x ↔ Injective (MvPolynomial.aeval x : MvPolynomial ι R →ₐ[R] A) :=
Iff.rfl
#align algebraic_independent_iff_injective_aeval algebraicIndependent_iff_injective_aeval
@[simp]
theorem algebraicIndependent_empty_type_iff [IsEmpty ι] :
AlgebraicIndependent R x ↔ Injective (algebraMap R A) := by
have : aeval x = (Algebra.ofId R A).comp (@isEmptyAlgEquiv R ι _ _).toAlgHom := by
ext i
exact IsEmpty.elim' ‹IsEmpty ι› i
rw [AlgebraicIndependent, this, ← Injective.of_comp_iff' _ (@isEmptyAlgEquiv R ι _ _).bijective]
rfl
#align algebraic_independent_empty_type_iff algebraicIndependent_empty_type_iff
namespace AlgebraicIndependent
variable (hx : AlgebraicIndependent R x)
theorem algebraMap_injective : Injective (algebraMap R A) := by
simpa [Function.comp] using
(Injective.of_comp_iff (algebraicIndependent_iff_injective_aeval.1 hx) MvPolynomial.C).2
(MvPolynomial.C_injective _ _)
#align algebraic_independent.algebra_map_injective AlgebraicIndependent.algebraMap_injective
theorem linearIndependent : LinearIndependent R x := by
rw [linearIndependent_iff_injective_total]
have : Finsupp.total ι A R x =
(MvPolynomial.aeval x).toLinearMap.comp (Finsupp.total ι _ R X) := by
ext
simp
rw [this]
refine hx.comp ?_
rw [← linearIndependent_iff_injective_total]
exact linearIndependent_X _ _
#align algebraic_independent.linear_independent AlgebraicIndependent.linearIndependent
protected theorem injective [Nontrivial R] : Injective x :=
hx.linearIndependent.injective
#align algebraic_independent.injective AlgebraicIndependent.injective
theorem ne_zero [Nontrivial R] (i : ι) : x i ≠ 0 :=
hx.linearIndependent.ne_zero i
#align algebraic_independent.ne_zero AlgebraicIndependent.ne_zero
theorem comp (f : ι' → ι) (hf : Function.Injective f) : AlgebraicIndependent R (x ∘ f) := by
intro p q
simpa [aeval_rename, (rename_injective f hf).eq_iff] using @hx (rename f p) (rename f q)
#align algebraic_independent.comp AlgebraicIndependent.comp
theorem coe_range : AlgebraicIndependent R ((↑) : range x → A) := by
simpa using hx.comp _ (rangeSplitting_injective x)
#align algebraic_independent.coe_range AlgebraicIndependent.coe_range
theorem map {f : A →ₐ[R] A'} (hf_inj : Set.InjOn f (adjoin R (range x))) :
AlgebraicIndependent R (f ∘ x) := by
have : aeval (f ∘ x) = f.comp (aeval x) := by ext; simp
have h : ∀ p : MvPolynomial ι R, aeval x p ∈ (@aeval R _ _ _ _ _ ((↑) : range x → A)).range := by
intro p
rw [AlgHom.mem_range]
refine ⟨MvPolynomial.rename (codRestrict x (range x) mem_range_self) p, ?_⟩
simp [Function.comp, aeval_rename]
intro x y hxy
rw [this] at hxy
rw [adjoin_eq_range] at hf_inj
exact hx (hf_inj (h x) (h y) hxy)
#align algebraic_independent.map AlgebraicIndependent.map
theorem map' {f : A →ₐ[R] A'} (hf_inj : Injective f) : AlgebraicIndependent R (f ∘ x) :=
hx.map hf_inj.injOn
#align algebraic_independent.map' AlgebraicIndependent.map'
theorem of_comp (f : A →ₐ[R] A') (hfv : AlgebraicIndependent R (f ∘ x)) :
AlgebraicIndependent R x := by
have : aeval (f ∘ x) = f.comp (aeval x) := by ext; simp
rw [AlgebraicIndependent, this, AlgHom.coe_comp] at hfv
exact hfv.of_comp
#align algebraic_independent.of_comp AlgebraicIndependent.of_comp
end AlgebraicIndependent
open AlgebraicIndependent
theorem AlgHom.algebraicIndependent_iff (f : A →ₐ[R] A') (hf : Injective f) :
AlgebraicIndependent R (f ∘ x) ↔ AlgebraicIndependent R x :=
⟨fun h => h.of_comp f, fun h => h.map hf.injOn⟩
#align alg_hom.algebraic_independent_iff AlgHom.algebraicIndependent_iff
@[nontriviality]
theorem algebraicIndependent_of_subsingleton [Subsingleton R] : AlgebraicIndependent R x :=
algebraicIndependent_iff.2 fun _ _ => Subsingleton.elim _ _
#align algebraic_independent_of_subsingleton algebraicIndependent_of_subsingleton
theorem algebraicIndependent_equiv (e : ι ≃ ι') {f : ι' → A} :
AlgebraicIndependent R (f ∘ e) ↔ AlgebraicIndependent R f :=
⟨fun h => Function.comp_id f ▸ e.self_comp_symm ▸ h.comp _ e.symm.injective,
fun h => h.comp _ e.injective⟩
#align algebraic_independent_equiv algebraicIndependent_equiv
theorem algebraicIndependent_equiv' (e : ι ≃ ι') {f : ι' → A} {g : ι → A} (h : f ∘ e = g) :
AlgebraicIndependent R g ↔ AlgebraicIndependent R f :=
h ▸ algebraicIndependent_equiv e
#align algebraic_independent_equiv' algebraicIndependent_equiv'
theorem algebraicIndependent_subtype_range {ι} {f : ι → A} (hf : Injective f) :
AlgebraicIndependent R ((↑) : range f → A) ↔ AlgebraicIndependent R f :=
Iff.symm <| algebraicIndependent_equiv' (Equiv.ofInjective f hf) rfl
#align algebraic_independent_subtype_range algebraicIndependent_subtype_range
alias ⟨AlgebraicIndependent.of_subtype_range, _⟩ := algebraicIndependent_subtype_range
#align algebraic_independent.of_subtype_range AlgebraicIndependent.of_subtype_range
theorem algebraicIndependent_image {ι} {s : Set ι} {f : ι → A} (hf : Set.InjOn f s) :
(AlgebraicIndependent R fun x : s => f x) ↔ AlgebraicIndependent R fun x : f '' s => (x : A) :=
algebraicIndependent_equiv' (Equiv.Set.imageOfInjOn _ _ hf) rfl
#align algebraic_independent_image algebraicIndependent_image
theorem algebraicIndependent_adjoin (hs : AlgebraicIndependent R x) :
@AlgebraicIndependent ι R (adjoin R (range x))
(fun i : ι => ⟨x i, subset_adjoin (mem_range_self i)⟩) _ _ _ :=
AlgebraicIndependent.of_comp (adjoin R (range x)).val hs
#align algebraic_independent_adjoin algebraicIndependent_adjoin
/-- A set of algebraically independent elements in an algebra `A` over a ring `K` is also
algebraically independent over a subring `R` of `K`. -/
theorem AlgebraicIndependent.restrictScalars {K : Type*} [CommRing K] [Algebra R K] [Algebra K A]
[IsScalarTower R K A] (hinj : Function.Injective (algebraMap R K))
(ai : AlgebraicIndependent K x) : AlgebraicIndependent R x := by
have : (aeval x : MvPolynomial ι K →ₐ[K] A).toRingHom.comp (MvPolynomial.map (algebraMap R K)) =
(aeval x : MvPolynomial ι R →ₐ[R] A).toRingHom := by
ext <;> simp [algebraMap_eq_smul_one]
show Injective (aeval x).toRingHom
rw [← this, RingHom.coe_comp]
exact Injective.comp ai (MvPolynomial.map_injective _ hinj)
#align algebraic_independent.restrict_scalars AlgebraicIndependent.restrictScalars
/-- Every finite subset of an algebraically independent set is algebraically independent. -/
theorem algebraicIndependent_finset_map_embedding_subtype (s : Set A)
(li : AlgebraicIndependent R ((↑) : s → A)) (t : Finset s) :
AlgebraicIndependent R ((↑) : Finset.map (Embedding.subtype s) t → A) := by
let f : t.map (Embedding.subtype s) → s := fun x =>
⟨x.1, by
obtain ⟨x, h⟩ := x
rw [Finset.mem_map] at h
obtain ⟨a, _, rfl⟩ := h
simp only [Subtype.coe_prop, Embedding.coe_subtype]⟩
convert AlgebraicIndependent.comp li f _
rintro ⟨x, hx⟩ ⟨y, hy⟩
rw [Finset.mem_map] at hx hy
obtain ⟨a, _, rfl⟩ := hx
obtain ⟨b, _, rfl⟩ := hy
simp only [f, imp_self, Subtype.mk_eq_mk]
#align algebraic_independent_finset_map_embedding_subtype algebraicIndependent_finset_map_embedding_subtype
/-- If every finite set of algebraically independent element has cardinality at most `n`,
then the same is true for arbitrary sets of algebraically independent elements. -/
theorem algebraicIndependent_bounded_of_finset_algebraicIndependent_bounded {n : ℕ}
(H : ∀ s : Finset A, (AlgebraicIndependent R fun i : s => (i : A)) → s.card ≤ n) :
∀ s : Set A, AlgebraicIndependent R ((↑) : s → A) → Cardinal.mk s ≤ n := by
intro s li
apply Cardinal.card_le_of
intro t
rw [← Finset.card_map (Embedding.subtype s)]
apply H
apply algebraicIndependent_finset_map_embedding_subtype _ li
#align algebraic_independent_bounded_of_finset_algebraic_independent_bounded algebraicIndependent_bounded_of_finset_algebraicIndependent_bounded
section Subtype
theorem AlgebraicIndependent.restrict_of_comp_subtype {s : Set ι}
(hs : AlgebraicIndependent R (x ∘ (↑) : s → A)) : AlgebraicIndependent R (s.restrict x) :=
hs
#align algebraic_independent.restrict_of_comp_subtype AlgebraicIndependent.restrict_of_comp_subtype
variable (R A)
theorem algebraicIndependent_empty_iff :
AlgebraicIndependent R ((↑) : (∅ : Set A) → A) ↔ Injective (algebraMap R A) := by simp
#align algebraic_independent_empty_iff algebraicIndependent_empty_iff
variable {R A}
theorem AlgebraicIndependent.mono {t s : Set A} (h : t ⊆ s)
(hx : AlgebraicIndependent R ((↑) : s → A)) : AlgebraicIndependent R ((↑) : t → A) := by
simpa [Function.comp] using hx.comp (inclusion h) (inclusion_injective h)
#align algebraic_independent.mono AlgebraicIndependent.mono
end Subtype
theorem AlgebraicIndependent.to_subtype_range {ι} {f : ι → A} (hf : AlgebraicIndependent R f) :
AlgebraicIndependent R ((↑) : range f → A) := by
nontriviality R
rwa [algebraicIndependent_subtype_range hf.injective]
#align algebraic_independent.to_subtype_range AlgebraicIndependent.to_subtype_range
theorem AlgebraicIndependent.to_subtype_range' {ι} {f : ι → A} (hf : AlgebraicIndependent R f) {t}
(ht : range f = t) : AlgebraicIndependent R ((↑) : t → A) :=
ht ▸ hf.to_subtype_range
#align algebraic_independent.to_subtype_range' AlgebraicIndependent.to_subtype_range'
theorem algebraicIndependent_comp_subtype {s : Set ι} :
AlgebraicIndependent R (x ∘ (↑) : s → A) ↔
∀ p ∈ MvPolynomial.supported R s, aeval x p = 0 → p = 0 := by
have : (aeval (x ∘ (↑) : s → A) : _ →ₐ[R] _) = (aeval x).comp (rename (↑)) := by ext; simp
have : ∀ p : MvPolynomial s R, rename ((↑) : s → ι) p = 0 ↔ p = 0 :=
(injective_iff_map_eq_zero' (rename ((↑) : s → ι) : MvPolynomial s R →ₐ[R] _).toRingHom).1
(rename_injective _ Subtype.val_injective)
simp [algebraicIndependent_iff, supported_eq_range_rename, *]
#align algebraic_independent_comp_subtype algebraicIndependent_comp_subtype
theorem algebraicIndependent_subtype {s : Set A} :
AlgebraicIndependent R ((↑) : s → A) ↔
∀ p : MvPolynomial A R, p ∈ MvPolynomial.supported R s → aeval id p = 0 → p = 0 := by
apply @algebraicIndependent_comp_subtype _ _ _ id
#align algebraic_independent_subtype algebraicIndependent_subtype
theorem algebraicIndependent_of_finite (s : Set A)
(H : ∀ t ⊆ s, t.Finite → AlgebraicIndependent R ((↑) : t → A)) :
AlgebraicIndependent R ((↑) : s → A) :=
algebraicIndependent_subtype.2 fun p hp =>
algebraicIndependent_subtype.1 (H _ (mem_supported.1 hp) (Finset.finite_toSet _)) _ (by simp)
#align algebraic_independent_of_finite algebraicIndependent_of_finite
theorem AlgebraicIndependent.image_of_comp {ι ι'} (s : Set ι) (f : ι → ι') (g : ι' → A)
(hs : AlgebraicIndependent R fun x : s => g (f x)) :
AlgebraicIndependent R fun x : f '' s => g x := by
nontriviality R
have : InjOn f s := injOn_iff_injective.2 hs.injective.of_comp
exact (algebraicIndependent_equiv' (Equiv.Set.imageOfInjOn f s this) rfl).1 hs
#align algebraic_independent.image_of_comp AlgebraicIndependent.image_of_comp
theorem AlgebraicIndependent.image {ι} {s : Set ι} {f : ι → A}
(hs : AlgebraicIndependent R fun x : s => f x) :
AlgebraicIndependent R fun x : f '' s => (x : A) := by
convert AlgebraicIndependent.image_of_comp s f id hs
#align algebraic_independent.image AlgebraicIndependent.image
theorem algebraicIndependent_iUnion_of_directed {η : Type*} [Nonempty η] {s : η → Set A}
(hs : Directed (· ⊆ ·) s) (h : ∀ i, AlgebraicIndependent R ((↑) : s i → A)) :
AlgebraicIndependent R ((↑) : (⋃ i, s i) → A) := by
refine algebraicIndependent_of_finite (⋃ i, s i) fun t ht ft => ?_
rcases finite_subset_iUnion ft ht with ⟨I, fi, hI⟩
rcases hs.finset_le fi.toFinset with ⟨i, hi⟩
exact (h i).mono (Subset.trans hI <| iUnion₂_subset fun j hj => hi j (fi.mem_toFinset.2 hj))
#align algebraic_independent_Union_of_directed algebraicIndependent_iUnion_of_directed
| Mathlib/RingTheory/AlgebraicIndependent.lean | 330 | 335 | theorem algebraicIndependent_sUnion_of_directed {s : Set (Set A)} (hsn : s.Nonempty)
(hs : DirectedOn (· ⊆ ·) s) (h : ∀ a ∈ s, AlgebraicIndependent R ((↑) : a → A)) :
AlgebraicIndependent R ((↑) : ⋃₀ s → A) := by |
letI : Nonempty s := Nonempty.to_subtype hsn
rw [sUnion_eq_iUnion]
exact algebraicIndependent_iUnion_of_directed hs.directed_val (by simpa using h)
|
/-
Copyright (c) 2019 Reid Barton. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Topology.Constructions
#align_import topology.continuous_on from "leanprover-community/mathlib"@"d4f691b9e5f94cfc64639973f3544c95f8d5d494"
/-!
# Neighborhoods and continuity relative to a subset
This file defines relative versions
* `nhdsWithin` of `nhds`
* `ContinuousOn` of `Continuous`
* `ContinuousWithinAt` of `ContinuousAt`
and proves their basic properties, including the relationships between
these restricted notions and the corresponding notions for the subtype
equipped with the subspace topology.
## Notation
* `𝓝 x`: the filter of neighborhoods of a point `x`;
* `𝓟 s`: the principal filter of a set `s`;
* `𝓝[s] x`: the filter `nhdsWithin x s` of neighborhoods of a point `x` within a set `s`.
-/
open Set Filter Function Topology Filter
variable {α : Type*} {β : Type*} {γ : Type*} {δ : Type*}
variable [TopologicalSpace α]
@[simp]
theorem nhds_bind_nhdsWithin {a : α} {s : Set α} : ((𝓝 a).bind fun x => 𝓝[s] x) = 𝓝[s] a :=
bind_inf_principal.trans <| congr_arg₂ _ nhds_bind_nhds rfl
#align nhds_bind_nhds_within nhds_bind_nhdsWithin
@[simp]
theorem eventually_nhds_nhdsWithin {a : α} {s : Set α} {p : α → Prop} :
(∀ᶠ y in 𝓝 a, ∀ᶠ x in 𝓝[s] y, p x) ↔ ∀ᶠ x in 𝓝[s] a, p x :=
Filter.ext_iff.1 nhds_bind_nhdsWithin { x | p x }
#align eventually_nhds_nhds_within eventually_nhds_nhdsWithin
theorem eventually_nhdsWithin_iff {a : α} {s : Set α} {p : α → Prop} :
(∀ᶠ x in 𝓝[s] a, p x) ↔ ∀ᶠ x in 𝓝 a, x ∈ s → p x :=
eventually_inf_principal
#align eventually_nhds_within_iff eventually_nhdsWithin_iff
theorem frequently_nhdsWithin_iff {z : α} {s : Set α} {p : α → Prop} :
(∃ᶠ x in 𝓝[s] z, p x) ↔ ∃ᶠ x in 𝓝 z, p x ∧ x ∈ s :=
frequently_inf_principal.trans <| by simp only [and_comm]
#align frequently_nhds_within_iff frequently_nhdsWithin_iff
theorem mem_closure_ne_iff_frequently_within {z : α} {s : Set α} :
z ∈ closure (s \ {z}) ↔ ∃ᶠ x in 𝓝[≠] z, x ∈ s := by
simp [mem_closure_iff_frequently, frequently_nhdsWithin_iff]
#align mem_closure_ne_iff_frequently_within mem_closure_ne_iff_frequently_within
@[simp]
theorem eventually_nhdsWithin_nhdsWithin {a : α} {s : Set α} {p : α → Prop} :
(∀ᶠ y in 𝓝[s] a, ∀ᶠ x in 𝓝[s] y, p x) ↔ ∀ᶠ x in 𝓝[s] a, p x := by
refine ⟨fun h => ?_, fun h => (eventually_nhds_nhdsWithin.2 h).filter_mono inf_le_left⟩
simp only [eventually_nhdsWithin_iff] at h ⊢
exact h.mono fun x hx hxs => (hx hxs).self_of_nhds hxs
#align eventually_nhds_within_nhds_within eventually_nhdsWithin_nhdsWithin
theorem nhdsWithin_eq (a : α) (s : Set α) :
𝓝[s] a = ⨅ t ∈ { t : Set α | a ∈ t ∧ IsOpen t }, 𝓟 (t ∩ s) :=
((nhds_basis_opens a).inf_principal s).eq_biInf
#align nhds_within_eq nhdsWithin_eq
theorem nhdsWithin_univ (a : α) : 𝓝[Set.univ] a = 𝓝 a := by
rw [nhdsWithin, principal_univ, inf_top_eq]
#align nhds_within_univ nhdsWithin_univ
theorem nhdsWithin_hasBasis {p : β → Prop} {s : β → Set α} {a : α} (h : (𝓝 a).HasBasis p s)
(t : Set α) : (𝓝[t] a).HasBasis p fun i => s i ∩ t :=
h.inf_principal t
#align nhds_within_has_basis nhdsWithin_hasBasis
theorem nhdsWithin_basis_open (a : α) (t : Set α) :
(𝓝[t] a).HasBasis (fun u => a ∈ u ∧ IsOpen u) fun u => u ∩ t :=
nhdsWithin_hasBasis (nhds_basis_opens a) t
#align nhds_within_basis_open nhdsWithin_basis_open
theorem mem_nhdsWithin {t : Set α} {a : α} {s : Set α} :
t ∈ 𝓝[s] a ↔ ∃ u, IsOpen u ∧ a ∈ u ∧ u ∩ s ⊆ t := by
simpa only [and_assoc, and_left_comm] using (nhdsWithin_basis_open a s).mem_iff
#align mem_nhds_within mem_nhdsWithin
theorem mem_nhdsWithin_iff_exists_mem_nhds_inter {t : Set α} {a : α} {s : Set α} :
t ∈ 𝓝[s] a ↔ ∃ u ∈ 𝓝 a, u ∩ s ⊆ t :=
(nhdsWithin_hasBasis (𝓝 a).basis_sets s).mem_iff
#align mem_nhds_within_iff_exists_mem_nhds_inter mem_nhdsWithin_iff_exists_mem_nhds_inter
theorem diff_mem_nhdsWithin_compl {x : α} {s : Set α} (hs : s ∈ 𝓝 x) (t : Set α) :
s \ t ∈ 𝓝[tᶜ] x :=
diff_mem_inf_principal_compl hs t
#align diff_mem_nhds_within_compl diff_mem_nhdsWithin_compl
theorem diff_mem_nhdsWithin_diff {x : α} {s t : Set α} (hs : s ∈ 𝓝[t] x) (t' : Set α) :
s \ t' ∈ 𝓝[t \ t'] x := by
rw [nhdsWithin, diff_eq, diff_eq, ← inf_principal, ← inf_assoc]
exact inter_mem_inf hs (mem_principal_self _)
#align diff_mem_nhds_within_diff diff_mem_nhdsWithin_diff
theorem nhds_of_nhdsWithin_of_nhds {s t : Set α} {a : α} (h1 : s ∈ 𝓝 a) (h2 : t ∈ 𝓝[s] a) :
t ∈ 𝓝 a := by
rcases mem_nhdsWithin_iff_exists_mem_nhds_inter.mp h2 with ⟨_, Hw, hw⟩
exact (𝓝 a).sets_of_superset ((𝓝 a).inter_sets Hw h1) hw
#align nhds_of_nhds_within_of_nhds nhds_of_nhdsWithin_of_nhds
theorem mem_nhdsWithin_iff_eventually {s t : Set α} {x : α} :
t ∈ 𝓝[s] x ↔ ∀ᶠ y in 𝓝 x, y ∈ s → y ∈ t :=
eventually_inf_principal
#align mem_nhds_within_iff_eventually mem_nhdsWithin_iff_eventually
theorem mem_nhdsWithin_iff_eventuallyEq {s t : Set α} {x : α} :
t ∈ 𝓝[s] x ↔ s =ᶠ[𝓝 x] (s ∩ t : Set α) := by
simp_rw [mem_nhdsWithin_iff_eventually, eventuallyEq_set, mem_inter_iff, iff_self_and]
#align mem_nhds_within_iff_eventually_eq mem_nhdsWithin_iff_eventuallyEq
theorem nhdsWithin_eq_iff_eventuallyEq {s t : Set α} {x : α} : 𝓝[s] x = 𝓝[t] x ↔ s =ᶠ[𝓝 x] t :=
set_eventuallyEq_iff_inf_principal.symm
#align nhds_within_eq_iff_eventually_eq nhdsWithin_eq_iff_eventuallyEq
theorem nhdsWithin_le_iff {s t : Set α} {x : α} : 𝓝[s] x ≤ 𝓝[t] x ↔ t ∈ 𝓝[s] x :=
set_eventuallyLE_iff_inf_principal_le.symm.trans set_eventuallyLE_iff_mem_inf_principal
#align nhds_within_le_iff nhdsWithin_le_iff
-- Porting note: golfed, dropped an unneeded assumption
theorem preimage_nhdsWithin_coinduced' {π : α → β} {s : Set β} {t : Set α} {a : α} (h : a ∈ t)
(hs : s ∈ @nhds β (.coinduced (fun x : t => π x) inferInstance) (π a)) :
π ⁻¹' s ∈ 𝓝[t] a := by
lift a to t using h
replace hs : (fun x : t => π x) ⁻¹' s ∈ 𝓝 a := preimage_nhds_coinduced hs
rwa [← map_nhds_subtype_val, mem_map]
#align preimage_nhds_within_coinduced' preimage_nhdsWithin_coinduced'ₓ
theorem mem_nhdsWithin_of_mem_nhds {s t : Set α} {a : α} (h : s ∈ 𝓝 a) : s ∈ 𝓝[t] a :=
mem_inf_of_left h
#align mem_nhds_within_of_mem_nhds mem_nhdsWithin_of_mem_nhds
theorem self_mem_nhdsWithin {a : α} {s : Set α} : s ∈ 𝓝[s] a :=
mem_inf_of_right (mem_principal_self s)
#align self_mem_nhds_within self_mem_nhdsWithin
theorem eventually_mem_nhdsWithin {a : α} {s : Set α} : ∀ᶠ x in 𝓝[s] a, x ∈ s :=
self_mem_nhdsWithin
#align eventually_mem_nhds_within eventually_mem_nhdsWithin
theorem inter_mem_nhdsWithin (s : Set α) {t : Set α} {a : α} (h : t ∈ 𝓝 a) : s ∩ t ∈ 𝓝[s] a :=
inter_mem self_mem_nhdsWithin (mem_inf_of_left h)
#align inter_mem_nhds_within inter_mem_nhdsWithin
theorem nhdsWithin_mono (a : α) {s t : Set α} (h : s ⊆ t) : 𝓝[s] a ≤ 𝓝[t] a :=
inf_le_inf_left _ (principal_mono.mpr h)
#align nhds_within_mono nhdsWithin_mono
theorem pure_le_nhdsWithin {a : α} {s : Set α} (ha : a ∈ s) : pure a ≤ 𝓝[s] a :=
le_inf (pure_le_nhds a) (le_principal_iff.2 ha)
#align pure_le_nhds_within pure_le_nhdsWithin
theorem mem_of_mem_nhdsWithin {a : α} {s t : Set α} (ha : a ∈ s) (ht : t ∈ 𝓝[s] a) : a ∈ t :=
pure_le_nhdsWithin ha ht
#align mem_of_mem_nhds_within mem_of_mem_nhdsWithin
theorem Filter.Eventually.self_of_nhdsWithin {p : α → Prop} {s : Set α} {x : α}
(h : ∀ᶠ y in 𝓝[s] x, p y) (hx : x ∈ s) : p x :=
mem_of_mem_nhdsWithin hx h
#align filter.eventually.self_of_nhds_within Filter.Eventually.self_of_nhdsWithin
theorem tendsto_const_nhdsWithin {l : Filter β} {s : Set α} {a : α} (ha : a ∈ s) :
Tendsto (fun _ : β => a) l (𝓝[s] a) :=
tendsto_const_pure.mono_right <| pure_le_nhdsWithin ha
#align tendsto_const_nhds_within tendsto_const_nhdsWithin
theorem nhdsWithin_restrict'' {a : α} (s : Set α) {t : Set α} (h : t ∈ 𝓝[s] a) :
𝓝[s] a = 𝓝[s ∩ t] a :=
le_antisymm (le_inf inf_le_left (le_principal_iff.mpr (inter_mem self_mem_nhdsWithin h)))
(inf_le_inf_left _ (principal_mono.mpr Set.inter_subset_left))
#align nhds_within_restrict'' nhdsWithin_restrict''
theorem nhdsWithin_restrict' {a : α} (s : Set α) {t : Set α} (h : t ∈ 𝓝 a) : 𝓝[s] a = 𝓝[s ∩ t] a :=
nhdsWithin_restrict'' s <| mem_inf_of_left h
#align nhds_within_restrict' nhdsWithin_restrict'
theorem nhdsWithin_restrict {a : α} (s : Set α) {t : Set α} (h₀ : a ∈ t) (h₁ : IsOpen t) :
𝓝[s] a = 𝓝[s ∩ t] a :=
nhdsWithin_restrict' s (IsOpen.mem_nhds h₁ h₀)
#align nhds_within_restrict nhdsWithin_restrict
theorem nhdsWithin_le_of_mem {a : α} {s t : Set α} (h : s ∈ 𝓝[t] a) : 𝓝[t] a ≤ 𝓝[s] a :=
nhdsWithin_le_iff.mpr h
#align nhds_within_le_of_mem nhdsWithin_le_of_mem
theorem nhdsWithin_le_nhds {a : α} {s : Set α} : 𝓝[s] a ≤ 𝓝 a := by
rw [← nhdsWithin_univ]
apply nhdsWithin_le_of_mem
exact univ_mem
#align nhds_within_le_nhds nhdsWithin_le_nhds
theorem nhdsWithin_eq_nhdsWithin' {a : α} {s t u : Set α} (hs : s ∈ 𝓝 a) (h₂ : t ∩ s = u ∩ s) :
𝓝[t] a = 𝓝[u] a := by rw [nhdsWithin_restrict' t hs, nhdsWithin_restrict' u hs, h₂]
#align nhds_within_eq_nhds_within' nhdsWithin_eq_nhdsWithin'
theorem nhdsWithin_eq_nhdsWithin {a : α} {s t u : Set α} (h₀ : a ∈ s) (h₁ : IsOpen s)
(h₂ : t ∩ s = u ∩ s) : 𝓝[t] a = 𝓝[u] a := by
rw [nhdsWithin_restrict t h₀ h₁, nhdsWithin_restrict u h₀ h₁, h₂]
#align nhds_within_eq_nhds_within nhdsWithin_eq_nhdsWithin
@[simp] theorem nhdsWithin_eq_nhds {a : α} {s : Set α} : 𝓝[s] a = 𝓝 a ↔ s ∈ 𝓝 a :=
inf_eq_left.trans le_principal_iff
#align nhds_within_eq_nhds nhdsWithin_eq_nhds
theorem IsOpen.nhdsWithin_eq {a : α} {s : Set α} (h : IsOpen s) (ha : a ∈ s) : 𝓝[s] a = 𝓝 a :=
nhdsWithin_eq_nhds.2 <| h.mem_nhds ha
#align is_open.nhds_within_eq IsOpen.nhdsWithin_eq
theorem preimage_nhds_within_coinduced {π : α → β} {s : Set β} {t : Set α} {a : α} (h : a ∈ t)
(ht : IsOpen t)
(hs : s ∈ @nhds β (.coinduced (fun x : t => π x) inferInstance) (π a)) :
π ⁻¹' s ∈ 𝓝 a := by
rw [← ht.nhdsWithin_eq h]
exact preimage_nhdsWithin_coinduced' h hs
#align preimage_nhds_within_coinduced preimage_nhds_within_coinduced
@[simp]
theorem nhdsWithin_empty (a : α) : 𝓝[∅] a = ⊥ := by rw [nhdsWithin, principal_empty, inf_bot_eq]
#align nhds_within_empty nhdsWithin_empty
theorem nhdsWithin_union (a : α) (s t : Set α) : 𝓝[s ∪ t] a = 𝓝[s] a ⊔ 𝓝[t] a := by
delta nhdsWithin
rw [← inf_sup_left, sup_principal]
#align nhds_within_union nhdsWithin_union
theorem nhdsWithin_biUnion {ι} {I : Set ι} (hI : I.Finite) (s : ι → Set α) (a : α) :
𝓝[⋃ i ∈ I, s i] a = ⨆ i ∈ I, 𝓝[s i] a :=
Set.Finite.induction_on hI (by simp) fun _ _ hT ↦ by
simp only [hT, nhdsWithin_union, iSup_insert, biUnion_insert]
#align nhds_within_bUnion nhdsWithin_biUnion
| Mathlib/Topology/ContinuousOn.lean | 246 | 248 | theorem nhdsWithin_sUnion {S : Set (Set α)} (hS : S.Finite) (a : α) :
𝓝[⋃₀ S] a = ⨆ s ∈ S, 𝓝[s] a := by |
rw [sUnion_eq_biUnion, nhdsWithin_biUnion hS]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Shing Tak Lam, Yury Kudryashov
-/
import Mathlib.Algebra.MvPolynomial.Derivation
import Mathlib.Algebra.MvPolynomial.Variables
#align_import data.mv_polynomial.pderiv from "leanprover-community/mathlib"@"2f5b500a507264de86d666a5f87ddb976e2d8de4"
/-!
# Partial derivatives of polynomials
This file defines the notion of the formal *partial derivative* of a polynomial,
the derivative with respect to a single variable.
This derivative is not connected to the notion of derivative from analysis.
It is based purely on the polynomial exponents and coefficients.
## Main declarations
* `MvPolynomial.pderiv i p` : the partial derivative of `p` with respect to `i`, as a bundled
derivation of `MvPolynomial σ R`.
## Notation
As in other polynomial files, we typically use the notation:
+ `σ : Type*` (indexing the variables)
+ `R : Type*` `[CommRing R]` (the coefficients)
+ `s : σ →₀ ℕ`, a function from `σ` to `ℕ` which is zero away from a finite set.
This will give rise to a monomial in `MvPolynomial σ R` which mathematicians might call `X^s`
+ `a : R`
+ `i : σ`, with corresponding monomial `X i`, often denoted `X_i` by mathematicians
+ `p : MvPolynomial σ R`
-/
noncomputable section
universe u v
namespace MvPolynomial
open Set Function Finsupp
variable {R : Type u} {σ : Type v} {a a' a₁ a₂ : R} {s : σ →₀ ℕ}
section PDeriv
variable [CommSemiring R]
/-- `pderiv i p` is the partial derivative of `p` with respect to `i` -/
def pderiv (i : σ) : Derivation R (MvPolynomial σ R) (MvPolynomial σ R) :=
letI := Classical.decEq σ
mkDerivation R <| Pi.single i 1
#align mv_polynomial.pderiv MvPolynomial.pderiv
theorem pderiv_def [DecidableEq σ] (i : σ) : pderiv i = mkDerivation R (Pi.single i 1) := by
unfold pderiv; congr!
#align mv_polynomial.pderiv_def MvPolynomial.pderiv_def
@[simp]
theorem pderiv_monomial {i : σ} :
pderiv i (monomial s a) = monomial (s - single i 1) (a * s i) := by
classical
simp only [pderiv_def, mkDerivation_monomial, Finsupp.smul_sum, smul_eq_mul, ← smul_mul_assoc,
← (monomial _).map_smul]
refine (Finset.sum_eq_single i (fun j _ hne => ?_) fun hi => ?_).trans ?_
· simp [Pi.single_eq_of_ne hne]
· rw [Finsupp.not_mem_support_iff] at hi; simp [hi]
· simp
#align mv_polynomial.pderiv_monomial MvPolynomial.pderiv_monomial
theorem pderiv_C {i : σ} : pderiv i (C a) = 0 :=
derivation_C _ _
set_option linter.uppercaseLean3 false in
#align mv_polynomial.pderiv_C MvPolynomial.pderiv_C
theorem pderiv_one {i : σ} : pderiv i (1 : MvPolynomial σ R) = 0 := pderiv_C
#align mv_polynomial.pderiv_one MvPolynomial.pderiv_one
@[simp]
theorem pderiv_X [DecidableEq σ] (i j : σ) :
pderiv i (X j : MvPolynomial σ R) = Pi.single (f := fun j => _) i 1 j := by
rw [pderiv_def, mkDerivation_X]
set_option linter.uppercaseLean3 false in
#align mv_polynomial.pderiv_X MvPolynomial.pderiv_X
@[simp]
theorem pderiv_X_self (i : σ) : pderiv i (X i : MvPolynomial σ R) = 1 := by classical simp
set_option linter.uppercaseLean3 false in
#align mv_polynomial.pderiv_X_self MvPolynomial.pderiv_X_self
@[simp]
theorem pderiv_X_of_ne {i j : σ} (h : j ≠ i) : pderiv i (X j : MvPolynomial σ R) = 0 := by
classical simp [h]
set_option linter.uppercaseLean3 false in
#align mv_polynomial.pderiv_X_of_ne MvPolynomial.pderiv_X_of_ne
theorem pderiv_eq_zero_of_not_mem_vars {i : σ} {f : MvPolynomial σ R} (h : i ∉ f.vars) :
pderiv i f = 0 :=
derivation_eq_zero_of_forall_mem_vars fun _ hj => pderiv_X_of_ne <| ne_of_mem_of_not_mem hj h
#align mv_polynomial.pderiv_eq_zero_of_not_mem_vars MvPolynomial.pderiv_eq_zero_of_not_mem_vars
theorem pderiv_monomial_single {i : σ} {n : ℕ} : pderiv i (monomial (single i n) a) =
monomial (single i (n - 1)) (a * n) := by simp
#align mv_polynomial.pderiv_monomial_single MvPolynomial.pderiv_monomial_single
| Mathlib/Algebra/MvPolynomial/PDeriv.lean | 115 | 117 | theorem pderiv_mul {i : σ} {f g : MvPolynomial σ R} :
pderiv i (f * g) = pderiv i f * g + f * pderiv i g := by |
simp only [(pderiv i).leibniz f g, smul_eq_mul, mul_comm, add_comm]
|
/-
Copyright (c) 2021 Kalle Kytölä. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kalle Kytölä
-/
import Mathlib.MeasureTheory.Measure.FiniteMeasure
import Mathlib.MeasureTheory.Integral.Average
#align_import measure_theory.measure.probability_measure from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Probability measures
This file defines the type of probability measures on a given measurable space. When the underlying
space has a topology and the measurable space structure (sigma algebra) is finer than the Borel
sigma algebra, then the type of probability measures is equipped with the topology of convergence
in distribution (weak convergence of measures). The topology of convergence in distribution is the
coarsest topology w.r.t. which for every bounded continuous `ℝ≥0`-valued random variable `X`, the
expected value of `X` depends continuously on the choice of probability measure. This is a special
case of the topology of weak convergence of finite measures.
## Main definitions
The main definitions are
* the type `MeasureTheory.ProbabilityMeasure Ω` with the topology of convergence in
distribution (a.k.a. convergence in law, weak convergence of measures);
* `MeasureTheory.ProbabilityMeasure.toFiniteMeasure`: Interpret a probability measure as
a finite measure;
* `MeasureTheory.FiniteMeasure.normalize`: Normalize a finite measure to a probability measure
(returns junk for the zero measure).
* `MeasureTheory.ProbabilityMeasure.map`: The push-forward `f* μ` of a probability measure
`μ` on `Ω` along a measurable function `f : Ω → Ω'`.
## Main results
* `MeasureTheory.ProbabilityMeasure.tendsto_iff_forall_integral_tendsto`: Convergence of
probability measures is characterized by the convergence of expected values of all bounded
continuous random variables. This shows that the chosen definition of topology coincides with
the common textbook definition of convergence in distribution, i.e., weak convergence of
measures. A similar characterization by the convergence of expected values (in the
`MeasureTheory.lintegral` sense) of all bounded continuous nonnegative random variables is
`MeasureTheory.ProbabilityMeasure.tendsto_iff_forall_lintegral_tendsto`.
* `MeasureTheory.FiniteMeasure.tendsto_normalize_iff_tendsto`: The convergence of finite
measures to a nonzero limit is characterized by the convergence of the probability-normalized
versions and of the total masses.
* `MeasureTheory.ProbabilityMeasure.continuous_map`: For a continuous function `f : Ω → Ω'`, the
push-forward of probability measures `f* : ProbabilityMeasure Ω → ProbabilityMeasure Ω'` is
continuous.
* `MeasureTheory.ProbabilityMeasure.t2Space`: The topology of convergence in distribution is
Hausdorff on Borel spaces where indicators of closed sets have continuous decreasing
approximating sequences (in particular on any pseudo-metrizable spaces).
TODO:
* Probability measures form a convex space.
## Implementation notes
The topology of convergence in distribution on `MeasureTheory.ProbabilityMeasure Ω` is inherited
weak convergence of finite measures via the mapping
`MeasureTheory.ProbabilityMeasure.toFiniteMeasure`.
Like `MeasureTheory.FiniteMeasure Ω`, the implementation of `MeasureTheory.ProbabilityMeasure Ω`
is directly as a subtype of `MeasureTheory.Measure Ω`, and the coercion to a function is the
composition `ENNReal.toNNReal` and the coercion to function of `MeasureTheory.Measure Ω`.
## References
* [Billingsley, *Convergence of probability measures*][billingsley1999]
## Tags
convergence in distribution, convergence in law, weak convergence of measures, probability measure
-/
noncomputable section
open MeasureTheory
open Set
open Filter
open BoundedContinuousFunction
open scoped Topology ENNReal NNReal BoundedContinuousFunction
namespace MeasureTheory
section ProbabilityMeasure
/-! ### Probability measures
In this section we define the type of probability measures on a measurable space `Ω`, denoted by
`MeasureTheory.ProbabilityMeasure Ω`.
If `Ω` is moreover a topological space and the sigma algebra on `Ω` is finer than the Borel sigma
algebra (i.e. `[OpensMeasurableSpace Ω]`), then `MeasureTheory.ProbabilityMeasure Ω` is
equipped with the topology of weak convergence of measures. Since every probability measure is a
finite measure, this is implemented as the induced topology from the mapping
`MeasureTheory.ProbabilityMeasure.toFiniteMeasure`.
-/
/-- Probability measures are defined as the subtype of measures that have the property of being
probability measures (i.e., their total mass is one). -/
def ProbabilityMeasure (Ω : Type*) [MeasurableSpace Ω] : Type _ :=
{ μ : Measure Ω // IsProbabilityMeasure μ }
#align measure_theory.probability_measure MeasureTheory.ProbabilityMeasure
namespace ProbabilityMeasure
variable {Ω : Type*} [MeasurableSpace Ω]
instance [Inhabited Ω] : Inhabited (ProbabilityMeasure Ω) :=
⟨⟨Measure.dirac default, Measure.dirac.isProbabilityMeasure⟩⟩
-- Porting note: as with other subtype synonyms (e.g., `ℝ≥0`), we need a new function for the
-- coercion instead of relying on `Subtype.val`.
/-- Coercion from `MeasureTheory.ProbabilityMeasure Ω` to `MeasureTheory.Measure Ω`. -/
@[coe]
def toMeasure : ProbabilityMeasure Ω → Measure Ω := Subtype.val
/-- A probability measure can be interpreted as a measure. -/
instance : Coe (ProbabilityMeasure Ω) (MeasureTheory.Measure Ω) where
coe := toMeasure
instance (μ : ProbabilityMeasure Ω) : IsProbabilityMeasure (μ : Measure Ω) :=
μ.prop
@[simp, norm_cast] lemma coe_mk (μ : Measure Ω) (hμ) : toMeasure ⟨μ, hμ⟩ = μ := rfl
@[simp]
theorem val_eq_to_measure (ν : ProbabilityMeasure Ω) : ν.val = (ν : Measure Ω) :=
rfl
#align measure_theory.probability_measure.val_eq_to_measure MeasureTheory.ProbabilityMeasure.val_eq_to_measure
theorem toMeasure_injective : Function.Injective ((↑) : ProbabilityMeasure Ω → Measure Ω) :=
Subtype.coe_injective
#align measure_theory.probability_measure.coe_injective MeasureTheory.ProbabilityMeasure.toMeasure_injective
instance instFunLike : FunLike (ProbabilityMeasure Ω) (Set Ω) ℝ≥0 where
coe μ s := ((μ : Measure Ω) s).toNNReal
coe_injective' μ ν h := toMeasure_injective $ Measure.ext fun s _ ↦ by
simpa [ENNReal.toNNReal_eq_toNNReal_iff, measure_ne_top] using congr_fun h s
lemma coeFn_def (μ : ProbabilityMeasure Ω) : μ = fun s ↦ ((μ : Measure Ω) s).toNNReal := rfl
#align measure_theory.probability_measure.coe_fn_eq_to_nnreal_coe_fn_to_measure MeasureTheory.ProbabilityMeasure.coeFn_def
lemma coeFn_mk (μ : Measure Ω) (hμ) :
DFunLike.coe (F := ProbabilityMeasure Ω) ⟨μ, hμ⟩ = fun s ↦ (μ s).toNNReal := rfl
@[simp, norm_cast]
lemma mk_apply (μ : Measure Ω) (hμ) (s : Set Ω) :
DFunLike.coe (F := ProbabilityMeasure Ω) ⟨μ, hμ⟩ s = (μ s).toNNReal := rfl
@[simp, norm_cast]
theorem coeFn_univ (ν : ProbabilityMeasure Ω) : ν univ = 1 :=
congr_arg ENNReal.toNNReal ν.prop.measure_univ
#align measure_theory.probability_measure.coe_fn_univ MeasureTheory.ProbabilityMeasure.coeFn_univ
theorem coeFn_univ_ne_zero (ν : ProbabilityMeasure Ω) : ν univ ≠ 0 := by
simp only [coeFn_univ, Ne, one_ne_zero, not_false_iff]
#align measure_theory.probability_measure.coe_fn_univ_ne_zero MeasureTheory.ProbabilityMeasure.coeFn_univ_ne_zero
/-- A probability measure can be interpreted as a finite measure. -/
def toFiniteMeasure (μ : ProbabilityMeasure Ω) : FiniteMeasure Ω :=
⟨μ, inferInstance⟩
#align measure_theory.probability_measure.to_finite_measure MeasureTheory.ProbabilityMeasure.toFiniteMeasure
@[simp] lemma coeFn_toFiniteMeasure (μ : ProbabilityMeasure Ω) : ⇑μ.toFiniteMeasure = μ := rfl
lemma toFiniteMeasure_apply (μ : ProbabilityMeasure Ω) (s : Set Ω) :
μ.toFiniteMeasure s = μ s := rfl
@[simp]
theorem toMeasure_comp_toFiniteMeasure_eq_toMeasure (ν : ProbabilityMeasure Ω) :
(ν.toFiniteMeasure : Measure Ω) = (ν : Measure Ω) :=
rfl
#align measure_theory.probability_measure.coe_comp_to_finite_measure_eq_coe MeasureTheory.ProbabilityMeasure.toMeasure_comp_toFiniteMeasure_eq_toMeasure
@[simp]
theorem coeFn_comp_toFiniteMeasure_eq_coeFn (ν : ProbabilityMeasure Ω) :
(ν.toFiniteMeasure : Set Ω → ℝ≥0) = (ν : Set Ω → ℝ≥0) :=
rfl
#align measure_theory.probability_measure.coe_fn_comp_to_finite_measure_eq_coe_fn MeasureTheory.ProbabilityMeasure.coeFn_comp_toFiniteMeasure_eq_coeFn
@[simp]
theorem toFiniteMeasure_apply_eq_apply (ν : ProbabilityMeasure Ω) (s : Set Ω) :
ν.toFiniteMeasure s = ν s := rfl
@[simp]
theorem ennreal_coeFn_eq_coeFn_toMeasure (ν : ProbabilityMeasure Ω) (s : Set Ω) :
(ν s : ℝ≥0∞) = (ν : Measure Ω) s := by
rw [← coeFn_comp_toFiniteMeasure_eq_coeFn, FiniteMeasure.ennreal_coeFn_eq_coeFn_toMeasure,
toMeasure_comp_toFiniteMeasure_eq_toMeasure]
#align measure_theory.probability_measure.ennreal_coe_fn_eq_coe_fn_to_measure MeasureTheory.ProbabilityMeasure.ennreal_coeFn_eq_coeFn_toMeasure
theorem apply_mono (μ : ProbabilityMeasure Ω) {s₁ s₂ : Set Ω} (h : s₁ ⊆ s₂) : μ s₁ ≤ μ s₂ := by
rw [← coeFn_comp_toFiniteMeasure_eq_coeFn]
exact MeasureTheory.FiniteMeasure.apply_mono _ h
#align measure_theory.probability_measure.apply_mono MeasureTheory.ProbabilityMeasure.apply_mono
@[simp] theorem apply_le_one (μ : ProbabilityMeasure Ω) (s : Set Ω) : μ s ≤ 1 := by
simpa using apply_mono μ (subset_univ s)
theorem nonempty (μ : ProbabilityMeasure Ω) : Nonempty Ω := by
by_contra maybe_empty
have zero : (μ : Measure Ω) univ = 0 := by
rw [univ_eq_empty_iff.mpr (not_nonempty_iff.mp maybe_empty), measure_empty]
rw [measure_univ] at zero
exact zero_ne_one zero.symm
#align measure_theory.probability_measure.nonempty_of_probability_measure MeasureTheory.ProbabilityMeasure.nonempty
@[ext]
theorem eq_of_forall_toMeasure_apply_eq (μ ν : ProbabilityMeasure Ω)
(h : ∀ s : Set Ω, MeasurableSet s → (μ : Measure Ω) s = (ν : Measure Ω) s) : μ = ν := by
apply toMeasure_injective
ext1 s s_mble
exact h s s_mble
#align measure_theory.probability_measure.eq_of_forall_measure_apply_eq MeasureTheory.ProbabilityMeasure.eq_of_forall_toMeasure_apply_eq
theorem eq_of_forall_apply_eq (μ ν : ProbabilityMeasure Ω)
(h : ∀ s : Set Ω, MeasurableSet s → μ s = ν s) : μ = ν := by
ext1 s s_mble
simpa [ennreal_coeFn_eq_coeFn_toMeasure] using congr_arg ((↑) : ℝ≥0 → ℝ≥0∞) (h s s_mble)
#align measure_theory.probability_measure.eq_of_forall_apply_eq MeasureTheory.ProbabilityMeasure.eq_of_forall_apply_eq
@[simp]
theorem mass_toFiniteMeasure (μ : ProbabilityMeasure Ω) : μ.toFiniteMeasure.mass = 1 :=
μ.coeFn_univ
#align measure_theory.probability_measure.mass_to_finite_measure MeasureTheory.ProbabilityMeasure.mass_toFiniteMeasure
theorem toFiniteMeasure_nonzero (μ : ProbabilityMeasure Ω) : μ.toFiniteMeasure ≠ 0 := by
rw [← FiniteMeasure.mass_nonzero_iff, μ.mass_toFiniteMeasure]
exact one_ne_zero
#align measure_theory.probability_measure.to_finite_measure_nonzero MeasureTheory.ProbabilityMeasure.toFiniteMeasure_nonzero
section convergence_in_distribution
variable [TopologicalSpace Ω] [OpensMeasurableSpace Ω]
theorem testAgainstNN_lipschitz (μ : ProbabilityMeasure Ω) :
LipschitzWith 1 fun f : Ω →ᵇ ℝ≥0 => μ.toFiniteMeasure.testAgainstNN f :=
μ.mass_toFiniteMeasure ▸ μ.toFiniteMeasure.testAgainstNN_lipschitz
#align measure_theory.probability_measure.test_against_nn_lipschitz MeasureTheory.ProbabilityMeasure.testAgainstNN_lipschitz
/-- The topology of weak convergence on `MeasureTheory.ProbabilityMeasure Ω`. This is inherited
(induced) from the topology of weak convergence of finite measures via the inclusion
`MeasureTheory.ProbabilityMeasure.toFiniteMeasure`. -/
instance : TopologicalSpace (ProbabilityMeasure Ω) :=
TopologicalSpace.induced toFiniteMeasure inferInstance
theorem toFiniteMeasure_continuous :
Continuous (toFiniteMeasure : ProbabilityMeasure Ω → FiniteMeasure Ω) :=
continuous_induced_dom
#align measure_theory.probability_measure.to_finite_measure_continuous MeasureTheory.ProbabilityMeasure.toFiniteMeasure_continuous
/-- Probability measures yield elements of the `WeakDual` of bounded continuous nonnegative
functions via `MeasureTheory.FiniteMeasure.testAgainstNN`, i.e., integration. -/
def toWeakDualBCNN : ProbabilityMeasure Ω → WeakDual ℝ≥0 (Ω →ᵇ ℝ≥0) :=
FiniteMeasure.toWeakDualBCNN ∘ toFiniteMeasure
#align measure_theory.probability_measure.to_weak_dual_bcnn MeasureTheory.ProbabilityMeasure.toWeakDualBCNN
@[simp]
theorem coe_toWeakDualBCNN (μ : ProbabilityMeasure Ω) :
⇑μ.toWeakDualBCNN = μ.toFiniteMeasure.testAgainstNN :=
rfl
#align measure_theory.probability_measure.coe_to_weak_dual_bcnn MeasureTheory.ProbabilityMeasure.coe_toWeakDualBCNN
@[simp]
theorem toWeakDualBCNN_apply (μ : ProbabilityMeasure Ω) (f : Ω →ᵇ ℝ≥0) :
μ.toWeakDualBCNN f = (∫⁻ ω, f ω ∂(μ : Measure Ω)).toNNReal :=
rfl
#align measure_theory.probability_measure.to_weak_dual_bcnn_apply MeasureTheory.ProbabilityMeasure.toWeakDualBCNN_apply
theorem toWeakDualBCNN_continuous : Continuous fun μ : ProbabilityMeasure Ω => μ.toWeakDualBCNN :=
FiniteMeasure.toWeakDualBCNN_continuous.comp toFiniteMeasure_continuous
#align measure_theory.probability_measure.to_weak_dual_bcnn_continuous MeasureTheory.ProbabilityMeasure.toWeakDualBCNN_continuous
/- Integration of (nonnegative bounded continuous) test functions against Borel probability
measures depends continuously on the measure. -/
theorem continuous_testAgainstNN_eval (f : Ω →ᵇ ℝ≥0) :
Continuous fun μ : ProbabilityMeasure Ω => μ.toFiniteMeasure.testAgainstNN f :=
(FiniteMeasure.continuous_testAgainstNN_eval f).comp toFiniteMeasure_continuous
#align measure_theory.probability_measure.continuous_test_against_nn_eval MeasureTheory.ProbabilityMeasure.continuous_testAgainstNN_eval
-- The canonical mapping from probability measures to finite measures is an embedding.
theorem toFiniteMeasure_embedding (Ω : Type*) [MeasurableSpace Ω] [TopologicalSpace Ω]
[OpensMeasurableSpace Ω] :
Embedding (toFiniteMeasure : ProbabilityMeasure Ω → FiniteMeasure Ω) :=
{ induced := rfl
inj := fun _μ _ν h => Subtype.eq <| congr_arg FiniteMeasure.toMeasure h }
#align measure_theory.probability_measure.to_finite_measure_embedding MeasureTheory.ProbabilityMeasure.toFiniteMeasure_embedding
theorem tendsto_nhds_iff_toFiniteMeasure_tendsto_nhds {δ : Type*} (F : Filter δ)
{μs : δ → ProbabilityMeasure Ω} {μ₀ : ProbabilityMeasure Ω} :
Tendsto μs F (𝓝 μ₀) ↔ Tendsto (toFiniteMeasure ∘ μs) F (𝓝 μ₀.toFiniteMeasure) :=
Embedding.tendsto_nhds_iff (toFiniteMeasure_embedding Ω)
#align measure_theory.probability_measure.tendsto_nhds_iff_to_finite_measures_tendsto_nhds MeasureTheory.ProbabilityMeasure.tendsto_nhds_iff_toFiniteMeasure_tendsto_nhds
/-- A characterization of weak convergence of probability measures by the condition that the
integrals of every continuous bounded nonnegative function converge to the integral of the function
against the limit measure. -/
theorem tendsto_iff_forall_lintegral_tendsto {γ : Type*} {F : Filter γ}
{μs : γ → ProbabilityMeasure Ω} {μ : ProbabilityMeasure Ω} :
Tendsto μs F (𝓝 μ) ↔
∀ f : Ω →ᵇ ℝ≥0,
Tendsto (fun i => ∫⁻ ω, f ω ∂(μs i : Measure Ω)) F (𝓝 (∫⁻ ω, f ω ∂(μ : Measure Ω))) := by
rw [tendsto_nhds_iff_toFiniteMeasure_tendsto_nhds]
exact FiniteMeasure.tendsto_iff_forall_lintegral_tendsto
#align measure_theory.probability_measure.tendsto_iff_forall_lintegral_tendsto MeasureTheory.ProbabilityMeasure.tendsto_iff_forall_lintegral_tendsto
/-- The characterization of weak convergence of probability measures by the usual (defining)
condition that the integrals of every continuous bounded function converge to the integral of the
function against the limit measure. -/
theorem tendsto_iff_forall_integral_tendsto {γ : Type*} {F : Filter γ}
{μs : γ → ProbabilityMeasure Ω} {μ : ProbabilityMeasure Ω} :
Tendsto μs F (𝓝 μ) ↔
∀ f : Ω →ᵇ ℝ,
Tendsto (fun i => ∫ ω, f ω ∂(μs i : Measure Ω)) F (𝓝 (∫ ω, f ω ∂(μ : Measure Ω))) := by
rw [tendsto_nhds_iff_toFiniteMeasure_tendsto_nhds]
rw [FiniteMeasure.tendsto_iff_forall_integral_tendsto]
rfl
#align measure_theory.probability_measure.tendsto_iff_forall_integral_tendsto MeasureTheory.ProbabilityMeasure.tendsto_iff_forall_integral_tendsto
end convergence_in_distribution -- section
section Hausdorff
variable [TopologicalSpace Ω] [HasOuterApproxClosed Ω] [BorelSpace Ω]
variable (Ω)
/-- On topological spaces where indicators of closed sets have decreasing approximating sequences of
continuous functions (`HasOuterApproxClosed`), the topology of convergence in distribution of Borel
probability measures is Hausdorff (`T2Space`). -/
instance t2Space : T2Space (ProbabilityMeasure Ω) :=
Embedding.t2Space (toFiniteMeasure_embedding Ω)
end Hausdorff -- section
end ProbabilityMeasure
-- namespace
end ProbabilityMeasure
-- section
section NormalizeFiniteMeasure
/-! ### Normalization of finite measures to probability measures
This section is about normalizing finite measures to probability measures.
The weak convergence of finite measures to nonzero limit measures is characterized by
the convergence of the total mass and the convergence of the normalized probability
measures.
-/
namespace FiniteMeasure
variable {Ω : Type*} [Nonempty Ω] {m0 : MeasurableSpace Ω} (μ : FiniteMeasure Ω)
/-- Normalize a finite measure so that it becomes a probability measure, i.e., divide by the
total mass. -/
def normalize : ProbabilityMeasure Ω :=
if zero : μ.mass = 0 then ⟨Measure.dirac ‹Nonempty Ω›.some, Measure.dirac.isProbabilityMeasure⟩
else
{ val := ↑(μ.mass⁻¹ • μ)
property := by
refine ⟨?_⟩
-- Porting note: paying the price that this isn't `simp` lemma now.
rw [FiniteMeasure.toMeasure_smul]
simp only [Measure.coe_smul, Pi.smul_apply, Measure.nnreal_smul_coe_apply, ne_eq,
mass_zero_iff, ENNReal.coe_inv zero, ennreal_mass]
rw [← Ne, ← ENNReal.coe_ne_zero, ennreal_mass] at zero
exact ENNReal.inv_mul_cancel zero μ.prop.measure_univ_lt_top.ne }
#align measure_theory.finite_measure.normalize MeasureTheory.FiniteMeasure.normalize
@[simp]
theorem self_eq_mass_mul_normalize (s : Set Ω) : μ s = μ.mass * μ.normalize s := by
obtain rfl | h := eq_or_ne μ 0
· simp
have mass_nonzero : μ.mass ≠ 0 := by rwa [μ.mass_nonzero_iff]
simp only [normalize, dif_neg mass_nonzero]
simp [ProbabilityMeasure.coe_mk, toMeasure_smul, mul_inv_cancel_left₀ mass_nonzero, coeFn_def]
#align measure_theory.finite_measure.self_eq_mass_mul_normalize MeasureTheory.FiniteMeasure.self_eq_mass_mul_normalize
theorem self_eq_mass_smul_normalize : μ = μ.mass • μ.normalize.toFiniteMeasure := by
apply eq_of_forall_apply_eq
intro s _s_mble
rw [μ.self_eq_mass_mul_normalize s, smul_apply, smul_eq_mul,
ProbabilityMeasure.coeFn_comp_toFiniteMeasure_eq_coeFn]
#align measure_theory.finite_measure.self_eq_mass_smul_normalize MeasureTheory.FiniteMeasure.self_eq_mass_smul_normalize
| Mathlib/MeasureTheory/Measure/ProbabilityMeasure.lean | 395 | 397 | theorem normalize_eq_of_nonzero (nonzero : μ ≠ 0) (s : Set Ω) : μ.normalize s = μ.mass⁻¹ * μ s := by |
simp only [μ.self_eq_mass_mul_normalize, μ.mass_nonzero_iff.mpr nonzero, inv_mul_cancel_left₀,
Ne, not_false_iff]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Data.Nat.ModEq
import Mathlib.Tactic.Abel
import Mathlib.Tactic.GCongr.Core
#align_import data.int.modeq from "leanprover-community/mathlib"@"47a1a73351de8dd6c8d3d32b569c8e434b03ca47"
/-!
# Congruences modulo an integer
This file defines the equivalence relation `a ≡ b [ZMOD n]` on the integers, similarly to how
`Data.Nat.ModEq` defines them for the natural numbers. The notation is short for `n.ModEq a b`,
which is defined to be `a % n = b % n` for integers `a b n`.
## Tags
modeq, congruence, mod, MOD, modulo, integers
-/
namespace Int
/-- `a ≡ b [ZMOD n]` when `a % n = b % n`. -/
def ModEq (n a b : ℤ) :=
a % n = b % n
#align int.modeq Int.ModEq
@[inherit_doc]
notation:50 a " ≡ " b " [ZMOD " n "]" => ModEq n a b
variable {m n a b c d : ℤ}
-- Porting note: This instance should be derivable automatically
instance : Decidable (ModEq n a b) := decEq (a % n) (b % n)
namespace ModEq
@[refl, simp]
protected theorem refl (a : ℤ) : a ≡ a [ZMOD n] :=
@rfl _ _
#align int.modeq.refl Int.ModEq.refl
protected theorem rfl : a ≡ a [ZMOD n] :=
ModEq.refl _
#align int.modeq.rfl Int.ModEq.rfl
instance : IsRefl _ (ModEq n) :=
⟨ModEq.refl⟩
@[symm]
protected theorem symm : a ≡ b [ZMOD n] → b ≡ a [ZMOD n] :=
Eq.symm
#align int.modeq.symm Int.ModEq.symm
@[trans]
protected theorem trans : a ≡ b [ZMOD n] → b ≡ c [ZMOD n] → a ≡ c [ZMOD n] :=
Eq.trans
#align int.modeq.trans Int.ModEq.trans
instance : IsTrans ℤ (ModEq n) where
trans := @Int.ModEq.trans n
protected theorem eq : a ≡ b [ZMOD n] → a % n = b % n := id
#align int.modeq.eq Int.ModEq.eq
end ModEq
theorem modEq_comm : a ≡ b [ZMOD n] ↔ b ≡ a [ZMOD n] := ⟨ModEq.symm, ModEq.symm⟩
#align int.modeq_comm Int.modEq_comm
theorem natCast_modEq_iff {a b n : ℕ} : a ≡ b [ZMOD n] ↔ a ≡ b [MOD n] := by
unfold ModEq Nat.ModEq; rw [← Int.ofNat_inj]; simp [natCast_mod]
#align int.coe_nat_modeq_iff Int.natCast_modEq_iff
theorem modEq_zero_iff_dvd : a ≡ 0 [ZMOD n] ↔ n ∣ a := by
rw [ModEq, zero_emod, dvd_iff_emod_eq_zero]
#align int.modeq_zero_iff_dvd Int.modEq_zero_iff_dvd
theorem _root_.Dvd.dvd.modEq_zero_int (h : n ∣ a) : a ≡ 0 [ZMOD n] :=
modEq_zero_iff_dvd.2 h
#align has_dvd.dvd.modeq_zero_int Dvd.dvd.modEq_zero_int
theorem _root_.Dvd.dvd.zero_modEq_int (h : n ∣ a) : 0 ≡ a [ZMOD n] :=
h.modEq_zero_int.symm
#align has_dvd.dvd.zero_modeq_int Dvd.dvd.zero_modEq_int
theorem modEq_iff_dvd : a ≡ b [ZMOD n] ↔ n ∣ b - a := by
rw [ModEq, eq_comm]
simp [emod_eq_emod_iff_emod_sub_eq_zero, dvd_iff_emod_eq_zero]
#align int.modeq_iff_dvd Int.modEq_iff_dvd
theorem modEq_iff_add_fac {a b n : ℤ} : a ≡ b [ZMOD n] ↔ ∃ t, b = a + n * t := by
rw [modEq_iff_dvd]
exact exists_congr fun t => sub_eq_iff_eq_add'
#align int.modeq_iff_add_fac Int.modEq_iff_add_fac
alias ⟨ModEq.dvd, modEq_of_dvd⟩ := modEq_iff_dvd
#align int.modeq.dvd Int.ModEq.dvd
#align int.modeq_of_dvd Int.modEq_of_dvd
theorem mod_modEq (a n) : a % n ≡ a [ZMOD n] :=
emod_emod _ _
#align int.mod_modeq Int.mod_modEq
@[simp]
theorem neg_modEq_neg : -a ≡ -b [ZMOD n] ↔ a ≡ b [ZMOD n] := by
-- Porting note: Restore old proof once #3309 is through
simp [-sub_neg_eq_add, neg_sub_neg, modEq_iff_dvd, dvd_sub_comm]
#align int.neg_modeq_neg Int.neg_modEq_neg
@[simp]
| Mathlib/Data/Int/ModEq.lean | 118 | 118 | theorem modEq_neg : a ≡ b [ZMOD -n] ↔ a ≡ b [ZMOD n] := by | simp [modEq_iff_dvd]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Floris van Doorn, Sébastien Gouëzel, Alex J. Best
-/
import Mathlib.Algebra.Divisibility.Basic
import Mathlib.Algebra.Group.Int
import Mathlib.Algebra.Group.Nat
import Mathlib.Algebra.Group.Opposite
import Mathlib.Algebra.Group.Units
import Mathlib.Data.List.Perm
import Mathlib.Data.List.ProdSigma
import Mathlib.Data.List.Range
import Mathlib.Data.List.Rotate
#align_import data.list.big_operators.basic from "leanprover-community/mathlib"@"6c5f73fd6f6cc83122788a80a27cdd54663609f4"
/-!
# Sums and products from lists
This file provides basic results about `List.prod`, `List.sum`, which calculate the product and sum
of elements of a list and `List.alternatingProd`, `List.alternatingSum`, their alternating
counterparts.
-/
-- Make sure we haven't imported `Data.Nat.Order.Basic`
assert_not_exists OrderedSub
assert_not_exists Ring
variable {ι α β M N P G : Type*}
namespace List
section Defs
/-- Product of a list.
