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/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Topology.ContinuousOn
import Mathlib.Order.Filter.SmallSets
#align_import topology.locally_finite from "leanprover-community/mathlib"@"55d771df074d0dd020139ee1cd4b95521422df9f"
/-!
### Locally finite families of sets
We say that a family of sets in a topological space is *locally finite* if at every point `x : X`,
there is a neighborhood of `x` which meets only finitely many sets in the family.
In this file we give the definition and prove basic properties of locally finite families of sets.
-/
-- locally finite family [General Topology (Bourbaki, 1995)]
open Set Function Filter Topology
variable {ι ι' α X Y : Type*} [TopologicalSpace X] [TopologicalSpace Y] {f g : ι → Set X}
/-- A family of sets in `Set X` is locally finite if at every point `x : X`,
there is a neighborhood of `x` which meets only finitely many sets in the family. -/
def LocallyFinite (f : ι → Set X) :=
∀ x : X, ∃ t ∈ 𝓝 x, { i | (f i ∩ t).Nonempty }.Finite
#align locally_finite LocallyFinite
theorem locallyFinite_of_finite [Finite ι] (f : ι → Set X) : LocallyFinite f := fun _ =>
⟨univ, univ_mem, toFinite _⟩
#align locally_finite_of_finite locallyFinite_of_finite
namespace LocallyFinite
theorem point_finite (hf : LocallyFinite f) (x : X) : { b | x ∈ f b }.Finite :=
let ⟨_t, hxt, ht⟩ := hf x
ht.subset fun _b hb => ⟨x, hb, mem_of_mem_nhds hxt⟩
#align locally_finite.point_finite LocallyFinite.point_finite
protected theorem subset (hf : LocallyFinite f) (hg : ∀ i, g i ⊆ f i) : LocallyFinite g := fun a =>
let ⟨t, ht₁, ht₂⟩ := hf a
⟨t, ht₁, ht₂.subset fun i hi => hi.mono <| inter_subset_inter (hg i) Subset.rfl⟩
#align locally_finite.subset LocallyFinite.subset
theorem comp_injOn {g : ι' → ι} (hf : LocallyFinite f) (hg : InjOn g { i | (f (g i)).Nonempty }) :
LocallyFinite (f ∘ g) := fun x => by
let ⟨t, htx, htf⟩ := hf x
refine ⟨t, htx, htf.preimage <| ?_⟩
exact hg.mono fun i (hi : Set.Nonempty _) => hi.left
#align locally_finite.comp_inj_on LocallyFinite.comp_injOn
theorem comp_injective {g : ι' → ι} (hf : LocallyFinite f) (hg : Injective g) :
LocallyFinite (f ∘ g) :=
hf.comp_injOn hg.injOn
#align locally_finite.comp_injective LocallyFinite.comp_injective
theorem _root_.locallyFinite_iff_smallSets :
LocallyFinite f ↔ ∀ x, ∀ᶠ s in (𝓝 x).smallSets, { i | (f i ∩ s).Nonempty }.Finite :=
forall_congr' fun _ => Iff.symm <|
eventually_smallSets' fun _s _t hst ht =>
ht.subset fun _i hi => hi.mono <| inter_subset_inter_right _ hst
#align locally_finite_iff_small_sets locallyFinite_iff_smallSets
protected theorem eventually_smallSets (hf : LocallyFinite f) (x : X) :
∀ᶠ s in (𝓝 x).smallSets, { i | (f i ∩ s).Nonempty }.Finite :=
locallyFinite_iff_smallSets.mp hf x
#align locally_finite.eventually_small_sets LocallyFinite.eventually_smallSets
theorem exists_mem_basis {ι' : Sort*} (hf : LocallyFinite f) {p : ι' → Prop} {s : ι' → Set X}
{x : X} (hb : (𝓝 x).HasBasis p s) : ∃ i, p i ∧ { j | (f j ∩ s i).Nonempty }.Finite :=
let ⟨i, hpi, hi⟩ := hb.smallSets.eventually_iff.mp (hf.eventually_smallSets x)
⟨i, hpi, hi Subset.rfl⟩
#align locally_finite.exists_mem_basis LocallyFinite.exists_mem_basis
protected theorem nhdsWithin_iUnion (hf : LocallyFinite f) (a : X) :
𝓝[⋃ i, f i] a = ⨆ i, 𝓝[f i] a := by
rcases hf a with ⟨U, haU, hfin⟩
refine le_antisymm ?_ (Monotone.le_map_iSup fun _ _ ↦ nhdsWithin_mono _)
calc
𝓝[⋃ i, f i] a = 𝓝[⋃ i, f i ∩ U] a := by
rw [← iUnion_inter, ← nhdsWithin_inter_of_mem' (nhdsWithin_le_nhds haU)]
_ = 𝓝[⋃ i ∈ {j | (f j ∩ U).Nonempty}, (f i ∩ U)] a := by
simp only [mem_setOf_eq, iUnion_nonempty_self]
_ = ⨆ i ∈ {j | (f j ∩ U).Nonempty}, 𝓝[f i ∩ U] a := nhdsWithin_biUnion hfin _ _
_ ≤ ⨆ i, 𝓝[f i ∩ U] a := iSup₂_le_iSup _ _
_ ≤ ⨆ i, 𝓝[f i] a := iSup_mono fun i ↦ nhdsWithin_mono _ inter_subset_left
#align locally_finite.nhds_within_Union LocallyFinite.nhdsWithin_iUnion
theorem continuousOn_iUnion' {g : X → Y} (hf : LocallyFinite f)
(hc : ∀ i x, x ∈ closure (f i) → ContinuousWithinAt g (f i) x) :
ContinuousOn g (⋃ i, f i) := by
rintro x -
rw [ContinuousWithinAt, hf.nhdsWithin_iUnion, tendsto_iSup]
intro i
by_cases hx : x ∈ closure (f i)
· exact hc i _ hx
· rw [mem_closure_iff_nhdsWithin_neBot, not_neBot] at hx
rw [hx]
exact tendsto_bot
#align locally_finite.continuous_on_Union' LocallyFinite.continuousOn_iUnion'
theorem continuousOn_iUnion {g : X → Y} (hf : LocallyFinite f) (h_cl : ∀ i, IsClosed (f i))
(h_cont : ∀ i, ContinuousOn g (f i)) : ContinuousOn g (⋃ i, f i) :=
hf.continuousOn_iUnion' fun i x hx ↦ h_cont i x <| (h_cl i).closure_subset hx
#align locally_finite.continuous_on_Union LocallyFinite.continuousOn_iUnion
protected theorem continuous' {g : X → Y} (hf : LocallyFinite f) (h_cov : ⋃ i, f i = univ)
(hc : ∀ i x, x ∈ closure (f i) → ContinuousWithinAt g (f i) x) :
Continuous g :=
continuous_iff_continuousOn_univ.2 <| h_cov ▸ hf.continuousOn_iUnion' hc
#align locally_finite.continuous' LocallyFinite.continuous'
protected theorem continuous {g : X → Y} (hf : LocallyFinite f) (h_cov : ⋃ i, f i = univ)
(h_cl : ∀ i, IsClosed (f i)) (h_cont : ∀ i, ContinuousOn g (f i)) :
Continuous g :=
continuous_iff_continuousOn_univ.2 <| h_cov ▸ hf.continuousOn_iUnion h_cl h_cont
#align locally_finite.continuous LocallyFinite.continuous
protected theorem closure (hf : LocallyFinite f) : LocallyFinite fun i => closure (f i) := by
intro x
rcases hf x with ⟨s, hsx, hsf⟩
refine ⟨interior s, interior_mem_nhds.2 hsx, hsf.subset fun i hi => ?_⟩
exact (hi.mono isOpen_interior.closure_inter).of_closure.mono
(inter_subset_inter_right _ interior_subset)
#align locally_finite.closure LocallyFinite.closure
theorem closure_iUnion (h : LocallyFinite f) : closure (⋃ i, f i) = ⋃ i, closure (f i) := by
ext x
simp only [mem_closure_iff_nhdsWithin_neBot, h.nhdsWithin_iUnion, iSup_neBot, mem_iUnion]
#align locally_finite.closure_Union LocallyFinite.closure_iUnion
theorem isClosed_iUnion (hf : LocallyFinite f) (hc : ∀ i, IsClosed (f i)) :
IsClosed (⋃ i, f i) := by
simp only [← closure_eq_iff_isClosed, hf.closure_iUnion, (hc _).closure_eq]
#align locally_finite.is_closed_Union LocallyFinite.isClosed_iUnion
/-- If `f : β → Set α` is a locally finite family of closed sets, then for any `x : α`, the
intersection of the complements to `f i`, `x ∉ f i`, is a neighbourhood of `x`. -/
theorem iInter_compl_mem_nhds (hf : LocallyFinite f) (hc : ∀ i, IsClosed (f i)) (x : X) :
(⋂ (i) (_ : x ∉ f i), (f i)ᶜ) ∈ 𝓝 x := by
refine IsOpen.mem_nhds ?_ (mem_iInter₂.2 fun i => id)
suffices IsClosed (⋃ i : { i // x ∉ f i }, f i) by
rwa [← isOpen_compl_iff, compl_iUnion, iInter_subtype] at this
exact (hf.comp_injective Subtype.val_injective).isClosed_iUnion fun i => hc _
#align locally_finite.Inter_compl_mem_nhds LocallyFinite.iInter_compl_mem_nhds
/-- Let `f : ℕ → Π a, β a` be a sequence of (dependent) functions on a topological space. Suppose
that the family of sets `s n = {x | f (n + 1) x ≠ f n x}` is locally finite. Then there exists a
function `F : Π a, β a` such that for any `x`, we have `f n x = F x` on the product of an infinite
interval `[N, +∞)` and a neighbourhood of `x`.
We formulate the conclusion in terms of the product of filter `Filter.atTop` and `𝓝 x`. -/
theorem exists_forall_eventually_eq_prod {π : X → Sort*} {f : ℕ → ∀ x : X, π x}
(hf : LocallyFinite fun n => { x | f (n + 1) x ≠ f n x }) :
∃ F : ∀ x : X, π x, ∀ x, ∀ᶠ p : ℕ × X in atTop ×ˢ 𝓝 x, f p.1 p.2 = F p.2 := by
choose U hUx hU using hf
choose N hN using fun x => (hU x).bddAbove
replace hN : ∀ (x), ∀ n > N x, ∀ y ∈ U x, f (n + 1) y = f n y :=
fun x n hn y hy => by_contra fun hne => hn.lt.not_le <| hN x ⟨y, hne, hy⟩
replace hN : ∀ (x), ∀ n ≥ N x + 1, ∀ y ∈ U x, f n y = f (N x + 1) y :=
fun x n hn y hy => Nat.le_induction rfl (fun k hle => (hN x _ hle _ hy).trans) n hn
refine ⟨fun x => f (N x + 1) x, fun x => ?_⟩
filter_upwards [Filter.prod_mem_prod (eventually_gt_atTop (N x)) (hUx x)]
rintro ⟨n, y⟩ ⟨hn : N x < n, hy : y ∈ U x⟩
calc
f n y = f (N x + 1) y := hN _ _ hn _ hy
_ = f (max (N x + 1) (N y + 1)) y := (hN _ _ (le_max_left _ _) _ hy).symm
_ = f (N y + 1) y := hN _ _ (le_max_right _ _) _ (mem_of_mem_nhds <| hUx y)
#align locally_finite.exists_forall_eventually_eq_prod LocallyFinite.exists_forall_eventually_eq_prod
/-- Let `f : ℕ → Π a, β a` be a sequence of (dependent) functions on a topological space. Suppose
that the family of sets `s n = {x | f (n + 1) x ≠ f n x}` is locally finite. Then there exists a
function `F : Π a, β a` such that for any `x`, for sufficiently large values of `n`, we have
`f n y = F y` in a neighbourhood of `x`. -/
theorem exists_forall_eventually_atTop_eventually_eq' {π : X → Sort*} {f : ℕ → ∀ x : X, π x}
(hf : LocallyFinite fun n => { x | f (n + 1) x ≠ f n x }) :
∃ F : ∀ x : X, π x, ∀ x, ∀ᶠ n : ℕ in atTop, ∀ᶠ y : X in 𝓝 x, f n y = F y :=
hf.exists_forall_eventually_eq_prod.imp fun _F hF x => (hF x).curry
#align locally_finite.exists_forall_eventually_at_top_eventually_eq' LocallyFinite.exists_forall_eventually_atTop_eventually_eq'
/-- Let `f : ℕ → α → β` be a sequence of functions on a topological space. Suppose
that the family of sets `s n = {x | f (n + 1) x ≠ f n x}` is locally finite. Then there exists a
function `F : α → β` such that for any `x`, for sufficiently large values of `n`, we have
`f n =ᶠ[𝓝 x] F`. -/
theorem exists_forall_eventually_atTop_eventuallyEq {f : ℕ → X → α}
(hf : LocallyFinite fun n => { x | f (n + 1) x ≠ f n x }) :
∃ F : X → α, ∀ x, ∀ᶠ n : ℕ in atTop, f n =ᶠ[𝓝 x] F :=
hf.exists_forall_eventually_atTop_eventually_eq'
#align locally_finite.exists_forall_eventually_at_top_eventually_eq LocallyFinite.exists_forall_eventually_atTop_eventuallyEq
theorem preimage_continuous {g : Y → X} (hf : LocallyFinite f) (hg : Continuous g) :
LocallyFinite (g ⁻¹' f ·) := fun x =>
let ⟨s, hsx, hs⟩ := hf (g x)
⟨g ⁻¹' s, hg.continuousAt hsx, hs.subset fun _ ⟨y, hy⟩ => ⟨g y, hy⟩⟩
#align locally_finite.preimage_continuous LocallyFinite.preimage_continuous
theorem prod_right (hf : LocallyFinite f) (g : ι → Set Y) : LocallyFinite (fun i ↦ f i ×ˢ g i) :=
(hf.preimage_continuous continuous_fst).subset fun _ ↦ prod_subset_preimage_fst _ _
theorem prod_left {g : ι → Set Y} (hg : LocallyFinite g) (f : ι → Set X) :
LocallyFinite (fun i ↦ f i ×ˢ g i) :=
(hg.preimage_continuous continuous_snd).subset fun _ ↦ prod_subset_preimage_snd _ _
end LocallyFinite
@[simp]
theorem Equiv.locallyFinite_comp_iff (e : ι' ≃ ι) : LocallyFinite (f ∘ e) ↔ LocallyFinite f :=
⟨fun h => by simpa only [(· ∘ ·), e.apply_symm_apply] using h.comp_injective e.symm.injective,
fun h => h.comp_injective e.injective⟩
#align equiv.locally_finite_comp_iff Equiv.locallyFinite_comp_iff
theorem locallyFinite_sum {f : Sum ι ι' → Set X} :
LocallyFinite f ↔ LocallyFinite (f ∘ Sum.inl) ∧ LocallyFinite (f ∘ Sum.inr) := by
simp only [locallyFinite_iff_smallSets, ← forall_and, ← finite_preimage_inl_and_inr,
preimage_setOf_eq, (· ∘ ·), eventually_and]
#align locally_finite_sum locallyFinite_sum
theorem LocallyFinite.sum_elim {g : ι' → Set X} (hf : LocallyFinite f) (hg : LocallyFinite g) :
LocallyFinite (Sum.elim f g) :=
locallyFinite_sum.mpr ⟨hf, hg⟩
#align locally_finite.sum_elim LocallyFinite.sum_elim
theorem locallyFinite_option {f : Option ι → Set X} :
LocallyFinite f ↔ LocallyFinite (f ∘ some) := by
rw [← (Equiv.optionEquivSumPUnit.{_, 0} ι).symm.locallyFinite_comp_iff, locallyFinite_sum]
simp only [locallyFinite_of_finite, and_true]
rfl
#align locally_finite_option locallyFinite_option
theorem LocallyFinite.option_elim' (hf : LocallyFinite f) (s : Set X) :
LocallyFinite (Option.elim' s f) :=
locallyFinite_option.2 hf
#align locally_finite.option_elim LocallyFinite.option_elim'
| Mathlib/Topology/LocallyFinite.lean | 237 | 242 | theorem LocallyFinite.eventually_subset {s : ι → Set X}
(hs : LocallyFinite s) (hs' : ∀ i, IsClosed (s i)) (x : X) :
∀ᶠ y in 𝓝 x, {i | y ∈ s i} ⊆ {i | x ∈ s i} := by |
filter_upwards [hs.iInter_compl_mem_nhds hs' x] with y hy i hi
simp only [mem_iInter, mem_compl_iff] at hy
exact not_imp_not.mp (hy i) hi
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Order.Ring.Defs
import Mathlib.Algebra.Group.Int
import Mathlib.Data.Nat.Dist
import Mathlib.Data.Ordmap.Ordnode
import Mathlib.Tactic.Abel
import Mathlib.Tactic.Linarith
#align_import data.ordmap.ordset from "leanprover-community/mathlib"@"47b51515e69f59bca5cf34ef456e6000fe205a69"
/-!
# Verification of the `Ordnode α` datatype
This file proves the correctness of the operations in `Data.Ordmap.Ordnode`.
The public facing version is the type `Ordset α`, which is a wrapper around
`Ordnode α` which includes the correctness invariant of the type, and it exposes
parallel operations like `insert` as functions on `Ordset` that do the same
thing but bundle the correctness proofs. The advantage is that it is possible
to, for example, prove that the result of `find` on `insert` will actually find
the element, while `Ordnode` cannot guarantee this if the input tree did not
satisfy the type invariants.
## Main definitions
* `Ordset α`: A well formed set of values of type `α`
## Implementation notes
The majority of this file is actually in the `Ordnode` namespace, because we first
have to prove the correctness of all the operations (and defining what correctness
means here is actually somewhat subtle). So all the actual `Ordset` operations are
at the very end, once we have all the theorems.
An `Ordnode α` is an inductive type which describes a tree which stores the `size` at
internal nodes. The correctness invariant of an `Ordnode α` is:
* `Ordnode.Sized t`: All internal `size` fields must match the actual measured
size of the tree. (This is not hard to satisfy.)
* `Ordnode.Balanced t`: Unless the tree has the form `()` or `((a) b)` or `(a (b))`
(that is, nil or a single singleton subtree), the two subtrees must satisfy
`size l ≤ δ * size r` and `size r ≤ δ * size l`, where `δ := 3` is a global
parameter of the data structure (and this property must hold recursively at subtrees).
This is why we say this is a "size balanced tree" data structure.
* `Ordnode.Bounded lo hi t`: The members of the tree must be in strictly increasing order,
meaning that if `a` is in the left subtree and `b` is the root, then `a ≤ b` and
`¬ (b ≤ a)`. We enforce this using `Ordnode.Bounded` which includes also a global
upper and lower bound.
Because the `Ordnode` file was ported from Haskell, the correctness invariants of some
of the functions have not been spelled out, and some theorems like
`Ordnode.Valid'.balanceL_aux` show very intricate assumptions on the sizes,
which may need to be revised if it turns out some operations violate these assumptions,
because there is a decent amount of slop in the actual data structure invariants, so the
theorem will go through with multiple choices of assumption.
**Note:** This file is incomplete, in the sense that the intent is to have verified
versions and lemmas about all the definitions in `Ordnode.lean`, but at the moment only
a few operations are verified (the hard part should be out of the way, but still).
Contributors are encouraged to pick this up and finish the job, if it appeals to you.
## Tags
ordered map, ordered set, data structure, verified programming
-/
variable {α : Type*}
namespace Ordnode
/-! ### delta and ratio -/
theorem not_le_delta {s} (H : 1 ≤ s) : ¬s ≤ delta * 0 :=
not_le_of_gt H
#align ordnode.not_le_delta Ordnode.not_le_delta
theorem delta_lt_false {a b : ℕ} (h₁ : delta * a < b) (h₂ : delta * b < a) : False :=
not_le_of_lt (lt_trans ((mul_lt_mul_left (by decide)).2 h₁) h₂) <| by
simpa [mul_assoc] using Nat.mul_le_mul_right a (by decide : 1 ≤ delta * delta)
#align ordnode.delta_lt_false Ordnode.delta_lt_false
/-! ### `singleton` -/
/-! ### `size` and `empty` -/
/-- O(n). Computes the actual number of elements in the set, ignoring the cached `size` field. -/
def realSize : Ordnode α → ℕ
| nil => 0
| node _ l _ r => realSize l + realSize r + 1
#align ordnode.real_size Ordnode.realSize
/-! ### `Sized` -/
/-- The `Sized` property asserts that all the `size` fields in nodes match the actual size of the
respective subtrees. -/
def Sized : Ordnode α → Prop
| nil => True
| node s l _ r => s = size l + size r + 1 ∧ Sized l ∧ Sized r
#align ordnode.sized Ordnode.Sized
theorem Sized.node' {l x r} (hl : @Sized α l) (hr : Sized r) : Sized (node' l x r) :=
⟨rfl, hl, hr⟩
#align ordnode.sized.node' Ordnode.Sized.node'
theorem Sized.eq_node' {s l x r} (h : @Sized α (node s l x r)) : node s l x r = .node' l x r := by
rw [h.1]
#align ordnode.sized.eq_node' Ordnode.Sized.eq_node'
theorem Sized.size_eq {s l x r} (H : Sized (@node α s l x r)) :
size (@node α s l x r) = size l + size r + 1 :=
H.1
#align ordnode.sized.size_eq Ordnode.Sized.size_eq
@[elab_as_elim]
theorem Sized.induction {t} (hl : @Sized α t) {C : Ordnode α → Prop} (H0 : C nil)
(H1 : ∀ l x r, C l → C r → C (.node' l x r)) : C t := by
induction t with
| nil => exact H0
| node _ _ _ _ t_ih_l t_ih_r =>
rw [hl.eq_node']
exact H1 _ _ _ (t_ih_l hl.2.1) (t_ih_r hl.2.2)
#align ordnode.sized.induction Ordnode.Sized.induction
theorem size_eq_realSize : ∀ {t : Ordnode α}, Sized t → size t = realSize t
| nil, _ => rfl
| node s l x r, ⟨h₁, h₂, h₃⟩ => by
rw [size, h₁, size_eq_realSize h₂, size_eq_realSize h₃]; rfl
#align ordnode.size_eq_real_size Ordnode.size_eq_realSize
@[simp]
theorem Sized.size_eq_zero {t : Ordnode α} (ht : Sized t) : size t = 0 ↔ t = nil := by
cases t <;> [simp;simp [ht.1]]
#align ordnode.sized.size_eq_zero Ordnode.Sized.size_eq_zero
theorem Sized.pos {s l x r} (h : Sized (@node α s l x r)) : 0 < s := by
rw [h.1]; apply Nat.le_add_left
#align ordnode.sized.pos Ordnode.Sized.pos
/-! `dual` -/
theorem dual_dual : ∀ t : Ordnode α, dual (dual t) = t
| nil => rfl
| node s l x r => by rw [dual, dual, dual_dual l, dual_dual r]
#align ordnode.dual_dual Ordnode.dual_dual
@[simp]
theorem size_dual (t : Ordnode α) : size (dual t) = size t := by cases t <;> rfl
#align ordnode.size_dual Ordnode.size_dual
/-! `Balanced` -/
/-- The `BalancedSz l r` asserts that a hypothetical tree with children of sizes `l` and `r` is
balanced: either `l ≤ δ * r` and `r ≤ δ * r`, or the tree is trivial with a singleton on one side
and nothing on the other. -/
def BalancedSz (l r : ℕ) : Prop :=
l + r ≤ 1 ∨ l ≤ delta * r ∧ r ≤ delta * l
#align ordnode.balanced_sz Ordnode.BalancedSz
instance BalancedSz.dec : DecidableRel BalancedSz := fun _ _ => Or.decidable
#align ordnode.balanced_sz.dec Ordnode.BalancedSz.dec
/-- The `Balanced t` asserts that the tree `t` satisfies the balance invariants
(at every level). -/
def Balanced : Ordnode α → Prop
| nil => True
| node _ l _ r => BalancedSz (size l) (size r) ∧ Balanced l ∧ Balanced r
#align ordnode.balanced Ordnode.Balanced
instance Balanced.dec : DecidablePred (@Balanced α)
| nil => by
unfold Balanced
infer_instance
| node _ l _ r => by
unfold Balanced
haveI := Balanced.dec l
haveI := Balanced.dec r
infer_instance
#align ordnode.balanced.dec Ordnode.Balanced.dec
@[symm]
theorem BalancedSz.symm {l r : ℕ} : BalancedSz l r → BalancedSz r l :=
Or.imp (by rw [add_comm]; exact id) And.symm
#align ordnode.balanced_sz.symm Ordnode.BalancedSz.symm
theorem balancedSz_zero {l : ℕ} : BalancedSz l 0 ↔ l ≤ 1 := by
simp (config := { contextual := true }) [BalancedSz]
#align ordnode.balanced_sz_zero Ordnode.balancedSz_zero
theorem balancedSz_up {l r₁ r₂ : ℕ} (h₁ : r₁ ≤ r₂) (h₂ : l + r₂ ≤ 1 ∨ r₂ ≤ delta * l)
(H : BalancedSz l r₁) : BalancedSz l r₂ := by
refine or_iff_not_imp_left.2 fun h => ?_
refine ⟨?_, h₂.resolve_left h⟩
cases H with
| inl H =>
cases r₂
· cases h (le_trans (Nat.add_le_add_left (Nat.zero_le _) _) H)
· exact le_trans (le_trans (Nat.le_add_right _ _) H) (Nat.le_add_left 1 _)
| inr H =>
exact le_trans H.1 (Nat.mul_le_mul_left _ h₁)
#align ordnode.balanced_sz_up Ordnode.balancedSz_up
theorem balancedSz_down {l r₁ r₂ : ℕ} (h₁ : r₁ ≤ r₂) (h₂ : l + r₂ ≤ 1 ∨ l ≤ delta * r₁)
(H : BalancedSz l r₂) : BalancedSz l r₁ :=
have : l + r₂ ≤ 1 → BalancedSz l r₁ := fun H => Or.inl (le_trans (Nat.add_le_add_left h₁ _) H)
Or.casesOn H this fun H => Or.casesOn h₂ this fun h₂ => Or.inr ⟨h₂, le_trans h₁ H.2⟩
#align ordnode.balanced_sz_down Ordnode.balancedSz_down
theorem Balanced.dual : ∀ {t : Ordnode α}, Balanced t → Balanced (dual t)
| nil, _ => ⟨⟩
| node _ l _ r, ⟨b, bl, br⟩ => ⟨by rw [size_dual, size_dual]; exact b.symm, br.dual, bl.dual⟩
#align ordnode.balanced.dual Ordnode.Balanced.dual
/-! ### `rotate` and `balance` -/
/-- Build a tree from three nodes, left associated (ignores the invariants). -/
def node3L (l : Ordnode α) (x : α) (m : Ordnode α) (y : α) (r : Ordnode α) : Ordnode α :=
node' (node' l x m) y r
#align ordnode.node3_l Ordnode.node3L
/-- Build a tree from three nodes, right associated (ignores the invariants). -/
def node3R (l : Ordnode α) (x : α) (m : Ordnode α) (y : α) (r : Ordnode α) : Ordnode α :=
node' l x (node' m y r)
#align ordnode.node3_r Ordnode.node3R
/-- Build a tree from three nodes, with `a () b -> (a ()) b` and `a (b c) d -> ((a b) (c d))`. -/
def node4L : Ordnode α → α → Ordnode α → α → Ordnode α → Ordnode α
| l, x, node _ ml y mr, z, r => node' (node' l x ml) y (node' mr z r)
| l, x, nil, z, r => node3L l x nil z r
#align ordnode.node4_l Ordnode.node4L
-- should not happen
/-- Build a tree from three nodes, with `a () b -> a (() b)` and `a (b c) d -> ((a b) (c d))`. -/
def node4R : Ordnode α → α → Ordnode α → α → Ordnode α → Ordnode α
| l, x, node _ ml y mr, z, r => node' (node' l x ml) y (node' mr z r)
| l, x, nil, z, r => node3R l x nil z r
#align ordnode.node4_r Ordnode.node4R
-- should not happen
/-- Concatenate two nodes, performing a left rotation `x (y z) -> ((x y) z)`
if balance is upset. -/
def rotateL : Ordnode α → α → Ordnode α → Ordnode α
| l, x, node _ m y r => if size m < ratio * size r then node3L l x m y r else node4L l x m y r
| l, x, nil => node' l x nil
#align ordnode.rotate_l Ordnode.rotateL
-- Porting note (#11467): during the port we marked these lemmas with `@[eqns]`
-- to emulate the old Lean 3 behaviour.
theorem rotateL_node (l : Ordnode α) (x : α) (sz : ℕ) (m : Ordnode α) (y : α) (r : Ordnode α) :
rotateL l x (node sz m y r) =
if size m < ratio * size r then node3L l x m y r else node4L l x m y r :=
rfl
theorem rotateL_nil (l : Ordnode α) (x : α) : rotateL l x nil = node' l x nil :=
rfl
-- should not happen
/-- Concatenate two nodes, performing a right rotation `(x y) z -> (x (y z))`
if balance is upset. -/
def rotateR : Ordnode α → α → Ordnode α → Ordnode α
| node _ l x m, y, r => if size m < ratio * size l then node3R l x m y r else node4R l x m y r
| nil, y, r => node' nil y r
#align ordnode.rotate_r Ordnode.rotateR
-- Porting note (#11467): during the port we marked these lemmas with `@[eqns]`
-- to emulate the old Lean 3 behaviour.
theorem rotateR_node (sz : ℕ) (l : Ordnode α) (x : α) (m : Ordnode α) (y : α) (r : Ordnode α) :
rotateR (node sz l x m) y r =
if size m < ratio * size l then node3R l x m y r else node4R l x m y r :=
rfl
theorem rotateR_nil (y : α) (r : Ordnode α) : rotateR nil y r = node' nil y r :=
rfl
-- should not happen
/-- A left balance operation. This will rebalance a concatenation, assuming the original nodes are
not too far from balanced. -/
def balanceL' (l : Ordnode α) (x : α) (r : Ordnode α) : Ordnode α :=
if size l + size r ≤ 1 then node' l x r
else if size l > delta * size r then rotateR l x r else node' l x r
#align ordnode.balance_l' Ordnode.balanceL'
/-- A right balance operation. This will rebalance a concatenation, assuming the original nodes are
not too far from balanced. -/
def balanceR' (l : Ordnode α) (x : α) (r : Ordnode α) : Ordnode α :=
if size l + size r ≤ 1 then node' l x r
else if size r > delta * size l then rotateL l x r else node' l x r
#align ordnode.balance_r' Ordnode.balanceR'
/-- The full balance operation. This is the same as `balance`, but with less manual inlining.
