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/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Wen Yang
-/
import Mathlib.LinearAlgebra.GeneralLinearGroup
import Mathlib.LinearAlgebra.Matrix.Adjugate
import Mathlib.LinearAlgebra.Matrix.Transvection
import Mathlib.RingTheory.RootsOfUnity.Basic
#align_import linear_algebra.matrix.special_linear_group from "leanprover-community/mathlib"@"f06058e64b7e8397234455038f3f8aec83aaba5a"
/-!
# The Special Linear group $SL(n, R)$
This file defines the elements of the Special Linear group `SpecialLinearGroup n R`, consisting
of all square `R`-matrices with determinant `1` on the fintype `n` by `n`. In addition, we define
the group structure on `SpecialLinearGroup n R` and the embedding into the general linear group
`GeneralLinearGroup R (n → R)`.
## Main definitions
* `Matrix.SpecialLinearGroup` is the type of matrices with determinant 1
* `Matrix.SpecialLinearGroup.group` gives the group structure (under multiplication)
* `Matrix.SpecialLinearGroup.toGL` is the embedding `SLₙ(R) → GLₙ(R)`
## Notation
For `m : ℕ`, we introduce the notation `SL(m,R)` for the special linear group on the fintype
`n = Fin m`, in the locale `MatrixGroups`.
## Implementation notes
The inverse operation in the `SpecialLinearGroup` is defined to be the adjugate
matrix, so that `SpecialLinearGroup n R` has a group structure for all `CommRing R`.
We define the elements of `SpecialLinearGroup` to be matrices, since we need to
compute their determinant. This is in contrast with `GeneralLinearGroup R M`,
which consists of invertible `R`-linear maps on `M`.
We provide `Matrix.SpecialLinearGroup.hasCoeToFun` for convenience, but do not state any
lemmas about it, and use `Matrix.SpecialLinearGroup.coeFn_eq_coe` to eliminate it `⇑` in favor
of a regular `↑` coercion.
## References
* https://en.wikipedia.org/wiki/Special_linear_group
## Tags
matrix group, group, matrix inverse
-/
namespace Matrix
universe u v
open Matrix
open LinearMap
section
variable (n : Type u) [DecidableEq n] [Fintype n] (R : Type v) [CommRing R]
/-- `SpecialLinearGroup n R` is the group of `n` by `n` `R`-matrices with determinant equal to 1.
-/
def SpecialLinearGroup :=
{ A : Matrix n n R // A.det = 1 }
#align matrix.special_linear_group Matrix.SpecialLinearGroup
end
@[inherit_doc]
scoped[MatrixGroups] notation "SL(" n ", " R ")" => Matrix.SpecialLinearGroup (Fin n) R
namespace SpecialLinearGroup
variable {n : Type u} [DecidableEq n] [Fintype n] {R : Type v} [CommRing R]
instance hasCoeToMatrix : Coe (SpecialLinearGroup n R) (Matrix n n R) :=
⟨fun A => A.val⟩
#align matrix.special_linear_group.has_coe_to_matrix Matrix.SpecialLinearGroup.hasCoeToMatrix
/-- In this file, Lean often has a hard time working out the values of `n` and `R` for an expression
like `det ↑A`. Rather than writing `(A : Matrix n n R)` everywhere in this file which is annoyingly
verbose, or `A.val` which is not the simp-normal form for subtypes, we create a local notation
`↑ₘA`. This notation references the local `n` and `R` variables, so is not valid as a global
notation. -/
local notation:1024 "↑ₘ" A:1024 => ((A : SpecialLinearGroup n R) : Matrix n n R)
-- Porting note: moved this section upwards because it used to be not simp-normal.
-- Now it is, since coercion arrows are unfolded.
section CoeFnInstance
/-- This instance is here for convenience, but is literally the same as the coercion from
`hasCoeToMatrix`. -/
instance instCoeFun : CoeFun (SpecialLinearGroup n R) fun _ => n → n → R where coe A := ↑ₘA
end CoeFnInstance
theorem ext_iff (A B : SpecialLinearGroup n R) : A = B ↔ ∀ i j, ↑ₘA i j = ↑ₘB i j :=
Subtype.ext_iff.trans Matrix.ext_iff.symm
#align matrix.special_linear_group.ext_iff Matrix.SpecialLinearGroup.ext_iff
@[ext]
theorem ext (A B : SpecialLinearGroup n R) : (∀ i j, ↑ₘA i j = ↑ₘB i j) → A = B :=
(SpecialLinearGroup.ext_iff A B).mpr
#align matrix.special_linear_group.ext Matrix.SpecialLinearGroup.ext
instance subsingleton_of_subsingleton [Subsingleton n] : Subsingleton (SpecialLinearGroup n R) := by
refine ⟨fun ⟨A, hA⟩ ⟨B, hB⟩ ↦ ?_⟩
ext i j
rcases isEmpty_or_nonempty n with hn | hn; · exfalso; exact IsEmpty.false i
rw [det_eq_elem_of_subsingleton _ i] at hA hB
simp only [Subsingleton.elim j i, hA, hB]
instance hasInv : Inv (SpecialLinearGroup n R) :=
⟨fun A => ⟨adjugate A, by rw [det_adjugate, A.prop, one_pow]⟩⟩
#align matrix.special_linear_group.has_inv Matrix.SpecialLinearGroup.hasInv
instance hasMul : Mul (SpecialLinearGroup n R) :=
⟨fun A B => ⟨↑ₘA * ↑ₘB, by rw [det_mul, A.prop, B.prop, one_mul]⟩⟩
#align matrix.special_linear_group.has_mul Matrix.SpecialLinearGroup.hasMul
instance hasOne : One (SpecialLinearGroup n R) :=
⟨⟨1, det_one⟩⟩
#align matrix.special_linear_group.has_one Matrix.SpecialLinearGroup.hasOne
instance : Pow (SpecialLinearGroup n R) ℕ where
pow x n := ⟨↑ₘx ^ n, (det_pow _ _).trans <| x.prop.symm ▸ one_pow _⟩
instance : Inhabited (SpecialLinearGroup n R) :=
⟨1⟩
/-- The transpose of a matrix in `SL(n, R)` -/
def transpose (A : SpecialLinearGroup n R) : SpecialLinearGroup n R :=
⟨A.1.transpose, A.1.det_transpose ▸ A.2⟩
@[inherit_doc]
scoped postfix:1024 "ᵀ" => SpecialLinearGroup.transpose
section CoeLemmas
variable (A B : SpecialLinearGroup n R)
-- Porting note: shouldn't be `@[simp]` because cast+mk gets reduced anyway
theorem coe_mk (A : Matrix n n R) (h : det A = 1) : ↑(⟨A, h⟩ : SpecialLinearGroup n R) = A :=
rfl
#align matrix.special_linear_group.coe_mk Matrix.SpecialLinearGroup.coe_mk
@[simp]
theorem coe_inv : ↑ₘA⁻¹ = adjugate A :=
rfl
#align matrix.special_linear_group.coe_inv Matrix.SpecialLinearGroup.coe_inv
@[simp]
theorem coe_mul : ↑ₘ(A * B) = ↑ₘA * ↑ₘB :=
rfl
#align matrix.special_linear_group.coe_mul Matrix.SpecialLinearGroup.coe_mul
@[simp]
theorem coe_one : ↑ₘ(1 : SpecialLinearGroup n R) = (1 : Matrix n n R) :=
rfl
#align matrix.special_linear_group.coe_one Matrix.SpecialLinearGroup.coe_one
@[simp]
theorem det_coe : det ↑ₘA = 1 :=
A.2
#align matrix.special_linear_group.det_coe Matrix.SpecialLinearGroup.det_coe
@[simp]
theorem coe_pow (m : ℕ) : ↑ₘ(A ^ m) = ↑ₘA ^ m :=
rfl
#align matrix.special_linear_group.coe_pow Matrix.SpecialLinearGroup.coe_pow
@[simp]
lemma coe_transpose (A : SpecialLinearGroup n R) : ↑ₘAᵀ = (↑ₘA)ᵀ :=
rfl
| Mathlib/LinearAlgebra/Matrix/SpecialLinearGroup.lean | 181 | 183 | theorem det_ne_zero [Nontrivial R] (g : SpecialLinearGroup n R) : det ↑ₘg ≠ 0 := by |
rw [g.det_coe]
norm_num
|
/-
Copyright (c) 2022 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Felix Weilacher
-/
import Mathlib.Data.Real.Cardinality
import Mathlib.Topology.MetricSpace.Perfect
import Mathlib.MeasureTheory.Constructions.BorelSpace.Metric
import Mathlib.Topology.CountableSeparatingOn
#align_import measure_theory.constructions.polish from "leanprover-community/mathlib"@"9f55d0d4363ae59948c33864cbc52e0b12e0e8ce"
/-!
# The Borel sigma-algebra on Polish spaces
We discuss several results pertaining to the relationship between the topology and the Borel
structure on Polish spaces.
## Main definitions and results
First, we define standard Borel spaces.
* A `StandardBorelSpace α` is a typeclass for measurable spaces which arise as the Borel sets
of some Polish topology.
Next, we define the class of analytic sets and establish its basic properties.
* `MeasureTheory.AnalyticSet s`: a set in a topological space is analytic if it is the continuous
image of a Polish space. Equivalently, it is empty, or the image of `ℕ → ℕ`.
* `MeasureTheory.AnalyticSet.image_of_continuous`: a continuous image of an analytic set is
analytic.
* `MeasurableSet.analyticSet`: in a Polish space, any Borel-measurable set is analytic.
Then, we show Lusin's theorem that two disjoint analytic sets can be separated by Borel sets.
* `MeasurablySeparable s t` states that there exists a measurable set containing `s` and disjoint
from `t`.
* `AnalyticSet.measurablySeparable` shows that two disjoint analytic sets are separated by a
Borel set.
We then prove the Lusin-Souslin theorem that a continuous injective image of a Borel subset of
a Polish space is Borel. The proof of this nontrivial result relies on the above results on
analytic sets.
* `MeasurableSet.image_of_continuousOn_injOn` asserts that, if `s` is a Borel measurable set in
a Polish space, then the image of `s` under a continuous injective map is still Borel measurable.
* `Continuous.measurableEmbedding` states that a continuous injective map on a Polish space
is a measurable embedding for the Borel sigma-algebra.
* `ContinuousOn.measurableEmbedding` is the same result for a map restricted to a measurable set
on which it is continuous.
* `Measurable.measurableEmbedding` states that a measurable injective map from
a standard Borel space to a second-countable topological space is a measurable embedding.
* `isClopenable_iff_measurableSet`: in a Polish space, a set is clopenable (i.e., it can be made
open and closed by using a finer Polish topology) if and only if it is Borel-measurable.
We use this to prove several versions of the Borel isomorphism theorem.
* `PolishSpace.measurableEquivOfNotCountable` : Any two uncountable standard Borel spaces
are Borel isomorphic.
* `PolishSpace.Equiv.measurableEquiv` : Any two standard Borel spaces of the same cardinality
are Borel isomorphic.
-/
open Set Function PolishSpace PiNat TopologicalSpace Bornology Metric Filter Topology MeasureTheory
/-! ### Standard Borel Spaces -/
variable (α : Type*)
/-- A standard Borel space is a measurable space arising as the Borel sets of some Polish topology.
This is useful in situations where a space has no natural topology or
the natural topology in a space is non-Polish.
To endow a standard Borel space `α` with a compatible Polish topology, use
`letI := upgradeStandardBorel α`. One can then use `eq_borel_upgradeStandardBorel α` to
rewrite the `MeasurableSpace α` instance to `borel α t`, where `t` is the new topology. -/
class StandardBorelSpace [MeasurableSpace α] : Prop where
/-- There exists a compatible Polish topology. -/
polish : ∃ _ : TopologicalSpace α, BorelSpace α ∧ PolishSpace α
/-- A convenience class similar to `UpgradedPolishSpace`. No instance should be registered.
Instead one should use `letI := upgradeStandardBorel α`. -/
class UpgradedStandardBorel extends MeasurableSpace α, TopologicalSpace α,
BorelSpace α, PolishSpace α
/-- Use as `letI := upgradeStandardBorel α` to endow a standard Borel space `α` with
a compatible Polish topology.
Warning: following this with `borelize α` will cause an error. Instead, one can
rewrite with `eq_borel_upgradeStandardBorel α`.
TODO: fix the corresponding bug in `borelize`. -/
noncomputable
def upgradeStandardBorel [MeasurableSpace α] [h : StandardBorelSpace α] :
UpgradedStandardBorel α := by
choose τ hb hp using h.polish
constructor
/-- The `MeasurableSpace α` instance on a `StandardBorelSpace` `α` is equal to
the borel sets of `upgradeStandardBorel α`. -/
theorem eq_borel_upgradeStandardBorel [MeasurableSpace α] [StandardBorelSpace α] :
‹MeasurableSpace α› = @borel _ (upgradeStandardBorel α).toTopologicalSpace :=
@BorelSpace.measurable_eq _ (upgradeStandardBorel α).toTopologicalSpace _
(upgradeStandardBorel α).toBorelSpace
variable {α}
section
variable [MeasurableSpace α]
instance standardBorel_of_polish [τ : TopologicalSpace α]
[BorelSpace α] [PolishSpace α] : StandardBorelSpace α := by exists τ
instance countablyGenerated_of_standardBorel [StandardBorelSpace α] :
MeasurableSpace.CountablyGenerated α :=
letI := upgradeStandardBorel α
inferInstance
instance measurableSingleton_of_standardBorel [StandardBorelSpace α] : MeasurableSingletonClass α :=
letI := upgradeStandardBorel α
inferInstance
namespace StandardBorelSpace
variable {β : Type*} [MeasurableSpace β]
section instances
/-- A product of two standard Borel spaces is standard Borel. -/
instance prod [StandardBorelSpace α] [StandardBorelSpace β] : StandardBorelSpace (α × β) :=
letI := upgradeStandardBorel α
letI := upgradeStandardBorel β
inferInstance
/-- A product of countably many standard Borel spaces is standard Borel. -/
instance pi_countable {ι : Type*} [Countable ι] {α : ι → Type*} [∀ n, MeasurableSpace (α n)]
[∀ n, StandardBorelSpace (α n)] : StandardBorelSpace (∀ n, α n) :=
letI := fun n => upgradeStandardBorel (α n)
inferInstance
end instances
end StandardBorelSpace
end section
variable {ι : Type*}
namespace MeasureTheory
variable [TopologicalSpace α]
/-! ### Analytic sets -/
/-- An analytic set is a set which is the continuous image of some Polish space. There are several
equivalent characterizations of this definition. For the definition, we pick one that avoids
universe issues: a set is analytic if and only if it is a continuous image of `ℕ → ℕ` (or if it
is empty). The above more usual characterization is given
in `analyticSet_iff_exists_polishSpace_range`.
Warning: these are analytic sets in the context of descriptive set theory (which is why they are
registered in the namespace `MeasureTheory`). They have nothing to do with analytic sets in the
context of complex analysis. -/
irreducible_def AnalyticSet (s : Set α) : Prop :=
s = ∅ ∨ ∃ f : (ℕ → ℕ) → α, Continuous f ∧ range f = s
#align measure_theory.analytic_set MeasureTheory.AnalyticSet
theorem analyticSet_empty : AnalyticSet (∅ : Set α) := by
rw [AnalyticSet]
exact Or.inl rfl
#align measure_theory.analytic_set_empty MeasureTheory.analyticSet_empty
theorem analyticSet_range_of_polishSpace {β : Type*} [TopologicalSpace β] [PolishSpace β]
{f : β → α} (f_cont : Continuous f) : AnalyticSet (range f) := by
cases isEmpty_or_nonempty β
· rw [range_eq_empty]
exact analyticSet_empty
· rw [AnalyticSet]
obtain ⟨g, g_cont, hg⟩ : ∃ g : (ℕ → ℕ) → β, Continuous g ∧ Surjective g :=
exists_nat_nat_continuous_surjective β
refine Or.inr ⟨f ∘ g, f_cont.comp g_cont, ?_⟩
rw [hg.range_comp]
#align measure_theory.analytic_set_range_of_polish_space MeasureTheory.analyticSet_range_of_polishSpace
/-- The image of an open set under a continuous map is analytic. -/
theorem _root_.IsOpen.analyticSet_image {β : Type*} [TopologicalSpace β] [PolishSpace β]
{s : Set β} (hs : IsOpen s) {f : β → α} (f_cont : Continuous f) : AnalyticSet (f '' s) := by
rw [image_eq_range]
haveI : PolishSpace s := hs.polishSpace
exact analyticSet_range_of_polishSpace (f_cont.comp continuous_subtype_val)
#align is_open.analytic_set_image IsOpen.analyticSet_image
/-- A set is analytic if and only if it is the continuous image of some Polish space. -/
theorem analyticSet_iff_exists_polishSpace_range {s : Set α} :
AnalyticSet s ↔
∃ (β : Type) (h : TopologicalSpace β) (_ : @PolishSpace β h) (f : β → α),
@Continuous _ _ h _ f ∧ range f = s := by
constructor
· intro h
rw [AnalyticSet] at h
cases' h with h h
· refine ⟨Empty, inferInstance, inferInstance, Empty.elim, continuous_bot, ?_⟩
rw [h]
exact range_eq_empty _
· exact ⟨ℕ → ℕ, inferInstance, inferInstance, h⟩
· rintro ⟨β, h, h', f, f_cont, f_range⟩
rw [← f_range]
exact analyticSet_range_of_polishSpace f_cont
#align measure_theory.analytic_set_iff_exists_polish_space_range MeasureTheory.analyticSet_iff_exists_polishSpace_range
/-- The continuous image of an analytic set is analytic -/
theorem AnalyticSet.image_of_continuousOn {β : Type*} [TopologicalSpace β] {s : Set α}
(hs : AnalyticSet s) {f : α → β} (hf : ContinuousOn f s) : AnalyticSet (f '' s) := by
rcases analyticSet_iff_exists_polishSpace_range.1 hs with ⟨γ, γtop, γpolish, g, g_cont, gs⟩
have : f '' s = range (f ∘ g) := by rw [range_comp, gs]
rw [this]
apply analyticSet_range_of_polishSpace
apply hf.comp_continuous g_cont fun x => _
rw [← gs]
exact mem_range_self
#align measure_theory.analytic_set.image_of_continuous_on MeasureTheory.AnalyticSet.image_of_continuousOn
theorem AnalyticSet.image_of_continuous {β : Type*} [TopologicalSpace β] {s : Set α}
(hs : AnalyticSet s) {f : α → β} (hf : Continuous f) : AnalyticSet (f '' s) :=
hs.image_of_continuousOn hf.continuousOn
#align measure_theory.analytic_set.image_of_continuous MeasureTheory.AnalyticSet.image_of_continuous
/-- A countable intersection of analytic sets is analytic. -/
theorem AnalyticSet.iInter [hι : Nonempty ι] [Countable ι] [T2Space α] {s : ι → Set α}
(hs : ∀ n, AnalyticSet (s n)) : AnalyticSet (⋂ n, s n) := by
rcases hι with ⟨i₀⟩
/- For the proof, write each `s n` as the continuous image under a map `f n` of a
Polish space `β n`. The product space `γ = Π n, β n` is also Polish, and so is the subset
`t` of sequences `x n` for which `f n (x n)` is independent of `n`. The set `t` is Polish, and
the range of `x ↦ f 0 (x 0)` on `t` is exactly `⋂ n, s n`, so this set is analytic. -/
choose β hβ h'β f f_cont f_range using fun n =>
analyticSet_iff_exists_polishSpace_range.1 (hs n)
let γ := ∀ n, β n
let t : Set γ := ⋂ n, { x | f n (x n) = f i₀ (x i₀) }
have t_closed : IsClosed t := by
apply isClosed_iInter
intro n
exact
isClosed_eq ((f_cont n).comp (continuous_apply n)) ((f_cont i₀).comp (continuous_apply i₀))
haveI : PolishSpace t := t_closed.polishSpace
let F : t → α := fun x => f i₀ ((x : γ) i₀)
have F_cont : Continuous F := (f_cont i₀).comp ((continuous_apply i₀).comp continuous_subtype_val)
have F_range : range F = ⋂ n : ι, s n := by
apply Subset.antisymm
· rintro y ⟨x, rfl⟩
refine mem_iInter.2 fun n => ?_
have : f n ((x : γ) n) = F x := (mem_iInter.1 x.2 n : _)
rw [← this, ← f_range n]
exact mem_range_self _
· intro y hy
have A : ∀ n, ∃ x : β n, f n x = y := by
intro n
rw [← mem_range, f_range n]
exact mem_iInter.1 hy n
choose x hx using A
have xt : x ∈ t := by
refine mem_iInter.2 fun n => ?_
simp [hx]
refine ⟨⟨x, xt⟩, ?_⟩
exact hx i₀
rw [← F_range]
exact analyticSet_range_of_polishSpace F_cont
#align measure_theory.analytic_set.Inter MeasureTheory.AnalyticSet.iInter
/-- A countable union of analytic sets is analytic. -/
theorem AnalyticSet.iUnion [Countable ι] {s : ι → Set α} (hs : ∀ n, AnalyticSet (s n)) :
AnalyticSet (⋃ n, s n) := by
/- For the proof, write each `s n` as the continuous image under a map `f n` of a
Polish space `β n`. The union space `γ = Σ n, β n` is also Polish, and the map `F : γ → α` which
coincides with `f n` on `β n` sends it to `⋃ n, s n`. -/
choose β hβ h'β f f_cont f_range using fun n =>
analyticSet_iff_exists_polishSpace_range.1 (hs n)
let γ := Σn, β n
let F : γ → α := fun ⟨n, x⟩ ↦ f n x
have F_cont : Continuous F := continuous_sigma f_cont
have F_range : range F = ⋃ n, s n := by
simp only [γ, range_sigma_eq_iUnion_range, f_range]
rw [← F_range]
exact analyticSet_range_of_polishSpace F_cont
#align measure_theory.analytic_set.Union MeasureTheory.AnalyticSet.iUnion
theorem _root_.IsClosed.analyticSet [PolishSpace α] {s : Set α} (hs : IsClosed s) :
AnalyticSet s := by
haveI : PolishSpace s := hs.polishSpace
rw [← @Subtype.range_val α s]
exact analyticSet_range_of_polishSpace continuous_subtype_val
#align is_closed.analytic_set IsClosed.analyticSet
/-- Given a Borel-measurable set in a Polish space, there exists a finer Polish topology making
it clopen. This is in fact an equivalence, see `isClopenable_iff_measurableSet`. -/
theorem _root_.MeasurableSet.isClopenable [PolishSpace α] [MeasurableSpace α] [BorelSpace α]
{s : Set α} (hs : MeasurableSet s) : IsClopenable s := by
revert s
apply MeasurableSet.induction_on_open
· exact fun u hu => hu.isClopenable
· exact fun u _ h'u => h'u.compl
· exact fun f _ _ hf => IsClopenable.iUnion hf
#align measurable_set.is_clopenable MeasurableSet.isClopenable
/-- A Borel-measurable set in a Polish space is analytic. -/
theorem _root_.MeasurableSet.analyticSet {α : Type*} [t : TopologicalSpace α] [PolishSpace α]
[MeasurableSpace α] [BorelSpace α] {s : Set α} (hs : MeasurableSet s) : AnalyticSet s := by
/- For a short proof (avoiding measurable induction), one sees `s` as a closed set for a finer
topology `t'`. It is analytic for this topology. As the identity from `t'` to `t` is continuous
and the image of an analytic set is analytic, it follows that `s` is also analytic for `t`. -/
obtain ⟨t', t't, t'_polish, s_closed, _⟩ :
∃ t' : TopologicalSpace α, t' ≤ t ∧ @PolishSpace α t' ∧ IsClosed[t'] s ∧ IsOpen[t'] s :=
hs.isClopenable
have A := @IsClosed.analyticSet α t' t'_polish s s_closed
convert @AnalyticSet.image_of_continuous α t' α t s A id (continuous_id_of_le t't)
simp only [id, image_id']
#align measurable_set.analytic_set MeasurableSet.analyticSet
/-- Given a Borel-measurable function from a Polish space to a second-countable space, there exists
a finer Polish topology on the source space for which the function is continuous. -/
theorem _root_.Measurable.exists_continuous {α β : Type*} [t : TopologicalSpace α] [PolishSpace α]
[MeasurableSpace α] [BorelSpace α] [tβ : TopologicalSpace β] [MeasurableSpace β]
[OpensMeasurableSpace β] {f : α → β} [SecondCountableTopology (range f)] (hf : Measurable f) :
∃ t' : TopologicalSpace α, t' ≤ t ∧ @Continuous α β t' tβ f ∧ @PolishSpace α t' := by
obtain ⟨b, b_count, -, hb⟩ :
∃ b : Set (Set (range f)), b.Countable ∧ ∅ ∉ b ∧ IsTopologicalBasis b :=
exists_countable_basis (range f)
haveI : Countable b := b_count.to_subtype
have : ∀ s : b, IsClopenable (rangeFactorization f ⁻¹' s) := fun s ↦ by
apply MeasurableSet.isClopenable
exact hf.subtype_mk (hb.isOpen s.2).measurableSet
choose T Tt Tpolish _ Topen using this
obtain ⟨t', t'T, t't, t'_polish⟩ :
∃ t' : TopologicalSpace α, (∀ i, t' ≤ T i) ∧ t' ≤ t ∧ @PolishSpace α t' :=
exists_polishSpace_forall_le (t := t) T Tt Tpolish
refine ⟨t', t't, ?_, t'_polish⟩
have : Continuous[t', _] (rangeFactorization f) :=
hb.continuous_iff.2 fun s hs => t'T ⟨s, hs⟩ _ (Topen ⟨s, hs⟩)
exact continuous_subtype_val.comp this
#align measurable.exists_continuous Measurable.exists_continuous
/-- The image of a measurable set in a standard Borel space under a measurable map
is an analytic set. -/
theorem _root_.MeasurableSet.analyticSet_image {X Y : Type*} [MeasurableSpace X]
[StandardBorelSpace X] [TopologicalSpace Y] [MeasurableSpace Y]
[OpensMeasurableSpace Y] {f : X → Y} [SecondCountableTopology (range f)] {s : Set X}
(hs : MeasurableSet s) (hf : Measurable f) : AnalyticSet (f '' s) := by
letI := upgradeStandardBorel X
rw [eq_borel_upgradeStandardBorel X] at hs
rcases hf.exists_continuous with ⟨τ', hle, hfc, hτ'⟩
letI m' : MeasurableSpace X := @borel _ τ'
haveI b' : BorelSpace X := ⟨rfl⟩
have hle := borel_anti hle
exact (hle _ hs).analyticSet.image_of_continuous hfc
#align measurable_set.analytic_set_image MeasurableSet.analyticSet_image
/-- Preimage of an analytic set is an analytic set. -/
protected lemma AnalyticSet.preimage {X Y : Type*} [TopologicalSpace X] [TopologicalSpace Y]
[PolishSpace X] [T2Space Y] {s : Set Y} (hs : AnalyticSet s) {f : X → Y} (hf : Continuous f) :
AnalyticSet (f ⁻¹' s) := by
rcases analyticSet_iff_exists_polishSpace_range.1 hs with ⟨Z, _, _, g, hg, rfl⟩
have : IsClosed {x : X × Z | f x.1 = g x.2} := isClosed_diagonal.preimage (hf.prod_map hg)
convert this.analyticSet.image_of_continuous continuous_fst
ext x
simp [eq_comm]
/-! ### Separating sets with measurable sets -/
/-- Two sets `u` and `v` in a measurable space are measurably separable if there
exists a measurable set containing `u` and disjoint from `v`.
This is mostly interesting for Borel-separable sets. -/
def MeasurablySeparable {α : Type*} [MeasurableSpace α] (s t : Set α) : Prop :=
∃ u, s ⊆ u ∧ Disjoint t u ∧ MeasurableSet u
#align measure_theory.measurably_separable MeasureTheory.MeasurablySeparable
theorem MeasurablySeparable.iUnion [Countable ι] {α : Type*} [MeasurableSpace α] {s t : ι → Set α}
(h : ∀ m n, MeasurablySeparable (s m) (t n)) : MeasurablySeparable (⋃ n, s n) (⋃ m, t m) := by
choose u hsu htu hu using h
refine ⟨⋃ m, ⋂ n, u m n, ?_, ?_, ?_⟩
· refine iUnion_subset fun m => subset_iUnion_of_subset m ?_
exact subset_iInter fun n => hsu m n
· simp_rw [disjoint_iUnion_left, disjoint_iUnion_right]
intro n m
apply Disjoint.mono_right _ (htu m n)
apply iInter_subset
· refine MeasurableSet.iUnion fun m => ?_
exact MeasurableSet.iInter fun n => hu m n
#align measure_theory.measurably_separable.Union MeasureTheory.MeasurablySeparable.iUnion
/-- The hard part of the Lusin separation theorem saying that two disjoint analytic sets are
contained in disjoint Borel sets (see the full statement in `AnalyticSet.measurablySeparable`).
Here, we prove this when our analytic sets are the ranges of functions from `ℕ → ℕ`.
-/
theorem measurablySeparable_range_of_disjoint [T2Space α] [MeasurableSpace α]
[OpensMeasurableSpace α] {f g : (ℕ → ℕ) → α} (hf : Continuous f) (hg : Continuous g)
(h : Disjoint (range f) (range g)) : MeasurablySeparable (range f) (range g) := by
/- We follow [Kechris, *Classical Descriptive Set Theory* (Theorem 14.7)][kechris1995].
If the ranges are not Borel-separated, then one can find two cylinders of length one whose
images are not Borel-separated, and then two smaller cylinders of length two whose images are
not Borel-separated, and so on. One thus gets two sequences of cylinders, that decrease to two
points `x` and `y`. Their images are different by the disjointness assumption, hence contained
in two disjoint open sets by the T2 property. By continuity, long enough cylinders around `x`
and `y` have images which are separated by these two disjoint open sets, a contradiction.
-/
by_contra hfg
have I : ∀ n x y, ¬MeasurablySeparable (f '' cylinder x n) (g '' cylinder y n) →
∃ x' y', x' ∈ cylinder x n ∧ y' ∈ cylinder y n ∧
¬MeasurablySeparable (f '' cylinder x' (n + 1)) (g '' cylinder y' (n + 1)) := by
intro n x y
contrapose!
intro H
rw [← iUnion_cylinder_update x n, ← iUnion_cylinder_update y n, image_iUnion, image_iUnion]
refine MeasurablySeparable.iUnion fun i j => ?_
exact H _ _ (update_mem_cylinder _ _ _) (update_mem_cylinder _ _ _)
-- consider the set of pairs of cylinders of some length whose images are not Borel-separated
let A :=
{ p : ℕ × (ℕ → ℕ) × (ℕ → ℕ) //
¬MeasurablySeparable (f '' cylinder p.2.1 p.1) (g '' cylinder p.2.2 p.1) }
-- for each such pair, one can find longer cylinders whose images are not Borel-separated either
have : ∀ p : A, ∃ q : A,
q.1.1 = p.1.1 + 1 ∧ q.1.2.1 ∈ cylinder p.1.2.1 p.1.1 ∧ q.1.2.2 ∈ cylinder p.1.2.2 p.1.1 := by
rintro ⟨⟨n, x, y⟩, hp⟩
rcases I n x y hp with ⟨x', y', hx', hy', h'⟩
exact ⟨⟨⟨n + 1, x', y'⟩, h'⟩, rfl, hx', hy'⟩
choose F hFn hFx hFy using this
let p0 : A := ⟨⟨0, fun _ => 0, fun _ => 0⟩, by simp [hfg]⟩
-- construct inductively decreasing sequences of cylinders whose images are not separated
let p : ℕ → A := fun n => F^[n] p0
have prec : ∀ n, p (n + 1) = F (p n) := fun n => by simp only [p, iterate_succ', Function.comp]
-- check that at the `n`-th step we deal with cylinders of length `n`
have pn_fst : ∀ n, (p n).1.1 = n := by
intro n
induction' n with n IH
· rfl
· simp only [prec, hFn, IH]
-- check that the cylinders we construct are indeed decreasing, by checking that the coordinates
-- are stationary.
have Ix : ∀ m n, m + 1 ≤ n → (p n).1.2.1 m = (p (m + 1)).1.2.1 m := by
intro m
apply Nat.le_induction
· rfl
intro n hmn IH
have I : (F (p n)).val.snd.fst m = (p n).val.snd.fst m := by
apply hFx (p n) m
rw [pn_fst]
exact hmn
rw [prec, I, IH]
have Iy : ∀ m n, m + 1 ≤ n → (p n).1.2.2 m = (p (m + 1)).1.2.2 m := by
intro m
apply Nat.le_induction
· rfl
intro n hmn IH
have I : (F (p n)).val.snd.snd m = (p n).val.snd.snd m := by
apply hFy (p n) m
rw [pn_fst]
exact hmn
rw [prec, I, IH]
-- denote by `x` and `y` the limit points of these two sequences of cylinders.
set x : ℕ → ℕ := fun n => (p (n + 1)).1.2.1 n with hx
set y : ℕ → ℕ := fun n => (p (n + 1)).1.2.2 n with hy
-- by design, the cylinders around these points have images which are not Borel-separable.
have M : ∀ n, ¬MeasurablySeparable (f '' cylinder x n) (g '' cylinder y n) := by
intro n
convert (p n).2 using 3
· rw [pn_fst, ← mem_cylinder_iff_eq, mem_cylinder_iff]
intro i hi
rw [hx]
exact (Ix i n hi).symm
· rw [pn_fst, ← mem_cylinder_iff_eq, mem_cylinder_iff]
intro i hi
rw [hy]
exact (Iy i n hi).symm
-- consider two open sets separating `f x` and `g y`.
obtain ⟨u, v, u_open, v_open, xu, yv, huv⟩ :
∃ u v : Set α, IsOpen u ∧ IsOpen v ∧ f x ∈ u ∧ g y ∈ v ∧ Disjoint u v := by
apply t2_separation
exact disjoint_iff_forall_ne.1 h (mem_range_self _) (mem_range_self _)
letI : MetricSpace (ℕ → ℕ) := metricSpaceNatNat
obtain ⟨εx, εxpos, hεx⟩ : ∃ (εx : ℝ), εx > 0 ∧ Metric.ball x εx ⊆ f ⁻¹' u := by
apply Metric.mem_nhds_iff.1
exact hf.continuousAt.preimage_mem_nhds (u_open.mem_nhds xu)
obtain ⟨εy, εypos, hεy⟩ : ∃ (εy : ℝ), εy > 0 ∧ Metric.ball y εy ⊆ g ⁻¹' v := by
apply Metric.mem_nhds_iff.1
exact hg.continuousAt.preimage_mem_nhds (v_open.mem_nhds yv)
obtain ⟨n, hn⟩ : ∃ n : ℕ, (1 / 2 : ℝ) ^ n < min εx εy :=
exists_pow_lt_of_lt_one (lt_min εxpos εypos) (by norm_num)
-- for large enough `n`, these open sets separate the images of long cylinders around `x` and `y`
have B : MeasurablySeparable (f '' cylinder x n) (g '' cylinder y n) := by
refine ⟨u, ?_, ?_, u_open.measurableSet⟩
· rw [image_subset_iff]
apply Subset.trans _ hεx
intro z hz
rw [mem_cylinder_iff_dist_le] at hz
exact hz.trans_lt (hn.trans_le (min_le_left _ _))
· refine Disjoint.mono_left ?_ huv.symm
change g '' cylinder y n ⊆ v
rw [image_subset_iff]
apply Subset.trans _ hεy
intro z hz
rw [mem_cylinder_iff_dist_le] at hz
exact hz.trans_lt (hn.trans_le (min_le_right _ _))
-- this is a contradiction.
exact M n B
#align measure_theory.measurably_separable_range_of_disjoint MeasureTheory.measurablySeparable_range_of_disjoint
/-- The **Lusin separation theorem**: if two analytic sets are disjoint, then they are contained in
disjoint Borel sets. -/
theorem AnalyticSet.measurablySeparable [T2Space α] [MeasurableSpace α] [OpensMeasurableSpace α]
{s t : Set α} (hs : AnalyticSet s) (ht : AnalyticSet t) (h : Disjoint s t) :
MeasurablySeparable s t := by
rw [AnalyticSet] at hs ht
rcases hs with (rfl | ⟨f, f_cont, rfl⟩)
· refine ⟨∅, Subset.refl _, by simp, MeasurableSet.empty⟩
rcases ht with (rfl | ⟨g, g_cont, rfl⟩)
· exact ⟨univ, subset_univ _, by simp, MeasurableSet.univ⟩
exact measurablySeparable_range_of_disjoint f_cont g_cont h
#align measure_theory.analytic_set.measurably_separable MeasureTheory.AnalyticSet.measurablySeparable
/-- **Suslin's Theorem**: in a Hausdorff topological space, an analytic set with an analytic
complement is measurable. -/
theorem AnalyticSet.measurableSet_of_compl [T2Space α] [MeasurableSpace α] [OpensMeasurableSpace α]
{s : Set α} (hs : AnalyticSet s) (hsc : AnalyticSet sᶜ) : MeasurableSet s := by
rcases hs.measurablySeparable hsc disjoint_compl_right with ⟨u, hsu, hdu, hmu⟩
obtain rfl : s = u := hsu.antisymm (disjoint_compl_left_iff_subset.1 hdu)
exact hmu
#align measure_theory.analytic_set.measurable_set_of_compl MeasureTheory.AnalyticSet.measurableSet_of_compl
end MeasureTheory
/-!
### Measurability of preimages under measurable maps
-/
namespace Measurable
open MeasurableSpace
variable {X Y Z β : Type*} [MeasurableSpace X] [StandardBorelSpace X]
[TopologicalSpace Y] [T0Space Y] [MeasurableSpace Y] [OpensMeasurableSpace Y] [MeasurableSpace β]
[MeasurableSpace Z]
/-- If `f : X → Z` is a surjective Borel measurable map from a standard Borel space
to a countably separated measurable space, then the preimage of a set `s`
is measurable if and only if the set is measurable.
One implication is the definition of measurability, the other one heavily relies on `X` being a
standard Borel space. -/
| Mathlib/MeasureTheory/Constructions/Polish.lean | 548 | 557 | theorem measurableSet_preimage_iff_of_surjective [CountablySeparated Z]
{f : X → Z} (hf : Measurable f) (hsurj : Surjective f) {s : Set Z} :
MeasurableSet (f ⁻¹' s) ↔ MeasurableSet s := by |
refine ⟨fun h => ?_, fun h => hf h⟩
rcases exists_opensMeasurableSpace_of_countablySeparated Z with ⟨τ, _, _, _⟩
apply AnalyticSet.measurableSet_of_compl
· rw [← image_preimage_eq s hsurj]
exact h.analyticSet_image hf
· rw [← image_preimage_eq sᶜ hsurj]
exact h.compl.analyticSet_image hf
|
/-
Copyright (c) 2020 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca
-/
import Mathlib.Algebra.NeZero
import Mathlib.Algebra.Polynomial.BigOperators
import Mathlib.Algebra.Polynomial.Lifts
import Mathlib.Algebra.Polynomial.Splits
import Mathlib.RingTheory.RootsOfUnity.Complex
import Mathlib.NumberTheory.ArithmeticFunction
import Mathlib.RingTheory.RootsOfUnity.Basic
import Mathlib.FieldTheory.RatFunc.AsPolynomial
#align_import ring_theory.polynomial.cyclotomic.basic from "leanprover-community/mathlib"@"7fdeecc0d03cd40f7a165e6cf00a4d2286db599f"
/-!
# Cyclotomic polynomials.
For `n : ℕ` and an integral domain `R`, we define a modified version of the `n`-th cyclotomic
polynomial with coefficients in `R`, denoted `cyclotomic' n R`, as `∏ (X - μ)`, where `μ` varies
over the primitive `n`th roots of unity. If there is a primitive `n`th root of unity in `R` then
this the standard definition. We then define the standard cyclotomic polynomial `cyclotomic n R`
with coefficients in any ring `R`.
## Main definition
* `cyclotomic n R` : the `n`-th cyclotomic polynomial with coefficients in `R`.
## Main results
* `Polynomial.degree_cyclotomic` : The degree of `cyclotomic n` is `totient n`.
* `Polynomial.prod_cyclotomic_eq_X_pow_sub_one` : `X ^ n - 1 = ∏ (cyclotomic i)`, where `i`
divides `n`.
* `Polynomial.cyclotomic_eq_prod_X_pow_sub_one_pow_moebius` : The Möbius inversion formula for
`cyclotomic n R` over an abstract fraction field for `R[X]`.
## Implementation details
Our definition of `cyclotomic' n R` makes sense in any integral domain `R`, but the interesting
results hold if there is a primitive `n`-th root of unity in `R`. In particular, our definition is
not the standard one unless there is a primitive `n`th root of unity in `R`. For example,
`cyclotomic' 3 ℤ = 1`, since there are no primitive cube roots of unity in `ℤ`. The main example is
`R = ℂ`, we decided to work in general since the difficulties are essentially the same.
To get the standard cyclotomic polynomials, we use `unique_int_coeff_of_cycl`, with `R = ℂ`,
to get a polynomial with integer coefficients and then we map it to `R[X]`, for any ring `R`.
-/
open scoped Polynomial
noncomputable section
universe u
namespace Polynomial
section Cyclotomic'
section IsDomain
variable {R : Type*} [CommRing R] [IsDomain R]
/-- The modified `n`-th cyclotomic polynomial with coefficients in `R`, it is the usual cyclotomic
polynomial if there is a primitive `n`-th root of unity in `R`. -/
def cyclotomic' (n : ℕ) (R : Type*) [CommRing R] [IsDomain R] : R[X] :=
∏ μ ∈ primitiveRoots n R, (X - C μ)
#align polynomial.cyclotomic' Polynomial.cyclotomic'
/-- The zeroth modified cyclotomic polyomial is `1`. -/
@[simp]
theorem cyclotomic'_zero (R : Type*) [CommRing R] [IsDomain R] : cyclotomic' 0 R = 1 := by
simp only [cyclotomic', Finset.prod_empty, primitiveRoots_zero]
#align polynomial.cyclotomic'_zero Polynomial.cyclotomic'_zero
/-- The first modified cyclotomic polyomial is `X - 1`. -/
@[simp]
theorem cyclotomic'_one (R : Type*) [CommRing R] [IsDomain R] : cyclotomic' 1 R = X - 1 := by
simp only [cyclotomic', Finset.prod_singleton, RingHom.map_one,
IsPrimitiveRoot.primitiveRoots_one]
#align polynomial.cyclotomic'_one Polynomial.cyclotomic'_one
/-- The second modified cyclotomic polyomial is `X + 1` if the characteristic of `R` is not `2`. -/
@[simp]
theorem cyclotomic'_two (R : Type*) [CommRing R] [IsDomain R] (p : ℕ) [CharP R p] (hp : p ≠ 2) :
cyclotomic' 2 R = X + 1 := by
rw [cyclotomic']
have prim_root_two : primitiveRoots 2 R = {(-1 : R)} := by
simp only [Finset.eq_singleton_iff_unique_mem, mem_primitiveRoots two_pos]
exact ⟨IsPrimitiveRoot.neg_one p hp, fun x => IsPrimitiveRoot.eq_neg_one_of_two_right⟩
simp only [prim_root_two, Finset.prod_singleton, RingHom.map_neg, RingHom.map_one, sub_neg_eq_add]
#align polynomial.cyclotomic'_two Polynomial.cyclotomic'_two
/-- `cyclotomic' n R` is monic. -/
theorem cyclotomic'.monic (n : ℕ) (R : Type*) [CommRing R] [IsDomain R] :
(cyclotomic' n R).Monic :=
monic_prod_of_monic _ _ fun _ _ => monic_X_sub_C _
#align polynomial.cyclotomic'.monic Polynomial.cyclotomic'.monic
/-- `cyclotomic' n R` is different from `0`. -/
theorem cyclotomic'_ne_zero (n : ℕ) (R : Type*) [CommRing R] [IsDomain R] : cyclotomic' n R ≠ 0 :=
(cyclotomic'.monic n R).ne_zero
#align polynomial.cyclotomic'_ne_zero Polynomial.cyclotomic'_ne_zero
/-- The natural degree of `cyclotomic' n R` is `totient n` if there is a primitive root of
unity in `R`. -/
theorem natDegree_cyclotomic' {ζ : R} {n : ℕ} (h : IsPrimitiveRoot ζ n) :
(cyclotomic' n R).natDegree = Nat.totient n := by
rw [cyclotomic']
rw [natDegree_prod (primitiveRoots n R) fun z : R => X - C z]
· simp only [IsPrimitiveRoot.card_primitiveRoots h, mul_one, natDegree_X_sub_C, Nat.cast_id,
Finset.sum_const, nsmul_eq_mul]
intro z _
exact X_sub_C_ne_zero z
#align polynomial.nat_degree_cyclotomic' Polynomial.natDegree_cyclotomic'
/-- The degree of `cyclotomic' n R` is `totient n` if there is a primitive root of unity in `R`. -/
theorem degree_cyclotomic' {ζ : R} {n : ℕ} (h : IsPrimitiveRoot ζ n) :
(cyclotomic' n R).degree = Nat.totient n := by
simp only [degree_eq_natDegree (cyclotomic'_ne_zero n R), natDegree_cyclotomic' h]
#align polynomial.degree_cyclotomic' Polynomial.degree_cyclotomic'
/-- The roots of `cyclotomic' n R` are the primitive `n`-th roots of unity. -/
theorem roots_of_cyclotomic (n : ℕ) (R : Type*) [CommRing R] [IsDomain R] :
(cyclotomic' n R).roots = (primitiveRoots n R).val := by
rw [cyclotomic']; exact roots_prod_X_sub_C (primitiveRoots n R)
#align polynomial.roots_of_cyclotomic Polynomial.roots_of_cyclotomic
/-- If there is a primitive `n`th root of unity in `K`, then `X ^ n - 1 = ∏ (X - μ)`, where `μ`
varies over the `n`-th roots of unity. -/
theorem X_pow_sub_one_eq_prod {ζ : R} {n : ℕ} (hpos : 0 < n) (h : IsPrimitiveRoot ζ n) :
X ^ n - 1 = ∏ ζ ∈ nthRootsFinset n R, (X - C ζ) := by
classical
rw [nthRootsFinset, ← Multiset.toFinset_eq (IsPrimitiveRoot.nthRoots_one_nodup h)]
simp only [Finset.prod_mk, RingHom.map_one]
rw [nthRoots]
have hmonic : (X ^ n - C (1 : R)).Monic := monic_X_pow_sub_C (1 : R) (ne_of_lt hpos).symm
symm
apply prod_multiset_X_sub_C_of_monic_of_roots_card_eq hmonic
rw [@natDegree_X_pow_sub_C R _ _ n 1, ← nthRoots]
exact IsPrimitiveRoot.card_nthRoots_one h
set_option linter.uppercaseLean3 false in
#align polynomial.X_pow_sub_one_eq_prod Polynomial.X_pow_sub_one_eq_prod
end IsDomain
section Field
variable {K : Type*} [Field K]
/-- `cyclotomic' n K` splits. -/
theorem cyclotomic'_splits (n : ℕ) : Splits (RingHom.id K) (cyclotomic' n K) := by
apply splits_prod (RingHom.id K)
intro z _
simp only [splits_X_sub_C (RingHom.id K)]
#align polynomial.cyclotomic'_splits Polynomial.cyclotomic'_splits
/-- If there is a primitive `n`-th root of unity in `K`, then `X ^ n - 1` splits. -/
theorem X_pow_sub_one_splits {ζ : K} {n : ℕ} (h : IsPrimitiveRoot ζ n) :
Splits (RingHom.id K) (X ^ n - C (1 : K)) := by
rw [splits_iff_card_roots, ← nthRoots, IsPrimitiveRoot.card_nthRoots_one h, natDegree_X_pow_sub_C]
set_option linter.uppercaseLean3 false in
#align polynomial.X_pow_sub_one_splits Polynomial.X_pow_sub_one_splits
/-- If there is a primitive `n`-th root of unity in `K`, then
`∏ i ∈ Nat.divisors n, cyclotomic' i K = X ^ n - 1`. -/
theorem prod_cyclotomic'_eq_X_pow_sub_one {K : Type*} [CommRing K] [IsDomain K] {ζ : K} {n : ℕ}
(hpos : 0 < n) (h : IsPrimitiveRoot ζ n) :
∏ i ∈ Nat.divisors n, cyclotomic' i K = X ^ n - 1 := by
classical
have hd : (n.divisors : Set ℕ).PairwiseDisjoint fun k => primitiveRoots k K :=
fun x _ y _ hne => IsPrimitiveRoot.disjoint hne
simp only [X_pow_sub_one_eq_prod hpos h, cyclotomic', ← Finset.prod_biUnion hd,
h.nthRoots_one_eq_biUnion_primitiveRoots]
set_option linter.uppercaseLean3 false in
#align polynomial.prod_cyclotomic'_eq_X_pow_sub_one Polynomial.prod_cyclotomic'_eq_X_pow_sub_one
/-- If there is a primitive `n`-th root of unity in `K`, then
`cyclotomic' n K = (X ^ k - 1) /ₘ (∏ i ∈ Nat.properDivisors k, cyclotomic' i K)`. -/
theorem cyclotomic'_eq_X_pow_sub_one_div {K : Type*} [CommRing K] [IsDomain K] {ζ : K} {n : ℕ}
(hpos : 0 < n) (h : IsPrimitiveRoot ζ n) :
cyclotomic' n K = (X ^ n - 1) /ₘ ∏ i ∈ Nat.properDivisors n, cyclotomic' i K := by
rw [← prod_cyclotomic'_eq_X_pow_sub_one hpos h, ← Nat.cons_self_properDivisors hpos.ne',
Finset.prod_cons]
have prod_monic : (∏ i ∈ Nat.properDivisors n, cyclotomic' i K).Monic := by
apply monic_prod_of_monic
intro i _
exact cyclotomic'.monic i K
rw [(div_modByMonic_unique (cyclotomic' n K) 0 prod_monic _).1]
simp only [degree_zero, zero_add]
refine ⟨by rw [mul_comm], ?_⟩
rw [bot_lt_iff_ne_bot]
intro h
exact Monic.ne_zero prod_monic (degree_eq_bot.1 h)
set_option linter.uppercaseLean3 false in
#align polynomial.cyclotomic'_eq_X_pow_sub_one_div Polynomial.cyclotomic'_eq_X_pow_sub_one_div
/-- If there is a primitive `n`-th root of unity in `K`, then `cyclotomic' n K` comes from a
monic polynomial with integer coefficients. -/
theorem int_coeff_of_cyclotomic' {K : Type*} [CommRing K] [IsDomain K] {ζ : K} {n : ℕ}
(h : IsPrimitiveRoot ζ n) : ∃ P : ℤ[X], map (Int.castRingHom K) P =
cyclotomic' n K ∧ P.degree = (cyclotomic' n K).degree ∧ P.Monic := by
refine lifts_and_degree_eq_and_monic ?_ (cyclotomic'.monic n K)
induction' n using Nat.strong_induction_on with k ihk generalizing ζ
rcases k.eq_zero_or_pos with (rfl | hpos)
· use 1
simp only [cyclotomic'_zero, coe_mapRingHom, Polynomial.map_one]
let B : K[X] := ∏ i ∈ Nat.properDivisors k, cyclotomic' i K
have Bmo : B.Monic := by
apply monic_prod_of_monic
intro i _
exact cyclotomic'.monic i K
have Bint : B ∈ lifts (Int.castRingHom K) := by
refine Subsemiring.prod_mem (lifts (Int.castRingHom K)) ?_
intro x hx
have xsmall := (Nat.mem_properDivisors.1 hx).2
obtain ⟨d, hd⟩ := (Nat.mem_properDivisors.1 hx).1
rw [mul_comm] at hd
exact ihk x xsmall (h.pow hpos hd)
replace Bint := lifts_and_degree_eq_and_monic Bint Bmo
obtain ⟨B₁, hB₁, _, hB₁mo⟩ := Bint
let Q₁ : ℤ[X] := (X ^ k - 1) /ₘ B₁
have huniq : 0 + B * cyclotomic' k K = X ^ k - 1 ∧ (0 : K[X]).degree < B.degree := by
constructor
· rw [zero_add, mul_comm, ← prod_cyclotomic'_eq_X_pow_sub_one hpos h, ←
Nat.cons_self_properDivisors hpos.ne', Finset.prod_cons]
· simpa only [degree_zero, bot_lt_iff_ne_bot, Ne, degree_eq_bot] using Bmo.ne_zero
replace huniq := div_modByMonic_unique (cyclotomic' k K) (0 : K[X]) Bmo huniq
simp only [lifts, RingHom.mem_rangeS]
use Q₁
rw [coe_mapRingHom, map_divByMonic (Int.castRingHom K) hB₁mo, hB₁, ← huniq.1]
simp
#align polynomial.int_coeff_of_cyclotomic' Polynomial.int_coeff_of_cyclotomic'
/-- If `K` is of characteristic `0` and there is a primitive `n`-th root of unity in `K`,
then `cyclotomic n K` comes from a unique polynomial with integer coefficients. -/
theorem unique_int_coeff_of_cycl {K : Type*} [CommRing K] [IsDomain K] [CharZero K] {ζ : K}
{n : ℕ+} (h : IsPrimitiveRoot ζ n) :
∃! P : ℤ[X], map (Int.castRingHom K) P = cyclotomic' n K := by
obtain ⟨P, hP⟩ := int_coeff_of_cyclotomic' h
refine ⟨P, hP.1, fun Q hQ => ?_⟩
apply map_injective (Int.castRingHom K) Int.cast_injective
rw [hP.1, hQ]
#align polynomial.unique_int_coeff_of_cycl Polynomial.unique_int_coeff_of_cycl
end Field
end Cyclotomic'
section Cyclotomic
/-- The `n`-th cyclotomic polynomial with coefficients in `R`. -/
def cyclotomic (n : ℕ) (R : Type*) [Ring R] : R[X] :=
if h : n = 0 then 1
else map (Int.castRingHom R) (int_coeff_of_cyclotomic' (Complex.isPrimitiveRoot_exp n h)).choose
#align polynomial.cyclotomic Polynomial.cyclotomic
theorem int_cyclotomic_rw {n : ℕ} (h : n ≠ 0) :
cyclotomic n ℤ = (int_coeff_of_cyclotomic' (Complex.isPrimitiveRoot_exp n h)).choose := by
simp only [cyclotomic, h, dif_neg, not_false_iff]
ext i
simp only [coeff_map, Int.cast_id, eq_intCast]
#align polynomial.int_cyclotomic_rw Polynomial.int_cyclotomic_rw
/-- `cyclotomic n R` comes from `cyclotomic n ℤ`. -/
theorem map_cyclotomic_int (n : ℕ) (R : Type*) [Ring R] :
map (Int.castRingHom R) (cyclotomic n ℤ) = cyclotomic n R := by
by_cases hzero : n = 0
· simp only [hzero, cyclotomic, dif_pos, Polynomial.map_one]
simp [cyclotomic, hzero]
#align polynomial.map_cyclotomic_int Polynomial.map_cyclotomic_int
theorem int_cyclotomic_spec (n : ℕ) :
map (Int.castRingHom ℂ) (cyclotomic n ℤ) = cyclotomic' n ℂ ∧
(cyclotomic n ℤ).degree = (cyclotomic' n ℂ).degree ∧ (cyclotomic n ℤ).Monic := by
by_cases hzero : n = 0
· simp only [hzero, cyclotomic, degree_one, monic_one, cyclotomic'_zero, dif_pos,
eq_self_iff_true, Polynomial.map_one, and_self_iff]
rw [int_cyclotomic_rw hzero]
exact (int_coeff_of_cyclotomic' (Complex.isPrimitiveRoot_exp n hzero)).choose_spec
#align polynomial.int_cyclotomic_spec Polynomial.int_cyclotomic_spec
theorem int_cyclotomic_unique {n : ℕ} {P : ℤ[X]} (h : map (Int.castRingHom ℂ) P = cyclotomic' n ℂ) :
P = cyclotomic n ℤ := by
apply map_injective (Int.castRingHom ℂ) Int.cast_injective
rw [h, (int_cyclotomic_spec n).1]
#align polynomial.int_cyclotomic_unique Polynomial.int_cyclotomic_unique
/-- The definition of `cyclotomic n R` commutes with any ring homomorphism. -/
@[simp]
theorem map_cyclotomic (n : ℕ) {R S : Type*} [Ring R] [Ring S] (f : R →+* S) :
map f (cyclotomic n R) = cyclotomic n S := by
rw [← map_cyclotomic_int n R, ← map_cyclotomic_int n S, map_map]
have : Subsingleton (ℤ →+* S) := inferInstance
congr!
#align polynomial.map_cyclotomic Polynomial.map_cyclotomic
| Mathlib/RingTheory/Polynomial/Cyclotomic/Basic.lean | 298 | 300 | theorem cyclotomic.eval_apply {R S : Type*} (q : R) (n : ℕ) [Ring R] [Ring S] (f : R →+* S) :
eval (f q) (cyclotomic n S) = f (eval q (cyclotomic n R)) := by |
rw [← map_cyclotomic n f, eval_map, eval₂_at_apply]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Floris van Doorn
-/
import Mathlib.Data.Sum.Order
import Mathlib.Order.InitialSeg
import Mathlib.SetTheory.Cardinal.Basic
import Mathlib.Tactic.PPWithUniv
#align_import set_theory.ordinal.basic from "leanprover-community/mathlib"@"8ea5598db6caeddde6cb734aa179cc2408dbd345"
/-!
# Ordinals
Ordinals are defined as equivalences of well-ordered sets under order isomorphism. They are endowed
with a total order, where an ordinal is smaller than another one if it embeds into it as an
initial segment (or, equivalently, in any way). This total order is well founded.
## Main definitions
* `Ordinal`: the type of ordinals (in a given universe)
* `Ordinal.type r`: given a well-founded order `r`, this is the corresponding ordinal
* `Ordinal.typein r a`: given a well-founded order `r` on a type `α`, and `a : α`, the ordinal
corresponding to all elements smaller than `a`.
* `enum r o h`: given a well-order `r` on a type `α`, and an ordinal `o` strictly smaller than
the ordinal corresponding to `r` (this is the assumption `h`), returns the `o`-th element of `α`.
In other words, the elements of `α` can be enumerated using ordinals up to `type r`.
* `Ordinal.card o`: the cardinality of an ordinal `o`.
* `Ordinal.lift` lifts an ordinal in universe `u` to an ordinal in universe `max u v`.
For a version registering additionally that this is an initial segment embedding, see
`Ordinal.lift.initialSeg`.
For a version registering that it is a principal segment embedding if `u < v`, see
`Ordinal.lift.principalSeg`.
* `Ordinal.omega` or `ω` is the order type of `ℕ`. This definition is universe polymorphic:
`Ordinal.omega.{u} : Ordinal.{u}` (contrast with `ℕ : Type`, which lives in a specific
universe). In some cases the universe level has to be given explicitly.
* `o₁ + o₂` is the order on the disjoint union of `o₁` and `o₂` obtained by declaring that
every element of `o₁` is smaller than every element of `o₂`.
The main properties of addition (and the other operations on ordinals) are stated and proved in
`Mathlib/SetTheory/Ordinal/Arithmetic.lean`.
Here, we only introduce it and prove its basic properties to deduce the fact that the order on
ordinals is total (and well founded).
* `succ o` is the successor of the ordinal `o`.
* `Cardinal.ord c`: when `c` is a cardinal, `ord c` is the smallest ordinal with this cardinality.
It is the canonical way to represent a cardinal with an ordinal.
A conditionally complete linear order with bot structure is registered on ordinals, where `⊥` is
`0`, the ordinal corresponding to the empty type, and `Inf` is the minimum for nonempty sets and `0`
for the empty set by convention.
## Notations
* `ω` is a notation for the first infinite ordinal in the locale `Ordinal`.
-/
assert_not_exists Module
assert_not_exists Field
noncomputable section
open Function Cardinal Set Equiv Order
open scoped Classical
open Cardinal InitialSeg
universe u v w
variable {α : Type u} {β : Type*} {γ : Type*} {r : α → α → Prop} {s : β → β → Prop}
{t : γ → γ → Prop}
/-! ### Well order on an arbitrary type -/
section WellOrderingThm
-- Porting note: `parameter` does not work
-- parameter {σ : Type u}
variable {σ : Type u}
open Function
theorem nonempty_embedding_to_cardinal : Nonempty (σ ↪ Cardinal.{u}) :=
(Embedding.total _ _).resolve_left fun ⟨⟨f, hf⟩⟩ =>
let g : σ → Cardinal.{u} := invFun f
let ⟨x, (hx : g x = 2 ^ sum g)⟩ := invFun_surjective hf (2 ^ sum g)
have : g x ≤ sum g := le_sum.{u, u} g x
not_le_of_gt (by rw [hx]; exact cantor _) this
#align nonempty_embedding_to_cardinal nonempty_embedding_to_cardinal
/-- An embedding of any type to the set of cardinals. -/
def embeddingToCardinal : σ ↪ Cardinal.{u} :=
Classical.choice nonempty_embedding_to_cardinal
#align embedding_to_cardinal embeddingToCardinal
/-- Any type can be endowed with a well order, obtained by pulling back the well order over
cardinals by some embedding. -/
def WellOrderingRel : σ → σ → Prop :=
embeddingToCardinal ⁻¹'o (· < ·)
#align well_ordering_rel WellOrderingRel
instance WellOrderingRel.isWellOrder : IsWellOrder σ WellOrderingRel :=
(RelEmbedding.preimage _ _).isWellOrder
#align well_ordering_rel.is_well_order WellOrderingRel.isWellOrder
instance IsWellOrder.subtype_nonempty : Nonempty { r // IsWellOrder σ r } :=
⟨⟨WellOrderingRel, inferInstance⟩⟩
#align is_well_order.subtype_nonempty IsWellOrder.subtype_nonempty
end WellOrderingThm
/-! ### Definition of ordinals -/
/-- Bundled structure registering a well order on a type. Ordinals will be defined as a quotient
of this type. -/
structure WellOrder : Type (u + 1) where
/-- The underlying type of the order. -/
α : Type u
/-- The underlying relation of the order. -/
r : α → α → Prop
/-- The proposition that `r` is a well-ordering for `α`. -/
wo : IsWellOrder α r
set_option linter.uppercaseLean3 false in
#align Well_order WellOrder
attribute [instance] WellOrder.wo
namespace WellOrder
instance inhabited : Inhabited WellOrder :=
⟨⟨PEmpty, _, inferInstanceAs (IsWellOrder PEmpty EmptyRelation)⟩⟩
@[simp]
theorem eta (o : WellOrder) : mk o.α o.r o.wo = o := by
cases o
rfl
set_option linter.uppercaseLean3 false in
#align Well_order.eta WellOrder.eta
end WellOrder
/-- Equivalence relation on well orders on arbitrary types in universe `u`, given by order
isomorphism. -/
instance Ordinal.isEquivalent : Setoid WellOrder where
r := fun ⟨_, r, _⟩ ⟨_, s, _⟩ => Nonempty (r ≃r s)
iseqv :=
⟨fun _ => ⟨RelIso.refl _⟩, fun ⟨e⟩ => ⟨e.symm⟩, fun ⟨e₁⟩ ⟨e₂⟩ => ⟨e₁.trans e₂⟩⟩
#align ordinal.is_equivalent Ordinal.isEquivalent
/-- `Ordinal.{u}` is the type of well orders in `Type u`, up to order isomorphism. -/
@[pp_with_univ]
def Ordinal : Type (u + 1) :=
Quotient Ordinal.isEquivalent
#align ordinal Ordinal
instance hasWellFoundedOut (o : Ordinal) : WellFoundedRelation o.out.α :=
⟨o.out.r, o.out.wo.wf⟩
#align has_well_founded_out hasWellFoundedOut
instance linearOrderOut (o : Ordinal) : LinearOrder o.out.α :=
IsWellOrder.linearOrder o.out.r
#align linear_order_out linearOrderOut
instance isWellOrder_out_lt (o : Ordinal) : IsWellOrder o.out.α (· < ·) :=
o.out.wo
#align is_well_order_out_lt isWellOrder_out_lt
namespace Ordinal
/-! ### Basic properties of the order type -/
/-- The order type of a well order is an ordinal. -/
def type (r : α → α → Prop) [wo : IsWellOrder α r] : Ordinal :=
⟦⟨α, r, wo⟩⟧
#align ordinal.type Ordinal.type
instance zero : Zero Ordinal :=
⟨type <| @EmptyRelation PEmpty⟩
instance inhabited : Inhabited Ordinal :=
⟨0⟩
instance one : One Ordinal :=
⟨type <| @EmptyRelation PUnit⟩
/-- The order type of an element inside a well order. For the embedding as a principal segment, see
`typein.principalSeg`. -/
def typein (r : α → α → Prop) [IsWellOrder α r] (a : α) : Ordinal :=
type (Subrel r { b | r b a })
#align ordinal.typein Ordinal.typein
@[simp]
theorem type_def' (w : WellOrder) : ⟦w⟧ = type w.r := by
cases w
rfl
#align ordinal.type_def' Ordinal.type_def'
@[simp, nolint simpNF] -- Porting note (#10675): dsimp can not prove this
theorem type_def (r) [wo : IsWellOrder α r] : (⟦⟨α, r, wo⟩⟧ : Ordinal) = type r := by
rfl
#align ordinal.type_def Ordinal.type_def
@[simp]
theorem type_out (o : Ordinal) : Ordinal.type o.out.r = o := by
rw [Ordinal.type, WellOrder.eta, Quotient.out_eq]
#align ordinal.type_out Ordinal.type_out
theorem type_eq {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s] :
type r = type s ↔ Nonempty (r ≃r s) :=
Quotient.eq'
#align ordinal.type_eq Ordinal.type_eq
theorem _root_.RelIso.ordinal_type_eq {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r]
[IsWellOrder β s] (h : r ≃r s) : type r = type s :=
type_eq.2 ⟨h⟩
#align rel_iso.ordinal_type_eq RelIso.ordinal_type_eq
@[simp]
theorem type_lt (o : Ordinal) : type ((· < ·) : o.out.α → o.out.α → Prop) = o :=
(type_def' _).symm.trans <| Quotient.out_eq o
#align ordinal.type_lt Ordinal.type_lt
theorem type_eq_zero_of_empty (r) [IsWellOrder α r] [IsEmpty α] : type r = 0 :=
(RelIso.relIsoOfIsEmpty r _).ordinal_type_eq
#align ordinal.type_eq_zero_of_empty Ordinal.type_eq_zero_of_empty
@[simp]
theorem type_eq_zero_iff_isEmpty [IsWellOrder α r] : type r = 0 ↔ IsEmpty α :=
⟨fun h =>
let ⟨s⟩ := type_eq.1 h
s.toEquiv.isEmpty,
@type_eq_zero_of_empty α r _⟩
#align ordinal.type_eq_zero_iff_is_empty Ordinal.type_eq_zero_iff_isEmpty
theorem type_ne_zero_iff_nonempty [IsWellOrder α r] : type r ≠ 0 ↔ Nonempty α := by simp
#align ordinal.type_ne_zero_iff_nonempty Ordinal.type_ne_zero_iff_nonempty
theorem type_ne_zero_of_nonempty (r) [IsWellOrder α r] [h : Nonempty α] : type r ≠ 0 :=
type_ne_zero_iff_nonempty.2 h
#align ordinal.type_ne_zero_of_nonempty Ordinal.type_ne_zero_of_nonempty
theorem type_pEmpty : type (@EmptyRelation PEmpty) = 0 :=
rfl
#align ordinal.type_pempty Ordinal.type_pEmpty
theorem type_empty : type (@EmptyRelation Empty) = 0 :=
type_eq_zero_of_empty _
#align ordinal.type_empty Ordinal.type_empty
theorem type_eq_one_of_unique (r) [IsWellOrder α r] [Unique α] : type r = 1 :=
(RelIso.relIsoOfUniqueOfIrrefl r _).ordinal_type_eq
#align ordinal.type_eq_one_of_unique Ordinal.type_eq_one_of_unique
@[simp]
theorem type_eq_one_iff_unique [IsWellOrder α r] : type r = 1 ↔ Nonempty (Unique α) :=
⟨fun h =>
let ⟨s⟩ := type_eq.1 h
⟨s.toEquiv.unique⟩,
fun ⟨h⟩ => @type_eq_one_of_unique α r _ h⟩
#align ordinal.type_eq_one_iff_unique Ordinal.type_eq_one_iff_unique
theorem type_pUnit : type (@EmptyRelation PUnit) = 1 :=
rfl
#align ordinal.type_punit Ordinal.type_pUnit
theorem type_unit : type (@EmptyRelation Unit) = 1 :=
rfl
#align ordinal.type_unit Ordinal.type_unit
@[simp]
theorem out_empty_iff_eq_zero {o : Ordinal} : IsEmpty o.out.α ↔ o = 0 := by
rw [← @type_eq_zero_iff_isEmpty o.out.α (· < ·), type_lt]
#align ordinal.out_empty_iff_eq_zero Ordinal.out_empty_iff_eq_zero
theorem eq_zero_of_out_empty (o : Ordinal) [h : IsEmpty o.out.α] : o = 0 :=
out_empty_iff_eq_zero.1 h
#align ordinal.eq_zero_of_out_empty Ordinal.eq_zero_of_out_empty
instance isEmpty_out_zero : IsEmpty (0 : Ordinal).out.α :=
out_empty_iff_eq_zero.2 rfl
#align ordinal.is_empty_out_zero Ordinal.isEmpty_out_zero
@[simp]
theorem out_nonempty_iff_ne_zero {o : Ordinal} : Nonempty o.out.α ↔ o ≠ 0 := by
rw [← @type_ne_zero_iff_nonempty o.out.α (· < ·), type_lt]
#align ordinal.out_nonempty_iff_ne_zero Ordinal.out_nonempty_iff_ne_zero
theorem ne_zero_of_out_nonempty (o : Ordinal) [h : Nonempty o.out.α] : o ≠ 0 :=
out_nonempty_iff_ne_zero.1 h
#align ordinal.ne_zero_of_out_nonempty Ordinal.ne_zero_of_out_nonempty
protected theorem one_ne_zero : (1 : Ordinal) ≠ 0 :=
type_ne_zero_of_nonempty _
#align ordinal.one_ne_zero Ordinal.one_ne_zero
instance nontrivial : Nontrivial Ordinal.{u} :=
⟨⟨1, 0, Ordinal.one_ne_zero⟩⟩
--@[simp] -- Porting note: not in simp nf, added aux lemma below
theorem type_preimage {α β : Type u} (r : α → α → Prop) [IsWellOrder α r] (f : β ≃ α) :
type (f ⁻¹'o r) = type r :=
(RelIso.preimage f r).ordinal_type_eq
#align ordinal.type_preimage Ordinal.type_preimage
@[simp, nolint simpNF] -- `simpNF` incorrectly complains the LHS doesn't simplify.
theorem type_preimage_aux {α β : Type u} (r : α → α → Prop) [IsWellOrder α r] (f : β ≃ α) :
@type _ (fun x y => r (f x) (f y)) (inferInstanceAs (IsWellOrder β (↑f ⁻¹'o r))) = type r := by
convert (RelIso.preimage f r).ordinal_type_eq
@[elab_as_elim]
theorem inductionOn {C : Ordinal → Prop} (o : Ordinal)
(H : ∀ (α r) [IsWellOrder α r], C (type r)) : C o :=
Quot.inductionOn o fun ⟨α, r, wo⟩ => @H α r wo
#align ordinal.induction_on Ordinal.inductionOn
/-! ### The order on ordinals -/
/--
For `Ordinal`:
* less-equal is defined such that well orders `r` and `s` satisfy `type r ≤ type s` if there exists
a function embedding `r` as an *initial* segment of `s`.
* less-than is defined such that well orders `r` and `s` satisfy `type r < type s` if there exists
a function embedding `r` as a *principal* segment of `s`.
-/
instance partialOrder : PartialOrder Ordinal where
le a b :=
Quotient.liftOn₂ a b (fun ⟨_, r, _⟩ ⟨_, s, _⟩ => Nonempty (r ≼i s))
fun _ _ _ _ ⟨f⟩ ⟨g⟩ =>
propext
⟨fun ⟨h⟩ => ⟨(InitialSeg.ofIso f.symm).trans <| h.trans (InitialSeg.ofIso g)⟩, fun ⟨h⟩ =>
⟨(InitialSeg.ofIso f).trans <| h.trans (InitialSeg.ofIso g.symm)⟩⟩
lt a b :=
Quotient.liftOn₂ a b (fun ⟨_, r, _⟩ ⟨_, s, _⟩ => Nonempty (r ≺i s))
fun _ _ _ _ ⟨f⟩ ⟨g⟩ =>
propext
⟨fun ⟨h⟩ => ⟨PrincipalSeg.equivLT f.symm <| h.ltLe (InitialSeg.ofIso g)⟩, fun ⟨h⟩ =>
⟨PrincipalSeg.equivLT f <| h.ltLe (InitialSeg.ofIso g.symm)⟩⟩
le_refl := Quot.ind fun ⟨_, _, _⟩ => ⟨InitialSeg.refl _⟩
le_trans a b c :=
Quotient.inductionOn₃ a b c fun _ _ _ ⟨f⟩ ⟨g⟩ => ⟨f.trans g⟩
lt_iff_le_not_le a b :=
Quotient.inductionOn₂ a b fun _ _ =>
⟨fun ⟨f⟩ => ⟨⟨f⟩, fun ⟨g⟩ => (f.ltLe g).irrefl⟩, fun ⟨⟨f⟩, h⟩ =>
Sum.recOn f.ltOrEq (fun g => ⟨g⟩) fun g => (h ⟨InitialSeg.ofIso g.symm⟩).elim⟩
le_antisymm a b :=
Quotient.inductionOn₂ a b fun _ _ ⟨h₁⟩ ⟨h₂⟩ =>
Quot.sound ⟨InitialSeg.antisymm h₁ h₂⟩
theorem type_le_iff {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r]
[IsWellOrder β s] : type r ≤ type s ↔ Nonempty (r ≼i s) :=
Iff.rfl
#align ordinal.type_le_iff Ordinal.type_le_iff
theorem type_le_iff' {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r]
[IsWellOrder β s] : type r ≤ type s ↔ Nonempty (r ↪r s) :=
⟨fun ⟨f⟩ => ⟨f⟩, fun ⟨f⟩ => ⟨f.collapse⟩⟩
#align ordinal.type_le_iff' Ordinal.type_le_iff'
theorem _root_.InitialSeg.ordinal_type_le {α β} {r : α → α → Prop} {s : β → β → Prop}
[IsWellOrder α r] [IsWellOrder β s] (h : r ≼i s) : type r ≤ type s :=
⟨h⟩
#align initial_seg.ordinal_type_le InitialSeg.ordinal_type_le
theorem _root_.RelEmbedding.ordinal_type_le {α β} {r : α → α → Prop} {s : β → β → Prop}
[IsWellOrder α r] [IsWellOrder β s] (h : r ↪r s) : type r ≤ type s :=
⟨h.collapse⟩
#align rel_embedding.ordinal_type_le RelEmbedding.ordinal_type_le
@[simp]
theorem type_lt_iff {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r]
[IsWellOrder β s] : type r < type s ↔ Nonempty (r ≺i s) :=
Iff.rfl
#align ordinal.type_lt_iff Ordinal.type_lt_iff
theorem _root_.PrincipalSeg.ordinal_type_lt {α β} {r : α → α → Prop} {s : β → β → Prop}
[IsWellOrder α r] [IsWellOrder β s] (h : r ≺i s) : type r < type s :=
⟨h⟩
#align principal_seg.ordinal_type_lt PrincipalSeg.ordinal_type_lt
@[simp]
protected theorem zero_le (o : Ordinal) : 0 ≤ o :=
inductionOn o fun _ r _ => (InitialSeg.ofIsEmpty _ r).ordinal_type_le
#align ordinal.zero_le Ordinal.zero_le
instance orderBot : OrderBot Ordinal where
bot := 0
bot_le := Ordinal.zero_le
@[simp]
theorem bot_eq_zero : (⊥ : Ordinal) = 0 :=
rfl
#align ordinal.bot_eq_zero Ordinal.bot_eq_zero
@[simp]
protected theorem le_zero {o : Ordinal} : o ≤ 0 ↔ o = 0 :=
le_bot_iff
#align ordinal.le_zero Ordinal.le_zero
protected theorem pos_iff_ne_zero {o : Ordinal} : 0 < o ↔ o ≠ 0 :=
bot_lt_iff_ne_bot
#align ordinal.pos_iff_ne_zero Ordinal.pos_iff_ne_zero
protected theorem not_lt_zero (o : Ordinal) : ¬o < 0 :=
not_lt_bot
#align ordinal.not_lt_zero Ordinal.not_lt_zero
theorem eq_zero_or_pos : ∀ a : Ordinal, a = 0 ∨ 0 < a :=
eq_bot_or_bot_lt
#align ordinal.eq_zero_or_pos Ordinal.eq_zero_or_pos
instance zeroLEOneClass : ZeroLEOneClass Ordinal :=
⟨Ordinal.zero_le _⟩
instance NeZero.one : NeZero (1 : Ordinal) :=
⟨Ordinal.one_ne_zero⟩
#align ordinal.ne_zero.one Ordinal.NeZero.one
/-- Given two ordinals `α ≤ β`, then `initialSegOut α β` is the initial segment embedding
of `α` to `β`, as map from a model type for `α` to a model type for `β`. -/
def initialSegOut {α β : Ordinal} (h : α ≤ β) :
InitialSeg ((· < ·) : α.out.α → α.out.α → Prop) ((· < ·) : β.out.α → β.out.α → Prop) := by
change α.out.r ≼i β.out.r
rw [← Quotient.out_eq α, ← Quotient.out_eq β] at h; revert h
cases Quotient.out α; cases Quotient.out β; exact Classical.choice
#align ordinal.initial_seg_out Ordinal.initialSegOut
/-- Given two ordinals `α < β`, then `principalSegOut α β` is the principal segment embedding
of `α` to `β`, as map from a model type for `α` to a model type for `β`. -/
def principalSegOut {α β : Ordinal} (h : α < β) :
PrincipalSeg ((· < ·) : α.out.α → α.out.α → Prop) ((· < ·) : β.out.α → β.out.α → Prop) := by
change α.out.r ≺i β.out.r
rw [← Quotient.out_eq α, ← Quotient.out_eq β] at h; revert h
cases Quotient.out α; cases Quotient.out β; exact Classical.choice
#align ordinal.principal_seg_out Ordinal.principalSegOut
theorem typein_lt_type (r : α → α → Prop) [IsWellOrder α r] (a : α) : typein r a < type r :=
⟨PrincipalSeg.ofElement _ _⟩
#align ordinal.typein_lt_type Ordinal.typein_lt_type
theorem typein_lt_self {o : Ordinal} (i : o.out.α) :
@typein _ (· < ·) (isWellOrder_out_lt _) i < o := by
simp_rw [← type_lt o]
apply typein_lt_type
#align ordinal.typein_lt_self Ordinal.typein_lt_self
@[simp]
theorem typein_top {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s]
(f : r ≺i s) : typein s f.top = type r :=
Eq.symm <|
Quot.sound
⟨RelIso.ofSurjective (RelEmbedding.codRestrict _ f f.lt_top) fun ⟨a, h⟩ => by
rcases f.down.1 h with ⟨b, rfl⟩; exact ⟨b, rfl⟩⟩
#align ordinal.typein_top Ordinal.typein_top
@[simp]
theorem typein_apply {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s]
(f : r ≼i s) (a : α) : Ordinal.typein s (f a) = Ordinal.typein r a :=
Eq.symm <|
Quotient.sound
⟨RelIso.ofSurjective
(RelEmbedding.codRestrict _ ((Subrel.relEmbedding _ _).trans f) fun ⟨x, h⟩ => by
rw [RelEmbedding.trans_apply]; exact f.toRelEmbedding.map_rel_iff.2 h)
fun ⟨y, h⟩ => by
rcases f.init h with ⟨a, rfl⟩
exact ⟨⟨a, f.toRelEmbedding.map_rel_iff.1 h⟩,
Subtype.eq <| RelEmbedding.trans_apply _ _ _⟩⟩
#align ordinal.typein_apply Ordinal.typein_apply
@[simp]
theorem typein_lt_typein (r : α → α → Prop) [IsWellOrder α r] {a b : α} :
typein r a < typein r b ↔ r a b :=
⟨fun ⟨f⟩ => by
have : f.top.1 = a := by
let f' := PrincipalSeg.ofElement r a
let g' := f.trans (PrincipalSeg.ofElement r b)
have : g'.top = f'.top := by rw [Subsingleton.elim f' g']
exact this
rw [← this]
exact f.top.2, fun h =>
⟨PrincipalSeg.codRestrict _ (PrincipalSeg.ofElement r a) (fun x => @trans _ r _ _ _ _ x.2 h) h⟩⟩
#align ordinal.typein_lt_typein Ordinal.typein_lt_typein
theorem typein_surj (r : α → α → Prop) [IsWellOrder α r] {o} (h : o < type r) :
∃ a, typein r a = o :=
inductionOn o (fun _ _ _ ⟨f⟩ => ⟨f.top, typein_top _⟩) h
#align ordinal.typein_surj Ordinal.typein_surj
theorem typein_injective (r : α → α → Prop) [IsWellOrder α r] : Injective (typein r) :=
injective_of_increasing r (· < ·) (typein r) (typein_lt_typein r).2
#align ordinal.typein_injective Ordinal.typein_injective
@[simp]
theorem typein_inj (r : α → α → Prop) [IsWellOrder α r] {a b} : typein r a = typein r b ↔ a = b :=
(typein_injective r).eq_iff
#align ordinal.typein_inj Ordinal.typein_inj
/-- Principal segment version of the `typein` function, embedding a well order into
ordinals as a principal segment. -/
def typein.principalSeg {α : Type u} (r : α → α → Prop) [IsWellOrder α r] :
@PrincipalSeg α Ordinal.{u} r (· < ·) :=
⟨⟨⟨typein r, typein_injective r⟩, typein_lt_typein r⟩, type r,
fun _ ↦ ⟨typein_surj r, fun ⟨a, h⟩ ↦ h ▸ typein_lt_type r a⟩⟩
#align ordinal.typein.principal_seg Ordinal.typein.principalSeg
@[simp]
theorem typein.principalSeg_coe (r : α → α → Prop) [IsWellOrder α r] :
(typein.principalSeg r : α → Ordinal) = typein r :=
rfl
#align ordinal.typein.principal_seg_coe Ordinal.typein.principalSeg_coe
/-! ### Enumerating elements in a well-order with ordinals. -/
/-- `enum r o h` is the `o`-th element of `α` ordered by `r`.
That is, `enum` maps an initial segment of the ordinals, those
less than the order type of `r`, to the elements of `α`. -/
def enum (r : α → α → Prop) [IsWellOrder α r] (o) (h : o < type r) : α :=
(typein.principalSeg r).subrelIso ⟨o, h⟩
@[simp]
theorem typein_enum (r : α → α → Prop) [IsWellOrder α r] {o} (h : o < type r) :
typein r (enum r o h) = o :=
(typein.principalSeg r).apply_subrelIso _
#align ordinal.typein_enum Ordinal.typein_enum
theorem enum_type {α β} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r] [IsWellOrder β s]
(f : s ≺i r) {h : type s < type r} : enum r (type s) h = f.top :=
(typein.principalSeg r).injective <| (typein_enum _ _).trans (typein_top _).symm
#align ordinal.enum_type Ordinal.enum_type
@[simp]
theorem enum_typein (r : α → α → Prop) [IsWellOrder α r] (a : α) :
enum r (typein r a) (typein_lt_type r a) = a :=
enum_type (PrincipalSeg.ofElement r a)
#align ordinal.enum_typein Ordinal.enum_typein
theorem enum_lt_enum {r : α → α → Prop} [IsWellOrder α r] {o₁ o₂ : Ordinal} (h₁ : o₁ < type r)
(h₂ : o₂ < type r) : r (enum r o₁ h₁) (enum r o₂ h₂) ↔ o₁ < o₂ := by
rw [← typein_lt_typein r, typein_enum, typein_enum]
#align ordinal.enum_lt_enum Ordinal.enum_lt_enum
theorem relIso_enum' {α β : Type u} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r]
[IsWellOrder β s] (f : r ≃r s) (o : Ordinal) :
∀ (hr : o < type r) (hs : o < type s), f (enum r o hr) = enum s o hs := by
refine inductionOn o ?_; rintro γ t wo ⟨g⟩ ⟨h⟩
rw [enum_type g, enum_type (PrincipalSeg.ltEquiv g f)]; rfl
#align ordinal.rel_iso_enum' Ordinal.relIso_enum'
theorem relIso_enum {α β : Type u} {r : α → α → Prop} {s : β → β → Prop} [IsWellOrder α r]
[IsWellOrder β s] (f : r ≃r s) (o : Ordinal) (hr : o < type r) :
f (enum r o hr) =
enum s o
(by
convert hr using 1
apply Quotient.sound
exact ⟨f.symm⟩) :=
relIso_enum' _ _ _ _
#align ordinal.rel_iso_enum Ordinal.relIso_enum
theorem lt_wf : @WellFounded Ordinal (· < ·) :=
/-
wellFounded_iff_wellFounded_subrel.mpr (·.induction_on fun ⟨_, r, wo⟩ ↦
RelHomClass.wellFounded (typein.principalSeg r).subrelIso wo.wf)
-/
⟨fun a =>
inductionOn a fun α r wo =>
suffices ∀ a, Acc (· < ·) (typein r a) from
⟨_, fun o h =>
let ⟨a, e⟩ := typein_surj r h
e ▸ this a⟩
fun a =>
Acc.recOn (wo.wf.apply a) fun x _ IH =>
⟨_, fun o h => by
rcases typein_surj r (lt_trans h (typein_lt_type r _)) with ⟨b, rfl⟩
exact IH _ ((typein_lt_typein r).1 h)⟩⟩
#align ordinal.lt_wf Ordinal.lt_wf
instance wellFoundedRelation : WellFoundedRelation Ordinal :=
⟨(· < ·), lt_wf⟩
/-- Reformulation of well founded induction on ordinals as a lemma that works with the
`induction` tactic, as in `induction i using Ordinal.induction with | h i IH => ?_`. -/
theorem induction {p : Ordinal.{u} → Prop} (i : Ordinal.{u}) (h : ∀ j, (∀ k, k < j → p k) → p j) :
p i :=
lt_wf.induction i h
#align ordinal.induction Ordinal.induction
/-! ### Cardinality of ordinals -/
/-- The cardinal of an ordinal is the cardinality of any type on which a relation with that order
type is defined. -/
def card : Ordinal → Cardinal :=
Quotient.map WellOrder.α fun _ _ ⟨e⟩ => ⟨e.toEquiv⟩
#align ordinal.card Ordinal.card
@[simp]
theorem card_type (r : α → α → Prop) [IsWellOrder α r] : card (type r) = #α :=
rfl
#align ordinal.card_type Ordinal.card_type
-- Porting note: nolint, simpNF linter falsely claims the lemma never applies
@[simp, nolint simpNF]
theorem card_typein {r : α → α → Prop} [IsWellOrder α r] (x : α) :
#{ y // r y x } = (typein r x).card :=
rfl
#align ordinal.card_typein Ordinal.card_typein
theorem card_le_card {o₁ o₂ : Ordinal} : o₁ ≤ o₂ → card o₁ ≤ card o₂ :=
inductionOn o₁ fun _ _ _ => inductionOn o₂ fun _ _ _ ⟨⟨⟨f, _⟩, _⟩⟩ => ⟨f⟩
#align ordinal.card_le_card Ordinal.card_le_card
@[simp]
theorem card_zero : card 0 = 0 := mk_eq_zero _
#align ordinal.card_zero Ordinal.card_zero
@[simp]
theorem card_one : card 1 = 1 := mk_eq_one _
#align ordinal.card_one Ordinal.card_one
/-! ### Lifting ordinals to a higher universe -/
-- Porting note: Needed to add universe hint .{u} below
/-- The universe lift operation for ordinals, which embeds `Ordinal.{u}` as
a proper initial segment of `Ordinal.{v}` for `v > u`. For the initial segment version,
see `lift.initialSeg`. -/
@[pp_with_univ]
def lift (o : Ordinal.{v}) : Ordinal.{max v u} :=
Quotient.liftOn o (fun w => type <| ULift.down.{u} ⁻¹'o w.r) fun ⟨_, r, _⟩ ⟨_, s, _⟩ ⟨f⟩ =>
Quot.sound
⟨(RelIso.preimage Equiv.ulift r).trans <| f.trans (RelIso.preimage Equiv.ulift s).symm⟩
#align ordinal.lift Ordinal.lift
-- Porting note: Needed to add universe hints ULift.down.{v,u} below
-- @[simp] -- Porting note: Not in simpnf, added aux lemma below
| Mathlib/SetTheory/Ordinal/Basic.lean | 641 | 644 | theorem type_uLift (r : α → α → Prop) [IsWellOrder α r] :
type (ULift.down.{v,u} ⁻¹'o r) = lift.{v} (type r) := by |
simp (config := { unfoldPartialApp := true })
rfl
|
/-
Copyright (c) 2023 Junyan Xu. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Junyan Xu
-/
import Mathlib.Topology.Connected.Basic
import Mathlib.Topology.Separation
/-!
# Separated maps and locally injective maps out of a topological space.
This module introduces a pair of dual notions `IsSeparatedMap` and `IsLocallyInjective`.
A function from a topological space `X` to a type `Y` is a separated map if any two distinct
points in `X` with the same image in `Y` can be separated by open neighborhoods.
A constant function is a separated map if and only if `X` is a `T2Space`.
A function from a topological space `X` is locally injective if every point of `X`
has a neighborhood on which `f` is injective.
A constant function is locally injective if and only if `X` is discrete.
Given `f : X → Y` we can form the pullback $X \times_Y X$; the diagonal map
$\Delta: X \to X \times_Y X$ is always an embedding. It is a closed embedding
iff `f` is a separated map, iff the equal locus of any two continuous maps
coequalized by `f` is closed. It is an open embedding iff `f` is locally injective,
iff any such equal locus is open. Therefore, if `f` is a locally injective separated map,
the equal locus of two continuous maps coequalized by `f` is clopen, so if the two maps
agree on a point, then they agree on the whole connected component.
The analogue of separated maps and locally injective maps in algebraic geometry are
separated morphisms and unramified morphisms, respectively.
## Reference
https://stacks.math.columbia.edu/tag/0CY0
-/
open scoped Topology
variable {X Y A} [TopologicalSpace X] [TopologicalSpace A]
theorem embedding_toPullbackDiag (f : X → Y) : Embedding (toPullbackDiag f) :=
Embedding.mk' _ (injective_toPullbackDiag f) fun x ↦ by
rw [toPullbackDiag, nhds_induced, Filter.comap_comap, nhds_prod_eq, Filter.comap_prod]
erw [Filter.comap_id, inf_idem]
lemma Continuous.mapPullback {X₁ X₂ Y₁ Y₂ Z₁ Z₂}
[TopologicalSpace X₁] [TopologicalSpace X₂] [TopologicalSpace Z₁] [TopologicalSpace Z₂]
{f₁ : X₁ → Y₁} {g₁ : Z₁ → Y₁} {f₂ : X₂ → Y₂} {g₂ : Z₂ → Y₂}
{mapX : X₁ → X₂} (contX : Continuous mapX) {mapY : Y₁ → Y₂}
{mapZ : Z₁ → Z₂} (contZ : Continuous mapZ)
{commX : f₂ ∘ mapX = mapY ∘ f₁} {commZ : g₂ ∘ mapZ = mapY ∘ g₁} :
Continuous (Function.mapPullback mapX mapY mapZ commX commZ) := by
refine continuous_induced_rng.mpr (continuous_prod_mk.mpr ⟨?_, ?_⟩) <;>
apply_rules [continuous_fst, continuous_snd, continuous_subtype_val, Continuous.comp]
/-- A function from a topological space `X` to a type `Y` is a separated map if any two distinct
points in `X` with the same image in `Y` can be separated by open neighborhoods. -/
def IsSeparatedMap (f : X → Y) : Prop := ∀ x₁ x₂, f x₁ = f x₂ →
x₁ ≠ x₂ → ∃ s₁ s₂, IsOpen s₁ ∧ IsOpen s₂ ∧ x₁ ∈ s₁ ∧ x₂ ∈ s₂ ∧ Disjoint s₁ s₂
lemma t2space_iff_isSeparatedMap (y : Y) : T2Space X ↔ IsSeparatedMap fun _ : X ↦ y :=
⟨fun ⟨t2⟩ _ _ _ hne ↦ t2 hne, fun sep ↦ ⟨fun x₁ x₂ hne ↦ sep x₁ x₂ rfl hne⟩⟩
lemma T2Space.isSeparatedMap [T2Space X] (f : X → Y) : IsSeparatedMap f := fun _ _ _ ↦ t2_separation
lemma Function.Injective.isSeparatedMap {f : X → Y} (inj : f.Injective) : IsSeparatedMap f :=
fun _ _ he hne ↦ (hne (inj he)).elim
lemma isSeparatedMap_iff_disjoint_nhds {f : X → Y} : IsSeparatedMap f ↔
∀ x₁ x₂, f x₁ = f x₂ → x₁ ≠ x₂ → Disjoint (𝓝 x₁) (𝓝 x₂) :=
forall₃_congr fun x x' _ ↦ by simp only [(nhds_basis_opens x).disjoint_iff (nhds_basis_opens x'),
exists_prop, ← exists_and_left, and_assoc, and_comm, and_left_comm]
lemma isSeparatedMap_iff_nhds {f : X → Y} : IsSeparatedMap f ↔
∀ x₁ x₂, f x₁ = f x₂ → x₁ ≠ x₂ → ∃ s₁ ∈ 𝓝 x₁, ∃ s₂ ∈ 𝓝 x₂, Disjoint s₁ s₂ := by
simp_rw [isSeparatedMap_iff_disjoint_nhds, Filter.disjoint_iff]
open Set Filter in
| Mathlib/Topology/SeparatedMap.lean | 79 | 87 | theorem isSeparatedMap_iff_isClosed_diagonal {f : X → Y} :
IsSeparatedMap f ↔ IsClosed f.pullbackDiagonal := by |
simp_rw [isSeparatedMap_iff_nhds, ← isOpen_compl_iff, isOpen_iff_mem_nhds,
Subtype.forall, Prod.forall, nhds_induced, nhds_prod_eq]
refine forall₄_congr fun x₁ x₂ _ _ ↦ ⟨fun h ↦ ?_, fun ⟨t, ht, t_sub⟩ ↦ ?_⟩
· simp_rw [← Filter.disjoint_iff, ← compl_diagonal_mem_prod] at h
exact ⟨_, h, subset_rfl⟩
· obtain ⟨s₁, h₁, s₂, h₂, s_sub⟩ := mem_prod_iff.mp ht
exact ⟨s₁, h₁, s₂, h₂, disjoint_left.2 fun x h₁ h₂ ↦ @t_sub ⟨(x, x), rfl⟩ (s_sub ⟨h₁, h₂⟩) rfl⟩
|
/-
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.Defs
import Mathlib.Algebra.GroupWithZero.Defs
import Mathlib.Data.Int.Cast.Defs
import Mathlib.Tactic.Spread
import Mathlib.Util.AssertExists
#align_import algebra.ring.defs from "leanprover-community/mathlib"@"76de8ae01554c3b37d66544866659ff174e66e1f"
/-!
# Semirings and rings
This file defines semirings, rings and domains. This is analogous to `Algebra.Group.Defs` and
`Algebra.Group.Basic`, the difference being that the former is about `+` and `*` separately, while
the present file is about their interaction.
## Main definitions
* `Distrib`: Typeclass for distributivity of multiplication over addition.
* `HasDistribNeg`: Typeclass for commutativity of negation and multiplication. This is useful when
dealing with multiplicative submonoids which are closed under negation without being closed under
addition, for example `Units`.
* `(NonUnital)(NonAssoc)(Semi)Ring`: Typeclasses for possibly non-unital or non-associative
rings and semirings. Some combinations are not defined yet because they haven't found use.
## Tags
`Semiring`, `CommSemiring`, `Ring`, `CommRing`, domain, `IsDomain`, nonzero, units
-/
universe u v w x
variable {α : Type u} {β : Type v} {γ : Type w} {R : Type x}
open Function
/-!
### `Distrib` class
-/
/-- A typeclass stating that multiplication is left and right distributive
over addition. -/
class Distrib (R : Type*) extends Mul R, Add R where
/-- Multiplication is left distributive over addition -/
protected left_distrib : ∀ a b c : R, a * (b + c) = a * b + a * c
/-- Multiplication is right distributive over addition -/
protected right_distrib : ∀ a b c : R, (a + b) * c = a * c + b * c
#align distrib Distrib
/-- A typeclass stating that multiplication is left distributive over addition. -/
class LeftDistribClass (R : Type*) [Mul R] [Add R] : Prop where
/-- Multiplication is left distributive over addition -/
protected left_distrib : ∀ a b c : R, a * (b + c) = a * b + a * c
#align left_distrib_class LeftDistribClass
/-- A typeclass stating that multiplication is right distributive over addition. -/
class RightDistribClass (R : Type*) [Mul R] [Add R] : Prop where
/-- Multiplication is right distributive over addition -/
protected right_distrib : ∀ a b c : R, (a + b) * c = a * c + b * c
#align right_distrib_class RightDistribClass
-- see Note [lower instance priority]
instance (priority := 100) Distrib.leftDistribClass (R : Type*) [Distrib R] : LeftDistribClass R :=
⟨Distrib.left_distrib⟩
#align distrib.left_distrib_class Distrib.leftDistribClass
-- see Note [lower instance priority]
instance (priority := 100) Distrib.rightDistribClass (R : Type*) [Distrib R] :
RightDistribClass R :=
⟨Distrib.right_distrib⟩
#align distrib.right_distrib_class Distrib.rightDistribClass
theorem left_distrib [Mul R] [Add R] [LeftDistribClass R] (a b c : R) :
a * (b + c) = a * b + a * c :=
LeftDistribClass.left_distrib a b c
#align left_distrib left_distrib
alias mul_add := left_distrib
#align mul_add mul_add
theorem right_distrib [Mul R] [Add R] [RightDistribClass R] (a b c : R) :
(a + b) * c = a * c + b * c :=
RightDistribClass.right_distrib a b c
#align right_distrib right_distrib
alias add_mul := right_distrib
#align add_mul add_mul
theorem distrib_three_right [Mul R] [Add R] [RightDistribClass R] (a b c d : R) :
(a + b + c) * d = a * d + b * d + c * d := by simp [right_distrib]
#align distrib_three_right distrib_three_right
/-!
### Classes of semirings and rings
We make sure that the canonical path from `NonAssocSemiring` to `Ring` passes through `Semiring`,
as this is a path which is followed all the time in linear algebra where the defining semilinear map
`σ : R →+* S` depends on the `NonAssocSemiring` structure of `R` and `S` while the module
definition depends on the `Semiring` structure.
It is not currently possible to adjust priorities by hand (see lean4#2115). Instead, the last
declared instance is used, so we make sure that `Semiring` is declared after `NonAssocRing`, so
that `Semiring -> NonAssocSemiring` is tried before `NonAssocRing -> NonAssocSemiring`.
TODO: clean this once lean4#2115 is fixed
-/
/-- A not-necessarily-unital, not-necessarily-associative semiring. -/
class NonUnitalNonAssocSemiring (α : Type u) extends AddCommMonoid α, Distrib α, MulZeroClass α
#align non_unital_non_assoc_semiring NonUnitalNonAssocSemiring
/-- An associative but not-necessarily unital semiring. -/
class NonUnitalSemiring (α : Type u) extends NonUnitalNonAssocSemiring α, SemigroupWithZero α
#align non_unital_semiring NonUnitalSemiring
/-- A unital but not-necessarily-associative semiring. -/
class NonAssocSemiring (α : Type u) extends NonUnitalNonAssocSemiring α, MulZeroOneClass α,
AddCommMonoidWithOne α
#align non_assoc_semiring NonAssocSemiring
/-- A not-necessarily-unital, not-necessarily-associative ring. -/
class NonUnitalNonAssocRing (α : Type u) extends AddCommGroup α, NonUnitalNonAssocSemiring α
#align non_unital_non_assoc_ring NonUnitalNonAssocRing
/-- An associative but not-necessarily unital ring. -/
class NonUnitalRing (α : Type*) extends NonUnitalNonAssocRing α, NonUnitalSemiring α
#align non_unital_ring NonUnitalRing
/-- A unital but not-necessarily-associative ring. -/
class NonAssocRing (α : Type*) extends NonUnitalNonAssocRing α, NonAssocSemiring α,
AddCommGroupWithOne α
#align non_assoc_ring NonAssocRing
/-- A `Semiring` is a type with addition, multiplication, a `0` and a `1` where addition is
commutative and associative, multiplication is associative and left and right distributive over
addition, and `0` and `1` are additive and multiplicative identities. -/
class Semiring (α : Type u) extends NonUnitalSemiring α, NonAssocSemiring α, MonoidWithZero α
#align semiring Semiring
/-- A `Ring` is a `Semiring` with negation making it an additive group. -/
class Ring (R : Type u) extends Semiring R, AddCommGroup R, AddGroupWithOne R
#align ring Ring
/-!
### Semirings
-/
section DistribMulOneClass
variable [Add α] [MulOneClass α]
theorem add_one_mul [RightDistribClass α] (a b : α) : (a + 1) * b = a * b + b := by
rw [add_mul, one_mul]
#align add_one_mul add_one_mul
theorem mul_add_one [LeftDistribClass α] (a b : α) : a * (b + 1) = a * b + a := by
rw [mul_add, mul_one]
#align mul_add_one mul_add_one
theorem one_add_mul [RightDistribClass α] (a b : α) : (1 + a) * b = b + a * b := by
rw [add_mul, one_mul]
#align one_add_mul one_add_mul
theorem mul_one_add [LeftDistribClass α] (a b : α) : a * (1 + b) = a + a * b := by
rw [mul_add, mul_one]
#align mul_one_add mul_one_add
end DistribMulOneClass
section NonAssocSemiring
variable [NonAssocSemiring α]
-- Porting note: was [has_add α] [mul_one_class α] [right_distrib_class α]
theorem two_mul (n : α) : 2 * n = n + n :=
(congrArg₂ _ one_add_one_eq_two.symm rfl).trans <| (right_distrib 1 1 n).trans (by rw [one_mul])
#align two_mul two_mul
-- Porting note: was [has_add α] [mul_one_class α] [right_distrib_class α]
set_option linter.deprecated false in
theorem bit0_eq_two_mul (n : α) : bit0 n = 2 * n :=
(two_mul _).symm
#align bit0_eq_two_mul bit0_eq_two_mul
-- Porting note: was [has_add α] [mul_one_class α] [left_distrib_class α]
theorem mul_two (n : α) : n * 2 = n + n :=
(congrArg₂ _ rfl one_add_one_eq_two.symm).trans <| (left_distrib n 1 1).trans (by rw [mul_one])
#align mul_two mul_two
end NonAssocSemiring
@[to_additive]
theorem mul_ite {α} [Mul α] (P : Prop) [Decidable P] (a b c : α) :
(a * if P then b else c) = if P then a * b else a * c := by split_ifs <;> rfl
#align mul_ite mul_ite
#align add_ite add_ite
@[to_additive]
theorem ite_mul {α} [Mul α] (P : Prop) [Decidable P] (a b c : α) :
(if P then a else b) * c = if P then a * c else b * c := by split_ifs <;> rfl
#align ite_mul ite_mul
#align ite_add ite_add
-- We make `mul_ite` and `ite_mul` simp lemmas,
-- but not `add_ite` or `ite_add`.
-- The problem we're trying to avoid is dealing with
-- summations of the form `∑ x ∈ s, (f x + ite P 1 0)`,
-- in which `add_ite` followed by `sum_ite` would needlessly slice up
-- the `f x` terms according to whether `P` holds at `x`.
-- There doesn't appear to be a corresponding difficulty so far with
-- `mul_ite` and `ite_mul`.
attribute [simp] mul_ite ite_mul
theorem ite_sub_ite {α} [Sub α] (P : Prop) [Decidable P] (a b c d : α) :
((if P then a else b) - if P then c else d) = if P then a - c else b - d := by
split
repeat rfl
theorem ite_add_ite {α} [Add α] (P : Prop) [Decidable P] (a b c d : α) :
((if P then a else b) + if P then c else d) = if P then a + c else b + d := by
split
repeat rfl
section MulZeroClass
variable [MulZeroClass α] (P Q : Prop) [Decidable P] [Decidable Q] (a b : α)
lemma ite_zero_mul : ite P a 0 * b = ite P (a * b) 0 := by simp
#align ite_mul_zero_left ite_zero_mul
lemma mul_ite_zero : a * ite P b 0 = ite P (a * b) 0 := by simp
#align ite_mul_zero_right mul_ite_zero
lemma ite_zero_mul_ite_zero : ite P a 0 * ite Q b 0 = ite (P ∧ Q) (a * b) 0 := by
simp only [← ite_and, ite_mul, mul_ite, mul_zero, zero_mul, and_comm]
#align ite_and_mul_zero ite_zero_mul_ite_zero
end MulZeroClass
-- Porting note: no @[simp] because simp proves it
theorem mul_boole {α} [MulZeroOneClass α] (P : Prop) [Decidable P] (a : α) :
(a * if P then 1 else 0) = if P then a else 0 := by simp
#align mul_boole mul_boole
-- Porting note: no @[simp] because simp proves it
theorem boole_mul {α} [MulZeroOneClass α] (P : Prop) [Decidable P] (a : α) :
(if P then 1 else 0) * a = if P then a else 0 := by simp
#align boole_mul boole_mul
/-- A not-necessarily-unital, not-necessarily-associative, but commutative semiring. -/
class NonUnitalNonAssocCommSemiring (α : Type u) extends NonUnitalNonAssocSemiring α, CommMagma α
/-- A non-unital commutative semiring is a `NonUnitalSemiring` with commutative multiplication.
In other words, it is a type with the following structures: additive commutative monoid
(`AddCommMonoid`), commutative semigroup (`CommSemigroup`), distributive laws (`Distrib`), and
multiplication by zero law (`MulZeroClass`). -/
class NonUnitalCommSemiring (α : Type u) extends NonUnitalSemiring α, CommSemigroup α
#align non_unital_comm_semiring NonUnitalCommSemiring
/-- A commutative semiring is a semiring with commutative multiplication. -/
class CommSemiring (R : Type u) extends Semiring R, CommMonoid R
#align comm_semiring CommSemiring
-- see Note [lower instance priority]
instance (priority := 100) CommSemiring.toNonUnitalCommSemiring [CommSemiring α] :
NonUnitalCommSemiring α :=
{ inferInstanceAs (CommMonoid α), inferInstanceAs (CommSemiring α) with }
#align comm_semiring.to_non_unital_comm_semiring CommSemiring.toNonUnitalCommSemiring
-- see Note [lower instance priority]
instance (priority := 100) CommSemiring.toCommMonoidWithZero [CommSemiring α] :
CommMonoidWithZero α :=
{ inferInstanceAs (CommMonoid α), inferInstanceAs (CommSemiring α) with }
#align comm_semiring.to_comm_monoid_with_zero CommSemiring.toCommMonoidWithZero
section CommSemiring
variable [CommSemiring α] {a b c : α}
theorem add_mul_self_eq (a b : α) : (a + b) * (a + b) = a * a + 2 * a * b + b * b := by
simp only [two_mul, add_mul, mul_add, add_assoc, mul_comm b]
#align add_mul_self_eq add_mul_self_eq
lemma add_sq (a b : α) : (a + b) ^ 2 = a ^ 2 + 2 * a * b + b ^ 2 := by
simp only [sq, add_mul_self_eq]
#align add_sq add_sq
lemma add_sq' (a b : α) : (a + b) ^ 2 = a ^ 2 + b ^ 2 + 2 * a * b := by
rw [add_sq, add_assoc, add_comm _ (b ^ 2), add_assoc]
#align add_sq' add_sq'
alias add_pow_two := add_sq
#align add_pow_two add_pow_two
end CommSemiring
section HasDistribNeg
/-- Typeclass for a negation operator that distributes across multiplication.
This is useful for dealing with submonoids of a ring that contain `-1` without having to duplicate
lemmas. -/
class HasDistribNeg (α : Type*) [Mul α] extends InvolutiveNeg α where
/-- Negation is left distributive over multiplication -/
neg_mul : ∀ x y : α, -x * y = -(x * y)
/-- Negation is right distributive over multiplication -/
mul_neg : ∀ x y : α, x * -y = -(x * y)
#align has_distrib_neg HasDistribNeg
section Mul
variable [Mul α] [HasDistribNeg α]
@[simp]
theorem neg_mul (a b : α) : -a * b = -(a * b) :=
HasDistribNeg.neg_mul _ _
#align neg_mul neg_mul
@[simp]
theorem mul_neg (a b : α) : a * -b = -(a * b) :=
HasDistribNeg.mul_neg _ _
#align mul_neg mul_neg
theorem neg_mul_neg (a b : α) : -a * -b = a * b := by simp
#align neg_mul_neg neg_mul_neg
theorem neg_mul_eq_neg_mul (a b : α) : -(a * b) = -a * b :=
(neg_mul _ _).symm
#align neg_mul_eq_neg_mul neg_mul_eq_neg_mul
theorem neg_mul_eq_mul_neg (a b : α) : -(a * b) = a * -b :=
(mul_neg _ _).symm
#align neg_mul_eq_mul_neg neg_mul_eq_mul_neg
theorem neg_mul_comm (a b : α) : -a * b = a * -b := by simp
#align neg_mul_comm neg_mul_comm
end Mul
section MulOneClass
variable [MulOneClass α] [HasDistribNeg α]
theorem neg_eq_neg_one_mul (a : α) : -a = -1 * a := by simp
#align neg_eq_neg_one_mul neg_eq_neg_one_mul
/-- An element of a ring multiplied by the additive inverse of one is the element's additive
inverse. -/
theorem mul_neg_one (a : α) : a * -1 = -a := by simp
#align mul_neg_one mul_neg_one
/-- The additive inverse of one multiplied by an element of a ring is the element's additive
inverse. -/
theorem neg_one_mul (a : α) : -1 * a = -a := by simp
#align neg_one_mul neg_one_mul
end MulOneClass
section MulZeroClass
variable [MulZeroClass α] [HasDistribNeg α]
instance (priority := 100) MulZeroClass.negZeroClass : NegZeroClass α where
__ := inferInstanceAs (Zero α); __ := inferInstanceAs (InvolutiveNeg α)
neg_zero := by rw [← zero_mul (0 : α), ← neg_mul, mul_zero, mul_zero]
#align mul_zero_class.neg_zero_class MulZeroClass.negZeroClass
end MulZeroClass
end HasDistribNeg
/-!
### Rings
-/
section NonUnitalNonAssocRing
variable [NonUnitalNonAssocRing α]
instance (priority := 100) NonUnitalNonAssocRing.toHasDistribNeg : HasDistribNeg α where
neg := Neg.neg
neg_neg := neg_neg
neg_mul a b := eq_neg_of_add_eq_zero_left <| by rw [← right_distrib, add_left_neg, zero_mul]
mul_neg a b := eq_neg_of_add_eq_zero_left <| by rw [← left_distrib, add_left_neg, mul_zero]
#align non_unital_non_assoc_ring.to_has_distrib_neg NonUnitalNonAssocRing.toHasDistribNeg
theorem mul_sub_left_distrib (a b c : α) : a * (b - c) = a * b - a * c := by
simpa only [sub_eq_add_neg, neg_mul_eq_mul_neg] using mul_add a b (-c)
#align mul_sub_left_distrib mul_sub_left_distrib
alias mul_sub := mul_sub_left_distrib
#align mul_sub mul_sub
theorem mul_sub_right_distrib (a b c : α) : (a - b) * c = a * c - b * c := by
simpa only [sub_eq_add_neg, neg_mul_eq_neg_mul] using add_mul a (-b) c
#align mul_sub_right_distrib mul_sub_right_distrib
alias sub_mul := mul_sub_right_distrib
#align sub_mul sub_mul
#noalign mul_add_eq_mul_add_iff_sub_mul_add_eq
#noalign sub_mul_add_eq_of_mul_add_eq_mul_add
end NonUnitalNonAssocRing
section NonAssocRing
variable [NonAssocRing α]
| Mathlib/Algebra/Ring/Defs.lean | 413 | 413 | theorem sub_one_mul (a b : α) : (a - 1) * b = a * b - b := by | rw [sub_mul, one_mul]
|
/-
Copyright (c) 2019 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Anne Baanen
-/
import Mathlib.LinearAlgebra.Dimension.Basic
import Mathlib.SetTheory.Cardinal.ToNat
#align_import linear_algebra.finrank from "leanprover-community/mathlib"@"347636a7a80595d55bedf6e6fbd996a3c39da69a"
/-!
# Finite dimension of vector spaces
Definition of the rank of a module, or dimension of a vector space, as a natural number.
## Main definitions
Defined is `FiniteDimensional.finrank`, the dimension of a finite dimensional space, returning a
`Nat`, as opposed to `Module.rank`, which returns a `Cardinal`. When the space has infinite
dimension, its `finrank` is by convention set to `0`.
The definition of `finrank` does not assume a `FiniteDimensional` instance, but lemmas might.
Import `LinearAlgebra.FiniteDimensional` to get access to these additional lemmas.
Formulas for the dimension are given for linear equivs, in `LinearEquiv.finrank_eq`.
## Implementation notes
Most results are deduced from the corresponding results for the general dimension (as a cardinal),
in `Dimension.lean`. Not all results have been ported yet.
You should not assume that there has been any effort to state lemmas as generally as possible.
-/
universe u v w
open Cardinal Submodule Module Function
variable {R : Type u} {M : Type v} {N : Type w}
variable [Ring R] [AddCommGroup M] [Module R M] [AddCommGroup N] [Module R N]
namespace FiniteDimensional
section Ring
/-- The rank of a module as a natural number.
Defined by convention to be `0` if the space has infinite rank.
For a vector space `M` over a field `R`, this is the same as the finite dimension
of `M` over `R`.
-/
noncomputable def finrank (R M : Type*) [Semiring R] [AddCommGroup M] [Module R M] : ℕ :=
Cardinal.toNat (Module.rank R M)
#align finite_dimensional.finrank FiniteDimensional.finrank
theorem finrank_eq_of_rank_eq {n : ℕ} (h : Module.rank R M = ↑n) : finrank R M = n := by
apply_fun toNat at h
rw [toNat_natCast] at h
exact mod_cast h
#align finite_dimensional.finrank_eq_of_rank_eq FiniteDimensional.finrank_eq_of_rank_eq
lemma rank_eq_one_iff_finrank_eq_one : Module.rank R M = 1 ↔ finrank R M = 1 :=
Cardinal.toNat_eq_one.symm
/-- This is like `rank_eq_one_iff_finrank_eq_one` but works for `2`, `3`, `4`, ... -/
lemma rank_eq_ofNat_iff_finrank_eq_ofNat (n : ℕ) [Nat.AtLeastTwo n] :
Module.rank R M = OfNat.ofNat n ↔ finrank R M = OfNat.ofNat n :=
Cardinal.toNat_eq_ofNat.symm
theorem finrank_le_of_rank_le {n : ℕ} (h : Module.rank R M ≤ ↑n) : finrank R M ≤ n := by
rwa [← Cardinal.toNat_le_iff_le_of_lt_aleph0, toNat_natCast] at h
· exact h.trans_lt (nat_lt_aleph0 n)
· exact nat_lt_aleph0 n
#align finite_dimensional.finrank_le_of_rank_le FiniteDimensional.finrank_le_of_rank_le
theorem finrank_lt_of_rank_lt {n : ℕ} (h : Module.rank R M < ↑n) : finrank R M < n := by
rwa [← Cardinal.toNat_lt_iff_lt_of_lt_aleph0, toNat_natCast] at h
· exact h.trans (nat_lt_aleph0 n)
· exact nat_lt_aleph0 n
#align finite_dimensional.finrank_lt_of_rank_lt FiniteDimensional.finrank_lt_of_rank_lt
theorem lt_rank_of_lt_finrank {n : ℕ} (h : n < finrank R M) : ↑n < Module.rank R M := by
rwa [← Cardinal.toNat_lt_iff_lt_of_lt_aleph0, toNat_natCast]
· exact nat_lt_aleph0 n
· contrapose! h
rw [finrank, Cardinal.toNat_apply_of_aleph0_le h]
exact n.zero_le
#align finite_dimensional.rank_lt_of_finrank_lt FiniteDimensional.lt_rank_of_lt_finrank
theorem one_lt_rank_of_one_lt_finrank (h : 1 < finrank R M) : 1 < Module.rank R M := by
simpa using lt_rank_of_lt_finrank h
theorem finrank_le_finrank_of_rank_le_rank
(h : lift.{w} (Module.rank R M) ≤ Cardinal.lift.{v} (Module.rank R N))
(h' : Module.rank R N < ℵ₀) : finrank R M ≤ finrank R N := by
simpa only [toNat_lift] using toNat_le_toNat h (lift_lt_aleph0.mpr h')
#align finite_dimensional.finrank_le_finrank_of_rank_le_rank FiniteDimensional.finrank_le_finrank_of_rank_le_rank
end Ring
end FiniteDimensional
open FiniteDimensional
namespace LinearEquiv
variable {R M M₂ : Type*} [Ring R] [AddCommGroup M] [AddCommGroup M₂]
variable [Module R M] [Module R M₂]
/-- The dimension of a finite dimensional space is preserved under linear equivalence. -/
| Mathlib/LinearAlgebra/Dimension/Finrank.lean | 113 | 115 | theorem finrank_eq (f : M ≃ₗ[R] M₂) : finrank R M = finrank R M₂ := by |
unfold finrank
rw [← Cardinal.toNat_lift, f.lift_rank_eq, Cardinal.toNat_lift]
|
/-
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
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)
#align algebraic_independent_sUnion_of_directed algebraicIndependent_sUnion_of_directed
theorem exists_maximal_algebraicIndependent (s t : Set A) (hst : s ⊆ t)
(hs : AlgebraicIndependent R ((↑) : s → A)) :
∃ u : Set A, AlgebraicIndependent R ((↑) : u → A) ∧ s ⊆ u ∧ u ⊆ t ∧
∀ x : Set A, AlgebraicIndependent R ((↑) : x → A) → u ⊆ x → x ⊆ t → x = u := by
rcases zorn_subset_nonempty { u : Set A | AlgebraicIndependent R ((↑) : u → A) ∧ s ⊆ u ∧ u ⊆ t }
(fun c hc chainc hcn =>
⟨⋃₀ c, by
refine ⟨⟨algebraicIndependent_sUnion_of_directed hcn chainc.directedOn
fun a ha => (hc ha).1, ?_, ?_⟩, ?_⟩
· cases' hcn with x hx
exact subset_sUnion_of_subset _ x (hc hx).2.1 hx
· exact sUnion_subset fun x hx => (hc hx).2.2
· intro s
exact subset_sUnion_of_mem⟩)
s ⟨hs, Set.Subset.refl s, hst⟩ with
⟨u, ⟨huai, _, hut⟩, hsu, hx⟩
use u, huai, hsu, hut
intro x hxai huv hxt
exact hx _ ⟨hxai, _root_.trans hsu huv, hxt⟩ huv
#align exists_maximal_algebraic_independent exists_maximal_algebraicIndependent
section repr
variable (hx : AlgebraicIndependent R x)
/-- Canonical isomorphism between polynomials and the subalgebra generated by
algebraically independent elements. -/
@[simps!]
def AlgebraicIndependent.aevalEquiv (hx : AlgebraicIndependent R x) :
MvPolynomial ι R ≃ₐ[R] Algebra.adjoin R (range x) := by
apply
AlgEquiv.ofBijective (AlgHom.codRestrict (@aeval R A ι _ _ _ x) (Algebra.adjoin R (range x)) _)
swap
· intro x
rw [adjoin_range_eq_range_aeval]
exact AlgHom.mem_range_self _ _
· constructor
· exact (AlgHom.injective_codRestrict _ _ _).2 hx
· rintro ⟨x, hx⟩
rw [adjoin_range_eq_range_aeval] at hx
rcases hx with ⟨y, rfl⟩
use y
ext
simp
#align algebraic_independent.aeval_equiv AlgebraicIndependent.aevalEquiv
--@[simp] Porting note: removing simp because the linter complains about deterministic timeout
theorem AlgebraicIndependent.algebraMap_aevalEquiv (hx : AlgebraicIndependent R x)
(p : MvPolynomial ι R) :
algebraMap (Algebra.adjoin R (range x)) A (hx.aevalEquiv p) = aeval x p :=
rfl
#align algebraic_independent.algebra_map_aeval_equiv AlgebraicIndependent.algebraMap_aevalEquiv
/-- The canonical map from the subalgebra generated by an algebraic independent family
into the polynomial ring. -/
def AlgebraicIndependent.repr (hx : AlgebraicIndependent R x) :
Algebra.adjoin R (range x) →ₐ[R] MvPolynomial ι R :=
hx.aevalEquiv.symm
#align algebraic_independent.repr AlgebraicIndependent.repr
@[simp]
theorem AlgebraicIndependent.aeval_repr (p) : aeval x (hx.repr p) = p :=
Subtype.ext_iff.1 (AlgEquiv.apply_symm_apply hx.aevalEquiv p)
#align algebraic_independent.aeval_repr AlgebraicIndependent.aeval_repr
theorem AlgebraicIndependent.aeval_comp_repr : (aeval x).comp hx.repr = Subalgebra.val _ :=
AlgHom.ext <| hx.aeval_repr
#align algebraic_independent.aeval_comp_repr AlgebraicIndependent.aeval_comp_repr
theorem AlgebraicIndependent.repr_ker :
RingHom.ker (hx.repr : adjoin R (range x) →+* MvPolynomial ι R) = ⊥ :=
(RingHom.injective_iff_ker_eq_bot _).1 (AlgEquiv.injective _)
#align algebraic_independent.repr_ker AlgebraicIndependent.repr_ker
end repr
-- TODO - make this an `AlgEquiv`
/-- The isomorphism between `MvPolynomial (Option ι) R` and the polynomial ring over
the algebra generated by an algebraically independent family. -/
def AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin (hx : AlgebraicIndependent R x) :
MvPolynomial (Option ι) R ≃+* Polynomial (adjoin R (Set.range x)) :=
(MvPolynomial.optionEquivLeft _ _).toRingEquiv.trans
(Polynomial.mapEquiv hx.aevalEquiv.toRingEquiv)
#align algebraic_independent.mv_polynomial_option_equiv_polynomial_adjoin AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin
@[simp]
theorem AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin_apply
(hx : AlgebraicIndependent R x) (y) :
hx.mvPolynomialOptionEquivPolynomialAdjoin y =
Polynomial.map (hx.aevalEquiv : MvPolynomial ι R →+* adjoin R (range x))
(aeval (fun o : Option ι => o.elim Polynomial.X fun s : ι => Polynomial.C (X s)) y) :=
rfl
#align algebraic_independent.mv_polynomial_option_equiv_polynomial_adjoin_apply AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin_apply
--@[simp] Porting note: removing simp because the linter complains about deterministic timeout
theorem AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin_C
(hx : AlgebraicIndependent R x) (r) :
hx.mvPolynomialOptionEquivPolynomialAdjoin (C r) = Polynomial.C (algebraMap _ _ r) := by
rw [AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin_apply, aeval_C,
IsScalarTower.algebraMap_apply R (MvPolynomial ι R), ← Polynomial.C_eq_algebraMap,
Polynomial.map_C, RingHom.coe_coe, AlgEquiv.commutes]
set_option linter.uppercaseLean3 false in
#align algebraic_independent.mv_polynomial_option_equiv_polynomial_adjoin_C AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin_C
--@[simp] Porting note (#10618): simp can prove it
theorem AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin_X_none
(hx : AlgebraicIndependent R x) :
hx.mvPolynomialOptionEquivPolynomialAdjoin (X none) = Polynomial.X := by
rw [AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin_apply, aeval_X, Option.elim,
Polynomial.map_X]
set_option linter.uppercaseLean3 false in
#align algebraic_independent.mv_polynomial_option_equiv_polynomial_adjoin_X_none AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin_X_none
--@[simp] Porting note (#10618): simp can prove it
theorem AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin_X_some
(hx : AlgebraicIndependent R x) (i) :
hx.mvPolynomialOptionEquivPolynomialAdjoin (X (some i)) =
Polynomial.C (hx.aevalEquiv (X i)) := by
rw [AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin_apply, aeval_X, Option.elim,
Polynomial.map_C, RingHom.coe_coe]
set_option linter.uppercaseLean3 false in
#align algebraic_independent.mv_polynomial_option_equiv_polynomial_adjoin_X_some AlgebraicIndependent.mvPolynomialOptionEquivPolynomialAdjoin_X_some
theorem AlgebraicIndependent.aeval_comp_mvPolynomialOptionEquivPolynomialAdjoin
(hx : AlgebraicIndependent R x) (a : A) :
RingHom.comp
(↑(Polynomial.aeval a : Polynomial (adjoin R (Set.range x)) →ₐ[_] A) :
Polynomial (adjoin R (Set.range x)) →+* A)
hx.mvPolynomialOptionEquivPolynomialAdjoin.toRingHom =
↑(MvPolynomial.aeval fun o : Option ι => o.elim a x : MvPolynomial (Option ι) R →ₐ[R] A) := by
refine MvPolynomial.ringHom_ext ?_ ?_ <;>
simp only [RingHom.comp_apply, RingEquiv.toRingHom_eq_coe, RingEquiv.coe_toRingHom,
AlgHom.coe_toRingHom, AlgHom.coe_toRingHom]
· intro r
rw [hx.mvPolynomialOptionEquivPolynomialAdjoin_C, aeval_C, Polynomial.aeval_C,
IsScalarTower.algebraMap_apply R (adjoin R (range x)) A]
· rintro (⟨⟩ | ⟨i⟩)
· rw [hx.mvPolynomialOptionEquivPolynomialAdjoin_X_none, aeval_X, Polynomial.aeval_X,
Option.elim]
· rw [hx.mvPolynomialOptionEquivPolynomialAdjoin_X_some, Polynomial.aeval_C,
hx.algebraMap_aevalEquiv, aeval_X, aeval_X, Option.elim]
#align algebraic_independent.aeval_comp_mv_polynomial_option_equiv_polynomial_adjoin AlgebraicIndependent.aeval_comp_mvPolynomialOptionEquivPolynomialAdjoin
theorem AlgebraicIndependent.option_iff (hx : AlgebraicIndependent R x) (a : A) :
(AlgebraicIndependent R fun o : Option ι => o.elim a x) ↔
¬IsAlgebraic (adjoin R (Set.range x)) a := by
rw [algebraicIndependent_iff_injective_aeval, isAlgebraic_iff_not_injective, Classical.not_not, ←
AlgHom.coe_toRingHom, ← hx.aeval_comp_mvPolynomialOptionEquivPolynomialAdjoin,
RingHom.coe_comp]
exact Injective.of_comp_iff' (Polynomial.aeval a)
(mvPolynomialOptionEquivPolynomialAdjoin hx).bijective
#align algebraic_independent.option_iff AlgebraicIndependent.option_iff
variable (R)
/-- A family is a transcendence basis if it is a maximal algebraically independent subset. -/
def IsTranscendenceBasis (x : ι → A) : Prop :=
AlgebraicIndependent R x ∧
∀ (s : Set A) (_ : AlgebraicIndependent R ((↑) : s → A)) (_ : range x ≤ s), range x = s
#align is_transcendence_basis IsTranscendenceBasis
theorem exists_isTranscendenceBasis (h : Injective (algebraMap R A)) :
∃ s : Set A, IsTranscendenceBasis R ((↑) : s → A) := by
cases' exists_maximal_algebraicIndependent (∅ : Set A) Set.univ (Set.subset_univ _)
((algebraicIndependent_empty_iff R A).2 h) with
s hs
use s, hs.1
intro t ht hr
simp only [Subtype.range_coe_subtype, setOf_mem_eq] at *
exact Eq.symm (hs.2.2.2 t ht hr (Set.subset_univ _))
#align exists_is_transcendence_basis exists_isTranscendenceBasis
variable {R}
theorem AlgebraicIndependent.isTranscendenceBasis_iff {ι : Type w} {R : Type u} [CommRing R]
[Nontrivial R] {A : Type v} [CommRing A] [Algebra R A] {x : ι → A}
(i : AlgebraicIndependent R x) :
IsTranscendenceBasis R x ↔
∀ (κ : Type v) (w : κ → A) (_ : AlgebraicIndependent R w) (j : ι → κ) (_ : w ∘ j = x),
Surjective j := by
fconstructor
· rintro p κ w i' j rfl
have p := p.2 (range w) i'.coe_range (range_comp_subset_range _ _)
rw [range_comp, ← @image_univ _ _ w] at p
exact range_iff_surjective.mp (image_injective.mpr i'.injective p)
· intro p
use i
intro w i' h
specialize p w ((↑) : w → A) i' (fun i => ⟨x i, range_subset_iff.mp h i⟩) (by ext; simp)
have q := congr_arg (fun s => ((↑) : w → A) '' s) p.range_eq
dsimp at q
rw [← image_univ, image_image] at q
simpa using q
#align algebraic_independent.is_transcendence_basis_iff AlgebraicIndependent.isTranscendenceBasis_iff
theorem IsTranscendenceBasis.isAlgebraic [Nontrivial R] (hx : IsTranscendenceBasis R x) :
Algebra.IsAlgebraic (adjoin R (range x)) A := by
constructor
intro a
rw [← not_iff_comm.1 (hx.1.option_iff _).symm]
intro ai
have h₁ : range x ⊆ range fun o : Option ι => o.elim a x := by
rintro x ⟨y, rfl⟩
exact ⟨some y, rfl⟩
have h₂ : range x ≠ range fun o : Option ι => o.elim a x := by
intro h
have : a ∈ range x := by
rw [h]
exact ⟨none, rfl⟩
rcases this with ⟨b, rfl⟩
have : some b = none := ai.injective rfl
simpa
exact h₂ (hx.2 (Set.range fun o : Option ι => o.elim a x)
((algebraicIndependent_subtype_range ai.injective).2 ai) h₁)
#align is_transcendence_basis.is_algebraic IsTranscendenceBasis.isAlgebraic
section Field
variable [Field K] [Algebra K A]
/- Porting note: removing `simp`, not in simp normal form. Could make `Function.Injective f` a
simp lemma when `f` is a field hom, and then simp would prove this -/
| Mathlib/RingTheory/AlgebraicIndependent.lean | 560 | 562 | theorem algebraicIndependent_empty_type [IsEmpty ι] [Nontrivial A] : AlgebraicIndependent K x := by |
rw [algebraicIndependent_empty_type_iff]
exact RingHom.injective _
|
/-
Copyright (c) 2014 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Order.Ring.Cast
import Mathlib.Data.Int.Cast.Lemmas
import Mathlib.Data.Nat.Bitwise
import Mathlib.Data.Nat.PSub
import Mathlib.Data.Nat.Size
import Mathlib.Data.Num.Bitwise
#align_import data.num.lemmas from "leanprover-community/mathlib"@"2196ab363eb097c008d4497125e0dde23fb36db2"
/-!
# Properties of the binary representation of integers
-/
/-
Porting note:
`bit0` and `bit1` are deprecated because it is mainly used to represent number literal in Lean3 but
not in Lean4 anymore. However, this file uses them for encoding numbers so this linter is
unnecessary.
-/
set_option linter.deprecated false
-- Porting note: Required for the notation `-[n+1]`.
open Int Function
attribute [local simp] add_assoc
namespace PosNum
variable {α : Type*}
@[simp, norm_cast]
theorem cast_one [One α] [Add α] : ((1 : PosNum) : α) = 1 :=
rfl
#align pos_num.cast_one PosNum.cast_one
@[simp]
theorem cast_one' [One α] [Add α] : (PosNum.one : α) = 1 :=
rfl
#align pos_num.cast_one' PosNum.cast_one'
@[simp, norm_cast]
theorem cast_bit0 [One α] [Add α] (n : PosNum) : (n.bit0 : α) = _root_.bit0 (n : α) :=
rfl
#align pos_num.cast_bit0 PosNum.cast_bit0
@[simp, norm_cast]
theorem cast_bit1 [One α] [Add α] (n : PosNum) : (n.bit1 : α) = _root_.bit1 (n : α) :=
rfl
#align pos_num.cast_bit1 PosNum.cast_bit1
@[simp, norm_cast]
theorem cast_to_nat [AddMonoidWithOne α] : ∀ n : PosNum, ((n : ℕ) : α) = n
| 1 => Nat.cast_one
| bit0 p => (Nat.cast_bit0 _).trans <| congr_arg _root_.bit0 p.cast_to_nat
| bit1 p => (Nat.cast_bit1 _).trans <| congr_arg _root_.bit1 p.cast_to_nat
#align pos_num.cast_to_nat PosNum.cast_to_nat
@[norm_cast] -- @[simp] -- Porting note (#10618): simp can prove this
theorem to_nat_to_int (n : PosNum) : ((n : ℕ) : ℤ) = n :=
cast_to_nat _
#align pos_num.to_nat_to_int PosNum.to_nat_to_int
@[simp, norm_cast]
theorem cast_to_int [AddGroupWithOne α] (n : PosNum) : ((n : ℤ) : α) = n := by
rw [← to_nat_to_int, Int.cast_natCast, cast_to_nat]
#align pos_num.cast_to_int PosNum.cast_to_int
theorem succ_to_nat : ∀ n, (succ n : ℕ) = n + 1
| 1 => rfl
| bit0 p => rfl
| bit1 p =>
(congr_arg _root_.bit0 (succ_to_nat p)).trans <|
show ↑p + 1 + ↑p + 1 = ↑p + ↑p + 1 + 1 by simp [add_left_comm]
#align pos_num.succ_to_nat PosNum.succ_to_nat
theorem one_add (n : PosNum) : 1 + n = succ n := by cases n <;> rfl
#align pos_num.one_add PosNum.one_add
theorem add_one (n : PosNum) : n + 1 = succ n := by cases n <;> rfl
#align pos_num.add_one PosNum.add_one
@[norm_cast]
theorem add_to_nat : ∀ m n, ((m + n : PosNum) : ℕ) = m + n
| 1, b => by rw [one_add b, succ_to_nat, add_comm, cast_one]
| a, 1 => by rw [add_one a, succ_to_nat, cast_one]
| bit0 a, bit0 b => (congr_arg _root_.bit0 (add_to_nat a b)).trans <| add_add_add_comm _ _ _ _
| bit0 a, bit1 b =>
(congr_arg _root_.bit1 (add_to_nat a b)).trans <|
show (a + b + (a + b) + 1 : ℕ) = a + a + (b + b + 1) by simp [add_left_comm]
| bit1 a, bit0 b =>
(congr_arg _root_.bit1 (add_to_nat a b)).trans <|
show (a + b + (a + b) + 1 : ℕ) = a + a + 1 + (b + b) by simp [add_comm, add_left_comm]
| bit1 a, bit1 b =>
show (succ (a + b) + succ (a + b) : ℕ) = a + a + 1 + (b + b + 1) by
rw [succ_to_nat, add_to_nat a b]; simp [add_left_comm]
#align pos_num.add_to_nat PosNum.add_to_nat
theorem add_succ : ∀ m n : PosNum, m + succ n = succ (m + n)
| 1, b => by simp [one_add]
| bit0 a, 1 => congr_arg bit0 (add_one a)
| bit1 a, 1 => congr_arg bit1 (add_one a)
| bit0 a, bit0 b => rfl
| bit0 a, bit1 b => congr_arg bit0 (add_succ a b)
| bit1 a, bit0 b => rfl
| bit1 a, bit1 b => congr_arg bit1 (add_succ a b)
#align pos_num.add_succ PosNum.add_succ
theorem bit0_of_bit0 : ∀ n, _root_.bit0 n = bit0 n
| 1 => rfl
| bit0 p => congr_arg bit0 (bit0_of_bit0 p)
| bit1 p => show bit0 (succ (_root_.bit0 p)) = _ by rw [bit0_of_bit0 p, succ]
#align pos_num.bit0_of_bit0 PosNum.bit0_of_bit0
theorem bit1_of_bit1 (n : PosNum) : _root_.bit1 n = bit1 n :=
show _root_.bit0 n + 1 = bit1 n by rw [add_one, bit0_of_bit0, succ]
#align pos_num.bit1_of_bit1 PosNum.bit1_of_bit1
@[norm_cast]
theorem mul_to_nat (m) : ∀ n, ((m * n : PosNum) : ℕ) = m * n
| 1 => (mul_one _).symm
| bit0 p => show (↑(m * p) + ↑(m * p) : ℕ) = ↑m * (p + p) by rw [mul_to_nat m p, left_distrib]
| bit1 p =>
(add_to_nat (bit0 (m * p)) m).trans <|
show (↑(m * p) + ↑(m * p) + ↑m : ℕ) = ↑m * (p + p) + m by rw [mul_to_nat m p, left_distrib]
#align pos_num.mul_to_nat PosNum.mul_to_nat
theorem to_nat_pos : ∀ n : PosNum, 0 < (n : ℕ)
| 1 => Nat.zero_lt_one
| bit0 p =>
let h := to_nat_pos p
add_pos h h
| bit1 _p => Nat.succ_pos _
#align pos_num.to_nat_pos PosNum.to_nat_pos
theorem cmp_to_nat_lemma {m n : PosNum} : (m : ℕ) < n → (bit1 m : ℕ) < bit0 n :=
show (m : ℕ) < n → (m + m + 1 + 1 : ℕ) ≤ n + n by
intro h; rw [Nat.add_right_comm m m 1, add_assoc]; exact Nat.add_le_add h h
#align pos_num.cmp_to_nat_lemma PosNum.cmp_to_nat_lemma
theorem cmp_swap (m) : ∀ n, (cmp m n).swap = cmp n m := by
induction' m with m IH m IH <;> intro n <;> cases' n with n n <;> unfold cmp <;>
try { rfl } <;> rw [← IH] <;> cases cmp m n <;> rfl
#align pos_num.cmp_swap PosNum.cmp_swap
theorem cmp_to_nat : ∀ m n, (Ordering.casesOn (cmp m n) ((m : ℕ) < n) (m = n) ((n : ℕ) < m) : Prop)
| 1, 1 => rfl
| bit0 a, 1 =>
let h : (1 : ℕ) ≤ a := to_nat_pos a
Nat.add_le_add h h
| bit1 a, 1 => Nat.succ_lt_succ <| to_nat_pos <| bit0 a
| 1, bit0 b =>
let h : (1 : ℕ) ≤ b := to_nat_pos b
Nat.add_le_add h h
| 1, bit1 b => Nat.succ_lt_succ <| to_nat_pos <| bit0 b
| bit0 a, bit0 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.add_lt_add this this
· rw [this]
· exact Nat.add_lt_add this this
| bit0 a, bit1 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.le_succ_of_le (Nat.add_lt_add this this)
· rw [this]
apply Nat.lt_succ_self
· exact cmp_to_nat_lemma this
| bit1 a, bit0 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact cmp_to_nat_lemma this
· rw [this]
apply Nat.lt_succ_self
· exact Nat.le_succ_of_le (Nat.add_lt_add this this)
| bit1 a, bit1 b => by
dsimp [cmp]
have := cmp_to_nat a b; revert this; cases cmp a b <;> dsimp <;> intro this
· exact Nat.succ_lt_succ (Nat.add_lt_add this this)
· rw [this]
· exact Nat.succ_lt_succ (Nat.add_lt_add this this)
#align pos_num.cmp_to_nat PosNum.cmp_to_nat
@[norm_cast]
theorem lt_to_nat {m n : PosNum} : (m : ℕ) < n ↔ m < n :=
show (m : ℕ) < n ↔ cmp m n = Ordering.lt from
match cmp m n, cmp_to_nat m n with
| Ordering.lt, h => by simp only at h; simp [h]
| Ordering.eq, h => by simp only at h; simp [h, lt_irrefl]
| Ordering.gt, h => by simp [not_lt_of_gt h]
#align pos_num.lt_to_nat PosNum.lt_to_nat
@[norm_cast]
theorem le_to_nat {m n : PosNum} : (m : ℕ) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr lt_to_nat
#align pos_num.le_to_nat PosNum.le_to_nat
end PosNum
namespace Num
variable {α : Type*}
open PosNum
theorem add_zero (n : Num) : n + 0 = n := by cases n <;> rfl
#align num.add_zero Num.add_zero
theorem zero_add (n : Num) : 0 + n = n := by cases n <;> rfl
#align num.zero_add Num.zero_add
theorem add_one : ∀ n : Num, n + 1 = succ n
| 0 => rfl
| pos p => by cases p <;> rfl
#align num.add_one Num.add_one
theorem add_succ : ∀ m n : Num, m + succ n = succ (m + n)
| 0, n => by simp [zero_add]
| pos p, 0 => show pos (p + 1) = succ (pos p + 0) by rw [PosNum.add_one, add_zero, succ, succ']
| pos p, pos q => congr_arg pos (PosNum.add_succ _ _)
#align num.add_succ Num.add_succ
theorem bit0_of_bit0 : ∀ n : Num, bit0 n = n.bit0
| 0 => rfl
| pos p => congr_arg pos p.bit0_of_bit0
#align num.bit0_of_bit0 Num.bit0_of_bit0
theorem bit1_of_bit1 : ∀ n : Num, bit1 n = n.bit1
| 0 => rfl
| pos p => congr_arg pos p.bit1_of_bit1
#align num.bit1_of_bit1 Num.bit1_of_bit1
@[simp]
theorem ofNat'_zero : Num.ofNat' 0 = 0 := by simp [Num.ofNat']
#align num.of_nat'_zero Num.ofNat'_zero
theorem ofNat'_bit (b n) : ofNat' (Nat.bit b n) = cond b Num.bit1 Num.bit0 (ofNat' n) :=
Nat.binaryRec_eq rfl _ _
#align num.of_nat'_bit Num.ofNat'_bit
@[simp]
theorem ofNat'_one : Num.ofNat' 1 = 1 := by erw [ofNat'_bit true 0, cond, ofNat'_zero]; rfl
#align num.of_nat'_one Num.ofNat'_one
theorem bit1_succ : ∀ n : Num, n.bit1.succ = n.succ.bit0
| 0 => rfl
| pos _n => rfl
#align num.bit1_succ Num.bit1_succ
theorem ofNat'_succ : ∀ {n}, ofNat' (n + 1) = ofNat' n + 1 :=
@(Nat.binaryRec (by simp [zero_add]) fun b n ih => by
cases b
· erw [ofNat'_bit true n, ofNat'_bit]
simp only [← bit1_of_bit1, ← bit0_of_bit0, cond, _root_.bit1]
-- Porting note: `cc` was not ported yet so `exact Nat.add_left_comm n 1 1` is used.
· erw [show n.bit true + 1 = (n + 1).bit false by
simpa [Nat.bit, _root_.bit1, _root_.bit0] using Nat.add_left_comm n 1 1,
ofNat'_bit, ofNat'_bit, ih]
simp only [cond, add_one, bit1_succ])
#align num.of_nat'_succ Num.ofNat'_succ
@[simp]
theorem add_ofNat' (m n) : Num.ofNat' (m + n) = Num.ofNat' m + Num.ofNat' n := by
induction n
· simp only [Nat.add_zero, ofNat'_zero, add_zero]
· simp only [Nat.add_succ, Nat.add_zero, ofNat'_succ, add_one, add_succ, *]
#align num.add_of_nat' Num.add_ofNat'
@[simp, norm_cast]
theorem cast_zero [Zero α] [One α] [Add α] : ((0 : Num) : α) = 0 :=
rfl
#align num.cast_zero Num.cast_zero
@[simp]
theorem cast_zero' [Zero α] [One α] [Add α] : (Num.zero : α) = 0 :=
rfl
#align num.cast_zero' Num.cast_zero'
@[simp, norm_cast]
theorem cast_one [Zero α] [One α] [Add α] : ((1 : Num) : α) = 1 :=
rfl
#align num.cast_one Num.cast_one
@[simp]
theorem cast_pos [Zero α] [One α] [Add α] (n : PosNum) : (Num.pos n : α) = n :=
rfl
#align num.cast_pos Num.cast_pos
theorem succ'_to_nat : ∀ n, (succ' n : ℕ) = n + 1
| 0 => (Nat.zero_add _).symm
| pos _p => PosNum.succ_to_nat _
#align num.succ'_to_nat Num.succ'_to_nat
theorem succ_to_nat (n) : (succ n : ℕ) = n + 1 :=
succ'_to_nat n
#align num.succ_to_nat Num.succ_to_nat
@[simp, norm_cast]
theorem cast_to_nat [AddMonoidWithOne α] : ∀ n : Num, ((n : ℕ) : α) = n
| 0 => Nat.cast_zero
| pos p => p.cast_to_nat
#align num.cast_to_nat Num.cast_to_nat
@[norm_cast]
theorem add_to_nat : ∀ m n, ((m + n : Num) : ℕ) = m + n
| 0, 0 => rfl
| 0, pos _q => (Nat.zero_add _).symm
| pos _p, 0 => rfl
| pos _p, pos _q => PosNum.add_to_nat _ _
#align num.add_to_nat Num.add_to_nat
@[norm_cast]
theorem mul_to_nat : ∀ m n, ((m * n : Num) : ℕ) = m * n
| 0, 0 => rfl
| 0, pos _q => (zero_mul _).symm
| pos _p, 0 => rfl
| pos _p, pos _q => PosNum.mul_to_nat _ _
#align num.mul_to_nat Num.mul_to_nat
theorem cmp_to_nat : ∀ m n, (Ordering.casesOn (cmp m n) ((m : ℕ) < n) (m = n) ((n : ℕ) < m) : Prop)
| 0, 0 => rfl
| 0, pos b => to_nat_pos _
| pos a, 0 => to_nat_pos _
| pos a, pos b => by
have := PosNum.cmp_to_nat a b; revert this; dsimp [cmp]; cases PosNum.cmp a b
exacts [id, congr_arg pos, id]
#align num.cmp_to_nat Num.cmp_to_nat
@[norm_cast]
theorem lt_to_nat {m n : Num} : (m : ℕ) < n ↔ m < n :=
show (m : ℕ) < n ↔ cmp m n = Ordering.lt from
match cmp m n, cmp_to_nat m n with
| Ordering.lt, h => by simp only at h; simp [h]
| Ordering.eq, h => by simp only at h; simp [h, lt_irrefl]
| Ordering.gt, h => by simp [not_lt_of_gt h]
#align num.lt_to_nat Num.lt_to_nat
@[norm_cast]
theorem le_to_nat {m n : Num} : (m : ℕ) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr lt_to_nat
#align num.le_to_nat Num.le_to_nat
end Num
namespace PosNum
@[simp]
theorem of_to_nat' : ∀ n : PosNum, Num.ofNat' (n : ℕ) = Num.pos n
| 1 => by erw [@Num.ofNat'_bit true 0, Num.ofNat'_zero]; rfl
| bit0 p => by erw [@Num.ofNat'_bit false, of_to_nat' p]; rfl
| bit1 p => by erw [@Num.ofNat'_bit true, of_to_nat' p]; rfl
#align pos_num.of_to_nat' PosNum.of_to_nat'
end PosNum
namespace Num
@[simp, norm_cast]
theorem of_to_nat' : ∀ n : Num, Num.ofNat' (n : ℕ) = n
| 0 => ofNat'_zero
| pos p => p.of_to_nat'
#align num.of_to_nat' Num.of_to_nat'
lemma toNat_injective : Injective (castNum : Num → ℕ) := LeftInverse.injective of_to_nat'
@[norm_cast]
theorem to_nat_inj {m n : Num} : (m : ℕ) = n ↔ m = n := toNat_injective.eq_iff
#align num.to_nat_inj Num.to_nat_inj
/-- This tactic tries to turn an (in)equality about `Num`s to one about `Nat`s by rewriting.
```lean
example (n : Num) (m : Num) : n ≤ n + m := by
transfer_rw
exact Nat.le_add_right _ _
```
-/
scoped macro (name := transfer_rw) "transfer_rw" : tactic => `(tactic|
(repeat first | rw [← to_nat_inj] | rw [← lt_to_nat] | rw [← le_to_nat]
repeat first | rw [add_to_nat] | rw [mul_to_nat] | rw [cast_one] | rw [cast_zero]))
/--
This tactic tries to prove (in)equalities about `Num`s by transferring them to the `Nat` world and
then trying to call `simp`.
```lean
example (n : Num) (m : Num) : n ≤ n + m := by transfer
```
-/
scoped macro (name := transfer) "transfer" : tactic => `(tactic|
(intros; transfer_rw; try simp))
instance addMonoid : AddMonoid Num where
add := (· + ·)
zero := 0
zero_add := zero_add
add_zero := add_zero
add_assoc := by transfer
nsmul := nsmulRec
#align num.add_monoid Num.addMonoid
instance addMonoidWithOne : AddMonoidWithOne Num :=
{ Num.addMonoid with
natCast := Num.ofNat'
one := 1
natCast_zero := ofNat'_zero
natCast_succ := fun _ => ofNat'_succ }
#align num.add_monoid_with_one Num.addMonoidWithOne
instance commSemiring : CommSemiring Num where
__ := Num.addMonoid
__ := Num.addMonoidWithOne
mul := (· * ·)
npow := @npowRec Num ⟨1⟩ ⟨(· * ·)⟩
mul_zero _ := by rw [← to_nat_inj, mul_to_nat, cast_zero, mul_zero]
zero_mul _ := by rw [← to_nat_inj, mul_to_nat, cast_zero, zero_mul]
mul_one _ := by rw [← to_nat_inj, mul_to_nat, cast_one, mul_one]
one_mul _ := by rw [← to_nat_inj, mul_to_nat, cast_one, one_mul]
add_comm _ _ := by simp_rw [← to_nat_inj, add_to_nat, add_comm]
mul_comm _ _ := by simp_rw [← to_nat_inj, mul_to_nat, mul_comm]
mul_assoc _ _ _ := by simp_rw [← to_nat_inj, mul_to_nat, mul_assoc]
left_distrib _ _ _ := by simp only [← to_nat_inj, mul_to_nat, add_to_nat, mul_add]
right_distrib _ _ _ := by simp only [← to_nat_inj, mul_to_nat, add_to_nat, add_mul]
#align num.comm_semiring Num.commSemiring
instance orderedCancelAddCommMonoid : OrderedCancelAddCommMonoid Num where
le := (· ≤ ·)
lt := (· < ·)
lt_iff_le_not_le a b := by simp only [← lt_to_nat, ← le_to_nat, lt_iff_le_not_le]
le_refl := by transfer
le_trans a b c := by transfer_rw; apply le_trans
le_antisymm a b := by transfer_rw; apply le_antisymm
add_le_add_left a b h c := by revert h; transfer_rw; exact fun h => add_le_add_left h c
le_of_add_le_add_left a b c := by transfer_rw; apply le_of_add_le_add_left
#align num.ordered_cancel_add_comm_monoid Num.orderedCancelAddCommMonoid
instance linearOrderedSemiring : LinearOrderedSemiring Num :=
{ Num.commSemiring,
Num.orderedCancelAddCommMonoid with
le_total := by
intro a b
transfer_rw
apply le_total
zero_le_one := by decide
mul_lt_mul_of_pos_left := by
intro a b c
transfer_rw
apply mul_lt_mul_of_pos_left
mul_lt_mul_of_pos_right := by
intro a b c
transfer_rw
apply mul_lt_mul_of_pos_right
decidableLT := Num.decidableLT
decidableLE := Num.decidableLE
-- This is relying on an automatically generated instance name,
-- generated in a `deriving` handler.
-- See https://github.com/leanprover/lean4/issues/2343
decidableEq := instDecidableEqNum
exists_pair_ne := ⟨0, 1, by decide⟩ }
#align num.linear_ordered_semiring Num.linearOrderedSemiring
@[norm_cast] -- @[simp] -- Porting note (#10618): simp can prove this
theorem add_of_nat (m n) : ((m + n : ℕ) : Num) = m + n :=
add_ofNat' _ _
#align num.add_of_nat Num.add_of_nat
@[norm_cast] -- @[simp] -- Porting note (#10618): simp can prove this
theorem to_nat_to_int (n : Num) : ((n : ℕ) : ℤ) = n :=
cast_to_nat _
#align num.to_nat_to_int Num.to_nat_to_int
@[simp, norm_cast]
theorem cast_to_int {α} [AddGroupWithOne α] (n : Num) : ((n : ℤ) : α) = n := by
rw [← to_nat_to_int, Int.cast_natCast, cast_to_nat]
#align num.cast_to_int Num.cast_to_int
theorem to_of_nat : ∀ n : ℕ, ((n : Num) : ℕ) = n
| 0 => by rw [Nat.cast_zero, cast_zero]
| n + 1 => by rw [Nat.cast_succ, add_one, succ_to_nat, to_of_nat n]
#align num.to_of_nat Num.to_of_nat
@[simp, norm_cast]
theorem of_natCast {α} [AddMonoidWithOne α] (n : ℕ) : ((n : Num) : α) = n := by
rw [← cast_to_nat, to_of_nat]
#align num.of_nat_cast Num.of_natCast
@[deprecated (since := "2024-04-17")]
alias of_nat_cast := of_natCast
@[norm_cast] -- @[simp] -- Porting note (#10618): simp can prove this
theorem of_nat_inj {m n : ℕ} : (m : Num) = n ↔ m = n :=
⟨fun h => Function.LeftInverse.injective to_of_nat h, congr_arg _⟩
#align num.of_nat_inj Num.of_nat_inj
-- Porting note: The priority should be `high`er than `cast_to_nat`.
@[simp high, norm_cast]
theorem of_to_nat : ∀ n : Num, ((n : ℕ) : Num) = n :=
of_to_nat'
#align num.of_to_nat Num.of_to_nat
@[norm_cast]
theorem dvd_to_nat (m n : Num) : (m : ℕ) ∣ n ↔ m ∣ n :=
⟨fun ⟨k, e⟩ => ⟨k, by rw [← of_to_nat n, e]; simp⟩, fun ⟨k, e⟩ => ⟨k, by simp [e, mul_to_nat]⟩⟩
#align num.dvd_to_nat Num.dvd_to_nat
end Num
namespace PosNum
variable {α : Type*}
open Num
-- Porting note: The priority should be `high`er than `cast_to_nat`.
@[simp high, norm_cast]
theorem of_to_nat : ∀ n : PosNum, ((n : ℕ) : Num) = Num.pos n :=
of_to_nat'
#align pos_num.of_to_nat PosNum.of_to_nat
@[norm_cast]
theorem to_nat_inj {m n : PosNum} : (m : ℕ) = n ↔ m = n :=
⟨fun h => Num.pos.inj <| by rw [← PosNum.of_to_nat, ← PosNum.of_to_nat, h], congr_arg _⟩
#align pos_num.to_nat_inj PosNum.to_nat_inj
theorem pred'_to_nat : ∀ n, (pred' n : ℕ) = Nat.pred n
| 1 => rfl
| bit0 n =>
have : Nat.succ ↑(pred' n) = ↑n := by
rw [pred'_to_nat n, Nat.succ_pred_eq_of_pos (to_nat_pos n)]
match (motive :=
∀ k : Num, Nat.succ ↑k = ↑n → ↑(Num.casesOn k 1 bit1 : PosNum) = Nat.pred (_root_.bit0 n))
pred' n, this with
| 0, (h : ((1 : Num) : ℕ) = n) => by rw [← to_nat_inj.1 h]; rfl
| Num.pos p, (h : Nat.succ ↑p = n) => by rw [← h]; exact (Nat.succ_add p p).symm
| bit1 n => rfl
#align pos_num.pred'_to_nat PosNum.pred'_to_nat
@[simp]
theorem pred'_succ' (n) : pred' (succ' n) = n :=
Num.to_nat_inj.1 <| by rw [pred'_to_nat, succ'_to_nat, Nat.add_one, Nat.pred_succ]
#align pos_num.pred'_succ' PosNum.pred'_succ'
@[simp]
theorem succ'_pred' (n) : succ' (pred' n) = n :=
to_nat_inj.1 <| by
rw [succ'_to_nat, pred'_to_nat, Nat.add_one, Nat.succ_pred_eq_of_pos (to_nat_pos _)]
#align pos_num.succ'_pred' PosNum.succ'_pred'
instance dvd : Dvd PosNum :=
⟨fun m n => pos m ∣ pos n⟩
#align pos_num.has_dvd PosNum.dvd
@[norm_cast]
theorem dvd_to_nat {m n : PosNum} : (m : ℕ) ∣ n ↔ m ∣ n :=
Num.dvd_to_nat (pos m) (pos n)
#align pos_num.dvd_to_nat PosNum.dvd_to_nat
theorem size_to_nat : ∀ n, (size n : ℕ) = Nat.size n
| 1 => Nat.size_one.symm
| bit0 n => by
rw [size, succ_to_nat, size_to_nat n, cast_bit0, Nat.size_bit0 <| ne_of_gt <| to_nat_pos n]
| bit1 n => by rw [size, succ_to_nat, size_to_nat n, cast_bit1, Nat.size_bit1]
#align pos_num.size_to_nat PosNum.size_to_nat
theorem size_eq_natSize : ∀ n, (size n : ℕ) = natSize n
| 1 => rfl
| bit0 n => by rw [size, succ_to_nat, natSize, size_eq_natSize n]
| bit1 n => by rw [size, succ_to_nat, natSize, size_eq_natSize n]
#align pos_num.size_eq_nat_size PosNum.size_eq_natSize
theorem natSize_to_nat (n) : natSize n = Nat.size n := by rw [← size_eq_natSize, size_to_nat]
#align pos_num.nat_size_to_nat PosNum.natSize_to_nat
theorem natSize_pos (n) : 0 < natSize n := by cases n <;> apply Nat.succ_pos
#align pos_num.nat_size_pos PosNum.natSize_pos
/-- This tactic tries to turn an (in)equality about `PosNum`s to one about `Nat`s by rewriting.
```lean
example (n : PosNum) (m : PosNum) : n ≤ n + m := by
transfer_rw
exact Nat.le_add_right _ _
```
-/
scoped macro (name := transfer_rw) "transfer_rw" : tactic => `(tactic|
(repeat first | rw [← to_nat_inj] | rw [← lt_to_nat] | rw [← le_to_nat]
repeat first | rw [add_to_nat] | rw [mul_to_nat] | rw [cast_one] | rw [cast_zero]))
/--
This tactic tries to prove (in)equalities about `PosNum`s by transferring them to the `Nat` world
and then trying to call `simp`.
```lean
example (n : PosNum) (m : PosNum) : n ≤ n + m := by transfer
```
-/
scoped macro (name := transfer) "transfer" : tactic => `(tactic|
(intros; transfer_rw; try simp [add_comm, add_left_comm, mul_comm, mul_left_comm]))
instance addCommSemigroup : AddCommSemigroup PosNum where
add := (· + ·)
add_assoc := by transfer
add_comm := by transfer
#align pos_num.add_comm_semigroup PosNum.addCommSemigroup
instance commMonoid : CommMonoid PosNum where
mul := (· * ·)
one := (1 : PosNum)
npow := @npowRec PosNum ⟨1⟩ ⟨(· * ·)⟩
mul_assoc := by transfer
one_mul := by transfer
mul_one := by transfer
mul_comm := by transfer
#align pos_num.comm_monoid PosNum.commMonoid
instance distrib : Distrib PosNum where
add := (· + ·)
mul := (· * ·)
left_distrib := by transfer; simp [mul_add]
right_distrib := by transfer; simp [mul_add, mul_comm]
#align pos_num.distrib PosNum.distrib
instance linearOrder : LinearOrder PosNum where
lt := (· < ·)
lt_iff_le_not_le := by
intro a b
transfer_rw
apply lt_iff_le_not_le
le := (· ≤ ·)
le_refl := by transfer
le_trans := by
intro a b c
transfer_rw
apply le_trans
le_antisymm := by
intro a b
transfer_rw
apply le_antisymm
le_total := by
intro a b
transfer_rw
apply le_total
decidableLT := by infer_instance
decidableLE := by infer_instance
decidableEq := by infer_instance
#align pos_num.linear_order PosNum.linearOrder
@[simp]
theorem cast_to_num (n : PosNum) : ↑n = Num.pos n := by rw [← cast_to_nat, ← of_to_nat n]
#align pos_num.cast_to_num PosNum.cast_to_num
@[simp, norm_cast]
theorem bit_to_nat (b n) : (bit b n : ℕ) = Nat.bit b n := by cases b <;> rfl
#align pos_num.bit_to_nat PosNum.bit_to_nat
@[simp, norm_cast]
theorem cast_add [AddMonoidWithOne α] (m n) : ((m + n : PosNum) : α) = m + n := by
rw [← cast_to_nat, add_to_nat, Nat.cast_add, cast_to_nat, cast_to_nat]
#align pos_num.cast_add PosNum.cast_add
@[simp 500, norm_cast]
theorem cast_succ [AddMonoidWithOne α] (n : PosNum) : (succ n : α) = n + 1 := by
rw [← add_one, cast_add, cast_one]
#align pos_num.cast_succ PosNum.cast_succ
@[simp, norm_cast]
theorem cast_inj [AddMonoidWithOne α] [CharZero α] {m n : PosNum} : (m : α) = n ↔ m = n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_inj, to_nat_inj]
#align pos_num.cast_inj PosNum.cast_inj
@[simp]
theorem one_le_cast [LinearOrderedSemiring α] (n : PosNum) : (1 : α) ≤ n := by
rw [← cast_to_nat, ← Nat.cast_one, Nat.cast_le (α := α)]; apply to_nat_pos
#align pos_num.one_le_cast PosNum.one_le_cast
@[simp]
theorem cast_pos [LinearOrderedSemiring α] (n : PosNum) : 0 < (n : α) :=
lt_of_lt_of_le zero_lt_one (one_le_cast n)
#align pos_num.cast_pos PosNum.cast_pos
@[simp, norm_cast]
theorem cast_mul [Semiring α] (m n) : ((m * n : PosNum) : α) = m * n := by
rw [← cast_to_nat, mul_to_nat, Nat.cast_mul, cast_to_nat, cast_to_nat]
#align pos_num.cast_mul PosNum.cast_mul
@[simp]
theorem cmp_eq (m n) : cmp m n = Ordering.eq ↔ m = n := by
have := cmp_to_nat m n
-- Porting note: `cases` didn't rewrite at `this`, so `revert` & `intro` are required.
revert this; cases cmp m n <;> intro this <;> simp at this ⊢ <;> try { exact this } <;>
simp [show m ≠ n from fun e => by rw [e] at this;exact lt_irrefl _ this]
#align pos_num.cmp_eq PosNum.cmp_eq
@[simp, norm_cast]
theorem cast_lt [LinearOrderedSemiring α] {m n : PosNum} : (m : α) < n ↔ m < n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_lt (α := α), lt_to_nat]
#align pos_num.cast_lt PosNum.cast_lt
@[simp, norm_cast]
theorem cast_le [LinearOrderedSemiring α] {m n : PosNum} : (m : α) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr cast_lt
#align pos_num.cast_le PosNum.cast_le
end PosNum
namespace Num
variable {α : Type*}
open PosNum
theorem bit_to_nat (b n) : (bit b n : ℕ) = Nat.bit b n := by cases b <;> cases n <;> rfl
#align num.bit_to_nat Num.bit_to_nat
theorem cast_succ' [AddMonoidWithOne α] (n) : (succ' n : α) = n + 1 := by
rw [← PosNum.cast_to_nat, succ'_to_nat, Nat.cast_add_one, cast_to_nat]
#align num.cast_succ' Num.cast_succ'
theorem cast_succ [AddMonoidWithOne α] (n) : (succ n : α) = n + 1 :=
cast_succ' n
#align num.cast_succ Num.cast_succ
@[simp, norm_cast]
theorem cast_add [Semiring α] (m n) : ((m + n : Num) : α) = m + n := by
rw [← cast_to_nat, add_to_nat, Nat.cast_add, cast_to_nat, cast_to_nat]
#align num.cast_add Num.cast_add
@[simp, norm_cast]
theorem cast_bit0 [Semiring α] (n : Num) : (n.bit0 : α) = _root_.bit0 (n : α) := by
rw [← bit0_of_bit0, _root_.bit0, cast_add]; rfl
#align num.cast_bit0 Num.cast_bit0
@[simp, norm_cast]
theorem cast_bit1 [Semiring α] (n : Num) : (n.bit1 : α) = _root_.bit1 (n : α) := by
rw [← bit1_of_bit1, _root_.bit1, bit0_of_bit0, cast_add, cast_bit0]; rfl
#align num.cast_bit1 Num.cast_bit1
@[simp, norm_cast]
theorem cast_mul [Semiring α] : ∀ m n, ((m * n : Num) : α) = m * n
| 0, 0 => (zero_mul _).symm
| 0, pos _q => (zero_mul _).symm
| pos _p, 0 => (mul_zero _).symm
| pos _p, pos _q => PosNum.cast_mul _ _
#align num.cast_mul Num.cast_mul
theorem size_to_nat : ∀ n, (size n : ℕ) = Nat.size n
| 0 => Nat.size_zero.symm
| pos p => p.size_to_nat
#align num.size_to_nat Num.size_to_nat
theorem size_eq_natSize : ∀ n, (size n : ℕ) = natSize n
| 0 => rfl
| pos p => p.size_eq_natSize
#align num.size_eq_nat_size Num.size_eq_natSize
theorem natSize_to_nat (n) : natSize n = Nat.size n := by rw [← size_eq_natSize, size_to_nat]
#align num.nat_size_to_nat Num.natSize_to_nat
@[simp 999]
theorem ofNat'_eq : ∀ n, Num.ofNat' n = n :=
Nat.binaryRec (by simp) fun b n IH => by
rw [ofNat'] at IH ⊢
rw [Nat.binaryRec_eq, IH]
-- Porting note: `Nat.cast_bit0` & `Nat.cast_bit1` are not `simp` theorems anymore.
· cases b <;> simp [Nat.bit, bit0_of_bit0, bit1_of_bit1, Nat.cast_bit0, Nat.cast_bit1]
· rfl
#align num.of_nat'_eq Num.ofNat'_eq
theorem zneg_toZNum (n : Num) : -n.toZNum = n.toZNumNeg := by cases n <;> rfl
#align num.zneg_to_znum Num.zneg_toZNum
theorem zneg_toZNumNeg (n : Num) : -n.toZNumNeg = n.toZNum := by cases n <;> rfl
#align num.zneg_to_znum_neg Num.zneg_toZNumNeg
theorem toZNum_inj {m n : Num} : m.toZNum = n.toZNum ↔ m = n :=
⟨fun h => by cases m <;> cases n <;> cases h <;> rfl, congr_arg _⟩
#align num.to_znum_inj Num.toZNum_inj
@[simp]
theorem cast_toZNum [Zero α] [One α] [Add α] [Neg α] : ∀ n : Num, (n.toZNum : α) = n
| 0 => rfl
| Num.pos _p => rfl
#align num.cast_to_znum Num.cast_toZNum
@[simp]
theorem cast_toZNumNeg [AddGroup α] [One α] : ∀ n : Num, (n.toZNumNeg : α) = -n
| 0 => neg_zero.symm
| Num.pos _p => rfl
#align num.cast_to_znum_neg Num.cast_toZNumNeg
@[simp]
theorem add_toZNum (m n : Num) : Num.toZNum (m + n) = m.toZNum + n.toZNum := by
cases m <;> cases n <;> rfl
#align num.add_to_znum Num.add_toZNum
end Num
namespace PosNum
open Num
theorem pred_to_nat {n : PosNum} (h : 1 < n) : (pred n : ℕ) = Nat.pred n := by
unfold pred
cases e : pred' n
· have : (1 : ℕ) ≤ Nat.pred n := Nat.pred_le_pred ((@cast_lt ℕ _ _ _).2 h)
rw [← pred'_to_nat, e] at this
exact absurd this (by decide)
· rw [← pred'_to_nat, e]
rfl
#align pos_num.pred_to_nat PosNum.pred_to_nat
theorem sub'_one (a : PosNum) : sub' a 1 = (pred' a).toZNum := by cases a <;> rfl
#align pos_num.sub'_one PosNum.sub'_one
theorem one_sub' (a : PosNum) : sub' 1 a = (pred' a).toZNumNeg := by cases a <;> rfl
#align pos_num.one_sub' PosNum.one_sub'
theorem lt_iff_cmp {m n} : m < n ↔ cmp m n = Ordering.lt :=
Iff.rfl
#align pos_num.lt_iff_cmp PosNum.lt_iff_cmp
theorem le_iff_cmp {m n} : m ≤ n ↔ cmp m n ≠ Ordering.gt :=
not_congr <| lt_iff_cmp.trans <| by rw [← cmp_swap]; cases cmp m n <;> decide
#align pos_num.le_iff_cmp PosNum.le_iff_cmp
end PosNum
namespace Num
variable {α : Type*}
open PosNum
theorem pred_to_nat : ∀ n : Num, (pred n : ℕ) = Nat.pred n
| 0 => rfl
| pos p => by rw [pred, PosNum.pred'_to_nat]; rfl
#align num.pred_to_nat Num.pred_to_nat
theorem ppred_to_nat : ∀ n : Num, (↑) <$> ppred n = Nat.ppred n
| 0 => rfl
| pos p => by
rw [ppred, Option.map_some, Nat.ppred_eq_some.2]
rw [PosNum.pred'_to_nat, Nat.succ_pred_eq_of_pos (PosNum.to_nat_pos _)]
rfl
#align num.ppred_to_nat Num.ppred_to_nat
theorem cmp_swap (m n) : (cmp m n).swap = cmp n m := by
cases m <;> cases n <;> try { rfl }; apply PosNum.cmp_swap
#align num.cmp_swap Num.cmp_swap
theorem cmp_eq (m n) : cmp m n = Ordering.eq ↔ m = n := by
have := cmp_to_nat m n
-- Porting note: `cases` didn't rewrite at `this`, so `revert` & `intro` are required.
revert this; cases cmp m n <;> intro this <;> simp at this ⊢ <;> try { exact this } <;>
simp [show m ≠ n from fun e => by rw [e] at this; exact lt_irrefl _ this]
#align num.cmp_eq Num.cmp_eq
@[simp, norm_cast]
theorem cast_lt [LinearOrderedSemiring α] {m n : Num} : (m : α) < n ↔ m < n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_lt (α := α), lt_to_nat]
#align num.cast_lt Num.cast_lt
@[simp, norm_cast]
theorem cast_le [LinearOrderedSemiring α] {m n : Num} : (m : α) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr cast_lt
#align num.cast_le Num.cast_le
@[simp, norm_cast]
theorem cast_inj [LinearOrderedSemiring α] {m n : Num} : (m : α) = n ↔ m = n := by
rw [← cast_to_nat m, ← cast_to_nat n, Nat.cast_inj, to_nat_inj]
#align num.cast_inj Num.cast_inj
theorem lt_iff_cmp {m n} : m < n ↔ cmp m n = Ordering.lt :=
Iff.rfl
#align num.lt_iff_cmp Num.lt_iff_cmp
theorem le_iff_cmp {m n} : m ≤ n ↔ cmp m n ≠ Ordering.gt :=
not_congr <| lt_iff_cmp.trans <| by rw [← cmp_swap]; cases cmp m n <;> decide
#align num.le_iff_cmp Num.le_iff_cmp
theorem castNum_eq_bitwise {f : Num → Num → Num} {g : Bool → Bool → Bool}
(p : PosNum → PosNum → Num)
(gff : g false false = false) (f00 : f 0 0 = 0)
(f0n : ∀ n, f 0 (pos n) = cond (g false true) (pos n) 0)
(fn0 : ∀ n, f (pos n) 0 = cond (g true false) (pos n) 0)
(fnn : ∀ m n, f (pos m) (pos n) = p m n) (p11 : p 1 1 = cond (g true true) 1 0)
(p1b : ∀ b n, p 1 (PosNum.bit b n) = bit (g true b) (cond (g false true) (pos n) 0))
(pb1 : ∀ a m, p (PosNum.bit a m) 1 = bit (g a true) (cond (g true false) (pos m) 0))
(pbb : ∀ a b m n, p (PosNum.bit a m) (PosNum.bit b n) = bit (g a b) (p m n)) :
∀ m n : Num, (f m n : ℕ) = Nat.bitwise g m n := by
intros m n
cases' m with m <;> cases' n with n <;>
try simp only [show zero = 0 from rfl, show ((0 : Num) : ℕ) = 0 from rfl]
· rw [f00, Nat.bitwise_zero]; rfl
· rw [f0n, Nat.bitwise_zero_left]
cases g false true <;> rfl
· rw [fn0, Nat.bitwise_zero_right]
cases g true false <;> rfl
· rw [fnn]
have : ∀ (b) (n : PosNum), (cond b (↑n) 0 : ℕ) = ↑(cond b (pos n) 0 : Num) := by
intros b _; cases b <;> rfl
induction' m with m IH m IH generalizing n <;> cases' n with n n
any_goals simp only [show one = 1 from rfl, show pos 1 = 1 from rfl,
show PosNum.bit0 = PosNum.bit false from rfl, show PosNum.bit1 = PosNum.bit true from rfl,
show ((1 : Num) : ℕ) = Nat.bit true 0 from rfl]
all_goals
repeat
rw [show ∀ b n, (pos (PosNum.bit b n) : ℕ) = Nat.bit b ↑n by
intros b _; cases b <;> rfl]
rw [Nat.bitwise_bit gff]
any_goals rw [Nat.bitwise_zero, p11]; cases g true true <;> rfl
any_goals rw [Nat.bitwise_zero_left, ← Bool.cond_eq_ite, this, ← bit_to_nat, p1b]
any_goals rw [Nat.bitwise_zero_right, ← Bool.cond_eq_ite, this, ← bit_to_nat, pb1]
all_goals
rw [← show ∀ n : PosNum, ↑(p m n) = Nat.bitwise g ↑m ↑n from IH]
rw [← bit_to_nat, pbb]
#align num.bitwise_to_nat Num.castNum_eq_bitwise
@[simp, norm_cast]
theorem castNum_or : ∀ m n : Num, ↑(m ||| n) = (↑m ||| ↑n : ℕ) := by
-- Porting note: A name of an implicit local hypothesis is not available so
-- `cases_type*` is used.
apply castNum_eq_bitwise fun x y => pos (PosNum.lor x y) <;>
intros <;> (try cases_type* Bool) <;> rfl
#align num.lor_to_nat Num.castNum_or
@[simp, norm_cast]
theorem castNum_and : ∀ m n : Num, ↑(m &&& n) = (↑m &&& ↑n : ℕ) := by
apply castNum_eq_bitwise PosNum.land <;> intros <;> (try cases_type* Bool) <;> rfl
#align num.land_to_nat Num.castNum_and
@[simp, norm_cast]
theorem castNum_ldiff : ∀ m n : Num, (ldiff m n : ℕ) = Nat.ldiff m n := by
apply castNum_eq_bitwise PosNum.ldiff <;> intros <;> (try cases_type* Bool) <;> rfl
#align num.ldiff_to_nat Num.castNum_ldiff
@[simp, norm_cast]
theorem castNum_xor : ∀ m n : Num, ↑(m ^^^ n) = (↑m ^^^ ↑n : ℕ) := by
apply castNum_eq_bitwise PosNum.lxor <;> intros <;> (try cases_type* Bool) <;> rfl
#align num.lxor_to_nat Num.castNum_ldiff
@[simp, norm_cast]
theorem castNum_shiftLeft (m : Num) (n : Nat) : ↑(m <<< n) = (m : ℕ) <<< (n : ℕ) := by
cases m <;> dsimp only [← shiftl_eq_shiftLeft, shiftl]
· symm
apply Nat.zero_shiftLeft
simp only [cast_pos]
induction' n with n IH
· rfl
simp [PosNum.shiftl_succ_eq_bit0_shiftl, Nat.shiftLeft_succ, IH,
Nat.bit0_val, pow_succ, ← mul_assoc, mul_comm,
-shiftl_eq_shiftLeft, -PosNum.shiftl_eq_shiftLeft, shiftl]
#align num.shiftl_to_nat Num.castNum_shiftLeft
@[simp, norm_cast]
theorem castNum_shiftRight (m : Num) (n : Nat) : ↑(m >>> n) = (m : ℕ) >>> (n : ℕ) := by
cases' m with m <;> dsimp only [← shiftr_eq_shiftRight, shiftr];
· symm
apply Nat.zero_shiftRight
induction' n with n IH generalizing m
· cases m <;> rfl
cases' m with m m <;> dsimp only [PosNum.shiftr, ← PosNum.shiftr_eq_shiftRight]
· rw [Nat.shiftRight_eq_div_pow]
symm
apply Nat.div_eq_of_lt
simp
· trans
· apply IH
change Nat.shiftRight m n = Nat.shiftRight (_root_.bit1 m) (n + 1)
rw [add_comm n 1, @Nat.shiftRight_eq _ (1 + n), Nat.shiftRight_add]
apply congr_arg fun x => Nat.shiftRight x n
simp [Nat.shiftRight_succ, Nat.shiftRight_zero, ← Nat.div2_val]
· trans
· apply IH
change Nat.shiftRight m n = Nat.shiftRight (_root_.bit0 m) (n + 1)
rw [add_comm n 1, @Nat.shiftRight_eq _ (1 + n), Nat.shiftRight_add]
apply congr_arg fun x => Nat.shiftRight x n
simp [Nat.shiftRight_succ, Nat.shiftRight_zero, ← Nat.div2_val]
#align num.shiftr_to_nat Num.castNum_shiftRight
@[simp]
theorem castNum_testBit (m n) : testBit m n = Nat.testBit m n := by
-- Porting note: `unfold` → `dsimp only`
cases m with dsimp only [testBit]
| zero =>
rw [show (Num.zero : Nat) = 0 from rfl, Nat.zero_testBit]
| pos m =>
rw [cast_pos]
induction' n with n IH generalizing m <;> cases' m with m m
<;> dsimp only [PosNum.testBit, Nat.zero_eq]
· rfl
· rw [PosNum.cast_bit1, ← Nat.bit_true, Nat.testBit_bit_zero]
· rw [PosNum.cast_bit0, ← Nat.bit_false, Nat.testBit_bit_zero]
· simp
· rw [PosNum.cast_bit1, ← Nat.bit_true, Nat.testBit_bit_succ, IH]
· rw [PosNum.cast_bit0, ← Nat.bit_false, Nat.testBit_bit_succ, IH]
#align num.test_bit_to_nat Num.castNum_testBit
end Num
namespace ZNum
variable {α : Type*}
open PosNum
@[simp, norm_cast]
theorem cast_zero [Zero α] [One α] [Add α] [Neg α] : ((0 : ZNum) : α) = 0 :=
rfl
#align znum.cast_zero ZNum.cast_zero
@[simp]
theorem cast_zero' [Zero α] [One α] [Add α] [Neg α] : (ZNum.zero : α) = 0 :=
rfl
#align znum.cast_zero' ZNum.cast_zero'
@[simp, norm_cast]
theorem cast_one [Zero α] [One α] [Add α] [Neg α] : ((1 : ZNum) : α) = 1 :=
rfl
#align znum.cast_one ZNum.cast_one
@[simp]
theorem cast_pos [Zero α] [One α] [Add α] [Neg α] (n : PosNum) : (pos n : α) = n :=
rfl
#align znum.cast_pos ZNum.cast_pos
@[simp]
theorem cast_neg [Zero α] [One α] [Add α] [Neg α] (n : PosNum) : (neg n : α) = -n :=
rfl
#align znum.cast_neg ZNum.cast_neg
@[simp, norm_cast]
theorem cast_zneg [AddGroup α] [One α] : ∀ n, ((-n : ZNum) : α) = -n
| 0 => neg_zero.symm
| pos _p => rfl
| neg _p => (neg_neg _).symm
#align znum.cast_zneg ZNum.cast_zneg
theorem neg_zero : (-0 : ZNum) = 0 :=
rfl
#align znum.neg_zero ZNum.neg_zero
theorem zneg_pos (n : PosNum) : -pos n = neg n :=
rfl
#align znum.zneg_pos ZNum.zneg_pos
theorem zneg_neg (n : PosNum) : -neg n = pos n :=
rfl
#align znum.zneg_neg ZNum.zneg_neg
theorem zneg_zneg (n : ZNum) : - -n = n := by cases n <;> rfl
#align znum.zneg_zneg ZNum.zneg_zneg
theorem zneg_bit1 (n : ZNum) : -n.bit1 = (-n).bitm1 := by cases n <;> rfl
#align znum.zneg_bit1 ZNum.zneg_bit1
theorem zneg_bitm1 (n : ZNum) : -n.bitm1 = (-n).bit1 := by cases n <;> rfl
#align znum.zneg_bitm1 ZNum.zneg_bitm1
theorem zneg_succ (n : ZNum) : -n.succ = (-n).pred := by
cases n <;> try { rfl }; rw [succ, Num.zneg_toZNumNeg]; rfl
#align znum.zneg_succ ZNum.zneg_succ
theorem zneg_pred (n : ZNum) : -n.pred = (-n).succ := by
rw [← zneg_zneg (succ (-n)), zneg_succ, zneg_zneg]
#align znum.zneg_pred ZNum.zneg_pred
@[simp]
theorem abs_to_nat : ∀ n, (abs n : ℕ) = Int.natAbs n
| 0 => rfl
| pos p => congr_arg Int.natAbs p.to_nat_to_int
| neg p => show Int.natAbs ((p : ℕ) : ℤ) = Int.natAbs (-p) by rw [p.to_nat_to_int, Int.natAbs_neg]
#align znum.abs_to_nat ZNum.abs_to_nat
@[simp]
theorem abs_toZNum : ∀ n : Num, abs n.toZNum = n
| 0 => rfl
| Num.pos _p => rfl
#align znum.abs_to_znum ZNum.abs_toZNum
@[simp, norm_cast]
theorem cast_to_int [AddGroupWithOne α] : ∀ n : ZNum, ((n : ℤ) : α) = n
| 0 => by rw [cast_zero, cast_zero, Int.cast_zero]
| pos p => by rw [cast_pos, cast_pos, PosNum.cast_to_int]
| neg p => by rw [cast_neg, cast_neg, Int.cast_neg, PosNum.cast_to_int]
#align znum.cast_to_int ZNum.cast_to_int
theorem bit0_of_bit0 : ∀ n : ZNum, bit0 n = n.bit0
| 0 => rfl
| pos a => congr_arg pos a.bit0_of_bit0
| neg a => congr_arg neg a.bit0_of_bit0
#align znum.bit0_of_bit0 ZNum.bit0_of_bit0
theorem bit1_of_bit1 : ∀ n : ZNum, bit1 n = n.bit1
| 0 => rfl
| pos a => congr_arg pos a.bit1_of_bit1
| neg a => show PosNum.sub' 1 (_root_.bit0 a) = _ by rw [PosNum.one_sub', a.bit0_of_bit0]; rfl
#align znum.bit1_of_bit1 ZNum.bit1_of_bit1
@[simp, norm_cast]
theorem cast_bit0 [AddGroupWithOne α] : ∀ n : ZNum, (n.bit0 : α) = bit0 (n : α)
| 0 => (add_zero _).symm
| pos p => by rw [ZNum.bit0, cast_pos, cast_pos]; rfl
| neg p => by
rw [ZNum.bit0, cast_neg, cast_neg, PosNum.cast_bit0, _root_.bit0, _root_.bit0, neg_add_rev]
#align znum.cast_bit0 ZNum.cast_bit0
@[simp, norm_cast]
theorem cast_bit1 [AddGroupWithOne α] : ∀ n : ZNum, (n.bit1 : α) = bit1 (n : α)
| 0 => by simp [ZNum.bit1, _root_.bit1, _root_.bit0]
| pos p => by rw [ZNum.bit1, cast_pos, cast_pos]; rfl
| neg p => by
rw [ZNum.bit1, cast_neg, cast_neg]
cases' e : pred' p with a <;>
have ep : p = _ := (succ'_pred' p).symm.trans (congr_arg Num.succ' e)
· conv at ep => change p = 1
subst p
simp [_root_.bit1, _root_.bit0]
-- Porting note: `rw [Num.succ']` yields a `match` pattern.
· dsimp only [Num.succ'] at ep
subst p
have : (↑(-↑a : ℤ) : α) = -1 + ↑(-↑a + 1 : ℤ) := by simp [add_comm (- ↑a : ℤ) 1]
simpa [_root_.bit1, _root_.bit0] using this
#align znum.cast_bit1 ZNum.cast_bit1
@[simp]
theorem cast_bitm1 [AddGroupWithOne α] (n : ZNum) : (n.bitm1 : α) = bit0 (n : α) - 1 := by
conv =>
lhs
rw [← zneg_zneg n]
rw [← zneg_bit1, cast_zneg, cast_bit1]
have : ((-1 + n + n : ℤ) : α) = (n + n + -1 : ℤ) := by simp [add_comm, add_left_comm]
simpa [_root_.bit1, _root_.bit0, sub_eq_add_neg] using this
#align znum.cast_bitm1 ZNum.cast_bitm1
theorem add_zero (n : ZNum) : n + 0 = n := by cases n <;> rfl
#align znum.add_zero ZNum.add_zero
theorem zero_add (n : ZNum) : 0 + n = n := by cases n <;> rfl
#align znum.zero_add ZNum.zero_add
theorem add_one : ∀ n : ZNum, n + 1 = succ n
| 0 => rfl
| pos p => congr_arg pos p.add_one
| neg p => by cases p <;> rfl
#align znum.add_one ZNum.add_one
end ZNum
namespace PosNum
variable {α : Type*}
theorem cast_to_znum : ∀ n : PosNum, (n : ZNum) = ZNum.pos n
| 1 => rfl
| bit0 p => (ZNum.bit0_of_bit0 p).trans <| congr_arg _ (cast_to_znum p)
| bit1 p => (ZNum.bit1_of_bit1 p).trans <| congr_arg _ (cast_to_znum p)
#align pos_num.cast_to_znum PosNum.cast_to_znum
theorem cast_sub' [AddGroupWithOne α] : ∀ m n : PosNum, (sub' m n : α) = m - n
| a, 1 => by
rw [sub'_one, Num.cast_toZNum, ← Num.cast_to_nat, pred'_to_nat, ← Nat.sub_one]
simp [PosNum.cast_pos]
| 1, b => by
rw [one_sub', Num.cast_toZNumNeg, ← neg_sub, neg_inj, ← Num.cast_to_nat, pred'_to_nat,
← Nat.sub_one]
simp [PosNum.cast_pos]
| bit0 a, bit0 b => by
rw [sub', ZNum.cast_bit0, cast_sub' a b]
have : ((a + -b + (a + -b) : ℤ) : α) = a + a + (-b + -b) := by simp [add_left_comm]
simpa [_root_.bit0, sub_eq_add_neg] using this
| bit0 a, bit1 b => by
rw [sub', ZNum.cast_bitm1, cast_sub' a b]
have : ((-b + (a + (-b + -1)) : ℤ) : α) = (a + -1 + (-b + -b) : ℤ) := by
simp [add_comm, add_left_comm]
simpa [_root_.bit1, _root_.bit0, sub_eq_add_neg] using this
| bit1 a, bit0 b => by
rw [sub', ZNum.cast_bit1, cast_sub' a b]
have : ((-b + (a + (-b + 1)) : ℤ) : α) = (a + 1 + (-b + -b) : ℤ) := by
simp [add_comm, add_left_comm]
simpa [_root_.bit1, _root_.bit0, sub_eq_add_neg] using this
| bit1 a, bit1 b => by
rw [sub', ZNum.cast_bit0, cast_sub' a b]
have : ((-b + (a + -b) : ℤ) : α) = a + (-b + -b) := by simp [add_left_comm]
simpa [_root_.bit1, _root_.bit0, sub_eq_add_neg] using this
#align pos_num.cast_sub' PosNum.cast_sub'
theorem to_nat_eq_succ_pred (n : PosNum) : (n : ℕ) = n.pred' + 1 := by
rw [← Num.succ'_to_nat, n.succ'_pred']
#align pos_num.to_nat_eq_succ_pred PosNum.to_nat_eq_succ_pred
theorem to_int_eq_succ_pred (n : PosNum) : (n : ℤ) = (n.pred' : ℕ) + 1 := by
rw [← n.to_nat_to_int, to_nat_eq_succ_pred]; rfl
#align pos_num.to_int_eq_succ_pred PosNum.to_int_eq_succ_pred
end PosNum
namespace Num
variable {α : Type*}
@[simp]
theorem cast_sub' [AddGroupWithOne α] : ∀ m n : Num, (sub' m n : α) = m - n
| 0, 0 => (sub_zero _).symm
| pos _a, 0 => (sub_zero _).symm
| 0, pos _b => (zero_sub _).symm
| pos _a, pos _b => PosNum.cast_sub' _ _
#align num.cast_sub' Num.cast_sub'
theorem toZNum_succ : ∀ n : Num, n.succ.toZNum = n.toZNum.succ
| 0 => rfl
| pos _n => rfl
#align num.to_znum_succ Num.toZNum_succ
theorem toZNumNeg_succ : ∀ n : Num, n.succ.toZNumNeg = n.toZNumNeg.pred
| 0 => rfl
| pos _n => rfl
#align num.to_znum_neg_succ Num.toZNumNeg_succ
@[simp]
theorem pred_succ : ∀ n : ZNum, n.pred.succ = n
| 0 => rfl
| ZNum.neg p => show toZNumNeg (pos p).succ'.pred' = _ by rw [PosNum.pred'_succ']; rfl
| ZNum.pos p => by rw [ZNum.pred, ← toZNum_succ, Num.succ, PosNum.succ'_pred', toZNum]
#align num.pred_succ Num.pred_succ
-- Porting note: `erw [ZNum.ofInt', ZNum.ofInt']` yields `match` so
-- `change` & `dsimp` are required.
theorem succ_ofInt' : ∀ n, ZNum.ofInt' (n + 1) = ZNum.ofInt' n + 1
| (n : ℕ) => by
change ZNum.ofInt' (n + 1 : ℕ) = ZNum.ofInt' (n : ℕ) + 1
dsimp only [ZNum.ofInt', ZNum.ofInt']
rw [Num.ofNat'_succ, Num.add_one, toZNum_succ, ZNum.add_one]
| -[0+1] => by
change ZNum.ofInt' 0 = ZNum.ofInt' (-[0+1]) + 1
dsimp only [ZNum.ofInt', ZNum.ofInt']
rw [ofNat'_succ, ofNat'_zero]; rfl
| -[(n + 1)+1] => by
change ZNum.ofInt' -[n+1] = ZNum.ofInt' -[(n + 1)+1] + 1
dsimp only [ZNum.ofInt', ZNum.ofInt']
rw [@Num.ofNat'_succ (n + 1), Num.add_one, toZNumNeg_succ,
@ofNat'_succ n, Num.add_one, ZNum.add_one, pred_succ]
#align num.succ_of_int' Num.succ_ofInt'
theorem ofInt'_toZNum : ∀ n : ℕ, toZNum n = ZNum.ofInt' n
| 0 => rfl
| n + 1 => by
rw [Nat.cast_succ, Num.add_one, toZNum_succ, ofInt'_toZNum n, Nat.cast_succ, succ_ofInt',
ZNum.add_one]
#align num.of_int'_to_znum Num.ofInt'_toZNum
theorem mem_ofZNum' : ∀ {m : Num} {n : ZNum}, m ∈ ofZNum' n ↔ n = toZNum m
| 0, 0 => ⟨fun _ => rfl, fun _ => rfl⟩
| pos m, 0 => ⟨nofun, nofun⟩
| m, ZNum.pos p =>
Option.some_inj.trans <| by cases m <;> constructor <;> intro h <;> try cases h <;> rfl
| m, ZNum.neg p => ⟨nofun, fun h => by cases m <;> cases h⟩
#align num.mem_of_znum' Num.mem_ofZNum'
theorem ofZNum'_toNat : ∀ n : ZNum, (↑) <$> ofZNum' n = Int.toNat' n
| 0 => rfl
| ZNum.pos p => show _ = Int.toNat' p by rw [← PosNum.to_nat_to_int p]; rfl
| ZNum.neg p =>
(congr_arg fun x => Int.toNat' (-x)) <|
show ((p.pred' + 1 : ℕ) : ℤ) = p by rw [← succ'_to_nat]; simp
#align num.of_znum'_to_nat Num.ofZNum'_toNat
@[simp]
theorem ofZNum_toNat : ∀ n : ZNum, (ofZNum n : ℕ) = Int.toNat n
| 0 => rfl
| ZNum.pos p => show _ = Int.toNat p by rw [← PosNum.to_nat_to_int p]; rfl
| ZNum.neg p =>
(congr_arg fun x => Int.toNat (-x)) <|
show ((p.pred' + 1 : ℕ) : ℤ) = p by rw [← succ'_to_nat]; simp
#align num.of_znum_to_nat Num.ofZNum_toNat
@[simp]
theorem cast_ofZNum [AddGroupWithOne α] (n : ZNum) : (ofZNum n : α) = Int.toNat n := by
rw [← cast_to_nat, ofZNum_toNat]
#align num.cast_of_znum Num.cast_ofZNum
@[simp, norm_cast]
theorem sub_to_nat (m n) : ((m - n : Num) : ℕ) = m - n :=
show (ofZNum _ : ℕ) = _ by
rw [ofZNum_toNat, cast_sub', ← to_nat_to_int, ← to_nat_to_int, Int.toNat_sub]
#align num.sub_to_nat Num.sub_to_nat
end Num
namespace ZNum
variable {α : Type*}
@[simp, norm_cast]
theorem cast_add [AddGroupWithOne α] : ∀ m n, ((m + n : ZNum) : α) = m + n
| 0, a => by cases a <;> exact (_root_.zero_add _).symm
| b, 0 => by cases b <;> exact (_root_.add_zero _).symm
| pos a, pos b => PosNum.cast_add _ _
| pos a, neg b => by simpa only [sub_eq_add_neg] using PosNum.cast_sub' (α := α) _ _
| neg a, pos b =>
have : (↑b + -↑a : α) = -↑a + ↑b := by
rw [← PosNum.cast_to_int a, ← PosNum.cast_to_int b, ← Int.cast_neg, ← Int.cast_add (-a)]
simp [add_comm]
(PosNum.cast_sub' _ _).trans <| (sub_eq_add_neg _ _).trans this
| neg a, neg b =>
show -(↑(a + b) : α) = -a + -b by
rw [PosNum.cast_add, neg_eq_iff_eq_neg, neg_add_rev, neg_neg, neg_neg,
← PosNum.cast_to_int a, ← PosNum.cast_to_int b, ← Int.cast_add, ← Int.cast_add, add_comm]
#align znum.cast_add ZNum.cast_add
@[simp]
theorem cast_succ [AddGroupWithOne α] (n) : ((succ n : ZNum) : α) = n + 1 := by
rw [← add_one, cast_add, cast_one]
#align znum.cast_succ ZNum.cast_succ
@[simp, norm_cast]
theorem mul_to_int : ∀ m n, ((m * n : ZNum) : ℤ) = m * n
| 0, a => by cases a <;> exact (zero_mul _).symm
| b, 0 => by cases b <;> exact (mul_zero _).symm
| pos a, pos b => PosNum.cast_mul a b
| pos a, neg b => show -↑(a * b) = ↑a * -↑b by rw [PosNum.cast_mul, neg_mul_eq_mul_neg]
| neg a, pos b => show -↑(a * b) = -↑a * ↑b by rw [PosNum.cast_mul, neg_mul_eq_neg_mul]
| neg a, neg b => show ↑(a * b) = -↑a * -↑b by rw [PosNum.cast_mul, neg_mul_neg]
#align znum.mul_to_int ZNum.mul_to_int
theorem cast_mul [Ring α] (m n) : ((m * n : ZNum) : α) = m * n := by
rw [← cast_to_int, mul_to_int, Int.cast_mul, cast_to_int, cast_to_int]
#align znum.cast_mul ZNum.cast_mul
theorem ofInt'_neg : ∀ n : ℤ, ofInt' (-n) = -ofInt' n
| -[n+1] => show ofInt' (n + 1 : ℕ) = _ by simp only [ofInt', Num.zneg_toZNumNeg]
| 0 => show Num.toZNum (Num.ofNat' 0) = -Num.toZNum (Num.ofNat' 0) by rw [Num.ofNat'_zero]; rfl
| (n + 1 : ℕ) => show Num.toZNumNeg _ = -Num.toZNum _ by rw [Num.zneg_toZNum]
#align znum.of_int'_neg ZNum.ofInt'_neg
-- Porting note: `erw [ofInt']` yields `match` so `dsimp` is required.
theorem of_to_int' : ∀ n : ZNum, ZNum.ofInt' n = n
| 0 => by dsimp [ofInt', cast_zero]; erw [Num.ofNat'_zero, Num.toZNum]
| pos a => by rw [cast_pos, ← PosNum.cast_to_nat, ← Num.ofInt'_toZNum, PosNum.of_to_nat]; rfl
| neg a => by
rw [cast_neg, ofInt'_neg, ← PosNum.cast_to_nat, ← Num.ofInt'_toZNum, PosNum.of_to_nat]; rfl
#align znum.of_to_int' ZNum.of_to_int'
theorem to_int_inj {m n : ZNum} : (m : ℤ) = n ↔ m = n :=
⟨fun h => Function.LeftInverse.injective of_to_int' h, congr_arg _⟩
#align znum.to_int_inj ZNum.to_int_inj
theorem cmp_to_int : ∀ m n, (Ordering.casesOn (cmp m n) ((m : ℤ) < n) (m = n) ((n : ℤ) < m) : Prop)
| 0, 0 => rfl
| pos a, pos b => by
have := PosNum.cmp_to_nat a b; revert this; dsimp [cmp]
cases PosNum.cmp a b <;> dsimp <;> [simp; exact congr_arg pos; simp [GT.gt]]
| neg a, neg b => by
have := PosNum.cmp_to_nat b a; revert this; dsimp [cmp]
cases PosNum.cmp b a <;> dsimp <;> [simp; simp (config := { contextual := true }); simp [GT.gt]]
| pos a, 0 => PosNum.cast_pos _
| pos a, neg b => lt_trans (neg_lt_zero.2 <| PosNum.cast_pos _) (PosNum.cast_pos _)
| 0, neg b => neg_lt_zero.2 <| PosNum.cast_pos _
| neg a, 0 => neg_lt_zero.2 <| PosNum.cast_pos _
| neg a, pos b => lt_trans (neg_lt_zero.2 <| PosNum.cast_pos _) (PosNum.cast_pos _)
| 0, pos b => PosNum.cast_pos _
#align znum.cmp_to_int ZNum.cmp_to_int
@[norm_cast]
theorem lt_to_int {m n : ZNum} : (m : ℤ) < n ↔ m < n :=
show (m : ℤ) < n ↔ cmp m n = Ordering.lt from
match cmp m n, cmp_to_int m n with
| Ordering.lt, h => by simp only at h; simp [h]
| Ordering.eq, h => by simp only at h; simp [h, lt_irrefl]
| Ordering.gt, h => by simp [not_lt_of_gt h]
#align znum.lt_to_int ZNum.lt_to_int
theorem le_to_int {m n : ZNum} : (m : ℤ) ≤ n ↔ m ≤ n := by
rw [← not_lt]; exact not_congr lt_to_int
#align znum.le_to_int ZNum.le_to_int
@[simp, norm_cast]
| Mathlib/Data/Num/Lemmas.lean | 1,380 | 1,381 | theorem cast_lt [LinearOrderedRing α] {m n : ZNum} : (m : α) < n ↔ m < n := by |
rw [← cast_to_int m, ← cast_to_int n, Int.cast_lt, lt_to_int]
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Data.Finset.Lattice
import Mathlib.Data.Set.Sigma
#align_import data.finset.sigma from "leanprover-community/mathlib"@"9003f28797c0664a49e4179487267c494477d853"
/-!
# Finite sets in a sigma type
This file defines a few `Finset` constructions on `Σ i, α i`.
## Main declarations
* `Finset.sigma`: Given a finset `s` in `ι` and finsets `t i` in each `α i`, `s.sigma t` is the
finset of the dependent sum `Σ i, α i`
* `Finset.sigmaLift`: Lifts maps `α i → β i → Finset (γ i)` to a map
`Σ i, α i → Σ i, β i → Finset (Σ i, γ i)`.
## TODO
`Finset.sigmaLift` can be generalized to any alternative functor. But to make the generalization
worth it, we must first refactor the functor library so that the `alternative` instance for `Finset`
is computable and universe-polymorphic.
-/
open Function Multiset
variable {ι : Type*}
namespace Finset
section Sigma
variable {α : ι → Type*} {β : Type*} (s s₁ s₂ : Finset ι) (t t₁ t₂ : ∀ i, Finset (α i))
/-- `s.sigma t` is the finset of dependent pairs `⟨i, a⟩` such that `i ∈ s` and `a ∈ t i`. -/
protected def sigma : Finset (Σi, α i) :=
⟨_, s.nodup.sigma fun i => (t i).nodup⟩
#align finset.sigma Finset.sigma
variable {s s₁ s₂ t t₁ t₂}
@[simp]
theorem mem_sigma {a : Σi, α i} : a ∈ s.sigma t ↔ a.1 ∈ s ∧ a.2 ∈ t a.1 :=
Multiset.mem_sigma
#align finset.mem_sigma Finset.mem_sigma
@[simp, norm_cast]
theorem coe_sigma (s : Finset ι) (t : ∀ i, Finset (α i)) :
(s.sigma t : Set (Σ i, α i)) = (s : Set ι).sigma fun i ↦ (t i : Set (α i)) :=
Set.ext fun _ => mem_sigma
#align finset.coe_sigma Finset.coe_sigma
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem sigma_nonempty : (s.sigma t).Nonempty ↔ ∃ i ∈ s, (t i).Nonempty := by simp [Finset.Nonempty]
#align finset.sigma_nonempty Finset.sigma_nonempty
@[simp]
theorem sigma_eq_empty : s.sigma t = ∅ ↔ ∀ i ∈ s, t i = ∅ := by
simp only [← not_nonempty_iff_eq_empty, sigma_nonempty, not_exists, not_and]
#align finset.sigma_eq_empty Finset.sigma_eq_empty
@[mono]
theorem sigma_mono (hs : s₁ ⊆ s₂) (ht : ∀ i, t₁ i ⊆ t₂ i) : s₁.sigma t₁ ⊆ s₂.sigma t₂ :=
fun ⟨i, _⟩ h =>
let ⟨hi, ha⟩ := mem_sigma.1 h
mem_sigma.2 ⟨hs hi, ht i ha⟩
#align finset.sigma_mono Finset.sigma_mono
theorem pairwiseDisjoint_map_sigmaMk :
(s : Set ι).PairwiseDisjoint fun i => (t i).map (Embedding.sigmaMk i) := by
intro i _ j _ hij
rw [Function.onFun, disjoint_left]
simp_rw [mem_map, Function.Embedding.sigmaMk_apply]
rintro _ ⟨y, _, rfl⟩ ⟨z, _, hz'⟩
exact hij (congr_arg Sigma.fst hz'.symm)
#align finset.pairwise_disjoint_map_sigma_mk Finset.pairwiseDisjoint_map_sigmaMk
@[simp]
theorem disjiUnion_map_sigma_mk :
s.disjiUnion (fun i => (t i).map (Embedding.sigmaMk i)) pairwiseDisjoint_map_sigmaMk =
s.sigma t :=
rfl
#align finset.disj_Union_map_sigma_mk Finset.disjiUnion_map_sigma_mk
theorem sigma_eq_biUnion [DecidableEq (Σi, α i)] (s : Finset ι) (t : ∀ i, Finset (α i)) :
s.sigma t = s.biUnion fun i => (t i).map <| Embedding.sigmaMk i := by
ext ⟨x, y⟩
simp [and_left_comm]
#align finset.sigma_eq_bUnion Finset.sigma_eq_biUnion
variable (s t) (f : (Σi, α i) → β)
theorem sup_sigma [SemilatticeSup β] [OrderBot β] :
(s.sigma t).sup f = s.sup fun i => (t i).sup fun b => f ⟨i, b⟩ := by
simp only [le_antisymm_iff, Finset.sup_le_iff, mem_sigma, and_imp, Sigma.forall]
exact
⟨fun i a hi ha => (le_sup hi).trans' <| le_sup (f := fun a => f ⟨i, a⟩) ha, fun i hi a ha =>
le_sup <| mem_sigma.2 ⟨hi, ha⟩⟩
#align finset.sup_sigma Finset.sup_sigma
theorem inf_sigma [SemilatticeInf β] [OrderTop β] :
(s.sigma t).inf f = s.inf fun i => (t i).inf fun b => f ⟨i, b⟩ :=
@sup_sigma _ _ βᵒᵈ _ _ _ _ _
#align finset.inf_sigma Finset.inf_sigma
theorem _root_.biSup_finsetSigma [CompleteLattice β] (s : Finset ι) (t : ∀ i, Finset (α i))
(f : Sigma α → β) : ⨆ ij ∈ s.sigma t, f ij = ⨆ (i ∈ s) (j ∈ t i), f ⟨i, j⟩ := by
simp_rw [← Finset.iSup_coe, Finset.coe_sigma, biSup_sigma]
theorem _root_.biSup_finsetSigma' [CompleteLattice β] (s : Finset ι) (t : ∀ i, Finset (α i))
(f : ∀ i, α i → β) : ⨆ (i ∈ s) (j ∈ t i), f i j = ⨆ ij ∈ s.sigma t, f ij.fst ij.snd :=
Eq.symm (biSup_finsetSigma _ _ _)
theorem _root_.biInf_finsetSigma [CompleteLattice β] (s : Finset ι) (t : ∀ i, Finset (α i))
(f : Sigma α → β) : ⨅ ij ∈ s.sigma t, f ij = ⨅ (i ∈ s) (j ∈ t i), f ⟨i, j⟩ :=
biSup_finsetSigma (β := βᵒᵈ) _ _ _
theorem _root_.biInf_finsetSigma' [CompleteLattice β] (s : Finset ι) (t : ∀ i, Finset (α i))
(f : ∀ i, α i → β) : ⨅ (i ∈ s) (j ∈ t i), f i j = ⨅ ij ∈ s.sigma t, f ij.fst ij.snd :=
Eq.symm (biInf_finsetSigma _ _ _)
theorem _root_.Set.biUnion_finsetSigma (s : Finset ι) (t : ∀ i, Finset (α i))
(f : Sigma α → Set β) : ⋃ ij ∈ s.sigma t, f ij = ⋃ i ∈ s, ⋃ j ∈ t i, f ⟨i, j⟩ :=
biSup_finsetSigma _ _ _
theorem _root_.Set.biUnion_finsetSigma' (s : Finset ι) (t : ∀ i, Finset (α i))
(f : ∀ i, α i → Set β) : ⋃ i ∈ s, ⋃ j ∈ t i, f i j = ⋃ ij ∈ s.sigma t, f ij.fst ij.snd :=
biSup_finsetSigma' _ _ _
theorem _root_.Set.biInter_finsetSigma (s : Finset ι) (t : ∀ i, Finset (α i))
(f : Sigma α → Set β) : ⋂ ij ∈ s.sigma t, f ij = ⋂ i ∈ s, ⋂ j ∈ t i, f ⟨i, j⟩ :=
biInf_finsetSigma _ _ _
theorem _root_.Set.biInter_finsetSigma' (s : Finset ι) (t : ∀ i, Finset (α i))
(f : ∀ i, α i → Set β) : ⋂ i ∈ s, ⋂ j ∈ t i, f i j = ⋂ ij ∈ s.sigma t, f ij.1 ij.2 :=
biInf_finsetSigma' _ _ _
end Sigma
section SigmaLift
variable {α β γ : ι → Type*} [DecidableEq ι]
/-- Lifts maps `α i → β i → Finset (γ i)` to a map `Σ i, α i → Σ i, β i → Finset (Σ i, γ i)`. -/
def sigmaLift (f : ∀ ⦃i⦄, α i → β i → Finset (γ i)) (a : Sigma α) (b : Sigma β) :
Finset (Sigma γ) :=
dite (a.1 = b.1) (fun h => (f (h ▸ a.2) b.2).map <| Embedding.sigmaMk _) fun _ => ∅
#align finset.sigma_lift Finset.sigmaLift
theorem mem_sigmaLift (f : ∀ ⦃i⦄, α i → β i → Finset (γ i)) (a : Sigma α) (b : Sigma β)
(x : Sigma γ) :
x ∈ sigmaLift f a b ↔ ∃ (ha : a.1 = x.1) (hb : b.1 = x.1), x.2 ∈ f (ha ▸ a.2) (hb ▸ b.2) := by
obtain ⟨⟨i, a⟩, j, b⟩ := a, b
obtain rfl | h := Decidable.eq_or_ne i j
· constructor
· simp_rw [sigmaLift]
simp only [dite_eq_ite, ite_true, mem_map, Embedding.sigmaMk_apply, forall_exists_index,
and_imp]
rintro x hx rfl
exact ⟨rfl, rfl, hx⟩
· rintro ⟨⟨⟩, ⟨⟩, hx⟩
rw [sigmaLift, dif_pos rfl, mem_map]
exact ⟨_, hx, by simp [Sigma.ext_iff]⟩
· rw [sigmaLift, dif_neg h]
refine iff_of_false (not_mem_empty _) ?_
rintro ⟨⟨⟩, ⟨⟩, _⟩
exact h rfl
#align finset.mem_sigma_lift Finset.mem_sigmaLift
theorem mk_mem_sigmaLift (f : ∀ ⦃i⦄, α i → β i → Finset (γ i)) (i : ι) (a : α i) (b : β i)
(x : γ i) : (⟨i, x⟩ : Sigma γ) ∈ sigmaLift f ⟨i, a⟩ ⟨i, b⟩ ↔ x ∈ f a b := by
rw [sigmaLift, dif_pos rfl, mem_map]
refine ⟨?_, fun hx => ⟨_, hx, rfl⟩⟩
rintro ⟨x, hx, _, rfl⟩
exact hx
#align finset.mk_mem_sigma_lift Finset.mk_mem_sigmaLift
theorem not_mem_sigmaLift_of_ne_left (f : ∀ ⦃i⦄, α i → β i → Finset (γ i)) (a : Sigma α)
(b : Sigma β) (x : Sigma γ) (h : a.1 ≠ x.1) : x ∉ sigmaLift f a b := by
rw [mem_sigmaLift]
exact fun H => h H.fst
#align finset.not_mem_sigma_lift_of_ne_left Finset.not_mem_sigmaLift_of_ne_left
theorem not_mem_sigmaLift_of_ne_right (f : ∀ ⦃i⦄, α i → β i → Finset (γ i)) {a : Sigma α}
(b : Sigma β) {x : Sigma γ} (h : b.1 ≠ x.1) : x ∉ sigmaLift f a b := by
rw [mem_sigmaLift]
exact fun H => h H.snd.fst
#align finset.not_mem_sigma_lift_of_ne_right Finset.not_mem_sigmaLift_of_ne_right
variable {f g : ∀ ⦃i⦄, α i → β i → Finset (γ i)} {a : Σi, α i} {b : Σi, β i}
theorem sigmaLift_nonempty :
(sigmaLift f a b).Nonempty ↔ ∃ h : a.1 = b.1, (f (h ▸ a.2) b.2).Nonempty := by
simp_rw [nonempty_iff_ne_empty, sigmaLift]
split_ifs with h <;> simp [h]
#align finset.sigma_lift_nonempty Finset.sigmaLift_nonempty
| Mathlib/Data/Finset/Sigma.lean | 204 | 208 | theorem sigmaLift_eq_empty : sigmaLift f a b = ∅ ↔ ∀ h : a.1 = b.1, f (h ▸ a.2) b.2 = ∅ := by |
simp_rw [sigmaLift]
split_ifs with h
· simp [h, forall_prop_of_true h]
· simp [h, forall_prop_of_false h]
|
/-
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.NumberTheory.BernoulliPolynomials
import Mathlib.MeasureTheory.Integral.IntervalIntegral
import Mathlib.Analysis.Calculus.Deriv.Polynomial
import Mathlib.Analysis.Fourier.AddCircle
import Mathlib.Analysis.PSeries
#align_import number_theory.zeta_values from "leanprover-community/mathlib"@"f0c8bf9245297a541f468be517f1bde6195105e9"
/-!
# Critical values of the Riemann zeta function
In this file we prove formulae for the critical values of `ζ(s)`, and more generally of Hurwitz
zeta functions, in terms of Bernoulli polynomials.
## Main results:
* `hasSum_zeta_nat`: the final formula for zeta values,
$$\zeta(2k) = \frac{(-1)^{(k + 1)} 2 ^ {2k - 1} \pi^{2k} B_{2 k}}{(2 k)!}.$$
* `hasSum_zeta_two` and `hasSum_zeta_four`: special cases given explicitly.
* `hasSum_one_div_nat_pow_mul_cos`: a formula for the sum `∑ (n : ℕ), cos (2 π i n x) / n ^ k` as
an explicit multiple of `Bₖ(x)`, for any `x ∈ [0, 1]` and `k ≥ 2` even.
* `hasSum_one_div_nat_pow_mul_sin`: a formula for the sum `∑ (n : ℕ), sin (2 π i n x) / n ^ k` as
an explicit multiple of `Bₖ(x)`, for any `x ∈ [0, 1]` and `k ≥ 3` odd.
-/
noncomputable section
open scoped Nat Real Interval
open Complex MeasureTheory Set intervalIntegral
local notation "𝕌" => UnitAddCircle
section BernoulliFunProps
/-! Simple properties of the Bernoulli polynomial, as a function `ℝ → ℝ`. -/
/-- The function `x ↦ Bₖ(x) : ℝ → ℝ`. -/
def bernoulliFun (k : ℕ) (x : ℝ) : ℝ :=
(Polynomial.map (algebraMap ℚ ℝ) (Polynomial.bernoulli k)).eval x
#align bernoulli_fun bernoulliFun
theorem bernoulliFun_eval_zero (k : ℕ) : bernoulliFun k 0 = bernoulli k := by
rw [bernoulliFun, Polynomial.eval_zero_map, Polynomial.bernoulli_eval_zero, eq_ratCast]
#align bernoulli_fun_eval_zero bernoulliFun_eval_zero
theorem bernoulliFun_endpoints_eq_of_ne_one {k : ℕ} (hk : k ≠ 1) :
bernoulliFun k 1 = bernoulliFun k 0 := by
rw [bernoulliFun_eval_zero, bernoulliFun, Polynomial.eval_one_map, Polynomial.bernoulli_eval_one,
bernoulli_eq_bernoulli'_of_ne_one hk, eq_ratCast]
#align bernoulli_fun_endpoints_eq_of_ne_one bernoulliFun_endpoints_eq_of_ne_one
theorem bernoulliFun_eval_one (k : ℕ) : bernoulliFun k 1 = bernoulliFun k 0 + ite (k = 1) 1 0 := by
rw [bernoulliFun, bernoulliFun_eval_zero, Polynomial.eval_one_map, Polynomial.bernoulli_eval_one]
split_ifs with h
· rw [h, bernoulli_one, bernoulli'_one, eq_ratCast]
push_cast; ring
· rw [bernoulli_eq_bernoulli'_of_ne_one h, add_zero, eq_ratCast]
#align bernoulli_fun_eval_one bernoulliFun_eval_one
theorem hasDerivAt_bernoulliFun (k : ℕ) (x : ℝ) :
HasDerivAt (bernoulliFun k) (k * bernoulliFun (k - 1) x) x := by
convert ((Polynomial.bernoulli k).map <| algebraMap ℚ ℝ).hasDerivAt x using 1
simp only [bernoulliFun, Polynomial.derivative_map, Polynomial.derivative_bernoulli k,
Polynomial.map_mul, Polynomial.map_natCast, Polynomial.eval_mul, Polynomial.eval_natCast]
#align has_deriv_at_bernoulli_fun hasDerivAt_bernoulliFun
theorem antideriv_bernoulliFun (k : ℕ) (x : ℝ) :
HasDerivAt (fun x => bernoulliFun (k + 1) x / (k + 1)) (bernoulliFun k x) x := by
convert (hasDerivAt_bernoulliFun (k + 1) x).div_const _ using 1
field_simp [Nat.cast_add_one_ne_zero k]
#align antideriv_bernoulli_fun antideriv_bernoulliFun
theorem integral_bernoulliFun_eq_zero {k : ℕ} (hk : k ≠ 0) :
∫ x : ℝ in (0)..1, bernoulliFun k x = 0 := by
rw [integral_eq_sub_of_hasDerivAt (fun x _ => antideriv_bernoulliFun k x)
((Polynomial.continuous _).intervalIntegrable _ _)]
rw [bernoulliFun_eval_one]
split_ifs with h
· exfalso; exact hk (Nat.succ_inj'.mp h)
· simp
#align integral_bernoulli_fun_eq_zero integral_bernoulliFun_eq_zero
end BernoulliFunProps
section BernoulliFourierCoeffs
/-! Compute the Fourier coefficients of the Bernoulli functions via integration by parts. -/
/-- The `n`-th Fourier coefficient of the `k`-th Bernoulli function on the interval `[0, 1]`. -/
def bernoulliFourierCoeff (k : ℕ) (n : ℤ) : ℂ :=
fourierCoeffOn zero_lt_one (fun x => bernoulliFun k x) n
#align bernoulli_fourier_coeff bernoulliFourierCoeff
/-- Recurrence relation (in `k`) for the `n`-th Fourier coefficient of `Bₖ`. -/
theorem bernoulliFourierCoeff_recurrence (k : ℕ) {n : ℤ} (hn : n ≠ 0) :
bernoulliFourierCoeff k n =
1 / (-2 * π * I * n) * (ite (k = 1) 1 0 - k * bernoulliFourierCoeff (k - 1) n) := by
unfold bernoulliFourierCoeff
rw [fourierCoeffOn_of_hasDerivAt zero_lt_one hn
(fun x _ => (hasDerivAt_bernoulliFun k x).ofReal_comp)
((continuous_ofReal.comp <|
continuous_const.mul <| Polynomial.continuous _).intervalIntegrable
_ _)]
simp_rw [ofReal_one, ofReal_zero, sub_zero, one_mul]
rw [QuotientAddGroup.mk_zero, fourier_eval_zero, one_mul, ← ofReal_sub, bernoulliFun_eval_one,
add_sub_cancel_left]
congr 2
· split_ifs <;> simp only [ofReal_one, ofReal_zero, one_mul]
· simp_rw [ofReal_mul, ofReal_natCast, fourierCoeffOn.const_mul]
#align bernoulli_fourier_coeff_recurrence bernoulliFourierCoeff_recurrence
/-- The Fourier coefficients of `B₀(x) = 1`. -/
| Mathlib/NumberTheory/ZetaValues.lean | 121 | 122 | theorem bernoulli_zero_fourier_coeff {n : ℤ} (hn : n ≠ 0) : bernoulliFourierCoeff 0 n = 0 := by |
simpa using bernoulliFourierCoeff_recurrence 0 hn
|
/-
Copyright (c) 2022 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.MeasureTheory.Function.ConvergenceInMeasure
import Mathlib.MeasureTheory.Function.L1Space
#align_import measure_theory.function.uniform_integrable from "leanprover-community/mathlib"@"57ac39bd365c2f80589a700f9fbb664d3a1a30c2"
/-!
# Uniform integrability
This file contains the definitions for uniform integrability (both in the measure theory sense
as well as the probability theory sense). This file also contains the Vitali convergence theorem
which establishes a relation between uniform integrability, convergence in measure and
Lp convergence.
Uniform integrability plays a vital role in the theory of martingales most notably is used to
formulate the martingale convergence theorem.
## Main definitions
* `MeasureTheory.UnifIntegrable`: uniform integrability in the measure theory sense.
In particular, a sequence of functions `f` is uniformly integrable if for all `ε > 0`, there
exists some `δ > 0` such that for all sets `s` of smaller measure than `δ`, the Lp-norm of
`f i` restricted `s` is smaller than `ε` for all `i`.
* `MeasureTheory.UniformIntegrable`: uniform integrability in the probability theory sense.
In particular, a sequence of measurable functions `f` is uniformly integrable in the
probability theory sense if it is uniformly integrable in the measure theory sense and
has uniformly bounded Lp-norm.
# Main results
* `MeasureTheory.unifIntegrable_finite`: a finite sequence of Lp functions is uniformly
integrable.
* `MeasureTheory.tendsto_Lp_of_tendsto_ae`: a sequence of Lp functions which is uniformly
integrable converges in Lp if they converge almost everywhere.
* `MeasureTheory.tendstoInMeasure_iff_tendsto_Lp`: Vitali convergence theorem:
a sequence of Lp functions converges in Lp if and only if it is uniformly integrable
and converges in measure.
## Tags
uniform integrable, uniformly absolutely continuous integral, Vitali convergence theorem
-/
noncomputable section
open scoped Classical MeasureTheory NNReal ENNReal Topology
namespace MeasureTheory
open Set Filter TopologicalSpace
variable {α β ι : Type*} {m : MeasurableSpace α} {μ : Measure α} [NormedAddCommGroup β]
/-- Uniform integrability in the measure theory sense.
A sequence of functions `f` is said to be uniformly integrable if for all `ε > 0`, there exists
some `δ > 0` such that for all sets `s` with measure less than `δ`, the Lp-norm of `f i`
restricted on `s` is less than `ε`.
Uniform integrability is also known as uniformly absolutely continuous integrals. -/
def UnifIntegrable {_ : MeasurableSpace α} (f : ι → α → β) (p : ℝ≥0∞) (μ : Measure α) : Prop :=
∀ ⦃ε : ℝ⦄ (_ : 0 < ε), ∃ (δ : ℝ) (_ : 0 < δ), ∀ i s,
MeasurableSet s → μ s ≤ ENNReal.ofReal δ → snorm (s.indicator (f i)) p μ ≤ ENNReal.ofReal ε
#align measure_theory.unif_integrable MeasureTheory.UnifIntegrable
/-- In probability theory, a family of measurable functions is uniformly integrable if it is
uniformly integrable in the measure theory sense and is uniformly bounded. -/
def UniformIntegrable {_ : MeasurableSpace α} (f : ι → α → β) (p : ℝ≥0∞) (μ : Measure α) : Prop :=
(∀ i, AEStronglyMeasurable (f i) μ) ∧ UnifIntegrable f p μ ∧ ∃ C : ℝ≥0, ∀ i, snorm (f i) p μ ≤ C
#align measure_theory.uniform_integrable MeasureTheory.UniformIntegrable
namespace UniformIntegrable
protected theorem aeStronglyMeasurable {f : ι → α → β} {p : ℝ≥0∞} (hf : UniformIntegrable f p μ)
(i : ι) : AEStronglyMeasurable (f i) μ :=
hf.1 i
#align measure_theory.uniform_integrable.ae_strongly_measurable MeasureTheory.UniformIntegrable.aeStronglyMeasurable
protected theorem unifIntegrable {f : ι → α → β} {p : ℝ≥0∞} (hf : UniformIntegrable f p μ) :
UnifIntegrable f p μ :=
hf.2.1
#align measure_theory.uniform_integrable.unif_integrable MeasureTheory.UniformIntegrable.unifIntegrable
protected theorem memℒp {f : ι → α → β} {p : ℝ≥0∞} (hf : UniformIntegrable f p μ) (i : ι) :
Memℒp (f i) p μ :=
⟨hf.1 i,
let ⟨_, _, hC⟩ := hf.2
lt_of_le_of_lt (hC i) ENNReal.coe_lt_top⟩
#align measure_theory.uniform_integrable.mem_ℒp MeasureTheory.UniformIntegrable.memℒp
end UniformIntegrable
section UnifIntegrable
/-! ### `UnifIntegrable`
This section deals with uniform integrability in the measure theory sense. -/
namespace UnifIntegrable
variable {f g : ι → α → β} {p : ℝ≥0∞}
protected theorem add (hf : UnifIntegrable f p μ) (hg : UnifIntegrable g p μ) (hp : 1 ≤ p)
(hf_meas : ∀ i, AEStronglyMeasurable (f i) μ) (hg_meas : ∀ i, AEStronglyMeasurable (g i) μ) :
UnifIntegrable (f + g) p μ := by
intro ε hε
have hε2 : 0 < ε / 2 := half_pos hε
obtain ⟨δ₁, hδ₁_pos, hfδ₁⟩ := hf hε2
obtain ⟨δ₂, hδ₂_pos, hgδ₂⟩ := hg hε2
refine ⟨min δ₁ δ₂, lt_min hδ₁_pos hδ₂_pos, fun i s hs hμs => ?_⟩
simp_rw [Pi.add_apply, Set.indicator_add']
refine (snorm_add_le ((hf_meas i).indicator hs) ((hg_meas i).indicator hs) hp).trans ?_
have hε_halves : ENNReal.ofReal ε = ENNReal.ofReal (ε / 2) + ENNReal.ofReal (ε / 2) := by
rw [← ENNReal.ofReal_add hε2.le hε2.le, add_halves]
rw [hε_halves]
exact add_le_add (hfδ₁ i s hs (hμs.trans (ENNReal.ofReal_le_ofReal (min_le_left _ _))))
(hgδ₂ i s hs (hμs.trans (ENNReal.ofReal_le_ofReal (min_le_right _ _))))
#align measure_theory.unif_integrable.add MeasureTheory.UnifIntegrable.add
protected theorem neg (hf : UnifIntegrable f p μ) : UnifIntegrable (-f) p μ := by
simp_rw [UnifIntegrable, Pi.neg_apply, Set.indicator_neg', snorm_neg]
exact hf
#align measure_theory.unif_integrable.neg MeasureTheory.UnifIntegrable.neg
protected theorem sub (hf : UnifIntegrable f p μ) (hg : UnifIntegrable g p μ) (hp : 1 ≤ p)
(hf_meas : ∀ i, AEStronglyMeasurable (f i) μ) (hg_meas : ∀ i, AEStronglyMeasurable (g i) μ) :
UnifIntegrable (f - g) p μ := by
rw [sub_eq_add_neg]
exact hf.add hg.neg hp hf_meas fun i => (hg_meas i).neg
#align measure_theory.unif_integrable.sub MeasureTheory.UnifIntegrable.sub
protected theorem ae_eq (hf : UnifIntegrable f p μ) (hfg : ∀ n, f n =ᵐ[μ] g n) :
UnifIntegrable g p μ := by
intro ε hε
obtain ⟨δ, hδ_pos, hfδ⟩ := hf hε
refine ⟨δ, hδ_pos, fun n s hs hμs => (le_of_eq <| snorm_congr_ae ?_).trans (hfδ n s hs hμs)⟩
filter_upwards [hfg n] with x hx
simp_rw [Set.indicator_apply, hx]
#align measure_theory.unif_integrable.ae_eq MeasureTheory.UnifIntegrable.ae_eq
end UnifIntegrable
theorem unifIntegrable_zero_meas [MeasurableSpace α] {p : ℝ≥0∞} {f : ι → α → β} :
UnifIntegrable f p (0 : Measure α) :=
fun ε _ => ⟨1, one_pos, fun i s _ _ => by simp⟩
#align measure_theory.unif_integrable_zero_meas MeasureTheory.unifIntegrable_zero_meas
theorem unifIntegrable_congr_ae {p : ℝ≥0∞} {f g : ι → α → β} (hfg : ∀ n, f n =ᵐ[μ] g n) :
UnifIntegrable f p μ ↔ UnifIntegrable g p μ :=
⟨fun hf => hf.ae_eq hfg, fun hg => hg.ae_eq fun n => (hfg n).symm⟩
#align measure_theory.unif_integrable_congr_ae MeasureTheory.unifIntegrable_congr_ae
theorem tendsto_indicator_ge (f : α → β) (x : α) :
Tendsto (fun M : ℕ => { x | (M : ℝ) ≤ ‖f x‖₊ }.indicator f x) atTop (𝓝 0) := by
refine tendsto_atTop_of_eventually_const (i₀ := Nat.ceil (‖f x‖₊ : ℝ) + 1) fun n hn => ?_
rw [Set.indicator_of_not_mem]
simp only [not_le, Set.mem_setOf_eq]
refine lt_of_le_of_lt (Nat.le_ceil _) ?_
refine lt_of_lt_of_le (lt_add_one _) ?_
norm_cast
#align measure_theory.tendsto_indicator_ge MeasureTheory.tendsto_indicator_ge
variable {p : ℝ≥0∞}
section
variable {f : α → β}
/-- This lemma is weaker than `MeasureTheory.Memℒp.integral_indicator_norm_ge_nonneg_le`
as the latter provides `0 ≤ M` and does not require the measurability of `f`. -/
theorem Memℒp.integral_indicator_norm_ge_le (hf : Memℒp f 1 μ) (hmeas : StronglyMeasurable f)
{ε : ℝ} (hε : 0 < ε) :
∃ M : ℝ, (∫⁻ x, ‖{ x | M ≤ ‖f x‖₊ }.indicator f x‖₊ ∂μ) ≤ ENNReal.ofReal ε := by
have htendsto :
∀ᵐ x ∂μ, Tendsto (fun M : ℕ => { x | (M : ℝ) ≤ ‖f x‖₊ }.indicator f x) atTop (𝓝 0) :=
univ_mem' (id fun x => tendsto_indicator_ge f x)
have hmeas : ∀ M : ℕ, AEStronglyMeasurable ({ x | (M : ℝ) ≤ ‖f x‖₊ }.indicator f) μ := by
intro M
apply hf.1.indicator
apply StronglyMeasurable.measurableSet_le stronglyMeasurable_const
hmeas.nnnorm.measurable.coe_nnreal_real.stronglyMeasurable
have hbound : HasFiniteIntegral (fun x => ‖f x‖) μ := by
rw [memℒp_one_iff_integrable] at hf
exact hf.norm.2
have : Tendsto (fun n : ℕ ↦ ∫⁻ a, ENNReal.ofReal ‖{ x | n ≤ ‖f x‖₊ }.indicator f a - 0‖ ∂μ)
atTop (𝓝 0) := by
refine tendsto_lintegral_norm_of_dominated_convergence hmeas hbound ?_ htendsto
refine fun n => univ_mem' (id fun x => ?_)
by_cases hx : (n : ℝ) ≤ ‖f x‖
· dsimp
rwa [Set.indicator_of_mem]
· dsimp
rw [Set.indicator_of_not_mem, norm_zero]
· exact norm_nonneg _
· assumption
rw [ENNReal.tendsto_atTop_zero] at this
obtain ⟨M, hM⟩ := this (ENNReal.ofReal ε) (ENNReal.ofReal_pos.2 hε)
simp only [true_and_iff, ge_iff_le, zero_tsub, zero_le, sub_zero, zero_add, coe_nnnorm,
Set.mem_Icc] at hM
refine ⟨M, ?_⟩
convert hM M le_rfl
simp only [coe_nnnorm, ENNReal.ofReal_eq_coe_nnreal (norm_nonneg _)]
rfl
#align measure_theory.mem_ℒp.integral_indicator_norm_ge_le MeasureTheory.Memℒp.integral_indicator_norm_ge_le
/-- This lemma is superceded by `MeasureTheory.Memℒp.integral_indicator_norm_ge_nonneg_le`
which does not require measurability. -/
theorem Memℒp.integral_indicator_norm_ge_nonneg_le_of_meas (hf : Memℒp f 1 μ)
(hmeas : StronglyMeasurable f) {ε : ℝ} (hε : 0 < ε) :
∃ M : ℝ, 0 ≤ M ∧ (∫⁻ x, ‖{ x | M ≤ ‖f x‖₊ }.indicator f x‖₊ ∂μ) ≤ ENNReal.ofReal ε :=
let ⟨M, hM⟩ := hf.integral_indicator_norm_ge_le hmeas hε
⟨max M 0, le_max_right _ _, by simpa⟩
#align measure_theory.mem_ℒp.integral_indicator_norm_ge_nonneg_le_of_meas MeasureTheory.Memℒp.integral_indicator_norm_ge_nonneg_le_of_meas
| Mathlib/MeasureTheory/Function/UniformIntegrable.lean | 220 | 228 | theorem Memℒp.integral_indicator_norm_ge_nonneg_le (hf : Memℒp f 1 μ) {ε : ℝ} (hε : 0 < ε) :
∃ M : ℝ, 0 ≤ M ∧ (∫⁻ x, ‖{ x | M ≤ ‖f x‖₊ }.indicator f x‖₊ ∂μ) ≤ ENNReal.ofReal ε := by |
have hf_mk : Memℒp (hf.1.mk f) 1 μ := (memℒp_congr_ae hf.1.ae_eq_mk).mp hf
obtain ⟨M, hM_pos, hfM⟩ :=
hf_mk.integral_indicator_norm_ge_nonneg_le_of_meas hf.1.stronglyMeasurable_mk hε
refine ⟨M, hM_pos, (le_of_eq ?_).trans hfM⟩
refine lintegral_congr_ae ?_
filter_upwards [hf.1.ae_eq_mk] with x hx
simp only [Set.indicator_apply, coe_nnnorm, Set.mem_setOf_eq, ENNReal.coe_inj, hx.symm]
|
/-
Copyright (c) 2022 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa
-/
import Mathlib.Data.DFinsupp.Basic
import Mathlib.Data.Finset.Pointwise
import Mathlib.LinearAlgebra.Basis.VectorSpace
#align_import algebra.group.unique_prods from "leanprover-community/mathlib"@"d6fad0e5bf2d6f48da9175d25c3dc5706b3834ce"
/-!
# Unique products and related notions
A group `G` has *unique products* if for any two non-empty finite subsets `A, B ⊆ G`, there is an
element `g ∈ A * B` that can be written uniquely as a product of an element of `A` and an element
of `B`. We call the formalization this property `UniqueProds`. Since the condition requires no
property of the group operation, we define it for a Type simply satisfying `Mul`. We also
introduce the analogous "additive" companion, `UniqueSums`, and link the two so that `to_additive`
converts `UniqueProds` into `UniqueSums`.
A common way of *proving* that a group satisfies the `UniqueProds/Sums` property is by assuming
the existence of some kind of ordering on the group that is well-behaved with respect to the
group operation and showing that minima/maxima are the "unique products/sums".
However, the order is just a convenience and is not part of the `UniqueProds/Sums` setup.
Here you can see several examples of Types that have `UniqueSums/Prods`
(`inferInstance` uses `Covariant.to_uniqueProds_left` and `Covariant.to_uniqueSums_left`).
```lean
import Mathlib.Data.Real.Basic
import Mathlib.Data.PNat.Basic
import Mathlib.Algebra.Group.UniqueProds
example : UniqueSums ℕ := inferInstance
example : UniqueSums ℕ+ := inferInstance
example : UniqueSums ℤ := inferInstance
example : UniqueSums ℚ := inferInstance
example : UniqueSums ℝ := inferInstance
example : UniqueProds ℕ+ := inferInstance
```
## Use in `(Add)MonoidAlgebra`s
`UniqueProds/Sums` allow to decouple certain arguments about `(Add)MonoidAlgebra`s into an argument
about the grading type and then a generic statement of the form "look at the coefficient of the
'unique product/sum'".
The file `Algebra/MonoidAlgebra/NoZeroDivisors` contains several examples of this use.
-/
/-- Let `G` be a Type with multiplication, let `A B : Finset G` be finite subsets and
let `a0 b0 : G` be two elements. `UniqueMul A B a0 b0` asserts `a0 * b0` can be written in at
most one way as a product of an element of `A` and an element of `B`. -/
@[to_additive
"Let `G` be a Type with addition, let `A B : Finset G` be finite subsets and
let `a0 b0 : G` be two elements. `UniqueAdd A B a0 b0` asserts `a0 + b0` can be written in at
most one way as a sum of an element from `A` and an element from `B`."]
def UniqueMul {G} [Mul G] (A B : Finset G) (a0 b0 : G) : Prop :=
∀ ⦃a b⦄, a ∈ A → b ∈ B → a * b = a0 * b0 → a = a0 ∧ b = b0
#align unique_mul UniqueMul
#align unique_add UniqueAdd
namespace UniqueMul
variable {G H : Type*} [Mul G] [Mul H] {A B : Finset G} {a0 b0 : G}
@[to_additive (attr := nontriviality, simp)]
theorem of_subsingleton [Subsingleton G] : UniqueMul A B a0 b0 := by
simp [UniqueMul, eq_iff_true_of_subsingleton]
@[to_additive]
| Mathlib/Algebra/Group/UniqueProds.lean | 71 | 75 | theorem of_card_le_one (hA : A.Nonempty) (hB : B.Nonempty) (hA1 : A.card ≤ 1) (hB1 : B.card ≤ 1) :
∃ a ∈ A, ∃ b ∈ B, UniqueMul A B a b := by |
rw [Finset.card_le_one_iff] at hA1 hB1
obtain ⟨a, ha⟩ := hA; obtain ⟨b, hb⟩ := hB
exact ⟨a, ha, b, hb, fun _ _ ha' hb' _ ↦ ⟨hA1 ha' ha, hB1 hb' hb⟩⟩
|
/-
Copyright (c) 2022 Jake Levinson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jake Levinson
-/
import Mathlib.Order.UpperLower.Basic
import Mathlib.Data.Finset.Preimage
#align_import combinatorics.young.young_diagram from "leanprover-community/mathlib"@"59694bd07f0a39c5beccba34bd9f413a160782bf"
/-!
# Young diagrams
A Young diagram is a finite set of up-left justified boxes:
```text
□□□□□
□□□
□□□
□
```
This Young diagram corresponds to the [5, 3, 3, 1] partition of 12.
We represent it as a lower set in `ℕ × ℕ` in the product partial order. We write `(i, j) ∈ μ`
to say that `(i, j)` (in matrix coordinates) is in the Young diagram `μ`.
## Main definitions
- `YoungDiagram` : Young diagrams
- `YoungDiagram.card` : the number of cells in a Young diagram (its *cardinality*)
- `YoungDiagram.instDistribLatticeYoungDiagram` : a distributive lattice instance for Young diagrams
ordered by containment, with `(⊥ : YoungDiagram)` the empty diagram.
- `YoungDiagram.row` and `YoungDiagram.rowLen`: rows of a Young diagram and their lengths
- `YoungDiagram.col` and `YoungDiagram.colLen`: columns of a Young diagram and their lengths
## Notation
In "English notation", a Young diagram is drawn so that (i1, j1) ≤ (i2, j2)
means (i1, j1) is weakly up-and-left of (i2, j2). This terminology is used
below, e.g. in `YoungDiagram.up_left_mem`.
## Tags
Young diagram
## References
<https://en.wikipedia.org/wiki/Young_tableau>
-/
open Function
/-- A Young diagram is a finite collection of cells on the `ℕ × ℕ` grid such that whenever
a cell is present, so are all the ones above and to the left of it. Like matrices, an `(i, j)` cell
is a cell in row `i` and column `j`, where rows are enumerated downward and columns rightward.
Young diagrams are modeled as finite sets in `ℕ × ℕ` that are lower sets with respect to the
standard order on products. -/
@[ext]
structure YoungDiagram where
/-- A finite set which represents a finite collection of cells on the `ℕ × ℕ` grid. -/
cells : Finset (ℕ × ℕ)
/-- Cells are up-left justified, witnessed by the fact that `cells` is a lower set in `ℕ × ℕ`. -/
isLowerSet : IsLowerSet (cells : Set (ℕ × ℕ))
#align young_diagram YoungDiagram
namespace YoungDiagram
instance : SetLike YoungDiagram (ℕ × ℕ) where
-- Porting note (#11215): TODO: figure out how to do this correctly
coe := fun y => y.cells
coe_injective' μ ν h := by rwa [YoungDiagram.ext_iff, ← Finset.coe_inj]
@[simp]
theorem mem_cells {μ : YoungDiagram} (c : ℕ × ℕ) : c ∈ μ.cells ↔ c ∈ μ :=
Iff.rfl
#align young_diagram.mem_cells YoungDiagram.mem_cells
@[simp]
theorem mem_mk (c : ℕ × ℕ) (cells) (isLowerSet) :
c ∈ YoungDiagram.mk cells isLowerSet ↔ c ∈ cells :=
Iff.rfl
#align young_diagram.mem_mk YoungDiagram.mem_mk
instance decidableMem (μ : YoungDiagram) : DecidablePred (· ∈ μ) :=
inferInstanceAs (DecidablePred (· ∈ μ.cells))
#align young_diagram.decidable_mem YoungDiagram.decidableMem
/-- In "English notation", a Young diagram is drawn so that (i1, j1) ≤ (i2, j2)
means (i1, j1) is weakly up-and-left of (i2, j2). -/
theorem up_left_mem (μ : YoungDiagram) {i1 i2 j1 j2 : ℕ} (hi : i1 ≤ i2) (hj : j1 ≤ j2)
(hcell : (i2, j2) ∈ μ) : (i1, j1) ∈ μ :=
μ.isLowerSet (Prod.mk_le_mk.mpr ⟨hi, hj⟩) hcell
#align young_diagram.up_left_mem YoungDiagram.up_left_mem
section DistribLattice
@[simp]
theorem cells_subset_iff {μ ν : YoungDiagram} : μ.cells ⊆ ν.cells ↔ μ ≤ ν :=
Iff.rfl
#align young_diagram.cells_subset_iff YoungDiagram.cells_subset_iff
@[simp]
theorem cells_ssubset_iff {μ ν : YoungDiagram} : μ.cells ⊂ ν.cells ↔ μ < ν :=
Iff.rfl
#align young_diagram.cells_ssubset_iff YoungDiagram.cells_ssubset_iff
instance : Sup YoungDiagram where
sup μ ν :=
{ cells := μ.cells ∪ ν.cells
isLowerSet := by
rw [Finset.coe_union]
exact μ.isLowerSet.union ν.isLowerSet }
@[simp]
theorem cells_sup (μ ν : YoungDiagram) : (μ ⊔ ν).cells = μ.cells ∪ ν.cells :=
rfl
#align young_diagram.cells_sup YoungDiagram.cells_sup
@[simp, norm_cast]
theorem coe_sup (μ ν : YoungDiagram) : ↑(μ ⊔ ν) = (μ ∪ ν : Set (ℕ × ℕ)) :=
Finset.coe_union _ _
#align young_diagram.coe_sup YoungDiagram.coe_sup
@[simp]
theorem mem_sup {μ ν : YoungDiagram} {x : ℕ × ℕ} : x ∈ μ ⊔ ν ↔ x ∈ μ ∨ x ∈ ν :=
Finset.mem_union
#align young_diagram.mem_sup YoungDiagram.mem_sup
instance : Inf YoungDiagram where
inf μ ν :=
{ cells := μ.cells ∩ ν.cells
isLowerSet := by
rw [Finset.coe_inter]
exact μ.isLowerSet.inter ν.isLowerSet }
@[simp]
theorem cells_inf (μ ν : YoungDiagram) : (μ ⊓ ν).cells = μ.cells ∩ ν.cells :=
rfl
#align young_diagram.cells_inf YoungDiagram.cells_inf
@[simp, norm_cast]
theorem coe_inf (μ ν : YoungDiagram) : ↑(μ ⊓ ν) = (μ ∩ ν : Set (ℕ × ℕ)) :=
Finset.coe_inter _ _
#align young_diagram.coe_inf YoungDiagram.coe_inf
@[simp]
theorem mem_inf {μ ν : YoungDiagram} {x : ℕ × ℕ} : x ∈ μ ⊓ ν ↔ x ∈ μ ∧ x ∈ ν :=
Finset.mem_inter
#align young_diagram.mem_inf YoungDiagram.mem_inf
/-- The empty Young diagram is (⊥ : young_diagram). -/
instance : OrderBot YoungDiagram where
bot :=
{ cells := ∅
isLowerSet := by
intros a b _ h
simp only [Finset.coe_empty, Set.mem_empty_iff_false]
simp only [Finset.coe_empty, Set.mem_empty_iff_false] at h }
bot_le _ _ := by
intro y
simp only [mem_mk, Finset.not_mem_empty] at y
@[simp]
theorem cells_bot : (⊥ : YoungDiagram).cells = ∅ :=
rfl
#align young_diagram.cells_bot YoungDiagram.cells_bot
-- Porting note: removed `↑`, added `.cells` and changed proof
-- @[simp] -- Porting note (#10618): simp can prove this
@[norm_cast]
theorem coe_bot : (⊥ : YoungDiagram).cells = (∅ : Set (ℕ × ℕ)) := by
refine Set.eq_of_subset_of_subset ?_ ?_
· intros x h
simp? [mem_mk, Finset.coe_empty, Set.mem_empty_iff_false] at h says
simp only [cells_bot, Finset.coe_empty, Set.mem_empty_iff_false] at h
· simp only [cells_bot, Finset.coe_empty, Set.empty_subset]
#align young_diagram.coe_bot YoungDiagram.coe_bot
@[simp]
theorem not_mem_bot (x : ℕ × ℕ) : x ∉ (⊥ : YoungDiagram) :=
Finset.not_mem_empty x
#align young_diagram.not_mem_bot YoungDiagram.not_mem_bot
instance : Inhabited YoungDiagram :=
⟨⊥⟩
instance : DistribLattice YoungDiagram :=
Function.Injective.distribLattice YoungDiagram.cells (fun μ ν h => by rwa [YoungDiagram.ext_iff])
(fun _ _ => rfl) fun _ _ => rfl
end DistribLattice
/-- Cardinality of a Young diagram -/
protected abbrev card (μ : YoungDiagram) : ℕ :=
μ.cells.card
#align young_diagram.card YoungDiagram.card
section Transpose
/-- The `transpose` of a Young diagram is obtained by swapping i's with j's. -/
def transpose (μ : YoungDiagram) : YoungDiagram where
cells := (Equiv.prodComm _ _).finsetCongr μ.cells
isLowerSet _ _ h := by
simp only [Finset.mem_coe, Equiv.finsetCongr_apply, Finset.mem_map_equiv]
intro hcell
apply μ.isLowerSet _ hcell
simp [h]
#align young_diagram.transpose YoungDiagram.transpose
@[simp]
theorem mem_transpose {μ : YoungDiagram} {c : ℕ × ℕ} : c ∈ μ.transpose ↔ c.swap ∈ μ := by
simp [transpose]
#align young_diagram.mem_transpose YoungDiagram.mem_transpose
@[simp]
theorem transpose_transpose (μ : YoungDiagram) : μ.transpose.transpose = μ := by
ext x
simp
#align young_diagram.transpose_transpose YoungDiagram.transpose_transpose
theorem transpose_eq_iff_eq_transpose {μ ν : YoungDiagram} : μ.transpose = ν ↔ μ = ν.transpose := by
constructor <;>
· rintro rfl
simp
#align young_diagram.transpose_eq_iff_eq_transpose YoungDiagram.transpose_eq_iff_eq_transpose
@[simp]
theorem transpose_eq_iff {μ ν : YoungDiagram} : μ.transpose = ν.transpose ↔ μ = ν := by
rw [transpose_eq_iff_eq_transpose]
simp
#align young_diagram.transpose_eq_iff YoungDiagram.transpose_eq_iff
-- This is effectively both directions of `transpose_le_iff` below.
protected theorem le_of_transpose_le {μ ν : YoungDiagram} (h_le : μ.transpose ≤ ν) :
μ ≤ ν.transpose := fun c hc => by
simp only [mem_cells, mem_transpose]
apply h_le
simpa
#align young_diagram.le_of_transpose_le YoungDiagram.le_of_transpose_le
@[simp]
theorem transpose_le_iff {μ ν : YoungDiagram} : μ.transpose ≤ ν.transpose ↔ μ ≤ ν :=
⟨fun h => by
convert YoungDiagram.le_of_transpose_le h
simp, fun h => by
rw [← transpose_transpose μ] at h
exact YoungDiagram.le_of_transpose_le h ⟩
#align young_diagram.transpose_le_iff YoungDiagram.transpose_le_iff
@[mono]
protected theorem transpose_mono {μ ν : YoungDiagram} (h_le : μ ≤ ν) : μ.transpose ≤ ν.transpose :=
transpose_le_iff.mpr h_le
#align young_diagram.transpose_mono YoungDiagram.transpose_mono
/-- Transposing Young diagrams is an `OrderIso`. -/
@[simps]
def transposeOrderIso : YoungDiagram ≃o YoungDiagram :=
⟨⟨transpose, transpose, fun _ => by simp, fun _ => by simp⟩, by simp⟩
#align young_diagram.transpose_order_iso YoungDiagram.transposeOrderIso
end Transpose
section Rows
/-! ### Rows and row lengths of Young diagrams.
This section defines `μ.row` and `μ.rowLen`, with the following API:
1. `(i, j) ∈ μ ↔ j < μ.rowLen i`
2. `μ.row i = {i} ×ˢ (Finset.range (μ.rowLen i))`
3. `μ.rowLen i = (μ.row i).card`
4. `∀ {i1 i2}, i1 ≤ i2 → μ.rowLen i2 ≤ μ.rowLen i1`
Note: #3 is not convenient for defining `μ.rowLen`; instead, `μ.rowLen` is defined
as the smallest `j` such that `(i, j) ∉ μ`. -/
/-- The `i`-th row of a Young diagram consists of the cells whose first coordinate is `i`. -/
def row (μ : YoungDiagram) (i : ℕ) : Finset (ℕ × ℕ) :=
μ.cells.filter fun c => c.fst = i
#align young_diagram.row YoungDiagram.row
theorem mem_row_iff {μ : YoungDiagram} {i : ℕ} {c : ℕ × ℕ} : c ∈ μ.row i ↔ c ∈ μ ∧ c.fst = i := by
simp [row]
#align young_diagram.mem_row_iff YoungDiagram.mem_row_iff
theorem mk_mem_row_iff {μ : YoungDiagram} {i j : ℕ} : (i, j) ∈ μ.row i ↔ (i, j) ∈ μ := by simp [row]
#align young_diagram.mk_mem_row_iff YoungDiagram.mk_mem_row_iff
protected theorem exists_not_mem_row (μ : YoungDiagram) (i : ℕ) : ∃ j, (i, j) ∉ μ := by
obtain ⟨j, hj⟩ :=
Infinite.exists_not_mem_finset
(μ.cells.preimage (Prod.mk i) fun _ _ _ _ h => by
cases h
rfl)
rw [Finset.mem_preimage] at hj
exact ⟨j, hj⟩
#align young_diagram.exists_not_mem_row YoungDiagram.exists_not_mem_row
/-- Length of a row of a Young diagram -/
def rowLen (μ : YoungDiagram) (i : ℕ) : ℕ :=
Nat.find <| μ.exists_not_mem_row i
#align young_diagram.row_len YoungDiagram.rowLen
theorem mem_iff_lt_rowLen {μ : YoungDiagram} {i j : ℕ} : (i, j) ∈ μ ↔ j < μ.rowLen i := by
rw [rowLen, Nat.lt_find_iff]
push_neg
exact ⟨fun h _ hmj => μ.up_left_mem (by rfl) hmj h, fun h => h _ (by rfl)⟩
#align young_diagram.mem_iff_lt_row_len YoungDiagram.mem_iff_lt_rowLen
theorem row_eq_prod {μ : YoungDiagram} {i : ℕ} : μ.row i = {i} ×ˢ Finset.range (μ.rowLen i) := by
ext ⟨a, b⟩
simp only [Finset.mem_product, Finset.mem_singleton, Finset.mem_range, mem_row_iff,
mem_iff_lt_rowLen, and_comm, and_congr_right_iff]
rintro rfl
rfl
#align young_diagram.row_eq_prod YoungDiagram.row_eq_prod
theorem rowLen_eq_card (μ : YoungDiagram) {i : ℕ} : μ.rowLen i = (μ.row i).card := by
simp [row_eq_prod]
#align young_diagram.row_len_eq_card YoungDiagram.rowLen_eq_card
@[mono]
theorem rowLen_anti (μ : YoungDiagram) (i1 i2 : ℕ) (hi : i1 ≤ i2) : μ.rowLen i2 ≤ μ.rowLen i1 := by
by_contra! h_lt
rw [← lt_self_iff_false (μ.rowLen i1)]
rw [← mem_iff_lt_rowLen] at h_lt ⊢
exact μ.up_left_mem hi (by rfl) h_lt
#align young_diagram.row_len_anti YoungDiagram.rowLen_anti
end Rows
section Columns
/-! ### Columns and column lengths of Young diagrams.
This section has an identical API to the rows section. -/
/-- The `j`-th column of a Young diagram consists of the cells whose second coordinate is `j`. -/
def col (μ : YoungDiagram) (j : ℕ) : Finset (ℕ × ℕ) :=
μ.cells.filter fun c => c.snd = j
#align young_diagram.col YoungDiagram.col
theorem mem_col_iff {μ : YoungDiagram} {j : ℕ} {c : ℕ × ℕ} : c ∈ μ.col j ↔ c ∈ μ ∧ c.snd = j := by
simp [col]
#align young_diagram.mem_col_iff YoungDiagram.mem_col_iff
theorem mk_mem_col_iff {μ : YoungDiagram} {i j : ℕ} : (i, j) ∈ μ.col j ↔ (i, j) ∈ μ := by simp [col]
#align young_diagram.mk_mem_col_iff YoungDiagram.mk_mem_col_iff
protected theorem exists_not_mem_col (μ : YoungDiagram) (j : ℕ) : ∃ i, (i, j) ∉ μ.cells := by
convert μ.transpose.exists_not_mem_row j using 1
simp
#align young_diagram.exists_not_mem_col YoungDiagram.exists_not_mem_col
/-- Length of a column of a Young diagram -/
def colLen (μ : YoungDiagram) (j : ℕ) : ℕ :=
Nat.find <| μ.exists_not_mem_col j
#align young_diagram.col_len YoungDiagram.colLen
@[simp]
theorem colLen_transpose (μ : YoungDiagram) (j : ℕ) : μ.transpose.colLen j = μ.rowLen j := by
simp [rowLen, colLen]
#align young_diagram.col_len_transpose YoungDiagram.colLen_transpose
@[simp]
theorem rowLen_transpose (μ : YoungDiagram) (i : ℕ) : μ.transpose.rowLen i = μ.colLen i := by
simp [rowLen, colLen]
#align young_diagram.row_len_transpose YoungDiagram.rowLen_transpose
theorem mem_iff_lt_colLen {μ : YoungDiagram} {i j : ℕ} : (i, j) ∈ μ ↔ i < μ.colLen j := by
rw [← rowLen_transpose, ← mem_iff_lt_rowLen]
simp
#align young_diagram.mem_iff_lt_col_len YoungDiagram.mem_iff_lt_colLen
theorem col_eq_prod {μ : YoungDiagram} {j : ℕ} : μ.col j = Finset.range (μ.colLen j) ×ˢ {j} := by
ext ⟨a, b⟩
simp only [Finset.mem_product, Finset.mem_singleton, Finset.mem_range, mem_col_iff,
mem_iff_lt_colLen, and_comm, and_congr_right_iff]
rintro rfl
rfl
#align young_diagram.col_eq_prod YoungDiagram.col_eq_prod
theorem colLen_eq_card (μ : YoungDiagram) {j : ℕ} : μ.colLen j = (μ.col j).card := by
simp [col_eq_prod]
#align young_diagram.col_len_eq_card YoungDiagram.colLen_eq_card
@[mono]
theorem colLen_anti (μ : YoungDiagram) (j1 j2 : ℕ) (hj : j1 ≤ j2) : μ.colLen j2 ≤ μ.colLen j1 := by
convert μ.transpose.rowLen_anti j1 j2 hj using 1 <;> simp
#align young_diagram.col_len_anti YoungDiagram.colLen_anti
end Columns
section RowLens
/-! ### The list of row lengths of a Young diagram
This section defines `μ.rowLens : List ℕ`, the list of row lengths of a Young diagram `μ`.
1. `YoungDiagram.rowLens_sorted` : It is weakly decreasing (`List.Sorted (· ≥ ·)`).
2. `YoungDiagram.rowLens_pos` : It is strictly positive.
-/
/-- List of row lengths of a Young diagram -/
def rowLens (μ : YoungDiagram) : List ℕ :=
(List.range <| μ.colLen 0).map μ.rowLen
#align young_diagram.row_lens YoungDiagram.rowLens
@[simp]
theorem get_rowLens {μ : YoungDiagram} {i} :
μ.rowLens.get i = μ.rowLen i := by simp only [rowLens, List.get_range, List.get_map]
#align young_diagram.nth_le_row_lens YoungDiagram.get_rowLens
@[simp]
| Mathlib/Combinatorics/Young/YoungDiagram.lean | 420 | 421 | theorem length_rowLens {μ : YoungDiagram} : μ.rowLens.length = μ.colLen 0 := by |
simp only [rowLens, List.length_map, List.length_range]
|
/-
Copyright (c) 2019 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Jakob von Raumer
-/
import Mathlib.CategoryTheory.Limits.Shapes.FiniteProducts
import Mathlib.CategoryTheory.Limits.Shapes.BinaryProducts
import Mathlib.CategoryTheory.Limits.Shapes.Kernels
#align_import category_theory.limits.shapes.biproducts from "leanprover-community/mathlib"@"ac3ae212f394f508df43e37aa093722fa9b65d31"
/-!
# Biproducts and binary biproducts
We introduce the notion of (finite) biproducts and binary biproducts.
These are slightly unusual relative to the other shapes in the library,
as they are simultaneously limits and colimits.
(Zero objects are similar; they are "biterminal".)
For results about biproducts in preadditive categories see
`CategoryTheory.Preadditive.Biproducts`.
In a category with zero morphisms, we model the (binary) biproduct of `P Q : C`
using a `BinaryBicone`, which has a cone point `X`,
and morphisms `fst : X ⟶ P`, `snd : X ⟶ Q`, `inl : P ⟶ X` and `inr : X ⟶ Q`,
such that `inl ≫ fst = 𝟙 P`, `inl ≫ snd = 0`, `inr ≫ fst = 0`, and `inr ≫ snd = 𝟙 Q`.
Such a `BinaryBicone` is a biproduct if the cone is a limit cone, and the cocone is a colimit
cocone.
For biproducts indexed by a `Fintype J`, a `bicone` again consists of a cone point `X`
and morphisms `π j : X ⟶ F j` and `ι j : F j ⟶ X` for each `j`,
such that `ι j ≫ π j'` is the identity when `j = j'` and zero otherwise.
## Notation
As `⊕` is already taken for the sum of types, we introduce the notation `X ⊞ Y` for
a binary biproduct. We introduce `⨁ f` for the indexed biproduct.
## Implementation notes
Prior to leanprover-community/mathlib#14046,
`HasFiniteBiproducts` required a `DecidableEq` instance on the indexing type.
As this had no pay-off (everything about limits is non-constructive in mathlib),
and occasional cost
(constructing decidability instances appropriate for constructions involving the indexing type),
we made everything classical.
-/
noncomputable section
universe w w' v u
open CategoryTheory
open CategoryTheory.Functor
open scoped Classical
namespace CategoryTheory
namespace Limits
variable {J : Type w}
universe uC' uC uD' uD
variable {C : Type uC} [Category.{uC'} C] [HasZeroMorphisms C]
variable {D : Type uD} [Category.{uD'} D] [HasZeroMorphisms D]
/-- A `c : Bicone F` is:
* an object `c.pt` and
* morphisms `π j : pt ⟶ F j` and `ι j : F j ⟶ pt` for each `j`,
* such that `ι j ≫ π j'` is the identity when `j = j'` and zero otherwise.
-/
-- @[nolint has_nonempty_instance] Porting note (#5171): removed
structure Bicone (F : J → C) where
pt : C
π : ∀ j, pt ⟶ F j
ι : ∀ j, F j ⟶ pt
ι_π : ∀ j j', ι j ≫ π j' =
if h : j = j' then eqToHom (congrArg F h) else 0 := by aesop
#align category_theory.limits.bicone CategoryTheory.Limits.Bicone
set_option linter.uppercaseLean3 false in
#align category_theory.limits.bicone_X CategoryTheory.Limits.Bicone.pt
attribute [inherit_doc Bicone] Bicone.pt Bicone.π Bicone.ι Bicone.ι_π
@[reassoc (attr := simp)]
theorem bicone_ι_π_self {F : J → C} (B : Bicone F) (j : J) : B.ι j ≫ B.π j = 𝟙 (F j) := by
simpa using B.ι_π j j
#align category_theory.limits.bicone_ι_π_self CategoryTheory.Limits.bicone_ι_π_self
@[reassoc (attr := simp)]
theorem bicone_ι_π_ne {F : J → C} (B : Bicone F) {j j' : J} (h : j ≠ j') : B.ι j ≫ B.π j' = 0 := by
simpa [h] using B.ι_π j j'
#align category_theory.limits.bicone_ι_π_ne CategoryTheory.Limits.bicone_ι_π_ne
variable {F : J → C}
/-- A bicone morphism between two bicones for the same diagram is a morphism of the bicone points
which commutes with the cone and cocone legs. -/
structure BiconeMorphism {F : J → C} (A B : Bicone F) where
/-- A morphism between the two vertex objects of the bicones -/
hom : A.pt ⟶ B.pt
/-- The triangle consisting of the two natural transformations and `hom` commutes -/
wπ : ∀ j : J, hom ≫ B.π j = A.π j := by aesop_cat
/-- The triangle consisting of the two natural transformations and `hom` commutes -/
wι : ∀ j : J, A.ι j ≫ hom = B.ι j := by aesop_cat
attribute [reassoc (attr := simp)] BiconeMorphism.wι
attribute [reassoc (attr := simp)] BiconeMorphism.wπ
/-- The category of bicones on a given diagram. -/
@[simps]
instance Bicone.category : Category (Bicone F) where
Hom A B := BiconeMorphism A B
comp f g := { hom := f.hom ≫ g.hom }
id B := { hom := 𝟙 B.pt }
-- Porting note: if we do not have `simps` automatically generate the lemma for simplifying
-- the `hom` field of a category, we need to write the `ext` lemma in terms of the categorical
-- morphism, rather than the underlying structure.
@[ext]
theorem BiconeMorphism.ext {c c' : Bicone F} (f g : c ⟶ c') (w : f.hom = g.hom) : f = g := by
cases f
cases g
congr
namespace Bicones
/-- To give an isomorphism between cocones, it suffices to give an
isomorphism between their vertices which commutes with the cocone
maps. -/
-- Porting note: `@[ext]` used to accept lemmas like this. Now we add an aesop rule
@[aesop apply safe (rule_sets := [CategoryTheory]), simps]
def ext {c c' : Bicone F} (φ : c.pt ≅ c'.pt)
(wι : ∀ j, c.ι j ≫ φ.hom = c'.ι j := by aesop_cat)
(wπ : ∀ j, φ.hom ≫ c'.π j = c.π j := by aesop_cat) : c ≅ c' where
hom := { hom := φ.hom }
inv :=
{ hom := φ.inv
wι := fun j => φ.comp_inv_eq.mpr (wι j).symm
wπ := fun j => φ.inv_comp_eq.mpr (wπ j).symm }
variable (F) in
/-- A functor `G : C ⥤ D` sends bicones over `F` to bicones over `G.obj ∘ F` functorially. -/
@[simps]
def functoriality (G : C ⥤ D) [Functor.PreservesZeroMorphisms G] :
Bicone F ⥤ Bicone (G.obj ∘ F) where
obj A :=
{ pt := G.obj A.pt
π := fun j => G.map (A.π j)
ι := fun j => G.map (A.ι j)
ι_π := fun i j => (Functor.map_comp _ _ _).symm.trans <| by
rw [A.ι_π]
aesop_cat }
map f :=
{ hom := G.map f.hom
wπ := fun j => by simp [-BiconeMorphism.wπ, ← f.wπ j]
wι := fun j => by simp [-BiconeMorphism.wι, ← f.wι j] }
variable (G : C ⥤ D)
instance functoriality_full [G.PreservesZeroMorphisms] [G.Full] [G.Faithful] :
(functoriality F G).Full where
map_surjective t :=
⟨{ hom := G.preimage t.hom
wι := fun j => G.map_injective (by simpa using t.wι j)
wπ := fun j => G.map_injective (by simpa using t.wπ j) }, by aesop_cat⟩
instance functoriality_faithful [G.PreservesZeroMorphisms] [G.Faithful] :
(functoriality F G).Faithful where
map_injective {_X} {_Y} f g h :=
BiconeMorphism.ext f g <| G.map_injective <| congr_arg BiconeMorphism.hom h
end Bicones
namespace Bicone
attribute [local aesop safe tactic (rule_sets := [CategoryTheory])]
CategoryTheory.Discrete.discreteCases
-- Porting note: would it be okay to use this more generally?
attribute [local aesop safe cases (rule_sets := [CategoryTheory])] Eq
/-- Extract the cone from a bicone. -/
def toConeFunctor : Bicone F ⥤ Cone (Discrete.functor F) where
obj B := { pt := B.pt, π := { app := fun j => B.π j.as } }
map {X Y} F := { hom := F.hom, w := fun _ => F.wπ _ }
/-- A shorthand for `toConeFunctor.obj` -/
abbrev toCone (B : Bicone F) : Cone (Discrete.functor F) := toConeFunctor.obj B
#align category_theory.limits.bicone.to_cone CategoryTheory.Limits.Bicone.toCone
-- TODO Consider changing this API to `toFan (B : Bicone F) : Fan F`.
@[simp]
theorem toCone_pt (B : Bicone F) : B.toCone.pt = B.pt := rfl
set_option linter.uppercaseLean3 false in
#align category_theory.limits.bicone.to_cone_X CategoryTheory.Limits.Bicone.toCone_pt
@[simp]
theorem toCone_π_app (B : Bicone F) (j : Discrete J) : B.toCone.π.app j = B.π j.as := rfl
#align category_theory.limits.bicone.to_cone_π_app CategoryTheory.Limits.Bicone.toCone_π_app
theorem toCone_π_app_mk (B : Bicone F) (j : J) : B.toCone.π.app ⟨j⟩ = B.π j := rfl
#align category_theory.limits.bicone.to_cone_π_app_mk CategoryTheory.Limits.Bicone.toCone_π_app_mk
@[simp]
theorem toCone_proj (B : Bicone F) (j : J) : Fan.proj B.toCone j = B.π j := rfl
/-- Extract the cocone from a bicone. -/
def toCoconeFunctor : Bicone F ⥤ Cocone (Discrete.functor F) where
obj B := { pt := B.pt, ι := { app := fun j => B.ι j.as } }
map {X Y} F := { hom := F.hom, w := fun _ => F.wι _ }
/-- A shorthand for `toCoconeFunctor.obj` -/
abbrev toCocone (B : Bicone F) : Cocone (Discrete.functor F) := toCoconeFunctor.obj B
#align category_theory.limits.bicone.to_cocone CategoryTheory.Limits.Bicone.toCocone
@[simp]
theorem toCocone_pt (B : Bicone F) : B.toCocone.pt = B.pt := rfl
set_option linter.uppercaseLean3 false in
#align category_theory.limits.bicone.to_cocone_X CategoryTheory.Limits.Bicone.toCocone_pt
@[simp]
theorem toCocone_ι_app (B : Bicone F) (j : Discrete J) : B.toCocone.ι.app j = B.ι j.as := rfl
#align category_theory.limits.bicone.to_cocone_ι_app CategoryTheory.Limits.Bicone.toCocone_ι_app
@[simp]
theorem toCocone_inj (B : Bicone F) (j : J) : Cofan.inj B.toCocone j = B.ι j := rfl
theorem toCocone_ι_app_mk (B : Bicone F) (j : J) : B.toCocone.ι.app ⟨j⟩ = B.ι j := rfl
#align category_theory.limits.bicone.to_cocone_ι_app_mk CategoryTheory.Limits.Bicone.toCocone_ι_app_mk
/-- We can turn any limit cone over a discrete collection of objects into a bicone. -/
@[simps]
def ofLimitCone {f : J → C} {t : Cone (Discrete.functor f)} (ht : IsLimit t) : Bicone f where
pt := t.pt
π j := t.π.app ⟨j⟩
ι j := ht.lift (Fan.mk _ fun j' => if h : j = j' then eqToHom (congr_arg f h) else 0)
ι_π j j' := by simp
#align category_theory.limits.bicone.of_limit_cone CategoryTheory.Limits.Bicone.ofLimitCone
theorem ι_of_isLimit {f : J → C} {t : Bicone f} (ht : IsLimit t.toCone) (j : J) :
t.ι j = ht.lift (Fan.mk _ fun j' => if h : j = j' then eqToHom (congr_arg f h) else 0) :=
ht.hom_ext fun j' => by
rw [ht.fac]
simp [t.ι_π]
#align category_theory.limits.bicone.ι_of_is_limit CategoryTheory.Limits.Bicone.ι_of_isLimit
/-- We can turn any colimit cocone over a discrete collection of objects into a bicone. -/
@[simps]
def ofColimitCocone {f : J → C} {t : Cocone (Discrete.functor f)} (ht : IsColimit t) :
Bicone f where
pt := t.pt
π j := ht.desc (Cofan.mk _ fun j' => if h : j' = j then eqToHom (congr_arg f h) else 0)
ι j := t.ι.app ⟨j⟩
ι_π j j' := by simp
#align category_theory.limits.bicone.of_colimit_cocone CategoryTheory.Limits.Bicone.ofColimitCocone
theorem π_of_isColimit {f : J → C} {t : Bicone f} (ht : IsColimit t.toCocone) (j : J) :
t.π j = ht.desc (Cofan.mk _ fun j' => if h : j' = j then eqToHom (congr_arg f h) else 0) :=
ht.hom_ext fun j' => by
rw [ht.fac]
simp [t.ι_π]
#align category_theory.limits.bicone.π_of_is_colimit CategoryTheory.Limits.Bicone.π_of_isColimit
/-- Structure witnessing that a bicone is both a limit cone and a colimit cocone. -/
-- @[nolint has_nonempty_instance] Porting note (#5171): removed
structure IsBilimit {F : J → C} (B : Bicone F) where
isLimit : IsLimit B.toCone
isColimit : IsColimit B.toCocone
#align category_theory.limits.bicone.is_bilimit CategoryTheory.Limits.Bicone.IsBilimit
#align category_theory.limits.bicone.is_bilimit.is_limit CategoryTheory.Limits.Bicone.IsBilimit.isLimit
#align category_theory.limits.bicone.is_bilimit.is_colimit CategoryTheory.Limits.Bicone.IsBilimit.isColimit
attribute [inherit_doc IsBilimit] IsBilimit.isLimit IsBilimit.isColimit
-- Porting note (#10618): simp can prove this, linter doesn't notice it is removed
attribute [-simp, nolint simpNF] IsBilimit.mk.injEq
attribute [local ext] Bicone.IsBilimit
instance subsingleton_isBilimit {f : J → C} {c : Bicone f} : Subsingleton c.IsBilimit :=
⟨fun _ _ => Bicone.IsBilimit.ext _ _ (Subsingleton.elim _ _) (Subsingleton.elim _ _)⟩
#align category_theory.limits.bicone.subsingleton_is_bilimit CategoryTheory.Limits.Bicone.subsingleton_isBilimit
section Whisker
variable {K : Type w'}
/-- Whisker a bicone with an equivalence between the indexing types. -/
@[simps]
def whisker {f : J → C} (c : Bicone f) (g : K ≃ J) : Bicone (f ∘ g) where
pt := c.pt
π k := c.π (g k)
ι k := c.ι (g k)
ι_π k k' := by
simp only [c.ι_π]
split_ifs with h h' h' <;> simp [Equiv.apply_eq_iff_eq g] at h h' <;> tauto
#align category_theory.limits.bicone.whisker CategoryTheory.Limits.Bicone.whisker
/-- Taking the cone of a whiskered bicone results in a cone isomorphic to one gained
by whiskering the cone and postcomposing with a suitable isomorphism. -/
def whiskerToCone {f : J → C} (c : Bicone f) (g : K ≃ J) :
(c.whisker g).toCone ≅
(Cones.postcompose (Discrete.functorComp f g).inv).obj
(c.toCone.whisker (Discrete.functor (Discrete.mk ∘ g))) :=
Cones.ext (Iso.refl _) (by aesop_cat)
#align category_theory.limits.bicone.whisker_to_cone CategoryTheory.Limits.Bicone.whiskerToCone
/-- Taking the cocone of a whiskered bicone results in a cone isomorphic to one gained
by whiskering the cocone and precomposing with a suitable isomorphism. -/
def whiskerToCocone {f : J → C} (c : Bicone f) (g : K ≃ J) :
(c.whisker g).toCocone ≅
(Cocones.precompose (Discrete.functorComp f g).hom).obj
(c.toCocone.whisker (Discrete.functor (Discrete.mk ∘ g))) :=
Cocones.ext (Iso.refl _) (by aesop_cat)
#align category_theory.limits.bicone.whisker_to_cocone CategoryTheory.Limits.Bicone.whiskerToCocone
/-- Whiskering a bicone with an equivalence between types preserves being a bilimit bicone. -/
def whiskerIsBilimitIff {f : J → C} (c : Bicone f) (g : K ≃ J) :
(c.whisker g).IsBilimit ≃ c.IsBilimit := by
refine equivOfSubsingletonOfSubsingleton (fun hc => ⟨?_, ?_⟩) fun hc => ⟨?_, ?_⟩
· let this := IsLimit.ofIsoLimit hc.isLimit (Bicone.whiskerToCone c g)
let this := (IsLimit.postcomposeHomEquiv (Discrete.functorComp f g).symm _) this
exact IsLimit.ofWhiskerEquivalence (Discrete.equivalence g) this
· let this := IsColimit.ofIsoColimit hc.isColimit (Bicone.whiskerToCocone c g)
let this := (IsColimit.precomposeHomEquiv (Discrete.functorComp f g) _) this
exact IsColimit.ofWhiskerEquivalence (Discrete.equivalence g) this
· apply IsLimit.ofIsoLimit _ (Bicone.whiskerToCone c g).symm
apply (IsLimit.postcomposeHomEquiv (Discrete.functorComp f g).symm _).symm _
exact IsLimit.whiskerEquivalence hc.isLimit (Discrete.equivalence g)
· apply IsColimit.ofIsoColimit _ (Bicone.whiskerToCocone c g).symm
apply (IsColimit.precomposeHomEquiv (Discrete.functorComp f g) _).symm _
exact IsColimit.whiskerEquivalence hc.isColimit (Discrete.equivalence g)
#align category_theory.limits.bicone.whisker_is_bilimit_iff CategoryTheory.Limits.Bicone.whiskerIsBilimitIff
end Whisker
end Bicone
/-- A bicone over `F : J → C`, which is both a limit cone and a colimit cocone.
-/
-- @[nolint has_nonempty_instance] -- Porting note(#5171): removed; linter not ported yet
structure LimitBicone (F : J → C) where
bicone : Bicone F
isBilimit : bicone.IsBilimit
#align category_theory.limits.limit_bicone CategoryTheory.Limits.LimitBicone
#align category_theory.limits.limit_bicone.is_bilimit CategoryTheory.Limits.LimitBicone.isBilimit
attribute [inherit_doc LimitBicone] LimitBicone.bicone LimitBicone.isBilimit
/-- `HasBiproduct F` expresses the mere existence of a bicone which is
simultaneously a limit and a colimit of the diagram `F`.
-/
class HasBiproduct (F : J → C) : Prop where mk' ::
exists_biproduct : Nonempty (LimitBicone F)
#align category_theory.limits.has_biproduct CategoryTheory.Limits.HasBiproduct
attribute [inherit_doc HasBiproduct] HasBiproduct.exists_biproduct
theorem HasBiproduct.mk {F : J → C} (d : LimitBicone F) : HasBiproduct F :=
⟨Nonempty.intro d⟩
#align category_theory.limits.has_biproduct.mk CategoryTheory.Limits.HasBiproduct.mk
/-- Use the axiom of choice to extract explicit `BiproductData F` from `HasBiproduct F`. -/
def getBiproductData (F : J → C) [HasBiproduct F] : LimitBicone F :=
Classical.choice HasBiproduct.exists_biproduct
#align category_theory.limits.get_biproduct_data CategoryTheory.Limits.getBiproductData
/-- A bicone for `F` which is both a limit cone and a colimit cocone. -/
def biproduct.bicone (F : J → C) [HasBiproduct F] : Bicone F :=
(getBiproductData F).bicone
#align category_theory.limits.biproduct.bicone CategoryTheory.Limits.biproduct.bicone
/-- `biproduct.bicone F` is a bilimit bicone. -/
def biproduct.isBilimit (F : J → C) [HasBiproduct F] : (biproduct.bicone F).IsBilimit :=
(getBiproductData F).isBilimit
#align category_theory.limits.biproduct.is_bilimit CategoryTheory.Limits.biproduct.isBilimit
/-- `biproduct.bicone F` is a limit cone. -/
def biproduct.isLimit (F : J → C) [HasBiproduct F] : IsLimit (biproduct.bicone F).toCone :=
(getBiproductData F).isBilimit.isLimit
#align category_theory.limits.biproduct.is_limit CategoryTheory.Limits.biproduct.isLimit
/-- `biproduct.bicone F` is a colimit cocone. -/
def biproduct.isColimit (F : J → C) [HasBiproduct F] : IsColimit (biproduct.bicone F).toCocone :=
(getBiproductData F).isBilimit.isColimit
#align category_theory.limits.biproduct.is_colimit CategoryTheory.Limits.biproduct.isColimit
instance (priority := 100) hasProduct_of_hasBiproduct [HasBiproduct F] : HasProduct F :=
HasLimit.mk
{ cone := (biproduct.bicone F).toCone
isLimit := biproduct.isLimit F }
#align category_theory.limits.has_product_of_has_biproduct CategoryTheory.Limits.hasProduct_of_hasBiproduct
instance (priority := 100) hasCoproduct_of_hasBiproduct [HasBiproduct F] : HasCoproduct F :=
HasColimit.mk
{ cocone := (biproduct.bicone F).toCocone
isColimit := biproduct.isColimit F }
#align category_theory.limits.has_coproduct_of_has_biproduct CategoryTheory.Limits.hasCoproduct_of_hasBiproduct
variable (J C)
/-- `C` has biproducts of shape `J` if we have
a limit and a colimit, with the same cone points,
of every function `F : J → C`.
-/
class HasBiproductsOfShape : Prop where
has_biproduct : ∀ F : J → C, HasBiproduct F
#align category_theory.limits.has_biproducts_of_shape CategoryTheory.Limits.HasBiproductsOfShape
attribute [instance 100] HasBiproductsOfShape.has_biproduct
/-- `HasFiniteBiproducts C` represents a choice of biproduct for every family of objects in `C`
indexed by a finite type. -/
class HasFiniteBiproducts : Prop where
out : ∀ n, HasBiproductsOfShape (Fin n) C
#align category_theory.limits.has_finite_biproducts CategoryTheory.Limits.HasFiniteBiproducts
attribute [inherit_doc HasFiniteBiproducts] HasFiniteBiproducts.out
variable {J}
theorem hasBiproductsOfShape_of_equiv {K : Type w'} [HasBiproductsOfShape K C] (e : J ≃ K) :
HasBiproductsOfShape J C :=
⟨fun F =>
let ⟨⟨h⟩⟩ := HasBiproductsOfShape.has_biproduct (F ∘ e.symm)
let ⟨c, hc⟩ := h
HasBiproduct.mk <| by
simpa only [(· ∘ ·), e.symm_apply_apply] using
LimitBicone.mk (c.whisker e) ((c.whiskerIsBilimitIff _).2 hc)⟩
#align category_theory.limits.has_biproducts_of_shape_of_equiv CategoryTheory.Limits.hasBiproductsOfShape_of_equiv
instance (priority := 100) hasBiproductsOfShape_finite [HasFiniteBiproducts C] [Finite J] :
HasBiproductsOfShape J C := by
rcases Finite.exists_equiv_fin J with ⟨n, ⟨e⟩⟩
haveI : HasBiproductsOfShape (Fin n) C := HasFiniteBiproducts.out n
exact hasBiproductsOfShape_of_equiv C e
#align category_theory.limits.has_biproducts_of_shape_finite CategoryTheory.Limits.hasBiproductsOfShape_finite
instance (priority := 100) hasFiniteProducts_of_hasFiniteBiproducts [HasFiniteBiproducts C] :
HasFiniteProducts C where
out _ := ⟨fun _ => hasLimitOfIso Discrete.natIsoFunctor.symm⟩
#align category_theory.limits.has_finite_products_of_has_finite_biproducts CategoryTheory.Limits.hasFiniteProducts_of_hasFiniteBiproducts
instance (priority := 100) hasFiniteCoproducts_of_hasFiniteBiproducts [HasFiniteBiproducts C] :
HasFiniteCoproducts C where
out _ := ⟨fun _ => hasColimitOfIso Discrete.natIsoFunctor⟩
#align category_theory.limits.has_finite_coproducts_of_has_finite_biproducts CategoryTheory.Limits.hasFiniteCoproducts_of_hasFiniteBiproducts
variable {C}
/-- The isomorphism between the specified limit and the specified colimit for
a functor with a bilimit.
-/
def biproductIso (F : J → C) [HasBiproduct F] : Limits.piObj F ≅ Limits.sigmaObj F :=
(IsLimit.conePointUniqueUpToIso (limit.isLimit _) (biproduct.isLimit F)).trans <|
IsColimit.coconePointUniqueUpToIso (biproduct.isColimit F) (colimit.isColimit _)
#align category_theory.limits.biproduct_iso CategoryTheory.Limits.biproductIso
end Limits
namespace Limits
variable {J : Type w} {K : Type*}
variable {C : Type u} [Category.{v} C] [HasZeroMorphisms C]
/-- `biproduct f` computes the biproduct of a family of elements `f`. (It is defined as an
abbreviation for `limit (Discrete.functor f)`, so for most facts about `biproduct f`, you will
just use general facts about limits and colimits.) -/
abbrev biproduct (f : J → C) [HasBiproduct f] : C :=
(biproduct.bicone f).pt
#align category_theory.limits.biproduct CategoryTheory.Limits.biproduct
@[inherit_doc biproduct]
notation "⨁ " f:20 => biproduct f
/-- The projection onto a summand of a biproduct. -/
abbrev biproduct.π (f : J → C) [HasBiproduct f] (b : J) : ⨁ f ⟶ f b :=
(biproduct.bicone f).π b
#align category_theory.limits.biproduct.π CategoryTheory.Limits.biproduct.π
@[simp]
theorem biproduct.bicone_π (f : J → C) [HasBiproduct f] (b : J) :
(biproduct.bicone f).π b = biproduct.π f b := rfl
#align category_theory.limits.biproduct.bicone_π CategoryTheory.Limits.biproduct.bicone_π
/-- The inclusion into a summand of a biproduct. -/
abbrev biproduct.ι (f : J → C) [HasBiproduct f] (b : J) : f b ⟶ ⨁ f :=
(biproduct.bicone f).ι b
#align category_theory.limits.biproduct.ι CategoryTheory.Limits.biproduct.ι
@[simp]
theorem biproduct.bicone_ι (f : J → C) [HasBiproduct f] (b : J) :
(biproduct.bicone f).ι b = biproduct.ι f b := rfl
#align category_theory.limits.biproduct.bicone_ι CategoryTheory.Limits.biproduct.bicone_ι
/-- Note that as this lemma has an `if` in the statement, we include a `DecidableEq` argument.
This means you may not be able to `simp` using this lemma unless you `open scoped Classical`. -/
@[reassoc]
theorem biproduct.ι_π [DecidableEq J] (f : J → C) [HasBiproduct f] (j j' : J) :
biproduct.ι f j ≫ biproduct.π f j' = if h : j = j' then eqToHom (congr_arg f h) else 0 := by
convert (biproduct.bicone f).ι_π j j'
#align category_theory.limits.biproduct.ι_π CategoryTheory.Limits.biproduct.ι_π
@[reassoc] -- Porting note: both versions proven by simp
theorem biproduct.ι_π_self (f : J → C) [HasBiproduct f] (j : J) :
biproduct.ι f j ≫ biproduct.π f j = 𝟙 _ := by simp [biproduct.ι_π]
#align category_theory.limits.biproduct.ι_π_self CategoryTheory.Limits.biproduct.ι_π_self
@[reassoc (attr := simp)]
theorem biproduct.ι_π_ne (f : J → C) [HasBiproduct f] {j j' : J} (h : j ≠ j') :
biproduct.ι f j ≫ biproduct.π f j' = 0 := by simp [biproduct.ι_π, h]
#align category_theory.limits.biproduct.ι_π_ne CategoryTheory.Limits.biproduct.ι_π_ne
-- The `simpNF` linter incorrectly identifies these as simp lemmas that could never apply.
-- https://github.com/leanprover-community/mathlib4/issues/5049
-- They are used by `simp` in `biproduct.whiskerEquiv` below.
@[reassoc (attr := simp, nolint simpNF)]
theorem biproduct.eqToHom_comp_ι (f : J → C) [HasBiproduct f] {j j' : J} (w : j = j') :
eqToHom (by simp [w]) ≫ biproduct.ι f j' = biproduct.ι f j := by
cases w
simp
-- The `simpNF` linter incorrectly identifies these as simp lemmas that could never apply.
-- https://github.com/leanprover-community/mathlib4/issues/5049
-- They are used by `simp` in `biproduct.whiskerEquiv` below.
@[reassoc (attr := simp, nolint simpNF)]
theorem biproduct.π_comp_eqToHom (f : J → C) [HasBiproduct f] {j j' : J} (w : j = j') :
biproduct.π f j ≫ eqToHom (by simp [w]) = biproduct.π f j' := by
cases w
simp
/-- Given a collection of maps into the summands, we obtain a map into the biproduct. -/
abbrev biproduct.lift {f : J → C} [HasBiproduct f] {P : C} (p : ∀ b, P ⟶ f b) : P ⟶ ⨁ f :=
(biproduct.isLimit f).lift (Fan.mk P p)
#align category_theory.limits.biproduct.lift CategoryTheory.Limits.biproduct.lift
/-- Given a collection of maps out of the summands, we obtain a map out of the biproduct. -/
abbrev biproduct.desc {f : J → C} [HasBiproduct f] {P : C} (p : ∀ b, f b ⟶ P) : ⨁ f ⟶ P :=
(biproduct.isColimit f).desc (Cofan.mk P p)
#align category_theory.limits.biproduct.desc CategoryTheory.Limits.biproduct.desc
@[reassoc (attr := simp)]
theorem biproduct.lift_π {f : J → C} [HasBiproduct f] {P : C} (p : ∀ b, P ⟶ f b) (j : J) :
biproduct.lift p ≫ biproduct.π f j = p j := (biproduct.isLimit f).fac _ ⟨j⟩
#align category_theory.limits.biproduct.lift_π CategoryTheory.Limits.biproduct.lift_π
@[reassoc (attr := simp)]
theorem biproduct.ι_desc {f : J → C} [HasBiproduct f] {P : C} (p : ∀ b, f b ⟶ P) (j : J) :
biproduct.ι f j ≫ biproduct.desc p = p j := (biproduct.isColimit f).fac _ ⟨j⟩
#align category_theory.limits.biproduct.ι_desc CategoryTheory.Limits.biproduct.ι_desc
/-- Given a collection of maps between corresponding summands of a pair of biproducts
indexed by the same type, we obtain a map between the biproducts. -/
abbrev biproduct.map {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ b, f b ⟶ g b) :
⨁ f ⟶ ⨁ g :=
IsLimit.map (biproduct.bicone f).toCone (biproduct.isLimit g)
(Discrete.natTrans (fun j => p j.as))
#align category_theory.limits.biproduct.map CategoryTheory.Limits.biproduct.map
/-- An alternative to `biproduct.map` constructed via colimits.
This construction only exists in order to show it is equal to `biproduct.map`. -/
abbrev biproduct.map' {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ b, f b ⟶ g b) :
⨁ f ⟶ ⨁ g :=
IsColimit.map (biproduct.isColimit f) (biproduct.bicone g).toCocone
(Discrete.natTrans fun j => p j.as)
#align category_theory.limits.biproduct.map' CategoryTheory.Limits.biproduct.map'
-- We put this at slightly higher priority than `biproduct.hom_ext'`,
-- to get the matrix indices in the "right" order.
@[ext 1001]
theorem biproduct.hom_ext {f : J → C} [HasBiproduct f] {Z : C} (g h : Z ⟶ ⨁ f)
(w : ∀ j, g ≫ biproduct.π f j = h ≫ biproduct.π f j) : g = h :=
(biproduct.isLimit f).hom_ext fun j => w j.as
#align category_theory.limits.biproduct.hom_ext CategoryTheory.Limits.biproduct.hom_ext
@[ext]
theorem biproduct.hom_ext' {f : J → C} [HasBiproduct f] {Z : C} (g h : ⨁ f ⟶ Z)
(w : ∀ j, biproduct.ι f j ≫ g = biproduct.ι f j ≫ h) : g = h :=
(biproduct.isColimit f).hom_ext fun j => w j.as
#align category_theory.limits.biproduct.hom_ext' CategoryTheory.Limits.biproduct.hom_ext'
/-- The canonical isomorphism between the chosen biproduct and the chosen product. -/
def biproduct.isoProduct (f : J → C) [HasBiproduct f] : ⨁ f ≅ ∏ᶜ f :=
IsLimit.conePointUniqueUpToIso (biproduct.isLimit f) (limit.isLimit _)
#align category_theory.limits.biproduct.iso_product CategoryTheory.Limits.biproduct.isoProduct
@[simp]
theorem biproduct.isoProduct_hom {f : J → C} [HasBiproduct f] :
(biproduct.isoProduct f).hom = Pi.lift (biproduct.π f) :=
limit.hom_ext fun j => by simp [biproduct.isoProduct]
#align category_theory.limits.biproduct.iso_product_hom CategoryTheory.Limits.biproduct.isoProduct_hom
@[simp]
theorem biproduct.isoProduct_inv {f : J → C} [HasBiproduct f] :
(biproduct.isoProduct f).inv = biproduct.lift (Pi.π f) :=
biproduct.hom_ext _ _ fun j => by simp [Iso.inv_comp_eq]
#align category_theory.limits.biproduct.iso_product_inv CategoryTheory.Limits.biproduct.isoProduct_inv
/-- The canonical isomorphism between the chosen biproduct and the chosen coproduct. -/
def biproduct.isoCoproduct (f : J → C) [HasBiproduct f] : ⨁ f ≅ ∐ f :=
IsColimit.coconePointUniqueUpToIso (biproduct.isColimit f) (colimit.isColimit _)
#align category_theory.limits.biproduct.iso_coproduct CategoryTheory.Limits.biproduct.isoCoproduct
@[simp]
theorem biproduct.isoCoproduct_inv {f : J → C} [HasBiproduct f] :
(biproduct.isoCoproduct f).inv = Sigma.desc (biproduct.ι f) :=
colimit.hom_ext fun j => by simp [biproduct.isoCoproduct]
#align category_theory.limits.biproduct.iso_coproduct_inv CategoryTheory.Limits.biproduct.isoCoproduct_inv
@[simp]
theorem biproduct.isoCoproduct_hom {f : J → C} [HasBiproduct f] :
(biproduct.isoCoproduct f).hom = biproduct.desc (Sigma.ι f) :=
biproduct.hom_ext' _ _ fun j => by simp [← Iso.eq_comp_inv]
#align category_theory.limits.biproduct.iso_coproduct_hom CategoryTheory.Limits.biproduct.isoCoproduct_hom
theorem biproduct.map_eq_map' {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ b, f b ⟶ g b) :
biproduct.map p = biproduct.map' p := by
ext
dsimp
simp only [Discrete.natTrans_app, Limits.IsColimit.ι_map_assoc, Limits.IsLimit.map_π,
Category.assoc, ← Bicone.toCone_π_app_mk, ← biproduct.bicone_π, ← Bicone.toCocone_ι_app_mk,
← biproduct.bicone_ι]
dsimp
rw [biproduct.ι_π_assoc, biproduct.ι_π]
split_ifs with h
· subst h; rw [eqToHom_refl, Category.id_comp]; erw [Category.comp_id]
· simp
#align category_theory.limits.biproduct.map_eq_map' CategoryTheory.Limits.biproduct.map_eq_map'
@[reassoc (attr := simp)]
theorem biproduct.map_π {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ j, f j ⟶ g j)
(j : J) : biproduct.map p ≫ biproduct.π g j = biproduct.π f j ≫ p j :=
Limits.IsLimit.map_π _ _ _ (Discrete.mk j)
#align category_theory.limits.biproduct.map_π CategoryTheory.Limits.biproduct.map_π
@[reassoc (attr := simp)]
theorem biproduct.ι_map {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ j, f j ⟶ g j)
(j : J) : biproduct.ι f j ≫ biproduct.map p = p j ≫ biproduct.ι g j := by
rw [biproduct.map_eq_map']
apply
Limits.IsColimit.ι_map (biproduct.isColimit f) (biproduct.bicone g).toCocone
(Discrete.natTrans fun j => p j.as) (Discrete.mk j)
#align category_theory.limits.biproduct.ι_map CategoryTheory.Limits.biproduct.ι_map
@[reassoc (attr := simp)]
| Mathlib/CategoryTheory/Limits/Shapes/Biproducts.lean | 649 | 652 | theorem biproduct.map_desc {f g : J → C} [HasBiproduct f] [HasBiproduct g] (p : ∀ j, f j ⟶ g j)
{P : C} (k : ∀ j, g j ⟶ P) :
biproduct.map p ≫ biproduct.desc k = biproduct.desc fun j => p j ≫ k j := by |
ext; simp
|
/-
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.Algebra.Group.Equiv.Basic
import Mathlib.Data.ENat.Lattice
import Mathlib.Data.Part
import Mathlib.Tactic.NormNum
#align_import data.nat.part_enat from "leanprover-community/mathlib"@"3ff3f2d6a3118b8711063de7111a0d77a53219a8"
/-!
# Natural numbers with infinity
The natural numbers and an extra `top` element `⊤`. This implementation uses `Part ℕ` as an
implementation. Use `ℕ∞` instead unless you care about computability.
## Main definitions
The following instances are defined:
* `OrderedAddCommMonoid PartENat`
* `CanonicallyOrderedAddCommMonoid PartENat`
* `CompleteLinearOrder PartENat`
There is no additive analogue of `MonoidWithZero`; if there were then `PartENat` could
be an `AddMonoidWithTop`.
* `toWithTop` : the map from `PartENat` to `ℕ∞`, with theorems that it plays well
with `+` and `≤`.
* `withTopAddEquiv : PartENat ≃+ ℕ∞`
* `withTopOrderIso : PartENat ≃o ℕ∞`
## Implementation details
`PartENat` is defined to be `Part ℕ`.
`+` and `≤` are defined on `PartENat`, but there is an issue with `*` because it's not
clear what `0 * ⊤` should be. `mul` is hence left undefined. Similarly `⊤ - ⊤` is ambiguous
so there is no `-` defined on `PartENat`.
Before the `open scoped Classical` line, various proofs are made with decidability assumptions.
This can cause issues -- see for example the non-simp lemma `toWithTopZero` proved by `rfl`,
followed by `@[simp] lemma toWithTopZero'` whose proof uses `convert`.
## Tags
PartENat, ℕ∞
-/
open Part hiding some
/-- Type of natural numbers with infinity (`⊤`) -/
def PartENat : Type :=
Part ℕ
#align part_enat PartENat
namespace PartENat
/-- The computable embedding `ℕ → PartENat`.
This coincides with the coercion `coe : ℕ → PartENat`, see `PartENat.some_eq_natCast`. -/
@[coe]
def some : ℕ → PartENat :=
Part.some
#align part_enat.some PartENat.some
instance : Zero PartENat :=
⟨some 0⟩
instance : Inhabited PartENat :=
⟨0⟩
instance : One PartENat :=
⟨some 1⟩
instance : Add PartENat :=
⟨fun x y => ⟨x.Dom ∧ y.Dom, fun h => get x h.1 + get y h.2⟩⟩
instance (n : ℕ) : Decidable (some n).Dom :=
isTrue trivial
@[simp]
theorem dom_some (x : ℕ) : (some x).Dom :=
trivial
#align part_enat.dom_some PartENat.dom_some
instance addCommMonoid : AddCommMonoid PartENat where
add := (· + ·)
zero := 0
add_comm x y := Part.ext' and_comm fun _ _ => add_comm _ _
zero_add x := Part.ext' (true_and_iff _) fun _ _ => zero_add _
add_zero x := Part.ext' (and_true_iff _) fun _ _ => add_zero _
add_assoc x y z := Part.ext' and_assoc fun _ _ => add_assoc _ _ _
nsmul := nsmulRec
instance : AddCommMonoidWithOne PartENat :=
{ PartENat.addCommMonoid with
one := 1
natCast := some
natCast_zero := rfl
natCast_succ := fun _ => Part.ext' (true_and_iff _).symm fun _ _ => rfl }
theorem some_eq_natCast (n : ℕ) : some n = n :=
rfl
#align part_enat.some_eq_coe PartENat.some_eq_natCast
instance : CharZero PartENat where
cast_injective := Part.some_injective
/-- Alias of `Nat.cast_inj` specialized to `PartENat` --/
theorem natCast_inj {x y : ℕ} : (x : PartENat) = y ↔ x = y :=
Nat.cast_inj
#align part_enat.coe_inj PartENat.natCast_inj
@[simp]
theorem dom_natCast (x : ℕ) : (x : PartENat).Dom :=
trivial
#align part_enat.dom_coe PartENat.dom_natCast
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem dom_ofNat (x : ℕ) [x.AtLeastTwo] : (no_index (OfNat.ofNat x : PartENat)).Dom :=
trivial
@[simp]
theorem dom_zero : (0 : PartENat).Dom :=
trivial
@[simp]
theorem dom_one : (1 : PartENat).Dom :=
trivial
instance : CanLift PartENat ℕ (↑) Dom :=
⟨fun n hn => ⟨n.get hn, Part.some_get _⟩⟩
instance : LE PartENat :=
⟨fun x y => ∃ h : y.Dom → x.Dom, ∀ hy : y.Dom, x.get (h hy) ≤ y.get hy⟩
instance : Top PartENat :=
⟨none⟩
instance : Bot PartENat :=
⟨0⟩
instance : Sup PartENat :=
⟨fun x y => ⟨x.Dom ∧ y.Dom, fun h => x.get h.1 ⊔ y.get h.2⟩⟩
theorem le_def (x y : PartENat) :
x ≤ y ↔ ∃ h : y.Dom → x.Dom, ∀ hy : y.Dom, x.get (h hy) ≤ y.get hy :=
Iff.rfl
#align part_enat.le_def PartENat.le_def
@[elab_as_elim]
protected theorem casesOn' {P : PartENat → Prop} :
∀ a : PartENat, P ⊤ → (∀ n : ℕ, P (some n)) → P a :=
Part.induction_on
#align part_enat.cases_on' PartENat.casesOn'
@[elab_as_elim]
protected theorem casesOn {P : PartENat → Prop} : ∀ a : PartENat, P ⊤ → (∀ n : ℕ, P n) → P a := by
exact PartENat.casesOn'
#align part_enat.cases_on PartENat.casesOn
-- not a simp lemma as we will provide a `LinearOrderedAddCommMonoidWithTop` instance later
theorem top_add (x : PartENat) : ⊤ + x = ⊤ :=
Part.ext' (false_and_iff _) fun h => h.left.elim
#align part_enat.top_add PartENat.top_add
-- not a simp lemma as we will provide a `LinearOrderedAddCommMonoidWithTop` instance later
theorem add_top (x : PartENat) : x + ⊤ = ⊤ := by rw [add_comm, top_add]
#align part_enat.add_top PartENat.add_top
@[simp]
theorem natCast_get {x : PartENat} (h : x.Dom) : (x.get h : PartENat) = x := by
exact Part.ext' (iff_of_true trivial h) fun _ _ => rfl
#align part_enat.coe_get PartENat.natCast_get
@[simp, norm_cast]
theorem get_natCast' (x : ℕ) (h : (x : PartENat).Dom) : get (x : PartENat) h = x := by
rw [← natCast_inj, natCast_get]
#align part_enat.get_coe' PartENat.get_natCast'
theorem get_natCast {x : ℕ} : get (x : PartENat) (dom_natCast x) = x :=
get_natCast' _ _
#align part_enat.get_coe PartENat.get_natCast
theorem coe_add_get {x : ℕ} {y : PartENat} (h : ((x : PartENat) + y).Dom) :
get ((x : PartENat) + y) h = x + get y h.2 := by
rfl
#align part_enat.coe_add_get PartENat.coe_add_get
@[simp]
theorem get_add {x y : PartENat} (h : (x + y).Dom) : get (x + y) h = x.get h.1 + y.get h.2 :=
rfl
#align part_enat.get_add PartENat.get_add
@[simp]
theorem get_zero (h : (0 : PartENat).Dom) : (0 : PartENat).get h = 0 :=
rfl
#align part_enat.get_zero PartENat.get_zero
@[simp]
theorem get_one (h : (1 : PartENat).Dom) : (1 : PartENat).get h = 1 :=
rfl
#align part_enat.get_one PartENat.get_one
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem get_ofNat' (x : ℕ) [x.AtLeastTwo] (h : (no_index (OfNat.ofNat x : PartENat)).Dom) :
Part.get (no_index (OfNat.ofNat x : PartENat)) h = (no_index (OfNat.ofNat x)) :=
get_natCast' x h
nonrec theorem get_eq_iff_eq_some {a : PartENat} {ha : a.Dom} {b : ℕ} : a.get ha = b ↔ a = some b :=
get_eq_iff_eq_some
#align part_enat.get_eq_iff_eq_some PartENat.get_eq_iff_eq_some
theorem get_eq_iff_eq_coe {a : PartENat} {ha : a.Dom} {b : ℕ} : a.get ha = b ↔ a = b := by
rw [get_eq_iff_eq_some]
rfl
#align part_enat.get_eq_iff_eq_coe PartENat.get_eq_iff_eq_coe
theorem dom_of_le_of_dom {x y : PartENat} : x ≤ y → y.Dom → x.Dom := fun ⟨h, _⟩ => h
#align part_enat.dom_of_le_of_dom PartENat.dom_of_le_of_dom
theorem dom_of_le_some {x : PartENat} {y : ℕ} (h : x ≤ some y) : x.Dom :=
dom_of_le_of_dom h trivial
#align part_enat.dom_of_le_some PartENat.dom_of_le_some
theorem dom_of_le_natCast {x : PartENat} {y : ℕ} (h : x ≤ y) : x.Dom := by
exact dom_of_le_some h
#align part_enat.dom_of_le_coe PartENat.dom_of_le_natCast
instance decidableLe (x y : PartENat) [Decidable x.Dom] [Decidable y.Dom] : Decidable (x ≤ y) :=
if hx : x.Dom then
decidable_of_decidable_of_iff (by rw [le_def])
else
if hy : y.Dom then isFalse fun h => hx <| dom_of_le_of_dom h hy
else isTrue ⟨fun h => (hy h).elim, fun h => (hy h).elim⟩
#align part_enat.decidable_le PartENat.decidableLe
-- Porting note: Removed. Use `Nat.castAddMonoidHom` instead.