`List.prod [a, b, c] = ((1 * a) * b) * c` -/
@[to_additive "Sum of a list.\n\n`List.sum [a, b, c] = ((0 + a) + b) + c`"]
def prod {α} [Mul α] [One α] : List α → α :=
foldl (· * ·) 1
#align list.prod List.prod
#align list.sum List.sum
/-- The alternating sum of a list. -/
def alternatingSum {G : Type*} [Zero G] [Add G] [Neg G] : List G → G
| [] => 0
| g :: [] => g
| g :: h :: t => g + -h + alternatingSum t
#align list.alternating_sum List.alternatingSum
/-- The alternating product of a list. -/
@[to_additive existing]
def alternatingProd {G : Type*} [One G] [Mul G] [Inv G] : List G → G
| [] => 1
| g :: [] => g
| g :: h :: t => g * h⁻¹ * alternatingProd t
#align list.alternating_prod List.alternatingProd
end Defs
section MulOneClass
variable [MulOneClass M] {l : List M} {a : M}
@[to_additive (attr := simp)]
theorem prod_nil : ([] : List M).prod = 1 :=
rfl
#align list.prod_nil List.prod_nil
#align list.sum_nil List.sum_nil
@[to_additive]
theorem prod_singleton : [a].prod = a :=
one_mul a
#align list.prod_singleton List.prod_singleton
#align list.sum_singleton List.sum_singleton
@[to_additive (attr := simp)]
theorem prod_one_cons : (1 :: l).prod = l.prod := by
rw [prod, foldl, mul_one]
@[to_additive]
theorem prod_map_one {l : List ι} :
(l.map fun _ => (1 : M)).prod = 1 := by
induction l with
| nil => rfl
| cons hd tl ih => rw [map_cons, prod_one_cons, ih]
end MulOneClass
section Monoid
variable [Monoid M] [Monoid N] [Monoid P] {l l₁ l₂ : List M} {a : M}
@[to_additive (attr := simp)]
theorem prod_cons : (a :: l).prod = a * l.prod :=
calc
(a :: l).prod = foldl (· * ·) (a * 1) l := by
simp only [List.prod, foldl_cons, one_mul, mul_one]
_ = _ := foldl_assoc
#align list.prod_cons List.prod_cons
#align list.sum_cons List.sum_cons
@[to_additive]
lemma prod_induction
(p : M → Prop) (hom : ∀ a b, p a → p b → p (a * b)) (unit : p 1) (base : ∀ x ∈ l, p x) :
p l.prod := by
induction' l with a l ih
· simpa
rw [List.prod_cons]
simp only [Bool.not_eq_true, List.mem_cons, forall_eq_or_imp] at base
exact hom _ _ (base.1) (ih base.2)
@[to_additive (attr := simp)]
theorem prod_append : (l₁ ++ l₂).prod = l₁.prod * l₂.prod :=
calc
(l₁ ++ l₂).prod = foldl (· * ·) (foldl (· * ·) 1 l₁ * 1) l₂ := by simp [List.prod]
_ = l₁.prod * l₂.prod := foldl_assoc
#align list.prod_append List.prod_append
#align list.sum_append List.sum_append
@[to_additive]
theorem prod_concat : (l.concat a).prod = l.prod * a := by
rw [concat_eq_append, prod_append, prod_singleton]
#align list.prod_concat List.prod_concat
#align list.sum_concat List.sum_concat
@[to_additive (attr := simp)]
theorem prod_join {l : List (List M)} : l.join.prod = (l.map List.prod).prod := by
induction l <;> [rfl; simp only [*, List.join, map, prod_append, prod_cons]]
#align list.prod_join List.prod_join
#align list.sum_join List.sum_join
@[to_additive]
theorem prod_eq_foldr : ∀ {l : List M}, l.prod = foldr (· * ·) 1 l
| [] => rfl
| cons a l => by rw [prod_cons, foldr_cons, prod_eq_foldr]
#align list.prod_eq_foldr List.prod_eq_foldr
#align list.sum_eq_foldr List.sum_eq_foldr
@[to_additive (attr := simp)]
theorem prod_replicate (n : ℕ) (a : M) : (replicate n a).prod = a ^ n := by
induction' n with n ih
· rw [pow_zero]
rfl
· rw [replicate_succ, prod_cons, ih, pow_succ']
#align list.prod_replicate List.prod_replicate
#align list.sum_replicate List.sum_replicate
@[to_additive sum_eq_card_nsmul]
theorem prod_eq_pow_card (l : List M) (m : M) (h : ∀ x ∈ l, x = m) : l.prod = m ^ l.length := by
rw [← prod_replicate, ← List.eq_replicate.mpr ⟨rfl, h⟩]
#align list.prod_eq_pow_card List.prod_eq_pow_card
#align list.sum_eq_card_nsmul List.sum_eq_card_nsmul
@[to_additive]
theorem prod_hom_rel (l : List ι) {r : M → N → Prop} {f : ι → M} {g : ι → N} (h₁ : r 1 1)
(h₂ : ∀ ⦃i a b⦄, r a b → r (f i * a) (g i * b)) : r (l.map f).prod (l.map g).prod :=
List.recOn l h₁ fun a l hl => by simp only [map_cons, prod_cons, h₂ hl]
#align list.prod_hom_rel List.prod_hom_rel
#align list.sum_hom_rel List.sum_hom_rel
@[to_additive]
theorem rel_prod {R : M → N → Prop} (h : R 1 1) (hf : (R ⇒ R ⇒ R) (· * ·) (· * ·)) :
(Forall₂ R ⇒ R) prod prod :=
rel_foldl hf h
#align list.rel_prod List.rel_prod
#align list.rel_sum List.rel_sum
@[to_additive]
theorem prod_hom (l : List M) {F : Type*} [FunLike F M N] [MonoidHomClass F M N] (f : F) :
(l.map f).prod = f l.prod := by
simp only [prod, foldl_map, ← map_one f]
exact l.foldl_hom f (· * ·) (· * f ·) 1 (fun x y => (map_mul f x y).symm)
#align list.prod_hom List.prod_hom
#align list.sum_hom List.sum_hom
@[to_additive]
theorem prod_hom₂ (l : List ι) (f : M → N → P) (hf : ∀ a b c d, f (a * b) (c * d) = f a c * f b d)
(hf' : f 1 1 = 1) (f₁ : ι → M) (f₂ : ι → N) :
(l.map fun i => f (f₁ i) (f₂ i)).prod = f (l.map f₁).prod (l.map f₂).prod := by
simp only [prod, foldl_map]
-- Porting note: next 3 lines used to be
-- convert l.foldl_hom₂ (fun a b => f a b) _ _ _ _ _ fun a b i => _
-- · exact hf'.symm
-- · exact hf _ _ _ _
rw [← l.foldl_hom₂ (fun a b => f a b), hf']
intros
exact hf _ _ _ _
#align list.prod_hom₂ List.prod_hom₂
#align list.sum_hom₂ List.sum_hom₂
@[to_additive (attr := simp)]
theorem prod_map_mul {α : Type*} [CommMonoid α] {l : List ι} {f g : ι → α} :
(l.map fun i => f i * g i).prod = (l.map f).prod * (l.map g).prod :=
l.prod_hom₂ (· * ·) mul_mul_mul_comm (mul_one _) _ _
#align list.prod_map_mul List.prod_map_mul
#align list.sum_map_add List.sum_map_add
@[to_additive]
theorem prod_map_hom (L : List ι) (f : ι → M) {G : Type*} [FunLike G M N] [MonoidHomClass G M N]
(g : G) :
(L.map (g ∘ f)).prod = g (L.map f).prod := by rw [← prod_hom, map_map]
#align list.prod_map_hom List.prod_map_hom
#align list.sum_map_hom List.sum_map_hom
@[to_additive]
theorem prod_isUnit : ∀ {L : List M}, (∀ m ∈ L, IsUnit m) → IsUnit L.prod
| [], _ => by simp
| h :: t, u => by
simp only [List.prod_cons]
exact IsUnit.mul (u h (mem_cons_self h t)) (prod_isUnit fun m mt => u m (mem_cons_of_mem h mt))
#align list.prod_is_unit List.prod_isUnit
#align list.sum_is_add_unit List.sum_isAddUnit
@[to_additive]
theorem prod_isUnit_iff {α : Type*} [CommMonoid α] {L : List α} :
IsUnit L.prod ↔ ∀ m ∈ L, IsUnit m := by
refine ⟨fun h => ?_, prod_isUnit⟩
induction' L with m L ih
· exact fun m' h' => False.elim (not_mem_nil m' h')
rw [prod_cons, IsUnit.mul_iff] at h
exact fun m' h' => Or.elim (eq_or_mem_of_mem_cons h') (fun H => H.substr h.1) fun H => ih h.2 _ H
#align list.prod_is_unit_iff List.prod_isUnit_iff
#align list.sum_is_add_unit_iff List.sum_isAddUnit_iff
@[to_additive (attr := simp)]
theorem prod_take_mul_prod_drop : ∀ (L : List M) (i : ℕ), (L.take i).prod * (L.drop i).prod = L.prod
| [], i => by simp [Nat.zero_le]
| L, 0 => by simp
| h :: t, n + 1 => by
dsimp
rw [prod_cons, prod_cons, mul_assoc, prod_take_mul_prod_drop t]
#align list.prod_take_mul_prod_drop List.prod_take_mul_prod_drop
#align list.sum_take_add_sum_drop List.sum_take_add_sum_drop
@[to_additive (attr := simp)]
theorem prod_take_succ :
∀ (L : List M) (i : ℕ) (p), (L.take (i + 1)).prod = (L.take i).prod * L.get ⟨i, p⟩
| [], i, p => by cases p
| h :: t, 0, _ => rfl
| h :: t, n + 1, p => by
dsimp
rw [prod_cons, prod_cons, prod_take_succ t n (Nat.lt_of_succ_lt_succ p), mul_assoc]
#align list.prod_take_succ List.prod_take_succ
#align list.sum_take_succ List.sum_take_succ
/-- A list with product not one must have positive length. -/
@[to_additive "A list with sum not zero must have positive length."]
theorem length_pos_of_prod_ne_one (L : List M) (h : L.prod ≠ 1) : 0 < L.length := by
cases L
· simp at h
· simp
#align list.length_pos_of_prod_ne_one List.length_pos_of_prod_ne_one
#align list.length_pos_of_sum_ne_zero List.length_pos_of_sum_ne_zero
/-- A list with product greater than one must have positive length. -/
@[to_additive length_pos_of_sum_pos "A list with positive sum must have positive length."]
theorem length_pos_of_one_lt_prod [Preorder M] (L : List M) (h : 1 < L.prod) : 0 < L.length :=
length_pos_of_prod_ne_one L h.ne'
#align list.length_pos_of_one_lt_prod List.length_pos_of_one_lt_prod
#align list.length_pos_of_sum_pos List.length_pos_of_sum_pos
/-- A list with product less than one must have positive length. -/
@[to_additive "A list with negative sum must have positive length."]
theorem length_pos_of_prod_lt_one [Preorder M] (L : List M) (h : L.prod < 1) : 0 < L.length :=
length_pos_of_prod_ne_one L h.ne
#align list.length_pos_of_prod_lt_one List.length_pos_of_prod_lt_one
#align list.length_pos_of_sum_neg List.length_pos_of_sum_neg
@[to_additive]
theorem prod_set :
∀ (L : List M) (n : ℕ) (a : M),
(L.set n a).prod =
((L.take n).prod * if n < L.length then a else 1) * (L.drop (n + 1)).prod
| x :: xs, 0, a => by simp [set]
| x :: xs, i + 1, a => by
simp [set, prod_set xs i a, mul_assoc, Nat.succ_eq_add_one, Nat.add_lt_add_iff_right]
| [], _, _ => by simp [set, (Nat.zero_le _).not_lt, Nat.zero_le]
#align list.prod_update_nth List.prod_set
#align list.sum_update_nth List.sum_set
/-- We'd like to state this as `L.headI * L.tail.prod = L.prod`, but because `L.headI` relies on an
inhabited instance to return a garbage value on the empty list, this is not possible.
Instead, we write the statement in terms of `(L.get? 0).getD 1`.
-/
@[to_additive "We'd like to state this as `L.headI + L.tail.sum = L.sum`, but because `L.headI`
relies on an inhabited instance to return a garbage value on the empty list, this is not possible.
Instead, we write the statement in terms of `(L.get? 0).getD 0`."]
theorem get?_zero_mul_tail_prod (l : List M) : (l.get? 0).getD 1 * l.tail.prod = l.prod := by
cases l <;> simp
#align list.nth_zero_mul_tail_prod List.get?_zero_mul_tail_prod
#align list.nth_zero_add_tail_sum List.get?_zero_add_tail_sum
/-- Same as `get?_zero_mul_tail_prod`, but avoiding the `List.headI` garbage complication by
requiring the list to be nonempty. -/
@[to_additive "Same as `get?_zero_add_tail_sum`, but avoiding the `List.headI` garbage complication
by requiring the list to be nonempty."]
theorem headI_mul_tail_prod_of_ne_nil [Inhabited M] (l : List M) (h : l ≠ []) :
l.headI * l.tail.prod = l.prod := by cases l <;> [contradiction; simp]
#align list.head_mul_tail_prod_of_ne_nil List.headI_mul_tail_prod_of_ne_nil
#align list.head_add_tail_sum_of_ne_nil List.headI_add_tail_sum_of_ne_nil
@[to_additive]
theorem _root_.Commute.list_prod_right (l : List M) (y : M) (h : ∀ x ∈ l, Commute y x) :
Commute y l.prod := by
induction' l with z l IH
· simp
· rw [List.forall_mem_cons] at h
rw [List.prod_cons]
exact Commute.mul_right h.1 (IH h.2)
#align commute.list_prod_right Commute.list_prod_right
#align add_commute.list_sum_right AddCommute.list_sum_right
@[to_additive]
theorem _root_.Commute.list_prod_left (l : List M) (y : M) (h : ∀ x ∈ l, Commute x y) :
Commute l.prod y :=
((Commute.list_prod_right _ _) fun _ hx => (h _ hx).symm).symm
#align commute.list_prod_left Commute.list_prod_left
#align add_commute.list_sum_left AddCommute.list_sum_left
@[to_additive] lemma prod_range_succ (f : ℕ → M) (n : ℕ) :
((range n.succ).map f).prod = ((range n).map f).prod * f n := by
rw [range_succ, map_append, map_singleton, prod_append, prod_cons, prod_nil, mul_one]
#align list.prod_range_succ List.prod_range_succ
#align list.sum_range_succ List.sum_range_succ
/-- A variant of `prod_range_succ` which pulls off the first term in the product rather than the
last. -/
@[to_additive
"A variant of `sum_range_succ` which pulls off the first term in the sum rather than the last."]
lemma prod_range_succ' (f : ℕ → M) (n : ℕ) :
((range n.succ).map f).prod = f 0 * ((range n).map fun i ↦ f i.succ).prod :=
Nat.recOn n (show 1 * f 0 = f 0 * 1 by rw [one_mul, mul_one]) fun _ hd => by
rw [List.prod_range_succ, hd, mul_assoc, ← List.prod_range_succ]
#align list.prod_range_succ' List.prod_range_succ'
#align list.sum_range_succ' List.sum_range_succ'
@[to_additive] lemma prod_eq_one (hl : ∀ x ∈ l, x = 1) : l.prod = 1 := by
induction' l with i l hil
· rfl
rw [List.prod_cons, hil fun x hx ↦ hl _ (mem_cons_of_mem i hx), hl _ (mem_cons_self i l), one_mul]
#align list.prod_eq_one List.prod_eq_one
#align list.sum_eq_zero List.sum_eq_zero
@[to_additive] lemma exists_mem_ne_one_of_prod_ne_one (h : l.prod ≠ 1) :
∃ x ∈ l, x ≠ (1 : M) := by simpa only [not_forall, exists_prop] using mt prod_eq_one h
#align list.exists_mem_ne_one_of_prod_ne_one List.exists_mem_ne_one_of_prod_ne_one
#align list.exists_mem_ne_zero_of_sum_ne_zero List.exists_mem_ne_zero_of_sum_ne_zero
@[to_additive]
lemma prod_erase_of_comm [DecidableEq M] (ha : a ∈ l) (comm : ∀ x ∈ l, ∀ y ∈ l, x * y = y * x) :
a * (l.erase a).prod = l.prod := by
induction' l with b l ih
· simp only [not_mem_nil] at ha
obtain rfl | ⟨ne, h⟩ := List.eq_or_ne_mem_of_mem ha
· simp only [erase_cons_head, prod_cons]
rw [List.erase, beq_false_of_ne ne.symm, List.prod_cons, List.prod_cons, ← mul_assoc,
comm a ha b (l.mem_cons_self b), mul_assoc,
ih h fun x hx y hy ↦ comm _ (List.mem_cons_of_mem b hx) _ (List.mem_cons_of_mem b hy)]
@[to_additive]
lemma prod_map_eq_pow_single [DecidableEq α] {l : List α} (a : α) (f : α → M)
(hf : ∀ a', a' ≠ a → a' ∈ l → f a' = 1) : (l.map f).prod = f a ^ l.count a := by
induction' l with a' as h generalizing a
· rw [map_nil, prod_nil, count_nil, _root_.pow_zero]
· specialize h a fun a' ha' hfa' => hf a' ha' (mem_cons_of_mem _ hfa')
rw [List.map_cons, List.prod_cons, count_cons, h]
split_ifs with ha'
· rw [ha', _root_.pow_succ']
· rw [hf a' (Ne.symm ha') (List.mem_cons_self a' as), one_mul, add_zero]
#align list.prod_map_eq_pow_single List.prod_map_eq_pow_single
#align list.sum_map_eq_nsmul_single List.sum_map_eq_nsmul_single
@[to_additive]
lemma prod_eq_pow_single [DecidableEq M] (a : M) (h : ∀ a', a' ≠ a → a' ∈ l → a' = 1) :
l.prod = a ^ l.count a :=
_root_.trans (by rw [map_id]) (prod_map_eq_pow_single a id h)
#align list.prod_eq_pow_single List.prod_eq_pow_single
#align list.sum_eq_nsmul_single List.sum_eq_nsmul_single
/-- If elements of a list commute with each other, then their product does not
depend on the order of elements. -/
@[to_additive "If elements of a list additively commute with each other, then their sum does not
depend on the order of elements."]
lemma Perm.prod_eq' (h : l₁ ~ l₂) (hc : l₁.Pairwise Commute) : l₁.prod = l₂.prod := by
refine h.foldl_eq' ?_ _
apply Pairwise.forall_of_forall
· intro x y h z
exact (h z).symm
· intros; rfl
· apply hc.imp
intro a b h z
rw [mul_assoc z, mul_assoc z, h]
#align list.perm.prod_eq' List.Perm.prod_eq'
#align list.perm.sum_eq' List.Perm.sum_eq'
end Monoid
section CommMonoid
variable [CommMonoid M] {a : M} {l l₁ l₂ : List M}
@[to_additive (attr := simp)]
lemma prod_erase [DecidableEq M] (ha : a ∈ l) : a * (l.erase a).prod = l.prod :=
prod_erase_of_comm ha fun x _ y _ ↦ mul_comm x y
#align list.prod_erase List.prod_erase
#align list.sum_erase List.sum_erase
@[to_additive (attr := simp)]
lemma prod_map_erase [DecidableEq α] (f : α → M) {a} :
∀ {l : List α}, a ∈ l → f a * ((l.erase a).map f).prod = (l.map f).prod
| b :: l, h => by
obtain rfl | ⟨ne, h⟩ := List.eq_or_ne_mem_of_mem h
· simp only [map, erase_cons_head, prod_cons]
· simp only [map, erase_cons_tail _ (not_beq_of_ne ne.symm), prod_cons, prod_map_erase _ h,
mul_left_comm (f a) (f b)]
#align list.prod_map_erase List.prod_map_erase
#align list.sum_map_erase List.sum_map_erase
@[to_additive] lemma Perm.prod_eq (h : Perm l₁ l₂) : prod l₁ = prod l₂ := h.fold_op_eq
#align list.perm.prod_eq List.Perm.prod_eq
#align list.perm.sum_eq List.Perm.sum_eq
@[to_additive] lemma prod_reverse (l : List M) : prod l.reverse = prod l := (reverse_perm l).prod_eq
#align list.prod_reverse List.prod_reverse
#align list.sum_reverse List.sum_reverse
@[to_additive]
lemma prod_mul_prod_eq_prod_zipWith_mul_prod_drop :
∀ l l' : List M,
l.prod * l'.prod =
(zipWith (· * ·) l l').prod * (l.drop l'.length).prod * (l'.drop l.length).prod
| [], ys => by simp [Nat.zero_le]
| xs, [] => by simp [Nat.zero_le]
| x :: xs, y :: ys => by
simp only [drop, length, zipWith_cons_cons, prod_cons]
conv =>
lhs; rw [mul_assoc]; right; rw [mul_comm, mul_assoc]; right
rw [mul_comm, prod_mul_prod_eq_prod_zipWith_mul_prod_drop xs ys]
simp [mul_assoc]
#align list.prod_mul_prod_eq_prod_zip_with_mul_prod_drop List.prod_mul_prod_eq_prod_zipWith_mul_prod_drop
#align list.sum_add_sum_eq_sum_zip_with_add_sum_drop List.sum_add_sum_eq_sum_zipWith_add_sum_drop
@[to_additive]
lemma prod_mul_prod_eq_prod_zipWith_of_length_eq (l l' : List M) (h : l.length = l'.length) :
l.prod * l'.prod = (zipWith (· * ·) l l').prod := by
apply (prod_mul_prod_eq_prod_zipWith_mul_prod_drop l l').trans
rw [← h, drop_length, h, drop_length, prod_nil, mul_one, mul_one]
#align list.prod_mul_prod_eq_prod_zip_with_of_length_eq List.prod_mul_prod_eq_prod_zipWith_of_length_eq
#align list.sum_add_sum_eq_sum_zip_with_of_length_eq List.sum_add_sum_eq_sum_zipWith_of_length_eq
end CommMonoid
@[to_additive]
lemma eq_of_prod_take_eq [LeftCancelMonoid M] {L L' : List M} (h : L.length = L'.length)
(h' : ∀ i ≤ L.length, (L.take i).prod = (L'.take i).prod) : L = L' := by
refine ext_get h fun i h₁ h₂ => ?_
have : (L.take (i + 1)).prod = (L'.take (i + 1)).prod := h' _ (Nat.succ_le_of_lt h₁)
rw [prod_take_succ L i h₁, prod_take_succ L' i h₂, h' i (le_of_lt h₁)] at this
convert mul_left_cancel this
#align list.eq_of_prod_take_eq List.eq_of_prod_take_eq
#align list.eq_of_sum_take_eq List.eq_of_sum_take_eq
section Group
variable [Group G]
/-- This is the `List.prod` version of `mul_inv_rev` -/
@[to_additive "This is the `List.sum` version of `add_neg_rev`"]
theorem prod_inv_reverse : ∀ L : List G, L.prod⁻¹ = (L.map fun x => x⁻¹).reverse.prod
| [] => by simp
| x :: xs => by simp [prod_inv_reverse xs]
#align list.prod_inv_reverse List.prod_inv_reverse
#align list.sum_neg_reverse List.sum_neg_reverse
/-- A non-commutative variant of `List.prod_reverse` -/
@[to_additive "A non-commutative variant of `List.sum_reverse`"]
theorem prod_reverse_noncomm : ∀ L : List G, L.reverse.prod = (L.map fun x => x⁻¹).prod⁻¹ := by
simp [prod_inv_reverse]
#align list.prod_reverse_noncomm List.prod_reverse_noncomm
#align list.sum_reverse_noncomm List.sum_reverse_noncomm
/-- Counterpart to `List.prod_take_succ` when we have an inverse operation -/
@[to_additive (attr := simp)
"Counterpart to `List.sum_take_succ` when we have a negation operation"]
theorem prod_drop_succ :
∀ (L : List G) (i : ℕ) (p), (L.drop (i + 1)).prod = (L.get ⟨i, p⟩)⁻¹ * (L.drop i).prod
| [], i, p => False.elim (Nat.not_lt_zero _ p)
| x :: xs, 0, _ => by simp
| x :: xs, i + 1, p => prod_drop_succ xs i _
#align list.prod_drop_succ List.prod_drop_succ
#align list.sum_drop_succ List.sum_drop_succ
/-- Cancellation of a telescoping product. -/
@[to_additive "Cancellation of a telescoping sum."]
theorem prod_range_div' (n : ℕ) (f : ℕ → G) :
((range n).map fun k ↦ f k / f (k + 1)).prod = f 0 / f n := by
induction' n with n h
· exact (div_self' (f 0)).symm
· rw [range_succ, map_append, map_singleton, prod_append, prod_singleton, h, div_mul_div_cancel']
lemma prod_rotate_eq_one_of_prod_eq_one :
∀ {l : List G} (_ : l.prod = 1) (n : ℕ), (l.rotate n).prod = 1
| [], _, _ => by simp
| a :: l, hl, n => by
have : n % List.length (a :: l) ≤ List.length (a :: l) := le_of_lt (Nat.mod_lt _ (by simp))
rw [← List.take_append_drop (n % List.length (a :: l)) (a :: l)] at hl;
rw [← rotate_mod, rotate_eq_drop_append_take this, List.prod_append, mul_eq_one_iff_inv_eq, ←
one_mul (List.prod _)⁻¹, ← hl, List.prod_append, mul_assoc, mul_inv_self, mul_one]
#align list.prod_rotate_eq_one_of_prod_eq_one List.prod_rotate_eq_one_of_prod_eq_one
end Group
section CommGroup
variable [CommGroup G]
/-- This is the `List.prod` version of `mul_inv` -/
@[to_additive "This is the `List.sum` version of `add_neg`"]
theorem prod_inv : ∀ L : List G, L.prod⁻¹ = (L.map fun x => x⁻¹).prod
| [] => by simp
| x :: xs => by simp [mul_comm, prod_inv xs]
#align list.prod_inv List.prod_inv
#align list.sum_neg List.sum_neg
/-- Cancellation of a telescoping product. -/
@[to_additive "Cancellation of a telescoping sum."]
theorem prod_range_div (n : ℕ) (f : ℕ → G) :
((range n).map fun k ↦ f (k + 1) / f k).prod = f n / f 0 := by
have h : ((·⁻¹) ∘ fun k ↦ f (k + 1) / f k) = fun k ↦ f k / f (k + 1) := by ext; apply inv_div
rw [← inv_inj, prod_inv, map_map, inv_div, h, prod_range_div']
/-- Alternative version of `List.prod_set` when the list is over a group -/
@[to_additive "Alternative version of `List.sum_set` when the list is over a group"]
| Mathlib/Algebra/BigOperators/Group/List.lean | 534 | 541 | theorem prod_set' (L : List G) (n : ℕ) (a : G) :
(L.set n a).prod = L.prod * if hn : n < L.length then (L.get ⟨n, hn⟩)⁻¹ * a else 1 := by |
refine (prod_set L n a).trans ?_
split_ifs with hn
· rw [mul_comm _ a, mul_assoc a, prod_drop_succ L n hn, mul_comm _ (drop n L).prod, ←
mul_assoc (take n L).prod, prod_take_mul_prod_drop, mul_comm a, mul_assoc]
· simp only [take_all_of_le (le_of_not_lt hn), prod_nil, mul_one,
drop_eq_nil_of_le ((le_of_not_lt hn).trans n.le_succ)]
|
/-
Copyright (c) 2020 Yury G. Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury G. Kudryashov, Patrick Massot, Sébastien Gouëzel
-/
import Mathlib.Order.Interval.Set.Disjoint
import Mathlib.MeasureTheory.Integral.SetIntegral
import Mathlib.MeasureTheory.Measure.Lebesgue.Basic
#align_import measure_theory.integral.interval_integral from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Integral over an interval
In this file we define `∫ x in a..b, f x ∂μ` to be `∫ x in Ioc a b, f x ∂μ` if `a ≤ b` and
`-∫ x in Ioc b a, f x ∂μ` if `b ≤ a`.
## Implementation notes
### Avoiding `if`, `min`, and `max`
In order to avoid `if`s in the definition, we define `IntervalIntegrable f μ a b` as
`integrable_on f (Ioc a b) μ ∧ integrable_on f (Ioc b a) μ`. For any `a`, `b` one of these
intervals is empty and the other coincides with `Set.uIoc a b = Set.Ioc (min a b) (max a b)`.
Similarly, we define `∫ x in a..b, f x ∂μ` to be `∫ x in Ioc a b, f x ∂μ - ∫ x in Ioc b a, f x ∂μ`.
Again, for any `a`, `b` one of these integrals is zero, and the other gives the expected result.
This way some properties can be translated from integrals over sets without dealing with
the cases `a ≤ b` and `b ≤ a` separately.
### Choice of the interval
We use integral over `Set.uIoc a b = Set.Ioc (min a b) (max a b)` instead of one of the other
three possible intervals with the same endpoints for two reasons:
* this way `∫ x in a..b, f x ∂μ + ∫ x in b..c, f x ∂μ = ∫ x in a..c, f x ∂μ` holds whenever
`f` is integrable on each interval; in particular, it works even if the measure `μ` has an atom
at `b`; this rules out `Set.Ioo` and `Set.Icc` intervals;
* with this definition for a probability measure `μ`, the integral `∫ x in a..b, 1 ∂μ` equals
the difference $F_μ(b)-F_μ(a)$, where $F_μ(a)=μ(-∞, a]$ is the
[cumulative distribution function](https://en.wikipedia.org/wiki/Cumulative_distribution_function)
of `μ`.
## Tags
integral
-/
noncomputable section
open scoped Classical
open MeasureTheory Set Filter Function
open scoped Classical Topology Filter ENNReal Interval NNReal
variable {ι 𝕜 E F A : Type*} [NormedAddCommGroup E]
/-!
### Integrability on an interval
-/
/-- A function `f` is called *interval integrable* with respect to a measure `μ` on an unordered
interval `a..b` if it is integrable on both intervals `(a, b]` and `(b, a]`. One of these
intervals is always empty, so this property is equivalent to `f` being integrable on
`(min a b, max a b]`. -/
def IntervalIntegrable (f : ℝ → E) (μ : Measure ℝ) (a b : ℝ) : Prop :=
IntegrableOn f (Ioc a b) μ ∧ IntegrableOn f (Ioc b a) μ
#align interval_integrable IntervalIntegrable
/-!
## Basic iff's for `IntervalIntegrable`
-/
section
variable {f : ℝ → E} {a b : ℝ} {μ : Measure ℝ}
/-- A function is interval integrable with respect to a given measure `μ` on `a..b` if and
only if it is integrable on `uIoc a b` with respect to `μ`. This is an equivalent
definition of `IntervalIntegrable`. -/
theorem intervalIntegrable_iff : IntervalIntegrable f μ a b ↔ IntegrableOn f (Ι a b) μ := by
rw [uIoc_eq_union, integrableOn_union, IntervalIntegrable]
#align interval_integrable_iff intervalIntegrable_iff
/-- If a function is interval integrable with respect to a given measure `μ` on `a..b` then
it is integrable on `uIoc a b` with respect to `μ`. -/
theorem IntervalIntegrable.def' (h : IntervalIntegrable f μ a b) : IntegrableOn f (Ι a b) μ :=
intervalIntegrable_iff.mp h
#align interval_integrable.def IntervalIntegrable.def'
theorem intervalIntegrable_iff_integrableOn_Ioc_of_le (hab : a ≤ b) :
IntervalIntegrable f μ a b ↔ IntegrableOn f (Ioc a b) μ := by
rw [intervalIntegrable_iff, uIoc_of_le hab]
#align interval_integrable_iff_integrable_Ioc_of_le intervalIntegrable_iff_integrableOn_Ioc_of_le
theorem intervalIntegrable_iff' [NoAtoms μ] :
IntervalIntegrable f μ a b ↔ IntegrableOn f (uIcc a b) μ := by
rw [intervalIntegrable_iff, ← Icc_min_max, uIoc, integrableOn_Icc_iff_integrableOn_Ioc]
#align interval_integrable_iff' intervalIntegrable_iff'
theorem intervalIntegrable_iff_integrableOn_Icc_of_le {f : ℝ → E} {a b : ℝ} (hab : a ≤ b)
{μ : Measure ℝ} [NoAtoms μ] : IntervalIntegrable f μ a b ↔ IntegrableOn f (Icc a b) μ := by
rw [intervalIntegrable_iff_integrableOn_Ioc_of_le hab, integrableOn_Icc_iff_integrableOn_Ioc]
#align interval_integrable_iff_integrable_Icc_of_le intervalIntegrable_iff_integrableOn_Icc_of_le
theorem intervalIntegrable_iff_integrableOn_Ico_of_le [NoAtoms μ] (hab : a ≤ b) :
IntervalIntegrable f μ a b ↔ IntegrableOn f (Ico a b) μ := by
rw [intervalIntegrable_iff_integrableOn_Icc_of_le hab, integrableOn_Icc_iff_integrableOn_Ico]
theorem intervalIntegrable_iff_integrableOn_Ioo_of_le [NoAtoms μ] (hab : a ≤ b) :
IntervalIntegrable f μ a b ↔ IntegrableOn f (Ioo a b) μ := by
rw [intervalIntegrable_iff_integrableOn_Icc_of_le hab, integrableOn_Icc_iff_integrableOn_Ioo]
/-- If a function is integrable with respect to a given measure `μ` then it is interval integrable
with respect to `μ` on `uIcc a b`. -/
theorem MeasureTheory.Integrable.intervalIntegrable (hf : Integrable f μ) :
IntervalIntegrable f μ a b :=
⟨hf.integrableOn, hf.integrableOn⟩
#align measure_theory.integrable.interval_integrable MeasureTheory.Integrable.intervalIntegrable
theorem MeasureTheory.IntegrableOn.intervalIntegrable (hf : IntegrableOn f [[a, b]] μ) :
IntervalIntegrable f μ a b :=
⟨MeasureTheory.IntegrableOn.mono_set hf (Ioc_subset_Icc_self.trans Icc_subset_uIcc),
MeasureTheory.IntegrableOn.mono_set hf (Ioc_subset_Icc_self.trans Icc_subset_uIcc')⟩
#align measure_theory.integrable_on.interval_integrable MeasureTheory.IntegrableOn.intervalIntegrable
theorem intervalIntegrable_const_iff {c : E} :
IntervalIntegrable (fun _ => c) μ a b ↔ c = 0 ∨ μ (Ι a b) < ∞ := by
simp only [intervalIntegrable_iff, integrableOn_const]
#align interval_integrable_const_iff intervalIntegrable_const_iff
@[simp]
theorem intervalIntegrable_const [IsLocallyFiniteMeasure μ] {c : E} :
IntervalIntegrable (fun _ => c) μ a b :=
intervalIntegrable_const_iff.2 <| Or.inr measure_Ioc_lt_top
#align interval_integrable_const intervalIntegrable_const
end
/-!
## Basic properties of interval integrability
- interval integrability is symmetric, reflexive, transitive
- monotonicity and strong measurability of the interval integral
- if `f` is interval integrable, so are its absolute value and norm
- arithmetic properties
-/
namespace IntervalIntegrable
section
variable {f : ℝ → E} {a b c d : ℝ} {μ ν : Measure ℝ}
@[symm]
nonrec theorem symm (h : IntervalIntegrable f μ a b) : IntervalIntegrable f μ b a :=
h.symm
#align interval_integrable.symm IntervalIntegrable.symm
@[refl, simp] -- Porting note: added `simp`
theorem refl : IntervalIntegrable f μ a a := by constructor <;> simp
#align interval_integrable.refl IntervalIntegrable.refl
@[trans]
theorem trans {a b c : ℝ} (hab : IntervalIntegrable f μ a b) (hbc : IntervalIntegrable f μ b c) :
IntervalIntegrable f μ a c :=
⟨(hab.1.union hbc.1).mono_set Ioc_subset_Ioc_union_Ioc,
(hbc.2.union hab.2).mono_set Ioc_subset_Ioc_union_Ioc⟩
#align interval_integrable.trans IntervalIntegrable.trans
theorem trans_iterate_Ico {a : ℕ → ℝ} {m n : ℕ} (hmn : m ≤ n)
(hint : ∀ k ∈ Ico m n, IntervalIntegrable f μ (a k) (a <| k + 1)) :
IntervalIntegrable f μ (a m) (a n) := by
revert hint
refine Nat.le_induction ?_ ?_ n hmn
· simp
· intro p hp IH h
exact (IH fun k hk => h k (Ico_subset_Ico_right p.le_succ hk)).trans (h p (by simp [hp]))
#align interval_integrable.trans_iterate_Ico IntervalIntegrable.trans_iterate_Ico
theorem trans_iterate {a : ℕ → ℝ} {n : ℕ}
(hint : ∀ k < n, IntervalIntegrable f μ (a k) (a <| k + 1)) :
IntervalIntegrable f μ (a 0) (a n) :=
trans_iterate_Ico bot_le fun k hk => hint k hk.2
#align interval_integrable.trans_iterate IntervalIntegrable.trans_iterate
theorem neg (h : IntervalIntegrable f μ a b) : IntervalIntegrable (-f) μ a b :=
⟨h.1.neg, h.2.neg⟩
#align interval_integrable.neg IntervalIntegrable.neg
theorem norm (h : IntervalIntegrable f μ a b) : IntervalIntegrable (fun x => ‖f x‖) μ a b :=
⟨h.1.norm, h.2.norm⟩
#align interval_integrable.norm IntervalIntegrable.norm
theorem intervalIntegrable_norm_iff {f : ℝ → E} {μ : Measure ℝ} {a b : ℝ}
(hf : AEStronglyMeasurable f (μ.restrict (Ι a b))) :
IntervalIntegrable (fun t => ‖f t‖) μ a b ↔ IntervalIntegrable f μ a b := by
simp_rw [intervalIntegrable_iff, IntegrableOn]; exact integrable_norm_iff hf
#align interval_integrable.interval_integrable_norm_iff IntervalIntegrable.intervalIntegrable_norm_iff
theorem abs {f : ℝ → ℝ} (h : IntervalIntegrable f μ a b) :
IntervalIntegrable (fun x => |f x|) μ a b :=
h.norm
#align interval_integrable.abs IntervalIntegrable.abs
theorem mono (hf : IntervalIntegrable f ν a b) (h1 : [[c, d]] ⊆ [[a, b]]) (h2 : μ ≤ ν) :
IntervalIntegrable f μ c d :=
intervalIntegrable_iff.mpr <| hf.def'.mono (uIoc_subset_uIoc_of_uIcc_subset_uIcc h1) h2
#align interval_integrable.mono IntervalIntegrable.mono
theorem mono_measure (hf : IntervalIntegrable f ν a b) (h : μ ≤ ν) : IntervalIntegrable f μ a b :=
hf.mono Subset.rfl h
#align interval_integrable.mono_measure IntervalIntegrable.mono_measure
theorem mono_set (hf : IntervalIntegrable f μ a b) (h : [[c, d]] ⊆ [[a, b]]) :
IntervalIntegrable f μ c d :=
hf.mono h le_rfl
#align interval_integrable.mono_set IntervalIntegrable.mono_set
theorem mono_set_ae (hf : IntervalIntegrable f μ a b) (h : Ι c d ≤ᵐ[μ] Ι a b) :
IntervalIntegrable f μ c d :=
intervalIntegrable_iff.mpr <| hf.def'.mono_set_ae h
#align interval_integrable.mono_set_ae IntervalIntegrable.mono_set_ae
theorem mono_set' (hf : IntervalIntegrable f μ a b) (hsub : Ι c d ⊆ Ι a b) :
IntervalIntegrable f μ c d :=
hf.mono_set_ae <| eventually_of_forall hsub
#align interval_integrable.mono_set' IntervalIntegrable.mono_set'
theorem mono_fun [NormedAddCommGroup F] {g : ℝ → F} (hf : IntervalIntegrable f μ a b)
(hgm : AEStronglyMeasurable g (μ.restrict (Ι a b)))
(hle : (fun x => ‖g x‖) ≤ᵐ[μ.restrict (Ι a b)] fun x => ‖f x‖) : IntervalIntegrable g μ a b :=
intervalIntegrable_iff.2 <| hf.def'.integrable.mono hgm hle
#align interval_integrable.mono_fun IntervalIntegrable.mono_fun
theorem mono_fun' {g : ℝ → ℝ} (hg : IntervalIntegrable g μ a b)
(hfm : AEStronglyMeasurable f (μ.restrict (Ι a b)))
(hle : (fun x => ‖f x‖) ≤ᵐ[μ.restrict (Ι a b)] g) : IntervalIntegrable f μ a b :=
intervalIntegrable_iff.2 <| hg.def'.integrable.mono' hfm hle
#align interval_integrable.mono_fun' IntervalIntegrable.mono_fun'
protected theorem aestronglyMeasurable (h : IntervalIntegrable f μ a b) :
AEStronglyMeasurable f (μ.restrict (Ioc a b)) :=
h.1.aestronglyMeasurable
#align interval_integrable.ae_strongly_measurable IntervalIntegrable.aestronglyMeasurable
protected theorem aestronglyMeasurable' (h : IntervalIntegrable f μ a b) :
AEStronglyMeasurable f (μ.restrict (Ioc b a)) :=
h.2.aestronglyMeasurable
#align interval_integrable.ae_strongly_measurable' IntervalIntegrable.aestronglyMeasurable'
end
variable [NormedRing A] {f g : ℝ → E} {a b : ℝ} {μ : Measure ℝ}
theorem smul [NormedField 𝕜] [NormedSpace 𝕜 E] {f : ℝ → E} {a b : ℝ} {μ : Measure ℝ}
(h : IntervalIntegrable f μ a b) (r : 𝕜) : IntervalIntegrable (r • f) μ a b :=
⟨h.1.smul r, h.2.smul r⟩
#align interval_integrable.smul IntervalIntegrable.smul
@[simp]
theorem add (hf : IntervalIntegrable f μ a b) (hg : IntervalIntegrable g μ a b) :
IntervalIntegrable (fun x => f x + g x) μ a b :=
⟨hf.1.add hg.1, hf.2.add hg.2⟩
#align interval_integrable.add IntervalIntegrable.add
@[simp]
theorem sub (hf : IntervalIntegrable f μ a b) (hg : IntervalIntegrable g μ a b) :
IntervalIntegrable (fun x => f x - g x) μ a b :=
⟨hf.1.sub hg.1, hf.2.sub hg.2⟩
#align interval_integrable.sub IntervalIntegrable.sub
theorem sum (s : Finset ι) {f : ι → ℝ → E} (h : ∀ i ∈ s, IntervalIntegrable (f i) μ a b) :
IntervalIntegrable (∑ i ∈ s, f i) μ a b :=
⟨integrable_finset_sum' s fun i hi => (h i hi).1, integrable_finset_sum' s fun i hi => (h i hi).2⟩
#align interval_integrable.sum IntervalIntegrable.sum
theorem mul_continuousOn {f g : ℝ → A} (hf : IntervalIntegrable f μ a b)
(hg : ContinuousOn g [[a, b]]) : IntervalIntegrable (fun x => f x * g x) μ a b := by
rw [intervalIntegrable_iff] at hf ⊢
exact hf.mul_continuousOn_of_subset hg measurableSet_Ioc isCompact_uIcc Ioc_subset_Icc_self
#align interval_integrable.mul_continuous_on IntervalIntegrable.mul_continuousOn
theorem continuousOn_mul {f g : ℝ → A} (hf : IntervalIntegrable f μ a b)
(hg : ContinuousOn g [[a, b]]) : IntervalIntegrable (fun x => g x * f x) μ a b := by
rw [intervalIntegrable_iff] at hf ⊢
exact hf.continuousOn_mul_of_subset hg isCompact_uIcc measurableSet_Ioc Ioc_subset_Icc_self
#align interval_integrable.continuous_on_mul IntervalIntegrable.continuousOn_mul
@[simp]
theorem const_mul {f : ℝ → A} (hf : IntervalIntegrable f μ a b) (c : A) :
IntervalIntegrable (fun x => c * f x) μ a b :=
hf.continuousOn_mul continuousOn_const
#align interval_integrable.const_mul IntervalIntegrable.const_mul
@[simp]
theorem mul_const {f : ℝ → A} (hf : IntervalIntegrable f μ a b) (c : A) :
IntervalIntegrable (fun x => f x * c) μ a b :=
hf.mul_continuousOn continuousOn_const
#align interval_integrable.mul_const IntervalIntegrable.mul_const
@[simp]
theorem div_const {𝕜 : Type*} {f : ℝ → 𝕜} [NormedField 𝕜] (h : IntervalIntegrable f μ a b)
(c : 𝕜) : IntervalIntegrable (fun x => f x / c) μ a b := by
simpa only [div_eq_mul_inv] using mul_const h c⁻¹
#align interval_integrable.div_const IntervalIntegrable.div_const
theorem comp_mul_left (hf : IntervalIntegrable f volume a b) (c : ℝ) :
IntervalIntegrable (fun x => f (c * x)) volume (a / c) (b / c) := by
rcases eq_or_ne c 0 with (hc | hc); · rw [hc]; simp
rw [intervalIntegrable_iff'] at hf ⊢
have A : MeasurableEmbedding fun x => x * c⁻¹ :=
(Homeomorph.mulRight₀ _ (inv_ne_zero hc)).closedEmbedding.measurableEmbedding
rw [← Real.smul_map_volume_mul_right (inv_ne_zero hc), IntegrableOn, Measure.restrict_smul,
integrable_smul_measure (by simpa : ENNReal.ofReal |c⁻¹| ≠ 0) ENNReal.ofReal_ne_top,
← IntegrableOn, MeasurableEmbedding.integrableOn_map_iff A]
convert hf using 1
· ext; simp only [comp_apply]; congr 1; field_simp
· rw [preimage_mul_const_uIcc (inv_ne_zero hc)]; field_simp [hc]
#align interval_integrable.comp_mul_left IntervalIntegrable.comp_mul_left
-- Porting note (#10756): new lemma
theorem comp_mul_left_iff {c : ℝ} (hc : c ≠ 0) :
IntervalIntegrable (fun x ↦ f (c * x)) volume (a / c) (b / c) ↔
IntervalIntegrable f volume a b :=
⟨fun h ↦ by simpa [hc] using h.comp_mul_left c⁻¹, (comp_mul_left · c)⟩
theorem comp_mul_right (hf : IntervalIntegrable f volume a b) (c : ℝ) :
IntervalIntegrable (fun x => f (x * c)) volume (a / c) (b / c) := by
simpa only [mul_comm] using comp_mul_left hf c
#align interval_integrable.comp_mul_right IntervalIntegrable.comp_mul_right
theorem comp_add_right (hf : IntervalIntegrable f volume a b) (c : ℝ) :
IntervalIntegrable (fun x => f (x + c)) volume (a - c) (b - c) := by
wlog h : a ≤ b generalizing a b
· exact IntervalIntegrable.symm (this hf.symm (le_of_not_le h))
rw [intervalIntegrable_iff'] at hf ⊢
have A : MeasurableEmbedding fun x => x + c :=
(Homeomorph.addRight c).closedEmbedding.measurableEmbedding
rw [← map_add_right_eq_self volume c] at hf
convert (MeasurableEmbedding.integrableOn_map_iff A).mp hf using 1
rw [preimage_add_const_uIcc]
#align interval_integrable.comp_add_right IntervalIntegrable.comp_add_right
theorem comp_add_left (hf : IntervalIntegrable f volume a b) (c : ℝ) :
IntervalIntegrable (fun x => f (c + x)) volume (a - c) (b - c) := by
simpa only [add_comm] using IntervalIntegrable.comp_add_right hf c
#align interval_integrable.comp_add_left IntervalIntegrable.comp_add_left
theorem comp_sub_right (hf : IntervalIntegrable f volume a b) (c : ℝ) :
IntervalIntegrable (fun x => f (x - c)) volume (a + c) (b + c) := by
simpa only [sub_neg_eq_add] using IntervalIntegrable.comp_add_right hf (-c)
#align interval_integrable.comp_sub_right IntervalIntegrable.comp_sub_right
theorem iff_comp_neg :
IntervalIntegrable f volume a b ↔ IntervalIntegrable (fun x => f (-x)) volume (-a) (-b) := by
rw [← comp_mul_left_iff (neg_ne_zero.2 one_ne_zero)]; simp [div_neg]
#align interval_integrable.iff_comp_neg IntervalIntegrable.iff_comp_neg
theorem comp_sub_left (hf : IntervalIntegrable f volume a b) (c : ℝ) :
IntervalIntegrable (fun x => f (c - x)) volume (c - a) (c - b) := by
simpa only [neg_sub, ← sub_eq_add_neg] using iff_comp_neg.mp (hf.comp_add_left c)
#align interval_integrable.comp_sub_left IntervalIntegrable.comp_sub_left
end IntervalIntegrable
/-!
## Continuous functions are interval integrable
-/
section
variable {μ : Measure ℝ} [IsLocallyFiniteMeasure μ]
theorem ContinuousOn.intervalIntegrable {u : ℝ → E} {a b : ℝ} (hu : ContinuousOn u (uIcc a b)) :
IntervalIntegrable u μ a b :=
(ContinuousOn.integrableOn_Icc hu).intervalIntegrable
#align continuous_on.interval_integrable ContinuousOn.intervalIntegrable
theorem ContinuousOn.intervalIntegrable_of_Icc {u : ℝ → E} {a b : ℝ} (h : a ≤ b)
(hu : ContinuousOn u (Icc a b)) : IntervalIntegrable u μ a b :=
ContinuousOn.intervalIntegrable ((uIcc_of_le h).symm ▸ hu)
#align continuous_on.interval_integrable_of_Icc ContinuousOn.intervalIntegrable_of_Icc
/-- A continuous function on `ℝ` is `IntervalIntegrable` with respect to any locally finite measure
`ν` on ℝ. -/
theorem Continuous.intervalIntegrable {u : ℝ → E} (hu : Continuous u) (a b : ℝ) :
IntervalIntegrable u μ a b :=
hu.continuousOn.intervalIntegrable
#align continuous.interval_integrable Continuous.intervalIntegrable
end
/-!
## Monotone and antitone functions are integral integrable
-/
section
variable {μ : Measure ℝ} [IsLocallyFiniteMeasure μ] [ConditionallyCompleteLinearOrder E]
[OrderTopology E] [SecondCountableTopology E]
theorem MonotoneOn.intervalIntegrable {u : ℝ → E} {a b : ℝ} (hu : MonotoneOn u (uIcc a b)) :
IntervalIntegrable u μ a b := by
rw [intervalIntegrable_iff]
exact (hu.integrableOn_isCompact isCompact_uIcc).mono_set Ioc_subset_Icc_self
#align monotone_on.interval_integrable MonotoneOn.intervalIntegrable
theorem AntitoneOn.intervalIntegrable {u : ℝ → E} {a b : ℝ} (hu : AntitoneOn u (uIcc a b)) :
IntervalIntegrable u μ a b :=
hu.dual_right.intervalIntegrable
#align antitone_on.interval_integrable AntitoneOn.intervalIntegrable
theorem Monotone.intervalIntegrable {u : ℝ → E} {a b : ℝ} (hu : Monotone u) :
IntervalIntegrable u μ a b :=
(hu.monotoneOn _).intervalIntegrable
#align monotone.interval_integrable Monotone.intervalIntegrable
theorem Antitone.intervalIntegrable {u : ℝ → E} {a b : ℝ} (hu : Antitone u) :
IntervalIntegrable u μ a b :=
(hu.antitoneOn _).intervalIntegrable
#align antitone.interval_integrable Antitone.intervalIntegrable
end
/-- Let `l'` be a measurably generated filter; let `l` be a of filter such that each `s ∈ l'`
eventually includes `Ioc u v` as both `u` and `v` tend to `l`. Let `μ` be a measure finite at `l'`.
Suppose that `f : ℝ → E` has a finite limit at `l' ⊓ ae μ`. Then `f` is interval integrable on
`u..v` provided that both `u` and `v` tend to `l`.
Typeclass instances allow Lean to find `l'` based on `l` but not vice versa, so
`apply Tendsto.eventually_intervalIntegrable_ae` will generate goals `Filter ℝ` and
`TendstoIxxClass Ioc ?m_1 l'`. -/
theorem Filter.Tendsto.eventually_intervalIntegrable_ae {f : ℝ → E} {μ : Measure ℝ}
{l l' : Filter ℝ} (hfm : StronglyMeasurableAtFilter f l' μ) [TendstoIxxClass Ioc l l']
[IsMeasurablyGenerated l'] (hμ : μ.FiniteAtFilter l') {c : E} (hf : Tendsto f (l' ⊓ ae μ) (𝓝 c))
{u v : ι → ℝ} {lt : Filter ι} (hu : Tendsto u lt l) (hv : Tendsto v lt l) :
∀ᶠ t in lt, IntervalIntegrable f μ (u t) (v t) :=
have := (hf.integrableAtFilter_ae hfm hμ).eventually
((hu.Ioc hv).eventually this).and <| (hv.Ioc hu).eventually this
#align filter.tendsto.eventually_interval_integrable_ae Filter.Tendsto.eventually_intervalIntegrable_ae
/-- Let `l'` be a measurably generated filter; let `l` be a of filter such that each `s ∈ l'`
eventually includes `Ioc u v` as both `u` and `v` tend to `l`. Let `μ` be a measure finite at `l'`.
Suppose that `f : ℝ → E` has a finite limit at `l`. Then `f` is interval integrable on `u..v`
provided that both `u` and `v` tend to `l`.
Typeclass instances allow Lean to find `l'` based on `l` but not vice versa, so
`apply Tendsto.eventually_intervalIntegrable` will generate goals `Filter ℝ` and
`TendstoIxxClass Ioc ?m_1 l'`. -/
theorem Filter.Tendsto.eventually_intervalIntegrable {f : ℝ → E} {μ : Measure ℝ} {l l' : Filter ℝ}
(hfm : StronglyMeasurableAtFilter f l' μ) [TendstoIxxClass Ioc l l'] [IsMeasurablyGenerated l']
(hμ : μ.FiniteAtFilter l') {c : E} (hf : Tendsto f l' (𝓝 c)) {u v : ι → ℝ} {lt : Filter ι}
(hu : Tendsto u lt l) (hv : Tendsto v lt l) : ∀ᶠ t in lt, IntervalIntegrable f μ (u t) (v t) :=
(hf.mono_left inf_le_left).eventually_intervalIntegrable_ae hfm hμ hu hv
#align filter.tendsto.eventually_interval_integrable Filter.Tendsto.eventually_intervalIntegrable
/-!
### Interval integral: definition and basic properties
In this section we define `∫ x in a..b, f x ∂μ` as `∫ x in Ioc a b, f x ∂μ - ∫ x in Ioc b a, f x ∂μ`
and prove some basic properties.
-/
variable [CompleteSpace E] [NormedSpace ℝ E]
/-- The interval integral `∫ x in a..b, f x ∂μ` is defined
as `∫ x in Ioc a b, f x ∂μ - ∫ x in Ioc b a, f x ∂μ`. If `a ≤ b`, then it equals
`∫ x in Ioc a b, f x ∂μ`, otherwise it equals `-∫ x in Ioc b a, f x ∂μ`. -/
def intervalIntegral (f : ℝ → E) (a b : ℝ) (μ : Measure ℝ) : E :=
(∫ x in Ioc a b, f x ∂μ) - ∫ x in Ioc b a, f x ∂μ
#align interval_integral intervalIntegral
notation3"∫ "(...)" in "a".."b", "r:60:(scoped f => f)" ∂"μ:70 => intervalIntegral r a b μ
notation3"∫ "(...)" in "a".."b", "r:60:(scoped f => intervalIntegral f a b volume) => r
namespace intervalIntegral
section Basic
variable {a b : ℝ} {f g : ℝ → E} {μ : Measure ℝ}
@[simp]
theorem integral_zero : (∫ _ in a..b, (0 : E) ∂μ) = 0 := by simp [intervalIntegral]
#align interval_integral.integral_zero intervalIntegral.integral_zero
theorem integral_of_le (h : a ≤ b) : ∫ x in a..b, f x ∂μ = ∫ x in Ioc a b, f x ∂μ := by
simp [intervalIntegral, h]
#align interval_integral.integral_of_le intervalIntegral.integral_of_le
@[simp]
theorem integral_same : ∫ x in a..a, f x ∂μ = 0 :=
sub_self _
#align interval_integral.integral_same intervalIntegral.integral_same
theorem integral_symm (a b) : ∫ x in b..a, f x ∂μ = -∫ x in a..b, f x ∂μ := by
simp only [intervalIntegral, neg_sub]
#align interval_integral.integral_symm intervalIntegral.integral_symm
| Mathlib/MeasureTheory/Integral/IntervalIntegral.lean | 501 | 502 | theorem integral_of_ge (h : b ≤ a) : ∫ x in a..b, f x ∂μ = -∫ x in Ioc b a, f x ∂μ := by |
simp only [integral_symm b, integral_of_le h]
|
/-
Copyright (c) 2022 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Analysis.Convex.StrictConvexSpace
#align_import analysis.convex.uniform from "leanprover-community/mathlib"@"17ef379e997badd73e5eabb4d38f11919ab3c4b3"
/-!
# Uniformly convex spaces
This file defines uniformly convex spaces, which are real normed vector spaces in which for all
strictly positive `ε`, there exists some strictly positive `δ` such that `ε ≤ ‖x - y‖` implies
`‖x + y‖ ≤ 2 - δ` for all `x` and `y` of norm at most than `1`. This means that the triangle
inequality is strict with a uniform bound, as opposed to strictly convex spaces where the triangle
inequality is strict but not necessarily uniformly (`‖x + y‖ < ‖x‖ + ‖y‖` for all `x` and `y` not in
the same ray).
## Main declarations
`UniformConvexSpace E` means that `E` is a uniformly convex space.
## TODO
* Milman-Pettis
* Hanner's inequalities
## Tags
convex, uniformly convex
-/
open Set Metric
open Convex Pointwise
/-- A *uniformly convex space* is a real normed space where the triangle inequality is strict with a
uniform bound. Namely, over the `x` and `y` of norm `1`, `‖x + y‖` is uniformly bounded above
by a constant `< 2` when `‖x - y‖` is uniformly bounded below by a positive constant. -/
class UniformConvexSpace (E : Type*) [SeminormedAddCommGroup E] : Prop where
uniform_convex : ∀ ⦃ε : ℝ⦄,
0 < ε → ∃ δ, 0 < δ ∧ ∀ ⦃x : E⦄, ‖x‖ = 1 → ∀ ⦃y⦄, ‖y‖ = 1 → ε ≤ ‖x - y‖ → ‖x + y‖ ≤ 2 - δ
#align uniform_convex_space UniformConvexSpace
variable {E : Type*}
section SeminormedAddCommGroup
variable (E) [SeminormedAddCommGroup E] [UniformConvexSpace E] {ε : ℝ}
theorem exists_forall_sphere_dist_add_le_two_sub (hε : 0 < ε) :
∃ δ, 0 < δ ∧ ∀ ⦃x : E⦄, ‖x‖ = 1 → ∀ ⦃y⦄, ‖y‖ = 1 → ε ≤ ‖x - y‖ → ‖x + y‖ ≤ 2 - δ :=
UniformConvexSpace.uniform_convex hε
#align exists_forall_sphere_dist_add_le_two_sub exists_forall_sphere_dist_add_le_two_sub
variable [NormedSpace ℝ E]
theorem exists_forall_closed_ball_dist_add_le_two_sub (hε : 0 < ε) :
∃ δ, 0 < δ ∧ ∀ ⦃x : E⦄, ‖x‖ ≤ 1 → ∀ ⦃y⦄, ‖y‖ ≤ 1 → ε ≤ ‖x - y‖ → ‖x + y‖ ≤ 2 - δ := by
have hε' : 0 < ε / 3 := div_pos hε zero_lt_three
obtain ⟨δ, hδ, h⟩ := exists_forall_sphere_dist_add_le_two_sub E hε'
set δ' := min (1 / 2) (min (ε / 3) <| δ / 3)
refine ⟨δ', lt_min one_half_pos <| lt_min hε' (div_pos hδ zero_lt_three), fun x hx y hy hxy => ?_⟩
obtain hx' | hx' := le_or_lt ‖x‖ (1 - δ')
· rw [← one_add_one_eq_two]
exact (norm_add_le_of_le hx' hy).trans (sub_add_eq_add_sub _ _ _).le
obtain hy' | hy' := le_or_lt ‖y‖ (1 - δ')
· rw [← one_add_one_eq_two]
exact (norm_add_le_of_le hx hy').trans (add_sub_assoc _ _ _).ge
have hδ' : 0 < 1 - δ' := sub_pos_of_lt (min_lt_of_left_lt one_half_lt_one)
have h₁ : ∀ z : E, 1 - δ' < ‖z‖ → ‖‖z‖⁻¹ • z‖ = 1 := by
rintro z hz
rw [norm_smul_of_nonneg (inv_nonneg.2 <| norm_nonneg _), inv_mul_cancel (hδ'.trans hz).ne']
have h₂ : ∀ z : E, ‖z‖ ≤ 1 → 1 - δ' ≤ ‖z‖ → ‖‖z‖⁻¹ • z - z‖ ≤ δ' := by
rintro z hz hδz
nth_rw 3 [← one_smul ℝ z]
rwa [← sub_smul, norm_smul_of_nonneg (sub_nonneg_of_le <| one_le_inv (hδ'.trans_le hδz) hz),
sub_mul, inv_mul_cancel (hδ'.trans_le hδz).ne', one_mul, sub_le_comm]
set x' := ‖x‖⁻¹ • x
set y' := ‖y‖⁻¹ • y
have hxy' : ε / 3 ≤ ‖x' - y'‖ :=
calc
ε / 3 = ε - (ε / 3 + ε / 3) := by ring
_ ≤ ‖x - y‖ - (‖x' - x‖ + ‖y' - y‖) := by
gcongr
· exact (h₂ _ hx hx'.le).trans <| min_le_of_right_le <| min_le_left _ _
· exact (h₂ _ hy hy'.le).trans <| min_le_of_right_le <| min_le_left _ _
_ ≤ _ := by
have : ∀ x' y', x - y = x' - y' + (x - x') + (y' - y) := fun _ _ => by abel
rw [sub_le_iff_le_add, norm_sub_rev _ x, ← add_assoc, this]
exact norm_add₃_le _ _ _
calc
‖x + y‖ ≤ ‖x' + y'‖ + ‖x' - x‖ + ‖y' - y‖ := by
have : ∀ x' y', x + y = x' + y' + (x - x') + (y - y') := fun _ _ => by abel
rw [norm_sub_rev, norm_sub_rev y', this]
exact norm_add₃_le _ _ _
_ ≤ 2 - δ + δ' + δ' :=
(add_le_add_three (h (h₁ _ hx') (h₁ _ hy') hxy') (h₂ _ hx hx'.le) (h₂ _ hy hy'.le))
_ ≤ 2 - δ' := by
dsimp [δ']
rw [← le_sub_iff_add_le, ← le_sub_iff_add_le, sub_sub, sub_sub]
refine sub_le_sub_left ?_ _
ring_nf
rw [← mul_div_cancel₀ δ three_ne_zero]
set_option tactic.skipAssignedInstances false in norm_num
-- Porting note: these three extra lines needed to make `exact` work
have : 3 * (δ / 3) * (1 / 3) = δ / 3 := by linarith
rw [this, mul_comm]
gcongr
exact min_le_of_right_le <| min_le_right _ _
#align exists_forall_closed_ball_dist_add_le_two_sub exists_forall_closed_ball_dist_add_le_two_sub
| Mathlib/Analysis/Convex/Uniform.lean | 115 | 126 | theorem exists_forall_closed_ball_dist_add_le_two_mul_sub (hε : 0 < ε) (r : ℝ) :
∃ δ, 0 < δ ∧ ∀ ⦃x : E⦄, ‖x‖ ≤ r → ∀ ⦃y⦄, ‖y‖ ≤ r → ε ≤ ‖x - y‖ → ‖x + y‖ ≤ 2 * r - δ := by |
obtain hr | hr := le_or_lt r 0
· exact ⟨1, one_pos, fun x hx y hy h => (hε.not_le <|
h.trans <| (norm_sub_le _ _).trans <| add_nonpos (hx.trans hr) (hy.trans hr)).elim⟩
obtain ⟨δ, hδ, h⟩ := exists_forall_closed_ball_dist_add_le_two_sub E (div_pos hε hr)
refine ⟨δ * r, mul_pos hδ hr, fun x hx y hy hxy => ?_⟩
rw [← div_le_one hr, div_eq_inv_mul, ← norm_smul_of_nonneg (inv_nonneg.2 hr.le)] at hx hy
have := h hx hy
simp_rw [← smul_add, ← smul_sub, norm_smul_of_nonneg (inv_nonneg.2 hr.le), ← div_eq_inv_mul,
div_le_div_right hr, div_le_iff hr, sub_mul] at this
exact this hxy
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Yury Kudryashov
-/
import Mathlib.Data.Set.Image
import Mathlib.Order.SuccPred.Relation
import Mathlib.Topology.Clopen
import Mathlib.Topology.Irreducible
#align_import topology.connected from "leanprover-community/mathlib"@"d101e93197bb5f6ea89bd7ba386b7f7dff1f3903"
/-!
# Connected subsets of topological spaces
In this file we define connected subsets of a topological spaces and various other properties and
classes related to connectivity.
## Main definitions
We define the following properties for sets in a topological space:
* `IsConnected`: a nonempty set that has no non-trivial open partition.
See also the section below in the module doc.
* `connectedComponent` is the connected component of an element in the space.
We also have a class stating that the whole space satisfies that property: `ConnectedSpace`
## On the definition of connected sets/spaces
In informal mathematics, connected spaces are assumed to be nonempty.
We formalise the predicate without that assumption as `IsPreconnected`.
In other words, the only difference is whether the empty space counts as connected.
There are good reasons to consider the empty space to be “too simple to be simple”
See also https://ncatlab.org/nlab/show/too+simple+to+be+simple,
and in particular
https://ncatlab.org/nlab/show/too+simple+to+be+simple#relationship_to_biased_definitions.