It is somewhat easier to work with this version in proofs. -/
def balance' (l : Ordnode α) (x : α) (r : Ordnode α) : Ordnode α :=
if size l + size r ≤ 1 then node' l x r
else
if size r > delta * size l then rotateL l x r
else if size l > delta * size r then rotateR l x r else node' l x r
#align ordnode.balance' Ordnode.balance'
theorem dual_node' (l : Ordnode α) (x : α) (r : Ordnode α) :
dual (node' l x r) = node' (dual r) x (dual l) := by simp [node', add_comm]
#align ordnode.dual_node' Ordnode.dual_node'
theorem dual_node3L (l : Ordnode α) (x : α) (m : Ordnode α) (y : α) (r : Ordnode α) :
dual (node3L l x m y r) = node3R (dual r) y (dual m) x (dual l) := by
simp [node3L, node3R, dual_node', add_comm]
#align ordnode.dual_node3_l Ordnode.dual_node3L
theorem dual_node3R (l : Ordnode α) (x : α) (m : Ordnode α) (y : α) (r : Ordnode α) :
dual (node3R l x m y r) = node3L (dual r) y (dual m) x (dual l) := by
simp [node3L, node3R, dual_node', add_comm]
#align ordnode.dual_node3_r Ordnode.dual_node3R
theorem dual_node4L (l : Ordnode α) (x : α) (m : Ordnode α) (y : α) (r : Ordnode α) :
dual (node4L l x m y r) = node4R (dual r) y (dual m) x (dual l) := by
cases m <;> simp [node4L, node4R, node3R, dual_node3L, dual_node', add_comm]
#align ordnode.dual_node4_l Ordnode.dual_node4L
theorem dual_node4R (l : Ordnode α) (x : α) (m : Ordnode α) (y : α) (r : Ordnode α) :
dual (node4R l x m y r) = node4L (dual r) y (dual m) x (dual l) := by
cases m <;> simp [node4L, node4R, node3L, dual_node3R, dual_node', add_comm]
#align ordnode.dual_node4_r Ordnode.dual_node4R
theorem dual_rotateL (l : Ordnode α) (x : α) (r : Ordnode α) :
dual (rotateL l x r) = rotateR (dual r) x (dual l) := by
cases r <;> simp [rotateL, rotateR, dual_node']; split_ifs <;>
simp [dual_node3L, dual_node4L, node3R, add_comm]
#align ordnode.dual_rotate_l Ordnode.dual_rotateL
theorem dual_rotateR (l : Ordnode α) (x : α) (r : Ordnode α) :
dual (rotateR l x r) = rotateL (dual r) x (dual l) := by
rw [← dual_dual (rotateL _ _ _), dual_rotateL, dual_dual, dual_dual]
#align ordnode.dual_rotate_r Ordnode.dual_rotateR
theorem dual_balance' (l : Ordnode α) (x : α) (r : Ordnode α) :
dual (balance' l x r) = balance' (dual r) x (dual l) := by
simp [balance', add_comm]; split_ifs with h h_1 h_2 <;>
simp [dual_node', dual_rotateL, dual_rotateR, add_comm]
cases delta_lt_false h_1 h_2
#align ordnode.dual_balance' Ordnode.dual_balance'
theorem dual_balanceL (l : Ordnode α) (x : α) (r : Ordnode α) :
dual (balanceL l x r) = balanceR (dual r) x (dual l) := by
unfold balanceL balanceR
cases' r with rs rl rx rr
· cases' l with ls ll lx lr; · rfl
cases' ll with lls lll llx llr <;> cases' lr with lrs lrl lrx lrr <;> dsimp only [dual, id] <;>
try rfl
split_ifs with h <;> repeat simp [h, add_comm]
· cases' l with ls ll lx lr; · rfl
dsimp only [dual, id]
split_ifs; swap; · simp [add_comm]
cases' ll with lls lll llx llr <;> cases' lr with lrs lrl lrx lrr <;> try rfl
dsimp only [dual, id]
split_ifs with h <;> simp [h, add_comm]
#align ordnode.dual_balance_l Ordnode.dual_balanceL
theorem dual_balanceR (l : Ordnode α) (x : α) (r : Ordnode α) :
dual (balanceR l x r) = balanceL (dual r) x (dual l) := by
rw [← dual_dual (balanceL _ _ _), dual_balanceL, dual_dual, dual_dual]
#align ordnode.dual_balance_r Ordnode.dual_balanceR
theorem Sized.node3L {l x m y r} (hl : @Sized α l) (hm : Sized m) (hr : Sized r) :
Sized (node3L l x m y r) :=
(hl.node' hm).node' hr
#align ordnode.sized.node3_l Ordnode.Sized.node3L
theorem Sized.node3R {l x m y r} (hl : @Sized α l) (hm : Sized m) (hr : Sized r) :
Sized (node3R l x m y r) :=
hl.node' (hm.node' hr)
#align ordnode.sized.node3_r Ordnode.Sized.node3R
theorem Sized.node4L {l x m y r} (hl : @Sized α l) (hm : Sized m) (hr : Sized r) :
Sized (node4L l x m y r) := by
cases m <;> [exact (hl.node' hm).node' hr; exact (hl.node' hm.2.1).node' (hm.2.2.node' hr)]
#align ordnode.sized.node4_l Ordnode.Sized.node4L
theorem node3L_size {l x m y r} : size (@node3L α l x m y r) = size l + size m + size r + 2 := by
dsimp [node3L, node', size]; rw [add_right_comm _ 1]
#align ordnode.node3_l_size Ordnode.node3L_size
theorem node3R_size {l x m y r} : size (@node3R α l x m y r) = size l + size m + size r + 2 := by
dsimp [node3R, node', size]; rw [← add_assoc, ← add_assoc]
#align ordnode.node3_r_size Ordnode.node3R_size
theorem node4L_size {l x m y r} (hm : Sized m) :
size (@node4L α l x m y r) = size l + size m + size r + 2 := by
cases m <;> simp [node4L, node3L, node'] <;> [abel; (simp [size, hm.1]; abel)]
#align ordnode.node4_l_size Ordnode.node4L_size
theorem Sized.dual : ∀ {t : Ordnode α}, Sized t → Sized (dual t)
| nil, _ => ⟨⟩
| node _ l _ r, ⟨rfl, sl, sr⟩ => ⟨by simp [size_dual, add_comm], Sized.dual sr, Sized.dual sl⟩
#align ordnode.sized.dual Ordnode.Sized.dual
theorem Sized.dual_iff {t : Ordnode α} : Sized (.dual t) ↔ Sized t :=
⟨fun h => by rw [← dual_dual t]; exact h.dual, Sized.dual⟩
#align ordnode.sized.dual_iff Ordnode.Sized.dual_iff
theorem Sized.rotateL {l x r} (hl : @Sized α l) (hr : Sized r) : Sized (rotateL l x r) := by
cases r; · exact hl.node' hr
rw [Ordnode.rotateL_node]; split_ifs
· exact hl.node3L hr.2.1 hr.2.2
· exact hl.node4L hr.2.1 hr.2.2
#align ordnode.sized.rotate_l Ordnode.Sized.rotateL
theorem Sized.rotateR {l x r} (hl : @Sized α l) (hr : Sized r) : Sized (rotateR l x r) :=
Sized.dual_iff.1 <| by rw [dual_rotateR]; exact hr.dual.rotateL hl.dual
#align ordnode.sized.rotate_r Ordnode.Sized.rotateR
theorem Sized.rotateL_size {l x r} (hm : Sized r) :
size (@Ordnode.rotateL α l x r) = size l + size r + 1 := by
cases r <;> simp [Ordnode.rotateL]
simp only [hm.1]
split_ifs <;> simp [node3L_size, node4L_size hm.2.1] <;> abel
#align ordnode.sized.rotate_l_size Ordnode.Sized.rotateL_size
theorem Sized.rotateR_size {l x r} (hl : Sized l) :
size (@Ordnode.rotateR α l x r) = size l + size r + 1 := by
rw [← size_dual, dual_rotateR, hl.dual.rotateL_size, size_dual, size_dual, add_comm (size l)]
#align ordnode.sized.rotate_r_size Ordnode.Sized.rotateR_size
theorem Sized.balance' {l x r} (hl : @Sized α l) (hr : Sized r) : Sized (balance' l x r) := by
unfold balance'; split_ifs
· exact hl.node' hr
· exact hl.rotateL hr
· exact hl.rotateR hr
· exact hl.node' hr
#align ordnode.sized.balance' Ordnode.Sized.balance'
theorem size_balance' {l x r} (hl : @Sized α l) (hr : Sized r) :
size (@balance' α l x r) = size l + size r + 1 := by
unfold balance'; split_ifs
· rfl
· exact hr.rotateL_size
· exact hl.rotateR_size
· rfl
#align ordnode.size_balance' Ordnode.size_balance'
/-! ## `All`, `Any`, `Emem`, `Amem` -/
theorem All.imp {P Q : α → Prop} (H : ∀ a, P a → Q a) : ∀ {t}, All P t → All Q t
| nil, _ => ⟨⟩
| node _ _ _ _, ⟨h₁, h₂, h₃⟩ => ⟨h₁.imp H, H _ h₂, h₃.imp H⟩
#align ordnode.all.imp Ordnode.All.imp
theorem Any.imp {P Q : α → Prop} (H : ∀ a, P a → Q a) : ∀ {t}, Any P t → Any Q t
| nil => id
| node _ _ _ _ => Or.imp (Any.imp H) <| Or.imp (H _) (Any.imp H)
#align ordnode.any.imp Ordnode.Any.imp
theorem all_singleton {P : α → Prop} {x : α} : All P (singleton x) ↔ P x :=
⟨fun h => h.2.1, fun h => ⟨⟨⟩, h, ⟨⟩⟩⟩
#align ordnode.all_singleton Ordnode.all_singleton
theorem any_singleton {P : α → Prop} {x : α} : Any P (singleton x) ↔ P x :=
⟨by rintro (⟨⟨⟩⟩ | h | ⟨⟨⟩⟩); exact h, fun h => Or.inr (Or.inl h)⟩
#align ordnode.any_singleton Ordnode.any_singleton
theorem all_dual {P : α → Prop} : ∀ {t : Ordnode α}, All P (dual t) ↔ All P t
| nil => Iff.rfl
| node _ _l _x _r =>
⟨fun ⟨hr, hx, hl⟩ => ⟨all_dual.1 hl, hx, all_dual.1 hr⟩, fun ⟨hl, hx, hr⟩ =>
⟨all_dual.2 hr, hx, all_dual.2 hl⟩⟩
#align ordnode.all_dual Ordnode.all_dual
theorem all_iff_forall {P : α → Prop} : ∀ {t}, All P t ↔ ∀ x, Emem x t → P x
| nil => (iff_true_intro <| by rintro _ ⟨⟩).symm
| node _ l x r => by simp [All, Emem, all_iff_forall, Any, or_imp, forall_and]
#align ordnode.all_iff_forall Ordnode.all_iff_forall
theorem any_iff_exists {P : α → Prop} : ∀ {t}, Any P t ↔ ∃ x, Emem x t ∧ P x
| nil => ⟨by rintro ⟨⟩, by rintro ⟨_, ⟨⟩, _⟩⟩
| node _ l x r => by simp only [Emem]; simp [Any, any_iff_exists, or_and_right, exists_or]
#align ordnode.any_iff_exists Ordnode.any_iff_exists
theorem emem_iff_all {x : α} {t} : Emem x t ↔ ∀ P, All P t → P x :=
⟨fun h _ al => all_iff_forall.1 al _ h, fun H => H _ <| all_iff_forall.2 fun _ => id⟩
#align ordnode.emem_iff_all Ordnode.emem_iff_all
theorem all_node' {P l x r} : @All α P (node' l x r) ↔ All P l ∧ P x ∧ All P r :=
Iff.rfl
#align ordnode.all_node' Ordnode.all_node'
theorem all_node3L {P l x m y r} :
@All α P (node3L l x m y r) ↔ All P l ∧ P x ∧ All P m ∧ P y ∧ All P r := by
simp [node3L, all_node', and_assoc]
#align ordnode.all_node3_l Ordnode.all_node3L
theorem all_node3R {P l x m y r} :
@All α P (node3R l x m y r) ↔ All P l ∧ P x ∧ All P m ∧ P y ∧ All P r :=
Iff.rfl
#align ordnode.all_node3_r Ordnode.all_node3R
theorem all_node4L {P l x m y r} :
@All α P (node4L l x m y r) ↔ All P l ∧ P x ∧ All P m ∧ P y ∧ All P r := by
cases m <;> simp [node4L, all_node', All, all_node3L, and_assoc]
#align ordnode.all_node4_l Ordnode.all_node4L
theorem all_node4R {P l x m y r} :
@All α P (node4R l x m y r) ↔ All P l ∧ P x ∧ All P m ∧ P y ∧ All P r := by
cases m <;> simp [node4R, all_node', All, all_node3R, and_assoc]
#align ordnode.all_node4_r Ordnode.all_node4R
theorem all_rotateL {P l x r} : @All α P (rotateL l x r) ↔ All P l ∧ P x ∧ All P r := by
cases r <;> simp [rotateL, all_node']; split_ifs <;>
simp [all_node3L, all_node4L, All, and_assoc]
#align ordnode.all_rotate_l Ordnode.all_rotateL
theorem all_rotateR {P l x r} : @All α P (rotateR l x r) ↔ All P l ∧ P x ∧ All P r := by
rw [← all_dual, dual_rotateR, all_rotateL]; simp [all_dual, and_comm, and_left_comm, and_assoc]
#align ordnode.all_rotate_r Ordnode.all_rotateR
theorem all_balance' {P l x r} : @All α P (balance' l x r) ↔ All P l ∧ P x ∧ All P r := by
rw [balance']; split_ifs <;> simp [all_node', all_rotateL, all_rotateR]
#align ordnode.all_balance' Ordnode.all_balance'
/-! ### `toList` -/
theorem foldr_cons_eq_toList : ∀ (t : Ordnode α) (r : List α), t.foldr List.cons r = toList t ++ r
| nil, r => rfl
| node _ l x r, r' => by
rw [foldr, foldr_cons_eq_toList l, foldr_cons_eq_toList r, ← List.cons_append,
← List.append_assoc, ← foldr_cons_eq_toList l]; rfl
#align ordnode.foldr_cons_eq_to_list Ordnode.foldr_cons_eq_toList
@[simp]
theorem toList_nil : toList (@nil α) = [] :=
rfl
#align ordnode.to_list_nil Ordnode.toList_nil
@[simp]
theorem toList_node (s l x r) : toList (@node α s l x r) = toList l ++ x :: toList r := by
rw [toList, foldr, foldr_cons_eq_toList]; rfl
#align ordnode.to_list_node Ordnode.toList_node
theorem emem_iff_mem_toList {x : α} {t} : Emem x t ↔ x ∈ toList t := by
unfold Emem; induction t <;> simp [Any, *, or_assoc]
#align ordnode.emem_iff_mem_to_list Ordnode.emem_iff_mem_toList
theorem length_toList' : ∀ t : Ordnode α, (toList t).length = t.realSize
| nil => rfl
| node _ l _ r => by
rw [toList_node, List.length_append, List.length_cons, length_toList' l,
length_toList' r]; rfl
#align ordnode.length_to_list' Ordnode.length_toList'
theorem length_toList {t : Ordnode α} (h : Sized t) : (toList t).length = t.size := by
rw [length_toList', size_eq_realSize h]
#align ordnode.length_to_list Ordnode.length_toList
theorem equiv_iff {t₁ t₂ : Ordnode α} (h₁ : Sized t₁) (h₂ : Sized t₂) :
Equiv t₁ t₂ ↔ toList t₁ = toList t₂ :=
and_iff_right_of_imp fun h => by rw [← length_toList h₁, h, length_toList h₂]
#align ordnode.equiv_iff Ordnode.equiv_iff
/-! ### `mem` -/
theorem pos_size_of_mem [LE α] [@DecidableRel α (· ≤ ·)] {x : α} {t : Ordnode α} (h : Sized t)
(h_mem : x ∈ t) : 0 < size t := by cases t; · { contradiction }; · { simp [h.1] }
#align ordnode.pos_size_of_mem Ordnode.pos_size_of_mem
/-! ### `(find/erase/split)(Min/Max)` -/
theorem findMin'_dual : ∀ (t) (x : α), findMin' (dual t) x = findMax' x t
| nil, _ => rfl
| node _ _ x r, _ => findMin'_dual r x
#align ordnode.find_min'_dual Ordnode.findMin'_dual
theorem findMax'_dual (t) (x : α) : findMax' x (dual t) = findMin' t x := by
rw [← findMin'_dual, dual_dual]
#align ordnode.find_max'_dual Ordnode.findMax'_dual
theorem findMin_dual : ∀ t : Ordnode α, findMin (dual t) = findMax t
| nil => rfl
| node _ _ _ _ => congr_arg some <| findMin'_dual _ _
#align ordnode.find_min_dual Ordnode.findMin_dual
theorem findMax_dual (t : Ordnode α) : findMax (dual t) = findMin t := by
rw [← findMin_dual, dual_dual]
#align ordnode.find_max_dual Ordnode.findMax_dual
theorem dual_eraseMin : ∀ t : Ordnode α, dual (eraseMin t) = eraseMax (dual t)
| nil => rfl
| node _ nil x r => rfl
| node _ (node sz l' y r') x r => by
rw [eraseMin, dual_balanceR, dual_eraseMin (node sz l' y r'), dual, dual, dual, eraseMax]
#align ordnode.dual_erase_min Ordnode.dual_eraseMin
theorem dual_eraseMax (t : Ordnode α) : dual (eraseMax t) = eraseMin (dual t) := by
rw [← dual_dual (eraseMin _), dual_eraseMin, dual_dual]
#align ordnode.dual_erase_max Ordnode.dual_eraseMax
theorem splitMin_eq :
∀ (s l) (x : α) (r), splitMin' l x r = (findMin' l x, eraseMin (node s l x r))
| _, nil, x, r => rfl
| _, node ls ll lx lr, x, r => by rw [splitMin', splitMin_eq ls ll lx lr, findMin', eraseMin]
#align ordnode.split_min_eq Ordnode.splitMin_eq
theorem splitMax_eq :
∀ (s l) (x : α) (r), splitMax' l x r = (eraseMax (node s l x r), findMax' x r)
| _, l, x, nil => rfl
| _, l, x, node ls ll lx lr => by rw [splitMax', splitMax_eq ls ll lx lr, findMax', eraseMax]
#align ordnode.split_max_eq Ordnode.splitMax_eq
-- @[elab_as_elim] -- Porting note: unexpected eliminator resulting type
theorem findMin'_all {P : α → Prop} : ∀ (t) (x : α), All P t → P x → P (findMin' t x)
| nil, _x, _, hx => hx
| node _ ll lx _, _, ⟨h₁, h₂, _⟩, _ => findMin'_all ll lx h₁ h₂
#align ordnode.find_min'_all Ordnode.findMin'_all
-- @[elab_as_elim] -- Porting note: unexpected eliminator resulting type
theorem findMax'_all {P : α → Prop} : ∀ (x : α) (t), P x → All P t → P (findMax' x t)
| _x, nil, hx, _ => hx
| _, node _ _ lx lr, _, ⟨_, h₂, h₃⟩ => findMax'_all lx lr h₂ h₃
#align ordnode.find_max'_all Ordnode.findMax'_all
/-! ### `glue` -/
/-! ### `merge` -/
@[simp]
theorem merge_nil_left (t : Ordnode α) : merge t nil = t := by cases t <;> rfl
#align ordnode.merge_nil_left Ordnode.merge_nil_left
@[simp]
theorem merge_nil_right (t : Ordnode α) : merge nil t = t :=
rfl
#align ordnode.merge_nil_right Ordnode.merge_nil_right
@[simp]
theorem merge_node {ls ll lx lr rs rl rx rr} :
merge (@node α ls ll lx lr) (node rs rl rx rr) =
if delta * ls < rs then balanceL (merge (node ls ll lx lr) rl) rx rr
else if delta * rs < ls then balanceR ll lx (merge lr (node rs rl rx rr))
else glue (node ls ll lx lr) (node rs rl rx rr) :=
rfl
#align ordnode.merge_node Ordnode.merge_node
/-! ### `insert` -/
theorem dual_insert [Preorder α] [IsTotal α (· ≤ ·)] [@DecidableRel α (· ≤ ·)] (x : α) :
∀ t : Ordnode α, dual (Ordnode.insert x t) = @Ordnode.insert αᵒᵈ _ _ x (dual t)
| nil => rfl
| node _ l y r => by
have : @cmpLE αᵒᵈ _ _ x y = cmpLE y x := rfl
rw [Ordnode.insert, dual, Ordnode.insert, this, ← cmpLE_swap x y]
cases cmpLE x y <;>
simp [Ordering.swap, Ordnode.insert, dual_balanceL, dual_balanceR, dual_insert]
#align ordnode.dual_insert Ordnode.dual_insert
/-! ### `balance` properties -/
theorem balance_eq_balance' {l x r} (hl : Balanced l) (hr : Balanced r) (sl : Sized l)
(sr : Sized r) : @balance α l x r = balance' l x r := by
cases' l with ls ll lx lr
· cases' r with rs rl rx rr
· rfl
· rw [sr.eq_node'] at hr ⊢
cases' rl with rls rll rlx rlr <;> cases' rr with rrs rrl rrx rrr <;>
dsimp [balance, balance']
· rfl
· have : size rrl = 0 ∧ size rrr = 0 := by
have := balancedSz_zero.1 hr.1.symm
rwa [size, sr.2.2.1, Nat.succ_le_succ_iff, Nat.le_zero, add_eq_zero_iff] at this
cases sr.2.2.2.1.size_eq_zero.1 this.1
cases sr.2.2.2.2.size_eq_zero.1 this.2
obtain rfl : rrs = 1 := sr.2.2.1
rw [if_neg, if_pos, rotateL_node, if_pos]; · rfl
all_goals dsimp only [size]; decide
· have : size rll = 0 ∧ size rlr = 0 := by
have := balancedSz_zero.1 hr.1
rwa [size, sr.2.1.1, Nat.succ_le_succ_iff, Nat.le_zero, add_eq_zero_iff] at this
cases sr.2.1.2.1.size_eq_zero.1 this.1
cases sr.2.1.2.2.size_eq_zero.1 this.2
obtain rfl : rls = 1 := sr.2.1.1
rw [if_neg, if_pos, rotateL_node, if_neg]; · rfl
all_goals dsimp only [size]; decide
· symm; rw [zero_add, if_neg, if_pos, rotateL]
· dsimp only [size_node]; split_ifs
· simp [node3L, node']; abel
· simp [node4L, node', sr.2.1.1]; abel
· apply Nat.zero_lt_succ
· exact not_le_of_gt (Nat.succ_lt_succ (add_pos sr.2.1.pos sr.2.2.pos))
· cases' r with rs rl rx rr
· rw [sl.eq_node'] at hl ⊢
cases' ll with lls lll llx llr <;> cases' lr with lrs lrl lrx lrr <;>
dsimp [balance, balance']
· rfl
· have : size lrl = 0 ∧ size lrr = 0 := by
have := balancedSz_zero.1 hl.1.symm
rwa [size, sl.2.2.1, Nat.succ_le_succ_iff, Nat.le_zero, add_eq_zero_iff] at this
cases sl.2.2.2.1.size_eq_zero.1 this.1
cases sl.2.2.2.2.size_eq_zero.1 this.2
obtain rfl : lrs = 1 := sl.2.2.1
rw [if_neg, if_neg, if_pos, rotateR_node, if_neg]; · rfl
all_goals dsimp only [size]; decide
· have : size lll = 0 ∧ size llr = 0 := by
have := balancedSz_zero.1 hl.1
rwa [size, sl.2.1.1, Nat.succ_le_succ_iff, Nat.le_zero, add_eq_zero_iff] at this
cases sl.2.1.2.1.size_eq_zero.1 this.1
cases sl.2.1.2.2.size_eq_zero.1 this.2
obtain rfl : lls = 1 := sl.2.1.1
rw [if_neg, if_neg, if_pos, rotateR_node, if_pos]; · rfl
all_goals dsimp only [size]; decide
· symm; rw [if_neg, if_neg, if_pos, rotateR]
· dsimp only [size_node]; split_ifs
· simp [node3R, node']; abel
· simp [node4R, node', sl.2.2.1]; abel
· apply Nat.zero_lt_succ
· apply Nat.not_lt_zero
· exact not_le_of_gt (Nat.succ_lt_succ (add_pos sl.2.1.pos sl.2.2.pos))
· simp [balance, balance']
symm; rw [if_neg]
· split_ifs with h h_1
· have rd : delta ≤ size rl + size rr := by
have := lt_of_le_of_lt (Nat.mul_le_mul_left _ sl.pos) h
rwa [sr.1, Nat.lt_succ_iff] at this
cases' rl with rls rll rlx rlr
· rw [size, zero_add] at rd
exact absurd (le_trans rd (balancedSz_zero.1 hr.1.symm)) (by decide)
cases' rr with rrs rrl rrx rrr
· exact absurd (le_trans rd (balancedSz_zero.1 hr.1)) (by decide)
dsimp [rotateL]; split_ifs
· simp [node3L, node', sr.1]; abel
· simp [node4L, node', sr.1, sr.2.1.1]; abel
· have ld : delta ≤ size ll + size lr := by
have := lt_of_le_of_lt (Nat.mul_le_mul_left _ sr.pos) h_1
rwa [sl.1, Nat.lt_succ_iff] at this
cases' ll with lls lll llx llr
· rw [size, zero_add] at ld
exact absurd (le_trans ld (balancedSz_zero.1 hl.1.symm)) (by decide)
cases' lr with lrs lrl lrx lrr
· exact absurd (le_trans ld (balancedSz_zero.1 hl.1)) (by decide)
dsimp [rotateR]; split_ifs
· simp [node3R, node', sl.1]; abel
· simp [node4R, node', sl.1, sl.2.2.1]; abel
· simp [node']
· exact not_le_of_gt (add_le_add (Nat.succ_le_of_lt sl.pos) (Nat.succ_le_of_lt sr.pos))
#align ordnode.balance_eq_balance' Ordnode.balance_eq_balance'
theorem balanceL_eq_balance {l x r} (sl : Sized l) (sr : Sized r) (H1 : size l = 0 → size r ≤ 1)
(H2 : 1 ≤ size l → 1 ≤ size r → size r ≤ delta * size l) :
@balanceL α l x r = balance l x r := by
cases' r with rs rl rx rr
· rfl
· cases' l with ls ll lx lr
· have : size rl = 0 ∧ size rr = 0 := by
have := H1 rfl
rwa [size, sr.1, Nat.succ_le_succ_iff, Nat.le_zero, add_eq_zero_iff] at this
cases sr.2.1.size_eq_zero.1 this.1
cases sr.2.2.size_eq_zero.1 this.2
rw [sr.eq_node']; rfl
· replace H2 : ¬rs > delta * ls := not_lt_of_le (H2 sl.pos sr.pos)
simp [balanceL, balance, H2]; split_ifs <;> simp [add_comm]
#align ordnode.balance_l_eq_balance Ordnode.balanceL_eq_balance
/-- `Raised n m` means `m` is either equal or one up from `n`. -/
def Raised (n m : ℕ) : Prop :=
m = n ∨ m = n + 1
#align ordnode.raised Ordnode.Raised
theorem raised_iff {n m} : Raised n m ↔ n ≤ m ∧ m ≤ n + 1 := by
constructor
· rintro (rfl | rfl)
· exact ⟨le_rfl, Nat.le_succ _⟩
· exact ⟨Nat.le_succ _, le_rfl⟩
· rintro ⟨h₁, h₂⟩
rcases eq_or_lt_of_le h₁ with (rfl | h₁)
· exact Or.inl rfl
· exact Or.inr (le_antisymm h₂ h₁)
#align ordnode.raised_iff Ordnode.raised_iff
theorem Raised.dist_le {n m} (H : Raised n m) : Nat.dist n m ≤ 1 := by