#noalign part_enat.coe_hom
#noalign part_enat.coe_coe_hom
instance partialOrder : PartialOrder PartENat where
le := (· ≤ ·)
le_refl _ := ⟨id, fun _ => le_rfl⟩
le_trans := fun _ _ _ ⟨hxy₁, hxy₂⟩ ⟨hyz₁, hyz₂⟩ =>
⟨hxy₁ ∘ hyz₁, fun _ => le_trans (hxy₂ _) (hyz₂ _)⟩
lt_iff_le_not_le _ _ := Iff.rfl
le_antisymm := fun _ _ ⟨hxy₁, hxy₂⟩ ⟨hyx₁, hyx₂⟩ =>
Part.ext' ⟨hyx₁, hxy₁⟩ fun _ _ => le_antisymm (hxy₂ _) (hyx₂ _)
theorem lt_def (x y : PartENat) : x < y ↔ ∃ hx : x.Dom, ∀ hy : y.Dom, x.get hx < y.get hy := by
rw [lt_iff_le_not_le, le_def, le_def, not_exists]
constructor
· rintro ⟨⟨hyx, H⟩, h⟩
by_cases hx : x.Dom
· use hx
intro hy
specialize H hy
specialize h fun _ => hy
rw [not_forall] at h
cases' h with hx' h
rw [not_le] at h
exact h
· specialize h fun hx' => (hx hx').elim
rw [not_forall] at h
cases' h with hx' h
exact (hx hx').elim
· rintro ⟨hx, H⟩
exact ⟨⟨fun _ => hx, fun hy => (H hy).le⟩, fun hxy h => not_lt_of_le (h _) (H _)⟩
#align part_enat.lt_def PartENat.lt_def
noncomputable instance orderedAddCommMonoid : OrderedAddCommMonoid PartENat :=
{ PartENat.partialOrder, PartENat.addCommMonoid with
add_le_add_left := fun a b ⟨h₁, h₂⟩ c =>
PartENat.casesOn c (by simp [top_add]) fun c =>
⟨fun h => And.intro (dom_natCast _) (h₁ h.2), fun h => by
simpa only [coe_add_get] using add_le_add_left (h₂ _) c⟩ }
instance semilatticeSup : SemilatticeSup PartENat :=
{ PartENat.partialOrder with
sup := (· ⊔ ·)
le_sup_left := fun _ _ => ⟨And.left, fun _ => le_sup_left⟩
le_sup_right := fun _ _ => ⟨And.right, fun _ => le_sup_right⟩
sup_le := fun _ _ _ ⟨hx₁, hx₂⟩ ⟨hy₁, hy₂⟩ =>
⟨fun hz => ⟨hx₁ hz, hy₁ hz⟩, fun _ => sup_le (hx₂ _) (hy₂ _)⟩ }
#align part_enat.semilattice_sup PartENat.semilatticeSup
instance orderBot : OrderBot PartENat where
bot := ⊥
bot_le _ := ⟨fun _ => trivial, fun _ => Nat.zero_le _⟩
#align part_enat.order_bot PartENat.orderBot
instance orderTop : OrderTop PartENat where
top := ⊤
le_top _ := ⟨fun h => False.elim h, fun hy => False.elim hy⟩
#align part_enat.order_top PartENat.orderTop
instance : ZeroLEOneClass PartENat where
zero_le_one := bot_le
/-- Alias of `Nat.cast_le` specialized to `PartENat` --/
theorem coe_le_coe {x y : ℕ} : (x : PartENat) ≤ y ↔ x ≤ y := Nat.cast_le
#align part_enat.coe_le_coe PartENat.coe_le_coe
/-- Alias of `Nat.cast_lt` specialized to `PartENat` --/
theorem coe_lt_coe {x y : ℕ} : (x : PartENat) < y ↔ x < y := Nat.cast_lt
#align part_enat.coe_lt_coe PartENat.coe_lt_coe
@[simp]
theorem get_le_get {x y : PartENat} {hx : x.Dom} {hy : y.Dom} : x.get hx ≤ y.get hy ↔ x ≤ y := by
conv =>
lhs
rw [← coe_le_coe, natCast_get, natCast_get]
#align part_enat.get_le_get PartENat.get_le_get
theorem le_coe_iff (x : PartENat) (n : ℕ) : x ≤ n ↔ ∃ h : x.Dom, x.get h ≤ n := by
show (∃ h : True → x.Dom, _) ↔ ∃ h : x.Dom, x.get h ≤ n
simp only [forall_prop_of_true, dom_natCast, get_natCast']
#align part_enat.le_coe_iff PartENat.le_coe_iff
theorem lt_coe_iff (x : PartENat) (n : ℕ) : x < n ↔ ∃ h : x.Dom, x.get h < n := by
simp only [lt_def, forall_prop_of_true, get_natCast', dom_natCast]
#align part_enat.lt_coe_iff PartENat.lt_coe_iff
theorem coe_le_iff (n : ℕ) (x : PartENat) : (n : PartENat) ≤ x ↔ ∀ h : x.Dom, n ≤ x.get h := by
rw [← some_eq_natCast]
simp only [le_def, exists_prop_of_true, dom_some, forall_true_iff]
rfl
#align part_enat.coe_le_iff PartENat.coe_le_iff
theorem coe_lt_iff (n : ℕ) (x : PartENat) : (n : PartENat) < x ↔ ∀ h : x.Dom, n < x.get h := by
rw [← some_eq_natCast]
simp only [lt_def, exists_prop_of_true, dom_some, forall_true_iff]
rfl
#align part_enat.coe_lt_iff PartENat.coe_lt_iff
nonrec theorem eq_zero_iff {x : PartENat} : x = 0 ↔ x ≤ 0 :=
eq_bot_iff
#align part_enat.eq_zero_iff PartENat.eq_zero_iff
theorem ne_zero_iff {x : PartENat} : x ≠ 0 ↔ ⊥ < x :=
bot_lt_iff_ne_bot.symm
#align part_enat.ne_zero_iff PartENat.ne_zero_iff
theorem dom_of_lt {x y : PartENat} : x < y → x.Dom :=
PartENat.casesOn x not_top_lt fun _ _ => dom_natCast _
#align part_enat.dom_of_lt PartENat.dom_of_lt
theorem top_eq_none : (⊤ : PartENat) = Part.none :=
rfl
#align part_enat.top_eq_none PartENat.top_eq_none
@[simp]
theorem natCast_lt_top (x : ℕ) : (x : PartENat) < ⊤ :=
Ne.lt_top fun h => absurd (congr_arg Dom h) <| by simp only [dom_natCast]; exact true_ne_false
#align part_enat.coe_lt_top PartENat.natCast_lt_top
@[simp]
theorem zero_lt_top : (0 : PartENat) < ⊤ :=
natCast_lt_top 0
@[simp]
theorem one_lt_top : (1 : PartENat) < ⊤ :=
natCast_lt_top 1
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem ofNat_lt_top (x : ℕ) [x.AtLeastTwo] : (no_index (OfNat.ofNat x : PartENat)) < ⊤ :=
natCast_lt_top x
@[simp]
theorem natCast_ne_top (x : ℕ) : (x : PartENat) ≠ ⊤ :=
ne_of_lt (natCast_lt_top x)
#align part_enat.coe_ne_top PartENat.natCast_ne_top
@[simp]
theorem zero_ne_top : (0 : PartENat) ≠ ⊤ :=
natCast_ne_top 0
@[simp]
theorem one_ne_top : (1 : PartENat) ≠ ⊤ :=
natCast_ne_top 1
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem ofNat_ne_top (x : ℕ) [x.AtLeastTwo] : (no_index (OfNat.ofNat x : PartENat)) ≠ ⊤ :=
natCast_ne_top x
theorem not_isMax_natCast (x : ℕ) : ¬IsMax (x : PartENat) :=
not_isMax_of_lt (natCast_lt_top x)
#align part_enat.not_is_max_coe PartENat.not_isMax_natCast
theorem ne_top_iff {x : PartENat} : x ≠ ⊤ ↔ ∃ n : ℕ, x = n := by
simpa only [← some_eq_natCast] using Part.ne_none_iff
#align part_enat.ne_top_iff PartENat.ne_top_iff
theorem ne_top_iff_dom {x : PartENat} : x ≠ ⊤ ↔ x.Dom := by
classical exact not_iff_comm.1 Part.eq_none_iff'.symm
#align part_enat.ne_top_iff_dom PartENat.ne_top_iff_dom
theorem not_dom_iff_eq_top {x : PartENat} : ¬x.Dom ↔ x = ⊤ :=
Iff.not_left ne_top_iff_dom.symm
#align part_enat.not_dom_iff_eq_top PartENat.not_dom_iff_eq_top
theorem ne_top_of_lt {x y : PartENat} (h : x < y) : x ≠ ⊤ :=
ne_of_lt <| lt_of_lt_of_le h le_top
#align part_enat.ne_top_of_lt PartENat.ne_top_of_lt
theorem eq_top_iff_forall_lt (x : PartENat) : x = ⊤ ↔ ∀ n : ℕ, (n : PartENat) < x := by
constructor
· rintro rfl n
exact natCast_lt_top _
· contrapose!
rw [ne_top_iff]
rintro ⟨n, rfl⟩
exact ⟨n, irrefl _⟩
#align part_enat.eq_top_iff_forall_lt PartENat.eq_top_iff_forall_lt
theorem eq_top_iff_forall_le (x : PartENat) : x = ⊤ ↔ ∀ n : ℕ, (n : PartENat) ≤ x :=
(eq_top_iff_forall_lt x).trans
⟨fun h n => (h n).le, fun h n => lt_of_lt_of_le (coe_lt_coe.mpr n.lt_succ_self) (h (n + 1))⟩
#align part_enat.eq_top_iff_forall_le PartENat.eq_top_iff_forall_le
theorem pos_iff_one_le {x : PartENat} : 0 < x ↔ 1 ≤ x :=
PartENat.casesOn x
(by simp only [iff_true_iff, le_top, natCast_lt_top, ← @Nat.cast_zero PartENat])
fun n => by
rw [← Nat.cast_zero, ← Nat.cast_one, PartENat.coe_lt_coe, PartENat.coe_le_coe]
rfl
#align part_enat.pos_iff_one_le PartENat.pos_iff_one_le
instance isTotal : IsTotal PartENat (· ≤ ·) where
total x y :=
PartENat.casesOn (P := fun z => z ≤ y ∨ y ≤ z) x (Or.inr le_top)
(PartENat.casesOn y (fun _ => Or.inl le_top) fun x y =>
(le_total x y).elim (Or.inr ∘ coe_le_coe.2) (Or.inl ∘ coe_le_coe.2))
noncomputable instance linearOrder : LinearOrder PartENat :=
{ PartENat.partialOrder with
le_total := IsTotal.total
decidableLE := Classical.decRel _
max := (· ⊔ ·)
-- Porting note: was `max_def := @sup_eq_maxDefault _ _ (id _) _ }`
max_def := fun a b => by
change (fun a b => a ⊔ b) a b = _
rw [@sup_eq_maxDefault PartENat _ (id _) _]
rfl }
instance boundedOrder : BoundedOrder PartENat :=
{ PartENat.orderTop, PartENat.orderBot with }
noncomputable instance lattice : Lattice PartENat :=
{ PartENat.semilatticeSup with
inf := min
inf_le_left := min_le_left
inf_le_right := min_le_right
le_inf := fun _ _ _ => le_min }
noncomputable instance : CanonicallyOrderedAddCommMonoid PartENat :=
{ PartENat.semilatticeSup, PartENat.orderBot,
PartENat.orderedAddCommMonoid with
le_self_add := fun a b =>
PartENat.casesOn b (le_top.trans_eq (add_top _).symm) fun b =>
PartENat.casesOn a (top_add _).ge fun a =>
(coe_le_coe.2 le_self_add).trans_eq (Nat.cast_add _ _)
exists_add_of_le := fun {a b} =>
PartENat.casesOn b (fun _ => ⟨⊤, (add_top _).symm⟩) fun b =>
PartENat.casesOn a (fun h => ((natCast_lt_top _).not_le h).elim) fun a h =>
⟨(b - a : ℕ), by
rw [← Nat.cast_add, natCast_inj, add_comm, tsub_add_cancel_of_le (coe_le_coe.1 h)]⟩ }
theorem eq_natCast_sub_of_add_eq_natCast {x y : PartENat} {n : ℕ} (h : x + y = n) :
x = ↑(n - y.get (dom_of_le_natCast ((le_add_left le_rfl).trans_eq h))) := by
lift x to ℕ using dom_of_le_natCast ((le_add_right le_rfl).trans_eq h)
lift y to ℕ using dom_of_le_natCast ((le_add_left le_rfl).trans_eq h)
rw [← Nat.cast_add, natCast_inj] at h
rw [get_natCast, natCast_inj, eq_tsub_of_add_eq h]
#align part_enat.eq_coe_sub_of_add_eq_coe PartENat.eq_natCast_sub_of_add_eq_natCast
protected theorem add_lt_add_right {x y z : PartENat} (h : x < y) (hz : z ≠ ⊤) : x + z < y + z := by
rcases ne_top_iff.mp (ne_top_of_lt h) with ⟨m, rfl⟩
rcases ne_top_iff.mp hz with ⟨k, rfl⟩
induction' y using PartENat.casesOn with n
· rw [top_add]
-- Porting note: was apply_mod_cast natCast_lt_top
norm_cast; apply natCast_lt_top
norm_cast at h
-- Porting note: was `apply_mod_cast add_lt_add_right h`
norm_cast; apply add_lt_add_right h
#align part_enat.add_lt_add_right PartENat.add_lt_add_right
protected theorem add_lt_add_iff_right {x y z : PartENat} (hz : z ≠ ⊤) : x + z < y + z ↔ x < y :=
⟨lt_of_add_lt_add_right, fun h => PartENat.add_lt_add_right h hz⟩
#align part_enat.add_lt_add_iff_right PartENat.add_lt_add_iff_right
protected theorem add_lt_add_iff_left {x y z : PartENat} (hz : z ≠ ⊤) : z + x < z + y ↔ x < y := by
rw [add_comm z, add_comm z, PartENat.add_lt_add_iff_right hz]
#align part_enat.add_lt_add_iff_left PartENat.add_lt_add_iff_left
protected theorem lt_add_iff_pos_right {x y : PartENat} (hx : x ≠ ⊤) : x < x + y ↔ 0 < y := by
conv_rhs => rw [← PartENat.add_lt_add_iff_left hx]
rw [add_zero]
#align part_enat.lt_add_iff_pos_right PartENat.lt_add_iff_pos_right
theorem lt_add_one {x : PartENat} (hx : x ≠ ⊤) : x < x + 1 := by
rw [PartENat.lt_add_iff_pos_right hx]
norm_cast
#align part_enat.lt_add_one PartENat.lt_add_one
theorem le_of_lt_add_one {x y : PartENat} (h : x < y + 1) : x ≤ y := by
induction' y using PartENat.casesOn with n
· apply le_top
rcases ne_top_iff.mp (ne_top_of_lt h) with ⟨m, rfl⟩
-- Porting note: was `apply_mod_cast Nat.le_of_lt_succ; apply_mod_cast h`
norm_cast; apply Nat.le_of_lt_succ; norm_cast at h
#align part_enat.le_of_lt_add_one PartENat.le_of_lt_add_one
theorem add_one_le_of_lt {x y : PartENat} (h : x < y) : x + 1 ≤ y := by
induction' y using PartENat.casesOn with n
· apply le_top
rcases ne_top_iff.mp (ne_top_of_lt h) with ⟨m, rfl⟩
-- Porting note: was `apply_mod_cast Nat.succ_le_of_lt; apply_mod_cast h`
norm_cast; apply Nat.succ_le_of_lt; norm_cast at h
#align part_enat.add_one_le_of_lt PartENat.add_one_le_of_lt
theorem add_one_le_iff_lt {x y : PartENat} (hx : x ≠ ⊤) : x + 1 ≤ y ↔ x < y := by
refine ⟨fun h => ?_, add_one_le_of_lt⟩
rcases ne_top_iff.mp hx with ⟨m, rfl⟩
induction' y using PartENat.casesOn with n
· apply natCast_lt_top
-- Porting note: was `apply_mod_cast Nat.lt_of_succ_le; apply_mod_cast h`
norm_cast; apply Nat.lt_of_succ_le; norm_cast at h
#align part_enat.add_one_le_iff_lt PartENat.add_one_le_iff_lt
theorem coe_succ_le_iff {n : ℕ} {e : PartENat} : ↑n.succ ≤ e ↔ ↑n < e := by
rw [Nat.succ_eq_add_one n, Nat.cast_add, Nat.cast_one, add_one_le_iff_lt (natCast_ne_top n)]
#align part_enat.coe_succ_le_succ_iff PartENat.coe_succ_le_iff
theorem lt_add_one_iff_lt {x y : PartENat} (hx : x ≠ ⊤) : x < y + 1 ↔ x ≤ y := by
refine ⟨le_of_lt_add_one, fun h => ?_⟩
rcases ne_top_iff.mp hx with ⟨m, rfl⟩
induction' y using PartENat.casesOn with n
· rw [top_add]
apply natCast_lt_top
-- Porting note: was `apply_mod_cast Nat.lt_succ_of_le; apply_mod_cast h`
norm_cast; apply Nat.lt_succ_of_le; norm_cast at h
#align part_enat.lt_add_one_iff_lt PartENat.lt_add_one_iff_lt
lemma lt_coe_succ_iff_le {x : PartENat} {n : ℕ} (hx : x ≠ ⊤) : x < n.succ ↔ x ≤ n := by
rw [Nat.succ_eq_add_one n, Nat.cast_add, Nat.cast_one, lt_add_one_iff_lt hx]
#align part_enat.lt_coe_succ_iff_le PartENat.lt_coe_succ_iff_le
theorem add_eq_top_iff {a b : PartENat} : a + b = ⊤ ↔ a = ⊤ ∨ b = ⊤ := by
refine PartENat.casesOn a ?_ ?_
<;> refine PartENat.casesOn b ?_ ?_
<;> simp [top_add, add_top]
simp only [← Nat.cast_add, PartENat.natCast_ne_top, forall_const, not_false_eq_true]
#align part_enat.add_eq_top_iff PartENat.add_eq_top_iff
protected theorem add_right_cancel_iff {a b c : PartENat} (hc : c ≠ ⊤) : a + c = b + c ↔ a = b := by
rcases ne_top_iff.1 hc with ⟨c, rfl⟩
refine PartENat.casesOn a ?_ ?_
<;> refine PartENat.casesOn b ?_ ?_
<;> simp [add_eq_top_iff, natCast_ne_top, @eq_comm _ (⊤ : PartENat), top_add]
simp only [← Nat.cast_add, add_left_cancel_iff, PartENat.natCast_inj, add_comm, forall_const]
#align part_enat.add_right_cancel_iff PartENat.add_right_cancel_iff
protected theorem add_left_cancel_iff {a b c : PartENat} (ha : a ≠ ⊤) : a + b = a + c ↔ b = c := by
rw [add_comm a, add_comm a, PartENat.add_right_cancel_iff ha]
#align part_enat.add_left_cancel_iff PartENat.add_left_cancel_iff
section WithTop
/-- Computably converts a `PartENat` to a `ℕ∞`. -/
def toWithTop (x : PartENat) [Decidable x.Dom] : ℕ∞ :=
x.toOption
#align part_enat.to_with_top PartENat.toWithTop
theorem toWithTop_top :
have : Decidable (⊤ : PartENat).Dom := Part.noneDecidable
toWithTop ⊤ = ⊤ :=
rfl
#align part_enat.to_with_top_top PartENat.toWithTop_top
@[simp]
theorem toWithTop_top' {h : Decidable (⊤ : PartENat).Dom} : toWithTop ⊤ = ⊤ := by
convert toWithTop_top
#align part_enat.to_with_top_top' PartENat.toWithTop_top'
theorem toWithTop_zero :
have : Decidable (0 : PartENat).Dom := someDecidable 0
toWithTop 0 = 0 :=
rfl
#align part_enat.to_with_top_zero PartENat.toWithTop_zero
@[simp]
theorem toWithTop_zero' {h : Decidable (0 : PartENat).Dom} : toWithTop 0 = 0 := by
convert toWithTop_zero
#align part_enat.to_with_top_zero' PartENat.toWithTop_zero'
theorem toWithTop_one :
have : Decidable (1 : PartENat).Dom := someDecidable 1
toWithTop 1 = 1 :=
rfl
@[simp]
theorem toWithTop_one' {h : Decidable (1 : PartENat).Dom} : toWithTop 1 = 1 := by
convert toWithTop_one
theorem toWithTop_some (n : ℕ) : toWithTop (some n) = n :=
rfl
#align part_enat.to_with_top_some PartENat.toWithTop_some
theorem toWithTop_natCast (n : ℕ) {_ : Decidable (n : PartENat).Dom} : toWithTop n = n := by
simp only [← toWithTop_some]
congr
#align part_enat.to_with_top_coe PartENat.toWithTop_natCast
@[simp]
theorem toWithTop_natCast' (n : ℕ) {_ : Decidable (n : PartENat).Dom} :
toWithTop (n : PartENat) = n := by
rw [toWithTop_natCast n]
#align part_enat.to_with_top_coe' PartENat.toWithTop_natCast'
@[simp]
theorem toWithTop_ofNat (n : ℕ) [n.AtLeastTwo] {_ : Decidable (OfNat.ofNat n : PartENat).Dom} :
toWithTop (no_index (OfNat.ofNat n : PartENat)) = OfNat.ofNat n := toWithTop_natCast' n
-- Porting note: statement changed. Mathlib 3 statement was
-- ```
-- @[simp] lemma to_with_top_le {x y : part_enat} :
-- Π [decidable x.dom] [decidable y.dom], by exactI to_with_top x ≤ to_with_top y ↔ x ≤ y :=
-- ```
-- This used to be really slow to typecheck when the definition of `ENat`
-- was still `deriving AddCommMonoidWithOne`. Now that I removed that it is fine.
-- (The problem was that the last `simp` got stuck at `CharZero ℕ∞ ≟ CharZero ℕ∞` where
-- one side used `instENatAddCommMonoidWithOne` and the other used
-- `NonAssocSemiring.toAddCommMonoidWithOne`. Now the former doesn't exist anymore.)
@[simp]
theorem toWithTop_le {x y : PartENat} [hx : Decidable x.Dom] [hy : Decidable y.Dom] :
toWithTop x ≤ toWithTop y ↔ x ≤ y := by
induction y using PartENat.casesOn generalizing hy
· simp
induction x using PartENat.casesOn generalizing hx
· simp
· simp -- Porting note: this takes too long.
#align part_enat.to_with_top_le PartENat.toWithTop_le
/-
Porting note: As part of the investigation above, I noticed that Lean4 does not
find the following two instances which it could find in Lean3 automatically:
```
#synth Decidable (⊤ : PartENat).Dom
variable {n : ℕ}
#synth Decidable (n : PartENat).Dom
```
-/
@[simp]
theorem toWithTop_lt {x y : PartENat} [Decidable x.Dom] [Decidable y.Dom] :
toWithTop x < toWithTop y ↔ x < y :=
lt_iff_lt_of_le_iff_le toWithTop_le
#align part_enat.to_with_top_lt PartENat.toWithTop_lt
end WithTop
-- Porting note: new, extracted from `withTopEquiv`.
/-- Coercion from `ℕ∞` to `PartENat`. -/
@[coe]
def ofENat : ℕ∞ → PartENat :=
fun x => match x with
| Option.none => none
| Option.some n => some n
-- Porting note (#10754): new instance
instance : Coe ℕ∞ PartENat := ⟨ofENat⟩
-- Porting note: new. This could probably be moved to tests or removed.
example (n : ℕ) : ((n : ℕ∞) : PartENat) = ↑n := rfl
-- Porting note (#10756): new lemma
@[simp, norm_cast]
lemma ofENat_top : ofENat ⊤ = ⊤ := rfl
-- Porting note (#10756): new lemma
@[simp, norm_cast]
lemma ofENat_coe (n : ℕ) : ofENat n = n := rfl
@[simp, norm_cast]
theorem ofENat_zero : ofENat 0 = 0 := rfl
@[simp, norm_cast]
theorem ofENat_one : ofENat 1 = 1 := rfl
@[simp, norm_cast]
theorem ofENat_ofNat (n : Nat) [n.AtLeastTwo] : ofENat (no_index (OfNat.ofNat n)) = OfNat.ofNat n :=
rfl
-- Porting note (#10756): new theorem
@[simp, norm_cast]
theorem toWithTop_ofENat (n : ℕ∞) {_ : Decidable (n : PartENat).Dom} : toWithTop (↑n) = n := by
cases n with
| top => simp
| coe n => simp
@[simp, norm_cast]
theorem ofENat_toWithTop (x : PartENat) {_ : Decidable (x : PartENat).Dom} : toWithTop x = x := by
induction x using PartENat.casesOn <;> simp
@[simp, norm_cast]
theorem ofENat_le {x y : ℕ∞} : ofENat x ≤ ofENat y ↔ x ≤ y := by
classical
rw [← toWithTop_le, toWithTop_ofENat, toWithTop_ofENat]
@[simp, norm_cast]
theorem ofENat_lt {x y : ℕ∞} : ofENat x < ofENat y ↔ x < y := by
classical
rw [← toWithTop_lt, toWithTop_ofENat, toWithTop_ofENat]
section WithTopEquiv
open scoped Classical
@[simp]
theorem toWithTop_add {x y : PartENat} : toWithTop (x + y) = toWithTop x + toWithTop y := by
refine PartENat.casesOn y ?_ ?_ <;> refine PartENat.casesOn x ?_ ?_
-- Porting note: was `simp [← Nat.cast_add, ← ENat.coe_add]`
· simp only [add_top, toWithTop_top', _root_.add_top]
· simp only [add_top, toWithTop_top', toWithTop_natCast', _root_.add_top, forall_const]
· simp only [top_add, toWithTop_top', toWithTop_natCast', _root_.top_add, forall_const]
· simp_rw [toWithTop_natCast', ← Nat.cast_add, toWithTop_natCast', forall_const]
#align part_enat.to_with_top_add PartENat.toWithTop_add
/-- `Equiv` between `PartENat` and `ℕ∞` (for the order isomorphism see
`withTopOrderIso`). -/
@[simps]
noncomputable def withTopEquiv : PartENat ≃ ℕ∞ where
toFun x := toWithTop x
invFun x := ↑x
left_inv x := by simp
right_inv x := by simp
#align part_enat.with_top_equiv PartENat.withTopEquiv
theorem withTopEquiv_top : withTopEquiv ⊤ = ⊤ := by
simp
#align part_enat.with_top_equiv_top PartENat.withTopEquiv_top
theorem withTopEquiv_natCast (n : Nat) : withTopEquiv n = n := by
simp
#align part_enat.with_top_equiv_coe PartENat.withTopEquiv_natCast
theorem withTopEquiv_zero : withTopEquiv 0 = 0 := by
simp
#align part_enat.with_top_equiv_zero PartENat.withTopEquiv_zero
theorem withTopEquiv_one : withTopEquiv 1 = 1 := by
simp
theorem withTopEquiv_ofNat (n : Nat) [n.AtLeastTwo] :
withTopEquiv (no_index (OfNat.ofNat n)) = OfNat.ofNat n := by
simp
theorem withTopEquiv_le {x y : PartENat} : withTopEquiv x ≤ withTopEquiv y ↔ x ≤ y := by
simp
#align part_enat.with_top_equiv_le PartENat.withTopEquiv_le
| Mathlib/Data/Nat/PartENat.lean | 775 | 776 | theorem withTopEquiv_lt {x y : PartENat} : withTopEquiv x < withTopEquiv y ↔ x < y := by |
simp
|
/-
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, Yury Kudryashov, Patrick Massot
-/
import Mathlib.Algebra.BigOperators.Group.Finset
import Mathlib.Algebra.Order.Field.Defs
import Mathlib.Algebra.Order.Group.Instances
import Mathlib.Algebra.Order.Group.MinMax
import Mathlib.Algebra.Order.Ring.Basic
import Mathlib.Data.Finset.Preimage
import Mathlib.Order.Interval.Set.Disjoint
import Mathlib.Order.Interval.Set.OrderIso
import Mathlib.Order.ConditionallyCompleteLattice.Basic
import Mathlib.Order.Filter.Bases
#align_import order.filter.at_top_bot from "leanprover-community/mathlib"@"1f0096e6caa61e9c849ec2adbd227e960e9dff58"
/-!
# `Filter.atTop` and `Filter.atBot` filters on preorders, monoids and groups.
In this file we define the filters
* `Filter.atTop`: corresponds to `n → +∞`;
* `Filter.atBot`: corresponds to `n → -∞`.
Then we prove many lemmas like “if `f → +∞`, then `f ± c → +∞`”.
-/
set_option autoImplicit true
variable {ι ι' α β γ : Type*}
open Set
namespace Filter
/-- `atTop` is the filter representing the limit `→ ∞` on an ordered set.
It is generated by the collection of up-sets `{b | a ≤ b}`.
(The preorder need not have a top element for this to be well defined,
and indeed is trivial when a top element exists.) -/
def atTop [Preorder α] : Filter α :=
⨅ a, 𝓟 (Ici a)
#align filter.at_top Filter.atTop
/-- `atBot` is the filter representing the limit `→ -∞` on an ordered set.
It is generated by the collection of down-sets `{b | b ≤ a}`.
(The preorder need not have a bottom element for this to be well defined,
and indeed is trivial when a bottom element exists.) -/
def atBot [Preorder α] : Filter α :=
⨅ a, 𝓟 (Iic a)
#align filter.at_bot Filter.atBot
theorem mem_atTop [Preorder α] (a : α) : { b : α | a ≤ b } ∈ @atTop α _ :=
mem_iInf_of_mem a <| Subset.refl _
#align filter.mem_at_top Filter.mem_atTop
theorem Ici_mem_atTop [Preorder α] (a : α) : Ici a ∈ (atTop : Filter α) :=
mem_atTop a
#align filter.Ici_mem_at_top Filter.Ici_mem_atTop
theorem Ioi_mem_atTop [Preorder α] [NoMaxOrder α] (x : α) : Ioi x ∈ (atTop : Filter α) :=
let ⟨z, hz⟩ := exists_gt x
mem_of_superset (mem_atTop z) fun _ h => lt_of_lt_of_le hz h
#align filter.Ioi_mem_at_top Filter.Ioi_mem_atTop
theorem mem_atBot [Preorder α] (a : α) : { b : α | b ≤ a } ∈ @atBot α _ :=
mem_iInf_of_mem a <| Subset.refl _
#align filter.mem_at_bot Filter.mem_atBot
theorem Iic_mem_atBot [Preorder α] (a : α) : Iic a ∈ (atBot : Filter α) :=
mem_atBot a
#align filter.Iic_mem_at_bot Filter.Iic_mem_atBot
theorem Iio_mem_atBot [Preorder α] [NoMinOrder α] (x : α) : Iio x ∈ (atBot : Filter α) :=
let ⟨z, hz⟩ := exists_lt x
mem_of_superset (mem_atBot z) fun _ h => lt_of_le_of_lt h hz
#align filter.Iio_mem_at_bot Filter.Iio_mem_atBot
theorem disjoint_atBot_principal_Ioi [Preorder α] (x : α) : Disjoint atBot (𝓟 (Ioi x)) :=
disjoint_of_disjoint_of_mem (Iic_disjoint_Ioi le_rfl) (Iic_mem_atBot x) (mem_principal_self _)
#align filter.disjoint_at_bot_principal_Ioi Filter.disjoint_atBot_principal_Ioi
theorem disjoint_atTop_principal_Iio [Preorder α] (x : α) : Disjoint atTop (𝓟 (Iio x)) :=
@disjoint_atBot_principal_Ioi αᵒᵈ _ _
#align filter.disjoint_at_top_principal_Iio Filter.disjoint_atTop_principal_Iio
theorem disjoint_atTop_principal_Iic [Preorder α] [NoMaxOrder α] (x : α) :
Disjoint atTop (𝓟 (Iic x)) :=
disjoint_of_disjoint_of_mem (Iic_disjoint_Ioi le_rfl).symm (Ioi_mem_atTop x)
(mem_principal_self _)
#align filter.disjoint_at_top_principal_Iic Filter.disjoint_atTop_principal_Iic
theorem disjoint_atBot_principal_Ici [Preorder α] [NoMinOrder α] (x : α) :
Disjoint atBot (𝓟 (Ici x)) :=
@disjoint_atTop_principal_Iic αᵒᵈ _ _ _
#align filter.disjoint_at_bot_principal_Ici Filter.disjoint_atBot_principal_Ici
theorem disjoint_pure_atTop [Preorder α] [NoMaxOrder α] (x : α) : Disjoint (pure x) atTop :=
Disjoint.symm <| (disjoint_atTop_principal_Iic x).mono_right <| le_principal_iff.2 <|
mem_pure.2 right_mem_Iic
#align filter.disjoint_pure_at_top Filter.disjoint_pure_atTop
theorem disjoint_pure_atBot [Preorder α] [NoMinOrder α] (x : α) : Disjoint (pure x) atBot :=
@disjoint_pure_atTop αᵒᵈ _ _ _
#align filter.disjoint_pure_at_bot Filter.disjoint_pure_atBot
theorem not_tendsto_const_atTop [Preorder α] [NoMaxOrder α] (x : α) (l : Filter β) [l.NeBot] :
¬Tendsto (fun _ => x) l atTop :=
tendsto_const_pure.not_tendsto (disjoint_pure_atTop x)
#align filter.not_tendsto_const_at_top Filter.not_tendsto_const_atTop
theorem not_tendsto_const_atBot [Preorder α] [NoMinOrder α] (x : α) (l : Filter β) [l.NeBot] :
¬Tendsto (fun _ => x) l atBot :=
tendsto_const_pure.not_tendsto (disjoint_pure_atBot x)
#align filter.not_tendsto_const_at_bot Filter.not_tendsto_const_atBot
theorem disjoint_atBot_atTop [PartialOrder α] [Nontrivial α] :
Disjoint (atBot : Filter α) atTop := by
rcases exists_pair_ne α with ⟨x, y, hne⟩
by_cases hle : x ≤ y
· refine disjoint_of_disjoint_of_mem ?_ (Iic_mem_atBot x) (Ici_mem_atTop y)
exact Iic_disjoint_Ici.2 (hle.lt_of_ne hne).not_le
· refine disjoint_of_disjoint_of_mem ?_ (Iic_mem_atBot y) (Ici_mem_atTop x)
exact Iic_disjoint_Ici.2 hle
#align filter.disjoint_at_bot_at_top Filter.disjoint_atBot_atTop
theorem disjoint_atTop_atBot [PartialOrder α] [Nontrivial α] : Disjoint (atTop : Filter α) atBot :=
disjoint_atBot_atTop.symm
#align filter.disjoint_at_top_at_bot Filter.disjoint_atTop_atBot
theorem hasAntitoneBasis_atTop [Nonempty α] [Preorder α] [IsDirected α (· ≤ ·)] :
(@atTop α _).HasAntitoneBasis Ici :=
.iInf_principal fun _ _ ↦ Ici_subset_Ici.2
theorem atTop_basis [Nonempty α] [SemilatticeSup α] : (@atTop α _).HasBasis (fun _ => True) Ici :=
hasAntitoneBasis_atTop.1
#align filter.at_top_basis Filter.atTop_basis
theorem atTop_eq_generate_Ici [SemilatticeSup α] : atTop = generate (range (Ici (α := α))) := by
rcases isEmpty_or_nonempty α with hα|hα
· simp only [eq_iff_true_of_subsingleton]
· simp [(atTop_basis (α := α)).eq_generate, range]
theorem atTop_basis' [SemilatticeSup α] (a : α) : (@atTop α _).HasBasis (fun x => a ≤ x) Ici :=
⟨fun _ =>
(@atTop_basis α ⟨a⟩ _).mem_iff.trans
⟨fun ⟨x, _, hx⟩ => ⟨x ⊔ a, le_sup_right, fun _y hy => hx (le_trans le_sup_left hy)⟩,
fun ⟨x, _, hx⟩ => ⟨x, trivial, hx⟩⟩⟩
#align filter.at_top_basis' Filter.atTop_basis'
theorem atBot_basis [Nonempty α] [SemilatticeInf α] : (@atBot α _).HasBasis (fun _ => True) Iic :=
@atTop_basis αᵒᵈ _ _
#align filter.at_bot_basis Filter.atBot_basis
theorem atBot_basis' [SemilatticeInf α] (a : α) : (@atBot α _).HasBasis (fun x => x ≤ a) Iic :=
@atTop_basis' αᵒᵈ _ _
#align filter.at_bot_basis' Filter.atBot_basis'
@[instance]
theorem atTop_neBot [Nonempty α] [SemilatticeSup α] : NeBot (atTop : Filter α) :=
atTop_basis.neBot_iff.2 fun _ => nonempty_Ici
#align filter.at_top_ne_bot Filter.atTop_neBot
@[instance]
theorem atBot_neBot [Nonempty α] [SemilatticeInf α] : NeBot (atBot : Filter α) :=
@atTop_neBot αᵒᵈ _ _
#align filter.at_bot_ne_bot Filter.atBot_neBot
@[simp]
theorem mem_atTop_sets [Nonempty α] [SemilatticeSup α] {s : Set α} :
s ∈ (atTop : Filter α) ↔ ∃ a : α, ∀ b ≥ a, b ∈ s :=
atTop_basis.mem_iff.trans <| exists_congr fun _ => true_and_iff _
#align filter.mem_at_top_sets Filter.mem_atTop_sets
@[simp]
theorem mem_atBot_sets [Nonempty α] [SemilatticeInf α] {s : Set α} :
s ∈ (atBot : Filter α) ↔ ∃ a : α, ∀ b ≤ a, b ∈ s :=
@mem_atTop_sets αᵒᵈ _ _ _
#align filter.mem_at_bot_sets Filter.mem_atBot_sets
@[simp]
theorem eventually_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop} :
(∀ᶠ x in atTop, p x) ↔ ∃ a, ∀ b ≥ a, p b :=
mem_atTop_sets
#align filter.eventually_at_top Filter.eventually_atTop
@[simp]
theorem eventually_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop} :
(∀ᶠ x in atBot, p x) ↔ ∃ a, ∀ b ≤ a, p b :=
mem_atBot_sets
#align filter.eventually_at_bot Filter.eventually_atBot
theorem eventually_ge_atTop [Preorder α] (a : α) : ∀ᶠ x in atTop, a ≤ x :=
mem_atTop a
#align filter.eventually_ge_at_top Filter.eventually_ge_atTop
theorem eventually_le_atBot [Preorder α] (a : α) : ∀ᶠ x in atBot, x ≤ a :=
mem_atBot a
#align filter.eventually_le_at_bot Filter.eventually_le_atBot
theorem eventually_gt_atTop [Preorder α] [NoMaxOrder α] (a : α) : ∀ᶠ x in atTop, a < x :=
Ioi_mem_atTop a
#align filter.eventually_gt_at_top Filter.eventually_gt_atTop
theorem eventually_ne_atTop [Preorder α] [NoMaxOrder α] (a : α) : ∀ᶠ x in atTop, x ≠ a :=
(eventually_gt_atTop a).mono fun _ => ne_of_gt
#align filter.eventually_ne_at_top Filter.eventually_ne_atTop
protected theorem Tendsto.eventually_gt_atTop [Preorder β] [NoMaxOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, c < f x :=
hf.eventually (eventually_gt_atTop c)
#align filter.tendsto.eventually_gt_at_top Filter.Tendsto.eventually_gt_atTop
protected theorem Tendsto.eventually_ge_atTop [Preorder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, c ≤ f x :=
hf.eventually (eventually_ge_atTop c)
#align filter.tendsto.eventually_ge_at_top Filter.Tendsto.eventually_ge_atTop
protected theorem Tendsto.eventually_ne_atTop [Preorder β] [NoMaxOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, f x ≠ c :=
hf.eventually (eventually_ne_atTop c)
#align filter.tendsto.eventually_ne_at_top Filter.Tendsto.eventually_ne_atTop
protected theorem Tendsto.eventually_ne_atTop' [Preorder β] [NoMaxOrder β] {f : α → β}
{l : Filter α} (hf : Tendsto f l atTop) (c : α) : ∀ᶠ x in l, x ≠ c :=
(hf.eventually_ne_atTop (f c)).mono fun _ => ne_of_apply_ne f
#align filter.tendsto.eventually_ne_at_top' Filter.Tendsto.eventually_ne_atTop'
theorem eventually_lt_atBot [Preorder α] [NoMinOrder α] (a : α) : ∀ᶠ x in atBot, x < a :=
Iio_mem_atBot a
#align filter.eventually_lt_at_bot Filter.eventually_lt_atBot
theorem eventually_ne_atBot [Preorder α] [NoMinOrder α] (a : α) : ∀ᶠ x in atBot, x ≠ a :=
(eventually_lt_atBot a).mono fun _ => ne_of_lt
#align filter.eventually_ne_at_bot Filter.eventually_ne_atBot
protected theorem Tendsto.eventually_lt_atBot [Preorder β] [NoMinOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x < c :=
hf.eventually (eventually_lt_atBot c)
#align filter.tendsto.eventually_lt_at_bot Filter.Tendsto.eventually_lt_atBot
protected theorem Tendsto.eventually_le_atBot [Preorder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x ≤ c :=
hf.eventually (eventually_le_atBot c)
#align filter.tendsto.eventually_le_at_bot Filter.Tendsto.eventually_le_atBot
protected theorem Tendsto.eventually_ne_atBot [Preorder β] [NoMinOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x ≠ c :=
hf.eventually (eventually_ne_atBot c)
#align filter.tendsto.eventually_ne_at_bot Filter.Tendsto.eventually_ne_atBot
theorem eventually_forall_ge_atTop [Preorder α] {p : α → Prop} :
(∀ᶠ x in atTop, ∀ y, x ≤ y → p y) ↔ ∀ᶠ x in atTop, p x := by
refine ⟨fun h ↦ h.mono fun x hx ↦ hx x le_rfl, fun h ↦ ?_⟩
rcases (hasBasis_iInf_principal_finite _).eventually_iff.1 h with ⟨S, hSf, hS⟩
refine mem_iInf_of_iInter hSf (V := fun x ↦ Ici x.1) (fun _ ↦ Subset.rfl) fun x hx y hy ↦ ?_
simp only [mem_iInter] at hS hx
exact hS fun z hz ↦ le_trans (hx ⟨z, hz⟩) hy
theorem eventually_forall_le_atBot [Preorder α] {p : α → Prop} :
(∀ᶠ x in atBot, ∀ y, y ≤ x → p y) ↔ ∀ᶠ x in atBot, p x :=
eventually_forall_ge_atTop (α := αᵒᵈ)
theorem Tendsto.eventually_forall_ge_atTop {α β : Type*} [Preorder β] {l : Filter α}
{p : β → Prop} {f : α → β} (hf : Tendsto f l atTop) (h_evtl : ∀ᶠ x in atTop, p x) :
∀ᶠ x in l, ∀ y, f x ≤ y → p y := by
rw [← Filter.eventually_forall_ge_atTop] at h_evtl; exact (h_evtl.comap f).filter_mono hf.le_comap
theorem Tendsto.eventually_forall_le_atBot {α β : Type*} [Preorder β] {l : Filter α}
{p : β → Prop} {f : α → β} (hf : Tendsto f l atBot) (h_evtl : ∀ᶠ x in atBot, p x) :
∀ᶠ x in l, ∀ y, y ≤ f x → p y := by
rw [← Filter.eventually_forall_le_atBot] at h_evtl; exact (h_evtl.comap f).filter_mono hf.le_comap
theorem atTop_basis_Ioi [Nonempty α] [SemilatticeSup α] [NoMaxOrder α] :
(@atTop α _).HasBasis (fun _ => True) Ioi :=
atTop_basis.to_hasBasis (fun a ha => ⟨a, ha, Ioi_subset_Ici_self⟩) fun a ha =>
(exists_gt a).imp fun _b hb => ⟨ha, Ici_subset_Ioi.2 hb⟩
#align filter.at_top_basis_Ioi Filter.atTop_basis_Ioi
lemma atTop_basis_Ioi' [SemilatticeSup α] [NoMaxOrder α] (a : α) : atTop.HasBasis (a < ·) Ioi :=
have : Nonempty α := ⟨a⟩
atTop_basis_Ioi.to_hasBasis (fun b _ ↦
let ⟨c, hc⟩ := exists_gt (a ⊔ b)
⟨c, le_sup_left.trans_lt hc, Ioi_subset_Ioi <| le_sup_right.trans hc.le⟩) fun b _ ↦
⟨b, trivial, Subset.rfl⟩
theorem atTop_countable_basis [Nonempty α] [SemilatticeSup α] [Countable α] :
HasCountableBasis (atTop : Filter α) (fun _ => True) Ici :=
{ atTop_basis with countable := to_countable _ }
#align filter.at_top_countable_basis Filter.atTop_countable_basis
theorem atBot_countable_basis [Nonempty α] [SemilatticeInf α] [Countable α] :
HasCountableBasis (atBot : Filter α) (fun _ => True) Iic :=
{ atBot_basis with countable := to_countable _ }
#align filter.at_bot_countable_basis Filter.atBot_countable_basis
instance (priority := 200) atTop.isCountablyGenerated [Preorder α] [Countable α] :
(atTop : Filter <| α).IsCountablyGenerated :=
isCountablyGenerated_seq _
#align filter.at_top.is_countably_generated Filter.atTop.isCountablyGenerated
instance (priority := 200) atBot.isCountablyGenerated [Preorder α] [Countable α] :
(atBot : Filter <| α).IsCountablyGenerated :=
isCountablyGenerated_seq _
#align filter.at_bot.is_countably_generated Filter.atBot.isCountablyGenerated
theorem _root_.IsTop.atTop_eq [Preorder α] {a : α} (ha : IsTop a) : atTop = 𝓟 (Ici a) :=
(iInf_le _ _).antisymm <| le_iInf fun b ↦ principal_mono.2 <| Ici_subset_Ici.2 <| ha b
theorem _root_.IsBot.atBot_eq [Preorder α] {a : α} (ha : IsBot a) : atBot = 𝓟 (Iic a) :=
ha.toDual.atTop_eq
theorem OrderTop.atTop_eq (α) [PartialOrder α] [OrderTop α] : (atTop : Filter α) = pure ⊤ := by
rw [isTop_top.atTop_eq, Ici_top, principal_singleton]
#align filter.order_top.at_top_eq Filter.OrderTop.atTop_eq
theorem OrderBot.atBot_eq (α) [PartialOrder α] [OrderBot α] : (atBot : Filter α) = pure ⊥ :=
@OrderTop.atTop_eq αᵒᵈ _ _
#align filter.order_bot.at_bot_eq Filter.OrderBot.atBot_eq
@[nontriviality]
theorem Subsingleton.atTop_eq (α) [Subsingleton α] [Preorder α] : (atTop : Filter α) = ⊤ := by
refine top_unique fun s hs x => ?_
rw [atTop, ciInf_subsingleton x, mem_principal] at hs
exact hs left_mem_Ici
#align filter.subsingleton.at_top_eq Filter.Subsingleton.atTop_eq
@[nontriviality]
theorem Subsingleton.atBot_eq (α) [Subsingleton α] [Preorder α] : (atBot : Filter α) = ⊤ :=
@Subsingleton.atTop_eq αᵒᵈ _ _
#align filter.subsingleton.at_bot_eq Filter.Subsingleton.atBot_eq
theorem tendsto_atTop_pure [PartialOrder α] [OrderTop α] (f : α → β) :
Tendsto f atTop (pure <| f ⊤) :=
(OrderTop.atTop_eq α).symm ▸ tendsto_pure_pure _ _
#align filter.tendsto_at_top_pure Filter.tendsto_atTop_pure
theorem tendsto_atBot_pure [PartialOrder α] [OrderBot α] (f : α → β) :
Tendsto f atBot (pure <| f ⊥) :=
@tendsto_atTop_pure αᵒᵈ _ _ _ _
#align filter.tendsto_at_bot_pure Filter.tendsto_atBot_pure
theorem Eventually.exists_forall_of_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop}
(h : ∀ᶠ x in atTop, p x) : ∃ a, ∀ b ≥ a, p b :=
eventually_atTop.mp h
#align filter.eventually.exists_forall_of_at_top Filter.Eventually.exists_forall_of_atTop
theorem Eventually.exists_forall_of_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop}
(h : ∀ᶠ x in atBot, p x) : ∃ a, ∀ b ≤ a, p b :=
eventually_atBot.mp h
#align filter.eventually.exists_forall_of_at_bot Filter.Eventually.exists_forall_of_atBot
lemma exists_eventually_atTop [SemilatticeSup α] [Nonempty α] {r : α → β → Prop} :
(∃ b, ∀ᶠ a in atTop, r a b) ↔ ∀ᶠ a₀ in atTop, ∃ b, ∀ a ≥ a₀, r a b := by
simp_rw [eventually_atTop, ← exists_swap (α := α)]
exact exists_congr fun a ↦ .symm <| forall_ge_iff <| Monotone.exists fun _ _ _ hb H n hn ↦
H n (hb.trans hn)
lemma exists_eventually_atBot [SemilatticeInf α] [Nonempty α] {r : α → β → Prop} :
(∃ b, ∀ᶠ a in atBot, r a b) ↔ ∀ᶠ a₀ in atBot, ∃ b, ∀ a ≤ a₀, r a b := by
simp_rw [eventually_atBot, ← exists_swap (α := α)]
exact exists_congr fun a ↦ .symm <| forall_le_iff <| Antitone.exists fun _ _ _ hb H n hn ↦
H n (hn.trans hb)
theorem frequently_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop} :
(∃ᶠ x in atTop, p x) ↔ ∀ a, ∃ b ≥ a, p b :=
atTop_basis.frequently_iff.trans <| by simp
#align filter.frequently_at_top Filter.frequently_atTop
theorem frequently_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop} :
(∃ᶠ x in atBot, p x) ↔ ∀ a, ∃ b ≤ a, p b :=
@frequently_atTop αᵒᵈ _ _ _
#align filter.frequently_at_bot Filter.frequently_atBot
theorem frequently_atTop' [SemilatticeSup α] [Nonempty α] [NoMaxOrder α] {p : α → Prop} :
(∃ᶠ x in atTop, p x) ↔ ∀ a, ∃ b > a, p b :=
atTop_basis_Ioi.frequently_iff.trans <| by simp
#align filter.frequently_at_top' Filter.frequently_atTop'
theorem frequently_atBot' [SemilatticeInf α] [Nonempty α] [NoMinOrder α] {p : α → Prop} :
(∃ᶠ x in atBot, p x) ↔ ∀ a, ∃ b < a, p b :=
@frequently_atTop' αᵒᵈ _ _ _ _
#align filter.frequently_at_bot' Filter.frequently_atBot'
theorem Frequently.forall_exists_of_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop}
(h : ∃ᶠ x in atTop, p x) : ∀ a, ∃ b ≥ a, p b :=
frequently_atTop.mp h
#align filter.frequently.forall_exists_of_at_top Filter.Frequently.forall_exists_of_atTop
theorem Frequently.forall_exists_of_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop}
(h : ∃ᶠ x in atBot, p x) : ∀ a, ∃ b ≤ a, p b :=
frequently_atBot.mp h
#align filter.frequently.forall_exists_of_at_bot Filter.Frequently.forall_exists_of_atBot
theorem map_atTop_eq [Nonempty α] [SemilatticeSup α] {f : α → β} :
atTop.map f = ⨅ a, 𝓟 (f '' { a' | a ≤ a' }) :=
(atTop_basis.map f).eq_iInf
#align filter.map_at_top_eq Filter.map_atTop_eq
theorem map_atBot_eq [Nonempty α] [SemilatticeInf α] {f : α → β} :
atBot.map f = ⨅ a, 𝓟 (f '' { a' | a' ≤ a }) :=
@map_atTop_eq αᵒᵈ _ _ _ _
#align filter.map_at_bot_eq Filter.map_atBot_eq
theorem tendsto_atTop [Preorder β] {m : α → β} {f : Filter α} :
Tendsto m f atTop ↔ ∀ b, ∀ᶠ a in f, b ≤ m a := by
simp only [atTop, tendsto_iInf, tendsto_principal, mem_Ici]
#align filter.tendsto_at_top Filter.tendsto_atTop
theorem tendsto_atBot [Preorder β] {m : α → β} {f : Filter α} :
Tendsto m f atBot ↔ ∀ b, ∀ᶠ a in f, m a ≤ b :=
@tendsto_atTop α βᵒᵈ _ m f
#align filter.tendsto_at_bot Filter.tendsto_atBot
theorem tendsto_atTop_mono' [Preorder β] (l : Filter α) ⦃f₁ f₂ : α → β⦄ (h : f₁ ≤ᶠ[l] f₂)
(h₁ : Tendsto f₁ l atTop) : Tendsto f₂ l atTop :=
tendsto_atTop.2 fun b => by filter_upwards [tendsto_atTop.1 h₁ b, h] with x using le_trans
#align filter.tendsto_at_top_mono' Filter.tendsto_atTop_mono'
theorem tendsto_atBot_mono' [Preorder β] (l : Filter α) ⦃f₁ f₂ : α → β⦄ (h : f₁ ≤ᶠ[l] f₂) :
Tendsto f₂ l atBot → Tendsto f₁ l atBot :=
@tendsto_atTop_mono' _ βᵒᵈ _ _ _ _ h
#align filter.tendsto_at_bot_mono' Filter.tendsto_atBot_mono'
theorem tendsto_atTop_mono [Preorder β] {l : Filter α} {f g : α → β} (h : ∀ n, f n ≤ g n) :
Tendsto f l atTop → Tendsto g l atTop :=
tendsto_atTop_mono' l <| eventually_of_forall h
#align filter.tendsto_at_top_mono Filter.tendsto_atTop_mono
theorem tendsto_atBot_mono [Preorder β] {l : Filter α} {f g : α → β} (h : ∀ n, f n ≤ g n) :
Tendsto g l atBot → Tendsto f l atBot :=
@tendsto_atTop_mono _ βᵒᵈ _ _ _ _ h
#align filter.tendsto_at_bot_mono Filter.tendsto_atBot_mono
lemma atTop_eq_generate_of_forall_exists_le [LinearOrder α] {s : Set α} (hs : ∀ x, ∃ y ∈ s, x ≤ y) :
(atTop : Filter α) = generate (Ici '' s) := by
rw [atTop_eq_generate_Ici]
apply le_antisymm
· rw [le_generate_iff]
rintro - ⟨y, -, rfl⟩
exact mem_generate_of_mem ⟨y, rfl⟩
· rw [le_generate_iff]
rintro - ⟨x, -, -, rfl⟩
rcases hs x with ⟨y, ys, hy⟩
have A : Ici y ∈ generate (Ici '' s) := mem_generate_of_mem (mem_image_of_mem _ ys)
have B : Ici y ⊆ Ici x := Ici_subset_Ici.2 hy
exact sets_of_superset (generate (Ici '' s)) A B
lemma atTop_eq_generate_of_not_bddAbove [LinearOrder α] {s : Set α} (hs : ¬ BddAbove s) :
(atTop : Filter α) = generate (Ici '' s) := by
refine atTop_eq_generate_of_forall_exists_le fun x ↦ ?_
obtain ⟨y, hy, hy'⟩ := not_bddAbove_iff.mp hs x
exact ⟨y, hy, hy'.le⟩
end Filter
namespace OrderIso
open Filter
variable [Preorder α] [Preorder β]
@[simp]
theorem comap_atTop (e : α ≃o β) : comap e atTop = atTop := by
simp [atTop, ← e.surjective.iInf_comp]
#align order_iso.comap_at_top OrderIso.comap_atTop
@[simp]
theorem comap_atBot (e : α ≃o β) : comap e atBot = atBot :=
e.dual.comap_atTop
#align order_iso.comap_at_bot OrderIso.comap_atBot
@[simp]
theorem map_atTop (e : α ≃o β) : map (e : α → β) atTop = atTop := by
rw [← e.comap_atTop, map_comap_of_surjective e.surjective]
#align order_iso.map_at_top OrderIso.map_atTop
@[simp]
theorem map_atBot (e : α ≃o β) : map (e : α → β) atBot = atBot :=
e.dual.map_atTop
#align order_iso.map_at_bot OrderIso.map_atBot
theorem tendsto_atTop (e : α ≃o β) : Tendsto e atTop atTop :=
e.map_atTop.le
#align order_iso.tendsto_at_top OrderIso.tendsto_atTop
theorem tendsto_atBot (e : α ≃o β) : Tendsto e atBot atBot :=
e.map_atBot.le
#align order_iso.tendsto_at_bot OrderIso.tendsto_atBot
@[simp]
theorem tendsto_atTop_iff {l : Filter γ} {f : γ → α} (e : α ≃o β) :
Tendsto (fun x => e (f x)) l atTop ↔ Tendsto f l atTop := by
rw [← e.comap_atTop, tendsto_comap_iff, Function.comp_def]
#align order_iso.tendsto_at_top_iff OrderIso.tendsto_atTop_iff
@[simp]
theorem tendsto_atBot_iff {l : Filter γ} {f : γ → α} (e : α ≃o β) :
Tendsto (fun x => e (f x)) l atBot ↔ Tendsto f l atBot :=
e.dual.tendsto_atTop_iff
#align order_iso.tendsto_at_bot_iff OrderIso.tendsto_atBot_iff
end OrderIso
namespace Filter
/-!
### Sequences
-/
theorem inf_map_atTop_neBot_iff [SemilatticeSup α] [Nonempty α] {F : Filter β} {u : α → β} :
NeBot (F ⊓ map u atTop) ↔ ∀ U ∈ F, ∀ N, ∃ n ≥ N, u n ∈ U := by
simp_rw [inf_neBot_iff_frequently_left, frequently_map, frequently_atTop]; rfl
#align filter.inf_map_at_top_ne_bot_iff Filter.inf_map_atTop_neBot_iff
theorem inf_map_atBot_neBot_iff [SemilatticeInf α] [Nonempty α] {F : Filter β} {u : α → β} :
NeBot (F ⊓ map u atBot) ↔ ∀ U ∈ F, ∀ N, ∃ n ≤ N, u n ∈ U :=
@inf_map_atTop_neBot_iff αᵒᵈ _ _ _ _ _
#align filter.inf_map_at_bot_ne_bot_iff Filter.inf_map_atBot_neBot_iff
theorem extraction_of_frequently_atTop' {P : ℕ → Prop} (h : ∀ N, ∃ n > N, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) := by
choose u hu hu' using h
refine ⟨fun n => u^[n + 1] 0, strictMono_nat_of_lt_succ fun n => ?_, fun n => ?_⟩
· exact Trans.trans (hu _) (Function.iterate_succ_apply' _ _ _).symm
· simpa only [Function.iterate_succ_apply'] using hu' _
#align filter.extraction_of_frequently_at_top' Filter.extraction_of_frequently_atTop'
theorem extraction_of_frequently_atTop {P : ℕ → Prop} (h : ∃ᶠ n in atTop, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) := by
rw [frequently_atTop'] at h
exact extraction_of_frequently_atTop' h
#align filter.extraction_of_frequently_at_top Filter.extraction_of_frequently_atTop
theorem extraction_of_eventually_atTop {P : ℕ → Prop} (h : ∀ᶠ n in atTop, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) :=
extraction_of_frequently_atTop h.frequently
#align filter.extraction_of_eventually_at_top Filter.extraction_of_eventually_atTop
theorem extraction_forall_of_frequently {P : ℕ → ℕ → Prop} (h : ∀ n, ∃ᶠ k in atTop, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) := by
simp only [frequently_atTop'] at h
choose u hu hu' using h
use (fun n => Nat.recOn n (u 0 0) fun n v => u (n + 1) v : ℕ → ℕ)
constructor
· apply strictMono_nat_of_lt_succ
intro n
apply hu
· intro n
cases n <;> simp [hu']
#align filter.extraction_forall_of_frequently Filter.extraction_forall_of_frequently
theorem extraction_forall_of_eventually {P : ℕ → ℕ → Prop} (h : ∀ n, ∀ᶠ k in atTop, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) :=
extraction_forall_of_frequently fun n => (h n).frequently
#align filter.extraction_forall_of_eventually Filter.extraction_forall_of_eventually
theorem extraction_forall_of_eventually' {P : ℕ → ℕ → Prop} (h : ∀ n, ∃ N, ∀ k ≥ N, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) :=
extraction_forall_of_eventually (by simp [eventually_atTop, h])
#align filter.extraction_forall_of_eventually' Filter.extraction_forall_of_eventually'
theorem Eventually.atTop_of_arithmetic {p : ℕ → Prop} {n : ℕ} (hn : n ≠ 0)
(hp : ∀ k < n, ∀ᶠ a in atTop, p (n * a + k)) : ∀ᶠ a in atTop, p a := by
simp only [eventually_atTop] at hp ⊢
choose! N hN using hp
refine ⟨(Finset.range n).sup (n * N ·), fun b hb => ?_⟩
rw [← Nat.div_add_mod b n]
have hlt := Nat.mod_lt b hn.bot_lt
refine hN _ hlt _ ?_
rw [ge_iff_le, Nat.le_div_iff_mul_le hn.bot_lt, mul_comm]
exact (Finset.le_sup (f := (n * N ·)) (Finset.mem_range.2 hlt)).trans hb
theorem exists_le_of_tendsto_atTop [SemilatticeSup α] [Preorder β] {u : α → β}
(h : Tendsto u atTop atTop) (a : α) (b : β) : ∃ a' ≥ a, b ≤ u a' := by
have : Nonempty α := ⟨a⟩
have : ∀ᶠ x in atTop, a ≤ x ∧ b ≤ u x :=
(eventually_ge_atTop a).and (h.eventually <| eventually_ge_atTop b)
exact this.exists
#align filter.exists_le_of_tendsto_at_top Filter.exists_le_of_tendsto_atTop
-- @[nolint ge_or_gt] -- Porting note: restore attribute
theorem exists_le_of_tendsto_atBot [SemilatticeSup α] [Preorder β] {u : α → β}
(h : Tendsto u atTop atBot) : ∀ a b, ∃ a' ≥ a, u a' ≤ b :=
@exists_le_of_tendsto_atTop _ βᵒᵈ _ _ _ h
#align filter.exists_le_of_tendsto_at_bot Filter.exists_le_of_tendsto_atBot
theorem exists_lt_of_tendsto_atTop [SemilatticeSup α] [Preorder β] [NoMaxOrder β] {u : α → β}
(h : Tendsto u atTop atTop) (a : α) (b : β) : ∃ a' ≥ a, b < u a' := by
cases' exists_gt b with b' hb'
rcases exists_le_of_tendsto_atTop h a b' with ⟨a', ha', ha''⟩
exact ⟨a', ha', lt_of_lt_of_le hb' ha''⟩
#align filter.exists_lt_of_tendsto_at_top Filter.exists_lt_of_tendsto_atTop
-- @[nolint ge_or_gt] -- Porting note: restore attribute
theorem exists_lt_of_tendsto_atBot [SemilatticeSup α] [Preorder β] [NoMinOrder β] {u : α → β}
(h : Tendsto u atTop atBot) : ∀ a b, ∃ a' ≥ a, u a' < b :=
@exists_lt_of_tendsto_atTop _ βᵒᵈ _ _ _ _ h
#align filter.exists_lt_of_tendsto_at_bot Filter.exists_lt_of_tendsto_atBot
/-- If `u` is a sequence which is unbounded above,
then after any point, it reaches a value strictly greater than all previous values.
-/
theorem high_scores [LinearOrder β] [NoMaxOrder β] {u : ℕ → β} (hu : Tendsto u atTop atTop) :
∀ N, ∃ n ≥ N, ∀ k < n, u k < u n := by
intro N
obtain ⟨k : ℕ, - : k ≤ N, hku : ∀ l ≤ N, u l ≤ u k⟩ : ∃ k ≤ N, ∀ l ≤ N, u l ≤ u k :=
exists_max_image _ u (finite_le_nat N) ⟨N, le_refl N⟩
have ex : ∃ n ≥ N, u k < u n := exists_lt_of_tendsto_atTop hu _ _
obtain ⟨n : ℕ, hnN : n ≥ N, hnk : u k < u n, hn_min : ∀ m, m < n → N ≤ m → u m ≤ u k⟩ :
∃ n ≥ N, u k < u n ∧ ∀ m, m < n → N ≤ m → u m ≤ u k := by
rcases Nat.findX ex with ⟨n, ⟨hnN, hnk⟩, hn_min⟩
push_neg at hn_min
exact ⟨n, hnN, hnk, hn_min⟩
use n, hnN
rintro (l : ℕ) (hl : l < n)
have hlk : u l ≤ u k := by
cases' (le_total l N : l ≤ N ∨ N ≤ l) with H H
· exact hku l H
· exact hn_min l hl H
calc
u l ≤ u k := hlk
_ < u n := hnk
#align filter.high_scores Filter.high_scores
-- see Note [nolint_ge]
/-- If `u` is a sequence which is unbounded below,
then after any point, it reaches a value strictly smaller than all previous values.
-/
-- @[nolint ge_or_gt] Porting note: restore attribute
theorem low_scores [LinearOrder β] [NoMinOrder β] {u : ℕ → β} (hu : Tendsto u atTop atBot) :
∀ N, ∃ n ≥ N, ∀ k < n, u n < u k :=
@high_scores βᵒᵈ _ _ _ hu
#align filter.low_scores Filter.low_scores
/-- If `u` is a sequence which is unbounded above,
then it `Frequently` reaches a value strictly greater than all previous values.
-/
theorem frequently_high_scores [LinearOrder β] [NoMaxOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atTop) : ∃ᶠ n in atTop, ∀ k < n, u k < u n := by
simpa [frequently_atTop] using high_scores hu
#align filter.frequently_high_scores Filter.frequently_high_scores
/-- If `u` is a sequence which is unbounded below,
then it `Frequently` reaches a value strictly smaller than all previous values.
-/
theorem frequently_low_scores [LinearOrder β] [NoMinOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atBot) : ∃ᶠ n in atTop, ∀ k < n, u n < u k :=
@frequently_high_scores βᵒᵈ _ _ _ hu
#align filter.frequently_low_scores Filter.frequently_low_scores
theorem strictMono_subseq_of_tendsto_atTop {β : Type*} [LinearOrder β] [NoMaxOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atTop) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ StrictMono (u ∘ φ) :=
let ⟨φ, h, h'⟩ := extraction_of_frequently_atTop (frequently_high_scores hu)
⟨φ, h, fun _ m hnm => h' m _ (h hnm)⟩
#align filter.strict_mono_subseq_of_tendsto_at_top Filter.strictMono_subseq_of_tendsto_atTop
theorem strictMono_subseq_of_id_le {u : ℕ → ℕ} (hu : ∀ n, n ≤ u n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ StrictMono (u ∘ φ) :=
strictMono_subseq_of_tendsto_atTop (tendsto_atTop_mono hu tendsto_id)
#align filter.strict_mono_subseq_of_id_le Filter.strictMono_subseq_of_id_le
theorem _root_.StrictMono.tendsto_atTop {φ : ℕ → ℕ} (h : StrictMono φ) : Tendsto φ atTop atTop :=
tendsto_atTop_mono h.id_le tendsto_id
#align strict_mono.tendsto_at_top StrictMono.tendsto_atTop
section OrderedAddCommMonoid
variable [OrderedAddCommMonoid β] {l : Filter α} {f g : α → β}
theorem tendsto_atTop_add_nonneg_left' (hf : ∀ᶠ x in l, 0 ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_mono' l (hf.mono fun _ => le_add_of_nonneg_left) hg
#align filter.tendsto_at_top_add_nonneg_left' Filter.tendsto_atTop_add_nonneg_left'
theorem tendsto_atBot_add_nonpos_left' (hf : ∀ᶠ x in l, f x ≤ 0) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_left' _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_left' Filter.tendsto_atBot_add_nonpos_left'
theorem tendsto_atTop_add_nonneg_left (hf : ∀ x, 0 ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_left' (eventually_of_forall hf) hg
#align filter.tendsto_at_top_add_nonneg_left Filter.tendsto_atTop_add_nonneg_left
theorem tendsto_atBot_add_nonpos_left (hf : ∀ x, f x ≤ 0) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_left _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_left Filter.tendsto_atBot_add_nonpos_left
theorem tendsto_atTop_add_nonneg_right' (hf : Tendsto f l atTop) (hg : ∀ᶠ x in l, 0 ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_mono' l (monotone_mem (fun _ => le_add_of_nonneg_right) hg) hf
#align filter.tendsto_at_top_add_nonneg_right' Filter.tendsto_atTop_add_nonneg_right'
theorem tendsto_atBot_add_nonpos_right' (hf : Tendsto f l atBot) (hg : ∀ᶠ x in l, g x ≤ 0) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_right' _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_right' Filter.tendsto_atBot_add_nonpos_right'
theorem tendsto_atTop_add_nonneg_right (hf : Tendsto f l atTop) (hg : ∀ x, 0 ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_right' hf (eventually_of_forall hg)
#align filter.tendsto_at_top_add_nonneg_right Filter.tendsto_atTop_add_nonneg_right
theorem tendsto_atBot_add_nonpos_right (hf : Tendsto f l atBot) (hg : ∀ x, g x ≤ 0) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_right _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_right Filter.tendsto_atBot_add_nonpos_right
theorem tendsto_atTop_add (hf : Tendsto f l atTop) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_left' (tendsto_atTop.mp hf 0) hg
#align filter.tendsto_at_top_add Filter.tendsto_atTop_add
theorem tendsto_atBot_add (hf : Tendsto f l atBot) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add Filter.tendsto_atBot_add
theorem Tendsto.nsmul_atTop (hf : Tendsto f l atTop) {n : ℕ} (hn : 0 < n) :
Tendsto (fun x => n • f x) l atTop :=
tendsto_atTop.2 fun y =>
(tendsto_atTop.1 hf y).mp <|
(tendsto_atTop.1 hf 0).mono fun x h₀ hy =>
calc
y ≤ f x := hy
_ = 1 • f x := (one_nsmul _).symm
_ ≤ n • f x := nsmul_le_nsmul_left h₀ hn
#align filter.tendsto.nsmul_at_top Filter.Tendsto.nsmul_atTop
theorem Tendsto.nsmul_atBot (hf : Tendsto f l atBot) {n : ℕ} (hn : 0 < n) :
Tendsto (fun x => n • f x) l atBot :=
@Tendsto.nsmul_atTop α βᵒᵈ _ l f hf n hn
#align filter.tendsto.nsmul_at_bot Filter.Tendsto.nsmul_atBot
#noalign filter.tendsto_bit0_at_top
#noalign filter.tendsto_bit0_at_bot
end OrderedAddCommMonoid
section OrderedCancelAddCommMonoid
variable [OrderedCancelAddCommMonoid β] {l : Filter α} {f g : α → β}
theorem tendsto_atTop_of_add_const_left (C : β) (hf : Tendsto (fun x => C + f x) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (C + b)).mono fun _ => le_of_add_le_add_left
#align filter.tendsto_at_top_of_add_const_left Filter.tendsto_atTop_of_add_const_left
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_const_left (C : β) (hf : Tendsto (fun x => C + f x) l atBot) :
Tendsto f l atBot :=
tendsto_atBot.2 fun b => (tendsto_atBot.1 hf (C + b)).mono fun _ => le_of_add_le_add_left
#align filter.tendsto_at_bot_of_add_const_left Filter.tendsto_atBot_of_add_const_left
theorem tendsto_atTop_of_add_const_right (C : β) (hf : Tendsto (fun x => f x + C) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (b + C)).mono fun _ => le_of_add_le_add_right
#align filter.tendsto_at_top_of_add_const_right Filter.tendsto_atTop_of_add_const_right
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_const_right (C : β) (hf : Tendsto (fun x => f x + C) l atBot) :
Tendsto f l atBot :=
tendsto_atBot.2 fun b => (tendsto_atBot.1 hf (b + C)).mono fun _ => le_of_add_le_add_right
#align filter.tendsto_at_bot_of_add_const_right Filter.tendsto_atBot_of_add_const_right
theorem tendsto_atTop_of_add_bdd_above_left' (C) (hC : ∀ᶠ x in l, f x ≤ C)
(h : Tendsto (fun x => f x + g x) l atTop) : Tendsto g l atTop :=
tendsto_atTop_of_add_const_left C
(tendsto_atTop_mono' l (hC.mono fun x hx => add_le_add_right hx (g x)) h)
#align filter.tendsto_at_top_of_add_bdd_above_left' Filter.tendsto_atTop_of_add_bdd_above_left'
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_left' (C) (hC : ∀ᶠ x in l, C ≤ f x)
(h : Tendsto (fun x => f x + g x) l atBot) : Tendsto g l atBot :=
tendsto_atBot_of_add_const_left C
(tendsto_atBot_mono' l (hC.mono fun x hx => add_le_add_right hx (g x)) h)
#align filter.tendsto_at_bot_of_add_bdd_below_left' Filter.tendsto_atBot_of_add_bdd_below_left'
theorem tendsto_atTop_of_add_bdd_above_left (C) (hC : ∀ x, f x ≤ C) :
Tendsto (fun x => f x + g x) l atTop → Tendsto g l atTop :=
tendsto_atTop_of_add_bdd_above_left' C (univ_mem' hC)
#align filter.tendsto_at_top_of_add_bdd_above_left Filter.tendsto_atTop_of_add_bdd_above_left
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_left (C) (hC : ∀ x, C ≤ f x) :
Tendsto (fun x => f x + g x) l atBot → Tendsto g l atBot :=
tendsto_atBot_of_add_bdd_below_left' C (univ_mem' hC)
#align filter.tendsto_at_bot_of_add_bdd_below_left Filter.tendsto_atBot_of_add_bdd_below_left
theorem tendsto_atTop_of_add_bdd_above_right' (C) (hC : ∀ᶠ x in l, g x ≤ C)
(h : Tendsto (fun x => f x + g x) l atTop) : Tendsto f l atTop :=
tendsto_atTop_of_add_const_right C
(tendsto_atTop_mono' l (hC.mono fun x hx => add_le_add_left hx (f x)) h)
#align filter.tendsto_at_top_of_add_bdd_above_right' Filter.tendsto_atTop_of_add_bdd_above_right'
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_right' (C) (hC : ∀ᶠ x in l, C ≤ g x)
(h : Tendsto (fun x => f x + g x) l atBot) : Tendsto f l atBot :=
tendsto_atBot_of_add_const_right C
(tendsto_atBot_mono' l (hC.mono fun x hx => add_le_add_left hx (f x)) h)
#align filter.tendsto_at_bot_of_add_bdd_below_right' Filter.tendsto_atBot_of_add_bdd_below_right'
theorem tendsto_atTop_of_add_bdd_above_right (C) (hC : ∀ x, g x ≤ C) :
Tendsto (fun x => f x + g x) l atTop → Tendsto f l atTop :=
tendsto_atTop_of_add_bdd_above_right' C (univ_mem' hC)
#align filter.tendsto_at_top_of_add_bdd_above_right Filter.tendsto_atTop_of_add_bdd_above_right
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_right (C) (hC : ∀ x, C ≤ g x) :
Tendsto (fun x => f x + g x) l atBot → Tendsto f l atBot :=
tendsto_atBot_of_add_bdd_below_right' C (univ_mem' hC)
#align filter.tendsto_at_bot_of_add_bdd_below_right Filter.tendsto_atBot_of_add_bdd_below_right
end OrderedCancelAddCommMonoid
section OrderedGroup
variable [OrderedAddCommGroup β] (l : Filter α) {f g : α → β}
theorem tendsto_atTop_add_left_of_le' (C : β) (hf : ∀ᶠ x in l, C ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
@tendsto_atTop_of_add_bdd_above_left' _ _ _ l (fun x => -f x) (fun x => f x + g x) (-C) (by simpa)
(by simpa)
#align filter.tendsto_at_top_add_left_of_le' Filter.tendsto_atTop_add_left_of_le'
theorem tendsto_atBot_add_left_of_ge' (C : β) (hf : ∀ᶠ x in l, f x ≤ C) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_left_of_le' _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_left_of_ge' Filter.tendsto_atBot_add_left_of_ge'
theorem tendsto_atTop_add_left_of_le (C : β) (hf : ∀ x, C ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_left_of_le' l C (univ_mem' hf) hg
#align filter.tendsto_at_top_add_left_of_le Filter.tendsto_atTop_add_left_of_le
theorem tendsto_atBot_add_left_of_ge (C : β) (hf : ∀ x, f x ≤ C) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_left_of_le _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_left_of_ge Filter.tendsto_atBot_add_left_of_ge
theorem tendsto_atTop_add_right_of_le' (C : β) (hf : Tendsto f l atTop) (hg : ∀ᶠ x in l, C ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
@tendsto_atTop_of_add_bdd_above_right' _ _ _ l (fun x => f x + g x) (fun x => -g x) (-C)
(by simp [hg]) (by simp [hf])
#align filter.tendsto_at_top_add_right_of_le' Filter.tendsto_atTop_add_right_of_le'
theorem tendsto_atBot_add_right_of_ge' (C : β) (hf : Tendsto f l atBot) (hg : ∀ᶠ x in l, g x ≤ C) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_right_of_le' _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_right_of_ge' Filter.tendsto_atBot_add_right_of_ge'
theorem tendsto_atTop_add_right_of_le (C : β) (hf : Tendsto f l atTop) (hg : ∀ x, C ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_right_of_le' l C hf (univ_mem' hg)
#align filter.tendsto_at_top_add_right_of_le Filter.tendsto_atTop_add_right_of_le
theorem tendsto_atBot_add_right_of_ge (C : β) (hf : Tendsto f l atBot) (hg : ∀ x, g x ≤ C) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_right_of_le _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_right_of_ge Filter.tendsto_atBot_add_right_of_ge
theorem tendsto_atTop_add_const_left (C : β) (hf : Tendsto f l atTop) :
Tendsto (fun x => C + f x) l atTop :=
tendsto_atTop_add_left_of_le' l C (univ_mem' fun _ => le_refl C) hf
#align filter.tendsto_at_top_add_const_left Filter.tendsto_atTop_add_const_left
theorem tendsto_atBot_add_const_left (C : β) (hf : Tendsto f l atBot) :
Tendsto (fun x => C + f x) l atBot :=
@tendsto_atTop_add_const_left _ βᵒᵈ _ _ _ C hf
#align filter.tendsto_at_bot_add_const_left Filter.tendsto_atBot_add_const_left
theorem tendsto_atTop_add_const_right (C : β) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x + C) l atTop :=
tendsto_atTop_add_right_of_le' l C hf (univ_mem' fun _ => le_refl C)
#align filter.tendsto_at_top_add_const_right Filter.tendsto_atTop_add_const_right
theorem tendsto_atBot_add_const_right (C : β) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x + C) l atBot :=
@tendsto_atTop_add_const_right _ βᵒᵈ _ _ _ C hf
#align filter.tendsto_at_bot_add_const_right Filter.tendsto_atBot_add_const_right
theorem map_neg_atBot : map (Neg.neg : β → β) atBot = atTop :=
(OrderIso.neg β).map_atBot
#align filter.map_neg_at_bot Filter.map_neg_atBot
theorem map_neg_atTop : map (Neg.neg : β → β) atTop = atBot :=
(OrderIso.neg β).map_atTop
#align filter.map_neg_at_top Filter.map_neg_atTop
theorem comap_neg_atBot : comap (Neg.neg : β → β) atBot = atTop :=
(OrderIso.neg β).comap_atTop
#align filter.comap_neg_at_bot Filter.comap_neg_atBot
theorem comap_neg_atTop : comap (Neg.neg : β → β) atTop = atBot :=
(OrderIso.neg β).comap_atBot
#align filter.comap_neg_at_top Filter.comap_neg_atTop
theorem tendsto_neg_atTop_atBot : Tendsto (Neg.neg : β → β) atTop atBot :=
(OrderIso.neg β).tendsto_atTop
#align filter.tendsto_neg_at_top_at_bot Filter.tendsto_neg_atTop_atBot
theorem tendsto_neg_atBot_atTop : Tendsto (Neg.neg : β → β) atBot atTop :=
@tendsto_neg_atTop_atBot βᵒᵈ _
#align filter.tendsto_neg_at_bot_at_top Filter.tendsto_neg_atBot_atTop
variable {l}
@[simp]
theorem tendsto_neg_atTop_iff : Tendsto (fun x => -f x) l atTop ↔ Tendsto f l atBot :=
(OrderIso.neg β).tendsto_atBot_iff
#align filter.tendsto_neg_at_top_iff Filter.tendsto_neg_atTop_iff
@[simp]
theorem tendsto_neg_atBot_iff : Tendsto (fun x => -f x) l atBot ↔ Tendsto f l atTop :=
(OrderIso.neg β).tendsto_atTop_iff
#align filter.tendsto_neg_at_bot_iff Filter.tendsto_neg_atBot_iff
end OrderedGroup
section OrderedSemiring
variable [OrderedSemiring α] {l : Filter β} {f g : β → α}
#noalign filter.tendsto_bit1_at_top
theorem Tendsto.atTop_mul_atTop (hf : Tendsto f l atTop) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x * g x) l atTop := by
refine tendsto_atTop_mono' _ ?_ hg
filter_upwards [hg.eventually (eventually_ge_atTop 0),
hf.eventually (eventually_ge_atTop 1)] with _ using le_mul_of_one_le_left
#align filter.tendsto.at_top_mul_at_top Filter.Tendsto.atTop_mul_atTop
theorem tendsto_mul_self_atTop : Tendsto (fun x : α => x * x) atTop atTop :=
tendsto_id.atTop_mul_atTop tendsto_id
#align filter.tendsto_mul_self_at_top Filter.tendsto_mul_self_atTop
/-- The monomial function `x^n` tends to `+∞` at `+∞` for any positive natural `n`.
A version for positive real powers exists as `tendsto_rpow_atTop`. -/
theorem tendsto_pow_atTop {n : ℕ} (hn : n ≠ 0) : Tendsto (fun x : α => x ^ n) atTop atTop :=
tendsto_atTop_mono' _ ((eventually_ge_atTop 1).mono fun _x hx => le_self_pow hx hn) tendsto_id
#align filter.tendsto_pow_at_top Filter.tendsto_pow_atTop
end OrderedSemiring
theorem zero_pow_eventuallyEq [MonoidWithZero α] :
(fun n : ℕ => (0 : α) ^ n) =ᶠ[atTop] fun _ => 0 :=
eventually_atTop.2 ⟨1, fun _n hn ↦ zero_pow $ Nat.one_le_iff_ne_zero.1 hn⟩
#align filter.zero_pow_eventually_eq Filter.zero_pow_eventuallyEq
section OrderedRing
variable [OrderedRing α] {l : Filter β} {f g : β → α}
theorem Tendsto.atTop_mul_atBot (hf : Tendsto f l atTop) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x * g x) l atBot := by
have := hf.atTop_mul_atTop <| tendsto_neg_atBot_atTop.comp hg
simpa only [(· ∘ ·), neg_mul_eq_mul_neg, neg_neg] using tendsto_neg_atTop_atBot.comp this
#align filter.tendsto.at_top_mul_at_bot Filter.Tendsto.atTop_mul_atBot
theorem Tendsto.atBot_mul_atTop (hf : Tendsto f l atBot) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x * g x) l atBot := by
have : Tendsto (fun x => -f x * g x) l atTop :=
(tendsto_neg_atBot_atTop.comp hf).atTop_mul_atTop hg
simpa only [(· ∘ ·), neg_mul_eq_neg_mul, neg_neg] using tendsto_neg_atTop_atBot.comp this
#align filter.tendsto.at_bot_mul_at_top Filter.Tendsto.atBot_mul_atTop
theorem Tendsto.atBot_mul_atBot (hf : Tendsto f l atBot) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x * g x) l atTop := by
have : Tendsto (fun x => -f x * -g x) l atTop :=
(tendsto_neg_atBot_atTop.comp hf).atTop_mul_atTop (tendsto_neg_atBot_atTop.comp hg)
simpa only [neg_mul_neg] using this
#align filter.tendsto.at_bot_mul_at_bot Filter.Tendsto.atBot_mul_atBot
end OrderedRing
section LinearOrderedAddCommGroup
variable [LinearOrderedAddCommGroup α]
/-- $\lim_{x\to+\infty}|x|=+\infty$ -/
theorem tendsto_abs_atTop_atTop : Tendsto (abs : α → α) atTop atTop :=
tendsto_atTop_mono le_abs_self tendsto_id
#align filter.tendsto_abs_at_top_at_top Filter.tendsto_abs_atTop_atTop
/-- $\lim_{x\to-\infty}|x|=+\infty$ -/
theorem tendsto_abs_atBot_atTop : Tendsto (abs : α → α) atBot atTop :=
tendsto_atTop_mono neg_le_abs tendsto_neg_atBot_atTop
#align filter.tendsto_abs_at_bot_at_top Filter.tendsto_abs_atBot_atTop
@[simp]
theorem comap_abs_atTop : comap (abs : α → α) atTop = atBot ⊔ atTop := by
refine
le_antisymm (((atTop_basis.comap _).le_basis_iff (atBot_basis.sup atTop_basis)).2 ?_)
(sup_le tendsto_abs_atBot_atTop.le_comap tendsto_abs_atTop_atTop.le_comap)
rintro ⟨a, b⟩ -
refine ⟨max (-a) b, trivial, fun x hx => ?_⟩
rw [mem_preimage, mem_Ici, le_abs', max_le_iff, ← min_neg_neg, le_min_iff, neg_neg] at hx
exact hx.imp And.left And.right
#align filter.comap_abs_at_top Filter.comap_abs_atTop
end LinearOrderedAddCommGroup
section LinearOrderedSemiring
variable [LinearOrderedSemiring α] {l : Filter β} {f : β → α}
theorem Tendsto.atTop_of_const_mul {c : α} (hc : 0 < c) (hf : Tendsto (fun x => c * f x) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (c * b)).mono
fun _x hx => le_of_mul_le_mul_left hx hc
#align filter.tendsto.at_top_of_const_mul Filter.Tendsto.atTop_of_const_mul
theorem Tendsto.atTop_of_mul_const {c : α} (hc : 0 < c) (hf : Tendsto (fun x => f x * c) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (b * c)).mono
fun _x hx => le_of_mul_le_mul_right hx hc
#align filter.tendsto.at_top_of_mul_const Filter.Tendsto.atTop_of_mul_const
@[simp]
theorem tendsto_pow_atTop_iff {n : ℕ} : Tendsto (fun x : α => x ^ n) atTop atTop ↔ n ≠ 0 :=
⟨fun h hn => by simp only [hn, pow_zero, not_tendsto_const_atTop] at h, tendsto_pow_atTop⟩
#align filter.tendsto_pow_at_top_iff Filter.tendsto_pow_atTop_iff
end LinearOrderedSemiring
theorem not_tendsto_pow_atTop_atBot [LinearOrderedRing α] :
∀ {n : ℕ}, ¬Tendsto (fun x : α => x ^ n) atTop atBot
| 0 => by simp [not_tendsto_const_atBot]
| n + 1 => (tendsto_pow_atTop n.succ_ne_zero).not_tendsto disjoint_atTop_atBot
#align filter.not_tendsto_pow_at_top_at_bot Filter.not_tendsto_pow_atTop_atBot
section LinearOrderedSemifield
variable [LinearOrderedSemifield α] {l : Filter β} {f : β → α} {r c : α} {n : ℕ}
/-!
### Multiplication by constant: iff lemmas
-/
/-- If `r` is a positive constant, `fun x ↦ r * f x` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
theorem tendsto_const_mul_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x => r * f x) l atTop ↔ Tendsto f l atTop :=
⟨fun h => h.atTop_of_const_mul hr, fun h =>
Tendsto.atTop_of_const_mul (inv_pos.2 hr) <| by simpa only [inv_mul_cancel_left₀ hr.ne'] ⟩
#align filter.tendsto_const_mul_at_top_of_pos Filter.tendsto_const_mul_atTop_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x * r` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
theorem tendsto_mul_const_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x => f x * r) l atTop ↔ Tendsto f l atTop := by
simpa only [mul_comm] using tendsto_const_mul_atTop_of_pos hr
#align filter.tendsto_mul_const_at_top_of_pos Filter.tendsto_mul_const_atTop_of_pos
/-- If `r` is a positive constant, `x ↦ f x / r` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
lemma tendsto_div_const_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x ↦ f x / r) l atTop ↔ Tendsto f l atTop := by
simpa only [div_eq_mul_inv] using tendsto_mul_const_atTop_of_pos (inv_pos.2 hr)
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`fun x ↦ r * f x` tends to infinity if and only if `0 < r. `-/
theorem tendsto_const_mul_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atTop ↔ 0 < r := by
refine ⟨fun hrf => not_le.mp fun hr => ?_, fun hr => (tendsto_const_mul_atTop_of_pos hr).mpr h⟩
rcases ((h.eventually_ge_atTop 0).and (hrf.eventually_gt_atTop 0)).exists with ⟨x, hx, hrx⟩
exact (mul_nonpos_of_nonpos_of_nonneg hr hx).not_lt hrx
#align filter.tendsto_const_mul_at_top_iff_pos Filter.tendsto_const_mul_atTop_iff_pos
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`fun x ↦ f x * r` tends to infinity if and only if `0 < r. `-/
theorem tendsto_mul_const_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atTop ↔ 0 < r := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff_pos h]
#align filter.tendsto_mul_const_at_top_iff_pos Filter.tendsto_mul_const_atTop_iff_pos
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`x ↦ f x * r` tends to infinity if and only if `0 < r. `-/
lemma tendsto_div_const_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atTop ↔ 0 < r := by
simp only [div_eq_mul_inv, tendsto_mul_const_atTop_iff_pos h, inv_pos]
/-- If `f` tends to infinity along a filter, then `f` multiplied by a positive
constant (on the left) also tends to infinity. For a version working in `ℕ` or `ℤ`, use
`Filter.Tendsto.const_mul_atTop'` instead. -/
theorem Tendsto.const_mul_atTop (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atTop :=
(tendsto_const_mul_atTop_of_pos hr).2 hf
#align filter.tendsto.const_mul_at_top Filter.Tendsto.const_mul_atTop
/-- If a function `f` tends to infinity along a filter, then `f` multiplied by a positive
constant (on the right) also tends to infinity. For a version working in `ℕ` or `ℤ`, use
`Filter.Tendsto.atTop_mul_const'` instead. -/
theorem Tendsto.atTop_mul_const (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atTop :=
(tendsto_mul_const_atTop_of_pos hr).2 hf
#align filter.tendsto.at_top_mul_const Filter.Tendsto.atTop_mul_const
/-- If a function `f` tends to infinity along a filter, then `f` divided by a positive
constant also tends to infinity. -/
theorem Tendsto.atTop_div_const (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x / r) l atTop := by
simpa only [div_eq_mul_inv] using hf.atTop_mul_const (inv_pos.2 hr)
#align filter.tendsto.at_top_div_const Filter.Tendsto.atTop_div_const
theorem tendsto_const_mul_pow_atTop (hn : n ≠ 0) (hc : 0 < c) :
Tendsto (fun x => c * x ^ n) atTop atTop :=
Tendsto.const_mul_atTop hc (tendsto_pow_atTop hn)
#align filter.tendsto_const_mul_pow_at_top Filter.tendsto_const_mul_pow_atTop
theorem tendsto_const_mul_pow_atTop_iff :
Tendsto (fun x => c * x ^ n) atTop atTop ↔ n ≠ 0 ∧ 0 < c := by
refine ⟨fun h => ⟨?_, ?_⟩, fun h => tendsto_const_mul_pow_atTop h.1 h.2⟩
· rintro rfl
simp only [pow_zero, not_tendsto_const_atTop] at h
· rcases ((h.eventually_gt_atTop 0).and (eventually_ge_atTop 0)).exists with ⟨k, hck, hk⟩
exact pos_of_mul_pos_left hck (pow_nonneg hk _)
#align filter.tendsto_const_mul_pow_at_top_iff Filter.tendsto_const_mul_pow_atTop_iff
lemma tendsto_zpow_atTop_atTop {n : ℤ} (hn : 0 < n) : Tendsto (fun x : α ↦ x ^ n) atTop atTop := by
lift n to ℕ+ using hn; simp
#align tendsto_zpow_at_top_at_top Filter.tendsto_zpow_atTop_atTop
end LinearOrderedSemifield
section LinearOrderedField
variable [LinearOrderedField α] {l : Filter β} {f : β → α} {r : α}
/-- If `r` is a positive constant, `fun x ↦ r * f x` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
theorem tendsto_const_mul_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x => r * f x) l atBot ↔ Tendsto f l atBot := by
simpa only [← mul_neg, ← tendsto_neg_atTop_iff] using tendsto_const_mul_atTop_of_pos hr
#align filter.tendsto_const_mul_at_bot_of_pos Filter.tendsto_const_mul_atBot_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x * r` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
theorem tendsto_mul_const_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x => f x * r) l atBot ↔ Tendsto f l atBot := by
simpa only [mul_comm] using tendsto_const_mul_atBot_of_pos hr
#align filter.tendsto_mul_const_at_bot_of_pos Filter.tendsto_mul_const_atBot_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x / r` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
lemma tendsto_div_const_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x ↦ f x / r) l atBot ↔ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_of_pos, hr]
/-- If `r` is a negative constant, `fun x ↦ r * f x` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
theorem tendsto_const_mul_atTop_of_neg (hr : r < 0) :
Tendsto (fun x => r * f x) l atTop ↔ Tendsto f l atBot := by
simpa only [neg_mul, tendsto_neg_atBot_iff] using tendsto_const_mul_atBot_of_pos (neg_pos.2 hr)
#align filter.tendsto_const_mul_at_top_of_neg Filter.tendsto_const_mul_atTop_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x * r` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
theorem tendsto_mul_const_atTop_of_neg (hr : r < 0) :
Tendsto (fun x => f x * r) l atTop ↔ Tendsto f l atBot := by
simpa only [mul_comm] using tendsto_const_mul_atTop_of_neg hr
/-- If `r` is a negative constant, `fun x ↦ f x / r` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
lemma tendsto_div_const_atTop_of_neg (hr : r < 0) :
Tendsto (fun x ↦ f x / r) l atTop ↔ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_of_neg, hr]
/-- If `r` is a negative constant, `fun x ↦ r * f x` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
theorem tendsto_const_mul_atBot_of_neg (hr : r < 0) :
Tendsto (fun x => r * f x) l atBot ↔ Tendsto f l atTop := by
simpa only [neg_mul, tendsto_neg_atTop_iff] using tendsto_const_mul_atTop_of_pos (neg_pos.2 hr)
#align filter.tendsto_const_mul_at_bot_of_neg Filter.tendsto_const_mul_atBot_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x * r` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
theorem tendsto_mul_const_atBot_of_neg (hr : r < 0) :
Tendsto (fun x => f x * r) l atBot ↔ Tendsto f l atTop := by
simpa only [mul_comm] using tendsto_const_mul_atBot_of_neg hr
#align filter.tendsto_mul_const_at_bot_of_neg Filter.tendsto_mul_const_atBot_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x / r` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
lemma tendsto_div_const_atBot_of_neg (hr : r < 0) :
Tendsto (fun x ↦ f x / r) l atBot ↔ Tendsto f l atTop := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_of_neg, hr]
/-- The function `fun x ↦ r * f x` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
theorem tendsto_const_mul_atTop_iff [NeBot l] :
Tendsto (fun x => r * f x) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
rcases lt_trichotomy r 0 with (hr | rfl | hr)
· simp [hr, hr.not_lt, tendsto_const_mul_atTop_of_neg]
· simp [not_tendsto_const_atTop]
· simp [hr, hr.not_lt, tendsto_const_mul_atTop_of_pos]
#align filter.tendsto_const_mul_at_top_iff Filter.tendsto_const_mul_atTop_iff
/-- The function `fun x ↦ f x * r` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
theorem tendsto_mul_const_atTop_iff [NeBot l] :
Tendsto (fun x => f x * r) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff]
#align filter.tendsto_mul_const_at_top_iff Filter.tendsto_mul_const_atTop_iff
/-- The function `fun x ↦ f x / r` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
lemma tendsto_div_const_atTop_iff [NeBot l] :
Tendsto (fun x ↦ f x / r) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_iff]
/-- The function `fun x ↦ r * f x` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
theorem tendsto_const_mul_atBot_iff [NeBot l] :
Tendsto (fun x => r * f x) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp only [← tendsto_neg_atTop_iff, ← mul_neg, tendsto_const_mul_atTop_iff, neg_neg]
#align filter.tendsto_const_mul_at_bot_iff Filter.tendsto_const_mul_atBot_iff
/-- The function `fun x ↦ f x * r` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
theorem tendsto_mul_const_atBot_iff [NeBot l] :
Tendsto (fun x => f x * r) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff]
#align filter.tendsto_mul_const_at_bot_iff Filter.tendsto_mul_const_atBot_iff
/-- The function `fun x ↦ f x / r` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
lemma tendsto_div_const_atBot_iff [NeBot l] :
Tendsto (fun x ↦ f x / r) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff]
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ r * f x` tends to infinity if and only if `r < 0. `-/
theorem tendsto_const_mul_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atTop ↔ r < 0 := by
simp [tendsto_const_mul_atTop_iff, h, h.not_tendsto disjoint_atBot_atTop]
#align filter.tendsto_const_mul_at_top_iff_neg Filter.tendsto_const_mul_atTop_iff_neg
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ f x * r` tends to infinity if and only if `r < 0. `-/
theorem tendsto_mul_const_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atTop ↔ r < 0 := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff_neg h]
#align filter.tendsto_mul_const_at_top_iff_neg Filter.tendsto_mul_const_atTop_iff_neg
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ f x / r` tends to infinity if and only if `r < 0. `-/
lemma tendsto_div_const_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x ↦ f x / r) l atTop ↔ r < 0 := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_iff_neg h]
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ r * f x` tends to negative infinity if and only if `0 < r. `-/
theorem tendsto_const_mul_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atBot ↔ 0 < r := by
simp [tendsto_const_mul_atBot_iff, h, h.not_tendsto disjoint_atBot_atTop]
#align filter.tendsto_const_mul_at_bot_iff_pos Filter.tendsto_const_mul_atBot_iff_pos
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ f x * r` tends to negative infinity if and only if `0 < r. `-/
theorem tendsto_mul_const_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atBot ↔ 0 < r := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff_pos h]
#align filter.tendsto_mul_const_at_bot_iff_pos Filter.tendsto_mul_const_atBot_iff_pos
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ f x / r` tends to negative infinity if and only if `0 < r. `-/
lemma tendsto_div_const_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x ↦ f x / r) l atBot ↔ 0 < r := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff_pos h]
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ r * f x` tends to negative infinity if and only if `r < 0. `-/
theorem tendsto_const_mul_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atBot ↔ r < 0 := by
simp [tendsto_const_mul_atBot_iff, h, h.not_tendsto disjoint_atTop_atBot]
#align filter.tendsto_const_mul_at_bot_iff_neg Filter.tendsto_const_mul_atBot_iff_neg
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ f x * r` tends to negative infinity if and only if `r < 0. `-/
theorem tendsto_mul_const_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atBot ↔ r < 0 := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff_neg h]
#align filter.tendsto_mul_const_at_bot_iff_neg Filter.tendsto_mul_const_atBot_iff_neg
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ f x / r` tends to negative infinity if and only if `r < 0. `-/
lemma tendsto_div_const_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atBot ↔ r < 0 := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff_neg h]
/-- If a function `f` tends to infinity along a filter,
then `f` multiplied by a negative constant (on the left) tends to negative infinity. -/
theorem Tendsto.const_mul_atTop_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atBot :=
(tendsto_const_mul_atBot_of_neg hr).2 hf
#align filter.tendsto.neg_const_mul_at_top Filter.Tendsto.const_mul_atTop_of_neg
/-- If a function `f` tends to infinity along a filter,
then `f` multiplied by a negative constant (on the right) tends to negative infinity. -/
theorem Tendsto.atTop_mul_const_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atBot :=
(tendsto_mul_const_atBot_of_neg hr).2 hf
#align filter.tendsto.at_top_mul_neg_const Filter.Tendsto.atTop_mul_const_of_neg
/-- If a function `f` tends to infinity along a filter,
then `f` divided by a negative constant tends to negative infinity. -/
lemma Tendsto.atTop_div_const_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atBot := (tendsto_div_const_atBot_of_neg hr).2 hf
/-- If a function `f` tends to negative infinity along a filter, then `f` multiplied by
a positive constant (on the left) also tends to negative infinity. -/
theorem Tendsto.const_mul_atBot (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atBot :=
(tendsto_const_mul_atBot_of_pos hr).2 hf
#align filter.tendsto.const_mul_at_bot Filter.Tendsto.const_mul_atBot
/-- If a function `f` tends to negative infinity along a filter, then `f` multiplied by
a positive constant (on the right) also tends to negative infinity. -/
theorem Tendsto.atBot_mul_const (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atBot :=
(tendsto_mul_const_atBot_of_pos hr).2 hf
#align filter.tendsto.at_bot_mul_const Filter.Tendsto.atBot_mul_const
/-- If a function `f` tends to negative infinity along a filter, then `f` divided by
a positive constant also tends to negative infinity. -/
theorem Tendsto.atBot_div_const (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x / r) l atBot := (tendsto_div_const_atBot_of_pos hr).2 hf
#align filter.tendsto.at_bot_div_const Filter.Tendsto.atBot_div_const
/-- If a function `f` tends to negative infinity along a filter,
then `f` multiplied by a negative constant (on the left) tends to positive infinity. -/
theorem Tendsto.const_mul_atBot_of_neg (hr : r < 0) (hf : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atTop :=
(tendsto_const_mul_atTop_of_neg hr).2 hf
#align filter.tendsto.neg_const_mul_at_bot Filter.Tendsto.const_mul_atBot_of_neg
/-- If a function tends to negative infinity along a filter,
then `f` multiplied by a negative constant (on the right) tends to positive infinity. -/
theorem Tendsto.atBot_mul_const_of_neg (hr : r < 0) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atTop :=
(tendsto_mul_const_atTop_of_neg hr).2 hf
#align filter.tendsto.at_bot_mul_neg_const Filter.Tendsto.atBot_mul_const_of_neg
theorem tendsto_neg_const_mul_pow_atTop {c : α} {n : ℕ} (hn : n ≠ 0) (hc : c < 0) :
Tendsto (fun x => c * x ^ n) atTop atBot :=
(tendsto_pow_atTop hn).const_mul_atTop_of_neg hc
#align filter.tendsto_neg_const_mul_pow_at_top Filter.tendsto_neg_const_mul_pow_atTop
theorem tendsto_const_mul_pow_atBot_iff {c : α} {n : ℕ} :
Tendsto (fun x => c * x ^ n) atTop atBot ↔ n ≠ 0 ∧ c < 0 := by
simp only [← tendsto_neg_atTop_iff, ← neg_mul, tendsto_const_mul_pow_atTop_iff, neg_pos]
#align filter.tendsto_const_mul_pow_at_bot_iff Filter.tendsto_const_mul_pow_atBot_iff
@[deprecated (since := "2024-05-06")]
alias Tendsto.neg_const_mul_atTop := Tendsto.const_mul_atTop_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.atTop_mul_neg_const := Tendsto.atTop_mul_const_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.neg_const_mul_atBot := Tendsto.const_mul_atBot_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.atBot_mul_neg_const := Tendsto.atBot_mul_const_of_neg
end LinearOrderedField
open Filter
theorem tendsto_atTop' [Nonempty α] [SemilatticeSup α] {f : α → β} {l : Filter β} :
Tendsto f atTop l ↔ ∀ s ∈ l, ∃ a, ∀ b ≥ a, f b ∈ s := by
simp only [tendsto_def, mem_atTop_sets, mem_preimage]
#align filter.tendsto_at_top' Filter.tendsto_atTop'
theorem tendsto_atBot' [Nonempty α] [SemilatticeInf α] {f : α → β} {l : Filter β} :
Tendsto f atBot l ↔ ∀ s ∈ l, ∃ a, ∀ b ≤ a, f b ∈ s :=
@tendsto_atTop' αᵒᵈ _ _ _ _ _
#align filter.tendsto_at_bot' Filter.tendsto_atBot'
theorem tendsto_atTop_principal [Nonempty β] [SemilatticeSup β] {f : β → α} {s : Set α} :
Tendsto f atTop (𝓟 s) ↔ ∃ N, ∀ n ≥ N, f n ∈ s := by
simp_rw [tendsto_iff_comap, comap_principal, le_principal_iff, mem_atTop_sets, mem_preimage]
#align filter.tendsto_at_top_principal Filter.tendsto_atTop_principal
theorem tendsto_atBot_principal [Nonempty β] [SemilatticeInf β] {f : β → α} {s : Set α} :
Tendsto f atBot (𝓟 s) ↔ ∃ N, ∀ n ≤ N, f n ∈ s :=
@tendsto_atTop_principal _ βᵒᵈ _ _ _ _
#align filter.tendsto_at_bot_principal Filter.tendsto_atBot_principal
/-- A function `f` grows to `+∞` independent of an order-preserving embedding `e`. -/
theorem tendsto_atTop_atTop [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β} :
Tendsto f atTop atTop ↔ ∀ b : β, ∃ i : α, ∀ a : α, i ≤ a → b ≤ f a :=
Iff.trans tendsto_iInf <| forall_congr' fun _ => tendsto_atTop_principal
#align filter.tendsto_at_top_at_top Filter.tendsto_atTop_atTop
theorem tendsto_atTop_atBot [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β} :
Tendsto f atTop atBot ↔ ∀ b : β, ∃ i : α, ∀ a : α, i ≤ a → f a ≤ b :=
@tendsto_atTop_atTop α βᵒᵈ _ _ _ f
#align filter.tendsto_at_top_at_bot Filter.tendsto_atTop_atBot
theorem tendsto_atBot_atTop [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β} :
Tendsto f atBot atTop ↔ ∀ b : β, ∃ i : α, ∀ a : α, a ≤ i → b ≤ f a :=
@tendsto_atTop_atTop αᵒᵈ β _ _ _ f
#align filter.tendsto_at_bot_at_top Filter.tendsto_atBot_atTop
theorem tendsto_atBot_atBot [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β} :
Tendsto f atBot atBot ↔ ∀ b : β, ∃ i : α, ∀ a : α, a ≤ i → f a ≤ b :=
@tendsto_atTop_atTop αᵒᵈ βᵒᵈ _ _ _ f
#align filter.tendsto_at_bot_at_bot Filter.tendsto_atBot_atBot
theorem tendsto_atTop_atTop_of_monotone [Preorder α] [Preorder β] {f : α → β} (hf : Monotone f)
(h : ∀ b, ∃ a, b ≤ f a) : Tendsto f atTop atTop :=
tendsto_iInf.2 fun b =>
tendsto_principal.2 <|
let ⟨a, ha⟩ := h b
mem_of_superset (mem_atTop a) fun _a' ha' => le_trans ha (hf ha')
#align filter.tendsto_at_top_at_top_of_monotone Filter.tendsto_atTop_atTop_of_monotone
theorem tendsto_atTop_atBot_of_antitone [Preorder α] [Preorder β] {f : α → β} (hf : Antitone f)
(h : ∀ b, ∃ a, f a ≤ b) : Tendsto f atTop atBot :=
@tendsto_atTop_atTop_of_monotone _ βᵒᵈ _ _ _ hf h
theorem tendsto_atBot_atBot_of_monotone [Preorder α] [Preorder β] {f : α → β} (hf : Monotone f)
(h : ∀ b, ∃ a, f a ≤ b) : Tendsto f atBot atBot :=
tendsto_iInf.2 fun b => tendsto_principal.2 <|
let ⟨a, ha⟩ := h b; mem_of_superset (mem_atBot a) fun _a' ha' => le_trans (hf ha') ha
#align filter.tendsto_at_bot_at_bot_of_monotone Filter.tendsto_atBot_atBot_of_monotone
theorem tendsto_atBot_atTop_of_antitone [Preorder α] [Preorder β] {f : α → β} (hf : Antitone f)
(h : ∀ b, ∃ a, b ≤ f a) : Tendsto f atBot atTop :=
@tendsto_atBot_atBot_of_monotone _ βᵒᵈ _ _ _ hf h
theorem tendsto_atTop_atTop_iff_of_monotone [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β}
(hf : Monotone f) : Tendsto f atTop atTop ↔ ∀ b : β, ∃ a : α, b ≤ f a :=
tendsto_atTop_atTop.trans <| forall_congr' fun _ => exists_congr fun a =>
⟨fun h => h a (le_refl a), fun h _a' ha' => le_trans h <| hf ha'⟩
#align filter.tendsto_at_top_at_top_iff_of_monotone Filter.tendsto_atTop_atTop_iff_of_monotone
theorem tendsto_atTop_atBot_iff_of_antitone [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β}
(hf : Antitone f) : Tendsto f atTop atBot ↔ ∀ b : β, ∃ a : α, f a ≤ b :=
@tendsto_atTop_atTop_iff_of_monotone _ βᵒᵈ _ _ _ _ hf
theorem tendsto_atBot_atBot_iff_of_monotone [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β}
(hf : Monotone f) : Tendsto f atBot atBot ↔ ∀ b : β, ∃ a : α, f a ≤ b :=
tendsto_atBot_atBot.trans <| forall_congr' fun _ => exists_congr fun a =>
⟨fun h => h a (le_refl a), fun h _a' ha' => le_trans (hf ha') h⟩
#align filter.tendsto_at_bot_at_bot_iff_of_monotone Filter.tendsto_atBot_atBot_iff_of_monotone
theorem tendsto_atBot_atTop_iff_of_antitone [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β}
(hf : Antitone f) : Tendsto f atBot atTop ↔ ∀ b : β, ∃ a : α, b ≤ f a :=
@tendsto_atBot_atBot_iff_of_monotone _ βᵒᵈ _ _ _ _ hf
alias _root_.Monotone.tendsto_atTop_atTop := tendsto_atTop_atTop_of_monotone
#align monotone.tendsto_at_top_at_top Monotone.tendsto_atTop_atTop
alias _root_.Monotone.tendsto_atBot_atBot := tendsto_atBot_atBot_of_monotone
#align monotone.tendsto_at_bot_at_bot Monotone.tendsto_atBot_atBot
alias _root_.Monotone.tendsto_atTop_atTop_iff := tendsto_atTop_atTop_iff_of_monotone
#align monotone.tendsto_at_top_at_top_iff Monotone.tendsto_atTop_atTop_iff
alias _root_.Monotone.tendsto_atBot_atBot_iff := tendsto_atBot_atBot_iff_of_monotone
#align monotone.tendsto_at_bot_at_bot_iff Monotone.tendsto_atBot_atBot_iff
theorem comap_embedding_atTop [Preorder β] [Preorder γ] {e : β → γ}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, c ≤ e b) : comap e atTop = atTop :=
le_antisymm
(le_iInf fun b =>
le_principal_iff.2 <| mem_comap.2 ⟨Ici (e b), mem_atTop _, fun _ => (hm _ _).1⟩)
(tendsto_atTop_atTop_of_monotone (fun _ _ => (hm _ _).2) hu).le_comap
#align filter.comap_embedding_at_top Filter.comap_embedding_atTop
theorem comap_embedding_atBot [Preorder β] [Preorder γ] {e : β → γ}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, e b ≤ c) : comap e atBot = atBot :=
@comap_embedding_atTop βᵒᵈ γᵒᵈ _ _ e (Function.swap hm) hu
#align filter.comap_embedding_at_bot Filter.comap_embedding_atBot
theorem tendsto_atTop_embedding [Preorder β] [Preorder γ] {f : α → β} {e : β → γ} {l : Filter α}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, c ≤ e b) :
Tendsto (e ∘ f) l atTop ↔ Tendsto f l atTop := by
rw [← comap_embedding_atTop hm hu, tendsto_comap_iff]
#align filter.tendsto_at_top_embedding Filter.tendsto_atTop_embedding
/-- A function `f` goes to `-∞` independent of an order-preserving embedding `e`. -/
theorem tendsto_atBot_embedding [Preorder β] [Preorder γ] {f : α → β} {e : β → γ} {l : Filter α}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, e b ≤ c) :
Tendsto (e ∘ f) l atBot ↔ Tendsto f l atBot :=
@tendsto_atTop_embedding α βᵒᵈ γᵒᵈ _ _ f e l (Function.swap hm) hu
#align filter.tendsto_at_bot_embedding Filter.tendsto_atBot_embedding
theorem tendsto_finset_range : Tendsto Finset.range atTop atTop :=
Finset.range_mono.tendsto_atTop_atTop Finset.exists_nat_subset_range
#align filter.tendsto_finset_range Filter.tendsto_finset_range
theorem atTop_finset_eq_iInf : (atTop : Filter (Finset α)) = ⨅ x : α, 𝓟 (Ici {x}) := by
refine le_antisymm (le_iInf fun i => le_principal_iff.2 <| mem_atTop ({i} : Finset α)) ?_
refine
le_iInf fun s =>
le_principal_iff.2 <| mem_iInf_of_iInter s.finite_toSet (fun i => mem_principal_self _) ?_
simp only [subset_def, mem_iInter, SetCoe.forall, mem_Ici, Finset.le_iff_subset,
Finset.mem_singleton, Finset.subset_iff, forall_eq]
exact fun t => id
#align filter.at_top_finset_eq_infi Filter.atTop_finset_eq_iInf
/-- If `f` is a monotone sequence of `Finset`s and each `x` belongs to one of `f n`, then
`Tendsto f atTop atTop`. -/
theorem tendsto_atTop_finset_of_monotone [Preorder β] {f : β → Finset α} (h : Monotone f)
(h' : ∀ x : α, ∃ n, x ∈ f n) : Tendsto f atTop atTop := by
simp only [atTop_finset_eq_iInf, tendsto_iInf, tendsto_principal]
intro a
rcases h' a with ⟨b, hb⟩
exact (eventually_ge_atTop b).mono fun b' hb' => (Finset.singleton_subset_iff.2 hb).trans (h hb')
#align filter.tendsto_at_top_finset_of_monotone Filter.tendsto_atTop_finset_of_monotone
alias _root_.Monotone.tendsto_atTop_finset := tendsto_atTop_finset_of_monotone
#align monotone.tendsto_at_top_finset Monotone.tendsto_atTop_finset
-- Porting note: add assumption `DecidableEq β` so that the lemma applies to any instance
theorem tendsto_finset_image_atTop_atTop [DecidableEq β] {i : β → γ} {j : γ → β}
(h : Function.LeftInverse j i) : Tendsto (Finset.image j) atTop atTop :=
(Finset.image_mono j).tendsto_atTop_finset fun a =>
⟨{i a}, by simp only [Finset.image_singleton, h a, Finset.mem_singleton]⟩
#align filter.tendsto_finset_image_at_top_at_top Filter.tendsto_finset_image_atTop_atTop
theorem tendsto_finset_preimage_atTop_atTop {f : α → β} (hf : Function.Injective f) :
Tendsto (fun s : Finset β => s.preimage f (hf.injOn)) atTop atTop :=
(Finset.monotone_preimage hf).tendsto_atTop_finset fun x =>
⟨{f x}, Finset.mem_preimage.2 <| Finset.mem_singleton_self _⟩
#align filter.tendsto_finset_preimage_at_top_at_top Filter.tendsto_finset_preimage_atTop_atTop
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_atTop_atTop_eq [Preorder α] [Preorder β] :
(atTop : Filter α) ×ˢ (atTop : Filter β) = (atTop : Filter (α × β)) := by
cases isEmpty_or_nonempty α
· exact Subsingleton.elim _ _
cases isEmpty_or_nonempty β
· exact Subsingleton.elim _ _
simpa [atTop, prod_iInf_left, prod_iInf_right, iInf_prod] using iInf_comm
#align filter.prod_at_top_at_top_eq Filter.prod_atTop_atTop_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_atBot_atBot_eq [Preorder β₁] [Preorder β₂] :
(atBot : Filter β₁) ×ˢ (atBot : Filter β₂) = (atBot : Filter (β₁ × β₂)) :=
@prod_atTop_atTop_eq β₁ᵒᵈ β₂ᵒᵈ _ _
#align filter.prod_at_bot_at_bot_eq Filter.prod_atBot_atBot_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_map_atTop_eq {α₁ α₂ β₁ β₂ : Type*} [Preorder β₁] [Preorder β₂]
(u₁ : β₁ → α₁) (u₂ : β₂ → α₂) : map u₁ atTop ×ˢ map u₂ atTop = map (Prod.map u₁ u₂) atTop := by
rw [prod_map_map_eq, prod_atTop_atTop_eq, Prod.map_def]
#align filter.prod_map_at_top_eq Filter.prod_map_atTop_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_map_atBot_eq {α₁ α₂ β₁ β₂ : Type*} [Preorder β₁] [Preorder β₂]
(u₁ : β₁ → α₁) (u₂ : β₂ → α₂) : map u₁ atBot ×ˢ map u₂ atBot = map (Prod.map u₁ u₂) atBot :=
@prod_map_atTop_eq _ _ β₁ᵒᵈ β₂ᵒᵈ _ _ _ _
#align filter.prod_map_at_bot_eq Filter.prod_map_atBot_eq
theorem Tendsto.subseq_mem {F : Filter α} {V : ℕ → Set α} (h : ∀ n, V n ∈ F) {u : ℕ → α}
(hu : Tendsto u atTop F) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, u (φ n) ∈ V n :=
extraction_forall_of_eventually'
(fun n => tendsto_atTop'.mp hu _ (h n) : ∀ n, ∃ N, ∀ k ≥ N, u k ∈ V n)
#align filter.tendsto.subseq_mem Filter.Tendsto.subseq_mem
theorem tendsto_atBot_diagonal [SemilatticeInf α] : Tendsto (fun a : α => (a, a)) atBot atBot := by
rw [← prod_atBot_atBot_eq]
exact tendsto_id.prod_mk tendsto_id
#align filter.tendsto_at_bot_diagonal Filter.tendsto_atBot_diagonal
theorem tendsto_atTop_diagonal [SemilatticeSup α] : Tendsto (fun a : α => (a, a)) atTop atTop := by
rw [← prod_atTop_atTop_eq]
exact tendsto_id.prod_mk tendsto_id
#align filter.tendsto_at_top_diagonal Filter.tendsto_atTop_diagonal
theorem Tendsto.prod_map_prod_atBot [SemilatticeInf γ] {F : Filter α} {G : Filter β} {f : α → γ}
{g : β → γ} (hf : Tendsto f F atBot) (hg : Tendsto g G atBot) :
Tendsto (Prod.map f g) (F ×ˢ G) atBot := by
rw [← prod_atBot_atBot_eq]
exact hf.prod_map hg
#align filter.tendsto.prod_map_prod_at_bot Filter.Tendsto.prod_map_prod_atBot
theorem Tendsto.prod_map_prod_atTop [SemilatticeSup γ] {F : Filter α} {G : Filter β} {f : α → γ}
{g : β → γ} (hf : Tendsto f F atTop) (hg : Tendsto g G atTop) :
Tendsto (Prod.map f g) (F ×ˢ G) atTop := by
rw [← prod_atTop_atTop_eq]
exact hf.prod_map hg
#align filter.tendsto.prod_map_prod_at_top Filter.Tendsto.prod_map_prod_atTop
theorem Tendsto.prod_atBot [SemilatticeInf α] [SemilatticeInf γ] {f g : α → γ}
(hf : Tendsto f atBot atBot) (hg : Tendsto g atBot atBot) :
Tendsto (Prod.map f g) atBot atBot := by
rw [← prod_atBot_atBot_eq]
exact hf.prod_map_prod_atBot hg
#align filter.tendsto.prod_at_bot Filter.Tendsto.prod_atBot
theorem Tendsto.prod_atTop [SemilatticeSup α] [SemilatticeSup γ] {f g : α → γ}
(hf : Tendsto f atTop atTop) (hg : Tendsto g atTop atTop) :
Tendsto (Prod.map f g) atTop atTop := by
rw [← prod_atTop_atTop_eq]
exact hf.prod_map_prod_atTop hg
#align filter.tendsto.prod_at_top Filter.Tendsto.prod_atTop
theorem eventually_atBot_prod_self [SemilatticeInf α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atBot, p x) ↔ ∃ a, ∀ k l, k ≤ a → l ≤ a → p (k, l) := by
simp [← prod_atBot_atBot_eq, (@atBot_basis α _ _).prod_self.eventually_iff]
#align filter.eventually_at_bot_prod_self Filter.eventually_atBot_prod_self
theorem eventually_atTop_prod_self [SemilatticeSup α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atTop, p x) ↔ ∃ a, ∀ k l, a ≤ k → a ≤ l → p (k, l) :=
eventually_atBot_prod_self (α := αᵒᵈ)
#align filter.eventually_at_top_prod_self Filter.eventually_atTop_prod_self
theorem eventually_atBot_prod_self' [SemilatticeInf α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atBot, p x) ↔ ∃ a, ∀ k ≤ a, ∀ l ≤ a, p (k, l) := by
simp only [eventually_atBot_prod_self, forall_cond_comm]
#align filter.eventually_at_bot_prod_self' Filter.eventually_atBot_prod_self'
theorem eventually_atTop_prod_self' [SemilatticeSup α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atTop, p x) ↔ ∃ a, ∀ k ≥ a, ∀ l ≥ a, p (k, l) := by
simp only [eventually_atTop_prod_self, forall_cond_comm]
#align filter.eventually_at_top_prod_self' Filter.eventually_atTop_prod_self'
theorem eventually_atTop_curry [SemilatticeSup α] [SemilatticeSup β] {p : α × β → Prop}
(hp : ∀ᶠ x : α × β in Filter.atTop, p x) : ∀ᶠ k in atTop, ∀ᶠ l in atTop, p (k, l) := by
rw [← prod_atTop_atTop_eq] at hp
exact hp.curry
#align filter.eventually_at_top_curry Filter.eventually_atTop_curry
theorem eventually_atBot_curry [SemilatticeInf α] [SemilatticeInf β] {p : α × β → Prop}
(hp : ∀ᶠ x : α × β in Filter.atBot, p x) : ∀ᶠ k in atBot, ∀ᶠ l in atBot, p (k, l) :=
@eventually_atTop_curry αᵒᵈ βᵒᵈ _ _ _ hp
#align filter.eventually_at_bot_curry Filter.eventually_atBot_curry
/-- A function `f` maps upwards closed sets (atTop sets) to upwards closed sets when it is a
Galois insertion. The Galois "insertion" and "connection" is weakened to only require it to be an
insertion and a connection above `b'`. -/
theorem map_atTop_eq_of_gc [SemilatticeSup α] [SemilatticeSup β] {f : α → β} (g : β → α) (b' : β)
(hf : Monotone f) (gc : ∀ a, ∀ b ≥ b', f a ≤ b ↔ a ≤ g b) (hgi : ∀ b ≥ b', b ≤ f (g b)) :
map f atTop = atTop := by
refine
le_antisymm
(hf.tendsto_atTop_atTop fun b => ⟨g (b ⊔ b'), le_sup_left.trans <| hgi _ le_sup_right⟩) ?_
rw [@map_atTop_eq _ _ ⟨g b'⟩]
refine le_iInf fun a => iInf_le_of_le (f a ⊔ b') <| principal_mono.2 fun b hb => ?_
rw [mem_Ici, sup_le_iff] at hb
exact ⟨g b, (gc _ _ hb.2).1 hb.1, le_antisymm ((gc _ _ hb.2).2 le_rfl) (hgi _ hb.2)⟩
#align filter.map_at_top_eq_of_gc Filter.map_atTop_eq_of_gc
theorem map_atBot_eq_of_gc [SemilatticeInf α] [SemilatticeInf β] {f : α → β} (g : β → α) (b' : β)
(hf : Monotone f) (gc : ∀ a, ∀ b ≤ b', b ≤ f a ↔ g b ≤ a) (hgi : ∀ b ≤ b', f (g b) ≤ b) :
map f atBot = atBot :=
@map_atTop_eq_of_gc αᵒᵈ βᵒᵈ _ _ _ _ _ hf.dual gc hgi
#align filter.map_at_bot_eq_of_gc Filter.map_atBot_eq_of_gc
theorem map_val_atTop_of_Ici_subset [SemilatticeSup α] {a : α} {s : Set α} (h : Ici a ⊆ s) :
map ((↑) : s → α) atTop = atTop := by
haveI : Nonempty s := ⟨⟨a, h le_rfl⟩⟩
have : Directed (· ≥ ·) fun x : s => 𝓟 (Ici x) := fun x y ↦ by
use ⟨x ⊔ y ⊔ a, h le_sup_right⟩
simp only [principal_mono, Ici_subset_Ici, ← Subtype.coe_le_coe, Subtype.coe_mk]
exact ⟨le_sup_left.trans le_sup_left, le_sup_right.trans le_sup_left⟩
simp only [le_antisymm_iff, atTop, le_iInf_iff, le_principal_iff, mem_map, mem_setOf_eq,
map_iInf_eq this, map_principal]
constructor
· intro x
refine mem_of_superset (mem_iInf_of_mem ⟨x ⊔ a, h le_sup_right⟩ (mem_principal_self _)) ?_
rintro _ ⟨y, hy, rfl⟩
exact le_trans le_sup_left (Subtype.coe_le_coe.2 hy)
· intro x
filter_upwards [mem_atTop (↑x ⊔ a)] with b hb
exact ⟨⟨b, h <| le_sup_right.trans hb⟩, Subtype.coe_le_coe.1 (le_sup_left.trans hb), rfl⟩
#align filter.map_coe_at_top_of_Ici_subset Filter.map_val_atTop_of_Ici_subset
/-- The image of the filter `atTop` on `Ici a` under the coercion equals `atTop`. -/
@[simp]
theorem map_val_Ici_atTop [SemilatticeSup α] (a : α) : map ((↑) : Ici a → α) atTop = atTop :=
map_val_atTop_of_Ici_subset (Subset.refl _)
#align filter.map_coe_Ici_at_top Filter.map_val_Ici_atTop
/-- The image of the filter `atTop` on `Ioi a` under the coercion equals `atTop`. -/
@[simp]
theorem map_val_Ioi_atTop [SemilatticeSup α] [NoMaxOrder α] (a : α) :
map ((↑) : Ioi a → α) atTop = atTop :=
let ⟨_b, hb⟩ := exists_gt a
map_val_atTop_of_Ici_subset <| Ici_subset_Ioi.2 hb
#align filter.map_coe_Ioi_at_top Filter.map_val_Ioi_atTop
/-- The `atTop` filter for an open interval `Ioi a` comes from the `atTop` filter in the ambient
order. -/
theorem atTop_Ioi_eq [SemilatticeSup α] (a : α) : atTop = comap ((↑) : Ioi a → α) atTop := by
rcases isEmpty_or_nonempty (Ioi a) with h|⟨⟨b, hb⟩⟩
· exact Subsingleton.elim _ _
· rw [← map_val_atTop_of_Ici_subset (Ici_subset_Ioi.2 hb), comap_map Subtype.coe_injective]
#align filter.at_top_Ioi_eq Filter.atTop_Ioi_eq
/-- The `atTop` filter for an open interval `Ici a` comes from the `atTop` filter in the ambient
order. -/
theorem atTop_Ici_eq [SemilatticeSup α] (a : α) : atTop = comap ((↑) : Ici a → α) atTop := by
rw [← map_val_Ici_atTop a, comap_map Subtype.coe_injective]
#align filter.at_top_Ici_eq Filter.atTop_Ici_eq
/-- The `atBot` filter for an open interval `Iio a` comes from the `atBot` filter in the ambient
order. -/
@[simp]
theorem map_val_Iio_atBot [SemilatticeInf α] [NoMinOrder α] (a : α) :
map ((↑) : Iio a → α) atBot = atBot :=
@map_val_Ioi_atTop αᵒᵈ _ _ _
#align filter.map_coe_Iio_at_bot Filter.map_val_Iio_atBot
/-- The `atBot` filter for an open interval `Iio a` comes from the `atBot` filter in the ambient
order. -/
theorem atBot_Iio_eq [SemilatticeInf α] (a : α) : atBot = comap ((↑) : Iio a → α) atBot :=
@atTop_Ioi_eq αᵒᵈ _ _
#align filter.at_bot_Iio_eq Filter.atBot_Iio_eq
/-- The `atBot` filter for an open interval `Iic a` comes from the `atBot` filter in the ambient
order. -/
@[simp]
theorem map_val_Iic_atBot [SemilatticeInf α] (a : α) : map ((↑) : Iic a → α) atBot = atBot :=
@map_val_Ici_atTop αᵒᵈ _ _
#align filter.map_coe_Iic_at_bot Filter.map_val_Iic_atBot
/-- The `atBot` filter for an open interval `Iic a` comes from the `atBot` filter in the ambient
order. -/
theorem atBot_Iic_eq [SemilatticeInf α] (a : α) : atBot = comap ((↑) : Iic a → α) atBot :=
@atTop_Ici_eq αᵒᵈ _ _
#align filter.at_bot_Iic_eq Filter.atBot_Iic_eq
theorem tendsto_Ioi_atTop [SemilatticeSup α] {a : α} {f : β → Ioi a} {l : Filter β} :
Tendsto f l atTop ↔ Tendsto (fun x => (f x : α)) l atTop := by
rw [atTop_Ioi_eq, tendsto_comap_iff, Function.comp_def]
#align filter.tendsto_Ioi_at_top Filter.tendsto_Ioi_atTop
theorem tendsto_Iio_atBot [SemilatticeInf α] {a : α} {f : β → Iio a} {l : Filter β} :
Tendsto f l atBot ↔ Tendsto (fun x => (f x : α)) l atBot := by
rw [atBot_Iio_eq, tendsto_comap_iff, Function.comp_def]
#align filter.tendsto_Iio_at_bot Filter.tendsto_Iio_atBot
theorem tendsto_Ici_atTop [SemilatticeSup α] {a : α} {f : β → Ici a} {l : Filter β} :
Tendsto f l atTop ↔ Tendsto (fun x => (f x : α)) l atTop := by
rw [atTop_Ici_eq, tendsto_comap_iff, Function.comp_def]
#align filter.tendsto_Ici_at_top Filter.tendsto_Ici_atTop
theorem tendsto_Iic_atBot [SemilatticeInf α] {a : α} {f : β → Iic a} {l : Filter β} :
Tendsto f l atBot ↔ Tendsto (fun x => (f x : α)) l atBot := by
rw [atBot_Iic_eq, tendsto_comap_iff, Function.comp_def]
#align filter.tendsto_Iic_at_bot Filter.tendsto_Iic_atBot
@[simp, nolint simpNF] -- Porting note: linter claims that LHS doesn't simplify. It does.
theorem tendsto_comp_val_Ioi_atTop [SemilatticeSup α] [NoMaxOrder α] {a : α} {f : α → β}
{l : Filter β} : Tendsto (fun x : Ioi a => f x) atTop l ↔ Tendsto f atTop l := by
rw [← map_val_Ioi_atTop a, tendsto_map'_iff, Function.comp_def]
#align filter.tendsto_comp_coe_Ioi_at_top Filter.tendsto_comp_val_Ioi_atTop
@[simp, nolint simpNF] -- Porting note: linter claims that LHS doesn't simplify. It does.
theorem tendsto_comp_val_Ici_atTop [SemilatticeSup α] {a : α} {f : α → β} {l : Filter β} :
Tendsto (fun x : Ici a => f x) atTop l ↔ Tendsto f atTop l := by
rw [← map_val_Ici_atTop a, tendsto_map'_iff, Function.comp_def]
#align filter.tendsto_comp_coe_Ici_at_top Filter.tendsto_comp_val_Ici_atTop
@[simp, nolint simpNF] -- Porting note: linter claims that LHS doesn't simplify. It does.
theorem tendsto_comp_val_Iio_atBot [SemilatticeInf α] [NoMinOrder α] {a : α} {f : α → β}
{l : Filter β} : Tendsto (fun x : Iio a => f x) atBot l ↔ Tendsto f atBot l := by
rw [← map_val_Iio_atBot a, tendsto_map'_iff, Function.comp_def]
#align filter.tendsto_comp_coe_Iio_at_bot Filter.tendsto_comp_val_Iio_atBot
@[simp, nolint simpNF] -- Porting note: linter claims that LHS doesn't simplify. It does.
theorem tendsto_comp_val_Iic_atBot [SemilatticeInf α] {a : α} {f : α → β} {l : Filter β} :
Tendsto (fun x : Iic a => f x) atBot l ↔ Tendsto f atBot l := by
rw [← map_val_Iic_atBot a, tendsto_map'_iff, Function.comp_def]
#align filter.tendsto_comp_coe_Iic_at_bot Filter.tendsto_comp_val_Iic_atBot
theorem map_add_atTop_eq_nat (k : ℕ) : map (fun a => a + k) atTop = atTop :=
map_atTop_eq_of_gc (fun a => a - k) k (fun a b h => add_le_add_right h k)
(fun a b h => (le_tsub_iff_right h).symm) fun a h => by rw [tsub_add_cancel_of_le h]
#align filter.map_add_at_top_eq_nat Filter.map_add_atTop_eq_nat
theorem map_sub_atTop_eq_nat (k : ℕ) : map (fun a => a - k) atTop = atTop :=
map_atTop_eq_of_gc (fun a => a + k) 0 (fun a b h => tsub_le_tsub_right h _)
(fun a b _ => tsub_le_iff_right) fun b _ => by rw [add_tsub_cancel_right]
#align filter.map_sub_at_top_eq_nat Filter.map_sub_atTop_eq_nat
theorem tendsto_add_atTop_nat (k : ℕ) : Tendsto (fun a => a + k) atTop atTop :=
le_of_eq (map_add_atTop_eq_nat k)
#align filter.tendsto_add_at_top_nat Filter.tendsto_add_atTop_nat
theorem tendsto_sub_atTop_nat (k : ℕ) : Tendsto (fun a => a - k) atTop atTop :=
le_of_eq (map_sub_atTop_eq_nat k)
#align filter.tendsto_sub_at_top_nat Filter.tendsto_sub_atTop_nat
theorem tendsto_add_atTop_iff_nat {f : ℕ → α} {l : Filter α} (k : ℕ) :
Tendsto (fun n => f (n + k)) atTop l ↔ Tendsto f atTop l :=
show Tendsto (f ∘ fun n => n + k) atTop l ↔ Tendsto f atTop l by
rw [← tendsto_map'_iff, map_add_atTop_eq_nat]
#align filter.tendsto_add_at_top_iff_nat Filter.tendsto_add_atTop_iff_nat
theorem map_div_atTop_eq_nat (k : ℕ) (hk : 0 < k) : map (fun a => a / k) atTop = atTop :=
map_atTop_eq_of_gc (fun b => b * k + (k - 1)) 1 (fun a b h => Nat.div_le_div_right h)
-- Porting note: there was a parse error in `calc`, use `simp` instead
(fun a b _ => by simp only [← Nat.lt_succ_iff, Nat.div_lt_iff_lt_mul hk, Nat.succ_eq_add_one,
add_assoc, tsub_add_cancel_of_le (Nat.one_le_iff_ne_zero.2 hk.ne'), add_mul, one_mul])
fun b _ =>
calc
b = b * k / k := by rw [Nat.mul_div_cancel b hk]
_ ≤ (b * k + (k - 1)) / k := Nat.div_le_div_right <| Nat.le_add_right _ _
#align filter.map_div_at_top_eq_nat Filter.map_div_atTop_eq_nat
/-- If `u` is a monotone function with linear ordered codomain and the range of `u` is not bounded
above, then `Tendsto u atTop atTop`. -/
theorem tendsto_atTop_atTop_of_monotone' [Preorder ι] [LinearOrder α] {u : ι → α} (h : Monotone u)
(H : ¬BddAbove (range u)) : Tendsto u atTop atTop := by
apply h.tendsto_atTop_atTop
intro b
rcases not_bddAbove_iff.1 H b with ⟨_, ⟨N, rfl⟩, hN⟩
exact ⟨N, le_of_lt hN⟩
#align filter.tendsto_at_top_at_top_of_monotone' Filter.tendsto_atTop_atTop_of_monotone'
/-- If `u` is a monotone function with linear ordered codomain and the range of `u` is not bounded
below, then `Tendsto u atBot atBot`. -/
theorem tendsto_atBot_atBot_of_monotone' [Preorder ι] [LinearOrder α] {u : ι → α} (h : Monotone u)
(H : ¬BddBelow (range u)) : Tendsto u atBot atBot :=
@tendsto_atTop_atTop_of_monotone' ιᵒᵈ αᵒᵈ _ _ _ h.dual H
#align filter.tendsto_at_bot_at_bot_of_monotone' Filter.tendsto_atBot_atBot_of_monotone'
| Mathlib/Order/Filter/AtTopBot.lean | 1,830 | 1,837 | theorem unbounded_of_tendsto_atTop [Nonempty α] [SemilatticeSup α] [Preorder β] [NoMaxOrder β]
{f : α → β} (h : Tendsto f atTop atTop) : ¬BddAbove (range f) := by |
rintro ⟨M, hM⟩
cases' mem_atTop_sets.mp (h <| Ioi_mem_atTop M) with a ha
apply lt_irrefl M
calc
M < f a := ha a le_rfl
_ ≤ M := hM (Set.mem_range_self a)
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Sean Leather
-/
import Mathlib.Data.List.Range
import Mathlib.Data.List.Perm
#align_import data.list.sigma from "leanprover-community/mathlib"@"f808feb6c18afddb25e66a71d317643cf7fb5fbb"
/-!
# Utilities for lists of sigmas
This file includes several ways of interacting with `List (Sigma β)`, treated as a key-value store.
If `α : Type*` and `β : α → Type*`, then we regard `s : Sigma β` as having key `s.1 : α` and value
`s.2 : β s.1`. Hence, `List (Sigma β)` behaves like a key-value store.
## Main Definitions
- `List.keys` extracts the list of keys.
- `List.NodupKeys` determines if the store has duplicate keys.
- `List.lookup`/`lookup_all` accesses the value(s) of a particular key.
- `List.kreplace` replaces the first value with a given key by a given value.
- `List.kerase` removes a value.
- `List.kinsert` inserts a value.
- `List.kunion` computes the union of two stores.
- `List.kextract` returns a value with a given key and the rest of the values.
-/
universe u v
namespace List
variable {α : Type u} {β : α → Type v} {l l₁ l₂ : List (Sigma β)}
/-! ### `keys` -/
/-- List of keys from a list of key-value pairs -/
def keys : List (Sigma β) → List α :=
map Sigma.fst
#align list.keys List.keys
@[simp]
theorem keys_nil : @keys α β [] = [] :=
rfl
#align list.keys_nil List.keys_nil
@[simp]
theorem keys_cons {s} {l : List (Sigma β)} : (s :: l).keys = s.1 :: l.keys :=
rfl
#align list.keys_cons List.keys_cons
theorem mem_keys_of_mem {s : Sigma β} {l : List (Sigma β)} : s ∈ l → s.1 ∈ l.keys :=
mem_map_of_mem Sigma.fst
#align list.mem_keys_of_mem List.mem_keys_of_mem
theorem exists_of_mem_keys {a} {l : List (Sigma β)} (h : a ∈ l.keys) :
∃ b : β a, Sigma.mk a b ∈ l :=
let ⟨⟨_, b'⟩, m, e⟩ := exists_of_mem_map h
Eq.recOn e (Exists.intro b' m)
#align list.exists_of_mem_keys List.exists_of_mem_keys
theorem mem_keys {a} {l : List (Sigma β)} : a ∈ l.keys ↔ ∃ b : β a, Sigma.mk a b ∈ l :=
⟨exists_of_mem_keys, fun ⟨_, h⟩ => mem_keys_of_mem h⟩
#align list.mem_keys List.mem_keys
theorem not_mem_keys {a} {l : List (Sigma β)} : a ∉ l.keys ↔ ∀ b : β a, Sigma.mk a b ∉ l :=
(not_congr mem_keys).trans not_exists
#align list.not_mem_keys List.not_mem_keys
theorem not_eq_key {a} {l : List (Sigma β)} : a ∉ l.keys ↔ ∀ s : Sigma β, s ∈ l → a ≠ s.1 :=
Iff.intro (fun h₁ s h₂ e => absurd (mem_keys_of_mem h₂) (by rwa [e] at h₁)) fun f h₁ =>
let ⟨b, h₂⟩ := exists_of_mem_keys h₁
f _ h₂ rfl
#align list.not_eq_key List.not_eq_key
/-! ### `NodupKeys` -/
/-- Determines whether the store uses a key several times. -/
def NodupKeys (l : List (Sigma β)) : Prop :=
l.keys.Nodup
#align list.nodupkeys List.NodupKeys
theorem nodupKeys_iff_pairwise {l} : NodupKeys l ↔ Pairwise (fun s s' : Sigma β => s.1 ≠ s'.1) l :=
pairwise_map
#align list.nodupkeys_iff_pairwise List.nodupKeys_iff_pairwise
theorem NodupKeys.pairwise_ne {l} (h : NodupKeys l) :
Pairwise (fun s s' : Sigma β => s.1 ≠ s'.1) l :=
nodupKeys_iff_pairwise.1 h
#align list.nodupkeys.pairwise_ne List.NodupKeys.pairwise_ne
@[simp]
theorem nodupKeys_nil : @NodupKeys α β [] :=
Pairwise.nil
#align list.nodupkeys_nil List.nodupKeys_nil
@[simp]
theorem nodupKeys_cons {s : Sigma β} {l : List (Sigma β)} :
NodupKeys (s :: l) ↔ s.1 ∉ l.keys ∧ NodupKeys l := by simp [keys, NodupKeys]
#align list.nodupkeys_cons List.nodupKeys_cons
theorem not_mem_keys_of_nodupKeys_cons {s : Sigma β} {l : List (Sigma β)} (h : NodupKeys (s :: l)) :
s.1 ∉ l.keys :=
(nodupKeys_cons.1 h).1
#align list.not_mem_keys_of_nodupkeys_cons List.not_mem_keys_of_nodupKeys_cons
theorem nodupKeys_of_nodupKeys_cons {s : Sigma β} {l : List (Sigma β)} (h : NodupKeys (s :: l)) :
NodupKeys l :=
(nodupKeys_cons.1 h).2
#align list.nodupkeys_of_nodupkeys_cons List.nodupKeys_of_nodupKeys_cons
theorem NodupKeys.eq_of_fst_eq {l : List (Sigma β)} (nd : NodupKeys l) {s s' : Sigma β} (h : s ∈ l)
(h' : s' ∈ l) : s.1 = s'.1 → s = s' :=
@Pairwise.forall_of_forall _ (fun s s' : Sigma β => s.1 = s'.1 → s = s') _
(fun _ _ H h => (H h.symm).symm) (fun _ _ _ => rfl)
((nodupKeys_iff_pairwise.1 nd).imp fun h h' => (h h').elim) _ h _ h'
#align list.nodupkeys.eq_of_fst_eq List.NodupKeys.eq_of_fst_eq
theorem NodupKeys.eq_of_mk_mem {a : α} {b b' : β a} {l : List (Sigma β)} (nd : NodupKeys l)
(h : Sigma.mk a b ∈ l) (h' : Sigma.mk a b' ∈ l) : b = b' := by
cases nd.eq_of_fst_eq h h' rfl; rfl
#align list.nodupkeys.eq_of_mk_mem List.NodupKeys.eq_of_mk_mem
theorem nodupKeys_singleton (s : Sigma β) : NodupKeys [s] :=
nodup_singleton _
#align list.nodupkeys_singleton List.nodupKeys_singleton
theorem NodupKeys.sublist {l₁ l₂ : List (Sigma β)} (h : l₁ <+ l₂) : NodupKeys l₂ → NodupKeys l₁ :=
Nodup.sublist <| h.map _
#align list.nodupkeys.sublist List.NodupKeys.sublist
protected theorem NodupKeys.nodup {l : List (Sigma β)} : NodupKeys l → Nodup l :=
Nodup.of_map _
#align list.nodupkeys.nodup List.NodupKeys.nodup
theorem perm_nodupKeys {l₁ l₂ : List (Sigma β)} (h : l₁ ~ l₂) : NodupKeys l₁ ↔ NodupKeys l₂ :=
(h.map _).nodup_iff
#align list.perm_nodupkeys List.perm_nodupKeys
theorem nodupKeys_join {L : List (List (Sigma β))} :
NodupKeys (join L) ↔ (∀ l ∈ L, NodupKeys l) ∧ Pairwise Disjoint (L.map keys) := by
rw [nodupKeys_iff_pairwise, pairwise_join, pairwise_map]
refine and_congr (forall₂_congr fun l _ => by simp [nodupKeys_iff_pairwise]) ?_
apply iff_of_eq; congr with (l₁ l₂)
simp [keys, disjoint_iff_ne]
#align list.nodupkeys_join List.nodupKeys_join
theorem nodup_enum_map_fst (l : List α) : (l.enum.map Prod.fst).Nodup := by simp [List.nodup_range]
#align list.nodup_enum_map_fst List.nodup_enum_map_fst
theorem mem_ext {l₀ l₁ : List (Sigma β)} (nd₀ : l₀.Nodup) (nd₁ : l₁.Nodup)
(h : ∀ x, x ∈ l₀ ↔ x ∈ l₁) : l₀ ~ l₁ :=
(perm_ext_iff_of_nodup nd₀ nd₁).2 h
#align list.mem_ext List.mem_ext
variable [DecidableEq α]
/-! ### `dlookup` -/
-- Porting note: renaming to `dlookup` since `lookup` already exists
/-- `dlookup a l` is the first value in `l` corresponding to the key `a`,
or `none` if no such element exists. -/
def dlookup (a : α) : List (Sigma β) → Option (β a)
| [] => none
| ⟨a', b⟩ :: l => if h : a' = a then some (Eq.recOn h b) else dlookup a l
#align list.lookup List.dlookup
@[simp]
theorem dlookup_nil (a : α) : dlookup a [] = @none (β a) :=
rfl
#align list.lookup_nil List.dlookup_nil
@[simp]
theorem dlookup_cons_eq (l) (a : α) (b : β a) : dlookup a (⟨a, b⟩ :: l) = some b :=
dif_pos rfl
#align list.lookup_cons_eq List.dlookup_cons_eq
@[simp]
theorem dlookup_cons_ne (l) {a} : ∀ s : Sigma β, a ≠ s.1 → dlookup a (s :: l) = dlookup a l
| ⟨_, _⟩, h => dif_neg h.symm
#align list.lookup_cons_ne List.dlookup_cons_ne
theorem dlookup_isSome {a : α} : ∀ {l : List (Sigma β)}, (dlookup a l).isSome ↔ a ∈ l.keys
| [] => by simp
| ⟨a', b⟩ :: l => by
by_cases h : a = a'
· subst a'
simp
· simp [h, dlookup_isSome]
#align list.lookup_is_some List.dlookup_isSome
theorem dlookup_eq_none {a : α} {l : List (Sigma β)} : dlookup a l = none ↔ a ∉ l.keys := by
simp [← dlookup_isSome, Option.isNone_iff_eq_none]
#align list.lookup_eq_none List.dlookup_eq_none
theorem of_mem_dlookup {a : α} {b : β a} :
∀ {l : List (Sigma β)}, b ∈ dlookup a l → Sigma.mk a b ∈ l
| ⟨a', b'⟩ :: l, H => by
by_cases h : a = a'
· subst a'
simp? at H says simp only [dlookup_cons_eq, Option.mem_def, Option.some.injEq] at H
simp [H]
· simp only [ne_eq, h, not_false_iff, dlookup_cons_ne] at H
simp [of_mem_dlookup H]
#align list.of_mem_lookup List.of_mem_dlookup
theorem mem_dlookup {a} {b : β a} {l : List (Sigma β)} (nd : l.NodupKeys) (h : Sigma.mk a b ∈ l) :
b ∈ dlookup a l := by
cases' Option.isSome_iff_exists.mp (dlookup_isSome.mpr (mem_keys_of_mem h)) with b' h'
cases nd.eq_of_mk_mem h (of_mem_dlookup h')
exact h'
#align list.mem_lookup List.mem_dlookup
theorem map_dlookup_eq_find (a : α) :
∀ l : List (Sigma β), (dlookup a l).map (Sigma.mk a) = find? (fun s => a = s.1) l
| [] => rfl
| ⟨a', b'⟩ :: l => by
by_cases h : a = a'
· subst a'
simp
· simpa [h] using map_dlookup_eq_find a l
#align list.map_lookup_eq_find List.map_dlookup_eq_find
theorem mem_dlookup_iff {a : α} {b : β a} {l : List (Sigma β)} (nd : l.NodupKeys) :
b ∈ dlookup a l ↔ Sigma.mk a b ∈ l :=
⟨of_mem_dlookup, mem_dlookup nd⟩
#align list.mem_lookup_iff List.mem_dlookup_iff
theorem perm_dlookup (a : α) {l₁ l₂ : List (Sigma β)} (nd₁ : l₁.NodupKeys) (nd₂ : l₂.NodupKeys)
(p : l₁ ~ l₂) : dlookup a l₁ = dlookup a l₂ := by
ext b; simp only [mem_dlookup_iff nd₁, mem_dlookup_iff nd₂]; exact p.mem_iff
#align list.perm_lookup List.perm_dlookup
theorem lookup_ext {l₀ l₁ : List (Sigma β)} (nd₀ : l₀.NodupKeys) (nd₁ : l₁.NodupKeys)
(h : ∀ x y, y ∈ l₀.dlookup x ↔ y ∈ l₁.dlookup x) : l₀ ~ l₁ :=
mem_ext nd₀.nodup nd₁.nodup fun ⟨a, b⟩ => by
rw [← mem_dlookup_iff, ← mem_dlookup_iff, h] <;> assumption
#align list.lookup_ext List.lookup_ext
/-! ### `lookupAll` -/
/-- `lookup_all a l` is the list of all values in `l` corresponding to the key `a`. -/
def lookupAll (a : α) : List (Sigma β) → List (β a)
| [] => []
| ⟨a', b⟩ :: l => if h : a' = a then Eq.recOn h b :: lookupAll a l else lookupAll a l
#align list.lookup_all List.lookupAll
@[simp]
theorem lookupAll_nil (a : α) : lookupAll a [] = @nil (β a) :=
rfl
#align list.lookup_all_nil List.lookupAll_nil
@[simp]
theorem lookupAll_cons_eq (l) (a : α) (b : β a) : lookupAll a (⟨a, b⟩ :: l) = b :: lookupAll a l :=
dif_pos rfl
#align list.lookup_all_cons_eq List.lookupAll_cons_eq
@[simp]
theorem lookupAll_cons_ne (l) {a} : ∀ s : Sigma β, a ≠ s.1 → lookupAll a (s :: l) = lookupAll a l
| ⟨_, _⟩, h => dif_neg h.symm
#align list.lookup_all_cons_ne List.lookupAll_cons_ne
theorem lookupAll_eq_nil {a : α} :
∀ {l : List (Sigma β)}, lookupAll a l = [] ↔ ∀ b : β a, Sigma.mk a b ∉ l
| [] => by simp
| ⟨a', b⟩ :: l => by
by_cases h : a = a'
· subst a'
simp only [lookupAll_cons_eq, mem_cons, Sigma.mk.inj_iff, heq_eq_eq, true_and, not_or,
false_iff, not_forall, not_and, not_not]
use b
simp
· simp [h, lookupAll_eq_nil]
#align list.lookup_all_eq_nil List.lookupAll_eq_nil
theorem head?_lookupAll (a : α) : ∀ l : List (Sigma β), head? (lookupAll a l) = dlookup a l
| [] => by simp
| ⟨a', b⟩ :: l => by
by_cases h : a = a'
· subst h; simp
· rw [lookupAll_cons_ne, dlookup_cons_ne, head?_lookupAll a l] <;> assumption
#align list.head_lookup_all List.head?_lookupAll
theorem mem_lookupAll {a : α} {b : β a} :
∀ {l : List (Sigma β)}, b ∈ lookupAll a l ↔ Sigma.mk a b ∈ l
| [] => by simp
| ⟨a', b'⟩ :: l => by
by_cases h : a = a'
· subst h
simp [*, mem_lookupAll]
· simp [*, mem_lookupAll]
#align list.mem_lookup_all List.mem_lookupAll
theorem lookupAll_sublist (a : α) : ∀ l : List (Sigma β), (lookupAll a l).map (Sigma.mk a) <+ l
| [] => by simp
| ⟨a', b'⟩ :: l => by
by_cases h : a = a'
· subst h
simp only [ne_eq, not_true, lookupAll_cons_eq, List.map]
exact (lookupAll_sublist a l).cons₂ _
· simp only [ne_eq, h, not_false_iff, lookupAll_cons_ne]
exact (lookupAll_sublist a l).cons _
#align list.lookup_all_sublist List.lookupAll_sublist
theorem lookupAll_length_le_one (a : α) {l : List (Sigma β)} (h : l.NodupKeys) :
length (lookupAll a l) ≤ 1 := by
have := Nodup.sublist ((lookupAll_sublist a l).map _) h
rw [map_map] at this
rwa [← nodup_replicate, ← map_const]
#align list.lookup_all_length_le_one List.lookupAll_length_le_one
theorem lookupAll_eq_dlookup (a : α) {l : List (Sigma β)} (h : l.NodupKeys) :
lookupAll a l = (dlookup a l).toList := by
rw [← head?_lookupAll]
have h1 := lookupAll_length_le_one a h; revert h1
rcases lookupAll a l with (_ | ⟨b, _ | ⟨c, l⟩⟩) <;> intro h1 <;> try rfl
exact absurd h1 (by simp)
#align list.lookup_all_eq_lookup List.lookupAll_eq_dlookup
theorem lookupAll_nodup (a : α) {l : List (Sigma β)} (h : l.NodupKeys) : (lookupAll a l).Nodup := by
(rw [lookupAll_eq_dlookup a h]; apply Option.toList_nodup)
#align list.lookup_all_nodup List.lookupAll_nodup
theorem perm_lookupAll (a : α) {l₁ l₂ : List (Sigma β)} (nd₁ : l₁.NodupKeys) (nd₂ : l₂.NodupKeys)
(p : l₁ ~ l₂) : lookupAll a l₁ = lookupAll a l₂ := by
simp [lookupAll_eq_dlookup, nd₁, nd₂, perm_dlookup a nd₁ nd₂ p]
#align list.perm_lookup_all List.perm_lookupAll
/-! ### `kreplace` -/
/-- Replaces the first value with key `a` by `b`. -/
def kreplace (a : α) (b : β a) : List (Sigma β) → List (Sigma β) :=
lookmap fun s => if a = s.1 then some ⟨a, b⟩ else none
#align list.kreplace List.kreplace
theorem kreplace_of_forall_not (a : α) (b : β a) {l : List (Sigma β)}
(H : ∀ b : β a, Sigma.mk a b ∉ l) : kreplace a b l = l :=
lookmap_of_forall_not _ <| by
rintro ⟨a', b'⟩ h; dsimp; split_ifs
· subst a'
exact H _ h
· rfl
#align list.kreplace_of_forall_not List.kreplace_of_forall_not
theorem kreplace_self {a : α} {b : β a} {l : List (Sigma β)} (nd : NodupKeys l)
(h : Sigma.mk a b ∈ l) : kreplace a b l = l := by
refine (lookmap_congr ?_).trans (lookmap_id' (Option.guard fun (s : Sigma β) => a = s.1) ?_ _)
· rintro ⟨a', b'⟩ h'
dsimp [Option.guard]
split_ifs
· subst a'
simp [nd.eq_of_mk_mem h h']
· rfl
· rintro ⟨a₁, b₁⟩ ⟨a₂, b₂⟩
dsimp [Option.guard]
split_ifs
· simp
· rintro ⟨⟩
#align list.kreplace_self List.kreplace_self
theorem keys_kreplace (a : α) (b : β a) : ∀ l : List (Sigma β), (kreplace a b l).keys = l.keys :=
lookmap_map_eq _ _ <| by
rintro ⟨a₁, b₂⟩ ⟨a₂, b₂⟩
dsimp
split_ifs with h <;> simp (config := { contextual := true }) [h]
#align list.keys_kreplace List.keys_kreplace
theorem kreplace_nodupKeys (a : α) (b : β a) {l : List (Sigma β)} :
(kreplace a b l).NodupKeys ↔ l.NodupKeys := by simp [NodupKeys, keys_kreplace]
#align list.kreplace_nodupkeys List.kreplace_nodupKeys
theorem Perm.kreplace {a : α} {b : β a} {l₁ l₂ : List (Sigma β)} (nd : l₁.NodupKeys) :
l₁ ~ l₂ → kreplace a b l₁ ~ kreplace a b l₂ :=
perm_lookmap _ <| by
refine nd.pairwise_ne.imp ?_
intro x y h z h₁ w h₂
split_ifs at h₁ h₂ with h_2 h_1 <;> cases h₁ <;> cases h₂
exact (h (h_2.symm.trans h_1)).elim
#align list.perm.kreplace List.Perm.kreplace
/-! ### `kerase` -/
/-- Remove the first pair with the key `a`. -/
def kerase (a : α) : List (Sigma β) → List (Sigma β) :=
eraseP fun s => a = s.1
#align list.kerase List.kerase
-- Porting note (#10618): removing @[simp], `simp` can prove it
theorem kerase_nil {a} : @kerase _ β _ a [] = [] :=
rfl
#align list.kerase_nil List.kerase_nil
@[simp]
| Mathlib/Data/List/Sigma.lean | 402 | 403 | theorem kerase_cons_eq {a} {s : Sigma β} {l : List (Sigma β)} (h : a = s.1) :
kerase a (s :: l) = l := by | simp [kerase, h]
|
/-
Copyright (c) 2021 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Scott Morrison
-/
import Mathlib.Algebra.Homology.ComplexShape
import Mathlib.CategoryTheory.Subobject.Limits
import Mathlib.CategoryTheory.GradedObject
import Mathlib.Algebra.Homology.ShortComplex.Basic
#align_import algebra.homology.homological_complex from "leanprover-community/mathlib"@"88bca0ce5d22ebfd9e73e682e51d60ea13b48347"
/-!
# Homological complexes.
A `HomologicalComplex V c` with a "shape" controlled by `c : ComplexShape ι`
has chain groups `X i` (objects in `V`) indexed by `i : ι`,
and a differential `d i j` whenever `c.Rel i j`.
We in fact ask for differentials `d i j` for all `i j : ι`,
but have a field `shape` requiring that these are zero when not allowed by `c`.
This avoids a lot of dependent type theory hell!
The composite of any two differentials `d i j ≫ d j k` must be zero.
We provide `ChainComplex V α` for
`α`-indexed chain complexes in which `d i j ≠ 0` only if `j + 1 = i`,
and similarly `CochainComplex V α`, with `i = j + 1`.
There is a category structure, where morphisms are chain maps.
For `C : HomologicalComplex V c`, we define `C.xNext i`, which is either `C.X j` for some
arbitrarily chosen `j` such that `c.r i j`, or `C.X i` if there is no such `j`.
Similarly we have `C.xPrev j`.
Defined in terms of these we have `C.dFrom i : C.X i ⟶ C.xNext i` and
`C.dTo j : C.xPrev j ⟶ C.X j`, which are either defined as `C.d i j`, or zero, as needed.
-/
universe v u
open CategoryTheory CategoryTheory.Category CategoryTheory.Limits
variable {ι : Type*}
variable (V : Type u) [Category.{v} V] [HasZeroMorphisms V]
/-- A `HomologicalComplex V c` with a "shape" controlled by `c : ComplexShape ι`
has chain groups `X i` (objects in `V`) indexed by `i : ι`,
and a differential `d i j` whenever `c.Rel i j`.
We in fact ask for differentials `d i j` for all `i j : ι`,
but have a field `shape` requiring that these are zero when not allowed by `c`.
This avoids a lot of dependent type theory hell!
The composite of any two differentials `d i j ≫ d j k` must be zero.
-/
structure HomologicalComplex (c : ComplexShape ι) where
X : ι → V
d : ∀ i j, X i ⟶ X j
shape : ∀ i j, ¬c.Rel i j → d i j = 0 := by aesop_cat
d_comp_d' : ∀ i j k, c.Rel i j → c.Rel j k → d i j ≫ d j k = 0 := by aesop_cat
#align homological_complex HomologicalComplex
namespace HomologicalComplex
attribute [simp] shape
variable {V} {c : ComplexShape ι}
@[reassoc (attr := simp)]
theorem d_comp_d (C : HomologicalComplex V c) (i j k : ι) : C.d i j ≫ C.d j k = 0 := by
by_cases hij : c.Rel i j
· by_cases hjk : c.Rel j k
· exact C.d_comp_d' i j k hij hjk
· rw [C.shape j k hjk, comp_zero]
· rw [C.shape i j hij, zero_comp]
#align homological_complex.d_comp_d HomologicalComplex.d_comp_d
theorem ext {C₁ C₂ : HomologicalComplex V c} (h_X : C₁.X = C₂.X)
(h_d :
∀ i j : ι,
c.Rel i j → C₁.d i j ≫ eqToHom (congr_fun h_X j) = eqToHom (congr_fun h_X i) ≫ C₂.d i j) :
C₁ = C₂ := by
obtain ⟨X₁, d₁, s₁, h₁⟩ := C₁
obtain ⟨X₂, d₂, s₂, h₂⟩ := C₂
dsimp at h_X
subst h_X
simp only [mk.injEq, heq_eq_eq, true_and]
ext i j
by_cases hij: c.Rel i j
· simpa only [comp_id, id_comp, eqToHom_refl] using h_d i j hij
· rw [s₁ i j hij, s₂ i j hij]
#align homological_complex.ext HomologicalComplex.ext
/-- The obvious isomorphism `K.X p ≅ K.X q` when `p = q`. -/
def XIsoOfEq (K : HomologicalComplex V c) {p q : ι} (h : p = q) : K.X p ≅ K.X q :=
eqToIso (by rw [h])
@[simp]
lemma XIsoOfEq_rfl (K : HomologicalComplex V c) (p : ι) :
K.XIsoOfEq (rfl : p = p) = Iso.refl _ := rfl
@[reassoc (attr := simp)]
lemma XIsoOfEq_hom_comp_XIsoOfEq_hom (K : HomologicalComplex V c) {p₁ p₂ p₃ : ι}
(h₁₂ : p₁ = p₂) (h₂₃ : p₂ = p₃) :
(K.XIsoOfEq h₁₂).hom ≫ (K.XIsoOfEq h₂₃).hom = (K.XIsoOfEq (h₁₂.trans h₂₃)).hom := by
dsimp [XIsoOfEq]
simp only [eqToHom_trans]
@[reassoc (attr := simp)]
lemma XIsoOfEq_hom_comp_XIsoOfEq_inv (K : HomologicalComplex V c) {p₁ p₂ p₃ : ι}
(h₁₂ : p₁ = p₂) (h₃₂ : p₃ = p₂) :
(K.XIsoOfEq h₁₂).hom ≫ (K.XIsoOfEq h₃₂).inv = (K.XIsoOfEq (h₁₂.trans h₃₂.symm)).hom := by
dsimp [XIsoOfEq]
simp only [eqToHom_trans]
@[reassoc (attr := simp)]
lemma XIsoOfEq_inv_comp_XIsoOfEq_hom (K : HomologicalComplex V c) {p₁ p₂ p₃ : ι}
(h₂₁ : p₂ = p₁) (h₂₃ : p₂ = p₃) :
(K.XIsoOfEq h₂₁).inv ≫ (K.XIsoOfEq h₂₃).hom = (K.XIsoOfEq (h₂₁.symm.trans h₂₃)).hom := by
dsimp [XIsoOfEq]
simp only [eqToHom_trans]
@[reassoc (attr := simp)]
lemma XIsoOfEq_inv_comp_XIsoOfEq_inv (K : HomologicalComplex V c) {p₁ p₂ p₃ : ι}
(h₂₁ : p₂ = p₁) (h₃₂ : p₃ = p₂) :
(K.XIsoOfEq h₂₁).inv ≫ (K.XIsoOfEq h₃₂).inv = (K.XIsoOfEq (h₃₂.trans h₂₁).symm).hom := by
dsimp [XIsoOfEq]
simp only [eqToHom_trans]
@[reassoc (attr := simp)]
lemma XIsoOfEq_hom_comp_d (K : HomologicalComplex V c) {p₁ p₂ : ι} (h : p₁ = p₂) (p₃ : ι) :
(K.XIsoOfEq h).hom ≫ K.d p₂ p₃ = K.d p₁ p₃ := by subst h; simp
@[reassoc (attr := simp)]
lemma XIsoOfEq_inv_comp_d (K : HomologicalComplex V c) {p₂ p₁ : ι} (h : p₂ = p₁) (p₃ : ι) :
(K.XIsoOfEq h).inv ≫ K.d p₂ p₃ = K.d p₁ p₃ := by subst h; simp
@[reassoc (attr := simp)]
lemma d_comp_XIsoOfEq_hom (K : HomologicalComplex V c) {p₂ p₃ : ι} (h : p₂ = p₃) (p₁ : ι) :
K.d p₁ p₂ ≫ (K.XIsoOfEq h).hom = K.d p₁ p₃ := by subst h; simp
@[reassoc (attr := simp)]
lemma d_comp_XIsoOfEq_inv (K : HomologicalComplex V c) {p₂ p₃ : ι} (h : p₃ = p₂) (p₁ : ι) :
K.d p₁ p₂ ≫ (K.XIsoOfEq h).inv = K.d p₁ p₃ := by subst h; simp
end HomologicalComplex
/-- An `α`-indexed chain complex is a `HomologicalComplex`
in which `d i j ≠ 0` only if `j + 1 = i`.
-/
abbrev ChainComplex (α : Type*) [AddRightCancelSemigroup α] [One α] : Type _ :=
HomologicalComplex V (ComplexShape.down α)
#align chain_complex ChainComplex
/-- An `α`-indexed cochain complex is a `HomologicalComplex`
in which `d i j ≠ 0` only if `i + 1 = j`.
-/
abbrev CochainComplex (α : Type*) [AddRightCancelSemigroup α] [One α] : Type _ :=
HomologicalComplex V (ComplexShape.up α)
#align cochain_complex CochainComplex
namespace ChainComplex
@[simp]
theorem prev (α : Type*) [AddRightCancelSemigroup α] [One α] (i : α) :
(ComplexShape.down α).prev i = i + 1 :=
(ComplexShape.down α).prev_eq' rfl
#align chain_complex.prev ChainComplex.prev
@[simp]
theorem next (α : Type*) [AddGroup α] [One α] (i : α) : (ComplexShape.down α).next i = i - 1 :=
(ComplexShape.down α).next_eq' <| sub_add_cancel _ _
#align chain_complex.next ChainComplex.next
@[simp]
theorem next_nat_zero : (ComplexShape.down ℕ).next 0 = 0 := by
classical
refine dif_neg ?_
push_neg
intro
apply Nat.noConfusion
#align chain_complex.next_nat_zero ChainComplex.next_nat_zero
@[simp]
theorem next_nat_succ (i : ℕ) : (ComplexShape.down ℕ).next (i + 1) = i :=
(ComplexShape.down ℕ).next_eq' rfl
#align chain_complex.next_nat_succ ChainComplex.next_nat_succ
end ChainComplex
namespace CochainComplex
@[simp]
theorem prev (α : Type*) [AddGroup α] [One α] (i : α) : (ComplexShape.up α).prev i = i - 1 :=
(ComplexShape.up α).prev_eq' <| sub_add_cancel _ _
#align cochain_complex.prev CochainComplex.prev
@[simp]
theorem next (α : Type*) [AddRightCancelSemigroup α] [One α] (i : α) :
(ComplexShape.up α).next i = i + 1 :=
(ComplexShape.up α).next_eq' rfl
#align cochain_complex.next CochainComplex.next
@[simp]
theorem prev_nat_zero : (ComplexShape.up ℕ).prev 0 = 0 := by
classical
refine dif_neg ?_
push_neg
intro
apply Nat.noConfusion
#align cochain_complex.prev_nat_zero CochainComplex.prev_nat_zero
@[simp]
theorem prev_nat_succ (i : ℕ) : (ComplexShape.up ℕ).prev (i + 1) = i :=
(ComplexShape.up ℕ).prev_eq' rfl
#align cochain_complex.prev_nat_succ CochainComplex.prev_nat_succ
end CochainComplex
namespace HomologicalComplex
variable {V}
variable {c : ComplexShape ι} (C : HomologicalComplex V c)
/-- A morphism of homological complexes consists of maps between the chain groups,
commuting with the differentials.
-/
@[ext]
structure Hom (A B : HomologicalComplex V c) where
f : ∀ i, A.X i ⟶ B.X i
comm' : ∀ i j, c.Rel i j → f i ≫ B.d i j = A.d i j ≫ f j := by aesop_cat
#align homological_complex.hom HomologicalComplex.Hom
@[reassoc (attr := simp)]
theorem Hom.comm {A B : HomologicalComplex V c} (f : A.Hom B) (i j : ι) :
f.f i ≫ B.d i j = A.d i j ≫ f.f j := by
by_cases hij : c.Rel i j
· exact f.comm' i j hij
· rw [A.shape i j hij, B.shape i j hij, comp_zero, zero_comp]
#align homological_complex.hom.comm HomologicalComplex.Hom.comm
instance (A B : HomologicalComplex V c) : Inhabited (Hom A B) :=
⟨{ f := fun i => 0 }⟩
/-- Identity chain map. -/
def id (A : HomologicalComplex V c) : Hom A A where f _ := 𝟙 _
#align homological_complex.id HomologicalComplex.id
/-- Composition of chain maps. -/
def comp (A B C : HomologicalComplex V c) (φ : Hom A B) (ψ : Hom B C) : Hom A C where
f i := φ.f i ≫ ψ.f i
#align homological_complex.comp HomologicalComplex.comp
section
attribute [local simp] id comp
instance : Category (HomologicalComplex V c) where
Hom := Hom
id := id
comp := comp _ _ _
end
-- Porting note: added because `Hom.ext` is not triggered automatically
@[ext]
lemma hom_ext {C D : HomologicalComplex V c} (f g : C ⟶ D)
(h : ∀ i, f.f i = g.f i) : f = g := by
apply Hom.ext
funext
apply h
@[simp]
theorem id_f (C : HomologicalComplex V c) (i : ι) : Hom.f (𝟙 C) i = 𝟙 (C.X i) :=
rfl
#align homological_complex.id_f HomologicalComplex.id_f
@[simp, reassoc]
theorem comp_f {C₁ C₂ C₃ : HomologicalComplex V c} (f : C₁ ⟶ C₂) (g : C₂ ⟶ C₃) (i : ι) :
(f ≫ g).f i = f.f i ≫ g.f i :=
rfl
#align homological_complex.comp_f HomologicalComplex.comp_f
@[simp]
theorem eqToHom_f {C₁ C₂ : HomologicalComplex V c} (h : C₁ = C₂) (n : ι) :
HomologicalComplex.Hom.f (eqToHom h) n =
eqToHom (congr_fun (congr_arg HomologicalComplex.X h) n) := by
subst h
rfl
#align homological_complex.eq_to_hom_f HomologicalComplex.eqToHom_f
-- We'll use this later to show that `HomologicalComplex V c` is preadditive when `V` is.
theorem hom_f_injective {C₁ C₂ : HomologicalComplex V c} :
Function.Injective fun f : Hom C₁ C₂ => f.f := by aesop_cat
#align homological_complex.hom_f_injective HomologicalComplex.hom_f_injective
instance (X Y : HomologicalComplex V c) : Zero (X ⟶ Y) :=
⟨{ f := fun i => 0}⟩
@[simp]
theorem zero_f (C D : HomologicalComplex V c) (i : ι) : (0 : C ⟶ D).f i = 0 :=
rfl
#align homological_complex.zero_apply HomologicalComplex.zero_f
instance : HasZeroMorphisms (HomologicalComplex V c) where
open ZeroObject
/-- The zero complex -/
noncomputable def zero [HasZeroObject V] : HomologicalComplex V c where
X _ := 0
d _ _ := 0
#align homological_complex.zero HomologicalComplex.zero
theorem isZero_zero [HasZeroObject V] : IsZero (zero : HomologicalComplex V c) := by
refine ⟨fun X => ⟨⟨⟨0⟩, fun f => ?_⟩⟩, fun X => ⟨⟨⟨0⟩, fun f => ?_⟩⟩⟩
all_goals
ext
dsimp [zero]
apply Subsingleton.elim
#align homological_complex.is_zero_zero HomologicalComplex.isZero_zero
instance [HasZeroObject V] : HasZeroObject (HomologicalComplex V c) :=
⟨⟨zero, isZero_zero⟩⟩
noncomputable instance [HasZeroObject V] : Inhabited (HomologicalComplex V c) :=
⟨zero⟩
theorem congr_hom {C D : HomologicalComplex V c} {f g : C ⟶ D} (w : f = g) (i : ι) :
f.f i = g.f i :=
congr_fun (congr_arg Hom.f w) i
#align homological_complex.congr_hom HomologicalComplex.congr_hom
lemma mono_of_mono_f {K L : HomologicalComplex V c} (φ : K ⟶ L)
(hφ : ∀ i, Mono (φ.f i)) : Mono φ where
right_cancellation g h eq := by
ext i
rw [← cancel_mono (φ.f i)]
exact congr_hom eq i
lemma epi_of_epi_f {K L : HomologicalComplex V c} (φ : K ⟶ L)
(hφ : ∀ i, Epi (φ.f i)) : Epi φ where
left_cancellation g h eq := by
ext i
rw [← cancel_epi (φ.f i)]
exact congr_hom eq i
section
variable (V c)
/-- The functor picking out the `i`-th object of a complex. -/
@[simps]
def eval (i : ι) : HomologicalComplex V c ⥤ V where
obj C := C.X i
map f := f.f i
#align homological_complex.eval HomologicalComplex.eval
/-- The functor forgetting the differential in a complex, obtaining a graded object. -/
@[simps]
def forget : HomologicalComplex V c ⥤ GradedObject ι V where
obj C := C.X
map f := f.f
#align homological_complex.forget HomologicalComplex.forget
instance : (forget V c).Faithful where
map_injective h := by
ext i
exact congr_fun h i
/-- Forgetting the differentials than picking out the `i`-th object is the same as
just picking out the `i`-th object. -/
@[simps!]
def forgetEval (i : ι) : forget V c ⋙ GradedObject.eval i ≅ eval V c i :=
NatIso.ofComponents fun X => Iso.refl _
#align homological_complex.forget_eval HomologicalComplex.forgetEval
end
noncomputable section
@[reassoc]
lemma XIsoOfEq_hom_naturality {K L : HomologicalComplex V c} (φ : K ⟶ L) {n n' : ι} (h : n = n') :
φ.f n ≫ (L.XIsoOfEq h).hom = (K.XIsoOfEq h).hom ≫ φ.f n' := by subst h; simp
@[reassoc]
lemma XIsoOfEq_inv_naturality {K L : HomologicalComplex V c} (φ : K ⟶ L) {n n' : ι} (h : n = n') :
φ.f n' ≫ (L.XIsoOfEq h).inv = (K.XIsoOfEq h).inv ≫ φ.f n := by subst h; simp
-- Porting note: removed @[simp] as the linter complained
/-- If `C.d i j` and `C.d i j'` are both allowed, then we must have `j = j'`,
and so the differentials only differ by an `eqToHom`.
-/
theorem d_comp_eqToHom {i j j' : ι} (rij : c.Rel i j) (rij' : c.Rel i j') :
C.d i j' ≫ eqToHom (congr_arg C.X (c.next_eq rij' rij)) = C.d i j := by
obtain rfl := c.next_eq rij rij'
simp only [eqToHom_refl, comp_id]
#align homological_complex.d_comp_eq_to_hom HomologicalComplex.d_comp_eqToHom
-- Porting note: removed @[simp] as the linter complained
/-- If `C.d i j` and `C.d i' j` are both allowed, then we must have `i = i'`,
and so the differentials only differ by an `eqToHom`.
-/
theorem eqToHom_comp_d {i i' j : ι} (rij : c.Rel i j) (rij' : c.Rel i' j) :
eqToHom (congr_arg C.X (c.prev_eq rij rij')) ≫ C.d i' j = C.d i j := by
obtain rfl := c.prev_eq rij rij'
simp only [eqToHom_refl, id_comp]
#align homological_complex.eq_to_hom_comp_d HomologicalComplex.eqToHom_comp_d
theorem kernel_eq_kernel [HasKernels V] {i j j' : ι} (r : c.Rel i j) (r' : c.Rel i j') :
kernelSubobject (C.d i j) = kernelSubobject (C.d i j') := by
rw [← d_comp_eqToHom C r r']
apply kernelSubobject_comp_mono
#align homological_complex.kernel_eq_kernel HomologicalComplex.kernel_eq_kernel
theorem image_eq_image [HasImages V] [HasEqualizers V] {i i' j : ι} (r : c.Rel i j)
(r' : c.Rel i' j) : imageSubobject (C.d i j) = imageSubobject (C.d i' j) := by
rw [← eqToHom_comp_d C r r']
apply imageSubobject_iso_comp
#align homological_complex.image_eq_image HomologicalComplex.image_eq_image
section
/-- Either `C.X i`, if there is some `i` with `c.Rel i j`, or `C.X j`. -/
abbrev xPrev (j : ι) : V :=
C.X (c.prev j)
set_option linter.uppercaseLean3 false in
#align homological_complex.X_prev HomologicalComplex.xPrev
/-- If `c.Rel i j`, then `C.xPrev j` is isomorphic to `C.X i`. -/
def xPrevIso {i j : ι} (r : c.Rel i j) : C.xPrev j ≅ C.X i :=
eqToIso <| by rw [← c.prev_eq' r]
set_option linter.uppercaseLean3 false in
#align homological_complex.X_prev_iso HomologicalComplex.xPrevIso
/-- If there is no `i` so `c.Rel i j`, then `C.xPrev j` is isomorphic to `C.X j`. -/
def xPrevIsoSelf {j : ι} (h : ¬c.Rel (c.prev j) j) : C.xPrev j ≅ C.X j :=
eqToIso <|
congr_arg C.X
(by
dsimp [ComplexShape.prev]
rw [dif_neg]
push_neg; intro i hi
have : c.prev j = i := c.prev_eq' hi
rw [this] at h; contradiction)
set_option linter.uppercaseLean3 false in
#align homological_complex.X_prev_iso_self HomologicalComplex.xPrevIsoSelf
/-- Either `C.X j`, if there is some `j` with `c.rel i j`, or `C.X i`. -/
abbrev xNext (i : ι) : V :=
C.X (c.next i)
set_option linter.uppercaseLean3 false in
#align homological_complex.X_next HomologicalComplex.xNext
/-- If `c.Rel i j`, then `C.xNext i` is isomorphic to `C.X j`. -/
def xNextIso {i j : ι} (r : c.Rel i j) : C.xNext i ≅ C.X j :=
eqToIso <| by rw [← c.next_eq' r]
set_option linter.uppercaseLean3 false in
#align homological_complex.X_next_iso HomologicalComplex.xNextIso
/-- If there is no `j` so `c.Rel i j`, then `C.xNext i` is isomorphic to `C.X i`. -/
def xNextIsoSelf {i : ι} (h : ¬c.Rel i (c.next i)) : C.xNext i ≅ C.X i :=
eqToIso <|
congr_arg C.X
(by
dsimp [ComplexShape.next]
rw [dif_neg]; rintro ⟨j, hj⟩
have : c.next i = j := c.next_eq' hj
rw [this] at h; contradiction)
set_option linter.uppercaseLean3 false in
#align homological_complex.X_next_iso_self HomologicalComplex.xNextIsoSelf
/-- The differential mapping into `C.X j`, or zero if there isn't one.
-/
abbrev dTo (j : ι) : C.xPrev j ⟶ C.X j :=
C.d (c.prev j) j
#align homological_complex.d_to HomologicalComplex.dTo
/-- The differential mapping out of `C.X i`, or zero if there isn't one.
-/
abbrev dFrom (i : ι) : C.X i ⟶ C.xNext i :=
C.d i (c.next i)
#align homological_complex.d_from HomologicalComplex.dFrom
theorem dTo_eq {i j : ι} (r : c.Rel i j) : C.dTo j = (C.xPrevIso r).hom ≫ C.d i j := by
obtain rfl := c.prev_eq' r
exact (Category.id_comp _).symm
#align homological_complex.d_to_eq HomologicalComplex.dTo_eq
@[simp]
theorem dTo_eq_zero {j : ι} (h : ¬c.Rel (c.prev j) j) : C.dTo j = 0 :=
C.shape _ _ h
#align homological_complex.d_to_eq_zero HomologicalComplex.dTo_eq_zero
theorem dFrom_eq {i j : ι} (r : c.Rel i j) : C.dFrom i = C.d i j ≫ (C.xNextIso r).inv := by
obtain rfl := c.next_eq' r
exact (Category.comp_id _).symm
#align homological_complex.d_from_eq HomologicalComplex.dFrom_eq
@[simp]
theorem dFrom_eq_zero {i : ι} (h : ¬c.Rel i (c.next i)) : C.dFrom i = 0 :=
C.shape _ _ h
#align homological_complex.d_from_eq_zero HomologicalComplex.dFrom_eq_zero
@[reassoc (attr := simp)]
theorem xPrevIso_comp_dTo {i j : ι} (r : c.Rel i j) : (C.xPrevIso r).inv ≫ C.dTo j = C.d i j := by
simp [C.dTo_eq r]
set_option linter.uppercaseLean3 false in
#align homological_complex.X_prev_iso_comp_d_to HomologicalComplex.xPrevIso_comp_dTo
@[reassoc (attr := simp)]
theorem xPrevIsoSelf_comp_dTo {j : ι} (h : ¬c.Rel (c.prev j) j) :
(C.xPrevIsoSelf h).inv ≫ C.dTo j = 0 := by simp [h]
set_option linter.uppercaseLean3 false in
#align homological_complex.X_prev_iso_self_comp_d_to HomologicalComplex.xPrevIsoSelf_comp_dTo
@[reassoc (attr := simp)]
theorem dFrom_comp_xNextIso {i j : ι} (r : c.Rel i j) :
C.dFrom i ≫ (C.xNextIso r).hom = C.d i j := by
simp [C.dFrom_eq r]
set_option linter.uppercaseLean3 false in
#align homological_complex.d_from_comp_X_next_iso HomologicalComplex.dFrom_comp_xNextIso
@[reassoc (attr := simp)]
theorem dFrom_comp_xNextIsoSelf {i : ι} (h : ¬c.Rel i (c.next i)) :
C.dFrom i ≫ (C.xNextIsoSelf h).hom = 0 := by simp [h]
set_option linter.uppercaseLean3 false in
#align homological_complex.d_from_comp_X_next_iso_self HomologicalComplex.dFrom_comp_xNextIsoSelf
@[simp 1100]
theorem dTo_comp_dFrom (j : ι) : C.dTo j ≫ C.dFrom j = 0 :=
C.d_comp_d _ _ _
#align homological_complex.d_to_comp_d_from HomologicalComplex.dTo_comp_dFrom
theorem kernel_from_eq_kernel [HasKernels V] {i j : ι} (r : c.Rel i j) :
kernelSubobject (C.dFrom i) = kernelSubobject (C.d i j) := by
rw [C.dFrom_eq r]
apply kernelSubobject_comp_mono
#align homological_complex.kernel_from_eq_kernel HomologicalComplex.kernel_from_eq_kernel
theorem image_to_eq_image [HasImages V] [HasEqualizers V] {i j : ι} (r : c.Rel i j) :
imageSubobject (C.dTo j) = imageSubobject (C.d i j) := by
rw [C.dTo_eq r]
apply imageSubobject_iso_comp
#align homological_complex.image_to_eq_image HomologicalComplex.image_to_eq_image
end
namespace Hom
variable {C₁ C₂ C₃ : HomologicalComplex V c}
/-- The `i`-th component of an isomorphism of chain complexes. -/
@[simps!]
def isoApp (f : C₁ ≅ C₂) (i : ι) : C₁.X i ≅ C₂.X i :=
(eval V c i).mapIso f
#align homological_complex.hom.iso_app HomologicalComplex.Hom.isoApp
/-- Construct an isomorphism of chain complexes from isomorphism of the objects
which commute with the differentials. -/
@[simps]
def isoOfComponents (f : ∀ i, C₁.X i ≅ C₂.X i)
(hf : ∀ i j, c.Rel i j → (f i).hom ≫ C₂.d i j = C₁.d i j ≫ (f j).hom := by aesop_cat) :
C₁ ≅ C₂ where
hom :=
{ f := fun i => (f i).hom
comm' := hf }
inv :=
{ f := fun i => (f i).inv
comm' := fun i j hij =>
calc
(f i).inv ≫ C₁.d i j = (f i).inv ≫ (C₁.d i j ≫ (f j).hom) ≫ (f j).inv := by simp
_ = (f i).inv ≫ ((f i).hom ≫ C₂.d i j) ≫ (f j).inv := by rw [hf i j hij]
_ = C₂.d i j ≫ (f j).inv := by simp }
hom_inv_id := by
ext i
exact (f i).hom_inv_id
inv_hom_id := by
ext i
exact (f i).inv_hom_id
#align homological_complex.hom.iso_of_components HomologicalComplex.Hom.isoOfComponents
@[simp]
theorem isoOfComponents_app (f : ∀ i, C₁.X i ≅ C₂.X i)
(hf : ∀ i j, c.Rel i j → (f i).hom ≫ C₂.d i j = C₁.d i j ≫ (f j).hom) (i : ι) :
isoApp (isoOfComponents f hf) i = f i := by
ext
simp
#align homological_complex.hom.iso_of_components_app HomologicalComplex.Hom.isoOfComponents_app
theorem isIso_of_components (f : C₁ ⟶ C₂) [∀ n : ι, IsIso (f.f n)] : IsIso f :=
(HomologicalComplex.Hom.isoOfComponents fun n => asIso (f.f n)).isIso_hom
#align homological_complex.hom.is_iso_of_components HomologicalComplex.Hom.isIso_of_components
/-! Lemmas relating chain maps and `dTo`/`dFrom`. -/
/-- `f.prev j` is `f.f i` if there is some `r i j`, and `f.f j` otherwise. -/
abbrev prev (f : Hom C₁ C₂) (j : ι) : C₁.xPrev j ⟶ C₂.xPrev j :=
f.f _
#align homological_complex.hom.prev HomologicalComplex.Hom.prev
theorem prev_eq (f : Hom C₁ C₂) {i j : ι} (w : c.Rel i j) :
f.prev j = (C₁.xPrevIso w).hom ≫ f.f i ≫ (C₂.xPrevIso w).inv := by
obtain rfl := c.prev_eq' w
simp only [xPrevIso, eqToIso_refl, Iso.refl_hom, Iso.refl_inv, comp_id, id_comp]
#align homological_complex.hom.prev_eq HomologicalComplex.Hom.prev_eq
/-- `f.next i` is `f.f j` if there is some `r i j`, and `f.f j` otherwise. -/
abbrev next (f : Hom C₁ C₂) (i : ι) : C₁.xNext i ⟶ C₂.xNext i :=
f.f _
#align homological_complex.hom.next HomologicalComplex.Hom.next
theorem next_eq (f : Hom C₁ C₂) {i j : ι} (w : c.Rel i j) :
f.next i = (C₁.xNextIso w).hom ≫ f.f j ≫ (C₂.xNextIso w).inv := by
obtain rfl := c.next_eq' w
simp only [xNextIso, eqToIso_refl, Iso.refl_hom, Iso.refl_inv, comp_id, id_comp]
#align homological_complex.hom.next_eq HomologicalComplex.Hom.next_eq
@[reassoc, elementwise] -- @[simp] -- Porting note (#10618): simp can prove this
theorem comm_from (f : Hom C₁ C₂) (i : ι) : f.f i ≫ C₂.dFrom i = C₁.dFrom i ≫ f.next i :=
f.comm _ _
#align homological_complex.hom.comm_from HomologicalComplex.Hom.comm_from
attribute [simp 1100] comm_from_assoc
attribute [simp] comm_from_apply
@[reassoc, elementwise] -- @[simp] -- Porting note (#10618): simp can prove this
theorem comm_to (f : Hom C₁ C₂) (j : ι) : f.prev j ≫ C₂.dTo j = C₁.dTo j ≫ f.f j :=
f.comm _ _
#align homological_complex.hom.comm_to HomologicalComplex.Hom.comm_to
attribute [simp 1100] comm_to_assoc
attribute [simp] comm_to_apply
/-- A morphism of chain complexes
induces a morphism of arrows of the differentials out of each object.
-/
def sqFrom (f : Hom C₁ C₂) (i : ι) : Arrow.mk (C₁.dFrom i) ⟶ Arrow.mk (C₂.dFrom i) :=
Arrow.homMk (f.comm_from i)
#align homological_complex.hom.sq_from HomologicalComplex.Hom.sqFrom
@[simp]
theorem sqFrom_left (f : Hom C₁ C₂) (i : ι) : (f.sqFrom i).left = f.f i :=
rfl
#align homological_complex.hom.sq_from_left HomologicalComplex.Hom.sqFrom_left
@[simp]
theorem sqFrom_right (f : Hom C₁ C₂) (i : ι) : (f.sqFrom i).right = f.next i :=
rfl
#align homological_complex.hom.sq_from_right HomologicalComplex.Hom.sqFrom_right
@[simp]
theorem sqFrom_id (C₁ : HomologicalComplex V c) (i : ι) : sqFrom (𝟙 C₁) i = 𝟙 _ :=
rfl
#align homological_complex.hom.sq_from_id HomologicalComplex.Hom.sqFrom_id
@[simp]
theorem sqFrom_comp (f : C₁ ⟶ C₂) (g : C₂ ⟶ C₃) (i : ι) :
sqFrom (f ≫ g) i = sqFrom f i ≫ sqFrom g i :=
rfl
#align homological_complex.hom.sq_from_comp HomologicalComplex.Hom.sqFrom_comp
/-- A morphism of chain complexes
induces a morphism of arrows of the differentials into each object.
-/
def sqTo (f : Hom C₁ C₂) (j : ι) : Arrow.mk (C₁.dTo j) ⟶ Arrow.mk (C₂.dTo j) :=
Arrow.homMk (f.comm_to j)
#align homological_complex.hom.sq_to HomologicalComplex.Hom.sqTo
@[simp]
theorem sqTo_left (f : Hom C₁ C₂) (j : ι) : (f.sqTo j).left = f.prev j :=
rfl
#align homological_complex.hom.sq_to_left HomologicalComplex.Hom.sqTo_left
@[simp]
theorem sqTo_right (f : Hom C₁ C₂) (j : ι) : (f.sqTo j).right = f.f j :=
rfl
#align homological_complex.hom.sq_to_right HomologicalComplex.Hom.sqTo_right
end Hom
end
end HomologicalComplex
namespace ChainComplex
section Of
variable {V} {α : Type*} [AddRightCancelSemigroup α] [One α] [DecidableEq α]
/-- Construct an `α`-indexed chain complex from a dependently-typed differential.
-/
def of (X : α → V) (d : ∀ n, X (n + 1) ⟶ X n) (sq : ∀ n, d (n + 1) ≫ d n = 0) : ChainComplex V α :=
{ X := X
d := fun i j => if h : i = j + 1 then eqToHom (by rw [h]) ≫ d j else 0
shape := fun i j w => by
dsimp
rw [dif_neg (Ne.symm w)]
d_comp_d' := fun i j k hij hjk => by
dsimp at hij hjk
substs hij hjk
simp only [eqToHom_refl, id_comp, dite_eq_ite, ite_true, sq] }
#align chain_complex.of ChainComplex.of
variable (X : α → V) (d : ∀ n, X (n + 1) ⟶ X n) (sq : ∀ n, d (n + 1) ≫ d n = 0)
@[simp]
theorem of_x (n : α) : (of X d sq).X n = X n :=
rfl
set_option linter.uppercaseLean3 false in
#align chain_complex.of_X ChainComplex.of_x
@[simp]
theorem of_d (j : α) : (of X d sq).d (j + 1) j = d j := by
dsimp [of]
rw [if_pos rfl, Category.id_comp]
#align chain_complex.of_d ChainComplex.of_d
theorem of_d_ne {i j : α} (h : i ≠ j + 1) : (of X d sq).d i j = 0 := by
dsimp [of]
rw [dif_neg h]
#align chain_complex.of_d_ne ChainComplex.of_d_ne
end Of
section OfHom
variable {V} {α : Type*} [AddRightCancelSemigroup α] [One α] [DecidableEq α]
variable (X : α → V) (d_X : ∀ n, X (n + 1) ⟶ X n) (sq_X : ∀ n, d_X (n + 1) ≫ d_X n = 0) (Y : α → V)
(d_Y : ∀ n, Y (n + 1) ⟶ Y n) (sq_Y : ∀ n, d_Y (n + 1) ≫ d_Y n = 0)
/-- A constructor for chain maps between `α`-indexed chain complexes built using `ChainComplex.of`,
from a dependently typed collection of morphisms.
-/
@[simps]
def ofHom (f : ∀ i : α, X i ⟶ Y i) (comm : ∀ i : α, f (i + 1) ≫ d_Y i = d_X i ≫ f i) :
of X d_X sq_X ⟶ of Y d_Y sq_Y :=
{ f
comm' := fun n m => by
by_cases h : n = m + 1
· subst h
simpa using comm m
· rw [of_d_ne X _ _ h, of_d_ne Y _ _ h]
simp }
#align chain_complex.of_hom ChainComplex.ofHom
end OfHom
section Mk
variable {V}
variable (X₀ X₁ X₂ : V) (d₀ : X₁ ⟶ X₀) (d₁ : X₂ ⟶ X₁) (s : d₁ ≫ d₀ = 0)
(succ : ∀ (S : ShortComplex V), Σ' (X₃ : V) (d₂ : X₃ ⟶ S.X₁), d₂ ≫ S.f = 0)
/-- Auxiliary definition for `mk`. -/
def mkAux : ℕ → ShortComplex V
| 0 => ShortComplex.mk _ _ s
| n + 1 => ShortComplex.mk _ _ (succ (mkAux n)).2.2
#align chain_complex.mk_aux ChainComplex.mkAux
/-- An inductive constructor for `ℕ`-indexed chain complexes.
You provide explicitly the first two differentials,
then a function which takes two differentials and the fact they compose to zero,
and returns the next object, its differential, and the fact it composes appropriately to zero.
See also `mk'`, which only sees the previous differential in the inductive step.
-/
def mk : ChainComplex V ℕ :=
of (fun n => (mkAux X₀ X₁ X₂ d₀ d₁ s succ n).X₃) (fun n => (mkAux X₀ X₁ X₂ d₀ d₁ s succ n).g)
fun n => (mkAux X₀ X₁ X₂ d₀ d₁ s succ n).zero
#align chain_complex.mk ChainComplex.mk
@[simp]
theorem mk_X_0 : (mk X₀ X₁ X₂ d₀ d₁ s succ).X 0 = X₀ :=
rfl
set_option linter.uppercaseLean3 false in
#align chain_complex.mk_X_0 ChainComplex.mk_X_0
@[simp]
theorem mk_X_1 : (mk X₀ X₁ X₂ d₀ d₁ s succ).X 1 = X₁ :=
rfl
set_option linter.uppercaseLean3 false in
#align chain_complex.mk_X_1 ChainComplex.mk_X_1
@[simp]
theorem mk_X_2 : (mk X₀ X₁ X₂ d₀ d₁ s succ).X 2 = X₂ :=
rfl
set_option linter.uppercaseLean3 false in
#align chain_complex.mk_X_2 ChainComplex.mk_X_2
@[simp]
theorem mk_d_1_0 : (mk X₀ X₁ X₂ d₀ d₁ s succ).d 1 0 = d₀ := by
change ite (1 = 0 + 1) (𝟙 X₁ ≫ d₀) 0 = d₀
rw [if_pos rfl, Category.id_comp]
#align chain_complex.mk_d_1_0 ChainComplex.mk_d_1_0
@[simp]
theorem mk_d_2_1 : (mk X₀ X₁ X₂ d₀ d₁ s succ).d 2 1 = d₁ := by
change ite (2 = 1 + 1) (𝟙 X₂ ≫ d₁) 0 = d₁
rw [if_pos rfl, Category.id_comp]
#align chain_complex.mk_d_2_0 ChainComplex.mk_d_2_1
-- TODO simp lemmas for the inductive steps? It's not entirely clear that they are needed.
/-- A simpler inductive constructor for `ℕ`-indexed chain complexes.
You provide explicitly the first differential,
then a function which takes a differential,
and returns the next object, its differential, and the fact it composes appropriately to zero.
-/
def mk' (X₀ X₁ : V) (d : X₁ ⟶ X₀)
(succ' : ∀ {X₀ X₁ : V} (f : X₁ ⟶ X₀), Σ' (X₂ : V) (d : X₂ ⟶ X₁), d ≫ f = 0) :
ChainComplex V ℕ :=
mk _ _ _ _ _ (succ' d).2.2 (fun S => succ' S.f)
#align chain_complex.mk' ChainComplex.mk'
variable (succ' : ∀ {X₀ X₁ : V} (f : X₁ ⟶ X₀), Σ' (X₂ : V) (d : X₂ ⟶ X₁), d ≫ f = 0)
@[simp]
theorem mk'_X_0 : (mk' X₀ X₁ d₀ succ').X 0 = X₀ :=
rfl
set_option linter.uppercaseLean3 false in
#align chain_complex.mk'_X_0 ChainComplex.mk'_X_0
@[simp]
theorem mk'_X_1 : (mk' X₀ X₁ d₀ succ').X 1 = X₁ :=
rfl
set_option linter.uppercaseLean3 false in
#align chain_complex.mk'_X_1 ChainComplex.mk'_X_1
@[simp]
theorem mk'_d_1_0 : (mk' X₀ X₁ d₀ succ').d 1 0 = d₀ := by
change ite (1 = 0 + 1) (𝟙 X₁ ≫ d₀) 0 = d₀
rw [if_pos rfl, Category.id_comp]
#align chain_complex.mk'_d_1_0 ChainComplex.mk'_d_1_0
/- Porting note:
Downstream constructions using `mk'` (e.g. in `CategoryTheory.Abelian.Projective`)
have very slow proofs, because of bad simp lemmas.
It would be better to write good lemmas here if possible, such as
```
theorem mk'_X_succ (j : ℕ) :
(mk' X₀ X₁ d₀ succ').X (j + 2) = (succ' ⟨_, _, (mk' X₀ X₁ d₀ succ').d (j + 1) j⟩).1 := by
sorry
theorem mk'_d_succ {i j : ℕ} :
(mk' X₀ X₁ d₀ succ').d (j + 2) (j + 1) =
eqToHom (mk'_X_succ X₀ X₁ d₀ succ' j) ≫
(succ' ⟨_, _, (mk' X₀ X₁ d₀ succ').d (j + 1) j⟩).2.1 :=
sorry
```
These are already tricky, and it may be better to write analogous lemmas for `mk` first.
-/
end Mk
section MkHom
variable {V}
variable (P Q : ChainComplex V ℕ) (zero : P.X 0 ⟶ Q.X 0) (one : P.X 1 ⟶ Q.X 1)
(one_zero_comm : one ≫ Q.d 1 0 = P.d 1 0 ≫ zero)
(succ :
∀ (n : ℕ)
(p :
Σ' (f : P.X n ⟶ Q.X n) (f' : P.X (n + 1) ⟶ Q.X (n + 1)),
f' ≫ Q.d (n + 1) n = P.d (n + 1) n ≫ f),
Σ'f'' : P.X (n + 2) ⟶ Q.X (n + 2), f'' ≫ Q.d (n + 2) (n + 1) = P.d (n + 2) (n + 1) ≫ p.2.1)
/-- An auxiliary construction for `mkHom`.
Here we build by induction a family of commutative squares,
but don't require at the type level that these successive commutative squares actually agree.
They do in fact agree, and we then capture that at the type level (i.e. by constructing a chain map)
in `mkHom`.
-/
def mkHomAux :
∀ n,
Σ' (f : P.X n ⟶ Q.X n) (f' : P.X (n + 1) ⟶ Q.X (n + 1)),
f' ≫ Q.d (n + 1) n = P.d (n + 1) n ≫ f
| 0 => ⟨zero, one, one_zero_comm⟩
| n + 1 => ⟨(mkHomAux n).2.1, (succ n (mkHomAux n)).1, (succ n (mkHomAux n)).2⟩
#align chain_complex.mk_hom_aux ChainComplex.mkHomAux
/-- A constructor for chain maps between `ℕ`-indexed chain complexes,
working by induction on commutative squares.
You need to provide the components of the chain map in degrees 0 and 1,
show that these form a commutative square,
and then give a construction of each component,
and the fact that it forms a commutative square with the previous component,
using as an inductive hypothesis the data (and commutativity) of the previous two components.
-/
def mkHom : P ⟶ Q where
f n := (mkHomAux P Q zero one one_zero_comm succ n).1
comm' n m := by
rintro (rfl : m + 1 = n)
exact (mkHomAux P Q zero one one_zero_comm succ m).2.2
#align chain_complex.mk_hom ChainComplex.mkHom
@[simp]
theorem mkHom_f_0 : (mkHom P Q zero one one_zero_comm succ).f 0 = zero :=
rfl
#align chain_complex.mk_hom_f_0 ChainComplex.mkHom_f_0
@[simp]
theorem mkHom_f_1 : (mkHom P Q zero one one_zero_comm succ).f 1 = one :=
rfl
#align chain_complex.mk_hom_f_1 ChainComplex.mkHom_f_1
@[simp]
| Mathlib/Algebra/Homology/HomologicalComplex.lean | 919 | 925 | theorem mkHom_f_succ_succ (n : ℕ) :
(mkHom P Q zero one one_zero_comm succ).f (n + 2) =
(succ n
⟨(mkHom P Q zero one one_zero_comm succ).f n,
(mkHom P Q zero one one_zero_comm succ).f (n + 1),
(mkHom P Q zero one one_zero_comm succ).comm (n + 1) n⟩).1 := by |
dsimp [mkHom, mkHomAux]
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Michael Howes
-/
import Mathlib.Data.Finite.Card
import Mathlib.GroupTheory.Commutator
import Mathlib.GroupTheory.Finiteness
#align_import group_theory.abelianization from "leanprover-community/mathlib"@"4be589053caf347b899a494da75410deb55fb3ef"
/-!
# The abelianization of a group
This file defines the commutator and the abelianization of a group. It furthermore prepares for the
result that the abelianization is left adjoint to the forgetful functor from abelian groups to
groups, which can be found in `Algebra/Category/Group/Adjunctions`.
## Main definitions
* `commutator`: defines the commutator of a group `G` as a subgroup of `G`.
* `Abelianization`: defines the abelianization of a group `G` as the quotient of a group by its
commutator subgroup.
* `Abelianization.map`: lifts a group homomorphism to a homomorphism between the abelianizations
* `MulEquiv.abelianizationCongr`: Equivalent groups have equivalent abelianizations
-/
universe u v w
-- Let G be a group.
variable (G : Type u) [Group G]
open Subgroup (centralizer)
/-- The commutator subgroup of a group G is the normal subgroup
generated by the commutators [p,q]=`p*q*p⁻¹*q⁻¹`. -/
def commutator : Subgroup G := ⁅(⊤ : Subgroup G), ⊤⁆
#align commutator commutator
-- Porting note: this instance should come from `deriving Subgroup.Normal`
instance : Subgroup.Normal (commutator G) := Subgroup.commutator_normal ⊤ ⊤
theorem commutator_def : commutator G = ⁅(⊤ : Subgroup G), ⊤⁆ :=
rfl
#align commutator_def commutator_def
theorem commutator_eq_closure : commutator G = Subgroup.closure (commutatorSet G) := by
simp [commutator, Subgroup.commutator_def, commutatorSet]
#align commutator_eq_closure commutator_eq_closure
theorem commutator_eq_normalClosure : commutator G = Subgroup.normalClosure (commutatorSet G) := by
simp [commutator, Subgroup.commutator_def', commutatorSet]
#align commutator_eq_normal_closure commutator_eq_normalClosure
instance commutator_characteristic : (commutator G).Characteristic :=
Subgroup.commutator_characteristic ⊤ ⊤
#align commutator_characteristic commutator_characteristic
instance [Finite (commutatorSet G)] : Group.FG (commutator G) := by
rw [commutator_eq_closure]
apply Group.closure_finite_fg
theorem rank_commutator_le_card [Finite (commutatorSet G)] :
Group.rank (commutator G) ≤ Nat.card (commutatorSet G) := by
rw [Subgroup.rank_congr (commutator_eq_closure G)]
apply Subgroup.rank_closure_finite_le_nat_card
#align rank_commutator_le_card rank_commutator_le_card
theorem commutator_centralizer_commutator_le_center :
⁅centralizer (commutator G : Set G), centralizer (commutator G)⁆ ≤ Subgroup.center G := by
rw [← Subgroup.centralizer_univ, ← Subgroup.coe_top, ←
Subgroup.commutator_eq_bot_iff_le_centralizer]
suffices ⁅⁅⊤, centralizer (commutator G : Set G)⁆, centralizer (commutator G : Set G)⁆ = ⊥ by
refine Subgroup.commutator_commutator_eq_bot_of_rotate ?_ this
rwa [Subgroup.commutator_comm (centralizer (commutator G : Set G))]
rw [Subgroup.commutator_comm, Subgroup.commutator_eq_bot_iff_le_centralizer]
exact Set.centralizer_subset (Subgroup.commutator_mono le_top le_top)
#align commutator_centralizer_commutator_le_center commutator_centralizer_commutator_le_center
/-- The abelianization of G is the quotient of G by its commutator subgroup. -/
def Abelianization : Type u :=
G ⧸ commutator G
#align abelianization Abelianization
namespace Abelianization
attribute [local instance] QuotientGroup.leftRel
instance commGroup : CommGroup (Abelianization G) :=
{ QuotientGroup.Quotient.group _ with
mul_comm := fun x y =>
Quotient.inductionOn₂' x y fun a b =>
Quotient.sound' <|
QuotientGroup.leftRel_apply.mpr <|
Subgroup.subset_closure
⟨b⁻¹, Subgroup.mem_top b⁻¹, a⁻¹, Subgroup.mem_top a⁻¹, by group⟩ }
instance : Inhabited (Abelianization G) :=
⟨1⟩
instance [Unique G] : Unique (Abelianization G) := Quotient.instUniqueQuotient _
instance [Fintype G] [DecidablePred (· ∈ commutator G)] : Fintype (Abelianization G) :=
QuotientGroup.fintype (commutator G)
instance [Finite G] : Finite (Abelianization G) :=
Quotient.finite _
variable {G}
/-- `of` is the canonical projection from G to its abelianization. -/
def of : G →* Abelianization G where
toFun := QuotientGroup.mk
map_one' := rfl
map_mul' _ _ := rfl
#align abelianization.of Abelianization.of
@[simp]
theorem mk_eq_of (a : G) : Quot.mk _ a = of a :=
rfl
#align abelianization.mk_eq_of Abelianization.mk_eq_of
section lift
-- So far we have built Gᵃᵇ and proved it's an abelian group.
-- Furthermore we defined the canonical projection `of : G → Gᵃᵇ`
-- Let `A` be an abelian group and let `f` be a group homomorphism from `G` to `A`.
variable {A : Type v} [CommGroup A] (f : G →* A)
theorem commutator_subset_ker : commutator G ≤ f.ker := by
rw [commutator_eq_closure, Subgroup.closure_le]
rintro x ⟨p, q, rfl⟩
simp [MonoidHom.mem_ker, mul_right_comm (f p) (f q), commutatorElement_def]
#align abelianization.commutator_subset_ker Abelianization.commutator_subset_ker
/-- If `f : G → A` is a group homomorphism to an abelian group, then `lift f` is the unique map
from the abelianization of a `G` to `A` that factors through `f`. -/
def lift : (G →* A) ≃ (Abelianization G →* A) where
toFun f := QuotientGroup.lift _ f fun _ h => f.mem_ker.2 <| commutator_subset_ker _ h
invFun F := F.comp of
left_inv _ := MonoidHom.ext fun _ => rfl
right_inv _ := MonoidHom.ext fun x => QuotientGroup.induction_on x fun _ => rfl
#align abelianization.lift Abelianization.lift
@[simp]
theorem lift.of (x : G) : lift f (of x) = f x :=
rfl
#align abelianization.lift.of Abelianization.lift.of
theorem lift.unique (φ : Abelianization G →* A)
-- hφ : φ agrees with f on the image of G in Gᵃᵇ
(hφ : ∀ x : G, φ (Abelianization.of x) = f x)
{x : Abelianization G} : φ x = lift f x :=
QuotientGroup.induction_on x hφ
#align abelianization.lift.unique Abelianization.lift.unique
@[simp]
theorem lift_of : lift of = MonoidHom.id (Abelianization G) :=
lift.apply_symm_apply <| MonoidHom.id _
#align abelianization.lift_of Abelianization.lift_of
end lift
variable {A : Type v} [Monoid A]
/-- See note [partially-applied ext lemmas]. -/
@[ext]
theorem hom_ext (φ ψ : Abelianization G →* A) (h : φ.comp of = ψ.comp of) : φ = ψ :=
MonoidHom.ext fun x => QuotientGroup.induction_on x <| DFunLike.congr_fun h
#align abelianization.hom_ext Abelianization.hom_ext
section Map
variable {H : Type v} [Group H] (f : G →* H)
/-- The map operation of the `Abelianization` functor -/
def map : Abelianization G →* Abelianization H :=
lift (of.comp f)
#align abelianization.map Abelianization.map
/-- Use `map` as the preferred simp normal form. -/
@[simp] theorem lift_of_comp :
Abelianization.lift (Abelianization.of.comp f) = Abelianization.map f := rfl
@[simp]
theorem map_of (x : G) : map f (of x) = of (f x) :=
rfl
#align abelianization.map_of Abelianization.map_of
@[simp]
theorem map_id : map (MonoidHom.id G) = MonoidHom.id (Abelianization G) :=
hom_ext _ _ rfl
#align abelianization.map_id Abelianization.map_id
@[simp]
theorem map_comp {I : Type w} [Group I] (g : H →* I) : (map g).comp (map f) = map (g.comp f) :=
hom_ext _ _ rfl
#align abelianization.map_comp Abelianization.map_comp
@[simp]
theorem map_map_apply {I : Type w} [Group I] {g : H →* I} {x : Abelianization G} :
map g (map f x) = map (g.comp f) x :=
DFunLike.congr_fun (map_comp _ _) x
#align abelianization.map_map_apply Abelianization.map_map_apply
end Map
end Abelianization
section AbelianizationCongr
-- Porting note: `[Group G]` should not be necessary here
variable {G} [Group G] {H : Type v} [Group H] (e : G ≃* H)
/-- Equivalent groups have equivalent abelianizations -/
def MulEquiv.abelianizationCongr : Abelianization G ≃* Abelianization H where
toFun := Abelianization.map e.toMonoidHom
invFun := Abelianization.map e.symm.toMonoidHom
left_inv := by
rintro ⟨a⟩
simp
right_inv := by
rintro ⟨a⟩
simp
map_mul' := MonoidHom.map_mul _
#align mul_equiv.abelianization_congr MulEquiv.abelianizationCongr
@[simp]
theorem abelianizationCongr_of (x : G) :
e.abelianizationCongr (Abelianization.of x) = Abelianization.of (e x) :=
rfl
#align abelianization_congr_of abelianizationCongr_of
@[simp]
theorem abelianizationCongr_refl :
(MulEquiv.refl G).abelianizationCongr = MulEquiv.refl (Abelianization G) :=
MulEquiv.toMonoidHom_injective Abelianization.lift_of
#align abelianization_congr_refl abelianizationCongr_refl
@[simp]
theorem abelianizationCongr_symm : e.abelianizationCongr.symm = e.symm.abelianizationCongr :=
rfl
#align abelianization_congr_symm abelianizationCongr_symm
@[simp]
theorem abelianizationCongr_trans {I : Type v} [Group I] (e₂ : H ≃* I) :
e.abelianizationCongr.trans e₂.abelianizationCongr = (e.trans e₂).abelianizationCongr :=
MulEquiv.toMonoidHom_injective (Abelianization.hom_ext _ _ rfl)
#align abelianization_congr_trans abelianizationCongr_trans
end AbelianizationCongr
/-- An Abelian group is equivalent to its own abelianization. -/
@[simps]
def Abelianization.equivOfComm {H : Type*} [CommGroup H] : H ≃* Abelianization H :=
{ Abelianization.of with
toFun := Abelianization.of
invFun := Abelianization.lift (MonoidHom.id H)
left_inv := fun a => rfl
right_inv := by
rintro ⟨a⟩
rfl }
#align abelianization.equiv_of_comm Abelianization.equivOfComm
section commutatorRepresentatives
open Subgroup
/-- Representatives `(g₁, g₂) : G × G` of commutators `⁅g₁, g₂⁆ ∈ G`. -/
def commutatorRepresentatives : Set (G × G) :=
Set.range fun g : commutatorSet G => (g.2.choose, g.2.choose_spec.choose)
#align commutator_representatives commutatorRepresentatives
instance [Finite (commutatorSet G)] : Finite (commutatorRepresentatives G) :=
Set.finite_coe_iff.mpr (Set.finite_range _)
/-- Subgroup generated by representatives `g₁ g₂ : G` of commutators `⁅g₁, g₂⁆ ∈ G`. -/
def closureCommutatorRepresentatives : Subgroup G :=
closure (Prod.fst '' commutatorRepresentatives G ∪ Prod.snd '' commutatorRepresentatives G)
#align closure_commutator_representatives closureCommutatorRepresentatives
instance closureCommutatorRepresentatives_fg [Finite (commutatorSet G)] :
Group.FG (closureCommutatorRepresentatives G) :=
Group.closure_finite_fg _
#align closure_commutator_representatives_fg closureCommutatorRepresentatives_fg
| Mathlib/GroupTheory/Abelianization.lean | 289 | 296 | theorem rank_closureCommutatorRepresentatives_le [Finite (commutatorSet G)] :
Group.rank (closureCommutatorRepresentatives G) ≤ 2 * Nat.card (commutatorSet G) := by |
rw [two_mul]
exact
(Subgroup.rank_closure_finite_le_nat_card _).trans
((Set.card_union_le _ _).trans
(add_le_add ((Finite.card_image_le _).trans (Finite.card_range_le _))
((Finite.card_image_le _).trans (Finite.card_range_le _))))
|
/-
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.Topology.Sheaves.Presheaf
import Mathlib.CategoryTheory.Adjunction.FullyFaithful
#align_import algebraic_geometry.presheafed_space from "leanprover-community/mathlib"@"d39590fc8728fbf6743249802486f8c91ffe07bc"
/-!
# Presheafed spaces
Introduces the category of topological spaces equipped with a presheaf (taking values in an
arbitrary target category `C`.)
We further describe how to apply functors and natural transformations to the values of the
presheaves.
-/
open Opposite CategoryTheory CategoryTheory.Category CategoryTheory.Functor TopCat TopologicalSpace
variable (C : Type*) [Category C]
-- Porting note: we used to have:
-- local attribute [tidy] tactic.auto_cases_opens
-- We would replace this by:
-- attribute [local aesop safe cases (rule_sets := [CategoryTheory])] Opens
-- although it doesn't appear to help in this file, in any case.
-- Porting note: we used to have:
-- local attribute [tidy] tactic.op_induction'
-- A possible replacement would be:
-- attribute [local aesop safe cases (rule_sets := [CategoryTheory])] Opposite
-- but this would probably require https://github.com/JLimperg/aesop/issues/59
-- In any case, it doesn't seem necessary here.
namespace AlgebraicGeometry
-- Porting note: `PresheafSpace.{w} C` is the type of topological spaces in `Type w` equipped
-- with a presheaf with values in `C`; then there is a total of three universe parameters
-- in `PresheafSpace.{w, v, u} C`, where `C : Type u` and `Category.{v} C`.
-- In mathlib3, some definitions in this file unnecessarily assumed `w=v`. This restriction
-- has been removed.
/-- A `PresheafedSpace C` is a topological space equipped with a presheaf of `C`s. -/
structure PresheafedSpace where
carrier : TopCat
protected presheaf : carrier.Presheaf C
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace AlgebraicGeometry.PresheafedSpace
variable {C}
namespace PresheafedSpace
-- Porting note: using `Coe` here triggers an error, `CoeOut` seems an acceptable alternative
instance coeCarrier : CoeOut (PresheafedSpace C) TopCat where coe X := X.carrier
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.coe_carrier AlgebraicGeometry.PresheafedSpace.coeCarrier
attribute [coe] PresheafedSpace.carrier
-- Porting note: we add this instance, as Lean does not reliably use the `CoeOut` instance above
-- in downstream files.
instance : CoeSort (PresheafedSpace C) Type* where coe := fun X => X.carrier
-- Porting note: the following lemma is removed because it is a syntactic tauto
/-@[simp]
theorem as_coe (X : PresheafedSpace.{w, v, u} C) : X.carrier = (X : TopCat.{w}) :=
rfl-/
set_option linter.uppercaseLean3 false in
#noalign algebraic_geometry.PresheafedSpace.as_coe
-- Porting note: removed @[simp] as the `simpVarHead` linter complains
-- @[simp]
theorem mk_coe (carrier) (presheaf) :
(({ carrier
presheaf } : PresheafedSpace C) : TopCat) = carrier :=
rfl
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.mk_coe AlgebraicGeometry.PresheafedSpace.mk_coe
instance (X : PresheafedSpace C) : TopologicalSpace X :=
X.carrier.str
/-- The constant presheaf on `X` with value `Z`. -/
def const (X : TopCat) (Z : C) : PresheafedSpace C where
carrier := X
presheaf := (Functor.const _).obj Z
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.const AlgebraicGeometry.PresheafedSpace.const
instance [Inhabited C] : Inhabited (PresheafedSpace C) :=
⟨const (TopCat.of PEmpty) default⟩
/-- A morphism between presheafed spaces `X` and `Y` consists of a continuous map
`f` between the underlying topological spaces, and a (notice contravariant!) map
from the presheaf on `Y` to the pushforward of the presheaf on `X` via `f`. -/
structure Hom (X Y : PresheafedSpace C) where
base : (X : TopCat) ⟶ (Y : TopCat)
c : Y.presheaf ⟶ base _* X.presheaf
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.hom AlgebraicGeometry.PresheafedSpace.Hom
-- Porting note: eventually, the ext lemma shall be applied to terms in `X ⟶ Y`
-- rather than `Hom X Y`, this one was renamed `Hom.ext` instead of `ext`,
-- and the more practical lemma `ext` is defined just after the definition
-- of the `Category` instance
@[ext]
theorem Hom.ext {X Y : PresheafedSpace C} (α β : Hom X Y) (w : α.base = β.base)
(h : α.c ≫ whiskerRight (eqToHom (by rw [w])) _ = β.c) : α = β := by
rcases α with ⟨base, c⟩
rcases β with ⟨base', c'⟩
dsimp at w
subst w
dsimp at h
erw [whiskerRight_id', comp_id] at h
subst h
rfl
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.ext AlgebraicGeometry.PresheafedSpace.Hom.ext
-- TODO including `injections` would make tidy work earlier.
theorem hext {X Y : PresheafedSpace C} (α β : Hom X Y) (w : α.base = β.base) (h : HEq α.c β.c) :
α = β := by
cases α
cases β
congr
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.hext AlgebraicGeometry.PresheafedSpace.hext
-- Porting note: `eqToHom` is no longer necessary in the definition of `c`
/-- The identity morphism of a `PresheafedSpace`. -/
def id (X : PresheafedSpace C) : Hom X X where
base := 𝟙 (X : TopCat)
c := 𝟙 _
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.id AlgebraicGeometry.PresheafedSpace.id
instance homInhabited (X : PresheafedSpace C) : Inhabited (Hom X X) :=
⟨id X⟩
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.hom_inhabited AlgebraicGeometry.PresheafedSpace.homInhabited
/-- Composition of morphisms of `PresheafedSpace`s. -/
def comp {X Y Z : PresheafedSpace C} (α : Hom X Y) (β : Hom Y Z) : Hom X Z where
base := α.base ≫ β.base
c := β.c ≫ (Presheaf.pushforward _ β.base).map α.c
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.comp AlgebraicGeometry.PresheafedSpace.comp
theorem comp_c {X Y Z : PresheafedSpace C} (α : Hom X Y) (β : Hom Y Z) :
(comp α β).c = β.c ≫ (Presheaf.pushforward _ β.base).map α.c :=
rfl
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.comp_c AlgebraicGeometry.PresheafedSpace.comp_c
variable (C)
section
attribute [local simp] id comp
-- Porting note: in mathlib3, `tidy` could (almost) prove the category axioms, but proofs
-- were included because `tidy` was slow. Here, `aesop_cat` succeeds reasonably quickly
-- for `comp_id` and `assoc`
/-- The category of PresheafedSpaces. Morphisms are pairs, a continuous map and a presheaf map
from the presheaf on the target to the pushforward of the presheaf on the source. -/
instance categoryOfPresheafedSpaces : Category (PresheafedSpace C) where
Hom := Hom
id := id
comp := comp
id_comp _ := by
dsimp
ext
· dsimp
simp
· dsimp
simp only [map_id, whiskerRight_id', assoc]
erw [comp_id, comp_id]
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.category_of_PresheafedSpaces AlgebraicGeometry.PresheafedSpace.categoryOfPresheafedSpaces
variable {C}
-- Porting note: adding an ext lemma.
-- See https://github.com/leanprover-community/mathlib4/issues/5229
@[ext]
theorem ext {X Y : PresheafedSpace C} (α β : X ⟶ Y) (w : α.base = β.base)
(h : α.c ≫ whiskerRight (eqToHom (by rw [w])) _ = β.c) : α = β :=
Hom.ext α β w h
end
variable {C}
attribute [local simp] eqToHom_map
@[simp]
theorem id_base (X : PresheafedSpace C) : (𝟙 X : X ⟶ X).base = 𝟙 (X : TopCat) :=
rfl
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.id_base AlgebraicGeometry.PresheafedSpace.id_base
-- Porting note: `eqToHom` is no longer needed in the statements of `id_c` and `id_c_app`
theorem id_c (X : PresheafedSpace C) :
(𝟙 X : X ⟶ X).c = 𝟙 X.presheaf :=
rfl
set_option linter.uppercaseLean3 false in
#align algebraic_geometry.PresheafedSpace.id_c AlgebraicGeometry.PresheafedSpace.id_c
@[simp]
| Mathlib/Geometry/RingedSpace/PresheafedSpace.lean | 215 | 218 | theorem id_c_app (X : PresheafedSpace C) (U) :
(𝟙 X : X ⟶ X).c.app U = X.presheaf.map (𝟙 U) := by |
rw [id_c, map_id]
rfl
|
/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers
-/
import Mathlib.Algebra.Module.BigOperators
import Mathlib.Data.Fintype.BigOperators
import Mathlib.LinearAlgebra.AffineSpace.AffineMap
import Mathlib.LinearAlgebra.AffineSpace.AffineSubspace
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.Tactic.FinCases
#align_import linear_algebra.affine_space.combination from "leanprover-community/mathlib"@"2de9c37fa71dde2f1c6feff19876dd6a7b1519f0"
/-!
# Affine combinations of points
This file defines affine combinations of points.
## Main definitions
* `weightedVSubOfPoint` is a general weighted combination of
subtractions with an explicit base point, yielding a vector.
* `weightedVSub` uses an arbitrary choice of base point and is intended
to be used when the sum of weights is 0, in which case the result is
independent of the choice of base point.
* `affineCombination` adds the weighted combination to the arbitrary
base point, yielding a point rather than a vector, and is intended
to be used when the sum of weights is 1, in which case the result is
independent of the choice of base point.
These definitions are for sums over a `Finset`; versions for a
`Fintype` may be obtained using `Finset.univ`, while versions for a
`Finsupp` may be obtained using `Finsupp.support`.
## References
* https://en.wikipedia.org/wiki/Affine_space
-/
noncomputable section
open Affine
namespace Finset
theorem univ_fin2 : (univ : Finset (Fin 2)) = {0, 1} := by
ext x
fin_cases x <;> simp
#align finset.univ_fin2 Finset.univ_fin2
variable {k : Type*} {V : Type*} {P : Type*} [Ring k] [AddCommGroup V] [Module k V]
variable [S : AffineSpace V P]
variable {ι : Type*} (s : Finset ι)
variable {ι₂ : Type*} (s₂ : Finset ι₂)
/-- A weighted sum of the results of subtracting a base point from the
given points, as a linear map on the weights. The main cases of
interest are where the sum of the weights is 0, in which case the sum
is independent of the choice of base point, and where the sum of the
weights is 1, in which case the sum added to the base point is
independent of the choice of base point. -/
def weightedVSubOfPoint (p : ι → P) (b : P) : (ι → k) →ₗ[k] V :=
∑ i ∈ s, (LinearMap.proj i : (ι → k) →ₗ[k] k).smulRight (p i -ᵥ b)
#align finset.weighted_vsub_of_point Finset.weightedVSubOfPoint
@[simp]
theorem weightedVSubOfPoint_apply (w : ι → k) (p : ι → P) (b : P) :
s.weightedVSubOfPoint p b w = ∑ i ∈ s, w i • (p i -ᵥ b) := by
simp [weightedVSubOfPoint, LinearMap.sum_apply]
#align finset.weighted_vsub_of_point_apply Finset.weightedVSubOfPoint_apply
/-- The value of `weightedVSubOfPoint`, where the given points are equal. -/
@[simp (high)]
theorem weightedVSubOfPoint_apply_const (w : ι → k) (p : P) (b : P) :
s.weightedVSubOfPoint (fun _ => p) b w = (∑ i ∈ s, w i) • (p -ᵥ b) := by
rw [weightedVSubOfPoint_apply, sum_smul]
#align finset.weighted_vsub_of_point_apply_const Finset.weightedVSubOfPoint_apply_const
/-- `weightedVSubOfPoint` gives equal results for two families of weights and two families of
points that are equal on `s`. -/
theorem weightedVSubOfPoint_congr {w₁ w₂ : ι → k} (hw : ∀ i ∈ s, w₁ i = w₂ i) {p₁ p₂ : ι → P}
(hp : ∀ i ∈ s, p₁ i = p₂ i) (b : P) :
s.weightedVSubOfPoint p₁ b w₁ = s.weightedVSubOfPoint p₂ b w₂ := by
simp_rw [weightedVSubOfPoint_apply]
refine sum_congr rfl fun i hi => ?_
rw [hw i hi, hp i hi]
#align finset.weighted_vsub_of_point_congr Finset.weightedVSubOfPoint_congr
/-- Given a family of points, if we use a member of the family as a base point, the
`weightedVSubOfPoint` does not depend on the value of the weights at this point. -/
theorem weightedVSubOfPoint_eq_of_weights_eq (p : ι → P) (j : ι) (w₁ w₂ : ι → k)
(hw : ∀ i, i ≠ j → w₁ i = w₂ i) :
s.weightedVSubOfPoint p (p j) w₁ = s.weightedVSubOfPoint p (p j) w₂ := by
simp only [Finset.weightedVSubOfPoint_apply]
congr
ext i
rcases eq_or_ne i j with h | h
· simp [h]
· simp [hw i h]
#align finset.weighted_vsub_of_point_eq_of_weights_eq Finset.weightedVSubOfPoint_eq_of_weights_eq
/-- The weighted sum is independent of the base point when the sum of
the weights is 0. -/
theorem weightedVSubOfPoint_eq_of_sum_eq_zero (w : ι → k) (p : ι → P) (h : ∑ i ∈ s, w i = 0)
(b₁ b₂ : P) : s.weightedVSubOfPoint p b₁ w = s.weightedVSubOfPoint p b₂ w := by
apply eq_of_sub_eq_zero
rw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply, ← sum_sub_distrib]
conv_lhs =>
congr
· skip
· ext
rw [← smul_sub, vsub_sub_vsub_cancel_left]
rw [← sum_smul, h, zero_smul]
#align finset.weighted_vsub_of_point_eq_of_sum_eq_zero Finset.weightedVSubOfPoint_eq_of_sum_eq_zero
/-- The weighted sum, added to the base point, is independent of the
base point when the sum of the weights is 1. -/
theorem weightedVSubOfPoint_vadd_eq_of_sum_eq_one (w : ι → k) (p : ι → P) (h : ∑ i ∈ s, w i = 1)
(b₁ b₂ : P) : s.weightedVSubOfPoint p b₁ w +ᵥ b₁ = s.weightedVSubOfPoint p b₂ w +ᵥ b₂ := by
erw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply, ← @vsub_eq_zero_iff_eq V,
vadd_vsub_assoc, vsub_vadd_eq_vsub_sub, ← add_sub_assoc, add_comm, add_sub_assoc, ←
sum_sub_distrib]
conv_lhs =>
congr
· skip
· congr
· skip
· ext
rw [← smul_sub, vsub_sub_vsub_cancel_left]
rw [← sum_smul, h, one_smul, vsub_add_vsub_cancel, vsub_self]
#align finset.weighted_vsub_of_point_vadd_eq_of_sum_eq_one Finset.weightedVSubOfPoint_vadd_eq_of_sum_eq_one
/-- The weighted sum is unaffected by removing the base point, if
present, from the set of points. -/
@[simp (high)]
theorem weightedVSubOfPoint_erase [DecidableEq ι] (w : ι → k) (p : ι → P) (i : ι) :
(s.erase i).weightedVSubOfPoint p (p i) w = s.weightedVSubOfPoint p (p i) w := by
rw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply]
apply sum_erase
rw [vsub_self, smul_zero]
#align finset.weighted_vsub_of_point_erase Finset.weightedVSubOfPoint_erase
/-- The weighted sum is unaffected by adding the base point, whether
or not present, to the set of points. -/
@[simp (high)]
theorem weightedVSubOfPoint_insert [DecidableEq ι] (w : ι → k) (p : ι → P) (i : ι) :
(insert i s).weightedVSubOfPoint p (p i) w = s.weightedVSubOfPoint p (p i) w := by
rw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply]
apply sum_insert_zero
rw [vsub_self, smul_zero]
#align finset.weighted_vsub_of_point_insert Finset.weightedVSubOfPoint_insert
/-- The weighted sum is unaffected by changing the weights to the
corresponding indicator function and adding points to the set. -/
theorem weightedVSubOfPoint_indicator_subset (w : ι → k) (p : ι → P) (b : P) {s₁ s₂ : Finset ι}
(h : s₁ ⊆ s₂) :
s₁.weightedVSubOfPoint p b w = s₂.weightedVSubOfPoint p b (Set.indicator (↑s₁) w) := by
rw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply]
exact Eq.symm <|
sum_indicator_subset_of_eq_zero w (fun i wi => wi • (p i -ᵥ b : V)) h fun i => zero_smul k _
#align finset.weighted_vsub_of_point_indicator_subset Finset.weightedVSubOfPoint_indicator_subset
/-- A weighted sum, over the image of an embedding, equals a weighted
sum with the same points and weights over the original
`Finset`. -/
theorem weightedVSubOfPoint_map (e : ι₂ ↪ ι) (w : ι → k) (p : ι → P) (b : P) :
(s₂.map e).weightedVSubOfPoint p b w = s₂.weightedVSubOfPoint (p ∘ e) b (w ∘ e) := by
simp_rw [weightedVSubOfPoint_apply]
exact Finset.sum_map _ _ _
#align finset.weighted_vsub_of_point_map Finset.weightedVSubOfPoint_map
/-- A weighted sum of pairwise subtractions, expressed as a subtraction of two
`weightedVSubOfPoint` expressions. -/
theorem sum_smul_vsub_eq_weightedVSubOfPoint_sub (w : ι → k) (p₁ p₂ : ι → P) (b : P) :
(∑ i ∈ s, w i • (p₁ i -ᵥ p₂ i)) =
s.weightedVSubOfPoint p₁ b w - s.weightedVSubOfPoint p₂ b w := by
simp_rw [weightedVSubOfPoint_apply, ← sum_sub_distrib, ← smul_sub, vsub_sub_vsub_cancel_right]
#align finset.sum_smul_vsub_eq_weighted_vsub_of_point_sub Finset.sum_smul_vsub_eq_weightedVSubOfPoint_sub
/-- A weighted sum of pairwise subtractions, where the point on the right is constant,
expressed as a subtraction involving a `weightedVSubOfPoint` expression. -/
theorem sum_smul_vsub_const_eq_weightedVSubOfPoint_sub (w : ι → k) (p₁ : ι → P) (p₂ b : P) :
(∑ i ∈ s, w i • (p₁ i -ᵥ p₂)) = s.weightedVSubOfPoint p₁ b w - (∑ i ∈ s, w i) • (p₂ -ᵥ b) := by
rw [sum_smul_vsub_eq_weightedVSubOfPoint_sub, weightedVSubOfPoint_apply_const]
#align finset.sum_smul_vsub_const_eq_weighted_vsub_of_point_sub Finset.sum_smul_vsub_const_eq_weightedVSubOfPoint_sub
/-- A weighted sum of pairwise subtractions, where the point on the left is constant,
expressed as a subtraction involving a `weightedVSubOfPoint` expression. -/
theorem sum_smul_const_vsub_eq_sub_weightedVSubOfPoint (w : ι → k) (p₂ : ι → P) (p₁ b : P) :
(∑ i ∈ s, w i • (p₁ -ᵥ p₂ i)) = (∑ i ∈ s, w i) • (p₁ -ᵥ b) - s.weightedVSubOfPoint p₂ b w := by
rw [sum_smul_vsub_eq_weightedVSubOfPoint_sub, weightedVSubOfPoint_apply_const]
#align finset.sum_smul_const_vsub_eq_sub_weighted_vsub_of_point Finset.sum_smul_const_vsub_eq_sub_weightedVSubOfPoint
/-- A weighted sum may be split into such sums over two subsets. -/
theorem weightedVSubOfPoint_sdiff [DecidableEq ι] {s₂ : Finset ι} (h : s₂ ⊆ s) (w : ι → k)
(p : ι → P) (b : P) :
(s \ s₂).weightedVSubOfPoint p b w + s₂.weightedVSubOfPoint p b w =
s.weightedVSubOfPoint p b w := by
simp_rw [weightedVSubOfPoint_apply, sum_sdiff h]
#align finset.weighted_vsub_of_point_sdiff Finset.weightedVSubOfPoint_sdiff
/-- A weighted sum may be split into a subtraction of such sums over two subsets. -/
theorem weightedVSubOfPoint_sdiff_sub [DecidableEq ι] {s₂ : Finset ι} (h : s₂ ⊆ s) (w : ι → k)
(p : ι → P) (b : P) :
(s \ s₂).weightedVSubOfPoint p b w - s₂.weightedVSubOfPoint p b (-w) =
s.weightedVSubOfPoint p b w := by
rw [map_neg, sub_neg_eq_add, s.weightedVSubOfPoint_sdiff h]
#align finset.weighted_vsub_of_point_sdiff_sub Finset.weightedVSubOfPoint_sdiff_sub
/-- A weighted sum over `s.subtype pred` equals one over `s.filter pred`. -/
theorem weightedVSubOfPoint_subtype_eq_filter (w : ι → k) (p : ι → P) (b : P) (pred : ι → Prop)
[DecidablePred pred] :
((s.subtype pred).weightedVSubOfPoint (fun i => p i) b fun i => w i) =
(s.filter pred).weightedVSubOfPoint p b w := by
rw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply, ← sum_subtype_eq_sum_filter]
#align finset.weighted_vsub_of_point_subtype_eq_filter Finset.weightedVSubOfPoint_subtype_eq_filter
/-- A weighted sum over `s.filter pred` equals one over `s` if all the weights at indices in `s`
not satisfying `pred` are zero. -/
theorem weightedVSubOfPoint_filter_of_ne (w : ι → k) (p : ι → P) (b : P) {pred : ι → Prop}
[DecidablePred pred] (h : ∀ i ∈ s, w i ≠ 0 → pred i) :
(s.filter pred).weightedVSubOfPoint p b w = s.weightedVSubOfPoint p b w := by
rw [weightedVSubOfPoint_apply, weightedVSubOfPoint_apply, sum_filter_of_ne]
intro i hi hne
refine h i hi ?_
intro hw
simp [hw] at hne
#align finset.weighted_vsub_of_point_filter_of_ne Finset.weightedVSubOfPoint_filter_of_ne
/-- A constant multiplier of the weights in `weightedVSubOfPoint` may be moved outside the
sum. -/
theorem weightedVSubOfPoint_const_smul (w : ι → k) (p : ι → P) (b : P) (c : k) :
s.weightedVSubOfPoint p b (c • w) = c • s.weightedVSubOfPoint p b w := by
simp_rw [weightedVSubOfPoint_apply, smul_sum, Pi.smul_apply, smul_smul, smul_eq_mul]
#align finset.weighted_vsub_of_point_const_smul Finset.weightedVSubOfPoint_const_smul
/-- A weighted sum of the results of subtracting a default base point
from the given points, as a linear map on the weights. This is
intended to be used when the sum of the weights is 0; that condition
is specified as a hypothesis on those lemmas that require it. -/
def weightedVSub (p : ι → P) : (ι → k) →ₗ[k] V :=
s.weightedVSubOfPoint p (Classical.choice S.nonempty)
#align finset.weighted_vsub Finset.weightedVSub
/-- Applying `weightedVSub` with given weights. This is for the case
where a result involving a default base point is OK (for example, when
that base point will cancel out later); a more typical use case for
`weightedVSub` would involve selecting a preferred base point with
`weightedVSub_eq_weightedVSubOfPoint_of_sum_eq_zero` and then
using `weightedVSubOfPoint_apply`. -/
theorem weightedVSub_apply (w : ι → k) (p : ι → P) :
s.weightedVSub p w = ∑ i ∈ s, w i • (p i -ᵥ Classical.choice S.nonempty) := by
simp [weightedVSub, LinearMap.sum_apply]
#align finset.weighted_vsub_apply Finset.weightedVSub_apply
/-- `weightedVSub` gives the sum of the results of subtracting any
base point, when the sum of the weights is 0. -/
theorem weightedVSub_eq_weightedVSubOfPoint_of_sum_eq_zero (w : ι → k) (p : ι → P)
(h : ∑ i ∈ s, w i = 0) (b : P) : s.weightedVSub p w = s.weightedVSubOfPoint p b w :=
s.weightedVSubOfPoint_eq_of_sum_eq_zero w p h _ _
#align finset.weighted_vsub_eq_weighted_vsub_of_point_of_sum_eq_zero Finset.weightedVSub_eq_weightedVSubOfPoint_of_sum_eq_zero
/-- The value of `weightedVSub`, where the given points are equal and the sum of the weights
is 0. -/
@[simp]
theorem weightedVSub_apply_const (w : ι → k) (p : P) (h : ∑ i ∈ s, w i = 0) :
s.weightedVSub (fun _ => p) w = 0 := by
rw [weightedVSub, weightedVSubOfPoint_apply_const, h, zero_smul]
#align finset.weighted_vsub_apply_const Finset.weightedVSub_apply_const
/-- The `weightedVSub` for an empty set is 0. -/
@[simp]
theorem weightedVSub_empty (w : ι → k) (p : ι → P) : (∅ : Finset ι).weightedVSub p w = (0 : V) := by
simp [weightedVSub_apply]
#align finset.weighted_vsub_empty Finset.weightedVSub_empty
/-- `weightedVSub` gives equal results for two families of weights and two families of points
that are equal on `s`. -/
theorem weightedVSub_congr {w₁ w₂ : ι → k} (hw : ∀ i ∈ s, w₁ i = w₂ i) {p₁ p₂ : ι → P}
(hp : ∀ i ∈ s, p₁ i = p₂ i) : s.weightedVSub p₁ w₁ = s.weightedVSub p₂ w₂ :=
s.weightedVSubOfPoint_congr hw hp _
#align finset.weighted_vsub_congr Finset.weightedVSub_congr
/-- The weighted sum is unaffected by changing the weights to the
corresponding indicator function and adding points to the set. -/
theorem weightedVSub_indicator_subset (w : ι → k) (p : ι → P) {s₁ s₂ : Finset ι} (h : s₁ ⊆ s₂) :
s₁.weightedVSub p w = s₂.weightedVSub p (Set.indicator (↑s₁) w) :=
weightedVSubOfPoint_indicator_subset _ _ _ h
#align finset.weighted_vsub_indicator_subset Finset.weightedVSub_indicator_subset
/-- A weighted subtraction, over the image of an embedding, equals a
weighted subtraction with the same points and weights over the
original `Finset`. -/
theorem weightedVSub_map (e : ι₂ ↪ ι) (w : ι → k) (p : ι → P) :
(s₂.map e).weightedVSub p w = s₂.weightedVSub (p ∘ e) (w ∘ e) :=
s₂.weightedVSubOfPoint_map _ _ _ _
#align finset.weighted_vsub_map Finset.weightedVSub_map
/-- A weighted sum of pairwise subtractions, expressed as a subtraction of two `weightedVSub`
expressions. -/
theorem sum_smul_vsub_eq_weightedVSub_sub (w : ι → k) (p₁ p₂ : ι → P) :
(∑ i ∈ s, w i • (p₁ i -ᵥ p₂ i)) = s.weightedVSub p₁ w - s.weightedVSub p₂ w :=
s.sum_smul_vsub_eq_weightedVSubOfPoint_sub _ _ _ _
#align finset.sum_smul_vsub_eq_weighted_vsub_sub Finset.sum_smul_vsub_eq_weightedVSub_sub
/-- A weighted sum of pairwise subtractions, where the point on the right is constant and the
sum of the weights is 0. -/
theorem sum_smul_vsub_const_eq_weightedVSub (w : ι → k) (p₁ : ι → P) (p₂ : P)
(h : ∑ i ∈ s, w i = 0) : (∑ i ∈ s, w i • (p₁ i -ᵥ p₂)) = s.weightedVSub p₁ w := by
rw [sum_smul_vsub_eq_weightedVSub_sub, s.weightedVSub_apply_const _ _ h, sub_zero]
#align finset.sum_smul_vsub_const_eq_weighted_vsub Finset.sum_smul_vsub_const_eq_weightedVSub
/-- A weighted sum of pairwise subtractions, where the point on the left is constant and the
sum of the weights is 0. -/
theorem sum_smul_const_vsub_eq_neg_weightedVSub (w : ι → k) (p₂ : ι → P) (p₁ : P)
(h : ∑ i ∈ s, w i = 0) : (∑ i ∈ s, w i • (p₁ -ᵥ p₂ i)) = -s.weightedVSub p₂ w := by
rw [sum_smul_vsub_eq_weightedVSub_sub, s.weightedVSub_apply_const _ _ h, zero_sub]
#align finset.sum_smul_const_vsub_eq_neg_weighted_vsub Finset.sum_smul_const_vsub_eq_neg_weightedVSub
/-- A weighted sum may be split into such sums over two subsets. -/
theorem weightedVSub_sdiff [DecidableEq ι] {s₂ : Finset ι} (h : s₂ ⊆ s) (w : ι → k) (p : ι → P) :
(s \ s₂).weightedVSub p w + s₂.weightedVSub p w = s.weightedVSub p w :=
s.weightedVSubOfPoint_sdiff h _ _ _
#align finset.weighted_vsub_sdiff Finset.weightedVSub_sdiff
/-- A weighted sum may be split into a subtraction of such sums over two subsets. -/
theorem weightedVSub_sdiff_sub [DecidableEq ι] {s₂ : Finset ι} (h : s₂ ⊆ s) (w : ι → k)
(p : ι → P) : (s \ s₂).weightedVSub p w - s₂.weightedVSub p (-w) = s.weightedVSub p w :=
s.weightedVSubOfPoint_sdiff_sub h _ _ _
#align finset.weighted_vsub_sdiff_sub Finset.weightedVSub_sdiff_sub
/-- A weighted sum over `s.subtype pred` equals one over `s.filter pred`. -/
theorem weightedVSub_subtype_eq_filter (w : ι → k) (p : ι → P) (pred : ι → Prop)
[DecidablePred pred] :
((s.subtype pred).weightedVSub (fun i => p i) fun i => w i) =
(s.filter pred).weightedVSub p w :=
s.weightedVSubOfPoint_subtype_eq_filter _ _ _ _
#align finset.weighted_vsub_subtype_eq_filter Finset.weightedVSub_subtype_eq_filter
/-- A weighted sum over `s.filter pred` equals one over `s` if all the weights at indices in `s`
not satisfying `pred` are zero. -/
theorem weightedVSub_filter_of_ne (w : ι → k) (p : ι → P) {pred : ι → Prop} [DecidablePred pred]
(h : ∀ i ∈ s, w i ≠ 0 → pred i) : (s.filter pred).weightedVSub p w = s.weightedVSub p w :=
s.weightedVSubOfPoint_filter_of_ne _ _ _ h
#align finset.weighted_vsub_filter_of_ne Finset.weightedVSub_filter_of_ne
/-- A constant multiplier of the weights in `weightedVSub_of` may be moved outside the sum. -/
theorem weightedVSub_const_smul (w : ι → k) (p : ι → P) (c : k) :
s.weightedVSub p (c • w) = c • s.weightedVSub p w :=
s.weightedVSubOfPoint_const_smul _ _ _ _
#align finset.weighted_vsub_const_smul Finset.weightedVSub_const_smul
instance : AffineSpace (ι → k) (ι → k) := Pi.instAddTorsor
variable (k)
/-- A weighted sum of the results of subtracting a default base point
from the given points, added to that base point, as an affine map on
the weights. This is intended to be used when the sum of the weights
is 1, in which case it is an affine combination (barycenter) of the
points with the given weights; that condition is specified as a
hypothesis on those lemmas that require it. -/
def affineCombination (p : ι → P) : (ι → k) →ᵃ[k] P where
toFun w := s.weightedVSubOfPoint p (Classical.choice S.nonempty) w +ᵥ Classical.choice S.nonempty
linear := s.weightedVSub p
map_vadd' w₁ w₂ := by simp_rw [vadd_vadd, weightedVSub, vadd_eq_add, LinearMap.map_add]
#align finset.affine_combination Finset.affineCombination
/-- The linear map corresponding to `affineCombination` is
`weightedVSub`. -/
@[simp]
theorem affineCombination_linear (p : ι → P) :
(s.affineCombination k p).linear = s.weightedVSub p :=
rfl
#align finset.affine_combination_linear Finset.affineCombination_linear
variable {k}
/-- Applying `affineCombination` with given weights. This is for the
case where a result involving a default base point is OK (for example,
when that base point will cancel out later); a more typical use case
for `affineCombination` would involve selecting a preferred base
point with
`affineCombination_eq_weightedVSubOfPoint_vadd_of_sum_eq_one` and
then using `weightedVSubOfPoint_apply`. -/
theorem affineCombination_apply (w : ι → k) (p : ι → P) :
(s.affineCombination k p) w =
s.weightedVSubOfPoint p (Classical.choice S.nonempty) w +ᵥ Classical.choice S.nonempty :=
rfl
#align finset.affine_combination_apply Finset.affineCombination_apply
/-- The value of `affineCombination`, where the given points are equal. -/
@[simp]
theorem affineCombination_apply_const (w : ι → k) (p : P) (h : ∑ i ∈ s, w i = 1) :
s.affineCombination k (fun _ => p) w = p := by
rw [affineCombination_apply, s.weightedVSubOfPoint_apply_const, h, one_smul, vsub_vadd]
#align finset.affine_combination_apply_const Finset.affineCombination_apply_const
/-- `affineCombination` gives equal results for two families of weights and two families of
points that are equal on `s`. -/
theorem affineCombination_congr {w₁ w₂ : ι → k} (hw : ∀ i ∈ s, w₁ i = w₂ i) {p₁ p₂ : ι → P}
(hp : ∀ i ∈ s, p₁ i = p₂ i) : s.affineCombination k p₁ w₁ = s.affineCombination k p₂ w₂ := by
simp_rw [affineCombination_apply, s.weightedVSubOfPoint_congr hw hp]
#align finset.affine_combination_congr Finset.affineCombination_congr
/-- `affineCombination` gives the sum with any base point, when the
sum of the weights is 1. -/
theorem affineCombination_eq_weightedVSubOfPoint_vadd_of_sum_eq_one (w : ι → k) (p : ι → P)
(h : ∑ i ∈ s, w i = 1) (b : P) :
s.affineCombination k p w = s.weightedVSubOfPoint p b w +ᵥ b :=
s.weightedVSubOfPoint_vadd_eq_of_sum_eq_one w p h _ _
#align finset.affine_combination_eq_weighted_vsub_of_point_vadd_of_sum_eq_one Finset.affineCombination_eq_weightedVSubOfPoint_vadd_of_sum_eq_one
/-- Adding a `weightedVSub` to an `affineCombination`. -/
theorem weightedVSub_vadd_affineCombination (w₁ w₂ : ι → k) (p : ι → P) :
s.weightedVSub p w₁ +ᵥ s.affineCombination k p w₂ = s.affineCombination k p (w₁ + w₂) := by
rw [← vadd_eq_add, AffineMap.map_vadd, affineCombination_linear]
#align finset.weighted_vsub_vadd_affine_combination Finset.weightedVSub_vadd_affineCombination
/-- Subtracting two `affineCombination`s. -/
theorem affineCombination_vsub (w₁ w₂ : ι → k) (p : ι → P) :
s.affineCombination k p w₁ -ᵥ s.affineCombination k p w₂ = s.weightedVSub p (w₁ - w₂) := by
rw [← AffineMap.linearMap_vsub, affineCombination_linear, vsub_eq_sub]
#align finset.affine_combination_vsub Finset.affineCombination_vsub
theorem attach_affineCombination_of_injective [DecidableEq P] (s : Finset P) (w : P → k) (f : s → P)
(hf : Function.Injective f) :
s.attach.affineCombination k f (w ∘ f) = (image f univ).affineCombination k id w := by
simp only [affineCombination, weightedVSubOfPoint_apply, id, vadd_right_cancel_iff,
Function.comp_apply, AffineMap.coe_mk]
let g₁ : s → V := fun i => w (f i) • (f i -ᵥ Classical.choice S.nonempty)
let g₂ : P → V := fun i => w i • (i -ᵥ Classical.choice S.nonempty)
change univ.sum g₁ = (image f univ).sum g₂
have hgf : g₁ = g₂ ∘ f := by
ext
simp
rw [hgf, sum_image]
· simp only [Function.comp_apply]
· exact fun _ _ _ _ hxy => hf hxy
#align finset.attach_affine_combination_of_injective Finset.attach_affineCombination_of_injective
theorem attach_affineCombination_coe (s : Finset P) (w : P → k) :
s.attach.affineCombination k ((↑) : s → P) (w ∘ (↑)) = s.affineCombination k id w := by
classical rw [attach_affineCombination_of_injective s w ((↑) : s → P) Subtype.coe_injective,
univ_eq_attach, attach_image_val]
#align finset.attach_affine_combination_coe Finset.attach_affineCombination_coe
/-- Viewing a module as an affine space modelled on itself, a `weightedVSub` is just a linear
combination. -/
@[simp]
theorem weightedVSub_eq_linear_combination {ι} (s : Finset ι) {w : ι → k} {p : ι → V}
(hw : s.sum w = 0) : s.weightedVSub p w = ∑ i ∈ s, w i • p i := by
simp [s.weightedVSub_apply, vsub_eq_sub, smul_sub, ← Finset.sum_smul, hw]
#align finset.weighted_vsub_eq_linear_combination Finset.weightedVSub_eq_linear_combination
/-- Viewing a module as an affine space modelled on itself, affine combinations are just linear
combinations. -/
@[simp]
theorem affineCombination_eq_linear_combination (s : Finset ι) (p : ι → V) (w : ι → k)
(hw : ∑ i ∈ s, w i = 1) : s.affineCombination k p w = ∑ i ∈ s, w i • p i := by
simp [s.affineCombination_eq_weightedVSubOfPoint_vadd_of_sum_eq_one w p hw 0]
#align finset.affine_combination_eq_linear_combination Finset.affineCombination_eq_linear_combination
/-- An `affineCombination` equals a point if that point is in the set
and has weight 1 and the other points in the set have weight 0. -/
@[simp]
| Mathlib/LinearAlgebra/AffineSpace/Combination.lean | 472 | 482 | theorem affineCombination_of_eq_one_of_eq_zero (w : ι → k) (p : ι → P) {i : ι} (his : i ∈ s)
(hwi : w i = 1) (hw0 : ∀ i2 ∈ s, i2 ≠ i → w i2 = 0) : s.affineCombination k p w = p i := by |
have h1 : ∑ i ∈ s, w i = 1 := hwi ▸ sum_eq_single i hw0 fun h => False.elim (h his)
rw [s.affineCombination_eq_weightedVSubOfPoint_vadd_of_sum_eq_one w p h1 (p i),
weightedVSubOfPoint_apply]
convert zero_vadd V (p i)
refine sum_eq_zero ?_
intro i2 hi2
by_cases h : i2 = i
· simp [h]
· simp [hw0 i2 hi2 h]
|
/-
Copyright (c) 2023 Alex Keizer. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alex Keizer
-/
import Mathlib.Data.Vector.Basic
import Mathlib.Data.Vector.Snoc
/-!
This file establishes a set of normalization lemmas for `map`/`mapAccumr` operations on vectors
-/
set_option autoImplicit true
namespace Vector
/-!
## Fold nested `mapAccumr`s into one
-/
section Fold
section Unary
variable (xs : Vector α n) (f₁ : β → σ₁ → σ₁ × γ) (f₂ : α → σ₂ → σ₂ × β)
@[simp]
theorem mapAccumr_mapAccumr :
mapAccumr f₁ (mapAccumr f₂ xs s₂).snd s₁
= let m := (mapAccumr (fun x s =>
let r₂ := f₂ x s.snd
let r₁ := f₁ r₂.snd s.fst
((r₁.fst, r₂.fst), r₁.snd)
) xs (s₁, s₂))
(m.fst.fst, m.snd) := by
induction xs using Vector.revInductionOn generalizing s₁ s₂ <;> simp_all
@[simp]
theorem mapAccumr_map (f₂ : α → β) :
(mapAccumr f₁ (map f₂ xs) s) = (mapAccumr (fun x s => f₁ (f₂ x) s) xs s) := by
induction xs using Vector.revInductionOn generalizing s <;> simp_all
@[simp]
theorem map_mapAccumr (f₁ : β → γ) :
(map f₁ (mapAccumr f₂ xs s).snd) = (mapAccumr (fun x s =>
let r := (f₂ x s); (r.fst, f₁ r.snd)
) xs s).snd := by
induction xs using Vector.revInductionOn generalizing s <;> simp_all
@[simp]
theorem map_map (f₁ : β → γ) (f₂ : α → β) :
map f₁ (map f₂ xs) = map (fun x => f₁ <| f₂ x) xs := by
induction xs <;> simp_all
end Unary
section Binary
variable (xs : Vector α n) (ys : Vector β n)
@[simp]
theorem mapAccumr₂_mapAccumr_left (f₁ : γ → β → σ₁ → σ₁ × ζ) (f₂ : α → σ₂ → σ₂ × γ) :
(mapAccumr₂ f₁ (mapAccumr f₂ xs s₂).snd ys s₁)
= let m := (mapAccumr₂ (fun x y s =>
let r₂ := f₂ x s.snd
let r₁ := f₁ r₂.snd y s.fst
((r₁.fst, r₂.fst), r₁.snd)
) xs ys (s₁, s₂))
(m.fst.fst, m.snd) := by
induction xs, ys using Vector.revInductionOn₂ generalizing s₁ s₂ <;> simp_all
@[simp]
theorem map₂_map_left (f₁ : γ → β → ζ) (f₂ : α → γ) :
map₂ f₁ (map f₂ xs) ys = map₂ (fun x y => f₁ (f₂ x) y) xs ys := by
induction xs, ys using Vector.revInductionOn₂ <;> simp_all
@[simp]
theorem mapAccumr₂_mapAccumr_right (f₁ : α → γ → σ₁ → σ₁ × ζ) (f₂ : β → σ₂ → σ₂ × γ) :
(mapAccumr₂ f₁ xs (mapAccumr f₂ ys s₂).snd s₁)
= let m := (mapAccumr₂ (fun x y s =>
let r₂ := f₂ y s.snd
let r₁ := f₁ x r₂.snd s.fst
((r₁.fst, r₂.fst), r₁.snd)
) xs ys (s₁, s₂))
(m.fst.fst, m.snd) := by
induction xs, ys using Vector.revInductionOn₂ generalizing s₁ s₂ <;> simp_all
@[simp]
theorem map₂_map_right (f₁ : α → γ → ζ) (f₂ : β → γ) :
map₂ f₁ xs (map f₂ ys) = map₂ (fun x y => f₁ x (f₂ y)) xs ys := by
induction xs, ys using Vector.revInductionOn₂ <;> simp_all
@[simp]
theorem mapAccumr_mapAccumr₂ (f₁ : γ → σ₁ → σ₁ × ζ) (f₂ : α → β → σ₂ → σ₂ × γ) :
(mapAccumr f₁ (mapAccumr₂ f₂ xs ys s₂).snd s₁)
= let m := mapAccumr₂ (fun x y s =>
let r₂ := f₂ x y s.snd
let r₁ := f₁ r₂.snd s.fst
((r₁.fst, r₂.fst), r₁.snd)
) xs ys (s₁, s₂)
(m.fst.fst, m.snd) := by
induction xs, ys using Vector.revInductionOn₂ generalizing s₁ s₂ <;> simp_all
@[simp]
theorem map_map₂ (f₁ : γ → ζ) (f₂ : α → β → γ) :
map f₁ (map₂ f₂ xs ys) = map₂ (fun x y => f₁ <| f₂ x y) xs ys := by
induction xs, ys using Vector.revInductionOn₂ <;> simp_all
@[simp]
| Mathlib/Data/Vector/MapLemmas.lean | 108 | 117 | theorem mapAccumr₂_mapAccumr₂_left_left (f₁ : γ → α → σ₁ → σ₁ × φ) (f₂ : α → β → σ₂ → σ₂ × γ) :
(mapAccumr₂ f₁ (mapAccumr₂ f₂ xs ys s₂).snd xs s₁)
= let m := mapAccumr₂ (fun x y (s₁, s₂) =>
let r₂ := f₂ x y s₂
let r₁ := f₁ r₂.snd x s₁
((r₁.fst, r₂.fst), r₁.snd)
)
xs ys (s₁, s₂)
(m.fst.fst, m.snd) := by |
induction xs, ys using Vector.revInductionOn₂ generalizing s₁ s₂ <;> simp_all
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin, Robert Y. Lewis
-/
import Mathlib.RingTheory.WittVector.StructurePolynomial
#align_import ring_theory.witt_vector.defs from "leanprover-community/mathlib"@"f1944b30c97c5eb626e498307dec8b022a05bd0a"
/-!
# Witt vectors
In this file we define the type of `p`-typical Witt vectors and ring operations on it.
The ring axioms are verified in `Mathlib/RingTheory/WittVector/Basic.lean`.
For a fixed commutative ring `R` and prime `p`,
a Witt vector `x : 𝕎 R` is an infinite sequence `ℕ → R` of elements of `R`.
However, the ring operations `+` and `*` are not defined in the obvious component-wise way.
Instead, these operations are defined via certain polynomials
using the machinery in `Mathlib/RingTheory/WittVector/StructurePolynomial.lean`.
The `n`th value of the sum of two Witt vectors can depend on the `0`-th through `n`th values
of the summands. This effectively simulates a “carrying” operation.
## Main definitions
* `WittVector p R`: the type of `p`-typical Witt vectors with coefficients in `R`.
* `WittVector.coeff x n`: projects the `n`th value of the Witt vector `x`.
## Notation
We use notation `𝕎 R`, entered `\bbW`, for the Witt vectors over `R`.
## References
* [Hazewinkel, *Witt Vectors*][Haze09]
* [Commelin and Lewis, *Formalizing the Ring of Witt Vectors*][CL21]
-/
noncomputable section
/-- `WittVector p R` is the ring of `p`-typical Witt vectors over the commutative ring `R`,
where `p` is a prime number.
If `p` is invertible in `R`, this ring is isomorphic to `ℕ → R` (the product of `ℕ` copies of `R`).
If `R` is a ring of characteristic `p`, then `WittVector p R` is a ring of characteristic `0`.
The canonical example is `WittVector p (ZMod p)`,
which is isomorphic to the `p`-adic integers `ℤ_[p]`. -/
structure WittVector (p : ℕ) (R : Type*) where mk' ::
/-- `x.coeff n` is the `n`th coefficient of the Witt vector `x`.
This concept does not have a standard name in the literature.
-/
coeff : ℕ → R
#align witt_vector WittVector
-- Porting note: added to make the `p` argument explicit
/-- Construct a Witt vector `mk p x : 𝕎 R` from a sequence `x` of elements of `R`. -/
def WittVector.mk (p : ℕ) {R : Type*} (coeff : ℕ → R) : WittVector p R := mk' coeff
variable {p : ℕ}
/- We cannot make this `localized` notation, because the `p` on the RHS doesn't occur on the left
Hiding the `p` in the notation is very convenient, so we opt for repeating the `local notation`
in other files that use Witt vectors. -/
local notation "𝕎" => WittVector p -- type as `\bbW`
namespace WittVector
variable {R : Type*}
@[ext]
theorem ext {x y : 𝕎 R} (h : ∀ n, x.coeff n = y.coeff n) : x = y := by
cases x
cases y
simp only at h
simp [Function.funext_iff, h]
#align witt_vector.ext WittVector.ext
theorem ext_iff {x y : 𝕎 R} : x = y ↔ ∀ n, x.coeff n = y.coeff n :=
⟨fun h n => by rw [h], ext⟩
#align witt_vector.ext_iff WittVector.ext_iff
variable (p)
theorem coeff_mk (x : ℕ → R) : (mk p x).coeff = x :=
rfl
#align witt_vector.coeff_mk WittVector.coeff_mk
/- These instances are not needed for the rest of the development,
but it is interesting to establish early on that `WittVector p` is a lawful functor. -/
instance : Functor (WittVector p) where
map f v := mk p (f ∘ v.coeff)
mapConst a _ := mk p fun _ => a
instance : LawfulFunctor (WittVector p) where
map_const := rfl
-- Porting note: no longer needs to deconstruct `v` to conclude `{coeff := v.coeff} = v`
id_map _ := rfl
comp_map _ _ _ := rfl
variable [hp : Fact p.Prime] [CommRing R]
open MvPolynomial
section RingOperations
/-- The polynomials used for defining the element `0` of the ring of Witt vectors. -/
def wittZero : ℕ → MvPolynomial (Fin 0 × ℕ) ℤ :=
wittStructureInt p 0
#align witt_vector.witt_zero WittVector.wittZero
/-- The polynomials used for defining the element `1` of the ring of Witt vectors. -/
def wittOne : ℕ → MvPolynomial (Fin 0 × ℕ) ℤ :=
wittStructureInt p 1
#align witt_vector.witt_one WittVector.wittOne
/-- The polynomials used for defining the addition of the ring of Witt vectors. -/
def wittAdd : ℕ → MvPolynomial (Fin 2 × ℕ) ℤ :=
wittStructureInt p (X 0 + X 1)
#align witt_vector.witt_add WittVector.wittAdd
/-- The polynomials used for defining repeated addition of the ring of Witt vectors. -/
def wittNSMul (n : ℕ) : ℕ → MvPolynomial (Fin 1 × ℕ) ℤ :=
wittStructureInt p (n • X (0 : (Fin 1)))
#align witt_vector.witt_nsmul WittVector.wittNSMul
/-- The polynomials used for defining repeated addition of the ring of Witt vectors. -/
def wittZSMul (n : ℤ) : ℕ → MvPolynomial (Fin 1 × ℕ) ℤ :=
wittStructureInt p (n • X (0 : (Fin 1)))
#align witt_vector.witt_zsmul WittVector.wittZSMul
/-- The polynomials used for describing the subtraction of the ring of Witt vectors. -/
def wittSub : ℕ → MvPolynomial (Fin 2 × ℕ) ℤ :=
wittStructureInt p (X 0 - X 1)
#align witt_vector.witt_sub WittVector.wittSub
/-- The polynomials used for defining the multiplication of the ring of Witt vectors. -/
def wittMul : ℕ → MvPolynomial (Fin 2 × ℕ) ℤ :=
wittStructureInt p (X 0 * X 1)
#align witt_vector.witt_mul WittVector.wittMul
/-- The polynomials used for defining the negation of the ring of Witt vectors. -/
def wittNeg : ℕ → MvPolynomial (Fin 1 × ℕ) ℤ :=
wittStructureInt p (-X 0)
#align witt_vector.witt_neg WittVector.wittNeg
/-- The polynomials used for defining repeated addition of the ring of Witt vectors. -/
def wittPow (n : ℕ) : ℕ → MvPolynomial (Fin 1 × ℕ) ℤ :=
wittStructureInt p (X 0 ^ n)
#align witt_vector.witt_pow WittVector.wittPow
variable {p}
/-- An auxiliary definition used in `WittVector.eval`.
Evaluates a polynomial whose variables come from the disjoint union of `k` copies of `ℕ`,
with a curried evaluation `x`.
This can be defined more generally but we use only a specific instance here. -/
def peval {k : ℕ} (φ : MvPolynomial (Fin k × ℕ) ℤ) (x : Fin k → ℕ → R) : R :=
aeval (Function.uncurry x) φ
#align witt_vector.peval WittVector.peval
/-- Let `φ` be a family of polynomials, indexed by natural numbers, whose variables come from the
disjoint union of `k` copies of `ℕ`, and let `xᵢ` be a Witt vector for `0 ≤ i < k`.
`eval φ x` evaluates `φ` mapping the variable `X_(i, n)` to the `n`th coefficient of `xᵢ`.
Instantiating `φ` with certain polynomials defined in
`Mathlib/RingTheory/WittVector/StructurePolynomial.lean` establishes the
ring operations on `𝕎 R`. For example, `WittVector.wittAdd` is such a `φ` with `k = 2`;
evaluating this at `(x₀, x₁)` gives us the sum of two Witt vectors `x₀ + x₁`.
-/
def eval {k : ℕ} (φ : ℕ → MvPolynomial (Fin k × ℕ) ℤ) (x : Fin k → 𝕎 R) : 𝕎 R :=
mk p fun n => peval (φ n) fun i => (x i).coeff
#align witt_vector.eval WittVector.eval
variable (R) [Fact p.Prime]
instance : Zero (𝕎 R) :=
⟨eval (wittZero p) ![]⟩
instance : Inhabited (𝕎 R) :=
⟨0⟩
instance : One (𝕎 R) :=
⟨eval (wittOne p) ![]⟩
instance : Add (𝕎 R) :=
⟨fun x y => eval (wittAdd p) ![x, y]⟩
instance : Sub (𝕎 R) :=
⟨fun x y => eval (wittSub p) ![x, y]⟩
instance hasNatScalar : SMul ℕ (𝕎 R) :=
⟨fun n x => eval (wittNSMul p n) ![x]⟩
#align witt_vector.has_nat_scalar WittVector.hasNatScalar
instance hasIntScalar : SMul ℤ (𝕎 R) :=
⟨fun n x => eval (wittZSMul p n) ![x]⟩
#align witt_vector.has_int_scalar WittVector.hasIntScalar
instance : Mul (𝕎 R) :=
⟨fun x y => eval (wittMul p) ![x, y]⟩
instance : Neg (𝕎 R) :=
⟨fun x => eval (wittNeg p) ![x]⟩
instance hasNatPow : Pow (𝕎 R) ℕ :=
⟨fun x n => eval (wittPow p n) ![x]⟩
#align witt_vector.has_nat_pow WittVector.hasNatPow
instance : NatCast (𝕎 R) :=
⟨Nat.unaryCast⟩
instance : IntCast (𝕎 R) :=
⟨Int.castDef⟩
end RingOperations
section WittStructureSimplifications
@[simp]
theorem wittZero_eq_zero (n : ℕ) : wittZero p n = 0 := by
apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective
simp only [wittZero, wittStructureRat, bind₁, aeval_zero', constantCoeff_xInTermsOfW,
RingHom.map_zero, AlgHom.map_zero, map_wittStructureInt]
#align witt_vector.witt_zero_eq_zero WittVector.wittZero_eq_zero
@[simp]
theorem wittOne_zero_eq_one : wittOne p 0 = 1 := by
apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective
simp only [wittOne, wittStructureRat, xInTermsOfW_zero, AlgHom.map_one, RingHom.map_one,
bind₁_X_right, map_wittStructureInt]
#align witt_vector.witt_one_zero_eq_one WittVector.wittOne_zero_eq_one
@[simp]
theorem wittOne_pos_eq_zero (n : ℕ) (hn : 0 < n) : wittOne p n = 0 := by
apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective
simp only [wittOne, wittStructureRat, RingHom.map_zero, AlgHom.map_one, RingHom.map_one,
map_wittStructureInt]
induction n using Nat.strong_induction_on with | h n IH => ?_
rw [xInTermsOfW_eq]
simp only [AlgHom.map_mul, AlgHom.map_sub, AlgHom.map_sum, AlgHom.map_pow, bind₁_X_right,
bind₁_C_right]
rw [sub_mul, one_mul]
rw [Finset.sum_eq_single 0]
· simp only [invOf_eq_inv, one_mul, inv_pow, tsub_zero, RingHom.map_one, pow_zero]
simp only [one_pow, one_mul, xInTermsOfW_zero, sub_self, bind₁_X_right]
· intro i hin hi0
rw [Finset.mem_range] at hin
rw [IH _ hin (Nat.pos_of_ne_zero hi0), zero_pow (pow_ne_zero _ hp.1.ne_zero), mul_zero]
· rw [Finset.mem_range]; intro; contradiction
#align witt_vector.witt_one_pos_eq_zero WittVector.wittOne_pos_eq_zero
@[simp]
theorem wittAdd_zero : wittAdd p 0 = X (0, 0) + X (1, 0) := by
apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective
simp only [wittAdd, wittStructureRat, AlgHom.map_add, RingHom.map_add, rename_X,
xInTermsOfW_zero, map_X, wittPolynomial_zero, bind₁_X_right, map_wittStructureInt]
#align witt_vector.witt_add_zero WittVector.wittAdd_zero
@[simp]
theorem wittSub_zero : wittSub p 0 = X (0, 0) - X (1, 0) := by
apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective
simp only [wittSub, wittStructureRat, AlgHom.map_sub, RingHom.map_sub, rename_X,
xInTermsOfW_zero, map_X, wittPolynomial_zero, bind₁_X_right, map_wittStructureInt]
#align witt_vector.witt_sub_zero WittVector.wittSub_zero
@[simp]
theorem wittMul_zero : wittMul p 0 = X (0, 0) * X (1, 0) := by
apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective
simp only [wittMul, wittStructureRat, rename_X, xInTermsOfW_zero, map_X, wittPolynomial_zero,
RingHom.map_mul, bind₁_X_right, AlgHom.map_mul, map_wittStructureInt]
#align witt_vector.witt_mul_zero WittVector.wittMul_zero
@[simp]
theorem wittNeg_zero : wittNeg p 0 = -X (0, 0) := by
apply MvPolynomial.map_injective (Int.castRingHom ℚ) Int.cast_injective
simp only [wittNeg, wittStructureRat, rename_X, xInTermsOfW_zero, map_X, wittPolynomial_zero,
RingHom.map_neg, AlgHom.map_neg, bind₁_X_right, map_wittStructureInt]
#align witt_vector.witt_neg_zero WittVector.wittNeg_zero
@[simp]
theorem constantCoeff_wittAdd (n : ℕ) : constantCoeff (wittAdd p n) = 0 := by
apply constantCoeff_wittStructureInt p _ _ n
simp only [add_zero, RingHom.map_add, constantCoeff_X]
#align witt_vector.constant_coeff_witt_add WittVector.constantCoeff_wittAdd
@[simp]
theorem constantCoeff_wittSub (n : ℕ) : constantCoeff (wittSub p n) = 0 := by
apply constantCoeff_wittStructureInt p _ _ n
simp only [sub_zero, RingHom.map_sub, constantCoeff_X]
#align witt_vector.constant_coeff_witt_sub WittVector.constantCoeff_wittSub
@[simp]
theorem constantCoeff_wittMul (n : ℕ) : constantCoeff (wittMul p n) = 0 := by
apply constantCoeff_wittStructureInt p _ _ n
simp only [mul_zero, RingHom.map_mul, constantCoeff_X]
#align witt_vector.constant_coeff_witt_mul WittVector.constantCoeff_wittMul
@[simp]
| Mathlib/RingTheory/WittVector/Defs.lean | 304 | 306 | theorem constantCoeff_wittNeg (n : ℕ) : constantCoeff (wittNeg p n) = 0 := by |
apply constantCoeff_wittStructureInt p _ _ n
simp only [neg_zero, RingHom.map_neg, constantCoeff_X]
|
/-
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, Sébastien Gouëzel
-/
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.MeasureTheory.Group.Pointwise
import Mathlib.MeasureTheory.Measure.Lebesgue.Basic
import Mathlib.MeasureTheory.Measure.Haar.Basic
import Mathlib.MeasureTheory.Measure.Doubling
import Mathlib.MeasureTheory.Constructions.BorelSpace.Metric
#align_import measure_theory.measure.lebesgue.eq_haar from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Relationship between the Haar and Lebesgue measures
We prove that the Haar measure and Lebesgue measure are equal on `ℝ` and on `ℝ^ι`, in
`MeasureTheory.addHaarMeasure_eq_volume` and `MeasureTheory.addHaarMeasure_eq_volume_pi`.
We deduce basic properties of any Haar measure on a finite dimensional real vector space:
* `map_linearMap_addHaar_eq_smul_addHaar`: a linear map rescales the Haar measure by the
absolute value of its determinant.
* `addHaar_preimage_linearMap` : when `f` is a linear map with nonzero determinant, the measure
of `f ⁻¹' s` is the measure of `s` multiplied by the absolute value of the inverse of the
determinant of `f`.
* `addHaar_image_linearMap` : when `f` is a linear map, the measure of `f '' s` is the
measure of `s` multiplied by the absolute value of the determinant of `f`.
* `addHaar_submodule` : a strict submodule has measure `0`.
* `addHaar_smul` : the measure of `r • s` is `|r| ^ dim * μ s`.
* `addHaar_ball`: the measure of `ball x r` is `r ^ dim * μ (ball 0 1)`.
* `addHaar_closedBall`: the measure of `closedBall x r` is `r ^ dim * μ (ball 0 1)`.
* `addHaar_sphere`: spheres have zero measure.
This makes it possible to associate a Lebesgue measure to an `n`-alternating map in dimension `n`.
This measure is called `AlternatingMap.measure`. Its main property is
`ω.measure_parallelepiped v`, stating that the associated measure of the parallelepiped spanned
by vectors `v₁, ..., vₙ` is given by `|ω v|`.
We also show that a Lebesgue density point `x` of a set `s` (with respect to closed balls) has
density one for the rescaled copies `{x} + r • t` of a given set `t` with positive measure, in
`tendsto_addHaar_inter_smul_one_of_density_one`. In particular, `s` intersects `{x} + r • t` for
small `r`, see `eventually_nonempty_inter_smul_of_density_one`.
Statements on integrals of functions with respect to an additive Haar measure can be found in
`MeasureTheory.Measure.Haar.NormedSpace`.
-/
assert_not_exists MeasureTheory.integral
open TopologicalSpace Set Filter Metric Bornology
open scoped ENNReal Pointwise Topology NNReal
/-- The interval `[0,1]` as a compact set with non-empty interior. -/
def TopologicalSpace.PositiveCompacts.Icc01 : PositiveCompacts ℝ where
carrier := Icc 0 1
isCompact' := isCompact_Icc
interior_nonempty' := by simp_rw [interior_Icc, nonempty_Ioo, zero_lt_one]
#align topological_space.positive_compacts.Icc01 TopologicalSpace.PositiveCompacts.Icc01
universe u
/-- The set `[0,1]^ι` as a compact set with non-empty interior. -/
def TopologicalSpace.PositiveCompacts.piIcc01 (ι : Type*) [Finite ι] :
PositiveCompacts (ι → ℝ) where
carrier := pi univ fun _ => Icc 0 1
isCompact' := isCompact_univ_pi fun _ => isCompact_Icc
interior_nonempty' := by
simp only [interior_pi_set, Set.toFinite, interior_Icc, univ_pi_nonempty_iff, nonempty_Ioo,
imp_true_iff, zero_lt_one]
#align topological_space.positive_compacts.pi_Icc01 TopologicalSpace.PositiveCompacts.piIcc01
/-- The parallelepiped formed from the standard basis for `ι → ℝ` is `[0,1]^ι` -/
theorem Basis.parallelepiped_basisFun (ι : Type*) [Fintype ι] :
(Pi.basisFun ℝ ι).parallelepiped = TopologicalSpace.PositiveCompacts.piIcc01 ι :=
SetLike.coe_injective <| by
refine Eq.trans ?_ ((uIcc_of_le ?_).trans (Set.pi_univ_Icc _ _).symm)
· classical convert parallelepiped_single (ι := ι) 1
· exact zero_le_one
#align basis.parallelepiped_basis_fun Basis.parallelepiped_basisFun
/-- A parallelepiped can be expressed on the standard basis. -/
theorem Basis.parallelepiped_eq_map {ι E : Type*} [Fintype ι] [NormedAddCommGroup E]
[NormedSpace ℝ E] (b : Basis ι ℝ E) :
b.parallelepiped = (PositiveCompacts.piIcc01 ι).map b.equivFun.symm
b.equivFunL.symm.continuous b.equivFunL.symm.isOpenMap := by
classical
rw [← Basis.parallelepiped_basisFun, ← Basis.parallelepiped_map]
congr with x
simp
open MeasureTheory MeasureTheory.Measure
theorem Basis.map_addHaar {ι E F : Type*} [Fintype ι] [NormedAddCommGroup E] [NormedAddCommGroup F]
[NormedSpace ℝ E] [NormedSpace ℝ F] [MeasurableSpace E] [MeasurableSpace F] [BorelSpace E]
[BorelSpace F] [SecondCountableTopology F] [SigmaCompactSpace F]
(b : Basis ι ℝ E) (f : E ≃L[ℝ] F) :
map f b.addHaar = (b.map f.toLinearEquiv).addHaar := by
have : IsAddHaarMeasure (map f b.addHaar) :=
AddEquiv.isAddHaarMeasure_map b.addHaar f.toAddEquiv f.continuous f.symm.continuous
rw [eq_comm, Basis.addHaar_eq_iff, Measure.map_apply f.continuous.measurable
(PositiveCompacts.isCompact _).measurableSet, Basis.coe_parallelepiped, Basis.coe_map]
erw [← image_parallelepiped, f.toEquiv.preimage_image, addHaar_self]
namespace MeasureTheory
open Measure TopologicalSpace.PositiveCompacts FiniteDimensional
/-!
### The Lebesgue measure is a Haar measure on `ℝ` and on `ℝ^ι`.
-/
/-- The Haar measure equals the Lebesgue measure on `ℝ`. -/
theorem addHaarMeasure_eq_volume : addHaarMeasure Icc01 = volume := by
convert (addHaarMeasure_unique volume Icc01).symm; simp [Icc01]
#align measure_theory.add_haar_measure_eq_volume MeasureTheory.addHaarMeasure_eq_volume
/-- The Haar measure equals the Lebesgue measure on `ℝ^ι`. -/
theorem addHaarMeasure_eq_volume_pi (ι : Type*) [Fintype ι] :
addHaarMeasure (piIcc01 ι) = volume := by
convert (addHaarMeasure_unique volume (piIcc01 ι)).symm
simp only [piIcc01, volume_pi_pi fun _ => Icc (0 : ℝ) 1, PositiveCompacts.coe_mk,
Compacts.coe_mk, Finset.prod_const_one, ENNReal.ofReal_one, Real.volume_Icc, one_smul, sub_zero]
#align measure_theory.add_haar_measure_eq_volume_pi MeasureTheory.addHaarMeasure_eq_volume_pi
-- Porting note (#11215): TODO: remove this instance?
instance isAddHaarMeasure_volume_pi (ι : Type*) [Fintype ι] :
IsAddHaarMeasure (volume : Measure (ι → ℝ)) :=
inferInstance
#align measure_theory.is_add_haar_measure_volume_pi MeasureTheory.isAddHaarMeasure_volume_pi
namespace Measure
/-!
### Strict subspaces have zero measure
-/
/-- If a set is disjoint of its translates by infinitely many bounded vectors, then it has measure
zero. This auxiliary lemma proves this assuming additionally that the set is bounded. -/
theorem addHaar_eq_zero_of_disjoint_translates_aux {E : Type*} [NormedAddCommGroup E]
[NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E)
[IsAddHaarMeasure μ] {s : Set E} (u : ℕ → E) (sb : IsBounded s) (hu : IsBounded (range u))
(hs : Pairwise (Disjoint on fun n => {u n} + s)) (h's : MeasurableSet s) : μ s = 0 := by
by_contra h
apply lt_irrefl ∞
calc
∞ = ∑' _ : ℕ, μ s := (ENNReal.tsum_const_eq_top_of_ne_zero h).symm
_ = ∑' n : ℕ, μ ({u n} + s) := by
congr 1; ext1 n; simp only [image_add_left, measure_preimage_add, singleton_add]
_ = μ (⋃ n, {u n} + s) := Eq.symm <| measure_iUnion hs fun n => by
simpa only [image_add_left, singleton_add] using measurable_id.const_add _ h's
_ = μ (range u + s) := by rw [← iUnion_add, iUnion_singleton_eq_range]
_ < ∞ := (hu.add sb).measure_lt_top
#align measure_theory.measure.add_haar_eq_zero_of_disjoint_translates_aux MeasureTheory.Measure.addHaar_eq_zero_of_disjoint_translates_aux
/-- If a set is disjoint of its translates by infinitely many bounded vectors, then it has measure
zero. -/
theorem addHaar_eq_zero_of_disjoint_translates {E : Type*} [NormedAddCommGroup E]
[NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E)
[IsAddHaarMeasure μ] {s : Set E} (u : ℕ → E) (hu : IsBounded (range u))
(hs : Pairwise (Disjoint on fun n => {u n} + s)) (h's : MeasurableSet s) : μ s = 0 := by
suffices H : ∀ R, μ (s ∩ closedBall 0 R) = 0 by
apply le_antisymm _ (zero_le _)
calc
μ s ≤ ∑' n : ℕ, μ (s ∩ closedBall 0 n) := by
conv_lhs => rw [← iUnion_inter_closedBall_nat s 0]
exact measure_iUnion_le _
_ = 0 := by simp only [H, tsum_zero]
intro R
apply addHaar_eq_zero_of_disjoint_translates_aux μ u
(isBounded_closedBall.subset inter_subset_right) hu _ (h's.inter measurableSet_closedBall)
refine pairwise_disjoint_mono hs fun n => ?_
exact add_subset_add Subset.rfl inter_subset_left
#align measure_theory.measure.add_haar_eq_zero_of_disjoint_translates MeasureTheory.Measure.addHaar_eq_zero_of_disjoint_translates
/-- A strict vector subspace has measure zero. -/
theorem addHaar_submodule {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E]
[BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] (s : Submodule ℝ E)
(hs : s ≠ ⊤) : μ s = 0 := by
obtain ⟨x, hx⟩ : ∃ x, x ∉ s := by
simpa only [Submodule.eq_top_iff', not_exists, Ne, not_forall] using hs
obtain ⟨c, cpos, cone⟩ : ∃ c : ℝ, 0 < c ∧ c < 1 := ⟨1 / 2, by norm_num, by norm_num⟩
have A : IsBounded (range fun n : ℕ => c ^ n • x) :=
have : Tendsto (fun n : ℕ => c ^ n • x) atTop (𝓝 ((0 : ℝ) • x)) :=
(tendsto_pow_atTop_nhds_zero_of_lt_one cpos.le cone).smul_const x
isBounded_range_of_tendsto _ this
apply addHaar_eq_zero_of_disjoint_translates μ _ A _
(Submodule.closed_of_finiteDimensional s).measurableSet
intro m n hmn
simp only [Function.onFun, image_add_left, singleton_add, disjoint_left, mem_preimage,
SetLike.mem_coe]
intro y hym hyn
have A : (c ^ n - c ^ m) • x ∈ s := by
convert s.sub_mem hym hyn using 1
simp only [sub_smul, neg_sub_neg, add_sub_add_right_eq_sub]
have H : c ^ n - c ^ m ≠ 0 := by
simpa only [sub_eq_zero, Ne] using (pow_right_strictAnti cpos cone).injective.ne hmn.symm
have : x ∈ s := by
convert s.smul_mem (c ^ n - c ^ m)⁻¹ A
rw [smul_smul, inv_mul_cancel H, one_smul]
exact hx this
#align measure_theory.measure.add_haar_submodule MeasureTheory.Measure.addHaar_submodule
/-- A strict affine subspace has measure zero. -/
theorem addHaar_affineSubspace {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[MeasurableSpace E] [BorelSpace E] [FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ]
(s : AffineSubspace ℝ E) (hs : s ≠ ⊤) : μ s = 0 := by
rcases s.eq_bot_or_nonempty with (rfl | hne)
· rw [AffineSubspace.bot_coe, measure_empty]
rw [Ne, ← AffineSubspace.direction_eq_top_iff_of_nonempty hne] at hs
rcases hne with ⟨x, hx : x ∈ s⟩
simpa only [AffineSubspace.coe_direction_eq_vsub_set_right hx, vsub_eq_sub, sub_eq_add_neg,
image_add_right, neg_neg, measure_preimage_add_right] using addHaar_submodule μ s.direction hs
#align measure_theory.measure.add_haar_affine_subspace MeasureTheory.Measure.addHaar_affineSubspace
/-!
### Applying a linear map rescales Haar measure by the determinant
We first prove this on `ι → ℝ`, using that this is already known for the product Lebesgue
measure (thanks to matrices computations). Then, we extend this to any finite-dimensional real
vector space by using a linear equiv with a space of the form `ι → ℝ`, and arguing that such a
linear equiv maps Haar measure to Haar measure.
-/
theorem map_linearMap_addHaar_pi_eq_smul_addHaar {ι : Type*} [Finite ι] {f : (ι → ℝ) →ₗ[ℝ] ι → ℝ}
(hf : LinearMap.det f ≠ 0) (μ : Measure (ι → ℝ)) [IsAddHaarMeasure μ] :
Measure.map f μ = ENNReal.ofReal (abs (LinearMap.det f)⁻¹) • μ := by
cases nonempty_fintype ι
/- We have already proved the result for the Lebesgue product measure, using matrices.
We deduce it for any Haar measure by uniqueness (up to scalar multiplication). -/
have := addHaarMeasure_unique μ (piIcc01 ι)
rw [this, addHaarMeasure_eq_volume_pi, Measure.map_smul,
Real.map_linearMap_volume_pi_eq_smul_volume_pi hf, smul_comm]
#align measure_theory.measure.map_linear_map_add_haar_pi_eq_smul_add_haar MeasureTheory.Measure.map_linearMap_addHaar_pi_eq_smul_addHaar
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [MeasurableSpace E] [BorelSpace E]
[FiniteDimensional ℝ E] (μ : Measure E) [IsAddHaarMeasure μ] {F : Type*} [NormedAddCommGroup F]
[NormedSpace ℝ F] [CompleteSpace F]
theorem map_linearMap_addHaar_eq_smul_addHaar {f : E →ₗ[ℝ] E} (hf : LinearMap.det f ≠ 0) :
Measure.map f μ = ENNReal.ofReal |(LinearMap.det f)⁻¹| • μ := by
-- we reduce to the case of `E = ι → ℝ`, for which we have already proved the result using
-- matrices in `map_linearMap_addHaar_pi_eq_smul_addHaar`.
let ι := Fin (finrank ℝ E)
haveI : FiniteDimensional ℝ (ι → ℝ) := by infer_instance
have : finrank ℝ E = finrank ℝ (ι → ℝ) := by simp [ι]
have e : E ≃ₗ[ℝ] ι → ℝ := LinearEquiv.ofFinrankEq E (ι → ℝ) this
-- next line is to avoid `g` getting reduced by `simp`.
obtain ⟨g, hg⟩ : ∃ g, g = (e : E →ₗ[ℝ] ι → ℝ).comp (f.comp (e.symm : (ι → ℝ) →ₗ[ℝ] E)) := ⟨_, rfl⟩
have gdet : LinearMap.det g = LinearMap.det f := by rw [hg]; exact LinearMap.det_conj f e
rw [← gdet] at hf ⊢
have fg : f = (e.symm : (ι → ℝ) →ₗ[ℝ] E).comp (g.comp (e : E →ₗ[ℝ] ι → ℝ)) := by
ext x
simp only [LinearEquiv.coe_coe, Function.comp_apply, LinearMap.coe_comp,
LinearEquiv.symm_apply_apply, hg]
simp only [fg, LinearEquiv.coe_coe, LinearMap.coe_comp]
have Ce : Continuous e := (e : E →ₗ[ℝ] ι → ℝ).continuous_of_finiteDimensional
have Cg : Continuous g := LinearMap.continuous_of_finiteDimensional g
have Cesymm : Continuous e.symm := (e.symm : (ι → ℝ) →ₗ[ℝ] E).continuous_of_finiteDimensional
rw [← map_map Cesymm.measurable (Cg.comp Ce).measurable, ← map_map Cg.measurable Ce.measurable]
haveI : IsAddHaarMeasure (map e μ) := (e : E ≃+ (ι → ℝ)).isAddHaarMeasure_map μ Ce Cesymm
have ecomp : e.symm ∘ e = id := by
ext x; simp only [id, Function.comp_apply, LinearEquiv.symm_apply_apply]
rw [map_linearMap_addHaar_pi_eq_smul_addHaar hf (map e μ), Measure.map_smul,
map_map Cesymm.measurable Ce.measurable, ecomp, Measure.map_id]
#align measure_theory.measure.map_linear_map_add_haar_eq_smul_add_haar MeasureTheory.Measure.map_linearMap_addHaar_eq_smul_addHaar
/-- The preimage of a set `s` under a linear map `f` with nonzero determinant has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_linearMap {f : E →ₗ[ℝ] E} (hf : LinearMap.det f ≠ 0) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal |(LinearMap.det f)⁻¹| * μ s :=
calc
μ (f ⁻¹' s) = Measure.map f μ s :=
((f.equivOfDetNeZero hf).toContinuousLinearEquiv.toHomeomorph.toMeasurableEquiv.map_apply
s).symm
_ = ENNReal.ofReal |(LinearMap.det f)⁻¹| * μ s := by
rw [map_linearMap_addHaar_eq_smul_addHaar μ hf]; rfl
#align measure_theory.measure.add_haar_preimage_linear_map MeasureTheory.Measure.addHaar_preimage_linearMap
/-- The preimage of a set `s` under a continuous linear map `f` with nonzero determinant has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_continuousLinearMap {f : E →L[ℝ] E}
(hf : LinearMap.det (f : E →ₗ[ℝ] E) ≠ 0) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal (abs (LinearMap.det (f : E →ₗ[ℝ] E))⁻¹) * μ s :=
addHaar_preimage_linearMap μ hf s
#align measure_theory.measure.add_haar_preimage_continuous_linear_map MeasureTheory.Measure.addHaar_preimage_continuousLinearMap
/-- The preimage of a set `s` under a linear equiv `f` has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_linearEquiv (f : E ≃ₗ[ℝ] E) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal |LinearMap.det (f.symm : E →ₗ[ℝ] E)| * μ s := by
have A : LinearMap.det (f : E →ₗ[ℝ] E) ≠ 0 := (LinearEquiv.isUnit_det' f).ne_zero
convert addHaar_preimage_linearMap μ A s
simp only [LinearEquiv.det_coe_symm]
#align measure_theory.measure.add_haar_preimage_linear_equiv MeasureTheory.Measure.addHaar_preimage_linearEquiv
/-- The preimage of a set `s` under a continuous linear equiv `f` has measure
equal to `μ s` times the absolute value of the inverse of the determinant of `f`. -/
@[simp]
theorem addHaar_preimage_continuousLinearEquiv (f : E ≃L[ℝ] E) (s : Set E) :
μ (f ⁻¹' s) = ENNReal.ofReal |LinearMap.det (f.symm : E →ₗ[ℝ] E)| * μ s :=
addHaar_preimage_linearEquiv μ _ s
#align measure_theory.measure.add_haar_preimage_continuous_linear_equiv MeasureTheory.Measure.addHaar_preimage_continuousLinearEquiv
/-- The image of a set `s` under a linear map `f` has measure
equal to `μ s` times the absolute value of the determinant of `f`. -/
@[simp]
theorem addHaar_image_linearMap (f : E →ₗ[ℝ] E) (s : Set E) :
μ (f '' s) = ENNReal.ofReal |LinearMap.det f| * μ s := by
rcases ne_or_eq (LinearMap.det f) 0 with (hf | hf)
· let g := (f.equivOfDetNeZero hf).toContinuousLinearEquiv
change μ (g '' s) = _
rw [ContinuousLinearEquiv.image_eq_preimage g s, addHaar_preimage_continuousLinearEquiv]
congr
· simp only [hf, zero_mul, ENNReal.ofReal_zero, abs_zero]
have : μ (LinearMap.range f) = 0 :=
addHaar_submodule μ _ (LinearMap.range_lt_top_of_det_eq_zero hf).ne
exact le_antisymm (le_trans (measure_mono (image_subset_range _ _)) this.le) (zero_le _)
#align measure_theory.measure.add_haar_image_linear_map MeasureTheory.Measure.addHaar_image_linearMap
/-- The image of a set `s` under a continuous linear map `f` has measure
equal to `μ s` times the absolute value of the determinant of `f`. -/
@[simp]
theorem addHaar_image_continuousLinearMap (f : E →L[ℝ] E) (s : Set E) :
μ (f '' s) = ENNReal.ofReal |LinearMap.det (f : E →ₗ[ℝ] E)| * μ s :=
addHaar_image_linearMap μ _ s
#align measure_theory.measure.add_haar_image_continuous_linear_map MeasureTheory.Measure.addHaar_image_continuousLinearMap
/-- The image of a set `s` under a continuous linear equiv `f` has measure
equal to `μ s` times the absolute value of the determinant of `f`. -/
@[simp]
theorem addHaar_image_continuousLinearEquiv (f : E ≃L[ℝ] E) (s : Set E) :
μ (f '' s) = ENNReal.ofReal |LinearMap.det (f : E →ₗ[ℝ] E)| * μ s :=
μ.addHaar_image_linearMap (f : E →ₗ[ℝ] E) s
#align measure_theory.measure.add_haar_image_continuous_linear_equiv MeasureTheory.Measure.addHaar_image_continuousLinearEquiv
theorem LinearMap.quasiMeasurePreserving (f : E →ₗ[ℝ] E) (hf : LinearMap.det f ≠ 0) :
QuasiMeasurePreserving f μ μ := by
refine ⟨f.continuous_of_finiteDimensional.measurable, ?_⟩
rw [map_linearMap_addHaar_eq_smul_addHaar μ hf]
exact smul_absolutelyContinuous
theorem ContinuousLinearMap.quasiMeasurePreserving (f : E →L[ℝ] E) (hf : f.det ≠ 0) :
QuasiMeasurePreserving f μ μ :=
LinearMap.quasiMeasurePreserving μ (f : E →ₗ[ℝ] E) hf
/-!
### Basic properties of Haar measures on real vector spaces
-/
theorem map_addHaar_smul {r : ℝ} (hr : r ≠ 0) :
Measure.map (r • ·) μ = ENNReal.ofReal (abs (r ^ finrank ℝ E)⁻¹) • μ := by
let f : E →ₗ[ℝ] E := r • (1 : E →ₗ[ℝ] E)
change Measure.map f μ = _
have hf : LinearMap.det f ≠ 0 := by
simp only [f, mul_one, LinearMap.det_smul, Ne, MonoidHom.map_one]
intro h
exact hr (pow_eq_zero h)
simp only [f, map_linearMap_addHaar_eq_smul_addHaar μ hf, mul_one, LinearMap.det_smul, map_one]
#align measure_theory.measure.map_add_haar_smul MeasureTheory.Measure.map_addHaar_smul
theorem quasiMeasurePreserving_smul {r : ℝ} (hr : r ≠ 0) :
QuasiMeasurePreserving (r • ·) μ μ := by
refine ⟨measurable_const_smul r, ?_⟩
rw [map_addHaar_smul μ hr]
exact smul_absolutelyContinuous
@[simp]
theorem addHaar_preimage_smul {r : ℝ} (hr : r ≠ 0) (s : Set E) :
μ ((r • ·) ⁻¹' s) = ENNReal.ofReal (abs (r ^ finrank ℝ E)⁻¹) * μ s :=
calc
μ ((r • ·) ⁻¹' s) = Measure.map (r • ·) μ s :=
((Homeomorph.smul (isUnit_iff_ne_zero.2 hr).unit).toMeasurableEquiv.map_apply s).symm
_ = ENNReal.ofReal (abs (r ^ finrank ℝ E)⁻¹) * μ s := by
rw [map_addHaar_smul μ hr, coe_smul, Pi.smul_apply, smul_eq_mul]
#align measure_theory.measure.add_haar_preimage_smul MeasureTheory.Measure.addHaar_preimage_smul
/-- Rescaling a set by a factor `r` multiplies its measure by `abs (r ^ dim)`. -/
@[simp]
theorem addHaar_smul (r : ℝ) (s : Set E) :
μ (r • s) = ENNReal.ofReal (abs (r ^ finrank ℝ E)) * μ s := by
rcases ne_or_eq r 0 with (h | rfl)
· rw [← preimage_smul_inv₀ h, addHaar_preimage_smul μ (inv_ne_zero h), inv_pow, inv_inv]
rcases eq_empty_or_nonempty s with (rfl | hs)
· simp only [measure_empty, mul_zero, smul_set_empty]
rw [zero_smul_set hs, ← singleton_zero]
by_cases h : finrank ℝ E = 0
· haveI : Subsingleton E := finrank_zero_iff.1 h
simp only [h, one_mul, ENNReal.ofReal_one, abs_one, Subsingleton.eq_univ_of_nonempty hs,
pow_zero, Subsingleton.eq_univ_of_nonempty (singleton_nonempty (0 : E))]
· haveI : Nontrivial E := nontrivial_of_finrank_pos (bot_lt_iff_ne_bot.2 h)
simp only [h, zero_mul, ENNReal.ofReal_zero, abs_zero, Ne, not_false_iff,
zero_pow, measure_singleton]
#align measure_theory.measure.add_haar_smul MeasureTheory.Measure.addHaar_smul
theorem addHaar_smul_of_nonneg {r : ℝ} (hr : 0 ≤ r) (s : Set E) :
μ (r • s) = ENNReal.ofReal (r ^ finrank ℝ E) * μ s := by
rw [addHaar_smul, abs_pow, abs_of_nonneg hr]
#align measure_theory.measure.add_haar_smul_of_nonneg MeasureTheory.Measure.addHaar_smul_of_nonneg
variable {μ} {s : Set E}
-- Note: We might want to rename this once we acquire the lemma corresponding to
-- `MeasurableSet.const_smul`
theorem NullMeasurableSet.const_smul (hs : NullMeasurableSet s μ) (r : ℝ) :
NullMeasurableSet (r • s) μ := by
obtain rfl | hs' := s.eq_empty_or_nonempty
· simp
obtain rfl | hr := eq_or_ne r 0
· simpa [zero_smul_set hs'] using nullMeasurableSet_singleton _
obtain ⟨t, ht, hst⟩ := hs
refine ⟨_, ht.const_smul_of_ne_zero hr, ?_⟩
rw [← measure_symmDiff_eq_zero_iff] at hst ⊢
rw [← smul_set_symmDiff₀ hr, addHaar_smul μ, hst, mul_zero]
#align measure_theory.measure.null_measurable_set.const_smul MeasureTheory.Measure.NullMeasurableSet.const_smul
variable (μ)
@[simp]
theorem addHaar_image_homothety (x : E) (r : ℝ) (s : Set E) :
μ (AffineMap.homothety x r '' s) = ENNReal.ofReal (abs (r ^ finrank ℝ E)) * μ s :=
calc
μ (AffineMap.homothety x r '' s) = μ ((fun y => y + x) '' (r • (fun y => y + -x) '' s)) := by
simp only [← image_smul, image_image, ← sub_eq_add_neg]; rfl
_ = ENNReal.ofReal (abs (r ^ finrank ℝ E)) * μ s := by
simp only [image_add_right, measure_preimage_add_right, addHaar_smul]
#align measure_theory.measure.add_haar_image_homothety MeasureTheory.Measure.addHaar_image_homothety
/-! We don't need to state `map_addHaar_neg` here, because it has already been proved for
general Haar measures on general commutative groups. -/
/-! ### Measure of balls -/
theorem addHaar_ball_center {E : Type*} [NormedAddCommGroup E] [MeasurableSpace E] [BorelSpace E]
(μ : Measure E) [IsAddHaarMeasure μ] (x : E) (r : ℝ) : μ (ball x r) = μ (ball (0 : E) r) := by
have : ball (0 : E) r = (x + ·) ⁻¹' ball x r := by simp [preimage_add_ball]
rw [this, measure_preimage_add]
#align measure_theory.measure.add_haar_ball_center MeasureTheory.Measure.addHaar_ball_center
theorem addHaar_closedBall_center {E : Type*} [NormedAddCommGroup E] [MeasurableSpace E]
[BorelSpace E] (μ : Measure E) [IsAddHaarMeasure μ] (x : E) (r : ℝ) :
μ (closedBall x r) = μ (closedBall (0 : E) r) := by
have : closedBall (0 : E) r = (x + ·) ⁻¹' closedBall x r := by simp [preimage_add_closedBall]
rw [this, measure_preimage_add]
#align measure_theory.measure.add_haar_closed_ball_center MeasureTheory.Measure.addHaar_closedBall_center
| Mathlib/MeasureTheory/Measure/Lebesgue/EqHaar.lean | 454 | 458 | theorem addHaar_ball_mul_of_pos (x : E) {r : ℝ} (hr : 0 < r) (s : ℝ) :
μ (ball x (r * s)) = ENNReal.ofReal (r ^ finrank ℝ E) * μ (ball 0 s) := by |
have : ball (0 : E) (r * s) = r • ball (0 : E) s := by
simp only [_root_.smul_ball hr.ne' (0 : E) s, Real.norm_eq_abs, abs_of_nonneg hr.le, smul_zero]
simp only [this, addHaar_smul, abs_of_nonneg hr.le, addHaar_ball_center, abs_pow]
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Johannes Hölzl
-/
import Mathlib.MeasureTheory.Integral.Lebesgue
/-!
# Measure with a given density with respect to another measure
For a measure `μ` on `α` and a function `f : α → ℝ≥0∞`, we define a new measure `μ.withDensity f`.
On a measurable set `s`, that measure has value `∫⁻ a in s, f a ∂μ`.
An important result about `withDensity` is the Radon-Nikodym theorem. It states that, given measures
`μ, ν`, if `HaveLebesgueDecomposition μ ν` then `μ` is absolutely continuous with respect to
`ν` if and only if there exists a measurable function `f : α → ℝ≥0∞` such that
`μ = ν.withDensity f`.
See `MeasureTheory.Measure.absolutelyContinuous_iff_withDensity_rnDeriv_eq`.
-/
open Set hiding restrict restrict_apply
open Filter ENNReal NNReal MeasureTheory.Measure
namespace MeasureTheory
variable {α : Type*} {m0 : MeasurableSpace α} {μ : Measure α}
/-- Given a measure `μ : Measure α` and a function `f : α → ℝ≥0∞`, `μ.withDensity f` is the
measure such that for a measurable set `s` we have `μ.withDensity f s = ∫⁻ a in s, f a ∂μ`. -/
noncomputable
def Measure.withDensity {m : MeasurableSpace α} (μ : Measure α) (f : α → ℝ≥0∞) : Measure α :=
Measure.ofMeasurable (fun s _ => ∫⁻ a in s, f a ∂μ) (by simp) fun s hs hd =>
lintegral_iUnion hs hd _
#align measure_theory.measure.with_density MeasureTheory.Measure.withDensity
@[simp]
theorem withDensity_apply (f : α → ℝ≥0∞) {s : Set α} (hs : MeasurableSet s) :
μ.withDensity f s = ∫⁻ a in s, f a ∂μ :=
Measure.ofMeasurable_apply s hs
#align measure_theory.with_density_apply MeasureTheory.withDensity_apply
theorem withDensity_apply_le (f : α → ℝ≥0∞) (s : Set α) :
∫⁻ a in s, f a ∂μ ≤ μ.withDensity f s := by
let t := toMeasurable (μ.withDensity f) s
calc
∫⁻ a in s, f a ∂μ ≤ ∫⁻ a in t, f a ∂μ :=
lintegral_mono_set (subset_toMeasurable (withDensity μ f) s)
_ = μ.withDensity f t :=
(withDensity_apply f (measurableSet_toMeasurable (withDensity μ f) s)).symm
_ = μ.withDensity f s := measure_toMeasurable s
/-! In the next theorem, the s-finiteness assumption is necessary. Here is a counterexample
without this assumption. Let `α` be an uncountable space, let `x₀` be some fixed point, and consider
the σ-algebra made of those sets which are countable and do not contain `x₀`, and of their
complements. This is the σ-algebra generated by the sets `{x}` for `x ≠ x₀`. Define a measure equal
to `+∞` on nonempty sets. Let `s = {x₀}` and `f` the indicator of `sᶜ`. Then
* `∫⁻ a in s, f a ∂μ = 0`. Indeed, consider a simple function `g ≤ f`. It vanishes on `s`. Then
`∫⁻ a in s, g a ∂μ = 0`. Taking the supremum over `g` gives the claim.
* `μ.withDensity f s = +∞`. Indeed, this is the infimum of `μ.withDensity f t` over measurable sets
`t` containing `s`. As `s` is not measurable, such a set `t` contains a point `x ≠ x₀`. Then
`μ.withDensity f t ≥ μ.withDensity f {x} = ∫⁻ a in {x}, f a ∂μ = μ {x} = +∞`.
One checks that `μ.withDensity f = μ`, while `μ.restrict s` gives zero mass to sets not
containing `x₀`, and infinite mass to those that contain it. -/
theorem withDensity_apply' [SFinite μ] (f : α → ℝ≥0∞) (s : Set α) :
μ.withDensity f s = ∫⁻ a in s, f a ∂μ := by
apply le_antisymm ?_ (withDensity_apply_le f s)
let t := toMeasurable μ s
calc
μ.withDensity f s ≤ μ.withDensity f t := measure_mono (subset_toMeasurable μ s)
_ = ∫⁻ a in t, f a ∂μ := withDensity_apply f (measurableSet_toMeasurable μ s)
_ = ∫⁻ a in s, f a ∂μ := by congr 1; exact restrict_toMeasurable_of_sFinite s
@[simp]
lemma withDensity_zero_left (f : α → ℝ≥0∞) : (0 : Measure α).withDensity f = 0 := by
ext s hs
rw [withDensity_apply _ hs]
simp
theorem withDensity_congr_ae {f g : α → ℝ≥0∞} (h : f =ᵐ[μ] g) :
μ.withDensity f = μ.withDensity g := by
refine Measure.ext fun s hs => ?_
rw [withDensity_apply _ hs, withDensity_apply _ hs]
exact lintegral_congr_ae (ae_restrict_of_ae h)
#align measure_theory.with_density_congr_ae MeasureTheory.withDensity_congr_ae
lemma withDensity_mono {f g : α → ℝ≥0∞} (hfg : f ≤ᵐ[μ] g) :
μ.withDensity f ≤ μ.withDensity g := by
refine le_iff.2 fun s hs ↦ ?_
rw [withDensity_apply _ hs, withDensity_apply _ hs]
refine set_lintegral_mono_ae' hs ?_
filter_upwards [hfg] with x h_le using fun _ ↦ h_le
theorem withDensity_add_left {f : α → ℝ≥0∞} (hf : Measurable f) (g : α → ℝ≥0∞) :
μ.withDensity (f + g) = μ.withDensity f + μ.withDensity g := by
refine Measure.ext fun s hs => ?_
rw [withDensity_apply _ hs, Measure.add_apply, withDensity_apply _ hs, withDensity_apply _ hs,
← lintegral_add_left hf]
simp only [Pi.add_apply]
#align measure_theory.with_density_add_left MeasureTheory.withDensity_add_left
| Mathlib/MeasureTheory/Measure/WithDensity.lean | 105 | 107 | theorem withDensity_add_right (f : α → ℝ≥0∞) {g : α → ℝ≥0∞} (hg : Measurable g) :
μ.withDensity (f + g) = μ.withDensity f + μ.withDensity g := by |
simpa only [add_comm] using withDensity_add_left hg f
|
/-
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, Minchao Wu, Mario Carneiro
-/
import Mathlib.Algebra.Group.Embedding
import Mathlib.Data.Fin.Basic
import Mathlib.Data.Finset.Union
#align_import data.finset.image from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-! # Image and map operations on finite sets
This file provides the finite analog of `Set.image`, along with some other similar functions.
Note there are two ways to take the image over a finset; via `Finset.image` which applies the
function then removes duplicates (requiring `DecidableEq`), or via `Finset.map` which exploits
injectivity of the function to avoid needing to deduplicate. Choosing between these is similar to
choosing between `insert` and `Finset.cons`, or between `Finset.union` and `Finset.disjUnion`.
## Main definitions
* `Finset.image`: Given a function `f : α → β`, `s.image f` is the image finset in `β`.
* `Finset.map`: Given an embedding `f : α ↪ β`, `s.map f` is the image finset in `β`.
* `Finset.filterMap` Given a function `f : α → Option β`, `s.filterMap f` is the
image finset in `β`, filtering out `none`s.
* `Finset.subtype`: `s.subtype p` is the finset of `Subtype p` whose elements belong to `s`.
* `Finset.fin`:`s.fin n` is the finset of all elements of `s` less than `n`.
## TODO
Move the material about `Finset.range` so that the `Mathlib.Algebra.Group.Embedding` import can be
removed.