-/
open Set Function Topology TopologicalSpace Relation
open scoped Classical
universe u v
variable {α : Type u} {β : Type v} {ι : Type*} {π : ι → Type*} [TopologicalSpace α]
{s t u v : Set α}
section Preconnected
/-- A preconnected set is one where there is no non-trivial open partition. -/
def IsPreconnected (s : Set α) : Prop :=
∀ u v : Set α, IsOpen u → IsOpen v → s ⊆ u ∪ v → (s ∩ u).Nonempty → (s ∩ v).Nonempty →
(s ∩ (u ∩ v)).Nonempty
#align is_preconnected IsPreconnected
/-- A connected set is one that is nonempty and where there is no non-trivial open partition. -/
def IsConnected (s : Set α) : Prop :=
s.Nonempty ∧ IsPreconnected s
#align is_connected IsConnected
theorem IsConnected.nonempty {s : Set α} (h : IsConnected s) : s.Nonempty :=
h.1
#align is_connected.nonempty IsConnected.nonempty
theorem IsConnected.isPreconnected {s : Set α} (h : IsConnected s) : IsPreconnected s :=
h.2
#align is_connected.is_preconnected IsConnected.isPreconnected
theorem IsPreirreducible.isPreconnected {s : Set α} (H : IsPreirreducible s) : IsPreconnected s :=
fun _ _ hu hv _ => H _ _ hu hv
#align is_preirreducible.is_preconnected IsPreirreducible.isPreconnected
theorem IsIrreducible.isConnected {s : Set α} (H : IsIrreducible s) : IsConnected s :=
⟨H.nonempty, H.isPreirreducible.isPreconnected⟩
#align is_irreducible.is_connected IsIrreducible.isConnected
theorem isPreconnected_empty : IsPreconnected (∅ : Set α) :=
isPreirreducible_empty.isPreconnected
#align is_preconnected_empty isPreconnected_empty
theorem isConnected_singleton {x} : IsConnected ({x} : Set α) :=
isIrreducible_singleton.isConnected
#align is_connected_singleton isConnected_singleton
theorem isPreconnected_singleton {x} : IsPreconnected ({x} : Set α) :=
isConnected_singleton.isPreconnected
#align is_preconnected_singleton isPreconnected_singleton
theorem Set.Subsingleton.isPreconnected {s : Set α} (hs : s.Subsingleton) : IsPreconnected s :=
hs.induction_on isPreconnected_empty fun _ => isPreconnected_singleton
#align set.subsingleton.is_preconnected Set.Subsingleton.isPreconnected
/-- If any point of a set is joined to a fixed point by a preconnected subset,
then the original set is preconnected as well. -/
theorem isPreconnected_of_forall {s : Set α} (x : α)
(H : ∀ y ∈ s, ∃ t, t ⊆ s ∧ x ∈ t ∧ y ∈ t ∧ IsPreconnected t) : IsPreconnected s := by
rintro u v hu hv hs ⟨z, zs, zu⟩ ⟨y, ys, yv⟩
have xs : x ∈ s := by
rcases H y ys with ⟨t, ts, xt, -, -⟩
exact ts xt
-- Porting note (#11215): TODO: use `wlog xu : x ∈ u := hs xs using u v y z, v u z y`
cases hs xs with
| inl xu =>
rcases H y ys with ⟨t, ts, xt, yt, ht⟩
have := ht u v hu hv (ts.trans hs) ⟨x, xt, xu⟩ ⟨y, yt, yv⟩
exact this.imp fun z hz => ⟨ts hz.1, hz.2⟩
| inr xv =>
rcases H z zs with ⟨t, ts, xt, zt, ht⟩
have := ht v u hv hu (ts.trans <| by rwa [union_comm]) ⟨x, xt, xv⟩ ⟨z, zt, zu⟩
exact this.imp fun _ h => ⟨ts h.1, h.2.2, h.2.1⟩
#align is_preconnected_of_forall isPreconnected_of_forall
/-- If any two points of a set are contained in a preconnected subset,
then the original set is preconnected as well. -/
theorem isPreconnected_of_forall_pair {s : Set α}
(H : ∀ x ∈ s, ∀ y ∈ s, ∃ t, t ⊆ s ∧ x ∈ t ∧ y ∈ t ∧ IsPreconnected t) :
IsPreconnected s := by
rcases eq_empty_or_nonempty s with (rfl | ⟨x, hx⟩)
exacts [isPreconnected_empty, isPreconnected_of_forall x fun y => H x hx y]
#align is_preconnected_of_forall_pair isPreconnected_of_forall_pair
/-- A union of a family of preconnected sets with a common point is preconnected as well. -/
theorem isPreconnected_sUnion (x : α) (c : Set (Set α)) (H1 : ∀ s ∈ c, x ∈ s)
(H2 : ∀ s ∈ c, IsPreconnected s) : IsPreconnected (⋃₀ c) := by
apply isPreconnected_of_forall x
rintro y ⟨s, sc, ys⟩
exact ⟨s, subset_sUnion_of_mem sc, H1 s sc, ys, H2 s sc⟩
#align is_preconnected_sUnion isPreconnected_sUnion
theorem isPreconnected_iUnion {ι : Sort*} {s : ι → Set α} (h₁ : (⋂ i, s i).Nonempty)
(h₂ : ∀ i, IsPreconnected (s i)) : IsPreconnected (⋃ i, s i) :=
Exists.elim h₁ fun f hf => isPreconnected_sUnion f _ hf (forall_mem_range.2 h₂)
#align is_preconnected_Union isPreconnected_iUnion
theorem IsPreconnected.union (x : α) {s t : Set α} (H1 : x ∈ s) (H2 : x ∈ t) (H3 : IsPreconnected s)
(H4 : IsPreconnected t) : IsPreconnected (s ∪ t) :=
sUnion_pair s t ▸ isPreconnected_sUnion x {s, t} (by rintro r (rfl | rfl | h) <;> assumption)
(by rintro r (rfl | rfl | h) <;> assumption)
#align is_preconnected.union IsPreconnected.union
theorem IsPreconnected.union' {s t : Set α} (H : (s ∩ t).Nonempty) (hs : IsPreconnected s)
(ht : IsPreconnected t) : IsPreconnected (s ∪ t) := by
rcases H with ⟨x, hxs, hxt⟩
exact hs.union x hxs hxt ht
#align is_preconnected.union' IsPreconnected.union'
theorem IsConnected.union {s t : Set α} (H : (s ∩ t).Nonempty) (Hs : IsConnected s)
(Ht : IsConnected t) : IsConnected (s ∪ t) := by
rcases H with ⟨x, hx⟩
refine ⟨⟨x, mem_union_left t (mem_of_mem_inter_left hx)⟩, ?_⟩
exact Hs.isPreconnected.union x (mem_of_mem_inter_left hx) (mem_of_mem_inter_right hx)
Ht.isPreconnected
#align is_connected.union IsConnected.union
/-- The directed sUnion of a set S of preconnected subsets is preconnected. -/
theorem IsPreconnected.sUnion_directed {S : Set (Set α)} (K : DirectedOn (· ⊆ ·) S)
(H : ∀ s ∈ S, IsPreconnected s) : IsPreconnected (⋃₀ S) := by
rintro u v hu hv Huv ⟨a, ⟨s, hsS, has⟩, hau⟩ ⟨b, ⟨t, htS, hbt⟩, hbv⟩
obtain ⟨r, hrS, hsr, htr⟩ : ∃ r ∈ S, s ⊆ r ∧ t ⊆ r := K s hsS t htS
have Hnuv : (r ∩ (u ∩ v)).Nonempty :=
H _ hrS u v hu hv ((subset_sUnion_of_mem hrS).trans Huv) ⟨a, hsr has, hau⟩ ⟨b, htr hbt, hbv⟩
have Kruv : r ∩ (u ∩ v) ⊆ ⋃₀ S ∩ (u ∩ v) := inter_subset_inter_left _ (subset_sUnion_of_mem hrS)
exact Hnuv.mono Kruv
#align is_preconnected.sUnion_directed IsPreconnected.sUnion_directed
/-- The biUnion of a family of preconnected sets is preconnected if the graph determined by
whether two sets intersect is preconnected. -/
theorem IsPreconnected.biUnion_of_reflTransGen {ι : Type*} {t : Set ι} {s : ι → Set α}
(H : ∀ i ∈ t, IsPreconnected (s i))
(K : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen (fun i j => (s i ∩ s j).Nonempty ∧ i ∈ t) i j) :
IsPreconnected (⋃ n ∈ t, s n) := by
let R := fun i j : ι => (s i ∩ s j).Nonempty ∧ i ∈ t
have P : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen R i j →
∃ p, p ⊆ t ∧ i ∈ p ∧ j ∈ p ∧ IsPreconnected (⋃ j ∈ p, s j) := fun i hi j hj h => by
induction h with
| refl =>
refine ⟨{i}, singleton_subset_iff.mpr hi, mem_singleton i, mem_singleton i, ?_⟩
rw [biUnion_singleton]
exact H i hi
| @tail j k _ hjk ih =>
obtain ⟨p, hpt, hip, hjp, hp⟩ := ih hjk.2
refine ⟨insert k p, insert_subset_iff.mpr ⟨hj, hpt⟩, mem_insert_of_mem k hip,
mem_insert k p, ?_⟩
rw [biUnion_insert]
refine (H k hj).union' (hjk.1.mono ?_) hp
rw [inter_comm]
exact inter_subset_inter_right _ (subset_biUnion_of_mem hjp)
refine isPreconnected_of_forall_pair ?_
intro x hx y hy
obtain ⟨i : ι, hi : i ∈ t, hxi : x ∈ s i⟩ := mem_iUnion₂.1 hx
obtain ⟨j : ι, hj : j ∈ t, hyj : y ∈ s j⟩ := mem_iUnion₂.1 hy
obtain ⟨p, hpt, hip, hjp, hp⟩ := P i hi j hj (K i hi j hj)
exact ⟨⋃ j ∈ p, s j, biUnion_subset_biUnion_left hpt, mem_biUnion hip hxi,
mem_biUnion hjp hyj, hp⟩
#align is_preconnected.bUnion_of_refl_trans_gen IsPreconnected.biUnion_of_reflTransGen
/-- The biUnion of a family of preconnected sets is preconnected if the graph determined by
whether two sets intersect is preconnected. -/
theorem IsConnected.biUnion_of_reflTransGen {ι : Type*} {t : Set ι} {s : ι → Set α}
(ht : t.Nonempty) (H : ∀ i ∈ t, IsConnected (s i))
(K : ∀ i, i ∈ t → ∀ j, j ∈ t → ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty ∧ i ∈ t) i j) :
IsConnected (⋃ n ∈ t, s n) :=
⟨nonempty_biUnion.2 <| ⟨ht.some, ht.some_mem, (H _ ht.some_mem).nonempty⟩,
IsPreconnected.biUnion_of_reflTransGen (fun i hi => (H i hi).isPreconnected) K⟩
#align is_connected.bUnion_of_refl_trans_gen IsConnected.biUnion_of_reflTransGen
/-- Preconnectedness of the iUnion of a family of preconnected sets
indexed by the vertices of a preconnected graph,
where two vertices are joined when the corresponding sets intersect. -/
theorem IsPreconnected.iUnion_of_reflTransGen {ι : Type*} {s : ι → Set α}
(H : ∀ i, IsPreconnected (s i))
(K : ∀ i j, ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty) i j) :
IsPreconnected (⋃ n, s n) := by
rw [← biUnion_univ]
exact IsPreconnected.biUnion_of_reflTransGen (fun i _ => H i) fun i _ j _ => by
simpa [mem_univ] using K i j
#align is_preconnected.Union_of_refl_trans_gen IsPreconnected.iUnion_of_reflTransGen
theorem IsConnected.iUnion_of_reflTransGen {ι : Type*} [Nonempty ι] {s : ι → Set α}
(H : ∀ i, IsConnected (s i))
(K : ∀ i j, ReflTransGen (fun i j : ι => (s i ∩ s j).Nonempty) i j) : IsConnected (⋃ n, s n) :=
⟨nonempty_iUnion.2 <| Nonempty.elim ‹_› fun i : ι => ⟨i, (H _).nonempty⟩,
IsPreconnected.iUnion_of_reflTransGen (fun i => (H i).isPreconnected) K⟩
#align is_connected.Union_of_refl_trans_gen IsConnected.iUnion_of_reflTransGen
section SuccOrder
open Order
variable [LinearOrder β] [SuccOrder β] [IsSuccArchimedean β]
/-- The iUnion of connected sets indexed by a type with an archimedean successor (like `ℕ` or `ℤ`)
such that any two neighboring sets meet is preconnected. -/
theorem IsPreconnected.iUnion_of_chain {s : β → Set α} (H : ∀ n, IsPreconnected (s n))
(K : ∀ n, (s n ∩ s (succ n)).Nonempty) : IsPreconnected (⋃ n, s n) :=
IsPreconnected.iUnion_of_reflTransGen H fun i j =>
reflTransGen_of_succ _ (fun i _ => K i) fun i _ => by
rw [inter_comm]
exact K i
#align is_preconnected.Union_of_chain IsPreconnected.iUnion_of_chain
/-- The iUnion of connected sets indexed by a type with an archimedean successor (like `ℕ` or `ℤ`)
such that any two neighboring sets meet is connected. -/
theorem IsConnected.iUnion_of_chain [Nonempty β] {s : β → Set α} (H : ∀ n, IsConnected (s n))
(K : ∀ n, (s n ∩ s (succ n)).Nonempty) : IsConnected (⋃ n, s n) :=
IsConnected.iUnion_of_reflTransGen H fun i j =>
reflTransGen_of_succ _ (fun i _ => K i) fun i _ => by
rw [inter_comm]
exact K i
#align is_connected.Union_of_chain IsConnected.iUnion_of_chain
/-- The iUnion of preconnected sets indexed by a subset of a type with an archimedean successor
(like `ℕ` or `ℤ`) such that any two neighboring sets meet is preconnected. -/
theorem IsPreconnected.biUnion_of_chain {s : β → Set α} {t : Set β} (ht : OrdConnected t)
(H : ∀ n ∈ t, IsPreconnected (s n))
(K : ∀ n : β, n ∈ t → succ n ∈ t → (s n ∩ s (succ n)).Nonempty) :
IsPreconnected (⋃ n ∈ t, s n) := by
have h1 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → k ∈ t := fun hi hj hk =>
ht.out hi hj (Ico_subset_Icc_self hk)
have h2 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → succ k ∈ t := fun hi hj hk =>
ht.out hi hj ⟨hk.1.trans <| le_succ _, succ_le_of_lt hk.2⟩
have h3 : ∀ {i j k : β}, i ∈ t → j ∈ t → k ∈ Ico i j → (s k ∩ s (succ k)).Nonempty :=
fun hi hj hk => K _ (h1 hi hj hk) (h2 hi hj hk)
refine IsPreconnected.biUnion_of_reflTransGen H fun i hi j hj => ?_
exact reflTransGen_of_succ _ (fun k hk => ⟨h3 hi hj hk, h1 hi hj hk⟩) fun k hk =>
⟨by rw [inter_comm]; exact h3 hj hi hk, h2 hj hi hk⟩
#align is_preconnected.bUnion_of_chain IsPreconnected.biUnion_of_chain
/-- The iUnion of connected sets indexed by a subset of a type with an archimedean successor
(like `ℕ` or `ℤ`) such that any two neighboring sets meet is preconnected. -/
theorem IsConnected.biUnion_of_chain {s : β → Set α} {t : Set β} (hnt : t.Nonempty)
(ht : OrdConnected t) (H : ∀ n ∈ t, IsConnected (s n))
(K : ∀ n : β, n ∈ t → succ n ∈ t → (s n ∩ s (succ n)).Nonempty) : IsConnected (⋃ n ∈ t, s n) :=
⟨nonempty_biUnion.2 <| ⟨hnt.some, hnt.some_mem, (H _ hnt.some_mem).nonempty⟩,
IsPreconnected.biUnion_of_chain ht (fun i hi => (H i hi).isPreconnected) K⟩
#align is_connected.bUnion_of_chain IsConnected.biUnion_of_chain
end SuccOrder
/-- Theorem of bark and tree: if a set is within a preconnected set and its closure, then it is
preconnected as well. See also `IsConnected.subset_closure`. -/
protected theorem IsPreconnected.subset_closure {s : Set α} {t : Set α} (H : IsPreconnected s)
(Kst : s ⊆ t) (Ktcs : t ⊆ closure s) : IsPreconnected t :=
fun u v hu hv htuv ⟨_y, hyt, hyu⟩ ⟨_z, hzt, hzv⟩ =>
let ⟨p, hpu, hps⟩ := mem_closure_iff.1 (Ktcs hyt) u hu hyu
let ⟨q, hqv, hqs⟩ := mem_closure_iff.1 (Ktcs hzt) v hv hzv
let ⟨r, hrs, hruv⟩ := H u v hu hv (Subset.trans Kst htuv) ⟨p, hps, hpu⟩ ⟨q, hqs, hqv⟩
⟨r, Kst hrs, hruv⟩
#align is_preconnected.subset_closure IsPreconnected.subset_closure
/-- Theorem of bark and tree: if a set is within a connected set and its closure, then it is
connected as well. See also `IsPreconnected.subset_closure`. -/
protected theorem IsConnected.subset_closure {s : Set α} {t : Set α} (H : IsConnected s)
(Kst : s ⊆ t) (Ktcs : t ⊆ closure s) : IsConnected t :=
⟨Nonempty.mono Kst H.left, IsPreconnected.subset_closure H.right Kst Ktcs⟩
#align is_connected.subset_closure IsConnected.subset_closure
/-- The closure of a preconnected set is preconnected as well. -/
protected theorem IsPreconnected.closure {s : Set α} (H : IsPreconnected s) :
IsPreconnected (closure s) :=
IsPreconnected.subset_closure H subset_closure Subset.rfl
#align is_preconnected.closure IsPreconnected.closure
/-- The closure of a connected set is connected as well. -/
protected theorem IsConnected.closure {s : Set α} (H : IsConnected s) : IsConnected (closure s) :=
IsConnected.subset_closure H subset_closure <| Subset.rfl
#align is_connected.closure IsConnected.closure
/-- The image of a preconnected set is preconnected as well. -/
protected theorem IsPreconnected.image [TopologicalSpace β] {s : Set α} (H : IsPreconnected s)
(f : α → β) (hf : ContinuousOn f s) : IsPreconnected (f '' s) := by
-- Unfold/destruct definitions in hypotheses
rintro u v hu hv huv ⟨_, ⟨x, xs, rfl⟩, xu⟩ ⟨_, ⟨y, ys, rfl⟩, yv⟩
rcases continuousOn_iff'.1 hf u hu with ⟨u', hu', u'_eq⟩
rcases continuousOn_iff'.1 hf v hv with ⟨v', hv', v'_eq⟩
-- Reformulate `huv : f '' s ⊆ u ∪ v` in terms of `u'` and `v'`
replace huv : s ⊆ u' ∪ v' := by
rw [image_subset_iff, preimage_union] at huv
replace huv := subset_inter huv Subset.rfl
rw [union_inter_distrib_right, u'_eq, v'_eq, ← union_inter_distrib_right] at huv
exact (subset_inter_iff.1 huv).1
-- Now `s ⊆ u' ∪ v'`, so we can apply `‹IsPreconnected s›`
obtain ⟨z, hz⟩ : (s ∩ (u' ∩ v')).Nonempty := by
refine H u' v' hu' hv' huv ⟨x, ?_⟩ ⟨y, ?_⟩ <;> rw [inter_comm]
exacts [u'_eq ▸ ⟨xu, xs⟩, v'_eq ▸ ⟨yv, ys⟩]
rw [← inter_self s, inter_assoc, inter_left_comm s u', ← inter_assoc, inter_comm s, inter_comm s,
← u'_eq, ← v'_eq] at hz
exact ⟨f z, ⟨z, hz.1.2, rfl⟩, hz.1.1, hz.2.1⟩
#align is_preconnected.image IsPreconnected.image
/-- The image of a connected set is connected as well. -/
protected theorem IsConnected.image [TopologicalSpace β] {s : Set α} (H : IsConnected s) (f : α → β)
(hf : ContinuousOn f s) : IsConnected (f '' s) :=
⟨image_nonempty.mpr H.nonempty, H.isPreconnected.image f hf⟩
#align is_connected.image IsConnected.image
theorem isPreconnected_closed_iff {s : Set α} :
IsPreconnected s ↔ ∀ t t', IsClosed t → IsClosed t' →
s ⊆ t ∪ t' → (s ∩ t).Nonempty → (s ∩ t').Nonempty → (s ∩ (t ∩ t')).Nonempty :=
⟨by
rintro h t t' ht ht' htt' ⟨x, xs, xt⟩ ⟨y, ys, yt'⟩
rw [← not_disjoint_iff_nonempty_inter, ← subset_compl_iff_disjoint_right, compl_inter]
intro h'
have xt' : x ∉ t' := (h' xs).resolve_left (absurd xt)
have yt : y ∉ t := (h' ys).resolve_right (absurd yt')
have := h _ _ ht.isOpen_compl ht'.isOpen_compl h' ⟨y, ys, yt⟩ ⟨x, xs, xt'⟩
rw [← compl_union] at this
exact this.ne_empty htt'.disjoint_compl_right.inter_eq,
by
rintro h u v hu hv huv ⟨x, xs, xu⟩ ⟨y, ys, yv⟩
rw [← not_disjoint_iff_nonempty_inter, ← subset_compl_iff_disjoint_right, compl_inter]
intro h'
have xv : x ∉ v := (h' xs).elim (absurd xu) id
have yu : y ∉ u := (h' ys).elim id (absurd yv)
have := h _ _ hu.isClosed_compl hv.isClosed_compl h' ⟨y, ys, yu⟩ ⟨x, xs, xv⟩
rw [← compl_union] at this
exact this.ne_empty huv.disjoint_compl_right.inter_eq⟩
#align is_preconnected_closed_iff isPreconnected_closed_iff
theorem Inducing.isPreconnected_image [TopologicalSpace β] {s : Set α} {f : α → β}
(hf : Inducing f) : IsPreconnected (f '' s) ↔ IsPreconnected s := by
refine ⟨fun h => ?_, fun h => h.image _ hf.continuous.continuousOn⟩
rintro u v hu' hv' huv ⟨x, hxs, hxu⟩ ⟨y, hys, hyv⟩
rcases hf.isOpen_iff.1 hu' with ⟨u, hu, rfl⟩
rcases hf.isOpen_iff.1 hv' with ⟨v, hv, rfl⟩
replace huv : f '' s ⊆ u ∪ v := by rwa [image_subset_iff]
rcases h u v hu hv huv ⟨f x, mem_image_of_mem _ hxs, hxu⟩ ⟨f y, mem_image_of_mem _ hys, hyv⟩ with
⟨_, ⟨z, hzs, rfl⟩, hzuv⟩
exact ⟨z, hzs, hzuv⟩
#align inducing.is_preconnected_image Inducing.isPreconnected_image
/- TODO: The following lemmas about connection of preimages hold more generally for strict maps
(the quotient and subspace topologies of the image agree) whose fibers are preconnected. -/
| Mathlib/Topology/Connected/Basic.lean | 376 | 385 | theorem IsPreconnected.preimage_of_isOpenMap [TopologicalSpace β] {f : α → β} {s : Set β}
(hs : IsPreconnected s) (hinj : Function.Injective f) (hf : IsOpenMap f) (hsf : s ⊆ range f) :
IsPreconnected (f ⁻¹' s) := fun u v hu hv hsuv hsu hsv => by
replace hsf : f '' (f ⁻¹' s) = s := image_preimage_eq_of_subset hsf
obtain ⟨_, has, ⟨a, hau, rfl⟩, hav⟩ : (s ∩ (f '' u ∩ f '' v)).Nonempty := by |
refine hs (f '' u) (f '' v) (hf u hu) (hf v hv) ?_ ?_ ?_
· simpa only [hsf, image_union] using image_subset f hsuv
· simpa only [image_preimage_inter] using hsu.image f
· simpa only [image_preimage_inter] using hsv.image f
· exact ⟨a, has, hau, hinj.mem_set_image.1 hav⟩
|
/-
Copyright (c) 2021 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.Algebra.Group.Basic
import Mathlib.Algebra.Order.Monoid.Unbundled.Basic
import Mathlib.Order.Lattice
#align_import algebra.order.sub.defs from "leanprover-community/mathlib"@"de29c328903507bb7aff506af9135f4bdaf1849c"
/-!
# Ordered Subtraction
This file proves lemmas relating (truncated) subtraction with an order. We provide a class
`OrderedSub` stating that `a - b ≤ c ↔ a ≤ c + b`.
The subtraction discussed here could both be normal subtraction in an additive group or truncated
subtraction on a canonically ordered monoid (`ℕ`, `Multiset`, `PartENat`, `ENNReal`, ...)
## Implementation details
`OrderedSub` is a mixin type-class, so that we can use the results in this file even in cases
where we don't have a `CanonicallyOrderedAddCommMonoid` instance
(even though that is our main focus). Conversely, this means we can use
`CanonicallyOrderedAddCommMonoid` without necessarily having to define a subtraction.
The results in this file are ordered by the type-class assumption needed to prove it.
This means that similar results might not be close to each other. Furthermore, we don't prove
implications if a bi-implication can be proven under the same assumptions.
Lemmas using this class are named using `tsub` instead of `sub` (short for "truncated subtraction").
This is to avoid naming conflicts with similar lemmas about ordered groups.
We provide a second version of most results that require `[ContravariantClass α α (+) (≤)]`. In the
second version we replace this type-class assumption by explicit `AddLECancellable` assumptions.
TODO: maybe we should make a multiplicative version of this, so that we can replace some identical
lemmas about subtraction/division in `Ordered[Add]CommGroup` with these.
TODO: generalize `Nat.le_of_le_of_sub_le_sub_right`, `Nat.sub_le_sub_right_iff`,
`Nat.mul_self_sub_mul_self_eq`
-/
variable {α β : Type*}
/-- `OrderedSub α` means that `α` has a subtraction characterized by `a - b ≤ c ↔ a ≤ c + b`.
In other words, `a - b` is the least `c` such that `a ≤ b + c`.
This is satisfied both by the subtraction in additive ordered groups and by truncated subtraction
in canonically ordered monoids on many specific types.
-/
class OrderedSub (α : Type*) [LE α] [Add α] [Sub α] : Prop where
/-- `a - b` provides a lower bound on `c` such that `a ≤ c + b`. -/
tsub_le_iff_right : ∀ a b c : α, a - b ≤ c ↔ a ≤ c + b
#align has_ordered_sub OrderedSub
section Add
@[simp]
theorem tsub_le_iff_right [LE α] [Add α] [Sub α] [OrderedSub α] {a b c : α} :
a - b ≤ c ↔ a ≤ c + b :=
OrderedSub.tsub_le_iff_right a b c
#align tsub_le_iff_right tsub_le_iff_right
variable [Preorder α] [Add α] [Sub α] [OrderedSub α] {a b c d : α}
/-- See `add_tsub_cancel_right` for the equality if `ContravariantClass α α (+) (≤)`. -/
theorem add_tsub_le_right : a + b - b ≤ a :=
tsub_le_iff_right.mpr le_rfl
#align add_tsub_le_right add_tsub_le_right
theorem le_tsub_add : b ≤ b - a + a :=
tsub_le_iff_right.mp le_rfl
#align le_tsub_add le_tsub_add
end Add
/-! ### Preorder -/
section OrderedAddCommSemigroup
section Preorder
variable [Preorder α]
section AddCommSemigroup
variable [AddCommSemigroup α] [Sub α] [OrderedSub α] {a b c d : α}
/- TODO: Most results can be generalized to [Add α] [IsSymmOp α α (· + ·)] -/
theorem tsub_le_iff_left : a - b ≤ c ↔ a ≤ b + c := by rw [tsub_le_iff_right, add_comm]
#align tsub_le_iff_left tsub_le_iff_left
theorem le_add_tsub : a ≤ b + (a - b) :=
tsub_le_iff_left.mp le_rfl
#align le_add_tsub le_add_tsub
/-- See `add_tsub_cancel_left` for the equality if `ContravariantClass α α (+) (≤)`. -/
theorem add_tsub_le_left : a + b - a ≤ b :=
tsub_le_iff_left.mpr le_rfl
#align add_tsub_le_left add_tsub_le_left
@[gcongr] theorem tsub_le_tsub_right (h : a ≤ b) (c : α) : a - c ≤ b - c :=
tsub_le_iff_left.mpr <| h.trans le_add_tsub
#align tsub_le_tsub_right tsub_le_tsub_right
theorem tsub_le_iff_tsub_le : a - b ≤ c ↔ a - c ≤ b := by rw [tsub_le_iff_left, tsub_le_iff_right]
#align tsub_le_iff_tsub_le tsub_le_iff_tsub_le
/-- See `tsub_tsub_cancel_of_le` for the equality. -/
theorem tsub_tsub_le : b - (b - a) ≤ a :=
tsub_le_iff_right.mpr le_add_tsub
#align tsub_tsub_le tsub_tsub_le
section Cov
variable [CovariantClass α α (· + ·) (· ≤ ·)]
@[gcongr] theorem tsub_le_tsub_left (h : a ≤ b) (c : α) : c - b ≤ c - a :=
tsub_le_iff_left.mpr <| le_add_tsub.trans <| add_le_add_right h _
#align tsub_le_tsub_left tsub_le_tsub_left
@[gcongr] theorem tsub_le_tsub (hab : a ≤ b) (hcd : c ≤ d) : a - d ≤ b - c :=
(tsub_le_tsub_right hab _).trans <| tsub_le_tsub_left hcd _
#align tsub_le_tsub tsub_le_tsub
theorem antitone_const_tsub : Antitone fun x => c - x := fun _ _ hxy => tsub_le_tsub rfl.le hxy
#align antitone_const_tsub antitone_const_tsub
/-- See `add_tsub_assoc_of_le` for the equality. -/
theorem add_tsub_le_assoc : a + b - c ≤ a + (b - c) := by
rw [tsub_le_iff_left, add_left_comm]
exact add_le_add_left le_add_tsub a
#align add_tsub_le_assoc add_tsub_le_assoc
/-- See `tsub_add_eq_add_tsub` for the equality. -/
theorem add_tsub_le_tsub_add : a + b - c ≤ a - c + b := by
rw [add_comm, add_comm _ b]
exact add_tsub_le_assoc
#align add_tsub_le_tsub_add add_tsub_le_tsub_add
theorem add_le_add_add_tsub : a + b ≤ a + c + (b - c) := by
rw [add_assoc]
exact add_le_add_left le_add_tsub a
#align add_le_add_add_tsub add_le_add_add_tsub
theorem le_tsub_add_add : a + b ≤ a - c + (b + c) := by
rw [add_comm a, add_comm (a - c)]
exact add_le_add_add_tsub
#align le_tsub_add_add le_tsub_add_add
theorem tsub_le_tsub_add_tsub : a - c ≤ a - b + (b - c) := by
rw [tsub_le_iff_left, ← add_assoc, add_right_comm]
exact le_add_tsub.trans (add_le_add_right le_add_tsub _)
#align tsub_le_tsub_add_tsub tsub_le_tsub_add_tsub
theorem tsub_tsub_tsub_le_tsub : c - a - (c - b) ≤ b - a := by
rw [tsub_le_iff_left, tsub_le_iff_left, add_left_comm]
exact le_tsub_add.trans (add_le_add_left le_add_tsub _)
#align tsub_tsub_tsub_le_tsub tsub_tsub_tsub_le_tsub
theorem tsub_tsub_le_tsub_add {a b c : α} : a - (b - c) ≤ a - b + c :=
tsub_le_iff_right.2 <|
calc
a ≤ a - b + b := le_tsub_add
_ ≤ a - b + (c + (b - c)) := add_le_add_left le_add_tsub _
_ = a - b + c + (b - c) := (add_assoc _ _ _).symm
#align tsub_tsub_le_tsub_add tsub_tsub_le_tsub_add
/-- See `tsub_add_tsub_comm` for the equality. -/
theorem add_tsub_add_le_tsub_add_tsub : a + b - (c + d) ≤ a - c + (b - d) := by
rw [add_comm c, tsub_le_iff_left, add_assoc, ← tsub_le_iff_left, ← tsub_le_iff_left]
refine (tsub_le_tsub_right add_tsub_le_assoc c).trans ?_
rw [add_comm a, add_comm (a - c)]
exact add_tsub_le_assoc
#align add_tsub_add_le_tsub_add_tsub add_tsub_add_le_tsub_add_tsub
/-- See `add_tsub_add_eq_tsub_left` for the equality. -/
theorem add_tsub_add_le_tsub_left : a + b - (a + c) ≤ b - c := by
rw [tsub_le_iff_left, add_assoc]
exact add_le_add_left le_add_tsub _
#align add_tsub_add_le_tsub_left add_tsub_add_le_tsub_left
/-- See `add_tsub_add_eq_tsub_right` for the equality. -/
theorem add_tsub_add_le_tsub_right : a + c - (b + c) ≤ a - b := by
rw [tsub_le_iff_left, add_right_comm]
exact add_le_add_right le_add_tsub c
#align add_tsub_add_le_tsub_right add_tsub_add_le_tsub_right
end Cov
/-! #### Lemmas that assume that an element is `AddLECancellable` -/
namespace AddLECancellable
protected theorem le_add_tsub_swap (hb : AddLECancellable b) : a ≤ b + a - b :=
hb le_add_tsub
#align add_le_cancellable.le_add_tsub_swap AddLECancellable.le_add_tsub_swap
protected theorem le_add_tsub (hb : AddLECancellable b) : a ≤ a + b - b := by
rw [add_comm]
exact hb.le_add_tsub_swap
#align add_le_cancellable.le_add_tsub AddLECancellable.le_add_tsub
protected theorem le_tsub_of_add_le_left (ha : AddLECancellable a) (h : a + b ≤ c) : b ≤ c - a :=
ha <| h.trans le_add_tsub
#align add_le_cancellable.le_tsub_of_add_le_left AddLECancellable.le_tsub_of_add_le_left
protected theorem le_tsub_of_add_le_right (hb : AddLECancellable b) (h : a + b ≤ c) : a ≤ c - b :=
hb.le_tsub_of_add_le_left <| by rwa [add_comm]
#align add_le_cancellable.le_tsub_of_add_le_right AddLECancellable.le_tsub_of_add_le_right
end AddLECancellable
/-! ### Lemmas where addition is order-reflecting -/
section Contra
variable [ContravariantClass α α (· + ·) (· ≤ ·)]
theorem le_add_tsub_swap : a ≤ b + a - b :=
Contravariant.AddLECancellable.le_add_tsub_swap
#align le_add_tsub_swap le_add_tsub_swap
theorem le_add_tsub' : a ≤ a + b - b :=
Contravariant.AddLECancellable.le_add_tsub
#align le_add_tsub' le_add_tsub'
theorem le_tsub_of_add_le_left (h : a + b ≤ c) : b ≤ c - a :=
Contravariant.AddLECancellable.le_tsub_of_add_le_left h
#align le_tsub_of_add_le_left le_tsub_of_add_le_left
theorem le_tsub_of_add_le_right (h : a + b ≤ c) : a ≤ c - b :=
Contravariant.AddLECancellable.le_tsub_of_add_le_right h
#align le_tsub_of_add_le_right le_tsub_of_add_le_right
end Contra
end AddCommSemigroup
variable [AddCommMonoid α] [Sub α] [OrderedSub α] {a b c d : α}
theorem tsub_nonpos : a - b ≤ 0 ↔ a ≤ b := by rw [tsub_le_iff_left, add_zero]
#align tsub_nonpos tsub_nonpos
alias ⟨_, tsub_nonpos_of_le⟩ := tsub_nonpos
#align tsub_nonpos_of_le tsub_nonpos_of_le
end Preorder
/-! ### Partial order -/
variable [PartialOrder α] [AddCommSemigroup α] [Sub α] [OrderedSub α] {a b c d : α}
theorem tsub_tsub (b a c : α) : b - a - c = b - (a + c) := by
apply le_antisymm
· rw [tsub_le_iff_left, tsub_le_iff_left, ← add_assoc, ← tsub_le_iff_left]
· rw [tsub_le_iff_left, add_assoc, ← tsub_le_iff_left, ← tsub_le_iff_left]
#align tsub_tsub tsub_tsub
theorem tsub_add_eq_tsub_tsub (a b c : α) : a - (b + c) = a - b - c :=
(tsub_tsub _ _ _).symm
#align tsub_add_eq_tsub_tsub tsub_add_eq_tsub_tsub
| Mathlib/Algebra/Order/Sub/Defs.lean | 271 | 273 | theorem tsub_add_eq_tsub_tsub_swap (a b c : α) : a - (b + c) = a - c - b := by |
rw [add_comm]
apply tsub_add_eq_tsub_tsub
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Kenny Lau
-/
import Mathlib.Algebra.BigOperators.GroupWithZero.Finset
import Mathlib.Algebra.Group.Submonoid.Membership
import Mathlib.Algebra.Module.LinearMap.Basic
import Mathlib.Data.Finset.Preimage
import Mathlib.Data.Set.Finite
import Mathlib.GroupTheory.GroupAction.BigOperators
#align_import data.dfinsupp.basic from "leanprover-community/mathlib"@"6623e6af705e97002a9054c1c05a980180276fc1"
/-!
# Dependent functions with finite support
For a non-dependent version see `data/finsupp.lean`.
## Notation
This file introduces the notation `Π₀ a, β a` as notation for `DFinsupp β`, mirroring the `α →₀ β`
notation used for `Finsupp`. This works for nested binders too, with `Π₀ a b, γ a b` as notation
for `DFinsupp (fun a ↦ DFinsupp (γ a))`.
## Implementation notes
The support is internally represented (in the primed `DFinsupp.support'`) as a `Multiset` that
represents a superset of the true support of the function, quotiented by the always-true relation so
that this does not impact equality. This approach has computational benefits over storing a
`Finset`; it allows us to add together two finitely-supported functions without
having to evaluate the resulting function to recompute its support (which would required
decidability of `b = 0` for `b : β i`).
The true support of the function can still be recovered with `DFinsupp.support`; but these
decidability obligations are now postponed to when the support is actually needed. As a consequence,
there are two ways to sum a `DFinsupp`: with `DFinsupp.sum` which works over an arbitrary function
but requires recomputation of the support and therefore a `Decidable` argument; and with
`DFinsupp.sumAddHom` which requires an additive morphism, using its properties to show that
summing over a superset of the support is sufficient.
`Finsupp` takes an altogether different approach here; it uses `Classical.Decidable` and declares
the `Add` instance as noncomputable. This design difference is independent of the fact that
`DFinsupp` is dependently-typed and `Finsupp` is not; in future, we may want to align these two
definitions, or introduce two more definitions for the other combinations of decisions.
-/
universe u u₁ u₂ v v₁ v₂ v₃ w x y l
variable {ι : Type u} {γ : Type w} {β : ι → Type v} {β₁ : ι → Type v₁} {β₂ : ι → Type v₂}
variable (β)
/-- A dependent function `Π i, β i` with finite support, with notation `Π₀ i, β i`.
Note that `DFinsupp.support` is the preferred API for accessing the support of the function,
`DFinsupp.support'` is an implementation detail that aids computability; see the implementation
notes in this file for more information. -/
structure DFinsupp [∀ i, Zero (β i)] : Type max u v where mk' ::
/-- The underlying function of a dependent function with finite support (aka `DFinsupp`). -/
toFun : ∀ i, β i
/-- The support of a dependent function with finite support (aka `DFinsupp`). -/
support' : Trunc { s : Multiset ι // ∀ i, i ∈ s ∨ toFun i = 0 }
#align dfinsupp DFinsupp
variable {β}
/-- `Π₀ i, β i` denotes the type of dependent functions with finite support `DFinsupp β`. -/
notation3 "Π₀ "(...)", "r:(scoped f => DFinsupp f) => r
namespace DFinsupp
section Basic
variable [∀ i, Zero (β i)] [∀ i, Zero (β₁ i)] [∀ i, Zero (β₂ i)]
instance instDFunLike : DFunLike (Π₀ i, β i) ι β :=
⟨fun f => f.toFun, fun ⟨f₁, s₁⟩ ⟨f₂, s₁⟩ ↦ fun (h : f₁ = f₂) ↦ by
subst h
congr
apply Subsingleton.elim ⟩
#align dfinsupp.fun_like DFinsupp.instDFunLike
/-- Helper instance for when there are too many metavariables to apply `DFunLike.coeFunForall`
directly. -/
instance : CoeFun (Π₀ i, β i) fun _ => ∀ i, β i :=
inferInstance
@[simp]
theorem toFun_eq_coe (f : Π₀ i, β i) : f.toFun = f :=
rfl
#align dfinsupp.to_fun_eq_coe DFinsupp.toFun_eq_coe
@[ext]
theorem ext {f g : Π₀ i, β i} (h : ∀ i, f i = g i) : f = g :=
DFunLike.ext _ _ h
#align dfinsupp.ext DFinsupp.ext
#align dfinsupp.ext_iff DFunLike.ext_iff
#align dfinsupp.coe_fn_injective DFunLike.coe_injective
lemma ne_iff {f g : Π₀ i, β i} : f ≠ g ↔ ∃ i, f i ≠ g i := DFunLike.ne_iff
instance : Zero (Π₀ i, β i) :=
⟨⟨0, Trunc.mk <| ⟨∅, fun _ => Or.inr rfl⟩⟩⟩
instance : Inhabited (Π₀ i, β i) :=
⟨0⟩
@[simp, norm_cast] lemma coe_mk' (f : ∀ i, β i) (s) : ⇑(⟨f, s⟩ : Π₀ i, β i) = f := rfl
#align dfinsupp.coe_mk' DFinsupp.coe_mk'
@[simp, norm_cast] lemma coe_zero : ⇑(0 : Π₀ i, β i) = 0 := rfl
#align dfinsupp.coe_zero DFinsupp.coe_zero
theorem zero_apply (i : ι) : (0 : Π₀ i, β i) i = 0 :=
rfl
#align dfinsupp.zero_apply DFinsupp.zero_apply
/-- The composition of `f : β₁ → β₂` and `g : Π₀ i, β₁ i` is
`mapRange f hf g : Π₀ i, β₂ i`, well defined when `f 0 = 0`.
This preserves the structure on `f`, and exists in various bundled forms for when `f` is itself
bundled:
* `DFinsupp.mapRange.addMonoidHom`
* `DFinsupp.mapRange.addEquiv`
* `dfinsupp.mapRange.linearMap`
* `dfinsupp.mapRange.linearEquiv`
-/
def mapRange (f : ∀ i, β₁ i → β₂ i) (hf : ∀ i, f i 0 = 0) (x : Π₀ i, β₁ i) : Π₀ i, β₂ i :=
⟨fun i => f i (x i),
x.support'.map fun s => ⟨s.1, fun i => (s.2 i).imp_right fun h : x i = 0 => by
rw [← hf i, ← h]⟩⟩
#align dfinsupp.map_range DFinsupp.mapRange
@[simp]
theorem mapRange_apply (f : ∀ i, β₁ i → β₂ i) (hf : ∀ i, f i 0 = 0) (g : Π₀ i, β₁ i) (i : ι) :
mapRange f hf g i = f i (g i) :=
rfl
#align dfinsupp.map_range_apply DFinsupp.mapRange_apply
@[simp]
theorem mapRange_id (h : ∀ i, id (0 : β₁ i) = 0 := fun i => rfl) (g : Π₀ i : ι, β₁ i) :
mapRange (fun i => (id : β₁ i → β₁ i)) h g = g := by
ext
rfl
#align dfinsupp.map_range_id DFinsupp.mapRange_id
theorem mapRange_comp (f : ∀ i, β₁ i → β₂ i) (f₂ : ∀ i, β i → β₁ i) (hf : ∀ i, f i 0 = 0)
(hf₂ : ∀ i, f₂ i 0 = 0) (h : ∀ i, (f i ∘ f₂ i) 0 = 0) (g : Π₀ i : ι, β i) :
mapRange (fun i => f i ∘ f₂ i) h g = mapRange f hf (mapRange f₂ hf₂ g) := by
ext
simp only [mapRange_apply]; rfl
#align dfinsupp.map_range_comp DFinsupp.mapRange_comp
@[simp]
theorem mapRange_zero (f : ∀ i, β₁ i → β₂ i) (hf : ∀ i, f i 0 = 0) :
mapRange f hf (0 : Π₀ i, β₁ i) = 0 := by
ext
simp only [mapRange_apply, coe_zero, Pi.zero_apply, hf]
#align dfinsupp.map_range_zero DFinsupp.mapRange_zero
/-- Let `f i` be a binary operation `β₁ i → β₂ i → β i` such that `f i 0 0 = 0`.
Then `zipWith f hf` is a binary operation `Π₀ i, β₁ i → Π₀ i, β₂ i → Π₀ i, β i`. -/
def zipWith (f : ∀ i, β₁ i → β₂ i → β i) (hf : ∀ i, f i 0 0 = 0) (x : Π₀ i, β₁ i) (y : Π₀ i, β₂ i) :
Π₀ i, β i :=
⟨fun i => f i (x i) (y i), by
refine x.support'.bind fun xs => ?_
refine y.support'.map fun ys => ?_
refine ⟨xs + ys, fun i => ?_⟩
obtain h1 | (h1 : x i = 0) := xs.prop i
· left
rw [Multiset.mem_add]
left
exact h1
obtain h2 | (h2 : y i = 0) := ys.prop i
· left
rw [Multiset.mem_add]
right
exact h2
right; rw [← hf, ← h1, ← h2]⟩
#align dfinsupp.zip_with DFinsupp.zipWith
@[simp]
theorem zipWith_apply (f : ∀ i, β₁ i → β₂ i → β i) (hf : ∀ i, f i 0 0 = 0) (g₁ : Π₀ i, β₁ i)
(g₂ : Π₀ i, β₂ i) (i : ι) : zipWith f hf g₁ g₂ i = f i (g₁ i) (g₂ i) :=
rfl
#align dfinsupp.zip_with_apply DFinsupp.zipWith_apply
section Piecewise
variable (x y : Π₀ i, β i) (s : Set ι) [∀ i, Decidable (i ∈ s)]
/-- `x.piecewise y s` is the finitely supported function equal to `x` on the set `s`,
and to `y` on its complement. -/
def piecewise : Π₀ i, β i :=
zipWith (fun i x y => if i ∈ s then x else y) (fun _ => ite_self 0) x y
#align dfinsupp.piecewise DFinsupp.piecewise
theorem piecewise_apply (i : ι) : x.piecewise y s i = if i ∈ s then x i else y i :=
zipWith_apply _ _ x y i
#align dfinsupp.piecewise_apply DFinsupp.piecewise_apply
@[simp, norm_cast]
theorem coe_piecewise : ⇑(x.piecewise y s) = s.piecewise x y := by
ext
apply piecewise_apply
#align dfinsupp.coe_piecewise DFinsupp.coe_piecewise
end Piecewise
end Basic
section Algebra
instance [∀ i, AddZeroClass (β i)] : Add (Π₀ i, β i) :=
⟨zipWith (fun _ => (· + ·)) fun _ => add_zero 0⟩
theorem add_apply [∀ i, AddZeroClass (β i)] (g₁ g₂ : Π₀ i, β i) (i : ι) :
(g₁ + g₂) i = g₁ i + g₂ i :=
rfl
#align dfinsupp.add_apply DFinsupp.add_apply
@[simp, norm_cast]
theorem coe_add [∀ i, AddZeroClass (β i)] (g₁ g₂ : Π₀ i, β i) : ⇑(g₁ + g₂) = g₁ + g₂ :=
rfl
#align dfinsupp.coe_add DFinsupp.coe_add
instance addZeroClass [∀ i, AddZeroClass (β i)] : AddZeroClass (Π₀ i, β i) :=
DFunLike.coe_injective.addZeroClass _ coe_zero coe_add
instance instIsLeftCancelAdd [∀ i, AddZeroClass (β i)] [∀ i, IsLeftCancelAdd (β i)] :
IsLeftCancelAdd (Π₀ i, β i) where
add_left_cancel _ _ _ h := ext fun x => add_left_cancel <| DFunLike.congr_fun h x
instance instIsRightCancelAdd [∀ i, AddZeroClass (β i)] [∀ i, IsRightCancelAdd (β i)] :
IsRightCancelAdd (Π₀ i, β i) where
add_right_cancel _ _ _ h := ext fun x => add_right_cancel <| DFunLike.congr_fun h x
instance instIsCancelAdd [∀ i, AddZeroClass (β i)] [∀ i, IsCancelAdd (β i)] :
IsCancelAdd (Π₀ i, β i) where
/-- Note the general `SMul` instance doesn't apply as `ℕ` is not distributive
unless `β i`'s addition is commutative. -/
instance hasNatScalar [∀ i, AddMonoid (β i)] : SMul ℕ (Π₀ i, β i) :=
⟨fun c v => v.mapRange (fun _ => (c • ·)) fun _ => nsmul_zero _⟩
#align dfinsupp.has_nat_scalar DFinsupp.hasNatScalar
theorem nsmul_apply [∀ i, AddMonoid (β i)] (b : ℕ) (v : Π₀ i, β i) (i : ι) : (b • v) i = b • v i :=
rfl
#align dfinsupp.nsmul_apply DFinsupp.nsmul_apply
@[simp, norm_cast]
theorem coe_nsmul [∀ i, AddMonoid (β i)] (b : ℕ) (v : Π₀ i, β i) : ⇑(b • v) = b • ⇑v :=
rfl
#align dfinsupp.coe_nsmul DFinsupp.coe_nsmul
instance [∀ i, AddMonoid (β i)] : AddMonoid (Π₀ i, β i) :=
DFunLike.coe_injective.addMonoid _ coe_zero coe_add fun _ _ => coe_nsmul _ _
/-- Coercion from a `DFinsupp` to a pi type is an `AddMonoidHom`. -/
def coeFnAddMonoidHom [∀ i, AddZeroClass (β i)] : (Π₀ i, β i) →+ ∀ i, β i where
toFun := (⇑)
map_zero' := coe_zero
map_add' := coe_add
#align dfinsupp.coe_fn_add_monoid_hom DFinsupp.coeFnAddMonoidHom
/-- Evaluation at a point is an `AddMonoidHom`. This is the finitely-supported version of
`Pi.evalAddMonoidHom`. -/
def evalAddMonoidHom [∀ i, AddZeroClass (β i)] (i : ι) : (Π₀ i, β i) →+ β i :=
(Pi.evalAddMonoidHom β i).comp coeFnAddMonoidHom
#align dfinsupp.eval_add_monoid_hom DFinsupp.evalAddMonoidHom
instance addCommMonoid [∀ i, AddCommMonoid (β i)] : AddCommMonoid (Π₀ i, β i) :=
DFunLike.coe_injective.addCommMonoid _ coe_zero coe_add fun _ _ => coe_nsmul _ _
@[simp, norm_cast]
theorem coe_finset_sum {α} [∀ i, AddCommMonoid (β i)] (s : Finset α) (g : α → Π₀ i, β i) :
⇑(∑ a ∈ s, g a) = ∑ a ∈ s, ⇑(g a) :=
map_sum coeFnAddMonoidHom g s
#align dfinsupp.coe_finset_sum DFinsupp.coe_finset_sum
@[simp]
theorem finset_sum_apply {α} [∀ i, AddCommMonoid (β i)] (s : Finset α) (g : α → Π₀ i, β i) (i : ι) :
(∑ a ∈ s, g a) i = ∑ a ∈ s, g a i :=
map_sum (evalAddMonoidHom i) g s
#align dfinsupp.finset_sum_apply DFinsupp.finset_sum_apply
instance [∀ i, AddGroup (β i)] : Neg (Π₀ i, β i) :=
⟨fun f => f.mapRange (fun _ => Neg.neg) fun _ => neg_zero⟩
theorem neg_apply [∀ i, AddGroup (β i)] (g : Π₀ i, β i) (i : ι) : (-g) i = -g i :=
rfl
#align dfinsupp.neg_apply DFinsupp.neg_apply
@[simp, norm_cast] lemma coe_neg [∀ i, AddGroup (β i)] (g : Π₀ i, β i) : ⇑(-g) = -g := rfl
#align dfinsupp.coe_neg DFinsupp.coe_neg
instance [∀ i, AddGroup (β i)] : Sub (Π₀ i, β i) :=
⟨zipWith (fun _ => Sub.sub) fun _ => sub_zero 0⟩
theorem sub_apply [∀ i, AddGroup (β i)] (g₁ g₂ : Π₀ i, β i) (i : ι) : (g₁ - g₂) i = g₁ i - g₂ i :=
rfl
#align dfinsupp.sub_apply DFinsupp.sub_apply
@[simp, norm_cast]
theorem coe_sub [∀ i, AddGroup (β i)] (g₁ g₂ : Π₀ i, β i) : ⇑(g₁ - g₂) = g₁ - g₂ :=
rfl
#align dfinsupp.coe_sub DFinsupp.coe_sub
/-- Note the general `SMul` instance doesn't apply as `ℤ` is not distributive
unless `β i`'s addition is commutative. -/
instance hasIntScalar [∀ i, AddGroup (β i)] : SMul ℤ (Π₀ i, β i) :=
⟨fun c v => v.mapRange (fun _ => (c • ·)) fun _ => zsmul_zero _⟩
#align dfinsupp.has_int_scalar DFinsupp.hasIntScalar
theorem zsmul_apply [∀ i, AddGroup (β i)] (b : ℤ) (v : Π₀ i, β i) (i : ι) : (b • v) i = b • v i :=
rfl
#align dfinsupp.zsmul_apply DFinsupp.zsmul_apply
@[simp, norm_cast]
theorem coe_zsmul [∀ i, AddGroup (β i)] (b : ℤ) (v : Π₀ i, β i) : ⇑(b • v) = b • ⇑v :=
rfl
#align dfinsupp.coe_zsmul DFinsupp.coe_zsmul
instance [∀ i, AddGroup (β i)] : AddGroup (Π₀ i, β i) :=
DFunLike.coe_injective.addGroup _ coe_zero coe_add coe_neg coe_sub (fun _ _ => coe_nsmul _ _)
fun _ _ => coe_zsmul _ _
instance addCommGroup [∀ i, AddCommGroup (β i)] : AddCommGroup (Π₀ i, β i) :=
DFunLike.coe_injective.addCommGroup _ coe_zero coe_add coe_neg coe_sub (fun _ _ => coe_nsmul _ _)
fun _ _ => coe_zsmul _ _
/-- Dependent functions with finite support inherit a semiring action from an action on each
coordinate. -/
instance [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)] : SMul γ (Π₀ i, β i) :=
⟨fun c v => v.mapRange (fun _ => (c • ·)) fun _ => smul_zero _⟩
theorem smul_apply [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)] (b : γ)
(v : Π₀ i, β i) (i : ι) : (b • v) i = b • v i :=
rfl
#align dfinsupp.smul_apply DFinsupp.smul_apply
@[simp, norm_cast]
theorem coe_smul [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)] (b : γ)
(v : Π₀ i, β i) : ⇑(b • v) = b • ⇑v :=
rfl
#align dfinsupp.coe_smul DFinsupp.coe_smul
instance smulCommClass {δ : Type*} [Monoid γ] [Monoid δ] [∀ i, AddMonoid (β i)]
[∀ i, DistribMulAction γ (β i)] [∀ i, DistribMulAction δ (β i)] [∀ i, SMulCommClass γ δ (β i)] :
SMulCommClass γ δ (Π₀ i, β i) where
smul_comm r s m := ext fun i => by simp only [smul_apply, smul_comm r s (m i)]
instance isScalarTower {δ : Type*} [Monoid γ] [Monoid δ] [∀ i, AddMonoid (β i)]
[∀ i, DistribMulAction γ (β i)] [∀ i, DistribMulAction δ (β i)] [SMul γ δ]
[∀ i, IsScalarTower γ δ (β i)] : IsScalarTower γ δ (Π₀ i, β i) where
smul_assoc r s m := ext fun i => by simp only [smul_apply, smul_assoc r s (m i)]
instance isCentralScalar [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)]
[∀ i, DistribMulAction γᵐᵒᵖ (β i)] [∀ i, IsCentralScalar γ (β i)] :
IsCentralScalar γ (Π₀ i, β i) where
op_smul_eq_smul r m := ext fun i => by simp only [smul_apply, op_smul_eq_smul r (m i)]
/-- Dependent functions with finite support inherit a `DistribMulAction` structure from such a
structure on each coordinate. -/
instance distribMulAction [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)] :
DistribMulAction γ (Π₀ i, β i) :=
Function.Injective.distribMulAction coeFnAddMonoidHom DFunLike.coe_injective coe_smul
/-- Dependent functions with finite support inherit a module structure from such a structure on
each coordinate. -/
instance module [Semiring γ] [∀ i, AddCommMonoid (β i)] [∀ i, Module γ (β i)] :
Module γ (Π₀ i, β i) :=
{ inferInstanceAs (DistribMulAction γ (Π₀ i, β i)) with
zero_smul := fun c => ext fun i => by simp only [smul_apply, zero_smul, zero_apply]
add_smul := fun c x y => ext fun i => by simp only [add_apply, smul_apply, add_smul] }
#align dfinsupp.module DFinsupp.module
end Algebra
section FilterAndSubtypeDomain
/-- `Filter p f` is the function which is `f i` if `p i` is true and 0 otherwise. -/
def filter [∀ i, Zero (β i)] (p : ι → Prop) [DecidablePred p] (x : Π₀ i, β i) : Π₀ i, β i :=
⟨fun i => if p i then x i else 0,
x.support'.map fun xs =>
⟨xs.1, fun i => (xs.prop i).imp_right fun H : x i = 0 => by simp only [H, ite_self]⟩⟩
#align dfinsupp.filter DFinsupp.filter
@[simp]
theorem filter_apply [∀ i, Zero (β i)] (p : ι → Prop) [DecidablePred p] (i : ι) (f : Π₀ i, β i) :
f.filter p i = if p i then f i else 0 :=
rfl
#align dfinsupp.filter_apply DFinsupp.filter_apply
theorem filter_apply_pos [∀ i, Zero (β i)] {p : ι → Prop} [DecidablePred p] (f : Π₀ i, β i) {i : ι}
(h : p i) : f.filter p i = f i := by simp only [filter_apply, if_pos h]
#align dfinsupp.filter_apply_pos DFinsupp.filter_apply_pos
theorem filter_apply_neg [∀ i, Zero (β i)] {p : ι → Prop} [DecidablePred p] (f : Π₀ i, β i) {i : ι}
(h : ¬p i) : f.filter p i = 0 := by simp only [filter_apply, if_neg h]
#align dfinsupp.filter_apply_neg DFinsupp.filter_apply_neg
theorem filter_pos_add_filter_neg [∀ i, AddZeroClass (β i)] (f : Π₀ i, β i) (p : ι → Prop)
[DecidablePred p] : (f.filter p + f.filter fun i => ¬p i) = f :=
ext fun i => by
simp only [add_apply, filter_apply]; split_ifs <;> simp only [add_zero, zero_add]
#align dfinsupp.filter_pos_add_filter_neg DFinsupp.filter_pos_add_filter_neg
@[simp]
theorem filter_zero [∀ i, Zero (β i)] (p : ι → Prop) [DecidablePred p] :
(0 : Π₀ i, β i).filter p = 0 := by
ext
simp
#align dfinsupp.filter_zero DFinsupp.filter_zero
@[simp]
theorem filter_add [∀ i, AddZeroClass (β i)] (p : ι → Prop) [DecidablePred p] (f g : Π₀ i, β i) :
(f + g).filter p = f.filter p + g.filter p := by
ext
simp [ite_add_zero]
#align dfinsupp.filter_add DFinsupp.filter_add
@[simp]
theorem filter_smul [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)] (p : ι → Prop)
[DecidablePred p] (r : γ) (f : Π₀ i, β i) : (r • f).filter p = r • f.filter p := by
ext
simp [smul_apply, smul_ite]
#align dfinsupp.filter_smul DFinsupp.filter_smul
variable (γ β)
/-- `DFinsupp.filter` as an `AddMonoidHom`. -/
@[simps]
def filterAddMonoidHom [∀ i, AddZeroClass (β i)] (p : ι → Prop) [DecidablePred p] :
(Π₀ i, β i) →+ Π₀ i, β i where
toFun := filter p
map_zero' := filter_zero p
map_add' := filter_add p
#align dfinsupp.filter_add_monoid_hom DFinsupp.filterAddMonoidHom
#align dfinsupp.filter_add_monoid_hom_apply DFinsupp.filterAddMonoidHom_apply
/-- `DFinsupp.filter` as a `LinearMap`. -/
@[simps]
def filterLinearMap [Semiring γ] [∀ i, AddCommMonoid (β i)] [∀ i, Module γ (β i)] (p : ι → Prop)
[DecidablePred p] : (Π₀ i, β i) →ₗ[γ] Π₀ i, β i where
toFun := filter p
map_add' := filter_add p
map_smul' := filter_smul p
#align dfinsupp.filter_linear_map DFinsupp.filterLinearMap
#align dfinsupp.filter_linear_map_apply DFinsupp.filterLinearMap_apply
variable {γ β}
@[simp]
theorem filter_neg [∀ i, AddGroup (β i)] (p : ι → Prop) [DecidablePred p] (f : Π₀ i, β i) :
(-f).filter p = -f.filter p :=
(filterAddMonoidHom β p).map_neg f
#align dfinsupp.filter_neg DFinsupp.filter_neg
@[simp]
theorem filter_sub [∀ i, AddGroup (β i)] (p : ι → Prop) [DecidablePred p] (f g : Π₀ i, β i) :
(f - g).filter p = f.filter p - g.filter p :=
(filterAddMonoidHom β p).map_sub f g
#align dfinsupp.filter_sub DFinsupp.filter_sub
/-- `subtypeDomain p f` is the restriction of the finitely supported function
`f` to the subtype `p`. -/
def subtypeDomain [∀ i, Zero (β i)] (p : ι → Prop) [DecidablePred p] (x : Π₀ i, β i) :
Π₀ i : Subtype p, β i :=
⟨fun i => x (i : ι),
x.support'.map fun xs =>
⟨(Multiset.filter p xs.1).attach.map fun j => ⟨j.1, (Multiset.mem_filter.1 j.2).2⟩, fun i =>
(xs.prop i).imp_left fun H =>
Multiset.mem_map.2
⟨⟨i, Multiset.mem_filter.2 ⟨H, i.2⟩⟩, Multiset.mem_attach _ _, Subtype.eta _ _⟩⟩⟩
#align dfinsupp.subtype_domain DFinsupp.subtypeDomain
@[simp]
theorem subtypeDomain_zero [∀ i, Zero (β i)] {p : ι → Prop} [DecidablePred p] :
subtypeDomain p (0 : Π₀ i, β i) = 0 :=
rfl
#align dfinsupp.subtype_domain_zero DFinsupp.subtypeDomain_zero
@[simp]
theorem subtypeDomain_apply [∀ i, Zero (β i)] {p : ι → Prop} [DecidablePred p] {i : Subtype p}
{v : Π₀ i, β i} : (subtypeDomain p v) i = v i :=
rfl
#align dfinsupp.subtype_domain_apply DFinsupp.subtypeDomain_apply
@[simp]
theorem subtypeDomain_add [∀ i, AddZeroClass (β i)] {p : ι → Prop} [DecidablePred p]
(v v' : Π₀ i, β i) : (v + v').subtypeDomain p = v.subtypeDomain p + v'.subtypeDomain p :=
DFunLike.coe_injective rfl
#align dfinsupp.subtype_domain_add DFinsupp.subtypeDomain_add
@[simp]
theorem subtypeDomain_smul [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)]
{p : ι → Prop} [DecidablePred p] (r : γ) (f : Π₀ i, β i) :
(r • f).subtypeDomain p = r • f.subtypeDomain p :=
DFunLike.coe_injective rfl
#align dfinsupp.subtype_domain_smul DFinsupp.subtypeDomain_smul
variable (γ β)
/-- `subtypeDomain` but as an `AddMonoidHom`. -/
@[simps]
def subtypeDomainAddMonoidHom [∀ i, AddZeroClass (β i)] (p : ι → Prop) [DecidablePred p] :
(Π₀ i : ι, β i) →+ Π₀ i : Subtype p, β i where
toFun := subtypeDomain p
map_zero' := subtypeDomain_zero
map_add' := subtypeDomain_add
#align dfinsupp.subtype_domain_add_monoid_hom DFinsupp.subtypeDomainAddMonoidHom
#align dfinsupp.subtype_domain_add_monoid_hom_apply DFinsupp.subtypeDomainAddMonoidHom_apply
/-- `DFinsupp.subtypeDomain` as a `LinearMap`. -/
@[simps]
def subtypeDomainLinearMap [Semiring γ] [∀ i, AddCommMonoid (β i)] [∀ i, Module γ (β i)]
(p : ι → Prop) [DecidablePred p] : (Π₀ i, β i) →ₗ[γ] Π₀ i : Subtype p, β i where
toFun := subtypeDomain p
map_add' := subtypeDomain_add
map_smul' := subtypeDomain_smul
#align dfinsupp.subtype_domain_linear_map DFinsupp.subtypeDomainLinearMap
#align dfinsupp.subtype_domain_linear_map_apply DFinsupp.subtypeDomainLinearMap_apply
variable {γ β}
@[simp]
theorem subtypeDomain_neg [∀ i, AddGroup (β i)] {p : ι → Prop} [DecidablePred p] {v : Π₀ i, β i} :
(-v).subtypeDomain p = -v.subtypeDomain p :=
DFunLike.coe_injective rfl
#align dfinsupp.subtype_domain_neg DFinsupp.subtypeDomain_neg
@[simp]
theorem subtypeDomain_sub [∀ i, AddGroup (β i)] {p : ι → Prop} [DecidablePred p]
{v v' : Π₀ i, β i} : (v - v').subtypeDomain p = v.subtypeDomain p - v'.subtypeDomain p :=
DFunLike.coe_injective rfl
#align dfinsupp.subtype_domain_sub DFinsupp.subtypeDomain_sub
end FilterAndSubtypeDomain
variable [DecidableEq ι]
section Basic
variable [∀ i, Zero (β i)]
theorem finite_support (f : Π₀ i, β i) : Set.Finite { i | f i ≠ 0 } :=
Trunc.induction_on f.support' fun xs ↦
xs.1.finite_toSet.subset fun i H ↦ ((xs.prop i).resolve_right H)
#align dfinsupp.finite_support DFinsupp.finite_support
/-- Create an element of `Π₀ i, β i` from a finset `s` and a function `x`
defined on this `Finset`. -/
def mk (s : Finset ι) (x : ∀ i : (↑s : Set ι), β (i : ι)) : Π₀ i, β i :=
⟨fun i => if H : i ∈ s then x ⟨i, H⟩ else 0,
Trunc.mk ⟨s.1, fun i => if H : i ∈ s then Or.inl H else Or.inr <| dif_neg H⟩⟩
#align dfinsupp.mk DFinsupp.mk
variable {s : Finset ι} {x : ∀ i : (↑s : Set ι), β i} {i : ι}
@[simp]
theorem mk_apply : (mk s x : ∀ i, β i) i = if H : i ∈ s then x ⟨i, H⟩ else 0 :=
rfl
#align dfinsupp.mk_apply DFinsupp.mk_apply
theorem mk_of_mem (hi : i ∈ s) : (mk s x : ∀ i, β i) i = x ⟨i, hi⟩ :=
dif_pos hi
#align dfinsupp.mk_of_mem DFinsupp.mk_of_mem
theorem mk_of_not_mem (hi : i ∉ s) : (mk s x : ∀ i, β i) i = 0 :=
dif_neg hi
#align dfinsupp.mk_of_not_mem DFinsupp.mk_of_not_mem
theorem mk_injective (s : Finset ι) : Function.Injective (@mk ι β _ _ s) := by
intro x y H
ext i
have h1 : (mk s x : ∀ i, β i) i = (mk s y : ∀ i, β i) i := by rw [H]
obtain ⟨i, hi : i ∈ s⟩ := i
dsimp only [mk_apply, Subtype.coe_mk] at h1
simpa only [dif_pos hi] using h1
#align dfinsupp.mk_injective DFinsupp.mk_injective
instance unique [∀ i, Subsingleton (β i)] : Unique (Π₀ i, β i) :=
DFunLike.coe_injective.unique
#align dfinsupp.unique DFinsupp.unique
instance uniqueOfIsEmpty [IsEmpty ι] : Unique (Π₀ i, β i) :=
DFunLike.coe_injective.unique
#align dfinsupp.unique_of_is_empty DFinsupp.uniqueOfIsEmpty
/-- Given `Fintype ι`, `equivFunOnFintype` is the `Equiv` between `Π₀ i, β i` and `Π i, β i`.