cases' raised_iff.1 H with H1 H2; rwa [Nat.dist_eq_sub_of_le H1, tsub_le_iff_left]
#align ordnode.raised.dist_le Ordnode.Raised.dist_le
theorem Raised.dist_le' {n m} (H : Raised n m) : Nat.dist m n ≤ 1 := by
rw [Nat.dist_comm]; exact H.dist_le
#align ordnode.raised.dist_le' Ordnode.Raised.dist_le'
theorem Raised.add_left (k) {n m} (H : Raised n m) : Raised (k + n) (k + m) := by
rcases H with (rfl | rfl)
· exact Or.inl rfl
· exact Or.inr rfl
#align ordnode.raised.add_left Ordnode.Raised.add_left
theorem Raised.add_right (k) {n m} (H : Raised n m) : Raised (n + k) (m + k) := by
rw [add_comm, add_comm m]; exact H.add_left _
#align ordnode.raised.add_right Ordnode.Raised.add_right
theorem Raised.right {l x₁ x₂ r₁ r₂} (H : Raised (size r₁) (size r₂)) :
Raised (size (@node' α l x₁ r₁)) (size (@node' α l x₂ r₂)) := by
rw [node', size_node, size_node]; generalize size r₂ = m at H ⊢
rcases H with (rfl | rfl)
· exact Or.inl rfl
· exact Or.inr rfl
#align ordnode.raised.right Ordnode.Raised.right
theorem balanceL_eq_balance' {l x r} (hl : Balanced l) (hr : Balanced r) (sl : Sized l)
(sr : Sized r)
(H :
(∃ l', Raised l' (size l) ∧ BalancedSz l' (size r)) ∨
∃ r', Raised (size r) r' ∧ BalancedSz (size l) r') :
@balanceL α l x r = balance' l x r := by
rw [← balance_eq_balance' hl hr sl sr, balanceL_eq_balance sl sr]
· intro l0; rw [l0] at H
rcases H with (⟨_, ⟨⟨⟩⟩ | ⟨⟨⟩⟩, H⟩ | ⟨r', e, H⟩)
· exact balancedSz_zero.1 H.symm
exact le_trans (raised_iff.1 e).1 (balancedSz_zero.1 H.symm)
· intro l1 _
rcases H with (⟨l', e, H | ⟨_, H₂⟩⟩ | ⟨r', e, H | ⟨_, H₂⟩⟩)
· exact le_trans (le_trans (Nat.le_add_left _ _) H) (mul_pos (by decide) l1 : (0 : ℕ) < _)
· exact le_trans H₂ (Nat.mul_le_mul_left _ (raised_iff.1 e).1)
· cases raised_iff.1 e; unfold delta; omega
· exact le_trans (raised_iff.1 e).1 H₂
#align ordnode.balance_l_eq_balance' Ordnode.balanceL_eq_balance'
theorem balance_sz_dual {l r}
(H : (∃ l', Raised (@size α l) l' ∧ BalancedSz l' (@size α r)) ∨
∃ r', Raised r' (size r) ∧ BalancedSz (size l) r') :
(∃ l', Raised l' (size (dual r)) ∧ BalancedSz l' (size (dual l))) ∨
∃ r', Raised (size (dual l)) r' ∧ BalancedSz (size (dual r)) r' := by
rw [size_dual, size_dual]
exact
H.symm.imp (Exists.imp fun _ => And.imp_right BalancedSz.symm)
(Exists.imp fun _ => And.imp_right BalancedSz.symm)
#align ordnode.balance_sz_dual Ordnode.balance_sz_dual
theorem size_balanceL {l x r} (hl : Balanced l) (hr : Balanced r) (sl : Sized l) (sr : Sized r)
(H : (∃ l', Raised l' (size l) ∧ BalancedSz l' (size r)) ∨
∃ r', Raised (size r) r' ∧ BalancedSz (size l) r') :
size (@balanceL α l x r) = size l + size r + 1 := by
rw [balanceL_eq_balance' hl hr sl sr H, size_balance' sl sr]
#align ordnode.size_balance_l Ordnode.size_balanceL
theorem all_balanceL {P l x r} (hl : Balanced l) (hr : Balanced r) (sl : Sized l) (sr : Sized r)
(H :
(∃ l', Raised l' (size l) ∧ BalancedSz l' (size r)) ∨
∃ r', Raised (size r) r' ∧ BalancedSz (size l) r') :
All P (@balanceL α l x r) ↔ All P l ∧ P x ∧ All P r := by
rw [balanceL_eq_balance' hl hr sl sr H, all_balance']
#align ordnode.all_balance_l Ordnode.all_balanceL
theorem balanceR_eq_balance' {l x r} (hl : Balanced l) (hr : Balanced r) (sl : Sized l)
(sr : Sized r)
(H : (∃ l', Raised (size l) l' ∧ BalancedSz l' (size r)) ∨
∃ r', Raised r' (size r) ∧ BalancedSz (size l) r') :
@balanceR α l x r = balance' l x r := by
rw [← dual_dual (balanceR l x r), dual_balanceR,
balanceL_eq_balance' hr.dual hl.dual sr.dual sl.dual (balance_sz_dual H), ← dual_balance',
dual_dual]
#align ordnode.balance_r_eq_balance' Ordnode.balanceR_eq_balance'
theorem size_balanceR {l x r} (hl : Balanced l) (hr : Balanced r) (sl : Sized l) (sr : Sized r)
(H : (∃ l', Raised (size l) l' ∧ BalancedSz l' (size r)) ∨
∃ r', Raised r' (size r) ∧ BalancedSz (size l) r') :
size (@balanceR α l x r) = size l + size r + 1 := by
rw [balanceR_eq_balance' hl hr sl sr H, size_balance' sl sr]
#align ordnode.size_balance_r Ordnode.size_balanceR
theorem all_balanceR {P l x r} (hl : Balanced l) (hr : Balanced r) (sl : Sized l) (sr : Sized r)
(H :
(∃ l', Raised (size l) l' ∧ BalancedSz l' (size r)) ∨
∃ r', Raised r' (size r) ∧ BalancedSz (size l) r') :
All P (@balanceR α l x r) ↔ All P l ∧ P x ∧ All P r := by
rw [balanceR_eq_balance' hl hr sl sr H, all_balance']
#align ordnode.all_balance_r Ordnode.all_balanceR
/-! ### `bounded` -/
section
variable [Preorder α]
/-- `Bounded t lo hi` says that every element `x ∈ t` is in the range `lo < x < hi`, and also this
property holds recursively in subtrees, making the full tree a BST. The bounds can be set to
`lo = ⊥` and `hi = ⊤` if we care only about the internal ordering constraints. -/
def Bounded : Ordnode α → WithBot α → WithTop α → Prop
| nil, some a, some b => a < b
| nil, _, _ => True
| node _ l x r, o₁, o₂ => Bounded l o₁ x ∧ Bounded r (↑x) o₂
#align ordnode.bounded Ordnode.Bounded
theorem Bounded.dual :
∀ {t : Ordnode α} {o₁ o₂}, Bounded t o₁ o₂ → @Bounded αᵒᵈ _ (dual t) o₂ o₁
| nil, o₁, o₂, h => by cases o₁ <;> cases o₂ <;> trivial
| node _ l x r, _, _, ⟨ol, Or⟩ => ⟨Or.dual, ol.dual⟩
#align ordnode.bounded.dual Ordnode.Bounded.dual
theorem Bounded.dual_iff {t : Ordnode α} {o₁ o₂} :
Bounded t o₁ o₂ ↔ @Bounded αᵒᵈ _ (.dual t) o₂ o₁ :=
⟨Bounded.dual, fun h => by
have := Bounded.dual h; rwa [dual_dual, OrderDual.Preorder.dual_dual] at this⟩
#align ordnode.bounded.dual_iff Ordnode.Bounded.dual_iff
theorem Bounded.weak_left : ∀ {t : Ordnode α} {o₁ o₂}, Bounded t o₁ o₂ → Bounded t ⊥ o₂
| nil, o₁, o₂, h => by cases o₂ <;> trivial
| node _ l x r, _, _, ⟨ol, Or⟩ => ⟨ol.weak_left, Or⟩
#align ordnode.bounded.weak_left Ordnode.Bounded.weak_left
theorem Bounded.weak_right : ∀ {t : Ordnode α} {o₁ o₂}, Bounded t o₁ o₂ → Bounded t o₁ ⊤
| nil, o₁, o₂, h => by cases o₁ <;> trivial
| node _ l x r, _, _, ⟨ol, Or⟩ => ⟨ol, Or.weak_right⟩
#align ordnode.bounded.weak_right Ordnode.Bounded.weak_right
theorem Bounded.weak {t : Ordnode α} {o₁ o₂} (h : Bounded t o₁ o₂) : Bounded t ⊥ ⊤ :=
h.weak_left.weak_right
#align ordnode.bounded.weak Ordnode.Bounded.weak
theorem Bounded.mono_left {x y : α} (xy : x ≤ y) :
∀ {t : Ordnode α} {o}, Bounded t y o → Bounded t x o
| nil, none, _ => ⟨⟩
| nil, some _, h => lt_of_le_of_lt xy h
| node _ _ _ _, _o, ⟨ol, or⟩ => ⟨ol.mono_left xy, or⟩
#align ordnode.bounded.mono_left Ordnode.Bounded.mono_left
theorem Bounded.mono_right {x y : α} (xy : x ≤ y) :
∀ {t : Ordnode α} {o}, Bounded t o x → Bounded t o y
| nil, none, _ => ⟨⟩
| nil, some _, h => lt_of_lt_of_le h xy
| node _ _ _ _, _o, ⟨ol, or⟩ => ⟨ol, or.mono_right xy⟩
#align ordnode.bounded.mono_right Ordnode.Bounded.mono_right
theorem Bounded.to_lt : ∀ {t : Ordnode α} {x y : α}, Bounded t x y → x < y
| nil, _, _, h => h
| node _ _ _ _, _, _, ⟨h₁, h₂⟩ => lt_trans h₁.to_lt h₂.to_lt
#align ordnode.bounded.to_lt Ordnode.Bounded.to_lt
theorem Bounded.to_nil {t : Ordnode α} : ∀ {o₁ o₂}, Bounded t o₁ o₂ → Bounded nil o₁ o₂
| none, _, _ => ⟨⟩
| some _, none, _ => ⟨⟩
| some _, some _, h => h.to_lt
#align ordnode.bounded.to_nil Ordnode.Bounded.to_nil
theorem Bounded.trans_left {t₁ t₂ : Ordnode α} {x : α} :
∀ {o₁ o₂}, Bounded t₁ o₁ x → Bounded t₂ x o₂ → Bounded t₂ o₁ o₂
| none, _, _, h₂ => h₂.weak_left
| some _, _, h₁, h₂ => h₂.mono_left (le_of_lt h₁.to_lt)
#align ordnode.bounded.trans_left Ordnode.Bounded.trans_left
theorem Bounded.trans_right {t₁ t₂ : Ordnode α} {x : α} :
∀ {o₁ o₂}, Bounded t₁ o₁ x → Bounded t₂ x o₂ → Bounded t₁ o₁ o₂
| _, none, h₁, _ => h₁.weak_right
| _, some _, h₁, h₂ => h₁.mono_right (le_of_lt h₂.to_lt)
#align ordnode.bounded.trans_right Ordnode.Bounded.trans_right
theorem Bounded.mem_lt : ∀ {t o} {x : α}, Bounded t o x → All (· < x) t
| nil, _, _, _ => ⟨⟩
| node _ _ _ _, _, _, ⟨h₁, h₂⟩ =>
⟨h₁.mem_lt.imp fun _ h => lt_trans h h₂.to_lt, h₂.to_lt, h₂.mem_lt⟩
#align ordnode.bounded.mem_lt Ordnode.Bounded.mem_lt
theorem Bounded.mem_gt : ∀ {t o} {x : α}, Bounded t x o → All (· > x) t
| nil, _, _, _ => ⟨⟩
| node _ _ _ _, _, _, ⟨h₁, h₂⟩ => ⟨h₁.mem_gt, h₁.to_lt, h₂.mem_gt.imp fun _ => lt_trans h₁.to_lt⟩
#align ordnode.bounded.mem_gt Ordnode.Bounded.mem_gt
theorem Bounded.of_lt :
∀ {t o₁ o₂} {x : α}, Bounded t o₁ o₂ → Bounded nil o₁ x → All (· < x) t → Bounded t o₁ x
| nil, _, _, _, _, hn, _ => hn
| node _ _ _ _, _, _, _, ⟨h₁, h₂⟩, _, ⟨_, al₂, al₃⟩ => ⟨h₁, h₂.of_lt al₂ al₃⟩
#align ordnode.bounded.of_lt Ordnode.Bounded.of_lt
theorem Bounded.of_gt :
∀ {t o₁ o₂} {x : α}, Bounded t o₁ o₂ → Bounded nil x o₂ → All (· > x) t → Bounded t x o₂
| nil, _, _, _, _, hn, _ => hn
| node _ _ _ _, _, _, _, ⟨h₁, h₂⟩, _, ⟨al₁, al₂, _⟩ => ⟨h₁.of_gt al₂ al₁, h₂⟩
#align ordnode.bounded.of_gt Ordnode.Bounded.of_gt
theorem Bounded.to_sep {t₁ t₂ o₁ o₂} {x : α}
(h₁ : Bounded t₁ o₁ (x : WithTop α)) (h₂ : Bounded t₂ (x : WithBot α) o₂) :
t₁.All fun y => t₂.All fun z : α => y < z := by
refine h₁.mem_lt.imp fun y yx => ?_
exact h₂.mem_gt.imp fun z xz => lt_trans yx xz
#align ordnode.bounded.to_sep Ordnode.Bounded.to_sep
end
/-! ### `Valid` -/
section
variable [Preorder α]
/-- The validity predicate for an `Ordnode` subtree. This asserts that the `size` fields are
correct, the tree is balanced, and the elements of the tree are organized according to the
ordering. This version of `Valid` also puts all elements in the tree in the interval `(lo, hi)`. -/
structure Valid' (lo : WithBot α) (t : Ordnode α) (hi : WithTop α) : Prop where
ord : t.Bounded lo hi
sz : t.Sized
bal : t.Balanced
#align ordnode.valid' Ordnode.Valid'
#align ordnode.valid'.ord Ordnode.Valid'.ord
#align ordnode.valid'.sz Ordnode.Valid'.sz
#align ordnode.valid'.bal Ordnode.Valid'.bal
/-- The validity predicate for an `Ordnode` subtree. This asserts that the `size` fields are
correct, the tree is balanced, and the elements of the tree are organized according to the
ordering. -/
def Valid (t : Ordnode α) : Prop :=
Valid' ⊥ t ⊤
#align ordnode.valid Ordnode.Valid
theorem Valid'.mono_left {x y : α} (xy : x ≤ y) {t : Ordnode α} {o} (h : Valid' y t o) :
Valid' x t o :=
⟨h.1.mono_left xy, h.2, h.3⟩
#align ordnode.valid'.mono_left Ordnode.Valid'.mono_left
theorem Valid'.mono_right {x y : α} (xy : x ≤ y) {t : Ordnode α} {o} (h : Valid' o t x) :
Valid' o t y :=
⟨h.1.mono_right xy, h.2, h.3⟩
#align ordnode.valid'.mono_right Ordnode.Valid'.mono_right
theorem Valid'.trans_left {t₁ t₂ : Ordnode α} {x : α} {o₁ o₂} (h : Bounded t₁ o₁ x)
(H : Valid' x t₂ o₂) : Valid' o₁ t₂ o₂ :=
⟨h.trans_left H.1, H.2, H.3⟩
#align ordnode.valid'.trans_left Ordnode.Valid'.trans_left
theorem Valid'.trans_right {t₁ t₂ : Ordnode α} {x : α} {o₁ o₂} (H : Valid' o₁ t₁ x)
(h : Bounded t₂ x o₂) : Valid' o₁ t₁ o₂ :=
⟨H.1.trans_right h, H.2, H.3⟩
#align ordnode.valid'.trans_right Ordnode.Valid'.trans_right
theorem Valid'.of_lt {t : Ordnode α} {x : α} {o₁ o₂} (H : Valid' o₁ t o₂) (h₁ : Bounded nil o₁ x)
(h₂ : All (· < x) t) : Valid' o₁ t x :=
⟨H.1.of_lt h₁ h₂, H.2, H.3⟩
#align ordnode.valid'.of_lt Ordnode.Valid'.of_lt
theorem Valid'.of_gt {t : Ordnode α} {x : α} {o₁ o₂} (H : Valid' o₁ t o₂) (h₁ : Bounded nil x o₂)
(h₂ : All (· > x) t) : Valid' x t o₂ :=
⟨H.1.of_gt h₁ h₂, H.2, H.3⟩
#align ordnode.valid'.of_gt Ordnode.Valid'.of_gt
theorem Valid'.valid {t o₁ o₂} (h : @Valid' α _ o₁ t o₂) : Valid t :=
⟨h.1.weak, h.2, h.3⟩
#align ordnode.valid'.valid Ordnode.Valid'.valid
theorem valid'_nil {o₁ o₂} (h : Bounded nil o₁ o₂) : Valid' o₁ (@nil α) o₂ :=
⟨h, ⟨⟩, ⟨⟩⟩
#align ordnode.valid'_nil Ordnode.valid'_nil
theorem valid_nil : Valid (@nil α) :=
valid'_nil ⟨⟩
#align ordnode.valid_nil Ordnode.valid_nil
theorem Valid'.node {s l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂)
(H : BalancedSz (size l) (size r)) (hs : s = size l + size r + 1) :
Valid' o₁ (@node α s l x r) o₂ :=
⟨⟨hl.1, hr.1⟩, ⟨hs, hl.2, hr.2⟩, ⟨H, hl.3, hr.3⟩⟩
#align ordnode.valid'.node Ordnode.Valid'.node
theorem Valid'.dual : ∀ {t : Ordnode α} {o₁ o₂}, Valid' o₁ t o₂ → @Valid' αᵒᵈ _ o₂ (dual t) o₁
| .nil, o₁, o₂, h => valid'_nil h.1.dual
| .node _ l x r, o₁, o₂, ⟨⟨ol, Or⟩, ⟨rfl, sl, sr⟩, ⟨b, bl, br⟩⟩ =>
let ⟨ol', sl', bl'⟩ := Valid'.dual ⟨ol, sl, bl⟩
let ⟨or', sr', br'⟩ := Valid'.dual ⟨Or, sr, br⟩
⟨⟨or', ol'⟩, ⟨by simp [size_dual, add_comm], sr', sl'⟩,
⟨by rw [size_dual, size_dual]; exact b.symm, br', bl'⟩⟩
#align ordnode.valid'.dual Ordnode.Valid'.dual
theorem Valid'.dual_iff {t : Ordnode α} {o₁ o₂} : Valid' o₁ t o₂ ↔ @Valid' αᵒᵈ _ o₂ (.dual t) o₁ :=
⟨Valid'.dual, fun h => by
have := Valid'.dual h; rwa [dual_dual, OrderDual.Preorder.dual_dual] at this⟩
#align ordnode.valid'.dual_iff Ordnode.Valid'.dual_iff
theorem Valid.dual {t : Ordnode α} : Valid t → @Valid αᵒᵈ _ (.dual t) :=
Valid'.dual
#align ordnode.valid.dual Ordnode.Valid.dual
theorem Valid.dual_iff {t : Ordnode α} : Valid t ↔ @Valid αᵒᵈ _ (.dual t) :=
Valid'.dual_iff
#align ordnode.valid.dual_iff Ordnode.Valid.dual_iff
theorem Valid'.left {s l x r o₁ o₂} (H : Valid' o₁ (@Ordnode.node α s l x r) o₂) : Valid' o₁ l x :=
⟨H.1.1, H.2.2.1, H.3.2.1⟩
#align ordnode.valid'.left Ordnode.Valid'.left
theorem Valid'.right {s l x r o₁ o₂} (H : Valid' o₁ (@Ordnode.node α s l x r) o₂) : Valid' x r o₂ :=
⟨H.1.2, H.2.2.2, H.3.2.2⟩
#align ordnode.valid'.right Ordnode.Valid'.right
nonrec theorem Valid.left {s l x r} (H : Valid (@node α s l x r)) : Valid l :=
H.left.valid
#align ordnode.valid.left Ordnode.Valid.left
nonrec theorem Valid.right {s l x r} (H : Valid (@node α s l x r)) : Valid r :=
H.right.valid
#align ordnode.valid.right Ordnode.Valid.right
theorem Valid.size_eq {s l x r} (H : Valid (@node α s l x r)) :
size (@node α s l x r) = size l + size r + 1 :=
H.2.1
#align ordnode.valid.size_eq Ordnode.Valid.size_eq
theorem Valid'.node' {l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂)
(H : BalancedSz (size l) (size r)) : Valid' o₁ (@node' α l x r) o₂ :=
hl.node hr H rfl
#align ordnode.valid'.node' Ordnode.Valid'.node'
theorem valid'_singleton {x : α} {o₁ o₂} (h₁ : Bounded nil o₁ x) (h₂ : Bounded nil x o₂) :
Valid' o₁ (singleton x : Ordnode α) o₂ :=
(valid'_nil h₁).node (valid'_nil h₂) (Or.inl zero_le_one) rfl
#align ordnode.valid'_singleton Ordnode.valid'_singleton
theorem valid_singleton {x : α} : Valid (singleton x : Ordnode α) :=
valid'_singleton ⟨⟩ ⟨⟩
#align ordnode.valid_singleton Ordnode.valid_singleton
theorem Valid'.node3L {l} {x : α} {m} {y : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hm : Valid' x m y)
(hr : Valid' y r o₂) (H1 : BalancedSz (size l) (size m))
(H2 : BalancedSz (size l + size m + 1) (size r)) : Valid' o₁ (@node3L α l x m y r) o₂ :=
(hl.node' hm H1).node' hr H2
#align ordnode.valid'.node3_l Ordnode.Valid'.node3L
theorem Valid'.node3R {l} {x : α} {m} {y : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hm : Valid' x m y)
(hr : Valid' y r o₂) (H1 : BalancedSz (size l) (size m + size r + 1))
(H2 : BalancedSz (size m) (size r)) : Valid' o₁ (@node3R α l x m y r) o₂ :=
hl.node' (hm.node' hr H2) H1
#align ordnode.valid'.node3_r Ordnode.Valid'.node3R
theorem Valid'.node4L_lemma₁ {a b c d : ℕ} (lr₂ : 3 * (b + c + 1 + d) ≤ 16 * a + 9)
(mr₂ : b + c + 1 ≤ 3 * d) (mm₁ : b ≤ 3 * c) : b < 3 * a + 1 := by omega
#align ordnode.valid'.node4_l_lemma₁ Ordnode.Valid'.node4L_lemma₁
theorem Valid'.node4L_lemma₂ {b c d : ℕ} (mr₂ : b + c + 1 ≤ 3 * d) : c ≤ 3 * d := by omega
#align ordnode.valid'.node4_l_lemma₂ Ordnode.Valid'.node4L_lemma₂
theorem Valid'.node4L_lemma₃ {b c d : ℕ} (mr₁ : 2 * d ≤ b + c + 1) (mm₁ : b ≤ 3 * c) :
d ≤ 3 * c := by omega
#align ordnode.valid'.node4_l_lemma₃ Ordnode.Valid'.node4L_lemma₃
theorem Valid'.node4L_lemma₄ {a b c d : ℕ} (lr₁ : 3 * a ≤ b + c + 1 + d) (mr₂ : b + c + 1 ≤ 3 * d)
(mm₁ : b ≤ 3 * c) : a + b + 1 ≤ 3 * (c + d + 1) := by omega
#align ordnode.valid'.node4_l_lemma₄ Ordnode.Valid'.node4L_lemma₄
theorem Valid'.node4L_lemma₅ {a b c d : ℕ} (lr₂ : 3 * (b + c + 1 + d) ≤ 16 * a + 9)
(mr₁ : 2 * d ≤ b + c + 1) (mm₂ : c ≤ 3 * b) : c + d + 1 ≤ 3 * (a + b + 1) := by omega
#align ordnode.valid'.node4_l_lemma₅ Ordnode.Valid'.node4L_lemma₅
theorem Valid'.node4L {l} {x : α} {m} {y : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hm : Valid' x m y)
(hr : Valid' (↑y) r o₂) (Hm : 0 < size m)
(H : size l = 0 ∧ size m = 1 ∧ size r ≤ 1 ∨
0 < size l ∧
ratio * size r ≤ size m ∧
delta * size l ≤ size m + size r ∧
3 * (size m + size r) ≤ 16 * size l + 9 ∧ size m ≤ delta * size r) :
Valid' o₁ (@node4L α l x m y r) o₂ := by
cases' m with s ml z mr; · cases Hm
suffices
BalancedSz (size l) (size ml) ∧
BalancedSz (size mr) (size r) ∧ BalancedSz (size l + size ml + 1) (size mr + size r + 1) from
Valid'.node' (hl.node' hm.left this.1) (hm.right.node' hr this.2.1) this.2.2
rcases H with (⟨l0, m1, r0⟩ | ⟨l0, mr₁, lr₁, lr₂, mr₂⟩)
· rw [hm.2.size_eq, Nat.succ_inj', add_eq_zero_iff] at m1
rw [l0, m1.1, m1.2]; revert r0; rcases size r with (_ | _ | _) <;>
[decide; decide; (intro r0; unfold BalancedSz delta; omega)]
· rcases Nat.eq_zero_or_pos (size r) with r0 | r0
· rw [r0] at mr₂; cases not_le_of_lt Hm mr₂
rw [hm.2.size_eq] at lr₁ lr₂ mr₁ mr₂
by_cases mm : size ml + size mr ≤ 1
· have r1 :=
le_antisymm
((mul_le_mul_left (by decide)).1 (le_trans mr₁ (Nat.succ_le_succ mm) : _ ≤ ratio * 1)) r0
rw [r1, add_assoc] at lr₁
have l1 :=
le_antisymm
((mul_le_mul_left (by decide)).1 (le_trans lr₁ (add_le_add_right mm 2) : _ ≤ delta * 1))
l0
rw [l1, r1]
revert mm; cases size ml <;> cases size mr <;> intro mm
· decide
· rw [zero_add] at mm; rcases mm with (_ | ⟨⟨⟩⟩)
decide
· rcases mm with (_ | ⟨⟨⟩⟩); decide
· rw [Nat.succ_add] at mm; rcases mm with (_ | ⟨⟨⟩⟩)
rcases hm.3.1.resolve_left mm with ⟨mm₁, mm₂⟩
rcases Nat.eq_zero_or_pos (size ml) with ml0 | ml0
· rw [ml0, mul_zero, Nat.le_zero] at mm₂
rw [ml0, mm₂] at mm; cases mm (by decide)
have : 2 * size l ≤ size ml + size mr + 1 := by
have := Nat.mul_le_mul_left ratio lr₁
rw [mul_left_comm, mul_add] at this
have := le_trans this (add_le_add_left mr₁ _)
rw [← Nat.succ_mul] at this
exact (mul_le_mul_left (by decide)).1 this
refine ⟨Or.inr ⟨?_, ?_⟩, Or.inr ⟨?_, ?_⟩, Or.inr ⟨?_, ?_⟩⟩
· refine (mul_le_mul_left (by decide)).1 (le_trans this ?_)
rw [two_mul, Nat.succ_le_iff]
refine add_lt_add_of_lt_of_le ?_ mm₂
simpa using (mul_lt_mul_right ml0).2 (by decide : 1 < 3)
· exact Nat.le_of_lt_succ (Valid'.node4L_lemma₁ lr₂ mr₂ mm₁)
· exact Valid'.node4L_lemma₂ mr₂
· exact Valid'.node4L_lemma₃ mr₁ mm₁
· exact Valid'.node4L_lemma₄ lr₁ mr₂ mm₁
· exact Valid'.node4L_lemma₅ lr₂ mr₁ mm₂
#align ordnode.valid'.node4_l Ordnode.Valid'.node4L
theorem Valid'.rotateL_lemma₁ {a b c : ℕ} (H2 : 3 * a ≤ b + c) (hb₂ : c ≤ 3 * b) : a ≤ 3 * b := by
omega
#align ordnode.valid'.rotate_l_lemma₁ Ordnode.Valid'.rotateL_lemma₁
theorem Valid'.rotateL_lemma₂ {a b c : ℕ} (H3 : 2 * (b + c) ≤ 9 * a + 3) (h : b < 2 * c) :
b < 3 * a + 1 := by omega
#align ordnode.valid'.rotate_l_lemma₂ Ordnode.Valid'.rotateL_lemma₂
theorem Valid'.rotateL_lemma₃ {a b c : ℕ} (H2 : 3 * a ≤ b + c) (h : b < 2 * c) : a + b < 3 * c := by
omega
#align ordnode.valid'.rotate_l_lemma₃ Ordnode.Valid'.rotateL_lemma₃
theorem Valid'.rotateL_lemma₄ {a b : ℕ} (H3 : 2 * b ≤ 9 * a + 3) : 3 * b ≤ 16 * a + 9 := by
omega
#align ordnode.valid'.rotate_l_lemma₄ Ordnode.Valid'.rotateL_lemma₄
theorem Valid'.rotateL {l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂)
(H1 : ¬size l + size r ≤ 1) (H2 : delta * size l < size r)
(H3 : 2 * size r ≤ 9 * size l + 5 ∨ size r ≤ 3) : Valid' o₁ (@rotateL α l x r) o₂ := by
cases' r with rs rl rx rr; · cases H2
rw [hr.2.size_eq, Nat.lt_succ_iff] at H2
rw [hr.2.size_eq] at H3
replace H3 : 2 * (size rl + size rr) ≤ 9 * size l + 3 ∨ size rl + size rr ≤ 2 :=
H3.imp (@Nat.le_of_add_le_add_right _ 2 _) Nat.le_of_succ_le_succ
have H3_0 : size l = 0 → size rl + size rr ≤ 2 := by
intro l0; rw [l0] at H3
exact
(or_iff_right_of_imp fun h => (mul_le_mul_left (by decide)).1 (le_trans h (by decide))).1 H3
have H3p : size l > 0 → 2 * (size rl + size rr) ≤ 9 * size l + 3 := fun l0 : 1 ≤ size l =>
(or_iff_left_of_imp <| by omega).1 H3
have ablem : ∀ {a b : ℕ}, 1 ≤ a → a + b ≤ 2 → b ≤ 1 := by omega
have hlp : size l > 0 → ¬size rl + size rr ≤ 1 := fun l0 hb =>
absurd (le_trans (le_trans (Nat.mul_le_mul_left _ l0) H2) hb) (by decide)
rw [Ordnode.rotateL_node]; split_ifs with h
· have rr0 : size rr > 0 :=