-/
-- TODO
-- assert_not_exists OrderedCommMonoid
assert_not_exists MonoidWithZero
assert_not_exists MulAction
variable {α β γ : Type*}
open Multiset
open Function
namespace Finset
/-! ### map -/
section Map
open Function
/-- When `f` is an embedding of `α` in `β` and `s` is a finset in `α`, then `s.map f` is the image
finset in `β`. The embedding condition guarantees that there are no duplicates in the image. -/
def map (f : α ↪ β) (s : Finset α) : Finset β :=
⟨s.1.map f, s.2.map f.2⟩
#align finset.map Finset.map
@[simp]
theorem map_val (f : α ↪ β) (s : Finset α) : (map f s).1 = s.1.map f :=
rfl
#align finset.map_val Finset.map_val
@[simp]
theorem map_empty (f : α ↪ β) : (∅ : Finset α).map f = ∅ :=
rfl
#align finset.map_empty Finset.map_empty
variable {f : α ↪ β} {s : Finset α}
@[simp]
theorem mem_map {b : β} : b ∈ s.map f ↔ ∃ a ∈ s, f a = b :=
Multiset.mem_map
#align finset.mem_map Finset.mem_map
-- Porting note: Higher priority to apply before `mem_map`.
@[simp 1100]
theorem mem_map_equiv {f : α ≃ β} {b : β} : b ∈ s.map f.toEmbedding ↔ f.symm b ∈ s := by
rw [mem_map]
exact
⟨by
rintro ⟨a, H, rfl⟩
simpa, fun h => ⟨_, h, by simp⟩⟩
#align finset.mem_map_equiv Finset.mem_map_equiv
-- The simpNF linter says that the LHS can be simplified via `Finset.mem_map`.
-- However this is a higher priority lemma.
-- https://github.com/leanprover/std4/issues/207
@[simp 1100, nolint simpNF]
theorem mem_map' (f : α ↪ β) {a} {s : Finset α} : f a ∈ s.map f ↔ a ∈ s :=
mem_map_of_injective f.2
#align finset.mem_map' Finset.mem_map'
theorem mem_map_of_mem (f : α ↪ β) {a} {s : Finset α} : a ∈ s → f a ∈ s.map f :=
(mem_map' _).2
#align finset.mem_map_of_mem Finset.mem_map_of_mem
theorem forall_mem_map {f : α ↪ β} {s : Finset α} {p : ∀ a, a ∈ s.map f → Prop} :
(∀ y (H : y ∈ s.map f), p y H) ↔ ∀ x (H : x ∈ s), p (f x) (mem_map_of_mem _ H) :=
⟨fun h y hy => h (f y) (mem_map_of_mem _ hy),
fun h x hx => by
obtain ⟨y, hy, rfl⟩ := mem_map.1 hx
exact h _ hy⟩
#align finset.forall_mem_map Finset.forall_mem_map
theorem apply_coe_mem_map (f : α ↪ β) (s : Finset α) (x : s) : f x ∈ s.map f :=
mem_map_of_mem f x.prop
#align finset.apply_coe_mem_map Finset.apply_coe_mem_map
@[simp, norm_cast]
theorem coe_map (f : α ↪ β) (s : Finset α) : (s.map f : Set β) = f '' s :=
Set.ext (by simp only [mem_coe, mem_map, Set.mem_image, implies_true])
#align finset.coe_map Finset.coe_map
theorem coe_map_subset_range (f : α ↪ β) (s : Finset α) : (s.map f : Set β) ⊆ Set.range f :=
calc
↑(s.map f) = f '' s := coe_map f s
_ ⊆ Set.range f := Set.image_subset_range f ↑s
#align finset.coe_map_subset_range Finset.coe_map_subset_range
/-- If the only elements outside `s` are those left fixed by `σ`, then mapping by `σ` has no effect.
-/
theorem map_perm {σ : Equiv.Perm α} (hs : { a | σ a ≠ a } ⊆ s) : s.map (σ : α ↪ α) = s :=
coe_injective <| (coe_map _ _).trans <| Set.image_perm hs
#align finset.map_perm Finset.map_perm
theorem map_toFinset [DecidableEq α] [DecidableEq β] {s : Multiset α} :
s.toFinset.map f = (s.map f).toFinset :=
ext fun _ => by simp only [mem_map, Multiset.mem_map, exists_prop, Multiset.mem_toFinset]
#align finset.map_to_finset Finset.map_toFinset
@[simp]
theorem map_refl : s.map (Embedding.refl _) = s :=
ext fun _ => by simpa only [mem_map, exists_prop] using exists_eq_right
#align finset.map_refl Finset.map_refl
@[simp]
theorem map_cast_heq {α β} (h : α = β) (s : Finset α) :
HEq (s.map (Equiv.cast h).toEmbedding) s := by
subst h
simp
#align finset.map_cast_heq Finset.map_cast_heq
theorem map_map (f : α ↪ β) (g : β ↪ γ) (s : Finset α) : (s.map f).map g = s.map (f.trans g) :=
eq_of_veq <| by simp only [map_val, Multiset.map_map]; rfl
#align finset.map_map Finset.map_map
theorem map_comm {β'} {f : β ↪ γ} {g : α ↪ β} {f' : α ↪ β'} {g' : β' ↪ γ}
(h_comm : ∀ a, f (g a) = g' (f' a)) : (s.map g).map f = (s.map f').map g' := by
simp_rw [map_map, Embedding.trans, Function.comp, h_comm]
#align finset.map_comm Finset.map_comm
theorem _root_.Function.Semiconj.finset_map {f : α ↪ β} {ga : α ↪ α} {gb : β ↪ β}
(h : Function.Semiconj f ga gb) : Function.Semiconj (map f) (map ga) (map gb) := fun _ =>
map_comm h
#align function.semiconj.finset_map Function.Semiconj.finset_map
theorem _root_.Function.Commute.finset_map {f g : α ↪ α} (h : Function.Commute f g) :
Function.Commute (map f) (map g) :=
Function.Semiconj.finset_map h
#align function.commute.finset_map Function.Commute.finset_map
@[simp]
theorem map_subset_map {s₁ s₂ : Finset α} : s₁.map f ⊆ s₂.map f ↔ s₁ ⊆ s₂ :=
⟨fun h x xs => (mem_map' _).1 <| h <| (mem_map' f).2 xs,
fun h => by simp [subset_def, Multiset.map_subset_map h]⟩
#align finset.map_subset_map Finset.map_subset_map
@[gcongr] alias ⟨_, _root_.GCongr.finsetMap_subset⟩ := map_subset_map
/-- The `Finset` version of `Equiv.subset_symm_image`. -/
theorem subset_map_symm {t : Finset β} {f : α ≃ β} : s ⊆ t.map f.symm ↔ s.map f ⊆ t := by
constructor <;> intro h x hx
· simp only [mem_map_equiv, Equiv.symm_symm] at hx
simpa using h hx
· simp only [mem_map_equiv]
exact h (by simp [hx])
/-- The `Finset` version of `Equiv.symm_image_subset`. -/
theorem map_symm_subset {t : Finset β} {f : α ≃ β} : t.map f.symm ⊆ s ↔ t ⊆ s.map f := by
simp only [← subset_map_symm, Equiv.symm_symm]
/-- Associate to an embedding `f` from `α` to `β` the order embedding that maps a finset to its
image under `f`. -/
def mapEmbedding (f : α ↪ β) : Finset α ↪o Finset β :=
OrderEmbedding.ofMapLEIff (map f) fun _ _ => map_subset_map
#align finset.map_embedding Finset.mapEmbedding
@[simp]
theorem map_inj {s₁ s₂ : Finset α} : s₁.map f = s₂.map f ↔ s₁ = s₂ :=
(mapEmbedding f).injective.eq_iff
#align finset.map_inj Finset.map_inj
theorem map_injective (f : α ↪ β) : Injective (map f) :=
(mapEmbedding f).injective
#align finset.map_injective Finset.map_injective
@[simp]
theorem map_ssubset_map {s t : Finset α} : s.map f ⊂ t.map f ↔ s ⊂ t := (mapEmbedding f).lt_iff_lt
@[gcongr] alias ⟨_, _root_.GCongr.finsetMap_ssubset⟩ := map_ssubset_map
@[simp]
theorem mapEmbedding_apply : mapEmbedding f s = map f s :=
rfl
#align finset.map_embedding_apply Finset.mapEmbedding_apply
theorem filter_map {p : β → Prop} [DecidablePred p] :
(s.map f).filter p = (s.filter (p ∘ f)).map f :=
eq_of_veq (map_filter _ _ _)
#align finset.filter_map Finset.filter_map
lemma map_filter' (p : α → Prop) [DecidablePred p] (f : α ↪ β) (s : Finset α)
[DecidablePred (∃ a, p a ∧ f a = ·)] :
(s.filter p).map f = (s.map f).filter fun b => ∃ a, p a ∧ f a = b := by
simp [(· ∘ ·), filter_map, f.injective.eq_iff]
#align finset.map_filter' Finset.map_filter'
lemma filter_attach' [DecidableEq α] (s : Finset α) (p : s → Prop) [DecidablePred p] :
s.attach.filter p =
(s.filter fun x => ∃ h, p ⟨x, h⟩).attach.map
⟨Subtype.map id <| filter_subset _ _, Subtype.map_injective _ injective_id⟩ :=
eq_of_veq <| Multiset.filter_attach' _ _
#align finset.filter_attach' Finset.filter_attach'
lemma filter_attach (p : α → Prop) [DecidablePred p] (s : Finset α) :
s.attach.filter (fun a : s ↦ p a) =
(s.filter p).attach.map ((Embedding.refl _).subtypeMap mem_of_mem_filter) :=
eq_of_veq <| Multiset.filter_attach _ _
#align finset.filter_attach Finset.filter_attach
theorem map_filter {f : α ≃ β} {p : α → Prop} [DecidablePred p] :
(s.filter p).map f.toEmbedding = (s.map f.toEmbedding).filter (p ∘ f.symm) := by
simp only [filter_map, Function.comp, Equiv.toEmbedding_apply, Equiv.symm_apply_apply]
#align finset.map_filter Finset.map_filter
@[simp]
theorem disjoint_map {s t : Finset α} (f : α ↪ β) :
Disjoint (s.map f) (t.map f) ↔ Disjoint s t :=
mod_cast Set.disjoint_image_iff f.injective (s := s) (t := t)
#align finset.disjoint_map Finset.disjoint_map
theorem map_disjUnion {f : α ↪ β} (s₁ s₂ : Finset α) (h) (h' := (disjoint_map _).mpr h) :
(s₁.disjUnion s₂ h).map f = (s₁.map f).disjUnion (s₂.map f) h' :=
eq_of_veq <| Multiset.map_add _ _ _
#align finset.map_disj_union Finset.map_disjUnion
/-- A version of `Finset.map_disjUnion` for writing in the other direction. -/
theorem map_disjUnion' {f : α ↪ β} (s₁ s₂ : Finset α) (h') (h := (disjoint_map _).mp h') :
(s₁.disjUnion s₂ h).map f = (s₁.map f).disjUnion (s₂.map f) h' :=
map_disjUnion _ _ _
#align finset.map_disj_union' Finset.map_disjUnion'
theorem map_union [DecidableEq α] [DecidableEq β] {f : α ↪ β} (s₁ s₂ : Finset α) :
(s₁ ∪ s₂).map f = s₁.map f ∪ s₂.map f :=
mod_cast Set.image_union f s₁ s₂
#align finset.map_union Finset.map_union
theorem map_inter [DecidableEq α] [DecidableEq β] {f : α ↪ β} (s₁ s₂ : Finset α) :
(s₁ ∩ s₂).map f = s₁.map f ∩ s₂.map f :=
mod_cast Set.image_inter f.injective (s := s₁) (t := s₂)
#align finset.map_inter Finset.map_inter
@[simp]
theorem map_singleton (f : α ↪ β) (a : α) : map f {a} = {f a} :=
coe_injective <| by simp only [coe_map, coe_singleton, Set.image_singleton]
#align finset.map_singleton Finset.map_singleton
@[simp]
theorem map_insert [DecidableEq α] [DecidableEq β] (f : α ↪ β) (a : α) (s : Finset α) :
(insert a s).map f = insert (f a) (s.map f) := by
simp only [insert_eq, map_union, map_singleton]
#align finset.map_insert Finset.map_insert
@[simp]
theorem map_cons (f : α ↪ β) (a : α) (s : Finset α) (ha : a ∉ s) :
(cons a s ha).map f = cons (f a) (s.map f) (by simpa using ha) :=
eq_of_veq <| Multiset.map_cons f a s.val
#align finset.map_cons Finset.map_cons
@[simp]
theorem map_eq_empty : s.map f = ∅ ↔ s = ∅ := (map_injective f).eq_iff' (map_empty f)
#align finset.map_eq_empty Finset.map_eq_empty
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem map_nonempty : (s.map f).Nonempty ↔ s.Nonempty :=
mod_cast Set.image_nonempty (f := f) (s := s)
#align finset.map_nonempty Finset.map_nonempty
protected alias ⟨_, Nonempty.map⟩ := map_nonempty
#align finset.nonempty.map Finset.Nonempty.map
@[simp]
theorem map_nontrivial : (s.map f).Nontrivial ↔ s.Nontrivial :=
mod_cast Set.image_nontrivial f.injective (s := s)
theorem attach_map_val {s : Finset α} : s.attach.map (Embedding.subtype _) = s :=
eq_of_veq <| by rw [map_val, attach_val]; exact Multiset.attach_map_val _
#align finset.attach_map_val Finset.attach_map_val
theorem disjoint_range_addLeftEmbedding (a b : ℕ) :
Disjoint (range a) (map (addLeftEmbedding a) (range b)) := by simp [disjoint_left]; omega
#align finset.disjoint_range_add_left_embedding Finset.disjoint_range_addLeftEmbedding
theorem disjoint_range_addRightEmbedding (a b : ℕ) :
Disjoint (range a) (map (addRightEmbedding a) (range b)) := by simp [disjoint_left]; omega
#align finset.disjoint_range_add_right_embedding Finset.disjoint_range_addRightEmbedding
theorem map_disjiUnion {f : α ↪ β} {s : Finset α} {t : β → Finset γ} {h} :
(s.map f).disjiUnion t h =
s.disjiUnion (fun a => t (f a)) fun _ ha _ hb hab =>
h (mem_map_of_mem _ ha) (mem_map_of_mem _ hb) (f.injective.ne hab) :=
eq_of_veq <| Multiset.bind_map _ _ _
#align finset.map_disj_Union Finset.map_disjiUnion
theorem disjiUnion_map {s : Finset α} {t : α → Finset β} {f : β ↪ γ} {h} :
(s.disjiUnion t h).map f =
s.disjiUnion (fun a => (t a).map f) (h.mono' fun _ _ ↦ (disjoint_map _).2) :=
eq_of_veq <| Multiset.map_bind _ _ _
#align finset.disj_Union_map Finset.disjiUnion_map
end Map
theorem range_add_one' (n : ℕ) :
range (n + 1) = insert 0 ((range n).map ⟨fun i => i + 1, fun i j => by simp⟩) := by
ext (⟨⟩ | ⟨n⟩) <;> simp [Nat.succ_eq_add_one, Nat.zero_lt_succ n]
#align finset.range_add_one' Finset.range_add_one'
/-! ### image -/
section Image
variable [DecidableEq β]
/-- `image f s` is the forward image of `s` under `f`. -/
def image (f : α → β) (s : Finset α) : Finset β :=
(s.1.map f).toFinset
#align finset.image Finset.image
@[simp]
theorem image_val (f : α → β) (s : Finset α) : (image f s).1 = (s.1.map f).dedup :=
rfl
#align finset.image_val Finset.image_val
@[simp]
theorem image_empty (f : α → β) : (∅ : Finset α).image f = ∅ :=
rfl
#align finset.image_empty Finset.image_empty
variable {f g : α → β} {s : Finset α} {t : Finset β} {a : α} {b c : β}
@[simp]
theorem mem_image : b ∈ s.image f ↔ ∃ a ∈ s, f a = b := by
simp only [mem_def, image_val, mem_dedup, Multiset.mem_map, exists_prop]
#align finset.mem_image Finset.mem_image
theorem mem_image_of_mem (f : α → β) {a} (h : a ∈ s) : f a ∈ s.image f :=
mem_image.2 ⟨_, h, rfl⟩
#align finset.mem_image_of_mem Finset.mem_image_of_mem
theorem forall_image {p : β → Prop} : (∀ b ∈ s.image f, p b) ↔ ∀ a ∈ s, p (f a) := by
simp only [mem_image, forall_exists_index, and_imp, forall_apply_eq_imp_iff₂]
#align finset.forall_image Finset.forall_image
theorem map_eq_image (f : α ↪ β) (s : Finset α) : s.map f = s.image f :=
eq_of_veq (s.map f).2.dedup.symm
#align finset.map_eq_image Finset.map_eq_image
--@[simp] Porting note: removing simp, `simp` [Nonempty] can prove it
theorem mem_image_const : c ∈ s.image (const α b) ↔ s.Nonempty ∧ b = c := by
rw [mem_image]
simp only [exists_prop, const_apply, exists_and_right]
rfl
#align finset.mem_image_const Finset.mem_image_const
theorem mem_image_const_self : b ∈ s.image (const α b) ↔ s.Nonempty :=
mem_image_const.trans <| and_iff_left rfl
#align finset.mem_image_const_self Finset.mem_image_const_self
instance canLift (c) (p) [CanLift β α c p] :
CanLift (Finset β) (Finset α) (image c) fun s => ∀ x ∈ s, p x where
prf := by
rintro ⟨⟨l⟩, hd : l.Nodup⟩ hl
lift l to List α using hl
exact ⟨⟨l, hd.of_map _⟩, ext fun a => by simp⟩
#align finset.can_lift Finset.canLift
theorem image_congr (h : (s : Set α).EqOn f g) : Finset.image f s = Finset.image g s := by
ext
simp_rw [mem_image, ← bex_def]
exact exists₂_congr fun x hx => by rw [h hx]
#align finset.image_congr Finset.image_congr
theorem _root_.Function.Injective.mem_finset_image (hf : Injective f) :
f a ∈ s.image f ↔ a ∈ s := by
refine ⟨fun h => ?_, Finset.mem_image_of_mem f⟩
obtain ⟨y, hy, heq⟩ := mem_image.1 h
exact hf heq ▸ hy
#align function.injective.mem_finset_image Function.Injective.mem_finset_image
theorem filter_mem_image_eq_image (f : α → β) (s : Finset α) (t : Finset β) (h : ∀ x ∈ s, f x ∈ t) :
(t.filter fun y => y ∈ s.image f) = s.image f := by
ext
simp only [mem_filter, mem_image, decide_eq_true_eq, and_iff_right_iff_imp, forall_exists_index,
and_imp]
rintro x xel rfl
exact h _ xel
#align finset.filter_mem_image_eq_image Finset.filter_mem_image_eq_image
theorem fiber_nonempty_iff_mem_image (f : α → β) (s : Finset α) (y : β) :
(s.filter fun x => f x = y).Nonempty ↔ y ∈ s.image f := by simp [Finset.Nonempty]
#align finset.fiber_nonempty_iff_mem_image Finset.fiber_nonempty_iff_mem_image
@[simp, norm_cast]
theorem coe_image : ↑(s.image f) = f '' ↑s :=
Set.ext <| by simp only [mem_coe, mem_image, Set.mem_image, implies_true]
#align finset.coe_image Finset.coe_image
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
lemma image_nonempty : (s.image f).Nonempty ↔ s.Nonempty :=
mod_cast Set.image_nonempty (f := f) (s := (s : Set α))
#align finset.nonempty.image_iff Finset.image_nonempty
protected theorem Nonempty.image (h : s.Nonempty) (f : α → β) : (s.image f).Nonempty :=
image_nonempty.2 h
#align finset.nonempty.image Finset.Nonempty.image
alias ⟨Nonempty.of_image, _⟩ := image_nonempty
@[deprecated image_nonempty (since := "2023-12-29")]
theorem Nonempty.image_iff (f : α → β) : (s.image f).Nonempty ↔ s.Nonempty :=
image_nonempty
theorem image_toFinset [DecidableEq α] {s : Multiset α} :
s.toFinset.image f = (s.map f).toFinset :=
ext fun _ => by simp only [mem_image, Multiset.mem_toFinset, exists_prop, Multiset.mem_map]
#align finset.image_to_finset Finset.image_toFinset
theorem image_val_of_injOn (H : Set.InjOn f s) : (image f s).1 = s.1.map f :=
(s.2.map_on H).dedup
#align finset.image_val_of_inj_on Finset.image_val_of_injOn
@[simp]
theorem image_id [DecidableEq α] : s.image id = s :=
ext fun _ => by simp only [mem_image, exists_prop, id, exists_eq_right]
#align finset.image_id Finset.image_id
@[simp]
theorem image_id' [DecidableEq α] : (s.image fun x => x) = s :=
image_id
#align finset.image_id' Finset.image_id'
theorem image_image [DecidableEq γ] {g : β → γ} : (s.image f).image g = s.image (g ∘ f) :=
eq_of_veq <| by simp only [image_val, dedup_map_dedup_eq, Multiset.map_map]
#align finset.image_image Finset.image_image
theorem image_comm {β'} [DecidableEq β'] [DecidableEq γ] {f : β → γ} {g : α → β} {f' : α → β'}
{g' : β' → γ} (h_comm : ∀ a, f (g a) = g' (f' a)) :
(s.image g).image f = (s.image f').image g' := by simp_rw [image_image, comp, h_comm]
#align finset.image_comm Finset.image_comm
theorem _root_.Function.Semiconj.finset_image [DecidableEq α] {f : α → β} {ga : α → α} {gb : β → β}
(h : Function.Semiconj f ga gb) : Function.Semiconj (image f) (image ga) (image gb) := fun _ =>
image_comm h
#align function.semiconj.finset_image Function.Semiconj.finset_image
theorem _root_.Function.Commute.finset_image [DecidableEq α] {f g : α → α}
(h : Function.Commute f g) : Function.Commute (image f) (image g) :=
Function.Semiconj.finset_image h
#align function.commute.finset_image Function.Commute.finset_image
theorem image_subset_image {s₁ s₂ : Finset α} (h : s₁ ⊆ s₂) : s₁.image f ⊆ s₂.image f := by
simp only [subset_def, image_val, subset_dedup', dedup_subset', Multiset.map_subset_map h]
#align finset.image_subset_image Finset.image_subset_image
theorem image_subset_iff : s.image f ⊆ t ↔ ∀ x ∈ s, f x ∈ t :=
calc
s.image f ⊆ t ↔ f '' ↑s ⊆ ↑t := by norm_cast
_ ↔ _ := Set.image_subset_iff
#align finset.image_subset_iff Finset.image_subset_iff
theorem image_mono (f : α → β) : Monotone (Finset.image f) := fun _ _ => image_subset_image
#align finset.image_mono Finset.image_mono
lemma image_injective (hf : Injective f) : Injective (image f) := by
simpa only [funext (map_eq_image _)] using map_injective ⟨f, hf⟩
lemma image_inj {t : Finset α} (hf : Injective f) : s.image f = t.image f ↔ s = t :=
(image_injective hf).eq_iff
theorem image_subset_image_iff {t : Finset α} (hf : Injective f) :
s.image f ⊆ t.image f ↔ s ⊆ t :=
mod_cast Set.image_subset_image_iff hf (s := s) (t := t)
#align finset.image_subset_image_iff Finset.image_subset_image_iff
lemma image_ssubset_image {t : Finset α} (hf : Injective f) : s.image f ⊂ t.image f ↔ s ⊂ t := by
simp_rw [← lt_iff_ssubset]
exact lt_iff_lt_of_le_iff_le' (image_subset_image_iff hf) (image_subset_image_iff hf)
theorem coe_image_subset_range : ↑(s.image f) ⊆ Set.range f :=
calc
↑(s.image f) = f '' ↑s := coe_image
_ ⊆ Set.range f := Set.image_subset_range f ↑s
#align finset.coe_image_subset_range Finset.coe_image_subset_range
theorem filter_image {p : β → Prop} [DecidablePred p] :
(s.image f).filter p = (s.filter fun a ↦ p (f a)).image f :=
ext fun b => by
simp only [mem_filter, mem_image, exists_prop]
exact
⟨by rintro ⟨⟨x, h1, rfl⟩, h2⟩; exact ⟨x, ⟨h1, h2⟩, rfl⟩,
by rintro ⟨x, ⟨h1, h2⟩, rfl⟩; exact ⟨⟨x, h1, rfl⟩, h2⟩⟩
#align finset.image_filter Finset.filter_image
theorem image_union [DecidableEq α] {f : α → β} (s₁ s₂ : Finset α) :
(s₁ ∪ s₂).image f = s₁.image f ∪ s₂.image f :=
mod_cast Set.image_union f s₁ s₂
#align finset.image_union Finset.image_union
theorem image_inter_subset [DecidableEq α] (f : α → β) (s t : Finset α) :
(s ∩ t).image f ⊆ s.image f ∩ t.image f :=
(image_mono f).map_inf_le s t
#align finset.image_inter_subset Finset.image_inter_subset
theorem image_inter_of_injOn [DecidableEq α] {f : α → β} (s t : Finset α)
(hf : Set.InjOn f (s ∪ t)) : (s ∩ t).image f = s.image f ∩ t.image f :=
coe_injective <| by
push_cast
exact Set.image_inter_on fun a ha b hb => hf (Or.inr ha) <| Or.inl hb
#align finset.image_inter_of_inj_on Finset.image_inter_of_injOn
theorem image_inter [DecidableEq α] (s₁ s₂ : Finset α) (hf : Injective f) :
(s₁ ∩ s₂).image f = s₁.image f ∩ s₂.image f :=
image_inter_of_injOn _ _ hf.injOn
#align finset.image_inter Finset.image_inter
@[simp]
theorem image_singleton (f : α → β) (a : α) : image f {a} = {f a} :=
ext fun x => by simpa only [mem_image, exists_prop, mem_singleton, exists_eq_left] using eq_comm
#align finset.image_singleton Finset.image_singleton
@[simp]
theorem image_insert [DecidableEq α] (f : α → β) (a : α) (s : Finset α) :
(insert a s).image f = insert (f a) (s.image f) := by
simp only [insert_eq, image_singleton, image_union]
#align finset.image_insert Finset.image_insert
theorem erase_image_subset_image_erase [DecidableEq α] (f : α → β) (s : Finset α) (a : α) :
(s.image f).erase (f a) ⊆ (s.erase a).image f := by
simp only [subset_iff, and_imp, exists_prop, mem_image, exists_imp, mem_erase]
rintro b hb x hx rfl
exact ⟨_, ⟨ne_of_apply_ne f hb, hx⟩, rfl⟩
#align finset.erase_image_subset_image_erase Finset.erase_image_subset_image_erase
@[simp]
theorem image_erase [DecidableEq α] {f : α → β} (hf : Injective f) (s : Finset α) (a : α) :
(s.erase a).image f = (s.image f).erase (f a) :=
coe_injective <| by push_cast [Set.image_diff hf, Set.image_singleton]; rfl
#align finset.image_erase Finset.image_erase
@[simp]
theorem image_eq_empty : s.image f = ∅ ↔ s = ∅ := mod_cast Set.image_eq_empty (f := f) (s := s)
#align finset.image_eq_empty Finset.image_eq_empty
theorem image_sdiff [DecidableEq α] {f : α → β} (s t : Finset α) (hf : Injective f) :
(s \ t).image f = s.image f \ t.image f :=
mod_cast Set.image_diff hf s t
#align finset.image_sdiff Finset.image_sdiff
open scoped symmDiff in
theorem image_symmDiff [DecidableEq α] {f : α → β} (s t : Finset α) (hf : Injective f) :
(s ∆ t).image f = s.image f ∆ t.image f :=
mod_cast Set.image_symmDiff hf s t
#align finset.image_symm_diff Finset.image_symmDiff
@[simp]
theorem _root_.Disjoint.of_image_finset {s t : Finset α} {f : α → β}
(h : Disjoint (s.image f) (t.image f)) : Disjoint s t :=
disjoint_iff_ne.2 fun _ ha _ hb =>
ne_of_apply_ne f <| h.forall_ne_finset (mem_image_of_mem _ ha) (mem_image_of_mem _ hb)
#align disjoint.of_image_finset Disjoint.of_image_finset
theorem mem_range_iff_mem_finset_range_of_mod_eq' [DecidableEq α] {f : ℕ → α} {a : α} {n : ℕ}
(hn : 0 < n) (h : ∀ i, f (i % n) = f i) :
a ∈ Set.range f ↔ a ∈ (Finset.range n).image fun i => f i := by
constructor
· rintro ⟨i, hi⟩
simp only [mem_image, exists_prop, mem_range]
exact ⟨i % n, Nat.mod_lt i hn, (rfl.congr hi).mp (h i)⟩
· rintro h
simp only [mem_image, exists_prop, Set.mem_range, mem_range] at *
rcases h with ⟨i, _, ha⟩
exact ⟨i, ha⟩
#align finset.mem_range_iff_mem_finset_range_of_mod_eq' Finset.mem_range_iff_mem_finset_range_of_mod_eq'
theorem mem_range_iff_mem_finset_range_of_mod_eq [DecidableEq α] {f : ℤ → α} {a : α} {n : ℕ}
(hn : 0 < n) (h : ∀ i, f (i % n) = f i) :
a ∈ Set.range f ↔ a ∈ (Finset.range n).image (fun (i : ℕ) => f i) :=
suffices (∃ i, f (i % n) = a) ↔ ∃ i, i < n ∧ f ↑i = a by simpa [h]
have hn' : 0 < (n : ℤ) := Int.ofNat_lt.mpr hn
Iff.intro
(fun ⟨i, hi⟩ =>
have : 0 ≤ i % ↑n := Int.emod_nonneg _ (ne_of_gt hn')
⟨Int.toNat (i % n), by
rw [← Int.ofNat_lt, Int.toNat_of_nonneg this]; exact ⟨Int.emod_lt_of_pos i hn', hi⟩⟩)
fun ⟨i, hi, ha⟩ =>
⟨i, by rw [Int.emod_eq_of_lt (Int.ofNat_zero_le _) (Int.ofNat_lt_ofNat_of_lt hi), ha]⟩
#align finset.mem_range_iff_mem_finset_range_of_mod_eq Finset.mem_range_iff_mem_finset_range_of_mod_eq
theorem range_add (a b : ℕ) : range (a + b) = range a ∪ (range b).map (addLeftEmbedding a) := by
rw [← val_inj, union_val]
exact Multiset.range_add_eq_union a b
#align finset.range_add Finset.range_add
@[simp]
theorem attach_image_val [DecidableEq α] {s : Finset α} : s.attach.image Subtype.val = s :=
eq_of_veq <| by rw [image_val, attach_val, Multiset.attach_map_val, dedup_eq_self]
#align finset.attach_image_val Finset.attach_image_val
#align finset.attach_image_coe Finset.attach_image_val
@[simp]
theorem attach_insert [DecidableEq α] {a : α} {s : Finset α} :
attach (insert a s) =
insert (⟨a, mem_insert_self a s⟩ : { x // x ∈ insert a s })
((attach s).image fun x => ⟨x.1, mem_insert_of_mem x.2⟩) :=
ext fun ⟨x, hx⟩ =>
⟨Or.casesOn (mem_insert.1 hx)
(fun h : x = a => fun _ => mem_insert.2 <| Or.inl <| Subtype.eq h) fun h : x ∈ s => fun _ =>
mem_insert_of_mem <| mem_image.2 <| ⟨⟨x, h⟩, mem_attach _ _, Subtype.eq rfl⟩,
fun _ => Finset.mem_attach _ _⟩
#align finset.attach_insert Finset.attach_insert
@[simp]
theorem disjoint_image {s t : Finset α} {f : α → β} (hf : Injective f) :
Disjoint (s.image f) (t.image f) ↔ Disjoint s t :=
mod_cast Set.disjoint_image_iff hf (s := s) (t := t)
#align finset.disjoint_image Finset.disjoint_image
theorem image_const {s : Finset α} (h : s.Nonempty) (b : β) : (s.image fun _ => b) = singleton b :=
mod_cast Set.Nonempty.image_const (coe_nonempty.2 h) b
#align finset.image_const Finset.image_const
@[simp]
| Mathlib/Data/Finset/Image.lean | 648 | 651 | theorem map_erase [DecidableEq α] (f : α ↪ β) (s : Finset α) (a : α) :
(s.erase a).map f = (s.map f).erase (f a) := by |
simp_rw [map_eq_image]
exact s.image_erase f.2 a
|
/-
Copyright (c) 2020 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou
-/
import Mathlib.Algebra.Group.Pi.Lemmas
import Mathlib.Algebra.Group.Support
#align_import algebra.indicator_function from "leanprover-community/mathlib"@"2445c98ae4b87eabebdde552593519b9b6dc350c"
/-!
# Indicator function
- `Set.indicator (s : Set α) (f : α → β) (a : α)` is `f a` if `a ∈ s` and is `0` otherwise.
- `Set.mulIndicator (s : Set α) (f : α → β) (a : α)` is `f a` if `a ∈ s` and is `1` otherwise.
## Implementation note
In mathematics, an indicator function or a characteristic function is a function
used to indicate membership of an element in a set `s`,
having the value `1` for all elements of `s` and the value `0` otherwise.
But since it is usually used to restrict a function to a certain set `s`,
we let the indicator function take the value `f x` for some function `f`, instead of `1`.
If the usual indicator function is needed, just set `f` to be the constant function `fun _ ↦ 1`.
The indicator function is implemented non-computably, to avoid having to pass around `Decidable`
arguments. This is in contrast with the design of `Pi.single` or `Set.piecewise`.
## Tags
indicator, characteristic
-/
assert_not_exists MonoidWithZero
open Function
variable {α β ι M N : Type*}
namespace Set
section One
variable [One M] [One N] {s t : Set α} {f g : α → M} {a : α}
/-- `Set.mulIndicator s f a` is `f a` if `a ∈ s`, `1` otherwise. -/
@[to_additive "`Set.indicator s f a` is `f a` if `a ∈ s`, `0` otherwise."]
noncomputable def mulIndicator (s : Set α) (f : α → M) (x : α) : M :=
haveI := Classical.decPred (· ∈ s)
if x ∈ s then f x else 1
#align set.mul_indicator Set.mulIndicator
@[to_additive (attr := simp)]
theorem piecewise_eq_mulIndicator [DecidablePred (· ∈ s)] : s.piecewise f 1 = s.mulIndicator f :=
funext fun _ => @if_congr _ _ _ _ (id _) _ _ _ _ Iff.rfl rfl rfl
#align set.piecewise_eq_mul_indicator Set.piecewise_eq_mulIndicator
#align set.piecewise_eq_indicator Set.piecewise_eq_indicator
-- Porting note: needed unfold for mulIndicator
@[to_additive]
theorem mulIndicator_apply (s : Set α) (f : α → M) (a : α) [Decidable (a ∈ s)] :
mulIndicator s f a = if a ∈ s then f a else 1 := by
unfold mulIndicator
congr
#align set.mul_indicator_apply Set.mulIndicator_apply
#align set.indicator_apply Set.indicator_apply
@[to_additive (attr := simp)]
theorem mulIndicator_of_mem (h : a ∈ s) (f : α → M) : mulIndicator s f a = f a :=
if_pos h
#align set.mul_indicator_of_mem Set.mulIndicator_of_mem
#align set.indicator_of_mem Set.indicator_of_mem
@[to_additive (attr := simp)]
theorem mulIndicator_of_not_mem (h : a ∉ s) (f : α → M) : mulIndicator s f a = 1 :=
if_neg h
#align set.mul_indicator_of_not_mem Set.mulIndicator_of_not_mem
#align set.indicator_of_not_mem Set.indicator_of_not_mem
@[to_additive]
theorem mulIndicator_eq_one_or_self (s : Set α) (f : α → M) (a : α) :
mulIndicator s f a = 1 ∨ mulIndicator s f a = f a := by
by_cases h : a ∈ s
· exact Or.inr (mulIndicator_of_mem h f)
· exact Or.inl (mulIndicator_of_not_mem h f)
#align set.mul_indicator_eq_one_or_self Set.mulIndicator_eq_one_or_self
#align set.indicator_eq_zero_or_self Set.indicator_eq_zero_or_self
@[to_additive (attr := simp)]
theorem mulIndicator_apply_eq_self : s.mulIndicator f a = f a ↔ a ∉ s → f a = 1 :=
letI := Classical.dec (a ∈ s)
ite_eq_left_iff.trans (by rw [@eq_comm _ (f a)])
#align set.mul_indicator_apply_eq_self Set.mulIndicator_apply_eq_self
#align set.indicator_apply_eq_self Set.indicator_apply_eq_self
@[to_additive (attr := simp)]
theorem mulIndicator_eq_self : s.mulIndicator f = f ↔ mulSupport f ⊆ s := by
simp only [funext_iff, subset_def, mem_mulSupport, mulIndicator_apply_eq_self, not_imp_comm]
#align set.mul_indicator_eq_self Set.mulIndicator_eq_self
#align set.indicator_eq_self Set.indicator_eq_self
@[to_additive]
theorem mulIndicator_eq_self_of_superset (h1 : s.mulIndicator f = f) (h2 : s ⊆ t) :
t.mulIndicator f = f := by
rw [mulIndicator_eq_self] at h1 ⊢
exact Subset.trans h1 h2
#align set.mul_indicator_eq_self_of_superset Set.mulIndicator_eq_self_of_superset
#align set.indicator_eq_self_of_superset Set.indicator_eq_self_of_superset
@[to_additive (attr := simp)]
theorem mulIndicator_apply_eq_one : mulIndicator s f a = 1 ↔ a ∈ s → f a = 1 :=
letI := Classical.dec (a ∈ s)
ite_eq_right_iff
#align set.mul_indicator_apply_eq_one Set.mulIndicator_apply_eq_one
#align set.indicator_apply_eq_zero Set.indicator_apply_eq_zero
@[to_additive (attr := simp)]
theorem mulIndicator_eq_one : (mulIndicator s f = fun x => 1) ↔ Disjoint (mulSupport f) s := by
simp only [funext_iff, mulIndicator_apply_eq_one, Set.disjoint_left, mem_mulSupport,
not_imp_not]
#align set.mul_indicator_eq_one Set.mulIndicator_eq_one
#align set.indicator_eq_zero Set.indicator_eq_zero
@[to_additive (attr := simp)]
theorem mulIndicator_eq_one' : mulIndicator s f = 1 ↔ Disjoint (mulSupport f) s :=
mulIndicator_eq_one
#align set.mul_indicator_eq_one' Set.mulIndicator_eq_one'
#align set.indicator_eq_zero' Set.indicator_eq_zero'
@[to_additive]
theorem mulIndicator_apply_ne_one {a : α} : s.mulIndicator f a ≠ 1 ↔ a ∈ s ∩ mulSupport f := by
simp only [Ne, mulIndicator_apply_eq_one, Classical.not_imp, mem_inter_iff, mem_mulSupport]
#align set.mul_indicator_apply_ne_one Set.mulIndicator_apply_ne_one
#align set.indicator_apply_ne_zero Set.indicator_apply_ne_zero
@[to_additive (attr := simp)]
theorem mulSupport_mulIndicator :
Function.mulSupport (s.mulIndicator f) = s ∩ Function.mulSupport f :=
ext fun x => by simp [Function.mem_mulSupport, mulIndicator_apply_eq_one]
#align set.mul_support_mul_indicator Set.mulSupport_mulIndicator
#align set.support_indicator Set.support_indicator
/-- If a multiplicative indicator function is not equal to `1` at a point, then that point is in the
set. -/
@[to_additive
"If an additive indicator function is not equal to `0` at a point, then that point is
in the set."]
theorem mem_of_mulIndicator_ne_one (h : mulIndicator s f a ≠ 1) : a ∈ s :=
not_imp_comm.1 (fun hn => mulIndicator_of_not_mem hn f) h
#align set.mem_of_mul_indicator_ne_one Set.mem_of_mulIndicator_ne_one
#align set.mem_of_indicator_ne_zero Set.mem_of_indicator_ne_zero
@[to_additive]
theorem eqOn_mulIndicator : EqOn (mulIndicator s f) f s := fun _ hx => mulIndicator_of_mem hx f
#align set.eq_on_mul_indicator Set.eqOn_mulIndicator
#align set.eq_on_indicator Set.eqOn_indicator
@[to_additive]
theorem mulSupport_mulIndicator_subset : mulSupport (s.mulIndicator f) ⊆ s := fun _ hx =>
hx.imp_symm fun h => mulIndicator_of_not_mem h f
#align set.mul_support_mul_indicator_subset Set.mulSupport_mulIndicator_subset
#align set.support_indicator_subset Set.support_indicator_subset
@[to_additive (attr := simp)]
theorem mulIndicator_mulSupport : mulIndicator (mulSupport f) f = f :=
mulIndicator_eq_self.2 Subset.rfl
#align set.mul_indicator_mul_support Set.mulIndicator_mulSupport
#align set.indicator_support Set.indicator_support
@[to_additive (attr := simp)]
theorem mulIndicator_range_comp {ι : Sort*} (f : ι → α) (g : α → M) :
mulIndicator (range f) g ∘ f = g ∘ f :=
letI := Classical.decPred (· ∈ range f)
piecewise_range_comp _ _ _
#align set.mul_indicator_range_comp Set.mulIndicator_range_comp
#align set.indicator_range_comp Set.indicator_range_comp
@[to_additive]
theorem mulIndicator_congr (h : EqOn f g s) : mulIndicator s f = mulIndicator s g :=
funext fun x => by
simp only [mulIndicator]
split_ifs with h_1
· exact h h_1
rfl
#align set.mul_indicator_congr Set.mulIndicator_congr
#align set.indicator_congr Set.indicator_congr
@[to_additive (attr := simp)]
theorem mulIndicator_univ (f : α → M) : mulIndicator (univ : Set α) f = f :=
mulIndicator_eq_self.2 <| subset_univ _
#align set.mul_indicator_univ Set.mulIndicator_univ
#align set.indicator_univ Set.indicator_univ
@[to_additive (attr := simp)]
theorem mulIndicator_empty (f : α → M) : mulIndicator (∅ : Set α) f = fun _ => 1 :=
mulIndicator_eq_one.2 <| disjoint_empty _
#align set.mul_indicator_empty Set.mulIndicator_empty
#align set.indicator_empty Set.indicator_empty
@[to_additive]
theorem mulIndicator_empty' (f : α → M) : mulIndicator (∅ : Set α) f = 1 :=
mulIndicator_empty f
#align set.mul_indicator_empty' Set.mulIndicator_empty'
#align set.indicator_empty' Set.indicator_empty'
variable (M)
@[to_additive (attr := simp)]
theorem mulIndicator_one (s : Set α) : (mulIndicator s fun _ => (1 : M)) = fun _ => (1 : M) :=
mulIndicator_eq_one.2 <| by simp only [mulSupport_one, empty_disjoint]
#align set.mul_indicator_one Set.mulIndicator_one
#align set.indicator_zero Set.indicator_zero
@[to_additive (attr := simp)]
theorem mulIndicator_one' {s : Set α} : s.mulIndicator (1 : α → M) = 1 :=
mulIndicator_one M s
#align set.mul_indicator_one' Set.mulIndicator_one'
#align set.indicator_zero' Set.indicator_zero'
variable {M}
@[to_additive]
theorem mulIndicator_mulIndicator (s t : Set α) (f : α → M) :
mulIndicator s (mulIndicator t f) = mulIndicator (s ∩ t) f :=
funext fun x => by
simp only [mulIndicator]
split_ifs <;> simp_all (config := { contextual := true })
#align set.mul_indicator_mul_indicator Set.mulIndicator_mulIndicator
#align set.indicator_indicator Set.indicator_indicator
@[to_additive (attr := simp)]
theorem mulIndicator_inter_mulSupport (s : Set α) (f : α → M) :
mulIndicator (s ∩ mulSupport f) f = mulIndicator s f := by
rw [← mulIndicator_mulIndicator, mulIndicator_mulSupport]
#align set.mul_indicator_inter_mul_support Set.mulIndicator_inter_mulSupport
#align set.indicator_inter_support Set.indicator_inter_support
@[to_additive]
theorem comp_mulIndicator (h : M → β) (f : α → M) {s : Set α} {x : α} [DecidablePred (· ∈ s)] :
h (s.mulIndicator f x) = s.piecewise (h ∘ f) (const α (h 1)) x := by
letI := Classical.decPred (· ∈ s)
convert s.apply_piecewise f (const α 1) (fun _ => h) (x := x) using 2
#align set.comp_mul_indicator Set.comp_mulIndicator
#align set.comp_indicator Set.comp_indicator
@[to_additive]
theorem mulIndicator_comp_right {s : Set α} (f : β → α) {g : α → M} {x : β} :
mulIndicator (f ⁻¹' s) (g ∘ f) x = mulIndicator s g (f x) := by
simp only [mulIndicator, Function.comp]
split_ifs with h h' h'' <;> first | rfl | contradiction
#align set.mul_indicator_comp_right Set.mulIndicator_comp_right
#align set.indicator_comp_right Set.indicator_comp_right
@[to_additive]
theorem mulIndicator_image {s : Set α} {f : β → M} {g : α → β} (hg : Injective g) {x : α} :
mulIndicator (g '' s) f (g x) = mulIndicator s (f ∘ g) x := by
rw [← mulIndicator_comp_right, preimage_image_eq _ hg]
#align set.mul_indicator_image Set.mulIndicator_image
#align set.indicator_image Set.indicator_image
@[to_additive]
theorem mulIndicator_comp_of_one {g : M → N} (hg : g 1 = 1) :
mulIndicator s (g ∘ f) = g ∘ mulIndicator s f := by
funext
simp only [mulIndicator]
split_ifs <;> simp [*]
#align set.mul_indicator_comp_of_one Set.mulIndicator_comp_of_one
#align set.indicator_comp_of_zero Set.indicator_comp_of_zero
@[to_additive]
theorem comp_mulIndicator_const (c : M) (f : M → N) (hf : f 1 = 1) :
(fun x => f (s.mulIndicator (fun _ => c) x)) = s.mulIndicator fun _ => f c :=
(mulIndicator_comp_of_one hf).symm
#align set.comp_mul_indicator_const Set.comp_mulIndicator_const
#align set.comp_indicator_const Set.comp_indicator_const
@[to_additive]
theorem mulIndicator_preimage (s : Set α) (f : α → M) (B : Set M) :
mulIndicator s f ⁻¹' B = s.ite (f ⁻¹' B) (1 ⁻¹' B) :=
letI := Classical.decPred (· ∈ s)
piecewise_preimage s f 1 B
#align set.mul_indicator_preimage Set.mulIndicator_preimage
#align set.indicator_preimage Set.indicator_preimage
@[to_additive]
theorem mulIndicator_one_preimage (s : Set M) :
t.mulIndicator 1 ⁻¹' s ∈ ({Set.univ, ∅} : Set (Set α)) := by
classical
rw [mulIndicator_one', preimage_one]
split_ifs <;> simp
#align set.mul_indicator_one_preimage Set.mulIndicator_one_preimage
#align set.indicator_zero_preimage Set.indicator_zero_preimage
@[to_additive]
theorem mulIndicator_const_preimage_eq_union (U : Set α) (s : Set M) (a : M) [Decidable (a ∈ s)]
[Decidable ((1 : M) ∈ s)] : (U.mulIndicator fun _ => a) ⁻¹' s =
(if a ∈ s then U else ∅) ∪ if (1 : M) ∈ s then Uᶜ else ∅ := by
rw [mulIndicator_preimage, preimage_one, preimage_const]
split_ifs <;> simp [← compl_eq_univ_diff]
#align set.mul_indicator_const_preimage_eq_union Set.mulIndicator_const_preimage_eq_union
#align set.indicator_const_preimage_eq_union Set.indicator_const_preimage_eq_union
@[to_additive]
theorem mulIndicator_const_preimage (U : Set α) (s : Set M) (a : M) :
(U.mulIndicator fun _ => a) ⁻¹' s ∈ ({Set.univ, U, Uᶜ, ∅} : Set (Set α)) := by
classical
rw [mulIndicator_const_preimage_eq_union]
split_ifs <;> simp
#align set.mul_indicator_const_preimage Set.mulIndicator_const_preimage
#align set.indicator_const_preimage Set.indicator_const_preimage
theorem indicator_one_preimage [Zero M] (U : Set α) (s : Set M) :
U.indicator 1 ⁻¹' s ∈ ({Set.univ, U, Uᶜ, ∅} : Set (Set α)) :=
indicator_const_preimage _ _ 1
#align set.indicator_one_preimage Set.indicator_one_preimage
@[to_additive]
theorem mulIndicator_preimage_of_not_mem (s : Set α) (f : α → M) {t : Set M} (ht : (1 : M) ∉ t) :
mulIndicator s f ⁻¹' t = f ⁻¹' t ∩ s := by
simp [mulIndicator_preimage, Pi.one_def, Set.preimage_const_of_not_mem ht]
#align set.mul_indicator_preimage_of_not_mem Set.mulIndicator_preimage_of_not_mem
#align set.indicator_preimage_of_not_mem Set.indicator_preimage_of_not_mem
@[to_additive]
theorem mem_range_mulIndicator {r : M} {s : Set α} {f : α → M} :
r ∈ range (mulIndicator s f) ↔ r = 1 ∧ s ≠ univ ∨ r ∈ f '' s := by
simp [mulIndicator, ite_eq_iff, exists_or, eq_univ_iff_forall, and_comm, or_comm,
@eq_comm _ r 1]
#align set.mem_range_mul_indicator Set.mem_range_mulIndicator
#align set.mem_range_indicator Set.mem_range_indicator
@[to_additive]
theorem mulIndicator_rel_mulIndicator {r : M → M → Prop} (h1 : r 1 1) (ha : a ∈ s → r (f a) (g a)) :
r (mulIndicator s f a) (mulIndicator s g a) := by
simp only [mulIndicator]
split_ifs with has
exacts [ha has, h1]
#align set.mul_indicator_rel_mul_indicator Set.mulIndicator_rel_mulIndicator
#align set.indicator_rel_indicator Set.indicator_rel_indicator
end One
section Monoid
variable [MulOneClass M] {s t : Set α} {f g : α → M} {a : α}
@[to_additive]
theorem mulIndicator_union_mul_inter_apply (f : α → M) (s t : Set α) (a : α) :
mulIndicator (s ∪ t) f a * mulIndicator (s ∩ t) f a
= mulIndicator s f a * mulIndicator t f a := by
by_cases hs : a ∈ s <;> by_cases ht : a ∈ t <;> simp [*]
#align set.mul_indicator_union_mul_inter_apply Set.mulIndicator_union_mul_inter_apply
#align set.indicator_union_add_inter_apply Set.indicator_union_add_inter_apply
@[to_additive]
theorem mulIndicator_union_mul_inter (f : α → M) (s t : Set α) :
mulIndicator (s ∪ t) f * mulIndicator (s ∩ t) f = mulIndicator s f * mulIndicator t f :=
funext <| mulIndicator_union_mul_inter_apply f s t
#align set.mul_indicator_union_mul_inter Set.mulIndicator_union_mul_inter
#align set.indicator_union_add_inter Set.indicator_union_add_inter
@[to_additive]
theorem mulIndicator_union_of_not_mem_inter (h : a ∉ s ∩ t) (f : α → M) :
mulIndicator (s ∪ t) f a = mulIndicator s f a * mulIndicator t f a := by
rw [← mulIndicator_union_mul_inter_apply f s t, mulIndicator_of_not_mem h, mul_one]
#align set.mul_indicator_union_of_not_mem_inter Set.mulIndicator_union_of_not_mem_inter
#align set.indicator_union_of_not_mem_inter Set.indicator_union_of_not_mem_inter
@[to_additive]
theorem mulIndicator_union_of_disjoint (h : Disjoint s t) (f : α → M) :
mulIndicator (s ∪ t) f = fun a => mulIndicator s f a * mulIndicator t f a :=
funext fun _ => mulIndicator_union_of_not_mem_inter (fun ha => h.le_bot ha) _
#align set.mul_indicator_union_of_disjoint Set.mulIndicator_union_of_disjoint
#align set.indicator_union_of_disjoint Set.indicator_union_of_disjoint
open scoped symmDiff in
@[to_additive]
theorem mulIndicator_symmDiff (s t : Set α) (f : α → M) :
mulIndicator (s ∆ t) f = mulIndicator (s \ t) f * mulIndicator (t \ s) f :=
mulIndicator_union_of_disjoint (disjoint_sdiff_self_right.mono_left sdiff_le) _
@[to_additive]
theorem mulIndicator_mul (s : Set α) (f g : α → M) :
(mulIndicator s fun a => f a * g a) = fun a => mulIndicator s f a * mulIndicator s g a := by
funext
simp only [mulIndicator]
split_ifs
· rfl
rw [mul_one]
#align set.mul_indicator_mul Set.mulIndicator_mul
#align set.indicator_add Set.indicator_add
@[to_additive]
theorem mulIndicator_mul' (s : Set α) (f g : α → M) :
mulIndicator s (f * g) = mulIndicator s f * mulIndicator s g :=
mulIndicator_mul s f g
#align set.mul_indicator_mul' Set.mulIndicator_mul'
#align set.indicator_add' Set.indicator_add'
@[to_additive (attr := simp)]
theorem mulIndicator_compl_mul_self_apply (s : Set α) (f : α → M) (a : α) :
mulIndicator sᶜ f a * mulIndicator s f a = f a :=
by_cases (fun ha : a ∈ s => by simp [ha]) fun ha => by simp [ha]
#align set.mul_indicator_compl_mul_self_apply Set.mulIndicator_compl_mul_self_apply
#align set.indicator_compl_add_self_apply Set.indicator_compl_add_self_apply
@[to_additive (attr := simp)]
theorem mulIndicator_compl_mul_self (s : Set α) (f : α → M) :
mulIndicator sᶜ f * mulIndicator s f = f :=
funext <| mulIndicator_compl_mul_self_apply s f
#align set.mul_indicator_compl_mul_self Set.mulIndicator_compl_mul_self
#align set.indicator_compl_add_self Set.indicator_compl_add_self
@[to_additive (attr := simp)]
theorem mulIndicator_self_mul_compl_apply (s : Set α) (f : α → M) (a : α) :
mulIndicator s f a * mulIndicator sᶜ f a = f a :=
by_cases (fun ha : a ∈ s => by simp [ha]) fun ha => by simp [ha]
#align set.mul_indicator_self_mul_compl_apply Set.mulIndicator_self_mul_compl_apply
#align set.indicator_self_add_compl_apply Set.indicator_self_add_compl_apply
@[to_additive (attr := simp)]
theorem mulIndicator_self_mul_compl (s : Set α) (f : α → M) :
mulIndicator s f * mulIndicator sᶜ f = f :=
funext <| mulIndicator_self_mul_compl_apply s f
#align set.mul_indicator_self_mul_compl Set.mulIndicator_self_mul_compl
#align set.indicator_self_add_compl Set.indicator_self_add_compl
@[to_additive]
theorem mulIndicator_mul_eq_left {f g : α → M} (h : Disjoint (mulSupport f) (mulSupport g)) :
(mulSupport f).mulIndicator (f * g) = f := by
refine (mulIndicator_congr fun x hx => ?_).trans mulIndicator_mulSupport
have : g x = 1 := nmem_mulSupport.1 (disjoint_left.1 h hx)
rw [Pi.mul_apply, this, mul_one]
#align set.mul_indicator_mul_eq_left Set.mulIndicator_mul_eq_left
#align set.indicator_add_eq_left Set.indicator_add_eq_left
@[to_additive]
theorem mulIndicator_mul_eq_right {f g : α → M} (h : Disjoint (mulSupport f) (mulSupport g)) :
(mulSupport g).mulIndicator (f * g) = g := by
refine (mulIndicator_congr fun x hx => ?_).trans mulIndicator_mulSupport
have : f x = 1 := nmem_mulSupport.1 (disjoint_right.1 h hx)
rw [Pi.mul_apply, this, one_mul]
#align set.mul_indicator_mul_eq_right Set.mulIndicator_mul_eq_right
#align set.indicator_add_eq_right Set.indicator_add_eq_right
@[to_additive]
theorem mulIndicator_mul_compl_eq_piecewise [DecidablePred (· ∈ s)] (f g : α → M) :
s.mulIndicator f * sᶜ.mulIndicator g = s.piecewise f g := by
ext x
by_cases h : x ∈ s
· rw [piecewise_eq_of_mem _ _ _ h, Pi.mul_apply, Set.mulIndicator_of_mem h,
Set.mulIndicator_of_not_mem (Set.not_mem_compl_iff.2 h), mul_one]
· rw [piecewise_eq_of_not_mem _ _ _ h, Pi.mul_apply, Set.mulIndicator_of_not_mem h,
Set.mulIndicator_of_mem (Set.mem_compl h), one_mul]
#align set.mul_indicator_mul_compl_eq_piecewise Set.mulIndicator_mul_compl_eq_piecewise
#align set.indicator_add_compl_eq_piecewise Set.indicator_add_compl_eq_piecewise
/-- `Set.mulIndicator` as a `monoidHom`. -/
@[to_additive "`Set.indicator` as an `addMonoidHom`."]
noncomputable def mulIndicatorHom {α} (M) [MulOneClass M] (s : Set α) : (α → M) →* α → M where
toFun := mulIndicator s
map_one' := mulIndicator_one M s
map_mul' := mulIndicator_mul s
#align set.mul_indicator_hom Set.mulIndicatorHom
#align set.indicator_hom Set.indicatorHom
end Monoid
section Group
variable {G : Type*} [Group G] {s t : Set α} {f g : α → G} {a : α}
@[to_additive]
theorem mulIndicator_inv' (s : Set α) (f : α → G) : mulIndicator s f⁻¹ = (mulIndicator s f)⁻¹ :=
(mulIndicatorHom G s).map_inv f
#align set.mul_indicator_inv' Set.mulIndicator_inv'
#align set.indicator_neg' Set.indicator_neg'
@[to_additive]
theorem mulIndicator_inv (s : Set α) (f : α → G) :
(mulIndicator s fun a => (f a)⁻¹) = fun a => (mulIndicator s f a)⁻¹ :=
mulIndicator_inv' s f
#align set.mul_indicator_inv Set.mulIndicator_inv
#align set.indicator_neg Set.indicator_neg
@[to_additive]
theorem mulIndicator_div (s : Set α) (f g : α → G) :
(mulIndicator s fun a => f a / g a) = fun a => mulIndicator s f a / mulIndicator s g a :=
(mulIndicatorHom G s).map_div f g
#align set.mul_indicator_div Set.mulIndicator_div
#align set.indicator_sub Set.indicator_sub
@[to_additive]
theorem mulIndicator_div' (s : Set α) (f g : α → G) :
mulIndicator s (f / g) = mulIndicator s f / mulIndicator s g :=
mulIndicator_div s f g
#align set.mul_indicator_div' Set.mulIndicator_div'
#align set.indicator_sub' Set.indicator_sub'
@[to_additive indicator_compl']
theorem mulIndicator_compl (s : Set α) (f : α → G) :
mulIndicator sᶜ f = f * (mulIndicator s f)⁻¹ :=
eq_mul_inv_of_mul_eq <| s.mulIndicator_compl_mul_self f
#align set.mul_indicator_compl Set.mulIndicator_compl
#align set.indicator_compl' Set.indicator_compl'
@[to_additive indicator_compl]
| Mathlib/Algebra/Group/Indicator.lean | 508 | 509 | theorem mulIndicator_compl' (s : Set α) (f : α → G) :
mulIndicator sᶜ f = f / mulIndicator s f := by | rw [div_eq_mul_inv, mulIndicator_compl]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Bhavik Mehta, Stuart Presnell
-/
import Mathlib.Data.Nat.Factorial.Basic
import Mathlib.Order.Monotone.Basic
#align_import data.nat.choose.basic from "leanprover-community/mathlib"@"2f3994e1b117b1e1da49bcfb67334f33460c3ce4"
/-!
# Binomial coefficients
This file defines binomial coefficients and proves simple lemmas (i.e. those not
requiring more imports).
## Main definition and results
* `Nat.choose`: binomial coefficients, defined inductively
* `Nat.choose_eq_factorial_div_factorial`: a proof that `choose n k = n! / (k! * (n - k)!)`
* `Nat.choose_symm`: symmetry of binomial coefficients
* `Nat.choose_le_succ_of_lt_half_left`: `choose n k` is increasing for small values of `k`
* `Nat.choose_le_middle`: `choose n r` is maximised when `r` is `n/2`
* `Nat.descFactorial_eq_factorial_mul_choose`: Relates binomial coefficients to the descending
factorial. This is used to prove `Nat.choose_le_pow` and variants. We provide similar statements
for the ascending factorial.
* `Nat.multichoose`: whereas `choose` counts combinations, `multichoose` counts multicombinations.
The fact that this is indeed the correct counting function for multisets is proved in
`Sym.card_sym_eq_multichoose` in `Data.Sym.Card`.
* `Nat.multichoose_eq` : a proof that `multichoose n k = (n + k - 1).choose k`.
This is central to the "stars and bars" technique in informal mathematics, where we switch between
counting multisets of size `k` over an alphabet of size `n` to counting strings of `k` elements
("stars") separated by `n-1` dividers ("bars"). See `Data.Sym.Card` for more detail.
## Tags
binomial coefficient, combination, multicombination, stars and bars
-/
open Nat
namespace Nat
/-- `choose n k` is the number of `k`-element subsets in an `n`-element set. Also known as binomial
coefficients. -/
def choose : ℕ → ℕ → ℕ
| _, 0 => 1
| 0, _ + 1 => 0
| n + 1, k + 1 => choose n k + choose n (k + 1)
#align nat.choose Nat.choose
@[simp]
theorem choose_zero_right (n : ℕ) : choose n 0 = 1 := by cases n <;> rfl
#align nat.choose_zero_right Nat.choose_zero_right
@[simp]
theorem choose_zero_succ (k : ℕ) : choose 0 (succ k) = 0 :=
rfl
#align nat.choose_zero_succ Nat.choose_zero_succ
theorem choose_succ_succ (n k : ℕ) : choose (succ n) (succ k) = choose n k + choose n (succ k) :=
rfl
#align nat.choose_succ_succ Nat.choose_succ_succ
theorem choose_succ_succ' (n k : ℕ) : choose (n + 1) (k + 1) = choose n k + choose n (k + 1) :=
rfl
theorem choose_eq_zero_of_lt : ∀ {n k}, n < k → choose n k = 0
| _, 0, hk => absurd hk (Nat.not_lt_zero _)
| 0, k + 1, _ => choose_zero_succ _
| n + 1, k + 1, hk => by
have hnk : n < k := lt_of_succ_lt_succ hk
have hnk1 : n < k + 1 := lt_of_succ_lt hk
rw [choose_succ_succ, choose_eq_zero_of_lt hnk, choose_eq_zero_of_lt hnk1]
#align nat.choose_eq_zero_of_lt Nat.choose_eq_zero_of_lt
@[simp]
theorem choose_self (n : ℕ) : choose n n = 1 := by
induction n <;> simp [*, choose, choose_eq_zero_of_lt (lt_succ_self _)]
#align nat.choose_self Nat.choose_self
@[simp]
theorem choose_succ_self (n : ℕ) : choose n (succ n) = 0 :=
choose_eq_zero_of_lt (lt_succ_self _)
#align nat.choose_succ_self Nat.choose_succ_self
@[simp]
lemma choose_one_right (n : ℕ) : choose n 1 = n := by induction n <;> simp [*, choose, Nat.add_comm]
#align nat.choose_one_right Nat.choose_one_right
-- The `n+1`-st triangle number is `n` more than the `n`-th triangle number
theorem triangle_succ (n : ℕ) : (n + 1) * (n + 1 - 1) / 2 = n * (n - 1) / 2 + n := by
rw [← add_mul_div_left, Nat.mul_comm 2 n, ← Nat.mul_add, Nat.add_sub_cancel, Nat.mul_comm]
cases n <;> rfl; apply zero_lt_succ
#align nat.triangle_succ Nat.triangle_succ
/-- `choose n 2` is the `n`-th triangle number. -/
theorem choose_two_right (n : ℕ) : choose n 2 = n * (n - 1) / 2 := by
induction' n with n ih
· simp
· rw [triangle_succ n, choose, ih]
simp [Nat.add_comm]
#align nat.choose_two_right Nat.choose_two_right
theorem choose_pos : ∀ {n k}, k ≤ n → 0 < choose n k
| 0, _, hk => by rw [Nat.eq_zero_of_le_zero hk]; decide
| n + 1, 0, _ => by simp
| n + 1, k + 1, hk => Nat.add_pos_left (choose_pos (le_of_succ_le_succ hk)) _
#align nat.choose_pos Nat.choose_pos
theorem choose_eq_zero_iff {n k : ℕ} : n.choose k = 0 ↔ n < k :=
⟨fun h => lt_of_not_ge (mt Nat.choose_pos h.symm.not_lt), Nat.choose_eq_zero_of_lt⟩
#align nat.choose_eq_zero_iff Nat.choose_eq_zero_iff
theorem succ_mul_choose_eq : ∀ n k, succ n * choose n k = choose (succ n) (succ k) * succ k
| 0, 0 => by decide
| 0, k + 1 => by simp [choose]
| n + 1, 0 => by simp [choose, mul_succ, succ_eq_add_one, Nat.add_comm]
| n + 1, k + 1 => by
rw [choose_succ_succ (succ n) (succ k), Nat.add_mul, ← succ_mul_choose_eq n, mul_succ, ←
succ_mul_choose_eq n, Nat.add_right_comm, ← Nat.mul_add, ← choose_succ_succ, ← succ_mul]
#align nat.succ_mul_choose_eq Nat.succ_mul_choose_eq
theorem choose_mul_factorial_mul_factorial : ∀ {n k}, k ≤ n → choose n k * k ! * (n - k)! = n !
| 0, _, hk => by simp [Nat.eq_zero_of_le_zero hk]
| n + 1, 0, _ => by simp
| n + 1, succ k, hk => by
rcases lt_or_eq_of_le hk with hk₁ | hk₁
· have h : choose n k * k.succ ! * (n - k)! = (k + 1) * n ! := by
rw [← choose_mul_factorial_mul_factorial (le_of_succ_le_succ hk)]
simp [factorial_succ, Nat.mul_comm, Nat.mul_left_comm, Nat.mul_assoc]
have h₁ : (n - k)! = (n - k) * (n - k.succ)! := by
rw [← succ_sub_succ, succ_sub (le_of_lt_succ hk₁), factorial_succ]
have h₂ : choose n (succ k) * k.succ ! * ((n - k) * (n - k.succ)!) = (n - k) * n ! := by
rw [← choose_mul_factorial_mul_factorial (le_of_lt_succ hk₁)]
simp [factorial_succ, Nat.mul_comm, Nat.mul_left_comm, Nat.mul_assoc]
have h₃ : k * n ! ≤ n * n ! := Nat.mul_le_mul_right _ (le_of_succ_le_succ hk)
rw [choose_succ_succ, Nat.add_mul, Nat.add_mul, succ_sub_succ, h, h₁, h₂, Nat.add_mul,
Nat.mul_sub_right_distrib, factorial_succ, ← Nat.add_sub_assoc h₃, Nat.add_assoc,
← Nat.add_mul, Nat.add_sub_cancel_left, Nat.add_comm]
· rw [hk₁]; simp [hk₁, Nat.mul_comm, choose, Nat.sub_self]
#align nat.choose_mul_factorial_mul_factorial Nat.choose_mul_factorial_mul_factorial
theorem choose_mul {n k s : ℕ} (hkn : k ≤ n) (hsk : s ≤ k) :
n.choose k * k.choose s = n.choose s * (n - s).choose (k - s) :=
have h : 0 < (n - k)! * (k - s)! * s ! := by apply_rules [factorial_pos, Nat.mul_pos]
Nat.mul_right_cancel h <|
calc
n.choose k * k.choose s * ((n - k)! * (k - s)! * s !) =
n.choose k * (k.choose s * s ! * (k - s)!) * (n - k)! := by
rw [Nat.mul_assoc, Nat.mul_assoc, Nat.mul_assoc, Nat.mul_assoc _ s !, Nat.mul_assoc,
Nat.mul_comm (n - k)!, Nat.mul_comm s !]
_ = n ! := by
rw [choose_mul_factorial_mul_factorial hsk, choose_mul_factorial_mul_factorial hkn]
_ = n.choose s * s ! * ((n - s).choose (k - s) * (k - s)! * (n - s - (k - s))!) := by
rw [choose_mul_factorial_mul_factorial (Nat.sub_le_sub_right hkn _),
choose_mul_factorial_mul_factorial (hsk.trans hkn)]
_ = n.choose s * (n - s).choose (k - s) * ((n - k)! * (k - s)! * s !) := by
rw [Nat.sub_sub_sub_cancel_right hsk, Nat.mul_assoc, Nat.mul_left_comm s !, Nat.mul_assoc,
Nat.mul_comm (k - s)!, Nat.mul_comm s !, Nat.mul_right_comm, ← Nat.mul_assoc]
#align nat.choose_mul Nat.choose_mul
theorem choose_eq_factorial_div_factorial {n k : ℕ} (hk : k ≤ n) :
choose n k = n ! / (k ! * (n - k)!) := by
rw [← choose_mul_factorial_mul_factorial hk, Nat.mul_assoc]
exact (mul_div_left _ (Nat.mul_pos (factorial_pos _) (factorial_pos _))).symm
#align nat.choose_eq_factorial_div_factorial Nat.choose_eq_factorial_div_factorial
theorem add_choose (i j : ℕ) : (i + j).choose j = (i + j)! / (i ! * j !) := by
rw [choose_eq_factorial_div_factorial (Nat.le_add_left j i), Nat.add_sub_cancel_right,
Nat.mul_comm]
#align nat.add_choose Nat.add_choose
| Mathlib/Data/Nat/Choose/Basic.lean | 175 | 178 | theorem add_choose_mul_factorial_mul_factorial (i j : ℕ) :
(i + j).choose j * i ! * j ! = (i + j)! := by |
rw [← choose_mul_factorial_mul_factorial (Nat.le_add_left _ _), Nat.add_sub_cancel_right,
Nat.mul_right_comm]
|
/-
Copyright (c) 2016 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Leonardo de Moura, Mario Carneiro, Yaël Dillies
-/
import Mathlib.Algebra.CharZero.Defs
import Mathlib.Algebra.Group.Pi.Basic
import Mathlib.Algebra.Group.Units
import Mathlib.Algebra.GroupWithZero.NeZero
import Mathlib.Algebra.Order.Group.Defs
import Mathlib.Algebra.Order.GroupWithZero.Unbundled
import Mathlib.Algebra.Order.Monoid.Canonical.Defs
import Mathlib.Algebra.Order.Monoid.NatCast
import Mathlib.Algebra.Order.Monoid.Unbundled.MinMax
import Mathlib.Algebra.Ring.Defs
import Mathlib.Tactic.Tauto
#align_import algebra.order.ring.char_zero from "leanprover-community/mathlib"@"655994e298904d7e5bbd1e18c95defd7b543eb94"
#align_import algebra.order.ring.defs from "leanprover-community/mathlib"@"44e29dbcff83ba7114a464d592b8c3743987c1e5"
/-!
# Ordered rings and semirings
This file develops the basics of ordered (semi)rings.
Each typeclass here comprises
* an algebraic class (`Semiring`, `CommSemiring`, `Ring`, `CommRing`)
* an order class (`PartialOrder`, `LinearOrder`)
* assumptions on how both interact ((strict) monotonicity, canonicity)
For short,
* "`+` respects `≤`" means "monotonicity of addition"
* "`+` respects `<`" means "strict monotonicity of addition"
* "`*` respects `≤`" means "monotonicity of multiplication by a nonnegative number".
* "`*` respects `<`" means "strict monotonicity of multiplication by a positive number".
## Typeclasses
* `OrderedSemiring`: Semiring with a partial order such that `+` and `*` respect `≤`.
* `StrictOrderedSemiring`: Nontrivial semiring with a partial order such that `+` and `*` respects
`<`.
* `OrderedCommSemiring`: Commutative semiring with a partial order such that `+` and `*` respect
`≤`.
* `StrictOrderedCommSemiring`: Nontrivial commutative semiring with a partial order such that `+`
and `*` respect `<`.
* `OrderedRing`: Ring with a partial order such that `+` respects `≤` and `*` respects `<`.
* `OrderedCommRing`: Commutative ring with a partial order such that `+` respects `≤` and
`*` respects `<`.
* `LinearOrderedSemiring`: Nontrivial semiring with a linear order such that `+` respects `≤` and
`*` respects `<`.
* `LinearOrderedCommSemiring`: Nontrivial commutative semiring with a linear order such that `+`
respects `≤` and `*` respects `<`.
* `LinearOrderedRing`: Nontrivial ring with a linear order such that `+` respects `≤` and `*`
respects `<`.
* `LinearOrderedCommRing`: Nontrivial commutative ring with a linear order such that `+` respects
`≤` and `*` respects `<`.
* `CanonicallyOrderedCommSemiring`: Commutative semiring with a partial order such that `+`
respects `≤`, `*` respects `<`, and `a ≤ b ↔ ∃ c, b = a + c`.
## Hierarchy
The hardest part of proving order lemmas might be to figure out the correct generality and its
corresponding typeclass. Here's an attempt at demystifying it. For each typeclass, we list its
immediate predecessors and what conditions are added to each of them.
* `OrderedSemiring`
- `OrderedAddCommMonoid` & multiplication & `*` respects `≤`
- `Semiring` & partial order structure & `+` respects `≤` & `*` respects `≤`
* `StrictOrderedSemiring`
- `OrderedCancelAddCommMonoid` & multiplication & `*` respects `<` & nontriviality
- `OrderedSemiring` & `+` respects `<` & `*` respects `<` & nontriviality
* `OrderedCommSemiring`
- `OrderedSemiring` & commutativity of multiplication
- `CommSemiring` & partial order structure & `+` respects `≤` & `*` respects `<`
* `StrictOrderedCommSemiring`
- `StrictOrderedSemiring` & commutativity of multiplication
- `OrderedCommSemiring` & `+` respects `<` & `*` respects `<` & nontriviality
* `OrderedRing`
- `OrderedSemiring` & additive inverses
- `OrderedAddCommGroup` & multiplication & `*` respects `<`
- `Ring` & partial order structure & `+` respects `≤` & `*` respects `<`
* `StrictOrderedRing`
- `StrictOrderedSemiring` & additive inverses
- `OrderedSemiring` & `+` respects `<` & `*` respects `<` & nontriviality
* `OrderedCommRing`
- `OrderedRing` & commutativity of multiplication
- `OrderedCommSemiring` & additive inverses
- `CommRing` & partial order structure & `+` respects `≤` & `*` respects `<`
* `StrictOrderedCommRing`
- `StrictOrderedCommSemiring` & additive inverses
- `StrictOrderedRing` & commutativity of multiplication
- `OrderedCommRing` & `+` respects `<` & `*` respects `<` & nontriviality
* `LinearOrderedSemiring`
- `StrictOrderedSemiring` & totality of the order
- `LinearOrderedAddCommMonoid` & multiplication & nontriviality & `*` respects `<`
* `LinearOrderedCommSemiring`
- `StrictOrderedCommSemiring` & totality of the order
- `LinearOrderedSemiring` & commutativity of multiplication
* `LinearOrderedRing`
- `StrictOrderedRing` & totality of the order
- `LinearOrderedSemiring` & additive inverses
- `LinearOrderedAddCommGroup` & multiplication & `*` respects `<`
- `Ring` & `IsDomain` & linear order structure
* `LinearOrderedCommRing`
- `StrictOrderedCommRing` & totality of the order
- `LinearOrderedRing` & commutativity of multiplication
- `LinearOrderedCommSemiring` & additive inverses
- `CommRing` & `IsDomain` & linear order structure
-/
open Function
universe u
variable {α : Type u} {β : Type*}
/-! Note that `OrderDual` does not satisfy any of the ordered ring typeclasses due to the
`zero_le_one` field. -/
theorem add_one_le_two_mul [LE α] [Semiring α] [CovariantClass α α (· + ·) (· ≤ ·)] {a : α}
(a1 : 1 ≤ a) : a + 1 ≤ 2 * a :=
calc
a + 1 ≤ a + a := add_le_add_left a1 a
_ = 2 * a := (two_mul _).symm
#align add_one_le_two_mul add_one_le_two_mul
/-- An `OrderedSemiring` is a semiring with a partial order such that addition is monotone and
multiplication by a nonnegative number is monotone. -/
class OrderedSemiring (α : Type u) extends Semiring α, OrderedAddCommMonoid α where
/-- `0 ≤ 1` in any ordered semiring. -/
protected zero_le_one : (0 : α) ≤ 1
/-- In an ordered semiring, we can multiply an inequality `a ≤ b` on the left
by a non-negative element `0 ≤ c` to obtain `c * a ≤ c * b`. -/
protected mul_le_mul_of_nonneg_left : ∀ a b c : α, a ≤ b → 0 ≤ c → c * a ≤ c * b
/-- In an ordered semiring, we can multiply an inequality `a ≤ b` on the right
by a non-negative element `0 ≤ c` to obtain `a * c ≤ b * c`. -/
protected mul_le_mul_of_nonneg_right : ∀ a b c : α, a ≤ b → 0 ≤ c → a * c ≤ b * c
#align ordered_semiring OrderedSemiring
/-- An `OrderedCommSemiring` is a commutative semiring with a partial order such that addition is
monotone and multiplication by a nonnegative number is monotone. -/
class OrderedCommSemiring (α : Type u) extends OrderedSemiring α, CommSemiring α where
mul_le_mul_of_nonneg_right a b c ha hc :=
-- parentheses ensure this generates an `optParam` rather than an `autoParam`
(by simpa only [mul_comm] using mul_le_mul_of_nonneg_left a b c ha hc)
#align ordered_comm_semiring OrderedCommSemiring
/-- An `OrderedRing` is a ring with a partial order such that addition is monotone and
multiplication by a nonnegative number is monotone. -/
class OrderedRing (α : Type u) extends Ring α, OrderedAddCommGroup α where
/-- `0 ≤ 1` in any ordered ring. -/
protected zero_le_one : 0 ≤ (1 : α)
/-- The product of non-negative elements is non-negative. -/
protected mul_nonneg : ∀ a b : α, 0 ≤ a → 0 ≤ b → 0 ≤ a * b
#align ordered_ring OrderedRing
/-- An `OrderedCommRing` is a commutative ring with a partial order such that addition is monotone
and multiplication by a nonnegative number is monotone. -/
class OrderedCommRing (α : Type u) extends OrderedRing α, CommRing α
#align ordered_comm_ring OrderedCommRing
/-- A `StrictOrderedSemiring` is a nontrivial semiring with a partial order such that addition is
strictly monotone and multiplication by a positive number is strictly monotone. -/
class StrictOrderedSemiring (α : Type u) extends Semiring α, OrderedCancelAddCommMonoid α,
Nontrivial α where
/-- In a strict ordered semiring, `0 ≤ 1`. -/
protected zero_le_one : (0 : α) ≤ 1
/-- Left multiplication by a positive element is strictly monotone. -/
protected mul_lt_mul_of_pos_left : ∀ a b c : α, a < b → 0 < c → c * a < c * b
/-- Right multiplication by a positive element is strictly monotone. -/
protected mul_lt_mul_of_pos_right : ∀ a b c : α, a < b → 0 < c → a * c < b * c
#align strict_ordered_semiring StrictOrderedSemiring
/-- A `StrictOrderedCommSemiring` is a commutative semiring with a partial order such that
addition is strictly monotone and multiplication by a positive number is strictly monotone. -/
class StrictOrderedCommSemiring (α : Type u) extends StrictOrderedSemiring α, CommSemiring α
#align strict_ordered_comm_semiring StrictOrderedCommSemiring
/-- A `StrictOrderedRing` is a ring with a partial order such that addition is strictly monotone
and multiplication by a positive number is strictly monotone. -/
class StrictOrderedRing (α : Type u) extends Ring α, OrderedAddCommGroup α, Nontrivial α where
/-- In a strict ordered ring, `0 ≤ 1`. -/
protected zero_le_one : 0 ≤ (1 : α)
/-- The product of two positive elements is positive. -/
protected mul_pos : ∀ a b : α, 0 < a → 0 < b → 0 < a * b
#align strict_ordered_ring StrictOrderedRing
/-- A `StrictOrderedCommRing` is a commutative ring with a partial order such that addition is
strictly monotone and multiplication by a positive number is strictly monotone. -/
class StrictOrderedCommRing (α : Type*) extends StrictOrderedRing α, CommRing α
#align strict_ordered_comm_ring StrictOrderedCommRing
/- It's not entirely clear we should assume `Nontrivial` at this point; it would be reasonable to
explore changing this, but be warned that the instances involving `Domain` may cause typeclass
search loops. -/
/-- A `LinearOrderedSemiring` is a nontrivial semiring with a linear order such that
addition is monotone and multiplication by a positive number is strictly monotone. -/
class LinearOrderedSemiring (α : Type u) extends StrictOrderedSemiring α,
LinearOrderedAddCommMonoid α
#align linear_ordered_semiring LinearOrderedSemiring
/-- A `LinearOrderedCommSemiring` is a nontrivial commutative semiring with a linear order such
that addition is monotone and multiplication by a positive number is strictly monotone. -/
class LinearOrderedCommSemiring (α : Type*) extends StrictOrderedCommSemiring α,
LinearOrderedSemiring α
#align linear_ordered_comm_semiring LinearOrderedCommSemiring
/-- A `LinearOrderedRing` is a ring with a linear order such that addition is monotone and
multiplication by a positive number is strictly monotone. -/
class LinearOrderedRing (α : Type u) extends StrictOrderedRing α, LinearOrder α
#align linear_ordered_ring LinearOrderedRing
/-- A `LinearOrderedCommRing` is a commutative ring with a linear order such that addition is
monotone and multiplication by a positive number is strictly monotone. -/
class LinearOrderedCommRing (α : Type u) extends LinearOrderedRing α, CommMonoid α
#align linear_ordered_comm_ring LinearOrderedCommRing
section OrderedSemiring
variable [OrderedSemiring α] {a b c d : α}
-- see Note [lower instance priority]
instance (priority := 100) OrderedSemiring.zeroLEOneClass : ZeroLEOneClass α :=
{ ‹OrderedSemiring α› with }
#align ordered_semiring.zero_le_one_class OrderedSemiring.zeroLEOneClass
-- see Note [lower instance priority]
instance (priority := 200) OrderedSemiring.toPosMulMono : PosMulMono α :=
⟨fun x _ _ h => OrderedSemiring.mul_le_mul_of_nonneg_left _ _ _ h x.2⟩
#align ordered_semiring.to_pos_mul_mono OrderedSemiring.toPosMulMono
-- see Note [lower instance priority]
instance (priority := 200) OrderedSemiring.toMulPosMono : MulPosMono α :=
⟨fun x _ _ h => OrderedSemiring.mul_le_mul_of_nonneg_right _ _ _ h x.2⟩
#align ordered_semiring.to_mul_pos_mono OrderedSemiring.toMulPosMono
set_option linter.deprecated false in
theorem bit1_mono : Monotone (bit1 : α → α) := fun _ _ h => add_le_add_right (bit0_mono h) _
#align bit1_mono bit1_mono
@[simp]
theorem pow_nonneg (H : 0 ≤ a) : ∀ n : ℕ, 0 ≤ a ^ n
| 0 => by
rw [pow_zero]
exact zero_le_one
| n + 1 => by
rw [pow_succ]
exact mul_nonneg (pow_nonneg H _) H
#align pow_nonneg pow_nonneg
lemma pow_le_pow_of_le_one (ha₀ : 0 ≤ a) (ha₁ : a ≤ 1) : ∀ {m n : ℕ}, m ≤ n → a ^ n ≤ a ^ m
| _, _, Nat.le.refl => le_rfl
| _, _, Nat.le.step h => by
rw [pow_succ']
exact (mul_le_of_le_one_left (pow_nonneg ha₀ _) ha₁).trans $ pow_le_pow_of_le_one ha₀ ha₁ h
#align pow_le_pow_of_le_one pow_le_pow_of_le_one
lemma pow_le_of_le_one (h₀ : 0 ≤ a) (h₁ : a ≤ 1) {n : ℕ} (hn : n ≠ 0) : a ^ n ≤ a :=
(pow_one a).subst (pow_le_pow_of_le_one h₀ h₁ (Nat.pos_of_ne_zero hn))
#align pow_le_of_le_one pow_le_of_le_one
lemma sq_le (h₀ : 0 ≤ a) (h₁ : a ≤ 1) : a ^ 2 ≤ a := pow_le_of_le_one h₀ h₁ two_ne_zero
#align sq_le sq_le
-- Porting note: it's unfortunate we need to write `(@one_le_two α)` here.
theorem add_le_mul_two_add (a2 : 2 ≤ a) (b0 : 0 ≤ b) : a + (2 + b) ≤ a * (2 + b) :=
calc
a + (2 + b) ≤ a + (a + a * b) :=
add_le_add_left (add_le_add a2 <| le_mul_of_one_le_left b0 <| (@one_le_two α).trans a2) a
_ ≤ a * (2 + b) := by rw [mul_add, mul_two, add_assoc]
#align add_le_mul_two_add add_le_mul_two_add
theorem one_le_mul_of_one_le_of_one_le (ha : 1 ≤ a) (hb : 1 ≤ b) : (1 : α) ≤ a * b :=
Left.one_le_mul_of_le_of_le ha hb <| zero_le_one.trans ha
#align one_le_mul_of_one_le_of_one_le one_le_mul_of_one_le_of_one_le
section Monotone
variable [Preorder β] {f g : β → α}
theorem monotone_mul_left_of_nonneg (ha : 0 ≤ a) : Monotone fun x => a * x := fun _ _ h =>
mul_le_mul_of_nonneg_left h ha
#align monotone_mul_left_of_nonneg monotone_mul_left_of_nonneg
theorem monotone_mul_right_of_nonneg (ha : 0 ≤ a) : Monotone fun x => x * a := fun _ _ h =>
mul_le_mul_of_nonneg_right h ha
#align monotone_mul_right_of_nonneg monotone_mul_right_of_nonneg
theorem Monotone.mul_const (hf : Monotone f) (ha : 0 ≤ a) : Monotone fun x => f x * a :=
(monotone_mul_right_of_nonneg ha).comp hf
#align monotone.mul_const Monotone.mul_const
theorem Monotone.const_mul (hf : Monotone f) (ha : 0 ≤ a) : Monotone fun x => a * f x :=
(monotone_mul_left_of_nonneg ha).comp hf
#align monotone.const_mul Monotone.const_mul
theorem Antitone.mul_const (hf : Antitone f) (ha : 0 ≤ a) : Antitone fun x => f x * a :=
(monotone_mul_right_of_nonneg ha).comp_antitone hf
#align antitone.mul_const Antitone.mul_const
theorem Antitone.const_mul (hf : Antitone f) (ha : 0 ≤ a) : Antitone fun x => a * f x :=
(monotone_mul_left_of_nonneg ha).comp_antitone hf
#align antitone.const_mul Antitone.const_mul
theorem Monotone.mul (hf : Monotone f) (hg : Monotone g) (hf₀ : ∀ x, 0 ≤ f x) (hg₀ : ∀ x, 0 ≤ g x) :
Monotone (f * g) := fun _ _ h => mul_le_mul (hf h) (hg h) (hg₀ _) (hf₀ _)
#align monotone.mul Monotone.mul
end Monotone
section
set_option linter.deprecated false
theorem bit1_pos [Nontrivial α] (h : 0 ≤ a) : 0 < bit1 a :=
zero_lt_one.trans_le <| bit1_zero.symm.trans_le <| bit1_mono h
#align bit1_pos bit1_pos
theorem bit1_pos' (h : 0 < a) : 0 < bit1 a := by
nontriviality
exact bit1_pos h.le
#align bit1_pos' bit1_pos'
end
theorem mul_le_one (ha : a ≤ 1) (hb' : 0 ≤ b) (hb : b ≤ 1) : a * b ≤ 1 :=
one_mul (1 : α) ▸ mul_le_mul ha hb hb' zero_le_one
#align mul_le_one mul_le_one
theorem one_lt_mul_of_le_of_lt (ha : 1 ≤ a) (hb : 1 < b) : 1 < a * b :=
hb.trans_le <| le_mul_of_one_le_left (zero_le_one.trans hb.le) ha
#align one_lt_mul_of_le_of_lt one_lt_mul_of_le_of_lt
theorem one_lt_mul_of_lt_of_le (ha : 1 < a) (hb : 1 ≤ b) : 1 < a * b :=
ha.trans_le <| le_mul_of_one_le_right (zero_le_one.trans ha.le) hb
#align one_lt_mul_of_lt_of_le one_lt_mul_of_lt_of_le
alias one_lt_mul := one_lt_mul_of_le_of_lt
#align one_lt_mul one_lt_mul
theorem mul_lt_one_of_nonneg_of_lt_one_left (ha₀ : 0 ≤ a) (ha : a < 1) (hb : b ≤ 1) : a * b < 1 :=
(mul_le_of_le_one_right ha₀ hb).trans_lt ha
#align mul_lt_one_of_nonneg_of_lt_one_left mul_lt_one_of_nonneg_of_lt_one_left
theorem mul_lt_one_of_nonneg_of_lt_one_right (ha : a ≤ 1) (hb₀ : 0 ≤ b) (hb : b < 1) : a * b < 1 :=
(mul_le_of_le_one_left hb₀ ha).trans_lt hb
#align mul_lt_one_of_nonneg_of_lt_one_right mul_lt_one_of_nonneg_of_lt_one_right
variable [ExistsAddOfLE α] [ContravariantClass α α (swap (· + ·)) (· ≤ ·)]
theorem mul_le_mul_of_nonpos_left (h : b ≤ a) (hc : c ≤ 0) : c * a ≤ c * b := by
obtain ⟨d, hcd⟩ := exists_add_of_le hc
refine le_of_add_le_add_right (a := d * b + d * a) ?_
calc
_ = d * b := by rw [add_left_comm, ← add_mul, ← hcd, zero_mul, add_zero]
_ ≤ d * a := mul_le_mul_of_nonneg_left h <| hcd.trans_le <| add_le_of_nonpos_left hc
_ = _ := by rw [← add_assoc, ← add_mul, ← hcd, zero_mul, zero_add]
#align mul_le_mul_of_nonpos_left mul_le_mul_of_nonpos_left
theorem mul_le_mul_of_nonpos_right (h : b ≤ a) (hc : c ≤ 0) : a * c ≤ b * c := by
obtain ⟨d, hcd⟩ := exists_add_of_le hc
refine le_of_add_le_add_right (a := b * d + a * d) ?_
calc
_ = b * d := by rw [add_left_comm, ← mul_add, ← hcd, mul_zero, add_zero]
_ ≤ a * d := mul_le_mul_of_nonneg_right h <| hcd.trans_le <| add_le_of_nonpos_left hc
_ = _ := by rw [← add_assoc, ← mul_add, ← hcd, mul_zero, zero_add]
#align mul_le_mul_of_nonpos_right mul_le_mul_of_nonpos_right
theorem mul_nonneg_of_nonpos_of_nonpos (ha : a ≤ 0) (hb : b ≤ 0) : 0 ≤ a * b := by
simpa only [zero_mul] using mul_le_mul_of_nonpos_right ha hb
#align mul_nonneg_of_nonpos_of_nonpos mul_nonneg_of_nonpos_of_nonpos
theorem mul_le_mul_of_nonneg_of_nonpos (hca : c ≤ a) (hbd : b ≤ d) (hc : 0 ≤ c) (hb : b ≤ 0) :
a * b ≤ c * d :=
(mul_le_mul_of_nonpos_right hca hb).trans <| mul_le_mul_of_nonneg_left hbd hc
#align mul_le_mul_of_nonneg_of_nonpos mul_le_mul_of_nonneg_of_nonpos
theorem mul_le_mul_of_nonneg_of_nonpos' (hca : c ≤ a) (hbd : b ≤ d) (ha : 0 ≤ a) (hd : d ≤ 0) :
a * b ≤ c * d :=
(mul_le_mul_of_nonneg_left hbd ha).trans <| mul_le_mul_of_nonpos_right hca hd
#align mul_le_mul_of_nonneg_of_nonpos' mul_le_mul_of_nonneg_of_nonpos'
theorem mul_le_mul_of_nonpos_of_nonneg (hac : a ≤ c) (hdb : d ≤ b) (hc : c ≤ 0) (hb : 0 ≤ b) :
a * b ≤ c * d :=
(mul_le_mul_of_nonneg_right hac hb).trans <| mul_le_mul_of_nonpos_left hdb hc
#align mul_le_mul_of_nonpos_of_nonneg mul_le_mul_of_nonpos_of_nonneg
theorem mul_le_mul_of_nonpos_of_nonneg' (hca : c ≤ a) (hbd : b ≤ d) (ha : 0 ≤ a) (hd : d ≤ 0) :
a * b ≤ c * d :=
(mul_le_mul_of_nonneg_left hbd ha).trans <| mul_le_mul_of_nonpos_right hca hd
#align mul_le_mul_of_nonpos_of_nonneg' mul_le_mul_of_nonpos_of_nonneg'
theorem mul_le_mul_of_nonpos_of_nonpos (hca : c ≤ a) (hdb : d ≤ b) (hc : c ≤ 0) (hb : b ≤ 0) :
a * b ≤ c * d :=
(mul_le_mul_of_nonpos_right hca hb).trans <| mul_le_mul_of_nonpos_left hdb hc
#align mul_le_mul_of_nonpos_of_nonpos mul_le_mul_of_nonpos_of_nonpos
theorem mul_le_mul_of_nonpos_of_nonpos' (hca : c ≤ a) (hdb : d ≤ b) (ha : a ≤ 0) (hd : d ≤ 0) :
a * b ≤ c * d :=
(mul_le_mul_of_nonpos_left hdb ha).trans <| mul_le_mul_of_nonpos_right hca hd
#align mul_le_mul_of_nonpos_of_nonpos' mul_le_mul_of_nonpos_of_nonpos'
/-- Variant of `mul_le_of_le_one_left` for `b` non-positive instead of non-negative. -/
theorem le_mul_of_le_one_left (hb : b ≤ 0) (h : a ≤ 1) : b ≤ a * b := by
simpa only [one_mul] using mul_le_mul_of_nonpos_right h hb
#align le_mul_of_le_one_left le_mul_of_le_one_left
/-- Variant of `le_mul_of_one_le_left` for `b` non-positive instead of non-negative. -/
theorem mul_le_of_one_le_left (hb : b ≤ 0) (h : 1 ≤ a) : a * b ≤ b := by
simpa only [one_mul] using mul_le_mul_of_nonpos_right h hb
#align mul_le_of_one_le_left mul_le_of_one_le_left
/-- Variant of `mul_le_of_le_one_right` for `a` non-positive instead of non-negative. -/
theorem le_mul_of_le_one_right (ha : a ≤ 0) (h : b ≤ 1) : a ≤ a * b := by
simpa only [mul_one] using mul_le_mul_of_nonpos_left h ha
#align le_mul_of_le_one_right le_mul_of_le_one_right
/-- Variant of `le_mul_of_one_le_right` for `a` non-positive instead of non-negative. -/
theorem mul_le_of_one_le_right (ha : a ≤ 0) (h : 1 ≤ b) : a * b ≤ a := by
simpa only [mul_one] using mul_le_mul_of_nonpos_left h ha
#align mul_le_of_one_le_right mul_le_of_one_le_right
section Monotone
variable [Preorder β] {f g : β → α}
theorem antitone_mul_left {a : α} (ha : a ≤ 0) : Antitone (a * ·) := fun _ _ b_le_c =>
mul_le_mul_of_nonpos_left b_le_c ha
#align antitone_mul_left antitone_mul_left
theorem antitone_mul_right {a : α} (ha : a ≤ 0) : Antitone fun x => x * a := fun _ _ b_le_c =>
mul_le_mul_of_nonpos_right b_le_c ha
#align antitone_mul_right antitone_mul_right
theorem Monotone.const_mul_of_nonpos (hf : Monotone f) (ha : a ≤ 0) : Antitone fun x => a * f x :=
(antitone_mul_left ha).comp_monotone hf
#align monotone.const_mul_of_nonpos Monotone.const_mul_of_nonpos
theorem Monotone.mul_const_of_nonpos (hf : Monotone f) (ha : a ≤ 0) : Antitone fun x => f x * a :=
(antitone_mul_right ha).comp_monotone hf
#align monotone.mul_const_of_nonpos Monotone.mul_const_of_nonpos
theorem Antitone.const_mul_of_nonpos (hf : Antitone f) (ha : a ≤ 0) : Monotone fun x => a * f x :=
(antitone_mul_left ha).comp hf
#align antitone.const_mul_of_nonpos Antitone.const_mul_of_nonpos
theorem Antitone.mul_const_of_nonpos (hf : Antitone f) (ha : a ≤ 0) : Monotone fun x => f x * a :=
(antitone_mul_right ha).comp hf
#align antitone.mul_const_of_nonpos Antitone.mul_const_of_nonpos
theorem Antitone.mul_monotone (hf : Antitone f) (hg : Monotone g) (hf₀ : ∀ x, f x ≤ 0)
(hg₀ : ∀ x, 0 ≤ g x) : Antitone (f * g) := fun _ _ h =>
mul_le_mul_of_nonpos_of_nonneg (hf h) (hg h) (hf₀ _) (hg₀ _)
#align antitone.mul_monotone Antitone.mul_monotone
theorem Monotone.mul_antitone (hf : Monotone f) (hg : Antitone g) (hf₀ : ∀ x, 0 ≤ f x)
(hg₀ : ∀ x, g x ≤ 0) : Antitone (f * g) := fun _ _ h =>
mul_le_mul_of_nonneg_of_nonpos (hf h) (hg h) (hf₀ _) (hg₀ _)
#align monotone.mul_antitone Monotone.mul_antitone
theorem Antitone.mul (hf : Antitone f) (hg : Antitone g) (hf₀ : ∀ x, f x ≤ 0) (hg₀ : ∀ x, g x ≤ 0) :
Monotone (f * g) := fun _ _ h => mul_le_mul_of_nonpos_of_nonpos (hf h) (hg h) (hf₀ _) (hg₀ _)
#align antitone.mul Antitone.mul
end Monotone
variable [ContravariantClass α α (· + ·) (· ≤ ·)]
lemma le_iff_exists_nonneg_add (a b : α) : a ≤ b ↔ ∃ c ≥ 0, b = a + c := by
refine ⟨fun h ↦ ?_, ?_⟩
· obtain ⟨c, rfl⟩ := exists_add_of_le h
exact ⟨c, nonneg_of_le_add_right h, rfl⟩
· rintro ⟨c, hc, rfl⟩
exact le_add_of_nonneg_right hc
#align le_iff_exists_nonneg_add le_iff_exists_nonneg_add
end OrderedSemiring
section OrderedRing
variable [OrderedRing α] {a b c d : α}
-- see Note [lower instance priority]
instance (priority := 100) OrderedRing.toOrderedSemiring : OrderedSemiring α :=
{ ‹OrderedRing α›, (Ring.toSemiring : Semiring α) with
mul_le_mul_of_nonneg_left := fun a b c h hc => by
simpa only [mul_sub, sub_nonneg] using OrderedRing.mul_nonneg _ _ hc (sub_nonneg.2 h),
mul_le_mul_of_nonneg_right := fun a b c h hc => by
simpa only [sub_mul, sub_nonneg] using OrderedRing.mul_nonneg _ _ (sub_nonneg.2 h) hc }
#align ordered_ring.to_ordered_semiring OrderedRing.toOrderedSemiring
end OrderedRing
section OrderedCommRing
variable [OrderedCommRing α]
-- See note [lower instance priority]
instance (priority := 100) OrderedCommRing.toOrderedCommSemiring : OrderedCommSemiring α :=
{ OrderedRing.toOrderedSemiring, ‹OrderedCommRing α› with }
#align ordered_comm_ring.to_ordered_comm_semiring OrderedCommRing.toOrderedCommSemiring
end OrderedCommRing
section StrictOrderedSemiring
variable [StrictOrderedSemiring α] {a b c d : α}
-- see Note [lower instance priority]
instance (priority := 200) StrictOrderedSemiring.toPosMulStrictMono : PosMulStrictMono α :=
⟨fun x _ _ h => StrictOrderedSemiring.mul_lt_mul_of_pos_left _ _ _ h x.prop⟩
#align strict_ordered_semiring.to_pos_mul_strict_mono StrictOrderedSemiring.toPosMulStrictMono
-- see Note [lower instance priority]
instance (priority := 200) StrictOrderedSemiring.toMulPosStrictMono : MulPosStrictMono α :=
⟨fun x _ _ h => StrictOrderedSemiring.mul_lt_mul_of_pos_right _ _ _ h x.prop⟩
#align strict_ordered_semiring.to_mul_pos_strict_mono StrictOrderedSemiring.toMulPosStrictMono
-- See note [reducible non-instances]
/-- A choice-free version of `StrictOrderedSemiring.toOrderedSemiring` to avoid using choice in
basic `Nat` lemmas. -/
abbrev StrictOrderedSemiring.toOrderedSemiring' [@DecidableRel α (· ≤ ·)] : OrderedSemiring α :=
{ ‹StrictOrderedSemiring α› with
mul_le_mul_of_nonneg_left := fun a b c hab hc => by
obtain rfl | hab := Decidable.eq_or_lt_of_le hab
· rfl
obtain rfl | hc := Decidable.eq_or_lt_of_le hc
· simp
· exact (mul_lt_mul_of_pos_left hab hc).le,
mul_le_mul_of_nonneg_right := fun a b c hab hc => by
obtain rfl | hab := Decidable.eq_or_lt_of_le hab
· rfl
obtain rfl | hc := Decidable.eq_or_lt_of_le hc
· simp
· exact (mul_lt_mul_of_pos_right hab hc).le }
#align strict_ordered_semiring.to_ordered_semiring' StrictOrderedSemiring.toOrderedSemiring'
-- see Note [lower instance priority]
instance (priority := 100) StrictOrderedSemiring.toOrderedSemiring : OrderedSemiring α :=
{ ‹StrictOrderedSemiring α› with
mul_le_mul_of_nonneg_left := fun _ _ _ =>
letI := @StrictOrderedSemiring.toOrderedSemiring' α _ (Classical.decRel _)
mul_le_mul_of_nonneg_left,
mul_le_mul_of_nonneg_right := fun _ _ _ =>
letI := @StrictOrderedSemiring.toOrderedSemiring' α _ (Classical.decRel _)
mul_le_mul_of_nonneg_right }
#align strict_ordered_semiring.to_ordered_semiring StrictOrderedSemiring.toOrderedSemiring
-- see Note [lower instance priority]
instance (priority := 100) StrictOrderedSemiring.toCharZero [StrictOrderedSemiring α] :
CharZero α where
cast_injective :=
(strictMono_nat_of_lt_succ fun n ↦ by rw [Nat.cast_succ]; apply lt_add_one).injective
#align strict_ordered_semiring.to_char_zero StrictOrderedSemiring.toCharZero
theorem mul_lt_mul (hac : a < c) (hbd : b ≤ d) (hb : 0 < b) (hc : 0 ≤ c) : a * b < c * d :=
(mul_lt_mul_of_pos_right hac hb).trans_le <| mul_le_mul_of_nonneg_left hbd hc
#align mul_lt_mul mul_lt_mul
theorem mul_lt_mul' (hac : a ≤ c) (hbd : b < d) (hb : 0 ≤ b) (hc : 0 < c) : a * b < c * d :=
(mul_le_mul_of_nonneg_right hac hb).trans_lt <| mul_lt_mul_of_pos_left hbd hc
#align mul_lt_mul' mul_lt_mul'
@[simp]
theorem pow_pos (H : 0 < a) : ∀ n : ℕ, 0 < a ^ n
| 0 => by
nontriviality
rw [pow_zero]
exact zero_lt_one
| n + 1 => by
rw [pow_succ]
exact mul_pos (pow_pos H _) H
#align pow_pos pow_pos
theorem mul_self_lt_mul_self (h1 : 0 ≤ a) (h2 : a < b) : a * a < b * b :=
mul_lt_mul' h2.le h2 h1 <| h1.trans_lt h2
#align mul_self_lt_mul_self mul_self_lt_mul_self
-- In the next lemma, we used to write `Set.Ici 0` instead of `{x | 0 ≤ x}`.
-- As this lemma is not used outside this file,
-- and the import for `Set.Ici` is not otherwise needed until later,
-- we choose not to use it here.
theorem strictMonoOn_mul_self : StrictMonoOn (fun x : α => x * x) { x | 0 ≤ x } :=
fun _ hx _ _ hxy => mul_self_lt_mul_self hx hxy
#align strict_mono_on_mul_self strictMonoOn_mul_self
-- See Note [decidable namespace]
protected theorem Decidable.mul_lt_mul'' [@DecidableRel α (· ≤ ·)] (h1 : a < c) (h2 : b < d)
(h3 : 0 ≤ a) (h4 : 0 ≤ b) : a * b < c * d :=
h4.lt_or_eq_dec.elim (fun b0 => mul_lt_mul h1 h2.le b0 <| h3.trans h1.le) fun b0 => by
rw [← b0, mul_zero]; exact mul_pos (h3.trans_lt h1) (h4.trans_lt h2)
#align decidable.mul_lt_mul'' Decidable.mul_lt_mul''
@[gcongr]
theorem mul_lt_mul'' : a < c → b < d → 0 ≤ a → 0 ≤ b → a * b < c * d := by classical
exact Decidable.mul_lt_mul''
#align mul_lt_mul'' mul_lt_mul''
theorem lt_mul_left (hn : 0 < a) (hm : 1 < b) : a < b * a := by
convert mul_lt_mul_of_pos_right hm hn
rw [one_mul]
#align lt_mul_left lt_mul_left
theorem lt_mul_right (hn : 0 < a) (hm : 1 < b) : a < a * b := by
convert mul_lt_mul_of_pos_left hm hn
rw [mul_one]
#align lt_mul_right lt_mul_right
theorem lt_mul_self (hn : 1 < a) : a < a * a :=
lt_mul_left (hn.trans_le' zero_le_one) hn
#align lt_mul_self lt_mul_self
section Monotone
variable [Preorder β] {f g : β → α}
theorem strictMono_mul_left_of_pos (ha : 0 < a) : StrictMono fun x => a * x := fun _ _ b_lt_c =>
mul_lt_mul_of_pos_left b_lt_c ha
#align strict_mono_mul_left_of_pos strictMono_mul_left_of_pos
theorem strictMono_mul_right_of_pos (ha : 0 < a) : StrictMono fun x => x * a := fun _ _ b_lt_c =>
mul_lt_mul_of_pos_right b_lt_c ha
#align strict_mono_mul_right_of_pos strictMono_mul_right_of_pos
theorem StrictMono.mul_const (hf : StrictMono f) (ha : 0 < a) : StrictMono fun x => f x * a :=
(strictMono_mul_right_of_pos ha).comp hf
#align strict_mono.mul_const StrictMono.mul_const
theorem StrictMono.const_mul (hf : StrictMono f) (ha : 0 < a) : StrictMono fun x => a * f x :=
(strictMono_mul_left_of_pos ha).comp hf
#align strict_mono.const_mul StrictMono.const_mul
theorem StrictAnti.mul_const (hf : StrictAnti f) (ha : 0 < a) : StrictAnti fun x => f x * a :=
(strictMono_mul_right_of_pos ha).comp_strictAnti hf
#align strict_anti.mul_const StrictAnti.mul_const
theorem StrictAnti.const_mul (hf : StrictAnti f) (ha : 0 < a) : StrictAnti fun x => a * f x :=
(strictMono_mul_left_of_pos ha).comp_strictAnti hf
#align strict_anti.const_mul StrictAnti.const_mul
theorem StrictMono.mul_monotone (hf : StrictMono f) (hg : Monotone g) (hf₀ : ∀ x, 0 ≤ f x)
(hg₀ : ∀ x, 0 < g x) : StrictMono (f * g) := fun _ _ h =>
mul_lt_mul (hf h) (hg h.le) (hg₀ _) (hf₀ _)
#align strict_mono.mul_monotone StrictMono.mul_monotone
theorem Monotone.mul_strictMono (hf : Monotone f) (hg : StrictMono g) (hf₀ : ∀ x, 0 < f x)
(hg₀ : ∀ x, 0 ≤ g x) : StrictMono (f * g) := fun _ _ h =>
mul_lt_mul' (hf h.le) (hg h) (hg₀ _) (hf₀ _)
#align monotone.mul_strict_mono Monotone.mul_strictMono
theorem StrictMono.mul (hf : StrictMono f) (hg : StrictMono g) (hf₀ : ∀ x, 0 ≤ f x)
(hg₀ : ∀ x, 0 ≤ g x) : StrictMono (f * g) := fun _ _ h =>
mul_lt_mul'' (hf h) (hg h) (hf₀ _) (hg₀ _)
#align strict_mono.mul StrictMono.mul
end Monotone
theorem lt_two_mul_self (ha : 0 < a) : a < 2 * a :=
lt_mul_of_one_lt_left ha one_lt_two
#align lt_two_mul_self lt_two_mul_self
-- see Note [lower instance priority]
instance (priority := 100) StrictOrderedSemiring.toNoMaxOrder : NoMaxOrder α :=
⟨fun a => ⟨a + 1, lt_add_of_pos_right _ one_pos⟩⟩
#align strict_ordered_semiring.to_no_max_order StrictOrderedSemiring.toNoMaxOrder
variable [ExistsAddOfLE α]
theorem mul_lt_mul_of_neg_left (h : b < a) (hc : c < 0) : c * a < c * b := by
obtain ⟨d, hcd⟩ := exists_add_of_le hc.le
refine (add_lt_add_iff_right (d * b + d * a)).1 ?_
calc
_ = d * b := by rw [add_left_comm, ← add_mul, ← hcd, zero_mul, add_zero]
_ < d * a := mul_lt_mul_of_pos_left h <| hcd.trans_lt <| add_lt_of_neg_left _ hc
_ = _ := by rw [← add_assoc, ← add_mul, ← hcd, zero_mul, zero_add]
#align mul_lt_mul_of_neg_left mul_lt_mul_of_neg_left
theorem mul_lt_mul_of_neg_right (h : b < a) (hc : c < 0) : a * c < b * c := by
obtain ⟨d, hcd⟩ := exists_add_of_le hc.le
refine (add_lt_add_iff_right (b * d + a * d)).1 ?_
calc
_ = b * d := by rw [add_left_comm, ← mul_add, ← hcd, mul_zero, add_zero]
_ < a * d := mul_lt_mul_of_pos_right h <| hcd.trans_lt <| add_lt_of_neg_left _ hc
_ = _ := by rw [← add_assoc, ← mul_add, ← hcd, mul_zero, zero_add]
#align mul_lt_mul_of_neg_right mul_lt_mul_of_neg_right
theorem mul_pos_of_neg_of_neg {a b : α} (ha : a < 0) (hb : b < 0) : 0 < a * b := by
simpa only [zero_mul] using mul_lt_mul_of_neg_right ha hb
#align mul_pos_of_neg_of_neg mul_pos_of_neg_of_neg
/-- Variant of `mul_lt_of_lt_one_left` for `b` negative instead of positive. -/
theorem lt_mul_of_lt_one_left (hb : b < 0) (h : a < 1) : b < a * b := by
simpa only [one_mul] using mul_lt_mul_of_neg_right h hb
#align lt_mul_of_lt_one_left lt_mul_of_lt_one_left
/-- Variant of `lt_mul_of_one_lt_left` for `b` negative instead of positive. -/
theorem mul_lt_of_one_lt_left (hb : b < 0) (h : 1 < a) : a * b < b := by
simpa only [one_mul] using mul_lt_mul_of_neg_right h hb
#align mul_lt_of_one_lt_left mul_lt_of_one_lt_left
/-- Variant of `mul_lt_of_lt_one_right` for `a` negative instead of positive. -/
theorem lt_mul_of_lt_one_right (ha : a < 0) (h : b < 1) : a < a * b := by
simpa only [mul_one] using mul_lt_mul_of_neg_left h ha
#align lt_mul_of_lt_one_right lt_mul_of_lt_one_right
/-- Variant of `lt_mul_of_lt_one_right` for `a` negative instead of positive. -/
theorem mul_lt_of_one_lt_right (ha : a < 0) (h : 1 < b) : a * b < a := by
simpa only [mul_one] using mul_lt_mul_of_neg_left h ha
#align mul_lt_of_one_lt_right mul_lt_of_one_lt_right
section Monotone
variable [Preorder β] {f g : β → α}
theorem strictAnti_mul_left {a : α} (ha : a < 0) : StrictAnti (a * ·) := fun _ _ b_lt_c =>
mul_lt_mul_of_neg_left b_lt_c ha
#align strict_anti_mul_left strictAnti_mul_left
theorem strictAnti_mul_right {a : α} (ha : a < 0) : StrictAnti fun x => x * a := fun _ _ b_lt_c =>
mul_lt_mul_of_neg_right b_lt_c ha
#align strict_anti_mul_right strictAnti_mul_right
theorem StrictMono.const_mul_of_neg (hf : StrictMono f) (ha : a < 0) :
StrictAnti fun x => a * f x :=
(strictAnti_mul_left ha).comp_strictMono hf
#align strict_mono.const_mul_of_neg StrictMono.const_mul_of_neg
theorem StrictMono.mul_const_of_neg (hf : StrictMono f) (ha : a < 0) :
StrictAnti fun x => f x * a :=
(strictAnti_mul_right ha).comp_strictMono hf
#align strict_mono.mul_const_of_neg StrictMono.mul_const_of_neg
theorem StrictAnti.const_mul_of_neg (hf : StrictAnti f) (ha : a < 0) :
StrictMono fun x => a * f x :=
(strictAnti_mul_left ha).comp hf
#align strict_anti.const_mul_of_neg StrictAnti.const_mul_of_neg
theorem StrictAnti.mul_const_of_neg (hf : StrictAnti f) (ha : a < 0) :
StrictMono fun x => f x * a :=
(strictAnti_mul_right ha).comp hf
#align strict_anti.mul_const_of_neg StrictAnti.mul_const_of_neg
end Monotone
/-- Binary **rearrangement inequality**. -/
lemma mul_add_mul_le_mul_add_mul (hab : a ≤ b) (hcd : c ≤ d) : a * d + b * c ≤ a * c + b * d := by
obtain ⟨b, rfl⟩ := exists_add_of_le hab
obtain ⟨d, rfl⟩ := exists_add_of_le hcd
rw [mul_add, add_right_comm, mul_add, ← add_assoc]
exact add_le_add_left (mul_le_mul_of_nonneg_right hab <| (le_add_iff_nonneg_right _).1 hcd) _
#align mul_add_mul_le_mul_add_mul mul_add_mul_le_mul_add_mul
/-- Binary **rearrangement inequality**. -/
lemma mul_add_mul_le_mul_add_mul' (hba : b ≤ a) (hdc : d ≤ c) : a * d + b * c ≤ a * c + b * d := by
rw [add_comm (a * d), add_comm (a * c)]; exact mul_add_mul_le_mul_add_mul hba hdc
#align mul_add_mul_le_mul_add_mul' mul_add_mul_le_mul_add_mul'
/-- Binary strict **rearrangement inequality**. -/
lemma mul_add_mul_lt_mul_add_mul (hab : a < b) (hcd : c < d) : a * d + b * c < a * c + b * d := by
obtain ⟨b, rfl⟩ := exists_add_of_le hab.le
obtain ⟨d, rfl⟩ := exists_add_of_le hcd.le
rw [mul_add, add_right_comm, mul_add, ← add_assoc]
exact add_lt_add_left (mul_lt_mul_of_pos_right hab <| (lt_add_iff_pos_right _).1 hcd) _
#align mul_add_mul_lt_mul_add_mul mul_add_mul_lt_mul_add_mul
/-- Binary **rearrangement inequality**. -/
lemma mul_add_mul_lt_mul_add_mul' (hba : b < a) (hdc : d < c) : a * d + b * c < a * c + b * d := by
rw [add_comm (a * d), add_comm (a * c)]
exact mul_add_mul_lt_mul_add_mul hba hdc
#align mul_add_mul_lt_mul_add_mul' mul_add_mul_lt_mul_add_mul'
end StrictOrderedSemiring
section StrictOrderedCommSemiring
variable [StrictOrderedCommSemiring α]
-- See note [reducible non-instances]
/-- A choice-free version of `StrictOrderedCommSemiring.toOrderedCommSemiring'` to avoid using
choice in basic `Nat` lemmas. -/
abbrev StrictOrderedCommSemiring.toOrderedCommSemiring' [@DecidableRel α (· ≤ ·)] :
OrderedCommSemiring α :=
{ ‹StrictOrderedCommSemiring α›, StrictOrderedSemiring.toOrderedSemiring' with }
#align strict_ordered_comm_semiring.to_ordered_comm_semiring' StrictOrderedCommSemiring.toOrderedCommSemiring'
-- see Note [lower instance priority]
instance (priority := 100) StrictOrderedCommSemiring.toOrderedCommSemiring :
OrderedCommSemiring α :=
{ ‹StrictOrderedCommSemiring α›, StrictOrderedSemiring.toOrderedSemiring with }
#align strict_ordered_comm_semiring.to_ordered_comm_semiring StrictOrderedCommSemiring.toOrderedCommSemiring
end StrictOrderedCommSemiring
section StrictOrderedRing
variable [StrictOrderedRing α] {a b c : α}
-- see Note [lower instance priority]
instance (priority := 100) StrictOrderedRing.toStrictOrderedSemiring : StrictOrderedSemiring α :=
{ ‹StrictOrderedRing α›, (Ring.toSemiring : Semiring α) with
le_of_add_le_add_left := @le_of_add_le_add_left α _ _ _,
mul_lt_mul_of_pos_left := fun a b c h hc => by
simpa only [mul_sub, sub_pos] using StrictOrderedRing.mul_pos _ _ hc (sub_pos.2 h),
mul_lt_mul_of_pos_right := fun a b c h hc => by
simpa only [sub_mul, sub_pos] using StrictOrderedRing.mul_pos _ _ (sub_pos.2 h) hc }
#align strict_ordered_ring.to_strict_ordered_semiring StrictOrderedRing.toStrictOrderedSemiring
-- See note [reducible non-instances]
/-- A choice-free version of `StrictOrderedRing.toOrderedRing` to avoid using choice in basic
`Int` lemmas. -/
abbrev StrictOrderedRing.toOrderedRing' [@DecidableRel α (· ≤ ·)] : OrderedRing α :=
{ ‹StrictOrderedRing α›, (Ring.toSemiring : Semiring α) with
mul_nonneg := fun a b ha hb => by
obtain ha | ha := Decidable.eq_or_lt_of_le ha
· rw [← ha, zero_mul]
obtain hb | hb := Decidable.eq_or_lt_of_le hb
· rw [← hb, mul_zero]
· exact (StrictOrderedRing.mul_pos _ _ ha hb).le }
#align strict_ordered_ring.to_ordered_ring' StrictOrderedRing.toOrderedRing'
-- see Note [lower instance priority]
instance (priority := 100) StrictOrderedRing.toOrderedRing : OrderedRing α where
__ := ‹StrictOrderedRing α›
mul_nonneg := fun _ _ => mul_nonneg
#align strict_ordered_ring.to_ordered_ring StrictOrderedRing.toOrderedRing
end StrictOrderedRing
section StrictOrderedCommRing
variable [StrictOrderedCommRing α]
-- See note [reducible non-instances]
/-- A choice-free version of `StrictOrderedCommRing.toOrderedCommRing` to avoid using
choice in basic `Int` lemmas. -/
abbrev StrictOrderedCommRing.toOrderedCommRing' [@DecidableRel α (· ≤ ·)] : OrderedCommRing α :=
{ ‹StrictOrderedCommRing α›, StrictOrderedRing.toOrderedRing' with }
#align strict_ordered_comm_ring.to_ordered_comm_ring' StrictOrderedCommRing.toOrderedCommRing'
-- See note [lower instance priority]
instance (priority := 100) StrictOrderedCommRing.toStrictOrderedCommSemiring :
StrictOrderedCommSemiring α :=
{ ‹StrictOrderedCommRing α›, StrictOrderedRing.toStrictOrderedSemiring with }
#align strict_ordered_comm_ring.to_strict_ordered_comm_semiring StrictOrderedCommRing.toStrictOrderedCommSemiring
-- See note [lower instance priority]
instance (priority := 100) StrictOrderedCommRing.toOrderedCommRing : OrderedCommRing α :=
{ ‹StrictOrderedCommRing α›, StrictOrderedRing.toOrderedRing with }
#align strict_ordered_comm_ring.to_ordered_comm_ring StrictOrderedCommRing.toOrderedCommRing
end StrictOrderedCommRing
section LinearOrderedSemiring
variable [LinearOrderedSemiring α] {a b c d : α}
-- see Note [lower instance priority]
instance (priority := 200) LinearOrderedSemiring.toPosMulReflectLT : PosMulReflectLT α :=
⟨fun a _ _ => (monotone_mul_left_of_nonneg a.2).reflect_lt⟩
#align linear_ordered_semiring.to_pos_mul_reflect_lt LinearOrderedSemiring.toPosMulReflectLT
-- see Note [lower instance priority]
instance (priority := 200) LinearOrderedSemiring.toMulPosReflectLT : MulPosReflectLT α :=
⟨fun a _ _ => (monotone_mul_right_of_nonneg a.2).reflect_lt⟩
#align linear_ordered_semiring.to_mul_pos_reflect_lt LinearOrderedSemiring.toMulPosReflectLT
attribute [local instance] LinearOrderedSemiring.decidableLE LinearOrderedSemiring.decidableLT
| Mathlib/Algebra/Order/Ring/Defs.lean | 867 | 874 | theorem nonneg_and_nonneg_or_nonpos_and_nonpos_of_mul_nonneg (hab : 0 ≤ a * b) :
0 ≤ a ∧ 0 ≤ b ∨ a ≤ 0 ∧ b ≤ 0 := by |
refine Decidable.or_iff_not_and_not.2 ?_
simp only [not_and, not_le]; intro ab nab; apply not_lt_of_le hab _
rcases lt_trichotomy 0 a with (ha | rfl | ha)
· exact mul_neg_of_pos_of_neg ha (ab ha.le)
· exact ((ab le_rfl).asymm (nab le_rfl)).elim
· exact mul_neg_of_neg_of_pos ha (nab ha.le)
|
/-
Copyright (c) 2019 Reid Barton. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Reid Barton, Johan Commelin, Bhavik Mehta
-/
import Mathlib.CategoryTheory.Equivalence
#align_import category_theory.adjunction.basic from "leanprover-community/mathlib"@"d101e93197bb5f6ea89bd7ba386b7f7dff1f3903"
/-!
# Adjunctions between functors
`F ⊣ G` represents the data of an adjunction between two functors
`F : C ⥤ D` and `G : D ⥤ C`. `F` is the left adjoint and `G` is the right adjoint.
We provide various useful constructors:
* `mkOfHomEquiv`
* `mkOfUnitCounit`
* `leftAdjointOfEquiv` / `rightAdjointOfEquiv`
construct a left/right adjoint of a given functor given the action on objects and
the relevant equivalence of morphism spaces.
* `adjunctionOfEquivLeft` / `adjunctionOfEquivRight` witness that these constructions
give adjunctions.
There are also typeclasses `IsLeftAdjoint` / `IsRightAdjoint`, which asserts the
existence of a adjoint functor. Given `[F.IsLeftAdjoint]`, a chosen right
adjoint can be obtained as `F.rightAdjoint`.
`Adjunction.comp` composes adjunctions.
`toEquivalence` upgrades an adjunction to an equivalence,
given witnesses that the unit and counit are pointwise isomorphisms.
Conversely `Equivalence.toAdjunction` recovers the underlying adjunction from an equivalence.
-/
namespace CategoryTheory
open Category
-- declare the `v`'s first; see `CategoryTheory.Category` for an explanation
universe v₁ v₂ v₃ u₁ u₂ u₃
-- Porting Note: `elab_without_expected_type` cannot be a local attribute
-- attribute [local elab_without_expected_type] whiskerLeft whiskerRight
variable {C : Type u₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₂} D]
/-- `F ⊣ G` represents the data of an adjunction between two functors
`F : C ⥤ D` and `G : D ⥤ C`. `F` is the left adjoint and `G` is the right adjoint.
To construct an `adjunction` between two functors, it's often easier to instead use the
constructors `mkOfHomEquiv` or `mkOfUnitCounit`. To construct a left adjoint,
there are also constructors `leftAdjointOfEquiv` and `adjunctionOfEquivLeft` (as
well as their duals) which can be simpler in practice.
Uniqueness of adjoints is shown in `CategoryTheory.Adjunction.Opposites`.
See <https://stacks.math.columbia.edu/tag/0037>.
-/
structure Adjunction (F : C ⥤ D) (G : D ⥤ C) where
/-- The equivalence between `Hom (F X) Y` and `Hom X (G Y)` coming from an adjunction -/
homEquiv : ∀ X Y, (F.obj X ⟶ Y) ≃ (X ⟶ G.obj Y)
/-- The unit of an adjunction -/
unit : 𝟭 C ⟶ F.comp G
/-- The counit of an adjunction -/
counit : G.comp F ⟶ 𝟭 D
-- Porting note: It's strange that this `Prop` is being flagged by the `docBlame` linter
/-- Naturality of the unit of an adjunction -/
homEquiv_unit : ∀ {X Y f}, (homEquiv X Y) f = (unit : _ ⟶ _).app X ≫ G.map f := by aesop_cat
-- Porting note: It's strange that this `Prop` is being flagged by the `docBlame` linter
/-- Naturality of the counit of an adjunction -/
homEquiv_counit : ∀ {X Y g}, (homEquiv X Y).symm g = F.map g ≫ counit.app Y := by aesop_cat
#align category_theory.adjunction CategoryTheory.Adjunction
#align category_theory.adjunction.hom_equiv CategoryTheory.Adjunction.homEquiv
#align category_theory.adjunction.hom_equiv_unit CategoryTheory.Adjunction.homEquiv_unit
#align category_theory.adjunction.hom_equiv_unit' CategoryTheory.Adjunction.homEquiv_unit
#align category_theory.adjunction.hom_equiv_counit CategoryTheory.Adjunction.homEquiv_counit
#align category_theory.adjunction.hom_equiv_counit' CategoryTheory.Adjunction.homEquiv_counit
/-- The notation `F ⊣ G` stands for `Adjunction F G` representing that `F` is left adjoint to `G` -/
infixl:15 " ⊣ " => Adjunction
namespace Functor
/-- A class asserting the existence of a right adjoint. -/
class IsLeftAdjoint (left : C ⥤ D) : Prop where
exists_rightAdjoint : ∃ (right : D ⥤ C), Nonempty (left ⊣ right)
#align category_theory.is_left_adjoint CategoryTheory.Functor.IsLeftAdjoint
/-- A class asserting the existence of a left adjoint. -/
class IsRightAdjoint (right : D ⥤ C) : Prop where
exists_leftAdjoint : ∃ (left : C ⥤ D), Nonempty (left ⊣ right)
#align category_theory.is_right_adjoint CategoryTheory.Functor.IsRightAdjoint
/-- A chosen left adjoint to a functor that is a right adjoint. -/
noncomputable def leftAdjoint (R : D ⥤ C) [IsRightAdjoint R] : C ⥤ D :=
(IsRightAdjoint.exists_leftAdjoint (right := R)).choose
#align category_theory.left_adjoint CategoryTheory.Functor.leftAdjoint
/-- A chosen right adjoint to a functor that is a left adjoint. -/
noncomputable def rightAdjoint (L : C ⥤ D) [IsLeftAdjoint L] : D ⥤ C :=
(IsLeftAdjoint.exists_rightAdjoint (left := L)).choose
#align category_theory.right_adjoint CategoryTheory.Functor.rightAdjoint
end Functor
/-- The adjunction associated to a functor known to be a left adjoint. -/
noncomputable def Adjunction.ofIsLeftAdjoint (left : C ⥤ D) [left.IsLeftAdjoint] :
left ⊣ left.rightAdjoint :=
Functor.IsLeftAdjoint.exists_rightAdjoint.choose_spec.some
#align category_theory.adjunction.of_left_adjoint CategoryTheory.Adjunction.ofIsLeftAdjoint
/-- The adjunction associated to a functor known to be a right adjoint. -/
noncomputable def Adjunction.ofIsRightAdjoint (right : C ⥤ D) [right.IsRightAdjoint] :
right.leftAdjoint ⊣ right :=
Functor.IsRightAdjoint.exists_leftAdjoint.choose_spec.some
#align category_theory.adjunction.of_right_adjoint CategoryTheory.Adjunction.ofIsRightAdjoint
namespace Adjunction
-- Porting note: Workaround not needed in Lean 4
-- restate_axiom homEquiv_unit'
-- restate_axiom homEquiv_counit'
attribute [simp] homEquiv_unit homEquiv_counit
section
variable {F : C ⥤ D} {G : D ⥤ C} (adj : F ⊣ G)
lemma isLeftAdjoint : F.IsLeftAdjoint := ⟨_, ⟨adj⟩⟩
lemma isRightAdjoint : G.IsRightAdjoint := ⟨_, ⟨adj⟩⟩
instance (R : D ⥤ C) [R.IsRightAdjoint] : R.leftAdjoint.IsLeftAdjoint :=
(ofIsRightAdjoint R).isLeftAdjoint
instance (L : C ⥤ D) [L.IsLeftAdjoint] : L.rightAdjoint.IsRightAdjoint :=
(ofIsLeftAdjoint L).isRightAdjoint
variable {X' X : C} {Y Y' : D}
theorem homEquiv_id (X : C) : adj.homEquiv X _ (𝟙 _) = adj.unit.app X := by simp
#align category_theory.adjunction.hom_equiv_id CategoryTheory.Adjunction.homEquiv_id
theorem homEquiv_symm_id (X : D) : (adj.homEquiv _ X).symm (𝟙 _) = adj.counit.app X := by simp
#align category_theory.adjunction.hom_equiv_symm_id CategoryTheory.Adjunction.homEquiv_symm_id
/-
Porting note: `nolint simpNF` as the linter was complaining that this was provable using `simp`
but it is in fact not. Also the `docBlame` linter expects a docstring even though this is `Prop`
valued
-/
@[simp, nolint simpNF]
theorem homEquiv_naturality_left_symm (f : X' ⟶ X) (g : X ⟶ G.obj Y) :
(adj.homEquiv X' Y).symm (f ≫ g) = F.map f ≫ (adj.homEquiv X Y).symm g := by
rw [homEquiv_counit, F.map_comp, assoc, adj.homEquiv_counit.symm]
#align category_theory.adjunction.hom_equiv_naturality_left_symm CategoryTheory.Adjunction.homEquiv_naturality_left_symm
-- Porting note: Same as above
@[simp, nolint simpNF]
theorem homEquiv_naturality_left (f : X' ⟶ X) (g : F.obj X ⟶ Y) :
(adj.homEquiv X' Y) (F.map f ≫ g) = f ≫ (adj.homEquiv X Y) g := by
rw [← Equiv.eq_symm_apply]
simp only [Equiv.symm_apply_apply,eq_self_iff_true,homEquiv_naturality_left_symm]
#align category_theory.adjunction.hom_equiv_naturality_left CategoryTheory.Adjunction.homEquiv_naturality_left
-- Porting note: Same as above
@[simp, nolint simpNF]
theorem homEquiv_naturality_right (f : F.obj X ⟶ Y) (g : Y ⟶ Y') :
(adj.homEquiv X Y') (f ≫ g) = (adj.homEquiv X Y) f ≫ G.map g := by
rw [homEquiv_unit, G.map_comp, ← assoc, ← homEquiv_unit]
#align category_theory.adjunction.hom_equiv_naturality_right CategoryTheory.Adjunction.homEquiv_naturality_right
-- Porting note: Same as above
@[simp, nolint simpNF]
theorem homEquiv_naturality_right_symm (f : X ⟶ G.obj Y) (g : Y ⟶ Y') :
(adj.homEquiv X Y').symm (f ≫ G.map g) = (adj.homEquiv X Y).symm f ≫ g := by
rw [Equiv.symm_apply_eq]
simp only [homEquiv_naturality_right,eq_self_iff_true,Equiv.apply_symm_apply]
#align category_theory.adjunction.hom_equiv_naturality_right_symm CategoryTheory.Adjunction.homEquiv_naturality_right_symm
@[reassoc]
theorem homEquiv_naturality_left_square (f : X' ⟶ X) (g : F.obj X ⟶ Y')
(h : F.obj X' ⟶ Y) (k : Y ⟶ Y') (w : F.map f ≫ g = h ≫ k) :
f ≫ (adj.homEquiv X Y') g = (adj.homEquiv X' Y) h ≫ G.map k := by
rw [← homEquiv_naturality_left, ← homEquiv_naturality_right, w]
@[reassoc]
theorem homEquiv_naturality_right_square (f : X' ⟶ X) (g : X ⟶ G.obj Y')
(h : X' ⟶ G.obj Y) (k : Y ⟶ Y') (w : f ≫ g = h ≫ G.map k) :
F.map f ≫ (adj.homEquiv X Y').symm g = (adj.homEquiv X' Y).symm h ≫ k := by
rw [← homEquiv_naturality_left_symm, ← homEquiv_naturality_right_symm, w]
theorem homEquiv_naturality_left_square_iff (f : X' ⟶ X) (g : F.obj X ⟶ Y')
(h : F.obj X' ⟶ Y) (k : Y ⟶ Y') :
(f ≫ (adj.homEquiv X Y') g = (adj.homEquiv X' Y) h ≫ G.map k) ↔
(F.map f ≫ g = h ≫ k) :=
⟨fun w ↦ by simpa only [Equiv.symm_apply_apply]
using homEquiv_naturality_right_square adj _ _ _ _ w,
homEquiv_naturality_left_square adj f g h k⟩
theorem homEquiv_naturality_right_square_iff (f : X' ⟶ X) (g : X ⟶ G.obj Y')
(h : X' ⟶ G.obj Y) (k : Y ⟶ Y') :
(F.map f ≫ (adj.homEquiv X Y').symm g = (adj.homEquiv X' Y).symm h ≫ k) ↔
(f ≫ g = h ≫ G.map k) :=
⟨fun w ↦ by simpa only [Equiv.apply_symm_apply]
using homEquiv_naturality_left_square adj _ _ _ _ w,
homEquiv_naturality_right_square adj f g h k⟩
@[simp]
theorem left_triangle : whiskerRight adj.unit F ≫ whiskerLeft F adj.counit = 𝟙 _ := by
ext; dsimp
erw [← adj.homEquiv_counit, Equiv.symm_apply_eq, adj.homEquiv_unit]
simp
#align category_theory.adjunction.left_triangle CategoryTheory.Adjunction.left_triangle
@[simp]
theorem right_triangle : whiskerLeft G adj.unit ≫ whiskerRight adj.counit G = 𝟙 _ := by
ext; dsimp
erw [← adj.homEquiv_unit, ← Equiv.eq_symm_apply, adj.homEquiv_counit]
simp
#align category_theory.adjunction.right_triangle CategoryTheory.Adjunction.right_triangle
variable (X Y)
@[reassoc (attr := simp)]
theorem left_triangle_components :
F.map (adj.unit.app X) ≫ adj.counit.app (F.obj X) = 𝟙 (F.obj X) :=
congr_arg (fun t : NatTrans _ (𝟭 C ⋙ F) => t.app X) adj.left_triangle
#align category_theory.adjunction.left_triangle_components CategoryTheory.Adjunction.left_triangle_components
@[reassoc (attr := simp)]
theorem right_triangle_components :
adj.unit.app (G.obj Y) ≫ G.map (adj.counit.app Y) = 𝟙 (G.obj Y) :=
congr_arg (fun t : NatTrans _ (G ⋙ 𝟭 C) => t.app Y) adj.right_triangle
#align category_theory.adjunction.right_triangle_components CategoryTheory.Adjunction.right_triangle_components
variable {X Y}
@[reassoc (attr := simp)]
theorem counit_naturality {X Y : D} (f : X ⟶ Y) :
F.map (G.map f) ≫ adj.counit.app Y = adj.counit.app X ≫ f :=
adj.counit.naturality f
#align category_theory.adjunction.counit_naturality CategoryTheory.Adjunction.counit_naturality
@[reassoc (attr := simp)]
theorem unit_naturality {X Y : C} (f : X ⟶ Y) :
adj.unit.app X ≫ G.map (F.map f) = f ≫ adj.unit.app Y :=
(adj.unit.naturality f).symm
#align category_theory.adjunction.unit_naturality CategoryTheory.Adjunction.unit_naturality
theorem homEquiv_apply_eq {A : C} {B : D} (f : F.obj A ⟶ B) (g : A ⟶ G.obj B) :
adj.homEquiv A B f = g ↔ f = (adj.homEquiv A B).symm g :=
⟨fun h => by
cases h
simp, fun h => by
cases h
simp⟩
#align category_theory.adjunction.hom_equiv_apply_eq CategoryTheory.Adjunction.homEquiv_apply_eq
theorem eq_homEquiv_apply {A : C} {B : D} (f : F.obj A ⟶ B) (g : A ⟶ G.obj B) :
g = adj.homEquiv A B f ↔ (adj.homEquiv A B).symm g = f :=
⟨fun h => by
cases h
simp, fun h => by
cases h
simp⟩
#align category_theory.adjunction.eq_hom_equiv_apply CategoryTheory.Adjunction.eq_homEquiv_apply
end
end Adjunction
namespace Adjunction
/-- This is an auxiliary data structure useful for constructing adjunctions.
See `Adjunction.mkOfHomEquiv`.
This structure won't typically be used anywhere else.
-/
-- Porting note(#5171): `has_nonempty_instance` linter not ported yet
-- @[nolint has_nonempty_instance]
structure CoreHomEquiv (F : C ⥤ D) (G : D ⥤ C) where
/-- The equivalence between `Hom (F X) Y` and `Hom X (G Y)` -/
homEquiv : ∀ X Y, (F.obj X ⟶ Y) ≃ (X ⟶ G.obj Y)
/-- The property that describes how `homEquiv.symm` transforms compositions `X' ⟶ X ⟶ G Y` -/
homEquiv_naturality_left_symm :
∀ {X' X Y} (f : X' ⟶ X) (g : X ⟶ G.obj Y),
(homEquiv X' Y).symm (f ≫ g) = F.map f ≫ (homEquiv X Y).symm g := by
aesop_cat
/-- The property that describes how `homEquiv` transforms compositions `F X ⟶ Y ⟶ Y'` -/
homEquiv_naturality_right :
∀ {X Y Y'} (f : F.obj X ⟶ Y) (g : Y ⟶ Y'),
(homEquiv X Y') (f ≫ g) = (homEquiv X Y) f ≫ G.map g := by
aesop_cat
#align category_theory.adjunction.core_hom_equiv CategoryTheory.Adjunction.CoreHomEquiv
#align category_theory.adjunction.core_hom_equiv.hom_equiv CategoryTheory.Adjunction.CoreHomEquiv.homEquiv
#align category_theory.adjunction.core_hom_equiv.hom_equiv' CategoryTheory.Adjunction.CoreHomEquiv.homEquiv
#align category_theory.adjunction.core_hom_equiv.hom_equiv_naturality_right CategoryTheory.Adjunction.CoreHomEquiv.homEquiv_naturality_right
#align category_theory.adjunction.core_hom_equiv.hom_equiv_naturality_right' CategoryTheory.Adjunction.CoreHomEquiv.homEquiv_naturality_right
#align category_theory.adjunction.core_hom_equiv.hom_equiv_naturality_left_symm CategoryTheory.Adjunction.CoreHomEquiv.homEquiv_naturality_left_symm
#align category_theory.adjunction.core_hom_equiv.hom_equiv_naturality_left_symm' CategoryTheory.Adjunction.CoreHomEquiv.homEquiv_naturality_left_symm
namespace CoreHomEquiv
-- Porting note: Workaround not needed in Lean 4.
-- restate_axiom homEquiv_naturality_left_symm'
-- restate_axiom homEquiv_naturality_right'
attribute [simp] homEquiv_naturality_left_symm homEquiv_naturality_right
variable {F : C ⥤ D} {G : D ⥤ C} (adj : CoreHomEquiv F G) {X' X : C} {Y Y' : D}
@[simp]
theorem homEquiv_naturality_left_aux (f : X' ⟶ X) (g : F.obj X ⟶ Y) :
(adj.homEquiv X' (F.obj X)) (F.map f) ≫ G.map g = f ≫ (adj.homEquiv X Y) g := by
rw [← homEquiv_naturality_right, ← Equiv.eq_symm_apply]; simp
-- @[simp] -- Porting note: LHS simplifies, added aux lemma above
theorem homEquiv_naturality_left (f : X' ⟶ X) (g : F.obj X ⟶ Y) :
(adj.homEquiv X' Y) (F.map f ≫ g) = f ≫ (adj.homEquiv X Y) g := by
rw [← Equiv.eq_symm_apply]; simp
#align category_theory.adjunction.core_hom_equiv.hom_equiv_naturality_left CategoryTheory.Adjunction.CoreHomEquiv.homEquiv_naturality_left
@[simp]
theorem homEquiv_naturality_right_symm_aux (f : X ⟶ G.obj Y) (g : Y ⟶ Y') :
F.map f ≫ (adj.homEquiv (G.obj Y) Y').symm (G.map g) = (adj.homEquiv X Y).symm f ≫ g := by
rw [← homEquiv_naturality_left_symm, Equiv.symm_apply_eq]; simp
-- @[simp] -- Porting note: LHS simplifies, added aux lemma above
| Mathlib/CategoryTheory/Adjunction/Basic.lean | 334 | 336 | theorem homEquiv_naturality_right_symm (f : X ⟶ G.obj Y) (g : Y ⟶ Y') :
(adj.homEquiv X Y').symm (f ≫ G.map g) = (adj.homEquiv X Y).symm f ≫ g := by |
rw [Equiv.symm_apply_eq]; simp
|
/-
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)
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])
theorem fg_adjoin_of_finite {s : Set A} (hfs : s.Finite) (his : ∀ x ∈ s, IsIntegral R x) :
(Algebra.adjoin R s).toSubmodule.FG :=
Set.Finite.induction_on hfs
(fun _ =>
⟨{1},
Submodule.ext fun x => by
rw [Algebra.adjoin_empty, Finset.coe_singleton, ← one_eq_span, Algebra.toSubmodule_bot]⟩)
(fun {a s} _ _ ih his => by
rw [← Set.union_singleton, Algebra.adjoin_union_coe_submodule]
exact
FG.mul (ih fun i hi => his i <| Set.mem_insert_of_mem a hi)
(his a <| Set.mem_insert a s).fg_adjoin_singleton)
his
#align fg_adjoin_of_finite fg_adjoin_of_finite
theorem isNoetherian_adjoin_finset [IsNoetherianRing R] (s : Finset A)
(hs : ∀ x ∈ s, IsIntegral R x) : IsNoetherian R (Algebra.adjoin R (s : Set A)) :=
isNoetherian_of_fg_of_noetherian _ (fg_adjoin_of_finite s.finite_toSet hs)
#align is_noetherian_adjoin_finset isNoetherian_adjoin_finset
instance Module.End.isIntegral {M : Type*} [AddCommGroup M] [Module R M] [Module.Finite R M] :
Algebra.IsIntegral R (Module.End R M) :=
⟨LinearMap.exists_monic_and_aeval_eq_zero R⟩
#align module.End.is_integral Module.End.isIntegral
variable (R)
theorem IsIntegral.of_finite [Module.Finite R B] (x : B) : IsIntegral R x :=
(isIntegral_algHom_iff (Algebra.lmul R B) Algebra.lmul_injective).mp
(Algebra.IsIntegral.isIntegral _)
variable (B)
instance Algebra.IsIntegral.of_finite [Module.Finite R B] : Algebra.IsIntegral R B :=
⟨.of_finite R⟩
#align algebra.is_integral.of_finite Algebra.IsIntegral.of_finite
variable {R B}
/-- If `S` is a sub-`R`-algebra of `A` and `S` is finitely-generated as an `R`-module,
then all elements of `S` are integral over `R`. -/
theorem IsIntegral.of_mem_of_fg {A} [Ring A] [Algebra R A] (S : Subalgebra R A)
(HS : S.toSubmodule.FG) (x : A) (hx : x ∈ S) : IsIntegral R x :=
have : Module.Finite R S := ⟨(fg_top _).mpr HS⟩
(isIntegral_algHom_iff S.val Subtype.val_injective).mpr (.of_finite R (⟨x, hx⟩ : S))
#align is_integral_of_mem_of_fg IsIntegral.of_mem_of_fg
theorem isIntegral_of_noetherian (_ : IsNoetherian R B) (x : B) : IsIntegral R x :=
.of_finite R x
#align is_integral_of_noetherian isIntegral_of_noetherian
theorem isIntegral_of_submodule_noetherian (S : Subalgebra R B)
(H : IsNoetherian R (Subalgebra.toSubmodule S)) (x : B) (hx : x ∈ S) : IsIntegral R x :=
.of_mem_of_fg _ ((fg_top _).mp <| H.noetherian _) _ hx
#align is_integral_of_submodule_noetherian isIntegral_of_submodule_noetherian
/-- Suppose `A` is an `R`-algebra, `M` is an `A`-module such that `a • m ≠ 0` for all non-zero `a`
and `m`. If `x : A` fixes a nontrivial f.g. `R`-submodule `N` of `M`, then `x` is `R`-integral. -/
theorem isIntegral_of_smul_mem_submodule {M : Type*} [AddCommGroup M] [Module R M] [Module A M]
[IsScalarTower R A M] [NoZeroSMulDivisors A M] (N : Submodule R M) (hN : N ≠ ⊥) (hN' : N.FG)
(x : A) (hx : ∀ n ∈ N, x • n ∈ N) : IsIntegral R x := by
let A' : Subalgebra R A :=
{ carrier := { x | ∀ n ∈ N, x • n ∈ N }
mul_mem' := fun {a b} ha hb n hn => smul_smul a b n ▸ ha _ (hb _ hn)
one_mem' := fun n hn => (one_smul A n).symm ▸ hn
add_mem' := fun {a b} ha hb n hn => (add_smul a b n).symm ▸ N.add_mem (ha _ hn) (hb _ hn)
zero_mem' := fun n _hn => (zero_smul A n).symm ▸ N.zero_mem
algebraMap_mem' := fun r n hn => (algebraMap_smul A r n).symm ▸ N.smul_mem r hn }
let f : A' →ₐ[R] Module.End R N :=
AlgHom.ofLinearMap
{ toFun := fun x => (DistribMulAction.toLinearMap R M x).restrict x.prop
-- Porting note: was
-- `fun x y => LinearMap.ext fun n => Subtype.ext <| add_smul x y n`
map_add' := by intros x y; ext; exact add_smul _ _ _
-- Porting note: was
-- `fun r s => LinearMap.ext fun n => Subtype.ext <| smul_assoc r s n`
map_smul' := by intros r s; ext; apply smul_assoc }
-- Porting note: the next two lines were
--`(LinearMap.ext fun n => Subtype.ext <| one_smul _ _) fun x y =>`
--`LinearMap.ext fun n => Subtype.ext <| mul_smul x y n`
(by ext; apply one_smul)
(by intros x y; ext; apply mul_smul)
obtain ⟨a, ha₁, ha₂⟩ : ∃ a ∈ N, a ≠ (0 : M) := by
by_contra! h'
apply hN
rwa [eq_bot_iff]
have : Function.Injective f := by
show Function.Injective f.toLinearMap
rw [← LinearMap.ker_eq_bot, eq_bot_iff]
intro s hs
have : s.1 • a = 0 := congr_arg Subtype.val (LinearMap.congr_fun hs ⟨a, ha₁⟩)
exact Subtype.ext ((eq_zero_or_eq_zero_of_smul_eq_zero this).resolve_right ha₂)
show IsIntegral R (A'.val ⟨x, hx⟩)
rw [isIntegral_algHom_iff A'.val Subtype.val_injective, ← isIntegral_algHom_iff f this]
haveI : Module.Finite R N := by rwa [Module.finite_def, Submodule.fg_top]
apply Algebra.IsIntegral.isIntegral
#align is_integral_of_smul_mem_submodule isIntegral_of_smul_mem_submodule
variable {f}
theorem RingHom.Finite.to_isIntegral (h : f.Finite) : f.IsIntegral :=
letI := f.toAlgebra
fun _ ↦ IsIntegral.of_mem_of_fg ⊤ h.1 _ trivial
#align ring_hom.finite.to_is_integral RingHom.Finite.to_isIntegral
alias RingHom.IsIntegral.of_finite := RingHom.Finite.to_isIntegral
#align ring_hom.is_integral.of_finite RingHom.IsIntegral.of_finite
/-- The [Kurosh problem](https://en.wikipedia.org/wiki/Kurosh_problem) asks to show that
this is still true when `A` is not necessarily commutative and `R` is a field, but it has
been solved in the negative. See https://arxiv.org/pdf/1706.02383.pdf for criteria for a
finitely generated algebraic (= integral) algebra over a field to be finite dimensional.
This could be an `instance`, but we tend to go from `Module.Finite` to `IsIntegral`/`IsAlgebraic`,
and making it an instance will cause the search to be complicated a lot.
-/
theorem Algebra.IsIntegral.finite [Algebra.IsIntegral R A] [h' : Algebra.FiniteType R A] :
Module.Finite R A :=
have ⟨s, hs⟩ := h'
⟨by apply hs ▸ fg_adjoin_of_finite s.finite_toSet fun x _ ↦ Algebra.IsIntegral.isIntegral x⟩
#align algebra.is_integral.finite Algebra.IsIntegral.finite
/-- finite = integral + finite type -/
theorem Algebra.finite_iff_isIntegral_and_finiteType :
Module.Finite R A ↔ Algebra.IsIntegral R A ∧ Algebra.FiniteType R A :=
⟨fun _ ↦ ⟨⟨.of_finite R⟩, inferInstance⟩, fun ⟨h, _⟩ ↦ h.finite⟩
#align algebra.finite_iff_is_integral_and_finite_type Algebra.finite_iff_isIntegral_and_finiteType
theorem RingHom.IsIntegral.to_finite (h : f.IsIntegral) (h' : f.FiniteType) : f.Finite :=
let _ := f.toAlgebra
let _ : Algebra.IsIntegral R S := ⟨h⟩
Algebra.IsIntegral.finite (h' := h')
#align ring_hom.is_integral.to_finite RingHom.IsIntegral.to_finite
alias RingHom.Finite.of_isIntegral_of_finiteType := RingHom.IsIntegral.to_finite
#align ring_hom.finite.of_is_integral_of_finite_type RingHom.Finite.of_isIntegral_of_finiteType
/-- finite = integral + finite type -/
theorem RingHom.finite_iff_isIntegral_and_finiteType : f.Finite ↔ f.IsIntegral ∧ f.FiniteType :=
⟨fun h ↦ ⟨h.to_isIntegral, h.to_finiteType⟩, fun ⟨h, h'⟩ ↦ h.to_finite h'⟩
#align ring_hom.finite_iff_is_integral_and_finite_type RingHom.finite_iff_isIntegral_and_finiteType
variable (f)
theorem RingHom.IsIntegralElem.of_mem_closure {x y z : S} (hx : f.IsIntegralElem x)
(hy : f.IsIntegralElem y) (hz : z ∈ Subring.closure ({x, y} : Set S)) : f.IsIntegralElem z := by
letI : Algebra R S := f.toAlgebra
have := (IsIntegral.fg_adjoin_singleton hx).mul (IsIntegral.fg_adjoin_singleton hy)
rw [← Algebra.adjoin_union_coe_submodule, Set.singleton_union] at this
exact
IsIntegral.of_mem_of_fg (Algebra.adjoin R {x, y}) this z
(Algebra.mem_adjoin_iff.2 <| Subring.closure_mono Set.subset_union_right hz)
#align ring_hom.is_integral_of_mem_closure RingHom.IsIntegralElem.of_mem_closure
nonrec theorem IsIntegral.of_mem_closure {x y z : A} (hx : IsIntegral R x) (hy : IsIntegral R y)
(hz : z ∈ Subring.closure ({x, y} : Set A)) : IsIntegral R z :=
hx.of_mem_closure (algebraMap R A) hy hz
#align is_integral_of_mem_closure IsIntegral.of_mem_closure
variable (f : R →+* B)
theorem RingHom.isIntegralElem_zero : f.IsIntegralElem 0 :=
f.map_zero ▸ f.isIntegralElem_map
#align ring_hom.is_integral_zero RingHom.isIntegralElem_zero
theorem isIntegral_zero : IsIntegral R (0 : B) :=
(algebraMap R B).isIntegralElem_zero
#align is_integral_zero isIntegral_zero
theorem RingHom.isIntegralElem_one : f.IsIntegralElem 1 :=
f.map_one ▸ f.isIntegralElem_map
#align ring_hom.is_integral_one RingHom.isIntegralElem_one
theorem isIntegral_one : IsIntegral R (1 : B) :=
(algebraMap R B).isIntegralElem_one
#align is_integral_one isIntegral_one
theorem RingHom.IsIntegralElem.add (f : R →+* S) {x y : S}
(hx : f.IsIntegralElem x) (hy : f.IsIntegralElem y) :
f.IsIntegralElem (x + y) :=
hx.of_mem_closure f hy <|
Subring.add_mem _ (Subring.subset_closure (Or.inl rfl)) (Subring.subset_closure (Or.inr rfl))
#align ring_hom.is_integral_add RingHom.IsIntegralElem.add
nonrec theorem IsIntegral.add {x y : A} (hx : IsIntegral R x) (hy : IsIntegral R y) :
IsIntegral R (x + y) :=
hx.add (algebraMap R A) hy
#align is_integral_add IsIntegral.add
variable (f : R →+* S)
-- can be generalized to noncommutative S.
theorem RingHom.IsIntegralElem.neg {x : S} (hx : f.IsIntegralElem x) : f.IsIntegralElem (-x) :=
hx.of_mem_closure f hx (Subring.neg_mem _ (Subring.subset_closure (Or.inl rfl)))
#align ring_hom.is_integral_neg RingHom.IsIntegralElem.neg
theorem IsIntegral.neg {x : B} (hx : IsIntegral R x) : IsIntegral R (-x) :=
.of_mem_of_fg _ hx.fg_adjoin_singleton _ (Subalgebra.neg_mem _ <| Algebra.subset_adjoin rfl)
#align is_integral_neg IsIntegral.neg
theorem RingHom.IsIntegralElem.sub {x y : S} (hx : f.IsIntegralElem x) (hy : f.IsIntegralElem y) :
f.IsIntegralElem (x - y) := by
simpa only [sub_eq_add_neg] using hx.add f (hy.neg f)
#align ring_hom.is_integral_sub RingHom.IsIntegralElem.sub
nonrec theorem IsIntegral.sub {x y : A} (hx : IsIntegral R x) (hy : IsIntegral R y) :
IsIntegral R (x - y) :=
hx.sub (algebraMap R A) hy
#align is_integral_sub IsIntegral.sub
theorem RingHom.IsIntegralElem.mul {x y : S} (hx : f.IsIntegralElem x) (hy : f.IsIntegralElem y) :
f.IsIntegralElem (x * y) :=
hx.of_mem_closure f hy
(Subring.mul_mem _ (Subring.subset_closure (Or.inl rfl)) (Subring.subset_closure (Or.inr rfl)))
#align ring_hom.is_integral_mul RingHom.IsIntegralElem.mul
nonrec theorem IsIntegral.mul {x y : A} (hx : IsIntegral R x) (hy : IsIntegral R y) :
IsIntegral R (x * y) :=
hx.mul (algebraMap R A) hy
#align is_integral_mul IsIntegral.mul
theorem IsIntegral.smul {R} [CommSemiring R] [CommRing S] [Algebra R B] [Algebra S B] [Algebra R S]
[IsScalarTower R S B] {x : B} (r : R)(hx : IsIntegral S x) : IsIntegral S (r • x) :=
.of_mem_of_fg _ hx.fg_adjoin_singleton _ <| by
rw [← algebraMap_smul S]; apply Subalgebra.smul_mem; exact Algebra.subset_adjoin rfl
#align is_integral_smul IsIntegral.smul
theorem IsIntegral.of_pow {x : B} {n : ℕ} (hn : 0 < n) (hx : IsIntegral R <| x ^ n) :
IsIntegral R x := by
rcases hx with ⟨p, hmonic, heval⟩
exact ⟨expand R n p, hmonic.expand hn, by rwa [← aeval_def, expand_aeval]⟩
#align is_integral_of_pow IsIntegral.of_pow
variable (R A)
/-- The integral closure of R in an R-algebra A. -/
def integralClosure : Subalgebra R A where
carrier := { r | IsIntegral R r }
zero_mem' := isIntegral_zero
one_mem' := isIntegral_one
add_mem' := IsIntegral.add
mul_mem' := IsIntegral.mul
algebraMap_mem' _ := isIntegral_algebraMap
#align integral_closure integralClosure
theorem mem_integralClosure_iff_mem_fg {r : A} :
r ∈ integralClosure R A ↔ ∃ M : Subalgebra R A, M.toSubmodule.FG ∧ r ∈ M :=
⟨fun hr =>
⟨Algebra.adjoin R {r}, hr.fg_adjoin_singleton, Algebra.subset_adjoin rfl⟩,
fun ⟨M, Hf, hrM⟩ => .of_mem_of_fg M Hf _ hrM⟩
#align mem_integral_closure_iff_mem_fg mem_integralClosure_iff_mem_fg
variable {R A}
theorem adjoin_le_integralClosure {x : A} (hx : IsIntegral R x) :
Algebra.adjoin R {x} ≤ integralClosure R A := by
rw [Algebra.adjoin_le_iff]
simp only [SetLike.mem_coe, Set.singleton_subset_iff]
exact hx
#align adjoin_le_integral_closure adjoin_le_integralClosure
theorem le_integralClosure_iff_isIntegral {S : Subalgebra R A} :
S ≤ integralClosure R A ↔ Algebra.IsIntegral R S :=
SetLike.forall.symm.trans <|
(forall_congr' fun x =>
show IsIntegral R (algebraMap S A x) ↔ IsIntegral R x from
isIntegral_algebraMap_iff Subtype.coe_injective).trans
Algebra.isIntegral_def.symm
#align le_integral_closure_iff_is_integral le_integralClosure_iff_isIntegral
theorem Algebra.isIntegral_sup {S T : Subalgebra R A} :
Algebra.IsIntegral R (S ⊔ T : Subalgebra R A) ↔
Algebra.IsIntegral R S ∧ Algebra.IsIntegral R T := by
simp only [← le_integralClosure_iff_isIntegral, sup_le_iff]
#align is_integral_sup Algebra.isIntegral_sup
/-- Mapping an integral closure along an `AlgEquiv` gives the integral closure. -/
theorem integralClosure_map_algEquiv [Algebra R S] (f : A ≃ₐ[R] S) :
(integralClosure R A).map (f : A →ₐ[R] S) = integralClosure R S := by
ext y
rw [Subalgebra.mem_map]
constructor
· rintro ⟨x, hx, rfl⟩
exact hx.map f
· intro hy
use f.symm y, hy.map (f.symm : S →ₐ[R] A)
simp
#align integral_closure_map_alg_equiv integralClosure_map_algEquiv
/-- An `AlgHom` between two rings restrict to an `AlgHom` between the integral closures inside
them. -/
def AlgHom.mapIntegralClosure [Algebra R S] (f : A →ₐ[R] S) :
integralClosure R A →ₐ[R] integralClosure R S :=
(f.restrictDomain (integralClosure R A)).codRestrict (integralClosure R S) (fun ⟨_, h⟩ => h.map f)
@[simp]
theorem AlgHom.coe_mapIntegralClosure [Algebra R S] (f : A →ₐ[R] S)
(x : integralClosure R A) : (f.mapIntegralClosure x : S) = f (x : A) := rfl
/-- An `AlgEquiv` between two rings restrict to an `AlgEquiv` between the integral closures inside
them. -/
def AlgEquiv.mapIntegralClosure [Algebra R S] (f : A ≃ₐ[R] S) :
integralClosure R A ≃ₐ[R] integralClosure R S :=
AlgEquiv.ofAlgHom (f : A →ₐ[R] S).mapIntegralClosure (f.symm : S →ₐ[R] A).mapIntegralClosure
(AlgHom.ext fun _ ↦ Subtype.ext (f.right_inv _))
(AlgHom.ext fun _ ↦ Subtype.ext (f.left_inv _))
@[simp]
theorem AlgEquiv.coe_mapIntegralClosure [Algebra R S] (f : A ≃ₐ[R] S)
(x : integralClosure R A) : (f.mapIntegralClosure x : S) = f (x : A) := rfl
theorem integralClosure.isIntegral (x : integralClosure R A) : IsIntegral R x :=
let ⟨p, hpm, hpx⟩ := x.2
⟨p, hpm,
Subtype.eq <| by
rwa [← aeval_def, ← Subalgebra.val_apply, aeval_algHom_apply] at hpx⟩
#align integral_closure.is_integral integralClosure.isIntegral
instance integralClosure.AlgebraIsIntegral : Algebra.IsIntegral R (integralClosure R A) :=
⟨integralClosure.isIntegral⟩
theorem IsIntegral.of_mul_unit {x y : B} {r : R} (hr : algebraMap R B r * y = 1)
(hx : IsIntegral R (x * y)) : IsIntegral R x := by
obtain ⟨p, p_monic, hp⟩ := hx
refine ⟨scaleRoots p r, (monic_scaleRoots_iff r).2 p_monic, ?_⟩
convert scaleRoots_aeval_eq_zero hp
rw [Algebra.commutes] at hr ⊢
rw [mul_assoc, hr, mul_one]; rfl
#align is_integral_of_is_integral_mul_unit IsIntegral.of_mul_unit
theorem RingHom.IsIntegralElem.of_mul_unit (x y : S) (r : R) (hr : f r * y = 1)
(hx : f.IsIntegralElem (x * y)) : f.IsIntegralElem x :=
letI : Algebra R S := f.toAlgebra
IsIntegral.of_mul_unit hr hx
#align ring_hom.is_integral_of_is_integral_mul_unit RingHom.IsIntegralElem.of_mul_unit
/-- Generalization of `IsIntegral.of_mem_closure` bootstrapped up from that lemma -/
theorem IsIntegral.of_mem_closure' (G : Set A) (hG : ∀ x ∈ G, IsIntegral R x) :
∀ x ∈ Subring.closure G, IsIntegral R x := fun _ hx ↦
Subring.closure_induction hx hG isIntegral_zero isIntegral_one (fun _ _ ↦ IsIntegral.add)
(fun _ ↦ IsIntegral.neg) fun _ _ ↦ IsIntegral.mul
#align is_integral_of_mem_closure' IsIntegral.of_mem_closure'
theorem IsIntegral.of_mem_closure'' {S : Type*} [CommRing S] {f : R →+* S} (G : Set S)
(hG : ∀ x ∈ G, f.IsIntegralElem x) : ∀ x ∈ Subring.closure G, f.IsIntegralElem x := fun x hx =>
@IsIntegral.of_mem_closure' R S _ _ f.toAlgebra G hG x hx
#align is_integral_of_mem_closure'' IsIntegral.of_mem_closure''
theorem IsIntegral.pow {x : B} (h : IsIntegral R x) (n : ℕ) : IsIntegral R (x ^ n) :=
.of_mem_of_fg _ h.fg_adjoin_singleton _ <|
Subalgebra.pow_mem _ (by exact Algebra.subset_adjoin rfl) _
#align is_integral.pow IsIntegral.pow
theorem IsIntegral.nsmul {x : B} (h : IsIntegral R x) (n : ℕ) : IsIntegral R (n • x) :=
h.smul n
#align is_integral.nsmul IsIntegral.nsmul
theorem IsIntegral.zsmul {x : B} (h : IsIntegral R x) (n : ℤ) : IsIntegral R (n • x) :=
h.smul n
#align is_integral.zsmul IsIntegral.zsmul
theorem IsIntegral.multiset_prod {s : Multiset A} (h : ∀ x ∈ s, IsIntegral R x) :
IsIntegral R s.prod :=
(integralClosure R A).multiset_prod_mem h
#align is_integral.multiset_prod IsIntegral.multiset_prod
theorem IsIntegral.multiset_sum {s : Multiset A} (h : ∀ x ∈ s, IsIntegral R x) :
IsIntegral R s.sum :=
(integralClosure R A).multiset_sum_mem h
#align is_integral.multiset_sum IsIntegral.multiset_sum
theorem IsIntegral.prod {α : Type*} {s : Finset α} (f : α → A) (h : ∀ x ∈ s, IsIntegral R (f x)) :
IsIntegral R (∏ x ∈ s, f x) :=
(integralClosure R A).prod_mem h
#align is_integral.prod IsIntegral.prod
theorem IsIntegral.sum {α : Type*} {s : Finset α} (f : α → A) (h : ∀ x ∈ s, IsIntegral R (f x)) :
IsIntegral R (∑ x ∈ s, f x) :=
(integralClosure R A).sum_mem h
#align is_integral.sum IsIntegral.sum
theorem IsIntegral.det {n : Type*} [Fintype n] [DecidableEq n] {M : Matrix n n A}
(h : ∀ i j, IsIntegral R (M i j)) : IsIntegral R M.det := by
rw [Matrix.det_apply]
exact IsIntegral.sum _ fun σ _hσ ↦ (IsIntegral.prod _ fun i _hi => h _ _).zsmul _
#align is_integral.det IsIntegral.det
@[simp]
theorem IsIntegral.pow_iff {x : A} {n : ℕ} (hn : 0 < n) : IsIntegral R (x ^ n) ↔ IsIntegral R x :=
⟨IsIntegral.of_pow hn, fun hx ↦ hx.pow n⟩
#align is_integral.pow_iff IsIntegral.pow_iff
open TensorProduct
theorem IsIntegral.tmul (x : A) {y : B} (h : IsIntegral R y) : IsIntegral A (x ⊗ₜ[R] y) := by
rw [← mul_one x, ← smul_eq_mul, ← smul_tmul']
exact smul _ (h.map_of_comp_eq (algebraMap R A)
(Algebra.TensorProduct.includeRight (R := R) (A := A) (B := B)).toRingHom
Algebra.TensorProduct.includeLeftRingHom_comp_algebraMap)
#align is_integral.tmul IsIntegral.tmul
section
variable (p : R[X]) (x : S)
/-- The monic polynomial whose roots are `p.leadingCoeff * x` for roots `x` of `p`. -/
noncomputable def normalizeScaleRoots (p : R[X]) : R[X] :=
∑ i ∈ p.support,
monomial i (if i = p.natDegree then 1 else p.coeff i * p.leadingCoeff ^ (p.natDegree - 1 - i))
#align normalize_scale_roots normalizeScaleRoots
| Mathlib/RingTheory/IntegralClosure.lean | 609 | 620 | theorem normalizeScaleRoots_coeff_mul_leadingCoeff_pow (i : ℕ) (hp : 1 ≤ natDegree p) :
(normalizeScaleRoots p).coeff i * p.leadingCoeff ^ i =
p.coeff i * p.leadingCoeff ^ (p.natDegree - 1) := by |
simp only [normalizeScaleRoots, finset_sum_coeff, coeff_monomial, Finset.sum_ite_eq', one_mul,
zero_mul, mem_support_iff, ite_mul, Ne, ite_not]
split_ifs with h₁ h₂
· simp [h₁]
· rw [h₂, leadingCoeff, ← pow_succ', tsub_add_cancel_of_le hp]
· rw [mul_assoc, ← pow_add, tsub_add_cancel_of_le]
apply Nat.le_sub_one_of_lt
rw [lt_iff_le_and_ne]
exact ⟨le_natDegree_of_ne_zero h₁, h₂⟩
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Floris van Doorn
-/
import Mathlib.Data.Sum.Order
import Mathlib.Order.InitialSeg
import Mathlib.SetTheory.Cardinal.Basic
import Mathlib.Tactic.PPWithUniv
#align_import set_theory.ordinal.basic from "leanprover-community/mathlib"@"8ea5598db6caeddde6cb734aa179cc2408dbd345"
/-!
# Ordinals
Ordinals are defined as equivalences of well-ordered sets under order isomorphism. They are endowed
with a total order, where an ordinal is smaller than another one if it embeds into it as an
initial segment (or, equivalently, in any way). This total order is well founded.
## Main definitions
* `Ordinal`: the type of ordinals (in a given universe)
* `Ordinal.type r`: given a well-founded order `r`, this is the corresponding ordinal
* `Ordinal.typein r a`: given a well-founded order `r` on a type `α`, and `a : α`, the ordinal
corresponding to all elements smaller than `a`.
* `enum r o h`: given a well-order `r` on a type `α`, and an ordinal `o` strictly smaller than
the ordinal corresponding to `r` (this is the assumption `h`), returns the `o`-th element of `α`.
In other words, the elements of `α` can be enumerated using ordinals up to `type r`.
* `Ordinal.card o`: the cardinality of an ordinal `o`.
* `Ordinal.lift` lifts an ordinal in universe `u` to an ordinal in universe `max u v`.
For a version registering additionally that this is an initial segment embedding, see
`Ordinal.lift.initialSeg`.
For a version registering that it is a principal segment embedding if `u < v`, see
`Ordinal.lift.principalSeg`.
* `Ordinal.omega` or `ω` is the order type of `ℕ`. This definition is universe polymorphic:
`Ordinal.omega.{u} : Ordinal.{u}` (contrast with `ℕ : Type`, which lives in a specific
universe). In some cases the universe level has to be given explicitly.
* `o₁ + o₂` is the order on the disjoint union of `o₁` and `o₂` obtained by declaring that
every element of `o₁` is smaller than every element of `o₂`.
The main properties of addition (and the other operations on ordinals) are stated and proved in
`Mathlib/SetTheory/Ordinal/Arithmetic.lean`.
Here, we only introduce it and prove its basic properties to deduce the fact that the order on
ordinals is total (and well founded).
* `succ o` is the successor of the ordinal `o`.
* `Cardinal.ord c`: when `c` is a cardinal, `ord c` is the smallest ordinal with this cardinality.
It is the canonical way to represent a cardinal with an ordinal.
A conditionally complete linear order with bot structure is registered on ordinals, where `⊥` is
`0`, the ordinal corresponding to the empty type, and `Inf` is the minimum for nonempty sets and `0`
for the empty set by convention.
## Notations
* `ω` is a notation for the first infinite ordinal in the locale `Ordinal`.
-/
assert_not_exists Module
assert_not_exists Field
noncomputable section
open Function Cardinal Set Equiv Order
open scoped Classical
open Cardinal InitialSeg
universe u v w
variable {α : Type u} {β : Type*} {γ : Type*} {r : α → α → Prop} {s : β → β → Prop}
{t : γ → γ → Prop}
/-! ### Well order on an arbitrary type -/
section WellOrderingThm
-- Porting note: `parameter` does not work
-- parameter {σ : Type u}
variable {σ : Type u}
open Function
theorem nonempty_embedding_to_cardinal : Nonempty (σ ↪ Cardinal.{u}) :=
(Embedding.total _ _).resolve_left fun ⟨⟨f, hf⟩⟩ =>
let g : σ → Cardinal.{u} := invFun f
let ⟨x, (hx : g x = 2 ^ sum g)⟩ := invFun_surjective hf (2 ^ sum g)
have : g x ≤ sum g := le_sum.{u, u} g x
not_le_of_gt (by rw [hx]; exact cantor _) this
#align nonempty_embedding_to_cardinal nonempty_embedding_to_cardinal
/-- An embedding of any type to the set of cardinals. -/
def embeddingToCardinal : σ ↪ Cardinal.{u} :=
Classical.choice nonempty_embedding_to_cardinal
#align embedding_to_cardinal embeddingToCardinal
/-- Any type can be endowed with a well order, obtained by pulling back the well order over
cardinals by some embedding. -/
def WellOrderingRel : σ → σ → Prop :=
embeddingToCardinal ⁻¹'o (· < ·)
#align well_ordering_rel WellOrderingRel
instance WellOrderingRel.isWellOrder : IsWellOrder σ WellOrderingRel :=
(RelEmbedding.preimage _ _).isWellOrder
#align well_ordering_rel.is_well_order WellOrderingRel.isWellOrder
instance IsWellOrder.subtype_nonempty : Nonempty { r // IsWellOrder σ r } :=
⟨⟨WellOrderingRel, inferInstance⟩⟩
#align is_well_order.subtype_nonempty IsWellOrder.subtype_nonempty
end WellOrderingThm
/-! ### Definition of ordinals -/
/-- Bundled structure registering a well order on a type. Ordinals will be defined as a quotient
of this type. -/
structure WellOrder : Type (u + 1) where
/-- The underlying type of the order. -/
α : Type u
/-- The underlying relation of the order. -/
r : α → α → Prop
/-- The proposition that `r` is a well-ordering for `α`. -/
wo : IsWellOrder α r
set_option linter.uppercaseLean3 false in
#align Well_order WellOrder
attribute [instance] WellOrder.wo
namespace WellOrder
instance inhabited : Inhabited WellOrder :=
⟨⟨PEmpty, _, inferInstanceAs (IsWellOrder PEmpty EmptyRelation)⟩⟩
@[simp]
theorem eta (o : WellOrder) : mk o.α o.r o.wo = o := by
cases o
rfl
set_option linter.uppercaseLean3 false in
#align Well_order.eta WellOrder.eta
end WellOrder
/-- Equivalence relation on well orders on arbitrary types in universe `u`, given by order
isomorphism. -/
instance Ordinal.isEquivalent : Setoid WellOrder where
r := fun ⟨_, r, _⟩ ⟨_, s, _⟩ => Nonempty (r ≃r s)
iseqv :=
⟨fun _ => ⟨RelIso.refl _⟩, fun ⟨e⟩ => ⟨e.symm⟩, fun ⟨e₁⟩ ⟨e₂⟩ => ⟨e₁.trans e₂⟩⟩
#align ordinal.is_equivalent Ordinal.isEquivalent
/-- `Ordinal.{u}` is the type of well orders in `Type u`, up to order isomorphism. -/
@[pp_with_univ]
def Ordinal : Type (u + 1) :=
Quotient Ordinal.isEquivalent
#align ordinal Ordinal
instance hasWellFoundedOut (o : Ordinal) : WellFoundedRelation o.out.α :=
⟨o.out.r, o.out.wo.wf⟩
#align has_well_founded_out hasWellFoundedOut
instance linearOrderOut (o : Ordinal) : LinearOrder o.out.α :=
IsWellOrder.linearOrder o.out.r
#align linear_order_out linearOrderOut
instance isWellOrder_out_lt (o : Ordinal) : IsWellOrder o.out.α (· < ·) :=
o.out.wo
#align is_well_order_out_lt isWellOrder_out_lt
namespace Ordinal
/-! ### Basic properties of the order type -/
/-- The order type of a well order is an ordinal. -/
def type (r : α → α → Prop) [wo : IsWellOrder α r] : Ordinal :=
⟦⟨α, r, wo⟩⟧
#align ordinal.type Ordinal.type
instance zero : Zero Ordinal :=
⟨type <| @EmptyRelation PEmpty⟩
instance inhabited : Inhabited Ordinal :=
⟨0⟩
instance one : One Ordinal :=
⟨type <| @EmptyRelation PUnit⟩
/-- The order type of an element inside a well order. For the embedding as a principal segment, see
`typein.principalSeg`. -/
def typein (r : α → α → Prop) [IsWellOrder α r] (a : α) : Ordinal :=
type (Subrel r { b | r b a })
#align ordinal.typein Ordinal.typein
@[simp]
| Mathlib/SetTheory/Ordinal/Basic.lean | 196 | 198 | theorem type_def' (w : WellOrder) : ⟦w⟧ = type w.r := by |
cases w
rfl
|
/-
Copyright (c) 2020 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.Constructions.Prod.Basic
import Mathlib.MeasureTheory.Integral.DominatedConvergence
import Mathlib.MeasureTheory.Integral.SetIntegral
#align_import measure_theory.constructions.prod.integral from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Integration with respect to the product measure
In this file we prove Fubini's theorem.
## Main results
* `MeasureTheory.integrable_prod_iff` states that a binary function is integrable iff both
* `y ↦ f (x, y)` is integrable for almost every `x`, and
* the function `x ↦ ∫ ‖f (x, y)‖ dy` is integrable.
* `MeasureTheory.integral_prod`: Fubini's theorem. It states that for an integrable function
`α × β → E` (where `E` is a second countable Banach space) we have
`∫ z, f z ∂(μ.prod ν) = ∫ x, ∫ y, f (x, y) ∂ν ∂μ`. This theorem has the same variants as
Tonelli's theorem (see `MeasureTheory.lintegral_prod`). The lemma
`MeasureTheory.Integrable.integral_prod_right` states that the inner integral of the right-hand
side is integrable.
* `MeasureTheory.integral_integral_swap_of_hasCompactSupport`: a version of Fubini theorem for
continuous functions with compact support, which does not assume that the measures are σ-finite
contrary to all the usual versions of Fubini.
## Tags
product measure, Fubini's theorem, Fubini-Tonelli theorem
-/
noncomputable section
open scoped Classical Topology ENNReal MeasureTheory
open Set Function Real ENNReal
open MeasureTheory MeasurableSpace MeasureTheory.Measure
open TopologicalSpace
open Filter hiding prod_eq map
variable {α α' β β' γ E : Type*}
variable [MeasurableSpace α] [MeasurableSpace α'] [MeasurableSpace β] [MeasurableSpace β']
variable [MeasurableSpace γ]
variable {μ μ' : Measure α} {ν ν' : Measure β} {τ : Measure γ}
variable [NormedAddCommGroup E]
/-! ### Measurability
Before we define the product measure, we can talk about the measurability of operations on binary
functions. We show that if `f` is a binary measurable function, then the function that integrates
along one of the variables (using either the Lebesgue or Bochner integral) is measurable.
-/
theorem measurableSet_integrable [SigmaFinite ν] ⦃f : α → β → E⦄
(hf : StronglyMeasurable (uncurry f)) : MeasurableSet {x | Integrable (f x) ν} := by
simp_rw [Integrable, hf.of_uncurry_left.aestronglyMeasurable, true_and_iff]
exact measurableSet_lt (Measurable.lintegral_prod_right hf.ennnorm) measurable_const
#align measurable_set_integrable measurableSet_integrable
section
variable [NormedSpace ℝ E]
/-- The Bochner integral is measurable. This shows that the integrand of (the right-hand-side of)
Fubini's theorem is measurable.
This version has `f` in curried form. -/
| Mathlib/MeasureTheory/Constructions/Prod/Integral.lean | 77 | 122 | theorem MeasureTheory.StronglyMeasurable.integral_prod_right [SigmaFinite ν] ⦃f : α → β → E⦄
(hf : StronglyMeasurable (uncurry f)) : StronglyMeasurable fun x => ∫ y, f x y ∂ν := by |
by_cases hE : CompleteSpace E; swap; · simp [integral, hE, stronglyMeasurable_const]
borelize E
haveI : SeparableSpace (range (uncurry f) ∪ {0} : Set E) :=
hf.separableSpace_range_union_singleton
let s : ℕ → SimpleFunc (α × β) E :=
SimpleFunc.approxOn _ hf.measurable (range (uncurry f) ∪ {0}) 0 (by simp)
let s' : ℕ → α → SimpleFunc β E := fun n x => (s n).comp (Prod.mk x) measurable_prod_mk_left
let f' : ℕ → α → E := fun n => {x | Integrable (f x) ν}.indicator fun x => (s' n x).integral ν
have hf' : ∀ n, StronglyMeasurable (f' n) := by
intro n; refine StronglyMeasurable.indicator ?_ (measurableSet_integrable hf)
have : ∀ x, ((s' n x).range.filter fun x => x ≠ 0) ⊆ (s n).range := by
intro x; refine Finset.Subset.trans (Finset.filter_subset _ _) ?_; intro y
simp_rw [SimpleFunc.mem_range]; rintro ⟨z, rfl⟩; exact ⟨(x, z), rfl⟩
simp only [SimpleFunc.integral_eq_sum_of_subset (this _)]
refine Finset.stronglyMeasurable_sum _ fun x _ => ?_
refine (Measurable.ennreal_toReal ?_).stronglyMeasurable.smul_const _
simp only [s', SimpleFunc.coe_comp, preimage_comp]
apply measurable_measure_prod_mk_left
exact (s n).measurableSet_fiber x
have h2f' : Tendsto f' atTop (𝓝 fun x : α => ∫ y : β, f x y ∂ν) := by
rw [tendsto_pi_nhds]; intro x
by_cases hfx : Integrable (f x) ν
· have (n) : Integrable (s' n x) ν := by
apply (hfx.norm.add hfx.norm).mono' (s' n x).aestronglyMeasurable
filter_upwards with y
simp_rw [s', SimpleFunc.coe_comp]; exact SimpleFunc.norm_approxOn_zero_le _ _ (x, y) n
simp only [f', hfx, SimpleFunc.integral_eq_integral _ (this _), indicator_of_mem,
mem_setOf_eq]
refine
tendsto_integral_of_dominated_convergence (fun y => ‖f x y‖ + ‖f x y‖)
(fun n => (s' n x).aestronglyMeasurable) (hfx.norm.add hfx.norm) ?_ ?_
· refine fun n => eventually_of_forall fun y =>
SimpleFunc.norm_approxOn_zero_le ?_ ?_ (x, y) n
-- Porting note: Lean 3 solved the following two subgoals on its own
· exact hf.measurable
· simp
· refine eventually_of_forall fun y => SimpleFunc.tendsto_approxOn ?_ ?_ ?_
-- Porting note: Lean 3 solved the following two subgoals on its own
· exact hf.measurable.of_uncurry_left
· simp
apply subset_closure
simp [-uncurry_apply_pair]
· simp [f', hfx, integral_undef]
exact stronglyMeasurable_of_tendsto _ hf' h2f'
|
/-
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.MeasureTheory.Measure.AEDisjoint
import Mathlib.MeasureTheory.Constructions.EventuallyMeasurable
#align_import measure_theory.measure.null_measurable from "leanprover-community/mathlib"@"e4edb23029fff178210b9945dcb77d293f001e1c"
/-!
# Null measurable sets and complete measures
## Main definitions
### Null measurable sets and functions
A set `s : Set α` is called *null measurable* (`MeasureTheory.NullMeasurableSet`) if it satisfies
any of the following equivalent conditions:
* there exists a measurable set `t` such that `s =ᵐ[μ] t` (this is used as a definition);
* `MeasureTheory.toMeasurable μ s =ᵐ[μ] s`;
* there exists a measurable subset `t ⊆ s` such that `t =ᵐ[μ] s` (in this case the latter equality
means that `μ (s \ t) = 0`);
* `s` can be represented as a union of a measurable set and a set of measure zero;
* `s` can be represented as a difference of a measurable set and a set of measure zero.
Null measurable sets form a σ-algebra that is registered as a `MeasurableSpace` instance on
`MeasureTheory.NullMeasurableSpace α μ`. We also say that `f : α → β` is
`MeasureTheory.NullMeasurable` if the preimage of a measurable set is a null measurable set.
In other words, `f : α → β` is null measurable if it is measurable as a function
`MeasureTheory.NullMeasurableSpace α μ → β`.
### Complete measures
We say that a measure `μ` is complete w.r.t. the `MeasurableSpace α` σ-algebra (or the σ-algebra is
complete w.r.t measure `μ`) if every set of measure zero is measurable. In this case all null
measurable sets and functions are measurable.
For each measure `μ`, we define `MeasureTheory.Measure.completion μ` to be the same measure
interpreted as a measure on `MeasureTheory.NullMeasurableSpace α μ` and prove that this is a
complete measure.
## Implementation notes
We define `MeasureTheory.NullMeasurableSet` as `@MeasurableSet (NullMeasurableSpace α μ) _` so
that theorems about `MeasurableSet`s like `MeasurableSet.union` can be applied to
`NullMeasurableSet`s. However, these lemmas output terms of the same form
`@MeasurableSet (NullMeasurableSpace α μ) _ _`. While this is definitionally equal to the
expected output `NullMeasurableSet s μ`, it looks different and may be misleading. So we copy all
standard lemmas about measurable sets to the `MeasureTheory.NullMeasurableSet` namespace and fix
the output type.
## Tags
measurable, measure, null measurable, completion
-/
open Filter Set Encodable
variable {ι α β γ : Type*}
namespace MeasureTheory
/-- A type tag for `α` with `MeasurableSet` given by `NullMeasurableSet`. -/
@[nolint unusedArguments]
def NullMeasurableSpace (α : Type*) [MeasurableSpace α]
(_μ : Measure α := by volume_tac) : Type _ :=
α
#align measure_theory.null_measurable_space MeasureTheory.NullMeasurableSpace
section
variable {m0 : MeasurableSpace α} {μ : Measure α} {s t : Set α}
instance NullMeasurableSpace.instInhabited [h : Inhabited α] :
Inhabited (NullMeasurableSpace α μ) :=
h
#align measure_theory.null_measurable_space.inhabited MeasureTheory.NullMeasurableSpace.instInhabited
instance NullMeasurableSpace.instSubsingleton [h : Subsingleton α] :
Subsingleton (NullMeasurableSpace α μ) :=
h
#align measure_theory.null_measurable_space.subsingleton MeasureTheory.NullMeasurableSpace.instSubsingleton
instance NullMeasurableSpace.instMeasurableSpace : MeasurableSpace (NullMeasurableSpace α μ) :=
@EventuallyMeasurableSpace α inferInstance (ae μ) _
/-- A set is called `NullMeasurableSet` if it can be approximated by a measurable set up to
a set of null measure. -/
def NullMeasurableSet [MeasurableSpace α] (s : Set α)
(μ : Measure α := by volume_tac) : Prop :=
@MeasurableSet (NullMeasurableSpace α μ) _ s
#align measure_theory.null_measurable_set MeasureTheory.NullMeasurableSet
@[simp]
theorem _root_.MeasurableSet.nullMeasurableSet (h : MeasurableSet s) : NullMeasurableSet s μ :=
h.eventuallyMeasurableSet
#align measurable_set.null_measurable_set MeasurableSet.nullMeasurableSet
-- @[simp] -- Porting note (#10618): simp can prove this
theorem nullMeasurableSet_empty : NullMeasurableSet ∅ μ :=
MeasurableSet.empty
#align measure_theory.null_measurable_set_empty MeasureTheory.nullMeasurableSet_empty
-- @[simp] -- Porting note (#10618): simp can prove this
theorem nullMeasurableSet_univ : NullMeasurableSet univ μ :=
MeasurableSet.univ
#align measure_theory.null_measurable_set_univ MeasureTheory.nullMeasurableSet_univ
namespace NullMeasurableSet
theorem of_null (h : μ s = 0) : NullMeasurableSet s μ :=
⟨∅, MeasurableSet.empty, ae_eq_empty.2 h⟩
#align measure_theory.null_measurable_set.of_null MeasureTheory.NullMeasurableSet.of_null
theorem compl (h : NullMeasurableSet s μ) : NullMeasurableSet sᶜ μ :=
MeasurableSet.compl h
#align measure_theory.null_measurable_set.compl MeasureTheory.NullMeasurableSet.compl
theorem of_compl (h : NullMeasurableSet sᶜ μ) : NullMeasurableSet s μ :=
MeasurableSet.of_compl h
#align measure_theory.null_measurable_set.of_compl MeasureTheory.NullMeasurableSet.of_compl
@[simp]
theorem compl_iff : NullMeasurableSet sᶜ μ ↔ NullMeasurableSet s μ :=
MeasurableSet.compl_iff
#align measure_theory.null_measurable_set.compl_iff MeasureTheory.NullMeasurableSet.compl_iff
@[nontriviality]
theorem of_subsingleton [Subsingleton α] : NullMeasurableSet s μ :=
Subsingleton.measurableSet
#align measure_theory.null_measurable_set.of_subsingleton MeasureTheory.NullMeasurableSet.of_subsingleton
protected theorem congr (hs : NullMeasurableSet s μ) (h : s =ᵐ[μ] t) : NullMeasurableSet t μ :=
EventuallyMeasurableSet.congr hs h.symm
#align measure_theory.null_measurable_set.congr MeasureTheory.NullMeasurableSet.congr
protected theorem iUnion {ι : Sort*} [Countable ι] {s : ι → Set α}
(h : ∀ i, NullMeasurableSet (s i) μ) : NullMeasurableSet (⋃ i, s i) μ :=
MeasurableSet.iUnion h
#align measure_theory.null_measurable_set.Union MeasureTheory.NullMeasurableSet.iUnion
@[deprecated iUnion (since := "2023-05-06")]
protected theorem biUnion_decode₂ [Encodable ι] ⦃f : ι → Set α⦄ (h : ∀ i, NullMeasurableSet (f i) μ)
(n : ℕ) : NullMeasurableSet (⋃ b ∈ Encodable.decode₂ ι n, f b) μ :=
.iUnion fun _ => .iUnion fun _ => h _
#align measure_theory.null_measurable_set.bUnion_decode₂ MeasureTheory.NullMeasurableSet.biUnion_decode₂
protected theorem biUnion {f : ι → Set α} {s : Set ι} (hs : s.Countable)
(h : ∀ b ∈ s, NullMeasurableSet (f b) μ) : NullMeasurableSet (⋃ b ∈ s, f b) μ :=
MeasurableSet.biUnion hs h
#align measure_theory.null_measurable_set.bUnion MeasureTheory.NullMeasurableSet.biUnion
protected theorem sUnion {s : Set (Set α)} (hs : s.Countable) (h : ∀ t ∈ s, NullMeasurableSet t μ) :
NullMeasurableSet (⋃₀ s) μ := by
rw [sUnion_eq_biUnion]
exact MeasurableSet.biUnion hs h
#align measure_theory.null_measurable_set.sUnion MeasureTheory.NullMeasurableSet.sUnion
protected theorem iInter {ι : Sort*} [Countable ι] {f : ι → Set α}
(h : ∀ i, NullMeasurableSet (f i) μ) : NullMeasurableSet (⋂ i, f i) μ :=
MeasurableSet.iInter h
#align measure_theory.null_measurable_set.Inter MeasureTheory.NullMeasurableSet.iInter
protected theorem biInter {f : β → Set α} {s : Set β} (hs : s.Countable)
(h : ∀ b ∈ s, NullMeasurableSet (f b) μ) : NullMeasurableSet (⋂ b ∈ s, f b) μ :=
MeasurableSet.biInter hs h
#align measure_theory.null_measurable_set.bInter MeasureTheory.NullMeasurableSet.biInter
protected theorem sInter {s : Set (Set α)} (hs : s.Countable) (h : ∀ t ∈ s, NullMeasurableSet t μ) :
NullMeasurableSet (⋂₀ s) μ :=
MeasurableSet.sInter hs h
#align measure_theory.null_measurable_set.sInter MeasureTheory.NullMeasurableSet.sInter
@[simp]
protected theorem union (hs : NullMeasurableSet s μ) (ht : NullMeasurableSet t μ) :
NullMeasurableSet (s ∪ t) μ :=
MeasurableSet.union hs ht
#align measure_theory.null_measurable_set.union MeasureTheory.NullMeasurableSet.union
protected theorem union_null (hs : NullMeasurableSet s μ) (ht : μ t = 0) :
NullMeasurableSet (s ∪ t) μ :=
hs.union (of_null ht)
#align measure_theory.null_measurable_set.union_null MeasureTheory.NullMeasurableSet.union_null
@[simp]
protected theorem inter (hs : NullMeasurableSet s μ) (ht : NullMeasurableSet t μ) :
NullMeasurableSet (s ∩ t) μ :=
MeasurableSet.inter hs ht
#align measure_theory.null_measurable_set.inter MeasureTheory.NullMeasurableSet.inter
@[simp]
protected theorem diff (hs : NullMeasurableSet s μ) (ht : NullMeasurableSet t μ) :
NullMeasurableSet (s \ t) μ :=
MeasurableSet.diff hs ht
#align measure_theory.null_measurable_set.diff MeasureTheory.NullMeasurableSet.diff
@[simp]
protected theorem disjointed {f : ℕ → Set α} (h : ∀ i, NullMeasurableSet (f i) μ) (n) :
NullMeasurableSet (disjointed f n) μ :=
MeasurableSet.disjointed h n
#align measure_theory.null_measurable_set.disjointed MeasureTheory.NullMeasurableSet.disjointed
-- @[simp] -- Porting note (#10618): simp can prove thisrove this
protected theorem const (p : Prop) : NullMeasurableSet { _a : α | p } μ :=
MeasurableSet.const p
#align measure_theory.null_measurable_set.const MeasureTheory.NullMeasurableSet.const
instance instMeasurableSingletonClass [MeasurableSingletonClass α] :
MeasurableSingletonClass (NullMeasurableSpace α μ) :=
EventuallyMeasurableSpace.measurableSingleton (m := m0)
#align measure_theory.null_measurable_set.measure_theory.null_measurable_space.measurable_singleton_class MeasureTheory.NullMeasurableSet.instMeasurableSingletonClass
protected theorem insert [MeasurableSingletonClass (NullMeasurableSpace α μ)]
(hs : NullMeasurableSet s μ) (a : α) : NullMeasurableSet (insert a s) μ :=
MeasurableSet.insert hs a
#align measure_theory.null_measurable_set.insert MeasureTheory.NullMeasurableSet.insert
theorem exists_measurable_superset_ae_eq (h : NullMeasurableSet s μ) :
∃ t ⊇ s, MeasurableSet t ∧ t =ᵐ[μ] s := by
rcases h with ⟨t, htm, hst⟩
refine ⟨t ∪ toMeasurable μ (s \ t), ?_, htm.union (measurableSet_toMeasurable _ _), ?_⟩
· exact diff_subset_iff.1 (subset_toMeasurable _ _)
· have : toMeasurable μ (s \ t) =ᵐ[μ] (∅ : Set α) := by simp [ae_le_set.1 hst.le]
simpa only [union_empty] using hst.symm.union this
#align measure_theory.null_measurable_set.exists_measurable_superset_ae_eq MeasureTheory.NullMeasurableSet.exists_measurable_superset_ae_eq
theorem toMeasurable_ae_eq (h : NullMeasurableSet s μ) : toMeasurable μ s =ᵐ[μ] s := by
rw [toMeasurable_def, dif_pos]
exact (exists_measurable_superset_ae_eq h).choose_spec.2.2
#align measure_theory.null_measurable_set.to_measurable_ae_eq MeasureTheory.NullMeasurableSet.toMeasurable_ae_eq
theorem compl_toMeasurable_compl_ae_eq (h : NullMeasurableSet s μ) : (toMeasurable μ sᶜ)ᶜ =ᵐ[μ] s :=
Iff.mpr ae_eq_set_compl <| toMeasurable_ae_eq h.compl
#align measure_theory.null_measurable_set.compl_to_measurable_compl_ae_eq MeasureTheory.NullMeasurableSet.compl_toMeasurable_compl_ae_eq
theorem exists_measurable_subset_ae_eq (h : NullMeasurableSet s μ) :
∃ t ⊆ s, MeasurableSet t ∧ t =ᵐ[μ] s :=
⟨(toMeasurable μ sᶜ)ᶜ, compl_subset_comm.2 <| subset_toMeasurable _ _,
(measurableSet_toMeasurable _ _).compl, compl_toMeasurable_compl_ae_eq h⟩
#align measure_theory.null_measurable_set.exists_measurable_subset_ae_eq MeasureTheory.NullMeasurableSet.exists_measurable_subset_ae_eq
end NullMeasurableSet
open NullMeasurableSet
/-- If `sᵢ` is a countable family of (null) measurable pairwise `μ`-a.e. disjoint sets, then there
exists a subordinate family `tᵢ ⊆ sᵢ` of measurable pairwise disjoint sets such that
`tᵢ =ᵐ[μ] sᵢ`. -/
theorem exists_subordinate_pairwise_disjoint [Countable ι] {s : ι → Set α}
(h : ∀ i, NullMeasurableSet (s i) μ) (hd : Pairwise (AEDisjoint μ on s)) :
∃ t : ι → Set α,
(∀ i, t i ⊆ s i) ∧
(∀ i, s i =ᵐ[μ] t i) ∧ (∀ i, MeasurableSet (t i)) ∧ Pairwise (Disjoint on t) := by
choose t ht_sub htm ht_eq using fun i => exists_measurable_subset_ae_eq (h i)
rcases exists_null_pairwise_disjoint_diff hd with ⟨u, hum, hu₀, hud⟩
exact
⟨fun i => t i \ u i, fun i => diff_subset.trans (ht_sub _), fun i =>
(ht_eq _).symm.trans (diff_null_ae_eq_self (hu₀ i)).symm, fun i => (htm i).diff (hum i),
hud.mono fun i j h =>
h.mono (diff_subset_diff_left (ht_sub i)) (diff_subset_diff_left (ht_sub j))⟩
#align measure_theory.exists_subordinate_pairwise_disjoint MeasureTheory.exists_subordinate_pairwise_disjoint
theorem measure_iUnion {m0 : MeasurableSpace α} {μ : Measure α} [Countable ι] {f : ι → Set α}
(hn : Pairwise (Disjoint on f)) (h : ∀ i, MeasurableSet (f i)) :
μ (⋃ i, f i) = ∑' i, μ (f i) := by
rw [measure_eq_extend (MeasurableSet.iUnion h),
extend_iUnion MeasurableSet.empty _ MeasurableSet.iUnion _ hn h]
· simp [measure_eq_extend, h]
· exact μ.empty
· exact μ.m_iUnion
#align measure_theory.measure_Union MeasureTheory.measure_iUnion
theorem measure_iUnion₀ [Countable ι] {f : ι → Set α} (hd : Pairwise (AEDisjoint μ on f))
(h : ∀ i, NullMeasurableSet (f i) μ) : μ (⋃ i, f i) = ∑' i, μ (f i) := by
rcases exists_subordinate_pairwise_disjoint h hd with ⟨t, _ht_sub, ht_eq, htm, htd⟩
calc
μ (⋃ i, f i) = μ (⋃ i, t i) := measure_congr (EventuallyEq.countable_iUnion ht_eq)
_ = ∑' i, μ (t i) := measure_iUnion htd htm
_ = ∑' i, μ (f i) := tsum_congr fun i => measure_congr (ht_eq _).symm
#align measure_theory.measure_Union₀ MeasureTheory.measure_iUnion₀
theorem measure_union₀_aux (hs : NullMeasurableSet s μ) (ht : NullMeasurableSet t μ)
(hd : AEDisjoint μ s t) : μ (s ∪ t) = μ s + μ t := by
rw [union_eq_iUnion, measure_iUnion₀, tsum_fintype, Fintype.sum_bool, cond, cond]
exacts [(pairwise_on_bool AEDisjoint.symmetric).2 hd, fun b => Bool.casesOn b ht hs]
#align measure_theory.measure_union₀_aux MeasureTheory.measure_union₀_aux
/-- A null measurable set `t` is Carathéodory measurable: for any `s`, we have
`μ (s ∩ t) + μ (s \ t) = μ s`. -/
theorem measure_inter_add_diff₀ (s : Set α) (ht : NullMeasurableSet t μ) :
μ (s ∩ t) + μ (s \ t) = μ s := by
refine le_antisymm ?_ (measure_le_inter_add_diff _ _ _)
rcases exists_measurable_superset μ s with ⟨s', hsub, hs'm, hs'⟩
replace hs'm : NullMeasurableSet s' μ := hs'm.nullMeasurableSet
calc
μ (s ∩ t) + μ (s \ t) ≤ μ (s' ∩ t) + μ (s' \ t) := by gcongr
_ = μ (s' ∩ t ∪ s' \ t) :=
(measure_union₀_aux (hs'm.inter ht) (hs'm.diff ht) <|
(@disjoint_inf_sdiff _ s' t _).aedisjoint).symm
_ = μ s' := congr_arg μ (inter_union_diff _ _)
_ = μ s := hs'
#align measure_theory.measure_inter_add_diff₀ MeasureTheory.measure_inter_add_diff₀
theorem measure_union_add_inter₀ (s : Set α) (ht : NullMeasurableSet t μ) :
μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by
rw [← measure_inter_add_diff₀ (s ∪ t) ht, union_inter_cancel_right, union_diff_right, ←
measure_inter_add_diff₀ s ht, add_comm, ← add_assoc, add_right_comm]
#align measure_theory.measure_union_add_inter₀ MeasureTheory.measure_union_add_inter₀
theorem measure_union_add_inter₀' (hs : NullMeasurableSet s μ) (t : Set α) :
μ (s ∪ t) + μ (s ∩ t) = μ s + μ t := by
rw [union_comm, inter_comm, measure_union_add_inter₀ t hs, add_comm]
#align measure_theory.measure_union_add_inter₀' MeasureTheory.measure_union_add_inter₀'
theorem measure_union₀ (ht : NullMeasurableSet t μ) (hd : AEDisjoint μ s t) :
μ (s ∪ t) = μ s + μ t := by rw [← measure_union_add_inter₀ s ht, hd, add_zero]
#align measure_theory.measure_union₀ MeasureTheory.measure_union₀
theorem measure_union₀' (hs : NullMeasurableSet s μ) (hd : AEDisjoint μ s t) :
μ (s ∪ t) = μ s + μ t := by rw [union_comm, measure_union₀ hs (AEDisjoint.symm hd), add_comm]
#align measure_theory.measure_union₀' MeasureTheory.measure_union₀'
| Mathlib/MeasureTheory/Measure/NullMeasurable.lean | 327 | 328 | theorem measure_add_measure_compl₀ {s : Set α} (hs : NullMeasurableSet s μ) :
μ s + μ sᶜ = μ univ := by | rw [← measure_union₀' hs aedisjoint_compl_right, union_compl_self]
|
/-
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`. -/
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
#align vitali_family.ae_tendsto_div VitaliFamily.ae_tendsto_div
theorem ae_tendsto_limRatio :
∀ᵐ x ∂μ, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatio ρ x)) := by
filter_upwards [v.ae_tendsto_div hρ]
intro x hx
exact tendsto_nhds_limUnder hx
#align vitali_family.ae_tendsto_lim_ratio VitaliFamily.ae_tendsto_limRatio
/-- Given two thresholds `p < q`, the sets `{x | v.limRatio ρ x < p}`
and `{x | q < v.limRatio ρ x}` are obviously disjoint. The key to proving that `v.limRatio ρ` is
almost everywhere measurable is to show that these sets have measurable supersets which are also
disjoint, up to zero measure. This is the content of this lemma. -/
theorem exists_measurable_supersets_limRatio {p q : ℝ≥0} (hpq : p < q) :
∃ a b, MeasurableSet a ∧ MeasurableSet b ∧
{x | v.limRatio ρ x < p} ⊆ a ∧ {x | (q : ℝ≥0∞) < v.limRatio ρ x} ⊆ b ∧ μ (a ∩ b) = 0 := by
/- Here is a rough sketch, assuming that the measure is finite and the limit is well defined
everywhere. Let `u := {x | v.limRatio ρ x < p}` and `w := {x | q < v.limRatio ρ x}`. They
have measurable supersets `u'` and `w'` of the same measure. We will show that these satisfy
the conclusion of the theorem, i.e., `μ (u' ∩ w') = 0`. For this, note that
`ρ (u' ∩ w') = ρ (u ∩ w')` (as `w'` is measurable, see `measure_toMeasurable_add_inter_left`).
The latter set is included in the set where the limit of the ratios is `< p`, and therefore
its measure is `≤ p * μ (u ∩ w')`. Using the same trick in the other direction gives that this
is `p * μ (u' ∩ w')`. We have shown that `ρ (u' ∩ w') ≤ p * μ (u' ∩ w')`. Arguing in the same
way but using the `w` part gives `q * μ (u' ∩ w') ≤ ρ (u' ∩ w')`. If `μ (u' ∩ w')` were nonzero,
this would be a contradiction as `p < q`.
For the rigorous proof, we need to work on a part of the space where the measure is finite
(provided by `spanningSets (ρ + μ)`) and to restrict to the set where the limit is well defined
(called `s` below, of full measure). Otherwise, the argument goes through.
-/
let s := {x | ∃ c, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 c)}
let o : ℕ → Set α := spanningSets (ρ + μ)
let u n := s ∩ {x | v.limRatio ρ x < p} ∩ o n
let w n := s ∩ {x | (q : ℝ≥0∞) < v.limRatio ρ x} ∩ o n
-- the supersets are obtained by restricting to the set `s` where the limit is well defined, to
-- a finite measure part `o n`, taking a measurable superset here, and then taking the union over
-- `n`.
refine
⟨toMeasurable μ sᶜ ∪ ⋃ n, toMeasurable (ρ + μ) (u n),
toMeasurable μ sᶜ ∪ ⋃ n, toMeasurable (ρ + μ) (w n), ?_, ?_, ?_, ?_, ?_⟩
-- check that these sets are measurable supersets as required
· exact
(measurableSet_toMeasurable _ _).union
(MeasurableSet.iUnion fun n => measurableSet_toMeasurable _ _)
· exact
(measurableSet_toMeasurable _ _).union
(MeasurableSet.iUnion fun n => measurableSet_toMeasurable _ _)
· intro x hx
by_cases h : x ∈ s
· refine Or.inr (mem_iUnion.2 ⟨spanningSetsIndex (ρ + μ) x, ?_⟩)
exact subset_toMeasurable _ _ ⟨⟨h, hx⟩, mem_spanningSetsIndex _ _⟩
· exact Or.inl (subset_toMeasurable μ sᶜ h)
· intro x hx
by_cases h : x ∈ s
· refine Or.inr (mem_iUnion.2 ⟨spanningSetsIndex (ρ + μ) x, ?_⟩)
exact subset_toMeasurable _ _ ⟨⟨h, hx⟩, mem_spanningSetsIndex _ _⟩
· exact Or.inl (subset_toMeasurable μ sᶜ h)
-- it remains to check the nontrivial part that these sets have zero measure intersection.
-- it suffices to do it for fixed `m` and `n`, as one is taking countable unions.
suffices H : ∀ m n : ℕ, μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) = 0 by
have A :
(toMeasurable μ sᶜ ∪ ⋃ n, toMeasurable (ρ + μ) (u n)) ∩
(toMeasurable μ sᶜ ∪ ⋃ n, toMeasurable (ρ + μ) (w n)) ⊆
toMeasurable μ sᶜ ∪
⋃ (m) (n), toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n) := by
simp only [inter_union_distrib_left, union_inter_distrib_right, true_and_iff,
subset_union_left, union_subset_iff, inter_self]
refine ⟨?_, ?_, ?_⟩
· exact inter_subset_right.trans subset_union_left
· exact inter_subset_left.trans subset_union_left
· simp_rw [iUnion_inter, inter_iUnion]; exact subset_union_right
refine le_antisymm ((measure_mono A).trans ?_) bot_le
calc
μ (toMeasurable μ sᶜ ∪
⋃ (m) (n), toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≤
μ (toMeasurable μ sᶜ) +
μ (⋃ (m) (n), toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) :=
measure_union_le _ _
_ = μ (⋃ (m) (n), toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := by
have : μ sᶜ = 0 := v.ae_tendsto_div hρ; rw [measure_toMeasurable, this, zero_add]
_ ≤ ∑' (m) (n), μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) :=
((measure_iUnion_le _).trans (ENNReal.tsum_le_tsum fun m => measure_iUnion_le _))
_ = 0 := by simp only [H, tsum_zero]
-- now starts the nontrivial part of the argument. We fix `m` and `n`, and show that the
-- measurable supersets of `u m` and `w n` have zero measure intersection by using the lemmas
-- `measure_toMeasurable_add_inter_left` (to reduce to `u m` or `w n` instead of the measurable
-- superset) and `measure_le_of_frequently_le` to compare their measures for `ρ` and `μ`.
intro m n
have I : (ρ + μ) (u m) ≠ ∞ := by
apply (lt_of_le_of_lt (measure_mono _) (measure_spanningSets_lt_top (ρ + μ) m)).ne
exact inter_subset_right
have J : (ρ + μ) (w n) ≠ ∞ := by
apply (lt_of_le_of_lt (measure_mono _) (measure_spanningSets_lt_top (ρ + μ) n)).ne
exact inter_subset_right
have A :
ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≤
p * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) :=
calc
ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) =
ρ (u m ∩ toMeasurable (ρ + μ) (w n)) :=
measure_toMeasurable_add_inter_left (measurableSet_toMeasurable _ _) I
_ ≤ (p • μ) (u m ∩ toMeasurable (ρ + μ) (w n)) := by
refine v.measure_le_of_frequently_le (p • μ) hρ _ fun x hx => ?_
have L : Tendsto (fun a : Set α => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatio ρ x)) :=
tendsto_nhds_limUnder hx.1.1.1
have I : ∀ᶠ b : Set α in v.filterAt x, ρ b / μ b < p := (tendsto_order.1 L).2 _ hx.1.1.2
apply I.frequently.mono fun a ha => ?_
rw [coe_nnreal_smul_apply]
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]
_ = p * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := by
simp only [coe_nnreal_smul_apply,
measure_toMeasurable_add_inter_right (measurableSet_toMeasurable _ _) I]
have B :
(q : ℝ≥0∞) * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≤
ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) :=
calc
(q : ℝ≥0∞) * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) =
(q : ℝ≥0∞) * μ (toMeasurable (ρ + μ) (u m) ∩ w n) := by
conv_rhs => rw [inter_comm]
rw [inter_comm, measure_toMeasurable_add_inter_right (measurableSet_toMeasurable _ _) J]
_ ≤ ρ (toMeasurable (ρ + μ) (u m) ∩ w n) := by
rw [← coe_nnreal_smul_apply]
refine v.measure_le_of_frequently_le _ (AbsolutelyContinuous.rfl.smul _) _ ?_
intro x hx
have L : Tendsto (fun a : Set α => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatio ρ x)) :=
tendsto_nhds_limUnder hx.2.1.1
have I : ∀ᶠ b : Set α in v.filterAt x, (q : ℝ≥0∞) < ρ b / μ b :=
(tendsto_order.1 L).1 _ hx.2.1.2
apply I.frequently.mono fun a ha => ?_
rw [coe_nnreal_smul_apply]
exact ENNReal.mul_le_of_le_div ha.le
_ = ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := by
conv_rhs => rw [inter_comm]
rw [inter_comm]
exact (measure_toMeasurable_add_inter_left (measurableSet_toMeasurable _ _) J).symm
by_contra h
apply lt_irrefl (ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)))
calc
ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≤
p * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) :=
A
_ < q * μ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := by
gcongr
suffices H : (ρ + μ) (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) ≠ ∞ by
simp only [not_or, ENNReal.add_eq_top, Pi.add_apply, Ne, coe_add] at H
exact H.2
apply (lt_of_le_of_lt (measure_mono inter_subset_left) _).ne
rw [measure_toMeasurable]
apply lt_of_le_of_lt (measure_mono _) (measure_spanningSets_lt_top (ρ + μ) m)
exact inter_subset_right
_ ≤ ρ (toMeasurable (ρ + μ) (u m) ∩ toMeasurable (ρ + μ) (w n)) := B
#align vitali_family.exists_measurable_supersets_lim_ratio VitaliFamily.exists_measurable_supersets_limRatio
theorem aemeasurable_limRatio : AEMeasurable (v.limRatio ρ) μ := by
apply ENNReal.aemeasurable_of_exist_almost_disjoint_supersets _ _ fun p q hpq => ?_
exact v.exists_measurable_supersets_limRatio hρ hpq
#align vitali_family.ae_measurable_lim_ratio VitaliFamily.aemeasurable_limRatio
/-- A measurable version of `v.limRatio ρ`. Do *not* use this definition: it is only a temporary
device to show that `v.limRatio` is almost everywhere equal to the Radon-Nikodym derivative. -/
noncomputable def limRatioMeas : α → ℝ≥0∞ :=
(v.aemeasurable_limRatio hρ).mk _
#align vitali_family.lim_ratio_meas VitaliFamily.limRatioMeas
theorem limRatioMeas_measurable : Measurable (v.limRatioMeas hρ) :=
AEMeasurable.measurable_mk _
#align vitali_family.lim_ratio_meas_measurable VitaliFamily.limRatioMeas_measurable
theorem ae_tendsto_limRatioMeas :
∀ᵐ x ∂μ, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatioMeas hρ x)) := by
filter_upwards [v.ae_tendsto_limRatio hρ, AEMeasurable.ae_eq_mk (v.aemeasurable_limRatio hρ)]
intro x hx h'x
rwa [h'x] at hx
#align vitali_family.ae_tendsto_lim_ratio_meas VitaliFamily.ae_tendsto_limRatioMeas
/-- If, for all `x` in a set `s`, one has frequently `ρ a / μ a < p`, then `ρ s ≤ p * μ s`, as
proved in `measure_le_of_frequently_le`. Since `ρ a / μ a` tends almost everywhere to
`v.limRatioMeas hρ x`, the same property holds for sets `s` on which `v.limRatioMeas hρ < p`. -/
theorem measure_le_mul_of_subset_limRatioMeas_lt {p : ℝ≥0} {s : Set α}
(h : s ⊆ {x | v.limRatioMeas hρ x < p}) : ρ s ≤ p * μ s := by
let t := {x : α | Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatioMeas hρ x))}
have A : μ tᶜ = 0 := v.ae_tendsto_limRatioMeas hρ
suffices H : ρ (s ∩ t) ≤ (p • μ) (s ∩ t) by calc
ρ s = ρ (s ∩ t ∪ s ∩ tᶜ) := by rw [inter_union_compl]
_ ≤ ρ (s ∩ t) + ρ (s ∩ tᶜ) := measure_union_le _ _
_ ≤ (p • μ) (s ∩ t) + ρ tᶜ := by gcongr; apply inter_subset_right
_ ≤ p * μ (s ∩ t) := by simp [(hρ A)]
_ ≤ p * μ s := by gcongr; apply inter_subset_left
refine v.measure_le_of_frequently_le (p • μ) hρ _ fun x hx => ?_
have I : ∀ᶠ b : Set α in v.filterAt x, ρ b / μ b < p := (tendsto_order.1 hx.2).2 _ (h hx.1)
apply I.frequently.mono fun a ha => ?_
rw [coe_nnreal_smul_apply]
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]
#align vitali_family.measure_le_mul_of_subset_lim_ratio_meas_lt VitaliFamily.measure_le_mul_of_subset_limRatioMeas_lt
/-- If, for all `x` in a set `s`, one has frequently `q < ρ a / μ a`, then `q * μ s ≤ ρ s`, as
proved in `measure_le_of_frequently_le`. Since `ρ a / μ a` tends almost everywhere to
`v.limRatioMeas hρ x`, the same property holds for sets `s` on which `q < v.limRatioMeas hρ`. -/
theorem mul_measure_le_of_subset_lt_limRatioMeas {q : ℝ≥0} {s : Set α}
(h : s ⊆ {x | (q : ℝ≥0∞) < v.limRatioMeas hρ x}) : (q : ℝ≥0∞) * μ s ≤ ρ s := by
let t := {x : α | Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (v.limRatioMeas hρ x))}
have A : μ tᶜ = 0 := v.ae_tendsto_limRatioMeas hρ
suffices H : (q • μ) (s ∩ t) ≤ ρ (s ∩ t) by calc
(q • μ) s = (q • μ) (s ∩ t ∪ s ∩ tᶜ) := by rw [inter_union_compl]
_ ≤ (q • μ) (s ∩ t) + (q • μ) (s ∩ tᶜ) := measure_union_le _ _
_ ≤ ρ (s ∩ t) + (q • μ) tᶜ := by gcongr; apply inter_subset_right
_ = ρ (s ∩ t) := by simp [A]
_ ≤ ρ s := by gcongr; apply inter_subset_left
refine v.measure_le_of_frequently_le _ (AbsolutelyContinuous.rfl.smul _) _ ?_
intro x hx
have I : ∀ᶠ a in v.filterAt x, (q : ℝ≥0∞) < ρ a / μ a := (tendsto_order.1 hx.2).1 _ (h hx.1)
apply I.frequently.mono fun a ha => ?_
rw [coe_nnreal_smul_apply]
exact ENNReal.mul_le_of_le_div ha.le
#align vitali_family.mul_measure_le_of_subset_lt_lim_ratio_meas VitaliFamily.mul_measure_le_of_subset_lt_limRatioMeas
/-- The points with `v.limRatioMeas hρ x = ∞` have measure `0` for `μ`. -/
theorem measure_limRatioMeas_top : μ {x | v.limRatioMeas hρ x = ∞} = 0 := by
refine measure_null_of_locally_null _ fun x _ => ?_
obtain ⟨o, xo, o_open, μo⟩ : ∃ o : Set α, x ∈ o ∧ IsOpen o ∧ ρ o < ∞ :=
Measure.exists_isOpen_measure_lt_top ρ x
let s := {x : α | v.limRatioMeas hρ x = ∞} ∩ o
refine ⟨s, inter_mem_nhdsWithin _ (o_open.mem_nhds xo), le_antisymm ?_ bot_le⟩
have ρs : ρ s ≠ ∞ := ((measure_mono inter_subset_right).trans_lt μo).ne
have A : ∀ q : ℝ≥0, 1 ≤ q → μ s ≤ (q : ℝ≥0∞)⁻¹ * ρ s := by
intro q hq
rw [mul_comm, ← div_eq_mul_inv, ENNReal.le_div_iff_mul_le _ (Or.inr ρs), mul_comm]
· apply v.mul_measure_le_of_subset_lt_limRatioMeas hρ
intro y hy
have : v.limRatioMeas hρ y = ∞ := hy.1
simp only [this, ENNReal.coe_lt_top, mem_setOf_eq]
· simp only [(zero_lt_one.trans_le hq).ne', true_or_iff, ENNReal.coe_eq_zero, Ne,
not_false_iff]
have B : Tendsto (fun q : ℝ≥0 => (q : ℝ≥0∞)⁻¹ * ρ s) atTop (𝓝 (∞⁻¹ * ρ s)) := by
apply ENNReal.Tendsto.mul_const _ (Or.inr ρs)
exact ENNReal.tendsto_inv_iff.2 (ENNReal.tendsto_coe_nhds_top.2 tendsto_id)
simp only [zero_mul, ENNReal.inv_top] at B
apply ge_of_tendsto B
exact eventually_atTop.2 ⟨1, A⟩
#align vitali_family.measure_lim_ratio_meas_top VitaliFamily.measure_limRatioMeas_top
/-- The points with `v.limRatioMeas hρ x = 0` have measure `0` for `ρ`. -/
theorem measure_limRatioMeas_zero : ρ {x | v.limRatioMeas hρ x = 0} = 0 := by
refine measure_null_of_locally_null _ 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
let s := {x : α | v.limRatioMeas hρ x = 0} ∩ o
refine ⟨s, inter_mem_nhdsWithin _ (o_open.mem_nhds xo), le_antisymm ?_ bot_le⟩
have μs : μ s ≠ ∞ := ((measure_mono inter_subset_right).trans_lt μo).ne
have A : ∀ q : ℝ≥0, 0 < q → ρ s ≤ q * μ s := by
intro q hq
apply v.measure_le_mul_of_subset_limRatioMeas_lt hρ
intro y hy
have : v.limRatioMeas hρ y = 0 := hy.1
simp only [this, mem_setOf_eq, hq, ENNReal.coe_pos]
have B : Tendsto (fun q : ℝ≥0 => (q : ℝ≥0∞) * μ s) (𝓝[>] (0 : ℝ≥0)) (𝓝 ((0 : ℝ≥0) * μ s)) := by
apply ENNReal.Tendsto.mul_const _ (Or.inr μs)
rw [ENNReal.tendsto_coe]
exact nhdsWithin_le_nhds
simp only [zero_mul, ENNReal.coe_zero] at B
apply ge_of_tendsto B
filter_upwards [self_mem_nhdsWithin] using A
#align vitali_family.measure_lim_ratio_meas_zero VitaliFamily.measure_limRatioMeas_zero
/-- As an intermediate step to show that `μ.withDensity (v.limRatioMeas hρ) = ρ`, we show here
that `μ.withDensity (v.limRatioMeas hρ) ≤ t^2 ρ` for any `t > 1`. -/
theorem withDensity_le_mul {s : Set α} (hs : MeasurableSet s) {t : ℝ≥0} (ht : 1 < t) :
μ.withDensity (v.limRatioMeas hρ) s ≤ (t : ℝ≥0∞) ^ 2 * ρ s := by
/- We cut `s` into the sets where `v.limRatioMeas hρ = 0`, where `v.limRatioMeas hρ = ∞`, and
where `v.limRatioMeas hρ ∈ [t^n, t^(n+1))` for `n : ℤ`. The first and second have measure `0`.
For the latter, since `v.limRatioMeas hρ` fluctuates by at most `t` on this slice, we can use
`measure_le_mul_of_subset_limRatioMeas_lt` and `mul_measure_le_of_subset_lt_limRatioMeas` to
show that the two measures are comparable up to `t` (in fact `t^2` for technical reasons of
strict inequalities). -/
have t_ne_zero' : t ≠ 0 := (zero_lt_one.trans ht).ne'
have t_ne_zero : (t : ℝ≥0∞) ≠ 0 := by simpa only [ENNReal.coe_eq_zero, Ne] using t_ne_zero'
let ν := μ.withDensity (v.limRatioMeas hρ)
let f := v.limRatioMeas hρ
have f_meas : Measurable f := v.limRatioMeas_measurable hρ
-- Note(kmill): smul elaborator when used for CoeFun fails to get CoeFun instance to trigger
-- unless you use the `(... :)` notation. Another fix is using `(2 : Nat)`, so this appears
-- to be an unpleasant interaction with default instances.
have A : ν (s ∩ f ⁻¹' {0}) ≤ ((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' {0}) := by
apply le_trans _ (zero_le _)
have M : MeasurableSet (s ∩ f ⁻¹' {0}) := hs.inter (f_meas (measurableSet_singleton _))
simp only [ν, nonpos_iff_eq_zero, M, withDensity_apply, lintegral_eq_zero_iff f_meas]
apply (ae_restrict_iff' M).2
exact eventually_of_forall fun x hx => hx.2
have B : ν (s ∩ f ⁻¹' {∞}) ≤ ((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' {∞}) := by
apply le_trans (le_of_eq _) (zero_le _)
apply withDensity_absolutelyContinuous μ _
rw [← nonpos_iff_eq_zero]
exact (measure_mono inter_subset_right).trans (v.measure_limRatioMeas_top hρ).le
have C :
∀ n : ℤ,
ν (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) ≤
((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) := by
intro n
let I := Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))
have M : MeasurableSet (s ∩ f ⁻¹' I) := hs.inter (f_meas measurableSet_Ico)
simp only [ν, M, withDensity_apply, coe_nnreal_smul_apply]
calc
(∫⁻ x in s ∩ f ⁻¹' I, f x ∂μ) ≤ ∫⁻ _ in s ∩ f ⁻¹' I, (t : ℝ≥0∞) ^ (n + 1) ∂μ :=
lintegral_mono_ae ((ae_restrict_iff' M).2 (eventually_of_forall fun x hx => hx.2.2.le))
_ = (t : ℝ≥0∞) ^ (n + 1) * μ (s ∩ f ⁻¹' I) := by
simp only [lintegral_const, MeasurableSet.univ, Measure.restrict_apply, univ_inter]
_ = (t : ℝ≥0∞) ^ (2 : ℤ) * ((t : ℝ≥0∞) ^ (n - 1) * μ (s ∩ f ⁻¹' I)) := by
rw [← mul_assoc, ← ENNReal.zpow_add t_ne_zero ENNReal.coe_ne_top]
congr 2
abel
_ ≤ (t : ℝ≥0∞) ^ (2 : ℤ) * ρ (s ∩ f ⁻¹' I) := by
gcongr
rw [← ENNReal.coe_zpow (zero_lt_one.trans ht).ne']
apply v.mul_measure_le_of_subset_lt_limRatioMeas hρ
intro x hx
apply lt_of_lt_of_le _ hx.2.1
rw [← ENNReal.coe_zpow (zero_lt_one.trans ht).ne', ENNReal.coe_lt_coe, sub_eq_add_neg,
zpow_add₀ t_ne_zero']
conv_rhs => rw [← mul_one (t ^ n)]
gcongr
rw [zpow_neg_one]
exact inv_lt_one ht
calc
ν s =
ν (s ∩ f ⁻¹' {0}) + ν (s ∩ f ⁻¹' {∞}) +
∑' n : ℤ, ν (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) :=
measure_eq_measure_preimage_add_measure_tsum_Ico_zpow ν f_meas hs ht
_ ≤
((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' {0}) + ((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' {∞}) +
∑' n : ℤ, ((t : ℝ≥0∞) ^ 2 • ρ :) (s ∩ f ⁻¹' Ico (t ^ n) (t ^ (n + 1))) :=
(add_le_add (add_le_add A B) (ENNReal.tsum_le_tsum C))
_ = ((t : ℝ≥0∞) ^ 2 • ρ :) s :=
(measure_eq_measure_preimage_add_measure_tsum_Ico_zpow ((t : ℝ≥0∞) ^ 2 • ρ) f_meas hs ht).symm
#align vitali_family.with_density_le_mul VitaliFamily.withDensity_le_mul
/-- As an intermediate step to show that `μ.withDensity (v.limRatioMeas hρ) = ρ`, we show here
that `ρ ≤ t μ.withDensity (v.limRatioMeas hρ)` for any `t > 1`. -/
theorem le_mul_withDensity {s : Set α} (hs : MeasurableSet s) {t : ℝ≥0} (ht : 1 < t) :
ρ s ≤ t * μ.withDensity (v.limRatioMeas hρ) s := by
/- We cut `s` into the sets where `v.limRatioMeas hρ = 0`, where `v.limRatioMeas hρ = ∞`, and
where `v.limRatioMeas hρ ∈ [t^n, t^(n+1))` for `n : ℤ`. The first and second have measure `0`.
For the latter, since `v.limRatioMeas hρ` fluctuates by at most `t` on this slice, we can use
`measure_le_mul_of_subset_limRatioMeas_lt` and `mul_measure_le_of_subset_lt_limRatioMeas` to
show that the two measures are comparable up to `t`. -/
have t_ne_zero' : t ≠ 0 := (zero_lt_one.trans ht).ne'
have t_ne_zero : (t : ℝ≥0∞) ≠ 0 := by simpa only [ENNReal.coe_eq_zero, Ne] using t_ne_zero'
let ν := μ.withDensity (v.limRatioMeas hρ)
let f := v.limRatioMeas hρ
have f_meas : Measurable f := v.limRatioMeas_measurable hρ
have A : ρ (s ∩ f ⁻¹' {0}) ≤ (t • ν) (s ∩ f ⁻¹' {0}) := by
refine le_trans (measure_mono inter_subset_right) (le_trans (le_of_eq ?_) (zero_le _))
exact v.measure_limRatioMeas_zero hρ
have B : ρ (s ∩ f ⁻¹' {∞}) ≤ (t • ν) (s ∩ f ⁻¹' {∞}) := by
apply le_trans (le_of_eq _) (zero_le _)
apply hρ
rw [← nonpos_iff_eq_zero]
exact (measure_mono inter_subset_right).trans (v.measure_limRatioMeas_top hρ).le
have C :
∀ n : ℤ,
ρ (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) ≤
(t • ν) (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) := by
intro n
let I := Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))
have M : MeasurableSet (s ∩ f ⁻¹' I) := hs.inter (f_meas measurableSet_Ico)
simp only [ν, M, withDensity_apply, coe_nnreal_smul_apply]
calc
ρ (s ∩ f ⁻¹' I) ≤ (t : ℝ≥0∞) ^ (n + 1) * μ (s ∩ f ⁻¹' I) := by
rw [← ENNReal.coe_zpow t_ne_zero']
apply v.measure_le_mul_of_subset_limRatioMeas_lt hρ
intro x hx
apply hx.2.2.trans_le (le_of_eq _)
rw [ENNReal.coe_zpow t_ne_zero']
_ = ∫⁻ _ in s ∩ f ⁻¹' I, (t : ℝ≥0∞) ^ (n + 1) ∂μ := by
simp only [lintegral_const, MeasurableSet.univ, Measure.restrict_apply, univ_inter]
_ ≤ ∫⁻ x in s ∩ f ⁻¹' I, t * f x ∂μ := by
apply lintegral_mono_ae ((ae_restrict_iff' M).2 (eventually_of_forall fun x hx => ?_))
rw [add_comm, ENNReal.zpow_add t_ne_zero ENNReal.coe_ne_top, zpow_one]
exact mul_le_mul_left' hx.2.1 _
_ = t * ∫⁻ x in s ∩ f ⁻¹' I, f x ∂μ := lintegral_const_mul _ f_meas
calc
ρ s =
ρ (s ∩ f ⁻¹' {0}) + ρ (s ∩ f ⁻¹' {∞}) +
∑' n : ℤ, ρ (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) :=
measure_eq_measure_preimage_add_measure_tsum_Ico_zpow ρ f_meas hs ht
_ ≤
(t • ν) (s ∩ f ⁻¹' {0}) + (t • ν) (s ∩ f ⁻¹' {∞}) +
∑' n : ℤ, (t • ν) (s ∩ f ⁻¹' Ico ((t : ℝ≥0∞) ^ n) ((t : ℝ≥0∞) ^ (n + 1))) :=
(add_le_add (add_le_add A B) (ENNReal.tsum_le_tsum C))
_ = (t • ν) s :=
(measure_eq_measure_preimage_add_measure_tsum_Ico_zpow (t • ν) f_meas hs ht).symm
#align vitali_family.le_mul_with_density VitaliFamily.le_mul_withDensity
theorem withDensity_limRatioMeas_eq : μ.withDensity (v.limRatioMeas hρ) = ρ := by
ext1 s hs
refine le_antisymm ?_ ?_
· have : Tendsto (fun t : ℝ≥0 =>
((t : ℝ≥0∞) ^ 2 * ρ s : ℝ≥0∞)) (𝓝[>] 1) (𝓝 ((1 : ℝ≥0∞) ^ 2 * ρ s)) := by
refine ENNReal.Tendsto.mul ?_ ?_ tendsto_const_nhds ?_
· exact ENNReal.Tendsto.pow (ENNReal.tendsto_coe.2 nhdsWithin_le_nhds)
· simp only [one_pow, ENNReal.coe_one, true_or_iff, Ne, not_false_iff, one_ne_zero]
· simp only [one_pow, ENNReal.coe_one, Ne, or_true_iff, ENNReal.one_ne_top, not_false_iff]
simp only [one_pow, one_mul, ENNReal.coe_one] at this
refine ge_of_tendsto this ?_
filter_upwards [self_mem_nhdsWithin] with _ ht
exact v.withDensity_le_mul hρ hs ht
· have :
Tendsto (fun t : ℝ≥0 => (t : ℝ≥0∞) * μ.withDensity (v.limRatioMeas hρ) s) (𝓝[>] 1)
(𝓝 ((1 : ℝ≥0∞) * μ.withDensity (v.limRatioMeas hρ) s)) := by
refine ENNReal.Tendsto.mul_const (ENNReal.tendsto_coe.2 nhdsWithin_le_nhds) ?_
simp only [ENNReal.coe_one, true_or_iff, Ne, not_false_iff, one_ne_zero]
simp only [one_mul, ENNReal.coe_one] at this
refine ge_of_tendsto this ?_
filter_upwards [self_mem_nhdsWithin] with _ ht
exact v.le_mul_withDensity hρ hs ht
#align vitali_family.with_density_lim_ratio_meas_eq VitaliFamily.withDensity_limRatioMeas_eq
/-- Weak version of the main theorem on differentiation of measures: given a Vitali family `v`
for a locally finite measure `μ`, and another locally finite measure `ρ`, then for `μ`-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 version assumes that `ρ` is absolutely continuous with respect to `μ`. The general version
without this superfluous assumption is `VitaliFamily.ae_tendsto_rnDeriv`.
-/
theorem ae_tendsto_rnDeriv_of_absolutelyContinuous :
∀ᵐ x ∂μ, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (ρ.rnDeriv μ x)) := by
have A : (μ.withDensity (v.limRatioMeas hρ)).rnDeriv μ =ᵐ[μ] v.limRatioMeas hρ :=
rnDeriv_withDensity μ (v.limRatioMeas_measurable hρ)
rw [v.withDensity_limRatioMeas_eq hρ] at A
filter_upwards [v.ae_tendsto_limRatioMeas hρ, A] with _ _ h'x
rwa [h'x]
#align vitali_family.ae_tendsto_rn_deriv_of_absolutely_continuous VitaliFamily.ae_tendsto_rnDeriv_of_absolutelyContinuous
end AbsolutelyContinuous
variable (ρ)
/-- Main theorem on differentiation of measures: given a Vitali family `v` for a locally finite
measure `μ`, and another locally finite measure `ρ`, then for `μ`-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`. -/
theorem ae_tendsto_rnDeriv :
∀ᵐ x ∂μ, Tendsto (fun a => ρ a / μ a) (v.filterAt x) (𝓝 (ρ.rnDeriv μ x)) := by
let t := μ.withDensity (ρ.rnDeriv μ)
have eq_add : ρ = ρ.singularPart μ + t := haveLebesgueDecomposition_add _ _
have A : ∀ᵐ x ∂μ, Tendsto (fun a => ρ.singularPart μ a / μ a) (v.filterAt x) (𝓝 0) :=
v.ae_eventually_measure_zero_of_singular (mutuallySingular_singularPart ρ μ)
have B : ∀ᵐ x ∂μ, t.rnDeriv μ x = ρ.rnDeriv μ x :=
rnDeriv_withDensity μ (measurable_rnDeriv ρ μ)
have C : ∀ᵐ x ∂μ, Tendsto (fun a => t a / μ a) (v.filterAt x) (𝓝 (t.rnDeriv μ x)) :=
v.ae_tendsto_rnDeriv_of_absolutelyContinuous (withDensity_absolutelyContinuous _ _)
filter_upwards [A, B, C] with _ Ax Bx Cx
convert Ax.add Cx using 1
· ext1 a
conv_lhs => rw [eq_add]
simp only [Pi.add_apply, coe_add, ENNReal.add_div]
· simp only [Bx, zero_add]
#align vitali_family.ae_tendsto_rn_deriv VitaliFamily.ae_tendsto_rnDeriv
/-! ### Lebesgue density points -/
/-- Given a measurable set `s`, then `μ (s ∩ a) / μ a` converges when `a` shrinks to a typical
point `x` along a Vitali family. The limit is `1` for `x ∈ s` and `0` for `x ∉ s`. This shows that
almost every point of `s` is a Lebesgue density point for `s`. A version for non-measurable sets
holds, but it only gives the first conclusion, see `ae_tendsto_measure_inter_div`. -/
theorem ae_tendsto_measure_inter_div_of_measurableSet {s : Set α} (hs : MeasurableSet s) :
∀ᵐ x ∂μ, Tendsto (fun a => μ (s ∩ a) / μ a) (v.filterAt x) (𝓝 (s.indicator 1 x)) := by
haveI : IsLocallyFiniteMeasure (μ.restrict s) :=
isLocallyFiniteMeasure_of_le restrict_le_self
filter_upwards [ae_tendsto_rnDeriv v (μ.restrict s), rnDeriv_restrict_self μ hs]
intro x hx h'x
simpa only [h'x, restrict_apply' hs, inter_comm] using hx
#align vitali_family.ae_tendsto_measure_inter_div_of_measurable_set VitaliFamily.ae_tendsto_measure_inter_div_of_measurableSet
/-- Given an arbitrary set `s`, then `μ (s ∩ a) / μ a` converges to `1` when `a` shrinks to a
typical point of `s` along a Vitali family. This shows that almost every point of `s` is a
Lebesgue density point for `s`. A stronger version for measurable sets is given
in `ae_tendsto_measure_inter_div_of_measurableSet`. -/
| Mathlib/MeasureTheory/Covering/Differentiation.lean | 746 | 764 | theorem ae_tendsto_measure_inter_div (s : Set α) :
∀ᵐ x ∂μ.restrict s, Tendsto (fun a => μ (s ∩ a) / μ a) (v.filterAt x) (𝓝 1) := by |
let t := toMeasurable μ s
have A :
∀ᵐ x ∂μ.restrict s,
Tendsto (fun a => μ (t ∩ a) / μ a) (v.filterAt x) (𝓝 (t.indicator 1 x)) := by
apply ae_mono restrict_le_self
apply ae_tendsto_measure_inter_div_of_measurableSet
exact measurableSet_toMeasurable _ _
have B : ∀ᵐ x ∂μ.restrict s, t.indicator 1 x = (1 : ℝ≥0∞) := by
refine ae_restrict_of_ae_restrict_of_subset (subset_toMeasurable μ s) ?_
filter_upwards [ae_restrict_mem (measurableSet_toMeasurable μ s)] with _ hx
simp only [hx, Pi.one_apply, indicator_of_mem]
filter_upwards [A, B] with x hx h'x
rw [h'x] at hx
apply hx.congr' _
filter_upwards [v.eventually_filterAt_measurableSet x] with _ ha
congr 1
exact measure_toMeasurable_inter_of_sFinite ha _
|
/-
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.Order.Antichain
import Mathlib.Order.UpperLower.Basic
import Mathlib.Order.Interval.Set.Basic
import Mathlib.Order.RelIso.Set
#align_import order.minimal from "leanprover-community/mathlib"@"59694bd07f0a39c5beccba34bd9f413a160782bf"
/-!
# Minimal/maximal elements of a set
This file defines minimal and maximal of a set with respect to an arbitrary relation.
## Main declarations
* `maximals r s`: Maximal elements of `s` with respect to `r`.
* `minimals r s`: Minimal elements of `s` with respect to `r`.
## TODO
Do we need a `Finset` version?
-/
open Function Set
variable {α : Type*} (r r₁ r₂ : α → α → Prop) (s t : Set α) (a b : α)
/-- Turns a set into an antichain by keeping only the "maximal" elements. -/
def maximals : Set α :=
{ a ∈ s | ∀ ⦃b⦄, b ∈ s → r a b → r b a }
#align maximals maximals
/-- Turns a set into an antichain by keeping only the "minimal" elements. -/
def minimals : Set α :=
{ a ∈ s | ∀ ⦃b⦄, b ∈ s → r b a → r a b }
#align minimals minimals
theorem maximals_subset : maximals r s ⊆ s :=
sep_subset _ _
#align maximals_subset maximals_subset
theorem minimals_subset : minimals r s ⊆ s :=
sep_subset _ _
#align minimals_subset minimals_subset
@[simp]
theorem maximals_empty : maximals r ∅ = ∅ :=
sep_empty _
#align maximals_empty maximals_empty
@[simp]
theorem minimals_empty : minimals r ∅ = ∅ :=
sep_empty _
#align minimals_empty minimals_empty
@[simp]
theorem maximals_singleton : maximals r {a} = {a} :=
(maximals_subset _ _).antisymm <|
singleton_subset_iff.2 <|
⟨rfl, by
rintro b (rfl : b = a)
exact id⟩
#align maximals_singleton maximals_singleton
@[simp]
theorem minimals_singleton : minimals r {a} = {a} :=
maximals_singleton _ _
#align minimals_singleton minimals_singleton
theorem maximals_swap : maximals (swap r) s = minimals r s :=
rfl
#align maximals_swap maximals_swap
theorem minimals_swap : minimals (swap r) s = maximals r s :=
rfl
#align minimals_swap minimals_swap
section IsAntisymm
variable {r s t a b} [IsAntisymm α r]
theorem eq_of_mem_maximals (ha : a ∈ maximals r s) (hb : b ∈ s) (h : r a b) : a = b :=
antisymm h <| ha.2 hb h
#align eq_of_mem_maximals eq_of_mem_maximals
theorem eq_of_mem_minimals (ha : a ∈ minimals r s) (hb : b ∈ s) (h : r b a) : a = b :=
antisymm (ha.2 hb h) h
#align eq_of_mem_minimals eq_of_mem_minimals
set_option autoImplicit true
theorem mem_maximals_iff : x ∈ maximals r s ↔ x ∈ s ∧ ∀ ⦃y⦄, y ∈ s → r x y → x = y := by
simp only [maximals, Set.mem_sep_iff, and_congr_right_iff]
refine fun _ ↦ ⟨fun h y hys hxy ↦ antisymm hxy (h hys hxy), fun h y hys hxy ↦ ?_⟩
convert hxy <;> rw [h hys hxy]
theorem mem_maximals_setOf_iff : x ∈ maximals r (setOf P) ↔ P x ∧ ∀ ⦃y⦄, P y → r x y → x = y :=
mem_maximals_iff
theorem mem_minimals_iff : x ∈ minimals r s ↔ x ∈ s ∧ ∀ ⦃y⦄, y ∈ s → r y x → x = y :=
@mem_maximals_iff _ _ _ (IsAntisymm.swap r) _
theorem mem_minimals_setOf_iff : x ∈ minimals r (setOf P) ↔ P x ∧ ∀ ⦃y⦄, P y → r y x → x = y :=
mem_minimals_iff
/-- This theorem can't be used to rewrite without specifying `rlt`, since `rlt` would have to be
guessed. See `mem_minimals_iff_forall_ssubset_not_mem` and `mem_minimals_iff_forall_lt_not_mem`
for `⊆` and `≤` versions. -/
theorem mem_minimals_iff_forall_lt_not_mem' (rlt : α → α → Prop) [IsNonstrictStrictOrder α r rlt] :
x ∈ minimals r s ↔ x ∈ s ∧ ∀ ⦃y⦄, rlt y x → y ∉ s := by
simp [minimals, right_iff_left_not_left_of r rlt, not_imp_not, imp.swap (a := _ ∈ _)]
theorem mem_maximals_iff_forall_lt_not_mem' (rlt : α → α → Prop) [IsNonstrictStrictOrder α r rlt] :
x ∈ maximals r s ↔ x ∈ s ∧ ∀ ⦃y⦄, rlt x y → y ∉ s := by
simp [maximals, right_iff_left_not_left_of r rlt, not_imp_not, imp.swap (a := _ ∈ _)]
theorem minimals_eq_minimals_of_subset_of_forall [IsTrans α r] (hts : t ⊆ s)
(h : ∀ x ∈ s, ∃ y ∈ t, r y x) : minimals r s = minimals r t := by
refine Set.ext fun a ↦ ⟨fun ⟨has, hmin⟩ ↦ ⟨?_,fun b hbt ↦ hmin (hts hbt)⟩,
fun ⟨hat, hmin⟩ ↦ ⟨hts hat, fun b hbs hba ↦ ?_⟩⟩
· obtain ⟨a', ha', haa'⟩ := h _ has
rwa [antisymm (hmin (hts ha') haa') haa']
obtain ⟨b', hb't, hb'b⟩ := h b hbs
rwa [antisymm (hmin hb't (Trans.trans hb'b hba)) (Trans.trans hb'b hba)]
theorem maximals_eq_maximals_of_subset_of_forall [IsTrans α r] (hts : t ⊆ s)
(h : ∀ x ∈ s, ∃ y ∈ t, r x y) : maximals r s = maximals r t :=
@minimals_eq_minimals_of_subset_of_forall _ _ _ _ (IsAntisymm.swap r) (IsTrans.swap r) hts h
variable (r s)
theorem maximals_antichain : IsAntichain r (maximals r s) := fun _a ha _b hb hab h =>
hab <| eq_of_mem_maximals ha hb.1 h
#align maximals_antichain maximals_antichain
theorem minimals_antichain : IsAntichain r (minimals r s) :=
haveI := IsAntisymm.swap r
(maximals_antichain _ _).swap
#align minimals_antichain minimals_antichain
end IsAntisymm
set_option autoImplicit true
theorem mem_minimals_iff_forall_ssubset_not_mem (s : Set (Set α)) :
x ∈ minimals (· ⊆ ·) s ↔ x ∈ s ∧ ∀ ⦃y⦄, y ⊂ x → y ∉ s :=
mem_minimals_iff_forall_lt_not_mem' (· ⊂ ·)
theorem mem_minimals_iff_forall_lt_not_mem [PartialOrder α] {s : Set α} :
x ∈ minimals (· ≤ ·) s ↔ x ∈ s ∧ ∀ ⦃y⦄, y < x → y ∉ s :=
mem_minimals_iff_forall_lt_not_mem' (· < ·)
theorem mem_maximals_iff_forall_ssubset_not_mem {s : Set (Set α)} :
x ∈ maximals (· ⊆ ·) s ↔ x ∈ s ∧ ∀ ⦃y⦄, x ⊂ y → y ∉ s :=
mem_maximals_iff_forall_lt_not_mem' (· ⊂ ·)
theorem mem_maximals_iff_forall_lt_not_mem [PartialOrder α] {s : Set α} :
x ∈ maximals (· ≤ ·) s ↔ x ∈ s ∧ ∀ ⦃y⦄, x < y → y ∉ s :=
mem_maximals_iff_forall_lt_not_mem' (· < ·)
-- Porting note (#10756): new theorem
theorem maximals_of_symm [IsSymm α r] : maximals r s = s :=
sep_eq_self_iff_mem_true.2 fun _ _ _ _ => symm
-- Porting note (#10756): new theorem
theorem minimals_of_symm [IsSymm α r] : minimals r s = s :=
sep_eq_self_iff_mem_true.2 fun _ _ _ _ => symm
| Mathlib/Order/Minimal.lean | 173 | 174 | theorem maximals_eq_minimals [IsSymm α r] : maximals r s = minimals r s := by |
rw [minimals_of_symm, maximals_of_symm]
|
/-
Copyright (c) 2020 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Yury Kudryashov
-/
import Mathlib.MeasureTheory.Integral.IntegrableOn
import Mathlib.MeasureTheory.Integral.Bochner
import Mathlib.MeasureTheory.Function.LocallyIntegrable
import Mathlib.Topology.MetricSpace.ThickenedIndicator
import Mathlib.Topology.ContinuousFunction.Compact
import Mathlib.Analysis.NormedSpace.HahnBanach.SeparatingDual
#align_import measure_theory.integral.setIntegral from "leanprover-community/mathlib"@"24e0c85412ff6adbeca08022c25ba4876eedf37a"
/-!
# Set integral
In this file we prove some properties of `∫ x in s, f x ∂μ`. Recall that this notation
is defined as `∫ x, f x ∂(μ.restrict s)`. In `integral_indicator` we prove that for a measurable
function `f` and a measurable set `s` this definition coincides with another natural definition:
`∫ x, indicator s f x ∂μ = ∫ x in s, f x ∂μ`, where `indicator s f x` is equal to `f x` for `x ∈ s`
and is zero otherwise.
Since `∫ x in s, f x ∂μ` is a notation, one can rewrite or apply any theorem about `∫ x, f x ∂μ`
directly. In this file we prove some theorems about dependence of `∫ x in s, f x ∂μ` on `s`, e.g.
`integral_union`, `integral_empty`, `integral_univ`.
We use the property `IntegrableOn f s μ := Integrable f (μ.restrict s)`, defined in
`MeasureTheory.IntegrableOn`. We also defined in that same file a predicate
`IntegrableAtFilter (f : X → E) (l : Filter X) (μ : Measure X)` saying that `f` is integrable at
some set `s ∈ l`.
Finally, we prove a version of the
[Fundamental theorem of calculus](https://en.wikipedia.org/wiki/Fundamental_theorem_of_calculus)
for set integral, see `Filter.Tendsto.integral_sub_linear_isLittleO_ae` and its corollaries.
Namely, consider a measurably generated filter `l`, a measure `μ` finite at this filter, and
a function `f` that has a finite limit `c` at `l ⊓ ae μ`. Then `∫ x in s, f x ∂μ = μ s • c + o(μ s)`
as `s` tends to `l.smallSets`, i.e. for any `ε>0` there exists `t ∈ l` such that
`‖∫ x in s, f x ∂μ - μ s • c‖ ≤ ε * μ s` whenever `s ⊆ t`. We also formulate a version of this
theorem for a locally finite measure `μ` and a function `f` continuous at a point `a`.
## Notation
We provide the following notations for expressing the integral of a function on a set :
* `∫ x in s, f x ∂μ` is `MeasureTheory.integral (μ.restrict s) f`
* `∫ x in s, f x` is `∫ x in s, f x ∂volume`
Note that the set notations are defined in the file `Mathlib/MeasureTheory/Integral/Bochner.lean`,
but we reference them here because all theorems about set integrals are in this file.
-/
assert_not_exists InnerProductSpace
noncomputable section
open Set Filter TopologicalSpace MeasureTheory Function RCLike
open scoped Classical Topology ENNReal NNReal
variable {X Y E F : Type*} [MeasurableSpace X]
namespace MeasureTheory
section NormedAddCommGroup
variable [NormedAddCommGroup E] [NormedSpace ℝ E]
{f g : X → E} {s t : Set X} {μ ν : Measure X} {l l' : Filter X}
theorem setIntegral_congr_ae₀ (hs : NullMeasurableSet s μ) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ :=
integral_congr_ae ((ae_restrict_iff'₀ hs).2 h)
#align measure_theory.set_integral_congr_ae₀ MeasureTheory.setIntegral_congr_ae₀
@[deprecated (since := "2024-04-17")]
alias set_integral_congr_ae₀ := setIntegral_congr_ae₀
theorem setIntegral_congr_ae (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ :=
integral_congr_ae ((ae_restrict_iff' hs).2 h)
#align measure_theory.set_integral_congr_ae MeasureTheory.setIntegral_congr_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_congr_ae := setIntegral_congr_ae
theorem setIntegral_congr₀ (hs : NullMeasurableSet s μ) (h : EqOn f g s) :
∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ :=
setIntegral_congr_ae₀ hs <| eventually_of_forall h
#align measure_theory.set_integral_congr₀ MeasureTheory.setIntegral_congr₀
@[deprecated (since := "2024-04-17")]
alias set_integral_congr₀ := setIntegral_congr₀
theorem setIntegral_congr (hs : MeasurableSet s) (h : EqOn f g s) :
∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ :=
setIntegral_congr_ae hs <| eventually_of_forall h
#align measure_theory.set_integral_congr MeasureTheory.setIntegral_congr
@[deprecated (since := "2024-04-17")]
alias set_integral_congr := setIntegral_congr
theorem setIntegral_congr_set_ae (hst : s =ᵐ[μ] t) : ∫ x in s, f x ∂μ = ∫ x in t, f x ∂μ := by
rw [Measure.restrict_congr_set hst]
#align measure_theory.set_integral_congr_set_ae MeasureTheory.setIntegral_congr_set_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_congr_set_ae := setIntegral_congr_set_ae
theorem integral_union_ae (hst : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hfs : IntegrableOn f s μ) (hft : IntegrableOn f t μ) :
∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ + ∫ x in t, f x ∂μ := by
simp only [IntegrableOn, Measure.restrict_union₀ hst ht, integral_add_measure hfs hft]
#align measure_theory.integral_union_ae MeasureTheory.integral_union_ae
theorem integral_union (hst : Disjoint s t) (ht : MeasurableSet t) (hfs : IntegrableOn f s μ)
(hft : IntegrableOn f t μ) : ∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ + ∫ x in t, f x ∂μ :=
integral_union_ae hst.aedisjoint ht.nullMeasurableSet hfs hft
#align measure_theory.integral_union MeasureTheory.integral_union
theorem integral_diff (ht : MeasurableSet t) (hfs : IntegrableOn f s μ) (hts : t ⊆ s) :
∫ x in s \ t, f x ∂μ = ∫ x in s, f x ∂μ - ∫ x in t, f x ∂μ := by
rw [eq_sub_iff_add_eq, ← integral_union, diff_union_of_subset hts]
exacts [disjoint_sdiff_self_left, ht, hfs.mono_set diff_subset, hfs.mono_set hts]
#align measure_theory.integral_diff MeasureTheory.integral_diff
theorem integral_inter_add_diff₀ (ht : NullMeasurableSet t μ) (hfs : IntegrableOn f s μ) :
∫ x in s ∩ t, f x ∂μ + ∫ x in s \ t, f x ∂μ = ∫ x in s, f x ∂μ := by
rw [← Measure.restrict_inter_add_diff₀ s ht, integral_add_measure]
· exact Integrable.mono_measure hfs (Measure.restrict_mono inter_subset_left le_rfl)
· exact Integrable.mono_measure hfs (Measure.restrict_mono diff_subset le_rfl)
#align measure_theory.integral_inter_add_diff₀ MeasureTheory.integral_inter_add_diff₀
theorem integral_inter_add_diff (ht : MeasurableSet t) (hfs : IntegrableOn f s μ) :
∫ x in s ∩ t, f x ∂μ + ∫ x in s \ t, f x ∂μ = ∫ x in s, f x ∂μ :=
integral_inter_add_diff₀ ht.nullMeasurableSet hfs
#align measure_theory.integral_inter_add_diff MeasureTheory.integral_inter_add_diff
theorem integral_finset_biUnion {ι : Type*} (t : Finset ι) {s : ι → Set X}
(hs : ∀ i ∈ t, MeasurableSet (s i)) (h's : Set.Pairwise (↑t) (Disjoint on s))
(hf : ∀ i ∈ t, IntegrableOn f (s i) μ) :
∫ x in ⋃ i ∈ t, s i, f x ∂μ = ∑ i ∈ t, ∫ x in s i, f x ∂μ := by
induction' t using Finset.induction_on with a t hat IH hs h's
· simp
· simp only [Finset.coe_insert, Finset.forall_mem_insert, Set.pairwise_insert,
Finset.set_biUnion_insert] at hs hf h's ⊢
rw [integral_union _ _ hf.1 (integrableOn_finset_iUnion.2 hf.2)]
· rw [Finset.sum_insert hat, IH hs.2 h's.1 hf.2]
· simp only [disjoint_iUnion_right]
exact fun i hi => (h's.2 i hi (ne_of_mem_of_not_mem hi hat).symm).1
· exact Finset.measurableSet_biUnion _ hs.2
#align measure_theory.integral_finset_bUnion MeasureTheory.integral_finset_biUnion
theorem integral_fintype_iUnion {ι : Type*} [Fintype ι] {s : ι → Set X}
(hs : ∀ i, MeasurableSet (s i)) (h's : Pairwise (Disjoint on s))
(hf : ∀ i, IntegrableOn f (s i) μ) : ∫ x in ⋃ i, s i, f x ∂μ = ∑ i, ∫ x in s i, f x ∂μ := by
convert integral_finset_biUnion Finset.univ (fun i _ => hs i) _ fun i _ => hf i
· simp
· simp [pairwise_univ, h's]
#align measure_theory.integral_fintype_Union MeasureTheory.integral_fintype_iUnion
theorem integral_empty : ∫ x in ∅, f x ∂μ = 0 := by
rw [Measure.restrict_empty, integral_zero_measure]
#align measure_theory.integral_empty MeasureTheory.integral_empty
theorem integral_univ : ∫ x in univ, f x ∂μ = ∫ x, f x ∂μ := by rw [Measure.restrict_univ]
#align measure_theory.integral_univ MeasureTheory.integral_univ
theorem integral_add_compl₀ (hs : NullMeasurableSet s μ) (hfi : Integrable f μ) :
∫ x in s, f x ∂μ + ∫ x in sᶜ, f x ∂μ = ∫ x, f x ∂μ := by
rw [
← integral_union_ae disjoint_compl_right.aedisjoint hs.compl hfi.integrableOn hfi.integrableOn,
union_compl_self, integral_univ]
#align measure_theory.integral_add_compl₀ MeasureTheory.integral_add_compl₀
theorem integral_add_compl (hs : MeasurableSet s) (hfi : Integrable f μ) :
∫ x in s, f x ∂μ + ∫ x in sᶜ, f x ∂μ = ∫ x, f x ∂μ :=
integral_add_compl₀ hs.nullMeasurableSet hfi
#align measure_theory.integral_add_compl MeasureTheory.integral_add_compl
/-- For a function `f` and a measurable set `s`, the integral of `indicator s f`
over the whole space is equal to `∫ x in s, f x ∂μ` defined as `∫ x, f x ∂(μ.restrict s)`. -/
theorem integral_indicator (hs : MeasurableSet s) :
∫ x, indicator s f x ∂μ = ∫ x in s, f x ∂μ := by
by_cases hfi : IntegrableOn f s μ; swap
· rw [integral_undef hfi, integral_undef]
rwa [integrable_indicator_iff hs]
calc
∫ x, indicator s f x ∂μ = ∫ x in s, indicator s f x ∂μ + ∫ x in sᶜ, indicator s f x ∂μ :=
(integral_add_compl hs (hfi.integrable_indicator hs)).symm
_ = ∫ x in s, f x ∂μ + ∫ x in sᶜ, 0 ∂μ :=
(congr_arg₂ (· + ·) (integral_congr_ae (indicator_ae_eq_restrict hs))
(integral_congr_ae (indicator_ae_eq_restrict_compl hs)))
_ = ∫ x in s, f x ∂μ := by simp
#align measure_theory.integral_indicator MeasureTheory.integral_indicator
theorem setIntegral_indicator (ht : MeasurableSet t) :
∫ x in s, t.indicator f x ∂μ = ∫ x in s ∩ t, f x ∂μ := by
rw [integral_indicator ht, Measure.restrict_restrict ht, Set.inter_comm]
#align measure_theory.set_integral_indicator MeasureTheory.setIntegral_indicator
@[deprecated (since := "2024-04-17")]
alias set_integral_indicator := setIntegral_indicator
theorem ofReal_setIntegral_one_of_measure_ne_top {X : Type*} {m : MeasurableSpace X}
{μ : Measure X} {s : Set X} (hs : μ s ≠ ∞) : ENNReal.ofReal (∫ _ in s, (1 : ℝ) ∂μ) = μ s :=
calc
ENNReal.ofReal (∫ _ in s, (1 : ℝ) ∂μ) = ENNReal.ofReal (∫ _ in s, ‖(1 : ℝ)‖ ∂μ) := by
simp only [norm_one]
_ = ∫⁻ _ in s, 1 ∂μ := by
rw [ofReal_integral_norm_eq_lintegral_nnnorm (integrableOn_const.2 (Or.inr hs.lt_top))]
simp only [nnnorm_one, ENNReal.coe_one]
_ = μ s := set_lintegral_one _
#align measure_theory.of_real_set_integral_one_of_measure_ne_top MeasureTheory.ofReal_setIntegral_one_of_measure_ne_top
@[deprecated (since := "2024-04-17")]
alias ofReal_set_integral_one_of_measure_ne_top := ofReal_setIntegral_one_of_measure_ne_top
theorem ofReal_setIntegral_one {X : Type*} {_ : MeasurableSpace X} (μ : Measure X)
[IsFiniteMeasure μ] (s : Set X) : ENNReal.ofReal (∫ _ in s, (1 : ℝ) ∂μ) = μ s :=
ofReal_setIntegral_one_of_measure_ne_top (measure_ne_top μ s)
#align measure_theory.of_real_set_integral_one MeasureTheory.ofReal_setIntegral_one
@[deprecated (since := "2024-04-17")]
alias ofReal_set_integral_one := ofReal_setIntegral_one
theorem integral_piecewise [DecidablePred (· ∈ s)] (hs : MeasurableSet s) (hf : IntegrableOn f s μ)
(hg : IntegrableOn g sᶜ μ) :
∫ x, s.piecewise f g x ∂μ = ∫ x in s, f x ∂μ + ∫ x in sᶜ, g x ∂μ := by
rw [← Set.indicator_add_compl_eq_piecewise,
integral_add' (hf.integrable_indicator hs) (hg.integrable_indicator hs.compl),
integral_indicator hs, integral_indicator hs.compl]
#align measure_theory.integral_piecewise MeasureTheory.integral_piecewise
theorem tendsto_setIntegral_of_monotone {ι : Type*} [Countable ι] [SemilatticeSup ι]
{s : ι → Set X} (hsm : ∀ i, MeasurableSet (s i)) (h_mono : Monotone s)
(hfi : IntegrableOn f (⋃ n, s n) μ) :
Tendsto (fun i => ∫ x in s i, f x ∂μ) atTop (𝓝 (∫ x in ⋃ n, s n, f x ∂μ)) := by
have hfi' : ∫⁻ x in ⋃ n, s n, ‖f x‖₊ ∂μ < ∞ := hfi.2
set S := ⋃ i, s i
have hSm : MeasurableSet S := MeasurableSet.iUnion hsm
have hsub : ∀ {i}, s i ⊆ S := @(subset_iUnion s)
rw [← withDensity_apply _ hSm] at hfi'
set ν := μ.withDensity fun x => ‖f x‖₊ with hν
refine Metric.nhds_basis_closedBall.tendsto_right_iff.2 fun ε ε0 => ?_
lift ε to ℝ≥0 using ε0.le
have : ∀ᶠ i in atTop, ν (s i) ∈ Icc (ν S - ε) (ν S + ε) :=
tendsto_measure_iUnion h_mono (ENNReal.Icc_mem_nhds hfi'.ne (ENNReal.coe_pos.2 ε0).ne')
filter_upwards [this] with i hi
rw [mem_closedBall_iff_norm', ← integral_diff (hsm i) hfi hsub, ← coe_nnnorm, NNReal.coe_le_coe, ←
ENNReal.coe_le_coe]
refine (ennnorm_integral_le_lintegral_ennnorm _).trans ?_
rw [← withDensity_apply _ (hSm.diff (hsm _)), ← hν, measure_diff hsub (hsm _)]
exacts [tsub_le_iff_tsub_le.mp hi.1,
(hi.2.trans_lt <| ENNReal.add_lt_top.2 ⟨hfi', ENNReal.coe_lt_top⟩).ne]
#align measure_theory.tendsto_set_integral_of_monotone MeasureTheory.tendsto_setIntegral_of_monotone
@[deprecated (since := "2024-04-17")]
alias tendsto_set_integral_of_monotone := tendsto_setIntegral_of_monotone
theorem tendsto_setIntegral_of_antitone {ι : Type*} [Countable ι] [SemilatticeSup ι]
{s : ι → Set X} (hsm : ∀ i, MeasurableSet (s i)) (h_anti : Antitone s)
(hfi : ∃ i, IntegrableOn f (s i) μ) :
Tendsto (fun i ↦ ∫ x in s i, f x ∂μ) atTop (𝓝 (∫ x in ⋂ n, s n, f x ∂μ)) := by
set S := ⋂ i, s i
have hSm : MeasurableSet S := MeasurableSet.iInter hsm
have hsub i : S ⊆ s i := iInter_subset _ _
set ν := μ.withDensity fun x => ‖f x‖₊ with hν
refine Metric.nhds_basis_closedBall.tendsto_right_iff.2 fun ε ε0 => ?_
lift ε to ℝ≥0 using ε0.le
rcases hfi with ⟨i₀, hi₀⟩
have νi₀ : ν (s i₀) ≠ ∞ := by
simpa [hsm i₀, ν, ENNReal.ofReal, norm_toNNReal] using hi₀.norm.lintegral_lt_top.ne
have νS : ν S ≠ ∞ := ((measure_mono (hsub i₀)).trans_lt νi₀.lt_top).ne
have : ∀ᶠ i in atTop, ν (s i) ∈ Icc (ν S - ε) (ν S + ε) := by
apply tendsto_measure_iInter hsm h_anti ⟨i₀, νi₀⟩
apply ENNReal.Icc_mem_nhds νS (ENNReal.coe_pos.2 ε0).ne'
filter_upwards [this, Ici_mem_atTop i₀] with i hi h'i
rw [mem_closedBall_iff_norm, ← integral_diff hSm (hi₀.mono_set (h_anti h'i)) (hsub i),
← coe_nnnorm, NNReal.coe_le_coe, ← ENNReal.coe_le_coe]
refine (ennnorm_integral_le_lintegral_ennnorm _).trans ?_
rw [← withDensity_apply _ ((hsm _).diff hSm), ← hν, measure_diff (hsub i) hSm νS]
exact tsub_le_iff_left.2 hi.2
@[deprecated (since := "2024-04-17")]
alias tendsto_set_integral_of_antitone := tendsto_setIntegral_of_antitone
theorem hasSum_integral_iUnion_ae {ι : Type*} [Countable ι] {s : ι → Set X}
(hm : ∀ i, NullMeasurableSet (s i) μ) (hd : Pairwise (AEDisjoint μ on s))
(hfi : IntegrableOn f (⋃ i, s i) μ) :
HasSum (fun n => ∫ x in s n, f x ∂μ) (∫ x in ⋃ n, s n, f x ∂μ) := by
simp only [IntegrableOn, Measure.restrict_iUnion_ae hd hm] at hfi ⊢
exact hasSum_integral_measure hfi
#align measure_theory.has_sum_integral_Union_ae MeasureTheory.hasSum_integral_iUnion_ae
theorem hasSum_integral_iUnion {ι : Type*} [Countable ι] {s : ι → Set X}
(hm : ∀ i, MeasurableSet (s i)) (hd : Pairwise (Disjoint on s))
(hfi : IntegrableOn f (⋃ i, s i) μ) :
HasSum (fun n => ∫ x in s n, f x ∂μ) (∫ x in ⋃ n, s n, f x ∂μ) :=
hasSum_integral_iUnion_ae (fun i => (hm i).nullMeasurableSet) (hd.mono fun _ _ h => h.aedisjoint)
hfi
#align measure_theory.has_sum_integral_Union MeasureTheory.hasSum_integral_iUnion
theorem integral_iUnion {ι : Type*} [Countable ι] {s : ι → Set X} (hm : ∀ i, MeasurableSet (s i))
(hd : Pairwise (Disjoint on s)) (hfi : IntegrableOn f (⋃ i, s i) μ) :
∫ x in ⋃ n, s n, f x ∂μ = ∑' n, ∫ x in s n, f x ∂μ :=
(HasSum.tsum_eq (hasSum_integral_iUnion hm hd hfi)).symm
#align measure_theory.integral_Union MeasureTheory.integral_iUnion
theorem integral_iUnion_ae {ι : Type*} [Countable ι] {s : ι → Set X}
(hm : ∀ i, NullMeasurableSet (s i) μ) (hd : Pairwise (AEDisjoint μ on s))
(hfi : IntegrableOn f (⋃ i, s i) μ) : ∫ x in ⋃ n, s n, f x ∂μ = ∑' n, ∫ x in s n, f x ∂μ :=
(HasSum.tsum_eq (hasSum_integral_iUnion_ae hm hd hfi)).symm
#align measure_theory.integral_Union_ae MeasureTheory.integral_iUnion_ae
theorem setIntegral_eq_zero_of_ae_eq_zero (ht_eq : ∀ᵐ x ∂μ, x ∈ t → f x = 0) :
∫ x in t, f x ∂μ = 0 := by
by_cases hf : AEStronglyMeasurable f (μ.restrict t); swap
· rw [integral_undef]
contrapose! hf
exact hf.1
have : ∫ x in t, hf.mk f x ∂μ = 0 := by
refine integral_eq_zero_of_ae ?_
rw [EventuallyEq,
ae_restrict_iff (hf.stronglyMeasurable_mk.measurableSet_eq_fun stronglyMeasurable_zero)]
filter_upwards [ae_imp_of_ae_restrict hf.ae_eq_mk, ht_eq] with x hx h'x h''x
rw [← hx h''x]
exact h'x h''x
rw [← this]
exact integral_congr_ae hf.ae_eq_mk
#align measure_theory.set_integral_eq_zero_of_ae_eq_zero MeasureTheory.setIntegral_eq_zero_of_ae_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_zero_of_ae_eq_zero := setIntegral_eq_zero_of_ae_eq_zero
theorem setIntegral_eq_zero_of_forall_eq_zero (ht_eq : ∀ x ∈ t, f x = 0) :
∫ x in t, f x ∂μ = 0 :=
setIntegral_eq_zero_of_ae_eq_zero (eventually_of_forall ht_eq)
#align measure_theory.set_integral_eq_zero_of_forall_eq_zero MeasureTheory.setIntegral_eq_zero_of_forall_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_zero_of_forall_eq_zero := setIntegral_eq_zero_of_forall_eq_zero
theorem integral_union_eq_left_of_ae_aux (ht_eq : ∀ᵐ x ∂μ.restrict t, f x = 0)
(haux : StronglyMeasurable f) (H : IntegrableOn f (s ∪ t) μ) :
∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ := by
let k := f ⁻¹' {0}
have hk : MeasurableSet k := by borelize E; exact haux.measurable (measurableSet_singleton _)
have h's : IntegrableOn f s μ := H.mono subset_union_left le_rfl
have A : ∀ u : Set X, ∫ x in u ∩ k, f x ∂μ = 0 := fun u =>
setIntegral_eq_zero_of_forall_eq_zero fun x hx => hx.2
rw [← integral_inter_add_diff hk h's, ← integral_inter_add_diff hk H, A, A, zero_add, zero_add,
union_diff_distrib, union_comm]
apply setIntegral_congr_set_ae
rw [union_ae_eq_right]
apply measure_mono_null diff_subset
rw [measure_zero_iff_ae_nmem]
filter_upwards [ae_imp_of_ae_restrict ht_eq] with x hx h'x using h'x.2 (hx h'x.1)
#align measure_theory.integral_union_eq_left_of_ae_aux MeasureTheory.integral_union_eq_left_of_ae_aux
theorem integral_union_eq_left_of_ae (ht_eq : ∀ᵐ x ∂μ.restrict t, f x = 0) :
∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ := by
have ht : IntegrableOn f t μ := by apply integrableOn_zero.congr_fun_ae; symm; exact ht_eq
by_cases H : IntegrableOn f (s ∪ t) μ; swap
· rw [integral_undef H, integral_undef]; simpa [integrableOn_union, ht] using H
let f' := H.1.mk f
calc
∫ x : X in s ∪ t, f x ∂μ = ∫ x : X in s ∪ t, f' x ∂μ := integral_congr_ae H.1.ae_eq_mk
_ = ∫ x in s, f' x ∂μ := by
apply
integral_union_eq_left_of_ae_aux _ H.1.stronglyMeasurable_mk (H.congr_fun_ae H.1.ae_eq_mk)
filter_upwards [ht_eq,
ae_mono (Measure.restrict_mono subset_union_right le_rfl) H.1.ae_eq_mk] with x hx h'x
rw [← h'x, hx]
_ = ∫ x in s, f x ∂μ :=
integral_congr_ae
(ae_mono (Measure.restrict_mono subset_union_left le_rfl) H.1.ae_eq_mk.symm)
#align measure_theory.integral_union_eq_left_of_ae MeasureTheory.integral_union_eq_left_of_ae
theorem integral_union_eq_left_of_forall₀ {f : X → E} (ht : NullMeasurableSet t μ)
(ht_eq : ∀ x ∈ t, f x = 0) : ∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ :=
integral_union_eq_left_of_ae ((ae_restrict_iff'₀ ht).2 (eventually_of_forall ht_eq))
#align measure_theory.integral_union_eq_left_of_forall₀ MeasureTheory.integral_union_eq_left_of_forall₀
theorem integral_union_eq_left_of_forall {f : X → E} (ht : MeasurableSet t)
(ht_eq : ∀ x ∈ t, f x = 0) : ∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ :=
integral_union_eq_left_of_forall₀ ht.nullMeasurableSet ht_eq
#align measure_theory.integral_union_eq_left_of_forall MeasureTheory.integral_union_eq_left_of_forall
theorem setIntegral_eq_of_subset_of_ae_diff_eq_zero_aux (hts : s ⊆ t)
(h't : ∀ᵐ x ∂μ, x ∈ t \ s → f x = 0) (haux : StronglyMeasurable f)
(h'aux : IntegrableOn f t μ) : ∫ x in t, f x ∂μ = ∫ x in s, f x ∂μ := by
let k := f ⁻¹' {0}
have hk : MeasurableSet k := by borelize E; exact haux.measurable (measurableSet_singleton _)
calc
∫ x in t, f x ∂μ = ∫ x in t ∩ k, f x ∂μ + ∫ x in t \ k, f x ∂μ := by
rw [integral_inter_add_diff hk h'aux]
_ = ∫ x in t \ k, f x ∂μ := by
rw [setIntegral_eq_zero_of_forall_eq_zero fun x hx => ?_, zero_add]; exact hx.2
_ = ∫ x in s \ k, f x ∂μ := by
apply setIntegral_congr_set_ae
filter_upwards [h't] with x hx
change (x ∈ t \ k) = (x ∈ s \ k)
simp only [mem_preimage, mem_singleton_iff, eq_iff_iff, and_congr_left_iff, mem_diff]
intro h'x
by_cases xs : x ∈ s
· simp only [xs, hts xs]
· simp only [xs, iff_false_iff]
intro xt
exact h'x (hx ⟨xt, xs⟩)
_ = ∫ x in s ∩ k, f x ∂μ + ∫ x in s \ k, f x ∂μ := by
have : ∀ x ∈ s ∩ k, f x = 0 := fun x hx => hx.2
rw [setIntegral_eq_zero_of_forall_eq_zero this, zero_add]
_ = ∫ x in s, f x ∂μ := by rw [integral_inter_add_diff hk (h'aux.mono hts le_rfl)]
#align measure_theory.set_integral_eq_of_subset_of_ae_diff_eq_zero_aux MeasureTheory.setIntegral_eq_of_subset_of_ae_diff_eq_zero_aux
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_of_subset_of_ae_diff_eq_zero_aux :=
setIntegral_eq_of_subset_of_ae_diff_eq_zero_aux
/-- If a function vanishes almost everywhere on `t \ s` with `s ⊆ t`, then its integrals on `s`
and `t` coincide if `t` is null-measurable. -/
theorem setIntegral_eq_of_subset_of_ae_diff_eq_zero (ht : NullMeasurableSet t μ) (hts : s ⊆ t)
(h't : ∀ᵐ x ∂μ, x ∈ t \ s → f x = 0) : ∫ x in t, f x ∂μ = ∫ x in s, f x ∂μ := by
by_cases h : IntegrableOn f t μ; swap
· have : ¬IntegrableOn f s μ := fun H => h (H.of_ae_diff_eq_zero ht h't)
rw [integral_undef h, integral_undef this]
let f' := h.1.mk f
calc
∫ x in t, f x ∂μ = ∫ x in t, f' x ∂μ := integral_congr_ae h.1.ae_eq_mk
_ = ∫ x in s, f' x ∂μ := by
apply
setIntegral_eq_of_subset_of_ae_diff_eq_zero_aux hts _ h.1.stronglyMeasurable_mk
(h.congr h.1.ae_eq_mk)
filter_upwards [h't, ae_imp_of_ae_restrict h.1.ae_eq_mk] with x hx h'x h''x
rw [← h'x h''x.1, hx h''x]
_ = ∫ x in s, f x ∂μ := by
apply integral_congr_ae
apply ae_restrict_of_ae_restrict_of_subset hts
exact h.1.ae_eq_mk.symm
#align measure_theory.set_integral_eq_of_subset_of_ae_diff_eq_zero MeasureTheory.setIntegral_eq_of_subset_of_ae_diff_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_of_subset_of_ae_diff_eq_zero := setIntegral_eq_of_subset_of_ae_diff_eq_zero
/-- If a function vanishes on `t \ s` with `s ⊆ t`, then its integrals on `s`
and `t` coincide if `t` is measurable. -/
theorem setIntegral_eq_of_subset_of_forall_diff_eq_zero (ht : MeasurableSet t) (hts : s ⊆ t)
(h't : ∀ x ∈ t \ s, f x = 0) : ∫ x in t, f x ∂μ = ∫ x in s, f x ∂μ :=
setIntegral_eq_of_subset_of_ae_diff_eq_zero ht.nullMeasurableSet hts
(eventually_of_forall fun x hx => h't x hx)
#align measure_theory.set_integral_eq_of_subset_of_forall_diff_eq_zero MeasureTheory.setIntegral_eq_of_subset_of_forall_diff_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_of_subset_of_forall_diff_eq_zero :=
setIntegral_eq_of_subset_of_forall_diff_eq_zero
/-- If a function vanishes almost everywhere on `sᶜ`, then its integral on `s`
coincides with its integral on the whole space. -/
theorem setIntegral_eq_integral_of_ae_compl_eq_zero (h : ∀ᵐ x ∂μ, x ∉ s → f x = 0) :
∫ x in s, f x ∂μ = ∫ x, f x ∂μ := by
symm
nth_rw 1 [← integral_univ]
apply setIntegral_eq_of_subset_of_ae_diff_eq_zero nullMeasurableSet_univ (subset_univ _)
filter_upwards [h] with x hx h'x using hx h'x.2
#align measure_theory.set_integral_eq_integral_of_ae_compl_eq_zero MeasureTheory.setIntegral_eq_integral_of_ae_compl_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_integral_of_ae_compl_eq_zero := setIntegral_eq_integral_of_ae_compl_eq_zero
/-- If a function vanishes on `sᶜ`, then its integral on `s` coincides with its integral on the
whole space. -/
theorem setIntegral_eq_integral_of_forall_compl_eq_zero (h : ∀ x, x ∉ s → f x = 0) :
∫ x in s, f x ∂μ = ∫ x, f x ∂μ :=
setIntegral_eq_integral_of_ae_compl_eq_zero (eventually_of_forall h)
#align measure_theory.set_integral_eq_integral_of_forall_compl_eq_zero MeasureTheory.setIntegral_eq_integral_of_forall_compl_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_integral_of_forall_compl_eq_zero :=
setIntegral_eq_integral_of_forall_compl_eq_zero
theorem setIntegral_neg_eq_setIntegral_nonpos [LinearOrder E] {f : X → E}
(hf : AEStronglyMeasurable f μ) :
∫ x in {x | f x < 0}, f x ∂μ = ∫ x in {x | f x ≤ 0}, f x ∂μ := by
have h_union : {x | f x ≤ 0} = {x | f x < 0} ∪ {x | f x = 0} := by
simp_rw [le_iff_lt_or_eq, setOf_or]
rw [h_union]
have B : NullMeasurableSet {x | f x = 0} μ :=
hf.nullMeasurableSet_eq_fun aestronglyMeasurable_zero
symm
refine integral_union_eq_left_of_ae ?_
filter_upwards [ae_restrict_mem₀ B] with x hx using hx
#align measure_theory.set_integral_neg_eq_set_integral_nonpos MeasureTheory.setIntegral_neg_eq_setIntegral_nonpos
@[deprecated (since := "2024-04-17")]
alias set_integral_neg_eq_set_integral_nonpos := setIntegral_neg_eq_setIntegral_nonpos
theorem integral_norm_eq_pos_sub_neg {f : X → ℝ} (hfi : Integrable f μ) :
∫ x, ‖f x‖ ∂μ = ∫ x in {x | 0 ≤ f x}, f x ∂μ - ∫ x in {x | f x ≤ 0}, f x ∂μ :=
have h_meas : NullMeasurableSet {x | 0 ≤ f x} μ :=
aestronglyMeasurable_const.nullMeasurableSet_le hfi.1
calc
∫ x, ‖f x‖ ∂μ = ∫ x in {x | 0 ≤ f x}, ‖f x‖ ∂μ + ∫ x in {x | 0 ≤ f x}ᶜ, ‖f x‖ ∂μ := by
rw [← integral_add_compl₀ h_meas hfi.norm]
_ = ∫ x in {x | 0 ≤ f x}, f x ∂μ + ∫ x in {x | 0 ≤ f x}ᶜ, ‖f x‖ ∂μ := by
congr 1
refine setIntegral_congr₀ h_meas fun x hx => ?_
dsimp only
rw [Real.norm_eq_abs, abs_eq_self.mpr _]
exact hx
_ = ∫ x in {x | 0 ≤ f x}, f x ∂μ - ∫ x in {x | 0 ≤ f x}ᶜ, f x ∂μ := by
congr 1
rw [← integral_neg]
refine setIntegral_congr₀ h_meas.compl fun x hx => ?_
dsimp only
rw [Real.norm_eq_abs, abs_eq_neg_self.mpr _]
rw [Set.mem_compl_iff, Set.nmem_setOf_iff] at hx
linarith
_ = ∫ x in {x | 0 ≤ f x}, f x ∂μ - ∫ x in {x | f x ≤ 0}, f x ∂μ := by
rw [← setIntegral_neg_eq_setIntegral_nonpos hfi.1, compl_setOf]; simp only [not_le]
#align measure_theory.integral_norm_eq_pos_sub_neg MeasureTheory.integral_norm_eq_pos_sub_neg
theorem setIntegral_const [CompleteSpace E] (c : E) : ∫ _ in s, c ∂μ = (μ s).toReal • c := by
rw [integral_const, Measure.restrict_apply_univ]
#align measure_theory.set_integral_const MeasureTheory.setIntegral_const
@[deprecated (since := "2024-04-17")]
alias set_integral_const := setIntegral_const
@[simp]
theorem integral_indicator_const [CompleteSpace E] (e : E) ⦃s : Set X⦄ (s_meas : MeasurableSet s) :
∫ x : X, s.indicator (fun _ : X => e) x ∂μ = (μ s).toReal • e := by
rw [integral_indicator s_meas, ← setIntegral_const]
#align measure_theory.integral_indicator_const MeasureTheory.integral_indicator_const
@[simp]
theorem integral_indicator_one ⦃s : Set X⦄ (hs : MeasurableSet s) :
∫ x, s.indicator 1 x ∂μ = (μ s).toReal :=
(integral_indicator_const 1 hs).trans ((smul_eq_mul _).trans (mul_one _))
#align measure_theory.integral_indicator_one MeasureTheory.integral_indicator_one
theorem setIntegral_indicatorConstLp [CompleteSpace E]
{p : ℝ≥0∞} (hs : MeasurableSet s) (ht : MeasurableSet t) (hμt : μ t ≠ ∞) (e : E) :
∫ x in s, indicatorConstLp p ht hμt e x ∂μ = (μ (t ∩ s)).toReal • e :=
calc
∫ x in s, indicatorConstLp p ht hμt e x ∂μ = ∫ x in s, t.indicator (fun _ => e) x ∂μ := by
rw [setIntegral_congr_ae hs (indicatorConstLp_coeFn.mono fun x hx _ => hx)]
_ = (μ (t ∩ s)).toReal • e := by rw [integral_indicator_const _ ht, Measure.restrict_apply ht]
set_option linter.uppercaseLean3 false in
#align measure_theory.set_integral_indicator_const_Lp MeasureTheory.setIntegral_indicatorConstLp
@[deprecated (since := "2024-04-17")]
alias set_integral_indicatorConstLp := setIntegral_indicatorConstLp
theorem integral_indicatorConstLp [CompleteSpace E]
{p : ℝ≥0∞} (ht : MeasurableSet t) (hμt : μ t ≠ ∞) (e : E) :
∫ x, indicatorConstLp p ht hμt e x ∂μ = (μ t).toReal • e :=
calc
∫ x, indicatorConstLp p ht hμt e x ∂μ = ∫ x in univ, indicatorConstLp p ht hμt e x ∂μ := by
rw [integral_univ]
_ = (μ (t ∩ univ)).toReal • e := setIntegral_indicatorConstLp MeasurableSet.univ ht hμt e
_ = (μ t).toReal • e := by rw [inter_univ]
set_option linter.uppercaseLean3 false in
#align measure_theory.integral_indicator_const_Lp MeasureTheory.integral_indicatorConstLp
theorem setIntegral_map {Y} [MeasurableSpace Y] {g : X → Y} {f : Y → E} {s : Set Y}
(hs : MeasurableSet s) (hf : AEStronglyMeasurable f (Measure.map g μ)) (hg : AEMeasurable g μ) :
∫ y in s, f y ∂Measure.map g μ = ∫ x in g ⁻¹' s, f (g x) ∂μ := by
rw [Measure.restrict_map_of_aemeasurable hg hs,
integral_map (hg.mono_measure Measure.restrict_le_self) (hf.mono_measure _)]
exact Measure.map_mono_of_aemeasurable Measure.restrict_le_self hg
#align measure_theory.set_integral_map MeasureTheory.setIntegral_map
@[deprecated (since := "2024-04-17")]
alias set_integral_map := setIntegral_map
theorem _root_.MeasurableEmbedding.setIntegral_map {Y} {_ : MeasurableSpace Y} {f : X → Y}
(hf : MeasurableEmbedding f) (g : Y → E) (s : Set Y) :
∫ y in s, g y ∂Measure.map f μ = ∫ x in f ⁻¹' s, g (f x) ∂μ := by
rw [hf.restrict_map, hf.integral_map]
#align measurable_embedding.set_integral_map MeasurableEmbedding.setIntegral_map
@[deprecated (since := "2024-04-17")]
alias _root_.MeasurableEmbedding.set_integral_map := _root_.MeasurableEmbedding.setIntegral_map
theorem _root_.ClosedEmbedding.setIntegral_map [TopologicalSpace X] [BorelSpace X] {Y}
[MeasurableSpace Y] [TopologicalSpace Y] [BorelSpace Y] {g : X → Y} {f : Y → E} (s : Set Y)
(hg : ClosedEmbedding g) : ∫ y in s, f y ∂Measure.map g μ = ∫ x in g ⁻¹' s, f (g x) ∂μ :=
hg.measurableEmbedding.setIntegral_map _ _
#align closed_embedding.set_integral_map ClosedEmbedding.setIntegral_map
@[deprecated (since := "2024-04-17")]
alias _root_.ClosedEmbedding.set_integral_map := _root_.ClosedEmbedding.setIntegral_map
theorem MeasurePreserving.setIntegral_preimage_emb {Y} {_ : MeasurableSpace Y} {f : X → Y} {ν}
(h₁ : MeasurePreserving f μ ν) (h₂ : MeasurableEmbedding f) (g : Y → E) (s : Set Y) :
∫ x in f ⁻¹' s, g (f x) ∂μ = ∫ y in s, g y ∂ν :=
(h₁.restrict_preimage_emb h₂ s).integral_comp h₂ _
#align measure_theory.measure_preserving.set_integral_preimage_emb MeasureTheory.MeasurePreserving.setIntegral_preimage_emb
@[deprecated (since := "2024-04-17")]
alias MeasurePreserving.set_integral_preimage_emb := MeasurePreserving.setIntegral_preimage_emb
theorem MeasurePreserving.setIntegral_image_emb {Y} {_ : MeasurableSpace Y} {f : X → Y} {ν}
(h₁ : MeasurePreserving f μ ν) (h₂ : MeasurableEmbedding f) (g : Y → E) (s : Set X) :
∫ y in f '' s, g y ∂ν = ∫ x in s, g (f x) ∂μ :=
Eq.symm <| (h₁.restrict_image_emb h₂ s).integral_comp h₂ _
#align measure_theory.measure_preserving.set_integral_image_emb MeasureTheory.MeasurePreserving.setIntegral_image_emb
@[deprecated (since := "2024-04-17")]
alias MeasurePreserving.set_integral_image_emb := MeasurePreserving.setIntegral_image_emb
theorem setIntegral_map_equiv {Y} [MeasurableSpace Y] (e : X ≃ᵐ Y) (f : Y → E) (s : Set Y) :
∫ y in s, f y ∂Measure.map e μ = ∫ x in e ⁻¹' s, f (e x) ∂μ :=
e.measurableEmbedding.setIntegral_map f s
#align measure_theory.set_integral_map_equiv MeasureTheory.setIntegral_map_equiv
@[deprecated (since := "2024-04-17")]
alias set_integral_map_equiv := setIntegral_map_equiv
theorem norm_setIntegral_le_of_norm_le_const_ae {C : ℝ} (hs : μ s < ∞)
(hC : ∀ᵐ x ∂μ.restrict s, ‖f x‖ ≤ C) : ‖∫ x in s, f x ∂μ‖ ≤ C * (μ s).toReal := by
rw [← Measure.restrict_apply_univ] at *
haveI : IsFiniteMeasure (μ.restrict s) := ⟨hs⟩
exact norm_integral_le_of_norm_le_const hC
#align measure_theory.norm_set_integral_le_of_norm_le_const_ae MeasureTheory.norm_setIntegral_le_of_norm_le_const_ae
@[deprecated (since := "2024-04-17")]
alias norm_set_integral_le_of_norm_le_const_ae := norm_setIntegral_le_of_norm_le_const_ae
theorem norm_setIntegral_le_of_norm_le_const_ae' {C : ℝ} (hs : μ s < ∞)
(hC : ∀ᵐ x ∂μ, x ∈ s → ‖f x‖ ≤ C) (hfm : AEStronglyMeasurable f (μ.restrict s)) :
‖∫ x in s, f x ∂μ‖ ≤ C * (μ s).toReal := by
apply norm_setIntegral_le_of_norm_le_const_ae hs
have A : ∀ᵐ x : X ∂μ, x ∈ s → ‖AEStronglyMeasurable.mk f hfm x‖ ≤ C := by
filter_upwards [hC, hfm.ae_mem_imp_eq_mk] with _ h1 h2 h3
rw [← h2 h3]
exact h1 h3
have B : MeasurableSet {x | ‖hfm.mk f x‖ ≤ C} :=
hfm.stronglyMeasurable_mk.norm.measurable measurableSet_Iic
filter_upwards [hfm.ae_eq_mk, (ae_restrict_iff B).2 A] with _ h1 _
rwa [h1]
#align measure_theory.norm_set_integral_le_of_norm_le_const_ae' MeasureTheory.norm_setIntegral_le_of_norm_le_const_ae'
@[deprecated (since := "2024-04-17")]
alias norm_set_integral_le_of_norm_le_const_ae' := norm_setIntegral_le_of_norm_le_const_ae'
theorem norm_setIntegral_le_of_norm_le_const_ae'' {C : ℝ} (hs : μ s < ∞) (hsm : MeasurableSet s)
(hC : ∀ᵐ x ∂μ, x ∈ s → ‖f x‖ ≤ C) : ‖∫ x in s, f x ∂μ‖ ≤ C * (μ s).toReal :=
norm_setIntegral_le_of_norm_le_const_ae hs <| by
rwa [ae_restrict_eq hsm, eventually_inf_principal]
#align measure_theory.norm_set_integral_le_of_norm_le_const_ae'' MeasureTheory.norm_setIntegral_le_of_norm_le_const_ae''
@[deprecated (since := "2024-04-17")]
alias norm_set_integral_le_of_norm_le_const_ae'' := norm_setIntegral_le_of_norm_le_const_ae''
theorem norm_setIntegral_le_of_norm_le_const {C : ℝ} (hs : μ s < ∞) (hC : ∀ x ∈ s, ‖f x‖ ≤ C)
(hfm : AEStronglyMeasurable f (μ.restrict s)) : ‖∫ x in s, f x ∂μ‖ ≤ C * (μ s).toReal :=
norm_setIntegral_le_of_norm_le_const_ae' hs (eventually_of_forall hC) hfm
#align measure_theory.norm_set_integral_le_of_norm_le_const MeasureTheory.norm_setIntegral_le_of_norm_le_const
@[deprecated (since := "2024-04-17")]
alias norm_set_integral_le_of_norm_le_const := norm_setIntegral_le_of_norm_le_const
theorem norm_setIntegral_le_of_norm_le_const' {C : ℝ} (hs : μ s < ∞) (hsm : MeasurableSet s)
(hC : ∀ x ∈ s, ‖f x‖ ≤ C) : ‖∫ x in s, f x ∂μ‖ ≤ C * (μ s).toReal :=
norm_setIntegral_le_of_norm_le_const_ae'' hs hsm <| eventually_of_forall hC
#align measure_theory.norm_set_integral_le_of_norm_le_const' MeasureTheory.norm_setIntegral_le_of_norm_le_const'
@[deprecated (since := "2024-04-17")]
alias norm_set_integral_le_of_norm_le_const' := norm_setIntegral_le_of_norm_le_const'
theorem setIntegral_eq_zero_iff_of_nonneg_ae {f : X → ℝ} (hf : 0 ≤ᵐ[μ.restrict s] f)
(hfi : IntegrableOn f s μ) : ∫ x in s, f x ∂μ = 0 ↔ f =ᵐ[μ.restrict s] 0 :=
integral_eq_zero_iff_of_nonneg_ae hf hfi
#align measure_theory.set_integral_eq_zero_iff_of_nonneg_ae MeasureTheory.setIntegral_eq_zero_iff_of_nonneg_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_zero_iff_of_nonneg_ae := setIntegral_eq_zero_iff_of_nonneg_ae
theorem setIntegral_pos_iff_support_of_nonneg_ae {f : X → ℝ} (hf : 0 ≤ᵐ[μ.restrict s] f)
(hfi : IntegrableOn f s μ) : (0 < ∫ x in s, f x ∂μ) ↔ 0 < μ (support f ∩ s) := by
rw [integral_pos_iff_support_of_nonneg_ae hf hfi, Measure.restrict_apply₀]
rw [support_eq_preimage]
exact hfi.aestronglyMeasurable.aemeasurable.nullMeasurable (measurableSet_singleton 0).compl
#align measure_theory.set_integral_pos_iff_support_of_nonneg_ae MeasureTheory.setIntegral_pos_iff_support_of_nonneg_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_pos_iff_support_of_nonneg_ae := setIntegral_pos_iff_support_of_nonneg_ae
theorem setIntegral_gt_gt {R : ℝ} {f : X → ℝ} (hR : 0 ≤ R) (hfm : Measurable f)
(hfint : IntegrableOn f {x | ↑R < f x} μ) (hμ : μ {x | ↑R < f x} ≠ 0) :
(μ {x | ↑R < f x}).toReal * R < ∫ x in {x | ↑R < f x}, f x ∂μ := by
have : IntegrableOn (fun _ => R) {x | ↑R < f x} μ := by
refine ⟨aestronglyMeasurable_const, lt_of_le_of_lt ?_ hfint.2⟩
refine
set_lintegral_mono (Measurable.nnnorm ?_).coe_nnreal_ennreal hfm.nnnorm.coe_nnreal_ennreal
fun x hx => ?_
· exact measurable_const
· simp only [ENNReal.coe_le_coe, Real.nnnorm_of_nonneg hR,
Real.nnnorm_of_nonneg (hR.trans <| le_of_lt hx), Subtype.mk_le_mk]
exact le_of_lt hx
rw [← sub_pos, ← smul_eq_mul, ← setIntegral_const, ← integral_sub hfint this,
setIntegral_pos_iff_support_of_nonneg_ae]
· rw [← zero_lt_iff] at hμ
rwa [Set.inter_eq_self_of_subset_right]
exact fun x hx => Ne.symm (ne_of_lt <| sub_pos.2 hx)
· rw [Pi.zero_def, EventuallyLE, ae_restrict_iff]
· exact eventually_of_forall fun x hx => sub_nonneg.2 <| le_of_lt hx
· exact measurableSet_le measurable_zero (hfm.sub measurable_const)
· exact Integrable.sub hfint this
#align measure_theory.set_integral_gt_gt MeasureTheory.setIntegral_gt_gt
@[deprecated (since := "2024-04-17")]
alias set_integral_gt_gt := setIntegral_gt_gt
theorem setIntegral_trim {X} {m m0 : MeasurableSpace X} {μ : Measure X} (hm : m ≤ m0) {f : X → E}
(hf_meas : StronglyMeasurable[m] f) {s : Set X} (hs : MeasurableSet[m] s) :
∫ x in s, f x ∂μ = ∫ x in s, f x ∂μ.trim hm := by
rwa [integral_trim hm hf_meas, restrict_trim hm μ]
#align measure_theory.set_integral_trim MeasureTheory.setIntegral_trim
@[deprecated (since := "2024-04-17")]
alias set_integral_trim := setIntegral_trim
/-! ### Lemmas about adding and removing interval boundaries
The primed lemmas take explicit arguments about the endpoint having zero measure, while the
unprimed ones use `[NoAtoms μ]`.