(All dependent functions on a finite type are finitely supported.) -/
@[simps apply]
def equivFunOnFintype [Fintype ι] : (Π₀ i, β i) ≃ ∀ i, β i where
toFun := (⇑)
invFun f := ⟨f, Trunc.mk ⟨Finset.univ.1, fun _ => Or.inl <| Finset.mem_univ_val _⟩⟩
left_inv _ := DFunLike.coe_injective rfl
right_inv _ := rfl
#align dfinsupp.equiv_fun_on_fintype DFinsupp.equivFunOnFintype
#align dfinsupp.equiv_fun_on_fintype_apply DFinsupp.equivFunOnFintype_apply
@[simp]
theorem equivFunOnFintype_symm_coe [Fintype ι] (f : Π₀ i, β i) : equivFunOnFintype.symm f = f :=
Equiv.symm_apply_apply _ _
#align dfinsupp.equiv_fun_on_fintype_symm_coe DFinsupp.equivFunOnFintype_symm_coe
/-- The function `single i b : Π₀ i, β i` sends `i` to `b`
and all other points to `0`. -/
def single (i : ι) (b : β i) : Π₀ i, β i :=
⟨Pi.single i b,
Trunc.mk ⟨{i}, fun j => (Decidable.eq_or_ne j i).imp (by simp) fun h => Pi.single_eq_of_ne h _⟩⟩
#align dfinsupp.single DFinsupp.single
theorem single_eq_pi_single {i b} : ⇑(single i b : Π₀ i, β i) = Pi.single i b :=
rfl
#align dfinsupp.single_eq_pi_single DFinsupp.single_eq_pi_single
@[simp]
theorem single_apply {i i' b} :
(single i b : Π₀ i, β i) i' = if h : i = i' then Eq.recOn h b else 0 := by
rw [single_eq_pi_single, Pi.single, Function.update]
simp [@eq_comm _ i i']
#align dfinsupp.single_apply DFinsupp.single_apply
@[simp]
theorem single_zero (i) : (single i 0 : Π₀ i, β i) = 0 :=
DFunLike.coe_injective <| Pi.single_zero _
#align dfinsupp.single_zero DFinsupp.single_zero
-- @[simp] -- Porting note (#10618): simp can prove this
theorem single_eq_same {i b} : (single i b : Π₀ i, β i) i = b := by
simp only [single_apply, dite_eq_ite, ite_true]
#align dfinsupp.single_eq_same DFinsupp.single_eq_same
theorem single_eq_of_ne {i i' b} (h : i ≠ i') : (single i b : Π₀ i, β i) i' = 0 := by
simp only [single_apply, dif_neg h]
#align dfinsupp.single_eq_of_ne DFinsupp.single_eq_of_ne
theorem single_injective {i} : Function.Injective (single i : β i → Π₀ i, β i) := fun _ _ H =>
Pi.single_injective β i <| DFunLike.coe_injective.eq_iff.mpr H
#align dfinsupp.single_injective DFinsupp.single_injective
/-- Like `Finsupp.single_eq_single_iff`, but with a `HEq` due to dependent types -/
theorem single_eq_single_iff (i j : ι) (xi : β i) (xj : β j) :
DFinsupp.single i xi = DFinsupp.single j xj ↔ i = j ∧ HEq xi xj ∨ xi = 0 ∧ xj = 0 := by
constructor
· intro h
by_cases hij : i = j
· subst hij
exact Or.inl ⟨rfl, heq_of_eq (DFinsupp.single_injective h)⟩
· have h_coe : ⇑(DFinsupp.single i xi) = DFinsupp.single j xj := congr_arg (⇑) h
have hci := congr_fun h_coe i
have hcj := congr_fun h_coe j
rw [DFinsupp.single_eq_same] at hci hcj
rw [DFinsupp.single_eq_of_ne (Ne.symm hij)] at hci
rw [DFinsupp.single_eq_of_ne hij] at hcj
exact Or.inr ⟨hci, hcj.symm⟩
· rintro (⟨rfl, hxi⟩ | ⟨hi, hj⟩)
· rw [eq_of_heq hxi]
· rw [hi, hj, DFinsupp.single_zero, DFinsupp.single_zero]
#align dfinsupp.single_eq_single_iff DFinsupp.single_eq_single_iff
/-- `DFinsupp.single a b` is injective in `a`. For the statement that it is injective in `b`, see
`DFinsupp.single_injective` -/
theorem single_left_injective {b : ∀ i : ι, β i} (h : ∀ i, b i ≠ 0) :
Function.Injective (fun i => single i (b i) : ι → Π₀ i, β i) := fun _ _ H =>
(((single_eq_single_iff _ _ _ _).mp H).resolve_right fun hb => h _ hb.1).left
#align dfinsupp.single_left_injective DFinsupp.single_left_injective
@[simp]
theorem single_eq_zero {i : ι} {xi : β i} : single i xi = 0 ↔ xi = 0 := by
rw [← single_zero i, single_eq_single_iff]
simp
#align dfinsupp.single_eq_zero DFinsupp.single_eq_zero
theorem filter_single (p : ι → Prop) [DecidablePred p] (i : ι) (x : β i) :
(single i x).filter p = if p i then single i x else 0 := by
ext j
have := apply_ite (fun x : Π₀ i, β i => x j) (p i) (single i x) 0
dsimp at this
rw [filter_apply, this]
obtain rfl | hij := Decidable.eq_or_ne i j
· rfl
· rw [single_eq_of_ne hij, ite_self, ite_self]
#align dfinsupp.filter_single DFinsupp.filter_single
@[simp]
theorem filter_single_pos {p : ι → Prop} [DecidablePred p] (i : ι) (x : β i) (h : p i) :
(single i x).filter p = single i x := by rw [filter_single, if_pos h]
#align dfinsupp.filter_single_pos DFinsupp.filter_single_pos
@[simp]
theorem filter_single_neg {p : ι → Prop} [DecidablePred p] (i : ι) (x : β i) (h : ¬p i) :
(single i x).filter p = 0 := by rw [filter_single, if_neg h]
#align dfinsupp.filter_single_neg DFinsupp.filter_single_neg
/-- Equality of sigma types is sufficient (but not necessary) to show equality of `DFinsupp`s. -/
theorem single_eq_of_sigma_eq {i j} {xi : β i} {xj : β j} (h : (⟨i, xi⟩ : Sigma β) = ⟨j, xj⟩) :
DFinsupp.single i xi = DFinsupp.single j xj := by
cases h
rfl
#align dfinsupp.single_eq_of_sigma_eq DFinsupp.single_eq_of_sigma_eq
@[simp]
theorem equivFunOnFintype_single [Fintype ι] (i : ι) (m : β i) :
(@DFinsupp.equivFunOnFintype ι β _ _) (DFinsupp.single i m) = Pi.single i m := by
ext x
dsimp [Pi.single, Function.update]
simp [DFinsupp.single_eq_pi_single, @eq_comm _ i]
#align dfinsupp.equiv_fun_on_fintype_single DFinsupp.equivFunOnFintype_single
@[simp]
theorem equivFunOnFintype_symm_single [Fintype ι] (i : ι) (m : β i) :
(@DFinsupp.equivFunOnFintype ι β _ _).symm (Pi.single i m) = DFinsupp.single i m := by
ext i'
simp only [← single_eq_pi_single, equivFunOnFintype_symm_coe]
#align dfinsupp.equiv_fun_on_fintype_symm_single DFinsupp.equivFunOnFintype_symm_single
section SingleAndZipWith
variable [∀ i, Zero (β₁ i)] [∀ i, Zero (β₂ i)]
@[simp]
theorem zipWith_single_single (f : ∀ i, β₁ i → β₂ i → β i) (hf : ∀ i, f i 0 0 = 0)
{i} (b₁ : β₁ i) (b₂ : β₂ i) :
zipWith f hf (single i b₁) (single i b₂) = single i (f i b₁ b₂) := by
ext j
rw [zipWith_apply]
obtain rfl | hij := Decidable.eq_or_ne i j
· rw [single_eq_same, single_eq_same, single_eq_same]
· rw [single_eq_of_ne hij, single_eq_of_ne hij, single_eq_of_ne hij, hf]
end SingleAndZipWith
/-- Redefine `f i` to be `0`. -/
def erase (i : ι) (x : Π₀ i, β i) : Π₀ i, β i :=
⟨fun j ↦ if j = i then 0 else x.1 j,
x.support'.map fun xs ↦ ⟨xs.1, fun j ↦ (xs.prop j).imp_right (by simp only [·, ite_self])⟩⟩
#align dfinsupp.erase DFinsupp.erase
@[simp]
theorem erase_apply {i j : ι} {f : Π₀ i, β i} : (f.erase i) j = if j = i then 0 else f j :=
rfl
#align dfinsupp.erase_apply DFinsupp.erase_apply
-- @[simp] -- Porting note (#10618): simp can prove this
theorem erase_same {i : ι} {f : Π₀ i, β i} : (f.erase i) i = 0 := by simp
#align dfinsupp.erase_same DFinsupp.erase_same
theorem erase_ne {i i' : ι} {f : Π₀ i, β i} (h : i' ≠ i) : (f.erase i) i' = f i' := by simp [h]
#align dfinsupp.erase_ne DFinsupp.erase_ne
theorem piecewise_single_erase (x : Π₀ i, β i) (i : ι)
[∀ i' : ι, Decidable <| (i' ∈ ({i} : Set ι))] : -- Porting note: added Decidable hypothesis
(single i (x i)).piecewise (x.erase i) {i} = x := by
ext j; rw [piecewise_apply]; split_ifs with h
· rw [(id h : j = i), single_eq_same]
· exact erase_ne h
#align dfinsupp.piecewise_single_erase DFinsupp.piecewise_single_erase
theorem erase_eq_sub_single {β : ι → Type*} [∀ i, AddGroup (β i)] (f : Π₀ i, β i) (i : ι) :
f.erase i = f - single i (f i) := by
ext j
rcases eq_or_ne i j with (rfl | h)
· simp
· simp [erase_ne h.symm, single_eq_of_ne h, @eq_comm _ j, h]
#align dfinsupp.erase_eq_sub_single DFinsupp.erase_eq_sub_single
@[simp]
theorem erase_zero (i : ι) : erase i (0 : Π₀ i, β i) = 0 :=
ext fun _ => ite_self _
#align dfinsupp.erase_zero DFinsupp.erase_zero
@[simp]
theorem filter_ne_eq_erase (f : Π₀ i, β i) (i : ι) : f.filter (· ≠ i) = f.erase i := by
ext1 j
simp only [DFinsupp.filter_apply, DFinsupp.erase_apply, ite_not]
#align dfinsupp.filter_ne_eq_erase DFinsupp.filter_ne_eq_erase
@[simp]
theorem filter_ne_eq_erase' (f : Π₀ i, β i) (i : ι) : f.filter (i ≠ ·) = f.erase i := by
rw [← filter_ne_eq_erase f i]
congr with j
exact ne_comm
#align dfinsupp.filter_ne_eq_erase' DFinsupp.filter_ne_eq_erase'
theorem erase_single (j : ι) (i : ι) (x : β i) :
(single i x).erase j = if i = j then 0 else single i x := by
rw [← filter_ne_eq_erase, filter_single, ite_not]
#align dfinsupp.erase_single DFinsupp.erase_single
@[simp]
theorem erase_single_same (i : ι) (x : β i) : (single i x).erase i = 0 := by
rw [erase_single, if_pos rfl]
#align dfinsupp.erase_single_same DFinsupp.erase_single_same
@[simp]
theorem erase_single_ne {i j : ι} (x : β i) (h : i ≠ j) : (single i x).erase j = single i x := by
rw [erase_single, if_neg h]
#align dfinsupp.erase_single_ne DFinsupp.erase_single_ne
section Update
variable (f : Π₀ i, β i) (i) (b : β i)
/-- Replace the value of a `Π₀ i, β i` at a given point `i : ι` by a given value `b : β i`.
If `b = 0`, this amounts to removing `i` from the support.
Otherwise, `i` is added to it.
This is the (dependent) finitely-supported version of `Function.update`. -/
def update : Π₀ i, β i :=
⟨Function.update f i b,
f.support'.map fun s =>
⟨i ::ₘ s.1, fun j => by
rcases eq_or_ne i j with (rfl | hi)
· simp
· obtain hj | (hj : f j = 0) := s.prop j
· exact Or.inl (Multiset.mem_cons_of_mem hj)
· exact Or.inr ((Function.update_noteq hi.symm b _).trans hj)⟩⟩
#align dfinsupp.update DFinsupp.update
variable (j : ι)
@[simp, norm_cast] lemma coe_update : (f.update i b : ∀ i : ι, β i) = Function.update f i b := rfl
#align dfinsupp.coe_update DFinsupp.coe_update
@[simp]
theorem update_self : f.update i (f i) = f := by
ext
simp
#align dfinsupp.update_self DFinsupp.update_self
@[simp]
theorem update_eq_erase : f.update i 0 = f.erase i := by
ext j
rcases eq_or_ne i j with (rfl | hi)
· simp
· simp [hi.symm]
#align dfinsupp.update_eq_erase DFinsupp.update_eq_erase
theorem update_eq_single_add_erase {β : ι → Type*} [∀ i, AddZeroClass (β i)] (f : Π₀ i, β i)
(i : ι) (b : β i) : f.update i b = single i b + f.erase i := by
ext j
rcases eq_or_ne i j with (rfl | h)
· simp
· simp [Function.update_noteq h.symm, h, erase_ne, h.symm]
#align dfinsupp.update_eq_single_add_erase DFinsupp.update_eq_single_add_erase
theorem update_eq_erase_add_single {β : ι → Type*} [∀ i, AddZeroClass (β i)] (f : Π₀ i, β i)
(i : ι) (b : β i) : f.update i b = f.erase i + single i b := by
ext j
rcases eq_or_ne i j with (rfl | h)
· simp
· simp [Function.update_noteq h.symm, h, erase_ne, h.symm]
#align dfinsupp.update_eq_erase_add_single DFinsupp.update_eq_erase_add_single
theorem update_eq_sub_add_single {β : ι → Type*} [∀ i, AddGroup (β i)] (f : Π₀ i, β i) (i : ι)
(b : β i) : f.update i b = f - single i (f i) + single i b := by
rw [update_eq_erase_add_single f i b, erase_eq_sub_single f i]
#align dfinsupp.update_eq_sub_add_single DFinsupp.update_eq_sub_add_single
end Update
end Basic
section AddMonoid
variable [∀ i, AddZeroClass (β i)]
@[simp]
theorem single_add (i : ι) (b₁ b₂ : β i) : single i (b₁ + b₂) = single i b₁ + single i b₂ :=
(zipWith_single_single (fun _ => (· + ·)) _ b₁ b₂).symm
#align dfinsupp.single_add DFinsupp.single_add
@[simp]
theorem erase_add (i : ι) (f₁ f₂ : Π₀ i, β i) : erase i (f₁ + f₂) = erase i f₁ + erase i f₂ :=
ext fun _ => by simp [ite_zero_add]
#align dfinsupp.erase_add DFinsupp.erase_add
variable (β)
/-- `DFinsupp.single` as an `AddMonoidHom`. -/
@[simps]
def singleAddHom (i : ι) : β i →+ Π₀ i, β i where
toFun := single i
map_zero' := single_zero i
map_add' := single_add i
#align dfinsupp.single_add_hom DFinsupp.singleAddHom
#align dfinsupp.single_add_hom_apply DFinsupp.singleAddHom_apply
/-- `DFinsupp.erase` as an `AddMonoidHom`. -/
@[simps]
def eraseAddHom (i : ι) : (Π₀ i, β i) →+ Π₀ i, β i where
toFun := erase i
map_zero' := erase_zero i
map_add' := erase_add i
#align dfinsupp.erase_add_hom DFinsupp.eraseAddHom
#align dfinsupp.erase_add_hom_apply DFinsupp.eraseAddHom_apply
variable {β}
@[simp]
theorem single_neg {β : ι → Type v} [∀ i, AddGroup (β i)] (i : ι) (x : β i) :
single i (-x) = -single i x :=
(singleAddHom β i).map_neg x
#align dfinsupp.single_neg DFinsupp.single_neg
@[simp]
theorem single_sub {β : ι → Type v} [∀ i, AddGroup (β i)] (i : ι) (x y : β i) :
single i (x - y) = single i x - single i y :=
(singleAddHom β i).map_sub x y
#align dfinsupp.single_sub DFinsupp.single_sub
@[simp]
theorem erase_neg {β : ι → Type v} [∀ i, AddGroup (β i)] (i : ι) (f : Π₀ i, β i) :
(-f).erase i = -f.erase i :=
(eraseAddHom β i).map_neg f
#align dfinsupp.erase_neg DFinsupp.erase_neg
@[simp]
theorem erase_sub {β : ι → Type v} [∀ i, AddGroup (β i)] (i : ι) (f g : Π₀ i, β i) :
(f - g).erase i = f.erase i - g.erase i :=
(eraseAddHom β i).map_sub f g
#align dfinsupp.erase_sub DFinsupp.erase_sub
theorem single_add_erase (i : ι) (f : Π₀ i, β i) : single i (f i) + f.erase i = f :=
ext fun i' =>
if h : i = i' then by
subst h; simp only [add_apply, single_apply, erase_apply, add_zero, dite_eq_ite, if_true]
else by
simp only [add_apply, single_apply, erase_apply, dif_neg h, if_neg (Ne.symm h), zero_add]
#align dfinsupp.single_add_erase DFinsupp.single_add_erase
theorem erase_add_single (i : ι) (f : Π₀ i, β i) : f.erase i + single i (f i) = f :=
ext fun i' =>
if h : i = i' then by
subst h; simp only [add_apply, single_apply, erase_apply, zero_add, dite_eq_ite, if_true]
else by
simp only [add_apply, single_apply, erase_apply, dif_neg h, if_neg (Ne.symm h), add_zero]
#align dfinsupp.erase_add_single DFinsupp.erase_add_single
protected theorem induction {p : (Π₀ i, β i) → Prop} (f : Π₀ i, β i) (h0 : p 0)
(ha : ∀ (i b) (f : Π₀ i, β i), f i = 0 → b ≠ 0 → p f → p (single i b + f)) : p f := by
cases' f with f s
induction' s using Trunc.induction_on with s
cases' s with s H
induction' s using Multiset.induction_on with i s ih generalizing f
· have : f = 0 := funext fun i => (H i).resolve_left (Multiset.not_mem_zero _)
subst this
exact h0
have H2 : p (erase i ⟨f, Trunc.mk ⟨i ::ₘ s, H⟩⟩) := by
dsimp only [erase, Trunc.map, Trunc.bind, Trunc.liftOn, Trunc.lift_mk,
Function.comp, Subtype.coe_mk]
have H2 : ∀ j, j ∈ s ∨ ite (j = i) 0 (f j) = 0 := by
intro j
cases' H j with H2 H2
· cases' Multiset.mem_cons.1 H2 with H3 H3
· right; exact if_pos H3
· left; exact H3
right
split_ifs <;> [rfl; exact H2]
have H3 : ∀ aux, (⟨fun j : ι => ite (j = i) 0 (f j), Trunc.mk ⟨i ::ₘ s, aux⟩⟩ : Π₀ i, β i) =
⟨fun j : ι => ite (j = i) 0 (f j), Trunc.mk ⟨s, H2⟩⟩ :=
fun _ ↦ ext fun _ => rfl
rw [H3]
apply ih
have H3 : single i _ + _ = (⟨f, Trunc.mk ⟨i ::ₘ s, H⟩⟩ : Π₀ i, β i) := single_add_erase _ _
rw [← H3]
change p (single i (f i) + _)
cases' Classical.em (f i = 0) with h h
· rw [h, single_zero, zero_add]
exact H2
refine ha _ _ _ ?_ h H2
rw [erase_same]
#align dfinsupp.induction DFinsupp.induction
theorem induction₂ {p : (Π₀ i, β i) → Prop} (f : Π₀ i, β i) (h0 : p 0)
(ha : ∀ (i b) (f : Π₀ i, β i), f i = 0 → b ≠ 0 → p f → p (f + single i b)) : p f :=
DFinsupp.induction f h0 fun i b f h1 h2 h3 =>
have h4 : f + single i b = single i b + f := by
ext j; by_cases H : i = j
· subst H
simp [h1]
· simp [H]
Eq.recOn h4 <| ha i b f h1 h2 h3
#align dfinsupp.induction₂ DFinsupp.induction₂
@[simp]
theorem add_closure_iUnion_range_single :
AddSubmonoid.closure (⋃ i : ι, Set.range (single i : β i → Π₀ i, β i)) = ⊤ :=
top_unique fun x _ => by
apply DFinsupp.induction x
· exact AddSubmonoid.zero_mem _
exact fun a b f _ _ hf =>
AddSubmonoid.add_mem _
(AddSubmonoid.subset_closure <| Set.mem_iUnion.2 ⟨a, Set.mem_range_self _⟩) hf
#align dfinsupp.add_closure_Union_range_single DFinsupp.add_closure_iUnion_range_single
/-- If two additive homomorphisms from `Π₀ i, β i` are equal on each `single a b`, then
they are equal. -/
theorem addHom_ext {γ : Type w} [AddZeroClass γ] ⦃f g : (Π₀ i, β i) →+ γ⦄
(H : ∀ (i : ι) (y : β i), f (single i y) = g (single i y)) : f = g := by
refine AddMonoidHom.eq_of_eqOn_denseM add_closure_iUnion_range_single fun f hf => ?_
simp only [Set.mem_iUnion, Set.mem_range] at hf
rcases hf with ⟨x, y, rfl⟩
apply H
#align dfinsupp.add_hom_ext DFinsupp.addHom_ext
/-- If two additive homomorphisms from `Π₀ i, β i` are equal on each `single a b`, then
they are equal.
See note [partially-applied ext lemmas]. -/
@[ext]
theorem addHom_ext' {γ : Type w} [AddZeroClass γ] ⦃f g : (Π₀ i, β i) →+ γ⦄
(H : ∀ x, f.comp (singleAddHom β x) = g.comp (singleAddHom β x)) : f = g :=
addHom_ext fun x => DFunLike.congr_fun (H x)
#align dfinsupp.add_hom_ext' DFinsupp.addHom_ext'
end AddMonoid
@[simp]
theorem mk_add [∀ i, AddZeroClass (β i)] {s : Finset ι} {x y : ∀ i : (↑s : Set ι), β i} :
mk s (x + y) = mk s x + mk s y :=
ext fun i => by simp only [add_apply, mk_apply]; split_ifs <;> [rfl; rw [zero_add]]
#align dfinsupp.mk_add DFinsupp.mk_add
@[simp]
theorem mk_zero [∀ i, Zero (β i)] {s : Finset ι} : mk s (0 : ∀ i : (↑s : Set ι), β i.1) = 0 :=
ext fun i => by simp only [mk_apply]; split_ifs <;> rfl
#align dfinsupp.mk_zero DFinsupp.mk_zero
@[simp]
theorem mk_neg [∀ i, AddGroup (β i)] {s : Finset ι} {x : ∀ i : (↑s : Set ι), β i.1} :
mk s (-x) = -mk s x :=
ext fun i => by simp only [neg_apply, mk_apply]; split_ifs <;> [rfl; rw [neg_zero]]
#align dfinsupp.mk_neg DFinsupp.mk_neg
@[simp]
theorem mk_sub [∀ i, AddGroup (β i)] {s : Finset ι} {x y : ∀ i : (↑s : Set ι), β i.1} :
mk s (x - y) = mk s x - mk s y :=
ext fun i => by simp only [sub_apply, mk_apply]; split_ifs <;> [rfl; rw [sub_zero]]
#align dfinsupp.mk_sub DFinsupp.mk_sub
/-- If `s` is a subset of `ι` then `mk_addGroupHom s` is the canonical additive
group homomorphism from $\prod_{i\in s}\beta_i$ to $\prod_{\mathtt{i : \iota}}\beta_i.$-/
def mkAddGroupHom [∀ i, AddGroup (β i)] (s : Finset ι) :
(∀ i : (s : Set ι), β ↑i) →+ Π₀ i : ι, β i where
toFun := mk s
map_zero' := mk_zero
map_add' _ _ := mk_add
#align dfinsupp.mk_add_group_hom DFinsupp.mkAddGroupHom
section
variable [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)]
@[simp]
theorem mk_smul {s : Finset ι} (c : γ) (x : ∀ i : (↑s : Set ι), β (i : ι)) :
mk s (c • x) = c • mk s x :=
ext fun i => by simp only [smul_apply, mk_apply]; split_ifs <;> [rfl; rw [smul_zero]]
#align dfinsupp.mk_smul DFinsupp.mk_smul
@[simp]
theorem single_smul {i : ι} (c : γ) (x : β i) : single i (c • x) = c • single i x :=
ext fun i => by
simp only [smul_apply, single_apply]
split_ifs with h
· cases h; rfl
· rw [smul_zero]
#align dfinsupp.single_smul DFinsupp.single_smul
end
section SupportBasic
variable [∀ i, Zero (β i)] [∀ (i) (x : β i), Decidable (x ≠ 0)]
/-- Set `{i | f x ≠ 0}` as a `Finset`. -/
def support (f : Π₀ i, β i) : Finset ι :=
(f.support'.lift fun xs => (Multiset.toFinset xs.1).filter fun i => f i ≠ 0) <| by
rintro ⟨sx, hx⟩ ⟨sy, hy⟩
dsimp only [Subtype.coe_mk, toFun_eq_coe] at *
ext i; constructor
· intro H
rcases Finset.mem_filter.1 H with ⟨_, h⟩
exact Finset.mem_filter.2 ⟨Multiset.mem_toFinset.2 <| (hy i).resolve_right h, h⟩
· intro H
rcases Finset.mem_filter.1 H with ⟨_, h⟩
exact Finset.mem_filter.2 ⟨Multiset.mem_toFinset.2 <| (hx i).resolve_right h, h⟩
#align dfinsupp.support DFinsupp.support
@[simp]
theorem support_mk_subset {s : Finset ι} {x : ∀ i : (↑s : Set ι), β i.1} : (mk s x).support ⊆ s :=
fun _ H => Multiset.mem_toFinset.1 (Finset.mem_filter.1 H).1
#align dfinsupp.support_mk_subset DFinsupp.support_mk_subset
@[simp]
theorem support_mk'_subset {f : ∀ i, β i} {s : Multiset ι} {h} :
(mk' f <| Trunc.mk ⟨s, h⟩).support ⊆ s.toFinset := fun i H =>
Multiset.mem_toFinset.1 <| by simpa using (Finset.mem_filter.1 H).1
#align dfinsupp.support_mk'_subset DFinsupp.support_mk'_subset
@[simp]
| Mathlib/Data/DFinsupp/Basic.lean | 1,107 | 1,112 | theorem mem_support_toFun (f : Π₀ i, β i) (i) : i ∈ f.support ↔ f i ≠ 0 := by |
cases' f with f s
induction' s using Trunc.induction_on with s
dsimp only [support, Trunc.lift_mk]
rw [Finset.mem_filter, Multiset.mem_toFinset, coe_mk']
exact and_iff_right_of_imp (s.prop i).resolve_right
|
/-
Copyright (c) 2019 Reid Barton. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Patrick Massot, Sébastien Gouëzel, Zhouhang Zhou, Reid Barton
-/
import Mathlib.Logic.Equiv.Fin
import Mathlib.Topology.DenseEmbedding
import Mathlib.Topology.Support
import Mathlib.Topology.Connected.LocallyConnected
#align_import topology.homeomorph from "leanprover-community/mathlib"@"4c3e1721c58ef9087bbc2c8c38b540f70eda2e53"
/-!
# Homeomorphisms
This file defines homeomorphisms between two topological spaces. They are bijections with both
directions continuous. We denote homeomorphisms with the notation `≃ₜ`.
# Main definitions
* `Homeomorph X Y`: The type of homeomorphisms from `X` to `Y`.
This type can be denoted using the following notation: `X ≃ₜ Y`.
# Main results
* Pretty much every topological property is preserved under homeomorphisms.
* `Homeomorph.homeomorphOfContinuousOpen`: A continuous bijection that is
an open map is a homeomorphism.
-/
open Set Filter
open Topology
variable {X : Type*} {Y : Type*} {Z : Type*}
-- not all spaces are homeomorphic to each other
/-- Homeomorphism between `X` and `Y`, also called topological isomorphism -/
structure Homeomorph (X : Type*) (Y : Type*) [TopologicalSpace X] [TopologicalSpace Y]
extends X ≃ Y where
/-- The forward map of a homeomorphism is a continuous function. -/
continuous_toFun : Continuous toFun := by continuity
/-- The inverse map of a homeomorphism is a continuous function. -/
continuous_invFun : Continuous invFun := by continuity
#align homeomorph Homeomorph
@[inherit_doc]
infixl:25 " ≃ₜ " => Homeomorph
namespace Homeomorph
variable [TopologicalSpace X] [TopologicalSpace Y] [TopologicalSpace Z]
{X' Y' : Type*} [TopologicalSpace X'] [TopologicalSpace Y']
theorem toEquiv_injective : Function.Injective (toEquiv : X ≃ₜ Y → X ≃ Y)
| ⟨_, _, _⟩, ⟨_, _, _⟩, rfl => rfl
#align homeomorph.to_equiv_injective Homeomorph.toEquiv_injective
instance : EquivLike (X ≃ₜ Y) X Y where
coe := fun h => h.toEquiv
inv := fun h => h.toEquiv.symm
left_inv := fun h => h.left_inv
right_inv := fun h => h.right_inv
coe_injective' := fun _ _ H _ => toEquiv_injective <| DFunLike.ext' H
instance : CoeFun (X ≃ₜ Y) fun _ ↦ X → Y := ⟨DFunLike.coe⟩
@[simp] theorem homeomorph_mk_coe (a : X ≃ Y) (b c) : (Homeomorph.mk a b c : X → Y) = a :=
rfl
#align homeomorph.homeomorph_mk_coe Homeomorph.homeomorph_mk_coe
/-- The unique homeomorphism between two empty types. -/
protected def empty [IsEmpty X] [IsEmpty Y] : X ≃ₜ Y where
__ := Equiv.equivOfIsEmpty X Y
/-- Inverse of a homeomorphism. -/
@[symm]
protected def symm (h : X ≃ₜ Y) : Y ≃ₜ X where
continuous_toFun := h.continuous_invFun
continuous_invFun := h.continuous_toFun
toEquiv := h.toEquiv.symm
#align homeomorph.symm Homeomorph.symm
@[simp] theorem symm_symm (h : X ≃ₜ Y) : h.symm.symm = h := rfl
#align homeomorph.symm_symm Homeomorph.symm_symm
theorem symm_bijective : Function.Bijective (Homeomorph.symm : (X ≃ₜ Y) → Y ≃ₜ X) :=
Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩
/-- See Note [custom simps projection] -/
def Simps.symm_apply (h : X ≃ₜ Y) : Y → X :=
h.symm
#align homeomorph.simps.symm_apply Homeomorph.Simps.symm_apply
initialize_simps_projections Homeomorph (toFun → apply, invFun → symm_apply)
@[simp]
theorem coe_toEquiv (h : X ≃ₜ Y) : ⇑h.toEquiv = h :=
rfl
#align homeomorph.coe_to_equiv Homeomorph.coe_toEquiv
@[simp]
theorem coe_symm_toEquiv (h : X ≃ₜ Y) : ⇑h.toEquiv.symm = h.symm :=
rfl
#align homeomorph.coe_symm_to_equiv Homeomorph.coe_symm_toEquiv
@[ext]
theorem ext {h h' : X ≃ₜ Y} (H : ∀ x, h x = h' x) : h = h' :=
DFunLike.ext _ _ H
#align homeomorph.ext Homeomorph.ext
/-- Identity map as a homeomorphism. -/
@[simps! (config := .asFn) apply]
protected def refl (X : Type*) [TopologicalSpace X] : X ≃ₜ X where
continuous_toFun := continuous_id
continuous_invFun := continuous_id
toEquiv := Equiv.refl X
#align homeomorph.refl Homeomorph.refl
/-- Composition of two homeomorphisms. -/
@[trans]
protected def trans (h₁ : X ≃ₜ Y) (h₂ : Y ≃ₜ Z) : X ≃ₜ Z where
continuous_toFun := h₂.continuous_toFun.comp h₁.continuous_toFun
continuous_invFun := h₁.continuous_invFun.comp h₂.continuous_invFun
toEquiv := Equiv.trans h₁.toEquiv h₂.toEquiv
#align homeomorph.trans Homeomorph.trans
@[simp]
theorem trans_apply (h₁ : X ≃ₜ Y) (h₂ : Y ≃ₜ Z) (x : X) : h₁.trans h₂ x = h₂ (h₁ x) :=
rfl
#align homeomorph.trans_apply Homeomorph.trans_apply
@[simp]
theorem symm_trans_apply (f : X ≃ₜ Y) (g : Y ≃ₜ Z) (z : Z) :
(f.trans g).symm z = f.symm (g.symm z) := rfl
@[simp]
theorem homeomorph_mk_coe_symm (a : X ≃ Y) (b c) :
((Homeomorph.mk a b c).symm : Y → X) = a.symm :=
rfl
#align homeomorph.homeomorph_mk_coe_symm Homeomorph.homeomorph_mk_coe_symm
@[simp]
theorem refl_symm : (Homeomorph.refl X).symm = Homeomorph.refl X :=
rfl
#align homeomorph.refl_symm Homeomorph.refl_symm
@[continuity]
protected theorem continuous (h : X ≃ₜ Y) : Continuous h :=
h.continuous_toFun
#align homeomorph.continuous Homeomorph.continuous
-- otherwise `by continuity` can't prove continuity of `h.to_equiv.symm`
@[continuity]
protected theorem continuous_symm (h : X ≃ₜ Y) : Continuous h.symm :=
h.continuous_invFun
#align homeomorph.continuous_symm Homeomorph.continuous_symm
@[simp]
theorem apply_symm_apply (h : X ≃ₜ Y) (y : Y) : h (h.symm y) = y :=
h.toEquiv.apply_symm_apply y
#align homeomorph.apply_symm_apply Homeomorph.apply_symm_apply
@[simp]
theorem symm_apply_apply (h : X ≃ₜ Y) (x : X) : h.symm (h x) = x :=
h.toEquiv.symm_apply_apply x
#align homeomorph.symm_apply_apply Homeomorph.symm_apply_apply
@[simp]
theorem self_trans_symm (h : X ≃ₜ Y) : h.trans h.symm = Homeomorph.refl X := by
ext
apply symm_apply_apply
#align homeomorph.self_trans_symm Homeomorph.self_trans_symm
@[simp]
theorem symm_trans_self (h : X ≃ₜ Y) : h.symm.trans h = Homeomorph.refl Y := by
ext
apply apply_symm_apply
#align homeomorph.symm_trans_self Homeomorph.symm_trans_self
protected theorem bijective (h : X ≃ₜ Y) : Function.Bijective h :=
h.toEquiv.bijective
#align homeomorph.bijective Homeomorph.bijective
protected theorem injective (h : X ≃ₜ Y) : Function.Injective h :=
h.toEquiv.injective
#align homeomorph.injective Homeomorph.injective
protected theorem surjective (h : X ≃ₜ Y) : Function.Surjective h :=
h.toEquiv.surjective
#align homeomorph.surjective Homeomorph.surjective
/-- Change the homeomorphism `f` to make the inverse function definitionally equal to `g`. -/
def changeInv (f : X ≃ₜ Y) (g : Y → X) (hg : Function.RightInverse g f) : X ≃ₜ Y :=
haveI : g = f.symm := (f.left_inv.eq_rightInverse hg).symm
{ toFun := f
invFun := g
left_inv := by convert f.left_inv
right_inv := by convert f.right_inv using 1
continuous_toFun := f.continuous
continuous_invFun := by convert f.symm.continuous }
#align homeomorph.change_inv Homeomorph.changeInv
@[simp]
theorem symm_comp_self (h : X ≃ₜ Y) : h.symm ∘ h = id :=
funext h.symm_apply_apply
#align homeomorph.symm_comp_self Homeomorph.symm_comp_self
@[simp]
theorem self_comp_symm (h : X ≃ₜ Y) : h ∘ h.symm = id :=
funext h.apply_symm_apply
#align homeomorph.self_comp_symm Homeomorph.self_comp_symm
@[simp]
theorem range_coe (h : X ≃ₜ Y) : range h = univ :=
h.surjective.range_eq
#align homeomorph.range_coe Homeomorph.range_coe
theorem image_symm (h : X ≃ₜ Y) : image h.symm = preimage h :=
funext h.symm.toEquiv.image_eq_preimage
#align homeomorph.image_symm Homeomorph.image_symm
theorem preimage_symm (h : X ≃ₜ Y) : preimage h.symm = image h :=
(funext h.toEquiv.image_eq_preimage).symm
#align homeomorph.preimage_symm Homeomorph.preimage_symm
@[simp]
theorem image_preimage (h : X ≃ₜ Y) (s : Set Y) : h '' (h ⁻¹' s) = s :=
h.toEquiv.image_preimage s
#align homeomorph.image_preimage Homeomorph.image_preimage
@[simp]
theorem preimage_image (h : X ≃ₜ Y) (s : Set X) : h ⁻¹' (h '' s) = s :=
h.toEquiv.preimage_image s
#align homeomorph.preimage_image Homeomorph.preimage_image
lemma image_compl (h : X ≃ₜ Y) (s : Set X) : h '' (sᶜ) = (h '' s)ᶜ :=
h.toEquiv.image_compl s
protected theorem inducing (h : X ≃ₜ Y) : Inducing h :=
inducing_of_inducing_compose h.continuous h.symm.continuous <| by
simp only [symm_comp_self, inducing_id]
#align homeomorph.inducing Homeomorph.inducing
theorem induced_eq (h : X ≃ₜ Y) : TopologicalSpace.induced h ‹_› = ‹_› :=
h.inducing.1.symm
#align homeomorph.induced_eq Homeomorph.induced_eq
protected theorem quotientMap (h : X ≃ₜ Y) : QuotientMap h :=
QuotientMap.of_quotientMap_compose h.symm.continuous h.continuous <| by
simp only [self_comp_symm, QuotientMap.id]
#align homeomorph.quotient_map Homeomorph.quotientMap
theorem coinduced_eq (h : X ≃ₜ Y) : TopologicalSpace.coinduced h ‹_› = ‹_› :=
h.quotientMap.2.symm
#align homeomorph.coinduced_eq Homeomorph.coinduced_eq
protected theorem embedding (h : X ≃ₜ Y) : Embedding h :=
⟨h.inducing, h.injective⟩
#align homeomorph.embedding Homeomorph.embedding
/-- Homeomorphism given an embedding. -/
noncomputable def ofEmbedding (f : X → Y) (hf : Embedding f) : X ≃ₜ Set.range f where
continuous_toFun := hf.continuous.subtype_mk _
continuous_invFun := hf.continuous_iff.2 <| by simp [continuous_subtype_val]
toEquiv := Equiv.ofInjective f hf.inj
#align homeomorph.of_embedding Homeomorph.ofEmbedding
protected theorem secondCountableTopology [SecondCountableTopology Y]
(h : X ≃ₜ Y) : SecondCountableTopology X :=
h.inducing.secondCountableTopology
#align homeomorph.second_countable_topology Homeomorph.secondCountableTopology
/-- If `h : X → Y` is a homeomorphism, `h(s)` is compact iff `s` is. -/
@[simp]
theorem isCompact_image {s : Set X} (h : X ≃ₜ Y) : IsCompact (h '' s) ↔ IsCompact s :=
h.embedding.isCompact_iff.symm
#align homeomorph.is_compact_image Homeomorph.isCompact_image
/-- If `h : X → Y` is a homeomorphism, `h⁻¹(s)` is compact iff `s` is. -/
@[simp]
theorem isCompact_preimage {s : Set Y} (h : X ≃ₜ Y) : IsCompact (h ⁻¹' s) ↔ IsCompact s := by
rw [← image_symm]; exact h.symm.isCompact_image
#align homeomorph.is_compact_preimage Homeomorph.isCompact_preimage
/-- If `h : X → Y` is a homeomorphism, `s` is σ-compact iff `h(s)` is. -/
@[simp]
theorem isSigmaCompact_image {s : Set X} (h : X ≃ₜ Y) :
IsSigmaCompact (h '' s) ↔ IsSigmaCompact s :=
h.embedding.isSigmaCompact_iff.symm
/-- If `h : X → Y` is a homeomorphism, `h⁻¹(s)` is σ-compact iff `s` is. -/
@[simp]
theorem isSigmaCompact_preimage {s : Set Y} (h : X ≃ₜ Y) :
IsSigmaCompact (h ⁻¹' s) ↔ IsSigmaCompact s := by
rw [← image_symm]; exact h.symm.isSigmaCompact_image
@[simp]
theorem isPreconnected_image {s : Set X} (h : X ≃ₜ Y) :
IsPreconnected (h '' s) ↔ IsPreconnected s :=
⟨fun hs ↦ by simpa only [image_symm, preimage_image]
using hs.image _ h.symm.continuous.continuousOn,
fun hs ↦ hs.image _ h.continuous.continuousOn⟩
@[simp]
theorem isPreconnected_preimage {s : Set Y} (h : X ≃ₜ Y) :
IsPreconnected (h ⁻¹' s) ↔ IsPreconnected s := by
rw [← image_symm, isPreconnected_image]
@[simp]
theorem isConnected_image {s : Set X} (h : X ≃ₜ Y) :
IsConnected (h '' s) ↔ IsConnected s :=
image_nonempty.and h.isPreconnected_image
@[simp]
theorem isConnected_preimage {s : Set Y} (h : X ≃ₜ Y) :
IsConnected (h ⁻¹' s) ↔ IsConnected s := by
rw [← image_symm, isConnected_image]
theorem image_connectedComponentIn {s : Set X} (h : X ≃ₜ Y) {x : X} (hx : x ∈ s) :
h '' connectedComponentIn s x = connectedComponentIn (h '' s) (h x) := by
refine (h.continuous.image_connectedComponentIn_subset hx).antisymm ?_
have := h.symm.continuous.image_connectedComponentIn_subset (mem_image_of_mem h hx)
rwa [image_subset_iff, h.preimage_symm, h.image_symm, h.preimage_image, h.symm_apply_apply]
at this
@[simp]
theorem comap_cocompact (h : X ≃ₜ Y) : comap h (cocompact Y) = cocompact X :=
(comap_cocompact_le h.continuous).antisymm <|
(hasBasis_cocompact.le_basis_iff (hasBasis_cocompact.comap h)).2 fun K hK =>
⟨h ⁻¹' K, h.isCompact_preimage.2 hK, Subset.rfl⟩
#align homeomorph.comap_cocompact Homeomorph.comap_cocompact
@[simp]
theorem map_cocompact (h : X ≃ₜ Y) : map h (cocompact X) = cocompact Y := by
rw [← h.comap_cocompact, map_comap_of_surjective h.surjective]
#align homeomorph.map_cocompact Homeomorph.map_cocompact
protected theorem compactSpace [CompactSpace X] (h : X ≃ₜ Y) : CompactSpace Y where
isCompact_univ := h.symm.isCompact_preimage.2 isCompact_univ
#align homeomorph.compact_space Homeomorph.compactSpace
protected theorem t0Space [T0Space X] (h : X ≃ₜ Y) : T0Space Y :=
h.symm.embedding.t0Space
#align homeomorph.t0_space Homeomorph.t0Space
protected theorem t1Space [T1Space X] (h : X ≃ₜ Y) : T1Space Y :=
h.symm.embedding.t1Space
#align homeomorph.t1_space Homeomorph.t1Space
protected theorem t2Space [T2Space X] (h : X ≃ₜ Y) : T2Space Y :=
h.symm.embedding.t2Space
#align homeomorph.t2_space Homeomorph.t2Space
protected theorem t3Space [T3Space X] (h : X ≃ₜ Y) : T3Space Y :=
h.symm.embedding.t3Space
#align homeomorph.t3_space Homeomorph.t3Space
protected theorem denseEmbedding (h : X ≃ₜ Y) : DenseEmbedding h :=
{ h.embedding with dense := h.surjective.denseRange }
#align homeomorph.dense_embedding Homeomorph.denseEmbedding
@[simp]
theorem isOpen_preimage (h : X ≃ₜ Y) {s : Set Y} : IsOpen (h ⁻¹' s) ↔ IsOpen s :=
h.quotientMap.isOpen_preimage
#align homeomorph.is_open_preimage Homeomorph.isOpen_preimage
@[simp]
theorem isOpen_image (h : X ≃ₜ Y) {s : Set X} : IsOpen (h '' s) ↔ IsOpen s := by
rw [← preimage_symm, isOpen_preimage]
#align homeomorph.is_open_image Homeomorph.isOpen_image
protected theorem isOpenMap (h : X ≃ₜ Y) : IsOpenMap h := fun _ => h.isOpen_image.2
#align homeomorph.is_open_map Homeomorph.isOpenMap
@[simp]
theorem isClosed_preimage (h : X ≃ₜ Y) {s : Set Y} : IsClosed (h ⁻¹' s) ↔ IsClosed s := by
simp only [← isOpen_compl_iff, ← preimage_compl, isOpen_preimage]
#align homeomorph.is_closed_preimage Homeomorph.isClosed_preimage
@[simp]
| Mathlib/Topology/Homeomorph.lean | 383 | 384 | theorem isClosed_image (h : X ≃ₜ Y) {s : Set X} : IsClosed (h '' s) ↔ IsClosed s := by |
rw [← preimage_symm, isClosed_preimage]
|
/-
Copyright (c) 2022 Yaël Dillies, Sara Rousta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Sara Rousta
-/
import Mathlib.Data.SetLike.Basic
import Mathlib.Order.Interval.Set.OrdConnected
import Mathlib.Order.Interval.Set.OrderIso
import Mathlib.Data.Set.Lattice
#align_import order.upper_lower.basic from "leanprover-community/mathlib"@"c0c52abb75074ed8b73a948341f50521fbf43b4c"
/-!
# Up-sets and down-sets
This file defines upper and lower sets in an order.
## Main declarations
* `IsUpperSet`: Predicate for a set to be an upper set. This means every element greater than a
member of the set is in the set itself.
* `IsLowerSet`: Predicate for a set to be a lower set. This means every element less than a member
of the set is in the set itself.
* `UpperSet`: The type of upper sets.
* `LowerSet`: The type of lower sets.
* `upperClosure`: The greatest upper set containing a set.
* `lowerClosure`: The least lower set containing a set.
* `UpperSet.Ici`: Principal upper set. `Set.Ici` as an upper set.
* `UpperSet.Ioi`: Strict principal upper set. `Set.Ioi` as an upper set.
* `LowerSet.Iic`: Principal lower set. `Set.Iic` as a lower set.
* `LowerSet.Iio`: Strict principal lower set. `Set.Iio` as a lower set.
## Notation
* `×ˢ` is notation for `UpperSet.prod` / `LowerSet.prod`.
## Notes
Upper sets are ordered by **reverse** inclusion. This convention is motivated by the fact that this
makes them order-isomorphic to lower sets and antichains, and matches the convention on `Filter`.
## TODO
Lattice structure on antichains. Order equivalence between upper/lower sets and antichains.
-/
open Function OrderDual Set
variable {α β γ : Type*} {ι : Sort*} {κ : ι → Sort*}
/-! ### Unbundled upper/lower sets -/
section LE
variable [LE α] [LE β] {s t : Set α} {a : α}
/-- An upper set in an order `α` is a set such that any element greater than one of its members is
also a member. Also called up-set, upward-closed set. -/
@[aesop norm unfold]
def IsUpperSet (s : Set α) : Prop :=
∀ ⦃a b : α⦄, a ≤ b → a ∈ s → b ∈ s
#align is_upper_set IsUpperSet
/-- A lower set in an order `α` is a set such that any element less than one of its members is also
a member. Also called down-set, downward-closed set. -/
@[aesop norm unfold]
def IsLowerSet (s : Set α) : Prop :=
∀ ⦃a b : α⦄, b ≤ a → a ∈ s → b ∈ s
#align is_lower_set IsLowerSet
theorem isUpperSet_empty : IsUpperSet (∅ : Set α) := fun _ _ _ => id
#align is_upper_set_empty isUpperSet_empty
theorem isLowerSet_empty : IsLowerSet (∅ : Set α) := fun _ _ _ => id
#align is_lower_set_empty isLowerSet_empty
theorem isUpperSet_univ : IsUpperSet (univ : Set α) := fun _ _ _ => id
#align is_upper_set_univ isUpperSet_univ
theorem isLowerSet_univ : IsLowerSet (univ : Set α) := fun _ _ _ => id
#align is_lower_set_univ isLowerSet_univ
theorem IsUpperSet.compl (hs : IsUpperSet s) : IsLowerSet sᶜ := fun _a _b h hb ha => hb <| hs h ha
#align is_upper_set.compl IsUpperSet.compl
theorem IsLowerSet.compl (hs : IsLowerSet s) : IsUpperSet sᶜ := fun _a _b h hb ha => hb <| hs h ha
#align is_lower_set.compl IsLowerSet.compl
@[simp]
theorem isUpperSet_compl : IsUpperSet sᶜ ↔ IsLowerSet s :=
⟨fun h => by
convert h.compl
rw [compl_compl], IsLowerSet.compl⟩
#align is_upper_set_compl isUpperSet_compl
@[simp]
theorem isLowerSet_compl : IsLowerSet sᶜ ↔ IsUpperSet s :=
⟨fun h => by
convert h.compl
rw [compl_compl], IsUpperSet.compl⟩
#align is_lower_set_compl isLowerSet_compl
theorem IsUpperSet.union (hs : IsUpperSet s) (ht : IsUpperSet t) : IsUpperSet (s ∪ t) :=
fun _ _ h => Or.imp (hs h) (ht h)
#align is_upper_set.union IsUpperSet.union
theorem IsLowerSet.union (hs : IsLowerSet s) (ht : IsLowerSet t) : IsLowerSet (s ∪ t) :=
fun _ _ h => Or.imp (hs h) (ht h)
#align is_lower_set.union IsLowerSet.union
theorem IsUpperSet.inter (hs : IsUpperSet s) (ht : IsUpperSet t) : IsUpperSet (s ∩ t) :=
fun _ _ h => And.imp (hs h) (ht h)
#align is_upper_set.inter IsUpperSet.inter
theorem IsLowerSet.inter (hs : IsLowerSet s) (ht : IsLowerSet t) : IsLowerSet (s ∩ t) :=
fun _ _ h => And.imp (hs h) (ht h)
#align is_lower_set.inter IsLowerSet.inter
theorem isUpperSet_sUnion {S : Set (Set α)} (hf : ∀ s ∈ S, IsUpperSet s) : IsUpperSet (⋃₀ S) :=
fun _ _ h => Exists.imp fun _ hs => ⟨hs.1, hf _ hs.1 h hs.2⟩
#align is_upper_set_sUnion isUpperSet_sUnion
theorem isLowerSet_sUnion {S : Set (Set α)} (hf : ∀ s ∈ S, IsLowerSet s) : IsLowerSet (⋃₀ S) :=
fun _ _ h => Exists.imp fun _ hs => ⟨hs.1, hf _ hs.1 h hs.2⟩
#align is_lower_set_sUnion isLowerSet_sUnion
theorem isUpperSet_iUnion {f : ι → Set α} (hf : ∀ i, IsUpperSet (f i)) : IsUpperSet (⋃ i, f i) :=
isUpperSet_sUnion <| forall_mem_range.2 hf
#align is_upper_set_Union isUpperSet_iUnion
theorem isLowerSet_iUnion {f : ι → Set α} (hf : ∀ i, IsLowerSet (f i)) : IsLowerSet (⋃ i, f i) :=
isLowerSet_sUnion <| forall_mem_range.2 hf
#align is_lower_set_Union isLowerSet_iUnion
theorem isUpperSet_iUnion₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsUpperSet (f i j)) :
IsUpperSet (⋃ (i) (j), f i j) :=
isUpperSet_iUnion fun i => isUpperSet_iUnion <| hf i
#align is_upper_set_Union₂ isUpperSet_iUnion₂
theorem isLowerSet_iUnion₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsLowerSet (f i j)) :
IsLowerSet (⋃ (i) (j), f i j) :=
isLowerSet_iUnion fun i => isLowerSet_iUnion <| hf i
#align is_lower_set_Union₂ isLowerSet_iUnion₂
theorem isUpperSet_sInter {S : Set (Set α)} (hf : ∀ s ∈ S, IsUpperSet s) : IsUpperSet (⋂₀ S) :=
fun _ _ h => forall₂_imp fun s hs => hf s hs h
#align is_upper_set_sInter isUpperSet_sInter
theorem isLowerSet_sInter {S : Set (Set α)} (hf : ∀ s ∈ S, IsLowerSet s) : IsLowerSet (⋂₀ S) :=
fun _ _ h => forall₂_imp fun s hs => hf s hs h
#align is_lower_set_sInter isLowerSet_sInter
theorem isUpperSet_iInter {f : ι → Set α} (hf : ∀ i, IsUpperSet (f i)) : IsUpperSet (⋂ i, f i) :=
isUpperSet_sInter <| forall_mem_range.2 hf
#align is_upper_set_Inter isUpperSet_iInter
theorem isLowerSet_iInter {f : ι → Set α} (hf : ∀ i, IsLowerSet (f i)) : IsLowerSet (⋂ i, f i) :=
isLowerSet_sInter <| forall_mem_range.2 hf
#align is_lower_set_Inter isLowerSet_iInter
theorem isUpperSet_iInter₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsUpperSet (f i j)) :
IsUpperSet (⋂ (i) (j), f i j) :=
isUpperSet_iInter fun i => isUpperSet_iInter <| hf i
#align is_upper_set_Inter₂ isUpperSet_iInter₂
theorem isLowerSet_iInter₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsLowerSet (f i j)) :
IsLowerSet (⋂ (i) (j), f i j) :=
isLowerSet_iInter fun i => isLowerSet_iInter <| hf i
#align is_lower_set_Inter₂ isLowerSet_iInter₂
@[simp]
theorem isLowerSet_preimage_ofDual_iff : IsLowerSet (ofDual ⁻¹' s) ↔ IsUpperSet s :=
Iff.rfl
#align is_lower_set_preimage_of_dual_iff isLowerSet_preimage_ofDual_iff
@[simp]
theorem isUpperSet_preimage_ofDual_iff : IsUpperSet (ofDual ⁻¹' s) ↔ IsLowerSet s :=
Iff.rfl
#align is_upper_set_preimage_of_dual_iff isUpperSet_preimage_ofDual_iff
@[simp]
theorem isLowerSet_preimage_toDual_iff {s : Set αᵒᵈ} : IsLowerSet (toDual ⁻¹' s) ↔ IsUpperSet s :=
Iff.rfl
#align is_lower_set_preimage_to_dual_iff isLowerSet_preimage_toDual_iff
@[simp]
theorem isUpperSet_preimage_toDual_iff {s : Set αᵒᵈ} : IsUpperSet (toDual ⁻¹' s) ↔ IsLowerSet s :=
Iff.rfl
#align is_upper_set_preimage_to_dual_iff isUpperSet_preimage_toDual_iff
alias ⟨_, IsUpperSet.toDual⟩ := isLowerSet_preimage_ofDual_iff
#align is_upper_set.to_dual IsUpperSet.toDual
alias ⟨_, IsLowerSet.toDual⟩ := isUpperSet_preimage_ofDual_iff
#align is_lower_set.to_dual IsLowerSet.toDual
alias ⟨_, IsUpperSet.ofDual⟩ := isLowerSet_preimage_toDual_iff
#align is_upper_set.of_dual IsUpperSet.ofDual
alias ⟨_, IsLowerSet.ofDual⟩ := isUpperSet_preimage_toDual_iff
#align is_lower_set.of_dual IsLowerSet.ofDual
lemma IsUpperSet.isLowerSet_preimage_coe (hs : IsUpperSet s) :
IsLowerSet ((↑) ⁻¹' t : Set s) ↔ ∀ b ∈ s, ∀ c ∈ t, b ≤ c → b ∈ t := by aesop
lemma IsLowerSet.isUpperSet_preimage_coe (hs : IsLowerSet s) :
IsUpperSet ((↑) ⁻¹' t : Set s) ↔ ∀ b ∈ s, ∀ c ∈ t, c ≤ b → b ∈ t := by aesop
lemma IsUpperSet.sdiff (hs : IsUpperSet s) (ht : ∀ b ∈ s, ∀ c ∈ t, b ≤ c → b ∈ t) :
IsUpperSet (s \ t) :=
fun _b _c hbc hb ↦ ⟨hs hbc hb.1, fun hc ↦ hb.2 <| ht _ hb.1 _ hc hbc⟩
lemma IsLowerSet.sdiff (hs : IsLowerSet s) (ht : ∀ b ∈ s, ∀ c ∈ t, c ≤ b → b ∈ t) :
IsLowerSet (s \ t) :=
fun _b _c hcb hb ↦ ⟨hs hcb hb.1, fun hc ↦ hb.2 <| ht _ hb.1 _ hc hcb⟩
lemma IsUpperSet.sdiff_of_isLowerSet (hs : IsUpperSet s) (ht : IsLowerSet t) : IsUpperSet (s \ t) :=
hs.sdiff <| by aesop
lemma IsLowerSet.sdiff_of_isUpperSet (hs : IsLowerSet s) (ht : IsUpperSet t) : IsLowerSet (s \ t) :=
hs.sdiff <| by aesop
lemma IsUpperSet.erase (hs : IsUpperSet s) (has : ∀ b ∈ s, b ≤ a → b = a) : IsUpperSet (s \ {a}) :=
hs.sdiff <| by simpa using has
lemma IsLowerSet.erase (hs : IsLowerSet s) (has : ∀ b ∈ s, a ≤ b → b = a) : IsLowerSet (s \ {a}) :=
hs.sdiff <| by simpa using has
end LE
section Preorder
variable [Preorder α] [Preorder β] {s : Set α} {p : α → Prop} (a : α)
theorem isUpperSet_Ici : IsUpperSet (Ici a) := fun _ _ => ge_trans
#align is_upper_set_Ici isUpperSet_Ici
theorem isLowerSet_Iic : IsLowerSet (Iic a) := fun _ _ => le_trans
#align is_lower_set_Iic isLowerSet_Iic
theorem isUpperSet_Ioi : IsUpperSet (Ioi a) := fun _ _ => flip lt_of_lt_of_le
#align is_upper_set_Ioi isUpperSet_Ioi
theorem isLowerSet_Iio : IsLowerSet (Iio a) := fun _ _ => lt_of_le_of_lt
#align is_lower_set_Iio isLowerSet_Iio
theorem isUpperSet_iff_Ici_subset : IsUpperSet s ↔ ∀ ⦃a⦄, a ∈ s → Ici a ⊆ s := by
simp [IsUpperSet, subset_def, @forall_swap (_ ∈ s)]
#align is_upper_set_iff_Ici_subset isUpperSet_iff_Ici_subset
theorem isLowerSet_iff_Iic_subset : IsLowerSet s ↔ ∀ ⦃a⦄, a ∈ s → Iic a ⊆ s := by
simp [IsLowerSet, subset_def, @forall_swap (_ ∈ s)]
#align is_lower_set_iff_Iic_subset isLowerSet_iff_Iic_subset
alias ⟨IsUpperSet.Ici_subset, _⟩ := isUpperSet_iff_Ici_subset
#align is_upper_set.Ici_subset IsUpperSet.Ici_subset
alias ⟨IsLowerSet.Iic_subset, _⟩ := isLowerSet_iff_Iic_subset
#align is_lower_set.Iic_subset IsLowerSet.Iic_subset
theorem IsUpperSet.Ioi_subset (h : IsUpperSet s) ⦃a⦄ (ha : a ∈ s) : Ioi a ⊆ s :=
Ioi_subset_Ici_self.trans <| h.Ici_subset ha
#align is_upper_set.Ioi_subset IsUpperSet.Ioi_subset
theorem IsLowerSet.Iio_subset (h : IsLowerSet s) ⦃a⦄ (ha : a ∈ s) : Iio a ⊆ s :=
h.toDual.Ioi_subset ha
#align is_lower_set.Iio_subset IsLowerSet.Iio_subset
theorem IsUpperSet.ordConnected (h : IsUpperSet s) : s.OrdConnected :=
⟨fun _ ha _ _ => Icc_subset_Ici_self.trans <| h.Ici_subset ha⟩
#align is_upper_set.ord_connected IsUpperSet.ordConnected
theorem IsLowerSet.ordConnected (h : IsLowerSet s) : s.OrdConnected :=
⟨fun _ _ _ hb => Icc_subset_Iic_self.trans <| h.Iic_subset hb⟩
#align is_lower_set.ord_connected IsLowerSet.ordConnected
theorem IsUpperSet.preimage (hs : IsUpperSet s) {f : β → α} (hf : Monotone f) :
IsUpperSet (f ⁻¹' s : Set β) := fun _ _ h => hs <| hf h
#align is_upper_set.preimage IsUpperSet.preimage
theorem IsLowerSet.preimage (hs : IsLowerSet s) {f : β → α} (hf : Monotone f) :
IsLowerSet (f ⁻¹' s : Set β) := fun _ _ h => hs <| hf h
#align is_lower_set.preimage IsLowerSet.preimage
theorem IsUpperSet.image (hs : IsUpperSet s) (f : α ≃o β) : IsUpperSet (f '' s : Set β) := by
change IsUpperSet ((f : α ≃ β) '' s)
rw [Set.image_equiv_eq_preimage_symm]
exact hs.preimage f.symm.monotone
#align is_upper_set.image IsUpperSet.image
theorem IsLowerSet.image (hs : IsLowerSet s) (f : α ≃o β) : IsLowerSet (f '' s : Set β) := by
change IsLowerSet ((f : α ≃ β) '' s)
rw [Set.image_equiv_eq_preimage_symm]
exact hs.preimage f.symm.monotone
#align is_lower_set.image IsLowerSet.image
theorem OrderEmbedding.image_Ici (e : α ↪o β) (he : IsUpperSet (range e)) (a : α) :
e '' Ici a = Ici (e a) := by
rw [← e.preimage_Ici, image_preimage_eq_inter_range,
inter_eq_left.2 <| he.Ici_subset (mem_range_self _)]
theorem OrderEmbedding.image_Iic (e : α ↪o β) (he : IsLowerSet (range e)) (a : α) :
e '' Iic a = Iic (e a) :=
e.dual.image_Ici he a
theorem OrderEmbedding.image_Ioi (e : α ↪o β) (he : IsUpperSet (range e)) (a : α) :
e '' Ioi a = Ioi (e a) := by
rw [← e.preimage_Ioi, image_preimage_eq_inter_range,
inter_eq_left.2 <| he.Ioi_subset (mem_range_self _)]
theorem OrderEmbedding.image_Iio (e : α ↪o β) (he : IsLowerSet (range e)) (a : α) :
e '' Iio a = Iio (e a) :=
e.dual.image_Ioi he a
@[simp]
theorem Set.monotone_mem : Monotone (· ∈ s) ↔ IsUpperSet s :=
Iff.rfl
#align set.monotone_mem Set.monotone_mem
@[simp]
theorem Set.antitone_mem : Antitone (· ∈ s) ↔ IsLowerSet s :=
forall_swap
#align set.antitone_mem Set.antitone_mem
@[simp]
theorem isUpperSet_setOf : IsUpperSet { a | p a } ↔ Monotone p :=
Iff.rfl
#align is_upper_set_set_of isUpperSet_setOf
@[simp]
theorem isLowerSet_setOf : IsLowerSet { a | p a } ↔ Antitone p :=
forall_swap
#align is_lower_set_set_of isLowerSet_setOf
lemma IsUpperSet.upperBounds_subset (hs : IsUpperSet s) : s.Nonempty → upperBounds s ⊆ s :=
fun ⟨_a, ha⟩ _b hb ↦ hs (hb ha) ha
lemma IsLowerSet.lowerBounds_subset (hs : IsLowerSet s) : s.Nonempty → lowerBounds s ⊆ s :=
fun ⟨_a, ha⟩ _b hb ↦ hs (hb ha) ha
section OrderTop
variable [OrderTop α]
theorem IsLowerSet.top_mem (hs : IsLowerSet s) : ⊤ ∈ s ↔ s = univ :=
⟨fun h => eq_univ_of_forall fun _ => hs le_top h, fun h => h.symm ▸ mem_univ _⟩
#align is_lower_set.top_mem IsLowerSet.top_mem
theorem IsUpperSet.top_mem (hs : IsUpperSet s) : ⊤ ∈ s ↔ s.Nonempty :=
⟨fun h => ⟨_, h⟩, fun ⟨_a, ha⟩ => hs le_top ha⟩
#align is_upper_set.top_mem IsUpperSet.top_mem
theorem IsUpperSet.not_top_mem (hs : IsUpperSet s) : ⊤ ∉ s ↔ s = ∅ :=
hs.top_mem.not.trans not_nonempty_iff_eq_empty
#align is_upper_set.not_top_mem IsUpperSet.not_top_mem
end OrderTop
section OrderBot
variable [OrderBot α]
theorem IsUpperSet.bot_mem (hs : IsUpperSet s) : ⊥ ∈ s ↔ s = univ :=
⟨fun h => eq_univ_of_forall fun _ => hs bot_le h, fun h => h.symm ▸ mem_univ _⟩
#align is_upper_set.bot_mem IsUpperSet.bot_mem
theorem IsLowerSet.bot_mem (hs : IsLowerSet s) : ⊥ ∈ s ↔ s.Nonempty :=
⟨fun h => ⟨_, h⟩, fun ⟨_a, ha⟩ => hs bot_le ha⟩
#align is_lower_set.bot_mem IsLowerSet.bot_mem
theorem IsLowerSet.not_bot_mem (hs : IsLowerSet s) : ⊥ ∉ s ↔ s = ∅ :=
hs.bot_mem.not.trans not_nonempty_iff_eq_empty
#align is_lower_set.not_bot_mem IsLowerSet.not_bot_mem
end OrderBot
section NoMaxOrder
variable [NoMaxOrder α]
theorem IsUpperSet.not_bddAbove (hs : IsUpperSet s) : s.Nonempty → ¬BddAbove s := by
rintro ⟨a, ha⟩ ⟨b, hb⟩
obtain ⟨c, hc⟩ := exists_gt b
exact hc.not_le (hb <| hs ((hb ha).trans hc.le) ha)
#align is_upper_set.not_bdd_above IsUpperSet.not_bddAbove
theorem not_bddAbove_Ici : ¬BddAbove (Ici a) :=
(isUpperSet_Ici _).not_bddAbove nonempty_Ici
#align not_bdd_above_Ici not_bddAbove_Ici
theorem not_bddAbove_Ioi : ¬BddAbove (Ioi a) :=
(isUpperSet_Ioi _).not_bddAbove nonempty_Ioi
#align not_bdd_above_Ioi not_bddAbove_Ioi
end NoMaxOrder
section NoMinOrder
variable [NoMinOrder α]
theorem IsLowerSet.not_bddBelow (hs : IsLowerSet s) : s.Nonempty → ¬BddBelow s := by
rintro ⟨a, ha⟩ ⟨b, hb⟩
obtain ⟨c, hc⟩ := exists_lt b
exact hc.not_le (hb <| hs (hc.le.trans <| hb ha) ha)
#align is_lower_set.not_bdd_below IsLowerSet.not_bddBelow
theorem not_bddBelow_Iic : ¬BddBelow (Iic a) :=
(isLowerSet_Iic _).not_bddBelow nonempty_Iic
#align not_bdd_below_Iic not_bddBelow_Iic
theorem not_bddBelow_Iio : ¬BddBelow (Iio a) :=
(isLowerSet_Iio _).not_bddBelow nonempty_Iio
#align not_bdd_below_Iio not_bddBelow_Iio
end NoMinOrder
end Preorder
section PartialOrder
variable [PartialOrder α] {s : Set α}
theorem isUpperSet_iff_forall_lt : IsUpperSet s ↔ ∀ ⦃a b : α⦄, a < b → a ∈ s → b ∈ s :=
forall_congr' fun a => by simp [le_iff_eq_or_lt, or_imp, forall_and]
#align is_upper_set_iff_forall_lt isUpperSet_iff_forall_lt
theorem isLowerSet_iff_forall_lt : IsLowerSet s ↔ ∀ ⦃a b : α⦄, b < a → a ∈ s → b ∈ s :=
forall_congr' fun a => by simp [le_iff_eq_or_lt, or_imp, forall_and]
#align is_lower_set_iff_forall_lt isLowerSet_iff_forall_lt
theorem isUpperSet_iff_Ioi_subset : IsUpperSet s ↔ ∀ ⦃a⦄, a ∈ s → Ioi a ⊆ s := by
simp [isUpperSet_iff_forall_lt, subset_def, @forall_swap (_ ∈ s)]
#align is_upper_set_iff_Ioi_subset isUpperSet_iff_Ioi_subset
theorem isLowerSet_iff_Iio_subset : IsLowerSet s ↔ ∀ ⦃a⦄, a ∈ s → Iio a ⊆ s := by
simp [isLowerSet_iff_forall_lt, subset_def, @forall_swap (_ ∈ s)]
#align is_lower_set_iff_Iio_subset isLowerSet_iff_Iio_subset
end PartialOrder
section LinearOrder
variable [LinearOrder α] {s t : Set α}
theorem IsUpperSet.total (hs : IsUpperSet s) (ht : IsUpperSet t) : s ⊆ t ∨ t ⊆ s := by
by_contra! h
simp_rw [Set.not_subset] at h
obtain ⟨⟨a, has, hat⟩, b, hbt, hbs⟩ := h
obtain hab | hba := le_total a b
· exact hbs (hs hab has)
· exact hat (ht hba hbt)
#align is_upper_set.total IsUpperSet.total
theorem IsLowerSet.total (hs : IsLowerSet s) (ht : IsLowerSet t) : s ⊆ t ∨ t ⊆ s :=
hs.toDual.total ht.toDual
#align is_lower_set.total IsLowerSet.total
end LinearOrder
/-! ### Bundled upper/lower sets -/
section LE
variable [LE α]
/-- The type of upper sets of an order. -/
structure UpperSet (α : Type*) [LE α] where
/-- The carrier of an `UpperSet`. -/
carrier : Set α
/-- The carrier of an `UpperSet` is an upper set. -/
upper' : IsUpperSet carrier
#align upper_set UpperSet
/-- The type of lower sets of an order. -/
structure LowerSet (α : Type*) [LE α] where
/-- The carrier of a `LowerSet`. -/
carrier : Set α