(mul_lt_mul_left (by decide)).1 (lt_of_le_of_lt (Nat.zero_le _) h : ratio * 0 < _)
suffices BalancedSz (size l) (size rl) ∧ BalancedSz (size l + size rl + 1) (size rr) by
exact hl.node3L hr.left hr.right this.1 this.2
rcases Nat.eq_zero_or_pos (size l) with l0 | l0
· rw [l0]; replace H3 := H3_0 l0
have := hr.3.1
rcases Nat.eq_zero_or_pos (size rl) with rl0 | rl0
· rw [rl0] at this ⊢
rw [le_antisymm (balancedSz_zero.1 this.symm) rr0]
decide
have rr1 : size rr = 1 := le_antisymm (ablem rl0 H3) rr0
rw [add_comm] at H3
rw [rr1, show size rl = 1 from le_antisymm (ablem rr0 H3) rl0]
decide
replace H3 := H3p l0
rcases hr.3.1.resolve_left (hlp l0) with ⟨_, hb₂⟩
refine ⟨Or.inr ⟨?_, ?_⟩, Or.inr ⟨?_, ?_⟩⟩
· exact Valid'.rotateL_lemma₁ H2 hb₂
· exact Nat.le_of_lt_succ (Valid'.rotateL_lemma₂ H3 h)
· exact Valid'.rotateL_lemma₃ H2 h
· exact
le_trans hb₂
(Nat.mul_le_mul_left _ <| le_trans (Nat.le_add_left _ _) (Nat.le_add_right _ _))
· rcases Nat.eq_zero_or_pos (size rl) with rl0 | rl0
· rw [rl0, not_lt, Nat.le_zero, Nat.mul_eq_zero] at h
replace h := h.resolve_left (by decide)
erw [rl0, h, Nat.le_zero, Nat.mul_eq_zero] at H2
rw [hr.2.size_eq, rl0, h, H2.resolve_left (by decide)] at H1
cases H1 (by decide)
refine hl.node4L hr.left hr.right rl0 ?_
rcases Nat.eq_zero_or_pos (size l) with l0 | l0
· replace H3 := H3_0 l0
rcases Nat.eq_zero_or_pos (size rr) with rr0 | rr0
· have := hr.3.1
rw [rr0] at this
exact Or.inl ⟨l0, le_antisymm (balancedSz_zero.1 this) rl0, rr0.symm ▸ zero_le_one⟩
exact Or.inl ⟨l0, le_antisymm (ablem rr0 <| by rwa [add_comm]) rl0, ablem rl0 H3⟩
exact
Or.inr ⟨l0, not_lt.1 h, H2, Valid'.rotateL_lemma₄ (H3p l0), (hr.3.1.resolve_left (hlp l0)).1⟩
#align ordnode.valid'.rotate_l Ordnode.Valid'.rotateL
theorem Valid'.rotateR {l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂)
(H1 : ¬size l + size r ≤ 1) (H2 : delta * size r < size l)
(H3 : 2 * size l ≤ 9 * size r + 5 ∨ size l ≤ 3) : Valid' o₁ (@rotateR α l x r) o₂ := by
refine Valid'.dual_iff.2 ?_
rw [dual_rotateR]
refine hr.dual.rotateL hl.dual ?_ ?_ ?_
· rwa [size_dual, size_dual, add_comm]
· rwa [size_dual, size_dual]
· rwa [size_dual, size_dual]
#align ordnode.valid'.rotate_r Ordnode.Valid'.rotateR
theorem Valid'.balance'_aux {l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂)
(H₁ : 2 * @size α r ≤ 9 * size l + 5 ∨ size r ≤ 3)
(H₂ : 2 * @size α l ≤ 9 * size r + 5 ∨ size l ≤ 3) : Valid' o₁ (@balance' α l x r) o₂ := by
rw [balance']; split_ifs with h h_1 h_2
· exact hl.node' hr (Or.inl h)
· exact hl.rotateL hr h h_1 H₁
· exact hl.rotateR hr h h_2 H₂
· exact hl.node' hr (Or.inr ⟨not_lt.1 h_2, not_lt.1 h_1⟩)
#align ordnode.valid'.balance'_aux Ordnode.Valid'.balance'_aux
theorem Valid'.balance'_lemma {α l l' r r'} (H1 : BalancedSz l' r')
(H2 : Nat.dist (@size α l) l' ≤ 1 ∧ size r = r' ∨ Nat.dist (size r) r' ≤ 1 ∧ size l = l') :
2 * @size α r ≤ 9 * size l + 5 ∨ size r ≤ 3 := by
suffices @size α r ≤ 3 * (size l + 1) by
rcases Nat.eq_zero_or_pos (size l) with l0 | l0
· apply Or.inr; rwa [l0] at this
change 1 ≤ _ at l0; apply Or.inl; omega
rcases H2 with (⟨hl, rfl⟩ | ⟨hr, rfl⟩) <;> rcases H1 with (h | ⟨_, h₂⟩)
· exact le_trans (Nat.le_add_left _ _) (le_trans h (Nat.le_add_left _ _))
· exact
le_trans h₂
(Nat.mul_le_mul_left _ <| le_trans (Nat.dist_tri_right _ _) (Nat.add_le_add_left hl _))
· exact
le_trans (Nat.dist_tri_left' _ _)
(le_trans (add_le_add hr (le_trans (Nat.le_add_left _ _) h)) (by omega))
· rw [Nat.mul_succ]
exact le_trans (Nat.dist_tri_right' _ _) (add_le_add h₂ (le_trans hr (by decide)))
#align ordnode.valid'.balance'_lemma Ordnode.Valid'.balance'_lemma
theorem Valid'.balance' {l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂)
(H : ∃ l' r', BalancedSz l' r' ∧
(Nat.dist (size l) l' ≤ 1 ∧ size r = r' ∨ Nat.dist (size r) r' ≤ 1 ∧ size l = l')) :
Valid' o₁ (@balance' α l x r) o₂ :=
let ⟨_, _, H1, H2⟩ := H
Valid'.balance'_aux hl hr (Valid'.balance'_lemma H1 H2) (Valid'.balance'_lemma H1.symm H2.symm)
#align ordnode.valid'.balance' Ordnode.Valid'.balance'
theorem Valid'.balance {l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂)
(H : ∃ l' r', BalancedSz l' r' ∧
(Nat.dist (size l) l' ≤ 1 ∧ size r = r' ∨ Nat.dist (size r) r' ≤ 1 ∧ size l = l')) :
Valid' o₁ (@balance α l x r) o₂ := by
rw [balance_eq_balance' hl.3 hr.3 hl.2 hr.2]; exact hl.balance' hr H
#align ordnode.valid'.balance Ordnode.Valid'.balance
theorem Valid'.balanceL_aux {l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂)
(H₁ : size l = 0 → size r ≤ 1) (H₂ : 1 ≤ size l → 1 ≤ size r → size r ≤ delta * size l)
(H₃ : 2 * @size α l ≤ 9 * size r + 5 ∨ size l ≤ 3) : Valid' o₁ (@balanceL α l x r) o₂ := by
rw [balanceL_eq_balance hl.2 hr.2 H₁ H₂, balance_eq_balance' hl.3 hr.3 hl.2 hr.2]
refine hl.balance'_aux hr (Or.inl ?_) H₃
rcases Nat.eq_zero_or_pos (size r) with r0 | r0
· rw [r0]; exact Nat.zero_le _
rcases Nat.eq_zero_or_pos (size l) with l0 | l0
· rw [l0]; exact le_trans (Nat.mul_le_mul_left _ (H₁ l0)) (by decide)
replace H₂ : _ ≤ 3 * _ := H₂ l0 r0; omega
#align ordnode.valid'.balance_l_aux Ordnode.Valid'.balanceL_aux
theorem Valid'.balanceL {l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂)
(H : (∃ l', Raised l' (size l) ∧ BalancedSz l' (size r)) ∨
∃ r', Raised (size r) r' ∧ BalancedSz (size l) r') :
Valid' o₁ (@balanceL α l x r) o₂ := by
rw [balanceL_eq_balance' hl.3 hr.3 hl.2 hr.2 H]
refine hl.balance' hr ?_
rcases H with (⟨l', e, H⟩ | ⟨r', e, H⟩)
· exact ⟨_, _, H, Or.inl ⟨e.dist_le', rfl⟩⟩
· exact ⟨_, _, H, Or.inr ⟨e.dist_le, rfl⟩⟩
#align ordnode.valid'.balance_l Ordnode.Valid'.balanceL
theorem Valid'.balanceR_aux {l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂)
(H₁ : size r = 0 → size l ≤ 1) (H₂ : 1 ≤ size r → 1 ≤ size l → size l ≤ delta * size r)
(H₃ : 2 * @size α r ≤ 9 * size l + 5 ∨ size r ≤ 3) : Valid' o₁ (@balanceR α l x r) o₂ := by
rw [Valid'.dual_iff, dual_balanceR]
have := hr.dual.balanceL_aux hl.dual
rw [size_dual, size_dual] at this
exact this H₁ H₂ H₃
#align ordnode.valid'.balance_r_aux Ordnode.Valid'.balanceR_aux
theorem Valid'.balanceR {l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂)
(H : (∃ l', Raised (size l) l' ∧ BalancedSz l' (size r)) ∨
∃ r', Raised r' (size r) ∧ BalancedSz (size l) r') :
Valid' o₁ (@balanceR α l x r) o₂ := by
rw [Valid'.dual_iff, dual_balanceR]; exact hr.dual.balanceL hl.dual (balance_sz_dual H)
#align ordnode.valid'.balance_r Ordnode.Valid'.balanceR
theorem Valid'.eraseMax_aux {s l x r o₁ o₂} (H : Valid' o₁ (.node s l x r) o₂) :
Valid' o₁ (@eraseMax α (.node' l x r)) ↑(findMax' x r) ∧
size (.node' l x r) = size (eraseMax (.node' l x r)) + 1 := by
have := H.2.eq_node'; rw [this] at H; clear this
induction' r with rs rl rx rr _ IHrr generalizing l x o₁
· exact ⟨H.left, rfl⟩
have := H.2.2.2.eq_node'; rw [this] at H ⊢
rcases IHrr H.right with ⟨h, e⟩
refine ⟨Valid'.balanceL H.left h (Or.inr ⟨_, Or.inr e, H.3.1⟩), ?_⟩
rw [eraseMax, size_balanceL H.3.2.1 h.3 H.2.2.1 h.2 (Or.inr ⟨_, Or.inr e, H.3.1⟩)]
rw [size_node, e]; rfl
#align ordnode.valid'.erase_max_aux Ordnode.Valid'.eraseMax_aux
theorem Valid'.eraseMin_aux {s l} {x : α} {r o₁ o₂} (H : Valid' o₁ (.node s l x r) o₂) :
Valid' ↑(findMin' l x) (@eraseMin α (.node' l x r)) o₂ ∧
size (.node' l x r) = size (eraseMin (.node' l x r)) + 1 := by
have := H.dual.eraseMax_aux
rwa [← dual_node', size_dual, ← dual_eraseMin, size_dual, ← Valid'.dual_iff, findMax'_dual]
at this
#align ordnode.valid'.erase_min_aux Ordnode.Valid'.eraseMin_aux
theorem eraseMin.valid : ∀ {t}, @Valid α _ t → Valid (eraseMin t)
| nil, _ => valid_nil
| node _ l x r, h => by rw [h.2.eq_node']; exact h.eraseMin_aux.1.valid
#align ordnode.erase_min.valid Ordnode.eraseMin.valid
theorem eraseMax.valid {t} (h : @Valid α _ t) : Valid (eraseMax t) := by
rw [Valid.dual_iff, dual_eraseMax]; exact eraseMin.valid h.dual
#align ordnode.erase_max.valid Ordnode.eraseMax.valid
theorem Valid'.glue_aux {l r o₁ o₂} (hl : Valid' o₁ l o₂) (hr : Valid' o₁ r o₂)
(sep : l.All fun x => r.All fun y => x < y) (bal : BalancedSz (size l) (size r)) :
Valid' o₁ (@glue α l r) o₂ ∧ size (glue l r) = size l + size r := by
cases' l with ls ll lx lr; · exact ⟨hr, (zero_add _).symm⟩
cases' r with rs rl rx rr; · exact ⟨hl, rfl⟩
dsimp [glue]; split_ifs
· rw [splitMax_eq]
· cases' Valid'.eraseMax_aux hl with v e
suffices H : _ by
refine ⟨Valid'.balanceR v (hr.of_gt ?_ ?_) H, ?_⟩
· refine findMax'_all (P := fun a : α => Bounded nil (a : WithTop α) o₂)
lx lr hl.1.2.to_nil (sep.2.2.imp ?_)
exact fun x h => hr.1.2.to_nil.mono_left (le_of_lt h.2.1)
· exact @findMax'_all _ (fun a => All (· > a) (.node rs rl rx rr)) lx lr sep.2.1 sep.2.2
· rw [size_balanceR v.3 hr.3 v.2 hr.2 H, add_right_comm, ← e, hl.2.1]; rfl
refine Or.inl ⟨_, Or.inr e, ?_⟩
rwa [hl.2.eq_node'] at bal
· rw [splitMin_eq]
· cases' Valid'.eraseMin_aux hr with v e
suffices H : _ by
refine ⟨Valid'.balanceL (hl.of_lt ?_ ?_) v H, ?_⟩
· refine @findMin'_all (P := fun a : α => Bounded nil o₁ (a : WithBot α))
rl rx (sep.2.1.1.imp ?_) hr.1.1.to_nil
exact fun y h => hl.1.1.to_nil.mono_right (le_of_lt h)
· exact
@findMin'_all _ (fun a => All (· < a) (.node ls ll lx lr)) rl rx
(all_iff_forall.2 fun x hx => sep.imp fun y hy => all_iff_forall.1 hy.1 _ hx)
(sep.imp fun y hy => hy.2.1)
· rw [size_balanceL hl.3 v.3 hl.2 v.2 H, add_assoc, ← e, hr.2.1]; rfl
refine Or.inr ⟨_, Or.inr e, ?_⟩
rwa [hr.2.eq_node'] at bal
#align ordnode.valid'.glue_aux Ordnode.Valid'.glue_aux
theorem Valid'.glue {l} {x : α} {r o₁ o₂} (hl : Valid' o₁ l x) (hr : Valid' x r o₂) :
BalancedSz (size l) (size r) →
Valid' o₁ (@glue α l r) o₂ ∧ size (@glue α l r) = size l + size r :=
Valid'.glue_aux (hl.trans_right hr.1) (hr.trans_left hl.1) (hl.1.to_sep hr.1)
#align ordnode.valid'.glue Ordnode.Valid'.glue
theorem Valid'.merge_lemma {a b c : ℕ} (h₁ : 3 * a < b + c + 1) (h₂ : b ≤ 3 * c) :
2 * (a + b) ≤ 9 * c + 5 := by omega
#align ordnode.valid'.merge_lemma Ordnode.Valid'.merge_lemma
theorem Valid'.merge_aux₁ {o₁ o₂ ls ll lx lr rs rl rx rr t}
(hl : Valid' o₁ (@Ordnode.node α ls ll lx lr) o₂) (hr : Valid' o₁ (.node rs rl rx rr) o₂)
(h : delta * ls < rs) (v : Valid' o₁ t rx) (e : size t = ls + size rl) :
Valid' o₁ (.balanceL t rx rr) o₂ ∧ size (.balanceL t rx rr) = ls + rs := by
rw [hl.2.1] at e
rw [hl.2.1, hr.2.1, delta] at h
rcases hr.3.1 with (H | ⟨hr₁, hr₂⟩); · omega
suffices H₂ : _ by
suffices H₁ : _ by
refine ⟨Valid'.balanceL_aux v hr.right H₁ H₂ ?_, ?_⟩
· rw [e]; exact Or.inl (Valid'.merge_lemma h hr₁)
· rw [balanceL_eq_balance v.2 hr.2.2.2 H₁ H₂, balance_eq_balance' v.3 hr.3.2.2 v.2 hr.2.2.2,
size_balance' v.2 hr.2.2.2, e, hl.2.1, hr.2.1]
abel
· rw [e, add_right_comm]; rintro ⟨⟩
intro _ _; rw [e]; unfold delta at hr₂ ⊢; omega
#align ordnode.valid'.merge_aux₁ Ordnode.Valid'.merge_aux₁
theorem Valid'.merge_aux {l r o₁ o₂} (hl : Valid' o₁ l o₂) (hr : Valid' o₁ r o₂)
(sep : l.All fun x => r.All fun y => x < y) :
Valid' o₁ (@merge α l r) o₂ ∧ size (merge l r) = size l + size r := by
induction' l with ls ll lx lr _ IHlr generalizing o₁ o₂ r
· exact ⟨hr, (zero_add _).symm⟩
induction' r with rs rl rx rr IHrl _ generalizing o₁ o₂
· exact ⟨hl, rfl⟩
rw [merge_node]; split_ifs with h h_1
· cases'
IHrl (hl.of_lt hr.1.1.to_nil <| sep.imp fun x h => h.2.1) hr.left
(sep.imp fun x h => h.1) with
v e
exact Valid'.merge_aux₁ hl hr h v e
· cases' IHlr hl.right (hr.of_gt hl.1.2.to_nil sep.2.1) sep.2.2 with v e
have := Valid'.merge_aux₁ hr.dual hl.dual h_1 v.dual
rw [size_dual, add_comm, size_dual, ← dual_balanceR, ← Valid'.dual_iff, size_dual,
add_comm rs] at this
exact this e
· refine Valid'.glue_aux hl hr sep (Or.inr ⟨not_lt.1 h_1, not_lt.1 h⟩)
#align ordnode.valid'.merge_aux Ordnode.Valid'.merge_aux
theorem Valid.merge {l r} (hl : Valid l) (hr : Valid r)
(sep : l.All fun x => r.All fun y => x < y) : Valid (@merge α l r) :=
(Valid'.merge_aux hl hr sep).1
#align ordnode.valid.merge Ordnode.Valid.merge
theorem insertWith.valid_aux [IsTotal α (· ≤ ·)] [@DecidableRel α (· ≤ ·)] (f : α → α) (x : α)
(hf : ∀ y, x ≤ y ∧ y ≤ x → x ≤ f y ∧ f y ≤ x) :
∀ {t o₁ o₂},
Valid' o₁ t o₂ →
Bounded nil o₁ x →
Bounded nil x o₂ →
Valid' o₁ (insertWith f x t) o₂ ∧ Raised (size t) (size (insertWith f x t))
| nil, o₁, o₂, _, bl, br => ⟨valid'_singleton bl br, Or.inr rfl⟩
| node sz l y r, o₁, o₂, h, bl, br => by
rw [insertWith, cmpLE]
split_ifs with h_1 h_2 <;> dsimp only
· rcases h with ⟨⟨lx, xr⟩, hs, hb⟩
rcases hf _ ⟨h_1, h_2⟩ with ⟨xf, fx⟩
refine
⟨⟨⟨lx.mono_right (le_trans h_2 xf), xr.mono_left (le_trans fx h_1)⟩, hs, hb⟩, Or.inl rfl⟩
· rcases insertWith.valid_aux f x hf h.left bl (lt_of_le_not_le h_1 h_2) with ⟨vl, e⟩
suffices H : _ by
refine ⟨vl.balanceL h.right H, ?_⟩
rw [size_balanceL vl.3 h.3.2.2 vl.2 h.2.2.2 H, h.2.size_eq]
exact (e.add_right _).add_right _
exact Or.inl ⟨_, e, h.3.1⟩
· have : y < x := lt_of_le_not_le ((total_of (· ≤ ·) _ _).resolve_left h_1) h_1
rcases insertWith.valid_aux f x hf h.right this br with ⟨vr, e⟩
suffices H : _ by
refine ⟨h.left.balanceR vr H, ?_⟩
rw [size_balanceR h.3.2.1 vr.3 h.2.2.1 vr.2 H, h.2.size_eq]
exact (e.add_left _).add_right _
exact Or.inr ⟨_, e, h.3.1⟩
#align ordnode.insert_with.valid_aux Ordnode.insertWith.valid_aux
theorem insertWith.valid [IsTotal α (· ≤ ·)] [@DecidableRel α (· ≤ ·)] (f : α → α) (x : α)
(hf : ∀ y, x ≤ y ∧ y ≤ x → x ≤ f y ∧ f y ≤ x) {t} (h : Valid t) : Valid (insertWith f x t) :=
(insertWith.valid_aux _ _ hf h ⟨⟩ ⟨⟩).1
#align ordnode.insert_with.valid Ordnode.insertWith.valid
theorem insert_eq_insertWith [@DecidableRel α (· ≤ ·)] (x : α) :
∀ t, Ordnode.insert x t = insertWith (fun _ => x) x t
| nil => rfl
| node _ l y r => by
unfold Ordnode.insert insertWith; cases cmpLE x y <;> simp [insert_eq_insertWith]
#align ordnode.insert_eq_insert_with Ordnode.insert_eq_insertWith
theorem insert.valid [IsTotal α (· ≤ ·)] [@DecidableRel α (· ≤ ·)] (x : α) {t} (h : Valid t) :
Valid (Ordnode.insert x t) := by
rw [insert_eq_insertWith]; exact insertWith.valid _ _ (fun _ _ => ⟨le_rfl, le_rfl⟩) h
#align ordnode.insert.valid Ordnode.insert.valid
theorem insert'_eq_insertWith [@DecidableRel α (· ≤ ·)] (x : α) :
∀ t, insert' x t = insertWith id x t
| nil => rfl
| node _ l y r => by
unfold insert' insertWith; cases cmpLE x y <;> simp [insert'_eq_insertWith]
#align ordnode.insert'_eq_insert_with Ordnode.insert'_eq_insertWith
theorem insert'.valid [IsTotal α (· ≤ ·)] [@DecidableRel α (· ≤ ·)] (x : α) {t} (h : Valid t) :
Valid (insert' x t) := by
rw [insert'_eq_insertWith]; exact insertWith.valid _ _ (fun _ => id) h
#align ordnode.insert'.valid Ordnode.insert'.valid
theorem Valid'.map_aux {β} [Preorder β] {f : α → β} (f_strict_mono : StrictMono f) {t a₁ a₂}
(h : Valid' a₁ t a₂) :
Valid' (Option.map f a₁) (map f t) (Option.map f a₂) ∧ (map f t).size = t.size := by
induction t generalizing a₁ a₂ with
| nil =>
simp [map]; apply valid'_nil
cases a₁; · trivial
cases a₂; · trivial
simp only [Bounded]
exact f_strict_mono h.ord
| node _ _ _ _ t_ih_l t_ih_r =>
have t_ih_l' := t_ih_l h.left
have t_ih_r' := t_ih_r h.right
clear t_ih_l t_ih_r
cases' t_ih_l' with t_l_valid t_l_size
cases' t_ih_r' with t_r_valid t_r_size
simp only [map, size_node, and_true]
constructor
· exact And.intro t_l_valid.ord t_r_valid.ord
· constructor
· rw [t_l_size, t_r_size]; exact h.sz.1
· constructor
· exact t_l_valid.sz
· exact t_r_valid.sz
· constructor
· rw [t_l_size, t_r_size]; exact h.bal.1
· constructor
· exact t_l_valid.bal
· exact t_r_valid.bal
#align ordnode.valid'.map_aux Ordnode.Valid'.map_aux
theorem map.valid {β} [Preorder β] {f : α → β} (f_strict_mono : StrictMono f) {t} (h : Valid t) :
Valid (map f t) :=
(Valid'.map_aux f_strict_mono h).1
#align ordnode.map.valid Ordnode.map.valid
theorem Valid'.erase_aux [@DecidableRel α (· ≤ ·)] (x : α) {t a₁ a₂} (h : Valid' a₁ t a₂) :
Valid' a₁ (erase x t) a₂ ∧ Raised (erase x t).size t.size := by
induction t generalizing a₁ a₂ with
| nil =>
simp [erase, Raised]; exact h
| node _ t_l t_x t_r t_ih_l t_ih_r =>
simp only [erase, size_node]
have t_ih_l' := t_ih_l h.left
have t_ih_r' := t_ih_r h.right
clear t_ih_l t_ih_r
cases' t_ih_l' with t_l_valid t_l_size
cases' t_ih_r' with t_r_valid t_r_size
cases cmpLE x t_x <;> rw [h.sz.1]
· suffices h_balanceable : _ by
constructor
· exact Valid'.balanceR t_l_valid h.right h_balanceable
· rw [size_balanceR t_l_valid.bal h.right.bal t_l_valid.sz h.right.sz h_balanceable]
repeat apply Raised.add_right
exact t_l_size
left; exists t_l.size; exact And.intro t_l_size h.bal.1
· have h_glue := Valid'.glue h.left h.right h.bal.1
cases' h_glue with h_glue_valid h_glue_sized
constructor
· exact h_glue_valid
· right; rw [h_glue_sized]
· suffices h_balanceable : _ by
constructor
· exact Valid'.balanceL h.left t_r_valid h_balanceable
· rw [size_balanceL h.left.bal t_r_valid.bal h.left.sz t_r_valid.sz h_balanceable]
apply Raised.add_right
apply Raised.add_left
exact t_r_size
right; exists t_r.size; exact And.intro t_r_size h.bal.1
#align ordnode.valid'.erase_aux Ordnode.Valid'.erase_aux
theorem erase.valid [@DecidableRel α (· ≤ ·)] (x : α) {t} (h : Valid t) : Valid (erase x t) :=
(Valid'.erase_aux x h).1
#align ordnode.erase.valid Ordnode.erase.valid
| Mathlib/Data/Ordmap/Ordset.lean | 1,642 | 1,676 | theorem size_erase_of_mem [@DecidableRel α (· ≤ ·)] {x : α} {t a₁ a₂} (h : Valid' a₁ t a₂)
(h_mem : x ∈ t) : size (erase x t) = size t - 1 := by |
induction t generalizing a₁ a₂ with
| nil =>
contradiction
| node _ t_l t_x t_r t_ih_l t_ih_r =>
have t_ih_l' := t_ih_l h.left
have t_ih_r' := t_ih_r h.right
clear t_ih_l t_ih_r
dsimp only [Membership.mem, mem] at h_mem
unfold erase
revert h_mem; cases cmpLE x t_x <;> intro h_mem <;> dsimp only at h_mem ⊢
· have t_ih_l := t_ih_l' h_mem
clear t_ih_l' t_ih_r'
have t_l_h := Valid'.erase_aux x h.left
cases' t_l_h with t_l_valid t_l_size
rw [size_balanceR t_l_valid.bal h.right.bal t_l_valid.sz h.right.sz
(Or.inl (Exists.intro t_l.size (And.intro t_l_size h.bal.1)))]
rw [t_ih_l, h.sz.1]
have h_pos_t_l_size := pos_size_of_mem h.left.sz h_mem
revert h_pos_t_l_size; cases' t_l.size with t_l_size <;> intro h_pos_t_l_size
· cases h_pos_t_l_size
· simp [Nat.add_right_comm]
· rw [(Valid'.glue h.left h.right h.bal.1).2, h.sz.1]; rfl
· have t_ih_r := t_ih_r' h_mem
clear t_ih_l' t_ih_r'
have t_r_h := Valid'.erase_aux x h.right
cases' t_r_h with t_r_valid t_r_size
rw [size_balanceL h.left.bal t_r_valid.bal h.left.sz t_r_valid.sz
(Or.inr (Exists.intro t_r.size (And.intro t_r_size h.bal.1)))]
rw [t_ih_r, h.sz.1]
have h_pos_t_r_size := pos_size_of_mem h.right.sz h_mem
revert h_pos_t_r_size; cases' t_r.size with t_r_size <;> intro h_pos_t_r_size
· cases h_pos_t_r_size
· simp [Nat.add_assoc]
|
/-
Copyright (c) 2021 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne, Kexing Ying
-/
import Mathlib.Probability.Notation
import Mathlib.Probability.Process.Stopping
#align_import probability.martingale.basic from "leanprover-community/mathlib"@"ba074af83b6cf54c3104e59402b39410ddbd6dca"
/-!
# Martingales
A family of functions `f : ι → Ω → E` is a martingale with respect to a filtration `ℱ` if every
`f i` is integrable, `f` is adapted with respect to `ℱ` and for all `i ≤ j`,
`μ[f j | ℱ i] =ᵐ[μ] f i`. On the other hand, `f : ι → Ω → E` is said to be a supermartingale
with respect to the filtration `ℱ` if `f i` is integrable, `f` is adapted with resepct to `ℱ`
and for all `i ≤ j`, `μ[f j | ℱ i] ≤ᵐ[μ] f i`. Finally, `f : ι → Ω → E` is said to be a
submartingale with respect to the filtration `ℱ` if `f i` is integrable, `f` is adapted with
resepct to `ℱ` and for all `i ≤ j`, `f i ≤ᵐ[μ] μ[f j | ℱ i]`.
The definitions of filtration and adapted can be found in `Probability.Process.Stopping`.
### Definitions
* `MeasureTheory.Martingale f ℱ μ`: `f` is a martingale with respect to filtration `ℱ` and
measure `μ`.
* `MeasureTheory.Supermartingale f ℱ μ`: `f` is a supermartingale with respect to
filtration `ℱ` and measure `μ`.
* `MeasureTheory.Submartingale f ℱ μ`: `f` is a submartingale with respect to filtration `ℱ` and
measure `μ`.
### Results
* `MeasureTheory.martingale_condexp f ℱ μ`: the sequence `fun i => μ[f | ℱ i, ℱ.le i])` is a
martingale with respect to `ℱ` and `μ`.