-/
section PartialOrder
variable [PartialOrder X] {x y : X}
theorem integral_Icc_eq_integral_Ioc' (hx : μ {x} = 0) :
∫ t in Icc x y, f t ∂μ = ∫ t in Ioc x y, f t ∂μ :=
setIntegral_congr_set_ae (Ioc_ae_eq_Icc' hx).symm
#align measure_theory.integral_Icc_eq_integral_Ioc' MeasureTheory.integral_Icc_eq_integral_Ioc'
theorem integral_Icc_eq_integral_Ico' (hy : μ {y} = 0) :
∫ t in Icc x y, f t ∂μ = ∫ t in Ico x y, f t ∂μ :=
setIntegral_congr_set_ae (Ico_ae_eq_Icc' hy).symm
#align measure_theory.integral_Icc_eq_integral_Ico' MeasureTheory.integral_Icc_eq_integral_Ico'
theorem integral_Ioc_eq_integral_Ioo' (hy : μ {y} = 0) :
∫ t in Ioc x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ :=
setIntegral_congr_set_ae (Ioo_ae_eq_Ioc' hy).symm
#align measure_theory.integral_Ioc_eq_integral_Ioo' MeasureTheory.integral_Ioc_eq_integral_Ioo'
theorem integral_Ico_eq_integral_Ioo' (hx : μ {x} = 0) :
∫ t in Ico x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ :=
setIntegral_congr_set_ae (Ioo_ae_eq_Ico' hx).symm
#align measure_theory.integral_Ico_eq_integral_Ioo' MeasureTheory.integral_Ico_eq_integral_Ioo'
theorem integral_Icc_eq_integral_Ioo' (hx : μ {x} = 0) (hy : μ {y} = 0) :
∫ t in Icc x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ :=
setIntegral_congr_set_ae (Ioo_ae_eq_Icc' hx hy).symm
#align measure_theory.integral_Icc_eq_integral_Ioo' MeasureTheory.integral_Icc_eq_integral_Ioo'
theorem integral_Iic_eq_integral_Iio' (hx : μ {x} = 0) :
∫ t in Iic x, f t ∂μ = ∫ t in Iio x, f t ∂μ :=
setIntegral_congr_set_ae (Iio_ae_eq_Iic' hx).symm
#align measure_theory.integral_Iic_eq_integral_Iio' MeasureTheory.integral_Iic_eq_integral_Iio'
theorem integral_Ici_eq_integral_Ioi' (hx : μ {x} = 0) :
∫ t in Ici x, f t ∂μ = ∫ t in Ioi x, f t ∂μ :=
setIntegral_congr_set_ae (Ioi_ae_eq_Ici' hx).symm
#align measure_theory.integral_Ici_eq_integral_Ioi' MeasureTheory.integral_Ici_eq_integral_Ioi'
variable [NoAtoms μ]
theorem integral_Icc_eq_integral_Ioc : ∫ t in Icc x y, f t ∂μ = ∫ t in Ioc x y, f t ∂μ :=
integral_Icc_eq_integral_Ioc' <| measure_singleton x
#align measure_theory.integral_Icc_eq_integral_Ioc MeasureTheory.integral_Icc_eq_integral_Ioc
theorem integral_Icc_eq_integral_Ico : ∫ t in Icc x y, f t ∂μ = ∫ t in Ico x y, f t ∂μ :=
integral_Icc_eq_integral_Ico' <| measure_singleton y
#align measure_theory.integral_Icc_eq_integral_Ico MeasureTheory.integral_Icc_eq_integral_Ico
theorem integral_Ioc_eq_integral_Ioo : ∫ t in Ioc x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ :=
integral_Ioc_eq_integral_Ioo' <| measure_singleton y
#align measure_theory.integral_Ioc_eq_integral_Ioo MeasureTheory.integral_Ioc_eq_integral_Ioo
theorem integral_Ico_eq_integral_Ioo : ∫ t in Ico x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ :=
integral_Ico_eq_integral_Ioo' <| measure_singleton x
#align measure_theory.integral_Ico_eq_integral_Ioo MeasureTheory.integral_Ico_eq_integral_Ioo
theorem integral_Icc_eq_integral_Ioo : ∫ t in Icc x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ := by
rw [integral_Icc_eq_integral_Ico, integral_Ico_eq_integral_Ioo]
#align measure_theory.integral_Icc_eq_integral_Ioo MeasureTheory.integral_Icc_eq_integral_Ioo
theorem integral_Iic_eq_integral_Iio : ∫ t in Iic x, f t ∂μ = ∫ t in Iio x, f t ∂μ :=
integral_Iic_eq_integral_Iio' <| measure_singleton x
#align measure_theory.integral_Iic_eq_integral_Iio MeasureTheory.integral_Iic_eq_integral_Iio
theorem integral_Ici_eq_integral_Ioi : ∫ t in Ici x, f t ∂μ = ∫ t in Ioi x, f t ∂μ :=
integral_Ici_eq_integral_Ioi' <| measure_singleton x
#align measure_theory.integral_Ici_eq_integral_Ioi MeasureTheory.integral_Ici_eq_integral_Ioi
end PartialOrder
end NormedAddCommGroup
section Mono
variable {μ : Measure X} {f g : X → ℝ} {s t : Set X} (hf : IntegrableOn f s μ)
(hg : IntegrableOn g s μ)
theorem setIntegral_mono_ae_restrict (h : f ≤ᵐ[μ.restrict s] g) :
∫ x in s, f x ∂μ ≤ ∫ x in s, g x ∂μ :=
integral_mono_ae hf hg h
#align measure_theory.set_integral_mono_ae_restrict MeasureTheory.setIntegral_mono_ae_restrict
@[deprecated (since := "2024-04-17")]
alias set_integral_mono_ae_restrict := setIntegral_mono_ae_restrict
theorem setIntegral_mono_ae (h : f ≤ᵐ[μ] g) : ∫ x in s, f x ∂μ ≤ ∫ x in s, g x ∂μ :=
setIntegral_mono_ae_restrict hf hg (ae_restrict_of_ae h)
#align measure_theory.set_integral_mono_ae MeasureTheory.setIntegral_mono_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_mono_ae := setIntegral_mono_ae
theorem setIntegral_mono_on (hs : MeasurableSet s) (h : ∀ x ∈ s, f x ≤ g x) :
∫ x in s, f x ∂μ ≤ ∫ x in s, g x ∂μ :=
setIntegral_mono_ae_restrict hf hg
(by simp [hs, EventuallyLE, eventually_inf_principal, ae_of_all _ h])
#align measure_theory.set_integral_mono_on MeasureTheory.setIntegral_mono_on
@[deprecated (since := "2024-04-17")]
alias set_integral_mono_on := setIntegral_mono_on
theorem setIntegral_mono_on_ae (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x ≤ g x) :
∫ x in s, f x ∂μ ≤ ∫ x in s, g x ∂μ := by
refine setIntegral_mono_ae_restrict hf hg ?_; rwa [EventuallyLE, ae_restrict_iff' hs]
#align measure_theory.set_integral_mono_on_ae MeasureTheory.setIntegral_mono_on_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_mono_on_ae := setIntegral_mono_on_ae
theorem setIntegral_mono (h : f ≤ g) : ∫ x in s, f x ∂μ ≤ ∫ x in s, g x ∂μ :=
integral_mono hf hg h
#align measure_theory.set_integral_mono MeasureTheory.setIntegral_mono
@[deprecated (since := "2024-04-17")]
alias set_integral_mono := setIntegral_mono
theorem setIntegral_mono_set (hfi : IntegrableOn f t μ) (hf : 0 ≤ᵐ[μ.restrict t] f)
(hst : s ≤ᵐ[μ] t) : ∫ x in s, f x ∂μ ≤ ∫ x in t, f x ∂μ :=
integral_mono_measure (Measure.restrict_mono_ae hst) hf hfi
#align measure_theory.set_integral_mono_set MeasureTheory.setIntegral_mono_set
@[deprecated (since := "2024-04-17")]
alias set_integral_mono_set := setIntegral_mono_set
theorem setIntegral_le_integral (hfi : Integrable f μ) (hf : 0 ≤ᵐ[μ] f) :
∫ x in s, f x ∂μ ≤ ∫ x, f x ∂μ :=
integral_mono_measure (Measure.restrict_le_self) hf hfi
@[deprecated (since := "2024-04-17")]
alias set_integral_le_integral := setIntegral_le_integral
theorem setIntegral_ge_of_const_le {c : ℝ} (hs : MeasurableSet s) (hμs : μ s ≠ ∞)
(hf : ∀ x ∈ s, c ≤ f x) (hfint : IntegrableOn (fun x : X => f x) s μ) :
c * (μ s).toReal ≤ ∫ x in s, f x ∂μ := by
rw [mul_comm, ← smul_eq_mul, ← setIntegral_const c]
exact setIntegral_mono_on (integrableOn_const.2 (Or.inr hμs.lt_top)) hfint hs hf
#align measure_theory.set_integral_ge_of_const_le MeasureTheory.setIntegral_ge_of_const_le
@[deprecated (since := "2024-04-17")]
alias set_integral_ge_of_const_le := setIntegral_ge_of_const_le
end Mono
section Nonneg
variable {μ : Measure X} {f : X → ℝ} {s : Set X}
theorem setIntegral_nonneg_of_ae_restrict (hf : 0 ≤ᵐ[μ.restrict s] f) : 0 ≤ ∫ x in s, f x ∂μ :=
integral_nonneg_of_ae hf
#align measure_theory.set_integral_nonneg_of_ae_restrict MeasureTheory.setIntegral_nonneg_of_ae_restrict
@[deprecated (since := "2024-04-17")]
alias set_integral_nonneg_of_ae_restrict := setIntegral_nonneg_of_ae_restrict
theorem setIntegral_nonneg_of_ae (hf : 0 ≤ᵐ[μ] f) : 0 ≤ ∫ x in s, f x ∂μ :=
setIntegral_nonneg_of_ae_restrict (ae_restrict_of_ae hf)
#align measure_theory.set_integral_nonneg_of_ae MeasureTheory.setIntegral_nonneg_of_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_nonneg_of_ae := setIntegral_nonneg_of_ae
theorem setIntegral_nonneg (hs : MeasurableSet s) (hf : ∀ x, x ∈ s → 0 ≤ f x) :
0 ≤ ∫ x in s, f x ∂μ :=
setIntegral_nonneg_of_ae_restrict ((ae_restrict_iff' hs).mpr (ae_of_all μ hf))
#align measure_theory.set_integral_nonneg MeasureTheory.setIntegral_nonneg
@[deprecated (since := "2024-04-17")]
alias set_integral_nonneg := setIntegral_nonneg
theorem setIntegral_nonneg_ae (hs : MeasurableSet s) (hf : ∀ᵐ x ∂μ, x ∈ s → 0 ≤ f x) :
0 ≤ ∫ x in s, f x ∂μ :=
setIntegral_nonneg_of_ae_restrict <| by rwa [EventuallyLE, ae_restrict_iff' hs]
#align measure_theory.set_integral_nonneg_ae MeasureTheory.setIntegral_nonneg_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_nonneg_ae := setIntegral_nonneg_ae
theorem setIntegral_le_nonneg {s : Set X} (hs : MeasurableSet s) (hf : StronglyMeasurable f)
(hfi : Integrable f μ) : ∫ x in s, f x ∂μ ≤ ∫ x in {y | 0 ≤ f y}, f x ∂μ := by
rw [← integral_indicator hs, ←
integral_indicator (stronglyMeasurable_const.measurableSet_le hf)]
exact
integral_mono (hfi.indicator hs)
(hfi.indicator (stronglyMeasurable_const.measurableSet_le hf))
(indicator_le_indicator_nonneg s f)
#align measure_theory.set_integral_le_nonneg MeasureTheory.setIntegral_le_nonneg
@[deprecated (since := "2024-04-17")]
alias set_integral_le_nonneg := setIntegral_le_nonneg
theorem setIntegral_nonpos_of_ae_restrict (hf : f ≤ᵐ[μ.restrict s] 0) : ∫ x in s, f x ∂μ ≤ 0 :=
integral_nonpos_of_ae hf
#align measure_theory.set_integral_nonpos_of_ae_restrict MeasureTheory.setIntegral_nonpos_of_ae_restrict
@[deprecated (since := "2024-04-17")]
alias set_integral_nonpos_of_ae_restrict := setIntegral_nonpos_of_ae_restrict
theorem setIntegral_nonpos_of_ae (hf : f ≤ᵐ[μ] 0) : ∫ x in s, f x ∂μ ≤ 0 :=
setIntegral_nonpos_of_ae_restrict (ae_restrict_of_ae hf)
#align measure_theory.set_integral_nonpos_of_ae MeasureTheory.setIntegral_nonpos_of_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_nonpos_of_ae := setIntegral_nonpos_of_ae
theorem setIntegral_nonpos_ae (hs : MeasurableSet s) (hf : ∀ᵐ x ∂μ, x ∈ s → f x ≤ 0) :
∫ x in s, f x ∂μ ≤ 0 :=
setIntegral_nonpos_of_ae_restrict <| by rwa [EventuallyLE, ae_restrict_iff' hs]
#align measure_theory.set_integral_nonpos_ae MeasureTheory.setIntegral_nonpos_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_nonpos_ae := setIntegral_nonpos_ae
theorem setIntegral_nonpos (hs : MeasurableSet s) (hf : ∀ x, x ∈ s → f x ≤ 0) :
∫ x in s, f x ∂μ ≤ 0 :=
setIntegral_nonpos_ae hs <| ae_of_all μ hf
#align measure_theory.set_integral_nonpos MeasureTheory.setIntegral_nonpos
@[deprecated (since := "2024-04-17")]
alias set_integral_nonpos := setIntegral_nonpos
theorem setIntegral_nonpos_le {s : Set X} (hs : MeasurableSet s) (hf : StronglyMeasurable f)
(hfi : Integrable f μ) : ∫ x in {y | f y ≤ 0}, f x ∂μ ≤ ∫ x in s, f x ∂μ := by
rw [← integral_indicator hs, ←
integral_indicator (hf.measurableSet_le stronglyMeasurable_const)]
exact
integral_mono (hfi.indicator (hf.measurableSet_le stronglyMeasurable_const))
(hfi.indicator hs) (indicator_nonpos_le_indicator s f)
#align measure_theory.set_integral_nonpos_le MeasureTheory.setIntegral_nonpos_le
@[deprecated (since := "2024-04-17")]
alias set_integral_nonpos_le := setIntegral_nonpos_le
lemma Integrable.measure_le_integral {f : X → ℝ} (f_int : Integrable f μ) (f_nonneg : 0 ≤ᵐ[μ] f)
{s : Set X} (hs : ∀ x ∈ s, 1 ≤ f x) :
μ s ≤ ENNReal.ofReal (∫ x, f x ∂μ) := by
rw [ofReal_integral_eq_lintegral_ofReal f_int f_nonneg]
apply meas_le_lintegral₀
· exact ENNReal.continuous_ofReal.measurable.comp_aemeasurable f_int.1.aemeasurable
· intro x hx
simpa using ENNReal.ofReal_le_ofReal (hs x hx)
lemma integral_le_measure {f : X → ℝ} {s : Set X}
(hs : ∀ x ∈ s, f x ≤ 1) (h's : ∀ x ∈ sᶜ, f x ≤ 0) :
ENNReal.ofReal (∫ x, f x ∂μ) ≤ μ s := by
by_cases H : Integrable f μ; swap
· simp [integral_undef H]
let g x := max (f x) 0
have g_int : Integrable g μ := H.pos_part
have : ENNReal.ofReal (∫ x, f x ∂μ) ≤ ENNReal.ofReal (∫ x, g x ∂μ) := by
apply ENNReal.ofReal_le_ofReal
exact integral_mono H g_int (fun x ↦ le_max_left _ _)
apply this.trans
rw [ofReal_integral_eq_lintegral_ofReal g_int (eventually_of_forall (fun x ↦ le_max_right _ _))]
apply lintegral_le_meas
· intro x
apply ENNReal.ofReal_le_of_le_toReal
by_cases H : x ∈ s
· simpa [g] using hs x H
· apply le_trans _ zero_le_one
simpa [g] using h's x H
· intro x hx
simpa [g] using h's x hx
end Nonneg
section IntegrableUnion
variable {ι : Type*} [Countable ι] {μ : Measure X} [NormedAddCommGroup E]
theorem integrableOn_iUnion_of_summable_integral_norm {f : X → E} {s : ι → Set X}
(hs : ∀ i : ι, MeasurableSet (s i)) (hi : ∀ i : ι, IntegrableOn f (s i) μ)
(h : Summable fun i : ι => ∫ x : X in s i, ‖f x‖ ∂μ) : IntegrableOn f (iUnion s) μ := by
refine ⟨AEStronglyMeasurable.iUnion fun i => (hi i).1, (lintegral_iUnion_le _ _).trans_lt ?_⟩
have B := fun i => lintegral_coe_eq_integral (fun x : X => ‖f x‖₊) (hi i).norm
rw [tsum_congr B]
have S' :
Summable fun i : ι =>
(⟨∫ x : X in s i, ‖f x‖₊ ∂μ, setIntegral_nonneg (hs i) fun x _ => NNReal.coe_nonneg _⟩ :
NNReal) := by
rw [← NNReal.summable_coe]; exact h
have S'' := ENNReal.tsum_coe_eq S'.hasSum
simp_rw [ENNReal.coe_nnreal_eq, NNReal.coe_mk, coe_nnnorm] at S''
convert ENNReal.ofReal_lt_top
#align measure_theory.integrable_on_Union_of_summable_integral_norm MeasureTheory.integrableOn_iUnion_of_summable_integral_norm
variable [TopologicalSpace X] [BorelSpace X] [MetrizableSpace X] [IsLocallyFiniteMeasure μ]
/-- If `s` is a countable family of compact sets, `f` is a continuous function, and the sequence
`‖f.restrict (s i)‖ * μ (s i)` is summable, then `f` is integrable on the union of the `s i`. -/
theorem integrableOn_iUnion_of_summable_norm_restrict {f : C(X, E)} {s : ι → Compacts X}
(hf : Summable fun i : ι => ‖f.restrict (s i)‖ * ENNReal.toReal (μ <| s i)) :
IntegrableOn f (⋃ i : ι, s i) μ := by
refine
integrableOn_iUnion_of_summable_integral_norm (fun i => (s i).isCompact.isClosed.measurableSet)
(fun i => (map_continuous f).continuousOn.integrableOn_compact (s i).isCompact)
(.of_nonneg_of_le (fun ι => integral_nonneg fun x => norm_nonneg _) (fun i => ?_) hf)
rw [← (Real.norm_of_nonneg (integral_nonneg fun x => norm_nonneg _) : ‖_‖ = ∫ x in s i, ‖f x‖ ∂μ)]
exact
norm_setIntegral_le_of_norm_le_const' (s i).isCompact.measure_lt_top
(s i).isCompact.isClosed.measurableSet fun x hx =>
(norm_norm (f x)).symm ▸ (f.restrict (s i : Set X)).norm_coe_le_norm ⟨x, hx⟩
#align measure_theory.integrable_on_Union_of_summable_norm_restrict MeasureTheory.integrableOn_iUnion_of_summable_norm_restrict
/-- If `s` is a countable family of compact sets covering `X`, `f` is a continuous function, and
the sequence `‖f.restrict (s i)‖ * μ (s i)` is summable, then `f` is integrable. -/
theorem integrable_of_summable_norm_restrict {f : C(X, E)} {s : ι → Compacts X}
(hf : Summable fun i : ι => ‖f.restrict (s i)‖ * ENNReal.toReal (μ <| s i))
(hs : ⋃ i : ι, ↑(s i) = (univ : Set X)) : Integrable f μ := by
simpa only [hs, integrableOn_univ] using integrableOn_iUnion_of_summable_norm_restrict hf
#align measure_theory.integrable_of_summable_norm_restrict MeasureTheory.integrable_of_summable_norm_restrict
end IntegrableUnion
/-! ### Continuity of the set integral
We prove that for any set `s`, the function
`fun f : X →₁[μ] E => ∫ x in s, f x ∂μ` is continuous. -/
section ContinuousSetIntegral
variable [NormedAddCommGroup E]
{𝕜 : Type*} [NormedField 𝕜] [NormedAddCommGroup F] [NormedSpace 𝕜 F] {p : ℝ≥0∞} {μ : Measure X}
/-- For `f : Lp E p μ`, we can define an element of `Lp E p (μ.restrict s)` by
`(Lp.memℒp f).restrict s).toLp f`. This map is additive. -/
theorem Lp_toLp_restrict_add (f g : Lp E p μ) (s : Set X) :
((Lp.memℒp (f + g)).restrict s).toLp (⇑(f + g)) =
((Lp.memℒp f).restrict s).toLp f + ((Lp.memℒp g).restrict s).toLp g := by
ext1
refine (ae_restrict_of_ae (Lp.coeFn_add f g)).mp ?_
refine
(Lp.coeFn_add (Memℒp.toLp f ((Lp.memℒp f).restrict s))
(Memℒp.toLp g ((Lp.memℒp g).restrict s))).mp ?_
refine (Memℒp.coeFn_toLp ((Lp.memℒp f).restrict s)).mp ?_
refine (Memℒp.coeFn_toLp ((Lp.memℒp g).restrict s)).mp ?_
refine (Memℒp.coeFn_toLp ((Lp.memℒp (f + g)).restrict s)).mono fun x hx1 hx2 hx3 hx4 hx5 => ?_
rw [hx4, hx1, Pi.add_apply, hx2, hx3, hx5, Pi.add_apply]
set_option linter.uppercaseLean3 false in
#align measure_theory.Lp_to_Lp_restrict_add MeasureTheory.Lp_toLp_restrict_add
/-- For `f : Lp E p μ`, we can define an element of `Lp E p (μ.restrict s)` by
`(Lp.memℒp f).restrict s).toLp f`. This map commutes with scalar multiplication. -/
theorem Lp_toLp_restrict_smul (c : 𝕜) (f : Lp F p μ) (s : Set X) :
((Lp.memℒp (c • f)).restrict s).toLp (⇑(c • f)) = c • ((Lp.memℒp f).restrict s).toLp f := by
ext1
refine (ae_restrict_of_ae (Lp.coeFn_smul c f)).mp ?_
refine (Memℒp.coeFn_toLp ((Lp.memℒp f).restrict s)).mp ?_
refine (Memℒp.coeFn_toLp ((Lp.memℒp (c • f)).restrict s)).mp ?_
refine
(Lp.coeFn_smul c (Memℒp.toLp f ((Lp.memℒp f).restrict s))).mono fun x hx1 hx2 hx3 hx4 => ?_
simp only [hx2, hx1, hx3, hx4, Pi.smul_apply]
set_option linter.uppercaseLean3 false in
#align measure_theory.Lp_to_Lp_restrict_smul MeasureTheory.Lp_toLp_restrict_smul
/-- For `f : Lp E p μ`, we can define an element of `Lp E p (μ.restrict s)` by
`(Lp.memℒp f).restrict s).toLp f`. This map is non-expansive. -/
theorem norm_Lp_toLp_restrict_le (s : Set X) (f : Lp E p μ) :
‖((Lp.memℒp f).restrict s).toLp f‖ ≤ ‖f‖ := by
rw [Lp.norm_def, Lp.norm_def, ENNReal.toReal_le_toReal (Lp.snorm_ne_top _) (Lp.snorm_ne_top _)]
apply (le_of_eq _).trans (snorm_mono_measure _ (Measure.restrict_le_self (s := s)))
exact snorm_congr_ae (Memℒp.coeFn_toLp _)
set_option linter.uppercaseLean3 false in
#align measure_theory.norm_Lp_to_Lp_restrict_le MeasureTheory.norm_Lp_toLp_restrict_le
variable (X F 𝕜) in
/-- Continuous linear map sending a function of `Lp F p μ` to the same function in
`Lp F p (μ.restrict s)`. -/
def LpToLpRestrictCLM (μ : Measure X) (p : ℝ≥0∞) [hp : Fact (1 ≤ p)] (s : Set X) :
Lp F p μ →L[𝕜] Lp F p (μ.restrict s) :=
@LinearMap.mkContinuous 𝕜 𝕜 (Lp F p μ) (Lp F p (μ.restrict s)) _ _ _ _ _ _ (RingHom.id 𝕜)
⟨⟨fun f => Memℒp.toLp f ((Lp.memℒp f).restrict s), fun f g => Lp_toLp_restrict_add f g s⟩,
fun c f => Lp_toLp_restrict_smul c f s⟩
1 (by intro f; rw [one_mul]; exact norm_Lp_toLp_restrict_le s f)
set_option linter.uppercaseLean3 false in
#align measure_theory.Lp_to_Lp_restrict_clm MeasureTheory.LpToLpRestrictCLM
variable (𝕜) in
theorem LpToLpRestrictCLM_coeFn [Fact (1 ≤ p)] (s : Set X) (f : Lp F p μ) :
LpToLpRestrictCLM X F 𝕜 μ p s f =ᵐ[μ.restrict s] f :=
Memℒp.coeFn_toLp ((Lp.memℒp f).restrict s)
set_option linter.uppercaseLean3 false in
#align measure_theory.Lp_to_Lp_restrict_clm_coe_fn MeasureTheory.LpToLpRestrictCLM_coeFn
@[continuity]
theorem continuous_setIntegral [NormedSpace ℝ E] (s : Set X) :
Continuous fun f : X →₁[μ] E => ∫ x in s, f x ∂μ := by
haveI : Fact ((1 : ℝ≥0∞) ≤ 1) := ⟨le_rfl⟩
have h_comp :
(fun f : X →₁[μ] E => ∫ x in s, f x ∂μ) =
integral (μ.restrict s) ∘ fun f => LpToLpRestrictCLM X E ℝ μ 1 s f := by
ext1 f
rw [Function.comp_apply, integral_congr_ae (LpToLpRestrictCLM_coeFn ℝ s f)]
rw [h_comp]
exact continuous_integral.comp (LpToLpRestrictCLM X E ℝ μ 1 s).continuous
#align measure_theory.continuous_set_integral MeasureTheory.continuous_setIntegral
@[deprecated (since := "2024-04-17")]
alias continuous_set_integral := continuous_setIntegral
end ContinuousSetIntegral
end MeasureTheory
section OpenPos
open Measure
variable [TopologicalSpace X] [OpensMeasurableSpace X] {μ : Measure X} [IsOpenPosMeasure μ]
theorem Continuous.integral_pos_of_hasCompactSupport_nonneg_nonzero [IsFiniteMeasureOnCompacts μ]
{f : X → ℝ} {x : X} (f_cont : Continuous f) (f_comp : HasCompactSupport f) (f_nonneg : 0 ≤ f)
(f_x : f x ≠ 0) : 0 < ∫ x, f x ∂μ :=
integral_pos_of_integrable_nonneg_nonzero f_cont (f_cont.integrable_of_hasCompactSupport f_comp)
f_nonneg f_x
end OpenPos
/-! Fundamental theorem of calculus for set integrals -/
section FTC
open MeasureTheory Asymptotics Metric
variable {ι : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] [CompleteSpace E]
/-- Fundamental theorem of calculus for set integrals:
if `μ` is a measure that is finite at a filter `l` and
`f` is a measurable function that has a finite limit `b` at `l ⊓ ae μ`, then
`∫ x in s i, f x ∂μ = μ (s i) • b + o(μ (s i))` at a filter `li` provided that
`s i` tends to `l.smallSets` along `li`.
Since `μ (s i)` is an `ℝ≥0∞` number, we use `(μ (s i)).toReal` in the actual statement.
Often there is a good formula for `(μ (s i)).toReal`, so the formalization can take an optional
argument `m` with this formula and a proof of `(fun i => (μ (s i)).toReal) =ᶠ[li] m`. Without these
arguments, `m i = (μ (s i)).toReal` is used in the output. -/
theorem Filter.Tendsto.integral_sub_linear_isLittleO_ae
{μ : Measure X} {l : Filter X} [l.IsMeasurablyGenerated] {f : X → E} {b : E}
(h : Tendsto f (l ⊓ ae μ) (𝓝 b)) (hfm : StronglyMeasurableAtFilter f l μ)
(hμ : μ.FiniteAtFilter l) {s : ι → Set X} {li : Filter ι} (hs : Tendsto s li l.smallSets)
(m : ι → ℝ := fun i => (μ (s i)).toReal)
(hsμ : (fun i => (μ (s i)).toReal) =ᶠ[li] m := by rfl) :
(fun i => (∫ x in s i, f x ∂μ) - m i • b) =o[li] m := by
suffices
(fun s => (∫ x in s, f x ∂μ) - (μ s).toReal • b) =o[l.smallSets] fun s => (μ s).toReal from
(this.comp_tendsto hs).congr'
(hsμ.mono fun a ha => by dsimp only [Function.comp_apply] at ha ⊢; rw [ha]) hsμ
refine isLittleO_iff.2 fun ε ε₀ => ?_
have : ∀ᶠ s in l.smallSets, ∀ᵐ x ∂μ, x ∈ s → f x ∈ closedBall b ε :=
eventually_smallSets_eventually.2 (h.eventually <| closedBall_mem_nhds _ ε₀)
filter_upwards [hμ.eventually, (hμ.integrableAtFilter_of_tendsto_ae hfm h).eventually,
hfm.eventually, this]
simp only [mem_closedBall, dist_eq_norm]
intro s hμs h_integrable hfm h_norm
rw [← setIntegral_const, ← integral_sub h_integrable (integrableOn_const.2 <| Or.inr hμs),
Real.norm_eq_abs, abs_of_nonneg ENNReal.toReal_nonneg]
exact norm_setIntegral_le_of_norm_le_const_ae' hμs h_norm (hfm.sub aestronglyMeasurable_const)
#align filter.tendsto.integral_sub_linear_is_o_ae Filter.Tendsto.integral_sub_linear_isLittleO_ae
/-- Fundamental theorem of calculus for set integrals, `nhdsWithin` version: if `μ` is a locally
finite measure and `f` is an almost everywhere measurable function that is continuous at a point `a`
within a measurable set `t`, then `∫ x in s i, f x ∂μ = μ (s i) • f a + o(μ (s i))` at a filter `li`
provided that `s i` tends to `(𝓝[t] a).smallSets` along `li`. Since `μ (s i)` is an `ℝ≥0∞`
number, we use `(μ (s i)).toReal` in the actual statement.
Often there is a good formula for `(μ (s i)).toReal`, so the formalization can take an optional
argument `m` with this formula and a proof of `(fun i => (μ (s i)).toReal) =ᶠ[li] m`. Without these
arguments, `m i = (μ (s i)).toReal` is used in the output. -/
theorem ContinuousWithinAt.integral_sub_linear_isLittleO_ae [TopologicalSpace X]
[OpensMeasurableSpace X] {μ : Measure X}
[IsLocallyFiniteMeasure μ] {x : X} {t : Set X} {f : X → E} (hx : ContinuousWithinAt f t x)
(ht : MeasurableSet t) (hfm : StronglyMeasurableAtFilter f (𝓝[t] x) μ) {s : ι → Set X}
{li : Filter ι} (hs : Tendsto s li (𝓝[t] x).smallSets) (m : ι → ℝ := fun i => (μ (s i)).toReal)
(hsμ : (fun i => (μ (s i)).toReal) =ᶠ[li] m := by rfl) :
(fun i => (∫ x in s i, f x ∂μ) - m i • f x) =o[li] m :=
haveI : (𝓝[t] x).IsMeasurablyGenerated := ht.nhdsWithin_isMeasurablyGenerated _
(hx.mono_left inf_le_left).integral_sub_linear_isLittleO_ae hfm (μ.finiteAt_nhdsWithin x t) hs m
hsμ
#align continuous_within_at.integral_sub_linear_is_o_ae ContinuousWithinAt.integral_sub_linear_isLittleO_ae
/-- Fundamental theorem of calculus for set integrals, `nhds` version: if `μ` is a locally finite
measure and `f` is an almost everywhere measurable function that is continuous at a point `a`, then
`∫ x in s i, f x ∂μ = μ (s i) • f a + o(μ (s i))` at `li` provided that `s` tends to
`(𝓝 a).smallSets` along `li`. Since `μ (s i)` is an `ℝ≥0∞` number, we use `(μ (s i)).toReal` in
the actual statement.
Often there is a good formula for `(μ (s i)).toReal`, so the formalization can take an optional
argument `m` with this formula and a proof of `(fun i => (μ (s i)).toReal) =ᶠ[li] m`. Without these
arguments, `m i = (μ (s i)).toReal` is used in the output. -/
theorem ContinuousAt.integral_sub_linear_isLittleO_ae [TopologicalSpace X] [OpensMeasurableSpace X]
{μ : Measure X} [IsLocallyFiniteMeasure μ] {x : X}
{f : X → E} (hx : ContinuousAt f x) (hfm : StronglyMeasurableAtFilter f (𝓝 x) μ) {s : ι → Set X}
{li : Filter ι} (hs : Tendsto s li (𝓝 x).smallSets) (m : ι → ℝ := fun i => (μ (s i)).toReal)
(hsμ : (fun i => (μ (s i)).toReal) =ᶠ[li] m := by rfl) :
(fun i => (∫ x in s i, f x ∂μ) - m i • f x) =o[li] m :=
(hx.mono_left inf_le_left).integral_sub_linear_isLittleO_ae hfm (μ.finiteAt_nhds x) hs m hsμ
#align continuous_at.integral_sub_linear_is_o_ae ContinuousAt.integral_sub_linear_isLittleO_ae
/-- Fundamental theorem of calculus for set integrals, `nhdsWithin` version: if `μ` is a locally
finite measure, `f` is continuous on a measurable set `t`, and `a ∈ t`, then `∫ x in (s i), f x ∂μ =
μ (s i) • f a + o(μ (s i))` at `li` provided that `s i` tends to `(𝓝[t] a).smallSets` along `li`.
Since `μ (s i)` is an `ℝ≥0∞` number, we use `(μ (s i)).toReal` in the actual statement.
Often there is a good formula for `(μ (s i)).toReal`, so the formalization can take an optional
argument `m` with this formula and a proof of `(fun i => (μ (s i)).toReal) =ᶠ[li] m`. Without these
arguments, `m i = (μ (s i)).toReal` is used in the output. -/
theorem ContinuousOn.integral_sub_linear_isLittleO_ae [TopologicalSpace X] [OpensMeasurableSpace X]
[SecondCountableTopologyEither X E] {μ : Measure X}
[IsLocallyFiniteMeasure μ] {x : X} {t : Set X} {f : X → E} (hft : ContinuousOn f t) (hx : x ∈ t)
(ht : MeasurableSet t) {s : ι → Set X} {li : Filter ι} (hs : Tendsto s li (𝓝[t] x).smallSets)
(m : ι → ℝ := fun i => (μ (s i)).toReal)
(hsμ : (fun i => (μ (s i)).toReal) =ᶠ[li] m := by rfl) :
(fun i => (∫ x in s i, f x ∂μ) - m i • f x) =o[li] m :=
(hft x hx).integral_sub_linear_isLittleO_ae ht
⟨t, self_mem_nhdsWithin, hft.aestronglyMeasurable ht⟩ hs m hsμ
#align continuous_on.integral_sub_linear_is_o_ae ContinuousOn.integral_sub_linear_isLittleO_ae
end FTC
section
/-! ### Continuous linear maps composed with integration
The goal of this section is to prove that integration commutes with continuous linear maps.
This holds for simple functions. The general result follows from the continuity of all involved
operations on the space `L¹`. Note that composition by a continuous linear map on `L¹` is not just
the composition, as we are dealing with classes of functions, but it has already been defined
as `ContinuousLinearMap.compLp`. We take advantage of this construction here.
-/
open scoped ComplexConjugate
variable {μ : Measure X} {𝕜 : Type*} [RCLike 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E]
[NormedAddCommGroup F] [NormedSpace 𝕜 F] {p : ENNReal}
namespace ContinuousLinearMap
variable [NormedSpace ℝ F]
theorem integral_compLp (L : E →L[𝕜] F) (φ : Lp E p μ) :
∫ x, (L.compLp φ) x ∂μ = ∫ x, L (φ x) ∂μ :=
integral_congr_ae <| coeFn_compLp _ _
set_option linter.uppercaseLean3 false in
#align continuous_linear_map.integral_comp_Lp ContinuousLinearMap.integral_compLp
theorem setIntegral_compLp (L : E →L[𝕜] F) (φ : Lp E p μ) {s : Set X} (hs : MeasurableSet s) :
∫ x in s, (L.compLp φ) x ∂μ = ∫ x in s, L (φ x) ∂μ :=
setIntegral_congr_ae hs ((L.coeFn_compLp φ).mono fun _x hx _ => hx)
set_option linter.uppercaseLean3 false in
#align continuous_linear_map.set_integral_comp_Lp ContinuousLinearMap.setIntegral_compLp
@[deprecated (since := "2024-04-17")]
alias set_integral_compLp := setIntegral_compLp
theorem continuous_integral_comp_L1 (L : E →L[𝕜] F) :
Continuous fun φ : X →₁[μ] E => ∫ x : X, L (φ x) ∂μ := by
rw [← funext L.integral_compLp]; exact continuous_integral.comp (L.compLpL 1 μ).continuous
set_option linter.uppercaseLean3 false in
#align continuous_linear_map.continuous_integral_comp_L1 ContinuousLinearMap.continuous_integral_comp_L1
variable [CompleteSpace F] [NormedSpace ℝ E]
theorem integral_comp_comm [CompleteSpace E] (L : E →L[𝕜] F) {φ : X → E} (φ_int : Integrable φ μ) :
∫ x, L (φ x) ∂μ = L (∫ x, φ x ∂μ) := by
apply φ_int.induction (P := fun φ => ∫ x, L (φ x) ∂μ = L (∫ x, φ x ∂μ))
· intro e s s_meas _
rw [integral_indicator_const e s_meas, ← @smul_one_smul E ℝ 𝕜 _ _ _ _ _ (μ s).toReal e,
ContinuousLinearMap.map_smul, @smul_one_smul F ℝ 𝕜 _ _ _ _ _ (μ s).toReal (L e), ←
integral_indicator_const (L e) s_meas]
congr 1 with a
rw [← Function.comp_def L, Set.indicator_comp_of_zero L.map_zero, Function.comp_apply]
· intro f g _ f_int g_int hf hg
simp [L.map_add, integral_add (μ := μ) f_int g_int,
integral_add (μ := μ) (L.integrable_comp f_int) (L.integrable_comp g_int), hf, hg]
· exact isClosed_eq L.continuous_integral_comp_L1 (L.continuous.comp continuous_integral)
· intro f g hfg _ hf
convert hf using 1 <;> clear hf
· exact integral_congr_ae (hfg.fun_comp L).symm
· rw [integral_congr_ae hfg.symm]
#align continuous_linear_map.integral_comp_comm ContinuousLinearMap.integral_comp_comm
theorem integral_apply {H : Type*} [NormedAddCommGroup H] [NormedSpace 𝕜 H] {φ : X → H →L[𝕜] E}
(φ_int : Integrable φ μ) (v : H) : (∫ x, φ x ∂μ) v = ∫ x, φ x v ∂μ := by
by_cases hE : CompleteSpace E
· exact ((ContinuousLinearMap.apply 𝕜 E v).integral_comp_comm φ_int).symm
· rcases subsingleton_or_nontrivial H with hH|hH
· simp [Subsingleton.eq_zero v]
· have : ¬(CompleteSpace (H →L[𝕜] E)) := by
rwa [SeparatingDual.completeSpace_continuousLinearMap_iff]
simp [integral, hE, this]
#align continuous_linear_map.integral_apply ContinuousLinearMap.integral_apply
theorem _root_.ContinuousMultilinearMap.integral_apply {ι : Type*} [Fintype ι] {M : ι → Type*}
[∀ i, NormedAddCommGroup (M i)] [∀ i, NormedSpace 𝕜 (M i)]
{φ : X → ContinuousMultilinearMap 𝕜 M E} (φ_int : Integrable φ μ) (m : ∀ i, M i) :
(∫ x, φ x ∂μ) m = ∫ x, φ x m ∂μ := by
by_cases hE : CompleteSpace E
· exact ((ContinuousMultilinearMap.apply 𝕜 M E m).integral_comp_comm φ_int).symm
· by_cases hm : ∀ i, m i ≠ 0
· have : ¬ CompleteSpace (ContinuousMultilinearMap 𝕜 M E) := by
rwa [SeparatingDual.completeSpace_continuousMultilinearMap_iff _ _ hm]
simp [integral, hE, this]
· push_neg at hm
rcases hm with ⟨i, hi⟩
simp [ContinuousMultilinearMap.map_coord_zero _ i hi]
variable [CompleteSpace E]
theorem integral_comp_comm' (L : E →L[𝕜] F) {K} (hL : AntilipschitzWith K L) (φ : X → E) :
∫ x, L (φ x) ∂μ = L (∫ x, φ x ∂μ) := by
by_cases h : Integrable φ μ
· exact integral_comp_comm L h
have : ¬Integrable (fun x => L (φ x)) μ := by
rwa [← Function.comp_def,
LipschitzWith.integrable_comp_iff_of_antilipschitz L.lipschitz hL L.map_zero]
simp [integral_undef, h, this]
#align continuous_linear_map.integral_comp_comm' ContinuousLinearMap.integral_comp_comm'
theorem integral_comp_L1_comm (L : E →L[𝕜] F) (φ : X →₁[μ] E) :
∫ x, L (φ x) ∂μ = L (∫ x, φ x ∂μ) :=
L.integral_comp_comm (L1.integrable_coeFn φ)
set_option linter.uppercaseLean3 false in
#align continuous_linear_map.integral_comp_L1_comm ContinuousLinearMap.integral_comp_L1_comm
end ContinuousLinearMap
namespace LinearIsometry
variable [CompleteSpace F] [NormedSpace ℝ F] [CompleteSpace E] [NormedSpace ℝ E]
theorem integral_comp_comm (L : E →ₗᵢ[𝕜] F) (φ : X → E) : ∫ x, L (φ x) ∂μ = L (∫ x, φ x ∂μ) :=
L.toContinuousLinearMap.integral_comp_comm' L.antilipschitz _
#align linear_isometry.integral_comp_comm LinearIsometry.integral_comp_comm
end LinearIsometry
namespace ContinuousLinearEquiv
variable [NormedSpace ℝ F] [NormedSpace ℝ E]
theorem integral_comp_comm (L : E ≃L[𝕜] F) (φ : X → E) : ∫ x, L (φ x) ∂μ = L (∫ x, φ x ∂μ) := by
have : CompleteSpace E ↔ CompleteSpace F :=
completeSpace_congr (e := L.toEquiv) L.uniformEmbedding
obtain ⟨_, _⟩|⟨_, _⟩ := iff_iff_and_or_not_and_not.mp this
· exact L.toContinuousLinearMap.integral_comp_comm' L.antilipschitz _
· simp [integral, *]
#align continuous_linear_equiv.integral_comp_comm ContinuousLinearEquiv.integral_comp_comm
end ContinuousLinearEquiv
@[norm_cast]
theorem integral_ofReal {f : X → ℝ} : ∫ x, (f x : 𝕜) ∂μ = ↑(∫ x, f x ∂μ) :=
(@RCLike.ofRealLI 𝕜 _).integral_comp_comm f
#align integral_of_real integral_ofReal
theorem integral_re {f : X → 𝕜} (hf : Integrable f μ) :
∫ x, RCLike.re (f x) ∂μ = RCLike.re (∫ x, f x ∂μ) :=
(@RCLike.reCLM 𝕜 _).integral_comp_comm hf
#align integral_re integral_re
theorem integral_im {f : X → 𝕜} (hf : Integrable f μ) :
∫ x, RCLike.im (f x) ∂μ = RCLike.im (∫ x, f x ∂μ) :=
(@RCLike.imCLM 𝕜 _).integral_comp_comm hf
#align integral_im integral_im
theorem integral_conj {f : X → 𝕜} : ∫ x, conj (f x) ∂μ = conj (∫ x, f x ∂μ) :=
(@RCLike.conjLIE 𝕜 _).toLinearIsometry.integral_comp_comm f
#align integral_conj integral_conj
theorem integral_coe_re_add_coe_im {f : X → 𝕜} (hf : Integrable f μ) :
∫ x, (re (f x) : 𝕜) ∂μ + (∫ x, (im (f x) : 𝕜) ∂μ) * RCLike.I = ∫ x, f x ∂μ := by
rw [mul_comm, ← smul_eq_mul, ← integral_smul, ← integral_add]
· congr
ext1 x
rw [smul_eq_mul, mul_comm, RCLike.re_add_im]
· exact hf.re.ofReal
· exact hf.im.ofReal.smul (𝕜 := 𝕜) (β := 𝕜) RCLike.I
#align integral_coe_re_add_coe_im integral_coe_re_add_coe_im
theorem integral_re_add_im {f : X → 𝕜} (hf : Integrable f μ) :
((∫ x, RCLike.re (f x) ∂μ : ℝ) : 𝕜) + (∫ x, RCLike.im (f x) ∂μ : ℝ) * RCLike.I =
∫ x, f x ∂μ := by
rw [← integral_ofReal, ← integral_ofReal, integral_coe_re_add_coe_im hf]
#align integral_re_add_im integral_re_add_im
theorem setIntegral_re_add_im {f : X → 𝕜} {i : Set X} (hf : IntegrableOn f i μ) :
((∫ x in i, RCLike.re (f x) ∂μ : ℝ) : 𝕜) + (∫ x in i, RCLike.im (f x) ∂μ : ℝ) * RCLike.I =
∫ x in i, f x ∂μ :=
integral_re_add_im hf
#align set_integral_re_add_im setIntegral_re_add_im
@[deprecated (since := "2024-04-17")]
alias set_integral_re_add_im := setIntegral_re_add_im
variable [NormedSpace ℝ E] [NormedSpace ℝ F]
lemma swap_integral (f : X → E × F) : (∫ x, f x ∂μ).swap = ∫ x, (f x).swap ∂μ :=
.symm <| (ContinuousLinearEquiv.prodComm ℝ E F).integral_comp_comm f
theorem fst_integral [CompleteSpace F] {f : X → E × F} (hf : Integrable f μ) :
(∫ x, f x ∂μ).1 = ∫ x, (f x).1 ∂μ := by
by_cases hE : CompleteSpace E
· exact ((ContinuousLinearMap.fst ℝ E F).integral_comp_comm hf).symm
· have : ¬(CompleteSpace (E × F)) := fun h ↦ hE <| .fst_of_prod (β := F)
simp [integral, *]
#align fst_integral fst_integral
theorem snd_integral [CompleteSpace E] {f : X → E × F} (hf : Integrable f μ) :
(∫ x, f x ∂μ).2 = ∫ x, (f x).2 ∂μ := by
rw [← Prod.fst_swap, swap_integral]
exact fst_integral <| hf.snd.prod_mk hf.fst
#align snd_integral snd_integral
theorem integral_pair [CompleteSpace E] [CompleteSpace F] {f : X → E} {g : X → F}
(hf : Integrable f μ) (hg : Integrable g μ) :
∫ x, (f x, g x) ∂μ = (∫ x, f x ∂μ, ∫ x, g x ∂μ) :=
have := hf.prod_mk hg
Prod.ext (fst_integral this) (snd_integral this)
#align integral_pair integral_pair
theorem integral_smul_const {𝕜 : Type*} [RCLike 𝕜] [NormedSpace 𝕜 E] [CompleteSpace E]
(f : X → 𝕜) (c : E) :
∫ x, f x • c ∂μ = (∫ x, f x ∂μ) • c := by
by_cases hf : Integrable f μ
· exact ((1 : 𝕜 →L[𝕜] 𝕜).smulRight c).integral_comp_comm hf
· by_cases hc : c = 0
· simp [hc, integral_zero, smul_zero]
rw [integral_undef hf, integral_undef, zero_smul]
rw [integrable_smul_const hc]
simp_rw [hf, not_false_eq_true]
#align integral_smul_const integral_smul_const
theorem integral_withDensity_eq_integral_smul {f : X → ℝ≥0} (f_meas : Measurable f) (g : X → E) :
∫ x, g x ∂μ.withDensity (fun x => f x) = ∫ x, f x • g x ∂μ := by
by_cases hE : CompleteSpace E; swap; · simp [integral, hE]
by_cases hg : Integrable g (μ.withDensity fun x => f x); swap
· rw [integral_undef hg, integral_undef]
rwa [← integrable_withDensity_iff_integrable_smul f_meas]
refine Integrable.induction
(P := fun g => ∫ x, g x ∂μ.withDensity (fun x => f x) = ∫ x, f x • g x ∂μ) ?_ ?_ ?_ ?_ hg
· intro c s s_meas hs
rw [integral_indicator s_meas]
simp_rw [← indicator_smul_apply, integral_indicator s_meas]
simp only [s_meas, integral_const, Measure.restrict_apply', univ_inter, withDensity_apply]
rw [lintegral_coe_eq_integral, ENNReal.toReal_ofReal, ← integral_smul_const]
· rfl
· exact integral_nonneg fun x => NNReal.coe_nonneg _
· refine ⟨f_meas.coe_nnreal_real.aemeasurable.aestronglyMeasurable, ?_⟩
rw [withDensity_apply _ s_meas] at hs
rw [HasFiniteIntegral]
convert hs with x
simp only [NNReal.nnnorm_eq]
· intro u u' _ u_int u'_int h h'
change
(∫ x : X, u x + u' x ∂μ.withDensity fun x : X => ↑(f x)) = ∫ x : X, f x • (u x + u' x) ∂μ
simp_rw [smul_add]
rw [integral_add u_int u'_int, h, h', integral_add]
· exact (integrable_withDensity_iff_integrable_smul f_meas).1 u_int
· exact (integrable_withDensity_iff_integrable_smul f_meas).1 u'_int
· have C1 :
Continuous fun u : Lp E 1 (μ.withDensity fun x => f x) =>
∫ x, u x ∂μ.withDensity fun x => f x :=
continuous_integral
have C2 : Continuous fun u : Lp E 1 (μ.withDensity fun x => f x) => ∫ x, f x • u x ∂μ := by
have : Continuous ((fun u : Lp E 1 μ => ∫ x, u x ∂μ) ∘ withDensitySMulLI (E := E) μ f_meas) :=
continuous_integral.comp (withDensitySMulLI (E := E) μ f_meas).continuous
convert this with u
simp only [Function.comp_apply, withDensitySMulLI_apply]
exact integral_congr_ae (memℒ1_smul_of_L1_withDensity f_meas u).coeFn_toLp.symm
exact isClosed_eq C1 C2
· intro u v huv _ hu
rw [← integral_congr_ae huv, hu]
apply integral_congr_ae
filter_upwards [(ae_withDensity_iff f_meas.coe_nnreal_ennreal).1 huv] with x hx
rcases eq_or_ne (f x) 0 with (h'x | h'x)
· simp only [h'x, zero_smul]
· rw [hx _]
simpa only [Ne, ENNReal.coe_eq_zero] using h'x
#align integral_with_density_eq_integral_smul integral_withDensity_eq_integral_smul
| Mathlib/MeasureTheory/Integral/SetIntegral.lean | 1,513 | 1,526 | theorem integral_withDensity_eq_integral_smul₀ {f : X → ℝ≥0} (hf : AEMeasurable f μ) (g : X → E) :
∫ x, g x ∂μ.withDensity (fun x => f x) = ∫ x, f x • g x ∂μ := by |
let f' := hf.mk _
calc
∫ x, g x ∂μ.withDensity (fun x => f x) = ∫ x, g x ∂μ.withDensity fun x => f' x := by
congr 1
apply withDensity_congr_ae
filter_upwards [hf.ae_eq_mk] with x hx
rw [hx]
_ = ∫ x, f' x • g x ∂μ := integral_withDensity_eq_integral_smul hf.measurable_mk _
_ = ∫ x, f x • g x ∂μ := by
apply integral_congr_ae
filter_upwards [hf.ae_eq_mk] with x hx
rw [hx]
|
/-
Copyright (c) 2018 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Order.Bounds.Basic
import Mathlib.Order.WellFounded
import Mathlib.Data.Set.Image
import Mathlib.Order.Interval.Set.Basic
import Mathlib.Data.Set.Lattice
#align_import order.conditionally_complete_lattice.basic from "leanprover-community/mathlib"@"29cb56a7b35f72758b05a30490e1f10bd62c35c1"
/-!
# Theory of conditionally complete lattices.
A conditionally complete lattice is a lattice in which every non-empty bounded subset `s`
has a least upper bound and a greatest lower bound, denoted below by `sSup s` and `sInf s`.
Typical examples are `ℝ`, `ℕ`, and `ℤ` with their usual orders.
The theory is very comparable to the theory of complete lattices, except that suitable
boundedness and nonemptiness assumptions have to be added to most statements.
We introduce two predicates `BddAbove` and `BddBelow` to express this boundedness, prove
their basic properties, and then go on to prove most useful properties of `sSup` and `sInf`
in conditionally complete lattices.
To differentiate the statements between complete lattices and conditionally complete
lattices, we prefix `sInf` and `sSup` in the statements by `c`, giving `csInf` and `csSup`.
For instance, `sInf_le` is a statement in complete lattices ensuring `sInf s ≤ x`,
while `csInf_le` is the same statement in conditionally complete lattices
with an additional assumption that `s` is bounded below.
-/
open Function OrderDual Set
variable {α β γ : Type*} {ι : Sort*}
section
/-!
Extension of `sSup` and `sInf` from a preorder `α` to `WithTop α` and `WithBot α`
-/
variable [Preorder α]
open scoped Classical
noncomputable instance WithTop.instSupSet [SupSet α] :
SupSet (WithTop α) :=
⟨fun S =>
if ⊤ ∈ S then ⊤ else if BddAbove ((fun (a : α) ↦ ↑a) ⁻¹' S : Set α) then
↑(sSup ((fun (a : α) ↦ (a : WithTop α)) ⁻¹' S : Set α)) else ⊤⟩
noncomputable instance WithTop.instInfSet [InfSet α] : InfSet (WithTop α) :=
⟨fun S => if S ⊆ {⊤} ∨ ¬BddBelow S then ⊤ else ↑(sInf ((fun (a : α) ↦ ↑a) ⁻¹' S : Set α))⟩
noncomputable instance WithBot.instSupSet [SupSet α] : SupSet (WithBot α) :=
⟨(WithTop.instInfSet (α := αᵒᵈ)).sInf⟩
noncomputable instance WithBot.instInfSet [InfSet α] :
InfSet (WithBot α) :=
⟨(WithTop.instSupSet (α := αᵒᵈ)).sSup⟩
theorem WithTop.sSup_eq [SupSet α] {s : Set (WithTop α)} (hs : ⊤ ∉ s)
(hs' : BddAbove ((↑) ⁻¹' s : Set α)) : sSup s = ↑(sSup ((↑) ⁻¹' s) : α) :=
(if_neg hs).trans <| if_pos hs'
#align with_top.Sup_eq WithTop.sSup_eq
theorem WithTop.sInf_eq [InfSet α] {s : Set (WithTop α)} (hs : ¬s ⊆ {⊤}) (h's : BddBelow s) :
sInf s = ↑(sInf ((↑) ⁻¹' s) : α) :=
if_neg <| by simp [hs, h's]
#align with_top.Inf_eq WithTop.sInf_eq
theorem WithBot.sInf_eq [InfSet α] {s : Set (WithBot α)} (hs : ⊥ ∉ s)
(hs' : BddBelow ((↑) ⁻¹' s : Set α)) : sInf s = ↑(sInf ((↑) ⁻¹' s) : α) :=
(if_neg hs).trans <| if_pos hs'
#align with_bot.Inf_eq WithBot.sInf_eq
theorem WithBot.sSup_eq [SupSet α] {s : Set (WithBot α)} (hs : ¬s ⊆ {⊥}) (h's : BddAbove s) :
sSup s = ↑(sSup ((↑) ⁻¹' s) : α) :=
WithTop.sInf_eq (α := αᵒᵈ) hs h's
#align with_bot.Sup_eq WithBot.sSup_eq
@[simp]
theorem WithTop.sInf_empty [InfSet α] : sInf (∅ : Set (WithTop α)) = ⊤ :=
if_pos <| by simp
#align with_top.cInf_empty WithTop.sInf_empty
@[simp]
theorem WithTop.iInf_empty [IsEmpty ι] [InfSet α] (f : ι → WithTop α) :
⨅ i, f i = ⊤ := by rw [iInf, range_eq_empty, WithTop.sInf_empty]
#align with_top.cinfi_empty WithTop.iInf_empty
theorem WithTop.coe_sInf' [InfSet α] {s : Set α} (hs : s.Nonempty) (h's : BddBelow s) :
↑(sInf s) = (sInf ((fun (a : α) ↦ ↑a) '' s) : WithTop α) := by
obtain ⟨x, hx⟩ := hs
change _ = ite _ _ _
split_ifs with h
· rcases h with h1 | h2
· cases h1 (mem_image_of_mem _ hx)
· exact (h2 (Monotone.map_bddBelow coe_mono h's)).elim
· rw [preimage_image_eq]
exact Option.some_injective _
#align with_top.coe_Inf' WithTop.coe_sInf'
-- Porting note: the mathlib3 proof uses `range_comp` in the opposite direction and
-- does not need `rfl`.
@[norm_cast]
theorem WithTop.coe_iInf [Nonempty ι] [InfSet α] {f : ι → α} (hf : BddBelow (range f)) :
↑(⨅ i, f i) = (⨅ i, f i : WithTop α) := by
rw [iInf, iInf, WithTop.coe_sInf' (range_nonempty f) hf, ← range_comp]
rfl
#align with_top.coe_infi WithTop.coe_iInf
theorem WithTop.coe_sSup' [SupSet α] {s : Set α} (hs : BddAbove s) :
↑(sSup s) = (sSup ((fun (a : α) ↦ ↑a) '' s) : WithTop α) := by
change _ = ite _ _ _
rw [if_neg, preimage_image_eq, if_pos hs]
· exact Option.some_injective _
· rintro ⟨x, _, ⟨⟩⟩
#align with_top.coe_Sup' WithTop.coe_sSup'
-- Porting note: the mathlib3 proof uses `range_comp` in the opposite direction and
-- does not need `rfl`.
@[norm_cast]
theorem WithTop.coe_iSup [SupSet α] (f : ι → α) (h : BddAbove (Set.range f)) :
↑(⨆ i, f i) = (⨆ i, f i : WithTop α) := by
rw [iSup, iSup, WithTop.coe_sSup' h, ← range_comp]; rfl
#align with_top.coe_supr WithTop.coe_iSup
@[simp]
theorem WithBot.sSup_empty [SupSet α] : sSup (∅ : Set (WithBot α)) = ⊥ :=
WithTop.sInf_empty (α := αᵒᵈ)
#align with_bot.cSup_empty WithBot.sSup_empty
@[deprecated (since := "2024-06-10")] alias WithBot.csSup_empty := WithBot.sSup_empty
@[simp]
theorem WithBot.ciSup_empty [IsEmpty ι] [SupSet α] (f : ι → WithBot α) :
⨆ i, f i = ⊥ :=
WithTop.iInf_empty (α := αᵒᵈ) _
#align with_bot.csupr_empty WithBot.ciSup_empty
@[norm_cast]
theorem WithBot.coe_sSup' [SupSet α] {s : Set α} (hs : s.Nonempty) (h's : BddAbove s) :
↑(sSup s) = (sSup ((fun (a : α) ↦ ↑a) '' s) : WithBot α) :=
WithTop.coe_sInf' (α := αᵒᵈ) hs h's
#align with_bot.coe_Sup' WithBot.coe_sSup'
@[norm_cast]
theorem WithBot.coe_iSup [Nonempty ι] [SupSet α] {f : ι → α} (hf : BddAbove (range f)) :
↑(⨆ i, f i) = (⨆ i, f i : WithBot α) :=
WithTop.coe_iInf (α := αᵒᵈ) hf
#align with_bot.coe_supr WithBot.coe_iSup
@[norm_cast]
theorem WithBot.coe_sInf' [InfSet α] {s : Set α} (hs : BddBelow s) :
↑(sInf s) = (sInf ((fun (a : α) ↦ ↑a) '' s) : WithBot α) :=
WithTop.coe_sSup' (α := αᵒᵈ) hs
#align with_bot.coe_Inf' WithBot.coe_sInf'
@[norm_cast]
theorem WithBot.coe_iInf [InfSet α] (f : ι → α) (h : BddBelow (Set.range f)) :
↑(⨅ i, f i) = (⨅ i, f i : WithBot α) :=
WithTop.coe_iSup (α := αᵒᵈ) _ h
#align with_bot.coe_infi WithBot.coe_iInf
end
/-- A conditionally complete lattice is a lattice in which
every nonempty subset which is bounded above has a supremum, and
every nonempty subset which is bounded below has an infimum.
Typical examples are real numbers or natural numbers.
To differentiate the statements from the corresponding statements in (unconditional)
complete lattices, we prefix sInf and subₛ by a c everywhere. The same statements should
hold in both worlds, sometimes with additional assumptions of nonemptiness or
boundedness. -/
class ConditionallyCompleteLattice (α : Type*) extends Lattice α, SupSet α, InfSet α where
/-- `a ≤ sSup s` for all `a ∈ s`. -/
le_csSup : ∀ s a, BddAbove s → a ∈ s → a ≤ sSup s
/-- `sSup s ≤ a` for all `a ∈ upperBounds s`. -/
csSup_le : ∀ s a, Set.Nonempty s → a ∈ upperBounds s → sSup s ≤ a
/-- `sInf s ≤ a` for all `a ∈ s`. -/
csInf_le : ∀ s a, BddBelow s → a ∈ s → sInf s ≤ a
/-- `a ≤ sInf s` for all `a ∈ lowerBounds s`. -/
le_csInf : ∀ s a, Set.Nonempty s → a ∈ lowerBounds s → a ≤ sInf s
#align conditionally_complete_lattice ConditionallyCompleteLattice
-- Porting note: mathlib3 used `renaming`
/-- A conditionally complete linear order is a linear order in which
every nonempty subset which is bounded above has a supremum, and
every nonempty subset which is bounded below has an infimum.
Typical examples are real numbers or natural numbers.
To differentiate the statements from the corresponding statements in (unconditional)
complete linear orders, we prefix sInf and sSup by a c everywhere. The same statements should
hold in both worlds, sometimes with additional assumptions of nonemptiness or
boundedness. -/
class ConditionallyCompleteLinearOrder (α : Type*) extends ConditionallyCompleteLattice α where
/-- A `ConditionallyCompleteLinearOrder` is total. -/
le_total (a b : α) : a ≤ b ∨ b ≤ a
/-- In a `ConditionallyCompleteLinearOrder`, we assume the order relations are all decidable. -/
decidableLE : DecidableRel (· ≤ · : α → α → Prop)
/-- In a `ConditionallyCompleteLinearOrder`, we assume the order relations are all decidable. -/
decidableEq : DecidableEq α := @decidableEqOfDecidableLE _ _ decidableLE
/-- In a `ConditionallyCompleteLinearOrder`, we assume the order relations are all decidable. -/
decidableLT : DecidableRel (· < · : α → α → Prop) :=
@decidableLTOfDecidableLE _ _ decidableLE
/-- If a set is not bounded above, its supremum is by convention `sSup ∅`. -/
csSup_of_not_bddAbove : ∀ s, ¬BddAbove s → sSup s = sSup (∅ : Set α)
/-- If a set is not bounded below, its infimum is by convention `sInf ∅`. -/
csInf_of_not_bddBelow : ∀ s, ¬BddBelow s → sInf s = sInf (∅ : Set α)
#align conditionally_complete_linear_order ConditionallyCompleteLinearOrder
instance ConditionallyCompleteLinearOrder.toLinearOrder [ConditionallyCompleteLinearOrder α] :
LinearOrder α :=
{ ‹ConditionallyCompleteLinearOrder α› with
max := Sup.sup, min := Inf.inf,
min_def := fun a b ↦ by
by_cases hab : a = b
· simp [hab]
· rcases ConditionallyCompleteLinearOrder.le_total a b with (h₁ | h₂)
· simp [h₁]
· simp [show ¬(a ≤ b) from fun h => hab (le_antisymm h h₂), h₂]
max_def := fun a b ↦ by
by_cases hab : a = b
· simp [hab]
· rcases ConditionallyCompleteLinearOrder.le_total a b with (h₁ | h₂)
· simp [h₁]
· simp [show ¬(a ≤ b) from fun h => hab (le_antisymm h h₂), h₂] }
/-- A conditionally complete linear order with `Bot` is a linear order with least element, in which
every nonempty subset which is bounded above has a supremum, and every nonempty subset (necessarily
bounded below) has an infimum. A typical example is the natural numbers.
To differentiate the statements from the corresponding statements in (unconditional)
complete linear orders, we prefix `sInf` and `sSup` by a c everywhere. The same statements should
hold in both worlds, sometimes with additional assumptions of nonemptiness or
boundedness. -/
class ConditionallyCompleteLinearOrderBot (α : Type*) extends ConditionallyCompleteLinearOrder α,
Bot α where
/-- `⊥` is the least element -/
bot_le : ∀ x : α, ⊥ ≤ x
/-- The supremum of the empty set is `⊥` -/
csSup_empty : sSup ∅ = ⊥
#align conditionally_complete_linear_order_bot ConditionallyCompleteLinearOrderBot
-- see Note [lower instance priority]
instance (priority := 100) ConditionallyCompleteLinearOrderBot.toOrderBot
[h : ConditionallyCompleteLinearOrderBot α] : OrderBot α :=
{ h with }
#align conditionally_complete_linear_order_bot.to_order_bot ConditionallyCompleteLinearOrderBot.toOrderBot
-- see Note [lower instance priority]
/-- A complete lattice is a conditionally complete lattice, as there are no restrictions
on the properties of sInf and sSup in a complete lattice. -/
instance (priority := 100) CompleteLattice.toConditionallyCompleteLattice [CompleteLattice α] :
ConditionallyCompleteLattice α :=
{ ‹CompleteLattice α› with
le_csSup := by intros; apply le_sSup; assumption
csSup_le := by intros; apply sSup_le; assumption
csInf_le := by intros; apply sInf_le; assumption
le_csInf := by intros; apply le_sInf; assumption }
#align complete_lattice.to_conditionally_complete_lattice CompleteLattice.toConditionallyCompleteLattice
-- see Note [lower instance priority]
instance (priority := 100) CompleteLinearOrder.toConditionallyCompleteLinearOrderBot {α : Type*}
[h : CompleteLinearOrder α] : ConditionallyCompleteLinearOrderBot α :=
{ CompleteLattice.toConditionallyCompleteLattice, h with
csSup_empty := sSup_empty
csSup_of_not_bddAbove := fun s H ↦ (H (OrderTop.bddAbove s)).elim
csInf_of_not_bddBelow := fun s H ↦ (H (OrderBot.bddBelow s)).elim }
#align complete_linear_order.to_conditionally_complete_linear_order_bot CompleteLinearOrder.toConditionallyCompleteLinearOrderBot
section
open scoped Classical
/-- A well founded linear order is conditionally complete, with a bottom element. -/
noncomputable abbrev IsWellOrder.conditionallyCompleteLinearOrderBot (α : Type*)
[i₁ : _root_.LinearOrder α] [i₂ : OrderBot α] [h : IsWellOrder α (· < ·)] :
ConditionallyCompleteLinearOrderBot α :=
{ i₁, i₂, LinearOrder.toLattice with
sInf := fun s => if hs : s.Nonempty then h.wf.min s hs else ⊥
csInf_le := fun s a _ has => by
have s_ne : s.Nonempty := ⟨a, has⟩
simpa [s_ne] using not_lt.1 (h.wf.not_lt_min s s_ne has)
le_csInf := fun s a hs has => by
simp only [hs, dif_pos]
exact has (h.wf.min_mem s hs)
sSup := fun s => if hs : (upperBounds s).Nonempty then h.wf.min _ hs else ⊥
le_csSup := fun s a hs has => by
have h's : (upperBounds s).Nonempty := hs
simp only [h's, dif_pos]
exact h.wf.min_mem _ h's has
csSup_le := fun s a _ has => by
have h's : (upperBounds s).Nonempty := ⟨a, has⟩
simp only [h's, dif_pos]
simpa using h.wf.not_lt_min _ h's has
csSup_empty := by simpa using eq_bot_iff.2 (not_lt.1 <| h.wf.not_lt_min _ _ <| mem_univ ⊥)
csSup_of_not_bddAbove := by
intro s H
have B : ¬((upperBounds s).Nonempty) := H
simp only [B, dite_false, upperBounds_empty, univ_nonempty, dite_true]
exact le_antisymm bot_le (WellFounded.min_le _ (mem_univ _))
csInf_of_not_bddBelow := fun s H ↦ (H (OrderBot.bddBelow s)).elim }
#align is_well_order.conditionally_complete_linear_order_bot IsWellOrder.conditionallyCompleteLinearOrderBot
end
namespace OrderDual
instance instConditionallyCompleteLattice (α : Type*) [ConditionallyCompleteLattice α] :
ConditionallyCompleteLattice αᵒᵈ :=
{ OrderDual.instInf α, OrderDual.instSup α, OrderDual.instLattice α with
le_csSup := ConditionallyCompleteLattice.csInf_le (α := α)
csSup_le := ConditionallyCompleteLattice.le_csInf (α := α)
le_csInf := ConditionallyCompleteLattice.csSup_le (α := α)
csInf_le := ConditionallyCompleteLattice.le_csSup (α := α) }
instance (α : Type*) [ConditionallyCompleteLinearOrder α] : ConditionallyCompleteLinearOrder αᵒᵈ :=
{ OrderDual.instConditionallyCompleteLattice α, OrderDual.instLinearOrder α with
csSup_of_not_bddAbove := ConditionallyCompleteLinearOrder.csInf_of_not_bddBelow (α := α)
csInf_of_not_bddBelow := ConditionallyCompleteLinearOrder.csSup_of_not_bddAbove (α := α) }
end OrderDual
/-- Create a `ConditionallyCompleteLattice` from a `PartialOrder` and `sup` function
that returns the least upper bound of a nonempty set which is bounded above. Usually this
constructor provides poor definitional equalities. If other fields are known explicitly, they
should be provided; for example, if `inf` is known explicitly, construct the
`ConditionallyCompleteLattice` instance as
```
instance : ConditionallyCompleteLattice my_T :=
{ inf := better_inf,
le_inf := ...,
inf_le_right := ...,
inf_le_left := ...
-- don't care to fix sup, sInf
..conditionallyCompleteLatticeOfsSup my_T _ }
```
-/
def conditionallyCompleteLatticeOfsSup (α : Type*) [H1 : PartialOrder α] [H2 : SupSet α]
(bddAbove_pair : ∀ a b : α, BddAbove ({a, b} : Set α))
(bddBelow_pair : ∀ a b : α, BddBelow ({a, b} : Set α))
(isLUB_sSup : ∀ s : Set α, BddAbove s → s.Nonempty → IsLUB s (sSup s)) :
ConditionallyCompleteLattice α :=
{ H1, H2 with
sup := fun a b => sSup {a, b}
le_sup_left := fun a b =>
(isLUB_sSup {a, b} (bddAbove_pair a b) (insert_nonempty _ _)).1 (mem_insert _ _)
le_sup_right := fun a b =>
(isLUB_sSup {a, b} (bddAbove_pair a b) (insert_nonempty _ _)).1
(mem_insert_of_mem _ (mem_singleton _))
sup_le := fun a b _ hac hbc =>
(isLUB_sSup {a, b} (bddAbove_pair a b) (insert_nonempty _ _)).2
(forall_insert_of_forall (forall_eq.mpr hbc) hac)
inf := fun a b => sSup (lowerBounds {a, b})
inf_le_left := fun a b =>
(isLUB_sSup (lowerBounds {a, b}) (Nonempty.bddAbove_lowerBounds ⟨a, mem_insert _ _⟩)
(bddBelow_pair a b)).2
fun _ hc => hc <| mem_insert _ _
inf_le_right := fun a b =>
(isLUB_sSup (lowerBounds {a, b}) (Nonempty.bddAbove_lowerBounds ⟨a, mem_insert _ _⟩)
(bddBelow_pair a b)).2
fun _ hc => hc <| mem_insert_of_mem _ (mem_singleton _)
le_inf := fun c a b hca hcb =>
(isLUB_sSup (lowerBounds {a, b}) (Nonempty.bddAbove_lowerBounds ⟨a, mem_insert _ _⟩)
⟨c, forall_insert_of_forall (forall_eq.mpr hcb) hca⟩).1
(forall_insert_of_forall (forall_eq.mpr hcb) hca)
sInf := fun s => sSup (lowerBounds s)
csSup_le := fun s a hs ha => (isLUB_sSup s ⟨a, ha⟩ hs).2 ha
le_csSup := fun s a hs ha => (isLUB_sSup s hs ⟨a, ha⟩).1 ha
csInf_le := fun s a hs ha =>
(isLUB_sSup (lowerBounds s) (Nonempty.bddAbove_lowerBounds ⟨a, ha⟩) hs).2 fun _ hb => hb ha
le_csInf := fun s a hs ha =>
(isLUB_sSup (lowerBounds s) hs.bddAbove_lowerBounds ⟨a, ha⟩).1 ha }
#align conditionally_complete_lattice_of_Sup conditionallyCompleteLatticeOfsSup
/-- Create a `ConditionallyCompleteLattice` from a `PartialOrder` and `inf` function
that returns the greatest lower bound of a nonempty set which is bounded below. Usually this
constructor provides poor definitional equalities. If other fields are known explicitly, they
should be provided; for example, if `inf` is known explicitly, construct the
`ConditionallyCompleteLattice` instance as
```
instance : ConditionallyCompleteLattice my_T :=
{ inf := better_inf,
le_inf := ...,
inf_le_right := ...,
inf_le_left := ...
-- don't care to fix sup, sSup
..conditionallyCompleteLatticeOfsInf my_T _ }
```
-/
def conditionallyCompleteLatticeOfsInf (α : Type*) [H1 : PartialOrder α] [H2 : InfSet α]
(bddAbove_pair : ∀ a b : α, BddAbove ({a, b} : Set α))
(bddBelow_pair : ∀ a b : α, BddBelow ({a, b} : Set α))
(isGLB_sInf : ∀ s : Set α, BddBelow s → s.Nonempty → IsGLB s (sInf s)) :
ConditionallyCompleteLattice α :=
{ H1, H2 with
inf := fun a b => sInf {a, b}
inf_le_left := fun a b =>
(isGLB_sInf {a, b} (bddBelow_pair a b) (insert_nonempty _ _)).1 (mem_insert _ _)
inf_le_right := fun a b =>
(isGLB_sInf {a, b} (bddBelow_pair a b) (insert_nonempty _ _)).1
(mem_insert_of_mem _ (mem_singleton _))
le_inf := fun _ a b hca hcb =>
(isGLB_sInf {a, b} (bddBelow_pair a b) (insert_nonempty _ _)).2
(forall_insert_of_forall (forall_eq.mpr hcb) hca)
sup := fun a b => sInf (upperBounds {a, b})
le_sup_left := fun a b =>
(isGLB_sInf (upperBounds {a, b}) (Nonempty.bddBelow_upperBounds ⟨a, mem_insert _ _⟩)
(bddAbove_pair a b)).2
fun _ hc => hc <| mem_insert _ _
le_sup_right := fun a b =>
(isGLB_sInf (upperBounds {a, b}) (Nonempty.bddBelow_upperBounds ⟨a, mem_insert _ _⟩)
(bddAbove_pair a b)).2
fun _ hc => hc <| mem_insert_of_mem _ (mem_singleton _)
sup_le := fun a b c hac hbc =>
(isGLB_sInf (upperBounds {a, b}) (Nonempty.bddBelow_upperBounds ⟨a, mem_insert _ _⟩)
⟨c, forall_insert_of_forall (forall_eq.mpr hbc) hac⟩).1
(forall_insert_of_forall (forall_eq.mpr hbc) hac)
sSup := fun s => sInf (upperBounds s)
le_csInf := fun s a hs ha => (isGLB_sInf s ⟨a, ha⟩ hs).2 ha
csInf_le := fun s a hs ha => (isGLB_sInf s hs ⟨a, ha⟩).1 ha
le_csSup := fun s a hs ha =>
(isGLB_sInf (upperBounds s) (Nonempty.bddBelow_upperBounds ⟨a, ha⟩) hs).2 fun _ hb => hb ha
csSup_le := fun s a hs ha =>
(isGLB_sInf (upperBounds s) hs.bddBelow_upperBounds ⟨a, ha⟩).1 ha }
#align conditionally_complete_lattice_of_Inf conditionallyCompleteLatticeOfsInf
/-- A version of `conditionallyCompleteLatticeOfsSup` when we already know that `α` is a lattice.
This should only be used when it is both hard and unnecessary to provide `inf` explicitly. -/
def conditionallyCompleteLatticeOfLatticeOfsSup (α : Type*) [H1 : Lattice α] [SupSet α]
(isLUB_sSup : ∀ s : Set α, BddAbove s → s.Nonempty → IsLUB s (sSup s)) :
ConditionallyCompleteLattice α :=
{ H1,
conditionallyCompleteLatticeOfsSup α
(fun a b => ⟨a ⊔ b, forall_insert_of_forall (forall_eq.mpr le_sup_right) le_sup_left⟩)
(fun a b => ⟨a ⊓ b, forall_insert_of_forall (forall_eq.mpr inf_le_right) inf_le_left⟩)
isLUB_sSup with }
#align conditionally_complete_lattice_of_lattice_of_Sup conditionallyCompleteLatticeOfLatticeOfsSup
/-- A version of `conditionallyCompleteLatticeOfsInf` when we already know that `α` is a lattice.
This should only be used when it is both hard and unnecessary to provide `sup` explicitly. -/
def conditionallyCompleteLatticeOfLatticeOfsInf (α : Type*) [H1 : Lattice α] [InfSet α]
(isGLB_sInf : ∀ s : Set α, BddBelow s → s.Nonempty → IsGLB s (sInf s)) :
ConditionallyCompleteLattice α :=
{ H1,
conditionallyCompleteLatticeOfsInf α
(fun a b => ⟨a ⊔ b, forall_insert_of_forall (forall_eq.mpr le_sup_right) le_sup_left⟩)
(fun a b => ⟨a ⊓ b, forall_insert_of_forall (forall_eq.mpr inf_le_right) inf_le_left⟩)
isGLB_sInf with }
#align conditionally_complete_lattice_of_lattice_of_Inf conditionallyCompleteLatticeOfLatticeOfsInf
section ConditionallyCompleteLattice
variable [ConditionallyCompleteLattice α] {s t : Set α} {a b : α}
theorem le_csSup (h₁ : BddAbove s) (h₂ : a ∈ s) : a ≤ sSup s :=
ConditionallyCompleteLattice.le_csSup s a h₁ h₂
#align le_cSup le_csSup
theorem csSup_le (h₁ : s.Nonempty) (h₂ : ∀ b ∈ s, b ≤ a) : sSup s ≤ a :=
ConditionallyCompleteLattice.csSup_le s a h₁ h₂
#align cSup_le csSup_le
theorem csInf_le (h₁ : BddBelow s) (h₂ : a ∈ s) : sInf s ≤ a :=
ConditionallyCompleteLattice.csInf_le s a h₁ h₂
#align cInf_le csInf_le
theorem le_csInf (h₁ : s.Nonempty) (h₂ : ∀ b ∈ s, a ≤ b) : a ≤ sInf s :=
ConditionallyCompleteLattice.le_csInf s a h₁ h₂
#align le_cInf le_csInf
theorem le_csSup_of_le (hs : BddAbove s) (hb : b ∈ s) (h : a ≤ b) : a ≤ sSup s :=
le_trans h (le_csSup hs hb)
#align le_cSup_of_le le_csSup_of_le
theorem csInf_le_of_le (hs : BddBelow s) (hb : b ∈ s) (h : b ≤ a) : sInf s ≤ a :=
le_trans (csInf_le hs hb) h
#align cInf_le_of_le csInf_le_of_le
theorem csSup_le_csSup (ht : BddAbove t) (hs : s.Nonempty) (h : s ⊆ t) : sSup s ≤ sSup t :=
csSup_le hs fun _ ha => le_csSup ht (h ha)
#align cSup_le_cSup csSup_le_csSup
theorem csInf_le_csInf (ht : BddBelow t) (hs : s.Nonempty) (h : s ⊆ t) : sInf t ≤ sInf s :=
le_csInf hs fun _ ha => csInf_le ht (h ha)
#align cInf_le_cInf csInf_le_csInf
theorem le_csSup_iff (h : BddAbove s) (hs : s.Nonempty) :
a ≤ sSup s ↔ ∀ b, b ∈ upperBounds s → a ≤ b :=
⟨fun h _ hb => le_trans h (csSup_le hs hb), fun hb => hb _ fun _ => le_csSup h⟩
#align le_cSup_iff le_csSup_iff
theorem csInf_le_iff (h : BddBelow s) (hs : s.Nonempty) : sInf s ≤ a ↔ ∀ b ∈ lowerBounds s, b ≤ a :=
⟨fun h _ hb => le_trans (le_csInf hs hb) h, fun hb => hb _ fun _ => csInf_le h⟩
#align cInf_le_iff csInf_le_iff
theorem isLUB_csSup (ne : s.Nonempty) (H : BddAbove s) : IsLUB s (sSup s) :=
⟨fun _ => le_csSup H, fun _ => csSup_le ne⟩
#align is_lub_cSup isLUB_csSup
theorem isLUB_ciSup [Nonempty ι] {f : ι → α} (H : BddAbove (range f)) :
IsLUB (range f) (⨆ i, f i) :=
isLUB_csSup (range_nonempty f) H
#align is_lub_csupr isLUB_ciSup
theorem isLUB_ciSup_set {f : β → α} {s : Set β} (H : BddAbove (f '' s)) (Hne : s.Nonempty) :
IsLUB (f '' s) (⨆ i : s, f i) := by
rw [← sSup_image']
exact isLUB_csSup (Hne.image _) H
#align is_lub_csupr_set isLUB_ciSup_set
theorem isGLB_csInf (ne : s.Nonempty) (H : BddBelow s) : IsGLB s (sInf s) :=
⟨fun _ => csInf_le H, fun _ => le_csInf ne⟩
#align is_glb_cInf isGLB_csInf
theorem isGLB_ciInf [Nonempty ι] {f : ι → α} (H : BddBelow (range f)) :
IsGLB (range f) (⨅ i, f i) :=
isGLB_csInf (range_nonempty f) H
#align is_glb_cinfi isGLB_ciInf
theorem isGLB_ciInf_set {f : β → α} {s : Set β} (H : BddBelow (f '' s)) (Hne : s.Nonempty) :
IsGLB (f '' s) (⨅ i : s, f i) :=
isLUB_ciSup_set (α := αᵒᵈ) H Hne
#align is_glb_cinfi_set isGLB_ciInf_set
theorem ciSup_le_iff [Nonempty ι] {f : ι → α} {a : α} (hf : BddAbove (range f)) :
iSup f ≤ a ↔ ∀ i, f i ≤ a :=
(isLUB_le_iff <| isLUB_ciSup hf).trans forall_mem_range
#align csupr_le_iff ciSup_le_iff
theorem le_ciInf_iff [Nonempty ι] {f : ι → α} {a : α} (hf : BddBelow (range f)) :
a ≤ iInf f ↔ ∀ i, a ≤ f i :=
(le_isGLB_iff <| isGLB_ciInf hf).trans forall_mem_range
#align le_cinfi_iff le_ciInf_iff
theorem ciSup_set_le_iff {ι : Type*} {s : Set ι} {f : ι → α} {a : α} (hs : s.Nonempty)
(hf : BddAbove (f '' s)) : ⨆ i : s, f i ≤ a ↔ ∀ i ∈ s, f i ≤ a :=
(isLUB_le_iff <| isLUB_ciSup_set hf hs).trans forall_mem_image
#align csupr_set_le_iff ciSup_set_le_iff
theorem le_ciInf_set_iff {ι : Type*} {s : Set ι} {f : ι → α} {a : α} (hs : s.Nonempty)
(hf : BddBelow (f '' s)) : (a ≤ ⨅ i : s, f i) ↔ ∀ i ∈ s, a ≤ f i :=
(le_isGLB_iff <| isGLB_ciInf_set hf hs).trans forall_mem_image
#align le_cinfi_set_iff le_ciInf_set_iff
theorem IsLUB.csSup_eq (H : IsLUB s a) (ne : s.Nonempty) : sSup s = a :=
(isLUB_csSup ne ⟨a, H.1⟩).unique H
#align is_lub.cSup_eq IsLUB.csSup_eq
theorem IsLUB.ciSup_eq [Nonempty ι] {f : ι → α} (H : IsLUB (range f) a) : ⨆ i, f i = a :=
H.csSup_eq (range_nonempty f)
#align is_lub.csupr_eq IsLUB.ciSup_eq
theorem IsLUB.ciSup_set_eq {s : Set β} {f : β → α} (H : IsLUB (f '' s) a) (Hne : s.Nonempty) :
⨆ i : s, f i = a :=
IsLUB.csSup_eq (image_eq_range f s ▸ H) (image_eq_range f s ▸ Hne.image f)
#align is_lub.csupr_set_eq IsLUB.ciSup_set_eq
/-- A greatest element of a set is the supremum of this set. -/
theorem IsGreatest.csSup_eq (H : IsGreatest s a) : sSup s = a :=
H.isLUB.csSup_eq H.nonempty
#align is_greatest.cSup_eq IsGreatest.csSup_eq
theorem IsGreatest.csSup_mem (H : IsGreatest s a) : sSup s ∈ s :=
H.csSup_eq.symm ▸ H.1
#align is_greatest.Sup_mem IsGreatest.csSup_mem
theorem IsGLB.csInf_eq (H : IsGLB s a) (ne : s.Nonempty) : sInf s = a :=
(isGLB_csInf ne ⟨a, H.1⟩).unique H
#align is_glb.cInf_eq IsGLB.csInf_eq
theorem IsGLB.ciInf_eq [Nonempty ι] {f : ι → α} (H : IsGLB (range f) a) : ⨅ i, f i = a :=
H.csInf_eq (range_nonempty f)
#align is_glb.cinfi_eq IsGLB.ciInf_eq
theorem IsGLB.ciInf_set_eq {s : Set β} {f : β → α} (H : IsGLB (f '' s) a) (Hne : s.Nonempty) :
⨅ i : s, f i = a :=
IsGLB.csInf_eq (image_eq_range f s ▸ H) (image_eq_range f s ▸ Hne.image f)
#align is_glb.cinfi_set_eq IsGLB.ciInf_set_eq
/-- A least element of a set is the infimum of this set. -/
theorem IsLeast.csInf_eq (H : IsLeast s a) : sInf s = a :=
H.isGLB.csInf_eq H.nonempty
#align is_least.cInf_eq IsLeast.csInf_eq
theorem IsLeast.csInf_mem (H : IsLeast s a) : sInf s ∈ s :=
H.csInf_eq.symm ▸ H.1
#align is_least.Inf_mem IsLeast.csInf_mem
theorem subset_Icc_csInf_csSup (hb : BddBelow s) (ha : BddAbove s) : s ⊆ Icc (sInf s) (sSup s) :=
fun _ hx => ⟨csInf_le hb hx, le_csSup ha hx⟩
#align subset_Icc_cInf_cSup subset_Icc_csInf_csSup
theorem csSup_le_iff (hb : BddAbove s) (hs : s.Nonempty) : sSup s ≤ a ↔ ∀ b ∈ s, b ≤ a :=
isLUB_le_iff (isLUB_csSup hs hb)
#align cSup_le_iff csSup_le_iff
theorem le_csInf_iff (hb : BddBelow s) (hs : s.Nonempty) : a ≤ sInf s ↔ ∀ b ∈ s, a ≤ b :=
le_isGLB_iff (isGLB_csInf hs hb)
#align le_cInf_iff le_csInf_iff
theorem csSup_lower_bounds_eq_csInf {s : Set α} (h : BddBelow s) (hs : s.Nonempty) :
sSup (lowerBounds s) = sInf s :=
(isLUB_csSup h <| hs.mono fun _ hx _ hy => hy hx).unique (isGLB_csInf hs h).isLUB
#align cSup_lower_bounds_eq_cInf csSup_lower_bounds_eq_csInf
theorem csInf_upper_bounds_eq_csSup {s : Set α} (h : BddAbove s) (hs : s.Nonempty) :
sInf (upperBounds s) = sSup s :=
(isGLB_csInf h <| hs.mono fun _ hx _ hy => hy hx).unique (isLUB_csSup hs h).isGLB
#align cInf_upper_bounds_eq_cSup csInf_upper_bounds_eq_csSup
theorem not_mem_of_lt_csInf {x : α} {s : Set α} (h : x < sInf s) (hs : BddBelow s) : x ∉ s :=
fun hx => lt_irrefl _ (h.trans_le (csInf_le hs hx))
#align not_mem_of_lt_cInf not_mem_of_lt_csInf
theorem not_mem_of_csSup_lt {x : α} {s : Set α} (h : sSup s < x) (hs : BddAbove s) : x ∉ s :=
not_mem_of_lt_csInf (α := αᵒᵈ) h hs
#align not_mem_of_cSup_lt not_mem_of_csSup_lt
/-- Introduction rule to prove that `b` is the supremum of `s`: it suffices to check that `b`
is larger than all elements of `s`, and that this is not the case of any `w<b`.
See `sSup_eq_of_forall_le_of_forall_lt_exists_gt` for a version in complete lattices. -/
theorem csSup_eq_of_forall_le_of_forall_lt_exists_gt (hs : s.Nonempty) (H : ∀ a ∈ s, a ≤ b)
(H' : ∀ w, w < b → ∃ a ∈ s, w < a) : sSup s = b :=
(eq_of_le_of_not_lt (csSup_le hs H)) fun hb =>
let ⟨_, ha, ha'⟩ := H' _ hb
lt_irrefl _ <| ha'.trans_le <| le_csSup ⟨b, H⟩ ha
#align cSup_eq_of_forall_le_of_forall_lt_exists_gt csSup_eq_of_forall_le_of_forall_lt_exists_gt
/-- Introduction rule to prove that `b` is the infimum of `s`: it suffices to check that `b`
is smaller than all elements of `s`, and that this is not the case of any `w>b`.
See `sInf_eq_of_forall_ge_of_forall_gt_exists_lt` for a version in complete lattices. -/
theorem csInf_eq_of_forall_ge_of_forall_gt_exists_lt :
s.Nonempty → (∀ a ∈ s, b ≤ a) → (∀ w, b < w → ∃ a ∈ s, a < w) → sInf s = b :=
csSup_eq_of_forall_le_of_forall_lt_exists_gt (α := αᵒᵈ)
#align cInf_eq_of_forall_ge_of_forall_gt_exists_lt csInf_eq_of_forall_ge_of_forall_gt_exists_lt
/-- `b < sSup s` when there is an element `a` in `s` with `b < a`, when `s` is bounded above.
This is essentially an iff, except that the assumptions for the two implications are
slightly different (one needs boundedness above for one direction, nonemptiness and linear
order for the other one), so we formulate separately the two implications, contrary to
the `CompleteLattice` case. -/
theorem lt_csSup_of_lt (hs : BddAbove s) (ha : a ∈ s) (h : b < a) : b < sSup s :=
lt_of_lt_of_le h (le_csSup hs ha)
#align lt_cSup_of_lt lt_csSup_of_lt
/-- `sInf s < b` when there is an element `a` in `s` with `a < b`, when `s` is bounded below.
This is essentially an iff, except that the assumptions for the two implications are
slightly different (one needs boundedness below for one direction, nonemptiness and linear
order for the other one), so we formulate separately the two implications, contrary to
the `CompleteLattice` case. -/
theorem csInf_lt_of_lt : BddBelow s → a ∈ s → a < b → sInf s < b :=
lt_csSup_of_lt (α := αᵒᵈ)
#align cInf_lt_of_lt csInf_lt_of_lt
/-- If all elements of a nonempty set `s` are less than or equal to all elements
of a nonempty set `t`, then there exists an element between these sets. -/
theorem exists_between_of_forall_le (sne : s.Nonempty) (tne : t.Nonempty)
(hst : ∀ x ∈ s, ∀ y ∈ t, x ≤ y) : (upperBounds s ∩ lowerBounds t).Nonempty :=
⟨sInf t, fun x hx => le_csInf tne <| hst x hx, fun _ hy => csInf_le (sne.mono hst) hy⟩
#align exists_between_of_forall_le exists_between_of_forall_le
/-- The supremum of a singleton is the element of the singleton-/
@[simp]
theorem csSup_singleton (a : α) : sSup {a} = a :=
isGreatest_singleton.csSup_eq
#align cSup_singleton csSup_singleton
/-- The infimum of a singleton is the element of the singleton-/
@[simp]
theorem csInf_singleton (a : α) : sInf {a} = a :=
isLeast_singleton.csInf_eq
#align cInf_singleton csInf_singleton
@[simp]
theorem csSup_pair (a b : α) : sSup {a, b} = a ⊔ b :=
(@isLUB_pair _ _ a b).csSup_eq (insert_nonempty _ _)
#align cSup_pair csSup_pair
@[simp]
theorem csInf_pair (a b : α) : sInf {a, b} = a ⊓ b :=
(@isGLB_pair _ _ a b).csInf_eq (insert_nonempty _ _)
#align cInf_pair csInf_pair
/-- If a set is bounded below and above, and nonempty, its infimum is less than or equal to
its supremum. -/
theorem csInf_le_csSup (hb : BddBelow s) (ha : BddAbove s) (ne : s.Nonempty) : sInf s ≤ sSup s :=
isGLB_le_isLUB (isGLB_csInf ne hb) (isLUB_csSup ne ha) ne
#align cInf_le_cSup csInf_le_csSup
/-- The `sSup` of a union of two sets is the max of the suprema of each subset, under the
assumptions that all sets are bounded above and nonempty. -/
theorem csSup_union (hs : BddAbove s) (sne : s.Nonempty) (ht : BddAbove t) (tne : t.Nonempty) :
sSup (s ∪ t) = sSup s ⊔ sSup t :=
((isLUB_csSup sne hs).union (isLUB_csSup tne ht)).csSup_eq sne.inl
#align cSup_union csSup_union
/-- The `sInf` of a union of two sets is the min of the infima of each subset, under the assumptions
that all sets are bounded below and nonempty. -/
theorem csInf_union (hs : BddBelow s) (sne : s.Nonempty) (ht : BddBelow t) (tne : t.Nonempty) :
sInf (s ∪ t) = sInf s ⊓ sInf t :=
csSup_union (α := αᵒᵈ) hs sne ht tne
#align cInf_union csInf_union
/-- The supremum of an intersection of two sets is bounded by the minimum of the suprema of each
set, if all sets are bounded above and nonempty. -/
theorem csSup_inter_le (hs : BddAbove s) (ht : BddAbove t) (hst : (s ∩ t).Nonempty) :
sSup (s ∩ t) ≤ sSup s ⊓ sSup t :=
(csSup_le hst) fun _ hx => le_inf (le_csSup hs hx.1) (le_csSup ht hx.2)
#align cSup_inter_le csSup_inter_le
/-- The infimum of an intersection of two sets is bounded below by the maximum of the
infima of each set, if all sets are bounded below and nonempty. -/
theorem le_csInf_inter :
BddBelow s → BddBelow t → (s ∩ t).Nonempty → sInf s ⊔ sInf t ≤ sInf (s ∩ t) :=
csSup_inter_le (α := αᵒᵈ)
#align le_cInf_inter le_csInf_inter
/-- The supremum of `insert a s` is the maximum of `a` and the supremum of `s`, if `s` is
nonempty and bounded above. -/
theorem csSup_insert (hs : BddAbove s) (sne : s.Nonempty) : sSup (insert a s) = a ⊔ sSup s :=
((isLUB_csSup sne hs).insert a).csSup_eq (insert_nonempty a s)
#align cSup_insert csSup_insert
/-- The infimum of `insert a s` is the minimum of `a` and the infimum of `s`, if `s` is
nonempty and bounded below. -/
theorem csInf_insert (hs : BddBelow s) (sne : s.Nonempty) : sInf (insert a s) = a ⊓ sInf s :=
csSup_insert (α := αᵒᵈ) hs sne
#align cInf_insert csInf_insert
@[simp]
theorem csInf_Icc (h : a ≤ b) : sInf (Icc a b) = a :=
(isGLB_Icc h).csInf_eq (nonempty_Icc.2 h)
#align cInf_Icc csInf_Icc
@[simp]
theorem csInf_Ici : sInf (Ici a) = a :=
isLeast_Ici.csInf_eq
#align cInf_Ici csInf_Ici
@[simp]
theorem csInf_Ico (h : a < b) : sInf (Ico a b) = a :=
(isGLB_Ico h).csInf_eq (nonempty_Ico.2 h)
#align cInf_Ico csInf_Ico
@[simp]
theorem csInf_Ioc [DenselyOrdered α] (h : a < b) : sInf (Ioc a b) = a :=
(isGLB_Ioc h).csInf_eq (nonempty_Ioc.2 h)
#align cInf_Ioc csInf_Ioc
@[simp]
theorem csInf_Ioi [NoMaxOrder α] [DenselyOrdered α] : sInf (Ioi a) = a :=
csInf_eq_of_forall_ge_of_forall_gt_exists_lt nonempty_Ioi (fun _ => le_of_lt) fun w hw => by
simpa using exists_between hw
#align cInf_Ioi csInf_Ioi
@[simp]
theorem csInf_Ioo [DenselyOrdered α] (h : a < b) : sInf (Ioo a b) = a :=
(isGLB_Ioo h).csInf_eq (nonempty_Ioo.2 h)
#align cInf_Ioo csInf_Ioo
@[simp]
theorem csSup_Icc (h : a ≤ b) : sSup (Icc a b) = b :=
(isLUB_Icc h).csSup_eq (nonempty_Icc.2 h)
#align cSup_Icc csSup_Icc
@[simp]
theorem csSup_Ico [DenselyOrdered α] (h : a < b) : sSup (Ico a b) = b :=
(isLUB_Ico h).csSup_eq (nonempty_Ico.2 h)
#align cSup_Ico csSup_Ico
@[simp]
theorem csSup_Iic : sSup (Iic a) = a :=
isGreatest_Iic.csSup_eq
#align cSup_Iic csSup_Iic
@[simp]
theorem csSup_Iio [NoMinOrder α] [DenselyOrdered α] : sSup (Iio a) = a :=
csSup_eq_of_forall_le_of_forall_lt_exists_gt nonempty_Iio (fun _ => le_of_lt) fun w hw => by
simpa [and_comm] using exists_between hw
#align cSup_Iio csSup_Iio
@[simp]
theorem csSup_Ioc (h : a < b) : sSup (Ioc a b) = b :=
(isLUB_Ioc h).csSup_eq (nonempty_Ioc.2 h)
#align cSup_Ioc csSup_Ioc
@[simp]
theorem csSup_Ioo [DenselyOrdered α] (h : a < b) : sSup (Ioo a b) = b :=
(isLUB_Ioo h).csSup_eq (nonempty_Ioo.2 h)
#align cSup_Ioo csSup_Ioo
/-- The indexed supremum of a function is bounded above by a uniform bound-/
theorem ciSup_le [Nonempty ι] {f : ι → α} {c : α} (H : ∀ x, f x ≤ c) : iSup f ≤ c :=
csSup_le (range_nonempty f) (by rwa [forall_mem_range])
#align csupr_le ciSup_le
/-- The indexed supremum of a function is bounded below by the value taken at one point-/
theorem le_ciSup {f : ι → α} (H : BddAbove (range f)) (c : ι) : f c ≤ iSup f :=
le_csSup H (mem_range_self _)
#align le_csupr le_ciSup
theorem le_ciSup_of_le {f : ι → α} (H : BddAbove (range f)) (c : ι) (h : a ≤ f c) : a ≤ iSup f :=
le_trans h (le_ciSup H c)
#align le_csupr_of_le le_ciSup_of_le
/-- The indexed supremum of two functions are comparable if the functions are pointwise comparable-/
theorem ciSup_mono {f g : ι → α} (B : BddAbove (range g)) (H : ∀ x, f x ≤ g x) :
iSup f ≤ iSup g := by
cases isEmpty_or_nonempty ι
· rw [iSup_of_empty', iSup_of_empty']
· exact ciSup_le fun x => le_ciSup_of_le B x (H x)
#align csupr_mono ciSup_mono
theorem le_ciSup_set {f : β → α} {s : Set β} (H : BddAbove (f '' s)) {c : β} (hc : c ∈ s) :
f c ≤ ⨆ i : s, f i :=
(le_csSup H <| mem_image_of_mem f hc).trans_eq sSup_image'
#align le_csupr_set le_ciSup_set
/-- The indexed infimum of two functions are comparable if the functions are pointwise comparable-/
theorem ciInf_mono {f g : ι → α} (B : BddBelow (range f)) (H : ∀ x, f x ≤ g x) : iInf f ≤ iInf g :=
ciSup_mono (α := αᵒᵈ) B H
#align cinfi_mono ciInf_mono
/-- The indexed minimum of a function is bounded below by a uniform lower bound-/
theorem le_ciInf [Nonempty ι] {f : ι → α} {c : α} (H : ∀ x, c ≤ f x) : c ≤ iInf f :=
ciSup_le (α := αᵒᵈ) H
#align le_cinfi le_ciInf
/-- The indexed infimum of a function is bounded above by the value taken at one point-/
theorem ciInf_le {f : ι → α} (H : BddBelow (range f)) (c : ι) : iInf f ≤ f c :=
le_ciSup (α := αᵒᵈ) H c
#align cinfi_le ciInf_le
theorem ciInf_le_of_le {f : ι → α} (H : BddBelow (range f)) (c : ι) (h : f c ≤ a) : iInf f ≤ a :=
le_ciSup_of_le (α := αᵒᵈ) H c h
#align cinfi_le_of_le ciInf_le_of_le
theorem ciInf_set_le {f : β → α} {s : Set β} (H : BddBelow (f '' s)) {c : β} (hc : c ∈ s) :
⨅ i : s, f i ≤ f c :=
le_ciSup_set (α := αᵒᵈ) H hc
#align cinfi_set_le ciInf_set_le
@[simp]
theorem ciSup_const [hι : Nonempty ι] {a : α} : ⨆ _ : ι, a = a := by
rw [iSup, range_const, csSup_singleton]
#align csupr_const ciSup_const
@[simp]
theorem ciInf_const [Nonempty ι] {a : α} : ⨅ _ : ι, a = a :=
ciSup_const (α := αᵒᵈ)
#align cinfi_const ciInf_const
@[simp]
theorem ciSup_unique [Unique ι] {s : ι → α} : ⨆ i, s i = s default := by
have : ∀ i, s i = s default := fun i => congr_arg s (Unique.eq_default i)
simp only [this, ciSup_const]
#align supr_unique ciSup_unique
@[simp]
theorem ciInf_unique [Unique ι] {s : ι → α} : ⨅ i, s i = s default :=
ciSup_unique (α := αᵒᵈ)
#align infi_unique ciInf_unique
-- Porting note (#10756): new lemma
theorem ciSup_subsingleton [Subsingleton ι] (i : ι) (s : ι → α) : ⨆ i, s i = s i :=
@ciSup_unique α ι _ ⟨⟨i⟩, fun j => Subsingleton.elim j i⟩ _
-- Porting note (#10756): new lemma
theorem ciInf_subsingleton [Subsingleton ι] (i : ι) (s : ι → α) : ⨅ i, s i = s i :=
@ciInf_unique α ι _ ⟨⟨i⟩, fun j => Subsingleton.elim j i⟩ _
@[simp]
theorem ciSup_pos {p : Prop} {f : p → α} (hp : p) : ⨆ h : p, f h = f hp :=
ciSup_subsingleton hp f
#align csupr_pos ciSup_pos
@[simp]
theorem ciInf_pos {p : Prop} {f : p → α} (hp : p) : ⨅ h : p, f h = f hp :=
ciSup_pos (α := αᵒᵈ) hp
#align cinfi_pos ciInf_pos
lemma ciSup_neg {p : Prop} {f : p → α} (hp : ¬ p) :
⨆ (h : p), f h = sSup (∅ : Set α) := by
rw [iSup]
congr
rwa [range_eq_empty_iff, isEmpty_Prop]
lemma ciInf_neg {p : Prop} {f : p → α} (hp : ¬ p) :
⨅ (h : p), f h = sInf (∅ : Set α) :=
ciSup_neg (α := αᵒᵈ) hp
lemma ciSup_eq_ite {p : Prop} [Decidable p] {f : p → α} :
(⨆ h : p, f h) = if h : p then f h else sSup (∅ : Set α) := by
by_cases H : p <;> simp [ciSup_neg, H]
lemma ciInf_eq_ite {p : Prop} [Decidable p] {f : p → α} :
(⨅ h : p, f h) = if h : p then f h else sInf (∅ : Set α) :=
ciSup_eq_ite (α := αᵒᵈ)
theorem cbiSup_eq_of_forall {p : ι → Prop} {f : Subtype p → α} (hp : ∀ i, p i) :
⨆ (i) (h : p i), f ⟨i, h⟩ = iSup f := by
simp only [hp, ciSup_unique]
simp only [iSup]
congr
apply Subset.antisymm
· rintro - ⟨i, rfl⟩
simp [hp i]
· rintro - ⟨i, rfl⟩
simp
theorem cbiInf_eq_of_forall {p : ι → Prop} {f : Subtype p → α} (hp : ∀ i, p i) :
⨅ (i) (h : p i), f ⟨i, h⟩ = iInf f :=
cbiSup_eq_of_forall (α := αᵒᵈ) hp
/-- Introduction rule to prove that `b` is the supremum of `f`: it suffices to check that `b`
is larger than `f i` for all `i`, and that this is not the case of any `w<b`.
See `iSup_eq_of_forall_le_of_forall_lt_exists_gt` for a version in complete lattices. -/
theorem ciSup_eq_of_forall_le_of_forall_lt_exists_gt [Nonempty ι] {f : ι → α} (h₁ : ∀ i, f i ≤ b)
(h₂ : ∀ w, w < b → ∃ i, w < f i) : ⨆ i : ι, f i = b :=
csSup_eq_of_forall_le_of_forall_lt_exists_gt (range_nonempty f) (forall_mem_range.mpr h₁)
fun w hw => exists_range_iff.mpr <| h₂ w hw
#align csupr_eq_of_forall_le_of_forall_lt_exists_gt ciSup_eq_of_forall_le_of_forall_lt_exists_gt
-- Porting note: in mathlib3 `by exact` is not needed
/-- Introduction rule to prove that `b` is the infimum of `f`: it suffices to check that `b`
is smaller than `f i` for all `i`, and that this is not the case of any `w>b`.
See `iInf_eq_of_forall_ge_of_forall_gt_exists_lt` for a version in complete lattices. -/
theorem ciInf_eq_of_forall_ge_of_forall_gt_exists_lt [Nonempty ι] {f : ι → α} (h₁ : ∀ i, b ≤ f i)
(h₂ : ∀ w, b < w → ∃ i, f i < w) : ⨅ i : ι, f i = b := by
exact ciSup_eq_of_forall_le_of_forall_lt_exists_gt (α := αᵒᵈ) (f := ‹_›) ‹_› ‹_›
#align cinfi_eq_of_forall_ge_of_forall_gt_exists_lt ciInf_eq_of_forall_ge_of_forall_gt_exists_lt
/-- **Nested intervals lemma**: if `f` is a monotone sequence, `g` is an antitone sequence, and
`f n ≤ g n` for all `n`, then `⨆ n, f n` belongs to all the intervals `[f n, g n]`. -/
theorem Monotone.ciSup_mem_iInter_Icc_of_antitone [SemilatticeSup β] {f g : β → α} (hf : Monotone f)
(hg : Antitone g) (h : f ≤ g) : (⨆ n, f n) ∈ ⋂ n, Icc (f n) (g n) := by
refine mem_iInter.2 fun n => ?_
haveI : Nonempty β := ⟨n⟩
have : ∀ m, f m ≤ g n := fun m => hf.forall_le_of_antitone hg h m n
exact ⟨le_ciSup ⟨g <| n, forall_mem_range.2 this⟩ _, ciSup_le this⟩
#align monotone.csupr_mem_Inter_Icc_of_antitone Monotone.ciSup_mem_iInter_Icc_of_antitone
/-- Nested intervals lemma: if `[f n, g n]` is an antitone sequence of nonempty
closed intervals, then `⨆ n, f n` belongs to all the intervals `[f n, g n]`. -/
theorem ciSup_mem_iInter_Icc_of_antitone_Icc [SemilatticeSup β] {f g : β → α}
(h : Antitone fun n => Icc (f n) (g n)) (h' : ∀ n, f n ≤ g n) :
(⨆ n, f n) ∈ ⋂ n, Icc (f n) (g n) :=
Monotone.ciSup_mem_iInter_Icc_of_antitone
(fun _ n hmn => ((Icc_subset_Icc_iff (h' n)).1 (h hmn)).1)
(fun _ n hmn => ((Icc_subset_Icc_iff (h' n)).1 (h hmn)).2) h'
#align csupr_mem_Inter_Icc_of_antitone_Icc ciSup_mem_iInter_Icc_of_antitone_Icc
/-- Introduction rule to prove that `b` is the supremum of `s`: it suffices to check that
1) `b` is an upper bound
2) every other upper bound `b'` satisfies `b ≤ b'`. -/
theorem csSup_eq_of_is_forall_le_of_forall_le_imp_ge (hs : s.Nonempty) (h_is_ub : ∀ a ∈ s, a ≤ b)
(h_b_le_ub : ∀ ub, (∀ a ∈ s, a ≤ ub) → b ≤ ub) : sSup s = b :=
(csSup_le hs h_is_ub).antisymm ((h_b_le_ub _) fun _ => le_csSup ⟨b, h_is_ub⟩)
#align cSup_eq_of_is_forall_le_of_forall_le_imp_ge csSup_eq_of_is_forall_le_of_forall_le_imp_ge
lemma Set.Iic_ciInf [Nonempty ι] {f : ι → α} (hf : BddBelow (range f)) :
Iic (⨅ i, f i) = ⋂ i, Iic (f i) := by
apply Subset.antisymm
· rintro x hx - ⟨i, rfl⟩
exact hx.trans (ciInf_le hf _)
· rintro x hx
apply le_ciInf
simpa using hx
lemma Set.Ici_ciSup [Nonempty ι] {f : ι → α} (hf : BddAbove (range f)) :
Ici (⨆ i, f i) = ⋂ i, Ici (f i) :=
Iic_ciInf (α := αᵒᵈ) hf
end ConditionallyCompleteLattice
instance Pi.conditionallyCompleteLattice {ι : Type*} {α : ι → Type*}
[∀ i, ConditionallyCompleteLattice (α i)] : ConditionallyCompleteLattice (∀ i, α i) :=
{ Pi.instLattice, Pi.supSet, Pi.infSet with
le_csSup := fun s f ⟨g, hg⟩ hf i =>
le_csSup ⟨g i, Set.forall_mem_range.2 fun ⟨f', hf'⟩ => hg hf' i⟩ ⟨⟨f, hf⟩, rfl⟩
csSup_le := fun s f hs hf i =>
(csSup_le (by haveI := hs.to_subtype; apply range_nonempty)) fun b ⟨⟨g, hg⟩, hb⟩ =>
hb ▸ hf hg i
csInf_le := fun s f ⟨g, hg⟩ hf i =>
csInf_le ⟨g i, Set.forall_mem_range.2 fun ⟨f', hf'⟩ => hg hf' i⟩ ⟨⟨f, hf⟩, rfl⟩
le_csInf := fun s f hs hf i =>
(le_csInf (by haveI := hs.to_subtype; apply range_nonempty)) fun b ⟨⟨g, hg⟩, hb⟩ =>
hb ▸ hf hg i }
#align pi.conditionally_complete_lattice Pi.conditionallyCompleteLattice
section ConditionallyCompleteLinearOrder
variable [ConditionallyCompleteLinearOrder α] {s t : Set α} {a b : α}
/-- When `b < sSup s`, there is an element `a` in `s` with `b < a`, if `s` is nonempty and the order
is a linear order. -/
theorem exists_lt_of_lt_csSup (hs : s.Nonempty) (hb : b < sSup s) : ∃ a ∈ s, b < a := by
contrapose! hb
exact csSup_le hs hb
#align exists_lt_of_lt_cSup exists_lt_of_lt_csSup
/-- Indexed version of the above lemma `exists_lt_of_lt_csSup`.
When `b < iSup f`, there is an element `i` such that `b < f i`.
-/
theorem exists_lt_of_lt_ciSup [Nonempty ι] {f : ι → α} (h : b < iSup f) : ∃ i, b < f i :=
let ⟨_, ⟨i, rfl⟩, h⟩ := exists_lt_of_lt_csSup (range_nonempty f) h
⟨i, h⟩
#align exists_lt_of_lt_csupr exists_lt_of_lt_ciSup
/-- When `sInf s < b`, there is an element `a` in `s` with `a < b`, if `s` is nonempty and the order
is a linear order. -/
theorem exists_lt_of_csInf_lt (hs : s.Nonempty) (hb : sInf s < b) : ∃ a ∈ s, a < b :=
exists_lt_of_lt_csSup (α := αᵒᵈ) hs hb
#align exists_lt_of_cInf_lt exists_lt_of_csInf_lt
/-- Indexed version of the above lemma `exists_lt_of_csInf_lt`
When `iInf f < a`, there is an element `i` such that `f i < a`.
-/
theorem exists_lt_of_ciInf_lt [Nonempty ι] {f : ι → α} (h : iInf f < a) : ∃ i, f i < a :=
exists_lt_of_lt_ciSup (α := αᵒᵈ) h
#align exists_lt_of_cinfi_lt exists_lt_of_ciInf_lt
theorem csSup_of_not_bddAbove {s : Set α} (hs : ¬BddAbove s) : sSup s = sSup ∅ :=
ConditionallyCompleteLinearOrder.csSup_of_not_bddAbove s hs
theorem csSup_eq_univ_of_not_bddAbove {s : Set α} (hs : ¬BddAbove s) : sSup s = sSup univ := by
rw [csSup_of_not_bddAbove hs, csSup_of_not_bddAbove (s := univ)]
contrapose! hs
exact hs.mono (subset_univ _)
theorem csInf_of_not_bddBelow {s : Set α} (hs : ¬BddBelow s) : sInf s = sInf ∅ :=
ConditionallyCompleteLinearOrder.csInf_of_not_bddBelow s hs
theorem csInf_eq_univ_of_not_bddBelow {s : Set α} (hs : ¬BddBelow s) : sInf s = sInf univ :=
csSup_eq_univ_of_not_bddAbove (α := αᵒᵈ) hs
/-- When every element of a set `s` is bounded by an element of a set `t`, and conversely, then
`s` and `t` have the same supremum. This holds even when the sets may be empty or unbounded. -/
theorem csSup_eq_csSup_of_forall_exists_le {s t : Set α}
(hs : ∀ x ∈ s, ∃ y ∈ t, x ≤ y) (ht : ∀ y ∈ t, ∃ x ∈ s, y ≤ x) :
sSup s = sSup t := by
rcases eq_empty_or_nonempty s with rfl|s_ne
· have : t = ∅ := eq_empty_of_forall_not_mem (fun y yt ↦ by simpa using ht y yt)
rw [this]
rcases eq_empty_or_nonempty t with rfl|t_ne
· have : s = ∅ := eq_empty_of_forall_not_mem (fun x xs ↦ by simpa using hs x xs)
rw [this]
by_cases B : BddAbove s ∨ BddAbove t
· have Bs : BddAbove s := by
rcases B with hB|⟨b, hb⟩
· exact hB
· refine ⟨b, fun x hx ↦ ?_⟩
rcases hs x hx with ⟨y, hy, hxy⟩
exact hxy.trans (hb hy)
have Bt : BddAbove t := by
rcases B with ⟨b, hb⟩|hB
· refine ⟨b, fun y hy ↦ ?_⟩
rcases ht y hy with ⟨x, hx, hyx⟩
exact hyx.trans (hb hx)
· exact hB
apply le_antisymm
· apply csSup_le s_ne (fun x hx ↦ ?_)
rcases hs x hx with ⟨y, yt, hxy⟩
exact hxy.trans (le_csSup Bt yt)
· apply csSup_le t_ne (fun y hy ↦ ?_)
rcases ht y hy with ⟨x, xs, hyx⟩
exact hyx.trans (le_csSup Bs xs)
· simp [csSup_of_not_bddAbove, (not_or.1 B).1, (not_or.1 B).2]
/-- When every element of a set `s` is bounded by an element of a set `t`, and conversely, then
`s` and `t` have the same infimum. This holds even when the sets may be empty or unbounded. -/
theorem csInf_eq_csInf_of_forall_exists_le {s t : Set α}
(hs : ∀ x ∈ s, ∃ y ∈ t, y ≤ x) (ht : ∀ y ∈ t, ∃ x ∈ s, x ≤ y) :
sInf s = sInf t :=
csSup_eq_csSup_of_forall_exists_le (α := αᵒᵈ) hs ht
lemma sSup_iUnion_Iic (f : ι → α) : sSup (⋃ (i : ι), Iic (f i)) = ⨆ i, f i := by
apply csSup_eq_csSup_of_forall_exists_le
· rintro x ⟨-, ⟨i, rfl⟩, hi⟩
exact ⟨f i, mem_range_self _, hi⟩
· rintro x ⟨i, rfl⟩
exact ⟨f i, mem_iUnion_of_mem i le_rfl, le_rfl⟩
lemma sInf_iUnion_Ici (f : ι → α) : sInf (⋃ (i : ι), Ici (f i)) = ⨅ i, f i :=
sSup_iUnion_Iic (α := αᵒᵈ) f
theorem cbiSup_eq_of_not_forall {p : ι → Prop} {f : Subtype p → α} (hp : ¬ (∀ i, p i)) :
⨆ (i) (h : p i), f ⟨i, h⟩ = iSup f ⊔ sSup ∅ := by
classical
rcases not_forall.1 hp with ⟨i₀, hi₀⟩
have : Nonempty ι := ⟨i₀⟩
simp only [ciSup_eq_ite]
by_cases H : BddAbove (range f)
· have B : BddAbove (range fun i ↦ if h : p i then f ⟨i, h⟩ else sSup ∅) := by
rcases H with ⟨c, hc⟩
refine ⟨c ⊔ sSup ∅, ?_⟩
rintro - ⟨i, rfl⟩
by_cases hi : p i
· simp only [hi, dite_true, ge_iff_le, le_sup_iff, hc (mem_range_self _), true_or]
· simp only [hi, dite_false, ge_iff_le, le_sup_right]
apply le_antisymm
· apply ciSup_le (fun i ↦ ?_)
by_cases hi : p i
· simp only [hi, dite_true, ge_iff_le, le_sup_iff]
left
exact le_ciSup H _
· simp [hi]
· apply sup_le
· rcases isEmpty_or_nonempty (Subtype p) with hp|hp
· simp [iSup_of_empty']
convert le_ciSup B i₀
simp [hi₀]
· apply ciSup_le
rintro ⟨i, hi⟩
convert le_ciSup B i
simp [hi]
· convert le_ciSup B i₀
simp [hi₀]
· have : iSup f = sSup (∅ : Set α) := csSup_of_not_bddAbove H
simp only [this, le_refl, sup_of_le_left]
apply csSup_of_not_bddAbove
contrapose! H
apply H.mono
rintro - ⟨i, rfl⟩
convert mem_range_self i.1
simp [i.2]
theorem cbiInf_eq_of_not_forall {p : ι → Prop} {f : Subtype p → α} (hp : ¬ (∀ i, p i)) :
⨅ (i) (h : p i), f ⟨i, h⟩ = iInf f ⊓ sInf ∅ :=
cbiSup_eq_of_not_forall (α := αᵒᵈ) hp
open Function
variable [IsWellOrder α (· < ·)]
theorem sInf_eq_argmin_on (hs : s.Nonempty) : sInf s = argminOn id wellFounded_lt s hs :=
IsLeast.csInf_eq ⟨argminOn_mem _ _ _ _, fun _ ha => argminOn_le id _ _ ha⟩
#align Inf_eq_argmin_on sInf_eq_argmin_on
theorem isLeast_csInf (hs : s.Nonempty) : IsLeast s (sInf s) := by
rw [sInf_eq_argmin_on hs]
exact ⟨argminOn_mem _ _ _ _, fun a ha => argminOn_le id _ _ ha⟩
#align is_least_Inf isLeast_csInf
theorem le_csInf_iff' (hs : s.Nonempty) : b ≤ sInf s ↔ b ∈ lowerBounds s :=
le_isGLB_iff (isLeast_csInf hs).isGLB
#align le_cInf_iff' le_csInf_iff'
theorem csInf_mem (hs : s.Nonempty) : sInf s ∈ s :=
(isLeast_csInf hs).1
#align Inf_mem csInf_mem
theorem ciInf_mem [Nonempty ι] (f : ι → α) : iInf f ∈ range f :=
csInf_mem (range_nonempty f)
#align infi_mem ciInf_mem
theorem MonotoneOn.map_csInf {β : Type*} [ConditionallyCompleteLattice β] {f : α → β}
(hf : MonotoneOn f s) (hs : s.Nonempty) : f (sInf s) = sInf (f '' s) :=
(hf.map_isLeast (isLeast_csInf hs)).csInf_eq.symm
#align monotone_on.map_Inf MonotoneOn.map_csInf
theorem Monotone.map_csInf {β : Type*} [ConditionallyCompleteLattice β] {f : α → β}
(hf : Monotone f) (hs : s.Nonempty) : f (sInf s) = sInf (f '' s) :=
(hf.map_isLeast (isLeast_csInf hs)).csInf_eq.symm
#align monotone.map_Inf Monotone.map_csInf
end ConditionallyCompleteLinearOrder
/-!
### Lemmas about a conditionally complete linear order with bottom element
In this case we have `Sup ∅ = ⊥`, so we can drop some `Nonempty`/`Set.Nonempty` assumptions.
-/
section ConditionallyCompleteLinearOrderBot
variable [ConditionallyCompleteLinearOrderBot α] {s : Set α} {f : ι → α} {a : α}
@[simp]
theorem csSup_empty : (sSup ∅ : α) = ⊥ :=
ConditionallyCompleteLinearOrderBot.csSup_empty
#align cSup_empty csSup_empty
@[simp]
theorem ciSup_of_empty [IsEmpty ι] (f : ι → α) : ⨆ i, f i = ⊥ := by
rw [iSup_of_empty', csSup_empty]
#align csupr_of_empty ciSup_of_empty
theorem ciSup_false (f : False → α) : ⨆ i, f i = ⊥ :=
ciSup_of_empty f
#align csupr_false ciSup_false
@[simp]
theorem csInf_univ : sInf (univ : Set α) = ⊥ :=
isLeast_univ.csInf_eq
#align cInf_univ csInf_univ
theorem isLUB_csSup' {s : Set α} (hs : BddAbove s) : IsLUB s (sSup s) := by
rcases eq_empty_or_nonempty s with (rfl | hne)
· simp only [csSup_empty, isLUB_empty]
· exact isLUB_csSup hne hs
#align is_lub_cSup' isLUB_csSup'
theorem csSup_le_iff' {s : Set α} (hs : BddAbove s) {a : α} : sSup s ≤ a ↔ ∀ x ∈ s, x ≤ a :=
isLUB_le_iff (isLUB_csSup' hs)
#align cSup_le_iff' csSup_le_iff'
theorem csSup_le' {s : Set α} {a : α} (h : a ∈ upperBounds s) : sSup s ≤ a :=
(csSup_le_iff' ⟨a, h⟩).2 h
#align cSup_le' csSup_le'
theorem le_csSup_iff' {s : Set α} {a : α} (h : BddAbove s) :
a ≤ sSup s ↔ ∀ b, b ∈ upperBounds s → a ≤ b :=
⟨fun h _ hb => le_trans h (csSup_le' hb), fun hb => hb _ fun _ => le_csSup h⟩
#align le_cSup_iff' le_csSup_iff'
| Mathlib/Order/ConditionallyCompleteLattice/Basic.lean | 1,227 | 1,228 | theorem le_ciSup_iff' {s : ι → α} {a : α} (h : BddAbove (range s)) :
a ≤ iSup s ↔ ∀ b, (∀ i, s i ≤ b) → a ≤ b := by | simp [iSup, h, le_csSup_iff', upperBounds]
|
/-
Copyright (c) 2020 Anatole Dedecker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anatole Dedecker
-/
import Mathlib.Analysis.Calculus.MeanValue
import Mathlib.Analysis.Calculus.Deriv.Inv
#align_import analysis.calculus.lhopital from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# L'Hôpital's rule for 0/0 indeterminate forms
In this file, we prove several forms of "L'Hôpital's rule" for computing 0/0
indeterminate forms. The proof of `HasDerivAt.lhopital_zero_right_on_Ioo`
is based on the one given in the corresponding
[Wikibooks](https://en.wikibooks.org/wiki/Calculus/L%27H%C3%B4pital%27s_Rule)
chapter, and all other statements are derived from this one by composing by
carefully chosen functions.
Note that the filter `f'/g'` tends to isn't required to be one of `𝓝 a`,
`atTop` or `atBot`. In fact, we give a slightly stronger statement by
allowing it to be any filter on `ℝ`.
Each statement is available in a `HasDerivAt` form and a `deriv` form, which
is denoted by each statement being in either the `HasDerivAt` or the `deriv`
namespace.
## Tags
L'Hôpital's rule, L'Hopital's rule
-/
open Filter Set
open scoped Filter Topology Pointwise
variable {a b : ℝ} (hab : a < b) {l : Filter ℝ} {f f' g g' : ℝ → ℝ}
/-!
## Interval-based versions
We start by proving statements where all conditions (derivability, `g' ≠ 0`) have
to be satisfied on an explicitly-provided interval.
-/
namespace HasDerivAt
theorem lhopital_zero_right_on_Ioo (hff' : ∀ x ∈ Ioo a b, HasDerivAt f (f' x) x)
(hgg' : ∀ x ∈ Ioo a b, HasDerivAt g (g' x) x) (hg' : ∀ x ∈ Ioo a b, g' x ≠ 0)
(hfa : Tendsto f (𝓝[>] a) (𝓝 0)) (hga : Tendsto g (𝓝[>] a) (𝓝 0))
(hdiv : Tendsto (fun x => f' x / g' x) (𝓝[>] a) l) :
Tendsto (fun x => f x / g x) (𝓝[>] a) l := by
have sub : ∀ x ∈ Ioo a b, Ioo a x ⊆ Ioo a b := fun x hx =>
Ioo_subset_Ioo (le_refl a) (le_of_lt hx.2)
have hg : ∀ x ∈ Ioo a b, g x ≠ 0 := by
intro x hx h
have : Tendsto g (𝓝[<] x) (𝓝 0) := by
rw [← h, ← nhdsWithin_Ioo_eq_nhdsWithin_Iio hx.1]
exact ((hgg' x hx).continuousAt.continuousWithinAt.mono <| sub x hx).tendsto
obtain ⟨y, hyx, hy⟩ : ∃ c ∈ Ioo a x, g' c = 0 :=
exists_hasDerivAt_eq_zero' hx.1 hga this fun y hy => hgg' y <| sub x hx hy
exact hg' y (sub x hx hyx) hy
have : ∀ x ∈ Ioo a b, ∃ c ∈ Ioo a x, f x * g' c = g x * f' c := by
intro x hx
rw [← sub_zero (f x), ← sub_zero (g x)]
exact exists_ratio_hasDerivAt_eq_ratio_slope' g g' hx.1 f f' (fun y hy => hgg' y <| sub x hx hy)
(fun y hy => hff' y <| sub x hx hy) hga hfa
(tendsto_nhdsWithin_of_tendsto_nhds (hgg' x hx).continuousAt.tendsto)
(tendsto_nhdsWithin_of_tendsto_nhds (hff' x hx).continuousAt.tendsto)
choose! c hc using this
have : ∀ x ∈ Ioo a b, ((fun x' => f' x' / g' x') ∘ c) x = f x / g x := by
intro x hx
rcases hc x hx with ⟨h₁, h₂⟩
field_simp [hg x hx, hg' (c x) ((sub x hx) h₁)]
simp only [h₂]
rw [mul_comm]
have cmp : ∀ x ∈ Ioo a b, a < c x ∧ c x < x := fun x hx => (hc x hx).1
rw [← nhdsWithin_Ioo_eq_nhdsWithin_Ioi hab]
apply tendsto_nhdsWithin_congr this
apply hdiv.comp
refine tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within _
(tendsto_of_tendsto_of_tendsto_of_le_of_le' tendsto_const_nhds
(tendsto_nhdsWithin_of_tendsto_nhds tendsto_id) ?_ ?_) ?_
all_goals
apply eventually_nhdsWithin_of_forall
intro x hx
have := cmp x hx
try simp
linarith [this]
#align has_deriv_at.lhopital_zero_right_on_Ioo HasDerivAt.lhopital_zero_right_on_Ioo
theorem lhopital_zero_right_on_Ico (hff' : ∀ x ∈ Ioo a b, HasDerivAt f (f' x) x)
(hgg' : ∀ x ∈ Ioo a b, HasDerivAt g (g' x) x) (hcf : ContinuousOn f (Ico a b))
(hcg : ContinuousOn g (Ico a b)) (hg' : ∀ x ∈ Ioo a b, g' x ≠ 0) (hfa : f a = 0) (hga : g a = 0)
(hdiv : Tendsto (fun x => f' x / g' x) (𝓝[>] a) l) :
Tendsto (fun x => f x / g x) (𝓝[>] a) l := by
refine lhopital_zero_right_on_Ioo hab hff' hgg' hg' ?_ ?_ hdiv
· rw [← hfa, ← nhdsWithin_Ioo_eq_nhdsWithin_Ioi hab]
exact ((hcf a <| left_mem_Ico.mpr hab).mono Ioo_subset_Ico_self).tendsto
· rw [← hga, ← nhdsWithin_Ioo_eq_nhdsWithin_Ioi hab]
exact ((hcg a <| left_mem_Ico.mpr hab).mono Ioo_subset_Ico_self).tendsto
#align has_deriv_at.lhopital_zero_right_on_Ico HasDerivAt.lhopital_zero_right_on_Ico
theorem lhopital_zero_left_on_Ioo (hff' : ∀ x ∈ Ioo a b, HasDerivAt f (f' x) x)
(hgg' : ∀ x ∈ Ioo a b, HasDerivAt g (g' x) x) (hg' : ∀ x ∈ Ioo a b, g' x ≠ 0)
(hfb : Tendsto f (𝓝[<] b) (𝓝 0)) (hgb : Tendsto g (𝓝[<] b) (𝓝 0))
(hdiv : Tendsto (fun x => f' x / g' x) (𝓝[<] b) l) :
Tendsto (fun x => f x / g x) (𝓝[<] b) l := by
-- Here, we essentially compose by `Neg.neg`. The following is mostly technical details.
have hdnf : ∀ x ∈ -Ioo a b, HasDerivAt (f ∘ Neg.neg) (f' (-x) * -1) x := fun x hx =>
comp x (hff' (-x) hx) (hasDerivAt_neg x)
have hdng : ∀ x ∈ -Ioo a b, HasDerivAt (g ∘ Neg.neg) (g' (-x) * -1) x := fun x hx =>
comp x (hgg' (-x) hx) (hasDerivAt_neg x)
rw [preimage_neg_Ioo] at hdnf
rw [preimage_neg_Ioo] at hdng
have := lhopital_zero_right_on_Ioo (neg_lt_neg hab) hdnf hdng (by
intro x hx h
apply hg' _ (by rw [← preimage_neg_Ioo] at hx; exact hx)
rwa [mul_comm, ← neg_eq_neg_one_mul, neg_eq_zero] at h)
(hfb.comp tendsto_neg_nhdsWithin_Ioi_neg) (hgb.comp tendsto_neg_nhdsWithin_Ioi_neg)
(by
simp only [neg_div_neg_eq, mul_one, mul_neg]
exact (tendsto_congr fun x => rfl).mp (hdiv.comp tendsto_neg_nhdsWithin_Ioi_neg))
have := this.comp tendsto_neg_nhdsWithin_Iio
unfold Function.comp at this
simpa only [neg_neg]
#align has_deriv_at.lhopital_zero_left_on_Ioo HasDerivAt.lhopital_zero_left_on_Ioo
theorem lhopital_zero_left_on_Ioc (hff' : ∀ x ∈ Ioo a b, HasDerivAt f (f' x) x)
(hgg' : ∀ x ∈ Ioo a b, HasDerivAt g (g' x) x) (hcf : ContinuousOn f (Ioc a b))
(hcg : ContinuousOn g (Ioc a b)) (hg' : ∀ x ∈ Ioo a b, g' x ≠ 0) (hfb : f b = 0) (hgb : g b = 0)
(hdiv : Tendsto (fun x => f' x / g' x) (𝓝[<] b) l) :
Tendsto (fun x => f x / g x) (𝓝[<] b) l := by
refine lhopital_zero_left_on_Ioo hab hff' hgg' hg' ?_ ?_ hdiv
· rw [← hfb, ← nhdsWithin_Ioo_eq_nhdsWithin_Iio hab]
exact ((hcf b <| right_mem_Ioc.mpr hab).mono Ioo_subset_Ioc_self).tendsto
· rw [← hgb, ← nhdsWithin_Ioo_eq_nhdsWithin_Iio hab]
exact ((hcg b <| right_mem_Ioc.mpr hab).mono Ioo_subset_Ioc_self).tendsto
#align has_deriv_at.lhopital_zero_left_on_Ioc HasDerivAt.lhopital_zero_left_on_Ioc
theorem lhopital_zero_atTop_on_Ioi (hff' : ∀ x ∈ Ioi a, HasDerivAt f (f' x) x)
(hgg' : ∀ x ∈ Ioi a, HasDerivAt g (g' x) x) (hg' : ∀ x ∈ Ioi a, g' x ≠ 0)
(hftop : Tendsto f atTop (𝓝 0)) (hgtop : Tendsto g atTop (𝓝 0))
(hdiv : Tendsto (fun x => f' x / g' x) atTop l) : Tendsto (fun x => f x / g x) atTop l := by
obtain ⟨a', haa', ha'⟩ : ∃ a', a < a' ∧ 0 < a' := ⟨1 + max a 0,
⟨lt_of_le_of_lt (le_max_left a 0) (lt_one_add _),
lt_of_le_of_lt (le_max_right a 0) (lt_one_add _)⟩⟩
have fact1 : ∀ x : ℝ, x ∈ Ioo 0 a'⁻¹ → x ≠ 0 := fun _ hx => (ne_of_lt hx.1).symm
have fact2 : ∀ x ∈ Ioo 0 a'⁻¹, a < x⁻¹ := fun _ hx => lt_trans haa' ((lt_inv ha' hx.1).mpr hx.2)
have hdnf : ∀ x ∈ Ioo 0 a'⁻¹, HasDerivAt (f ∘ Inv.inv) (f' x⁻¹ * -(x ^ 2)⁻¹) x := fun x hx =>
comp x (hff' x⁻¹ <| fact2 x hx) (hasDerivAt_inv <| fact1 x hx)
have hdng : ∀ x ∈ Ioo 0 a'⁻¹, HasDerivAt (g ∘ Inv.inv) (g' x⁻¹ * -(x ^ 2)⁻¹) x := fun x hx =>
comp x (hgg' x⁻¹ <| fact2 x hx) (hasDerivAt_inv <| fact1 x hx)
have := lhopital_zero_right_on_Ioo (inv_pos.mpr ha') hdnf hdng
(by
intro x hx
refine mul_ne_zero ?_ (neg_ne_zero.mpr <| inv_ne_zero <| pow_ne_zero _ <| fact1 x hx)
exact hg' _ (fact2 x hx))
(hftop.comp tendsto_inv_zero_atTop) (hgtop.comp tendsto_inv_zero_atTop)
(by
refine (tendsto_congr' ?_).mp (hdiv.comp tendsto_inv_zero_atTop)
rw [eventuallyEq_iff_exists_mem]
use Ioi 0, self_mem_nhdsWithin
intro x hx
unfold Function.comp
simp only
erw [mul_div_mul_right]
exact neg_ne_zero.mpr (inv_ne_zero <| pow_ne_zero _ <| ne_of_gt hx))
have := this.comp tendsto_inv_atTop_zero'
unfold Function.comp at this
simpa only [inv_inv]
#align has_deriv_at.lhopital_zero_at_top_on_Ioi HasDerivAt.lhopital_zero_atTop_on_Ioi
theorem lhopital_zero_atBot_on_Iio (hff' : ∀ x ∈ Iio a, HasDerivAt f (f' x) x)
(hgg' : ∀ x ∈ Iio a, HasDerivAt g (g' x) x) (hg' : ∀ x ∈ Iio a, g' x ≠ 0)
(hfbot : Tendsto f atBot (𝓝 0)) (hgbot : Tendsto g atBot (𝓝 0))
(hdiv : Tendsto (fun x => f' x / g' x) atBot l) : Tendsto (fun x => f x / g x) atBot l := by
-- Here, we essentially compose by `Neg.neg`. The following is mostly technical details.
have hdnf : ∀ x ∈ -Iio a, HasDerivAt (f ∘ Neg.neg) (f' (-x) * -1) x := fun x hx =>
comp x (hff' (-x) hx) (hasDerivAt_neg x)
have hdng : ∀ x ∈ -Iio a, HasDerivAt (g ∘ Neg.neg) (g' (-x) * -1) x := fun x hx =>
comp x (hgg' (-x) hx) (hasDerivAt_neg x)
rw [preimage_neg_Iio] at hdnf
rw [preimage_neg_Iio] at hdng
have := lhopital_zero_atTop_on_Ioi hdnf hdng
(by
intro x hx h
apply hg' _ (by rw [← preimage_neg_Iio] at hx; exact hx)
rwa [mul_comm, ← neg_eq_neg_one_mul, neg_eq_zero] at h)
(hfbot.comp tendsto_neg_atTop_atBot) (hgbot.comp tendsto_neg_atTop_atBot)
(by
simp only [mul_one, mul_neg, neg_div_neg_eq]
exact (tendsto_congr fun x => rfl).mp (hdiv.comp tendsto_neg_atTop_atBot))
have := this.comp tendsto_neg_atBot_atTop
unfold Function.comp at this
simpa only [neg_neg]
#align has_deriv_at.lhopital_zero_at_bot_on_Iio HasDerivAt.lhopital_zero_atBot_on_Iio
end HasDerivAt
namespace deriv
theorem lhopital_zero_right_on_Ioo (hdf : DifferentiableOn ℝ f (Ioo a b))
(hg' : ∀ x ∈ Ioo a b, deriv g x ≠ 0) (hfa : Tendsto f (𝓝[>] a) (𝓝 0))
(hga : Tendsto g (𝓝[>] a) (𝓝 0))
(hdiv : Tendsto (fun x => (deriv f) x / (deriv g) x) (𝓝[>] a) l) :
Tendsto (fun x => f x / g x) (𝓝[>] a) l := by
have hdf : ∀ x ∈ Ioo a b, DifferentiableAt ℝ f x := fun x hx =>
(hdf x hx).differentiableAt (Ioo_mem_nhds hx.1 hx.2)
have hdg : ∀ x ∈ Ioo a b, DifferentiableAt ℝ g x := fun x hx =>
by_contradiction fun h => hg' x hx (deriv_zero_of_not_differentiableAt h)
exact HasDerivAt.lhopital_zero_right_on_Ioo hab (fun x hx => (hdf x hx).hasDerivAt)
(fun x hx => (hdg x hx).hasDerivAt) hg' hfa hga hdiv
#align deriv.lhopital_zero_right_on_Ioo deriv.lhopital_zero_right_on_Ioo
theorem lhopital_zero_right_on_Ico (hdf : DifferentiableOn ℝ f (Ioo a b))
(hcf : ContinuousOn f (Ico a b)) (hcg : ContinuousOn g (Ico a b))
(hg' : ∀ x ∈ Ioo a b, (deriv g) x ≠ 0) (hfa : f a = 0) (hga : g a = 0)
(hdiv : Tendsto (fun x => (deriv f) x / (deriv g) x) (𝓝[>] a) l) :
Tendsto (fun x => f x / g x) (𝓝[>] a) l := by
refine lhopital_zero_right_on_Ioo hab hdf hg' ?_ ?_ hdiv
· rw [← hfa, ← nhdsWithin_Ioo_eq_nhdsWithin_Ioi hab]
exact ((hcf a <| left_mem_Ico.mpr hab).mono Ioo_subset_Ico_self).tendsto
· rw [← hga, ← nhdsWithin_Ioo_eq_nhdsWithin_Ioi hab]
exact ((hcg a <| left_mem_Ico.mpr hab).mono Ioo_subset_Ico_self).tendsto
#align deriv.lhopital_zero_right_on_Ico deriv.lhopital_zero_right_on_Ico
theorem lhopital_zero_left_on_Ioo (hdf : DifferentiableOn ℝ f (Ioo a b))
(hg' : ∀ x ∈ Ioo a b, (deriv g) x ≠ 0) (hfb : Tendsto f (𝓝[<] b) (𝓝 0))
(hgb : Tendsto g (𝓝[<] b) (𝓝 0))
(hdiv : Tendsto (fun x => (deriv f) x / (deriv g) x) (𝓝[<] b) l) :
Tendsto (fun x => f x / g x) (𝓝[<] b) l := by
have hdf : ∀ x ∈ Ioo a b, DifferentiableAt ℝ f x := fun x hx =>
(hdf x hx).differentiableAt (Ioo_mem_nhds hx.1 hx.2)
have hdg : ∀ x ∈ Ioo a b, DifferentiableAt ℝ g x := fun x hx =>
by_contradiction fun h => hg' x hx (deriv_zero_of_not_differentiableAt h)
exact HasDerivAt.lhopital_zero_left_on_Ioo hab (fun x hx => (hdf x hx).hasDerivAt)
(fun x hx => (hdg x hx).hasDerivAt) hg' hfb hgb hdiv
#align deriv.lhopital_zero_left_on_Ioo deriv.lhopital_zero_left_on_Ioo
theorem lhopital_zero_atTop_on_Ioi (hdf : DifferentiableOn ℝ f (Ioi a))
(hg' : ∀ x ∈ Ioi a, (deriv g) x ≠ 0) (hftop : Tendsto f atTop (𝓝 0))
(hgtop : Tendsto g atTop (𝓝 0)) (hdiv : Tendsto (fun x => (deriv f) x / (deriv g) x) atTop l) :
Tendsto (fun x => f x / g x) atTop l := by
have hdf : ∀ x ∈ Ioi a, DifferentiableAt ℝ f x := fun x hx =>
(hdf x hx).differentiableAt (Ioi_mem_nhds hx)
have hdg : ∀ x ∈ Ioi a, DifferentiableAt ℝ g x := fun x hx =>
by_contradiction fun h => hg' x hx (deriv_zero_of_not_differentiableAt h)
exact HasDerivAt.lhopital_zero_atTop_on_Ioi (fun x hx => (hdf x hx).hasDerivAt)
(fun x hx => (hdg x hx).hasDerivAt) hg' hftop hgtop hdiv
#align deriv.lhopital_zero_at_top_on_Ioi deriv.lhopital_zero_atTop_on_Ioi
theorem lhopital_zero_atBot_on_Iio (hdf : DifferentiableOn ℝ f (Iio a))
(hg' : ∀ x ∈ Iio a, (deriv g) x ≠ 0) (hfbot : Tendsto f atBot (𝓝 0))
(hgbot : Tendsto g atBot (𝓝 0)) (hdiv : Tendsto (fun x => (deriv f) x / (deriv g) x) atBot l) :
Tendsto (fun x => f x / g x) atBot l := by
have hdf : ∀ x ∈ Iio a, DifferentiableAt ℝ f x := fun x hx =>
(hdf x hx).differentiableAt (Iio_mem_nhds hx)
have hdg : ∀ x ∈ Iio a, DifferentiableAt ℝ g x := fun x hx =>
by_contradiction fun h => hg' x hx (deriv_zero_of_not_differentiableAt h)
exact HasDerivAt.lhopital_zero_atBot_on_Iio (fun x hx => (hdf x hx).hasDerivAt)
(fun x hx => (hdg x hx).hasDerivAt) hg' hfbot hgbot hdiv
#align deriv.lhopital_zero_at_bot_on_Iio deriv.lhopital_zero_atBot_on_Iio
end deriv
/-!
## Generic versions
The following statements no longer any explicit interval, as they only require
conditions holding eventually.
-/
namespace HasDerivAt
/-- L'Hôpital's rule for approaching a real from the right, `HasDerivAt` version -/
theorem lhopital_zero_nhds_right (hff' : ∀ᶠ x in 𝓝[>] a, HasDerivAt f (f' x) x)
(hgg' : ∀ᶠ x in 𝓝[>] a, HasDerivAt g (g' x) x) (hg' : ∀ᶠ x in 𝓝[>] a, g' x ≠ 0)
(hfa : Tendsto f (𝓝[>] a) (𝓝 0)) (hga : Tendsto g (𝓝[>] a) (𝓝 0))
(hdiv : Tendsto (fun x => f' x / g' x) (𝓝[>] a) l) :
Tendsto (fun x => f x / g x) (𝓝[>] a) l := by
rw [eventually_iff_exists_mem] at *
rcases hff' with ⟨s₁, hs₁, hff'⟩
rcases hgg' with ⟨s₂, hs₂, hgg'⟩
rcases hg' with ⟨s₃, hs₃, hg'⟩
let s := s₁ ∩ s₂ ∩ s₃
have hs : s ∈ 𝓝[>] a := inter_mem (inter_mem hs₁ hs₂) hs₃
rw [mem_nhdsWithin_Ioi_iff_exists_Ioo_subset] at hs
rcases hs with ⟨u, hau, hu⟩
refine lhopital_zero_right_on_Ioo hau ?_ ?_ ?_ hfa hga hdiv <;>
intro x hx <;> apply_assumption <;>
first | exact (hu hx).1.1 | exact (hu hx).1.2 | exact (hu hx).2
#align has_deriv_at.lhopital_zero_nhds_right HasDerivAt.lhopital_zero_nhds_right
/-- L'Hôpital's rule for approaching a real from the left, `HasDerivAt` version -/
theorem lhopital_zero_nhds_left (hff' : ∀ᶠ x in 𝓝[<] a, HasDerivAt f (f' x) x)
(hgg' : ∀ᶠ x in 𝓝[<] a, HasDerivAt g (g' x) x) (hg' : ∀ᶠ x in 𝓝[<] a, g' x ≠ 0)
(hfa : Tendsto f (𝓝[<] a) (𝓝 0)) (hga : Tendsto g (𝓝[<] a) (𝓝 0))
(hdiv : Tendsto (fun x => f' x / g' x) (𝓝[<] a) l) :
Tendsto (fun x => f x / g x) (𝓝[<] a) l := by
rw [eventually_iff_exists_mem] at *
rcases hff' with ⟨s₁, hs₁, hff'⟩
rcases hgg' with ⟨s₂, hs₂, hgg'⟩
rcases hg' with ⟨s₃, hs₃, hg'⟩
let s := s₁ ∩ s₂ ∩ s₃
have hs : s ∈ 𝓝[<] a := inter_mem (inter_mem hs₁ hs₂) hs₃
rw [mem_nhdsWithin_Iio_iff_exists_Ioo_subset] at hs
rcases hs with ⟨l, hal, hl⟩
refine lhopital_zero_left_on_Ioo hal ?_ ?_ ?_ hfa hga hdiv <;> intro x hx <;> apply_assumption <;>
first | exact (hl hx).1.1| exact (hl hx).1.2| exact (hl hx).2
#align has_deriv_at.lhopital_zero_nhds_left HasDerivAt.lhopital_zero_nhds_left
/-- L'Hôpital's rule for approaching a real, `HasDerivAt` version. This
does not require anything about the situation at `a` -/
theorem lhopital_zero_nhds' (hff' : ∀ᶠ x in 𝓝[≠] a, HasDerivAt f (f' x) x)
(hgg' : ∀ᶠ x in 𝓝[≠] a, HasDerivAt g (g' x) x) (hg' : ∀ᶠ x in 𝓝[≠] a, g' x ≠ 0)
(hfa : Tendsto f (𝓝[≠] a) (𝓝 0)) (hga : Tendsto g (𝓝[≠] a) (𝓝 0))
(hdiv : Tendsto (fun x => f' x / g' x) (𝓝[≠] a) l) :
Tendsto (fun x => f x / g x) (𝓝[≠] a) l := by
simp only [← Iio_union_Ioi, nhdsWithin_union, tendsto_sup, eventually_sup] at *
exact ⟨lhopital_zero_nhds_left hff'.1 hgg'.1 hg'.1 hfa.1 hga.1 hdiv.1,
lhopital_zero_nhds_right hff'.2 hgg'.2 hg'.2 hfa.2 hga.2 hdiv.2⟩
#align has_deriv_at.lhopital_zero_nhds' HasDerivAt.lhopital_zero_nhds'
/-- **L'Hôpital's rule** for approaching a real, `HasDerivAt` version -/
theorem lhopital_zero_nhds (hff' : ∀ᶠ x in 𝓝 a, HasDerivAt f (f' x) x)
(hgg' : ∀ᶠ x in 𝓝 a, HasDerivAt g (g' x) x) (hg' : ∀ᶠ x in 𝓝 a, g' x ≠ 0)
(hfa : Tendsto f (𝓝 a) (𝓝 0)) (hga : Tendsto g (𝓝 a) (𝓝 0))
(hdiv : Tendsto (fun x => f' x / g' x) (𝓝 a) l) : Tendsto (fun x => f x / g x) (𝓝[≠] a) l := by
apply @lhopital_zero_nhds' _ _ _ f' _ g' <;>
(first | apply eventually_nhdsWithin_of_eventually_nhds |
apply tendsto_nhdsWithin_of_tendsto_nhds) <;> assumption
#align has_deriv_at.lhopital_zero_nhds HasDerivAt.lhopital_zero_nhds
/-- L'Hôpital's rule for approaching +∞, `HasDerivAt` version -/
| Mathlib/Analysis/Calculus/LHopital.lean | 340 | 354 | theorem lhopital_zero_atTop (hff' : ∀ᶠ x in atTop, HasDerivAt f (f' x) x)
(hgg' : ∀ᶠ x in atTop, HasDerivAt g (g' x) x) (hg' : ∀ᶠ x in atTop, g' x ≠ 0)
(hftop : Tendsto f atTop (𝓝 0)) (hgtop : Tendsto g atTop (𝓝 0))
(hdiv : Tendsto (fun x => f' x / g' x) atTop l) : Tendsto (fun x => f x / g x) atTop l := by |
rw [eventually_iff_exists_mem] at *
rcases hff' with ⟨s₁, hs₁, hff'⟩
rcases hgg' with ⟨s₂, hs₂, hgg'⟩
rcases hg' with ⟨s₃, hs₃, hg'⟩
let s := s₁ ∩ s₂ ∩ s₃
have hs : s ∈ atTop := inter_mem (inter_mem hs₁ hs₂) hs₃
rw [mem_atTop_sets] at hs
rcases hs with ⟨l, hl⟩
have hl' : Ioi l ⊆ s := fun x hx => hl x (le_of_lt hx)
refine lhopital_zero_atTop_on_Ioi ?_ ?_ (fun x hx => hg' x <| (hl' hx).2) hftop hgtop hdiv <;>
intro x hx <;> apply_assumption <;> first | exact (hl' hx).1.1| exact (hl' hx).1.2
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Scott Morrison, Jens Wagemaker
-/
import Mathlib.Algebra.Polynomial.Degree.Definitions
import Mathlib.Algebra.Polynomial.Induction
#align_import data.polynomial.eval from "leanprover-community/mathlib"@"728baa2f54e6062c5879a3e397ac6bac323e506f"
/-!
# Theory of univariate polynomials
The main defs here are `eval₂`, `eval`, and `map`.
We give several lemmas about their interaction with each other and with module operations.
-/
set_option linter.uppercaseLean3 false
noncomputable section
open Finset AddMonoidAlgebra
open Polynomial
namespace Polynomial
universe u v w y
variable {R : Type u} {S : Type v} {T : Type w} {ι : Type y} {a b : R} {m n : ℕ}
section Semiring
variable [Semiring R] {p q r : R[X]}
section
variable [Semiring S]
variable (f : R →+* S) (x : S)
/-- Evaluate a polynomial `p` given a ring hom `f` from the scalar ring
to the target and a value `x` for the variable in the target -/
irreducible_def eval₂ (p : R[X]) : S :=
p.sum fun e a => f a * x ^ e
#align polynomial.eval₂ Polynomial.eval₂
theorem eval₂_eq_sum {f : R →+* S} {x : S} : p.eval₂ f x = p.sum fun e a => f a * x ^ e := by
rw [eval₂_def]
#align polynomial.eval₂_eq_sum Polynomial.eval₂_eq_sum
theorem eval₂_congr {R S : Type*} [Semiring R] [Semiring S] {f g : R →+* S} {s t : S}
{φ ψ : R[X]} : f = g → s = t → φ = ψ → eval₂ f s φ = eval₂ g t ψ := by
rintro rfl rfl rfl; rfl
#align polynomial.eval₂_congr Polynomial.eval₂_congr
@[simp]
theorem eval₂_at_zero : p.eval₂ f 0 = f (coeff p 0) := by
simp (config := { contextual := true }) only [eval₂_eq_sum, zero_pow_eq, mul_ite, mul_zero,
mul_one, sum, Classical.not_not, mem_support_iff, sum_ite_eq', ite_eq_left_iff,
RingHom.map_zero, imp_true_iff, eq_self_iff_true]
#align polynomial.eval₂_at_zero Polynomial.eval₂_at_zero
@[simp]
theorem eval₂_zero : (0 : R[X]).eval₂ f x = 0 := by simp [eval₂_eq_sum]
#align polynomial.eval₂_zero Polynomial.eval₂_zero
@[simp]
theorem eval₂_C : (C a).eval₂ f x = f a := by simp [eval₂_eq_sum]
#align polynomial.eval₂_C Polynomial.eval₂_C
@[simp]
theorem eval₂_X : X.eval₂ f x = x := by simp [eval₂_eq_sum]
#align polynomial.eval₂_X Polynomial.eval₂_X
@[simp]
theorem eval₂_monomial {n : ℕ} {r : R} : (monomial n r).eval₂ f x = f r * x ^ n := by
simp [eval₂_eq_sum]
#align polynomial.eval₂_monomial Polynomial.eval₂_monomial
@[simp]
| Mathlib/Algebra/Polynomial/Eval.lean | 82 | 85 | theorem eval₂_X_pow {n : ℕ} : (X ^ n).eval₂ f x = x ^ n := by |
rw [X_pow_eq_monomial]
convert eval₂_monomial f x (n := n) (r := 1)
simp
|
/-
Copyright (c) 2023 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Data.Set.Image
import Mathlib.Data.List.GetD
#align_import data.set.list from "leanprover-community/mathlib"@"2ec920d35348cb2d13ac0e1a2ad9df0fdf1a76b4"
/-!
# Lemmas about `List`s and `Set.range`
In this file we prove lemmas about range of some operations on lists.
-/
open List
variable {α β : Type*} (l : List α)
namespace Set
theorem range_list_map (f : α → β) : range (map f) = { l | ∀ x ∈ l, x ∈ range f } := by
refine antisymm (range_subset_iff.2 fun l => forall_mem_map_iff.2 fun y _ => mem_range_self _)
fun l hl => ?_
induction' l with a l ihl; · exact ⟨[], rfl⟩
rcases ihl fun x hx => hl x <| subset_cons _ _ hx with ⟨l, rfl⟩
rcases hl a (mem_cons_self _ _) with ⟨a, rfl⟩
exact ⟨a :: l, map_cons _ _ _⟩
#align set.range_list_map Set.range_list_map
theorem range_list_map_coe (s : Set α) : range (map ((↑) : s → α)) = { l | ∀ x ∈ l, x ∈ s } := by
rw [range_list_map, Subtype.range_coe]
#align set.range_list_map_coe Set.range_list_map_coe
@[simp]
theorem range_list_get : range l.get = { x | x ∈ l } := by
ext x
rw [mem_setOf_eq, mem_iff_get, mem_range]
#align set.range_list_nth_le Set.range_list_get
@[deprecated (since := "2024-04-22")] alias range_list_nthLe := range_list_get
theorem range_list_get? : range l.get? = insert none (some '' { x | x ∈ l }) := by
rw [← range_list_get, ← range_comp]
refine (range_subset_iff.2 fun n => ?_).antisymm (insert_subset_iff.2 ⟨?_, ?_⟩)
exacts [(le_or_lt l.length n).imp get?_eq_none.2 (fun hlt => ⟨⟨_, hlt⟩, (get?_eq_get hlt).symm⟩),
⟨_, get?_eq_none.2 le_rfl⟩, range_subset_iff.2 fun k => ⟨_, get?_eq_get _⟩]
#align set.range_list_nth Set.range_list_get?
@[simp]
| Mathlib/Data/Set/List.lean | 52 | 57 | theorem range_list_getD (d : α) : (range fun n => l.getD n d) = insert d { x | x ∈ l } :=
calc
(range fun n => l.getD n d) = (fun o : Option α => o.getD d) '' range l.get? := by |
simp only [← range_comp, (· ∘ ·), getD_eq_getD_get?]
_ = insert d { x | x ∈ l } := by
simp only [range_list_get?, image_insert_eq, Option.getD, image_image, image_id']
|
/-
Copyright (c) 2023 Xavier Roblot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Xavier Roblot
-/
import Mathlib.NumberTheory.NumberField.Embeddings
#align_import number_theory.number_field.units from "leanprover-community/mathlib"@"00f91228655eecdcd3ac97a7fd8dbcb139fe990a"
/-!
# Units of a number field
We prove some basic results on the group `(𝓞 K)ˣ` of units of the ring of integers `𝓞 K` of a number
field `K` and its torsion subgroup.
## Main definition
* `NumberField.Units.torsion`: the torsion subgroup of a number field.
## Main results
* `NumberField.isUnit_iff_norm`: an algebraic integer `x : 𝓞 K` is a unit if and only if
`|norm ℚ x| = 1`.
* `NumberField.Units.mem_torsion`: a unit `x : (𝓞 K)ˣ` is torsion iff `w x = 1` for all infinite
places `w` of `K`.
## Tags
number field, units
-/
open scoped NumberField
noncomputable section
open NumberField Units
section Rat
theorem Rat.RingOfIntegers.isUnit_iff {x : 𝓞 ℚ} : IsUnit x ↔ (x : ℚ) = 1 ∨ (x : ℚ) = -1 := by
simp_rw [(isUnit_map_iff (Rat.ringOfIntegersEquiv : 𝓞 ℚ →+* ℤ) x).symm, Int.isUnit_iff,
RingEquiv.coe_toRingHom, RingEquiv.map_eq_one_iff, RingEquiv.map_eq_neg_one_iff, ←
Subtype.coe_injective.eq_iff]; rfl
#align rat.ring_of_integers.is_unit_iff Rat.RingOfIntegers.isUnit_iff
end Rat
variable (K : Type*) [Field K]
section IsUnit
variable {K}
theorem NumberField.isUnit_iff_norm [NumberField K] {x : 𝓞 K} :
IsUnit x ↔ |(RingOfIntegers.norm ℚ x : ℚ)| = 1 := by
convert (RingOfIntegers.isUnit_norm ℚ (F := K)).symm
rw [← abs_one, abs_eq_abs, ← Rat.RingOfIntegers.isUnit_iff]
#align is_unit_iff_norm NumberField.isUnit_iff_norm
end IsUnit
namespace NumberField.Units
section coe
instance : CoeHTC (𝓞 K)ˣ K :=
⟨fun x => algebraMap _ K (Units.val x)⟩
theorem coe_injective : Function.Injective ((↑) : (𝓞 K)ˣ → K) :=
RingOfIntegers.coe_injective.comp Units.ext
variable {K}
theorem coe_coe (u : (𝓞 K)ˣ) : ((u : 𝓞 K) : K) = (u : K) := rfl
theorem coe_mul (x y : (𝓞 K)ˣ) : ((x * y : (𝓞 K)ˣ) : K) = (x : K) * (y : K) := rfl
theorem coe_pow (x : (𝓞 K)ˣ) (n : ℕ) : ((x ^ n : (𝓞 K)ˣ) : K) = (x : K) ^ n := by
rw [← map_pow, ← val_pow_eq_pow_val]
theorem coe_zpow (x : (𝓞 K)ˣ) (n : ℤ) : (↑(x ^ n) : K) = (x : K) ^ n := by
change ((Units.coeHom K).comp (map (algebraMap (𝓞 K) K))) (x ^ n) = _
exact map_zpow _ x n
theorem coe_one : ((1 : (𝓞 K)ˣ) : K) = (1 : K) := rfl
theorem coe_neg_one : ((-1 : (𝓞 K)ˣ) : K) = (-1 : K) := rfl
theorem coe_ne_zero (x : (𝓞 K)ˣ) : (x : K) ≠ 0 :=
Subtype.coe_injective.ne_iff.mpr (_root_.Units.ne_zero x)
end coe
open NumberField.InfinitePlace
section torsion
/-- The torsion subgroup of the group of units. -/
def torsion : Subgroup (𝓞 K)ˣ := CommGroup.torsion (𝓞 K)ˣ
theorem mem_torsion {x : (𝓞 K)ˣ} [NumberField K] :
x ∈ torsion K ↔ ∀ w : InfinitePlace K, w x = 1 := by
rw [eq_iff_eq (x : K) 1, torsion, CommGroup.mem_torsion]
refine ⟨fun hx φ ↦ (((φ.comp $ algebraMap (𝓞 K) K).toMonoidHom.comp $
Units.coeHom _).isOfFinOrder hx).norm_eq_one, fun h ↦ isOfFinOrder_iff_pow_eq_one.2 ?_⟩
obtain ⟨n, hn, hx⟩ := Embeddings.pow_eq_one_of_norm_eq_one K ℂ x.val.isIntegral_coe h
exact ⟨n, hn, by ext; rw [NumberField.RingOfIntegers.coe_eq_algebraMap, coe_pow, hx,
NumberField.RingOfIntegers.coe_eq_algebraMap, coe_one]⟩
/-- The torsion subgroup is finite. -/
instance [NumberField K] : Fintype (torsion K) := by
refine @Fintype.ofFinite _ (Set.finite_coe_iff.mpr ?_)
refine Set.Finite.of_finite_image ?_ (coe_injective K).injOn
refine (Embeddings.finite_of_norm_le K ℂ 1).subset
(fun a ⟨u, ⟨h_tors, h_ua⟩⟩ => ⟨?_, fun φ => ?_⟩)
· rw [← h_ua]
exact u.val.prop
· rw [← h_ua]
exact le_of_eq ((eq_iff_eq _ 1).mp ((mem_torsion K).mp h_tors) φ)
instance : Nonempty (torsion K) := One.instNonempty
/-- The torsion subgroup is cylic. -/
instance [NumberField K] : IsCyclic (torsion K) := subgroup_units_cyclic _
/-- The order of the torsion subgroup as a positive integer. -/
def torsionOrder [NumberField K] : ℕ+ := ⟨Fintype.card (torsion K), Fintype.card_pos⟩
/-- If `k` does not divide `torsionOrder` then there are no nontrivial roots of unity of
order dividing `k`. -/
theorem rootsOfUnity_eq_one [NumberField K] {k : ℕ+} (hc : Nat.Coprime k (torsionOrder K))
{ζ : (𝓞 K)ˣ} : ζ ∈ rootsOfUnity k (𝓞 K) ↔ ζ = 1 := by
rw [mem_rootsOfUnity]
refine ⟨fun h => ?_, fun h => by rw [h, one_pow]⟩
refine orderOf_eq_one_iff.mp (Nat.eq_one_of_dvd_coprimes hc ?_ ?_)
· exact orderOf_dvd_of_pow_eq_one h
· have hζ : ζ ∈ torsion K := by
rw [torsion, CommGroup.mem_torsion, isOfFinOrder_iff_pow_eq_one]
exact ⟨k, k.prop, h⟩
rw [orderOf_submonoid (⟨ζ, hζ⟩ : torsion K)]
exact orderOf_dvd_card
/-- The group of roots of unity of order dividing `torsionOrder` is equal to the torsion
group. -/
| Mathlib/NumberTheory/NumberField/Units/Basic.lean | 145 | 152 | theorem rootsOfUnity_eq_torsion [NumberField K] :
rootsOfUnity (torsionOrder K) (𝓞 K) = torsion K := by |
ext ζ
rw [torsion, mem_rootsOfUnity]
refine ⟨fun h => ?_, fun h => ?_⟩
· rw [CommGroup.mem_torsion, isOfFinOrder_iff_pow_eq_one]
exact ⟨↑(torsionOrder K), (torsionOrder K).prop, h⟩
· exact Subtype.ext_iff.mp (@pow_card_eq_one (torsion K) _ _ ⟨ζ, h⟩)
|
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne
-/
import Mathlib.MeasureTheory.Function.LpSeminorm.Basic
import Mathlib.MeasureTheory.Integral.MeanInequalities
#align_import measure_theory.function.lp_seminorm from "leanprover-community/mathlib"@"c4015acc0a223449d44061e27ddac1835a3852b9"
/-!
# Triangle inequality for `Lp`-seminorm
In this file we prove several versions of the triangle inequality for the `Lp` seminorm,
as well as simple corollaries.
-/
open Filter
open scoped ENNReal Topology
namespace MeasureTheory
variable {α E : Type*} {m : MeasurableSpace α} [NormedAddCommGroup E]
{p : ℝ≥0∞} {q : ℝ} {μ : Measure α} {f g : α → E}
theorem snorm'_add_le {f g : α → E} (hf : AEStronglyMeasurable f μ) (hg : AEStronglyMeasurable g μ)
(hq1 : 1 ≤ q) : snorm' (f + g) q μ ≤ snorm' f q μ + snorm' g q μ :=
calc
(∫⁻ a, (‖(f + g) a‖₊ : ℝ≥0∞) ^ q ∂μ) ^ (1 / q) ≤
(∫⁻ a, ((fun a => (‖f a‖₊ : ℝ≥0∞)) + fun a => (‖g a‖₊ : ℝ≥0∞)) a ^ q ∂μ) ^ (1 / q) := by
gcongr with a
simp only [Pi.add_apply, ← ENNReal.coe_add, ENNReal.coe_le_coe, nnnorm_add_le]
_ ≤ snorm' f q μ + snorm' g q μ := ENNReal.lintegral_Lp_add_le hf.ennnorm hg.ennnorm hq1
#align measure_theory.snorm'_add_le MeasureTheory.snorm'_add_le
theorem snorm'_add_le_of_le_one {f g : α → E} (hf : AEStronglyMeasurable f μ) (hq0 : 0 ≤ q)
(hq1 : q ≤ 1) : snorm' (f + g) q μ ≤ (2 : ℝ≥0∞) ^ (1 / q - 1) * (snorm' f q μ + snorm' g q μ) :=
calc
(∫⁻ a, (‖(f + g) a‖₊ : ℝ≥0∞) ^ q ∂μ) ^ (1 / q) ≤
(∫⁻ a, ((fun a => (‖f a‖₊ : ℝ≥0∞)) + fun a => (‖g a‖₊ : ℝ≥0∞)) a ^ q ∂μ) ^ (1 / q) := by
gcongr with a
simp only [Pi.add_apply, ← ENNReal.coe_add, ENNReal.coe_le_coe, nnnorm_add_le]
_ ≤ (2 : ℝ≥0∞) ^ (1 / q - 1) * (snorm' f q μ + snorm' g q μ) :=
ENNReal.lintegral_Lp_add_le_of_le_one hf.ennnorm hq0 hq1
#align measure_theory.snorm'_add_le_of_le_one MeasureTheory.snorm'_add_le_of_le_one
theorem snormEssSup_add_le {f g : α → E} :
snormEssSup (f + g) μ ≤ snormEssSup f μ + snormEssSup g μ := by
refine le_trans (essSup_mono_ae (eventually_of_forall fun x => ?_)) (ENNReal.essSup_add_le _ _)
simp_rw [Pi.add_apply, ← ENNReal.coe_add, ENNReal.coe_le_coe]
exact nnnorm_add_le _ _
#align measure_theory.snorm_ess_sup_add_le MeasureTheory.snormEssSup_add_le
theorem snorm_add_le {f g : α → E} (hf : AEStronglyMeasurable f μ) (hg : AEStronglyMeasurable g μ)
(hp1 : 1 ≤ p) : snorm (f + g) p μ ≤ snorm f p μ + snorm g p μ := by
by_cases hp0 : p = 0
· simp [hp0]
by_cases hp_top : p = ∞
· simp [hp_top, snormEssSup_add_le]
have hp1_real : 1 ≤ p.toReal := by
rwa [← ENNReal.one_toReal, ENNReal.toReal_le_toReal ENNReal.one_ne_top hp_top]
repeat rw [snorm_eq_snorm' hp0 hp_top]
exact snorm'_add_le hf hg hp1_real
#align measure_theory.snorm_add_le MeasureTheory.snorm_add_le
/-- A constant for the inequality `‖f + g‖_{L^p} ≤ C * (‖f‖_{L^p} + ‖g‖_{L^p})`. It is equal to `1`
for `p ≥ 1` or `p = 0`, and `2^(1/p-1)` in the more tricky interval `(0, 1)`. -/
noncomputable def LpAddConst (p : ℝ≥0∞) : ℝ≥0∞ :=
if p ∈ Set.Ioo (0 : ℝ≥0∞) 1 then (2 : ℝ≥0∞) ^ (1 / p.toReal - 1) else 1
set_option linter.uppercaseLean3 false in
#align measure_theory.Lp_add_const MeasureTheory.LpAddConst
theorem LpAddConst_of_one_le {p : ℝ≥0∞} (hp : 1 ≤ p) : LpAddConst p = 1 := by
rw [LpAddConst, if_neg]
intro h
exact lt_irrefl _ (h.2.trans_le hp)
set_option linter.uppercaseLean3 false in
#align measure_theory.Lp_add_const_of_one_le MeasureTheory.LpAddConst_of_one_le
theorem LpAddConst_zero : LpAddConst 0 = 1 := by
rw [LpAddConst, if_neg]
intro h
exact lt_irrefl _ h.1
set_option linter.uppercaseLean3 false in
#align measure_theory.Lp_add_const_zero MeasureTheory.LpAddConst_zero
theorem LpAddConst_lt_top (p : ℝ≥0∞) : LpAddConst p < ∞ := by
rw [LpAddConst]
split_ifs with h
· apply ENNReal.rpow_lt_top_of_nonneg _ ENNReal.two_ne_top
simp only [one_div, sub_nonneg]
apply one_le_inv (ENNReal.toReal_pos h.1.ne' (h.2.trans ENNReal.one_lt_top).ne)
simpa using ENNReal.toReal_mono ENNReal.one_ne_top h.2.le
· exact ENNReal.one_lt_top
set_option linter.uppercaseLean3 false in
#align measure_theory.Lp_add_const_lt_top MeasureTheory.LpAddConst_lt_top
theorem snorm_add_le' {f g : α → E} (hf : AEStronglyMeasurable f μ) (hg : AEStronglyMeasurable g μ)
(p : ℝ≥0∞) : snorm (f + g) p μ ≤ LpAddConst p * (snorm f p μ + snorm g p μ) := by
rcases eq_or_ne p 0 with (rfl | hp)
· simp only [snorm_exponent_zero, add_zero, mul_zero, le_zero_iff]
rcases lt_or_le p 1 with (h'p | h'p)
· simp only [snorm_eq_snorm' hp (h'p.trans ENNReal.one_lt_top).ne]
convert snorm'_add_le_of_le_one hf ENNReal.toReal_nonneg _
· have : p ∈ Set.Ioo (0 : ℝ≥0∞) 1 := ⟨hp.bot_lt, h'p⟩
simp only [LpAddConst, if_pos this]
· simpa using ENNReal.toReal_mono ENNReal.one_ne_top h'p.le
· simp [LpAddConst_of_one_le h'p]
exact snorm_add_le hf hg h'p
#align measure_theory.snorm_add_le' MeasureTheory.snorm_add_le'
variable (μ E)
/-- Technical lemma to control the addition of functions in `L^p` even for `p < 1`: Given `δ > 0`,
there exists `η` such that two functions bounded by `η` in `L^p` have a sum bounded by `δ`. One
could take `η = δ / 2` for `p ≥ 1`, but the point of the lemma is that it works also for `p < 1`.
-/
| Mathlib/MeasureTheory/Function/LpSeminorm/TriangleInequality.lean | 118 | 134 | theorem exists_Lp_half (p : ℝ≥0∞) {δ : ℝ≥0∞} (hδ : δ ≠ 0) :
∃ η : ℝ≥0∞,
0 < η ∧
∀ (f g : α → E), AEStronglyMeasurable f μ → AEStronglyMeasurable g μ →
snorm f p μ ≤ η → snorm g p μ ≤ η → snorm (f + g) p μ < δ := by |
have :
Tendsto (fun η : ℝ≥0∞ => LpAddConst p * (η + η)) (𝓝[>] 0) (𝓝 (LpAddConst p * (0 + 0))) :=
(ENNReal.Tendsto.const_mul (tendsto_id.add tendsto_id)
(Or.inr (LpAddConst_lt_top p).ne)).mono_left
nhdsWithin_le_nhds
simp only [add_zero, mul_zero] at this
rcases (((tendsto_order.1 this).2 δ hδ.bot_lt).and self_mem_nhdsWithin).exists with ⟨η, hη, ηpos⟩
refine ⟨η, ηpos, fun f g hf hg Hf Hg => ?_⟩
calc
snorm (f + g) p μ ≤ LpAddConst p * (snorm f p μ + snorm g p μ) := snorm_add_le' hf hg p
_ ≤ LpAddConst p * (η + η) := by gcongr
_ < δ := hη
|
/-
Copyright (c) 2023 Matthew Robert Ballard. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Matthew Robert Ballard
-/
import Mathlib.Algebra.Divisibility.Units
import Mathlib.Algebra.Order.Ring.Nat
import Mathlib.Tactic.Common
/-!
# The maximal power of one natural number dividing another
Here we introduce `p.maxPowDiv n` which returns the maximal `k : ℕ` for
which `p ^ k ∣ n` with the convention that `maxPowDiv 1 n = 0` for all `n`.
We prove enough about `maxPowDiv` in this file to show equality with `Nat.padicValNat` in
`padicValNat.padicValNat_eq_maxPowDiv`.
The implementation of `maxPowDiv` improves on the speed of `padicValNat`.
-/
namespace Nat
open Nat
/--
Tail recursive function which returns the largest `k : ℕ` such that `p ^ k ∣ n` for any `p : ℕ`.
`padicValNat_eq_maxPowDiv` allows the code generator to use this definition for `padicValNat`
-/
def maxPowDiv (p n : ℕ) : ℕ :=
go 0 p n
where go (k p n : ℕ) : ℕ :=
if 1 < p ∧ 0 < n ∧ n % p = 0 then
go (k+1) p (n / p)
else
k
termination_by n
decreasing_by apply Nat.div_lt_self <;> tauto
attribute [inherit_doc maxPowDiv] maxPowDiv.go
end Nat
namespace Nat.maxPowDiv
theorem go_succ {k p n : ℕ} : go (k+1) p n = go k p n + 1 := by
induction k, p, n using go.induct
case case1 h ih =>
unfold go
simp only [if_pos h]
exact ih
case case2 h =>
unfold go
simp only [if_neg h]
@[simp]
theorem zero_base {n : ℕ} : maxPowDiv 0 n = 0 := by
dsimp [maxPowDiv]
rw [maxPowDiv.go]
simp
@[simp]
theorem zero {p : ℕ} : maxPowDiv p 0 = 0 := by
dsimp [maxPowDiv]
rw [maxPowDiv.go]
simp
theorem base_mul_eq_succ {p n : ℕ} (hp : 1 < p) (hn : 0 < n) :
p.maxPowDiv (p*n) = p.maxPowDiv n + 1 := by
have : 0 < p := lt_trans (b := 1) (by simp) hp
dsimp [maxPowDiv]
rw [maxPowDiv.go, if_pos, mul_div_right _ this]
· apply go_succ
· refine ⟨hp, ?_, by simp⟩
apply Nat.mul_pos this hn
theorem base_pow_mul {p n exp : ℕ} (hp : 1 < p) (hn : 0 < n) :
p.maxPowDiv (p ^ exp * n) = p.maxPowDiv n + exp := by
match exp with
| 0 => simp
| e + 1 =>
rw [Nat.pow_succ, mul_assoc, mul_comm, mul_assoc, base_mul_eq_succ hp, mul_comm,
base_pow_mul hp hn]
· ac_rfl
· apply Nat.mul_pos hn <| pow_pos (pos_of_gt hp) e
theorem pow_dvd (p n : ℕ) : p ^ (p.maxPowDiv n) ∣ n := by
dsimp [maxPowDiv]
rw [go]
by_cases h : (1 < p ∧ 0 < n ∧ n % p = 0)
· have : n / p < n := by apply Nat.div_lt_self <;> aesop
rw [if_pos h]
have ⟨c,hc⟩ := pow_dvd p (n / p)
rw [go_succ, pow_succ]
nth_rw 2 [← mod_add_div' n p]
rw [h.right.right, zero_add]
exact ⟨c,by nth_rw 1 [hc]; ac_rfl⟩
· rw [if_neg h]
simp
| Mathlib/Data/Nat/MaxPowDiv.lean | 101 | 109 | theorem le_of_dvd {p n pow : ℕ} (hp : 1 < p) (hn : 0 < n) (h : p ^ pow ∣ n) :
pow ≤ p.maxPowDiv n := by |
have ⟨c, hc⟩ := h
have : 0 < c := by
apply Nat.pos_of_ne_zero
intro h'
rw [h',mul_zero] at hc
exact not_eq_zero_of_lt hn hc
simp [hc, base_pow_mul hp this]
|
/-
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.Algebra.Ring.Prod
import Mathlib.GroupTheory.OrderOfElement
import Mathlib.Tactic.FinCases
#align_import data.zmod.basic from "leanprover-community/mathlib"@"74ad1c88c77e799d2fea62801d1dbbd698cff1b7"
/-!
# Integers mod `n`
Definition of the integers mod n, and the field structure on the integers mod p.
## Definitions
* `ZMod n`, which is for integers modulo a nat `n : ℕ`
* `val a` is defined as a natural number:
- for `a : ZMod 0` it is the absolute value of `a`
- for `a : ZMod n` with `0 < n` it is the least natural number in the equivalence class
* `valMinAbs` returns the integer closest to zero in the equivalence class.
* A coercion `cast` is defined from `ZMod n` into any ring.
This is a ring hom if the ring has characteristic dividing `n`
-/
assert_not_exists Submodule
open Function
namespace ZMod
instance charZero : CharZero (ZMod 0) := inferInstanceAs (CharZero ℤ)
/-- `val a` is a natural number defined as:
- for `a : ZMod 0` it is the absolute value of `a`
- for `a : ZMod n` with `0 < n` it is the least natural number in the equivalence class
See `ZMod.valMinAbs` for a variant that takes values in the integers.
-/
def val : ∀ {n : ℕ}, ZMod n → ℕ
| 0 => Int.natAbs
| n + 1 => ((↑) : Fin (n + 1) → ℕ)
#align zmod.val ZMod.val
theorem val_lt {n : ℕ} [NeZero n] (a : ZMod n) : a.val < n := by
cases n
· cases NeZero.ne 0 rfl
exact Fin.is_lt a
#align zmod.val_lt ZMod.val_lt
theorem val_le {n : ℕ} [NeZero n] (a : ZMod n) : a.val ≤ n :=
a.val_lt.le
#align zmod.val_le ZMod.val_le
@[simp]
theorem val_zero : ∀ {n}, (0 : ZMod n).val = 0
| 0 => rfl
| _ + 1 => rfl
#align zmod.val_zero ZMod.val_zero
@[simp]
theorem val_one' : (1 : ZMod 0).val = 1 :=
rfl
#align zmod.val_one' ZMod.val_one'
@[simp]
theorem val_neg' {n : ZMod 0} : (-n).val = n.val :=
Int.natAbs_neg n
#align zmod.val_neg' ZMod.val_neg'
@[simp]
theorem val_mul' {m n : ZMod 0} : (m * n).val = m.val * n.val :=
Int.natAbs_mul m n
#align zmod.val_mul' ZMod.val_mul'
@[simp]
theorem val_natCast {n : ℕ} (a : ℕ) : (a : ZMod n).val = a % n := by
cases n
· rw [Nat.mod_zero]
exact Int.natAbs_ofNat a
· apply Fin.val_natCast
#align zmod.val_nat_cast ZMod.val_natCast
@[deprecated (since := "2024-04-17")]
alias val_nat_cast := val_natCast
theorem val_unit' {n : ZMod 0} : IsUnit n ↔ n.val = 1 := by
simp only [val]
rw [Int.isUnit_iff, Int.natAbs_eq_iff, Nat.cast_one]
lemma eq_one_of_isUnit_natCast {n : ℕ} (h : IsUnit (n : ZMod 0)) : n = 1 := by
rw [← Nat.mod_zero n, ← val_natCast, val_unit'.mp h]
theorem val_natCast_of_lt {n a : ℕ} (h : a < n) : (a : ZMod n).val = a := by
rwa [val_natCast, Nat.mod_eq_of_lt]
@[deprecated (since := "2024-04-17")]
alias val_nat_cast_of_lt := val_natCast_of_lt
instance charP (n : ℕ) : CharP (ZMod n) n where
cast_eq_zero_iff' := by
intro k
cases' n with n
· simp [zero_dvd_iff, Int.natCast_eq_zero, Nat.zero_eq]
· exact Fin.natCast_eq_zero
@[simp]
theorem addOrderOf_one (n : ℕ) : addOrderOf (1 : ZMod n) = n :=
CharP.eq _ (CharP.addOrderOf_one _) (ZMod.charP n)
#align zmod.add_order_of_one ZMod.addOrderOf_one
/-- This lemma works in the case in which `ZMod n` is not infinite, i.e. `n ≠ 0`. The version
where `a ≠ 0` is `addOrderOf_coe'`. -/
@[simp]
theorem addOrderOf_coe (a : ℕ) {n : ℕ} (n0 : n ≠ 0) : addOrderOf (a : ZMod n) = n / n.gcd a := by
cases' a with a
· simp only [Nat.zero_eq, Nat.cast_zero, addOrderOf_zero, Nat.gcd_zero_right,
Nat.pos_of_ne_zero n0, Nat.div_self]
rw [← Nat.smul_one_eq_cast, addOrderOf_nsmul' _ a.succ_ne_zero, ZMod.addOrderOf_one]
#align zmod.add_order_of_coe ZMod.addOrderOf_coe
/-- This lemma works in the case in which `a ≠ 0`. The version where
`ZMod n` is not infinite, i.e. `n ≠ 0`, is `addOrderOf_coe`. -/
@[simp]
theorem addOrderOf_coe' {a : ℕ} (n : ℕ) (a0 : a ≠ 0) : addOrderOf (a : ZMod n) = n / n.gcd a := by
rw [← Nat.smul_one_eq_cast, addOrderOf_nsmul' _ a0, ZMod.addOrderOf_one]
#align zmod.add_order_of_coe' ZMod.addOrderOf_coe'
/-- We have that `ringChar (ZMod n) = n`. -/
theorem ringChar_zmod_n (n : ℕ) : ringChar (ZMod n) = n := by
rw [ringChar.eq_iff]
exact ZMod.charP n
#align zmod.ring_char_zmod_n ZMod.ringChar_zmod_n
-- @[simp] -- Porting note (#10618): simp can prove this
theorem natCast_self (n : ℕ) : (n : ZMod n) = 0 :=
CharP.cast_eq_zero (ZMod n) n
#align zmod.nat_cast_self ZMod.natCast_self
@[deprecated (since := "2024-04-17")]
alias nat_cast_self := natCast_self
@[simp]
theorem natCast_self' (n : ℕ) : (n + 1 : ZMod (n + 1)) = 0 := by
rw [← Nat.cast_add_one, natCast_self (n + 1)]
#align zmod.nat_cast_self' ZMod.natCast_self'
@[deprecated (since := "2024-04-17")]
alias nat_cast_self' := natCast_self'
section UniversalProperty
variable {n : ℕ} {R : Type*}
section
variable [AddGroupWithOne R]
/-- Cast an integer modulo `n` to another semiring.
This function is a morphism if the characteristic of `R` divides `n`.
See `ZMod.castHom` for a bundled version. -/
def cast : ∀ {n : ℕ}, ZMod n → R
| 0 => Int.cast
| _ + 1 => fun i => i.val
#align zmod.cast ZMod.cast
@[simp]
theorem cast_zero : (cast (0 : ZMod n) : R) = 0 := by
delta ZMod.cast
cases n
· exact Int.cast_zero
· simp
#align zmod.cast_zero ZMod.cast_zero
theorem cast_eq_val [NeZero n] (a : ZMod n) : (cast a : R) = a.val := by
cases n
· cases NeZero.ne 0 rfl
rfl
#align zmod.cast_eq_val ZMod.cast_eq_val
variable {S : Type*} [AddGroupWithOne S]
@[simp]
theorem _root_.Prod.fst_zmod_cast (a : ZMod n) : (cast a : R × S).fst = cast a := by
cases n
· rfl
· simp [ZMod.cast]
#align prod.fst_zmod_cast Prod.fst_zmod_cast
@[simp]
theorem _root_.Prod.snd_zmod_cast (a : ZMod n) : (cast a : R × S).snd = cast a := by
cases n
· rfl
· simp [ZMod.cast]
#align prod.snd_zmod_cast Prod.snd_zmod_cast
end
/-- So-named because the coercion is `Nat.cast` into `ZMod`. For `Nat.cast` into an arbitrary ring,
see `ZMod.natCast_val`. -/
theorem natCast_zmod_val {n : ℕ} [NeZero n] (a : ZMod n) : (a.val : ZMod n) = a := by
cases n
· cases NeZero.ne 0 rfl
· apply Fin.cast_val_eq_self
#align zmod.nat_cast_zmod_val ZMod.natCast_zmod_val
@[deprecated (since := "2024-04-17")]
alias nat_cast_zmod_val := natCast_zmod_val
theorem natCast_rightInverse [NeZero n] : Function.RightInverse val ((↑) : ℕ → ZMod n) :=
natCast_zmod_val
#align zmod.nat_cast_right_inverse ZMod.natCast_rightInverse
@[deprecated (since := "2024-04-17")]
alias nat_cast_rightInverse := natCast_rightInverse
theorem natCast_zmod_surjective [NeZero n] : Function.Surjective ((↑) : ℕ → ZMod n) :=
natCast_rightInverse.surjective
#align zmod.nat_cast_zmod_surjective ZMod.natCast_zmod_surjective
@[deprecated (since := "2024-04-17")]
alias nat_cast_zmod_surjective := natCast_zmod_surjective
/-- So-named because the outer coercion is `Int.cast` into `ZMod`. For `Int.cast` into an arbitrary
ring, see `ZMod.intCast_cast`. -/
@[norm_cast]
theorem intCast_zmod_cast (a : ZMod n) : ((cast a : ℤ) : ZMod n) = a := by
cases n
· simp [ZMod.cast, ZMod]
· dsimp [ZMod.cast, ZMod]
erw [Int.cast_natCast, Fin.cast_val_eq_self]
#align zmod.int_cast_zmod_cast ZMod.intCast_zmod_cast
@[deprecated (since := "2024-04-17")]
alias int_cast_zmod_cast := intCast_zmod_cast
theorem intCast_rightInverse : Function.RightInverse (cast : ZMod n → ℤ) ((↑) : ℤ → ZMod n) :=
intCast_zmod_cast
#align zmod.int_cast_right_inverse ZMod.intCast_rightInverse
@[deprecated (since := "2024-04-17")]
alias int_cast_rightInverse := intCast_rightInverse
theorem intCast_surjective : Function.Surjective ((↑) : ℤ → ZMod n) :=
intCast_rightInverse.surjective
#align zmod.int_cast_surjective ZMod.intCast_surjective
@[deprecated (since := "2024-04-17")]
alias int_cast_surjective := intCast_surjective
theorem cast_id : ∀ (n) (i : ZMod n), (ZMod.cast i : ZMod n) = i
| 0, _ => Int.cast_id
| _ + 1, i => natCast_zmod_val i
#align zmod.cast_id ZMod.cast_id
@[simp]
theorem cast_id' : (ZMod.cast : ZMod n → ZMod n) = id :=
funext (cast_id n)
#align zmod.cast_id' ZMod.cast_id'
variable (R) [Ring R]
/-- The coercions are respectively `Nat.cast` and `ZMod.cast`. -/
@[simp]
theorem natCast_comp_val [NeZero n] : ((↑) : ℕ → R) ∘ (val : ZMod n → ℕ) = cast := by
cases n
· cases NeZero.ne 0 rfl
rfl
#align zmod.nat_cast_comp_val ZMod.natCast_comp_val
@[deprecated (since := "2024-04-17")]
alias nat_cast_comp_val := natCast_comp_val
/-- The coercions are respectively `Int.cast`, `ZMod.cast`, and `ZMod.cast`. -/
@[simp]
theorem intCast_comp_cast : ((↑) : ℤ → R) ∘ (cast : ZMod n → ℤ) = cast := by
cases n
· exact congr_arg (Int.cast ∘ ·) ZMod.cast_id'
· ext
simp [ZMod, ZMod.cast]
#align zmod.int_cast_comp_cast ZMod.intCast_comp_cast
@[deprecated (since := "2024-04-17")]
alias int_cast_comp_cast := intCast_comp_cast
variable {R}
@[simp]
theorem natCast_val [NeZero n] (i : ZMod n) : (i.val : R) = cast i :=
congr_fun (natCast_comp_val R) i
#align zmod.nat_cast_val ZMod.natCast_val
@[deprecated (since := "2024-04-17")]
alias nat_cast_val := natCast_val
@[simp]
theorem intCast_cast (i : ZMod n) : ((cast i : ℤ) : R) = cast i :=
congr_fun (intCast_comp_cast R) i
#align zmod.int_cast_cast ZMod.intCast_cast
@[deprecated (since := "2024-04-17")]
alias int_cast_cast := intCast_cast
theorem cast_add_eq_ite {n : ℕ} (a b : ZMod n) :
(cast (a + b) : ℤ) =
if (n : ℤ) ≤ cast a + cast b then (cast a + cast b - n : ℤ) else cast a + cast b := by
cases' n with n
· simp; rfl
change Fin (n + 1) at a b
change ((((a + b) : Fin (n + 1)) : ℕ) : ℤ) = if ((n + 1 : ℕ) : ℤ) ≤ (a : ℕ) + b then _ else _
simp only [Fin.val_add_eq_ite, Int.ofNat_succ, Int.ofNat_le]
norm_cast
split_ifs with h
· rw [Nat.cast_sub h]
congr
· rfl
#align zmod.coe_add_eq_ite ZMod.cast_add_eq_ite
section CharDvd
/-! If the characteristic of `R` divides `n`, then `cast` is a homomorphism. -/
variable {m : ℕ} [CharP R m]
@[simp]
theorem cast_one (h : m ∣ n) : (cast (1 : ZMod n) : R) = 1 := by
cases' n with n
· exact Int.cast_one
show ((1 % (n + 1) : ℕ) : R) = 1
cases n;
· rw [Nat.dvd_one] at h
subst m
have : Subsingleton R := CharP.CharOne.subsingleton
apply Subsingleton.elim
rw [Nat.mod_eq_of_lt]
· exact Nat.cast_one
exact Nat.lt_of_sub_eq_succ rfl
#align zmod.cast_one ZMod.cast_one
theorem cast_add (h : m ∣ n) (a b : ZMod n) : (cast (a + b : ZMod n) : R) = cast a + cast b := by
cases n
· apply Int.cast_add
symm
dsimp [ZMod, ZMod.cast]
erw [← Nat.cast_add, ← sub_eq_zero, ← Nat.cast_sub (Nat.mod_le _ _),
@CharP.cast_eq_zero_iff R _ m]
exact h.trans (Nat.dvd_sub_mod _)
#align zmod.cast_add ZMod.cast_add
theorem cast_mul (h : m ∣ n) (a b : ZMod n) : (cast (a * b : ZMod n) : R) = cast a * cast b := by
cases n
· apply Int.cast_mul
symm
dsimp [ZMod, ZMod.cast]
erw [← Nat.cast_mul, ← sub_eq_zero, ← Nat.cast_sub (Nat.mod_le _ _),
@CharP.cast_eq_zero_iff R _ m]
exact h.trans (Nat.dvd_sub_mod _)
#align zmod.cast_mul ZMod.cast_mul
/-- The canonical ring homomorphism from `ZMod n` to a ring of characteristic dividing `n`.
See also `ZMod.lift` for a generalized version working in `AddGroup`s.
-/
def castHom (h : m ∣ n) (R : Type*) [Ring R] [CharP R m] : ZMod n →+* R where
toFun := cast
map_zero' := cast_zero
map_one' := cast_one h
map_add' := cast_add h
map_mul' := cast_mul h
#align zmod.cast_hom ZMod.castHom
@[simp]
theorem castHom_apply {h : m ∣ n} (i : ZMod n) : castHom h R i = cast i :=
rfl
#align zmod.cast_hom_apply ZMod.castHom_apply
@[simp]
theorem cast_sub (h : m ∣ n) (a b : ZMod n) : (cast (a - b : ZMod n) : R) = cast a - cast b :=
(castHom h R).map_sub a b
#align zmod.cast_sub ZMod.cast_sub
@[simp]
theorem cast_neg (h : m ∣ n) (a : ZMod n) : (cast (-a : ZMod n) : R) = -(cast a) :=
(castHom h R).map_neg a
#align zmod.cast_neg ZMod.cast_neg
@[simp]
theorem cast_pow (h : m ∣ n) (a : ZMod n) (k : ℕ) : (cast (a ^ k : ZMod n) : R) = (cast a) ^ k :=
(castHom h R).map_pow a k
#align zmod.cast_pow ZMod.cast_pow
@[simp, norm_cast]
theorem cast_natCast (h : m ∣ n) (k : ℕ) : (cast (k : ZMod n) : R) = k :=
map_natCast (castHom h R) k
#align zmod.cast_nat_cast ZMod.cast_natCast
@[deprecated (since := "2024-04-17")]
alias cast_nat_cast := cast_natCast
@[simp, norm_cast]
theorem cast_intCast (h : m ∣ n) (k : ℤ) : (cast (k : ZMod n) : R) = k :=
map_intCast (castHom h R) k
#align zmod.cast_int_cast ZMod.cast_intCast
@[deprecated (since := "2024-04-17")]
alias cast_int_cast := cast_intCast
end CharDvd
section CharEq
/-! Some specialised simp lemmas which apply when `R` has characteristic `n`. -/
variable [CharP R n]
@[simp]
theorem cast_one' : (cast (1 : ZMod n) : R) = 1 :=
cast_one dvd_rfl
#align zmod.cast_one' ZMod.cast_one'
@[simp]
theorem cast_add' (a b : ZMod n) : (cast (a + b : ZMod n) : R) = cast a + cast b :=
cast_add dvd_rfl a b
#align zmod.cast_add' ZMod.cast_add'
@[simp]
theorem cast_mul' (a b : ZMod n) : (cast (a * b : ZMod n) : R) = cast a * cast b :=
cast_mul dvd_rfl a b
#align zmod.cast_mul' ZMod.cast_mul'
@[simp]
theorem cast_sub' (a b : ZMod n) : (cast (a - b : ZMod n) : R) = cast a - cast b :=
cast_sub dvd_rfl a b
#align zmod.cast_sub' ZMod.cast_sub'
@[simp]
theorem cast_pow' (a : ZMod n) (k : ℕ) : (cast (a ^ k : ZMod n) : R) = (cast a : R) ^ k :=
cast_pow dvd_rfl a k
#align zmod.cast_pow' ZMod.cast_pow'
@[simp, norm_cast]
theorem cast_natCast' (k : ℕ) : (cast (k : ZMod n) : R) = k :=
cast_natCast dvd_rfl k
#align zmod.cast_nat_cast' ZMod.cast_natCast'
@[deprecated (since := "2024-04-17")]
alias cast_nat_cast' := cast_natCast'
@[simp, norm_cast]
theorem cast_intCast' (k : ℤ) : (cast (k : ZMod n) : R) = k :=
cast_intCast dvd_rfl k
#align zmod.cast_int_cast' ZMod.cast_intCast'
@[deprecated (since := "2024-04-17")]
alias cast_int_cast' := cast_intCast'
variable (R)
theorem castHom_injective : Function.Injective (ZMod.castHom (dvd_refl n) R) := by
rw [injective_iff_map_eq_zero]
intro x
obtain ⟨k, rfl⟩ := ZMod.intCast_surjective x
rw [map_intCast, CharP.intCast_eq_zero_iff R n, CharP.intCast_eq_zero_iff (ZMod n) n]
exact id
#align zmod.cast_hom_injective ZMod.castHom_injective
theorem castHom_bijective [Fintype R] (h : Fintype.card R = n) :
Function.Bijective (ZMod.castHom (dvd_refl n) R) := by
haveI : NeZero n :=
⟨by
intro hn
rw [hn] at h
exact (Fintype.card_eq_zero_iff.mp h).elim' 0⟩
rw [Fintype.bijective_iff_injective_and_card, ZMod.card, h, eq_self_iff_true, and_true_iff]
apply ZMod.castHom_injective
#align zmod.cast_hom_bijective ZMod.castHom_bijective
/-- The unique ring isomorphism between `ZMod n` and a ring `R`
of characteristic `n` and cardinality `n`. -/
noncomputable def ringEquiv [Fintype R] (h : Fintype.card R = n) : ZMod n ≃+* R :=
RingEquiv.ofBijective _ (ZMod.castHom_bijective R h)
#align zmod.ring_equiv ZMod.ringEquiv
/-- The identity between `ZMod m` and `ZMod n` when `m = n`, as a ring isomorphism. -/
def ringEquivCongr {m n : ℕ} (h : m = n) : ZMod m ≃+* ZMod n := by
cases' m with m <;> cases' n with n
· exact RingEquiv.refl _
· exfalso
exact n.succ_ne_zero h.symm
· exfalso
exact m.succ_ne_zero h
· exact
{ finCongr h with
map_mul' := fun a b => by
dsimp [ZMod]
ext
rw [Fin.coe_cast, Fin.coe_mul, Fin.coe_mul, Fin.coe_cast, Fin.coe_cast, ← h]
map_add' := fun a b => by
dsimp [ZMod]
ext
rw [Fin.coe_cast, Fin.val_add, Fin.val_add, Fin.coe_cast, Fin.coe_cast, ← h] }
#align zmod.ring_equiv_congr ZMod.ringEquivCongr
@[simp] lemma ringEquivCongr_refl (a : ℕ) : ringEquivCongr (rfl : a = a) = .refl _ := by
cases a <;> rfl
lemma ringEquivCongr_refl_apply {a : ℕ} (x : ZMod a) : ringEquivCongr rfl x = x := by
rw [ringEquivCongr_refl]
rfl
lemma ringEquivCongr_symm {a b : ℕ} (hab : a = b) :
(ringEquivCongr hab).symm = ringEquivCongr hab.symm := by
subst hab
cases a <;> rfl
lemma ringEquivCongr_trans {a b c : ℕ} (hab : a = b) (hbc : b = c) :
(ringEquivCongr hab).trans (ringEquivCongr hbc) = ringEquivCongr (hab.trans hbc) := by
subst hab hbc
cases a <;> rfl
lemma ringEquivCongr_ringEquivCongr_apply {a b c : ℕ} (hab : a = b) (hbc : b = c) (x : ZMod a) :
ringEquivCongr hbc (ringEquivCongr hab x) = ringEquivCongr (hab.trans hbc) x := by
rw [← ringEquivCongr_trans hab hbc]
rfl
lemma ringEquivCongr_val {a b : ℕ} (h : a = b) (x : ZMod a) :
ZMod.val ((ZMod.ringEquivCongr h) x) = ZMod.val x := by
subst h
cases a <;> rfl
lemma ringEquivCongr_intCast {a b : ℕ} (h : a = b) (z : ℤ) :
ZMod.ringEquivCongr h z = z := by
subst h
cases a <;> rfl
@[deprecated (since := "2024-05-25")] alias int_coe_ringEquivCongr := ringEquivCongr_intCast
end CharEq
end UniversalProperty
theorem intCast_eq_intCast_iff (a b : ℤ) (c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a ≡ b [ZMOD c] :=
CharP.intCast_eq_intCast (ZMod c) c
#align zmod.int_coe_eq_int_coe_iff ZMod.intCast_eq_intCast_iff
@[deprecated (since := "2024-04-17")]
alias int_cast_eq_int_cast_iff := intCast_eq_intCast_iff
theorem intCast_eq_intCast_iff' (a b : ℤ) (c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a % c = b % c :=
ZMod.intCast_eq_intCast_iff a b c
#align zmod.int_coe_eq_int_coe_iff' ZMod.intCast_eq_intCast_iff'
@[deprecated (since := "2024-04-17")]
alias int_cast_eq_int_cast_iff' := intCast_eq_intCast_iff'
theorem natCast_eq_natCast_iff (a b c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a ≡ b [MOD c] := by
simpa [Int.natCast_modEq_iff] using ZMod.intCast_eq_intCast_iff a b c
#align zmod.nat_coe_eq_nat_coe_iff ZMod.natCast_eq_natCast_iff
@[deprecated (since := "2024-04-17")]
alias nat_cast_eq_nat_cast_iff := natCast_eq_natCast_iff
theorem natCast_eq_natCast_iff' (a b c : ℕ) : (a : ZMod c) = (b : ZMod c) ↔ a % c = b % c :=
ZMod.natCast_eq_natCast_iff a b c
#align zmod.nat_coe_eq_nat_coe_iff' ZMod.natCast_eq_natCast_iff'
@[deprecated (since := "2024-04-17")]
alias nat_cast_eq_nat_cast_iff' := natCast_eq_natCast_iff'
theorem intCast_zmod_eq_zero_iff_dvd (a : ℤ) (b : ℕ) : (a : ZMod b) = 0 ↔ (b : ℤ) ∣ a := by
rw [← Int.cast_zero, ZMod.intCast_eq_intCast_iff, Int.modEq_zero_iff_dvd]
#align zmod.int_coe_zmod_eq_zero_iff_dvd ZMod.intCast_zmod_eq_zero_iff_dvd
@[deprecated (since := "2024-04-17")]
alias int_cast_zmod_eq_zero_iff_dvd := intCast_zmod_eq_zero_iff_dvd
theorem intCast_eq_intCast_iff_dvd_sub (a b : ℤ) (c : ℕ) : (a : ZMod c) = ↑b ↔ ↑c ∣ b - a := by
rw [ZMod.intCast_eq_intCast_iff, Int.modEq_iff_dvd]
#align zmod.int_coe_eq_int_coe_iff_dvd_sub ZMod.intCast_eq_intCast_iff_dvd_sub
@[deprecated (since := "2024-04-17")]
alias int_cast_eq_int_cast_iff_dvd_sub := intCast_eq_intCast_iff_dvd_sub
theorem natCast_zmod_eq_zero_iff_dvd (a b : ℕ) : (a : ZMod b) = 0 ↔ b ∣ a := by
rw [← Nat.cast_zero, ZMod.natCast_eq_natCast_iff, Nat.modEq_zero_iff_dvd]
#align zmod.nat_coe_zmod_eq_zero_iff_dvd ZMod.natCast_zmod_eq_zero_iff_dvd
@[deprecated (since := "2024-04-17")]
alias nat_cast_zmod_eq_zero_iff_dvd := natCast_zmod_eq_zero_iff_dvd
theorem val_intCast {n : ℕ} (a : ℤ) [NeZero n] : ↑(a : ZMod n).val = a % n := by
have hle : (0 : ℤ) ≤ ↑(a : ZMod n).val := Int.natCast_nonneg _
have hlt : ↑(a : ZMod n).val < (n : ℤ) := Int.ofNat_lt.mpr (ZMod.val_lt a)
refine (Int.emod_eq_of_lt hle hlt).symm.trans ?_
rw [← ZMod.intCast_eq_intCast_iff', Int.cast_natCast, ZMod.natCast_val, ZMod.cast_id]
#align zmod.val_int_cast ZMod.val_intCast
@[deprecated (since := "2024-04-17")]
alias val_int_cast := val_intCast
theorem coe_intCast {n : ℕ} (a : ℤ) : cast (a : ZMod n) = a % n := by
cases n
· rw [Int.ofNat_zero, Int.emod_zero, Int.cast_id]; rfl
· rw [← val_intCast, val]; rfl
#align zmod.coe_int_cast ZMod.coe_intCast
@[deprecated (since := "2024-04-17")]
alias coe_int_cast := coe_intCast
@[simp]
theorem val_neg_one (n : ℕ) : (-1 : ZMod n.succ).val = n := by
dsimp [val, Fin.coe_neg]
cases n
· simp [Nat.mod_one]
· dsimp [ZMod, ZMod.cast]
rw [Fin.coe_neg_one]
#align zmod.val_neg_one ZMod.val_neg_one
/-- `-1 : ZMod n` lifts to `n - 1 : R`. This avoids the characteristic assumption in `cast_neg`. -/
theorem cast_neg_one {R : Type*} [Ring R] (n : ℕ) : cast (-1 : ZMod n) = (n - 1 : R) := by
cases' n with n
· dsimp [ZMod, ZMod.cast]; simp
· rw [← natCast_val, val_neg_one, Nat.cast_succ, add_sub_cancel_right]
#align zmod.cast_neg_one ZMod.cast_neg_one
theorem cast_sub_one {R : Type*} [Ring R] {n : ℕ} (k : ZMod n) :
(cast (k - 1 : ZMod n) : R) = (if k = 0 then (n : R) else cast k) - 1 := by
split_ifs with hk
· rw [hk, zero_sub, ZMod.cast_neg_one]
· cases n
· dsimp [ZMod, ZMod.cast]
rw [Int.cast_sub, Int.cast_one]
· dsimp [ZMod, ZMod.cast, ZMod.val]
rw [Fin.coe_sub_one, if_neg]
· rw [Nat.cast_sub, Nat.cast_one]
rwa [Fin.ext_iff, Fin.val_zero, ← Ne, ← Nat.one_le_iff_ne_zero] at hk
· exact hk
#align zmod.cast_sub_one ZMod.cast_sub_one
theorem natCast_eq_iff (p : ℕ) (n : ℕ) (z : ZMod p) [NeZero p] :
↑n = z ↔ ∃ k, n = z.val + p * k := by
constructor
· rintro rfl
refine ⟨n / p, ?_⟩
rw [val_natCast, Nat.mod_add_div]
· rintro ⟨k, rfl⟩
rw [Nat.cast_add, natCast_zmod_val, Nat.cast_mul, natCast_self, zero_mul,
add_zero]
#align zmod.nat_coe_zmod_eq_iff ZMod.natCast_eq_iff
theorem intCast_eq_iff (p : ℕ) (n : ℤ) (z : ZMod p) [NeZero p] :
↑n = z ↔ ∃ k, n = z.val + p * k := by
constructor
· rintro rfl
refine ⟨n / p, ?_⟩
rw [val_intCast, Int.emod_add_ediv]
· rintro ⟨k, rfl⟩
rw [Int.cast_add, Int.cast_mul, Int.cast_natCast, Int.cast_natCast, natCast_val,
ZMod.natCast_self, zero_mul, add_zero, cast_id]
#align zmod.int_coe_zmod_eq_iff ZMod.intCast_eq_iff
@[deprecated (since := "2024-05-25")] alias nat_coe_zmod_eq_iff := natCast_eq_iff
@[deprecated (since := "2024-05-25")] alias int_coe_zmod_eq_iff := intCast_eq_iff
@[push_cast, simp]
theorem intCast_mod (a : ℤ) (b : ℕ) : ((a % b : ℤ) : ZMod b) = (a : ZMod b) := by
rw [ZMod.intCast_eq_intCast_iff]
apply Int.mod_modEq
#align zmod.int_cast_mod ZMod.intCast_mod
@[deprecated (since := "2024-04-17")]
alias int_cast_mod := intCast_mod
theorem ker_intCastAddHom (n : ℕ) :
(Int.castAddHom (ZMod n)).ker = AddSubgroup.zmultiples (n : ℤ) := by
ext
rw [Int.mem_zmultiples_iff, AddMonoidHom.mem_ker, Int.coe_castAddHom,
intCast_zmod_eq_zero_iff_dvd]
#align zmod.ker_int_cast_add_hom ZMod.ker_intCastAddHom
@[deprecated (since := "2024-04-17")]
alias ker_int_castAddHom := ker_intCastAddHom
theorem cast_injective_of_le {m n : ℕ} [nzm : NeZero m] (h : m ≤ n) :
Function.Injective (@cast (ZMod n) _ m) := by
cases m with
| zero => cases nzm; simp_all
| succ m =>
rintro ⟨x, hx⟩ ⟨y, hy⟩ f
simp only [cast, val, natCast_eq_natCast_iff',
Nat.mod_eq_of_lt (hx.trans_le h), Nat.mod_eq_of_lt (hy.trans_le h)] at f
apply Fin.ext
exact f
theorem cast_zmod_eq_zero_iff_of_le {m n : ℕ} [NeZero m] (h : m ≤ n) (a : ZMod m) :
(cast a : ZMod n) = 0 ↔ a = 0 := by
rw [← ZMod.cast_zero (n := m)]
exact Injective.eq_iff' (cast_injective_of_le h) rfl
-- Porting note: commented
-- unseal Int.NonNeg
@[simp]
theorem natCast_toNat (p : ℕ) : ∀ {z : ℤ} (_h : 0 ≤ z), (z.toNat : ZMod p) = z
| (n : ℕ), _h => by simp only [Int.cast_natCast, Int.toNat_natCast]
| Int.negSucc n, h => by simp at h
#align zmod.nat_cast_to_nat ZMod.natCast_toNat
@[deprecated (since := "2024-04-17")]
alias nat_cast_toNat := natCast_toNat
theorem val_injective (n : ℕ) [NeZero n] : Function.Injective (val : ZMod n → ℕ) := by
cases n
· cases NeZero.ne 0 rfl
intro a b h
dsimp [ZMod]
ext
exact h
#align zmod.val_injective ZMod.val_injective
theorem val_one_eq_one_mod (n : ℕ) : (1 : ZMod n).val = 1 % n := by
rw [← Nat.cast_one, val_natCast]
#align zmod.val_one_eq_one_mod ZMod.val_one_eq_one_mod
theorem val_one (n : ℕ) [Fact (1 < n)] : (1 : ZMod n).val = 1 := by
rw [val_one_eq_one_mod]
exact Nat.mod_eq_of_lt Fact.out
#align zmod.val_one ZMod.val_one
theorem val_add {n : ℕ} [NeZero n] (a b : ZMod n) : (a + b).val = (a.val + b.val) % n := by
cases n
· cases NeZero.ne 0 rfl
· apply Fin.val_add
#align zmod.val_add ZMod.val_add
theorem val_add_of_lt {n : ℕ} {a b : ZMod n} (h : a.val + b.val < n) :
(a + b).val = a.val + b.val := by
have : NeZero n := by constructor; rintro rfl; simp at h
rw [ZMod.val_add, Nat.mod_eq_of_lt h]
theorem val_add_val_of_le {n : ℕ} [NeZero n] {a b : ZMod n} (h : n ≤ a.val + b.val) :
a.val + b.val = (a + b).val + n := by
rw [val_add, Nat.add_mod_add_of_le_add_mod, Nat.mod_eq_of_lt (val_lt _),
Nat.mod_eq_of_lt (val_lt _)]
rwa [Nat.mod_eq_of_lt (val_lt _), Nat.mod_eq_of_lt (val_lt _)]
theorem val_add_of_le {n : ℕ} [NeZero n] {a b : ZMod n} (h : n ≤ a.val + b.val) :
(a + b).val = a.val + b.val - n := by
rw [val_add_val_of_le h]
exact eq_tsub_of_add_eq rfl
theorem val_add_le {n : ℕ} (a b : ZMod n) : (a + b).val ≤ a.val + b.val := by
cases n
· simp [ZMod.val]; apply Int.natAbs_add_le
· simp [ZMod.val_add]; apply Nat.mod_le
theorem val_mul {n : ℕ} (a b : ZMod n) : (a * b).val = a.val * b.val % n := by
cases n
· rw [Nat.mod_zero]
apply Int.natAbs_mul
· apply Fin.val_mul
#align zmod.val_mul ZMod.val_mul
theorem val_mul_le {n : ℕ} (a b : ZMod n) : (a * b).val ≤ a.val * b.val := by
rw [val_mul]
apply Nat.mod_le
theorem val_mul_of_lt {n : ℕ} {a b : ZMod n} (h : a.val * b.val < n) :
(a * b).val = a.val * b.val := by
rw [val_mul]
apply Nat.mod_eq_of_lt h
instance nontrivial (n : ℕ) [Fact (1 < n)] : Nontrivial (ZMod n) :=
⟨⟨0, 1, fun h =>
zero_ne_one <|
calc
0 = (0 : ZMod n).val := by rw [val_zero]
_ = (1 : ZMod n).val := congr_arg ZMod.val h
_ = 1 := val_one n
⟩⟩
#align zmod.nontrivial ZMod.nontrivial
instance nontrivial' : Nontrivial (ZMod 0) := by
delta ZMod; infer_instance
#align zmod.nontrivial' ZMod.nontrivial'
/-- The inversion on `ZMod n`.
It is setup in such a way that `a * a⁻¹` is equal to `gcd a.val n`.
In particular, if `a` is coprime to `n`, and hence a unit, `a * a⁻¹ = 1`. -/
def inv : ∀ n : ℕ, ZMod n → ZMod n
| 0, i => Int.sign i
| n + 1, i => Nat.gcdA i.val (n + 1)
#align zmod.inv ZMod.inv
instance (n : ℕ) : Inv (ZMod n) :=
⟨inv n⟩
@[nolint unusedHavesSuffices]
theorem inv_zero : ∀ n : ℕ, (0 : ZMod n)⁻¹ = 0
| 0 => Int.sign_zero
| n + 1 =>
show (Nat.gcdA _ (n + 1) : ZMod (n + 1)) = 0 by
rw [val_zero]
unfold Nat.gcdA Nat.xgcd Nat.xgcdAux
rfl
#align zmod.inv_zero ZMod.inv_zero
theorem mul_inv_eq_gcd {n : ℕ} (a : ZMod n) : a * a⁻¹ = Nat.gcd a.val n := by
cases' n with n
· dsimp [ZMod] at a ⊢
calc
_ = a * Int.sign a := rfl
_ = a.natAbs := by rw [Int.mul_sign]
_ = a.natAbs.gcd 0 := by rw [Nat.gcd_zero_right]
· calc
a * a⁻¹ = a * a⁻¹ + n.succ * Nat.gcdB (val a) n.succ := by
rw [natCast_self, zero_mul, add_zero]
_ = ↑(↑a.val * Nat.gcdA (val a) n.succ + n.succ * Nat.gcdB (val a) n.succ) := by
push_cast
rw [natCast_zmod_val]
rfl
_ = Nat.gcd a.val n.succ := by rw [← Nat.gcd_eq_gcd_ab a.val n.succ]; rfl
#align zmod.mul_inv_eq_gcd ZMod.mul_inv_eq_gcd
@[simp]
theorem natCast_mod (a : ℕ) (n : ℕ) : ((a % n : ℕ) : ZMod n) = a := by
conv =>
rhs
rw [← Nat.mod_add_div a n]
simp
#align zmod.nat_cast_mod ZMod.natCast_mod
@[deprecated (since := "2024-04-17")]
alias nat_cast_mod := natCast_mod
theorem eq_iff_modEq_nat (n : ℕ) {a b : ℕ} : (a : ZMod n) = b ↔ a ≡ b [MOD n] := by
cases n
· simp [Nat.ModEq, Int.natCast_inj, Nat.mod_zero]
· rw [Fin.ext_iff, Nat.ModEq, ← val_natCast, ← val_natCast]
exact Iff.rfl
#align zmod.eq_iff_modeq_nat ZMod.eq_iff_modEq_nat
theorem coe_mul_inv_eq_one {n : ℕ} (x : ℕ) (h : Nat.Coprime x n) :
((x : ZMod n) * (x : ZMod n)⁻¹) = 1 := by
rw [Nat.Coprime, Nat.gcd_comm, Nat.gcd_rec] at h
rw [mul_inv_eq_gcd, val_natCast, h, Nat.cast_one]
#align zmod.coe_mul_inv_eq_one ZMod.coe_mul_inv_eq_one
/-- `unitOfCoprime` makes an element of `(ZMod n)ˣ` given
a natural number `x` and a proof that `x` is coprime to `n` -/
def unitOfCoprime {n : ℕ} (x : ℕ) (h : Nat.Coprime x n) : (ZMod n)ˣ :=
⟨x, x⁻¹, coe_mul_inv_eq_one x h, by rw [mul_comm, coe_mul_inv_eq_one x h]⟩
#align zmod.unit_of_coprime ZMod.unitOfCoprime
@[simp]
theorem coe_unitOfCoprime {n : ℕ} (x : ℕ) (h : Nat.Coprime x n) :
(unitOfCoprime x h : ZMod n) = x :=
rfl
#align zmod.coe_unit_of_coprime ZMod.coe_unitOfCoprime
theorem val_coe_unit_coprime {n : ℕ} (u : (ZMod n)ˣ) : Nat.Coprime (u : ZMod n).val n := by
cases' n with n
· rcases Int.units_eq_one_or u with (rfl | rfl) <;> simp
apply Nat.coprime_of_mul_modEq_one ((u⁻¹ : Units (ZMod (n + 1))) : ZMod (n + 1)).val
have := Units.ext_iff.1 (mul_right_inv u)
rw [Units.val_one] at this
rw [← eq_iff_modEq_nat, Nat.cast_one, ← this]; clear this
rw [← natCast_zmod_val ((u * u⁻¹ : Units (ZMod (n + 1))) : ZMod (n + 1))]
rw [Units.val_mul, val_mul, natCast_mod]
#align zmod.val_coe_unit_coprime ZMod.val_coe_unit_coprime
lemma isUnit_iff_coprime (m n : ℕ) : IsUnit (m : ZMod n) ↔ m.Coprime n := by
refine ⟨fun H ↦ ?_, fun H ↦ (unitOfCoprime m H).isUnit⟩
have H' := val_coe_unit_coprime H.unit
rw [IsUnit.unit_spec, val_natCast m, Nat.coprime_iff_gcd_eq_one] at H'
rw [Nat.coprime_iff_gcd_eq_one, Nat.gcd_comm, ← H']
exact Nat.gcd_rec n m
lemma isUnit_prime_iff_not_dvd {n p : ℕ} (hp : p.Prime) : IsUnit (p : ZMod n) ↔ ¬p ∣ n := by
rw [isUnit_iff_coprime, Nat.Prime.coprime_iff_not_dvd hp]
lemma isUnit_prime_of_not_dvd {n p : ℕ} (hp : p.Prime) (h : ¬ p ∣ n) : IsUnit (p : ZMod n) :=
(isUnit_prime_iff_not_dvd hp).mpr h
@[simp]
theorem inv_coe_unit {n : ℕ} (u : (ZMod n)ˣ) : (u : ZMod n)⁻¹ = (u⁻¹ : (ZMod n)ˣ) := by
have := congr_arg ((↑) : ℕ → ZMod n) (val_coe_unit_coprime u)
rw [← mul_inv_eq_gcd, Nat.cast_one] at this
let u' : (ZMod n)ˣ := ⟨u, (u : ZMod n)⁻¹, this, by rwa [mul_comm]⟩
have h : u = u' := by
apply Units.ext
rfl
rw [h]
rfl
#align zmod.inv_coe_unit ZMod.inv_coe_unit
theorem mul_inv_of_unit {n : ℕ} (a : ZMod n) (h : IsUnit a) : a * a⁻¹ = 1 := by
rcases h with ⟨u, rfl⟩
rw [inv_coe_unit, u.mul_inv]
#align zmod.mul_inv_of_unit ZMod.mul_inv_of_unit
theorem inv_mul_of_unit {n : ℕ} (a : ZMod n) (h : IsUnit a) : a⁻¹ * a = 1 := by
rw [mul_comm, mul_inv_of_unit a h]
#align zmod.inv_mul_of_unit ZMod.inv_mul_of_unit
-- TODO: If we changed `⁻¹` so that `ZMod n` is always a `DivisionMonoid`,
-- then we could use the general lemma `inv_eq_of_mul_eq_one`
protected theorem inv_eq_of_mul_eq_one (n : ℕ) (a b : ZMod n) (h : a * b = 1) : a⁻¹ = b :=
left_inv_eq_right_inv (inv_mul_of_unit a ⟨⟨a, b, h, mul_comm a b ▸ h⟩, rfl⟩) h
-- TODO: this equivalence is true for `ZMod 0 = ℤ`, but needs to use different functions.
/-- Equivalence between the units of `ZMod n` and
the subtype of terms `x : ZMod n` for which `x.val` is coprime to `n` -/
def unitsEquivCoprime {n : ℕ} [NeZero n] : (ZMod n)ˣ ≃ { x : ZMod n // Nat.Coprime x.val n } where
toFun x := ⟨x, val_coe_unit_coprime x⟩
invFun x := unitOfCoprime x.1.val x.2
left_inv := fun ⟨_, _, _, _⟩ => Units.ext (natCast_zmod_val _)
right_inv := fun ⟨_, _⟩ => by simp
#align zmod.units_equiv_coprime ZMod.unitsEquivCoprime
/-- The **Chinese remainder theorem**. For a pair of coprime natural numbers, `m` and `n`,
the rings `ZMod (m * n)` and `ZMod m × ZMod n` are isomorphic.
See `Ideal.quotientInfRingEquivPiQuotient` for the Chinese remainder theorem for ideals in any
ring.
-/
def chineseRemainder {m n : ℕ} (h : m.Coprime n) : ZMod (m * n) ≃+* ZMod m × ZMod n :=
let to_fun : ZMod (m * n) → ZMod m × ZMod n :=
ZMod.castHom (show m.lcm n ∣ m * n by simp [Nat.lcm_dvd_iff]) (ZMod m × ZMod n)
let inv_fun : ZMod m × ZMod n → ZMod (m * n) := fun x =>
if m * n = 0 then
if m = 1 then cast (RingHom.snd _ (ZMod n) x) else cast (RingHom.fst (ZMod m) _ x)
else Nat.chineseRemainder h x.1.val x.2.val
have inv : Function.LeftInverse inv_fun to_fun ∧ Function.RightInverse inv_fun to_fun :=
if hmn0 : m * n = 0 then by
rcases h.eq_of_mul_eq_zero hmn0 with (⟨rfl, rfl⟩ | ⟨rfl, rfl⟩)
· constructor
· intro x; rfl
· rintro ⟨x, y⟩
fin_cases y
simp [to_fun, inv_fun, castHom, Prod.ext_iff, eq_iff_true_of_subsingleton]
· constructor
· intro x; rfl
· rintro ⟨x, y⟩
fin_cases x
simp [to_fun, inv_fun, castHom, Prod.ext_iff, eq_iff_true_of_subsingleton]
else by
haveI : NeZero (m * n) := ⟨hmn0⟩
haveI : NeZero m := ⟨left_ne_zero_of_mul hmn0⟩
haveI : NeZero n := ⟨right_ne_zero_of_mul hmn0⟩
have left_inv : Function.LeftInverse inv_fun to_fun := by
intro x
dsimp only [to_fun, inv_fun, ZMod.castHom_apply]
conv_rhs => rw [← ZMod.natCast_zmod_val x]
rw [if_neg hmn0, ZMod.eq_iff_modEq_nat, ← Nat.modEq_and_modEq_iff_modEq_mul h,
Prod.fst_zmod_cast, Prod.snd_zmod_cast]
refine
⟨(Nat.chineseRemainder h (cast x : ZMod m).val (cast x : ZMod n).val).2.left.trans ?_,
(Nat.chineseRemainder h (cast x : ZMod m).val (cast x : ZMod n).val).2.right.trans ?_⟩
· rw [← ZMod.eq_iff_modEq_nat, ZMod.natCast_zmod_val, ZMod.natCast_val]
· rw [← ZMod.eq_iff_modEq_nat, ZMod.natCast_zmod_val, ZMod.natCast_val]
exact ⟨left_inv, left_inv.rightInverse_of_card_le (by simp)⟩
{ toFun := to_fun,
invFun := inv_fun,
map_mul' := RingHom.map_mul _
map_add' := RingHom.map_add _
left_inv := inv.1
right_inv := inv.2 }
#align zmod.chinese_remainder ZMod.chineseRemainder
lemma subsingleton_iff {n : ℕ} : Subsingleton (ZMod n) ↔ n = 1 := by
constructor
· obtain (_ | _ | n) := n
· simpa [ZMod] using not_subsingleton _
· simp [ZMod]
· simpa [ZMod] using not_subsingleton _
· rintro rfl
infer_instance
lemma nontrivial_iff {n : ℕ} : Nontrivial (ZMod n) ↔ n ≠ 1 := by
rw [← not_subsingleton_iff_nontrivial, subsingleton_iff]
-- todo: this can be made a `Unique` instance.
instance subsingleton_units : Subsingleton (ZMod 2)ˣ :=
⟨by decide⟩
#align zmod.subsingleton_units ZMod.subsingleton_units
@[simp]
theorem add_self_eq_zero_iff_eq_zero {n : ℕ} (hn : Odd n) {a : ZMod n} :
a + a = 0 ↔ a = 0 := by
rw [Nat.odd_iff, ← Nat.two_dvd_ne_zero, ← Nat.prime_two.coprime_iff_not_dvd] at hn
rw [← mul_two, ← @Nat.cast_two (ZMod n), ← ZMod.coe_unitOfCoprime 2 hn, Units.mul_left_eq_zero]
theorem ne_neg_self {n : ℕ} (hn : Odd n) {a : ZMod n} (ha : a ≠ 0) : a ≠ -a := by
rwa [Ne, eq_neg_iff_add_eq_zero, add_self_eq_zero_iff_eq_zero hn]
#align zmod.ne_neg_self ZMod.ne_neg_self
theorem neg_one_ne_one {n : ℕ} [Fact (2 < n)] : (-1 : ZMod n) ≠ 1 :=
CharP.neg_one_ne_one (ZMod n) n
#align zmod.neg_one_ne_one ZMod.neg_one_ne_one
theorem neg_eq_self_mod_two (a : ZMod 2) : -a = a := by
fin_cases a <;> apply Fin.ext <;> simp [Fin.coe_neg, Int.natMod]; rfl
#align zmod.neg_eq_self_mod_two ZMod.neg_eq_self_mod_two
@[simp]
theorem natAbs_mod_two (a : ℤ) : (a.natAbs : ZMod 2) = a := by
cases a
· simp only [Int.natAbs_ofNat, Int.cast_natCast, Int.ofNat_eq_coe]
· simp only [neg_eq_self_mod_two, Nat.cast_succ, Int.natAbs, Int.cast_negSucc]
#align zmod.nat_abs_mod_two ZMod.natAbs_mod_two
@[simp]
theorem val_eq_zero : ∀ {n : ℕ} (a : ZMod n), a.val = 0 ↔ a = 0
| 0, a => Int.natAbs_eq_zero
| n + 1, a => by
rw [Fin.ext_iff]
exact Iff.rfl
#align zmod.val_eq_zero ZMod.val_eq_zero
theorem val_ne_zero {n : ℕ} (a : ZMod n) : a.val ≠ 0 ↔ a ≠ 0 :=
(val_eq_zero a).not
theorem neg_eq_self_iff {n : ℕ} (a : ZMod n) : -a = a ↔ a = 0 ∨ 2 * a.val = n := by
rw [neg_eq_iff_add_eq_zero, ← two_mul]
cases n
· erw [@mul_eq_zero ℤ, @mul_eq_zero ℕ, val_eq_zero]
exact
⟨fun h => h.elim (by simp) Or.inl, fun h =>
Or.inr (h.elim id fun h => h.elim (by simp) id)⟩
conv_lhs =>
rw [← a.natCast_zmod_val, ← Nat.cast_two, ← Nat.cast_mul, natCast_zmod_eq_zero_iff_dvd]
constructor
· rintro ⟨m, he⟩
cases' m with m
· erw [mul_zero, mul_eq_zero] at he
rcases he with (⟨⟨⟩⟩ | he)
exact Or.inl (a.val_eq_zero.1 he)
cases m
· right
rwa [show 0 + 1 = 1 from rfl, mul_one] at he
refine (a.val_lt.not_le <| Nat.le_of_mul_le_mul_left ?_ zero_lt_two).elim
rw [he, mul_comm]
apply Nat.mul_le_mul_left
erw [Nat.succ_le_succ_iff, Nat.succ_le_succ_iff]; simp
· rintro (rfl | h)
· rw [val_zero, mul_zero]
apply dvd_zero
· rw [h]
#align zmod.neg_eq_self_iff ZMod.neg_eq_self_iff
theorem val_cast_of_lt {n : ℕ} {a : ℕ} (h : a < n) : (a : ZMod n).val = a := by
rw [val_natCast, Nat.mod_eq_of_lt h]
#align zmod.val_cast_of_lt ZMod.val_cast_of_lt
theorem neg_val' {n : ℕ} [NeZero n] (a : ZMod n) : (-a).val = (n - a.val) % n :=
calc
(-a).val = val (-a) % n := by rw [Nat.mod_eq_of_lt (-a).val_lt]
_ = (n - val a) % n :=
Nat.ModEq.add_right_cancel' _
(by
rw [Nat.ModEq, ← val_add, add_left_neg, tsub_add_cancel_of_le a.val_le, Nat.mod_self,
val_zero])
#align zmod.neg_val' ZMod.neg_val'
theorem neg_val {n : ℕ} [NeZero n] (a : ZMod n) : (-a).val = if a = 0 then 0 else n - a.val := by
rw [neg_val']
by_cases h : a = 0; · rw [if_pos h, h, val_zero, tsub_zero, Nat.mod_self]
rw [if_neg h]
apply Nat.mod_eq_of_lt
apply Nat.sub_lt (NeZero.pos n)
contrapose! h
rwa [Nat.le_zero, val_eq_zero] at h
#align zmod.neg_val ZMod.neg_val
theorem val_neg_of_ne_zero {n : ℕ} [nz : NeZero n] (a : ZMod n) [na : NeZero a] :
(- a).val = n - a.val := by simp_all [neg_val a, na.out]
theorem val_sub {n : ℕ} [NeZero n] {a b : ZMod n} (h : b.val ≤ a.val) :
(a - b).val = a.val - b.val := by
by_cases hb : b = 0
· cases hb; simp
· have : NeZero b := ⟨hb⟩
rw [sub_eq_add_neg, val_add, val_neg_of_ne_zero, ← Nat.add_sub_assoc (le_of_lt (val_lt _)),
add_comm, Nat.add_sub_assoc h, Nat.add_mod_left]
apply Nat.mod_eq_of_lt (tsub_lt_of_lt (val_lt _))
theorem val_cast_eq_val_of_lt {m n : ℕ} [nzm : NeZero m] {a : ZMod m}
(h : a.val < n) : (a.cast : ZMod n).val = a.val := by
have nzn : NeZero n := by constructor; rintro rfl; simp at h
cases m with
| zero => cases nzm; simp_all
| succ m =>
cases n with
| zero => cases nzn; simp_all
| succ n => exact Fin.val_cast_of_lt h
theorem cast_cast_zmod_of_le {m n : ℕ} [hm : NeZero m] (h : m ≤ n) (a : ZMod m) :
(cast (cast a : ZMod n) : ZMod m) = a := by
have : NeZero n := ⟨((Nat.zero_lt_of_ne_zero hm.out).trans_le h).ne'⟩
rw [cast_eq_val, val_cast_eq_val_of_lt (a.val_lt.trans_le h), natCast_zmod_val]
/-- `valMinAbs x` returns the integer in the same equivalence class as `x` that is closest to `0`,
The result will be in the interval `(-n/2, n/2]`. -/
def valMinAbs : ∀ {n : ℕ}, ZMod n → ℤ
| 0, x => x
| n@(_ + 1), x => if x.val ≤ n / 2 then x.val else (x.val : ℤ) - n
#align zmod.val_min_abs ZMod.valMinAbs
@[simp]
theorem valMinAbs_def_zero (x : ZMod 0) : valMinAbs x = x :=
rfl
#align zmod.val_min_abs_def_zero ZMod.valMinAbs_def_zero
theorem valMinAbs_def_pos {n : ℕ} [NeZero n] (x : ZMod n) :
valMinAbs x = if x.val ≤ n / 2 then (x.val : ℤ) else x.val - n := by
cases n
· cases NeZero.ne 0 rfl
· rfl
#align zmod.val_min_abs_def_pos ZMod.valMinAbs_def_pos
@[simp, norm_cast]
theorem coe_valMinAbs : ∀ {n : ℕ} (x : ZMod n), (x.valMinAbs : ZMod n) = x
| 0, x => Int.cast_id
| k@(n + 1), x => by
rw [valMinAbs_def_pos]
split_ifs
· rw [Int.cast_natCast, natCast_zmod_val]
· rw [Int.cast_sub, Int.cast_natCast, natCast_zmod_val, Int.cast_natCast, natCast_self,
sub_zero]
#align zmod.coe_val_min_abs ZMod.coe_valMinAbs
theorem injective_valMinAbs {n : ℕ} : (valMinAbs : ZMod n → ℤ).Injective :=
Function.injective_iff_hasLeftInverse.2 ⟨_, coe_valMinAbs⟩
#align zmod.injective_val_min_abs ZMod.injective_valMinAbs
theorem _root_.Nat.le_div_two_iff_mul_two_le {n m : ℕ} : m ≤ n / 2 ↔ (m : ℤ) * 2 ≤ n := by
rw [Nat.le_div_iff_mul_le zero_lt_two, ← Int.ofNat_le, Int.ofNat_mul, Nat.cast_two]
#align nat.le_div_two_iff_mul_two_le Nat.le_div_two_iff_mul_two_le
theorem valMinAbs_nonneg_iff {n : ℕ} [NeZero n] (x : ZMod n) : 0 ≤ x.valMinAbs ↔ x.val ≤ n / 2 := by
rw [valMinAbs_def_pos]; split_ifs with h
· exact iff_of_true (Nat.cast_nonneg _) h
· exact iff_of_false (sub_lt_zero.2 <| Int.ofNat_lt.2 x.val_lt).not_le h
#align zmod.val_min_abs_nonneg_iff ZMod.valMinAbs_nonneg_iff
theorem valMinAbs_mul_two_eq_iff {n : ℕ} (a : ZMod n) : a.valMinAbs * 2 = n ↔ 2 * a.val = n := by
cases' n with n
· simp
by_cases h : a.val ≤ n.succ / 2
· dsimp [valMinAbs]
rw [if_pos h, ← Int.natCast_inj, Nat.cast_mul, Nat.cast_two, mul_comm]
apply iff_of_false _ (mt _ h)
· intro he
rw [← a.valMinAbs_nonneg_iff, ← mul_nonneg_iff_left_nonneg_of_pos, he] at h
exacts [h (Nat.cast_nonneg _), zero_lt_two]
· rw [mul_comm]
exact fun h => (Nat.le_div_iff_mul_le zero_lt_two).2 h.le
#align zmod.val_min_abs_mul_two_eq_iff ZMod.valMinAbs_mul_two_eq_iff
theorem valMinAbs_mem_Ioc {n : ℕ} [NeZero n] (x : ZMod n) :
x.valMinAbs * 2 ∈ Set.Ioc (-n : ℤ) n := by
simp_rw [valMinAbs_def_pos, Nat.le_div_two_iff_mul_two_le]; split_ifs with h
· refine ⟨(neg_lt_zero.2 <| mod_cast NeZero.pos n).trans_le (mul_nonneg ?_ ?_), h⟩
exacts [Nat.cast_nonneg _, zero_le_two]
· refine ⟨?_, le_trans (mul_nonpos_of_nonpos_of_nonneg ?_ zero_le_two) <| Nat.cast_nonneg _⟩
· linarith only [h]
· rw [sub_nonpos, Int.ofNat_le]
exact x.val_lt.le
#align zmod.val_min_abs_mem_Ioc ZMod.valMinAbs_mem_Ioc
theorem valMinAbs_spec {n : ℕ} [NeZero n] (x : ZMod n) (y : ℤ) :
x.valMinAbs = y ↔ x = y ∧ y * 2 ∈ Set.Ioc (-n : ℤ) n :=
⟨by
rintro rfl
exact ⟨x.coe_valMinAbs.symm, x.valMinAbs_mem_Ioc⟩, fun h =>
by
rw [← sub_eq_zero]
apply @Int.eq_zero_of_abs_lt_dvd n
· rw [← intCast_zmod_eq_zero_iff_dvd, Int.cast_sub, coe_valMinAbs, h.1, sub_self]
rw [← mul_lt_mul_right (@zero_lt_two ℤ _ _ _ _ _)]
nth_rw 1 [← abs_eq_self.2 (@zero_le_two ℤ _ _ _ _)]
rw [← abs_mul, sub_mul, abs_lt]
constructor <;> linarith only [x.valMinAbs_mem_Ioc.1, x.valMinAbs_mem_Ioc.2, h.2.1, h.2.2]⟩
#align zmod.val_min_abs_spec ZMod.valMinAbs_spec
theorem natAbs_valMinAbs_le {n : ℕ} [NeZero n] (x : ZMod n) : x.valMinAbs.natAbs ≤ n / 2 := by
rw [Nat.le_div_two_iff_mul_two_le]
cases' x.valMinAbs.natAbs_eq with h h
· rw [← h]
exact x.valMinAbs_mem_Ioc.2
· rw [← neg_le_neg_iff, ← neg_mul, ← h]
exact x.valMinAbs_mem_Ioc.1.le
#align zmod.nat_abs_val_min_abs_le ZMod.natAbs_valMinAbs_le
@[simp]
theorem valMinAbs_zero : ∀ n, (0 : ZMod n).valMinAbs = 0
| 0 => by simp only [valMinAbs_def_zero]
| n + 1 => by simp only [valMinAbs_def_pos, if_true, Int.ofNat_zero, zero_le, val_zero]
#align zmod.val_min_abs_zero ZMod.valMinAbs_zero
@[simp]
theorem valMinAbs_eq_zero {n : ℕ} (x : ZMod n) : x.valMinAbs = 0 ↔ x = 0 := by
cases' n with n
· simp
rw [← valMinAbs_zero n.succ]
apply injective_valMinAbs.eq_iff
#align zmod.val_min_abs_eq_zero ZMod.valMinAbs_eq_zero
| Mathlib/Data/ZMod/Basic.lean | 1,220 | 1,229 | theorem natCast_natAbs_valMinAbs {n : ℕ} [NeZero n] (a : ZMod n) :
(a.valMinAbs.natAbs : ZMod n) = if a.val ≤ (n : ℕ) / 2 then a else -a := by |
have : (a.val : ℤ) - n ≤ 0 := by
erw [sub_nonpos, Int.ofNat_le]
exact a.val_le
rw [valMinAbs_def_pos]
split_ifs
· rw [Int.natAbs_ofNat, natCast_zmod_val]
· rw [← Int.cast_natCast, Int.ofNat_natAbs_of_nonpos this, Int.cast_neg, Int.cast_sub,
Int.cast_natCast, Int.cast_natCast, natCast_self, sub_zero, natCast_zmod_val]
|
/-
Copyright (c) 2022 Vincent Beffara. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Vincent Beffara
-/
import Mathlib.Analysis.Complex.RemovableSingularity
import Mathlib.Analysis.Calculus.UniformLimitsDeriv
import Mathlib.Analysis.NormedSpace.FunctionSeries
#align_import analysis.complex.locally_uniform_limit from "leanprover-community/mathlib"@"fe44cd36149e675eb5dec87acc7e8f1d6568e081"
/-!
# Locally uniform limits of holomorphic functions
This file gathers some results about locally uniform limits of holomorphic functions on an open
subset of the complex plane.
## Main results
* `TendstoLocallyUniformlyOn.differentiableOn`: A locally uniform limit of holomorphic functions
is holomorphic.
* `TendstoLocallyUniformlyOn.deriv`: Locally uniform convergence implies locally uniform
convergence of the derivatives to the derivative of the limit.
-/
open Set Metric MeasureTheory Filter Complex intervalIntegral
open scoped Real Topology
variable {E ι : Type*} [NormedAddCommGroup E] [NormedSpace ℂ E] [CompleteSpace E] {U K : Set ℂ}
{z : ℂ} {M r δ : ℝ} {φ : Filter ι} {F : ι → ℂ → E} {f g : ℂ → E}
namespace Complex
section Cderiv
/-- A circle integral which coincides with `deriv f z` whenever one can apply the Cauchy formula for
the derivative. It is useful in the proof that locally uniform limits of holomorphic functions are
holomorphic, because it depends continuously on `f` for the uniform topology. -/
noncomputable def cderiv (r : ℝ) (f : ℂ → E) (z : ℂ) : E :=
(2 * π * I : ℂ)⁻¹ • ∮ w in C(z, r), ((w - z) ^ 2)⁻¹ • f w
#align complex.cderiv Complex.cderiv
theorem cderiv_eq_deriv (hU : IsOpen U) (hf : DifferentiableOn ℂ f U) (hr : 0 < r)
(hzr : closedBall z r ⊆ U) : cderiv r f z = deriv f z :=
two_pi_I_inv_smul_circleIntegral_sub_sq_inv_smul_of_differentiable hU hzr hf (mem_ball_self hr)
#align complex.cderiv_eq_deriv Complex.cderiv_eq_deriv
theorem norm_cderiv_le (hr : 0 < r) (hf : ∀ w ∈ sphere z r, ‖f w‖ ≤ M) :
‖cderiv r f z‖ ≤ M / r := by
have hM : 0 ≤ M := by
obtain ⟨w, hw⟩ : (sphere z r).Nonempty := NormedSpace.sphere_nonempty.mpr hr.le
exact (norm_nonneg _).trans (hf w hw)
have h1 : ∀ w ∈ sphere z r, ‖((w - z) ^ 2)⁻¹ • f w‖ ≤ M / r ^ 2 := by
intro w hw
simp only [mem_sphere_iff_norm, norm_eq_abs] at hw
simp only [norm_smul, inv_mul_eq_div, hw, norm_eq_abs, map_inv₀, Complex.abs_pow]
exact div_le_div hM (hf w hw) (sq_pos_of_pos hr) le_rfl
have h2 := circleIntegral.norm_integral_le_of_norm_le_const hr.le h1
simp only [cderiv, norm_smul]
refine (mul_le_mul le_rfl h2 (norm_nonneg _) (norm_nonneg _)).trans (le_of_eq ?_)
field_simp [_root_.abs_of_nonneg Real.pi_pos.le]
ring
#align complex.norm_cderiv_le Complex.norm_cderiv_le
theorem cderiv_sub (hr : 0 < r) (hf : ContinuousOn f (sphere z r))
(hg : ContinuousOn g (sphere z r)) : cderiv r (f - g) z = cderiv r f z - cderiv r g z := by
have h1 : ContinuousOn (fun w : ℂ => ((w - z) ^ 2)⁻¹) (sphere z r) := by
refine ((continuous_id'.sub continuous_const).pow 2).continuousOn.inv₀ fun w hw h => hr.ne ?_
rwa [mem_sphere_iff_norm, sq_eq_zero_iff.mp h, norm_zero] at hw
simp_rw [cderiv, ← smul_sub]
congr 1
simpa only [Pi.sub_apply, smul_sub] using
circleIntegral.integral_sub ((h1.smul hf).circleIntegrable hr.le)
((h1.smul hg).circleIntegrable hr.le)
#align complex.cderiv_sub Complex.cderiv_sub
theorem norm_cderiv_lt (hr : 0 < r) (hfM : ∀ w ∈ sphere z r, ‖f w‖ < M)
(hf : ContinuousOn f (sphere z r)) : ‖cderiv r f z‖ < M / r := by
obtain ⟨L, hL1, hL2⟩ : ∃ L < M, ∀ w ∈ sphere z r, ‖f w‖ ≤ L := by
have e1 : (sphere z r).Nonempty := NormedSpace.sphere_nonempty.mpr hr.le
have e2 : ContinuousOn (fun w => ‖f w‖) (sphere z r) := continuous_norm.comp_continuousOn hf
obtain ⟨x, hx, hx'⟩ := (isCompact_sphere z r).exists_isMaxOn e1 e2
exact ⟨‖f x‖, hfM x hx, hx'⟩
exact (norm_cderiv_le hr hL2).trans_lt ((div_lt_div_right hr).mpr hL1)
#align complex.norm_cderiv_lt Complex.norm_cderiv_lt
theorem norm_cderiv_sub_lt (hr : 0 < r) (hfg : ∀ w ∈ sphere z r, ‖f w - g w‖ < M)
(hf : ContinuousOn f (sphere z r)) (hg : ContinuousOn g (sphere z r)) :
‖cderiv r f z - cderiv r g z‖ < M / r :=
cderiv_sub hr hf hg ▸ norm_cderiv_lt hr hfg (hf.sub hg)
#align complex.norm_cderiv_sub_lt Complex.norm_cderiv_sub_lt
| Mathlib/Analysis/Complex/LocallyUniformLimit.lean | 95 | 110 | theorem _root_.TendstoUniformlyOn.cderiv (hF : TendstoUniformlyOn F f φ (cthickening δ K))
(hδ : 0 < δ) (hFn : ∀ᶠ n in φ, ContinuousOn (F n) (cthickening δ K)) :
TendstoUniformlyOn (cderiv δ ∘ F) (cderiv δ f) φ K := by |
rcases φ.eq_or_neBot with rfl | hne
· simp only [TendstoUniformlyOn, eventually_bot, imp_true_iff]
have e1 : ContinuousOn f (cthickening δ K) := TendstoUniformlyOn.continuousOn hF hFn
rw [tendstoUniformlyOn_iff] at hF ⊢
rintro ε hε
filter_upwards [hF (ε * δ) (mul_pos hε hδ), hFn] with n h h' z hz
simp_rw [dist_eq_norm] at h ⊢
have e2 : ∀ w ∈ sphere z δ, ‖f w - F n w‖ < ε * δ := fun w hw1 =>
h w (closedBall_subset_cthickening hz δ (sphere_subset_closedBall hw1))
have e3 := sphere_subset_closedBall.trans (closedBall_subset_cthickening hz δ)
have hf : ContinuousOn f (sphere z δ) :=
e1.mono (sphere_subset_closedBall.trans (closedBall_subset_cthickening hz δ))
simpa only [mul_div_cancel_right₀ _ hδ.ne.symm] using norm_cderiv_sub_lt hδ e2 hf (h'.mono e3)
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Scott Morrison, Jens Wagemaker
-/
import Mathlib.Algebra.GroupPower.IterateHom
import Mathlib.Algebra.Polynomial.Eval
import Mathlib.GroupTheory.GroupAction.Ring
#align_import data.polynomial.derivative from "leanprover-community/mathlib"@"bbeb185db4ccee8ed07dc48449414ebfa39cb821"
/-!
# The derivative map on polynomials
## Main definitions
* `Polynomial.derivative`: The formal derivative of polynomials, expressed as a linear map.
-/
noncomputable section
open Finset
open Polynomial
namespace Polynomial
universe u v w y z
variable {R : Type u} {S : Type v} {T : Type w} {ι : Type y} {A : Type z} {a b : R} {n : ℕ}
section Derivative
section Semiring
variable [Semiring R]
/-- `derivative p` is the formal derivative of the polynomial `p` -/
def derivative : R[X] →ₗ[R] R[X] where
toFun p := p.sum fun n a => C (a * n) * X ^ (n - 1)
map_add' p q := by
dsimp only
rw [sum_add_index] <;>
simp only [add_mul, forall_const, RingHom.map_add, eq_self_iff_true, zero_mul,
RingHom.map_zero]
map_smul' a p := by
dsimp; rw [sum_smul_index] <;>
simp only [mul_sum, ← C_mul', mul_assoc, coeff_C_mul, RingHom.map_mul, forall_const, zero_mul,
RingHom.map_zero, sum]
#align polynomial.derivative Polynomial.derivative
theorem derivative_apply (p : R[X]) : derivative p = p.sum fun n a => C (a * n) * X ^ (n - 1) :=
rfl
#align polynomial.derivative_apply Polynomial.derivative_apply
theorem coeff_derivative (p : R[X]) (n : ℕ) :
coeff (derivative p) n = coeff p (n + 1) * (n + 1) := by
rw [derivative_apply]
simp only [coeff_X_pow, coeff_sum, coeff_C_mul]
rw [sum, Finset.sum_eq_single (n + 1)]
· simp only [Nat.add_succ_sub_one, add_zero, mul_one, if_true, eq_self_iff_true]; norm_cast
· intro b
cases b
· intros
rw [Nat.cast_zero, mul_zero, zero_mul]
· intro _ H
rw [Nat.add_one_sub_one, if_neg (mt (congr_arg Nat.succ) H.symm), mul_zero]
· rw [if_pos (add_tsub_cancel_right n 1).symm, mul_one, Nat.cast_add, Nat.cast_one,
mem_support_iff]
intro h
push_neg at h
simp [h]
#align polynomial.coeff_derivative Polynomial.coeff_derivative
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_zero : derivative (0 : R[X]) = 0 :=
derivative.map_zero
#align polynomial.derivative_zero Polynomial.derivative_zero
theorem iterate_derivative_zero {k : ℕ} : derivative^[k] (0 : R[X]) = 0 :=
iterate_map_zero derivative k
#align polynomial.iterate_derivative_zero Polynomial.iterate_derivative_zero
@[simp]
theorem derivative_monomial (a : R) (n : ℕ) :
derivative (monomial n a) = monomial (n - 1) (a * n) := by
rw [derivative_apply, sum_monomial_index, C_mul_X_pow_eq_monomial]
simp
#align polynomial.derivative_monomial Polynomial.derivative_monomial
theorem derivative_C_mul_X (a : R) : derivative (C a * X) = C a := by
simp [C_mul_X_eq_monomial, derivative_monomial, Nat.cast_one, mul_one]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_C_mul_X Polynomial.derivative_C_mul_X
theorem derivative_C_mul_X_pow (a : R) (n : ℕ) :
derivative (C a * X ^ n) = C (a * n) * X ^ (n - 1) := by
rw [C_mul_X_pow_eq_monomial, C_mul_X_pow_eq_monomial, derivative_monomial]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_C_mul_X_pow Polynomial.derivative_C_mul_X_pow
theorem derivative_C_mul_X_sq (a : R) : derivative (C a * X ^ 2) = C (a * 2) * X := by
rw [derivative_C_mul_X_pow, Nat.cast_two, pow_one]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_C_mul_X_sq Polynomial.derivative_C_mul_X_sq
@[simp]
theorem derivative_X_pow (n : ℕ) : derivative (X ^ n : R[X]) = C (n : R) * X ^ (n - 1) := by
convert derivative_C_mul_X_pow (1 : R) n <;> simp
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_X_pow Polynomial.derivative_X_pow
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_X_sq : derivative (X ^ 2 : R[X]) = C 2 * X := by
rw [derivative_X_pow, Nat.cast_two, pow_one]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_X_sq Polynomial.derivative_X_sq
@[simp]
theorem derivative_C {a : R} : derivative (C a) = 0 := by simp [derivative_apply]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_C Polynomial.derivative_C
theorem derivative_of_natDegree_zero {p : R[X]} (hp : p.natDegree = 0) : derivative p = 0 := by
rw [eq_C_of_natDegree_eq_zero hp, derivative_C]
#align polynomial.derivative_of_nat_degree_zero Polynomial.derivative_of_natDegree_zero
@[simp]
theorem derivative_X : derivative (X : R[X]) = 1 :=
(derivative_monomial _ _).trans <| by simp
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_X Polynomial.derivative_X
@[simp]
theorem derivative_one : derivative (1 : R[X]) = 0 :=
derivative_C
#align polynomial.derivative_one Polynomial.derivative_one
#noalign polynomial.derivative_bit0
#noalign polynomial.derivative_bit1
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_add {f g : R[X]} : derivative (f + g) = derivative f + derivative g :=
derivative.map_add f g
#align polynomial.derivative_add Polynomial.derivative_add
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_X_add_C (c : R) : derivative (X + C c) = 1 := by
rw [derivative_add, derivative_X, derivative_C, add_zero]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_X_add_C Polynomial.derivative_X_add_C
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_sum {s : Finset ι} {f : ι → R[X]} :
derivative (∑ b ∈ s, f b) = ∑ b ∈ s, derivative (f b) :=
map_sum ..
#align polynomial.derivative_sum Polynomial.derivative_sum
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_smul {S : Type*} [Monoid S] [DistribMulAction S R] [IsScalarTower S R R] (s : S)
(p : R[X]) : derivative (s • p) = s • derivative p :=
derivative.map_smul_of_tower s p
#align polynomial.derivative_smul Polynomial.derivative_smul
@[simp]
theorem iterate_derivative_smul {S : Type*} [Monoid S] [DistribMulAction S R] [IsScalarTower S R R]
(s : S) (p : R[X]) (k : ℕ) : derivative^[k] (s • p) = s • derivative^[k] p := by
induction' k with k ih generalizing p
· simp
· simp [ih]
#align polynomial.iterate_derivative_smul Polynomial.iterate_derivative_smul
@[simp]
theorem iterate_derivative_C_mul (a : R) (p : R[X]) (k : ℕ) :
derivative^[k] (C a * p) = C a * derivative^[k] p := by
simp_rw [← smul_eq_C_mul, iterate_derivative_smul]
set_option linter.uppercaseLean3 false in
#align polynomial.iterate_derivative_C_mul Polynomial.iterate_derivative_C_mul
theorem of_mem_support_derivative {p : R[X]} {n : ℕ} (h : n ∈ p.derivative.support) :
n + 1 ∈ p.support :=
mem_support_iff.2 fun h1 : p.coeff (n + 1) = 0 =>
mem_support_iff.1 h <| show p.derivative.coeff n = 0 by rw [coeff_derivative, h1, zero_mul]
#align polynomial.of_mem_support_derivative Polynomial.of_mem_support_derivative
theorem degree_derivative_lt {p : R[X]} (hp : p ≠ 0) : p.derivative.degree < p.degree :=
(Finset.sup_lt_iff <| bot_lt_iff_ne_bot.2 <| mt degree_eq_bot.1 hp).2 fun n hp =>
lt_of_lt_of_le (WithBot.coe_lt_coe.2 n.lt_succ_self) <|
Finset.le_sup <| of_mem_support_derivative hp
#align polynomial.degree_derivative_lt Polynomial.degree_derivative_lt
theorem degree_derivative_le {p : R[X]} : p.derivative.degree ≤ p.degree :=
letI := Classical.decEq R
if H : p = 0 then le_of_eq <| by rw [H, derivative_zero] else (degree_derivative_lt H).le
#align polynomial.degree_derivative_le Polynomial.degree_derivative_le
theorem natDegree_derivative_lt {p : R[X]} (hp : p.natDegree ≠ 0) :
p.derivative.natDegree < p.natDegree := by
rcases eq_or_ne (derivative p) 0 with hp' | hp'
· rw [hp', Polynomial.natDegree_zero]
exact hp.bot_lt
· rw [natDegree_lt_natDegree_iff hp']
exact degree_derivative_lt fun h => hp (h.symm ▸ natDegree_zero)
#align polynomial.nat_degree_derivative_lt Polynomial.natDegree_derivative_lt
theorem natDegree_derivative_le (p : R[X]) : p.derivative.natDegree ≤ p.natDegree - 1 := by
by_cases p0 : p.natDegree = 0
· simp [p0, derivative_of_natDegree_zero]
· exact Nat.le_sub_one_of_lt (natDegree_derivative_lt p0)
#align polynomial.nat_degree_derivative_le Polynomial.natDegree_derivative_le
theorem natDegree_iterate_derivative (p : R[X]) (k : ℕ) :
(derivative^[k] p).natDegree ≤ p.natDegree - k := by
induction k with
| zero => rw [Function.iterate_zero_apply, Nat.sub_zero]
| succ d hd =>
rw [Function.iterate_succ_apply', Nat.sub_succ']
exact (natDegree_derivative_le _).trans <| Nat.sub_le_sub_right hd 1
@[simp]
theorem derivative_natCast {n : ℕ} : derivative (n : R[X]) = 0 := by
rw [← map_natCast C n]
exact derivative_C
#align polynomial.derivative_nat_cast Polynomial.derivative_natCast
@[deprecated (since := "2024-04-17")]
alias derivative_nat_cast := derivative_natCast
-- Porting note (#10756): new theorem
@[simp]
theorem derivative_ofNat (n : ℕ) [n.AtLeastTwo] :
derivative (no_index (OfNat.ofNat n) : R[X]) = 0 :=
derivative_natCast
theorem iterate_derivative_eq_zero {p : R[X]} {x : ℕ} (hx : p.natDegree < x) :
Polynomial.derivative^[x] p = 0 := by
induction' h : p.natDegree using Nat.strong_induction_on with _ ih generalizing p x
subst h
obtain ⟨t, rfl⟩ := Nat.exists_eq_succ_of_ne_zero (pos_of_gt hx).ne'
rw [Function.iterate_succ_apply]
by_cases hp : p.natDegree = 0
· rw [derivative_of_natDegree_zero hp, iterate_derivative_zero]
have := natDegree_derivative_lt hp
exact ih _ this (this.trans_le <| Nat.le_of_lt_succ hx) rfl
#align polynomial.iterate_derivative_eq_zero Polynomial.iterate_derivative_eq_zero
@[simp]
theorem iterate_derivative_C {k} (h : 0 < k) : derivative^[k] (C a : R[X]) = 0 :=
iterate_derivative_eq_zero <| (natDegree_C _).trans_lt h
set_option linter.uppercaseLean3 false in
#align polynomial.iterate_derivative_C Polynomial.iterate_derivative_C
@[simp]
theorem iterate_derivative_one {k} (h : 0 < k) : derivative^[k] (1 : R[X]) = 0 :=
iterate_derivative_C h
#align polynomial.iterate_derivative_one Polynomial.iterate_derivative_one
@[simp]
theorem iterate_derivative_X {k} (h : 1 < k) : derivative^[k] (X : R[X]) = 0 :=
iterate_derivative_eq_zero <| natDegree_X_le.trans_lt h
set_option linter.uppercaseLean3 false in
#align polynomial.iterate_derivative_X Polynomial.iterate_derivative_X
theorem natDegree_eq_zero_of_derivative_eq_zero [NoZeroSMulDivisors ℕ R] {f : R[X]}
(h : derivative f = 0) : f.natDegree = 0 := by
rcases eq_or_ne f 0 with (rfl | hf)
· exact natDegree_zero
rw [natDegree_eq_zero_iff_degree_le_zero]
by_contra! f_nat_degree_pos
rw [← natDegree_pos_iff_degree_pos] at f_nat_degree_pos
let m := f.natDegree - 1
have hm : m + 1 = f.natDegree := tsub_add_cancel_of_le f_nat_degree_pos
have h2 := coeff_derivative f m
rw [Polynomial.ext_iff] at h
rw [h m, coeff_zero, ← Nat.cast_add_one, ← nsmul_eq_mul', eq_comm, smul_eq_zero] at h2
replace h2 := h2.resolve_left m.succ_ne_zero
rw [hm, ← leadingCoeff, leadingCoeff_eq_zero] at h2
exact hf h2
#align polynomial.nat_degree_eq_zero_of_derivative_eq_zero Polynomial.natDegree_eq_zero_of_derivative_eq_zero
theorem eq_C_of_derivative_eq_zero [NoZeroSMulDivisors ℕ R] {f : R[X]} (h : derivative f = 0) :
f = C (f.coeff 0) :=
eq_C_of_natDegree_eq_zero <| natDegree_eq_zero_of_derivative_eq_zero h
set_option linter.uppercaseLean3 false in
#align polynomial.eq_C_of_derivative_eq_zero Polynomial.eq_C_of_derivative_eq_zero
@[simp]
theorem derivative_mul {f g : R[X]} : derivative (f * g) = derivative f * g + f * derivative g := by
induction f using Polynomial.induction_on' with
| h_add => simp only [add_mul, map_add, add_assoc, add_left_comm, *]
| h_monomial m a =>
induction g using Polynomial.induction_on' with
| h_add => simp only [mul_add, map_add, add_assoc, add_left_comm, *]
| h_monomial n b =>
simp only [monomial_mul_monomial, derivative_monomial]
simp only [mul_assoc, (Nat.cast_commute _ _).eq, Nat.cast_add, mul_add, map_add]
cases m with
| zero => simp only [zero_add, Nat.cast_zero, mul_zero, map_zero]
| succ m =>
cases n with
| zero => simp only [add_zero, Nat.cast_zero, mul_zero, map_zero]
| succ n =>
simp only [Nat.add_succ_sub_one, add_tsub_cancel_right]
rw [add_assoc, add_comm n 1]
#align polynomial.derivative_mul Polynomial.derivative_mul
theorem derivative_eval (p : R[X]) (x : R) :
p.derivative.eval x = p.sum fun n a => a * n * x ^ (n - 1) := by
simp_rw [derivative_apply, eval_sum, eval_mul_X_pow, eval_C]
#align polynomial.derivative_eval Polynomial.derivative_eval
@[simp]
theorem derivative_map [Semiring S] (p : R[X]) (f : R →+* S) :
derivative (p.map f) = p.derivative.map f := by
let n := max p.natDegree (map f p).natDegree
rw [derivative_apply, derivative_apply]
rw [sum_over_range' _ _ (n + 1) ((le_max_left _ _).trans_lt (lt_add_one _))]
on_goal 1 => rw [sum_over_range' _ _ (n + 1) ((le_max_right _ _).trans_lt (lt_add_one _))]
· simp only [Polynomial.map_sum, Polynomial.map_mul, Polynomial.map_C, map_mul, coeff_map,
map_natCast, Polynomial.map_natCast, Polynomial.map_pow, map_X]
all_goals intro n; rw [zero_mul, C_0, zero_mul]
#align polynomial.derivative_map Polynomial.derivative_map
@[simp]
theorem iterate_derivative_map [Semiring S] (p : R[X]) (f : R →+* S) (k : ℕ) :
Polynomial.derivative^[k] (p.map f) = (Polynomial.derivative^[k] p).map f := by
induction' k with k ih generalizing p
· simp
· simp only [ih, Function.iterate_succ, Polynomial.derivative_map, Function.comp_apply]
#align polynomial.iterate_derivative_map Polynomial.iterate_derivative_map
theorem derivative_natCast_mul {n : ℕ} {f : R[X]} :
derivative ((n : R[X]) * f) = n * derivative f := by
simp
#align polynomial.derivative_nat_cast_mul Polynomial.derivative_natCast_mul
@[deprecated (since := "2024-04-17")]
alias derivative_nat_cast_mul := derivative_natCast_mul
@[simp]
theorem iterate_derivative_natCast_mul {n k : ℕ} {f : R[X]} :
derivative^[k] ((n : R[X]) * f) = n * derivative^[k] f := by
induction' k with k ih generalizing f <;> simp [*]
#align polynomial.iterate_derivative_nat_cast_mul Polynomial.iterate_derivative_natCast_mul
@[deprecated (since := "2024-04-17")]
alias iterate_derivative_nat_cast_mul := iterate_derivative_natCast_mul
theorem mem_support_derivative [NoZeroSMulDivisors ℕ R] (p : R[X]) (n : ℕ) :
n ∈ (derivative p).support ↔ n + 1 ∈ p.support := by
suffices ¬p.coeff (n + 1) * (n + 1 : ℕ) = 0 ↔ coeff p (n + 1) ≠ 0 by
simpa only [mem_support_iff, coeff_derivative, Ne, Nat.cast_succ]
rw [← nsmul_eq_mul', smul_eq_zero]
simp only [Nat.succ_ne_zero, false_or_iff]
#align polynomial.mem_support_derivative Polynomial.mem_support_derivative
@[simp]
theorem degree_derivative_eq [NoZeroSMulDivisors ℕ R] (p : R[X]) (hp : 0 < natDegree p) :
degree (derivative p) = (natDegree p - 1 : ℕ) := by
apply le_antisymm
· rw [derivative_apply]
apply le_trans (degree_sum_le _ _) (Finset.sup_le _)
intro n hn
apply le_trans (degree_C_mul_X_pow_le _ _) (WithBot.coe_le_coe.2 (tsub_le_tsub_right _ _))
apply le_natDegree_of_mem_supp _ hn
· refine le_sup ?_
rw [mem_support_derivative, tsub_add_cancel_of_le, mem_support_iff]
· rw [coeff_natDegree, Ne, leadingCoeff_eq_zero]
intro h
rw [h, natDegree_zero] at hp
exact hp.false
exact hp
#align polynomial.degree_derivative_eq Polynomial.degree_derivative_eq
#noalign polynomial.coeff_iterate_derivative_as_prod_Ico
#noalign polynomial.coeff_iterate_derivative_as_prod_range
theorem coeff_iterate_derivative {k} (p : R[X]) (m : ℕ) :
(derivative^[k] p).coeff m = (m + k).descFactorial k • p.coeff (m + k) := by
induction k generalizing m with
| zero => simp
| succ k ih =>
calc
(derivative^[k + 1] p).coeff m
_ = Nat.descFactorial (Nat.succ (m + k)) k • p.coeff (m + k.succ) * (m + 1) := by
rw [Function.iterate_succ_apply', coeff_derivative, ih m.succ, Nat.succ_add, Nat.add_succ]
_ = ((m + 1) * Nat.descFactorial (Nat.succ (m + k)) k) • p.coeff (m + k.succ) := by
rw [← Nat.cast_add_one, ← nsmul_eq_mul', smul_smul]
_ = Nat.descFactorial (m.succ + k) k.succ • p.coeff (m + k.succ) := by
rw [← Nat.succ_add, Nat.descFactorial_succ, add_tsub_cancel_right]
_ = Nat.descFactorial (m + k.succ) k.succ • p.coeff (m + k.succ) := by
rw [Nat.succ_add_eq_add_succ]
theorem iterate_derivative_mul {n} (p q : R[X]) :
derivative^[n] (p * q) =
∑ k ∈ range n.succ, (n.choose k • (derivative^[n - k] p * derivative^[k] q)) := by
induction' n with n IH
· simp [Finset.range]
calc
derivative^[n + 1] (p * q) =
derivative (∑ k ∈ range n.succ,
n.choose k • (derivative^[n - k] p * derivative^[k] q)) := by
rw [Function.iterate_succ_apply', IH]
_ = (∑ k ∈ range n.succ,
n.choose k • (derivative^[n - k + 1] p * derivative^[k] q)) +
∑ k ∈ range n.succ,
n.choose k • (derivative^[n - k] p * derivative^[k + 1] q) := by
simp_rw [derivative_sum, derivative_smul, derivative_mul, Function.iterate_succ_apply',
smul_add, sum_add_distrib]
_ = (∑ k ∈ range n.succ,
n.choose k.succ • (derivative^[n - k] p * derivative^[k + 1] q)) +
1 • (derivative^[n + 1] p * derivative^[0] q) +
∑ k ∈ range n.succ, n.choose k • (derivative^[n - k] p * derivative^[k + 1] q) :=
?_
_ = ((∑ k ∈ range n.succ, n.choose k • (derivative^[n - k] p * derivative^[k + 1] q)) +
∑ k ∈ range n.succ,
n.choose k.succ • (derivative^[n - k] p * derivative^[k + 1] q)) +
1 • (derivative^[n + 1] p * derivative^[0] q) := by
rw [add_comm, add_assoc]
_ = (∑ i ∈ range n.succ,
(n + 1).choose (i + 1) • (derivative^[n + 1 - (i + 1)] p * derivative^[i + 1] q)) +
1 • (derivative^[n + 1] p * derivative^[0] q) := by
simp_rw [Nat.choose_succ_succ, Nat.succ_sub_succ, add_smul, sum_add_distrib]
_ = ∑ k ∈ range n.succ.succ,
n.succ.choose k • (derivative^[n.succ - k] p * derivative^[k] q) := by
rw [sum_range_succ' _ n.succ, Nat.choose_zero_right, tsub_zero]
congr
refine (sum_range_succ' _ _).trans (congr_arg₂ (· + ·) ?_ ?_)
· rw [sum_range_succ, Nat.choose_succ_self, zero_smul, add_zero]
refine sum_congr rfl fun k hk => ?_
rw [mem_range] at hk
congr
omega
· rw [Nat.choose_zero_right, tsub_zero]
#align polynomial.iterate_derivative_mul Polynomial.iterate_derivative_mul
end Semiring
section CommSemiring
variable [CommSemiring R]
theorem derivative_pow_succ (p : R[X]) (n : ℕ) :
derivative (p ^ (n + 1)) = C (n + 1 : R) * p ^ n * derivative p :=
Nat.recOn n (by simp) fun n ih => by
rw [pow_succ, derivative_mul, ih, Nat.add_one, mul_right_comm, C_add,
add_mul, add_mul, pow_succ, ← mul_assoc, C_1, one_mul]; simp [add_mul]
#align polynomial.derivative_pow_succ Polynomial.derivative_pow_succ
theorem derivative_pow (p : R[X]) (n : ℕ) :
derivative (p ^ n) = C (n : R) * p ^ (n - 1) * derivative p :=
Nat.casesOn n (by rw [pow_zero, derivative_one, Nat.cast_zero, C_0, zero_mul, zero_mul]) fun n =>
by rw [p.derivative_pow_succ n, Nat.add_one_sub_one, n.cast_succ]
#align polynomial.derivative_pow Polynomial.derivative_pow
theorem derivative_sq (p : R[X]) : derivative (p ^ 2) = C 2 * p * derivative p := by
rw [derivative_pow_succ, Nat.cast_one, one_add_one_eq_two, pow_one]
#align polynomial.derivative_sq Polynomial.derivative_sq
theorem pow_sub_one_dvd_derivative_of_pow_dvd {p q : R[X]} {n : ℕ}
(dvd : q ^ n ∣ p) : q ^ (n - 1) ∣ derivative p := by
obtain ⟨r, rfl⟩ := dvd
rw [derivative_mul, derivative_pow]
exact (((dvd_mul_left _ _).mul_right _).mul_right _).add ((pow_dvd_pow q n.pred_le).mul_right _)
theorem pow_sub_dvd_iterate_derivative_of_pow_dvd {p q : R[X]} {n : ℕ} (m : ℕ)
(dvd : q ^ n ∣ p) : q ^ (n - m) ∣ derivative^[m] p := by
induction m generalizing p with
| zero => simpa
| succ m ih =>
rw [Nat.sub_succ, Function.iterate_succ']
exact pow_sub_one_dvd_derivative_of_pow_dvd (ih dvd)
theorem pow_sub_dvd_iterate_derivative_pow (p : R[X]) (n m : ℕ) :
p ^ (n - m) ∣ derivative^[m] (p ^ n) := pow_sub_dvd_iterate_derivative_of_pow_dvd m dvd_rfl
theorem dvd_iterate_derivative_pow (f : R[X]) (n : ℕ) {m : ℕ} (c : R) (hm : m ≠ 0) :
(n : R) ∣ eval c (derivative^[m] (f ^ n)) := by
obtain ⟨m, rfl⟩ := Nat.exists_eq_succ_of_ne_zero hm
rw [Function.iterate_succ_apply, derivative_pow, mul_assoc, C_eq_natCast,
iterate_derivative_natCast_mul, eval_mul, eval_natCast]
exact dvd_mul_right _ _
#align polynomial.dvd_iterate_derivative_pow Polynomial.dvd_iterate_derivative_pow
theorem iterate_derivative_X_pow_eq_natCast_mul (n k : ℕ) :
derivative^[k] (X ^ n : R[X]) = ↑(Nat.descFactorial n k : R[X]) * X ^ (n - k) := by
induction' k with k ih
· erw [Function.iterate_zero_apply, tsub_zero, Nat.descFactorial_zero, Nat.cast_one, one_mul]
· rw [Function.iterate_succ_apply', ih, derivative_natCast_mul, derivative_X_pow, C_eq_natCast,
Nat.descFactorial_succ, Nat.sub_sub, Nat.cast_mul];
simp [mul_comm, mul_assoc, mul_left_comm]
set_option linter.uppercaseLean3 false in
#align polynomial.iterate_derivative_X_pow_eq_nat_cast_mul Polynomial.iterate_derivative_X_pow_eq_natCast_mul
@[deprecated (since := "2024-04-17")]
alias iterate_derivative_X_pow_eq_nat_cast_mul := iterate_derivative_X_pow_eq_natCast_mul
theorem iterate_derivative_X_pow_eq_C_mul (n k : ℕ) :
derivative^[k] (X ^ n : R[X]) = C (Nat.descFactorial n k : R) * X ^ (n - k) := by
rw [iterate_derivative_X_pow_eq_natCast_mul n k, C_eq_natCast]
set_option linter.uppercaseLean3 false in
#align polynomial.iterate_derivative_X_pow_eq_C_mul Polynomial.iterate_derivative_X_pow_eq_C_mul
theorem iterate_derivative_X_pow_eq_smul (n : ℕ) (k : ℕ) :
derivative^[k] (X ^ n : R[X]) = (Nat.descFactorial n k : R) • X ^ (n - k) := by
rw [iterate_derivative_X_pow_eq_C_mul n k, smul_eq_C_mul]
set_option linter.uppercaseLean3 false in
#align polynomial.iterate_derivative_X_pow_eq_smul Polynomial.iterate_derivative_X_pow_eq_smul
theorem derivative_X_add_C_pow (c : R) (m : ℕ) :
derivative ((X + C c) ^ m) = C (m : R) * (X + C c) ^ (m - 1) := by
rw [derivative_pow, derivative_X_add_C, mul_one]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_X_add_C_pow Polynomial.derivative_X_add_C_pow
theorem derivative_X_add_C_sq (c : R) : derivative ((X + C c) ^ 2) = C 2 * (X + C c) := by
rw [derivative_sq, derivative_X_add_C, mul_one]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_X_add_C_sq Polynomial.derivative_X_add_C_sq
theorem iterate_derivative_X_add_pow (n k : ℕ) (c : R) :
derivative^[k] ((X + C c) ^ n) = Nat.descFactorial n k • (X + C c) ^ (n - k) := by
induction k with
| zero => simp
| succ k IH =>
rw [Nat.sub_succ', Function.iterate_succ_apply', IH, derivative_smul,
derivative_X_add_C_pow, map_natCast, Nat.descFactorial_succ, nsmul_eq_mul, nsmul_eq_mul,
Nat.cast_mul]
ring
set_option linter.uppercaseLean3 false in
#align polynomial.iterate_derivative_X_add_pow Polynomial.iterate_derivative_X_add_powₓ
theorem derivative_comp (p q : R[X]) :
derivative (p.comp q) = derivative q * p.derivative.comp q := by
induction p using Polynomial.induction_on'
· simp [*, mul_add]
· simp only [derivative_pow, derivative_mul, monomial_comp, derivative_monomial, derivative_C,
zero_mul, C_eq_natCast, zero_add, RingHom.map_mul]
ring
#align polynomial.derivative_comp Polynomial.derivative_comp
/-- Chain rule for formal derivative of polynomials. -/
theorem derivative_eval₂_C (p q : R[X]) :
derivative (p.eval₂ C q) = p.derivative.eval₂ C q * derivative q :=
Polynomial.induction_on p (fun r => by rw [eval₂_C, derivative_C, eval₂_zero, zero_mul])
(fun p₁ p₂ ih₁ ih₂ => by
rw [eval₂_add, derivative_add, ih₁, ih₂, derivative_add, eval₂_add, add_mul])
fun n r ih => by
rw [pow_succ, ← mul_assoc, eval₂_mul, eval₂_X, derivative_mul, ih, @derivative_mul _ _ _ X,
derivative_X, mul_one, eval₂_add, @eval₂_mul _ _ _ _ X, eval₂_X, add_mul, mul_right_comm]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_eval₂_C Polynomial.derivative_eval₂_C
theorem derivative_prod [DecidableEq ι] {s : Multiset ι} {f : ι → R[X]} :
derivative (Multiset.map f s).prod =
(Multiset.map (fun i => (Multiset.map f (s.erase i)).prod * derivative (f i)) s).sum := by
refine Multiset.induction_on s (by simp) fun i s h => ?_
rw [Multiset.map_cons, Multiset.prod_cons, derivative_mul, Multiset.map_cons _ i s,
Multiset.sum_cons, Multiset.erase_cons_head, mul_comm (derivative (f i))]
congr
rw [h, ← AddMonoidHom.coe_mulLeft, (AddMonoidHom.mulLeft (f i)).map_multiset_sum _,
AddMonoidHom.coe_mulLeft]
simp only [Function.comp_apply, Multiset.map_map]
refine congr_arg _ (Multiset.map_congr rfl fun j hj => ?_)
rw [← mul_assoc, ← Multiset.prod_cons, ← Multiset.map_cons]
by_cases hij : i = j
· simp [hij, ← Multiset.prod_cons, ← Multiset.map_cons, Multiset.cons_erase hj]
· simp [hij]
#align polynomial.derivative_prod Polynomial.derivative_prod
end CommSemiring
section Ring
variable [Ring R]
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_neg (f : R[X]) : derivative (-f) = -derivative f :=
LinearMap.map_neg derivative f
#align polynomial.derivative_neg Polynomial.derivative_neg
theorem iterate_derivative_neg {f : R[X]} {k : ℕ} : derivative^[k] (-f) = -derivative^[k] f :=
iterate_map_neg derivative k f
#align polynomial.iterate_derivative_neg Polynomial.iterate_derivative_neg
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_sub {f g : R[X]} : derivative (f - g) = derivative f - derivative g :=
LinearMap.map_sub derivative f g
#align polynomial.derivative_sub Polynomial.derivative_sub
-- Porting note (#10618): removed `simp`: `simp` can prove it.
theorem derivative_X_sub_C (c : R) : derivative (X - C c) = 1 := by
rw [derivative_sub, derivative_X, derivative_C, sub_zero]
set_option linter.uppercaseLean3 false in
#align polynomial.derivative_X_sub_C Polynomial.derivative_X_sub_C
theorem iterate_derivative_sub {k : ℕ} {f g : R[X]} :
derivative^[k] (f - g) = derivative^[k] f - derivative^[k] g :=
iterate_map_sub derivative k f g
#align polynomial.iterate_derivative_sub Polynomial.iterate_derivative_sub
@[simp]
| Mathlib/Algebra/Polynomial/Derivative.lean | 604 | 606 | theorem derivative_intCast {n : ℤ} : derivative (n : R[X]) = 0 := by |
rw [← C_eq_intCast n]
exact derivative_C
|
/-
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]
| Mathlib/Order/SymmDiff.lean | 347 | 347 | theorem top_symmDiff' : ⊤ ∆ a = ￢a := by | simp [symmDiff]
|
/-
Copyright (c) 2020 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel, Sophie Morel, Yury Kudryashov
-/
import Mathlib.Analysis.NormedSpace.OperatorNorm.NormedSpace
import Mathlib.Logic.Embedding.Basic
import Mathlib.Data.Fintype.CardEmbedding
import Mathlib.Topology.Algebra.Module.Multilinear.Topology
#align_import analysis.normed_space.multilinear from "leanprover-community/mathlib"@"f40476639bac089693a489c9e354ebd75dc0f886"
/-!
# Operator norm on the space of continuous multilinear maps
When `f` is a continuous multilinear map in finitely many variables, we define its norm `‖f‖` as the
smallest number such that `‖f m‖ ≤ ‖f‖ * ∏ i, ‖m i‖` for all `m`.
We show that it is indeed a norm, and prove its basic properties.
## Main results
Let `f` be a multilinear map in finitely many variables.
* `exists_bound_of_continuous` asserts that, if `f` is continuous, then there exists `C > 0`
with `‖f m‖ ≤ C * ∏ i, ‖m i‖` for all `m`.
* `continuous_of_bound`, conversely, asserts that this bound implies continuity.
* `mkContinuous` constructs the associated continuous multilinear map.
Let `f` be a continuous multilinear map in finitely many variables.
* `‖f‖` is its norm, i.e., the smallest number such that `‖f m‖ ≤ ‖f‖ * ∏ i, ‖m i‖` for
all `m`.
* `le_opNorm f m` asserts the fundamental inequality `‖f m‖ ≤ ‖f‖ * ∏ i, ‖m i‖`.
* `norm_image_sub_le f m₁ m₂` gives a control of the difference `f m₁ - f m₂` in terms of
`‖f‖` and `‖m₁ - m₂‖`.
## Implementation notes
We mostly follow the API (and the proofs) of `OperatorNorm.lean`, with the additional complexity
that we should deal with multilinear maps in several variables. The currying/uncurrying
constructions are based on those in `Multilinear.lean`.
From the mathematical point of view, all the results follow from the results on operator norm in
one variable, by applying them to one variable after the other through currying. However, this
is only well defined when there is an order on the variables (for instance on `Fin n`) although
the final result is independent of the order. While everything could be done following this
approach, it turns out that direct proofs are easier and more efficient.
-/
suppress_compilation
noncomputable section
open scoped NNReal Topology Uniformity
open Finset Metric Function Filter
/-
Porting note: These lines are not required in Mathlib4.
```lean
attribute [local instance 1001]
AddCommGroup.toAddCommMonoid NormedAddCommGroup.toAddCommGroup NormedSpace.toModule'
```
-/
/-!
### Type variables
We use the following type variables in this file:
* `𝕜` : a `NontriviallyNormedField`;
* `ι`, `ι'` : finite index types with decidable equality;
* `E`, `E₁` : families of normed vector spaces over `𝕜` indexed by `i : ι`;
* `E'` : a family of normed vector spaces over `𝕜` indexed by `i' : ι'`;
* `Ei` : a family of normed vector spaces over `𝕜` indexed by `i : Fin (Nat.succ n)`;
* `G`, `G'` : normed vector spaces over `𝕜`.
-/
universe u v v' wE wE₁ wE' wG wG'
section Seminorm
variable {𝕜 : Type u} {ι : Type v} {ι' : Type v'} {E : ι → Type wE} {E₁ : ι → Type wE₁}
{E' : ι' → Type wE'} {G : Type wG} {G' : Type wG'} [Fintype ι]
[Fintype ι'] [NontriviallyNormedField 𝕜] [∀ i, SeminormedAddCommGroup (E i)]
[∀ i, NormedSpace 𝕜 (E i)] [∀ i, SeminormedAddCommGroup (E₁ i)] [∀ i, NormedSpace 𝕜 (E₁ i)]
[∀ i, SeminormedAddCommGroup (E' i)] [∀ i, NormedSpace 𝕜 (E' i)]
[SeminormedAddCommGroup G] [NormedSpace 𝕜 G] [SeminormedAddCommGroup G'] [NormedSpace 𝕜 G']
/-!
### Continuity properties of multilinear maps
We relate continuity of multilinear maps to the inequality `‖f m‖ ≤ C * ∏ i, ‖m i‖`, in
both directions. Along the way, we prove useful bounds on the difference `‖f m₁ - f m₂‖`.
-/
namespace MultilinearMap
variable (f : MultilinearMap 𝕜 E G)
/-- If `f` is a continuous multilinear map in finitely many variables on `E` and `m` is an element
of `∀ i, E i` such that one of the `m i` has norm `0`, then `f m` has norm `0`.
Note that we cannot drop the continuity assumption because `f (m : Unit → E) = f (m ())`,
where the domain has zero norm and the codomain has a nonzero norm
does not satisfy this condition. -/
lemma norm_map_coord_zero (hf : Continuous f) {m : ∀ i, E i} {i : ι} (hi : ‖m i‖ = 0) :
‖f m‖ = 0 := by
classical
rw [← inseparable_zero_iff_norm] at hi ⊢
have : Inseparable (update m i 0) m := inseparable_pi.2 <|
(forall_update_iff m fun i a ↦ Inseparable a (m i)).2 ⟨hi.symm, fun _ _ ↦ rfl⟩
simpa only [map_update_zero] using this.symm.map hf
theorem bound_of_shell_of_norm_map_coord_zero (hf₀ : ∀ {m i}, ‖m i‖ = 0 → ‖f m‖ = 0)
{ε : ι → ℝ} {C : ℝ} (hε : ∀ i, 0 < ε i) {c : ι → 𝕜} (hc : ∀ i, 1 < ‖c i‖)
(hf : ∀ m : ∀ i, E i, (∀ i, ε i / ‖c i‖ ≤ ‖m i‖) → (∀ i, ‖m i‖ < ε i) → ‖f m‖ ≤ C * ∏ i, ‖m i‖)
(m : ∀ i, E i) : ‖f m‖ ≤ C * ∏ i, ‖m i‖ := by
rcases em (∃ i, ‖m i‖ = 0) with (⟨i, hi⟩ | hm)
· rw [hf₀ hi, prod_eq_zero (mem_univ i) hi, mul_zero]
push_neg at hm
choose δ hδ0 hδm_lt hle_δm _ using fun i => rescale_to_shell_semi_normed (hc i) (hε i) (hm i)
have hδ0 : 0 < ∏ i, ‖δ i‖ := prod_pos fun i _ => norm_pos_iff.2 (hδ0 i)
simpa [map_smul_univ, norm_smul, prod_mul_distrib, mul_left_comm C, mul_le_mul_left hδ0] using
hf (fun i => δ i • m i) hle_δm hδm_lt
/-- If a continuous multilinear map in finitely many variables on normed spaces satisfies
the inequality `‖f m‖ ≤ C * ∏ i, ‖m i‖` on a shell `ε i / ‖c i‖ < ‖m i‖ < ε i` for some positive
numbers `ε i` and elements `c i : 𝕜`, `1 < ‖c i‖`, then it satisfies this inequality for all `m`. -/
theorem bound_of_shell_of_continuous (hfc : Continuous f)
{ε : ι → ℝ} {C : ℝ} (hε : ∀ i, 0 < ε i) {c : ι → 𝕜} (hc : ∀ i, 1 < ‖c i‖)
(hf : ∀ m : ∀ i, E i, (∀ i, ε i / ‖c i‖ ≤ ‖m i‖) → (∀ i, ‖m i‖ < ε i) → ‖f m‖ ≤ C * ∏ i, ‖m i‖)
(m : ∀ i, E i) : ‖f m‖ ≤ C * ∏ i, ‖m i‖ :=
bound_of_shell_of_norm_map_coord_zero f (norm_map_coord_zero f hfc) hε hc hf m
/-- If a multilinear map in finitely many variables on normed spaces is continuous, then it
satisfies the inequality `‖f m‖ ≤ C * ∏ i, ‖m i‖`, for some `C` which can be chosen to be
positive. -/
theorem exists_bound_of_continuous (hf : Continuous f) :
∃ C : ℝ, 0 < C ∧ ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖ := by
cases isEmpty_or_nonempty ι
· refine ⟨‖f 0‖ + 1, add_pos_of_nonneg_of_pos (norm_nonneg _) zero_lt_one, fun m => ?_⟩
obtain rfl : m = 0 := funext (IsEmpty.elim ‹_›)
simp [univ_eq_empty, zero_le_one]
obtain ⟨ε : ℝ, ε0 : 0 < ε, hε : ∀ m : ∀ i, E i, ‖m - 0‖ < ε → ‖f m - f 0‖ < 1⟩ :=
NormedAddCommGroup.tendsto_nhds_nhds.1 (hf.tendsto 0) 1 zero_lt_one
simp only [sub_zero, f.map_zero] at hε
rcases NormedField.exists_one_lt_norm 𝕜 with ⟨c, hc⟩
have : 0 < (‖c‖ / ε) ^ Fintype.card ι := pow_pos (div_pos (zero_lt_one.trans hc) ε0) _
refine ⟨_, this, ?_⟩
refine f.bound_of_shell_of_continuous hf (fun _ => ε0) (fun _ => hc) fun m hcm hm => ?_
refine (hε m ((pi_norm_lt_iff ε0).2 hm)).le.trans ?_
rw [← div_le_iff' this, one_div, ← inv_pow, inv_div, Fintype.card, ← prod_const]
exact prod_le_prod (fun _ _ => div_nonneg ε0.le (norm_nonneg _)) fun i _ => hcm i
#align multilinear_map.exists_bound_of_continuous MultilinearMap.exists_bound_of_continuous
/-- If `f` satisfies a boundedness property around `0`, one can deduce a bound on `f m₁ - f m₂`
using the multilinearity. Here, we give a precise but hard to use version. See
`norm_image_sub_le_of_bound` for a less precise but more usable version. The bound reads
`‖f m - f m'‖ ≤
C * ‖m 1 - m' 1‖ * max ‖m 2‖ ‖m' 2‖ * max ‖m 3‖ ‖m' 3‖ * ... * max ‖m n‖ ‖m' n‖ + ...`,
where the other terms in the sum are the same products where `1` is replaced by any `i`. -/
theorem norm_image_sub_le_of_bound' [DecidableEq ι] {C : ℝ} (hC : 0 ≤ C)
(H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖) (m₁ m₂ : ∀ i, E i) :
‖f m₁ - f m₂‖ ≤ C * ∑ i, ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ := by
have A :
∀ s : Finset ι,
‖f m₁ - f (s.piecewise m₂ m₁)‖ ≤
C * ∑ i ∈ s, ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ := by
intro s
induction' s using Finset.induction with i s his Hrec
· simp
have I :
‖f (s.piecewise m₂ m₁) - f ((insert i s).piecewise m₂ m₁)‖ ≤
C * ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ := by
have A : (insert i s).piecewise m₂ m₁ = Function.update (s.piecewise m₂ m₁) i (m₂ i) :=
s.piecewise_insert _ _ _
have B : s.piecewise m₂ m₁ = Function.update (s.piecewise m₂ m₁) i (m₁ i) := by
simp [eq_update_iff, his]
rw [B, A, ← f.map_sub]
apply le_trans (H _)
gcongr with j
· exact fun j _ => norm_nonneg _
by_cases h : j = i
· rw [h]
simp
· by_cases h' : j ∈ s <;> simp [h', h, le_refl]
calc
‖f m₁ - f ((insert i s).piecewise m₂ m₁)‖ ≤
‖f m₁ - f (s.piecewise m₂ m₁)‖ +
‖f (s.piecewise m₂ m₁) - f ((insert i s).piecewise m₂ m₁)‖ := by
rw [← dist_eq_norm, ← dist_eq_norm, ← dist_eq_norm]
exact dist_triangle _ _ _
_ ≤ (C * ∑ i ∈ s, ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖) +
C * ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ :=
(add_le_add Hrec I)
_ = C * ∑ i ∈ insert i s, ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ := by
simp [his, add_comm, left_distrib]
convert A univ
simp
#align multilinear_map.norm_image_sub_le_of_bound' MultilinearMap.norm_image_sub_le_of_bound'
/-- If `f` satisfies a boundedness property around `0`, one can deduce a bound on `f m₁ - f m₂`
using the multilinearity. Here, we give a usable but not very precise version. See
`norm_image_sub_le_of_bound'` for a more precise but less usable version. The bound is
`‖f m - f m'‖ ≤ C * card ι * ‖m - m'‖ * (max ‖m‖ ‖m'‖) ^ (card ι - 1)`. -/
theorem norm_image_sub_le_of_bound {C : ℝ} (hC : 0 ≤ C) (H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖)
(m₁ m₂ : ∀ i, E i) :
‖f m₁ - f m₂‖ ≤ C * Fintype.card ι * max ‖m₁‖ ‖m₂‖ ^ (Fintype.card ι - 1) * ‖m₁ - m₂‖ := by
classical
have A :
∀ i : ι,
∏ j, (if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖) ≤
‖m₁ - m₂‖ * max ‖m₁‖ ‖m₂‖ ^ (Fintype.card ι - 1) := by
intro i
calc
∏ j, (if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖) ≤
∏ j : ι, Function.update (fun _ => max ‖m₁‖ ‖m₂‖) i ‖m₁ - m₂‖ j := by
apply Finset.prod_le_prod
· intro j _
by_cases h : j = i <;> simp [h, norm_nonneg]
· intro j _
by_cases h : j = i
· rw [h]
simp only [ite_true, Function.update_same]
exact norm_le_pi_norm (m₁ - m₂) i
· simp [h, -le_max_iff, -max_le_iff, max_le_max, norm_le_pi_norm (_ : ∀ i, E i)]
_ = ‖m₁ - m₂‖ * max ‖m₁‖ ‖m₂‖ ^ (Fintype.card ι - 1) := by
rw [prod_update_of_mem (Finset.mem_univ _)]
simp [card_univ_diff]
calc
‖f m₁ - f m₂‖ ≤ C * ∑ i, ∏ j, if j = i then ‖m₁ i - m₂ i‖ else max ‖m₁ j‖ ‖m₂ j‖ :=
f.norm_image_sub_le_of_bound' hC H m₁ m₂
_ ≤ C * ∑ _i, ‖m₁ - m₂‖ * max ‖m₁‖ ‖m₂‖ ^ (Fintype.card ι - 1) := by gcongr; apply A
_ = C * Fintype.card ι * max ‖m₁‖ ‖m₂‖ ^ (Fintype.card ι - 1) * ‖m₁ - m₂‖ := by
rw [sum_const, card_univ, nsmul_eq_mul]
ring
#align multilinear_map.norm_image_sub_le_of_bound MultilinearMap.norm_image_sub_le_of_bound
/-- If a multilinear map satisfies an inequality `‖f m‖ ≤ C * ∏ i, ‖m i‖`, then it is
continuous. -/
theorem continuous_of_bound (C : ℝ) (H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖) : Continuous f := by
let D := max C 1
have D_pos : 0 ≤ D := le_trans zero_le_one (le_max_right _ _)
replace H (m) : ‖f m‖ ≤ D * ∏ i, ‖m i‖ :=
(H m).trans (mul_le_mul_of_nonneg_right (le_max_left _ _) <| by positivity)
refine continuous_iff_continuousAt.2 fun m => ?_
refine
continuousAt_of_locally_lipschitz zero_lt_one
(D * Fintype.card ι * (‖m‖ + 1) ^ (Fintype.card ι - 1)) fun m' h' => ?_
rw [dist_eq_norm, dist_eq_norm]
have : max ‖m'‖ ‖m‖ ≤ ‖m‖ + 1 := by
simp [zero_le_one, norm_le_of_mem_closedBall (le_of_lt h')]
calc
‖f m' - f m‖ ≤ D * Fintype.card ι * max ‖m'‖ ‖m‖ ^ (Fintype.card ι - 1) * ‖m' - m‖ :=
f.norm_image_sub_le_of_bound D_pos H m' m
_ ≤ D * Fintype.card ι * (‖m‖ + 1) ^ (Fintype.card ι - 1) * ‖m' - m‖ := by gcongr
#align multilinear_map.continuous_of_bound MultilinearMap.continuous_of_bound
/-- Constructing a continuous multilinear map from a multilinear map satisfying a boundedness
condition. -/
def mkContinuous (C : ℝ) (H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖) : ContinuousMultilinearMap 𝕜 E G :=
{ f with cont := f.continuous_of_bound C H }
#align multilinear_map.mk_continuous MultilinearMap.mkContinuous
@[simp]
theorem coe_mkContinuous (C : ℝ) (H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖) : ⇑(f.mkContinuous C H) = f :=
rfl
#align multilinear_map.coe_mk_continuous MultilinearMap.coe_mkContinuous
/-- Given a multilinear map in `n` variables, if one restricts it to `k` variables putting `z` on
the other coordinates, then the resulting restricted function satisfies an inequality
`‖f.restr v‖ ≤ C * ‖z‖^(n-k) * Π ‖v i‖` if the original function satisfies `‖f v‖ ≤ C * Π ‖v i‖`. -/
theorem restr_norm_le {k n : ℕ} (f : (MultilinearMap 𝕜 (fun _ : Fin n => G) G' : _))
(s : Finset (Fin n)) (hk : s.card = k) (z : G) {C : ℝ} (H : ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖)
(v : Fin k → G) : ‖f.restr s hk z v‖ ≤ C * ‖z‖ ^ (n - k) * ∏ i, ‖v i‖ := by
rw [mul_right_comm, mul_assoc]
convert H _ using 2
simp only [apply_dite norm, Fintype.prod_dite, prod_const ‖z‖, Finset.card_univ,
Fintype.card_of_subtype sᶜ fun _ => mem_compl, card_compl, Fintype.card_fin, hk, mk_coe, ←
(s.orderIsoOfFin hk).symm.bijective.prod_comp fun x => ‖v x‖]
convert rfl
#align multilinear_map.restr_norm_le MultilinearMap.restr_norm_le
end MultilinearMap
/-!
### Continuous multilinear maps
We define the norm `‖f‖` of a continuous multilinear map `f` in finitely many variables as the
smallest number such that `‖f m‖ ≤ ‖f‖ * ∏ i, ‖m i‖` for all `m`. We show that this
defines a normed space structure on `ContinuousMultilinearMap 𝕜 E G`.
-/
namespace ContinuousMultilinearMap
variable (c : 𝕜) (f g : ContinuousMultilinearMap 𝕜 E G) (m : ∀ i, E i)
theorem bound : ∃ C : ℝ, 0 < C ∧ ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖ :=
f.toMultilinearMap.exists_bound_of_continuous f.2
#align continuous_multilinear_map.bound ContinuousMultilinearMap.bound
open Real
/-- The operator norm of a continuous multilinear map is the inf of all its bounds. -/
def opNorm :=
sInf { c | 0 ≤ (c : ℝ) ∧ ∀ m, ‖f m‖ ≤ c * ∏ i, ‖m i‖ }
#align continuous_multilinear_map.op_norm ContinuousMultilinearMap.opNorm
instance hasOpNorm : Norm (ContinuousMultilinearMap 𝕜 E G) :=
⟨opNorm⟩
#align continuous_multilinear_map.has_op_norm ContinuousMultilinearMap.hasOpNorm
/-- An alias of `ContinuousMultilinearMap.hasOpNorm` with non-dependent types to help typeclass
search. -/
instance hasOpNorm' : Norm (ContinuousMultilinearMap 𝕜 (fun _ : ι => G) G') :=
ContinuousMultilinearMap.hasOpNorm
#align continuous_multilinear_map.has_op_norm' ContinuousMultilinearMap.hasOpNorm'
theorem norm_def : ‖f‖ = sInf { c | 0 ≤ (c : ℝ) ∧ ∀ m, ‖f m‖ ≤ c * ∏ i, ‖m i‖ } :=
rfl
#align continuous_multilinear_map.norm_def ContinuousMultilinearMap.norm_def
-- So that invocations of `le_csInf` make sense: we show that the set of
-- bounds is nonempty and bounded below.
theorem bounds_nonempty {f : ContinuousMultilinearMap 𝕜 E G} :
∃ c, c ∈ { c | 0 ≤ c ∧ ∀ m, ‖f m‖ ≤ c * ∏ i, ‖m i‖ } :=
let ⟨M, hMp, hMb⟩ := f.bound
⟨M, le_of_lt hMp, hMb⟩
#align continuous_multilinear_map.bounds_nonempty ContinuousMultilinearMap.bounds_nonempty
theorem bounds_bddBelow {f : ContinuousMultilinearMap 𝕜 E G} :
BddBelow { c | 0 ≤ c ∧ ∀ m, ‖f m‖ ≤ c * ∏ i, ‖m i‖ } :=
⟨0, fun _ ⟨hn, _⟩ => hn⟩
#align continuous_multilinear_map.bounds_bdd_below ContinuousMultilinearMap.bounds_bddBelow
theorem isLeast_opNorm : IsLeast {c : ℝ | 0 ≤ c ∧ ∀ m, ‖f m‖ ≤ c * ∏ i, ‖m i‖} ‖f‖ := by
refine IsClosed.isLeast_csInf ?_ bounds_nonempty bounds_bddBelow
simp only [Set.setOf_and, Set.setOf_forall]
exact isClosed_Ici.inter (isClosed_iInter fun m ↦
isClosed_le continuous_const (continuous_id.mul continuous_const))
@[deprecated (since := "2024-02-02")] alias isLeast_op_norm := isLeast_opNorm
theorem opNorm_nonneg : 0 ≤ ‖f‖ :=
Real.sInf_nonneg _ fun _ ⟨hx, _⟩ => hx
#align continuous_multilinear_map.op_norm_nonneg ContinuousMultilinearMap.opNorm_nonneg
@[deprecated (since := "2024-02-02")] alias op_norm_nonneg := opNorm_nonneg
/-- The fundamental property of the operator norm of a continuous multilinear map:
`‖f m‖` is bounded by `‖f‖` times the product of the `‖m i‖`. -/
theorem le_opNorm : ‖f m‖ ≤ ‖f‖ * ∏ i, ‖m i‖ := f.isLeast_opNorm.1.2 m
#align continuous_multilinear_map.le_op_norm ContinuousMultilinearMap.le_opNorm
@[deprecated (since := "2024-02-02")] alias le_op_norm := le_opNorm
variable {f m}
theorem le_mul_prod_of_le_opNorm_of_le {C : ℝ} {b : ι → ℝ} (hC : ‖f‖ ≤ C) (hm : ∀ i, ‖m i‖ ≤ b i) :
‖f m‖ ≤ C * ∏ i, b i :=
(f.le_opNorm m).trans <| mul_le_mul hC (prod_le_prod (fun _ _ ↦ norm_nonneg _) fun _ _ ↦ hm _)
(by positivity) ((opNorm_nonneg _).trans hC)
@[deprecated (since := "2024-02-02")]
alias le_mul_prod_of_le_op_norm_of_le := le_mul_prod_of_le_opNorm_of_le
variable (f)
theorem le_opNorm_mul_prod_of_le {b : ι → ℝ} (hm : ∀ i, ‖m i‖ ≤ b i) : ‖f m‖ ≤ ‖f‖ * ∏ i, b i :=
le_mul_prod_of_le_opNorm_of_le le_rfl hm
#align continuous_multilinear_map.le_op_norm_mul_prod_of_le ContinuousMultilinearMap.le_opNorm_mul_prod_of_le
@[deprecated (since := "2024-02-02")] alias le_op_norm_mul_prod_of_le := le_opNorm_mul_prod_of_le
theorem le_opNorm_mul_pow_card_of_le {b : ℝ} (hm : ‖m‖ ≤ b) :
‖f m‖ ≤ ‖f‖ * b ^ Fintype.card ι := by
simpa only [prod_const] using f.le_opNorm_mul_prod_of_le fun i => (norm_le_pi_norm m i).trans hm
#align continuous_multilinear_map.le_op_norm_mul_pow_card_of_le ContinuousMultilinearMap.le_opNorm_mul_pow_card_of_le
@[deprecated (since := "2024-02-02")]
alias le_op_norm_mul_pow_card_of_le := le_opNorm_mul_pow_card_of_le
theorem le_opNorm_mul_pow_of_le {n : ℕ} {Ei : Fin n → Type*} [∀ i, SeminormedAddCommGroup (Ei i)]
[∀ i, NormedSpace 𝕜 (Ei i)] (f : ContinuousMultilinearMap 𝕜 Ei G) {m : ∀ i, Ei i} {b : ℝ}
(hm : ‖m‖ ≤ b) : ‖f m‖ ≤ ‖f‖ * b ^ n := by
simpa only [Fintype.card_fin] using f.le_opNorm_mul_pow_card_of_le hm
#align continuous_multilinear_map.le_op_norm_mul_pow_of_le ContinuousMultilinearMap.le_opNorm_mul_pow_of_le
@[deprecated (since := "2024-02-02")] alias le_op_norm_mul_pow_of_le := le_opNorm_mul_pow_of_le
variable {f} (m)
theorem le_of_opNorm_le {C : ℝ} (h : ‖f‖ ≤ C) : ‖f m‖ ≤ C * ∏ i, ‖m i‖ :=
le_mul_prod_of_le_opNorm_of_le h fun _ ↦ le_rfl
#align continuous_multilinear_map.le_of_op_norm_le ContinuousMultilinearMap.le_of_opNorm_le
@[deprecated (since := "2024-02-02")] alias le_of_op_norm_le := le_of_opNorm_le
variable (f)
theorem ratio_le_opNorm : (‖f m‖ / ∏ i, ‖m i‖) ≤ ‖f‖ :=
div_le_of_nonneg_of_le_mul (by positivity) (opNorm_nonneg _) (f.le_opNorm m)
#align continuous_multilinear_map.ratio_le_op_norm ContinuousMultilinearMap.ratio_le_opNorm
@[deprecated (since := "2024-02-02")] alias ratio_le_op_norm := ratio_le_opNorm
/-- The image of the unit ball under a continuous multilinear map is bounded. -/
theorem unit_le_opNorm (h : ‖m‖ ≤ 1) : ‖f m‖ ≤ ‖f‖ :=
(le_opNorm_mul_pow_card_of_le f h).trans <| by simp
#align continuous_multilinear_map.unit_le_op_norm ContinuousMultilinearMap.unit_le_opNorm
@[deprecated (since := "2024-02-02")] alias unit_le_op_norm := unit_le_opNorm
/-- If one controls the norm of every `f x`, then one controls the norm of `f`. -/
theorem opNorm_le_bound {M : ℝ} (hMp : 0 ≤ M) (hM : ∀ m, ‖f m‖ ≤ M * ∏ i, ‖m i‖) : ‖f‖ ≤ M :=
csInf_le bounds_bddBelow ⟨hMp, hM⟩
#align continuous_multilinear_map.op_norm_le_bound ContinuousMultilinearMap.opNorm_le_bound
@[deprecated (since := "2024-02-02")] alias op_norm_le_bound := opNorm_le_bound
theorem opNorm_le_iff {C : ℝ} (hC : 0 ≤ C) : ‖f‖ ≤ C ↔ ∀ m, ‖f m‖ ≤ C * ∏ i, ‖m i‖ :=
⟨fun h _ ↦ le_of_opNorm_le _ h, opNorm_le_bound _ hC⟩
@[deprecated (since := "2024-02-02")] alias op_norm_le_iff := opNorm_le_iff
/-- The operator norm satisfies the triangle inequality. -/
theorem opNorm_add_le : ‖f + g‖ ≤ ‖f‖ + ‖g‖ :=
opNorm_le_bound _ (add_nonneg (opNorm_nonneg _) (opNorm_nonneg _)) fun x => by
rw [add_mul]
exact norm_add_le_of_le (le_opNorm _ _) (le_opNorm _ _)
#align continuous_multilinear_map.op_norm_add_le ContinuousMultilinearMap.opNorm_add_le
@[deprecated (since := "2024-02-02")] alias op_norm_add_le := opNorm_add_le
theorem opNorm_zero : ‖(0 : ContinuousMultilinearMap 𝕜 E G)‖ = 0 :=
(opNorm_nonneg _).antisymm' <| opNorm_le_bound 0 le_rfl fun m => by simp
#align continuous_multilinear_map.op_norm_zero ContinuousMultilinearMap.opNorm_zero
@[deprecated (since := "2024-02-02")] alias op_norm_zero := opNorm_zero
section
variable {𝕜' : Type*} [NormedField 𝕜'] [NormedSpace 𝕜' G] [SMulCommClass 𝕜 𝕜' G]
theorem opNorm_smul_le (c : 𝕜') : ‖c • f‖ ≤ ‖c‖ * ‖f‖ :=
(c • f).opNorm_le_bound (mul_nonneg (norm_nonneg _) (opNorm_nonneg _)) fun m ↦ by
rw [smul_apply, norm_smul, mul_assoc]
exact mul_le_mul_of_nonneg_left (le_opNorm _ _) (norm_nonneg _)
#align continuous_multilinear_map.op_norm_smul_le ContinuousMultilinearMap.opNorm_smul_le
@[deprecated (since := "2024-02-02")] alias op_norm_smul_le := opNorm_smul_le
theorem opNorm_neg : ‖-f‖ = ‖f‖ := by
rw [norm_def]
apply congr_arg
ext
simp
#align continuous_multilinear_map.op_norm_neg ContinuousMultilinearMap.opNorm_neg
@[deprecated (since := "2024-02-02")] alias op_norm_neg := opNorm_neg
variable (𝕜 E G) in
/-- Operator seminorm on the space of continuous multilinear maps, as `Seminorm`.
We use this seminorm
to define a `SeminormedAddCommGroup` structure on `ContinuousMultilinearMap 𝕜 E G`,
but we have to override the projection `UniformSpace`
so that it is definitionally equal to the one coming from the topologies on `E` and `G`. -/
protected def seminorm : Seminorm 𝕜 (ContinuousMultilinearMap 𝕜 E G) :=
.ofSMulLE norm opNorm_zero opNorm_add_le fun c f ↦ opNorm_smul_le f c
private lemma uniformity_eq_seminorm :
𝓤 (ContinuousMultilinearMap 𝕜 E G) = ⨅ r > 0, 𝓟 {f | ‖f.1 - f.2‖ < r} := by
refine (ContinuousMultilinearMap.seminorm 𝕜 E G).uniformity_eq_of_hasBasis
(ContinuousMultilinearMap.hasBasis_nhds_zero_of_basis Metric.nhds_basis_closedBall)
?_ fun (s, r) ⟨hs, hr⟩ ↦ ?_
· rcases NormedField.exists_lt_norm 𝕜 1 with ⟨c, hc⟩
have hc₀ : 0 < ‖c‖ := one_pos.trans hc
simp only [hasBasis_nhds_zero.mem_iff, Prod.exists]
use 1, closedBall 0 ‖c‖, closedBall 0 1
suffices ∀ f : ContinuousMultilinearMap 𝕜 E G, (∀ x, ‖x‖ ≤ ‖c‖ → ‖f x‖ ≤ 1) → ‖f‖ ≤ 1 by
simpa [NormedSpace.isVonNBounded_closedBall, closedBall_mem_nhds, Set.subset_def, Set.MapsTo]
intro f hf
refine opNorm_le_bound _ (by positivity) <|
f.1.bound_of_shell_of_continuous f.2 (fun _ ↦ hc₀) (fun _ ↦ hc) fun x hcx hx ↦ ?_
calc
‖f x‖ ≤ 1 := hf _ <| (pi_norm_le_iff_of_nonneg (norm_nonneg c)).2 fun i ↦ (hx i).le
_ = ∏ i : ι, 1 := by simp
_ ≤ ∏ i, ‖x i‖ := Finset.prod_le_prod (fun _ _ ↦ zero_le_one) fun i _ ↦ by
simpa only [div_self hc₀.ne'] using hcx i
_ = 1 * ∏ i, ‖x i‖ := (one_mul _).symm
· rcases (NormedSpace.isVonNBounded_iff' _).1 hs with ⟨ε, hε⟩
rcases exists_pos_mul_lt hr (ε ^ Fintype.card ι) with ⟨δ, hδ₀, hδ⟩
refine ⟨δ, hδ₀, fun f hf x hx ↦ ?_⟩
simp only [Seminorm.mem_ball_zero, mem_closedBall_zero_iff] at hf ⊢
replace hf : ‖f‖ ≤ δ := hf.le
replace hx : ‖x‖ ≤ ε := hε x hx
calc
‖f x‖ ≤ ‖f‖ * ε ^ Fintype.card ι := le_opNorm_mul_pow_card_of_le f hx
_ ≤ δ * ε ^ Fintype.card ι := by have := (norm_nonneg x).trans hx; gcongr
_ ≤ r := (mul_comm _ _).trans_le hδ.le
instance instPseudoMetricSpace : PseudoMetricSpace (ContinuousMultilinearMap 𝕜 E G) :=
.replaceUniformity
(ContinuousMultilinearMap.seminorm 𝕜 E G).toSeminormedAddCommGroup.toPseudoMetricSpace
uniformity_eq_seminorm
/-- Continuous multilinear maps themselves form a seminormed space with respect to
the operator norm. -/
instance seminormedAddCommGroup :
SeminormedAddCommGroup (ContinuousMultilinearMap 𝕜 E G) := ⟨fun _ _ ↦ rfl⟩
/-- An alias of `ContinuousMultilinearMap.seminormedAddCommGroup` with non-dependent types to help
typeclass search. -/
instance seminormedAddCommGroup' :
SeminormedAddCommGroup (ContinuousMultilinearMap 𝕜 (fun _ : ι => G) G') :=
ContinuousMultilinearMap.seminormedAddCommGroup
instance normedSpace : NormedSpace 𝕜' (ContinuousMultilinearMap 𝕜 E G) :=
⟨fun c f => f.opNorm_smul_le c⟩
#align continuous_multilinear_map.normed_space ContinuousMultilinearMap.normedSpace
/-- An alias of `ContinuousMultilinearMap.normedSpace` with non-dependent types to help typeclass
search. -/
instance normedSpace' : NormedSpace 𝕜' (ContinuousMultilinearMap 𝕜 (fun _ : ι => G') G) :=
ContinuousMultilinearMap.normedSpace
#align continuous_multilinear_map.normed_space' ContinuousMultilinearMap.normedSpace'
/-- The fundamental property of the operator norm of a continuous multilinear map:
`‖f m‖` is bounded by `‖f‖` times the product of the `‖m i‖`, `nnnorm` version. -/
theorem le_opNNNorm : ‖f m‖₊ ≤ ‖f‖₊ * ∏ i, ‖m i‖₊ :=
NNReal.coe_le_coe.1 <| by
push_cast
exact f.le_opNorm m
#align continuous_multilinear_map.le_op_nnnorm ContinuousMultilinearMap.le_opNNNorm
@[deprecated (since := "2024-02-02")] alias le_op_nnnorm := le_opNNNorm
theorem le_of_opNNNorm_le {C : ℝ≥0} (h : ‖f‖₊ ≤ C) : ‖f m‖₊ ≤ C * ∏ i, ‖m i‖₊ :=
(f.le_opNNNorm m).trans <| mul_le_mul' h le_rfl
#align continuous_multilinear_map.le_of_op_nnnorm_le ContinuousMultilinearMap.le_of_opNNNorm_le
@[deprecated (since := "2024-02-02")] alias le_of_op_nnnorm_le := le_of_opNNNorm_le
theorem opNNNorm_le_iff {C : ℝ≥0} : ‖f‖₊ ≤ C ↔ ∀ m, ‖f m‖₊ ≤ C * ∏ i, ‖m i‖₊ := by
simp only [← NNReal.coe_le_coe]; simp [opNorm_le_iff _ C.coe_nonneg, NNReal.coe_prod]
@[deprecated (since := "2024-02-02")] alias op_nnnorm_le_iff := opNNNorm_le_iff
| Mathlib/Analysis/NormedSpace/Multilinear/Basic.lean | 550 | 551 | theorem isLeast_opNNNorm : IsLeast {C : ℝ≥0 | ∀ m, ‖f m‖₊ ≤ C * ∏ i, ‖m i‖₊} ‖f‖₊ := by |
simpa only [← opNNNorm_le_iff] using isLeast_Ici
|
/-
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.MFDeriv.Defs
#align_import geometry.manifold.mfderiv from "leanprover-community/mathlib"@"e473c3198bb41f68560cab68a0529c854b618833"
/-!
# Basic properties of the manifold Fréchet derivative
In this file, we show various properties of the manifold Fréchet derivative,
mimicking the API for Fréchet derivatives.
- basic properties of unique differentiability sets
- various general lemmas about the manifold Fréchet derivative
- deducing differentiability from smoothness,
- deriving continuity from differentiability on manifolds,
- congruence lemmas for derivatives on manifolds
- composition lemmas and the chain rule
-/
noncomputable section
open scoped Topology Manifold
open Set Bundle
section DerivativesProperties
/-! ### Unique differentiability sets in manifolds -/
variable
{𝕜 : Type*} [NontriviallyNormedField 𝕜]
{E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
{H : Type*} [TopologicalSpace H] (I : ModelWithCorners 𝕜 E H)
{M : Type*} [TopologicalSpace M] [ChartedSpace H M]
{E' : Type*} [NormedAddCommGroup E'] [NormedSpace 𝕜 E']
{H' : Type*} [TopologicalSpace H'] {I' : ModelWithCorners 𝕜 E' H'}
{M' : Type*} [TopologicalSpace M'] [ChartedSpace H' M']
{E'' : Type*} [NormedAddCommGroup E''] [NormedSpace 𝕜 E'']
{H'' : Type*} [TopologicalSpace H''] {I'' : ModelWithCorners 𝕜 E'' H''}
{M'' : Type*} [TopologicalSpace M''] [ChartedSpace H'' M'']
{f f₀ f₁ : M → M'} {x : M} {s t : Set M} {g : M' → M''} {u : Set M'}
theorem uniqueMDiffWithinAt_univ : UniqueMDiffWithinAt I univ x := by
unfold UniqueMDiffWithinAt
simp only [preimage_univ, univ_inter]
exact I.unique_diff _ (mem_range_self _)
#align unique_mdiff_within_at_univ uniqueMDiffWithinAt_univ
variable {I}
theorem uniqueMDiffWithinAt_iff {s : Set M} {x : M} :
UniqueMDiffWithinAt I s x ↔
UniqueDiffWithinAt 𝕜 ((extChartAt I x).symm ⁻¹' s ∩ (extChartAt I x).target)
((extChartAt I x) x) := by
apply uniqueDiffWithinAt_congr
rw [nhdsWithin_inter, nhdsWithin_inter, nhdsWithin_extChartAt_target_eq]
#align unique_mdiff_within_at_iff uniqueMDiffWithinAt_iff
nonrec theorem UniqueMDiffWithinAt.mono_nhds {s t : Set M} {x : M} (hs : UniqueMDiffWithinAt I s x)
(ht : 𝓝[s] x ≤ 𝓝[t] x) : UniqueMDiffWithinAt I t x :=
hs.mono_nhds <| by simpa only [← map_extChartAt_nhdsWithin] using Filter.map_mono ht
theorem UniqueMDiffWithinAt.mono_of_mem {s t : Set M} {x : M} (hs : UniqueMDiffWithinAt I s x)
(ht : t ∈ 𝓝[s] x) : UniqueMDiffWithinAt I t x :=
hs.mono_nhds (nhdsWithin_le_iff.2 ht)
theorem UniqueMDiffWithinAt.mono (h : UniqueMDiffWithinAt I s x) (st : s ⊆ t) :
UniqueMDiffWithinAt I t x :=
UniqueDiffWithinAt.mono h <| inter_subset_inter (preimage_mono st) (Subset.refl _)
#align unique_mdiff_within_at.mono UniqueMDiffWithinAt.mono
theorem UniqueMDiffWithinAt.inter' (hs : UniqueMDiffWithinAt I s x) (ht : t ∈ 𝓝[s] x) :
UniqueMDiffWithinAt I (s ∩ t) x :=
hs.mono_of_mem (Filter.inter_mem self_mem_nhdsWithin ht)
#align unique_mdiff_within_at.inter' UniqueMDiffWithinAt.inter'
theorem UniqueMDiffWithinAt.inter (hs : UniqueMDiffWithinAt I s x) (ht : t ∈ 𝓝 x) :
UniqueMDiffWithinAt I (s ∩ t) x :=
hs.inter' (nhdsWithin_le_nhds ht)
#align unique_mdiff_within_at.inter UniqueMDiffWithinAt.inter
theorem IsOpen.uniqueMDiffWithinAt (hs : IsOpen s) (xs : x ∈ s) : UniqueMDiffWithinAt I s x :=
(uniqueMDiffWithinAt_univ I).mono_of_mem <| nhdsWithin_le_nhds <| hs.mem_nhds xs
#align is_open.unique_mdiff_within_at IsOpen.uniqueMDiffWithinAt
theorem UniqueMDiffOn.inter (hs : UniqueMDiffOn I s) (ht : IsOpen t) : UniqueMDiffOn I (s ∩ t) :=
fun _x hx => UniqueMDiffWithinAt.inter (hs _ hx.1) (ht.mem_nhds hx.2)
#align unique_mdiff_on.inter UniqueMDiffOn.inter
theorem IsOpen.uniqueMDiffOn (hs : IsOpen s) : UniqueMDiffOn I s :=
fun _x hx => hs.uniqueMDiffWithinAt hx
#align is_open.unique_mdiff_on IsOpen.uniqueMDiffOn
theorem uniqueMDiffOn_univ : UniqueMDiffOn I (univ : Set M) :=
isOpen_univ.uniqueMDiffOn
#align unique_mdiff_on_univ uniqueMDiffOn_univ
/- We name the typeclass variables related to `SmoothManifoldWithCorners` structure as they are
necessary in lemmas mentioning the derivative, but not in lemmas about differentiability, so we
want to include them or omit them when necessary. -/
variable [Is : SmoothManifoldWithCorners I M] [I's : SmoothManifoldWithCorners I' M']
[I''s : SmoothManifoldWithCorners I'' M'']
{f' f₀' f₁' : TangentSpace I x →L[𝕜] TangentSpace I' (f x)}
{g' : TangentSpace I' (f x) →L[𝕜] TangentSpace I'' (g (f x))}
/-- `UniqueMDiffWithinAt` achieves its goal: it implies the uniqueness of the derivative. -/
nonrec theorem UniqueMDiffWithinAt.eq (U : UniqueMDiffWithinAt I s x)
(h : HasMFDerivWithinAt I I' f s x f') (h₁ : HasMFDerivWithinAt I I' f s x f₁') : f' = f₁' := by
-- Porting note: didn't need `convert` because of finding instances by unification
convert U.eq h.2 h₁.2
#align unique_mdiff_within_at.eq UniqueMDiffWithinAt.eq
theorem UniqueMDiffOn.eq (U : UniqueMDiffOn I s) (hx : x ∈ s) (h : HasMFDerivWithinAt I I' f s x f')
(h₁ : HasMFDerivWithinAt I I' f s x f₁') : f' = f₁' :=
UniqueMDiffWithinAt.eq (U _ hx) h h₁
#align unique_mdiff_on.eq UniqueMDiffOn.eq
nonrec theorem UniqueMDiffWithinAt.prod {x : M} {y : M'} {s t} (hs : UniqueMDiffWithinAt I s x)
(ht : UniqueMDiffWithinAt I' t y) : UniqueMDiffWithinAt (I.prod I') (s ×ˢ t) (x, y) := by
refine (hs.prod ht).mono ?_
rw [ModelWithCorners.range_prod, ← prod_inter_prod]
rfl
theorem UniqueMDiffOn.prod {s : Set M} {t : Set M'} (hs : UniqueMDiffOn I s)
(ht : UniqueMDiffOn I' t) : UniqueMDiffOn (I.prod I') (s ×ˢ t) := fun x h ↦
(hs x.1 h.1).prod (ht x.2 h.2)
/-!