/-- The carrier of a `LowerSet` is a lower set. -/
lower' : IsLowerSet carrier
#align lower_set LowerSet
namespace UpperSet
instance : SetLike (UpperSet α) α where
coe := UpperSet.carrier
coe_injective' s t h := by cases s; cases t; congr
/-- See Note [custom simps projection]. -/
def Simps.coe (s : UpperSet α) : Set α := s
initialize_simps_projections UpperSet (carrier → coe)
@[ext]
theorem ext {s t : UpperSet α} : (s : Set α) = t → s = t :=
SetLike.ext'
#align upper_set.ext UpperSet.ext
@[simp]
theorem carrier_eq_coe (s : UpperSet α) : s.carrier = s :=
rfl
#align upper_set.carrier_eq_coe UpperSet.carrier_eq_coe
@[simp] protected lemma upper (s : UpperSet α) : IsUpperSet (s : Set α) := s.upper'
#align upper_set.upper UpperSet.upper
@[simp, norm_cast] lemma coe_mk (s : Set α) (hs) : mk s hs = s := rfl
@[simp] lemma mem_mk {s : Set α} (hs) {a : α} : a ∈ mk s hs ↔ a ∈ s := Iff.rfl
#align upper_set.mem_mk UpperSet.mem_mk
end UpperSet
namespace LowerSet
instance : SetLike (LowerSet α) α where
coe := LowerSet.carrier
coe_injective' s t h := by cases s; cases t; congr
/-- See Note [custom simps projection]. -/
def Simps.coe (s : LowerSet α) : Set α := s
initialize_simps_projections LowerSet (carrier → coe)
@[ext]
theorem ext {s t : LowerSet α} : (s : Set α) = t → s = t :=
SetLike.ext'
#align lower_set.ext LowerSet.ext
@[simp]
theorem carrier_eq_coe (s : LowerSet α) : s.carrier = s :=
rfl
#align lower_set.carrier_eq_coe LowerSet.carrier_eq_coe
@[simp] protected lemma lower (s : LowerSet α) : IsLowerSet (s : Set α) := s.lower'
#align lower_set.lower LowerSet.lower
@[simp, norm_cast] lemma coe_mk (s : Set α) (hs) : mk s hs = s := rfl
@[simp] lemma mem_mk {s : Set α} (hs) {a : α} : a ∈ mk s hs ↔ a ∈ s := Iff.rfl
#align lower_set.mem_mk LowerSet.mem_mk
end LowerSet
/-! #### Order -/
namespace UpperSet
variable {S : Set (UpperSet α)} {s t : UpperSet α} {a : α}
instance : Sup (UpperSet α) :=
⟨fun s t => ⟨s ∩ t, s.upper.inter t.upper⟩⟩
instance : Inf (UpperSet α) :=
⟨fun s t => ⟨s ∪ t, s.upper.union t.upper⟩⟩
instance : Top (UpperSet α) :=
⟨⟨∅, isUpperSet_empty⟩⟩
instance : Bot (UpperSet α) :=
⟨⟨univ, isUpperSet_univ⟩⟩
instance : SupSet (UpperSet α) :=
⟨fun S => ⟨⋂ s ∈ S, ↑s, isUpperSet_iInter₂ fun s _ => s.upper⟩⟩
instance : InfSet (UpperSet α) :=
⟨fun S => ⟨⋃ s ∈ S, ↑s, isUpperSet_iUnion₂ fun s _ => s.upper⟩⟩
instance completelyDistribLattice : CompletelyDistribLattice (UpperSet α) :=
(toDual.injective.comp SetLike.coe_injective).completelyDistribLattice _ (fun _ _ => rfl)
(fun _ _ => rfl) (fun _ => rfl) (fun _ => rfl) rfl rfl
instance : Inhabited (UpperSet α) :=
⟨⊥⟩
@[simp 1100, norm_cast]
theorem coe_subset_coe : (s : Set α) ⊆ t ↔ t ≤ s :=
Iff.rfl
#align upper_set.coe_subset_coe UpperSet.coe_subset_coe
@[simp 1100, norm_cast] lemma coe_ssubset_coe : (s : Set α) ⊂ t ↔ t < s := Iff.rfl
@[simp, norm_cast]
theorem coe_top : ((⊤ : UpperSet α) : Set α) = ∅ :=
rfl
#align upper_set.coe_top UpperSet.coe_top
@[simp, norm_cast]
theorem coe_bot : ((⊥ : UpperSet α) : Set α) = univ :=
rfl
#align upper_set.coe_bot UpperSet.coe_bot
@[simp, norm_cast]
theorem coe_eq_univ : (s : Set α) = univ ↔ s = ⊥ := by simp [SetLike.ext'_iff]
#align upper_set.coe_eq_univ UpperSet.coe_eq_univ
@[simp, norm_cast]
theorem coe_eq_empty : (s : Set α) = ∅ ↔ s = ⊤ := by simp [SetLike.ext'_iff]
#align upper_set.coe_eq_empty UpperSet.coe_eq_empty
@[simp, norm_cast] lemma coe_nonempty : (s : Set α).Nonempty ↔ s ≠ ⊤ :=
nonempty_iff_ne_empty.trans coe_eq_empty.not
@[simp, norm_cast]
theorem coe_sup (s t : UpperSet α) : (↑(s ⊔ t) : Set α) = (s : Set α) ∩ t :=
rfl
#align upper_set.coe_sup UpperSet.coe_sup
@[simp, norm_cast]
theorem coe_inf (s t : UpperSet α) : (↑(s ⊓ t) : Set α) = (s : Set α) ∪ t :=
rfl
#align upper_set.coe_inf UpperSet.coe_inf
@[simp, norm_cast]
theorem coe_sSup (S : Set (UpperSet α)) : (↑(sSup S) : Set α) = ⋂ s ∈ S, ↑s :=
rfl
#align upper_set.coe_Sup UpperSet.coe_sSup
@[simp, norm_cast]
theorem coe_sInf (S : Set (UpperSet α)) : (↑(sInf S) : Set α) = ⋃ s ∈ S, ↑s :=
rfl
#align upper_set.coe_Inf UpperSet.coe_sInf
@[simp, norm_cast]
theorem coe_iSup (f : ι → UpperSet α) : (↑(⨆ i, f i) : Set α) = ⋂ i, f i := by simp [iSup]
#align upper_set.coe_supr UpperSet.coe_iSup
@[simp, norm_cast]
theorem coe_iInf (f : ι → UpperSet α) : (↑(⨅ i, f i) : Set α) = ⋃ i, f i := by simp [iInf]
#align upper_set.coe_infi UpperSet.coe_iInf
@[norm_cast] -- Porting note: no longer a `simp`
theorem coe_iSup₂ (f : ∀ i, κ i → UpperSet α) :
(↑(⨆ (i) (j), f i j) : Set α) = ⋂ (i) (j), f i j := by simp_rw [coe_iSup]
#align upper_set.coe_supr₂ UpperSet.coe_iSup₂
@[norm_cast] -- Porting note: no longer a `simp`
theorem coe_iInf₂ (f : ∀ i, κ i → UpperSet α) :
(↑(⨅ (i) (j), f i j) : Set α) = ⋃ (i) (j), f i j := by simp_rw [coe_iInf]
#align upper_set.coe_infi₂ UpperSet.coe_iInf₂
@[simp]
theorem not_mem_top : a ∉ (⊤ : UpperSet α) :=
id
#align upper_set.not_mem_top UpperSet.not_mem_top
@[simp]
theorem mem_bot : a ∈ (⊥ : UpperSet α) :=
trivial
#align upper_set.mem_bot UpperSet.mem_bot
@[simp]
theorem mem_sup_iff : a ∈ s ⊔ t ↔ a ∈ s ∧ a ∈ t :=
Iff.rfl
#align upper_set.mem_sup_iff UpperSet.mem_sup_iff
@[simp]
theorem mem_inf_iff : a ∈ s ⊓ t ↔ a ∈ s ∨ a ∈ t :=
Iff.rfl
#align upper_set.mem_inf_iff UpperSet.mem_inf_iff
@[simp]
theorem mem_sSup_iff : a ∈ sSup S ↔ ∀ s ∈ S, a ∈ s :=
mem_iInter₂
#align upper_set.mem_Sup_iff UpperSet.mem_sSup_iff
@[simp]
theorem mem_sInf_iff : a ∈ sInf S ↔ ∃ s ∈ S, a ∈ s :=
mem_iUnion₂.trans <| by simp only [exists_prop, SetLike.mem_coe]
#align upper_set.mem_Inf_iff UpperSet.mem_sInf_iff
@[simp]
theorem mem_iSup_iff {f : ι → UpperSet α} : (a ∈ ⨆ i, f i) ↔ ∀ i, a ∈ f i := by
rw [← SetLike.mem_coe, coe_iSup]
exact mem_iInter
#align upper_set.mem_supr_iff UpperSet.mem_iSup_iff
@[simp]
theorem mem_iInf_iff {f : ι → UpperSet α} : (a ∈ ⨅ i, f i) ↔ ∃ i, a ∈ f i := by
rw [← SetLike.mem_coe, coe_iInf]
exact mem_iUnion
#align upper_set.mem_infi_iff UpperSet.mem_iInf_iff
-- Porting note: no longer a @[simp]
theorem mem_iSup₂_iff {f : ∀ i, κ i → UpperSet α} : (a ∈ ⨆ (i) (j), f i j) ↔ ∀ i j, a ∈ f i j := by
simp_rw [mem_iSup_iff]
#align upper_set.mem_supr₂_iff UpperSet.mem_iSup₂_iff
-- Porting note: no longer a @[simp]
theorem mem_iInf₂_iff {f : ∀ i, κ i → UpperSet α} : (a ∈ ⨅ (i) (j), f i j) ↔ ∃ i j, a ∈ f i j := by
simp_rw [mem_iInf_iff]
#align upper_set.mem_infi₂_iff UpperSet.mem_iInf₂_iff
@[simp, norm_cast]
theorem codisjoint_coe : Codisjoint (s : Set α) t ↔ Disjoint s t := by
simp [disjoint_iff, codisjoint_iff, SetLike.ext'_iff]
#align upper_set.codisjoint_coe UpperSet.codisjoint_coe
end UpperSet
namespace LowerSet
variable {S : Set (LowerSet α)} {s t : LowerSet α} {a : α}
instance : Sup (LowerSet α) :=
⟨fun s t => ⟨s ∪ t, fun _ _ h => Or.imp (s.lower h) (t.lower h)⟩⟩
instance : Inf (LowerSet α) :=
⟨fun s t => ⟨s ∩ t, fun _ _ h => And.imp (s.lower h) (t.lower h)⟩⟩
instance : Top (LowerSet α) :=
⟨⟨univ, fun _ _ _ => id⟩⟩
instance : Bot (LowerSet α) :=
⟨⟨∅, fun _ _ _ => id⟩⟩
instance : SupSet (LowerSet α) :=
⟨fun S => ⟨⋃ s ∈ S, ↑s, isLowerSet_iUnion₂ fun s _ => s.lower⟩⟩
instance : InfSet (LowerSet α) :=
⟨fun S => ⟨⋂ s ∈ S, ↑s, isLowerSet_iInter₂ fun s _ => s.lower⟩⟩
instance completelyDistribLattice : CompletelyDistribLattice (LowerSet α) :=
SetLike.coe_injective.completelyDistribLattice _ (fun _ _ => rfl) (fun _ _ => rfl) (fun _ => rfl)
(fun _ => rfl) rfl rfl
instance : Inhabited (LowerSet α) :=
⟨⊥⟩
@[norm_cast] lemma coe_subset_coe : (s : Set α) ⊆ t ↔ s ≤ t := Iff.rfl
#align lower_set.coe_subset_coe LowerSet.coe_subset_coe
@[norm_cast] lemma coe_ssubset_coe : (s : Set α) ⊂ t ↔ s < t := Iff.rfl
@[simp, norm_cast]
theorem coe_top : ((⊤ : LowerSet α) : Set α) = univ :=
rfl
#align lower_set.coe_top LowerSet.coe_top
@[simp, norm_cast]
theorem coe_bot : ((⊥ : LowerSet α) : Set α) = ∅ :=
rfl
#align lower_set.coe_bot LowerSet.coe_bot
@[simp, norm_cast]
theorem coe_eq_univ : (s : Set α) = univ ↔ s = ⊤ := by simp [SetLike.ext'_iff]
#align lower_set.coe_eq_univ LowerSet.coe_eq_univ
@[simp, norm_cast]
theorem coe_eq_empty : (s : Set α) = ∅ ↔ s = ⊥ := by simp [SetLike.ext'_iff]
#align lower_set.coe_eq_empty LowerSet.coe_eq_empty
@[simp, norm_cast] lemma coe_nonempty : (s : Set α).Nonempty ↔ s ≠ ⊥ :=
nonempty_iff_ne_empty.trans coe_eq_empty.not
@[simp, norm_cast]
theorem coe_sup (s t : LowerSet α) : (↑(s ⊔ t) : Set α) = (s : Set α) ∪ t :=
rfl
#align lower_set.coe_sup LowerSet.coe_sup
@[simp, norm_cast]
theorem coe_inf (s t : LowerSet α) : (↑(s ⊓ t) : Set α) = (s : Set α) ∩ t :=
rfl
#align lower_set.coe_inf LowerSet.coe_inf
@[simp, norm_cast]
theorem coe_sSup (S : Set (LowerSet α)) : (↑(sSup S) : Set α) = ⋃ s ∈ S, ↑s :=
rfl
#align lower_set.coe_Sup LowerSet.coe_sSup
@[simp, norm_cast]
theorem coe_sInf (S : Set (LowerSet α)) : (↑(sInf S) : Set α) = ⋂ s ∈ S, ↑s :=
rfl
#align lower_set.coe_Inf LowerSet.coe_sInf
@[simp, norm_cast]
theorem coe_iSup (f : ι → LowerSet α) : (↑(⨆ i, f i) : Set α) = ⋃ i, f i := by
simp_rw [iSup, coe_sSup, mem_range, iUnion_exists, iUnion_iUnion_eq']
#align lower_set.coe_supr LowerSet.coe_iSup
@[simp, norm_cast]
theorem coe_iInf (f : ι → LowerSet α) : (↑(⨅ i, f i) : Set α) = ⋂ i, f i := by
simp_rw [iInf, coe_sInf, mem_range, iInter_exists, iInter_iInter_eq']
#align lower_set.coe_infi LowerSet.coe_iInf
@[norm_cast] -- Porting note: no longer a `simp`
theorem coe_iSup₂ (f : ∀ i, κ i → LowerSet α) :
(↑(⨆ (i) (j), f i j) : Set α) = ⋃ (i) (j), f i j := by simp_rw [coe_iSup]
#align lower_set.coe_supr₂ LowerSet.coe_iSup₂
@[norm_cast] -- Porting note: no longer a `simp`
theorem coe_iInf₂ (f : ∀ i, κ i → LowerSet α) :
(↑(⨅ (i) (j), f i j) : Set α) = ⋂ (i) (j), f i j := by simp_rw [coe_iInf]
#align lower_set.coe_infi₂ LowerSet.coe_iInf₂
@[simp]
theorem mem_top : a ∈ (⊤ : LowerSet α) :=
trivial
#align lower_set.mem_top LowerSet.mem_top
@[simp]
theorem not_mem_bot : a ∉ (⊥ : LowerSet α) :=
id
#align lower_set.not_mem_bot LowerSet.not_mem_bot
@[simp]
theorem mem_sup_iff : a ∈ s ⊔ t ↔ a ∈ s ∨ a ∈ t :=
Iff.rfl
#align lower_set.mem_sup_iff LowerSet.mem_sup_iff
@[simp]
theorem mem_inf_iff : a ∈ s ⊓ t ↔ a ∈ s ∧ a ∈ t :=
Iff.rfl
#align lower_set.mem_inf_iff LowerSet.mem_inf_iff
@[simp]
theorem mem_sSup_iff : a ∈ sSup S ↔ ∃ s ∈ S, a ∈ s :=
mem_iUnion₂.trans <| by simp only [exists_prop, SetLike.mem_coe]
#align lower_set.mem_Sup_iff LowerSet.mem_sSup_iff
@[simp]
theorem mem_sInf_iff : a ∈ sInf S ↔ ∀ s ∈ S, a ∈ s :=
mem_iInter₂
#align lower_set.mem_Inf_iff LowerSet.mem_sInf_iff
@[simp]
theorem mem_iSup_iff {f : ι → LowerSet α} : (a ∈ ⨆ i, f i) ↔ ∃ i, a ∈ f i := by
rw [← SetLike.mem_coe, coe_iSup]
exact mem_iUnion
#align lower_set.mem_supr_iff LowerSet.mem_iSup_iff
@[simp]
theorem mem_iInf_iff {f : ι → LowerSet α} : (a ∈ ⨅ i, f i) ↔ ∀ i, a ∈ f i := by
rw [← SetLike.mem_coe, coe_iInf]
exact mem_iInter
#align lower_set.mem_infi_iff LowerSet.mem_iInf_iff
-- Porting note: no longer a @[simp]
theorem mem_iSup₂_iff {f : ∀ i, κ i → LowerSet α} : (a ∈ ⨆ (i) (j), f i j) ↔ ∃ i j, a ∈ f i j := by
simp_rw [mem_iSup_iff]
#align lower_set.mem_supr₂_iff LowerSet.mem_iSup₂_iff
-- Porting note: no longer a @[simp]
theorem mem_iInf₂_iff {f : ∀ i, κ i → LowerSet α} : (a ∈ ⨅ (i) (j), f i j) ↔ ∀ i j, a ∈ f i j := by
simp_rw [mem_iInf_iff]
#align lower_set.mem_infi₂_iff LowerSet.mem_iInf₂_iff
@[simp, norm_cast]
theorem disjoint_coe : Disjoint (s : Set α) t ↔ Disjoint s t := by
simp [disjoint_iff, SetLike.ext'_iff]
#align lower_set.disjoint_coe LowerSet.disjoint_coe
end LowerSet
/-! #### Complement -/
/-- The complement of a lower set as an upper set. -/
def UpperSet.compl (s : UpperSet α) : LowerSet α :=
⟨sᶜ, s.upper.compl⟩
#align upper_set.compl UpperSet.compl
/-- The complement of a lower set as an upper set. -/
def LowerSet.compl (s : LowerSet α) : UpperSet α :=
⟨sᶜ, s.lower.compl⟩
#align lower_set.compl LowerSet.compl
namespace UpperSet
variable {s t : UpperSet α} {a : α}
@[simp]
theorem coe_compl (s : UpperSet α) : (s.compl : Set α) = (↑s)ᶜ :=
rfl
#align upper_set.coe_compl UpperSet.coe_compl
@[simp]
theorem mem_compl_iff : a ∈ s.compl ↔ a ∉ s :=
Iff.rfl
#align upper_set.mem_compl_iff UpperSet.mem_compl_iff
@[simp]
nonrec theorem compl_compl (s : UpperSet α) : s.compl.compl = s :=
UpperSet.ext <| compl_compl _
#align upper_set.compl_compl UpperSet.compl_compl
@[simp]
theorem compl_le_compl : s.compl ≤ t.compl ↔ s ≤ t :=
compl_subset_compl
#align upper_set.compl_le_compl UpperSet.compl_le_compl
@[simp]
protected theorem compl_sup (s t : UpperSet α) : (s ⊔ t).compl = s.compl ⊔ t.compl :=
LowerSet.ext compl_inf
#align upper_set.compl_sup UpperSet.compl_sup
@[simp]
protected theorem compl_inf (s t : UpperSet α) : (s ⊓ t).compl = s.compl ⊓ t.compl :=
LowerSet.ext compl_sup
#align upper_set.compl_inf UpperSet.compl_inf
@[simp]
protected theorem compl_top : (⊤ : UpperSet α).compl = ⊤ :=
LowerSet.ext compl_empty
#align upper_set.compl_top UpperSet.compl_top
@[simp]
protected theorem compl_bot : (⊥ : UpperSet α).compl = ⊥ :=
LowerSet.ext compl_univ
#align upper_set.compl_bot UpperSet.compl_bot
@[simp]
protected theorem compl_sSup (S : Set (UpperSet α)) : (sSup S).compl = ⨆ s ∈ S, UpperSet.compl s :=
LowerSet.ext <| by simp only [coe_compl, coe_sSup, compl_iInter₂, LowerSet.coe_iSup₂]
#align upper_set.compl_Sup UpperSet.compl_sSup
@[simp]
protected theorem compl_sInf (S : Set (UpperSet α)) : (sInf S).compl = ⨅ s ∈ S, UpperSet.compl s :=
LowerSet.ext <| by simp only [coe_compl, coe_sInf, compl_iUnion₂, LowerSet.coe_iInf₂]
#align upper_set.compl_Inf UpperSet.compl_sInf
@[simp]
protected theorem compl_iSup (f : ι → UpperSet α) : (⨆ i, f i).compl = ⨆ i, (f i).compl :=
LowerSet.ext <| by simp only [coe_compl, coe_iSup, compl_iInter, LowerSet.coe_iSup]
#align upper_set.compl_supr UpperSet.compl_iSup
@[simp]
protected theorem compl_iInf (f : ι → UpperSet α) : (⨅ i, f i).compl = ⨅ i, (f i).compl :=
LowerSet.ext <| by simp only [coe_compl, coe_iInf, compl_iUnion, LowerSet.coe_iInf]
#align upper_set.compl_infi UpperSet.compl_iInf
-- Porting note: no longer a @[simp]
theorem compl_iSup₂ (f : ∀ i, κ i → UpperSet α) :
(⨆ (i) (j), f i j).compl = ⨆ (i) (j), (f i j).compl := by simp_rw [UpperSet.compl_iSup]
#align upper_set.compl_supr₂ UpperSet.compl_iSup₂
-- Porting note: no longer a @[simp]
theorem compl_iInf₂ (f : ∀ i, κ i → UpperSet α) :
(⨅ (i) (j), f i j).compl = ⨅ (i) (j), (f i j).compl := by simp_rw [UpperSet.compl_iInf]
#align upper_set.compl_infi₂ UpperSet.compl_iInf₂
end UpperSet
namespace LowerSet
variable {s t : LowerSet α} {a : α}
@[simp]
theorem coe_compl (s : LowerSet α) : (s.compl : Set α) = (↑s)ᶜ :=
rfl
#align lower_set.coe_compl LowerSet.coe_compl
@[simp]
theorem mem_compl_iff : a ∈ s.compl ↔ a ∉ s :=
Iff.rfl
#align lower_set.mem_compl_iff LowerSet.mem_compl_iff
@[simp]
nonrec theorem compl_compl (s : LowerSet α) : s.compl.compl = s :=
LowerSet.ext <| compl_compl _
#align lower_set.compl_compl LowerSet.compl_compl
@[simp]
theorem compl_le_compl : s.compl ≤ t.compl ↔ s ≤ t :=
compl_subset_compl
#align lower_set.compl_le_compl LowerSet.compl_le_compl
protected theorem compl_sup (s t : LowerSet α) : (s ⊔ t).compl = s.compl ⊔ t.compl :=
UpperSet.ext compl_sup
#align lower_set.compl_sup LowerSet.compl_sup
protected theorem compl_inf (s t : LowerSet α) : (s ⊓ t).compl = s.compl ⊓ t.compl :=
UpperSet.ext compl_inf
#align lower_set.compl_inf LowerSet.compl_inf
protected theorem compl_top : (⊤ : LowerSet α).compl = ⊤ :=
UpperSet.ext compl_univ
#align lower_set.compl_top LowerSet.compl_top
protected theorem compl_bot : (⊥ : LowerSet α).compl = ⊥ :=
UpperSet.ext compl_empty
#align lower_set.compl_bot LowerSet.compl_bot
protected theorem compl_sSup (S : Set (LowerSet α)) : (sSup S).compl = ⨆ s ∈ S, LowerSet.compl s :=
UpperSet.ext <| by simp only [coe_compl, coe_sSup, compl_iUnion₂, UpperSet.coe_iSup₂]
#align lower_set.compl_Sup LowerSet.compl_sSup
protected theorem compl_sInf (S : Set (LowerSet α)) : (sInf S).compl = ⨅ s ∈ S, LowerSet.compl s :=
UpperSet.ext <| by simp only [coe_compl, coe_sInf, compl_iInter₂, UpperSet.coe_iInf₂]
#align lower_set.compl_Inf LowerSet.compl_sInf
protected theorem compl_iSup (f : ι → LowerSet α) : (⨆ i, f i).compl = ⨆ i, (f i).compl :=
UpperSet.ext <| by simp only [coe_compl, coe_iSup, compl_iUnion, UpperSet.coe_iSup]
#align lower_set.compl_supr LowerSet.compl_iSup
protected theorem compl_iInf (f : ι → LowerSet α) : (⨅ i, f i).compl = ⨅ i, (f i).compl :=
UpperSet.ext <| by simp only [coe_compl, coe_iInf, compl_iInter, UpperSet.coe_iInf]
#align lower_set.compl_infi LowerSet.compl_iInf
@[simp]
theorem compl_iSup₂ (f : ∀ i, κ i → LowerSet α) :
(⨆ (i) (j), f i j).compl = ⨆ (i) (j), (f i j).compl := by simp_rw [LowerSet.compl_iSup]
#align lower_set.compl_supr₂ LowerSet.compl_iSup₂
@[simp]
theorem compl_iInf₂ (f : ∀ i, κ i → LowerSet α) :
(⨅ (i) (j), f i j).compl = ⨅ (i) (j), (f i j).compl := by simp_rw [LowerSet.compl_iInf]
#align lower_set.compl_infi₂ LowerSet.compl_iInf₂
end LowerSet
/-- Upper sets are order-isomorphic to lower sets under complementation. -/
@[simps]
def upperSetIsoLowerSet : UpperSet α ≃o LowerSet α where
toFun := UpperSet.compl
invFun := LowerSet.compl
left_inv := UpperSet.compl_compl
right_inv := LowerSet.compl_compl
map_rel_iff' := UpperSet.compl_le_compl
#align upper_set_iso_lower_set upperSetIsoLowerSet
end LE
section LinearOrder
variable [LinearOrder α]
instance UpperSet.isTotal_le : IsTotal (UpperSet α) (· ≤ ·) := ⟨fun s t => t.upper.total s.upper⟩
#align upper_set.is_total_le UpperSet.isTotal_le
instance LowerSet.isTotal_le : IsTotal (LowerSet α) (· ≤ ·) := ⟨fun s t => s.lower.total t.lower⟩
#align lower_set.is_total_le LowerSet.isTotal_le
noncomputable instance : CompleteLinearOrder (UpperSet α) :=
{ UpperSet.completelyDistribLattice with
le_total := IsTotal.total
decidableLE := Classical.decRel _
decidableEq := Classical.decRel _
decidableLT := Classical.decRel _ }
noncomputable instance : CompleteLinearOrder (LowerSet α) :=
{ LowerSet.completelyDistribLattice with
le_total := IsTotal.total
decidableLE := Classical.decRel _
decidableEq := Classical.decRel _
decidableLT := Classical.decRel _ }
end LinearOrder
/-! #### Map -/
section
variable [Preorder α] [Preorder β] [Preorder γ]
namespace UpperSet
variable {f : α ≃o β} {s t : UpperSet α} {a : α} {b : β}
/-- An order isomorphism of preorders induces an order isomorphism of their upper sets. -/
def map (f : α ≃o β) : UpperSet α ≃o UpperSet β where
toFun s := ⟨f '' s, s.upper.image f⟩
invFun t := ⟨f ⁻¹' t, t.upper.preimage f.monotone⟩
left_inv _ := ext <| f.preimage_image _
right_inv _ := ext <| f.image_preimage _
map_rel_iff' := image_subset_image_iff f.injective
#align upper_set.map UpperSet.map
@[simp]
theorem symm_map (f : α ≃o β) : (map f).symm = map f.symm :=
DFunLike.ext _ _ fun s => ext <| by convert Set.preimage_equiv_eq_image_symm s f.toEquiv
#align upper_set.symm_map UpperSet.symm_map
@[simp]
theorem mem_map : b ∈ map f s ↔ f.symm b ∈ s := by
rw [← f.symm_symm, ← symm_map, f.symm_symm]
rfl
#align upper_set.mem_map UpperSet.mem_map
@[simp]
theorem map_refl : map (OrderIso.refl α) = OrderIso.refl _ := by
ext
simp
#align upper_set.map_refl UpperSet.map_refl
@[simp]
theorem map_map (g : β ≃o γ) (f : α ≃o β) : map g (map f s) = map (f.trans g) s := by
ext
simp
#align upper_set.map_map UpperSet.map_map
variable (f s t)
@[simp, norm_cast]
theorem coe_map : (map f s : Set β) = f '' s :=
rfl
#align upper_set.coe_map UpperSet.coe_map
end UpperSet
namespace LowerSet
variable {f : α ≃o β} {s t : LowerSet α} {a : α} {b : β}
/-- An order isomorphism of preorders induces an order isomorphism of their lower sets. -/
def map (f : α ≃o β) : LowerSet α ≃o LowerSet β where
toFun s := ⟨f '' s, s.lower.image f⟩
invFun t := ⟨f ⁻¹' t, t.lower.preimage f.monotone⟩
left_inv _ := SetLike.coe_injective <| f.preimage_image _
right_inv _ := SetLike.coe_injective <| f.image_preimage _
map_rel_iff' := image_subset_image_iff f.injective
#align lower_set.map LowerSet.map
@[simp]
theorem symm_map (f : α ≃o β) : (map f).symm = map f.symm :=
DFunLike.ext _ _ fun s => ext <| by convert Set.preimage_equiv_eq_image_symm s f.toEquiv
#align lower_set.symm_map LowerSet.symm_map
@[simp]
theorem mem_map {f : α ≃o β} {b : β} : b ∈ map f s ↔ f.symm b ∈ s := by
rw [← f.symm_symm, ← symm_map, f.symm_symm]
rfl
#align lower_set.mem_map LowerSet.mem_map
@[simp]
theorem map_refl : map (OrderIso.refl α) = OrderIso.refl _ := by
ext
simp
#align lower_set.map_refl LowerSet.map_refl
@[simp]
theorem map_map (g : β ≃o γ) (f : α ≃o β) : map g (map f s) = map (f.trans g) s := by
ext
simp
#align lower_set.map_map LowerSet.map_map
variable (f s t)
@[simp, norm_cast]
theorem coe_map : (map f s : Set β) = f '' s :=
rfl
#align lower_set.coe_map LowerSet.coe_map
end LowerSet
namespace UpperSet
@[simp]
theorem compl_map (f : α ≃o β) (s : UpperSet α) : (map f s).compl = LowerSet.map f s.compl :=
SetLike.coe_injective (Set.image_compl_eq f.bijective).symm
#align upper_set.compl_map UpperSet.compl_map
end UpperSet
namespace LowerSet
@[simp]
theorem compl_map (f : α ≃o β) (s : LowerSet α) : (map f s).compl = UpperSet.map f s.compl :=
SetLike.coe_injective (Set.image_compl_eq f.bijective).symm
#align lower_set.compl_map LowerSet.compl_map
end LowerSet
end
/-! #### Principal sets -/
namespace UpperSet
section Preorder
variable [Preorder α] [Preorder β] {s : UpperSet α} {a b : α}
/-- The smallest upper set containing a given element. -/
nonrec def Ici (a : α) : UpperSet α :=
⟨Ici a, isUpperSet_Ici a⟩
#align upper_set.Ici UpperSet.Ici
/-- The smallest upper set containing a given element. -/
nonrec def Ioi (a : α) : UpperSet α :=
⟨Ioi a, isUpperSet_Ioi a⟩
#align upper_set.Ioi UpperSet.Ioi
@[simp]
theorem coe_Ici (a : α) : ↑(Ici a) = Set.Ici a :=
rfl
#align upper_set.coe_Ici UpperSet.coe_Ici
@[simp]
theorem coe_Ioi (a : α) : ↑(Ioi a) = Set.Ioi a :=
rfl
#align upper_set.coe_Ioi UpperSet.coe_Ioi
@[simp]
theorem mem_Ici_iff : b ∈ Ici a ↔ a ≤ b :=
Iff.rfl
#align upper_set.mem_Ici_iff UpperSet.mem_Ici_iff
@[simp]
theorem mem_Ioi_iff : b ∈ Ioi a ↔ a < b :=
Iff.rfl
#align upper_set.mem_Ioi_iff UpperSet.mem_Ioi_iff
@[simp]
theorem map_Ici (f : α ≃o β) (a : α) : map f (Ici a) = Ici (f a) := by
ext
simp
#align upper_set.map_Ici UpperSet.map_Ici
@[simp]
theorem map_Ioi (f : α ≃o β) (a : α) : map f (Ioi a) = Ioi (f a) := by
ext
simp
#align upper_set.map_Ioi UpperSet.map_Ioi
theorem Ici_le_Ioi (a : α) : Ici a ≤ Ioi a :=
Ioi_subset_Ici_self
#align upper_set.Ici_le_Ioi UpperSet.Ici_le_Ioi
@[simp]
nonrec theorem Ici_bot [OrderBot α] : Ici (⊥ : α) = ⊥ :=
SetLike.coe_injective Ici_bot
#align upper_set.Ici_bot UpperSet.Ici_bot
@[simp]
nonrec theorem Ioi_top [OrderTop α] : Ioi (⊤ : α) = ⊤ :=
SetLike.coe_injective Ioi_top
#align upper_set.Ioi_top UpperSet.Ioi_top
@[simp] lemma Ici_ne_top : Ici a ≠ ⊤ := SetLike.coe_ne_coe.1 nonempty_Ici.ne_empty
@[simp] lemma Ici_lt_top : Ici a < ⊤ := lt_top_iff_ne_top.2 Ici_ne_top
@[simp] lemma le_Ici : s ≤ Ici a ↔ a ∈ s := ⟨fun h ↦ h le_rfl, fun ha ↦ s.upper.Ici_subset ha⟩
end Preorder
section PartialOrder
variable [PartialOrder α] {a b : α}
nonrec lemma Ici_injective : Injective (Ici : α → UpperSet α) := fun _a _b hab ↦
Ici_injective <| congr_arg ((↑) : _ → Set α) hab
@[simp] lemma Ici_inj : Ici a = Ici b ↔ a = b := Ici_injective.eq_iff
lemma Ici_ne_Ici : Ici a ≠ Ici b ↔ a ≠ b := Ici_inj.not
end PartialOrder
@[simp]
theorem Ici_sup [SemilatticeSup α] (a b : α) : Ici (a ⊔ b) = Ici a ⊔ Ici b :=
ext Ici_inter_Ici.symm
#align upper_set.Ici_sup UpperSet.Ici_sup
section CompleteLattice
variable [CompleteLattice α]
@[simp]
theorem Ici_sSup (S : Set α) : Ici (sSup S) = ⨆ a ∈ S, Ici a :=
SetLike.ext fun c => by simp only [mem_Ici_iff, mem_iSup_iff, sSup_le_iff]
#align upper_set.Ici_Sup UpperSet.Ici_sSup
@[simp]
theorem Ici_iSup (f : ι → α) : Ici (⨆ i, f i) = ⨆ i, Ici (f i) :=
SetLike.ext fun c => by simp only [mem_Ici_iff, mem_iSup_iff, iSup_le_iff]
#align upper_set.Ici_supr UpperSet.Ici_iSup
-- Porting note: no longer a @[simp]
theorem Ici_iSup₂ (f : ∀ i, κ i → α) : Ici (⨆ (i) (j), f i j) = ⨆ (i) (j), Ici (f i j) := by
simp_rw [Ici_iSup]
#align upper_set.Ici_supr₂ UpperSet.Ici_iSup₂
end CompleteLattice
end UpperSet
namespace LowerSet
section Preorder
variable [Preorder α] [Preorder β] {s : LowerSet α} {a b : α}
/-- Principal lower set. `Set.Iic` as a lower set. The smallest lower set containing a given
element. -/
nonrec def Iic (a : α) : LowerSet α :=
⟨Iic a, isLowerSet_Iic a⟩
#align lower_set.Iic LowerSet.Iic
/-- Strict principal lower set. `Set.Iio` as a lower set. -/
nonrec def Iio (a : α) : LowerSet α :=
⟨Iio a, isLowerSet_Iio a⟩
#align lower_set.Iio LowerSet.Iio
@[simp]
theorem coe_Iic (a : α) : ↑(Iic a) = Set.Iic a :=
rfl
#align lower_set.coe_Iic LowerSet.coe_Iic
@[simp]
theorem coe_Iio (a : α) : ↑(Iio a) = Set.Iio a :=
rfl
#align lower_set.coe_Iio LowerSet.coe_Iio
@[simp]
theorem mem_Iic_iff : b ∈ Iic a ↔ b ≤ a :=
Iff.rfl
#align lower_set.mem_Iic_iff LowerSet.mem_Iic_iff
@[simp]
theorem mem_Iio_iff : b ∈ Iio a ↔ b < a :=
Iff.rfl
#align lower_set.mem_Iio_iff LowerSet.mem_Iio_iff
@[simp]
theorem map_Iic (f : α ≃o β) (a : α) : map f (Iic a) = Iic (f a) := by
ext
simp
#align lower_set.map_Iic LowerSet.map_Iic
@[simp]
theorem map_Iio (f : α ≃o β) (a : α) : map f (Iio a) = Iio (f a) := by
ext
simp
#align lower_set.map_Iio LowerSet.map_Iio
theorem Ioi_le_Ici (a : α) : Ioi a ≤ Ici a :=
Ioi_subset_Ici_self
#align lower_set.Ioi_le_Ici LowerSet.Ioi_le_Ici
@[simp]
nonrec theorem Iic_top [OrderTop α] : Iic (⊤ : α) = ⊤ :=
SetLike.coe_injective Iic_top
#align lower_set.Iic_top LowerSet.Iic_top
@[simp]
nonrec theorem Iio_bot [OrderBot α] : Iio (⊥ : α) = ⊥ :=
SetLike.coe_injective Iio_bot
#align lower_set.Iio_bot LowerSet.Iio_bot
@[simp] lemma Iic_ne_bot : Iic a ≠ ⊥ := SetLike.coe_ne_coe.1 nonempty_Iic.ne_empty
@[simp] lemma bot_lt_Iic : ⊥ < Iic a := bot_lt_iff_ne_bot.2 Iic_ne_bot
@[simp] lemma Iic_le : Iic a ≤ s ↔ a ∈ s := ⟨fun h ↦ h le_rfl, fun ha ↦ s.lower.Iic_subset ha⟩
end Preorder
section PartialOrder
variable [PartialOrder α] {a b : α}
nonrec lemma Iic_injective : Injective (Iic : α → LowerSet α) := fun _a _b hab ↦
Iic_injective <| congr_arg ((↑) : _ → Set α) hab
@[simp] lemma Iic_inj : Iic a = Iic b ↔ a = b := Iic_injective.eq_iff
lemma Iic_ne_Iic : Iic a ≠ Iic b ↔ a ≠ b := Iic_inj.not
end PartialOrder
@[simp]
theorem Iic_inf [SemilatticeInf α] (a b : α) : Iic (a ⊓ b) = Iic a ⊓ Iic b :=
SetLike.coe_injective Iic_inter_Iic.symm
#align lower_set.Iic_inf LowerSet.Iic_inf
section CompleteLattice
variable [CompleteLattice α]
@[simp]
theorem Iic_sInf (S : Set α) : Iic (sInf S) = ⨅ a ∈ S, Iic a :=
SetLike.ext fun c => by simp only [mem_Iic_iff, mem_iInf₂_iff, le_sInf_iff]
#align lower_set.Iic_Inf LowerSet.Iic_sInf
@[simp]
theorem Iic_iInf (f : ι → α) : Iic (⨅ i, f i) = ⨅ i, Iic (f i) :=
SetLike.ext fun c => by simp only [mem_Iic_iff, mem_iInf_iff, le_iInf_iff]
#align lower_set.Iic_infi LowerSet.Iic_iInf
-- Porting note: no longer a @[simp]
theorem Iic_iInf₂ (f : ∀ i, κ i → α) : Iic (⨅ (i) (j), f i j) = ⨅ (i) (j), Iic (f i j) := by
simp_rw [Iic_iInf]
#align lower_set.Iic_infi₂ LowerSet.Iic_iInf₂
end CompleteLattice
end LowerSet
section closure
variable [Preorder α] [Preorder β] {s t : Set α} {x : α}
/-- The greatest upper set containing a given set. -/
def upperClosure (s : Set α) : UpperSet α :=
⟨{ x | ∃ a ∈ s, a ≤ x }, fun _ _ hle h => h.imp fun _x hx => ⟨hx.1, hx.2.trans hle⟩⟩
#align upper_closure upperClosure
/-- The least lower set containing a given set. -/
def lowerClosure (s : Set α) : LowerSet α :=
⟨{ x | ∃ a ∈ s, x ≤ a }, fun _ _ hle h => h.imp fun _x hx => ⟨hx.1, hle.trans hx.2⟩⟩
#align lower_closure lowerClosure
-- Porting note (#11215): TODO: move `GaloisInsertion`s up, use them to prove lemmas
@[simp]
theorem mem_upperClosure : x ∈ upperClosure s ↔ ∃ a ∈ s, a ≤ x :=
Iff.rfl
#align mem_upper_closure mem_upperClosure
@[simp]
theorem mem_lowerClosure : x ∈ lowerClosure s ↔ ∃ a ∈ s, x ≤ a :=
Iff.rfl
#align mem_lower_closure mem_lowerClosure
-- We do not tag those two as `simp` to respect the abstraction.
@[norm_cast]
theorem coe_upperClosure (s : Set α) : ↑(upperClosure s) = ⋃ a ∈ s, Ici a := by
ext
simp
#align coe_upper_closure coe_upperClosure
@[norm_cast]
theorem coe_lowerClosure (s : Set α) : ↑(lowerClosure s) = ⋃ a ∈ s, Iic a := by
ext
simp
#align coe_lower_closure coe_lowerClosure
instance instDecidablePredMemUpperClosure [DecidablePred (∃ a ∈ s, a ≤ ·)] :
DecidablePred (· ∈ upperClosure s) := ‹DecidablePred _›
instance instDecidablePredMemLowerClosure [DecidablePred (∃ a ∈ s, · ≤ a)] :
DecidablePred (· ∈ lowerClosure s) := ‹DecidablePred _›
theorem subset_upperClosure : s ⊆ upperClosure s := fun x hx => ⟨x, hx, le_rfl⟩
#align subset_upper_closure subset_upperClosure
theorem subset_lowerClosure : s ⊆ lowerClosure s := fun x hx => ⟨x, hx, le_rfl⟩
#align subset_lower_closure subset_lowerClosure
theorem upperClosure_min (h : s ⊆ t) (ht : IsUpperSet t) : ↑(upperClosure s) ⊆ t :=
fun _a ⟨_b, hb, hba⟩ => ht hba <| h hb
#align upper_closure_min upperClosure_min
theorem lowerClosure_min (h : s ⊆ t) (ht : IsLowerSet t) : ↑(lowerClosure s) ⊆ t :=
fun _a ⟨_b, hb, hab⟩ => ht hab <| h hb
#align lower_closure_min lowerClosure_min
protected theorem IsUpperSet.upperClosure (hs : IsUpperSet s) : ↑(upperClosure s) = s :=
(upperClosure_min Subset.rfl hs).antisymm subset_upperClosure
#align is_upper_set.upper_closure IsUpperSet.upperClosure
protected theorem IsLowerSet.lowerClosure (hs : IsLowerSet s) : ↑(lowerClosure s) = s :=
(lowerClosure_min Subset.rfl hs).antisymm subset_lowerClosure
#align is_lower_set.lower_closure IsLowerSet.lowerClosure
@[simp]
protected theorem UpperSet.upperClosure (s : UpperSet α) : upperClosure (s : Set α) = s :=
SetLike.coe_injective s.2.upperClosure
#align upper_set.upper_closure UpperSet.upperClosure
@[simp]
protected theorem LowerSet.lowerClosure (s : LowerSet α) : lowerClosure (s : Set α) = s :=
SetLike.coe_injective s.2.lowerClosure
#align lower_set.lower_closure LowerSet.lowerClosure
@[simp]
theorem upperClosure_image (f : α ≃o β) :
upperClosure (f '' s) = UpperSet.map f (upperClosure s) := by
rw [← f.symm_symm, ← UpperSet.symm_map, f.symm_symm]
ext
simp [-UpperSet.symm_map, UpperSet.map, OrderIso.symm, ← f.le_symm_apply]
#align upper_closure_image upperClosure_image
@[simp]
theorem lowerClosure_image (f : α ≃o β) :
lowerClosure (f '' s) = LowerSet.map f (lowerClosure s) := by
rw [← f.symm_symm, ← LowerSet.symm_map, f.symm_symm]
ext
simp [-LowerSet.symm_map, LowerSet.map, OrderIso.symm, ← f.symm_apply_le]
#align lower_closure_image lowerClosure_image
@[simp]
theorem UpperSet.iInf_Ici (s : Set α) : ⨅ a ∈ s, UpperSet.Ici a = upperClosure s := by
ext
simp
#align upper_set.infi_Ici UpperSet.iInf_Ici
@[simp]
theorem LowerSet.iSup_Iic (s : Set α) : ⨆ a ∈ s, LowerSet.Iic a = lowerClosure s := by
ext
simp
#align lower_set.supr_Iic LowerSet.iSup_Iic
@[simp] lemma lowerClosure_le {t : LowerSet α} : lowerClosure s ≤ t ↔ s ⊆ t :=
⟨fun h ↦ subset_lowerClosure.trans <| LowerSet.coe_subset_coe.2 h,
fun h ↦ lowerClosure_min h t.lower⟩
@[simp] lemma le_upperClosure {s : UpperSet α} : s ≤ upperClosure t ↔ t ⊆ s :=
⟨fun h ↦ subset_upperClosure.trans <| UpperSet.coe_subset_coe.2 h,
fun h ↦ upperClosure_min h s.upper⟩
theorem gc_upperClosure_coe :
GaloisConnection (toDual ∘ upperClosure : Set α → (UpperSet α)ᵒᵈ) ((↑) ∘ ofDual) :=
fun _s _t ↦ le_upperClosure
#align gc_upper_closure_coe gc_upperClosure_coe
theorem gc_lowerClosure_coe :
GaloisConnection (lowerClosure : Set α → LowerSet α) (↑) := fun _s _t ↦ lowerClosure_le
#align gc_lower_closure_coe gc_lowerClosure_coe
/-- `upperClosure` forms a reversed Galois insertion with the coercion from upper sets to sets. -/
def giUpperClosureCoe :
GaloisInsertion (toDual ∘ upperClosure : Set α → (UpperSet α)ᵒᵈ) ((↑) ∘ ofDual) where
choice s hs := toDual (⟨s, fun a _b hab ha => hs ⟨a, ha, hab⟩⟩ : UpperSet α)
gc := gc_upperClosure_coe
le_l_u _ := subset_upperClosure
choice_eq _s hs := ofDual.injective <| SetLike.coe_injective <| subset_upperClosure.antisymm hs
#align gi_upper_closure_coe giUpperClosureCoe
/-- `lowerClosure` forms a Galois insertion with the coercion from lower sets to sets. -/
def giLowerClosureCoe : GaloisInsertion (lowerClosure : Set α → LowerSet α) (↑) where
choice s hs := ⟨s, fun a _b hba ha => hs ⟨a, ha, hba⟩⟩
gc := gc_lowerClosure_coe
le_l_u _ := subset_lowerClosure
choice_eq _s hs := SetLike.coe_injective <| subset_lowerClosure.antisymm hs
#align gi_lower_closure_coe giLowerClosureCoe
theorem upperClosure_anti : Antitone (upperClosure : Set α → UpperSet α) :=
gc_upperClosure_coe.monotone_l
#align upper_closure_anti upperClosure_anti
theorem lowerClosure_mono : Monotone (lowerClosure : Set α → LowerSet α) :=
gc_lowerClosure_coe.monotone_l
#align lower_closure_mono lowerClosure_mono
@[simp]
theorem upperClosure_empty : upperClosure (∅ : Set α) = ⊤ :=
(@gc_upperClosure_coe α).l_bot
#align upper_closure_empty upperClosure_empty
@[simp]
theorem lowerClosure_empty : lowerClosure (∅ : Set α) = ⊥ :=
(@gc_lowerClosure_coe α).l_bot
#align lower_closure_empty lowerClosure_empty
@[simp]
theorem upperClosure_singleton (a : α) : upperClosure ({a} : Set α) = UpperSet.Ici a := by
ext
simp
#align upper_closure_singleton upperClosure_singleton
@[simp]
theorem lowerClosure_singleton (a : α) : lowerClosure ({a} : Set α) = LowerSet.Iic a := by
ext
simp
#align lower_closure_singleton lowerClosure_singleton
@[simp]
theorem upperClosure_univ : upperClosure (univ : Set α) = ⊥ :=
bot_unique subset_upperClosure
#align upper_closure_univ upperClosure_univ
@[simp]
theorem lowerClosure_univ : lowerClosure (univ : Set α) = ⊤ :=
top_unique subset_lowerClosure
#align lower_closure_univ lowerClosure_univ
@[simp]
theorem upperClosure_eq_top_iff : upperClosure s = ⊤ ↔ s = ∅ :=
(@gc_upperClosure_coe α _).l_eq_bot.trans subset_empty_iff
#align upper_closure_eq_top_iff upperClosure_eq_top_iff
@[simp]
theorem lowerClosure_eq_bot_iff : lowerClosure s = ⊥ ↔ s = ∅ :=
(@gc_lowerClosure_coe α _).l_eq_bot.trans subset_empty_iff
#align lower_closure_eq_bot_iff lowerClosure_eq_bot_iff
@[simp]
theorem upperClosure_union (s t : Set α) : upperClosure (s ∪ t) = upperClosure s ⊓ upperClosure t :=
(@gc_upperClosure_coe α _).l_sup
#align upper_closure_union upperClosure_union
@[simp]
theorem lowerClosure_union (s t : Set α) : lowerClosure (s ∪ t) = lowerClosure s ⊔ lowerClosure t :=
(@gc_lowerClosure_coe α _).l_sup
#align lower_closure_union lowerClosure_union
@[simp]
theorem upperClosure_iUnion (f : ι → Set α) : upperClosure (⋃ i, f i) = ⨅ i, upperClosure (f i) :=
(@gc_upperClosure_coe α _).l_iSup
#align upper_closure_Union upperClosure_iUnion
@[simp]
theorem lowerClosure_iUnion (f : ι → Set α) : lowerClosure (⋃ i, f i) = ⨆ i, lowerClosure (f i) :=
(@gc_lowerClosure_coe α _).l_iSup
#align lower_closure_Union lowerClosure_iUnion
@[simp]
theorem upperClosure_sUnion (S : Set (Set α)) : upperClosure (⋃₀ S) = ⨅ s ∈ S, upperClosure s := by
simp_rw [sUnion_eq_biUnion, upperClosure_iUnion]
#align upper_closure_sUnion upperClosure_sUnion
@[simp]
theorem lowerClosure_sUnion (S : Set (Set α)) : lowerClosure (⋃₀ S) = ⨆ s ∈ S, lowerClosure s := by
simp_rw [sUnion_eq_biUnion, lowerClosure_iUnion]
#align lower_closure_sUnion lowerClosure_sUnion
theorem Set.OrdConnected.upperClosure_inter_lowerClosure (h : s.OrdConnected) :
↑(upperClosure s) ∩ ↑(lowerClosure s) = s :=
(subset_inter subset_upperClosure subset_lowerClosure).antisymm'
fun _a ⟨⟨_b, hb, hba⟩, _c, hc, hac⟩ => h.out hb hc ⟨hba, hac⟩
#align set.ord_connected.upper_closure_inter_lower_closure Set.OrdConnected.upperClosure_inter_lowerClosure
theorem ordConnected_iff_upperClosure_inter_lowerClosure :
s.OrdConnected ↔ ↑(upperClosure s) ∩ ↑(lowerClosure s) = s := by
refine ⟨Set.OrdConnected.upperClosure_inter_lowerClosure, fun h => ?_⟩
rw [← h]
exact (UpperSet.upper _).ordConnected.inter (LowerSet.lower _).ordConnected
#align ord_connected_iff_upper_closure_inter_lower_closure ordConnected_iff_upperClosure_inter_lowerClosure
@[simp]
theorem upperBounds_lowerClosure : upperBounds (lowerClosure s : Set α) = upperBounds s :=
(upperBounds_mono_set subset_lowerClosure).antisymm
fun _a ha _b ⟨_c, hc, hcb⟩ ↦ hcb.trans <| ha hc
#align upper_bounds_lower_closure upperBounds_lowerClosure
@[simp]
theorem lowerBounds_upperClosure : lowerBounds (upperClosure s : Set α) = lowerBounds s :=
(lowerBounds_mono_set subset_upperClosure).antisymm
fun _a ha _b ⟨_c, hc, hcb⟩ ↦ (ha hc).trans hcb
#align lower_bounds_upper_closure lowerBounds_upperClosure
@[simp]
theorem bddAbove_lowerClosure : BddAbove (lowerClosure s : Set α) ↔ BddAbove s := by
simp_rw [BddAbove, upperBounds_lowerClosure]
#align bdd_above_lower_closure bddAbove_lowerClosure
@[simp]
theorem bddBelow_upperClosure : BddBelow (upperClosure s : Set α) ↔ BddBelow s := by
simp_rw [BddBelow, lowerBounds_upperClosure]
#align bdd_below_upper_closure bddBelow_upperClosure
protected alias ⟨BddAbove.of_lowerClosure, BddAbove.lowerClosure⟩ := bddAbove_lowerClosure
#align bdd_above.of_lower_closure BddAbove.of_lowerClosure
#align bdd_above.lower_closure BddAbove.lowerClosure
protected alias ⟨BddBelow.of_upperClosure, BddBelow.upperClosure⟩ := bddBelow_upperClosure
#align bdd_below.of_upper_closure BddBelow.of_upperClosure
#align bdd_below.upper_closure BddBelow.upperClosure
@[simp] lemma IsLowerSet.disjoint_upperClosure_left (ht : IsLowerSet t) :
Disjoint ↑(upperClosure s) t ↔ Disjoint s t := by
refine ⟨Disjoint.mono_left subset_upperClosure, ?_⟩
simp only [disjoint_left, SetLike.mem_coe, mem_upperClosure, forall_exists_index, and_imp]
exact fun h a b hb hba ha ↦ h hb <| ht hba ha
@[simp] lemma IsLowerSet.disjoint_upperClosure_right (hs : IsLowerSet s) :
Disjoint s (upperClosure t) ↔ Disjoint s t := by
simpa only [disjoint_comm] using hs.disjoint_upperClosure_left
@[simp] lemma IsUpperSet.disjoint_lowerClosure_left (ht : IsUpperSet t) :
Disjoint ↑(lowerClosure s) t ↔ Disjoint s t := ht.toDual.disjoint_upperClosure_left
@[simp] lemma IsUpperSet.disjoint_lowerClosure_right (hs : IsUpperSet s) :
Disjoint s (lowerClosure t) ↔ Disjoint s t := hs.toDual.disjoint_upperClosure_right
end closure
/-! ### Set Difference -/
namespace LowerSet
variable [Preorder α] {s : LowerSet α} {t : Set α} {a : α}
/-- The biggest lower subset of a lower set `s` disjoint from a set `t`. -/
def sdiff (s : LowerSet α) (t : Set α) : LowerSet α where
carrier := s \ upperClosure t
lower' := s.lower.sdiff_of_isUpperSet (upperClosure t).upper
/-- The biggest lower subset of a lower set `s` not containing an element `a`. -/
def erase (s : LowerSet α) (a : α) : LowerSet α where
carrier := s \ UpperSet.Ici a
lower' := s.lower.sdiff_of_isUpperSet (UpperSet.Ici a).upper
@[simp, norm_cast]
lemma coe_sdiff (s : LowerSet α) (t : Set α) : s.sdiff t = (s : Set α) \ upperClosure t := rfl
@[simp, norm_cast]
lemma coe_erase (s : LowerSet α) (a : α) : s.erase a = (s : Set α) \ UpperSet.Ici a := rfl
@[simp] lemma sdiff_singleton (s : LowerSet α) (a : α) : s.sdiff {a} = s.erase a := by
simp [sdiff, erase]
lemma sdiff_le_left : s.sdiff t ≤ s := diff_subset
lemma erase_le : s.erase a ≤ s := diff_subset
@[simp] protected lemma sdiff_eq_left : s.sdiff t = s ↔ Disjoint ↑s t := by
simp [← SetLike.coe_set_eq]
@[simp] lemma erase_eq : s.erase a = s ↔ a ∉ s := by rw [← sdiff_singleton]; simp [-sdiff_singleton]
@[simp] lemma sdiff_lt_left : s.sdiff t < s ↔ ¬ Disjoint ↑s t :=
sdiff_le_left.lt_iff_ne.trans LowerSet.sdiff_eq_left.not
@[simp] lemma erase_lt : s.erase a < s ↔ a ∈ s := erase_le.lt_iff_ne.trans erase_eq.not_left
@[simp] protected lemma sdiff_idem (s : LowerSet α) (t : Set α) : (s.sdiff t).sdiff t = s.sdiff t :=
SetLike.coe_injective sdiff_idem
@[simp] lemma erase_idem (s : LowerSet α) (a : α) : (s.erase a).erase a = s.erase a :=
SetLike.coe_injective sdiff_idem
lemma sdiff_sup_lowerClosure (hts : t ⊆ s) (hst : ∀ b ∈ s, ∀ c ∈ t, c ≤ b → b ∈ t) :
s.sdiff t ⊔ lowerClosure t = s := by
refine le_antisymm (sup_le sdiff_le_left <| lowerClosure_le.2 hts) fun a ha ↦ ?_
obtain hat | hat := em (a ∈ t)
· exact subset_union_right (subset_lowerClosure hat)
· refine subset_union_left ⟨ha, ?_⟩
rintro ⟨b, hb, hba⟩
exact hat <| hst _ ha _ hb hba
lemma lowerClosure_sup_sdiff (hts : t ⊆ s) (hst : ∀ b ∈ s, ∀ c ∈ t, c ≤ b → b ∈ t) :
lowerClosure t ⊔ s.sdiff t = s := by rw [sup_comm, sdiff_sup_lowerClosure hts hst]
lemma erase_sup_Iic (ha : a ∈ s) (has : ∀ b ∈ s, a ≤ b → b = a) : s.erase a ⊔ Iic a = s := by
rw [← lowerClosure_singleton, ← sdiff_singleton, sdiff_sup_lowerClosure] <;> simpa
lemma Iic_sup_erase (ha : a ∈ s) (has : ∀ b ∈ s, a ≤ b → b = a) : Iic a ⊔ s.erase a = s := by
rw [sup_comm, erase_sup_Iic ha has]
end LowerSet
namespace UpperSet
variable [Preorder α] {s : UpperSet α} {t : Set α} {a : α}
/-- The biggest upper subset of a upper set `s` disjoint from a set `t`. -/
def sdiff (s : UpperSet α) (t : Set α) : UpperSet α where
carrier := s \ lowerClosure t
upper' := s.upper.sdiff_of_isLowerSet (lowerClosure t).lower
/-- The biggest upper subset of a upper set `s` not containing an element `a`. -/
def erase (s : UpperSet α) (a : α) : UpperSet α where
carrier := s \ LowerSet.Iic a
upper' := s.upper.sdiff_of_isLowerSet (LowerSet.Iic a).lower
@[simp, norm_cast]
lemma coe_sdiff (s : UpperSet α) (t : Set α) : s.sdiff t = (s : Set α) \ lowerClosure t := rfl
@[simp, norm_cast]
lemma coe_erase (s : UpperSet α) (a : α) : s.erase a = (s : Set α) \ LowerSet.Iic a := rfl
@[simp] lemma sdiff_singleton (s : UpperSet α) (a : α) : s.sdiff {a} = s.erase a := by
simp [sdiff, erase]
lemma le_sdiff_left : s ≤ s.sdiff t := diff_subset
lemma le_erase : s ≤ s.erase a := diff_subset
@[simp] protected lemma sdiff_eq_left : s.sdiff t = s ↔ Disjoint ↑s t := by
simp [← SetLike.coe_set_eq]
@[simp] lemma erase_eq : s.erase a = s ↔ a ∉ s := by rw [← sdiff_singleton]; simp [-sdiff_singleton]
@[simp] lemma lt_sdiff_left : s < s.sdiff t ↔ ¬ Disjoint ↑s t :=
le_sdiff_left.gt_iff_ne.trans UpperSet.sdiff_eq_left.not
@[simp] lemma lt_erase : s < s.erase a ↔ a ∈ s := le_erase.gt_iff_ne.trans erase_eq.not_left
@[simp] protected lemma sdiff_idem (s : UpperSet α) (t : Set α) : (s.sdiff t).sdiff t = s.sdiff t :=
SetLike.coe_injective sdiff_idem
@[simp] lemma erase_idem (s : UpperSet α) (a : α) : (s.erase a).erase a = s.erase a :=
SetLike.coe_injective sdiff_idem
lemma sdiff_inf_upperClosure (hts : t ⊆ s) (hst : ∀ b ∈ s, ∀ c ∈ t, b ≤ c → b ∈ t) :
s.sdiff t ⊓ upperClosure t = s := by
refine ge_antisymm (le_inf le_sdiff_left <| le_upperClosure.2 hts) fun a ha ↦ ?_
obtain hat | hat := em (a ∈ t)
· exact subset_union_right (subset_upperClosure hat)
· refine subset_union_left ⟨ha, ?_⟩
rintro ⟨b, hb, hab⟩
exact hat <| hst _ ha _ hb hab
lemma upperClosure_inf_sdiff (hts : t ⊆ s) (hst : ∀ b ∈ s, ∀ c ∈ t, b ≤ c → b ∈ t) :
upperClosure t ⊓ s.sdiff t = s := by rw [inf_comm, sdiff_inf_upperClosure hts hst]
lemma erase_inf_Ici (ha : a ∈ s) (has : ∀ b ∈ s, b ≤ a → b = a) : s.erase a ⊓ Ici a = s := by
rw [← upperClosure_singleton, ← sdiff_singleton, sdiff_inf_upperClosure] <;> simpa
lemma Ici_inf_erase (ha : a ∈ s) (has : ∀ b ∈ s, b ≤ a → b = a) : Ici a ⊓ s.erase a = s := by
rw [inf_comm, erase_inf_Ici ha has]
end UpperSet
/-! ### Product -/
section Preorder
variable [Preorder α] [Preorder β]
section
variable {s : Set α} {t : Set β} {x : α × β}
theorem IsUpperSet.prod (hs : IsUpperSet s) (ht : IsUpperSet t) : IsUpperSet (s ×ˢ t) :=
fun _ _ h ha => ⟨hs h.1 ha.1, ht h.2 ha.2⟩
#align is_upper_set.prod IsUpperSet.prod
theorem IsLowerSet.prod (hs : IsLowerSet s) (ht : IsLowerSet t) : IsLowerSet (s ×ˢ t) :=
fun _ _ h ha => ⟨hs h.1 ha.1, ht h.2 ha.2⟩
#align is_lower_set.prod IsLowerSet.prod
end
namespace UpperSet
variable (s s₁ s₂ : UpperSet α) (t t₁ t₂ : UpperSet β) {x : α × β}
/-- The product of two upper sets as an upper set. -/
def prod : UpperSet (α × β) :=
⟨s ×ˢ t, s.2.prod t.2⟩
#align upper_set.prod UpperSet.prod
instance instSProd : SProd (UpperSet α) (UpperSet β) (UpperSet (α × β)) where
sprod := UpperSet.prod
@[simp, norm_cast]
theorem coe_prod : ((s ×ˢ t : UpperSet (α × β)) : Set (α × β)) = (s : Set α) ×ˢ t :=
rfl
#align upper_set.coe_prod UpperSet.coe_prod
@[simp]
theorem mem_prod {s : UpperSet α} {t : UpperSet β} : x ∈ s ×ˢ t ↔ x.1 ∈ s ∧ x.2 ∈ t :=
Iff.rfl
#align upper_set.mem_prod UpperSet.mem_prod
theorem Ici_prod (x : α × β) : Ici x = Ici x.1 ×ˢ Ici x.2 :=
rfl
#align upper_set.Ici_prod UpperSet.Ici_prod
@[simp]
theorem Ici_prod_Ici (a : α) (b : β) : Ici a ×ˢ Ici b = Ici (a, b) :=
rfl
#align upper_set.Ici_prod_Ici UpperSet.Ici_prod_Ici
@[simp]
theorem prod_top : s ×ˢ (⊤ : UpperSet β) = ⊤ :=
ext prod_empty
#align upper_set.prod_top UpperSet.prod_top
@[simp]
theorem top_prod : (⊤ : UpperSet α) ×ˢ t = ⊤ :=
ext empty_prod
#align upper_set.top_prod UpperSet.top_prod
@[simp]
theorem bot_prod_bot : (⊥ : UpperSet α) ×ˢ (⊥ : UpperSet β) = ⊥ :=
ext univ_prod_univ
#align upper_set.bot_prod_bot UpperSet.bot_prod_bot
@[simp]
theorem sup_prod : (s₁ ⊔ s₂) ×ˢ t = s₁ ×ˢ t ⊔ s₂ ×ˢ t :=
ext inter_prod
#align upper_set.sup_prod UpperSet.sup_prod
@[simp]
theorem prod_sup : s ×ˢ (t₁ ⊔ t₂) = s ×ˢ t₁ ⊔ s ×ˢ t₂ :=
ext prod_inter
#align upper_set.prod_sup UpperSet.prod_sup
@[simp]
theorem inf_prod : (s₁ ⊓ s₂) ×ˢ t = s₁ ×ˢ t ⊓ s₂ ×ˢ t :=
ext union_prod
#align upper_set.inf_prod UpperSet.inf_prod
@[simp]
theorem prod_inf : s ×ˢ (t₁ ⊓ t₂) = s ×ˢ t₁ ⊓ s ×ˢ t₂ :=
ext prod_union
#align upper_set.prod_inf UpperSet.prod_inf
theorem prod_sup_prod : s₁ ×ˢ t₁ ⊔ s₂ ×ˢ t₂ = (s₁ ⊔ s₂) ×ˢ (t₁ ⊔ t₂) :=
ext prod_inter_prod
#align upper_set.prod_sup_prod UpperSet.prod_sup_prod
variable {s s₁ s₂ t t₁ t₂}
@[mono]
theorem prod_mono : s₁ ≤ s₂ → t₁ ≤ t₂ → s₁ ×ˢ t₁ ≤ s₂ ×ˢ t₂ :=
Set.prod_mono
#align upper_set.prod_mono UpperSet.prod_mono
theorem prod_mono_left : s₁ ≤ s₂ → s₁ ×ˢ t ≤ s₂ ×ˢ t :=
Set.prod_mono_left
#align upper_set.prod_mono_left UpperSet.prod_mono_left
theorem prod_mono_right : t₁ ≤ t₂ → s ×ˢ t₁ ≤ s ×ˢ t₂ :=
Set.prod_mono_right
#align upper_set.prod_mono_right UpperSet.prod_mono_right
@[simp]
theorem prod_self_le_prod_self : s₁ ×ˢ s₁ ≤ s₂ ×ˢ s₂ ↔ s₁ ≤ s₂ :=
prod_self_subset_prod_self
#align upper_set.prod_self_le_prod_self UpperSet.prod_self_le_prod_self
@[simp]
theorem prod_self_lt_prod_self : s₁ ×ˢ s₁ < s₂ ×ˢ s₂ ↔ s₁ < s₂ :=
prod_self_ssubset_prod_self
#align upper_set.prod_self_lt_prod_self UpperSet.prod_self_lt_prod_self
theorem prod_le_prod_iff : s₁ ×ˢ t₁ ≤ s₂ ×ˢ t₂ ↔ s₁ ≤ s₂ ∧ t₁ ≤ t₂ ∨ s₂ = ⊤ ∨ t₂ = ⊤ :=
prod_subset_prod_iff.trans <| by simp
#align upper_set.prod_le_prod_iff UpperSet.prod_le_prod_iff
@[simp]
theorem prod_eq_top : s ×ˢ t = ⊤ ↔ s = ⊤ ∨ t = ⊤ := by
simp_rw [SetLike.ext'_iff]
exact prod_eq_empty_iff
#align upper_set.prod_eq_top UpperSet.prod_eq_top
@[simp]
theorem codisjoint_prod :
Codisjoint (s₁ ×ˢ t₁) (s₂ ×ˢ t₂) ↔ Codisjoint s₁ s₂ ∨ Codisjoint t₁ t₂ := by
simp_rw [codisjoint_iff, prod_sup_prod, prod_eq_top]
#align upper_set.codisjoint_prod UpperSet.codisjoint_prod
end UpperSet
namespace LowerSet
variable (s s₁ s₂ : LowerSet α) (t t₁ t₂ : LowerSet β) {x : α × β}
/-- The product of two lower sets as a lower set. -/
def prod : LowerSet (α × β) := ⟨s ×ˢ t, s.2.prod t.2⟩
#align lower_set.prod LowerSet.prod
instance instSProd : SProd (LowerSet α) (LowerSet β) (LowerSet (α × β)) where
sprod := LowerSet.prod
@[simp, norm_cast]
theorem coe_prod : ((s ×ˢ t : LowerSet (α × β)) : Set (α × β)) = (s : Set α) ×ˢ t := rfl
#align lower_set.coe_prod LowerSet.coe_prod
@[simp]
theorem mem_prod {s : LowerSet α} {t : LowerSet β} : x ∈ s ×ˢ t ↔ x.1 ∈ s ∧ x.2 ∈ t :=
Iff.rfl
#align lower_set.mem_prod LowerSet.mem_prod
theorem Iic_prod (x : α × β) : Iic x = Iic x.1 ×ˢ Iic x.2 :=
rfl
#align lower_set.Iic_prod LowerSet.Iic_prod
@[simp]
theorem Ici_prod_Ici (a : α) (b : β) : Iic a ×ˢ Iic b = Iic (a, b) :=
rfl
#align lower_set.Ici_prod_Ici LowerSet.Ici_prod_Ici
@[simp]
theorem prod_bot : s ×ˢ (⊥ : LowerSet β) = ⊥ :=
ext prod_empty
#align lower_set.prod_bot LowerSet.prod_bot
@[simp]
theorem bot_prod : (⊥ : LowerSet α) ×ˢ t = ⊥ :=
ext empty_prod
#align lower_set.bot_prod LowerSet.bot_prod
@[simp]
theorem top_prod_top : (⊤ : LowerSet α) ×ˢ (⊤ : LowerSet β) = ⊤ :=
ext univ_prod_univ
#align lower_set.top_prod_top LowerSet.top_prod_top
@[simp]
theorem inf_prod : (s₁ ⊓ s₂) ×ˢ t = s₁ ×ˢ t ⊓ s₂ ×ˢ t :=
ext inter_prod
#align lower_set.inf_prod LowerSet.inf_prod
@[simp]
theorem prod_inf : s ×ˢ (t₁ ⊓ t₂) = s ×ˢ t₁ ⊓ s ×ˢ t₂ :=
ext prod_inter
#align lower_set.prod_inf LowerSet.prod_inf
@[simp]
theorem sup_prod : (s₁ ⊔ s₂) ×ˢ t = s₁ ×ˢ t ⊔ s₂ ×ˢ t :=
ext union_prod
#align lower_set.sup_prod LowerSet.sup_prod
@[simp]
theorem prod_sup : s ×ˢ (t₁ ⊔ t₂) = s ×ˢ t₁ ⊔ s ×ˢ t₂ :=
ext prod_union
#align lower_set.prod_sup LowerSet.prod_sup
theorem prod_inf_prod : s₁ ×ˢ t₁ ⊓ s₂ ×ˢ t₂ = (s₁ ⊓ s₂) ×ˢ (t₁ ⊓ t₂) :=
ext prod_inter_prod
#align lower_set.prod_inf_prod LowerSet.prod_inf_prod
variable {s s₁ s₂ t t₁ t₂}
theorem prod_mono : s₁ ≤ s₂ → t₁ ≤ t₂ → s₁ ×ˢ t₁ ≤ s₂ ×ˢ t₂ := Set.prod_mono
#align lower_set.prod_mono LowerSet.prod_mono
theorem prod_mono_left : s₁ ≤ s₂ → s₁ ×ˢ t ≤ s₂ ×ˢ t := Set.prod_mono_left
#align lower_set.prod_mono_left LowerSet.prod_mono_left
theorem prod_mono_right : t₁ ≤ t₂ → s ×ˢ t₁ ≤ s ×ˢ t₂ := Set.prod_mono_right
#align lower_set.prod_mono_right LowerSet.prod_mono_right
@[simp]
theorem prod_self_le_prod_self : s₁ ×ˢ s₁ ≤ s₂ ×ˢ s₂ ↔ s₁ ≤ s₂ :=
prod_self_subset_prod_self
#align lower_set.prod_self_le_prod_self LowerSet.prod_self_le_prod_self
@[simp]
theorem prod_self_lt_prod_self : s₁ ×ˢ s₁ < s₂ ×ˢ s₂ ↔ s₁ < s₂ :=
prod_self_ssubset_prod_self
#align lower_set.prod_self_lt_prod_self LowerSet.prod_self_lt_prod_self
theorem prod_le_prod_iff : s₁ ×ˢ t₁ ≤ s₂ ×ˢ t₂ ↔ s₁ ≤ s₂ ∧ t₁ ≤ t₂ ∨ s₁ = ⊥ ∨ t₁ = ⊥ :=
prod_subset_prod_iff.trans <| by simp
#align lower_set.prod_le_prod_iff LowerSet.prod_le_prod_iff
@[simp]
theorem prod_eq_bot : s ×ˢ t = ⊥ ↔ s = ⊥ ∨ t = ⊥ := by
simp_rw [SetLike.ext'_iff]
exact prod_eq_empty_iff
#align lower_set.prod_eq_bot LowerSet.prod_eq_bot
@[simp]
theorem disjoint_prod : Disjoint (s₁ ×ˢ t₁) (s₂ ×ˢ t₂) ↔ Disjoint s₁ s₂ ∨ Disjoint t₁ t₂ := by
simp_rw [disjoint_iff, prod_inf_prod, prod_eq_bot]
#align lower_set.disjoint_prod LowerSet.disjoint_prod
end LowerSet
@[simp]
theorem upperClosure_prod (s : Set α) (t : Set β) :
upperClosure (s ×ˢ t) = upperClosure s ×ˢ upperClosure t := by
ext
simp [Prod.le_def, @and_and_and_comm _ (_ ∈ t)]
#align upper_closure_prod upperClosure_prod
@[simp]
| Mathlib/Order/UpperLower/Basic.lean | 2,035 | 2,038 | theorem lowerClosure_prod (s : Set α) (t : Set β) :
lowerClosure (s ×ˢ t) = lowerClosure s ×ˢ lowerClosure t := by |
ext
simp [Prod.le_def, @and_and_and_comm _ (_ ∈ t)]
|
/-
Copyright (c) 2022 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers, Heather Macbeth
-/
import Mathlib.Analysis.InnerProductSpace.GramSchmidtOrtho
import Mathlib.LinearAlgebra.Orientation
#align_import analysis.inner_product_space.orientation from "leanprover-community/mathlib"@"bd65478311e4dfd41f48bf38c7e3b02fb75d0163"
/-!