-/
open TopologicalSpace Filter
open scoped NNReal ENNReal MeasureTheory ProbabilityTheory
namespace MeasureTheory
variable {Ω E ι : Type*} [Preorder ι] {m0 : MeasurableSpace Ω} {μ : Measure Ω}
[NormedAddCommGroup E] [NormedSpace ℝ E] [CompleteSpace E] {f g : ι → Ω → E} {ℱ : Filtration ι m0}
/-- A family of functions `f : ι → Ω → E` is a martingale with respect to a filtration `ℱ` if `f`
is adapted with respect to `ℱ` and for all `i ≤ j`, `μ[f j | ℱ i] =ᵐ[μ] f i`. -/
def Martingale (f : ι → Ω → E) (ℱ : Filtration ι m0) (μ : Measure Ω) : Prop :=
Adapted ℱ f ∧ ∀ i j, i ≤ j → μ[f j|ℱ i] =ᵐ[μ] f i
#align measure_theory.martingale MeasureTheory.Martingale
/-- A family of integrable functions `f : ι → Ω → E` is a supermartingale with respect to a
filtration `ℱ` if `f` is adapted with respect to `ℱ` and for all `i ≤ j`,
`μ[f j | ℱ.le i] ≤ᵐ[μ] f i`. -/
def Supermartingale [LE E] (f : ι → Ω → E) (ℱ : Filtration ι m0) (μ : Measure Ω) : Prop :=
Adapted ℱ f ∧ (∀ i j, i ≤ j → μ[f j|ℱ i] ≤ᵐ[μ] f i) ∧ ∀ i, Integrable (f i) μ
#align measure_theory.supermartingale MeasureTheory.Supermartingale
/-- A family of integrable functions `f : ι → Ω → E` is a submartingale with respect to a
filtration `ℱ` if `f` is adapted with respect to `ℱ` and for all `i ≤ j`,
`f i ≤ᵐ[μ] μ[f j | ℱ.le i]`. -/
def Submartingale [LE E] (f : ι → Ω → E) (ℱ : Filtration ι m0) (μ : Measure Ω) : Prop :=
Adapted ℱ f ∧ (∀ i j, i ≤ j → f i ≤ᵐ[μ] μ[f j|ℱ i]) ∧ ∀ i, Integrable (f i) μ
#align measure_theory.submartingale MeasureTheory.Submartingale
theorem martingale_const (ℱ : Filtration ι m0) (μ : Measure Ω) [IsFiniteMeasure μ] (x : E) :
Martingale (fun _ _ => x) ℱ μ :=
⟨adapted_const ℱ _, fun i j _ => by rw [condexp_const (ℱ.le _)]⟩
#align measure_theory.martingale_const MeasureTheory.martingale_const
theorem martingale_const_fun [OrderBot ι] (ℱ : Filtration ι m0) (μ : Measure Ω) [IsFiniteMeasure μ]
{f : Ω → E} (hf : StronglyMeasurable[ℱ ⊥] f) (hfint : Integrable f μ) :
Martingale (fun _ => f) ℱ μ := by
refine ⟨fun i => hf.mono <| ℱ.mono bot_le, fun i j _ => ?_⟩
rw [condexp_of_stronglyMeasurable (ℱ.le _) (hf.mono <| ℱ.mono bot_le) hfint]
#align measure_theory.martingale_const_fun MeasureTheory.martingale_const_fun
variable (E)
theorem martingale_zero (ℱ : Filtration ι m0) (μ : Measure Ω) : Martingale (0 : ι → Ω → E) ℱ μ :=
⟨adapted_zero E ℱ, fun i j _ => by rw [Pi.zero_apply, condexp_zero]; simp⟩
#align measure_theory.martingale_zero MeasureTheory.martingale_zero
variable {E}
namespace Martingale
protected theorem adapted (hf : Martingale f ℱ μ) : Adapted ℱ f :=
hf.1
#align measure_theory.martingale.adapted MeasureTheory.Martingale.adapted
protected theorem stronglyMeasurable (hf : Martingale f ℱ μ) (i : ι) :
StronglyMeasurable[ℱ i] (f i) :=
hf.adapted i
#align measure_theory.martingale.strongly_measurable MeasureTheory.Martingale.stronglyMeasurable
theorem condexp_ae_eq (hf : Martingale f ℱ μ) {i j : ι} (hij : i ≤ j) : μ[f j|ℱ i] =ᵐ[μ] f i :=
hf.2 i j hij
#align measure_theory.martingale.condexp_ae_eq MeasureTheory.Martingale.condexp_ae_eq
protected theorem integrable (hf : Martingale f ℱ μ) (i : ι) : Integrable (f i) μ :=
integrable_condexp.congr (hf.condexp_ae_eq (le_refl i))
#align measure_theory.martingale.integrable MeasureTheory.Martingale.integrable
theorem setIntegral_eq [SigmaFiniteFiltration μ ℱ] (hf : Martingale f ℱ μ) {i j : ι} (hij : i ≤ j)
{s : Set Ω} (hs : MeasurableSet[ℱ i] s) : ∫ ω in s, f i ω ∂μ = ∫ ω in s, f j ω ∂μ := by
rw [← @setIntegral_condexp _ _ _ _ _ (ℱ i) m0 _ _ _ (ℱ.le i) _ (hf.integrable j) hs]
refine setIntegral_congr_ae (ℱ.le i s hs) ?_
filter_upwards [hf.2 i j hij] with _ heq _ using heq.symm
#align measure_theory.martingale.set_integral_eq MeasureTheory.Martingale.setIntegral_eq
@[deprecated (since := "2024-04-17")]
alias set_integral_eq := setIntegral_eq
theorem add (hf : Martingale f ℱ μ) (hg : Martingale g ℱ μ) : Martingale (f + g) ℱ μ := by
refine ⟨hf.adapted.add hg.adapted, fun i j hij => ?_⟩
exact (condexp_add (hf.integrable j) (hg.integrable j)).trans ((hf.2 i j hij).add (hg.2 i j hij))
#align measure_theory.martingale.add MeasureTheory.Martingale.add
theorem neg (hf : Martingale f ℱ μ) : Martingale (-f) ℱ μ :=
⟨hf.adapted.neg, fun i j hij => (condexp_neg (f j)).trans (hf.2 i j hij).neg⟩
#align measure_theory.martingale.neg MeasureTheory.Martingale.neg
theorem sub (hf : Martingale f ℱ μ) (hg : Martingale g ℱ μ) : Martingale (f - g) ℱ μ := by
rw [sub_eq_add_neg]; exact hf.add hg.neg
#align measure_theory.martingale.sub MeasureTheory.Martingale.sub
theorem smul (c : ℝ) (hf : Martingale f ℱ μ) : Martingale (c • f) ℱ μ := by
refine ⟨hf.adapted.smul c, fun i j hij => ?_⟩
refine (condexp_smul c (f j)).trans ((hf.2 i j hij).mono fun x hx => ?_)
simp only [Pi.smul_apply, hx]
#align measure_theory.martingale.smul MeasureTheory.Martingale.smul
theorem supermartingale [Preorder E] (hf : Martingale f ℱ μ) : Supermartingale f ℱ μ :=
⟨hf.1, fun i j hij => (hf.2 i j hij).le, fun i => hf.integrable i⟩
#align measure_theory.martingale.supermartingale MeasureTheory.Martingale.supermartingale
theorem submartingale [Preorder E] (hf : Martingale f ℱ μ) : Submartingale f ℱ μ :=
⟨hf.1, fun i j hij => (hf.2 i j hij).symm.le, fun i => hf.integrable i⟩
#align measure_theory.martingale.submartingale MeasureTheory.Martingale.submartingale
end Martingale
theorem martingale_iff [PartialOrder E] :
Martingale f ℱ μ ↔ Supermartingale f ℱ μ ∧ Submartingale f ℱ μ :=
⟨fun hf => ⟨hf.supermartingale, hf.submartingale⟩, fun ⟨hf₁, hf₂⟩ =>
⟨hf₁.1, fun i j hij => (hf₁.2.1 i j hij).antisymm (hf₂.2.1 i j hij)⟩⟩
#align measure_theory.martingale_iff MeasureTheory.martingale_iff
theorem martingale_condexp (f : Ω → E) (ℱ : Filtration ι m0) (μ : Measure Ω)
[SigmaFiniteFiltration μ ℱ] : Martingale (fun i => μ[f|ℱ i]) ℱ μ :=
⟨fun _ => stronglyMeasurable_condexp, fun _ j hij => condexp_condexp_of_le (ℱ.mono hij) (ℱ.le j)⟩
#align measure_theory.martingale_condexp MeasureTheory.martingale_condexp
namespace Supermartingale
protected theorem adapted [LE E] (hf : Supermartingale f ℱ μ) : Adapted ℱ f :=
hf.1
#align measure_theory.supermartingale.adapted MeasureTheory.Supermartingale.adapted
protected theorem stronglyMeasurable [LE E] (hf : Supermartingale f ℱ μ) (i : ι) :
StronglyMeasurable[ℱ i] (f i) :=
hf.adapted i
#align measure_theory.supermartingale.strongly_measurable MeasureTheory.Supermartingale.stronglyMeasurable
protected theorem integrable [LE E] (hf : Supermartingale f ℱ μ) (i : ι) : Integrable (f i) μ :=
hf.2.2 i
#align measure_theory.supermartingale.integrable MeasureTheory.Supermartingale.integrable
theorem condexp_ae_le [LE E] (hf : Supermartingale f ℱ μ) {i j : ι} (hij : i ≤ j) :
μ[f j|ℱ i] ≤ᵐ[μ] f i :=
hf.2.1 i j hij
#align measure_theory.supermartingale.condexp_ae_le MeasureTheory.Supermartingale.condexp_ae_le
theorem setIntegral_le [SigmaFiniteFiltration μ ℱ] {f : ι → Ω → ℝ} (hf : Supermartingale f ℱ μ)
{i j : ι} (hij : i ≤ j) {s : Set Ω} (hs : MeasurableSet[ℱ i] s) :
∫ ω in s, f j ω ∂μ ≤ ∫ ω in s, f i ω ∂μ := by
rw [← setIntegral_condexp (ℱ.le i) (hf.integrable j) hs]
refine setIntegral_mono_ae integrable_condexp.integrableOn (hf.integrable i).integrableOn ?_
filter_upwards [hf.2.1 i j hij] with _ heq using heq
#align measure_theory.supermartingale.set_integral_le MeasureTheory.Supermartingale.setIntegral_le
@[deprecated (since := "2024-04-17")]
alias set_integral_le := setIntegral_le
| Mathlib/Probability/Martingale/Basic.lean | 190 | 196 | theorem add [Preorder E] [CovariantClass E E (· + ·) (· ≤ ·)] (hf : Supermartingale f ℱ μ)
(hg : Supermartingale g ℱ μ) : Supermartingale (f + g) ℱ μ := by |
refine ⟨hf.1.add hg.1, fun i j hij => ?_, fun i => (hf.2.2 i).add (hg.2.2 i)⟩
refine (condexp_add (hf.integrable j) (hg.integrable j)).le.trans ?_
filter_upwards [hf.2.1 i j hij, hg.2.1 i j hij]
intros
refine add_le_add ?_ ?_ <;> assumption
|
/-
Copyright (c) 2023 Dagur Asgeirsson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Dagur Asgeirsson
-/
import Mathlib.Algebra.Category.ModuleCat.Free
import Mathlib.Topology.Category.Profinite.CofilteredLimit
import Mathlib.Topology.Category.Profinite.Product
import Mathlib.Topology.LocallyConstant.Algebra
import Mathlib.Init.Data.Bool.Lemmas
/-!
# Nöbeling's theorem
This file proves Nöbeling's theorem.
## Main result
* `LocallyConstant.freeOfProfinite`: Nöbeling's theorem.
For `S : Profinite`, the `ℤ`-module `LocallyConstant S ℤ` is free.
## Proof idea
We follow the proof of theorem 5.4 in [scholze2019condensed], in which the idea is to embed `S` in
a product of `I` copies of `Bool` for some sufficiently large `I`, and then to choose a
well-ordering on `I` and use ordinal induction over that well-order. Here we can let `I` be
the set of clopen subsets of `S` since `S` is totally separated.
The above means it suffices to prove the following statement: For a closed subset `C` of `I → Bool`,
the `ℤ`-module `LocallyConstant C ℤ` is free.
For `i : I`, let `e C i : LocallyConstant C ℤ` denote the map `fun f ↦ (if f.val i then 1 else 0)`.
The basis will consist of products `e C iᵣ * ⋯ * e C i₁` with `iᵣ > ⋯ > i₁` which cannot be written
as linear combinations of lexicographically smaller products. We call this set `GoodProducts C`
What is proved by ordinal induction is that this set is linearly independent. The fact that it
spans can be proved directly.
## References
- [scholze2019condensed], Theorem 5.4.
-/
universe u
namespace Profinite
namespace NobelingProof
variable {I : Type u} [LinearOrder I] [IsWellOrder I (·<·)] (C : Set (I → Bool))
open Profinite ContinuousMap CategoryTheory Limits Opposite Submodule
section Projections
/-!
## Projection maps
The purpose of this section is twofold.
Firstly, in the proof that the set `GoodProducts C` spans the whole module `LocallyConstant C ℤ`,
we need to project `C` down to finite discrete subsets and write `C` as a cofiltered limit of those.
Secondly, in the inductive argument, we need to project `C` down to "smaller" sets satisfying the
inductive hypothesis.
In this section we define the relevant projection maps and prove some compatibility results.
### Main definitions
* Let `J : I → Prop`. Then `Proj J : (I → Bool) → (I → Bool)` is the projection mapping everything
that satisfies `J i` to itself, and everything else to `false`.
* The image of `C` under `Proj J` is denoted `π C J` and the corresponding map `C → π C J` is called
`ProjRestrict`. If `J` implies `K` we have a map `ProjRestricts : π C K → π C J`.
* `spanCone_isLimit` establishes that when `C` is compact, it can be written as a limit of its
images under the maps `Proj (· ∈ s)` where `s : Finset I`.
-/
variable (J K L : I → Prop) [∀ i, Decidable (J i)] [∀ i, Decidable (K i)] [∀ i, Decidable (L i)]
/--
The projection mapping everything that satisfies `J i` to itself, and everything else to `false`
-/
def Proj : (I → Bool) → (I → Bool) :=
fun c i ↦ if J i then c i else false
@[simp]
theorem continuous_proj :
Continuous (Proj J : (I → Bool) → (I → Bool)) := by
dsimp (config := { unfoldPartialApp := true }) [Proj]
apply continuous_pi
intro i
split
· apply continuous_apply
· apply continuous_const
/-- The image of `Proj π J` -/
def π : Set (I → Bool) := (Proj J) '' C
/-- The restriction of `Proj π J` to a subset, mapping to its image. -/
@[simps!]
def ProjRestrict : C → π C J :=
Set.MapsTo.restrict (Proj J) _ _ (Set.mapsTo_image _ _)
@[simp]
theorem continuous_projRestrict : Continuous (ProjRestrict C J) :=
Continuous.restrict _ (continuous_proj _)
theorem proj_eq_self {x : I → Bool} (h : ∀ i, x i ≠ false → J i) : Proj J x = x := by
ext i
simp only [Proj, ite_eq_left_iff]
contrapose!
simpa only [ne_comm] using h i
theorem proj_prop_eq_self (hh : ∀ i x, x ∈ C → x i ≠ false → J i) : π C J = C := by
ext x
refine ⟨fun ⟨y, hy, h⟩ ↦ ?_, fun h ↦ ⟨x, h, ?_⟩⟩
· rwa [← h, proj_eq_self]; exact (hh · y hy)
· rw [proj_eq_self]; exact (hh · x h)
theorem proj_comp_of_subset (h : ∀ i, J i → K i) : (Proj J ∘ Proj K) =
(Proj J : (I → Bool) → (I → Bool)) := by
ext x i; dsimp [Proj]; aesop
theorem proj_eq_of_subset (h : ∀ i, J i → K i) : π (π C K) J = π C J := by
ext x
refine ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· obtain ⟨y, ⟨z, hz, rfl⟩, rfl⟩ := h
refine ⟨z, hz, (?_ : _ = (Proj J ∘ Proj K) z)⟩
rw [proj_comp_of_subset J K h]
· obtain ⟨y, hy, rfl⟩ := h
dsimp [π]
rw [← Set.image_comp]
refine ⟨y, hy, ?_⟩
rw [proj_comp_of_subset J K h]
variable {J K L}
/-- A variant of `ProjRestrict` with domain of the form `π C K` -/
@[simps!]
def ProjRestricts (h : ∀ i, J i → K i) : π C K → π C J :=
Homeomorph.setCongr (proj_eq_of_subset C J K h) ∘ ProjRestrict (π C K) J
@[simp]
theorem continuous_projRestricts (h : ∀ i, J i → K i) : Continuous (ProjRestricts C h) :=
Continuous.comp (Homeomorph.continuous _) (continuous_projRestrict _ _)
theorem surjective_projRestricts (h : ∀ i, J i → K i) : Function.Surjective (ProjRestricts C h) :=
(Homeomorph.surjective _).comp (Set.surjective_mapsTo_image_restrict _ _)
variable (J) in
theorem projRestricts_eq_id : ProjRestricts C (fun i (h : J i) ↦ h) = id := by
ext ⟨x, y, hy, rfl⟩ i
simp (config := { contextual := true }) only [π, Proj, ProjRestricts_coe, id_eq, if_true]
| Mathlib/Topology/Category/Profinite/Nobeling.lean | 160 | 164 | theorem projRestricts_eq_comp (hJK : ∀ i, J i → K i) (hKL : ∀ i, K i → L i) :
ProjRestricts C hJK ∘ ProjRestricts C hKL = ProjRestricts C (fun i ↦ hKL i ∘ hJK i) := by |
ext x i
simp only [π, Proj, Function.comp_apply, ProjRestricts_coe]
aesop
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Fintype.Basic
import Mathlib.Data.Finset.Card
import Mathlib.Data.List.NodupEquivFin
import Mathlib.Data.Set.Image
#align_import data.fintype.card from "leanprover-community/mathlib"@"bf2428c9486c407ca38b5b3fb10b87dad0bc99fa"
/-!
# Cardinalities of finite types
## Main declarations
* `Fintype.card α`: Cardinality of a fintype. Equal to `Finset.univ.card`.
* `Fintype.truncEquivFin`: A fintype `α` is computably equivalent to `Fin (card α)`. The
`Trunc`-free, noncomputable version is `Fintype.equivFin`.
* `Fintype.truncEquivOfCardEq` `Fintype.equivOfCardEq`: Two fintypes of same cardinality are
equivalent. See above.
* `Fin.equiv_iff_eq`: `Fin m ≃ Fin n` iff `m = n`.
* `Infinite.natEmbedding`: An embedding of `ℕ` into an infinite type.
We also provide the following versions of the pigeonholes principle.
* `Fintype.exists_ne_map_eq_of_card_lt` and `isEmpty_of_card_lt`: Finitely many pigeons and
pigeonholes. Weak formulation.
* `Finite.exists_ne_map_eq_of_infinite`: Infinitely many pigeons in finitely many pigeonholes.
Weak formulation.
* `Finite.exists_infinite_fiber`: Infinitely many pigeons in finitely many pigeonholes. Strong
formulation.
Some more pigeonhole-like statements can be found in `Data.Fintype.CardEmbedding`.
Types which have an injection from/a surjection to an `Infinite` type are themselves `Infinite`.
See `Infinite.of_injective` and `Infinite.of_surjective`.
## Instances
We provide `Infinite` instances for
* specific types: `ℕ`, `ℤ`, `String`
* type constructors: `Multiset α`, `List α`
-/
assert_not_exists MonoidWithZero
assert_not_exists MulAction
open Function
open Nat
universe u v
variable {α β γ : Type*}
open Finset Function
namespace Fintype
/-- `card α` is the number of elements in `α`, defined when `α` is a fintype. -/
def card (α) [Fintype α] : ℕ :=
(@univ α _).card
#align fintype.card Fintype.card
/-- There is (computably) an equivalence between `α` and `Fin (card α)`.
Since it is not unique and depends on which permutation
of the universe list is used, the equivalence is wrapped in `Trunc` to
preserve computability.
See `Fintype.equivFin` for the noncomputable version,
and `Fintype.truncEquivFinOfCardEq` and `Fintype.equivFinOfCardEq`
for an equiv `α ≃ Fin n` given `Fintype.card α = n`.
See `Fintype.truncFinBijection` for a version without `[DecidableEq α]`.
-/
def truncEquivFin (α) [DecidableEq α] [Fintype α] : Trunc (α ≃ Fin (card α)) := by
unfold card Finset.card
exact
Quot.recOnSubsingleton'
(motive := fun s : Multiset α =>
(∀ x : α, x ∈ s) → s.Nodup → Trunc (α ≃ Fin (Multiset.card s)))
univ.val
(fun l (h : ∀ x : α, x ∈ l) (nd : l.Nodup) => Trunc.mk (nd.getEquivOfForallMemList _ h).symm)
mem_univ_val univ.2
#align fintype.trunc_equiv_fin Fintype.truncEquivFin
/-- There is (noncomputably) an equivalence between `α` and `Fin (card α)`.
See `Fintype.truncEquivFin` for the computable version,
and `Fintype.truncEquivFinOfCardEq` and `Fintype.equivFinOfCardEq`
for an equiv `α ≃ Fin n` given `Fintype.card α = n`.
-/
noncomputable def equivFin (α) [Fintype α] : α ≃ Fin (card α) :=
letI := Classical.decEq α
(truncEquivFin α).out
#align fintype.equiv_fin Fintype.equivFin
/-- There is (computably) a bijection between `Fin (card α)` and `α`.
Since it is not unique and depends on which permutation
of the universe list is used, the bijection is wrapped in `Trunc` to
preserve computability.
See `Fintype.truncEquivFin` for a version that gives an equivalence
given `[DecidableEq α]`.
-/
def truncFinBijection (α) [Fintype α] : Trunc { f : Fin (card α) → α // Bijective f } := by
unfold card Finset.card
refine
Quot.recOnSubsingleton'
(motive := fun s : Multiset α =>
(∀ x : α, x ∈ s) → s.Nodup → Trunc {f : Fin (Multiset.card s) → α // Bijective f})
univ.val
(fun l (h : ∀ x : α, x ∈ l) (nd : l.Nodup) => Trunc.mk (nd.getBijectionOfForallMemList _ h))
mem_univ_val univ.2
#align fintype.trunc_fin_bijection Fintype.truncFinBijection
theorem subtype_card {p : α → Prop} (s : Finset α) (H : ∀ x : α, x ∈ s ↔ p x) :
@card { x // p x } (Fintype.subtype s H) = s.card :=
Multiset.card_pmap _ _ _
#align fintype.subtype_card Fintype.subtype_card
theorem card_of_subtype {p : α → Prop} (s : Finset α) (H : ∀ x : α, x ∈ s ↔ p x)
[Fintype { x // p x }] : card { x // p x } = s.card := by
rw [← subtype_card s H]
congr
apply Subsingleton.elim
#align fintype.card_of_subtype Fintype.card_of_subtype
@[simp]
theorem card_ofFinset {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) :
@Fintype.card p (ofFinset s H) = s.card :=
Fintype.subtype_card s H
#align fintype.card_of_finset Fintype.card_ofFinset
theorem card_of_finset' {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) [Fintype p] :
Fintype.card p = s.card := by rw [← card_ofFinset s H]; congr; apply Subsingleton.elim
#align fintype.card_of_finset' Fintype.card_of_finset'
end Fintype
namespace Fintype
theorem ofEquiv_card [Fintype α] (f : α ≃ β) : @card β (ofEquiv α f) = card α :=
Multiset.card_map _ _
#align fintype.of_equiv_card Fintype.ofEquiv_card
theorem card_congr {α β} [Fintype α] [Fintype β] (f : α ≃ β) : card α = card β := by
rw [← ofEquiv_card f]; congr; apply Subsingleton.elim
#align fintype.card_congr Fintype.card_congr
@[congr]
theorem card_congr' {α β} [Fintype α] [Fintype β] (h : α = β) : card α = card β :=
card_congr (by rw [h])
#align fintype.card_congr' Fintype.card_congr'
section
variable [Fintype α] [Fintype β]
/-- If the cardinality of `α` is `n`, there is computably a bijection between `α` and `Fin n`.
See `Fintype.equivFinOfCardEq` for the noncomputable definition,
and `Fintype.truncEquivFin` and `Fintype.equivFin` for the bijection `α ≃ Fin (card α)`.
-/
def truncEquivFinOfCardEq [DecidableEq α] {n : ℕ} (h : Fintype.card α = n) : Trunc (α ≃ Fin n) :=
(truncEquivFin α).map fun e => e.trans (finCongr h)
#align fintype.trunc_equiv_fin_of_card_eq Fintype.truncEquivFinOfCardEq
/-- If the cardinality of `α` is `n`, there is noncomputably a bijection between `α` and `Fin n`.
See `Fintype.truncEquivFinOfCardEq` for the computable definition,
and `Fintype.truncEquivFin` and `Fintype.equivFin` for the bijection `α ≃ Fin (card α)`.
-/
noncomputable def equivFinOfCardEq {n : ℕ} (h : Fintype.card α = n) : α ≃ Fin n :=
letI := Classical.decEq α
(truncEquivFinOfCardEq h).out
#align fintype.equiv_fin_of_card_eq Fintype.equivFinOfCardEq
/-- Two `Fintype`s with the same cardinality are (computably) in bijection.
See `Fintype.equivOfCardEq` for the noncomputable version,
and `Fintype.truncEquivFinOfCardEq` and `Fintype.equivFinOfCardEq` for
the specialization to `Fin`.
-/
def truncEquivOfCardEq [DecidableEq α] [DecidableEq β] (h : card α = card β) : Trunc (α ≃ β) :=
(truncEquivFinOfCardEq h).bind fun e => (truncEquivFin β).map fun e' => e.trans e'.symm
#align fintype.trunc_equiv_of_card_eq Fintype.truncEquivOfCardEq
/-- Two `Fintype`s with the same cardinality are (noncomputably) in bijection.
See `Fintype.truncEquivOfCardEq` for the computable version,
and `Fintype.truncEquivFinOfCardEq` and `Fintype.equivFinOfCardEq` for
the specialization to `Fin`.
-/
noncomputable def equivOfCardEq (h : card α = card β) : α ≃ β := by
letI := Classical.decEq α
letI := Classical.decEq β
exact (truncEquivOfCardEq h).out
#align fintype.equiv_of_card_eq Fintype.equivOfCardEq
end
theorem card_eq {α β} [_F : Fintype α] [_G : Fintype β] : card α = card β ↔ Nonempty (α ≃ β) :=
⟨fun h =>
haveI := Classical.propDecidable
(truncEquivOfCardEq h).nonempty,
fun ⟨f⟩ => card_congr f⟩
#align fintype.card_eq Fintype.card_eq
/-- Note: this lemma is specifically about `Fintype.ofSubsingleton`. For a statement about
arbitrary `Fintype` instances, use either `Fintype.card_le_one_iff_subsingleton` or
`Fintype.card_unique`. -/
@[simp]
theorem card_ofSubsingleton (a : α) [Subsingleton α] : @Fintype.card _ (ofSubsingleton a) = 1 :=
rfl
#align fintype.card_of_subsingleton Fintype.card_ofSubsingleton
@[simp]
theorem card_unique [Unique α] [h : Fintype α] : Fintype.card α = 1 :=
Subsingleton.elim (ofSubsingleton default) h ▸ card_ofSubsingleton _
#align fintype.card_unique Fintype.card_unique
/-- Note: this lemma is specifically about `Fintype.ofIsEmpty`. For a statement about
arbitrary `Fintype` instances, use `Fintype.card_eq_zero`. -/
@[simp]
theorem card_ofIsEmpty [IsEmpty α] : @Fintype.card α Fintype.ofIsEmpty = 0 :=
rfl
#align fintype.card_of_is_empty Fintype.card_ofIsEmpty
end Fintype
namespace Set
variable {s t : Set α}
-- We use an arbitrary `[Fintype s]` instance here,
-- not necessarily coming from a `[Fintype α]`.
@[simp]
theorem toFinset_card {α : Type*} (s : Set α) [Fintype s] : s.toFinset.card = Fintype.card s :=
Multiset.card_map Subtype.val Finset.univ.val
#align set.to_finset_card Set.toFinset_card
end Set
@[simp]
theorem Finset.card_univ [Fintype α] : (Finset.univ : Finset α).card = Fintype.card α :=
rfl
#align finset.card_univ Finset.card_univ
theorem Finset.eq_univ_of_card [Fintype α] (s : Finset α) (hs : s.card = Fintype.card α) :
s = univ :=
eq_of_subset_of_card_le (subset_univ _) <| by rw [hs, Finset.card_univ]
#align finset.eq_univ_of_card Finset.eq_univ_of_card
theorem Finset.card_eq_iff_eq_univ [Fintype α] (s : Finset α) :
s.card = Fintype.card α ↔ s = Finset.univ :=
⟨s.eq_univ_of_card, by
rintro rfl
exact Finset.card_univ⟩
#align finset.card_eq_iff_eq_univ Finset.card_eq_iff_eq_univ
theorem Finset.card_le_univ [Fintype α] (s : Finset α) : s.card ≤ Fintype.card α :=
card_le_card (subset_univ s)
#align finset.card_le_univ Finset.card_le_univ
theorem Finset.card_lt_univ_of_not_mem [Fintype α] {s : Finset α} {x : α} (hx : x ∉ s) :
s.card < Fintype.card α :=
card_lt_card ⟨subset_univ s, not_forall.2 ⟨x, fun hx' => hx (hx' <| mem_univ x)⟩⟩
#align finset.card_lt_univ_of_not_mem Finset.card_lt_univ_of_not_mem
theorem Finset.card_lt_iff_ne_univ [Fintype α] (s : Finset α) :
s.card < Fintype.card α ↔ s ≠ Finset.univ :=
s.card_le_univ.lt_iff_ne.trans (not_congr s.card_eq_iff_eq_univ)
#align finset.card_lt_iff_ne_univ Finset.card_lt_iff_ne_univ
theorem Finset.card_compl_lt_iff_nonempty [Fintype α] [DecidableEq α] (s : Finset α) :
sᶜ.card < Fintype.card α ↔ s.Nonempty :=
sᶜ.card_lt_iff_ne_univ.trans s.compl_ne_univ_iff_nonempty
#align finset.card_compl_lt_iff_nonempty Finset.card_compl_lt_iff_nonempty
theorem Finset.card_univ_diff [DecidableEq α] [Fintype α] (s : Finset α) :
(Finset.univ \ s).card = Fintype.card α - s.card :=
Finset.card_sdiff (subset_univ s)
#align finset.card_univ_diff Finset.card_univ_diff
theorem Finset.card_compl [DecidableEq α] [Fintype α] (s : Finset α) :
sᶜ.card = Fintype.card α - s.card :=
Finset.card_univ_diff s
#align finset.card_compl Finset.card_compl
@[simp]
theorem Finset.card_add_card_compl [DecidableEq α] [Fintype α] (s : Finset α) :
s.card + sᶜ.card = Fintype.card α := by
rw [Finset.card_compl, ← Nat.add_sub_assoc (card_le_univ s), Nat.add_sub_cancel_left]
@[simp]
theorem Finset.card_compl_add_card [DecidableEq α] [Fintype α] (s : Finset α) :
sᶜ.card + s.card = Fintype.card α := by
rw [add_comm, card_add_card_compl]
theorem Fintype.card_compl_set [Fintype α] (s : Set α) [Fintype s] [Fintype (↥sᶜ : Sort _)] :
Fintype.card (↥sᶜ : Sort _) = Fintype.card α - Fintype.card s := by
classical rw [← Set.toFinset_card, ← Set.toFinset_card, ← Finset.card_compl, Set.toFinset_compl]
#align fintype.card_compl_set Fintype.card_compl_set
@[simp]
theorem Fintype.card_fin (n : ℕ) : Fintype.card (Fin n) = n :=
List.length_finRange n
#align fintype.card_fin Fintype.card_fin
theorem Fintype.card_fin_lt_of_le {m n : ℕ} (h : m ≤ n) :
Fintype.card {i : Fin n // i < m} = m := by
conv_rhs => rw [← Fintype.card_fin m]
apply Fintype.card_congr
exact { toFun := fun ⟨⟨i, _⟩, hi⟩ ↦ ⟨i, hi⟩
invFun := fun ⟨i, hi⟩ ↦ ⟨⟨i, lt_of_lt_of_le hi h⟩, hi⟩
left_inv := fun i ↦ rfl
right_inv := fun i ↦ rfl }
theorem Finset.card_fin (n : ℕ) : Finset.card (Finset.univ : Finset (Fin n)) = n := by simp
#align finset.card_fin Finset.card_fin
/-- `Fin` as a map from `ℕ` to `Type` is injective. Note that since this is a statement about
equality of types, using it should be avoided if possible. -/
theorem fin_injective : Function.Injective Fin := fun m n h =>
(Fintype.card_fin m).symm.trans <| (Fintype.card_congr <| Equiv.cast h).trans (Fintype.card_fin n)
#align fin_injective fin_injective
/-- A reversed version of `Fin.cast_eq_cast` that is easier to rewrite with. -/
theorem Fin.cast_eq_cast' {n m : ℕ} (h : Fin n = Fin m) :
_root_.cast h = Fin.cast (fin_injective h) := by
cases fin_injective h
rfl
#align fin.cast_eq_cast' Fin.cast_eq_cast'
theorem card_finset_fin_le {n : ℕ} (s : Finset (Fin n)) : s.card ≤ n := by
simpa only [Fintype.card_fin] using s.card_le_univ
#align card_finset_fin_le card_finset_fin_le
--@[simp] Porting note (#10618): simp can prove it
theorem Fintype.card_subtype_eq (y : α) [Fintype { x // x = y }] :
Fintype.card { x // x = y } = 1 :=
Fintype.card_unique
#align fintype.card_subtype_eq Fintype.card_subtype_eq
--@[simp] Porting note (#10618): simp can prove it
theorem Fintype.card_subtype_eq' (y : α) [Fintype { x // y = x }] :
Fintype.card { x // y = x } = 1 :=
Fintype.card_unique
#align fintype.card_subtype_eq' Fintype.card_subtype_eq'
theorem Fintype.card_empty : Fintype.card Empty = 0 :=
rfl
#align fintype.card_empty Fintype.card_empty
theorem Fintype.card_pempty : Fintype.card PEmpty = 0 :=
rfl
#align fintype.card_pempty Fintype.card_pempty
theorem Fintype.card_unit : Fintype.card Unit = 1 :=
rfl
#align fintype.card_unit Fintype.card_unit
@[simp]
theorem Fintype.card_punit : Fintype.card PUnit = 1 :=
rfl
#align fintype.card_punit Fintype.card_punit
@[simp]
theorem Fintype.card_bool : Fintype.card Bool = 2 :=
rfl
#align fintype.card_bool Fintype.card_bool
@[simp]
theorem Fintype.card_ulift (α : Type*) [Fintype α] : Fintype.card (ULift α) = Fintype.card α :=
Fintype.ofEquiv_card _
#align fintype.card_ulift Fintype.card_ulift
@[simp]
theorem Fintype.card_plift (α : Type*) [Fintype α] : Fintype.card (PLift α) = Fintype.card α :=
Fintype.ofEquiv_card _
#align fintype.card_plift Fintype.card_plift
@[simp]
theorem Fintype.card_orderDual (α : Type*) [Fintype α] : Fintype.card αᵒᵈ = Fintype.card α :=
rfl
#align fintype.card_order_dual Fintype.card_orderDual
@[simp]
theorem Fintype.card_lex (α : Type*) [Fintype α] : Fintype.card (Lex α) = Fintype.card α :=
rfl
#align fintype.card_lex Fintype.card_lex
@[simp] lemma Fintype.card_multiplicative (α : Type*) [Fintype α] :
card (Multiplicative α) = card α := Finset.card_map _
@[simp] lemma Fintype.card_additive (α : Type*) [Fintype α] : card (Additive α) = card α :=
Finset.card_map _
/-- Given that `α ⊕ β` is a fintype, `α` is also a fintype. This is non-computable as it uses
that `Sum.inl` is an injection, but there's no clear inverse if `α` is empty. -/
noncomputable def Fintype.sumLeft {α β} [Fintype (Sum α β)] : Fintype α :=
Fintype.ofInjective (Sum.inl : α → Sum α β) Sum.inl_injective
#align fintype.sum_left Fintype.sumLeft
/-- Given that `α ⊕ β` is a fintype, `β` is also a fintype. This is non-computable as it uses
that `Sum.inr` is an injection, but there's no clear inverse if `β` is empty. -/
noncomputable def Fintype.sumRight {α β} [Fintype (Sum α β)] : Fintype β :=
Fintype.ofInjective (Sum.inr : β → Sum α β) Sum.inr_injective
#align fintype.sum_right Fintype.sumRight
/-!