### General lemmas on derivatives of functions between manifolds
We mimick the API for functions between vector spaces
-/
theorem mdifferentiableWithinAt_iff {f : M → M'} {s : Set M} {x : M} :
MDifferentiableWithinAt I I' f s x ↔
ContinuousWithinAt f s x ∧
DifferentiableWithinAt 𝕜 (writtenInExtChartAt I I' x f)
((extChartAt I x).target ∩ (extChartAt I x).symm ⁻¹' s) ((extChartAt I x) x) := by
rw [mdifferentiableWithinAt_iff']
refine and_congr Iff.rfl (exists_congr fun f' => ?_)
rw [inter_comm]
simp only [HasFDerivWithinAt, nhdsWithin_inter, nhdsWithin_extChartAt_target_eq]
#align mdifferentiable_within_at_iff mdifferentiableWithinAt_iff
/-- One can reformulate differentiability within a set at a point as continuity within this set at
this point, and differentiability in any chart containing that point. -/
theorem mdifferentiableWithinAt_iff_of_mem_source {x' : M} {y : M'}
(hx : x' ∈ (chartAt H x).source) (hy : f x' ∈ (chartAt H' y).source) :
MDifferentiableWithinAt I I' f s x' ↔
ContinuousWithinAt f s x' ∧
DifferentiableWithinAt 𝕜 (extChartAt I' y ∘ f ∘ (extChartAt I x).symm)
((extChartAt I x).symm ⁻¹' s ∩ Set.range I) ((extChartAt I x) x') :=
(differentiable_within_at_localInvariantProp I I').liftPropWithinAt_indep_chart
(StructureGroupoid.chart_mem_maximalAtlas _ x) hx (StructureGroupoid.chart_mem_maximalAtlas _ y)
hy
#align mdifferentiable_within_at_iff_of_mem_source mdifferentiableWithinAt_iff_of_mem_source
theorem mfderivWithin_zero_of_not_mdifferentiableWithinAt
(h : ¬MDifferentiableWithinAt I I' f s x) : mfderivWithin I I' f s x = 0 := by
simp only [mfderivWithin, h, if_neg, not_false_iff]
#align mfderiv_within_zero_of_not_mdifferentiable_within_at mfderivWithin_zero_of_not_mdifferentiableWithinAt
theorem mfderiv_zero_of_not_mdifferentiableAt (h : ¬MDifferentiableAt I I' f x) :
mfderiv I I' f x = 0 := by simp only [mfderiv, h, if_neg, not_false_iff]
#align mfderiv_zero_of_not_mdifferentiable_at mfderiv_zero_of_not_mdifferentiableAt
theorem HasMFDerivWithinAt.mono (h : HasMFDerivWithinAt I I' f t x f') (hst : s ⊆ t) :
HasMFDerivWithinAt I I' f s x f' :=
⟨ContinuousWithinAt.mono h.1 hst,
HasFDerivWithinAt.mono h.2 (inter_subset_inter (preimage_mono hst) (Subset.refl _))⟩
#align has_mfderiv_within_at.mono HasMFDerivWithinAt.mono
theorem HasMFDerivAt.hasMFDerivWithinAt (h : HasMFDerivAt I I' f x f') :
HasMFDerivWithinAt I I' f s x f' :=
⟨ContinuousAt.continuousWithinAt h.1, HasFDerivWithinAt.mono h.2 inter_subset_right⟩
#align has_mfderiv_at.has_mfderiv_within_at HasMFDerivAt.hasMFDerivWithinAt
theorem HasMFDerivWithinAt.mdifferentiableWithinAt (h : HasMFDerivWithinAt I I' f s x f') :
MDifferentiableWithinAt I I' f s x :=
⟨h.1, ⟨f', h.2⟩⟩
#align has_mfderiv_within_at.mdifferentiable_within_at HasMFDerivWithinAt.mdifferentiableWithinAt
theorem HasMFDerivAt.mdifferentiableAt (h : HasMFDerivAt I I' f x f') :
MDifferentiableAt I I' f x := by
rw [mdifferentiableAt_iff]
exact ⟨h.1, ⟨f', h.2⟩⟩
#align has_mfderiv_at.mdifferentiable_at HasMFDerivAt.mdifferentiableAt
@[simp, mfld_simps]
theorem hasMFDerivWithinAt_univ :
HasMFDerivWithinAt I I' f univ x f' ↔ HasMFDerivAt I I' f x f' := by
simp only [HasMFDerivWithinAt, HasMFDerivAt, continuousWithinAt_univ, mfld_simps]
#align has_mfderiv_within_at_univ hasMFDerivWithinAt_univ
theorem hasMFDerivAt_unique (h₀ : HasMFDerivAt I I' f x f₀') (h₁ : HasMFDerivAt I I' f x f₁') :
f₀' = f₁' := by
rw [← hasMFDerivWithinAt_univ] at h₀ h₁
exact (uniqueMDiffWithinAt_univ I).eq h₀ h₁
#align has_mfderiv_at_unique hasMFDerivAt_unique
theorem hasMFDerivWithinAt_inter' (h : t ∈ 𝓝[s] x) :
HasMFDerivWithinAt I I' f (s ∩ t) x f' ↔ HasMFDerivWithinAt I I' f s x f' := by
rw [HasMFDerivWithinAt, HasMFDerivWithinAt, extChartAt_preimage_inter_eq,
hasFDerivWithinAt_inter', continuousWithinAt_inter' h]
exact extChartAt_preimage_mem_nhdsWithin I h
#align has_mfderiv_within_at_inter' hasMFDerivWithinAt_inter'
theorem hasMFDerivWithinAt_inter (h : t ∈ 𝓝 x) :
HasMFDerivWithinAt I I' f (s ∩ t) x f' ↔ HasMFDerivWithinAt I I' f s x f' := by
rw [HasMFDerivWithinAt, HasMFDerivWithinAt, extChartAt_preimage_inter_eq, hasFDerivWithinAt_inter,
continuousWithinAt_inter h]
exact extChartAt_preimage_mem_nhds I h
#align has_mfderiv_within_at_inter hasMFDerivWithinAt_inter
theorem HasMFDerivWithinAt.union (hs : HasMFDerivWithinAt I I' f s x f')
(ht : HasMFDerivWithinAt I I' f t x f') : HasMFDerivWithinAt I I' f (s ∪ t) x f' := by
constructor
· exact ContinuousWithinAt.union hs.1 ht.1
· convert HasFDerivWithinAt.union hs.2 ht.2 using 1
simp only [union_inter_distrib_right, preimage_union]
#align has_mfderiv_within_at.union HasMFDerivWithinAt.union
theorem HasMFDerivWithinAt.mono_of_mem (h : HasMFDerivWithinAt I I' f s x f') (ht : s ∈ 𝓝[t] x) :
HasMFDerivWithinAt I I' f t x f' :=
(hasMFDerivWithinAt_inter' ht).1 (h.mono inter_subset_right)
#align has_mfderiv_within_at.nhds_within HasMFDerivWithinAt.mono_of_mem
theorem HasMFDerivWithinAt.hasMFDerivAt (h : HasMFDerivWithinAt I I' f s x f') (hs : s ∈ 𝓝 x) :
HasMFDerivAt I I' f x f' := by
rwa [← univ_inter s, hasMFDerivWithinAt_inter hs, hasMFDerivWithinAt_univ] at h
#align has_mfderiv_within_at.has_mfderiv_at HasMFDerivWithinAt.hasMFDerivAt
theorem MDifferentiableWithinAt.hasMFDerivWithinAt (h : MDifferentiableWithinAt I I' f s x) :
HasMFDerivWithinAt I I' f s x (mfderivWithin I I' f s x) := by
refine ⟨h.1, ?_⟩
simp only [mfderivWithin, h, if_pos, mfld_simps]
exact DifferentiableWithinAt.hasFDerivWithinAt h.2
#align mdifferentiable_within_at.has_mfderiv_within_at MDifferentiableWithinAt.hasMFDerivWithinAt
protected theorem MDifferentiableWithinAt.mfderivWithin (h : MDifferentiableWithinAt I I' f s x) :
mfderivWithin I I' f s x =
fderivWithin 𝕜 (writtenInExtChartAt I I' x f : _) ((extChartAt I x).symm ⁻¹' s ∩ range I)
((extChartAt I x) x) := by
simp only [mfderivWithin, h, if_pos]
#align mdifferentiable_within_at.mfderiv_within MDifferentiableWithinAt.mfderivWithin
theorem MDifferentiableAt.hasMFDerivAt (h : MDifferentiableAt I I' f x) :
HasMFDerivAt I I' f x (mfderiv I I' f x) := by
refine ⟨h.continuousAt, ?_⟩
simp only [mfderiv, h, if_pos, mfld_simps]
exact DifferentiableWithinAt.hasFDerivWithinAt h.differentiableWithinAt_writtenInExtChartAt
#align mdifferentiable_at.has_mfderiv_at MDifferentiableAt.hasMFDerivAt
protected theorem MDifferentiableAt.mfderiv (h : MDifferentiableAt I I' f x) :
mfderiv I I' f x =
fderivWithin 𝕜 (writtenInExtChartAt I I' x f : _) (range I) ((extChartAt I x) x) := by
simp only [mfderiv, h, if_pos]
#align mdifferentiable_at.mfderiv MDifferentiableAt.mfderiv
protected theorem HasMFDerivAt.mfderiv (h : HasMFDerivAt I I' f x f') : mfderiv I I' f x = f' :=
(hasMFDerivAt_unique h h.mdifferentiableAt.hasMFDerivAt).symm
#align has_mfderiv_at.mfderiv HasMFDerivAt.mfderiv
theorem HasMFDerivWithinAt.mfderivWithin (h : HasMFDerivWithinAt I I' f s x f')
(hxs : UniqueMDiffWithinAt I s x) : mfderivWithin I I' f s x = f' := by
ext
rw [hxs.eq h h.mdifferentiableWithinAt.hasMFDerivWithinAt]
#align has_mfderiv_within_at.mfderiv_within HasMFDerivWithinAt.mfderivWithin
theorem MDifferentiable.mfderivWithin (h : MDifferentiableAt I I' f x)
(hxs : UniqueMDiffWithinAt I s x) : mfderivWithin I I' f s x = mfderiv I I' f x := by
apply HasMFDerivWithinAt.mfderivWithin _ hxs
exact h.hasMFDerivAt.hasMFDerivWithinAt
#align mdifferentiable.mfderiv_within MDifferentiable.mfderivWithin
theorem mfderivWithin_subset (st : s ⊆ t) (hs : UniqueMDiffWithinAt I s x)
(h : MDifferentiableWithinAt I I' f t x) :
mfderivWithin I I' f s x = mfderivWithin I I' f t x :=
((MDifferentiableWithinAt.hasMFDerivWithinAt h).mono st).mfderivWithin hs
#align mfderiv_within_subset mfderivWithin_subset
theorem MDifferentiableWithinAt.mono (hst : s ⊆ t) (h : MDifferentiableWithinAt I I' f t x) :
MDifferentiableWithinAt I I' f s x :=
⟨ContinuousWithinAt.mono h.1 hst, DifferentiableWithinAt.mono
h.differentiableWithinAt_writtenInExtChartAt
(inter_subset_inter_left _ (preimage_mono hst))⟩
#align mdifferentiable_within_at.mono MDifferentiableWithinAt.mono
theorem mdifferentiableWithinAt_univ :
MDifferentiableWithinAt I I' f univ x ↔ MDifferentiableAt I I' f x := by
simp_rw [MDifferentiableWithinAt, MDifferentiableAt, ChartedSpace.LiftPropAt]
#align mdifferentiable_within_at_univ mdifferentiableWithinAt_univ
theorem mdifferentiableWithinAt_inter (ht : t ∈ 𝓝 x) :
MDifferentiableWithinAt I I' f (s ∩ t) x ↔ MDifferentiableWithinAt I I' f s x := by
rw [MDifferentiableWithinAt, MDifferentiableWithinAt,
(differentiable_within_at_localInvariantProp I I').liftPropWithinAt_inter ht]
#align mdifferentiable_within_at_inter mdifferentiableWithinAt_inter
theorem mdifferentiableWithinAt_inter' (ht : t ∈ 𝓝[s] x) :
MDifferentiableWithinAt I I' f (s ∩ t) x ↔ MDifferentiableWithinAt I I' f s x := by
rw [MDifferentiableWithinAt, MDifferentiableWithinAt,
(differentiable_within_at_localInvariantProp I I').liftPropWithinAt_inter' ht]
#align mdifferentiable_within_at_inter' mdifferentiableWithinAt_inter'
theorem MDifferentiableAt.mdifferentiableWithinAt (h : MDifferentiableAt I I' f x) :
MDifferentiableWithinAt I I' f s x :=
MDifferentiableWithinAt.mono (subset_univ _) (mdifferentiableWithinAt_univ.2 h)
#align mdifferentiable_at.mdifferentiable_within_at MDifferentiableAt.mdifferentiableWithinAt
theorem MDifferentiableWithinAt.mdifferentiableAt (h : MDifferentiableWithinAt I I' f s x)
(hs : s ∈ 𝓝 x) : MDifferentiableAt I I' f x := by
have : s = univ ∩ s := by rw [univ_inter]
rwa [this, mdifferentiableWithinAt_inter hs, mdifferentiableWithinAt_univ] at h
#align mdifferentiable_within_at.mdifferentiable_at MDifferentiableWithinAt.mdifferentiableAt
theorem MDifferentiableOn.mdifferentiableAt (h : MDifferentiableOn I I' f s) (hx : s ∈ 𝓝 x) :
MDifferentiableAt I I' f x :=
(h x (mem_of_mem_nhds hx)).mdifferentiableAt hx
theorem MDifferentiableOn.mono (h : MDifferentiableOn I I' f t) (st : s ⊆ t) :
MDifferentiableOn I I' f s := fun x hx => (h x (st hx)).mono st
#align mdifferentiable_on.mono MDifferentiableOn.mono
theorem mdifferentiableOn_univ : MDifferentiableOn I I' f univ ↔ MDifferentiable I I' f := by
simp only [MDifferentiableOn, mdifferentiableWithinAt_univ, mfld_simps]; rfl
#align mdifferentiable_on_univ mdifferentiableOn_univ
theorem MDifferentiable.mdifferentiableOn (h : MDifferentiable I I' f) :
MDifferentiableOn I I' f s :=
(mdifferentiableOn_univ.2 h).mono (subset_univ _)
#align mdifferentiable.mdifferentiable_on MDifferentiable.mdifferentiableOn
theorem mdifferentiableOn_of_locally_mdifferentiableOn
(h : ∀ x ∈ s, ∃ u, IsOpen u ∧ x ∈ u ∧ MDifferentiableOn I I' f (s ∩ u)) :
MDifferentiableOn I I' f s := by
intro x xs
rcases h x xs with ⟨t, t_open, xt, ht⟩
exact (mdifferentiableWithinAt_inter (t_open.mem_nhds xt)).1 (ht x ⟨xs, xt⟩)
#align mdifferentiable_on_of_locally_mdifferentiable_on mdifferentiableOn_of_locally_mdifferentiableOn
@[simp, mfld_simps]
theorem mfderivWithin_univ : mfderivWithin I I' f univ = mfderiv I I' f := by
ext x : 1
simp only [mfderivWithin, mfderiv, mfld_simps]
rw [mdifferentiableWithinAt_univ]
#align mfderiv_within_univ mfderivWithin_univ
theorem mfderivWithin_inter (ht : t ∈ 𝓝 x) :
mfderivWithin I I' f (s ∩ t) x = mfderivWithin I I' f s x := by
rw [mfderivWithin, mfderivWithin, extChartAt_preimage_inter_eq, mdifferentiableWithinAt_inter ht,
fderivWithin_inter (extChartAt_preimage_mem_nhds I ht)]
#align mfderiv_within_inter mfderivWithin_inter
theorem mfderivWithin_of_mem_nhds (h : s ∈ 𝓝 x) : mfderivWithin I I' f s x = mfderiv I I' f x := by
rw [← mfderivWithin_univ, ← univ_inter s, mfderivWithin_inter h]
lemma mfderivWithin_of_isOpen (hs : IsOpen s) (hx : x ∈ s) :
mfderivWithin I I' f s x = mfderiv I I' f x :=
mfderivWithin_of_mem_nhds (hs.mem_nhds hx)
theorem mfderivWithin_eq_mfderiv (hs : UniqueMDiffWithinAt I s x) (h : MDifferentiableAt I I' f x) :
mfderivWithin I I' f s x = mfderiv I I' f x := by
rw [← mfderivWithin_univ]
exact mfderivWithin_subset (subset_univ _) hs h.mdifferentiableWithinAt
theorem mdifferentiableAt_iff_of_mem_source {x' : M} {y : M'}
(hx : x' ∈ (chartAt H x).source) (hy : f x' ∈ (chartAt H' y).source) :
MDifferentiableAt I I' f x' ↔
ContinuousAt f x' ∧
DifferentiableWithinAt 𝕜 (extChartAt I' y ∘ f ∘ (extChartAt I x).symm) (Set.range I)
((extChartAt I x) x') :=
mdifferentiableWithinAt_univ.symm.trans <|
(mdifferentiableWithinAt_iff_of_mem_source hx hy).trans <| by
rw [continuousWithinAt_univ, Set.preimage_univ, Set.univ_inter]
#align mdifferentiable_at_iff_of_mem_source mdifferentiableAt_iff_of_mem_source
/-! ### Deducing differentiability from smoothness -/
-- Porting note: moved from `ContMDiffMFDeriv`
variable {n : ℕ∞}
theorem ContMDiffWithinAt.mdifferentiableWithinAt (hf : ContMDiffWithinAt I I' n f s x)
(hn : 1 ≤ n) : MDifferentiableWithinAt I I' f s x := by
suffices h : MDifferentiableWithinAt I I' f (s ∩ f ⁻¹' (extChartAt I' (f x)).source) x by
rwa [mdifferentiableWithinAt_inter'] at h
apply hf.1.preimage_mem_nhdsWithin
exact extChartAt_source_mem_nhds I' (f x)
rw [mdifferentiableWithinAt_iff]
exact ⟨hf.1.mono inter_subset_left, (hf.2.differentiableWithinAt hn).mono (by mfld_set_tac)⟩
#align cont_mdiff_within_at.mdifferentiable_within_at ContMDiffWithinAt.mdifferentiableWithinAt
theorem ContMDiffAt.mdifferentiableAt (hf : ContMDiffAt I I' n f x) (hn : 1 ≤ n) :
MDifferentiableAt I I' f x :=
mdifferentiableWithinAt_univ.1 <| ContMDiffWithinAt.mdifferentiableWithinAt hf hn
#align cont_mdiff_at.mdifferentiable_at ContMDiffAt.mdifferentiableAt
theorem ContMDiffOn.mdifferentiableOn (hf : ContMDiffOn I I' n f s) (hn : 1 ≤ n) :
MDifferentiableOn I I' f s := fun x hx => (hf x hx).mdifferentiableWithinAt hn
#align cont_mdiff_on.mdifferentiable_on ContMDiffOn.mdifferentiableOn
theorem ContMDiff.mdifferentiable (hf : ContMDiff I I' n f) (hn : 1 ≤ n) : MDifferentiable I I' f :=
fun x => (hf x).mdifferentiableAt hn
#align cont_mdiff.mdifferentiable ContMDiff.mdifferentiable
nonrec theorem SmoothWithinAt.mdifferentiableWithinAt (hf : SmoothWithinAt I I' f s x) :
MDifferentiableWithinAt I I' f s x :=
hf.mdifferentiableWithinAt le_top
#align smooth_within_at.mdifferentiable_within_at SmoothWithinAt.mdifferentiableWithinAt
nonrec theorem SmoothAt.mdifferentiableAt (hf : SmoothAt I I' f x) : MDifferentiableAt I I' f x :=
hf.mdifferentiableAt le_top
#align smooth_at.mdifferentiable_at SmoothAt.mdifferentiableAt
nonrec theorem SmoothOn.mdifferentiableOn (hf : SmoothOn I I' f s) : MDifferentiableOn I I' f s :=
hf.mdifferentiableOn le_top
#align smooth_on.mdifferentiable_on SmoothOn.mdifferentiableOn
theorem Smooth.mdifferentiable (hf : Smooth I I' f) : MDifferentiable I I' f :=
ContMDiff.mdifferentiable hf le_top
#align smooth.mdifferentiable Smooth.mdifferentiable
theorem Smooth.mdifferentiableAt (hf : Smooth I I' f) : MDifferentiableAt I I' f x :=
hf.mdifferentiable x
#align smooth.mdifferentiable_at Smooth.mdifferentiableAt
theorem Smooth.mdifferentiableWithinAt (hf : Smooth I I' f) : MDifferentiableWithinAt I I' f s x :=
hf.mdifferentiableAt.mdifferentiableWithinAt
#align smooth.mdifferentiable_within_at Smooth.mdifferentiableWithinAt
/-! ### Deriving continuity from differentiability on manifolds -/
theorem HasMFDerivWithinAt.continuousWithinAt (h : HasMFDerivWithinAt I I' f s x f') :
ContinuousWithinAt f s x :=
h.1
#align has_mfderiv_within_at.continuous_within_at HasMFDerivWithinAt.continuousWithinAt
theorem HasMFDerivAt.continuousAt (h : HasMFDerivAt I I' f x f') : ContinuousAt f x :=
h.1
#align has_mfderiv_at.continuous_at HasMFDerivAt.continuousAt
theorem MDifferentiableOn.continuousOn (h : MDifferentiableOn I I' f s) : ContinuousOn f s :=
fun x hx => (h x hx).continuousWithinAt
#align mdifferentiable_on.continuous_on MDifferentiableOn.continuousOn
theorem MDifferentiable.continuous (h : MDifferentiable I I' f) : Continuous f :=
continuous_iff_continuousAt.2 fun x => (h x).continuousAt
#align mdifferentiable.continuous MDifferentiable.continuous
theorem tangentMapWithin_subset {p : TangentBundle I M} (st : s ⊆ t)
(hs : UniqueMDiffWithinAt I s p.1) (h : MDifferentiableWithinAt I I' f t p.1) :
tangentMapWithin I I' f s p = tangentMapWithin I I' f t p := by
simp only [tangentMapWithin, mfld_simps]
rw [mfderivWithin_subset st hs h]
#align tangent_map_within_subset tangentMapWithin_subset
theorem tangentMapWithin_univ : tangentMapWithin I I' f univ = tangentMap I I' f := by
ext p : 1
simp only [tangentMapWithin, tangentMap, mfld_simps]
#align tangent_map_within_univ tangentMapWithin_univ
theorem tangentMapWithin_eq_tangentMap {p : TangentBundle I M} (hs : UniqueMDiffWithinAt I s p.1)
(h : MDifferentiableAt I I' f p.1) : tangentMapWithin I I' f s p = tangentMap I I' f p := by
rw [← mdifferentiableWithinAt_univ] at h
rw [← tangentMapWithin_univ]
exact tangentMapWithin_subset (subset_univ _) hs h
#align tangent_map_within_eq_tangent_map tangentMapWithin_eq_tangentMap
@[simp, mfld_simps]
theorem tangentMapWithin_proj {p : TangentBundle I M} :
(tangentMapWithin I I' f s p).proj = f p.proj :=
rfl
#align tangent_map_within_proj tangentMapWithin_proj
@[simp, mfld_simps]
theorem tangentMap_proj {p : TangentBundle I M} : (tangentMap I I' f p).proj = f p.proj :=
rfl
#align tangent_map_proj tangentMap_proj
theorem MDifferentiableWithinAt.prod_mk {f : M → M'} {g : M → M''}
(hf : MDifferentiableWithinAt I I' f s x) (hg : MDifferentiableWithinAt I I'' g s x) :
MDifferentiableWithinAt I (I'.prod I'') (fun x => (f x, g x)) s x :=
⟨hf.1.prod hg.1, hf.2.prod hg.2⟩
#align mdifferentiable_within_at.prod_mk MDifferentiableWithinAt.prod_mk
theorem MDifferentiableAt.prod_mk {f : M → M'} {g : M → M''} (hf : MDifferentiableAt I I' f x)
(hg : MDifferentiableAt I I'' g x) :
MDifferentiableAt I (I'.prod I'') (fun x => (f x, g x)) x :=
⟨hf.1.prod hg.1, hf.2.prod hg.2⟩
#align mdifferentiable_at.prod_mk MDifferentiableAt.prod_mk
theorem MDifferentiableOn.prod_mk {f : M → M'} {g : M → M''} (hf : MDifferentiableOn I I' f s)
(hg : MDifferentiableOn I I'' g s) :
MDifferentiableOn I (I'.prod I'') (fun x => (f x, g x)) s := fun x hx =>
(hf x hx).prod_mk (hg x hx)
#align mdifferentiable_on.prod_mk MDifferentiableOn.prod_mk
theorem MDifferentiable.prod_mk {f : M → M'} {g : M → M''} (hf : MDifferentiable I I' f)
(hg : MDifferentiable I I'' g) : MDifferentiable I (I'.prod I'') fun x => (f x, g x) := fun x =>
(hf x).prod_mk (hg x)
#align mdifferentiable.prod_mk MDifferentiable.prod_mk
theorem MDifferentiableWithinAt.prod_mk_space {f : M → E'} {g : M → E''}
(hf : MDifferentiableWithinAt I 𝓘(𝕜, E') f s x)
(hg : MDifferentiableWithinAt I 𝓘(𝕜, E'') g s x) :
MDifferentiableWithinAt I 𝓘(𝕜, E' × E'') (fun x => (f x, g x)) s x :=
⟨hf.1.prod hg.1, hf.2.prod hg.2⟩
#align mdifferentiable_within_at.prod_mk_space MDifferentiableWithinAt.prod_mk_space
theorem MDifferentiableAt.prod_mk_space {f : M → E'} {g : M → E''}
(hf : MDifferentiableAt I 𝓘(𝕜, E') f x) (hg : MDifferentiableAt I 𝓘(𝕜, E'') g x) :
MDifferentiableAt I 𝓘(𝕜, E' × E'') (fun x => (f x, g x)) x :=
⟨hf.1.prod hg.1, hf.2.prod hg.2⟩
#align mdifferentiable_at.prod_mk_space MDifferentiableAt.prod_mk_space
theorem MDifferentiableOn.prod_mk_space {f : M → E'} {g : M → E''}
(hf : MDifferentiableOn I 𝓘(𝕜, E') f s) (hg : MDifferentiableOn I 𝓘(𝕜, E'') g s) :
MDifferentiableOn I 𝓘(𝕜, E' × E'') (fun x => (f x, g x)) s := fun x hx =>
(hf x hx).prod_mk_space (hg x hx)
#align mdifferentiable_on.prod_mk_space MDifferentiableOn.prod_mk_space
theorem MDifferentiable.prod_mk_space {f : M → E'} {g : M → E''} (hf : MDifferentiable I 𝓘(𝕜, E') f)
(hg : MDifferentiable I 𝓘(𝕜, E'') g) : MDifferentiable I 𝓘(𝕜, E' × E'') fun x => (f x, g x) :=
fun x => (hf x).prod_mk_space (hg x)
#align mdifferentiable.prod_mk_space MDifferentiable.prod_mk_space
/-! ### Congruence lemmas for derivatives on manifolds -/
theorem HasMFDerivAt.congr_mfderiv (h : HasMFDerivAt I I' f x f') (h' : f' = f₁') :
HasMFDerivAt I I' f x f₁' :=
h' ▸ h
theorem HasMFDerivWithinAt.congr_mfderiv (h : HasMFDerivWithinAt I I' f s x f') (h' : f' = f₁') :
HasMFDerivWithinAt I I' f s x f₁' :=
h' ▸ h
theorem HasMFDerivWithinAt.congr_of_eventuallyEq (h : HasMFDerivWithinAt I I' f s x f')
(h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) : HasMFDerivWithinAt I I' f₁ s x f' := by
refine ⟨ContinuousWithinAt.congr_of_eventuallyEq h.1 h₁ hx, ?_⟩
apply HasFDerivWithinAt.congr_of_eventuallyEq h.2
· have :
(extChartAt I x).symm ⁻¹' {y | f₁ y = f y} ∈
𝓝[(extChartAt I x).symm ⁻¹' s ∩ range I] (extChartAt I x) x :=
extChartAt_preimage_mem_nhdsWithin I h₁
apply Filter.mem_of_superset this fun y => _
simp (config := { contextual := true }) only [hx, mfld_simps]
· simp only [hx, mfld_simps]
#align has_mfderiv_within_at.congr_of_eventually_eq HasMFDerivWithinAt.congr_of_eventuallyEq
theorem HasMFDerivWithinAt.congr_mono (h : HasMFDerivWithinAt I I' f s x f')
(ht : ∀ x ∈ t, f₁ x = f x) (hx : f₁ x = f x) (h₁ : t ⊆ s) : HasMFDerivWithinAt I I' f₁ t x f' :=
(h.mono h₁).congr_of_eventuallyEq (Filter.mem_inf_of_right ht) hx
#align has_mfderiv_within_at.congr_mono HasMFDerivWithinAt.congr_mono
theorem HasMFDerivAt.congr_of_eventuallyEq (h : HasMFDerivAt I I' f x f') (h₁ : f₁ =ᶠ[𝓝 x] f) :
HasMFDerivAt I I' f₁ x f' := by
rw [← hasMFDerivWithinAt_univ] at h ⊢
apply h.congr_of_eventuallyEq _ (mem_of_mem_nhds h₁ : _)
rwa [nhdsWithin_univ]
#align has_mfderiv_at.congr_of_eventually_eq HasMFDerivAt.congr_of_eventuallyEq
theorem MDifferentiableWithinAt.congr_of_eventuallyEq (h : MDifferentiableWithinAt I I' f s x)
(h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) : MDifferentiableWithinAt I I' f₁ s x :=
(h.hasMFDerivWithinAt.congr_of_eventuallyEq h₁ hx).mdifferentiableWithinAt
#align mdifferentiable_within_at.congr_of_eventually_eq MDifferentiableWithinAt.congr_of_eventuallyEq
variable (I I')
theorem Filter.EventuallyEq.mdifferentiableWithinAt_iff (h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) :
MDifferentiableWithinAt I I' f s x ↔ MDifferentiableWithinAt I I' f₁ s x := by
constructor
· intro h
apply h.congr_of_eventuallyEq h₁ hx
· intro h
apply h.congr_of_eventuallyEq _ hx.symm
apply h₁.mono
intro y
apply Eq.symm
#align filter.eventually_eq.mdifferentiable_within_at_iff Filter.EventuallyEq.mdifferentiableWithinAt_iff
variable {I I'}
theorem MDifferentiableWithinAt.congr_mono (h : MDifferentiableWithinAt I I' f s x)
(ht : ∀ x ∈ t, f₁ x = f x) (hx : f₁ x = f x) (h₁ : t ⊆ s) :
MDifferentiableWithinAt I I' f₁ t x :=
(HasMFDerivWithinAt.congr_mono h.hasMFDerivWithinAt ht hx h₁).mdifferentiableWithinAt
#align mdifferentiable_within_at.congr_mono MDifferentiableWithinAt.congr_mono
theorem MDifferentiableWithinAt.congr (h : MDifferentiableWithinAt I I' f s x)
(ht : ∀ x ∈ s, f₁ x = f x) (hx : f₁ x = f x) : MDifferentiableWithinAt I I' f₁ s x :=
(HasMFDerivWithinAt.congr_mono h.hasMFDerivWithinAt ht hx (Subset.refl _)).mdifferentiableWithinAt
#align mdifferentiable_within_at.congr MDifferentiableWithinAt.congr
theorem MDifferentiableOn.congr_mono (h : MDifferentiableOn I I' f s) (h' : ∀ x ∈ t, f₁ x = f x)
(h₁ : t ⊆ s) : MDifferentiableOn I I' f₁ t := fun x hx =>
(h x (h₁ hx)).congr_mono h' (h' x hx) h₁
#align mdifferentiable_on.congr_mono MDifferentiableOn.congr_mono
theorem MDifferentiableAt.congr_of_eventuallyEq (h : MDifferentiableAt I I' f x)
(hL : f₁ =ᶠ[𝓝 x] f) : MDifferentiableAt I I' f₁ x :=
(h.hasMFDerivAt.congr_of_eventuallyEq hL).mdifferentiableAt
#align mdifferentiable_at.congr_of_eventually_eq MDifferentiableAt.congr_of_eventuallyEq
theorem MDifferentiableWithinAt.mfderivWithin_congr_mono (h : MDifferentiableWithinAt I I' f s x)
(hs : ∀ x ∈ t, f₁ x = f x) (hx : f₁ x = f x) (hxt : UniqueMDiffWithinAt I t x) (h₁ : t ⊆ s) :
mfderivWithin I I' f₁ t x = (mfderivWithin I I' f s x : _) :=
(HasMFDerivWithinAt.congr_mono h.hasMFDerivWithinAt hs hx h₁).mfderivWithin hxt
#align mdifferentiable_within_at.mfderiv_within_congr_mono MDifferentiableWithinAt.mfderivWithin_congr_mono
theorem Filter.EventuallyEq.mfderivWithin_eq (hs : UniqueMDiffWithinAt I s x) (hL : f₁ =ᶠ[𝓝[s] x] f)
(hx : f₁ x = f x) : mfderivWithin I I' f₁ s x = (mfderivWithin I I' f s x : _) := by
by_cases h : MDifferentiableWithinAt I I' f s x
· exact (h.hasMFDerivWithinAt.congr_of_eventuallyEq hL hx).mfderivWithin hs
· unfold mfderivWithin
rw [if_neg h, if_neg]
rwa [← hL.mdifferentiableWithinAt_iff I I' hx]
#align filter.eventually_eq.mfderiv_within_eq Filter.EventuallyEq.mfderivWithin_eq
theorem mfderivWithin_congr (hs : UniqueMDiffWithinAt I s x) (hL : ∀ x ∈ s, f₁ x = f x)
(hx : f₁ x = f x) : mfderivWithin I I' f₁ s x = (mfderivWithin I I' f s x : _) :=
Filter.EventuallyEq.mfderivWithin_eq hs (Filter.eventuallyEq_of_mem self_mem_nhdsWithin hL) hx
#align mfderiv_within_congr mfderivWithin_congr
theorem tangentMapWithin_congr (h : ∀ x ∈ s, f x = f₁ x) (p : TangentBundle I M) (hp : p.1 ∈ s)
(hs : UniqueMDiffWithinAt I s p.1) :
tangentMapWithin I I' f s p = tangentMapWithin I I' f₁ s p := by
refine TotalSpace.ext _ _ (h p.1 hp) ?_
-- This used to be `simp only`, but we need `erw` after leanprover/lean4#2644
rw [tangentMapWithin, h p.1 hp, tangentMapWithin, mfderivWithin_congr hs h (h _ hp)]
#align tangent_map_within_congr tangentMapWithin_congr
| Mathlib/Geometry/Manifold/MFDeriv/Basic.lean | 635 | 640 | theorem Filter.EventuallyEq.mfderiv_eq (hL : f₁ =ᶠ[𝓝 x] f) :
mfderiv I I' f₁ x = (mfderiv I I' f x : _) := by |
have A : f₁ x = f x := (mem_of_mem_nhds hL : _)
rw [← mfderivWithin_univ, ← mfderivWithin_univ]
rw [← nhdsWithin_univ] at hL
exact hL.mfderivWithin_eq (uniqueMDiffWithinAt_univ I) A
|
/-
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
| Mathlib/MeasureTheory/Integral/SetToL1.lean | 589 | 603 | 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
|
/-
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."]
| Mathlib/Algebra/BigOperators/Group/Finset.lean | 1,682 | 1,687 | 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]
|
/-
Copyright (c) 2022 Jujian Zhang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang, Jujian Zhang
-/
import Mathlib.Algebra.Algebra.Bilinear
import Mathlib.RingTheory.Localization.Basic
#align_import algebra.module.localized_module from "leanprover-community/mathlib"@"831c494092374cfe9f50591ed0ac81a25efc5b86"
/-!
# Localized Module
Given a commutative semiring `R`, a multiplicative subset `S ⊆ R` and an `R`-module `M`, we can
localize `M` by `S`. This gives us a `Localization S`-module.
## Main definitions
* `LocalizedModule.r` : the equivalence relation defining this localization, namely
`(m, s) ≈ (m', s')` if and only if there is some `u : S` such that `u • s' • m = u • s • m'`.
* `LocalizedModule M S` : the localized module by `S`.
* `LocalizedModule.mk` : the canonical map sending `(m, s) : M × S ↦ m/s : LocalizedModule M S`
* `LocalizedModule.liftOn` : any well defined function `f : M × S → α` respecting `r` descents to
a function `LocalizedModule M S → α`
* `LocalizedModule.liftOn₂` : any well defined function `f : M × S → M × S → α` respecting `r`
descents to a function `LocalizedModule M S → LocalizedModule M S`
* `LocalizedModule.mk_add_mk` : in the localized module
`mk m s + mk m' s' = mk (s' • m + s • m') (s * s')`
* `LocalizedModule.mk_smul_mk` : in the localized module, for any `r : R`, `s t : S`, `m : M`,
we have `mk r s • mk m t = mk (r • m) (s * t)` where `mk r s : Localization S` is localized ring
by `S`.
* `LocalizedModule.isModule` : `LocalizedModule M S` is a `Localization S`-module.
## Future work
* Redefine `Localization` for monoids and rings to coincide with `LocalizedModule`.
-/
namespace LocalizedModule
universe u v
variable {R : Type u} [CommSemiring R] (S : Submonoid R)
variable (M : Type v) [AddCommMonoid M] [Module R M]
variable (T : Type*) [CommSemiring T] [Algebra R T] [IsLocalization S T]
/-- The equivalence relation on `M × S` where `(m1, s1) ≈ (m2, s2)` if and only if
for some (u : S), u * (s2 • m1 - s1 • m2) = 0-/
/- Porting note: We use small letter `r` since `R` is used for a ring. -/
def r (a b : M × S) : Prop :=
∃ u : S, u • b.2 • a.1 = u • a.2 • b.1
#align localized_module.r LocalizedModule.r
theorem r.isEquiv : IsEquiv _ (r S M) :=
{ refl := fun ⟨m, s⟩ => ⟨1, by rw [one_smul]⟩
trans := fun ⟨m1, s1⟩ ⟨m2, s2⟩ ⟨m3, s3⟩ ⟨u1, hu1⟩ ⟨u2, hu2⟩ => by
use u1 * u2 * s2
-- Put everything in the same shape, sorting the terms using `simp`
have hu1' := congr_arg ((u2 * s3) • ·) hu1.symm
have hu2' := congr_arg ((u1 * s1) • ·) hu2.symm
simp only [← mul_smul, smul_assoc, mul_assoc, mul_comm, mul_left_comm] at hu1' hu2' ⊢
rw [hu2', hu1']
symm := fun ⟨m1, s1⟩ ⟨m2, s2⟩ ⟨u, hu⟩ => ⟨u, hu.symm⟩ }
#align localized_module.r.is_equiv LocalizedModule.r.isEquiv
instance r.setoid : Setoid (M × S) where
r := r S M
iseqv := ⟨(r.isEquiv S M).refl, (r.isEquiv S M).symm _ _, (r.isEquiv S M).trans _ _ _⟩
#align localized_module.r.setoid LocalizedModule.r.setoid
-- TODO: change `Localization` to use `r'` instead of `r` so that the two types are also defeq,
-- `Localization S = LocalizedModule S R`.
example {R} [CommSemiring R] (S : Submonoid R) : ⇑(Localization.r' S) = LocalizedModule.r S R :=
rfl
/-- If `S` is a multiplicative subset of a ring `R` and `M` an `R`-module, then
we can localize `M` by `S`.
-/
-- Porting note(#5171): @[nolint has_nonempty_instance]
def _root_.LocalizedModule : Type max u v :=
Quotient (r.setoid S M)
#align localized_module LocalizedModule
section
variable {M S}
/-- The canonical map sending `(m, s) ↦ m/s`-/
def mk (m : M) (s : S) : LocalizedModule S M :=
Quotient.mk' ⟨m, s⟩
#align localized_module.mk LocalizedModule.mk
theorem mk_eq {m m' : M} {s s' : S} : mk m s = mk m' s' ↔ ∃ u : S, u • s' • m = u • s • m' :=
Quotient.eq'
#align localized_module.mk_eq LocalizedModule.mk_eq
@[elab_as_elim]
theorem induction_on {β : LocalizedModule S M → Prop} (h : ∀ (m : M) (s : S), β (mk m s)) :
∀ x : LocalizedModule S M, β x := by
rintro ⟨⟨m, s⟩⟩
exact h m s
#align localized_module.induction_on LocalizedModule.induction_on
@[elab_as_elim]
theorem induction_on₂ {β : LocalizedModule S M → LocalizedModule S M → Prop}
(h : ∀ (m m' : M) (s s' : S), β (mk m s) (mk m' s')) : ∀ x y, β x y := by
rintro ⟨⟨m, s⟩⟩ ⟨⟨m', s'⟩⟩
exact h m m' s s'
#align localized_module.induction_on₂ LocalizedModule.induction_on₂
/-- If `f : M × S → α` respects the equivalence relation `LocalizedModule.r`, then
`f` descents to a map `LocalizedModule M S → α`.
-/
def liftOn {α : Type*} (x : LocalizedModule S M) (f : M × S → α)
(wd : ∀ (p p' : M × S), p ≈ p' → f p = f p') : α :=
Quotient.liftOn x f wd
#align localized_module.lift_on LocalizedModule.liftOn
theorem liftOn_mk {α : Type*} {f : M × S → α} (wd : ∀ (p p' : M × S), p ≈ p' → f p = f p')
(m : M) (s : S) : liftOn (mk m s) f wd = f ⟨m, s⟩ := by convert Quotient.liftOn_mk f wd ⟨m, s⟩
#align localized_module.lift_on_mk LocalizedModule.liftOn_mk
/-- If `f : M × S → M × S → α` respects the equivalence relation `LocalizedModule.r`, then
`f` descents to a map `LocalizedModule M S → LocalizedModule M S → α`.
-/
def liftOn₂ {α : Type*} (x y : LocalizedModule S M) (f : M × S → M × S → α)
(wd : ∀ (p q p' q' : M × S), p ≈ p' → q ≈ q' → f p q = f p' q') : α :=
Quotient.liftOn₂ x y f wd
#align localized_module.lift_on₂ LocalizedModule.liftOn₂
| Mathlib/Algebra/Module/LocalizedModule.lean | 132 | 135 | theorem liftOn₂_mk {α : Type*} (f : M × S → M × S → α)
(wd : ∀ (p q p' q' : M × S), p ≈ p' → q ≈ q' → f p q = f p' q') (m m' : M)
(s s' : S) : liftOn₂ (mk m s) (mk m' s') f wd = f ⟨m, s⟩ ⟨m', s'⟩ := by |
convert Quotient.liftOn₂_mk f wd _ _
|
/-
Copyright (c) 2021 Aaron Anderson, Jesse Michael Han, Floris van Doorn. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Jesse Michael Han, Floris van Doorn
-/
import Mathlib.Data.Finset.Basic
import Mathlib.ModelTheory.Syntax
import Mathlib.Data.List.ProdSigma
#align_import model_theory.semantics from "leanprover-community/mathlib"@"d565b3df44619c1498326936be16f1a935df0728"
/-!
# Basics on First-Order Semantics
This file defines the interpretations of first-order terms, formulas, sentences, and theories
in a style inspired by the [Flypitch project](https://flypitch.github.io/).
## Main Definitions
* `FirstOrder.Language.Term.realize` is defined so that `t.realize v` is the term `t` evaluated at
variables `v`.
* `FirstOrder.Language.BoundedFormula.Realize` is defined so that `φ.Realize v xs` is the bounded
formula `φ` evaluated at tuples of variables `v` and `xs`.
* `FirstOrder.Language.Formula.Realize` is defined so that `φ.Realize v` is the formula `φ`
evaluated at variables `v`.
* `FirstOrder.Language.Sentence.Realize` is defined so that `φ.Realize M` is the sentence `φ`
evaluated in the structure `M`. Also denoted `M ⊨ φ`.
* `FirstOrder.Language.Theory.Model` is defined so that `T.Model M` is true if and only if every
sentence of `T` is realized in `M`. Also denoted `T ⊨ φ`.
## Main Results
* `FirstOrder.Language.BoundedFormula.realize_toPrenex` shows that the prenex normal form of a
formula has the same realization as the original formula.
* Several results in this file show that syntactic constructions such as `relabel`, `castLE`,
`liftAt`, `subst`, and the actions of language maps commute with realization of terms, formulas,
sentences, and theories.
## Implementation Notes
* Formulas use a modified version of de Bruijn variables. Specifically, a `L.BoundedFormula α n`
is a formula with some variables indexed by a type `α`, which cannot be quantified over, and some
indexed by `Fin n`, which can. For any `φ : L.BoundedFormula α (n + 1)`, we define the formula
`∀' φ : L.BoundedFormula α n` by universally quantifying over the variable indexed by
`n : Fin (n + 1)`.
## References
For the Flypitch project:
- [J. Han, F. van Doorn, *A formal proof of the independence of the continuum hypothesis*]
[flypitch_cpp]
- [J. Han, F. van Doorn, *A formalization of forcing and the unprovability of
the continuum hypothesis*][flypitch_itp]
-/
universe u v w u' v'
namespace FirstOrder
namespace Language
variable {L : Language.{u, v}} {L' : Language}
variable {M : Type w} {N P : Type*} [L.Structure M] [L.Structure N] [L.Structure P]
variable {α : Type u'} {β : Type v'} {γ : Type*}
open FirstOrder Cardinal
open Structure Cardinal Fin
namespace Term
-- Porting note: universes in different order
/-- A term `t` with variables indexed by `α` can be evaluated by giving a value to each variable. -/
def realize (v : α → M) : ∀ _t : L.Term α, M
| var k => v k
| func f ts => funMap f fun i => (ts i).realize v
#align first_order.language.term.realize FirstOrder.Language.Term.realize
/- Porting note: The equation lemma of `realize` is too strong; it simplifies terms like the LHS of
`realize_functions_apply₁`. Even `eqns` can't fix this. We removed `simp` attr from `realize` and
prepare new simp lemmas for `realize`. -/
@[simp]
theorem realize_var (v : α → M) (k) : realize v (var k : L.Term α) = v k := rfl
@[simp]
theorem realize_func (v : α → M) {n} (f : L.Functions n) (ts) :
realize v (func f ts : L.Term α) = funMap f fun i => (ts i).realize v := rfl
@[simp]
theorem realize_relabel {t : L.Term α} {g : α → β} {v : β → M} :
(t.relabel g).realize v = t.realize (v ∘ g) := by
induction' t with _ n f ts ih
· rfl
· simp [ih]
#align first_order.language.term.realize_relabel FirstOrder.Language.Term.realize_relabel
@[simp]
theorem realize_liftAt {n n' m : ℕ} {t : L.Term (Sum α (Fin n))} {v : Sum α (Fin (n + n')) → M} :
(t.liftAt n' m).realize v =
t.realize (v ∘ Sum.map id fun i : Fin _ =>
if ↑i < m then Fin.castAdd n' i else Fin.addNat i n') :=
realize_relabel
#align first_order.language.term.realize_lift_at FirstOrder.Language.Term.realize_liftAt
@[simp]
theorem realize_constants {c : L.Constants} {v : α → M} : c.term.realize v = c :=
funMap_eq_coe_constants
#align first_order.language.term.realize_constants FirstOrder.Language.Term.realize_constants
@[simp]
theorem realize_functions_apply₁ {f : L.Functions 1} {t : L.Term α} {v : α → M} :
(f.apply₁ t).realize v = funMap f ![t.realize v] := by
rw [Functions.apply₁, Term.realize]
refine congr rfl (funext fun i => ?_)
simp only [Matrix.cons_val_fin_one]
#align first_order.language.term.realize_functions_apply₁ FirstOrder.Language.Term.realize_functions_apply₁
@[simp]
theorem realize_functions_apply₂ {f : L.Functions 2} {t₁ t₂ : L.Term α} {v : α → M} :
(f.apply₂ t₁ t₂).realize v = funMap f ![t₁.realize v, t₂.realize v] := by
rw [Functions.apply₂, Term.realize]
refine congr rfl (funext (Fin.cases ?_ ?_))
· simp only [Matrix.cons_val_zero]
· simp only [Matrix.cons_val_succ, Matrix.cons_val_fin_one, forall_const]
#align first_order.language.term.realize_functions_apply₂ FirstOrder.Language.Term.realize_functions_apply₂
theorem realize_con {A : Set M} {a : A} {v : α → M} : (L.con a).term.realize v = a :=
rfl
#align first_order.language.term.realize_con FirstOrder.Language.Term.realize_con
@[simp]
theorem realize_subst {t : L.Term α} {tf : α → L.Term β} {v : β → M} :
(t.subst tf).realize v = t.realize fun a => (tf a).realize v := by
induction' t with _ _ _ _ ih
· rfl
· simp [ih]
#align first_order.language.term.realize_subst FirstOrder.Language.Term.realize_subst
@[simp]
theorem realize_restrictVar [DecidableEq α] {t : L.Term α} {s : Set α} (h : ↑t.varFinset ⊆ s)
{v : α → M} : (t.restrictVar (Set.inclusion h)).realize (v ∘ (↑)) = t.realize v := by
induction' t with _ _ _ _ ih
· rfl
· simp_rw [varFinset, Finset.coe_biUnion, Set.iUnion_subset_iff] at h
exact congr rfl (funext fun i => ih i (h i (Finset.mem_univ i)))
#align first_order.language.term.realize_restrict_var FirstOrder.Language.Term.realize_restrictVar
@[simp]
theorem realize_restrictVarLeft [DecidableEq α] {γ : Type*} {t : L.Term (Sum α γ)} {s : Set α}
(h : ↑t.varFinsetLeft ⊆ s) {v : α → M} {xs : γ → M} :
(t.restrictVarLeft (Set.inclusion h)).realize (Sum.elim (v ∘ (↑)) xs) =
t.realize (Sum.elim v xs) := by
induction' t with a _ _ _ ih
· cases a <;> rfl
· simp_rw [varFinsetLeft, Finset.coe_biUnion, Set.iUnion_subset_iff] at h
exact congr rfl (funext fun i => ih i (h i (Finset.mem_univ i)))
#align first_order.language.term.realize_restrict_var_left FirstOrder.Language.Term.realize_restrictVarLeft
@[simp]
theorem realize_constantsToVars [L[[α]].Structure M] [(lhomWithConstants L α).IsExpansionOn M]
{t : L[[α]].Term β} {v : β → M} :
t.constantsToVars.realize (Sum.elim (fun a => ↑(L.con a)) v) = t.realize v := by
induction' t with _ n f ts ih
· simp
· cases n
· cases f
· simp only [realize, ih, Nat.zero_eq, constantsOn, mk₂_Functions]
-- Porting note: below lemma does not work with simp for some reason
rw [withConstants_funMap_sum_inl]
· simp only [realize, constantsToVars, Sum.elim_inl, funMap_eq_coe_constants]
rfl
· cases' f with _ f
· simp only [realize, ih, constantsOn, mk₂_Functions]
-- Porting note: below lemma does not work with simp for some reason
rw [withConstants_funMap_sum_inl]
· exact isEmptyElim f
#align first_order.language.term.realize_constants_to_vars FirstOrder.Language.Term.realize_constantsToVars
@[simp]
theorem realize_varsToConstants [L[[α]].Structure M] [(lhomWithConstants L α).IsExpansionOn M]
{t : L.Term (Sum α β)} {v : β → M} :
t.varsToConstants.realize v = t.realize (Sum.elim (fun a => ↑(L.con a)) v) := by
induction' t with ab n f ts ih
· cases' ab with a b
-- Porting note: both cases were `simp [Language.con]`
· simp [Language.con, realize, funMap_eq_coe_constants]
· simp [realize, constantMap]
· simp only [realize, constantsOn, mk₂_Functions, ih]
-- Porting note: below lemma does not work with simp for some reason
rw [withConstants_funMap_sum_inl]
#align first_order.language.term.realize_vars_to_constants FirstOrder.Language.Term.realize_varsToConstants
theorem realize_constantsVarsEquivLeft [L[[α]].Structure M]
[(lhomWithConstants L α).IsExpansionOn M] {n} {t : L[[α]].Term (Sum β (Fin n))} {v : β → M}
{xs : Fin n → M} :
(constantsVarsEquivLeft t).realize (Sum.elim (Sum.elim (fun a => ↑(L.con a)) v) xs) =
t.realize (Sum.elim v xs) := by
simp only [constantsVarsEquivLeft, realize_relabel, Equiv.coe_trans, Function.comp_apply,
constantsVarsEquiv_apply, relabelEquiv_symm_apply]
refine _root_.trans ?_ realize_constantsToVars
rcongr x
rcases x with (a | (b | i)) <;> simp
#align first_order.language.term.realize_constants_vars_equiv_left FirstOrder.Language.Term.realize_constantsVarsEquivLeft
end Term
namespace LHom
@[simp]
theorem realize_onTerm [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M] (t : L.Term α)
(v : α → M) : (φ.onTerm t).realize v = t.realize v := by
induction' t with _ n f ts ih
· rfl
· simp only [Term.realize, LHom.onTerm, LHom.map_onFunction, ih]
set_option linter.uppercaseLean3 false in
#align first_order.language.Lhom.realize_on_term FirstOrder.Language.LHom.realize_onTerm
end LHom
@[simp]
theorem Hom.realize_term (g : M →[L] N) {t : L.Term α} {v : α → M} :
t.realize (g ∘ v) = g (t.realize v) := by
induction t
· rfl
· rw [Term.realize, Term.realize, g.map_fun]
refine congr rfl ?_
ext x
simp [*]
#align first_order.language.hom.realize_term FirstOrder.Language.Hom.realize_term
@[simp]
theorem Embedding.realize_term {v : α → M} (t : L.Term α) (g : M ↪[L] N) :
t.realize (g ∘ v) = g (t.realize v) :=
g.toHom.realize_term
#align first_order.language.embedding.realize_term FirstOrder.Language.Embedding.realize_term
@[simp]
theorem Equiv.realize_term {v : α → M} (t : L.Term α) (g : M ≃[L] N) :
t.realize (g ∘ v) = g (t.realize v) :=
g.toHom.realize_term
#align first_order.language.equiv.realize_term FirstOrder.Language.Equiv.realize_term
variable {n : ℕ}
namespace BoundedFormula
open Term
-- Porting note: universes in different order
/-- A bounded formula can be evaluated as true or false by giving values to each free variable. -/
def Realize : ∀ {l} (_f : L.BoundedFormula α l) (_v : α → M) (_xs : Fin l → M), Prop
| _, falsum, _v, _xs => False
| _, equal t₁ t₂, v, xs => t₁.realize (Sum.elim v xs) = t₂.realize (Sum.elim v xs)
| _, rel R ts, v, xs => RelMap R fun i => (ts i).realize (Sum.elim v xs)
| _, imp f₁ f₂, v, xs => Realize f₁ v xs → Realize f₂ v xs
| _, all f, v, xs => ∀ x : M, Realize f v (snoc xs x)
#align first_order.language.bounded_formula.realize FirstOrder.Language.BoundedFormula.Realize
variable {l : ℕ} {φ ψ : L.BoundedFormula α l} {θ : L.BoundedFormula α l.succ}
variable {v : α → M} {xs : Fin l → M}
@[simp]
theorem realize_bot : (⊥ : L.BoundedFormula α l).Realize v xs ↔ False :=
Iff.rfl
#align first_order.language.bounded_formula.realize_bot FirstOrder.Language.BoundedFormula.realize_bot
@[simp]
theorem realize_not : φ.not.Realize v xs ↔ ¬φ.Realize v xs :=
Iff.rfl
#align first_order.language.bounded_formula.realize_not FirstOrder.Language.BoundedFormula.realize_not
@[simp]
theorem realize_bdEqual (t₁ t₂ : L.Term (Sum α (Fin l))) :
(t₁.bdEqual t₂).Realize v xs ↔ t₁.realize (Sum.elim v xs) = t₂.realize (Sum.elim v xs) :=
Iff.rfl
#align first_order.language.bounded_formula.realize_bd_equal FirstOrder.Language.BoundedFormula.realize_bdEqual
@[simp]
theorem realize_top : (⊤ : L.BoundedFormula α l).Realize v xs ↔ True := by simp [Top.top]
#align first_order.language.bounded_formula.realize_top FirstOrder.Language.BoundedFormula.realize_top
@[simp]
theorem realize_inf : (φ ⊓ ψ).Realize v xs ↔ φ.Realize v xs ∧ ψ.Realize v xs := by
simp [Inf.inf, Realize]
#align first_order.language.bounded_formula.realize_inf FirstOrder.Language.BoundedFormula.realize_inf
@[simp]
theorem realize_foldr_inf (l : List (L.BoundedFormula α n)) (v : α → M) (xs : Fin n → M) :
(l.foldr (· ⊓ ·) ⊤).Realize v xs ↔ ∀ φ ∈ l, BoundedFormula.Realize φ v xs := by
induction' l with φ l ih
· simp
· simp [ih]
#align first_order.language.bounded_formula.realize_foldr_inf FirstOrder.Language.BoundedFormula.realize_foldr_inf
@[simp]
theorem realize_imp : (φ.imp ψ).Realize v xs ↔ φ.Realize v xs → ψ.Realize v xs := by
simp only [Realize]
#align first_order.language.bounded_formula.realize_imp FirstOrder.Language.BoundedFormula.realize_imp
@[simp]
theorem realize_rel {k : ℕ} {R : L.Relations k} {ts : Fin k → L.Term _} :
(R.boundedFormula ts).Realize v xs ↔ RelMap R fun i => (ts i).realize (Sum.elim v xs) :=
Iff.rfl
#align first_order.language.bounded_formula.realize_rel FirstOrder.Language.BoundedFormula.realize_rel
@[simp]
theorem realize_rel₁ {R : L.Relations 1} {t : L.Term _} :
(R.boundedFormula₁ t).Realize v xs ↔ RelMap R ![t.realize (Sum.elim v xs)] := by
rw [Relations.boundedFormula₁, realize_rel, iff_eq_eq]
refine congr rfl (funext fun _ => ?_)
simp only [Matrix.cons_val_fin_one]
#align first_order.language.bounded_formula.realize_rel₁ FirstOrder.Language.BoundedFormula.realize_rel₁
@[simp]
theorem realize_rel₂ {R : L.Relations 2} {t₁ t₂ : L.Term _} :
(R.boundedFormula₂ t₁ t₂).Realize v xs ↔
RelMap R ![t₁.realize (Sum.elim v xs), t₂.realize (Sum.elim v xs)] := by
rw [Relations.boundedFormula₂, realize_rel, iff_eq_eq]
refine congr rfl (funext (Fin.cases ?_ ?_))
· simp only [Matrix.cons_val_zero]
· simp only [Matrix.cons_val_succ, Matrix.cons_val_fin_one, forall_const]
#align first_order.language.bounded_formula.realize_rel₂ FirstOrder.Language.BoundedFormula.realize_rel₂
@[simp]
theorem realize_sup : (φ ⊔ ψ).Realize v xs ↔ φ.Realize v xs ∨ ψ.Realize v xs := by
simp only [realize, Sup.sup, realize_not, eq_iff_iff]
tauto
#align first_order.language.bounded_formula.realize_sup FirstOrder.Language.BoundedFormula.realize_sup
@[simp]
theorem realize_foldr_sup (l : List (L.BoundedFormula α n)) (v : α → M) (xs : Fin n → M) :
(l.foldr (· ⊔ ·) ⊥).Realize v xs ↔ ∃ φ ∈ l, BoundedFormula.Realize φ v xs := by
induction' l with φ l ih
· simp
· simp_rw [List.foldr_cons, realize_sup, ih, List.mem_cons, or_and_right, exists_or,
exists_eq_left]
#align first_order.language.bounded_formula.realize_foldr_sup FirstOrder.Language.BoundedFormula.realize_foldr_sup
@[simp]
theorem realize_all : (all θ).Realize v xs ↔ ∀ a : M, θ.Realize v (Fin.snoc xs a) :=
Iff.rfl
#align first_order.language.bounded_formula.realize_all FirstOrder.Language.BoundedFormula.realize_all
@[simp]
theorem realize_ex : θ.ex.Realize v xs ↔ ∃ a : M, θ.Realize v (Fin.snoc xs a) := by
rw [BoundedFormula.ex, realize_not, realize_all, not_forall]
simp_rw [realize_not, Classical.not_not]
#align first_order.language.bounded_formula.realize_ex FirstOrder.Language.BoundedFormula.realize_ex
@[simp]
theorem realize_iff : (φ.iff ψ).Realize v xs ↔ (φ.Realize v xs ↔ ψ.Realize v xs) := by
simp only [BoundedFormula.iff, realize_inf, realize_imp, and_imp, ← iff_def]
#align first_order.language.bounded_formula.realize_iff FirstOrder.Language.BoundedFormula.realize_iff
theorem realize_castLE_of_eq {m n : ℕ} (h : m = n) {h' : m ≤ n} {φ : L.BoundedFormula α m}
{v : α → M} {xs : Fin n → M} : (φ.castLE h').Realize v xs ↔ φ.Realize v (xs ∘ cast h) := by
subst h
simp only [castLE_rfl, cast_refl, OrderIso.coe_refl, Function.comp_id]
#align first_order.language.bounded_formula.realize_cast_le_of_eq FirstOrder.Language.BoundedFormula.realize_castLE_of_eq
theorem realize_mapTermRel_id [L'.Structure M]
{ft : ∀ n, L.Term (Sum α (Fin n)) → L'.Term (Sum β (Fin n))}
{fr : ∀ n, L.Relations n → L'.Relations n} {n} {φ : L.BoundedFormula α n} {v : α → M}
{v' : β → M} {xs : Fin n → M}
(h1 :
∀ (n) (t : L.Term (Sum α (Fin n))) (xs : Fin n → M),
(ft n t).realize (Sum.elim v' xs) = t.realize (Sum.elim v xs))
(h2 : ∀ (n) (R : L.Relations n) (x : Fin n → M), RelMap (fr n R) x = RelMap R x) :
(φ.mapTermRel ft fr fun _ => id).Realize v' xs ↔ φ.Realize v xs := by
induction' φ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 _ _ ih
· rfl
· simp [mapTermRel, Realize, h1]
· simp [mapTermRel, Realize, h1, h2]
· simp [mapTermRel, Realize, ih1, ih2]
· simp only [mapTermRel, Realize, ih, id]
#align first_order.language.bounded_formula.realize_map_term_rel_id FirstOrder.Language.BoundedFormula.realize_mapTermRel_id
theorem realize_mapTermRel_add_castLe [L'.Structure M] {k : ℕ}
{ft : ∀ n, L.Term (Sum α (Fin n)) → L'.Term (Sum β (Fin (k + n)))}
{fr : ∀ n, L.Relations n → L'.Relations n} {n} {φ : L.BoundedFormula α n}
(v : ∀ {n}, (Fin (k + n) → M) → α → M) {v' : β → M} (xs : Fin (k + n) → M)
(h1 :
∀ (n) (t : L.Term (Sum α (Fin n))) (xs' : Fin (k + n) → M),
(ft n t).realize (Sum.elim v' xs') = t.realize (Sum.elim (v xs') (xs' ∘ Fin.natAdd _)))
(h2 : ∀ (n) (R : L.Relations n) (x : Fin n → M), RelMap (fr n R) x = RelMap R x)
(hv : ∀ (n) (xs : Fin (k + n) → M) (x : M), @v (n + 1) (snoc xs x : Fin _ → M) = v xs) :
(φ.mapTermRel ft fr fun n => castLE (add_assoc _ _ _).symm.le).Realize v' xs ↔
φ.Realize (v xs) (xs ∘ Fin.natAdd _) := by
induction' φ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 _ _ ih
· rfl
· simp [mapTermRel, Realize, h1]
· simp [mapTermRel, Realize, h1, h2]
· simp [mapTermRel, Realize, ih1, ih2]
· simp [mapTermRel, Realize, ih, hv]
#align first_order.language.bounded_formula.realize_map_term_rel_add_cast_le FirstOrder.Language.BoundedFormula.realize_mapTermRel_add_castLe
@[simp]
theorem realize_relabel {m n : ℕ} {φ : L.BoundedFormula α n} {g : α → Sum β (Fin m)} {v : β → M}
{xs : Fin (m + n) → M} :
(φ.relabel g).Realize v xs ↔
φ.Realize (Sum.elim v (xs ∘ Fin.castAdd n) ∘ g) (xs ∘ Fin.natAdd m) := by
rw [relabel, realize_mapTermRel_add_castLe] <;> intros <;> simp
#align first_order.language.bounded_formula.realize_relabel FirstOrder.Language.BoundedFormula.realize_relabel
theorem realize_liftAt {n n' m : ℕ} {φ : L.BoundedFormula α n} {v : α → M} {xs : Fin (n + n') → M}
(hmn : m + n' ≤ n + 1) :
(φ.liftAt n' m).Realize v xs ↔
φ.Realize v (xs ∘ fun i => if ↑i < m then Fin.castAdd n' i else Fin.addNat i n') := by
rw [liftAt]
induction' φ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 k _ ih3
· simp [mapTermRel, Realize]
· simp [mapTermRel, Realize, realize_rel, realize_liftAt, Sum.elim_comp_map]
· simp [mapTermRel, Realize, realize_rel, realize_liftAt, Sum.elim_comp_map]
· simp only [mapTermRel, Realize, ih1 hmn, ih2 hmn]
· have h : k + 1 + n' = k + n' + 1 := by rw [add_assoc, add_comm 1 n', ← add_assoc]
simp only [mapTermRel, Realize, realize_castLE_of_eq h, ih3 (hmn.trans k.succ.le_succ)]
refine forall_congr' fun x => iff_eq_eq.mpr (congr rfl (funext (Fin.lastCases ?_ fun i => ?_)))
· simp only [Function.comp_apply, val_last, snoc_last]
by_cases h : k < m
· rw [if_pos h]
refine (congr rfl (ext ?_)).trans (snoc_last _ _)
simp only [coe_cast, coe_castAdd, val_last, self_eq_add_right]
refine le_antisymm
(le_of_add_le_add_left ((hmn.trans (Nat.succ_le_of_lt h)).trans ?_)) n'.zero_le
rw [add_zero]
· rw [if_neg h]
refine (congr rfl (ext ?_)).trans (snoc_last _ _)
simp
· simp only [Function.comp_apply, Fin.snoc_castSucc]
refine (congr rfl (ext ?_)).trans (snoc_castSucc _ _ _)
simp only [coe_castSucc, coe_cast]
split_ifs <;> simp
#align first_order.language.bounded_formula.realize_lift_at FirstOrder.Language.BoundedFormula.realize_liftAt
theorem realize_liftAt_one {n m : ℕ} {φ : L.BoundedFormula α n} {v : α → M} {xs : Fin (n + 1) → M}
(hmn : m ≤ n) :
(φ.liftAt 1 m).Realize v xs ↔
φ.Realize v (xs ∘ fun i => if ↑i < m then castSucc i else i.succ) := by
simp [realize_liftAt (add_le_add_right hmn 1), castSucc]
#align first_order.language.bounded_formula.realize_lift_at_one FirstOrder.Language.BoundedFormula.realize_liftAt_one
@[simp]
theorem realize_liftAt_one_self {n : ℕ} {φ : L.BoundedFormula α n} {v : α → M}
{xs : Fin (n + 1) → M} : (φ.liftAt 1 n).Realize v xs ↔ φ.Realize v (xs ∘ castSucc) := by
rw [realize_liftAt_one (refl n), iff_eq_eq]
refine congr rfl (congr rfl (funext fun i => ?_))
rw [if_pos i.is_lt]
#align first_order.language.bounded_formula.realize_lift_at_one_self FirstOrder.Language.BoundedFormula.realize_liftAt_one_self
@[simp]
theorem realize_subst {φ : L.BoundedFormula α n} {tf : α → L.Term β} {v : β → M} {xs : Fin n → M} :
(φ.subst tf).Realize v xs ↔ φ.Realize (fun a => (tf a).realize v) xs :=
realize_mapTermRel_id
(fun n t x => by
rw [Term.realize_subst]
rcongr a
cases a
· simp only [Sum.elim_inl, Function.comp_apply, Term.realize_relabel, Sum.elim_comp_inl]
· rfl)
(by simp)
#align first_order.language.bounded_formula.realize_subst FirstOrder.Language.BoundedFormula.realize_subst
@[simp]
theorem realize_restrictFreeVar [DecidableEq α] {n : ℕ} {φ : L.BoundedFormula α n} {s : Set α}
(h : ↑φ.freeVarFinset ⊆ s) {v : α → M} {xs : Fin n → M} :
(φ.restrictFreeVar (Set.inclusion h)).Realize (v ∘ (↑)) xs ↔ φ.Realize v xs := by
induction' φ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 _ _ ih3
· rfl
· simp [restrictFreeVar, Realize]
· simp [restrictFreeVar, Realize]
· simp [restrictFreeVar, Realize, ih1, ih2]
· simp [restrictFreeVar, Realize, ih3]
#align first_order.language.bounded_formula.realize_restrict_free_var FirstOrder.Language.BoundedFormula.realize_restrictFreeVar
theorem realize_constantsVarsEquiv [L[[α]].Structure M] [(lhomWithConstants L α).IsExpansionOn M]
{n} {φ : L[[α]].BoundedFormula β n} {v : β → M} {xs : Fin n → M} :
(constantsVarsEquiv φ).Realize (Sum.elim (fun a => ↑(L.con a)) v) xs ↔ φ.Realize v xs := by
refine realize_mapTermRel_id (fun n t xs => realize_constantsVarsEquivLeft) fun n R xs => ?_
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [← (lhomWithConstants L α).map_onRelation
(Equiv.sumEmpty (L.Relations n) ((constantsOn α).Relations n) R) xs]
rcongr
cases' R with R R
· simp
· exact isEmptyElim R
#align first_order.language.bounded_formula.realize_constants_vars_equiv FirstOrder.Language.BoundedFormula.realize_constantsVarsEquiv
@[simp]
theorem realize_relabelEquiv {g : α ≃ β} {k} {φ : L.BoundedFormula α k} {v : β → M}
{xs : Fin k → M} : (relabelEquiv g φ).Realize v xs ↔ φ.Realize (v ∘ g) xs := by
simp only [relabelEquiv, mapTermRelEquiv_apply, Equiv.coe_refl]
refine realize_mapTermRel_id (fun n t xs => ?_) fun _ _ _ => rfl
simp only [relabelEquiv_apply, Term.realize_relabel]
refine congr (congr rfl ?_) rfl
ext (i | i) <;> rfl
#align first_order.language.bounded_formula.realize_relabel_equiv FirstOrder.Language.BoundedFormula.realize_relabelEquiv
variable [Nonempty M]
theorem realize_all_liftAt_one_self {n : ℕ} {φ : L.BoundedFormula α n} {v : α → M}
{xs : Fin n → M} : (φ.liftAt 1 n).all.Realize v xs ↔ φ.Realize v xs := by
inhabit M
simp only [realize_all, realize_liftAt_one_self]
refine ⟨fun h => ?_, fun h a => ?_⟩
· refine (congr rfl (funext fun i => ?_)).mp (h default)
simp
· refine (congr rfl (funext fun i => ?_)).mp h
simp
#align first_order.language.bounded_formula.realize_all_lift_at_one_self FirstOrder.Language.BoundedFormula.realize_all_liftAt_one_self
theorem realize_toPrenexImpRight {φ ψ : L.BoundedFormula α n} (hφ : IsQF φ) (hψ : IsPrenex ψ)
{v : α → M} {xs : Fin n → M} :
(φ.toPrenexImpRight ψ).Realize v xs ↔ (φ.imp ψ).Realize v xs := by
induction' hψ with _ _ hψ _ _ _hψ ih _ _ _hψ ih
· rw [hψ.toPrenexImpRight]
· refine _root_.trans (forall_congr' fun _ => ih hφ.liftAt) ?_
simp only [realize_imp, realize_liftAt_one_self, snoc_comp_castSucc, realize_all]
exact ⟨fun h1 a h2 => h1 h2 a, fun h1 h2 a => h1 a h2⟩
· unfold toPrenexImpRight
rw [realize_ex]
refine _root_.trans (exists_congr fun _ => ih hφ.liftAt) ?_
simp only [realize_imp, realize_liftAt_one_self, snoc_comp_castSucc, realize_ex]
refine ⟨?_, fun h' => ?_⟩
· rintro ⟨a, ha⟩ h
exact ⟨a, ha h⟩
· by_cases h : φ.Realize v xs
· obtain ⟨a, ha⟩ := h' h
exact ⟨a, fun _ => ha⟩
· inhabit M
exact ⟨default, fun h'' => (h h'').elim⟩
#align first_order.language.bounded_formula.realize_to_prenex_imp_right FirstOrder.Language.BoundedFormula.realize_toPrenexImpRight
theorem realize_toPrenexImp {φ ψ : L.BoundedFormula α n} (hφ : IsPrenex φ) (hψ : IsPrenex ψ)
{v : α → M} {xs : Fin n → M} : (φ.toPrenexImp ψ).Realize v xs ↔ (φ.imp ψ).Realize v xs := by
revert ψ
induction' hφ with _ _ hφ _ _ _hφ ih _ _ _hφ ih <;> intro ψ hψ
· rw [hφ.toPrenexImp]
exact realize_toPrenexImpRight hφ hψ
· unfold toPrenexImp
rw [realize_ex]
refine _root_.trans (exists_congr fun _ => ih hψ.liftAt) ?_
simp only [realize_imp, realize_liftAt_one_self, snoc_comp_castSucc, realize_all]
refine ⟨?_, fun h' => ?_⟩
· rintro ⟨a, ha⟩ h
exact ha (h a)
· by_cases h : ψ.Realize v xs
· inhabit M
exact ⟨default, fun _h'' => h⟩
· obtain ⟨a, ha⟩ := not_forall.1 (h ∘ h')
exact ⟨a, fun h => (ha h).elim⟩
· refine _root_.trans (forall_congr' fun _ => ih hψ.liftAt) ?_
simp
#align first_order.language.bounded_formula.realize_to_prenex_imp FirstOrder.Language.BoundedFormula.realize_toPrenexImp
@[simp]
theorem realize_toPrenex (φ : L.BoundedFormula α n) {v : α → M} :
∀ {xs : Fin n → M}, φ.toPrenex.Realize v xs ↔ φ.Realize v xs := by
induction' φ with _ _ _ _ _ _ _ _ _ f1 f2 h1 h2 _ _ h
· exact Iff.rfl
· exact Iff.rfl
· exact Iff.rfl
· intros
rw [toPrenex, realize_toPrenexImp f1.toPrenex_isPrenex f2.toPrenex_isPrenex, realize_imp,
realize_imp, h1, h2]
· intros
rw [realize_all, toPrenex, realize_all]
exact forall_congr' fun a => h
#align first_order.language.bounded_formula.realize_to_prenex FirstOrder.Language.BoundedFormula.realize_toPrenex
end BoundedFormula
-- Porting note: no `protected` attribute in Lean4
-- attribute [protected] bounded_formula.falsum bounded_formula.equal bounded_formula.rel
-- attribute [protected] bounded_formula.imp bounded_formula.all
namespace LHom
open BoundedFormula
@[simp]
theorem realize_onBoundedFormula [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M] {n : ℕ}
(ψ : L.BoundedFormula α n) {v : α → M} {xs : Fin n → M} :
(φ.onBoundedFormula ψ).Realize v xs ↔ ψ.Realize v xs := by
induction' ψ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 _ _ ih3
· rfl
· simp only [onBoundedFormula, realize_bdEqual, realize_onTerm]
rfl
· simp only [onBoundedFormula, realize_rel, LHom.map_onRelation,
Function.comp_apply, realize_onTerm]
rfl
· simp only [onBoundedFormula, ih1, ih2, realize_imp]
· simp only [onBoundedFormula, ih3, realize_all]
set_option linter.uppercaseLean3 false in
#align first_order.language.Lhom.realize_on_bounded_formula FirstOrder.Language.LHom.realize_onBoundedFormula
end LHom
-- Porting note: no `protected` attribute in Lean4
-- attribute [protected] bounded_formula.falsum bounded_formula.equal bounded_formula.rel
-- attribute [protected] bounded_formula.imp bounded_formula.all
namespace Formula
/-- A formula can be evaluated as true or false by giving values to each free variable. -/
nonrec def Realize (φ : L.Formula α) (v : α → M) : Prop :=
φ.Realize v default
#align first_order.language.formula.realize FirstOrder.Language.Formula.Realize
variable {φ ψ : L.Formula α} {v : α → M}
@[simp]
theorem realize_not : φ.not.Realize v ↔ ¬φ.Realize v :=
Iff.rfl
#align first_order.language.formula.realize_not FirstOrder.Language.Formula.realize_not
@[simp]
theorem realize_bot : (⊥ : L.Formula α).Realize v ↔ False :=
Iff.rfl
#align first_order.language.formula.realize_bot FirstOrder.Language.Formula.realize_bot
@[simp]
theorem realize_top : (⊤ : L.Formula α).Realize v ↔ True :=
BoundedFormula.realize_top
#align first_order.language.formula.realize_top FirstOrder.Language.Formula.realize_top
@[simp]
theorem realize_inf : (φ ⊓ ψ).Realize v ↔ φ.Realize v ∧ ψ.Realize v :=
BoundedFormula.realize_inf
#align first_order.language.formula.realize_inf FirstOrder.Language.Formula.realize_inf
@[simp]
theorem realize_imp : (φ.imp ψ).Realize v ↔ φ.Realize v → ψ.Realize v :=
BoundedFormula.realize_imp
#align first_order.language.formula.realize_imp FirstOrder.Language.Formula.realize_imp
@[simp]
theorem realize_rel {k : ℕ} {R : L.Relations k} {ts : Fin k → L.Term α} :
(R.formula ts).Realize v ↔ RelMap R fun i => (ts i).realize v :=
BoundedFormula.realize_rel.trans (by simp)
#align first_order.language.formula.realize_rel FirstOrder.Language.Formula.realize_rel
@[simp]
theorem realize_rel₁ {R : L.Relations 1} {t : L.Term _} :
(R.formula₁ t).Realize v ↔ RelMap R ![t.realize v] := by
rw [Relations.formula₁, realize_rel, iff_eq_eq]
refine congr rfl (funext fun _ => ?_)
simp only [Matrix.cons_val_fin_one]
#align first_order.language.formula.realize_rel₁ FirstOrder.Language.Formula.realize_rel₁
@[simp]
theorem realize_rel₂ {R : L.Relations 2} {t₁ t₂ : L.Term _} :
(R.formula₂ t₁ t₂).Realize v ↔ RelMap R ![t₁.realize v, t₂.realize v] := by
rw [Relations.formula₂, realize_rel, iff_eq_eq]
refine congr rfl (funext (Fin.cases ?_ ?_))
· simp only [Matrix.cons_val_zero]
· simp only [Matrix.cons_val_succ, Matrix.cons_val_fin_one, forall_const]
#align first_order.language.formula.realize_rel₂ FirstOrder.Language.Formula.realize_rel₂
@[simp]
theorem realize_sup : (φ ⊔ ψ).Realize v ↔ φ.Realize v ∨ ψ.Realize v :=
BoundedFormula.realize_sup
#align first_order.language.formula.realize_sup FirstOrder.Language.Formula.realize_sup
@[simp]
theorem realize_iff : (φ.iff ψ).Realize v ↔ (φ.Realize v ↔ ψ.Realize v) :=
BoundedFormula.realize_iff
#align first_order.language.formula.realize_iff FirstOrder.Language.Formula.realize_iff
@[simp]
theorem realize_relabel {φ : L.Formula α} {g : α → β} {v : β → M} :
(φ.relabel g).Realize v ↔ φ.Realize (v ∘ g) := by
rw [Realize, Realize, relabel, BoundedFormula.realize_relabel, iff_eq_eq, Fin.castAdd_zero]
exact congr rfl (funext finZeroElim)
#align first_order.language.formula.realize_relabel FirstOrder.Language.Formula.realize_relabel
theorem realize_relabel_sum_inr (φ : L.Formula (Fin n)) {v : Empty → M} {x : Fin n → M} :
(BoundedFormula.relabel Sum.inr φ).Realize v x ↔ φ.Realize x := by
rw [BoundedFormula.realize_relabel, Formula.Realize, Sum.elim_comp_inr, Fin.castAdd_zero,
cast_refl, Function.comp_id,
Subsingleton.elim (x ∘ (natAdd n : Fin 0 → Fin n)) default]
#align first_order.language.formula.realize_relabel_sum_inr FirstOrder.Language.Formula.realize_relabel_sum_inr
@[simp]
theorem realize_equal {t₁ t₂ : L.Term α} {x : α → M} :
(t₁.equal t₂).Realize x ↔ t₁.realize x = t₂.realize x := by simp [Term.equal, Realize]
#align first_order.language.formula.realize_equal FirstOrder.Language.Formula.realize_equal
@[simp]
theorem realize_graph {f : L.Functions n} {x : Fin n → M} {y : M} :
(Formula.graph f).Realize (Fin.cons y x : _ → M) ↔ funMap f x = y := by
simp only [Formula.graph, Term.realize, realize_equal, Fin.cons_zero, Fin.cons_succ]
rw [eq_comm]
#align first_order.language.formula.realize_graph FirstOrder.Language.Formula.realize_graph
end Formula
@[simp]
theorem LHom.realize_onFormula [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M] (ψ : L.Formula α)
{v : α → M} : (φ.onFormula ψ).Realize v ↔ ψ.Realize v :=
φ.realize_onBoundedFormula ψ
set_option linter.uppercaseLean3 false in
#align first_order.language.Lhom.realize_on_formula FirstOrder.Language.LHom.realize_onFormula
@[simp]
theorem LHom.setOf_realize_onFormula [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M]
(ψ : L.Formula α) : (setOf (φ.onFormula ψ).Realize : Set (α → M)) = setOf ψ.Realize := by
ext
simp
set_option linter.uppercaseLean3 false in
#align first_order.language.Lhom.set_of_realize_on_formula FirstOrder.Language.LHom.setOf_realize_onFormula
variable (M)
/-- A sentence can be evaluated as true or false in a structure. -/
nonrec def Sentence.Realize (φ : L.Sentence) : Prop :=
φ.Realize (default : _ → M)
#align first_order.language.sentence.realize FirstOrder.Language.Sentence.Realize
-- input using \|= or \vDash, but not using \models
@[inherit_doc Sentence.Realize]
infixl:51 " ⊨ " => Sentence.Realize
@[simp]
theorem Sentence.realize_not {φ : L.Sentence} : M ⊨ φ.not ↔ ¬M ⊨ φ :=
Iff.rfl
#align first_order.language.sentence.realize_not FirstOrder.Language.Sentence.realize_not
namespace Formula
@[simp]
theorem realize_equivSentence_symm_con [L[[α]].Structure M]
[(L.lhomWithConstants α).IsExpansionOn M] (φ : L[[α]].Sentence) :
((equivSentence.symm φ).Realize fun a => (L.con a : M)) ↔ φ.Realize M := by
simp only [equivSentence, _root_.Equiv.symm_symm, Equiv.coe_trans, Realize,
BoundedFormula.realize_relabelEquiv, Function.comp]
refine _root_.trans ?_ BoundedFormula.realize_constantsVarsEquiv
rw [iff_iff_eq]
congr with (_ | a)
· simp
· cases a
#align first_order.language.formula.realize_equiv_sentence_symm_con FirstOrder.Language.Formula.realize_equivSentence_symm_con
@[simp]
theorem realize_equivSentence [L[[α]].Structure M] [(L.lhomWithConstants α).IsExpansionOn M]
(φ : L.Formula α) : (equivSentence φ).Realize M ↔ φ.Realize fun a => (L.con a : M) := by
rw [← realize_equivSentence_symm_con M (equivSentence φ), _root_.Equiv.symm_apply_apply]
#align first_order.language.formula.realize_equiv_sentence FirstOrder.Language.Formula.realize_equivSentence
theorem realize_equivSentence_symm (φ : L[[α]].Sentence) (v : α → M) :
(equivSentence.symm φ).Realize v ↔
@Sentence.Realize _ M (@Language.withConstantsStructure L M _ α (constantsOn.structure v))
φ :=
letI := constantsOn.structure v
realize_equivSentence_symm_con M φ
#align first_order.language.formula.realize_equiv_sentence_symm FirstOrder.Language.Formula.realize_equivSentence_symm
end Formula
@[simp]
theorem LHom.realize_onSentence [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M]
(ψ : L.Sentence) : M ⊨ φ.onSentence ψ ↔ M ⊨ ψ :=
φ.realize_onFormula ψ
set_option linter.uppercaseLean3 false in
#align first_order.language.Lhom.realize_on_sentence FirstOrder.Language.LHom.realize_onSentence
variable (L)
/-- The complete theory of a structure `M` is the set of all sentences `M` satisfies. -/
def completeTheory : L.Theory :=
{ φ | M ⊨ φ }
#align first_order.language.complete_theory FirstOrder.Language.completeTheory
variable (N)
/-- Two structures are elementarily equivalent when they satisfy the same sentences. -/
def ElementarilyEquivalent : Prop :=
L.completeTheory M = L.completeTheory N
#align first_order.language.elementarily_equivalent FirstOrder.Language.ElementarilyEquivalent
@[inherit_doc FirstOrder.Language.ElementarilyEquivalent]
scoped[FirstOrder]
notation:25 A " ≅[" L "] " B:50 => FirstOrder.Language.ElementarilyEquivalent L A B
variable {L} {M} {N}
@[simp]
theorem mem_completeTheory {φ : Sentence L} : φ ∈ L.completeTheory M ↔ M ⊨ φ :=
Iff.rfl
#align first_order.language.mem_complete_theory FirstOrder.Language.mem_completeTheory
theorem elementarilyEquivalent_iff : M ≅[L] N ↔ ∀ φ : L.Sentence, M ⊨ φ ↔ N ⊨ φ := by
simp only [ElementarilyEquivalent, Set.ext_iff, completeTheory, Set.mem_setOf_eq]
#align first_order.language.elementarily_equivalent_iff FirstOrder.Language.elementarilyEquivalent_iff
variable (M)
/-- A model of a theory is a structure in which every sentence is realized as true. -/
class Theory.Model (T : L.Theory) : Prop where
realize_of_mem : ∀ φ ∈ T, M ⊨ φ
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.model FirstOrder.Language.Theory.Model
-- input using \|= or \vDash, but not using \models
@[inherit_doc Theory.Model]
infixl:51 " ⊨ " => Theory.Model
variable {M} (T : L.Theory)
@[simp default-10]
theorem Theory.model_iff : M ⊨ T ↔ ∀ φ ∈ T, M ⊨ φ :=
⟨fun h => h.realize_of_mem, fun h => ⟨h⟩⟩
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.model_iff FirstOrder.Language.Theory.model_iff
theorem Theory.realize_sentence_of_mem [M ⊨ T] {φ : L.Sentence} (h : φ ∈ T) : M ⊨ φ :=
Theory.Model.realize_of_mem φ h
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.realize_sentence_of_mem FirstOrder.Language.Theory.realize_sentence_of_mem
@[simp]
theorem LHom.onTheory_model [L'.Structure M] (φ : L →ᴸ L') [φ.IsExpansionOn M] (T : L.Theory) :
M ⊨ φ.onTheory T ↔ M ⊨ T := by simp [Theory.model_iff, LHom.onTheory]
set_option linter.uppercaseLean3 false in
#align first_order.language.Lhom.on_Theory_model FirstOrder.Language.LHom.onTheory_model
variable {T}
instance model_empty : M ⊨ (∅ : L.Theory) :=
⟨fun φ hφ => (Set.not_mem_empty φ hφ).elim⟩
#align first_order.language.model_empty FirstOrder.Language.model_empty
namespace Theory
theorem Model.mono {T' : L.Theory} (_h : M ⊨ T') (hs : T ⊆ T') : M ⊨ T :=
⟨fun _φ hφ => T'.realize_sentence_of_mem (hs hφ)⟩
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.model.mono FirstOrder.Language.Theory.Model.mono
theorem Model.union {T' : L.Theory} (h : M ⊨ T) (h' : M ⊨ T') : M ⊨ T ∪ T' := by
simp only [model_iff, Set.mem_union] at *
exact fun φ hφ => hφ.elim (h _) (h' _)
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.model.union FirstOrder.Language.Theory.Model.union
@[simp]
theorem model_union_iff {T' : L.Theory} : M ⊨ T ∪ T' ↔ M ⊨ T ∧ M ⊨ T' :=
⟨fun h => ⟨h.mono Set.subset_union_left, h.mono Set.subset_union_right⟩, fun h =>
h.1.union h.2⟩
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.model_union_iff FirstOrder.Language.Theory.model_union_iff
theorem model_singleton_iff {φ : L.Sentence} : M ⊨ ({φ} : L.Theory) ↔ M ⊨ φ := by simp
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.model_singleton_iff FirstOrder.Language.Theory.model_singleton_iff
theorem model_iff_subset_completeTheory : M ⊨ T ↔ T ⊆ L.completeTheory M :=
T.model_iff
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.model_iff_subset_complete_theory FirstOrder.Language.Theory.model_iff_subset_completeTheory
theorem completeTheory.subset [MT : M ⊨ T] : T ⊆ L.completeTheory M :=
model_iff_subset_completeTheory.1 MT
set_option linter.uppercaseLean3 false in
#align first_order.language.Theory.complete_theory.subset FirstOrder.Language.Theory.completeTheory.subset
end Theory
instance model_completeTheory : M ⊨ L.completeTheory M :=
Theory.model_iff_subset_completeTheory.2 (subset_refl _)
#align first_order.language.model_complete_theory FirstOrder.Language.model_completeTheory
variable (M N)
theorem realize_iff_of_model_completeTheory [N ⊨ L.completeTheory M] (φ : L.Sentence) :
N ⊨ φ ↔ M ⊨ φ := by
refine ⟨fun h => ?_, (L.completeTheory M).realize_sentence_of_mem⟩
contrapose! h
rw [← Sentence.realize_not] at *
exact (L.completeTheory M).realize_sentence_of_mem (mem_completeTheory.2 h)
#align first_order.language.realize_iff_of_model_complete_theory FirstOrder.Language.realize_iff_of_model_completeTheory
variable {M N}
namespace BoundedFormula
@[simp]
theorem realize_alls {φ : L.BoundedFormula α n} {v : α → M} :
φ.alls.Realize v ↔ ∀ xs : Fin n → M, φ.Realize v xs := by
induction' n with n ih
· exact Unique.forall_iff.symm
· simp only [alls, ih, Realize]
exact ⟨fun h xs => Fin.snoc_init_self xs ▸ h _ _, fun h xs x => h (Fin.snoc xs x)⟩
#align first_order.language.bounded_formula.realize_alls FirstOrder.Language.BoundedFormula.realize_alls
@[simp]
theorem realize_exs {φ : L.BoundedFormula α n} {v : α → M} :
φ.exs.Realize v ↔ ∃ xs : Fin n → M, φ.Realize v xs := by
induction' n with n ih
· exact Unique.exists_iff.symm
· simp only [BoundedFormula.exs, ih, realize_ex]
constructor
· rintro ⟨xs, x, h⟩
exact ⟨_, h⟩
· rintro ⟨xs, h⟩
rw [← Fin.snoc_init_self xs] at h
exact ⟨_, _, h⟩
#align first_order.language.bounded_formula.realize_exs FirstOrder.Language.BoundedFormula.realize_exs
@[simp]
theorem _root_.FirstOrder.Language.Formula.realize_iAlls
[Finite γ] {f : α → β ⊕ γ}
{φ : L.Formula α} {v : β → M} : (φ.iAlls f).Realize v ↔
∀ (i : γ → M), φ.Realize (fun a => Sum.elim v i (f a)) := by
let e := Classical.choice (Classical.choose_spec (Finite.exists_equiv_fin γ))
rw [Formula.iAlls]
simp only [Nat.add_zero, realize_alls, realize_relabel, Function.comp,
castAdd_zero, finCongr_refl, OrderIso.refl_apply, Sum.elim_map, id_eq]
refine Equiv.forall_congr ?_ ?_
· exact ⟨fun v => v ∘ e, fun v => v ∘ e.symm,
fun _ => by simp [Function.comp],
fun _ => by simp [Function.comp]⟩
· intro x
rw [Formula.Realize, iff_iff_eq]
congr
funext i
exact i.elim0
@[simp]
theorem realize_iAlls [Finite γ] {f : α → β ⊕ γ}
{φ : L.Formula α} {v : β → M} {v' : Fin 0 → M} :
BoundedFormula.Realize (φ.iAlls f) v v' ↔
∀ (i : γ → M), φ.Realize (fun a => Sum.elim v i (f a)) := by
rw [← Formula.realize_iAlls, iff_iff_eq]; congr; simp [eq_iff_true_of_subsingleton]
@[simp]
theorem _root_.FirstOrder.Language.Formula.realize_iExs
[Finite γ] {f : α → β ⊕ γ}
{φ : L.Formula α} {v : β → M} : (φ.iExs f).Realize v ↔
∃ (i : γ → M), φ.Realize (fun a => Sum.elim v i (f a)) := by
let e := Classical.choice (Classical.choose_spec (Finite.exists_equiv_fin γ))
rw [Formula.iExs]
simp only [Nat.add_zero, realize_exs, realize_relabel, Function.comp,
castAdd_zero, finCongr_refl, OrderIso.refl_apply, Sum.elim_map, id_eq]
rw [← not_iff_not, not_exists, not_exists]
refine Equiv.forall_congr ?_ ?_
· exact ⟨fun v => v ∘ e, fun v => v ∘ e.symm,
fun _ => by simp [Function.comp],
fun _ => by simp [Function.comp]⟩
· intro x
rw [Formula.Realize, iff_iff_eq]
congr
funext i
exact i.elim0
@[simp]
theorem realize_iExs [Finite γ] {f : α → β ⊕ γ}
{φ : L.Formula α} {v : β → M} {v' : Fin 0 → M} :
BoundedFormula.Realize (φ.iExs f) v v' ↔
∃ (i : γ → M), φ.Realize (fun a => Sum.elim v i (f a)) := by
rw [← Formula.realize_iExs, iff_iff_eq]; congr; simp [eq_iff_true_of_subsingleton]
@[simp]
theorem realize_toFormula (φ : L.BoundedFormula α n) (v : Sum α (Fin n) → M) :
φ.toFormula.Realize v ↔ φ.Realize (v ∘ Sum.inl) (v ∘ Sum.inr) := by
induction' φ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 _ _ ih3 a8 a9 a0
· rfl
· simp [BoundedFormula.Realize]
· simp [BoundedFormula.Realize]
· rw [toFormula, Formula.Realize, realize_imp, ← Formula.Realize, ih1, ← Formula.Realize, ih2,
realize_imp]
· rw [toFormula, Formula.Realize, realize_all, realize_all]
refine forall_congr' fun a => ?_
have h := ih3 (Sum.elim (v ∘ Sum.inl) (snoc (v ∘ Sum.inr) a))
simp only [Sum.elim_comp_inl, Sum.elim_comp_inr] at h
rw [← h, realize_relabel, Formula.Realize, iff_iff_eq]
simp only [Function.comp]
congr with x
· cases' x with _ x
· simp
· refine Fin.lastCases ?_ ?_ x
· rw [Sum.elim_inr, Sum.elim_inr,
finSumFinEquiv_symm_last, Sum.map_inr, Sum.elim_inr]
simp [Fin.snoc]
· simp only [castSucc, Function.comp_apply, Sum.elim_inr,
finSumFinEquiv_symm_apply_castAdd, Sum.map_inl, Sum.elim_inl]
rw [← castSucc]
simp
· exact Fin.elim0 x
#align first_order.language.bounded_formula.realize_to_formula FirstOrder.Language.BoundedFormula.realize_toFormula
@[simp]
theorem realize_iSup (s : Finset β) (f : β → L.BoundedFormula α n)
(v : α → M) (v' : Fin n → M) :
(iSup s f).Realize v v' ↔ ∃ b ∈ s, (f b).Realize v v' := by
simp only [iSup, realize_foldr_sup, List.mem_map, Finset.mem_toList,
exists_exists_and_eq_and]
@[simp]
theorem realize_iInf (s : Finset β) (f : β → L.BoundedFormula α n)
(v : α → M) (v' : Fin n → M) :
(iInf s f).Realize v v' ↔ ∀ b ∈ s, (f b).Realize v v' := by
simp only [iInf, realize_foldr_inf, List.mem_map, Finset.mem_toList,
forall_exists_index, and_imp, forall_apply_eq_imp_iff₂]
end BoundedFormula
namespace Equiv
@[simp]
theorem realize_boundedFormula (g : M ≃[L] N) (φ : L.BoundedFormula α n) {v : α → M}
{xs : Fin n → M} : φ.Realize (g ∘ v) (g ∘ xs) ↔ φ.Realize v xs := by
induction' φ with _ _ _ _ _ _ _ _ _ _ _ ih1 ih2 _ _ ih3
· rfl
· simp only [BoundedFormula.Realize, ← Sum.comp_elim, Equiv.realize_term, g.injective.eq_iff]
· simp only [BoundedFormula.Realize, ← Sum.comp_elim, Equiv.realize_term]
exact g.map_rel _ _
· rw [BoundedFormula.Realize, ih1, ih2, BoundedFormula.Realize]
· rw [BoundedFormula.Realize, BoundedFormula.Realize]
constructor
· intro h a
have h' := h (g a)
rw [← Fin.comp_snoc, ih3] at h'
exact h'
· intro h a
have h' := h (g.symm a)
rw [← ih3, Fin.comp_snoc, g.apply_symm_apply] at h'
exact h'
#align first_order.language.equiv.realize_bounded_formula FirstOrder.Language.Equiv.realize_boundedFormula
@[simp]
theorem realize_formula (g : M ≃[L] N) (φ : L.Formula α) {v : α → M} :
φ.Realize (g ∘ v) ↔ φ.Realize v := by
rw [Formula.Realize, Formula.Realize, ← g.realize_boundedFormula φ, iff_eq_eq,
Unique.eq_default (g ∘ default)]
#align first_order.language.equiv.realize_formula FirstOrder.Language.Equiv.realize_formula
theorem realize_sentence (g : M ≃[L] N) (φ : L.Sentence) : M ⊨ φ ↔ N ⊨ φ := by
rw [Sentence.Realize, Sentence.Realize, ← g.realize_formula, Unique.eq_default (g ∘ default)]
#align first_order.language.equiv.realize_sentence FirstOrder.Language.Equiv.realize_sentence
theorem theory_model (g : M ≃[L] N) [M ⊨ T] : N ⊨ T :=
⟨fun φ hφ => (g.realize_sentence φ).1 (Theory.realize_sentence_of_mem T hφ)⟩
set_option linter.uppercaseLean3 false in
#align first_order.language.equiv.Theory_model FirstOrder.Language.Equiv.theory_model
theorem elementarilyEquivalent (g : M ≃[L] N) : M ≅[L] N :=
elementarilyEquivalent_iff.2 g.realize_sentence
#align first_order.language.equiv.elementarily_equivalent FirstOrder.Language.Equiv.elementarilyEquivalent
end Equiv
namespace Relations
open BoundedFormula
variable {r : L.Relations 2}
@[simp]
theorem realize_reflexive : M ⊨ r.reflexive ↔ Reflexive fun x y : M => RelMap r ![x, y] :=
forall_congr' fun _ => realize_rel₂
#align first_order.language.relations.realize_reflexive FirstOrder.Language.Relations.realize_reflexive
@[simp]
theorem realize_irreflexive : M ⊨ r.irreflexive ↔ Irreflexive fun x y : M => RelMap r ![x, y] :=
forall_congr' fun _ => not_congr realize_rel₂
#align first_order.language.relations.realize_irreflexive FirstOrder.Language.Relations.realize_irreflexive
@[simp]
theorem realize_symmetric : M ⊨ r.symmetric ↔ Symmetric fun x y : M => RelMap r ![x, y] :=
forall_congr' fun _ => forall_congr' fun _ => imp_congr realize_rel₂ realize_rel₂
#align first_order.language.relations.realize_symmetric FirstOrder.Language.Relations.realize_symmetric
@[simp]
theorem realize_antisymmetric :
M ⊨ r.antisymmetric ↔ AntiSymmetric fun x y : M => RelMap r ![x, y] :=
forall_congr' fun _ =>
forall_congr' fun _ => imp_congr realize_rel₂ (imp_congr realize_rel₂ Iff.rfl)
#align first_order.language.relations.realize_antisymmetric FirstOrder.Language.Relations.realize_antisymmetric
@[simp]
theorem realize_transitive : M ⊨ r.transitive ↔ Transitive fun x y : M => RelMap r ![x, y] :=
forall_congr' fun _ =>
forall_congr' fun _ =>
forall_congr' fun _ => imp_congr realize_rel₂ (imp_congr realize_rel₂ realize_rel₂)
#align first_order.language.relations.realize_transitive FirstOrder.Language.Relations.realize_transitive
@[simp]
theorem realize_total : M ⊨ r.total ↔ Total fun x y : M => RelMap r ![x, y] :=
forall_congr' fun _ =>
forall_congr' fun _ => realize_sup.trans (or_congr realize_rel₂ realize_rel₂)
#align first_order.language.relations.realize_total FirstOrder.Language.Relations.realize_total
end Relations
section Cardinality
variable (L)
@[simp]
theorem Sentence.realize_cardGe (n) : M ⊨ Sentence.cardGe L n ↔ ↑n ≤ #M := by
rw [← lift_mk_fin, ← lift_le.{0}, lift_lift, lift_mk_le, Sentence.cardGe, Sentence.Realize,
BoundedFormula.realize_exs]
simp_rw [BoundedFormula.realize_foldr_inf]
simp only [Function.comp_apply, List.mem_map, Prod.exists, Ne, List.mem_product,
List.mem_finRange, forall_exists_index, and_imp, List.mem_filter, true_and_iff]
refine ⟨?_, fun xs => ⟨xs.some, ?_⟩⟩
· rintro ⟨xs, h⟩
refine ⟨⟨xs, fun i j ij => ?_⟩⟩
contrapose! ij
have hij := h _ i j (by simpa using ij) rfl
simp only [BoundedFormula.realize_not, Term.realize, BoundedFormula.realize_bdEqual,
Sum.elim_inr] at hij
exact hij
· rintro _ i j ij rfl
simpa using ij
#align first_order.language.sentence.realize_card_ge FirstOrder.Language.Sentence.realize_cardGe
@[simp]
theorem model_infiniteTheory_iff : M ⊨ L.infiniteTheory ↔ Infinite M := by
simp [infiniteTheory, infinite_iff, aleph0_le]
#align first_order.language.model_infinite_theory_iff FirstOrder.Language.model_infiniteTheory_iff
instance model_infiniteTheory [h : Infinite M] : M ⊨ L.infiniteTheory :=
L.model_infiniteTheory_iff.2 h
#align first_order.language.model_infinite_theory FirstOrder.Language.model_infiniteTheory
@[simp]
theorem model_nonemptyTheory_iff : M ⊨ L.nonemptyTheory ↔ Nonempty M := by
simp only [nonemptyTheory, Theory.model_iff, Set.mem_singleton_iff, forall_eq,
Sentence.realize_cardGe, Nat.cast_one, one_le_iff_ne_zero, mk_ne_zero_iff]
#align first_order.language.model_nonempty_theory_iff FirstOrder.Language.model_nonemptyTheory_iff
instance model_nonempty [h : Nonempty M] : M ⊨ L.nonemptyTheory :=
L.model_nonemptyTheory_iff.2 h
#align first_order.language.model_nonempty FirstOrder.Language.model_nonempty
theorem model_distinctConstantsTheory {M : Type w} [L[[α]].Structure M] (s : Set α) :
M ⊨ L.distinctConstantsTheory s ↔ Set.InjOn (fun i : α => (L.con i : M)) s := by
simp only [distinctConstantsTheory, Theory.model_iff, Set.mem_image, Set.mem_inter,
Set.mem_prod, Set.mem_compl, Prod.exists, forall_exists_index, and_imp]
refine ⟨fun h a as b bs ab => ?_, ?_⟩
· contrapose! ab
have h' := h _ a b ⟨⟨as, bs⟩, ab⟩ rfl
simp only [Sentence.Realize, Formula.realize_not, Formula.realize_equal,
Term.realize_constants] at h'
exact h'
· rintro h φ a b ⟨⟨as, bs⟩, ab⟩ rfl
simp only [Sentence.Realize, Formula.realize_not, Formula.realize_equal, Term.realize_constants]
exact fun contra => ab (h as bs contra)
#align first_order.language.model_distinct_constants_theory FirstOrder.Language.model_distinctConstantsTheory
theorem card_le_of_model_distinctConstantsTheory (s : Set α) (M : Type w) [L[[α]].Structure M]
[h : M ⊨ L.distinctConstantsTheory s] : Cardinal.lift.{w} #s ≤ Cardinal.lift.{u'} #M :=
lift_mk_le'.2 ⟨⟨_, Set.injOn_iff_injective.1 ((L.model_distinctConstantsTheory s).1 h)⟩⟩
#align first_order.language.card_le_of_model_distinct_constants_theory FirstOrder.Language.card_le_of_model_distinctConstantsTheory
end Cardinality
namespace ElementarilyEquivalent
@[symm]
nonrec theorem symm (h : M ≅[L] N) : N ≅[L] M :=
h.symm
#align first_order.language.elementarily_equivalent.symm FirstOrder.Language.ElementarilyEquivalent.symm
@[trans]
nonrec theorem trans (MN : M ≅[L] N) (NP : N ≅[L] P) : M ≅[L] P :=
MN.trans NP
#align first_order.language.elementarily_equivalent.trans FirstOrder.Language.ElementarilyEquivalent.trans
theorem completeTheory_eq (h : M ≅[L] N) : L.completeTheory M = L.completeTheory N :=
h
#align first_order.language.elementarily_equivalent.complete_theory_eq FirstOrder.Language.ElementarilyEquivalent.completeTheory_eq
theorem realize_sentence (h : M ≅[L] N) (φ : L.Sentence) : M ⊨ φ ↔ N ⊨ φ :=
(elementarilyEquivalent_iff.1 h) φ
#align first_order.language.elementarily_equivalent.realize_sentence FirstOrder.Language.ElementarilyEquivalent.realize_sentence
| Mathlib/ModelTheory/Semantics.lean | 1,179 | 1,181 | theorem theory_model_iff (h : M ≅[L] N) : M ⊨ T ↔ N ⊨ T := by |
rw [Theory.model_iff_subset_completeTheory, Theory.model_iff_subset_completeTheory,
h.completeTheory_eq]
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Antoine Chambert-Loir
-/
import Mathlib.Algebra.DirectSum.Finsupp
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.LinearAlgebra.DirectSum.TensorProduct
#align_import linear_algebra.direct_sum.finsupp from "leanprover-community/mathlib"@"9b9d125b7be0930f564a68f1d73ace10cf46064d"
/-!
# Results on finitely supported functions.
* `TensorProduct.finsuppLeft`, the tensor product of `ι →₀ M` and `N`
is linearly equivalent to `ι →₀ M ⊗[R] N`
* `TensorProduct.finsuppScalarLeft`, the tensor product of `ι →₀ R` and `N`
is linearly equivalent to `ι →₀ N`
* `TensorProduct.finsuppRight`, the tensor product of `M` and `ι →₀ N`
is linearly equivalent to `ι →₀ M ⊗[R] N`
* `TensorProduct.finsuppScalarRight`, the tensor product of `M` and `ι →₀ R`
is linearly equivalent to `ι →₀ N`
* `TensorProduct.finsuppLeft'`, if `M` is an `S`-module,
then the tensor product of `ι →₀ M` and `N` is `S`-linearly equivalent
to `ι →₀ M ⊗[R] N`
* `finsuppTensorFinsupp`, the tensor product of `ι →₀ M` and `κ →₀ N`
is linearly equivalent to `(ι × κ) →₀ (M ⊗ N)`.
## Case of MvPolynomial
These functions apply to `MvPolynomial`, one can define
```
noncomputable def MvPolynomial.rTensor' :
MvPolynomial σ S ⊗[R] N ≃ₗ[S] (σ →₀ ℕ) →₀ (S ⊗[R] N) :=
TensorProduct.finsuppLeft'
noncomputable def MvPolynomial.rTensor :
MvPolynomial σ R ⊗[R] N ≃ₗ[R] (σ →₀ ℕ) →₀ N :=
TensorProduct.finsuppScalarLeft
```
However, to be actually usable, these definitions need lemmas to be given in companion PR.
## Case of `Polynomial`
`Polynomial` is a structure containing a `Finsupp`, so these functions
can't be applied directly to `Polynomial`.
Some linear equivs need to be added to mathlib for that.
This belongs to a companion PR.
## TODO
* generalize to `MonoidAlgebra`, `AlgHom `
* reprove `TensorProduct.finsuppLeft'` using existing heterobasic version of `TensorProduct.congr`
-/
noncomputable section
open DirectSum TensorProduct
open Set LinearMap Submodule
section TensorProduct
variable (R : Type*) [CommSemiring R]
(M : Type*) [AddCommMonoid M] [Module R M]
(N : Type*) [AddCommMonoid N] [Module R N]
namespace TensorProduct
variable (ι : Type*) [DecidableEq ι]
/-- The tensor product of `ι →₀ M` and `N` is linearly equivalent to `ι →₀ M ⊗[R] N` -/
noncomputable def finsuppLeft :
(ι →₀ M) ⊗[R] N ≃ₗ[R] ι →₀ M ⊗[R] N :=
congr (finsuppLEquivDirectSum R M ι) (.refl R N) ≪≫ₗ
directSumLeft R (fun _ ↦ M) N ≪≫ₗ (finsuppLEquivDirectSum R _ ι).symm
variable {R M N ι}
lemma finsuppLeft_apply_tmul (p : ι →₀ M) (n : N) :
finsuppLeft R M N ι (p ⊗ₜ[R] n) = p.sum fun i m ↦ Finsupp.single i (m ⊗ₜ[R] n) := by
apply p.induction_linear
· simp
· intros f g hf hg; simp [add_tmul, map_add, hf, hg, Finsupp.sum_add_index]
· simp [finsuppLeft]
@[simp]
lemma finsuppLeft_apply_tmul_apply (p : ι →₀ M) (n : N) (i : ι) :
finsuppLeft R M N ι (p ⊗ₜ[R] n) i = p i ⊗ₜ[R] n := by
rw [finsuppLeft_apply_tmul, Finsupp.sum_apply,
Finsupp.sum_eq_single i (fun _ _ ↦ Finsupp.single_eq_of_ne) (by simp), Finsupp.single_eq_same]
theorem finsuppLeft_apply (t : (ι →₀ M) ⊗[R] N) (i : ι) :
finsuppLeft R M N ι t i = rTensor N (Finsupp.lapply i) t := by
induction t using TensorProduct.induction_on with
| zero => simp
| tmul f n => simp only [finsuppLeft_apply_tmul_apply, rTensor_tmul, Finsupp.lapply_apply]
| add x y hx hy => simp [map_add, hx, hy]
@[simp]
lemma finsuppLeft_symm_apply_single (i : ι) (m : M) (n : N) :
(finsuppLeft R M N ι).symm (Finsupp.single i (m ⊗ₜ[R] n)) =
Finsupp.single i m ⊗ₜ[R] n := by
simp [finsuppLeft, Finsupp.lsum]
variable (R M N ι)
/-- The tensor product of `M` and `ι →₀ N` is linearly equivalent to `ι →₀ M ⊗[R] N` -/
noncomputable def finsuppRight :
M ⊗[R] (ι →₀ N) ≃ₗ[R] ι →₀ M ⊗[R] N :=
congr (.refl R M) (finsuppLEquivDirectSum R N ι) ≪≫ₗ
directSumRight R M (fun _ : ι ↦ N) ≪≫ₗ (finsuppLEquivDirectSum R _ ι).symm
variable {R M N ι}
lemma finsuppRight_apply_tmul (m : M) (p : ι →₀ N) :
finsuppRight R M N ι (m ⊗ₜ[R] p) = p.sum fun i n ↦ Finsupp.single i (m ⊗ₜ[R] n) := by
apply p.induction_linear
· simp
· intros f g hf hg; simp [tmul_add, map_add, hf, hg, Finsupp.sum_add_index]
· simp [finsuppRight]
@[simp]
lemma finsuppRight_apply_tmul_apply (m : M) (p : ι →₀ N) (i : ι) :
finsuppRight R M N ι (m ⊗ₜ[R] p) i = m ⊗ₜ[R] p i := by
rw [finsuppRight_apply_tmul, Finsupp.sum_apply,
Finsupp.sum_eq_single i (fun _ _ ↦ Finsupp.single_eq_of_ne) (by simp), Finsupp.single_eq_same]
theorem finsuppRight_apply (t : M ⊗[R] (ι →₀ N)) (i : ι) :
finsuppRight R M N ι t i = lTensor M (Finsupp.lapply i) t := by
induction t using TensorProduct.induction_on with
| zero => simp
| tmul m f => simp [finsuppRight_apply_tmul_apply]
| add x y hx hy => simp [map_add, hx, hy]
@[simp]
lemma finsuppRight_symm_apply_single (i : ι) (m : M) (n : N) :
(finsuppRight R M N ι).symm (Finsupp.single i (m ⊗ₜ[R] n)) =
m ⊗ₜ[R] Finsupp.single i n := by
simp [finsuppRight, Finsupp.lsum]
variable {S : Type*} [CommSemiring S] [Algebra R S]
[Module S M] [IsScalarTower R S M]
lemma finsuppLeft_smul' (s : S) (t : (ι →₀ M) ⊗[R] N) :
finsuppLeft R M N ι (s • t) = s • finsuppLeft R M N ι t := by
induction t using TensorProduct.induction_on with
| zero => simp
| add x y hx hy => simp [hx, hy]
| tmul p n => ext; simp [smul_tmul', finsuppLeft_apply_tmul_apply]
variable (R M N ι S)
/-- When `M` is also an `S`-module, then `TensorProduct.finsuppLeft R M N``
is an `S`-linear equiv -/
noncomputable def finsuppLeft' :
(ι →₀ M) ⊗[R] N ≃ₗ[S] ι →₀ M ⊗[R] N where
__ := finsuppLeft R M N ι
map_smul' := finsuppLeft_smul'
variable {R M N ι S}
lemma finsuppLeft'_apply (x : (ι →₀ M) ⊗[R] N) :
finsuppLeft' R M N ι S x = finsuppLeft R M N ι x := rfl
/- -- TODO : reprove using the existing heterobasic lemmas
noncomputable example :
(ι →₀ M) ⊗[R] N ≃ₗ[S] ι →₀ (M ⊗[R] N) := by
have f : (⨁ (i₁ : ι), M) ⊗[R] N ≃ₗ[S] ⨁ (i : ι), M ⊗[R] N := sorry
exact (AlgebraTensorModule.congr
(finsuppLEquivDirectSum S M ι) (.refl R N)).trans
(f.trans (finsuppLEquivDirectSum S (M ⊗[R] N) ι).symm) -/
variable (R M N ι)
/-- The tensor product of `ι →₀ R` and `N` is linearly equivalent to `ι →₀ N` -/
noncomputable def finsuppScalarLeft :
(ι →₀ R) ⊗[R] N ≃ₗ[R] ι →₀ N :=
finsuppLeft R R N ι ≪≫ₗ (Finsupp.mapRange.linearEquiv (TensorProduct.lid R N))
variable {R M N ι}
@[simp]
lemma finsuppScalarLeft_apply_tmul_apply (p : ι →₀ R) (n : N) (i : ι) :
finsuppScalarLeft R N ι (p ⊗ₜ[R] n) i = p i • n := by
simp [finsuppScalarLeft]
lemma finsuppScalarLeft_apply_tmul (p : ι →₀ R) (n : N) :
finsuppScalarLeft R N ι (p ⊗ₜ[R] n) = p.sum fun i m ↦ Finsupp.single i (m • n) := by
ext i
rw [finsuppScalarLeft_apply_tmul_apply, Finsupp.sum_apply,
Finsupp.sum_eq_single i (fun _ _ ↦ Finsupp.single_eq_of_ne) (by simp), Finsupp.single_eq_same]
lemma finsuppScalarLeft_apply (pn : (ι →₀ R) ⊗[R] N) (i : ι) :
finsuppScalarLeft R N ι pn i = TensorProduct.lid R N ((Finsupp.lapply i).rTensor N pn) := by
simp [finsuppScalarLeft, finsuppLeft_apply]
@[simp]
lemma finsuppScalarLeft_symm_apply_single (i : ι) (n : N) :
(finsuppScalarLeft R N ι).symm (Finsupp.single i n) =
(Finsupp.single i 1) ⊗ₜ[R] n := by
simp [finsuppScalarLeft, finsuppLeft_symm_apply_single]
variable (R M N ι)
/-- The tensor product of `M` and `ι →₀ R` is linearly equivalent to `ι →₀ N` -/
noncomputable def finsuppScalarRight :
M ⊗[R] (ι →₀ R) ≃ₗ[R] ι →₀ M :=
finsuppRight R M R ι ≪≫ₗ Finsupp.mapRange.linearEquiv (TensorProduct.rid R M)
variable {R M N ι}
@[simp]
lemma finsuppScalarRight_apply_tmul_apply (m : M) (p : ι →₀ R) (i : ι) :
finsuppScalarRight R M ι (m ⊗ₜ[R] p) i = p i • m := by
simp [finsuppScalarRight]
lemma finsuppScalarRight_apply_tmul (m : M) (p : ι →₀ R) :
finsuppScalarRight R M ι (m ⊗ₜ[R] p) = p.sum fun i n ↦ Finsupp.single i (n • m) := by
ext i
rw [finsuppScalarRight_apply_tmul_apply, Finsupp.sum_apply,
Finsupp.sum_eq_single i (fun _ _ ↦ Finsupp.single_eq_of_ne) (by simp), Finsupp.single_eq_same]
lemma finsuppScalarRight_apply (t : M ⊗[R] (ι →₀ R)) (i : ι) :
finsuppScalarRight R M ι t i = TensorProduct.rid R M ((Finsupp.lapply i).lTensor M t) := by
simp [finsuppScalarRight, finsuppRight_apply]
@[simp]
lemma finsuppScalarRight_symm_apply_single (i : ι) (m : M) :
(finsuppScalarRight R M ι).symm (Finsupp.single i m) =
m ⊗ₜ[R] (Finsupp.single i 1) := by
simp [finsuppScalarRight, finsuppRight_symm_apply_single]
end TensorProduct
end TensorProduct
variable (R S M N ι κ : Type*)
[CommSemiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid N] [Module R N]
[Semiring S] [Algebra R S] [Module S M] [IsScalarTower R S M]
open scoped Classical in
/-- The tensor product of `ι →₀ M` and `κ →₀ N` is linearly equivalent to `(ι × κ) →₀ (M ⊗ N)`. -/
def finsuppTensorFinsupp : (ι →₀ M) ⊗[R] (κ →₀ N) ≃ₗ[S] ι × κ →₀ M ⊗[R] N :=
TensorProduct.AlgebraTensorModule.congr
(finsuppLEquivDirectSum S M ι) (finsuppLEquivDirectSum R N κ) ≪≫ₗ
((TensorProduct.directSum R S (fun _ : ι => M) fun _ : κ => N) ≪≫ₗ
(finsuppLEquivDirectSum S (M ⊗[R] N) (ι × κ)).symm)
#align finsupp_tensor_finsupp finsuppTensorFinsupp
@[simp]
| Mathlib/LinearAlgebra/DirectSum/Finsupp.lean | 256 | 259 | theorem finsuppTensorFinsupp_single (i : ι) (m : M) (k : κ) (n : N) :
finsuppTensorFinsupp R S M N ι κ (Finsupp.single i m ⊗ₜ Finsupp.single k n) =
Finsupp.single (i, k) (m ⊗ₜ n) := by |
simp [finsuppTensorFinsupp]
|
/-
Copyright (c) 2014 Parikshit Khanna. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Parikshit Khanna, Jeremy Avigad, Leonardo de Moura, Floris van Doorn, Mario Carneiro
-/
import Batteries.Control.ForInStep.Lemmas
import Batteries.Data.List.Basic
import Batteries.Tactic.Init
import Batteries.Tactic.Alias
namespace List
open Nat
/-! ### mem -/
@[simp] theorem mem_toArray {a : α} {l : List α} : a ∈ l.toArray ↔ a ∈ l := by
simp [Array.mem_def]
/-! ### drop -/
@[simp]
theorem drop_one : ∀ l : List α, drop 1 l = tail l
| [] | _ :: _ => rfl
/-! ### zipWith -/
theorem zipWith_distrib_tail : (zipWith f l l').tail = zipWith f l.tail l'.tail := by
rw [← drop_one]; simp [zipWith_distrib_drop]
/-! ### List subset -/
theorem subset_def {l₁ l₂ : List α} : l₁ ⊆ l₂ ↔ ∀ {a : α}, a ∈ l₁ → a ∈ l₂ := .rfl
@[simp] theorem nil_subset (l : List α) : [] ⊆ l := nofun
@[simp] theorem Subset.refl (l : List α) : l ⊆ l := fun _ i => i
theorem Subset.trans {l₁ l₂ l₃ : List α} (h₁ : l₁ ⊆ l₂) (h₂ : l₂ ⊆ l₃) : l₁ ⊆ l₃ :=
fun _ i => h₂ (h₁ i)
instance : Trans (Membership.mem : α → List α → Prop) Subset Membership.mem :=
⟨fun h₁ h₂ => h₂ h₁⟩
instance : Trans (Subset : List α → List α → Prop) Subset Subset :=
⟨Subset.trans⟩
@[simp] theorem subset_cons (a : α) (l : List α) : l ⊆ a :: l := fun _ => Mem.tail _
theorem subset_of_cons_subset {a : α} {l₁ l₂ : List α} : a :: l₁ ⊆ l₂ → l₁ ⊆ l₂ :=
fun s _ i => s (mem_cons_of_mem _ i)
theorem subset_cons_of_subset (a : α) {l₁ l₂ : List α} : l₁ ⊆ l₂ → l₁ ⊆ a :: l₂ :=
fun s _ i => .tail _ (s i)
theorem cons_subset_cons {l₁ l₂ : List α} (a : α) (s : l₁ ⊆ l₂) : a :: l₁ ⊆ a :: l₂ :=
fun _ => by simp only [mem_cons]; exact Or.imp_right (@s _)
@[simp] theorem subset_append_left (l₁ l₂ : List α) : l₁ ⊆ l₁ ++ l₂ := fun _ => mem_append_left _
@[simp] theorem subset_append_right (l₁ l₂ : List α) : l₂ ⊆ l₁ ++ l₂ := fun _ => mem_append_right _
theorem subset_append_of_subset_left (l₂ : List α) : l ⊆ l₁ → l ⊆ l₁ ++ l₂ :=
fun s => Subset.trans s <| subset_append_left _ _
theorem subset_append_of_subset_right (l₁ : List α) : l ⊆ l₂ → l ⊆ l₁ ++ l₂ :=
fun s => Subset.trans s <| subset_append_right _ _
@[simp] theorem cons_subset : a :: l ⊆ m ↔ a ∈ m ∧ l ⊆ m := by
simp only [subset_def, mem_cons, or_imp, forall_and, forall_eq]
@[simp] theorem append_subset {l₁ l₂ l : List α} :
l₁ ++ l₂ ⊆ l ↔ l₁ ⊆ l ∧ l₂ ⊆ l := by simp [subset_def, or_imp, forall_and]
theorem subset_nil {l : List α} : l ⊆ [] ↔ l = [] :=
⟨fun h => match l with | [] => rfl | _::_ => (nomatch h (.head ..)), fun | rfl => Subset.refl _⟩
theorem map_subset {l₁ l₂ : List α} (f : α → β) (H : l₁ ⊆ l₂) : map f l₁ ⊆ map f l₂ :=
fun x => by simp only [mem_map]; exact .imp fun a => .imp_left (@H _)
/-! ### sublists -/
@[simp] theorem nil_sublist : ∀ l : List α, [] <+ l
| [] => .slnil
| a :: l => (nil_sublist l).cons a
@[simp] theorem Sublist.refl : ∀ l : List α, l <+ l
| [] => .slnil
| a :: l => (Sublist.refl l).cons₂ a
theorem Sublist.trans {l₁ l₂ l₃ : List α} (h₁ : l₁ <+ l₂) (h₂ : l₂ <+ l₃) : l₁ <+ l₃ := by
induction h₂ generalizing l₁ with
| slnil => exact h₁
| cons _ _ IH => exact (IH h₁).cons _
| @cons₂ l₂ _ a _ IH =>
generalize e : a :: l₂ = l₂'
match e ▸ h₁ with
| .slnil => apply nil_sublist
| .cons a' h₁' => cases e; apply (IH h₁').cons
| .cons₂ a' h₁' => cases e; apply (IH h₁').cons₂
instance : Trans (@Sublist α) Sublist Sublist := ⟨Sublist.trans⟩
@[simp] theorem sublist_cons (a : α) (l : List α) : l <+ a :: l := (Sublist.refl l).cons _
theorem sublist_of_cons_sublist : a :: l₁ <+ l₂ → l₁ <+ l₂ :=
(sublist_cons a l₁).trans
@[simp] theorem sublist_append_left : ∀ l₁ l₂ : List α, l₁ <+ l₁ ++ l₂
| [], _ => nil_sublist _
| _ :: l₁, l₂ => (sublist_append_left l₁ l₂).cons₂ _
@[simp] theorem sublist_append_right : ∀ l₁ l₂ : List α, l₂ <+ l₁ ++ l₂
| [], _ => Sublist.refl _
| _ :: l₁, l₂ => (sublist_append_right l₁ l₂).cons _
theorem sublist_append_of_sublist_left (s : l <+ l₁) : l <+ l₁ ++ l₂ :=
s.trans <| sublist_append_left ..
theorem sublist_append_of_sublist_right (s : l <+ l₂) : l <+ l₁ ++ l₂ :=
s.trans <| sublist_append_right ..
@[simp]
theorem cons_sublist_cons : a :: l₁ <+ a :: l₂ ↔ l₁ <+ l₂ :=
⟨fun | .cons _ s => sublist_of_cons_sublist s | .cons₂ _ s => s, .cons₂ _⟩
@[simp] theorem append_sublist_append_left : ∀ l, l ++ l₁ <+ l ++ l₂ ↔ l₁ <+ l₂
| [] => Iff.rfl
| _ :: l => cons_sublist_cons.trans (append_sublist_append_left l)
theorem Sublist.append_left : l₁ <+ l₂ → ∀ l, l ++ l₁ <+ l ++ l₂ :=
fun h l => (append_sublist_append_left l).mpr h
theorem Sublist.append_right : l₁ <+ l₂ → ∀ l, l₁ ++ l <+ l₂ ++ l
| .slnil, _ => Sublist.refl _
| .cons _ h, _ => (h.append_right _).cons _
| .cons₂ _ h, _ => (h.append_right _).cons₂ _
theorem sublist_or_mem_of_sublist (h : l <+ l₁ ++ a :: l₂) : l <+ l₁ ++ l₂ ∨ a ∈ l := by
induction l₁ generalizing l with
| nil => match h with
| .cons _ h => exact .inl h
| .cons₂ _ h => exact .inr (.head ..)
| cons b l₁ IH =>
match h with
| .cons _ h => exact (IH h).imp_left (Sublist.cons _)
| .cons₂ _ h => exact (IH h).imp (Sublist.cons₂ _) (.tail _)
theorem Sublist.reverse : l₁ <+ l₂ → l₁.reverse <+ l₂.reverse
| .slnil => Sublist.refl _
| .cons _ h => by rw [reverse_cons]; exact sublist_append_of_sublist_left h.reverse
| .cons₂ _ h => by rw [reverse_cons, reverse_cons]; exact h.reverse.append_right _
@[simp] theorem reverse_sublist : l₁.reverse <+ l₂.reverse ↔ l₁ <+ l₂ :=
⟨fun h => l₁.reverse_reverse ▸ l₂.reverse_reverse ▸ h.reverse, Sublist.reverse⟩
@[simp] theorem append_sublist_append_right (l) : l₁ ++ l <+ l₂ ++ l ↔ l₁ <+ l₂ :=
⟨fun h => by
have := h.reverse
simp only [reverse_append, append_sublist_append_left, reverse_sublist] at this
exact this,
fun h => h.append_right l⟩
theorem Sublist.append (hl : l₁ <+ l₂) (hr : r₁ <+ r₂) : l₁ ++ r₁ <+ l₂ ++ r₂ :=
(hl.append_right _).trans ((append_sublist_append_left _).2 hr)
theorem Sublist.subset : l₁ <+ l₂ → l₁ ⊆ l₂
| .slnil, _, h => h
| .cons _ s, _, h => .tail _ (s.subset h)
| .cons₂ .., _, .head .. => .head ..
| .cons₂ _ s, _, .tail _ h => .tail _ (s.subset h)
instance : Trans (@Sublist α) Subset Subset :=
⟨fun h₁ h₂ => trans h₁.subset h₂⟩
instance : Trans Subset (@Sublist α) Subset :=
⟨fun h₁ h₂ => trans h₁ h₂.subset⟩
instance : Trans (Membership.mem : α → List α → Prop) Sublist Membership.mem :=
⟨fun h₁ h₂ => h₂.subset h₁⟩
theorem Sublist.length_le : l₁ <+ l₂ → length l₁ ≤ length l₂
| .slnil => Nat.le_refl 0
| .cons _l s => le_succ_of_le (length_le s)
| .cons₂ _ s => succ_le_succ (length_le s)
@[simp] theorem sublist_nil {l : List α} : l <+ [] ↔ l = [] :=
⟨fun s => subset_nil.1 s.subset, fun H => H ▸ Sublist.refl _⟩
theorem Sublist.eq_of_length : l₁ <+ l₂ → length l₁ = length l₂ → l₁ = l₂
| .slnil, _ => rfl
| .cons a s, h => nomatch Nat.not_lt.2 s.length_le (h ▸ lt_succ_self _)
| .cons₂ a s, h => by rw [s.eq_of_length (succ.inj h)]
theorem Sublist.eq_of_length_le (s : l₁ <+ l₂) (h : length l₂ ≤ length l₁) : l₁ = l₂ :=
s.eq_of_length <| Nat.le_antisymm s.length_le h
@[simp] theorem singleton_sublist {a : α} {l} : [a] <+ l ↔ a ∈ l := by
refine ⟨fun h => h.subset (mem_singleton_self _), fun h => ?_⟩
obtain ⟨_, _, rfl⟩ := append_of_mem h
exact ((nil_sublist _).cons₂ _).trans (sublist_append_right ..)
@[simp] theorem replicate_sublist_replicate {m n} (a : α) :
replicate m a <+ replicate n a ↔ m ≤ n := by
refine ⟨fun h => ?_, fun h => ?_⟩
· have := h.length_le; simp only [length_replicate] at this ⊢; exact this
· induction h with
| refl => apply Sublist.refl
| step => simp [*, replicate, Sublist.cons]
theorem isSublist_iff_sublist [BEq α] [LawfulBEq α] {l₁ l₂ : List α} :
l₁.isSublist l₂ ↔ l₁ <+ l₂ := by
cases l₁ <;> cases l₂ <;> simp [isSublist]
case cons.cons hd₁ tl₁ hd₂ tl₂ =>
if h_eq : hd₁ = hd₂ then
simp [h_eq, cons_sublist_cons, isSublist_iff_sublist]
else
simp only [beq_iff_eq, h_eq]
constructor
· intro h_sub
apply Sublist.cons
exact isSublist_iff_sublist.mp h_sub
· intro h_sub
cases h_sub
case cons h_sub =>
exact isSublist_iff_sublist.mpr h_sub
case cons₂ =>
contradiction
instance [DecidableEq α] (l₁ l₂ : List α) : Decidable (l₁ <+ l₂) :=
decidable_of_iff (l₁.isSublist l₂) isSublist_iff_sublist
/-! ### tail -/
theorem tail_eq_tailD (l) : @tail α l = tailD l [] := by cases l <;> rfl
theorem tail_eq_tail? (l) : @tail α l = (tail? l).getD [] := by simp [tail_eq_tailD]
/-! ### next? -/
@[simp] theorem next?_nil : @next? α [] = none := rfl
@[simp] theorem next?_cons (a l) : @next? α (a :: l) = some (a, l) := rfl
/-! ### get? -/
theorem get_eq_iff : List.get l n = x ↔ l.get? n.1 = some x := by simp [get?_eq_some]
theorem get?_inj
(h₀ : i < xs.length) (h₁ : Nodup xs) (h₂ : xs.get? i = xs.get? j) : i = j := by
induction xs generalizing i j with
| nil => cases h₀
| cons x xs ih =>
match i, j with
| 0, 0 => rfl
| i+1, j+1 => simp; cases h₁ with
| cons ha h₁ => exact ih (Nat.lt_of_succ_lt_succ h₀) h₁ h₂
| i+1, 0 => ?_ | 0, j+1 => ?_
all_goals
simp at h₂
cases h₁; rename_i h' h
have := h x ?_ rfl; cases this
rw [mem_iff_get?]
exact ⟨_, h₂⟩; exact ⟨_ , h₂.symm⟩
/-! ### drop -/
theorem tail_drop (l : List α) (n : Nat) : (l.drop n).tail = l.drop (n + 1) := by
induction l generalizing n with
| nil => simp
| cons hd tl hl =>
cases n
· simp
· simp [hl]
/-! ### modifyNth -/
@[simp] theorem modifyNth_nil (f : α → α) (n) : [].modifyNth f n = [] := by cases n <;> rfl
@[simp] theorem modifyNth_zero_cons (f : α → α) (a : α) (l : List α) :
(a :: l).modifyNth f 0 = f a :: l := rfl
@[simp] theorem modifyNth_succ_cons (f : α → α) (a : α) (l : List α) (n) :
(a :: l).modifyNth f (n + 1) = a :: l.modifyNth f n := by rfl
theorem modifyNthTail_id : ∀ n (l : List α), l.modifyNthTail id n = l
| 0, _ => rfl
| _+1, [] => rfl
| n+1, a :: l => congrArg (cons a) (modifyNthTail_id n l)
theorem eraseIdx_eq_modifyNthTail : ∀ n (l : List α), eraseIdx l n = modifyNthTail tail n l
| 0, l => by cases l <;> rfl
| n+1, [] => rfl
| n+1, a :: l => congrArg (cons _) (eraseIdx_eq_modifyNthTail _ _)
@[deprecated] alias removeNth_eq_nth_tail := eraseIdx_eq_modifyNthTail
theorem get?_modifyNth (f : α → α) :
∀ n (l : List α) m, (modifyNth f n l).get? m = (fun a => if n = m then f a else a) <$> l.get? m
| n, l, 0 => by cases l <;> cases n <;> rfl
| n, [], _+1 => by cases n <;> rfl
| 0, _ :: l, m+1 => by cases h : l.get? m <;> simp [h, modifyNth, m.succ_ne_zero.symm]
| n+1, a :: l, m+1 =>
(get?_modifyNth f n l m).trans <| by
cases h' : l.get? m <;> by_cases h : n = m <;>
simp [h, if_pos, if_neg, Option.map, mt Nat.succ.inj, not_false_iff, h']
theorem modifyNthTail_length (f : List α → List α) (H : ∀ l, length (f l) = length l) :
∀ n l, length (modifyNthTail f n l) = length l
| 0, _ => H _
| _+1, [] => rfl
| _+1, _ :: _ => congrArg (·+1) (modifyNthTail_length _ H _ _)
theorem modifyNthTail_add (f : List α → List α) (n) (l₁ l₂ : List α) :
modifyNthTail f (l₁.length + n) (l₁ ++ l₂) = l₁ ++ modifyNthTail f n l₂ := by
induction l₁ <;> simp [*, Nat.succ_add]
theorem exists_of_modifyNthTail (f : List α → List α) {n} {l : List α} (h : n ≤ l.length) :
∃ l₁ l₂, l = l₁ ++ l₂ ∧ l₁.length = n ∧ modifyNthTail f n l = l₁ ++ f l₂ :=
have ⟨_, _, eq, hl⟩ : ∃ l₁ l₂, l = l₁ ++ l₂ ∧ l₁.length = n :=
⟨_, _, (take_append_drop n l).symm, length_take_of_le h⟩
⟨_, _, eq, hl, hl ▸ eq ▸ modifyNthTail_add (n := 0) ..⟩
@[simp] theorem modify_get?_length (f : α → α) : ∀ n l, length (modifyNth f n l) = length l :=
modifyNthTail_length _ fun l => by cases l <;> rfl
@[simp] theorem get?_modifyNth_eq (f : α → α) (n) (l : List α) :
(modifyNth f n l).get? n = f <$> l.get? n := by
simp only [get?_modifyNth, if_pos]
@[simp] theorem get?_modifyNth_ne (f : α → α) {m n} (l : List α) (h : m ≠ n) :
(modifyNth f m l).get? n = l.get? n := by
simp only [get?_modifyNth, if_neg h, id_map']
theorem exists_of_modifyNth (f : α → α) {n} {l : List α} (h : n < l.length) :
∃ l₁ a l₂, l = l₁ ++ a :: l₂ ∧ l₁.length = n ∧ modifyNth f n l = l₁ ++ f a :: l₂ :=
match exists_of_modifyNthTail _ (Nat.le_of_lt h) with
| ⟨_, _::_, eq, hl, H⟩ => ⟨_, _, _, eq, hl, H⟩
| ⟨_, [], eq, hl, _⟩ => nomatch Nat.ne_of_gt h (eq ▸ append_nil _ ▸ hl)
theorem modifyNthTail_eq_take_drop (f : List α → List α) (H : f [] = []) :
∀ n l, modifyNthTail f n l = take n l ++ f (drop n l)
| 0, _ => rfl
| _ + 1, [] => H.symm
| n + 1, b :: l => congrArg (cons b) (modifyNthTail_eq_take_drop f H n l)
theorem modifyNth_eq_take_drop (f : α → α) :
∀ n l, modifyNth f n l = take n l ++ modifyHead f (drop n l) :=
modifyNthTail_eq_take_drop _ rfl
theorem modifyNth_eq_take_cons_drop (f : α → α) {n l} (h) :
modifyNth f n l = take n l ++ f (get l ⟨n, h⟩) :: drop (n + 1) l := by
rw [modifyNth_eq_take_drop, drop_eq_get_cons h]; rfl
/-! ### set -/
theorem set_eq_modifyNth (a : α) : ∀ n (l : List α), set l n a = modifyNth (fun _ => a) n l
| 0, l => by cases l <;> rfl
| n+1, [] => rfl
| n+1, b :: l => congrArg (cons _) (set_eq_modifyNth _ _ _)
theorem set_eq_take_cons_drop (a : α) {n l} (h : n < length l) :
set l n a = take n l ++ a :: drop (n + 1) l := by
rw [set_eq_modifyNth, modifyNth_eq_take_cons_drop _ h]
theorem modifyNth_eq_set_get? (f : α → α) :
∀ n (l : List α), l.modifyNth f n = ((fun a => l.set n (f a)) <$> l.get? n).getD l
| 0, l => by cases l <;> rfl
| n+1, [] => rfl
| n+1, b :: l =>
(congrArg (cons _) (modifyNth_eq_set_get? ..)).trans <| by cases h : l.get? n <;> simp [h]
theorem modifyNth_eq_set_get (f : α → α) {n} {l : List α} (h) :
l.modifyNth f n = l.set n (f (l.get ⟨n, h⟩)) := by
rw [modifyNth_eq_set_get?, get?_eq_get h]; rfl
theorem exists_of_set {l : List α} (h : n < l.length) :
∃ l₁ a l₂, l = l₁ ++ a :: l₂ ∧ l₁.length = n ∧ l.set n a' = l₁ ++ a' :: l₂ := by
rw [set_eq_modifyNth]; exact exists_of_modifyNth _ h
theorem exists_of_set' {l : List α} (h : n < l.length) :
∃ l₁ l₂, l = l₁ ++ l.get ⟨n, h⟩ :: l₂ ∧ l₁.length = n ∧ l.set n a' = l₁ ++ a' :: l₂ :=
have ⟨_, _, _, h₁, h₂, h₃⟩ := exists_of_set h; ⟨_, _, get_of_append h₁ h₂ ▸ h₁, h₂, h₃⟩
@[simp]
theorem get?_set_eq (a : α) (n) (l : List α) : (set l n a).get? n = (fun _ => a) <$> l.get? n := by
simp only [set_eq_modifyNth, get?_modifyNth_eq]
theorem get?_set_eq_of_lt (a : α) {n} {l : List α} (h : n < length l) :
(set l n a).get? n = some a := by rw [get?_set_eq, get?_eq_get h]; rfl
@[simp]
theorem get?_set_ne (a : α) {m n} (l : List α) (h : m ≠ n) : (set l m a).get? n = l.get? n := by
simp only [set_eq_modifyNth, get?_modifyNth_ne _ _ h]
theorem get?_set (a : α) {m n} (l : List α) :
(set l m a).get? n = if m = n then (fun _ => a) <$> l.get? n else l.get? n := by
by_cases m = n <;> simp [*, get?_set_eq, get?_set_ne]
theorem get?_set_of_lt (a : α) {m n} (l : List α) (h : n < length l) :
(set l m a).get? n = if m = n then some a else l.get? n := by
simp [get?_set, get?_eq_get h]
theorem get?_set_of_lt' (a : α) {m n} (l : List α) (h : m < length l) :
(set l m a).get? n = if m = n then some a else l.get? n := by
simp [get?_set]; split <;> subst_vars <;> simp [*, get?_eq_get h]
theorem drop_set_of_lt (a : α) {n m : Nat} (l : List α) (h : n < m) :
(l.set n a).drop m = l.drop m :=
List.ext fun i => by rw [get?_drop, get?_drop, get?_set_ne _ _ (by omega)]
theorem take_set_of_lt (a : α) {n m : Nat} (l : List α) (h : m < n) :
(l.set n a).take m = l.take m :=
List.ext fun i => by
rw [get?_take_eq_if, get?_take_eq_if]
split
· next h' => rw [get?_set_ne _ _ (by omega)]
· rfl
/-! ### removeNth -/
theorem length_eraseIdx : ∀ {l i}, i < length l → length (@eraseIdx α l i) = length l - 1
| [], _, _ => rfl
| _::_, 0, _ => by simp [eraseIdx]
| x::xs, i+1, h => by
have : i < length xs := Nat.lt_of_succ_lt_succ h
simp [eraseIdx, ← Nat.add_one]
rw [length_eraseIdx this, Nat.sub_add_cancel (Nat.lt_of_le_of_lt (Nat.zero_le _) this)]
@[deprecated] alias length_removeNth := length_eraseIdx
/-! ### tail -/
@[simp] theorem length_tail (l : List α) : length (tail l) = length l - 1 := by cases l <;> rfl
/-! ### eraseP -/
@[simp] theorem eraseP_nil : [].eraseP p = [] := rfl
theorem eraseP_cons (a : α) (l : List α) :
(a :: l).eraseP p = bif p a then l else a :: l.eraseP p := rfl
@[simp] theorem eraseP_cons_of_pos {l : List α} (p) (h : p a) : (a :: l).eraseP p = l := by
simp [eraseP_cons, h]
@[simp] theorem eraseP_cons_of_neg {l : List α} (p) (h : ¬p a) :
(a :: l).eraseP p = a :: l.eraseP p := by simp [eraseP_cons, h]
theorem eraseP_of_forall_not {l : List α} (h : ∀ a, a ∈ l → ¬p a) : l.eraseP p = l := by
induction l with
| nil => rfl
| cons _ _ ih => simp [h _ (.head ..), ih (forall_mem_cons.1 h).2]
theorem exists_of_eraseP : ∀ {l : List α} {a} (al : a ∈ l) (pa : p a),
∃ a l₁ l₂, (∀ b ∈ l₁, ¬p b) ∧ p a ∧ l = l₁ ++ a :: l₂ ∧ l.eraseP p = l₁ ++ l₂
| b :: l, a, al, pa =>
if pb : p b then
⟨b, [], l, forall_mem_nil _, pb, by simp [pb]⟩
else
match al with
| .head .. => nomatch pb pa
| .tail _ al =>
let ⟨c, l₁, l₂, h₁, h₂, h₃, h₄⟩ := exists_of_eraseP al pa
⟨c, b::l₁, l₂, (forall_mem_cons ..).2 ⟨pb, h₁⟩,
h₂, by rw [h₃, cons_append], by simp [pb, h₄]⟩
theorem exists_or_eq_self_of_eraseP (p) (l : List α) :
l.eraseP p = l ∨
∃ a l₁ l₂, (∀ b ∈ l₁, ¬p b) ∧ p a ∧ l = l₁ ++ a :: l₂ ∧ l.eraseP p = l₁ ++ l₂ :=
if h : ∃ a ∈ l, p a then
let ⟨_, ha, pa⟩ := h
.inr (exists_of_eraseP ha pa)
else
.inl (eraseP_of_forall_not (h ⟨·, ·, ·⟩))
@[simp] theorem length_eraseP_of_mem (al : a ∈ l) (pa : p a) :
length (l.eraseP p) = Nat.pred (length l) := by
let ⟨_, l₁, l₂, _, _, e₁, e₂⟩ := exists_of_eraseP al pa
rw [e₂]; simp [length_append, e₁]; rfl
theorem eraseP_append_left {a : α} (pa : p a) :
∀ {l₁ : List α} l₂, a ∈ l₁ → (l₁++l₂).eraseP p = l₁.eraseP p ++ l₂
| x :: xs, l₂, h => by
by_cases h' : p x <;> simp [h']
rw [eraseP_append_left pa l₂ ((mem_cons.1 h).resolve_left (mt _ h'))]
intro | rfl => exact pa
theorem eraseP_append_right :
∀ {l₁ : List α} l₂, (∀ b ∈ l₁, ¬p b) → eraseP p (l₁++l₂) = l₁ ++ l₂.eraseP p
| [], l₂, _ => rfl
| x :: xs, l₂, h => by
simp [(forall_mem_cons.1 h).1, eraseP_append_right _ (forall_mem_cons.1 h).2]
theorem eraseP_sublist (l : List α) : l.eraseP p <+ l := by
match exists_or_eq_self_of_eraseP p l with
| .inl h => rw [h]; apply Sublist.refl
| .inr ⟨c, l₁, l₂, _, _, h₃, h₄⟩ => rw [h₄, h₃]; simp
theorem eraseP_subset (l : List α) : l.eraseP p ⊆ l := (eraseP_sublist l).subset
protected theorem Sublist.eraseP : l₁ <+ l₂ → l₁.eraseP p <+ l₂.eraseP p
| .slnil => Sublist.refl _
| .cons a s => by
by_cases h : p a <;> simp [h]
exacts [s.eraseP.trans (eraseP_sublist _), s.eraseP.cons _]
| .cons₂ a s => by
by_cases h : p a <;> simp [h]
exacts [s, s.eraseP]
theorem mem_of_mem_eraseP {l : List α} : a ∈ l.eraseP p → a ∈ l := (eraseP_subset _ ·)
@[simp] theorem mem_eraseP_of_neg {l : List α} (pa : ¬p a) : a ∈ l.eraseP p ↔ a ∈ l := by
refine ⟨mem_of_mem_eraseP, fun al => ?_⟩
match exists_or_eq_self_of_eraseP p l with
| .inl h => rw [h]; assumption
| .inr ⟨c, l₁, l₂, h₁, h₂, h₃, h₄⟩ =>
rw [h₄]; rw [h₃] at al
have : a ≠ c := fun h => (h ▸ pa).elim h₂
simp [this] at al; simp [al]
theorem eraseP_map (f : β → α) : ∀ (l : List β), (map f l).eraseP p = map f (l.eraseP (p ∘ f))
| [] => rfl
| b::l => by by_cases h : p (f b) <;> simp [h, eraseP_map f l, eraseP_cons_of_pos]
@[simp] theorem extractP_eq_find?_eraseP
(l : List α) : extractP p l = (find? p l, eraseP p l) := by
let rec go (acc) : ∀ xs, l = acc.data ++ xs →
extractP.go p l xs acc = (xs.find? p, acc.data ++ xs.eraseP p)
| [] => fun h => by simp [extractP.go, find?, eraseP, h]
| x::xs => by
simp [extractP.go, find?, eraseP]; cases p x <;> simp
· intro h; rw [go _ xs]; {simp}; simp [h]
exact go #[] _ rfl
/-! ### erase -/
section erase
variable [BEq α]
theorem erase_eq_eraseP' (a : α) (l : List α) : l.erase a = l.eraseP (· == a) := by
induction l
· simp
· next b t ih =>
rw [erase_cons, eraseP_cons, ih]
if h : b == a then simp [h] else simp [h]
theorem erase_eq_eraseP [LawfulBEq α] (a : α) : ∀ l : List α, l.erase a = l.eraseP (a == ·)
| [] => rfl
| b :: l => by
if h : a = b then simp [h] else simp [h, Ne.symm h, erase_eq_eraseP a l]
theorem exists_erase_eq [LawfulBEq α] {a : α} {l : List α} (h : a ∈ l) :
∃ l₁ l₂, a ∉ l₁ ∧ l = l₁ ++ a :: l₂ ∧ l.erase a = l₁ ++ l₂ := by
let ⟨_, l₁, l₂, h₁, e, h₂, h₃⟩ := exists_of_eraseP h (beq_self_eq_true _)
rw [erase_eq_eraseP]; exact ⟨l₁, l₂, fun h => h₁ _ h (beq_self_eq_true _), eq_of_beq e ▸ h₂, h₃⟩
@[simp] theorem length_erase_of_mem [LawfulBEq α] {a : α} {l : List α} (h : a ∈ l) :
length (l.erase a) = Nat.pred (length l) := by
rw [erase_eq_eraseP]; exact length_eraseP_of_mem h (beq_self_eq_true a)
theorem erase_append_left [LawfulBEq α] {l₁ : List α} (l₂) (h : a ∈ l₁) :
(l₁ ++ l₂).erase a = l₁.erase a ++ l₂ := by
simp [erase_eq_eraseP]; exact eraseP_append_left (beq_self_eq_true a) l₂ h
theorem erase_append_right [LawfulBEq α] {a : α} {l₁ : List α} (l₂ : List α) (h : a ∉ l₁) :
(l₁ ++ l₂).erase a = (l₁ ++ l₂.erase a) := by
rw [erase_eq_eraseP, erase_eq_eraseP, eraseP_append_right]
intros b h' h''; rw [eq_of_beq h''] at h; exact h h'
theorem erase_sublist (a : α) (l : List α) : l.erase a <+ l :=
erase_eq_eraseP' a l ▸ eraseP_sublist l
theorem erase_subset (a : α) (l : List α) : l.erase a ⊆ l := (erase_sublist a l).subset
theorem Sublist.erase (a : α) {l₁ l₂ : List α} (h : l₁ <+ l₂) : l₁.erase a <+ l₂.erase a := by
simp only [erase_eq_eraseP']; exact h.eraseP
@[deprecated] alias sublist.erase := Sublist.erase
theorem mem_of_mem_erase {a b : α} {l : List α} (h : a ∈ l.erase b) : a ∈ l := erase_subset _ _ h
@[simp] theorem mem_erase_of_ne [LawfulBEq α] {a b : α} {l : List α} (ab : a ≠ b) :
a ∈ l.erase b ↔ a ∈ l :=
erase_eq_eraseP b l ▸ mem_eraseP_of_neg (mt eq_of_beq ab.symm)
theorem erase_comm [LawfulBEq α] (a b : α) (l : List α) :
(l.erase a).erase b = (l.erase b).erase a := by
if ab : a == b then rw [eq_of_beq ab] else ?_
if ha : a ∈ l then ?_ else
simp only [erase_of_not_mem ha, erase_of_not_mem (mt mem_of_mem_erase ha)]
if hb : b ∈ l then ?_ else
simp only [erase_of_not_mem hb, erase_of_not_mem (mt mem_of_mem_erase hb)]
match l, l.erase a, exists_erase_eq ha with
| _, _, ⟨l₁, l₂, ha', rfl, rfl⟩ =>
if h₁ : b ∈ l₁ then
rw [erase_append_left _ h₁, erase_append_left _ h₁,
erase_append_right _ (mt mem_of_mem_erase ha'), erase_cons_head]
else
rw [erase_append_right _ h₁, erase_append_right _ h₁, erase_append_right _ ha',
erase_cons_tail _ ab, erase_cons_head]
end erase
/-! ### filter and partition -/
@[simp] theorem filter_sublist {p : α → Bool} : ∀ (l : List α), filter p l <+ l
| [] => .slnil
| a :: l => by rw [filter]; split <;> simp [Sublist.cons, Sublist.cons₂, filter_sublist l]
/-! ### filterMap -/
theorem length_filter_le (p : α → Bool) (l : List α) :
(l.filter p).length ≤ l.length := (filter_sublist _).length_le
theorem length_filterMap_le (f : α → Option β) (l : List α) :
(filterMap f l).length ≤ l.length := by
rw [← length_map _ some, map_filterMap_some_eq_filter_map_is_some, ← length_map _ f]
apply length_filter_le
protected theorem Sublist.filterMap (f : α → Option β) (s : l₁ <+ l₂) :
filterMap f l₁ <+ filterMap f l₂ := by
induction s <;> simp <;> split <;> simp [*, cons, cons₂]
theorem Sublist.filter (p : α → Bool) {l₁ l₂} (s : l₁ <+ l₂) : filter p l₁ <+ filter p l₂ := by
rw [← filterMap_eq_filter]; apply s.filterMap
@[simp]
theorem filter_eq_self {l} : filter p l = l ↔ ∀ a ∈ l, p a := by
induction l with simp
| cons a l ih =>
cases h : p a <;> simp [*]
intro h; exact Nat.lt_irrefl _ (h ▸ length_filter_le p l)
@[simp]
theorem filter_length_eq_length {l} : (filter p l).length = l.length ↔ ∀ a ∈ l, p a :=
Iff.trans ⟨l.filter_sublist.eq_of_length, congrArg length⟩ filter_eq_self
/-! ### findIdx -/
@[simp] theorem findIdx_nil {α : Type _} (p : α → Bool) : [].findIdx p = 0 := rfl
theorem findIdx_cons (p : α → Bool) (b : α) (l : List α) :
(b :: l).findIdx p = bif p b then 0 else (l.findIdx p) + 1 := by
cases H : p b with
| true => simp [H, findIdx, findIdx.go]
| false => simp [H, findIdx, findIdx.go, findIdx_go_succ]
where
findIdx_go_succ (p : α → Bool) (l : List α) (n : Nat) :
List.findIdx.go p l (n + 1) = (findIdx.go p l n) + 1 := by
cases l with
| nil => unfold findIdx.go; exact Nat.succ_eq_add_one n
| cons head tail =>
unfold findIdx.go
cases p head <;> simp only [cond_false, cond_true]
exact findIdx_go_succ p tail (n + 1)
theorem findIdx_of_get?_eq_some {xs : List α} (w : xs.get? (xs.findIdx p) = some y) : p y := by
induction xs with
| nil => simp_all
| cons x xs ih => by_cases h : p x <;> simp_all [findIdx_cons]
theorem findIdx_get {xs : List α} {w : xs.findIdx p < xs.length} :
p (xs.get ⟨xs.findIdx p, w⟩) :=
xs.findIdx_of_get?_eq_some (get?_eq_get w)
theorem findIdx_lt_length_of_exists {xs : List α} (h : ∃ x ∈ xs, p x) :
xs.findIdx p < xs.length := by
induction xs with
| nil => simp_all
| cons x xs ih =>
by_cases p x
· simp_all only [forall_exists_index, and_imp, mem_cons, exists_eq_or_imp, true_or,
findIdx_cons, cond_true, length_cons]
apply Nat.succ_pos
· simp_all [findIdx_cons]
refine Nat.succ_lt_succ ?_
obtain ⟨x', m', h'⟩ := h
exact ih x' m' h'
theorem findIdx_get?_eq_get_of_exists {xs : List α} (h : ∃ x ∈ xs, p x) :
xs.get? (xs.findIdx p) = some (xs.get ⟨xs.findIdx p, xs.findIdx_lt_length_of_exists h⟩) :=
get?_eq_get (findIdx_lt_length_of_exists h)
/-! ### findIdx? -/
@[simp] theorem findIdx?_nil : ([] : List α).findIdx? p i = none := rfl
@[simp] theorem findIdx?_cons :
(x :: xs).findIdx? p i = if p x then some i else findIdx? p xs (i + 1) := rfl
@[simp] theorem findIdx?_succ :
(xs : List α).findIdx? p (i+1) = (xs.findIdx? p i).map fun i => i + 1 := by
induction xs generalizing i with simp
| cons _ _ _ => split <;> simp_all
theorem findIdx?_eq_some_iff (xs : List α) (p : α → Bool) :
xs.findIdx? p = some i ↔ (xs.take (i + 1)).map p = replicate i false ++ [true] := by
induction xs generalizing i with
| nil => simp
| cons x xs ih =>
simp only [findIdx?_cons, Nat.zero_add, findIdx?_succ, take_succ_cons, map_cons]
split <;> cases i <;> simp_all
theorem findIdx?_of_eq_some {xs : List α} {p : α → Bool} (w : xs.findIdx? p = some i) :
match xs.get? i with | some a => p a | none => false := by
induction xs generalizing i with
| nil => simp_all
| cons x xs ih =>
simp_all only [findIdx?_cons, Nat.zero_add, findIdx?_succ]
split at w <;> cases i <;> simp_all
theorem findIdx?_of_eq_none {xs : List α} {p : α → Bool} (w : xs.findIdx? p = none) :
∀ i, match xs.get? i with | some a => ¬ p a | none => true := by
intro i
induction xs generalizing i with
| nil => simp_all
| cons x xs ih =>
simp_all only [Bool.not_eq_true, findIdx?_cons, Nat.zero_add, findIdx?_succ]
cases i with
| zero =>
split at w <;> simp_all
| succ i =>
simp only [get?_cons_succ]
apply ih
split at w <;> simp_all
@[simp] theorem findIdx?_append :
(xs ++ ys : List α).findIdx? p =
(xs.findIdx? p <|> (ys.findIdx? p).map fun i => i + xs.length) := by
induction xs with simp
| cons _ _ _ => split <;> simp_all [Option.map_orElse, Option.map_map]; rfl
@[simp] theorem findIdx?_replicate :
(replicate n a).findIdx? p = if 0 < n ∧ p a then some 0 else none := by
induction n with
| zero => simp
| succ n ih =>
simp only [replicate, findIdx?_cons, Nat.zero_add, findIdx?_succ, Nat.zero_lt_succ, true_and]
split <;> simp_all
/-! ### pairwise -/
theorem Pairwise.sublist : l₁ <+ l₂ → l₂.Pairwise R → l₁.Pairwise R
| .slnil, h => h
| .cons _ s, .cons _ h₂ => h₂.sublist s
| .cons₂ _ s, .cons h₁ h₂ => (h₂.sublist s).cons fun _ h => h₁ _ (s.subset h)
| .lake/packages/batteries/Batteries/Data/List/Lemmas.lean | 746 | 750 | theorem pairwise_map {l : List α} :
(l.map f).Pairwise R ↔ l.Pairwise fun a b => R (f a) (f b) := by |
induction l
· simp
· simp only [map, pairwise_cons, forall_mem_map_iff, *]
|
/-
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]
| Mathlib/Order/Filter/Basic.lean | 216 | 217 | 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]
|
/-
Copyright (c) 2022 Rémi Bottinelli. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémi Bottinelli, Junyan Xu
-/
import Mathlib.Algebra.Group.Subgroup.Basic
import Mathlib.CategoryTheory.Groupoid.VertexGroup
import Mathlib.CategoryTheory.Groupoid.Basic
import Mathlib.CategoryTheory.Groupoid
import Mathlib.Data.Set.Lattice
import Mathlib.Order.GaloisConnection
#align_import category_theory.groupoid.subgroupoid from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Subgroupoid
This file defines subgroupoids as `structure`s containing the subsets of arrows and their
stability under composition and inversion.
Also defined are:
* containment of subgroupoids is a complete lattice;
* images and preimages of subgroupoids under a functor;
* the notion of normality of subgroupoids and its stability under intersection and preimage;
* compatibility of the above with `CategoryTheory.Groupoid.vertexGroup`.
## Main definitions
Given a type `C` with associated `groupoid C` instance.
* `CategoryTheory.Subgroupoid C` is the type of subgroupoids of `C`
* `CategoryTheory.Subgroupoid.IsNormal` is the property that the subgroupoid is stable under
conjugation by arbitrary arrows, _and_ that all identity arrows are contained in the subgroupoid.
* `CategoryTheory.Subgroupoid.comap` is the "preimage" map of subgroupoids along a functor.
* `CategoryTheory.Subgroupoid.map` is the "image" map of subgroupoids along a functor _injective on
objects_.
* `CategoryTheory.Subgroupoid.vertexSubgroup` is the subgroup of the `vertex group` at a given
vertex `v`, assuming `v` is contained in the `CategoryTheory.Subgroupoid` (meaning, by definition,
that the arrow `𝟙 v` is contained in the subgroupoid).
## Implementation details
The structure of this file is copied from/inspired by `Mathlib/GroupTheory/Subgroup/Basic.lean`
and `Mathlib/Combinatorics/SimpleGraph/Subgraph.lean`.
## TODO
* Equivalent inductive characterization of generated (normal) subgroupoids.
* Characterization of normal subgroupoids as kernels.
* Prove that `CategoryTheory.Subgroupoid.full` and `CategoryTheory.Subgroupoid.disconnect` preserve
intersections (and `CategoryTheory.Subgroupoid.disconnect` also unions)
## Tags
category theory, groupoid, subgroupoid
-/
namespace CategoryTheory
open Set Groupoid
universe u v
variable {C : Type u} [Groupoid C]
/-- A sugroupoid of `C` consists of a choice of arrows for each pair of vertices, closed
under composition and inverses.
-/
@[ext]
structure Subgroupoid (C : Type u) [Groupoid C] where
arrows : ∀ c d : C, Set (c ⟶ d)
protected inv : ∀ {c d} {p : c ⟶ d}, p ∈ arrows c d → Groupoid.inv p ∈ arrows d c
protected mul : ∀ {c d e} {p}, p ∈ arrows c d → ∀ {q}, q ∈ arrows d e → p ≫ q ∈ arrows c e
#align category_theory.subgroupoid CategoryTheory.Subgroupoid
namespace Subgroupoid
variable (S : Subgroupoid C)
theorem inv_mem_iff {c d : C} (f : c ⟶ d) :
Groupoid.inv f ∈ S.arrows d c ↔ f ∈ S.arrows c d := by
constructor
· intro h
simpa only [inv_eq_inv, IsIso.inv_inv] using S.inv h
· apply S.inv
#align category_theory.subgroupoid.inv_mem_iff CategoryTheory.Subgroupoid.inv_mem_iff
theorem mul_mem_cancel_left {c d e : C} {f : c ⟶ d} {g : d ⟶ e} (hf : f ∈ S.arrows c d) :
f ≫ g ∈ S.arrows c e ↔ g ∈ S.arrows d e := by
constructor
· rintro h
suffices Groupoid.inv f ≫ f ≫ g ∈ S.arrows d e by
simpa only [inv_eq_inv, IsIso.inv_hom_id_assoc] using this
apply S.mul (S.inv hf) h
· apply S.mul hf
#align category_theory.subgroupoid.mul_mem_cancel_left CategoryTheory.Subgroupoid.mul_mem_cancel_left
theorem mul_mem_cancel_right {c d e : C} {f : c ⟶ d} {g : d ⟶ e} (hg : g ∈ S.arrows d e) :
f ≫ g ∈ S.arrows c e ↔ f ∈ S.arrows c d := by
constructor
· rintro h
suffices (f ≫ g) ≫ Groupoid.inv g ∈ S.arrows c d by
simpa only [inv_eq_inv, IsIso.hom_inv_id, Category.comp_id, Category.assoc] using this
apply S.mul h (S.inv hg)
· exact fun hf => S.mul hf hg
#align category_theory.subgroupoid.mul_mem_cancel_right CategoryTheory.Subgroupoid.mul_mem_cancel_right
/-- The vertices of `C` on which `S` has non-trivial isotropy -/
def objs : Set C :=
{c : C | (S.arrows c c).Nonempty}
#align category_theory.subgroupoid.objs CategoryTheory.Subgroupoid.objs
theorem mem_objs_of_src {c d : C} {f : c ⟶ d} (h : f ∈ S.arrows c d) : c ∈ S.objs :=
⟨f ≫ Groupoid.inv f, S.mul h (S.inv h)⟩
#align category_theory.subgroupoid.mem_objs_of_src CategoryTheory.Subgroupoid.mem_objs_of_src
theorem mem_objs_of_tgt {c d : C} {f : c ⟶ d} (h : f ∈ S.arrows c d) : d ∈ S.objs :=
⟨Groupoid.inv f ≫ f, S.mul (S.inv h) h⟩
#align category_theory.subgroupoid.mem_objs_of_tgt CategoryTheory.Subgroupoid.mem_objs_of_tgt
theorem id_mem_of_nonempty_isotropy (c : C) : c ∈ objs S → 𝟙 c ∈ S.arrows c c := by
rintro ⟨γ, hγ⟩
convert S.mul hγ (S.inv hγ)
simp only [inv_eq_inv, IsIso.hom_inv_id]
#align category_theory.subgroupoid.id_mem_of_nonempty_isotropy CategoryTheory.Subgroupoid.id_mem_of_nonempty_isotropy
theorem id_mem_of_src {c d : C} {f : c ⟶ d} (h : f ∈ S.arrows c d) : 𝟙 c ∈ S.arrows c c :=
id_mem_of_nonempty_isotropy S c (mem_objs_of_src S h)
#align category_theory.subgroupoid.id_mem_of_src CategoryTheory.Subgroupoid.id_mem_of_src
theorem id_mem_of_tgt {c d : C} {f : c ⟶ d} (h : f ∈ S.arrows c d) : 𝟙 d ∈ S.arrows d d :=
id_mem_of_nonempty_isotropy S d (mem_objs_of_tgt S h)
#align category_theory.subgroupoid.id_mem_of_tgt CategoryTheory.Subgroupoid.id_mem_of_tgt
/-- A subgroupoid seen as a quiver on vertex set `C` -/
def asWideQuiver : Quiver C :=
⟨fun c d => Subtype <| S.arrows c d⟩
#align category_theory.subgroupoid.as_wide_quiver CategoryTheory.Subgroupoid.asWideQuiver
/-- The coercion of a subgroupoid as a groupoid -/
@[simps comp_coe, simps (config := .lemmasOnly) inv_coe]
instance coe : Groupoid S.objs where
Hom a b := S.arrows a.val b.val
id a := ⟨𝟙 a.val, id_mem_of_nonempty_isotropy S a.val a.prop⟩
comp p q := ⟨p.val ≫ q.val, S.mul p.prop q.prop⟩
inv p := ⟨Groupoid.inv p.val, S.inv p.prop⟩
#align category_theory.subgroupoid.coe CategoryTheory.Subgroupoid.coe
@[simp]
theorem coe_inv_coe' {c d : S.objs} (p : c ⟶ d) :
(CategoryTheory.inv p).val = CategoryTheory.inv p.val := by
simp only [← inv_eq_inv, coe_inv_coe]
#align category_theory.subgroupoid.coe_inv_coe' CategoryTheory.Subgroupoid.coe_inv_coe'
/-- The embedding of the coerced subgroupoid to its parent-/
def hom : S.objs ⥤ C where
obj c := c.val
map f := f.val
map_id _ := rfl
map_comp _ _ := rfl
#align category_theory.subgroupoid.hom CategoryTheory.Subgroupoid.hom
theorem hom.inj_on_objects : Function.Injective (hom S).obj := by
rintro ⟨c, hc⟩ ⟨d, hd⟩ hcd
simp only [Subtype.mk_eq_mk]; exact hcd
#align category_theory.subgroupoid.hom.inj_on_objects CategoryTheory.Subgroupoid.hom.inj_on_objects
theorem hom.faithful : ∀ c d, Function.Injective fun f : c ⟶ d => (hom S).map f := by
rintro ⟨c, hc⟩ ⟨d, hd⟩ ⟨f, hf⟩ ⟨g, hg⟩ hfg; exact Subtype.eq hfg
#align category_theory.subgroupoid.hom.faithful CategoryTheory.Subgroupoid.hom.faithful
/-- The subgroup of the vertex group at `c` given by the subgroupoid -/
def vertexSubgroup {c : C} (hc : c ∈ S.objs) : Subgroup (c ⟶ c) where
carrier := S.arrows c c
mul_mem' hf hg := S.mul hf hg
one_mem' := id_mem_of_nonempty_isotropy _ _ hc
inv_mem' hf := S.inv hf
#align category_theory.subgroupoid.vertex_subgroup CategoryTheory.Subgroupoid.vertexSubgroup
/-- The set of all arrows of a subgroupoid, as a set in `Σ c d : C, c ⟶ d`. -/
@[coe] def toSet (S : Subgroupoid C) : Set (Σ c d : C, c ⟶ d) :=
{F | F.2.2 ∈ S.arrows F.1 F.2.1}
instance : SetLike (Subgroupoid C) (Σ c d : C, c ⟶ d) where
coe := toSet
coe_injective' := fun ⟨S, _, _⟩ ⟨T, _, _⟩ h => by ext c d f; apply Set.ext_iff.1 h ⟨c, d, f⟩
theorem mem_iff (S : Subgroupoid C) (F : Σ c d, c ⟶ d) : F ∈ S ↔ F.2.2 ∈ S.arrows F.1 F.2.1 :=
Iff.rfl
#align category_theory.subgroupoid.mem_iff CategoryTheory.Subgroupoid.mem_iff
theorem le_iff (S T : Subgroupoid C) : S ≤ T ↔ ∀ {c d}, S.arrows c d ⊆ T.arrows c d := by
rw [SetLike.le_def, Sigma.forall]; exact forall_congr' fun c => Sigma.forall
#align category_theory.subgroupoid.le_iff CategoryTheory.Subgroupoid.le_iff
instance : Top (Subgroupoid C) :=
⟨{ arrows := fun _ _ => Set.univ
mul := by intros; trivial
inv := by intros; trivial }⟩
theorem mem_top {c d : C} (f : c ⟶ d) : f ∈ (⊤ : Subgroupoid C).arrows c d :=
trivial
#align category_theory.subgroupoid.mem_top CategoryTheory.Subgroupoid.mem_top
theorem mem_top_objs (c : C) : c ∈ (⊤ : Subgroupoid C).objs := by
dsimp [Top.top, objs]
simp only [univ_nonempty]
#align category_theory.subgroupoid.mem_top_objs CategoryTheory.Subgroupoid.mem_top_objs
instance : Bot (Subgroupoid C) :=
⟨{ arrows := fun _ _ => ∅
mul := False.elim
inv := False.elim }⟩
instance : Inhabited (Subgroupoid C) :=
⟨⊤⟩
instance : Inf (Subgroupoid C) :=
⟨fun S T =>
{ arrows := fun c d => S.arrows c d ∩ T.arrows c d
inv := fun hp ↦ ⟨S.inv hp.1, T.inv hp.2⟩
mul := fun hp _ hq ↦ ⟨S.mul hp.1 hq.1, T.mul hp.2 hq.2⟩ }⟩
instance : InfSet (Subgroupoid C) :=
⟨fun s =>
{ arrows := fun c d => ⋂ S ∈ s, Subgroupoid.arrows S c d
inv := fun hp ↦ by rw [mem_iInter₂] at hp ⊢; exact fun S hS => S.inv (hp S hS)
mul := fun hp _ hq ↦ by
rw [mem_iInter₂] at hp hq ⊢;
exact fun S hS => S.mul (hp S hS) (hq S hS) }⟩
-- Porting note (#10756): new lemma
theorem mem_sInf_arrows {s : Set (Subgroupoid C)} {c d : C} {p : c ⟶ d} :
p ∈ (sInf s).arrows c d ↔ ∀ S ∈ s, p ∈ S.arrows c d :=
mem_iInter₂
theorem mem_sInf {s : Set (Subgroupoid C)} {p : Σ c d : C, c ⟶ d} :
p ∈ sInf s ↔ ∀ S ∈ s, p ∈ S :=
mem_sInf_arrows
instance : CompleteLattice (Subgroupoid C) :=
{ completeLatticeOfInf (Subgroupoid C) (by
refine fun s => ⟨fun S Ss F => ?_, fun T Tl F fT => ?_⟩ <;> simp only [mem_sInf]
exacts [fun hp => hp S Ss, fun S Ss => Tl Ss fT]) with
bot := ⊥
bot_le := fun S => empty_subset _
top := ⊤
le_top := fun S => subset_univ _
inf := (· ⊓ ·)
le_inf := fun R S T RS RT _ pR => ⟨RS pR, RT pR⟩
inf_le_left := fun R S _ => And.left
inf_le_right := fun R S _ => And.right }
theorem le_objs {S T : Subgroupoid C} (h : S ≤ T) : S.objs ⊆ T.objs := fun s ⟨γ, hγ⟩ =>
⟨γ, @h ⟨s, s, γ⟩ hγ⟩
#align category_theory.subgroupoid.le_objs CategoryTheory.Subgroupoid.le_objs
/-- The functor associated to the embedding of subgroupoids -/
def inclusion {S T : Subgroupoid C} (h : S ≤ T) : S.objs ⥤ T.objs where
obj s := ⟨s.val, le_objs h s.prop⟩
map f := ⟨f.val, @h ⟨_, _, f.val⟩ f.prop⟩
map_id _ := rfl
map_comp _ _ := rfl
#align category_theory.subgroupoid.inclusion CategoryTheory.Subgroupoid.inclusion
theorem inclusion_inj_on_objects {S T : Subgroupoid C} (h : S ≤ T) :
Function.Injective (inclusion h).obj := fun ⟨s, hs⟩ ⟨t, ht⟩ => by
simpa only [inclusion, Subtype.mk_eq_mk] using id
#align category_theory.subgroupoid.inclusion_inj_on_objects CategoryTheory.Subgroupoid.inclusion_inj_on_objects
theorem inclusion_faithful {S T : Subgroupoid C} (h : S ≤ T) (s t : S.objs) :
Function.Injective fun f : s ⟶ t => (inclusion h).map f := fun ⟨f, hf⟩ ⟨g, hg⟩ => by
-- Porting note: was `...; simpa only [Subtype.mk_eq_mk] using id`
dsimp only [inclusion]; rw [Subtype.mk_eq_mk, Subtype.mk_eq_mk]; exact id
#align category_theory.subgroupoid.inclusion_faithful CategoryTheory.Subgroupoid.inclusion_faithful
theorem inclusion_refl {S : Subgroupoid C} : inclusion (le_refl S) = 𝟭 S.objs :=
Functor.hext (fun _ => rfl) fun _ _ _ => HEq.refl _
#align category_theory.subgroupoid.inclusion_refl CategoryTheory.Subgroupoid.inclusion_refl
theorem inclusion_trans {R S T : Subgroupoid C} (k : R ≤ S) (h : S ≤ T) :
inclusion (k.trans h) = inclusion k ⋙ inclusion h :=
rfl
#align category_theory.subgroupoid.inclusion_trans CategoryTheory.Subgroupoid.inclusion_trans
theorem inclusion_comp_embedding {S T : Subgroupoid C} (h : S ≤ T) : inclusion h ⋙ T.hom = S.hom :=
rfl
#align category_theory.subgroupoid.inclusion_comp_embedding CategoryTheory.Subgroupoid.inclusion_comp_embedding
/-- The family of arrows of the discrete groupoid -/
inductive Discrete.Arrows : ∀ c d : C, (c ⟶ d) → Prop
| id (c : C) : Discrete.Arrows c c (𝟙 c)
#align category_theory.subgroupoid.discrete.arrows CategoryTheory.Subgroupoid.Discrete.Arrows
/-- The only arrows of the discrete groupoid are the identity arrows. -/
def discrete : Subgroupoid C where
arrows c d := {p | Discrete.Arrows c d p}
inv := by rintro _ _ _ ⟨⟩; simp only [inv_eq_inv, IsIso.inv_id]; constructor
mul := by rintro _ _ _ _ ⟨⟩ _ ⟨⟩; rw [Category.comp_id]; constructor
#align category_theory.subgroupoid.discrete CategoryTheory.Subgroupoid.discrete
theorem mem_discrete_iff {c d : C} (f : c ⟶ d) :
f ∈ discrete.arrows c d ↔ ∃ h : c = d, f = eqToHom h :=
⟨by rintro ⟨⟩; exact ⟨rfl, rfl⟩, by rintro ⟨rfl, rfl⟩; constructor⟩
#align category_theory.subgroupoid.mem_discrete_iff CategoryTheory.Subgroupoid.mem_discrete_iff
/-- A subgroupoid is wide if its carrier set is all of `C`-/
structure IsWide : Prop where
wide : ∀ c, 𝟙 c ∈ S.arrows c c
#align category_theory.subgroupoid.is_wide CategoryTheory.Subgroupoid.IsWide
theorem isWide_iff_objs_eq_univ : S.IsWide ↔ S.objs = Set.univ := by
constructor
· rintro h
ext x; constructor <;> simp only [top_eq_univ, mem_univ, imp_true_iff, forall_true_left]
apply mem_objs_of_src S (h.wide x)
· rintro h
refine ⟨fun c => ?_⟩
obtain ⟨γ, γS⟩ := (le_of_eq h.symm : ⊤ ⊆ S.objs) (Set.mem_univ c)
exact id_mem_of_src S γS
#align category_theory.subgroupoid.is_wide_iff_objs_eq_univ CategoryTheory.Subgroupoid.isWide_iff_objs_eq_univ
theorem IsWide.id_mem {S : Subgroupoid C} (Sw : S.IsWide) (c : C) : 𝟙 c ∈ S.arrows c c :=
Sw.wide c
#align category_theory.subgroupoid.is_wide.id_mem CategoryTheory.Subgroupoid.IsWide.id_mem
theorem IsWide.eqToHom_mem {S : Subgroupoid C} (Sw : S.IsWide) {c d : C} (h : c = d) :
eqToHom h ∈ S.arrows c d := by cases h; simp only [eqToHom_refl]; apply Sw.id_mem c
#align category_theory.subgroupoid.is_wide.eq_to_hom_mem CategoryTheory.Subgroupoid.IsWide.eqToHom_mem
/-- A subgroupoid is normal if it is wide and satisfies the expected stability under conjugacy. -/
structure IsNormal extends IsWide S : Prop where
conj : ∀ {c d} (p : c ⟶ d) {γ : c ⟶ c}, γ ∈ S.arrows c c → Groupoid.inv p ≫ γ ≫ p ∈ S.arrows d d
#align category_theory.subgroupoid.is_normal CategoryTheory.Subgroupoid.IsNormal
theorem IsNormal.conj' {S : Subgroupoid C} (Sn : IsNormal S) :
∀ {c d} (p : d ⟶ c) {γ : c ⟶ c}, γ ∈ S.arrows c c → p ≫ γ ≫ Groupoid.inv p ∈ S.arrows d d :=
fun p γ hs => by convert Sn.conj (Groupoid.inv p) hs; simp
#align category_theory.subgroupoid.is_normal.conj' CategoryTheory.Subgroupoid.IsNormal.conj'
theorem IsNormal.conjugation_bij (Sn : IsNormal S) {c d} (p : c ⟶ d) :
Set.BijOn (fun γ : c ⟶ c => Groupoid.inv p ≫ γ ≫ p) (S.arrows c c) (S.arrows d d) := by
refine ⟨fun γ γS => Sn.conj p γS, fun γ₁ _ γ₂ _ h => ?_, fun δ δS =>
⟨p ≫ δ ≫ Groupoid.inv p, Sn.conj' p δS, ?_⟩⟩
· simpa only [inv_eq_inv, Category.assoc, IsIso.hom_inv_id, Category.comp_id,
IsIso.hom_inv_id_assoc] using p ≫= h =≫ inv p
· simp only [inv_eq_inv, Category.assoc, IsIso.inv_hom_id, Category.comp_id,
IsIso.inv_hom_id_assoc]
#align category_theory.subgroupoid.is_normal.conjugation_bij CategoryTheory.Subgroupoid.IsNormal.conjugation_bij
theorem top_isNormal : IsNormal (⊤ : Subgroupoid C) :=
{ wide := fun _ => trivial
conj := fun _ _ _ => trivial }
#align category_theory.subgroupoid.top_is_normal CategoryTheory.Subgroupoid.top_isNormal
theorem sInf_isNormal (s : Set <| Subgroupoid C) (sn : ∀ S ∈ s, IsNormal S) : IsNormal (sInf s) :=
{ wide := by simp_rw [sInf, mem_iInter₂]; exact fun c S Ss => (sn S Ss).wide c
conj := by simp_rw [sInf, mem_iInter₂]; exact fun p γ hγ S Ss => (sn S Ss).conj p (hγ S Ss) }
#align category_theory.subgroupoid.Inf_is_normal CategoryTheory.Subgroupoid.sInf_isNormal
theorem discrete_isNormal : (@discrete C _).IsNormal :=
{ wide := fun c => by constructor
conj := fun f γ hγ => by
cases hγ
simp only [inv_eq_inv, Category.id_comp, IsIso.inv_hom_id]; constructor }
#align category_theory.subgroupoid.discrete_is_normal CategoryTheory.Subgroupoid.discrete_isNormal
theorem IsNormal.vertexSubgroup (Sn : IsNormal S) (c : C) (cS : c ∈ S.objs) :
(S.vertexSubgroup cS).Normal where
conj_mem x hx y := by rw [mul_assoc]; exact Sn.conj' y hx
#align category_theory.subgroupoid.is_normal.vertex_subgroup CategoryTheory.Subgroupoid.IsNormal.vertexSubgroup
section GeneratedSubgroupoid
-- TODO: proof that generated is just "words in X" and generatedNormal is similarly
variable (X : ∀ c d : C, Set (c ⟶ d))
/-- The subgropoid generated by the set of arrows `X` -/
def generated : Subgroupoid C :=
sInf {S : Subgroupoid C | ∀ c d, X c d ⊆ S.arrows c d}
#align category_theory.subgroupoid.generated CategoryTheory.Subgroupoid.generated
theorem subset_generated (c d : C) : X c d ⊆ (generated X).arrows c d := by
dsimp only [generated, sInf]
simp only [subset_iInter₂_iff]
exact fun S hS f fS => hS _ _ fS
#align category_theory.subgroupoid.subset_generated CategoryTheory.Subgroupoid.subset_generated
/-- The normal sugroupoid generated by the set of arrows `X` -/
def generatedNormal : Subgroupoid C :=
sInf {S : Subgroupoid C | (∀ c d, X c d ⊆ S.arrows c d) ∧ S.IsNormal}
#align category_theory.subgroupoid.generated_normal CategoryTheory.Subgroupoid.generatedNormal
theorem generated_le_generatedNormal : generated X ≤ generatedNormal X := by
apply @sInf_le_sInf (Subgroupoid C) _
exact fun S ⟨h, _⟩ => h
#align category_theory.subgroupoid.generated_le_generated_normal CategoryTheory.Subgroupoid.generated_le_generatedNormal
theorem generatedNormal_isNormal : (generatedNormal X).IsNormal :=
sInf_isNormal _ fun _ h => h.right
#align category_theory.subgroupoid.generated_normal_is_normal CategoryTheory.Subgroupoid.generatedNormal_isNormal
theorem IsNormal.generatedNormal_le {S : Subgroupoid C} (Sn : S.IsNormal) :
generatedNormal X ≤ S ↔ ∀ c d, X c d ⊆ S.arrows c d := by
constructor
· rintro h c d
have h' := generated_le_generatedNormal X
rw [le_iff] at h h'
exact ((subset_generated X c d).trans (@h' c d)).trans (@h c d)
· rintro h
apply @sInf_le (Subgroupoid C) _
exact ⟨h, Sn⟩
#align category_theory.subgroupoid.is_normal.generated_normal_le CategoryTheory.Subgroupoid.IsNormal.generatedNormal_le
end GeneratedSubgroupoid
section Hom
variable {D : Type*} [Groupoid D] (φ : C ⥤ D)
/-- A functor between groupoid defines a map of subgroupoids in the reverse direction
by taking preimages.
-/
def comap (S : Subgroupoid D) : Subgroupoid C where
arrows c d := {f : c ⟶ d | φ.map f ∈ S.arrows (φ.obj c) (φ.obj d)}
inv hp := by rw [mem_setOf, inv_eq_inv, φ.map_inv, ← inv_eq_inv]; exact S.inv hp
mul := by
intros
simp only [mem_setOf, Functor.map_comp]
apply S.mul <;> assumption
#align category_theory.subgroupoid.comap CategoryTheory.Subgroupoid.comap
theorem comap_mono (S T : Subgroupoid D) : S ≤ T → comap φ S ≤ comap φ T := fun ST _ =>
@ST ⟨_, _, _⟩
#align category_theory.subgroupoid.comap_mono CategoryTheory.Subgroupoid.comap_mono
theorem isNormal_comap {S : Subgroupoid D} (Sn : IsNormal S) : IsNormal (comap φ S) where
wide c := by rw [comap, mem_setOf, Functor.map_id]; apply Sn.wide
conj f γ hγ := by
simp_rw [inv_eq_inv f, comap, mem_setOf, Functor.map_comp, Functor.map_inv, ← inv_eq_inv]
exact Sn.conj _ hγ
#align category_theory.subgroupoid.is_normal_comap CategoryTheory.Subgroupoid.isNormal_comap
@[simp]
theorem comap_comp {E : Type*} [Groupoid E] (ψ : D ⥤ E) : comap (φ ⋙ ψ) = comap φ ∘ comap ψ :=
rfl
#align category_theory.subgroupoid.comap_comp CategoryTheory.Subgroupoid.comap_comp
/-- The kernel of a functor between subgroupoid is the preimage. -/
def ker : Subgroupoid C :=
comap φ discrete
#align category_theory.subgroupoid.ker CategoryTheory.Subgroupoid.ker
theorem mem_ker_iff {c d : C} (f : c ⟶ d) :
f ∈ (ker φ).arrows c d ↔ ∃ h : φ.obj c = φ.obj d, φ.map f = eqToHom h :=
mem_discrete_iff (φ.map f)
#align category_theory.subgroupoid.mem_ker_iff CategoryTheory.Subgroupoid.mem_ker_iff
theorem ker_isNormal : (ker φ).IsNormal :=
isNormal_comap φ discrete_isNormal
#align category_theory.subgroupoid.ker_is_normal CategoryTheory.Subgroupoid.ker_isNormal
@[simp]
theorem ker_comp {E : Type*} [Groupoid E] (ψ : D ⥤ E) : ker (φ ⋙ ψ) = comap φ (ker ψ) :=
rfl
#align category_theory.subgroupoid.ker_comp CategoryTheory.Subgroupoid.ker_comp
/-- The family of arrows of the image of a subgroupoid under a functor injective on objects -/
inductive Map.Arrows (hφ : Function.Injective φ.obj) (S : Subgroupoid C) : ∀ c d : D, (c ⟶ d) → Prop
| im {c d : C} (f : c ⟶ d) (hf : f ∈ S.arrows c d) : Map.Arrows hφ S (φ.obj c) (φ.obj d) (φ.map f)
#align category_theory.subgroupoid.map.arrows CategoryTheory.Subgroupoid.Map.Arrows
theorem Map.arrows_iff (hφ : Function.Injective φ.obj) (S : Subgroupoid C) {c d : D} (f : c ⟶ d) :
Map.Arrows φ hφ S c d f ↔
∃ (a b : C) (g : a ⟶ b) (ha : φ.obj a = c) (hb : φ.obj b = d) (_hg : g ∈ S.arrows a b),
f = eqToHom ha.symm ≫ φ.map g ≫ eqToHom hb := by
constructor
· rintro ⟨g, hg⟩; exact ⟨_, _, g, rfl, rfl, hg, eq_conj_eqToHom _⟩
· rintro ⟨a, b, g, rfl, rfl, hg, rfl⟩; rw [← eq_conj_eqToHom]; constructor; exact hg
#align category_theory.subgroupoid.map.arrows_iff CategoryTheory.Subgroupoid.Map.arrows_iff
/-- The "forward" image of a subgroupoid under a functor injective on objects -/
def map (hφ : Function.Injective φ.obj) (S : Subgroupoid C) : Subgroupoid D where
arrows c d := {x | Map.Arrows φ hφ S c d x}
inv := by
rintro _ _ _ ⟨⟩
rw [inv_eq_inv, ← Functor.map_inv, ← inv_eq_inv]
constructor; apply S.inv; assumption
mul := by
rintro _ _ _ _ ⟨f, hf⟩ q hq
obtain ⟨c₃, c₄, g, he, rfl, hg, gq⟩ := (Map.arrows_iff φ hφ S q).mp hq
cases hφ he; rw [gq, ← eq_conj_eqToHom, ← φ.map_comp]
constructor; exact S.mul hf hg
#align category_theory.subgroupoid.map CategoryTheory.Subgroupoid.map
theorem mem_map_iff (hφ : Function.Injective φ.obj) (S : Subgroupoid C) {c d : D} (f : c ⟶ d) :
f ∈ (map φ hφ S).arrows c d ↔
∃ (a b : C) (g : a ⟶ b) (ha : φ.obj a = c) (hb : φ.obj b = d) (_hg : g ∈ S.arrows a b),
f = eqToHom ha.symm ≫ φ.map g ≫ eqToHom hb :=
Map.arrows_iff φ hφ S f
#align category_theory.subgroupoid.mem_map_iff CategoryTheory.Subgroupoid.mem_map_iff
theorem galoisConnection_map_comap (hφ : Function.Injective φ.obj) :
GaloisConnection (map φ hφ) (comap φ) := by
rintro S T; simp_rw [le_iff]; constructor
· exact fun h c d f fS => h (Map.Arrows.im f fS)
· rintro h _ _ g ⟨a, gφS⟩
exact h gφS
#align category_theory.subgroupoid.galois_connection_map_comap CategoryTheory.Subgroupoid.galoisConnection_map_comap
theorem map_mono (hφ : Function.Injective φ.obj) (S T : Subgroupoid C) :
S ≤ T → map φ hφ S ≤ map φ hφ T := fun h => (galoisConnection_map_comap φ hφ).monotone_l h
#align category_theory.subgroupoid.map_mono CategoryTheory.Subgroupoid.map_mono
theorem le_comap_map (hφ : Function.Injective φ.obj) (S : Subgroupoid C) :
S ≤ comap φ (map φ hφ S) :=
(galoisConnection_map_comap φ hφ).le_u_l S
#align category_theory.subgroupoid.le_comap_map CategoryTheory.Subgroupoid.le_comap_map
theorem map_comap_le (hφ : Function.Injective φ.obj) (T : Subgroupoid D) :
map φ hφ (comap φ T) ≤ T :=
(galoisConnection_map_comap φ hφ).l_u_le T
#align category_theory.subgroupoid.map_comap_le CategoryTheory.Subgroupoid.map_comap_le
theorem map_le_iff_le_comap (hφ : Function.Injective φ.obj) (S : Subgroupoid C)
(T : Subgroupoid D) : map φ hφ S ≤ T ↔ S ≤ comap φ T :=
(galoisConnection_map_comap φ hφ).le_iff_le
#align category_theory.subgroupoid.map_le_iff_le_comap CategoryTheory.Subgroupoid.map_le_iff_le_comap
theorem mem_map_objs_iff (hφ : Function.Injective φ.obj) (d : D) :
d ∈ (map φ hφ S).objs ↔ ∃ c ∈ S.objs, φ.obj c = d := by
dsimp [objs, map]
constructor
· rintro ⟨f, hf⟩
change Map.Arrows φ hφ S d d f at hf; rw [Map.arrows_iff] at hf
obtain ⟨c, d, g, ec, ed, eg, gS, eg⟩ := hf
exact ⟨c, ⟨mem_objs_of_src S eg, ec⟩⟩
· rintro ⟨c, ⟨γ, γS⟩, rfl⟩
exact ⟨φ.map γ, ⟨γ, γS⟩⟩
#align category_theory.subgroupoid.mem_map_objs_iff CategoryTheory.Subgroupoid.mem_map_objs_iff
@[simp]
theorem map_objs_eq (hφ : Function.Injective φ.obj) : (map φ hφ S).objs = φ.obj '' S.objs := by
ext x; convert mem_map_objs_iff S φ hφ x
#align category_theory.subgroupoid.map_objs_eq CategoryTheory.Subgroupoid.map_objs_eq
/-- The image of a functor injective on objects -/
def im (hφ : Function.Injective φ.obj) :=
map φ hφ ⊤
#align category_theory.subgroupoid.im CategoryTheory.Subgroupoid.im
theorem mem_im_iff (hφ : Function.Injective φ.obj) {c d : D} (f : c ⟶ d) :
f ∈ (im φ hφ).arrows c d ↔
∃ (a b : C) (g : a ⟶ b) (ha : φ.obj a = c) (hb : φ.obj b = d),
f = eqToHom ha.symm ≫ φ.map g ≫ eqToHom hb := by
convert Map.arrows_iff φ hφ ⊤ f; simp only [Top.top, mem_univ, exists_true_left]
#align category_theory.subgroupoid.mem_im_iff CategoryTheory.Subgroupoid.mem_im_iff
theorem mem_im_objs_iff (hφ : Function.Injective φ.obj) (d : D) :
d ∈ (im φ hφ).objs ↔ ∃ c : C, φ.obj c = d := by
simp only [im, mem_map_objs_iff, mem_top_objs, true_and]
#align category_theory.subgroupoid.mem_im_objs_iff CategoryTheory.Subgroupoid.mem_im_objs_iff
theorem obj_surjective_of_im_eq_top (hφ : Function.Injective φ.obj) (hφ' : im φ hφ = ⊤) :
Function.Surjective φ.obj := by
rintro d
rw [← mem_im_objs_iff, hφ']
apply mem_top_objs
#align category_theory.subgroupoid.obj_surjective_of_im_eq_top CategoryTheory.Subgroupoid.obj_surjective_of_im_eq_top
theorem isNormal_map (hφ : Function.Injective φ.obj) (hφ' : im φ hφ = ⊤) (Sn : S.IsNormal) :
(map φ hφ S).IsNormal :=
{ wide := fun d => by
obtain ⟨c, rfl⟩ := obj_surjective_of_im_eq_top φ hφ hφ' d
change Map.Arrows φ hφ S _ _ (𝟙 _); rw [← Functor.map_id]
constructor; exact Sn.wide c
conj := fun {d d'} g δ hδ => by
rw [mem_map_iff] at hδ
obtain ⟨c, c', γ, cd, cd', γS, hγ⟩ := hδ; subst_vars; cases hφ cd'
have : d' ∈ (im φ hφ).objs := by rw [hφ']; apply mem_top_objs
rw [mem_im_objs_iff] at this
obtain ⟨c', rfl⟩ := this
have : g ∈ (im φ hφ).arrows (φ.obj c) (φ.obj c') := by rw [hφ']; trivial
rw [mem_im_iff] at this
obtain ⟨b, b', f, hb, hb', _, hf⟩ := this; cases hφ hb; cases hφ hb'
change Map.Arrows φ hφ S (φ.obj c') (φ.obj c') _
simp only [eqToHom_refl, Category.comp_id, Category.id_comp, inv_eq_inv]
suffices Map.Arrows φ hφ S (φ.obj c') (φ.obj c') (φ.map <| Groupoid.inv f ≫ γ ≫ f) by
simp only [inv_eq_inv, Functor.map_comp, Functor.map_inv] at this; exact this
constructor; apply Sn.conj f γS }
#align category_theory.subgroupoid.is_normal_map CategoryTheory.Subgroupoid.isNormal_map
end Hom
section Thin
/-- A subgroupoid is thin (`CategoryTheory.Subgroupoid.IsThin`) if it has at most one arrow between
any two vertices. -/
abbrev IsThin :=
Quiver.IsThin S.objs
#align category_theory.subgroupoid.is_thin CategoryTheory.Subgroupoid.IsThin
nonrec theorem isThin_iff : S.IsThin ↔ ∀ c : S.objs, Subsingleton (S.arrows c c) := isThin_iff _
#align category_theory.subgroupoid.is_thin_iff CategoryTheory.Subgroupoid.isThin_iff
end Thin
section Disconnected
/-- A subgroupoid `IsTotallyDisconnected` if it has only isotropy arrows. -/
nonrec abbrev IsTotallyDisconnected :=
IsTotallyDisconnected S.objs
#align category_theory.subgroupoid.is_totally_disconnected CategoryTheory.Subgroupoid.IsTotallyDisconnected
theorem isTotallyDisconnected_iff :
S.IsTotallyDisconnected ↔ ∀ c d, (S.arrows c d).Nonempty → c = d := by
constructor
· rintro h c d ⟨f, fS⟩
have := h ⟨c, mem_objs_of_src S fS⟩ ⟨d, mem_objs_of_tgt S fS⟩ ⟨f, fS⟩
exact congr_arg Subtype.val this
· rintro h ⟨c, hc⟩ ⟨d, hd⟩ ⟨f, fS⟩
simp only [Subtype.mk_eq_mk]
exact h c d ⟨f, fS⟩
#align category_theory.subgroupoid.is_totally_disconnected_iff CategoryTheory.Subgroupoid.isTotallyDisconnected_iff
/-- The isotropy subgroupoid of `S` -/
def disconnect : Subgroupoid C where
arrows c d := {f | c = d ∧ f ∈ S.arrows c d}
inv := by rintro _ _ _ ⟨rfl, h⟩; exact ⟨rfl, S.inv h⟩
mul := by rintro _ _ _ _ ⟨rfl, h⟩ _ ⟨rfl, h'⟩; exact ⟨rfl, S.mul h h'⟩
#align category_theory.subgroupoid.disconnect CategoryTheory.Subgroupoid.disconnect
| Mathlib/CategoryTheory/Groupoid/Subgroupoid.lean | 635 | 635 | theorem disconnect_le : S.disconnect ≤ S := by | rw [le_iff]; rintro _ _ _ ⟨⟩; assumption
|
/-
Copyright (c) 2023 Peter Nelson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Peter Nelson
-/
import Mathlib.Data.Matroid.IndepAxioms
/-!
# Matroid Duality
For a matroid `M` on ground set `E`, the collection of complements of the bases of `M` is the
collection of bases of another matroid on `E` called the 'dual' of `M`.
The map from `M` to its dual is an involution, interacts nicely with minors,
and preserves many important matroid properties such as representability and connectivity.
This file defines the dual matroid `M✶` of `M`, and gives associated API. The definition
is in terms of its independent sets, using `IndepMatroid.matroid`.
We also define 'Co-independence' (independence in the dual) of a set as a predicate `M.Coindep X`.
This is an abbreviation for `M✶.Indep X`, but has its own name for the sake of dot notation.
## Main Definitions
* `M.Dual`, written `M✶`, is the matroid in which a set `B` is a base if and only if `B ⊆ M.E`
and `M.E \ B` is a base for `M`.
* `M.Coindep X` means `M✶.Indep X`, or equivalently that `X` is contained in `M.E \ B` for some
base `B` of `M`.
-/
open Set
namespace Matroid
variable {α : Type*} {M : Matroid α} {I B X : Set α}
section dual
/-- Given `M : Matroid α`, the `IndepMatroid α` whose independent sets are
the subsets of `M.E` that are disjoint from some base of `M` -/
@[simps] def dualIndepMatroid (M : Matroid α) : IndepMatroid α where
E := M.E
Indep I := I ⊆ M.E ∧ ∃ B, M.Base B ∧ Disjoint I B
indep_empty := ⟨empty_subset M.E, M.exists_base.imp (fun B hB ↦ ⟨hB, empty_disjoint _⟩)⟩
indep_subset := by
rintro I J ⟨hJE, B, hB, hJB⟩ hIJ
exact ⟨hIJ.trans hJE, ⟨B, hB, disjoint_of_subset_left hIJ hJB⟩⟩
indep_aug := by
rintro I X ⟨hIE, B, hB, hIB⟩ hI_not_max hX_max
have hXE := hX_max.1.1
have hB' := (base_compl_iff_mem_maximals_disjoint_base hXE).mpr hX_max
set B' := M.E \ X with hX
have hI := (not_iff_not.mpr (base_compl_iff_mem_maximals_disjoint_base)).mpr hI_not_max
obtain ⟨B'', hB'', hB''₁, hB''₂⟩ := (hB'.indep.diff I).exists_base_subset_union_base hB
rw [← compl_subset_compl, ← hIB.sdiff_eq_right, ← union_diff_distrib, diff_eq, compl_inter,
compl_compl, union_subset_iff, compl_subset_compl] at hB''₂
have hssu := (subset_inter (hB''₂.2) hIE).ssubset_of_ne
(by { rintro rfl; apply hI; convert hB''; simp [hB''.subset_ground] })
obtain ⟨e, ⟨(heB'' : e ∉ _), heE⟩, heI⟩ := exists_of_ssubset hssu
use e
simp_rw [mem_diff, insert_subset_iff, and_iff_left heI, and_iff_right heE, and_iff_right hIE]
refine ⟨by_contra (fun heX ↦ heB'' (hB''₁ ⟨?_, heI⟩)), ⟨B'', hB'', ?_⟩⟩
· rw [hX]; exact ⟨heE, heX⟩
rw [← union_singleton, disjoint_union_left, disjoint_singleton_left, and_iff_left heB'']
exact disjoint_of_subset_left hB''₂.2 disjoint_compl_left
indep_maximal := by
rintro X - I'⟨hI'E, B, hB, hI'B⟩ hI'X
obtain ⟨I, hI⟩ := M.exists_basis (M.E \ X)
obtain ⟨B', hB', hIB', hB'IB⟩ := hI.indep.exists_base_subset_union_base hB
refine ⟨(X \ B') ∩ M.E,
⟨?_, subset_inter (subset_diff.mpr ?_) hI'E, inter_subset_left.trans
diff_subset⟩, ?_⟩
· simp only [inter_subset_right, true_and]
exact ⟨B', hB', disjoint_of_subset_left inter_subset_left disjoint_sdiff_left⟩
· rw [and_iff_right hI'X]
refine disjoint_of_subset_right hB'IB ?_
rw [disjoint_union_right, and_iff_left hI'B]
exact disjoint_of_subset hI'X hI.subset disjoint_sdiff_right
simp only [mem_setOf_eq, subset_inter_iff, and_imp, forall_exists_index]
intros J hJE B'' hB'' hdj _ hJX hssJ
rw [and_iff_left hJE]
rw [diff_eq, inter_right_comm, ← diff_eq, diff_subset_iff] at hssJ
have hI' : (B'' ∩ X) ∪ (B' \ X) ⊆ B' := by
rw [union_subset_iff, and_iff_left diff_subset,
← inter_eq_self_of_subset_left hB''.subset_ground, inter_right_comm, inter_assoc]
calc _ ⊆ _ := inter_subset_inter_right _ hssJ
_ ⊆ _ := by rw [inter_union_distrib_left, hdj.symm.inter_eq, union_empty]
_ ⊆ _ := inter_subset_right
obtain ⟨B₁,hB₁,hI'B₁,hB₁I⟩ := (hB'.indep.subset hI').exists_base_subset_union_base hB''
rw [union_comm, ← union_assoc, union_eq_self_of_subset_right inter_subset_left] at hB₁I
have : B₁ = B' := by
refine hB₁.eq_of_subset_indep hB'.indep (fun e he ↦ ?_)
refine (hB₁I he).elim (fun heB'' ↦ ?_) (fun h ↦ h.1)
refine (em (e ∈ X)).elim (fun heX ↦ hI' (Or.inl ⟨heB'', heX⟩)) (fun heX ↦ hIB' ?_)
refine hI.mem_of_insert_indep ⟨hB₁.subset_ground he, heX⟩
(hB₁.indep.subset (insert_subset he ?_))
refine (subset_union_of_subset_right (subset_diff.mpr ⟨hIB',?_⟩) _).trans hI'B₁
exact disjoint_of_subset_left hI.subset disjoint_sdiff_left
subst this
refine subset_diff.mpr ⟨hJX, by_contra (fun hne ↦ ?_)⟩
obtain ⟨e, heJ, heB'⟩ := not_disjoint_iff.mp hne
obtain (heB'' | ⟨-,heX⟩ ) := hB₁I heB'
· exact hdj.ne_of_mem heJ heB'' rfl
exact heX (hJX heJ)
subset_ground := by tauto
/-- The dual of a matroid; the bases are the complements (w.r.t `M.E`) of the bases of `M`. -/
def dual (M : Matroid α) : Matroid α := M.dualIndepMatroid.matroid
/-- The `✶` symbol, which denotes matroid duality.
(This is distinct from the usual `*` symbol for multiplication, due to precedence issues. )-/
postfix:max "✶" => Matroid.dual
theorem dual_indep_iff_exists' : (M✶.Indep I) ↔ I ⊆ M.E ∧ (∃ B, M.Base B ∧ Disjoint I B) := Iff.rfl
@[simp] theorem dual_ground : M✶.E = M.E := rfl
@[simp] theorem dual_indep_iff_exists (hI : I ⊆ M.E := by aesop_mat) :
M✶.Indep I ↔ (∃ B, M.Base B ∧ Disjoint I B) := by
rw [dual_indep_iff_exists', and_iff_right hI]
theorem dual_dep_iff_forall : (M✶.Dep I) ↔ (∀ B, M.Base B → (I ∩ B).Nonempty) ∧ I ⊆ M.E := by
simp_rw [dep_iff, dual_indep_iff_exists', dual_ground, and_congr_left_iff, not_and,
not_exists, not_and, not_disjoint_iff_nonempty_inter, Classical.imp_iff_right_iff,
iff_true_intro Or.inl]
instance dual_finite [M.Finite] : M✶.Finite :=
⟨M.ground_finite⟩
instance dual_nonempty [M.Nonempty] : M✶.Nonempty :=
⟨M.ground_nonempty⟩
@[simp] theorem dual_base_iff (hB : B ⊆ M.E := by aesop_mat) : M✶.Base B ↔ M.Base (M.E \ B) := by
rw [base_compl_iff_mem_maximals_disjoint_base, base_iff_maximal_indep, dual_indep_iff_exists',
mem_maximals_setOf_iff]
simp [dual_indep_iff_exists']
theorem dual_base_iff' : M✶.Base B ↔ M.Base (M.E \ B) ∧ B ⊆ M.E :=
(em (B ⊆ M.E)).elim (fun h ↦ by rw [dual_base_iff, and_iff_left h])
(fun h ↦ iff_of_false (h ∘ (fun h' ↦ h'.subset_ground)) (h ∘ And.right))
theorem setOf_dual_base_eq : {B | M✶.Base B} = (fun X ↦ M.E \ X) '' {B | M.Base B} := by
ext B
simp only [mem_setOf_eq, mem_image, dual_base_iff']
refine ⟨fun h ↦ ⟨_, h.1, diff_diff_cancel_left h.2⟩,
fun ⟨B', hB', h⟩ ↦ ⟨?_,h.symm.trans_subset diff_subset⟩⟩
rwa [← h, diff_diff_cancel_left hB'.subset_ground]
@[simp] theorem dual_dual (M : Matroid α) : M✶✶ = M :=
eq_of_base_iff_base_forall rfl (fun B (h : B ⊆ M.E) ↦
by rw [dual_base_iff, dual_base_iff, dual_ground, diff_diff_cancel_left h])
theorem dual_involutive : Function.Involutive (dual : Matroid α → Matroid α) := dual_dual
theorem dual_injective : Function.Injective (dual : Matroid α → Matroid α) :=
dual_involutive.injective
@[simp] theorem dual_inj {M₁ M₂ : Matroid α} : M₁✶ = M₂✶ ↔ M₁ = M₂ :=
dual_injective.eq_iff
theorem eq_dual_comm {M₁ M₂ : Matroid α} : M₁ = M₂✶ ↔ M₂ = M₁✶ := by
rw [← dual_inj, dual_dual, eq_comm]
theorem eq_dual_iff_dual_eq {M₁ M₂ : Matroid α} : M₁ = M₂✶ ↔ M₁✶ = M₂ :=
dual_involutive.eq_iff.symm
theorem Base.compl_base_of_dual (h : M✶.Base B) : M.Base (M.E \ B) :=
(dual_base_iff'.1 h).1
theorem Base.compl_base_dual (h : M.Base B) : M✶.Base (M.E \ B) := by
rwa [dual_base_iff, diff_diff_cancel_left h.subset_ground]
theorem Base.compl_inter_basis_of_inter_basis (hB : M.Base B) (hBX : M.Basis (B ∩ X) X) :
M✶.Basis ((M.E \ B) ∩ (M.E \ X)) (M.E \ X) := by
refine Indep.basis_of_forall_insert ?_ inter_subset_right (fun e he ↦ ?_)
· rw [dual_indep_iff_exists]
exact ⟨B, hB, disjoint_of_subset_left inter_subset_left disjoint_sdiff_left⟩
simp only [diff_inter_self_eq_diff, mem_diff, not_and, not_not, imp_iff_right he.1.1] at he
simp_rw [dual_dep_iff_forall, insert_subset_iff, and_iff_right he.1.1,
and_iff_left (inter_subset_left.trans diff_subset)]
refine fun B' hB' ↦ by_contra (fun hem ↦ ?_)
rw [nonempty_iff_ne_empty, not_ne_iff, ← union_singleton, diff_inter_diff,
union_inter_distrib_right, union_empty_iff, singleton_inter_eq_empty, diff_eq,
inter_right_comm, inter_eq_self_of_subset_right hB'.subset_ground, ← diff_eq,
diff_eq_empty] at hem
obtain ⟨f, hfb, hBf⟩ := hB.exchange hB' ⟨he.2, hem.2⟩
have hi : M.Indep (insert f (B ∩ X)) := by
refine hBf.indep.subset (insert_subset_insert ?_)
simp_rw [subset_diff, and_iff_right inter_subset_left, disjoint_singleton_right,
mem_inter_iff, iff_false_intro he.1.2, and_false, not_false_iff]
exact hfb.2 (hBX.mem_of_insert_indep (Or.elim (hem.1 hfb.1) (False.elim ∘ hfb.2) id) hi).1
| Mathlib/Data/Matroid/Dual.lean | 203 | 207 | theorem Base.inter_basis_iff_compl_inter_basis_dual (hB : M.Base B) (hX : X ⊆ M.E := by | aesop_mat):
M.Basis (B ∩ X) X ↔ M✶.Basis ((M.E \ B) ∩ (M.E \ X)) (M.E \ X) := by
refine ⟨hB.compl_inter_basis_of_inter_basis, fun h ↦ ?_⟩
simpa [inter_eq_self_of_subset_right hX, inter_eq_self_of_subset_right hB.subset_ground] using
hB.compl_base_dual.compl_inter_basis_of_inter_basis h
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Johannes Hölzl
-/
import Mathlib.MeasureTheory.Constructions.BorelSpace.Order
#align_import measure_theory.function.simple_func from "leanprover-community/mathlib"@"bf6a01357ff5684b1ebcd0f1a13be314fc82c0bf"
/-!
# Simple functions
A function `f` from a measurable space to any type is called *simple*, if every preimage `f ⁻¹' {x}`
is measurable, and the range is finite. In this file, we define simple functions and establish their
basic properties; and we construct a sequence of simple functions approximating an arbitrary Borel
measurable function `f : α → ℝ≥0∞`.
The theorem `Measurable.ennreal_induction` shows that in order to prove something for an arbitrary
measurable function into `ℝ≥0∞`, it is sufficient to show that the property holds for (multiples of)
characteristic functions and is closed under addition and supremum of increasing sequences of
functions.
-/
noncomputable section
open Set hiding restrict restrict_apply
open Filter ENNReal
open Function (support)
open scoped Classical
open Topology NNReal ENNReal MeasureTheory
namespace MeasureTheory
variable {α β γ δ : Type*}
/-- A function `f` from a measurable space to any type is called *simple*,
if every preimage `f ⁻¹' {x}` is measurable, and the range is finite. This structure bundles
a function with these properties. -/
structure SimpleFunc.{u, v} (α : Type u) [MeasurableSpace α] (β : Type v) where
toFun : α → β
measurableSet_fiber' : ∀ x, MeasurableSet (toFun ⁻¹' {x})
finite_range' : (Set.range toFun).Finite
#align measure_theory.simple_func MeasureTheory.SimpleFunc
#align measure_theory.simple_func.to_fun MeasureTheory.SimpleFunc.toFun
#align measure_theory.simple_func.measurable_set_fiber' MeasureTheory.SimpleFunc.measurableSet_fiber'
#align measure_theory.simple_func.finite_range' MeasureTheory.SimpleFunc.finite_range'
local infixr:25 " →ₛ " => SimpleFunc
namespace SimpleFunc
section Measurable
variable [MeasurableSpace α]
attribute [coe] toFun
instance instCoeFun : CoeFun (α →ₛ β) fun _ => α → β :=
⟨toFun⟩
#align measure_theory.simple_func.has_coe_to_fun MeasureTheory.SimpleFunc.instCoeFun
theorem coe_injective ⦃f g : α →ₛ β⦄ (H : (f : α → β) = g) : f = g := by
cases f; cases g; congr
#align measure_theory.simple_func.coe_injective MeasureTheory.SimpleFunc.coe_injective
@[ext]
theorem ext {f g : α →ₛ β} (H : ∀ a, f a = g a) : f = g :=
coe_injective <| funext H
#align measure_theory.simple_func.ext MeasureTheory.SimpleFunc.ext
theorem finite_range (f : α →ₛ β) : (Set.range f).Finite :=
f.finite_range'
#align measure_theory.simple_func.finite_range MeasureTheory.SimpleFunc.finite_range
theorem measurableSet_fiber (f : α →ₛ β) (x : β) : MeasurableSet (f ⁻¹' {x}) :=
f.measurableSet_fiber' x
#align measure_theory.simple_func.measurable_set_fiber MeasureTheory.SimpleFunc.measurableSet_fiber
-- @[simp] -- Porting note (#10618): simp can prove this
theorem apply_mk (f : α → β) (h h') (x : α) : SimpleFunc.mk f h h' x = f x :=
rfl
#align measure_theory.simple_func.apply_mk MeasureTheory.SimpleFunc.apply_mk
/-- Simple function defined on a finite type. -/
def ofFinite [Finite α] [MeasurableSingletonClass α] (f : α → β) : α →ₛ β where
toFun := f
measurableSet_fiber' x := (toFinite (f ⁻¹' {x})).measurableSet
finite_range' := Set.finite_range f
@[deprecated (since := "2024-02-05")] alias ofFintype := ofFinite
/-- Simple function defined on the empty type. -/
def ofIsEmpty [IsEmpty α] : α →ₛ β := ofFinite isEmptyElim
#align measure_theory.simple_func.of_is_empty MeasureTheory.SimpleFunc.ofIsEmpty
/-- Range of a simple function `α →ₛ β` as a `Finset β`. -/
protected def range (f : α →ₛ β) : Finset β :=
f.finite_range.toFinset
#align measure_theory.simple_func.range MeasureTheory.SimpleFunc.range
@[simp]
theorem mem_range {f : α →ₛ β} {b} : b ∈ f.range ↔ b ∈ range f :=
Finite.mem_toFinset _
#align measure_theory.simple_func.mem_range MeasureTheory.SimpleFunc.mem_range
theorem mem_range_self (f : α →ₛ β) (x : α) : f x ∈ f.range :=
mem_range.2 ⟨x, rfl⟩
#align measure_theory.simple_func.mem_range_self MeasureTheory.SimpleFunc.mem_range_self
@[simp]
theorem coe_range (f : α →ₛ β) : (↑f.range : Set β) = Set.range f :=
f.finite_range.coe_toFinset
#align measure_theory.simple_func.coe_range MeasureTheory.SimpleFunc.coe_range
theorem mem_range_of_measure_ne_zero {f : α →ₛ β} {x : β} {μ : Measure α} (H : μ (f ⁻¹' {x}) ≠ 0) :
x ∈ f.range :=
let ⟨a, ha⟩ := nonempty_of_measure_ne_zero H
mem_range.2 ⟨a, ha⟩
#align measure_theory.simple_func.mem_range_of_measure_ne_zero MeasureTheory.SimpleFunc.mem_range_of_measure_ne_zero
theorem forall_mem_range {f : α →ₛ β} {p : β → Prop} : (∀ y ∈ f.range, p y) ↔ ∀ x, p (f x) := by
simp only [mem_range, Set.forall_mem_range]
#align measure_theory.simple_func.forall_mem_range MeasureTheory.SimpleFunc.forall_mem_range
theorem exists_range_iff {f : α →ₛ β} {p : β → Prop} : (∃ y ∈ f.range, p y) ↔ ∃ x, p (f x) := by
simpa only [mem_range, exists_prop] using Set.exists_range_iff
#align measure_theory.simple_func.exists_range_iff MeasureTheory.SimpleFunc.exists_range_iff
theorem preimage_eq_empty_iff (f : α →ₛ β) (b : β) : f ⁻¹' {b} = ∅ ↔ b ∉ f.range :=
preimage_singleton_eq_empty.trans <| not_congr mem_range.symm
#align measure_theory.simple_func.preimage_eq_empty_iff MeasureTheory.SimpleFunc.preimage_eq_empty_iff
theorem exists_forall_le [Nonempty β] [Preorder β] [IsDirected β (· ≤ ·)] (f : α →ₛ β) :
∃ C, ∀ x, f x ≤ C :=
f.range.exists_le.imp fun _ => forall_mem_range.1
#align measure_theory.simple_func.exists_forall_le MeasureTheory.SimpleFunc.exists_forall_le
/-- Constant function as a `SimpleFunc`. -/
def const (α) {β} [MeasurableSpace α] (b : β) : α →ₛ β :=
⟨fun _ => b, fun _ => MeasurableSet.const _, finite_range_const⟩
#align measure_theory.simple_func.const MeasureTheory.SimpleFunc.const
instance instInhabited [Inhabited β] : Inhabited (α →ₛ β) :=
⟨const _ default⟩
#align measure_theory.simple_func.inhabited MeasureTheory.SimpleFunc.instInhabited
theorem const_apply (a : α) (b : β) : (const α b) a = b :=
rfl
#align measure_theory.simple_func.const_apply MeasureTheory.SimpleFunc.const_apply
@[simp]
theorem coe_const (b : β) : ⇑(const α b) = Function.const α b :=
rfl
#align measure_theory.simple_func.coe_const MeasureTheory.SimpleFunc.coe_const
@[simp]
theorem range_const (α) [MeasurableSpace α] [Nonempty α] (b : β) : (const α b).range = {b} :=
Finset.coe_injective <| by simp (config := { unfoldPartialApp := true }) [Function.const]
#align measure_theory.simple_func.range_const MeasureTheory.SimpleFunc.range_const
theorem range_const_subset (α) [MeasurableSpace α] (b : β) : (const α b).range ⊆ {b} :=
Finset.coe_subset.1 <| by simp
#align measure_theory.simple_func.range_const_subset MeasureTheory.SimpleFunc.range_const_subset
theorem simpleFunc_bot {α} (f : @SimpleFunc α ⊥ β) [Nonempty β] : ∃ c, ∀ x, f x = c := by
have hf_meas := @SimpleFunc.measurableSet_fiber α _ ⊥ f
simp_rw [MeasurableSpace.measurableSet_bot_iff] at hf_meas
exact (exists_eq_const_of_preimage_singleton hf_meas).imp fun c hc ↦ congr_fun hc
#align measure_theory.simple_func.simple_func_bot MeasureTheory.SimpleFunc.simpleFunc_bot
theorem simpleFunc_bot' {α} [Nonempty β] (f : @SimpleFunc α ⊥ β) :
∃ c, f = @SimpleFunc.const α _ ⊥ c :=
letI : MeasurableSpace α := ⊥; (simpleFunc_bot f).imp fun _ ↦ ext
#align measure_theory.simple_func.simple_func_bot' MeasureTheory.SimpleFunc.simpleFunc_bot'
theorem measurableSet_cut (r : α → β → Prop) (f : α →ₛ β) (h : ∀ b, MeasurableSet { a | r a b }) :
MeasurableSet { a | r a (f a) } := by
have : { a | r a (f a) } = ⋃ b ∈ range f, { a | r a b } ∩ f ⁻¹' {b} := by
ext a
suffices r a (f a) ↔ ∃ i, r a (f i) ∧ f a = f i by simpa
exact ⟨fun h => ⟨a, ⟨h, rfl⟩⟩, fun ⟨a', ⟨h', e⟩⟩ => e.symm ▸ h'⟩
rw [this]
exact
MeasurableSet.biUnion f.finite_range.countable fun b _ =>
MeasurableSet.inter (h b) (f.measurableSet_fiber _)
#align measure_theory.simple_func.measurable_set_cut MeasureTheory.SimpleFunc.measurableSet_cut
@[measurability]
theorem measurableSet_preimage (f : α →ₛ β) (s) : MeasurableSet (f ⁻¹' s) :=
measurableSet_cut (fun _ b => b ∈ s) f fun b => MeasurableSet.const (b ∈ s)
#align measure_theory.simple_func.measurable_set_preimage MeasureTheory.SimpleFunc.measurableSet_preimage
/-- A simple function is measurable -/
@[measurability]
protected theorem measurable [MeasurableSpace β] (f : α →ₛ β) : Measurable f := fun s _ =>
measurableSet_preimage f s
#align measure_theory.simple_func.measurable MeasureTheory.SimpleFunc.measurable
@[measurability]
protected theorem aemeasurable [MeasurableSpace β] {μ : Measure α} (f : α →ₛ β) :
AEMeasurable f μ :=
f.measurable.aemeasurable
#align measure_theory.simple_func.ae_measurable MeasureTheory.SimpleFunc.aemeasurable
protected theorem sum_measure_preimage_singleton (f : α →ₛ β) {μ : Measure α} (s : Finset β) :
(∑ y ∈ s, μ (f ⁻¹' {y})) = μ (f ⁻¹' ↑s) :=
sum_measure_preimage_singleton _ fun _ _ => f.measurableSet_fiber _
#align measure_theory.simple_func.sum_measure_preimage_singleton MeasureTheory.SimpleFunc.sum_measure_preimage_singleton
theorem sum_range_measure_preimage_singleton (f : α →ₛ β) (μ : Measure α) :
(∑ y ∈ f.range, μ (f ⁻¹' {y})) = μ univ := by
rw [f.sum_measure_preimage_singleton, coe_range, preimage_range]
#align measure_theory.simple_func.sum_range_measure_preimage_singleton MeasureTheory.SimpleFunc.sum_range_measure_preimage_singleton
/-- If-then-else as a `SimpleFunc`. -/
def piecewise (s : Set α) (hs : MeasurableSet s) (f g : α →ₛ β) : α →ₛ β :=
⟨s.piecewise f g, fun _ =>
letI : MeasurableSpace β := ⊤
f.measurable.piecewise hs g.measurable trivial,
(f.finite_range.union g.finite_range).subset range_ite_subset⟩
#align measure_theory.simple_func.piecewise MeasureTheory.SimpleFunc.piecewise
@[simp]
theorem coe_piecewise {s : Set α} (hs : MeasurableSet s) (f g : α →ₛ β) :
⇑(piecewise s hs f g) = s.piecewise f g :=
rfl
#align measure_theory.simple_func.coe_piecewise MeasureTheory.SimpleFunc.coe_piecewise
theorem piecewise_apply {s : Set α} (hs : MeasurableSet s) (f g : α →ₛ β) (a) :
piecewise s hs f g a = if a ∈ s then f a else g a :=
rfl
#align measure_theory.simple_func.piecewise_apply MeasureTheory.SimpleFunc.piecewise_apply
@[simp]
theorem piecewise_compl {s : Set α} (hs : MeasurableSet sᶜ) (f g : α →ₛ β) :
piecewise sᶜ hs f g = piecewise s hs.of_compl g f :=
coe_injective <| by
set_option tactic.skipAssignedInstances false in
simp [hs]; convert Set.piecewise_compl s f g
#align measure_theory.simple_func.piecewise_compl MeasureTheory.SimpleFunc.piecewise_compl
@[simp]
theorem piecewise_univ (f g : α →ₛ β) : piecewise univ MeasurableSet.univ f g = f :=
coe_injective <| by
set_option tactic.skipAssignedInstances false in
simp; convert Set.piecewise_univ f g
#align measure_theory.simple_func.piecewise_univ MeasureTheory.SimpleFunc.piecewise_univ
@[simp]
theorem piecewise_empty (f g : α →ₛ β) : piecewise ∅ MeasurableSet.empty f g = g :=
coe_injective <| by
set_option tactic.skipAssignedInstances false in
simp; convert Set.piecewise_empty f g
#align measure_theory.simple_func.piecewise_empty MeasureTheory.SimpleFunc.piecewise_empty
@[simp]
theorem piecewise_same (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) :
piecewise s hs f f = f :=
coe_injective <| Set.piecewise_same _ _
theorem support_indicator [Zero β] {s : Set α} (hs : MeasurableSet s) (f : α →ₛ β) :
Function.support (f.piecewise s hs (SimpleFunc.const α 0)) = s ∩ Function.support f :=
Set.support_indicator
#align measure_theory.simple_func.support_indicator MeasureTheory.SimpleFunc.support_indicator
theorem range_indicator {s : Set α} (hs : MeasurableSet s) (hs_nonempty : s.Nonempty)
(hs_ne_univ : s ≠ univ) (x y : β) :
(piecewise s hs (const α x) (const α y)).range = {x, y} := by
simp only [← Finset.coe_inj, coe_range, coe_piecewise, range_piecewise, coe_const,
Finset.coe_insert, Finset.coe_singleton, hs_nonempty.image_const,
(nonempty_compl.2 hs_ne_univ).image_const, singleton_union, Function.const]
#align measure_theory.simple_func.range_indicator MeasureTheory.SimpleFunc.range_indicator
theorem measurable_bind [MeasurableSpace γ] (f : α →ₛ β) (g : β → α → γ)
(hg : ∀ b, Measurable (g b)) : Measurable fun a => g (f a) a := fun s hs =>
f.measurableSet_cut (fun a b => g b a ∈ s) fun b => hg b hs
#align measure_theory.simple_func.measurable_bind MeasureTheory.SimpleFunc.measurable_bind
/-- If `f : α →ₛ β` is a simple function and `g : β → α →ₛ γ` is a family of simple functions,
then `f.bind g` binds the first argument of `g` to `f`. In other words, `f.bind g a = g (f a) a`. -/
def bind (f : α →ₛ β) (g : β → α →ₛ γ) : α →ₛ γ :=
⟨fun a => g (f a) a, fun c =>
f.measurableSet_cut (fun a b => g b a = c) fun b => (g b).measurableSet_preimage {c},
(f.finite_range.biUnion fun b _ => (g b).finite_range).subset <| by
rintro _ ⟨a, rfl⟩; simp⟩
#align measure_theory.simple_func.bind MeasureTheory.SimpleFunc.bind
@[simp]
theorem bind_apply (f : α →ₛ β) (g : β → α →ₛ γ) (a) : f.bind g a = g (f a) a :=
rfl
#align measure_theory.simple_func.bind_apply MeasureTheory.SimpleFunc.bind_apply
/-- Given a function `g : β → γ` and a simple function `f : α →ₛ β`, `f.map g` return the simple
function `g ∘ f : α →ₛ γ` -/
def map (g : β → γ) (f : α →ₛ β) : α →ₛ γ :=
bind f (const α ∘ g)
#align measure_theory.simple_func.map MeasureTheory.SimpleFunc.map
theorem map_apply (g : β → γ) (f : α →ₛ β) (a) : f.map g a = g (f a) :=
rfl
#align measure_theory.simple_func.map_apply MeasureTheory.SimpleFunc.map_apply
theorem map_map (g : β → γ) (h : γ → δ) (f : α →ₛ β) : (f.map g).map h = f.map (h ∘ g) :=
rfl
#align measure_theory.simple_func.map_map MeasureTheory.SimpleFunc.map_map
@[simp]
theorem coe_map (g : β → γ) (f : α →ₛ β) : (f.map g : α → γ) = g ∘ f :=
rfl
#align measure_theory.simple_func.coe_map MeasureTheory.SimpleFunc.coe_map
@[simp]
theorem range_map [DecidableEq γ] (g : β → γ) (f : α →ₛ β) : (f.map g).range = f.range.image g :=
Finset.coe_injective <| by simp only [coe_range, coe_map, Finset.coe_image, range_comp]
#align measure_theory.simple_func.range_map MeasureTheory.SimpleFunc.range_map
@[simp]
theorem map_const (g : β → γ) (b : β) : (const α b).map g = const α (g b) :=
rfl
#align measure_theory.simple_func.map_const MeasureTheory.SimpleFunc.map_const
theorem map_preimage (f : α →ₛ β) (g : β → γ) (s : Set γ) :
f.map g ⁻¹' s = f ⁻¹' ↑(f.range.filter fun b => g b ∈ s) := by
simp only [coe_range, sep_mem_eq, coe_map, Finset.coe_filter,
← mem_preimage, inter_comm, preimage_inter_range, ← Finset.mem_coe]
exact preimage_comp
#align measure_theory.simple_func.map_preimage MeasureTheory.SimpleFunc.map_preimage
theorem map_preimage_singleton (f : α →ₛ β) (g : β → γ) (c : γ) :
f.map g ⁻¹' {c} = f ⁻¹' ↑(f.range.filter fun b => g b = c) :=
map_preimage _ _ _
#align measure_theory.simple_func.map_preimage_singleton MeasureTheory.SimpleFunc.map_preimage_singleton
/-- Composition of a `SimpleFun` and a measurable function is a `SimpleFunc`. -/
def comp [MeasurableSpace β] (f : β →ₛ γ) (g : α → β) (hgm : Measurable g) : α →ₛ γ where
toFun := f ∘ g
finite_range' := f.finite_range.subset <| Set.range_comp_subset_range _ _
measurableSet_fiber' z := hgm (f.measurableSet_fiber z)
#align measure_theory.simple_func.comp MeasureTheory.SimpleFunc.comp
@[simp]
theorem coe_comp [MeasurableSpace β] (f : β →ₛ γ) {g : α → β} (hgm : Measurable g) :
⇑(f.comp g hgm) = f ∘ g :=
rfl
#align measure_theory.simple_func.coe_comp MeasureTheory.SimpleFunc.coe_comp
theorem range_comp_subset_range [MeasurableSpace β] (f : β →ₛ γ) {g : α → β} (hgm : Measurable g) :
(f.comp g hgm).range ⊆ f.range :=
Finset.coe_subset.1 <| by simp only [coe_range, coe_comp, Set.range_comp_subset_range]
#align measure_theory.simple_func.range_comp_subset_range MeasureTheory.SimpleFunc.range_comp_subset_range
/-- Extend a `SimpleFunc` along a measurable embedding: `f₁.extend g hg f₂` is the function
`F : β →ₛ γ` such that `F ∘ g = f₁` and `F y = f₂ y` whenever `y ∉ range g`. -/
def extend [MeasurableSpace β] (f₁ : α →ₛ γ) (g : α → β) (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) : β →ₛ γ where
toFun := Function.extend g f₁ f₂
finite_range' :=
(f₁.finite_range.union <| f₂.finite_range.subset (image_subset_range _ _)).subset
(range_extend_subset _ _ _)
measurableSet_fiber' := by
letI : MeasurableSpace γ := ⊤; haveI : MeasurableSingletonClass γ := ⟨fun _ => trivial⟩
exact fun x => hg.measurable_extend f₁.measurable f₂.measurable (measurableSet_singleton _)
#align measure_theory.simple_func.extend MeasureTheory.SimpleFunc.extend
@[simp]
theorem extend_apply [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) (x : α) : (f₁.extend g hg f₂) (g x) = f₁ x :=
hg.injective.extend_apply _ _ _
#align measure_theory.simple_func.extend_apply MeasureTheory.SimpleFunc.extend_apply
@[simp]
theorem extend_apply' [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) {y : β} (h : ¬∃ x, g x = y) : (f₁.extend g hg f₂) y = f₂ y :=
Function.extend_apply' _ _ _ h
#align measure_theory.simple_func.extend_apply' MeasureTheory.SimpleFunc.extend_apply'
@[simp]
theorem extend_comp_eq' [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) : f₁.extend g hg f₂ ∘ g = f₁ :=
funext fun _ => extend_apply _ _ _ _
#align measure_theory.simple_func.extend_comp_eq' MeasureTheory.SimpleFunc.extend_comp_eq'
@[simp]
theorem extend_comp_eq [MeasurableSpace β] (f₁ : α →ₛ γ) {g : α → β} (hg : MeasurableEmbedding g)
(f₂ : β →ₛ γ) : (f₁.extend g hg f₂).comp g hg.measurable = f₁ :=
coe_injective <| extend_comp_eq' _ hg _
#align measure_theory.simple_func.extend_comp_eq MeasureTheory.SimpleFunc.extend_comp_eq
/-- If `f` is a simple function taking values in `β → γ` and `g` is another simple function
with the same domain and codomain `β`, then `f.seq g = f a (g a)`. -/
def seq (f : α →ₛ β → γ) (g : α →ₛ β) : α →ₛ γ :=
f.bind fun f => g.map f
#align measure_theory.simple_func.seq MeasureTheory.SimpleFunc.seq
@[simp]
theorem seq_apply (f : α →ₛ β → γ) (g : α →ₛ β) (a : α) : f.seq g a = f a (g a) :=
rfl
#align measure_theory.simple_func.seq_apply MeasureTheory.SimpleFunc.seq_apply
/-- Combine two simple functions `f : α →ₛ β` and `g : α →ₛ β`
into `fun a => (f a, g a)`. -/
def pair (f : α →ₛ β) (g : α →ₛ γ) : α →ₛ β × γ :=
(f.map Prod.mk).seq g
#align measure_theory.simple_func.pair MeasureTheory.SimpleFunc.pair
@[simp]
theorem pair_apply (f : α →ₛ β) (g : α →ₛ γ) (a) : pair f g a = (f a, g a) :=
rfl
#align measure_theory.simple_func.pair_apply MeasureTheory.SimpleFunc.pair_apply
theorem pair_preimage (f : α →ₛ β) (g : α →ₛ γ) (s : Set β) (t : Set γ) :
pair f g ⁻¹' s ×ˢ t = f ⁻¹' s ∩ g ⁻¹' t :=
rfl
#align measure_theory.simple_func.pair_preimage MeasureTheory.SimpleFunc.pair_preimage
-- A special form of `pair_preimage`
theorem pair_preimage_singleton (f : α →ₛ β) (g : α →ₛ γ) (b : β) (c : γ) :
pair f g ⁻¹' {(b, c)} = f ⁻¹' {b} ∩ g ⁻¹' {c} := by
rw [← singleton_prod_singleton]
exact pair_preimage _ _ _ _
#align measure_theory.simple_func.pair_preimage_singleton MeasureTheory.SimpleFunc.pair_preimage_singleton
theorem bind_const (f : α →ₛ β) : f.bind (const α) = f := by ext; simp
#align measure_theory.simple_func.bind_const MeasureTheory.SimpleFunc.bind_const
@[to_additive]
instance instOne [One β] : One (α →ₛ β) :=
⟨const α 1⟩
#align measure_theory.simple_func.has_one MeasureTheory.SimpleFunc.instOne
#align measure_theory.simple_func.has_zero MeasureTheory.SimpleFunc.instZero
@[to_additive]
instance instMul [Mul β] : Mul (α →ₛ β) :=
⟨fun f g => (f.map (· * ·)).seq g⟩
#align measure_theory.simple_func.has_mul MeasureTheory.SimpleFunc.instMul
#align measure_theory.simple_func.has_add MeasureTheory.SimpleFunc.instAdd
@[to_additive]
instance instDiv [Div β] : Div (α →ₛ β) :=
⟨fun f g => (f.map (· / ·)).seq g⟩
#align measure_theory.simple_func.has_div MeasureTheory.SimpleFunc.instDiv
#align measure_theory.simple_func.has_sub MeasureTheory.SimpleFunc.instSub
@[to_additive]
instance instInv [Inv β] : Inv (α →ₛ β) :=
⟨fun f => f.map Inv.inv⟩
#align measure_theory.simple_func.has_inv MeasureTheory.SimpleFunc.instInv
#align measure_theory.simple_func.has_neg MeasureTheory.SimpleFunc.instNeg
instance instSup [Sup β] : Sup (α →ₛ β) :=
⟨fun f g => (f.map (· ⊔ ·)).seq g⟩
#align measure_theory.simple_func.has_sup MeasureTheory.SimpleFunc.instSup
instance instInf [Inf β] : Inf (α →ₛ β) :=
⟨fun f g => (f.map (· ⊓ ·)).seq g⟩
#align measure_theory.simple_func.has_inf MeasureTheory.SimpleFunc.instInf
instance instLE [LE β] : LE (α →ₛ β) :=
⟨fun f g => ∀ a, f a ≤ g a⟩
#align measure_theory.simple_func.has_le MeasureTheory.SimpleFunc.instLE
@[to_additive (attr := simp)]
theorem const_one [One β] : const α (1 : β) = 1 :=
rfl
#align measure_theory.simple_func.const_one MeasureTheory.SimpleFunc.const_one
#align measure_theory.simple_func.const_zero MeasureTheory.SimpleFunc.const_zero
@[to_additive (attr := simp, norm_cast)]
theorem coe_one [One β] : ⇑(1 : α →ₛ β) = 1 :=
rfl
#align measure_theory.simple_func.coe_one MeasureTheory.SimpleFunc.coe_one
#align measure_theory.simple_func.coe_zero MeasureTheory.SimpleFunc.coe_zero
@[to_additive (attr := simp, norm_cast)]
theorem coe_mul [Mul β] (f g : α →ₛ β) : ⇑(f * g) = ⇑f * ⇑g :=
rfl
#align measure_theory.simple_func.coe_mul MeasureTheory.SimpleFunc.coe_mul
#align measure_theory.simple_func.coe_add MeasureTheory.SimpleFunc.coe_add
@[to_additive (attr := simp, norm_cast)]
theorem coe_inv [Inv β] (f : α →ₛ β) : ⇑(f⁻¹) = (⇑f)⁻¹ :=
rfl
#align measure_theory.simple_func.coe_inv MeasureTheory.SimpleFunc.coe_inv
#align measure_theory.simple_func.coe_neg MeasureTheory.SimpleFunc.coe_neg
@[to_additive (attr := simp, norm_cast)]
theorem coe_div [Div β] (f g : α →ₛ β) : ⇑(f / g) = ⇑f / ⇑g :=
rfl
#align measure_theory.simple_func.coe_div MeasureTheory.SimpleFunc.coe_div
#align measure_theory.simple_func.coe_sub MeasureTheory.SimpleFunc.coe_sub
@[simp, norm_cast]
theorem coe_le [Preorder β] {f g : α →ₛ β} : (f : α → β) ≤ g ↔ f ≤ g :=
Iff.rfl
#align measure_theory.simple_func.coe_le MeasureTheory.SimpleFunc.coe_le
@[simp, norm_cast]
theorem coe_sup [Sup β] (f g : α →ₛ β) : ⇑(f ⊔ g) = ⇑f ⊔ ⇑g :=
rfl
#align measure_theory.simple_func.coe_sup MeasureTheory.SimpleFunc.coe_sup
@[simp, norm_cast]
theorem coe_inf [Inf β] (f g : α →ₛ β) : ⇑(f ⊓ g) = ⇑f ⊓ ⇑g :=
rfl
#align measure_theory.simple_func.coe_inf MeasureTheory.SimpleFunc.coe_inf
@[to_additive]
theorem mul_apply [Mul β] (f g : α →ₛ β) (a : α) : (f * g) a = f a * g a :=
rfl
#align measure_theory.simple_func.mul_apply MeasureTheory.SimpleFunc.mul_apply
#align measure_theory.simple_func.add_apply MeasureTheory.SimpleFunc.add_apply
@[to_additive]
theorem div_apply [Div β] (f g : α →ₛ β) (x : α) : (f / g) x = f x / g x :=
rfl
#align measure_theory.simple_func.div_apply MeasureTheory.SimpleFunc.div_apply
#align measure_theory.simple_func.sub_apply MeasureTheory.SimpleFunc.sub_apply
@[to_additive]
theorem inv_apply [Inv β] (f : α →ₛ β) (x : α) : f⁻¹ x = (f x)⁻¹ :=
rfl
#align measure_theory.simple_func.inv_apply MeasureTheory.SimpleFunc.inv_apply
#align measure_theory.simple_func.neg_apply MeasureTheory.SimpleFunc.neg_apply
theorem sup_apply [Sup β] (f g : α →ₛ β) (a : α) : (f ⊔ g) a = f a ⊔ g a :=
rfl
#align measure_theory.simple_func.sup_apply MeasureTheory.SimpleFunc.sup_apply
theorem inf_apply [Inf β] (f g : α →ₛ β) (a : α) : (f ⊓ g) a = f a ⊓ g a :=
rfl
#align measure_theory.simple_func.inf_apply MeasureTheory.SimpleFunc.inf_apply
@[to_additive (attr := simp)]
theorem range_one [Nonempty α] [One β] : (1 : α →ₛ β).range = {1} :=
Finset.ext fun x => by simp [eq_comm]
#align measure_theory.simple_func.range_one MeasureTheory.SimpleFunc.range_one
#align measure_theory.simple_func.range_zero MeasureTheory.SimpleFunc.range_zero
@[simp]
theorem range_eq_empty_of_isEmpty {β} [hα : IsEmpty α] (f : α →ₛ β) : f.range = ∅ := by
rw [← Finset.not_nonempty_iff_eq_empty]
by_contra h
obtain ⟨y, hy_mem⟩ := h
rw [SimpleFunc.mem_range, Set.mem_range] at hy_mem
obtain ⟨x, hxy⟩ := hy_mem
rw [isEmpty_iff] at hα
exact hα x
#align measure_theory.simple_func.range_eq_empty_of_is_empty MeasureTheory.SimpleFunc.range_eq_empty_of_isEmpty
theorem eq_zero_of_mem_range_zero [Zero β] : ∀ {y : β}, y ∈ (0 : α →ₛ β).range → y = 0 :=
@(forall_mem_range.2 fun _ => rfl)
#align measure_theory.simple_func.eq_zero_of_mem_range_zero MeasureTheory.SimpleFunc.eq_zero_of_mem_range_zero
@[to_additive]
theorem mul_eq_map₂ [Mul β] (f g : α →ₛ β) : f * g = (pair f g).map fun p : β × β => p.1 * p.2 :=
rfl
#align measure_theory.simple_func.mul_eq_map₂ MeasureTheory.SimpleFunc.mul_eq_map₂
#align measure_theory.simple_func.add_eq_map₂ MeasureTheory.SimpleFunc.add_eq_map₂
theorem sup_eq_map₂ [Sup β] (f g : α →ₛ β) : f ⊔ g = (pair f g).map fun p : β × β => p.1 ⊔ p.2 :=
rfl
#align measure_theory.simple_func.sup_eq_map₂ MeasureTheory.SimpleFunc.sup_eq_map₂
@[to_additive]
theorem const_mul_eq_map [Mul β] (f : α →ₛ β) (b : β) : const α b * f = f.map fun a => b * a :=
rfl
#align measure_theory.simple_func.const_mul_eq_map MeasureTheory.SimpleFunc.const_mul_eq_map
#align measure_theory.simple_func.const_add_eq_map MeasureTheory.SimpleFunc.const_add_eq_map
@[to_additive]
theorem map_mul [Mul β] [Mul γ] {g : β → γ} (hg : ∀ x y, g (x * y) = g x * g y) (f₁ f₂ : α →ₛ β) :
(f₁ * f₂).map g = f₁.map g * f₂.map g :=
ext fun _ => hg _ _
#align measure_theory.simple_func.map_mul MeasureTheory.SimpleFunc.map_mul
#align measure_theory.simple_func.map_add MeasureTheory.SimpleFunc.map_add
variable {K : Type*}
@[to_additive]
instance instSMul [SMul K β] : SMul K (α →ₛ β) :=
⟨fun k f => f.map (k • ·)⟩
#align measure_theory.simple_func.has_smul MeasureTheory.SimpleFunc.instSMul
@[to_additive (attr := simp)]
theorem coe_smul [SMul K β] (c : K) (f : α →ₛ β) : ⇑(c • f) = c • ⇑f :=
rfl
#align measure_theory.simple_func.coe_smul MeasureTheory.SimpleFunc.coe_smul
@[to_additive (attr := simp)]
theorem smul_apply [SMul K β] (k : K) (f : α →ₛ β) (a : α) : (k • f) a = k • f a :=
rfl
#align measure_theory.simple_func.smul_apply MeasureTheory.SimpleFunc.smul_apply
instance hasNatSMul [AddMonoid β] : SMul ℕ (α →ₛ β) := inferInstance
@[to_additive existing hasNatSMul]
instance hasNatPow [Monoid β] : Pow (α →ₛ β) ℕ :=
⟨fun f n => f.map (· ^ n)⟩
#align measure_theory.simple_func.has_nat_pow MeasureTheory.SimpleFunc.hasNatPow
@[simp]
theorem coe_pow [Monoid β] (f : α →ₛ β) (n : ℕ) : ⇑(f ^ n) = (⇑f) ^ n :=
rfl
#align measure_theory.simple_func.coe_pow MeasureTheory.SimpleFunc.coe_pow
theorem pow_apply [Monoid β] (n : ℕ) (f : α →ₛ β) (a : α) : (f ^ n) a = f a ^ n :=
rfl
#align measure_theory.simple_func.pow_apply MeasureTheory.SimpleFunc.pow_apply
instance hasIntPow [DivInvMonoid β] : Pow (α →ₛ β) ℤ :=
⟨fun f n => f.map (· ^ n)⟩
#align measure_theory.simple_func.has_int_pow MeasureTheory.SimpleFunc.hasIntPow
@[simp]
theorem coe_zpow [DivInvMonoid β] (f : α →ₛ β) (z : ℤ) : ⇑(f ^ z) = (⇑f) ^ z :=
rfl
#align measure_theory.simple_func.coe_zpow MeasureTheory.SimpleFunc.coe_zpow
theorem zpow_apply [DivInvMonoid β] (z : ℤ) (f : α →ₛ β) (a : α) : (f ^ z) a = f a ^ z :=
rfl
#align measure_theory.simple_func.zpow_apply MeasureTheory.SimpleFunc.zpow_apply
-- TODO: work out how to generate these instances with `to_additive`, which gets confused by the
-- argument order swap between `coe_smul` and `coe_pow`.
section Additive
instance instAddMonoid [AddMonoid β] : AddMonoid (α →ₛ β) :=
Function.Injective.addMonoid (fun f => show α → β from f) coe_injective coe_zero coe_add
fun _ _ => coe_smul _ _
#align measure_theory.simple_func.add_monoid MeasureTheory.SimpleFunc.instAddMonoid
instance instAddCommMonoid [AddCommMonoid β] : AddCommMonoid (α →ₛ β) :=
Function.Injective.addCommMonoid (fun f => show α → β from f) coe_injective coe_zero coe_add
fun _ _ => coe_smul _ _
#align measure_theory.simple_func.add_comm_monoid MeasureTheory.SimpleFunc.instAddCommMonoid
instance instAddGroup [AddGroup β] : AddGroup (α →ₛ β) :=
Function.Injective.addGroup (fun f => show α → β from f) coe_injective coe_zero coe_add coe_neg
coe_sub (fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _
#align measure_theory.simple_func.add_group MeasureTheory.SimpleFunc.instAddGroup
instance instAddCommGroup [AddCommGroup β] : AddCommGroup (α →ₛ β) :=
Function.Injective.addCommGroup (fun f => show α → β from f) coe_injective coe_zero coe_add
coe_neg coe_sub (fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _
#align measure_theory.simple_func.add_comm_group MeasureTheory.SimpleFunc.instAddCommGroup
end Additive
@[to_additive existing]
instance instMonoid [Monoid β] : Monoid (α →ₛ β) :=
Function.Injective.monoid (fun f => show α → β from f) coe_injective coe_one coe_mul coe_pow
#align measure_theory.simple_func.monoid MeasureTheory.SimpleFunc.instMonoid
@[to_additive existing]
instance instCommMonoid [CommMonoid β] : CommMonoid (α →ₛ β) :=
Function.Injective.commMonoid (fun f => show α → β from f) coe_injective coe_one coe_mul coe_pow
#align measure_theory.simple_func.comm_monoid MeasureTheory.SimpleFunc.instCommMonoid
@[to_additive existing]
instance instGroup [Group β] : Group (α →ₛ β) :=
Function.Injective.group (fun f => show α → β from f) coe_injective coe_one coe_mul coe_inv
coe_div coe_pow coe_zpow
#align measure_theory.simple_func.group MeasureTheory.SimpleFunc.instGroup
@[to_additive existing]
instance instCommGroup [CommGroup β] : CommGroup (α →ₛ β) :=
Function.Injective.commGroup (fun f => show α → β from f) coe_injective coe_one coe_mul coe_inv
coe_div coe_pow coe_zpow
#align measure_theory.simple_func.comm_group MeasureTheory.SimpleFunc.instCommGroup
instance instModule [Semiring K] [AddCommMonoid β] [Module K β] : Module K (α →ₛ β) :=
Function.Injective.module K ⟨⟨fun f => show α → β from f, coe_zero⟩, coe_add⟩
coe_injective coe_smul
#align measure_theory.simple_func.module MeasureTheory.SimpleFunc.instModule
theorem smul_eq_map [SMul K β] (k : K) (f : α →ₛ β) : k • f = f.map (k • ·) :=
rfl
#align measure_theory.simple_func.smul_eq_map MeasureTheory.SimpleFunc.smul_eq_map
instance instPreorder [Preorder β] : Preorder (α →ₛ β) :=
{ SimpleFunc.instLE with
le_refl := fun f a => le_rfl
le_trans := fun f g h hfg hgh a => le_trans (hfg _) (hgh a) }
#align measure_theory.simple_func.preorder MeasureTheory.SimpleFunc.instPreorder
instance instPartialOrder [PartialOrder β] : PartialOrder (α →ₛ β) :=
{ SimpleFunc.instPreorder with
le_antisymm := fun _f _g hfg hgf => ext fun a => le_antisymm (hfg a) (hgf a) }
#align measure_theory.simple_func.partial_order MeasureTheory.SimpleFunc.instPartialOrder
instance instOrderBot [LE β] [OrderBot β] : OrderBot (α →ₛ β) where
bot := const α ⊥
bot_le _ _ := bot_le
#align measure_theory.simple_func.order_bot MeasureTheory.SimpleFunc.instOrderBot
instance instOrderTop [LE β] [OrderTop β] : OrderTop (α →ₛ β) where
top := const α ⊤
le_top _ _ := le_top
#align measure_theory.simple_func.order_top MeasureTheory.SimpleFunc.instOrderTop
instance instSemilatticeInf [SemilatticeInf β] : SemilatticeInf (α →ₛ β) :=
{ SimpleFunc.instPartialOrder with
inf := (· ⊓ ·)
inf_le_left := fun _ _ _ => inf_le_left
inf_le_right := fun _ _ _ => inf_le_right
le_inf := fun _f _g _h hfh hgh a => le_inf (hfh a) (hgh a) }
#align measure_theory.simple_func.semilattice_inf MeasureTheory.SimpleFunc.instSemilatticeInf
instance instSemilatticeSup [SemilatticeSup β] : SemilatticeSup (α →ₛ β) :=
{ SimpleFunc.instPartialOrder with
sup := (· ⊔ ·)
le_sup_left := fun _ _ _ => le_sup_left
le_sup_right := fun _ _ _ => le_sup_right
sup_le := fun _f _g _h hfh hgh a => sup_le (hfh a) (hgh a) }
#align measure_theory.simple_func.semilattice_sup MeasureTheory.SimpleFunc.instSemilatticeSup
instance instLattice [Lattice β] : Lattice (α →ₛ β) :=
{ SimpleFunc.instSemilatticeSup, SimpleFunc.instSemilatticeInf with }
#align measure_theory.simple_func.lattice MeasureTheory.SimpleFunc.instLattice
instance instBoundedOrder [LE β] [BoundedOrder β] : BoundedOrder (α →ₛ β) :=
{ SimpleFunc.instOrderBot, SimpleFunc.instOrderTop with }
#align measure_theory.simple_func.bounded_order MeasureTheory.SimpleFunc.instBoundedOrder
theorem finset_sup_apply [SemilatticeSup β] [OrderBot β] {f : γ → α →ₛ β} (s : Finset γ) (a : α) :
s.sup f a = s.sup fun c => f c a := by
refine Finset.induction_on s rfl ?_
intro a s _ ih
rw [Finset.sup_insert, Finset.sup_insert, sup_apply, ih]
#align measure_theory.simple_func.finset_sup_apply MeasureTheory.SimpleFunc.finset_sup_apply
section Restrict
variable [Zero β]
/-- Restrict a simple function `f : α →ₛ β` to a set `s`. If `s` is measurable,
then `f.restrict s a = if a ∈ s then f a else 0`, otherwise `f.restrict s = const α 0`. -/
def restrict (f : α →ₛ β) (s : Set α) : α →ₛ β :=
if hs : MeasurableSet s then piecewise s hs f 0 else 0
#align measure_theory.simple_func.restrict MeasureTheory.SimpleFunc.restrict
theorem restrict_of_not_measurable {f : α →ₛ β} {s : Set α} (hs : ¬MeasurableSet s) :
restrict f s = 0 :=
dif_neg hs
#align measure_theory.simple_func.restrict_of_not_measurable MeasureTheory.SimpleFunc.restrict_of_not_measurable
@[simp]
theorem coe_restrict (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) :
⇑(restrict f s) = indicator s f := by
rw [restrict, dif_pos hs, coe_piecewise, coe_zero, piecewise_eq_indicator]
#align measure_theory.simple_func.coe_restrict MeasureTheory.SimpleFunc.coe_restrict
@[simp]
theorem restrict_univ (f : α →ₛ β) : restrict f univ = f := by simp [restrict]
#align measure_theory.simple_func.restrict_univ MeasureTheory.SimpleFunc.restrict_univ
@[simp]
theorem restrict_empty (f : α →ₛ β) : restrict f ∅ = 0 := by simp [restrict]
#align measure_theory.simple_func.restrict_empty MeasureTheory.SimpleFunc.restrict_empty
theorem map_restrict_of_zero [Zero γ] {g : β → γ} (hg : g 0 = 0) (f : α →ₛ β) (s : Set α) :
(f.restrict s).map g = (f.map g).restrict s :=
ext fun x =>
if hs : MeasurableSet s then by simp [hs, Set.indicator_comp_of_zero hg]
else by simp [restrict_of_not_measurable hs, hg]
#align measure_theory.simple_func.map_restrict_of_zero MeasureTheory.SimpleFunc.map_restrict_of_zero
theorem map_coe_ennreal_restrict (f : α →ₛ ℝ≥0) (s : Set α) :
(f.restrict s).map ((↑) : ℝ≥0 → ℝ≥0∞) = (f.map (↑)).restrict s :=
map_restrict_of_zero ENNReal.coe_zero _ _
#align measure_theory.simple_func.map_coe_ennreal_restrict MeasureTheory.SimpleFunc.map_coe_ennreal_restrict
theorem map_coe_nnreal_restrict (f : α →ₛ ℝ≥0) (s : Set α) :
(f.restrict s).map ((↑) : ℝ≥0 → ℝ) = (f.map (↑)).restrict s :=
map_restrict_of_zero NNReal.coe_zero _ _
#align measure_theory.simple_func.map_coe_nnreal_restrict MeasureTheory.SimpleFunc.map_coe_nnreal_restrict
theorem restrict_apply (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) (a) :
restrict f s a = indicator s f a := by simp only [f.coe_restrict hs]
#align measure_theory.simple_func.restrict_apply MeasureTheory.SimpleFunc.restrict_apply
theorem restrict_preimage (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) {t : Set β}
(ht : (0 : β) ∉ t) : restrict f s ⁻¹' t = s ∩ f ⁻¹' t := by
simp [hs, indicator_preimage_of_not_mem _ _ ht, inter_comm]
#align measure_theory.simple_func.restrict_preimage MeasureTheory.SimpleFunc.restrict_preimage
theorem restrict_preimage_singleton (f : α →ₛ β) {s : Set α} (hs : MeasurableSet s) {r : β}
(hr : r ≠ 0) : restrict f s ⁻¹' {r} = s ∩ f ⁻¹' {r} :=
f.restrict_preimage hs hr.symm
#align measure_theory.simple_func.restrict_preimage_singleton MeasureTheory.SimpleFunc.restrict_preimage_singleton
theorem mem_restrict_range {r : β} {s : Set α} {f : α →ₛ β} (hs : MeasurableSet s) :
r ∈ (restrict f s).range ↔ r = 0 ∧ s ≠ univ ∨ r ∈ f '' s := by
rw [← Finset.mem_coe, coe_range, coe_restrict _ hs, mem_range_indicator]
#align measure_theory.simple_func.mem_restrict_range MeasureTheory.SimpleFunc.mem_restrict_range
theorem mem_image_of_mem_range_restrict {r : β} {s : Set α} {f : α →ₛ β}
(hr : r ∈ (restrict f s).range) (h0 : r ≠ 0) : r ∈ f '' s :=
if hs : MeasurableSet s then by simpa [mem_restrict_range hs, h0, -mem_range] using hr
else by
rw [restrict_of_not_measurable hs] at hr
exact (h0 <| eq_zero_of_mem_range_zero hr).elim
#align measure_theory.simple_func.mem_image_of_mem_range_restrict MeasureTheory.SimpleFunc.mem_image_of_mem_range_restrict
@[mono]
theorem restrict_mono [Preorder β] (s : Set α) {f g : α →ₛ β} (H : f ≤ g) :
f.restrict s ≤ g.restrict s :=
if hs : MeasurableSet s then fun x => by
simp only [coe_restrict _ hs, indicator_le_indicator (H x)]
else by simp only [restrict_of_not_measurable hs, le_refl]
#align measure_theory.simple_func.restrict_mono MeasureTheory.SimpleFunc.restrict_mono
end Restrict
section Approx
section
variable [SemilatticeSup β] [OrderBot β] [Zero β]
/-- Fix a sequence `i : ℕ → β`. Given a function `α → β`, its `n`-th approximation
by simple functions is defined so that in case `β = ℝ≥0∞` it sends each `a` to the supremum
of the set `{i k | k ≤ n ∧ i k ≤ f a}`, see `approx_apply` and `iSup_approx_apply` for details. -/
def approx (i : ℕ → β) (f : α → β) (n : ℕ) : α →ₛ β :=
(Finset.range n).sup fun k => restrict (const α (i k)) { a : α | i k ≤ f a }
#align measure_theory.simple_func.approx MeasureTheory.SimpleFunc.approx
theorem approx_apply [TopologicalSpace β] [OrderClosedTopology β] [MeasurableSpace β]
[OpensMeasurableSpace β] {i : ℕ → β} {f : α → β} {n : ℕ} (a : α) (hf : Measurable f) :
(approx i f n : α →ₛ β) a = (Finset.range n).sup fun k => if i k ≤ f a then i k else 0 := by
dsimp only [approx]
rw [finset_sup_apply]
congr
funext k
rw [restrict_apply]
· simp only [coe_const, mem_setOf_eq, indicator_apply, Function.const_apply]
· exact hf measurableSet_Ici
#align measure_theory.simple_func.approx_apply MeasureTheory.SimpleFunc.approx_apply
theorem monotone_approx (i : ℕ → β) (f : α → β) : Monotone (approx i f) := fun _ _ h =>
Finset.sup_mono <| Finset.range_subset.2 h
#align measure_theory.simple_func.monotone_approx MeasureTheory.SimpleFunc.monotone_approx
theorem approx_comp [TopologicalSpace β] [OrderClosedTopology β] [MeasurableSpace β]
[OpensMeasurableSpace β] [MeasurableSpace γ] {i : ℕ → β} {f : γ → β} {g : α → γ} {n : ℕ} (a : α)
(hf : Measurable f) (hg : Measurable g) :
(approx i (f ∘ g) n : α →ₛ β) a = (approx i f n : γ →ₛ β) (g a) := by
rw [approx_apply _ hf, approx_apply _ (hf.comp hg), Function.comp_apply]
#align measure_theory.simple_func.approx_comp MeasureTheory.SimpleFunc.approx_comp
end
theorem iSup_approx_apply [TopologicalSpace β] [CompleteLattice β] [OrderClosedTopology β] [Zero β]
[MeasurableSpace β] [OpensMeasurableSpace β] (i : ℕ → β) (f : α → β) (a : α) (hf : Measurable f)
(h_zero : (0 : β) = ⊥) : ⨆ n, (approx i f n : α →ₛ β) a = ⨆ (k) (_ : i k ≤ f a), i k := by
refine le_antisymm (iSup_le fun n => ?_) (iSup_le fun k => iSup_le fun hk => ?_)
· rw [approx_apply a hf, h_zero]
refine Finset.sup_le fun k _ => ?_
split_ifs with h
· exact le_iSup_of_le k (le_iSup (fun _ : i k ≤ f a => i k) h)
· exact bot_le
· refine le_iSup_of_le (k + 1) ?_
rw [approx_apply a hf]
have : k ∈ Finset.range (k + 1) := Finset.mem_range.2 (Nat.lt_succ_self _)
refine le_trans (le_of_eq ?_) (Finset.le_sup this)
rw [if_pos hk]
#align measure_theory.simple_func.supr_approx_apply MeasureTheory.SimpleFunc.iSup_approx_apply
end Approx
section EApprox
/-- A sequence of `ℝ≥0∞`s such that its range is the set of non-negative rational numbers. -/
def ennrealRatEmbed (n : ℕ) : ℝ≥0∞ :=
ENNReal.ofReal ((Encodable.decode (α := ℚ) n).getD (0 : ℚ))
#align measure_theory.simple_func.ennreal_rat_embed MeasureTheory.SimpleFunc.ennrealRatEmbed
theorem ennrealRatEmbed_encode (q : ℚ) :
ennrealRatEmbed (Encodable.encode q) = Real.toNNReal q := by
rw [ennrealRatEmbed, Encodable.encodek]; rfl
#align measure_theory.simple_func.ennreal_rat_embed_encode MeasureTheory.SimpleFunc.ennrealRatEmbed_encode
/-- Approximate a function `α → ℝ≥0∞` by a sequence of simple functions. -/
def eapprox : (α → ℝ≥0∞) → ℕ → α →ₛ ℝ≥0∞ :=
approx ennrealRatEmbed
#align measure_theory.simple_func.eapprox MeasureTheory.SimpleFunc.eapprox
| Mathlib/MeasureTheory/Function/SimpleFunc.lean | 892 | 903 | theorem eapprox_lt_top (f : α → ℝ≥0∞) (n : ℕ) (a : α) : eapprox f n a < ∞ := by |
simp only [eapprox, approx, finset_sup_apply, Finset.mem_range, ENNReal.bot_eq_zero, restrict]
rw [Finset.sup_lt_iff (α := ℝ≥0∞) WithTop.zero_lt_top]
intro b _
split_ifs
· simp only [coe_zero, coe_piecewise, piecewise_eq_indicator, coe_const]
calc
{ a : α | ennrealRatEmbed b ≤ f a }.indicator (fun _ => ennrealRatEmbed b) a ≤
ennrealRatEmbed b :=
indicator_le_self _ _ a
_ < ⊤ := ENNReal.coe_lt_top
· exact WithTop.zero_lt_top
|
/-
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, Yury Kudryashov, Patrick Massot
-/
import Mathlib.Algebra.BigOperators.Group.Finset
import Mathlib.Algebra.Order.Field.Defs
import Mathlib.Algebra.Order.Group.Instances
import Mathlib.Algebra.Order.Group.MinMax
import Mathlib.Algebra.Order.Ring.Basic
import Mathlib.Data.Finset.Preimage
import Mathlib.Order.Interval.Set.Disjoint
import Mathlib.Order.Interval.Set.OrderIso
import Mathlib.Order.ConditionallyCompleteLattice.Basic
import Mathlib.Order.Filter.Bases
#align_import order.filter.at_top_bot from "leanprover-community/mathlib"@"1f0096e6caa61e9c849ec2adbd227e960e9dff58"
/-!
# `Filter.atTop` and `Filter.atBot` filters on preorders, monoids and groups.
In this file we define the filters
* `Filter.atTop`: corresponds to `n → +∞`;
* `Filter.atBot`: corresponds to `n → -∞`.
Then we prove many lemmas like “if `f → +∞`, then `f ± c → +∞`”.
-/
set_option autoImplicit true
variable {ι ι' α β γ : Type*}
open Set
namespace Filter
/-- `atTop` is the filter representing the limit `→ ∞` on an ordered set.
It is generated by the collection of up-sets `{b | a ≤ b}`.
(The preorder need not have a top element for this to be well defined,
and indeed is trivial when a top element exists.) -/
def atTop [Preorder α] : Filter α :=
⨅ a, 𝓟 (Ici a)
#align filter.at_top Filter.atTop
/-- `atBot` is the filter representing the limit `→ -∞` on an ordered set.
It is generated by the collection of down-sets `{b | b ≤ a}`.
(The preorder need not have a bottom element for this to be well defined,
and indeed is trivial when a bottom element exists.) -/
def atBot [Preorder α] : Filter α :=
⨅ a, 𝓟 (Iic a)
#align filter.at_bot Filter.atBot
theorem mem_atTop [Preorder α] (a : α) : { b : α | a ≤ b } ∈ @atTop α _ :=
mem_iInf_of_mem a <| Subset.refl _
#align filter.mem_at_top Filter.mem_atTop
theorem Ici_mem_atTop [Preorder α] (a : α) : Ici a ∈ (atTop : Filter α) :=
mem_atTop a
#align filter.Ici_mem_at_top Filter.Ici_mem_atTop
theorem Ioi_mem_atTop [Preorder α] [NoMaxOrder α] (x : α) : Ioi x ∈ (atTop : Filter α) :=
let ⟨z, hz⟩ := exists_gt x
mem_of_superset (mem_atTop z) fun _ h => lt_of_lt_of_le hz h
#align filter.Ioi_mem_at_top Filter.Ioi_mem_atTop
theorem mem_atBot [Preorder α] (a : α) : { b : α | b ≤ a } ∈ @atBot α _ :=
mem_iInf_of_mem a <| Subset.refl _
#align filter.mem_at_bot Filter.mem_atBot
theorem Iic_mem_atBot [Preorder α] (a : α) : Iic a ∈ (atBot : Filter α) :=
mem_atBot a
#align filter.Iic_mem_at_bot Filter.Iic_mem_atBot
theorem Iio_mem_atBot [Preorder α] [NoMinOrder α] (x : α) : Iio x ∈ (atBot : Filter α) :=
let ⟨z, hz⟩ := exists_lt x
mem_of_superset (mem_atBot z) fun _ h => lt_of_le_of_lt h hz
#align filter.Iio_mem_at_bot Filter.Iio_mem_atBot
theorem disjoint_atBot_principal_Ioi [Preorder α] (x : α) : Disjoint atBot (𝓟 (Ioi x)) :=
disjoint_of_disjoint_of_mem (Iic_disjoint_Ioi le_rfl) (Iic_mem_atBot x) (mem_principal_self _)
#align filter.disjoint_at_bot_principal_Ioi Filter.disjoint_atBot_principal_Ioi
theorem disjoint_atTop_principal_Iio [Preorder α] (x : α) : Disjoint atTop (𝓟 (Iio x)) :=
@disjoint_atBot_principal_Ioi αᵒᵈ _ _
#align filter.disjoint_at_top_principal_Iio Filter.disjoint_atTop_principal_Iio
theorem disjoint_atTop_principal_Iic [Preorder α] [NoMaxOrder α] (x : α) :
Disjoint atTop (𝓟 (Iic x)) :=
disjoint_of_disjoint_of_mem (Iic_disjoint_Ioi le_rfl).symm (Ioi_mem_atTop x)
(mem_principal_self _)
#align filter.disjoint_at_top_principal_Iic Filter.disjoint_atTop_principal_Iic
theorem disjoint_atBot_principal_Ici [Preorder α] [NoMinOrder α] (x : α) :
Disjoint atBot (𝓟 (Ici x)) :=
@disjoint_atTop_principal_Iic αᵒᵈ _ _ _
#align filter.disjoint_at_bot_principal_Ici Filter.disjoint_atBot_principal_Ici
theorem disjoint_pure_atTop [Preorder α] [NoMaxOrder α] (x : α) : Disjoint (pure x) atTop :=
Disjoint.symm <| (disjoint_atTop_principal_Iic x).mono_right <| le_principal_iff.2 <|
mem_pure.2 right_mem_Iic
#align filter.disjoint_pure_at_top Filter.disjoint_pure_atTop
theorem disjoint_pure_atBot [Preorder α] [NoMinOrder α] (x : α) : Disjoint (pure x) atBot :=
@disjoint_pure_atTop αᵒᵈ _ _ _
#align filter.disjoint_pure_at_bot Filter.disjoint_pure_atBot
theorem not_tendsto_const_atTop [Preorder α] [NoMaxOrder α] (x : α) (l : Filter β) [l.NeBot] :
¬Tendsto (fun _ => x) l atTop :=
tendsto_const_pure.not_tendsto (disjoint_pure_atTop x)
#align filter.not_tendsto_const_at_top Filter.not_tendsto_const_atTop
theorem not_tendsto_const_atBot [Preorder α] [NoMinOrder α] (x : α) (l : Filter β) [l.NeBot] :
¬Tendsto (fun _ => x) l atBot :=
tendsto_const_pure.not_tendsto (disjoint_pure_atBot x)
#align filter.not_tendsto_const_at_bot Filter.not_tendsto_const_atBot
theorem disjoint_atBot_atTop [PartialOrder α] [Nontrivial α] :
Disjoint (atBot : Filter α) atTop := by
rcases exists_pair_ne α with ⟨x, y, hne⟩
by_cases hle : x ≤ y
· refine disjoint_of_disjoint_of_mem ?_ (Iic_mem_atBot x) (Ici_mem_atTop y)
exact Iic_disjoint_Ici.2 (hle.lt_of_ne hne).not_le
· refine disjoint_of_disjoint_of_mem ?_ (Iic_mem_atBot y) (Ici_mem_atTop x)
exact Iic_disjoint_Ici.2 hle
#align filter.disjoint_at_bot_at_top Filter.disjoint_atBot_atTop
theorem disjoint_atTop_atBot [PartialOrder α] [Nontrivial α] : Disjoint (atTop : Filter α) atBot :=
disjoint_atBot_atTop.symm
#align filter.disjoint_at_top_at_bot Filter.disjoint_atTop_atBot
theorem hasAntitoneBasis_atTop [Nonempty α] [Preorder α] [IsDirected α (· ≤ ·)] :
(@atTop α _).HasAntitoneBasis Ici :=
.iInf_principal fun _ _ ↦ Ici_subset_Ici.2
theorem atTop_basis [Nonempty α] [SemilatticeSup α] : (@atTop α _).HasBasis (fun _ => True) Ici :=
hasAntitoneBasis_atTop.1
#align filter.at_top_basis Filter.atTop_basis
theorem atTop_eq_generate_Ici [SemilatticeSup α] : atTop = generate (range (Ici (α := α))) := by
rcases isEmpty_or_nonempty α with hα|hα
· simp only [eq_iff_true_of_subsingleton]
· simp [(atTop_basis (α := α)).eq_generate, range]
theorem atTop_basis' [SemilatticeSup α] (a : α) : (@atTop α _).HasBasis (fun x => a ≤ x) Ici :=
⟨fun _ =>
(@atTop_basis α ⟨a⟩ _).mem_iff.trans
⟨fun ⟨x, _, hx⟩ => ⟨x ⊔ a, le_sup_right, fun _y hy => hx (le_trans le_sup_left hy)⟩,
fun ⟨x, _, hx⟩ => ⟨x, trivial, hx⟩⟩⟩
#align filter.at_top_basis' Filter.atTop_basis'
theorem atBot_basis [Nonempty α] [SemilatticeInf α] : (@atBot α _).HasBasis (fun _ => True) Iic :=
@atTop_basis αᵒᵈ _ _
#align filter.at_bot_basis Filter.atBot_basis
theorem atBot_basis' [SemilatticeInf α] (a : α) : (@atBot α _).HasBasis (fun x => x ≤ a) Iic :=
@atTop_basis' αᵒᵈ _ _
#align filter.at_bot_basis' Filter.atBot_basis'
@[instance]
theorem atTop_neBot [Nonempty α] [SemilatticeSup α] : NeBot (atTop : Filter α) :=
atTop_basis.neBot_iff.2 fun _ => nonempty_Ici
#align filter.at_top_ne_bot Filter.atTop_neBot
@[instance]
theorem atBot_neBot [Nonempty α] [SemilatticeInf α] : NeBot (atBot : Filter α) :=
@atTop_neBot αᵒᵈ _ _
#align filter.at_bot_ne_bot Filter.atBot_neBot
@[simp]
theorem mem_atTop_sets [Nonempty α] [SemilatticeSup α] {s : Set α} :
s ∈ (atTop : Filter α) ↔ ∃ a : α, ∀ b ≥ a, b ∈ s :=
atTop_basis.mem_iff.trans <| exists_congr fun _ => true_and_iff _
#align filter.mem_at_top_sets Filter.mem_atTop_sets
@[simp]
theorem mem_atBot_sets [Nonempty α] [SemilatticeInf α] {s : Set α} :
s ∈ (atBot : Filter α) ↔ ∃ a : α, ∀ b ≤ a, b ∈ s :=
@mem_atTop_sets αᵒᵈ _ _ _
#align filter.mem_at_bot_sets Filter.mem_atBot_sets
@[simp]
theorem eventually_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop} :
(∀ᶠ x in atTop, p x) ↔ ∃ a, ∀ b ≥ a, p b :=
mem_atTop_sets
#align filter.eventually_at_top Filter.eventually_atTop
@[simp]
theorem eventually_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop} :
(∀ᶠ x in atBot, p x) ↔ ∃ a, ∀ b ≤ a, p b :=
mem_atBot_sets
#align filter.eventually_at_bot Filter.eventually_atBot
theorem eventually_ge_atTop [Preorder α] (a : α) : ∀ᶠ x in atTop, a ≤ x :=
mem_atTop a
#align filter.eventually_ge_at_top Filter.eventually_ge_atTop
theorem eventually_le_atBot [Preorder α] (a : α) : ∀ᶠ x in atBot, x ≤ a :=
mem_atBot a
#align filter.eventually_le_at_bot Filter.eventually_le_atBot
theorem eventually_gt_atTop [Preorder α] [NoMaxOrder α] (a : α) : ∀ᶠ x in atTop, a < x :=
Ioi_mem_atTop a
#align filter.eventually_gt_at_top Filter.eventually_gt_atTop
theorem eventually_ne_atTop [Preorder α] [NoMaxOrder α] (a : α) : ∀ᶠ x in atTop, x ≠ a :=
(eventually_gt_atTop a).mono fun _ => ne_of_gt
#align filter.eventually_ne_at_top Filter.eventually_ne_atTop
protected theorem Tendsto.eventually_gt_atTop [Preorder β] [NoMaxOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, c < f x :=
hf.eventually (eventually_gt_atTop c)
#align filter.tendsto.eventually_gt_at_top Filter.Tendsto.eventually_gt_atTop
protected theorem Tendsto.eventually_ge_atTop [Preorder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, c ≤ f x :=
hf.eventually (eventually_ge_atTop c)
#align filter.tendsto.eventually_ge_at_top Filter.Tendsto.eventually_ge_atTop
protected theorem Tendsto.eventually_ne_atTop [Preorder β] [NoMaxOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atTop) (c : β) : ∀ᶠ x in l, f x ≠ c :=
hf.eventually (eventually_ne_atTop c)
#align filter.tendsto.eventually_ne_at_top Filter.Tendsto.eventually_ne_atTop
protected theorem Tendsto.eventually_ne_atTop' [Preorder β] [NoMaxOrder β] {f : α → β}
{l : Filter α} (hf : Tendsto f l atTop) (c : α) : ∀ᶠ x in l, x ≠ c :=
(hf.eventually_ne_atTop (f c)).mono fun _ => ne_of_apply_ne f
#align filter.tendsto.eventually_ne_at_top' Filter.Tendsto.eventually_ne_atTop'
theorem eventually_lt_atBot [Preorder α] [NoMinOrder α] (a : α) : ∀ᶠ x in atBot, x < a :=
Iio_mem_atBot a
#align filter.eventually_lt_at_bot Filter.eventually_lt_atBot
theorem eventually_ne_atBot [Preorder α] [NoMinOrder α] (a : α) : ∀ᶠ x in atBot, x ≠ a :=
(eventually_lt_atBot a).mono fun _ => ne_of_lt
#align filter.eventually_ne_at_bot Filter.eventually_ne_atBot
protected theorem Tendsto.eventually_lt_atBot [Preorder β] [NoMinOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x < c :=
hf.eventually (eventually_lt_atBot c)
#align filter.tendsto.eventually_lt_at_bot Filter.Tendsto.eventually_lt_atBot
protected theorem Tendsto.eventually_le_atBot [Preorder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x ≤ c :=
hf.eventually (eventually_le_atBot c)
#align filter.tendsto.eventually_le_at_bot Filter.Tendsto.eventually_le_atBot
protected theorem Tendsto.eventually_ne_atBot [Preorder β] [NoMinOrder β] {f : α → β} {l : Filter α}
(hf : Tendsto f l atBot) (c : β) : ∀ᶠ x in l, f x ≠ c :=
hf.eventually (eventually_ne_atBot c)
#align filter.tendsto.eventually_ne_at_bot Filter.Tendsto.eventually_ne_atBot
theorem eventually_forall_ge_atTop [Preorder α] {p : α → Prop} :
(∀ᶠ x in atTop, ∀ y, x ≤ y → p y) ↔ ∀ᶠ x in atTop, p x := by
refine ⟨fun h ↦ h.mono fun x hx ↦ hx x le_rfl, fun h ↦ ?_⟩
rcases (hasBasis_iInf_principal_finite _).eventually_iff.1 h with ⟨S, hSf, hS⟩
refine mem_iInf_of_iInter hSf (V := fun x ↦ Ici x.1) (fun _ ↦ Subset.rfl) fun x hx y hy ↦ ?_
simp only [mem_iInter] at hS hx
exact hS fun z hz ↦ le_trans (hx ⟨z, hz⟩) hy
theorem eventually_forall_le_atBot [Preorder α] {p : α → Prop} :
(∀ᶠ x in atBot, ∀ y, y ≤ x → p y) ↔ ∀ᶠ x in atBot, p x :=
eventually_forall_ge_atTop (α := αᵒᵈ)
theorem Tendsto.eventually_forall_ge_atTop {α β : Type*} [Preorder β] {l : Filter α}
{p : β → Prop} {f : α → β} (hf : Tendsto f l atTop) (h_evtl : ∀ᶠ x in atTop, p x) :
∀ᶠ x in l, ∀ y, f x ≤ y → p y := by
rw [← Filter.eventually_forall_ge_atTop] at h_evtl; exact (h_evtl.comap f).filter_mono hf.le_comap
theorem Tendsto.eventually_forall_le_atBot {α β : Type*} [Preorder β] {l : Filter α}
{p : β → Prop} {f : α → β} (hf : Tendsto f l atBot) (h_evtl : ∀ᶠ x in atBot, p x) :
∀ᶠ x in l, ∀ y, y ≤ f x → p y := by
rw [← Filter.eventually_forall_le_atBot] at h_evtl; exact (h_evtl.comap f).filter_mono hf.le_comap
theorem atTop_basis_Ioi [Nonempty α] [SemilatticeSup α] [NoMaxOrder α] :
(@atTop α _).HasBasis (fun _ => True) Ioi :=
atTop_basis.to_hasBasis (fun a ha => ⟨a, ha, Ioi_subset_Ici_self⟩) fun a ha =>
(exists_gt a).imp fun _b hb => ⟨ha, Ici_subset_Ioi.2 hb⟩
#align filter.at_top_basis_Ioi Filter.atTop_basis_Ioi
lemma atTop_basis_Ioi' [SemilatticeSup α] [NoMaxOrder α] (a : α) : atTop.HasBasis (a < ·) Ioi :=
have : Nonempty α := ⟨a⟩
atTop_basis_Ioi.to_hasBasis (fun b _ ↦
let ⟨c, hc⟩ := exists_gt (a ⊔ b)
⟨c, le_sup_left.trans_lt hc, Ioi_subset_Ioi <| le_sup_right.trans hc.le⟩) fun b _ ↦
⟨b, trivial, Subset.rfl⟩
theorem atTop_countable_basis [Nonempty α] [SemilatticeSup α] [Countable α] :
HasCountableBasis (atTop : Filter α) (fun _ => True) Ici :=
{ atTop_basis with countable := to_countable _ }
#align filter.at_top_countable_basis Filter.atTop_countable_basis
theorem atBot_countable_basis [Nonempty α] [SemilatticeInf α] [Countable α] :
HasCountableBasis (atBot : Filter α) (fun _ => True) Iic :=
{ atBot_basis with countable := to_countable _ }
#align filter.at_bot_countable_basis Filter.atBot_countable_basis
instance (priority := 200) atTop.isCountablyGenerated [Preorder α] [Countable α] :
(atTop : Filter <| α).IsCountablyGenerated :=
isCountablyGenerated_seq _
#align filter.at_top.is_countably_generated Filter.atTop.isCountablyGenerated
instance (priority := 200) atBot.isCountablyGenerated [Preorder α] [Countable α] :
(atBot : Filter <| α).IsCountablyGenerated :=
isCountablyGenerated_seq _
#align filter.at_bot.is_countably_generated Filter.atBot.isCountablyGenerated
theorem _root_.IsTop.atTop_eq [Preorder α] {a : α} (ha : IsTop a) : atTop = 𝓟 (Ici a) :=
(iInf_le _ _).antisymm <| le_iInf fun b ↦ principal_mono.2 <| Ici_subset_Ici.2 <| ha b
theorem _root_.IsBot.atBot_eq [Preorder α] {a : α} (ha : IsBot a) : atBot = 𝓟 (Iic a) :=
ha.toDual.atTop_eq
theorem OrderTop.atTop_eq (α) [PartialOrder α] [OrderTop α] : (atTop : Filter α) = pure ⊤ := by
rw [isTop_top.atTop_eq, Ici_top, principal_singleton]
#align filter.order_top.at_top_eq Filter.OrderTop.atTop_eq
theorem OrderBot.atBot_eq (α) [PartialOrder α] [OrderBot α] : (atBot : Filter α) = pure ⊥ :=
@OrderTop.atTop_eq αᵒᵈ _ _
#align filter.order_bot.at_bot_eq Filter.OrderBot.atBot_eq
@[nontriviality]
theorem Subsingleton.atTop_eq (α) [Subsingleton α] [Preorder α] : (atTop : Filter α) = ⊤ := by
refine top_unique fun s hs x => ?_
rw [atTop, ciInf_subsingleton x, mem_principal] at hs
exact hs left_mem_Ici
#align filter.subsingleton.at_top_eq Filter.Subsingleton.atTop_eq
@[nontriviality]
theorem Subsingleton.atBot_eq (α) [Subsingleton α] [Preorder α] : (atBot : Filter α) = ⊤ :=
@Subsingleton.atTop_eq αᵒᵈ _ _
#align filter.subsingleton.at_bot_eq Filter.Subsingleton.atBot_eq
theorem tendsto_atTop_pure [PartialOrder α] [OrderTop α] (f : α → β) :
Tendsto f atTop (pure <| f ⊤) :=
(OrderTop.atTop_eq α).symm ▸ tendsto_pure_pure _ _
#align filter.tendsto_at_top_pure Filter.tendsto_atTop_pure
theorem tendsto_atBot_pure [PartialOrder α] [OrderBot α] (f : α → β) :
Tendsto f atBot (pure <| f ⊥) :=
@tendsto_atTop_pure αᵒᵈ _ _ _ _
#align filter.tendsto_at_bot_pure Filter.tendsto_atBot_pure
theorem Eventually.exists_forall_of_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop}
(h : ∀ᶠ x in atTop, p x) : ∃ a, ∀ b ≥ a, p b :=
eventually_atTop.mp h
#align filter.eventually.exists_forall_of_at_top Filter.Eventually.exists_forall_of_atTop
theorem Eventually.exists_forall_of_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop}
(h : ∀ᶠ x in atBot, p x) : ∃ a, ∀ b ≤ a, p b :=
eventually_atBot.mp h
#align filter.eventually.exists_forall_of_at_bot Filter.Eventually.exists_forall_of_atBot
lemma exists_eventually_atTop [SemilatticeSup α] [Nonempty α] {r : α → β → Prop} :
(∃ b, ∀ᶠ a in atTop, r a b) ↔ ∀ᶠ a₀ in atTop, ∃ b, ∀ a ≥ a₀, r a b := by
simp_rw [eventually_atTop, ← exists_swap (α := α)]
exact exists_congr fun a ↦ .symm <| forall_ge_iff <| Monotone.exists fun _ _ _ hb H n hn ↦
H n (hb.trans hn)
lemma exists_eventually_atBot [SemilatticeInf α] [Nonempty α] {r : α → β → Prop} :
(∃ b, ∀ᶠ a in atBot, r a b) ↔ ∀ᶠ a₀ in atBot, ∃ b, ∀ a ≤ a₀, r a b := by
simp_rw [eventually_atBot, ← exists_swap (α := α)]
exact exists_congr fun a ↦ .symm <| forall_le_iff <| Antitone.exists fun _ _ _ hb H n hn ↦
H n (hn.trans hb)
theorem frequently_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop} :
(∃ᶠ x in atTop, p x) ↔ ∀ a, ∃ b ≥ a, p b :=
atTop_basis.frequently_iff.trans <| by simp
#align filter.frequently_at_top Filter.frequently_atTop
theorem frequently_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop} :
(∃ᶠ x in atBot, p x) ↔ ∀ a, ∃ b ≤ a, p b :=
@frequently_atTop αᵒᵈ _ _ _
#align filter.frequently_at_bot Filter.frequently_atBot
theorem frequently_atTop' [SemilatticeSup α] [Nonempty α] [NoMaxOrder α] {p : α → Prop} :
(∃ᶠ x in atTop, p x) ↔ ∀ a, ∃ b > a, p b :=
atTop_basis_Ioi.frequently_iff.trans <| by simp
#align filter.frequently_at_top' Filter.frequently_atTop'
theorem frequently_atBot' [SemilatticeInf α] [Nonempty α] [NoMinOrder α] {p : α → Prop} :
(∃ᶠ x in atBot, p x) ↔ ∀ a, ∃ b < a, p b :=
@frequently_atTop' αᵒᵈ _ _ _ _
#align filter.frequently_at_bot' Filter.frequently_atBot'
theorem Frequently.forall_exists_of_atTop [SemilatticeSup α] [Nonempty α] {p : α → Prop}
(h : ∃ᶠ x in atTop, p x) : ∀ a, ∃ b ≥ a, p b :=
frequently_atTop.mp h
#align filter.frequently.forall_exists_of_at_top Filter.Frequently.forall_exists_of_atTop
theorem Frequently.forall_exists_of_atBot [SemilatticeInf α] [Nonempty α] {p : α → Prop}
(h : ∃ᶠ x in atBot, p x) : ∀ a, ∃ b ≤ a, p b :=
frequently_atBot.mp h
#align filter.frequently.forall_exists_of_at_bot Filter.Frequently.forall_exists_of_atBot
theorem map_atTop_eq [Nonempty α] [SemilatticeSup α] {f : α → β} :
atTop.map f = ⨅ a, 𝓟 (f '' { a' | a ≤ a' }) :=
(atTop_basis.map f).eq_iInf
#align filter.map_at_top_eq Filter.map_atTop_eq
theorem map_atBot_eq [Nonempty α] [SemilatticeInf α] {f : α → β} :
atBot.map f = ⨅ a, 𝓟 (f '' { a' | a' ≤ a }) :=
@map_atTop_eq αᵒᵈ _ _ _ _
#align filter.map_at_bot_eq Filter.map_atBot_eq
theorem tendsto_atTop [Preorder β] {m : α → β} {f : Filter α} :
Tendsto m f atTop ↔ ∀ b, ∀ᶠ a in f, b ≤ m a := by
simp only [atTop, tendsto_iInf, tendsto_principal, mem_Ici]
#align filter.tendsto_at_top Filter.tendsto_atTop
theorem tendsto_atBot [Preorder β] {m : α → β} {f : Filter α} :
Tendsto m f atBot ↔ ∀ b, ∀ᶠ a in f, m a ≤ b :=
@tendsto_atTop α βᵒᵈ _ m f
#align filter.tendsto_at_bot Filter.tendsto_atBot
theorem tendsto_atTop_mono' [Preorder β] (l : Filter α) ⦃f₁ f₂ : α → β⦄ (h : f₁ ≤ᶠ[l] f₂)
(h₁ : Tendsto f₁ l atTop) : Tendsto f₂ l atTop :=
tendsto_atTop.2 fun b => by filter_upwards [tendsto_atTop.1 h₁ b, h] with x using le_trans
#align filter.tendsto_at_top_mono' Filter.tendsto_atTop_mono'
theorem tendsto_atBot_mono' [Preorder β] (l : Filter α) ⦃f₁ f₂ : α → β⦄ (h : f₁ ≤ᶠ[l] f₂) :
Tendsto f₂ l atBot → Tendsto f₁ l atBot :=
@tendsto_atTop_mono' _ βᵒᵈ _ _ _ _ h
#align filter.tendsto_at_bot_mono' Filter.tendsto_atBot_mono'
theorem tendsto_atTop_mono [Preorder β] {l : Filter α} {f g : α → β} (h : ∀ n, f n ≤ g n) :
Tendsto f l atTop → Tendsto g l atTop :=
tendsto_atTop_mono' l <| eventually_of_forall h
#align filter.tendsto_at_top_mono Filter.tendsto_atTop_mono
theorem tendsto_atBot_mono [Preorder β] {l : Filter α} {f g : α → β} (h : ∀ n, f n ≤ g n) :
Tendsto g l atBot → Tendsto f l atBot :=
@tendsto_atTop_mono _ βᵒᵈ _ _ _ _ h
#align filter.tendsto_at_bot_mono Filter.tendsto_atBot_mono
lemma atTop_eq_generate_of_forall_exists_le [LinearOrder α] {s : Set α} (hs : ∀ x, ∃ y ∈ s, x ≤ y) :
(atTop : Filter α) = generate (Ici '' s) := by
rw [atTop_eq_generate_Ici]
apply le_antisymm
· rw [le_generate_iff]
rintro - ⟨y, -, rfl⟩
exact mem_generate_of_mem ⟨y, rfl⟩
· rw [le_generate_iff]
rintro - ⟨x, -, -, rfl⟩
rcases hs x with ⟨y, ys, hy⟩
have A : Ici y ∈ generate (Ici '' s) := mem_generate_of_mem (mem_image_of_mem _ ys)
have B : Ici y ⊆ Ici x := Ici_subset_Ici.2 hy
exact sets_of_superset (generate (Ici '' s)) A B
lemma atTop_eq_generate_of_not_bddAbove [LinearOrder α] {s : Set α} (hs : ¬ BddAbove s) :
(atTop : Filter α) = generate (Ici '' s) := by
refine atTop_eq_generate_of_forall_exists_le fun x ↦ ?_
obtain ⟨y, hy, hy'⟩ := not_bddAbove_iff.mp hs x
exact ⟨y, hy, hy'.le⟩
end Filter
namespace OrderIso
open Filter
variable [Preorder α] [Preorder β]
@[simp]
theorem comap_atTop (e : α ≃o β) : comap e atTop = atTop := by
simp [atTop, ← e.surjective.iInf_comp]
#align order_iso.comap_at_top OrderIso.comap_atTop
@[simp]
theorem comap_atBot (e : α ≃o β) : comap e atBot = atBot :=
e.dual.comap_atTop
#align order_iso.comap_at_bot OrderIso.comap_atBot
@[simp]
theorem map_atTop (e : α ≃o β) : map (e : α → β) atTop = atTop := by
rw [← e.comap_atTop, map_comap_of_surjective e.surjective]
#align order_iso.map_at_top OrderIso.map_atTop
@[simp]
theorem map_atBot (e : α ≃o β) : map (e : α → β) atBot = atBot :=
e.dual.map_atTop
#align order_iso.map_at_bot OrderIso.map_atBot
theorem tendsto_atTop (e : α ≃o β) : Tendsto e atTop atTop :=
e.map_atTop.le
#align order_iso.tendsto_at_top OrderIso.tendsto_atTop
theorem tendsto_atBot (e : α ≃o β) : Tendsto e atBot atBot :=
e.map_atBot.le
#align order_iso.tendsto_at_bot OrderIso.tendsto_atBot
@[simp]
theorem tendsto_atTop_iff {l : Filter γ} {f : γ → α} (e : α ≃o β) :
Tendsto (fun x => e (f x)) l atTop ↔ Tendsto f l atTop := by
rw [← e.comap_atTop, tendsto_comap_iff, Function.comp_def]
#align order_iso.tendsto_at_top_iff OrderIso.tendsto_atTop_iff
@[simp]
theorem tendsto_atBot_iff {l : Filter γ} {f : γ → α} (e : α ≃o β) :
Tendsto (fun x => e (f x)) l atBot ↔ Tendsto f l atBot :=
e.dual.tendsto_atTop_iff
#align order_iso.tendsto_at_bot_iff OrderIso.tendsto_atBot_iff
end OrderIso
namespace Filter
/-!
### Sequences
-/
theorem inf_map_atTop_neBot_iff [SemilatticeSup α] [Nonempty α] {F : Filter β} {u : α → β} :
NeBot (F ⊓ map u atTop) ↔ ∀ U ∈ F, ∀ N, ∃ n ≥ N, u n ∈ U := by
simp_rw [inf_neBot_iff_frequently_left, frequently_map, frequently_atTop]; rfl
#align filter.inf_map_at_top_ne_bot_iff Filter.inf_map_atTop_neBot_iff
theorem inf_map_atBot_neBot_iff [SemilatticeInf α] [Nonempty α] {F : Filter β} {u : α → β} :
NeBot (F ⊓ map u atBot) ↔ ∀ U ∈ F, ∀ N, ∃ n ≤ N, u n ∈ U :=
@inf_map_atTop_neBot_iff αᵒᵈ _ _ _ _ _
#align filter.inf_map_at_bot_ne_bot_iff Filter.inf_map_atBot_neBot_iff
theorem extraction_of_frequently_atTop' {P : ℕ → Prop} (h : ∀ N, ∃ n > N, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) := by
choose u hu hu' using h
refine ⟨fun n => u^[n + 1] 0, strictMono_nat_of_lt_succ fun n => ?_, fun n => ?_⟩
· exact Trans.trans (hu _) (Function.iterate_succ_apply' _ _ _).symm
· simpa only [Function.iterate_succ_apply'] using hu' _
#align filter.extraction_of_frequently_at_top' Filter.extraction_of_frequently_atTop'
theorem extraction_of_frequently_atTop {P : ℕ → Prop} (h : ∃ᶠ n in atTop, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) := by
rw [frequently_atTop'] at h
exact extraction_of_frequently_atTop' h
#align filter.extraction_of_frequently_at_top Filter.extraction_of_frequently_atTop
theorem extraction_of_eventually_atTop {P : ℕ → Prop} (h : ∀ᶠ n in atTop, P n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P (φ n) :=
extraction_of_frequently_atTop h.frequently
#align filter.extraction_of_eventually_at_top Filter.extraction_of_eventually_atTop
theorem extraction_forall_of_frequently {P : ℕ → ℕ → Prop} (h : ∀ n, ∃ᶠ k in atTop, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) := by
simp only [frequently_atTop'] at h
choose u hu hu' using h
use (fun n => Nat.recOn n (u 0 0) fun n v => u (n + 1) v : ℕ → ℕ)
constructor
· apply strictMono_nat_of_lt_succ
intro n
apply hu
· intro n
cases n <;> simp [hu']
#align filter.extraction_forall_of_frequently Filter.extraction_forall_of_frequently
theorem extraction_forall_of_eventually {P : ℕ → ℕ → Prop} (h : ∀ n, ∀ᶠ k in atTop, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) :=
extraction_forall_of_frequently fun n => (h n).frequently
#align filter.extraction_forall_of_eventually Filter.extraction_forall_of_eventually
theorem extraction_forall_of_eventually' {P : ℕ → ℕ → Prop} (h : ∀ n, ∃ N, ∀ k ≥ N, P n k) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, P n (φ n) :=
extraction_forall_of_eventually (by simp [eventually_atTop, h])
#align filter.extraction_forall_of_eventually' Filter.extraction_forall_of_eventually'
theorem Eventually.atTop_of_arithmetic {p : ℕ → Prop} {n : ℕ} (hn : n ≠ 0)
(hp : ∀ k < n, ∀ᶠ a in atTop, p (n * a + k)) : ∀ᶠ a in atTop, p a := by
simp only [eventually_atTop] at hp ⊢
choose! N hN using hp
refine ⟨(Finset.range n).sup (n * N ·), fun b hb => ?_⟩
rw [← Nat.div_add_mod b n]
have hlt := Nat.mod_lt b hn.bot_lt
refine hN _ hlt _ ?_
rw [ge_iff_le, Nat.le_div_iff_mul_le hn.bot_lt, mul_comm]
exact (Finset.le_sup (f := (n * N ·)) (Finset.mem_range.2 hlt)).trans hb
theorem exists_le_of_tendsto_atTop [SemilatticeSup α] [Preorder β] {u : α → β}
(h : Tendsto u atTop atTop) (a : α) (b : β) : ∃ a' ≥ a, b ≤ u a' := by
have : Nonempty α := ⟨a⟩
have : ∀ᶠ x in atTop, a ≤ x ∧ b ≤ u x :=
(eventually_ge_atTop a).and (h.eventually <| eventually_ge_atTop b)
exact this.exists
#align filter.exists_le_of_tendsto_at_top Filter.exists_le_of_tendsto_atTop
-- @[nolint ge_or_gt] -- Porting note: restore attribute
theorem exists_le_of_tendsto_atBot [SemilatticeSup α] [Preorder β] {u : α → β}
(h : Tendsto u atTop atBot) : ∀ a b, ∃ a' ≥ a, u a' ≤ b :=
@exists_le_of_tendsto_atTop _ βᵒᵈ _ _ _ h
#align filter.exists_le_of_tendsto_at_bot Filter.exists_le_of_tendsto_atBot
theorem exists_lt_of_tendsto_atTop [SemilatticeSup α] [Preorder β] [NoMaxOrder β] {u : α → β}
(h : Tendsto u atTop atTop) (a : α) (b : β) : ∃ a' ≥ a, b < u a' := by
cases' exists_gt b with b' hb'
rcases exists_le_of_tendsto_atTop h a b' with ⟨a', ha', ha''⟩
exact ⟨a', ha', lt_of_lt_of_le hb' ha''⟩
#align filter.exists_lt_of_tendsto_at_top Filter.exists_lt_of_tendsto_atTop
-- @[nolint ge_or_gt] -- Porting note: restore attribute
theorem exists_lt_of_tendsto_atBot [SemilatticeSup α] [Preorder β] [NoMinOrder β] {u : α → β}
(h : Tendsto u atTop atBot) : ∀ a b, ∃ a' ≥ a, u a' < b :=
@exists_lt_of_tendsto_atTop _ βᵒᵈ _ _ _ _ h
#align filter.exists_lt_of_tendsto_at_bot Filter.exists_lt_of_tendsto_atBot
/-- If `u` is a sequence which is unbounded above,
then after any point, it reaches a value strictly greater than all previous values.
-/
theorem high_scores [LinearOrder β] [NoMaxOrder β] {u : ℕ → β} (hu : Tendsto u atTop atTop) :
∀ N, ∃ n ≥ N, ∀ k < n, u k < u n := by
intro N
obtain ⟨k : ℕ, - : k ≤ N, hku : ∀ l ≤ N, u l ≤ u k⟩ : ∃ k ≤ N, ∀ l ≤ N, u l ≤ u k :=
exists_max_image _ u (finite_le_nat N) ⟨N, le_refl N⟩
have ex : ∃ n ≥ N, u k < u n := exists_lt_of_tendsto_atTop hu _ _
obtain ⟨n : ℕ, hnN : n ≥ N, hnk : u k < u n, hn_min : ∀ m, m < n → N ≤ m → u m ≤ u k⟩ :
∃ n ≥ N, u k < u n ∧ ∀ m, m < n → N ≤ m → u m ≤ u k := by
rcases Nat.findX ex with ⟨n, ⟨hnN, hnk⟩, hn_min⟩
push_neg at hn_min
exact ⟨n, hnN, hnk, hn_min⟩
use n, hnN
rintro (l : ℕ) (hl : l < n)
have hlk : u l ≤ u k := by
cases' (le_total l N : l ≤ N ∨ N ≤ l) with H H
· exact hku l H
· exact hn_min l hl H
calc
u l ≤ u k := hlk
_ < u n := hnk
#align filter.high_scores Filter.high_scores
-- see Note [nolint_ge]
/-- If `u` is a sequence which is unbounded below,
then after any point, it reaches a value strictly smaller than all previous values.
-/
-- @[nolint ge_or_gt] Porting note: restore attribute
theorem low_scores [LinearOrder β] [NoMinOrder β] {u : ℕ → β} (hu : Tendsto u atTop atBot) :
∀ N, ∃ n ≥ N, ∀ k < n, u n < u k :=
@high_scores βᵒᵈ _ _ _ hu
#align filter.low_scores Filter.low_scores
/-- If `u` is a sequence which is unbounded above,
then it `Frequently` reaches a value strictly greater than all previous values.
-/
theorem frequently_high_scores [LinearOrder β] [NoMaxOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atTop) : ∃ᶠ n in atTop, ∀ k < n, u k < u n := by
simpa [frequently_atTop] using high_scores hu
#align filter.frequently_high_scores Filter.frequently_high_scores
/-- If `u` is a sequence which is unbounded below,
then it `Frequently` reaches a value strictly smaller than all previous values.