# Orientations of real inner product spaces.
This file provides definitions and proves lemmas about orientations of real inner product spaces.
## Main definitions
* `OrthonormalBasis.adjustToOrientation` takes an orthonormal basis and an orientation, and
returns an orthonormal basis with that orientation: either the original orthonormal basis, or one
constructed by negating a single (arbitrary) basis vector.
* `Orientation.finOrthonormalBasis` is an orthonormal basis, indexed by `Fin n`, with the given
orientation.
* `Orientation.volumeForm` is a nonvanishing top-dimensional alternating form on an oriented real
inner product space, uniquely defined by compatibility with the orientation and inner product
structure.
## Main theorems
* `Orientation.volumeForm_apply_le` states that the result of applying the volume form to a set of
`n` vectors, where `n` is the dimension the inner product space, is bounded by the product of the
lengths of the vectors.
* `Orientation.abs_volumeForm_apply_of_pairwise_orthogonal` states that the result of applying the
volume form to a set of `n` orthogonal vectors, where `n` is the dimension the inner product
space, is equal up to sign to the product of the lengths of the vectors.
-/
noncomputable section
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
open FiniteDimensional
open scoped RealInnerProductSpace
namespace OrthonormalBasis
variable {ι : Type*} [Fintype ι] [DecidableEq ι] [ne : Nonempty ι] (e f : OrthonormalBasis ι ℝ E)
(x : Orientation ℝ E ι)
/-- The change-of-basis matrix between two orthonormal bases with the same orientation has
determinant 1. -/
theorem det_to_matrix_orthonormalBasis_of_same_orientation
(h : e.toBasis.orientation = f.toBasis.orientation) : e.toBasis.det f = 1 := by
apply (e.det_to_matrix_orthonormalBasis_real f).resolve_right
have : 0 < e.toBasis.det f := by
rw [e.toBasis.orientation_eq_iff_det_pos] at h
simpa using h
linarith
#align orthonormal_basis.det_to_matrix_orthonormal_basis_of_same_orientation OrthonormalBasis.det_to_matrix_orthonormalBasis_of_same_orientation
/-- The change-of-basis matrix between two orthonormal bases with the opposite orientations has
determinant -1. -/
theorem det_to_matrix_orthonormalBasis_of_opposite_orientation
(h : e.toBasis.orientation ≠ f.toBasis.orientation) : e.toBasis.det f = -1 := by
contrapose! h
simp [e.toBasis.orientation_eq_iff_det_pos,
(e.det_to_matrix_orthonormalBasis_real f).resolve_right h]
#align orthonormal_basis.det_to_matrix_orthonormal_basis_of_opposite_orientation OrthonormalBasis.det_to_matrix_orthonormalBasis_of_opposite_orientation
variable {e f}
/-- Two orthonormal bases with the same orientation determine the same "determinant" top-dimensional
form on `E`, and conversely. -/
theorem same_orientation_iff_det_eq_det :
e.toBasis.det = f.toBasis.det ↔ e.toBasis.orientation = f.toBasis.orientation := by
constructor
· intro h
dsimp [Basis.orientation]
congr
· intro h
rw [e.toBasis.det.eq_smul_basis_det f.toBasis]
simp [e.det_to_matrix_orthonormalBasis_of_same_orientation f h]
#align orthonormal_basis.same_orientation_iff_det_eq_det OrthonormalBasis.same_orientation_iff_det_eq_det
variable (e f)
/-- Two orthonormal bases with opposite orientations determine opposite "determinant"
top-dimensional forms on `E`. -/
theorem det_eq_neg_det_of_opposite_orientation (h : e.toBasis.orientation ≠ f.toBasis.orientation) :
e.toBasis.det = -f.toBasis.det := by
rw [e.toBasis.det.eq_smul_basis_det f.toBasis]
-- Porting note: added `neg_one_smul` with explicit type
simp [e.det_to_matrix_orthonormalBasis_of_opposite_orientation f h,
neg_one_smul ℝ (M := E [⋀^ι]→ₗ[ℝ] ℝ)]
#align orthonormal_basis.det_eq_neg_det_of_opposite_orientation OrthonormalBasis.det_eq_neg_det_of_opposite_orientation
section AdjustToOrientation
/-- `OrthonormalBasis.adjustToOrientation`, applied to an orthonormal basis, preserves the
property of orthonormality. -/
theorem orthonormal_adjustToOrientation : Orthonormal ℝ (e.toBasis.adjustToOrientation x) := by
apply e.orthonormal.orthonormal_of_forall_eq_or_eq_neg
simpa using e.toBasis.adjustToOrientation_apply_eq_or_eq_neg x
#align orthonormal_basis.orthonormal_adjust_to_orientation OrthonormalBasis.orthonormal_adjustToOrientation
/-- Given an orthonormal basis and an orientation, return an orthonormal basis giving that
orientation: either the original basis, or one constructed by negating a single (arbitrary) basis
vector. -/
def adjustToOrientation : OrthonormalBasis ι ℝ E :=
(e.toBasis.adjustToOrientation x).toOrthonormalBasis (e.orthonormal_adjustToOrientation x)
#align orthonormal_basis.adjust_to_orientation OrthonormalBasis.adjustToOrientation
theorem toBasis_adjustToOrientation :
(e.adjustToOrientation x).toBasis = e.toBasis.adjustToOrientation x :=
(e.toBasis.adjustToOrientation x).toBasis_toOrthonormalBasis _
#align orthonormal_basis.to_basis_adjust_to_orientation OrthonormalBasis.toBasis_adjustToOrientation
/-- `adjustToOrientation` gives an orthonormal basis with the required orientation. -/
@[simp]
theorem orientation_adjustToOrientation : (e.adjustToOrientation x).toBasis.orientation = x := by
rw [e.toBasis_adjustToOrientation]
exact e.toBasis.orientation_adjustToOrientation x
#align orthonormal_basis.orientation_adjust_to_orientation OrthonormalBasis.orientation_adjustToOrientation
/-- Every basis vector from `adjustToOrientation` is either that from the original basis or its
negation. -/
theorem adjustToOrientation_apply_eq_or_eq_neg (i : ι) :
e.adjustToOrientation x i = e i ∨ e.adjustToOrientation x i = -e i := by
simpa [← e.toBasis_adjustToOrientation] using
e.toBasis.adjustToOrientation_apply_eq_or_eq_neg x i
#align orthonormal_basis.adjust_to_orientation_apply_eq_or_eq_neg OrthonormalBasis.adjustToOrientation_apply_eq_or_eq_neg
theorem det_adjustToOrientation :
(e.adjustToOrientation x).toBasis.det = e.toBasis.det ∨
(e.adjustToOrientation x).toBasis.det = -e.toBasis.det := by
simpa using e.toBasis.det_adjustToOrientation x
#align orthonormal_basis.det_adjust_to_orientation OrthonormalBasis.det_adjustToOrientation
theorem abs_det_adjustToOrientation (v : ι → E) :
|(e.adjustToOrientation x).toBasis.det v| = |e.toBasis.det v| := by
simp [toBasis_adjustToOrientation]
#align orthonormal_basis.abs_det_adjust_to_orientation OrthonormalBasis.abs_det_adjustToOrientation
end AdjustToOrientation
end OrthonormalBasis
namespace Orientation
variable {n : ℕ}
open OrthonormalBasis
/-- An orthonormal basis, indexed by `Fin n`, with the given orientation. -/
protected def finOrthonormalBasis (hn : 0 < n) (h : finrank ℝ E = n) (x : Orientation ℝ E (Fin n)) :
OrthonormalBasis (Fin n) ℝ E := by
haveI := Fin.pos_iff_nonempty.1 hn
haveI : FiniteDimensional ℝ E := .of_finrank_pos <| h.symm ▸ hn
exact ((@stdOrthonormalBasis _ _ _ _ _ this).reindex <| finCongr h).adjustToOrientation x
#align orientation.fin_orthonormal_basis Orientation.finOrthonormalBasis
/-- `Orientation.finOrthonormalBasis` gives a basis with the required orientation. -/
@[simp]
theorem finOrthonormalBasis_orientation (hn : 0 < n) (h : finrank ℝ E = n)
(x : Orientation ℝ E (Fin n)) : (x.finOrthonormalBasis hn h).toBasis.orientation = x := by
haveI := Fin.pos_iff_nonempty.1 hn
haveI : FiniteDimensional ℝ E := .of_finrank_pos <| h.symm ▸ hn
exact ((@stdOrthonormalBasis _ _ _ _ _ this).reindex <|
finCongr h).orientation_adjustToOrientation x
#align orientation.fin_orthonormal_basis_orientation Orientation.finOrthonormalBasis_orientation
section VolumeForm
variable [_i : Fact (finrank ℝ E = n)] (o : Orientation ℝ E (Fin n))
/-- The volume form on an oriented real inner product space, a nonvanishing top-dimensional
alternating form uniquely defined by compatibility with the orientation and inner product structure.
-/
irreducible_def volumeForm : E [⋀^Fin n]→ₗ[ℝ] ℝ := by
classical
cases' n with n
· let opos : E [⋀^Fin 0]→ₗ[ℝ] ℝ := .constOfIsEmpty ℝ E (Fin 0) (1 : ℝ)
exact o.eq_or_eq_neg_of_isEmpty.by_cases (fun _ => opos) fun _ => -opos
· exact (o.finOrthonormalBasis n.succ_pos _i.out).toBasis.det
#align orientation.volume_form Orientation.volumeForm
@[simp]
theorem volumeForm_zero_pos [_i : Fact (finrank ℝ E = 0)] :
Orientation.volumeForm (positiveOrientation : Orientation ℝ E (Fin 0)) =
AlternatingMap.constLinearEquivOfIsEmpty 1 := by
simp [volumeForm, Or.by_cases, if_pos]
#align orientation.volume_form_zero_pos Orientation.volumeForm_zero_pos
theorem volumeForm_zero_neg [_i : Fact (finrank ℝ E = 0)] :
Orientation.volumeForm (-positiveOrientation : Orientation ℝ E (Fin 0)) =
-AlternatingMap.constLinearEquivOfIsEmpty 1 := by
simp_rw [volumeForm, Or.by_cases, positiveOrientation]
apply if_neg
simp only [neg_rayOfNeZero]
rw [ray_eq_iff, SameRay.sameRay_comm]
intro h
simpa using
congr_arg AlternatingMap.constLinearEquivOfIsEmpty.symm (eq_zero_of_sameRay_self_neg h)
#align orientation.volume_form_zero_neg Orientation.volumeForm_zero_neg
/-- The volume form on an oriented real inner product space can be evaluated as the determinant with
respect to any orthonormal basis of the space compatible with the orientation. -/
theorem volumeForm_robust (b : OrthonormalBasis (Fin n) ℝ E) (hb : b.toBasis.orientation = o) :
o.volumeForm = b.toBasis.det := by
cases n
· classical
have : o = positiveOrientation := hb.symm.trans b.toBasis.orientation_isEmpty
simp_rw [volumeForm, Or.by_cases, dif_pos this, Nat.rec_zero, Basis.det_isEmpty]
· simp_rw [volumeForm]
rw [same_orientation_iff_det_eq_det, hb]
exact o.finOrthonormalBasis_orientation _ _
#align orientation.volume_form_robust Orientation.volumeForm_robust
/-- The volume form on an oriented real inner product space can be evaluated as the determinant with
respect to any orthonormal basis of the space compatible with the orientation. -/
theorem volumeForm_robust_neg (b : OrthonormalBasis (Fin n) ℝ E) (hb : b.toBasis.orientation ≠ o) :
o.volumeForm = -b.toBasis.det := by
cases' n with n
· classical
have : positiveOrientation ≠ o := by rwa [b.toBasis.orientation_isEmpty] at hb
simp_rw [volumeForm, Or.by_cases, dif_neg this.symm, Nat.rec_zero, Basis.det_isEmpty]
let e : OrthonormalBasis (Fin n.succ) ℝ E := o.finOrthonormalBasis n.succ_pos Fact.out
simp_rw [volumeForm]
apply e.det_eq_neg_det_of_opposite_orientation b
convert hb.symm
exact o.finOrthonormalBasis_orientation _ _
#align orientation.volume_form_robust_neg Orientation.volumeForm_robust_neg
@[simp]
| Mathlib/Analysis/InnerProductSpace/Orientation.lean | 237 | 248 | theorem volumeForm_neg_orientation : (-o).volumeForm = -o.volumeForm := by |
cases' n with n
· refine o.eq_or_eq_neg_of_isEmpty.elim ?_ ?_ <;> rintro rfl
· simp [volumeForm_zero_neg]
· rw [neg_neg (positiveOrientation (R := ℝ))] -- Porting note: added
simp [volumeForm_zero_neg]
let e : OrthonormalBasis (Fin n.succ) ℝ E := o.finOrthonormalBasis n.succ_pos Fact.out
have h₁ : e.toBasis.orientation = o := o.finOrthonormalBasis_orientation _ _
have h₂ : e.toBasis.orientation ≠ -o := by
symm
rw [e.toBasis.orientation_ne_iff_eq_neg, h₁]
rw [o.volumeForm_robust e h₁, (-o).volumeForm_robust_neg e h₂]
|
/-
Copyright (c) 2021 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou, Adam Topaz, Johan Commelin
-/
import Mathlib.Algebra.Homology.Additive
import Mathlib.AlgebraicTopology.MooreComplex
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.CategoryTheory.Preadditive.Opposite
import Mathlib.CategoryTheory.Idempotents.FunctorCategories
#align_import algebraic_topology.alternating_face_map_complex from "leanprover-community/mathlib"@"88bca0ce5d22ebfd9e73e682e51d60ea13b48347"
/-!
# The alternating face map complex of a simplicial object in a preadditive category
We construct the alternating face map complex, as a
functor `alternatingFaceMapComplex : SimplicialObject C ⥤ ChainComplex C ℕ`
for any preadditive category `C`. For any simplicial object `X` in `C`,
this is the homological complex `... → X_2 → X_1 → X_0`
where the differentials are alternating sums of faces.
The dual version `alternatingCofaceMapComplex : CosimplicialObject C ⥤ CochainComplex C ℕ`
is also constructed.
We also construct the natural transformation
`inclusionOfMooreComplex : normalizedMooreComplex A ⟶ alternatingFaceMapComplex A`
when `A` is an abelian category.
## References
* https://stacks.math.columbia.edu/tag/0194
* https://ncatlab.org/nlab/show/Moore+complex
-/
open CategoryTheory CategoryTheory.Limits CategoryTheory.Subobject
open CategoryTheory.Preadditive CategoryTheory.Category CategoryTheory.Idempotents
open Opposite
open Simplicial
noncomputable section
namespace AlgebraicTopology
namespace AlternatingFaceMapComplex
/-!
## Construction of the alternating face map complex
-/
variable {C : Type*} [Category C] [Preadditive C]
variable (X : SimplicialObject C)
variable (Y : SimplicialObject C)
/-- The differential on the alternating face map complex is the alternate
sum of the face maps -/
@[simp]
def objD (n : ℕ) : X _[n + 1] ⟶ X _[n] :=
∑ i : Fin (n + 2), (-1 : ℤ) ^ (i : ℕ) • X.δ i
#align algebraic_topology.alternating_face_map_complex.obj_d AlgebraicTopology.AlternatingFaceMapComplex.objD
/-- ## The chain complex relation `d ≫ d`
-/
theorem d_squared (n : ℕ) : objD X (n + 1) ≫ objD X n = 0 := by
-- we start by expanding d ≫ d as a double sum
dsimp
simp only [comp_sum, sum_comp, ← Finset.sum_product']
-- then, we decompose the index set P into a subset S and its complement Sᶜ
let P := Fin (n + 2) × Fin (n + 3)
let S := Finset.univ.filter fun ij : P => (ij.2 : ℕ) ≤ (ij.1 : ℕ)
erw [← Finset.sum_add_sum_compl S, ← eq_neg_iff_add_eq_zero, ← Finset.sum_neg_distrib]
/- we are reduced to showing that two sums are equal, and this is obtained
by constructing a bijection φ : S -> Sᶜ, which maps (i,j) to (j,i+1),
and by comparing the terms -/
let φ : ∀ ij : P, ij ∈ S → P := fun ij hij =>
(Fin.castLT ij.2 (lt_of_le_of_lt (Finset.mem_filter.mp hij).right (Fin.is_lt ij.1)), ij.1.succ)
apply Finset.sum_bij φ
· -- φ(S) is contained in Sᶜ
intro ij hij
simp only [S, Finset.mem_univ, Finset.compl_filter, Finset.mem_filter, true_and_iff,
Fin.val_succ, Fin.coe_castLT] at hij ⊢
linarith
· -- φ : S → Sᶜ is injective
rintro ⟨i, j⟩ hij ⟨i', j'⟩ hij' h
rw [Prod.mk.inj_iff]
exact ⟨by simpa using congr_arg Prod.snd h,
by simpa [Fin.castSucc_castLT] using congr_arg Fin.castSucc (congr_arg Prod.fst h)⟩
· -- φ : S → Sᶜ is surjective
rintro ⟨i', j'⟩ hij'
simp only [S, Finset.mem_univ, forall_true_left, Prod.forall, ge_iff_le, Finset.compl_filter,
not_le, Finset.mem_filter, true_and] at hij'
refine ⟨(j'.pred <| ?_, Fin.castSucc i'), ?_, ?_⟩
· rintro rfl
simp only [Fin.val_zero, not_lt_zero'] at hij'
· simpa only [S, Finset.mem_univ, forall_true_left, Prod.forall, ge_iff_le, Finset.mem_filter,
Fin.coe_castSucc, Fin.coe_pred, true_and] using Nat.le_sub_one_of_lt hij'
· simp only [φ, Fin.castLT_castSucc, Fin.succ_pred]
· -- identification of corresponding terms in both sums
rintro ⟨i, j⟩ hij
dsimp
simp only [zsmul_comp, comp_zsmul, smul_smul, ← neg_smul]
congr 1
· simp only [Fin.val_succ, pow_add, pow_one, mul_neg, neg_neg, mul_one]
apply mul_comm
· rw [CategoryTheory.SimplicialObject.δ_comp_δ'']
simpa [S] using hij
#align algebraic_topology.alternating_face_map_complex.d_squared AlgebraicTopology.AlternatingFaceMapComplex.d_squared
/-!
## Construction of the alternating face map complex functor
-/
/-- The alternating face map complex, on objects -/
def obj : ChainComplex C ℕ :=
ChainComplex.of (fun n => X _[n]) (objD X) (d_squared X)
#align algebraic_topology.alternating_face_map_complex.obj AlgebraicTopology.AlternatingFaceMapComplex.obj
@[simp]
theorem obj_X (X : SimplicialObject C) (n : ℕ) : (AlternatingFaceMapComplex.obj X).X n = X _[n] :=
rfl
set_option linter.uppercaseLean3 false in
#align algebraic_topology.alternating_face_map_complex.obj_X AlgebraicTopology.AlternatingFaceMapComplex.obj_X
@[simp]
theorem obj_d_eq (X : SimplicialObject C) (n : ℕ) :
(AlternatingFaceMapComplex.obj X).d (n + 1) n
= ∑ i : Fin (n + 2), (-1 : ℤ) ^ (i : ℕ) • X.δ i := by
apply ChainComplex.of_d
#align algebraic_topology.alternating_face_map_complex.obj_d_eq AlgebraicTopology.AlternatingFaceMapComplex.obj_d_eq
variable {X} {Y}
/-- The alternating face map complex, on morphisms -/
def map (f : X ⟶ Y) : obj X ⟶ obj Y :=
ChainComplex.ofHom _ _ _ _ _ _ (fun n => f.app (op [n])) fun n => by
dsimp
rw [comp_sum, sum_comp]
refine Finset.sum_congr rfl fun _ _ => ?_
rw [comp_zsmul, zsmul_comp]
congr 1
symm
apply f.naturality
#align algebraic_topology.alternating_face_map_complex.map AlgebraicTopology.AlternatingFaceMapComplex.map
@[simp]
theorem map_f (f : X ⟶ Y) (n : ℕ) : (map f).f n = f.app (op [n]) :=
rfl
#align algebraic_topology.alternating_face_map_complex.map_f AlgebraicTopology.AlternatingFaceMapComplex.map_f
end AlternatingFaceMapComplex
variable (C : Type*) [Category C] [Preadditive C]
/-- The alternating face map complex, as a functor -/
def alternatingFaceMapComplex : SimplicialObject C ⥤ ChainComplex C ℕ where
obj := AlternatingFaceMapComplex.obj
map f := AlternatingFaceMapComplex.map f
#align algebraic_topology.alternating_face_map_complex AlgebraicTopology.alternatingFaceMapComplex
variable {C}
@[simp]
theorem alternatingFaceMapComplex_obj_X (X : SimplicialObject C) (n : ℕ) :
((alternatingFaceMapComplex C).obj X).X n = X _[n] :=
rfl
set_option linter.uppercaseLean3 false in
#align algebraic_topology.alternating_face_map_complex_obj_X AlgebraicTopology.alternatingFaceMapComplex_obj_X
@[simp]
theorem alternatingFaceMapComplex_obj_d (X : SimplicialObject C) (n : ℕ) :
((alternatingFaceMapComplex C).obj X).d (n + 1) n = AlternatingFaceMapComplex.objD X n := by
dsimp only [alternatingFaceMapComplex, AlternatingFaceMapComplex.obj]
apply ChainComplex.of_d
#align algebraic_topology.alternating_face_map_complex_obj_d AlgebraicTopology.alternatingFaceMapComplex_obj_d
@[simp]
theorem alternatingFaceMapComplex_map_f {X Y : SimplicialObject C} (f : X ⟶ Y) (n : ℕ) :
((alternatingFaceMapComplex C).map f).f n = f.app (op [n]) :=
rfl
#align algebraic_topology.alternating_face_map_complex_map_f AlgebraicTopology.alternatingFaceMapComplex_map_f
theorem map_alternatingFaceMapComplex {D : Type*} [Category D] [Preadditive D] (F : C ⥤ D)
[F.Additive] :
alternatingFaceMapComplex C ⋙ F.mapHomologicalComplex _ =
(SimplicialObject.whiskering C D).obj F ⋙ alternatingFaceMapComplex D := by
apply CategoryTheory.Functor.ext
· intro X Y f
ext n
simp only [Functor.comp_map, HomologicalComplex.comp_f, alternatingFaceMapComplex_map_f,
Functor.mapHomologicalComplex_map_f, HomologicalComplex.eqToHom_f, eqToHom_refl, comp_id,
id_comp, SimplicialObject.whiskering_obj_map_app]
· intro X
apply HomologicalComplex.ext
· rintro i j (rfl : j + 1 = i)
dsimp only [Functor.comp_obj]
simp only [Functor.mapHomologicalComplex_obj_d, alternatingFaceMapComplex_obj_d,
eqToHom_refl, id_comp, comp_id, AlternatingFaceMapComplex.objD, Functor.map_sum,
Functor.map_zsmul]
rfl
· ext n
rfl
#align algebraic_topology.map_alternating_face_map_complex AlgebraicTopology.map_alternatingFaceMapComplex
theorem karoubi_alternatingFaceMapComplex_d (P : Karoubi (SimplicialObject C)) (n : ℕ) :
((AlternatingFaceMapComplex.obj (KaroubiFunctorCategoryEmbedding.obj P)).d (n + 1) n).f =
P.p.app (op [n + 1]) ≫ (AlternatingFaceMapComplex.obj P.X).d (n + 1) n := by
dsimp
simp only [AlternatingFaceMapComplex.obj_d_eq, Karoubi.sum_hom, Preadditive.comp_sum,
Karoubi.zsmul_hom, Preadditive.comp_zsmul]
rfl
#align algebraic_topology.karoubi_alternating_face_map_complex_d AlgebraicTopology.karoubi_alternatingFaceMapComplex_d
namespace AlternatingFaceMapComplex
/-- The natural transformation which gives the augmentation of the alternating face map
complex attached to an augmented simplicial object. -/
def ε [Limits.HasZeroObject C] :
SimplicialObject.Augmented.drop ⋙ AlgebraicTopology.alternatingFaceMapComplex C ⟶
SimplicialObject.Augmented.point ⋙ ChainComplex.single₀ C where
app X := by
refine (ChainComplex.toSingle₀Equiv _ _).symm ?_
refine ⟨X.hom.app (op [0]), ?_⟩
dsimp
rw [alternatingFaceMapComplex_obj_d, objD, Fin.sum_univ_two, Fin.val_zero,
pow_zero, one_smul, Fin.val_one, pow_one, neg_smul, one_smul, add_comp,
neg_comp, SimplicialObject.δ_naturality, SimplicialObject.δ_naturality]
apply add_right_neg
naturality X Y f := by
apply HomologicalComplex.to_single_hom_ext
dsimp
erw [ChainComplex.toSingle₀Equiv_symm_apply_f_zero,
ChainComplex.toSingle₀Equiv_symm_apply_f_zero]
simp only [ChainComplex.single₀_map_f_zero]
exact congr_app f.w _
#align algebraic_topology.alternating_face_map_complex.ε AlgebraicTopology.AlternatingFaceMapComplex.ε
@[simp]
lemma ε_app_f_zero [Limits.HasZeroObject C] (X : SimplicialObject.Augmented C) :
(ε.app X).f 0 = X.hom.app (op [0]) :=
ChainComplex.toSingle₀Equiv_symm_apply_f_zero _ _
@[simp]
lemma ε_app_f_succ [Limits.HasZeroObject C] (X : SimplicialObject.Augmented C) (n : ℕ) :
(ε.app X).f (n + 1) = 0 := rfl
end AlternatingFaceMapComplex
/-!
## Construction of the natural inclusion of the normalized Moore complex
-/
variable {A : Type*} [Category A] [Abelian A]
/-- The inclusion map of the Moore complex in the alternating face map complex -/
def inclusionOfMooreComplexMap (X : SimplicialObject A) :
(normalizedMooreComplex A).obj X ⟶ (alternatingFaceMapComplex A).obj X := by
dsimp only [normalizedMooreComplex, NormalizedMooreComplex.obj,
alternatingFaceMapComplex, AlternatingFaceMapComplex.obj]
apply ChainComplex.ofHom _ _ _ _ _ _ (fun n => (NormalizedMooreComplex.objX X n).arrow)
/- we have to show the compatibility of the differentials on the alternating
face map complex with those defined on the normalized Moore complex:
we first get rid of the terms of the alternating sum that are obviously
zero on the normalized_Moore_complex -/
intro i
simp only [AlternatingFaceMapComplex.objD, comp_sum]
rw [Fin.sum_univ_succ, Fintype.sum_eq_zero]
swap
· intro j
rw [NormalizedMooreComplex.objX, comp_zsmul,
← factorThru_arrow _ _ (finset_inf_arrow_factors Finset.univ _ _ (Finset.mem_univ j)),
Category.assoc, kernelSubobject_arrow_comp, comp_zero, smul_zero]
-- finally, we study the remaining term which is induced by X.δ 0
rw [add_zero, Fin.val_zero, pow_zero, one_zsmul]
dsimp [NormalizedMooreComplex.objD, NormalizedMooreComplex.objX]
cases i <;> simp
set_option linter.uppercaseLean3 false in
#align algebraic_topology.inclusion_of_Moore_complex_map AlgebraicTopology.inclusionOfMooreComplexMap
@[simp]
theorem inclusionOfMooreComplexMap_f (X : SimplicialObject A) (n : ℕ) :
(inclusionOfMooreComplexMap X).f n = (NormalizedMooreComplex.objX X n).arrow := by
dsimp only [inclusionOfMooreComplexMap]
exact ChainComplex.ofHom_f _ _ _ _ _ _ _ _ n
set_option linter.uppercaseLean3 false in
#align algebraic_topology.inclusion_of_Moore_complex_map_f AlgebraicTopology.inclusionOfMooreComplexMap_f
variable (A)
/-- The inclusion map of the Moore complex in the alternating face map complex,
as a natural transformation -/
@[simps]
def inclusionOfMooreComplex : normalizedMooreComplex A ⟶ alternatingFaceMapComplex A where
app := inclusionOfMooreComplexMap
set_option linter.uppercaseLean3 false in
#align algebraic_topology.inclusion_of_Moore_complex AlgebraicTopology.inclusionOfMooreComplex
namespace AlternatingCofaceMapComplex
variable (X Y : CosimplicialObject C)
/-- The differential on the alternating coface map complex is the alternate
sum of the coface maps -/
@[simp]
def objD (n : ℕ) : X.obj [n] ⟶ X.obj [n + 1] :=
∑ i : Fin (n + 2), (-1 : ℤ) ^ (i : ℕ) • X.δ i
#align algebraic_topology.alternating_coface_map_complex.obj_d AlgebraicTopology.AlternatingCofaceMapComplex.objD
| Mathlib/AlgebraicTopology/AlternatingFaceMapComplex.lean | 315 | 320 | theorem d_eq_unop_d (n : ℕ) :
objD X n =
(AlternatingFaceMapComplex.objD ((cosimplicialSimplicialEquiv C).functor.obj (op X))
n).unop := by |
simp only [objD, AlternatingFaceMapComplex.objD, unop_sum, unop_zsmul]
rfl
|
/-
Copyright (c) 2022 Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn
-/
import Mathlib.MeasureTheory.Integral.IntegrableOn
#align_import measure_theory.function.locally_integrable from "leanprover-community/mathlib"@"08a4542bec7242a5c60f179e4e49de8c0d677b1b"
/-!
# Locally integrable functions
A function is called *locally integrable* (`MeasureTheory.LocallyIntegrable`) if it is integrable
on a neighborhood of every point. More generally, it is *locally integrable on `s`* if it is
locally integrable on a neighbourhood within `s` of any point of `s`.
This file contains properties of locally integrable functions, and integrability results
on compact sets.
## Main statements
* `Continuous.locallyIntegrable`: A continuous function is locally integrable.
* `ContinuousOn.locallyIntegrableOn`: A function which is continuous on `s` is locally
integrable on `s`.
-/
open MeasureTheory MeasureTheory.Measure Set Function TopologicalSpace Bornology
open scoped Topology Interval ENNReal
variable {X Y E F R : Type*} [MeasurableSpace X] [TopologicalSpace X]
variable [MeasurableSpace Y] [TopologicalSpace Y]
variable [NormedAddCommGroup E] [NormedAddCommGroup F] {f g : X → E} {μ : Measure X} {s : Set X}
namespace MeasureTheory
section LocallyIntegrableOn
/-- A function `f : X → E` is *locally integrable on s*, for `s ⊆ X`, if for every `x ∈ s` there is
a neighbourhood of `x` within `s` on which `f` is integrable. (Note this is, in general, strictly
weaker than local integrability with respect to `μ.restrict s`.) -/
def LocallyIntegrableOn (f : X → E) (s : Set X) (μ : Measure X := by volume_tac) : Prop :=
∀ x : X, x ∈ s → IntegrableAtFilter f (𝓝[s] x) μ
#align measure_theory.locally_integrable_on MeasureTheory.LocallyIntegrableOn
theorem LocallyIntegrableOn.mono_set (hf : LocallyIntegrableOn f s μ) {t : Set X}
(hst : t ⊆ s) : LocallyIntegrableOn f t μ := fun x hx =>
(hf x <| hst hx).filter_mono (nhdsWithin_mono x hst)
#align measure_theory.locally_integrable_on.mono MeasureTheory.LocallyIntegrableOn.mono_set
theorem LocallyIntegrableOn.norm (hf : LocallyIntegrableOn f s μ) :
LocallyIntegrableOn (fun x => ‖f x‖) s μ := fun t ht =>
let ⟨U, hU_nhd, hU_int⟩ := hf t ht
⟨U, hU_nhd, hU_int.norm⟩
#align measure_theory.locally_integrable_on.norm MeasureTheory.LocallyIntegrableOn.norm
theorem LocallyIntegrableOn.mono (hf : LocallyIntegrableOn f s μ) {g : X → F}
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ x ∂μ, ‖g x‖ ≤ ‖f x‖) :
LocallyIntegrableOn g s μ := by
intro x hx
rcases hf x hx with ⟨t, t_mem, ht⟩
exact ⟨t, t_mem, Integrable.mono ht hg.restrict (ae_restrict_of_ae h)⟩
theorem IntegrableOn.locallyIntegrableOn (hf : IntegrableOn f s μ) : LocallyIntegrableOn f s μ :=
fun _ _ => ⟨s, self_mem_nhdsWithin, hf⟩
#align measure_theory.integrable_on.locally_integrable_on MeasureTheory.IntegrableOn.locallyIntegrableOn
/-- If a function is locally integrable on a compact set, then it is integrable on that set. -/
theorem LocallyIntegrableOn.integrableOn_isCompact (hf : LocallyIntegrableOn f s μ)
(hs : IsCompact s) : IntegrableOn f s μ :=
IsCompact.induction_on hs integrableOn_empty (fun _u _v huv hv => hv.mono_set huv)
(fun _u _v hu hv => integrableOn_union.mpr ⟨hu, hv⟩) hf
#align measure_theory.locally_integrable_on.integrable_on_is_compact MeasureTheory.LocallyIntegrableOn.integrableOn_isCompact
theorem LocallyIntegrableOn.integrableOn_compact_subset (hf : LocallyIntegrableOn f s μ) {t : Set X}
(hst : t ⊆ s) (ht : IsCompact t) : IntegrableOn f t μ :=
(hf.mono_set hst).integrableOn_isCompact ht
#align measure_theory.locally_integrable_on.integrable_on_compact_subset MeasureTheory.LocallyIntegrableOn.integrableOn_compact_subset
/-- If a function `f` is locally integrable on a set `s` in a second countable topological space,
then there exist countably many open sets `u` covering `s` such that `f` is integrable on each
set `u ∩ s`. -/
theorem LocallyIntegrableOn.exists_countable_integrableOn [SecondCountableTopology X]
(hf : LocallyIntegrableOn f s μ) : ∃ T : Set (Set X), T.Countable ∧
(∀ u ∈ T, IsOpen u) ∧ (s ⊆ ⋃ u ∈ T, u) ∧ (∀ u ∈ T, IntegrableOn f (u ∩ s) μ) := by
have : ∀ x : s, ∃ u, IsOpen u ∧ x.1 ∈ u ∧ IntegrableOn f (u ∩ s) μ := by
rintro ⟨x, hx⟩
rcases hf x hx with ⟨t, ht, h't⟩
rcases mem_nhdsWithin.1 ht with ⟨u, u_open, x_mem, u_sub⟩
exact ⟨u, u_open, x_mem, h't.mono_set u_sub⟩
choose u u_open xu hu using this
obtain ⟨T, T_count, hT⟩ : ∃ T : Set s, T.Countable ∧ s ⊆ ⋃ i ∈ T, u i := by
have : s ⊆ ⋃ x : s, u x := fun y hy => mem_iUnion_of_mem ⟨y, hy⟩ (xu ⟨y, hy⟩)
obtain ⟨T, hT_count, hT_un⟩ := isOpen_iUnion_countable u u_open
exact ⟨T, hT_count, by rwa [hT_un]⟩
refine ⟨u '' T, T_count.image _, ?_, by rwa [biUnion_image], ?_⟩
· rintro v ⟨w, -, rfl⟩
exact u_open _
· rintro v ⟨w, -, rfl⟩
exact hu _
/-- If a function `f` is locally integrable on a set `s` in a second countable topological space,
then there exists a sequence of open sets `u n` covering `s` such that `f` is integrable on each
set `u n ∩ s`. -/
theorem LocallyIntegrableOn.exists_nat_integrableOn [SecondCountableTopology X]
(hf : LocallyIntegrableOn f s μ) : ∃ u : ℕ → Set X,
(∀ n, IsOpen (u n)) ∧ (s ⊆ ⋃ n, u n) ∧ (∀ n, IntegrableOn f (u n ∩ s) μ) := by
rcases hf.exists_countable_integrableOn with ⟨T, T_count, T_open, sT, hT⟩
let T' : Set (Set X) := insert ∅ T
have T'_count : T'.Countable := Countable.insert ∅ T_count
have T'_ne : T'.Nonempty := by simp only [T', insert_nonempty]
rcases T'_count.exists_eq_range T'_ne with ⟨u, hu⟩
refine ⟨u, ?_, ?_, ?_⟩
· intro n
have : u n ∈ T' := by rw [hu]; exact mem_range_self n
rcases mem_insert_iff.1 this with h|h
· rw [h]
exact isOpen_empty
· exact T_open _ h
· intro x hx
obtain ⟨v, hv, h'v⟩ : ∃ v, v ∈ T ∧ x ∈ v := by simpa only [mem_iUnion, exists_prop] using sT hx
have : v ∈ range u := by rw [← hu]; exact subset_insert ∅ T hv
obtain ⟨n, rfl⟩ : ∃ n, u n = v := by simpa only [mem_range] using this
exact mem_iUnion_of_mem _ h'v
· intro n
have : u n ∈ T' := by rw [hu]; exact mem_range_self n
rcases mem_insert_iff.1 this with h|h
· simp only [h, empty_inter, integrableOn_empty]
· exact hT _ h
theorem LocallyIntegrableOn.aestronglyMeasurable [SecondCountableTopology X]
(hf : LocallyIntegrableOn f s μ) : AEStronglyMeasurable f (μ.restrict s) := by
rcases hf.exists_nat_integrableOn with ⟨u, -, su, hu⟩
have : s = ⋃ n, u n ∩ s := by rw [← iUnion_inter]; exact (inter_eq_right.mpr su).symm
rw [this, aestronglyMeasurable_iUnion_iff]
exact fun i : ℕ => (hu i).aestronglyMeasurable
#align measure_theory.locally_integrable_on.ae_strongly_measurable MeasureTheory.LocallyIntegrableOn.aestronglyMeasurable
/-- If `s` is either open, or closed, then `f` is locally integrable on `s` iff it is integrable on
every compact subset contained in `s`. -/
theorem locallyIntegrableOn_iff [LocallyCompactSpace X] [T2Space X] (hs : IsClosed s ∨ IsOpen s) :
LocallyIntegrableOn f s μ ↔ ∀ (k : Set X), k ⊆ s → (IsCompact k → IntegrableOn f k μ) := by
-- The correct condition is that `s` be *locally closed*, i.e. for every `x ∈ s` there is some
-- `U ∈ 𝓝 x` such that `U ∩ s` is closed. But mathlib doesn't have locally closed sets yet.
refine ⟨fun hf k hk => hf.integrableOn_compact_subset hk, fun hf x hx => ?_⟩
cases hs with
| inl hs =>
exact
let ⟨K, hK, h2K⟩ := exists_compact_mem_nhds x
⟨_, inter_mem_nhdsWithin s h2K,
hf _ inter_subset_left
(hK.of_isClosed_subset (hs.inter hK.isClosed) inter_subset_right)⟩
| inr hs =>
obtain ⟨K, hK, h2K, h3K⟩ := exists_compact_subset hs hx
refine ⟨K, ?_, hf K h3K hK⟩
simpa only [IsOpen.nhdsWithin_eq hs hx, interior_eq_nhds'] using h2K
#align measure_theory.locally_integrable_on_iff MeasureTheory.locallyIntegrableOn_iff
protected theorem LocallyIntegrableOn.add
(hf : LocallyIntegrableOn f s μ) (hg : LocallyIntegrableOn g s μ) :
LocallyIntegrableOn (f + g) s μ := fun x hx ↦ (hf x hx).add (hg x hx)
protected theorem LocallyIntegrableOn.sub
(hf : LocallyIntegrableOn f s μ) (hg : LocallyIntegrableOn g s μ) :
LocallyIntegrableOn (f - g) s μ := fun x hx ↦ (hf x hx).sub (hg x hx)
protected theorem LocallyIntegrableOn.neg (hf : LocallyIntegrableOn f s μ) :
LocallyIntegrableOn (-f) s μ := fun x hx ↦ (hf x hx).neg
end LocallyIntegrableOn
/-- A function `f : X → E` is *locally integrable* if it is integrable on a neighborhood of every
point. In particular, it is integrable on all compact sets,
see `LocallyIntegrable.integrableOn_isCompact`. -/
def LocallyIntegrable (f : X → E) (μ : Measure X := by volume_tac) : Prop :=
∀ x : X, IntegrableAtFilter f (𝓝 x) μ
#align measure_theory.locally_integrable MeasureTheory.LocallyIntegrable
theorem locallyIntegrable_comap (hs : MeasurableSet s) :
LocallyIntegrable (fun x : s ↦ f x) (μ.comap Subtype.val) ↔ LocallyIntegrableOn f s μ := by
simp_rw [LocallyIntegrableOn, Subtype.forall', ← map_nhds_subtype_val]
exact forall_congr' fun _ ↦ (MeasurableEmbedding.subtype_coe hs).integrableAtFilter_iff_comap.symm
theorem locallyIntegrableOn_univ : LocallyIntegrableOn f univ μ ↔ LocallyIntegrable f μ := by
simp only [LocallyIntegrableOn, nhdsWithin_univ, mem_univ, true_imp_iff]; rfl
#align measure_theory.locally_integrable_on_univ MeasureTheory.locallyIntegrableOn_univ
theorem LocallyIntegrable.locallyIntegrableOn (hf : LocallyIntegrable f μ) (s : Set X) :
LocallyIntegrableOn f s μ := fun x _ => (hf x).filter_mono nhdsWithin_le_nhds
#align measure_theory.locally_integrable.locally_integrable_on MeasureTheory.LocallyIntegrable.locallyIntegrableOn
theorem Integrable.locallyIntegrable (hf : Integrable f μ) : LocallyIntegrable f μ := fun _ =>
hf.integrableAtFilter _
#align measure_theory.integrable.locally_integrable MeasureTheory.Integrable.locallyIntegrable
theorem LocallyIntegrable.mono (hf : LocallyIntegrable f μ) {g : X → F}
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ x ∂μ, ‖g x‖ ≤ ‖f x‖) :
LocallyIntegrable g μ := by
rw [← locallyIntegrableOn_univ] at hf ⊢
exact hf.mono hg h
/-- If `f` is locally integrable with respect to `μ.restrict s`, it is locally integrable on `s`.
(See `locallyIntegrableOn_iff_locallyIntegrable_restrict` for an iff statement when `s` is
closed.) -/
theorem locallyIntegrableOn_of_locallyIntegrable_restrict [OpensMeasurableSpace X]
(hf : LocallyIntegrable f (μ.restrict s)) : LocallyIntegrableOn f s μ := by
intro x _
obtain ⟨t, ht_mem, ht_int⟩ := hf x
obtain ⟨u, hu_sub, hu_o, hu_mem⟩ := mem_nhds_iff.mp ht_mem
refine ⟨_, inter_mem_nhdsWithin s (hu_o.mem_nhds hu_mem), ?_⟩
simpa only [IntegrableOn, Measure.restrict_restrict hu_o.measurableSet, inter_comm] using
ht_int.mono_set hu_sub
#align measure_theory.locally_integrable_on_of_locally_integrable_restrict MeasureTheory.locallyIntegrableOn_of_locallyIntegrable_restrict
/-- If `s` is closed, being locally integrable on `s` wrt `μ` is equivalent to being locally
integrable with respect to `μ.restrict s`. For the one-way implication without assuming `s` closed,
see `locallyIntegrableOn_of_locallyIntegrable_restrict`. -/
theorem locallyIntegrableOn_iff_locallyIntegrable_restrict [OpensMeasurableSpace X]
(hs : IsClosed s) : LocallyIntegrableOn f s μ ↔ LocallyIntegrable f (μ.restrict s) := by
refine ⟨fun hf x => ?_, locallyIntegrableOn_of_locallyIntegrable_restrict⟩
by_cases h : x ∈ s
· obtain ⟨t, ht_nhds, ht_int⟩ := hf x h
obtain ⟨u, hu_o, hu_x, hu_sub⟩ := mem_nhdsWithin.mp ht_nhds
refine ⟨u, hu_o.mem_nhds hu_x, ?_⟩
rw [IntegrableOn, restrict_restrict hu_o.measurableSet]
exact ht_int.mono_set hu_sub
· rw [← isOpen_compl_iff] at hs
refine ⟨sᶜ, hs.mem_nhds h, ?_⟩
rw [IntegrableOn, restrict_restrict, inter_comm, inter_compl_self, ← IntegrableOn]
exacts [integrableOn_empty, hs.measurableSet]
#align measure_theory.locally_integrable_on_iff_locally_integrable_restrict MeasureTheory.locallyIntegrableOn_iff_locallyIntegrable_restrict
/-- If a function is locally integrable, then it is integrable on any compact set. -/
theorem LocallyIntegrable.integrableOn_isCompact {k : Set X} (hf : LocallyIntegrable f μ)
(hk : IsCompact k) : IntegrableOn f k μ :=
(hf.locallyIntegrableOn k).integrableOn_isCompact hk
#align measure_theory.locally_integrable.integrable_on_is_compact MeasureTheory.LocallyIntegrable.integrableOn_isCompact
/-- If a function is locally integrable, then it is integrable on an open neighborhood of any
compact set. -/
theorem LocallyIntegrable.integrableOn_nhds_isCompact (hf : LocallyIntegrable f μ) {k : Set X}
(hk : IsCompact k) : ∃ u, IsOpen u ∧ k ⊆ u ∧ IntegrableOn f u μ := by
refine IsCompact.induction_on hk ?_ ?_ ?_ ?_
· refine ⟨∅, isOpen_empty, Subset.rfl, integrableOn_empty⟩
· rintro s t hst ⟨u, u_open, tu, hu⟩
exact ⟨u, u_open, hst.trans tu, hu⟩
· rintro s t ⟨u, u_open, su, hu⟩ ⟨v, v_open, tv, hv⟩
exact ⟨u ∪ v, u_open.union v_open, union_subset_union su tv, hu.union hv⟩
· intro x _
rcases hf x with ⟨u, ux, hu⟩
rcases mem_nhds_iff.1 ux with ⟨v, vu, v_open, xv⟩
exact ⟨v, nhdsWithin_le_nhds (v_open.mem_nhds xv), v, v_open, Subset.rfl, hu.mono_set vu⟩
#align measure_theory.locally_integrable.integrable_on_nhds_is_compact MeasureTheory.LocallyIntegrable.integrableOn_nhds_isCompact
theorem locallyIntegrable_iff [LocallyCompactSpace X] :
LocallyIntegrable f μ ↔ ∀ k : Set X, IsCompact k → IntegrableOn f k μ :=
⟨fun hf _k hk => hf.integrableOn_isCompact hk, fun hf x =>
let ⟨K, hK, h2K⟩ := exists_compact_mem_nhds x
⟨K, h2K, hf K hK⟩⟩
#align measure_theory.locally_integrable_iff MeasureTheory.locallyIntegrable_iff
theorem LocallyIntegrable.aestronglyMeasurable [SecondCountableTopology X]
(hf : LocallyIntegrable f μ) : AEStronglyMeasurable f μ := by
simpa only [restrict_univ] using (locallyIntegrableOn_univ.mpr hf).aestronglyMeasurable
#align measure_theory.locally_integrable.ae_strongly_measurable MeasureTheory.LocallyIntegrable.aestronglyMeasurable
/-- If a function is locally integrable in a second countable topological space,
then there exists a sequence of open sets covering the space on which it is integrable. -/
theorem LocallyIntegrable.exists_nat_integrableOn [SecondCountableTopology X]
(hf : LocallyIntegrable f μ) : ∃ u : ℕ → Set X,
(∀ n, IsOpen (u n)) ∧ ((⋃ n, u n) = univ) ∧ (∀ n, IntegrableOn f (u n) μ) := by
rcases (hf.locallyIntegrableOn univ).exists_nat_integrableOn with ⟨u, u_open, u_union, hu⟩
refine ⟨u, u_open, eq_univ_of_univ_subset u_union, fun n ↦ ?_⟩
simpa only [inter_univ] using hu n
theorem Memℒp.locallyIntegrable [IsLocallyFiniteMeasure μ] {f : X → E} {p : ℝ≥0∞}
(hf : Memℒp f p μ) (hp : 1 ≤ p) : LocallyIntegrable f μ := by
intro x
rcases μ.finiteAt_nhds x with ⟨U, hU, h'U⟩
have : Fact (μ U < ⊤) := ⟨h'U⟩
refine ⟨U, hU, ?_⟩
rw [IntegrableOn, ← memℒp_one_iff_integrable]
apply (hf.restrict U).memℒp_of_exponent_le hp
theorem locallyIntegrable_const [IsLocallyFiniteMeasure μ] (c : E) :
LocallyIntegrable (fun _ => c) μ :=
(memℒp_top_const c).locallyIntegrable le_top
#align measure_theory.locally_integrable_const MeasureTheory.locallyIntegrable_const
theorem locallyIntegrableOn_const [IsLocallyFiniteMeasure μ] (c : E) :
LocallyIntegrableOn (fun _ => c) s μ :=
(locallyIntegrable_const c).locallyIntegrableOn s
#align measure_theory.locally_integrable_on_const MeasureTheory.locallyIntegrableOn_const
theorem locallyIntegrable_zero : LocallyIntegrable (fun _ ↦ (0 : E)) μ :=
(integrable_zero X E μ).locallyIntegrable
theorem locallyIntegrableOn_zero : LocallyIntegrableOn (fun _ ↦ (0 : E)) s μ :=
locallyIntegrable_zero.locallyIntegrableOn s
theorem LocallyIntegrable.indicator (hf : LocallyIntegrable f μ) {s : Set X}
(hs : MeasurableSet s) : LocallyIntegrable (s.indicator f) μ := by
intro x
rcases hf x with ⟨U, hU, h'U⟩
exact ⟨U, hU, h'U.indicator hs⟩
#align measure_theory.locally_integrable.indicator MeasureTheory.LocallyIntegrable.indicator
theorem locallyIntegrable_map_homeomorph [BorelSpace X] [BorelSpace Y] (e : X ≃ₜ Y) {f : Y → E}
{μ : Measure X} : LocallyIntegrable f (Measure.map e μ) ↔ LocallyIntegrable (f ∘ e) μ := by
refine ⟨fun h x => ?_, fun h x => ?_⟩
· rcases h (e x) with ⟨U, hU, h'U⟩
refine ⟨e ⁻¹' U, e.continuous.continuousAt.preimage_mem_nhds hU, ?_⟩
exact (integrableOn_map_equiv e.toMeasurableEquiv).1 h'U
· rcases h (e.symm x) with ⟨U, hU, h'U⟩
refine ⟨e.symm ⁻¹' U, e.symm.continuous.continuousAt.preimage_mem_nhds hU, ?_⟩
apply (integrableOn_map_equiv e.toMeasurableEquiv).2
simp only [Homeomorph.toMeasurableEquiv_coe]
convert h'U
ext x
simp only [mem_preimage, Homeomorph.symm_apply_apply]
#align measure_theory.locally_integrable_map_homeomorph MeasureTheory.locallyIntegrable_map_homeomorph
protected theorem LocallyIntegrable.add (hf : LocallyIntegrable f μ) (hg : LocallyIntegrable g μ) :
LocallyIntegrable (f + g) μ := fun x ↦ (hf x).add (hg x)
protected theorem LocallyIntegrable.sub (hf : LocallyIntegrable f μ) (hg : LocallyIntegrable g μ) :
LocallyIntegrable (f - g) μ := fun x ↦ (hf x).sub (hg x)
protected theorem LocallyIntegrable.neg (hf : LocallyIntegrable f μ) :
LocallyIntegrable (-f) μ := fun x ↦ (hf x).neg
protected theorem LocallyIntegrable.smul {𝕜 : Type*} [NormedAddCommGroup 𝕜] [SMulZeroClass 𝕜 E]
[BoundedSMul 𝕜 E] (hf : LocallyIntegrable f μ) (c : 𝕜) :
LocallyIntegrable (c • f) μ := fun x ↦ (hf x).smul c
theorem locallyIntegrable_finset_sum' {ι} (s : Finset ι) {f : ι → X → E}
(hf : ∀ i ∈ s, LocallyIntegrable (f i) μ) : LocallyIntegrable (∑ i ∈ s, f i) μ :=
Finset.sum_induction f (fun g => LocallyIntegrable g μ) (fun _ _ => LocallyIntegrable.add)
locallyIntegrable_zero hf
theorem locallyIntegrable_finset_sum {ι} (s : Finset ι) {f : ι → X → E}
(hf : ∀ i ∈ s, LocallyIntegrable (f i) μ) : LocallyIntegrable (fun a ↦ ∑ i ∈ s, f i a) μ := by
simpa only [← Finset.sum_apply] using locallyIntegrable_finset_sum' s hf
/-- If `f` is locally integrable and `g` is continuous with compact support,
then `g • f` is integrable. -/
theorem LocallyIntegrable.integrable_smul_left_of_hasCompactSupport
[NormedSpace ℝ E] [OpensMeasurableSpace X] [T2Space X]
(hf : LocallyIntegrable f μ) {g : X → ℝ} (hg : Continuous g) (h'g : HasCompactSupport g) :
Integrable (fun x ↦ g x • f x) μ := by
let K := tsupport g
have hK : IsCompact K := h'g
have : K.indicator (fun x ↦ g x • f x) = (fun x ↦ g x • f x) := by
apply indicator_eq_self.2
apply support_subset_iff'.2
intros x hx
simp [image_eq_zero_of_nmem_tsupport hx]
rw [← this, indicator_smul]
apply Integrable.smul_of_top_right
· rw [integrable_indicator_iff hK.measurableSet]
exact hf.integrableOn_isCompact hK
· exact hg.memℒp_top_of_hasCompactSupport h'g μ
/-- If `f` is locally integrable and `g` is continuous with compact support,
then `f • g` is integrable. -/
theorem LocallyIntegrable.integrable_smul_right_of_hasCompactSupport
[NormedSpace ℝ E] [OpensMeasurableSpace X] [T2Space X] {f : X → ℝ} (hf : LocallyIntegrable f μ)
{g : X → E} (hg : Continuous g) (h'g : HasCompactSupport g) :
Integrable (fun x ↦ f x • g x) μ := by
let K := tsupport g
have hK : IsCompact K := h'g
have : K.indicator (fun x ↦ f x • g x) = (fun x ↦ f x • g x) := by
apply indicator_eq_self.2
apply support_subset_iff'.2
intros x hx
simp [image_eq_zero_of_nmem_tsupport hx]
rw [← this, indicator_smul_left]
apply Integrable.smul_of_top_left
· rw [integrable_indicator_iff hK.measurableSet]
exact hf.integrableOn_isCompact hK
· exact hg.memℒp_top_of_hasCompactSupport h'g μ
open Filter
theorem integrable_iff_integrableAtFilter_cocompact :
Integrable f μ ↔ (IntegrableAtFilter f (cocompact X) μ ∧ LocallyIntegrable f μ) := by
refine ⟨fun hf ↦ ⟨hf.integrableAtFilter _, hf.locallyIntegrable⟩, fun ⟨⟨s, hsc, hs⟩, hloc⟩ ↦ ?_⟩
obtain ⟨t, htc, ht⟩ := mem_cocompact'.mp hsc
rewrite [← integrableOn_univ, ← compl_union_self s, integrableOn_union]
exact ⟨(hloc.integrableOn_isCompact htc).mono ht le_rfl, hs⟩
theorem integrable_iff_integrableAtFilter_atBot_atTop [LinearOrder X] [CompactIccSpace X] :
Integrable f μ ↔
(IntegrableAtFilter f atBot μ ∧ IntegrableAtFilter f atTop μ) ∧ LocallyIntegrable f μ := by
constructor
· exact fun hf ↦ ⟨⟨hf.integrableAtFilter _, hf.integrableAtFilter _⟩, hf.locallyIntegrable⟩
· refine fun h ↦ integrable_iff_integrableAtFilter_cocompact.mpr ⟨?_, h.2⟩
exact (IntegrableAtFilter.sup_iff.mpr h.1).filter_mono cocompact_le_atBot_atTop
| Mathlib/MeasureTheory/Function/LocallyIntegrable.lean | 400 | 405 | theorem integrable_iff_integrableAtFilter_atBot [LinearOrder X] [OrderTop X] [CompactIccSpace X] :
Integrable f μ ↔ IntegrableAtFilter f atBot μ ∧ LocallyIntegrable f μ := by |
constructor
· exact fun hf ↦ ⟨hf.integrableAtFilter _, hf.locallyIntegrable⟩
· refine fun h ↦ integrable_iff_integrableAtFilter_cocompact.mpr ⟨?_, h.2⟩
exact h.1.filter_mono cocompact_le_atBot
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Johannes Hölzl, Yury G. Kudryashov, Patrick Massot
-/
import Mathlib.Algebra.GeomSum
import Mathlib.Order.Filter.Archimedean
import Mathlib.Order.Iterate
import Mathlib.Topology.Algebra.Algebra
import Mathlib.Topology.Algebra.InfiniteSum.Real
#align_import analysis.specific_limits.basic from "leanprover-community/mathlib"@"57ac39bd365c2f80589a700f9fbb664d3a1a30c2"
/-!
# A collection of specific limit computations
This file, by design, is independent of `NormedSpace` in the import hierarchy. It contains
important specific limit computations in metric spaces, in ordered rings/fields, and in specific
instances of these such as `ℝ`, `ℝ≥0` and `ℝ≥0∞`.
-/
noncomputable section
open scoped Classical
open Set Function Filter Finset Metric
open scoped Classical
open Topology Nat uniformity NNReal ENNReal
variable {α : Type*} {β : Type*} {ι : Type*}
theorem tendsto_inverse_atTop_nhds_zero_nat : Tendsto (fun n : ℕ ↦ (n : ℝ)⁻¹) atTop (𝓝 0) :=
tendsto_inv_atTop_zero.comp tendsto_natCast_atTop_atTop
#align tendsto_inverse_at_top_nhds_0_nat tendsto_inverse_atTop_nhds_zero_nat
@[deprecated (since := "2024-01-31")]
alias tendsto_inverse_atTop_nhds_0_nat := tendsto_inverse_atTop_nhds_zero_nat
| Mathlib/Analysis/SpecificLimits/Basic.lean | 39 | 41 | theorem tendsto_const_div_atTop_nhds_zero_nat (C : ℝ) :
Tendsto (fun n : ℕ ↦ C / n) atTop (𝓝 0) := by |
simpa only [mul_zero] using tendsto_const_nhds.mul tendsto_inverse_atTop_nhds_zero_nat
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Scott Morrison
-/
import Mathlib.Algebra.BigOperators.Finsupp
import Mathlib.Algebra.Module.Basic
import Mathlib.Algebra.Regular.SMul
import Mathlib.Data.Finset.Preimage
import Mathlib.Data.Rat.BigOperators
import Mathlib.GroupTheory.GroupAction.Hom
import Mathlib.Data.Set.Subsingleton
#align_import data.finsupp.basic from "leanprover-community/mathlib"@"f69db8cecc668e2d5894d7e9bfc491da60db3b9f"
/-!
# Miscellaneous definitions, lemmas, and constructions using finsupp
## Main declarations
* `Finsupp.graph`: the finset of input and output pairs with non-zero outputs.
* `Finsupp.mapRange.equiv`: `Finsupp.mapRange` as an equiv.
* `Finsupp.mapDomain`: maps the domain of a `Finsupp` by a function and by summing.
* `Finsupp.comapDomain`: postcomposition of a `Finsupp` with a function injective on the preimage
of its support.
* `Finsupp.some`: restrict a finitely supported function on `Option α` to a finitely supported
function on `α`.
* `Finsupp.filter`: `filter p f` is the finitely supported function that is `f a` if `p a` is true
and 0 otherwise.
* `Finsupp.frange`: the image of a finitely supported function on its support.
* `Finsupp.subtype_domain`: the restriction of a finitely supported function `f` to a subtype.
## Implementation notes
This file is a `noncomputable theory` and uses classical logic throughout.