### Relation to `Finite`
In this section we prove that `α : Type*` is `Finite` if and only if `Fintype α` is nonempty.
-/
-- @[nolint fintype_finite] -- Porting note: do we need this
protected theorem Fintype.finite {α : Type*} (_inst : Fintype α) : Finite α :=
⟨Fintype.equivFin α⟩
#align fintype.finite Fintype.finite
/-- For efficiency reasons, we want `Finite` instances to have higher
priority than ones coming from `Fintype` instances. -/
-- @[nolint fintype_finite] -- Porting note: do we need this
instance (priority := 900) Finite.of_fintype (α : Type*) [Fintype α] : Finite α :=
Fintype.finite ‹_›
#align finite.of_fintype Finite.of_fintype
theorem finite_iff_nonempty_fintype (α : Type*) : Finite α ↔ Nonempty (Fintype α) :=
⟨fun h =>
let ⟨_k, ⟨e⟩⟩ := @Finite.exists_equiv_fin α h
⟨Fintype.ofEquiv _ e.symm⟩,
fun ⟨_⟩ => inferInstance⟩
#align finite_iff_nonempty_fintype finite_iff_nonempty_fintype
/-- See also `nonempty_encodable`, `nonempty_denumerable`. -/
theorem nonempty_fintype (α : Type*) [Finite α] : Nonempty (Fintype α) :=
(finite_iff_nonempty_fintype α).mp ‹_›
#align nonempty_fintype nonempty_fintype
/-- Noncomputably get a `Fintype` instance from a `Finite` instance. This is not an
instance because we want `Fintype` instances to be useful for computations. -/
noncomputable def Fintype.ofFinite (α : Type*) [Finite α] : Fintype α :=
(nonempty_fintype α).some
#align fintype.of_finite Fintype.ofFinite
| Mathlib/Data/Fintype/Card.lean | 453 | 455 | theorem Finite.of_injective {α β : Sort*} [Finite β] (f : α → β) (H : Injective f) : Finite α := by |
rcases Finite.exists_equiv_fin β with ⟨n, ⟨e⟩⟩
classical exact .of_equiv (Set.range (e ∘ f)) (Equiv.ofInjective _ (e.injective.comp H)).symm
|
/-
Copyright (c) 2019 Jean Lo. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jean Lo, Bhavik Mehta, Yaël Dillies
-/
import Mathlib.Analysis.Convex.Basic
import Mathlib.Analysis.Convex.Hull
import Mathlib.Analysis.NormedSpace.Basic
import Mathlib.Topology.Bornology.Absorbs
#align_import analysis.locally_convex.basic from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Local convexity
This file defines absorbent and balanced sets.
An absorbent set is one that "surrounds" the origin. The idea is made precise by requiring that any
point belongs to all large enough scalings of the set. This is the vector world analog of a
topological neighborhood of the origin.
A balanced set is one that is everywhere around the origin. This means that `a • s ⊆ s` for all `a`
of norm less than `1`.
## Main declarations
For a module over a normed ring:
* `Absorbs`: A set `s` absorbs a set `t` if all large scalings of `s` contain `t`.
* `Absorbent`: A set `s` is absorbent if every point eventually belongs to all large scalings of
`s`.
* `Balanced`: A set `s` is balanced if `a • s ⊆ s` for all `a` of norm less than `1`.
## References
* [H. H. Schaefer, *Topological Vector Spaces*][schaefer1966]
## Tags
absorbent, balanced, locally convex, LCTVS
-/
open Set
open Pointwise Topology
variable {𝕜 𝕝 E : Type*} {ι : Sort*} {κ : ι → Sort*}
section SeminormedRing
variable [SeminormedRing 𝕜]
section SMul
variable [SMul 𝕜 E] {s t u v A B : Set E}
variable (𝕜)
/-- A set `A` is balanced if `a • A` is contained in `A` whenever `a` has norm at most `1`. -/
def Balanced (A : Set E) :=
∀ a : 𝕜, ‖a‖ ≤ 1 → a • A ⊆ A
#align balanced Balanced
variable {𝕜}
lemma absorbs_iff_norm : Absorbs 𝕜 A B ↔ ∃ r, ∀ c : 𝕜, r ≤ ‖c‖ → B ⊆ c • A :=
Filter.atTop_basis.cobounded_of_norm.eventually_iff.trans <| by simp only [true_and]; rfl
alias ⟨_, Absorbs.of_norm⟩ := absorbs_iff_norm
lemma Absorbs.exists_pos (h : Absorbs 𝕜 A B) : ∃ r > 0, ∀ c : 𝕜, r ≤ ‖c‖ → B ⊆ c • A :=
let ⟨r, hr₁, hr⟩ := (Filter.atTop_basis' 1).cobounded_of_norm.eventually_iff.1 h
⟨r, one_pos.trans_le hr₁, hr⟩
theorem balanced_iff_smul_mem : Balanced 𝕜 s ↔ ∀ ⦃a : 𝕜⦄, ‖a‖ ≤ 1 → ∀ ⦃x : E⦄, x ∈ s → a • x ∈ s :=
forall₂_congr fun _a _ha => smul_set_subset_iff
#align balanced_iff_smul_mem balanced_iff_smul_mem
alias ⟨Balanced.smul_mem, _⟩ := balanced_iff_smul_mem
#align balanced.smul_mem Balanced.smul_mem
theorem balanced_iff_closedBall_smul : Balanced 𝕜 s ↔ Metric.closedBall (0 : 𝕜) 1 • s ⊆ s := by
simp [balanced_iff_smul_mem, smul_subset_iff]
@[simp]
theorem balanced_empty : Balanced 𝕜 (∅ : Set E) := fun _ _ => by rw [smul_set_empty]
#align balanced_empty balanced_empty
@[simp]
theorem balanced_univ : Balanced 𝕜 (univ : Set E) := fun _a _ha => subset_univ _
#align balanced_univ balanced_univ
theorem Balanced.union (hA : Balanced 𝕜 A) (hB : Balanced 𝕜 B) : Balanced 𝕜 (A ∪ B) := fun _a ha =>
smul_set_union.subset.trans <| union_subset_union (hA _ ha) <| hB _ ha
#align balanced.union Balanced.union
theorem Balanced.inter (hA : Balanced 𝕜 A) (hB : Balanced 𝕜 B) : Balanced 𝕜 (A ∩ B) := fun _a ha =>
smul_set_inter_subset.trans <| inter_subset_inter (hA _ ha) <| hB _ ha
#align balanced.inter Balanced.inter
theorem balanced_iUnion {f : ι → Set E} (h : ∀ i, Balanced 𝕜 (f i)) : Balanced 𝕜 (⋃ i, f i) :=
fun _a ha => (smul_set_iUnion _ _).subset.trans <| iUnion_mono fun _ => h _ _ ha
#align balanced_Union balanced_iUnion
theorem balanced_iUnion₂ {f : ∀ i, κ i → Set E} (h : ∀ i j, Balanced 𝕜 (f i j)) :
Balanced 𝕜 (⋃ (i) (j), f i j) :=
balanced_iUnion fun _ => balanced_iUnion <| h _
#align balanced_Union₂ balanced_iUnion₂
theorem balanced_iInter {f : ι → Set E} (h : ∀ i, Balanced 𝕜 (f i)) : Balanced 𝕜 (⋂ i, f i) :=
fun _a ha => (smul_set_iInter_subset _ _).trans <| iInter_mono fun _ => h _ _ ha
#align balanced_Inter balanced_iInter
theorem balanced_iInter₂ {f : ∀ i, κ i → Set E} (h : ∀ i j, Balanced 𝕜 (f i j)) :
Balanced 𝕜 (⋂ (i) (j), f i j) :=
balanced_iInter fun _ => balanced_iInter <| h _
#align balanced_Inter₂ balanced_iInter₂
variable [SMul 𝕝 E] [SMulCommClass 𝕜 𝕝 E]
theorem Balanced.smul (a : 𝕝) (hs : Balanced 𝕜 s) : Balanced 𝕜 (a • s) := fun _b hb =>
(smul_comm _ _ _).subset.trans <| smul_set_mono <| hs _ hb
#align balanced.smul Balanced.smul
end SMul
section Module
variable [AddCommGroup E] [Module 𝕜 E] {s s₁ s₂ t t₁ t₂ : Set E}
theorem Balanced.neg : Balanced 𝕜 s → Balanced 𝕜 (-s) :=
forall₂_imp fun _ _ h => (smul_set_neg _ _).subset.trans <| neg_subset_neg.2 h
#align balanced.neg Balanced.neg
@[simp]
theorem balanced_neg : Balanced 𝕜 (-s) ↔ Balanced 𝕜 s :=
⟨fun h ↦ neg_neg s ▸ h.neg, fun h ↦ h.neg⟩
theorem Balanced.neg_mem_iff [NormOneClass 𝕜] (h : Balanced 𝕜 s) {x : E} : -x ∈ s ↔ x ∈ s :=
⟨fun hx ↦ by simpa using h.smul_mem (a := -1) (by simp) hx,
fun hx ↦ by simpa using h.smul_mem (a := -1) (by simp) hx⟩
#align balanced.neg_mem_iff Balanced.neg_mem_iff
theorem Balanced.neg_eq [NormOneClass 𝕜] (h : Balanced 𝕜 s) : -s = s :=
Set.ext fun _ ↦ h.neg_mem_iff
theorem Balanced.add (hs : Balanced 𝕜 s) (ht : Balanced 𝕜 t) : Balanced 𝕜 (s + t) := fun _a ha =>
(smul_add _ _ _).subset.trans <| add_subset_add (hs _ ha) <| ht _ ha
#align balanced.add Balanced.add
theorem Balanced.sub (hs : Balanced 𝕜 s) (ht : Balanced 𝕜 t) : Balanced 𝕜 (s - t) := by
simp_rw [sub_eq_add_neg]
exact hs.add ht.neg
#align balanced.sub Balanced.sub
theorem balanced_zero : Balanced 𝕜 (0 : Set E) := fun _a _ha => (smul_zero _).subset
#align balanced_zero balanced_zero
end Module
end SeminormedRing
section NormedDivisionRing
variable [NormedDivisionRing 𝕜] [AddCommGroup E] [Module 𝕜 E] {s t : Set E} {x : E} {a b : 𝕜}
theorem absorbs_iff_eventually_nhdsWithin_zero :
Absorbs 𝕜 s t ↔ ∀ᶠ c : 𝕜 in 𝓝[≠] 0, MapsTo (c • ·) t s := by
rw [absorbs_iff_eventually_cobounded_mapsTo, ← Filter.inv_cobounded₀]; rfl
alias ⟨Absorbs.eventually_nhdsWithin_zero, _⟩ := absorbs_iff_eventually_nhdsWithin_zero
theorem absorbent_iff_eventually_nhdsWithin_zero :
Absorbent 𝕜 s ↔ ∀ x : E, ∀ᶠ c : 𝕜 in 𝓝[≠] 0, c • x ∈ s :=
forall_congr' fun x ↦ by simp only [absorbs_iff_eventually_nhdsWithin_zero, mapsTo_singleton]
alias ⟨Absorbent.eventually_nhdsWithin_zero, _⟩ := absorbent_iff_eventually_nhdsWithin_zero
| Mathlib/Analysis/LocallyConvex/Basic.lean | 178 | 183 | theorem absorbs_iff_eventually_nhds_zero (h₀ : 0 ∈ s) :
Absorbs 𝕜 s t ↔ ∀ᶠ c : 𝕜 in 𝓝 0, MapsTo (c • ·) t s := by |
rw [← nhdsWithin_compl_singleton_sup_pure, Filter.eventually_sup, Filter.eventually_pure,
← absorbs_iff_eventually_nhdsWithin_zero, and_iff_left]
intro x _
simpa only [zero_smul]
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Alexander Bentkamp, Anne Baanen
-/
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.LinearAlgebra.Finsupp
import Mathlib.LinearAlgebra.Prod
import Mathlib.SetTheory.Cardinal.Basic
import Mathlib.Tactic.FinCases
import Mathlib.Tactic.LinearCombination
import Mathlib.Lean.Expr.ExtraRecognizers
import Mathlib.Data.Set.Subsingleton
#align_import linear_algebra.linear_independent from "leanprover-community/mathlib"@"9d684a893c52e1d6692a504a118bfccbae04feeb"
/-!
# Linear independence
This file defines linear independence in a module or vector space.
It is inspired by Isabelle/HOL's linear algebra, and hence indirectly by HOL Light.
We define `LinearIndependent R v` as `ker (Finsupp.total ι M R v) = ⊥`. Here `Finsupp.total` is the
linear map sending a function `f : ι →₀ R` with finite support to the linear combination of vectors
from `v` with these coefficients. Then we prove that several other statements are equivalent to this
one, including injectivity of `Finsupp.total ι M R v` and some versions with explicitly written
linear combinations.
## Main definitions
All definitions are given for families of vectors, i.e. `v : ι → M` where `M` is the module or
vector space and `ι : Type*` is an arbitrary indexing type.
* `LinearIndependent R v` states that the elements of the family `v` are linearly independent.
* `LinearIndependent.repr hv x` returns the linear combination representing `x : span R (range v)`
on the linearly independent vectors `v`, given `hv : LinearIndependent R v`
(using classical choice). `LinearIndependent.repr hv` is provided as a linear map.
## Main statements
We prove several specialized tests for linear independence of families of vectors and of sets of
vectors.
* `Fintype.linearIndependent_iff`: if `ι` is a finite type, then any function `f : ι → R` has
finite support, so we can reformulate the statement using `∑ i : ι, f i • v i` instead of a sum
over an auxiliary `s : Finset ι`;
* `linearIndependent_empty_type`: a family indexed by an empty type is linearly independent;
* `linearIndependent_unique_iff`: if `ι` is a singleton, then `LinearIndependent K v` is
equivalent to `v default ≠ 0`;
* `linearIndependent_option`, `linearIndependent_sum`, `linearIndependent_fin_cons`,
`linearIndependent_fin_succ`: type-specific tests for linear independence of families of vector
fields;
* `linearIndependent_insert`, `linearIndependent_union`, `linearIndependent_pair`,
`linearIndependent_singleton`: linear independence tests for set operations.
In many cases we additionally provide dot-style operations (e.g., `LinearIndependent.union`) to
make the linear independence tests usable as `hv.insert ha` etc.
We also prove that, when working over a division ring,
any family of vectors includes a linear independent subfamily spanning the same subspace.
## Implementation notes
We use families instead of sets because it allows us to say that two identical vectors are linearly
dependent.
If you want to use sets, use the family `(fun x ↦ x : s → M)` given a set `s : Set M`. The lemmas
`LinearIndependent.to_subtype_range` and `LinearIndependent.of_subtype_range` connect those two
worlds.
## Tags
linearly dependent, linear dependence, linearly independent, linear independence
-/
noncomputable section
open Function Set Submodule
open Cardinal
universe u' u
variable {ι : Type u'} {ι' : Type*} {R : Type*} {K : Type*}
variable {M : Type*} {M' M'' : Type*} {V : Type u} {V' : Type*}
section Module
variable {v : ι → M}
variable [Semiring R] [AddCommMonoid M] [AddCommMonoid M'] [AddCommMonoid M'']
variable [Module R M] [Module R M'] [Module R M'']
variable {a b : R} {x y : M}
variable (R) (v)
/-- `LinearIndependent R v` states the family of vectors `v` is linearly independent over `R`. -/
def LinearIndependent : Prop :=
LinearMap.ker (Finsupp.total ι M R v) = ⊥
#align linear_independent LinearIndependent
open Lean PrettyPrinter.Delaborator SubExpr in
/-- Delaborator for `LinearIndependent` that suggests pretty printing with type hints
in case the family of vectors is over a `Set`.
Type hints look like `LinearIndependent fun (v : ↑s) => ↑v` or `LinearIndependent (ι := ↑s) f`,
depending on whether the family is a lambda expression or not. -/
@[delab app.LinearIndependent]
def delabLinearIndependent : Delab :=
whenPPOption getPPNotation <|
whenNotPPOption getPPAnalysisSkip <|
withOptionAtCurrPos `pp.analysis.skip true do
let e ← getExpr
guard <| e.isAppOfArity ``LinearIndependent 7
let some _ := (e.getArg! 0).coeTypeSet? | failure
let optionsPerPos ← if (e.getArg! 3).isLambda then
withNaryArg 3 do return (← read).optionsPerPos.setBool (← getPos) pp.funBinderTypes.name true
else
withNaryArg 0 do return (← read).optionsPerPos.setBool (← getPos) `pp.analysis.namedArg true
withTheReader Context ({· with optionsPerPos}) delab
variable {R} {v}
theorem linearIndependent_iff :
LinearIndependent R v ↔ ∀ l, Finsupp.total ι M R v l = 0 → l = 0 := by
simp [LinearIndependent, LinearMap.ker_eq_bot']
#align linear_independent_iff linearIndependent_iff
theorem linearIndependent_iff' :
LinearIndependent R v ↔
∀ s : Finset ι, ∀ g : ι → R, ∑ i ∈ s, g i • v i = 0 → ∀ i ∈ s, g i = 0 :=
linearIndependent_iff.trans
⟨fun hf s g hg i his =>
have h :=
hf (∑ i ∈ s, Finsupp.single i (g i)) <| by
simpa only [map_sum, Finsupp.total_single] using hg
calc
g i = (Finsupp.lapply i : (ι →₀ R) →ₗ[R] R) (Finsupp.single i (g i)) := by
{ rw [Finsupp.lapply_apply, Finsupp.single_eq_same] }
_ = ∑ j ∈ s, (Finsupp.lapply i : (ι →₀ R) →ₗ[R] R) (Finsupp.single j (g j)) :=
Eq.symm <|
Finset.sum_eq_single i
(fun j _hjs hji => by rw [Finsupp.lapply_apply, Finsupp.single_eq_of_ne hji])
fun hnis => hnis.elim his
_ = (∑ j ∈ s, Finsupp.single j (g j)) i := (map_sum ..).symm
_ = 0 := DFunLike.ext_iff.1 h i,
fun hf l hl =>
Finsupp.ext fun i =>
_root_.by_contradiction fun hni => hni <| hf _ _ hl _ <| Finsupp.mem_support_iff.2 hni⟩
#align linear_independent_iff' linearIndependent_iff'
theorem linearIndependent_iff'' :
LinearIndependent R v ↔
∀ (s : Finset ι) (g : ι → R), (∀ i ∉ s, g i = 0) →
∑ i ∈ s, g i • v i = 0 → ∀ i, g i = 0 := by
classical
exact linearIndependent_iff'.trans
⟨fun H s g hg hv i => if his : i ∈ s then H s g hv i his else hg i his, fun H s g hg i hi => by
convert
H s (fun j => if j ∈ s then g j else 0) (fun j hj => if_neg hj)
(by simp_rw [ite_smul, zero_smul, Finset.sum_extend_by_zero, hg]) i
exact (if_pos hi).symm⟩
#align linear_independent_iff'' linearIndependent_iff''
theorem not_linearIndependent_iff :
¬LinearIndependent R v ↔
∃ s : Finset ι, ∃ g : ι → R, ∑ i ∈ s, g i • v i = 0 ∧ ∃ i ∈ s, g i ≠ 0 := by
rw [linearIndependent_iff']
simp only [exists_prop, not_forall]
#align not_linear_independent_iff not_linearIndependent_iff
theorem Fintype.linearIndependent_iff [Fintype ι] :
LinearIndependent R v ↔ ∀ g : ι → R, ∑ i, g i • v i = 0 → ∀ i, g i = 0 := by
refine
⟨fun H g => by simpa using linearIndependent_iff'.1 H Finset.univ g, fun H =>
linearIndependent_iff''.2 fun s g hg hs i => H _ ?_ _⟩
rw [← hs]
refine (Finset.sum_subset (Finset.subset_univ _) fun i _ hi => ?_).symm
rw [hg i hi, zero_smul]
#align fintype.linear_independent_iff Fintype.linearIndependent_iff
/-- A finite family of vectors `v i` is linear independent iff the linear map that sends
`c : ι → R` to `∑ i, c i • v i` has the trivial kernel. -/
theorem Fintype.linearIndependent_iff' [Fintype ι] [DecidableEq ι] :
LinearIndependent R v ↔
LinearMap.ker (LinearMap.lsum R (fun _ ↦ R) ℕ fun i ↦ LinearMap.id.smulRight (v i)) = ⊥ := by
simp [Fintype.linearIndependent_iff, LinearMap.ker_eq_bot', funext_iff]
#align fintype.linear_independent_iff' Fintype.linearIndependent_iff'
theorem Fintype.not_linearIndependent_iff [Fintype ι] :
¬LinearIndependent R v ↔ ∃ g : ι → R, ∑ i, g i • v i = 0 ∧ ∃ i, g i ≠ 0 := by
simpa using not_iff_not.2 Fintype.linearIndependent_iff
#align fintype.not_linear_independent_iff Fintype.not_linearIndependent_iff
theorem linearIndependent_empty_type [IsEmpty ι] : LinearIndependent R v :=
linearIndependent_iff.mpr fun v _hv => Subsingleton.elim v 0
#align linear_independent_empty_type linearIndependent_empty_type
theorem LinearIndependent.ne_zero [Nontrivial R] (i : ι) (hv : LinearIndependent R v) : v i ≠ 0 :=
fun h =>
zero_ne_one' R <|
Eq.symm
(by
suffices (Finsupp.single i 1 : ι →₀ R) i = 0 by simpa
rw [linearIndependent_iff.1 hv (Finsupp.single i 1)]
· simp
· simp [h])
#align linear_independent.ne_zero LinearIndependent.ne_zero
lemma LinearIndependent.eq_zero_of_pair {x y : M} (h : LinearIndependent R ![x, y])
{s t : R} (h' : s • x + t • y = 0) : s = 0 ∧ t = 0 := by
have := linearIndependent_iff'.1 h Finset.univ ![s, t]
simp only [Fin.sum_univ_two, Matrix.cons_val_zero, Matrix.cons_val_one, Matrix.head_cons, h',
Finset.mem_univ, forall_true_left] at this
exact ⟨this 0, this 1⟩
/-- Also see `LinearIndependent.pair_iff'` for a simpler version over fields. -/
lemma LinearIndependent.pair_iff {x y : M} :
LinearIndependent R ![x, y] ↔ ∀ (s t : R), s • x + t • y = 0 → s = 0 ∧ t = 0 := by
refine ⟨fun h s t hst ↦ h.eq_zero_of_pair hst, fun h ↦ ?_⟩
apply Fintype.linearIndependent_iff.2
intro g hg
simp only [Fin.sum_univ_two, Matrix.cons_val_zero, Matrix.cons_val_one, Matrix.head_cons] at hg
intro i
fin_cases i
exacts [(h _ _ hg).1, (h _ _ hg).2]
/-- A subfamily of a linearly independent family (i.e., a composition with an injective map) is a
linearly independent family. -/
theorem LinearIndependent.comp (h : LinearIndependent R v) (f : ι' → ι) (hf : Injective f) :
LinearIndependent R (v ∘ f) := by
rw [linearIndependent_iff, Finsupp.total_comp]
intro l hl
have h_map_domain : ∀ x, (Finsupp.mapDomain f l) (f x) = 0 := by
rw [linearIndependent_iff.1 h (Finsupp.mapDomain f l) hl]; simp
ext x
convert h_map_domain x
rw [Finsupp.mapDomain_apply hf]
#align linear_independent.comp LinearIndependent.comp
/-- A family is linearly independent if and only if all of its finite subfamily is
linearly independent. -/
theorem linearIndependent_iff_finset_linearIndependent :
LinearIndependent R v ↔ ∀ (s : Finset ι), LinearIndependent R (v ∘ (Subtype.val : s → ι)) :=
⟨fun H _ ↦ H.comp _ Subtype.val_injective, fun H ↦ linearIndependent_iff'.2 fun s g hg i hi ↦
Fintype.linearIndependent_iff.1 (H s) (g ∘ Subtype.val)
(hg ▸ Finset.sum_attach s fun j ↦ g j • v j) ⟨i, hi⟩⟩
theorem LinearIndependent.coe_range (i : LinearIndependent R v) :
LinearIndependent R ((↑) : range v → M) := by simpa using i.comp _ (rangeSplitting_injective v)
#align linear_independent.coe_range LinearIndependent.coe_range
/-- If `v` is a linearly independent family of vectors and the kernel of a linear map `f` is
disjoint with the submodule spanned by the vectors of `v`, then `f ∘ v` is a linearly independent
family of vectors. See also `LinearIndependent.map'` for a special case assuming `ker f = ⊥`. -/
theorem LinearIndependent.map (hv : LinearIndependent R v) {f : M →ₗ[R] M'}
(hf_inj : Disjoint (span R (range v)) (LinearMap.ker f)) : LinearIndependent R (f ∘ v) := by
rw [disjoint_iff_inf_le, ← Set.image_univ, Finsupp.span_image_eq_map_total,
map_inf_eq_map_inf_comap, map_le_iff_le_comap, comap_bot, Finsupp.supported_univ, top_inf_eq]
at hf_inj
unfold LinearIndependent at hv ⊢
rw [hv, le_bot_iff] at hf_inj
haveI : Inhabited M := ⟨0⟩
rw [Finsupp.total_comp, Finsupp.lmapDomain_total _ _ f, LinearMap.ker_comp,
hf_inj]
exact fun _ => rfl
#align linear_independent.map LinearIndependent.map
/-- If `v` is an injective family of vectors such that `f ∘ v` is linearly independent, then `v`
spans a submodule disjoint from the kernel of `f` -/
theorem Submodule.range_ker_disjoint {f : M →ₗ[R] M'}
(hv : LinearIndependent R (f ∘ v)) :
Disjoint (span R (range v)) (LinearMap.ker f) := by
rw [LinearIndependent, Finsupp.total_comp, Finsupp.lmapDomain_total R _ f (fun _ ↦ rfl),
LinearMap.ker_comp] at hv
rw [disjoint_iff_inf_le, ← Set.image_univ, Finsupp.span_image_eq_map_total,
map_inf_eq_map_inf_comap, hv, inf_bot_eq, map_bot]
/-- An injective linear map sends linearly independent families of vectors to linearly independent
families of vectors. See also `LinearIndependent.map` for a more general statement. -/
theorem LinearIndependent.map' (hv : LinearIndependent R v) (f : M →ₗ[R] M')
(hf_inj : LinearMap.ker f = ⊥) : LinearIndependent R (f ∘ v) :=
hv.map <| by simp [hf_inj]
#align linear_independent.map' LinearIndependent.map'
/-- If `M / R` and `M' / R'` are modules, `i : R' → R` is a map, `j : M →+ M'` is a monoid map,
such that they send non-zero elements to non-zero elements, and compatible with the scalar
multiplications on `M` and `M'`, then `j` sends linearly independent families of vectors to
linearly independent families of vectors. As a special case, taking `R = R'`
it is `LinearIndependent.map'`. -/
theorem LinearIndependent.map_of_injective_injective {R' : Type*} {M' : Type*}
[Semiring R'] [AddCommMonoid M'] [Module R' M'] (hv : LinearIndependent R v)
(i : R' → R) (j : M →+ M') (hi : ∀ r, i r = 0 → r = 0) (hj : ∀ m, j m = 0 → m = 0)
(hc : ∀ (r : R') (m : M), j (i r • m) = r • j m) : LinearIndependent R' (j ∘ v) := by
rw [linearIndependent_iff'] at hv ⊢
intro S r' H s hs
simp_rw [comp_apply, ← hc, ← map_sum] at H
exact hi _ <| hv _ _ (hj _ H) s hs
/-- If `M / R` and `M' / R'` are modules, `i : R → R'` is a surjective map which maps zero to zero,
`j : M →+ M'` is a monoid map which sends non-zero elements to non-zero elements, such that the
scalar multiplications on `M` and `M'` are compatible, then `j` sends linearly independent families
of vectors to linearly independent families of vectors. As a special case, taking `R = R'`
it is `LinearIndependent.map'`. -/
theorem LinearIndependent.map_of_surjective_injective {R' : Type*} {M' : Type*}
[Semiring R'] [AddCommMonoid M'] [Module R' M'] (hv : LinearIndependent R v)
(i : ZeroHom R R') (j : M →+ M') (hi : Surjective i) (hj : ∀ m, j m = 0 → m = 0)
(hc : ∀ (r : R) (m : M), j (r • m) = i r • j m) : LinearIndependent R' (j ∘ v) := by
obtain ⟨i', hi'⟩ := hi.hasRightInverse
refine hv.map_of_injective_injective i' j (fun _ h ↦ ?_) hj fun r m ↦ ?_
· apply_fun i at h
rwa [hi', i.map_zero] at h
rw [hc (i' r) m, hi']
/-- If the image of a family of vectors under a linear map is linearly independent, then so is
the original family. -/
theorem LinearIndependent.of_comp (f : M →ₗ[R] M') (hfv : LinearIndependent R (f ∘ v)) :
LinearIndependent R v :=
linearIndependent_iff'.2 fun s g hg i his =>
have : (∑ i ∈ s, g i • f (v i)) = 0 := by
simp_rw [← map_smul, ← map_sum, hg, f.map_zero]
linearIndependent_iff'.1 hfv s g this i his
#align linear_independent.of_comp LinearIndependent.of_comp
/-- If `f` is an injective linear map, then the family `f ∘ v` is linearly independent
if and only if the family `v` is linearly independent. -/
protected theorem LinearMap.linearIndependent_iff (f : M →ₗ[R] M') (hf_inj : LinearMap.ker f = ⊥) :
LinearIndependent R (f ∘ v) ↔ LinearIndependent R v :=
⟨fun h => h.of_comp f, fun h => h.map <| by simp only [hf_inj, disjoint_bot_right]⟩
#align linear_map.linear_independent_iff LinearMap.linearIndependent_iff
@[nontriviality]
theorem linearIndependent_of_subsingleton [Subsingleton R] : LinearIndependent R v :=
linearIndependent_iff.2 fun _l _hl => Subsingleton.elim _ _
#align linear_independent_of_subsingleton linearIndependent_of_subsingleton
theorem linearIndependent_equiv (e : ι ≃ ι') {f : ι' → M} :
LinearIndependent R (f ∘ e) ↔ LinearIndependent R f :=
⟨fun h => Function.comp_id f ▸ e.self_comp_symm ▸ h.comp _ e.symm.injective, fun h =>
h.comp _ e.injective⟩
#align linear_independent_equiv linearIndependent_equiv
theorem linearIndependent_equiv' (e : ι ≃ ι') {f : ι' → M} {g : ι → M} (h : f ∘ e = g) :
LinearIndependent R g ↔ LinearIndependent R f :=
h ▸ linearIndependent_equiv e
#align linear_independent_equiv' linearIndependent_equiv'
theorem linearIndependent_subtype_range {ι} {f : ι → M} (hf : Injective f) :
LinearIndependent R ((↑) : range f → M) ↔ LinearIndependent R f :=
Iff.symm <| linearIndependent_equiv' (Equiv.ofInjective f hf) rfl
#align linear_independent_subtype_range linearIndependent_subtype_range
alias ⟨LinearIndependent.of_subtype_range, _⟩ := linearIndependent_subtype_range
#align linear_independent.of_subtype_range LinearIndependent.of_subtype_range
theorem linearIndependent_image {ι} {s : Set ι} {f : ι → M} (hf : Set.InjOn f s) :
(LinearIndependent R fun x : s => f x) ↔ LinearIndependent R fun x : f '' s => (x : M) :=
linearIndependent_equiv' (Equiv.Set.imageOfInjOn _ _ hf) rfl
#align linear_independent_image linearIndependent_image
theorem linearIndependent_span (hs : LinearIndependent R v) :
LinearIndependent R (M := span R (range v))
(fun i : ι => ⟨v i, subset_span (mem_range_self i)⟩) :=
LinearIndependent.of_comp (span R (range v)).subtype hs
#align linear_independent_span linearIndependent_span
/-- See `LinearIndependent.fin_cons` for a family of elements in a vector space. -/
theorem LinearIndependent.fin_cons' {m : ℕ} (x : M) (v : Fin m → M) (hli : LinearIndependent R v)
(x_ortho : ∀ (c : R) (y : Submodule.span R (Set.range v)), c • x + y = (0 : M) → c = 0) :
LinearIndependent R (Fin.cons x v : Fin m.succ → M) := by
rw [Fintype.linearIndependent_iff] at hli ⊢
rintro g total_eq j
simp_rw [Fin.sum_univ_succ, Fin.cons_zero, Fin.cons_succ] at total_eq
have : g 0 = 0 := by
refine x_ortho (g 0) ⟨∑ i : Fin m, g i.succ • v i, ?_⟩ total_eq
exact sum_mem fun i _ => smul_mem _ _ (subset_span ⟨i, rfl⟩)
rw [this, zero_smul, zero_add] at total_eq
exact Fin.cases this (hli _ total_eq) j
#align linear_independent.fin_cons' LinearIndependent.fin_cons'
/-- A set of linearly independent vectors in a module `M` over a semiring `K` is also linearly
independent over a subring `R` of `K`.