-/
theorem frequently_low_scores [LinearOrder β] [NoMinOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atBot) : ∃ᶠ n in atTop, ∀ k < n, u n < u k :=
@frequently_high_scores βᵒᵈ _ _ _ hu
#align filter.frequently_low_scores Filter.frequently_low_scores
theorem strictMono_subseq_of_tendsto_atTop {β : Type*} [LinearOrder β] [NoMaxOrder β] {u : ℕ → β}
(hu : Tendsto u atTop atTop) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ StrictMono (u ∘ φ) :=
let ⟨φ, h, h'⟩ := extraction_of_frequently_atTop (frequently_high_scores hu)
⟨φ, h, fun _ m hnm => h' m _ (h hnm)⟩
#align filter.strict_mono_subseq_of_tendsto_at_top Filter.strictMono_subseq_of_tendsto_atTop
theorem strictMono_subseq_of_id_le {u : ℕ → ℕ} (hu : ∀ n, n ≤ u n) :
∃ φ : ℕ → ℕ, StrictMono φ ∧ StrictMono (u ∘ φ) :=
strictMono_subseq_of_tendsto_atTop (tendsto_atTop_mono hu tendsto_id)
#align filter.strict_mono_subseq_of_id_le Filter.strictMono_subseq_of_id_le
theorem _root_.StrictMono.tendsto_atTop {φ : ℕ → ℕ} (h : StrictMono φ) : Tendsto φ atTop atTop :=
tendsto_atTop_mono h.id_le tendsto_id
#align strict_mono.tendsto_at_top StrictMono.tendsto_atTop
section OrderedAddCommMonoid
variable [OrderedAddCommMonoid β] {l : Filter α} {f g : α → β}
theorem tendsto_atTop_add_nonneg_left' (hf : ∀ᶠ x in l, 0 ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_mono' l (hf.mono fun _ => le_add_of_nonneg_left) hg
#align filter.tendsto_at_top_add_nonneg_left' Filter.tendsto_atTop_add_nonneg_left'
theorem tendsto_atBot_add_nonpos_left' (hf : ∀ᶠ x in l, f x ≤ 0) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_left' _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_left' Filter.tendsto_atBot_add_nonpos_left'
theorem tendsto_atTop_add_nonneg_left (hf : ∀ x, 0 ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_left' (eventually_of_forall hf) hg
#align filter.tendsto_at_top_add_nonneg_left Filter.tendsto_atTop_add_nonneg_left
theorem tendsto_atBot_add_nonpos_left (hf : ∀ x, f x ≤ 0) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_left _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_left Filter.tendsto_atBot_add_nonpos_left
theorem tendsto_atTop_add_nonneg_right' (hf : Tendsto f l atTop) (hg : ∀ᶠ x in l, 0 ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_mono' l (monotone_mem (fun _ => le_add_of_nonneg_right) hg) hf
#align filter.tendsto_at_top_add_nonneg_right' Filter.tendsto_atTop_add_nonneg_right'
theorem tendsto_atBot_add_nonpos_right' (hf : Tendsto f l atBot) (hg : ∀ᶠ x in l, g x ≤ 0) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_right' _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_right' Filter.tendsto_atBot_add_nonpos_right'
theorem tendsto_atTop_add_nonneg_right (hf : Tendsto f l atTop) (hg : ∀ x, 0 ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_right' hf (eventually_of_forall hg)
#align filter.tendsto_at_top_add_nonneg_right Filter.tendsto_atTop_add_nonneg_right
theorem tendsto_atBot_add_nonpos_right (hf : Tendsto f l atBot) (hg : ∀ x, g x ≤ 0) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_nonneg_right _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add_nonpos_right Filter.tendsto_atBot_add_nonpos_right
theorem tendsto_atTop_add (hf : Tendsto f l atTop) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_nonneg_left' (tendsto_atTop.mp hf 0) hg
#align filter.tendsto_at_top_add Filter.tendsto_atTop_add
theorem tendsto_atBot_add (hf : Tendsto f l atBot) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add _ βᵒᵈ _ _ _ _ hf hg
#align filter.tendsto_at_bot_add Filter.tendsto_atBot_add
theorem Tendsto.nsmul_atTop (hf : Tendsto f l atTop) {n : ℕ} (hn : 0 < n) :
Tendsto (fun x => n • f x) l atTop :=
tendsto_atTop.2 fun y =>
(tendsto_atTop.1 hf y).mp <|
(tendsto_atTop.1 hf 0).mono fun x h₀ hy =>
calc
y ≤ f x := hy
_ = 1 • f x := (one_nsmul _).symm
_ ≤ n • f x := nsmul_le_nsmul_left h₀ hn
#align filter.tendsto.nsmul_at_top Filter.Tendsto.nsmul_atTop
theorem Tendsto.nsmul_atBot (hf : Tendsto f l atBot) {n : ℕ} (hn : 0 < n) :
Tendsto (fun x => n • f x) l atBot :=
@Tendsto.nsmul_atTop α βᵒᵈ _ l f hf n hn
#align filter.tendsto.nsmul_at_bot Filter.Tendsto.nsmul_atBot
#noalign filter.tendsto_bit0_at_top
#noalign filter.tendsto_bit0_at_bot
end OrderedAddCommMonoid
section OrderedCancelAddCommMonoid
variable [OrderedCancelAddCommMonoid β] {l : Filter α} {f g : α → β}
theorem tendsto_atTop_of_add_const_left (C : β) (hf : Tendsto (fun x => C + f x) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (C + b)).mono fun _ => le_of_add_le_add_left
#align filter.tendsto_at_top_of_add_const_left Filter.tendsto_atTop_of_add_const_left
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_const_left (C : β) (hf : Tendsto (fun x => C + f x) l atBot) :
Tendsto f l atBot :=
tendsto_atBot.2 fun b => (tendsto_atBot.1 hf (C + b)).mono fun _ => le_of_add_le_add_left
#align filter.tendsto_at_bot_of_add_const_left Filter.tendsto_atBot_of_add_const_left
theorem tendsto_atTop_of_add_const_right (C : β) (hf : Tendsto (fun x => f x + C) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (b + C)).mono fun _ => le_of_add_le_add_right
#align filter.tendsto_at_top_of_add_const_right Filter.tendsto_atTop_of_add_const_right
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_const_right (C : β) (hf : Tendsto (fun x => f x + C) l atBot) :
Tendsto f l atBot :=
tendsto_atBot.2 fun b => (tendsto_atBot.1 hf (b + C)).mono fun _ => le_of_add_le_add_right
#align filter.tendsto_at_bot_of_add_const_right Filter.tendsto_atBot_of_add_const_right
theorem tendsto_atTop_of_add_bdd_above_left' (C) (hC : ∀ᶠ x in l, f x ≤ C)
(h : Tendsto (fun x => f x + g x) l atTop) : Tendsto g l atTop :=
tendsto_atTop_of_add_const_left C
(tendsto_atTop_mono' l (hC.mono fun x hx => add_le_add_right hx (g x)) h)
#align filter.tendsto_at_top_of_add_bdd_above_left' Filter.tendsto_atTop_of_add_bdd_above_left'
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_left' (C) (hC : ∀ᶠ x in l, C ≤ f x)
(h : Tendsto (fun x => f x + g x) l atBot) : Tendsto g l atBot :=
tendsto_atBot_of_add_const_left C
(tendsto_atBot_mono' l (hC.mono fun x hx => add_le_add_right hx (g x)) h)
#align filter.tendsto_at_bot_of_add_bdd_below_left' Filter.tendsto_atBot_of_add_bdd_below_left'
theorem tendsto_atTop_of_add_bdd_above_left (C) (hC : ∀ x, f x ≤ C) :
Tendsto (fun x => f x + g x) l atTop → Tendsto g l atTop :=
tendsto_atTop_of_add_bdd_above_left' C (univ_mem' hC)
#align filter.tendsto_at_top_of_add_bdd_above_left Filter.tendsto_atTop_of_add_bdd_above_left
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_left (C) (hC : ∀ x, C ≤ f x) :
Tendsto (fun x => f x + g x) l atBot → Tendsto g l atBot :=
tendsto_atBot_of_add_bdd_below_left' C (univ_mem' hC)
#align filter.tendsto_at_bot_of_add_bdd_below_left Filter.tendsto_atBot_of_add_bdd_below_left
theorem tendsto_atTop_of_add_bdd_above_right' (C) (hC : ∀ᶠ x in l, g x ≤ C)
(h : Tendsto (fun x => f x + g x) l atTop) : Tendsto f l atTop :=
tendsto_atTop_of_add_const_right C
(tendsto_atTop_mono' l (hC.mono fun x hx => add_le_add_left hx (f x)) h)
#align filter.tendsto_at_top_of_add_bdd_above_right' Filter.tendsto_atTop_of_add_bdd_above_right'
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_right' (C) (hC : ∀ᶠ x in l, C ≤ g x)
(h : Tendsto (fun x => f x + g x) l atBot) : Tendsto f l atBot :=
tendsto_atBot_of_add_const_right C
(tendsto_atBot_mono' l (hC.mono fun x hx => add_le_add_left hx (f x)) h)
#align filter.tendsto_at_bot_of_add_bdd_below_right' Filter.tendsto_atBot_of_add_bdd_below_right'
theorem tendsto_atTop_of_add_bdd_above_right (C) (hC : ∀ x, g x ≤ C) :
Tendsto (fun x => f x + g x) l atTop → Tendsto f l atTop :=
tendsto_atTop_of_add_bdd_above_right' C (univ_mem' hC)
#align filter.tendsto_at_top_of_add_bdd_above_right Filter.tendsto_atTop_of_add_bdd_above_right
-- Porting note: the "order dual" trick timeouts
theorem tendsto_atBot_of_add_bdd_below_right (C) (hC : ∀ x, C ≤ g x) :
Tendsto (fun x => f x + g x) l atBot → Tendsto f l atBot :=
tendsto_atBot_of_add_bdd_below_right' C (univ_mem' hC)
#align filter.tendsto_at_bot_of_add_bdd_below_right Filter.tendsto_atBot_of_add_bdd_below_right
end OrderedCancelAddCommMonoid
section OrderedGroup
variable [OrderedAddCommGroup β] (l : Filter α) {f g : α → β}
theorem tendsto_atTop_add_left_of_le' (C : β) (hf : ∀ᶠ x in l, C ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
@tendsto_atTop_of_add_bdd_above_left' _ _ _ l (fun x => -f x) (fun x => f x + g x) (-C) (by simpa)
(by simpa)
#align filter.tendsto_at_top_add_left_of_le' Filter.tendsto_atTop_add_left_of_le'
theorem tendsto_atBot_add_left_of_ge' (C : β) (hf : ∀ᶠ x in l, f x ≤ C) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_left_of_le' _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_left_of_ge' Filter.tendsto_atBot_add_left_of_ge'
theorem tendsto_atTop_add_left_of_le (C : β) (hf : ∀ x, C ≤ f x) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_left_of_le' l C (univ_mem' hf) hg
#align filter.tendsto_at_top_add_left_of_le Filter.tendsto_atTop_add_left_of_le
theorem tendsto_atBot_add_left_of_ge (C : β) (hf : ∀ x, f x ≤ C) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_left_of_le _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_left_of_ge Filter.tendsto_atBot_add_left_of_ge
theorem tendsto_atTop_add_right_of_le' (C : β) (hf : Tendsto f l atTop) (hg : ∀ᶠ x in l, C ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
@tendsto_atTop_of_add_bdd_above_right' _ _ _ l (fun x => f x + g x) (fun x => -g x) (-C)
(by simp [hg]) (by simp [hf])
#align filter.tendsto_at_top_add_right_of_le' Filter.tendsto_atTop_add_right_of_le'
theorem tendsto_atBot_add_right_of_ge' (C : β) (hf : Tendsto f l atBot) (hg : ∀ᶠ x in l, g x ≤ C) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_right_of_le' _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_right_of_ge' Filter.tendsto_atBot_add_right_of_ge'
theorem tendsto_atTop_add_right_of_le (C : β) (hf : Tendsto f l atTop) (hg : ∀ x, C ≤ g x) :
Tendsto (fun x => f x + g x) l atTop :=
tendsto_atTop_add_right_of_le' l C hf (univ_mem' hg)
#align filter.tendsto_at_top_add_right_of_le Filter.tendsto_atTop_add_right_of_le
theorem tendsto_atBot_add_right_of_ge (C : β) (hf : Tendsto f l atBot) (hg : ∀ x, g x ≤ C) :
Tendsto (fun x => f x + g x) l atBot :=
@tendsto_atTop_add_right_of_le _ βᵒᵈ _ _ _ _ C hf hg
#align filter.tendsto_at_bot_add_right_of_ge Filter.tendsto_atBot_add_right_of_ge
theorem tendsto_atTop_add_const_left (C : β) (hf : Tendsto f l atTop) :
Tendsto (fun x => C + f x) l atTop :=
tendsto_atTop_add_left_of_le' l C (univ_mem' fun _ => le_refl C) hf
#align filter.tendsto_at_top_add_const_left Filter.tendsto_atTop_add_const_left
theorem tendsto_atBot_add_const_left (C : β) (hf : Tendsto f l atBot) :
Tendsto (fun x => C + f x) l atBot :=
@tendsto_atTop_add_const_left _ βᵒᵈ _ _ _ C hf
#align filter.tendsto_at_bot_add_const_left Filter.tendsto_atBot_add_const_left
theorem tendsto_atTop_add_const_right (C : β) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x + C) l atTop :=
tendsto_atTop_add_right_of_le' l C hf (univ_mem' fun _ => le_refl C)
#align filter.tendsto_at_top_add_const_right Filter.tendsto_atTop_add_const_right
theorem tendsto_atBot_add_const_right (C : β) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x + C) l atBot :=
@tendsto_atTop_add_const_right _ βᵒᵈ _ _ _ C hf
#align filter.tendsto_at_bot_add_const_right Filter.tendsto_atBot_add_const_right
theorem map_neg_atBot : map (Neg.neg : β → β) atBot = atTop :=
(OrderIso.neg β).map_atBot
#align filter.map_neg_at_bot Filter.map_neg_atBot
theorem map_neg_atTop : map (Neg.neg : β → β) atTop = atBot :=
(OrderIso.neg β).map_atTop
#align filter.map_neg_at_top Filter.map_neg_atTop
theorem comap_neg_atBot : comap (Neg.neg : β → β) atBot = atTop :=
(OrderIso.neg β).comap_atTop
#align filter.comap_neg_at_bot Filter.comap_neg_atBot
theorem comap_neg_atTop : comap (Neg.neg : β → β) atTop = atBot :=
(OrderIso.neg β).comap_atBot
#align filter.comap_neg_at_top Filter.comap_neg_atTop
theorem tendsto_neg_atTop_atBot : Tendsto (Neg.neg : β → β) atTop atBot :=
(OrderIso.neg β).tendsto_atTop
#align filter.tendsto_neg_at_top_at_bot Filter.tendsto_neg_atTop_atBot
theorem tendsto_neg_atBot_atTop : Tendsto (Neg.neg : β → β) atBot atTop :=
@tendsto_neg_atTop_atBot βᵒᵈ _
#align filter.tendsto_neg_at_bot_at_top Filter.tendsto_neg_atBot_atTop
variable {l}
@[simp]
theorem tendsto_neg_atTop_iff : Tendsto (fun x => -f x) l atTop ↔ Tendsto f l atBot :=
(OrderIso.neg β).tendsto_atBot_iff
#align filter.tendsto_neg_at_top_iff Filter.tendsto_neg_atTop_iff
@[simp]
theorem tendsto_neg_atBot_iff : Tendsto (fun x => -f x) l atBot ↔ Tendsto f l atTop :=
(OrderIso.neg β).tendsto_atTop_iff
#align filter.tendsto_neg_at_bot_iff Filter.tendsto_neg_atBot_iff
end OrderedGroup
section OrderedSemiring
variable [OrderedSemiring α] {l : Filter β} {f g : β → α}
#noalign filter.tendsto_bit1_at_top
theorem Tendsto.atTop_mul_atTop (hf : Tendsto f l atTop) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x * g x) l atTop := by
refine tendsto_atTop_mono' _ ?_ hg
filter_upwards [hg.eventually (eventually_ge_atTop 0),
hf.eventually (eventually_ge_atTop 1)] with _ using le_mul_of_one_le_left
#align filter.tendsto.at_top_mul_at_top Filter.Tendsto.atTop_mul_atTop
theorem tendsto_mul_self_atTop : Tendsto (fun x : α => x * x) atTop atTop :=
tendsto_id.atTop_mul_atTop tendsto_id
#align filter.tendsto_mul_self_at_top Filter.tendsto_mul_self_atTop
/-- The monomial function `x^n` tends to `+∞` at `+∞` for any positive natural `n`.
A version for positive real powers exists as `tendsto_rpow_atTop`. -/
theorem tendsto_pow_atTop {n : ℕ} (hn : n ≠ 0) : Tendsto (fun x : α => x ^ n) atTop atTop :=
tendsto_atTop_mono' _ ((eventually_ge_atTop 1).mono fun _x hx => le_self_pow hx hn) tendsto_id
#align filter.tendsto_pow_at_top Filter.tendsto_pow_atTop
end OrderedSemiring
theorem zero_pow_eventuallyEq [MonoidWithZero α] :
(fun n : ℕ => (0 : α) ^ n) =ᶠ[atTop] fun _ => 0 :=
eventually_atTop.2 ⟨1, fun _n hn ↦ zero_pow $ Nat.one_le_iff_ne_zero.1 hn⟩
#align filter.zero_pow_eventually_eq Filter.zero_pow_eventuallyEq
section OrderedRing
variable [OrderedRing α] {l : Filter β} {f g : β → α}
theorem Tendsto.atTop_mul_atBot (hf : Tendsto f l atTop) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x * g x) l atBot := by
have := hf.atTop_mul_atTop <| tendsto_neg_atBot_atTop.comp hg
simpa only [(· ∘ ·), neg_mul_eq_mul_neg, neg_neg] using tendsto_neg_atTop_atBot.comp this
#align filter.tendsto.at_top_mul_at_bot Filter.Tendsto.atTop_mul_atBot
theorem Tendsto.atBot_mul_atTop (hf : Tendsto f l atBot) (hg : Tendsto g l atTop) :
Tendsto (fun x => f x * g x) l atBot := by
have : Tendsto (fun x => -f x * g x) l atTop :=
(tendsto_neg_atBot_atTop.comp hf).atTop_mul_atTop hg
simpa only [(· ∘ ·), neg_mul_eq_neg_mul, neg_neg] using tendsto_neg_atTop_atBot.comp this
#align filter.tendsto.at_bot_mul_at_top Filter.Tendsto.atBot_mul_atTop
theorem Tendsto.atBot_mul_atBot (hf : Tendsto f l atBot) (hg : Tendsto g l atBot) :
Tendsto (fun x => f x * g x) l atTop := by
have : Tendsto (fun x => -f x * -g x) l atTop :=
(tendsto_neg_atBot_atTop.comp hf).atTop_mul_atTop (tendsto_neg_atBot_atTop.comp hg)
simpa only [neg_mul_neg] using this
#align filter.tendsto.at_bot_mul_at_bot Filter.Tendsto.atBot_mul_atBot
end OrderedRing
section LinearOrderedAddCommGroup
variable [LinearOrderedAddCommGroup α]
/-- $\lim_{x\to+\infty}|x|=+\infty$ -/
theorem tendsto_abs_atTop_atTop : Tendsto (abs : α → α) atTop atTop :=
tendsto_atTop_mono le_abs_self tendsto_id
#align filter.tendsto_abs_at_top_at_top Filter.tendsto_abs_atTop_atTop
/-- $\lim_{x\to-\infty}|x|=+\infty$ -/
theorem tendsto_abs_atBot_atTop : Tendsto (abs : α → α) atBot atTop :=
tendsto_atTop_mono neg_le_abs tendsto_neg_atBot_atTop
#align filter.tendsto_abs_at_bot_at_top Filter.tendsto_abs_atBot_atTop
@[simp]
theorem comap_abs_atTop : comap (abs : α → α) atTop = atBot ⊔ atTop := by
refine
le_antisymm (((atTop_basis.comap _).le_basis_iff (atBot_basis.sup atTop_basis)).2 ?_)
(sup_le tendsto_abs_atBot_atTop.le_comap tendsto_abs_atTop_atTop.le_comap)
rintro ⟨a, b⟩ -
refine ⟨max (-a) b, trivial, fun x hx => ?_⟩
rw [mem_preimage, mem_Ici, le_abs', max_le_iff, ← min_neg_neg, le_min_iff, neg_neg] at hx
exact hx.imp And.left And.right
#align filter.comap_abs_at_top Filter.comap_abs_atTop
end LinearOrderedAddCommGroup
section LinearOrderedSemiring
variable [LinearOrderedSemiring α] {l : Filter β} {f : β → α}
theorem Tendsto.atTop_of_const_mul {c : α} (hc : 0 < c) (hf : Tendsto (fun x => c * f x) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (c * b)).mono
fun _x hx => le_of_mul_le_mul_left hx hc
#align filter.tendsto.at_top_of_const_mul Filter.Tendsto.atTop_of_const_mul
theorem Tendsto.atTop_of_mul_const {c : α} (hc : 0 < c) (hf : Tendsto (fun x => f x * c) l atTop) :
Tendsto f l atTop :=
tendsto_atTop.2 fun b => (tendsto_atTop.1 hf (b * c)).mono
fun _x hx => le_of_mul_le_mul_right hx hc
#align filter.tendsto.at_top_of_mul_const Filter.Tendsto.atTop_of_mul_const
@[simp]
theorem tendsto_pow_atTop_iff {n : ℕ} : Tendsto (fun x : α => x ^ n) atTop atTop ↔ n ≠ 0 :=
⟨fun h hn => by simp only [hn, pow_zero, not_tendsto_const_atTop] at h, tendsto_pow_atTop⟩
#align filter.tendsto_pow_at_top_iff Filter.tendsto_pow_atTop_iff
end LinearOrderedSemiring
theorem not_tendsto_pow_atTop_atBot [LinearOrderedRing α] :
∀ {n : ℕ}, ¬Tendsto (fun x : α => x ^ n) atTop atBot
| 0 => by simp [not_tendsto_const_atBot]
| n + 1 => (tendsto_pow_atTop n.succ_ne_zero).not_tendsto disjoint_atTop_atBot
#align filter.not_tendsto_pow_at_top_at_bot Filter.not_tendsto_pow_atTop_atBot
section LinearOrderedSemifield
variable [LinearOrderedSemifield α] {l : Filter β} {f : β → α} {r c : α} {n : ℕ}
/-!
### Multiplication by constant: iff lemmas
-/
/-- If `r` is a positive constant, `fun x ↦ r * f x` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
theorem tendsto_const_mul_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x => r * f x) l atTop ↔ Tendsto f l atTop :=
⟨fun h => h.atTop_of_const_mul hr, fun h =>
Tendsto.atTop_of_const_mul (inv_pos.2 hr) <| by simpa only [inv_mul_cancel_left₀ hr.ne'] ⟩
#align filter.tendsto_const_mul_at_top_of_pos Filter.tendsto_const_mul_atTop_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x * r` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
theorem tendsto_mul_const_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x => f x * r) l atTop ↔ Tendsto f l atTop := by
simpa only [mul_comm] using tendsto_const_mul_atTop_of_pos hr
#align filter.tendsto_mul_const_at_top_of_pos Filter.tendsto_mul_const_atTop_of_pos
/-- If `r` is a positive constant, `x ↦ f x / r` tends to infinity along a filter
if and only if `f` tends to infinity along the same filter. -/
lemma tendsto_div_const_atTop_of_pos (hr : 0 < r) :
Tendsto (fun x ↦ f x / r) l atTop ↔ Tendsto f l atTop := by
simpa only [div_eq_mul_inv] using tendsto_mul_const_atTop_of_pos (inv_pos.2 hr)
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`fun x ↦ r * f x` tends to infinity if and only if `0 < r. `-/
theorem tendsto_const_mul_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atTop ↔ 0 < r := by
refine ⟨fun hrf => not_le.mp fun hr => ?_, fun hr => (tendsto_const_mul_atTop_of_pos hr).mpr h⟩
rcases ((h.eventually_ge_atTop 0).and (hrf.eventually_gt_atTop 0)).exists with ⟨x, hx, hrx⟩
exact (mul_nonpos_of_nonpos_of_nonneg hr hx).not_lt hrx
#align filter.tendsto_const_mul_at_top_iff_pos Filter.tendsto_const_mul_atTop_iff_pos
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`fun x ↦ f x * r` tends to infinity if and only if `0 < r. `-/
theorem tendsto_mul_const_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atTop ↔ 0 < r := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff_pos h]
#align filter.tendsto_mul_const_at_top_iff_pos Filter.tendsto_mul_const_atTop_iff_pos
/-- If `f` tends to infinity along a nontrivial filter `l`, then
`x ↦ f x * r` tends to infinity if and only if `0 < r. `-/
lemma tendsto_div_const_atTop_iff_pos [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atTop ↔ 0 < r := by
simp only [div_eq_mul_inv, tendsto_mul_const_atTop_iff_pos h, inv_pos]
/-- If `f` tends to infinity along a filter, then `f` multiplied by a positive
constant (on the left) also tends to infinity. For a version working in `ℕ` or `ℤ`, use
`Filter.Tendsto.const_mul_atTop'` instead. -/
theorem Tendsto.const_mul_atTop (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atTop :=
(tendsto_const_mul_atTop_of_pos hr).2 hf
#align filter.tendsto.const_mul_at_top Filter.Tendsto.const_mul_atTop
/-- If a function `f` tends to infinity along a filter, then `f` multiplied by a positive
constant (on the right) also tends to infinity. For a version working in `ℕ` or `ℤ`, use
`Filter.Tendsto.atTop_mul_const'` instead. -/
theorem Tendsto.atTop_mul_const (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atTop :=
(tendsto_mul_const_atTop_of_pos hr).2 hf
#align filter.tendsto.at_top_mul_const Filter.Tendsto.atTop_mul_const
/-- If a function `f` tends to infinity along a filter, then `f` divided by a positive
constant also tends to infinity. -/
theorem Tendsto.atTop_div_const (hr : 0 < r) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x / r) l atTop := by
simpa only [div_eq_mul_inv] using hf.atTop_mul_const (inv_pos.2 hr)
#align filter.tendsto.at_top_div_const Filter.Tendsto.atTop_div_const
theorem tendsto_const_mul_pow_atTop (hn : n ≠ 0) (hc : 0 < c) :
Tendsto (fun x => c * x ^ n) atTop atTop :=
Tendsto.const_mul_atTop hc (tendsto_pow_atTop hn)
#align filter.tendsto_const_mul_pow_at_top Filter.tendsto_const_mul_pow_atTop
theorem tendsto_const_mul_pow_atTop_iff :
Tendsto (fun x => c * x ^ n) atTop atTop ↔ n ≠ 0 ∧ 0 < c := by
refine ⟨fun h => ⟨?_, ?_⟩, fun h => tendsto_const_mul_pow_atTop h.1 h.2⟩
· rintro rfl
simp only [pow_zero, not_tendsto_const_atTop] at h
· rcases ((h.eventually_gt_atTop 0).and (eventually_ge_atTop 0)).exists with ⟨k, hck, hk⟩
exact pos_of_mul_pos_left hck (pow_nonneg hk _)
#align filter.tendsto_const_mul_pow_at_top_iff Filter.tendsto_const_mul_pow_atTop_iff
lemma tendsto_zpow_atTop_atTop {n : ℤ} (hn : 0 < n) : Tendsto (fun x : α ↦ x ^ n) atTop atTop := by
lift n to ℕ+ using hn; simp
#align tendsto_zpow_at_top_at_top Filter.tendsto_zpow_atTop_atTop
end LinearOrderedSemifield
section LinearOrderedField
variable [LinearOrderedField α] {l : Filter β} {f : β → α} {r : α}
/-- If `r` is a positive constant, `fun x ↦ r * f x` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
theorem tendsto_const_mul_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x => r * f x) l atBot ↔ Tendsto f l atBot := by
simpa only [← mul_neg, ← tendsto_neg_atTop_iff] using tendsto_const_mul_atTop_of_pos hr
#align filter.tendsto_const_mul_at_bot_of_pos Filter.tendsto_const_mul_atBot_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x * r` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
theorem tendsto_mul_const_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x => f x * r) l atBot ↔ Tendsto f l atBot := by
simpa only [mul_comm] using tendsto_const_mul_atBot_of_pos hr
#align filter.tendsto_mul_const_at_bot_of_pos Filter.tendsto_mul_const_atBot_of_pos
/-- If `r` is a positive constant, `fun x ↦ f x / r` tends to negative infinity along a filter
if and only if `f` tends to negative infinity along the same filter. -/
lemma tendsto_div_const_atBot_of_pos (hr : 0 < r) :
Tendsto (fun x ↦ f x / r) l atBot ↔ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_of_pos, hr]
/-- If `r` is a negative constant, `fun x ↦ r * f x` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
theorem tendsto_const_mul_atTop_of_neg (hr : r < 0) :
Tendsto (fun x => r * f x) l atTop ↔ Tendsto f l atBot := by
simpa only [neg_mul, tendsto_neg_atBot_iff] using tendsto_const_mul_atBot_of_pos (neg_pos.2 hr)
#align filter.tendsto_const_mul_at_top_of_neg Filter.tendsto_const_mul_atTop_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x * r` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
theorem tendsto_mul_const_atTop_of_neg (hr : r < 0) :
Tendsto (fun x => f x * r) l atTop ↔ Tendsto f l atBot := by
simpa only [mul_comm] using tendsto_const_mul_atTop_of_neg hr
/-- If `r` is a negative constant, `fun x ↦ f x / r` tends to infinity along a filter `l`
if and only if `f` tends to negative infinity along `l`. -/
lemma tendsto_div_const_atTop_of_neg (hr : r < 0) :
Tendsto (fun x ↦ f x / r) l atTop ↔ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_of_neg, hr]
/-- If `r` is a negative constant, `fun x ↦ r * f x` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
theorem tendsto_const_mul_atBot_of_neg (hr : r < 0) :
Tendsto (fun x => r * f x) l atBot ↔ Tendsto f l atTop := by
simpa only [neg_mul, tendsto_neg_atTop_iff] using tendsto_const_mul_atTop_of_pos (neg_pos.2 hr)
#align filter.tendsto_const_mul_at_bot_of_neg Filter.tendsto_const_mul_atBot_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x * r` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
theorem tendsto_mul_const_atBot_of_neg (hr : r < 0) :
Tendsto (fun x => f x * r) l atBot ↔ Tendsto f l atTop := by
simpa only [mul_comm] using tendsto_const_mul_atBot_of_neg hr
#align filter.tendsto_mul_const_at_bot_of_neg Filter.tendsto_mul_const_atBot_of_neg
/-- If `r` is a negative constant, `fun x ↦ f x / r` tends to negative infinity along a filter `l`
if and only if `f` tends to infinity along `l`. -/
lemma tendsto_div_const_atBot_of_neg (hr : r < 0) :
Tendsto (fun x ↦ f x / r) l atBot ↔ Tendsto f l atTop := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_of_neg, hr]
/-- The function `fun x ↦ r * f x` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
theorem tendsto_const_mul_atTop_iff [NeBot l] :
Tendsto (fun x => r * f x) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
rcases lt_trichotomy r 0 with (hr | rfl | hr)
· simp [hr, hr.not_lt, tendsto_const_mul_atTop_of_neg]
· simp [not_tendsto_const_atTop]
· simp [hr, hr.not_lt, tendsto_const_mul_atTop_of_pos]
#align filter.tendsto_const_mul_at_top_iff Filter.tendsto_const_mul_atTop_iff
/-- The function `fun x ↦ f x * r` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
theorem tendsto_mul_const_atTop_iff [NeBot l] :
Tendsto (fun x => f x * r) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff]
#align filter.tendsto_mul_const_at_top_iff Filter.tendsto_mul_const_atTop_iff
/-- The function `fun x ↦ f x / r` tends to infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to infinity or `r < 0` and `f` tends to negative infinity. -/
lemma tendsto_div_const_atTop_iff [NeBot l] :
Tendsto (fun x ↦ f x / r) l atTop ↔ 0 < r ∧ Tendsto f l atTop ∨ r < 0 ∧ Tendsto f l atBot := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_iff]
/-- The function `fun x ↦ r * f x` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
theorem tendsto_const_mul_atBot_iff [NeBot l] :
Tendsto (fun x => r * f x) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp only [← tendsto_neg_atTop_iff, ← mul_neg, tendsto_const_mul_atTop_iff, neg_neg]
#align filter.tendsto_const_mul_at_bot_iff Filter.tendsto_const_mul_atBot_iff
/-- The function `fun x ↦ f x * r` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
theorem tendsto_mul_const_atBot_iff [NeBot l] :
Tendsto (fun x => f x * r) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff]
#align filter.tendsto_mul_const_at_bot_iff Filter.tendsto_mul_const_atBot_iff
/-- The function `fun x ↦ f x / r` tends to negative infinity along a nontrivial filter
if and only if `r > 0` and `f` tends to negative infinity or `r < 0` and `f` tends to infinity. -/
lemma tendsto_div_const_atBot_iff [NeBot l] :
Tendsto (fun x ↦ f x / r) l atBot ↔ 0 < r ∧ Tendsto f l atBot ∨ r < 0 ∧ Tendsto f l atTop := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff]
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ r * f x` tends to infinity if and only if `r < 0. `-/
theorem tendsto_const_mul_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atTop ↔ r < 0 := by
simp [tendsto_const_mul_atTop_iff, h, h.not_tendsto disjoint_atBot_atTop]
#align filter.tendsto_const_mul_at_top_iff_neg Filter.tendsto_const_mul_atTop_iff_neg
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ f x * r` tends to infinity if and only if `r < 0. `-/
theorem tendsto_mul_const_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atTop ↔ r < 0 := by
simp only [mul_comm _ r, tendsto_const_mul_atTop_iff_neg h]
#align filter.tendsto_mul_const_at_top_iff_neg Filter.tendsto_mul_const_atTop_iff_neg
/-- If `f` tends to negative infinity along a nontrivial filter `l`,
then `fun x ↦ f x / r` tends to infinity if and only if `r < 0. `-/
lemma tendsto_div_const_atTop_iff_neg [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x ↦ f x / r) l atTop ↔ r < 0 := by
simp [div_eq_mul_inv, tendsto_mul_const_atTop_iff_neg h]
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ r * f x` tends to negative infinity if and only if `0 < r. `-/
theorem tendsto_const_mul_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atBot ↔ 0 < r := by
simp [tendsto_const_mul_atBot_iff, h, h.not_tendsto disjoint_atBot_atTop]
#align filter.tendsto_const_mul_at_bot_iff_pos Filter.tendsto_const_mul_atBot_iff_pos
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ f x * r` tends to negative infinity if and only if `0 < r. `-/
theorem tendsto_mul_const_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atBot ↔ 0 < r := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff_pos h]
#align filter.tendsto_mul_const_at_bot_iff_pos Filter.tendsto_mul_const_atBot_iff_pos
/-- If `f` tends to negative infinity along a nontrivial filter `l`, then
`fun x ↦ f x / r` tends to negative infinity if and only if `0 < r. `-/
lemma tendsto_div_const_atBot_iff_pos [NeBot l] (h : Tendsto f l atBot) :
Tendsto (fun x ↦ f x / r) l atBot ↔ 0 < r := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff_pos h]
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ r * f x` tends to negative infinity if and only if `r < 0. `-/
theorem tendsto_const_mul_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atBot ↔ r < 0 := by
simp [tendsto_const_mul_atBot_iff, h, h.not_tendsto disjoint_atTop_atBot]
#align filter.tendsto_const_mul_at_bot_iff_neg Filter.tendsto_const_mul_atBot_iff_neg
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ f x * r` tends to negative infinity if and only if `r < 0. `-/
theorem tendsto_mul_const_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atBot ↔ r < 0 := by
simp only [mul_comm _ r, tendsto_const_mul_atBot_iff_neg h]
#align filter.tendsto_mul_const_at_bot_iff_neg Filter.tendsto_mul_const_atBot_iff_neg
/-- If `f` tends to infinity along a nontrivial filter,
`fun x ↦ f x / r` tends to negative infinity if and only if `r < 0. `-/
lemma tendsto_div_const_atBot_iff_neg [NeBot l] (h : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atBot ↔ r < 0 := by
simp [div_eq_mul_inv, tendsto_mul_const_atBot_iff_neg h]
/-- If a function `f` tends to infinity along a filter,
then `f` multiplied by a negative constant (on the left) tends to negative infinity. -/
theorem Tendsto.const_mul_atTop_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x => r * f x) l atBot :=
(tendsto_const_mul_atBot_of_neg hr).2 hf
#align filter.tendsto.neg_const_mul_at_top Filter.Tendsto.const_mul_atTop_of_neg
/-- If a function `f` tends to infinity along a filter,
then `f` multiplied by a negative constant (on the right) tends to negative infinity. -/
theorem Tendsto.atTop_mul_const_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x => f x * r) l atBot :=
(tendsto_mul_const_atBot_of_neg hr).2 hf
#align filter.tendsto.at_top_mul_neg_const Filter.Tendsto.atTop_mul_const_of_neg
/-- If a function `f` tends to infinity along a filter,
then `f` divided by a negative constant tends to negative infinity. -/
lemma Tendsto.atTop_div_const_of_neg (hr : r < 0) (hf : Tendsto f l atTop) :
Tendsto (fun x ↦ f x / r) l atBot := (tendsto_div_const_atBot_of_neg hr).2 hf
/-- If a function `f` tends to negative infinity along a filter, then `f` multiplied by
a positive constant (on the left) also tends to negative infinity. -/
theorem Tendsto.const_mul_atBot (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atBot :=
(tendsto_const_mul_atBot_of_pos hr).2 hf
#align filter.tendsto.const_mul_at_bot Filter.Tendsto.const_mul_atBot
/-- If a function `f` tends to negative infinity along a filter, then `f` multiplied by
a positive constant (on the right) also tends to negative infinity. -/
theorem Tendsto.atBot_mul_const (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atBot :=
(tendsto_mul_const_atBot_of_pos hr).2 hf
#align filter.tendsto.at_bot_mul_const Filter.Tendsto.atBot_mul_const
/-- If a function `f` tends to negative infinity along a filter, then `f` divided by
a positive constant also tends to negative infinity. -/
theorem Tendsto.atBot_div_const (hr : 0 < r) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x / r) l atBot := (tendsto_div_const_atBot_of_pos hr).2 hf
#align filter.tendsto.at_bot_div_const Filter.Tendsto.atBot_div_const
/-- If a function `f` tends to negative infinity along a filter,
then `f` multiplied by a negative constant (on the left) tends to positive infinity. -/
theorem Tendsto.const_mul_atBot_of_neg (hr : r < 0) (hf : Tendsto f l atBot) :
Tendsto (fun x => r * f x) l atTop :=
(tendsto_const_mul_atTop_of_neg hr).2 hf
#align filter.tendsto.neg_const_mul_at_bot Filter.Tendsto.const_mul_atBot_of_neg
/-- If a function tends to negative infinity along a filter,
then `f` multiplied by a negative constant (on the right) tends to positive infinity. -/
theorem Tendsto.atBot_mul_const_of_neg (hr : r < 0) (hf : Tendsto f l atBot) :
Tendsto (fun x => f x * r) l atTop :=
(tendsto_mul_const_atTop_of_neg hr).2 hf
#align filter.tendsto.at_bot_mul_neg_const Filter.Tendsto.atBot_mul_const_of_neg
theorem tendsto_neg_const_mul_pow_atTop {c : α} {n : ℕ} (hn : n ≠ 0) (hc : c < 0) :
Tendsto (fun x => c * x ^ n) atTop atBot :=
(tendsto_pow_atTop hn).const_mul_atTop_of_neg hc
#align filter.tendsto_neg_const_mul_pow_at_top Filter.tendsto_neg_const_mul_pow_atTop
theorem tendsto_const_mul_pow_atBot_iff {c : α} {n : ℕ} :
Tendsto (fun x => c * x ^ n) atTop atBot ↔ n ≠ 0 ∧ c < 0 := by
simp only [← tendsto_neg_atTop_iff, ← neg_mul, tendsto_const_mul_pow_atTop_iff, neg_pos]
#align filter.tendsto_const_mul_pow_at_bot_iff Filter.tendsto_const_mul_pow_atBot_iff
@[deprecated (since := "2024-05-06")]
alias Tendsto.neg_const_mul_atTop := Tendsto.const_mul_atTop_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.atTop_mul_neg_const := Tendsto.atTop_mul_const_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.neg_const_mul_atBot := Tendsto.const_mul_atBot_of_neg
@[deprecated (since := "2024-05-06")]
alias Tendsto.atBot_mul_neg_const := Tendsto.atBot_mul_const_of_neg
end LinearOrderedField
open Filter
theorem tendsto_atTop' [Nonempty α] [SemilatticeSup α] {f : α → β} {l : Filter β} :
Tendsto f atTop l ↔ ∀ s ∈ l, ∃ a, ∀ b ≥ a, f b ∈ s := by
simp only [tendsto_def, mem_atTop_sets, mem_preimage]
#align filter.tendsto_at_top' Filter.tendsto_atTop'
theorem tendsto_atBot' [Nonempty α] [SemilatticeInf α] {f : α → β} {l : Filter β} :
Tendsto f atBot l ↔ ∀ s ∈ l, ∃ a, ∀ b ≤ a, f b ∈ s :=
@tendsto_atTop' αᵒᵈ _ _ _ _ _
#align filter.tendsto_at_bot' Filter.tendsto_atBot'
theorem tendsto_atTop_principal [Nonempty β] [SemilatticeSup β] {f : β → α} {s : Set α} :
Tendsto f atTop (𝓟 s) ↔ ∃ N, ∀ n ≥ N, f n ∈ s := by
simp_rw [tendsto_iff_comap, comap_principal, le_principal_iff, mem_atTop_sets, mem_preimage]
#align filter.tendsto_at_top_principal Filter.tendsto_atTop_principal
theorem tendsto_atBot_principal [Nonempty β] [SemilatticeInf β] {f : β → α} {s : Set α} :
Tendsto f atBot (𝓟 s) ↔ ∃ N, ∀ n ≤ N, f n ∈ s :=
@tendsto_atTop_principal _ βᵒᵈ _ _ _ _
#align filter.tendsto_at_bot_principal Filter.tendsto_atBot_principal
/-- A function `f` grows to `+∞` independent of an order-preserving embedding `e`. -/
theorem tendsto_atTop_atTop [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β} :
Tendsto f atTop atTop ↔ ∀ b : β, ∃ i : α, ∀ a : α, i ≤ a → b ≤ f a :=
Iff.trans tendsto_iInf <| forall_congr' fun _ => tendsto_atTop_principal
#align filter.tendsto_at_top_at_top Filter.tendsto_atTop_atTop
theorem tendsto_atTop_atBot [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β} :
Tendsto f atTop atBot ↔ ∀ b : β, ∃ i : α, ∀ a : α, i ≤ a → f a ≤ b :=
@tendsto_atTop_atTop α βᵒᵈ _ _ _ f
#align filter.tendsto_at_top_at_bot Filter.tendsto_atTop_atBot
theorem tendsto_atBot_atTop [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β} :
Tendsto f atBot atTop ↔ ∀ b : β, ∃ i : α, ∀ a : α, a ≤ i → b ≤ f a :=
@tendsto_atTop_atTop αᵒᵈ β _ _ _ f
#align filter.tendsto_at_bot_at_top Filter.tendsto_atBot_atTop
theorem tendsto_atBot_atBot [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β} :
Tendsto f atBot atBot ↔ ∀ b : β, ∃ i : α, ∀ a : α, a ≤ i → f a ≤ b :=
@tendsto_atTop_atTop αᵒᵈ βᵒᵈ _ _ _ f
#align filter.tendsto_at_bot_at_bot Filter.tendsto_atBot_atBot
theorem tendsto_atTop_atTop_of_monotone [Preorder α] [Preorder β] {f : α → β} (hf : Monotone f)
(h : ∀ b, ∃ a, b ≤ f a) : Tendsto f atTop atTop :=
tendsto_iInf.2 fun b =>
tendsto_principal.2 <|
let ⟨a, ha⟩ := h b
mem_of_superset (mem_atTop a) fun _a' ha' => le_trans ha (hf ha')
#align filter.tendsto_at_top_at_top_of_monotone Filter.tendsto_atTop_atTop_of_monotone
theorem tendsto_atTop_atBot_of_antitone [Preorder α] [Preorder β] {f : α → β} (hf : Antitone f)
(h : ∀ b, ∃ a, f a ≤ b) : Tendsto f atTop atBot :=
@tendsto_atTop_atTop_of_monotone _ βᵒᵈ _ _ _ hf h
theorem tendsto_atBot_atBot_of_monotone [Preorder α] [Preorder β] {f : α → β} (hf : Monotone f)
(h : ∀ b, ∃ a, f a ≤ b) : Tendsto f atBot atBot :=
tendsto_iInf.2 fun b => tendsto_principal.2 <|
let ⟨a, ha⟩ := h b; mem_of_superset (mem_atBot a) fun _a' ha' => le_trans (hf ha') ha
#align filter.tendsto_at_bot_at_bot_of_monotone Filter.tendsto_atBot_atBot_of_monotone
theorem tendsto_atBot_atTop_of_antitone [Preorder α] [Preorder β] {f : α → β} (hf : Antitone f)
(h : ∀ b, ∃ a, b ≤ f a) : Tendsto f atBot atTop :=
@tendsto_atBot_atBot_of_monotone _ βᵒᵈ _ _ _ hf h
theorem tendsto_atTop_atTop_iff_of_monotone [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β}
(hf : Monotone f) : Tendsto f atTop atTop ↔ ∀ b : β, ∃ a : α, b ≤ f a :=
tendsto_atTop_atTop.trans <| forall_congr' fun _ => exists_congr fun a =>
⟨fun h => h a (le_refl a), fun h _a' ha' => le_trans h <| hf ha'⟩
#align filter.tendsto_at_top_at_top_iff_of_monotone Filter.tendsto_atTop_atTop_iff_of_monotone
theorem tendsto_atTop_atBot_iff_of_antitone [Nonempty α] [SemilatticeSup α] [Preorder β] {f : α → β}
(hf : Antitone f) : Tendsto f atTop atBot ↔ ∀ b : β, ∃ a : α, f a ≤ b :=
@tendsto_atTop_atTop_iff_of_monotone _ βᵒᵈ _ _ _ _ hf
theorem tendsto_atBot_atBot_iff_of_monotone [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β}
(hf : Monotone f) : Tendsto f atBot atBot ↔ ∀ b : β, ∃ a : α, f a ≤ b :=
tendsto_atBot_atBot.trans <| forall_congr' fun _ => exists_congr fun a =>
⟨fun h => h a (le_refl a), fun h _a' ha' => le_trans (hf ha') h⟩
#align filter.tendsto_at_bot_at_bot_iff_of_monotone Filter.tendsto_atBot_atBot_iff_of_monotone
theorem tendsto_atBot_atTop_iff_of_antitone [Nonempty α] [SemilatticeInf α] [Preorder β] {f : α → β}
(hf : Antitone f) : Tendsto f atBot atTop ↔ ∀ b : β, ∃ a : α, b ≤ f a :=
@tendsto_atBot_atBot_iff_of_monotone _ βᵒᵈ _ _ _ _ hf
alias _root_.Monotone.tendsto_atTop_atTop := tendsto_atTop_atTop_of_monotone
#align monotone.tendsto_at_top_at_top Monotone.tendsto_atTop_atTop
alias _root_.Monotone.tendsto_atBot_atBot := tendsto_atBot_atBot_of_monotone
#align monotone.tendsto_at_bot_at_bot Monotone.tendsto_atBot_atBot
alias _root_.Monotone.tendsto_atTop_atTop_iff := tendsto_atTop_atTop_iff_of_monotone
#align monotone.tendsto_at_top_at_top_iff Monotone.tendsto_atTop_atTop_iff
alias _root_.Monotone.tendsto_atBot_atBot_iff := tendsto_atBot_atBot_iff_of_monotone
#align monotone.tendsto_at_bot_at_bot_iff Monotone.tendsto_atBot_atBot_iff
theorem comap_embedding_atTop [Preorder β] [Preorder γ] {e : β → γ}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, c ≤ e b) : comap e atTop = atTop :=
le_antisymm
(le_iInf fun b =>
le_principal_iff.2 <| mem_comap.2 ⟨Ici (e b), mem_atTop _, fun _ => (hm _ _).1⟩)
(tendsto_atTop_atTop_of_monotone (fun _ _ => (hm _ _).2) hu).le_comap
#align filter.comap_embedding_at_top Filter.comap_embedding_atTop
theorem comap_embedding_atBot [Preorder β] [Preorder γ] {e : β → γ}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, e b ≤ c) : comap e atBot = atBot :=
@comap_embedding_atTop βᵒᵈ γᵒᵈ _ _ e (Function.swap hm) hu
#align filter.comap_embedding_at_bot Filter.comap_embedding_atBot
theorem tendsto_atTop_embedding [Preorder β] [Preorder γ] {f : α → β} {e : β → γ} {l : Filter α}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, c ≤ e b) :
Tendsto (e ∘ f) l atTop ↔ Tendsto f l atTop := by
rw [← comap_embedding_atTop hm hu, tendsto_comap_iff]
#align filter.tendsto_at_top_embedding Filter.tendsto_atTop_embedding
/-- A function `f` goes to `-∞` independent of an order-preserving embedding `e`. -/
theorem tendsto_atBot_embedding [Preorder β] [Preorder γ] {f : α → β} {e : β → γ} {l : Filter α}
(hm : ∀ b₁ b₂, e b₁ ≤ e b₂ ↔ b₁ ≤ b₂) (hu : ∀ c, ∃ b, e b ≤ c) :
Tendsto (e ∘ f) l atBot ↔ Tendsto f l atBot :=
@tendsto_atTop_embedding α βᵒᵈ γᵒᵈ _ _ f e l (Function.swap hm) hu
#align filter.tendsto_at_bot_embedding Filter.tendsto_atBot_embedding
theorem tendsto_finset_range : Tendsto Finset.range atTop atTop :=
Finset.range_mono.tendsto_atTop_atTop Finset.exists_nat_subset_range
#align filter.tendsto_finset_range Filter.tendsto_finset_range
theorem atTop_finset_eq_iInf : (atTop : Filter (Finset α)) = ⨅ x : α, 𝓟 (Ici {x}) := by
refine le_antisymm (le_iInf fun i => le_principal_iff.2 <| mem_atTop ({i} : Finset α)) ?_
refine
le_iInf fun s =>
le_principal_iff.2 <| mem_iInf_of_iInter s.finite_toSet (fun i => mem_principal_self _) ?_
simp only [subset_def, mem_iInter, SetCoe.forall, mem_Ici, Finset.le_iff_subset,
Finset.mem_singleton, Finset.subset_iff, forall_eq]
exact fun t => id
#align filter.at_top_finset_eq_infi Filter.atTop_finset_eq_iInf
/-- If `f` is a monotone sequence of `Finset`s and each `x` belongs to one of `f n`, then
`Tendsto f atTop atTop`. -/
theorem tendsto_atTop_finset_of_monotone [Preorder β] {f : β → Finset α} (h : Monotone f)
(h' : ∀ x : α, ∃ n, x ∈ f n) : Tendsto f atTop atTop := by
simp only [atTop_finset_eq_iInf, tendsto_iInf, tendsto_principal]
intro a
rcases h' a with ⟨b, hb⟩
exact (eventually_ge_atTop b).mono fun b' hb' => (Finset.singleton_subset_iff.2 hb).trans (h hb')
#align filter.tendsto_at_top_finset_of_monotone Filter.tendsto_atTop_finset_of_monotone
alias _root_.Monotone.tendsto_atTop_finset := tendsto_atTop_finset_of_monotone
#align monotone.tendsto_at_top_finset Monotone.tendsto_atTop_finset
-- Porting note: add assumption `DecidableEq β` so that the lemma applies to any instance
theorem tendsto_finset_image_atTop_atTop [DecidableEq β] {i : β → γ} {j : γ → β}
(h : Function.LeftInverse j i) : Tendsto (Finset.image j) atTop atTop :=
(Finset.image_mono j).tendsto_atTop_finset fun a =>
⟨{i a}, by simp only [Finset.image_singleton, h a, Finset.mem_singleton]⟩
#align filter.tendsto_finset_image_at_top_at_top Filter.tendsto_finset_image_atTop_atTop
theorem tendsto_finset_preimage_atTop_atTop {f : α → β} (hf : Function.Injective f) :
Tendsto (fun s : Finset β => s.preimage f (hf.injOn)) atTop atTop :=
(Finset.monotone_preimage hf).tendsto_atTop_finset fun x =>
⟨{f x}, Finset.mem_preimage.2 <| Finset.mem_singleton_self _⟩
#align filter.tendsto_finset_preimage_at_top_at_top Filter.tendsto_finset_preimage_atTop_atTop
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_atTop_atTop_eq [Preorder α] [Preorder β] :
(atTop : Filter α) ×ˢ (atTop : Filter β) = (atTop : Filter (α × β)) := by
cases isEmpty_or_nonempty α
· exact Subsingleton.elim _ _
cases isEmpty_or_nonempty β
· exact Subsingleton.elim _ _
simpa [atTop, prod_iInf_left, prod_iInf_right, iInf_prod] using iInf_comm
#align filter.prod_at_top_at_top_eq Filter.prod_atTop_atTop_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_atBot_atBot_eq [Preorder β₁] [Preorder β₂] :
(atBot : Filter β₁) ×ˢ (atBot : Filter β₂) = (atBot : Filter (β₁ × β₂)) :=
@prod_atTop_atTop_eq β₁ᵒᵈ β₂ᵒᵈ _ _
#align filter.prod_at_bot_at_bot_eq Filter.prod_atBot_atBot_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_map_atTop_eq {α₁ α₂ β₁ β₂ : Type*} [Preorder β₁] [Preorder β₂]
(u₁ : β₁ → α₁) (u₂ : β₂ → α₂) : map u₁ atTop ×ˢ map u₂ atTop = map (Prod.map u₁ u₂) atTop := by
rw [prod_map_map_eq, prod_atTop_atTop_eq, Prod.map_def]
#align filter.prod_map_at_top_eq Filter.prod_map_atTop_eq
-- Porting note: generalized from `SemilatticeSup` to `Preorder`
theorem prod_map_atBot_eq {α₁ α₂ β₁ β₂ : Type*} [Preorder β₁] [Preorder β₂]
(u₁ : β₁ → α₁) (u₂ : β₂ → α₂) : map u₁ atBot ×ˢ map u₂ atBot = map (Prod.map u₁ u₂) atBot :=
@prod_map_atTop_eq _ _ β₁ᵒᵈ β₂ᵒᵈ _ _ _ _
#align filter.prod_map_at_bot_eq Filter.prod_map_atBot_eq
theorem Tendsto.subseq_mem {F : Filter α} {V : ℕ → Set α} (h : ∀ n, V n ∈ F) {u : ℕ → α}
(hu : Tendsto u atTop F) : ∃ φ : ℕ → ℕ, StrictMono φ ∧ ∀ n, u (φ n) ∈ V n :=
extraction_forall_of_eventually'
(fun n => tendsto_atTop'.mp hu _ (h n) : ∀ n, ∃ N, ∀ k ≥ N, u k ∈ V n)
#align filter.tendsto.subseq_mem Filter.Tendsto.subseq_mem
theorem tendsto_atBot_diagonal [SemilatticeInf α] : Tendsto (fun a : α => (a, a)) atBot atBot := by
rw [← prod_atBot_atBot_eq]
exact tendsto_id.prod_mk tendsto_id
#align filter.tendsto_at_bot_diagonal Filter.tendsto_atBot_diagonal
theorem tendsto_atTop_diagonal [SemilatticeSup α] : Tendsto (fun a : α => (a, a)) atTop atTop := by
rw [← prod_atTop_atTop_eq]
exact tendsto_id.prod_mk tendsto_id
#align filter.tendsto_at_top_diagonal Filter.tendsto_atTop_diagonal
theorem Tendsto.prod_map_prod_atBot [SemilatticeInf γ] {F : Filter α} {G : Filter β} {f : α → γ}
{g : β → γ} (hf : Tendsto f F atBot) (hg : Tendsto g G atBot) :
Tendsto (Prod.map f g) (F ×ˢ G) atBot := by
rw [← prod_atBot_atBot_eq]
exact hf.prod_map hg
#align filter.tendsto.prod_map_prod_at_bot Filter.Tendsto.prod_map_prod_atBot
theorem Tendsto.prod_map_prod_atTop [SemilatticeSup γ] {F : Filter α} {G : Filter β} {f : α → γ}
{g : β → γ} (hf : Tendsto f F atTop) (hg : Tendsto g G atTop) :
Tendsto (Prod.map f g) (F ×ˢ G) atTop := by
rw [← prod_atTop_atTop_eq]
exact hf.prod_map hg
#align filter.tendsto.prod_map_prod_at_top Filter.Tendsto.prod_map_prod_atTop
theorem Tendsto.prod_atBot [SemilatticeInf α] [SemilatticeInf γ] {f g : α → γ}
(hf : Tendsto f atBot atBot) (hg : Tendsto g atBot atBot) :
Tendsto (Prod.map f g) atBot atBot := by
rw [← prod_atBot_atBot_eq]
exact hf.prod_map_prod_atBot hg
#align filter.tendsto.prod_at_bot Filter.Tendsto.prod_atBot
theorem Tendsto.prod_atTop [SemilatticeSup α] [SemilatticeSup γ] {f g : α → γ}
(hf : Tendsto f atTop atTop) (hg : Tendsto g atTop atTop) :
Tendsto (Prod.map f g) atTop atTop := by
rw [← prod_atTop_atTop_eq]
exact hf.prod_map_prod_atTop hg
#align filter.tendsto.prod_at_top Filter.Tendsto.prod_atTop
theorem eventually_atBot_prod_self [SemilatticeInf α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atBot, p x) ↔ ∃ a, ∀ k l, k ≤ a → l ≤ a → p (k, l) := by
simp [← prod_atBot_atBot_eq, (@atBot_basis α _ _).prod_self.eventually_iff]
#align filter.eventually_at_bot_prod_self Filter.eventually_atBot_prod_self
theorem eventually_atTop_prod_self [SemilatticeSup α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atTop, p x) ↔ ∃ a, ∀ k l, a ≤ k → a ≤ l → p (k, l) :=
eventually_atBot_prod_self (α := αᵒᵈ)
#align filter.eventually_at_top_prod_self Filter.eventually_atTop_prod_self
| Mathlib/Order/Filter/AtTopBot.lean | 1,618 | 1,620 | theorem eventually_atBot_prod_self' [SemilatticeInf α] [Nonempty α] {p : α × α → Prop} :
(∀ᶠ x in atBot, p x) ↔ ∃ a, ∀ k ≤ a, ∀ l ≤ a, p (k, l) := by |
simp only [eventually_atBot_prod_self, forall_cond_comm]
|
/-
Copyright (c) 2022 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.Order.Interval.Set.Monotone
import Mathlib.Probability.Process.HittingTime
import Mathlib.Probability.Martingale.Basic
import Mathlib.Tactic.AdaptationNote
#align_import probability.martingale.upcrossing from "leanprover-community/mathlib"@"2c1d8ca2812b64f88992a5294ea3dba144755cd1"
/-!
# Doob's upcrossing estimate
Given a discrete real-valued submartingale $(f_n)_{n \in \mathbb{N}}$, denoting by $U_N(a, b)$ the
number of times $f_n$ crossed from below $a$ to above $b$ before time $N$, Doob's upcrossing
estimate (also known as Doob's inequality) states that
$$(b - a) \mathbb{E}[U_N(a, b)] \le \mathbb{E}[(f_N - a)^+].$$
Doob's upcrossing estimate is an important inequality and is central in proving the martingale
convergence theorems.
## Main definitions
* `MeasureTheory.upperCrossingTime a b f N n`: is the stopping time corresponding to `f`
crossing above `b` the `n`-th time before time `N` (if this does not occur then the value is
taken to be `N`).
* `MeasureTheory.lowerCrossingTime a b f N n`: is the stopping time corresponding to `f`
crossing below `a` the `n`-th time before time `N` (if this does not occur then the value is
taken to be `N`).
* `MeasureTheory.upcrossingStrat a b f N`: is the predictable process which is 1 if `n` is
between a consecutive pair of lower and upper crossings and is 0 otherwise. Intuitively
one might think of the `upcrossingStrat` as the strategy of buying 1 share whenever the process
crosses below `a` for the first time after selling and selling 1 share whenever the process
crosses above `b` for the first time after buying.
* `MeasureTheory.upcrossingsBefore a b f N`: is the number of times `f` crosses from below `a` to
above `b` before time `N`.
* `MeasureTheory.upcrossings a b f`: is the number of times `f` crosses from below `a` to above
`b`. This takes value in `ℝ≥0∞` and so is allowed to be `∞`.
## Main results
* `MeasureTheory.Adapted.isStoppingTime_upperCrossingTime`: `upperCrossingTime` is a
stopping time whenever the process it is associated to is adapted.
* `MeasureTheory.Adapted.isStoppingTime_lowerCrossingTime`: `lowerCrossingTime` is a
stopping time whenever the process it is associated to is adapted.
* `MeasureTheory.Submartingale.mul_integral_upcrossingsBefore_le_integral_pos_part`: Doob's
upcrossing estimate.
* `MeasureTheory.Submartingale.mul_lintegral_upcrossings_le_lintegral_pos_part`: the inequality
obtained by taking the supremum on both sides of Doob's upcrossing estimate.
### References
We mostly follow the proof from [Kallenberg, *Foundations of modern probability*][kallenberg2021]
-/
open TopologicalSpace Filter
open scoped NNReal ENNReal MeasureTheory ProbabilityTheory Topology
namespace MeasureTheory
variable {Ω ι : Type*} {m0 : MeasurableSpace Ω} {μ : Measure Ω}
/-!
## Proof outline
In this section, we will denote by $U_N(a, b)$ the number of upcrossings of $(f_n)$ from below $a$
to above $b$ before time $N$.
To define $U_N(a, b)$, we will construct two stopping times corresponding to when $(f_n)$ crosses
below $a$ and above $b$. Namely, we define
$$
\sigma_n := \inf \{n \ge \tau_n \mid f_n \le a\} \wedge N;
$$
$$
\tau_{n + 1} := \inf \{n \ge \sigma_n \mid f_n \ge b\} \wedge N.
$$
These are `lowerCrossingTime` and `upperCrossingTime` in our formalization which are defined
using `MeasureTheory.hitting` allowing us to specify a starting and ending time.
Then, we may simply define $U_N(a, b) := \sup \{n \mid \tau_n < N\}$.
Fixing $a < b \in \mathbb{R}$, we will first prove the theorem in the special case that
$0 \le f_0$ and $a \le f_N$. In particular, we will show
$$
(b - a) \mathbb{E}[U_N(a, b)] \le \mathbb{E}[f_N].
$$
This is `MeasureTheory.integral_mul_upcrossingsBefore_le_integral` in our formalization.
To prove this, we use the fact that given a non-negative, bounded, predictable process $(C_n)$
(i.e. $(C_{n + 1})$ is adapted), $(C \bullet f)_n := \sum_{k \le n} C_{k + 1}(f_{k + 1} - f_k)$ is
a submartingale if $(f_n)$ is.
Define $C_n := \sum_{k \le n} \mathbf{1}_{[\sigma_k, \tau_{k + 1})}(n)$. It is easy to see that
$(1 - C_n)$ is non-negative, bounded and predictable, and hence, given a submartingale $(f_n)$,
$(1 - C) \bullet f$ is also a submartingale. Thus, by the submartingale property,
$0 \le \mathbb{E}[((1 - C) \bullet f)_0] \le \mathbb{E}[((1 - C) \bullet f)_N]$ implying
$$
\mathbb{E}[(C \bullet f)_N] \le \mathbb{E}[(1 \bullet f)_N] = \mathbb{E}[f_N] - \mathbb{E}[f_0].
$$
Furthermore,
\begin{align}
(C \bullet f)_N & =
\sum_{n \le N} \sum_{k \le N} \mathbf{1}_{[\sigma_k, \tau_{k + 1})}(n)(f_{n + 1} - f_n)\\
& = \sum_{k \le N} \sum_{n \le N} \mathbf{1}_{[\sigma_k, \tau_{k + 1})}(n)(f_{n + 1} - f_n)\\
& = \sum_{k \le N} (f_{\sigma_k + 1} - f_{\sigma_k} + f_{\sigma_k + 2} - f_{\sigma_k + 1}
+ \cdots + f_{\tau_{k + 1}} - f_{\tau_{k + 1} - 1})\\
& = \sum_{k \le N} (f_{\tau_{k + 1}} - f_{\sigma_k})
\ge \sum_{k < U_N(a, b)} (b - a) = (b - a) U_N(a, b)
\end{align}
where the inequality follows since for all $k < U_N(a, b)$,
$f_{\tau_{k + 1}} - f_{\sigma_k} \ge b - a$ while for all $k > U_N(a, b)$,
$f_{\tau_{k + 1}} = f_{\sigma_k} = f_N$ and
$f_{\tau_{U_N(a, b) + 1}} - f_{\sigma_{U_N(a, b)}} = f_N - a \ge 0$. Hence, we have
$$
(b - a) \mathbb{E}[U_N(a, b)] \le \mathbb{E}[(C \bullet f)_N]
\le \mathbb{E}[f_N] - \mathbb{E}[f_0] \le \mathbb{E}[f_N],
$$
as required.
To obtain the general case, we simply apply the above to $((f_n - a)^+)_n$.
-/
/-- `lowerCrossingTimeAux a f c N` is the first time `f` reached below `a` after time `c` before
time `N`. -/
noncomputable def lowerCrossingTimeAux [Preorder ι] [InfSet ι] (a : ℝ) (f : ι → Ω → ℝ) (c N : ι) :
Ω → ι :=
hitting f (Set.Iic a) c N
#align measure_theory.lower_crossing_time_aux MeasureTheory.lowerCrossingTimeAux
/-- `upperCrossingTime a b f N n` is the first time before time `N`, `f` reaches
above `b` after `f` reached below `a` for the `n - 1`-th time. -/
noncomputable def upperCrossingTime [Preorder ι] [OrderBot ι] [InfSet ι] (a b : ℝ) (f : ι → Ω → ℝ)
(N : ι) : ℕ → Ω → ι
| 0 => ⊥
| n + 1 => fun ω =>
hitting f (Set.Ici b) (lowerCrossingTimeAux a f (upperCrossingTime a b f N n ω) N ω) N ω
#align measure_theory.upper_crossing_time MeasureTheory.upperCrossingTime
/-- `lowerCrossingTime a b f N n` is the first time before time `N`, `f` reaches
below `a` after `f` reached above `b` for the `n`-th time. -/
noncomputable def lowerCrossingTime [Preorder ι] [OrderBot ι] [InfSet ι] (a b : ℝ) (f : ι → Ω → ℝ)
(N : ι) (n : ℕ) : Ω → ι := fun ω => hitting f (Set.Iic a) (upperCrossingTime a b f N n ω) N ω
#align measure_theory.lower_crossing_time MeasureTheory.lowerCrossingTime
section
variable [Preorder ι] [OrderBot ι] [InfSet ι]
variable {a b : ℝ} {f : ι → Ω → ℝ} {N : ι} {n m : ℕ} {ω : Ω}
@[simp]
theorem upperCrossingTime_zero : upperCrossingTime a b f N 0 = ⊥ :=
rfl
#align measure_theory.upper_crossing_time_zero MeasureTheory.upperCrossingTime_zero
@[simp]
theorem lowerCrossingTime_zero : lowerCrossingTime a b f N 0 = hitting f (Set.Iic a) ⊥ N :=
rfl
#align measure_theory.lower_crossing_time_zero MeasureTheory.lowerCrossingTime_zero
theorem upperCrossingTime_succ : upperCrossingTime a b f N (n + 1) ω =
hitting f (Set.Ici b) (lowerCrossingTimeAux a f (upperCrossingTime a b f N n ω) N ω) N ω := by
rw [upperCrossingTime]
#align measure_theory.upper_crossing_time_succ MeasureTheory.upperCrossingTime_succ
theorem upperCrossingTime_succ_eq (ω : Ω) : upperCrossingTime a b f N (n + 1) ω =
hitting f (Set.Ici b) (lowerCrossingTime a b f N n ω) N ω := by
simp only [upperCrossingTime_succ]
rfl
#align measure_theory.upper_crossing_time_succ_eq MeasureTheory.upperCrossingTime_succ_eq
end
section ConditionallyCompleteLinearOrderBot
variable [ConditionallyCompleteLinearOrderBot ι]
variable {a b : ℝ} {f : ι → Ω → ℝ} {N : ι} {n m : ℕ} {ω : Ω}
theorem upperCrossingTime_le : upperCrossingTime a b f N n ω ≤ N := by
cases n
· simp only [upperCrossingTime_zero, Pi.bot_apply, bot_le, Nat.zero_eq]
· simp only [upperCrossingTime_succ, hitting_le]
#align measure_theory.upper_crossing_time_le MeasureTheory.upperCrossingTime_le
@[simp]
theorem upperCrossingTime_zero' : upperCrossingTime a b f ⊥ n ω = ⊥ :=
eq_bot_iff.2 upperCrossingTime_le
#align measure_theory.upper_crossing_time_zero' MeasureTheory.upperCrossingTime_zero'
theorem lowerCrossingTime_le : lowerCrossingTime a b f N n ω ≤ N := by
simp only [lowerCrossingTime, hitting_le ω]
#align measure_theory.lower_crossing_time_le MeasureTheory.lowerCrossingTime_le
theorem upperCrossingTime_le_lowerCrossingTime :
upperCrossingTime a b f N n ω ≤ lowerCrossingTime a b f N n ω := by
simp only [lowerCrossingTime, le_hitting upperCrossingTime_le ω]
#align measure_theory.upper_crossing_time_le_lower_crossing_time MeasureTheory.upperCrossingTime_le_lowerCrossingTime
theorem lowerCrossingTime_le_upperCrossingTime_succ :
lowerCrossingTime a b f N n ω ≤ upperCrossingTime a b f N (n + 1) ω := by
rw [upperCrossingTime_succ]
exact le_hitting lowerCrossingTime_le ω
#align measure_theory.lower_crossing_time_le_upper_crossing_time_succ MeasureTheory.lowerCrossingTime_le_upperCrossingTime_succ
theorem lowerCrossingTime_mono (hnm : n ≤ m) :
lowerCrossingTime a b f N n ω ≤ lowerCrossingTime a b f N m ω := by
suffices Monotone fun n => lowerCrossingTime a b f N n ω by exact this hnm
exact monotone_nat_of_le_succ fun n =>
le_trans lowerCrossingTime_le_upperCrossingTime_succ upperCrossingTime_le_lowerCrossingTime
#align measure_theory.lower_crossing_time_mono MeasureTheory.lowerCrossingTime_mono
theorem upperCrossingTime_mono (hnm : n ≤ m) :
upperCrossingTime a b f N n ω ≤ upperCrossingTime a b f N m ω := by
suffices Monotone fun n => upperCrossingTime a b f N n ω by exact this hnm
exact monotone_nat_of_le_succ fun n =>
le_trans upperCrossingTime_le_lowerCrossingTime lowerCrossingTime_le_upperCrossingTime_succ
#align measure_theory.upper_crossing_time_mono MeasureTheory.upperCrossingTime_mono
end ConditionallyCompleteLinearOrderBot
variable {a b : ℝ} {f : ℕ → Ω → ℝ} {N : ℕ} {n m : ℕ} {ω : Ω}
theorem stoppedValue_lowerCrossingTime (h : lowerCrossingTime a b f N n ω ≠ N) :
stoppedValue f (lowerCrossingTime a b f N n) ω ≤ a := by
obtain ⟨j, hj₁, hj₂⟩ := (hitting_le_iff_of_lt _ (lt_of_le_of_ne lowerCrossingTime_le h)).1 le_rfl
exact stoppedValue_hitting_mem ⟨j, ⟨hj₁.1, le_trans hj₁.2 lowerCrossingTime_le⟩, hj₂⟩
#align measure_theory.stopped_value_lower_crossing_time MeasureTheory.stoppedValue_lowerCrossingTime
theorem stoppedValue_upperCrossingTime (h : upperCrossingTime a b f N (n + 1) ω ≠ N) :
b ≤ stoppedValue f (upperCrossingTime a b f N (n + 1)) ω := by
obtain ⟨j, hj₁, hj₂⟩ := (hitting_le_iff_of_lt _ (lt_of_le_of_ne upperCrossingTime_le h)).1 le_rfl
exact stoppedValue_hitting_mem ⟨j, ⟨hj₁.1, le_trans hj₁.2 (hitting_le _)⟩, hj₂⟩
#align measure_theory.stopped_value_upper_crossing_time MeasureTheory.stoppedValue_upperCrossingTime
theorem upperCrossingTime_lt_lowerCrossingTime (hab : a < b)
(hn : lowerCrossingTime a b f N (n + 1) ω ≠ N) :
upperCrossingTime a b f N (n + 1) ω < lowerCrossingTime a b f N (n + 1) ω := by
refine lt_of_le_of_ne upperCrossingTime_le_lowerCrossingTime fun h =>
not_le.2 hab <| le_trans ?_ (stoppedValue_lowerCrossingTime hn)
simp only [stoppedValue]
rw [← h]
exact stoppedValue_upperCrossingTime (h.symm ▸ hn)
#align measure_theory.upper_crossing_time_lt_lower_crossing_time MeasureTheory.upperCrossingTime_lt_lowerCrossingTime
theorem lowerCrossingTime_lt_upperCrossingTime (hab : a < b)
(hn : upperCrossingTime a b f N (n + 1) ω ≠ N) :
lowerCrossingTime a b f N n ω < upperCrossingTime a b f N (n + 1) ω := by
refine lt_of_le_of_ne lowerCrossingTime_le_upperCrossingTime_succ fun h =>
not_le.2 hab <| le_trans (stoppedValue_upperCrossingTime hn) ?_
simp only [stoppedValue]
rw [← h]
exact stoppedValue_lowerCrossingTime (h.symm ▸ hn)
#align measure_theory.lower_crossing_time_lt_upper_crossing_time MeasureTheory.lowerCrossingTime_lt_upperCrossingTime
theorem upperCrossingTime_lt_succ (hab : a < b) (hn : upperCrossingTime a b f N (n + 1) ω ≠ N) :
upperCrossingTime a b f N n ω < upperCrossingTime a b f N (n + 1) ω :=
lt_of_le_of_lt upperCrossingTime_le_lowerCrossingTime
(lowerCrossingTime_lt_upperCrossingTime hab hn)
#align measure_theory.upper_crossing_time_lt_succ MeasureTheory.upperCrossingTime_lt_succ
theorem lowerCrossingTime_stabilize (hnm : n ≤ m) (hn : lowerCrossingTime a b f N n ω = N) :
lowerCrossingTime a b f N m ω = N :=
le_antisymm lowerCrossingTime_le (le_trans (le_of_eq hn.symm) (lowerCrossingTime_mono hnm))
#align measure_theory.lower_crossing_time_stabilize MeasureTheory.lowerCrossingTime_stabilize
theorem upperCrossingTime_stabilize (hnm : n ≤ m) (hn : upperCrossingTime a b f N n ω = N) :
upperCrossingTime a b f N m ω = N :=
le_antisymm upperCrossingTime_le (le_trans (le_of_eq hn.symm) (upperCrossingTime_mono hnm))
#align measure_theory.upper_crossing_time_stabilize MeasureTheory.upperCrossingTime_stabilize
theorem lowerCrossingTime_stabilize' (hnm : n ≤ m) (hn : N ≤ lowerCrossingTime a b f N n ω) :
lowerCrossingTime a b f N m ω = N :=
lowerCrossingTime_stabilize hnm (le_antisymm lowerCrossingTime_le hn)
#align measure_theory.lower_crossing_time_stabilize' MeasureTheory.lowerCrossingTime_stabilize'
theorem upperCrossingTime_stabilize' (hnm : n ≤ m) (hn : N ≤ upperCrossingTime a b f N n ω) :
upperCrossingTime a b f N m ω = N :=
upperCrossingTime_stabilize hnm (le_antisymm upperCrossingTime_le hn)
#align measure_theory.upper_crossing_time_stabilize' MeasureTheory.upperCrossingTime_stabilize'
-- `upperCrossingTime_bound_eq` provides an explicit bound
theorem exists_upperCrossingTime_eq (f : ℕ → Ω → ℝ) (N : ℕ) (ω : Ω) (hab : a < b) :
∃ n, upperCrossingTime a b f N n ω = N := by
by_contra h; push_neg at h
have : StrictMono fun n => upperCrossingTime a b f N n ω :=
strictMono_nat_of_lt_succ fun n => upperCrossingTime_lt_succ hab (h _)
obtain ⟨_, ⟨k, rfl⟩, hk⟩ :
∃ (m : _) (_ : m ∈ Set.range fun n => upperCrossingTime a b f N n ω), N < m :=
⟨upperCrossingTime a b f N (N + 1) ω, ⟨N + 1, rfl⟩,
lt_of_lt_of_le N.lt_succ_self (StrictMono.id_le this (N + 1))⟩
exact not_le.2 hk upperCrossingTime_le
#align measure_theory.exists_upper_crossing_time_eq MeasureTheory.exists_upperCrossingTime_eq
theorem upperCrossingTime_lt_bddAbove (hab : a < b) :
BddAbove {n | upperCrossingTime a b f N n ω < N} := by
obtain ⟨k, hk⟩ := exists_upperCrossingTime_eq f N ω hab
refine ⟨k, fun n (hn : upperCrossingTime a b f N n ω < N) => ?_⟩
by_contra hn'
exact hn.ne (upperCrossingTime_stabilize (not_le.1 hn').le hk)
#align measure_theory.upper_crossing_time_lt_bdd_above MeasureTheory.upperCrossingTime_lt_bddAbove
theorem upperCrossingTime_lt_nonempty (hN : 0 < N) :
{n | upperCrossingTime a b f N n ω < N}.Nonempty :=
⟨0, hN⟩
#align measure_theory.upper_crossing_time_lt_nonempty MeasureTheory.upperCrossingTime_lt_nonempty
theorem upperCrossingTime_bound_eq (f : ℕ → Ω → ℝ) (N : ℕ) (ω : Ω) (hab : a < b) :
upperCrossingTime a b f N N ω = N := by
by_cases hN' : N < Nat.find (exists_upperCrossingTime_eq f N ω hab)
· refine le_antisymm upperCrossingTime_le ?_
have hmono : StrictMonoOn (fun n => upperCrossingTime a b f N n ω)
(Set.Iic (Nat.find (exists_upperCrossingTime_eq f N ω hab)).pred) := by
refine strictMonoOn_Iic_of_lt_succ fun m hm => upperCrossingTime_lt_succ hab ?_
rw [Nat.lt_pred_iff] at hm
convert Nat.find_min _ hm
convert StrictMonoOn.Iic_id_le hmono N (Nat.le_sub_one_of_lt hN')
· rw [not_lt] at hN'
exact upperCrossingTime_stabilize hN' (Nat.find_spec (exists_upperCrossingTime_eq f N ω hab))
#align measure_theory.upper_crossing_time_bound_eq MeasureTheory.upperCrossingTime_bound_eq
theorem upperCrossingTime_eq_of_bound_le (hab : a < b) (hn : N ≤ n) :
upperCrossingTime a b f N n ω = N :=
le_antisymm upperCrossingTime_le
(le_trans (upperCrossingTime_bound_eq f N ω hab).symm.le (upperCrossingTime_mono hn))
#align measure_theory.upper_crossing_time_eq_of_bound_le MeasureTheory.upperCrossingTime_eq_of_bound_le
variable {ℱ : Filtration ℕ m0}
theorem Adapted.isStoppingTime_crossing (hf : Adapted ℱ f) :
IsStoppingTime ℱ (upperCrossingTime a b f N n) ∧
IsStoppingTime ℱ (lowerCrossingTime a b f N n) := by
induction' n with k ih
· refine ⟨isStoppingTime_const _ 0, ?_⟩
simp [hitting_isStoppingTime hf measurableSet_Iic]
· obtain ⟨_, ih₂⟩ := ih
have : IsStoppingTime ℱ (upperCrossingTime a b f N (k + 1)) := by
intro n
simp_rw [upperCrossingTime_succ_eq]
exact isStoppingTime_hitting_isStoppingTime ih₂ (fun _ => lowerCrossingTime_le)
measurableSet_Ici hf _
refine ⟨this, ?_⟩
intro n
exact isStoppingTime_hitting_isStoppingTime this (fun _ => upperCrossingTime_le)
measurableSet_Iic hf _
#align measure_theory.adapted.is_stopping_time_crossing MeasureTheory.Adapted.isStoppingTime_crossing
theorem Adapted.isStoppingTime_upperCrossingTime (hf : Adapted ℱ f) :
IsStoppingTime ℱ (upperCrossingTime a b f N n) :=
hf.isStoppingTime_crossing.1
#align measure_theory.adapted.is_stopping_time_upper_crossing_time MeasureTheory.Adapted.isStoppingTime_upperCrossingTime
theorem Adapted.isStoppingTime_lowerCrossingTime (hf : Adapted ℱ f) :
IsStoppingTime ℱ (lowerCrossingTime a b f N n) :=
hf.isStoppingTime_crossing.2
#align measure_theory.adapted.is_stopping_time_lower_crossing_time MeasureTheory.Adapted.isStoppingTime_lowerCrossingTime
/-- `upcrossingStrat a b f N n` is 1 if `n` is between a consecutive pair of lower and upper
crossings and is 0 otherwise. `upcrossingStrat` is shifted by one index so that it is adapted
rather than predictable. -/
noncomputable def upcrossingStrat (a b : ℝ) (f : ℕ → Ω → ℝ) (N n : ℕ) (ω : Ω) : ℝ :=
∑ k ∈ Finset.range N,
(Set.Ico (lowerCrossingTime a b f N k ω) (upperCrossingTime a b f N (k + 1) ω)).indicator 1 n
#align measure_theory.upcrossing_strat MeasureTheory.upcrossingStrat
theorem upcrossingStrat_nonneg : 0 ≤ upcrossingStrat a b f N n ω :=
Finset.sum_nonneg fun _ _ => Set.indicator_nonneg (fun _ _ => zero_le_one) _
#align measure_theory.upcrossing_strat_nonneg MeasureTheory.upcrossingStrat_nonneg
theorem upcrossingStrat_le_one : upcrossingStrat a b f N n ω ≤ 1 := by
rw [upcrossingStrat, ← Finset.indicator_biUnion_apply]
· exact Set.indicator_le_self' (fun _ _ => zero_le_one) _
intro i _ j _ hij
simp only [Set.Ico_disjoint_Ico]
obtain hij' | hij' := lt_or_gt_of_ne hij
· rw [min_eq_left (upperCrossingTime_mono (Nat.succ_le_succ hij'.le) :
upperCrossingTime a b f N _ ω ≤ upperCrossingTime a b f N _ ω),
max_eq_right (lowerCrossingTime_mono hij'.le :
lowerCrossingTime a b f N _ _ ≤ lowerCrossingTime _ _ _ _ _ _)]
refine le_trans upperCrossingTime_le_lowerCrossingTime
(lowerCrossingTime_mono (Nat.succ_le_of_lt hij'))
· rw [gt_iff_lt] at hij'
rw [min_eq_right (upperCrossingTime_mono (Nat.succ_le_succ hij'.le) :
upperCrossingTime a b f N _ ω ≤ upperCrossingTime a b f N _ ω),
max_eq_left (lowerCrossingTime_mono hij'.le :
lowerCrossingTime a b f N _ _ ≤ lowerCrossingTime _ _ _ _ _ _)]
refine le_trans upperCrossingTime_le_lowerCrossingTime
(lowerCrossingTime_mono (Nat.succ_le_of_lt hij'))
#align measure_theory.upcrossing_strat_le_one MeasureTheory.upcrossingStrat_le_one
theorem Adapted.upcrossingStrat_adapted (hf : Adapted ℱ f) :
Adapted ℱ (upcrossingStrat a b f N) := by
intro n
change StronglyMeasurable[ℱ n] fun ω =>
∑ k ∈ Finset.range N, ({n | lowerCrossingTime a b f N k ω ≤ n} ∩
{n | n < upperCrossingTime a b f N (k + 1) ω}).indicator 1 n
refine Finset.stronglyMeasurable_sum _ fun i _ =>
stronglyMeasurable_const.indicator ((hf.isStoppingTime_lowerCrossingTime n).inter ?_)
simp_rw [← not_le]
exact (hf.isStoppingTime_upperCrossingTime n).compl
#align measure_theory.adapted.upcrossing_strat_adapted MeasureTheory.Adapted.upcrossingStrat_adapted
theorem Submartingale.sum_upcrossingStrat_mul [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ)
(a b : ℝ) (N : ℕ) : Submartingale (fun n : ℕ =>
∑ k ∈ Finset.range n, upcrossingStrat a b f N k * (f (k + 1) - f k)) ℱ μ :=
hf.sum_mul_sub hf.adapted.upcrossingStrat_adapted (fun _ _ => upcrossingStrat_le_one) fun _ _ =>
upcrossingStrat_nonneg
#align measure_theory.submartingale.sum_upcrossing_strat_mul MeasureTheory.Submartingale.sum_upcrossingStrat_mul
theorem Submartingale.sum_sub_upcrossingStrat_mul [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ)
(a b : ℝ) (N : ℕ) : Submartingale (fun n : ℕ =>
∑ k ∈ Finset.range n, (1 - upcrossingStrat a b f N k) * (f (k + 1) - f k)) ℱ μ := by
refine hf.sum_mul_sub (fun n => (adapted_const ℱ 1 n).sub (hf.adapted.upcrossingStrat_adapted n))
(?_ : ∀ n ω, (1 - upcrossingStrat a b f N n) ω ≤ 1) ?_
· exact fun n ω => sub_le_self _ upcrossingStrat_nonneg
· intro n ω
simp [upcrossingStrat_le_one]
#align measure_theory.submartingale.sum_sub_upcrossing_strat_mul MeasureTheory.Submartingale.sum_sub_upcrossingStrat_mul
theorem Submartingale.sum_mul_upcrossingStrat_le [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ) :
μ[∑ k ∈ Finset.range n, upcrossingStrat a b f N k * (f (k + 1) - f k)] ≤ μ[f n] - μ[f 0] := by
have h₁ : (0 : ℝ) ≤
μ[∑ k ∈ Finset.range n, (1 - upcrossingStrat a b f N k) * (f (k + 1) - f k)] := by
have := (hf.sum_sub_upcrossingStrat_mul a b N).setIntegral_le (zero_le n) MeasurableSet.univ
rw [integral_univ, integral_univ] at this
refine le_trans ?_ this
simp only [Finset.range_zero, Finset.sum_empty, integral_zero', le_refl]
have h₂ : μ[∑ k ∈ Finset.range n, (1 - upcrossingStrat a b f N k) * (f (k + 1) - f k)] =
μ[∑ k ∈ Finset.range n, (f (k + 1) - f k)] -
μ[∑ k ∈ Finset.range n, upcrossingStrat a b f N k * (f (k + 1) - f k)] := by
simp only [sub_mul, one_mul, Finset.sum_sub_distrib, Pi.sub_apply, Finset.sum_apply,
Pi.mul_apply]
refine integral_sub (Integrable.sub (integrable_finset_sum _ fun i _ => hf.integrable _)
(integrable_finset_sum _ fun i _ => hf.integrable _)) ?_
convert (hf.sum_upcrossingStrat_mul a b N).integrable n using 1
ext; simp
rw [h₂, sub_nonneg] at h₁
refine le_trans h₁ ?_
simp_rw [Finset.sum_range_sub, integral_sub' (hf.integrable _) (hf.integrable _), le_refl]
#align measure_theory.submartingale.sum_mul_upcrossing_strat_le MeasureTheory.Submartingale.sum_mul_upcrossingStrat_le
/-- The number of upcrossings (strictly) before time `N`. -/
noncomputable def upcrossingsBefore [Preorder ι] [OrderBot ι] [InfSet ι] (a b : ℝ) (f : ι → Ω → ℝ)
(N : ι) (ω : Ω) : ℕ :=
sSup {n | upperCrossingTime a b f N n ω < N}
#align measure_theory.upcrossings_before MeasureTheory.upcrossingsBefore
@[simp]
theorem upcrossingsBefore_bot [Preorder ι] [OrderBot ι] [InfSet ι] {a b : ℝ} {f : ι → Ω → ℝ}
{ω : Ω} : upcrossingsBefore a b f ⊥ ω = ⊥ := by simp [upcrossingsBefore]
#align measure_theory.upcrossings_before_bot MeasureTheory.upcrossingsBefore_bot
theorem upcrossingsBefore_zero : upcrossingsBefore a b f 0 ω = 0 := by simp [upcrossingsBefore]
#align measure_theory.upcrossings_before_zero MeasureTheory.upcrossingsBefore_zero
@[simp]
theorem upcrossingsBefore_zero' : upcrossingsBefore a b f 0 = 0 := by
ext ω; exact upcrossingsBefore_zero
#align measure_theory.upcrossings_before_zero' MeasureTheory.upcrossingsBefore_zero'
theorem upperCrossingTime_lt_of_le_upcrossingsBefore (hN : 0 < N) (hab : a < b)
(hn : n ≤ upcrossingsBefore a b f N ω) : upperCrossingTime a b f N n ω < N :=
haveI : upperCrossingTime a b f N (upcrossingsBefore a b f N ω) ω < N :=
(upperCrossingTime_lt_nonempty hN).csSup_mem
((OrderBot.bddBelow _).finite_of_bddAbove (upperCrossingTime_lt_bddAbove hab))
lt_of_le_of_lt (upperCrossingTime_mono hn) this
#align measure_theory.upper_crossing_time_lt_of_le_upcrossings_before MeasureTheory.upperCrossingTime_lt_of_le_upcrossingsBefore
theorem upperCrossingTime_eq_of_upcrossingsBefore_lt (hab : a < b)
(hn : upcrossingsBefore a b f N ω < n) : upperCrossingTime a b f N n ω = N := by
refine le_antisymm upperCrossingTime_le (not_lt.1 ?_)
convert not_mem_of_csSup_lt hn (upperCrossingTime_lt_bddAbove hab)
#align measure_theory.upper_crossing_time_eq_of_upcrossings_before_lt MeasureTheory.upperCrossingTime_eq_of_upcrossingsBefore_lt
theorem upcrossingsBefore_le (f : ℕ → Ω → ℝ) (ω : Ω) (hab : a < b) :
upcrossingsBefore a b f N ω ≤ N := by
by_cases hN : N = 0
· subst hN
rw [upcrossingsBefore_zero]
· refine csSup_le ⟨0, zero_lt_iff.2 hN⟩ fun n (hn : _ < N) => ?_
by_contra hnN
exact hn.ne (upperCrossingTime_eq_of_bound_le hab (not_le.1 hnN).le)
#align measure_theory.upcrossings_before_le MeasureTheory.upcrossingsBefore_le
theorem crossing_eq_crossing_of_lowerCrossingTime_lt {M : ℕ} (hNM : N ≤ M)
(h : lowerCrossingTime a b f N n ω < N) :
upperCrossingTime a b f M n ω = upperCrossingTime a b f N n ω ∧
lowerCrossingTime a b f M n ω = lowerCrossingTime a b f N n ω := by
have h' : upperCrossingTime a b f N n ω < N :=
lt_of_le_of_lt upperCrossingTime_le_lowerCrossingTime h
induction' n with k ih
· simp only [Nat.zero_eq, upperCrossingTime_zero, bot_eq_zero', eq_self_iff_true,
lowerCrossingTime_zero, true_and_iff, eq_comm]
refine hitting_eq_hitting_of_exists hNM ?_
rw [lowerCrossingTime, hitting_lt_iff] at h
· obtain ⟨j, hj₁, hj₂⟩ := h
exact ⟨j, ⟨hj₁.1, hj₁.2.le⟩, hj₂⟩
· exact le_rfl
· specialize ih (lt_of_le_of_lt (lowerCrossingTime_mono (Nat.le_succ _)) h)
(lt_of_le_of_lt (upperCrossingTime_mono (Nat.le_succ _)) h')
have : upperCrossingTime a b f M k.succ ω = upperCrossingTime a b f N k.succ ω := by
rw [upperCrossingTime_succ_eq, hitting_lt_iff] at h'
· simp only [upperCrossingTime_succ_eq]
obtain ⟨j, hj₁, hj₂⟩ := h'
rw [eq_comm, ih.2]
exact hitting_eq_hitting_of_exists hNM ⟨j, ⟨hj₁.1, hj₁.2.le⟩, hj₂⟩
· exact le_rfl
refine ⟨this, ?_⟩
simp only [lowerCrossingTime, eq_comm, this, Nat.succ_eq_add_one]
refine hitting_eq_hitting_of_exists hNM ?_
rw [lowerCrossingTime, hitting_lt_iff _ le_rfl] at h
obtain ⟨j, hj₁, hj₂⟩ := h
exact ⟨j, ⟨hj₁.1, hj₁.2.le⟩, hj₂⟩
#align measure_theory.crossing_eq_crossing_of_lower_crossing_time_lt MeasureTheory.crossing_eq_crossing_of_lowerCrossingTime_lt
| Mathlib/Probability/Martingale/Upcrossing.lean | 522 | 534 | theorem crossing_eq_crossing_of_upperCrossingTime_lt {M : ℕ} (hNM : N ≤ M)
(h : upperCrossingTime a b f N (n + 1) ω < N) :
upperCrossingTime a b f M (n + 1) ω = upperCrossingTime a b f N (n + 1) ω ∧
lowerCrossingTime a b f M n ω = lowerCrossingTime a b f N n ω := by |
have := (crossing_eq_crossing_of_lowerCrossingTime_lt hNM
(lt_of_le_of_lt lowerCrossingTime_le_upperCrossingTime_succ h)).2
refine ⟨?_, this⟩
rw [upperCrossingTime_succ_eq, upperCrossingTime_succ_eq, eq_comm, this]
refine hitting_eq_hitting_of_exists hNM ?_
rw [upperCrossingTime_succ_eq, hitting_lt_iff] at h
· obtain ⟨j, hj₁, hj₂⟩ := h
exact ⟨j, ⟨hj₁.1, hj₁.2.le⟩, hj₂⟩
· exact le_rfl
|
/-
Copyright (c) 2021 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.Geometry.RingedSpace.OpenImmersion
import Mathlib.AlgebraicGeometry.Scheme
import Mathlib.CategoryTheory.Limits.Shapes.CommSq
#align_import algebraic_geometry.open_immersion.Scheme from "leanprover-community/mathlib"@"533f62f4dd62a5aad24a04326e6e787c8f7e98b1"
/-!
# Open immersions of schemes
-/
-- Explicit universe annotations were used in this file to improve perfomance #12737
set_option linter.uppercaseLean3 false
noncomputable section
open TopologicalSpace CategoryTheory Opposite
open CategoryTheory.Limits
namespace AlgebraicGeometry
universe v v₁ v₂ u
variable {C : Type u} [Category.{v} C]
/-- A morphism of Schemes is an open immersion if it is an open immersion as a morphism
of LocallyRingedSpaces
-/
abbrev IsOpenImmersion {X Y : Scheme.{u}} (f : X ⟶ Y) : Prop :=
LocallyRingedSpace.IsOpenImmersion f
#align algebraic_geometry.IsOpenImmersion AlgebraicGeometry.IsOpenImmersion
instance IsOpenImmersion.comp {X Y Z : Scheme.{u}} (f : X ⟶ Y) (g : Y ⟶ Z)
[IsOpenImmersion f] [IsOpenImmersion g] : IsOpenImmersion (f ≫ g) :=
LocallyRingedSpace.IsOpenImmersion.comp f g
namespace LocallyRingedSpace.IsOpenImmersion
/-- To show that a locally ringed space is a scheme, it suffices to show that it has a jointly
surjective family of open immersions from affine schemes. -/
protected def scheme (X : LocallyRingedSpace.{u})
(h :
∀ x : X,
∃ (R : CommRingCat) (f : Spec.toLocallyRingedSpace.obj (op R) ⟶ X),
(x ∈ Set.range f.1.base : _) ∧ LocallyRingedSpace.IsOpenImmersion f) :
Scheme where
toLocallyRingedSpace := X
local_affine := by
intro x
obtain ⟨R, f, h₁, h₂⟩ := h x
refine ⟨⟨⟨_, h₂.base_open.isOpen_range⟩, h₁⟩, R, ⟨?_⟩⟩
apply LocallyRingedSpace.isoOfSheafedSpaceIso
refine SheafedSpace.forgetToPresheafedSpace.preimageIso ?_
apply PresheafedSpace.IsOpenImmersion.isoOfRangeEq (PresheafedSpace.ofRestrict _ _) f.1
· exact Subtype.range_coe_subtype
· exact Opens.openEmbedding _ -- Porting note (#11187): was `infer_instance`
#align algebraic_geometry.LocallyRingedSpace.IsOpenImmersion.Scheme AlgebraicGeometry.LocallyRingedSpace.IsOpenImmersion.scheme
end LocallyRingedSpace.IsOpenImmersion
theorem IsOpenImmersion.isOpen_range {X Y : Scheme.{u}} (f : X ⟶ Y) [H : IsOpenImmersion f] :
IsOpen (Set.range f.1.base) :=
H.base_open.isOpen_range
#align algebraic_geometry.IsOpenImmersion.open_range AlgebraicGeometry.IsOpenImmersion.isOpen_range
@[deprecated (since := "2024-03-17")]
alias IsOpenImmersion.open_range := IsOpenImmersion.isOpen_range
section OpenCover
namespace Scheme
-- TODO: provide API to and from a presieve.
/-- An open cover of `X` consists of a family of open immersions into `X`,
and for each `x : X` an open immersion (indexed by `f x`) that covers `x`.
This is merely a coverage in the Zariski pretopology, and it would be optimal
if we could reuse the existing API about pretopologies, However, the definitions of sieves and
grothendieck topologies uses `Prop`s, so that the actual open sets and immersions are hard to
obtain. Also, since such a coverage in the pretopology usually contains a proper class of
immersions, it is quite hard to glue them, reason about finite covers, etc.
-/
structure OpenCover (X : Scheme.{u}) where
/-- index set of an open cover of a scheme `X` -/
J : Type v
/-- the subschemes of an open cover -/
obj : J → Scheme
/-- the embedding of subschemes to `X` -/
map : ∀ j : J, obj j ⟶ X
/-- given a point of `x : X`, `f x` is the index of the subscheme which contains `x` -/
f : X.carrier → J
/-- the subschemes covers `X` -/
Covers : ∀ x, x ∈ Set.range (map (f x)).1.base
/-- the embedding of subschemes are open immersions -/
IsOpen : ∀ x, IsOpenImmersion (map x) := by infer_instance
#align algebraic_geometry.Scheme.open_cover AlgebraicGeometry.Scheme.OpenCover
attribute [instance] OpenCover.IsOpen
variable {X Y Z : Scheme.{u}} (𝒰 : OpenCover X) (f : X ⟶ Z) (g : Y ⟶ Z)
variable [∀ x, HasPullback (𝒰.map x ≫ f) g]
/-- The affine cover of a scheme. -/
def affineCover (X : Scheme.{u}) : OpenCover X where
J := X.carrier
obj x := Spec.obj <| Opposite.op (X.local_affine x).choose_spec.choose
map x :=
((X.local_affine x).choose_spec.choose_spec.some.inv ≫ X.toLocallyRingedSpace.ofRestrict _ : _)
f x := x
IsOpen x := by
apply (config := { allowSynthFailures := true }) PresheafedSpace.IsOpenImmersion.comp
apply PresheafedSpace.IsOpenImmersion.ofRestrict
Covers := by
intro x
erw [TopCat.coe_comp] -- now `erw` after #13170
rw [Set.range_comp, Set.range_iff_surjective.mpr, Set.image_univ]
· erw [Subtype.range_coe_subtype]
exact (X.local_affine x).choose.2
erw [← TopCat.epi_iff_surjective] -- now `erw` after #13170
change Epi ((SheafedSpace.forget _).map (LocallyRingedSpace.forgetToSheafedSpace.map _))
infer_instance
#align algebraic_geometry.Scheme.affine_cover AlgebraicGeometry.Scheme.affineCover
instance : Inhabited X.OpenCover :=
⟨X.affineCover⟩
/-- Given an open cover `{ Uᵢ }` of `X`, and for each `Uᵢ` an open cover, we may combine these
open covers to form an open cover of `X`. -/
@[simps! J obj map]
def OpenCover.bind (f : ∀ x : 𝒰.J, OpenCover (𝒰.obj x)) : OpenCover X where
J := Σ i : 𝒰.J, (f i).J
obj x := (f x.1).obj x.2
map x := (f x.1).map x.2 ≫ 𝒰.map x.1
f x := ⟨_, (f _).f (𝒰.Covers x).choose⟩
Covers x := by
let y := (𝒰.Covers x).choose
have hy : (𝒰.map (𝒰.f x)).val.base y = x := (𝒰.Covers x).choose_spec
rcases (f (𝒰.f x)).Covers y with ⟨z, hz⟩
change x ∈ Set.range ((f (𝒰.f x)).map ((f (𝒰.f x)).f y) ≫ 𝒰.map (𝒰.f x)).1.base
use z
erw [comp_apply]
erw [hz, hy] -- now `erw` after #13170
-- Porting note: weirdly, even though no input is needed, `inferInstance` does not work
-- `PresheafedSpace.IsOpenImmersion.comp` is marked as `instance`
IsOpen x := PresheafedSpace.IsOpenImmersion.comp _ _
#align algebraic_geometry.Scheme.open_cover.bind AlgebraicGeometry.Scheme.OpenCover.bind
/-- An isomorphism `X ⟶ Y` is an open cover of `Y`. -/
@[simps J obj map]
def openCoverOfIsIso {X Y : Scheme.{u}} (f : X ⟶ Y) [IsIso f] : OpenCover Y where
J := PUnit.{v + 1}
obj _ := X
map _ := f
f _ := PUnit.unit
Covers x := by
rw [Set.range_iff_surjective.mpr]
all_goals try trivial
rw [← TopCat.epi_iff_surjective]
infer_instance
#align algebraic_geometry.Scheme.open_cover_of_is_iso AlgebraicGeometry.Scheme.openCoverOfIsIso
/-- We construct an open cover from another, by providing the needed fields and showing that the
provided fields are isomorphic with the original open cover. -/
@[simps J obj map]
def OpenCover.copy {X : Scheme.{u}} (𝒰 : OpenCover X) (J : Type*) (obj : J → Scheme)
(map : ∀ i, obj i ⟶ X) (e₁ : J ≃ 𝒰.J) (e₂ : ∀ i, obj i ≅ 𝒰.obj (e₁ i))
(e₂ : ∀ i, map i = (e₂ i).hom ≫ 𝒰.map (e₁ i)) : OpenCover X :=
{ J, obj, map
f := fun x => e₁.symm (𝒰.f x)
Covers := fun x => by
rw [e₂, Scheme.comp_val_base, TopCat.coe_comp, Set.range_comp, Set.range_iff_surjective.mpr,
Set.image_univ, e₁.rightInverse_symm]
· exact 𝒰.Covers x
· erw [← TopCat.epi_iff_surjective]; infer_instance -- now `erw` after #13170
-- Porting note: weirdly, even though no input is needed, `inferInstance` does not work
-- `PresheafedSpace.IsOpenImmersion.comp` is marked as `instance`
IsOpen := fun i => by rw [e₂]; exact PresheafedSpace.IsOpenImmersion.comp _ _ }
#align algebraic_geometry.Scheme.open_cover.copy AlgebraicGeometry.Scheme.OpenCover.copy
-- Porting note: need more hint on universe level
/-- The pushforward of an open cover along an isomorphism. -/
@[simps! J obj map]
def OpenCover.pushforwardIso {X Y : Scheme.{u}} (𝒰 : OpenCover.{v} X) (f : X ⟶ Y) [IsIso f] :
OpenCover.{v} Y :=
((openCoverOfIsIso.{v, u} f).bind fun _ => 𝒰).copy 𝒰.J _ _
((Equiv.punitProd _).symm.trans (Equiv.sigmaEquivProd PUnit 𝒰.J).symm) (fun _ => Iso.refl _)
fun _ => (Category.id_comp _).symm
#align algebraic_geometry.Scheme.open_cover.pushforward_iso AlgebraicGeometry.Scheme.OpenCover.pushforwardIso
/-- Adding an open immersion into an open cover gives another open cover. -/
@[simps]
def OpenCover.add {X Y : Scheme.{u}} (𝒰 : X.OpenCover) (f : Y ⟶ X) [IsOpenImmersion f] :
X.OpenCover where
J := Option 𝒰.J
obj i := Option.rec Y 𝒰.obj i
map i := Option.rec f 𝒰.map i
f x := some (𝒰.f x)
Covers := 𝒰.Covers
IsOpen := by rintro (_ | _) <;> dsimp <;> infer_instance
#align algebraic_geometry.Scheme.open_cover.add AlgebraicGeometry.Scheme.OpenCover.add
-- Related result : `open_cover.pullback_cover`, where we pullback an open cover on `X` along a
-- morphism `W ⟶ X`. This is provided at the end of the file since it needs some more results
-- about open immersion (which in turn needs the open cover API).
-- attribute [local reducible] CommRingCat.of CommRingCat.ofHom
instance val_base_isIso {X Y : Scheme.{u}} (f : X ⟶ Y) [IsIso f] : IsIso f.1.base :=
Scheme.forgetToTop.map_isIso f
#align algebraic_geometry.Scheme.val_base_is_iso AlgebraicGeometry.Scheme.val_base_isIso
instance basic_open_isOpenImmersion {R : CommRingCat.{u}} (f : R) :
AlgebraicGeometry.IsOpenImmersion
(Scheme.Spec.map (CommRingCat.ofHom (algebraMap R (Localization.Away f))).op) := by
apply SheafedSpace.IsOpenImmersion.of_stalk_iso (H := ?_)
· exact (PrimeSpectrum.localization_away_openEmbedding (Localization.Away f) f : _)
· intro x
exact Spec_map_localization_isIso R (Submonoid.powers f) x
#align algebraic_geometry.Scheme.basic_open_IsOpenImmersion AlgebraicGeometry.Scheme.basic_open_isOpenImmersion
/-- The basic open sets form an affine open cover of `Spec R`. -/
def affineBasisCoverOfAffine (R : CommRingCat.{u}) : OpenCover (Spec.obj (Opposite.op R)) where
J := R
obj r := Spec.obj (Opposite.op <| CommRingCat.of <| Localization.Away r)
map r := Spec.map (Quiver.Hom.op (algebraMap R (Localization.Away r) : _))
f _ := 1
Covers r := by
rw [Set.range_iff_surjective.mpr ((TopCat.epi_iff_surjective _).mp _)]
· exact trivial
· -- Porting note: need more hand holding here because Lean knows that
-- `CommRing.ofHom ...` is iso, but without `ofHom` Lean does not know what to do
change Epi (Spec.map (CommRingCat.ofHom (algebraMap _ _)).op).1.base
infer_instance
IsOpen x := AlgebraicGeometry.Scheme.basic_open_isOpenImmersion x
#align algebraic_geometry.Scheme.affine_basis_cover_of_affine AlgebraicGeometry.Scheme.affineBasisCoverOfAffine
/-- We may bind the basic open sets of an open affine cover to form an affine cover that is also
a basis. -/
def affineBasisCover (X : Scheme.{u}) : OpenCover X :=
X.affineCover.bind fun _ => affineBasisCoverOfAffine _
#align algebraic_geometry.Scheme.affine_basis_cover AlgebraicGeometry.Scheme.affineBasisCover
/-- The coordinate ring of a component in the `affine_basis_cover`. -/
def affineBasisCoverRing (X : Scheme.{u}) (i : X.affineBasisCover.J) : CommRingCat :=
CommRingCat.of <| @Localization.Away (X.local_affine i.1).choose_spec.choose _ i.2
#align algebraic_geometry.Scheme.affine_basis_cover_ring AlgebraicGeometry.Scheme.affineBasisCoverRing
theorem affineBasisCover_obj (X : Scheme.{u}) (i : X.affineBasisCover.J) :
X.affineBasisCover.obj i = Spec.obj (op <| X.affineBasisCoverRing i) :=
rfl
#align algebraic_geometry.Scheme.affine_basis_cover_obj AlgebraicGeometry.Scheme.affineBasisCover_obj
theorem affineBasisCover_map_range (X : Scheme.{u}) (x : X)
(r : (X.local_affine x).choose_spec.choose) :
Set.range (X.affineBasisCover.map ⟨x, r⟩).1.base =
(X.affineCover.map x).1.base '' (PrimeSpectrum.basicOpen r).1 := by
erw [coe_comp, Set.range_comp]
-- Porting note: `congr` fails to see the goal is comparing image of the same function
refine congr_arg (_ '' ·) ?_
exact (PrimeSpectrum.localization_away_comap_range (Localization.Away r) r : _)
#align algebraic_geometry.Scheme.affine_basis_cover_map_range AlgebraicGeometry.Scheme.affineBasisCover_map_range
theorem affineBasisCover_is_basis (X : Scheme.{u}) :
TopologicalSpace.IsTopologicalBasis
{x : Set X |
∃ a : X.affineBasisCover.J, x = Set.range (X.affineBasisCover.map a).1.base} := by
apply TopologicalSpace.isTopologicalBasis_of_isOpen_of_nhds
· rintro _ ⟨a, rfl⟩
exact IsOpenImmersion.isOpen_range (X.affineBasisCover.map a)
· rintro a U haU hU
rcases X.affineCover.Covers a with ⟨x, e⟩
let U' := (X.affineCover.map (X.affineCover.f a)).1.base ⁻¹' U
have hxU' : x ∈ U' := by rw [← e] at haU; exact haU
rcases PrimeSpectrum.isBasis_basic_opens.exists_subset_of_mem_open hxU'
((X.affineCover.map (X.affineCover.f a)).1.base.continuous_toFun.isOpen_preimage _
hU) with
⟨_, ⟨_, ⟨s, rfl⟩, rfl⟩, hxV, hVU⟩
refine ⟨_, ⟨⟨_, s⟩, rfl⟩, ?_, ?_⟩ <;> erw [affineBasisCover_map_range]
· exact ⟨x, hxV, e⟩
· rw [Set.image_subset_iff]; exact hVU
#align algebraic_geometry.Scheme.affine_basis_cover_is_basis AlgebraicGeometry.Scheme.affineBasisCover_is_basis
/-- Every open cover of a quasi-compact scheme can be refined into a finite subcover.
-/
@[simps! obj map]
def OpenCover.finiteSubcover {X : Scheme.{u}} (𝒰 : OpenCover X) [H : CompactSpace X] :
OpenCover X := by
have :=
@CompactSpace.elim_nhds_subcover _ _ H (fun x : X => Set.range (𝒰.map (𝒰.f x)).1.base)
fun x => (IsOpenImmersion.isOpen_range (𝒰.map (𝒰.f x))).mem_nhds (𝒰.Covers x)
let t := this.choose
have h : ∀ x : X, ∃ y : t, x ∈ Set.range (𝒰.map (𝒰.f y)).1.base := by
intro x
have h' : x ∈ (⊤ : Set X) := trivial
rw [← Classical.choose_spec this, Set.mem_iUnion] at h'
rcases h' with ⟨y, _, ⟨hy, rfl⟩, hy'⟩
exact ⟨⟨y, hy⟩, hy'⟩
exact
{ J := t
obj := fun x => 𝒰.obj (𝒰.f x.1)
map := fun x => 𝒰.map (𝒰.f x.1)
f := fun x => (h x).choose
Covers := fun x => (h x).choose_spec }
#align algebraic_geometry.Scheme.open_cover.finite_subcover AlgebraicGeometry.Scheme.OpenCover.finiteSubcover
instance [H : CompactSpace X] : Fintype 𝒰.finiteSubcover.J := by
delta OpenCover.finiteSubcover; infer_instance
end Scheme
end OpenCover
namespace PresheafedSpace.IsOpenImmersion
section ToScheme
variable {X : PresheafedSpace CommRingCat.{u}} (Y : Scheme.{u})
variable (f : X ⟶ Y.toPresheafedSpace) [H : PresheafedSpace.IsOpenImmersion f]
/-- If `X ⟶ Y` is an open immersion, and `Y` is a scheme, then so is `X`. -/
def toScheme : Scheme := by
apply LocallyRingedSpace.IsOpenImmersion.scheme (toLocallyRingedSpace _ f)
intro x
obtain ⟨_, ⟨i, rfl⟩, hx, hi⟩ :=
Y.affineBasisCover_is_basis.exists_subset_of_mem_open (Set.mem_range_self x)
H.base_open.isOpen_range
use Y.affineBasisCoverRing i
use LocallyRingedSpace.IsOpenImmersion.lift (toLocallyRingedSpaceHom _ f) _ hi
constructor
· rw [LocallyRingedSpace.IsOpenImmersion.lift_range]; exact hx
· delta LocallyRingedSpace.IsOpenImmersion.lift; infer_instance
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.to_Scheme AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.toScheme
@[simp]
theorem toScheme_toLocallyRingedSpace :
(toScheme Y f).toLocallyRingedSpace = toLocallyRingedSpace Y.1 f :=
rfl
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.to_Scheme_to_LocallyRingedSpace AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.toScheme_toLocallyRingedSpace
/-- If `X ⟶ Y` is an open immersion of PresheafedSpaces, and `Y` is a Scheme, we can
upgrade it into a morphism of Schemes.
-/
def toSchemeHom : toScheme Y f ⟶ Y :=
toLocallyRingedSpaceHom _ f
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.to_Scheme_hom AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.toSchemeHom
@[simp]
theorem toSchemeHom_val : (toSchemeHom Y f).val = f :=
rfl
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.to_Scheme_hom_val AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.toSchemeHom_val
instance toSchemeHom_isOpenImmersion : AlgebraicGeometry.IsOpenImmersion (toSchemeHom Y f) :=
H
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.to_Scheme_hom_IsOpenImmersion AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.toSchemeHom_isOpenImmersionₓ
theorem scheme_eq_of_locallyRingedSpace_eq {X Y : Scheme.{u}}
(H : X.toLocallyRingedSpace = Y.toLocallyRingedSpace) : X = Y := by
cases X; cases Y; congr
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.Scheme_eq_of_LocallyRingedSpace_eq AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.scheme_eq_of_locallyRingedSpace_eq
theorem scheme_toScheme {X Y : Scheme.{u}} (f : X ⟶ Y) [AlgebraicGeometry.IsOpenImmersion f] :
toScheme Y f.1 = X := by
apply scheme_eq_of_locallyRingedSpace_eq
exact locallyRingedSpace_toLocallyRingedSpace f
#align algebraic_geometry.PresheafedSpace.IsOpenImmersion.Scheme_to_Scheme AlgebraicGeometry.PresheafedSpace.IsOpenImmersionₓ.scheme_toScheme
end ToScheme
end PresheafedSpace.IsOpenImmersion
/-- The restriction of a Scheme along an open embedding. -/
@[simps! (config := .lemmasOnly) carrier, simps! presheaf_map presheaf_obj]
def Scheme.restrict {U : TopCat.{u}} (X : Scheme.{u}) {f : U ⟶ TopCat.of X} (h : OpenEmbedding f) :
Scheme :=
{ PresheafedSpace.IsOpenImmersion.toScheme X (X.toPresheafedSpace.ofRestrict h) with
toPresheafedSpace := X.toPresheafedSpace.restrict h }
#align algebraic_geometry.Scheme.restrict AlgebraicGeometry.Scheme.restrict
lemma Scheme.restrict_toPresheafedSpace
{U : TopCat.{u}} (X : Scheme.{u}) {f : U ⟶ TopCat.of X} (h : OpenEmbedding f) :
(X.restrict h).toPresheafedSpace = X.toPresheafedSpace.restrict h := rfl
/-- The canonical map from the restriction to the subspace. -/
@[simps!]
def Scheme.ofRestrict {U : TopCat.{u}} (X : Scheme.{u}) {f : U ⟶ TopCat.of X}
(h : OpenEmbedding f) : X.restrict h ⟶ X :=
X.toLocallyRingedSpace.ofRestrict h
#align algebraic_geometry.Scheme.ofRestrict AlgebraicGeometry.Scheme.ofRestrict
instance IsOpenImmersion.ofRestrict {U : TopCat.{u}} (X : Scheme.{u}) {f : U ⟶ TopCat.of X}
(h : OpenEmbedding f) : IsOpenImmersion (X.ofRestrict h) :=
show PresheafedSpace.IsOpenImmersion (X.toPresheafedSpace.ofRestrict h) by infer_instance
#align algebraic_geometry.IsOpenImmersion.ofRestrict AlgebraicGeometry.IsOpenImmersion.ofRestrict
namespace IsOpenImmersion
variable {X Y Z : Scheme.{u}} (f : X ⟶ Z) (g : Y ⟶ Z)
variable [H : IsOpenImmersion f]
instance (priority := 100) of_isIso [IsIso g] : IsOpenImmersion g :=
@LocallyRingedSpace.IsOpenImmersion.of_isIso _ _ _
(show IsIso ((inducedFunctor _).map g) by infer_instance)
#align algebraic_geometry.IsOpenImmersion.of_is_iso AlgebraicGeometry.IsOpenImmersion.of_isIso
theorem to_iso {X Y : Scheme.{u}} (f : X ⟶ Y) [h : IsOpenImmersion f] [Epi f.1.base] : IsIso f :=
@isIso_of_reflects_iso _ _ _ _ _ _ f
(Scheme.forgetToLocallyRingedSpace ⋙
LocallyRingedSpace.forgetToSheafedSpace ⋙ SheafedSpace.forgetToPresheafedSpace)
(@PresheafedSpace.IsOpenImmersion.to_iso _ _ _ _ f.1 h _) _
#align algebraic_geometry.IsOpenImmersion.to_iso AlgebraicGeometry.IsOpenImmersion.to_iso
theorem of_stalk_iso {X Y : Scheme.{u}} (f : X ⟶ Y) (hf : OpenEmbedding f.1.base)
[∀ x, IsIso (PresheafedSpace.stalkMap f.1 x)] : IsOpenImmersion f :=
SheafedSpace.IsOpenImmersion.of_stalk_iso f.1 hf
#align algebraic_geometry.IsOpenImmersion.of_stalk_iso AlgebraicGeometry.IsOpenImmersion.of_stalk_iso
theorem iff_stalk_iso {X Y : Scheme.{u}} (f : X ⟶ Y) :
IsOpenImmersion f ↔ OpenEmbedding f.1.base ∧ ∀ x, IsIso (PresheafedSpace.stalkMap f.1 x) :=
⟨fun H => ⟨H.1, inferInstance⟩, fun ⟨h₁, h₂⟩ => @IsOpenImmersion.of_stalk_iso _ _ f h₁ h₂⟩
#align algebraic_geometry.IsOpenImmersion.iff_stalk_iso AlgebraicGeometry.IsOpenImmersion.iff_stalk_iso
theorem _root_.AlgebraicGeometry.isIso_iff_isOpenImmersion {X Y : Scheme.{u}} (f : X ⟶ Y) :
IsIso f ↔ IsOpenImmersion f ∧ Epi f.1.base :=
⟨fun _ => ⟨inferInstance, inferInstance⟩, fun ⟨h₁, h₂⟩ => @IsOpenImmersion.to_iso _ _ f h₁ h₂⟩
#align algebraic_geometry.is_iso_iff_IsOpenImmersion AlgebraicGeometry.isIso_iff_isOpenImmersion
| Mathlib/AlgebraicGeometry/OpenImmersion.lean | 433 | 445 | theorem _root_.AlgebraicGeometry.isIso_iff_stalk_iso {X Y : Scheme.{u}} (f : X ⟶ Y) :
IsIso f ↔ IsIso f.1.base ∧ ∀ x, IsIso (PresheafedSpace.stalkMap f.1 x) := by |
rw [isIso_iff_isOpenImmersion, IsOpenImmersion.iff_stalk_iso, and_comm, ← and_assoc]
refine and_congr ⟨?_, ?_⟩ Iff.rfl
· rintro ⟨h₁, h₂⟩
convert_to
IsIso
(TopCat.isoOfHomeo
(Homeomorph.homeomorphOfContinuousOpen
(Equiv.ofBijective _ ⟨h₂.inj, (TopCat.epi_iff_surjective _).mp h₁⟩) h₂.continuous
h₂.isOpenMap)).hom
infer_instance
· intro H; exact ⟨inferInstance, (TopCat.homeoOfIso (asIso f.1.base)).openEmbedding⟩
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Yury Kudryashov, Kexing Ying
-/
import Mathlib.Topology.Semicontinuous
import Mathlib.MeasureTheory.Function.AEMeasurableSequence
import Mathlib.MeasureTheory.Order.Lattice
import Mathlib.Topology.Order.Lattice
import Mathlib.MeasureTheory.Constructions.BorelSpace.Basic
#align_import measure_theory.constructions.borel_space.basic from "leanprover-community/mathlib"@"9f55d0d4363ae59948c33864cbc52e0b12e0e8ce"
/-!
# Borel sigma algebras on spaces with orders
## Main statements
* `borel_eq_generateFrom_Ixx` (where Ixx is one of {Iio, Ioi, Iic, Ici, Ico, Ioc}):
The Borel sigma algebra of a linear order topology is generated by intervals of the given kind.
* `Dense.borel_eq_generateFrom_Ico_mem`, `Dense.borel_eq_generateFrom_Ioc_mem`:
The Borel sigma algebra of a dense linear order topology is generated by intervals of a given
kind, with endpoints from dense subsets.
* `ext_of_Ico`, `ext_of_Ioc`:
A locally finite Borel measure on a second countable conditionally complete linear order is
characterized by the measures of intervals of the given kind.
* `ext_of_Iic`, `ext_of_Ici`:
A finite Borel measure on a second countable linear order is characterized by the measures of
intervals of the given kind.
* `UpperSemicontinuous.measurable`, `LowerSemicontinuous.measurable`:
Semicontinuous functions are measurable.
* `measurable_iSup`, `measurable_iInf`, `measurable_sSup`, `measurable_sInf`:
Countable supremums and infimums of measurable functions to conditionally complete linear orders
are measurable.
* `measurable_liminf`, `measurable_limsup`:
Countable liminfs and limsups of measurable functions to conditionally complete linear orders
are measurable.
-/
open Set Filter MeasureTheory MeasurableSpace TopologicalSpace
open scoped Classical Topology NNReal ENNReal MeasureTheory
universe u v w x y
variable {α β γ δ : Type*} {ι : Sort y} {s t u : Set α}
section OrderTopology
variable (α)
variable [TopologicalSpace α] [SecondCountableTopology α] [LinearOrder α] [OrderTopology α]
theorem borel_eq_generateFrom_Iio : borel α = .generateFrom (range Iio) := by
refine le_antisymm ?_ (generateFrom_le ?_)
· rw [borel_eq_generateFrom_of_subbasis (@OrderTopology.topology_eq_generate_intervals α _ _ _)]
letI : MeasurableSpace α := MeasurableSpace.generateFrom (range Iio)
have H : ∀ a : α, MeasurableSet (Iio a) := fun a => GenerateMeasurable.basic _ ⟨_, rfl⟩
refine generateFrom_le ?_
rintro _ ⟨a, rfl | rfl⟩
· rcases em (∃ b, a ⋖ b) with ⟨b, hb⟩ | hcovBy
· rw [hb.Ioi_eq, ← compl_Iio]
exact (H _).compl
· rcases isOpen_biUnion_countable (Ioi a) Ioi fun _ _ ↦ isOpen_Ioi with ⟨t, hat, htc, htU⟩
have : Ioi a = ⋃ b ∈ t, Ici b := by
refine Subset.antisymm ?_ <| iUnion₂_subset fun b hb ↦ Ici_subset_Ioi.2 (hat hb)
refine Subset.trans ?_ <| iUnion₂_mono fun _ _ ↦ Ioi_subset_Ici_self
simpa [CovBy, htU, subset_def] using hcovBy
simp only [this, ← compl_Iio]
exact .biUnion htc <| fun _ _ ↦ (H _).compl
· apply H
· rw [forall_mem_range]
intro a
exact GenerateMeasurable.basic _ isOpen_Iio
#align borel_eq_generate_from_Iio borel_eq_generateFrom_Iio
theorem borel_eq_generateFrom_Ioi : borel α = .generateFrom (range Ioi) :=
@borel_eq_generateFrom_Iio αᵒᵈ _ (by infer_instance : SecondCountableTopology α) _ _
#align borel_eq_generate_from_Ioi borel_eq_generateFrom_Ioi
theorem borel_eq_generateFrom_Iic :
borel α = MeasurableSpace.generateFrom (range Iic) := by
rw [borel_eq_generateFrom_Ioi]
refine le_antisymm ?_ ?_
· refine MeasurableSpace.generateFrom_le fun t ht => ?_
obtain ⟨u, rfl⟩ := ht
rw [← compl_Iic]
exact (MeasurableSpace.measurableSet_generateFrom (mem_range.mpr ⟨u, rfl⟩)).compl
· refine MeasurableSpace.generateFrom_le fun t ht => ?_
obtain ⟨u, rfl⟩ := ht
rw [← compl_Ioi]
exact (MeasurableSpace.measurableSet_generateFrom (mem_range.mpr ⟨u, rfl⟩)).compl
#align borel_eq_generate_from_Iic borel_eq_generateFrom_Iic
theorem borel_eq_generateFrom_Ici : borel α = MeasurableSpace.generateFrom (range Ici) :=
@borel_eq_generateFrom_Iic αᵒᵈ _ _ _ _
#align borel_eq_generate_from_Ici borel_eq_generateFrom_Ici
end OrderTopology
section Orders
variable [TopologicalSpace α] [MeasurableSpace α] [OpensMeasurableSpace α]
variable [MeasurableSpace δ]
section Preorder
variable [Preorder α] [OrderClosedTopology α] {a b x : α}
@[simp, measurability]
theorem measurableSet_Ici : MeasurableSet (Ici a) :=
isClosed_Ici.measurableSet
#align measurable_set_Ici measurableSet_Ici
@[simp, measurability]
theorem measurableSet_Iic : MeasurableSet (Iic a) :=
isClosed_Iic.measurableSet
#align measurable_set_Iic measurableSet_Iic
@[simp, measurability]
theorem measurableSet_Icc : MeasurableSet (Icc a b) :=
isClosed_Icc.measurableSet
#align measurable_set_Icc measurableSet_Icc
instance nhdsWithin_Ici_isMeasurablyGenerated : (𝓝[Ici b] a).IsMeasurablyGenerated :=
measurableSet_Ici.nhdsWithin_isMeasurablyGenerated _
#align nhds_within_Ici_is_measurably_generated nhdsWithin_Ici_isMeasurablyGenerated
instance nhdsWithin_Iic_isMeasurablyGenerated : (𝓝[Iic b] a).IsMeasurablyGenerated :=
measurableSet_Iic.nhdsWithin_isMeasurablyGenerated _
#align nhds_within_Iic_is_measurably_generated nhdsWithin_Iic_isMeasurablyGenerated
instance nhdsWithin_Icc_isMeasurablyGenerated : IsMeasurablyGenerated (𝓝[Icc a b] x) := by
rw [← Ici_inter_Iic, nhdsWithin_inter]
infer_instance
#align nhds_within_Icc_is_measurably_generated nhdsWithin_Icc_isMeasurablyGenerated
instance atTop_isMeasurablyGenerated : (Filter.atTop : Filter α).IsMeasurablyGenerated :=
@Filter.iInf_isMeasurablyGenerated _ _ _ _ fun a =>
(measurableSet_Ici : MeasurableSet (Ici a)).principal_isMeasurablyGenerated
#align at_top_is_measurably_generated atTop_isMeasurablyGenerated
instance atBot_isMeasurablyGenerated : (Filter.atBot : Filter α).IsMeasurablyGenerated :=
@Filter.iInf_isMeasurablyGenerated _ _ _ _ fun a =>
(measurableSet_Iic : MeasurableSet (Iic a)).principal_isMeasurablyGenerated
#align at_bot_is_measurably_generated atBot_isMeasurablyGenerated
instance [R1Space α] : IsMeasurablyGenerated (cocompact α) where
exists_measurable_subset := by
intro _ hs
obtain ⟨t, ht, hts⟩ := mem_cocompact.mp hs
exact ⟨(closure t)ᶜ, ht.closure.compl_mem_cocompact, isClosed_closure.measurableSet.compl,
(compl_subset_compl.2 subset_closure).trans hts⟩
end Preorder
section PartialOrder
variable [PartialOrder α] [OrderClosedTopology α] [SecondCountableTopology α] {a b : α}
@[measurability]
theorem measurableSet_le' : MeasurableSet { p : α × α | p.1 ≤ p.2 } :=
OrderClosedTopology.isClosed_le'.measurableSet
#align measurable_set_le' measurableSet_le'
@[measurability]
theorem measurableSet_le {f g : δ → α} (hf : Measurable f) (hg : Measurable g) :
MeasurableSet { a | f a ≤ g a } :=
hf.prod_mk hg measurableSet_le'
#align measurable_set_le measurableSet_le
end PartialOrder
section LinearOrder
variable [LinearOrder α] [OrderClosedTopology α] {a b x : α}
-- we open this locale only here to avoid issues with list being treated as intervals above
open Interval
@[simp, measurability]
theorem measurableSet_Iio : MeasurableSet (Iio a) :=
isOpen_Iio.measurableSet
#align measurable_set_Iio measurableSet_Iio
@[simp, measurability]
theorem measurableSet_Ioi : MeasurableSet (Ioi a) :=
isOpen_Ioi.measurableSet
#align measurable_set_Ioi measurableSet_Ioi
@[simp, measurability]
theorem measurableSet_Ioo : MeasurableSet (Ioo a b) :=
isOpen_Ioo.measurableSet
#align measurable_set_Ioo measurableSet_Ioo
@[simp, measurability]
theorem measurableSet_Ioc : MeasurableSet (Ioc a b) :=
measurableSet_Ioi.inter measurableSet_Iic
#align measurable_set_Ioc measurableSet_Ioc
@[simp, measurability]
theorem measurableSet_Ico : MeasurableSet (Ico a b) :=
measurableSet_Ici.inter measurableSet_Iio
#align measurable_set_Ico measurableSet_Ico
instance nhdsWithin_Ioi_isMeasurablyGenerated : (𝓝[Ioi b] a).IsMeasurablyGenerated :=
measurableSet_Ioi.nhdsWithin_isMeasurablyGenerated _
#align nhds_within_Ioi_is_measurably_generated nhdsWithin_Ioi_isMeasurablyGenerated
instance nhdsWithin_Iio_isMeasurablyGenerated : (𝓝[Iio b] a).IsMeasurablyGenerated :=
measurableSet_Iio.nhdsWithin_isMeasurablyGenerated _
#align nhds_within_Iio_is_measurably_generated nhdsWithin_Iio_isMeasurablyGenerated
instance nhdsWithin_uIcc_isMeasurablyGenerated : IsMeasurablyGenerated (𝓝[[[a, b]]] x) :=
nhdsWithin_Icc_isMeasurablyGenerated
#align nhds_within_uIcc_is_measurably_generated nhdsWithin_uIcc_isMeasurablyGenerated
@[measurability]
theorem measurableSet_lt' [SecondCountableTopology α] : MeasurableSet { p : α × α | p.1 < p.2 } :=
(isOpen_lt continuous_fst continuous_snd).measurableSet
#align measurable_set_lt' measurableSet_lt'
@[measurability]
theorem measurableSet_lt [SecondCountableTopology α] {f g : δ → α} (hf : Measurable f)
(hg : Measurable g) : MeasurableSet { a | f a < g a } :=
hf.prod_mk hg measurableSet_lt'
#align measurable_set_lt measurableSet_lt
theorem nullMeasurableSet_lt [SecondCountableTopology α] {μ : Measure δ} {f g : δ → α}
(hf : AEMeasurable f μ) (hg : AEMeasurable g μ) : NullMeasurableSet { a | f a < g a } μ :=
(hf.prod_mk hg).nullMeasurable measurableSet_lt'
#align null_measurable_set_lt nullMeasurableSet_lt
theorem nullMeasurableSet_lt' [SecondCountableTopology α] {μ : Measure (α × α)} :
NullMeasurableSet { p : α × α | p.1 < p.2 } μ :=
measurableSet_lt'.nullMeasurableSet
theorem nullMeasurableSet_le [SecondCountableTopology α] {μ : Measure δ}
{f g : δ → α} (hf : AEMeasurable f μ) (hg : AEMeasurable g μ) :
NullMeasurableSet { a | f a ≤ g a } μ :=
(hf.prod_mk hg).nullMeasurable measurableSet_le'
theorem Set.OrdConnected.measurableSet (h : OrdConnected s) : MeasurableSet s := by
let u := ⋃ (x ∈ s) (y ∈ s), Ioo x y
have huopen : IsOpen u := isOpen_biUnion fun _ _ => isOpen_biUnion fun _ _ => isOpen_Ioo
have humeas : MeasurableSet u := huopen.measurableSet
have hfinite : (s \ u).Finite := s.finite_diff_iUnion_Ioo
have : u ⊆ s := iUnion₂_subset fun x hx => iUnion₂_subset fun y hy =>
Ioo_subset_Icc_self.trans (h.out hx hy)
rw [← union_diff_cancel this]
exact humeas.union hfinite.measurableSet
#align set.ord_connected.measurable_set Set.OrdConnected.measurableSet
theorem IsPreconnected.measurableSet (h : IsPreconnected s) : MeasurableSet s :=
h.ordConnected.measurableSet
#align is_preconnected.measurable_set IsPreconnected.measurableSet
theorem generateFrom_Ico_mem_le_borel {α : Type*} [TopologicalSpace α] [LinearOrder α]
[OrderClosedTopology α] (s t : Set α) :
MeasurableSpace.generateFrom { S | ∃ l ∈ s, ∃ u ∈ t, l < u ∧ Ico l u = S }
≤ borel α := by
apply generateFrom_le
borelize α
rintro _ ⟨a, -, b, -, -, rfl⟩
exact measurableSet_Ico
#align generate_from_Ico_mem_le_borel generateFrom_Ico_mem_le_borel
theorem Dense.borel_eq_generateFrom_Ico_mem_aux {α : Type*} [TopologicalSpace α] [LinearOrder α]
[OrderTopology α] [SecondCountableTopology α] {s : Set α} (hd : Dense s)
(hbot : ∀ x, IsBot x → x ∈ s) (hIoo : ∀ x y : α, x < y → Ioo x y = ∅ → y ∈ s) :
borel α = .generateFrom { S : Set α | ∃ l ∈ s, ∃ u ∈ s, l < u ∧ Ico l u = S } := by
set S : Set (Set α) := { S | ∃ l ∈ s, ∃ u ∈ s, l < u ∧ Ico l u = S }
refine le_antisymm ?_ (generateFrom_Ico_mem_le_borel _ _)
letI : MeasurableSpace α := generateFrom S
rw [borel_eq_generateFrom_Iio]
refine generateFrom_le (forall_mem_range.2 fun a => ?_)
rcases hd.exists_countable_dense_subset_bot_top with ⟨t, hts, hc, htd, htb, -⟩
by_cases ha : ∀ b < a, (Ioo b a).Nonempty
· convert_to MeasurableSet (⋃ (l ∈ t) (u ∈ t) (_ : l < u) (_ : u ≤ a), Ico l u)
· ext y
simp only [mem_iUnion, mem_Iio, mem_Ico]
constructor
· intro hy
rcases htd.exists_le' (fun b hb => htb _ hb (hbot b hb)) y with ⟨l, hlt, hly⟩
rcases htd.exists_mem_open isOpen_Ioo (ha y hy) with ⟨u, hut, hyu, hua⟩
exact ⟨l, hlt, u, hut, hly.trans_lt hyu, hua.le, hly, hyu⟩
· rintro ⟨l, -, u, -, -, hua, -, hyu⟩
exact hyu.trans_le hua
· refine MeasurableSet.biUnion hc fun a ha => MeasurableSet.biUnion hc fun b hb => ?_
refine MeasurableSet.iUnion fun hab => MeasurableSet.iUnion fun _ => ?_
exact .basic _ ⟨a, hts ha, b, hts hb, hab, mem_singleton _⟩
· simp only [not_forall, not_nonempty_iff_eq_empty] at ha
replace ha : a ∈ s := hIoo ha.choose a ha.choose_spec.fst ha.choose_spec.snd
convert_to MeasurableSet (⋃ (l ∈ t) (_ : l < a), Ico l a)
· symm
simp only [← Ici_inter_Iio, ← iUnion_inter, inter_eq_right, subset_def, mem_iUnion,
mem_Ici, mem_Iio]
intro x hx
rcases htd.exists_le' (fun b hb => htb _ hb (hbot b hb)) x with ⟨z, hzt, hzx⟩
exact ⟨z, hzt, hzx.trans_lt hx, hzx⟩
· refine .biUnion hc fun x hx => MeasurableSet.iUnion fun hlt => ?_
exact .basic _ ⟨x, hts hx, a, ha, hlt, mem_singleton _⟩
#align dense.borel_eq_generate_from_Ico_mem_aux Dense.borel_eq_generateFrom_Ico_mem_aux
theorem Dense.borel_eq_generateFrom_Ico_mem {α : Type*} [TopologicalSpace α] [LinearOrder α]
[OrderTopology α] [SecondCountableTopology α] [DenselyOrdered α] [NoMinOrder α] {s : Set α}
(hd : Dense s) :
borel α = .generateFrom { S : Set α | ∃ l ∈ s, ∃ u ∈ s, l < u ∧ Ico l u = S } :=
hd.borel_eq_generateFrom_Ico_mem_aux (by simp) fun x y hxy H =>
((nonempty_Ioo.2 hxy).ne_empty H).elim
#align dense.borel_eq_generate_from_Ico_mem Dense.borel_eq_generateFrom_Ico_mem
theorem borel_eq_generateFrom_Ico (α : Type*) [TopologicalSpace α] [SecondCountableTopology α]
[LinearOrder α] [OrderTopology α] :
borel α = .generateFrom { S : Set α | ∃ (l u : α), l < u ∧ Ico l u = S } := by
simpa only [exists_prop, mem_univ, true_and_iff] using
(@dense_univ α _).borel_eq_generateFrom_Ico_mem_aux (fun _ _ => mem_univ _) fun _ _ _ _ =>
mem_univ _
#align borel_eq_generate_from_Ico borel_eq_generateFrom_Ico
theorem Dense.borel_eq_generateFrom_Ioc_mem_aux {α : Type*} [TopologicalSpace α] [LinearOrder α]
[OrderTopology α] [SecondCountableTopology α] {s : Set α} (hd : Dense s)
(hbot : ∀ x, IsTop x → x ∈ s) (hIoo : ∀ x y : α, x < y → Ioo x y = ∅ → x ∈ s) :
borel α = .generateFrom { S : Set α | ∃ l ∈ s, ∃ u ∈ s, l < u ∧ Ioc l u = S } := by
convert hd.orderDual.borel_eq_generateFrom_Ico_mem_aux hbot fun x y hlt he => hIoo y x hlt _
using 2
· ext s
constructor <;> rintro ⟨l, hl, u, hu, hlt, rfl⟩
exacts [⟨u, hu, l, hl, hlt, dual_Ico⟩, ⟨u, hu, l, hl, hlt, dual_Ioc⟩]
· erw [dual_Ioo]
exact he
#align dense.borel_eq_generate_from_Ioc_mem_aux Dense.borel_eq_generateFrom_Ioc_mem_aux
theorem Dense.borel_eq_generateFrom_Ioc_mem {α : Type*} [TopologicalSpace α] [LinearOrder α]
[OrderTopology α] [SecondCountableTopology α] [DenselyOrdered α] [NoMaxOrder α] {s : Set α}
(hd : Dense s) :
borel α = .generateFrom { S : Set α | ∃ l ∈ s, ∃ u ∈ s, l < u ∧ Ioc l u = S } :=
hd.borel_eq_generateFrom_Ioc_mem_aux (by simp) fun x y hxy H =>
((nonempty_Ioo.2 hxy).ne_empty H).elim
#align dense.borel_eq_generate_from_Ioc_mem Dense.borel_eq_generateFrom_Ioc_mem
theorem borel_eq_generateFrom_Ioc (α : Type*) [TopologicalSpace α] [SecondCountableTopology α]
[LinearOrder α] [OrderTopology α] :
borel α = .generateFrom { S : Set α | ∃ l u, l < u ∧ Ioc l u = S } := by
simpa only [exists_prop, mem_univ, true_and_iff] using
(@dense_univ α _).borel_eq_generateFrom_Ioc_mem_aux (fun _ _ => mem_univ _) fun _ _ _ _ =>
mem_univ _
#align borel_eq_generate_from_Ioc borel_eq_generateFrom_Ioc
namespace MeasureTheory.Measure
/-- Two finite measures on a Borel space are equal if they agree on all closed-open intervals. If
`α` is a conditionally complete linear order with no top element,
`MeasureTheory.Measure.ext_of_Ico` is an extensionality lemma with weaker assumptions on `μ` and
`ν`. -/
theorem ext_of_Ico_finite {α : Type*} [TopologicalSpace α] {m : MeasurableSpace α}
[SecondCountableTopology α] [LinearOrder α] [OrderTopology α] [BorelSpace α] (μ ν : Measure α)
[IsFiniteMeasure μ] (hμν : μ univ = ν univ) (h : ∀ ⦃a b⦄, a < b → μ (Ico a b) = ν (Ico a b)) :
μ = ν := by
refine
ext_of_generate_finite _ (BorelSpace.measurable_eq.trans (borel_eq_generateFrom_Ico α))
(isPiSystem_Ico (id : α → α) id) ?_ hμν
rintro - ⟨a, b, hlt, rfl⟩
exact h hlt
#align measure_theory.measure.ext_of_Ico_finite MeasureTheory.Measure.ext_of_Ico_finite
/-- Two finite measures on a Borel space are equal if they agree on all open-closed intervals. If
`α` is a conditionally complete linear order with no top element,
`MeasureTheory.Measure.ext_of_Ioc` is an extensionality lemma with weaker assumptions on `μ` and
`ν`. -/
theorem ext_of_Ioc_finite {α : Type*} [TopologicalSpace α] {m : MeasurableSpace α}
[SecondCountableTopology α] [LinearOrder α] [OrderTopology α] [BorelSpace α] (μ ν : Measure α)
[IsFiniteMeasure μ] (hμν : μ univ = ν univ) (h : ∀ ⦃a b⦄, a < b → μ (Ioc a b) = ν (Ioc a b)) :
μ = ν := by
refine @ext_of_Ico_finite αᵒᵈ _ _ _ _ _ ‹_› μ ν _ hμν fun a b hab => ?_
erw [dual_Ico (α := α)]
exact h hab
#align measure_theory.measure.ext_of_Ioc_finite MeasureTheory.Measure.ext_of_Ioc_finite
/-- Two measures which are finite on closed-open intervals are equal if they agree on all
closed-open intervals. -/
theorem ext_of_Ico' {α : Type*} [TopologicalSpace α] {m : MeasurableSpace α}
[SecondCountableTopology α] [LinearOrder α] [OrderTopology α] [BorelSpace α] [NoMaxOrder α]
(μ ν : Measure α) (hμ : ∀ ⦃a b⦄, a < b → μ (Ico a b) ≠ ∞)
(h : ∀ ⦃a b⦄, a < b → μ (Ico a b) = ν (Ico a b)) : μ = ν := by
rcases exists_countable_dense_bot_top α with ⟨s, hsc, hsd, hsb, _⟩
have : (⋃ (l ∈ s) (u ∈ s) (_ : l < u), {Ico l u} : Set (Set α)).Countable :=
hsc.biUnion fun l _ => hsc.biUnion fun u _ => countable_iUnion fun _ => countable_singleton _
simp only [← setOf_eq_eq_singleton, ← setOf_exists] at this
refine
Measure.ext_of_generateFrom_of_cover_subset
(BorelSpace.measurable_eq.trans (borel_eq_generateFrom_Ico α)) (isPiSystem_Ico id id) ?_ this
?_ ?_ ?_
· rintro _ ⟨l, -, u, -, h, rfl⟩
exact ⟨l, u, h, rfl⟩
· refine sUnion_eq_univ_iff.2 fun x => ?_
rcases hsd.exists_le' hsb x with ⟨l, hls, hlx⟩
rcases hsd.exists_gt x with ⟨u, hus, hxu⟩
exact ⟨_, ⟨l, hls, u, hus, hlx.trans_lt hxu, rfl⟩, hlx, hxu⟩
· rintro _ ⟨l, -, u, -, hlt, rfl⟩
exact hμ hlt
· rintro _ ⟨l, u, hlt, rfl⟩
exact h hlt
#align measure_theory.measure.ext_of_Ico' MeasureTheory.Measure.ext_of_Ico'
/-- Two measures which are finite on closed-open intervals are equal if they agree on all
open-closed intervals. -/
theorem ext_of_Ioc' {α : Type*} [TopologicalSpace α] {m : MeasurableSpace α}
[SecondCountableTopology α] [LinearOrder α] [OrderTopology α] [BorelSpace α] [NoMinOrder α]
(μ ν : Measure α) (hμ : ∀ ⦃a b⦄, a < b → μ (Ioc a b) ≠ ∞)
(h : ∀ ⦃a b⦄, a < b → μ (Ioc a b) = ν (Ioc a b)) : μ = ν := by
refine @ext_of_Ico' αᵒᵈ _ _ _ _ _ ‹_› _ μ ν ?_ ?_ <;> intro a b hab <;> erw [dual_Ico (α := α)]
exacts [hμ hab, h hab]
#align measure_theory.measure.ext_of_Ioc' MeasureTheory.Measure.ext_of_Ioc'
/-- Two measures which are finite on closed-open intervals are equal if they agree on all
closed-open intervals. -/
theorem ext_of_Ico {α : Type*} [TopologicalSpace α] {_m : MeasurableSpace α}
[SecondCountableTopology α] [ConditionallyCompleteLinearOrder α] [OrderTopology α]
[BorelSpace α] [NoMaxOrder α] (μ ν : Measure α) [IsLocallyFiniteMeasure μ]
(h : ∀ ⦃a b⦄, a < b → μ (Ico a b) = ν (Ico a b)) : μ = ν :=
μ.ext_of_Ico' ν (fun _ _ _ => measure_Ico_lt_top.ne) h
#align measure_theory.measure.ext_of_Ico MeasureTheory.Measure.ext_of_Ico
/-- Two measures which are finite on closed-open intervals are equal if they agree on all
open-closed intervals. -/
theorem ext_of_Ioc {α : Type*} [TopologicalSpace α] {_m : MeasurableSpace α}
[SecondCountableTopology α] [ConditionallyCompleteLinearOrder α] [OrderTopology α]
[BorelSpace α] [NoMinOrder α] (μ ν : Measure α) [IsLocallyFiniteMeasure μ]
(h : ∀ ⦃a b⦄, a < b → μ (Ioc a b) = ν (Ioc a b)) : μ = ν :=
μ.ext_of_Ioc' ν (fun _ _ _ => measure_Ioc_lt_top.ne) h
#align measure_theory.measure.ext_of_Ioc MeasureTheory.Measure.ext_of_Ioc
/-- Two finite measures on a Borel space are equal if they agree on all left-infinite right-closed
intervals. -/
theorem ext_of_Iic {α : Type*} [TopologicalSpace α] {m : MeasurableSpace α}
[SecondCountableTopology α] [LinearOrder α] [OrderTopology α] [BorelSpace α] (μ ν : Measure α)
[IsFiniteMeasure μ] (h : ∀ a, μ (Iic a) = ν (Iic a)) : μ = ν := by
refine ext_of_Ioc_finite μ ν ?_ fun a b hlt => ?_
· rcases exists_countable_dense_bot_top α with ⟨s, hsc, hsd, -, hst⟩
have : DirectedOn (· ≤ ·) s := directedOn_iff_directed.2 (Subtype.mono_coe _).directed_le
simp only [← biSup_measure_Iic hsc (hsd.exists_ge' hst) this, h]
rw [← Iic_diff_Iic, measure_diff (Iic_subset_Iic.2 hlt.le) measurableSet_Iic,
measure_diff (Iic_subset_Iic.2 hlt.le) measurableSet_Iic, h a, h b]
· rw [← h a]
exact (measure_lt_top μ _).ne
· exact (measure_lt_top μ _).ne
#align measure_theory.measure.ext_of_Iic MeasureTheory.Measure.ext_of_Iic
/-- Two finite measures on a Borel space are equal if they agree on all left-closed right-infinite
intervals. -/
theorem ext_of_Ici {α : Type*} [TopologicalSpace α] {m : MeasurableSpace α}
[SecondCountableTopology α] [LinearOrder α] [OrderTopology α] [BorelSpace α] (μ ν : Measure α)
[IsFiniteMeasure μ] (h : ∀ a, μ (Ici a) = ν (Ici a)) : μ = ν :=
@ext_of_Iic αᵒᵈ _ _ _ _ _ ‹_› _ _ _ h
#align measure_theory.measure.ext_of_Ici MeasureTheory.Measure.ext_of_Ici
end MeasureTheory.Measure
@[measurability]
theorem measurableSet_uIcc : MeasurableSet (uIcc a b) :=
measurableSet_Icc
#align measurable_set_uIcc measurableSet_uIcc
@[measurability]
theorem measurableSet_uIoc : MeasurableSet (uIoc a b) :=
measurableSet_Ioc
#align measurable_set_uIoc measurableSet_uIoc
variable [SecondCountableTopology α]
@[measurability]
theorem Measurable.max {f g : δ → α} (hf : Measurable f) (hg : Measurable g) :
Measurable fun a => max (f a) (g a) := by
simpa only [max_def'] using hf.piecewise (measurableSet_le hg hf) hg
#align measurable.max Measurable.max
@[measurability]
nonrec theorem AEMeasurable.max {f g : δ → α} {μ : Measure δ} (hf : AEMeasurable f μ)
(hg : AEMeasurable g μ) : AEMeasurable (fun a => max (f a) (g a)) μ :=
⟨fun a => max (hf.mk f a) (hg.mk g a), hf.measurable_mk.max hg.measurable_mk,
EventuallyEq.comp₂ hf.ae_eq_mk _ hg.ae_eq_mk⟩
#align ae_measurable.max AEMeasurable.max
@[measurability]
| Mathlib/MeasureTheory/Constructions/BorelSpace/Order.lean | 486 | 488 | theorem Measurable.min {f g : δ → α} (hf : Measurable f) (hg : Measurable g) :
Measurable fun a => min (f a) (g a) := by |
simpa only [min_def] using hf.piecewise (measurableSet_le hf hg) hg
|
/-
Copyright (c) 2023 David Loeffler. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Loeffler
-/
import Mathlib.Analysis.SpecialFunctions.Gaussian.GaussianIntegral
#align_import analysis.special_functions.gamma.bohr_mollerup from "leanprover-community/mathlib"@"a3209ddf94136d36e5e5c624b10b2a347cc9d090"
/-! # Convexity properties of the Gamma function
In this file, we prove that `Gamma` and `log ∘ Gamma` are convex functions on the positive real
line. We then prove the Bohr-Mollerup theorem, which characterises `Gamma` as the *unique*
positive-real-valued, log-convex function on the positive reals satisfying `f (x + 1) = x f x` and
`f 1 = 1`.
The proof of the Bohr-Mollerup theorem is bound up with the proof of (a weak form of) the Euler
limit formula, `Real.BohrMollerup.tendsto_logGammaSeq`, stating that for positive
real `x` the sequence `x * log n + log n! - ∑ (m : ℕ) ∈ Finset.range (n + 1), log (x + m)`
tends to `log Γ(x)` as `n → ∞`. We prove that any function satisfying the hypotheses of the
Bohr-Mollerup theorem must agree with the limit in the Euler limit formula, so there is at most one
such function; then we show that `Γ` satisfies these conditions.
Since most of the auxiliary lemmas for the Bohr-Mollerup theorem are of no relevance outside the
context of this proof, we place them in a separate namespace `Real.BohrMollerup` to avoid clutter.
(This includes the logarithmic form of the Euler limit formula, since later we will prove a more
general form of the Euler limit formula valid for any real or complex `x`; see
`Real.Gamma_seq_tendsto_Gamma` and `Complex.Gamma_seq_tendsto_Gamma` in the file
`Mathlib/Analysis/SpecialFunctions/Gamma/Beta.lean`.)
As an application of the Bohr-Mollerup theorem we prove the Legendre doubling formula for the
Gamma function for real positive `s` (which will be upgraded to a proof for all complex `s` in a
later file).
TODO: This argument can be extended to prove the general `k`-multiplication formula (at least up
to a constant, and it should be possible to deduce the value of this constant using Stirling's
formula).
-/
set_option linter.uppercaseLean3 false
noncomputable section
open Filter Set MeasureTheory
open scoped Nat ENNReal Topology Real
section Convexity
-- Porting note: move the following lemmas to `Analysis.Convex.Function`
variable {𝕜 E β : Type*} {s : Set E} {f g : E → β} [OrderedSemiring 𝕜] [SMul 𝕜 E] [AddCommMonoid E]
[OrderedAddCommMonoid β]
theorem ConvexOn.congr [SMul 𝕜 β] (hf : ConvexOn 𝕜 s f) (hfg : EqOn f g s) : ConvexOn 𝕜 s g :=
⟨hf.1, fun x hx y hy a b ha hb hab => by
simpa only [← hfg hx, ← hfg hy, ← hfg (hf.1 hx hy ha hb hab)] using hf.2 hx hy ha hb hab⟩
#align convex_on.congr ConvexOn.congr
theorem ConcaveOn.congr [SMul 𝕜 β] (hf : ConcaveOn 𝕜 s f) (hfg : EqOn f g s) : ConcaveOn 𝕜 s g :=
⟨hf.1, fun x hx y hy a b ha hb hab => by
simpa only [← hfg hx, ← hfg hy, ← hfg (hf.1 hx hy ha hb hab)] using hf.2 hx hy ha hb hab⟩
#align concave_on.congr ConcaveOn.congr
theorem StrictConvexOn.congr [SMul 𝕜 β] (hf : StrictConvexOn 𝕜 s f) (hfg : EqOn f g s) :
StrictConvexOn 𝕜 s g :=
⟨hf.1, fun x hx y hy hxy a b ha hb hab => by
simpa only [← hfg hx, ← hfg hy, ← hfg (hf.1 hx hy ha.le hb.le hab)] using
hf.2 hx hy hxy ha hb hab⟩
#align strict_convex_on.congr StrictConvexOn.congr
theorem StrictConcaveOn.congr [SMul 𝕜 β] (hf : StrictConcaveOn 𝕜 s f) (hfg : EqOn f g s) :
StrictConcaveOn 𝕜 s g :=
⟨hf.1, fun x hx y hy hxy a b ha hb hab => by
simpa only [← hfg hx, ← hfg hy, ← hfg (hf.1 hx hy ha.le hb.le hab)] using
hf.2 hx hy hxy ha hb hab⟩
#align strict_concave_on.congr StrictConcaveOn.congr
theorem ConvexOn.add_const [Module 𝕜 β] (hf : ConvexOn 𝕜 s f) (b : β) :
ConvexOn 𝕜 s (f + fun _ => b) :=
hf.add (convexOn_const _ hf.1)
#align convex_on.add_const ConvexOn.add_const
theorem ConcaveOn.add_const [Module 𝕜 β] (hf : ConcaveOn 𝕜 s f) (b : β) :
ConcaveOn 𝕜 s (f + fun _ => b) :=
hf.add (concaveOn_const _ hf.1)
#align concave_on.add_const ConcaveOn.add_const
theorem StrictConvexOn.add_const {γ : Type*} {f : E → γ} [OrderedCancelAddCommMonoid γ]
[Module 𝕜 γ] (hf : StrictConvexOn 𝕜 s f) (b : γ) : StrictConvexOn 𝕜 s (f + fun _ => b) :=
hf.add_convexOn (convexOn_const _ hf.1)
#align strict_convex_on.add_const StrictConvexOn.add_const
theorem StrictConcaveOn.add_const {γ : Type*} {f : E → γ} [OrderedCancelAddCommMonoid γ]
[Module 𝕜 γ] (hf : StrictConcaveOn 𝕜 s f) (b : γ) : StrictConcaveOn 𝕜 s (f + fun _ => b) :=
hf.add_concaveOn (concaveOn_const _ hf.1)
#align strict_concave_on.add_const StrictConcaveOn.add_const
end Convexity
namespace Real
section Convexity
/-- Log-convexity of the Gamma function on the positive reals (stated in multiplicative form),
proved using the Hölder inequality applied to Euler's integral. -/
theorem Gamma_mul_add_mul_le_rpow_Gamma_mul_rpow_Gamma {s t a b : ℝ} (hs : 0 < s) (ht : 0 < t)
(ha : 0 < a) (hb : 0 < b) (hab : a + b = 1) :
Gamma (a * s + b * t) ≤ Gamma s ^ a * Gamma t ^ b := by
-- We will apply Hölder's inequality, for the conjugate exponents `p = 1 / a`
-- and `q = 1 / b`, to the functions `f a s` and `f b t`, where `f` is as follows:
let f : ℝ → ℝ → ℝ → ℝ := fun c u x => exp (-c * x) * x ^ (c * (u - 1))
have e : IsConjExponent (1 / a) (1 / b) := Real.isConjExponent_one_div ha hb hab
have hab' : b = 1 - a := by linarith
have hst : 0 < a * s + b * t := add_pos (mul_pos ha hs) (mul_pos hb ht)
-- some properties of f:
have posf : ∀ c u x : ℝ, x ∈ Ioi (0 : ℝ) → 0 ≤ f c u x := fun c u x hx =>
mul_nonneg (exp_pos _).le (rpow_pos_of_pos hx _).le
have posf' : ∀ c u : ℝ, ∀ᵐ x : ℝ ∂volume.restrict (Ioi 0), 0 ≤ f c u x := fun c u =>
(ae_restrict_iff' measurableSet_Ioi).mpr (ae_of_all _ (posf c u))
have fpow :
∀ {c x : ℝ} (_ : 0 < c) (u : ℝ) (_ : 0 < x), exp (-x) * x ^ (u - 1) = f c u x ^ (1 / c) := by
intro c x hc u hx
dsimp only [f]
rw [mul_rpow (exp_pos _).le ((rpow_nonneg hx.le) _), ← exp_mul, ← rpow_mul hx.le]
congr 2 <;> field_simp [hc.ne']; ring
-- show `f c u` is in `ℒp` for `p = 1/c`:
have f_mem_Lp :
∀ {c u : ℝ} (hc : 0 < c) (hu : 0 < u),
Memℒp (f c u) (ENNReal.ofReal (1 / c)) (volume.restrict (Ioi 0)) := by
intro c u hc hu
have A : ENNReal.ofReal (1 / c) ≠ 0 := by
rwa [Ne, ENNReal.ofReal_eq_zero, not_le, one_div_pos]
have B : ENNReal.ofReal (1 / c) ≠ ∞ := ENNReal.ofReal_ne_top
rw [← memℒp_norm_rpow_iff _ A B, ENNReal.toReal_ofReal (one_div_nonneg.mpr hc.le),
ENNReal.div_self A B, memℒp_one_iff_integrable]
· apply Integrable.congr (GammaIntegral_convergent hu)
refine eventuallyEq_of_mem (self_mem_ae_restrict measurableSet_Ioi) fun x hx => ?_
dsimp only
rw [fpow hc u hx]
congr 1
exact (norm_of_nonneg (posf _ _ x hx)).symm
· refine ContinuousOn.aestronglyMeasurable ?_ measurableSet_Ioi
refine (Continuous.continuousOn ?_).mul (ContinuousAt.continuousOn fun x hx => ?_)
· exact continuous_exp.comp (continuous_const.mul continuous_id')
· exact continuousAt_rpow_const _ _ (Or.inl (mem_Ioi.mp hx).ne')
-- now apply Hölder:
rw [Gamma_eq_integral hs, Gamma_eq_integral ht, Gamma_eq_integral hst]
convert
MeasureTheory.integral_mul_le_Lp_mul_Lq_of_nonneg e (posf' a s) (posf' b t) (f_mem_Lp ha hs)
(f_mem_Lp hb ht) using
1
· refine setIntegral_congr measurableSet_Ioi fun x hx => ?_
dsimp only
have A : exp (-x) = exp (-a * x) * exp (-b * x) := by
rw [← exp_add, ← add_mul, ← neg_add, hab, neg_one_mul]
have B : x ^ (a * s + b * t - 1) = x ^ (a * (s - 1)) * x ^ (b * (t - 1)) := by
rw [← rpow_add hx, hab']; congr 1; ring
rw [A, B]
ring
· rw [one_div_one_div, one_div_one_div]
congr 2 <;> exact setIntegral_congr measurableSet_Ioi fun x hx => fpow (by assumption) _ hx
#align real.Gamma_mul_add_mul_le_rpow_Gamma_mul_rpow_Gamma Real.Gamma_mul_add_mul_le_rpow_Gamma_mul_rpow_Gamma
| Mathlib/Analysis/SpecialFunctions/Gamma/BohrMollerup.lean | 164 | 173 | theorem convexOn_log_Gamma : ConvexOn ℝ (Ioi 0) (log ∘ Gamma) := by |
refine convexOn_iff_forall_pos.mpr ⟨convex_Ioi _, fun x hx y hy a b ha hb hab => ?_⟩
have : b = 1 - a := by linarith
subst this
simp_rw [Function.comp_apply, smul_eq_mul]
simp only [mem_Ioi] at hx hy
rw [← log_rpow, ← log_rpow, ← log_mul]
· gcongr
exact Gamma_mul_add_mul_le_rpow_Gamma_mul_rpow_Gamma hx hy ha hb hab
all_goals positivity
|
/-
Copyright (c) 2020 Nicolò Cavalleri. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Nicolò Cavalleri, Andrew Yang
-/
import Mathlib.RingTheory.Adjoin.Basic
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.Derivative
#align_import ring_theory.derivation.basic from "leanprover-community/mathlib"@"b608348ffaeb7f557f2fd46876037abafd326ff3"
/-!
# Derivations
This file defines derivation. A derivation `D` from the `R`-algebra `A` to the `A`-module `M` is an
`R`-linear map that satisfy the Leibniz rule `D (a * b) = a * D b + D a * b`.
## Main results
- `Derivation`: The type of `R`-derivations from `A` to `M`. This has an `A`-module structure.
- `Derivation.llcomp`: We may compose linear maps and derivations to obtain a derivation,
and the composition is bilinear.
See `RingTheory.Derivation.Lie` for
- `derivation.lie_algebra`: The `R`-derivations from `A` to `A` form a lie algebra over `R`.
and `RingTheory.Derivation.ToSquareZero` for
- `derivation_to_square_zero_equiv_lift`: The `R`-derivations from `A` into a square-zero ideal `I`
of `B` corresponds to the lifts `A →ₐ[R] B` of the map `A →ₐ[R] B ⧸ I`.
## Future project
- Generalize derivations into bimodules.
-/
open Algebra
/-- `D : Derivation R A M` is an `R`-linear map from `A` to `M` that satisfies the `leibniz`
equality. We also require that `D 1 = 0`. See `Derivation.mk'` for a constructor that deduces this
assumption from the Leibniz rule when `M` is cancellative.
TODO: update this when bimodules are defined. -/
structure Derivation (R : Type*) (A : Type*) (M : Type*)
[CommSemiring R] [CommSemiring A] [AddCommMonoid M] [Algebra R A] [Module A M] [Module R M]
extends A →ₗ[R] M where
protected map_one_eq_zero' : toLinearMap 1 = 0
protected leibniz' (a b : A) : toLinearMap (a * b) = a • toLinearMap b + b • toLinearMap a
#align derivation Derivation
/-- The `LinearMap` underlying a `Derivation`. -/
add_decl_doc Derivation.toLinearMap
namespace Derivation
section
variable {R : Type*} {A : Type*} {B : Type*} {M : Type*}
variable [CommSemiring R] [CommSemiring A] [CommSemiring B] [AddCommMonoid M]
variable [Algebra R A] [Algebra R B]
variable [Module A M] [Module B M] [Module R M]
variable (D : Derivation R A M) {D1 D2 : Derivation R A M} (r : R) (a b : A)
instance : FunLike (Derivation R A M) A M where
coe D := D.toFun
coe_injective' D1 D2 h := by cases D1; cases D2; congr; exact DFunLike.coe_injective h
instance : AddMonoidHomClass (Derivation R A M) A M where
map_add D := D.toLinearMap.map_add'
map_zero D := D.toLinearMap.map_zero
-- Not a simp lemma because it can be proved via `coeFn_coe` + `toLinearMap_eq_coe`
theorem toFun_eq_coe : D.toFun = ⇑D :=
rfl
#align derivation.to_fun_eq_coe Derivation.toFun_eq_coe
/-- See Note [custom simps projection] -/
def Simps.apply (D : Derivation R A M) : A → M := D
initialize_simps_projections Derivation (toFun → apply)
attribute [coe] toLinearMap
instance hasCoeToLinearMap : Coe (Derivation R A M) (A →ₗ[R] M) :=
⟨fun D => D.toLinearMap⟩
#align derivation.has_coe_to_linear_map Derivation.hasCoeToLinearMap
#noalign derivation.to_linear_map_eq_coe -- Porting note: not needed anymore
@[simp]
theorem mk_coe (f : A →ₗ[R] M) (h₁ h₂) : ((⟨f, h₁, h₂⟩ : Derivation R A M) : A → M) = f :=
rfl
#align derivation.mk_coe Derivation.mk_coe
@[simp, norm_cast]
theorem coeFn_coe (f : Derivation R A M) : ⇑(f : A →ₗ[R] M) = f :=
rfl
#align derivation.coe_fn_coe Derivation.coeFn_coe
theorem coe_injective : @Function.Injective (Derivation R A M) (A → M) DFunLike.coe :=
DFunLike.coe_injective
#align derivation.coe_injective Derivation.coe_injective
@[ext]
theorem ext (H : ∀ a, D1 a = D2 a) : D1 = D2 :=
DFunLike.ext _ _ H
#align derivation.ext Derivation.ext
theorem congr_fun (h : D1 = D2) (a : A) : D1 a = D2 a :=
DFunLike.congr_fun h a
#align derivation.congr_fun Derivation.congr_fun
protected theorem map_add : D (a + b) = D a + D b :=
map_add D a b
#align derivation.map_add Derivation.map_add
protected theorem map_zero : D 0 = 0 :=
map_zero D
#align derivation.map_zero Derivation.map_zero
@[simp]
theorem map_smul : D (r • a) = r • D a :=
D.toLinearMap.map_smul r a
#align derivation.map_smul Derivation.map_smul
@[simp]
theorem leibniz : D (a * b) = a • D b + b • D a :=
D.leibniz' _ _
#align derivation.leibniz Derivation.leibniz
#noalign derivation.map_sum
@[simp]
theorem map_smul_of_tower {S : Type*} [SMul S A] [SMul S M] [LinearMap.CompatibleSMul A M S R]
(D : Derivation R A M) (r : S) (a : A) : D (r • a) = r • D a :=
D.toLinearMap.map_smul_of_tower r a
#align derivation.map_smul_of_tower Derivation.map_smul_of_tower
@[simp]
theorem map_one_eq_zero : D 1 = 0 :=
D.map_one_eq_zero'
#align derivation.map_one_eq_zero Derivation.map_one_eq_zero
@[simp]
theorem map_algebraMap : D (algebraMap R A r) = 0 := by
rw [← mul_one r, RingHom.map_mul, RingHom.map_one, ← smul_def, map_smul, map_one_eq_zero,
smul_zero]
#align derivation.map_algebra_map Derivation.map_algebraMap
@[simp]
theorem map_natCast (n : ℕ) : D (n : A) = 0 := by
rw [← nsmul_one, D.map_smul_of_tower n, map_one_eq_zero, smul_zero]
#align derivation.map_coe_nat Derivation.map_natCast
@[simp]
theorem leibniz_pow (n : ℕ) : D (a ^ n) = n • a ^ (n - 1) • D a := by
induction' n with n ihn
· rw [pow_zero, map_one_eq_zero, zero_smul]
· rcases (zero_le n).eq_or_lt with (rfl | hpos)
· erw [pow_one, one_smul, pow_zero, one_smul]
· have : a * a ^ (n - 1) = a ^ n := by rw [← pow_succ', Nat.sub_add_cancel hpos]
simp only [pow_succ', leibniz, ihn, smul_comm a n (_ : M), smul_smul a, add_smul, this,
Nat.succ_eq_add_one, Nat.add_succ_sub_one, add_zero, one_nsmul]
#align derivation.leibniz_pow Derivation.leibniz_pow
open Polynomial in
@[simp]
theorem map_aeval (P : R[X]) (x : A) :
D (aeval x P) = aeval x (derivative P) • D x := by
induction P using Polynomial.induction_on
· simp
· simp [add_smul, *]
· simp [mul_smul, nsmul_eq_smul_cast A]
theorem eqOn_adjoin {s : Set A} (h : Set.EqOn D1 D2 s) : Set.EqOn D1 D2 (adjoin R s) := fun x hx =>
Algebra.adjoin_induction hx h (fun r => (D1.map_algebraMap r).trans (D2.map_algebraMap r).symm)
(fun x y hx hy => by simp only [map_add, *]) fun x y hx hy => by simp only [leibniz, *]
#align derivation.eq_on_adjoin Derivation.eqOn_adjoin
/-- If adjoin of a set is the whole algebra, then any two derivations equal on this set are equal
on the whole algebra. -/
theorem ext_of_adjoin_eq_top (s : Set A) (hs : adjoin R s = ⊤) (h : Set.EqOn D1 D2 s) : D1 = D2 :=
ext fun _ => eqOn_adjoin h <| hs.symm ▸ trivial
#align derivation.ext_of_adjoin_eq_top Derivation.ext_of_adjoin_eq_top
-- Data typeclasses
instance : Zero (Derivation R A M) :=
⟨{ toLinearMap := 0
map_one_eq_zero' := rfl
leibniz' := fun a b => by simp only [add_zero, LinearMap.zero_apply, smul_zero] }⟩
@[simp]
theorem coe_zero : ⇑(0 : Derivation R A M) = 0 :=
rfl
#align derivation.coe_zero Derivation.coe_zero
@[simp]
theorem coe_zero_linearMap : ↑(0 : Derivation R A M) = (0 : A →ₗ[R] M) :=
rfl
#align derivation.coe_zero_linear_map Derivation.coe_zero_linearMap
theorem zero_apply (a : A) : (0 : Derivation R A M) a = 0 :=
rfl
#align derivation.zero_apply Derivation.zero_apply
instance : Add (Derivation R A M) :=
⟨fun D1 D2 =>
{ toLinearMap := D1 + D2
map_one_eq_zero' := by simp
leibniz' := fun a b => by
simp only [leibniz, LinearMap.add_apply, coeFn_coe, smul_add, add_add_add_comm] }⟩
@[simp]
theorem coe_add (D1 D2 : Derivation R A M) : ⇑(D1 + D2) = D1 + D2 :=
rfl
#align derivation.coe_add Derivation.coe_add
@[simp]
theorem coe_add_linearMap (D1 D2 : Derivation R A M) : ↑(D1 + D2) = (D1 + D2 : A →ₗ[R] M) :=
rfl
#align derivation.coe_add_linear_map Derivation.coe_add_linearMap
theorem add_apply : (D1 + D2) a = D1 a + D2 a :=
rfl
#align derivation.add_apply Derivation.add_apply
instance : Inhabited (Derivation R A M) :=
⟨0⟩
section Scalar
variable {S T : Type*}
variable [Monoid S] [DistribMulAction S M] [SMulCommClass R S M] [SMulCommClass S A M]
variable [Monoid T] [DistribMulAction T M] [SMulCommClass R T M] [SMulCommClass T A M]
instance : SMul S (Derivation R A M) :=
⟨fun r D =>
{ toLinearMap := r • D.1
map_one_eq_zero' := by rw [LinearMap.smul_apply, coeFn_coe, D.map_one_eq_zero, smul_zero]
leibniz' := fun a b => by simp only [LinearMap.smul_apply, coeFn_coe, leibniz, smul_add,
smul_comm r (_ : A) (_ : M)] }⟩
@[simp]
theorem coe_smul (r : S) (D : Derivation R A M) : ⇑(r • D) = r • ⇑D :=
rfl
#align derivation.coe_smul Derivation.coe_smul
@[simp]
theorem coe_smul_linearMap (r : S) (D : Derivation R A M) : ↑(r • D) = r • (D : A →ₗ[R] M) :=
rfl
#align derivation.coe_smul_linear_map Derivation.coe_smul_linearMap
theorem smul_apply (r : S) (D : Derivation R A M) : (r • D) a = r • D a :=
rfl
#align derivation.smul_apply Derivation.smul_apply
instance : AddCommMonoid (Derivation R A M) :=
coe_injective.addCommMonoid _ coe_zero coe_add fun _ _ => rfl
/-- `coe_fn` as an `AddMonoidHom`. -/
def coeFnAddMonoidHom : Derivation R A M →+ A → M where
toFun := (↑)
map_zero' := coe_zero
map_add' := coe_add
#align derivation.coe_fn_add_monoid_hom Derivation.coeFnAddMonoidHom
instance : DistribMulAction S (Derivation R A M) :=
Function.Injective.distribMulAction coeFnAddMonoidHom coe_injective coe_smul
instance [DistribMulAction Sᵐᵒᵖ M] [IsCentralScalar S M] :
IsCentralScalar S (Derivation R A M) where
op_smul_eq_smul _ _ := ext fun _ => op_smul_eq_smul _ _
instance [SMul S T] [IsScalarTower S T M] : IsScalarTower S T (Derivation R A M) :=
⟨fun _ _ _ => ext fun _ => smul_assoc _ _ _⟩
instance [SMulCommClass S T M] : SMulCommClass S T (Derivation R A M) :=
⟨fun _ _ _ => ext fun _ => smul_comm _ _ _⟩
end Scalar
instance instModule {S : Type*} [Semiring S] [Module S M] [SMulCommClass R S M]
[SMulCommClass S A M] : Module S (Derivation R A M) :=
Function.Injective.module S coeFnAddMonoidHom coe_injective coe_smul
section PushForward
variable {N : Type*} [AddCommMonoid N] [Module A N] [Module R N] [IsScalarTower R A M]
[IsScalarTower R A N]
variable (f : M →ₗ[A] N) (e : M ≃ₗ[A] N)
/-- We can push forward derivations using linear maps, i.e., the composition of a derivation with a
linear map is a derivation. Furthermore, this operation is linear on the spaces of derivations. -/
def _root_.LinearMap.compDer : Derivation R A M →ₗ[R] Derivation R A N where
toFun D :=
{ toLinearMap := (f : M →ₗ[R] N).comp (D : A →ₗ[R] M)
map_one_eq_zero' := by simp only [LinearMap.comp_apply, coeFn_coe, map_one_eq_zero, map_zero]
leibniz' := fun a b => by
simp only [coeFn_coe, LinearMap.comp_apply, LinearMap.map_add, leibniz,
LinearMap.coe_restrictScalars, LinearMap.map_smul] }
map_add' D₁ D₂ := by ext; exact LinearMap.map_add _ _ _
map_smul' r D := by dsimp; ext; exact LinearMap.map_smul (f : M →ₗ[R] N) _ _
#align linear_map.comp_der LinearMap.compDer
@[simp]
theorem coe_to_linearMap_comp : (f.compDer D : A →ₗ[R] N) = (f : M →ₗ[R] N).comp (D : A →ₗ[R] M) :=
rfl
#align derivation.coe_to_linear_map_comp Derivation.coe_to_linearMap_comp
@[simp]
theorem coe_comp : (f.compDer D : A → N) = (f : M →ₗ[R] N).comp (D : A →ₗ[R] M) :=
rfl
#align derivation.coe_comp Derivation.coe_comp
/-- The composition of a derivation with a linear map as a bilinear map -/
@[simps]
def llcomp : (M →ₗ[A] N) →ₗ[A] Derivation R A M →ₗ[R] Derivation R A N where
toFun f := f.compDer
map_add' f₁ f₂ := by ext; rfl
map_smul' r D := by ext; rfl
#align derivation.llcomp Derivation.llcomp
/-- Pushing a derivation forward through a linear equivalence is an equivalence. -/
def _root_.LinearEquiv.compDer : Derivation R A M ≃ₗ[R] Derivation R A N :=
{ e.toLinearMap.compDer with
invFun := e.symm.toLinearMap.compDer
left_inv := fun D => by ext a; exact e.symm_apply_apply (D a)
right_inv := fun D => by ext a; exact e.apply_symm_apply (D a) }
#align linear_equiv.comp_der LinearEquiv.compDer
end PushForward
variable (A) in
/-- For a tower `R → A → B` and an `R`-derivation `B → M`, we may compose with `A → B` to obtain an
`R`-derivation `A → M`. -/
@[simps!]
def compAlgebraMap [Algebra A B] [IsScalarTower R A B] [IsScalarTower A B M]
(d : Derivation R B M) : Derivation R A M where
map_one_eq_zero' := by simp
leibniz' a b := by simp
toLinearMap := d.toLinearMap.comp (IsScalarTower.toAlgHom R A B).toLinearMap
#align derivation.comp_algebra_map Derivation.compAlgebraMap
section RestrictScalars
variable {S : Type*} [CommSemiring S]
variable [Algebra S A] [Module S M] [LinearMap.CompatibleSMul A M R S]
variable (R)
/-- If `A` is both an `R`-algebra and an `S`-algebra; `M` is both an `R`-module and an `S`-module,
then an `S`-derivation `A → M` is also an `R`-derivation if it is also `R`-linear. -/
protected def restrictScalars (d : Derivation S A M) : Derivation R A M where
map_one_eq_zero' := d.map_one_eq_zero
leibniz' := d.leibniz
toLinearMap := d.toLinearMap.restrictScalars R
#align derivation.restrict_scalars Derivation.restrictScalars
end RestrictScalars
end
section Cancel
variable {R : Type*} [CommSemiring R] {A : Type*} [CommSemiring A] [Algebra R A] {M : Type*}
[AddCancelCommMonoid M] [Module R M] [Module A M]
/-- Define `Derivation R A M` from a linear map when `M` is cancellative by verifying the Leibniz
rule. -/
def mk' (D : A →ₗ[R] M) (h : ∀ a b, D (a * b) = a • D b + b • D a) : Derivation R A M where
toLinearMap := D
map_one_eq_zero' := add_right_eq_self.1 <| by simpa only [one_smul, one_mul] using (h 1 1).symm
leibniz' := h
#align derivation.mk' Derivation.mk'
@[simp]
theorem coe_mk' (D : A →ₗ[R] M) (h) : ⇑(mk' D h) = D :=
rfl
#align derivation.coe_mk' Derivation.coe_mk'
@[simp]
theorem coe_mk'_linearMap (D : A →ₗ[R] M) (h) : (mk' D h : A →ₗ[R] M) = D :=
rfl
#align derivation.coe_mk'_linear_map Derivation.coe_mk'_linearMap
end Cancel
section
variable {R : Type*} [CommRing R]
variable {A : Type*} [CommRing A] [Algebra R A]
section
variable {M : Type*} [AddCommGroup M] [Module A M] [Module R M]
variable (D : Derivation R A M) {D1 D2 : Derivation R A M} (r : R) (a b : A)
protected theorem map_neg : D (-a) = -D a :=
map_neg D a
#align derivation.map_neg Derivation.map_neg
protected theorem map_sub : D (a - b) = D a - D b :=
map_sub D a b
#align derivation.map_sub Derivation.map_sub
@[simp]
| Mathlib/RingTheory/Derivation/Basic.lean | 409 | 410 | theorem map_intCast (n : ℤ) : D (n : A) = 0 := by |
rw [← zsmul_one, D.map_smul_of_tower n, map_one_eq_zero, smul_zero]
|
/-
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.Analysis.BoxIntegral.Partition.Basic
#align_import analysis.box_integral.partition.split from "leanprover-community/mathlib"@"6ca1a09bc9aa75824bf97388c9e3b441fc4ccf3f"
/-!
# Split a box along one or more hyperplanes
## Main definitions
A hyperplane `{x : ι → ℝ | x i = a}` splits a rectangular box `I : BoxIntegral.Box ι` into two
smaller boxes. If `a ∉ Ioo (I.lower i, I.upper i)`, then one of these boxes is empty, so it is not a
box in the sense of `BoxIntegral.Box`.
We introduce the following definitions.
* `BoxIntegral.Box.splitLower I i a` and `BoxIntegral.Box.splitUpper I i a` are these boxes (as
`WithBot (BoxIntegral.Box ι)`);
* `BoxIntegral.Prepartition.split I i a` is the partition of `I` made of these two boxes (or of one
box `I` if one of these boxes is empty);
* `BoxIntegral.Prepartition.splitMany I s`, where `s : Finset (ι × ℝ)` is a finite set of
hyperplanes `{x : ι → ℝ | x i = a}` encoded as pairs `(i, a)`, is the partition of `I` made by
cutting it along all the hyperplanes in `s`.
## Main results
The main result `BoxIntegral.Prepartition.exists_iUnion_eq_diff` says that any prepartition `π` of
`I` admits a prepartition `π'` of `I` that covers exactly `I \ π.iUnion`. One of these prepartitions
is available as `BoxIntegral.Prepartition.compl`.
## Tags
rectangular box, partition, hyperplane
-/
noncomputable section
open scoped Classical
open Filter
open Function Set Filter
namespace BoxIntegral
variable {ι M : Type*} {n : ℕ}
namespace Box
variable {I : Box ι} {i : ι} {x : ℝ} {y : ι → ℝ}
/-- Given a box `I` and `x ∈ (I.lower i, I.upper i)`, the hyperplane `{y : ι → ℝ | y i = x}` splits
`I` into two boxes. `BoxIntegral.Box.splitLower I i x` is the box `I ∩ {y | y i ≤ x}`
(if it is nonempty). As usual, we represent a box that may be empty as
`WithBot (BoxIntegral.Box ι)`. -/
def splitLower (I : Box ι) (i : ι) (x : ℝ) : WithBot (Box ι) :=
mk' I.lower (update I.upper i (min x (I.upper i)))
#align box_integral.box.split_lower BoxIntegral.Box.splitLower
@[simp]
theorem coe_splitLower : (splitLower I i x : Set (ι → ℝ)) = ↑I ∩ { y | y i ≤ x } := by
rw [splitLower, coe_mk']
ext y
simp only [mem_univ_pi, mem_Ioc, mem_inter_iff, mem_coe, mem_setOf_eq, forall_and, ← Pi.le_def,
le_update_iff, le_min_iff, and_assoc, and_forall_ne (p := fun j => y j ≤ upper I j) i, mem_def]
rw [and_comm (a := y i ≤ x)]
#align box_integral.box.coe_split_lower BoxIntegral.Box.coe_splitLower
theorem splitLower_le : I.splitLower i x ≤ I :=
withBotCoe_subset_iff.1 <| by simp
#align box_integral.box.split_lower_le BoxIntegral.Box.splitLower_le
@[simp]
theorem splitLower_eq_bot {i x} : I.splitLower i x = ⊥ ↔ x ≤ I.lower i := by
rw [splitLower, mk'_eq_bot, exists_update_iff I.upper fun j y => y ≤ I.lower j]
simp [(I.lower_lt_upper _).not_le]
#align box_integral.box.split_lower_eq_bot BoxIntegral.Box.splitLower_eq_bot
@[simp]
theorem splitLower_eq_self : I.splitLower i x = I ↔ I.upper i ≤ x := by
simp [splitLower, update_eq_iff]
#align box_integral.box.split_lower_eq_self BoxIntegral.Box.splitLower_eq_self
| Mathlib/Analysis/BoxIntegral/Partition/Split.lean | 88 | 94 | theorem splitLower_def [DecidableEq ι] {i x} (h : x ∈ Ioo (I.lower i) (I.upper i))
(h' : ∀ j, I.lower j < update I.upper i x j :=
(forall_update_iff I.upper fun j y => I.lower j < y).2
⟨h.1, fun j _ => I.lower_lt_upper _⟩) :
I.splitLower i x = (⟨I.lower, update I.upper i x, h'⟩ : Box ι) := by |
simp (config := { unfoldPartialApp := true }) only [splitLower, mk'_eq_coe, min_eq_left h.2.le,
update, and_self]
|
/-
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]
| Mathlib/CategoryTheory/Monoidal/Rigid/Basic.lean | 206 | 207 | theorem leftAdjointMate_id {X : C} [HasLeftDual X] : (ᘁ(𝟙 X)) = 𝟙 (ᘁX) := by |
simp [leftAdjointMate]
|
/-
Copyright (c) 2022 Moritz Doll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Moritz Doll
-/
import Mathlib.Algebra.Polynomial.Module.Basic
import Mathlib.Analysis.Calculus.Deriv.Pow
import Mathlib.Analysis.Calculus.IteratedDeriv.Defs
import Mathlib.Analysis.Calculus.MeanValue
#align_import analysis.calculus.taylor from "leanprover-community/mathlib"@"3a69562db5a458db8322b190ec8d9a8bbd8a5b14"
/-!
# Taylor's theorem
This file defines the Taylor polynomial of a real function `f : ℝ → E`,
where `E` is a normed vector space over `ℝ` and proves Taylor's theorem,
which states that if `f` is sufficiently smooth, then
`f` can be approximated by the Taylor polynomial up to an explicit error term.
## Main definitions
* `taylorCoeffWithin`: the Taylor coefficient using `iteratedDerivWithin`
* `taylorWithin`: the Taylor polynomial using `iteratedDerivWithin`
## Main statements
* `taylor_mean_remainder`: Taylor's theorem with the general form of the remainder term
* `taylor_mean_remainder_lagrange`: Taylor's theorem with the Lagrange remainder
* `taylor_mean_remainder_cauchy`: Taylor's theorem with the Cauchy remainder
* `exists_taylor_mean_remainder_bound`: Taylor's theorem for vector valued functions with a
polynomial bound on the remainder
## TODO
* the Peano form of the remainder
* the integral form of the remainder
* Generalization to higher dimensions
## Tags
Taylor polynomial, Taylor's theorem
-/
open scoped Interval Topology Nat
open Set
variable {𝕜 E F : Type*}
variable [NormedAddCommGroup E] [NormedSpace ℝ E]
/-- The `k`th coefficient of the Taylor polynomial. -/
noncomputable def taylorCoeffWithin (f : ℝ → E) (k : ℕ) (s : Set ℝ) (x₀ : ℝ) : E :=
(k ! : ℝ)⁻¹ • iteratedDerivWithin k f s x₀
#align taylor_coeff_within taylorCoeffWithin
/-- The Taylor polynomial with derivatives inside of a set `s`.
The Taylor polynomial is given by
$$∑_{k=0}^n \frac{(x - x₀)^k}{k!} f^{(k)}(x₀),$$
where $f^{(k)}(x₀)$ denotes the iterated derivative in the set `s`. -/
noncomputable def taylorWithin (f : ℝ → E) (n : ℕ) (s : Set ℝ) (x₀ : ℝ) : PolynomialModule ℝ E :=
(Finset.range (n + 1)).sum fun k =>
PolynomialModule.comp (Polynomial.X - Polynomial.C x₀)
(PolynomialModule.single ℝ k (taylorCoeffWithin f k s x₀))
#align taylor_within taylorWithin
/-- The Taylor polynomial with derivatives inside of a set `s` considered as a function `ℝ → E`-/
noncomputable def taylorWithinEval (f : ℝ → E) (n : ℕ) (s : Set ℝ) (x₀ x : ℝ) : E :=
PolynomialModule.eval x (taylorWithin f n s x₀)
#align taylor_within_eval taylorWithinEval
theorem taylorWithin_succ (f : ℝ → E) (n : ℕ) (s : Set ℝ) (x₀ : ℝ) :
taylorWithin f (n + 1) s x₀ = taylorWithin f n s x₀ +
PolynomialModule.comp (Polynomial.X - Polynomial.C x₀)
(PolynomialModule.single ℝ (n + 1) (taylorCoeffWithin f (n + 1) s x₀)) := by
dsimp only [taylorWithin]
rw [Finset.sum_range_succ]
#align taylor_within_succ taylorWithin_succ
@[simp]
theorem taylorWithinEval_succ (f : ℝ → E) (n : ℕ) (s : Set ℝ) (x₀ x : ℝ) :
taylorWithinEval f (n + 1) s x₀ x = taylorWithinEval f n s x₀ x +
(((n + 1 : ℝ) * n !)⁻¹ * (x - x₀) ^ (n + 1)) • iteratedDerivWithin (n + 1) f s x₀ := by
simp_rw [taylorWithinEval, taylorWithin_succ, LinearMap.map_add, PolynomialModule.comp_eval]
congr
simp only [Polynomial.eval_sub, Polynomial.eval_X, Polynomial.eval_C,
PolynomialModule.eval_single, mul_inv_rev]
dsimp only [taylorCoeffWithin]
rw [← mul_smul, mul_comm, Nat.factorial_succ, Nat.cast_mul, Nat.cast_add, Nat.cast_one,
mul_inv_rev]
#align taylor_within_eval_succ taylorWithinEval_succ
/-- The Taylor polynomial of order zero evaluates to `f x`. -/
@[simp]
theorem taylor_within_zero_eval (f : ℝ → E) (s : Set ℝ) (x₀ x : ℝ) :
taylorWithinEval f 0 s x₀ x = f x₀ := by
dsimp only [taylorWithinEval]
dsimp only [taylorWithin]
dsimp only [taylorCoeffWithin]
simp
#align taylor_within_zero_eval taylor_within_zero_eval
/-- Evaluating the Taylor polynomial at `x = x₀` yields `f x`. -/
@[simp]
theorem taylorWithinEval_self (f : ℝ → E) (n : ℕ) (s : Set ℝ) (x₀ : ℝ) :
taylorWithinEval f n s x₀ x₀ = f x₀ := by
induction' n with k hk
· exact taylor_within_zero_eval _ _ _ _
simp [hk]
#align taylor_within_eval_self taylorWithinEval_self
theorem taylor_within_apply (f : ℝ → E) (n : ℕ) (s : Set ℝ) (x₀ x : ℝ) :
taylorWithinEval f n s x₀ x =
∑ k ∈ Finset.range (n + 1), ((k ! : ℝ)⁻¹ * (x - x₀) ^ k) • iteratedDerivWithin k f s x₀ := by
induction' n with k hk
· simp
rw [taylorWithinEval_succ, Finset.sum_range_succ, hk]
simp [Nat.factorial]
#align taylor_within_apply taylor_within_apply
/-- If `f` is `n` times continuous differentiable on a set `s`, then the Taylor polynomial
`taylorWithinEval f n s x₀ x` is continuous in `x₀`. -/
theorem continuousOn_taylorWithinEval {f : ℝ → E} {x : ℝ} {n : ℕ} {s : Set ℝ}
(hs : UniqueDiffOn ℝ s) (hf : ContDiffOn ℝ n f s) :
ContinuousOn (fun t => taylorWithinEval f n s t x) s := by
simp_rw [taylor_within_apply]
refine continuousOn_finset_sum (Finset.range (n + 1)) fun i hi => ?_
refine (continuousOn_const.mul ((continuousOn_const.sub continuousOn_id).pow _)).smul ?_
rw [contDiffOn_iff_continuousOn_differentiableOn_deriv hs] at hf
cases' hf with hf_left
specialize hf_left i
simp only [Finset.mem_range] at hi
refine hf_left ?_
simp only [WithTop.coe_le_coe, Nat.cast_le, Nat.lt_succ_iff.mp hi]
#align continuous_on_taylor_within_eval continuousOn_taylorWithinEval
/-- Helper lemma for calculating the derivative of the monomial that appears in Taylor
expansions. -/
theorem monomial_has_deriv_aux (t x : ℝ) (n : ℕ) :
HasDerivAt (fun y => (x - y) ^ (n + 1)) (-(n + 1) * (x - t) ^ n) t := by
simp_rw [sub_eq_neg_add]
rw [← neg_one_mul, mul_comm (-1 : ℝ), mul_assoc, mul_comm (-1 : ℝ), ← mul_assoc]
convert HasDerivAt.pow (n + 1) ((hasDerivAt_id t).neg.add_const x)
simp only [Nat.cast_add, Nat.cast_one]
#align monomial_has_deriv_aux monomial_has_deriv_aux
theorem hasDerivWithinAt_taylor_coeff_within {f : ℝ → E} {x y : ℝ} {k : ℕ} {s t : Set ℝ}
(ht : UniqueDiffWithinAt ℝ t y) (hs : s ∈ 𝓝[t] y)
(hf : DifferentiableWithinAt ℝ (iteratedDerivWithin (k + 1) f s) s y) :
HasDerivWithinAt
(fun z => (((k + 1 : ℝ) * k !)⁻¹ * (x - z) ^ (k + 1)) • iteratedDerivWithin (k + 1) f s z)
((((k + 1 : ℝ) * k !)⁻¹ * (x - y) ^ (k + 1)) • iteratedDerivWithin (k + 2) f s y -
((k ! : ℝ)⁻¹ * (x - y) ^ k) • iteratedDerivWithin (k + 1) f s y) t y := by
replace hf :
HasDerivWithinAt (iteratedDerivWithin (k + 1) f s) (iteratedDerivWithin (k + 2) f s y) t y := by
convert (hf.mono_of_mem hs).hasDerivWithinAt using 1
rw [iteratedDerivWithin_succ (ht.mono_nhds (nhdsWithin_le_iff.mpr hs))]
exact (derivWithin_of_mem hs ht hf).symm
have : HasDerivWithinAt (fun t => ((k + 1 : ℝ) * k !)⁻¹ * (x - t) ^ (k + 1))
(-((k ! : ℝ)⁻¹ * (x - y) ^ k)) t y := by
-- Commuting the factors:
have : -((k ! : ℝ)⁻¹ * (x - y) ^ k) = ((k + 1 : ℝ) * k !)⁻¹ * (-(k + 1) * (x - y) ^ k) := by
field_simp; ring
rw [this]
exact (monomial_has_deriv_aux y x _).hasDerivWithinAt.const_mul _
convert this.smul hf using 1
field_simp
rw [neg_div, neg_smul, sub_eq_add_neg]
#align has_deriv_within_at_taylor_coeff_within hasDerivWithinAt_taylor_coeff_within
/-- Calculate the derivative of the Taylor polynomial with respect to `x₀`.
Version for arbitrary sets -/
theorem hasDerivWithinAt_taylorWithinEval {f : ℝ → E} {x y : ℝ} {n : ℕ} {s s' : Set ℝ}
(hs'_unique : UniqueDiffWithinAt ℝ s' y) (hs_unique : UniqueDiffOn ℝ s) (hs' : s' ∈ 𝓝[s] y)
(hy : y ∈ s') (h : s' ⊆ s) (hf : ContDiffOn ℝ n f s)
(hf' : DifferentiableWithinAt ℝ (iteratedDerivWithin n f s) s y) :
HasDerivWithinAt (fun t => taylorWithinEval f n s t x)
(((n ! : ℝ)⁻¹ * (x - y) ^ n) • iteratedDerivWithin (n + 1) f s y) s' y := by
induction' n with k hk
· simp only [taylor_within_zero_eval, Nat.factorial_zero, Nat.cast_one, inv_one, pow_zero,
mul_one, zero_add, one_smul]
simp only [iteratedDerivWithin_zero] at hf'
rw [iteratedDerivWithin_one (hs_unique _ (h hy))]
exact hf'.hasDerivWithinAt.mono h
simp_rw [Nat.add_succ, taylorWithinEval_succ]
simp only [add_zero, Nat.factorial_succ, Nat.cast_mul, Nat.cast_add, Nat.cast_one]
have coe_lt_succ : (k : WithTop ℕ) < k.succ := Nat.cast_lt.2 k.lt_succ_self
have hdiff : DifferentiableOn ℝ (iteratedDerivWithin k f s) s' :=
(hf.differentiableOn_iteratedDerivWithin coe_lt_succ hs_unique).mono h
specialize hk hf.of_succ ((hdiff y hy).mono_of_mem hs')
convert hk.add (hasDerivWithinAt_taylor_coeff_within hs'_unique
(nhdsWithin_mono _ h self_mem_nhdsWithin) hf') using 1
exact (add_sub_cancel _ _).symm
#align has_deriv_within_at_taylor_within_eval hasDerivWithinAt_taylorWithinEval
/-- Calculate the derivative of the Taylor polynomial with respect to `x₀`.
Version for open intervals -/
theorem taylorWithinEval_hasDerivAt_Ioo {f : ℝ → E} {a b t : ℝ} (x : ℝ) {n : ℕ} (hx : a < b)
(ht : t ∈ Ioo a b) (hf : ContDiffOn ℝ n f (Icc a b))
(hf' : DifferentiableOn ℝ (iteratedDerivWithin n f (Icc a b)) (Ioo a b)) :
HasDerivAt (fun y => taylorWithinEval f n (Icc a b) y x)
(((n ! : ℝ)⁻¹ * (x - t) ^ n) • iteratedDerivWithin (n + 1) f (Icc a b) t) t :=
have h_nhds : Ioo a b ∈ 𝓝 t := isOpen_Ioo.mem_nhds ht
have h_nhds' : Ioo a b ∈ 𝓝[Icc a b] t := nhdsWithin_le_nhds h_nhds
(hasDerivWithinAt_taylorWithinEval (uniqueDiffWithinAt_Ioo ht) (uniqueDiffOn_Icc hx) h_nhds' ht
Ioo_subset_Icc_self hf <| (hf' t ht).mono_of_mem h_nhds').hasDerivAt h_nhds
#align taylor_within_eval_has_deriv_at_Ioo taylorWithinEval_hasDerivAt_Ioo
/-- Calculate the derivative of the Taylor polynomial with respect to `x₀`.
Version for closed intervals -/
theorem hasDerivWithinAt_taylorWithinEval_at_Icc {f : ℝ → E} {a b t : ℝ} (x : ℝ) {n : ℕ}
(hx : a < b) (ht : t ∈ Icc a b) (hf : ContDiffOn ℝ n f (Icc a b))
(hf' : DifferentiableOn ℝ (iteratedDerivWithin n f (Icc a b)) (Icc a b)) :
HasDerivWithinAt (fun y => taylorWithinEval f n (Icc a b) y x)
(((n ! : ℝ)⁻¹ * (x - t) ^ n) • iteratedDerivWithin (n + 1) f (Icc a b) t) (Icc a b) t :=
hasDerivWithinAt_taylorWithinEval (uniqueDiffOn_Icc hx t ht) (uniqueDiffOn_Icc hx)
self_mem_nhdsWithin ht rfl.subset hf (hf' t ht)
#align has_deriv_within_taylor_within_eval_at_Icc hasDerivWithinAt_taylorWithinEval_at_Icc
/-! ### Taylor's theorem with mean value type remainder estimate -/
/-- **Taylor's theorem** with the general mean value form of the remainder.
We assume that `f` is `n+1`-times continuously differentiable in the closed set `Icc x₀ x` and
`n+1`-times differentiable on the open set `Ioo x₀ x`, and `g` is a differentiable function on
`Ioo x₀ x` and continuous on `Icc x₀ x`. Then there exists an `x' ∈ Ioo x₀ x` such that
$$f(x) - (P_n f)(x₀, x) = \frac{(x - x')^n}{n!} \frac{g(x) - g(x₀)}{g' x'},$$
where $P_n f$ denotes the Taylor polynomial of degree $n$. -/
theorem taylor_mean_remainder {f : ℝ → ℝ} {g g' : ℝ → ℝ} {x x₀ : ℝ} {n : ℕ} (hx : x₀ < x)
(hf : ContDiffOn ℝ n f (Icc x₀ x))
(hf' : DifferentiableOn ℝ (iteratedDerivWithin n f (Icc x₀ x)) (Ioo x₀ x))
(gcont : ContinuousOn g (Icc x₀ x))
(gdiff : ∀ x_1 : ℝ, x_1 ∈ Ioo x₀ x → HasDerivAt g (g' x_1) x_1)
(g'_ne : ∀ x_1 : ℝ, x_1 ∈ Ioo x₀ x → g' x_1 ≠ 0) :
∃ x' ∈ Ioo x₀ x, f x - taylorWithinEval f n (Icc x₀ x) x₀ x =
((x - x') ^ n / n ! * (g x - g x₀) / g' x') • iteratedDerivWithin (n + 1) f (Icc x₀ x) x' := by
-- We apply the mean value theorem
rcases exists_ratio_hasDerivAt_eq_ratio_slope (fun t => taylorWithinEval f n (Icc x₀ x) t x)
(fun t => ((n ! : ℝ)⁻¹ * (x - t) ^ n) • iteratedDerivWithin (n + 1) f (Icc x₀ x) t) hx
(continuousOn_taylorWithinEval (uniqueDiffOn_Icc hx) hf)
(fun _ hy => taylorWithinEval_hasDerivAt_Ioo x hx hy hf hf') g g' gcont gdiff with ⟨y, hy, h⟩
use y, hy
-- The rest is simplifications and trivial calculations
simp only [taylorWithinEval_self] at h
rw [mul_comm, ← div_left_inj' (g'_ne y hy), mul_div_cancel_right₀ _ (g'_ne y hy)] at h
rw [← h]
field_simp [g'_ne y hy]
ring
#align taylor_mean_remainder taylor_mean_remainder
/-- **Taylor's theorem** with the Lagrange form of the remainder.
We assume that `f` is `n+1`-times continuously differentiable in the closed set `Icc x₀ x` and
`n+1`-times differentiable on the open set `Ioo x₀ x`. Then there exists an `x' ∈ Ioo x₀ x` such
that $$f(x) - (P_n f)(x₀, x) = \frac{f^{(n+1)}(x') (x - x₀)^{n+1}}{(n+1)!},$$
where $P_n f$ denotes the Taylor polynomial of degree $n$ and $f^{(n+1)}$ is the $n+1$-th iterated
derivative. -/
theorem taylor_mean_remainder_lagrange {f : ℝ → ℝ} {x x₀ : ℝ} {n : ℕ} (hx : x₀ < x)
(hf : ContDiffOn ℝ n f (Icc x₀ x))
(hf' : DifferentiableOn ℝ (iteratedDerivWithin n f (Icc x₀ x)) (Ioo x₀ x)) :
∃ x' ∈ Ioo x₀ x, f x - taylorWithinEval f n (Icc x₀ x) x₀ x =
iteratedDerivWithin (n + 1) f (Icc x₀ x) x' * (x - x₀) ^ (n + 1) / (n + 1)! := by
have gcont : ContinuousOn (fun t : ℝ => (x - t) ^ (n + 1)) (Icc x₀ x) := by
refine Continuous.continuousOn ?_
exact (continuous_const.sub continuous_id').pow _ -- Porting note: was `continuity`
have xy_ne : ∀ y : ℝ, y ∈ Ioo x₀ x → (x - y) ^ n ≠ 0 := by
intro y hy
refine pow_ne_zero _ ?_
rw [mem_Ioo] at hy
rw [sub_ne_zero]
exact hy.2.ne'
have hg' : ∀ y : ℝ, y ∈ Ioo x₀ x → -(↑n + 1) * (x - y) ^ n ≠ 0 := fun y hy =>
mul_ne_zero (neg_ne_zero.mpr (Nat.cast_add_one_ne_zero n)) (xy_ne y hy)
-- We apply the general theorem with g(t) = (x - t)^(n+1)
rcases taylor_mean_remainder hx hf hf' gcont (fun y _ => monomial_has_deriv_aux y x _) hg' with
⟨y, hy, h⟩
use y, hy
simp only [sub_self, zero_pow, Ne, Nat.succ_ne_zero, not_false_iff, zero_sub, mul_neg] at h
rw [h, neg_div, ← div_neg, neg_mul, neg_neg]
field_simp [xy_ne y hy, Nat.factorial]; ring
#align taylor_mean_remainder_lagrange taylor_mean_remainder_lagrange
/-- **Taylor's theorem** with the Cauchy form of the remainder.
We assume that `f` is `n+1`-times continuously differentiable on the closed set `Icc x₀ x` and
`n+1`-times differentiable on the open set `Ioo x₀ x`. Then there exists an `x' ∈ Ioo x₀ x` such
that $$f(x) - (P_n f)(x₀, x) = \frac{f^{(n+1)}(x') (x - x')^n (x-x₀)}{n!},$$
where $P_n f$ denotes the Taylor polynomial of degree $n$ and $f^{(n+1)}$ is the $n+1$-th iterated
derivative. -/
| Mathlib/Analysis/Calculus/Taylor.lean | 296 | 309 | theorem taylor_mean_remainder_cauchy {f : ℝ → ℝ} {x x₀ : ℝ} {n : ℕ} (hx : x₀ < x)
(hf : ContDiffOn ℝ n f (Icc x₀ x))
(hf' : DifferentiableOn ℝ (iteratedDerivWithin n f (Icc x₀ x)) (Ioo x₀ x)) :
∃ x' ∈ Ioo x₀ x, f x - taylorWithinEval f n (Icc x₀ x) x₀ x =
iteratedDerivWithin (n + 1) f (Icc x₀ x) x' * (x - x') ^ n / n ! * (x - x₀) := by |
have gcont : ContinuousOn id (Icc x₀ x) := Continuous.continuousOn (by continuity)
have gdiff : ∀ x_1 : ℝ, x_1 ∈ Ioo x₀ x → HasDerivAt id ((fun _ : ℝ => (1 : ℝ)) x_1) x_1 :=
fun _ _ => hasDerivAt_id _
-- We apply the general theorem with g = id
rcases taylor_mean_remainder hx hf hf' gcont gdiff fun _ _ => by simp with ⟨y, hy, h⟩
use y, hy
rw [h]
field_simp [n.factorial_ne_zero]
ring
|
/-
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.Topology.Order.MonotoneContinuity
import Mathlib.Topology.Algebra.Order.LiminfLimsup
import Mathlib.Topology.Instances.NNReal
import Mathlib.Topology.EMetricSpace.Lipschitz
import Mathlib.Topology.Metrizable.Basic
import Mathlib.Topology.Order.T5
#align_import topology.instances.ennreal from "leanprover-community/mathlib"@"ec4b2eeb50364487f80421c0b4c41328a611f30d"
/-!
# Topology on extended non-negative reals
-/
noncomputable section
open Set Filter Metric Function
open scoped Classical Topology ENNReal NNReal Filter
variable {α : Type*} {β : Type*} {γ : Type*}
namespace ENNReal
variable {a b c d : ℝ≥0∞} {r p q : ℝ≥0} {x y z : ℝ≥0∞} {ε ε₁ ε₂ : ℝ≥0∞} {s : Set ℝ≥0∞}
section TopologicalSpace
open TopologicalSpace
/-- Topology on `ℝ≥0∞`.
Note: this is different from the `EMetricSpace` topology. The `EMetricSpace` topology has
`IsOpen {∞}`, while this topology doesn't have singleton elements. -/
instance : TopologicalSpace ℝ≥0∞ := Preorder.topology ℝ≥0∞
instance : OrderTopology ℝ≥0∞ := ⟨rfl⟩
-- short-circuit type class inference
instance : T2Space ℝ≥0∞ := inferInstance
instance : T5Space ℝ≥0∞ := inferInstance
instance : T4Space ℝ≥0∞ := inferInstance
instance : SecondCountableTopology ℝ≥0∞ :=
orderIsoUnitIntervalBirational.toHomeomorph.embedding.secondCountableTopology
instance : MetrizableSpace ENNReal :=
orderIsoUnitIntervalBirational.toHomeomorph.embedding.metrizableSpace
theorem embedding_coe : Embedding ((↑) : ℝ≥0 → ℝ≥0∞) :=
coe_strictMono.embedding_of_ordConnected <| by rw [range_coe']; exact ordConnected_Iio
#align ennreal.embedding_coe ENNReal.embedding_coe
theorem isOpen_ne_top : IsOpen { a : ℝ≥0∞ | a ≠ ∞ } := isOpen_ne
#align ennreal.is_open_ne_top ENNReal.isOpen_ne_top
theorem isOpen_Ico_zero : IsOpen (Ico 0 b) := by
rw [ENNReal.Ico_eq_Iio]
exact isOpen_Iio
#align ennreal.is_open_Ico_zero ENNReal.isOpen_Ico_zero
theorem openEmbedding_coe : OpenEmbedding ((↑) : ℝ≥0 → ℝ≥0∞) :=
⟨embedding_coe, by rw [range_coe']; exact isOpen_Iio⟩
#align ennreal.open_embedding_coe ENNReal.openEmbedding_coe
theorem coe_range_mem_nhds : range ((↑) : ℝ≥0 → ℝ≥0∞) ∈ 𝓝 (r : ℝ≥0∞) :=
IsOpen.mem_nhds openEmbedding_coe.isOpen_range <| mem_range_self _
#align ennreal.coe_range_mem_nhds ENNReal.coe_range_mem_nhds
@[norm_cast]
theorem tendsto_coe {f : Filter α} {m : α → ℝ≥0} {a : ℝ≥0} :
Tendsto (fun a => (m a : ℝ≥0∞)) f (𝓝 ↑a) ↔ Tendsto m f (𝓝 a) :=
embedding_coe.tendsto_nhds_iff.symm
#align ennreal.tendsto_coe ENNReal.tendsto_coe
theorem continuous_coe : Continuous ((↑) : ℝ≥0 → ℝ≥0∞) :=
embedding_coe.continuous
#align ennreal.continuous_coe ENNReal.continuous_coe
theorem continuous_coe_iff {α} [TopologicalSpace α] {f : α → ℝ≥0} :
(Continuous fun a => (f a : ℝ≥0∞)) ↔ Continuous f :=
embedding_coe.continuous_iff.symm
#align ennreal.continuous_coe_iff ENNReal.continuous_coe_iff
theorem nhds_coe {r : ℝ≥0} : 𝓝 (r : ℝ≥0∞) = (𝓝 r).map (↑) :=
(openEmbedding_coe.map_nhds_eq r).symm
#align ennreal.nhds_coe ENNReal.nhds_coe
theorem tendsto_nhds_coe_iff {α : Type*} {l : Filter α} {x : ℝ≥0} {f : ℝ≥0∞ → α} :
Tendsto f (𝓝 ↑x) l ↔ Tendsto (f ∘ (↑) : ℝ≥0 → α) (𝓝 x) l := by
rw [nhds_coe, tendsto_map'_iff]
#align ennreal.tendsto_nhds_coe_iff ENNReal.tendsto_nhds_coe_iff
theorem continuousAt_coe_iff {α : Type*} [TopologicalSpace α] {x : ℝ≥0} {f : ℝ≥0∞ → α} :
ContinuousAt f ↑x ↔ ContinuousAt (f ∘ (↑) : ℝ≥0 → α) x :=
tendsto_nhds_coe_iff
#align ennreal.continuous_at_coe_iff ENNReal.continuousAt_coe_iff
theorem nhds_coe_coe {r p : ℝ≥0} :
𝓝 ((r : ℝ≥0∞), (p : ℝ≥0∞)) = (𝓝 (r, p)).map fun p : ℝ≥0 × ℝ≥0 => (↑p.1, ↑p.2) :=
((openEmbedding_coe.prod openEmbedding_coe).map_nhds_eq (r, p)).symm
#align ennreal.nhds_coe_coe ENNReal.nhds_coe_coe
theorem continuous_ofReal : Continuous ENNReal.ofReal :=
(continuous_coe_iff.2 continuous_id).comp continuous_real_toNNReal
#align ennreal.continuous_of_real ENNReal.continuous_ofReal
theorem tendsto_ofReal {f : Filter α} {m : α → ℝ} {a : ℝ} (h : Tendsto m f (𝓝 a)) :
Tendsto (fun a => ENNReal.ofReal (m a)) f (𝓝 (ENNReal.ofReal a)) :=
(continuous_ofReal.tendsto a).comp h
#align ennreal.tendsto_of_real ENNReal.tendsto_ofReal
theorem tendsto_toNNReal {a : ℝ≥0∞} (ha : a ≠ ∞) :
Tendsto ENNReal.toNNReal (𝓝 a) (𝓝 a.toNNReal) := by
lift a to ℝ≥0 using ha
rw [nhds_coe, tendsto_map'_iff]
exact tendsto_id
#align ennreal.tendsto_to_nnreal ENNReal.tendsto_toNNReal
theorem eventuallyEq_of_toReal_eventuallyEq {l : Filter α} {f g : α → ℝ≥0∞}
(hfi : ∀ᶠ x in l, f x ≠ ∞) (hgi : ∀ᶠ x in l, g x ≠ ∞)
(hfg : (fun x => (f x).toReal) =ᶠ[l] fun x => (g x).toReal) : f =ᶠ[l] g := by
filter_upwards [hfi, hgi, hfg] with _ hfx hgx _
rwa [← ENNReal.toReal_eq_toReal hfx hgx]
#align ennreal.eventually_eq_of_to_real_eventually_eq ENNReal.eventuallyEq_of_toReal_eventuallyEq
theorem continuousOn_toNNReal : ContinuousOn ENNReal.toNNReal { a | a ≠ ∞ } := fun _a ha =>
ContinuousAt.continuousWithinAt (tendsto_toNNReal ha)
#align ennreal.continuous_on_to_nnreal ENNReal.continuousOn_toNNReal
theorem tendsto_toReal {a : ℝ≥0∞} (ha : a ≠ ∞) : Tendsto ENNReal.toReal (𝓝 a) (𝓝 a.toReal) :=
NNReal.tendsto_coe.2 <| tendsto_toNNReal ha
#align ennreal.tendsto_to_real ENNReal.tendsto_toReal
lemma continuousOn_toReal : ContinuousOn ENNReal.toReal { a | a ≠ ∞ } :=
NNReal.continuous_coe.comp_continuousOn continuousOn_toNNReal
lemma continuousAt_toReal (hx : x ≠ ∞) : ContinuousAt ENNReal.toReal x :=
continuousOn_toReal.continuousAt (isOpen_ne_top.mem_nhds_iff.mpr hx)
/-- The set of finite `ℝ≥0∞` numbers is homeomorphic to `ℝ≥0`. -/
def neTopHomeomorphNNReal : { a | a ≠ ∞ } ≃ₜ ℝ≥0 where
toEquiv := neTopEquivNNReal
continuous_toFun := continuousOn_iff_continuous_restrict.1 continuousOn_toNNReal
continuous_invFun := continuous_coe.subtype_mk _
#align ennreal.ne_top_homeomorph_nnreal ENNReal.neTopHomeomorphNNReal
/-- The set of finite `ℝ≥0∞` numbers is homeomorphic to `ℝ≥0`. -/
def ltTopHomeomorphNNReal : { a | a < ∞ } ≃ₜ ℝ≥0 := by
refine (Homeomorph.setCongr ?_).trans neTopHomeomorphNNReal
simp only [mem_setOf_eq, lt_top_iff_ne_top]
#align ennreal.lt_top_homeomorph_nnreal ENNReal.ltTopHomeomorphNNReal
theorem nhds_top : 𝓝 ∞ = ⨅ (a) (_ : a ≠ ∞), 𝓟 (Ioi a) :=
nhds_top_order.trans <| by simp [lt_top_iff_ne_top, Ioi]
#align ennreal.nhds_top ENNReal.nhds_top
theorem nhds_top' : 𝓝 ∞ = ⨅ r : ℝ≥0, 𝓟 (Ioi ↑r) :=
nhds_top.trans <| iInf_ne_top _
#align ennreal.nhds_top' ENNReal.nhds_top'
theorem nhds_top_basis : (𝓝 ∞).HasBasis (fun a => a < ∞) fun a => Ioi a :=
_root_.nhds_top_basis
#align ennreal.nhds_top_basis ENNReal.nhds_top_basis
theorem tendsto_nhds_top_iff_nnreal {m : α → ℝ≥0∞} {f : Filter α} :
Tendsto m f (𝓝 ∞) ↔ ∀ x : ℝ≥0, ∀ᶠ a in f, ↑x < m a := by
simp only [nhds_top', tendsto_iInf, tendsto_principal, mem_Ioi]
#align ennreal.tendsto_nhds_top_iff_nnreal ENNReal.tendsto_nhds_top_iff_nnreal
theorem tendsto_nhds_top_iff_nat {m : α → ℝ≥0∞} {f : Filter α} :
Tendsto m f (𝓝 ∞) ↔ ∀ n : ℕ, ∀ᶠ a in f, ↑n < m a :=
tendsto_nhds_top_iff_nnreal.trans
⟨fun h n => by simpa only [ENNReal.coe_natCast] using h n, fun h x =>
let ⟨n, hn⟩ := exists_nat_gt x
(h n).mono fun y => lt_trans <| by rwa [← ENNReal.coe_natCast, coe_lt_coe]⟩
#align ennreal.tendsto_nhds_top_iff_nat ENNReal.tendsto_nhds_top_iff_nat
theorem tendsto_nhds_top {m : α → ℝ≥0∞} {f : Filter α} (h : ∀ n : ℕ, ∀ᶠ a in f, ↑n < m a) :
Tendsto m f (𝓝 ∞) :=
tendsto_nhds_top_iff_nat.2 h
#align ennreal.tendsto_nhds_top ENNReal.tendsto_nhds_top
theorem tendsto_nat_nhds_top : Tendsto (fun n : ℕ => ↑n) atTop (𝓝 ∞) :=
tendsto_nhds_top fun n =>
mem_atTop_sets.2 ⟨n + 1, fun _m hm => mem_setOf.2 <| Nat.cast_lt.2 <| Nat.lt_of_succ_le hm⟩
#align ennreal.tendsto_nat_nhds_top ENNReal.tendsto_nat_nhds_top
@[simp, norm_cast]
theorem tendsto_coe_nhds_top {f : α → ℝ≥0} {l : Filter α} :
Tendsto (fun x => (f x : ℝ≥0∞)) l (𝓝 ∞) ↔ Tendsto f l atTop := by
rw [tendsto_nhds_top_iff_nnreal, atTop_basis_Ioi.tendsto_right_iff]; simp
#align ennreal.tendsto_coe_nhds_top ENNReal.tendsto_coe_nhds_top
theorem tendsto_ofReal_atTop : Tendsto ENNReal.ofReal atTop (𝓝 ∞) :=
tendsto_coe_nhds_top.2 tendsto_real_toNNReal_atTop
#align ennreal.tendsto_of_real_at_top ENNReal.tendsto_ofReal_atTop
theorem nhds_zero : 𝓝 (0 : ℝ≥0∞) = ⨅ (a) (_ : a ≠ 0), 𝓟 (Iio a) :=
nhds_bot_order.trans <| by simp [pos_iff_ne_zero, Iio]
#align ennreal.nhds_zero ENNReal.nhds_zero
theorem nhds_zero_basis : (𝓝 (0 : ℝ≥0∞)).HasBasis (fun a : ℝ≥0∞ => 0 < a) fun a => Iio a :=
nhds_bot_basis
#align ennreal.nhds_zero_basis ENNReal.nhds_zero_basis
theorem nhds_zero_basis_Iic : (𝓝 (0 : ℝ≥0∞)).HasBasis (fun a : ℝ≥0∞ => 0 < a) Iic :=
nhds_bot_basis_Iic
#align ennreal.nhds_zero_basis_Iic ENNReal.nhds_zero_basis_Iic
-- Porting note (#11215): TODO: add a TC for `≠ ∞`?
@[instance]
theorem nhdsWithin_Ioi_coe_neBot {r : ℝ≥0} : (𝓝[>] (r : ℝ≥0∞)).NeBot :=
nhdsWithin_Ioi_self_neBot' ⟨∞, ENNReal.coe_lt_top⟩
#align ennreal.nhds_within_Ioi_coe_ne_bot ENNReal.nhdsWithin_Ioi_coe_neBot
@[instance]
theorem nhdsWithin_Ioi_zero_neBot : (𝓝[>] (0 : ℝ≥0∞)).NeBot :=
nhdsWithin_Ioi_coe_neBot
#align ennreal.nhds_within_Ioi_zero_ne_bot ENNReal.nhdsWithin_Ioi_zero_neBot
@[instance]
theorem nhdsWithin_Ioi_one_neBot : (𝓝[>] (1 : ℝ≥0∞)).NeBot := nhdsWithin_Ioi_coe_neBot
@[instance]
theorem nhdsWithin_Ioi_nat_neBot (n : ℕ) : (𝓝[>] (n : ℝ≥0∞)).NeBot := nhdsWithin_Ioi_coe_neBot
@[instance]
theorem nhdsWithin_Ioi_ofNat_nebot (n : ℕ) [n.AtLeastTwo] :
(𝓝[>] (OfNat.ofNat n : ℝ≥0∞)).NeBot := nhdsWithin_Ioi_coe_neBot
@[instance]
theorem nhdsWithin_Iio_neBot [NeZero x] : (𝓝[<] x).NeBot :=
nhdsWithin_Iio_self_neBot' ⟨0, NeZero.pos x⟩
/-- Closed intervals `Set.Icc (x - ε) (x + ε)`, `ε ≠ 0`, form a basis of neighborhoods of an
extended nonnegative real number `x ≠ ∞`. We use `Set.Icc` instead of `Set.Ioo` because this way the
statement works for `x = 0`.
-/
| Mathlib/Topology/Instances/ENNReal.lean | 243 | 256 | theorem hasBasis_nhds_of_ne_top' (xt : x ≠ ∞) :
(𝓝 x).HasBasis (· ≠ 0) (fun ε => Icc (x - ε) (x + ε)) := by |
rcases (zero_le x).eq_or_gt with rfl | x0
· simp_rw [zero_tsub, zero_add, ← bot_eq_zero, Icc_bot, ← bot_lt_iff_ne_bot]
exact nhds_bot_basis_Iic
· refine (nhds_basis_Ioo' ⟨_, x0⟩ ⟨_, xt.lt_top⟩).to_hasBasis ?_ fun ε ε0 => ?_
· rintro ⟨a, b⟩ ⟨ha, hb⟩
rcases exists_between (tsub_pos_of_lt ha) with ⟨ε, ε0, hε⟩
rcases lt_iff_exists_add_pos_lt.1 hb with ⟨δ, δ0, hδ⟩
refine ⟨min ε δ, (lt_min ε0 (coe_pos.2 δ0)).ne', Icc_subset_Ioo ?_ ?_⟩
· exact lt_tsub_comm.2 ((min_le_left _ _).trans_lt hε)
· exact (add_le_add_left (min_le_right _ _) _).trans_lt hδ
· exact ⟨(x - ε, x + ε), ⟨ENNReal.sub_lt_self xt x0.ne' ε0,
lt_add_right xt ε0⟩, Ioo_subset_Icc_self⟩
|
/-
Copyright (c) 2022 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Probability.IdentDistrib
import Mathlib.MeasureTheory.Integral.DominatedConvergence
import Mathlib.Analysis.SpecificLimits.FloorPow
import Mathlib.Analysis.PSeries
import Mathlib.Analysis.Asymptotics.SpecificAsymptotics
#align_import probability.strong_law from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# The strong law of large numbers
We prove the strong law of large numbers, in `ProbabilityTheory.strong_law_ae`:
If `X n` is a sequence of independent identically distributed integrable random
variables, then `∑ i ∈ range n, X i / n` converges almost surely to `𝔼[X 0]`.
We give here the strong version, due to Etemadi, that only requires pairwise independence.
This file also contains the Lᵖ version of the strong law of large numbers provided by
`ProbabilityTheory.strong_law_Lp` which shows `∑ i ∈ range n, X i / n` converges in Lᵖ to
`𝔼[X 0]` provided `X n` is independent identically distributed and is Lᵖ.
## Implementation
The main point is to prove the result for real-valued random variables, as the general case
of Banach-space valued random variables follows from this case and approximation by simple
functions. The real version is given in `ProbabilityTheory.strong_law_ae_real`.
We follow the proof by Etemadi
[Etemadi, *An elementary proof of the strong law of large numbers*][etemadi_strong_law],
which goes as follows.
It suffices to prove the result for nonnegative `X`, as one can prove the general result by
splitting a general `X` into its positive part and negative part.
Consider `Xₙ` a sequence of nonnegative integrable identically distributed pairwise independent
random variables. Let `Yₙ` be the truncation of `Xₙ` up to `n`. We claim that
* Almost surely, `Xₙ = Yₙ` for all but finitely many indices. Indeed, `∑ ℙ (Xₙ ≠ Yₙ)` is bounded by
`1 + 𝔼[X]` (see `sum_prob_mem_Ioc_le` and `tsum_prob_mem_Ioi_lt_top`).
* Let `c > 1`. Along the sequence `n = c ^ k`, then `(∑_{i=0}^{n-1} Yᵢ - 𝔼[Yᵢ])/n` converges almost
surely to `0`. This follows from a variance control, as
```
∑_k ℙ (|∑_{i=0}^{c^k - 1} Yᵢ - 𝔼[Yᵢ]| > c^k ε)
≤ ∑_k (c^k ε)^{-2} ∑_{i=0}^{c^k - 1} Var[Yᵢ] (by Markov inequality)
≤ ∑_i (C/i^2) Var[Yᵢ] (as ∑_{c^k > i} 1/(c^k)^2 ≤ C/i^2)
≤ ∑_i (C/i^2) 𝔼[Yᵢ^2]
≤ 2C 𝔼[X^2] (see `sum_variance_truncation_le`)
```
* As `𝔼[Yᵢ]` converges to `𝔼[X]`, it follows from the two previous items and Cesàro that, along
the sequence `n = c^k`, one has `(∑_{i=0}^{n-1} Xᵢ) / n → 𝔼[X]` almost surely.
* To generalize it to all indices, we use the fact that `∑_{i=0}^{n-1} Xᵢ` is nondecreasing and
that, if `c` is close enough to `1`, the gap between `c^k` and `c^(k+1)` is small.
-/
noncomputable section
open MeasureTheory Filter Finset Asymptotics
open Set (indicator)
open scoped Topology MeasureTheory ProbabilityTheory ENNReal NNReal
namespace ProbabilityTheory
/-! ### Prerequisites on truncations -/
section Truncation
variable {α : Type*}
/-- Truncating a real-valued function to the interval `(-A, A]`. -/
def truncation (f : α → ℝ) (A : ℝ) :=
indicator (Set.Ioc (-A) A) id ∘ f
#align probability_theory.truncation ProbabilityTheory.truncation
variable {m : MeasurableSpace α} {μ : Measure α} {f : α → ℝ}
theorem _root_.MeasureTheory.AEStronglyMeasurable.truncation (hf : AEStronglyMeasurable f μ)
{A : ℝ} : AEStronglyMeasurable (truncation f A) μ := by
apply AEStronglyMeasurable.comp_aemeasurable _ hf.aemeasurable
exact (stronglyMeasurable_id.indicator measurableSet_Ioc).aestronglyMeasurable
#align measure_theory.ae_strongly_measurable.truncation MeasureTheory.AEStronglyMeasurable.truncation
theorem abs_truncation_le_bound (f : α → ℝ) (A : ℝ) (x : α) : |truncation f A x| ≤ |A| := by
simp only [truncation, Set.indicator, Set.mem_Icc, id, Function.comp_apply]
split_ifs with h
· exact abs_le_abs h.2 (neg_le.2 h.1.le)
· simp [abs_nonneg]
#align probability_theory.abs_truncation_le_bound ProbabilityTheory.abs_truncation_le_bound
@[simp]
theorem truncation_zero (f : α → ℝ) : truncation f 0 = 0 := by simp [truncation]; rfl
#align probability_theory.truncation_zero ProbabilityTheory.truncation_zero
theorem abs_truncation_le_abs_self (f : α → ℝ) (A : ℝ) (x : α) : |truncation f A x| ≤ |f x| := by
simp only [truncation, indicator, Set.mem_Icc, id, Function.comp_apply]
split_ifs
· exact le_rfl
· simp [abs_nonneg]
#align probability_theory.abs_truncation_le_abs_self ProbabilityTheory.abs_truncation_le_abs_self
theorem truncation_eq_self {f : α → ℝ} {A : ℝ} {x : α} (h : |f x| < A) :
truncation f A x = f x := by
simp only [truncation, indicator, Set.mem_Icc, id, Function.comp_apply, ite_eq_left_iff]
intro H
apply H.elim
simp [(abs_lt.1 h).1, (abs_lt.1 h).2.le]
#align probability_theory.truncation_eq_self ProbabilityTheory.truncation_eq_self
theorem truncation_eq_of_nonneg {f : α → ℝ} {A : ℝ} (h : ∀ x, 0 ≤ f x) :
truncation f A = indicator (Set.Ioc 0 A) id ∘ f := by
ext x
rcases (h x).lt_or_eq with (hx | hx)
· simp only [truncation, indicator, hx, Set.mem_Ioc, id, Function.comp_apply, true_and_iff]
by_cases h'x : f x ≤ A
· have : -A < f x := by linarith [h x]
simp only [this, true_and_iff]
· simp only [h'x, and_false_iff]
· simp only [truncation, indicator, hx, id, Function.comp_apply, ite_self]
#align probability_theory.truncation_eq_of_nonneg ProbabilityTheory.truncation_eq_of_nonneg
theorem truncation_nonneg {f : α → ℝ} (A : ℝ) {x : α} (h : 0 ≤ f x) : 0 ≤ truncation f A x :=
Set.indicator_apply_nonneg fun _ => h
#align probability_theory.truncation_nonneg ProbabilityTheory.truncation_nonneg
theorem _root_.MeasureTheory.AEStronglyMeasurable.memℒp_truncation [IsFiniteMeasure μ]
(hf : AEStronglyMeasurable f μ) {A : ℝ} {p : ℝ≥0∞} : Memℒp (truncation f A) p μ :=
Memℒp.of_bound hf.truncation |A| (eventually_of_forall fun _ => abs_truncation_le_bound _ _ _)
#align measure_theory.ae_strongly_measurable.mem_ℒp_truncation MeasureTheory.AEStronglyMeasurable.memℒp_truncation
theorem _root_.MeasureTheory.AEStronglyMeasurable.integrable_truncation [IsFiniteMeasure μ]
(hf : AEStronglyMeasurable f μ) {A : ℝ} : Integrable (truncation f A) μ := by
rw [← memℒp_one_iff_integrable]; exact hf.memℒp_truncation
#align measure_theory.ae_strongly_measurable.integrable_truncation MeasureTheory.AEStronglyMeasurable.integrable_truncation
theorem moment_truncation_eq_intervalIntegral (hf : AEStronglyMeasurable f μ) {A : ℝ} (hA : 0 ≤ A)
{n : ℕ} (hn : n ≠ 0) : ∫ x, truncation f A x ^ n ∂μ = ∫ y in -A..A, y ^ n ∂Measure.map f μ := by
have M : MeasurableSet (Set.Ioc (-A) A) := measurableSet_Ioc
change ∫ x, (fun z => indicator (Set.Ioc (-A) A) id z ^ n) (f x) ∂μ = _
rw [← integral_map (f := fun z => _ ^ n) hf.aemeasurable, intervalIntegral.integral_of_le,
← integral_indicator M]
· simp only [indicator, zero_pow hn, id, ite_pow]
· linarith
· exact ((measurable_id.indicator M).pow_const n).aestronglyMeasurable
#align probability_theory.moment_truncation_eq_interval_integral ProbabilityTheory.moment_truncation_eq_intervalIntegral
theorem moment_truncation_eq_intervalIntegral_of_nonneg (hf : AEStronglyMeasurable f μ) {A : ℝ}
{n : ℕ} (hn : n ≠ 0) (h'f : 0 ≤ f) :
∫ x, truncation f A x ^ n ∂μ = ∫ y in (0)..A, y ^ n ∂Measure.map f μ := by
have M : MeasurableSet (Set.Ioc 0 A) := measurableSet_Ioc
have M' : MeasurableSet (Set.Ioc A 0) := measurableSet_Ioc
rw [truncation_eq_of_nonneg h'f]
change ∫ x, (fun z => indicator (Set.Ioc 0 A) id z ^ n) (f x) ∂μ = _
rcases le_or_lt 0 A with (hA | hA)
· rw [← integral_map (f := fun z => _ ^ n) hf.aemeasurable, intervalIntegral.integral_of_le hA,
← integral_indicator M]
· simp only [indicator, zero_pow hn, id, ite_pow]
· exact ((measurable_id.indicator M).pow_const n).aestronglyMeasurable
· rw [← integral_map (f := fun z => _ ^ n) hf.aemeasurable, intervalIntegral.integral_of_ge hA.le,
← integral_indicator M']
· simp only [Set.Ioc_eq_empty_of_le hA.le, zero_pow hn, Set.indicator_empty, integral_zero,
zero_eq_neg]
apply integral_eq_zero_of_ae
have : ∀ᵐ x ∂Measure.map f μ, (0 : ℝ) ≤ x :=
(ae_map_iff hf.aemeasurable measurableSet_Ici).2 (eventually_of_forall h'f)
filter_upwards [this] with x hx
simp only [indicator, Set.mem_Ioc, Pi.zero_apply, ite_eq_right_iff, and_imp]
intro _ h''x
have : x = 0 := by linarith
simp [this, zero_pow hn]
· exact ((measurable_id.indicator M).pow_const n).aestronglyMeasurable
#align probability_theory.moment_truncation_eq_interval_integral_of_nonneg ProbabilityTheory.moment_truncation_eq_intervalIntegral_of_nonneg
theorem integral_truncation_eq_intervalIntegral (hf : AEStronglyMeasurable f μ) {A : ℝ}
(hA : 0 ≤ A) : ∫ x, truncation f A x ∂μ = ∫ y in -A..A, y ∂Measure.map f μ := by
simpa using moment_truncation_eq_intervalIntegral hf hA one_ne_zero
#align probability_theory.integral_truncation_eq_interval_integral ProbabilityTheory.integral_truncation_eq_intervalIntegral
theorem integral_truncation_eq_intervalIntegral_of_nonneg (hf : AEStronglyMeasurable f μ) {A : ℝ}
(h'f : 0 ≤ f) : ∫ x, truncation f A x ∂μ = ∫ y in (0)..A, y ∂Measure.map f μ := by
simpa using moment_truncation_eq_intervalIntegral_of_nonneg hf one_ne_zero h'f
#align probability_theory.integral_truncation_eq_interval_integral_of_nonneg ProbabilityTheory.integral_truncation_eq_intervalIntegral_of_nonneg
theorem integral_truncation_le_integral_of_nonneg (hf : Integrable f μ) (h'f : 0 ≤ f) {A : ℝ} :
∫ x, truncation f A x ∂μ ≤ ∫ x, f x ∂μ := by
apply integral_mono_of_nonneg
(eventually_of_forall fun x => ?_) hf (eventually_of_forall fun x => ?_)
· exact truncation_nonneg _ (h'f x)
· calc
truncation f A x ≤ |truncation f A x| := le_abs_self _
_ ≤ |f x| := abs_truncation_le_abs_self _ _ _
_ = f x := abs_of_nonneg (h'f x)
#align probability_theory.integral_truncation_le_integral_of_nonneg ProbabilityTheory.integral_truncation_le_integral_of_nonneg
/-- If a function is integrable, then the integral of its truncated versions converges to the
integral of the whole function. -/
theorem tendsto_integral_truncation {f : α → ℝ} (hf : Integrable f μ) :
Tendsto (fun A => ∫ x, truncation f A x ∂μ) atTop (𝓝 (∫ x, f x ∂μ)) := by
refine tendsto_integral_filter_of_dominated_convergence (fun x => abs (f x)) ?_ ?_ ?_ ?_
· exact eventually_of_forall fun A ↦ hf.aestronglyMeasurable.truncation
· filter_upwards with A
filter_upwards with x
rw [Real.norm_eq_abs]
exact abs_truncation_le_abs_self _ _ _
· exact hf.abs
· filter_upwards with x
apply tendsto_const_nhds.congr' _
filter_upwards [Ioi_mem_atTop (abs (f x))] with A hA
exact (truncation_eq_self hA).symm
#align probability_theory.tendsto_integral_truncation ProbabilityTheory.tendsto_integral_truncation
theorem IdentDistrib.truncation {β : Type*} [MeasurableSpace β] {ν : Measure β} {f : α → ℝ}
{g : β → ℝ} (h : IdentDistrib f g μ ν) {A : ℝ} :
IdentDistrib (truncation f A) (truncation g A) μ ν :=
h.comp (measurable_id.indicator measurableSet_Ioc)
#align probability_theory.ident_distrib.truncation ProbabilityTheory.IdentDistrib.truncation
end Truncation
section StrongLawAeReal
variable {Ω : Type*} [MeasureSpace Ω] [IsProbabilityMeasure (ℙ : Measure Ω)]
section MomentEstimates
theorem sum_prob_mem_Ioc_le {X : Ω → ℝ} (hint : Integrable X) (hnonneg : 0 ≤ X) {K : ℕ} {N : ℕ}
(hKN : K ≤ N) :
∑ j ∈ range K, ℙ {ω | X ω ∈ Set.Ioc (j : ℝ) N} ≤ ENNReal.ofReal (𝔼[X] + 1) := by
let ρ : Measure ℝ := Measure.map X ℙ
haveI : IsProbabilityMeasure ρ := isProbabilityMeasure_map hint.aemeasurable
have A : ∑ j ∈ range K, ∫ _ in j..N, (1 : ℝ) ∂ρ ≤ 𝔼[X] + 1 :=
calc
∑ j ∈ range K, ∫ _ in j..N, (1 : ℝ) ∂ρ =
∑ j ∈ range K, ∑ i ∈ Ico j N, ∫ _ in i..(i + 1 : ℕ), (1 : ℝ) ∂ρ := by
apply sum_congr rfl fun j hj => ?_
rw [intervalIntegral.sum_integral_adjacent_intervals_Ico ((mem_range.1 hj).le.trans hKN)]
intro k _
exact continuous_const.intervalIntegrable _ _
_ = ∑ i ∈ range N, ∑ j ∈ range (min (i + 1) K), ∫ _ in i..(i + 1 : ℕ), (1 : ℝ) ∂ρ := by
simp_rw [sum_sigma']
refine sum_nbij' (fun p ↦ ⟨p.2, p.1⟩) (fun p ↦ ⟨p.2, p.1⟩) ?_ ?_ ?_ ?_ ?_ <;>
aesop (add simp Nat.lt_succ_iff)
_ ≤ ∑ i ∈ range N, (i + 1) * ∫ _ in i..(i + 1 : ℕ), (1 : ℝ) ∂ρ := by
apply sum_le_sum fun i _ => ?_
simp only [Nat.cast_add, Nat.cast_one, sum_const, card_range, nsmul_eq_mul, Nat.cast_min]
refine mul_le_mul_of_nonneg_right (min_le_left _ _) ?_
apply intervalIntegral.integral_nonneg
· simp only [le_add_iff_nonneg_right, zero_le_one]
· simp only [zero_le_one, imp_true_iff]
_ ≤ ∑ i ∈ range N, ∫ x in i..(i + 1 : ℕ), x + 1 ∂ρ := by
apply sum_le_sum fun i _ => ?_
have I : (i : ℝ) ≤ (i + 1 : ℕ) := by
simp only [Nat.cast_add, Nat.cast_one, le_add_iff_nonneg_right, zero_le_one]
simp_rw [intervalIntegral.integral_of_le I, ← integral_mul_left]
apply setIntegral_mono_on
· exact continuous_const.integrableOn_Ioc
· exact (continuous_id.add continuous_const).integrableOn_Ioc
· exact measurableSet_Ioc
· intro x hx
simp only [Nat.cast_add, Nat.cast_one, Set.mem_Ioc] at hx
simp [hx.1.le]
_ = ∫ x in (0)..N, x + 1 ∂ρ := by
rw [intervalIntegral.sum_integral_adjacent_intervals fun k _ => ?_]
· norm_cast
· exact (continuous_id.add continuous_const).intervalIntegrable _ _
_ = ∫ x in (0)..N, x ∂ρ + ∫ x in (0)..N, 1 ∂ρ := by
rw [intervalIntegral.integral_add]
· exact continuous_id.intervalIntegrable _ _
· exact continuous_const.intervalIntegrable _ _
_ = 𝔼[truncation X N] + ∫ x in (0)..N, 1 ∂ρ := by
rw [integral_truncation_eq_intervalIntegral_of_nonneg hint.1 hnonneg]
_ ≤ 𝔼[X] + ∫ x in (0)..N, 1 ∂ρ :=
(add_le_add_right (integral_truncation_le_integral_of_nonneg hint hnonneg) _)
_ ≤ 𝔼[X] + 1 := by
refine add_le_add le_rfl ?_
rw [intervalIntegral.integral_of_le (Nat.cast_nonneg _)]
simp only [integral_const, Measure.restrict_apply', measurableSet_Ioc, Set.univ_inter,
Algebra.id.smul_eq_mul, mul_one]
rw [← ENNReal.one_toReal]
exact ENNReal.toReal_mono ENNReal.one_ne_top prob_le_one
have B : ∀ a b, ℙ {ω | X ω ∈ Set.Ioc a b} = ENNReal.ofReal (∫ _ in Set.Ioc a b, (1 : ℝ) ∂ρ) := by
intro a b
rw [ofReal_setIntegral_one ρ _,
Measure.map_apply_of_aemeasurable hint.aemeasurable measurableSet_Ioc]
rfl
calc
∑ j ∈ range K, ℙ {ω | X ω ∈ Set.Ioc (j : ℝ) N} =
∑ j ∈ range K, ENNReal.ofReal (∫ _ in Set.Ioc (j : ℝ) N, (1 : ℝ) ∂ρ) := by simp_rw [B]
_ = ENNReal.ofReal (∑ j ∈ range K, ∫ _ in Set.Ioc (j : ℝ) N, (1 : ℝ) ∂ρ) := by
rw [ENNReal.ofReal_sum_of_nonneg]
simp only [integral_const, Algebra.id.smul_eq_mul, mul_one, ENNReal.toReal_nonneg,
imp_true_iff]
_ = ENNReal.ofReal (∑ j ∈ range K, ∫ _ in (j : ℝ)..N, (1 : ℝ) ∂ρ) := by
congr 1
refine sum_congr rfl fun j hj => ?_
rw [intervalIntegral.integral_of_le (Nat.cast_le.2 ((mem_range.1 hj).le.trans hKN))]
_ ≤ ENNReal.ofReal (𝔼[X] + 1) := ENNReal.ofReal_le_ofReal A
#align probability_theory.sum_prob_mem_Ioc_le ProbabilityTheory.sum_prob_mem_Ioc_le
theorem tsum_prob_mem_Ioi_lt_top {X : Ω → ℝ} (hint : Integrable X) (hnonneg : 0 ≤ X) :
(∑' j : ℕ, ℙ {ω | X ω ∈ Set.Ioi (j : ℝ)}) < ∞ := by
suffices ∀ K : ℕ, ∑ j ∈ range K, ℙ {ω | X ω ∈ Set.Ioi (j : ℝ)} ≤ ENNReal.ofReal (𝔼[X] + 1) from
(le_of_tendsto_of_tendsto (ENNReal.tendsto_nat_tsum _) tendsto_const_nhds
(eventually_of_forall this)).trans_lt ENNReal.ofReal_lt_top
intro K
have A : Tendsto (fun N : ℕ => ∑ j ∈ range K, ℙ {ω | X ω ∈ Set.Ioc (j : ℝ) N}) atTop
(𝓝 (∑ j ∈ range K, ℙ {ω | X ω ∈ Set.Ioi (j : ℝ)})) := by
refine tendsto_finset_sum _ fun i _ => ?_
have : {ω | X ω ∈ Set.Ioi (i : ℝ)} = ⋃ N : ℕ, {ω | X ω ∈ Set.Ioc (i : ℝ) N} := by
apply Set.Subset.antisymm _ _
· intro ω hω
obtain ⟨N, hN⟩ : ∃ N : ℕ, X ω ≤ N := exists_nat_ge (X ω)
exact Set.mem_iUnion.2 ⟨N, hω, hN⟩
· simp (config := {contextual := true}) only [Set.mem_Ioc, Set.mem_Ioi,
Set.iUnion_subset_iff, Set.setOf_subset_setOf, imp_true_iff]
rw [this]
apply tendsto_measure_iUnion
intro m n hmn x hx
exact ⟨hx.1, hx.2.trans (Nat.cast_le.2 hmn)⟩
apply le_of_tendsto_of_tendsto A tendsto_const_nhds
filter_upwards [Ici_mem_atTop K] with N hN
exact sum_prob_mem_Ioc_le hint hnonneg hN
#align probability_theory.tsum_prob_mem_Ioi_lt_top ProbabilityTheory.tsum_prob_mem_Ioi_lt_top
theorem sum_variance_truncation_le {X : Ω → ℝ} (hint : Integrable X) (hnonneg : 0 ≤ X) (K : ℕ) :
∑ j ∈ range K, ((j : ℝ) ^ 2)⁻¹ * 𝔼[truncation X j ^ 2] ≤ 2 * 𝔼[X] := by
set Y := fun n : ℕ => truncation X n
let ρ : Measure ℝ := Measure.map X ℙ
have Y2 : ∀ n, 𝔼[Y n ^ 2] = ∫ x in (0)..n, x ^ 2 ∂ρ := by
intro n
change 𝔼[fun x => Y n x ^ 2] = _
rw [moment_truncation_eq_intervalIntegral_of_nonneg hint.1 two_ne_zero hnonneg]
calc
∑ j ∈ range K, ((j : ℝ) ^ 2)⁻¹ * 𝔼[Y j ^ 2] =
∑ j ∈ range K, ((j : ℝ) ^ 2)⁻¹ * ∫ x in (0)..j, x ^ 2 ∂ρ := by simp_rw [Y2]
_ = ∑ j ∈ range K, ((j : ℝ) ^ 2)⁻¹ * ∑ k ∈ range j, ∫ x in k..(k + 1 : ℕ), x ^ 2 ∂ρ := by
congr 1 with j
congr 1
rw [intervalIntegral.sum_integral_adjacent_intervals]
· norm_cast
intro k _
exact (continuous_id.pow _).intervalIntegrable _ _
_ = ∑ k ∈ range K, (∑ j ∈ Ioo k K, ((j : ℝ) ^ 2)⁻¹) * ∫ x in k..(k + 1 : ℕ), x ^ 2 ∂ρ := by
simp_rw [mul_sum, sum_mul, sum_sigma']
refine sum_nbij' (fun p ↦ ⟨p.2, p.1⟩) (fun p ↦ ⟨p.2, p.1⟩) ?_ ?_ ?_ ?_ ?_ <;>
aesop (add unsafe lt_trans)
_ ≤ ∑ k ∈ range K, 2 / (k + 1 : ℝ) * ∫ x in k..(k + 1 : ℕ), x ^ 2 ∂ρ := by
apply sum_le_sum fun k _ => ?_
refine mul_le_mul_of_nonneg_right (sum_Ioo_inv_sq_le _ _) ?_
refine intervalIntegral.integral_nonneg_of_forall ?_ fun u => sq_nonneg _
simp only [Nat.cast_add, Nat.cast_one, le_add_iff_nonneg_right, zero_le_one]
_ ≤ ∑ k ∈ range K, ∫ x in k..(k + 1 : ℕ), 2 * x ∂ρ := by
apply sum_le_sum fun k _ => ?_
have Ik : (k : ℝ) ≤ (k + 1 : ℕ) := by simp
rw [← intervalIntegral.integral_const_mul, intervalIntegral.integral_of_le Ik,
intervalIntegral.integral_of_le Ik]
refine setIntegral_mono_on ?_ ?_ measurableSet_Ioc fun x hx => ?_
· apply Continuous.integrableOn_Ioc
exact continuous_const.mul (continuous_pow 2)
· apply Continuous.integrableOn_Ioc
exact continuous_const.mul continuous_id'
· calc
↑2 / (↑k + ↑1) * x ^ 2 = x / (k + 1) * (2 * x) := by ring
_ ≤ 1 * (2 * x) :=
(mul_le_mul_of_nonneg_right (by
convert (div_le_one _).2 hx.2
· norm_cast
simp only [Nat.cast_add, Nat.cast_one]
linarith only [show (0 : ℝ) ≤ k from Nat.cast_nonneg k])
(mul_nonneg zero_le_two ((Nat.cast_nonneg k).trans hx.1.le)))
_ = 2 * x := by rw [one_mul]
_ = 2 * ∫ x in (0 : ℝ)..K, x ∂ρ := by
rw [intervalIntegral.sum_integral_adjacent_intervals fun k _ => ?_]
swap; · exact (continuous_const.mul continuous_id').intervalIntegrable _ _
rw [intervalIntegral.integral_const_mul]
norm_cast
_ ≤ 2 * 𝔼[X] := mul_le_mul_of_nonneg_left (by
rw [← integral_truncation_eq_intervalIntegral_of_nonneg hint.1 hnonneg]
exact integral_truncation_le_integral_of_nonneg hint hnonneg) zero_le_two
#align probability_theory.sum_variance_truncation_le ProbabilityTheory.sum_variance_truncation_le
end MomentEstimates
/-! Proof of the strong law of large numbers (almost sure version, assuming only
pairwise independence) for nonnegative random variables, following Etemadi's proof. -/
section StrongLawNonneg
variable (X : ℕ → Ω → ℝ) (hint : Integrable (X 0))
(hindep : Pairwise fun i j => IndepFun (X i) (X j)) (hident : ∀ i, IdentDistrib (X i) (X 0))
(hnonneg : ∀ i ω, 0 ≤ X i ω)
/-- The truncation of `Xᵢ` up to `i` satisfies the strong law of large numbers (with respect to
the truncated expectation) along the sequence `c^n`, for any `c > 1`, up to a given `ε > 0`.
This follows from a variance control. -/
theorem strong_law_aux1 {c : ℝ} (c_one : 1 < c) {ε : ℝ} (εpos : 0 < ε) : ∀ᵐ ω, ∀ᶠ n : ℕ in atTop,
|∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) i ω - 𝔼[∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) i]| <
ε * ⌊c ^ n⌋₊ := by
/- Let `S n = ∑ i ∈ range n, Y i` where `Y i = truncation (X i) i`. We should show that
`|S k - 𝔼[S k]| / k ≤ ε` along the sequence of powers of `c`. For this, we apply Borel-Cantelli:
it suffices to show that the converse probabilites are summable. From Chebyshev inequality, this
will follow from a variance control `∑' Var[S (c^i)] / (c^i)^2 < ∞`. This is checked in `I2`
using pairwise independence to expand the variance of the sum as the sum of the variances,
and then a straightforward but tedious computation (essentially boiling down to the fact that
the sum of `1/(c ^ i)^2` beyong a threshold `j` is comparable to `1/j^2`).
Note that we have written `c^i` in the above proof sketch, but rigorously one should put integer
parts everywhere, making things more painful. We write `u i = ⌊c^i⌋₊` for brevity. -/
have c_pos : 0 < c := zero_lt_one.trans c_one
have hX : ∀ i, AEStronglyMeasurable (X i) ℙ := fun i =>
(hident i).symm.aestronglyMeasurable_snd hint.1
have A : ∀ i, StronglyMeasurable (indicator (Set.Ioc (-i : ℝ) i) id) := fun i =>
stronglyMeasurable_id.indicator measurableSet_Ioc
set Y := fun n : ℕ => truncation (X n) n
set S := fun n => ∑ i ∈ range n, Y i with hS
let u : ℕ → ℕ := fun n => ⌊c ^ n⌋₊
have u_mono : Monotone u := fun i j hij => Nat.floor_mono (pow_le_pow_right c_one.le hij)
have I1 : ∀ K, ∑ j ∈ range K, ((j : ℝ) ^ 2)⁻¹ * Var[Y j] ≤ 2 * 𝔼[X 0] := by
intro K
calc
∑ j ∈ range K, ((j : ℝ) ^ 2)⁻¹ * Var[Y j] ≤
∑ j ∈ range K, ((j : ℝ) ^ 2)⁻¹ * 𝔼[truncation (X 0) j ^ 2] := by
apply sum_le_sum fun j _ => ?_
refine mul_le_mul_of_nonneg_left ?_ (inv_nonneg.2 (sq_nonneg _))
rw [(hident j).truncation.variance_eq]
exact variance_le_expectation_sq (hX 0).truncation
_ ≤ 2 * 𝔼[X 0] := sum_variance_truncation_le hint (hnonneg 0) K
let C := c ^ 5 * (c - 1)⁻¹ ^ 3 * (2 * 𝔼[X 0])
have I2 : ∀ N, ∑ i ∈ range N, ((u i : ℝ) ^ 2)⁻¹ * Var[S (u i)] ≤ C := by
intro N
calc
∑ i ∈ range N, ((u i : ℝ) ^ 2)⁻¹ * Var[S (u i)] =
∑ i ∈ range N, ((u i : ℝ) ^ 2)⁻¹ * ∑ j ∈ range (u i), Var[Y j] := by
congr 1 with i
congr 1
rw [hS, IndepFun.variance_sum]
· intro j _
exact (hident j).aestronglyMeasurable_fst.memℒp_truncation
· intro k _ l _ hkl
exact (hindep hkl).comp (A k).measurable (A l).measurable
_ = ∑ j ∈ range (u (N - 1)),
(∑ i ∈ (range N).filter fun i => j < u i, ((u i : ℝ) ^ 2)⁻¹) * Var[Y j] := by
simp_rw [mul_sum, sum_mul, sum_sigma']
refine sum_nbij' (fun p ↦ ⟨p.2, p.1⟩) (fun p ↦ ⟨p.2, p.1⟩) ?_ ?_ ?_ ?_ ?_
· simp only [mem_sigma, mem_range, filter_congr_decidable, mem_filter, and_imp,
Sigma.forall]
exact fun a b haN hb ↦ ⟨hb.trans_le <| u_mono <| Nat.le_pred_of_lt haN, haN, hb⟩
all_goals aesop
_ ≤ ∑ j ∈ range (u (N - 1)), c ^ 5 * (c - 1)⁻¹ ^ 3 / ↑j ^ 2 * Var[Y j] := by
apply sum_le_sum fun j hj => ?_
rcases @eq_zero_or_pos _ _ j with (rfl | hj)
· simp only [Nat.cast_zero, zero_pow, Ne, bit0_eq_zero, Nat.one_ne_zero,
not_false_iff, div_zero, zero_mul]
simp only [Y, Nat.cast_zero, truncation_zero, variance_zero, mul_zero, le_rfl]
apply mul_le_mul_of_nonneg_right _ (variance_nonneg _ _)
convert sum_div_nat_floor_pow_sq_le_div_sq N (Nat.cast_pos.2 hj) c_one using 2
· simp only [Nat.cast_lt]
· simp only [one_div]
_ = c ^ 5 * (c - 1)⁻¹ ^ 3 * ∑ j ∈ range (u (N - 1)), ((j : ℝ) ^ 2)⁻¹ * Var[Y j] := by
simp_rw [mul_sum, div_eq_mul_inv, mul_assoc]
_ ≤ c ^ 5 * (c - 1)⁻¹ ^ 3 * (2 * 𝔼[X 0]) := by
apply mul_le_mul_of_nonneg_left (I1 _)
apply mul_nonneg (pow_nonneg c_pos.le _)
exact pow_nonneg (inv_nonneg.2 (sub_nonneg.2 c_one.le)) _
have I3 : ∀ N, ∑ i ∈ range N, ℙ {ω | (u i * ε : ℝ) ≤ |S (u i) ω - 𝔼[S (u i)]|} ≤
ENNReal.ofReal (ε⁻¹ ^ 2 * C) := by
intro N
calc
∑ i ∈ range N, ℙ {ω | (u i * ε : ℝ) ≤ |S (u i) ω - 𝔼[S (u i)]|} ≤
∑ i ∈ range N, ENNReal.ofReal (Var[S (u i)] / (u i * ε) ^ 2) := by
refine sum_le_sum fun i _ => ?_
apply meas_ge_le_variance_div_sq
· exact memℒp_finset_sum' _ fun j _ => (hident j).aestronglyMeasurable_fst.memℒp_truncation
· apply mul_pos (Nat.cast_pos.2 _) εpos
refine zero_lt_one.trans_le ?_
apply Nat.le_floor
rw [Nat.cast_one]
apply one_le_pow_of_one_le c_one.le
_ = ENNReal.ofReal (∑ i ∈ range N, Var[S (u i)] / (u i * ε) ^ 2) := by
rw [ENNReal.ofReal_sum_of_nonneg fun i _ => ?_]
exact div_nonneg (variance_nonneg _ _) (sq_nonneg _)
_ ≤ ENNReal.ofReal (ε⁻¹ ^ 2 * C) := by
apply ENNReal.ofReal_le_ofReal
-- Porting note: do most of the rewrites under `conv` so as not to expand `variance`
conv_lhs =>
enter [2, i]
rw [div_eq_inv_mul, ← inv_pow, mul_inv, mul_comm _ ε⁻¹, mul_pow, mul_assoc]
rw [← mul_sum]
refine mul_le_mul_of_nonneg_left ?_ (sq_nonneg _)
conv_lhs => enter [2, i]; rw [inv_pow]
exact I2 N
have I4 : (∑' i, ℙ {ω | (u i * ε : ℝ) ≤ |S (u i) ω - 𝔼[S (u i)]|}) < ∞ :=
(le_of_tendsto_of_tendsto' (ENNReal.tendsto_nat_tsum _) tendsto_const_nhds I3).trans_lt
ENNReal.ofReal_lt_top
filter_upwards [ae_eventually_not_mem I4.ne] with ω hω
simp_rw [S, not_le, mul_comm, sum_apply] at hω
convert hω; simp only [sum_apply]
#align probability_theory.strong_law_aux1 ProbabilityTheory.strong_law_aux1
/- The truncation of `Xᵢ` up to `i` satisfies the strong law of large numbers
(with respect to the truncated expectation) along the sequence
`c^n`, for any `c > 1`. This follows from `strong_law_aux1` by varying `ε`. -/
theorem strong_law_aux2 {c : ℝ} (c_one : 1 < c) :
∀ᵐ ω, (fun n : ℕ => ∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) i ω -
𝔼[∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) i]) =o[atTop] fun n : ℕ => (⌊c ^ n⌋₊ : ℝ) := by
obtain ⟨v, -, v_pos, v_lim⟩ :
∃ v : ℕ → ℝ, StrictAnti v ∧ (∀ n : ℕ, 0 < v n) ∧ Tendsto v atTop (𝓝 0) :=
exists_seq_strictAnti_tendsto (0 : ℝ)
have := fun i => strong_law_aux1 X hint hindep hident hnonneg c_one (v_pos i)
filter_upwards [ae_all_iff.2 this] with ω hω
apply Asymptotics.isLittleO_iff.2 fun ε εpos => ?_
obtain ⟨i, hi⟩ : ∃ i, v i < ε := ((tendsto_order.1 v_lim).2 ε εpos).exists
filter_upwards [hω i] with n hn
simp only [Real.norm_eq_abs, abs_abs, Nat.abs_cast]
exact hn.le.trans (mul_le_mul_of_nonneg_right hi.le (Nat.cast_nonneg _))
#align probability_theory.strong_law_aux2 ProbabilityTheory.strong_law_aux2
/-- The expectation of the truncated version of `Xᵢ` behaves asymptotically like the whole
expectation. This follows from convergence and Cesàro averaging. -/
theorem strong_law_aux3 :
(fun n => 𝔼[∑ i ∈ range n, truncation (X i) i] - n * 𝔼[X 0]) =o[atTop] ((↑) : ℕ → ℝ) := by
have A : Tendsto (fun i => 𝔼[truncation (X i) i]) atTop (𝓝 𝔼[X 0]) := by
convert (tendsto_integral_truncation hint).comp tendsto_natCast_atTop_atTop using 1
ext i
exact (hident i).truncation.integral_eq
convert Asymptotics.isLittleO_sum_range_of_tendsto_zero (tendsto_sub_nhds_zero_iff.2 A) using 1
ext1 n
simp only [sum_sub_distrib, sum_const, card_range, nsmul_eq_mul, sum_apply, sub_left_inj]
rw [integral_finset_sum _ fun i _ => ?_]
exact ((hident i).symm.integrable_snd hint).1.integrable_truncation
#align probability_theory.strong_law_aux3 ProbabilityTheory.strong_law_aux3
/- The truncation of `Xᵢ` up to `i` satisfies the strong law of large numbers
(with respect to the original expectation) along the sequence
`c^n`, for any `c > 1`. This follows from the version from the truncated expectation, and the
fact that the truncated and the original expectations have the same asymptotic behavior. -/
theorem strong_law_aux4 {c : ℝ} (c_one : 1 < c) :
∀ᵐ ω, (fun n : ℕ => ∑ i ∈ range ⌊c ^ n⌋₊, truncation (X i) i ω - ⌊c ^ n⌋₊ * 𝔼[X 0]) =o[atTop]
fun n : ℕ => (⌊c ^ n⌋₊ : ℝ) := by
filter_upwards [strong_law_aux2 X hint hindep hident hnonneg c_one] with ω hω
have A : Tendsto (fun n : ℕ => ⌊c ^ n⌋₊) atTop atTop :=
tendsto_nat_floor_atTop.comp (tendsto_pow_atTop_atTop_of_one_lt c_one)
convert hω.add ((strong_law_aux3 X hint hident).comp_tendsto A) using 1
ext1 n
simp
#align probability_theory.strong_law_aux4 ProbabilityTheory.strong_law_aux4
/-- The truncated and non-truncated versions of `Xᵢ` have the same asymptotic behavior, as they
almost surely coincide at all but finitely many steps. This follows from a probability computation
and Borel-Cantelli. -/
theorem strong_law_aux5 :
∀ᵐ ω, (fun n : ℕ => ∑ i ∈ range n, truncation (X i) i ω - ∑ i ∈ range n, X i ω) =o[atTop]
fun n : ℕ => (n : ℝ) := by
have A : (∑' j : ℕ, ℙ {ω | X j ω ∈ Set.Ioi (j : ℝ)}) < ∞ := by
convert tsum_prob_mem_Ioi_lt_top hint (hnonneg 0) using 2
ext1 j
exact (hident j).measure_mem_eq measurableSet_Ioi
have B : ∀ᵐ ω, Tendsto (fun n : ℕ => truncation (X n) n ω - X n ω) atTop (𝓝 0) := by
filter_upwards [ae_eventually_not_mem A.ne] with ω hω
apply tendsto_const_nhds.congr' _
filter_upwards [hω, Ioi_mem_atTop 0] with n hn npos
simp only [truncation, indicator, Set.mem_Ioc, id, Function.comp_apply]
split_ifs with h
· exact (sub_self _).symm
· have : -(n : ℝ) < X n ω := by
apply lt_of_lt_of_le _ (hnonneg n ω)
simpa only [Right.neg_neg_iff, Nat.cast_pos] using npos
simp only [this, true_and_iff, not_le] at h
exact (hn h).elim
filter_upwards [B] with ω hω
convert isLittleO_sum_range_of_tendsto_zero hω using 1
ext n
rw [sum_sub_distrib]
#align probability_theory.strong_law_aux5 ProbabilityTheory.strong_law_aux5
/- `Xᵢ` satisfies the strong law of large numbers along the sequence
`c^n`, for any `c > 1`. This follows from the version for the truncated `Xᵢ`, and the fact that
`Xᵢ` and its truncated version have the same asymptotic behavior. -/
theorem strong_law_aux6 {c : ℝ} (c_one : 1 < c) :
∀ᵐ ω, Tendsto (fun n : ℕ => (∑ i ∈ range ⌊c ^ n⌋₊, X i ω) / ⌊c ^ n⌋₊) atTop (𝓝 𝔼[X 0]) := by
have H : ∀ n : ℕ, (0 : ℝ) < ⌊c ^ n⌋₊ := by
intro n
refine zero_lt_one.trans_le ?_
simp only [Nat.one_le_cast, Nat.one_le_floor_iff, one_le_pow_of_one_le c_one.le n]
filter_upwards [strong_law_aux4 X hint hindep hident hnonneg c_one,
strong_law_aux5 X hint hident hnonneg] with ω hω h'ω
rw [← tendsto_sub_nhds_zero_iff, ← Asymptotics.isLittleO_one_iff ℝ]
have L : (fun n : ℕ => ∑ i ∈ range ⌊c ^ n⌋₊, X i ω - ⌊c ^ n⌋₊ * 𝔼[X 0]) =o[atTop] fun n =>
(⌊c ^ n⌋₊ : ℝ) := by
have A : Tendsto (fun n : ℕ => ⌊c ^ n⌋₊) atTop atTop :=
tendsto_nat_floor_atTop.comp (tendsto_pow_atTop_atTop_of_one_lt c_one)
convert hω.sub (h'ω.comp_tendsto A) using 1
ext1 n
simp only [Function.comp_apply, sub_sub_sub_cancel_left]
convert L.mul_isBigO (isBigO_refl (fun n : ℕ => (⌊c ^ n⌋₊ : ℝ)⁻¹) atTop) using 1 <;>
(ext1 n; field_simp [(H n).ne'])
#align probability_theory.strong_law_aux6 ProbabilityTheory.strong_law_aux6
/-- `Xᵢ` satisfies the strong law of large numbers along all integers. This follows from the
corresponding fact along the sequences `c^n`, and the fact that any integer can be sandwiched
between `c^n` and `c^(n+1)` with comparably small error if `c` is close enough to `1`
(which is formalized in `tendsto_div_of_monotone_of_tendsto_div_floor_pow`). -/
theorem strong_law_aux7 :
∀ᵐ ω, Tendsto (fun n : ℕ => (∑ i ∈ range n, X i ω) / n) atTop (𝓝 𝔼[X 0]) := by
obtain ⟨c, -, cone, clim⟩ :
∃ c : ℕ → ℝ, StrictAnti c ∧ (∀ n : ℕ, 1 < c n) ∧ Tendsto c atTop (𝓝 1) :=
exists_seq_strictAnti_tendsto (1 : ℝ)
have : ∀ k, ∀ᵐ ω,
Tendsto (fun n : ℕ => (∑ i ∈ range ⌊c k ^ n⌋₊, X i ω) / ⌊c k ^ n⌋₊) atTop (𝓝 𝔼[X 0]) :=
fun k => strong_law_aux6 X hint hindep hident hnonneg (cone k)
filter_upwards [ae_all_iff.2 this] with ω hω
apply tendsto_div_of_monotone_of_tendsto_div_floor_pow _ _ _ c cone clim _
· intro m n hmn
exact sum_le_sum_of_subset_of_nonneg (range_mono hmn) fun i _ _ => hnonneg i ω
· exact hω
#align probability_theory.strong_law_aux7 ProbabilityTheory.strong_law_aux7
end StrongLawNonneg
/-- **Strong law of large numbers**, almost sure version: if `X n` is a sequence of independent
identically distributed integrable real-valued random variables, then `∑ i ∈ range n, X i / n`
converges almost surely to `𝔼[X 0]`. We give here the strong version, due to Etemadi, that only
requires pairwise independence. Superseded by `strong_law_ae`, which works for random variables
taking values in any Banach space. -/
| Mathlib/Probability/StrongLaw.lean | 627 | 645 | theorem strong_law_ae_real (X : ℕ → Ω → ℝ) (hint : Integrable (X 0))
(hindep : Pairwise fun i j => IndepFun (X i) (X j)) (hident : ∀ i, IdentDistrib (X i) (X 0)) :
∀ᵐ ω, Tendsto (fun n : ℕ => (∑ i ∈ range n, X i ω) / n) atTop (𝓝 𝔼[X 0]) := by |
let pos : ℝ → ℝ := fun x => max x 0
let neg : ℝ → ℝ := fun x => max (-x) 0
have posm : Measurable pos := measurable_id'.max measurable_const
have negm : Measurable neg := measurable_id'.neg.max measurable_const
have A: ∀ᵐ ω, Tendsto (fun n : ℕ => (∑ i ∈ range n, (pos ∘ X i) ω) / n) atTop (𝓝 𝔼[pos ∘ X 0]) :=
strong_law_aux7 _ hint.pos_part (fun i j hij => (hindep hij).comp posm posm)
(fun i => (hident i).comp posm) fun i ω => le_max_right _ _
have B: ∀ᵐ ω, Tendsto (fun n : ℕ => (∑ i ∈ range n, (neg ∘ X i) ω) / n) atTop (𝓝 𝔼[neg ∘ X 0]) :=
strong_law_aux7 _ hint.neg_part (fun i j hij => (hindep hij).comp negm negm)
(fun i => (hident i).comp negm) fun i ω => le_max_right _ _
filter_upwards [A, B] with ω hωpos hωneg
convert hωpos.sub hωneg using 1
· simp only [pos, neg, ← sub_div, ← sum_sub_distrib, max_zero_sub_max_neg_zero_eq_self,
Function.comp_apply]
· simp only [← integral_sub hint.pos_part hint.neg_part, max_zero_sub_max_neg_zero_eq_self,
Function.comp_apply]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Scott Morrison, Jens Wagemaker, Johan Commelin
-/
import Mathlib.Algebra.Polynomial.AlgebraMap
import Mathlib.Algebra.Polynomial.BigOperators
import Mathlib.Algebra.Polynomial.Degree.Lemmas
import Mathlib.Algebra.Polynomial.Div
#align_import data.polynomial.ring_division from "leanprover-community/mathlib"@"8efcf8022aac8e01df8d302dcebdbc25d6a886c8"
/-!
# Theory of univariate polynomials
We prove basic results about univariate polynomials.
-/
noncomputable section
open Polynomial
open Finset
namespace Polynomial
universe u v w z
variable {R : Type u} {S : Type v} {T : Type w} {a b : R} {n : ℕ}
section CommRing
variable [CommRing R] {p q : R[X]}
section
variable [Semiring S]
theorem natDegree_pos_of_aeval_root [Algebra R S] {p : R[X]} (hp : p ≠ 0) {z : S}
(hz : aeval z p = 0) (inj : ∀ x : R, algebraMap R S x = 0 → x = 0) : 0 < p.natDegree :=
natDegree_pos_of_eval₂_root hp (algebraMap R S) hz inj
#align polynomial.nat_degree_pos_of_aeval_root Polynomial.natDegree_pos_of_aeval_root
theorem degree_pos_of_aeval_root [Algebra R S] {p : R[X]} (hp : p ≠ 0) {z : S} (hz : aeval z p = 0)
(inj : ∀ x : R, algebraMap R S x = 0 → x = 0) : 0 < p.degree :=
natDegree_pos_iff_degree_pos.mp (natDegree_pos_of_aeval_root hp hz inj)
#align polynomial.degree_pos_of_aeval_root Polynomial.degree_pos_of_aeval_root
theorem modByMonic_eq_of_dvd_sub (hq : q.Monic) {p₁ p₂ : R[X]} (h : q ∣ p₁ - p₂) :
p₁ %ₘ q = p₂ %ₘ q := by
nontriviality R
obtain ⟨f, sub_eq⟩ := h
refine (div_modByMonic_unique (p₂ /ₘ q + f) _ hq ⟨?_, degree_modByMonic_lt _ hq⟩).2
rw [sub_eq_iff_eq_add.mp sub_eq, mul_add, ← add_assoc, modByMonic_add_div _ hq, add_comm]
#align polynomial.mod_by_monic_eq_of_dvd_sub Polynomial.modByMonic_eq_of_dvd_sub
theorem add_modByMonic (p₁ p₂ : R[X]) : (p₁ + p₂) %ₘ q = p₁ %ₘ q + p₂ %ₘ q := by
by_cases hq : q.Monic
· cases' subsingleton_or_nontrivial R with hR hR
· simp only [eq_iff_true_of_subsingleton]
· exact
(div_modByMonic_unique (p₁ /ₘ q + p₂ /ₘ q) _ hq
⟨by
rw [mul_add, add_left_comm, add_assoc, modByMonic_add_div _ hq, ← add_assoc,
add_comm (q * _), modByMonic_add_div _ hq],
(degree_add_le _ _).trans_lt
(max_lt (degree_modByMonic_lt _ hq) (degree_modByMonic_lt _ hq))⟩).2
· simp_rw [modByMonic_eq_of_not_monic _ hq]
#align polynomial.add_mod_by_monic Polynomial.add_modByMonic
theorem smul_modByMonic (c : R) (p : R[X]) : c • p %ₘ q = c • (p %ₘ q) := by
by_cases hq : q.Monic
· cases' subsingleton_or_nontrivial R with hR hR
· simp only [eq_iff_true_of_subsingleton]
· exact
(div_modByMonic_unique (c • (p /ₘ q)) (c • (p %ₘ q)) hq
⟨by rw [mul_smul_comm, ← smul_add, modByMonic_add_div p hq],
(degree_smul_le _ _).trans_lt (degree_modByMonic_lt _ hq)⟩).2
· simp_rw [modByMonic_eq_of_not_monic _ hq]
#align polynomial.smul_mod_by_monic Polynomial.smul_modByMonic
/-- `_ %ₘ q` as an `R`-linear map. -/
@[simps]
def modByMonicHom (q : R[X]) : R[X] →ₗ[R] R[X] where
toFun p := p %ₘ q
map_add' := add_modByMonic
map_smul' := smul_modByMonic
#align polynomial.mod_by_monic_hom Polynomial.modByMonicHom
theorem neg_modByMonic (p mod : R[X]) : (-p) %ₘ mod = - (p %ₘ mod) :=
(modByMonicHom mod).map_neg p
theorem sub_modByMonic (a b mod : R[X]) : (a - b) %ₘ mod = a %ₘ mod - b %ₘ mod :=
(modByMonicHom mod).map_sub a b
end
section
variable [Ring S]
| Mathlib/Algebra/Polynomial/RingDivision.lean | 103 | 107 | theorem aeval_modByMonic_eq_self_of_root [Algebra R S] {p q : R[X]} (hq : q.Monic) {x : S}
(hx : aeval x q = 0) : aeval x (p %ₘ q) = aeval x p := by |
--`eval₂_modByMonic_eq_self_of_root` doesn't work here as it needs commutativity
rw [modByMonic_eq_sub_mul_div p hq, _root_.map_sub, _root_.map_mul, hx, zero_mul,
sub_zero]
|
/-
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
| Mathlib/SetTheory/Game/PGame.lean | 1,433 | 1,433 | theorem lt_neg_iff {x y : PGame} : y < -x ↔ x < -y := by | rw [← neg_neg x, neg_lt_neg_iff, neg_neg]
|
/-
Copyright (c) 2021 Oliver Nash. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Oliver Nash
-/
import Mathlib.Algebra.Lie.BaseChange
import Mathlib.Algebra.Lie.Solvable
import Mathlib.Algebra.Lie.Quotient
import Mathlib.Algebra.Lie.Normalizer
import Mathlib.LinearAlgebra.Eigenspace.Basic
import Mathlib.Order.Filter.AtTopBot
import Mathlib.RingTheory.Artinian
import Mathlib.RingTheory.Nilpotent.Lemmas
import Mathlib.Tactic.Monotonicity
#align_import algebra.lie.nilpotent from "leanprover-community/mathlib"@"6b0169218d01f2837d79ea2784882009a0da1aa1"
/-!
# Nilpotent Lie algebras
Like groups, Lie algebras admit a natural concept of nilpotency. More generally, any Lie module
carries a natural concept of nilpotency. We define these here via the lower central series.
## Main definitions
* `LieModule.lowerCentralSeries`
* `LieModule.IsNilpotent`
## Tags
lie algebra, lower central series, nilpotent
-/
universe u v w w₁ w₂
section NilpotentModules
variable {R : Type u} {L : Type v} {M : Type w}
variable [CommRing R] [LieRing L] [LieAlgebra R L] [AddCommGroup M] [Module R M]
variable [LieRingModule L M] [LieModule R L M]
variable (k : ℕ) (N : LieSubmodule R L M)
namespace LieSubmodule
/-- A generalisation of the lower central series. The zeroth term is a specified Lie submodule of
a Lie module. In the case when we specify the top ideal `⊤` of the Lie algebra, regarded as a Lie
module over itself, we get the usual lower central series of a Lie algebra.
It can be more convenient to work with this generalisation when considering the lower central series
of a Lie submodule, regarded as a Lie module in its own right, since it provides a type-theoretic
expression of the fact that the terms of the Lie submodule's lower central series are also Lie
submodules of the enclosing Lie module.
See also `LieSubmodule.lowerCentralSeries_eq_lcs_comap` and
`LieSubmodule.lowerCentralSeries_map_eq_lcs` below, as well as `LieSubmodule.ucs`. -/
def lcs : LieSubmodule R L M → LieSubmodule R L M :=
(fun N => ⁅(⊤ : LieIdeal R L), N⁆)^[k]
#align lie_submodule.lcs LieSubmodule.lcs
@[simp]
theorem lcs_zero (N : LieSubmodule R L M) : N.lcs 0 = N :=
rfl
#align lie_submodule.lcs_zero LieSubmodule.lcs_zero
@[simp]
theorem lcs_succ : N.lcs (k + 1) = ⁅(⊤ : LieIdeal R L), N.lcs k⁆ :=
Function.iterate_succ_apply' (fun N' => ⁅⊤, N'⁆) k N
#align lie_submodule.lcs_succ LieSubmodule.lcs_succ
@[simp]
lemma lcs_sup {N₁ N₂ : LieSubmodule R L M} {k : ℕ} :
(N₁ ⊔ N₂).lcs k = N₁.lcs k ⊔ N₂.lcs k := by
induction' k with k ih
· simp
· simp only [LieSubmodule.lcs_succ, ih, LieSubmodule.lie_sup]
end LieSubmodule
namespace LieModule
variable (R L M)
/-- The lower central series of Lie submodules of a Lie module. -/
def lowerCentralSeries : LieSubmodule R L M :=
(⊤ : LieSubmodule R L M).lcs k
#align lie_module.lower_central_series LieModule.lowerCentralSeries
@[simp]
theorem lowerCentralSeries_zero : lowerCentralSeries R L M 0 = ⊤ :=
rfl
#align lie_module.lower_central_series_zero LieModule.lowerCentralSeries_zero
@[simp]
theorem lowerCentralSeries_succ :
lowerCentralSeries R L M (k + 1) = ⁅(⊤ : LieIdeal R L), lowerCentralSeries R L M k⁆ :=
(⊤ : LieSubmodule R L M).lcs_succ k
#align lie_module.lower_central_series_succ LieModule.lowerCentralSeries_succ
end LieModule
namespace LieSubmodule
open LieModule
theorem lcs_le_self : N.lcs k ≤ N := by
induction' k with k ih
· simp
· simp only [lcs_succ]
exact (LieSubmodule.mono_lie_right _ _ ⊤ ih).trans (N.lie_le_right ⊤)
#align lie_submodule.lcs_le_self LieSubmodule.lcs_le_self
theorem lowerCentralSeries_eq_lcs_comap : lowerCentralSeries R L N k = (N.lcs k).comap N.incl := by
induction' k with k ih
· simp
· simp only [lcs_succ, lowerCentralSeries_succ] at ih ⊢
have : N.lcs k ≤ N.incl.range := by
rw [N.range_incl]
apply lcs_le_self
rw [ih, LieSubmodule.comap_bracket_eq _ _ N.incl N.ker_incl this]
#align lie_submodule.lower_central_series_eq_lcs_comap LieSubmodule.lowerCentralSeries_eq_lcs_comap
theorem lowerCentralSeries_map_eq_lcs : (lowerCentralSeries R L N k).map N.incl = N.lcs k := by
rw [lowerCentralSeries_eq_lcs_comap, LieSubmodule.map_comap_incl, inf_eq_right]
apply lcs_le_self
#align lie_submodule.lower_central_series_map_eq_lcs LieSubmodule.lowerCentralSeries_map_eq_lcs
end LieSubmodule
namespace LieModule
variable {M₂ : Type w₁} [AddCommGroup M₂] [Module R M₂] [LieRingModule L M₂] [LieModule R L M₂]
variable (R L M)
theorem antitone_lowerCentralSeries : Antitone <| lowerCentralSeries R L M := by
intro l k
induction' k with k ih generalizing l <;> intro h
· exact (Nat.le_zero.mp h).symm ▸ le_rfl
· rcases Nat.of_le_succ h with (hk | hk)
· rw [lowerCentralSeries_succ]
exact (LieSubmodule.mono_lie_right _ _ ⊤ (ih hk)).trans (LieSubmodule.lie_le_right _ _)
· exact hk.symm ▸ le_rfl
#align lie_module.antitone_lower_central_series LieModule.antitone_lowerCentralSeries
theorem eventually_iInf_lowerCentralSeries_eq [IsArtinian R M] :
∀ᶠ l in Filter.atTop, ⨅ k, lowerCentralSeries R L M k = lowerCentralSeries R L M l := by
have h_wf : WellFounded ((· > ·) : (LieSubmodule R L M)ᵒᵈ → (LieSubmodule R L M)ᵒᵈ → Prop) :=
LieSubmodule.wellFounded_of_isArtinian R L M
obtain ⟨n, hn : ∀ m, n ≤ m → lowerCentralSeries R L M n = lowerCentralSeries R L M m⟩ :=
WellFounded.monotone_chain_condition.mp h_wf ⟨_, antitone_lowerCentralSeries R L M⟩
refine Filter.eventually_atTop.mpr ⟨n, fun l hl ↦ le_antisymm (iInf_le _ _) (le_iInf fun m ↦ ?_)⟩
rcases le_or_lt l m with h | h
· rw [← hn _ hl, ← hn _ (hl.trans h)]
· exact antitone_lowerCentralSeries R L M (le_of_lt h)
theorem trivial_iff_lower_central_eq_bot : IsTrivial L M ↔ lowerCentralSeries R L M 1 = ⊥ := by
constructor <;> intro h
· erw [eq_bot_iff, LieSubmodule.lieSpan_le]; rintro m ⟨x, n, hn⟩; rw [← hn, h.trivial]; simp
· rw [LieSubmodule.eq_bot_iff] at h; apply IsTrivial.mk; intro x m; apply h
apply LieSubmodule.subset_lieSpan
-- Porting note: was `use x, m; rfl`
simp only [LieSubmodule.top_coe, Subtype.exists, LieSubmodule.mem_top, exists_prop, true_and,
Set.mem_setOf]
exact ⟨x, m, rfl⟩
#align lie_module.trivial_iff_lower_central_eq_bot LieModule.trivial_iff_lower_central_eq_bot
theorem iterate_toEnd_mem_lowerCentralSeries (x : L) (m : M) (k : ℕ) :
(toEnd R L M x)^[k] m ∈ lowerCentralSeries R L M k := by
induction' k with k ih
· simp only [Nat.zero_eq, Function.iterate_zero, lowerCentralSeries_zero, LieSubmodule.mem_top]
· simp only [lowerCentralSeries_succ, Function.comp_apply, Function.iterate_succ',
toEnd_apply_apply]
exact LieSubmodule.lie_mem_lie _ _ (LieSubmodule.mem_top x) ih
#align lie_module.iterate_to_endomorphism_mem_lower_central_series LieModule.iterate_toEnd_mem_lowerCentralSeries
theorem iterate_toEnd_mem_lowerCentralSeries₂ (x y : L) (m : M) (k : ℕ) :
(toEnd R L M x ∘ₗ toEnd R L M y)^[k] m ∈
lowerCentralSeries R L M (2 * k) := by
induction' k with k ih
· simp
have hk : 2 * k.succ = (2 * k + 1) + 1 := rfl
simp only [lowerCentralSeries_succ, Function.comp_apply, Function.iterate_succ', hk,
toEnd_apply_apply, LinearMap.coe_comp, toEnd_apply_apply]
refine LieSubmodule.lie_mem_lie _ _ (LieSubmodule.mem_top x) ?_
exact LieSubmodule.lie_mem_lie _ _ (LieSubmodule.mem_top y) ih
variable {R L M}
theorem map_lowerCentralSeries_le (f : M →ₗ⁅R,L⁆ M₂) :
(lowerCentralSeries R L M k).map f ≤ lowerCentralSeries R L M₂ k := by
induction' k with k ih
· simp only [Nat.zero_eq, lowerCentralSeries_zero, le_top]
· simp only [LieModule.lowerCentralSeries_succ, LieSubmodule.map_bracket_eq]
exact LieSubmodule.mono_lie_right _ _ ⊤ ih
#align lie_module.map_lower_central_series_le LieModule.map_lowerCentralSeries_le
lemma map_lowerCentralSeries_eq {f : M →ₗ⁅R,L⁆ M₂} (hf : Function.Surjective f) :
(lowerCentralSeries R L M k).map f = lowerCentralSeries R L M₂ k := by
apply le_antisymm (map_lowerCentralSeries_le k f)
induction' k with k ih
· rwa [lowerCentralSeries_zero, lowerCentralSeries_zero, top_le_iff, f.map_top, f.range_eq_top]
· simp only [lowerCentralSeries_succ, LieSubmodule.map_bracket_eq]
apply LieSubmodule.mono_lie_right
assumption
variable (R L M)
open LieAlgebra
theorem derivedSeries_le_lowerCentralSeries (k : ℕ) :
derivedSeries R L k ≤ lowerCentralSeries R L L k := by
induction' k with k h
· rw [derivedSeries_def, derivedSeriesOfIdeal_zero, lowerCentralSeries_zero]
· have h' : derivedSeries R L k ≤ ⊤ := by simp only [le_top]
rw [derivedSeries_def, derivedSeriesOfIdeal_succ, lowerCentralSeries_succ]
exact LieSubmodule.mono_lie _ _ _ _ h' h
#align lie_module.derived_series_le_lower_central_series LieModule.derivedSeries_le_lowerCentralSeries
/-- A Lie module is nilpotent if its lower central series reaches 0 (in a finite number of
steps). -/
class IsNilpotent : Prop where
nilpotent : ∃ k, lowerCentralSeries R L M k = ⊥
#align lie_module.is_nilpotent LieModule.IsNilpotent
theorem exists_lowerCentralSeries_eq_bot_of_isNilpotent [IsNilpotent R L M] :
∃ k, lowerCentralSeries R L M k = ⊥ :=
IsNilpotent.nilpotent
@[simp] lemma iInf_lowerCentralSeries_eq_bot_of_isNilpotent [IsNilpotent R L M] :
⨅ k, lowerCentralSeries R L M k = ⊥ := by
obtain ⟨k, hk⟩ := exists_lowerCentralSeries_eq_bot_of_isNilpotent R L M
rw [eq_bot_iff, ← hk]
exact iInf_le _ _
/-- See also `LieModule.isNilpotent_iff_exists_ucs_eq_top`. -/
theorem isNilpotent_iff : IsNilpotent R L M ↔ ∃ k, lowerCentralSeries R L M k = ⊥ :=
⟨fun h => h.nilpotent, fun h => ⟨h⟩⟩
#align lie_module.is_nilpotent_iff LieModule.isNilpotent_iff
variable {R L M}
theorem _root_.LieSubmodule.isNilpotent_iff_exists_lcs_eq_bot (N : LieSubmodule R L M) :
LieModule.IsNilpotent R L N ↔ ∃ k, N.lcs k = ⊥ := by
rw [isNilpotent_iff]
refine exists_congr fun k => ?_
rw [N.lowerCentralSeries_eq_lcs_comap k, LieSubmodule.comap_incl_eq_bot,
inf_eq_right.mpr (N.lcs_le_self k)]
#align lie_submodule.is_nilpotent_iff_exists_lcs_eq_bot LieSubmodule.isNilpotent_iff_exists_lcs_eq_bot
variable (R L M)
instance (priority := 100) trivialIsNilpotent [IsTrivial L M] : IsNilpotent R L M :=
⟨by use 1; change ⁅⊤, ⊤⁆ = ⊥; simp⟩
#align lie_module.trivial_is_nilpotent LieModule.trivialIsNilpotent
theorem exists_forall_pow_toEnd_eq_zero [hM : IsNilpotent R L M] :
∃ k : ℕ, ∀ x : L, toEnd R L M x ^ k = 0 := by
obtain ⟨k, hM⟩ := hM
use k
intro x; ext m
rw [LinearMap.pow_apply, LinearMap.zero_apply, ← @LieSubmodule.mem_bot R L M, ← hM]
exact iterate_toEnd_mem_lowerCentralSeries R L M x m k
#align lie_module.nilpotent_endo_of_nilpotent_module LieModule.exists_forall_pow_toEnd_eq_zero
theorem isNilpotent_toEnd_of_isNilpotent [IsNilpotent R L M] (x : L) :
_root_.IsNilpotent (toEnd R L M x) := by
change ∃ k, toEnd R L M x ^ k = 0
have := exists_forall_pow_toEnd_eq_zero R L M
tauto
theorem isNilpotent_toEnd_of_isNilpotent₂ [IsNilpotent R L M] (x y : L) :
_root_.IsNilpotent (toEnd R L M x ∘ₗ toEnd R L M y) := by
obtain ⟨k, hM⟩ := exists_lowerCentralSeries_eq_bot_of_isNilpotent R L M
replace hM : lowerCentralSeries R L M (2 * k) = ⊥ := by
rw [eq_bot_iff, ← hM]; exact antitone_lowerCentralSeries R L M (by omega)
use k
ext m
rw [LinearMap.pow_apply, LinearMap.zero_apply, ← LieSubmodule.mem_bot (R := R) (L := L), ← hM]
exact iterate_toEnd_mem_lowerCentralSeries₂ R L M x y m k
@[simp] lemma maxGenEigenSpace_toEnd_eq_top [IsNilpotent R L M] (x : L) :
((toEnd R L M x).maxGenEigenspace 0) = ⊤ := by
ext m
simp only [Module.End.mem_maxGenEigenspace, zero_smul, sub_zero, Submodule.mem_top,
iff_true]
obtain ⟨k, hk⟩ := exists_forall_pow_toEnd_eq_zero R L M
exact ⟨k, by simp [hk x]⟩
/-- If the quotient of a Lie module `M` by a Lie submodule on which the Lie algebra acts trivially
is nilpotent then `M` is nilpotent.
This is essentially the Lie module equivalent of the fact that a central
extension of nilpotent Lie algebras is nilpotent. See `LieAlgebra.nilpotent_of_nilpotent_quotient`
below for the corresponding result for Lie algebras. -/
theorem nilpotentOfNilpotentQuotient {N : LieSubmodule R L M} (h₁ : N ≤ maxTrivSubmodule R L M)
(h₂ : IsNilpotent R L (M ⧸ N)) : IsNilpotent R L M := by
obtain ⟨k, hk⟩ := h₂
use k + 1
simp only [lowerCentralSeries_succ]
suffices lowerCentralSeries R L M k ≤ N by
replace this := LieSubmodule.mono_lie_right _ _ ⊤ (le_trans this h₁)
rwa [ideal_oper_maxTrivSubmodule_eq_bot, le_bot_iff] at this
rw [← LieSubmodule.Quotient.map_mk'_eq_bot_le, ← le_bot_iff, ← hk]
exact map_lowerCentralSeries_le k (LieSubmodule.Quotient.mk' N)
#align lie_module.nilpotent_of_nilpotent_quotient LieModule.nilpotentOfNilpotentQuotient
theorem isNilpotent_quotient_iff :
IsNilpotent R L (M ⧸ N) ↔ ∃ k, lowerCentralSeries R L M k ≤ N := by
rw [LieModule.isNilpotent_iff]
refine exists_congr fun k ↦ ?_
rw [← LieSubmodule.Quotient.map_mk'_eq_bot_le, map_lowerCentralSeries_eq k
(LieSubmodule.Quotient.surjective_mk' N)]
theorem iInf_lcs_le_of_isNilpotent_quot (h : IsNilpotent R L (M ⧸ N)) :
⨅ k, lowerCentralSeries R L M k ≤ N := by
obtain ⟨k, hk⟩ := (isNilpotent_quotient_iff R L M N).mp h
exact iInf_le_of_le k hk
/-- Given a nilpotent Lie module `M` with lower central series `M = C₀ ≥ C₁ ≥ ⋯ ≥ Cₖ = ⊥`, this is
the natural number `k` (the number of inclusions).
For a non-nilpotent module, we use the junk value 0. -/
noncomputable def nilpotencyLength : ℕ :=
sInf {k | lowerCentralSeries R L M k = ⊥}
#align lie_module.nilpotency_length LieModule.nilpotencyLength
@[simp]
theorem nilpotencyLength_eq_zero_iff [IsNilpotent R L M] :
nilpotencyLength R L M = 0 ↔ Subsingleton M := by
let s := {k | lowerCentralSeries R L M k = ⊥}
have hs : s.Nonempty := by
obtain ⟨k, hk⟩ := (by infer_instance : IsNilpotent R L M)
exact ⟨k, hk⟩
change sInf s = 0 ↔ _
rw [← LieSubmodule.subsingleton_iff R L M, ← subsingleton_iff_bot_eq_top, ←
lowerCentralSeries_zero, @eq_comm (LieSubmodule R L M)]
refine ⟨fun h => h ▸ Nat.sInf_mem hs, fun h => ?_⟩
rw [Nat.sInf_eq_zero]
exact Or.inl h
#align lie_module.nilpotency_length_eq_zero_iff LieModule.nilpotencyLength_eq_zero_iff
theorem nilpotencyLength_eq_succ_iff (k : ℕ) :
nilpotencyLength R L M = k + 1 ↔
lowerCentralSeries R L M (k + 1) = ⊥ ∧ lowerCentralSeries R L M k ≠ ⊥ := by
let s := {k | lowerCentralSeries R L M k = ⊥}
change sInf s = k + 1 ↔ k + 1 ∈ s ∧ k ∉ s
have hs : ∀ k₁ k₂, k₁ ≤ k₂ → k₁ ∈ s → k₂ ∈ s := by
rintro k₁ k₂ h₁₂ (h₁ : lowerCentralSeries R L M k₁ = ⊥)
exact eq_bot_iff.mpr (h₁ ▸ antitone_lowerCentralSeries R L M h₁₂)
exact Nat.sInf_upward_closed_eq_succ_iff hs k
#align lie_module.nilpotency_length_eq_succ_iff LieModule.nilpotencyLength_eq_succ_iff
@[simp]
theorem nilpotencyLength_eq_one_iff [Nontrivial M] :
nilpotencyLength R L M = 1 ↔ IsTrivial L M := by
rw [nilpotencyLength_eq_succ_iff, ← trivial_iff_lower_central_eq_bot]
simp
theorem isTrivial_of_nilpotencyLength_le_one [IsNilpotent R L M] (h : nilpotencyLength R L M ≤ 1) :
IsTrivial L M := by
nontriviality M
cases' Nat.le_one_iff_eq_zero_or_eq_one.mp h with h h
· rw [nilpotencyLength_eq_zero_iff] at h; infer_instance
· rwa [nilpotencyLength_eq_one_iff] at h
/-- Given a non-trivial nilpotent Lie module `M` with lower central series
`M = C₀ ≥ C₁ ≥ ⋯ ≥ Cₖ = ⊥`, this is the `k-1`th term in the lower central series (the last
non-trivial term).
For a trivial or non-nilpotent module, this is the bottom submodule, `⊥`. -/
noncomputable def lowerCentralSeriesLast : LieSubmodule R L M :=
match nilpotencyLength R L M with
| 0 => ⊥
| k + 1 => lowerCentralSeries R L M k
#align lie_module.lower_central_series_last LieModule.lowerCentralSeriesLast
theorem lowerCentralSeriesLast_le_max_triv :
lowerCentralSeriesLast R L M ≤ maxTrivSubmodule R L M := by
rw [lowerCentralSeriesLast]
cases' h : nilpotencyLength R L M with k
· exact bot_le
· rw [le_max_triv_iff_bracket_eq_bot]
rw [nilpotencyLength_eq_succ_iff, lowerCentralSeries_succ] at h
exact h.1
#align lie_module.lower_central_series_last_le_max_triv LieModule.lowerCentralSeriesLast_le_max_triv
theorem nontrivial_lowerCentralSeriesLast [Nontrivial M] [IsNilpotent R L M] :
Nontrivial (lowerCentralSeriesLast R L M) := by
rw [LieSubmodule.nontrivial_iff_ne_bot, lowerCentralSeriesLast]
cases h : nilpotencyLength R L M
· rw [nilpotencyLength_eq_zero_iff, ← not_nontrivial_iff_subsingleton] at h
contradiction
· rw [nilpotencyLength_eq_succ_iff] at h
exact h.2
#align lie_module.nontrivial_lower_central_series_last LieModule.nontrivial_lowerCentralSeriesLast
theorem lowerCentralSeriesLast_le_of_not_isTrivial [IsNilpotent R L M] (h : ¬ IsTrivial L M) :
lowerCentralSeriesLast R L M ≤ lowerCentralSeries R L M 1 := by
rw [lowerCentralSeriesLast]
replace h : 1 < nilpotencyLength R L M := by
by_contra contra
have := isTrivial_of_nilpotencyLength_le_one R L M (not_lt.mp contra)
contradiction
cases' hk : nilpotencyLength R L M with k <;> rw [hk] at h
· contradiction
· exact antitone_lowerCentralSeries _ _ _ (Nat.lt_succ.mp h)
/-- For a nilpotent Lie module `M` of a Lie algebra `L`, the first term in the lower central series
of `M` contains a non-zero element on which `L` acts trivially unless the entire action is trivial.
Taking `M = L`, this provides a useful characterisation of Abelian-ness for nilpotent Lie
algebras. -/
lemma disjoint_lowerCentralSeries_maxTrivSubmodule_iff [IsNilpotent R L M] :
Disjoint (lowerCentralSeries R L M 1) (maxTrivSubmodule R L M) ↔ IsTrivial L M := by
refine ⟨fun h ↦ ?_, fun h ↦ by simp⟩
nontriviality M
by_contra contra
have : lowerCentralSeriesLast R L M ≤ lowerCentralSeries R L M 1 ⊓ maxTrivSubmodule R L M :=
le_inf_iff.mpr ⟨lowerCentralSeriesLast_le_of_not_isTrivial R L M contra,
lowerCentralSeriesLast_le_max_triv R L M⟩
suffices ¬ Nontrivial (lowerCentralSeriesLast R L M) by
exact this (nontrivial_lowerCentralSeriesLast R L M)
rw [h.eq_bot, le_bot_iff] at this
exact this ▸ not_nontrivial _
theorem nontrivial_max_triv_of_isNilpotent [Nontrivial M] [IsNilpotent R L M] :
Nontrivial (maxTrivSubmodule R L M) :=
Set.nontrivial_mono (lowerCentralSeriesLast_le_max_triv R L M)
(nontrivial_lowerCentralSeriesLast R L M)
#align lie_module.nontrivial_max_triv_of_is_nilpotent LieModule.nontrivial_max_triv_of_isNilpotent
@[simp]
theorem coe_lcs_range_toEnd_eq (k : ℕ) :
(lowerCentralSeries R (toEnd R L M).range M k : Submodule R M) =
lowerCentralSeries R L M k := by
induction' k with k ih
· simp
· simp only [lowerCentralSeries_succ, LieSubmodule.lieIdeal_oper_eq_linear_span', ←
(lowerCentralSeries R (toEnd R L M).range M k).mem_coeSubmodule, ih]
congr
ext m
constructor
· rintro ⟨⟨-, ⟨y, rfl⟩⟩, -, n, hn, rfl⟩
exact ⟨y, LieSubmodule.mem_top _, n, hn, rfl⟩
· rintro ⟨x, -, n, hn, rfl⟩
exact
⟨⟨toEnd R L M x, LieHom.mem_range_self _ x⟩, LieSubmodule.mem_top _, n, hn, rfl⟩
#align lie_module.coe_lcs_range_to_endomorphism_eq LieModule.coe_lcs_range_toEnd_eq
@[simp]
theorem isNilpotent_range_toEnd_iff :
IsNilpotent R (toEnd R L M).range M ↔ IsNilpotent R L M := by
constructor <;> rintro ⟨k, hk⟩ <;> use k <;>
rw [← LieSubmodule.coe_toSubmodule_eq_iff] at hk ⊢ <;>
simpa using hk
#align lie_module.is_nilpotent_range_to_endomorphism_iff LieModule.isNilpotent_range_toEnd_iff
end LieModule
namespace LieSubmodule
variable {N₁ N₂ : LieSubmodule R L M}
/-- The upper (aka ascending) central series.
See also `LieSubmodule.lcs`. -/
def ucs (k : ℕ) : LieSubmodule R L M → LieSubmodule R L M :=
normalizer^[k]
#align lie_submodule.ucs LieSubmodule.ucs
@[simp]
theorem ucs_zero : N.ucs 0 = N :=
rfl
#align lie_submodule.ucs_zero LieSubmodule.ucs_zero
@[simp]
theorem ucs_succ (k : ℕ) : N.ucs (k + 1) = (N.ucs k).normalizer :=
Function.iterate_succ_apply' normalizer k N
#align lie_submodule.ucs_succ LieSubmodule.ucs_succ
theorem ucs_add (k l : ℕ) : N.ucs (k + l) = (N.ucs l).ucs k :=
Function.iterate_add_apply normalizer k l N
#align lie_submodule.ucs_add LieSubmodule.ucs_add
@[mono]
theorem ucs_mono (k : ℕ) (h : N₁ ≤ N₂) : N₁.ucs k ≤ N₂.ucs k := by
induction' k with k ih
· simpa
simp only [ucs_succ]
-- Porting note: `mono` makes no progress
apply monotone_normalizer ih
#align lie_submodule.ucs_mono LieSubmodule.ucs_mono
theorem ucs_eq_self_of_normalizer_eq_self (h : N₁.normalizer = N₁) (k : ℕ) : N₁.ucs k = N₁ := by
induction' k with k ih
· simp
· rwa [ucs_succ, ih]
#align lie_submodule.ucs_eq_self_of_normalizer_eq_self LieSubmodule.ucs_eq_self_of_normalizer_eq_self
/-- If a Lie module `M` contains a self-normalizing Lie submodule `N`, then all terms of the upper
central series of `M` are contained in `N`.
An important instance of this situation arises from a Cartan subalgebra `H ⊆ L` with the roles of
`L`, `M`, `N` played by `H`, `L`, `H`, respectively. -/
| Mathlib/Algebra/Lie/Nilpotent.lean | 504 | 508 | theorem ucs_le_of_normalizer_eq_self (h : N₁.normalizer = N₁) (k : ℕ) :
(⊥ : LieSubmodule R L M).ucs k ≤ N₁ := by |
rw [← ucs_eq_self_of_normalizer_eq_self h k]
mono
simp
|
/-
Copyright (c) 2020 Adam Topaz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Adam Topaz
-/
import Mathlib.CategoryTheory.Monad.Types
import Mathlib.CategoryTheory.Monad.Limits
import Mathlib.CategoryTheory.Equivalence
import Mathlib.Topology.Category.CompHaus.Basic
import Mathlib.Topology.Category.Profinite.Basic
import Mathlib.Data.Set.Constructions
#align_import topology.category.Compactum from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Compacta and Compact Hausdorff Spaces
Recall that, given a monad `M` on `Type*`, an *algebra* for `M` consists of the following data:
- A type `X : Type*`
- A "structure" map `M X → X`.
This data must also satisfy a distributivity and unit axiom, and algebras for `M` form a category
in an evident way.
See the file `CategoryTheory.Monad.Algebra` for a general version, as well as the following link.
https://ncatlab.org/nlab/show/monad
This file proves the equivalence between the category of *compact Hausdorff topological spaces*
and the category of algebras for the *ultrafilter monad*.
## Notation:
Here are the main objects introduced in this file.
- `Compactum` is the type of compacta, which we define as algebras for the ultrafilter monad.
- `compactumToCompHaus` is the functor `Compactum ⥤ CompHaus`. Here `CompHaus` is the usual
category of compact Hausdorff spaces.
- `compactumToCompHaus.isEquivalence` is a term of type `IsEquivalence compactumToCompHaus`.
The proof of this equivalence is a bit technical. But the idea is quite simply that the structure
map `Ultrafilter X → X` for an algebra `X` of the ultrafilter monad should be considered as the map
sending an ultrafilter to its limit in `X`. The topology on `X` is then defined by mimicking the
characterization of open sets in terms of ultrafilters.
Any `X : Compactum` is endowed with a coercion to `Type*`, as well as the following instances:
- `TopologicalSpace X`.
- `CompactSpace X`.
- `T2Space X`.
Any morphism `f : X ⟶ Y` of is endowed with a coercion to a function `X → Y`, which is shown to
be continuous in `continuous_of_hom`.
The function `Compactum.ofTopologicalSpace` can be used to construct a `Compactum` from a
topological space which satisfies `CompactSpace` and `T2Space`.
We also add wrappers around structures which already exist. Here are the main ones, all in the
`Compactum` namespace:
- `forget : Compactum ⥤ Type*` is the forgetful functor, which induces a `ConcreteCategory`
instance for `Compactum`.
- `free : Type* ⥤ Compactum` is the left adjoint to `forget`, and the adjunction is in `adj`.
- `str : Ultrafilter X → X` is the structure map for `X : Compactum`.
The notation `X.str` is preferred.
- `join : Ultrafilter (Ultrafilter X) → Ultrafilter X` is the monadic join for `X : Compactum`.
Again, the notation `X.join` is preferred.
- `incl : X → Ultrafilter X` is the unit for `X : Compactum`. The notation `X.incl` is preferred.
## References
- E. Manes, Algebraic Theories, Graduate Texts in Mathematics 26, Springer-Verlag, 1976.