## TODO
* This file is currently ~1600 lines long and is quite a miscellany of definitions and lemmas,
so it should be divided into smaller pieces.
* Expand the list of definitions and important lemmas to the module docstring.
-/
noncomputable section
open Finset Function
variable {α β γ ι M M' N P G H R S : Type*}
namespace Finsupp
/-! ### Declarations about `graph` -/
section Graph
variable [Zero M]
/-- The graph of a finitely supported function over its support, i.e. the finset of input and output
pairs with non-zero outputs. -/
def graph (f : α →₀ M) : Finset (α × M) :=
f.support.map ⟨fun a => Prod.mk a (f a), fun _ _ h => (Prod.mk.inj h).1⟩
#align finsupp.graph Finsupp.graph
theorem mk_mem_graph_iff {a : α} {m : M} {f : α →₀ M} : (a, m) ∈ f.graph ↔ f a = m ∧ m ≠ 0 := by
simp_rw [graph, mem_map, mem_support_iff]
constructor
· rintro ⟨b, ha, rfl, -⟩
exact ⟨rfl, ha⟩
· rintro ⟨rfl, ha⟩
exact ⟨a, ha, rfl⟩
#align finsupp.mk_mem_graph_iff Finsupp.mk_mem_graph_iff
@[simp]
theorem mem_graph_iff {c : α × M} {f : α →₀ M} : c ∈ f.graph ↔ f c.1 = c.2 ∧ c.2 ≠ 0 := by
cases c
exact mk_mem_graph_iff
#align finsupp.mem_graph_iff Finsupp.mem_graph_iff
theorem mk_mem_graph (f : α →₀ M) {a : α} (ha : a ∈ f.support) : (a, f a) ∈ f.graph :=
mk_mem_graph_iff.2 ⟨rfl, mem_support_iff.1 ha⟩
#align finsupp.mk_mem_graph Finsupp.mk_mem_graph
theorem apply_eq_of_mem_graph {a : α} {m : M} {f : α →₀ M} (h : (a, m) ∈ f.graph) : f a = m :=
(mem_graph_iff.1 h).1
#align finsupp.apply_eq_of_mem_graph Finsupp.apply_eq_of_mem_graph
@[simp 1100] -- Porting note: change priority to appease `simpNF`
theorem not_mem_graph_snd_zero (a : α) (f : α →₀ M) : (a, (0 : M)) ∉ f.graph := fun h =>
(mem_graph_iff.1 h).2.irrefl
#align finsupp.not_mem_graph_snd_zero Finsupp.not_mem_graph_snd_zero
@[simp]
theorem image_fst_graph [DecidableEq α] (f : α →₀ M) : f.graph.image Prod.fst = f.support := by
classical simp only [graph, map_eq_image, image_image, Embedding.coeFn_mk, (· ∘ ·), image_id']
#align finsupp.image_fst_graph Finsupp.image_fst_graph
theorem graph_injective (α M) [Zero M] : Injective (@graph α M _) := by
intro f g h
classical
have hsup : f.support = g.support := by rw [← image_fst_graph, h, image_fst_graph]
refine ext_iff'.2 ⟨hsup, fun x hx => apply_eq_of_mem_graph <| h.symm ▸ ?_⟩
exact mk_mem_graph _ (hsup ▸ hx)
#align finsupp.graph_injective Finsupp.graph_injective
@[simp]
theorem graph_inj {f g : α →₀ M} : f.graph = g.graph ↔ f = g :=
(graph_injective α M).eq_iff
#align finsupp.graph_inj Finsupp.graph_inj
@[simp]
theorem graph_zero : graph (0 : α →₀ M) = ∅ := by simp [graph]
#align finsupp.graph_zero Finsupp.graph_zero
@[simp]
theorem graph_eq_empty {f : α →₀ M} : f.graph = ∅ ↔ f = 0 :=
(graph_injective α M).eq_iff' graph_zero
#align finsupp.graph_eq_empty Finsupp.graph_eq_empty
end Graph
end Finsupp
/-! ### Declarations about `mapRange` -/
section MapRange
namespace Finsupp
section Equiv
variable [Zero M] [Zero N] [Zero P]
/-- `Finsupp.mapRange` as an equiv. -/
@[simps apply]
def mapRange.equiv (f : M ≃ N) (hf : f 0 = 0) (hf' : f.symm 0 = 0) : (α →₀ M) ≃ (α →₀ N) where
toFun := (mapRange f hf : (α →₀ M) → α →₀ N)
invFun := (mapRange f.symm hf' : (α →₀ N) → α →₀ M)
left_inv x := by
rw [← mapRange_comp _ _ _ _] <;> simp_rw [Equiv.symm_comp_self]
· exact mapRange_id _
· rfl
right_inv x := by
rw [← mapRange_comp _ _ _ _] <;> simp_rw [Equiv.self_comp_symm]
· exact mapRange_id _
· rfl
#align finsupp.map_range.equiv Finsupp.mapRange.equiv
@[simp]
theorem mapRange.equiv_refl : mapRange.equiv (Equiv.refl M) rfl rfl = Equiv.refl (α →₀ M) :=
Equiv.ext mapRange_id
#align finsupp.map_range.equiv_refl Finsupp.mapRange.equiv_refl
theorem mapRange.equiv_trans (f : M ≃ N) (hf : f 0 = 0) (hf') (f₂ : N ≃ P) (hf₂ : f₂ 0 = 0) (hf₂') :
(mapRange.equiv (f.trans f₂) (by rw [Equiv.trans_apply, hf, hf₂])
(by rw [Equiv.symm_trans_apply, hf₂', hf']) :
(α →₀ _) ≃ _) =
(mapRange.equiv f hf hf').trans (mapRange.equiv f₂ hf₂ hf₂') :=
Equiv.ext <| mapRange_comp f₂ hf₂ f hf ((congrArg f₂ hf).trans hf₂)
#align finsupp.map_range.equiv_trans Finsupp.mapRange.equiv_trans
@[simp]
theorem mapRange.equiv_symm (f : M ≃ N) (hf hf') :
((mapRange.equiv f hf hf').symm : (α →₀ _) ≃ _) = mapRange.equiv f.symm hf' hf :=
Equiv.ext fun _ => rfl
#align finsupp.map_range.equiv_symm Finsupp.mapRange.equiv_symm
end Equiv
section ZeroHom
variable [Zero M] [Zero N] [Zero P]
/-- Composition with a fixed zero-preserving homomorphism is itself a zero-preserving homomorphism
on functions. -/
@[simps]
def mapRange.zeroHom (f : ZeroHom M N) : ZeroHom (α →₀ M) (α →₀ N) where
toFun := (mapRange f f.map_zero : (α →₀ M) → α →₀ N)
map_zero' := mapRange_zero
#align finsupp.map_range.zero_hom Finsupp.mapRange.zeroHom
@[simp]
theorem mapRange.zeroHom_id : mapRange.zeroHom (ZeroHom.id M) = ZeroHom.id (α →₀ M) :=
ZeroHom.ext mapRange_id
#align finsupp.map_range.zero_hom_id Finsupp.mapRange.zeroHom_id
theorem mapRange.zeroHom_comp (f : ZeroHom N P) (f₂ : ZeroHom M N) :
(mapRange.zeroHom (f.comp f₂) : ZeroHom (α →₀ _) _) =
(mapRange.zeroHom f).comp (mapRange.zeroHom f₂) :=
ZeroHom.ext <| mapRange_comp f (map_zero f) f₂ (map_zero f₂) (by simp only [comp_apply, map_zero])
#align finsupp.map_range.zero_hom_comp Finsupp.mapRange.zeroHom_comp
end ZeroHom
section AddMonoidHom
variable [AddCommMonoid M] [AddCommMonoid N] [AddCommMonoid P]
variable {F : Type*} [FunLike F M N] [AddMonoidHomClass F M N]
/-- Composition with a fixed additive homomorphism is itself an additive homomorphism on functions.
-/
@[simps]
def mapRange.addMonoidHom (f : M →+ N) : (α →₀ M) →+ α →₀ N where
toFun := (mapRange f f.map_zero : (α →₀ M) → α →₀ N)
map_zero' := mapRange_zero
map_add' a b := by dsimp only; exact mapRange_add f.map_add _ _; -- Porting note: `dsimp` needed
#align finsupp.map_range.add_monoid_hom Finsupp.mapRange.addMonoidHom
@[simp]
theorem mapRange.addMonoidHom_id :
mapRange.addMonoidHom (AddMonoidHom.id M) = AddMonoidHom.id (α →₀ M) :=
AddMonoidHom.ext mapRange_id
#align finsupp.map_range.add_monoid_hom_id Finsupp.mapRange.addMonoidHom_id
theorem mapRange.addMonoidHom_comp (f : N →+ P) (f₂ : M →+ N) :
(mapRange.addMonoidHom (f.comp f₂) : (α →₀ _) →+ _) =
(mapRange.addMonoidHom f).comp (mapRange.addMonoidHom f₂) :=
AddMonoidHom.ext <|
mapRange_comp f (map_zero f) f₂ (map_zero f₂) (by simp only [comp_apply, map_zero])
#align finsupp.map_range.add_monoid_hom_comp Finsupp.mapRange.addMonoidHom_comp
@[simp]
theorem mapRange.addMonoidHom_toZeroHom (f : M →+ N) :
(mapRange.addMonoidHom f).toZeroHom = (mapRange.zeroHom f.toZeroHom : ZeroHom (α →₀ _) _) :=
ZeroHom.ext fun _ => rfl
#align finsupp.map_range.add_monoid_hom_to_zero_hom Finsupp.mapRange.addMonoidHom_toZeroHom
theorem mapRange_multiset_sum (f : F) (m : Multiset (α →₀ M)) :
mapRange f (map_zero f) m.sum = (m.map fun x => mapRange f (map_zero f) x).sum :=
(mapRange.addMonoidHom (f : M →+ N) : (α →₀ _) →+ _).map_multiset_sum _
#align finsupp.map_range_multiset_sum Finsupp.mapRange_multiset_sum
theorem mapRange_finset_sum (f : F) (s : Finset ι) (g : ι → α →₀ M) :
mapRange f (map_zero f) (∑ x ∈ s, g x) = ∑ x ∈ s, mapRange f (map_zero f) (g x) :=
map_sum (mapRange.addMonoidHom (f : M →+ N)) _ _
#align finsupp.map_range_finset_sum Finsupp.mapRange_finset_sum
/-- `Finsupp.mapRange.AddMonoidHom` as an equiv. -/
@[simps apply]
def mapRange.addEquiv (f : M ≃+ N) : (α →₀ M) ≃+ (α →₀ N) :=
{ mapRange.addMonoidHom f.toAddMonoidHom with
toFun := (mapRange f f.map_zero : (α →₀ M) → α →₀ N)
invFun := (mapRange f.symm f.symm.map_zero : (α →₀ N) → α →₀ M)
left_inv := fun x => by
rw [← mapRange_comp _ _ _ _] <;> simp_rw [AddEquiv.symm_comp_self]
· exact mapRange_id _
· rfl
right_inv := fun x => by
rw [← mapRange_comp _ _ _ _] <;> simp_rw [AddEquiv.self_comp_symm]
· exact mapRange_id _
· rfl }
#align finsupp.map_range.add_equiv Finsupp.mapRange.addEquiv
@[simp]
theorem mapRange.addEquiv_refl : mapRange.addEquiv (AddEquiv.refl M) = AddEquiv.refl (α →₀ M) :=
AddEquiv.ext mapRange_id
#align finsupp.map_range.add_equiv_refl Finsupp.mapRange.addEquiv_refl
theorem mapRange.addEquiv_trans (f : M ≃+ N) (f₂ : N ≃+ P) :
(mapRange.addEquiv (f.trans f₂) : (α →₀ M) ≃+ (α →₀ P)) =
(mapRange.addEquiv f).trans (mapRange.addEquiv f₂) :=
AddEquiv.ext (mapRange_comp _ f₂.map_zero _ f.map_zero (by simp))
#align finsupp.map_range.add_equiv_trans Finsupp.mapRange.addEquiv_trans
@[simp]
theorem mapRange.addEquiv_symm (f : M ≃+ N) :
((mapRange.addEquiv f).symm : (α →₀ _) ≃+ _) = mapRange.addEquiv f.symm :=
AddEquiv.ext fun _ => rfl
#align finsupp.map_range.add_equiv_symm Finsupp.mapRange.addEquiv_symm
@[simp]
theorem mapRange.addEquiv_toAddMonoidHom (f : M ≃+ N) :
((mapRange.addEquiv f : (α →₀ _) ≃+ _) : _ →+ _) =
(mapRange.addMonoidHom f.toAddMonoidHom : (α →₀ _) →+ _) :=
AddMonoidHom.ext fun _ => rfl
#align finsupp.map_range.add_equiv_to_add_monoid_hom Finsupp.mapRange.addEquiv_toAddMonoidHom
@[simp]
theorem mapRange.addEquiv_toEquiv (f : M ≃+ N) :
↑(mapRange.addEquiv f : (α →₀ _) ≃+ _) =
(mapRange.equiv (f : M ≃ N) f.map_zero f.symm.map_zero : (α →₀ _) ≃ _) :=
Equiv.ext fun _ => rfl
#align finsupp.map_range.add_equiv_to_equiv Finsupp.mapRange.addEquiv_toEquiv
end AddMonoidHom
end Finsupp
end MapRange
/-! ### Declarations about `equivCongrLeft` -/
section EquivCongrLeft
variable [Zero M]
namespace Finsupp
/-- Given `f : α ≃ β`, we can map `l : α →₀ M` to `equivMapDomain f l : β →₀ M` (computably)
by mapping the support forwards and the function backwards. -/
def equivMapDomain (f : α ≃ β) (l : α →₀ M) : β →₀ M where
support := l.support.map f.toEmbedding
toFun a := l (f.symm a)
mem_support_toFun a := by simp only [Finset.mem_map_equiv, mem_support_toFun]; rfl
#align finsupp.equiv_map_domain Finsupp.equivMapDomain
@[simp]
theorem equivMapDomain_apply (f : α ≃ β) (l : α →₀ M) (b : β) :
equivMapDomain f l b = l (f.symm b) :=
rfl
#align finsupp.equiv_map_domain_apply Finsupp.equivMapDomain_apply
theorem equivMapDomain_symm_apply (f : α ≃ β) (l : β →₀ M) (a : α) :
equivMapDomain f.symm l a = l (f a) :=
rfl
#align finsupp.equiv_map_domain_symm_apply Finsupp.equivMapDomain_symm_apply
@[simp]
theorem equivMapDomain_refl (l : α →₀ M) : equivMapDomain (Equiv.refl _) l = l := by ext x; rfl
#align finsupp.equiv_map_domain_refl Finsupp.equivMapDomain_refl
theorem equivMapDomain_refl' : equivMapDomain (Equiv.refl _) = @id (α →₀ M) := by ext x; rfl
#align finsupp.equiv_map_domain_refl' Finsupp.equivMapDomain_refl'
theorem equivMapDomain_trans (f : α ≃ β) (g : β ≃ γ) (l : α →₀ M) :
equivMapDomain (f.trans g) l = equivMapDomain g (equivMapDomain f l) := by ext x; rfl
#align finsupp.equiv_map_domain_trans Finsupp.equivMapDomain_trans
theorem equivMapDomain_trans' (f : α ≃ β) (g : β ≃ γ) :
@equivMapDomain _ _ M _ (f.trans g) = equivMapDomain g ∘ equivMapDomain f := by ext x; rfl
#align finsupp.equiv_map_domain_trans' Finsupp.equivMapDomain_trans'
@[simp]
theorem equivMapDomain_single (f : α ≃ β) (a : α) (b : M) :
equivMapDomain f (single a b) = single (f a) b := by
classical
ext x
simp only [single_apply, Equiv.apply_eq_iff_eq_symm_apply, equivMapDomain_apply]
#align finsupp.equiv_map_domain_single Finsupp.equivMapDomain_single
@[simp]
theorem equivMapDomain_zero {f : α ≃ β} : equivMapDomain f (0 : α →₀ M) = (0 : β →₀ M) := by
ext; simp only [equivMapDomain_apply, coe_zero, Pi.zero_apply]
#align finsupp.equiv_map_domain_zero Finsupp.equivMapDomain_zero
@[to_additive (attr := simp)]
theorem prod_equivMapDomain [CommMonoid N] (f : α ≃ β) (l : α →₀ M) (g : β → M → N):
prod (equivMapDomain f l) g = prod l (fun a m => g (f a) m) := by
simp [prod, equivMapDomain]
/-- Given `f : α ≃ β`, the finitely supported function spaces are also in bijection:
`(α →₀ M) ≃ (β →₀ M)`.
This is the finitely-supported version of `Equiv.piCongrLeft`. -/
def equivCongrLeft (f : α ≃ β) : (α →₀ M) ≃ (β →₀ M) := by
refine ⟨equivMapDomain f, equivMapDomain f.symm, fun f => ?_, fun f => ?_⟩ <;> ext x <;>
simp only [equivMapDomain_apply, Equiv.symm_symm, Equiv.symm_apply_apply,
Equiv.apply_symm_apply]
#align finsupp.equiv_congr_left Finsupp.equivCongrLeft
@[simp]
theorem equivCongrLeft_apply (f : α ≃ β) (l : α →₀ M) : equivCongrLeft f l = equivMapDomain f l :=
rfl
#align finsupp.equiv_congr_left_apply Finsupp.equivCongrLeft_apply
@[simp]
theorem equivCongrLeft_symm (f : α ≃ β) :
(@equivCongrLeft _ _ M _ f).symm = equivCongrLeft f.symm :=
rfl
#align finsupp.equiv_congr_left_symm Finsupp.equivCongrLeft_symm
end Finsupp
end EquivCongrLeft
section CastFinsupp
variable [Zero M] (f : α →₀ M)
namespace Nat
@[simp, norm_cast]
theorem cast_finsupp_prod [CommSemiring R] (g : α → M → ℕ) :
(↑(f.prod g) : R) = f.prod fun a b => ↑(g a b) :=
Nat.cast_prod _ _
#align nat.cast_finsupp_prod Nat.cast_finsupp_prod
@[simp, norm_cast]
theorem cast_finsupp_sum [CommSemiring R] (g : α → M → ℕ) :
(↑(f.sum g) : R) = f.sum fun a b => ↑(g a b) :=
Nat.cast_sum _ _
#align nat.cast_finsupp_sum Nat.cast_finsupp_sum
end Nat
namespace Int
@[simp, norm_cast]
theorem cast_finsupp_prod [CommRing R] (g : α → M → ℤ) :
(↑(f.prod g) : R) = f.prod fun a b => ↑(g a b) :=
Int.cast_prod _ _
#align int.cast_finsupp_prod Int.cast_finsupp_prod
@[simp, norm_cast]
theorem cast_finsupp_sum [CommRing R] (g : α → M → ℤ) :
(↑(f.sum g) : R) = f.sum fun a b => ↑(g a b) :=
Int.cast_sum _ _
#align int.cast_finsupp_sum Int.cast_finsupp_sum
end Int
namespace Rat
@[simp, norm_cast]
theorem cast_finsupp_sum [DivisionRing R] [CharZero R] (g : α → M → ℚ) :
(↑(f.sum g) : R) = f.sum fun a b => ↑(g a b) :=
cast_sum _ _
#align rat.cast_finsupp_sum Rat.cast_finsupp_sum
@[simp, norm_cast]
theorem cast_finsupp_prod [Field R] [CharZero R] (g : α → M → ℚ) :
(↑(f.prod g) : R) = f.prod fun a b => ↑(g a b) :=
cast_prod _ _
#align rat.cast_finsupp_prod Rat.cast_finsupp_prod
end Rat
end CastFinsupp
/-! ### Declarations about `mapDomain` -/
namespace Finsupp
section MapDomain
variable [AddCommMonoid M] {v v₁ v₂ : α →₀ M}
/-- Given `f : α → β` and `v : α →₀ M`, `mapDomain f v : β →₀ M`
is the finitely supported function whose value at `a : β` is the sum
of `v x` over all `x` such that `f x = a`. -/
def mapDomain (f : α → β) (v : α →₀ M) : β →₀ M :=
v.sum fun a => single (f a)
#align finsupp.map_domain Finsupp.mapDomain
theorem mapDomain_apply {f : α → β} (hf : Function.Injective f) (x : α →₀ M) (a : α) :
mapDomain f x (f a) = x a := by
rw [mapDomain, sum_apply, sum_eq_single a, single_eq_same]
· intro b _ hba
exact single_eq_of_ne (hf.ne hba)
· intro _
rw [single_zero, coe_zero, Pi.zero_apply]
#align finsupp.map_domain_apply Finsupp.mapDomain_apply
theorem mapDomain_notin_range {f : α → β} (x : α →₀ M) (a : β) (h : a ∉ Set.range f) :
mapDomain f x a = 0 := by
rw [mapDomain, sum_apply, sum]
exact Finset.sum_eq_zero fun a' _ => single_eq_of_ne fun eq => h <| eq ▸ Set.mem_range_self _
#align finsupp.map_domain_notin_range Finsupp.mapDomain_notin_range
@[simp]
theorem mapDomain_id : mapDomain id v = v :=
sum_single _
#align finsupp.map_domain_id Finsupp.mapDomain_id
theorem mapDomain_comp {f : α → β} {g : β → γ} :
mapDomain (g ∘ f) v = mapDomain g (mapDomain f v) := by
refine ((sum_sum_index ?_ ?_).trans ?_).symm
· intro
exact single_zero _
· intro
exact single_add _
refine sum_congr fun _ _ => sum_single_index ?_
exact single_zero _
#align finsupp.map_domain_comp Finsupp.mapDomain_comp
@[simp]
theorem mapDomain_single {f : α → β} {a : α} {b : M} : mapDomain f (single a b) = single (f a) b :=
sum_single_index <| single_zero _
#align finsupp.map_domain_single Finsupp.mapDomain_single
@[simp]
theorem mapDomain_zero {f : α → β} : mapDomain f (0 : α →₀ M) = (0 : β →₀ M) :=
sum_zero_index
#align finsupp.map_domain_zero Finsupp.mapDomain_zero
theorem mapDomain_congr {f g : α → β} (h : ∀ x ∈ v.support, f x = g x) :
v.mapDomain f = v.mapDomain g :=
Finset.sum_congr rfl fun _ H => by simp only [h _ H]
#align finsupp.map_domain_congr Finsupp.mapDomain_congr
theorem mapDomain_add {f : α → β} : mapDomain f (v₁ + v₂) = mapDomain f v₁ + mapDomain f v₂ :=
sum_add_index' (fun _ => single_zero _) fun _ => single_add _
#align finsupp.map_domain_add Finsupp.mapDomain_add
@[simp]
theorem mapDomain_equiv_apply {f : α ≃ β} (x : α →₀ M) (a : β) :
mapDomain f x a = x (f.symm a) := by
conv_lhs => rw [← f.apply_symm_apply a]
exact mapDomain_apply f.injective _ _
#align finsupp.map_domain_equiv_apply Finsupp.mapDomain_equiv_apply
/-- `Finsupp.mapDomain` is an `AddMonoidHom`. -/
@[simps]
def mapDomain.addMonoidHom (f : α → β) : (α →₀ M) →+ β →₀ M where
toFun := mapDomain f
map_zero' := mapDomain_zero
map_add' _ _ := mapDomain_add
#align finsupp.map_domain.add_monoid_hom Finsupp.mapDomain.addMonoidHom
@[simp]
theorem mapDomain.addMonoidHom_id : mapDomain.addMonoidHom id = AddMonoidHom.id (α →₀ M) :=
AddMonoidHom.ext fun _ => mapDomain_id
#align finsupp.map_domain.add_monoid_hom_id Finsupp.mapDomain.addMonoidHom_id
theorem mapDomain.addMonoidHom_comp (f : β → γ) (g : α → β) :
(mapDomain.addMonoidHom (f ∘ g) : (α →₀ M) →+ γ →₀ M) =
(mapDomain.addMonoidHom f).comp (mapDomain.addMonoidHom g) :=
AddMonoidHom.ext fun _ => mapDomain_comp
#align finsupp.map_domain.add_monoid_hom_comp Finsupp.mapDomain.addMonoidHom_comp
theorem mapDomain_finset_sum {f : α → β} {s : Finset ι} {v : ι → α →₀ M} :
mapDomain f (∑ i ∈ s, v i) = ∑ i ∈ s, mapDomain f (v i) :=
map_sum (mapDomain.addMonoidHom f) _ _
#align finsupp.map_domain_finset_sum Finsupp.mapDomain_finset_sum
theorem mapDomain_sum [Zero N] {f : α → β} {s : α →₀ N} {v : α → N → α →₀ M} :
mapDomain f (s.sum v) = s.sum fun a b => mapDomain f (v a b) :=
map_finsupp_sum (mapDomain.addMonoidHom f : (α →₀ M) →+ β →₀ M) _ _
#align finsupp.map_domain_sum Finsupp.mapDomain_sum
theorem mapDomain_support [DecidableEq β] {f : α → β} {s : α →₀ M} :
(s.mapDomain f).support ⊆ s.support.image f :=
Finset.Subset.trans support_sum <|
Finset.Subset.trans (Finset.biUnion_mono fun a _ => support_single_subset) <| by
rw [Finset.biUnion_singleton]
#align finsupp.map_domain_support Finsupp.mapDomain_support
theorem mapDomain_apply' (S : Set α) {f : α → β} (x : α →₀ M) (hS : (x.support : Set α) ⊆ S)
(hf : Set.InjOn f S) {a : α} (ha : a ∈ S) : mapDomain f x (f a) = x a := by
classical
rw [mapDomain, sum_apply, sum]
simp_rw [single_apply]
by_cases hax : a ∈ x.support
· rw [← Finset.add_sum_erase _ _ hax, if_pos rfl]
convert add_zero (x a)
refine Finset.sum_eq_zero fun i hi => if_neg ?_
exact (hf.mono hS).ne (Finset.mem_of_mem_erase hi) hax (Finset.ne_of_mem_erase hi)
· rw [not_mem_support_iff.1 hax]
refine Finset.sum_eq_zero fun i hi => if_neg ?_
exact hf.ne (hS hi) ha (ne_of_mem_of_not_mem hi hax)
#align finsupp.map_domain_apply' Finsupp.mapDomain_apply'
theorem mapDomain_support_of_injOn [DecidableEq β] {f : α → β} (s : α →₀ M)
(hf : Set.InjOn f s.support) : (mapDomain f s).support = Finset.image f s.support :=
Finset.Subset.antisymm mapDomain_support <| by
intro x hx
simp only [mem_image, exists_prop, mem_support_iff, Ne] at hx
rcases hx with ⟨hx_w, hx_h_left, rfl⟩
simp only [mem_support_iff, Ne]
rw [mapDomain_apply' (↑s.support : Set _) _ _ hf]
· exact hx_h_left
· simp only [mem_coe, mem_support_iff, Ne]
exact hx_h_left
· exact Subset.refl _
#align finsupp.map_domain_support_of_inj_on Finsupp.mapDomain_support_of_injOn
theorem mapDomain_support_of_injective [DecidableEq β] {f : α → β} (hf : Function.Injective f)
(s : α →₀ M) : (mapDomain f s).support = Finset.image f s.support :=
mapDomain_support_of_injOn s hf.injOn
#align finsupp.map_domain_support_of_injective Finsupp.mapDomain_support_of_injective
@[to_additive]
theorem prod_mapDomain_index [CommMonoid N] {f : α → β} {s : α →₀ M} {h : β → M → N}
(h_zero : ∀ b, h b 0 = 1) (h_add : ∀ b m₁ m₂, h b (m₁ + m₂) = h b m₁ * h b m₂) :
(mapDomain f s).prod h = s.prod fun a m => h (f a) m :=
(prod_sum_index h_zero h_add).trans <| prod_congr fun _ _ => prod_single_index (h_zero _)
#align finsupp.prod_map_domain_index Finsupp.prod_mapDomain_index
#align finsupp.sum_map_domain_index Finsupp.sum_mapDomain_index
-- Note that in `prod_mapDomain_index`, `M` is still an additive monoid,
-- so there is no analogous version in terms of `MonoidHom`.
/-- A version of `sum_mapDomain_index` that takes a bundled `AddMonoidHom`,
rather than separate linearity hypotheses.
-/
@[simp]
theorem sum_mapDomain_index_addMonoidHom [AddCommMonoid N] {f : α → β} {s : α →₀ M}
(h : β → M →+ N) : ((mapDomain f s).sum fun b m => h b m) = s.sum fun a m => h (f a) m :=
sum_mapDomain_index (fun b => (h b).map_zero) (fun b _ _ => (h b).map_add _ _)
#align finsupp.sum_map_domain_index_add_monoid_hom Finsupp.sum_mapDomain_index_addMonoidHom
theorem embDomain_eq_mapDomain (f : α ↪ β) (v : α →₀ M) : embDomain f v = mapDomain f v := by
ext a
by_cases h : a ∈ Set.range f
· rcases h with ⟨a, rfl⟩
rw [mapDomain_apply f.injective, embDomain_apply]
· rw [mapDomain_notin_range, embDomain_notin_range] <;> assumption
#align finsupp.emb_domain_eq_map_domain Finsupp.embDomain_eq_mapDomain
@[to_additive]
theorem prod_mapDomain_index_inj [CommMonoid N] {f : α → β} {s : α →₀ M} {h : β → M → N}
(hf : Function.Injective f) : (s.mapDomain f).prod h = s.prod fun a b => h (f a) b := by
rw [← Function.Embedding.coeFn_mk f hf, ← embDomain_eq_mapDomain, prod_embDomain]
#align finsupp.prod_map_domain_index_inj Finsupp.prod_mapDomain_index_inj
#align finsupp.sum_map_domain_index_inj Finsupp.sum_mapDomain_index_inj
theorem mapDomain_injective {f : α → β} (hf : Function.Injective f) :
Function.Injective (mapDomain f : (α →₀ M) → β →₀ M) := by
intro v₁ v₂ eq
ext a
have : mapDomain f v₁ (f a) = mapDomain f v₂ (f a) := by rw [eq]
rwa [mapDomain_apply hf, mapDomain_apply hf] at this
#align finsupp.map_domain_injective Finsupp.mapDomain_injective
/-- When `f` is an embedding we have an embedding `(α →₀ ℕ) ↪ (β →₀ ℕ)` given by `mapDomain`. -/
@[simps]
def mapDomainEmbedding {α β : Type*} (f : α ↪ β) : (α →₀ ℕ) ↪ β →₀ ℕ :=
⟨Finsupp.mapDomain f, Finsupp.mapDomain_injective f.injective⟩
#align finsupp.map_domain_embedding Finsupp.mapDomainEmbedding
theorem mapDomain.addMonoidHom_comp_mapRange [AddCommMonoid N] (f : α → β) (g : M →+ N) :
(mapDomain.addMonoidHom f).comp (mapRange.addMonoidHom g) =
(mapRange.addMonoidHom g).comp (mapDomain.addMonoidHom f) := by
ext
simp only [AddMonoidHom.coe_comp, Finsupp.mapRange_single, Finsupp.mapDomain.addMonoidHom_apply,
Finsupp.singleAddHom_apply, eq_self_iff_true, Function.comp_apply, Finsupp.mapDomain_single,
Finsupp.mapRange.addMonoidHom_apply]
#align finsupp.map_domain.add_monoid_hom_comp_map_range Finsupp.mapDomain.addMonoidHom_comp_mapRange
/-- When `g` preserves addition, `mapRange` and `mapDomain` commute. -/
theorem mapDomain_mapRange [AddCommMonoid N] (f : α → β) (v : α →₀ M) (g : M → N) (h0 : g 0 = 0)
(hadd : ∀ x y, g (x + y) = g x + g y) :
mapDomain f (mapRange g h0 v) = mapRange g h0 (mapDomain f v) :=
let g' : M →+ N :=
{ toFun := g
map_zero' := h0
map_add' := hadd }
DFunLike.congr_fun (mapDomain.addMonoidHom_comp_mapRange f g') v
#align finsupp.map_domain_map_range Finsupp.mapDomain_mapRange
theorem sum_update_add [AddCommMonoid α] [AddCommMonoid β] (f : ι →₀ α) (i : ι) (a : α)
(g : ι → α → β) (hg : ∀ i, g i 0 = 0)
(hgg : ∀ (j : ι) (a₁ a₂ : α), g j (a₁ + a₂) = g j a₁ + g j a₂) :
(f.update i a).sum g + g i (f i) = f.sum g + g i a := by
rw [update_eq_erase_add_single, sum_add_index' hg hgg]
conv_rhs => rw [← Finsupp.update_self f i]
rw [update_eq_erase_add_single, sum_add_index' hg hgg, add_assoc, add_assoc]
congr 1
rw [add_comm, sum_single_index (hg _), sum_single_index (hg _)]
#align finsupp.sum_update_add Finsupp.sum_update_add
theorem mapDomain_injOn (S : Set α) {f : α → β} (hf : Set.InjOn f S) :
Set.InjOn (mapDomain f : (α →₀ M) → β →₀ M) { w | (w.support : Set α) ⊆ S } := by
intro v₁ hv₁ v₂ hv₂ eq
ext a
classical
by_cases h : a ∈ v₁.support ∪ v₂.support
· rw [← mapDomain_apply' S _ hv₁ hf _, ← mapDomain_apply' S _ hv₂ hf _, eq] <;>
· apply Set.union_subset hv₁ hv₂
exact mod_cast h
· simp only [not_or, mem_union, not_not, mem_support_iff] at h
simp [h]
#align finsupp.map_domain_inj_on Finsupp.mapDomain_injOn
theorem equivMapDomain_eq_mapDomain {M} [AddCommMonoid M] (f : α ≃ β) (l : α →₀ M) :
equivMapDomain f l = mapDomain f l := by ext x; simp [mapDomain_equiv_apply]
#align finsupp.equiv_map_domain_eq_map_domain Finsupp.equivMapDomain_eq_mapDomain
end MapDomain
/-! ### Declarations about `comapDomain` -/
section ComapDomain
/-- Given `f : α → β`, `l : β →₀ M` and a proof `hf` that `f` is injective on
the preimage of `l.support`, `comapDomain f l hf` is the finitely supported function
from `α` to `M` given by composing `l` with `f`. -/
@[simps support]
def comapDomain [Zero M] (f : α → β) (l : β →₀ M) (hf : Set.InjOn f (f ⁻¹' ↑l.support)) :
α →₀ M where
support := l.support.preimage f hf
toFun a := l (f a)
mem_support_toFun := by
intro a
simp only [Finset.mem_def.symm, Finset.mem_preimage]
exact l.mem_support_toFun (f a)
#align finsupp.comap_domain Finsupp.comapDomain
@[simp]
theorem comapDomain_apply [Zero M] (f : α → β) (l : β →₀ M) (hf : Set.InjOn f (f ⁻¹' ↑l.support))
(a : α) : comapDomain f l hf a = l (f a) :=
rfl
#align finsupp.comap_domain_apply Finsupp.comapDomain_apply
theorem sum_comapDomain [Zero M] [AddCommMonoid N] (f : α → β) (l : β →₀ M) (g : β → M → N)
(hf : Set.BijOn f (f ⁻¹' ↑l.support) ↑l.support) :
(comapDomain f l hf.injOn).sum (g ∘ f) = l.sum g := by
simp only [sum, comapDomain_apply, (· ∘ ·), comapDomain]
exact Finset.sum_preimage_of_bij f _ hf fun x => g x (l x)
#align finsupp.sum_comap_domain Finsupp.sum_comapDomain
theorem eq_zero_of_comapDomain_eq_zero [AddCommMonoid M] (f : α → β) (l : β →₀ M)
(hf : Set.BijOn f (f ⁻¹' ↑l.support) ↑l.support) : comapDomain f l hf.injOn = 0 → l = 0 := by
rw [← support_eq_empty, ← support_eq_empty, comapDomain]
simp only [Finset.ext_iff, Finset.not_mem_empty, iff_false_iff, mem_preimage]
intro h a ha
cases' hf.2.2 ha with b hb
exact h b (hb.2.symm ▸ ha)
#align finsupp.eq_zero_of_comap_domain_eq_zero Finsupp.eq_zero_of_comapDomain_eq_zero
section FInjective
section Zero
variable [Zero M]
lemma embDomain_comapDomain {f : α ↪ β} {g : β →₀ M} (hg : ↑g.support ⊆ Set.range f) :
embDomain f (comapDomain f g f.injective.injOn) = g := by
ext b
by_cases hb : b ∈ Set.range f
· obtain ⟨a, rfl⟩ := hb
rw [embDomain_apply, comapDomain_apply]
· replace hg : g b = 0 := not_mem_support_iff.mp <| mt (hg ·) hb
rw [embDomain_notin_range _ _ _ hb, hg]
/-- Note the `hif` argument is needed for this to work in `rw`. -/
@[simp]
theorem comapDomain_zero (f : α → β)
(hif : Set.InjOn f (f ⁻¹' ↑(0 : β →₀ M).support) := Finset.coe_empty ▸ (Set.injOn_empty f)) :
comapDomain f (0 : β →₀ M) hif = (0 : α →₀ M) := by
ext
rfl
#align finsupp.comap_domain_zero Finsupp.comapDomain_zero
@[simp]
theorem comapDomain_single (f : α → β) (a : α) (m : M)
(hif : Set.InjOn f (f ⁻¹' (single (f a) m).support)) :
comapDomain f (Finsupp.single (f a) m) hif = Finsupp.single a m := by
rcases eq_or_ne m 0 with (rfl | hm)
· simp only [single_zero, comapDomain_zero]
· rw [eq_single_iff, comapDomain_apply, comapDomain_support, ← Finset.coe_subset, coe_preimage,
support_single_ne_zero _ hm, coe_singleton, coe_singleton, single_eq_same]
rw [support_single_ne_zero _ hm, coe_singleton] at hif
exact ⟨fun x hx => hif hx rfl hx, rfl⟩
#align finsupp.comap_domain_single Finsupp.comapDomain_single
end Zero
section AddZeroClass
variable [AddZeroClass M] {f : α → β}
theorem comapDomain_add (v₁ v₂ : β →₀ M) (hv₁ : Set.InjOn f (f ⁻¹' ↑v₁.support))
(hv₂ : Set.InjOn f (f ⁻¹' ↑v₂.support)) (hv₁₂ : Set.InjOn f (f ⁻¹' ↑(v₁ + v₂).support)) :
comapDomain f (v₁ + v₂) hv₁₂ = comapDomain f v₁ hv₁ + comapDomain f v₂ hv₂ := by
ext
simp only [comapDomain_apply, coe_add, Pi.add_apply]
#align finsupp.comap_domain_add Finsupp.comapDomain_add
/-- A version of `Finsupp.comapDomain_add` that's easier to use. -/
theorem comapDomain_add_of_injective (hf : Function.Injective f) (v₁ v₂ : β →₀ M) :
comapDomain f (v₁ + v₂) hf.injOn =
comapDomain f v₁ hf.injOn + comapDomain f v₂ hf.injOn :=
comapDomain_add _ _ _ _ _
#align finsupp.comap_domain_add_of_injective Finsupp.comapDomain_add_of_injective
/-- `Finsupp.comapDomain` is an `AddMonoidHom`. -/
@[simps]
def comapDomain.addMonoidHom (hf : Function.Injective f) : (β →₀ M) →+ α →₀ M where
toFun x := comapDomain f x hf.injOn
map_zero' := comapDomain_zero f
map_add' := comapDomain_add_of_injective hf
#align finsupp.comap_domain.add_monoid_hom Finsupp.comapDomain.addMonoidHom
end AddZeroClass
variable [AddCommMonoid M] (f : α → β)
theorem mapDomain_comapDomain (hf : Function.Injective f) (l : β →₀ M)
(hl : ↑l.support ⊆ Set.range f) :
mapDomain f (comapDomain f l hf.injOn) = l := by
conv_rhs => rw [← embDomain_comapDomain (f := ⟨f, hf⟩) hl (M := M), embDomain_eq_mapDomain]
rfl
#align finsupp.map_domain_comap_domain Finsupp.mapDomain_comapDomain
end FInjective
end ComapDomain
/-! ### Declarations about finitely supported functions whose support is an `Option` type -/
section Option
/-- Restrict a finitely supported function on `Option α` to a finitely supported function on `α`. -/
def some [Zero M] (f : Option α →₀ M) : α →₀ M :=
f.comapDomain Option.some fun _ => by simp
#align finsupp.some Finsupp.some
@[simp]
theorem some_apply [Zero M] (f : Option α →₀ M) (a : α) : f.some a = f (Option.some a) :=
rfl
#align finsupp.some_apply Finsupp.some_apply
@[simp]
theorem some_zero [Zero M] : (0 : Option α →₀ M).some = 0 := by
ext
simp
#align finsupp.some_zero Finsupp.some_zero
@[simp]
theorem some_add [AddCommMonoid M] (f g : Option α →₀ M) : (f + g).some = f.some + g.some := by
ext
simp
#align finsupp.some_add Finsupp.some_add
@[simp]
theorem some_single_none [Zero M] (m : M) : (single none m : Option α →₀ M).some = 0 := by
ext
simp
#align finsupp.some_single_none Finsupp.some_single_none
@[simp]
| Mathlib/Data/Finsupp/Basic.lean | 830 | 834 | theorem some_single_some [Zero M] (a : α) (m : M) :
(single (Option.some a) m : Option α →₀ M).some = single a m := by |
classical
ext b
simp [single_apply]
|
/-
Copyright (c) 2022 Yaël Dillies, Sara Rousta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Sara Rousta
-/
import Mathlib.Data.SetLike.Basic
import Mathlib.Order.Interval.Set.OrdConnected
import Mathlib.Order.Interval.Set.OrderIso
import Mathlib.Data.Set.Lattice
#align_import order.upper_lower.basic from "leanprover-community/mathlib"@"c0c52abb75074ed8b73a948341f50521fbf43b4c"
/-!
# Up-sets and down-sets
This file defines upper and lower sets in an order.
## Main declarations
* `IsUpperSet`: Predicate for a set to be an upper set. This means every element greater than a
member of the set is in the set itself.
* `IsLowerSet`: Predicate for a set to be a lower set. This means every element less than a member
of the set is in the set itself.
* `UpperSet`: The type of upper sets.
* `LowerSet`: The type of lower sets.
* `upperClosure`: The greatest upper set containing a set.
* `lowerClosure`: The least lower set containing a set.
* `UpperSet.Ici`: Principal upper set. `Set.Ici` as an upper set.
* `UpperSet.Ioi`: Strict principal upper set. `Set.Ioi` as an upper set.
* `LowerSet.Iic`: Principal lower set. `Set.Iic` as a lower set.
* `LowerSet.Iio`: Strict principal lower set. `Set.Iio` as a lower set.
## Notation
* `×ˢ` is notation for `UpperSet.prod` / `LowerSet.prod`.
## Notes
Upper sets are ordered by **reverse** inclusion. This convention is motivated by the fact that this
makes them order-isomorphic to lower sets and antichains, and matches the convention on `Filter`.
## TODO
Lattice structure on antichains. Order equivalence between upper/lower sets and antichains.
-/
open Function OrderDual Set
variable {α β γ : Type*} {ι : Sort*} {κ : ι → Sort*}
/-! ### Unbundled upper/lower sets -/
section LE
variable [LE α] [LE β] {s t : Set α} {a : α}
/-- An upper set in an order `α` is a set such that any element greater than one of its members is
also a member. Also called up-set, upward-closed set. -/
@[aesop norm unfold]
def IsUpperSet (s : Set α) : Prop :=
∀ ⦃a b : α⦄, a ≤ b → a ∈ s → b ∈ s
#align is_upper_set IsUpperSet
/-- A lower set in an order `α` is a set such that any element less than one of its members is also
a member. Also called down-set, downward-closed set. -/
@[aesop norm unfold]
def IsLowerSet (s : Set α) : Prop :=
∀ ⦃a b : α⦄, b ≤ a → a ∈ s → b ∈ s
#align is_lower_set IsLowerSet
theorem isUpperSet_empty : IsUpperSet (∅ : Set α) := fun _ _ _ => id
#align is_upper_set_empty isUpperSet_empty
theorem isLowerSet_empty : IsLowerSet (∅ : Set α) := fun _ _ _ => id
#align is_lower_set_empty isLowerSet_empty
theorem isUpperSet_univ : IsUpperSet (univ : Set α) := fun _ _ _ => id
#align is_upper_set_univ isUpperSet_univ
theorem isLowerSet_univ : IsLowerSet (univ : Set α) := fun _ _ _ => id
#align is_lower_set_univ isLowerSet_univ
theorem IsUpperSet.compl (hs : IsUpperSet s) : IsLowerSet sᶜ := fun _a _b h hb ha => hb <| hs h ha
#align is_upper_set.compl IsUpperSet.compl
theorem IsLowerSet.compl (hs : IsLowerSet s) : IsUpperSet sᶜ := fun _a _b h hb ha => hb <| hs h ha
#align is_lower_set.compl IsLowerSet.compl
@[simp]
theorem isUpperSet_compl : IsUpperSet sᶜ ↔ IsLowerSet s :=
⟨fun h => by
convert h.compl
rw [compl_compl], IsLowerSet.compl⟩
#align is_upper_set_compl isUpperSet_compl
@[simp]
theorem isLowerSet_compl : IsLowerSet sᶜ ↔ IsUpperSet s :=
⟨fun h => by
convert h.compl
rw [compl_compl], IsUpperSet.compl⟩
#align is_lower_set_compl isLowerSet_compl
theorem IsUpperSet.union (hs : IsUpperSet s) (ht : IsUpperSet t) : IsUpperSet (s ∪ t) :=
fun _ _ h => Or.imp (hs h) (ht h)
#align is_upper_set.union IsUpperSet.union
theorem IsLowerSet.union (hs : IsLowerSet s) (ht : IsLowerSet t) : IsLowerSet (s ∪ t) :=
fun _ _ h => Or.imp (hs h) (ht h)
#align is_lower_set.union IsLowerSet.union
theorem IsUpperSet.inter (hs : IsUpperSet s) (ht : IsUpperSet t) : IsUpperSet (s ∩ t) :=
fun _ _ h => And.imp (hs h) (ht h)
#align is_upper_set.inter IsUpperSet.inter
theorem IsLowerSet.inter (hs : IsLowerSet s) (ht : IsLowerSet t) : IsLowerSet (s ∩ t) :=
fun _ _ h => And.imp (hs h) (ht h)
#align is_lower_set.inter IsLowerSet.inter
theorem isUpperSet_sUnion {S : Set (Set α)} (hf : ∀ s ∈ S, IsUpperSet s) : IsUpperSet (⋃₀ S) :=
fun _ _ h => Exists.imp fun _ hs => ⟨hs.1, hf _ hs.1 h hs.2⟩
#align is_upper_set_sUnion isUpperSet_sUnion
theorem isLowerSet_sUnion {S : Set (Set α)} (hf : ∀ s ∈ S, IsLowerSet s) : IsLowerSet (⋃₀ S) :=
fun _ _ h => Exists.imp fun _ hs => ⟨hs.1, hf _ hs.1 h hs.2⟩
#align is_lower_set_sUnion isLowerSet_sUnion
theorem isUpperSet_iUnion {f : ι → Set α} (hf : ∀ i, IsUpperSet (f i)) : IsUpperSet (⋃ i, f i) :=
isUpperSet_sUnion <| forall_mem_range.2 hf
#align is_upper_set_Union isUpperSet_iUnion
theorem isLowerSet_iUnion {f : ι → Set α} (hf : ∀ i, IsLowerSet (f i)) : IsLowerSet (⋃ i, f i) :=
isLowerSet_sUnion <| forall_mem_range.2 hf
#align is_lower_set_Union isLowerSet_iUnion
theorem isUpperSet_iUnion₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsUpperSet (f i j)) :
IsUpperSet (⋃ (i) (j), f i j) :=
isUpperSet_iUnion fun i => isUpperSet_iUnion <| hf i
#align is_upper_set_Union₂ isUpperSet_iUnion₂
theorem isLowerSet_iUnion₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsLowerSet (f i j)) :
IsLowerSet (⋃ (i) (j), f i j) :=
isLowerSet_iUnion fun i => isLowerSet_iUnion <| hf i
#align is_lower_set_Union₂ isLowerSet_iUnion₂
theorem isUpperSet_sInter {S : Set (Set α)} (hf : ∀ s ∈ S, IsUpperSet s) : IsUpperSet (⋂₀ S) :=
fun _ _ h => forall₂_imp fun s hs => hf s hs h
#align is_upper_set_sInter isUpperSet_sInter
theorem isLowerSet_sInter {S : Set (Set α)} (hf : ∀ s ∈ S, IsLowerSet s) : IsLowerSet (⋂₀ S) :=
fun _ _ h => forall₂_imp fun s hs => hf s hs h
#align is_lower_set_sInter isLowerSet_sInter
theorem isUpperSet_iInter {f : ι → Set α} (hf : ∀ i, IsUpperSet (f i)) : IsUpperSet (⋂ i, f i) :=
isUpperSet_sInter <| forall_mem_range.2 hf
#align is_upper_set_Inter isUpperSet_iInter
theorem isLowerSet_iInter {f : ι → Set α} (hf : ∀ i, IsLowerSet (f i)) : IsLowerSet (⋂ i, f i) :=
isLowerSet_sInter <| forall_mem_range.2 hf
#align is_lower_set_Inter isLowerSet_iInter
theorem isUpperSet_iInter₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsUpperSet (f i j)) :
IsUpperSet (⋂ (i) (j), f i j) :=
isUpperSet_iInter fun i => isUpperSet_iInter <| hf i
#align is_upper_set_Inter₂ isUpperSet_iInter₂
theorem isLowerSet_iInter₂ {f : ∀ i, κ i → Set α} (hf : ∀ i j, IsLowerSet (f i j)) :
IsLowerSet (⋂ (i) (j), f i j) :=
isLowerSet_iInter fun i => isLowerSet_iInter <| hf i
#align is_lower_set_Inter₂ isLowerSet_iInter₂
@[simp]
theorem isLowerSet_preimage_ofDual_iff : IsLowerSet (ofDual ⁻¹' s) ↔ IsUpperSet s :=
Iff.rfl
#align is_lower_set_preimage_of_dual_iff isLowerSet_preimage_ofDual_iff
@[simp]
theorem isUpperSet_preimage_ofDual_iff : IsUpperSet (ofDual ⁻¹' s) ↔ IsLowerSet s :=
Iff.rfl
#align is_upper_set_preimage_of_dual_iff isUpperSet_preimage_ofDual_iff
@[simp]
theorem isLowerSet_preimage_toDual_iff {s : Set αᵒᵈ} : IsLowerSet (toDual ⁻¹' s) ↔ IsUpperSet s :=
Iff.rfl
#align is_lower_set_preimage_to_dual_iff isLowerSet_preimage_toDual_iff
@[simp]
theorem isUpperSet_preimage_toDual_iff {s : Set αᵒᵈ} : IsUpperSet (toDual ⁻¹' s) ↔ IsLowerSet s :=
Iff.rfl
#align is_upper_set_preimage_to_dual_iff isUpperSet_preimage_toDual_iff
alias ⟨_, IsUpperSet.toDual⟩ := isLowerSet_preimage_ofDual_iff
#align is_upper_set.to_dual IsUpperSet.toDual
alias ⟨_, IsLowerSet.toDual⟩ := isUpperSet_preimage_ofDual_iff
#align is_lower_set.to_dual IsLowerSet.toDual
alias ⟨_, IsUpperSet.ofDual⟩ := isLowerSet_preimage_toDual_iff
#align is_upper_set.of_dual IsUpperSet.ofDual
alias ⟨_, IsLowerSet.ofDual⟩ := isUpperSet_preimage_toDual_iff
#align is_lower_set.of_dual IsLowerSet.ofDual
lemma IsUpperSet.isLowerSet_preimage_coe (hs : IsUpperSet s) :
IsLowerSet ((↑) ⁻¹' t : Set s) ↔ ∀ b ∈ s, ∀ c ∈ t, b ≤ c → b ∈ t := by aesop
lemma IsLowerSet.isUpperSet_preimage_coe (hs : IsLowerSet s) :
IsUpperSet ((↑) ⁻¹' t : Set s) ↔ ∀ b ∈ s, ∀ c ∈ t, c ≤ b → b ∈ t := by aesop
lemma IsUpperSet.sdiff (hs : IsUpperSet s) (ht : ∀ b ∈ s, ∀ c ∈ t, b ≤ c → b ∈ t) :
IsUpperSet (s \ t) :=
fun _b _c hbc hb ↦ ⟨hs hbc hb.1, fun hc ↦ hb.2 <| ht _ hb.1 _ hc hbc⟩
lemma IsLowerSet.sdiff (hs : IsLowerSet s) (ht : ∀ b ∈ s, ∀ c ∈ t, c ≤ b → b ∈ t) :
IsLowerSet (s \ t) :=
fun _b _c hcb hb ↦ ⟨hs hcb hb.1, fun hc ↦ hb.2 <| ht _ hb.1 _ hc hcb⟩
lemma IsUpperSet.sdiff_of_isLowerSet (hs : IsUpperSet s) (ht : IsLowerSet t) : IsUpperSet (s \ t) :=
hs.sdiff <| by aesop
lemma IsLowerSet.sdiff_of_isUpperSet (hs : IsLowerSet s) (ht : IsUpperSet t) : IsLowerSet (s \ t) :=
hs.sdiff <| by aesop
lemma IsUpperSet.erase (hs : IsUpperSet s) (has : ∀ b ∈ s, b ≤ a → b = a) : IsUpperSet (s \ {a}) :=
hs.sdiff <| by simpa using has
lemma IsLowerSet.erase (hs : IsLowerSet s) (has : ∀ b ∈ s, a ≤ b → b = a) : IsLowerSet (s \ {a}) :=
hs.sdiff <| by simpa using has
end LE
section Preorder
variable [Preorder α] [Preorder β] {s : Set α} {p : α → Prop} (a : α)
theorem isUpperSet_Ici : IsUpperSet (Ici a) := fun _ _ => ge_trans
#align is_upper_set_Ici isUpperSet_Ici
theorem isLowerSet_Iic : IsLowerSet (Iic a) := fun _ _ => le_trans
#align is_lower_set_Iic isLowerSet_Iic
theorem isUpperSet_Ioi : IsUpperSet (Ioi a) := fun _ _ => flip lt_of_lt_of_le
#align is_upper_set_Ioi isUpperSet_Ioi
theorem isLowerSet_Iio : IsLowerSet (Iio a) := fun _ _ => lt_of_le_of_lt
#align is_lower_set_Iio isLowerSet_Iio
theorem isUpperSet_iff_Ici_subset : IsUpperSet s ↔ ∀ ⦃a⦄, a ∈ s → Ici a ⊆ s := by
simp [IsUpperSet, subset_def, @forall_swap (_ ∈ s)]
#align is_upper_set_iff_Ici_subset isUpperSet_iff_Ici_subset
theorem isLowerSet_iff_Iic_subset : IsLowerSet s ↔ ∀ ⦃a⦄, a ∈ s → Iic a ⊆ s := by
simp [IsLowerSet, subset_def, @forall_swap (_ ∈ s)]
#align is_lower_set_iff_Iic_subset isLowerSet_iff_Iic_subset
alias ⟨IsUpperSet.Ici_subset, _⟩ := isUpperSet_iff_Ici_subset
#align is_upper_set.Ici_subset IsUpperSet.Ici_subset
alias ⟨IsLowerSet.Iic_subset, _⟩ := isLowerSet_iff_Iic_subset
#align is_lower_set.Iic_subset IsLowerSet.Iic_subset
theorem IsUpperSet.Ioi_subset (h : IsUpperSet s) ⦃a⦄ (ha : a ∈ s) : Ioi a ⊆ s :=
Ioi_subset_Ici_self.trans <| h.Ici_subset ha
#align is_upper_set.Ioi_subset IsUpperSet.Ioi_subset
theorem IsLowerSet.Iio_subset (h : IsLowerSet s) ⦃a⦄ (ha : a ∈ s) : Iio a ⊆ s :=
h.toDual.Ioi_subset ha
#align is_lower_set.Iio_subset IsLowerSet.Iio_subset
theorem IsUpperSet.ordConnected (h : IsUpperSet s) : s.OrdConnected :=
⟨fun _ ha _ _ => Icc_subset_Ici_self.trans <| h.Ici_subset ha⟩
#align is_upper_set.ord_connected IsUpperSet.ordConnected
theorem IsLowerSet.ordConnected (h : IsLowerSet s) : s.OrdConnected :=
⟨fun _ _ _ hb => Icc_subset_Iic_self.trans <| h.Iic_subset hb⟩
#align is_lower_set.ord_connected IsLowerSet.ordConnected
theorem IsUpperSet.preimage (hs : IsUpperSet s) {f : β → α} (hf : Monotone f) :
IsUpperSet (f ⁻¹' s : Set β) := fun _ _ h => hs <| hf h
#align is_upper_set.preimage IsUpperSet.preimage
theorem IsLowerSet.preimage (hs : IsLowerSet s) {f : β → α} (hf : Monotone f) :
IsLowerSet (f ⁻¹' s : Set β) := fun _ _ h => hs <| hf h
#align is_lower_set.preimage IsLowerSet.preimage
theorem IsUpperSet.image (hs : IsUpperSet s) (f : α ≃o β) : IsUpperSet (f '' s : Set β) := by
change IsUpperSet ((f : α ≃ β) '' s)
rw [Set.image_equiv_eq_preimage_symm]
exact hs.preimage f.symm.monotone
#align is_upper_set.image IsUpperSet.image
theorem IsLowerSet.image (hs : IsLowerSet s) (f : α ≃o β) : IsLowerSet (f '' s : Set β) := by
change IsLowerSet ((f : α ≃ β) '' s)
rw [Set.image_equiv_eq_preimage_symm]
exact hs.preimage f.symm.monotone
#align is_lower_set.image IsLowerSet.image
theorem OrderEmbedding.image_Ici (e : α ↪o β) (he : IsUpperSet (range e)) (a : α) :
e '' Ici a = Ici (e a) := by
rw [← e.preimage_Ici, image_preimage_eq_inter_range,
inter_eq_left.2 <| he.Ici_subset (mem_range_self _)]
theorem OrderEmbedding.image_Iic (e : α ↪o β) (he : IsLowerSet (range e)) (a : α) :
e '' Iic a = Iic (e a) :=
e.dual.image_Ici he a
theorem OrderEmbedding.image_Ioi (e : α ↪o β) (he : IsUpperSet (range e)) (a : α) :
e '' Ioi a = Ioi (e a) := by
rw [← e.preimage_Ioi, image_preimage_eq_inter_range,
inter_eq_left.2 <| he.Ioi_subset (mem_range_self _)]
theorem OrderEmbedding.image_Iio (e : α ↪o β) (he : IsLowerSet (range e)) (a : α) :
e '' Iio a = Iio (e a) :=
e.dual.image_Ioi he a
@[simp]
theorem Set.monotone_mem : Monotone (· ∈ s) ↔ IsUpperSet s :=
Iff.rfl
#align set.monotone_mem Set.monotone_mem
@[simp]
theorem Set.antitone_mem : Antitone (· ∈ s) ↔ IsLowerSet s :=
forall_swap
#align set.antitone_mem Set.antitone_mem
@[simp]
theorem isUpperSet_setOf : IsUpperSet { a | p a } ↔ Monotone p :=
Iff.rfl
#align is_upper_set_set_of isUpperSet_setOf
@[simp]
theorem isLowerSet_setOf : IsLowerSet { a | p a } ↔ Antitone p :=
forall_swap
#align is_lower_set_set_of isLowerSet_setOf
lemma IsUpperSet.upperBounds_subset (hs : IsUpperSet s) : s.Nonempty → upperBounds s ⊆ s :=
fun ⟨_a, ha⟩ _b hb ↦ hs (hb ha) ha
lemma IsLowerSet.lowerBounds_subset (hs : IsLowerSet s) : s.Nonempty → lowerBounds s ⊆ s :=
fun ⟨_a, ha⟩ _b hb ↦ hs (hb ha) ha
section OrderTop
variable [OrderTop α]
theorem IsLowerSet.top_mem (hs : IsLowerSet s) : ⊤ ∈ s ↔ s = univ :=
⟨fun h => eq_univ_of_forall fun _ => hs le_top h, fun h => h.symm ▸ mem_univ _⟩
#align is_lower_set.top_mem IsLowerSet.top_mem
theorem IsUpperSet.top_mem (hs : IsUpperSet s) : ⊤ ∈ s ↔ s.Nonempty :=
⟨fun h => ⟨_, h⟩, fun ⟨_a, ha⟩ => hs le_top ha⟩
#align is_upper_set.top_mem IsUpperSet.top_mem
theorem IsUpperSet.not_top_mem (hs : IsUpperSet s) : ⊤ ∉ s ↔ s = ∅ :=
hs.top_mem.not.trans not_nonempty_iff_eq_empty
#align is_upper_set.not_top_mem IsUpperSet.not_top_mem
end OrderTop
section OrderBot
variable [OrderBot α]
theorem IsUpperSet.bot_mem (hs : IsUpperSet s) : ⊥ ∈ s ↔ s = univ :=
⟨fun h => eq_univ_of_forall fun _ => hs bot_le h, fun h => h.symm ▸ mem_univ _⟩
#align is_upper_set.bot_mem IsUpperSet.bot_mem
theorem IsLowerSet.bot_mem (hs : IsLowerSet s) : ⊥ ∈ s ↔ s.Nonempty :=
⟨fun h => ⟨_, h⟩, fun ⟨_a, ha⟩ => hs bot_le ha⟩
#align is_lower_set.bot_mem IsLowerSet.bot_mem
theorem IsLowerSet.not_bot_mem (hs : IsLowerSet s) : ⊥ ∉ s ↔ s = ∅ :=
hs.bot_mem.not.trans not_nonempty_iff_eq_empty
#align is_lower_set.not_bot_mem IsLowerSet.not_bot_mem
end OrderBot
section NoMaxOrder
variable [NoMaxOrder α]
theorem IsUpperSet.not_bddAbove (hs : IsUpperSet s) : s.Nonempty → ¬BddAbove s := by
rintro ⟨a, ha⟩ ⟨b, hb⟩
obtain ⟨c, hc⟩ := exists_gt b
exact hc.not_le (hb <| hs ((hb ha).trans hc.le) ha)
#align is_upper_set.not_bdd_above IsUpperSet.not_bddAbove
theorem not_bddAbove_Ici : ¬BddAbove (Ici a) :=
(isUpperSet_Ici _).not_bddAbove nonempty_Ici
#align not_bdd_above_Ici not_bddAbove_Ici
theorem not_bddAbove_Ioi : ¬BddAbove (Ioi a) :=
(isUpperSet_Ioi _).not_bddAbove nonempty_Ioi
#align not_bdd_above_Ioi not_bddAbove_Ioi
end NoMaxOrder
section NoMinOrder
variable [NoMinOrder α]
theorem IsLowerSet.not_bddBelow (hs : IsLowerSet s) : s.Nonempty → ¬BddBelow s := by
rintro ⟨a, ha⟩ ⟨b, hb⟩
obtain ⟨c, hc⟩ := exists_lt b
exact hc.not_le (hb <| hs (hc.le.trans <| hb ha) ha)
#align is_lower_set.not_bdd_below IsLowerSet.not_bddBelow
theorem not_bddBelow_Iic : ¬BddBelow (Iic a) :=
(isLowerSet_Iic _).not_bddBelow nonempty_Iic
#align not_bdd_below_Iic not_bddBelow_Iic
theorem not_bddBelow_Iio : ¬BddBelow (Iio a) :=
(isLowerSet_Iio _).not_bddBelow nonempty_Iio
#align not_bdd_below_Iio not_bddBelow_Iio
end NoMinOrder
end Preorder
section PartialOrder
variable [PartialOrder α] {s : Set α}
theorem isUpperSet_iff_forall_lt : IsUpperSet s ↔ ∀ ⦃a b : α⦄, a < b → a ∈ s → b ∈ s :=
forall_congr' fun a => by simp [le_iff_eq_or_lt, or_imp, forall_and]
#align is_upper_set_iff_forall_lt isUpperSet_iff_forall_lt
theorem isLowerSet_iff_forall_lt : IsLowerSet s ↔ ∀ ⦃a b : α⦄, b < a → a ∈ s → b ∈ s :=
forall_congr' fun a => by simp [le_iff_eq_or_lt, or_imp, forall_and]
#align is_lower_set_iff_forall_lt isLowerSet_iff_forall_lt
theorem isUpperSet_iff_Ioi_subset : IsUpperSet s ↔ ∀ ⦃a⦄, a ∈ s → Ioi a ⊆ s := by
simp [isUpperSet_iff_forall_lt, subset_def, @forall_swap (_ ∈ s)]
#align is_upper_set_iff_Ioi_subset isUpperSet_iff_Ioi_subset
theorem isLowerSet_iff_Iio_subset : IsLowerSet s ↔ ∀ ⦃a⦄, a ∈ s → Iio a ⊆ s := by
simp [isLowerSet_iff_forall_lt, subset_def, @forall_swap (_ ∈ s)]
#align is_lower_set_iff_Iio_subset isLowerSet_iff_Iio_subset
end PartialOrder
section LinearOrder
variable [LinearOrder α] {s t : Set α}
theorem IsUpperSet.total (hs : IsUpperSet s) (ht : IsUpperSet t) : s ⊆ t ∨ t ⊆ s := by
by_contra! h
simp_rw [Set.not_subset] at h
obtain ⟨⟨a, has, hat⟩, b, hbt, hbs⟩ := h
obtain hab | hba := le_total a b
· exact hbs (hs hab has)
· exact hat (ht hba hbt)
#align is_upper_set.total IsUpperSet.total
theorem IsLowerSet.total (hs : IsLowerSet s) (ht : IsLowerSet t) : s ⊆ t ∨ t ⊆ s :=
hs.toDual.total ht.toDual
#align is_lower_set.total IsLowerSet.total
end LinearOrder
/-! ### Bundled upper/lower sets -/
section LE
variable [LE α]
/-- The type of upper sets of an order. -/
structure UpperSet (α : Type*) [LE α] where
/-- The carrier of an `UpperSet`. -/
carrier : Set α
/-- The carrier of an `UpperSet` is an upper set. -/
upper' : IsUpperSet carrier
#align upper_set UpperSet
/-- The type of lower sets of an order. -/
structure LowerSet (α : Type*) [LE α] where
/-- The carrier of a `LowerSet`. -/
carrier : Set α
/-- The carrier of a `LowerSet` is a lower set. -/
lower' : IsLowerSet carrier
#align lower_set LowerSet
namespace UpperSet
instance : SetLike (UpperSet α) α where
coe := UpperSet.carrier
coe_injective' s t h := by cases s; cases t; congr
/-- See Note [custom simps projection]. -/
def Simps.coe (s : UpperSet α) : Set α := s
initialize_simps_projections UpperSet (carrier → coe)
@[ext]
theorem ext {s t : UpperSet α} : (s : Set α) = t → s = t :=
SetLike.ext'
#align upper_set.ext UpperSet.ext
@[simp]
theorem carrier_eq_coe (s : UpperSet α) : s.carrier = s :=
rfl
#align upper_set.carrier_eq_coe UpperSet.carrier_eq_coe
@[simp] protected lemma upper (s : UpperSet α) : IsUpperSet (s : Set α) := s.upper'
#align upper_set.upper UpperSet.upper
@[simp, norm_cast] lemma coe_mk (s : Set α) (hs) : mk s hs = s := rfl