The implementation uses minimal assumptions about the relationship between `R`, `K` and `M`.
The version where `K` is an `R`-algebra is `LinearIndependent.restrict_scalars_algebras`.
-/
theorem LinearIndependent.restrict_scalars [Semiring K] [SMulWithZero R K] [Module K M]
[IsScalarTower R K M] (hinj : Function.Injective fun r : R => r • (1 : K))
(li : LinearIndependent K v) : LinearIndependent R v := by
refine linearIndependent_iff'.mpr fun s g hg i hi => hinj ?_
dsimp only; rw [zero_smul]
refine (linearIndependent_iff'.mp li : _) _ (g · • (1:K)) ?_ i hi
simp_rw [smul_assoc, one_smul]
exact hg
#align linear_independent.restrict_scalars LinearIndependent.restrict_scalars
/-- Every finite subset of a linearly independent set is linearly independent. -/
theorem linearIndependent_finset_map_embedding_subtype (s : Set M)
(li : LinearIndependent R ((↑) : s → M)) (t : Finset s) :
LinearIndependent R ((↑) : Finset.map (Embedding.subtype s) t → M) := by
let f : t.map (Embedding.subtype s) → s := fun x =>
⟨x.1, by
obtain ⟨x, h⟩ := x
rw [Finset.mem_map] at h
obtain ⟨a, _ha, rfl⟩ := h
simp only [Subtype.coe_prop, Embedding.coe_subtype]⟩
convert LinearIndependent.comp li f ?_
rintro ⟨x, hx⟩ ⟨y, hy⟩
rw [Finset.mem_map] at hx hy
obtain ⟨a, _ha, rfl⟩ := hx
obtain ⟨b, _hb, rfl⟩ := hy
simp only [f, imp_self, Subtype.mk_eq_mk]
#align linear_independent_finset_map_embedding_subtype linearIndependent_finset_map_embedding_subtype
/-- If every finite set of linearly independent vectors has cardinality at most `n`,
then the same is true for arbitrary sets of linearly independent vectors.
-/
theorem linearIndependent_bounded_of_finset_linearIndependent_bounded {n : ℕ}
(H : ∀ s : Finset M, (LinearIndependent R fun i : s => (i : M)) → s.card ≤ n) :
∀ s : Set M, LinearIndependent R ((↑) : s → M) → #s ≤ n := by
intro s li
apply Cardinal.card_le_of
intro t
rw [← Finset.card_map (Embedding.subtype s)]
apply H
apply linearIndependent_finset_map_embedding_subtype _ li
#align linear_independent_bounded_of_finset_linear_independent_bounded linearIndependent_bounded_of_finset_linearIndependent_bounded
section Subtype
/-! The following lemmas use the subtype defined by a set in `M` as the index set `ι`. -/
theorem linearIndependent_comp_subtype {s : Set ι} :
LinearIndependent R (v ∘ (↑) : s → M) ↔
∀ l ∈ Finsupp.supported R R s, (Finsupp.total ι M R v) l = 0 → l = 0 := by
simp only [linearIndependent_iff, (· ∘ ·), Finsupp.mem_supported, Finsupp.total_apply,
Set.subset_def, Finset.mem_coe]
constructor
· intro h l hl₁ hl₂
have := h (l.subtypeDomain s) ((Finsupp.sum_subtypeDomain_index hl₁).trans hl₂)
exact (Finsupp.subtypeDomain_eq_zero_iff hl₁).1 this
· intro h l hl
refine Finsupp.embDomain_eq_zero.1 (h (l.embDomain <| Function.Embedding.subtype s) ?_ ?_)
· suffices ∀ i hi, ¬l ⟨i, hi⟩ = 0 → i ∈ s by simpa
intros
assumption
· rwa [Finsupp.embDomain_eq_mapDomain, Finsupp.sum_mapDomain_index]
exacts [fun _ => zero_smul _ _, fun _ _ _ => add_smul _ _ _]
#align linear_independent_comp_subtype linearIndependent_comp_subtype
theorem linearDependent_comp_subtype' {s : Set ι} :
¬LinearIndependent R (v ∘ (↑) : s → M) ↔
∃ f : ι →₀ R, f ∈ Finsupp.supported R R s ∧ Finsupp.total ι M R v f = 0 ∧ f ≠ 0 := by
simp [linearIndependent_comp_subtype, and_left_comm]
#align linear_dependent_comp_subtype' linearDependent_comp_subtype'
/-- A version of `linearDependent_comp_subtype'` with `Finsupp.total` unfolded. -/
theorem linearDependent_comp_subtype {s : Set ι} :
¬LinearIndependent R (v ∘ (↑) : s → M) ↔
∃ f : ι →₀ R, f ∈ Finsupp.supported R R s ∧ ∑ i ∈ f.support, f i • v i = 0 ∧ f ≠ 0 :=
linearDependent_comp_subtype'
#align linear_dependent_comp_subtype linearDependent_comp_subtype
theorem linearIndependent_subtype {s : Set M} :
LinearIndependent R (fun x => x : s → M) ↔
∀ l ∈ Finsupp.supported R R s, (Finsupp.total M M R id) l = 0 → l = 0 := by
apply linearIndependent_comp_subtype (v := id)
#align linear_independent_subtype linearIndependent_subtype
theorem linearIndependent_comp_subtype_disjoint {s : Set ι} :
LinearIndependent R (v ∘ (↑) : s → M) ↔
Disjoint (Finsupp.supported R R s) (LinearMap.ker <| Finsupp.total ι M R v) := by
rw [linearIndependent_comp_subtype, LinearMap.disjoint_ker]
#align linear_independent_comp_subtype_disjoint linearIndependent_comp_subtype_disjoint
theorem linearIndependent_subtype_disjoint {s : Set M} :
LinearIndependent R (fun x => x : s → M) ↔
Disjoint (Finsupp.supported R R s) (LinearMap.ker <| Finsupp.total M M R id) := by
apply linearIndependent_comp_subtype_disjoint (v := id)
#align linear_independent_subtype_disjoint linearIndependent_subtype_disjoint
theorem linearIndependent_iff_totalOn {s : Set M} :
LinearIndependent R (fun x => x : s → M) ↔
(LinearMap.ker <| Finsupp.totalOn M M R id s) = ⊥ := by
rw [Finsupp.totalOn, LinearMap.ker, LinearMap.comap_codRestrict, Submodule.map_bot, comap_bot,
LinearMap.ker_comp, linearIndependent_subtype_disjoint, disjoint_iff_inf_le, ←
map_comap_subtype, map_le_iff_le_comap, comap_bot, ker_subtype, le_bot_iff]
#align linear_independent_iff_total_on linearIndependent_iff_totalOn
theorem LinearIndependent.restrict_of_comp_subtype {s : Set ι}
(hs : LinearIndependent R (v ∘ (↑) : s → M)) : LinearIndependent R (s.restrict v) :=
hs
#align linear_independent.restrict_of_comp_subtype LinearIndependent.restrict_of_comp_subtype
variable (R M)
theorem linearIndependent_empty : LinearIndependent R (fun x => x : (∅ : Set M) → M) := by
simp [linearIndependent_subtype_disjoint]
#align linear_independent_empty linearIndependent_empty
variable {R M}
theorem LinearIndependent.mono {t s : Set M} (h : t ⊆ s) :
LinearIndependent R (fun x => x : s → M) → LinearIndependent R (fun x => x : t → M) := by
simp only [linearIndependent_subtype_disjoint]
exact Disjoint.mono_left (Finsupp.supported_mono h)
#align linear_independent.mono LinearIndependent.mono
theorem linearIndependent_of_finite (s : Set M)
(H : ∀ t ⊆ s, Set.Finite t → LinearIndependent R (fun x => x : t → M)) :
LinearIndependent R (fun x => x : s → M) :=
linearIndependent_subtype.2 fun l hl =>
linearIndependent_subtype.1 (H _ hl (Finset.finite_toSet _)) l (Subset.refl _)
#align linear_independent_of_finite linearIndependent_of_finite
theorem linearIndependent_iUnion_of_directed {η : Type*} {s : η → Set M} (hs : Directed (· ⊆ ·) s)
(h : ∀ i, LinearIndependent R (fun x => x : s i → M)) :
LinearIndependent R (fun x => x : (⋃ i, s i) → M) := by
by_cases hη : Nonempty η
· refine linearIndependent_of_finite (⋃ i, s i) fun t ht ft => ?_
rcases finite_subset_iUnion ft ht with ⟨I, fi, hI⟩
rcases hs.finset_le fi.toFinset with ⟨i, hi⟩
exact (h i).mono (Subset.trans hI <| iUnion₂_subset fun j hj => hi j (fi.mem_toFinset.2 hj))
· refine (linearIndependent_empty R M).mono (t := iUnion (s ·)) ?_
rintro _ ⟨_, ⟨i, _⟩, _⟩
exact hη ⟨i⟩
#align linear_independent_Union_of_directed linearIndependent_iUnion_of_directed
theorem linearIndependent_sUnion_of_directed {s : Set (Set M)} (hs : DirectedOn (· ⊆ ·) s)
(h : ∀ a ∈ s, LinearIndependent R ((↑) : ((a : Set M) : Type _) → M)) :
LinearIndependent R (fun x => x : ⋃₀ s → M) := by
rw [sUnion_eq_iUnion];
exact linearIndependent_iUnion_of_directed hs.directed_val (by simpa using h)
#align linear_independent_sUnion_of_directed linearIndependent_sUnion_of_directed
theorem linearIndependent_biUnion_of_directed {η} {s : Set η} {t : η → Set M}
(hs : DirectedOn (t ⁻¹'o (· ⊆ ·)) s) (h : ∀ a ∈ s, LinearIndependent R (fun x => x : t a → M)) :
LinearIndependent R (fun x => x : (⋃ a ∈ s, t a) → M) := by
rw [biUnion_eq_iUnion]
exact
linearIndependent_iUnion_of_directed (directed_comp.2 <| hs.directed_val) (by simpa using h)
#align linear_independent_bUnion_of_directed linearIndependent_biUnion_of_directed
end Subtype
end Module
/-! ### Properties which require `Ring R` -/
section Module
variable {v : ι → M}
variable [Ring R] [AddCommGroup M] [AddCommGroup M'] [AddCommGroup M'']
variable [Module R M] [Module R M'] [Module R M'']
variable {a b : R} {x y : M}
theorem linearIndependent_iff_injective_total :
LinearIndependent R v ↔ Function.Injective (Finsupp.total ι M R v) :=
linearIndependent_iff.trans
(injective_iff_map_eq_zero (Finsupp.total ι M R v).toAddMonoidHom).symm
#align linear_independent_iff_injective_total linearIndependent_iff_injective_total
alias ⟨LinearIndependent.injective_total, _⟩ := linearIndependent_iff_injective_total
#align linear_independent.injective_total LinearIndependent.injective_total
theorem LinearIndependent.injective [Nontrivial R] (hv : LinearIndependent R v) : Injective v := by
intro i j hij
let l : ι →₀ R := Finsupp.single i (1 : R) - Finsupp.single j 1
have h_total : Finsupp.total ι M R v l = 0 := by
simp_rw [l, LinearMap.map_sub, Finsupp.total_apply]
simp [hij]
have h_single_eq : Finsupp.single i (1 : R) = Finsupp.single j 1 := by
rw [linearIndependent_iff] at hv
simp [eq_add_of_sub_eq' (hv l h_total)]
simpa [Finsupp.single_eq_single_iff] using h_single_eq
#align linear_independent.injective LinearIndependent.injective
| Mathlib/LinearAlgebra/LinearIndependent.lean | 581 | 584 | theorem LinearIndependent.to_subtype_range {ι} {f : ι → M} (hf : LinearIndependent R f) :
LinearIndependent R ((↑) : range f → M) := by |
nontriviality R
exact (linearIndependent_subtype_range hf.injective).2 hf
|
/-
Copyright (c) 2022 Moritz Doll. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Moritz Doll, Anatole Dedecker
-/
import Mathlib.Analysis.Seminorm
import Mathlib.Topology.Algebra.Equicontinuity
import Mathlib.Topology.MetricSpace.Equicontinuity
import Mathlib.Topology.Algebra.FilterBasis
import Mathlib.Topology.Algebra.Module.LocallyConvex
#align_import analysis.locally_convex.with_seminorms from "leanprover-community/mathlib"@"b31173ee05c911d61ad6a05bd2196835c932e0ec"
/-!
# Topology induced by a family of seminorms
## Main definitions
* `SeminormFamily.basisSets`: The set of open seminorm balls for a family of seminorms.
* `SeminormFamily.moduleFilterBasis`: A module filter basis formed by the open balls.
* `Seminorm.IsBounded`: A linear map `f : E →ₗ[𝕜] F` is bounded iff every seminorm in `F` can be
bounded by a finite number of seminorms in `E`.
## Main statements
* `WithSeminorms.toLocallyConvexSpace`: A space equipped with a family of seminorms is locally
convex.
* `WithSeminorms.firstCountable`: A space is first countable if it's topology is induced by a
countable family of seminorms.
## Continuity of semilinear maps
If `E` and `F` are topological vector space with the topology induced by a family of seminorms, then
we have a direct method to prove that a linear map is continuous:
* `Seminorm.continuous_from_bounded`: A bounded linear map `f : E →ₗ[𝕜] F` is continuous.
If the topology of a space `E` is induced by a family of seminorms, then we can characterize von
Neumann boundedness in terms of that seminorm family. Together with
`LinearMap.continuous_of_locally_bounded` this gives general criterion for continuity.
* `WithSeminorms.isVonNBounded_iff_finset_seminorm_bounded`
* `WithSeminorms.isVonNBounded_iff_seminorm_bounded`
* `WithSeminorms.image_isVonNBounded_iff_finset_seminorm_bounded`
* `WithSeminorms.image_isVonNBounded_iff_seminorm_bounded`
## Tags
seminorm, locally convex
-/
open NormedField Set Seminorm TopologicalSpace Filter List
open NNReal Pointwise Topology Uniformity
variable {𝕜 𝕜₂ 𝕝 𝕝₂ E F G ι ι' : Type*}
section FilterBasis
variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E]
variable (𝕜 E ι)
/-- An abbreviation for indexed families of seminorms. This is mainly to allow for dot-notation. -/
abbrev SeminormFamily :=
ι → Seminorm 𝕜 E
#align seminorm_family SeminormFamily
variable {𝕜 E ι}
namespace SeminormFamily
/-- The sets of a filter basis for the neighborhood filter of 0. -/
def basisSets (p : SeminormFamily 𝕜 E ι) : Set (Set E) :=
⋃ (s : Finset ι) (r) (_ : 0 < r), singleton (ball (s.sup p) (0 : E) r)
#align seminorm_family.basis_sets SeminormFamily.basisSets
variable (p : SeminormFamily 𝕜 E ι)
theorem basisSets_iff {U : Set E} :
U ∈ p.basisSets ↔ ∃ (i : Finset ι) (r : ℝ), 0 < r ∧ U = ball (i.sup p) 0 r := by
simp only [basisSets, mem_iUnion, exists_prop, mem_singleton_iff]
#align seminorm_family.basis_sets_iff SeminormFamily.basisSets_iff
theorem basisSets_mem (i : Finset ι) {r : ℝ} (hr : 0 < r) : (i.sup p).ball 0 r ∈ p.basisSets :=
(basisSets_iff _).mpr ⟨i, _, hr, rfl⟩
#align seminorm_family.basis_sets_mem SeminormFamily.basisSets_mem
theorem basisSets_singleton_mem (i : ι) {r : ℝ} (hr : 0 < r) : (p i).ball 0 r ∈ p.basisSets :=
(basisSets_iff _).mpr ⟨{i}, _, hr, by rw [Finset.sup_singleton]⟩
#align seminorm_family.basis_sets_singleton_mem SeminormFamily.basisSets_singleton_mem
theorem basisSets_nonempty [Nonempty ι] : p.basisSets.Nonempty := by
let i := Classical.arbitrary ι
refine nonempty_def.mpr ⟨(p i).ball 0 1, ?_⟩
exact p.basisSets_singleton_mem i zero_lt_one
#align seminorm_family.basis_sets_nonempty SeminormFamily.basisSets_nonempty
theorem basisSets_intersect (U V : Set E) (hU : U ∈ p.basisSets) (hV : V ∈ p.basisSets) :
∃ z ∈ p.basisSets, z ⊆ U ∩ V := by
classical
rcases p.basisSets_iff.mp hU with ⟨s, r₁, hr₁, hU⟩
rcases p.basisSets_iff.mp hV with ⟨t, r₂, hr₂, hV⟩
use ((s ∪ t).sup p).ball 0 (min r₁ r₂)
refine ⟨p.basisSets_mem (s ∪ t) (lt_min_iff.mpr ⟨hr₁, hr₂⟩), ?_⟩
rw [hU, hV, ball_finset_sup_eq_iInter _ _ _ (lt_min_iff.mpr ⟨hr₁, hr₂⟩),
ball_finset_sup_eq_iInter _ _ _ hr₁, ball_finset_sup_eq_iInter _ _ _ hr₂]
exact
Set.subset_inter
(Set.iInter₂_mono' fun i hi =>
⟨i, Finset.subset_union_left hi, ball_mono <| min_le_left _ _⟩)
(Set.iInter₂_mono' fun i hi =>
⟨i, Finset.subset_union_right hi, ball_mono <| min_le_right _ _⟩)
#align seminorm_family.basis_sets_intersect SeminormFamily.basisSets_intersect
theorem basisSets_zero (U) (hU : U ∈ p.basisSets) : (0 : E) ∈ U := by
rcases p.basisSets_iff.mp hU with ⟨ι', r, hr, hU⟩
rw [hU, mem_ball_zero, map_zero]
exact hr
#align seminorm_family.basis_sets_zero SeminormFamily.basisSets_zero
theorem basisSets_add (U) (hU : U ∈ p.basisSets) :
∃ V ∈ p.basisSets, V + V ⊆ U := by
rcases p.basisSets_iff.mp hU with ⟨s, r, hr, hU⟩
use (s.sup p).ball 0 (r / 2)
refine ⟨p.basisSets_mem s (div_pos hr zero_lt_two), ?_⟩
refine Set.Subset.trans (ball_add_ball_subset (s.sup p) (r / 2) (r / 2) 0 0) ?_
rw [hU, add_zero, add_halves']
#align seminorm_family.basis_sets_add SeminormFamily.basisSets_add
theorem basisSets_neg (U) (hU' : U ∈ p.basisSets) :
∃ V ∈ p.basisSets, V ⊆ (fun x : E => -x) ⁻¹' U := by
rcases p.basisSets_iff.mp hU' with ⟨s, r, _, hU⟩
rw [hU, neg_preimage, neg_ball (s.sup p), neg_zero]
exact ⟨U, hU', Eq.subset hU⟩
#align seminorm_family.basis_sets_neg SeminormFamily.basisSets_neg
/-- The `addGroupFilterBasis` induced by the filter basis `Seminorm.basisSets`. -/
protected def addGroupFilterBasis [Nonempty ι] : AddGroupFilterBasis E :=
addGroupFilterBasisOfComm p.basisSets p.basisSets_nonempty p.basisSets_intersect p.basisSets_zero
p.basisSets_add p.basisSets_neg
#align seminorm_family.add_group_filter_basis SeminormFamily.addGroupFilterBasis
theorem basisSets_smul_right (v : E) (U : Set E) (hU : U ∈ p.basisSets) :
∀ᶠ x : 𝕜 in 𝓝 0, x • v ∈ U := by
rcases p.basisSets_iff.mp hU with ⟨s, r, hr, hU⟩
rw [hU, Filter.eventually_iff]
simp_rw [(s.sup p).mem_ball_zero, map_smul_eq_mul]
by_cases h : 0 < (s.sup p) v
· simp_rw [(lt_div_iff h).symm]
rw [← _root_.ball_zero_eq]
exact Metric.ball_mem_nhds 0 (div_pos hr h)
simp_rw [le_antisymm (not_lt.mp h) (apply_nonneg _ v), mul_zero, hr]
exact IsOpen.mem_nhds isOpen_univ (mem_univ 0)
#align seminorm_family.basis_sets_smul_right SeminormFamily.basisSets_smul_right
variable [Nonempty ι]
theorem basisSets_smul (U) (hU : U ∈ p.basisSets) :
∃ V ∈ 𝓝 (0 : 𝕜), ∃ W ∈ p.addGroupFilterBasis.sets, V • W ⊆ U := by
rcases p.basisSets_iff.mp hU with ⟨s, r, hr, hU⟩
refine ⟨Metric.ball 0 √r, Metric.ball_mem_nhds 0 (Real.sqrt_pos.mpr hr), ?_⟩
refine ⟨(s.sup p).ball 0 √r, p.basisSets_mem s (Real.sqrt_pos.mpr hr), ?_⟩
refine Set.Subset.trans (ball_smul_ball (s.sup p) √r √r) ?_
rw [hU, Real.mul_self_sqrt (le_of_lt hr)]
#align seminorm_family.basis_sets_smul SeminormFamily.basisSets_smul
theorem basisSets_smul_left (x : 𝕜) (U : Set E) (hU : U ∈ p.basisSets) :
∃ V ∈ p.addGroupFilterBasis.sets, V ⊆ (fun y : E => x • y) ⁻¹' U := by
rcases p.basisSets_iff.mp hU with ⟨s, r, hr, hU⟩
rw [hU]
by_cases h : x ≠ 0
· rw [(s.sup p).smul_ball_preimage 0 r x h, smul_zero]
use (s.sup p).ball 0 (r / ‖x‖)
exact ⟨p.basisSets_mem s (div_pos hr (norm_pos_iff.mpr h)), Subset.rfl⟩
refine ⟨(s.sup p).ball 0 r, p.basisSets_mem s hr, ?_⟩
simp only [not_ne_iff.mp h, Set.subset_def, mem_ball_zero, hr, mem_univ, map_zero, imp_true_iff,
preimage_const_of_mem, zero_smul]
#align seminorm_family.basis_sets_smul_left SeminormFamily.basisSets_smul_left
/-- The `moduleFilterBasis` induced by the filter basis `Seminorm.basisSets`. -/
protected def moduleFilterBasis : ModuleFilterBasis 𝕜 E where
toAddGroupFilterBasis := p.addGroupFilterBasis
smul' := p.basisSets_smul _
smul_left' := p.basisSets_smul_left
smul_right' := p.basisSets_smul_right
#align seminorm_family.module_filter_basis SeminormFamily.moduleFilterBasis
theorem filter_eq_iInf (p : SeminormFamily 𝕜 E ι) :
p.moduleFilterBasis.toFilterBasis.filter = ⨅ i, (𝓝 0).comap (p i) := by
refine le_antisymm (le_iInf fun i => ?_) ?_
· rw [p.moduleFilterBasis.toFilterBasis.hasBasis.le_basis_iff
(Metric.nhds_basis_ball.comap _)]
intro ε hε
refine ⟨(p i).ball 0 ε, ?_, ?_⟩
· rw [← (Finset.sup_singleton : _ = p i)]
exact p.basisSets_mem {i} hε
· rw [id, (p i).ball_zero_eq_preimage_ball]
· rw [p.moduleFilterBasis.toFilterBasis.hasBasis.ge_iff]
rintro U (hU : U ∈ p.basisSets)
rcases p.basisSets_iff.mp hU with ⟨s, r, hr, rfl⟩
rw [id, Seminorm.ball_finset_sup_eq_iInter _ _ _ hr, s.iInter_mem_sets]
exact fun i _ =>
Filter.mem_iInf_of_mem i
⟨Metric.ball 0 r, Metric.ball_mem_nhds 0 hr,
Eq.subset (p i).ball_zero_eq_preimage_ball.symm⟩
#align seminorm_family.filter_eq_infi SeminormFamily.filter_eq_iInf
end SeminormFamily
end FilterBasis
section Bounded
namespace Seminorm
variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E]
variable [NormedField 𝕜₂] [AddCommGroup F] [Module 𝕜₂ F]
variable {σ₁₂ : 𝕜 →+* 𝕜₂} [RingHomIsometric σ₁₂]
-- Todo: This should be phrased entirely in terms of the von Neumann bornology.