- https://ncatlab.org/nlab/show/ultrafilter
-/
-- Porting note: "Compactum" is already upper case
set_option linter.uppercaseLean3 false
universe u
open CategoryTheory Filter Ultrafilter TopologicalSpace CategoryTheory.Limits FiniteInter
open scoped Classical
open Topology
local notation "β" => ofTypeMonad Ultrafilter
/-- The type `Compactum` of Compacta, defined as algebras for the ultrafilter monad. -/
def Compactum :=
Monad.Algebra β deriving Category, Inhabited
#align Compactum Compactum
namespace Compactum
/-- The forgetful functor to Type* -/
def forget : Compactum ⥤ Type* :=
Monad.forget _ --deriving CreatesLimits, Faithful
-- Porting note: deriving fails, adding manually. Note `CreatesLimits` now noncomputable
#align Compactum.forget Compactum.forget
instance : forget.Faithful :=
show (Monad.forget _).Faithful from inferInstance
noncomputable instance : CreatesLimits forget :=
show CreatesLimits <| Monad.forget _ from inferInstance
/-- The "free" Compactum functor. -/
def free : Type* ⥤ Compactum :=
Monad.free _
#align Compactum.free Compactum.free
/-- The adjunction between `free` and `forget`. -/
def adj : free ⊣ forget :=
Monad.adj _
#align Compactum.adj Compactum.adj
-- Basic instances
instance : ConcreteCategory Compactum where forget := forget
-- Porting note: changed from forget to X.A
instance : CoeSort Compactum Type* :=
⟨fun X => X.A⟩
instance {X Y : Compactum} : CoeFun (X ⟶ Y) fun _ => X → Y :=
⟨fun f => f.f⟩
instance : HasLimits Compactum :=
hasLimits_of_hasLimits_createsLimits forget
/-- The structure map for a compactum, essentially sending an ultrafilter to its limit. -/
def str (X : Compactum) : Ultrafilter X → X :=
X.a
#align Compactum.str Compactum.str
/-- The monadic join. -/
def join (X : Compactum) : Ultrafilter (Ultrafilter X) → Ultrafilter X :=
(β ).μ.app _
#align Compactum.join Compactum.join
/-- The inclusion of `X` into `Ultrafilter X`. -/
def incl (X : Compactum) : X → Ultrafilter X :=
(β ).η.app _
#align Compactum.incl Compactum.incl
@[simp]
theorem str_incl (X : Compactum) (x : X) : X.str (X.incl x) = x := by
change ((β ).η.app _ ≫ X.a) _ = _
rw [Monad.Algebra.unit]
rfl
#align Compactum.str_incl Compactum.str_incl
@[simp]
theorem str_hom_commute (X Y : Compactum) (f : X ⟶ Y) (xs : Ultrafilter X) :
f (X.str xs) = Y.str (map f xs) := by
change (X.a ≫ f.f) _ = _
rw [← f.h]
rfl
#align Compactum.str_hom_commute Compactum.str_hom_commute
@[simp]
theorem join_distrib (X : Compactum) (uux : Ultrafilter (Ultrafilter X)) :
X.str (X.join uux) = X.str (map X.str uux) := by
change ((β ).μ.app _ ≫ X.a) _ = _
rw [Monad.Algebra.assoc]
rfl
#align Compactum.join_distrib Compactum.join_distrib
-- Porting note: changes to X.A from X since Lean can't see through X to X.A below
instance {X : Compactum} : TopologicalSpace X.A where
IsOpen U := ∀ F : Ultrafilter X, X.str F ∈ U → U ∈ F
isOpen_univ _ _ := Filter.univ_sets _
isOpen_inter _ _ h3 h4 _ h6 := Filter.inter_sets _ (h3 _ h6.1) (h4 _ h6.2)
isOpen_sUnion := fun _ h1 _ ⟨T, hT, h2⟩ =>
mem_of_superset (h1 T hT _ h2) (Set.subset_sUnion_of_mem hT)
theorem isClosed_iff {X : Compactum} (S : Set X) :
IsClosed S ↔ ∀ F : Ultrafilter X, S ∈ F → X.str F ∈ S := by
rw [← isOpen_compl_iff]
constructor
· intro cond F h
by_contra c
specialize cond F c
rw [compl_mem_iff_not_mem] at cond
contradiction
· intro h1 F h2
specialize h1 F
cases' F.mem_or_compl_mem S with h h
exacts [absurd (h1 h) h2, h]
#align Compactum.is_closed_iff Compactum.isClosed_iff
instance {X : Compactum} : CompactSpace X := by
constructor
rw [isCompact_iff_ultrafilter_le_nhds]
intro F _
refine ⟨X.str F, by tauto, ?_⟩
rw [le_nhds_iff]
intro S h1 h2
exact h2 F h1
/-- A local definition used only in the proofs. -/
private def basic {X : Compactum} (A : Set X) : Set (Ultrafilter X) :=
{ F | A ∈ F }
/-- A local definition used only in the proofs. -/
private def cl {X : Compactum} (A : Set X) : Set X :=
X.str '' basic A
private theorem basic_inter {X : Compactum} (A B : Set X) : basic (A ∩ B) = basic A ∩ basic B := by
ext G
constructor
· intro hG
constructor <;> filter_upwards [hG] with _
exacts [And.left, And.right]
· rintro ⟨h1, h2⟩
exact inter_mem h1 h2
private theorem subset_cl {X : Compactum} (A : Set X) : A ⊆ cl A := fun a ha =>
⟨X.incl a, ha, by simp⟩
private theorem cl_cl {X : Compactum} (A : Set X) : cl (cl A) ⊆ cl A := by
rintro _ ⟨F, hF, rfl⟩
-- Notation to be used in this proof.
let fsu := Finset (Set (Ultrafilter X))
let ssu := Set (Set (Ultrafilter X))
let ι : fsu → ssu := fun x ↦ ↑x
let C0 : ssu := { Z | ∃ B ∈ F, X.str ⁻¹' B = Z }
let AA := { G : Ultrafilter X | A ∈ G }
let C1 := insert AA C0
let C2 := finiteInterClosure C1
-- C0 is closed under intersections.
have claim1 : ∀ (B) (_ : B ∈ C0) (C) (_ : C ∈ C0), B ∩ C ∈ C0 := by
rintro B ⟨Q, hQ, rfl⟩ C ⟨R, hR, rfl⟩
use Q ∩ R
simp only [and_true_iff, eq_self_iff_true, Set.preimage_inter]
exact inter_sets _ hQ hR
-- All sets in C0 are nonempty.
have claim2 : ∀ B ∈ C0, Set.Nonempty B := by
rintro B ⟨Q, hQ, rfl⟩
obtain ⟨q⟩ := Filter.nonempty_of_mem hQ
use X.incl q
simpa
-- The intersection of AA with every set in C0 is nonempty.
have claim3 : ∀ B ∈ C0, (AA ∩ B).Nonempty := by
rintro B ⟨Q, hQ, rfl⟩
have : (Q ∩ cl A).Nonempty := Filter.nonempty_of_mem (inter_mem hQ hF)
rcases this with ⟨q, hq1, P, hq2, hq3⟩
refine ⟨P, hq2, ?_⟩
rw [← hq3] at hq1
simpa
-- Suffices to show that the intersection of any finite subcollection of C1 is nonempty.
suffices ∀ T : fsu, ι T ⊆ C1 → (⋂₀ ι T).Nonempty by
obtain ⟨G, h1⟩ := exists_ultrafilter_of_finite_inter_nonempty _ this
use X.join G
have : G.map X.str = F := Ultrafilter.coe_le_coe.1 fun S hS => h1 (Or.inr ⟨S, hS, rfl⟩)
rw [join_distrib, this]
exact ⟨h1 (Or.inl rfl), rfl⟩
-- C2 is closed under finite intersections (by construction!).
have claim4 := finiteInterClosure_finiteInter C1
-- C0 is closed under finite intersections by claim1.
have claim5 : FiniteInter C0 := ⟨⟨_, univ_mem, Set.preimage_univ⟩, claim1⟩
-- Every element of C2 is nonempty.
have claim6 : ∀ P ∈ C2, (P : Set (Ultrafilter X)).Nonempty := by
suffices ∀ P ∈ C2, P ∈ C0 ∨ ∃ Q ∈ C0, P = AA ∩ Q by
intro P hP
cases' this P hP with h h
· exact claim2 _ h
· rcases h with ⟨Q, hQ, rfl⟩
exact claim3 _ hQ
intro P hP
exact claim5.finiteInterClosure_insert _ hP
intro T hT
-- Suffices to show that the intersection of the T's is contained in C2.
suffices ⋂₀ ι T ∈ C2 by exact claim6 _ this
-- Finish
apply claim4.finiteInter_mem T
intro t ht
exact finiteInterClosure.basic (@hT t ht)
theorem isClosed_cl {X : Compactum} (A : Set X) : IsClosed (cl A) := by
rw [isClosed_iff]
intro F hF
exact cl_cl _ ⟨F, hF, rfl⟩
#align Compactum.is_closed_cl Compactum.isClosed_cl
| Mathlib/Topology/Category/Compactum.lean | 282 | 350 | theorem str_eq_of_le_nhds {X : Compactum} (F : Ultrafilter X) (x : X) : ↑F ≤ 𝓝 x → X.str F = x := by |
-- Notation to be used in this proof.
let fsu := Finset (Set (Ultrafilter X))
let ssu := Set (Set (Ultrafilter X))
let ι : fsu → ssu := fun x ↦ ↑x
let T0 : ssu := { S | ∃ A ∈ F, S = basic A }
let AA := X.str ⁻¹' {x}
let T1 := insert AA T0
let T2 := finiteInterClosure T1
intro cond
-- If F contains a closed set A, then x is contained in A.
have claim1 : ∀ A : Set X, IsClosed A → A ∈ F → x ∈ A := by
intro A hA h
by_contra H
rw [le_nhds_iff] at cond
specialize cond Aᶜ H hA.isOpen_compl
rw [Ultrafilter.mem_coe, Ultrafilter.compl_mem_iff_not_mem] at cond
contradiction
-- If A ∈ F, then x ∈ cl A.
have claim2 : ∀ A : Set X, A ∈ F → x ∈ cl A := by
intro A hA
exact claim1 (cl A) (isClosed_cl A) (mem_of_superset hA (subset_cl A))
-- T0 is closed under intersections.
have claim3 : ∀ (S1) (_ : S1 ∈ T0) (S2) (_ : S2 ∈ T0), S1 ∩ S2 ∈ T0 := by
rintro S1 ⟨S1, hS1, rfl⟩ S2 ⟨S2, hS2, rfl⟩
exact ⟨S1 ∩ S2, inter_mem hS1 hS2, by simp [basic_inter]⟩
-- For every S ∈ T0, the intersection AA ∩ S is nonempty.
have claim4 : ∀ S ∈ T0, (AA ∩ S).Nonempty := by
rintro S ⟨S, hS, rfl⟩
rcases claim2 _ hS with ⟨G, hG, hG2⟩
exact ⟨G, hG2, hG⟩
-- Every element of T0 is nonempty.
have claim5 : ∀ S ∈ T0, Set.Nonempty S := by
rintro S ⟨S, hS, rfl⟩
exact ⟨F, hS⟩
-- Every element of T2 is nonempty.
have claim6 : ∀ S ∈ T2, Set.Nonempty S := by
suffices ∀ S ∈ T2, S ∈ T0 ∨ ∃ Q ∈ T0, S = AA ∩ Q by
intro S hS
cases' this _ hS with h h
· exact claim5 S h
· rcases h with ⟨Q, hQ, rfl⟩
exact claim4 Q hQ
intro S hS
apply finiteInterClosure_insert
· constructor
· use Set.univ
refine ⟨Filter.univ_sets _, ?_⟩
ext
refine ⟨?_, by tauto⟩
· intro
apply Filter.univ_sets
· exact claim3
· exact hS
-- It suffices to show that the intersection of any finite subset of T1 is nonempty.
suffices ∀ F : fsu, ↑F ⊆ T1 → (⋂₀ ι F).Nonempty by
obtain ⟨G, h1⟩ := Ultrafilter.exists_ultrafilter_of_finite_inter_nonempty _ this
have c1 : X.join G = F := Ultrafilter.coe_le_coe.1 fun P hP => h1 (Or.inr ⟨P, hP, rfl⟩)
have c2 : G.map X.str = X.incl x := by
refine Ultrafilter.coe_le_coe.1 fun P hP => ?_
apply mem_of_superset (h1 (Or.inl rfl))
rintro x ⟨rfl⟩
exact hP
simp [← c1, c2]
-- Finish...
intro T hT
refine claim6 _ (finiteInter_mem (.finiteInterClosure_finiteInter _) _ ?_)
intro t ht
exact finiteInterClosure.basic (@hT t ht)
|
/-
Copyright (c) 2020 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Analysis.SpecialFunctions.ExpDeriv
#align_import analysis.ODE.gronwall from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Grönwall's inequality
The main technical result of this file is the Grönwall-like inequality
`norm_le_gronwallBound_of_norm_deriv_right_le`. It states that if `f : ℝ → E` satisfies `‖f a‖ ≤ δ`
and `∀ x ∈ [a, b), ‖f' x‖ ≤ K * ‖f x‖ + ε`, then for all `x ∈ [a, b]` we have `‖f x‖ ≤ δ * exp (K *
x) + (ε / K) * (exp (K * x) - 1)`.
Then we use this inequality to prove some estimates on the possible rate of growth of the distance
between two approximate or exact solutions of an ordinary differential equation.
The proofs are based on [Hubbard and West, *Differential Equations: A Dynamical Systems Approach*,
Sec. 4.5][HubbardWest-ode], where `norm_le_gronwallBound_of_norm_deriv_right_le` is called
“Fundamental Inequality”.
## TODO
- Once we have FTC, prove an inequality for a function satisfying `‖f' x‖ ≤ K x * ‖f x‖ + ε`,
or more generally `liminf_{y→x+0} (f y - f x)/(y - x) ≤ K x * f x + ε` with any sign
of `K x` and `f x`.
-/
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E] {F : Type*} [NormedAddCommGroup F]
[NormedSpace ℝ F]
open Metric Set Asymptotics Filter Real
open scoped Classical Topology NNReal
/-! ### Technical lemmas about `gronwallBound` -/
/-- Upper bound used in several Grönwall-like inequalities. -/
noncomputable def gronwallBound (δ K ε x : ℝ) : ℝ :=
if K = 0 then δ + ε * x else δ * exp (K * x) + ε / K * (exp (K * x) - 1)
#align gronwall_bound gronwallBound
theorem gronwallBound_K0 (δ ε : ℝ) : gronwallBound δ 0 ε = fun x => δ + ε * x :=
funext fun _ => if_pos rfl
set_option linter.uppercaseLean3 false in
#align gronwall_bound_K0 gronwallBound_K0
theorem gronwallBound_of_K_ne_0 {δ K ε : ℝ} (hK : K ≠ 0) :
gronwallBound δ K ε = fun x => δ * exp (K * x) + ε / K * (exp (K * x) - 1) :=
funext fun _ => if_neg hK
set_option linter.uppercaseLean3 false in
#align gronwall_bound_of_K_ne_0 gronwallBound_of_K_ne_0
theorem hasDerivAt_gronwallBound (δ K ε x : ℝ) :
HasDerivAt (gronwallBound δ K ε) (K * gronwallBound δ K ε x + ε) x := by
by_cases hK : K = 0
· subst K
simp only [gronwallBound_K0, zero_mul, zero_add]
convert ((hasDerivAt_id x).const_mul ε).const_add δ
rw [mul_one]
· simp only [gronwallBound_of_K_ne_0 hK]
convert (((hasDerivAt_id x).const_mul K).exp.const_mul δ).add
((((hasDerivAt_id x).const_mul K).exp.sub_const 1).const_mul (ε / K)) using 1
simp only [id, mul_add, (mul_assoc _ _ _).symm, mul_comm _ K, mul_div_cancel₀ _ hK]
ring
#align has_deriv_at_gronwall_bound hasDerivAt_gronwallBound
theorem hasDerivAt_gronwallBound_shift (δ K ε x a : ℝ) :
HasDerivAt (fun y => gronwallBound δ K ε (y - a)) (K * gronwallBound δ K ε (x - a) + ε) x := by
convert (hasDerivAt_gronwallBound δ K ε _).comp x ((hasDerivAt_id x).sub_const a) using 1
rw [id, mul_one]
#align has_deriv_at_gronwall_bound_shift hasDerivAt_gronwallBound_shift
theorem gronwallBound_x0 (δ K ε : ℝ) : gronwallBound δ K ε 0 = δ := by
by_cases hK : K = 0
· simp only [gronwallBound, if_pos hK, mul_zero, add_zero]
· simp only [gronwallBound, if_neg hK, mul_zero, exp_zero, sub_self, mul_one,
add_zero]
#align gronwall_bound_x0 gronwallBound_x0
theorem gronwallBound_ε0 (δ K x : ℝ) : gronwallBound δ K 0 x = δ * exp (K * x) := by
by_cases hK : K = 0
· simp only [gronwallBound_K0, hK, zero_mul, exp_zero, add_zero, mul_one]
· simp only [gronwallBound_of_K_ne_0 hK, zero_div, zero_mul, add_zero]
#align gronwall_bound_ε0 gronwallBound_ε0
theorem gronwallBound_ε0_δ0 (K x : ℝ) : gronwallBound 0 K 0 x = 0 := by
simp only [gronwallBound_ε0, zero_mul]
#align gronwall_bound_ε0_δ0 gronwallBound_ε0_δ0
theorem gronwallBound_continuous_ε (δ K x : ℝ) : Continuous fun ε => gronwallBound δ K ε x := by
by_cases hK : K = 0
· simp only [gronwallBound_K0, hK]
exact continuous_const.add (continuous_id.mul continuous_const)
· simp only [gronwallBound_of_K_ne_0 hK]
exact continuous_const.add ((continuous_id.mul continuous_const).mul continuous_const)
#align gronwall_bound_continuous_ε gronwallBound_continuous_ε
/-! ### Inequality and corollaries -/
/-- A Grönwall-like inequality: if `f : ℝ → ℝ` is continuous on `[a, b]` and satisfies
the inequalities `f a ≤ δ` and
`∀ x ∈ [a, b), liminf_{z→x+0} (f z - f x)/(z - x) ≤ K * (f x) + ε`, then `f x`
is bounded by `gronwallBound δ K ε (x - a)` on `[a, b]`.
See also `norm_le_gronwallBound_of_norm_deriv_right_le` for a version bounding `‖f x‖`,
`f : ℝ → E`. -/
theorem le_gronwallBound_of_liminf_deriv_right_le {f f' : ℝ → ℝ} {δ K ε : ℝ} {a b : ℝ}
(hf : ContinuousOn f (Icc a b))
(hf' : ∀ x ∈ Ico a b, ∀ r, f' x < r → ∃ᶠ z in 𝓝[>] x, (z - x)⁻¹ * (f z - f x) < r)
(ha : f a ≤ δ) (bound : ∀ x ∈ Ico a b, f' x ≤ K * f x + ε) :
∀ x ∈ Icc a b, f x ≤ gronwallBound δ K ε (x - a) := by
have H : ∀ x ∈ Icc a b, ∀ ε' ∈ Ioi ε, f x ≤ gronwallBound δ K ε' (x - a) := by
intro x hx ε' hε'
apply image_le_of_liminf_slope_right_lt_deriv_boundary hf hf'
· rwa [sub_self, gronwallBound_x0]
· exact fun x => hasDerivAt_gronwallBound_shift δ K ε' x a
· intro x hx hfB
rw [← hfB]
apply lt_of_le_of_lt (bound x hx)
exact add_lt_add_left (mem_Ioi.1 hε') _
· exact hx
intro x hx
change f x ≤ (fun ε' => gronwallBound δ K ε' (x - a)) ε
convert continuousWithinAt_const.closure_le _ _ (H x hx)
· simp only [closure_Ioi, left_mem_Ici]
exact (gronwallBound_continuous_ε δ K (x - a)).continuousWithinAt
#align le_gronwall_bound_of_liminf_deriv_right_le le_gronwallBound_of_liminf_deriv_right_le
/-- A Grönwall-like inequality: if `f : ℝ → E` is continuous on `[a, b]`, has right derivative
`f' x` at every point `x ∈ [a, b)`, and satisfies the inequalities `‖f a‖ ≤ δ`,
`∀ x ∈ [a, b), ‖f' x‖ ≤ K * ‖f x‖ + ε`, then `‖f x‖` is bounded by `gronwallBound δ K ε (x - a)`
on `[a, b]`. -/
theorem norm_le_gronwallBound_of_norm_deriv_right_le {f f' : ℝ → E} {δ K ε : ℝ} {a b : ℝ}
(hf : ContinuousOn f (Icc a b)) (hf' : ∀ x ∈ Ico a b, HasDerivWithinAt f (f' x) (Ici x) x)
(ha : ‖f a‖ ≤ δ) (bound : ∀ x ∈ Ico a b, ‖f' x‖ ≤ K * ‖f x‖ + ε) :
∀ x ∈ Icc a b, ‖f x‖ ≤ gronwallBound δ K ε (x - a) :=
le_gronwallBound_of_liminf_deriv_right_le (continuous_norm.comp_continuousOn hf)
(fun x hx _r hr => (hf' x hx).liminf_right_slope_norm_le hr) ha bound
#align norm_le_gronwall_bound_of_norm_deriv_right_le norm_le_gronwallBound_of_norm_deriv_right_le
variable {v : ℝ → E → E} {s : ℝ → Set E} {K : ℝ≥0} {f g f' g' : ℝ → E} {a b t₀ : ℝ} {εf εg δ : ℝ}
(hv : ∀ t, LipschitzOnWith K (v t) (s t))
/-- If `f` and `g` are two approximate solutions of the same ODE, then the distance between them
can't grow faster than exponentially. This is a simple corollary of Grönwall's inequality, and some
people call this Grönwall's inequality too.
This version assumes all inequalities to be true in some time-dependent set `s t`,
and assumes that the solutions never leave this set. -/
theorem dist_le_of_approx_trajectories_ODE_of_mem
(hf : ContinuousOn f (Icc a b))
(hf' : ∀ t ∈ Ico a b, HasDerivWithinAt f (f' t) (Ici t) t)
(f_bound : ∀ t ∈ Ico a b, dist (f' t) (v t (f t)) ≤ εf)
(hfs : ∀ t ∈ Ico a b, f t ∈ s t)
(hg : ContinuousOn g (Icc a b))
(hg' : ∀ t ∈ Ico a b, HasDerivWithinAt g (g' t) (Ici t) t)
(g_bound : ∀ t ∈ Ico a b, dist (g' t) (v t (g t)) ≤ εg)
(hgs : ∀ t ∈ Ico a b, g t ∈ s t)
(ha : dist (f a) (g a) ≤ δ) :
∀ t ∈ Icc a b, dist (f t) (g t) ≤ gronwallBound δ K (εf + εg) (t - a) := by
simp only [dist_eq_norm] at ha ⊢
have h_deriv : ∀ t ∈ Ico a b, HasDerivWithinAt (fun t => f t - g t) (f' t - g' t) (Ici t) t :=
fun t ht => (hf' t ht).sub (hg' t ht)
apply norm_le_gronwallBound_of_norm_deriv_right_le (hf.sub hg) h_deriv ha
intro t ht
have := dist_triangle4_right (f' t) (g' t) (v t (f t)) (v t (g t))
have hv := (hv t).dist_le_mul _ (hfs t ht) _ (hgs t ht)
rw [← dist_eq_norm, ← dist_eq_norm]
refine this.trans ((add_le_add (add_le_add (f_bound t ht) (g_bound t ht)) hv).trans ?_)
rw [add_comm]
set_option linter.uppercaseLean3 false in
#align dist_le_of_approx_trajectories_ODE_of_mem_set dist_le_of_approx_trajectories_ODE_of_mem
/-- If `f` and `g` are two approximate solutions of the same ODE, then the distance between them
can't grow faster than exponentially. This is a simple corollary of Grönwall's inequality, and some
people call this Grönwall's inequality too.
This version assumes all inequalities to be true in the whole space. -/
theorem dist_le_of_approx_trajectories_ODE
(hv : ∀ t, LipschitzWith K (v t))
(hf : ContinuousOn f (Icc a b))
(hf' : ∀ t ∈ Ico a b, HasDerivWithinAt f (f' t) (Ici t) t)
(f_bound : ∀ t ∈ Ico a b, dist (f' t) (v t (f t)) ≤ εf)
(hg : ContinuousOn g (Icc a b))
(hg' : ∀ t ∈ Ico a b, HasDerivWithinAt g (g' t) (Ici t) t)
(g_bound : ∀ t ∈ Ico a b, dist (g' t) (v t (g t)) ≤ εg)
(ha : dist (f a) (g a) ≤ δ) :
∀ t ∈ Icc a b, dist (f t) (g t) ≤ gronwallBound δ K (εf + εg) (t - a) :=
have hfs : ∀ t ∈ Ico a b, f t ∈ @univ E := fun _ _ => trivial
dist_le_of_approx_trajectories_ODE_of_mem (fun t => (hv t).lipschitzOnWith _) hf hf'
f_bound hfs hg hg' g_bound (fun _ _ => trivial) ha
set_option linter.uppercaseLean3 false in
#align dist_le_of_approx_trajectories_ODE dist_le_of_approx_trajectories_ODE
/-- If `f` and `g` are two exact solutions of the same ODE, then the distance between them
can't grow faster than exponentially. This is a simple corollary of Grönwall's inequality, and some
people call this Grönwall's inequality too.
This version assumes all inequalities to be true in some time-dependent set `s t`,
and assumes that the solutions never leave this set. -/
theorem dist_le_of_trajectories_ODE_of_mem
(hf : ContinuousOn f (Icc a b))
(hf' : ∀ t ∈ Ico a b, HasDerivWithinAt f (v t (f t)) (Ici t) t)
(hfs : ∀ t ∈ Ico a b, f t ∈ s t)
(hg : ContinuousOn g (Icc a b)) (hg' : ∀ t ∈ Ico a b, HasDerivWithinAt g (v t (g t)) (Ici t) t)
(hgs : ∀ t ∈ Ico a b, g t ∈ s t) (ha : dist (f a) (g a) ≤ δ) :
∀ t ∈ Icc a b, dist (f t) (g t) ≤ δ * exp (K * (t - a)) := by
have f_bound : ∀ t ∈ Ico a b, dist (v t (f t)) (v t (f t)) ≤ 0 := by intros; rw [dist_self]
have g_bound : ∀ t ∈ Ico a b, dist (v t (g t)) (v t (g t)) ≤ 0 := by intros; rw [dist_self]
intro t ht
have :=
dist_le_of_approx_trajectories_ODE_of_mem hv hf hf' f_bound hfs hg hg' g_bound hgs ha t ht
rwa [zero_add, gronwallBound_ε0] at this
set_option linter.uppercaseLean3 false in
#align dist_le_of_trajectories_ODE_of_mem_set dist_le_of_trajectories_ODE_of_mem
/-- If `f` and `g` are two exact solutions of the same ODE, then the distance between them
can't grow faster than exponentially. This is a simple corollary of Grönwall's inequality, and some
people call this Grönwall's inequality too.
This version assumes all inequalities to be true in the whole space. -/
theorem dist_le_of_trajectories_ODE
(hv : ∀ t, LipschitzWith K (v t))
(hf : ContinuousOn f (Icc a b))
(hf' : ∀ t ∈ Ico a b, HasDerivWithinAt f (v t (f t)) (Ici t) t)
(hg : ContinuousOn g (Icc a b))
(hg' : ∀ t ∈ Ico a b, HasDerivWithinAt g (v t (g t)) (Ici t) t)
(ha : dist (f a) (g a) ≤ δ) :
∀ t ∈ Icc a b, dist (f t) (g t) ≤ δ * exp (K * (t - a)) :=
have hfs : ∀ t ∈ Ico a b, f t ∈ @univ E := fun _ _ => trivial
dist_le_of_trajectories_ODE_of_mem (fun t => (hv t).lipschitzOnWith _) hf hf' hfs hg
hg' (fun _ _ => trivial) ha
set_option linter.uppercaseLean3 false in
#align dist_le_of_trajectories_ODE dist_le_of_trajectories_ODE
/-- There exists only one solution of an ODE \(\dot x=v(t, x)\) in a set `s ⊆ ℝ × E` with
a given initial value provided that the RHS is Lipschitz continuous in `x` within `s`,
and we consider only solutions included in `s`.
This version shows uniqueness in a closed interval `Icc a b`, where `a` is the initial time. -/
theorem ODE_solution_unique_of_mem_Icc_right
(hf : ContinuousOn f (Icc a b))
(hf' : ∀ t ∈ Ico a b, HasDerivWithinAt f (v t (f t)) (Ici t) t)
(hfs : ∀ t ∈ Ico a b, f t ∈ s t)
(hg : ContinuousOn g (Icc a b))
(hg' : ∀ t ∈ Ico a b, HasDerivWithinAt g (v t (g t)) (Ici t) t)
(hgs : ∀ t ∈ Ico a b, g t ∈ s t)
(ha : f a = g a) :
EqOn f g (Icc a b) := fun t ht ↦ by
have := dist_le_of_trajectories_ODE_of_mem hv hf hf' hfs hg hg' hgs (dist_le_zero.2 ha) t ht
rwa [zero_mul, dist_le_zero] at this
set_option linter.uppercaseLean3 false in
#align ODE_solution_unique_of_mem_set ODE_solution_unique_of_mem_Icc_right
/-- A time-reversed version of `ODE_solution_unique_of_mem_Icc_right`. Uniqueness is shown in a
closed interval `Icc a b`, where `b` is the "initial" time. -/
| Mathlib/Analysis/ODE/Gronwall.lean | 263 | 295 | theorem ODE_solution_unique_of_mem_Icc_left
(hf : ContinuousOn f (Icc a b))
(hf' : ∀ t ∈ Ioc a b, HasDerivWithinAt f (v t (f t)) (Iic t) t)
(hfs : ∀ t ∈ Ioc a b, f t ∈ s t)
(hg : ContinuousOn g (Icc a b))
(hg' : ∀ t ∈ Ioc a b, HasDerivWithinAt g (v t (g t)) (Iic t) t)
(hgs : ∀ t ∈ Ioc a b, g t ∈ s t)
(hb : f b = g b) :
EqOn f g (Icc a b) := by |
have hv' t : LipschitzOnWith K (Neg.neg ∘ (v (-t))) (s (-t)) := by
rw [← one_mul K]
exact LipschitzWith.id.neg.comp_lipschitzOnWith (hv _)
have hmt1 : MapsTo Neg.neg (Icc (-b) (-a)) (Icc a b) :=
fun _ ht ↦ ⟨le_neg.mp ht.2, neg_le.mp ht.1⟩
have hmt2 : MapsTo Neg.neg (Ico (-b) (-a)) (Ioc a b) :=
fun _ ht ↦ ⟨lt_neg.mp ht.2, neg_le.mp ht.1⟩
have hmt3 (t : ℝ) : MapsTo Neg.neg (Ici t) (Iic (-t)) :=
fun _ ht' ↦ mem_Iic.mpr <| neg_le_neg ht'
suffices EqOn (f ∘ Neg.neg) (g ∘ Neg.neg) (Icc (-b) (-a)) by
rw [eqOn_comp_right_iff] at this
convert this
simp
apply ODE_solution_unique_of_mem_Icc_right hv'
(hf.comp continuousOn_neg hmt1) _ (fun _ ht ↦ hfs _ (hmt2 ht))
(hg.comp continuousOn_neg hmt1) _ (fun _ ht ↦ hgs _ (hmt2 ht)) (by simp [hb])
· intros t ht
convert HasFDerivWithinAt.comp_hasDerivWithinAt t (hf' (-t) (hmt2 ht))
(hasDerivAt_neg t).hasDerivWithinAt (hmt3 t)
simp
· intros t ht
convert HasFDerivWithinAt.comp_hasDerivWithinAt t (hg' (-t) (hmt2 ht))
(hasDerivAt_neg t).hasDerivWithinAt (hmt3 t)
simp
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Sébastien Gouëzel, Yury Kudryashov
-/
import Mathlib.Dynamics.Ergodic.MeasurePreserving
import Mathlib.LinearAlgebra.Determinant
import Mathlib.LinearAlgebra.Matrix.Diagonal
import Mathlib.LinearAlgebra.Matrix.Transvection
import Mathlib.MeasureTheory.Group.LIntegral
import Mathlib.MeasureTheory.Integral.Marginal
import Mathlib.MeasureTheory.Measure.Stieltjes
import Mathlib.MeasureTheory.Measure.Haar.OfBasis
#align_import measure_theory.measure.lebesgue.basic from "leanprover-community/mathlib"@"fd5edc43dc4f10b85abfe544b88f82cf13c5f844"
/-!
# Lebesgue measure on the real line and on `ℝⁿ`
We show that the Lebesgue measure on the real line (constructed as a particular case of additive
Haar measure on inner product spaces) coincides with the Stieltjes measure associated
to the function `x ↦ x`. We deduce properties of this measure on `ℝ`, and then of the product
Lebesgue measure on `ℝⁿ`. In particular, we prove that they are translation invariant.
We show that, on `ℝⁿ`, a linear map acts on Lebesgue measure by rescaling it through the absolute
value of its determinant, in `Real.map_linearMap_volume_pi_eq_smul_volume_pi`.
More properties of the Lebesgue measure are deduced from this in
`Mathlib/MeasureTheory/Measure/Lebesgue/EqHaar.lean`, where they are proved more generally for any
additive Haar measure on a finite-dimensional real vector space.
-/
assert_not_exists MeasureTheory.integral
noncomputable section
open scoped Classical
open Set Filter MeasureTheory MeasureTheory.Measure TopologicalSpace
open ENNReal (ofReal)
open scoped ENNReal NNReal Topology
/-!
### Definition of the Lebesgue measure and lengths of intervals
-/
namespace Real
variable {ι : Type*} [Fintype ι]
/-- The volume on the real line (as a particular case of the volume on a finite-dimensional
inner product space) coincides with the Stieltjes measure coming from the identity function. -/
theorem volume_eq_stieltjes_id : (volume : Measure ℝ) = StieltjesFunction.id.measure := by
haveI : IsAddLeftInvariant StieltjesFunction.id.measure :=
⟨fun a =>
Eq.symm <|
Real.measure_ext_Ioo_rat fun p q => by
simp only [Measure.map_apply (measurable_const_add a) measurableSet_Ioo,
sub_sub_sub_cancel_right, StieltjesFunction.measure_Ioo, StieltjesFunction.id_leftLim,
StieltjesFunction.id_apply, id, preimage_const_add_Ioo]⟩
have A : StieltjesFunction.id.measure (stdOrthonormalBasis ℝ ℝ).toBasis.parallelepiped = 1 := by
change StieltjesFunction.id.measure (parallelepiped (stdOrthonormalBasis ℝ ℝ)) = 1
rcases parallelepiped_orthonormalBasis_one_dim (stdOrthonormalBasis ℝ ℝ) with (H | H) <;>
simp only [H, StieltjesFunction.measure_Icc, StieltjesFunction.id_apply, id, tsub_zero,
StieltjesFunction.id_leftLim, sub_neg_eq_add, zero_add, ENNReal.ofReal_one]
conv_rhs =>
rw [addHaarMeasure_unique StieltjesFunction.id.measure
(stdOrthonormalBasis ℝ ℝ).toBasis.parallelepiped, A]
simp only [volume, Basis.addHaar, one_smul]
#align real.volume_eq_stieltjes_id Real.volume_eq_stieltjes_id
theorem volume_val (s) : volume s = StieltjesFunction.id.measure s := by
simp [volume_eq_stieltjes_id]
#align real.volume_val Real.volume_val
@[simp]
theorem volume_Ico {a b : ℝ} : volume (Ico a b) = ofReal (b - a) := by simp [volume_val]
#align real.volume_Ico Real.volume_Ico
@[simp]
theorem volume_Icc {a b : ℝ} : volume (Icc a b) = ofReal (b - a) := by simp [volume_val]
#align real.volume_Icc Real.volume_Icc
@[simp]
theorem volume_Ioo {a b : ℝ} : volume (Ioo a b) = ofReal (b - a) := by simp [volume_val]
#align real.volume_Ioo Real.volume_Ioo
@[simp]
| Mathlib/MeasureTheory/Measure/Lebesgue/Basic.lean | 92 | 92 | theorem volume_Ioc {a b : ℝ} : volume (Ioc a b) = ofReal (b - a) := by | simp [volume_val]
|
/-
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.MeasureTheory.OuterMeasure.Operations
import Mathlib.Analysis.SpecificLimits.Basic
/-!
# Outer measures from functions
Given an arbitrary function `m : Set α → ℝ≥0∞` that sends `∅` to `0` we can define an outer
measure on `α` that on `s` is defined to be the infimum of `∑ᵢ, m (sᵢ)` for all collections of sets
`sᵢ` that cover `s`. This is the unique maximal outer measure that is at most the given function.
Given an outer measure `m`, the Carathéodory-measurable sets are the sets `s` such that
for all sets `t` we have `m t = m (t ∩ s) + m (t \ s)`. This forms a measurable space.
## Main definitions and statements
* `OuterMeasure.boundedBy` is the greatest outer measure that is at most the given function.
If you know that the given function sends `∅` to `0`, then `OuterMeasure.ofFunction` is a
special case.
* `sInf_eq_boundedBy_sInfGen` is a characterization of the infimum of outer measures.
## References
* <https://en.wikipedia.org/wiki/Outer_measure>
* <https://en.wikipedia.org/wiki/Carath%C3%A9odory%27s_criterion>
## Tags
outer measure, Carathéodory-measurable, Carathéodory's criterion
-/
#align_import measure_theory.measure.outer_measure from "leanprover-community/mathlib"@"343e80208d29d2d15f8050b929aa50fe4ce71b55"
noncomputable section
open Set Function Filter
open scoped Classical NNReal Topology ENNReal
namespace MeasureTheory
namespace OuterMeasure
section OfFunction
-- Porting note: "set_option eqn_compiler.zeta true" removed
variable {α : Type*} (m : Set α → ℝ≥0∞) (m_empty : m ∅ = 0)
/-- Given any function `m` assigning measures to sets satisying `m ∅ = 0`, there is
a unique maximal outer measure `μ` satisfying `μ s ≤ m s` for all `s : Set α`. -/
protected def ofFunction : OuterMeasure α :=
let μ s := ⨅ (f : ℕ → Set α) (_ : s ⊆ ⋃ i, f i), ∑' i, m (f i)
{ measureOf := μ
empty :=
le_antisymm
((iInf_le_of_le fun _ => ∅) <| iInf_le_of_le (empty_subset _) <| by simp [m_empty])
(zero_le _)
mono := fun {s₁ s₂} hs => iInf_mono fun f => iInf_mono' fun hb => ⟨hs.trans hb, le_rfl⟩
iUnion_nat := fun s _ =>
ENNReal.le_of_forall_pos_le_add <| by
intro ε hε (hb : (∑' i, μ (s i)) < ∞)
rcases ENNReal.exists_pos_sum_of_countable (ENNReal.coe_pos.2 hε).ne' ℕ with ⟨ε', hε', hl⟩
refine le_trans ?_ (add_le_add_left (le_of_lt hl) _)
rw [← ENNReal.tsum_add]
choose f hf using
show ∀ i, ∃ f : ℕ → Set α, (s i ⊆ ⋃ i, f i) ∧ (∑' i, m (f i)) < μ (s i) + ε' i by
intro i
have : μ (s i) < μ (s i) + ε' i :=
ENNReal.lt_add_right (ne_top_of_le_ne_top hb.ne <| ENNReal.le_tsum _)
(by simpa using (hε' i).ne')
rcases iInf_lt_iff.mp this with ⟨t, ht⟩
exists t
contrapose! ht
exact le_iInf ht
refine le_trans ?_ (ENNReal.tsum_le_tsum fun i => le_of_lt (hf i).2)
rw [← ENNReal.tsum_prod, ← Nat.pairEquiv.symm.tsum_eq]
refine iInf_le_of_le _ (iInf_le _ ?_)
apply iUnion_subset
intro i
apply Subset.trans (hf i).1
apply iUnion_subset
simp only [Nat.pairEquiv_symm_apply]
rw [iUnion_unpair]
intro j
apply subset_iUnion₂ i }
#align measure_theory.outer_measure.of_function MeasureTheory.OuterMeasure.ofFunction
theorem ofFunction_apply (s : Set α) :
OuterMeasure.ofFunction m m_empty s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, m (t n) :=
rfl
#align measure_theory.outer_measure.of_function_apply MeasureTheory.OuterMeasure.ofFunction_apply
variable {m m_empty}
theorem ofFunction_le (s : Set α) : OuterMeasure.ofFunction m m_empty s ≤ m s :=
let f : ℕ → Set α := fun i => Nat.casesOn i s fun _ => ∅
iInf_le_of_le f <|
iInf_le_of_le (subset_iUnion f 0) <|
le_of_eq <| tsum_eq_single 0 <| by
rintro (_ | i)
· simp
· simp [m_empty]
#align measure_theory.outer_measure.of_function_le MeasureTheory.OuterMeasure.ofFunction_le
theorem ofFunction_eq (s : Set α) (m_mono : ∀ ⦃t : Set α⦄, s ⊆ t → m s ≤ m t)
(m_subadd : ∀ s : ℕ → Set α, m (⋃ i, s i) ≤ ∑' i, m (s i)) :
OuterMeasure.ofFunction m m_empty s = m s :=
le_antisymm (ofFunction_le s) <|
le_iInf fun f => le_iInf fun hf => le_trans (m_mono hf) (m_subadd f)
#align measure_theory.outer_measure.of_function_eq MeasureTheory.OuterMeasure.ofFunction_eq
theorem le_ofFunction {μ : OuterMeasure α} :
μ ≤ OuterMeasure.ofFunction m m_empty ↔ ∀ s, μ s ≤ m s :=
⟨fun H s => le_trans (H s) (ofFunction_le s), fun H _ =>
le_iInf fun f =>
le_iInf fun hs =>
le_trans (μ.mono hs) <| le_trans (measure_iUnion_le f) <| ENNReal.tsum_le_tsum fun _ => H _⟩
#align measure_theory.outer_measure.le_of_function MeasureTheory.OuterMeasure.le_ofFunction
theorem isGreatest_ofFunction :
IsGreatest { μ : OuterMeasure α | ∀ s, μ s ≤ m s } (OuterMeasure.ofFunction m m_empty) :=
⟨fun _ => ofFunction_le _, fun _ => le_ofFunction.2⟩
#align measure_theory.outer_measure.is_greatest_of_function MeasureTheory.OuterMeasure.isGreatest_ofFunction
theorem ofFunction_eq_sSup : OuterMeasure.ofFunction m m_empty = sSup { μ | ∀ s, μ s ≤ m s } :=
(@isGreatest_ofFunction α m m_empty).isLUB.sSup_eq.symm
#align measure_theory.outer_measure.of_function_eq_Sup MeasureTheory.OuterMeasure.ofFunction_eq_sSup
/-- If `m u = ∞` for any set `u` that has nonempty intersection both with `s` and `t`, then
`μ (s ∪ t) = μ s + μ t`, where `μ = MeasureTheory.OuterMeasure.ofFunction m m_empty`.
E.g., if `α` is an (e)metric space and `m u = ∞` on any set of diameter `≥ r`, then this lemma
implies that `μ (s ∪ t) = μ s + μ t` on any two sets such that `r ≤ edist x y` for all `x ∈ s`
and `y ∈ t`. -/
theorem ofFunction_union_of_top_of_nonempty_inter {s t : Set α}
(h : ∀ u, (s ∩ u).Nonempty → (t ∩ u).Nonempty → m u = ∞) :
OuterMeasure.ofFunction m m_empty (s ∪ t) =
OuterMeasure.ofFunction m m_empty s + OuterMeasure.ofFunction m m_empty t := by
refine le_antisymm (measure_union_le _ _) (le_iInf₂ fun f hf ↦ ?_)
set μ := OuterMeasure.ofFunction m m_empty
rcases Classical.em (∃ i, (s ∩ f i).Nonempty ∧ (t ∩ f i).Nonempty) with (⟨i, hs, ht⟩ | he)
· calc
μ s + μ t ≤ ∞ := le_top
_ = m (f i) := (h (f i) hs ht).symm
_ ≤ ∑' i, m (f i) := ENNReal.le_tsum i
set I := fun s => { i : ℕ | (s ∩ f i).Nonempty }
have hd : Disjoint (I s) (I t) := disjoint_iff_inf_le.mpr fun i hi => he ⟨i, hi⟩
have hI : ∀ u ⊆ s ∪ t, μ u ≤ ∑' i : I u, μ (f i) := fun u hu =>
calc
μ u ≤ μ (⋃ i : I u, f i) :=
μ.mono fun x hx =>
let ⟨i, hi⟩ := mem_iUnion.1 (hf (hu hx))
mem_iUnion.2 ⟨⟨i, ⟨x, hx, hi⟩⟩, hi⟩
_ ≤ ∑' i : I u, μ (f i) := measure_iUnion_le _
calc
μ s + μ t ≤ (∑' i : I s, μ (f i)) + ∑' i : I t, μ (f i) :=
add_le_add (hI _ subset_union_left) (hI _ subset_union_right)
_ = ∑' i : ↑(I s ∪ I t), μ (f i) :=
(tsum_union_disjoint (f := fun i => μ (f i)) hd ENNReal.summable ENNReal.summable).symm
_ ≤ ∑' i, μ (f i) :=
(tsum_le_tsum_of_inj (↑) Subtype.coe_injective (fun _ _ => zero_le _) (fun _ => le_rfl)
ENNReal.summable ENNReal.summable)
_ ≤ ∑' i, m (f i) := ENNReal.tsum_le_tsum fun i => ofFunction_le _
#align measure_theory.outer_measure.of_function_union_of_top_of_nonempty_inter MeasureTheory.OuterMeasure.ofFunction_union_of_top_of_nonempty_inter
theorem comap_ofFunction {β} (f : β → α) (h : Monotone m ∨ Surjective f) :
comap f (OuterMeasure.ofFunction m m_empty) =
OuterMeasure.ofFunction (fun s => m (f '' s)) (by simp; simp [m_empty]) := by
refine le_antisymm (le_ofFunction.2 fun s => ?_) fun s => ?_
· rw [comap_apply]
apply ofFunction_le
· rw [comap_apply, ofFunction_apply, ofFunction_apply]
refine iInf_mono' fun t => ⟨fun k => f ⁻¹' t k, ?_⟩
refine iInf_mono' fun ht => ?_
rw [Set.image_subset_iff, preimage_iUnion] at ht
refine ⟨ht, ENNReal.tsum_le_tsum fun n => ?_⟩
cases' h with hl hr
exacts [hl (image_preimage_subset _ _), (congr_arg m (hr.image_preimage (t n))).le]
#align measure_theory.outer_measure.comap_of_function MeasureTheory.OuterMeasure.comap_ofFunction
theorem map_ofFunction_le {β} (f : α → β) :
map f (OuterMeasure.ofFunction m m_empty) ≤
OuterMeasure.ofFunction (fun s => m (f ⁻¹' s)) m_empty :=
le_ofFunction.2 fun s => by
rw [map_apply]
apply ofFunction_le
#align measure_theory.outer_measure.map_of_function_le MeasureTheory.OuterMeasure.map_ofFunction_le
theorem map_ofFunction {β} {f : α → β} (hf : Injective f) :
map f (OuterMeasure.ofFunction m m_empty) =
OuterMeasure.ofFunction (fun s => m (f ⁻¹' s)) m_empty := by
refine (map_ofFunction_le _).antisymm fun s => ?_
simp only [ofFunction_apply, map_apply, le_iInf_iff]
intro t ht
refine iInf_le_of_le (fun n => (range f)ᶜ ∪ f '' t n) (iInf_le_of_le ?_ ?_)
· rw [← union_iUnion, ← inter_subset, ← image_preimage_eq_inter_range, ← image_iUnion]
exact image_subset _ ht
· refine ENNReal.tsum_le_tsum fun n => le_of_eq ?_
simp [hf.preimage_image]
#align measure_theory.outer_measure.map_of_function MeasureTheory.OuterMeasure.map_ofFunction
-- TODO (kmill): change `m (t ∩ s)` to `m (s ∩ t)`
theorem restrict_ofFunction (s : Set α) (hm : Monotone m) :
restrict s (OuterMeasure.ofFunction m m_empty) =
OuterMeasure.ofFunction (fun t => m (t ∩ s)) (by simp; simp [m_empty]) := by
rw [restrict]
simp only [inter_comm _ s, LinearMap.comp_apply]
rw [comap_ofFunction _ (Or.inl hm)]
simp only [map_ofFunction Subtype.coe_injective, Subtype.image_preimage_coe]
#align measure_theory.outer_measure.restrict_of_function MeasureTheory.OuterMeasure.restrict_ofFunction
theorem smul_ofFunction {c : ℝ≥0∞} (hc : c ≠ ∞) : c • OuterMeasure.ofFunction m m_empty =
OuterMeasure.ofFunction (c • m) (by simp [m_empty]) := by
ext1 s
haveI : Nonempty { t : ℕ → Set α // s ⊆ ⋃ i, t i } := ⟨⟨fun _ => s, subset_iUnion (fun _ => s) 0⟩⟩
simp only [smul_apply, ofFunction_apply, ENNReal.tsum_mul_left, Pi.smul_apply, smul_eq_mul,
iInf_subtype']
rw [ENNReal.iInf_mul_left fun h => (hc h).elim]
#align measure_theory.outer_measure.smul_of_function MeasureTheory.OuterMeasure.smul_ofFunction
end OfFunction
section BoundedBy
variable {α : Type*} (m : Set α → ℝ≥0∞)
/-- Given any function `m` assigning measures to sets, there is a unique maximal outer measure `μ`
satisfying `μ s ≤ m s` for all `s : Set α`. This is the same as `OuterMeasure.ofFunction`,
except that it doesn't require `m ∅ = 0`. -/
def boundedBy : OuterMeasure α :=
OuterMeasure.ofFunction (fun s => ⨆ _ : s.Nonempty, m s) (by simp [Set.not_nonempty_empty])
#align measure_theory.outer_measure.bounded_by MeasureTheory.OuterMeasure.boundedBy
variable {m}
theorem boundedBy_le (s : Set α) : boundedBy m s ≤ m s :=
(ofFunction_le _).trans iSup_const_le
#align measure_theory.outer_measure.bounded_by_le MeasureTheory.OuterMeasure.boundedBy_le
theorem boundedBy_eq_ofFunction (m_empty : m ∅ = 0) (s : Set α) :
boundedBy m s = OuterMeasure.ofFunction m m_empty s := by
have : (fun s : Set α => ⨆ _ : s.Nonempty, m s) = m := by
ext1 t
rcases t.eq_empty_or_nonempty with h | h <;> simp [h, Set.not_nonempty_empty, m_empty]
simp [boundedBy, this]
#align measure_theory.outer_measure.bounded_by_eq_of_function MeasureTheory.OuterMeasure.boundedBy_eq_ofFunction
theorem boundedBy_apply (s : Set α) :
boundedBy m s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t),
∑' n, ⨆ _ : (t n).Nonempty, m (t n) := by
simp [boundedBy, ofFunction_apply]
#align measure_theory.outer_measure.bounded_by_apply MeasureTheory.OuterMeasure.boundedBy_apply
theorem boundedBy_eq (s : Set α) (m_empty : m ∅ = 0) (m_mono : ∀ ⦃t : Set α⦄, s ⊆ t → m s ≤ m t)
(m_subadd : ∀ s : ℕ → Set α, m (⋃ i, s i) ≤ ∑' i, m (s i)) : boundedBy m s = m s := by
rw [boundedBy_eq_ofFunction m_empty, ofFunction_eq s m_mono m_subadd]
#align measure_theory.outer_measure.bounded_by_eq MeasureTheory.OuterMeasure.boundedBy_eq
@[simp]
theorem boundedBy_eq_self (m : OuterMeasure α) : boundedBy m = m :=
ext fun _ => boundedBy_eq _ measure_empty (fun _ ht => measure_mono ht) measure_iUnion_le
#align measure_theory.outer_measure.bounded_by_eq_self MeasureTheory.OuterMeasure.boundedBy_eq_self
theorem le_boundedBy {μ : OuterMeasure α} : μ ≤ boundedBy m ↔ ∀ s, μ s ≤ m s := by
rw [boundedBy , le_ofFunction, forall_congr']; intro s
rcases s.eq_empty_or_nonempty with h | h <;> simp [h, Set.not_nonempty_empty]
#align measure_theory.outer_measure.le_bounded_by MeasureTheory.OuterMeasure.le_boundedBy
theorem le_boundedBy' {μ : OuterMeasure α} :
μ ≤ boundedBy m ↔ ∀ s : Set α, s.Nonempty → μ s ≤ m s := by
rw [le_boundedBy, forall_congr']
intro s
rcases s.eq_empty_or_nonempty with h | h <;> simp [h]
#align measure_theory.outer_measure.le_bounded_by' MeasureTheory.OuterMeasure.le_boundedBy'
@[simp]
theorem boundedBy_top : boundedBy (⊤ : Set α → ℝ≥0∞) = ⊤ := by
rw [eq_top_iff, le_boundedBy']
intro s hs
rw [top_apply hs]
exact le_rfl
#align measure_theory.outer_measure.bounded_by_top MeasureTheory.OuterMeasure.boundedBy_top
@[simp]
theorem boundedBy_zero : boundedBy (0 : Set α → ℝ≥0∞) = 0 := by
rw [← coe_bot, eq_bot_iff]
apply boundedBy_le
#align measure_theory.outer_measure.bounded_by_zero MeasureTheory.OuterMeasure.boundedBy_zero
theorem smul_boundedBy {c : ℝ≥0∞} (hc : c ≠ ∞) : c • boundedBy m = boundedBy (c • m) := by
simp only [boundedBy , smul_ofFunction hc]
congr 1 with s : 1
rcases s.eq_empty_or_nonempty with (rfl | hs) <;> simp [*]
#align measure_theory.outer_measure.smul_bounded_by MeasureTheory.OuterMeasure.smul_boundedBy
theorem comap_boundedBy {β} (f : β → α)
(h : (Monotone fun s : { s : Set α // s.Nonempty } => m s) ∨ Surjective f) :
comap f (boundedBy m) = boundedBy fun s => m (f '' s) := by
refine (comap_ofFunction _ ?_).trans ?_
· refine h.imp (fun H s t hst => iSup_le fun hs => ?_) id
have ht : t.Nonempty := hs.mono hst
exact (@H ⟨s, hs⟩ ⟨t, ht⟩ hst).trans (le_iSup (fun _ : t.Nonempty => m t) ht)
· dsimp only [boundedBy]
congr with s : 1
rw [image_nonempty]
#align measure_theory.outer_measure.comap_bounded_by MeasureTheory.OuterMeasure.comap_boundedBy
/-- If `m u = ∞` for any set `u` that has nonempty intersection both with `s` and `t`, then
`μ (s ∪ t) = μ s + μ t`, where `μ = MeasureTheory.OuterMeasure.boundedBy m`.
E.g., if `α` is an (e)metric space and `m u = ∞` on any set of diameter `≥ r`, then this lemma
implies that `μ (s ∪ t) = μ s + μ t` on any two sets such that `r ≤ edist x y` for all `x ∈ s`
and `y ∈ t`. -/
theorem boundedBy_union_of_top_of_nonempty_inter {s t : Set α}
(h : ∀ u, (s ∩ u).Nonempty → (t ∩ u).Nonempty → m u = ∞) :
boundedBy m (s ∪ t) = boundedBy m s + boundedBy m t :=
ofFunction_union_of_top_of_nonempty_inter fun u hs ht =>
top_unique <| (h u hs ht).ge.trans <| le_iSup (fun _ => m u) (hs.mono inter_subset_right)
#align measure_theory.outer_measure.bounded_by_union_of_top_of_nonempty_inter MeasureTheory.OuterMeasure.boundedBy_union_of_top_of_nonempty_inter
end BoundedBy
section sInfGen
variable {α : Type*}
/-- Given a set of outer measures, we define a new function that on a set `s` is defined to be the
infimum of `μ(s)` for the outer measures `μ` in the collection. We ensure that this
function is defined to be `0` on `∅`, even if the collection of outer measures is empty.
The outer measure generated by this function is the infimum of the given outer measures. -/
def sInfGen (m : Set (OuterMeasure α)) (s : Set α) : ℝ≥0∞ :=
⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ s
#align measure_theory.outer_measure.Inf_gen MeasureTheory.OuterMeasure.sInfGen
theorem sInfGen_def (m : Set (OuterMeasure α)) (t : Set α) :
sInfGen m t = ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ t :=
rfl
#align measure_theory.outer_measure.Inf_gen_def MeasureTheory.OuterMeasure.sInfGen_def
theorem sInf_eq_boundedBy_sInfGen (m : Set (OuterMeasure α)) :
sInf m = OuterMeasure.boundedBy (sInfGen m) := by
refine le_antisymm ?_ ?_
· refine le_boundedBy.2 fun s => le_iInf₂ fun μ hμ => ?_
apply sInf_le hμ
· refine le_sInf ?_
intro μ hμ t
exact le_trans (boundedBy_le t) (iInf₂_le μ hμ)
#align measure_theory.outer_measure.Inf_eq_bounded_by_Inf_gen MeasureTheory.OuterMeasure.sInf_eq_boundedBy_sInfGen
theorem iSup_sInfGen_nonempty {m : Set (OuterMeasure α)} (h : m.Nonempty) (t : Set α) :
⨆ _ : t.Nonempty, sInfGen m t = ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ t := by
rcases t.eq_empty_or_nonempty with (rfl | ht)
· simp [biInf_const h]
· simp [ht, sInfGen_def]
#align measure_theory.outer_measure.supr_Inf_gen_nonempty MeasureTheory.OuterMeasure.iSup_sInfGen_nonempty
/-- The value of the Infimum of a nonempty set of outer measures on a set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem sInf_apply {m : Set (OuterMeasure α)} {s : Set α} (h : m.Nonempty) :
sInf m s =
⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ (t n) := by
simp_rw [sInf_eq_boundedBy_sInfGen, boundedBy_apply, iSup_sInfGen_nonempty h]
#align measure_theory.outer_measure.Inf_apply MeasureTheory.OuterMeasure.sInf_apply
/-- The value of the Infimum of a set of outer measures on a nonempty set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem sInf_apply' {m : Set (OuterMeasure α)} {s : Set α} (h : s.Nonempty) :
sInf m s =
⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ (μ : OuterMeasure α) (_ : μ ∈ m), μ (t n) :=
m.eq_empty_or_nonempty.elim (fun hm => by simp [hm, h]) sInf_apply
#align measure_theory.outer_measure.Inf_apply' MeasureTheory.OuterMeasure.sInf_apply'
/-- The value of the Infimum of a nonempty family of outer measures on a set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem iInf_apply {ι} [Nonempty ι] (m : ι → OuterMeasure α) (s : Set α) :
(⨅ i, m i) s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ i, m i (t n) := by
rw [iInf, sInf_apply (range_nonempty m)]
simp only [iInf_range]
#align measure_theory.outer_measure.infi_apply MeasureTheory.OuterMeasure.iInf_apply
/-- The value of the Infimum of a family of outer measures on a nonempty set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem iInf_apply' {ι} (m : ι → OuterMeasure α) {s : Set α} (hs : s.Nonempty) :
(⨅ i, m i) s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ i, m i (t n) := by
rw [iInf, sInf_apply' hs]
simp only [iInf_range]
#align measure_theory.outer_measure.infi_apply' MeasureTheory.OuterMeasure.iInf_apply'
/-- The value of the Infimum of a nonempty family of outer measures on a set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem biInf_apply {ι} {I : Set ι} (hI : I.Nonempty) (m : ι → OuterMeasure α) (s : Set α) :
(⨅ i ∈ I, m i) s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ i ∈ I, m i (t n) := by
haveI := hI.to_subtype
simp only [← iInf_subtype'', iInf_apply]
#align measure_theory.outer_measure.binfi_apply MeasureTheory.OuterMeasure.biInf_apply
/-- The value of the Infimum of a nonempty family of outer measures on a set is not simply
the minimum value of a measure on that set: it is the infimum sum of measures of countable set of
sets that covers that set, where a different measure can be used for each set in the cover. -/
theorem biInf_apply' {ι} (I : Set ι) (m : ι → OuterMeasure α) {s : Set α} (hs : s.Nonempty) :
(⨅ i ∈ I, m i) s = ⨅ (t : ℕ → Set α) (_ : s ⊆ iUnion t), ∑' n, ⨅ i ∈ I, m i (t n) := by
simp only [← iInf_subtype'', iInf_apply' _ hs]
#align measure_theory.outer_measure.binfi_apply' MeasureTheory.OuterMeasure.biInf_apply'
theorem map_iInf_le {ι β} (f : α → β) (m : ι → OuterMeasure α) :
map f (⨅ i, m i) ≤ ⨅ i, map f (m i) :=
(map_mono f).map_iInf_le
#align measure_theory.outer_measure.map_infi_le MeasureTheory.OuterMeasure.map_iInf_le
| Mathlib/MeasureTheory/OuterMeasure/OfFunction.lean | 421 | 428 | theorem comap_iInf {ι β} (f : α → β) (m : ι → OuterMeasure β) :
comap f (⨅ i, m i) = ⨅ i, comap f (m i) := by |
refine ext_nonempty fun s hs => ?_
refine ((comap_mono f).map_iInf_le s).antisymm ?_
simp only [comap_apply, iInf_apply' _ hs, iInf_apply' _ (hs.image _), le_iInf_iff,
Set.image_subset_iff, preimage_iUnion]
refine fun t ht => iInf_le_of_le _ (iInf_le_of_le ht <| ENNReal.tsum_le_tsum fun k => ?_)
exact iInf_mono fun i => (m i).mono (image_preimage_subset _ _)
|
/-
Copyright (c) 2021 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies
-/
import Mathlib.Order.Interval.Multiset
#align_import data.nat.interval from "leanprover-community/mathlib"@"1d29de43a5ba4662dd33b5cfeecfc2a27a5a8a29"
/-!
# Finite intervals of naturals
This file proves that `ℕ` is a `LocallyFiniteOrder` and calculates the cardinality of its
intervals as finsets and fintypes.
## TODO
Some lemmas can be generalized using `OrderedGroup`, `CanonicallyOrderedCommMonoid` or `SuccOrder`
and subsequently be moved upstream to `Order.Interval.Finset`.
-/
-- TODO
-- assert_not_exists Ring
open Finset Nat
variable (a b c : ℕ)
namespace Nat
instance instLocallyFiniteOrder : LocallyFiniteOrder ℕ where
finsetIcc a b := ⟨List.range' a (b + 1 - a), List.nodup_range' _ _⟩
finsetIco a b := ⟨List.range' a (b - a), List.nodup_range' _ _⟩
finsetIoc a b := ⟨List.range' (a + 1) (b - a), List.nodup_range' _ _⟩
finsetIoo a b := ⟨List.range' (a + 1) (b - a - 1), List.nodup_range' _ _⟩
finset_mem_Icc a b x := by rw [Finset.mem_mk, Multiset.mem_coe, List.mem_range'_1]; omega
finset_mem_Ico a b x := by rw [Finset.mem_mk, Multiset.mem_coe, List.mem_range'_1]; omega
finset_mem_Ioc a b x := by rw [Finset.mem_mk, Multiset.mem_coe, List.mem_range'_1]; omega
finset_mem_Ioo a b x := by rw [Finset.mem_mk, Multiset.mem_coe, List.mem_range'_1]; omega
theorem Icc_eq_range' : Icc a b = ⟨List.range' a (b + 1 - a), List.nodup_range' _ _⟩ :=
rfl
#align nat.Icc_eq_range' Nat.Icc_eq_range'
theorem Ico_eq_range' : Ico a b = ⟨List.range' a (b - a), List.nodup_range' _ _⟩ :=
rfl
#align nat.Ico_eq_range' Nat.Ico_eq_range'
theorem Ioc_eq_range' : Ioc a b = ⟨List.range' (a + 1) (b - a), List.nodup_range' _ _⟩ :=
rfl
#align nat.Ioc_eq_range' Nat.Ioc_eq_range'
theorem Ioo_eq_range' : Ioo a b = ⟨List.range' (a + 1) (b - a - 1), List.nodup_range' _ _⟩ :=
rfl
#align nat.Ioo_eq_range' Nat.Ioo_eq_range'
theorem uIcc_eq_range' :
uIcc a b = ⟨List.range' (min a b) (max a b + 1 - min a b), List.nodup_range' _ _⟩ := rfl
#align nat.uIcc_eq_range' Nat.uIcc_eq_range'
theorem Iio_eq_range : Iio = range := by
ext b x
rw [mem_Iio, mem_range]
#align nat.Iio_eq_range Nat.Iio_eq_range
@[simp]
theorem Ico_zero_eq_range : Ico 0 = range := by rw [← Nat.bot_eq_zero, ← Iio_eq_Ico, Iio_eq_range]
#align nat.Ico_zero_eq_range Nat.Ico_zero_eq_range
lemma range_eq_Icc_zero_sub_one (n : ℕ) (hn : n ≠ 0): range n = Icc 0 (n - 1) := by
ext b
simp_all only [mem_Icc, zero_le, true_and, mem_range]
exact lt_iff_le_pred (zero_lt_of_ne_zero hn)
theorem _root_.Finset.range_eq_Ico : range = Ico 0 :=
Ico_zero_eq_range.symm
#align finset.range_eq_Ico Finset.range_eq_Ico
@[simp]
theorem card_Icc : (Icc a b).card = b + 1 - a :=
List.length_range' _ _ _
#align nat.card_Icc Nat.card_Icc
@[simp]
theorem card_Ico : (Ico a b).card = b - a :=
List.length_range' _ _ _
#align nat.card_Ico Nat.card_Ico
@[simp]
theorem card_Ioc : (Ioc a b).card = b - a :=
List.length_range' _ _ _
#align nat.card_Ioc Nat.card_Ioc
@[simp]
theorem card_Ioo : (Ioo a b).card = b - a - 1 :=
List.length_range' _ _ _
#align nat.card_Ioo Nat.card_Ioo
@[simp]
theorem card_uIcc : (uIcc a b).card = (b - a : ℤ).natAbs + 1 :=
(card_Icc _ _).trans $ by rw [← Int.natCast_inj, sup_eq_max, inf_eq_min, Int.ofNat_sub] <;> omega
#align nat.card_uIcc Nat.card_uIcc
@[simp]
lemma card_Iic : (Iic b).card = b + 1 := by rw [Iic_eq_Icc, card_Icc, Nat.bot_eq_zero, Nat.sub_zero]
#align nat.card_Iic Nat.card_Iic
@[simp]
theorem card_Iio : (Iio b).card = b := by rw [Iio_eq_Ico, card_Ico, Nat.bot_eq_zero, Nat.sub_zero]
#align nat.card_Iio Nat.card_Iio
-- Porting note (#10618): simp can prove this
-- @[simp]
theorem card_fintypeIcc : Fintype.card (Set.Icc a b) = b + 1 - a := by
rw [Fintype.card_ofFinset, card_Icc]
#align nat.card_fintype_Icc Nat.card_fintypeIcc
-- Porting note (#10618): simp can prove this
-- @[simp]
theorem card_fintypeIco : Fintype.card (Set.Ico a b) = b - a := by
rw [Fintype.card_ofFinset, card_Ico]
#align nat.card_fintype_Ico Nat.card_fintypeIco
-- Porting note (#10618): simp can prove this
-- @[simp]
theorem card_fintypeIoc : Fintype.card (Set.Ioc a b) = b - a := by
rw [Fintype.card_ofFinset, card_Ioc]
#align nat.card_fintype_Ioc Nat.card_fintypeIoc
-- Porting note (#10618): simp can prove this
-- @[simp]
theorem card_fintypeIoo : Fintype.card (Set.Ioo a b) = b - a - 1 := by
rw [Fintype.card_ofFinset, card_Ioo]
#align nat.card_fintype_Ioo Nat.card_fintypeIoo
-- Porting note (#10618): simp can prove this
-- @[simp]
theorem card_fintypeIic : Fintype.card (Set.Iic b) = b + 1 := by
rw [Fintype.card_ofFinset, card_Iic]
#align nat.card_fintype_Iic Nat.card_fintypeIic
-- Porting note (#10618): simp can prove this
-- @[simp]
theorem card_fintypeIio : Fintype.card (Set.Iio b) = b := by rw [Fintype.card_ofFinset, card_Iio]
#align nat.card_fintype_Iio Nat.card_fintypeIio
-- TODO@Yaël: Generalize all the following lemmas to `SuccOrder`
theorem Icc_succ_left : Icc a.succ b = Ioc a b := by
ext x
rw [mem_Icc, mem_Ioc, succ_le_iff]
#align nat.Icc_succ_left Nat.Icc_succ_left
theorem Ico_succ_right : Ico a b.succ = Icc a b := by
ext x
rw [mem_Ico, mem_Icc, Nat.lt_succ_iff]
#align nat.Ico_succ_right Nat.Ico_succ_right
theorem Ico_succ_left : Ico a.succ b = Ioo a b := by
ext x
rw [mem_Ico, mem_Ioo, succ_le_iff]
#align nat.Ico_succ_left Nat.Ico_succ_left
theorem Icc_pred_right {b : ℕ} (h : 0 < b) : Icc a (b - 1) = Ico a b := by
ext x
rw [mem_Icc, mem_Ico, lt_iff_le_pred h]
#align nat.Icc_pred_right Nat.Icc_pred_right
theorem Ico_succ_succ : Ico a.succ b.succ = Ioc a b := by
ext x
rw [mem_Ico, mem_Ioc, succ_le_iff, Nat.lt_succ_iff]
#align nat.Ico_succ_succ Nat.Ico_succ_succ
@[simp]
theorem Ico_succ_singleton : Ico a (a + 1) = {a} := by rw [Ico_succ_right, Icc_self]
#align nat.Ico_succ_singleton Nat.Ico_succ_singleton
@[simp]
theorem Ico_pred_singleton {a : ℕ} (h : 0 < a) : Ico (a - 1) a = {a - 1} := by
rw [← Icc_pred_right _ h, Icc_self]
#align nat.Ico_pred_singleton Nat.Ico_pred_singleton
@[simp]
theorem Ioc_succ_singleton : Ioc b (b + 1) = {b + 1} := by rw [← Nat.Icc_succ_left, Icc_self]
#align nat.Ioc_succ_singleton Nat.Ioc_succ_singleton
variable {a b c}
theorem Ico_succ_right_eq_insert_Ico (h : a ≤ b) : Ico a (b + 1) = insert b (Ico a b) := by
rw [Ico_succ_right, ← Ico_insert_right h]
#align nat.Ico_succ_right_eq_insert_Ico Nat.Ico_succ_right_eq_insert_Ico
theorem Ico_insert_succ_left (h : a < b) : insert a (Ico a.succ b) = Ico a b := by
rw [Ico_succ_left, ← Ioo_insert_left h]
#align nat.Ico_insert_succ_left Nat.Ico_insert_succ_left
theorem image_sub_const_Ico (h : c ≤ a) :
((Ico a b).image fun x => x - c) = Ico (a - c) (b - c) := by
ext x
simp_rw [mem_image, mem_Ico]
refine ⟨?_, fun h ↦ ⟨x + c, by omega⟩⟩
rintro ⟨x, hx, rfl⟩
omega
#align nat.image_sub_const_Ico Nat.image_sub_const_Ico
theorem Ico_image_const_sub_eq_Ico (hac : a ≤ c) :
((Ico a b).image fun x => c - x) = Ico (c + 1 - b) (c + 1 - a) := by
ext x
simp_rw [mem_image, mem_Ico]
refine ⟨?_, fun h ↦ ⟨c - x, by omega⟩⟩
rintro ⟨x, hx, rfl⟩
omega
#align nat.Ico_image_const_sub_eq_Ico Nat.Ico_image_const_sub_eq_Ico
theorem Ico_succ_left_eq_erase_Ico : Ico a.succ b = erase (Ico a b) a := by
ext x
rw [Ico_succ_left, mem_erase, mem_Ico, mem_Ioo, ← and_assoc, ne_comm, @and_comm (a ≠ x),
lt_iff_le_and_ne]
#align nat.Ico_succ_left_eq_erase_Ico Nat.Ico_succ_left_eq_erase_Ico
theorem mod_injOn_Ico (n a : ℕ) : Set.InjOn (· % a) (Finset.Ico n (n + a)) := by
induction' n with n ih
· simp only [zero_add, Nat.zero_eq, Ico_zero_eq_range]
rintro k hk l hl (hkl : k % a = l % a)
simp only [Finset.mem_range, Finset.mem_coe] at hk hl
rwa [mod_eq_of_lt hk, mod_eq_of_lt hl] at hkl
rw [Ico_succ_left_eq_erase_Ico, succ_add, succ_eq_add_one,
Ico_succ_right_eq_insert_Ico (by omega)]
rintro k hk l hl (hkl : k % a = l % a)
have ha : 0 < a := Nat.pos_iff_ne_zero.2 $ by rintro rfl; simp at hk
simp only [Finset.mem_coe, Finset.mem_insert, Finset.mem_erase] at hk hl
rcases hk with ⟨hkn, rfl | hk⟩ <;> rcases hl with ⟨hln, rfl | hl⟩
· rfl
· rw [add_mod_right] at hkl
refine (hln <| ih hl ?_ hkl.symm).elim
simpa using Nat.lt_add_of_pos_right (n := n) ha
· rw [add_mod_right] at hkl
suffices k = n by contradiction
refine ih hk ?_ hkl
simpa using Nat.lt_add_of_pos_right (n := n) ha
· refine ih ?_ ?_ hkl <;> simp only [Finset.mem_coe, hk, hl]
#align nat.mod_inj_on_Ico Nat.mod_injOn_Ico
/-- Note that while this lemma cannot be easily generalized to a type class, it holds for ℤ as
well. See `Int.image_Ico_emod` for the ℤ version. -/
theorem image_Ico_mod (n a : ℕ) : (Ico n (n + a)).image (· % a) = range a := by
obtain rfl | ha := eq_or_ne a 0
· rw [range_zero, add_zero, Ico_self, image_empty]
ext i
simp only [mem_image, exists_prop, mem_range, mem_Ico]
constructor
· rintro ⟨i, _, rfl⟩
exact mod_lt i ha.bot_lt
intro hia
have hn := Nat.mod_add_div n a
obtain hi | hi := lt_or_le i (n % a)
· refine ⟨i + a * (n / a + 1), ⟨?_, ?_⟩, ?_⟩
· rw [add_comm (n / a), Nat.mul_add, mul_one, ← add_assoc]
refine hn.symm.le.trans (Nat.add_le_add_right ?_ _)
simpa only [zero_add] using add_le_add (zero_le i) (Nat.mod_lt n ha.bot_lt).le
· refine lt_of_lt_of_le (Nat.add_lt_add_right hi (a * (n / a + 1))) ?_
rw [Nat.mul_add, mul_one, ← add_assoc, hn]
· rw [Nat.add_mul_mod_self_left, Nat.mod_eq_of_lt hia]
· refine ⟨i + a * (n / a), ⟨?_, ?_⟩, ?_⟩
· omega
· omega
· rw [Nat.add_mul_mod_self_left, Nat.mod_eq_of_lt hia]
#align nat.image_Ico_mod Nat.image_Ico_mod
section Multiset
open Multiset
theorem multiset_Ico_map_mod (n a : ℕ) :
(Multiset.Ico n (n + a)).map (· % a) = Multiset.range a := by
convert congr_arg Finset.val (image_Ico_mod n a)
refine ((nodup_map_iff_inj_on (Finset.Ico _ _).nodup).2 <| ?_).dedup.symm
exact mod_injOn_Ico _ _
#align nat.multiset_Ico_map_mod Nat.multiset_Ico_map_mod
end Multiset
end Nat
namespace Finset
| Mathlib/Order/Interval/Finset/Nat.lean | 286 | 291 | theorem range_image_pred_top_sub (n : ℕ) :
((Finset.range n).image fun j => n - 1 - j) = Finset.range n := by |
cases n
· rw [range_zero, image_empty]
· rw [Finset.range_eq_Ico, Nat.Ico_image_const_sub_eq_Ico (Nat.zero_le _)]
simp_rw [succ_sub_succ, Nat.sub_zero, Nat.sub_self]
|
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Jens Wagemaker, Aaron Anderson
-/
import Mathlib.Algebra.BigOperators.Associated
import Mathlib.Algebra.GCDMonoid.Basic
import Mathlib.Data.Finsupp.Multiset
import Mathlib.Data.Nat.Factors
import Mathlib.RingTheory.Noetherian
import Mathlib.RingTheory.Multiplicity
#align_import ring_theory.unique_factorization_domain from "leanprover-community/mathlib"@"570e9f4877079b3a923135b3027ac3be8695ab8c"
/-!
# Unique factorization
## Main Definitions
* `WfDvdMonoid` holds for `Monoid`s for which a strict divisibility relation is
well-founded.
* `UniqueFactorizationMonoid` holds for `WfDvdMonoid`s where
`Irreducible` is equivalent to `Prime`
## To do
* set up the complete lattice structure on `FactorSet`.
-/
variable {α : Type*}
local infixl:50 " ~ᵤ " => Associated
/-- Well-foundedness of the strict version of |, which is equivalent to the descending chain
condition on divisibility and to the ascending chain condition on
principal ideals in an integral domain.
-/
class WfDvdMonoid (α : Type*) [CommMonoidWithZero α] : Prop where
wellFounded_dvdNotUnit : WellFounded (@DvdNotUnit α _)
#align wf_dvd_monoid WfDvdMonoid
export WfDvdMonoid (wellFounded_dvdNotUnit)
-- see Note [lower instance priority]
instance (priority := 100) IsNoetherianRing.wfDvdMonoid [CommRing α] [IsDomain α]
[IsNoetherianRing α] : WfDvdMonoid α :=
⟨by
convert InvImage.wf (fun a => Ideal.span ({a} : Set α)) (wellFounded_submodule_gt _ _)
ext
exact Ideal.span_singleton_lt_span_singleton.symm⟩
#align is_noetherian_ring.wf_dvd_monoid IsNoetherianRing.wfDvdMonoid
namespace WfDvdMonoid
variable [CommMonoidWithZero α]
open Associates Nat
theorem of_wfDvdMonoid_associates (_ : WfDvdMonoid (Associates α)) : WfDvdMonoid α :=
⟨(mk_surjective.wellFounded_iff mk_dvdNotUnit_mk_iff.symm).2 wellFounded_dvdNotUnit⟩
#align wf_dvd_monoid.of_wf_dvd_monoid_associates WfDvdMonoid.of_wfDvdMonoid_associates
variable [WfDvdMonoid α]
instance wfDvdMonoid_associates : WfDvdMonoid (Associates α) :=
⟨(mk_surjective.wellFounded_iff mk_dvdNotUnit_mk_iff.symm).1 wellFounded_dvdNotUnit⟩
#align wf_dvd_monoid.wf_dvd_monoid_associates WfDvdMonoid.wfDvdMonoid_associates
theorem wellFounded_associates : WellFounded ((· < ·) : Associates α → Associates α → Prop) :=
Subrelation.wf dvdNotUnit_of_lt wellFounded_dvdNotUnit
#align wf_dvd_monoid.well_founded_associates WfDvdMonoid.wellFounded_associates
-- Porting note: elab_as_elim can only be global and cannot be changed on an imported decl
-- attribute [local elab_as_elim] WellFounded.fix
theorem exists_irreducible_factor {a : α} (ha : ¬IsUnit a) (ha0 : a ≠ 0) :
∃ i, Irreducible i ∧ i ∣ a :=
let ⟨b, hs, hr⟩ := wellFounded_dvdNotUnit.has_min { b | b ∣ a ∧ ¬IsUnit b } ⟨a, dvd_rfl, ha⟩
⟨b,
⟨hs.2, fun c d he =>
let h := dvd_trans ⟨d, he⟩ hs.1
or_iff_not_imp_left.2 fun hc =>
of_not_not fun hd => hr c ⟨h, hc⟩ ⟨ne_zero_of_dvd_ne_zero ha0 h, d, hd, he⟩⟩,
hs.1⟩
#align wf_dvd_monoid.exists_irreducible_factor WfDvdMonoid.exists_irreducible_factor
@[elab_as_elim]
theorem induction_on_irreducible {P : α → Prop} (a : α) (h0 : P 0) (hu : ∀ u : α, IsUnit u → P u)
(hi : ∀ a i : α, a ≠ 0 → Irreducible i → P a → P (i * a)) : P a :=
haveI := Classical.dec
wellFounded_dvdNotUnit.fix
(fun a ih =>
if ha0 : a = 0 then ha0.substr h0
else
if hau : IsUnit a then hu a hau
else
let ⟨i, hii, b, hb⟩ := exists_irreducible_factor hau ha0
let hb0 : b ≠ 0 := ne_zero_of_dvd_ne_zero ha0 ⟨i, mul_comm i b ▸ hb⟩
hb.symm ▸ hi b i hb0 hii <| ih b ⟨hb0, i, hii.1, mul_comm i b ▸ hb⟩)
a
#align wf_dvd_monoid.induction_on_irreducible WfDvdMonoid.induction_on_irreducible
theorem exists_factors (a : α) :
a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ Associated f.prod a :=
induction_on_irreducible a (fun h => (h rfl).elim)
(fun u hu _ => ⟨0, fun _ h => False.elim (Multiset.not_mem_zero _ h), hu.unit, one_mul _⟩)
fun a i ha0 hi ih _ =>
let ⟨s, hs⟩ := ih ha0
⟨i ::ₘ s, fun b H => (Multiset.mem_cons.1 H).elim (fun h => h.symm ▸ hi) (hs.1 b), by
rw [s.prod_cons i]
exact hs.2.mul_left i⟩
#align wf_dvd_monoid.exists_factors WfDvdMonoid.exists_factors
theorem not_unit_iff_exists_factors_eq (a : α) (hn0 : a ≠ 0) :
¬IsUnit a ↔ ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod = a ∧ f ≠ ∅ :=
⟨fun hnu => by
obtain ⟨f, hi, u, rfl⟩ := exists_factors a hn0
obtain ⟨b, h⟩ := Multiset.exists_mem_of_ne_zero fun h : f = 0 => hnu <| by simp [h]
classical
refine ⟨(f.erase b).cons (b * u), fun a ha => ?_, ?_, Multiset.cons_ne_zero⟩
· obtain rfl | ha := Multiset.mem_cons.1 ha
exacts [Associated.irreducible ⟨u, rfl⟩ (hi b h), hi a (Multiset.mem_of_mem_erase ha)]
· rw [Multiset.prod_cons, mul_comm b, mul_assoc, Multiset.prod_erase h, mul_comm],
fun ⟨f, hi, he, hne⟩ =>
let ⟨b, h⟩ := Multiset.exists_mem_of_ne_zero hne
not_isUnit_of_not_isUnit_dvd (hi b h).not_unit <| he ▸ Multiset.dvd_prod h⟩
#align wf_dvd_monoid.not_unit_iff_exists_factors_eq WfDvdMonoid.not_unit_iff_exists_factors_eq
theorem isRelPrime_of_no_irreducible_factors {x y : α} (nonzero : ¬(x = 0 ∧ y = 0))
(H : ∀ z : α, Irreducible z → z ∣ x → ¬z ∣ y) : IsRelPrime x y :=
isRelPrime_of_no_nonunits_factors nonzero fun _z znu znz zx zy ↦
have ⟨i, h1, h2⟩ := exists_irreducible_factor znu znz
H i h1 (h2.trans zx) (h2.trans zy)
end WfDvdMonoid
theorem WfDvdMonoid.of_wellFounded_associates [CancelCommMonoidWithZero α]
(h : WellFounded ((· < ·) : Associates α → Associates α → Prop)) : WfDvdMonoid α :=
WfDvdMonoid.of_wfDvdMonoid_associates
⟨by
convert h
ext
exact Associates.dvdNotUnit_iff_lt⟩
#align wf_dvd_monoid.of_well_founded_associates WfDvdMonoid.of_wellFounded_associates
theorem WfDvdMonoid.iff_wellFounded_associates [CancelCommMonoidWithZero α] :
WfDvdMonoid α ↔ WellFounded ((· < ·) : Associates α → Associates α → Prop) :=
⟨by apply WfDvdMonoid.wellFounded_associates, WfDvdMonoid.of_wellFounded_associates⟩
#align wf_dvd_monoid.iff_well_founded_associates WfDvdMonoid.iff_wellFounded_associates
theorem WfDvdMonoid.max_power_factor' [CommMonoidWithZero α] [WfDvdMonoid α] {a₀ x : α}
(h : a₀ ≠ 0) (hx : ¬IsUnit x) : ∃ (n : ℕ) (a : α), ¬x ∣ a ∧ a₀ = x ^ n * a := by
obtain ⟨a, ⟨n, rfl⟩, hm⟩ := wellFounded_dvdNotUnit.has_min
{a | ∃ n, x ^ n * a = a₀} ⟨a₀, 0, by rw [pow_zero, one_mul]⟩
refine ⟨n, a, ?_, rfl⟩; rintro ⟨d, rfl⟩
exact hm d ⟨n + 1, by rw [pow_succ, mul_assoc]⟩
⟨(right_ne_zero_of_mul <| right_ne_zero_of_mul h), x, hx, mul_comm _ _⟩
theorem WfDvdMonoid.max_power_factor [CommMonoidWithZero α] [WfDvdMonoid α] {a₀ x : α}
(h : a₀ ≠ 0) (hx : Irreducible x) : ∃ (n : ℕ) (a : α), ¬x ∣ a ∧ a₀ = x ^ n * a :=
max_power_factor' h hx.not_unit
theorem multiplicity.finite_of_not_isUnit [CancelCommMonoidWithZero α] [WfDvdMonoid α]
{a b : α} (ha : ¬IsUnit a) (hb : b ≠ 0) : multiplicity.Finite a b := by
obtain ⟨n, c, ndvd, rfl⟩ := WfDvdMonoid.max_power_factor' hb ha
exact ⟨n, by rwa [pow_succ, mul_dvd_mul_iff_left (left_ne_zero_of_mul hb)]⟩
section Prio
-- set_option default_priority 100
-- see Note [default priority]
/-- unique factorization monoids.
These are defined as `CancelCommMonoidWithZero`s with well-founded strict divisibility
relations, but this is equivalent to more familiar definitions:
Each element (except zero) is uniquely represented as a multiset of irreducible factors.
Uniqueness is only up to associated elements.
Each element (except zero) is non-uniquely represented as a multiset
of prime factors.
To define a UFD using the definition in terms of multisets
of irreducible factors, use the definition `of_exists_unique_irreducible_factors`
To define a UFD using the definition in terms of multisets
of prime factors, use the definition `of_exists_prime_factors`
-/
class UniqueFactorizationMonoid (α : Type*) [CancelCommMonoidWithZero α] extends WfDvdMonoid α :
Prop where
protected irreducible_iff_prime : ∀ {a : α}, Irreducible a ↔ Prime a
#align unique_factorization_monoid UniqueFactorizationMonoid
/-- Can't be an instance because it would cause a loop `ufm → WfDvdMonoid → ufm → ...`. -/
theorem ufm_of_decomposition_of_wfDvdMonoid [CancelCommMonoidWithZero α] [WfDvdMonoid α]
[DecompositionMonoid α] : UniqueFactorizationMonoid α :=
{ ‹WfDvdMonoid α› with irreducible_iff_prime := irreducible_iff_prime }
#align ufm_of_gcd_of_wf_dvd_monoid ufm_of_decomposition_of_wfDvdMonoid
@[deprecated] alias ufm_of_gcd_of_wfDvdMonoid := ufm_of_decomposition_of_wfDvdMonoid
instance Associates.ufm [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α] :
UniqueFactorizationMonoid (Associates α) :=
{ (WfDvdMonoid.wfDvdMonoid_associates : WfDvdMonoid (Associates α)) with
irreducible_iff_prime := by
rw [← Associates.irreducible_iff_prime_iff]
apply UniqueFactorizationMonoid.irreducible_iff_prime }
#align associates.ufm Associates.ufm
end Prio
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
theorem exists_prime_factors (a : α) :
a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a := by
simp_rw [← UniqueFactorizationMonoid.irreducible_iff_prime]
apply WfDvdMonoid.exists_factors a
#align unique_factorization_monoid.exists_prime_factors UniqueFactorizationMonoid.exists_prime_factors
instance : DecompositionMonoid α where
primal a := by
obtain rfl | ha := eq_or_ne a 0; · exact isPrimal_zero
obtain ⟨f, hf, u, rfl⟩ := exists_prime_factors a ha
exact ((Submonoid.isPrimal α).multiset_prod_mem f (hf · ·|>.isPrimal)).mul u.isUnit.isPrimal
lemma exists_prime_iff :
(∃ (p : α), Prime p) ↔ ∃ (x : α), x ≠ 0 ∧ ¬ IsUnit x := by
refine ⟨fun ⟨p, hp⟩ ↦ ⟨p, hp.ne_zero, hp.not_unit⟩, fun ⟨x, hx₀, hxu⟩ ↦ ?_⟩
obtain ⟨f, hf, -⟩ := WfDvdMonoid.exists_irreducible_factor hxu hx₀
exact ⟨f, UniqueFactorizationMonoid.irreducible_iff_prime.mp hf⟩
@[elab_as_elim]
theorem induction_on_prime {P : α → Prop} (a : α) (h₁ : P 0) (h₂ : ∀ x : α, IsUnit x → P x)
(h₃ : ∀ a p : α, a ≠ 0 → Prime p → P a → P (p * a)) : P a := by
simp_rw [← UniqueFactorizationMonoid.irreducible_iff_prime] at h₃
exact WfDvdMonoid.induction_on_irreducible a h₁ h₂ h₃
#align unique_factorization_monoid.induction_on_prime UniqueFactorizationMonoid.induction_on_prime
end UniqueFactorizationMonoid
theorem prime_factors_unique [CancelCommMonoidWithZero α] :
∀ {f g : Multiset α},
(∀ x ∈ f, Prime x) → (∀ x ∈ g, Prime x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g := by
classical
intro f
induction' f using Multiset.induction_on with p f ih
· intros g _ hg h
exact Multiset.rel_zero_left.2 <|
Multiset.eq_zero_of_forall_not_mem fun x hx =>
have : IsUnit g.prod := by simpa [associated_one_iff_isUnit] using h.symm
(hg x hx).not_unit <|
isUnit_iff_dvd_one.2 <| (Multiset.dvd_prod hx).trans (isUnit_iff_dvd_one.1 this)
· intros g hf hg hfg
let ⟨b, hbg, hb⟩ :=
(exists_associated_mem_of_dvd_prod (hf p (by simp)) fun q hq => hg _ hq) <|
hfg.dvd_iff_dvd_right.1 (show p ∣ (p ::ₘ f).prod by simp)
haveI := Classical.decEq α
rw [← Multiset.cons_erase hbg]
exact
Multiset.Rel.cons hb
(ih (fun q hq => hf _ (by simp [hq]))
(fun {q} (hq : q ∈ g.erase b) => hg q (Multiset.mem_of_mem_erase hq))
(Associated.of_mul_left
(by rwa [← Multiset.prod_cons, ← Multiset.prod_cons, Multiset.cons_erase hbg]) hb
(hf p (by simp)).ne_zero))
#align prime_factors_unique prime_factors_unique
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
theorem factors_unique {f g : Multiset α} (hf : ∀ x ∈ f, Irreducible x)
(hg : ∀ x ∈ g, Irreducible x) (h : f.prod ~ᵤ g.prod) : Multiset.Rel Associated f g :=
prime_factors_unique (fun x hx => UniqueFactorizationMonoid.irreducible_iff_prime.mp (hf x hx))
(fun x hx => UniqueFactorizationMonoid.irreducible_iff_prime.mp (hg x hx)) h
#align unique_factorization_monoid.factors_unique UniqueFactorizationMonoid.factors_unique
end UniqueFactorizationMonoid
/-- If an irreducible has a prime factorization,
then it is an associate of one of its prime factors. -/
theorem prime_factors_irreducible [CancelCommMonoidWithZero α] {a : α} {f : Multiset α}
(ha : Irreducible a) (pfa : (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a) : ∃ p, a ~ᵤ p ∧ f = {p} := by
haveI := Classical.decEq α
refine @Multiset.induction_on _
(fun g => (g.prod ~ᵤ a) → (∀ b ∈ g, Prime b) → ∃ p, a ~ᵤ p ∧ g = {p}) f ?_ ?_ pfa.2 pfa.1
· intro h; exact (ha.not_unit (associated_one_iff_isUnit.1 (Associated.symm h))).elim
· rintro p s _ ⟨u, hu⟩ hs
use p
have hs0 : s = 0 := by
by_contra hs0
obtain ⟨q, hq⟩ := Multiset.exists_mem_of_ne_zero hs0
apply (hs q (by simp [hq])).2.1
refine (ha.isUnit_or_isUnit (?_ : _ = p * ↑u * (s.erase q).prod * _)).resolve_left ?_
· rw [mul_right_comm _ _ q, mul_assoc, ← Multiset.prod_cons, Multiset.cons_erase hq, ← hu,
mul_comm, mul_comm p _, mul_assoc]
simp
apply mt isUnit_of_mul_isUnit_left (mt isUnit_of_mul_isUnit_left _)
apply (hs p (Multiset.mem_cons_self _ _)).2.1
simp only [mul_one, Multiset.prod_cons, Multiset.prod_zero, hs0] at *
exact ⟨Associated.symm ⟨u, hu⟩, rfl⟩
#align prime_factors_irreducible prime_factors_irreducible
section ExistsPrimeFactors
variable [CancelCommMonoidWithZero α]
variable (pf : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a)
theorem WfDvdMonoid.of_exists_prime_factors : WfDvdMonoid α :=
⟨by
classical
refine RelHomClass.wellFounded
(RelHom.mk ?_ ?_ : (DvdNotUnit : α → α → Prop) →r ((· < ·) : ℕ∞ → ℕ∞ → Prop)) wellFounded_lt
· intro a
by_cases h : a = 0
· exact ⊤
exact ↑(Multiset.card (Classical.choose (pf a h)))
rintro a b ⟨ane0, ⟨c, hc, b_eq⟩⟩
rw [dif_neg ane0]
by_cases h : b = 0
· simp [h, lt_top_iff_ne_top]
· rw [dif_neg h]
erw [WithTop.coe_lt_coe]
have cne0 : c ≠ 0 := by
refine mt (fun con => ?_) h
rw [b_eq, con, mul_zero]
calc
Multiset.card (Classical.choose (pf a ane0)) <
_ + Multiset.card (Classical.choose (pf c cne0)) :=
lt_add_of_pos_right _
(Multiset.card_pos.mpr fun con => hc (associated_one_iff_isUnit.mp ?_))
_ = Multiset.card (Classical.choose (pf a ane0) + Classical.choose (pf c cne0)) :=
(Multiset.card_add _ _).symm
_ = Multiset.card (Classical.choose (pf b h)) :=
Multiset.card_eq_card_of_rel
(prime_factors_unique ?_ (Classical.choose_spec (pf _ h)).1 ?_)
· convert (Classical.choose_spec (pf c cne0)).2.symm
rw [con, Multiset.prod_zero]
· intro x hadd
rw [Multiset.mem_add] at hadd
cases' hadd with h h <;> apply (Classical.choose_spec (pf _ _)).1 _ h <;> assumption
· rw [Multiset.prod_add]
trans a * c
· apply Associated.mul_mul <;> apply (Classical.choose_spec (pf _ _)).2 <;> assumption
· rw [← b_eq]
apply (Classical.choose_spec (pf _ _)).2.symm; assumption⟩
#align wf_dvd_monoid.of_exists_prime_factors WfDvdMonoid.of_exists_prime_factors
theorem irreducible_iff_prime_of_exists_prime_factors {p : α} : Irreducible p ↔ Prime p := by
by_cases hp0 : p = 0
· simp [hp0]
refine ⟨fun h => ?_, Prime.irreducible⟩
obtain ⟨f, hf⟩ := pf p hp0
obtain ⟨q, hq, rfl⟩ := prime_factors_irreducible h hf
rw [hq.prime_iff]
exact hf.1 q (Multiset.mem_singleton_self _)
#align irreducible_iff_prime_of_exists_prime_factors irreducible_iff_prime_of_exists_prime_factors
theorem UniqueFactorizationMonoid.of_exists_prime_factors : UniqueFactorizationMonoid α :=
{ WfDvdMonoid.of_exists_prime_factors pf with
irreducible_iff_prime := irreducible_iff_prime_of_exists_prime_factors pf }
#align unique_factorization_monoid.of_exists_prime_factors UniqueFactorizationMonoid.of_exists_prime_factors
end ExistsPrimeFactors
theorem UniqueFactorizationMonoid.iff_exists_prime_factors [CancelCommMonoidWithZero α] :
UniqueFactorizationMonoid α ↔
∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Prime b) ∧ f.prod ~ᵤ a :=
⟨fun h => @UniqueFactorizationMonoid.exists_prime_factors _ _ h,
UniqueFactorizationMonoid.of_exists_prime_factors⟩
#align unique_factorization_monoid.iff_exists_prime_factors UniqueFactorizationMonoid.iff_exists_prime_factors
section
variable {β : Type*} [CancelCommMonoidWithZero α] [CancelCommMonoidWithZero β]
theorem MulEquiv.uniqueFactorizationMonoid (e : α ≃* β) (hα : UniqueFactorizationMonoid α) :
UniqueFactorizationMonoid β := by
rw [UniqueFactorizationMonoid.iff_exists_prime_factors] at hα ⊢
intro a ha
obtain ⟨w, hp, u, h⟩ :=
hα (e.symm a) fun h =>
ha <| by
convert← map_zero e
simp [← h]
exact
⟨w.map e, fun b hb =>
let ⟨c, hc, he⟩ := Multiset.mem_map.1 hb
he ▸ e.prime_iff.1 (hp c hc),
Units.map e.toMonoidHom u,
by
erw [Multiset.prod_hom, ← e.map_mul, h]
simp⟩
#align mul_equiv.unique_factorization_monoid MulEquiv.uniqueFactorizationMonoid
theorem MulEquiv.uniqueFactorizationMonoid_iff (e : α ≃* β) :
UniqueFactorizationMonoid α ↔ UniqueFactorizationMonoid β :=
⟨e.uniqueFactorizationMonoid, e.symm.uniqueFactorizationMonoid⟩
#align mul_equiv.unique_factorization_monoid_iff MulEquiv.uniqueFactorizationMonoid_iff
end
theorem irreducible_iff_prime_of_exists_unique_irreducible_factors [CancelCommMonoidWithZero α]
(eif : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod ~ᵤ a)
(uif :
∀ f g : Multiset α,
(∀ x ∈ f, Irreducible x) →
(∀ x ∈ g, Irreducible x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g)
(p : α) : Irreducible p ↔ Prime p :=
letI := Classical.decEq α
⟨ fun hpi =>
⟨hpi.ne_zero, hpi.1, fun a b ⟨x, hx⟩ =>
if hab0 : a * b = 0 then
(eq_zero_or_eq_zero_of_mul_eq_zero hab0).elim (fun ha0 => by simp [ha0]) fun hb0 => by
simp [hb0]
else by
have hx0 : x ≠ 0 := fun hx0 => by simp_all
have ha0 : a ≠ 0 := left_ne_zero_of_mul hab0
have hb0 : b ≠ 0 := right_ne_zero_of_mul hab0
cases' eif x hx0 with fx hfx
cases' eif a ha0 with fa hfa
cases' eif b hb0 with fb hfb
have h : Multiset.Rel Associated (p ::ₘ fx) (fa + fb) := by
apply uif
· exact fun i hi => (Multiset.mem_cons.1 hi).elim (fun hip => hip.symm ▸ hpi) (hfx.1 _)
· exact fun i hi => (Multiset.mem_add.1 hi).elim (hfa.1 _) (hfb.1 _)
calc
Multiset.prod (p ::ₘ fx) ~ᵤ a * b := by
rw [hx, Multiset.prod_cons]; exact hfx.2.mul_left _
_ ~ᵤ fa.prod * fb.prod := hfa.2.symm.mul_mul hfb.2.symm
_ = _ := by rw [Multiset.prod_add]
exact
let ⟨q, hqf, hq⟩ := Multiset.exists_mem_of_rel_of_mem h (Multiset.mem_cons_self p _)
(Multiset.mem_add.1 hqf).elim
(fun hqa =>
Or.inl <| hq.dvd_iff_dvd_left.2 <| hfa.2.dvd_iff_dvd_right.1 (Multiset.dvd_prod hqa))
fun hqb =>
Or.inr <| hq.dvd_iff_dvd_left.2 <| hfb.2.dvd_iff_dvd_right.1 (Multiset.dvd_prod hqb)⟩,
Prime.irreducible⟩
#align irreducible_iff_prime_of_exists_unique_irreducible_factors irreducible_iff_prime_of_exists_unique_irreducible_factors
theorem UniqueFactorizationMonoid.of_exists_unique_irreducible_factors [CancelCommMonoidWithZero α]
(eif : ∀ a : α, a ≠ 0 → ∃ f : Multiset α, (∀ b ∈ f, Irreducible b) ∧ f.prod ~ᵤ a)
(uif :
∀ f g : Multiset α,
(∀ x ∈ f, Irreducible x) →
(∀ x ∈ g, Irreducible x) → f.prod ~ᵤ g.prod → Multiset.Rel Associated f g) :
UniqueFactorizationMonoid α :=
UniqueFactorizationMonoid.of_exists_prime_factors
(by
convert eif using 7
simp_rw [irreducible_iff_prime_of_exists_unique_irreducible_factors eif uif])
#align unique_factorization_monoid.of_exists_unique_irreducible_factors UniqueFactorizationMonoid.of_exists_unique_irreducible_factors
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α]
variable [UniqueFactorizationMonoid α]
open Classical in
/-- Noncomputably determines the multiset of prime factors. -/
noncomputable def factors (a : α) : Multiset α :=
if h : a = 0 then 0 else Classical.choose (UniqueFactorizationMonoid.exists_prime_factors a h)
#align unique_factorization_monoid.factors UniqueFactorizationMonoid.factors
theorem factors_prod {a : α} (ane0 : a ≠ 0) : Associated (factors a).prod a := by
rw [factors, dif_neg ane0]
exact (Classical.choose_spec (exists_prime_factors a ane0)).2
#align unique_factorization_monoid.factors_prod UniqueFactorizationMonoid.factors_prod
@[simp]
theorem factors_zero : factors (0 : α) = 0 := by simp [factors]
#align unique_factorization_monoid.factors_zero UniqueFactorizationMonoid.factors_zero
theorem ne_zero_of_mem_factors {p a : α} (h : p ∈ factors a) : a ≠ 0 := by
rintro rfl
simp at h
#align unique_factorization_monoid.ne_zero_of_mem_factors UniqueFactorizationMonoid.ne_zero_of_mem_factors
theorem dvd_of_mem_factors {p a : α} (h : p ∈ factors a) : p ∣ a :=
dvd_trans (Multiset.dvd_prod h) (Associated.dvd (factors_prod (ne_zero_of_mem_factors h)))
#align unique_factorization_monoid.dvd_of_mem_factors UniqueFactorizationMonoid.dvd_of_mem_factors
theorem prime_of_factor {a : α} (x : α) (hx : x ∈ factors a) : Prime x := by
have ane0 := ne_zero_of_mem_factors hx
rw [factors, dif_neg ane0] at hx
exact (Classical.choose_spec (UniqueFactorizationMonoid.exists_prime_factors a ane0)).1 x hx
#align unique_factorization_monoid.prime_of_factor UniqueFactorizationMonoid.prime_of_factor
theorem irreducible_of_factor {a : α} : ∀ x : α, x ∈ factors a → Irreducible x := fun x h =>
(prime_of_factor x h).irreducible
#align unique_factorization_monoid.irreducible_of_factor UniqueFactorizationMonoid.irreducible_of_factor
@[simp]
theorem factors_one : factors (1 : α) = 0 := by
nontriviality α using factors
rw [← Multiset.rel_zero_right]
refine factors_unique irreducible_of_factor (fun x hx => (Multiset.not_mem_zero x hx).elim) ?_
rw [Multiset.prod_zero]
exact factors_prod one_ne_zero
#align unique_factorization_monoid.factors_one UniqueFactorizationMonoid.factors_one
theorem exists_mem_factors_of_dvd {a p : α} (ha0 : a ≠ 0) (hp : Irreducible p) :
p ∣ a → ∃ q ∈ factors a, p ~ᵤ q := fun ⟨b, hb⟩ =>
have hb0 : b ≠ 0 := fun hb0 => by simp_all
have : Multiset.Rel Associated (p ::ₘ factors b) (factors a) :=
factors_unique
(fun x hx => (Multiset.mem_cons.1 hx).elim (fun h => h.symm ▸ hp) (irreducible_of_factor _))
irreducible_of_factor
(Associated.symm <|
calc
Multiset.prod (factors a) ~ᵤ a := factors_prod ha0
_ = p * b := hb
_ ~ᵤ Multiset.prod (p ::ₘ factors b) := by
rw [Multiset.prod_cons]; exact (factors_prod hb0).symm.mul_left _
)
Multiset.exists_mem_of_rel_of_mem this (by simp)
#align unique_factorization_monoid.exists_mem_factors_of_dvd UniqueFactorizationMonoid.exists_mem_factors_of_dvd
theorem exists_mem_factors {x : α} (hx : x ≠ 0) (h : ¬IsUnit x) : ∃ p, p ∈ factors x := by
obtain ⟨p', hp', hp'x⟩ := WfDvdMonoid.exists_irreducible_factor h hx
obtain ⟨p, hp, _⟩ := exists_mem_factors_of_dvd hx hp' hp'x
exact ⟨p, hp⟩
#align unique_factorization_monoid.exists_mem_factors UniqueFactorizationMonoid.exists_mem_factors
open Classical in
theorem factors_mul {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
Multiset.Rel Associated (factors (x * y)) (factors x + factors y) := by
refine
factors_unique irreducible_of_factor
(fun a ha =>
(Multiset.mem_add.mp ha).by_cases (irreducible_of_factor _) (irreducible_of_factor _))
((factors_prod (mul_ne_zero hx hy)).trans ?_)
rw [Multiset.prod_add]
exact (Associated.mul_mul (factors_prod hx) (factors_prod hy)).symm
#align unique_factorization_monoid.factors_mul UniqueFactorizationMonoid.factors_mul
theorem factors_pow {x : α} (n : ℕ) :
Multiset.Rel Associated (factors (x ^ n)) (n • factors x) := by
match n with
| 0 => rw [zero_smul, pow_zero, factors_one, Multiset.rel_zero_right]
| n+1 =>
by_cases h0 : x = 0
· simp [h0, zero_pow n.succ_ne_zero, smul_zero]
· rw [pow_succ', succ_nsmul']
refine Multiset.Rel.trans _ (factors_mul h0 (pow_ne_zero n h0)) ?_
refine Multiset.Rel.add ?_ <| factors_pow n
exact Multiset.rel_refl_of_refl_on fun y _ => Associated.refl _
#align unique_factorization_monoid.factors_pow UniqueFactorizationMonoid.factors_pow
@[simp]
theorem factors_pos (x : α) (hx : x ≠ 0) : 0 < factors x ↔ ¬IsUnit x := by
constructor
· intro h hx
obtain ⟨p, hp⟩ := Multiset.exists_mem_of_ne_zero h.ne'
exact (prime_of_factor _ hp).not_unit (isUnit_of_dvd_unit (dvd_of_mem_factors hp) hx)
· intro h
obtain ⟨p, hp⟩ := exists_mem_factors hx h
exact
bot_lt_iff_ne_bot.mpr
(mt Multiset.eq_zero_iff_forall_not_mem.mp (not_forall.mpr ⟨p, not_not.mpr hp⟩))
#align unique_factorization_monoid.factors_pos UniqueFactorizationMonoid.factors_pos
open Multiset in
theorem factors_pow_count_prod [DecidableEq α] {x : α} (hx : x ≠ 0) :
(∏ p ∈ (factors x).toFinset, p ^ (factors x).count p) ~ᵤ x :=
calc
_ = prod (∑ a ∈ toFinset (factors x), count a (factors x) • {a}) := by
simp only [prod_sum, prod_nsmul, prod_singleton]
_ = prod (factors x) := by rw [toFinset_sum_count_nsmul_eq (factors x)]
_ ~ᵤ x := factors_prod hx
end UniqueFactorizationMonoid
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero α] [NormalizationMonoid α]
variable [UniqueFactorizationMonoid α]
/-- Noncomputably determines the multiset of prime factors. -/
noncomputable def normalizedFactors (a : α) : Multiset α :=
Multiset.map normalize <| factors a
#align unique_factorization_monoid.normalized_factors UniqueFactorizationMonoid.normalizedFactors
/-- An arbitrary choice of factors of `x : M` is exactly the (unique) normalized set of factors,
if `M` has a trivial group of units. -/
@[simp]
theorem factors_eq_normalizedFactors {M : Type*} [CancelCommMonoidWithZero M]
[UniqueFactorizationMonoid M] [Unique Mˣ] (x : M) : factors x = normalizedFactors x := by
unfold normalizedFactors
convert (Multiset.map_id (factors x)).symm
ext p
exact normalize_eq p
#align unique_factorization_monoid.factors_eq_normalized_factors UniqueFactorizationMonoid.factors_eq_normalizedFactors
theorem normalizedFactors_prod {a : α} (ane0 : a ≠ 0) :
Associated (normalizedFactors a).prod a := by
rw [normalizedFactors, factors, dif_neg ane0]
refine Associated.trans ?_ (Classical.choose_spec (exists_prime_factors a ane0)).2
rw [← Associates.mk_eq_mk_iff_associated, ← Associates.prod_mk, ← Associates.prod_mk,
Multiset.map_map]
congr 2
ext
rw [Function.comp_apply, Associates.mk_normalize]
#align unique_factorization_monoid.normalized_factors_prod UniqueFactorizationMonoid.normalizedFactors_prod
theorem prime_of_normalized_factor {a : α} : ∀ x : α, x ∈ normalizedFactors a → Prime x := by
rw [normalizedFactors, factors]
split_ifs with ane0; · simp
intro x hx; rcases Multiset.mem_map.1 hx with ⟨y, ⟨hy, rfl⟩⟩
rw [(normalize_associated _).prime_iff]
exact (Classical.choose_spec (UniqueFactorizationMonoid.exists_prime_factors a ane0)).1 y hy
#align unique_factorization_monoid.prime_of_normalized_factor UniqueFactorizationMonoid.prime_of_normalized_factor
theorem irreducible_of_normalized_factor {a : α} :
∀ x : α, x ∈ normalizedFactors a → Irreducible x := fun x h =>
(prime_of_normalized_factor x h).irreducible
#align unique_factorization_monoid.irreducible_of_normalized_factor UniqueFactorizationMonoid.irreducible_of_normalized_factor
theorem normalize_normalized_factor {a : α} :
∀ x : α, x ∈ normalizedFactors a → normalize x = x := by
rw [normalizedFactors, factors]
split_ifs with h; · simp
intro x hx
obtain ⟨y, _, rfl⟩ := Multiset.mem_map.1 hx
apply normalize_idem
#align unique_factorization_monoid.normalize_normalized_factor UniqueFactorizationMonoid.normalize_normalized_factor
theorem normalizedFactors_irreducible {a : α} (ha : Irreducible a) :
normalizedFactors a = {normalize a} := by
obtain ⟨p, a_assoc, hp⟩ :=
prime_factors_irreducible ha ⟨prime_of_normalized_factor, normalizedFactors_prod ha.ne_zero⟩
have p_mem : p ∈ normalizedFactors a := by
rw [hp]
exact Multiset.mem_singleton_self _
convert hp
rwa [← normalize_normalized_factor p p_mem, normalize_eq_normalize_iff, dvd_dvd_iff_associated]
#align unique_factorization_monoid.normalized_factors_irreducible UniqueFactorizationMonoid.normalizedFactors_irreducible
theorem normalizedFactors_eq_of_dvd (a : α) :
∀ᵉ (p ∈ normalizedFactors a) (q ∈ normalizedFactors a), p ∣ q → p = q := by
intro p hp q hq hdvd
convert normalize_eq_normalize hdvd
((prime_of_normalized_factor _ hp).irreducible.dvd_symm
(prime_of_normalized_factor _ hq).irreducible hdvd) <;>
apply (normalize_normalized_factor _ ‹_›).symm
#align unique_factorization_monoid.normalized_factors_eq_of_dvd UniqueFactorizationMonoid.normalizedFactors_eq_of_dvd
theorem exists_mem_normalizedFactors_of_dvd {a p : α} (ha0 : a ≠ 0) (hp : Irreducible p) :
p ∣ a → ∃ q ∈ normalizedFactors a, p ~ᵤ q := fun ⟨b, hb⟩ =>
have hb0 : b ≠ 0 := fun hb0 => by simp_all
have : Multiset.Rel Associated (p ::ₘ normalizedFactors b) (normalizedFactors a) :=
factors_unique
(fun x hx =>
(Multiset.mem_cons.1 hx).elim (fun h => h.symm ▸ hp) (irreducible_of_normalized_factor _))
irreducible_of_normalized_factor
(Associated.symm <|
calc
Multiset.prod (normalizedFactors a) ~ᵤ a := normalizedFactors_prod ha0
_ = p * b := hb
_ ~ᵤ Multiset.prod (p ::ₘ normalizedFactors b) := by
rw [Multiset.prod_cons]
exact (normalizedFactors_prod hb0).symm.mul_left _
)
Multiset.exists_mem_of_rel_of_mem this (by simp)
#align unique_factorization_monoid.exists_mem_normalized_factors_of_dvd UniqueFactorizationMonoid.exists_mem_normalizedFactors_of_dvd
theorem exists_mem_normalizedFactors {x : α} (hx : x ≠ 0) (h : ¬IsUnit x) :
∃ p, p ∈ normalizedFactors x := by
obtain ⟨p', hp', hp'x⟩ := WfDvdMonoid.exists_irreducible_factor h hx
obtain ⟨p, hp, _⟩ := exists_mem_normalizedFactors_of_dvd hx hp' hp'x
exact ⟨p, hp⟩
#align unique_factorization_monoid.exists_mem_normalized_factors UniqueFactorizationMonoid.exists_mem_normalizedFactors
@[simp]
theorem normalizedFactors_zero : normalizedFactors (0 : α) = 0 := by
simp [normalizedFactors, factors]
#align unique_factorization_monoid.normalized_factors_zero UniqueFactorizationMonoid.normalizedFactors_zero
@[simp]
theorem normalizedFactors_one : normalizedFactors (1 : α) = 0 := by
cases' subsingleton_or_nontrivial α with h h
· dsimp [normalizedFactors, factors]
simp [Subsingleton.elim (1:α) 0]
· rw [← Multiset.rel_zero_right]
apply factors_unique irreducible_of_normalized_factor
· intro x hx
exfalso
apply Multiset.not_mem_zero x hx
· apply normalizedFactors_prod one_ne_zero
#align unique_factorization_monoid.normalized_factors_one UniqueFactorizationMonoid.normalizedFactors_one
@[simp]
theorem normalizedFactors_mul {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
normalizedFactors (x * y) = normalizedFactors x + normalizedFactors y := by
have h : (normalize : α → α) = Associates.out ∘ Associates.mk := by
ext
rw [Function.comp_apply, Associates.out_mk]
rw [← Multiset.map_id' (normalizedFactors (x * y)), ← Multiset.map_id' (normalizedFactors x), ←
Multiset.map_id' (normalizedFactors y), ← Multiset.map_congr rfl normalize_normalized_factor, ←
Multiset.map_congr rfl normalize_normalized_factor, ←
Multiset.map_congr rfl normalize_normalized_factor, ← Multiset.map_add, h, ←
Multiset.map_map Associates.out, eq_comm, ← Multiset.map_map Associates.out]
refine congr rfl ?_
apply Multiset.map_mk_eq_map_mk_of_rel
apply factors_unique
· intro x hx
rcases Multiset.mem_add.1 hx with (hx | hx) <;> exact irreducible_of_normalized_factor x hx
· exact irreducible_of_normalized_factor
· rw [Multiset.prod_add]
exact
((normalizedFactors_prod hx).mul_mul (normalizedFactors_prod hy)).trans
(normalizedFactors_prod (mul_ne_zero hx hy)).symm
#align unique_factorization_monoid.normalized_factors_mul UniqueFactorizationMonoid.normalizedFactors_mul
@[simp]
theorem normalizedFactors_pow {x : α} (n : ℕ) :
normalizedFactors (x ^ n) = n • normalizedFactors x := by
induction' n with n ih
· simp
by_cases h0 : x = 0
· simp [h0, zero_pow n.succ_ne_zero, smul_zero]
rw [pow_succ', succ_nsmul', normalizedFactors_mul h0 (pow_ne_zero _ h0), ih]
#align unique_factorization_monoid.normalized_factors_pow UniqueFactorizationMonoid.normalizedFactors_pow
theorem _root_.Irreducible.normalizedFactors_pow {p : α} (hp : Irreducible p) (k : ℕ) :
normalizedFactors (p ^ k) = Multiset.replicate k (normalize p) := by
rw [UniqueFactorizationMonoid.normalizedFactors_pow, normalizedFactors_irreducible hp,
Multiset.nsmul_singleton]
#align irreducible.normalized_factors_pow Irreducible.normalizedFactors_pow
theorem normalizedFactors_prod_eq (s : Multiset α) (hs : ∀ a ∈ s, Irreducible a) :
normalizedFactors s.prod = s.map normalize := by
induction' s using Multiset.induction with a s ih
· rw [Multiset.prod_zero, normalizedFactors_one, Multiset.map_zero]
· have ia := hs a (Multiset.mem_cons_self a _)
have ib := fun b h => hs b (Multiset.mem_cons_of_mem h)
obtain rfl | ⟨b, hb⟩ := s.empty_or_exists_mem
· rw [Multiset.cons_zero, Multiset.prod_singleton, Multiset.map_singleton,
normalizedFactors_irreducible ia]
haveI := nontrivial_of_ne b 0 (ib b hb).ne_zero
rw [Multiset.prod_cons, Multiset.map_cons,
normalizedFactors_mul ia.ne_zero (Multiset.prod_ne_zero fun h => (ib 0 h).ne_zero rfl),
normalizedFactors_irreducible ia, ih ib, Multiset.singleton_add]
#align unique_factorization_monoid.normalized_factors_prod_eq UniqueFactorizationMonoid.normalizedFactors_prod_eq
theorem dvd_iff_normalizedFactors_le_normalizedFactors {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
x ∣ y ↔ normalizedFactors x ≤ normalizedFactors y := by
constructor
· rintro ⟨c, rfl⟩
simp [hx, right_ne_zero_of_mul hy]
· rw [← (normalizedFactors_prod hx).dvd_iff_dvd_left, ←
(normalizedFactors_prod hy).dvd_iff_dvd_right]
apply Multiset.prod_dvd_prod_of_le
#align unique_factorization_monoid.dvd_iff_normalized_factors_le_normalized_factors UniqueFactorizationMonoid.dvd_iff_normalizedFactors_le_normalizedFactors
theorem associated_iff_normalizedFactors_eq_normalizedFactors {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
x ~ᵤ y ↔ normalizedFactors x = normalizedFactors y := by
refine
⟨fun h => ?_, fun h =>
(normalizedFactors_prod hx).symm.trans (_root_.trans (by rw [h]) (normalizedFactors_prod hy))⟩
apply le_antisymm <;> rw [← dvd_iff_normalizedFactors_le_normalizedFactors]
all_goals simp [*, h.dvd, h.symm.dvd]
#align unique_factorization_monoid.associated_iff_normalized_factors_eq_normalized_factors UniqueFactorizationMonoid.associated_iff_normalizedFactors_eq_normalizedFactors
theorem normalizedFactors_of_irreducible_pow {p : α} (hp : Irreducible p) (k : ℕ) :
normalizedFactors (p ^ k) = Multiset.replicate k (normalize p) := by
rw [normalizedFactors_pow, normalizedFactors_irreducible hp, Multiset.nsmul_singleton]
#align unique_factorization_monoid.normalized_factors_of_irreducible_pow UniqueFactorizationMonoid.normalizedFactors_of_irreducible_pow
theorem zero_not_mem_normalizedFactors (x : α) : (0 : α) ∉ normalizedFactors x := fun h =>
Prime.ne_zero (prime_of_normalized_factor _ h) rfl
#align unique_factorization_monoid.zero_not_mem_normalized_factors UniqueFactorizationMonoid.zero_not_mem_normalizedFactors
theorem dvd_of_mem_normalizedFactors {a p : α} (H : p ∈ normalizedFactors a) : p ∣ a := by
by_cases hcases : a = 0
· rw [hcases]
exact dvd_zero p
· exact dvd_trans (Multiset.dvd_prod H) (Associated.dvd (normalizedFactors_prod hcases))
#align unique_factorization_monoid.dvd_of_mem_normalized_factors UniqueFactorizationMonoid.dvd_of_mem_normalizedFactors
theorem mem_normalizedFactors_iff [Unique αˣ] {p x : α} (hx : x ≠ 0) :
p ∈ normalizedFactors x ↔ Prime p ∧ p ∣ x := by
constructor
· intro h
exact ⟨prime_of_normalized_factor p h, dvd_of_mem_normalizedFactors h⟩
· rintro ⟨hprime, hdvd⟩
obtain ⟨q, hqmem, hqeq⟩ := exists_mem_normalizedFactors_of_dvd hx hprime.irreducible hdvd
rw [associated_iff_eq] at hqeq
exact hqeq ▸ hqmem
theorem exists_associated_prime_pow_of_unique_normalized_factor {p r : α}
(h : ∀ {m}, m ∈ normalizedFactors r → m = p) (hr : r ≠ 0) : ∃ i : ℕ, Associated (p ^ i) r := by
use Multiset.card.toFun (normalizedFactors r)
have := UniqueFactorizationMonoid.normalizedFactors_prod hr
rwa [Multiset.eq_replicate_of_mem fun b => h, Multiset.prod_replicate] at this
#align unique_factorization_monoid.exists_associated_prime_pow_of_unique_normalized_factor UniqueFactorizationMonoid.exists_associated_prime_pow_of_unique_normalized_factor
theorem normalizedFactors_prod_of_prime [Nontrivial α] [Unique αˣ] {m : Multiset α}
(h : ∀ p ∈ m, Prime p) : normalizedFactors m.prod = m := by
simpa only [← Multiset.rel_eq, ← associated_eq_eq] using
prime_factors_unique prime_of_normalized_factor h
(normalizedFactors_prod (m.prod_ne_zero_of_prime h))
#align unique_factorization_monoid.normalized_factors_prod_of_prime UniqueFactorizationMonoid.normalizedFactors_prod_of_prime
theorem mem_normalizedFactors_eq_of_associated {a b c : α} (ha : a ∈ normalizedFactors c)
(hb : b ∈ normalizedFactors c) (h : Associated a b) : a = b := by
rw [← normalize_normalized_factor a ha, ← normalize_normalized_factor b hb,
normalize_eq_normalize_iff]
exact Associated.dvd_dvd h
#align unique_factorization_monoid.mem_normalized_factors_eq_of_associated UniqueFactorizationMonoid.mem_normalizedFactors_eq_of_associated
@[simp]
theorem normalizedFactors_pos (x : α) (hx : x ≠ 0) : 0 < normalizedFactors x ↔ ¬IsUnit x := by
constructor
· intro h hx
obtain ⟨p, hp⟩ := Multiset.exists_mem_of_ne_zero h.ne'
exact
(prime_of_normalized_factor _ hp).not_unit
(isUnit_of_dvd_unit (dvd_of_mem_normalizedFactors hp) hx)
· intro h
obtain ⟨p, hp⟩ := exists_mem_normalizedFactors hx h
exact
bot_lt_iff_ne_bot.mpr
(mt Multiset.eq_zero_iff_forall_not_mem.mp (not_forall.mpr ⟨p, not_not.mpr hp⟩))
#align unique_factorization_monoid.normalized_factors_pos UniqueFactorizationMonoid.normalizedFactors_pos
theorem dvdNotUnit_iff_normalizedFactors_lt_normalizedFactors {x y : α} (hx : x ≠ 0) (hy : y ≠ 0) :
DvdNotUnit x y ↔ normalizedFactors x < normalizedFactors y := by
constructor
· rintro ⟨_, c, hc, rfl⟩
simp only [hx, right_ne_zero_of_mul hy, normalizedFactors_mul, Ne, not_false_iff,
lt_add_iff_pos_right, normalizedFactors_pos, hc]
· intro h
exact
dvdNotUnit_of_dvd_of_not_dvd
((dvd_iff_normalizedFactors_le_normalizedFactors hx hy).mpr h.le)
(mt (dvd_iff_normalizedFactors_le_normalizedFactors hy hx).mp h.not_le)
#align unique_factorization_monoid.dvd_not_unit_iff_normalized_factors_lt_normalized_factors UniqueFactorizationMonoid.dvdNotUnit_iff_normalizedFactors_lt_normalizedFactors
theorem normalizedFactors_multiset_prod (s : Multiset α) (hs : 0 ∉ s) :
normalizedFactors (s.prod) = (s.map normalizedFactors).sum := by
cases subsingleton_or_nontrivial α
· obtain rfl : s = 0 := by
apply Multiset.eq_zero_of_forall_not_mem
intro _
convert hs
simp
induction s using Multiset.induction with
| empty => simp
| cons _ _ IH =>
rw [Multiset.prod_cons, Multiset.map_cons, Multiset.sum_cons, normalizedFactors_mul, IH]
· exact fun h ↦ hs (Multiset.mem_cons_of_mem h)
· exact fun h ↦ hs (h ▸ Multiset.mem_cons_self _ _)
· apply Multiset.prod_ne_zero
exact fun h ↦ hs (Multiset.mem_cons_of_mem h)
end UniqueFactorizationMonoid
namespace UniqueFactorizationMonoid
open scoped Classical
open Multiset Associates
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
/-- Noncomputably defines a `normalizationMonoid` structure on a `UniqueFactorizationMonoid`. -/
protected noncomputable def normalizationMonoid : NormalizationMonoid α :=
normalizationMonoidOfMonoidHomRightInverse
{ toFun := fun a : Associates α =>
if a = 0 then 0
else
((normalizedFactors a).map
(Classical.choose mk_surjective.hasRightInverse : Associates α → α)).prod
map_one' := by nontriviality α; simp
map_mul' := fun x y => by
by_cases hx : x = 0
· simp [hx]
by_cases hy : y = 0
· simp [hy]
simp [hx, hy] }
(by
intro x
dsimp
by_cases hx : x = 0
· simp [hx]
have h : Associates.mkMonoidHom ∘ Classical.choose mk_surjective.hasRightInverse =
(id : Associates α → Associates α) := by
ext x
rw [Function.comp_apply, mkMonoidHom_apply,
Classical.choose_spec mk_surjective.hasRightInverse x]
rfl
rw [if_neg hx, ← mkMonoidHom_apply, MonoidHom.map_multiset_prod, map_map, h, map_id, ←
associated_iff_eq]
apply normalizedFactors_prod hx)
#align unique_factorization_monoid.normalization_monoid UniqueFactorizationMonoid.normalizationMonoid
end UniqueFactorizationMonoid
namespace UniqueFactorizationMonoid
variable {R : Type*} [CancelCommMonoidWithZero R] [UniqueFactorizationMonoid R]
theorem isRelPrime_iff_no_prime_factors {a b : R} (ha : a ≠ 0) :
IsRelPrime a b ↔ ∀ ⦃d⦄, d ∣ a → d ∣ b → ¬Prime d :=
⟨fun h _ ha hb ↦ (·.not_unit <| h ha hb), fun h ↦ WfDvdMonoid.isRelPrime_of_no_irreducible_factors
(ha ·.1) fun _ irr ha hb ↦ h ha hb (UniqueFactorizationMonoid.irreducible_iff_prime.mp irr)⟩
#align unique_factorization_monoid.no_factors_of_no_prime_factors UniqueFactorizationMonoid.isRelPrime_iff_no_prime_factors
/-- Euclid's lemma: if `a ∣ b * c` and `a` and `c` have no common prime factors, `a ∣ b`.
Compare `IsCoprime.dvd_of_dvd_mul_left`. -/
theorem dvd_of_dvd_mul_left_of_no_prime_factors {a b c : R} (ha : a ≠ 0)
(h : ∀ ⦃d⦄, d ∣ a → d ∣ c → ¬Prime d) : a ∣ b * c → a ∣ b :=
((isRelPrime_iff_no_prime_factors ha).mpr h).dvd_of_dvd_mul_right
#align unique_factorization_monoid.dvd_of_dvd_mul_left_of_no_prime_factors UniqueFactorizationMonoid.dvd_of_dvd_mul_left_of_no_prime_factors
/-- Euclid's lemma: if `a ∣ b * c` and `a` and `b` have no common prime factors, `a ∣ c`.
Compare `IsCoprime.dvd_of_dvd_mul_right`. -/
theorem dvd_of_dvd_mul_right_of_no_prime_factors {a b c : R} (ha : a ≠ 0)
(no_factors : ∀ {d}, d ∣ a → d ∣ b → ¬Prime d) : a ∣ b * c → a ∣ c := by
simpa [mul_comm b c] using dvd_of_dvd_mul_left_of_no_prime_factors ha @no_factors
#align unique_factorization_monoid.dvd_of_dvd_mul_right_of_no_prime_factors UniqueFactorizationMonoid.dvd_of_dvd_mul_right_of_no_prime_factors
/-- If `a ≠ 0, b` are elements of a unique factorization domain, then dividing
out their common factor `c'` gives `a'` and `b'` with no factors in common. -/
theorem exists_reduced_factors :
∀ a ≠ (0 : R), ∀ b,
∃ a' b' c', IsRelPrime a' b' ∧ c' * a' = a ∧ c' * b' = b := by
intro a
refine induction_on_prime a ?_ ?_ ?_
· intros
contradiction
· intro a a_unit _ b
use a, b, 1
constructor
· intro p p_dvd_a _
exact isUnit_of_dvd_unit p_dvd_a a_unit
· simp
· intro a p a_ne_zero p_prime ih_a pa_ne_zero b
by_cases h : p ∣ b
· rcases h with ⟨b, rfl⟩
obtain ⟨a', b', c', no_factor, ha', hb'⟩ := ih_a a_ne_zero b
refine ⟨a', b', p * c', @no_factor, ?_, ?_⟩
· rw [mul_assoc, ha']
· rw [mul_assoc, hb']
· obtain ⟨a', b', c', coprime, rfl, rfl⟩ := ih_a a_ne_zero b
refine ⟨p * a', b', c', ?_, mul_left_comm _ _ _, rfl⟩
intro q q_dvd_pa' q_dvd_b'
cases' p_prime.left_dvd_or_dvd_right_of_dvd_mul q_dvd_pa' with p_dvd_q q_dvd_a'
· have : p ∣ c' * b' := dvd_mul_of_dvd_right (p_dvd_q.trans q_dvd_b') _
contradiction
exact coprime q_dvd_a' q_dvd_b'
#align unique_factorization_monoid.exists_reduced_factors UniqueFactorizationMonoid.exists_reduced_factors
theorem exists_reduced_factors' (a b : R) (hb : b ≠ 0) :
∃ a' b' c', IsRelPrime a' b' ∧ c' * a' = a ∧ c' * b' = b :=
let ⟨b', a', c', no_factor, hb, ha⟩ := exists_reduced_factors b hb a
⟨a', b', c', fun _ hpb hpa => no_factor hpa hpb, ha, hb⟩
#align unique_factorization_monoid.exists_reduced_factors' UniqueFactorizationMonoid.exists_reduced_factors'
theorem pow_right_injective {a : R} (ha0 : a ≠ 0) (ha1 : ¬IsUnit a) :
Function.Injective (a ^ · : ℕ → R) := by
letI := Classical.decEq R
intro i j hij
letI : Nontrivial R := ⟨⟨a, 0, ha0⟩⟩
letI : NormalizationMonoid R := UniqueFactorizationMonoid.normalizationMonoid
obtain ⟨p', hp', dvd'⟩ := WfDvdMonoid.exists_irreducible_factor ha1 ha0
obtain ⟨p, mem, _⟩ := exists_mem_normalizedFactors_of_dvd ha0 hp' dvd'
have := congr_arg (fun x => Multiset.count p (normalizedFactors x)) hij
simp only [normalizedFactors_pow, Multiset.count_nsmul] at this
exact mul_right_cancel₀ (Multiset.count_ne_zero.mpr mem) this
#align unique_factorization_monoid.pow_right_injective UniqueFactorizationMonoid.pow_right_injective
theorem pow_eq_pow_iff {a : R} (ha0 : a ≠ 0) (ha1 : ¬IsUnit a) {i j : ℕ} : a ^ i = a ^ j ↔ i = j :=
(pow_right_injective ha0 ha1).eq_iff
#align unique_factorization_monoid.pow_eq_pow_iff UniqueFactorizationMonoid.pow_eq_pow_iff
section multiplicity
variable [NormalizationMonoid R]
variable [DecidableRel (Dvd.dvd : R → R → Prop)]
open multiplicity Multiset
theorem le_multiplicity_iff_replicate_le_normalizedFactors {a b : R} {n : ℕ} (ha : Irreducible a)
(hb : b ≠ 0) :
↑n ≤ multiplicity a b ↔ replicate n (normalize a) ≤ normalizedFactors b := by
rw [← pow_dvd_iff_le_multiplicity]
revert b
induction' n with n ih; · simp
intro b hb
constructor
· rintro ⟨c, rfl⟩
rw [Ne, pow_succ', mul_assoc, mul_eq_zero, not_or] at hb
rw [pow_succ', mul_assoc, normalizedFactors_mul hb.1 hb.2, replicate_succ,
normalizedFactors_irreducible ha, singleton_add, cons_le_cons_iff, ← ih hb.2]
apply Dvd.intro _ rfl
· rw [Multiset.le_iff_exists_add]
rintro ⟨u, hu⟩
rw [← (normalizedFactors_prod hb).dvd_iff_dvd_right, hu, prod_add, prod_replicate]
exact (Associated.pow_pow <| associated_normalize a).dvd.trans (Dvd.intro u.prod rfl)
#align unique_factorization_monoid.le_multiplicity_iff_replicate_le_normalized_factors UniqueFactorizationMonoid.le_multiplicity_iff_replicate_le_normalizedFactors
/-- The multiplicity of an irreducible factor of a nonzero element is exactly the number of times
the normalized factor occurs in the `normalizedFactors`.
See also `count_normalizedFactors_eq` which expands the definition of `multiplicity`
to produce a specification for `count (normalizedFactors _) _`..
-/
theorem multiplicity_eq_count_normalizedFactors [DecidableEq R] {a b : R} (ha : Irreducible a)
(hb : b ≠ 0) : multiplicity a b = (normalizedFactors b).count (normalize a) := by
apply le_antisymm
· apply PartENat.le_of_lt_add_one
rw [← Nat.cast_one, ← Nat.cast_add, lt_iff_not_ge, ge_iff_le,
le_multiplicity_iff_replicate_le_normalizedFactors ha hb, ← le_count_iff_replicate_le]
simp
rw [le_multiplicity_iff_replicate_le_normalizedFactors ha hb, ← le_count_iff_replicate_le]
#align unique_factorization_monoid.multiplicity_eq_count_normalized_factors UniqueFactorizationMonoid.multiplicity_eq_count_normalizedFactors
/-- The number of times an irreducible factor `p` appears in `normalizedFactors x` is defined by
the number of times it divides `x`.
See also `multiplicity_eq_count_normalizedFactors` if `n` is given by `multiplicity p x`.
-/
theorem count_normalizedFactors_eq [DecidableEq R] {p x : R} (hp : Irreducible p)
(hnorm : normalize p = p) {n : ℕ} (hle : p ^ n ∣ x) (hlt : ¬p ^ (n + 1) ∣ x) :
(normalizedFactors x).count p = n := by
letI : DecidableRel ((· ∣ ·) : R → R → Prop) := fun _ _ => Classical.propDecidable _
by_cases hx0 : x = 0
· simp [hx0] at hlt
rw [← PartENat.natCast_inj]
convert (multiplicity_eq_count_normalizedFactors hp hx0).symm
· exact hnorm.symm
exact (multiplicity.eq_coe_iff.mpr ⟨hle, hlt⟩).symm
#align unique_factorization_monoid.count_normalized_factors_eq UniqueFactorizationMonoid.count_normalizedFactors_eq
/-- The number of times an irreducible factor `p` appears in `normalizedFactors x` is defined by
the number of times it divides `x`. This is a slightly more general version of
`UniqueFactorizationMonoid.count_normalizedFactors_eq` that allows `p = 0`.
See also `multiplicity_eq_count_normalizedFactors` if `n` is given by `multiplicity p x`.
-/
theorem count_normalizedFactors_eq' [DecidableEq R] {p x : R} (hp : p = 0 ∨ Irreducible p)
(hnorm : normalize p = p) {n : ℕ} (hle : p ^ n ∣ x) (hlt : ¬p ^ (n + 1) ∣ x) :
(normalizedFactors x).count p = n := by
rcases hp with (rfl | hp)
· cases n
· exact count_eq_zero.2 (zero_not_mem_normalizedFactors _)
· rw [zero_pow (Nat.succ_ne_zero _)] at hle hlt
exact absurd hle hlt
· exact count_normalizedFactors_eq hp hnorm hle hlt
#align unique_factorization_monoid.count_normalized_factors_eq' UniqueFactorizationMonoid.count_normalizedFactors_eq'
/-- Deprecated. Use `WfDvdMonoid.max_power_factor` instead. -/
@[deprecated WfDvdMonoid.max_power_factor]
theorem max_power_factor {a₀ x : R} (h : a₀ ≠ 0) (hx : Irreducible x) :
∃ n : ℕ, ∃ a : R, ¬x ∣ a ∧ a₀ = x ^ n * a := WfDvdMonoid.max_power_factor h hx
#align unique_factorization_monoid.max_power_factor UniqueFactorizationMonoid.max_power_factor
end multiplicity
section Multiplicative
variable [CancelCommMonoidWithZero α] [UniqueFactorizationMonoid α]
variable {β : Type*} [CancelCommMonoidWithZero β]
theorem prime_pow_coprime_prod_of_coprime_insert [DecidableEq α] {s : Finset α} (i : α → ℕ) (p : α)
(hps : p ∉ s) (is_prime : ∀ q ∈ insert p s, Prime q)
(is_coprime : ∀ᵉ (q ∈ insert p s) (q' ∈ insert p s), q ∣ q' → q = q') :
IsRelPrime (p ^ i p) (∏ p' ∈ s, p' ^ i p') := by
have hp := is_prime _ (Finset.mem_insert_self _ _)
refine (isRelPrime_iff_no_prime_factors <| pow_ne_zero _ hp.ne_zero).mpr ?_
intro d hdp hdprod hd
apply hps
replace hdp := hd.dvd_of_dvd_pow hdp
obtain ⟨q, q_mem', hdq⟩ := hd.exists_mem_multiset_dvd hdprod
obtain ⟨q, q_mem, rfl⟩ := Multiset.mem_map.mp q_mem'
replace hdq := hd.dvd_of_dvd_pow hdq
have : p ∣ q := dvd_trans (hd.irreducible.dvd_symm hp.irreducible hdp) hdq
convert q_mem
rw [Finset.mem_val,
is_coprime _ (Finset.mem_insert_self p s) _ (Finset.mem_insert_of_mem q_mem) this]
#align unique_factorization_monoid.prime_pow_coprime_prod_of_coprime_insert UniqueFactorizationMonoid.prime_pow_coprime_prod_of_coprime_insert
/-- If `P` holds for units and powers of primes,
and `P x ∧ P y` for coprime `x, y` implies `P (x * y)`,
then `P` holds on a product of powers of distinct primes. -/
-- @[elab_as_elim] Porting note: commented out
theorem induction_on_prime_power {P : α → Prop} (s : Finset α) (i : α → ℕ)
(is_prime : ∀ p ∈ s, Prime p) (is_coprime : ∀ᵉ (p ∈ s) (q ∈ s), p ∣ q → p = q)
(h1 : ∀ {x}, IsUnit x → P x) (hpr : ∀ {p} (i : ℕ), Prime p → P (p ^ i))
(hcp : ∀ {x y}, IsRelPrime x y → P x → P y → P (x * y)) :
P (∏ p ∈ s, p ^ i p) := by
letI := Classical.decEq α
induction' s using Finset.induction_on with p f' hpf' ih
· simpa using h1 isUnit_one
rw [Finset.prod_insert hpf']
exact
hcp (prime_pow_coprime_prod_of_coprime_insert i p hpf' is_prime is_coprime)
(hpr (i p) (is_prime _ (Finset.mem_insert_self _ _)))
(ih (fun q hq => is_prime _ (Finset.mem_insert_of_mem hq)) fun q hq q' hq' =>
is_coprime _ (Finset.mem_insert_of_mem hq) _ (Finset.mem_insert_of_mem hq'))
#align unique_factorization_monoid.induction_on_prime_power UniqueFactorizationMonoid.induction_on_prime_power
/-- If `P` holds for `0`, units and powers of primes,
and `P x ∧ P y` for coprime `x, y` implies `P (x * y)`,
then `P` holds on all `a : α`. -/
@[elab_as_elim]
theorem induction_on_coprime {P : α → Prop} (a : α) (h0 : P 0) (h1 : ∀ {x}, IsUnit x → P x)
(hpr : ∀ {p} (i : ℕ), Prime p → P (p ^ i))
(hcp : ∀ {x y}, IsRelPrime x y → P x → P y → P (x * y)) : P a := by
letI := Classical.decEq α
have P_of_associated : ∀ {x y}, Associated x y → P x → P y := by
rintro x y ⟨u, rfl⟩ hx
exact hcp (fun p _ hpx => isUnit_of_dvd_unit hpx u.isUnit) hx (h1 u.isUnit)
by_cases ha0 : a = 0
· rwa [ha0]
haveI : Nontrivial α := ⟨⟨_, _, ha0⟩⟩
letI : NormalizationMonoid α := UniqueFactorizationMonoid.normalizationMonoid
refine P_of_associated (normalizedFactors_prod ha0) ?_
rw [← (normalizedFactors a).map_id, Finset.prod_multiset_map_count]
refine induction_on_prime_power _ _ ?_ ?_ @h1 @hpr @hcp <;> simp only [Multiset.mem_toFinset]
· apply prime_of_normalized_factor
· apply normalizedFactors_eq_of_dvd
#align unique_factorization_monoid.induction_on_coprime UniqueFactorizationMonoid.induction_on_coprime
/-- If `f` maps `p ^ i` to `(f p) ^ i` for primes `p`, and `f`
is multiplicative on coprime elements, then `f` is multiplicative on all products of primes. -/
-- @[elab_as_elim] Porting note: commented out
theorem multiplicative_prime_power {f : α → β} (s : Finset α) (i j : α → ℕ)
(is_prime : ∀ p ∈ s, Prime p) (is_coprime : ∀ᵉ (p ∈ s) (q ∈ s), p ∣ q → p = q)
(h1 : ∀ {x y}, IsUnit y → f (x * y) = f x * f y)
(hpr : ∀ {p} (i : ℕ), Prime p → f (p ^ i) = f p ^ i)
(hcp : ∀ {x y}, IsRelPrime x y → f (x * y) = f x * f y) :
f (∏ p ∈ s, p ^ (i p + j p)) = f (∏ p ∈ s, p ^ i p) * f (∏ p ∈ s, p ^ j p) := by
letI := Classical.decEq α
induction' s using Finset.induction_on with p s hps ih
· simpa using h1 isUnit_one
have hpr_p := is_prime _ (Finset.mem_insert_self _ _)
have hpr_s : ∀ p ∈ s, Prime p := fun p hp => is_prime _ (Finset.mem_insert_of_mem hp)
have hcp_p := fun i => prime_pow_coprime_prod_of_coprime_insert i p hps is_prime is_coprime
have hcp_s : ∀ᵉ (p ∈ s) (q ∈ s), p ∣ q → p = q := fun p hp q hq =>
is_coprime p (Finset.mem_insert_of_mem hp) q (Finset.mem_insert_of_mem hq)
rw [Finset.prod_insert hps, Finset.prod_insert hps, Finset.prod_insert hps, hcp (hcp_p _),
hpr _ hpr_p, hcp (hcp_p _), hpr _ hpr_p, hcp (hcp_p (fun p => i p + j p)), hpr _ hpr_p,
ih hpr_s hcp_s, pow_add, mul_assoc, mul_left_comm (f p ^ j p), mul_assoc]
#align unique_factorization_monoid.multiplicative_prime_power UniqueFactorizationMonoid.multiplicative_prime_power
/-- If `f` maps `p ^ i` to `(f p) ^ i` for primes `p`, and `f`
is multiplicative on coprime elements, then `f` is multiplicative everywhere. -/
theorem multiplicative_of_coprime (f : α → β) (a b : α) (h0 : f 0 = 0)
(h1 : ∀ {x y}, IsUnit y → f (x * y) = f x * f y)
(hpr : ∀ {p} (i : ℕ), Prime p → f (p ^ i) = f p ^ i)
(hcp : ∀ {x y}, IsRelPrime x y → f (x * y) = f x * f y) :
f (a * b) = f a * f b := by
letI := Classical.decEq α
by_cases ha0 : a = 0
· rw [ha0, zero_mul, h0, zero_mul]
by_cases hb0 : b = 0
· rw [hb0, mul_zero, h0, mul_zero]
by_cases hf1 : f 1 = 0
· calc
f (a * b) = f (a * b * 1) := by rw [mul_one]
_ = 0 := by simp only [h1 isUnit_one, hf1, mul_zero]
_ = f a * f (b * 1) := by simp only [h1 isUnit_one, hf1, mul_zero]
_ = f a * f b := by rw [mul_one]
haveI : Nontrivial α := ⟨⟨_, _, ha0⟩⟩
letI : NormalizationMonoid α := UniqueFactorizationMonoid.normalizationMonoid
suffices
f (∏ p ∈ (normalizedFactors a).toFinset ∪ (normalizedFactors b).toFinset,
p ^ ((normalizedFactors a).count p + (normalizedFactors b).count p)) =
f (∏ p ∈ (normalizedFactors a).toFinset ∪ (normalizedFactors b).toFinset,
p ^ (normalizedFactors a).count p) *
f (∏ p ∈ (normalizedFactors a).toFinset ∪ (normalizedFactors b).toFinset,
p ^ (normalizedFactors b).count p) by
obtain ⟨ua, a_eq⟩ := normalizedFactors_prod ha0
obtain ⟨ub, b_eq⟩ := normalizedFactors_prod hb0
rw [← a_eq, ← b_eq, mul_right_comm (Multiset.prod (normalizedFactors a)) ua
(Multiset.prod (normalizedFactors b) * ub), h1 ua.isUnit, h1 ub.isUnit, h1 ua.isUnit, ←
mul_assoc, h1 ub.isUnit, mul_right_comm _ (f ua), ← mul_assoc]
congr
rw [← (normalizedFactors a).map_id, ← (normalizedFactors b).map_id,
Finset.prod_multiset_map_count, Finset.prod_multiset_map_count,
Finset.prod_subset (Finset.subset_union_left (s₂:=(normalizedFactors b).toFinset)),
Finset.prod_subset (Finset.subset_union_right (s₂:=(normalizedFactors b).toFinset)), ←
Finset.prod_mul_distrib]
· simp_rw [id, ← pow_add, this]
all_goals simp only [Multiset.mem_toFinset]
· intro p _ hpb
simp [hpb]
· intro p _ hpa
simp [hpa]
refine multiplicative_prime_power _ _ _ ?_ ?_ @h1 @hpr @hcp
all_goals simp only [Multiset.mem_toFinset, Finset.mem_union]
· rintro p (hpa | hpb) <;> apply prime_of_normalized_factor <;> assumption
· rintro p (hp | hp) q (hq | hq) hdvd <;>
rw [← normalize_normalized_factor _ hp, ← normalize_normalized_factor _ hq] <;>
exact
normalize_eq_normalize hdvd
((prime_of_normalized_factor _ hp).irreducible.dvd_symm
(prime_of_normalized_factor _ hq).irreducible hdvd)
#align unique_factorization_monoid.multiplicative_of_coprime UniqueFactorizationMonoid.multiplicative_of_coprime
end Multiplicative
end UniqueFactorizationMonoid
namespace Associates
open UniqueFactorizationMonoid Associated Multiset
variable [CancelCommMonoidWithZero α]
/-- `FactorSet α` representation elements of unique factorization domain as multisets.
`Multiset α` produced by `normalizedFactors` are only unique up to associated elements, while the
multisets in `FactorSet α` are unique by equality and restricted to irreducible elements. This
gives us a representation of each element as a unique multisets (or the added ⊤ for 0), which has a
complete lattice structure. Infimum is the greatest common divisor and supremum is the least common
multiple.
-/
abbrev FactorSet.{u} (α : Type u) [CancelCommMonoidWithZero α] : Type u :=
WithTop (Multiset { a : Associates α // Irreducible a })
#align associates.factor_set Associates.FactorSet
attribute [local instance] Associated.setoid
theorem FactorSet.coe_add {a b : Multiset { a : Associates α // Irreducible a }} :
(↑(a + b) : FactorSet α) = a + b := by norm_cast
#align associates.factor_set.coe_add Associates.FactorSet.coe_add
theorem FactorSet.sup_add_inf_eq_add [DecidableEq (Associates α)] :
∀ a b : FactorSet α, a ⊔ b + a ⊓ b = a + b
| ⊤, b => show ⊤ ⊔ b + ⊤ ⊓ b = ⊤ + b by simp
| a, ⊤ => show a ⊔ ⊤ + a ⊓ ⊤ = a + ⊤ by simp
| WithTop.some a, WithTop.some b =>
show (a : FactorSet α) ⊔ b + (a : FactorSet α) ⊓ b = a + b by
rw [← WithTop.coe_sup, ← WithTop.coe_inf, ← WithTop.coe_add, ← WithTop.coe_add,
WithTop.coe_eq_coe]
exact Multiset.union_add_inter _ _
#align associates.factor_set.sup_add_inf_eq_add Associates.FactorSet.sup_add_inf_eq_add
/-- Evaluates the product of a `FactorSet` to be the product of the corresponding multiset,
or `0` if there is none. -/
def FactorSet.prod : FactorSet α → Associates α
| ⊤ => 0
| WithTop.some s => (s.map (↑)).prod
#align associates.factor_set.prod Associates.FactorSet.prod
@[simp]
theorem prod_top : (⊤ : FactorSet α).prod = 0 :=
rfl
#align associates.prod_top Associates.prod_top
@[simp]
theorem prod_coe {s : Multiset { a : Associates α // Irreducible a }} :
FactorSet.prod (s : FactorSet α) = (s.map (↑)).prod :=
rfl
#align associates.prod_coe Associates.prod_coe
@[simp]
theorem prod_add : ∀ a b : FactorSet α, (a + b).prod = a.prod * b.prod
| ⊤, b => show (⊤ + b).prod = (⊤ : FactorSet α).prod * b.prod by simp
| a, ⊤ => show (a + ⊤).prod = a.prod * (⊤ : FactorSet α).prod by simp
| WithTop.some a, WithTop.some b => by
rw [← FactorSet.coe_add, prod_coe, prod_coe, prod_coe, Multiset.map_add, Multiset.prod_add]
#align associates.prod_add Associates.prod_add
@[gcongr]
theorem prod_mono : ∀ {a b : FactorSet α}, a ≤ b → a.prod ≤ b.prod
| ⊤, b, h => by
have : b = ⊤ := top_unique h
rw [this, prod_top]
| a, ⊤, _ => show a.prod ≤ (⊤ : FactorSet α).prod by simp
| WithTop.some a, WithTop.some b, h =>
prod_le_prod <| Multiset.map_le_map <| WithTop.coe_le_coe.1 <| h
#align associates.prod_mono Associates.prod_mono
theorem FactorSet.prod_eq_zero_iff [Nontrivial α] (p : FactorSet α) : p.prod = 0 ↔ p = ⊤ := by
unfold FactorSet at p
induction p -- TODO: `induction_eliminator` doesn't work with `abbrev`
· simp only [iff_self_iff, eq_self_iff_true, Associates.prod_top]
· rw [prod_coe, Multiset.prod_eq_zero_iff, Multiset.mem_map, eq_false WithTop.coe_ne_top,
iff_false_iff, not_exists]
exact fun a => not_and_of_not_right _ a.prop.ne_zero
#align associates.factor_set.prod_eq_zero_iff Associates.FactorSet.prod_eq_zero_iff
section count
variable [DecidableEq (Associates α)]
/-- `bcount p s` is the multiplicity of `p` in the FactorSet `s` (with bundled `p`)-/
def bcount (p : { a : Associates α // Irreducible a }) :
FactorSet α → ℕ
| ⊤ => 0
| WithTop.some s => s.count p
#align associates.bcount Associates.bcount
variable [∀ p : Associates α, Decidable (Irreducible p)] {p : Associates α}
/-- `count p s` is the multiplicity of the irreducible `p` in the FactorSet `s`.
If `p` is not irreducible, `count p s` is defined to be `0`. -/
def count (p : Associates α) : FactorSet α → ℕ :=
if hp : Irreducible p then bcount ⟨p, hp⟩ else 0
#align associates.count Associates.count
@[simp]
theorem count_some (hp : Irreducible p) (s : Multiset _) :
count p (WithTop.some s) = s.count ⟨p, hp⟩ := by
simp only [count, dif_pos hp, bcount]
#align associates.count_some Associates.count_some
@[simp]
| Mathlib/RingTheory/UniqueFactorizationDomain.lean | 1,322 | 1,323 | theorem count_zero (hp : Irreducible p) : count p (0 : FactorSet α) = 0 := by |
simp only [count, dif_pos hp, bcount, Multiset.count_zero]
|
/-
Copyright (c) 2019 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.Analysis.Calculus.ContDiff.Basic
import Mathlib.Data.Finset.Sym
import Mathlib.Data.Nat.Choose.Cast
import Mathlib.Data.Nat.Choose.Multinomial
#align_import analysis.calculus.cont_diff from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# Bounds on higher derivatives
`norm_iteratedFDeriv_comp_le` gives the bound `n! * C * D ^ n` for the `n`-th derivative
of `g ∘ f` assuming that the derivatives of `g` are bounded by `C` and the `i`-th
derivative of `f` is bounded by `D ^ i`.
-/
noncomputable section
open scoped Classical NNReal Nat
universe u uD uE uF uG
open Set Fin Filter Function
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] {D : Type uD} [NormedAddCommGroup D]
[NormedSpace 𝕜 D] {E : Type uE} [NormedAddCommGroup E] [NormedSpace 𝕜 E] {F : Type uF}
[NormedAddCommGroup F] [NormedSpace 𝕜 F] {G : Type uG} [NormedAddCommGroup G] [NormedSpace 𝕜 G]
{s s₁ t u : Set E}
/-!## Quantitative bounds -/
/-- Bounding the norm of the iterated derivative of `B (f x) (g x)` within a set in terms of the
iterated derivatives of `f` and `g` when `B` is bilinear. This lemma is an auxiliary version
assuming all spaces live in the same universe, to enable an induction. Use instead
`ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear` that removes this assumption. -/
| Mathlib/Analysis/Calculus/ContDiff/Bounds.lean | 40 | 122 | theorem ContinuousLinearMap.norm_iteratedFDerivWithin_le_of_bilinear_aux {Du Eu Fu Gu : Type u}
[NormedAddCommGroup Du] [NormedSpace 𝕜 Du] [NormedAddCommGroup Eu] [NormedSpace 𝕜 Eu]
[NormedAddCommGroup Fu] [NormedSpace 𝕜 Fu] [NormedAddCommGroup Gu] [NormedSpace 𝕜 Gu]
(B : Eu →L[𝕜] Fu →L[𝕜] Gu) {f : Du → Eu} {g : Du → Fu} {n : ℕ} {s : Set Du} {x : Du}
(hf : ContDiffOn 𝕜 n f s) (hg : ContDiffOn 𝕜 n g s) (hs : UniqueDiffOn 𝕜 s) (hx : x ∈ s) :
‖iteratedFDerivWithin 𝕜 n (fun y => B (f y) (g y)) s x‖ ≤
‖B‖ * ∑ i ∈ Finset.range (n + 1), (n.choose i : ℝ) * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ := by |
/- We argue by induction on `n`. The bound is trivial for `n = 0`. For `n + 1`, we write
the `(n+1)`-th derivative as the `n`-th derivative of the derivative `B f g' + B f' g`,
and apply the inductive assumption to each of those two terms. For this induction to make sense,
the spaces of linear maps that appear in the induction should be in the same universe as the
original spaces, which explains why we assume in the lemma that all spaces live in the same
universe. -/
induction' n with n IH generalizing Eu Fu Gu
· simp only [Nat.zero_eq, norm_iteratedFDerivWithin_zero, zero_add, Finset.range_one,
Finset.sum_singleton, Nat.choose_self, Nat.cast_one, one_mul, Nat.sub_zero, ← mul_assoc]
apply B.le_opNorm₂
· have In : (n : ℕ∞) + 1 ≤ n.succ := by simp only [Nat.cast_succ, le_refl]
-- Porting note: the next line is a hack allowing Lean to find the operator norm instance.
let norm := @ContinuousLinearMap.hasOpNorm _ _ Eu ((Du →L[𝕜] Fu) →L[𝕜] Du →L[𝕜] Gu) _ _ _ _ _ _
(RingHom.id 𝕜)
have I1 :
‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompR Du (f y) (fderivWithin 𝕜 g s y)) s x‖ ≤
‖B‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n + 1 - i) g s x‖ := by
calc
‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompR Du (f y) (fderivWithin 𝕜 g s y)) s x‖ ≤
‖B.precompR Du‖ * ∑ i ∈ Finset.range (n + 1),
n.choose i * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) (fderivWithin 𝕜 g s) s x‖ :=
IH _ (hf.of_le (Nat.cast_le.2 (Nat.le_succ n))) (hg.fderivWithin hs In)
_ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 i f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) (fderivWithin 𝕜 g s) s x‖ :=
mul_le_mul_of_nonneg_right (B.norm_precompR_le Du) (by positivity)
_ = _ := by
congr 1
apply Finset.sum_congr rfl fun i hi => ?_
rw [Nat.succ_sub (Nat.lt_succ_iff.1 (Finset.mem_range.1 hi)),
← norm_iteratedFDerivWithin_fderivWithin hs hx]
-- Porting note: the next line is a hack allowing Lean to find the operator norm instance.
let norm := @ContinuousLinearMap.hasOpNorm _ _ (Du →L[𝕜] Eu) (Fu →L[𝕜] Du →L[𝕜] Gu) _ _ _ _ _ _
(RingHom.id 𝕜)
have I2 :
‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s x‖ ≤
‖B‖ * ∑ i ∈ Finset.range (n + 1), n.choose i * ‖iteratedFDerivWithin 𝕜 (i + 1) f s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ :=
calc
‖iteratedFDerivWithin 𝕜 n (fun y : Du => B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s x‖ ≤
‖B.precompL Du‖ * ∑ i ∈ Finset.range (n + 1),
n.choose i * ‖iteratedFDerivWithin 𝕜 i (fderivWithin 𝕜 f s) s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ :=
IH _ (hf.fderivWithin hs In) (hg.of_le (Nat.cast_le.2 (Nat.le_succ n)))
_ ≤ ‖B‖ * ∑ i ∈ Finset.range (n + 1),
n.choose i * ‖iteratedFDerivWithin 𝕜 i (fderivWithin 𝕜 f s) s x‖ *
‖iteratedFDerivWithin 𝕜 (n - i) g s x‖ :=
mul_le_mul_of_nonneg_right (B.norm_precompL_le Du) (by positivity)
_ = _ := by
congr 1
apply Finset.sum_congr rfl fun i _ => ?_
rw [← norm_iteratedFDerivWithin_fderivWithin hs hx]
have J : iteratedFDerivWithin 𝕜 n
(fun y : Du => fderivWithin 𝕜 (fun y : Du => B (f y) (g y)) s y) s x =
iteratedFDerivWithin 𝕜 n (fun y => B.precompR Du (f y)
(fderivWithin 𝕜 g s y) + B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s x := by
apply iteratedFDerivWithin_congr (fun y hy => ?_) hx
have L : (1 : ℕ∞) ≤ n.succ := by
simpa only [ENat.coe_one, Nat.one_le_cast] using Nat.succ_pos n
exact B.fderivWithin_of_bilinear (hf.differentiableOn L y hy) (hg.differentiableOn L y hy)
(hs y hy)
rw [← norm_iteratedFDerivWithin_fderivWithin hs hx, J]
have A : ContDiffOn 𝕜 n (fun y => B.precompR Du (f y) (fderivWithin 𝕜 g s y)) s :=
(B.precompR Du).isBoundedBilinearMap.contDiff.comp_contDiff_on₂
(hf.of_le (Nat.cast_le.2 (Nat.le_succ n))) (hg.fderivWithin hs In)
have A' : ContDiffOn 𝕜 n (fun y => B.precompL Du (fderivWithin 𝕜 f s y) (g y)) s :=
(B.precompL Du).isBoundedBilinearMap.contDiff.comp_contDiff_on₂ (hf.fderivWithin hs In)
(hg.of_le (Nat.cast_le.2 (Nat.le_succ n)))
rw [iteratedFDerivWithin_add_apply' A A' hs hx]
apply (norm_add_le _ _).trans ((add_le_add I1 I2).trans (le_of_eq ?_))
simp_rw [← mul_add, mul_assoc]
congr 1
exact (Finset.sum_choose_succ_mul
(fun i j => ‖iteratedFDerivWithin 𝕜 i f s x‖ * ‖iteratedFDerivWithin 𝕜 j g s x‖) n).symm
|
/-
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, Minchao Wu, Mario Carneiro
-/
import Mathlib.Data.Finset.Attr
import Mathlib.Data.Multiset.FinsetOps
import Mathlib.Logic.Equiv.Set
import Mathlib.Order.Directed
import Mathlib.Order.Interval.Set.Basic
#align_import data.finset.basic from "leanprover-community/mathlib"@"442a83d738cb208d3600056c489be16900ba701d"
/-!
# Finite sets
Terms of type `Finset α` are one way of talking about finite subsets of `α` in mathlib.
Below, `Finset α` is defined as a structure with 2 fields:
1. `val` is a `Multiset α` of elements;
2. `nodup` is a proof that `val` has no duplicates.
Finsets in Lean are constructive in that they have an underlying `List` that enumerates their
elements. In particular, any function that uses the data of the underlying list cannot depend on its
ordering. This is handled on the `Multiset` level by multiset API, so in most cases one needn't
worry about it explicitly.
Finsets give a basic foundation for defining finite sums and products over types:
1. `∑ i ∈ (s : Finset α), f i`;
2. `∏ i ∈ (s : Finset α), f i`.
Lean refers to these operations as big operators.
More information can be found in `Mathlib.Algebra.BigOperators.Group.Finset`.
Finsets are directly used to define fintypes in Lean.
A `Fintype α` instance for a type `α` consists of a universal `Finset α` containing every term of
`α`, called `univ`. See `Mathlib.Data.Fintype.Basic`.
There is also `univ'`, the noncomputable partner to `univ`,
which is defined to be `α` as a finset if `α` is finite,
and the empty finset otherwise. See `Mathlib.Data.Fintype.Basic`.
`Finset.card`, the size of a finset is defined in `Mathlib.Data.Finset.Card`.
This is then used to define `Fintype.card`, the size of a type.
## Main declarations
### Main definitions
* `Finset`: Defines a type for the finite subsets of `α`.
Constructing a `Finset` requires two pieces of data: `val`, a `Multiset α` of elements,
and `nodup`, a proof that `val` has no duplicates.
* `Finset.instMembershipFinset`: Defines membership `a ∈ (s : Finset α)`.
* `Finset.instCoeTCFinsetSet`: Provides a coercion `s : Finset α` to `s : Set α`.
* `Finset.instCoeSortFinsetType`: Coerce `s : Finset α` to the type of all `x ∈ s`.
* `Finset.induction_on`: Induction on finsets. To prove a proposition about an arbitrary `Finset α`,
it suffices to prove it for the empty finset, and to show that if it holds for some `Finset α`,
then it holds for the finset obtained by inserting a new element.
* `Finset.choose`: Given a proof `h` of existence and uniqueness of a certain element
satisfying a predicate, `choose s h` returns the element of `s` satisfying that predicate.
### Finset constructions
* `Finset.instSingletonFinset`: Denoted by `{a}`; the finset consisting of one element.
* `Finset.empty`: Denoted by `∅`. The finset associated to any type consisting of no elements.
* `Finset.range`: For any `n : ℕ`, `range n` is equal to `{0, 1, ... , n - 1} ⊆ ℕ`.
This convention is consistent with other languages and normalizes `card (range n) = n`.
Beware, `n` is not in `range n`.
* `Finset.attach`: Given `s : Finset α`, `attach s` forms a finset of elements of the subtype
`{a // a ∈ s}`; in other words, it attaches elements to a proof of membership in the set.
### Finsets from functions
* `Finset.filter`: Given a decidable predicate `p : α → Prop`, `s.filter p` is
the finset consisting of those elements in `s` satisfying the predicate `p`.
### The lattice structure on subsets of finsets
There is a natural lattice structure on the subsets of a set.
In Lean, we use lattice notation to talk about things involving unions and intersections. See
`Mathlib.Order.Lattice`. For the lattice structure on finsets, `⊥` is called `bot` with `⊥ = ∅` and
`⊤` is called `top` with `⊤ = univ`.
* `Finset.instHasSubsetFinset`: Lots of API about lattices, otherwise behaves as one would expect.
* `Finset.instUnionFinset`: Defines `s ∪ t` (or `s ⊔ t`) as the union of `s` and `t`.
See `Finset.sup`/`Finset.biUnion` for finite unions.
* `Finset.instInterFinset`: Defines `s ∩ t` (or `s ⊓ t`) as the intersection of `s` and `t`.
See `Finset.inf` for finite intersections.
### Operations on two or more finsets
* `insert` and `Finset.cons`: For any `a : α`, `insert s a` returns `s ∪ {a}`. `cons s a h`
returns the same except that it requires a hypothesis stating that `a` is not already in `s`.
This does not require decidable equality on the type `α`.
* `Finset.instUnionFinset`: see "The lattice structure on subsets of finsets"
* `Finset.instInterFinset`: see "The lattice structure on subsets of finsets"
* `Finset.erase`: For any `a : α`, `erase s a` returns `s` with the element `a` removed.
* `Finset.instSDiffFinset`: Defines the set difference `s \ t` for finsets `s` and `t`.
* `Finset.product`: Given finsets of `α` and `β`, defines finsets of `α × β`.
For arbitrary dependent products, see `Mathlib.Data.Finset.Pi`.
### Predicates on finsets
* `Disjoint`: defined via the lattice structure on finsets; two sets are disjoint if their
intersection is empty.
* `Finset.Nonempty`: A finset is nonempty if it has elements. This is equivalent to saying `s ≠ ∅`.
### Equivalences between finsets
* The `Mathlib.Data.Equiv` files describe a general type of equivalence, so look in there for any
lemmas. There is some API for rewriting sums and products from `s` to `t` given that `s ≃ t`.
TODO: examples
## Tags
finite sets, finset
-/
-- Assert that we define `Finset` without the material on `List.sublists`.
-- Note that we cannot use `List.sublists` itself as that is defined very early.
assert_not_exists List.sublistsLen
assert_not_exists Multiset.Powerset
assert_not_exists CompleteLattice
open Multiset Subtype Nat Function
universe u
variable {α : Type*} {β : Type*} {γ : Type*}
/-- `Finset α` is the type of finite sets of elements of `α`. It is implemented
as a multiset (a list up to permutation) which has no duplicate elements. -/
structure Finset (α : Type*) where
/-- The underlying multiset -/
val : Multiset α
/-- `val` contains no duplicates -/
nodup : Nodup val
#align finset Finset
instance Multiset.canLiftFinset {α} : CanLift (Multiset α) (Finset α) Finset.val Multiset.Nodup :=
⟨fun m hm => ⟨⟨m, hm⟩, rfl⟩⟩
#align multiset.can_lift_finset Multiset.canLiftFinset
namespace Finset
theorem eq_of_veq : ∀ {s t : Finset α}, s.1 = t.1 → s = t
| ⟨s, _⟩, ⟨t, _⟩, h => by cases h; rfl
#align finset.eq_of_veq Finset.eq_of_veq
theorem val_injective : Injective (val : Finset α → Multiset α) := fun _ _ => eq_of_veq
#align finset.val_injective Finset.val_injective
@[simp]
theorem val_inj {s t : Finset α} : s.1 = t.1 ↔ s = t :=
val_injective.eq_iff
#align finset.val_inj Finset.val_inj
@[simp]
theorem dedup_eq_self [DecidableEq α] (s : Finset α) : dedup s.1 = s.1 :=
s.2.dedup
#align finset.dedup_eq_self Finset.dedup_eq_self
instance decidableEq [DecidableEq α] : DecidableEq (Finset α)
| _, _ => decidable_of_iff _ val_inj
#align finset.has_decidable_eq Finset.decidableEq
/-! ### membership -/
instance : Membership α (Finset α) :=
⟨fun a s => a ∈ s.1⟩
theorem mem_def {a : α} {s : Finset α} : a ∈ s ↔ a ∈ s.1 :=
Iff.rfl
#align finset.mem_def Finset.mem_def
@[simp]
theorem mem_val {a : α} {s : Finset α} : a ∈ s.1 ↔ a ∈ s :=
Iff.rfl
#align finset.mem_val Finset.mem_val
@[simp]
theorem mem_mk {a : α} {s nd} : a ∈ @Finset.mk α s nd ↔ a ∈ s :=
Iff.rfl
#align finset.mem_mk Finset.mem_mk
instance decidableMem [_h : DecidableEq α] (a : α) (s : Finset α) : Decidable (a ∈ s) :=
Multiset.decidableMem _ _
#align finset.decidable_mem Finset.decidableMem
@[simp] lemma forall_mem_not_eq {s : Finset α} {a : α} : (∀ b ∈ s, ¬ a = b) ↔ a ∉ s := by aesop
@[simp] lemma forall_mem_not_eq' {s : Finset α} {a : α} : (∀ b ∈ s, ¬ b = a) ↔ a ∉ s := by aesop
/-! ### set coercion -/
-- Porting note (#11445): new definition
/-- Convert a finset to a set in the natural way. -/
@[coe] def toSet (s : Finset α) : Set α :=
{ a | a ∈ s }
/-- Convert a finset to a set in the natural way. -/
instance : CoeTC (Finset α) (Set α) :=
⟨toSet⟩
@[simp, norm_cast]
theorem mem_coe {a : α} {s : Finset α} : a ∈ (s : Set α) ↔ a ∈ (s : Finset α) :=
Iff.rfl
#align finset.mem_coe Finset.mem_coe
@[simp]
theorem setOf_mem {α} {s : Finset α} : { a | a ∈ s } = s :=
rfl
#align finset.set_of_mem Finset.setOf_mem
@[simp]
theorem coe_mem {s : Finset α} (x : (s : Set α)) : ↑x ∈ s :=
x.2
#align finset.coe_mem Finset.coe_mem
-- Porting note (#10618): @[simp] can prove this
theorem mk_coe {s : Finset α} (x : (s : Set α)) {h} : (⟨x, h⟩ : (s : Set α)) = x :=
Subtype.coe_eta _ _
#align finset.mk_coe Finset.mk_coe
instance decidableMem' [DecidableEq α] (a : α) (s : Finset α) : Decidable (a ∈ (s : Set α)) :=
s.decidableMem _
#align finset.decidable_mem' Finset.decidableMem'
/-! ### extensionality -/
theorem ext_iff {s₁ s₂ : Finset α} : s₁ = s₂ ↔ ∀ a, a ∈ s₁ ↔ a ∈ s₂ :=
val_inj.symm.trans <| s₁.nodup.ext s₂.nodup
#align finset.ext_iff Finset.ext_iff
@[ext]
theorem ext {s₁ s₂ : Finset α} : (∀ a, a ∈ s₁ ↔ a ∈ s₂) → s₁ = s₂ :=
ext_iff.2
#align finset.ext Finset.ext
@[simp, norm_cast]
theorem coe_inj {s₁ s₂ : Finset α} : (s₁ : Set α) = s₂ ↔ s₁ = s₂ :=
Set.ext_iff.trans ext_iff.symm
#align finset.coe_inj Finset.coe_inj
theorem coe_injective {α} : Injective ((↑) : Finset α → Set α) := fun _s _t => coe_inj.1
#align finset.coe_injective Finset.coe_injective
/-! ### type coercion -/
/-- Coercion from a finset to the corresponding subtype. -/
instance {α : Type u} : CoeSort (Finset α) (Type u) :=
⟨fun s => { x // x ∈ s }⟩
-- Porting note (#10618): @[simp] can prove this
protected theorem forall_coe {α : Type*} (s : Finset α) (p : s → Prop) :
(∀ x : s, p x) ↔ ∀ (x : α) (h : x ∈ s), p ⟨x, h⟩ :=
Subtype.forall
#align finset.forall_coe Finset.forall_coe
-- Porting note (#10618): @[simp] can prove this
protected theorem exists_coe {α : Type*} (s : Finset α) (p : s → Prop) :
(∃ x : s, p x) ↔ ∃ (x : α) (h : x ∈ s), p ⟨x, h⟩ :=
Subtype.exists
#align finset.exists_coe Finset.exists_coe
instance PiFinsetCoe.canLift (ι : Type*) (α : ι → Type*) [_ne : ∀ i, Nonempty (α i)]
(s : Finset ι) : CanLift (∀ i : s, α i) (∀ i, α i) (fun f i => f i) fun _ => True :=
PiSubtype.canLift ι α (· ∈ s)
#align finset.pi_finset_coe.can_lift Finset.PiFinsetCoe.canLift
instance PiFinsetCoe.canLift' (ι α : Type*) [_ne : Nonempty α] (s : Finset ι) :
CanLift (s → α) (ι → α) (fun f i => f i) fun _ => True :=
PiFinsetCoe.canLift ι (fun _ => α) s
#align finset.pi_finset_coe.can_lift' Finset.PiFinsetCoe.canLift'
instance FinsetCoe.canLift (s : Finset α) : CanLift α s (↑) fun a => a ∈ s where
prf a ha := ⟨⟨a, ha⟩, rfl⟩
#align finset.finset_coe.can_lift Finset.FinsetCoe.canLift
@[simp, norm_cast]
theorem coe_sort_coe (s : Finset α) : ((s : Set α) : Sort _) = s :=
rfl
#align finset.coe_sort_coe Finset.coe_sort_coe
/-! ### Subset and strict subset relations -/
section Subset
variable {s t : Finset α}
instance : HasSubset (Finset α) :=
⟨fun s t => ∀ ⦃a⦄, a ∈ s → a ∈ t⟩
instance : HasSSubset (Finset α) :=
⟨fun s t => s ⊆ t ∧ ¬t ⊆ s⟩
instance partialOrder : PartialOrder (Finset α) where
le := (· ⊆ ·)
lt := (· ⊂ ·)
le_refl s a := id
le_trans s t u hst htu a ha := htu <| hst ha
le_antisymm s t hst hts := ext fun a => ⟨@hst _, @hts _⟩
instance : IsRefl (Finset α) (· ⊆ ·) :=
show IsRefl (Finset α) (· ≤ ·) by infer_instance
instance : IsTrans (Finset α) (· ⊆ ·) :=
show IsTrans (Finset α) (· ≤ ·) by infer_instance
instance : IsAntisymm (Finset α) (· ⊆ ·) :=
show IsAntisymm (Finset α) (· ≤ ·) by infer_instance
instance : IsIrrefl (Finset α) (· ⊂ ·) :=
show IsIrrefl (Finset α) (· < ·) by infer_instance
instance : IsTrans (Finset α) (· ⊂ ·) :=
show IsTrans (Finset α) (· < ·) by infer_instance
instance : IsAsymm (Finset α) (· ⊂ ·) :=
show IsAsymm (Finset α) (· < ·) by infer_instance
instance : IsNonstrictStrictOrder (Finset α) (· ⊆ ·) (· ⊂ ·) :=
⟨fun _ _ => Iff.rfl⟩
theorem subset_def : s ⊆ t ↔ s.1 ⊆ t.1 :=
Iff.rfl
#align finset.subset_def Finset.subset_def
theorem ssubset_def : s ⊂ t ↔ s ⊆ t ∧ ¬t ⊆ s :=
Iff.rfl
#align finset.ssubset_def Finset.ssubset_def
@[simp]
theorem Subset.refl (s : Finset α) : s ⊆ s :=
Multiset.Subset.refl _
#align finset.subset.refl Finset.Subset.refl
protected theorem Subset.rfl {s : Finset α} : s ⊆ s :=
Subset.refl _
#align finset.subset.rfl Finset.Subset.rfl
protected theorem subset_of_eq {s t : Finset α} (h : s = t) : s ⊆ t :=
h ▸ Subset.refl _
#align finset.subset_of_eq Finset.subset_of_eq
theorem Subset.trans {s₁ s₂ s₃ : Finset α} : s₁ ⊆ s₂ → s₂ ⊆ s₃ → s₁ ⊆ s₃ :=
Multiset.Subset.trans
#align finset.subset.trans Finset.Subset.trans
theorem Superset.trans {s₁ s₂ s₃ : Finset α} : s₁ ⊇ s₂ → s₂ ⊇ s₃ → s₁ ⊇ s₃ := fun h' h =>
Subset.trans h h'
#align finset.superset.trans Finset.Superset.trans
theorem mem_of_subset {s₁ s₂ : Finset α} {a : α} : s₁ ⊆ s₂ → a ∈ s₁ → a ∈ s₂ :=
Multiset.mem_of_subset
#align finset.mem_of_subset Finset.mem_of_subset
theorem not_mem_mono {s t : Finset α} (h : s ⊆ t) {a : α} : a ∉ t → a ∉ s :=
mt <| @h _
#align finset.not_mem_mono Finset.not_mem_mono
theorem Subset.antisymm {s₁ s₂ : Finset α} (H₁ : s₁ ⊆ s₂) (H₂ : s₂ ⊆ s₁) : s₁ = s₂ :=
ext fun a => ⟨@H₁ a, @H₂ a⟩
#align finset.subset.antisymm Finset.Subset.antisymm
theorem subset_iff {s₁ s₂ : Finset α} : s₁ ⊆ s₂ ↔ ∀ ⦃x⦄, x ∈ s₁ → x ∈ s₂ :=
Iff.rfl
#align finset.subset_iff Finset.subset_iff
@[simp, norm_cast]
theorem coe_subset {s₁ s₂ : Finset α} : (s₁ : Set α) ⊆ s₂ ↔ s₁ ⊆ s₂ :=
Iff.rfl
#align finset.coe_subset Finset.coe_subset
@[simp]
theorem val_le_iff {s₁ s₂ : Finset α} : s₁.1 ≤ s₂.1 ↔ s₁ ⊆ s₂ :=
le_iff_subset s₁.2
#align finset.val_le_iff Finset.val_le_iff
theorem Subset.antisymm_iff {s₁ s₂ : Finset α} : s₁ = s₂ ↔ s₁ ⊆ s₂ ∧ s₂ ⊆ s₁ :=
le_antisymm_iff
#align finset.subset.antisymm_iff Finset.Subset.antisymm_iff
theorem not_subset : ¬s ⊆ t ↔ ∃ x ∈ s, x ∉ t := by simp only [← coe_subset, Set.not_subset, mem_coe]
#align finset.not_subset Finset.not_subset
@[simp]
theorem le_eq_subset : ((· ≤ ·) : Finset α → Finset α → Prop) = (· ⊆ ·) :=
rfl
#align finset.le_eq_subset Finset.le_eq_subset
@[simp]
theorem lt_eq_subset : ((· < ·) : Finset α → Finset α → Prop) = (· ⊂ ·) :=
rfl
#align finset.lt_eq_subset Finset.lt_eq_subset
theorem le_iff_subset {s₁ s₂ : Finset α} : s₁ ≤ s₂ ↔ s₁ ⊆ s₂ :=
Iff.rfl
#align finset.le_iff_subset Finset.le_iff_subset
theorem lt_iff_ssubset {s₁ s₂ : Finset α} : s₁ < s₂ ↔ s₁ ⊂ s₂ :=
Iff.rfl
#align finset.lt_iff_ssubset Finset.lt_iff_ssubset
@[simp, norm_cast]
theorem coe_ssubset {s₁ s₂ : Finset α} : (s₁ : Set α) ⊂ s₂ ↔ s₁ ⊂ s₂ :=
show (s₁ : Set α) ⊂ s₂ ↔ s₁ ⊆ s₂ ∧ ¬s₂ ⊆ s₁ by simp only [Set.ssubset_def, Finset.coe_subset]
#align finset.coe_ssubset Finset.coe_ssubset
@[simp]
theorem val_lt_iff {s₁ s₂ : Finset α} : s₁.1 < s₂.1 ↔ s₁ ⊂ s₂ :=
and_congr val_le_iff <| not_congr val_le_iff
#align finset.val_lt_iff Finset.val_lt_iff
lemma val_strictMono : StrictMono (val : Finset α → Multiset α) := fun _ _ ↦ val_lt_iff.2
theorem ssubset_iff_subset_ne {s t : Finset α} : s ⊂ t ↔ s ⊆ t ∧ s ≠ t :=
@lt_iff_le_and_ne _ _ s t
#align finset.ssubset_iff_subset_ne Finset.ssubset_iff_subset_ne
theorem ssubset_iff_of_subset {s₁ s₂ : Finset α} (h : s₁ ⊆ s₂) : s₁ ⊂ s₂ ↔ ∃ x ∈ s₂, x ∉ s₁ :=
Set.ssubset_iff_of_subset h
#align finset.ssubset_iff_of_subset Finset.ssubset_iff_of_subset
theorem ssubset_of_ssubset_of_subset {s₁ s₂ s₃ : Finset α} (hs₁s₂ : s₁ ⊂ s₂) (hs₂s₃ : s₂ ⊆ s₃) :
s₁ ⊂ s₃ :=
Set.ssubset_of_ssubset_of_subset hs₁s₂ hs₂s₃
#align finset.ssubset_of_ssubset_of_subset Finset.ssubset_of_ssubset_of_subset
theorem ssubset_of_subset_of_ssubset {s₁ s₂ s₃ : Finset α} (hs₁s₂ : s₁ ⊆ s₂) (hs₂s₃ : s₂ ⊂ s₃) :
s₁ ⊂ s₃ :=
Set.ssubset_of_subset_of_ssubset hs₁s₂ hs₂s₃
#align finset.ssubset_of_subset_of_ssubset Finset.ssubset_of_subset_of_ssubset
theorem exists_of_ssubset {s₁ s₂ : Finset α} (h : s₁ ⊂ s₂) : ∃ x ∈ s₂, x ∉ s₁ :=
Set.exists_of_ssubset h
#align finset.exists_of_ssubset Finset.exists_of_ssubset
instance isWellFounded_ssubset : IsWellFounded (Finset α) (· ⊂ ·) :=
Subrelation.isWellFounded (InvImage _ _) val_lt_iff.2
#align finset.is_well_founded_ssubset Finset.isWellFounded_ssubset
instance wellFoundedLT : WellFoundedLT (Finset α) :=
Finset.isWellFounded_ssubset
#align finset.is_well_founded_lt Finset.wellFoundedLT
end Subset
-- TODO: these should be global attributes, but this will require fixing other files
attribute [local trans] Subset.trans Superset.trans
/-! ### Order embedding from `Finset α` to `Set α` -/
/-- Coercion to `Set α` as an `OrderEmbedding`. -/
def coeEmb : Finset α ↪o Set α :=
⟨⟨(↑), coe_injective⟩, coe_subset⟩
#align finset.coe_emb Finset.coeEmb
@[simp]
theorem coe_coeEmb : ⇑(coeEmb : Finset α ↪o Set α) = ((↑) : Finset α → Set α) :=
rfl
#align finset.coe_coe_emb Finset.coe_coeEmb
/-! ### Nonempty -/
/-- The property `s.Nonempty` expresses the fact that the finset `s` is not empty. It should be used
in theorem assumptions instead of `∃ x, x ∈ s` or `s ≠ ∅` as it gives access to a nice API thanks
to the dot notation. -/
protected def Nonempty (s : Finset α) : Prop := ∃ x : α, x ∈ s
#align finset.nonempty Finset.Nonempty
-- Porting note: Much longer than in Lean3
instance decidableNonempty {s : Finset α} : Decidable s.Nonempty :=
Quotient.recOnSubsingleton (motive := fun s : Multiset α => Decidable (∃ a, a ∈ s)) s.1
(fun l : List α =>
match l with
| [] => isFalse <| by simp
| a::l => isTrue ⟨a, by simp⟩)
#align finset.decidable_nonempty Finset.decidableNonempty
@[simp, norm_cast]
theorem coe_nonempty {s : Finset α} : (s : Set α).Nonempty ↔ s.Nonempty :=
Iff.rfl
#align finset.coe_nonempty Finset.coe_nonempty
-- Porting note: Left-hand side simplifies @[simp]
theorem nonempty_coe_sort {s : Finset α} : Nonempty (s : Type _) ↔ s.Nonempty :=
nonempty_subtype
#align finset.nonempty_coe_sort Finset.nonempty_coe_sort
alias ⟨_, Nonempty.to_set⟩ := coe_nonempty
#align finset.nonempty.to_set Finset.Nonempty.to_set
alias ⟨_, Nonempty.coe_sort⟩ := nonempty_coe_sort
#align finset.nonempty.coe_sort Finset.Nonempty.coe_sort
theorem Nonempty.exists_mem {s : Finset α} (h : s.Nonempty) : ∃ x : α, x ∈ s :=
h
#align finset.nonempty.bex Finset.Nonempty.exists_mem
@[deprecated (since := "2024-03-23")] alias Nonempty.bex := Nonempty.exists_mem
theorem Nonempty.mono {s t : Finset α} (hst : s ⊆ t) (hs : s.Nonempty) : t.Nonempty :=
Set.Nonempty.mono hst hs
#align finset.nonempty.mono Finset.Nonempty.mono
theorem Nonempty.forall_const {s : Finset α} (h : s.Nonempty) {p : Prop} : (∀ x ∈ s, p) ↔ p :=
let ⟨x, hx⟩ := h
⟨fun h => h x hx, fun h _ _ => h⟩
#align finset.nonempty.forall_const Finset.Nonempty.forall_const
theorem Nonempty.to_subtype {s : Finset α} : s.Nonempty → Nonempty s :=
nonempty_coe_sort.2
#align finset.nonempty.to_subtype Finset.Nonempty.to_subtype
theorem Nonempty.to_type {s : Finset α} : s.Nonempty → Nonempty α := fun ⟨x, _hx⟩ => ⟨x⟩
#align finset.nonempty.to_type Finset.Nonempty.to_type
/-! ### empty -/
section Empty
variable {s : Finset α}
/-- The empty finset -/
protected def empty : Finset α :=
⟨0, nodup_zero⟩
#align finset.empty Finset.empty
instance : EmptyCollection (Finset α) :=
⟨Finset.empty⟩
instance inhabitedFinset : Inhabited (Finset α) :=
⟨∅⟩
#align finset.inhabited_finset Finset.inhabitedFinset
@[simp]
theorem empty_val : (∅ : Finset α).1 = 0 :=
rfl
#align finset.empty_val Finset.empty_val
@[simp]
theorem not_mem_empty (a : α) : a ∉ (∅ : Finset α) := by
-- Porting note: was `id`. `a ∈ List.nil` is no longer definitionally equal to `False`
simp only [mem_def, empty_val, not_mem_zero, not_false_iff]
#align finset.not_mem_empty Finset.not_mem_empty
@[simp]
theorem not_nonempty_empty : ¬(∅ : Finset α).Nonempty := fun ⟨x, hx⟩ => not_mem_empty x hx
#align finset.not_nonempty_empty Finset.not_nonempty_empty
@[simp]
theorem mk_zero : (⟨0, nodup_zero⟩ : Finset α) = ∅ :=
rfl
#align finset.mk_zero Finset.mk_zero
theorem ne_empty_of_mem {a : α} {s : Finset α} (h : a ∈ s) : s ≠ ∅ := fun e =>
not_mem_empty a <| e ▸ h
#align finset.ne_empty_of_mem Finset.ne_empty_of_mem
theorem Nonempty.ne_empty {s : Finset α} (h : s.Nonempty) : s ≠ ∅ :=
(Exists.elim h) fun _a => ne_empty_of_mem
#align finset.nonempty.ne_empty Finset.Nonempty.ne_empty
@[simp]
theorem empty_subset (s : Finset α) : ∅ ⊆ s :=
zero_subset _
#align finset.empty_subset Finset.empty_subset
theorem eq_empty_of_forall_not_mem {s : Finset α} (H : ∀ x, x ∉ s) : s = ∅ :=
eq_of_veq (eq_zero_of_forall_not_mem H)
#align finset.eq_empty_of_forall_not_mem Finset.eq_empty_of_forall_not_mem
theorem eq_empty_iff_forall_not_mem {s : Finset α} : s = ∅ ↔ ∀ x, x ∉ s :=
-- Porting note: used `id`
⟨by rintro rfl x; apply not_mem_empty, fun h => eq_empty_of_forall_not_mem h⟩
#align finset.eq_empty_iff_forall_not_mem Finset.eq_empty_iff_forall_not_mem
@[simp]
theorem val_eq_zero {s : Finset α} : s.1 = 0 ↔ s = ∅ :=
@val_inj _ s ∅
#align finset.val_eq_zero Finset.val_eq_zero
theorem subset_empty {s : Finset α} : s ⊆ ∅ ↔ s = ∅ :=
subset_zero.trans val_eq_zero
#align finset.subset_empty Finset.subset_empty
@[simp]
theorem not_ssubset_empty (s : Finset α) : ¬s ⊂ ∅ := fun h =>
let ⟨_, he, _⟩ := exists_of_ssubset h
-- Porting note: was `he`
not_mem_empty _ he
#align finset.not_ssubset_empty Finset.not_ssubset_empty
theorem nonempty_of_ne_empty {s : Finset α} (h : s ≠ ∅) : s.Nonempty :=
exists_mem_of_ne_zero (mt val_eq_zero.1 h)
#align finset.nonempty_of_ne_empty Finset.nonempty_of_ne_empty
theorem nonempty_iff_ne_empty {s : Finset α} : s.Nonempty ↔ s ≠ ∅ :=
⟨Nonempty.ne_empty, nonempty_of_ne_empty⟩
#align finset.nonempty_iff_ne_empty Finset.nonempty_iff_ne_empty
@[simp]
theorem not_nonempty_iff_eq_empty {s : Finset α} : ¬s.Nonempty ↔ s = ∅ :=
nonempty_iff_ne_empty.not.trans not_not
#align finset.not_nonempty_iff_eq_empty Finset.not_nonempty_iff_eq_empty
theorem eq_empty_or_nonempty (s : Finset α) : s = ∅ ∨ s.Nonempty :=
by_cases Or.inl fun h => Or.inr (nonempty_of_ne_empty h)
#align finset.eq_empty_or_nonempty Finset.eq_empty_or_nonempty
@[simp, norm_cast]
theorem coe_empty : ((∅ : Finset α) : Set α) = ∅ :=
Set.ext <| by simp
#align finset.coe_empty Finset.coe_empty
@[simp, norm_cast]
theorem coe_eq_empty {s : Finset α} : (s : Set α) = ∅ ↔ s = ∅ := by rw [← coe_empty, coe_inj]
#align finset.coe_eq_empty Finset.coe_eq_empty
-- Porting note: Left-hand side simplifies @[simp]
theorem isEmpty_coe_sort {s : Finset α} : IsEmpty (s : Type _) ↔ s = ∅ := by
simpa using @Set.isEmpty_coe_sort α s
#align finset.is_empty_coe_sort Finset.isEmpty_coe_sort
instance instIsEmpty : IsEmpty (∅ : Finset α) :=
isEmpty_coe_sort.2 rfl
/-- A `Finset` for an empty type is empty. -/
theorem eq_empty_of_isEmpty [IsEmpty α] (s : Finset α) : s = ∅ :=
Finset.eq_empty_of_forall_not_mem isEmptyElim
#align finset.eq_empty_of_is_empty Finset.eq_empty_of_isEmpty
instance : OrderBot (Finset α) where
bot := ∅
bot_le := empty_subset
@[simp]
theorem bot_eq_empty : (⊥ : Finset α) = ∅ :=
rfl
#align finset.bot_eq_empty Finset.bot_eq_empty
@[simp]
theorem empty_ssubset : ∅ ⊂ s ↔ s.Nonempty :=
(@bot_lt_iff_ne_bot (Finset α) _ _ _).trans nonempty_iff_ne_empty.symm
#align finset.empty_ssubset Finset.empty_ssubset
alias ⟨_, Nonempty.empty_ssubset⟩ := empty_ssubset
#align finset.nonempty.empty_ssubset Finset.Nonempty.empty_ssubset
end Empty
/-! ### singleton -/
section Singleton
variable {s : Finset α} {a b : α}
/-- `{a} : Finset a` is the set `{a}` containing `a` and nothing else.
This differs from `insert a ∅` in that it does not require a `DecidableEq` instance for `α`.
-/
instance : Singleton α (Finset α) :=
⟨fun a => ⟨{a}, nodup_singleton a⟩⟩
@[simp]
theorem singleton_val (a : α) : ({a} : Finset α).1 = {a} :=
rfl
#align finset.singleton_val Finset.singleton_val
@[simp]
theorem mem_singleton {a b : α} : b ∈ ({a} : Finset α) ↔ b = a :=
Multiset.mem_singleton
#align finset.mem_singleton Finset.mem_singleton
theorem eq_of_mem_singleton {x y : α} (h : x ∈ ({y} : Finset α)) : x = y :=
mem_singleton.1 h
#align finset.eq_of_mem_singleton Finset.eq_of_mem_singleton
theorem not_mem_singleton {a b : α} : a ∉ ({b} : Finset α) ↔ a ≠ b :=
not_congr mem_singleton
#align finset.not_mem_singleton Finset.not_mem_singleton
theorem mem_singleton_self (a : α) : a ∈ ({a} : Finset α) :=
-- Porting note: was `Or.inl rfl`
mem_singleton.mpr rfl
#align finset.mem_singleton_self Finset.mem_singleton_self
@[simp]
theorem val_eq_singleton_iff {a : α} {s : Finset α} : s.val = {a} ↔ s = {a} := by
rw [← val_inj]
rfl
#align finset.val_eq_singleton_iff Finset.val_eq_singleton_iff
theorem singleton_injective : Injective (singleton : α → Finset α) := fun _a _b h =>
mem_singleton.1 (h ▸ mem_singleton_self _)
#align finset.singleton_injective Finset.singleton_injective
@[simp]
theorem singleton_inj : ({a} : Finset α) = {b} ↔ a = b :=
singleton_injective.eq_iff
#align finset.singleton_inj Finset.singleton_inj
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem singleton_nonempty (a : α) : ({a} : Finset α).Nonempty :=
⟨a, mem_singleton_self a⟩
#align finset.singleton_nonempty Finset.singleton_nonempty
@[simp]
theorem singleton_ne_empty (a : α) : ({a} : Finset α) ≠ ∅ :=
(singleton_nonempty a).ne_empty
#align finset.singleton_ne_empty Finset.singleton_ne_empty
theorem empty_ssubset_singleton : (∅ : Finset α) ⊂ {a} :=
(singleton_nonempty _).empty_ssubset
#align finset.empty_ssubset_singleton Finset.empty_ssubset_singleton
@[simp, norm_cast]
theorem coe_singleton (a : α) : (({a} : Finset α) : Set α) = {a} := by
ext
simp
#align finset.coe_singleton Finset.coe_singleton
@[simp, norm_cast]
theorem coe_eq_singleton {s : Finset α} {a : α} : (s : Set α) = {a} ↔ s = {a} := by
rw [← coe_singleton, coe_inj]
#align finset.coe_eq_singleton Finset.coe_eq_singleton
@[norm_cast]
lemma coe_subset_singleton : (s : Set α) ⊆ {a} ↔ s ⊆ {a} := by rw [← coe_subset, coe_singleton]
@[norm_cast]
lemma singleton_subset_coe : {a} ⊆ (s : Set α) ↔ {a} ⊆ s := by rw [← coe_subset, coe_singleton]
theorem eq_singleton_iff_unique_mem {s : Finset α} {a : α} : s = {a} ↔ a ∈ s ∧ ∀ x ∈ s, x = a := by
constructor <;> intro t
· rw [t]
exact ⟨Finset.mem_singleton_self _, fun _ => Finset.mem_singleton.1⟩
· ext
rw [Finset.mem_singleton]
exact ⟨t.right _, fun r => r.symm ▸ t.left⟩
#align finset.eq_singleton_iff_unique_mem Finset.eq_singleton_iff_unique_mem
theorem eq_singleton_iff_nonempty_unique_mem {s : Finset α} {a : α} :
s = {a} ↔ s.Nonempty ∧ ∀ x ∈ s, x = a := by
constructor
· rintro rfl
simp
· rintro ⟨hne, h_uniq⟩
rw [eq_singleton_iff_unique_mem]
refine ⟨?_, h_uniq⟩
rw [← h_uniq hne.choose hne.choose_spec]
exact hne.choose_spec
#align finset.eq_singleton_iff_nonempty_unique_mem Finset.eq_singleton_iff_nonempty_unique_mem
theorem nonempty_iff_eq_singleton_default [Unique α] {s : Finset α} :
s.Nonempty ↔ s = {default} := by
simp [eq_singleton_iff_nonempty_unique_mem, eq_iff_true_of_subsingleton]
#align finset.nonempty_iff_eq_singleton_default Finset.nonempty_iff_eq_singleton_default
alias ⟨Nonempty.eq_singleton_default, _⟩ := nonempty_iff_eq_singleton_default
#align finset.nonempty.eq_singleton_default Finset.Nonempty.eq_singleton_default
theorem singleton_iff_unique_mem (s : Finset α) : (∃ a, s = {a}) ↔ ∃! a, a ∈ s := by
simp only [eq_singleton_iff_unique_mem, ExistsUnique]
#align finset.singleton_iff_unique_mem Finset.singleton_iff_unique_mem
theorem singleton_subset_set_iff {s : Set α} {a : α} : ↑({a} : Finset α) ⊆ s ↔ a ∈ s := by
rw [coe_singleton, Set.singleton_subset_iff]
#align finset.singleton_subset_set_iff Finset.singleton_subset_set_iff
@[simp]
theorem singleton_subset_iff {s : Finset α} {a : α} : {a} ⊆ s ↔ a ∈ s :=
singleton_subset_set_iff
#align finset.singleton_subset_iff Finset.singleton_subset_iff
@[simp]
theorem subset_singleton_iff {s : Finset α} {a : α} : s ⊆ {a} ↔ s = ∅ ∨ s = {a} := by
rw [← coe_subset, coe_singleton, Set.subset_singleton_iff_eq, coe_eq_empty, coe_eq_singleton]
#align finset.subset_singleton_iff Finset.subset_singleton_iff
theorem singleton_subset_singleton : ({a} : Finset α) ⊆ {b} ↔ a = b := by simp
#align finset.singleton_subset_singleton Finset.singleton_subset_singleton
protected theorem Nonempty.subset_singleton_iff {s : Finset α} {a : α} (h : s.Nonempty) :
s ⊆ {a} ↔ s = {a} :=
subset_singleton_iff.trans <| or_iff_right h.ne_empty
#align finset.nonempty.subset_singleton_iff Finset.Nonempty.subset_singleton_iff
theorem subset_singleton_iff' {s : Finset α} {a : α} : s ⊆ {a} ↔ ∀ b ∈ s, b = a :=
forall₂_congr fun _ _ => mem_singleton
#align finset.subset_singleton_iff' Finset.subset_singleton_iff'
@[simp]
| Mathlib/Data/Finset/Basic.lean | 803 | 804 | theorem ssubset_singleton_iff {s : Finset α} {a : α} : s ⊂ {a} ↔ s = ∅ := by |
rw [← coe_ssubset, coe_singleton, Set.ssubset_singleton_iff, coe_eq_empty]
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Floris van Doorn
-/
import Mathlib.Algebra.Star.Basic
import Mathlib.Algebra.Order.CauSeq.Completion
#align_import data.real.basic from "leanprover-community/mathlib"@"cb42593171ba005beaaf4549fcfe0dece9ada4c9"
/-!
# Real numbers from Cauchy sequences
This file defines `ℝ` as the type of equivalence classes of Cauchy sequences of rational numbers.
This choice is motivated by how easy it is to prove that `ℝ` is a commutative ring, by simply
lifting everything to `ℚ`.
The facts that the real numbers are an Archimedean floor ring,
and a conditionally complete linear order,
have been deferred to the file `Mathlib/Data/Real/Archimedean.lean`,
in order to keep the imports here simple.
-/
assert_not_exists Finset
assert_not_exists Module
assert_not_exists Submonoid
assert_not_exists FloorRing
/-- The type `ℝ` of real numbers constructed as equivalence classes of Cauchy sequences of rational
numbers. -/
structure Real where ofCauchy ::
/-- The underlying Cauchy completion -/
cauchy : CauSeq.Completion.Cauchy (abs : ℚ → ℚ)
#align real Real
@[inherit_doc]
notation "ℝ" => Real
-- Porting note: unknown attribute
-- attribute [pp_using_anonymous_constructor] Real
namespace CauSeq.Completion
-- this can't go in `Data.Real.CauSeqCompletion` as the structure on `ℚ` isn't available
@[simp]
theorem ofRat_rat {abv : ℚ → ℚ} [IsAbsoluteValue abv] (q : ℚ) :
ofRat (q : ℚ) = (q : Cauchy abv) :=
rfl
#align cau_seq.completion.of_rat_rat CauSeq.Completion.ofRat_rat
end CauSeq.Completion
namespace Real
open CauSeq CauSeq.Completion
variable {x y : ℝ}
theorem ext_cauchy_iff : ∀ {x y : Real}, x = y ↔ x.cauchy = y.cauchy
| ⟨a⟩, ⟨b⟩ => by rw [ofCauchy.injEq]
#align real.ext_cauchy_iff Real.ext_cauchy_iff
theorem ext_cauchy {x y : Real} : x.cauchy = y.cauchy → x = y :=
ext_cauchy_iff.2
#align real.ext_cauchy Real.ext_cauchy
/-- The real numbers are isomorphic to the quotient of Cauchy sequences on the rationals. -/
def equivCauchy : ℝ ≃ CauSeq.Completion.Cauchy (abs : ℚ → ℚ) :=
⟨Real.cauchy, Real.ofCauchy, fun ⟨_⟩ => rfl, fun _ => rfl⟩
set_option linter.uppercaseLean3 false in
#align real.equiv_Cauchy Real.equivCauchy
-- irreducible doesn't work for instances: https://github.com/leanprover-community/lean/issues/511
private irreducible_def zero : ℝ :=
⟨0⟩
private irreducible_def one : ℝ :=
⟨1⟩
private irreducible_def add : ℝ → ℝ → ℝ
| ⟨a⟩, ⟨b⟩ => ⟨a + b⟩
private irreducible_def neg : ℝ → ℝ
| ⟨a⟩ => ⟨-a⟩
private irreducible_def mul : ℝ → ℝ → ℝ
| ⟨a⟩, ⟨b⟩ => ⟨a * b⟩
private noncomputable irreducible_def inv' : ℝ → ℝ
| ⟨a⟩ => ⟨a⁻¹⟩
instance : Zero ℝ :=
⟨zero⟩
instance : One ℝ :=
⟨one⟩
instance : Add ℝ :=
⟨add⟩
instance : Neg ℝ :=
⟨neg⟩
instance : Mul ℝ :=
⟨mul⟩
instance : Sub ℝ :=
⟨fun a b => a + -b⟩
noncomputable instance : Inv ℝ :=
⟨inv'⟩
theorem ofCauchy_zero : (⟨0⟩ : ℝ) = 0 :=
zero_def.symm
#align real.of_cauchy_zero Real.ofCauchy_zero
theorem ofCauchy_one : (⟨1⟩ : ℝ) = 1 :=
one_def.symm
#align real.of_cauchy_one Real.ofCauchy_one
theorem ofCauchy_add (a b) : (⟨a + b⟩ : ℝ) = ⟨a⟩ + ⟨b⟩ :=
(add_def _ _).symm
#align real.of_cauchy_add Real.ofCauchy_add
theorem ofCauchy_neg (a) : (⟨-a⟩ : ℝ) = -⟨a⟩ :=
(neg_def _).symm
#align real.of_cauchy_neg Real.ofCauchy_neg
theorem ofCauchy_sub (a b) : (⟨a - b⟩ : ℝ) = ⟨a⟩ - ⟨b⟩ := by
rw [sub_eq_add_neg, ofCauchy_add, ofCauchy_neg]
rfl
#align real.of_cauchy_sub Real.ofCauchy_sub
theorem ofCauchy_mul (a b) : (⟨a * b⟩ : ℝ) = ⟨a⟩ * ⟨b⟩ :=
(mul_def _ _).symm
#align real.of_cauchy_mul Real.ofCauchy_mul
theorem ofCauchy_inv {f} : (⟨f⁻¹⟩ : ℝ) = ⟨f⟩⁻¹ :=
show _ = inv' _ by rw [inv']
#align real.of_cauchy_inv Real.ofCauchy_inv
theorem cauchy_zero : (0 : ℝ).cauchy = 0 :=
show zero.cauchy = 0 by rw [zero_def]
#align real.cauchy_zero Real.cauchy_zero
theorem cauchy_one : (1 : ℝ).cauchy = 1 :=
show one.cauchy = 1 by rw [one_def]
#align real.cauchy_one Real.cauchy_one
theorem cauchy_add : ∀ a b, (a + b : ℝ).cauchy = a.cauchy + b.cauchy
| ⟨a⟩, ⟨b⟩ => show (add _ _).cauchy = _ by rw [add_def]
#align real.cauchy_add Real.cauchy_add
theorem cauchy_neg : ∀ a, (-a : ℝ).cauchy = -a.cauchy
| ⟨a⟩ => show (neg _).cauchy = _ by rw [neg_def]
#align real.cauchy_neg Real.cauchy_neg
theorem cauchy_mul : ∀ a b, (a * b : ℝ).cauchy = a.cauchy * b.cauchy
| ⟨a⟩, ⟨b⟩ => show (mul _ _).cauchy = _ by rw [mul_def]
#align real.cauchy_mul Real.cauchy_mul
theorem cauchy_sub : ∀ a b, (a - b : ℝ).cauchy = a.cauchy - b.cauchy
| ⟨a⟩, ⟨b⟩ => by
rw [sub_eq_add_neg, ← cauchy_neg, ← cauchy_add]
rfl
#align real.cauchy_sub Real.cauchy_sub
theorem cauchy_inv : ∀ f, (f⁻¹ : ℝ).cauchy = f.cauchy⁻¹
| ⟨f⟩ => show (inv' _).cauchy = _ by rw [inv']
#align real.cauchy_inv Real.cauchy_inv
instance instNatCast : NatCast ℝ where natCast n := ⟨n⟩
instance instIntCast : IntCast ℝ where intCast z := ⟨z⟩
instance instNNRatCast : NNRatCast ℝ where nnratCast q := ⟨q⟩
instance instRatCast : RatCast ℝ where ratCast q := ⟨q⟩
lemma ofCauchy_natCast (n : ℕ) : (⟨n⟩ : ℝ) = n := rfl
lemma ofCauchy_intCast (z : ℤ) : (⟨z⟩ : ℝ) = z := rfl
lemma ofCauchy_nnratCast (q : ℚ≥0) : (⟨q⟩ : ℝ) = q := rfl
lemma ofCauchy_ratCast (q : ℚ) : (⟨q⟩ : ℝ) = q := rfl
#align real.of_cauchy_nat_cast Real.ofCauchy_natCast
#align real.of_cauchy_int_cast Real.ofCauchy_intCast
#align real.of_cauchy_rat_cast Real.ofCauchy_ratCast
lemma cauchy_natCast (n : ℕ) : (n : ℝ).cauchy = n := rfl
lemma cauchy_intCast (z : ℤ) : (z : ℝ).cauchy = z := rfl
lemma cauchy_nnratCast (q : ℚ≥0) : (q : ℝ).cauchy = q := rfl
lemma cauchy_ratCast (q : ℚ) : (q : ℝ).cauchy = q := rfl
#align real.cauchy_nat_cast Real.cauchy_natCast
#align real.cauchy_int_cast Real.cauchy_intCast
#align real.cauchy_rat_cast Real.cauchy_ratCast
instance commRing : CommRing ℝ where
natCast n := ⟨n⟩
intCast z := ⟨z⟩
zero := (0 : ℝ)
one := (1 : ℝ)
mul := (· * ·)
add := (· + ·)
neg := @Neg.neg ℝ _
sub := @Sub.sub ℝ _
npow := @npowRec ℝ ⟨1⟩ ⟨(· * ·)⟩
nsmul := @nsmulRec ℝ ⟨0⟩ ⟨(· + ·)⟩
zsmul := @zsmulRec ℝ ⟨0⟩ ⟨(· + ·)⟩ ⟨@Neg.neg ℝ _⟩ (@nsmulRec ℝ ⟨0⟩ ⟨(· + ·)⟩)
add_zero a := by apply ext_cauchy; simp [cauchy_add, cauchy_zero]
zero_add a := by apply ext_cauchy; simp [cauchy_add, cauchy_zero]
add_comm a b := by apply ext_cauchy; simp only [cauchy_add, add_comm]
add_assoc a b c := by apply ext_cauchy; simp only [cauchy_add, add_assoc]
mul_zero a := by apply ext_cauchy; simp [cauchy_mul, cauchy_zero]
zero_mul a := by apply ext_cauchy; simp [cauchy_mul, cauchy_zero]
mul_one a := by apply ext_cauchy; simp [cauchy_mul, cauchy_one]
one_mul a := by apply ext_cauchy; simp [cauchy_mul, cauchy_one]
mul_comm a b := by apply ext_cauchy; simp only [cauchy_mul, mul_comm]
mul_assoc a b c := by apply ext_cauchy; simp only [cauchy_mul, mul_assoc]
left_distrib a b c := by apply ext_cauchy; simp only [cauchy_add, cauchy_mul, mul_add]
right_distrib a b c := by apply ext_cauchy; simp only [cauchy_add, cauchy_mul, add_mul]
add_left_neg a := by apply ext_cauchy; simp [cauchy_add, cauchy_neg, cauchy_zero]
natCast_zero := by apply ext_cauchy; simp [cauchy_zero]
natCast_succ n := by apply ext_cauchy; simp [cauchy_one, cauchy_add]
intCast_negSucc z := by apply ext_cauchy; simp [cauchy_neg, cauchy_natCast]
/-- `Real.equivCauchy` as a ring equivalence. -/
@[simps]
def ringEquivCauchy : ℝ ≃+* CauSeq.Completion.Cauchy (abs : ℚ → ℚ) :=
{ equivCauchy with
toFun := cauchy
invFun := ofCauchy
map_add' := cauchy_add
map_mul' := cauchy_mul }
set_option linter.uppercaseLean3 false in
#align real.ring_equiv_Cauchy Real.ringEquivCauchy
set_option linter.uppercaseLean3 false in
#align real.ring_equiv_Cauchy_apply Real.ringEquivCauchy_apply
set_option linter.uppercaseLean3 false in
#align real.ring_equiv_Cauchy_symm_apply_cauchy Real.ringEquivCauchy_symm_apply_cauchy
/-! Extra instances to short-circuit type class resolution.
These short-circuits have an additional property of ensuring that a computable path is found; if
`Field ℝ` is found first, then decaying it to these typeclasses would result in a `noncomputable`
version of them. -/
instance instRing : Ring ℝ := by infer_instance
instance : CommSemiring ℝ := by infer_instance
instance semiring : Semiring ℝ := by infer_instance
instance : CommMonoidWithZero ℝ := by infer_instance
instance : MonoidWithZero ℝ := by infer_instance
instance : AddCommGroup ℝ := by infer_instance
instance : AddGroup ℝ := by infer_instance
instance : AddCommMonoid ℝ := by infer_instance
instance : AddMonoid ℝ := by infer_instance
instance : AddLeftCancelSemigroup ℝ := by infer_instance
instance : AddRightCancelSemigroup ℝ := by infer_instance
instance : AddCommSemigroup ℝ := by infer_instance
instance : AddSemigroup ℝ := by infer_instance
instance : CommMonoid ℝ := by infer_instance
instance : Monoid ℝ := by infer_instance
instance : CommSemigroup ℝ := by infer_instance
instance : Semigroup ℝ := by infer_instance
instance : Inhabited ℝ :=
⟨0⟩
/-- The real numbers are a `*`-ring, with the trivial `*`-structure. -/
instance : StarRing ℝ :=
starRingOfComm
instance : TrivialStar ℝ :=
⟨fun _ => rfl⟩
/-- Make a real number from a Cauchy sequence of rationals (by taking the equivalence class). -/
def mk (x : CauSeq ℚ abs) : ℝ :=
⟨CauSeq.Completion.mk x⟩
#align real.mk Real.mk
theorem mk_eq {f g : CauSeq ℚ abs} : mk f = mk g ↔ f ≈ g :=
ext_cauchy_iff.trans CauSeq.Completion.mk_eq
#align real.mk_eq Real.mk_eq
private irreducible_def lt : ℝ → ℝ → Prop
| ⟨x⟩, ⟨y⟩ =>
(Quotient.liftOn₂ x y (· < ·)) fun _ _ _ _ hf hg =>
propext <|
⟨fun h => lt_of_eq_of_lt (Setoid.symm hf) (lt_of_lt_of_eq h hg), fun h =>
lt_of_eq_of_lt hf (lt_of_lt_of_eq h (Setoid.symm hg))⟩
instance : LT ℝ :=
⟨lt⟩
theorem lt_cauchy {f g} : (⟨⟦f⟧⟩ : ℝ) < ⟨⟦g⟧⟩ ↔ f < g :=
show lt _ _ ↔ _ by rw [lt_def]; rfl
#align real.lt_cauchy Real.lt_cauchy
@[simp]
theorem mk_lt {f g : CauSeq ℚ abs} : mk f < mk g ↔ f < g :=
lt_cauchy
#align real.mk_lt Real.mk_lt
theorem mk_zero : mk 0 = 0 := by rw [← ofCauchy_zero]; rfl
#align real.mk_zero Real.mk_zero
theorem mk_one : mk 1 = 1 := by rw [← ofCauchy_one]; rfl
#align real.mk_one Real.mk_one
theorem mk_add {f g : CauSeq ℚ abs} : mk (f + g) = mk f + mk g := by simp [mk, ← ofCauchy_add]
#align real.mk_add Real.mk_add
theorem mk_mul {f g : CauSeq ℚ abs} : mk (f * g) = mk f * mk g := by simp [mk, ← ofCauchy_mul]
#align real.mk_mul Real.mk_mul
| Mathlib/Data/Real/Basic.lean | 328 | 328 | theorem mk_neg {f : CauSeq ℚ abs} : mk (-f) = -mk f := by | simp [mk, ← ofCauchy_neg]
|
/-
Copyright (c) 2019 Calle Sönne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Calle Sönne
-/
import Mathlib.Analysis.SpecialFunctions.Trigonometric.Basic
import Mathlib.Analysis.Normed.Group.AddCircle
import Mathlib.Algebra.CharZero.Quotient
import Mathlib.Topology.Instances.Sign
#align_import analysis.special_functions.trigonometric.angle from "leanprover-community/mathlib"@"213b0cff7bc5ab6696ee07cceec80829ce42efec"
/-!
# The type of angles
In this file we define `Real.Angle` to be the quotient group `ℝ/2πℤ` and prove a few simple lemmas
about trigonometric functions and angles.
-/
open Real
noncomputable section
namespace Real
-- Porting note: can't derive `NormedAddCommGroup, Inhabited`
/-- The type of angles -/
def Angle : Type :=
AddCircle (2 * π)
#align real.angle Real.Angle
namespace Angle
-- Porting note (#10754): added due to missing instances due to no deriving
instance : NormedAddCommGroup Angle :=
inferInstanceAs (NormedAddCommGroup (AddCircle (2 * π)))
-- Porting note (#10754): added due to missing instances due to no deriving
instance : Inhabited Angle :=
inferInstanceAs (Inhabited (AddCircle (2 * π)))
-- Porting note (#10754): added due to missing instances due to no deriving
-- also, without this, a plain `QuotientAddGroup.mk`
-- causes coerced terms to be of type `ℝ ⧸ AddSubgroup.zmultiples (2 * π)`
/-- The canonical map from `ℝ` to the quotient `Angle`. -/
@[coe]
protected def coe (r : ℝ) : Angle := QuotientAddGroup.mk r
instance : Coe ℝ Angle := ⟨Angle.coe⟩
instance : CircularOrder Real.Angle :=
QuotientAddGroup.circularOrder (hp' := ⟨by norm_num [pi_pos]⟩)
@[continuity]
theorem continuous_coe : Continuous ((↑) : ℝ → Angle) :=
continuous_quotient_mk'
#align real.angle.continuous_coe Real.Angle.continuous_coe
/-- Coercion `ℝ → Angle` as an additive homomorphism. -/
def coeHom : ℝ →+ Angle :=
QuotientAddGroup.mk' _
#align real.angle.coe_hom Real.Angle.coeHom
@[simp]
theorem coe_coeHom : (coeHom : ℝ → Angle) = ((↑) : ℝ → Angle) :=
rfl
#align real.angle.coe_coe_hom Real.Angle.coe_coeHom
/-- An induction principle to deduce results for `Angle` from those for `ℝ`, used with
`induction θ using Real.Angle.induction_on`. -/
@[elab_as_elim]
protected theorem induction_on {p : Angle → Prop} (θ : Angle) (h : ∀ x : ℝ, p x) : p θ :=
Quotient.inductionOn' θ h
#align real.angle.induction_on Real.Angle.induction_on
@[simp]
theorem coe_zero : ↑(0 : ℝ) = (0 : Angle) :=
rfl
#align real.angle.coe_zero Real.Angle.coe_zero
@[simp]
theorem coe_add (x y : ℝ) : ↑(x + y : ℝ) = (↑x + ↑y : Angle) :=
rfl
#align real.angle.coe_add Real.Angle.coe_add
@[simp]
theorem coe_neg (x : ℝ) : ↑(-x : ℝ) = -(↑x : Angle) :=
rfl
#align real.angle.coe_neg Real.Angle.coe_neg
@[simp]
theorem coe_sub (x y : ℝ) : ↑(x - y : ℝ) = (↑x - ↑y : Angle) :=
rfl
#align real.angle.coe_sub Real.Angle.coe_sub
theorem coe_nsmul (n : ℕ) (x : ℝ) : ↑(n • x : ℝ) = n • (↑x : Angle) :=
rfl
#align real.angle.coe_nsmul Real.Angle.coe_nsmul
theorem coe_zsmul (z : ℤ) (x : ℝ) : ↑(z • x : ℝ) = z • (↑x : Angle) :=
rfl
#align real.angle.coe_zsmul Real.Angle.coe_zsmul
@[simp, norm_cast]
theorem natCast_mul_eq_nsmul (x : ℝ) (n : ℕ) : ↑((n : ℝ) * x) = n • (↑x : Angle) := by
simpa only [nsmul_eq_mul] using coeHom.map_nsmul x n
#align real.angle.coe_nat_mul_eq_nsmul Real.Angle.natCast_mul_eq_nsmul
@[simp, norm_cast]
theorem intCast_mul_eq_zsmul (x : ℝ) (n : ℤ) : ↑((n : ℝ) * x : ℝ) = n • (↑x : Angle) := by
simpa only [zsmul_eq_mul] using coeHom.map_zsmul x n
#align real.angle.coe_int_mul_eq_zsmul Real.Angle.intCast_mul_eq_zsmul
@[deprecated (since := "2024-05-25")] alias coe_nat_mul_eq_nsmul := natCast_mul_eq_nsmul
@[deprecated (since := "2024-05-25")] alias coe_int_mul_eq_zsmul := intCast_mul_eq_zsmul
theorem angle_eq_iff_two_pi_dvd_sub {ψ θ : ℝ} : (θ : Angle) = ψ ↔ ∃ k : ℤ, θ - ψ = 2 * π * k := by
simp only [QuotientAddGroup.eq, AddSubgroup.zmultiples_eq_closure,
AddSubgroup.mem_closure_singleton, zsmul_eq_mul', (sub_eq_neg_add _ _).symm, eq_comm]
-- Porting note: added `rw`, `simp [Angle.coe, QuotientAddGroup.eq]` doesn't fire otherwise
rw [Angle.coe, Angle.coe, QuotientAddGroup.eq]
simp only [AddSubgroup.zmultiples_eq_closure,
AddSubgroup.mem_closure_singleton, zsmul_eq_mul', (sub_eq_neg_add _ _).symm, eq_comm]
#align real.angle.angle_eq_iff_two_pi_dvd_sub Real.Angle.angle_eq_iff_two_pi_dvd_sub
@[simp]
theorem coe_two_pi : ↑(2 * π : ℝ) = (0 : Angle) :=
angle_eq_iff_two_pi_dvd_sub.2 ⟨1, by rw [sub_zero, Int.cast_one, mul_one]⟩
#align real.angle.coe_two_pi Real.Angle.coe_two_pi
@[simp]
| Mathlib/Analysis/SpecialFunctions/Trigonometric/Angle.lean | 134 | 137 | theorem neg_coe_pi : -(π : Angle) = π := by |
rw [← coe_neg, angle_eq_iff_two_pi_dvd_sub]
use -1
simp [two_mul, sub_eq_add_neg]
|
/-
Copyright (c) 2021 Aaron Anderson, Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson, Kevin Buzzard, Yaël Dillies, Eric Wieser
-/
import Mathlib.Data.Finset.Sigma
import Mathlib.Data.Finset.Pairwise
import Mathlib.Data.Finset.Powerset
import Mathlib.Data.Fintype.Basic
import Mathlib.Order.CompleteLatticeIntervals
#align_import order.sup_indep from "leanprover-community/mathlib"@"c4c2ed622f43768eff32608d4a0f8a6cec1c047d"
/-!
# Supremum independence
In this file, we define supremum independence of indexed sets. An indexed family `f : ι → α` is
sup-independent if, for all `a`, `f a` and the supremum of the rest are disjoint.
## Main definitions
* `Finset.SupIndep s f`: a family of elements `f` are supremum independent on the finite set `s`.
* `CompleteLattice.SetIndependent s`: a set of elements are supremum independent.
* `CompleteLattice.Independent f`: a family of elements are supremum independent.
## Main statements
* In a distributive lattice, supremum independence is equivalent to pairwise disjointness:
* `Finset.supIndep_iff_pairwiseDisjoint`
* `CompleteLattice.setIndependent_iff_pairwiseDisjoint`
* `CompleteLattice.independent_iff_pairwiseDisjoint`
* Otherwise, supremum independence is stronger than pairwise disjointness:
* `Finset.SupIndep.pairwiseDisjoint`
* `CompleteLattice.SetIndependent.pairwiseDisjoint`
* `CompleteLattice.Independent.pairwiseDisjoint`
## Implementation notes
For the finite version, we avoid the "obvious" definition
`∀ i ∈ s, Disjoint (f i) ((s.erase i).sup f)` because `erase` would require decidable equality on
`ι`.
-/
variable {α β ι ι' : Type*}
/-! ### On lattices with a bottom element, via `Finset.sup` -/
namespace Finset
section Lattice
variable [Lattice α] [OrderBot α]
/-- Supremum independence of finite sets. We avoid the "obvious" definition using `s.erase i`
because `erase` would require decidable equality on `ι`. -/
def SupIndep (s : Finset ι) (f : ι → α) : Prop :=
∀ ⦃t⦄, t ⊆ s → ∀ ⦃i⦄, i ∈ s → i ∉ t → Disjoint (f i) (t.sup f)
#align finset.sup_indep Finset.SupIndep
variable {s t : Finset ι} {f : ι → α} {i : ι}
instance [DecidableEq ι] [DecidableEq α] : Decidable (SupIndep s f) := by
refine @Finset.decidableForallOfDecidableSubsets _ _ _ (?_)
rintro t -
refine @Finset.decidableDforallFinset _ _ _ (?_)
rintro i -
have : Decidable (Disjoint (f i) (sup t f)) := decidable_of_iff' (_ = ⊥) disjoint_iff
infer_instance
theorem SupIndep.subset (ht : t.SupIndep f) (h : s ⊆ t) : s.SupIndep f := fun _ hu _ hi =>
ht (hu.trans h) (h hi)
#align finset.sup_indep.subset Finset.SupIndep.subset
@[simp]
theorem supIndep_empty (f : ι → α) : (∅ : Finset ι).SupIndep f := fun _ _ a ha =>
(not_mem_empty a ha).elim
#align finset.sup_indep_empty Finset.supIndep_empty
theorem supIndep_singleton (i : ι) (f : ι → α) : ({i} : Finset ι).SupIndep f :=
fun s hs j hji hj => by
rw [eq_empty_of_ssubset_singleton ⟨hs, fun h => hj (h hji)⟩, sup_empty]
exact disjoint_bot_right
#align finset.sup_indep_singleton Finset.supIndep_singleton
theorem SupIndep.pairwiseDisjoint (hs : s.SupIndep f) : (s : Set ι).PairwiseDisjoint f :=
fun _ ha _ hb hab =>
sup_singleton.subst <| hs (singleton_subset_iff.2 hb) ha <| not_mem_singleton.2 hab
#align finset.sup_indep.pairwise_disjoint Finset.SupIndep.pairwiseDisjoint
| Mathlib/Order/SupIndep.lean | 92 | 96 | theorem SupIndep.le_sup_iff (hs : s.SupIndep f) (hts : t ⊆ s) (hi : i ∈ s) (hf : ∀ i, f i ≠ ⊥) :
f i ≤ t.sup f ↔ i ∈ t := by |
refine ⟨fun h => ?_, le_sup⟩
by_contra hit
exact hf i (disjoint_self.1 <| (hs hts hi hit).mono_right h)
|
/-
Copyright (c) 2015 Jeremy Avigad. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jeremy Avigad, Robert Y. Lewis, Yury G. Kudryashov
-/
import Mathlib.Algebra.Order.Monoid.OrderDual
import Mathlib.Tactic.Lift
import Mathlib.Tactic.Monotonicity.Attr
/-!
# Lemmas about the interaction of power operations with order in terms of `CovariantClass`
-/
open Function
variable {β G M : Type*}
section Monoid
variable [Monoid M]
section Preorder
variable [Preorder M]
section Left
variable [CovariantClass M M (· * ·) (· ≤ ·)] {x : M}
@[to_additive (attr := mono, gcongr) nsmul_le_nsmul_right]
theorem pow_le_pow_left' [CovariantClass M M (swap (· * ·)) (· ≤ ·)] {a b : M} (hab : a ≤ b) :
∀ i : ℕ, a ^ i ≤ b ^ i
| 0 => by simp
| k + 1 => by
rw [pow_succ, pow_succ]
exact mul_le_mul' (pow_le_pow_left' hab k) hab
#align pow_le_pow_of_le_left' pow_le_pow_left'
#align nsmul_le_nsmul_of_le_right nsmul_le_nsmul_right
@[to_additive nsmul_nonneg]
theorem one_le_pow_of_one_le' {a : M} (H : 1 ≤ a) : ∀ n : ℕ, 1 ≤ a ^ n
| 0 => by simp
| k + 1 => by
rw [pow_succ]
exact one_le_mul (one_le_pow_of_one_le' H k) H
#align one_le_pow_of_one_le' one_le_pow_of_one_le'
#align nsmul_nonneg nsmul_nonneg
@[to_additive nsmul_nonpos]
theorem pow_le_one' {a : M} (H : a ≤ 1) (n : ℕ) : a ^ n ≤ 1 :=
@one_le_pow_of_one_le' Mᵒᵈ _ _ _ _ H n
#align pow_le_one' pow_le_one'
#align nsmul_nonpos nsmul_nonpos
@[to_additive (attr := gcongr) nsmul_le_nsmul_left]
theorem pow_le_pow_right' {a : M} {n m : ℕ} (ha : 1 ≤ a) (h : n ≤ m) : a ^ n ≤ a ^ m :=
let ⟨k, hk⟩ := Nat.le.dest h
calc
a ^ n ≤ a ^ n * a ^ k := le_mul_of_one_le_right' (one_le_pow_of_one_le' ha _)
_ = a ^ m := by rw [← hk, pow_add]
#align pow_le_pow' pow_le_pow_right'
#align nsmul_le_nsmul nsmul_le_nsmul_left
@[to_additive nsmul_le_nsmul_left_of_nonpos]
theorem pow_le_pow_right_of_le_one' {a : M} {n m : ℕ} (ha : a ≤ 1) (h : n ≤ m) : a ^ m ≤ a ^ n :=
pow_le_pow_right' (M := Mᵒᵈ) ha h
#align pow_le_pow_of_le_one' pow_le_pow_right_of_le_one'
#align nsmul_le_nsmul_of_nonpos nsmul_le_nsmul_left_of_nonpos
@[to_additive nsmul_pos]
| Mathlib/Algebra/Order/Monoid/Unbundled/Pow.lean | 71 | 77 | theorem one_lt_pow' {a : M} (ha : 1 < a) {k : ℕ} (hk : k ≠ 0) : 1 < a ^ k := by |
rcases Nat.exists_eq_succ_of_ne_zero hk with ⟨l, rfl⟩
clear hk
induction' l with l IH
· rw [pow_succ]; simpa using ha
· rw [pow_succ]
exact one_lt_mul'' IH ha
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Kenny Lau
-/
import Mathlib.Data.List.Forall2
import Mathlib.Data.Set.Pairwise.Basic
import Mathlib.Init.Data.Fin.Basic
#align_import data.list.nodup from "leanprover-community/mathlib"@"c227d107bbada5d0d9d20287e3282c0a7f1651a0"
/-!
# Lists with no duplicates
`List.Nodup` is defined in `Data/List/Basic`. In this file we prove various properties of this
predicate.
-/
universe u v
open Nat Function
variable {α : Type u} {β : Type v} {l l₁ l₂ : List α} {r : α → α → Prop} {a b : α}
namespace List
@[simp]
theorem forall_mem_ne {a : α} {l : List α} : (∀ a' : α, a' ∈ l → ¬a = a') ↔ a ∉ l :=
⟨fun h m => h _ m rfl, fun h _ m e => h (e.symm ▸ m)⟩
#align list.forall_mem_ne List.forall_mem_ne
@[simp]
theorem nodup_nil : @Nodup α [] :=
Pairwise.nil
#align list.nodup_nil List.nodup_nil
@[simp]
theorem nodup_cons {a : α} {l : List α} : Nodup (a :: l) ↔ a ∉ l ∧ Nodup l := by
simp only [Nodup, pairwise_cons, forall_mem_ne]
#align list.nodup_cons List.nodup_cons
protected theorem Pairwise.nodup {l : List α} {r : α → α → Prop} [IsIrrefl α r] (h : Pairwise r l) :
Nodup l :=
h.imp ne_of_irrefl
#align list.pairwise.nodup List.Pairwise.nodup
theorem rel_nodup {r : α → β → Prop} (hr : Relator.BiUnique r) : (Forall₂ r ⇒ (· ↔ ·)) Nodup Nodup
| _, _, Forall₂.nil => by simp only [nodup_nil]
| _, _, Forall₂.cons hab h => by
simpa only [nodup_cons] using
Relator.rel_and (Relator.rel_not (rel_mem hr hab h)) (rel_nodup hr h)
#align list.rel_nodup List.rel_nodup
protected theorem Nodup.cons (ha : a ∉ l) (hl : Nodup l) : Nodup (a :: l) :=
nodup_cons.2 ⟨ha, hl⟩
#align list.nodup.cons List.Nodup.cons
theorem nodup_singleton (a : α) : Nodup [a] :=
pairwise_singleton _ _
#align list.nodup_singleton List.nodup_singleton
theorem Nodup.of_cons (h : Nodup (a :: l)) : Nodup l :=
(nodup_cons.1 h).2
#align list.nodup.of_cons List.Nodup.of_cons
theorem Nodup.not_mem (h : (a :: l).Nodup) : a ∉ l :=
(nodup_cons.1 h).1
#align list.nodup.not_mem List.Nodup.not_mem
theorem not_nodup_cons_of_mem : a ∈ l → ¬Nodup (a :: l) :=
imp_not_comm.1 Nodup.not_mem
#align list.not_nodup_cons_of_mem List.not_nodup_cons_of_mem
protected theorem Nodup.sublist : l₁ <+ l₂ → Nodup l₂ → Nodup l₁ :=
Pairwise.sublist
#align list.nodup.sublist List.Nodup.sublist
theorem not_nodup_pair (a : α) : ¬Nodup [a, a] :=
not_nodup_cons_of_mem <| mem_singleton_self _
#align list.not_nodup_pair List.not_nodup_pair
theorem nodup_iff_sublist {l : List α} : Nodup l ↔ ∀ a, ¬[a, a] <+ l :=
⟨fun d a h => not_nodup_pair a (d.sublist h),
by
induction' l with a l IH <;> intro h; · exact nodup_nil
exact (IH fun a s => h a <| sublist_cons_of_sublist _ s).cons fun al =>
h a <| (singleton_sublist.2 al).cons_cons _⟩
#align list.nodup_iff_sublist List.nodup_iff_sublist
-- Porting note (#10756): new theorem
theorem nodup_iff_injective_get {l : List α} :
Nodup l ↔ Function.Injective l.get :=
pairwise_iff_get.trans
⟨fun h i j hg => by
cases' i with i hi; cases' j with j hj
rcases lt_trichotomy i j with (hij | rfl | hji)
· exact (h ⟨i, hi⟩ ⟨j, hj⟩ hij hg).elim
· rfl
· exact (h ⟨j, hj⟩ ⟨i, hi⟩ hji hg.symm).elim,
fun hinj i j hij h => Nat.ne_of_lt hij (Fin.val_eq_of_eq (hinj h))⟩
set_option linter.deprecated false in
@[deprecated nodup_iff_injective_get (since := "2023-01-10")]
theorem nodup_iff_nthLe_inj {l : List α} :
Nodup l ↔ ∀ i j h₁ h₂, nthLe l i h₁ = nthLe l j h₂ → i = j :=
nodup_iff_injective_get.trans
⟨fun hinj _ _ _ _ h => congr_arg Fin.val (hinj h),
fun hinj i j h => Fin.eq_of_veq (hinj i j i.2 j.2 h)⟩
#align list.nodup_iff_nth_le_inj List.nodup_iff_nthLe_inj
theorem Nodup.get_inj_iff {l : List α} (h : Nodup l) {i j : Fin l.length} :
l.get i = l.get j ↔ i = j :=
(nodup_iff_injective_get.1 h).eq_iff
set_option linter.deprecated false in
@[deprecated Nodup.get_inj_iff (since := "2023-01-10")]
theorem Nodup.nthLe_inj_iff {l : List α} (h : Nodup l) {i j : ℕ} (hi : i < l.length)
(hj : j < l.length) : l.nthLe i hi = l.nthLe j hj ↔ i = j :=
⟨nodup_iff_nthLe_inj.mp h _ _ _ _, by simp (config := { contextual := true })⟩
#align list.nodup.nth_le_inj_iff List.Nodup.nthLe_inj_iff
theorem nodup_iff_get?_ne_get? {l : List α} :
l.Nodup ↔ ∀ i j : ℕ, i < j → j < l.length → l.get? i ≠ l.get? j := by
rw [Nodup, pairwise_iff_get]
constructor
· intro h i j hij hj
rw [get?_eq_get (lt_trans hij hj), get?_eq_get hj, Ne, Option.some_inj]
exact h _ _ hij
· intro h i j hij
rw [Ne, ← Option.some_inj, ← get?_eq_get, ← get?_eq_get]
exact h i j hij j.2
#align list.nodup_iff_nth_ne_nth List.nodup_iff_get?_ne_get?
theorem Nodup.ne_singleton_iff {l : List α} (h : Nodup l) (x : α) :
l ≠ [x] ↔ l = [] ∨ ∃ y ∈ l, y ≠ x := by
induction' l with hd tl hl
· simp
· specialize hl h.of_cons
by_cases hx : tl = [x]
· simpa [hx, and_comm, and_or_left] using h
· rw [← Ne, hl] at hx
rcases hx with (rfl | ⟨y, hy, hx⟩)
· simp
· suffices ∃ y ∈ hd :: tl, y ≠ x by simpa [ne_nil_of_mem hy]
exact ⟨y, mem_cons_of_mem _ hy, hx⟩
#align list.nodup.ne_singleton_iff List.Nodup.ne_singleton_iff
| Mathlib/Data/List/Nodup.lean | 149 | 152 | theorem not_nodup_of_get_eq_of_ne (xs : List α) (n m : Fin xs.length)
(h : xs.get n = xs.get m) (hne : n ≠ m) : ¬Nodup xs := by |
rw [nodup_iff_injective_get]
exact fun hinj => hne (hinj h)
|
/-
Copyright (c) 2020 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Yury Kudryashov
-/
import Mathlib.MeasureTheory.Integral.IntegrableOn
import Mathlib.MeasureTheory.Integral.Bochner
import Mathlib.MeasureTheory.Function.LocallyIntegrable
import Mathlib.Topology.MetricSpace.ThickenedIndicator
import Mathlib.Topology.ContinuousFunction.Compact
import Mathlib.Analysis.NormedSpace.HahnBanach.SeparatingDual
#align_import measure_theory.integral.setIntegral from "leanprover-community/mathlib"@"24e0c85412ff6adbeca08022c25ba4876eedf37a"
/-!
# Set integral
In this file we prove some properties of `∫ x in s, f x ∂μ`. Recall that this notation
is defined as `∫ x, f x ∂(μ.restrict s)`. In `integral_indicator` we prove that for a measurable
function `f` and a measurable set `s` this definition coincides with another natural definition:
`∫ x, indicator s f x ∂μ = ∫ x in s, f x ∂μ`, where `indicator s f x` is equal to `f x` for `x ∈ s`
and is zero otherwise.
Since `∫ x in s, f x ∂μ` is a notation, one can rewrite or apply any theorem about `∫ x, f x ∂μ`
directly. In this file we prove some theorems about dependence of `∫ x in s, f x ∂μ` on `s`, e.g.
`integral_union`, `integral_empty`, `integral_univ`.
We use the property `IntegrableOn f s μ := Integrable f (μ.restrict s)`, defined in
`MeasureTheory.IntegrableOn`. We also defined in that same file a predicate
`IntegrableAtFilter (f : X → E) (l : Filter X) (μ : Measure X)` saying that `f` is integrable at
some set `s ∈ l`.
Finally, we prove a version of the
[Fundamental theorem of calculus](https://en.wikipedia.org/wiki/Fundamental_theorem_of_calculus)
for set integral, see `Filter.Tendsto.integral_sub_linear_isLittleO_ae` and its corollaries.
Namely, consider a measurably generated filter `l`, a measure `μ` finite at this filter, and
a function `f` that has a finite limit `c` at `l ⊓ ae μ`. Then `∫ x in s, f x ∂μ = μ s • c + o(μ s)`
as `s` tends to `l.smallSets`, i.e. for any `ε>0` there exists `t ∈ l` such that
`‖∫ x in s, f x ∂μ - μ s • c‖ ≤ ε * μ s` whenever `s ⊆ t`. We also formulate a version of this
theorem for a locally finite measure `μ` and a function `f` continuous at a point `a`.
## Notation
We provide the following notations for expressing the integral of a function on a set :
* `∫ x in s, f x ∂μ` is `MeasureTheory.integral (μ.restrict s) f`
* `∫ x in s, f x` is `∫ x in s, f x ∂volume`
Note that the set notations are defined in the file `Mathlib/MeasureTheory/Integral/Bochner.lean`,
but we reference them here because all theorems about set integrals are in this file.
-/
assert_not_exists InnerProductSpace
noncomputable section
open Set Filter TopologicalSpace MeasureTheory Function RCLike
open scoped Classical Topology ENNReal NNReal
variable {X Y E F : Type*} [MeasurableSpace X]
namespace MeasureTheory
section NormedAddCommGroup
variable [NormedAddCommGroup E] [NormedSpace ℝ E]
{f g : X → E} {s t : Set X} {μ ν : Measure X} {l l' : Filter X}
theorem setIntegral_congr_ae₀ (hs : NullMeasurableSet s μ) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ :=
integral_congr_ae ((ae_restrict_iff'₀ hs).2 h)
#align measure_theory.set_integral_congr_ae₀ MeasureTheory.setIntegral_congr_ae₀
@[deprecated (since := "2024-04-17")]
alias set_integral_congr_ae₀ := setIntegral_congr_ae₀
theorem setIntegral_congr_ae (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x = g x) :
∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ :=
integral_congr_ae ((ae_restrict_iff' hs).2 h)
#align measure_theory.set_integral_congr_ae MeasureTheory.setIntegral_congr_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_congr_ae := setIntegral_congr_ae
theorem setIntegral_congr₀ (hs : NullMeasurableSet s μ) (h : EqOn f g s) :
∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ :=
setIntegral_congr_ae₀ hs <| eventually_of_forall h
#align measure_theory.set_integral_congr₀ MeasureTheory.setIntegral_congr₀
@[deprecated (since := "2024-04-17")]
alias set_integral_congr₀ := setIntegral_congr₀
theorem setIntegral_congr (hs : MeasurableSet s) (h : EqOn f g s) :
∫ x in s, f x ∂μ = ∫ x in s, g x ∂μ :=
setIntegral_congr_ae hs <| eventually_of_forall h
#align measure_theory.set_integral_congr MeasureTheory.setIntegral_congr
@[deprecated (since := "2024-04-17")]
alias set_integral_congr := setIntegral_congr
theorem setIntegral_congr_set_ae (hst : s =ᵐ[μ] t) : ∫ x in s, f x ∂μ = ∫ x in t, f x ∂μ := by
rw [Measure.restrict_congr_set hst]
#align measure_theory.set_integral_congr_set_ae MeasureTheory.setIntegral_congr_set_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_congr_set_ae := setIntegral_congr_set_ae
theorem integral_union_ae (hst : AEDisjoint μ s t) (ht : NullMeasurableSet t μ)
(hfs : IntegrableOn f s μ) (hft : IntegrableOn f t μ) :
∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ + ∫ x in t, f x ∂μ := by
simp only [IntegrableOn, Measure.restrict_union₀ hst ht, integral_add_measure hfs hft]
#align measure_theory.integral_union_ae MeasureTheory.integral_union_ae
theorem integral_union (hst : Disjoint s t) (ht : MeasurableSet t) (hfs : IntegrableOn f s μ)
(hft : IntegrableOn f t μ) : ∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ + ∫ x in t, f x ∂μ :=
integral_union_ae hst.aedisjoint ht.nullMeasurableSet hfs hft
#align measure_theory.integral_union MeasureTheory.integral_union
theorem integral_diff (ht : MeasurableSet t) (hfs : IntegrableOn f s μ) (hts : t ⊆ s) :
∫ x in s \ t, f x ∂μ = ∫ x in s, f x ∂μ - ∫ x in t, f x ∂μ := by
rw [eq_sub_iff_add_eq, ← integral_union, diff_union_of_subset hts]
exacts [disjoint_sdiff_self_left, ht, hfs.mono_set diff_subset, hfs.mono_set hts]
#align measure_theory.integral_diff MeasureTheory.integral_diff
theorem integral_inter_add_diff₀ (ht : NullMeasurableSet t μ) (hfs : IntegrableOn f s μ) :
∫ x in s ∩ t, f x ∂μ + ∫ x in s \ t, f x ∂μ = ∫ x in s, f x ∂μ := by
rw [← Measure.restrict_inter_add_diff₀ s ht, integral_add_measure]
· exact Integrable.mono_measure hfs (Measure.restrict_mono inter_subset_left le_rfl)
· exact Integrable.mono_measure hfs (Measure.restrict_mono diff_subset le_rfl)
#align measure_theory.integral_inter_add_diff₀ MeasureTheory.integral_inter_add_diff₀
theorem integral_inter_add_diff (ht : MeasurableSet t) (hfs : IntegrableOn f s μ) :
∫ x in s ∩ t, f x ∂μ + ∫ x in s \ t, f x ∂μ = ∫ x in s, f x ∂μ :=
integral_inter_add_diff₀ ht.nullMeasurableSet hfs
#align measure_theory.integral_inter_add_diff MeasureTheory.integral_inter_add_diff
theorem integral_finset_biUnion {ι : Type*} (t : Finset ι) {s : ι → Set X}
(hs : ∀ i ∈ t, MeasurableSet (s i)) (h's : Set.Pairwise (↑t) (Disjoint on s))
(hf : ∀ i ∈ t, IntegrableOn f (s i) μ) :
∫ x in ⋃ i ∈ t, s i, f x ∂μ = ∑ i ∈ t, ∫ x in s i, f x ∂μ := by
induction' t using Finset.induction_on with a t hat IH hs h's
· simp
· simp only [Finset.coe_insert, Finset.forall_mem_insert, Set.pairwise_insert,
Finset.set_biUnion_insert] at hs hf h's ⊢
rw [integral_union _ _ hf.1 (integrableOn_finset_iUnion.2 hf.2)]
· rw [Finset.sum_insert hat, IH hs.2 h's.1 hf.2]
· simp only [disjoint_iUnion_right]
exact fun i hi => (h's.2 i hi (ne_of_mem_of_not_mem hi hat).symm).1
· exact Finset.measurableSet_biUnion _ hs.2
#align measure_theory.integral_finset_bUnion MeasureTheory.integral_finset_biUnion
theorem integral_fintype_iUnion {ι : Type*} [Fintype ι] {s : ι → Set X}
(hs : ∀ i, MeasurableSet (s i)) (h's : Pairwise (Disjoint on s))
(hf : ∀ i, IntegrableOn f (s i) μ) : ∫ x in ⋃ i, s i, f x ∂μ = ∑ i, ∫ x in s i, f x ∂μ := by
convert integral_finset_biUnion Finset.univ (fun i _ => hs i) _ fun i _ => hf i
· simp
· simp [pairwise_univ, h's]
#align measure_theory.integral_fintype_Union MeasureTheory.integral_fintype_iUnion
theorem integral_empty : ∫ x in ∅, f x ∂μ = 0 := by
rw [Measure.restrict_empty, integral_zero_measure]
#align measure_theory.integral_empty MeasureTheory.integral_empty
theorem integral_univ : ∫ x in univ, f x ∂μ = ∫ x, f x ∂μ := by rw [Measure.restrict_univ]
#align measure_theory.integral_univ MeasureTheory.integral_univ
theorem integral_add_compl₀ (hs : NullMeasurableSet s μ) (hfi : Integrable f μ) :
∫ x in s, f x ∂μ + ∫ x in sᶜ, f x ∂μ = ∫ x, f x ∂μ := by
rw [
← integral_union_ae disjoint_compl_right.aedisjoint hs.compl hfi.integrableOn hfi.integrableOn,
union_compl_self, integral_univ]
#align measure_theory.integral_add_compl₀ MeasureTheory.integral_add_compl₀
theorem integral_add_compl (hs : MeasurableSet s) (hfi : Integrable f μ) :
∫ x in s, f x ∂μ + ∫ x in sᶜ, f x ∂μ = ∫ x, f x ∂μ :=
integral_add_compl₀ hs.nullMeasurableSet hfi
#align measure_theory.integral_add_compl MeasureTheory.integral_add_compl
/-- For a function `f` and a measurable set `s`, the integral of `indicator s f`
over the whole space is equal to `∫ x in s, f x ∂μ` defined as `∫ x, f x ∂(μ.restrict s)`. -/
theorem integral_indicator (hs : MeasurableSet s) :
∫ x, indicator s f x ∂μ = ∫ x in s, f x ∂μ := by
by_cases hfi : IntegrableOn f s μ; swap
· rw [integral_undef hfi, integral_undef]
rwa [integrable_indicator_iff hs]
calc
∫ x, indicator s f x ∂μ = ∫ x in s, indicator s f x ∂μ + ∫ x in sᶜ, indicator s f x ∂μ :=
(integral_add_compl hs (hfi.integrable_indicator hs)).symm
_ = ∫ x in s, f x ∂μ + ∫ x in sᶜ, 0 ∂μ :=
(congr_arg₂ (· + ·) (integral_congr_ae (indicator_ae_eq_restrict hs))
(integral_congr_ae (indicator_ae_eq_restrict_compl hs)))
_ = ∫ x in s, f x ∂μ := by simp
#align measure_theory.integral_indicator MeasureTheory.integral_indicator
theorem setIntegral_indicator (ht : MeasurableSet t) :
∫ x in s, t.indicator f x ∂μ = ∫ x in s ∩ t, f x ∂μ := by
rw [integral_indicator ht, Measure.restrict_restrict ht, Set.inter_comm]
#align measure_theory.set_integral_indicator MeasureTheory.setIntegral_indicator
@[deprecated (since := "2024-04-17")]
alias set_integral_indicator := setIntegral_indicator
theorem ofReal_setIntegral_one_of_measure_ne_top {X : Type*} {m : MeasurableSpace X}
{μ : Measure X} {s : Set X} (hs : μ s ≠ ∞) : ENNReal.ofReal (∫ _ in s, (1 : ℝ) ∂μ) = μ s :=
calc
ENNReal.ofReal (∫ _ in s, (1 : ℝ) ∂μ) = ENNReal.ofReal (∫ _ in s, ‖(1 : ℝ)‖ ∂μ) := by
simp only [norm_one]
_ = ∫⁻ _ in s, 1 ∂μ := by
rw [ofReal_integral_norm_eq_lintegral_nnnorm (integrableOn_const.2 (Or.inr hs.lt_top))]
simp only [nnnorm_one, ENNReal.coe_one]
_ = μ s := set_lintegral_one _
#align measure_theory.of_real_set_integral_one_of_measure_ne_top MeasureTheory.ofReal_setIntegral_one_of_measure_ne_top
@[deprecated (since := "2024-04-17")]
alias ofReal_set_integral_one_of_measure_ne_top := ofReal_setIntegral_one_of_measure_ne_top
theorem ofReal_setIntegral_one {X : Type*} {_ : MeasurableSpace X} (μ : Measure X)
[IsFiniteMeasure μ] (s : Set X) : ENNReal.ofReal (∫ _ in s, (1 : ℝ) ∂μ) = μ s :=
ofReal_setIntegral_one_of_measure_ne_top (measure_ne_top μ s)
#align measure_theory.of_real_set_integral_one MeasureTheory.ofReal_setIntegral_one
@[deprecated (since := "2024-04-17")]
alias ofReal_set_integral_one := ofReal_setIntegral_one
theorem integral_piecewise [DecidablePred (· ∈ s)] (hs : MeasurableSet s) (hf : IntegrableOn f s μ)
(hg : IntegrableOn g sᶜ μ) :
∫ x, s.piecewise f g x ∂μ = ∫ x in s, f x ∂μ + ∫ x in sᶜ, g x ∂μ := by
rw [← Set.indicator_add_compl_eq_piecewise,
integral_add' (hf.integrable_indicator hs) (hg.integrable_indicator hs.compl),
integral_indicator hs, integral_indicator hs.compl]
#align measure_theory.integral_piecewise MeasureTheory.integral_piecewise
theorem tendsto_setIntegral_of_monotone {ι : Type*} [Countable ι] [SemilatticeSup ι]
{s : ι → Set X} (hsm : ∀ i, MeasurableSet (s i)) (h_mono : Monotone s)
(hfi : IntegrableOn f (⋃ n, s n) μ) :
Tendsto (fun i => ∫ x in s i, f x ∂μ) atTop (𝓝 (∫ x in ⋃ n, s n, f x ∂μ)) := by
have hfi' : ∫⁻ x in ⋃ n, s n, ‖f x‖₊ ∂μ < ∞ := hfi.2
set S := ⋃ i, s i
have hSm : MeasurableSet S := MeasurableSet.iUnion hsm
have hsub : ∀ {i}, s i ⊆ S := @(subset_iUnion s)
rw [← withDensity_apply _ hSm] at hfi'
set ν := μ.withDensity fun x => ‖f x‖₊ with hν
refine Metric.nhds_basis_closedBall.tendsto_right_iff.2 fun ε ε0 => ?_
lift ε to ℝ≥0 using ε0.le
have : ∀ᶠ i in atTop, ν (s i) ∈ Icc (ν S - ε) (ν S + ε) :=
tendsto_measure_iUnion h_mono (ENNReal.Icc_mem_nhds hfi'.ne (ENNReal.coe_pos.2 ε0).ne')
filter_upwards [this] with i hi
rw [mem_closedBall_iff_norm', ← integral_diff (hsm i) hfi hsub, ← coe_nnnorm, NNReal.coe_le_coe, ←
ENNReal.coe_le_coe]
refine (ennnorm_integral_le_lintegral_ennnorm _).trans ?_
rw [← withDensity_apply _ (hSm.diff (hsm _)), ← hν, measure_diff hsub (hsm _)]
exacts [tsub_le_iff_tsub_le.mp hi.1,
(hi.2.trans_lt <| ENNReal.add_lt_top.2 ⟨hfi', ENNReal.coe_lt_top⟩).ne]
#align measure_theory.tendsto_set_integral_of_monotone MeasureTheory.tendsto_setIntegral_of_monotone
@[deprecated (since := "2024-04-17")]
alias tendsto_set_integral_of_monotone := tendsto_setIntegral_of_monotone
theorem tendsto_setIntegral_of_antitone {ι : Type*} [Countable ι] [SemilatticeSup ι]
{s : ι → Set X} (hsm : ∀ i, MeasurableSet (s i)) (h_anti : Antitone s)
(hfi : ∃ i, IntegrableOn f (s i) μ) :
Tendsto (fun i ↦ ∫ x in s i, f x ∂μ) atTop (𝓝 (∫ x in ⋂ n, s n, f x ∂μ)) := by
set S := ⋂ i, s i
have hSm : MeasurableSet S := MeasurableSet.iInter hsm
have hsub i : S ⊆ s i := iInter_subset _ _
set ν := μ.withDensity fun x => ‖f x‖₊ with hν
refine Metric.nhds_basis_closedBall.tendsto_right_iff.2 fun ε ε0 => ?_
lift ε to ℝ≥0 using ε0.le
rcases hfi with ⟨i₀, hi₀⟩
have νi₀ : ν (s i₀) ≠ ∞ := by
simpa [hsm i₀, ν, ENNReal.ofReal, norm_toNNReal] using hi₀.norm.lintegral_lt_top.ne
have νS : ν S ≠ ∞ := ((measure_mono (hsub i₀)).trans_lt νi₀.lt_top).ne
have : ∀ᶠ i in atTop, ν (s i) ∈ Icc (ν S - ε) (ν S + ε) := by
apply tendsto_measure_iInter hsm h_anti ⟨i₀, νi₀⟩
apply ENNReal.Icc_mem_nhds νS (ENNReal.coe_pos.2 ε0).ne'
filter_upwards [this, Ici_mem_atTop i₀] with i hi h'i
rw [mem_closedBall_iff_norm, ← integral_diff hSm (hi₀.mono_set (h_anti h'i)) (hsub i),
← coe_nnnorm, NNReal.coe_le_coe, ← ENNReal.coe_le_coe]
refine (ennnorm_integral_le_lintegral_ennnorm _).trans ?_
rw [← withDensity_apply _ ((hsm _).diff hSm), ← hν, measure_diff (hsub i) hSm νS]
exact tsub_le_iff_left.2 hi.2
@[deprecated (since := "2024-04-17")]
alias tendsto_set_integral_of_antitone := tendsto_setIntegral_of_antitone
theorem hasSum_integral_iUnion_ae {ι : Type*} [Countable ι] {s : ι → Set X}
(hm : ∀ i, NullMeasurableSet (s i) μ) (hd : Pairwise (AEDisjoint μ on s))
(hfi : IntegrableOn f (⋃ i, s i) μ) :
HasSum (fun n => ∫ x in s n, f x ∂μ) (∫ x in ⋃ n, s n, f x ∂μ) := by
simp only [IntegrableOn, Measure.restrict_iUnion_ae hd hm] at hfi ⊢
exact hasSum_integral_measure hfi
#align measure_theory.has_sum_integral_Union_ae MeasureTheory.hasSum_integral_iUnion_ae
theorem hasSum_integral_iUnion {ι : Type*} [Countable ι] {s : ι → Set X}
(hm : ∀ i, MeasurableSet (s i)) (hd : Pairwise (Disjoint on s))
(hfi : IntegrableOn f (⋃ i, s i) μ) :
HasSum (fun n => ∫ x in s n, f x ∂μ) (∫ x in ⋃ n, s n, f x ∂μ) :=
hasSum_integral_iUnion_ae (fun i => (hm i).nullMeasurableSet) (hd.mono fun _ _ h => h.aedisjoint)
hfi
#align measure_theory.has_sum_integral_Union MeasureTheory.hasSum_integral_iUnion
theorem integral_iUnion {ι : Type*} [Countable ι] {s : ι → Set X} (hm : ∀ i, MeasurableSet (s i))
(hd : Pairwise (Disjoint on s)) (hfi : IntegrableOn f (⋃ i, s i) μ) :
∫ x in ⋃ n, s n, f x ∂μ = ∑' n, ∫ x in s n, f x ∂μ :=
(HasSum.tsum_eq (hasSum_integral_iUnion hm hd hfi)).symm
#align measure_theory.integral_Union MeasureTheory.integral_iUnion
theorem integral_iUnion_ae {ι : Type*} [Countable ι] {s : ι → Set X}
(hm : ∀ i, NullMeasurableSet (s i) μ) (hd : Pairwise (AEDisjoint μ on s))
(hfi : IntegrableOn f (⋃ i, s i) μ) : ∫ x in ⋃ n, s n, f x ∂μ = ∑' n, ∫ x in s n, f x ∂μ :=
(HasSum.tsum_eq (hasSum_integral_iUnion_ae hm hd hfi)).symm
#align measure_theory.integral_Union_ae MeasureTheory.integral_iUnion_ae
theorem setIntegral_eq_zero_of_ae_eq_zero (ht_eq : ∀ᵐ x ∂μ, x ∈ t → f x = 0) :
∫ x in t, f x ∂μ = 0 := by
by_cases hf : AEStronglyMeasurable f (μ.restrict t); swap
· rw [integral_undef]
contrapose! hf
exact hf.1
have : ∫ x in t, hf.mk f x ∂μ = 0 := by
refine integral_eq_zero_of_ae ?_
rw [EventuallyEq,
ae_restrict_iff (hf.stronglyMeasurable_mk.measurableSet_eq_fun stronglyMeasurable_zero)]
filter_upwards [ae_imp_of_ae_restrict hf.ae_eq_mk, ht_eq] with x hx h'x h''x
rw [← hx h''x]
exact h'x h''x
rw [← this]
exact integral_congr_ae hf.ae_eq_mk
#align measure_theory.set_integral_eq_zero_of_ae_eq_zero MeasureTheory.setIntegral_eq_zero_of_ae_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_zero_of_ae_eq_zero := setIntegral_eq_zero_of_ae_eq_zero
theorem setIntegral_eq_zero_of_forall_eq_zero (ht_eq : ∀ x ∈ t, f x = 0) :
∫ x in t, f x ∂μ = 0 :=
setIntegral_eq_zero_of_ae_eq_zero (eventually_of_forall ht_eq)
#align measure_theory.set_integral_eq_zero_of_forall_eq_zero MeasureTheory.setIntegral_eq_zero_of_forall_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_zero_of_forall_eq_zero := setIntegral_eq_zero_of_forall_eq_zero
theorem integral_union_eq_left_of_ae_aux (ht_eq : ∀ᵐ x ∂μ.restrict t, f x = 0)
(haux : StronglyMeasurable f) (H : IntegrableOn f (s ∪ t) μ) :
∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ := by
let k := f ⁻¹' {0}
have hk : MeasurableSet k := by borelize E; exact haux.measurable (measurableSet_singleton _)
have h's : IntegrableOn f s μ := H.mono subset_union_left le_rfl
have A : ∀ u : Set X, ∫ x in u ∩ k, f x ∂μ = 0 := fun u =>
setIntegral_eq_zero_of_forall_eq_zero fun x hx => hx.2
rw [← integral_inter_add_diff hk h's, ← integral_inter_add_diff hk H, A, A, zero_add, zero_add,
union_diff_distrib, union_comm]
apply setIntegral_congr_set_ae
rw [union_ae_eq_right]
apply measure_mono_null diff_subset
rw [measure_zero_iff_ae_nmem]
filter_upwards [ae_imp_of_ae_restrict ht_eq] with x hx h'x using h'x.2 (hx h'x.1)
#align measure_theory.integral_union_eq_left_of_ae_aux MeasureTheory.integral_union_eq_left_of_ae_aux
theorem integral_union_eq_left_of_ae (ht_eq : ∀ᵐ x ∂μ.restrict t, f x = 0) :
∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ := by
have ht : IntegrableOn f t μ := by apply integrableOn_zero.congr_fun_ae; symm; exact ht_eq
by_cases H : IntegrableOn f (s ∪ t) μ; swap
· rw [integral_undef H, integral_undef]; simpa [integrableOn_union, ht] using H
let f' := H.1.mk f
calc
∫ x : X in s ∪ t, f x ∂μ = ∫ x : X in s ∪ t, f' x ∂μ := integral_congr_ae H.1.ae_eq_mk
_ = ∫ x in s, f' x ∂μ := by
apply
integral_union_eq_left_of_ae_aux _ H.1.stronglyMeasurable_mk (H.congr_fun_ae H.1.ae_eq_mk)
filter_upwards [ht_eq,
ae_mono (Measure.restrict_mono subset_union_right le_rfl) H.1.ae_eq_mk] with x hx h'x
rw [← h'x, hx]
_ = ∫ x in s, f x ∂μ :=
integral_congr_ae
(ae_mono (Measure.restrict_mono subset_union_left le_rfl) H.1.ae_eq_mk.symm)
#align measure_theory.integral_union_eq_left_of_ae MeasureTheory.integral_union_eq_left_of_ae
theorem integral_union_eq_left_of_forall₀ {f : X → E} (ht : NullMeasurableSet t μ)
(ht_eq : ∀ x ∈ t, f x = 0) : ∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ :=
integral_union_eq_left_of_ae ((ae_restrict_iff'₀ ht).2 (eventually_of_forall ht_eq))
#align measure_theory.integral_union_eq_left_of_forall₀ MeasureTheory.integral_union_eq_left_of_forall₀
theorem integral_union_eq_left_of_forall {f : X → E} (ht : MeasurableSet t)
(ht_eq : ∀ x ∈ t, f x = 0) : ∫ x in s ∪ t, f x ∂μ = ∫ x in s, f x ∂μ :=
integral_union_eq_left_of_forall₀ ht.nullMeasurableSet ht_eq
#align measure_theory.integral_union_eq_left_of_forall MeasureTheory.integral_union_eq_left_of_forall
theorem setIntegral_eq_of_subset_of_ae_diff_eq_zero_aux (hts : s ⊆ t)
(h't : ∀ᵐ x ∂μ, x ∈ t \ s → f x = 0) (haux : StronglyMeasurable f)
(h'aux : IntegrableOn f t μ) : ∫ x in t, f x ∂μ = ∫ x in s, f x ∂μ := by
let k := f ⁻¹' {0}
have hk : MeasurableSet k := by borelize E; exact haux.measurable (measurableSet_singleton _)
calc
∫ x in t, f x ∂μ = ∫ x in t ∩ k, f x ∂μ + ∫ x in t \ k, f x ∂μ := by
rw [integral_inter_add_diff hk h'aux]
_ = ∫ x in t \ k, f x ∂μ := by
rw [setIntegral_eq_zero_of_forall_eq_zero fun x hx => ?_, zero_add]; exact hx.2
_ = ∫ x in s \ k, f x ∂μ := by
apply setIntegral_congr_set_ae
filter_upwards [h't] with x hx
change (x ∈ t \ k) = (x ∈ s \ k)
simp only [mem_preimage, mem_singleton_iff, eq_iff_iff, and_congr_left_iff, mem_diff]
intro h'x
by_cases xs : x ∈ s
· simp only [xs, hts xs]
· simp only [xs, iff_false_iff]
intro xt
exact h'x (hx ⟨xt, xs⟩)
_ = ∫ x in s ∩ k, f x ∂μ + ∫ x in s \ k, f x ∂μ := by
have : ∀ x ∈ s ∩ k, f x = 0 := fun x hx => hx.2
rw [setIntegral_eq_zero_of_forall_eq_zero this, zero_add]
_ = ∫ x in s, f x ∂μ := by rw [integral_inter_add_diff hk (h'aux.mono hts le_rfl)]
#align measure_theory.set_integral_eq_of_subset_of_ae_diff_eq_zero_aux MeasureTheory.setIntegral_eq_of_subset_of_ae_diff_eq_zero_aux
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_of_subset_of_ae_diff_eq_zero_aux :=
setIntegral_eq_of_subset_of_ae_diff_eq_zero_aux
/-- If a function vanishes almost everywhere on `t \ s` with `s ⊆ t`, then its integrals on `s`
and `t` coincide if `t` is null-measurable. -/
theorem setIntegral_eq_of_subset_of_ae_diff_eq_zero (ht : NullMeasurableSet t μ) (hts : s ⊆ t)
(h't : ∀ᵐ x ∂μ, x ∈ t \ s → f x = 0) : ∫ x in t, f x ∂μ = ∫ x in s, f x ∂μ := by
by_cases h : IntegrableOn f t μ; swap
· have : ¬IntegrableOn f s μ := fun H => h (H.of_ae_diff_eq_zero ht h't)
rw [integral_undef h, integral_undef this]
let f' := h.1.mk f
calc
∫ x in t, f x ∂μ = ∫ x in t, f' x ∂μ := integral_congr_ae h.1.ae_eq_mk
_ = ∫ x in s, f' x ∂μ := by
apply
setIntegral_eq_of_subset_of_ae_diff_eq_zero_aux hts _ h.1.stronglyMeasurable_mk
(h.congr h.1.ae_eq_mk)
filter_upwards [h't, ae_imp_of_ae_restrict h.1.ae_eq_mk] with x hx h'x h''x
rw [← h'x h''x.1, hx h''x]
_ = ∫ x in s, f x ∂μ := by
apply integral_congr_ae
apply ae_restrict_of_ae_restrict_of_subset hts
exact h.1.ae_eq_mk.symm
#align measure_theory.set_integral_eq_of_subset_of_ae_diff_eq_zero MeasureTheory.setIntegral_eq_of_subset_of_ae_diff_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_of_subset_of_ae_diff_eq_zero := setIntegral_eq_of_subset_of_ae_diff_eq_zero
/-- If a function vanishes on `t \ s` with `s ⊆ t`, then its integrals on `s`
and `t` coincide if `t` is measurable. -/
theorem setIntegral_eq_of_subset_of_forall_diff_eq_zero (ht : MeasurableSet t) (hts : s ⊆ t)
(h't : ∀ x ∈ t \ s, f x = 0) : ∫ x in t, f x ∂μ = ∫ x in s, f x ∂μ :=
setIntegral_eq_of_subset_of_ae_diff_eq_zero ht.nullMeasurableSet hts
(eventually_of_forall fun x hx => h't x hx)
#align measure_theory.set_integral_eq_of_subset_of_forall_diff_eq_zero MeasureTheory.setIntegral_eq_of_subset_of_forall_diff_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_of_subset_of_forall_diff_eq_zero :=
setIntegral_eq_of_subset_of_forall_diff_eq_zero
/-- If a function vanishes almost everywhere on `sᶜ`, then its integral on `s`
coincides with its integral on the whole space. -/
theorem setIntegral_eq_integral_of_ae_compl_eq_zero (h : ∀ᵐ x ∂μ, x ∉ s → f x = 0) :
∫ x in s, f x ∂μ = ∫ x, f x ∂μ := by
symm
nth_rw 1 [← integral_univ]
apply setIntegral_eq_of_subset_of_ae_diff_eq_zero nullMeasurableSet_univ (subset_univ _)
filter_upwards [h] with x hx h'x using hx h'x.2
#align measure_theory.set_integral_eq_integral_of_ae_compl_eq_zero MeasureTheory.setIntegral_eq_integral_of_ae_compl_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_integral_of_ae_compl_eq_zero := setIntegral_eq_integral_of_ae_compl_eq_zero
/-- If a function vanishes on `sᶜ`, then its integral on `s` coincides with its integral on the
whole space. -/
theorem setIntegral_eq_integral_of_forall_compl_eq_zero (h : ∀ x, x ∉ s → f x = 0) :
∫ x in s, f x ∂μ = ∫ x, f x ∂μ :=
setIntegral_eq_integral_of_ae_compl_eq_zero (eventually_of_forall h)
#align measure_theory.set_integral_eq_integral_of_forall_compl_eq_zero MeasureTheory.setIntegral_eq_integral_of_forall_compl_eq_zero
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_integral_of_forall_compl_eq_zero :=
setIntegral_eq_integral_of_forall_compl_eq_zero
theorem setIntegral_neg_eq_setIntegral_nonpos [LinearOrder E] {f : X → E}
(hf : AEStronglyMeasurable f μ) :
∫ x in {x | f x < 0}, f x ∂μ = ∫ x in {x | f x ≤ 0}, f x ∂μ := by
have h_union : {x | f x ≤ 0} = {x | f x < 0} ∪ {x | f x = 0} := by
simp_rw [le_iff_lt_or_eq, setOf_or]
rw [h_union]
have B : NullMeasurableSet {x | f x = 0} μ :=
hf.nullMeasurableSet_eq_fun aestronglyMeasurable_zero
symm
refine integral_union_eq_left_of_ae ?_
filter_upwards [ae_restrict_mem₀ B] with x hx using hx
#align measure_theory.set_integral_neg_eq_set_integral_nonpos MeasureTheory.setIntegral_neg_eq_setIntegral_nonpos
@[deprecated (since := "2024-04-17")]
alias set_integral_neg_eq_set_integral_nonpos := setIntegral_neg_eq_setIntegral_nonpos
theorem integral_norm_eq_pos_sub_neg {f : X → ℝ} (hfi : Integrable f μ) :
∫ x, ‖f x‖ ∂μ = ∫ x in {x | 0 ≤ f x}, f x ∂μ - ∫ x in {x | f x ≤ 0}, f x ∂μ :=
have h_meas : NullMeasurableSet {x | 0 ≤ f x} μ :=
aestronglyMeasurable_const.nullMeasurableSet_le hfi.1
calc
∫ x, ‖f x‖ ∂μ = ∫ x in {x | 0 ≤ f x}, ‖f x‖ ∂μ + ∫ x in {x | 0 ≤ f x}ᶜ, ‖f x‖ ∂μ := by
rw [← integral_add_compl₀ h_meas hfi.norm]
_ = ∫ x in {x | 0 ≤ f x}, f x ∂μ + ∫ x in {x | 0 ≤ f x}ᶜ, ‖f x‖ ∂μ := by
congr 1
refine setIntegral_congr₀ h_meas fun x hx => ?_
dsimp only
rw [Real.norm_eq_abs, abs_eq_self.mpr _]
exact hx
_ = ∫ x in {x | 0 ≤ f x}, f x ∂μ - ∫ x in {x | 0 ≤ f x}ᶜ, f x ∂μ := by
congr 1
rw [← integral_neg]
refine setIntegral_congr₀ h_meas.compl fun x hx => ?_
dsimp only
rw [Real.norm_eq_abs, abs_eq_neg_self.mpr _]
rw [Set.mem_compl_iff, Set.nmem_setOf_iff] at hx
linarith
_ = ∫ x in {x | 0 ≤ f x}, f x ∂μ - ∫ x in {x | f x ≤ 0}, f x ∂μ := by
rw [← setIntegral_neg_eq_setIntegral_nonpos hfi.1, compl_setOf]; simp only [not_le]
#align measure_theory.integral_norm_eq_pos_sub_neg MeasureTheory.integral_norm_eq_pos_sub_neg
theorem setIntegral_const [CompleteSpace E] (c : E) : ∫ _ in s, c ∂μ = (μ s).toReal • c := by
rw [integral_const, Measure.restrict_apply_univ]
#align measure_theory.set_integral_const MeasureTheory.setIntegral_const
@[deprecated (since := "2024-04-17")]
alias set_integral_const := setIntegral_const
@[simp]
theorem integral_indicator_const [CompleteSpace E] (e : E) ⦃s : Set X⦄ (s_meas : MeasurableSet s) :
∫ x : X, s.indicator (fun _ : X => e) x ∂μ = (μ s).toReal • e := by
rw [integral_indicator s_meas, ← setIntegral_const]
#align measure_theory.integral_indicator_const MeasureTheory.integral_indicator_const
@[simp]
theorem integral_indicator_one ⦃s : Set X⦄ (hs : MeasurableSet s) :
∫ x, s.indicator 1 x ∂μ = (μ s).toReal :=
(integral_indicator_const 1 hs).trans ((smul_eq_mul _).trans (mul_one _))
#align measure_theory.integral_indicator_one MeasureTheory.integral_indicator_one
theorem setIntegral_indicatorConstLp [CompleteSpace E]
{p : ℝ≥0∞} (hs : MeasurableSet s) (ht : MeasurableSet t) (hμt : μ t ≠ ∞) (e : E) :
∫ x in s, indicatorConstLp p ht hμt e x ∂μ = (μ (t ∩ s)).toReal • e :=
calc
∫ x in s, indicatorConstLp p ht hμt e x ∂μ = ∫ x in s, t.indicator (fun _ => e) x ∂μ := by
rw [setIntegral_congr_ae hs (indicatorConstLp_coeFn.mono fun x hx _ => hx)]
_ = (μ (t ∩ s)).toReal • e := by rw [integral_indicator_const _ ht, Measure.restrict_apply ht]
set_option linter.uppercaseLean3 false in
#align measure_theory.set_integral_indicator_const_Lp MeasureTheory.setIntegral_indicatorConstLp
@[deprecated (since := "2024-04-17")]
alias set_integral_indicatorConstLp := setIntegral_indicatorConstLp
theorem integral_indicatorConstLp [CompleteSpace E]
{p : ℝ≥0∞} (ht : MeasurableSet t) (hμt : μ t ≠ ∞) (e : E) :
∫ x, indicatorConstLp p ht hμt e x ∂μ = (μ t).toReal • e :=
calc
∫ x, indicatorConstLp p ht hμt e x ∂μ = ∫ x in univ, indicatorConstLp p ht hμt e x ∂μ := by
rw [integral_univ]
_ = (μ (t ∩ univ)).toReal • e := setIntegral_indicatorConstLp MeasurableSet.univ ht hμt e
_ = (μ t).toReal • e := by rw [inter_univ]
set_option linter.uppercaseLean3 false in
#align measure_theory.integral_indicator_const_Lp MeasureTheory.integral_indicatorConstLp
theorem setIntegral_map {Y} [MeasurableSpace Y] {g : X → Y} {f : Y → E} {s : Set Y}
(hs : MeasurableSet s) (hf : AEStronglyMeasurable f (Measure.map g μ)) (hg : AEMeasurable g μ) :
∫ y in s, f y ∂Measure.map g μ = ∫ x in g ⁻¹' s, f (g x) ∂μ := by
rw [Measure.restrict_map_of_aemeasurable hg hs,
integral_map (hg.mono_measure Measure.restrict_le_self) (hf.mono_measure _)]
exact Measure.map_mono_of_aemeasurable Measure.restrict_le_self hg
#align measure_theory.set_integral_map MeasureTheory.setIntegral_map
@[deprecated (since := "2024-04-17")]
alias set_integral_map := setIntegral_map
theorem _root_.MeasurableEmbedding.setIntegral_map {Y} {_ : MeasurableSpace Y} {f : X → Y}
(hf : MeasurableEmbedding f) (g : Y → E) (s : Set Y) :
∫ y in s, g y ∂Measure.map f μ = ∫ x in f ⁻¹' s, g (f x) ∂μ := by
rw [hf.restrict_map, hf.integral_map]
#align measurable_embedding.set_integral_map MeasurableEmbedding.setIntegral_map
@[deprecated (since := "2024-04-17")]
alias _root_.MeasurableEmbedding.set_integral_map := _root_.MeasurableEmbedding.setIntegral_map
theorem _root_.ClosedEmbedding.setIntegral_map [TopologicalSpace X] [BorelSpace X] {Y}
[MeasurableSpace Y] [TopologicalSpace Y] [BorelSpace Y] {g : X → Y} {f : Y → E} (s : Set Y)
(hg : ClosedEmbedding g) : ∫ y in s, f y ∂Measure.map g μ = ∫ x in g ⁻¹' s, f (g x) ∂μ :=
hg.measurableEmbedding.setIntegral_map _ _
#align closed_embedding.set_integral_map ClosedEmbedding.setIntegral_map
@[deprecated (since := "2024-04-17")]
alias _root_.ClosedEmbedding.set_integral_map := _root_.ClosedEmbedding.setIntegral_map
theorem MeasurePreserving.setIntegral_preimage_emb {Y} {_ : MeasurableSpace Y} {f : X → Y} {ν}
(h₁ : MeasurePreserving f μ ν) (h₂ : MeasurableEmbedding f) (g : Y → E) (s : Set Y) :
∫ x in f ⁻¹' s, g (f x) ∂μ = ∫ y in s, g y ∂ν :=
(h₁.restrict_preimage_emb h₂ s).integral_comp h₂ _
#align measure_theory.measure_preserving.set_integral_preimage_emb MeasureTheory.MeasurePreserving.setIntegral_preimage_emb
@[deprecated (since := "2024-04-17")]
alias MeasurePreserving.set_integral_preimage_emb := MeasurePreserving.setIntegral_preimage_emb
theorem MeasurePreserving.setIntegral_image_emb {Y} {_ : MeasurableSpace Y} {f : X → Y} {ν}
(h₁ : MeasurePreserving f μ ν) (h₂ : MeasurableEmbedding f) (g : Y → E) (s : Set X) :
∫ y in f '' s, g y ∂ν = ∫ x in s, g (f x) ∂μ :=
Eq.symm <| (h₁.restrict_image_emb h₂ s).integral_comp h₂ _
#align measure_theory.measure_preserving.set_integral_image_emb MeasureTheory.MeasurePreserving.setIntegral_image_emb
@[deprecated (since := "2024-04-17")]
alias MeasurePreserving.set_integral_image_emb := MeasurePreserving.setIntegral_image_emb
theorem setIntegral_map_equiv {Y} [MeasurableSpace Y] (e : X ≃ᵐ Y) (f : Y → E) (s : Set Y) :
∫ y in s, f y ∂Measure.map e μ = ∫ x in e ⁻¹' s, f (e x) ∂μ :=
e.measurableEmbedding.setIntegral_map f s
#align measure_theory.set_integral_map_equiv MeasureTheory.setIntegral_map_equiv
@[deprecated (since := "2024-04-17")]
alias set_integral_map_equiv := setIntegral_map_equiv
theorem norm_setIntegral_le_of_norm_le_const_ae {C : ℝ} (hs : μ s < ∞)
(hC : ∀ᵐ x ∂μ.restrict s, ‖f x‖ ≤ C) : ‖∫ x in s, f x ∂μ‖ ≤ C * (μ s).toReal := by
rw [← Measure.restrict_apply_univ] at *
haveI : IsFiniteMeasure (μ.restrict s) := ⟨hs⟩
exact norm_integral_le_of_norm_le_const hC
#align measure_theory.norm_set_integral_le_of_norm_le_const_ae MeasureTheory.norm_setIntegral_le_of_norm_le_const_ae
@[deprecated (since := "2024-04-17")]
alias norm_set_integral_le_of_norm_le_const_ae := norm_setIntegral_le_of_norm_le_const_ae
theorem norm_setIntegral_le_of_norm_le_const_ae' {C : ℝ} (hs : μ s < ∞)
(hC : ∀ᵐ x ∂μ, x ∈ s → ‖f x‖ ≤ C) (hfm : AEStronglyMeasurable f (μ.restrict s)) :
‖∫ x in s, f x ∂μ‖ ≤ C * (μ s).toReal := by
apply norm_setIntegral_le_of_norm_le_const_ae hs
have A : ∀ᵐ x : X ∂μ, x ∈ s → ‖AEStronglyMeasurable.mk f hfm x‖ ≤ C := by
filter_upwards [hC, hfm.ae_mem_imp_eq_mk] with _ h1 h2 h3
rw [← h2 h3]
exact h1 h3
have B : MeasurableSet {x | ‖hfm.mk f x‖ ≤ C} :=
hfm.stronglyMeasurable_mk.norm.measurable measurableSet_Iic
filter_upwards [hfm.ae_eq_mk, (ae_restrict_iff B).2 A] with _ h1 _
rwa [h1]
#align measure_theory.norm_set_integral_le_of_norm_le_const_ae' MeasureTheory.norm_setIntegral_le_of_norm_le_const_ae'
@[deprecated (since := "2024-04-17")]
alias norm_set_integral_le_of_norm_le_const_ae' := norm_setIntegral_le_of_norm_le_const_ae'
theorem norm_setIntegral_le_of_norm_le_const_ae'' {C : ℝ} (hs : μ s < ∞) (hsm : MeasurableSet s)
(hC : ∀ᵐ x ∂μ, x ∈ s → ‖f x‖ ≤ C) : ‖∫ x in s, f x ∂μ‖ ≤ C * (μ s).toReal :=
norm_setIntegral_le_of_norm_le_const_ae hs <| by
rwa [ae_restrict_eq hsm, eventually_inf_principal]
#align measure_theory.norm_set_integral_le_of_norm_le_const_ae'' MeasureTheory.norm_setIntegral_le_of_norm_le_const_ae''
@[deprecated (since := "2024-04-17")]
alias norm_set_integral_le_of_norm_le_const_ae'' := norm_setIntegral_le_of_norm_le_const_ae''
theorem norm_setIntegral_le_of_norm_le_const {C : ℝ} (hs : μ s < ∞) (hC : ∀ x ∈ s, ‖f x‖ ≤ C)
(hfm : AEStronglyMeasurable f (μ.restrict s)) : ‖∫ x in s, f x ∂μ‖ ≤ C * (μ s).toReal :=
norm_setIntegral_le_of_norm_le_const_ae' hs (eventually_of_forall hC) hfm
#align measure_theory.norm_set_integral_le_of_norm_le_const MeasureTheory.norm_setIntegral_le_of_norm_le_const
@[deprecated (since := "2024-04-17")]
alias norm_set_integral_le_of_norm_le_const := norm_setIntegral_le_of_norm_le_const
theorem norm_setIntegral_le_of_norm_le_const' {C : ℝ} (hs : μ s < ∞) (hsm : MeasurableSet s)
(hC : ∀ x ∈ s, ‖f x‖ ≤ C) : ‖∫ x in s, f x ∂μ‖ ≤ C * (μ s).toReal :=
norm_setIntegral_le_of_norm_le_const_ae'' hs hsm <| eventually_of_forall hC
#align measure_theory.norm_set_integral_le_of_norm_le_const' MeasureTheory.norm_setIntegral_le_of_norm_le_const'
@[deprecated (since := "2024-04-17")]
alias norm_set_integral_le_of_norm_le_const' := norm_setIntegral_le_of_norm_le_const'
theorem setIntegral_eq_zero_iff_of_nonneg_ae {f : X → ℝ} (hf : 0 ≤ᵐ[μ.restrict s] f)
(hfi : IntegrableOn f s μ) : ∫ x in s, f x ∂μ = 0 ↔ f =ᵐ[μ.restrict s] 0 :=
integral_eq_zero_iff_of_nonneg_ae hf hfi
#align measure_theory.set_integral_eq_zero_iff_of_nonneg_ae MeasureTheory.setIntegral_eq_zero_iff_of_nonneg_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_eq_zero_iff_of_nonneg_ae := setIntegral_eq_zero_iff_of_nonneg_ae
theorem setIntegral_pos_iff_support_of_nonneg_ae {f : X → ℝ} (hf : 0 ≤ᵐ[μ.restrict s] f)
(hfi : IntegrableOn f s μ) : (0 < ∫ x in s, f x ∂μ) ↔ 0 < μ (support f ∩ s) := by
rw [integral_pos_iff_support_of_nonneg_ae hf hfi, Measure.restrict_apply₀]
rw [support_eq_preimage]
exact hfi.aestronglyMeasurable.aemeasurable.nullMeasurable (measurableSet_singleton 0).compl
#align measure_theory.set_integral_pos_iff_support_of_nonneg_ae MeasureTheory.setIntegral_pos_iff_support_of_nonneg_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_pos_iff_support_of_nonneg_ae := setIntegral_pos_iff_support_of_nonneg_ae
theorem setIntegral_gt_gt {R : ℝ} {f : X → ℝ} (hR : 0 ≤ R) (hfm : Measurable f)
(hfint : IntegrableOn f {x | ↑R < f x} μ) (hμ : μ {x | ↑R < f x} ≠ 0) :
(μ {x | ↑R < f x}).toReal * R < ∫ x in {x | ↑R < f x}, f x ∂μ := by
have : IntegrableOn (fun _ => R) {x | ↑R < f x} μ := by
refine ⟨aestronglyMeasurable_const, lt_of_le_of_lt ?_ hfint.2⟩
refine
set_lintegral_mono (Measurable.nnnorm ?_).coe_nnreal_ennreal hfm.nnnorm.coe_nnreal_ennreal
fun x hx => ?_
· exact measurable_const
· simp only [ENNReal.coe_le_coe, Real.nnnorm_of_nonneg hR,
Real.nnnorm_of_nonneg (hR.trans <| le_of_lt hx), Subtype.mk_le_mk]
exact le_of_lt hx
rw [← sub_pos, ← smul_eq_mul, ← setIntegral_const, ← integral_sub hfint this,
setIntegral_pos_iff_support_of_nonneg_ae]
· rw [← zero_lt_iff] at hμ
rwa [Set.inter_eq_self_of_subset_right]
exact fun x hx => Ne.symm (ne_of_lt <| sub_pos.2 hx)
· rw [Pi.zero_def, EventuallyLE, ae_restrict_iff]
· exact eventually_of_forall fun x hx => sub_nonneg.2 <| le_of_lt hx
· exact measurableSet_le measurable_zero (hfm.sub measurable_const)
· exact Integrable.sub hfint this
#align measure_theory.set_integral_gt_gt MeasureTheory.setIntegral_gt_gt
@[deprecated (since := "2024-04-17")]
alias set_integral_gt_gt := setIntegral_gt_gt
theorem setIntegral_trim {X} {m m0 : MeasurableSpace X} {μ : Measure X} (hm : m ≤ m0) {f : X → E}
(hf_meas : StronglyMeasurable[m] f) {s : Set X} (hs : MeasurableSet[m] s) :
∫ x in s, f x ∂μ = ∫ x in s, f x ∂μ.trim hm := by
rwa [integral_trim hm hf_meas, restrict_trim hm μ]
#align measure_theory.set_integral_trim MeasureTheory.setIntegral_trim
@[deprecated (since := "2024-04-17")]
alias set_integral_trim := setIntegral_trim
/-! ### Lemmas about adding and removing interval boundaries
The primed lemmas take explicit arguments about the endpoint having zero measure, while the
unprimed ones use `[NoAtoms μ]`.
-/
section PartialOrder
variable [PartialOrder X] {x y : X}
theorem integral_Icc_eq_integral_Ioc' (hx : μ {x} = 0) :
∫ t in Icc x y, f t ∂μ = ∫ t in Ioc x y, f t ∂μ :=
setIntegral_congr_set_ae (Ioc_ae_eq_Icc' hx).symm
#align measure_theory.integral_Icc_eq_integral_Ioc' MeasureTheory.integral_Icc_eq_integral_Ioc'
theorem integral_Icc_eq_integral_Ico' (hy : μ {y} = 0) :
∫ t in Icc x y, f t ∂μ = ∫ t in Ico x y, f t ∂μ :=
setIntegral_congr_set_ae (Ico_ae_eq_Icc' hy).symm
#align measure_theory.integral_Icc_eq_integral_Ico' MeasureTheory.integral_Icc_eq_integral_Ico'
theorem integral_Ioc_eq_integral_Ioo' (hy : μ {y} = 0) :
∫ t in Ioc x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ :=
setIntegral_congr_set_ae (Ioo_ae_eq_Ioc' hy).symm
#align measure_theory.integral_Ioc_eq_integral_Ioo' MeasureTheory.integral_Ioc_eq_integral_Ioo'
theorem integral_Ico_eq_integral_Ioo' (hx : μ {x} = 0) :
∫ t in Ico x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ :=
setIntegral_congr_set_ae (Ioo_ae_eq_Ico' hx).symm
#align measure_theory.integral_Ico_eq_integral_Ioo' MeasureTheory.integral_Ico_eq_integral_Ioo'
theorem integral_Icc_eq_integral_Ioo' (hx : μ {x} = 0) (hy : μ {y} = 0) :
∫ t in Icc x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ :=
setIntegral_congr_set_ae (Ioo_ae_eq_Icc' hx hy).symm
#align measure_theory.integral_Icc_eq_integral_Ioo' MeasureTheory.integral_Icc_eq_integral_Ioo'
theorem integral_Iic_eq_integral_Iio' (hx : μ {x} = 0) :
∫ t in Iic x, f t ∂μ = ∫ t in Iio x, f t ∂μ :=
setIntegral_congr_set_ae (Iio_ae_eq_Iic' hx).symm
#align measure_theory.integral_Iic_eq_integral_Iio' MeasureTheory.integral_Iic_eq_integral_Iio'
theorem integral_Ici_eq_integral_Ioi' (hx : μ {x} = 0) :
∫ t in Ici x, f t ∂μ = ∫ t in Ioi x, f t ∂μ :=
setIntegral_congr_set_ae (Ioi_ae_eq_Ici' hx).symm
#align measure_theory.integral_Ici_eq_integral_Ioi' MeasureTheory.integral_Ici_eq_integral_Ioi'
variable [NoAtoms μ]
theorem integral_Icc_eq_integral_Ioc : ∫ t in Icc x y, f t ∂μ = ∫ t in Ioc x y, f t ∂μ :=
integral_Icc_eq_integral_Ioc' <| measure_singleton x
#align measure_theory.integral_Icc_eq_integral_Ioc MeasureTheory.integral_Icc_eq_integral_Ioc
theorem integral_Icc_eq_integral_Ico : ∫ t in Icc x y, f t ∂μ = ∫ t in Ico x y, f t ∂μ :=
integral_Icc_eq_integral_Ico' <| measure_singleton y
#align measure_theory.integral_Icc_eq_integral_Ico MeasureTheory.integral_Icc_eq_integral_Ico
theorem integral_Ioc_eq_integral_Ioo : ∫ t in Ioc x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ :=
integral_Ioc_eq_integral_Ioo' <| measure_singleton y
#align measure_theory.integral_Ioc_eq_integral_Ioo MeasureTheory.integral_Ioc_eq_integral_Ioo
theorem integral_Ico_eq_integral_Ioo : ∫ t in Ico x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ :=
integral_Ico_eq_integral_Ioo' <| measure_singleton x
#align measure_theory.integral_Ico_eq_integral_Ioo MeasureTheory.integral_Ico_eq_integral_Ioo
theorem integral_Icc_eq_integral_Ioo : ∫ t in Icc x y, f t ∂μ = ∫ t in Ioo x y, f t ∂μ := by
rw [integral_Icc_eq_integral_Ico, integral_Ico_eq_integral_Ioo]
#align measure_theory.integral_Icc_eq_integral_Ioo MeasureTheory.integral_Icc_eq_integral_Ioo
theorem integral_Iic_eq_integral_Iio : ∫ t in Iic x, f t ∂μ = ∫ t in Iio x, f t ∂μ :=
integral_Iic_eq_integral_Iio' <| measure_singleton x
#align measure_theory.integral_Iic_eq_integral_Iio MeasureTheory.integral_Iic_eq_integral_Iio
theorem integral_Ici_eq_integral_Ioi : ∫ t in Ici x, f t ∂μ = ∫ t in Ioi x, f t ∂μ :=
integral_Ici_eq_integral_Ioi' <| measure_singleton x
#align measure_theory.integral_Ici_eq_integral_Ioi MeasureTheory.integral_Ici_eq_integral_Ioi
end PartialOrder
end NormedAddCommGroup
section Mono
variable {μ : Measure X} {f g : X → ℝ} {s t : Set X} (hf : IntegrableOn f s μ)
(hg : IntegrableOn g s μ)
theorem setIntegral_mono_ae_restrict (h : f ≤ᵐ[μ.restrict s] g) :
∫ x in s, f x ∂μ ≤ ∫ x in s, g x ∂μ :=
integral_mono_ae hf hg h
#align measure_theory.set_integral_mono_ae_restrict MeasureTheory.setIntegral_mono_ae_restrict
@[deprecated (since := "2024-04-17")]
alias set_integral_mono_ae_restrict := setIntegral_mono_ae_restrict
theorem setIntegral_mono_ae (h : f ≤ᵐ[μ] g) : ∫ x in s, f x ∂μ ≤ ∫ x in s, g x ∂μ :=
setIntegral_mono_ae_restrict hf hg (ae_restrict_of_ae h)
#align measure_theory.set_integral_mono_ae MeasureTheory.setIntegral_mono_ae
@[deprecated (since := "2024-04-17")]
alias set_integral_mono_ae := setIntegral_mono_ae
theorem setIntegral_mono_on (hs : MeasurableSet s) (h : ∀ x ∈ s, f x ≤ g x) :
∫ x in s, f x ∂μ ≤ ∫ x in s, g x ∂μ :=
setIntegral_mono_ae_restrict hf hg
(by simp [hs, EventuallyLE, eventually_inf_principal, ae_of_all _ h])
#align measure_theory.set_integral_mono_on MeasureTheory.setIntegral_mono_on
@[deprecated (since := "2024-04-17")]
alias set_integral_mono_on := setIntegral_mono_on
| Mathlib/MeasureTheory/Integral/SetIntegral.lean | 835 | 837 | theorem setIntegral_mono_on_ae (hs : MeasurableSet s) (h : ∀ᵐ x ∂μ, x ∈ s → f x ≤ g x) :
∫ x in s, f x ∂μ ≤ ∫ x in s, g x ∂μ := by |
refine setIntegral_mono_ae_restrict hf hg ?_; rwa [EventuallyLE, ae_restrict_iff' hs]
|
/-
Copyright (c) 2020 Frédéric Dupuis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Frédéric Dupuis
-/
import Mathlib.Data.Real.Sqrt
import Mathlib.Analysis.NormedSpace.Star.Basic
import Mathlib.Analysis.NormedSpace.ContinuousLinearMap
import Mathlib.Analysis.NormedSpace.Basic
#align_import data.is_R_or_C.basic from "leanprover-community/mathlib"@"baa88307f3e699fa7054ef04ec79fa4f056169cb"
/-!
# `RCLike`: a typeclass for ℝ or ℂ
This file defines the typeclass `RCLike` intended to have only two instances:
ℝ and ℂ. It is meant for definitions and theorems which hold for both the real and the complex case,
and in particular when the real case follows directly from the complex case by setting `re` to `id`,
`im` to zero and so on. Its API follows closely that of ℂ.
Applications include defining inner products and Hilbert spaces for both the real and
complex case. One typically produces the definitions and proof for an arbitrary field of this
typeclass, which basically amounts to doing the complex case, and the two cases then fall out
immediately from the two instances of the class.
The instance for `ℝ` is registered in this file.
The instance for `ℂ` is declared in `Mathlib/Analysis/Complex/Basic.lean`.
## Implementation notes
The coercion from reals into an `RCLike` field is done by registering `RCLike.ofReal` as
a `CoeTC`. For this to work, we must proceed carefully to avoid problems involving circular
coercions in the case `K=ℝ`; in particular, we cannot use the plain `Coe` and must set
priorities carefully. This problem was already solved for `ℕ`, and we copy the solution detailed
in `Mathlib/Data/Nat/Cast/Defs.lean`. See also Note [coercion into rings] for more details.
In addition, several lemmas need to be set at priority 900 to make sure that they do not override
their counterparts in `Mathlib/Analysis/Complex/Basic.lean` (which causes linter errors).
A few lemmas requiring heavier imports are in `Mathlib/Data/RCLike/Lemmas.lean`.
-/
section
local notation "𝓚" => algebraMap ℝ _
open ComplexConjugate
/--
This typeclass captures properties shared by ℝ and ℂ, with an API that closely matches that of ℂ.
-/
class RCLike (K : semiOutParam Type*) extends DenselyNormedField K, StarRing K,
NormedAlgebra ℝ K, CompleteSpace K where
re : K →+ ℝ
im : K →+ ℝ
/-- Imaginary unit in `K`. Meant to be set to `0` for `K = ℝ`. -/
I : K
I_re_ax : re I = 0
I_mul_I_ax : I = 0 ∨ I * I = -1
re_add_im_ax : ∀ z : K, 𝓚 (re z) + 𝓚 (im z) * I = z
ofReal_re_ax : ∀ r : ℝ, re (𝓚 r) = r
ofReal_im_ax : ∀ r : ℝ, im (𝓚 r) = 0
mul_re_ax : ∀ z w : K, re (z * w) = re z * re w - im z * im w
mul_im_ax : ∀ z w : K, im (z * w) = re z * im w + im z * re w
conj_re_ax : ∀ z : K, re (conj z) = re z
conj_im_ax : ∀ z : K, im (conj z) = -im z
conj_I_ax : conj I = -I
norm_sq_eq_def_ax : ∀ z : K, ‖z‖ ^ 2 = re z * re z + im z * im z
mul_im_I_ax : ∀ z : K, im z * im I = im z
/-- only an instance in the `ComplexOrder` locale -/
[toPartialOrder : PartialOrder K]
le_iff_re_im {z w : K} : z ≤ w ↔ re z ≤ re w ∧ im z = im w
-- note we cannot put this in the `extends` clause
[toDecidableEq : DecidableEq K]
#align is_R_or_C RCLike
scoped[ComplexOrder] attribute [instance 100] RCLike.toPartialOrder
attribute [instance 100] RCLike.toDecidableEq
end
variable {K E : Type*} [RCLike K]
namespace RCLike
open ComplexConjugate
/-- Coercion from `ℝ` to an `RCLike` field. -/
@[coe] abbrev ofReal : ℝ → K := Algebra.cast
/- The priority must be set at 900 to ensure that coercions are tried in the right order.