@[simp] lemma mem_mk {s : Set α} (hs) {a : α} : a ∈ mk s hs ↔ a ∈ s := Iff.rfl
#align upper_set.mem_mk UpperSet.mem_mk
end UpperSet
namespace LowerSet
instance : SetLike (LowerSet α) α where
coe := LowerSet.carrier
coe_injective' s t h := by cases s; cases t; congr
/-- See Note [custom simps projection]. -/
def Simps.coe (s : LowerSet α) : Set α := s
initialize_simps_projections LowerSet (carrier → coe)
@[ext]
theorem ext {s t : LowerSet α} : (s : Set α) = t → s = t :=
SetLike.ext'
#align lower_set.ext LowerSet.ext
@[simp]
theorem carrier_eq_coe (s : LowerSet α) : s.carrier = s :=
rfl
#align lower_set.carrier_eq_coe LowerSet.carrier_eq_coe
@[simp] protected lemma lower (s : LowerSet α) : IsLowerSet (s : Set α) := s.lower'
#align lower_set.lower LowerSet.lower
@[simp, norm_cast] lemma coe_mk (s : Set α) (hs) : mk s hs = s := rfl
@[simp] lemma mem_mk {s : Set α} (hs) {a : α} : a ∈ mk s hs ↔ a ∈ s := Iff.rfl
#align lower_set.mem_mk LowerSet.mem_mk
end LowerSet
/-! #### Order -/
namespace UpperSet
variable {S : Set (UpperSet α)} {s t : UpperSet α} {a : α}
instance : Sup (UpperSet α) :=
⟨fun s t => ⟨s ∩ t, s.upper.inter t.upper⟩⟩
instance : Inf (UpperSet α) :=
⟨fun s t => ⟨s ∪ t, s.upper.union t.upper⟩⟩
instance : Top (UpperSet α) :=
⟨⟨∅, isUpperSet_empty⟩⟩
instance : Bot (UpperSet α) :=
⟨⟨univ, isUpperSet_univ⟩⟩
instance : SupSet (UpperSet α) :=
⟨fun S => ⟨⋂ s ∈ S, ↑s, isUpperSet_iInter₂ fun s _ => s.upper⟩⟩
instance : InfSet (UpperSet α) :=
⟨fun S => ⟨⋃ s ∈ S, ↑s, isUpperSet_iUnion₂ fun s _ => s.upper⟩⟩
instance completelyDistribLattice : CompletelyDistribLattice (UpperSet α) :=
(toDual.injective.comp SetLike.coe_injective).completelyDistribLattice _ (fun _ _ => rfl)
(fun _ _ => rfl) (fun _ => rfl) (fun _ => rfl) rfl rfl
instance : Inhabited (UpperSet α) :=
⟨⊥⟩
@[simp 1100, norm_cast]
theorem coe_subset_coe : (s : Set α) ⊆ t ↔ t ≤ s :=
Iff.rfl
#align upper_set.coe_subset_coe UpperSet.coe_subset_coe
@[simp 1100, norm_cast] lemma coe_ssubset_coe : (s : Set α) ⊂ t ↔ t < s := Iff.rfl
@[simp, norm_cast]
theorem coe_top : ((⊤ : UpperSet α) : Set α) = ∅ :=
rfl
#align upper_set.coe_top UpperSet.coe_top
@[simp, norm_cast]
theorem coe_bot : ((⊥ : UpperSet α) : Set α) = univ :=
rfl
#align upper_set.coe_bot UpperSet.coe_bot
@[simp, norm_cast]
theorem coe_eq_univ : (s : Set α) = univ ↔ s = ⊥ := by simp [SetLike.ext'_iff]
#align upper_set.coe_eq_univ UpperSet.coe_eq_univ
@[simp, norm_cast]
theorem coe_eq_empty : (s : Set α) = ∅ ↔ s = ⊤ := by simp [SetLike.ext'_iff]
#align upper_set.coe_eq_empty UpperSet.coe_eq_empty
@[simp, norm_cast] lemma coe_nonempty : (s : Set α).Nonempty ↔ s ≠ ⊤ :=
nonempty_iff_ne_empty.trans coe_eq_empty.not
@[simp, norm_cast]
theorem coe_sup (s t : UpperSet α) : (↑(s ⊔ t) : Set α) = (s : Set α) ∩ t :=
rfl
#align upper_set.coe_sup UpperSet.coe_sup
@[simp, norm_cast]
theorem coe_inf (s t : UpperSet α) : (↑(s ⊓ t) : Set α) = (s : Set α) ∪ t :=
rfl
#align upper_set.coe_inf UpperSet.coe_inf
@[simp, norm_cast]
theorem coe_sSup (S : Set (UpperSet α)) : (↑(sSup S) : Set α) = ⋂ s ∈ S, ↑s :=
rfl
#align upper_set.coe_Sup UpperSet.coe_sSup
@[simp, norm_cast]
theorem coe_sInf (S : Set (UpperSet α)) : (↑(sInf S) : Set α) = ⋃ s ∈ S, ↑s :=
rfl
#align upper_set.coe_Inf UpperSet.coe_sInf
@[simp, norm_cast]
theorem coe_iSup (f : ι → UpperSet α) : (↑(⨆ i, f i) : Set α) = ⋂ i, f i := by simp [iSup]
#align upper_set.coe_supr UpperSet.coe_iSup
@[simp, norm_cast]
theorem coe_iInf (f : ι → UpperSet α) : (↑(⨅ i, f i) : Set α) = ⋃ i, f i := by simp [iInf]
#align upper_set.coe_infi UpperSet.coe_iInf
@[norm_cast] -- Porting note: no longer a `simp`
theorem coe_iSup₂ (f : ∀ i, κ i → UpperSet α) :
(↑(⨆ (i) (j), f i j) : Set α) = ⋂ (i) (j), f i j := by simp_rw [coe_iSup]
#align upper_set.coe_supr₂ UpperSet.coe_iSup₂
@[norm_cast] -- Porting note: no longer a `simp`
theorem coe_iInf₂ (f : ∀ i, κ i → UpperSet α) :
(↑(⨅ (i) (j), f i j) : Set α) = ⋃ (i) (j), f i j := by simp_rw [coe_iInf]
#align upper_set.coe_infi₂ UpperSet.coe_iInf₂
@[simp]
theorem not_mem_top : a ∉ (⊤ : UpperSet α) :=
id
#align upper_set.not_mem_top UpperSet.not_mem_top
@[simp]
theorem mem_bot : a ∈ (⊥ : UpperSet α) :=
trivial
#align upper_set.mem_bot UpperSet.mem_bot
@[simp]
theorem mem_sup_iff : a ∈ s ⊔ t ↔ a ∈ s ∧ a ∈ t :=
Iff.rfl
#align upper_set.mem_sup_iff UpperSet.mem_sup_iff
@[simp]
theorem mem_inf_iff : a ∈ s ⊓ t ↔ a ∈ s ∨ a ∈ t :=
Iff.rfl
#align upper_set.mem_inf_iff UpperSet.mem_inf_iff
@[simp]
theorem mem_sSup_iff : a ∈ sSup S ↔ ∀ s ∈ S, a ∈ s :=
mem_iInter₂
#align upper_set.mem_Sup_iff UpperSet.mem_sSup_iff
@[simp]
theorem mem_sInf_iff : a ∈ sInf S ↔ ∃ s ∈ S, a ∈ s :=
mem_iUnion₂.trans <| by simp only [exists_prop, SetLike.mem_coe]
#align upper_set.mem_Inf_iff UpperSet.mem_sInf_iff
@[simp]
theorem mem_iSup_iff {f : ι → UpperSet α} : (a ∈ ⨆ i, f i) ↔ ∀ i, a ∈ f i := by
rw [← SetLike.mem_coe, coe_iSup]
exact mem_iInter
#align upper_set.mem_supr_iff UpperSet.mem_iSup_iff
@[simp]
theorem mem_iInf_iff {f : ι → UpperSet α} : (a ∈ ⨅ i, f i) ↔ ∃ i, a ∈ f i := by
rw [← SetLike.mem_coe, coe_iInf]
exact mem_iUnion
#align upper_set.mem_infi_iff UpperSet.mem_iInf_iff
-- Porting note: no longer a @[simp]
theorem mem_iSup₂_iff {f : ∀ i, κ i → UpperSet α} : (a ∈ ⨆ (i) (j), f i j) ↔ ∀ i j, a ∈ f i j := by
simp_rw [mem_iSup_iff]
#align upper_set.mem_supr₂_iff UpperSet.mem_iSup₂_iff
-- Porting note: no longer a @[simp]
theorem mem_iInf₂_iff {f : ∀ i, κ i → UpperSet α} : (a ∈ ⨅ (i) (j), f i j) ↔ ∃ i j, a ∈ f i j := by
simp_rw [mem_iInf_iff]
#align upper_set.mem_infi₂_iff UpperSet.mem_iInf₂_iff
@[simp, norm_cast]
theorem codisjoint_coe : Codisjoint (s : Set α) t ↔ Disjoint s t := by
simp [disjoint_iff, codisjoint_iff, SetLike.ext'_iff]
#align upper_set.codisjoint_coe UpperSet.codisjoint_coe
end UpperSet
namespace LowerSet
variable {S : Set (LowerSet α)} {s t : LowerSet α} {a : α}
instance : Sup (LowerSet α) :=
⟨fun s t => ⟨s ∪ t, fun _ _ h => Or.imp (s.lower h) (t.lower h)⟩⟩
instance : Inf (LowerSet α) :=
⟨fun s t => ⟨s ∩ t, fun _ _ h => And.imp (s.lower h) (t.lower h)⟩⟩
instance : Top (LowerSet α) :=
⟨⟨univ, fun _ _ _ => id⟩⟩
instance : Bot (LowerSet α) :=
⟨⟨∅, fun _ _ _ => id⟩⟩
instance : SupSet (LowerSet α) :=
⟨fun S => ⟨⋃ s ∈ S, ↑s, isLowerSet_iUnion₂ fun s _ => s.lower⟩⟩
instance : InfSet (LowerSet α) :=
⟨fun S => ⟨⋂ s ∈ S, ↑s, isLowerSet_iInter₂ fun s _ => s.lower⟩⟩
instance completelyDistribLattice : CompletelyDistribLattice (LowerSet α) :=
SetLike.coe_injective.completelyDistribLattice _ (fun _ _ => rfl) (fun _ _ => rfl) (fun _ => rfl)
(fun _ => rfl) rfl rfl
instance : Inhabited (LowerSet α) :=
⟨⊥⟩
@[norm_cast] lemma coe_subset_coe : (s : Set α) ⊆ t ↔ s ≤ t := Iff.rfl
#align lower_set.coe_subset_coe LowerSet.coe_subset_coe
@[norm_cast] lemma coe_ssubset_coe : (s : Set α) ⊂ t ↔ s < t := Iff.rfl
@[simp, norm_cast]
theorem coe_top : ((⊤ : LowerSet α) : Set α) = univ :=
rfl
#align lower_set.coe_top LowerSet.coe_top
@[simp, norm_cast]
theorem coe_bot : ((⊥ : LowerSet α) : Set α) = ∅ :=
rfl
#align lower_set.coe_bot LowerSet.coe_bot
@[simp, norm_cast]
theorem coe_eq_univ : (s : Set α) = univ ↔ s = ⊤ := by simp [SetLike.ext'_iff]
#align lower_set.coe_eq_univ LowerSet.coe_eq_univ
@[simp, norm_cast]
theorem coe_eq_empty : (s : Set α) = ∅ ↔ s = ⊥ := by simp [SetLike.ext'_iff]
#align lower_set.coe_eq_empty LowerSet.coe_eq_empty
@[simp, norm_cast] lemma coe_nonempty : (s : Set α).Nonempty ↔ s ≠ ⊥ :=
nonempty_iff_ne_empty.trans coe_eq_empty.not
@[simp, norm_cast]
theorem coe_sup (s t : LowerSet α) : (↑(s ⊔ t) : Set α) = (s : Set α) ∪ t :=
rfl
#align lower_set.coe_sup LowerSet.coe_sup
@[simp, norm_cast]
theorem coe_inf (s t : LowerSet α) : (↑(s ⊓ t) : Set α) = (s : Set α) ∩ t :=
rfl
#align lower_set.coe_inf LowerSet.coe_inf
@[simp, norm_cast]
theorem coe_sSup (S : Set (LowerSet α)) : (↑(sSup S) : Set α) = ⋃ s ∈ S, ↑s :=
rfl
#align lower_set.coe_Sup LowerSet.coe_sSup
@[simp, norm_cast]
theorem coe_sInf (S : Set (LowerSet α)) : (↑(sInf S) : Set α) = ⋂ s ∈ S, ↑s :=
rfl
#align lower_set.coe_Inf LowerSet.coe_sInf
@[simp, norm_cast]
theorem coe_iSup (f : ι → LowerSet α) : (↑(⨆ i, f i) : Set α) = ⋃ i, f i := by
simp_rw [iSup, coe_sSup, mem_range, iUnion_exists, iUnion_iUnion_eq']
#align lower_set.coe_supr LowerSet.coe_iSup
@[simp, norm_cast]
theorem coe_iInf (f : ι → LowerSet α) : (↑(⨅ i, f i) : Set α) = ⋂ i, f i := by
simp_rw [iInf, coe_sInf, mem_range, iInter_exists, iInter_iInter_eq']
#align lower_set.coe_infi LowerSet.coe_iInf
@[norm_cast] -- Porting note: no longer a `simp`
theorem coe_iSup₂ (f : ∀ i, κ i → LowerSet α) :
(↑(⨆ (i) (j), f i j) : Set α) = ⋃ (i) (j), f i j := by simp_rw [coe_iSup]
#align lower_set.coe_supr₂ LowerSet.coe_iSup₂
@[norm_cast] -- Porting note: no longer a `simp`
theorem coe_iInf₂ (f : ∀ i, κ i → LowerSet α) :
(↑(⨅ (i) (j), f i j) : Set α) = ⋂ (i) (j), f i j := by simp_rw [coe_iInf]
#align lower_set.coe_infi₂ LowerSet.coe_iInf₂
@[simp]
theorem mem_top : a ∈ (⊤ : LowerSet α) :=
trivial
#align lower_set.mem_top LowerSet.mem_top
@[simp]
theorem not_mem_bot : a ∉ (⊥ : LowerSet α) :=
id
#align lower_set.not_mem_bot LowerSet.not_mem_bot
@[simp]
theorem mem_sup_iff : a ∈ s ⊔ t ↔ a ∈ s ∨ a ∈ t :=
Iff.rfl
#align lower_set.mem_sup_iff LowerSet.mem_sup_iff
@[simp]
theorem mem_inf_iff : a ∈ s ⊓ t ↔ a ∈ s ∧ a ∈ t :=
Iff.rfl
#align lower_set.mem_inf_iff LowerSet.mem_inf_iff
@[simp]
theorem mem_sSup_iff : a ∈ sSup S ↔ ∃ s ∈ S, a ∈ s :=
mem_iUnion₂.trans <| by simp only [exists_prop, SetLike.mem_coe]
#align lower_set.mem_Sup_iff LowerSet.mem_sSup_iff
@[simp]
theorem mem_sInf_iff : a ∈ sInf S ↔ ∀ s ∈ S, a ∈ s :=
mem_iInter₂
#align lower_set.mem_Inf_iff LowerSet.mem_sInf_iff
@[simp]
theorem mem_iSup_iff {f : ι → LowerSet α} : (a ∈ ⨆ i, f i) ↔ ∃ i, a ∈ f i := by
rw [← SetLike.mem_coe, coe_iSup]
exact mem_iUnion
#align lower_set.mem_supr_iff LowerSet.mem_iSup_iff
@[simp]
theorem mem_iInf_iff {f : ι → LowerSet α} : (a ∈ ⨅ i, f i) ↔ ∀ i, a ∈ f i := by
rw [← SetLike.mem_coe, coe_iInf]
exact mem_iInter
#align lower_set.mem_infi_iff LowerSet.mem_iInf_iff
-- Porting note: no longer a @[simp]
theorem mem_iSup₂_iff {f : ∀ i, κ i → LowerSet α} : (a ∈ ⨆ (i) (j), f i j) ↔ ∃ i j, a ∈ f i j := by
simp_rw [mem_iSup_iff]
#align lower_set.mem_supr₂_iff LowerSet.mem_iSup₂_iff
-- Porting note: no longer a @[simp]
theorem mem_iInf₂_iff {f : ∀ i, κ i → LowerSet α} : (a ∈ ⨅ (i) (j), f i j) ↔ ∀ i j, a ∈ f i j := by
simp_rw [mem_iInf_iff]
#align lower_set.mem_infi₂_iff LowerSet.mem_iInf₂_iff
@[simp, norm_cast]
theorem disjoint_coe : Disjoint (s : Set α) t ↔ Disjoint s t := by
simp [disjoint_iff, SetLike.ext'_iff]
#align lower_set.disjoint_coe LowerSet.disjoint_coe
end LowerSet
/-! #### Complement -/
/-- The complement of a lower set as an upper set. -/
def UpperSet.compl (s : UpperSet α) : LowerSet α :=
⟨sᶜ, s.upper.compl⟩
#align upper_set.compl UpperSet.compl
/-- The complement of a lower set as an upper set. -/
def LowerSet.compl (s : LowerSet α) : UpperSet α :=
⟨sᶜ, s.lower.compl⟩
#align lower_set.compl LowerSet.compl
namespace UpperSet
variable {s t : UpperSet α} {a : α}
@[simp]
theorem coe_compl (s : UpperSet α) : (s.compl : Set α) = (↑s)ᶜ :=
rfl
#align upper_set.coe_compl UpperSet.coe_compl
@[simp]
theorem mem_compl_iff : a ∈ s.compl ↔ a ∉ s :=
Iff.rfl
#align upper_set.mem_compl_iff UpperSet.mem_compl_iff
@[simp]
nonrec theorem compl_compl (s : UpperSet α) : s.compl.compl = s :=
UpperSet.ext <| compl_compl _
#align upper_set.compl_compl UpperSet.compl_compl
@[simp]
theorem compl_le_compl : s.compl ≤ t.compl ↔ s ≤ t :=
compl_subset_compl
#align upper_set.compl_le_compl UpperSet.compl_le_compl
@[simp]
protected theorem compl_sup (s t : UpperSet α) : (s ⊔ t).compl = s.compl ⊔ t.compl :=
LowerSet.ext compl_inf
#align upper_set.compl_sup UpperSet.compl_sup
@[simp]
protected theorem compl_inf (s t : UpperSet α) : (s ⊓ t).compl = s.compl ⊓ t.compl :=
LowerSet.ext compl_sup
#align upper_set.compl_inf UpperSet.compl_inf
@[simp]
protected theorem compl_top : (⊤ : UpperSet α).compl = ⊤ :=
LowerSet.ext compl_empty
#align upper_set.compl_top UpperSet.compl_top
@[simp]
protected theorem compl_bot : (⊥ : UpperSet α).compl = ⊥ :=
LowerSet.ext compl_univ
#align upper_set.compl_bot UpperSet.compl_bot
@[simp]
protected theorem compl_sSup (S : Set (UpperSet α)) : (sSup S).compl = ⨆ s ∈ S, UpperSet.compl s :=
LowerSet.ext <| by simp only [coe_compl, coe_sSup, compl_iInter₂, LowerSet.coe_iSup₂]
#align upper_set.compl_Sup UpperSet.compl_sSup
@[simp]
protected theorem compl_sInf (S : Set (UpperSet α)) : (sInf S).compl = ⨅ s ∈ S, UpperSet.compl s :=
LowerSet.ext <| by simp only [coe_compl, coe_sInf, compl_iUnion₂, LowerSet.coe_iInf₂]
#align upper_set.compl_Inf UpperSet.compl_sInf
@[simp]
protected theorem compl_iSup (f : ι → UpperSet α) : (⨆ i, f i).compl = ⨆ i, (f i).compl :=
LowerSet.ext <| by simp only [coe_compl, coe_iSup, compl_iInter, LowerSet.coe_iSup]
#align upper_set.compl_supr UpperSet.compl_iSup
@[simp]
protected theorem compl_iInf (f : ι → UpperSet α) : (⨅ i, f i).compl = ⨅ i, (f i).compl :=
LowerSet.ext <| by simp only [coe_compl, coe_iInf, compl_iUnion, LowerSet.coe_iInf]
#align upper_set.compl_infi UpperSet.compl_iInf
-- Porting note: no longer a @[simp]
theorem compl_iSup₂ (f : ∀ i, κ i → UpperSet α) :
(⨆ (i) (j), f i j).compl = ⨆ (i) (j), (f i j).compl := by simp_rw [UpperSet.compl_iSup]
#align upper_set.compl_supr₂ UpperSet.compl_iSup₂
-- Porting note: no longer a @[simp]
theorem compl_iInf₂ (f : ∀ i, κ i → UpperSet α) :
(⨅ (i) (j), f i j).compl = ⨅ (i) (j), (f i j).compl := by simp_rw [UpperSet.compl_iInf]
#align upper_set.compl_infi₂ UpperSet.compl_iInf₂
end UpperSet
namespace LowerSet
variable {s t : LowerSet α} {a : α}
@[simp]
theorem coe_compl (s : LowerSet α) : (s.compl : Set α) = (↑s)ᶜ :=
rfl
#align lower_set.coe_compl LowerSet.coe_compl
@[simp]
theorem mem_compl_iff : a ∈ s.compl ↔ a ∉ s :=
Iff.rfl
#align lower_set.mem_compl_iff LowerSet.mem_compl_iff
@[simp]
nonrec theorem compl_compl (s : LowerSet α) : s.compl.compl = s :=
LowerSet.ext <| compl_compl _
#align lower_set.compl_compl LowerSet.compl_compl
@[simp]
theorem compl_le_compl : s.compl ≤ t.compl ↔ s ≤ t :=
compl_subset_compl
#align lower_set.compl_le_compl LowerSet.compl_le_compl
protected theorem compl_sup (s t : LowerSet α) : (s ⊔ t).compl = s.compl ⊔ t.compl :=
UpperSet.ext compl_sup
#align lower_set.compl_sup LowerSet.compl_sup
protected theorem compl_inf (s t : LowerSet α) : (s ⊓ t).compl = s.compl ⊓ t.compl :=
UpperSet.ext compl_inf
#align lower_set.compl_inf LowerSet.compl_inf
protected theorem compl_top : (⊤ : LowerSet α).compl = ⊤ :=
UpperSet.ext compl_univ
#align lower_set.compl_top LowerSet.compl_top
protected theorem compl_bot : (⊥ : LowerSet α).compl = ⊥ :=
UpperSet.ext compl_empty
#align lower_set.compl_bot LowerSet.compl_bot
protected theorem compl_sSup (S : Set (LowerSet α)) : (sSup S).compl = ⨆ s ∈ S, LowerSet.compl s :=
UpperSet.ext <| by simp only [coe_compl, coe_sSup, compl_iUnion₂, UpperSet.coe_iSup₂]
#align lower_set.compl_Sup LowerSet.compl_sSup
protected theorem compl_sInf (S : Set (LowerSet α)) : (sInf S).compl = ⨅ s ∈ S, LowerSet.compl s :=
UpperSet.ext <| by simp only [coe_compl, coe_sInf, compl_iInter₂, UpperSet.coe_iInf₂]
#align lower_set.compl_Inf LowerSet.compl_sInf
protected theorem compl_iSup (f : ι → LowerSet α) : (⨆ i, f i).compl = ⨆ i, (f i).compl :=
UpperSet.ext <| by simp only [coe_compl, coe_iSup, compl_iUnion, UpperSet.coe_iSup]
#align lower_set.compl_supr LowerSet.compl_iSup
protected theorem compl_iInf (f : ι → LowerSet α) : (⨅ i, f i).compl = ⨅ i, (f i).compl :=
UpperSet.ext <| by simp only [coe_compl, coe_iInf, compl_iInter, UpperSet.coe_iInf]
#align lower_set.compl_infi LowerSet.compl_iInf
@[simp]
theorem compl_iSup₂ (f : ∀ i, κ i → LowerSet α) :
(⨆ (i) (j), f i j).compl = ⨆ (i) (j), (f i j).compl := by simp_rw [LowerSet.compl_iSup]
#align lower_set.compl_supr₂ LowerSet.compl_iSup₂
@[simp]
theorem compl_iInf₂ (f : ∀ i, κ i → LowerSet α) :
(⨅ (i) (j), f i j).compl = ⨅ (i) (j), (f i j).compl := by simp_rw [LowerSet.compl_iInf]
#align lower_set.compl_infi₂ LowerSet.compl_iInf₂
end LowerSet
/-- Upper sets are order-isomorphic to lower sets under complementation. -/
@[simps]
def upperSetIsoLowerSet : UpperSet α ≃o LowerSet α where
toFun := UpperSet.compl
invFun := LowerSet.compl
left_inv := UpperSet.compl_compl
right_inv := LowerSet.compl_compl
map_rel_iff' := UpperSet.compl_le_compl
#align upper_set_iso_lower_set upperSetIsoLowerSet
end LE
section LinearOrder
variable [LinearOrder α]
instance UpperSet.isTotal_le : IsTotal (UpperSet α) (· ≤ ·) := ⟨fun s t => t.upper.total s.upper⟩
#align upper_set.is_total_le UpperSet.isTotal_le
instance LowerSet.isTotal_le : IsTotal (LowerSet α) (· ≤ ·) := ⟨fun s t => s.lower.total t.lower⟩
#align lower_set.is_total_le LowerSet.isTotal_le
noncomputable instance : CompleteLinearOrder (UpperSet α) :=
{ UpperSet.completelyDistribLattice with
le_total := IsTotal.total
decidableLE := Classical.decRel _
decidableEq := Classical.decRel _
decidableLT := Classical.decRel _ }
noncomputable instance : CompleteLinearOrder (LowerSet α) :=
{ LowerSet.completelyDistribLattice with
le_total := IsTotal.total
decidableLE := Classical.decRel _
decidableEq := Classical.decRel _
decidableLT := Classical.decRel _ }
end LinearOrder
/-! #### Map -/
section
variable [Preorder α] [Preorder β] [Preorder γ]
namespace UpperSet
variable {f : α ≃o β} {s t : UpperSet α} {a : α} {b : β}
/-- An order isomorphism of preorders induces an order isomorphism of their upper sets. -/
def map (f : α ≃o β) : UpperSet α ≃o UpperSet β where
toFun s := ⟨f '' s, s.upper.image f⟩
invFun t := ⟨f ⁻¹' t, t.upper.preimage f.monotone⟩
left_inv _ := ext <| f.preimage_image _
right_inv _ := ext <| f.image_preimage _
map_rel_iff' := image_subset_image_iff f.injective
#align upper_set.map UpperSet.map
@[simp]
theorem symm_map (f : α ≃o β) : (map f).symm = map f.symm :=
DFunLike.ext _ _ fun s => ext <| by convert Set.preimage_equiv_eq_image_symm s f.toEquiv
#align upper_set.symm_map UpperSet.symm_map
@[simp]
theorem mem_map : b ∈ map f s ↔ f.symm b ∈ s := by
rw [← f.symm_symm, ← symm_map, f.symm_symm]
rfl
#align upper_set.mem_map UpperSet.mem_map
@[simp]
theorem map_refl : map (OrderIso.refl α) = OrderIso.refl _ := by
ext
simp
#align upper_set.map_refl UpperSet.map_refl
@[simp]
theorem map_map (g : β ≃o γ) (f : α ≃o β) : map g (map f s) = map (f.trans g) s := by
ext
simp
#align upper_set.map_map UpperSet.map_map
variable (f s t)
@[simp, norm_cast]
theorem coe_map : (map f s : Set β) = f '' s :=
rfl
#align upper_set.coe_map UpperSet.coe_map
end UpperSet
namespace LowerSet
variable {f : α ≃o β} {s t : LowerSet α} {a : α} {b : β}
/-- An order isomorphism of preorders induces an order isomorphism of their lower sets. -/
def map (f : α ≃o β) : LowerSet α ≃o LowerSet β where
toFun s := ⟨f '' s, s.lower.image f⟩
invFun t := ⟨f ⁻¹' t, t.lower.preimage f.monotone⟩
left_inv _ := SetLike.coe_injective <| f.preimage_image _
right_inv _ := SetLike.coe_injective <| f.image_preimage _
map_rel_iff' := image_subset_image_iff f.injective
#align lower_set.map LowerSet.map
@[simp]
theorem symm_map (f : α ≃o β) : (map f).symm = map f.symm :=
DFunLike.ext _ _ fun s => ext <| by convert Set.preimage_equiv_eq_image_symm s f.toEquiv
#align lower_set.symm_map LowerSet.symm_map
@[simp]
theorem mem_map {f : α ≃o β} {b : β} : b ∈ map f s ↔ f.symm b ∈ s := by
rw [← f.symm_symm, ← symm_map, f.symm_symm]
rfl
#align lower_set.mem_map LowerSet.mem_map
@[simp]
theorem map_refl : map (OrderIso.refl α) = OrderIso.refl _ := by
ext
simp
#align lower_set.map_refl LowerSet.map_refl
@[simp]
theorem map_map (g : β ≃o γ) (f : α ≃o β) : map g (map f s) = map (f.trans g) s := by
ext
simp
#align lower_set.map_map LowerSet.map_map
variable (f s t)
@[simp, norm_cast]
theorem coe_map : (map f s : Set β) = f '' s :=
rfl
#align lower_set.coe_map LowerSet.coe_map
end LowerSet
namespace UpperSet
@[simp]
theorem compl_map (f : α ≃o β) (s : UpperSet α) : (map f s).compl = LowerSet.map f s.compl :=
SetLike.coe_injective (Set.image_compl_eq f.bijective).symm
#align upper_set.compl_map UpperSet.compl_map
end UpperSet
namespace LowerSet
@[simp]
theorem compl_map (f : α ≃o β) (s : LowerSet α) : (map f s).compl = UpperSet.map f s.compl :=
SetLike.coe_injective (Set.image_compl_eq f.bijective).symm
#align lower_set.compl_map LowerSet.compl_map
end LowerSet
end
/-! #### Principal sets -/
namespace UpperSet
section Preorder
variable [Preorder α] [Preorder β] {s : UpperSet α} {a b : α}
/-- The smallest upper set containing a given element. -/
nonrec def Ici (a : α) : UpperSet α :=
⟨Ici a, isUpperSet_Ici a⟩
#align upper_set.Ici UpperSet.Ici
/-- The smallest upper set containing a given element. -/
nonrec def Ioi (a : α) : UpperSet α :=
⟨Ioi a, isUpperSet_Ioi a⟩
#align upper_set.Ioi UpperSet.Ioi
@[simp]
theorem coe_Ici (a : α) : ↑(Ici a) = Set.Ici a :=
rfl
#align upper_set.coe_Ici UpperSet.coe_Ici
@[simp]
theorem coe_Ioi (a : α) : ↑(Ioi a) = Set.Ioi a :=
rfl
#align upper_set.coe_Ioi UpperSet.coe_Ioi
@[simp]
theorem mem_Ici_iff : b ∈ Ici a ↔ a ≤ b :=
Iff.rfl
#align upper_set.mem_Ici_iff UpperSet.mem_Ici_iff
@[simp]
theorem mem_Ioi_iff : b ∈ Ioi a ↔ a < b :=
Iff.rfl
#align upper_set.mem_Ioi_iff UpperSet.mem_Ioi_iff
@[simp]
theorem map_Ici (f : α ≃o β) (a : α) : map f (Ici a) = Ici (f a) := by
ext
simp
#align upper_set.map_Ici UpperSet.map_Ici
@[simp]
theorem map_Ioi (f : α ≃o β) (a : α) : map f (Ioi a) = Ioi (f a) := by
ext
simp
#align upper_set.map_Ioi UpperSet.map_Ioi
theorem Ici_le_Ioi (a : α) : Ici a ≤ Ioi a :=
Ioi_subset_Ici_self
#align upper_set.Ici_le_Ioi UpperSet.Ici_le_Ioi
@[simp]
nonrec theorem Ici_bot [OrderBot α] : Ici (⊥ : α) = ⊥ :=
SetLike.coe_injective Ici_bot
#align upper_set.Ici_bot UpperSet.Ici_bot
@[simp]
nonrec theorem Ioi_top [OrderTop α] : Ioi (⊤ : α) = ⊤ :=
SetLike.coe_injective Ioi_top
#align upper_set.Ioi_top UpperSet.Ioi_top
@[simp] lemma Ici_ne_top : Ici a ≠ ⊤ := SetLike.coe_ne_coe.1 nonempty_Ici.ne_empty
@[simp] lemma Ici_lt_top : Ici a < ⊤ := lt_top_iff_ne_top.2 Ici_ne_top
@[simp] lemma le_Ici : s ≤ Ici a ↔ a ∈ s := ⟨fun h ↦ h le_rfl, fun ha ↦ s.upper.Ici_subset ha⟩
end Preorder
section PartialOrder
variable [PartialOrder α] {a b : α}
nonrec lemma Ici_injective : Injective (Ici : α → UpperSet α) := fun _a _b hab ↦
Ici_injective <| congr_arg ((↑) : _ → Set α) hab
@[simp] lemma Ici_inj : Ici a = Ici b ↔ a = b := Ici_injective.eq_iff
lemma Ici_ne_Ici : Ici a ≠ Ici b ↔ a ≠ b := Ici_inj.not
end PartialOrder
@[simp]
theorem Ici_sup [SemilatticeSup α] (a b : α) : Ici (a ⊔ b) = Ici a ⊔ Ici b :=
ext Ici_inter_Ici.symm
#align upper_set.Ici_sup UpperSet.Ici_sup
section CompleteLattice
variable [CompleteLattice α]
@[simp]
theorem Ici_sSup (S : Set α) : Ici (sSup S) = ⨆ a ∈ S, Ici a :=
SetLike.ext fun c => by simp only [mem_Ici_iff, mem_iSup_iff, sSup_le_iff]
#align upper_set.Ici_Sup UpperSet.Ici_sSup
@[simp]
theorem Ici_iSup (f : ι → α) : Ici (⨆ i, f i) = ⨆ i, Ici (f i) :=
SetLike.ext fun c => by simp only [mem_Ici_iff, mem_iSup_iff, iSup_le_iff]
#align upper_set.Ici_supr UpperSet.Ici_iSup
-- Porting note: no longer a @[simp]
theorem Ici_iSup₂ (f : ∀ i, κ i → α) : Ici (⨆ (i) (j), f i j) = ⨆ (i) (j), Ici (f i j) := by
simp_rw [Ici_iSup]
#align upper_set.Ici_supr₂ UpperSet.Ici_iSup₂
end CompleteLattice
end UpperSet
namespace LowerSet
section Preorder
variable [Preorder α] [Preorder β] {s : LowerSet α} {a b : α}
/-- Principal lower set. `Set.Iic` as a lower set. The smallest lower set containing a given
element. -/
nonrec def Iic (a : α) : LowerSet α :=
⟨Iic a, isLowerSet_Iic a⟩
#align lower_set.Iic LowerSet.Iic
/-- Strict principal lower set. `Set.Iio` as a lower set. -/
nonrec def Iio (a : α) : LowerSet α :=
⟨Iio a, isLowerSet_Iio a⟩
#align lower_set.Iio LowerSet.Iio
@[simp]
theorem coe_Iic (a : α) : ↑(Iic a) = Set.Iic a :=
rfl
#align lower_set.coe_Iic LowerSet.coe_Iic
@[simp]
theorem coe_Iio (a : α) : ↑(Iio a) = Set.Iio a :=
rfl
#align lower_set.coe_Iio LowerSet.coe_Iio
@[simp]
theorem mem_Iic_iff : b ∈ Iic a ↔ b ≤ a :=
Iff.rfl
#align lower_set.mem_Iic_iff LowerSet.mem_Iic_iff
@[simp]
theorem mem_Iio_iff : b ∈ Iio a ↔ b < a :=
Iff.rfl
#align lower_set.mem_Iio_iff LowerSet.mem_Iio_iff
@[simp]
theorem map_Iic (f : α ≃o β) (a : α) : map f (Iic a) = Iic (f a) := by
ext
simp
#align lower_set.map_Iic LowerSet.map_Iic
@[simp]
theorem map_Iio (f : α ≃o β) (a : α) : map f (Iio a) = Iio (f a) := by
ext
simp
#align lower_set.map_Iio LowerSet.map_Iio
theorem Ioi_le_Ici (a : α) : Ioi a ≤ Ici a :=
Ioi_subset_Ici_self
#align lower_set.Ioi_le_Ici LowerSet.Ioi_le_Ici
@[simp]
nonrec theorem Iic_top [OrderTop α] : Iic (⊤ : α) = ⊤ :=
SetLike.coe_injective Iic_top
#align lower_set.Iic_top LowerSet.Iic_top
@[simp]
nonrec theorem Iio_bot [OrderBot α] : Iio (⊥ : α) = ⊥ :=
SetLike.coe_injective Iio_bot
#align lower_set.Iio_bot LowerSet.Iio_bot
@[simp] lemma Iic_ne_bot : Iic a ≠ ⊥ := SetLike.coe_ne_coe.1 nonempty_Iic.ne_empty
@[simp] lemma bot_lt_Iic : ⊥ < Iic a := bot_lt_iff_ne_bot.2 Iic_ne_bot
@[simp] lemma Iic_le : Iic a ≤ s ↔ a ∈ s := ⟨fun h ↦ h le_rfl, fun ha ↦ s.lower.Iic_subset ha⟩
end Preorder
section PartialOrder
variable [PartialOrder α] {a b : α}
nonrec lemma Iic_injective : Injective (Iic : α → LowerSet α) := fun _a _b hab ↦
Iic_injective <| congr_arg ((↑) : _ → Set α) hab
@[simp] lemma Iic_inj : Iic a = Iic b ↔ a = b := Iic_injective.eq_iff
lemma Iic_ne_Iic : Iic a ≠ Iic b ↔ a ≠ b := Iic_inj.not
end PartialOrder
@[simp]
theorem Iic_inf [SemilatticeInf α] (a b : α) : Iic (a ⊓ b) = Iic a ⊓ Iic b :=
SetLike.coe_injective Iic_inter_Iic.symm
#align lower_set.Iic_inf LowerSet.Iic_inf
section CompleteLattice
variable [CompleteLattice α]
@[simp]
theorem Iic_sInf (S : Set α) : Iic (sInf S) = ⨅ a ∈ S, Iic a :=
SetLike.ext fun c => by simp only [mem_Iic_iff, mem_iInf₂_iff, le_sInf_iff]
#align lower_set.Iic_Inf LowerSet.Iic_sInf
@[simp]
theorem Iic_iInf (f : ι → α) : Iic (⨅ i, f i) = ⨅ i, Iic (f i) :=
SetLike.ext fun c => by simp only [mem_Iic_iff, mem_iInf_iff, le_iInf_iff]
#align lower_set.Iic_infi LowerSet.Iic_iInf
-- Porting note: no longer a @[simp]
theorem Iic_iInf₂ (f : ∀ i, κ i → α) : Iic (⨅ (i) (j), f i j) = ⨅ (i) (j), Iic (f i j) := by
simp_rw [Iic_iInf]
#align lower_set.Iic_infi₂ LowerSet.Iic_iInf₂
end CompleteLattice
end LowerSet
section closure
variable [Preorder α] [Preorder β] {s t : Set α} {x : α}
/-- The greatest upper set containing a given set. -/
def upperClosure (s : Set α) : UpperSet α :=
⟨{ x | ∃ a ∈ s, a ≤ x }, fun _ _ hle h => h.imp fun _x hx => ⟨hx.1, hx.2.trans hle⟩⟩
#align upper_closure upperClosure
/-- The least lower set containing a given set. -/
def lowerClosure (s : Set α) : LowerSet α :=
⟨{ x | ∃ a ∈ s, x ≤ a }, fun _ _ hle h => h.imp fun _x hx => ⟨hx.1, hle.trans hx.2⟩⟩
#align lower_closure lowerClosure
-- Porting note (#11215): TODO: move `GaloisInsertion`s up, use them to prove lemmas
@[simp]
theorem mem_upperClosure : x ∈ upperClosure s ↔ ∃ a ∈ s, a ≤ x :=
Iff.rfl
#align mem_upper_closure mem_upperClosure
@[simp]
theorem mem_lowerClosure : x ∈ lowerClosure s ↔ ∃ a ∈ s, x ≤ a :=
Iff.rfl
#align mem_lower_closure mem_lowerClosure
-- We do not tag those two as `simp` to respect the abstraction.
@[norm_cast]
theorem coe_upperClosure (s : Set α) : ↑(upperClosure s) = ⋃ a ∈ s, Ici a := by
ext
simp
#align coe_upper_closure coe_upperClosure
@[norm_cast]
theorem coe_lowerClosure (s : Set α) : ↑(lowerClosure s) = ⋃ a ∈ s, Iic a := by
ext
simp
#align coe_lower_closure coe_lowerClosure
instance instDecidablePredMemUpperClosure [DecidablePred (∃ a ∈ s, a ≤ ·)] :
DecidablePred (· ∈ upperClosure s) := ‹DecidablePred _›
instance instDecidablePredMemLowerClosure [DecidablePred (∃ a ∈ s, · ≤ a)] :
DecidablePred (· ∈ lowerClosure s) := ‹DecidablePred _›
theorem subset_upperClosure : s ⊆ upperClosure s := fun x hx => ⟨x, hx, le_rfl⟩
#align subset_upper_closure subset_upperClosure
theorem subset_lowerClosure : s ⊆ lowerClosure s := fun x hx => ⟨x, hx, le_rfl⟩
#align subset_lower_closure subset_lowerClosure
theorem upperClosure_min (h : s ⊆ t) (ht : IsUpperSet t) : ↑(upperClosure s) ⊆ t :=
fun _a ⟨_b, hb, hba⟩ => ht hba <| h hb
#align upper_closure_min upperClosure_min
theorem lowerClosure_min (h : s ⊆ t) (ht : IsLowerSet t) : ↑(lowerClosure s) ⊆ t :=
fun _a ⟨_b, hb, hab⟩ => ht hab <| h hb
#align lower_closure_min lowerClosure_min
protected theorem IsUpperSet.upperClosure (hs : IsUpperSet s) : ↑(upperClosure s) = s :=
(upperClosure_min Subset.rfl hs).antisymm subset_upperClosure
#align is_upper_set.upper_closure IsUpperSet.upperClosure
protected theorem IsLowerSet.lowerClosure (hs : IsLowerSet s) : ↑(lowerClosure s) = s :=
(lowerClosure_min Subset.rfl hs).antisymm subset_lowerClosure
#align is_lower_set.lower_closure IsLowerSet.lowerClosure
@[simp]
protected theorem UpperSet.upperClosure (s : UpperSet α) : upperClosure (s : Set α) = s :=
SetLike.coe_injective s.2.upperClosure
#align upper_set.upper_closure UpperSet.upperClosure
@[simp]
protected theorem LowerSet.lowerClosure (s : LowerSet α) : lowerClosure (s : Set α) = s :=
SetLike.coe_injective s.2.lowerClosure
#align lower_set.lower_closure LowerSet.lowerClosure
@[simp]
theorem upperClosure_image (f : α ≃o β) :
upperClosure (f '' s) = UpperSet.map f (upperClosure s) := by
rw [← f.symm_symm, ← UpperSet.symm_map, f.symm_symm]
ext
simp [-UpperSet.symm_map, UpperSet.map, OrderIso.symm, ← f.le_symm_apply]
#align upper_closure_image upperClosure_image
@[simp]
theorem lowerClosure_image (f : α ≃o β) :
lowerClosure (f '' s) = LowerSet.map f (lowerClosure s) := by
rw [← f.symm_symm, ← LowerSet.symm_map, f.symm_symm]
ext
simp [-LowerSet.symm_map, LowerSet.map, OrderIso.symm, ← f.symm_apply_le]
#align lower_closure_image lowerClosure_image
@[simp]
theorem UpperSet.iInf_Ici (s : Set α) : ⨅ a ∈ s, UpperSet.Ici a = upperClosure s := by
ext
simp
#align upper_set.infi_Ici UpperSet.iInf_Ici
@[simp]
theorem LowerSet.iSup_Iic (s : Set α) : ⨆ a ∈ s, LowerSet.Iic a = lowerClosure s := by
ext
simp
#align lower_set.supr_Iic LowerSet.iSup_Iic
@[simp] lemma lowerClosure_le {t : LowerSet α} : lowerClosure s ≤ t ↔ s ⊆ t :=
⟨fun h ↦ subset_lowerClosure.trans <| LowerSet.coe_subset_coe.2 h,
fun h ↦ lowerClosure_min h t.lower⟩
@[simp] lemma le_upperClosure {s : UpperSet α} : s ≤ upperClosure t ↔ t ⊆ s :=
⟨fun h ↦ subset_upperClosure.trans <| UpperSet.coe_subset_coe.2 h,
fun h ↦ upperClosure_min h s.upper⟩
theorem gc_upperClosure_coe :
GaloisConnection (toDual ∘ upperClosure : Set α → (UpperSet α)ᵒᵈ) ((↑) ∘ ofDual) :=
fun _s _t ↦ le_upperClosure
#align gc_upper_closure_coe gc_upperClosure_coe
theorem gc_lowerClosure_coe :
GaloisConnection (lowerClosure : Set α → LowerSet α) (↑) := fun _s _t ↦ lowerClosure_le
#align gc_lower_closure_coe gc_lowerClosure_coe
/-- `upperClosure` forms a reversed Galois insertion with the coercion from upper sets to sets. -/
def giUpperClosureCoe :
GaloisInsertion (toDual ∘ upperClosure : Set α → (UpperSet α)ᵒᵈ) ((↑) ∘ ofDual) where
choice s hs := toDual (⟨s, fun a _b hab ha => hs ⟨a, ha, hab⟩⟩ : UpperSet α)
gc := gc_upperClosure_coe
le_l_u _ := subset_upperClosure
choice_eq _s hs := ofDual.injective <| SetLike.coe_injective <| subset_upperClosure.antisymm hs
#align gi_upper_closure_coe giUpperClosureCoe
/-- `lowerClosure` forms a Galois insertion with the coercion from lower sets to sets. -/
def giLowerClosureCoe : GaloisInsertion (lowerClosure : Set α → LowerSet α) (↑) where
choice s hs := ⟨s, fun a _b hba ha => hs ⟨a, ha, hba⟩⟩
gc := gc_lowerClosure_coe
le_l_u _ := subset_lowerClosure
choice_eq _s hs := SetLike.coe_injective <| subset_lowerClosure.antisymm hs
#align gi_lower_closure_coe giLowerClosureCoe
theorem upperClosure_anti : Antitone (upperClosure : Set α → UpperSet α) :=
gc_upperClosure_coe.monotone_l
#align upper_closure_anti upperClosure_anti
theorem lowerClosure_mono : Monotone (lowerClosure : Set α → LowerSet α) :=
gc_lowerClosure_coe.monotone_l
#align lower_closure_mono lowerClosure_mono
@[simp]
theorem upperClosure_empty : upperClosure (∅ : Set α) = ⊤ :=
(@gc_upperClosure_coe α).l_bot
#align upper_closure_empty upperClosure_empty
@[simp]
theorem lowerClosure_empty : lowerClosure (∅ : Set α) = ⊥ :=
(@gc_lowerClosure_coe α).l_bot
#align lower_closure_empty lowerClosure_empty
@[simp]
theorem upperClosure_singleton (a : α) : upperClosure ({a} : Set α) = UpperSet.Ici a := by
ext
simp
#align upper_closure_singleton upperClosure_singleton
@[simp]
theorem lowerClosure_singleton (a : α) : lowerClosure ({a} : Set α) = LowerSet.Iic a := by
ext
simp
#align lower_closure_singleton lowerClosure_singleton
@[simp]
theorem upperClosure_univ : upperClosure (univ : Set α) = ⊥ :=
bot_unique subset_upperClosure
#align upper_closure_univ upperClosure_univ
@[simp]
theorem lowerClosure_univ : lowerClosure (univ : Set α) = ⊤ :=
top_unique subset_lowerClosure
#align lower_closure_univ lowerClosure_univ
@[simp]
theorem upperClosure_eq_top_iff : upperClosure s = ⊤ ↔ s = ∅ :=
(@gc_upperClosure_coe α _).l_eq_bot.trans subset_empty_iff
#align upper_closure_eq_top_iff upperClosure_eq_top_iff
@[simp]
theorem lowerClosure_eq_bot_iff : lowerClosure s = ⊥ ↔ s = ∅ :=
(@gc_lowerClosure_coe α _).l_eq_bot.trans subset_empty_iff
#align lower_closure_eq_bot_iff lowerClosure_eq_bot_iff
@[simp]
theorem upperClosure_union (s t : Set α) : upperClosure (s ∪ t) = upperClosure s ⊓ upperClosure t :=
(@gc_upperClosure_coe α _).l_sup
#align upper_closure_union upperClosure_union
@[simp]
theorem lowerClosure_union (s t : Set α) : lowerClosure (s ∪ t) = lowerClosure s ⊔ lowerClosure t :=
(@gc_lowerClosure_coe α _).l_sup
#align lower_closure_union lowerClosure_union
@[simp]
theorem upperClosure_iUnion (f : ι → Set α) : upperClosure (⋃ i, f i) = ⨅ i, upperClosure (f i) :=
(@gc_upperClosure_coe α _).l_iSup
#align upper_closure_Union upperClosure_iUnion
@[simp]
theorem lowerClosure_iUnion (f : ι → Set α) : lowerClosure (⋃ i, f i) = ⨆ i, lowerClosure (f i) :=
(@gc_lowerClosure_coe α _).l_iSup
#align lower_closure_Union lowerClosure_iUnion
@[simp]
theorem upperClosure_sUnion (S : Set (Set α)) : upperClosure (⋃₀ S) = ⨅ s ∈ S, upperClosure s := by
simp_rw [sUnion_eq_biUnion, upperClosure_iUnion]
#align upper_closure_sUnion upperClosure_sUnion
@[simp]
| Mathlib/Order/UpperLower/Basic.lean | 1,598 | 1,599 | theorem lowerClosure_sUnion (S : Set (Set α)) : lowerClosure (⋃₀ S) = ⨆ s ∈ S, lowerClosure s := by |
simp_rw [sUnion_eq_biUnion, lowerClosure_iUnion]
|
/-
Copyright (c) 2021 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.MeasureTheory.Covering.VitaliFamily
import Mathlib.MeasureTheory.Measure.Regular
import Mathlib.MeasureTheory.Function.AEMeasurableOrder
import Mathlib.MeasureTheory.Integral.Lebesgue
import Mathlib.MeasureTheory.Integral.Average
import Mathlib.MeasureTheory.Decomposition.Lebesgue
#align_import measure_theory.covering.differentiation from "leanprover-community/mathlib"@"57ac39bd365c2f80589a700f9fbb664d3a1a30c2"
/-!
# Differentiation of measures
On a second countable metric space with a measure `μ`, consider a Vitali family (i.e., for each `x`
one has a family of sets shrinking to `x`, with a good behavior with respect to covering theorems).
Consider also another measure `ρ`. Then, for almost every `x`, the ratio `ρ a / μ a` converges when
`a` shrinks to `x` along the Vitali family, towards the Radon-Nikodym derivative of `ρ` with
respect to `μ`. This is the main theorem on differentiation of measures.
This theorem is proved in this file, under the name `VitaliFamily.ae_tendsto_rnDeriv`. Note that,
almost surely, `μ a` is eventually positive and finite (see
`VitaliFamily.ae_eventually_measure_pos` and `VitaliFamily.eventually_measure_lt_top`), so the
ratio really makes sense.
For concrete applications, one needs concrete instances of Vitali families, as provided for instance
by `Besicovitch.vitaliFamily` (for balls) or by `Vitali.vitaliFamily` (for doubling measures).
Specific applications to Lebesgue density points and the Lebesgue differentiation theorem are also
derived:
* `VitaliFamily.ae_tendsto_measure_inter_div` states that, for almost every point `x ∈ s`,
then `μ (s ∩ a) / μ a` tends to `1` as `a` shrinks to `x` along a Vitali family.
* `VitaliFamily.ae_tendsto_average_norm_sub` states that, for almost every point `x`, then the
average of `y ↦ ‖f y - f x‖` on `a` tends to `0` as `a` shrinks to `x` along a Vitali family.
## Sketch of proof
Let `v` be a Vitali family for `μ`. Assume for simplicity that `ρ` is absolutely continuous with
respect to `μ`, as the case of a singular measure is easier.
It is easy to see that a set `s` on which `liminf ρ a / μ a < q` satisfies `ρ s ≤ q * μ s`, by using
a disjoint subcovering provided by the definition of Vitali families. Similarly for the limsup.
It follows that a set on which `ρ a / μ a` oscillates has measure `0`, and therefore that
`ρ a / μ a` converges almost surely (`VitaliFamily.ae_tendsto_div`). Moreover, on a set where the
limit is close to a constant `c`, one gets `ρ s ∼ c μ s`, using again a covering lemma as above.
It follows that `ρ` is equal to `μ.withDensity (v.limRatio ρ x)`, where `v.limRatio ρ x` is the
limit of `ρ a / μ a` at `x` (which is well defined almost everywhere). By uniqueness of the
Radon-Nikodym derivative, one gets `v.limRatio ρ x = ρ.rnDeriv μ x` almost everywhere, completing
the proof.
There is a difficulty in this sketch: this argument works well when `v.limRatio ρ` is measurable,
but there is no guarantee that this is the case, especially if one doesn't make further assumptions
on the Vitali family. We use an indirect argument to show that `v.limRatio ρ` is always
almost everywhere measurable, again based on the disjoint subcovering argument
(see `VitaliFamily.exists_measurable_supersets_limRatio`), and then proceed as sketched above
but replacing `v.limRatio ρ` by a measurable version called `v.limRatioMeas ρ`.
## Counterexample
The standing assumption in this file is that spaces are second countable. Without this assumption,
measures may be zero locally but nonzero globally, which is not compatible with differentiation
theory (which deduces global information from local one). Here is an example displaying this
behavior.
Define a measure `μ` by `μ s = 0` if `s` is covered by countably many balls of radius `1`,
and `μ s = ∞` otherwise. This is indeed a countably additive measure, which is moreover
locally finite and doubling at small scales. It vanishes on every ball of radius `1`, so all the
quantities in differentiation theory (defined as ratios of measures as the radius tends to zero)
make no sense. However, the measure is not globally zero if the space is big enough.
## References
* [Herbert Federer, Geometric Measure Theory, Chapter 2.9][Federer1996]
-/
open MeasureTheory Metric Set Filter TopologicalSpace MeasureTheory.Measure
open scoped Filter ENNReal MeasureTheory NNReal Topology
variable {α : Type*} [MetricSpace α] {m0 : MeasurableSpace α} {μ : Measure α} (v : VitaliFamily μ)
{E : Type*} [NormedAddCommGroup E]
namespace VitaliFamily
/-- The limit along a Vitali family of `ρ a / μ a` where it makes sense, and garbage otherwise.
Do *not* use this definition: it is only a temporary device to show that this ratio tends almost
everywhere to the Radon-Nikodym derivative. -/
noncomputable def limRatio (ρ : Measure α) (x : α) : ℝ≥0∞ :=
limUnder (v.filterAt x) fun a => ρ a / μ a
#align vitali_family.lim_ratio VitaliFamily.limRatio
/-- For almost every point `x`, sufficiently small sets in a Vitali family around `x` have positive
measure. (This is a nontrivial result, following from the covering property of Vitali families). -/
theorem ae_eventually_measure_pos [SecondCountableTopology α] :
∀ᵐ x ∂μ, ∀ᶠ a in v.filterAt x, 0 < μ a := by
set s := {x | ¬∀ᶠ a in v.filterAt x, 0 < μ a} with hs
simp (config := { zeta := false }) only [not_lt, not_eventually, nonpos_iff_eq_zero] at hs
change μ s = 0
let f : α → Set (Set α) := fun _ => {a | μ a = 0}
have h : v.FineSubfamilyOn f s := by
intro x hx ε εpos
rw [hs] at hx
simp only [frequently_filterAt_iff, exists_prop, gt_iff_lt, mem_setOf_eq] at hx
rcases hx ε εpos with ⟨a, a_sets, ax, μa⟩
exact ⟨a, ⟨a_sets, μa⟩, ax⟩
refine le_antisymm ?_ bot_le
calc
μ s ≤ ∑' x : h.index, μ (h.covering x) := h.measure_le_tsum
_ = ∑' x : h.index, 0 := by congr; ext1 x; exact h.covering_mem x.2
_ = 0 := by simp only [tsum_zero, add_zero]
#align vitali_family.ae_eventually_measure_pos VitaliFamily.ae_eventually_measure_pos
/-- For every point `x`, sufficiently small sets in a Vitali family around `x` have finite measure.
(This is a trivial result, following from the fact that the measure is locally finite). -/
theorem eventually_measure_lt_top [IsLocallyFiniteMeasure μ] (x : α) :
∀ᶠ a in v.filterAt x, μ a < ∞ :=
(μ.finiteAt_nhds x).eventually.filter_mono inf_le_left
#align vitali_family.eventually_measure_lt_top VitaliFamily.eventually_measure_lt_top
/-- If two measures `ρ` and `ν` have, at every point of a set `s`, arbitrarily small sets in a
Vitali family satisfying `ρ a ≤ ν a`, then `ρ s ≤ ν s` if `ρ ≪ μ`. -/
theorem measure_le_of_frequently_le [SecondCountableTopology α] [BorelSpace α] {ρ : Measure α}
(ν : Measure α) [IsLocallyFiniteMeasure ν] (hρ : ρ ≪ μ) (s : Set α)
(hs : ∀ x ∈ s, ∃ᶠ a in v.filterAt x, ρ a ≤ ν a) : ρ s ≤ ν s := by
-- this follows from a covering argument using the sets satisfying `ρ a ≤ ν a`.
apply ENNReal.le_of_forall_pos_le_add fun ε εpos _ => ?_
obtain ⟨U, sU, U_open, νU⟩ : ∃ (U : Set α), s ⊆ U ∧ IsOpen U ∧ ν U ≤ ν s + ε :=
exists_isOpen_le_add s ν (ENNReal.coe_pos.2 εpos).ne'
let f : α → Set (Set α) := fun _ => {a | ρ a ≤ ν a ∧ a ⊆ U}
have h : v.FineSubfamilyOn f s := by
apply v.fineSubfamilyOn_of_frequently f s fun x hx => ?_
have :=
(hs x hx).and_eventually
((v.eventually_filterAt_mem_setsAt x).and
(v.eventually_filterAt_subset_of_nhds (U_open.mem_nhds (sU hx))))
apply Frequently.mono this
rintro a ⟨ρa, _, aU⟩
exact ⟨ρa, aU⟩
haveI : Encodable h.index := h.index_countable.toEncodable
calc
ρ s ≤ ∑' x : h.index, ρ (h.covering x) := h.measure_le_tsum_of_absolutelyContinuous hρ
_ ≤ ∑' x : h.index, ν (h.covering x) := ENNReal.tsum_le_tsum fun x => (h.covering_mem x.2).1
_ = ν (⋃ x : h.index, h.covering x) := by
rw [measure_iUnion h.covering_disjoint_subtype fun i => h.measurableSet_u i.2]
_ ≤ ν U := (measure_mono (iUnion_subset fun i => (h.covering_mem i.2).2))
_ ≤ ν s + ε := νU
#align vitali_family.measure_le_of_frequently_le VitaliFamily.measure_le_of_frequently_le
section
variable [SecondCountableTopology α] [BorelSpace α] [IsLocallyFiniteMeasure μ] {ρ : Measure α}
[IsLocallyFiniteMeasure ρ]
/-- If a measure `ρ` is singular with respect to `μ`, then for `μ` almost every `x`, the ratio
`ρ a / μ a` tends to zero when `a` shrinks to `x` along the Vitali family. This makes sense
as `μ a` is eventually positive by `ae_eventually_measure_pos`. -/
theorem ae_eventually_measure_zero_of_singular (hρ : ρ ⟂ₘ μ) :
∀ᵐ x ∂μ, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 0) := by
have A : ∀ ε > (0 : ℝ≥0), ∀ᵐ x ∂μ, ∀ᶠ a in v.filterAt x, ρ a < ε * μ a := by
intro ε εpos
set s := {x | ¬∀ᶠ a in v.filterAt x, ρ a < ε * μ a} with hs
change μ s = 0
obtain ⟨o, _, ρo, μo⟩ : ∃ o : Set α, MeasurableSet o ∧ ρ o = 0 ∧ μ oᶜ = 0 := hρ
apply le_antisymm _ bot_le
calc
μ s ≤ μ (s ∩ o ∪ oᶜ) := by
conv_lhs => rw [← inter_union_compl s o]
gcongr
apply inter_subset_right
_ ≤ μ (s ∩ o) + μ oᶜ := measure_union_le _ _
_ = μ (s ∩ o) := by rw [μo, add_zero]
_ = (ε : ℝ≥0∞)⁻¹ * (ε • μ) (s ∩ o) := by
simp only [coe_nnreal_smul_apply, ← mul_assoc, mul_comm _ (ε : ℝ≥0∞)]
rw [ENNReal.mul_inv_cancel (ENNReal.coe_pos.2 εpos).ne' ENNReal.coe_ne_top, one_mul]
_ ≤ (ε : ℝ≥0∞)⁻¹ * ρ (s ∩ o) := by
gcongr
refine v.measure_le_of_frequently_le ρ ((Measure.AbsolutelyContinuous.refl μ).smul ε) _ ?_
intro x hx
rw [hs] at hx
simp only [mem_inter_iff, not_lt, not_eventually, mem_setOf_eq] at hx
exact hx.1
_ ≤ (ε : ℝ≥0∞)⁻¹ * ρ o := by gcongr; apply inter_subset_right
_ = 0 := by rw [ρo, mul_zero]
obtain ⟨u, _, u_pos, u_lim⟩ :
∃ u : ℕ → ℝ≥0, StrictAnti u ∧ (∀ n : ℕ, 0 < u n) ∧ Tendsto u atTop (𝓝 0) :=
exists_seq_strictAnti_tendsto (0 : ℝ≥0)
have B : ∀ᵐ x ∂μ, ∀ n, ∀ᶠ a in v.filterAt x, ρ a < u n * μ a :=
ae_all_iff.2 fun n => A (u n) (u_pos n)
filter_upwards [B, v.ae_eventually_measure_pos]
intro x hx h'x
refine tendsto_order.2 ⟨fun z hz => (ENNReal.not_lt_zero hz).elim, fun z hz => ?_⟩
obtain ⟨w, w_pos, w_lt⟩ : ∃ w : ℝ≥0, (0 : ℝ≥0∞) < w ∧ (w : ℝ≥0∞) < z :=
ENNReal.lt_iff_exists_nnreal_btwn.1 hz
obtain ⟨n, hn⟩ : ∃ n, u n < w := ((tendsto_order.1 u_lim).2 w (ENNReal.coe_pos.1 w_pos)).exists
filter_upwards [hx n, h'x, v.eventually_measure_lt_top x]
intro a ha μa_pos μa_lt_top
rw [ENNReal.div_lt_iff (Or.inl μa_pos.ne') (Or.inl μa_lt_top.ne)]
exact ha.trans_le (mul_le_mul_right' ((ENNReal.coe_le_coe.2 hn.le).trans w_lt.le) _)
#align vitali_family.ae_eventually_measure_zero_of_singular VitaliFamily.ae_eventually_measure_zero_of_singular
section AbsolutelyContinuous
variable (hρ : ρ ≪ μ)
/-- A set of points `s` satisfying both `ρ a ≤ c * μ a` and `ρ a ≥ d * μ a` at arbitrarily small
sets in a Vitali family has measure `0` if `c < d`. Indeed, the first inequality should imply
that `ρ s ≤ c * μ s`, and the second one that `ρ s ≥ d * μ s`, a contradiction if `0 < μ s`. -/
theorem null_of_frequently_le_of_frequently_ge {c d : ℝ≥0} (hcd : c < d) (s : Set α)
(hc : ∀ x ∈ s, ∃ᶠ a in v.filterAt x, ρ a ≤ c * μ a)
(hd : ∀ x ∈ s, ∃ᶠ a in v.filterAt x, (d : ℝ≥0∞) * μ a ≤ ρ a) : μ s = 0 := by
apply measure_null_of_locally_null s fun x _ => ?_
obtain ⟨o, xo, o_open, μo⟩ : ∃ o : Set α, x ∈ o ∧ IsOpen o ∧ μ o < ∞ :=
Measure.exists_isOpen_measure_lt_top μ x
refine ⟨s ∩ o, inter_mem_nhdsWithin _ (o_open.mem_nhds xo), ?_⟩
let s' := s ∩ o
by_contra h
apply lt_irrefl (ρ s')
calc
ρ s' ≤ c * μ s' := v.measure_le_of_frequently_le (c • μ) hρ s' fun x hx => hc x hx.1
_ < d * μ s' := by
apply (ENNReal.mul_lt_mul_right h _).2 (ENNReal.coe_lt_coe.2 hcd)
exact (lt_of_le_of_lt (measure_mono inter_subset_right) μo).ne
_ ≤ ρ s' :=
v.measure_le_of_frequently_le ρ ((Measure.AbsolutelyContinuous.refl μ).smul d) s' fun x hx =>
hd x hx.1
#align vitali_family.null_of_frequently_le_of_frequently_ge VitaliFamily.null_of_frequently_le_of_frequently_ge
/-- If `ρ` is absolutely continuous with respect to `μ`, then for almost every `x`,
the ratio `ρ a / μ a` converges as `a` shrinks to `x` along a Vitali family for `μ`. -/
| Mathlib/MeasureTheory/Covering/Differentiation.lean | 233 | 263 | theorem ae_tendsto_div : ∀ᵐ x ∂μ, ∃ c, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 c) := by |
obtain ⟨w, w_count, w_dense, _, w_top⟩ :
∃ w : Set ℝ≥0∞, w.Countable ∧ Dense w ∧ 0 ∉ w ∧ ∞ ∉ w :=
ENNReal.exists_countable_dense_no_zero_top
have I : ∀ x ∈ w, x ≠ ∞ := fun x xs hx => w_top (hx ▸ xs)
have A : ∀ c ∈ w, ∀ d ∈ w, c < d → ∀ᵐ x ∂μ,
¬((∃ᶠ a in v.filterAt x, ρ a / μ a < c) ∧ ∃ᶠ a in v.filterAt x, d < ρ a / μ a) := by
intro c hc d hd hcd
lift c to ℝ≥0 using I c hc
lift d to ℝ≥0 using I d hd
apply v.null_of_frequently_le_of_frequently_ge hρ (ENNReal.coe_lt_coe.1 hcd)
· simp only [and_imp, exists_prop, not_frequently, not_and, not_lt, not_le, not_eventually,
mem_setOf_eq, mem_compl_iff, not_forall]
intro x h1x _
apply h1x.mono fun a ha => ?_
refine (ENNReal.div_le_iff_le_mul ?_ (Or.inr (bot_le.trans_lt ha).ne')).1 ha.le
simp only [ENNReal.coe_ne_top, Ne, or_true_iff, not_false_iff]
· simp only [and_imp, exists_prop, not_frequently, not_and, not_lt, not_le, not_eventually,
mem_setOf_eq, mem_compl_iff, not_forall]
intro x _ h2x
apply h2x.mono fun a ha => ?_
exact ENNReal.mul_le_of_le_div ha.le
have B : ∀ᵐ x ∂μ, ∀ c ∈ w, ∀ d ∈ w, c < d →
¬((∃ᶠ a in v.filterAt x, ρ a / μ a < c) ∧ ∃ᶠ a in v.filterAt x, d < ρ a / μ a) := by
#adaptation_note /-- 2024-04-23
The next two lines were previously just `simpa only [ae_ball_iff w_count, ae_all_iff]` -/
rw [ae_ball_iff w_count]; intro x hx; rw [ae_ball_iff w_count]; revert x
simpa only [ae_all_iff]
filter_upwards [B]
intro x hx
exact tendsto_of_no_upcrossings w_dense hx
|
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