See Note [coercion into rings], or `Mathlib/Data/Nat/Cast/Basic.lean` for more details. -/
noncomputable instance (priority := 900) algebraMapCoe : CoeTC ℝ K :=
⟨ofReal⟩
#align is_R_or_C.algebra_map_coe RCLike.algebraMapCoe
theorem ofReal_alg (x : ℝ) : (x : K) = x • (1 : K) :=
Algebra.algebraMap_eq_smul_one x
#align is_R_or_C.of_real_alg RCLike.ofReal_alg
theorem real_smul_eq_coe_mul (r : ℝ) (z : K) : r • z = (r : K) * z :=
Algebra.smul_def r z
#align is_R_or_C.real_smul_eq_coe_mul RCLike.real_smul_eq_coe_mul
theorem real_smul_eq_coe_smul [AddCommGroup E] [Module K E] [Module ℝ E] [IsScalarTower ℝ K E]
(r : ℝ) (x : E) : r • x = (r : K) • x := by rw [RCLike.ofReal_alg, smul_one_smul]
#align is_R_or_C.real_smul_eq_coe_smul RCLike.real_smul_eq_coe_smul
theorem algebraMap_eq_ofReal : ⇑(algebraMap ℝ K) = ofReal :=
rfl
#align is_R_or_C.algebra_map_eq_of_real RCLike.algebraMap_eq_ofReal
@[simp, rclike_simps]
theorem re_add_im (z : K) : (re z : K) + im z * I = z :=
RCLike.re_add_im_ax z
#align is_R_or_C.re_add_im RCLike.re_add_im
@[simp, norm_cast, rclike_simps]
theorem ofReal_re : ∀ r : ℝ, re (r : K) = r :=
RCLike.ofReal_re_ax
#align is_R_or_C.of_real_re RCLike.ofReal_re
@[simp, norm_cast, rclike_simps]
theorem ofReal_im : ∀ r : ℝ, im (r : K) = 0 :=
RCLike.ofReal_im_ax
#align is_R_or_C.of_real_im RCLike.ofReal_im
@[simp, rclike_simps]
theorem mul_re : ∀ z w : K, re (z * w) = re z * re w - im z * im w :=
RCLike.mul_re_ax
#align is_R_or_C.mul_re RCLike.mul_re
@[simp, rclike_simps]
theorem mul_im : ∀ z w : K, im (z * w) = re z * im w + im z * re w :=
RCLike.mul_im_ax
#align is_R_or_C.mul_im RCLike.mul_im
theorem ext_iff {z w : K} : z = w ↔ re z = re w ∧ im z = im w :=
⟨fun h => h ▸ ⟨rfl, rfl⟩, fun ⟨h₁, h₂⟩ => re_add_im z ▸ re_add_im w ▸ h₁ ▸ h₂ ▸ rfl⟩
#align is_R_or_C.ext_iff RCLike.ext_iff
theorem ext {z w : K} (hre : re z = re w) (him : im z = im w) : z = w :=
ext_iff.2 ⟨hre, him⟩
#align is_R_or_C.ext RCLike.ext
@[norm_cast]
theorem ofReal_zero : ((0 : ℝ) : K) = 0 :=
algebraMap.coe_zero
#align is_R_or_C.of_real_zero RCLike.ofReal_zero
@[rclike_simps]
theorem zero_re' : re (0 : K) = (0 : ℝ) :=
map_zero re
#align is_R_or_C.zero_re' RCLike.zero_re'
@[norm_cast]
theorem ofReal_one : ((1 : ℝ) : K) = 1 :=
map_one (algebraMap ℝ K)
#align is_R_or_C.of_real_one RCLike.ofReal_one
@[simp, rclike_simps]
theorem one_re : re (1 : K) = 1 := by rw [← ofReal_one, ofReal_re]
#align is_R_or_C.one_re RCLike.one_re
@[simp, rclike_simps]
theorem one_im : im (1 : K) = 0 := by rw [← ofReal_one, ofReal_im]
#align is_R_or_C.one_im RCLike.one_im
theorem ofReal_injective : Function.Injective ((↑) : ℝ → K) :=
(algebraMap ℝ K).injective
#align is_R_or_C.of_real_injective RCLike.ofReal_injective
@[norm_cast]
theorem ofReal_inj {z w : ℝ} : (z : K) = (w : K) ↔ z = w :=
algebraMap.coe_inj
#align is_R_or_C.of_real_inj RCLike.ofReal_inj
-- replaced by `RCLike.ofNat_re`
#noalign is_R_or_C.bit0_re
#noalign is_R_or_C.bit1_re
-- replaced by `RCLike.ofNat_im`
#noalign is_R_or_C.bit0_im
#noalign is_R_or_C.bit1_im
theorem ofReal_eq_zero {x : ℝ} : (x : K) = 0 ↔ x = 0 :=
algebraMap.lift_map_eq_zero_iff x
#align is_R_or_C.of_real_eq_zero RCLike.ofReal_eq_zero
theorem ofReal_ne_zero {x : ℝ} : (x : K) ≠ 0 ↔ x ≠ 0 :=
ofReal_eq_zero.not
#align is_R_or_C.of_real_ne_zero RCLike.ofReal_ne_zero
@[simp, rclike_simps, norm_cast]
theorem ofReal_add (r s : ℝ) : ((r + s : ℝ) : K) = r + s :=
algebraMap.coe_add _ _
#align is_R_or_C.of_real_add RCLike.ofReal_add
-- replaced by `RCLike.ofReal_ofNat`
#noalign is_R_or_C.of_real_bit0
#noalign is_R_or_C.of_real_bit1
@[simp, norm_cast, rclike_simps]
theorem ofReal_neg (r : ℝ) : ((-r : ℝ) : K) = -r :=
algebraMap.coe_neg r
#align is_R_or_C.of_real_neg RCLike.ofReal_neg
@[simp, norm_cast, rclike_simps]
theorem ofReal_sub (r s : ℝ) : ((r - s : ℝ) : K) = r - s :=
map_sub (algebraMap ℝ K) r s
#align is_R_or_C.of_real_sub RCLike.ofReal_sub
@[simp, rclike_simps, norm_cast]
theorem ofReal_sum {α : Type*} (s : Finset α) (f : α → ℝ) :
((∑ i ∈ s, f i : ℝ) : K) = ∑ i ∈ s, (f i : K) :=
map_sum (algebraMap ℝ K) _ _
#align is_R_or_C.of_real_sum RCLike.ofReal_sum
@[simp, rclike_simps, norm_cast]
theorem ofReal_finsupp_sum {α M : Type*} [Zero M] (f : α →₀ M) (g : α → M → ℝ) :
((f.sum fun a b => g a b : ℝ) : K) = f.sum fun a b => (g a b : K) :=
map_finsupp_sum (algebraMap ℝ K) f g
#align is_R_or_C.of_real_finsupp_sum RCLike.ofReal_finsupp_sum
@[simp, norm_cast, rclike_simps]
theorem ofReal_mul (r s : ℝ) : ((r * s : ℝ) : K) = r * s :=
algebraMap.coe_mul _ _
#align is_R_or_C.of_real_mul RCLike.ofReal_mul
@[simp, norm_cast, rclike_simps]
theorem ofReal_pow (r : ℝ) (n : ℕ) : ((r ^ n : ℝ) : K) = (r : K) ^ n :=
map_pow (algebraMap ℝ K) r n
#align is_R_or_C.of_real_pow RCLike.ofReal_pow
@[simp, rclike_simps, norm_cast]
theorem ofReal_prod {α : Type*} (s : Finset α) (f : α → ℝ) :
((∏ i ∈ s, f i : ℝ) : K) = ∏ i ∈ s, (f i : K) :=
map_prod (algebraMap ℝ K) _ _
#align is_R_or_C.of_real_prod RCLike.ofReal_prod
@[simp, rclike_simps, norm_cast]
theorem ofReal_finsupp_prod {α M : Type*} [Zero M] (f : α →₀ M) (g : α → M → ℝ) :
((f.prod fun a b => g a b : ℝ) : K) = f.prod fun a b => (g a b : K) :=
map_finsupp_prod _ f g
#align is_R_or_C.of_real_finsupp_prod RCLike.ofReal_finsupp_prod
@[simp, norm_cast, rclike_simps]
theorem real_smul_ofReal (r x : ℝ) : r • (x : K) = (r : K) * (x : K) :=
real_smul_eq_coe_mul _ _
#align is_R_or_C.real_smul_of_real RCLike.real_smul_ofReal
@[rclike_simps]
theorem re_ofReal_mul (r : ℝ) (z : K) : re (↑r * z) = r * re z := by
simp only [mul_re, ofReal_im, zero_mul, ofReal_re, sub_zero]
#align is_R_or_C.of_real_mul_re RCLike.re_ofReal_mul
@[rclike_simps]
theorem im_ofReal_mul (r : ℝ) (z : K) : im (↑r * z) = r * im z := by
simp only [add_zero, ofReal_im, zero_mul, ofReal_re, mul_im]
#align is_R_or_C.of_real_mul_im RCLike.im_ofReal_mul
@[rclike_simps]
theorem smul_re (r : ℝ) (z : K) : re (r • z) = r * re z := by
rw [real_smul_eq_coe_mul, re_ofReal_mul]
#align is_R_or_C.smul_re RCLike.smul_re
@[rclike_simps]
theorem smul_im (r : ℝ) (z : K) : im (r • z) = r * im z := by
rw [real_smul_eq_coe_mul, im_ofReal_mul]
#align is_R_or_C.smul_im RCLike.smul_im
@[simp, norm_cast, rclike_simps]
theorem norm_ofReal (r : ℝ) : ‖(r : K)‖ = |r| :=
norm_algebraMap' K r
#align is_R_or_C.norm_of_real RCLike.norm_ofReal
/-! ### Characteristic zero -/
-- see Note [lower instance priority]
/-- ℝ and ℂ are both of characteristic zero. -/
instance (priority := 100) charZero_rclike : CharZero K :=
(RingHom.charZero_iff (algebraMap ℝ K).injective).1 inferInstance
set_option linter.uppercaseLean3 false in
#align is_R_or_C.char_zero_R_or_C RCLike.charZero_rclike
/-! ### The imaginary unit, `I` -/
/-- The imaginary unit. -/
@[simp, rclike_simps]
theorem I_re : re (I : K) = 0 :=
I_re_ax
set_option linter.uppercaseLean3 false in
#align is_R_or_C.I_re RCLike.I_re
@[simp, rclike_simps]
theorem I_im (z : K) : im z * im (I : K) = im z :=
mul_im_I_ax z
set_option linter.uppercaseLean3 false in
#align is_R_or_C.I_im RCLike.I_im
@[simp, rclike_simps]
theorem I_im' (z : K) : im (I : K) * im z = im z := by rw [mul_comm, I_im]
set_option linter.uppercaseLean3 false in
#align is_R_or_C.I_im' RCLike.I_im'
@[rclike_simps] -- porting note (#10618): was `simp`
theorem I_mul_re (z : K) : re (I * z) = -im z := by
simp only [I_re, zero_sub, I_im', zero_mul, mul_re]
set_option linter.uppercaseLean3 false in
#align is_R_or_C.I_mul_re RCLike.I_mul_re
theorem I_mul_I : (I : K) = 0 ∨ (I : K) * I = -1 :=
I_mul_I_ax
set_option linter.uppercaseLean3 false in
#align is_R_or_C.I_mul_I RCLike.I_mul_I
variable (𝕜) in
lemma I_eq_zero_or_im_I_eq_one : (I : K) = 0 ∨ im (I : K) = 1 :=
I_mul_I (K := K) |>.imp_right fun h ↦ by simpa [h] using (I_mul_re (I : K)).symm
@[simp, rclike_simps]
theorem conj_re (z : K) : re (conj z) = re z :=
RCLike.conj_re_ax z
#align is_R_or_C.conj_re RCLike.conj_re
@[simp, rclike_simps]
theorem conj_im (z : K) : im (conj z) = -im z :=
RCLike.conj_im_ax z
#align is_R_or_C.conj_im RCLike.conj_im
@[simp, rclike_simps]
theorem conj_I : conj (I : K) = -I :=
RCLike.conj_I_ax
set_option linter.uppercaseLean3 false in
#align is_R_or_C.conj_I RCLike.conj_I
@[simp, rclike_simps]
theorem conj_ofReal (r : ℝ) : conj (r : K) = (r : K) := by
rw [ext_iff]
simp only [ofReal_im, conj_im, eq_self_iff_true, conj_re, and_self_iff, neg_zero]
#align is_R_or_C.conj_of_real RCLike.conj_ofReal
-- replaced by `RCLike.conj_ofNat`
#noalign is_R_or_C.conj_bit0
#noalign is_R_or_C.conj_bit1
theorem conj_nat_cast (n : ℕ) : conj (n : K) = n := map_natCast _ _
-- See note [no_index around OfNat.ofNat]
theorem conj_ofNat (n : ℕ) [n.AtLeastTwo] : conj (no_index (OfNat.ofNat n : K)) = OfNat.ofNat n :=
map_ofNat _ _
@[rclike_simps] -- Porting note (#10618): was a `simp` but `simp` can prove it
theorem conj_neg_I : conj (-I) = (I : K) := by rw [map_neg, conj_I, neg_neg]
set_option linter.uppercaseLean3 false in
#align is_R_or_C.conj_neg_I RCLike.conj_neg_I
theorem conj_eq_re_sub_im (z : K) : conj z = re z - im z * I :=
(congr_arg conj (re_add_im z).symm).trans <| by
rw [map_add, map_mul, conj_I, conj_ofReal, conj_ofReal, mul_neg, sub_eq_add_neg]
#align is_R_or_C.conj_eq_re_sub_im RCLike.conj_eq_re_sub_im
theorem sub_conj (z : K) : z - conj z = 2 * im z * I :=
calc
z - conj z = re z + im z * I - (re z - im z * I) := by rw [re_add_im, ← conj_eq_re_sub_im]
_ = 2 * im z * I := by rw [add_sub_sub_cancel, ← two_mul, mul_assoc]
#align is_R_or_C.sub_conj RCLike.sub_conj
@[rclike_simps]
theorem conj_smul (r : ℝ) (z : K) : conj (r • z) = r • conj z := by
rw [conj_eq_re_sub_im, conj_eq_re_sub_im, smul_re, smul_im, ofReal_mul, ofReal_mul,
real_smul_eq_coe_mul r (_ - _), mul_sub, mul_assoc]
#align is_R_or_C.conj_smul RCLike.conj_smul
theorem add_conj (z : K) : z + conj z = 2 * re z :=
calc
z + conj z = re z + im z * I + (re z - im z * I) := by rw [re_add_im, conj_eq_re_sub_im]
_ = 2 * re z := by rw [add_add_sub_cancel, two_mul]
#align is_R_or_C.add_conj RCLike.add_conj
theorem re_eq_add_conj (z : K) : ↑(re z) = (z + conj z) / 2 := by
rw [add_conj, mul_div_cancel_left₀ (re z : K) two_ne_zero]
#align is_R_or_C.re_eq_add_conj RCLike.re_eq_add_conj
theorem im_eq_conj_sub (z : K) : ↑(im z) = I * (conj z - z) / 2 := by
rw [← neg_inj, ← ofReal_neg, ← I_mul_re, re_eq_add_conj, map_mul, conj_I, ← neg_div, ← mul_neg,
neg_sub, mul_sub, neg_mul, sub_eq_add_neg]
#align is_R_or_C.im_eq_conj_sub RCLike.im_eq_conj_sub
open List in
/-- There are several equivalent ways to say that a number `z` is in fact a real number. -/
theorem is_real_TFAE (z : K) : TFAE [conj z = z, ∃ r : ℝ, (r : K) = z, ↑(re z) = z, im z = 0] := by
tfae_have 1 → 4
· intro h
rw [← @ofReal_inj K, im_eq_conj_sub, h, sub_self, mul_zero, zero_div,
ofReal_zero]
tfae_have 4 → 3
· intro h
conv_rhs => rw [← re_add_im z, h, ofReal_zero, zero_mul, add_zero]
tfae_have 3 → 2
· exact fun h => ⟨_, h⟩
tfae_have 2 → 1
· exact fun ⟨r, hr⟩ => hr ▸ conj_ofReal _
tfae_finish
#align is_R_or_C.is_real_tfae RCLike.is_real_TFAE
theorem conj_eq_iff_real {z : K} : conj z = z ↔ ∃ r : ℝ, z = (r : K) :=
((is_real_TFAE z).out 0 1).trans <| by simp only [eq_comm]
#align is_R_or_C.conj_eq_iff_real RCLike.conj_eq_iff_real
theorem conj_eq_iff_re {z : K} : conj z = z ↔ (re z : K) = z :=
(is_real_TFAE z).out 0 2
#align is_R_or_C.conj_eq_iff_re RCLike.conj_eq_iff_re
theorem conj_eq_iff_im {z : K} : conj z = z ↔ im z = 0 :=
(is_real_TFAE z).out 0 3
#align is_R_or_C.conj_eq_iff_im RCLike.conj_eq_iff_im
@[simp]
theorem star_def : (Star.star : K → K) = conj :=
rfl
#align is_R_or_C.star_def RCLike.star_def
variable (K)
/-- Conjugation as a ring equivalence. This is used to convert the inner product into a
sesquilinear product. -/
abbrev conjToRingEquiv : K ≃+* Kᵐᵒᵖ :=
starRingEquiv
#align is_R_or_C.conj_to_ring_equiv RCLike.conjToRingEquiv
variable {K} {z : K}
/-- The norm squared function. -/
def normSq : K →*₀ ℝ where
toFun z := re z * re z + im z * im z
map_zero' := by simp only [add_zero, mul_zero, map_zero]
map_one' := by simp only [one_im, add_zero, mul_one, one_re, mul_zero]
map_mul' z w := by
simp only [mul_im, mul_re]
ring
#align is_R_or_C.norm_sq RCLike.normSq
theorem normSq_apply (z : K) : normSq z = re z * re z + im z * im z :=
rfl
#align is_R_or_C.norm_sq_apply RCLike.normSq_apply
theorem norm_sq_eq_def {z : K} : ‖z‖ ^ 2 = re z * re z + im z * im z :=
norm_sq_eq_def_ax z
#align is_R_or_C.norm_sq_eq_def RCLike.norm_sq_eq_def
theorem normSq_eq_def' (z : K) : normSq z = ‖z‖ ^ 2 :=
norm_sq_eq_def.symm
#align is_R_or_C.norm_sq_eq_def' RCLike.normSq_eq_def'
@[rclike_simps]
theorem normSq_zero : normSq (0 : K) = 0 :=
normSq.map_zero
#align is_R_or_C.norm_sq_zero RCLike.normSq_zero
@[rclike_simps]
theorem normSq_one : normSq (1 : K) = 1 :=
normSq.map_one
#align is_R_or_C.norm_sq_one RCLike.normSq_one
theorem normSq_nonneg (z : K) : 0 ≤ normSq z :=
add_nonneg (mul_self_nonneg _) (mul_self_nonneg _)
#align is_R_or_C.norm_sq_nonneg RCLike.normSq_nonneg
@[rclike_simps] -- porting note (#10618): was `simp`
theorem normSq_eq_zero {z : K} : normSq z = 0 ↔ z = 0 :=
map_eq_zero _
#align is_R_or_C.norm_sq_eq_zero RCLike.normSq_eq_zero
@[simp, rclike_simps]
theorem normSq_pos {z : K} : 0 < normSq z ↔ z ≠ 0 := by
rw [lt_iff_le_and_ne, Ne, eq_comm]; simp [normSq_nonneg]
#align is_R_or_C.norm_sq_pos RCLike.normSq_pos
@[simp, rclike_simps]
theorem normSq_neg (z : K) : normSq (-z) = normSq z := by simp only [normSq_eq_def', norm_neg]
#align is_R_or_C.norm_sq_neg RCLike.normSq_neg
@[simp, rclike_simps]
theorem normSq_conj (z : K) : normSq (conj z) = normSq z := by
simp only [normSq_apply, neg_mul, mul_neg, neg_neg, rclike_simps]
#align is_R_or_C.norm_sq_conj RCLike.normSq_conj
@[rclike_simps] -- porting note (#10618): was `simp`
theorem normSq_mul (z w : K) : normSq (z * w) = normSq z * normSq w :=
map_mul _ z w
#align is_R_or_C.norm_sq_mul RCLike.normSq_mul
theorem normSq_add (z w : K) : normSq (z + w) = normSq z + normSq w + 2 * re (z * conj w) := by
simp only [normSq_apply, map_add, rclike_simps]
ring
#align is_R_or_C.norm_sq_add RCLike.normSq_add
theorem re_sq_le_normSq (z : K) : re z * re z ≤ normSq z :=
le_add_of_nonneg_right (mul_self_nonneg _)
#align is_R_or_C.re_sq_le_norm_sq RCLike.re_sq_le_normSq
theorem im_sq_le_normSq (z : K) : im z * im z ≤ normSq z :=
le_add_of_nonneg_left (mul_self_nonneg _)
#align is_R_or_C.im_sq_le_norm_sq RCLike.im_sq_le_normSq
theorem mul_conj (z : K) : z * conj z = ‖z‖ ^ 2 := by
apply ext <;> simp [← ofReal_pow, norm_sq_eq_def, mul_comm]
#align is_R_or_C.mul_conj RCLike.mul_conj
theorem conj_mul (z : K) : conj z * z = ‖z‖ ^ 2 := by rw [mul_comm, mul_conj]
#align is_R_or_C.conj_mul RCLike.conj_mul
lemma inv_eq_conj (hz : ‖z‖ = 1) : z⁻¹ = conj z :=
inv_eq_of_mul_eq_one_left $ by simp_rw [conj_mul, hz, algebraMap.coe_one, one_pow]
theorem normSq_sub (z w : K) : normSq (z - w) = normSq z + normSq w - 2 * re (z * conj w) := by
simp only [normSq_add, sub_eq_add_neg, map_neg, mul_neg, normSq_neg, map_neg]
#align is_R_or_C.norm_sq_sub RCLike.normSq_sub
theorem sqrt_normSq_eq_norm {z : K} : √(normSq z) = ‖z‖ := by
rw [normSq_eq_def', Real.sqrt_sq (norm_nonneg _)]
#align is_R_or_C.sqrt_norm_sq_eq_norm RCLike.sqrt_normSq_eq_norm
/-! ### Inversion -/
@[simp, norm_cast, rclike_simps]
theorem ofReal_inv (r : ℝ) : ((r⁻¹ : ℝ) : K) = (r : K)⁻¹ :=
map_inv₀ _ r
#align is_R_or_C.of_real_inv RCLike.ofReal_inv
theorem inv_def (z : K) : z⁻¹ = conj z * ((‖z‖ ^ 2)⁻¹ : ℝ) := by
rcases eq_or_ne z 0 with (rfl | h₀)
· simp
· apply inv_eq_of_mul_eq_one_right
rw [← mul_assoc, mul_conj, ofReal_inv, ofReal_pow, mul_inv_cancel]
simpa
#align is_R_or_C.inv_def RCLike.inv_def
@[simp, rclike_simps]
theorem inv_re (z : K) : re z⁻¹ = re z / normSq z := by
rw [inv_def, normSq_eq_def', mul_comm, re_ofReal_mul, conj_re, div_eq_inv_mul]
#align is_R_or_C.inv_re RCLike.inv_re
@[simp, rclike_simps]
theorem inv_im (z : K) : im z⁻¹ = -im z / normSq z := by
rw [inv_def, normSq_eq_def', mul_comm, im_ofReal_mul, conj_im, div_eq_inv_mul]
#align is_R_or_C.inv_im RCLike.inv_im
theorem div_re (z w : K) : re (z / w) = re z * re w / normSq w + im z * im w / normSq w := by
simp only [div_eq_mul_inv, mul_assoc, sub_eq_add_neg, neg_mul, mul_neg, neg_neg, map_neg,
rclike_simps]
#align is_R_or_C.div_re RCLike.div_re
theorem div_im (z w : K) : im (z / w) = im z * re w / normSq w - re z * im w / normSq w := by
simp only [div_eq_mul_inv, mul_assoc, sub_eq_add_neg, add_comm, neg_mul, mul_neg, map_neg,
rclike_simps]
#align is_R_or_C.div_im RCLike.div_im
@[rclike_simps] -- porting note (#10618): was `simp`
theorem conj_inv (x : K) : conj x⁻¹ = (conj x)⁻¹ :=
star_inv' _
#align is_R_or_C.conj_inv RCLike.conj_inv
lemma conj_div (x y : K) : conj (x / y) = conj x / conj y := map_div' conj conj_inv _ _
--TODO: Do we rather want the map as an explicit definition?
lemma exists_norm_eq_mul_self (x : K) : ∃ c, ‖c‖ = 1 ∧ ↑‖x‖ = c * x := by
obtain rfl | hx := eq_or_ne x 0
· exact ⟨1, by simp⟩
· exact ⟨‖x‖ / x, by simp [norm_ne_zero_iff.2, hx]⟩
lemma exists_norm_mul_eq_self (x : K) : ∃ c, ‖c‖ = 1 ∧ c * ‖x‖ = x := by
obtain rfl | hx := eq_or_ne x 0
· exact ⟨1, by simp⟩
· exact ⟨x / ‖x‖, by simp [norm_ne_zero_iff.2, hx]⟩
@[simp, norm_cast, rclike_simps]
theorem ofReal_div (r s : ℝ) : ((r / s : ℝ) : K) = r / s :=
map_div₀ (algebraMap ℝ K) r s
#align is_R_or_C.of_real_div RCLike.ofReal_div
theorem div_re_ofReal {z : K} {r : ℝ} : re (z / r) = re z / r := by
rw [div_eq_inv_mul, div_eq_inv_mul, ← ofReal_inv, re_ofReal_mul]
#align is_R_or_C.div_re_of_real RCLike.div_re_ofReal
@[simp, norm_cast, rclike_simps]
theorem ofReal_zpow (r : ℝ) (n : ℤ) : ((r ^ n : ℝ) : K) = (r : K) ^ n :=
map_zpow₀ (algebraMap ℝ K) r n
#align is_R_or_C.of_real_zpow RCLike.ofReal_zpow
theorem I_mul_I_of_nonzero : (I : K) ≠ 0 → (I : K) * I = -1 :=
I_mul_I_ax.resolve_left
set_option linter.uppercaseLean3 false in
#align is_R_or_C.I_mul_I_of_nonzero RCLike.I_mul_I_of_nonzero
@[simp, rclike_simps]
theorem inv_I : (I : K)⁻¹ = -I := by
by_cases h : (I : K) = 0
· simp [h]
· field_simp [I_mul_I_of_nonzero h]
set_option linter.uppercaseLean3 false in
#align is_R_or_C.inv_I RCLike.inv_I
@[simp, rclike_simps]
theorem div_I (z : K) : z / I = -(z * I) := by rw [div_eq_mul_inv, inv_I, mul_neg]
set_option linter.uppercaseLean3 false in
#align is_R_or_C.div_I RCLike.div_I
@[rclike_simps] -- porting note (#10618): was `simp`
theorem normSq_inv (z : K) : normSq z⁻¹ = (normSq z)⁻¹ :=
map_inv₀ normSq z
#align is_R_or_C.norm_sq_inv RCLike.normSq_inv
@[rclike_simps] -- porting note (#10618): was `simp`
theorem normSq_div (z w : K) : normSq (z / w) = normSq z / normSq w :=
map_div₀ normSq z w
#align is_R_or_C.norm_sq_div RCLike.normSq_div
@[rclike_simps] -- porting note (#10618): was `simp`
theorem norm_conj {z : K} : ‖conj z‖ = ‖z‖ := by simp only [← sqrt_normSq_eq_norm, normSq_conj]
#align is_R_or_C.norm_conj RCLike.norm_conj
instance (priority := 100) : CstarRing K where
norm_star_mul_self {x} := (norm_mul _ _).trans <| congr_arg (· * ‖x‖) norm_conj
/-! ### Cast lemmas -/
@[simp, rclike_simps, norm_cast]
theorem ofReal_natCast (n : ℕ) : ((n : ℝ) : K) = n :=
map_natCast (algebraMap ℝ K) n
#align is_R_or_C.of_real_nat_cast RCLike.ofReal_natCast
@[simp, rclike_simps] -- Porting note: removed `norm_cast`
theorem natCast_re (n : ℕ) : re (n : K) = n := by rw [← ofReal_natCast, ofReal_re]
#align is_R_or_C.nat_cast_re RCLike.natCast_re
@[simp, rclike_simps, norm_cast]
theorem natCast_im (n : ℕ) : im (n : K) = 0 := by rw [← ofReal_natCast, ofReal_im]
#align is_R_or_C.nat_cast_im RCLike.natCast_im
-- See note [no_index around OfNat.ofNat]
@[simp, rclike_simps]
theorem ofNat_re (n : ℕ) [n.AtLeastTwo] : re (no_index (OfNat.ofNat n) : K) = OfNat.ofNat n :=
natCast_re n
-- See note [no_index around OfNat.ofNat]
@[simp, rclike_simps]
theorem ofNat_im (n : ℕ) [n.AtLeastTwo] : im (no_index (OfNat.ofNat n) : K) = 0 :=
natCast_im n
-- See note [no_index around OfNat.ofNat]
@[simp, rclike_simps, norm_cast]
theorem ofReal_ofNat (n : ℕ) [n.AtLeastTwo] :
((no_index (OfNat.ofNat n) : ℝ) : K) = OfNat.ofNat n :=
ofReal_natCast n
theorem ofNat_mul_re (n : ℕ) [n.AtLeastTwo] (z : K) :
re (OfNat.ofNat n * z) = OfNat.ofNat n * re z := by
rw [← ofReal_ofNat, re_ofReal_mul]
theorem ofNat_mul_im (n : ℕ) [n.AtLeastTwo] (z : K) :
im (OfNat.ofNat n * z) = OfNat.ofNat n * im z := by
rw [← ofReal_ofNat, im_ofReal_mul]
@[simp, rclike_simps, norm_cast]
theorem ofReal_intCast (n : ℤ) : ((n : ℝ) : K) = n :=
map_intCast _ n
#align is_R_or_C.of_real_int_cast RCLike.ofReal_intCast
@[simp, rclike_simps] -- Porting note: removed `norm_cast`
theorem intCast_re (n : ℤ) : re (n : K) = n := by rw [← ofReal_intCast, ofReal_re]
#align is_R_or_C.int_cast_re RCLike.intCast_re
@[simp, rclike_simps, norm_cast]
theorem intCast_im (n : ℤ) : im (n : K) = 0 := by rw [← ofReal_intCast, ofReal_im]
#align is_R_or_C.int_cast_im RCLike.intCast_im
@[simp, rclike_simps, norm_cast]
theorem ofReal_ratCast (n : ℚ) : ((n : ℝ) : K) = n :=
map_ratCast _ n
#align is_R_or_C.of_real_rat_cast RCLike.ofReal_ratCast
@[simp, rclike_simps] -- Porting note: removed `norm_cast`
theorem ratCast_re (q : ℚ) : re (q : K) = q := by rw [← ofReal_ratCast, ofReal_re]
#align is_R_or_C.rat_cast_re RCLike.ratCast_re
@[simp, rclike_simps, norm_cast]
theorem ratCast_im (q : ℚ) : im (q : K) = 0 := by rw [← ofReal_ratCast, ofReal_im]
#align is_R_or_C.rat_cast_im RCLike.ratCast_im
/-! ### Norm -/
theorem norm_of_nonneg {r : ℝ} (h : 0 ≤ r) : ‖(r : K)‖ = r :=
(norm_ofReal _).trans (abs_of_nonneg h)
#align is_R_or_C.norm_of_nonneg RCLike.norm_of_nonneg
@[simp, rclike_simps, norm_cast]
theorem norm_natCast (n : ℕ) : ‖(n : K)‖ = n := by
rw [← ofReal_natCast]
exact norm_of_nonneg (Nat.cast_nonneg n)
#align is_R_or_C.norm_nat_cast RCLike.norm_natCast
@[simp, rclike_simps]
theorem norm_ofNat (n : ℕ) [n.AtLeastTwo] : ‖(no_index (OfNat.ofNat n) : K)‖ = OfNat.ofNat n :=
norm_natCast n
variable (K) in
lemma norm_nsmul [NormedAddCommGroup E] [NormedSpace K E] (n : ℕ) (x : E) : ‖n • x‖ = n • ‖x‖ := by
rw [nsmul_eq_smul_cast K, norm_smul, RCLike.norm_natCast, nsmul_eq_mul]
theorem mul_self_norm (z : K) : ‖z‖ * ‖z‖ = normSq z := by rw [normSq_eq_def', sq]
#align is_R_or_C.mul_self_norm RCLike.mul_self_norm
attribute [rclike_simps] norm_zero norm_one norm_eq_zero abs_norm norm_inv norm_div
-- Porting note: removed @[simp, rclike_simps], b/c generalized to `norm_ofNat`
theorem norm_two : ‖(2 : K)‖ = 2 := norm_ofNat 2
#align is_R_or_C.norm_two RCLike.norm_two
theorem abs_re_le_norm (z : K) : |re z| ≤ ‖z‖ := by
rw [mul_self_le_mul_self_iff (abs_nonneg _) (norm_nonneg _), abs_mul_abs_self, mul_self_norm]
apply re_sq_le_normSq
#align is_R_or_C.abs_re_le_norm RCLike.abs_re_le_norm
theorem abs_im_le_norm (z : K) : |im z| ≤ ‖z‖ := by
rw [mul_self_le_mul_self_iff (abs_nonneg _) (norm_nonneg _), abs_mul_abs_self, mul_self_norm]
apply im_sq_le_normSq
#align is_R_or_C.abs_im_le_norm RCLike.abs_im_le_norm
theorem norm_re_le_norm (z : K) : ‖re z‖ ≤ ‖z‖ :=
abs_re_le_norm z
#align is_R_or_C.norm_re_le_norm RCLike.norm_re_le_norm
theorem norm_im_le_norm (z : K) : ‖im z‖ ≤ ‖z‖ :=
abs_im_le_norm z
#align is_R_or_C.norm_im_le_norm RCLike.norm_im_le_norm
theorem re_le_norm (z : K) : re z ≤ ‖z‖ :=
(abs_le.1 (abs_re_le_norm z)).2
#align is_R_or_C.re_le_norm RCLike.re_le_norm
theorem im_le_norm (z : K) : im z ≤ ‖z‖ :=
(abs_le.1 (abs_im_le_norm _)).2
#align is_R_or_C.im_le_norm RCLike.im_le_norm
theorem im_eq_zero_of_le {a : K} (h : ‖a‖ ≤ re a) : im a = 0 := by
simpa only [mul_self_norm a, normSq_apply, self_eq_add_right, mul_self_eq_zero]
using congr_arg (fun z => z * z) ((re_le_norm a).antisymm h)
#align is_R_or_C.im_eq_zero_of_le RCLike.im_eq_zero_of_le
theorem re_eq_self_of_le {a : K} (h : ‖a‖ ≤ re a) : (re a : K) = a := by
rw [← conj_eq_iff_re, conj_eq_iff_im, im_eq_zero_of_le h]
#align is_R_or_C.re_eq_self_of_le RCLike.re_eq_self_of_le
open IsAbsoluteValue
theorem abs_re_div_norm_le_one (z : K) : |re z / ‖z‖| ≤ 1 := by
rw [abs_div, abs_norm]
exact div_le_one_of_le (abs_re_le_norm _) (norm_nonneg _)
#align is_R_or_C.abs_re_div_norm_le_one RCLike.abs_re_div_norm_le_one
theorem abs_im_div_norm_le_one (z : K) : |im z / ‖z‖| ≤ 1 := by
rw [abs_div, abs_norm]
exact div_le_one_of_le (abs_im_le_norm _) (norm_nonneg _)
#align is_R_or_C.abs_im_div_norm_le_one RCLike.abs_im_div_norm_le_one
theorem norm_I_of_ne_zero (hI : (I : K) ≠ 0) : ‖(I : K)‖ = 1 := by
rw [← mul_self_inj_of_nonneg (norm_nonneg I) zero_le_one, one_mul, ← norm_mul,
I_mul_I_of_nonzero hI, norm_neg, norm_one]
set_option linter.uppercaseLean3 false in
#align is_R_or_C.norm_I_of_ne_zero RCLike.norm_I_of_ne_zero
theorem re_eq_norm_of_mul_conj (x : K) : re (x * conj x) = ‖x * conj x‖ := by
rw [mul_conj, ← ofReal_pow]; simp [-ofReal_pow]
#align is_R_or_C.re_eq_norm_of_mul_conj RCLike.re_eq_norm_of_mul_conj
theorem norm_sq_re_add_conj (x : K) : ‖x + conj x‖ ^ 2 = re (x + conj x) ^ 2 := by
rw [add_conj, ← ofReal_ofNat, ← ofReal_mul, norm_ofReal, sq_abs, ofReal_re]
#align is_R_or_C.norm_sq_re_add_conj RCLike.norm_sq_re_add_conj
| Mathlib/Analysis/RCLike/Basic.lean | 782 | 783 | theorem norm_sq_re_conj_add (x : K) : ‖conj x + x‖ ^ 2 = re (conj x + x) ^ 2 := by |
rw [add_comm, norm_sq_re_add_conj]
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Scott Morrison, Jens Wagemaker
-/
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Algebra.MonoidAlgebra.Basic
import Mathlib.Data.Finset.Sort
#align_import data.polynomial.basic from "leanprover-community/mathlib"@"949dc57e616a621462062668c9f39e4e17b64b69"
/-!
# Theory of univariate polynomials
This file defines `Polynomial R`, the type of univariate polynomials over the semiring `R`, builds
a semiring structure on it, and gives basic definitions that are expanded in other files in this
directory.
## Main definitions
* `monomial n a` is the polynomial `a X^n`. Note that `monomial n` is defined as an `R`-linear map.
* `C a` is the constant polynomial `a`. Note that `C` is defined as a ring homomorphism.
* `X` is the polynomial `X`, i.e., `monomial 1 1`.
* `p.sum f` is `∑ n ∈ p.support, f n (p.coeff n)`, i.e., one sums the values of functions applied
to coefficients of the polynomial `p`.
* `p.erase n` is the polynomial `p` in which one removes the `c X^n` term.
There are often two natural variants of lemmas involving sums, depending on whether one acts on the
polynomials, or on the function. The naming convention is that one adds `index` when acting on
the polynomials. For instance,
* `sum_add_index` states that `(p + q).sum f = p.sum f + q.sum f`;
* `sum_add` states that `p.sum (fun n x ↦ f n x + g n x) = p.sum f + p.sum g`.
* Notation to refer to `Polynomial R`, as `R[X]` or `R[t]`.
## Implementation
Polynomials are defined using `R[ℕ]`, where `R` is a semiring.
The variable `X` commutes with every polynomial `p`: lemma `X_mul` proves the identity
`X * p = p * X`. The relationship to `R[ℕ]` is through a structure
to make polynomials irreducible from the point of view of the kernel. Most operations
are irreducible since Lean can not compute anyway with `AddMonoidAlgebra`. There are two
exceptions that we make semireducible:
* The zero polynomial, so that its coefficients are definitionally equal to `0`.
* The scalar action, to permit typeclass search to unfold it to resolve potential instance
diamonds.
The raw implementation of the equivalence between `R[X]` and `R[ℕ]` is
done through `ofFinsupp` and `toFinsupp` (or, equivalently, `rcases p` when `p` is a polynomial
gives an element `q` of `R[ℕ]`, and conversely `⟨q⟩` gives back `p`). The
equivalence is also registered as a ring equiv in `Polynomial.toFinsuppIso`. These should
in general not be used once the basic API for polynomials is constructed.
-/
set_option linter.uppercaseLean3 false
noncomputable section
/-- `Polynomial R` is the type of univariate polynomials over `R`.
Polynomials should be seen as (semi-)rings with the additional constructor `X`.
The embedding from `R` is called `C`. -/
structure Polynomial (R : Type*) [Semiring R] where ofFinsupp ::
toFinsupp : AddMonoidAlgebra R ℕ
#align polynomial Polynomial
#align polynomial.of_finsupp Polynomial.ofFinsupp
#align polynomial.to_finsupp Polynomial.toFinsupp
@[inherit_doc] scoped[Polynomial] notation:9000 R "[X]" => Polynomial R
open AddMonoidAlgebra
open Finsupp hiding single
open Function hiding Commute
open Polynomial
namespace Polynomial
universe u
variable {R : Type u} {a b : R} {m n : ℕ}
section Semiring
variable [Semiring R] {p q : R[X]}
theorem forall_iff_forall_finsupp (P : R[X] → Prop) :
(∀ p, P p) ↔ ∀ q : R[ℕ], P ⟨q⟩ :=
⟨fun h q => h ⟨q⟩, fun h ⟨p⟩ => h p⟩
#align polynomial.forall_iff_forall_finsupp Polynomial.forall_iff_forall_finsupp
theorem exists_iff_exists_finsupp (P : R[X] → Prop) :
(∃ p, P p) ↔ ∃ q : R[ℕ], P ⟨q⟩ :=
⟨fun ⟨⟨p⟩, hp⟩ => ⟨p, hp⟩, fun ⟨q, hq⟩ => ⟨⟨q⟩, hq⟩⟩
#align polynomial.exists_iff_exists_finsupp Polynomial.exists_iff_exists_finsupp
@[simp]
theorem eta (f : R[X]) : Polynomial.ofFinsupp f.toFinsupp = f := by cases f; rfl
#align polynomial.eta Polynomial.eta
/-! ### Conversions to and from `AddMonoidAlgebra`
Since `R[X]` is not defeq to `R[ℕ]`, but instead is a structure wrapping
it, we have to copy across all the arithmetic operators manually, along with the lemmas about how
they unfold around `Polynomial.ofFinsupp` and `Polynomial.toFinsupp`.
-/
section AddMonoidAlgebra
private irreducible_def add : R[X] → R[X] → R[X]
| ⟨a⟩, ⟨b⟩ => ⟨a + b⟩
private irreducible_def neg {R : Type u} [Ring R] : R[X] → R[X]
| ⟨a⟩ => ⟨-a⟩
private irreducible_def mul : R[X] → R[X] → R[X]
| ⟨a⟩, ⟨b⟩ => ⟨a * b⟩
instance zero : Zero R[X] :=
⟨⟨0⟩⟩
#align polynomial.has_zero Polynomial.zero
instance one : One R[X] :=
⟨⟨1⟩⟩
#align polynomial.one Polynomial.one
instance add' : Add R[X] :=
⟨add⟩
#align polynomial.has_add Polynomial.add'
instance neg' {R : Type u} [Ring R] : Neg R[X] :=
⟨neg⟩
#align polynomial.has_neg Polynomial.neg'
instance sub {R : Type u} [Ring R] : Sub R[X] :=
⟨fun a b => a + -b⟩
#align polynomial.has_sub Polynomial.sub
instance mul' : Mul R[X] :=
⟨mul⟩
#align polynomial.has_mul Polynomial.mul'
-- If the private definitions are accidentally exposed, simplify them away.
@[simp] theorem add_eq_add : add p q = p + q := rfl
@[simp] theorem mul_eq_mul : mul p q = p * q := rfl
instance smulZeroClass {S : Type*} [SMulZeroClass S R] : SMulZeroClass S R[X] where
smul r p := ⟨r • p.toFinsupp⟩
smul_zero a := congr_arg ofFinsupp (smul_zero a)
#align polynomial.smul_zero_class Polynomial.smulZeroClass
-- to avoid a bug in the `ring` tactic
instance (priority := 1) pow : Pow R[X] ℕ where pow p n := npowRec n p
#align polynomial.has_pow Polynomial.pow
@[simp]
theorem ofFinsupp_zero : (⟨0⟩ : R[X]) = 0 :=
rfl
#align polynomial.of_finsupp_zero Polynomial.ofFinsupp_zero
@[simp]
theorem ofFinsupp_one : (⟨1⟩ : R[X]) = 1 :=
rfl
#align polynomial.of_finsupp_one Polynomial.ofFinsupp_one
@[simp]
theorem ofFinsupp_add {a b} : (⟨a + b⟩ : R[X]) = ⟨a⟩ + ⟨b⟩ :=
show _ = add _ _ by rw [add_def]
#align polynomial.of_finsupp_add Polynomial.ofFinsupp_add
@[simp]
theorem ofFinsupp_neg {R : Type u} [Ring R] {a} : (⟨-a⟩ : R[X]) = -⟨a⟩ :=
show _ = neg _ by rw [neg_def]
#align polynomial.of_finsupp_neg Polynomial.ofFinsupp_neg
@[simp]
theorem ofFinsupp_sub {R : Type u} [Ring R] {a b} : (⟨a - b⟩ : R[X]) = ⟨a⟩ - ⟨b⟩ := by
rw [sub_eq_add_neg, ofFinsupp_add, ofFinsupp_neg]
rfl
#align polynomial.of_finsupp_sub Polynomial.ofFinsupp_sub
@[simp]
theorem ofFinsupp_mul (a b) : (⟨a * b⟩ : R[X]) = ⟨a⟩ * ⟨b⟩ :=
show _ = mul _ _ by rw [mul_def]
#align polynomial.of_finsupp_mul Polynomial.ofFinsupp_mul
@[simp]
theorem ofFinsupp_smul {S : Type*} [SMulZeroClass S R] (a : S) (b) :
(⟨a • b⟩ : R[X]) = (a • ⟨b⟩ : R[X]) :=
rfl
#align polynomial.of_finsupp_smul Polynomial.ofFinsupp_smul
@[simp]
theorem ofFinsupp_pow (a) (n : ℕ) : (⟨a ^ n⟩ : R[X]) = ⟨a⟩ ^ n := by
change _ = npowRec n _
induction n with
| zero => simp [npowRec]
| succ n n_ih => simp [npowRec, n_ih, pow_succ]
#align polynomial.of_finsupp_pow Polynomial.ofFinsupp_pow
@[simp]
theorem toFinsupp_zero : (0 : R[X]).toFinsupp = 0 :=
rfl
#align polynomial.to_finsupp_zero Polynomial.toFinsupp_zero
@[simp]
theorem toFinsupp_one : (1 : R[X]).toFinsupp = 1 :=
rfl
#align polynomial.to_finsupp_one Polynomial.toFinsupp_one
@[simp]
theorem toFinsupp_add (a b : R[X]) : (a + b).toFinsupp = a.toFinsupp + b.toFinsupp := by
cases a
cases b
rw [← ofFinsupp_add]
#align polynomial.to_finsupp_add Polynomial.toFinsupp_add
@[simp]
theorem toFinsupp_neg {R : Type u} [Ring R] (a : R[X]) : (-a).toFinsupp = -a.toFinsupp := by
cases a
rw [← ofFinsupp_neg]
#align polynomial.to_finsupp_neg Polynomial.toFinsupp_neg
@[simp]
theorem toFinsupp_sub {R : Type u} [Ring R] (a b : R[X]) :
(a - b).toFinsupp = a.toFinsupp - b.toFinsupp := by
rw [sub_eq_add_neg, ← toFinsupp_neg, ← toFinsupp_add]
rfl
#align polynomial.to_finsupp_sub Polynomial.toFinsupp_sub
@[simp]
theorem toFinsupp_mul (a b : R[X]) : (a * b).toFinsupp = a.toFinsupp * b.toFinsupp := by
cases a
cases b
rw [← ofFinsupp_mul]
#align polynomial.to_finsupp_mul Polynomial.toFinsupp_mul
@[simp]
theorem toFinsupp_smul {S : Type*} [SMulZeroClass S R] (a : S) (b : R[X]) :
(a • b).toFinsupp = a • b.toFinsupp :=
rfl
#align polynomial.to_finsupp_smul Polynomial.toFinsupp_smul
@[simp]
theorem toFinsupp_pow (a : R[X]) (n : ℕ) : (a ^ n).toFinsupp = a.toFinsupp ^ n := by
cases a
rw [← ofFinsupp_pow]
#align polynomial.to_finsupp_pow Polynomial.toFinsupp_pow
theorem _root_.IsSMulRegular.polynomial {S : Type*} [Monoid S] [DistribMulAction S R] {a : S}
(ha : IsSMulRegular R a) : IsSMulRegular R[X] a
| ⟨_x⟩, ⟨_y⟩, h => congr_arg _ <| ha.finsupp (Polynomial.ofFinsupp.inj h)
#align is_smul_regular.polynomial IsSMulRegular.polynomial
theorem toFinsupp_injective : Function.Injective (toFinsupp : R[X] → AddMonoidAlgebra _ _) :=
fun ⟨_x⟩ ⟨_y⟩ => congr_arg _
#align polynomial.to_finsupp_injective Polynomial.toFinsupp_injective
@[simp]
theorem toFinsupp_inj {a b : R[X]} : a.toFinsupp = b.toFinsupp ↔ a = b :=
toFinsupp_injective.eq_iff
#align polynomial.to_finsupp_inj Polynomial.toFinsupp_inj
@[simp]
theorem toFinsupp_eq_zero {a : R[X]} : a.toFinsupp = 0 ↔ a = 0 := by
rw [← toFinsupp_zero, toFinsupp_inj]
#align polynomial.to_finsupp_eq_zero Polynomial.toFinsupp_eq_zero
@[simp]
theorem toFinsupp_eq_one {a : R[X]} : a.toFinsupp = 1 ↔ a = 1 := by
rw [← toFinsupp_one, toFinsupp_inj]
#align polynomial.to_finsupp_eq_one Polynomial.toFinsupp_eq_one
/-- A more convenient spelling of `Polynomial.ofFinsupp.injEq` in terms of `Iff`. -/
theorem ofFinsupp_inj {a b} : (⟨a⟩ : R[X]) = ⟨b⟩ ↔ a = b :=
iff_of_eq (ofFinsupp.injEq _ _)
#align polynomial.of_finsupp_inj Polynomial.ofFinsupp_inj
@[simp]
theorem ofFinsupp_eq_zero {a} : (⟨a⟩ : R[X]) = 0 ↔ a = 0 := by
rw [← ofFinsupp_zero, ofFinsupp_inj]
#align polynomial.of_finsupp_eq_zero Polynomial.ofFinsupp_eq_zero
@[simp]
theorem ofFinsupp_eq_one {a} : (⟨a⟩ : R[X]) = 1 ↔ a = 1 := by rw [← ofFinsupp_one, ofFinsupp_inj]
#align polynomial.of_finsupp_eq_one Polynomial.ofFinsupp_eq_one
instance inhabited : Inhabited R[X] :=
⟨0⟩
#align polynomial.inhabited Polynomial.inhabited
instance instNatCast : NatCast R[X] where natCast n := ofFinsupp n
#align polynomial.has_nat_cast Polynomial.instNatCast
instance semiring : Semiring R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.semiring toFinsupp toFinsupp_injective toFinsupp_zero toFinsupp_one
toFinsupp_add toFinsupp_mul (fun _ _ => toFinsupp_smul _ _) toFinsupp_pow fun _ => rfl with
toAdd := Polynomial.add'
toMul := Polynomial.mul'
toZero := Polynomial.zero
toOne := Polynomial.one
nsmul := (· • ·)
npow := fun n x => (x ^ n) }
#align polynomial.semiring Polynomial.semiring
instance distribSMul {S} [DistribSMul S R] : DistribSMul S R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.distribSMul ⟨⟨toFinsupp, toFinsupp_zero⟩, toFinsupp_add⟩ toFinsupp_injective
toFinsupp_smul with
toSMulZeroClass := Polynomial.smulZeroClass }
#align polynomial.distrib_smul Polynomial.distribSMul
instance distribMulAction {S} [Monoid S] [DistribMulAction S R] : DistribMulAction S R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.distribMulAction ⟨⟨toFinsupp, toFinsupp_zero (R := R)⟩, toFinsupp_add⟩
toFinsupp_injective toFinsupp_smul with
toSMul := Polynomial.smulZeroClass.toSMul }
#align polynomial.distrib_mul_action Polynomial.distribMulAction
instance faithfulSMul {S} [SMulZeroClass S R] [FaithfulSMul S R] : FaithfulSMul S R[X] where
eq_of_smul_eq_smul {_s₁ _s₂} h :=
eq_of_smul_eq_smul fun a : ℕ →₀ R => congr_arg toFinsupp (h ⟨a⟩)
#align polynomial.has_faithful_smul Polynomial.faithfulSMul
instance module {S} [Semiring S] [Module S R] : Module S R[X] :=
--TODO: add reference to library note in PR #7432
{ Function.Injective.module _ ⟨⟨toFinsupp, toFinsupp_zero⟩, toFinsupp_add⟩ toFinsupp_injective
toFinsupp_smul with
toDistribMulAction := Polynomial.distribMulAction }
#align polynomial.module Polynomial.module
instance smulCommClass {S₁ S₂} [SMulZeroClass S₁ R] [SMulZeroClass S₂ R] [SMulCommClass S₁ S₂ R] :
SMulCommClass S₁ S₂ R[X] :=
⟨by
rintro m n ⟨f⟩
simp_rw [← ofFinsupp_smul, smul_comm m n f]⟩
#align polynomial.smul_comm_class Polynomial.smulCommClass
instance isScalarTower {S₁ S₂} [SMul S₁ S₂] [SMulZeroClass S₁ R] [SMulZeroClass S₂ R]
[IsScalarTower S₁ S₂ R] : IsScalarTower S₁ S₂ R[X] :=
⟨by
rintro _ _ ⟨⟩
simp_rw [← ofFinsupp_smul, smul_assoc]⟩
#align polynomial.is_scalar_tower Polynomial.isScalarTower
instance isScalarTower_right {α K : Type*} [Semiring K] [DistribSMul α K] [IsScalarTower α K K] :
IsScalarTower α K[X] K[X] :=
⟨by
rintro _ ⟨⟩ ⟨⟩;
simp_rw [smul_eq_mul, ← ofFinsupp_smul, ← ofFinsupp_mul, ← ofFinsupp_smul, smul_mul_assoc]⟩
#align polynomial.is_scalar_tower_right Polynomial.isScalarTower_right
instance isCentralScalar {S} [SMulZeroClass S R] [SMulZeroClass Sᵐᵒᵖ R] [IsCentralScalar S R] :
IsCentralScalar S R[X] :=
⟨by
rintro _ ⟨⟩
simp_rw [← ofFinsupp_smul, op_smul_eq_smul]⟩
#align polynomial.is_central_scalar Polynomial.isCentralScalar
instance unique [Subsingleton R] : Unique R[X] :=
{ Polynomial.inhabited with
uniq := by
rintro ⟨x⟩
apply congr_arg ofFinsupp
simp [eq_iff_true_of_subsingleton] }
#align polynomial.unique Polynomial.unique
variable (R)
/-- Ring isomorphism between `R[X]` and `R[ℕ]`. This is just an
implementation detail, but it can be useful to transfer results from `Finsupp` to polynomials. -/
@[simps apply symm_apply]
def toFinsuppIso : R[X] ≃+* R[ℕ] where
toFun := toFinsupp
invFun := ofFinsupp
left_inv := fun ⟨_p⟩ => rfl
right_inv _p := rfl
map_mul' := toFinsupp_mul
map_add' := toFinsupp_add
#align polynomial.to_finsupp_iso Polynomial.toFinsuppIso
#align polynomial.to_finsupp_iso_apply Polynomial.toFinsuppIso_apply
#align polynomial.to_finsupp_iso_symm_apply Polynomial.toFinsuppIso_symm_apply
instance [DecidableEq R] : DecidableEq R[X] :=
@Equiv.decidableEq R[X] _ (toFinsuppIso R).toEquiv (Finsupp.instDecidableEq)
end AddMonoidAlgebra
theorem ofFinsupp_sum {ι : Type*} (s : Finset ι) (f : ι → R[ℕ]) :
(⟨∑ i ∈ s, f i⟩ : R[X]) = ∑ i ∈ s, ⟨f i⟩ :=
map_sum (toFinsuppIso R).symm f s
#align polynomial.of_finsupp_sum Polynomial.ofFinsupp_sum
theorem toFinsupp_sum {ι : Type*} (s : Finset ι) (f : ι → R[X]) :
(∑ i ∈ s, f i : R[X]).toFinsupp = ∑ i ∈ s, (f i).toFinsupp :=
map_sum (toFinsuppIso R) f s
#align polynomial.to_finsupp_sum Polynomial.toFinsupp_sum
/-- The set of all `n` such that `X^n` has a non-zero coefficient.
-/
-- @[simp] -- Porting note: The original generated theorem is same to `support_ofFinsupp` and
-- the new generated theorem is different, so this attribute should be
-- removed.
def support : R[X] → Finset ℕ
| ⟨p⟩ => p.support
#align polynomial.support Polynomial.support
@[simp]
theorem support_ofFinsupp (p) : support (⟨p⟩ : R[X]) = p.support := by rw [support]
#align polynomial.support_of_finsupp Polynomial.support_ofFinsupp
theorem support_toFinsupp (p : R[X]) : p.toFinsupp.support = p.support := by rw [support]
@[simp]
theorem support_zero : (0 : R[X]).support = ∅ :=
rfl
#align polynomial.support_zero Polynomial.support_zero
@[simp]
theorem support_eq_empty : p.support = ∅ ↔ p = 0 := by
rcases p with ⟨⟩
simp [support]
#align polynomial.support_eq_empty Polynomial.support_eq_empty
@[simp] lemma support_nonempty : p.support.Nonempty ↔ p ≠ 0 :=
Finset.nonempty_iff_ne_empty.trans support_eq_empty.not
theorem card_support_eq_zero : p.support.card = 0 ↔ p = 0 := by simp
#align polynomial.card_support_eq_zero Polynomial.card_support_eq_zero
/-- `monomial s a` is the monomial `a * X^s` -/
def monomial (n : ℕ) : R →ₗ[R] R[X] where
toFun t := ⟨Finsupp.single n t⟩
-- porting note (#10745): was `simp`.
map_add' x y := by simp; rw [ofFinsupp_add]
-- porting note (#10745): was `simp [← ofFinsupp_smul]`.
map_smul' r x := by simp; rw [← ofFinsupp_smul, smul_single']
#align polynomial.monomial Polynomial.monomial
@[simp]
theorem toFinsupp_monomial (n : ℕ) (r : R) : (monomial n r).toFinsupp = Finsupp.single n r := by
simp [monomial]
#align polynomial.to_finsupp_monomial Polynomial.toFinsupp_monomial
@[simp]
theorem ofFinsupp_single (n : ℕ) (r : R) : (⟨Finsupp.single n r⟩ : R[X]) = monomial n r := by
simp [monomial]
#align polynomial.of_finsupp_single Polynomial.ofFinsupp_single
-- @[simp] -- Porting note (#10618): simp can prove this
theorem monomial_zero_right (n : ℕ) : monomial n (0 : R) = 0 :=
(monomial n).map_zero
#align polynomial.monomial_zero_right Polynomial.monomial_zero_right
-- This is not a `simp` lemma as `monomial_zero_left` is more general.
theorem monomial_zero_one : monomial 0 (1 : R) = 1 :=
rfl
#align polynomial.monomial_zero_one Polynomial.monomial_zero_one
-- TODO: can't we just delete this one?
theorem monomial_add (n : ℕ) (r s : R) : monomial n (r + s) = monomial n r + monomial n s :=
(monomial n).map_add _ _
#align polynomial.monomial_add Polynomial.monomial_add
theorem monomial_mul_monomial (n m : ℕ) (r s : R) :
monomial n r * monomial m s = monomial (n + m) (r * s) :=
toFinsupp_injective <| by
simp only [toFinsupp_monomial, toFinsupp_mul, AddMonoidAlgebra.single_mul_single]
#align polynomial.monomial_mul_monomial Polynomial.monomial_mul_monomial
@[simp]
theorem monomial_pow (n : ℕ) (r : R) (k : ℕ) : monomial n r ^ k = monomial (n * k) (r ^ k) := by
induction' k with k ih
· simp [pow_zero, monomial_zero_one]
· simp [pow_succ, ih, monomial_mul_monomial, Nat.succ_eq_add_one, mul_add, add_comm]
#align polynomial.monomial_pow Polynomial.monomial_pow
theorem smul_monomial {S} [SMulZeroClass S R] (a : S) (n : ℕ) (b : R) :
a • monomial n b = monomial n (a • b) :=
toFinsupp_injective <| by simp; rw [smul_single]
#align polynomial.smul_monomial Polynomial.smul_monomial
theorem monomial_injective (n : ℕ) : Function.Injective (monomial n : R → R[X]) :=
(toFinsuppIso R).symm.injective.comp (single_injective n)
#align polynomial.monomial_injective Polynomial.monomial_injective
@[simp]
theorem monomial_eq_zero_iff (t : R) (n : ℕ) : monomial n t = 0 ↔ t = 0 :=
LinearMap.map_eq_zero_iff _ (Polynomial.monomial_injective n)
#align polynomial.monomial_eq_zero_iff Polynomial.monomial_eq_zero_iff
theorem support_add : (p + q).support ⊆ p.support ∪ q.support := by
simpa [support] using Finsupp.support_add
#align polynomial.support_add Polynomial.support_add
/-- `C a` is the constant polynomial `a`.
`C` is provided as a ring homomorphism.
-/
def C : R →+* R[X] :=
{ monomial 0 with
map_one' := by simp [monomial_zero_one]
map_mul' := by simp [monomial_mul_monomial]
map_zero' := by simp }
#align polynomial.C Polynomial.C
@[simp]
theorem monomial_zero_left (a : R) : monomial 0 a = C a :=
rfl
#align polynomial.monomial_zero_left Polynomial.monomial_zero_left
@[simp]
theorem toFinsupp_C (a : R) : (C a).toFinsupp = single 0 a :=
rfl
#align polynomial.to_finsupp_C Polynomial.toFinsupp_C
theorem C_0 : C (0 : R) = 0 := by simp
#align polynomial.C_0 Polynomial.C_0
theorem C_1 : C (1 : R) = 1 :=
rfl
#align polynomial.C_1 Polynomial.C_1
theorem C_mul : C (a * b) = C a * C b :=
C.map_mul a b
#align polynomial.C_mul Polynomial.C_mul
theorem C_add : C (a + b) = C a + C b :=
C.map_add a b
#align polynomial.C_add Polynomial.C_add
@[simp]
theorem smul_C {S} [SMulZeroClass S R] (s : S) (r : R) : s • C r = C (s • r) :=
smul_monomial _ _ r
#align polynomial.smul_C Polynomial.smul_C
set_option linter.deprecated false in
-- @[simp] -- Porting note (#10618): simp can prove this
theorem C_bit0 : C (bit0 a) = bit0 (C a) :=
C_add
#align polynomial.C_bit0 Polynomial.C_bit0
set_option linter.deprecated false in
-- @[simp] -- Porting note (#10618): simp can prove this
theorem C_bit1 : C (bit1 a) = bit1 (C a) := by simp [bit1, C_bit0]
#align polynomial.C_bit1 Polynomial.C_bit1
theorem C_pow : C (a ^ n) = C a ^ n :=
C.map_pow a n
#align polynomial.C_pow Polynomial.C_pow
-- @[simp] -- Porting note (#10618): simp can prove this
theorem C_eq_natCast (n : ℕ) : C (n : R) = (n : R[X]) :=
map_natCast C n
#align polynomial.C_eq_nat_cast Polynomial.C_eq_natCast
@[deprecated (since := "2024-04-17")]
alias C_eq_nat_cast := C_eq_natCast
@[simp]
theorem C_mul_monomial : C a * monomial n b = monomial n (a * b) := by
simp only [← monomial_zero_left, monomial_mul_monomial, zero_add]
#align polynomial.C_mul_monomial Polynomial.C_mul_monomial
@[simp]
theorem monomial_mul_C : monomial n a * C b = monomial n (a * b) := by
simp only [← monomial_zero_left, monomial_mul_monomial, add_zero]
#align polynomial.monomial_mul_C Polynomial.monomial_mul_C
/-- `X` is the polynomial variable (aka indeterminate). -/
def X : R[X] :=
monomial 1 1
#align polynomial.X Polynomial.X
theorem monomial_one_one_eq_X : monomial 1 (1 : R) = X :=
rfl
#align polynomial.monomial_one_one_eq_X Polynomial.monomial_one_one_eq_X
theorem monomial_one_right_eq_X_pow (n : ℕ) : monomial n (1 : R) = X ^ n := by
induction' n with n ih
· simp [monomial_zero_one]
· rw [pow_succ, ← ih, ← monomial_one_one_eq_X, monomial_mul_monomial, mul_one]
#align polynomial.monomial_one_right_eq_X_pow Polynomial.monomial_one_right_eq_X_pow
@[simp]
theorem toFinsupp_X : X.toFinsupp = Finsupp.single 1 (1 : R) :=
rfl
#align polynomial.to_finsupp_X Polynomial.toFinsupp_X
/-- `X` commutes with everything, even when the coefficients are noncommutative. -/
theorem X_mul : X * p = p * X := by
rcases p with ⟨⟩
-- Porting note: `ofFinsupp.injEq` is required.
simp only [X, ← ofFinsupp_single, ← ofFinsupp_mul, LinearMap.coe_mk, ofFinsupp.injEq]
-- Porting note: Was `ext`.
refine Finsupp.ext fun _ => ?_
simp [AddMonoidAlgebra.mul_apply, AddMonoidAlgebra.sum_single_index, add_comm]
#align polynomial.X_mul Polynomial.X_mul
theorem X_pow_mul {n : ℕ} : X ^ n * p = p * X ^ n := by
induction' n with n ih
· simp
· conv_lhs => rw [pow_succ]
rw [mul_assoc, X_mul, ← mul_assoc, ih, mul_assoc, ← pow_succ]
#align polynomial.X_pow_mul Polynomial.X_pow_mul
/-- Prefer putting constants to the left of `X`.
This lemma is the loop-avoiding `simp` version of `Polynomial.X_mul`. -/
@[simp]
theorem X_mul_C (r : R) : X * C r = C r * X :=
X_mul
#align polynomial.X_mul_C Polynomial.X_mul_C
/-- Prefer putting constants to the left of `X ^ n`.
This lemma is the loop-avoiding `simp` version of `X_pow_mul`. -/
@[simp]
theorem X_pow_mul_C (r : R) (n : ℕ) : X ^ n * C r = C r * X ^ n :=
X_pow_mul
#align polynomial.X_pow_mul_C Polynomial.X_pow_mul_C
theorem X_pow_mul_assoc {n : ℕ} : p * X ^ n * q = p * q * X ^ n := by
rw [mul_assoc, X_pow_mul, ← mul_assoc]
#align polynomial.X_pow_mul_assoc Polynomial.X_pow_mul_assoc
/-- Prefer putting constants to the left of `X ^ n`.
This lemma is the loop-avoiding `simp` version of `X_pow_mul_assoc`. -/
@[simp]
theorem X_pow_mul_assoc_C {n : ℕ} (r : R) : p * X ^ n * C r = p * C r * X ^ n :=
X_pow_mul_assoc
#align polynomial.X_pow_mul_assoc_C Polynomial.X_pow_mul_assoc_C
theorem commute_X (p : R[X]) : Commute X p :=
X_mul
#align polynomial.commute_X Polynomial.commute_X
theorem commute_X_pow (p : R[X]) (n : ℕ) : Commute (X ^ n) p :=
X_pow_mul
#align polynomial.commute_X_pow Polynomial.commute_X_pow
@[simp]
theorem monomial_mul_X (n : ℕ) (r : R) : monomial n r * X = monomial (n + 1) r := by
erw [monomial_mul_monomial, mul_one]
#align polynomial.monomial_mul_X Polynomial.monomial_mul_X
@[simp]
theorem monomial_mul_X_pow (n : ℕ) (r : R) (k : ℕ) :
monomial n r * X ^ k = monomial (n + k) r := by
induction' k with k ih
· simp
· simp [ih, pow_succ, ← mul_assoc, add_assoc, Nat.succ_eq_add_one]
#align polynomial.monomial_mul_X_pow Polynomial.monomial_mul_X_pow
@[simp]
theorem X_mul_monomial (n : ℕ) (r : R) : X * monomial n r = monomial (n + 1) r := by
rw [X_mul, monomial_mul_X]
#align polynomial.X_mul_monomial Polynomial.X_mul_monomial
@[simp]
theorem X_pow_mul_monomial (k n : ℕ) (r : R) : X ^ k * monomial n r = monomial (n + k) r := by
rw [X_pow_mul, monomial_mul_X_pow]
#align polynomial.X_pow_mul_monomial Polynomial.X_pow_mul_monomial
/-- `coeff p n` (often denoted `p.coeff n`) is the coefficient of `X^n` in `p`. -/
-- @[simp] -- Porting note: The original generated theorem is same to `coeff_ofFinsupp` and
-- the new generated theorem is different, so this attribute should be
-- removed.
def coeff : R[X] → ℕ → R
| ⟨p⟩ => p
#align polynomial.coeff Polynomial.coeff
-- Porting note (#10756): new theorem
@[simp]
theorem coeff_ofFinsupp (p) : coeff (⟨p⟩ : R[X]) = p := by rw [coeff]
theorem coeff_injective : Injective (coeff : R[X] → ℕ → R) := by
rintro ⟨p⟩ ⟨q⟩
-- Porting note: `ofFinsupp.injEq` is required.
simp only [coeff, DFunLike.coe_fn_eq, imp_self, ofFinsupp.injEq]
#align polynomial.coeff_injective Polynomial.coeff_injective
@[simp]
theorem coeff_inj : p.coeff = q.coeff ↔ p = q :=
coeff_injective.eq_iff
#align polynomial.coeff_inj Polynomial.coeff_inj
theorem toFinsupp_apply (f : R[X]) (i) : f.toFinsupp i = f.coeff i := by cases f; rfl
#align polynomial.to_finsupp_apply Polynomial.toFinsupp_apply
theorem coeff_monomial : coeff (monomial n a) m = if n = m then a else 0 := by
simp [coeff, Finsupp.single_apply]
#align polynomial.coeff_monomial Polynomial.coeff_monomial
@[simp]
theorem coeff_zero (n : ℕ) : coeff (0 : R[X]) n = 0 :=
rfl
#align polynomial.coeff_zero Polynomial.coeff_zero
theorem coeff_one {n : ℕ} : coeff (1 : R[X]) n = if n = 0 then 1 else 0 := by
simp_rw [eq_comm (a := n) (b := 0)]
exact coeff_monomial
#align polynomial.coeff_one Polynomial.coeff_one
@[simp]
theorem coeff_one_zero : coeff (1 : R[X]) 0 = 1 := by
simp [coeff_one]
#align polynomial.coeff_one_zero Polynomial.coeff_one_zero
@[simp]
theorem coeff_X_one : coeff (X : R[X]) 1 = 1 :=
coeff_monomial
#align polynomial.coeff_X_one Polynomial.coeff_X_one
@[simp]
theorem coeff_X_zero : coeff (X : R[X]) 0 = 0 :=
coeff_monomial
#align polynomial.coeff_X_zero Polynomial.coeff_X_zero
@[simp]
theorem coeff_monomial_succ : coeff (monomial (n + 1) a) 0 = 0 := by simp [coeff_monomial]
#align polynomial.coeff_monomial_succ Polynomial.coeff_monomial_succ
theorem coeff_X : coeff (X : R[X]) n = if 1 = n then 1 else 0 :=
coeff_monomial
#align polynomial.coeff_X Polynomial.coeff_X
theorem coeff_X_of_ne_one {n : ℕ} (hn : n ≠ 1) : coeff (X : R[X]) n = 0 := by
rw [coeff_X, if_neg hn.symm]
#align polynomial.coeff_X_of_ne_one Polynomial.coeff_X_of_ne_one
@[simp]
theorem mem_support_iff : n ∈ p.support ↔ p.coeff n ≠ 0 := by
rcases p with ⟨⟩
simp
#align polynomial.mem_support_iff Polynomial.mem_support_iff
theorem not_mem_support_iff : n ∉ p.support ↔ p.coeff n = 0 := by simp
#align polynomial.not_mem_support_iff Polynomial.not_mem_support_iff
theorem coeff_C : coeff (C a) n = ite (n = 0) a 0 := by
convert coeff_monomial (a := a) (m := n) (n := 0) using 2
simp [eq_comm]
#align polynomial.coeff_C Polynomial.coeff_C
@[simp]
theorem coeff_C_zero : coeff (C a) 0 = a :=
coeff_monomial
#align polynomial.coeff_C_zero Polynomial.coeff_C_zero
theorem coeff_C_ne_zero (h : n ≠ 0) : (C a).coeff n = 0 := by rw [coeff_C, if_neg h]
#align polynomial.coeff_C_ne_zero Polynomial.coeff_C_ne_zero
@[simp]
lemma coeff_C_succ {r : R} {n : ℕ} : coeff (C r) (n + 1) = 0 := by simp [coeff_C]
@[simp]
theorem coeff_natCast_ite : (Nat.cast m : R[X]).coeff n = ite (n = 0) m 0 := by
simp only [← C_eq_natCast, coeff_C, Nat.cast_ite, Nat.cast_zero]
@[deprecated (since := "2024-04-17")]
alias coeff_nat_cast_ite := coeff_natCast_ite
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem coeff_ofNat_zero (a : ℕ) [a.AtLeastTwo] :
coeff (no_index (OfNat.ofNat a : R[X])) 0 = OfNat.ofNat a :=
coeff_monomial
-- See note [no_index around OfNat.ofNat]
@[simp]
theorem coeff_ofNat_succ (a n : ℕ) [h : a.AtLeastTwo] :
coeff (no_index (OfNat.ofNat a : R[X])) (n + 1) = 0 := by
rw [← Nat.cast_eq_ofNat]
simp
theorem C_mul_X_pow_eq_monomial : ∀ {n : ℕ}, C a * X ^ n = monomial n a
| 0 => mul_one _
| n + 1 => by
rw [pow_succ, ← mul_assoc, C_mul_X_pow_eq_monomial, X, monomial_mul_monomial, mul_one]
#align polynomial.C_mul_X_pow_eq_monomial Polynomial.C_mul_X_pow_eq_monomial
@[simp high]
theorem toFinsupp_C_mul_X_pow (a : R) (n : ℕ) :
Polynomial.toFinsupp (C a * X ^ n) = Finsupp.single n a := by
rw [C_mul_X_pow_eq_monomial, toFinsupp_monomial]
#align polynomial.to_finsupp_C_mul_X_pow Polynomial.toFinsupp_C_mul_X_pow
theorem C_mul_X_eq_monomial : C a * X = monomial 1 a := by rw [← C_mul_X_pow_eq_monomial, pow_one]
#align polynomial.C_mul_X_eq_monomial Polynomial.C_mul_X_eq_monomial
@[simp high]
theorem toFinsupp_C_mul_X (a : R) : Polynomial.toFinsupp (C a * X) = Finsupp.single 1 a := by
rw [C_mul_X_eq_monomial, toFinsupp_monomial]
#align polynomial.to_finsupp_C_mul_X Polynomial.toFinsupp_C_mul_X
theorem C_injective : Injective (C : R → R[X]) :=
monomial_injective 0
#align polynomial.C_injective Polynomial.C_injective
@[simp]
theorem C_inj : C a = C b ↔ a = b :=
C_injective.eq_iff
#align polynomial.C_inj Polynomial.C_inj
@[simp]
theorem C_eq_zero : C a = 0 ↔ a = 0 :=
C_injective.eq_iff' (map_zero C)
#align polynomial.C_eq_zero Polynomial.C_eq_zero
theorem C_ne_zero : C a ≠ 0 ↔ a ≠ 0 :=
C_eq_zero.not
#align polynomial.C_ne_zero Polynomial.C_ne_zero
theorem subsingleton_iff_subsingleton : Subsingleton R[X] ↔ Subsingleton R :=
⟨@Injective.subsingleton _ _ _ C_injective, by
intro
infer_instance⟩
#align polynomial.subsingleton_iff_subsingleton Polynomial.subsingleton_iff_subsingleton
theorem Nontrivial.of_polynomial_ne (h : p ≠ q) : Nontrivial R :=
(subsingleton_or_nontrivial R).resolve_left fun _hI => h <| Subsingleton.elim _ _
#align polynomial.nontrivial.of_polynomial_ne Polynomial.Nontrivial.of_polynomial_ne
theorem forall_eq_iff_forall_eq : (∀ f g : R[X], f = g) ↔ ∀ a b : R, a = b := by
simpa only [← subsingleton_iff] using subsingleton_iff_subsingleton
#align polynomial.forall_eq_iff_forall_eq Polynomial.forall_eq_iff_forall_eq
theorem ext_iff {p q : R[X]} : p = q ↔ ∀ n, coeff p n = coeff q n := by
rcases p with ⟨f : ℕ →₀ R⟩
rcases q with ⟨g : ℕ →₀ R⟩
-- porting note (#10745): was `simp [coeff, DFunLike.ext_iff]`
simpa [coeff] using DFunLike.ext_iff (f := f) (g := g)
#align polynomial.ext_iff Polynomial.ext_iff
@[ext]
theorem ext {p q : R[X]} : (∀ n, coeff p n = coeff q n) → p = q :=
ext_iff.2
#align polynomial.ext Polynomial.ext
/-- Monomials generate the additive monoid of polynomials. -/
theorem addSubmonoid_closure_setOf_eq_monomial :
AddSubmonoid.closure { p : R[X] | ∃ n a, p = monomial n a } = ⊤ := by
apply top_unique
rw [← AddSubmonoid.map_equiv_top (toFinsuppIso R).symm.toAddEquiv, ←
Finsupp.add_closure_setOf_eq_single, AddMonoidHom.map_mclosure]
refine AddSubmonoid.closure_mono (Set.image_subset_iff.2 ?_)
rintro _ ⟨n, a, rfl⟩
exact ⟨n, a, Polynomial.ofFinsupp_single _ _⟩
#align polynomial.add_submonoid_closure_set_of_eq_monomial Polynomial.addSubmonoid_closure_setOf_eq_monomial
theorem addHom_ext {M : Type*} [AddMonoid M] {f g : R[X] →+ M}
(h : ∀ n a, f (monomial n a) = g (monomial n a)) : f = g :=
AddMonoidHom.eq_of_eqOn_denseM addSubmonoid_closure_setOf_eq_monomial <| by
rintro p ⟨n, a, rfl⟩
exact h n a
#align polynomial.add_hom_ext Polynomial.addHom_ext
@[ext high]
theorem addHom_ext' {M : Type*} [AddMonoid M] {f g : R[X] →+ M}
(h : ∀ n, f.comp (monomial n).toAddMonoidHom = g.comp (monomial n).toAddMonoidHom) : f = g :=
addHom_ext fun n => DFunLike.congr_fun (h n)
#align polynomial.add_hom_ext' Polynomial.addHom_ext'
@[ext high]
theorem lhom_ext' {M : Type*} [AddCommMonoid M] [Module R M] {f g : R[X] →ₗ[R] M}
(h : ∀ n, f.comp (monomial n) = g.comp (monomial n)) : f = g :=
LinearMap.toAddMonoidHom_injective <| addHom_ext fun n => LinearMap.congr_fun (h n)
#align polynomial.lhom_ext' Polynomial.lhom_ext'
-- this has the same content as the subsingleton
theorem eq_zero_of_eq_zero (h : (0 : R) = (1 : R)) (p : R[X]) : p = 0 := by
rw [← one_smul R p, ← h, zero_smul]
#align polynomial.eq_zero_of_eq_zero Polynomial.eq_zero_of_eq_zero
section Fewnomials
theorem support_monomial (n) {a : R} (H : a ≠ 0) : (monomial n a).support = singleton n := by
rw [← ofFinsupp_single, support]; exact Finsupp.support_single_ne_zero _ H
#align polynomial.support_monomial Polynomial.support_monomial
theorem support_monomial' (n) (a : R) : (monomial n a).support ⊆ singleton n := by
rw [← ofFinsupp_single, support]
exact Finsupp.support_single_subset
#align polynomial.support_monomial' Polynomial.support_monomial'
theorem support_C_mul_X {c : R} (h : c ≠ 0) : Polynomial.support (C c * X) = singleton 1 := by
rw [C_mul_X_eq_monomial, support_monomial 1 h]
#align polynomial.support_C_mul_X Polynomial.support_C_mul_X
theorem support_C_mul_X' (c : R) : Polynomial.support (C c * X) ⊆ singleton 1 := by
simpa only [C_mul_X_eq_monomial] using support_monomial' 1 c
#align polynomial.support_C_mul_X' Polynomial.support_C_mul_X'
theorem support_C_mul_X_pow (n : ℕ) {c : R} (h : c ≠ 0) :
Polynomial.support (C c * X ^ n) = singleton n := by
rw [C_mul_X_pow_eq_monomial, support_monomial n h]
#align polynomial.support_C_mul_X_pow Polynomial.support_C_mul_X_pow
theorem support_C_mul_X_pow' (n : ℕ) (c : R) : Polynomial.support (C c * X ^ n) ⊆ singleton n := by
simpa only [C_mul_X_pow_eq_monomial] using support_monomial' n c
#align polynomial.support_C_mul_X_pow' Polynomial.support_C_mul_X_pow'
open Finset
theorem support_binomial' (k m : ℕ) (x y : R) :
Polynomial.support (C x * X ^ k + C y * X ^ m) ⊆ {k, m} :=
support_add.trans
(union_subset
((support_C_mul_X_pow' k x).trans (singleton_subset_iff.mpr (mem_insert_self k {m})))
((support_C_mul_X_pow' m y).trans
(singleton_subset_iff.mpr (mem_insert_of_mem (mem_singleton_self m)))))
#align polynomial.support_binomial' Polynomial.support_binomial'
theorem support_trinomial' (k m n : ℕ) (x y z : R) :
Polynomial.support (C x * X ^ k + C y * X ^ m + C z * X ^ n) ⊆ {k, m, n} :=
support_add.trans
(union_subset
(support_add.trans
(union_subset
((support_C_mul_X_pow' k x).trans (singleton_subset_iff.mpr (mem_insert_self k {m, n})))
((support_C_mul_X_pow' m y).trans
(singleton_subset_iff.mpr (mem_insert_of_mem (mem_insert_self m {n}))))))
((support_C_mul_X_pow' n z).trans
(singleton_subset_iff.mpr (mem_insert_of_mem (mem_insert_of_mem (mem_singleton_self n))))))
#align polynomial.support_trinomial' Polynomial.support_trinomial'
end Fewnomials
theorem X_pow_eq_monomial (n) : X ^ n = monomial n (1 : R) := by
induction' n with n hn
· rw [pow_zero, monomial_zero_one]
· rw [pow_succ, hn, X, monomial_mul_monomial, one_mul]
#align polynomial.X_pow_eq_monomial Polynomial.X_pow_eq_monomial
@[simp high]
theorem toFinsupp_X_pow (n : ℕ) : (X ^ n).toFinsupp = Finsupp.single n (1 : R) := by
rw [X_pow_eq_monomial, toFinsupp_monomial]
#align polynomial.to_finsupp_X_pow Polynomial.toFinsupp_X_pow
theorem smul_X_eq_monomial {n} : a • X ^ n = monomial n (a : R) := by
rw [X_pow_eq_monomial, smul_monomial, smul_eq_mul, mul_one]
#align polynomial.smul_X_eq_monomial Polynomial.smul_X_eq_monomial
theorem support_X_pow (H : ¬(1 : R) = 0) (n : ℕ) : (X ^ n : R[X]).support = singleton n := by
convert support_monomial n H
exact X_pow_eq_monomial n
#align polynomial.support_X_pow Polynomial.support_X_pow
theorem support_X_empty (H : (1 : R) = 0) : (X : R[X]).support = ∅ := by
rw [X, H, monomial_zero_right, support_zero]
#align polynomial.support_X_empty Polynomial.support_X_empty
theorem support_X (H : ¬(1 : R) = 0) : (X : R[X]).support = singleton 1 := by
rw [← pow_one X, support_X_pow H 1]
#align polynomial.support_X Polynomial.support_X
theorem monomial_left_inj {a : R} (ha : a ≠ 0) {i j : ℕ} :
monomial i a = monomial j a ↔ i = j := by
simp only [← ofFinsupp_single, ofFinsupp.injEq, Finsupp.single_left_inj ha]
#align polynomial.monomial_left_inj Polynomial.monomial_left_inj
theorem binomial_eq_binomial {k l m n : ℕ} {u v : R} (hu : u ≠ 0) (hv : v ≠ 0) :
C u * X ^ k + C v * X ^ l = C u * X ^ m + C v * X ^ n ↔
k = m ∧ l = n ∨ u = v ∧ k = n ∧ l = m ∨ u + v = 0 ∧ k = l ∧ m = n := by
simp_rw [C_mul_X_pow_eq_monomial, ← toFinsupp_inj, toFinsupp_add, toFinsupp_monomial]
exact Finsupp.single_add_single_eq_single_add_single hu hv
#align polynomial.binomial_eq_binomial Polynomial.binomial_eq_binomial
theorem natCast_mul (n : ℕ) (p : R[X]) : (n : R[X]) * p = n • p :=
(nsmul_eq_mul _ _).symm
#align polynomial.nat_cast_mul Polynomial.natCast_mul
@[deprecated (since := "2024-04-17")]
alias nat_cast_mul := natCast_mul
/-- Summing the values of a function applied to the coefficients of a polynomial -/
def sum {S : Type*} [AddCommMonoid S] (p : R[X]) (f : ℕ → R → S) : S :=
∑ n ∈ p.support, f n (p.coeff n)
#align polynomial.sum Polynomial.sum
theorem sum_def {S : Type*} [AddCommMonoid S] (p : R[X]) (f : ℕ → R → S) :
p.sum f = ∑ n ∈ p.support, f n (p.coeff n) :=
rfl
#align polynomial.sum_def Polynomial.sum_def
theorem sum_eq_of_subset {S : Type*} [AddCommMonoid S] {p : R[X]} (f : ℕ → R → S)
(hf : ∀ i, f i 0 = 0) {s : Finset ℕ} (hs : p.support ⊆ s) :
p.sum f = ∑ n ∈ s, f n (p.coeff n) :=
Finsupp.sum_of_support_subset _ hs f (fun i _ ↦ hf i)
#align polynomial.sum_eq_of_subset Polynomial.sum_eq_of_subset
/-- Expressing the product of two polynomials as a double sum. -/
theorem mul_eq_sum_sum :
p * q = ∑ i ∈ p.support, q.sum fun j a => (monomial (i + j)) (p.coeff i * a) := by
apply toFinsupp_injective
rcases p with ⟨⟩; rcases q with ⟨⟩
simp_rw [sum, coeff, toFinsupp_sum, support, toFinsupp_mul, toFinsupp_monomial,
AddMonoidAlgebra.mul_def, Finsupp.sum]
#align polynomial.mul_eq_sum_sum Polynomial.mul_eq_sum_sum
@[simp]
theorem sum_zero_index {S : Type*} [AddCommMonoid S] (f : ℕ → R → S) : (0 : R[X]).sum f = 0 := by
simp [sum]
#align polynomial.sum_zero_index Polynomial.sum_zero_index
@[simp]
theorem sum_monomial_index {S : Type*} [AddCommMonoid S] {n : ℕ} (a : R) (f : ℕ → R → S)
(hf : f n 0 = 0) : (monomial n a : R[X]).sum f = f n a :=
Finsupp.sum_single_index hf
#align polynomial.sum_monomial_index Polynomial.sum_monomial_index
@[simp]
theorem sum_C_index {a} {β} [AddCommMonoid β] {f : ℕ → R → β} (h : f 0 0 = 0) :
(C a).sum f = f 0 a :=
sum_monomial_index a f h
#align polynomial.sum_C_index Polynomial.sum_C_index
-- the assumption `hf` is only necessary when the ring is trivial
@[simp]
theorem sum_X_index {S : Type*} [AddCommMonoid S] {f : ℕ → R → S} (hf : f 1 0 = 0) :
(X : R[X]).sum f = f 1 1 :=
sum_monomial_index 1 f hf
#align polynomial.sum_X_index Polynomial.sum_X_index
theorem sum_add_index {S : Type*} [AddCommMonoid S] (p q : R[X]) (f : ℕ → R → S)
(hf : ∀ i, f i 0 = 0) (h_add : ∀ a b₁ b₂, f a (b₁ + b₂) = f a b₁ + f a b₂) :
(p + q).sum f = p.sum f + q.sum f := by
rw [show p + q = ⟨p.toFinsupp + q.toFinsupp⟩ from add_def p q]
exact Finsupp.sum_add_index (fun i _ ↦ hf i) (fun a _ b₁ b₂ ↦ h_add a b₁ b₂)
#align polynomial.sum_add_index Polynomial.sum_add_index
| Mathlib/Algebra/Polynomial/Basic.lean | 1,035 | 1,036 | theorem sum_add' {S : Type*} [AddCommMonoid S] (p : R[X]) (f g : ℕ → R → S) :
p.sum (f + g) = p.sum f + p.sum g := by | simp [sum_def, Finset.sum_add_distrib]
|
/-
Copyright (c) 2020 Aaron Anderson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Aaron Anderson
-/
import Mathlib.RingTheory.Nilpotent.Basic
import Mathlib.RingTheory.UniqueFactorizationDomain
#align_import algebra.squarefree from "leanprover-community/mathlib"@"00d163e35035c3577c1c79fa53b68de17781ffc1"
/-!
# Squarefree elements of monoids
An element of a monoid is squarefree when it is not divisible by any squares
except the squares of units.
Results about squarefree natural numbers are proved in `Data.Nat.Squarefree`.
## Main Definitions
- `Squarefree r` indicates that `r` is only divisible by `x * x` if `x` is a unit.
## Main Results
- `multiplicity.squarefree_iff_multiplicity_le_one`: `x` is `Squarefree` iff for every `y`, either
`multiplicity y x ≤ 1` or `IsUnit y`.
- `UniqueFactorizationMonoid.squarefree_iff_nodup_factors`: A nonzero element `x` of a unique
factorization monoid is squarefree iff `factors x` has no duplicate factors.
## Tags
squarefree, multiplicity
-/
variable {R : Type*}
/-- An element of a monoid is squarefree if the only squares that
divide it are the squares of units. -/
def Squarefree [Monoid R] (r : R) : Prop :=
∀ x : R, x * x ∣ r → IsUnit x
#align squarefree Squarefree
theorem IsRelPrime.of_squarefree_mul [CommMonoid R] {m n : R} (h : Squarefree (m * n)) :
IsRelPrime m n := fun c hca hcb ↦ h c (mul_dvd_mul hca hcb)
@[simp]
theorem IsUnit.squarefree [CommMonoid R] {x : R} (h : IsUnit x) : Squarefree x := fun _ hdvd =>
isUnit_of_mul_isUnit_left (isUnit_of_dvd_unit hdvd h)
#align is_unit.squarefree IsUnit.squarefree
-- @[simp] -- Porting note (#10618): simp can prove this
theorem squarefree_one [CommMonoid R] : Squarefree (1 : R) :=
isUnit_one.squarefree
#align squarefree_one squarefree_one
@[simp]
theorem not_squarefree_zero [MonoidWithZero R] [Nontrivial R] : ¬Squarefree (0 : R) := by
erw [not_forall]
exact ⟨0, by simp⟩
#align not_squarefree_zero not_squarefree_zero
theorem Squarefree.ne_zero [MonoidWithZero R] [Nontrivial R] {m : R} (hm : Squarefree (m : R)) :
m ≠ 0 := by
rintro rfl
exact not_squarefree_zero hm
#align squarefree.ne_zero Squarefree.ne_zero
@[simp]
theorem Irreducible.squarefree [CommMonoid R] {x : R} (h : Irreducible x) : Squarefree x := by
rintro y ⟨z, hz⟩
rw [mul_assoc] at hz
rcases h.isUnit_or_isUnit hz with (hu | hu)
· exact hu
· apply isUnit_of_mul_isUnit_left hu
#align irreducible.squarefree Irreducible.squarefree
@[simp]
theorem Prime.squarefree [CancelCommMonoidWithZero R] {x : R} (h : Prime x) : Squarefree x :=
h.irreducible.squarefree
#align prime.squarefree Prime.squarefree
theorem Squarefree.of_mul_left [CommMonoid R] {m n : R} (hmn : Squarefree (m * n)) : Squarefree m :=
fun p hp => hmn p (dvd_mul_of_dvd_left hp n)
#align squarefree.of_mul_left Squarefree.of_mul_left
theorem Squarefree.of_mul_right [CommMonoid R] {m n : R} (hmn : Squarefree (m * n)) :
Squarefree n := fun p hp => hmn p (dvd_mul_of_dvd_right hp m)
#align squarefree.of_mul_right Squarefree.of_mul_right
theorem Squarefree.squarefree_of_dvd [CommMonoid R] {x y : R} (hdvd : x ∣ y) (hsq : Squarefree y) :
Squarefree x := fun _ h => hsq _ (h.trans hdvd)
#align squarefree.squarefree_of_dvd Squarefree.squarefree_of_dvd
theorem Squarefree.eq_zero_or_one_of_pow_of_not_isUnit [CommMonoid R] {x : R} {n : ℕ}
(h : Squarefree (x ^ n)) (h' : ¬ IsUnit x) :
n = 0 ∨ n = 1 := by
contrapose! h'
replace h' : 2 ≤ n := by omega
have : x * x ∣ x ^ n := by rw [← sq]; exact pow_dvd_pow x h'
exact h.squarefree_of_dvd this x (refl _)
section SquarefreeGcdOfSquarefree
variable {α : Type*} [CancelCommMonoidWithZero α] [GCDMonoid α]
theorem Squarefree.gcd_right (a : α) {b : α} (hb : Squarefree b) : Squarefree (gcd a b) :=
hb.squarefree_of_dvd (gcd_dvd_right _ _)
#align squarefree.gcd_right Squarefree.gcd_right
theorem Squarefree.gcd_left {a : α} (b : α) (ha : Squarefree a) : Squarefree (gcd a b) :=
ha.squarefree_of_dvd (gcd_dvd_left _ _)
#align squarefree.gcd_left Squarefree.gcd_left
end SquarefreeGcdOfSquarefree
namespace multiplicity
section CommMonoid
variable [CommMonoid R] [DecidableRel (Dvd.dvd : R → R → Prop)]
theorem squarefree_iff_multiplicity_le_one (r : R) :
Squarefree r ↔ ∀ x : R, multiplicity x r ≤ 1 ∨ IsUnit x := by
refine forall_congr' fun a => ?_
rw [← sq, pow_dvd_iff_le_multiplicity, or_iff_not_imp_left, not_le, imp_congr _ Iff.rfl]
norm_cast
rw [← one_add_one_eq_two]
simpa using PartENat.add_one_le_iff_lt (PartENat.natCast_ne_top 1)
#align multiplicity.squarefree_iff_multiplicity_le_one multiplicity.squarefree_iff_multiplicity_le_one
end CommMonoid
section CancelCommMonoidWithZero
variable [CancelCommMonoidWithZero R] [WfDvdMonoid R]
theorem finite_prime_left {a b : R} (ha : Prime a) (hb : b ≠ 0) : multiplicity.Finite a b :=
finite_of_not_isUnit ha.not_unit hb
#align multiplicity.finite_prime_left multiplicity.finite_prime_left
end CancelCommMonoidWithZero
end multiplicity
section Irreducible
variable [CommMonoidWithZero R] [WfDvdMonoid R]
theorem squarefree_iff_no_irreducibles {x : R} (hx₀ : x ≠ 0) :
Squarefree x ↔ ∀ p, Irreducible p → ¬ (p * p ∣ x) := by
refine ⟨fun h p hp hp' ↦ hp.not_unit (h p hp'), fun h d hd ↦ by_contra fun hdu ↦ ?_⟩
have hd₀ : d ≠ 0 := ne_zero_of_dvd_ne_zero (ne_zero_of_dvd_ne_zero hx₀ hd) (dvd_mul_left d d)
obtain ⟨p, irr, dvd⟩ := WfDvdMonoid.exists_irreducible_factor hdu hd₀
exact h p irr ((mul_dvd_mul dvd dvd).trans hd)
theorem irreducible_sq_not_dvd_iff_eq_zero_and_no_irreducibles_or_squarefree (r : R) :
(∀ x : R, Irreducible x → ¬x * x ∣ r) ↔ (r = 0 ∧ ∀ x : R, ¬Irreducible x) ∨ Squarefree r := by
refine ⟨fun h ↦ ?_, ?_⟩
· rcases eq_or_ne r 0 with (rfl | hr)
· exact .inl (by simpa using h)
· exact .inr ((squarefree_iff_no_irreducibles hr).mpr h)
· rintro (⟨rfl, h⟩ | h)
· simpa using h
intro x hx t
exact hx.not_unit (h x t)
#align irreducible_sq_not_dvd_iff_eq_zero_and_no_irreducibles_or_squarefree irreducible_sq_not_dvd_iff_eq_zero_and_no_irreducibles_or_squarefree
theorem squarefree_iff_irreducible_sq_not_dvd_of_ne_zero {r : R} (hr : r ≠ 0) :
Squarefree r ↔ ∀ x : R, Irreducible x → ¬x * x ∣ r := by
simpa [hr] using (irreducible_sq_not_dvd_iff_eq_zero_and_no_irreducibles_or_squarefree r).symm
#align squarefree_iff_irreducible_sq_not_dvd_of_ne_zero squarefree_iff_irreducible_sq_not_dvd_of_ne_zero
theorem squarefree_iff_irreducible_sq_not_dvd_of_exists_irreducible {r : R}
(hr : ∃ x : R, Irreducible x) : Squarefree r ↔ ∀ x : R, Irreducible x → ¬x * x ∣ r := by
rw [irreducible_sq_not_dvd_iff_eq_zero_and_no_irreducibles_or_squarefree, ← not_exists]
simp only [hr, not_true, false_or_iff, and_false_iff]
#align squarefree_iff_irreducible_sq_not_dvd_of_exists_irreducible squarefree_iff_irreducible_sq_not_dvd_of_exists_irreducible
end Irreducible
section IsRadical
section
variable [CommMonoidWithZero R] [DecompositionMonoid R]
theorem Squarefree.isRadical {x : R} (hx : Squarefree x) : IsRadical x :=
(isRadical_iff_pow_one_lt 2 one_lt_two).2 fun y hy ↦ by
obtain ⟨a, b, ha, hb, rfl⟩ := exists_dvd_and_dvd_of_dvd_mul (sq y ▸ hy)
exact (IsRelPrime.of_squarefree_mul hx).mul_dvd ha hb
#align squarefree.is_radical Squarefree.isRadical
theorem Squarefree.dvd_pow_iff_dvd {x y : R} {n : ℕ} (hsq : Squarefree x) (h0 : n ≠ 0) :
x ∣ y ^ n ↔ x ∣ y := ⟨hsq.isRadical n y, (·.pow h0)⟩
#align unique_factorization_monoid.dvd_pow_iff_dvd_of_squarefree Squarefree.dvd_pow_iff_dvd
@[deprecated (since := "2024-02-12")]
alias UniqueFactorizationMonoid.dvd_pow_iff_dvd_of_squarefree := Squarefree.dvd_pow_iff_dvd
end
variable [CancelCommMonoidWithZero R] {x y p d : R}
theorem IsRadical.squarefree (h0 : x ≠ 0) (h : IsRadical x) : Squarefree x := by
rintro z ⟨w, rfl⟩
specialize h 2 (z * w) ⟨w, by simp_rw [pow_two, mul_left_comm, ← mul_assoc]⟩
rwa [← one_mul (z * w), mul_assoc, mul_dvd_mul_iff_right, ← isUnit_iff_dvd_one] at h
rw [mul_assoc, mul_ne_zero_iff] at h0; exact h0.2
#align is_radical.squarefree IsRadical.squarefree
namespace Squarefree
theorem pow_dvd_of_squarefree_of_pow_succ_dvd_mul_right {k : ℕ}
(hx : Squarefree x) (hp : Prime p) (h : p ^ (k + 1) ∣ x * y) :
p ^ k ∣ y := by
by_cases hxp : p ∣ x
· obtain ⟨x', rfl⟩ := hxp
have hx' : ¬ p ∣ x' := fun contra ↦ hp.not_unit <| hx p (mul_dvd_mul_left p contra)
replace h : p ^ k ∣ x' * y := by
rw [pow_succ', mul_assoc] at h
exact (mul_dvd_mul_iff_left hp.ne_zero).mp h
exact hp.pow_dvd_of_dvd_mul_left _ hx' h
· exact (pow_dvd_pow _ k.le_succ).trans (hp.pow_dvd_of_dvd_mul_left _ hxp h)
theorem pow_dvd_of_squarefree_of_pow_succ_dvd_mul_left {k : ℕ}
(hy : Squarefree y) (hp : Prime p) (h : p ^ (k + 1) ∣ x * y) :
p ^ k ∣ x := by
rw [mul_comm] at h
exact pow_dvd_of_squarefree_of_pow_succ_dvd_mul_right hy hp h
variable [DecompositionMonoid R]
theorem dvd_of_squarefree_of_mul_dvd_mul_right (hx : Squarefree x) (h : d * d ∣ x * y) : d ∣ y := by
nontriviality R
obtain ⟨a, b, ha, hb, eq⟩ := exists_dvd_and_dvd_of_dvd_mul h
replace ha : Squarefree a := hx.squarefree_of_dvd ha
obtain ⟨c, hc⟩ : a ∣ d := ha.isRadical 2 d ⟨b, by rw [sq, eq]⟩
rw [hc, mul_assoc, (mul_right_injective₀ ha.ne_zero).eq_iff] at eq
exact dvd_trans ⟨c, by rw [hc, ← eq, mul_comm]⟩ hb
theorem dvd_of_squarefree_of_mul_dvd_mul_left (hy : Squarefree y) (h : d * d ∣ x * y) : d ∣ x :=
dvd_of_squarefree_of_mul_dvd_mul_right hy (mul_comm x y ▸ h)
end Squarefree
variable [DecompositionMonoid R]
/-- `x * y` is square-free iff `x` and `y` have no common factors and are themselves square-free. -/
theorem squarefree_mul_iff : Squarefree (x * y) ↔ IsRelPrime x y ∧ Squarefree x ∧ Squarefree y :=
⟨fun h ↦ ⟨IsRelPrime.of_squarefree_mul h, h.of_mul_left, h.of_mul_right⟩,
fun ⟨hp, sqx, sqy⟩ _ dvd ↦ hp (sqy.dvd_of_squarefree_of_mul_dvd_mul_left dvd)
(sqx.dvd_of_squarefree_of_mul_dvd_mul_right dvd)⟩
theorem isRadical_iff_squarefree_or_zero : IsRadical x ↔ Squarefree x ∨ x = 0 :=
⟨fun hx ↦ (em <| x = 0).elim .inr fun h ↦ .inl <| hx.squarefree h,
Or.rec Squarefree.isRadical <| by
rintro rfl
rw [zero_isRadical_iff]
infer_instance⟩
#align is_radical_iff_squarefree_or_zero isRadical_iff_squarefree_or_zero
theorem isRadical_iff_squarefree_of_ne_zero (h : x ≠ 0) : IsRadical x ↔ Squarefree x :=
⟨IsRadical.squarefree h, Squarefree.isRadical⟩
#align is_radical_iff_squarefree_of_ne_zero isRadical_iff_squarefree_of_ne_zero
end IsRadical
namespace UniqueFactorizationMonoid
variable [CancelCommMonoidWithZero R] [UniqueFactorizationMonoid R]
lemma _root_.exists_squarefree_dvd_pow_of_ne_zero {x : R} (hx : x ≠ 0) :
∃ (y : R) (n : ℕ), Squarefree y ∧ y ∣ x ∧ x ∣ y ^ n := by
induction' x using WfDvdMonoid.induction_on_irreducible with u hu z p hz hp ih
· contradiction
· exact ⟨1, 0, squarefree_one, one_dvd u, hu.dvd⟩
· obtain ⟨y, n, hy, hyx, hy'⟩ := ih hz
rcases n.eq_zero_or_pos with rfl | hn
· exact ⟨p, 1, hp.squarefree, dvd_mul_right p z, by simp [isUnit_of_dvd_one (pow_zero y ▸ hy')]⟩
by_cases hp' : p ∣ y
· exact ⟨y, n + 1, hy, dvd_mul_of_dvd_right hyx _,
mul_comm p z ▸ pow_succ y n ▸ mul_dvd_mul hy' hp'⟩
· suffices Squarefree (p * y) from ⟨p * y, n, this,
mul_dvd_mul_left p hyx, mul_pow p y n ▸ mul_dvd_mul (dvd_pow_self p hn.ne') hy'⟩
exact squarefree_mul_iff.mpr ⟨hp.isRelPrime_iff_not_dvd.mpr hp', hp.squarefree, hy⟩
theorem squarefree_iff_nodup_normalizedFactors [NormalizationMonoid R] {x : R}
(x0 : x ≠ 0) : Squarefree x ↔ Multiset.Nodup (normalizedFactors x) := by
classical
rw [multiplicity.squarefree_iff_multiplicity_le_one, Multiset.nodup_iff_count_le_one]
haveI := nontrivial_of_ne x 0 x0
constructor <;> intro h a
· by_cases hmem : a ∈ normalizedFactors x
· have ha := irreducible_of_normalized_factor _ hmem
rcases h a with (h | h)
· rw [← normalize_normalized_factor _ hmem]
rw [multiplicity_eq_count_normalizedFactors ha x0] at h
assumption_mod_cast
· have := ha.1
contradiction
· simp [Multiset.count_eq_zero_of_not_mem hmem]
· rw [or_iff_not_imp_right]
intro hu
rcases eq_or_ne a 0 with rfl | h0
· simp [x0]
rcases WfDvdMonoid.exists_irreducible_factor hu h0 with ⟨b, hib, hdvd⟩
apply le_trans (multiplicity.multiplicity_le_multiplicity_of_dvd_left hdvd)
rw [multiplicity_eq_count_normalizedFactors hib x0]
exact_mod_cast h (normalize b)
#align unique_factorization_monoid.squarefree_iff_nodup_normalized_factors UniqueFactorizationMonoid.squarefree_iff_nodup_normalizedFactors
end UniqueFactorizationMonoid
namespace Int
@[simp]
theorem squarefree_natAbs {n : ℤ} : Squarefree n.natAbs ↔ Squarefree n := by
simp_rw [Squarefree, natAbs_surjective.forall, ← natAbs_mul, natAbs_dvd_natAbs,
isUnit_iff_natAbs_eq, Nat.isUnit_iff]
#align int.squarefree_nat_abs Int.squarefree_natAbs
@[simp]
| Mathlib/Algebra/Squarefree/Basic.lean | 320 | 321 | theorem squarefree_natCast {n : ℕ} : Squarefree (n : ℤ) ↔ Squarefree n := by |
rw [← squarefree_natAbs, natAbs_ofNat]
|
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou
-/
import Mathlib.MeasureTheory.Function.LpOrder
#align_import measure_theory.function.l1_space from "leanprover-community/mathlib"@"ccdbfb6e5614667af5aa3ab2d50885e0ef44a46f"
/-!
# Integrable functions and `L¹` space
In the first part of this file, the predicate `Integrable` is defined and basic properties of
integrable functions are proved.
Such a predicate is already available under the name `Memℒp 1`. We give a direct definition which
is easier to use, and show that it is equivalent to `Memℒp 1`
In the second part, we establish an API between `Integrable` and the space `L¹` of equivalence
classes of integrable functions, already defined as a special case of `L^p` spaces for `p = 1`.
## Notation
* `α →₁[μ] β` is the type of `L¹` space, where `α` is a `MeasureSpace` and `β` is a
`NormedAddCommGroup` with a `SecondCountableTopology`. `f : α →ₘ β` is a "function" in `L¹`.
In comments, `[f]` is also used to denote an `L¹` function.
`₁` can be typed as `\1`.
## Main definitions
* Let `f : α → β` be a function, where `α` is a `MeasureSpace` and `β` a `NormedAddCommGroup`.
Then `HasFiniteIntegral f` means `(∫⁻ a, ‖f a‖₊) < ∞`.
* If `β` is moreover a `MeasurableSpace` then `f` is called `Integrable` if
`f` is `Measurable` and `HasFiniteIntegral f` holds.
## Implementation notes
To prove something for an arbitrary integrable function, a useful theorem is
`Integrable.induction` in the file `SetIntegral`.
## Tags
integrable, function space, l1
-/
noncomputable section
open scoped Classical
open Topology ENNReal MeasureTheory NNReal
open Set Filter TopologicalSpace ENNReal EMetric MeasureTheory
variable {α β γ δ : Type*} {m : MeasurableSpace α} {μ ν : Measure α} [MeasurableSpace δ]
variable [NormedAddCommGroup β]
variable [NormedAddCommGroup γ]
namespace MeasureTheory
/-! ### Some results about the Lebesgue integral involving a normed group -/
theorem lintegral_nnnorm_eq_lintegral_edist (f : α → β) :
∫⁻ a, ‖f a‖₊ ∂μ = ∫⁻ a, edist (f a) 0 ∂μ := by simp only [edist_eq_coe_nnnorm]
#align measure_theory.lintegral_nnnorm_eq_lintegral_edist MeasureTheory.lintegral_nnnorm_eq_lintegral_edist
theorem lintegral_norm_eq_lintegral_edist (f : α → β) :
∫⁻ a, ENNReal.ofReal ‖f a‖ ∂μ = ∫⁻ a, edist (f a) 0 ∂μ := by
simp only [ofReal_norm_eq_coe_nnnorm, edist_eq_coe_nnnorm]
#align measure_theory.lintegral_norm_eq_lintegral_edist MeasureTheory.lintegral_norm_eq_lintegral_edist
theorem lintegral_edist_triangle {f g h : α → β} (hf : AEStronglyMeasurable f μ)
(hh : AEStronglyMeasurable h μ) :
(∫⁻ a, edist (f a) (g a) ∂μ) ≤ (∫⁻ a, edist (f a) (h a) ∂μ) + ∫⁻ a, edist (g a) (h a) ∂μ := by
rw [← lintegral_add_left' (hf.edist hh)]
refine lintegral_mono fun a => ?_
apply edist_triangle_right
#align measure_theory.lintegral_edist_triangle MeasureTheory.lintegral_edist_triangle
theorem lintegral_nnnorm_zero : (∫⁻ _ : α, ‖(0 : β)‖₊ ∂μ) = 0 := by simp
#align measure_theory.lintegral_nnnorm_zero MeasureTheory.lintegral_nnnorm_zero
theorem lintegral_nnnorm_add_left {f : α → β} (hf : AEStronglyMeasurable f μ) (g : α → γ) :
∫⁻ a, ‖f a‖₊ + ‖g a‖₊ ∂μ = (∫⁻ a, ‖f a‖₊ ∂μ) + ∫⁻ a, ‖g a‖₊ ∂μ :=
lintegral_add_left' hf.ennnorm _
#align measure_theory.lintegral_nnnorm_add_left MeasureTheory.lintegral_nnnorm_add_left
theorem lintegral_nnnorm_add_right (f : α → β) {g : α → γ} (hg : AEStronglyMeasurable g μ) :
∫⁻ a, ‖f a‖₊ + ‖g a‖₊ ∂μ = (∫⁻ a, ‖f a‖₊ ∂μ) + ∫⁻ a, ‖g a‖₊ ∂μ :=
lintegral_add_right' _ hg.ennnorm
#align measure_theory.lintegral_nnnorm_add_right MeasureTheory.lintegral_nnnorm_add_right
theorem lintegral_nnnorm_neg {f : α → β} : (∫⁻ a, ‖(-f) a‖₊ ∂μ) = ∫⁻ a, ‖f a‖₊ ∂μ := by
simp only [Pi.neg_apply, nnnorm_neg]
#align measure_theory.lintegral_nnnorm_neg MeasureTheory.lintegral_nnnorm_neg
/-! ### The predicate `HasFiniteIntegral` -/
/-- `HasFiniteIntegral f μ` means that the integral `∫⁻ a, ‖f a‖ ∂μ` is finite.
`HasFiniteIntegral f` means `HasFiniteIntegral f volume`. -/
def HasFiniteIntegral {_ : MeasurableSpace α} (f : α → β) (μ : Measure α := by volume_tac) : Prop :=
(∫⁻ a, ‖f a‖₊ ∂μ) < ∞
#align measure_theory.has_finite_integral MeasureTheory.HasFiniteIntegral
theorem hasFiniteIntegral_def {_ : MeasurableSpace α} (f : α → β) (μ : Measure α) :
HasFiniteIntegral f μ ↔ ((∫⁻ a, ‖f a‖₊ ∂μ) < ∞) :=
Iff.rfl
theorem hasFiniteIntegral_iff_norm (f : α → β) :
HasFiniteIntegral f μ ↔ (∫⁻ a, ENNReal.ofReal ‖f a‖ ∂μ) < ∞ := by
simp only [HasFiniteIntegral, ofReal_norm_eq_coe_nnnorm]
#align measure_theory.has_finite_integral_iff_norm MeasureTheory.hasFiniteIntegral_iff_norm
theorem hasFiniteIntegral_iff_edist (f : α → β) :
HasFiniteIntegral f μ ↔ (∫⁻ a, edist (f a) 0 ∂μ) < ∞ := by
simp only [hasFiniteIntegral_iff_norm, edist_dist, dist_zero_right]
#align measure_theory.has_finite_integral_iff_edist MeasureTheory.hasFiniteIntegral_iff_edist
theorem hasFiniteIntegral_iff_ofReal {f : α → ℝ} (h : 0 ≤ᵐ[μ] f) :
HasFiniteIntegral f μ ↔ (∫⁻ a, ENNReal.ofReal (f a) ∂μ) < ∞ := by
rw [HasFiniteIntegral, lintegral_nnnorm_eq_of_ae_nonneg h]
#align measure_theory.has_finite_integral_iff_of_real MeasureTheory.hasFiniteIntegral_iff_ofReal
theorem hasFiniteIntegral_iff_ofNNReal {f : α → ℝ≥0} :
HasFiniteIntegral (fun x => (f x : ℝ)) μ ↔ (∫⁻ a, f a ∂μ) < ∞ := by
simp [hasFiniteIntegral_iff_norm]
#align measure_theory.has_finite_integral_iff_of_nnreal MeasureTheory.hasFiniteIntegral_iff_ofNNReal
theorem HasFiniteIntegral.mono {f : α → β} {g : α → γ} (hg : HasFiniteIntegral g μ)
(h : ∀ᵐ a ∂μ, ‖f a‖ ≤ ‖g a‖) : HasFiniteIntegral f μ := by
simp only [hasFiniteIntegral_iff_norm] at *
calc
(∫⁻ a, ENNReal.ofReal ‖f a‖ ∂μ) ≤ ∫⁻ a : α, ENNReal.ofReal ‖g a‖ ∂μ :=
lintegral_mono_ae (h.mono fun a h => ofReal_le_ofReal h)
_ < ∞ := hg
#align measure_theory.has_finite_integral.mono MeasureTheory.HasFiniteIntegral.mono
theorem HasFiniteIntegral.mono' {f : α → β} {g : α → ℝ} (hg : HasFiniteIntegral g μ)
(h : ∀ᵐ a ∂μ, ‖f a‖ ≤ g a) : HasFiniteIntegral f μ :=
hg.mono <| h.mono fun _x hx => le_trans hx (le_abs_self _)
#align measure_theory.has_finite_integral.mono' MeasureTheory.HasFiniteIntegral.mono'
theorem HasFiniteIntegral.congr' {f : α → β} {g : α → γ} (hf : HasFiniteIntegral f μ)
(h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) : HasFiniteIntegral g μ :=
hf.mono <| EventuallyEq.le <| EventuallyEq.symm h
#align measure_theory.has_finite_integral.congr' MeasureTheory.HasFiniteIntegral.congr'
theorem hasFiniteIntegral_congr' {f : α → β} {g : α → γ} (h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) :
HasFiniteIntegral f μ ↔ HasFiniteIntegral g μ :=
⟨fun hf => hf.congr' h, fun hg => hg.congr' <| EventuallyEq.symm h⟩
#align measure_theory.has_finite_integral_congr' MeasureTheory.hasFiniteIntegral_congr'
theorem HasFiniteIntegral.congr {f g : α → β} (hf : HasFiniteIntegral f μ) (h : f =ᵐ[μ] g) :
HasFiniteIntegral g μ :=
hf.congr' <| h.fun_comp norm
#align measure_theory.has_finite_integral.congr MeasureTheory.HasFiniteIntegral.congr
theorem hasFiniteIntegral_congr {f g : α → β} (h : f =ᵐ[μ] g) :
HasFiniteIntegral f μ ↔ HasFiniteIntegral g μ :=
hasFiniteIntegral_congr' <| h.fun_comp norm
#align measure_theory.has_finite_integral_congr MeasureTheory.hasFiniteIntegral_congr
theorem hasFiniteIntegral_const_iff {c : β} :
HasFiniteIntegral (fun _ : α => c) μ ↔ c = 0 ∨ μ univ < ∞ := by
simp [HasFiniteIntegral, lintegral_const, lt_top_iff_ne_top, ENNReal.mul_eq_top,
or_iff_not_imp_left]
#align measure_theory.has_finite_integral_const_iff MeasureTheory.hasFiniteIntegral_const_iff
theorem hasFiniteIntegral_const [IsFiniteMeasure μ] (c : β) :
HasFiniteIntegral (fun _ : α => c) μ :=
hasFiniteIntegral_const_iff.2 (Or.inr <| measure_lt_top _ _)
#align measure_theory.has_finite_integral_const MeasureTheory.hasFiniteIntegral_const
theorem hasFiniteIntegral_of_bounded [IsFiniteMeasure μ] {f : α → β} {C : ℝ}
(hC : ∀ᵐ a ∂μ, ‖f a‖ ≤ C) : HasFiniteIntegral f μ :=
(hasFiniteIntegral_const C).mono' hC
#align measure_theory.has_finite_integral_of_bounded MeasureTheory.hasFiniteIntegral_of_bounded
theorem HasFiniteIntegral.of_finite [Finite α] [IsFiniteMeasure μ] {f : α → β} :
HasFiniteIntegral f μ :=
let ⟨_⟩ := nonempty_fintype α
hasFiniteIntegral_of_bounded <| ae_of_all μ <| norm_le_pi_norm f
@[deprecated (since := "2024-02-05")]
alias hasFiniteIntegral_of_fintype := HasFiniteIntegral.of_finite
theorem HasFiniteIntegral.mono_measure {f : α → β} (h : HasFiniteIntegral f ν) (hμ : μ ≤ ν) :
HasFiniteIntegral f μ :=
lt_of_le_of_lt (lintegral_mono' hμ le_rfl) h
#align measure_theory.has_finite_integral.mono_measure MeasureTheory.HasFiniteIntegral.mono_measure
theorem HasFiniteIntegral.add_measure {f : α → β} (hμ : HasFiniteIntegral f μ)
(hν : HasFiniteIntegral f ν) : HasFiniteIntegral f (μ + ν) := by
simp only [HasFiniteIntegral, lintegral_add_measure] at *
exact add_lt_top.2 ⟨hμ, hν⟩
#align measure_theory.has_finite_integral.add_measure MeasureTheory.HasFiniteIntegral.add_measure
theorem HasFiniteIntegral.left_of_add_measure {f : α → β} (h : HasFiniteIntegral f (μ + ν)) :
HasFiniteIntegral f μ :=
h.mono_measure <| Measure.le_add_right <| le_rfl
#align measure_theory.has_finite_integral.left_of_add_measure MeasureTheory.HasFiniteIntegral.left_of_add_measure
theorem HasFiniteIntegral.right_of_add_measure {f : α → β} (h : HasFiniteIntegral f (μ + ν)) :
HasFiniteIntegral f ν :=
h.mono_measure <| Measure.le_add_left <| le_rfl
#align measure_theory.has_finite_integral.right_of_add_measure MeasureTheory.HasFiniteIntegral.right_of_add_measure
@[simp]
theorem hasFiniteIntegral_add_measure {f : α → β} :
HasFiniteIntegral f (μ + ν) ↔ HasFiniteIntegral f μ ∧ HasFiniteIntegral f ν :=
⟨fun h => ⟨h.left_of_add_measure, h.right_of_add_measure⟩, fun h => h.1.add_measure h.2⟩
#align measure_theory.has_finite_integral_add_measure MeasureTheory.hasFiniteIntegral_add_measure
theorem HasFiniteIntegral.smul_measure {f : α → β} (h : HasFiniteIntegral f μ) {c : ℝ≥0∞}
(hc : c ≠ ∞) : HasFiniteIntegral f (c • μ) := by
simp only [HasFiniteIntegral, lintegral_smul_measure] at *
exact mul_lt_top hc h.ne
#align measure_theory.has_finite_integral.smul_measure MeasureTheory.HasFiniteIntegral.smul_measure
@[simp]
theorem hasFiniteIntegral_zero_measure {m : MeasurableSpace α} (f : α → β) :
HasFiniteIntegral f (0 : Measure α) := by
simp only [HasFiniteIntegral, lintegral_zero_measure, zero_lt_top]
#align measure_theory.has_finite_integral_zero_measure MeasureTheory.hasFiniteIntegral_zero_measure
variable (α β μ)
@[simp]
theorem hasFiniteIntegral_zero : HasFiniteIntegral (fun _ : α => (0 : β)) μ := by
simp [HasFiniteIntegral]
#align measure_theory.has_finite_integral_zero MeasureTheory.hasFiniteIntegral_zero
variable {α β μ}
theorem HasFiniteIntegral.neg {f : α → β} (hfi : HasFiniteIntegral f μ) :
HasFiniteIntegral (-f) μ := by simpa [HasFiniteIntegral] using hfi
#align measure_theory.has_finite_integral.neg MeasureTheory.HasFiniteIntegral.neg
@[simp]
theorem hasFiniteIntegral_neg_iff {f : α → β} : HasFiniteIntegral (-f) μ ↔ HasFiniteIntegral f μ :=
⟨fun h => neg_neg f ▸ h.neg, HasFiniteIntegral.neg⟩
#align measure_theory.has_finite_integral_neg_iff MeasureTheory.hasFiniteIntegral_neg_iff
theorem HasFiniteIntegral.norm {f : α → β} (hfi : HasFiniteIntegral f μ) :
HasFiniteIntegral (fun a => ‖f a‖) μ := by
have eq : (fun a => (nnnorm ‖f a‖ : ℝ≥0∞)) = fun a => (‖f a‖₊ : ℝ≥0∞) := by
funext
rw [nnnorm_norm]
rwa [HasFiniteIntegral, eq]
#align measure_theory.has_finite_integral.norm MeasureTheory.HasFiniteIntegral.norm
theorem hasFiniteIntegral_norm_iff (f : α → β) :
HasFiniteIntegral (fun a => ‖f a‖) μ ↔ HasFiniteIntegral f μ :=
hasFiniteIntegral_congr' <| eventually_of_forall fun x => norm_norm (f x)
#align measure_theory.has_finite_integral_norm_iff MeasureTheory.hasFiniteIntegral_norm_iff
theorem hasFiniteIntegral_toReal_of_lintegral_ne_top {f : α → ℝ≥0∞} (hf : (∫⁻ x, f x ∂μ) ≠ ∞) :
HasFiniteIntegral (fun x => (f x).toReal) μ := by
have :
∀ x, (‖(f x).toReal‖₊ : ℝ≥0∞) = ENNReal.ofNNReal ⟨(f x).toReal, ENNReal.toReal_nonneg⟩ := by
intro x
rw [Real.nnnorm_of_nonneg]
simp_rw [HasFiniteIntegral, this]
refine lt_of_le_of_lt (lintegral_mono fun x => ?_) (lt_top_iff_ne_top.2 hf)
by_cases hfx : f x = ∞
· simp [hfx]
· lift f x to ℝ≥0 using hfx with fx h
simp [← h, ← NNReal.coe_le_coe]
#align measure_theory.has_finite_integral_to_real_of_lintegral_ne_top MeasureTheory.hasFiniteIntegral_toReal_of_lintegral_ne_top
theorem isFiniteMeasure_withDensity_ofReal {f : α → ℝ} (hfi : HasFiniteIntegral f μ) :
IsFiniteMeasure (μ.withDensity fun x => ENNReal.ofReal <| f x) := by
refine isFiniteMeasure_withDensity ((lintegral_mono fun x => ?_).trans_lt hfi).ne
exact Real.ofReal_le_ennnorm (f x)
#align measure_theory.is_finite_measure_with_density_of_real MeasureTheory.isFiniteMeasure_withDensity_ofReal
section DominatedConvergence
variable {F : ℕ → α → β} {f : α → β} {bound : α → ℝ}
theorem all_ae_ofReal_F_le_bound (h : ∀ n, ∀ᵐ a ∂μ, ‖F n a‖ ≤ bound a) :
∀ n, ∀ᵐ a ∂μ, ENNReal.ofReal ‖F n a‖ ≤ ENNReal.ofReal (bound a) := fun n =>
(h n).mono fun _ h => ENNReal.ofReal_le_ofReal h
set_option linter.uppercaseLean3 false in
#align measure_theory.all_ae_of_real_F_le_bound MeasureTheory.all_ae_ofReal_F_le_bound
theorem all_ae_tendsto_ofReal_norm (h : ∀ᵐ a ∂μ, Tendsto (fun n => F n a) atTop <| 𝓝 <| f a) :
∀ᵐ a ∂μ, Tendsto (fun n => ENNReal.ofReal ‖F n a‖) atTop <| 𝓝 <| ENNReal.ofReal ‖f a‖ :=
h.mono fun _ h => tendsto_ofReal <| Tendsto.comp (Continuous.tendsto continuous_norm _) h
#align measure_theory.all_ae_tendsto_of_real_norm MeasureTheory.all_ae_tendsto_ofReal_norm
theorem all_ae_ofReal_f_le_bound (h_bound : ∀ n, ∀ᵐ a ∂μ, ‖F n a‖ ≤ bound a)
(h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => F n a) atTop (𝓝 (f a))) :
∀ᵐ a ∂μ, ENNReal.ofReal ‖f a‖ ≤ ENNReal.ofReal (bound a) := by
have F_le_bound := all_ae_ofReal_F_le_bound h_bound
rw [← ae_all_iff] at F_le_bound
apply F_le_bound.mp ((all_ae_tendsto_ofReal_norm h_lim).mono _)
intro a tendsto_norm F_le_bound
exact le_of_tendsto' tendsto_norm F_le_bound
#align measure_theory.all_ae_of_real_f_le_bound MeasureTheory.all_ae_ofReal_f_le_bound
theorem hasFiniteIntegral_of_dominated_convergence {F : ℕ → α → β} {f : α → β} {bound : α → ℝ}
(bound_hasFiniteIntegral : HasFiniteIntegral bound μ)
(h_bound : ∀ n, ∀ᵐ a ∂μ, ‖F n a‖ ≤ bound a)
(h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => F n a) atTop (𝓝 (f a))) : HasFiniteIntegral f μ := by
/- `‖F n a‖ ≤ bound a` and `‖F n a‖ --> ‖f a‖` implies `‖f a‖ ≤ bound a`,
and so `∫ ‖f‖ ≤ ∫ bound < ∞` since `bound` is has_finite_integral -/
rw [hasFiniteIntegral_iff_norm]
calc
(∫⁻ a, ENNReal.ofReal ‖f a‖ ∂μ) ≤ ∫⁻ a, ENNReal.ofReal (bound a) ∂μ :=
lintegral_mono_ae <| all_ae_ofReal_f_le_bound h_bound h_lim
_ < ∞ := by
rw [← hasFiniteIntegral_iff_ofReal]
· exact bound_hasFiniteIntegral
exact (h_bound 0).mono fun a h => le_trans (norm_nonneg _) h
#align measure_theory.has_finite_integral_of_dominated_convergence MeasureTheory.hasFiniteIntegral_of_dominated_convergence
theorem tendsto_lintegral_norm_of_dominated_convergence {F : ℕ → α → β} {f : α → β} {bound : α → ℝ}
(F_measurable : ∀ n, AEStronglyMeasurable (F n) μ)
(bound_hasFiniteIntegral : HasFiniteIntegral bound μ)
(h_bound : ∀ n, ∀ᵐ a ∂μ, ‖F n a‖ ≤ bound a)
(h_lim : ∀ᵐ a ∂μ, Tendsto (fun n => F n a) atTop (𝓝 (f a))) :
Tendsto (fun n => ∫⁻ a, ENNReal.ofReal ‖F n a - f a‖ ∂μ) atTop (𝓝 0) := by
have f_measurable : AEStronglyMeasurable f μ :=
aestronglyMeasurable_of_tendsto_ae _ F_measurable h_lim
let b a := 2 * ENNReal.ofReal (bound a)
/- `‖F n a‖ ≤ bound a` and `F n a --> f a` implies `‖f a‖ ≤ bound a`, and thus by the
triangle inequality, have `‖F n a - f a‖ ≤ 2 * (bound a)`. -/
have hb : ∀ n, ∀ᵐ a ∂μ, ENNReal.ofReal ‖F n a - f a‖ ≤ b a := by
intro n
filter_upwards [all_ae_ofReal_F_le_bound h_bound n,
all_ae_ofReal_f_le_bound h_bound h_lim] with a h₁ h₂
calc
ENNReal.ofReal ‖F n a - f a‖ ≤ ENNReal.ofReal ‖F n a‖ + ENNReal.ofReal ‖f a‖ := by
rw [← ENNReal.ofReal_add]
· apply ofReal_le_ofReal
apply norm_sub_le
· exact norm_nonneg _
· exact norm_nonneg _
_ ≤ ENNReal.ofReal (bound a) + ENNReal.ofReal (bound a) := add_le_add h₁ h₂
_ = b a := by rw [← two_mul]
-- On the other hand, `F n a --> f a` implies that `‖F n a - f a‖ --> 0`
have h : ∀ᵐ a ∂μ, Tendsto (fun n => ENNReal.ofReal ‖F n a - f a‖) atTop (𝓝 0) := by
rw [← ENNReal.ofReal_zero]
refine h_lim.mono fun a h => (continuous_ofReal.tendsto _).comp ?_
rwa [← tendsto_iff_norm_sub_tendsto_zero]
/- Therefore, by the dominated convergence theorem for nonnegative integration, have
` ∫ ‖f a - F n a‖ --> 0 ` -/
suffices Tendsto (fun n => ∫⁻ a, ENNReal.ofReal ‖F n a - f a‖ ∂μ) atTop (𝓝 (∫⁻ _ : α, 0 ∂μ)) by
rwa [lintegral_zero] at this
-- Using the dominated convergence theorem.
refine tendsto_lintegral_of_dominated_convergence' _ ?_ hb ?_ ?_
-- Show `fun a => ‖f a - F n a‖` is almost everywhere measurable for all `n`
· exact fun n =>
measurable_ofReal.comp_aemeasurable ((F_measurable n).sub f_measurable).norm.aemeasurable
-- Show `2 * bound` `HasFiniteIntegral`
· rw [hasFiniteIntegral_iff_ofReal] at bound_hasFiniteIntegral
· calc
∫⁻ a, b a ∂μ = 2 * ∫⁻ a, ENNReal.ofReal (bound a) ∂μ := by
rw [lintegral_const_mul']
exact coe_ne_top
_ ≠ ∞ := mul_ne_top coe_ne_top bound_hasFiniteIntegral.ne
filter_upwards [h_bound 0] with _ h using le_trans (norm_nonneg _) h
-- Show `‖f a - F n a‖ --> 0`
· exact h
#align measure_theory.tendsto_lintegral_norm_of_dominated_convergence MeasureTheory.tendsto_lintegral_norm_of_dominated_convergence
end DominatedConvergence
section PosPart
/-! Lemmas used for defining the positive part of an `L¹` function -/
theorem HasFiniteIntegral.max_zero {f : α → ℝ} (hf : HasFiniteIntegral f μ) :
HasFiniteIntegral (fun a => max (f a) 0) μ :=
hf.mono <| eventually_of_forall fun x => by simp [abs_le, le_abs_self]
#align measure_theory.has_finite_integral.max_zero MeasureTheory.HasFiniteIntegral.max_zero
theorem HasFiniteIntegral.min_zero {f : α → ℝ} (hf : HasFiniteIntegral f μ) :
HasFiniteIntegral (fun a => min (f a) 0) μ :=
hf.mono <| eventually_of_forall fun x => by simpa [abs_le] using neg_abs_le _
#align measure_theory.has_finite_integral.min_zero MeasureTheory.HasFiniteIntegral.min_zero
end PosPart
section NormedSpace
variable {𝕜 : Type*}
theorem HasFiniteIntegral.smul [NormedAddCommGroup 𝕜] [SMulZeroClass 𝕜 β] [BoundedSMul 𝕜 β] (c : 𝕜)
{f : α → β} : HasFiniteIntegral f μ → HasFiniteIntegral (c • f) μ := by
simp only [HasFiniteIntegral]; intro hfi
calc
(∫⁻ a : α, ‖c • f a‖₊ ∂μ) ≤ ∫⁻ a : α, ‖c‖₊ * ‖f a‖₊ ∂μ := by
refine lintegral_mono ?_
intro i
-- After leanprover/lean4#2734, we need to do beta reduction `exact mod_cast`
beta_reduce
exact mod_cast (nnnorm_smul_le c (f i))
_ < ∞ := by
rw [lintegral_const_mul']
exacts [mul_lt_top coe_ne_top hfi.ne, coe_ne_top]
#align measure_theory.has_finite_integral.smul MeasureTheory.HasFiniteIntegral.smul
theorem hasFiniteIntegral_smul_iff [NormedRing 𝕜] [MulActionWithZero 𝕜 β] [BoundedSMul 𝕜 β] {c : 𝕜}
(hc : IsUnit c) (f : α → β) : HasFiniteIntegral (c • f) μ ↔ HasFiniteIntegral f μ := by
obtain ⟨c, rfl⟩ := hc
constructor
· intro h
simpa only [smul_smul, Units.inv_mul, one_smul] using h.smul ((c⁻¹ : 𝕜ˣ) : 𝕜)
exact HasFiniteIntegral.smul _
#align measure_theory.has_finite_integral_smul_iff MeasureTheory.hasFiniteIntegral_smul_iff
theorem HasFiniteIntegral.const_mul [NormedRing 𝕜] {f : α → 𝕜} (h : HasFiniteIntegral f μ) (c : 𝕜) :
HasFiniteIntegral (fun x => c * f x) μ :=
h.smul c
#align measure_theory.has_finite_integral.const_mul MeasureTheory.HasFiniteIntegral.const_mul
theorem HasFiniteIntegral.mul_const [NormedRing 𝕜] {f : α → 𝕜} (h : HasFiniteIntegral f μ) (c : 𝕜) :
HasFiniteIntegral (fun x => f x * c) μ :=
h.smul (MulOpposite.op c)
#align measure_theory.has_finite_integral.mul_const MeasureTheory.HasFiniteIntegral.mul_const
end NormedSpace
/-! ### The predicate `Integrable` -/
-- variable [MeasurableSpace β] [MeasurableSpace γ] [MeasurableSpace δ]
/-- `Integrable f μ` means that `f` is measurable and that the integral `∫⁻ a, ‖f a‖ ∂μ` is finite.
`Integrable f` means `Integrable f volume`. -/
def Integrable {α} {_ : MeasurableSpace α} (f : α → β) (μ : Measure α := by volume_tac) : Prop :=
AEStronglyMeasurable f μ ∧ HasFiniteIntegral f μ
#align measure_theory.integrable MeasureTheory.Integrable
theorem memℒp_one_iff_integrable {f : α → β} : Memℒp f 1 μ ↔ Integrable f μ := by
simp_rw [Integrable, HasFiniteIntegral, Memℒp, snorm_one_eq_lintegral_nnnorm]
#align measure_theory.mem_ℒp_one_iff_integrable MeasureTheory.memℒp_one_iff_integrable
theorem Integrable.aestronglyMeasurable {f : α → β} (hf : Integrable f μ) :
AEStronglyMeasurable f μ :=
hf.1
#align measure_theory.integrable.ae_strongly_measurable MeasureTheory.Integrable.aestronglyMeasurable
theorem Integrable.aemeasurable [MeasurableSpace β] [BorelSpace β] {f : α → β}
(hf : Integrable f μ) : AEMeasurable f μ :=
hf.aestronglyMeasurable.aemeasurable
#align measure_theory.integrable.ae_measurable MeasureTheory.Integrable.aemeasurable
theorem Integrable.hasFiniteIntegral {f : α → β} (hf : Integrable f μ) : HasFiniteIntegral f μ :=
hf.2
#align measure_theory.integrable.has_finite_integral MeasureTheory.Integrable.hasFiniteIntegral
theorem Integrable.mono {f : α → β} {g : α → γ} (hg : Integrable g μ)
(hf : AEStronglyMeasurable f μ) (h : ∀ᵐ a ∂μ, ‖f a‖ ≤ ‖g a‖) : Integrable f μ :=
⟨hf, hg.hasFiniteIntegral.mono h⟩
#align measure_theory.integrable.mono MeasureTheory.Integrable.mono
theorem Integrable.mono' {f : α → β} {g : α → ℝ} (hg : Integrable g μ)
(hf : AEStronglyMeasurable f μ) (h : ∀ᵐ a ∂μ, ‖f a‖ ≤ g a) : Integrable f μ :=
⟨hf, hg.hasFiniteIntegral.mono' h⟩
#align measure_theory.integrable.mono' MeasureTheory.Integrable.mono'
theorem Integrable.congr' {f : α → β} {g : α → γ} (hf : Integrable f μ)
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) : Integrable g μ :=
⟨hg, hf.hasFiniteIntegral.congr' h⟩
#align measure_theory.integrable.congr' MeasureTheory.Integrable.congr'
theorem integrable_congr' {f : α → β} {g : α → γ} (hf : AEStronglyMeasurable f μ)
(hg : AEStronglyMeasurable g μ) (h : ∀ᵐ a ∂μ, ‖f a‖ = ‖g a‖) :
Integrable f μ ↔ Integrable g μ :=
⟨fun h2f => h2f.congr' hg h, fun h2g => h2g.congr' hf <| EventuallyEq.symm h⟩
#align measure_theory.integrable_congr' MeasureTheory.integrable_congr'
theorem Integrable.congr {f g : α → β} (hf : Integrable f μ) (h : f =ᵐ[μ] g) : Integrable g μ :=
⟨hf.1.congr h, hf.2.congr h⟩
#align measure_theory.integrable.congr MeasureTheory.Integrable.congr
theorem integrable_congr {f g : α → β} (h : f =ᵐ[μ] g) : Integrable f μ ↔ Integrable g μ :=
⟨fun hf => hf.congr h, fun hg => hg.congr h.symm⟩
#align measure_theory.integrable_congr MeasureTheory.integrable_congr
theorem integrable_const_iff {c : β} : Integrable (fun _ : α => c) μ ↔ c = 0 ∨ μ univ < ∞ := by
have : AEStronglyMeasurable (fun _ : α => c) μ := aestronglyMeasurable_const
rw [Integrable, and_iff_right this, hasFiniteIntegral_const_iff]
#align measure_theory.integrable_const_iff MeasureTheory.integrable_const_iff
@[simp]
theorem integrable_const [IsFiniteMeasure μ] (c : β) : Integrable (fun _ : α => c) μ :=
integrable_const_iff.2 <| Or.inr <| measure_lt_top _ _
#align measure_theory.integrable_const MeasureTheory.integrable_const
@[simp]
theorem Integrable.of_finite [Finite α] [MeasurableSpace α] [MeasurableSingletonClass α]
(μ : Measure α) [IsFiniteMeasure μ] (f : α → β) : Integrable (fun a ↦ f a) μ :=
⟨(StronglyMeasurable.of_finite f).aestronglyMeasurable, .of_finite⟩
@[deprecated (since := "2024-02-05")] alias integrable_of_fintype := Integrable.of_finite
theorem Memℒp.integrable_norm_rpow {f : α → β} {p : ℝ≥0∞} (hf : Memℒp f p μ) (hp_ne_zero : p ≠ 0)
(hp_ne_top : p ≠ ∞) : Integrable (fun x : α => ‖f x‖ ^ p.toReal) μ := by
rw [← memℒp_one_iff_integrable]
exact hf.norm_rpow hp_ne_zero hp_ne_top
#align measure_theory.mem_ℒp.integrable_norm_rpow MeasureTheory.Memℒp.integrable_norm_rpow
theorem Memℒp.integrable_norm_rpow' [IsFiniteMeasure μ] {f : α → β} {p : ℝ≥0∞} (hf : Memℒp f p μ) :
Integrable (fun x : α => ‖f x‖ ^ p.toReal) μ := by
by_cases h_zero : p = 0
· simp [h_zero, integrable_const]
by_cases h_top : p = ∞
· simp [h_top, integrable_const]
exact hf.integrable_norm_rpow h_zero h_top
#align measure_theory.mem_ℒp.integrable_norm_rpow' MeasureTheory.Memℒp.integrable_norm_rpow'
theorem Integrable.mono_measure {f : α → β} (h : Integrable f ν) (hμ : μ ≤ ν) : Integrable f μ :=
⟨h.aestronglyMeasurable.mono_measure hμ, h.hasFiniteIntegral.mono_measure hμ⟩
#align measure_theory.integrable.mono_measure MeasureTheory.Integrable.mono_measure
theorem Integrable.of_measure_le_smul {μ' : Measure α} (c : ℝ≥0∞) (hc : c ≠ ∞) (hμ'_le : μ' ≤ c • μ)
{f : α → β} (hf : Integrable f μ) : Integrable f μ' := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact hf.of_measure_le_smul c hc hμ'_le
#align measure_theory.integrable.of_measure_le_smul MeasureTheory.Integrable.of_measure_le_smul
theorem Integrable.add_measure {f : α → β} (hμ : Integrable f μ) (hν : Integrable f ν) :
Integrable f (μ + ν) := by
simp_rw [← memℒp_one_iff_integrable] at hμ hν ⊢
refine ⟨hμ.aestronglyMeasurable.add_measure hν.aestronglyMeasurable, ?_⟩
rw [snorm_one_add_measure, ENNReal.add_lt_top]
exact ⟨hμ.snorm_lt_top, hν.snorm_lt_top⟩
#align measure_theory.integrable.add_measure MeasureTheory.Integrable.add_measure
theorem Integrable.left_of_add_measure {f : α → β} (h : Integrable f (μ + ν)) : Integrable f μ := by
rw [← memℒp_one_iff_integrable] at h ⊢
exact h.left_of_add_measure
#align measure_theory.integrable.left_of_add_measure MeasureTheory.Integrable.left_of_add_measure
theorem Integrable.right_of_add_measure {f : α → β} (h : Integrable f (μ + ν)) :
Integrable f ν := by
rw [← memℒp_one_iff_integrable] at h ⊢
exact h.right_of_add_measure
#align measure_theory.integrable.right_of_add_measure MeasureTheory.Integrable.right_of_add_measure
@[simp]
theorem integrable_add_measure {f : α → β} :
Integrable f (μ + ν) ↔ Integrable f μ ∧ Integrable f ν :=
⟨fun h => ⟨h.left_of_add_measure, h.right_of_add_measure⟩, fun h => h.1.add_measure h.2⟩
#align measure_theory.integrable_add_measure MeasureTheory.integrable_add_measure
@[simp]
theorem integrable_zero_measure {_ : MeasurableSpace α} {f : α → β} :
Integrable f (0 : Measure α) :=
⟨aestronglyMeasurable_zero_measure f, hasFiniteIntegral_zero_measure f⟩
#align measure_theory.integrable_zero_measure MeasureTheory.integrable_zero_measure
theorem integrable_finset_sum_measure {ι} {m : MeasurableSpace α} {f : α → β} {μ : ι → Measure α}
{s : Finset ι} : Integrable f (∑ i ∈ s, μ i) ↔ ∀ i ∈ s, Integrable f (μ i) := by
induction s using Finset.induction_on <;> simp [*]
#align measure_theory.integrable_finset_sum_measure MeasureTheory.integrable_finset_sum_measure
theorem Integrable.smul_measure {f : α → β} (h : Integrable f μ) {c : ℝ≥0∞} (hc : c ≠ ∞) :
Integrable f (c • μ) := by
rw [← memℒp_one_iff_integrable] at h ⊢
exact h.smul_measure hc
#align measure_theory.integrable.smul_measure MeasureTheory.Integrable.smul_measure
theorem Integrable.smul_measure_nnreal {f : α → β} (h : Integrable f μ) {c : ℝ≥0} :
Integrable f (c • μ) := by
apply h.smul_measure
simp
theorem integrable_smul_measure {f : α → β} {c : ℝ≥0∞} (h₁ : c ≠ 0) (h₂ : c ≠ ∞) :
Integrable f (c • μ) ↔ Integrable f μ :=
⟨fun h => by
simpa only [smul_smul, ENNReal.inv_mul_cancel h₁ h₂, one_smul] using
h.smul_measure (ENNReal.inv_ne_top.2 h₁),
fun h => h.smul_measure h₂⟩
#align measure_theory.integrable_smul_measure MeasureTheory.integrable_smul_measure
theorem integrable_inv_smul_measure {f : α → β} {c : ℝ≥0∞} (h₁ : c ≠ 0) (h₂ : c ≠ ∞) :
Integrable f (c⁻¹ • μ) ↔ Integrable f μ :=
integrable_smul_measure (by simpa using h₂) (by simpa using h₁)
#align measure_theory.integrable_inv_smul_measure MeasureTheory.integrable_inv_smul_measure
theorem Integrable.to_average {f : α → β} (h : Integrable f μ) : Integrable f ((μ univ)⁻¹ • μ) := by
rcases eq_or_ne μ 0 with (rfl | hne)
· rwa [smul_zero]
· apply h.smul_measure
simpa
#align measure_theory.integrable.to_average MeasureTheory.Integrable.to_average
theorem integrable_average [IsFiniteMeasure μ] {f : α → β} :
Integrable f ((μ univ)⁻¹ • μ) ↔ Integrable f μ :=
(eq_or_ne μ 0).by_cases (fun h => by simp [h]) fun h =>
integrable_smul_measure (ENNReal.inv_ne_zero.2 <| measure_ne_top _ _)
(ENNReal.inv_ne_top.2 <| mt Measure.measure_univ_eq_zero.1 h)
#align measure_theory.integrable_average MeasureTheory.integrable_average
theorem integrable_map_measure {f : α → δ} {g : δ → β}
(hg : AEStronglyMeasurable g (Measure.map f μ)) (hf : AEMeasurable f μ) :
Integrable g (Measure.map f μ) ↔ Integrable (g ∘ f) μ := by
simp_rw [← memℒp_one_iff_integrable]
exact memℒp_map_measure_iff hg hf
#align measure_theory.integrable_map_measure MeasureTheory.integrable_map_measure
theorem Integrable.comp_aemeasurable {f : α → δ} {g : δ → β} (hg : Integrable g (Measure.map f μ))
(hf : AEMeasurable f μ) : Integrable (g ∘ f) μ :=
(integrable_map_measure hg.aestronglyMeasurable hf).mp hg
#align measure_theory.integrable.comp_ae_measurable MeasureTheory.Integrable.comp_aemeasurable
theorem Integrable.comp_measurable {f : α → δ} {g : δ → β} (hg : Integrable g (Measure.map f μ))
(hf : Measurable f) : Integrable (g ∘ f) μ :=
hg.comp_aemeasurable hf.aemeasurable
#align measure_theory.integrable.comp_measurable MeasureTheory.Integrable.comp_measurable
theorem _root_.MeasurableEmbedding.integrable_map_iff {f : α → δ} (hf : MeasurableEmbedding f)
{g : δ → β} : Integrable g (Measure.map f μ) ↔ Integrable (g ∘ f) μ := by
simp_rw [← memℒp_one_iff_integrable]
exact hf.memℒp_map_measure_iff
#align measurable_embedding.integrable_map_iff MeasurableEmbedding.integrable_map_iff
theorem integrable_map_equiv (f : α ≃ᵐ δ) (g : δ → β) :
Integrable g (Measure.map f μ) ↔ Integrable (g ∘ f) μ := by
simp_rw [← memℒp_one_iff_integrable]
exact f.memℒp_map_measure_iff
#align measure_theory.integrable_map_equiv MeasureTheory.integrable_map_equiv
theorem MeasurePreserving.integrable_comp {ν : Measure δ} {g : δ → β} {f : α → δ}
(hf : MeasurePreserving f μ ν) (hg : AEStronglyMeasurable g ν) :
Integrable (g ∘ f) μ ↔ Integrable g ν := by
rw [← hf.map_eq] at hg ⊢
exact (integrable_map_measure hg hf.measurable.aemeasurable).symm
#align measure_theory.measure_preserving.integrable_comp MeasureTheory.MeasurePreserving.integrable_comp
theorem MeasurePreserving.integrable_comp_emb {f : α → δ} {ν} (h₁ : MeasurePreserving f μ ν)
(h₂ : MeasurableEmbedding f) {g : δ → β} : Integrable (g ∘ f) μ ↔ Integrable g ν :=
h₁.map_eq ▸ Iff.symm h₂.integrable_map_iff
#align measure_theory.measure_preserving.integrable_comp_emb MeasureTheory.MeasurePreserving.integrable_comp_emb
theorem lintegral_edist_lt_top {f g : α → β} (hf : Integrable f μ) (hg : Integrable g μ) :
(∫⁻ a, edist (f a) (g a) ∂μ) < ∞ :=
lt_of_le_of_lt (lintegral_edist_triangle hf.aestronglyMeasurable aestronglyMeasurable_zero)
(ENNReal.add_lt_top.2 <| by
simp_rw [Pi.zero_apply, ← hasFiniteIntegral_iff_edist]
exact ⟨hf.hasFiniteIntegral, hg.hasFiniteIntegral⟩)
#align measure_theory.lintegral_edist_lt_top MeasureTheory.lintegral_edist_lt_top
variable (α β μ)
@[simp]
theorem integrable_zero : Integrable (fun _ => (0 : β)) μ := by
simp [Integrable, aestronglyMeasurable_const]
#align measure_theory.integrable_zero MeasureTheory.integrable_zero
variable {α β μ}
theorem Integrable.add' {f g : α → β} (hf : Integrable f μ) (hg : Integrable g μ) :
HasFiniteIntegral (f + g) μ :=
calc
(∫⁻ a, ‖f a + g a‖₊ ∂μ) ≤ ∫⁻ a, ‖f a‖₊ + ‖g a‖₊ ∂μ :=
lintegral_mono fun a => by
-- After leanprover/lean4#2734, we need to do beta reduction before `exact mod_cast`
beta_reduce
exact mod_cast nnnorm_add_le _ _
_ = _ := lintegral_nnnorm_add_left hf.aestronglyMeasurable _
_ < ∞ := add_lt_top.2 ⟨hf.hasFiniteIntegral, hg.hasFiniteIntegral⟩
#align measure_theory.integrable.add' MeasureTheory.Integrable.add'
theorem Integrable.add {f g : α → β} (hf : Integrable f μ) (hg : Integrable g μ) :
Integrable (f + g) μ :=
⟨hf.aestronglyMeasurable.add hg.aestronglyMeasurable, hf.add' hg⟩
#align measure_theory.integrable.add MeasureTheory.Integrable.add
theorem integrable_finset_sum' {ι} (s : Finset ι) {f : ι → α → β}
(hf : ∀ i ∈ s, Integrable (f i) μ) : Integrable (∑ i ∈ s, f i) μ :=
Finset.sum_induction f (fun g => Integrable g μ) (fun _ _ => Integrable.add)
(integrable_zero _ _ _) hf
#align measure_theory.integrable_finset_sum' MeasureTheory.integrable_finset_sum'
theorem integrable_finset_sum {ι} (s : Finset ι) {f : ι → α → β}
(hf : ∀ i ∈ s, Integrable (f i) μ) : Integrable (fun a => ∑ i ∈ s, f i a) μ := by
simpa only [← Finset.sum_apply] using integrable_finset_sum' s hf
#align measure_theory.integrable_finset_sum MeasureTheory.integrable_finset_sum
theorem Integrable.neg {f : α → β} (hf : Integrable f μ) : Integrable (-f) μ :=
⟨hf.aestronglyMeasurable.neg, hf.hasFiniteIntegral.neg⟩
#align measure_theory.integrable.neg MeasureTheory.Integrable.neg
@[simp]
theorem integrable_neg_iff {f : α → β} : Integrable (-f) μ ↔ Integrable f μ :=
⟨fun h => neg_neg f ▸ h.neg, Integrable.neg⟩
#align measure_theory.integrable_neg_iff MeasureTheory.integrable_neg_iff
@[simp]
lemma integrable_add_iff_integrable_right {f g : α → β} (hf : Integrable f μ) :
Integrable (f + g) μ ↔ Integrable g μ :=
⟨fun h ↦ show g = f + g + (-f) by simp only [add_neg_cancel_comm] ▸ h.add hf.neg,
fun h ↦ hf.add h⟩
@[simp]
lemma integrable_add_iff_integrable_left {f g : α → β} (hf : Integrable f μ) :
Integrable (g + f) μ ↔ Integrable g μ := by
rw [add_comm, integrable_add_iff_integrable_right hf]
lemma integrable_left_of_integrable_add_of_nonneg {f g : α → ℝ}
(h_meas : AEStronglyMeasurable f μ) (hf : 0 ≤ᵐ[μ] f) (hg : 0 ≤ᵐ[μ] g)
(h_int : Integrable (f + g) μ) : Integrable f μ := by
refine h_int.mono' h_meas ?_
filter_upwards [hf, hg] with a haf hag
exact (Real.norm_of_nonneg haf).symm ▸ (le_add_iff_nonneg_right _).mpr hag
lemma integrable_right_of_integrable_add_of_nonneg {f g : α → ℝ}
(h_meas : AEStronglyMeasurable f μ) (hf : 0 ≤ᵐ[μ] f) (hg : 0 ≤ᵐ[μ] g)
(h_int : Integrable (f + g) μ) : Integrable g μ :=
integrable_left_of_integrable_add_of_nonneg
((AEStronglyMeasurable.add_iff_right h_meas).mp h_int.aestronglyMeasurable)
hg hf (add_comm f g ▸ h_int)
lemma integrable_add_iff_of_nonneg {f g : α → ℝ} (h_meas : AEStronglyMeasurable f μ)
(hf : 0 ≤ᵐ[μ] f) (hg : 0 ≤ᵐ[μ] g) :
Integrable (f + g) μ ↔ Integrable f μ ∧ Integrable g μ :=
⟨fun h ↦ ⟨integrable_left_of_integrable_add_of_nonneg h_meas hf hg h,
integrable_right_of_integrable_add_of_nonneg h_meas hf hg h⟩, fun ⟨hf, hg⟩ ↦ hf.add hg⟩
lemma integrable_add_iff_of_nonpos {f g : α → ℝ} (h_meas : AEStronglyMeasurable f μ)
(hf : f ≤ᵐ[μ] 0) (hg : g ≤ᵐ[μ] 0) :
Integrable (f + g) μ ↔ Integrable f μ ∧ Integrable g μ := by
rw [← integrable_neg_iff, ← integrable_neg_iff (f := f), ← integrable_neg_iff (f := g), neg_add]
exact integrable_add_iff_of_nonneg h_meas.neg (hf.mono (fun _ ↦ neg_nonneg_of_nonpos))
(hg.mono (fun _ ↦ neg_nonneg_of_nonpos))
@[simp]
lemma integrable_add_const_iff [IsFiniteMeasure μ] {f : α → β} {c : β} :
Integrable (fun x ↦ f x + c) μ ↔ Integrable f μ :=
integrable_add_iff_integrable_left (integrable_const _)
@[simp]
lemma integrable_const_add_iff [IsFiniteMeasure μ] {f : α → β} {c : β} :
Integrable (fun x ↦ c + f x) μ ↔ Integrable f μ :=
integrable_add_iff_integrable_right (integrable_const _)
theorem Integrable.sub {f g : α → β} (hf : Integrable f μ) (hg : Integrable g μ) :
Integrable (f - g) μ := by simpa only [sub_eq_add_neg] using hf.add hg.neg
#align measure_theory.integrable.sub MeasureTheory.Integrable.sub
theorem Integrable.norm {f : α → β} (hf : Integrable f μ) : Integrable (fun a => ‖f a‖) μ :=
⟨hf.aestronglyMeasurable.norm, hf.hasFiniteIntegral.norm⟩
#align measure_theory.integrable.norm MeasureTheory.Integrable.norm
theorem Integrable.inf {β} [NormedLatticeAddCommGroup β] {f g : α → β} (hf : Integrable f μ)
(hg : Integrable g μ) : Integrable (f ⊓ g) μ := by
rw [← memℒp_one_iff_integrable] at hf hg ⊢
exact hf.inf hg
#align measure_theory.integrable.inf MeasureTheory.Integrable.inf
theorem Integrable.sup {β} [NormedLatticeAddCommGroup β] {f g : α → β} (hf : Integrable f μ)
(hg : Integrable g μ) : Integrable (f ⊔ g) μ := by
rw [← memℒp_one_iff_integrable] at hf hg ⊢
exact hf.sup hg
#align measure_theory.integrable.sup MeasureTheory.Integrable.sup
theorem Integrable.abs {β} [NormedLatticeAddCommGroup β] {f : α → β} (hf : Integrable f μ) :
Integrable (fun a => |f a|) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact hf.abs
#align measure_theory.integrable.abs MeasureTheory.Integrable.abs
theorem Integrable.bdd_mul {F : Type*} [NormedDivisionRing F] {f g : α → F} (hint : Integrable g μ)
(hm : AEStronglyMeasurable f μ) (hfbdd : ∃ C, ∀ x, ‖f x‖ ≤ C) :
Integrable (fun x => f x * g x) μ := by
cases' isEmpty_or_nonempty α with hα hα
· rw [μ.eq_zero_of_isEmpty]
exact integrable_zero_measure
· refine ⟨hm.mul hint.1, ?_⟩
obtain ⟨C, hC⟩ := hfbdd
have hCnonneg : 0 ≤ C := le_trans (norm_nonneg _) (hC hα.some)
have : (fun x => ‖f x * g x‖₊) ≤ fun x => ⟨C, hCnonneg⟩ * ‖g x‖₊ := by
intro x
simp only [nnnorm_mul]
exact mul_le_mul_of_nonneg_right (hC x) (zero_le _)
refine lt_of_le_of_lt (lintegral_mono_nnreal this) ?_
simp only [ENNReal.coe_mul]
rw [lintegral_const_mul' _ _ ENNReal.coe_ne_top]
exact ENNReal.mul_lt_top ENNReal.coe_ne_top (ne_of_lt hint.2)
#align measure_theory.integrable.bdd_mul MeasureTheory.Integrable.bdd_mul
/-- **Hölder's inequality for integrable functions**: the scalar multiplication of an integrable
vector-valued function by a scalar function with finite essential supremum is integrable. -/
theorem Integrable.essSup_smul {𝕜 : Type*} [NormedField 𝕜] [NormedSpace 𝕜 β] {f : α → β}
(hf : Integrable f μ) {g : α → 𝕜} (g_aestronglyMeasurable : AEStronglyMeasurable g μ)
(ess_sup_g : essSup (fun x => (‖g x‖₊ : ℝ≥0∞)) μ ≠ ∞) :
Integrable (fun x : α => g x • f x) μ := by
rw [← memℒp_one_iff_integrable] at *
refine ⟨g_aestronglyMeasurable.smul hf.1, ?_⟩
have h : (1 : ℝ≥0∞) / 1 = 1 / ∞ + 1 / 1 := by norm_num
have hg' : snorm g ∞ μ ≠ ∞ := by rwa [snorm_exponent_top]
calc
snorm (fun x : α => g x • f x) 1 μ ≤ _ := by
simpa using MeasureTheory.snorm_smul_le_mul_snorm hf.1 g_aestronglyMeasurable h
_ < ∞ := ENNReal.mul_lt_top hg' hf.2.ne
#align measure_theory.integrable.ess_sup_smul MeasureTheory.Integrable.essSup_smul
/-- Hölder's inequality for integrable functions: the scalar multiplication of an integrable
scalar-valued function by a vector-value function with finite essential supremum is integrable. -/
theorem Integrable.smul_essSup {𝕜 : Type*} [NormedRing 𝕜] [Module 𝕜 β] [BoundedSMul 𝕜 β]
{f : α → 𝕜} (hf : Integrable f μ) {g : α → β}
(g_aestronglyMeasurable : AEStronglyMeasurable g μ)
(ess_sup_g : essSup (fun x => (‖g x‖₊ : ℝ≥0∞)) μ ≠ ∞) :
Integrable (fun x : α => f x • g x) μ := by
rw [← memℒp_one_iff_integrable] at *
refine ⟨hf.1.smul g_aestronglyMeasurable, ?_⟩
have h : (1 : ℝ≥0∞) / 1 = 1 / 1 + 1 / ∞ := by norm_num
have hg' : snorm g ∞ μ ≠ ∞ := by rwa [snorm_exponent_top]
calc
snorm (fun x : α => f x • g x) 1 μ ≤ _ := by
simpa using MeasureTheory.snorm_smul_le_mul_snorm g_aestronglyMeasurable hf.1 h
_ < ∞ := ENNReal.mul_lt_top hf.2.ne hg'
#align measure_theory.integrable.smul_ess_sup MeasureTheory.Integrable.smul_essSup
theorem integrable_norm_iff {f : α → β} (hf : AEStronglyMeasurable f μ) :
Integrable (fun a => ‖f a‖) μ ↔ Integrable f μ := by
simp_rw [Integrable, and_iff_right hf, and_iff_right hf.norm, hasFiniteIntegral_norm_iff]
#align measure_theory.integrable_norm_iff MeasureTheory.integrable_norm_iff
theorem integrable_of_norm_sub_le {f₀ f₁ : α → β} {g : α → ℝ} (hf₁_m : AEStronglyMeasurable f₁ μ)
(hf₀_i : Integrable f₀ μ) (hg_i : Integrable g μ) (h : ∀ᵐ a ∂μ, ‖f₀ a - f₁ a‖ ≤ g a) :
Integrable f₁ μ :=
haveI : ∀ᵐ a ∂μ, ‖f₁ a‖ ≤ ‖f₀ a‖ + g a := by
apply h.mono
intro a ha
calc
‖f₁ a‖ ≤ ‖f₀ a‖ + ‖f₀ a - f₁ a‖ := norm_le_insert _ _
_ ≤ ‖f₀ a‖ + g a := add_le_add_left ha _
Integrable.mono' (hf₀_i.norm.add hg_i) hf₁_m this
#align measure_theory.integrable_of_norm_sub_le MeasureTheory.integrable_of_norm_sub_le
theorem Integrable.prod_mk {f : α → β} {g : α → γ} (hf : Integrable f μ) (hg : Integrable g μ) :
Integrable (fun x => (f x, g x)) μ :=
⟨hf.aestronglyMeasurable.prod_mk hg.aestronglyMeasurable,
(hf.norm.add' hg.norm).mono <|
eventually_of_forall fun x =>
calc
max ‖f x‖ ‖g x‖ ≤ ‖f x‖ + ‖g x‖ := max_le_add_of_nonneg (norm_nonneg _) (norm_nonneg _)
_ ≤ ‖‖f x‖ + ‖g x‖‖ := le_abs_self _⟩
#align measure_theory.integrable.prod_mk MeasureTheory.Integrable.prod_mk
theorem Memℒp.integrable {q : ℝ≥0∞} (hq1 : 1 ≤ q) {f : α → β} [IsFiniteMeasure μ]
(hfq : Memℒp f q μ) : Integrable f μ :=
memℒp_one_iff_integrable.mp (hfq.memℒp_of_exponent_le hq1)
#align measure_theory.mem_ℒp.integrable MeasureTheory.Memℒp.integrable
/-- A non-quantitative version of Markov inequality for integrable functions: the measure of points
where `‖f x‖ ≥ ε` is finite for all positive `ε`. -/
theorem Integrable.measure_norm_ge_lt_top {f : α → β} (hf : Integrable f μ) {ε : ℝ} (hε : 0 < ε) :
μ { x | ε ≤ ‖f x‖ } < ∞ := by
rw [show { x | ε ≤ ‖f x‖ } = { x | ENNReal.ofReal ε ≤ ‖f x‖₊ } by
simp only [ENNReal.ofReal, Real.toNNReal_le_iff_le_coe, ENNReal.coe_le_coe, coe_nnnorm]]
refine (meas_ge_le_mul_pow_snorm μ one_ne_zero ENNReal.one_ne_top hf.1 ?_).trans_lt ?_
· simpa only [Ne, ENNReal.ofReal_eq_zero, not_le] using hε
apply ENNReal.mul_lt_top
· simpa only [ENNReal.one_toReal, ENNReal.rpow_one, Ne, ENNReal.inv_eq_top,
ENNReal.ofReal_eq_zero, not_le] using hε
simpa only [ENNReal.one_toReal, ENNReal.rpow_one] using
(memℒp_one_iff_integrable.2 hf).snorm_ne_top
#align measure_theory.integrable.measure_ge_lt_top MeasureTheory.Integrable.measure_norm_ge_lt_top
/-- A non-quantitative version of Markov inequality for integrable functions: the measure of points
where `‖f x‖ > ε` is finite for all positive `ε`. -/
lemma Integrable.measure_norm_gt_lt_top {f : α → β} (hf : Integrable f μ) {ε : ℝ} (hε : 0 < ε) :
μ {x | ε < ‖f x‖} < ∞ :=
lt_of_le_of_lt (measure_mono (fun _ h ↦ (Set.mem_setOf_eq ▸ h).le)) (hf.measure_norm_ge_lt_top hε)
/-- If `f` is `ℝ`-valued and integrable, then for any `c > 0` the set `{x | f x ≥ c}` has finite
measure. -/
lemma Integrable.measure_ge_lt_top {f : α → ℝ} (hf : Integrable f μ) {ε : ℝ} (ε_pos : 0 < ε) :
μ {a : α | ε ≤ f a} < ∞ := by
refine lt_of_le_of_lt (measure_mono ?_) (hf.measure_norm_ge_lt_top ε_pos)
intro x hx
simp only [Real.norm_eq_abs, Set.mem_setOf_eq] at hx ⊢
exact hx.trans (le_abs_self _)
/-- If `f` is `ℝ`-valued and integrable, then for any `c < 0` the set `{x | f x ≤ c}` has finite
measure. -/
lemma Integrable.measure_le_lt_top {f : α → ℝ} (hf : Integrable f μ) {c : ℝ} (c_neg : c < 0) :
μ {a : α | f a ≤ c} < ∞ := by
refine lt_of_le_of_lt (measure_mono ?_) (hf.measure_norm_ge_lt_top (show 0 < -c by linarith))
intro x hx
simp only [Real.norm_eq_abs, Set.mem_setOf_eq] at hx ⊢
exact (show -c ≤ - f x by linarith).trans (neg_le_abs _)
/-- If `f` is `ℝ`-valued and integrable, then for any `c > 0` the set `{x | f x > c}` has finite
measure. -/
lemma Integrable.measure_gt_lt_top {f : α → ℝ} (hf : Integrable f μ) {ε : ℝ} (ε_pos : 0 < ε) :
μ {a : α | ε < f a} < ∞ :=
lt_of_le_of_lt (measure_mono (fun _ hx ↦ (Set.mem_setOf_eq ▸ hx).le))
(Integrable.measure_ge_lt_top hf ε_pos)
/-- If `f` is `ℝ`-valued and integrable, then for any `c < 0` the set `{x | f x < c}` has finite
measure. -/
lemma Integrable.measure_lt_lt_top {f : α → ℝ} (hf : Integrable f μ) {c : ℝ} (c_neg : c < 0) :
μ {a : α | f a < c} < ∞ :=
lt_of_le_of_lt (measure_mono (fun _ hx ↦ (Set.mem_setOf_eq ▸ hx).le))
(Integrable.measure_le_lt_top hf c_neg)
theorem LipschitzWith.integrable_comp_iff_of_antilipschitz {K K'} {f : α → β} {g : β → γ}
(hg : LipschitzWith K g) (hg' : AntilipschitzWith K' g) (g0 : g 0 = 0) :
Integrable (g ∘ f) μ ↔ Integrable f μ := by
simp [← memℒp_one_iff_integrable, hg.memℒp_comp_iff_of_antilipschitz hg' g0]
#align measure_theory.lipschitz_with.integrable_comp_iff_of_antilipschitz MeasureTheory.LipschitzWith.integrable_comp_iff_of_antilipschitz
theorem Integrable.real_toNNReal {f : α → ℝ} (hf : Integrable f μ) :
Integrable (fun x => ((f x).toNNReal : ℝ)) μ := by
refine
⟨hf.aestronglyMeasurable.aemeasurable.real_toNNReal.coe_nnreal_real.aestronglyMeasurable, ?_⟩
rw [hasFiniteIntegral_iff_norm]
refine lt_of_le_of_lt ?_ ((hasFiniteIntegral_iff_norm _).1 hf.hasFiniteIntegral)
apply lintegral_mono
intro x
simp [ENNReal.ofReal_le_ofReal, abs_le, le_abs_self]
#align measure_theory.integrable.real_to_nnreal MeasureTheory.Integrable.real_toNNReal
theorem ofReal_toReal_ae_eq {f : α → ℝ≥0∞} (hf : ∀ᵐ x ∂μ, f x < ∞) :
(fun x => ENNReal.ofReal (f x).toReal) =ᵐ[μ] f := by
filter_upwards [hf]
intro x hx
simp only [hx.ne, ofReal_toReal, Ne, not_false_iff]
#align measure_theory.of_real_to_real_ae_eq MeasureTheory.ofReal_toReal_ae_eq
theorem coe_toNNReal_ae_eq {f : α → ℝ≥0∞} (hf : ∀ᵐ x ∂μ, f x < ∞) :
(fun x => ((f x).toNNReal : ℝ≥0∞)) =ᵐ[μ] f := by
filter_upwards [hf]
intro x hx
simp only [hx.ne, Ne, not_false_iff, coe_toNNReal]
#align measure_theory.coe_to_nnreal_ae_eq MeasureTheory.coe_toNNReal_ae_eq
section
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
| Mathlib/MeasureTheory/Function/L1Space.lean | 945 | 960 | theorem integrable_withDensity_iff_integrable_coe_smul {f : α → ℝ≥0} (hf : Measurable f)
{g : α → E} :
Integrable g (μ.withDensity fun x => f x) ↔ Integrable (fun x => (f x : ℝ) • g x) μ := by |
by_cases H : AEStronglyMeasurable (fun x : α => (f x : ℝ) • g x) μ
· simp only [Integrable, aestronglyMeasurable_withDensity_iff hf, HasFiniteIntegral, H,
true_and_iff]
rw [lintegral_withDensity_eq_lintegral_mul₀' hf.coe_nnreal_ennreal.aemeasurable]
· rw [iff_iff_eq]
congr
ext1 x
simp only [nnnorm_smul, NNReal.nnnorm_eq, coe_mul, Pi.mul_apply]
· rw [aemeasurable_withDensity_ennreal_iff hf]
convert H.ennnorm using 1
ext1 x
simp only [nnnorm_smul, NNReal.nnnorm_eq, coe_mul]
· simp only [Integrable, aestronglyMeasurable_withDensity_iff hf, H, false_and_iff]
|
/-
Copyright (c) 2023 Peter Nelson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Peter Nelson
-/
import Mathlib.SetTheory.Cardinal.Finite
#align_import data.set.ncard from "leanprover-community/mathlib"@"74c2af38a828107941029b03839882c5c6f87a04"
/-!
# Noncomputable Set Cardinality
We define the cardinality of set `s` as a term `Set.encard s : ℕ∞` and a term `Set.ncard s : ℕ`.
The latter takes the junk value of zero if `s` is infinite. Both functions are noncomputable, and
are defined in terms of `PartENat.card` (which takes a type as its argument); this file can be seen
as an API for the same function in the special case where the type is a coercion of a `Set`,
allowing for smoother interactions with the `Set` API.
`Set.encard` never takes junk values, so is more mathematically natural than `Set.ncard`, even
though it takes values in a less convenient type. It is probably the right choice in settings where
one is concerned with the cardinalities of sets that may or may not be infinite.
`Set.ncard` has a nicer codomain, but when using it, `Set.Finite` hypotheses are normally needed to
make sure its values are meaningful. More generally, `Set.ncard` is intended to be used over the
obvious alternative `Finset.card` when finiteness is 'propositional' rather than 'structural'.
When working with sets that are finite by virtue of their definition, then `Finset.card` probably
makes more sense. One setting where `Set.ncard` works nicely is in a type `α` with `[Finite α]`,
where every set is automatically finite. In this setting, we use default arguments and a simple
tactic so that finiteness goals are discharged automatically in `Set.ncard` theorems.
## Main Definitions
* `Set.encard s` is the cardinality of the set `s` as an extended natural number, with value `⊤` if
`s` is infinite.
* `Set.ncard s` is the cardinality of the set `s` as a natural number, provided `s` is Finite.
If `s` is Infinite, then `Set.ncard s = 0`.
* `toFinite_tac` is a tactic that tries to synthesize a `Set.Finite s` argument with
`Set.toFinite`. This will work for `s : Set α` where there is a `Finite α` instance.
## Implementation Notes
The theorems in this file are very similar to those in `Data.Finset.Card`, but with `Set` operations
instead of `Finset`. We first prove all the theorems for `Set.encard`, and then derive most of the
`Set.ncard` results as a consequence. Things are done this way to avoid reliance on the `Finset` API
for theorems about infinite sets, and to allow for a refactor that removes or modifies `Set.ncard`
in the future.
Nearly all the theorems for `Set.ncard` require finiteness of one or more of their arguments. We
provide this assumption with a default argument of the form `(hs : s.Finite := by toFinite_tac)`,
where `toFinite_tac` will find an `s.Finite` term in the cases where `s` is a set in a `Finite`
type.
Often, where there are two set arguments `s` and `t`, the finiteness of one follows from the other
in the context of the theorem, in which case we only include the ones that are needed, and derive
the other inside the proof. A few of the theorems, such as `ncard_union_le` do not require
finiteness arguments; they are true by coincidence due to junk values.
-/
namespace Set
variable {α β : Type*} {s t : Set α}
/-- The cardinality of a set as a term in `ℕ∞` -/
noncomputable def encard (s : Set α) : ℕ∞ := PartENat.withTopEquiv (PartENat.card s)
@[simp] theorem encard_univ_coe (s : Set α) : encard (univ : Set s) = encard s := by
rw [encard, encard, PartENat.card_congr (Equiv.Set.univ ↑s)]
theorem encard_univ (α : Type*) :
encard (univ : Set α) = PartENat.withTopEquiv (PartENat.card α) := by
rw [encard, PartENat.card_congr (Equiv.Set.univ α)]
theorem Finite.encard_eq_coe_toFinset_card (h : s.Finite) : s.encard = h.toFinset.card := by
have := h.fintype
rw [encard, PartENat.card_eq_coe_fintype_card,
PartENat.withTopEquiv_natCast, toFinite_toFinset, toFinset_card]
theorem encard_eq_coe_toFinset_card (s : Set α) [Fintype s] : encard s = s.toFinset.card := by
have h := toFinite s
rw [h.encard_eq_coe_toFinset_card, toFinite_toFinset]
theorem encard_coe_eq_coe_finsetCard (s : Finset α) : encard (s : Set α) = s.card := by
rw [Finite.encard_eq_coe_toFinset_card (Finset.finite_toSet s)]; simp
theorem Infinite.encard_eq {s : Set α} (h : s.Infinite) : s.encard = ⊤ := by
have := h.to_subtype
rw [encard, ← PartENat.withTopEquiv.symm.injective.eq_iff, Equiv.symm_apply_apply,
PartENat.withTopEquiv_symm_top, PartENat.card_eq_top_of_infinite]
@[simp] theorem encard_eq_zero : s.encard = 0 ↔ s = ∅ := by
rw [encard, ← PartENat.withTopEquiv.symm.injective.eq_iff, Equiv.symm_apply_apply,
PartENat.withTopEquiv_symm_zero, PartENat.card_eq_zero_iff_empty, isEmpty_subtype,
eq_empty_iff_forall_not_mem]
@[simp] theorem encard_empty : (∅ : Set α).encard = 0 := by
rw [encard_eq_zero]
theorem nonempty_of_encard_ne_zero (h : s.encard ≠ 0) : s.Nonempty := by
rwa [nonempty_iff_ne_empty, Ne, ← encard_eq_zero]
theorem encard_ne_zero : s.encard ≠ 0 ↔ s.Nonempty := by
rw [ne_eq, encard_eq_zero, nonempty_iff_ne_empty]
@[simp] theorem encard_pos : 0 < s.encard ↔ s.Nonempty := by
rw [pos_iff_ne_zero, encard_ne_zero]
@[simp] theorem encard_singleton (e : α) : ({e} : Set α).encard = 1 := by
rw [encard, ← PartENat.withTopEquiv.symm.injective.eq_iff, Equiv.symm_apply_apply,
PartENat.card_eq_coe_fintype_card, Fintype.card_ofSubsingleton, Nat.cast_one]; rfl
theorem encard_union_eq (h : Disjoint s t) : (s ∪ t).encard = s.encard + t.encard := by
classical
have e := (Equiv.Set.union (by rwa [subset_empty_iff, ← disjoint_iff_inter_eq_empty])).symm
simp [encard, ← PartENat.card_congr e, PartENat.card_sum, PartENat.withTopEquiv]
theorem encard_insert_of_not_mem {a : α} (has : a ∉ s) : (insert a s).encard = s.encard + 1 := by
rw [← union_singleton, encard_union_eq (by simpa), encard_singleton]
theorem Finite.encard_lt_top (h : s.Finite) : s.encard < ⊤ := by
refine h.induction_on (by simp) ?_
rintro a t hat _ ht'
rw [encard_insert_of_not_mem hat]
exact lt_tsub_iff_right.1 ht'
theorem Finite.encard_eq_coe (h : s.Finite) : s.encard = ENat.toNat s.encard :=
(ENat.coe_toNat h.encard_lt_top.ne).symm
theorem Finite.exists_encard_eq_coe (h : s.Finite) : ∃ (n : ℕ), s.encard = n :=
⟨_, h.encard_eq_coe⟩
@[simp] theorem encard_lt_top_iff : s.encard < ⊤ ↔ s.Finite :=
⟨fun h ↦ by_contra fun h' ↦ h.ne (Infinite.encard_eq h'), Finite.encard_lt_top⟩
@[simp] theorem encard_eq_top_iff : s.encard = ⊤ ↔ s.Infinite := by
rw [← not_iff_not, ← Ne, ← lt_top_iff_ne_top, encard_lt_top_iff, not_infinite]
theorem encard_ne_top_iff : s.encard ≠ ⊤ ↔ s.Finite := by
simp
theorem finite_of_encard_le_coe {k : ℕ} (h : s.encard ≤ k) : s.Finite := by
rw [← encard_lt_top_iff]; exact h.trans_lt (WithTop.coe_lt_top _)
theorem finite_of_encard_eq_coe {k : ℕ} (h : s.encard = k) : s.Finite :=
finite_of_encard_le_coe h.le
theorem encard_le_coe_iff {k : ℕ} : s.encard ≤ k ↔ s.Finite ∧ ∃ (n₀ : ℕ), s.encard = n₀ ∧ n₀ ≤ k :=
⟨fun h ↦ ⟨finite_of_encard_le_coe h, by rwa [ENat.le_coe_iff] at h⟩,
fun ⟨_,⟨n₀,hs, hle⟩⟩ ↦ by rwa [hs, Nat.cast_le]⟩
section Lattice
theorem encard_le_card (h : s ⊆ t) : s.encard ≤ t.encard := by
rw [← union_diff_cancel h, encard_union_eq disjoint_sdiff_right]; exact le_self_add
theorem encard_mono {α : Type*} : Monotone (encard : Set α → ℕ∞) :=
fun _ _ ↦ encard_le_card
theorem encard_diff_add_encard_of_subset (h : s ⊆ t) : (t \ s).encard + s.encard = t.encard := by
rw [← encard_union_eq disjoint_sdiff_left, diff_union_self, union_eq_self_of_subset_right h]
@[simp] theorem one_le_encard_iff_nonempty : 1 ≤ s.encard ↔ s.Nonempty := by
rw [nonempty_iff_ne_empty, Ne, ← encard_eq_zero, ENat.one_le_iff_ne_zero]
theorem encard_diff_add_encard_inter (s t : Set α) :
(s \ t).encard + (s ∩ t).encard = s.encard := by
rw [← encard_union_eq (disjoint_of_subset_right inter_subset_right disjoint_sdiff_left),
diff_union_inter]
theorem encard_union_add_encard_inter (s t : Set α) :
(s ∪ t).encard + (s ∩ t).encard = s.encard + t.encard := by
rw [← diff_union_self, encard_union_eq disjoint_sdiff_left, add_right_comm,
encard_diff_add_encard_inter]
theorem encard_eq_encard_iff_encard_diff_eq_encard_diff (h : (s ∩ t).Finite) :
s.encard = t.encard ↔ (s \ t).encard = (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_right_cancel_iff h.encard_lt_top.ne]
theorem encard_le_encard_iff_encard_diff_le_encard_diff (h : (s ∩ t).Finite) :
s.encard ≤ t.encard ↔ (s \ t).encard ≤ (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_le_add_iff_right h.encard_lt_top.ne]
theorem encard_lt_encard_iff_encard_diff_lt_encard_diff (h : (s ∩ t).Finite) :
s.encard < t.encard ↔ (s \ t).encard < (t \ s).encard := by
rw [← encard_diff_add_encard_inter s t, ← encard_diff_add_encard_inter t s, inter_comm t s,
WithTop.add_lt_add_iff_right h.encard_lt_top.ne]
theorem encard_union_le (s t : Set α) : (s ∪ t).encard ≤ s.encard + t.encard := by
rw [← encard_union_add_encard_inter]; exact le_self_add
theorem finite_iff_finite_of_encard_eq_encard (h : s.encard = t.encard) : s.Finite ↔ t.Finite := by
rw [← encard_lt_top_iff, ← encard_lt_top_iff, h]
theorem infinite_iff_infinite_of_encard_eq_encard (h : s.encard = t.encard) :
s.Infinite ↔ t.Infinite := by rw [← encard_eq_top_iff, h, encard_eq_top_iff]
theorem Finite.finite_of_encard_le {s : Set α} {t : Set β} (hs : s.Finite)
(h : t.encard ≤ s.encard) : t.Finite :=
encard_lt_top_iff.1 (h.trans_lt hs.encard_lt_top)
theorem Finite.eq_of_subset_of_encard_le (ht : t.Finite) (hst : s ⊆ t) (hts : t.encard ≤ s.encard) :
s = t := by
rw [← zero_add (a := encard s), ← encard_diff_add_encard_of_subset hst] at hts
have hdiff := WithTop.le_of_add_le_add_right (ht.subset hst).encard_lt_top.ne hts
rw [nonpos_iff_eq_zero, encard_eq_zero, diff_eq_empty] at hdiff
exact hst.antisymm hdiff
theorem Finite.eq_of_subset_of_encard_le' (hs : s.Finite) (hst : s ⊆ t)
(hts : t.encard ≤ s.encard) : s = t :=
(hs.finite_of_encard_le hts).eq_of_subset_of_encard_le hst hts
theorem Finite.encard_lt_encard (ht : t.Finite) (h : s ⊂ t) : s.encard < t.encard :=
(encard_mono h.subset).lt_of_ne (fun he ↦ h.ne (ht.eq_of_subset_of_encard_le h.subset he.symm.le))
theorem encard_strictMono [Finite α] : StrictMono (encard : Set α → ℕ∞) :=
fun _ _ h ↦ (toFinite _).encard_lt_encard h
theorem encard_diff_add_encard (s t : Set α) : (s \ t).encard + t.encard = (s ∪ t).encard := by
rw [← encard_union_eq disjoint_sdiff_left, diff_union_self]
theorem encard_le_encard_diff_add_encard (s t : Set α) : s.encard ≤ (s \ t).encard + t.encard :=
(encard_mono subset_union_left).trans_eq (encard_diff_add_encard _ _).symm
theorem tsub_encard_le_encard_diff (s t : Set α) : s.encard - t.encard ≤ (s \ t).encard := by
rw [tsub_le_iff_left, add_comm]; apply encard_le_encard_diff_add_encard
theorem encard_add_encard_compl (s : Set α) : s.encard + sᶜ.encard = (univ : Set α).encard := by
rw [← encard_union_eq disjoint_compl_right, union_compl_self]
end Lattice
section InsertErase
variable {a b : α}
theorem encard_insert_le (s : Set α) (x : α) : (insert x s).encard ≤ s.encard + 1 := by
rw [← union_singleton, ← encard_singleton x]; apply encard_union_le
theorem encard_singleton_inter (s : Set α) (x : α) : ({x} ∩ s).encard ≤ 1 := by
rw [← encard_singleton x]; exact encard_le_card inter_subset_left
theorem encard_diff_singleton_add_one (h : a ∈ s) :
(s \ {a}).encard + 1 = s.encard := by
rw [← encard_insert_of_not_mem (fun h ↦ h.2 rfl), insert_diff_singleton, insert_eq_of_mem h]
theorem encard_diff_singleton_of_mem (h : a ∈ s) :
(s \ {a}).encard = s.encard - 1 := by
rw [← encard_diff_singleton_add_one h, ← WithTop.add_right_cancel_iff WithTop.one_ne_top,
tsub_add_cancel_of_le (self_le_add_left _ _)]
theorem encard_tsub_one_le_encard_diff_singleton (s : Set α) (x : α) :
s.encard - 1 ≤ (s \ {x}).encard := by
rw [← encard_singleton x]; apply tsub_encard_le_encard_diff
theorem encard_exchange (ha : a ∉ s) (hb : b ∈ s) : (insert a (s \ {b})).encard = s.encard := by
rw [encard_insert_of_not_mem, encard_diff_singleton_add_one hb]
simp_all only [not_true, mem_diff, mem_singleton_iff, false_and, not_false_eq_true]
theorem encard_exchange' (ha : a ∉ s) (hb : b ∈ s) : (insert a s \ {b}).encard = s.encard := by
rw [← insert_diff_singleton_comm (by rintro rfl; exact ha hb), encard_exchange ha hb]
theorem encard_eq_add_one_iff {k : ℕ∞} :
s.encard = k + 1 ↔ (∃ a t, ¬a ∈ t ∧ insert a t = s ∧ t.encard = k) := by
refine ⟨fun h ↦ ?_, ?_⟩
· obtain ⟨a, ha⟩ := nonempty_of_encard_ne_zero (s := s) (by simp [h])
refine ⟨a, s \ {a}, fun h ↦ h.2 rfl, by rwa [insert_diff_singleton, insert_eq_of_mem], ?_⟩
rw [← WithTop.add_right_cancel_iff WithTop.one_ne_top, ← h,
encard_diff_singleton_add_one ha]
rintro ⟨a, t, h, rfl, rfl⟩
rw [encard_insert_of_not_mem h]
/-- Every set is either empty, infinite, or can have its `encard` reduced by a removal. Intended
for well-founded induction on the value of `encard`. -/
theorem eq_empty_or_encard_eq_top_or_encard_diff_singleton_lt (s : Set α) :
s = ∅ ∨ s.encard = ⊤ ∨ ∃ a ∈ s, (s \ {a}).encard < s.encard := by
refine s.eq_empty_or_nonempty.elim Or.inl (Or.inr ∘ fun ⟨a,ha⟩ ↦
(s.finite_or_infinite.elim (fun hfin ↦ Or.inr ⟨a, ha, ?_⟩) (Or.inl ∘ Infinite.encard_eq)))
rw [← encard_diff_singleton_add_one ha]; nth_rw 1 [← add_zero (encard _)]
exact WithTop.add_lt_add_left (hfin.diff _).encard_lt_top.ne zero_lt_one
end InsertErase
section SmallSets
theorem encard_pair {x y : α} (hne : x ≠ y) : ({x, y} : Set α).encard = 2 := by
rw [encard_insert_of_not_mem (by simpa), ← one_add_one_eq_two,
WithTop.add_right_cancel_iff WithTop.one_ne_top, encard_singleton]
theorem encard_eq_one : s.encard = 1 ↔ ∃ x, s = {x} := by
refine ⟨fun h ↦ ?_, fun ⟨x, hx⟩ ↦ by rw [hx, encard_singleton]⟩
obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
exact ⟨x, ((finite_singleton x).eq_of_subset_of_encard_le' (by simpa) (by simp [h])).symm⟩
theorem encard_le_one_iff_eq : s.encard ≤ 1 ↔ s = ∅ ∨ ∃ x, s = {x} := by
rw [le_iff_lt_or_eq, lt_iff_not_le, ENat.one_le_iff_ne_zero, not_not, encard_eq_zero,
encard_eq_one]
theorem encard_le_one_iff : s.encard ≤ 1 ↔ ∀ a b, a ∈ s → b ∈ s → a = b := by
rw [encard_le_one_iff_eq, or_iff_not_imp_left, ← Ne, ← nonempty_iff_ne_empty]
refine ⟨fun h a b has hbs ↦ ?_,
fun h ⟨x, hx⟩ ↦ ⟨x, ((singleton_subset_iff.2 hx).antisymm' (fun y hy ↦ h _ _ hy hx))⟩⟩
obtain ⟨x, rfl⟩ := h ⟨_, has⟩
rw [(has : a = x), (hbs : b = x)]
theorem one_lt_encard_iff : 1 < s.encard ↔ ∃ a b, a ∈ s ∧ b ∈ s ∧ a ≠ b := by
rw [← not_iff_not, not_exists, not_lt, encard_le_one_iff]; aesop
theorem exists_ne_of_one_lt_encard (h : 1 < s.encard) (a : α) : ∃ b ∈ s, b ≠ a := by
by_contra! h'
obtain ⟨b, b', hb, hb', hne⟩ := one_lt_encard_iff.1 h
apply hne
rw [h' b hb, h' b' hb']
theorem encard_eq_two : s.encard = 2 ↔ ∃ x y, x ≠ y ∧ s = {x, y} := by
refine ⟨fun h ↦ ?_, fun ⟨x, y, hne, hs⟩ ↦ by rw [hs, encard_pair hne]⟩
obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
rw [← insert_eq_of_mem hx, ← insert_diff_singleton, encard_insert_of_not_mem (fun h ↦ h.2 rfl),
← one_add_one_eq_two, WithTop.add_right_cancel_iff (WithTop.one_ne_top), encard_eq_one] at h
obtain ⟨y, h⟩ := h
refine ⟨x, y, by rintro rfl; exact (h.symm.subset rfl).2 rfl, ?_⟩
rw [← h, insert_diff_singleton, insert_eq_of_mem hx]
theorem encard_eq_three {α : Type u_1} {s : Set α} :
encard s = 3 ↔ ∃ x y z, x ≠ y ∧ x ≠ z ∧ y ≠ z ∧ s = {x, y, z} := by
refine ⟨fun h ↦ ?_, fun ⟨x, y, z, hxy, hyz, hxz, hs⟩ ↦ ?_⟩
· obtain ⟨x, hx⟩ := nonempty_of_encard_ne_zero (s := s) (by rw [h]; simp)
rw [← insert_eq_of_mem hx, ← insert_diff_singleton,
encard_insert_of_not_mem (fun h ↦ h.2 rfl), (by exact rfl : (3 : ℕ∞) = 2 + 1),
WithTop.add_right_cancel_iff WithTop.one_ne_top, encard_eq_two] at h
obtain ⟨y, z, hne, hs⟩ := h
refine ⟨x, y, z, ?_, ?_, hne, ?_⟩
· rintro rfl; exact (hs.symm.subset (Or.inl rfl)).2 rfl
· rintro rfl; exact (hs.symm.subset (Or.inr rfl)).2 rfl
rw [← hs, insert_diff_singleton, insert_eq_of_mem hx]
rw [hs, encard_insert_of_not_mem, encard_insert_of_not_mem, encard_singleton] <;> aesop
theorem Nat.encard_range (k : ℕ) : {i | i < k}.encard = k := by
convert encard_coe_eq_coe_finsetCard (Finset.range k) using 1
· rw [Finset.coe_range, Iio_def]
rw [Finset.card_range]
end SmallSets
theorem Finite.eq_insert_of_subset_of_encard_eq_succ (hs : s.Finite) (h : s ⊆ t)
(hst : t.encard = s.encard + 1) : ∃ a, t = insert a s := by
rw [← encard_diff_add_encard_of_subset h, add_comm,
WithTop.add_left_cancel_iff hs.encard_lt_top.ne, encard_eq_one] at hst
obtain ⟨x, hx⟩ := hst; use x; rw [← diff_union_of_subset h, hx, singleton_union]
| Mathlib/Data/Set/Card.lean | 351 | 361 | theorem exists_subset_encard_eq {k : ℕ∞} (hk : k ≤ s.encard) : ∃ t, t ⊆ s ∧ t.encard = k := by |
revert hk
refine ENat.nat_induction k (fun _ ↦ ⟨∅, empty_subset _, by simp⟩) (fun n IH hle ↦ ?_) ?_
· obtain ⟨t₀, ht₀s, ht₀⟩ := IH (le_trans (by simp) hle)
simp only [Nat.cast_succ] at *
have hne : t₀ ≠ s := by
rintro rfl; rw [ht₀, ← Nat.cast_one, ← Nat.cast_add, Nat.cast_le] at hle; simp at hle
obtain ⟨x, hx⟩ := exists_of_ssubset (ht₀s.ssubset_of_ne hne)
exact ⟨insert x t₀, insert_subset hx.1 ht₀s, by rw [encard_insert_of_not_mem hx.2, ht₀]⟩
simp only [top_le_iff, encard_eq_top_iff]
exact fun _ hi ↦ ⟨s, Subset.rfl, hi⟩
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Johannes Hölzl, Scott Morrison, Jens Wagemaker
-/
import Mathlib.Algebra.Polynomial.Basic
#align_import data.polynomial.monomial from "leanprover-community/mathlib"@"220f71ba506c8958c9b41bd82226b3d06b0991e8"
/-!
# Univariate monomials
Preparatory lemmas for degree_basic.
-/
noncomputable section
namespace Polynomial
open Polynomial
universe u
variable {R : Type u} {a b : R} {m n : ℕ}
variable [Semiring R] {p q r : R[X]}
theorem monomial_one_eq_iff [Nontrivial R] {i j : ℕ} :
(monomial i 1 : R[X]) = monomial j 1 ↔ i = j := by
-- Porting note: `ofFinsupp.injEq` is required.
simp_rw [← ofFinsupp_single, ofFinsupp.injEq]
exact AddMonoidAlgebra.of_injective.eq_iff
#align polynomial.monomial_one_eq_iff Polynomial.monomial_one_eq_iff
instance infinite [Nontrivial R] : Infinite R[X] :=
Infinite.of_injective (fun i => monomial i 1) fun m n h => by simpa [monomial_one_eq_iff] using h
#align polynomial.infinite Polynomial.infinite
| Mathlib/Algebra/Polynomial/Monomial.lean | 39 | 56 | theorem card_support_le_one_iff_monomial {f : R[X]} :
Finset.card f.support ≤ 1 ↔ ∃ n a, f = monomial n a := by |
constructor
· intro H
rw [Finset.card_le_one_iff_subset_singleton] at H
rcases H with ⟨n, hn⟩
refine ⟨n, f.coeff n, ?_⟩
ext i
by_cases hi : i = n
· simp [hi, coeff_monomial]
· have : f.coeff i = 0 := by
rw [← not_mem_support_iff]
exact fun hi' => hi (Finset.mem_singleton.1 (hn hi'))
simp [this, Ne.symm hi, coeff_monomial]
· rintro ⟨n, a, rfl⟩
rw [← Finset.card_singleton n]
apply Finset.card_le_card
exact support_monomial' _ _
|
/-
Copyright (c) 2020 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.Algebra.Group.Conj
import Mathlib.Algebra.Group.Pi.Lemmas
import Mathlib.Algebra.Group.Subsemigroup.Operations
import Mathlib.Algebra.Group.Submonoid.Operations
import Mathlib.Algebra.Order.Group.Abs
import Mathlib.Data.Set.Image
import Mathlib.Order.Atoms
import Mathlib.Tactic.ApplyFun
#align_import group_theory.subgroup.basic from "leanprover-community/mathlib"@"4be589053caf347b899a494da75410deb55fb3ef"
/-!
# Subgroups
This file defines multiplicative and additive subgroups as an extension of submonoids, in a bundled
form (unbundled subgroups are in `Deprecated/Subgroups.lean`).
We prove subgroups of a group form a complete lattice, and results about images and preimages of
subgroups under group homomorphisms. The bundled subgroups use bundled monoid homomorphisms.
There are also theorems about the subgroups generated by an element or a subset of a group,
defined both inductively and as the infimum of the set of subgroups containing a given
element/subset.
Special thanks goes to Amelia Livingston and Yury Kudryashov for their help and inspiration.
## Main definitions
Notation used here:
- `G N` are `Group`s
- `A` is an `AddGroup`
- `H K` are `Subgroup`s of `G` or `AddSubgroup`s of `A`
- `x` is an element of type `G` or type `A`
- `f g : N →* G` are group homomorphisms
- `s k` are sets of elements of type `G`
Definitions in the file:
* `Subgroup G` : the type of subgroups of a group `G`
* `AddSubgroup A` : the type of subgroups of an additive group `A`
* `CompleteLattice (Subgroup G)` : the subgroups of `G` form a complete lattice
* `Subgroup.closure k` : the minimal subgroup that includes the set `k`
* `Subgroup.subtype` : the natural group homomorphism from a subgroup of group `G` to `G`
* `Subgroup.gi` : `closure` forms a Galois insertion with the coercion to set
* `Subgroup.comap H f` : the preimage of a subgroup `H` along the group homomorphism `f` is also a
subgroup
* `Subgroup.map f H` : the image of a subgroup `H` along the group homomorphism `f` is also a
subgroup
* `Subgroup.prod H K` : the product of subgroups `H`, `K` of groups `G`, `N` respectively, `H × K`
is a subgroup of `G × N`
* `MonoidHom.range f` : the range of the group homomorphism `f` is a subgroup
* `MonoidHom.ker f` : the kernel of a group homomorphism `f` is the subgroup of elements `x : G`
such that `f x = 1`
* `MonoidHom.eq_locus f g` : given group homomorphisms `f`, `g`, the elements of `G` such that
`f x = g x` form a subgroup of `G`
## Implementation notes
Subgroup inclusion is denoted `≤` rather than `⊆`, although `∈` is defined as
membership of a subgroup's underlying set.
## Tags
subgroup, subgroups
-/
open Function
open Int
variable {G G' G'' : Type*} [Group G] [Group G'] [Group G'']
variable {A : Type*} [AddGroup A]
section SubgroupClass
/-- `InvMemClass S G` states `S` is a type of subsets `s ⊆ G` closed under inverses. -/
class InvMemClass (S G : Type*) [Inv G] [SetLike S G] : Prop where
/-- `s` is closed under inverses -/
inv_mem : ∀ {s : S} {x}, x ∈ s → x⁻¹ ∈ s
#align inv_mem_class InvMemClass
export InvMemClass (inv_mem)
/-- `NegMemClass S G` states `S` is a type of subsets `s ⊆ G` closed under negation. -/
class NegMemClass (S G : Type*) [Neg G] [SetLike S G] : Prop where
/-- `s` is closed under negation -/
neg_mem : ∀ {s : S} {x}, x ∈ s → -x ∈ s
#align neg_mem_class NegMemClass
export NegMemClass (neg_mem)
/-- `SubgroupClass S G` states `S` is a type of subsets `s ⊆ G` that are subgroups of `G`. -/
class SubgroupClass (S G : Type*) [DivInvMonoid G] [SetLike S G] extends SubmonoidClass S G,
InvMemClass S G : Prop
#align subgroup_class SubgroupClass
/-- `AddSubgroupClass S G` states `S` is a type of subsets `s ⊆ G` that are
additive subgroups of `G`. -/
class AddSubgroupClass (S G : Type*) [SubNegMonoid G] [SetLike S G] extends AddSubmonoidClass S G,
NegMemClass S G : Prop
#align add_subgroup_class AddSubgroupClass
attribute [to_additive] InvMemClass SubgroupClass
attribute [aesop safe apply (rule_sets := [SetLike])] inv_mem neg_mem
@[to_additive (attr := simp)]
theorem inv_mem_iff {S G} [InvolutiveInv G] {_ : SetLike S G} [InvMemClass S G] {H : S}
{x : G} : x⁻¹ ∈ H ↔ x ∈ H :=
⟨fun h => inv_inv x ▸ inv_mem h, inv_mem⟩
#align inv_mem_iff inv_mem_iff
#align neg_mem_iff neg_mem_iff
@[simp] theorem abs_mem_iff {S G} [AddGroup G] [LinearOrder G] {_ : SetLike S G}
[NegMemClass S G] {H : S} {x : G} : |x| ∈ H ↔ x ∈ H := by
cases abs_choice x <;> simp [*]
variable {M S : Type*} [DivInvMonoid M] [SetLike S M] [hSM : SubgroupClass S M] {H K : S}
/-- A subgroup is closed under division. -/
@[to_additive (attr := aesop safe apply (rule_sets := [SetLike]))
"An additive subgroup is closed under subtraction."]
| Mathlib/Algebra/Group/Subgroup/Basic.lean | 144 | 145 | theorem div_mem {x y : M} (hx : x ∈ H) (hy : y ∈ H) : x / y ∈ H := by |
rw [div_eq_mul_inv]; exact mul_mem hx (inv_mem hy)
|
/-
Copyright (c) 2022 Violeta Hernández Palacios. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Violeta Hernández Palacios
-/
import Mathlib.SetTheory.Ordinal.Arithmetic
import Mathlib.Tactic.Abel
#align_import set_theory.ordinal.natural_ops from "leanprover-community/mathlib"@"31b269b60935483943542d547a6dd83a66b37dc7"
/-!
# Natural operations on ordinals
The goal of this file is to define natural addition and multiplication on ordinals, also known as
the Hessenberg sum and product, and provide a basic API. The natural addition of two ordinals
`a ♯ b` is recursively defined as the least ordinal greater than `a' ♯ b` and `a ♯ b'` for `a' < a`
and `b' < b`. The natural multiplication `a ⨳ b` is likewise recursively defined as the least
ordinal such that `a ⨳ b ♯ a' ⨳ b'` is greater than `a' ⨳ b ♯ a ⨳ b'` for any `a' < a` and
`b' < b`.
These operations form a rich algebraic structure: they're commutative, associative, preserve order,
have the usual `0` and `1` from ordinals, and distribute over one another.
Moreover, these operations are the addition and multiplication of ordinals when viewed as
combinatorial `Game`s. This makes them particularly useful for game theory.
Finally, both operations admit simple, intuitive descriptions in terms of the Cantor normal form.
The natural addition of two ordinals corresponds to adding their Cantor normal forms as if they were
polynomials in `ω`. Likewise, their natural multiplication corresponds to multiplying the Cantor
normal forms as polynomials.
# Implementation notes
Given the rich algebraic structure of these two operations, we choose to create a type synonym
`NatOrdinal`, where we provide the appropriate instances. However, to avoid casting back and forth
between both types, we attempt to prove and state most results on `Ordinal`.
# Todo
- Prove the characterizations of natural addition and multiplication in terms of the Cantor normal
form.
-/
set_option autoImplicit true
universe u v
open Function Order
noncomputable section
/-! ### Basic casts between `Ordinal` and `NatOrdinal` -/
/-- A type synonym for ordinals with natural addition and multiplication. -/
def NatOrdinal : Type _ :=
-- Porting note: used to derive LinearOrder & SuccOrder but need to manually define
Ordinal deriving Zero, Inhabited, One, WellFoundedRelation
#align nat_ordinal NatOrdinal
instance NatOrdinal.linearOrder : LinearOrder NatOrdinal := {Ordinal.linearOrder with}
instance NatOrdinal.succOrder : SuccOrder NatOrdinal := {Ordinal.succOrder with}
/-- The identity function between `Ordinal` and `NatOrdinal`. -/
@[match_pattern]
def Ordinal.toNatOrdinal : Ordinal ≃o NatOrdinal :=
OrderIso.refl _
#align ordinal.to_nat_ordinal Ordinal.toNatOrdinal
/-- The identity function between `NatOrdinal` and `Ordinal`. -/
@[match_pattern]
def NatOrdinal.toOrdinal : NatOrdinal ≃o Ordinal :=
OrderIso.refl _
#align nat_ordinal.to_ordinal NatOrdinal.toOrdinal
namespace NatOrdinal
open Ordinal
@[simp]
theorem toOrdinal_symm_eq : NatOrdinal.toOrdinal.symm = Ordinal.toNatOrdinal :=
rfl
#align nat_ordinal.to_ordinal_symm_eq NatOrdinal.toOrdinal_symm_eq
-- Porting note: used to use dot notation, but doesn't work in Lean 4 with `OrderIso`
@[simp]
theorem toOrdinal_toNatOrdinal (a : NatOrdinal) :
Ordinal.toNatOrdinal (NatOrdinal.toOrdinal a) = a := rfl
#align nat_ordinal.to_ordinal_to_nat_ordinal NatOrdinal.toOrdinal_toNatOrdinal
theorem lt_wf : @WellFounded NatOrdinal (· < ·) :=
Ordinal.lt_wf
#align nat_ordinal.lt_wf NatOrdinal.lt_wf
instance : WellFoundedLT NatOrdinal :=
Ordinal.wellFoundedLT
instance : IsWellOrder NatOrdinal (· < ·) :=
Ordinal.isWellOrder
@[simp]
theorem toOrdinal_zero : toOrdinal 0 = 0 :=
rfl
#align nat_ordinal.to_ordinal_zero NatOrdinal.toOrdinal_zero
@[simp]
theorem toOrdinal_one : toOrdinal 1 = 1 :=
rfl
#align nat_ordinal.to_ordinal_one NatOrdinal.toOrdinal_one
@[simp]
theorem toOrdinal_eq_zero (a) : toOrdinal a = 0 ↔ a = 0 :=
Iff.rfl
#align nat_ordinal.to_ordinal_eq_zero NatOrdinal.toOrdinal_eq_zero
@[simp]
theorem toOrdinal_eq_one (a) : toOrdinal a = 1 ↔ a = 1 :=
Iff.rfl
#align nat_ordinal.to_ordinal_eq_one NatOrdinal.toOrdinal_eq_one
@[simp]
theorem toOrdinal_max : toOrdinal (max a b) = max (toOrdinal a) (toOrdinal b) :=
rfl
#align nat_ordinal.to_ordinal_max NatOrdinal.toOrdinal_max
@[simp]
theorem toOrdinal_min : toOrdinal (min a b)= min (toOrdinal a) (toOrdinal b) :=
rfl
#align nat_ordinal.to_ordinal_min NatOrdinal.toOrdinal_min
theorem succ_def (a : NatOrdinal) : succ a = toNatOrdinal (toOrdinal a + 1) :=
rfl
#align nat_ordinal.succ_def NatOrdinal.succ_def
/-- A recursor for `NatOrdinal`. Use as `induction x using NatOrdinal.rec`. -/
protected def rec {β : NatOrdinal → Sort*} (h : ∀ a, β (toNatOrdinal a)) : ∀ a, β a := fun a =>
h (toOrdinal a)
#align nat_ordinal.rec NatOrdinal.rec
/-- `Ordinal.induction` but for `NatOrdinal`. -/
theorem induction {p : NatOrdinal → Prop} : ∀ (i) (_ : ∀ j, (∀ k, k < j → p k) → p j), p i :=
Ordinal.induction
#align nat_ordinal.induction NatOrdinal.induction
end NatOrdinal
namespace Ordinal
variable {a b c : Ordinal.{u}}
@[simp]
theorem toNatOrdinal_symm_eq : toNatOrdinal.symm = NatOrdinal.toOrdinal :=
rfl
#align ordinal.to_nat_ordinal_symm_eq Ordinal.toNatOrdinal_symm_eq
@[simp]
theorem toNatOrdinal_toOrdinal (a : Ordinal) : NatOrdinal.toOrdinal (toNatOrdinal a) = a :=
rfl
#align ordinal.to_nat_ordinal_to_ordinal Ordinal.toNatOrdinal_toOrdinal
@[simp]
theorem toNatOrdinal_zero : toNatOrdinal 0 = 0 :=
rfl
#align ordinal.to_nat_ordinal_zero Ordinal.toNatOrdinal_zero
@[simp]
theorem toNatOrdinal_one : toNatOrdinal 1 = 1 :=
rfl
#align ordinal.to_nat_ordinal_one Ordinal.toNatOrdinal_one
@[simp]
theorem toNatOrdinal_eq_zero (a) : toNatOrdinal a = 0 ↔ a = 0 :=
Iff.rfl
#align ordinal.to_nat_ordinal_eq_zero Ordinal.toNatOrdinal_eq_zero
@[simp]
theorem toNatOrdinal_eq_one (a) : toNatOrdinal a = 1 ↔ a = 1 :=
Iff.rfl
#align ordinal.to_nat_ordinal_eq_one Ordinal.toNatOrdinal_eq_one
@[simp]
theorem toNatOrdinal_max (a b : Ordinal) :
toNatOrdinal (max a b) = max (toNatOrdinal a) (toNatOrdinal b) :=
rfl
#align ordinal.to_nat_ordinal_max Ordinal.toNatOrdinal_max
@[simp]
theorem toNatOrdinal_min (a b : Ordinal) :
toNatOrdinal (linearOrder.min a b) = linearOrder.min (toNatOrdinal a) (toNatOrdinal b) :=
rfl
#align ordinal.to_nat_ordinal_min Ordinal.toNatOrdinal_min
/-! We place the definitions of `nadd` and `nmul` before actually developing their API, as this
guarantees we only need to open the `NaturalOps` locale once. -/
/-- Natural addition on ordinals `a ♯ b`, also known as the Hessenberg sum, is recursively defined
as the least ordinal greater than `a' ♯ b` and `a ♯ b'` for all `a' < a` and `b' < b`. In contrast
to normal ordinal addition, it is commutative.
Natural addition can equivalently be characterized as the ordinal resulting from adding up
corresponding coefficients in the Cantor normal forms of `a` and `b`. -/
noncomputable def nadd : Ordinal → Ordinal → Ordinal
| a, b =>
max (blsub.{u, u} a fun a' _ => nadd a' b) (blsub.{u, u} b fun b' _ => nadd a b')
termination_by o₁ o₂ => (o₁, o₂)
#align ordinal.nadd Ordinal.nadd
@[inherit_doc]
scoped[NaturalOps] infixl:65 " ♯ " => Ordinal.nadd
open NaturalOps
/-- Natural multiplication on ordinals `a ⨳ b`, also known as the Hessenberg product, is recursively
defined as the least ordinal such that `a ⨳ b + a' ⨳ b'` is greater than `a' ⨳ b + a ⨳ b'` for all
`a' < a` and `b < b'`. In contrast to normal ordinal multiplication, it is commutative and
distributive (over natural addition).
Natural multiplication can equivalently be characterized as the ordinal resulting from multiplying
the Cantor normal forms of `a` and `b` as if they were polynomials in `ω`. Addition of exponents is
done via natural addition. -/
noncomputable def nmul : Ordinal.{u} → Ordinal.{u} → Ordinal.{u}
| a, b => sInf {c | ∀ a' < a, ∀ b' < b, nmul a' b ♯ nmul a b' < c ♯ nmul a' b'}
termination_by a b => (a, b)
#align ordinal.nmul Ordinal.nmul
@[inherit_doc]
scoped[NaturalOps] infixl:70 " ⨳ " => Ordinal.nmul
/-! ### Natural addition -/
theorem nadd_def (a b : Ordinal) :
a ♯ b = max (blsub.{u, u} a fun a' _ => a' ♯ b) (blsub.{u, u} b fun b' _ => a ♯ b') := by
rw [nadd]
#align ordinal.nadd_def Ordinal.nadd_def
theorem lt_nadd_iff : a < b ♯ c ↔ (∃ b' < b, a ≤ b' ♯ c) ∨ ∃ c' < c, a ≤ b ♯ c' := by
rw [nadd_def]
simp [lt_blsub_iff]
#align ordinal.lt_nadd_iff Ordinal.lt_nadd_iff
theorem nadd_le_iff : b ♯ c ≤ a ↔ (∀ b' < b, b' ♯ c < a) ∧ ∀ c' < c, b ♯ c' < a := by
rw [nadd_def]
simp [blsub_le_iff]
#align ordinal.nadd_le_iff Ordinal.nadd_le_iff
theorem nadd_lt_nadd_left (h : b < c) (a) : a ♯ b < a ♯ c :=
lt_nadd_iff.2 (Or.inr ⟨b, h, le_rfl⟩)
#align ordinal.nadd_lt_nadd_left Ordinal.nadd_lt_nadd_left
theorem nadd_lt_nadd_right (h : b < c) (a) : b ♯ a < c ♯ a :=
lt_nadd_iff.2 (Or.inl ⟨b, h, le_rfl⟩)
#align ordinal.nadd_lt_nadd_right Ordinal.nadd_lt_nadd_right
| Mathlib/SetTheory/Ordinal/NaturalOps.lean | 255 | 258 | theorem nadd_le_nadd_left (h : b ≤ c) (a) : a ♯ b ≤ a ♯ c := by |
rcases lt_or_eq_of_le h with (h | rfl)
· exact (nadd_lt_nadd_left h a).le
· exact le_rfl
|
/-
Copyright (c) 2015 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Leonardo de Moura, Mario Carneiro
-/
import Mathlib.Data.Set.Function
import Mathlib.Logic.Equiv.Defs
import Mathlib.Tactic.Says
#align_import logic.equiv.set from "leanprover-community/mathlib"@"aba57d4d3dae35460225919dcd82fe91355162f9"
/-!
# Equivalences and sets
In this file we provide lemmas linking equivalences to sets.
Some notable definitions are:
* `Equiv.ofInjective`: an injective function is (noncomputably) equivalent to its range.
* `Equiv.setCongr`: two equal sets are equivalent as types.
* `Equiv.Set.union`: a disjoint union of sets is equivalent to their `Sum`.
This file is separate from `Equiv/Basic` such that we do not require the full lattice structure
on sets before defining what an equivalence is.
-/
open Function Set
universe u v w z
variable {α : Sort u} {β : Sort v} {γ : Sort w}
namespace Equiv
@[simp]
theorem range_eq_univ {α : Type*} {β : Type*} (e : α ≃ β) : range e = univ :=
eq_univ_of_forall e.surjective
#align equiv.range_eq_univ Equiv.range_eq_univ
protected theorem image_eq_preimage {α β} (e : α ≃ β) (s : Set α) : e '' s = e.symm ⁻¹' s :=
Set.ext fun _ => mem_image_iff_of_inverse e.left_inv e.right_inv
#align equiv.image_eq_preimage Equiv.image_eq_preimage
@[simp 1001]
theorem _root_.Set.mem_image_equiv {α β} {S : Set α} {f : α ≃ β} {x : β} :
x ∈ f '' S ↔ f.symm x ∈ S :=
Set.ext_iff.mp (f.image_eq_preimage S) x
#align set.mem_image_equiv Set.mem_image_equiv
/-- Alias for `Equiv.image_eq_preimage` -/
theorem _root_.Set.image_equiv_eq_preimage_symm {α β} (S : Set α) (f : α ≃ β) :
f '' S = f.symm ⁻¹' S :=
f.image_eq_preimage S
#align set.image_equiv_eq_preimage_symm Set.image_equiv_eq_preimage_symm
/-- Alias for `Equiv.image_eq_preimage` -/
theorem _root_.Set.preimage_equiv_eq_image_symm {α β} (S : Set α) (f : β ≃ α) :
f ⁻¹' S = f.symm '' S :=
(f.symm.image_eq_preimage S).symm
#align set.preimage_equiv_eq_image_symm Set.preimage_equiv_eq_image_symm
-- Porting note: increased priority so this fires before `image_subset_iff`
@[simp high]
protected theorem symm_image_subset {α β} (e : α ≃ β) (s : Set α) (t : Set β) :
e.symm '' t ⊆ s ↔ t ⊆ e '' s := by rw [image_subset_iff, e.image_eq_preimage]
#align equiv.subset_image Equiv.symm_image_subset
@[deprecated (since := "2024-01-19")] alias subset_image := Equiv.symm_image_subset
-- Porting note: increased priority so this fires before `image_subset_iff`
@[simp high]
protected theorem subset_symm_image {α β} (e : α ≃ β) (s : Set α) (t : Set β) :
s ⊆ e.symm '' t ↔ e '' s ⊆ t :=
calc
s ⊆ e.symm '' t ↔ e.symm.symm '' s ⊆ t := by rw [e.symm.symm_image_subset]
_ ↔ e '' s ⊆ t := by rw [e.symm_symm]
#align equiv.subset_image' Equiv.subset_symm_image
@[deprecated (since := "2024-01-19")] alias subset_image' := Equiv.subset_symm_image
@[simp]
theorem symm_image_image {α β} (e : α ≃ β) (s : Set α) : e.symm '' (e '' s) = s :=
e.leftInverse_symm.image_image s
#align equiv.symm_image_image Equiv.symm_image_image
theorem eq_image_iff_symm_image_eq {α β} (e : α ≃ β) (s : Set α) (t : Set β) :
t = e '' s ↔ e.symm '' t = s :=
(e.symm.injective.image_injective.eq_iff' (e.symm_image_image s)).symm
#align equiv.eq_image_iff_symm_image_eq Equiv.eq_image_iff_symm_image_eq
@[simp]
theorem image_symm_image {α β} (e : α ≃ β) (s : Set β) : e '' (e.symm '' s) = s :=
e.symm.symm_image_image s
#align equiv.image_symm_image Equiv.image_symm_image
@[simp]
theorem image_preimage {α β} (e : α ≃ β) (s : Set β) : e '' (e ⁻¹' s) = s :=
e.surjective.image_preimage s
#align equiv.image_preimage Equiv.image_preimage
@[simp]
theorem preimage_image {α β} (e : α ≃ β) (s : Set α) : e ⁻¹' (e '' s) = s :=
e.injective.preimage_image s
#align equiv.preimage_image Equiv.preimage_image
protected theorem image_compl {α β} (f : Equiv α β) (s : Set α) : f '' sᶜ = (f '' s)ᶜ :=
image_compl_eq f.bijective
#align equiv.image_compl Equiv.image_compl
@[simp]
theorem symm_preimage_preimage {α β} (e : α ≃ β) (s : Set β) : e.symm ⁻¹' (e ⁻¹' s) = s :=
e.rightInverse_symm.preimage_preimage s
#align equiv.symm_preimage_preimage Equiv.symm_preimage_preimage
@[simp]
theorem preimage_symm_preimage {α β} (e : α ≃ β) (s : Set α) : e ⁻¹' (e.symm ⁻¹' s) = s :=
e.leftInverse_symm.preimage_preimage s
#align equiv.preimage_symm_preimage Equiv.preimage_symm_preimage
theorem preimage_subset {α β} (e : α ≃ β) (s t : Set β) : e ⁻¹' s ⊆ e ⁻¹' t ↔ s ⊆ t :=
e.surjective.preimage_subset_preimage_iff
#align equiv.preimage_subset Equiv.preimage_subset
-- Porting note (#10618): removed `simp` attribute. `simp` can prove it.
theorem image_subset {α β} (e : α ≃ β) (s t : Set α) : e '' s ⊆ e '' t ↔ s ⊆ t :=
image_subset_image_iff e.injective
#align equiv.image_subset Equiv.image_subset
@[simp]
theorem image_eq_iff_eq {α β} (e : α ≃ β) (s t : Set α) : e '' s = e '' t ↔ s = t :=
image_eq_image e.injective
#align equiv.image_eq_iff_eq Equiv.image_eq_iff_eq
theorem preimage_eq_iff_eq_image {α β} (e : α ≃ β) (s t) : e ⁻¹' s = t ↔ s = e '' t :=
Set.preimage_eq_iff_eq_image e.bijective
#align equiv.preimage_eq_iff_eq_image Equiv.preimage_eq_iff_eq_image
theorem eq_preimage_iff_image_eq {α β} (e : α ≃ β) (s t) : s = e ⁻¹' t ↔ e '' s = t :=
Set.eq_preimage_iff_image_eq e.bijective
#align equiv.eq_preimage_iff_image_eq Equiv.eq_preimage_iff_image_eq
lemma setOf_apply_symm_eq_image_setOf {α β} (e : α ≃ β) (p : α → Prop) :
{b | p (e.symm b)} = e '' {a | p a} := by
rw [Equiv.image_eq_preimage, preimage_setOf_eq]
@[simp]
theorem prod_assoc_preimage {α β γ} {s : Set α} {t : Set β} {u : Set γ} :
Equiv.prodAssoc α β γ ⁻¹' s ×ˢ t ×ˢ u = (s ×ˢ t) ×ˢ u := by
ext
simp [and_assoc]
#align equiv.prod_assoc_preimage Equiv.prod_assoc_preimage
@[simp]
theorem prod_assoc_symm_preimage {α β γ} {s : Set α} {t : Set β} {u : Set γ} :
(Equiv.prodAssoc α β γ).symm ⁻¹' (s ×ˢ t) ×ˢ u = s ×ˢ t ×ˢ u := by
ext
simp [and_assoc]
#align equiv.prod_assoc_symm_preimage Equiv.prod_assoc_symm_preimage
-- `@[simp]` doesn't like these lemmas, as it uses `Set.image_congr'` to turn `Equiv.prodAssoc`
-- into a lambda expression and then unfold it.
theorem prod_assoc_image {α β γ} {s : Set α} {t : Set β} {u : Set γ} :
Equiv.prodAssoc α β γ '' (s ×ˢ t) ×ˢ u = s ×ˢ t ×ˢ u := by
simpa only [Equiv.image_eq_preimage] using prod_assoc_symm_preimage
#align equiv.prod_assoc_image Equiv.prod_assoc_image
theorem prod_assoc_symm_image {α β γ} {s : Set α} {t : Set β} {u : Set γ} :
(Equiv.prodAssoc α β γ).symm '' s ×ˢ t ×ˢ u = (s ×ˢ t) ×ˢ u := by
simpa only [Equiv.image_eq_preimage] using prod_assoc_preimage
#align equiv.prod_assoc_symm_image Equiv.prod_assoc_symm_image
/-- A set `s` in `α × β` is equivalent to the sigma-type `Σ x, {y | (x, y) ∈ s}`. -/
def setProdEquivSigma {α β : Type*} (s : Set (α × β)) :
s ≃ Σx : α, { y : β | (x, y) ∈ s } where
toFun x := ⟨x.1.1, x.1.2, by simp⟩
invFun x := ⟨(x.1, x.2.1), x.2.2⟩
left_inv := fun ⟨⟨x, y⟩, h⟩ => rfl
right_inv := fun ⟨x, y, h⟩ => rfl
#align equiv.set_prod_equiv_sigma Equiv.setProdEquivSigma
/-- The subtypes corresponding to equal sets are equivalent. -/
@[simps! apply]
def setCongr {α : Type*} {s t : Set α} (h : s = t) : s ≃ t :=
subtypeEquivProp h
#align equiv.set_congr Equiv.setCongr
#align equiv.set_congr_apply Equiv.setCongr_apply
-- We could construct this using `Equiv.Set.image e s e.injective`,
-- but this definition provides an explicit inverse.
/-- A set is equivalent to its image under an equivalence.
-/
@[simps]
def image {α β : Type*} (e : α ≃ β) (s : Set α) :
s ≃ e '' s where
toFun x := ⟨e x.1, by simp⟩
invFun y :=
⟨e.symm y.1, by
rcases y with ⟨-, ⟨a, ⟨m, rfl⟩⟩⟩
simpa using m⟩
left_inv x := by simp
right_inv y := by simp
#align equiv.image Equiv.image
#align equiv.image_symm_apply_coe Equiv.image_symm_apply_coe
#align equiv.image_apply_coe Equiv.image_apply_coe
namespace Set
-- Porting note: Removed attribute @[simps apply symm_apply]
/-- `univ α` is equivalent to `α`. -/
protected def univ (α) : @univ α ≃ α :=
⟨Subtype.val, fun a => ⟨a, trivial⟩, fun ⟨_, _⟩ => rfl, fun _ => rfl⟩
#align equiv.set.univ Equiv.Set.univ
/-- An empty set is equivalent to the `Empty` type. -/
protected def empty (α) : (∅ : Set α) ≃ Empty :=
equivEmpty _
#align equiv.set.empty Equiv.Set.empty
/-- An empty set is equivalent to a `PEmpty` type. -/
protected def pempty (α) : (∅ : Set α) ≃ PEmpty :=
equivPEmpty _
#align equiv.set.pempty Equiv.Set.pempty
/-- If sets `s` and `t` are separated by a decidable predicate, then `s ∪ t` is equivalent to
`s ⊕ t`. -/
protected def union' {α} {s t : Set α} (p : α → Prop) [DecidablePred p] (hs : ∀ x ∈ s, p x)
(ht : ∀ x ∈ t, ¬p x) : (s ∪ t : Set α) ≃ s ⊕ t where
toFun x :=
if hp : p x then Sum.inl ⟨_, x.2.resolve_right fun xt => ht _ xt hp⟩
else Sum.inr ⟨_, x.2.resolve_left fun xs => hp (hs _ xs)⟩
invFun o :=
match o with
| Sum.inl x => ⟨x, Or.inl x.2⟩
| Sum.inr x => ⟨x, Or.inr x.2⟩
left_inv := fun ⟨x, h'⟩ => by by_cases h : p x <;> simp [h]
right_inv o := by
rcases o with (⟨x, h⟩ | ⟨x, h⟩) <;> [simp [hs _ h]; simp [ht _ h]]
#align equiv.set.union' Equiv.Set.union'
/-- If sets `s` and `t` are disjoint, then `s ∪ t` is equivalent to `s ⊕ t`. -/
protected def union {α} {s t : Set α} [DecidablePred fun x => x ∈ s] (H : s ∩ t ⊆ ∅) :
(s ∪ t : Set α) ≃ s ⊕ t :=
Set.union' (fun x => x ∈ s) (fun _ => id) fun _ xt xs => H ⟨xs, xt⟩
#align equiv.set.union Equiv.Set.union
theorem union_apply_left {α} {s t : Set α} [DecidablePred fun x => x ∈ s] (H : s ∩ t ⊆ ∅)
{a : (s ∪ t : Set α)} (ha : ↑a ∈ s) : Equiv.Set.union H a = Sum.inl ⟨a, ha⟩ :=
dif_pos ha
#align equiv.set.union_apply_left Equiv.Set.union_apply_left
theorem union_apply_right {α} {s t : Set α} [DecidablePred fun x => x ∈ s] (H : s ∩ t ⊆ ∅)
{a : (s ∪ t : Set α)} (ha : ↑a ∈ t) : Equiv.Set.union H a = Sum.inr ⟨a, ha⟩ :=
dif_neg fun h => H ⟨h, ha⟩
#align equiv.set.union_apply_right Equiv.Set.union_apply_right
@[simp]
theorem union_symm_apply_left {α} {s t : Set α} [DecidablePred fun x => x ∈ s] (H : s ∩ t ⊆ ∅)
(a : s) : (Equiv.Set.union H).symm (Sum.inl a) = ⟨a, by simp⟩ :=
rfl
#align equiv.set.union_symm_apply_left Equiv.Set.union_symm_apply_left
@[simp]
theorem union_symm_apply_right {α} {s t : Set α} [DecidablePred fun x => x ∈ s] (H : s ∩ t ⊆ ∅)
(a : t) : (Equiv.Set.union H).symm (Sum.inr a) = ⟨a, by simp⟩ :=
rfl
#align equiv.set.union_symm_apply_right Equiv.Set.union_symm_apply_right
/-- A singleton set is equivalent to a `PUnit` type. -/
protected def singleton {α} (a : α) : ({a} : Set α) ≃ PUnit.{u} :=
⟨fun _ => PUnit.unit, fun _ => ⟨a, mem_singleton _⟩, fun ⟨x, h⟩ => by
simp? at h says simp only [mem_singleton_iff] at h
subst x
rfl, fun ⟨⟩ => rfl⟩
#align equiv.set.singleton Equiv.Set.singleton
/-- Equal sets are equivalent.
TODO: this is the same as `Equiv.setCongr`! -/
@[simps! apply symm_apply]
protected def ofEq {α : Type u} {s t : Set α} (h : s = t) : s ≃ t :=
Equiv.setCongr h
#align equiv.set.of_eq Equiv.Set.ofEq
/-- If `a ∉ s`, then `insert a s` is equivalent to `s ⊕ PUnit`. -/
protected def insert {α} {s : Set.{u} α} [DecidablePred (· ∈ s)] {a : α} (H : a ∉ s) :
(insert a s : Set α) ≃ Sum s PUnit.{u + 1} :=
calc
(insert a s : Set α) ≃ ↥(s ∪ {a}) := Equiv.Set.ofEq (by simp)
_ ≃ Sum s ({a} : Set α) := Equiv.Set.union fun x ⟨hx, _⟩ => by simp_all
_ ≃ Sum s PUnit.{u + 1} := sumCongr (Equiv.refl _) (Equiv.Set.singleton _)
#align equiv.set.insert Equiv.Set.insert
@[simp]
theorem insert_symm_apply_inl {α} {s : Set.{u} α} [DecidablePred (· ∈ s)] {a : α} (H : a ∉ s)
(b : s) : (Equiv.Set.insert H).symm (Sum.inl b) = ⟨b, Or.inr b.2⟩ :=
rfl
#align equiv.set.insert_symm_apply_inl Equiv.Set.insert_symm_apply_inl
@[simp]
theorem insert_symm_apply_inr {α} {s : Set.{u} α} [DecidablePred (· ∈ s)] {a : α} (H : a ∉ s)
(b : PUnit.{u + 1}) : (Equiv.Set.insert H).symm (Sum.inr b) = ⟨a, Or.inl rfl⟩ :=
rfl
#align equiv.set.insert_symm_apply_inr Equiv.Set.insert_symm_apply_inr
@[simp]
theorem insert_apply_left {α} {s : Set.{u} α} [DecidablePred (· ∈ s)] {a : α} (H : a ∉ s) :
Equiv.Set.insert H ⟨a, Or.inl rfl⟩ = Sum.inr PUnit.unit :=
(Equiv.Set.insert H).apply_eq_iff_eq_symm_apply.2 rfl
#align equiv.set.insert_apply_left Equiv.Set.insert_apply_left
@[simp]
theorem insert_apply_right {α} {s : Set.{u} α} [DecidablePred (· ∈ s)] {a : α} (H : a ∉ s) (b : s) :
Equiv.Set.insert H ⟨b, Or.inr b.2⟩ = Sum.inl b :=
(Equiv.Set.insert H).apply_eq_iff_eq_symm_apply.2 rfl
#align equiv.set.insert_apply_right Equiv.Set.insert_apply_right
/-- If `s : Set α` is a set with decidable membership, then `s ⊕ sᶜ` is equivalent to `α`. -/
protected def sumCompl {α} (s : Set α) [DecidablePred (· ∈ s)] : Sum s (sᶜ : Set α) ≃ α :=
calc
Sum s (sᶜ : Set α) ≃ ↥(s ∪ sᶜ) := (Equiv.Set.union (by simp [Set.ext_iff])).symm
_ ≃ @univ α := Equiv.Set.ofEq (by simp)
_ ≃ α := Equiv.Set.univ _
#align equiv.set.sum_compl Equiv.Set.sumCompl
@[simp]
theorem sumCompl_apply_inl {α : Type u} (s : Set α) [DecidablePred (· ∈ s)] (x : s) :
Equiv.Set.sumCompl s (Sum.inl x) = x :=
rfl
#align equiv.set.sum_compl_apply_inl Equiv.Set.sumCompl_apply_inl
@[simp]
theorem sumCompl_apply_inr {α : Type u} (s : Set α) [DecidablePred (· ∈ s)] (x : (sᶜ : Set α)) :
Equiv.Set.sumCompl s (Sum.inr x) = x :=
rfl
#align equiv.set.sum_compl_apply_inr Equiv.Set.sumCompl_apply_inr
theorem sumCompl_symm_apply_of_mem {α : Type u} {s : Set α} [DecidablePred (· ∈ s)] {x : α}
(hx : x ∈ s) : (Equiv.Set.sumCompl s).symm x = Sum.inl ⟨x, hx⟩ := by
have : ((⟨x, Or.inl hx⟩ : (s ∪ sᶜ : Set α)) : α) ∈ s := hx
rw [Equiv.Set.sumCompl]
simpa using Set.union_apply_left (by simp) this
#align equiv.set.sum_compl_symm_apply_of_mem Equiv.Set.sumCompl_symm_apply_of_mem
theorem sumCompl_symm_apply_of_not_mem {α : Type u} {s : Set α} [DecidablePred (· ∈ s)] {x : α}
(hx : x ∉ s) : (Equiv.Set.sumCompl s).symm x = Sum.inr ⟨x, hx⟩ := by
have : ((⟨x, Or.inr hx⟩ : (s ∪ sᶜ : Set α)) : α) ∈ sᶜ := hx
rw [Equiv.Set.sumCompl]
simpa using Set.union_apply_right (by simp) this
#align equiv.set.sum_compl_symm_apply_of_not_mem Equiv.Set.sumCompl_symm_apply_of_not_mem
@[simp]
theorem sumCompl_symm_apply {α : Type*} {s : Set α} [DecidablePred (· ∈ s)] {x : s} :
(Equiv.Set.sumCompl s).symm x = Sum.inl x := by
cases' x with x hx; exact Set.sumCompl_symm_apply_of_mem hx
#align equiv.set.sum_compl_symm_apply Equiv.Set.sumCompl_symm_apply
@[simp]
theorem sumCompl_symm_apply_compl {α : Type*} {s : Set α} [DecidablePred (· ∈ s)]
{x : (sᶜ : Set α)} : (Equiv.Set.sumCompl s).symm x = Sum.inr x := by
cases' x with x hx; exact Set.sumCompl_symm_apply_of_not_mem hx
#align equiv.set.sum_compl_symm_apply_compl Equiv.Set.sumCompl_symm_apply_compl
/-- `sumDiffSubset s t` is the natural equivalence between
`s ⊕ (t \ s)` and `t`, where `s` and `t` are two sets. -/
protected def sumDiffSubset {α} {s t : Set α} (h : s ⊆ t) [DecidablePred (· ∈ s)] :
Sum s (t \ s : Set α) ≃ t :=
calc
Sum s (t \ s : Set α) ≃ (s ∪ t \ s : Set α) :=
(Equiv.Set.union (by simp [inter_diff_self])).symm
_ ≃ t := Equiv.Set.ofEq (by simp [union_diff_self, union_eq_self_of_subset_left h])
#align equiv.set.sum_diff_subset Equiv.Set.sumDiffSubset
@[simp]
theorem sumDiffSubset_apply_inl {α} {s t : Set α} (h : s ⊆ t) [DecidablePred (· ∈ s)] (x : s) :
Equiv.Set.sumDiffSubset h (Sum.inl x) = inclusion h x :=
rfl
#align equiv.set.sum_diff_subset_apply_inl Equiv.Set.sumDiffSubset_apply_inl
@[simp]
theorem sumDiffSubset_apply_inr {α} {s t : Set α} (h : s ⊆ t) [DecidablePred (· ∈ s)]
(x : (t \ s : Set α)) : Equiv.Set.sumDiffSubset h (Sum.inr x) = inclusion diff_subset x :=
rfl
#align equiv.set.sum_diff_subset_apply_inr Equiv.Set.sumDiffSubset_apply_inr
theorem sumDiffSubset_symm_apply_of_mem {α} {s t : Set α} (h : s ⊆ t) [DecidablePred (· ∈ s)]
{x : t} (hx : x.1 ∈ s) : (Equiv.Set.sumDiffSubset h).symm x = Sum.inl ⟨x, hx⟩ := by
apply (Equiv.Set.sumDiffSubset h).injective
simp only [apply_symm_apply, sumDiffSubset_apply_inl]
exact Subtype.eq rfl
#align equiv.set.sum_diff_subset_symm_apply_of_mem Equiv.Set.sumDiffSubset_symm_apply_of_mem
theorem sumDiffSubset_symm_apply_of_not_mem {α} {s t : Set α} (h : s ⊆ t) [DecidablePred (· ∈ s)]
{x : t} (hx : x.1 ∉ s) : (Equiv.Set.sumDiffSubset h).symm x = Sum.inr ⟨x, ⟨x.2, hx⟩⟩ := by
apply (Equiv.Set.sumDiffSubset h).injective
simp only [apply_symm_apply, sumDiffSubset_apply_inr]
exact Subtype.eq rfl
#align equiv.set.sum_diff_subset_symm_apply_of_not_mem Equiv.Set.sumDiffSubset_symm_apply_of_not_mem
/-- If `s` is a set with decidable membership, then the sum of `s ∪ t` and `s ∩ t` is equivalent
to `s ⊕ t`. -/
protected def unionSumInter {α : Type u} (s t : Set α) [DecidablePred (· ∈ s)] :
Sum (s ∪ t : Set α) (s ∩ t : Set α) ≃ Sum s t :=
calc
Sum (s ∪ t : Set α) (s ∩ t : Set α)
≃ Sum (s ∪ t \ s : Set α) (s ∩ t : Set α) := by rw [union_diff_self]
_ ≃ Sum (Sum s (t \ s : Set α)) (s ∩ t : Set α) :=
sumCongr (Set.union <| subset_empty_iff.2 (inter_diff_self _ _)) (Equiv.refl _)
_ ≃ Sum s (Sum (t \ s : Set α) (s ∩ t : Set α)) := sumAssoc _ _ _
_ ≃ Sum s (t \ s ∪ s ∩ t : Set α) :=
sumCongr (Equiv.refl _)
(by
refine (Set.union' (· ∉ s) ?_ ?_).symm
exacts [fun x hx => hx.2, fun x hx => not_not_intro hx.1])
_ ≃ Sum s t := by
{ rw [(_ : t \ s ∪ s ∩ t = t)]
rw [union_comm, inter_comm, inter_union_diff] }
#align equiv.set.union_sum_inter Equiv.Set.unionSumInter
/-- Given an equivalence `e₀` between sets `s : Set α` and `t : Set β`, the set of equivalences
`e : α ≃ β` such that `e ↑x = ↑(e₀ x)` for each `x : s` is equivalent to the set of equivalences
between `sᶜ` and `tᶜ`. -/
protected def compl {α : Type u} {β : Type v} {s : Set α} {t : Set β} [DecidablePred (· ∈ s)]
[DecidablePred (· ∈ t)] (e₀ : s ≃ t) :
{ e : α ≃ β // ∀ x : s, e x = e₀ x } ≃ ((sᶜ : Set α) ≃ (tᶜ : Set β)) where
toFun e :=
subtypeEquiv e fun a =>
not_congr <|
Iff.symm <|
MapsTo.mem_iff (mapsTo_iff_exists_map_subtype.2 ⟨e₀, e.2⟩)
(SurjOn.mapsTo_compl
(surjOn_iff_exists_map_subtype.2 ⟨t, e₀, Subset.refl t, e₀.surjective, e.2⟩)
e.1.injective)
invFun e₁ :=
Subtype.mk
(calc
α ≃ Sum s (sᶜ : Set α) := (Set.sumCompl s).symm
_ ≃ Sum t (tᶜ : Set β) := e₀.sumCongr e₁
_ ≃ β := Set.sumCompl t
)
fun x => by
simp only [Sum.map_inl, trans_apply, sumCongr_apply, Set.sumCompl_apply_inl,
Set.sumCompl_symm_apply, Trans.trans]
left_inv e := by
ext x
by_cases hx : x ∈ s
· simp only [Set.sumCompl_symm_apply_of_mem hx, ← e.prop ⟨x, hx⟩, Sum.map_inl, sumCongr_apply,
trans_apply, Subtype.coe_mk, Set.sumCompl_apply_inl, Trans.trans]
· simp only [Set.sumCompl_symm_apply_of_not_mem hx, Sum.map_inr, subtypeEquiv_apply,
Set.sumCompl_apply_inr, trans_apply, sumCongr_apply, Subtype.coe_mk, Trans.trans]
right_inv e :=
Equiv.ext fun x => by
simp only [Sum.map_inr, subtypeEquiv_apply, Set.sumCompl_apply_inr, Function.comp_apply,
sumCongr_apply, Equiv.coe_trans, Subtype.coe_eta, Subtype.coe_mk, Trans.trans,
Set.sumCompl_symm_apply_compl]
#align equiv.set.compl Equiv.Set.compl
/-- The set product of two sets is equivalent to the type product of their coercions to types. -/
protected def prod {α β} (s : Set α) (t : Set β) : ↥(s ×ˢ t) ≃ s × t :=
@subtypeProdEquivProd α β s t
#align equiv.set.prod Equiv.Set.prod
/-- The set `Set.pi Set.univ s` is equivalent to `Π a, s a`. -/
@[simps]
protected def univPi {α : Type*} {β : α → Type*} (s : ∀ a, Set (β a)) :
pi univ s ≃ ∀ a, s a where
toFun f a := ⟨(f : ∀ a, β a) a, f.2 a (mem_univ a)⟩
invFun f := ⟨fun a => f a, fun a _ => (f a).2⟩
left_inv := fun ⟨f, hf⟩ => by
ext a
rfl
right_inv f := by
ext a
rfl
#align equiv.set.univ_pi Equiv.Set.univPi
#align equiv.set.univ_pi_symm_apply_coe Equiv.Set.univPi_symm_apply_coe
#align equiv.set.univ_pi_apply_coe Equiv.Set.univPi_apply_coe
/-- If a function `f` is injective on a set `s`, then `s` is equivalent to `f '' s`. -/
protected noncomputable def imageOfInjOn {α β} (f : α → β) (s : Set α) (H : InjOn f s) :
s ≃ f '' s :=
⟨fun p => ⟨f p, mem_image_of_mem f p.2⟩, fun p =>
⟨Classical.choose p.2, (Classical.choose_spec p.2).1⟩, fun ⟨_, h⟩ =>
Subtype.eq
(H (Classical.choose_spec (mem_image_of_mem f h)).1 h
(Classical.choose_spec (mem_image_of_mem f h)).2),
fun ⟨_, h⟩ => Subtype.eq (Classical.choose_spec h).2⟩
#align equiv.set.image_of_inj_on Equiv.Set.imageOfInjOn
/-- If `f` is an injective function, then `s` is equivalent to `f '' s`. -/
@[simps! apply]
protected noncomputable def image {α β} (f : α → β) (s : Set α) (H : Injective f) : s ≃ f '' s :=
Equiv.Set.imageOfInjOn f s H.injOn
#align equiv.set.image Equiv.Set.image
#align equiv.set.image_apply Equiv.Set.image_apply
@[simp]
protected theorem image_symm_apply {α β} (f : α → β) (s : Set α) (H : Injective f) (x : α)
(h : f x ∈ f '' s) : (Set.image f s H).symm ⟨f x, h⟩ = ⟨x, H.mem_set_image.1 h⟩ :=
(Equiv.symm_apply_eq _).2 rfl
#align equiv.set.image_symm_apply Equiv.Set.image_symm_apply
theorem image_symm_preimage {α β} {f : α → β} (hf : Injective f) (u s : Set α) :
(fun x => (Set.image f s hf).symm x : f '' s → α) ⁻¹' u = Subtype.val ⁻¹' (f '' u) := by
ext ⟨b, a, has, rfl⟩
simp [hf.eq_iff]
#align equiv.set.image_symm_preimage Equiv.Set.image_symm_preimage
/-- If `α` is equivalent to `β`, then `Set α` is equivalent to `Set β`. -/
@[simps]
protected def congr {α β : Type*} (e : α ≃ β) : Set α ≃ Set β :=
⟨fun s => e '' s, fun t => e.symm '' t, symm_image_image e, symm_image_image e.symm⟩
#align equiv.set.congr Equiv.Set.congr
#align equiv.set.congr_apply Equiv.Set.congr_apply
#align equiv.set.congr_symm_apply Equiv.Set.congr_symm_apply
/-- The set `{x ∈ s | t x}` is equivalent to the set of `x : s` such that `t x`. -/
protected def sep {α : Type u} (s : Set α) (t : α → Prop) :
({ x ∈ s | t x } : Set α) ≃ { x : s | t x } :=
(Equiv.subtypeSubtypeEquivSubtypeInter s t).symm
#align equiv.set.sep Equiv.Set.sep
/-- The set `𝒫 S := {x | x ⊆ S}` is equivalent to the type `Set S`. -/
protected def powerset {α} (S : Set α) :
𝒫 S ≃ Set S where
toFun := fun x : 𝒫 S => Subtype.val ⁻¹' (x : Set α)
invFun := fun x : Set S => ⟨Subtype.val '' x, by rintro _ ⟨a : S, _, rfl⟩; exact a.2⟩
left_inv x := by ext y;exact ⟨fun ⟨⟨_, _⟩, h, rfl⟩ => h, fun h => ⟨⟨_, x.2 h⟩, h, rfl⟩⟩
right_inv x := by ext; simp
#align equiv.set.powerset Equiv.Set.powerset
/-- If `s` is a set in `range f`,
then its image under `rangeSplitting f` is in bijection (via `f`) with `s`.
-/
@[simps]
noncomputable def rangeSplittingImageEquiv {α β : Type*} (f : α → β) (s : Set (range f)) :
rangeSplitting f '' s ≃ s where
toFun x :=
⟨⟨f x, by simp⟩, by
rcases x with ⟨x, ⟨y, ⟨m, rfl⟩⟩⟩
simpa [apply_rangeSplitting f] using m⟩
invFun x := ⟨rangeSplitting f x, ⟨x, ⟨x.2, rfl⟩⟩⟩
left_inv x := by
rcases x with ⟨x, ⟨y, ⟨m, rfl⟩⟩⟩
simp [apply_rangeSplitting f]
right_inv x := by simp [apply_rangeSplitting f]
#align equiv.set.range_splitting_image_equiv Equiv.Set.rangeSplittingImageEquiv
#align equiv.set.range_splitting_image_equiv_symm_apply_coe Equiv.Set.rangeSplittingImageEquiv_symm_apply_coe
#align equiv.set.range_splitting_image_equiv_apply_coe_coe Equiv.Set.rangeSplittingImageEquiv_apply_coe_coe
/-- Equivalence between the range of `Sum.inl : α → α ⊕ β` and `α`. -/
@[simps symm_apply_coe]
def rangeInl (α β : Type*) : Set.range (Sum.inl : α → α ⊕ β) ≃ α where
toFun
| ⟨.inl x, _⟩ => x
| ⟨.inr _, h⟩ => False.elim <| by rcases h with ⟨x, h'⟩; cases h'
invFun x := ⟨.inl x, mem_range_self _⟩
left_inv := fun ⟨_, _, rfl⟩ => rfl
right_inv x := rfl
@[simp] lemma rangeInl_apply_inl {α : Type*} (β : Type*) (x : α) :
(rangeInl α β) ⟨.inl x, mem_range_self _⟩ = x :=
rfl
/-- Equivalence between the range of `Sum.inr : β → α ⊕ β` and `β`. -/
@[simps symm_apply_coe]
def rangeInr (α β : Type*) : Set.range (Sum.inr : β → α ⊕ β) ≃ β where
toFun
| ⟨.inl _, h⟩ => False.elim <| by rcases h with ⟨x, h'⟩; cases h'
| ⟨.inr x, _⟩ => x
invFun x := ⟨.inr x, mem_range_self _⟩
left_inv := fun ⟨_, _, rfl⟩ => rfl
right_inv x := rfl
@[simp] lemma rangeInr_apply_inr (α : Type*) {β : Type*} (x : β) :
(rangeInr α β) ⟨.inr x, mem_range_self _⟩ = x :=
rfl
end Set
/-- If `f : α → β` has a left-inverse when `α` is nonempty, then `α` is computably equivalent to the
range of `f`.
While awkward, the `Nonempty α` hypothesis on `f_inv` and `hf` allows this to be used when `α` is
empty too. This hypothesis is absent on analogous definitions on stronger `Equiv`s like
`LinearEquiv.ofLeftInverse` and `RingEquiv.ofLeftInverse` as their typeclass assumptions
are already sufficient to ensure non-emptiness. -/
@[simps]
def ofLeftInverse {α β : Sort _} (f : α → β) (f_inv : Nonempty α → β → α)
(hf : ∀ h : Nonempty α, LeftInverse (f_inv h) f) :
α ≃ range f where
toFun a := ⟨f a, a, rfl⟩
invFun b := f_inv (nonempty_of_exists b.2) b
left_inv a := hf ⟨a⟩ a
right_inv := fun ⟨b, a, ha⟩ =>
Subtype.eq <| show f (f_inv ⟨a⟩ b) = b from Eq.trans (congr_arg f <| ha ▸ hf _ a) ha
#align equiv.of_left_inverse Equiv.ofLeftInverse
#align equiv.of_left_inverse_apply_coe Equiv.ofLeftInverse_apply_coe
#align equiv.of_left_inverse_symm_apply Equiv.ofLeftInverse_symm_apply
/-- If `f : α → β` has a left-inverse, then `α` is computably equivalent to the range of `f`.
Note that if `α` is empty, no such `f_inv` exists and so this definition can't be used, unlike
the stronger but less convenient `ofLeftInverse`. -/
abbrev ofLeftInverse' {α β : Sort _} (f : α → β) (f_inv : β → α) (hf : LeftInverse f_inv f) :
α ≃ range f :=
ofLeftInverse f (fun _ => f_inv) fun _ => hf
#align equiv.of_left_inverse' Equiv.ofLeftInverse'
/-- If `f : α → β` is an injective function, then domain `α` is equivalent to the range of `f`. -/
@[simps! apply]
noncomputable def ofInjective {α β} (f : α → β) (hf : Injective f) : α ≃ range f :=
Equiv.ofLeftInverse f (fun _ => Function.invFun f) fun _ => Function.leftInverse_invFun hf
#align equiv.of_injective Equiv.ofInjective
#align equiv.of_injective_apply Equiv.ofInjective_apply
theorem apply_ofInjective_symm {α β} {f : α → β} (hf : Injective f) (b : range f) :
f ((ofInjective f hf).symm b) = b :=
Subtype.ext_iff.1 <| (ofInjective f hf).apply_symm_apply b
#align equiv.apply_of_injective_symm Equiv.apply_ofInjective_symm
@[simp]
theorem ofInjective_symm_apply {α β} {f : α → β} (hf : Injective f) (a : α) :
(ofInjective f hf).symm ⟨f a, ⟨a, rfl⟩⟩ = a := by
apply (ofInjective f hf).injective
simp [apply_ofInjective_symm hf]
#align equiv.of_injective_symm_apply Equiv.ofInjective_symm_apply
theorem coe_ofInjective_symm {α β} {f : α → β} (hf : Injective f) :
((ofInjective f hf).symm : range f → α) = rangeSplitting f := by
ext ⟨y, x, rfl⟩
apply hf
simp [apply_rangeSplitting f]
#align equiv.coe_of_injective_symm Equiv.coe_ofInjective_symm
@[simp]
theorem self_comp_ofInjective_symm {α β} {f : α → β} (hf : Injective f) :
f ∘ (ofInjective f hf).symm = Subtype.val :=
funext fun x => apply_ofInjective_symm hf x
#align equiv.self_comp_of_injective_symm Equiv.self_comp_ofInjective_symm
theorem ofLeftInverse_eq_ofInjective {α β : Type*} (f : α → β) (f_inv : Nonempty α → β → α)
(hf : ∀ h : Nonempty α, LeftInverse (f_inv h) f) :
ofLeftInverse f f_inv hf =
ofInjective f ((isEmpty_or_nonempty α).elim (fun h _ _ _ => Subsingleton.elim _ _)
(fun h => (hf h).injective)) := by
ext
simp
#align equiv.of_left_inverse_eq_of_injective Equiv.ofLeftInverse_eq_ofInjective
theorem ofLeftInverse'_eq_ofInjective {α β : Type*} (f : α → β) (f_inv : β → α)
(hf : LeftInverse f_inv f) : ofLeftInverse' f f_inv hf = ofInjective f hf.injective := by
ext
simp
#align equiv.of_left_inverse'_eq_of_injective Equiv.ofLeftInverse'_eq_ofInjective
protected theorem set_forall_iff {α β} (e : α ≃ β) {p : Set α → Prop} :
(∀ a, p a) ↔ ∀ a, p (e ⁻¹' a) :=
e.injective.preimage_surjective.forall
#align equiv.set_forall_iff Equiv.set_forall_iff
theorem preimage_piEquivPiSubtypeProd_symm_pi {α : Type*} {β : α → Type*} (p : α → Prop)
[DecidablePred p] (s : ∀ i, Set (β i)) :
(piEquivPiSubtypeProd p β).symm ⁻¹' pi univ s =
(pi univ fun i : { i // p i } => s i) ×ˢ pi univ fun i : { i // ¬p i } => s i := by
ext ⟨f, g⟩
simp only [mem_preimage, mem_univ_pi, prod_mk_mem_set_prod_eq, Subtype.forall, ← forall_and]
refine forall_congr' fun i => ?_
dsimp only [Subtype.coe_mk]
by_cases hi : p i <;> simp [hi]
#align equiv.preimage_pi_equiv_pi_subtype_prod_symm_pi Equiv.preimage_piEquivPiSubtypeProd_symm_pi
-- See also `Equiv.sigmaFiberEquiv`.
/-- `sigmaPreimageEquiv f` for `f : α → β` is the natural equivalence between
the type of all preimages of points under `f` and the total space `α`. -/
@[simps!]
def sigmaPreimageEquiv {α β} (f : α → β) : (Σb, f ⁻¹' {b}) ≃ α :=
sigmaFiberEquiv f
#align equiv.sigma_preimage_equiv Equiv.sigmaPreimageEquiv
#align equiv.sigma_preimage_equiv_symm_apply_snd_coe Equiv.sigmaPreimageEquiv_symm_apply_snd_coe
#align equiv.sigma_preimage_equiv_apply Equiv.sigmaPreimageEquiv_apply
#align equiv.sigma_preimage_equiv_symm_apply_fst Equiv.sigmaPreimageEquiv_symm_apply_fst
-- See also `Equiv.ofFiberEquiv`.
/-- A family of equivalences between preimages of points gives an equivalence between domains. -/
@[simps!]
def ofPreimageEquiv {α β γ} {f : α → γ} {g : β → γ} (e : ∀ c, f ⁻¹' {c} ≃ g ⁻¹' {c}) : α ≃ β :=
Equiv.ofFiberEquiv e
#align equiv.of_preimage_equiv Equiv.ofPreimageEquiv
#align equiv.of_preimage_equiv_apply Equiv.ofPreimageEquiv_apply
#align equiv.of_preimage_equiv_symm_apply Equiv.ofPreimageEquiv_symm_apply
theorem ofPreimageEquiv_map {α β γ} {f : α → γ} {g : β → γ} (e : ∀ c, f ⁻¹' {c} ≃ g ⁻¹' {c})
(a : α) : g (ofPreimageEquiv e a) = f a :=
Equiv.ofFiberEquiv_map e a
#align equiv.of_preimage_equiv_map Equiv.ofPreimageEquiv_map
end Equiv
/-- If a function is a bijection between two sets `s` and `t`, then it induces an
equivalence between the types `↥s` and `↥t`. -/
noncomputable def Set.BijOn.equiv {α : Type*} {β : Type*} {s : Set α} {t : Set β} (f : α → β)
(h : BijOn f s t) : s ≃ t :=
Equiv.ofBijective _ h.bijective
#align set.bij_on.equiv Set.BijOn.equiv
/-- The composition of an updated function with an equiv on a subtype can be expressed as an
updated function. -/
-- Porting note: replace `s : Set α` and `: s` with `p : α → Prop` and `: Subtype p`, since the
-- former now unfolds syntactically to a less general case of the latter.
theorem dite_comp_equiv_update {α : Type*} {β : Sort*} {γ : Sort*} {p : α → Prop}
(e : β ≃ Subtype p)
(v : β → γ) (w : α → γ) (j : β) (x : γ) [DecidableEq β] [DecidableEq α]
[∀ j, Decidable (p j)] :
(fun i : α => if h : p i then (Function.update v j x) (e.symm ⟨i, h⟩) else w i) =
Function.update (fun i : α => if h : p i then v (e.symm ⟨i, h⟩) else w i) (e j) x := by
ext i
by_cases h : p i
· rw [dif_pos h, Function.update_apply_equiv_apply, Equiv.symm_symm,
Function.update_apply, Function.update_apply, dif_pos h]
have h_coe : (⟨i, h⟩ : Subtype p) = e j ↔ i = e j :=
Subtype.ext_iff.trans (by rw [Subtype.coe_mk])
simp [h_coe]
· have : i ≠ e j := by
contrapose! h
have : p (e j : α) := (e j).2
rwa [← h] at this
simp [h, this]
#align dite_comp_equiv_update dite_comp_equiv_updateₓ
section Swap
variable {α : Type*} [DecidableEq α] {a b : α} {s : Set α}
theorem Equiv.swap_bijOn_self (hs : a ∈ s ↔ b ∈ s) : BijOn (Equiv.swap a b) s s := by
refine ⟨fun x hx ↦ ?_, (Equiv.injective _).injOn, fun x hx ↦ ?_⟩
· obtain (rfl | hxa) := eq_or_ne x a; rwa [swap_apply_left, ← hs]
obtain (rfl | hxb) := eq_or_ne x b; rwa [swap_apply_right, hs]
rwa [swap_apply_of_ne_of_ne hxa hxb]
obtain (rfl | hxa) := eq_or_ne x a; simp [hs.1 hx]
obtain (rfl | hxb) := eq_or_ne x b; simp [hs.2 hx]
exact ⟨x, hx, swap_apply_of_ne_of_ne hxa hxb⟩
| Mathlib/Logic/Equiv/Set.lean | 744 | 752 | theorem Equiv.swap_bijOn_exchange (ha : a ∈ s) (hb : b ∉ s) :
BijOn (Equiv.swap a b) s (insert b (s \ {a})) := by |
refine ⟨fun x hx ↦ ?_, (Equiv.injective _).injOn, fun x hx ↦ ?_⟩
· obtain (rfl | hxa) := eq_or_ne x a; simp [swap_apply_left]
rw [swap_apply_of_ne_of_ne hxa (by rintro rfl; contradiction)]
exact .inr ⟨hx, hxa⟩
obtain (rfl | hxb) := eq_or_ne x b; exact ⟨a, ha, by simp⟩
simp only [mem_insert_iff, mem_diff, mem_singleton_iff, or_iff_right hxb] at hx
exact ⟨x, hx.1, swap_apply_of_ne_of_ne hx.2 hxb⟩
|
/-
Copyright (c) 2017 Robert Y. Lewis. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Robert Y. Lewis, Keeley Hoek
-/
import Mathlib.Algebra.NeZero
import Mathlib.Data.Nat.Defs
import Mathlib.Logic.Embedding.Basic
import Mathlib.Logic.Equiv.Set
import Mathlib.Tactic.Common
#align_import data.fin.basic from "leanprover-community/mathlib"@"3a2b5524a138b5d0b818b858b516d4ac8a484b03"
/-!
# The finite type with `n` elements
`Fin n` is the type whose elements are natural numbers smaller than `n`.
This file expands on the development in the core library.
## Main definitions
### Induction principles
* `finZeroElim` : Elimination principle for the empty set `Fin 0`, generalizes `Fin.elim0`.
* `Fin.succRec` : Define `C n i` by induction on `i : Fin n` interpreted
as `(0 : Fin (n - i)).succ.succ…`. This function has two arguments: `H0 n` defines
`0`-th element `C (n+1) 0` of an `(n+1)`-tuple, and `Hs n i` defines `(i+1)`-st element
of `(n+1)`-tuple based on `n`, `i`, and `i`-th element of `n`-tuple.
* `Fin.succRecOn` : same as `Fin.succRec` but `i : Fin n` is the first argument;
* `Fin.induction` : Define `C i` by induction on `i : Fin (n + 1)`, separating into the
`Nat`-like base cases of `C 0` and `C (i.succ)`.
* `Fin.inductionOn` : same as `Fin.induction` but with `i : Fin (n + 1)` as the first argument.
* `Fin.cases` : define `f : Π i : Fin n.succ, C i` by separately handling the cases `i = 0` and
`i = Fin.succ j`, `j : Fin n`, defined using `Fin.induction`.
* `Fin.reverseInduction`: reverse induction on `i : Fin (n + 1)`; given `C (Fin.last n)` and
`∀ i : Fin n, C (Fin.succ i) → C (Fin.castSucc i)`, constructs all values `C i` by going down;
* `Fin.lastCases`: define `f : Π i, Fin (n + 1), C i` by separately handling the cases
`i = Fin.last n` and `i = Fin.castSucc j`, a special case of `Fin.reverseInduction`;
* `Fin.addCases`: define a function on `Fin (m + n)` by separately handling the cases
`Fin.castAdd n i` and `Fin.natAdd m i`;
* `Fin.succAboveCases`: given `i : Fin (n + 1)`, define a function on `Fin (n + 1)` by separately
handling the cases `j = i` and `j = Fin.succAbove i k`, same as `Fin.insertNth` but marked
as eliminator and works for `Sort*`. -- Porting note: this is in another file
### Embeddings and isomorphisms
* `Fin.valEmbedding` : coercion to natural numbers as an `Embedding`;
* `Fin.succEmb` : `Fin.succ` as an `Embedding`;
* `Fin.castLEEmb h` : `Fin.castLE` as an `Embedding`, embed `Fin n` into `Fin m`, `h : n ≤ m`;
* `finCongr` : `Fin.cast` as an `Equiv`, equivalence between `Fin n` and `Fin m` when `n = m`;
* `Fin.castAddEmb m` : `Fin.castAdd` as an `Embedding`, embed `Fin n` into `Fin (n+m)`;
* `Fin.castSuccEmb` : `Fin.castSucc` as an `Embedding`, embed `Fin n` into `Fin (n+1)`;
* `Fin.addNatEmb m i` : `Fin.addNat` as an `Embedding`, add `m` on `i` on the right,
generalizes `Fin.succ`;
* `Fin.natAddEmb n i` : `Fin.natAdd` as an `Embedding`, adds `n` on `i` on the left;
### Other casts
* `Fin.ofNat'`: given a positive number `n` (deduced from `[NeZero n]`), `Fin.ofNat' i` is
`i % n` interpreted as an element of `Fin n`;
* `Fin.divNat i` : divides `i : Fin (m * n)` by `n`;
* `Fin.modNat i` : takes the mod of `i : Fin (m * n)` by `n`;
### Misc definitions
* `Fin.revPerm : Equiv.Perm (Fin n)` : `Fin.rev` as an `Equiv.Perm`, the antitone involution given
by `i ↦ n-(i+1)`
-/
assert_not_exists Monoid
universe u v
open Fin Nat Function
/-- Elimination principle for the empty set `Fin 0`, dependent version. -/
def finZeroElim {α : Fin 0 → Sort*} (x : Fin 0) : α x :=
x.elim0
#align fin_zero_elim finZeroElim
namespace Fin
instance {n : ℕ} : CanLift ℕ (Fin n) Fin.val (· < n) where
prf k hk := ⟨⟨k, hk⟩, rfl⟩
/-- A dependent variant of `Fin.elim0`. -/
def rec0 {α : Fin 0 → Sort*} (i : Fin 0) : α i := absurd i.2 (Nat.not_lt_zero _)
#align fin.elim0' Fin.elim0
variable {n m : ℕ}
--variable {a b : Fin n} -- this *really* breaks stuff
#align fin.fin_to_nat Fin.coeToNat
theorem val_injective : Function.Injective (@Fin.val n) :=
@Fin.eq_of_val_eq n
#align fin.val_injective Fin.val_injective
/-- If you actually have an element of `Fin n`, then the `n` is always positive -/
lemma size_positive : Fin n → 0 < n := Fin.pos
lemma size_positive' [Nonempty (Fin n)] : 0 < n :=
‹Nonempty (Fin n)›.elim Fin.pos
protected theorem prop (a : Fin n) : a.val < n :=
a.2
#align fin.prop Fin.prop
#align fin.is_lt Fin.is_lt
#align fin.pos Fin.pos
#align fin.pos_iff_nonempty Fin.pos_iff_nonempty
section Order
variable {a b c : Fin n}
protected lemma lt_of_le_of_lt : a ≤ b → b < c → a < c := Nat.lt_of_le_of_lt
protected lemma lt_of_lt_of_le : a < b → b ≤ c → a < c := Nat.lt_of_lt_of_le
protected lemma le_rfl : a ≤ a := Nat.le_refl _
protected lemma lt_iff_le_and_ne : a < b ↔ a ≤ b ∧ a ≠ b := by
rw [← val_ne_iff]; exact Nat.lt_iff_le_and_ne
protected lemma lt_or_lt_of_ne (h : a ≠ b) : a < b ∨ b < a := Nat.lt_or_lt_of_ne $ val_ne_iff.2 h
protected lemma lt_or_le (a b : Fin n) : a < b ∨ b ≤ a := Nat.lt_or_ge _ _
protected lemma le_or_lt (a b : Fin n) : a ≤ b ∨ b < a := (b.lt_or_le a).symm
protected lemma le_of_eq (hab : a = b) : a ≤ b := Nat.le_of_eq $ congr_arg val hab
protected lemma ge_of_eq (hab : a = b) : b ≤ a := Fin.le_of_eq hab.symm
protected lemma eq_or_lt_of_le : a ≤ b → a = b ∨ a < b := by rw [ext_iff]; exact Nat.eq_or_lt_of_le
protected lemma lt_or_eq_of_le : a ≤ b → a < b ∨ a = b := by rw [ext_iff]; exact Nat.lt_or_eq_of_le
end Order
lemma lt_last_iff_ne_last {a : Fin (n + 1)} : a < last n ↔ a ≠ last n := by
simp [Fin.lt_iff_le_and_ne, le_last]
lemma ne_zero_of_lt {a b : Fin (n + 1)} (hab : a < b) : b ≠ 0 :=
Fin.ne_of_gt $ Fin.lt_of_le_of_lt a.zero_le hab
lemma ne_last_of_lt {a b : Fin (n + 1)} (hab : a < b) : a ≠ last n :=
Fin.ne_of_lt $ Fin.lt_of_lt_of_le hab b.le_last
/-- Equivalence between `Fin n` and `{ i // i < n }`. -/
@[simps apply symm_apply]
def equivSubtype : Fin n ≃ { i // i < n } where
toFun a := ⟨a.1, a.2⟩
invFun a := ⟨a.1, a.2⟩
left_inv := fun ⟨_, _⟩ => rfl
right_inv := fun ⟨_, _⟩ => rfl
#align fin.equiv_subtype Fin.equivSubtype
#align fin.equiv_subtype_symm_apply Fin.equivSubtype_symm_apply
#align fin.equiv_subtype_apply Fin.equivSubtype_apply
section coe
/-!
### coercions and constructions
-/
#align fin.eta Fin.eta
#align fin.ext Fin.ext
#align fin.ext_iff Fin.ext_iff
#align fin.coe_injective Fin.val_injective
theorem val_eq_val (a b : Fin n) : (a : ℕ) = b ↔ a = b :=
ext_iff.symm
#align fin.coe_eq_coe Fin.val_eq_val
@[deprecated ext_iff (since := "2024-02-20")]
theorem eq_iff_veq (a b : Fin n) : a = b ↔ a.1 = b.1 :=
ext_iff
#align fin.eq_iff_veq Fin.eq_iff_veq
theorem ne_iff_vne (a b : Fin n) : a ≠ b ↔ a.1 ≠ b.1 :=
ext_iff.not
#align fin.ne_iff_vne Fin.ne_iff_vne
-- Porting note: I'm not sure if this comment still applies.
-- built-in reduction doesn't always work
@[simp, nolint simpNF]
theorem mk_eq_mk {a h a' h'} : @mk n a h = @mk n a' h' ↔ a = a' :=
ext_iff
#align fin.mk_eq_mk Fin.mk_eq_mk
#align fin.mk.inj_iff Fin.mk.inj_iff
#align fin.mk_val Fin.val_mk
#align fin.eq_mk_iff_coe_eq Fin.eq_mk_iff_val_eq
#align fin.coe_mk Fin.val_mk
#align fin.mk_coe Fin.mk_val
-- syntactic tautologies now
#noalign fin.coe_eq_val
#noalign fin.val_eq_coe
/-- Assume `k = l`. If two functions defined on `Fin k` and `Fin l` are equal on each element,
then they coincide (in the heq sense). -/
protected theorem heq_fun_iff {α : Sort*} {k l : ℕ} (h : k = l) {f : Fin k → α} {g : Fin l → α} :
HEq f g ↔ ∀ i : Fin k, f i = g ⟨(i : ℕ), h ▸ i.2⟩ := by
subst h
simp [Function.funext_iff]
#align fin.heq_fun_iff Fin.heq_fun_iff
/-- Assume `k = l` and `k' = l'`.
If two functions `Fin k → Fin k' → α` and `Fin l → Fin l' → α` are equal on each pair,
then they coincide (in the heq sense). -/
protected theorem heq_fun₂_iff {α : Sort*} {k l k' l' : ℕ} (h : k = l) (h' : k' = l')
{f : Fin k → Fin k' → α} {g : Fin l → Fin l' → α} :
HEq f g ↔ ∀ (i : Fin k) (j : Fin k'), f i j = g ⟨(i : ℕ), h ▸ i.2⟩ ⟨(j : ℕ), h' ▸ j.2⟩ := by
subst h
subst h'
simp [Function.funext_iff]
protected theorem heq_ext_iff {k l : ℕ} (h : k = l) {i : Fin k} {j : Fin l} :
HEq i j ↔ (i : ℕ) = (j : ℕ) := by
subst h
simp [val_eq_val]
#align fin.heq_ext_iff Fin.heq_ext_iff
#align fin.exists_iff Fin.exists_iff
#align fin.forall_iff Fin.forall_iff
end coe
section Order
/-!
### order
-/
#align fin.is_le Fin.is_le
#align fin.is_le' Fin.is_le'
#align fin.lt_iff_coe_lt_coe Fin.lt_iff_val_lt_val
theorem le_iff_val_le_val {a b : Fin n} : a ≤ b ↔ (a : ℕ) ≤ b :=
Iff.rfl
#align fin.le_iff_coe_le_coe Fin.le_iff_val_le_val
#align fin.mk_lt_of_lt_coe Fin.mk_lt_of_lt_val
#align fin.mk_le_of_le_coe Fin.mk_le_of_le_val
/-- `a < b` as natural numbers if and only if `a < b` in `Fin n`. -/
@[norm_cast, simp]
theorem val_fin_lt {n : ℕ} {a b : Fin n} : (a : ℕ) < (b : ℕ) ↔ a < b :=
Iff.rfl
#align fin.coe_fin_lt Fin.val_fin_lt
/-- `a ≤ b` as natural numbers if and only if `a ≤ b` in `Fin n`. -/
@[norm_cast, simp]
theorem val_fin_le {n : ℕ} {a b : Fin n} : (a : ℕ) ≤ (b : ℕ) ↔ a ≤ b :=
Iff.rfl
#align fin.coe_fin_le Fin.val_fin_le
#align fin.mk_le_mk Fin.mk_le_mk
#align fin.mk_lt_mk Fin.mk_lt_mk
-- @[simp] -- Porting note (#10618): simp can prove this
theorem min_val {a : Fin n} : min (a : ℕ) n = a := by simp
#align fin.min_coe Fin.min_val
-- @[simp] -- Porting note (#10618): simp can prove this
theorem max_val {a : Fin n} : max (a : ℕ) n = n := by simp
#align fin.max_coe Fin.max_val
/-- The inclusion map `Fin n → ℕ` is an embedding. -/
@[simps apply]
def valEmbedding : Fin n ↪ ℕ :=
⟨val, val_injective⟩
#align fin.coe_embedding Fin.valEmbedding
@[simp]
theorem equivSubtype_symm_trans_valEmbedding :
equivSubtype.symm.toEmbedding.trans valEmbedding = Embedding.subtype (· < n) :=
rfl
#align fin.equiv_subtype_symm_trans_val_embedding Fin.equivSubtype_symm_trans_valEmbedding
/-- Use the ordering on `Fin n` for checking recursive definitions.
For example, the following definition is not accepted by the termination checker,
unless we declare the `WellFoundedRelation` instance:
```lean
def factorial {n : ℕ} : Fin n → ℕ
| ⟨0, _⟩ := 1
| ⟨i + 1, hi⟩ := (i + 1) * factorial ⟨i, i.lt_succ_self.trans hi⟩
```
-/
instance {n : ℕ} : WellFoundedRelation (Fin n) :=
measure (val : Fin n → ℕ)
/-- Given a positive `n`, `Fin.ofNat' i` is `i % n` as an element of `Fin n`. -/
def ofNat'' [NeZero n] (i : ℕ) : Fin n :=
⟨i % n, mod_lt _ n.pos_of_neZero⟩
#align fin.of_nat' Fin.ofNat''ₓ
-- Porting note: `Fin.ofNat'` conflicts with something in core (there the hypothesis is `n > 0`),
-- so for now we make this double-prime `''`. This is also the reason for the dubious translation.
instance {n : ℕ} [NeZero n] : Zero (Fin n) := ⟨ofNat'' 0⟩
instance {n : ℕ} [NeZero n] : One (Fin n) := ⟨ofNat'' 1⟩
#align fin.coe_zero Fin.val_zero
/--
The `Fin.val_zero` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
theorem val_zero' (n : ℕ) [NeZero n] : ((0 : Fin n) : ℕ) = 0 :=
rfl
#align fin.val_zero' Fin.val_zero'
#align fin.mk_zero Fin.mk_zero
/--
The `Fin.zero_le` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
protected theorem zero_le' [NeZero n] (a : Fin n) : 0 ≤ a :=
Nat.zero_le a.val
#align fin.zero_le Fin.zero_le'
#align fin.zero_lt_one Fin.zero_lt_one
#align fin.not_lt_zero Fin.not_lt_zero
/--
The `Fin.pos_iff_ne_zero` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
theorem pos_iff_ne_zero' [NeZero n] (a : Fin n) : 0 < a ↔ a ≠ 0 := by
rw [← val_fin_lt, val_zero', Nat.pos_iff_ne_zero, Ne, Ne, ext_iff, val_zero']
#align fin.pos_iff_ne_zero Fin.pos_iff_ne_zero'
#align fin.eq_zero_or_eq_succ Fin.eq_zero_or_eq_succ
#align fin.eq_succ_of_ne_zero Fin.eq_succ_of_ne_zero
@[simp] lemma cast_eq_self (a : Fin n) : cast rfl a = a := rfl
theorem rev_involutive : Involutive (rev : Fin n → Fin n) := fun i =>
ext <| by
dsimp only [rev]
rw [← Nat.sub_sub, Nat.sub_sub_self (Nat.add_one_le_iff.2 i.is_lt), Nat.add_sub_cancel_right]
#align fin.rev_involutive Fin.rev_involutive
/-- `Fin.rev` as an `Equiv.Perm`, the antitone involution `Fin n → Fin n` given by
`i ↦ n-(i+1)`. -/
@[simps! apply symm_apply]
def revPerm : Equiv.Perm (Fin n) :=
Involutive.toPerm rev rev_involutive
#align fin.rev Fin.revPerm
#align fin.coe_rev Fin.val_revₓ
theorem rev_injective : Injective (@rev n) :=
rev_involutive.injective
#align fin.rev_injective Fin.rev_injective
theorem rev_surjective : Surjective (@rev n) :=
rev_involutive.surjective
#align fin.rev_surjective Fin.rev_surjective
theorem rev_bijective : Bijective (@rev n) :=
rev_involutive.bijective
#align fin.rev_bijective Fin.rev_bijective
#align fin.rev_inj Fin.rev_injₓ
#align fin.rev_rev Fin.rev_revₓ
@[simp]
theorem revPerm_symm : (@revPerm n).symm = revPerm :=
rfl
#align fin.rev_symm Fin.revPerm_symm
#align fin.rev_eq Fin.rev_eqₓ
#align fin.rev_le_rev Fin.rev_le_revₓ
#align fin.rev_lt_rev Fin.rev_lt_revₓ
theorem cast_rev (i : Fin n) (h : n = m) :
cast h i.rev = (i.cast h).rev := by
subst h; simp
theorem rev_eq_iff {i j : Fin n} : rev i = j ↔ i = rev j := by
rw [← rev_inj, rev_rev]
theorem rev_ne_iff {i j : Fin n} : rev i ≠ j ↔ i ≠ rev j := rev_eq_iff.not
theorem rev_lt_iff {i j : Fin n} : rev i < j ↔ rev j < i := by
rw [← rev_lt_rev, rev_rev]
theorem rev_le_iff {i j : Fin n} : rev i ≤ j ↔ rev j ≤ i := by
rw [← rev_le_rev, rev_rev]
theorem lt_rev_iff {i j : Fin n} : i < rev j ↔ j < rev i := by
rw [← rev_lt_rev, rev_rev]
theorem le_rev_iff {i j : Fin n} : i ≤ rev j ↔ j ≤ rev i := by
rw [← rev_le_rev, rev_rev]
#align fin.last Fin.last
#align fin.coe_last Fin.val_last
-- Porting note: this is now syntactically equal to `val_last`
#align fin.last_val Fin.val_last
#align fin.le_last Fin.le_last
#align fin.last_pos Fin.last_pos
#align fin.eq_last_of_not_lt Fin.eq_last_of_not_lt
theorem last_pos' [NeZero n] : 0 < last n := n.pos_of_neZero
theorem one_lt_last [NeZero n] : 1 < last (n + 1) := Nat.lt_add_left_iff_pos.2 n.pos_of_neZero
end Order
section Add
/-!
### addition, numerals, and coercion from Nat
-/
#align fin.val_one Fin.val_one
#align fin.coe_one Fin.val_one
@[simp]
theorem val_one' (n : ℕ) [NeZero n] : ((1 : Fin n) : ℕ) = 1 % n :=
rfl
#align fin.coe_one' Fin.val_one'
-- Porting note: Delete this lemma after porting
theorem val_one'' {n : ℕ} : ((1 : Fin (n + 1)) : ℕ) = 1 % (n + 1) :=
rfl
#align fin.one_val Fin.val_one''
#align fin.mk_one Fin.mk_one
instance nontrivial {n : ℕ} : Nontrivial (Fin (n + 2)) where
exists_pair_ne := ⟨0, 1, (ne_iff_vne 0 1).mpr (by simp [val_one, val_zero])⟩
theorem nontrivial_iff_two_le : Nontrivial (Fin n) ↔ 2 ≤ n := by
rcases n with (_ | _ | n) <;>
simp [← Nat.one_eq_succ_zero, Fin.nontrivial, not_nontrivial, Nat.succ_le_iff]
-- Porting note: here and in the next lemma, had to use `← Nat.one_eq_succ_zero`.
#align fin.nontrivial_iff_two_le Fin.nontrivial_iff_two_le
#align fin.subsingleton_iff_le_one Fin.subsingleton_iff_le_one
section Monoid
-- Porting note (#10618): removing `simp`, `simp` can prove it with AddCommMonoid instance
protected theorem add_zero [NeZero n] (k : Fin n) : k + 0 = k := by
simp only [add_def, val_zero', Nat.add_zero, mod_eq_of_lt (is_lt k)]
#align fin.add_zero Fin.add_zero
-- Porting note (#10618): removing `simp`, `simp` can prove it with AddCommMonoid instance
protected theorem zero_add [NeZero n] (k : Fin n) : 0 + k = k := by
simp [ext_iff, add_def, mod_eq_of_lt (is_lt k)]
#align fin.zero_add Fin.zero_add
instance {a : ℕ} [NeZero n] : OfNat (Fin n) a where
ofNat := Fin.ofNat' a n.pos_of_neZero
instance inhabited (n : ℕ) [NeZero n] : Inhabited (Fin n) :=
⟨0⟩
instance inhabitedFinOneAdd (n : ℕ) : Inhabited (Fin (1 + n)) :=
haveI : NeZero (1 + n) := by rw [Nat.add_comm]; infer_instance
inferInstance
@[simp]
theorem default_eq_zero (n : ℕ) [NeZero n] : (default : Fin n) = 0 :=
rfl
#align fin.default_eq_zero Fin.default_eq_zero
section from_ad_hoc
@[simp] lemma ofNat'_zero {h : 0 < n} [NeZero n] : (Fin.ofNat' 0 h : Fin n) = 0 := rfl
@[simp] lemma ofNat'_one {h : 0 < n} [NeZero n] : (Fin.ofNat' 1 h : Fin n) = 1 := rfl
end from_ad_hoc
instance instNatCast [NeZero n] : NatCast (Fin n) where
natCast n := Fin.ofNat'' n
lemma natCast_def [NeZero n] (a : ℕ) : (a : Fin n) = ⟨a % n, mod_lt _ n.pos_of_neZero⟩ := rfl
end Monoid
#align fin.val_add Fin.val_add
#align fin.coe_add Fin.val_add
theorem val_add_eq_ite {n : ℕ} (a b : Fin n) :
(↑(a + b) : ℕ) = if n ≤ a + b then a + b - n else a + b := by
rw [Fin.val_add, Nat.add_mod_eq_ite, Nat.mod_eq_of_lt (show ↑a < n from a.2),
Nat.mod_eq_of_lt (show ↑b < n from b.2)]
#align fin.coe_add_eq_ite Fin.val_add_eq_ite
section deprecated
set_option linter.deprecated false
@[deprecated]
theorem val_bit0 {n : ℕ} (k : Fin n) : ((bit0 k : Fin n) : ℕ) = bit0 (k : ℕ) % n := by
cases k
rfl
#align fin.coe_bit0 Fin.val_bit0
@[deprecated]
theorem val_bit1 {n : ℕ} [NeZero n] (k : Fin n) :
((bit1 k : Fin n) : ℕ) = bit1 (k : ℕ) % n := by
cases n;
· cases' k with k h
cases k
· show _ % _ = _
simp at h
cases' h with _ h
simp [bit1, Fin.val_bit0, Fin.val_add, Fin.val_one]
#align fin.coe_bit1 Fin.val_bit1
end deprecated
#align fin.coe_add_one_of_lt Fin.val_add_one_of_lt
#align fin.last_add_one Fin.last_add_one
#align fin.coe_add_one Fin.val_add_one
section Bit
set_option linter.deprecated false
@[simp, deprecated]
theorem mk_bit0 {m n : ℕ} (h : bit0 m < n) :
(⟨bit0 m, h⟩ : Fin n) = (bit0 ⟨m, (Nat.le_add_right m m).trans_lt h⟩ : Fin _) :=
eq_of_val_eq (Nat.mod_eq_of_lt h).symm
#align fin.mk_bit0 Fin.mk_bit0
@[simp, deprecated]
theorem mk_bit1 {m n : ℕ} [NeZero n] (h : bit1 m < n) :
(⟨bit1 m, h⟩ : Fin n) =
(bit1 ⟨m, (Nat.le_add_right m m).trans_lt ((m + m).lt_succ_self.trans h)⟩ : Fin _) := by
ext
simp only [bit1, bit0] at h
simp only [bit1, bit0, val_add, val_one', ← Nat.add_mod, Nat.mod_eq_of_lt h]
#align fin.mk_bit1 Fin.mk_bit1
end Bit
#align fin.val_two Fin.val_two
--- Porting note: syntactically the same as the above
#align fin.coe_two Fin.val_two
section OfNatCoe
@[simp]
theorem ofNat''_eq_cast (n : ℕ) [NeZero n] (a : ℕ) : (Fin.ofNat'' a : Fin n) = a :=
rfl
#align fin.of_nat_eq_coe Fin.ofNat''_eq_cast
@[simp] lemma val_natCast (a n : ℕ) [NeZero n] : (a : Fin n).val = a % n := rfl
@[deprecated (since := "2024-04-17")]
alias val_nat_cast := val_natCast
-- Porting note: is this the right name for things involving `Nat.cast`?
/-- Converting an in-range number to `Fin (n + 1)` produces a result
whose value is the original number. -/
theorem val_cast_of_lt {n : ℕ} [NeZero n] {a : ℕ} (h : a < n) : (a : Fin n).val = a :=
Nat.mod_eq_of_lt h
#align fin.coe_val_of_lt Fin.val_cast_of_lt
/-- If `n` is non-zero, converting the value of a `Fin n` to `Fin n` results
in the same value. -/
@[simp] theorem cast_val_eq_self {n : ℕ} [NeZero n] (a : Fin n) : (a.val : Fin n) = a :=
ext <| val_cast_of_lt a.isLt
#align fin.coe_val_eq_self Fin.cast_val_eq_self
-- Porting note: this is syntactically the same as `val_cast_of_lt`
#align fin.coe_coe_of_lt Fin.val_cast_of_lt
-- Porting note: this is syntactically the same as `cast_val_of_lt`
#align fin.coe_coe_eq_self Fin.cast_val_eq_self
@[simp] lemma natCast_self (n : ℕ) [NeZero n] : (n : Fin n) = 0 := by ext; simp
@[deprecated (since := "2024-04-17")]
alias nat_cast_self := natCast_self
@[simp] lemma natCast_eq_zero {a n : ℕ} [NeZero n] : (a : Fin n) = 0 ↔ n ∣ a := by
simp [ext_iff, Nat.dvd_iff_mod_eq_zero]
@[deprecated (since := "2024-04-17")]
alias nat_cast_eq_zero := natCast_eq_zero
@[simp]
theorem natCast_eq_last (n) : (n : Fin (n + 1)) = Fin.last n := by ext; simp
#align fin.coe_nat_eq_last Fin.natCast_eq_last
@[deprecated (since := "2024-05-04")] alias cast_nat_eq_last := natCast_eq_last
theorem le_val_last (i : Fin (n + 1)) : i ≤ n := by
rw [Fin.natCast_eq_last]
exact Fin.le_last i
#align fin.le_coe_last Fin.le_val_last
variable {a b : ℕ}
lemma natCast_le_natCast (han : a ≤ n) (hbn : b ≤ n) : (a : Fin (n + 1)) ≤ b ↔ a ≤ b := by
rw [← Nat.lt_succ_iff] at han hbn
simp [le_iff_val_le_val, -val_fin_le, Nat.mod_eq_of_lt, han, hbn]
lemma natCast_lt_natCast (han : a ≤ n) (hbn : b ≤ n) : (a : Fin (n + 1)) < b ↔ a < b := by
rw [← Nat.lt_succ_iff] at han hbn; simp [lt_iff_val_lt_val, Nat.mod_eq_of_lt, han, hbn]
lemma natCast_mono (hbn : b ≤ n) (hab : a ≤ b) : (a : Fin (n + 1)) ≤ b :=
(natCast_le_natCast (hab.trans hbn) hbn).2 hab
lemma natCast_strictMono (hbn : b ≤ n) (hab : a < b) : (a : Fin (n + 1)) < b :=
(natCast_lt_natCast (hab.le.trans hbn) hbn).2 hab
end OfNatCoe
#align fin.add_one_pos Fin.add_one_pos
#align fin.one_pos Fin.one_pos
#align fin.zero_ne_one Fin.zero_ne_one
@[simp]
theorem one_eq_zero_iff [NeZero n] : (1 : Fin n) = 0 ↔ n = 1 := by
obtain _ | _ | n := n <;> simp [Fin.ext_iff]
#align fin.one_eq_zero_iff Fin.one_eq_zero_iff
@[simp]
theorem zero_eq_one_iff [NeZero n] : (0 : Fin n) = 1 ↔ n = 1 := by rw [eq_comm, one_eq_zero_iff]
#align fin.zero_eq_one_iff Fin.zero_eq_one_iff
end Add
section Succ
/-!
### succ and casts into larger Fin types
-/
#align fin.coe_succ Fin.val_succ
#align fin.succ_pos Fin.succ_pos
lemma succ_injective (n : ℕ) : Injective (@Fin.succ n) := fun a b ↦ by simp [ext_iff]
#align fin.succ_injective Fin.succ_injective
/-- `Fin.succ` as an `Embedding` -/
def succEmb (n : ℕ) : Fin n ↪ Fin (n + 1) where
toFun := succ
inj' := succ_injective _
@[simp]
theorem val_succEmb : ⇑(succEmb n) = Fin.succ := rfl
#align fin.succ_le_succ_iff Fin.succ_le_succ_iff
#align fin.succ_lt_succ_iff Fin.succ_lt_succ_iff
@[simp]
theorem exists_succ_eq {x : Fin (n + 1)} : (∃ y, Fin.succ y = x) ↔ x ≠ 0 :=
⟨fun ⟨_, hy⟩ => hy ▸ succ_ne_zero _, x.cases (fun h => h.irrefl.elim) (fun _ _ => ⟨_, rfl⟩)⟩
#align fin.exists_succ_eq_iff Fin.exists_succ_eq
theorem exists_succ_eq_of_ne_zero {x : Fin (n + 1)} (h : x ≠ 0) :
∃ y, Fin.succ y = x := exists_succ_eq.mpr h
#align fin.succ_inj Fin.succ_inj
#align fin.succ_ne_zero Fin.succ_ne_zero
@[simp]
theorem succ_zero_eq_one' [NeZero n] : Fin.succ (0 : Fin n) = 1 := by
cases n
· exact (NeZero.ne 0 rfl).elim
· rfl
#align fin.succ_zero_eq_one Fin.succ_zero_eq_one'
theorem one_pos' [NeZero n] : (0 : Fin (n + 1)) < 1 := succ_zero_eq_one' (n := n) ▸ succ_pos _
theorem zero_ne_one' [NeZero n] : (0 : Fin (n + 1)) ≠ 1 := Fin.ne_of_lt one_pos'
#align fin.succ_zero_eq_one' Fin.succ_zero_eq_one
/--
The `Fin.succ_one_eq_two` in `Lean` only applies in `Fin (n+2)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
theorem succ_one_eq_two' [NeZero n] : Fin.succ (1 : Fin (n + 1)) = 2 := by
cases n
· exact (NeZero.ne 0 rfl).elim
· rfl
#align fin.succ_one_eq_two Fin.succ_one_eq_two'
-- Version of `succ_one_eq_two` to be used by `dsimp`.
-- Note the `'` swapped around due to a move to std4.
#align fin.succ_one_eq_two' Fin.succ_one_eq_two
#align fin.succ_mk Fin.succ_mk
#align fin.mk_succ_pos Fin.mk_succ_pos
#align fin.one_lt_succ_succ Fin.one_lt_succ_succ
#align fin.add_one_lt_iff Fin.add_one_lt_iff
#align fin.add_one_le_iff Fin.add_one_le_iff
#align fin.last_le_iff Fin.last_le_iff
#align fin.lt_add_one_iff Fin.lt_add_one_iff
/--
The `Fin.le_zero_iff` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
theorem le_zero_iff' {n : ℕ} [NeZero n] {k : Fin n} : k ≤ 0 ↔ k = 0 :=
⟨fun h => Fin.ext <| by rw [Nat.eq_zero_of_le_zero h]; rfl, by rintro rfl; exact Nat.le_refl _⟩
#align fin.le_zero_iff Fin.le_zero_iff'
#align fin.succ_succ_ne_one Fin.succ_succ_ne_one
#align fin.cast_lt Fin.castLT
#align fin.coe_cast_lt Fin.coe_castLT
#align fin.cast_lt_mk Fin.castLT_mk
-- Move to Batteries?
@[simp] theorem cast_refl {n : Nat} (h : n = n) :
Fin.cast h = id := rfl
-- TODO: Move to Batteries
@[simp] lemma castLE_inj {hmn : m ≤ n} {a b : Fin m} : castLE hmn a = castLE hmn b ↔ a = b := by
simp [ext_iff]
@[simp] lemma castAdd_inj {a b : Fin m} : castAdd n a = castAdd n b ↔ a = b := by simp [ext_iff]
attribute [simp] castSucc_inj
lemma castLE_injective (hmn : m ≤ n) : Injective (castLE hmn) :=
fun a b hab ↦ ext (by have := congr_arg val hab; exact this)
lemma castAdd_injective (m n : ℕ) : Injective (@Fin.castAdd m n) := castLE_injective _
lemma castSucc_injective (n : ℕ) : Injective (@Fin.castSucc n) := castAdd_injective _ _
#align fin.cast_succ_injective Fin.castSucc_injective
/-- `Fin.castLE` as an `Embedding`, `castLEEmb h i` embeds `i` into a larger `Fin` type. -/
@[simps! apply]
def castLEEmb (h : n ≤ m) : Fin n ↪ Fin m where
toFun := castLE h
inj' := castLE_injective _
@[simp, norm_cast] lemma coe_castLEEmb {m n} (hmn : m ≤ n) : castLEEmb hmn = castLE hmn := rfl
#align fin.coe_cast_le Fin.coe_castLE
#align fin.cast_le_mk Fin.castLE_mk
#align fin.cast_le_zero Fin.castLE_zero
/- The next proof can be golfed a lot using `Fintype.card`.
It is written this way to define `ENat.card` and `Nat.card` without a `Fintype` dependency
(not done yet). -/
assert_not_exists Fintype
lemma nonempty_embedding_iff : Nonempty (Fin n ↪ Fin m) ↔ n ≤ m := by
refine ⟨fun h ↦ ?_, fun h ↦ ⟨castLEEmb h⟩⟩
induction n generalizing m with
| zero => exact m.zero_le
| succ n ihn =>
cases' h with e
rcases exists_eq_succ_of_ne_zero (pos_iff_nonempty.2 (Nonempty.map e inferInstance)).ne'
with ⟨m, rfl⟩
refine Nat.succ_le_succ <| ihn ⟨?_⟩
refine ⟨fun i ↦ (e.setValue 0 0 i.succ).pred (mt e.setValue_eq_iff.1 i.succ_ne_zero),
fun i j h ↦ ?_⟩
simpa only [pred_inj, EmbeddingLike.apply_eq_iff_eq, succ_inj] using h
lemma equiv_iff_eq : Nonempty (Fin m ≃ Fin n) ↔ m = n :=
⟨fun ⟨e⟩ ↦ le_antisymm (nonempty_embedding_iff.1 ⟨e⟩) (nonempty_embedding_iff.1 ⟨e.symm⟩),
fun h ↦ h ▸ ⟨.refl _⟩⟩
#align fin.equiv_iff_eq Fin.equiv_iff_eq
@[simp] lemma castLE_castSucc {n m} (i : Fin n) (h : n + 1 ≤ m) :
i.castSucc.castLE h = i.castLE (Nat.le_of_succ_le h) :=
rfl
@[simp] lemma castLE_comp_castSucc {n m} (h : n + 1 ≤ m) :
Fin.castLE h ∘ Fin.castSucc = Fin.castLE (Nat.le_of_succ_le h) :=
rfl
@[simp] lemma castLE_rfl (n : ℕ) : Fin.castLE (le_refl n) = id :=
rfl
@[simp]
theorem range_castLE {n k : ℕ} (h : n ≤ k) : Set.range (castLE h) = { i : Fin k | (i : ℕ) < n } :=
Set.ext fun x => ⟨fun ⟨y, hy⟩ => hy ▸ y.2, fun hx => ⟨⟨x, hx⟩, Fin.ext rfl⟩⟩
#align fin.range_cast_le Fin.range_castLE
@[simp]
theorem coe_of_injective_castLE_symm {n k : ℕ} (h : n ≤ k) (i : Fin k) (hi) :
((Equiv.ofInjective _ (castLE_injective h)).symm ⟨i, hi⟩ : ℕ) = i := by
rw [← coe_castLE h]
exact congr_arg Fin.val (Equiv.apply_ofInjective_symm _ _)
#align fin.coe_of_injective_cast_le_symm Fin.coe_of_injective_castLE_symm
#align fin.cast_le_succ Fin.castLE_succ
#align fin.cast_le_cast_le Fin.castLE_castLE
#align fin.cast_le_comp_cast_le Fin.castLE_comp_castLE
theorem leftInverse_cast (eq : n = m) : LeftInverse (cast eq.symm) (cast eq) :=
fun _ => rfl
theorem rightInverse_cast (eq : n = m) : RightInverse (cast eq.symm) (cast eq) :=
fun _ => rfl
theorem cast_le_cast (eq : n = m) {a b : Fin n} : cast eq a ≤ cast eq b ↔ a ≤ b :=
Iff.rfl
/-- The 'identity' equivalence between `Fin m` and `Fin n` when `m = n`. -/
@[simps]
def _root_.finCongr (eq : n = m) : Fin n ≃ Fin m where
toFun := cast eq
invFun := cast eq.symm
left_inv := leftInverse_cast eq
right_inv := rightInverse_cast eq
#align fin_congr finCongr
@[simp] lemma _root_.finCongr_apply_mk (h : m = n) (k : ℕ) (hk : k < m) :
finCongr h ⟨k, hk⟩ = ⟨k, h ▸ hk⟩ := rfl
#align fin_congr_apply_mk finCongr_apply_mk
@[simp]
lemma _root_.finCongr_refl (h : n = n := rfl) : finCongr h = Equiv.refl (Fin n) := by ext; simp
@[simp] lemma _root_.finCongr_symm (h : m = n) : (finCongr h).symm = finCongr h.symm := rfl
#align fin_congr_symm finCongr_symm
@[simp] lemma _root_.finCongr_apply_coe (h : m = n) (k : Fin m) : (finCongr h k : ℕ) = k := rfl
#align fin_congr_apply_coe finCongr_apply_coe
lemma _root_.finCongr_symm_apply_coe (h : m = n) (k : Fin n) : ((finCongr h).symm k : ℕ) = k := rfl
#align fin_congr_symm_apply_coe finCongr_symm_apply_coe
/-- While in many cases `finCongr` is better than `Equiv.cast`/`cast`, sometimes we want to apply
a generic theorem about `cast`. -/
lemma _root_.finCongr_eq_equivCast (h : n = m) : finCongr h = .cast (h ▸ rfl) := by subst h; simp
#align fin.coe_cast Fin.coe_castₓ
@[simp]
theorem cast_zero {n' : ℕ} [NeZero n] {h : n = n'} : cast h (0 : Fin n) =
by { haveI : NeZero n' := by {rw [← h]; infer_instance}; exact 0} :=
ext rfl
#align fin.cast_zero Fin.cast_zero
#align fin.cast_last Fin.cast_lastₓ
#align fin.cast_mk Fin.cast_mkₓ
#align fin.cast_trans Fin.cast_transₓ
#align fin.cast_le_of_eq Fin.castLE_of_eq
/-- While in many cases `Fin.cast` is better than `Equiv.cast`/`cast`, sometimes we want to apply
a generic theorem about `cast`. -/
theorem cast_eq_cast (h : n = m) : (cast h : Fin n → Fin m) = _root_.cast (h ▸ rfl) := by
subst h
ext
rfl
#align fin.cast_eq_cast Fin.cast_eq_cast
/-- `Fin.castAdd` as an `Embedding`, `castAddEmb m i` embeds `i : Fin n` in `Fin (n+m)`.
See also `Fin.natAddEmb` and `Fin.addNatEmb`. -/
@[simps! apply]
def castAddEmb (m) : Fin n ↪ Fin (n + m) := castLEEmb (le_add_right n m)
#align fin.coe_cast_add Fin.coe_castAdd
#align fin.cast_add_zero Fin.castAdd_zeroₓ
#align fin.cast_add_lt Fin.castAdd_lt
#align fin.cast_add_mk Fin.castAdd_mk
#align fin.cast_add_cast_lt Fin.castAdd_castLT
#align fin.cast_lt_cast_add Fin.castLT_castAdd
#align fin.cast_add_cast Fin.castAdd_castₓ
#align fin.cast_cast_add_left Fin.cast_castAdd_leftₓ
#align fin.cast_cast_add_right Fin.cast_castAdd_rightₓ
#align fin.cast_add_cast_add Fin.castAdd_castAdd
#align fin.cast_succ_eq Fin.cast_succ_eqₓ
#align fin.succ_cast_eq Fin.succ_cast_eqₓ
/-- `Fin.castSucc` as an `Embedding`, `castSuccEmb i` embeds `i : Fin n` in `Fin (n+1)`. -/
@[simps! apply]
def castSuccEmb : Fin n ↪ Fin (n + 1) := castAddEmb _
@[simp, norm_cast] lemma coe_castSuccEmb : (castSuccEmb : Fin n → Fin (n + 1)) = Fin.castSucc := rfl
#align fin.coe_cast_succ Fin.coe_castSucc
#align fin.cast_succ_mk Fin.castSucc_mk
#align fin.cast_cast_succ Fin.cast_castSuccₓ
#align fin.cast_succ_lt_succ Fin.castSucc_lt_succ
#align fin.le_cast_succ_iff Fin.le_castSucc_iff
#align fin.cast_succ_lt_iff_succ_le Fin.castSucc_lt_iff_succ_le
#align fin.succ_last Fin.succ_last
#align fin.succ_eq_last_succ Fin.succ_eq_last_succ
#align fin.cast_succ_cast_lt Fin.castSucc_castLT
#align fin.cast_lt_cast_succ Fin.castLT_castSucc
#align fin.cast_succ_lt_cast_succ_iff Fin.castSucc_lt_castSucc_iff
@[simp]
theorem castSucc_le_castSucc_iff {a b : Fin n} : castSucc a ≤ castSucc b ↔ a ≤ b := Iff.rfl
@[simp]
theorem succ_le_castSucc_iff {a b : Fin n} : succ a ≤ castSucc b ↔ a < b := by
rw [le_castSucc_iff, succ_lt_succ_iff]
@[simp]
theorem castSucc_lt_succ_iff {a b : Fin n} : castSucc a < succ b ↔ a ≤ b := by
rw [castSucc_lt_iff_succ_le, succ_le_succ_iff]
theorem le_of_castSucc_lt_of_succ_lt {a b : Fin (n + 1)} {i : Fin n}
(hl : castSucc i < a) (hu : b < succ i) : b < a := by
simp [Fin.lt_def, -val_fin_lt] at *; omega
theorem castSucc_lt_or_lt_succ (p : Fin (n + 1)) (i : Fin n) : castSucc i < p ∨ p < i.succ := by
simp [Fin.lt_def, -val_fin_lt]; omega
#align fin.succ_above_lt_gt Fin.castSucc_lt_or_lt_succ
@[deprecated] alias succAbove_lt_gt := castSucc_lt_or_lt_succ
theorem succ_le_or_le_castSucc (p : Fin (n + 1)) (i : Fin n) : succ i ≤ p ∨ p ≤ i.castSucc := by
rw [le_castSucc_iff, ← castSucc_lt_iff_succ_le]
exact p.castSucc_lt_or_lt_succ i
theorem exists_castSucc_eq_of_ne_last {x : Fin (n + 1)} (h : x ≠ (last _)) :
∃ y, Fin.castSucc y = x := exists_castSucc_eq.mpr h
#align fin.cast_succ_inj Fin.castSucc_inj
#align fin.cast_succ_lt_last Fin.castSucc_lt_last
theorem forall_fin_succ' {P : Fin (n + 1) → Prop} :
(∀ i, P i) ↔ (∀ i : Fin n, P i.castSucc) ∧ P (.last _) :=
⟨fun H => ⟨fun _ => H _, H _⟩, fun ⟨H0, H1⟩ i => Fin.lastCases H1 H0 i⟩
-- to match `Fin.eq_zero_or_eq_succ`
theorem eq_castSucc_or_eq_last {n : Nat} (i : Fin (n + 1)) :
(∃ j : Fin n, i = j.castSucc) ∨ i = last n := i.lastCases (Or.inr rfl) (Or.inl ⟨·, rfl⟩)
theorem exists_fin_succ' {P : Fin (n + 1) → Prop} :
(∃ i, P i) ↔ (∃ i : Fin n, P i.castSucc) ∨ P (.last _) :=
⟨fun ⟨i, h⟩ => Fin.lastCases Or.inr (fun i hi => Or.inl ⟨i, hi⟩) i h,
fun h => h.elim (fun ⟨i, hi⟩ => ⟨i.castSucc, hi⟩) (fun h => ⟨.last _, h⟩)⟩
/--
The `Fin.castSucc_zero` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
theorem castSucc_zero' [NeZero n] : castSucc (0 : Fin n) = 0 :=
ext rfl
#align fin.cast_succ_zero Fin.castSucc_zero'
#align fin.cast_succ_one Fin.castSucc_one
/-- `castSucc i` is positive when `i` is positive.
The `Fin.castSucc_pos` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis. -/
theorem castSucc_pos' [NeZero n] {i : Fin n} (h : 0 < i) : 0 < castSucc i := by
simpa [lt_iff_val_lt_val] using h
#align fin.cast_succ_pos Fin.castSucc_pos'
/--
The `Fin.castSucc_eq_zero_iff` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
@[simp]
theorem castSucc_eq_zero_iff' [NeZero n] (a : Fin n) : castSucc a = 0 ↔ a = 0 :=
Fin.ext_iff.trans <| (Fin.ext_iff.trans <| by simp).symm
#align fin.cast_succ_eq_zero_iff Fin.castSucc_eq_zero_iff'
/--
The `Fin.castSucc_ne_zero_iff` in `Lean` only applies in `Fin (n+1)`.
This one instead uses a `NeZero n` typeclass hypothesis.
-/
theorem castSucc_ne_zero_iff' [NeZero n] (a : Fin n) : castSucc a ≠ 0 ↔ a ≠ 0 :=
not_iff_not.mpr <| castSucc_eq_zero_iff' a
#align fin.cast_succ_ne_zero_iff Fin.castSucc_ne_zero_iff
theorem castSucc_ne_zero_of_lt {p i : Fin n} (h : p < i) : castSucc i ≠ 0 := by
cases n
· exact i.elim0
· rw [castSucc_ne_zero_iff', Ne, ext_iff]
exact ((zero_le _).trans_lt h).ne'
theorem succ_ne_last_iff (a : Fin (n + 1)) : succ a ≠ last (n + 1) ↔ a ≠ last n :=
not_iff_not.mpr <| succ_eq_last_succ a
theorem succ_ne_last_of_lt {p i : Fin n} (h : i < p) : succ i ≠ last n := by
cases n
· exact i.elim0
· rw [succ_ne_last_iff, Ne, ext_iff]
exact ((le_last _).trans_lt' h).ne
#align fin.cast_succ_fin_succ Fin.castSucc_fin_succ
@[norm_cast, simp]
theorem coe_eq_castSucc {a : Fin n} : (a : Fin (n + 1)) = castSucc a := by
ext
exact val_cast_of_lt (Nat.lt.step a.is_lt)
#align fin.coe_eq_cast_succ Fin.coe_eq_castSucc
theorem coe_succ_lt_iff_lt {n : ℕ} {j k : Fin n} : (j : Fin <| n + 1) < k ↔ j < k := by
simp only [coe_eq_castSucc, castSucc_lt_castSucc_iff]
#align fin.coe_succ_eq_succ Fin.coeSucc_eq_succ
#align fin.lt_succ Fin.lt_succ
@[simp]
theorem range_castSucc {n : ℕ} : Set.range (castSucc : Fin n → Fin n.succ) =
({ i | (i : ℕ) < n } : Set (Fin n.succ)) := range_castLE (by omega)
#align fin.range_cast_succ Fin.range_castSucc
@[simp]
theorem coe_of_injective_castSucc_symm {n : ℕ} (i : Fin n.succ) (hi) :
((Equiv.ofInjective castSucc (castSucc_injective _)).symm ⟨i, hi⟩ : ℕ) = i := by
rw [← coe_castSucc]
exact congr_arg val (Equiv.apply_ofInjective_symm _ _)
#align fin.coe_of_injective_cast_succ_symm Fin.coe_of_injective_castSucc_symm
#align fin.succ_cast_succ Fin.succ_castSucc
/-- `Fin.addNat` as an `Embedding`, `addNatEmb m i` adds `m` to `i`, generalizes `Fin.succ`. -/
@[simps! apply]
def addNatEmb (m) : Fin n ↪ Fin (n + m) where
toFun := (addNat · m)
inj' a b := by simp [ext_iff]
#align fin.coe_add_nat Fin.coe_addNat
#align fin.add_nat_one Fin.addNat_one
#align fin.le_coe_add_nat Fin.le_coe_addNat
#align fin.add_nat_mk Fin.addNat_mk
#align fin.cast_add_nat_zero Fin.cast_addNat_zeroₓ
#align fin.add_nat_cast Fin.addNat_castₓ
#align fin.cast_add_nat_left Fin.cast_addNat_leftₓ
#align fin.cast_add_nat_right Fin.cast_addNat_rightₓ
/-- `Fin.natAdd` as an `Embedding`, `natAddEmb n i` adds `n` to `i` "on the left". -/
@[simps! apply]
def natAddEmb (n) {m} : Fin m ↪ Fin (n + m) where
toFun := natAdd n
inj' a b := by simp [ext_iff]
#align fin.coe_nat_add Fin.coe_natAdd
#align fin.nat_add_mk Fin.natAdd_mk
#align fin.le_coe_nat_add Fin.le_coe_natAdd
#align fin.nat_add_zero Fin.natAdd_zeroₓ
#align fin.nat_add_cast Fin.natAdd_castₓ
#align fin.cast_nat_add_right Fin.cast_natAdd_rightₓ
#align fin.cast_nat_add_left Fin.cast_natAdd_leftₓ
#align fin.cast_add_nat_add Fin.castAdd_natAddₓ
#align fin.nat_add_cast_add Fin.natAdd_castAddₓ
#align fin.nat_add_nat_add Fin.natAdd_natAddₓ
#align fin.cast_nat_add_zero Fin.cast_natAdd_zeroₓ
#align fin.cast_nat_add Fin.cast_natAddₓ
#align fin.cast_add_nat Fin.cast_addNatₓ
#align fin.nat_add_last Fin.natAdd_last
#align fin.nat_add_cast_succ Fin.natAdd_castSucc
end Succ
section Pred
/-!
### pred
-/
#align fin.pred Fin.pred
#align fin.coe_pred Fin.coe_pred
#align fin.succ_pred Fin.succ_pred
#align fin.pred_succ Fin.pred_succ
#align fin.pred_eq_iff_eq_succ Fin.pred_eq_iff_eq_succ
#align fin.pred_mk_succ Fin.pred_mk_succ
#align fin.pred_mk Fin.pred_mk
#align fin.pred_le_pred_iff Fin.pred_le_pred_iff
#align fin.pred_lt_pred_iff Fin.pred_lt_pred_iff
#align fin.pred_inj Fin.pred_inj
#align fin.pred_one Fin.pred_one
#align fin.pred_add_one Fin.pred_add_one
#align fin.sub_nat Fin.subNat
#align fin.coe_sub_nat Fin.coe_subNat
#align fin.sub_nat_mk Fin.subNat_mk
#align fin.pred_cast_succ_succ Fin.pred_castSucc_succ
#align fin.add_nat_sub_nat Fin.addNat_subNat
#align fin.sub_nat_add_nat Fin.subNat_addNat
#align fin.nat_add_sub_nat_cast Fin.natAdd_subNat_castₓ
theorem pred_one' [NeZero n] (h := (zero_ne_one' (n := n)).symm) :
Fin.pred (1 : Fin (n + 1)) h = 0 := by
simp_rw [Fin.ext_iff, coe_pred, val_one', val_zero', Nat.sub_eq_zero_iff_le, Nat.mod_le]
theorem pred_last (h := ext_iff.not.2 last_pos'.ne') :
pred (last (n + 1)) h = last n := by simp_rw [← succ_last, pred_succ]
theorem pred_lt_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : pred i hi < j ↔ i < succ j := by
rw [← succ_lt_succ_iff, succ_pred]
theorem lt_pred_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : j < pred i hi ↔ succ j < i := by
rw [← succ_lt_succ_iff, succ_pred]
theorem pred_le_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : pred i hi ≤ j ↔ i ≤ succ j := by
rw [← succ_le_succ_iff, succ_pred]
theorem le_pred_iff {j : Fin n} {i : Fin (n + 1)} (hi : i ≠ 0) : j ≤ pred i hi ↔ succ j ≤ i := by
rw [← succ_le_succ_iff, succ_pred]
theorem castSucc_pred_eq_pred_castSucc {a : Fin (n + 1)} (ha : a ≠ 0)
(ha' := a.castSucc_ne_zero_iff.mpr ha) :
(a.pred ha).castSucc = (castSucc a).pred ha' := rfl
#align fin.cast_succ_pred_eq_pred_cast_succ Fin.castSucc_pred_eq_pred_castSucc
theorem castSucc_pred_add_one_eq {a : Fin (n + 1)} (ha : a ≠ 0) :
(a.pred ha).castSucc + 1 = a := by
cases' a using cases with a
· exact (ha rfl).elim
· rw [pred_succ, coeSucc_eq_succ]
theorem le_pred_castSucc_iff {a b : Fin (n + 1)} (ha : castSucc a ≠ 0) :
b ≤ (castSucc a).pred ha ↔ b < a := by
rw [le_pred_iff, succ_le_castSucc_iff]
theorem pred_castSucc_lt_iff {a b : Fin (n + 1)} (ha : castSucc a ≠ 0) :
(castSucc a).pred ha < b ↔ a ≤ b := by
rw [pred_lt_iff, castSucc_lt_succ_iff]
theorem pred_castSucc_lt {a : Fin (n + 1)} (ha : castSucc a ≠ 0) :
(castSucc a).pred ha < a := by rw [pred_castSucc_lt_iff, le_def]
theorem le_castSucc_pred_iff {a b : Fin (n + 1)} (ha : a ≠ 0) :
b ≤ castSucc (a.pred ha) ↔ b < a := by
rw [castSucc_pred_eq_pred_castSucc, le_pred_castSucc_iff]
| Mathlib/Data/Fin/Basic.lean | 1,152 | 1,154 | theorem castSucc_pred_lt_iff {a b : Fin (n + 1)} (ha : a ≠ 0) :
castSucc (a.pred ha) < b ↔ a ≤ b := by |
rw [castSucc_pred_eq_pred_castSucc, pred_castSucc_lt_iff]
|
/-
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.Nat.Prime
import Mathlib.Tactic.NormNum.Basic
#align_import data.nat.prime_norm_num from "leanprover-community/mathlib"@"10b4e499f43088dd3bb7b5796184ad5216648ab1"
/-!
# `norm_num` extensions on natural numbers
This file provides a `norm_num` extension to prove that natural numbers are prime and compute
its minimal factor. Todo: compute the list of all factors.
## Implementation Notes
For numbers larger than 25 bits, the primality proof produced by `norm_num` is an expression
that is thousands of levels deep, and the Lean kernel seems to raise a stack overflow when
type-checking that proof. If we want an implementation that works for larger primes, we should
generate a proof that has a smaller depth.
Note: `evalMinFac.aux` does not raise a stack overflow, which can be checked by replacing the
`prf'` in the recursive call by something like `(.sort .zero)`
-/
open Nat Qq Lean Meta
namespace Mathlib.Meta.NormNum
theorem not_prime_mul_of_ble (a b n : ℕ) (h : a * b = n) (h₁ : a.ble 1 = false)
(h₂ : b.ble 1 = false) : ¬ n.Prime :=
not_prime_mul' h (ble_eq_false.mp h₁).ne' (ble_eq_false.mp h₂).ne'
/-- Produce a proof that `n` is not prime from a factor `1 < d < n`. `en` should be the expression
that is the natural number literal `n`. -/
def deriveNotPrime (n d : ℕ) (en : Q(ℕ)) : Q(¬ Nat.Prime $en) := Id.run <| do
let d' : ℕ := n / d
let prf : Q($d * $d' = $en) := (q(Eq.refl $en) : Expr)
let r : Q(Nat.ble $d 1 = false) := (q(Eq.refl false) : Expr)
let r' : Q(Nat.ble $d' 1 = false) := (q(Eq.refl false) : Expr)
return q(not_prime_mul_of_ble _ _ _ $prf $r $r')
/-- A predicate representing partial progress in a proof of `minFac`. -/
def MinFacHelper (n k : ℕ) : Prop :=
2 < k ∧ k % 2 = 1 ∧ k ≤ minFac n
theorem MinFacHelper.one_lt {n k : ℕ} (h : MinFacHelper n k) : 1 < n := by
have : 2 < minFac n := h.1.trans_le h.2.2
obtain rfl | h := n.eq_zero_or_pos
· contradiction
rcases (succ_le_of_lt h).eq_or_lt with rfl|h
· simp_all
exact h
theorem minFacHelper_0 (n : ℕ)
(h1 : Nat.ble (nat_lit 2) n = true) (h2 : nat_lit 1 = n % (nat_lit 2)) :
MinFacHelper n (nat_lit 3) := by
refine ⟨by norm_num, by norm_num, ?_⟩
refine (le_minFac'.mpr λ p hp hpn ↦ ?_).resolve_left (Nat.ne_of_gt (Nat.le_of_ble_eq_true h1))
rcases hp.eq_or_lt with rfl|h
· simp [(Nat.dvd_iff_mod_eq_zero ..).1 hpn] at h2
· exact h
theorem minFacHelper_1 {n k k' : ℕ} (e : k + 2 = k') (h : MinFacHelper n k)
(np : minFac n ≠ k) : MinFacHelper n k' := by
rw [← e]
refine ⟨Nat.lt_add_right _ h.1, ?_, ?_⟩
· rw [add_mod, mod_self, add_zero, mod_mod]
exact h.2.1
rcases h.2.2.eq_or_lt with rfl|h2
· exact (np rfl).elim
rcases (succ_le_of_lt h2).eq_or_lt with h2|h2
· refine ((h.1.trans_le h.2.2).ne ?_).elim
have h3 : 2 ∣ minFac n := by
rw [Nat.dvd_iff_mod_eq_zero, ← h2, succ_eq_add_one, add_mod, h.2.1]
rw [dvd_prime <| minFac_prime h.one_lt.ne'] at h3
norm_num at h3
exact h3
exact h2
theorem minFacHelper_2 {n k k' : ℕ} (e : k + 2 = k') (nk : ¬ Nat.Prime k)
(h : MinFacHelper n k) : MinFacHelper n k' := by
refine minFacHelper_1 e h λ h2 ↦ ?_
rw [← h2] at nk
exact nk <| minFac_prime h.one_lt.ne'
| Mathlib/Tactic/NormNum/Prime.lean | 90 | 95 | theorem minFacHelper_3 {n k k' : ℕ} (e : k + 2 = k') (nk : (n % k).beq 0 = false)
(h : MinFacHelper n k) : MinFacHelper n k' := by |
refine minFacHelper_1 e h λ h2 ↦ ?_
have nk := Nat.ne_of_beq_eq_false nk
rw [← Nat.dvd_iff_mod_eq_zero, ← h2] at nk
exact nk <| minFac_dvd n
|
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