/-- The proposition that a linear map is bounded between spaces with families of seminorms. -/
def IsBounded (p : ι → Seminorm 𝕜 E) (q : ι' → Seminorm 𝕜₂ F) (f : E →ₛₗ[σ₁₂] F) : Prop :=
∀ i, ∃ s : Finset ι, ∃ C : ℝ≥0, (q i).comp f ≤ C • s.sup p
#align seminorm.is_bounded Seminorm.IsBounded
theorem isBounded_const (ι' : Type*) [Nonempty ι'] {p : ι → Seminorm 𝕜 E} {q : Seminorm 𝕜₂ F}
(f : E →ₛₗ[σ₁₂] F) :
IsBounded p (fun _ : ι' => q) f ↔ ∃ (s : Finset ι) (C : ℝ≥0), q.comp f ≤ C • s.sup p := by
simp only [IsBounded, forall_const]
#align seminorm.is_bounded_const Seminorm.isBounded_const
theorem const_isBounded (ι : Type*) [Nonempty ι] {p : Seminorm 𝕜 E} {q : ι' → Seminorm 𝕜₂ F}
(f : E →ₛₗ[σ₁₂] F) : IsBounded (fun _ : ι => p) q f ↔ ∀ i, ∃ C : ℝ≥0, (q i).comp f ≤ C • p := by
constructor <;> intro h i
· rcases h i with ⟨s, C, h⟩
exact ⟨C, le_trans h (smul_le_smul (Finset.sup_le fun _ _ => le_rfl) le_rfl)⟩
use {Classical.arbitrary ι}
simp only [h, Finset.sup_singleton]
#align seminorm.const_is_bounded Seminorm.const_isBounded
theorem isBounded_sup {p : ι → Seminorm 𝕜 E} {q : ι' → Seminorm 𝕜₂ F} {f : E →ₛₗ[σ₁₂] F}
(hf : IsBounded p q f) (s' : Finset ι') :
∃ (C : ℝ≥0) (s : Finset ι), (s'.sup q).comp f ≤ C • s.sup p := by
classical
obtain rfl | _ := s'.eq_empty_or_nonempty
· exact ⟨1, ∅, by simp [Seminorm.bot_eq_zero]⟩
choose fₛ fC hf using hf
use s'.card • s'.sup fC, Finset.biUnion s' fₛ
have hs : ∀ i : ι', i ∈ s' → (q i).comp f ≤ s'.sup fC • (Finset.biUnion s' fₛ).sup p := by
intro i hi
refine (hf i).trans (smul_le_smul ?_ (Finset.le_sup hi))
exact Finset.sup_mono (Finset.subset_biUnion_of_mem fₛ hi)
refine (comp_mono f (finset_sup_le_sum q s')).trans ?_
simp_rw [← pullback_apply, map_sum, pullback_apply]
refine (Finset.sum_le_sum hs).trans ?_
rw [Finset.sum_const, smul_assoc]
#align seminorm.is_bounded_sup Seminorm.isBounded_sup
end Seminorm
end Bounded
section Topology
variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] [Nonempty ι]
/-- The proposition that the topology of `E` is induced by a family of seminorms `p`. -/
structure WithSeminorms (p : SeminormFamily 𝕜 E ι) [topology : TopologicalSpace E] : Prop where
topology_eq_withSeminorms : topology = p.moduleFilterBasis.topology
#align with_seminorms WithSeminorms
theorem WithSeminorms.withSeminorms_eq {p : SeminormFamily 𝕜 E ι} [t : TopologicalSpace E]
(hp : WithSeminorms p) : t = p.moduleFilterBasis.topology :=
hp.1
#align with_seminorms.with_seminorms_eq WithSeminorms.withSeminorms_eq
variable [TopologicalSpace E]
variable {p : SeminormFamily 𝕜 E ι}
theorem WithSeminorms.topologicalAddGroup (hp : WithSeminorms p) : TopologicalAddGroup E := by
rw [hp.withSeminorms_eq]
exact AddGroupFilterBasis.isTopologicalAddGroup _
#align with_seminorms.topological_add_group WithSeminorms.topologicalAddGroup
theorem WithSeminorms.continuousSMul (hp : WithSeminorms p) : ContinuousSMul 𝕜 E := by
rw [hp.withSeminorms_eq]
exact ModuleFilterBasis.continuousSMul _
theorem WithSeminorms.hasBasis (hp : WithSeminorms p) :
(𝓝 (0 : E)).HasBasis (fun s : Set E => s ∈ p.basisSets) id := by
rw [congr_fun (congr_arg (@nhds E) hp.1) 0]
exact AddGroupFilterBasis.nhds_zero_hasBasis _
#align with_seminorms.has_basis WithSeminorms.hasBasis
theorem WithSeminorms.hasBasis_zero_ball (hp : WithSeminorms p) :
(𝓝 (0 : E)).HasBasis
(fun sr : Finset ι × ℝ => 0 < sr.2) fun sr => (sr.1.sup p).ball 0 sr.2 := by
refine ⟨fun V => ?_⟩
simp only [hp.hasBasis.mem_iff, SeminormFamily.basisSets_iff, Prod.exists]
constructor
· rintro ⟨-, ⟨s, r, hr, rfl⟩, hV⟩
exact ⟨s, r, hr, hV⟩
· rintro ⟨s, r, hr, hV⟩
exact ⟨_, ⟨s, r, hr, rfl⟩, hV⟩
#align with_seminorms.has_basis_zero_ball WithSeminorms.hasBasis_zero_ball
theorem WithSeminorms.hasBasis_ball (hp : WithSeminorms p) {x : E} :
(𝓝 (x : E)).HasBasis
(fun sr : Finset ι × ℝ => 0 < sr.2) fun sr => (sr.1.sup p).ball x sr.2 := by
have : TopologicalAddGroup E := hp.topologicalAddGroup
rw [← map_add_left_nhds_zero]
convert hp.hasBasis_zero_ball.map (x + ·) using 1
ext sr : 1
-- Porting note: extra type ascriptions needed on `0`
have : (sr.fst.sup p).ball (x +ᵥ (0 : E)) sr.snd = x +ᵥ (sr.fst.sup p).ball 0 sr.snd :=
Eq.symm (Seminorm.vadd_ball (sr.fst.sup p))
rwa [vadd_eq_add, add_zero] at this
#align with_seminorms.has_basis_ball WithSeminorms.hasBasis_ball
/-- The `x`-neighbourhoods of a space whose topology is induced by a family of seminorms
are exactly the sets which contain seminorm balls around `x`. -/
theorem WithSeminorms.mem_nhds_iff (hp : WithSeminorms p) (x : E) (U : Set E) :
U ∈ 𝓝 x ↔ ∃ s : Finset ι, ∃ r > 0, (s.sup p).ball x r ⊆ U := by
rw [hp.hasBasis_ball.mem_iff, Prod.exists]
#align with_seminorms.mem_nhds_iff WithSeminorms.mem_nhds_iff
/-- The open sets of a space whose topology is induced by a family of seminorms
are exactly the sets which contain seminorm balls around all of their points. -/
theorem WithSeminorms.isOpen_iff_mem_balls (hp : WithSeminorms p) (U : Set E) :
IsOpen U ↔ ∀ x ∈ U, ∃ s : Finset ι, ∃ r > 0, (s.sup p).ball x r ⊆ U := by
simp_rw [← WithSeminorms.mem_nhds_iff hp _ U, isOpen_iff_mem_nhds]
#align with_seminorms.is_open_iff_mem_balls WithSeminorms.isOpen_iff_mem_balls
/- Note that through the following lemmas, one also immediately has that separating families
of seminorms induce T₂ and T₃ topologies by `TopologicalAddGroup.t2Space`
and `TopologicalAddGroup.t3Space` -/
/-- A separating family of seminorms induces a T₁ topology. -/
theorem WithSeminorms.T1_of_separating (hp : WithSeminorms p)
(h : ∀ x, x ≠ 0 → ∃ i, p i x ≠ 0) : T1Space E := by
have := hp.topologicalAddGroup
refine TopologicalAddGroup.t1Space _ ?_
rw [← isOpen_compl_iff, hp.isOpen_iff_mem_balls]
rintro x (hx : x ≠ 0)
cases' h x hx with i pi_nonzero
refine ⟨{i}, p i x, by positivity, subset_compl_singleton_iff.mpr ?_⟩
rw [Finset.sup_singleton, mem_ball, zero_sub, map_neg_eq_map, not_lt]
#align with_seminorms.t1_of_separating WithSeminorms.T1_of_separating
/-- A family of seminorms inducing a T₁ topology is separating. -/
theorem WithSeminorms.separating_of_T1 [T1Space E] (hp : WithSeminorms p) (x : E) (hx : x ≠ 0) :
∃ i, p i x ≠ 0 := by
have := ((t1Space_TFAE E).out 0 9).mp (inferInstanceAs <| T1Space E)
by_contra! h
refine hx (this ?_)
rw [hp.hasBasis_zero_ball.specializes_iff]
rintro ⟨s, r⟩ (hr : 0 < r)
simp only [ball_finset_sup_eq_iInter _ _ _ hr, mem_iInter₂, mem_ball_zero, h, hr, forall_true_iff]
#align with_seminorms.separating_of_t1 WithSeminorms.separating_of_T1
/-- A family of seminorms is separating iff it induces a T₁ topology. -/
theorem WithSeminorms.separating_iff_T1 (hp : WithSeminorms p) :
(∀ x, x ≠ 0 → ∃ i, p i x ≠ 0) ↔ T1Space E := by
refine ⟨WithSeminorms.T1_of_separating hp, ?_⟩
intro
exact WithSeminorms.separating_of_T1 hp
#align with_seminorms.separating_iff_t1 WithSeminorms.separating_iff_T1
end Topology
section Tendsto
variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E] [Nonempty ι] [TopologicalSpace E]
variable {p : SeminormFamily 𝕜 E ι}
/-- Convergence along filters for `WithSeminorms`.
Variant with `Finset.sup`. -/
theorem WithSeminorms.tendsto_nhds' (hp : WithSeminorms p) (u : F → E) {f : Filter F} (y₀ : E) :
Filter.Tendsto u f (𝓝 y₀) ↔
∀ (s : Finset ι) (ε), 0 < ε → ∀ᶠ x in f, s.sup p (u x - y₀) < ε := by
simp [hp.hasBasis_ball.tendsto_right_iff]
#align with_seminorms.tendsto_nhds' WithSeminorms.tendsto_nhds'
/-- Convergence along filters for `WithSeminorms`. -/
theorem WithSeminorms.tendsto_nhds (hp : WithSeminorms p) (u : F → E) {f : Filter F} (y₀ : E) :
Filter.Tendsto u f (𝓝 y₀) ↔ ∀ i ε, 0 < ε → ∀ᶠ x in f, p i (u x - y₀) < ε := by
rw [hp.tendsto_nhds' u y₀]
exact
⟨fun h i => by simpa only [Finset.sup_singleton] using h {i}, fun h s ε hε =>
(s.eventually_all.2 fun i _ => h i ε hε).mono fun _ => finset_sup_apply_lt hε⟩
#align with_seminorms.tendsto_nhds WithSeminorms.tendsto_nhds
variable [SemilatticeSup F] [Nonempty F]
/-- Limit `→ ∞` for `WithSeminorms`. -/
theorem WithSeminorms.tendsto_nhds_atTop (hp : WithSeminorms p) (u : F → E) (y₀ : E) :
Filter.Tendsto u Filter.atTop (𝓝 y₀) ↔
∀ i ε, 0 < ε → ∃ x₀, ∀ x, x₀ ≤ x → p i (u x - y₀) < ε := by
rw [hp.tendsto_nhds u y₀]
exact forall₃_congr fun _ _ _ => Filter.eventually_atTop
#align with_seminorms.tendsto_nhds_at_top WithSeminorms.tendsto_nhds_atTop
end Tendsto
section TopologicalAddGroup
variable [NormedField 𝕜] [AddCommGroup E] [Module 𝕜 E]
variable [Nonempty ι]
section TopologicalSpace
variable [t : TopologicalSpace E]
theorem SeminormFamily.withSeminorms_of_nhds [TopologicalAddGroup E] (p : SeminormFamily 𝕜 E ι)
(h : 𝓝 (0 : E) = p.moduleFilterBasis.toFilterBasis.filter) : WithSeminorms p := by
refine
⟨TopologicalAddGroup.ext inferInstance p.addGroupFilterBasis.isTopologicalAddGroup ?_⟩
rw [AddGroupFilterBasis.nhds_zero_eq]
exact h
#align seminorm_family.with_seminorms_of_nhds SeminormFamily.withSeminorms_of_nhds
theorem SeminormFamily.withSeminorms_of_hasBasis [TopologicalAddGroup E] (p : SeminormFamily 𝕜 E ι)
(h : (𝓝 (0 : E)).HasBasis (fun s : Set E => s ∈ p.basisSets) id) : WithSeminorms p :=
p.withSeminorms_of_nhds <|
Filter.HasBasis.eq_of_same_basis h p.addGroupFilterBasis.toFilterBasis.hasBasis
#align seminorm_family.with_seminorms_of_has_basis SeminormFamily.withSeminorms_of_hasBasis
theorem SeminormFamily.withSeminorms_iff_nhds_eq_iInf [TopologicalAddGroup E]
(p : SeminormFamily 𝕜 E ι) : WithSeminorms p ↔ (𝓝 (0 : E)) = ⨅ i, (𝓝 0).comap (p i) := by
rw [← p.filter_eq_iInf]
refine ⟨fun h => ?_, p.withSeminorms_of_nhds⟩
rw [h.topology_eq_withSeminorms]
exact AddGroupFilterBasis.nhds_zero_eq _
#align seminorm_family.with_seminorms_iff_nhds_eq_infi SeminormFamily.withSeminorms_iff_nhds_eq_iInf
/-- The topology induced by a family of seminorms is exactly the infimum of the ones induced by
each seminorm individually. We express this as a characterization of `WithSeminorms p`. -/
| Mathlib/Analysis/LocallyConvex/WithSeminorms.lean | 438 | 446 | theorem SeminormFamily.withSeminorms_iff_topologicalSpace_eq_iInf [TopologicalAddGroup E]
(p : SeminormFamily 𝕜 E ι) :
WithSeminorms p ↔
t = ⨅ i, (p i).toSeminormedAddCommGroup.toUniformSpace.toTopologicalSpace := by |
rw [p.withSeminorms_iff_nhds_eq_iInf,
TopologicalAddGroup.ext_iff inferInstance (topologicalAddGroup_iInf fun i => inferInstance),
nhds_iInf]
congrm _ = ⨅ i, ?_
exact @comap_norm_nhds_zero _ (p i).toSeminormedAddGroup
|
/-
Copyright (c) 2023 Sophie Morel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sophie Morel
-/
import Mathlib.Analysis.Analytic.Basic
/-! We specialize the theory fo analytic functions to the case of functions that admit a
development given by a *finite* formal multilinear series. We call them "continuously polynomial",
which is abbreviated to `CPolynomial`. One reason to do that is that we no longer need a
completeness assumption on the target space `F` to make the series converge, so some of the results
are more general. The class of continuously polynomial functions includes functions defined by
polynomials on a normed `𝕜`-algebra and continuous multilinear maps.
## Main definitions
Let `p` be a formal multilinear series from `E` to `F`, i.e., `p n` is a multilinear map on `E^n`
for `n : ℕ`, and let `f` be a function from `E` to `F`.
* `HasFiniteFPowerSeriesOnBall f p x n r`: on the ball of center `x` with radius `r`,
`f (x + y) = ∑'_n pₘ yᵐ`, and moreover `pₘ = 0` if `n ≤ m`.
* `HasFiniteFPowerSeriesAt f p x n`: on some ball of center `x` with positive radius, holds
`HasFiniteFPowerSeriesOnBall f p x n r`.
* `CPolynomialAt 𝕜 f x`: there exists a power series `p` and a natural number `n` such that
holds `HasFPowerSeriesAt f p x n`.
* `CPolynomialOn 𝕜 f s`: the function `f` is analytic at every point of `s`.
We develop the basic properties of these notions, notably:
* If a function is continuously polynomial, then it is analytic, see
`HasFiniteFPowerSeriesOnBall.hasFPowerSeriesOnBall`, `HasFiniteFPowerSeriesAt.hasFPowerSeriesAt`,
`CPolynomialAt.analyticAt` and `CPolynomialOn.analyticOn`.
* The sum of a finite formal power series with positive radius is well defined on the whole space,
see `FormalMultilinearSeries.hasFiniteFPowerSeriesOnBall_of_finite`.
* If a function admits a finite power series in a ball, then it is continuously polynomial at
any point `y` of this ball, and the power series there can be expressed in terms of the initial
power series `p` as `p.changeOrigin y`, which is finite (with the same bound as `p`) by
`changeOrigin_finite_of_finite`. See `HasFiniteFPowerSeriesOnBall.changeOrigin `. It follows in
particular that the set of points at which a given function is continuously polynomial is open,
see `isOpen_cPolynomialAt`.
-/
variable {𝕜 E F G : Type*} [NontriviallyNormedField 𝕜] [NormedAddCommGroup E] [NormedSpace 𝕜 E]
[NormedAddCommGroup F] [NormedSpace 𝕜 F] [NormedAddCommGroup G] [NormedSpace 𝕜 G]
open scoped Classical
open Topology NNReal Filter ENNReal
open Set Filter Asymptotics
variable {f g : E → F} {p pf pg : FormalMultilinearSeries 𝕜 E F} {x : E} {r r' : ℝ≥0∞} {n m : ℕ}
section FiniteFPowerSeries
/-- Given a function `f : E → F`, a formal multilinear series `p` and `n : ℕ`, we say that
`f` has `p` as a finite power series on the ball of radius `r > 0` around `x` if
`f (x + y) = ∑' pₘ yᵐ` for all `‖y‖ < r` and `pₙ = 0` for `n ≤ m`. -/
structure HasFiniteFPowerSeriesOnBall (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E)
(n : ℕ) (r : ℝ≥0∞) extends HasFPowerSeriesOnBall f p x r : Prop where
finite : ∀ (m : ℕ), n ≤ m → p m = 0
theorem HasFiniteFPowerSeriesOnBall.mk' {f : E → F} {p : FormalMultilinearSeries 𝕜 E F} {x : E}
{n : ℕ} {r : ℝ≥0∞} (finite : ∀ (m : ℕ), n ≤ m → p m = 0) (pos : 0 < r)
(sum_eq : ∀ y ∈ EMetric.ball 0 r, (∑ i ∈ Finset.range n, p i fun _ ↦ y) = f (x + y)) :
HasFiniteFPowerSeriesOnBall f p x n r where
r_le := p.radius_eq_top_of_eventually_eq_zero (Filter.eventually_atTop.mpr ⟨n, finite⟩) ▸ le_top
r_pos := pos
hasSum hy := sum_eq _ hy ▸ hasSum_sum_of_ne_finset_zero fun m hm ↦ by
rw [Finset.mem_range, not_lt] at hm; rw [finite m hm]; rfl
finite := finite
/-- Given a function `f : E → F`, a formal multilinear series `p` and `n : ℕ`, we say that
`f` has `p` as a finite power series around `x` if `f (x + y) = ∑' pₙ yⁿ` for all `y` in a
neighborhood of `0`and `pₙ = 0` for `n ≤ m`. -/
def HasFiniteFPowerSeriesAt (f : E → F) (p : FormalMultilinearSeries 𝕜 E F) (x : E) (n : ℕ) :=
∃ r, HasFiniteFPowerSeriesOnBall f p x n r
theorem HasFiniteFPowerSeriesAt.toHasFPowerSeriesAt
(hf : HasFiniteFPowerSeriesAt f p x n) : HasFPowerSeriesAt f p x :=
let ⟨r, hf⟩ := hf
⟨r, hf.toHasFPowerSeriesOnBall⟩
theorem HasFiniteFPowerSeriesAt.finite (hf : HasFiniteFPowerSeriesAt f p x n) :
∀ m : ℕ, n ≤ m → p m = 0 := let ⟨_, hf⟩ := hf; hf.finite
variable (𝕜)
/-- Given a function `f : E → F`, we say that `f` is continuously polynomial (cpolynomial)
at `x` if it admits a finite power series expansion around `x`. -/
def CPolynomialAt (f : E → F) (x : E) :=
∃ (p : FormalMultilinearSeries 𝕜 E F) (n : ℕ), HasFiniteFPowerSeriesAt f p x n
/-- Given a function `f : E → F`, we say that `f` is continuously polynomial on a set `s`
if it is continuously polynomial around every point of `s`. -/
def CPolynomialOn (f : E → F) (s : Set E) :=
∀ x, x ∈ s → CPolynomialAt 𝕜 f x
variable {𝕜}
theorem HasFiniteFPowerSeriesOnBall.hasFiniteFPowerSeriesAt
(hf : HasFiniteFPowerSeriesOnBall f p x n r) :
HasFiniteFPowerSeriesAt f p x n :=
⟨r, hf⟩
theorem HasFiniteFPowerSeriesAt.cPolynomialAt (hf : HasFiniteFPowerSeriesAt f p x n) :
CPolynomialAt 𝕜 f x :=
⟨p, n, hf⟩
theorem HasFiniteFPowerSeriesOnBall.cPolynomialAt (hf : HasFiniteFPowerSeriesOnBall f p x n r) :
CPolynomialAt 𝕜 f x :=
hf.hasFiniteFPowerSeriesAt.cPolynomialAt
theorem CPolynomialAt.analyticAt (hf : CPolynomialAt 𝕜 f x) : AnalyticAt 𝕜 f x :=
let ⟨p, _, hp⟩ := hf
⟨p, hp.toHasFPowerSeriesAt⟩
theorem CPolynomialOn.analyticOn {s : Set E} (hf : CPolynomialOn 𝕜 f s) : AnalyticOn 𝕜 f s :=
fun x hx ↦ (hf x hx).analyticAt
theorem HasFiniteFPowerSeriesOnBall.congr (hf : HasFiniteFPowerSeriesOnBall f p x n r)
(hg : EqOn f g (EMetric.ball x r)) : HasFiniteFPowerSeriesOnBall g p x n r :=
⟨hf.1.congr hg, hf.finite⟩
/-- If a function `f` has a finite power series `p` around `x`, then the function
`z ↦ f (z - y)` has the same finite power series around `x + y`. -/
theorem HasFiniteFPowerSeriesOnBall.comp_sub (hf : HasFiniteFPowerSeriesOnBall f p x n r) (y : E) :
HasFiniteFPowerSeriesOnBall (fun z => f (z - y)) p (x + y) n r :=
⟨hf.1.comp_sub y, hf.finite⟩
theorem HasFiniteFPowerSeriesOnBall.mono (hf : HasFiniteFPowerSeriesOnBall f p x n r)
(r'_pos : 0 < r') (hr : r' ≤ r) : HasFiniteFPowerSeriesOnBall f p x n r' :=
⟨hf.1.mono r'_pos hr, hf.finite⟩
theorem HasFiniteFPowerSeriesAt.congr (hf : HasFiniteFPowerSeriesAt f p x n) (hg : f =ᶠ[𝓝 x] g) :
HasFiniteFPowerSeriesAt g p x n :=
Exists.imp (fun _ hg ↦ ⟨hg, hf.finite⟩) (hf.toHasFPowerSeriesAt.congr hg)
protected theorem HasFiniteFPowerSeriesAt.eventually (hf : HasFiniteFPowerSeriesAt f p x n) :
∀ᶠ r : ℝ≥0∞ in 𝓝[>] 0, HasFiniteFPowerSeriesOnBall f p x n r :=
hf.toHasFPowerSeriesAt.eventually.mono fun _ h ↦ ⟨h, hf.finite⟩
theorem hasFiniteFPowerSeriesOnBall_const {c : F} {e : E} :
HasFiniteFPowerSeriesOnBall (fun _ => c) (constFormalMultilinearSeries 𝕜 E c) e 1 ⊤ :=
⟨hasFPowerSeriesOnBall_const, fun n hn ↦ constFormalMultilinearSeries_apply (id hn : 0 < n).ne'⟩
theorem hasFiniteFPowerSeriesAt_const {c : F} {e : E} :
HasFiniteFPowerSeriesAt (fun _ => c) (constFormalMultilinearSeries 𝕜 E c) e 1 :=
⟨⊤, hasFiniteFPowerSeriesOnBall_const⟩
theorem CPolynomialAt_const {v : F} : CPolynomialAt 𝕜 (fun _ => v) x :=
⟨constFormalMultilinearSeries 𝕜 E v, 1, hasFiniteFPowerSeriesAt_const⟩
theorem CPolynomialOn_const {v : F} {s : Set E} : CPolynomialOn 𝕜 (fun _ => v) s :=
fun _ _ => CPolynomialAt_const
theorem HasFiniteFPowerSeriesOnBall.add (hf : HasFiniteFPowerSeriesOnBall f pf x n r)
(hg : HasFiniteFPowerSeriesOnBall g pg x m r) :
HasFiniteFPowerSeriesOnBall (f + g) (pf + pg) x (max n m) r :=
⟨hf.1.add hg.1, fun N hN ↦ by
rw [Pi.add_apply, hf.finite _ ((le_max_left n m).trans hN),
hg.finite _ ((le_max_right n m).trans hN), zero_add]⟩
theorem HasFiniteFPowerSeriesAt.add (hf : HasFiniteFPowerSeriesAt f pf x n)
(hg : HasFiniteFPowerSeriesAt g pg x m) :
HasFiniteFPowerSeriesAt (f + g) (pf + pg) x (max n m) := by
rcases (hf.eventually.and hg.eventually).exists with ⟨r, hr⟩
exact ⟨r, hr.1.add hr.2⟩
theorem CPolynomialAt.congr (hf : CPolynomialAt 𝕜 f x) (hg : f =ᶠ[𝓝 x] g) : CPolynomialAt 𝕜 g x :=
let ⟨_, _, hpf⟩ := hf
(hpf.congr hg).cPolynomialAt
theorem CPolynomialAt_congr (h : f =ᶠ[𝓝 x] g) : CPolynomialAt 𝕜 f x ↔ CPolynomialAt 𝕜 g x :=
⟨fun hf ↦ hf.congr h, fun hg ↦ hg.congr h.symm⟩
theorem CPolynomialAt.add (hf : CPolynomialAt 𝕜 f x) (hg : CPolynomialAt 𝕜 g x) :
CPolynomialAt 𝕜 (f + g) x :=
let ⟨_, _, hpf⟩ := hf
let ⟨_, _, hqf⟩ := hg
(hpf.add hqf).cPolynomialAt
theorem HasFiniteFPowerSeriesOnBall.neg (hf : HasFiniteFPowerSeriesOnBall f pf x n r) :
HasFiniteFPowerSeriesOnBall (-f) (-pf) x n r :=
⟨hf.1.neg, fun m hm ↦ by rw [Pi.neg_apply, hf.finite m hm, neg_zero]⟩
theorem HasFiniteFPowerSeriesAt.neg (hf : HasFiniteFPowerSeriesAt f pf x n) :
HasFiniteFPowerSeriesAt (-f) (-pf) x n :=
let ⟨_, hrf⟩ := hf
hrf.neg.hasFiniteFPowerSeriesAt
theorem CPolynomialAt.neg (hf : CPolynomialAt 𝕜 f x) : CPolynomialAt 𝕜 (-f) x :=
let ⟨_, _, hpf⟩ := hf
hpf.neg.cPolynomialAt
theorem HasFiniteFPowerSeriesOnBall.sub (hf : HasFiniteFPowerSeriesOnBall f pf x n r)
(hg : HasFiniteFPowerSeriesOnBall g pg x m r) :
HasFiniteFPowerSeriesOnBall (f - g) (pf - pg) x (max n m) r := by
simpa only [sub_eq_add_neg] using hf.add hg.neg
theorem HasFiniteFPowerSeriesAt.sub (hf : HasFiniteFPowerSeriesAt f pf x n)
(hg : HasFiniteFPowerSeriesAt g pg x m) :
HasFiniteFPowerSeriesAt (f - g) (pf - pg) x (max n m) := by
simpa only [sub_eq_add_neg] using hf.add hg.neg
theorem CPolynomialAt.sub (hf : CPolynomialAt 𝕜 f x) (hg : CPolynomialAt 𝕜 g x) :
CPolynomialAt 𝕜 (f - g) x := by
simpa only [sub_eq_add_neg] using hf.add hg.neg
theorem CPolynomialOn.mono {s t : Set E} (hf : CPolynomialOn 𝕜 f t) (hst : s ⊆ t) :
CPolynomialOn 𝕜 f s :=
fun z hz => hf z (hst hz)
theorem CPolynomialOn.congr' {s : Set E} (hf : CPolynomialOn 𝕜 f s) (hg : f =ᶠ[𝓝ˢ s] g) :
CPolynomialOn 𝕜 g s :=
fun z hz => (hf z hz).congr (mem_nhdsSet_iff_forall.mp hg z hz)
theorem CPolynomialOn_congr' {s : Set E} (h : f =ᶠ[𝓝ˢ s] g) :
CPolynomialOn 𝕜 f s ↔ CPolynomialOn 𝕜 g s :=
⟨fun hf => hf.congr' h, fun hg => hg.congr' h.symm⟩
theorem CPolynomialOn.congr {s : Set E} (hs : IsOpen s) (hf : CPolynomialOn 𝕜 f s)
(hg : s.EqOn f g) : CPolynomialOn 𝕜 g s :=
hf.congr' <| mem_nhdsSet_iff_forall.mpr
(fun _ hz => eventuallyEq_iff_exists_mem.mpr ⟨s, hs.mem_nhds hz, hg⟩)
theorem CPolynomialOn_congr {s : Set E} (hs : IsOpen s) (h : s.EqOn f g) :
CPolynomialOn 𝕜 f s ↔ CPolynomialOn 𝕜 g s :=
⟨fun hf => hf.congr hs h, fun hg => hg.congr hs h.symm⟩
theorem CPolynomialOn.add {s : Set E} (hf : CPolynomialOn 𝕜 f s) (hg : CPolynomialOn 𝕜 g s) :
CPolynomialOn 𝕜 (f + g) s :=
fun z hz => (hf z hz).add (hg z hz)
theorem CPolynomialOn.sub {s : Set E} (hf : CPolynomialOn 𝕜 f s) (hg : CPolynomialOn 𝕜 g s) :
CPolynomialOn 𝕜 (f - g) s :=
fun z hz => (hf z hz).sub (hg z hz)
/-- If a function `f` has a finite power series `p` on a ball and `g` is a continuous linear map,
then `g ∘ f` has the finite power series `g ∘ p` on the same ball. -/
theorem ContinuousLinearMap.comp_hasFiniteFPowerSeriesOnBall (g : F →L[𝕜] G)
(h : HasFiniteFPowerSeriesOnBall f p x n r) :
HasFiniteFPowerSeriesOnBall (g ∘ f) (g.compFormalMultilinearSeries p) x n r :=
⟨g.comp_hasFPowerSeriesOnBall h.1, fun m hm ↦ by
rw [compFormalMultilinearSeries_apply, h.finite m hm]
ext; exact map_zero g⟩
/-- If a function `f` is continuously polynomial on a set `s` and `g` is a continuous linear map,
then `g ∘ f` is continuously polynomial on `s`. -/
theorem ContinuousLinearMap.comp_cPolynomialOn {s : Set E} (g : F →L[𝕜] G)
(h : CPolynomialOn 𝕜 f s) : CPolynomialOn 𝕜 (g ∘ f) s := by
rintro x hx
rcases h x hx with ⟨p, n, r, hp⟩
exact ⟨g.compFormalMultilinearSeries p, n, r, g.comp_hasFiniteFPowerSeriesOnBall hp⟩
/-- If a function admits a finite power series expansion bounded by `n`, then it is equal to
the `m`th partial sums of this power series at every point of the disk for `n ≤ m`. -/
theorem HasFiniteFPowerSeriesOnBall.eq_partialSum
(hf : HasFiniteFPowerSeriesOnBall f p x n r) :
∀ y ∈ EMetric.ball (0 : E) r, ∀ m, n ≤ m →
f (x + y) = p.partialSum m y :=
fun y hy m hm ↦ (hf.hasSum hy).unique (hasSum_sum_of_ne_finset_zero
(f := fun m => p m (fun _ => y)) (s := Finset.range m)
(fun N hN => by simp only; simp only [Finset.mem_range, not_lt] at hN
rw [hf.finite _ (le_trans hm hN), ContinuousMultilinearMap.zero_apply]))
/-- Variant of the previous result with the variable expressed as `y` instead of `x + y`. -/
theorem HasFiniteFPowerSeriesOnBall.eq_partialSum'
(hf : HasFiniteFPowerSeriesOnBall f p x n r) :
∀ y ∈ EMetric.ball x r, ∀ m, n ≤ m →
f y = p.partialSum m (y - x) := by
intro y hy m hm
rw [EMetric.mem_ball, edist_eq_coe_nnnorm_sub, ← mem_emetric_ball_zero_iff] at hy
rw [← (HasFiniteFPowerSeriesOnBall.eq_partialSum hf _ hy m hm), add_sub_cancel]
/-! The particular cases where `f` has a finite power series bounded by `0` or `1`. -/
/-- If `f` has a formal power series on a ball bounded by `0`, then `f` is equal to `0` on
the ball. -/
theorem HasFiniteFPowerSeriesOnBall.eq_zero_of_bound_zero
(hf : HasFiniteFPowerSeriesOnBall f pf x 0 r) : ∀ y ∈ EMetric.ball x r, f y = 0 := by
intro y hy
rw [hf.eq_partialSum' y hy 0 le_rfl, FormalMultilinearSeries.partialSum]
simp only [Finset.range_zero, Finset.sum_empty]
theorem HasFiniteFPowerSeriesOnBall.bound_zero_of_eq_zero (hf : ∀ y ∈ EMetric.ball x r, f y = 0)
(r_pos : 0 < r) (hp : ∀ n, p n = 0) : HasFiniteFPowerSeriesOnBall f p x 0 r := by
refine ⟨⟨?_, r_pos, ?_⟩, fun n _ ↦ hp n⟩
· rw [p.radius_eq_top_of_forall_image_add_eq_zero 0 (fun n ↦ by rw [add_zero]; exact hp n)]
exact le_top
· intro y hy
rw [hf (x + y)]
· convert hasSum_zero
rw [hp, ContinuousMultilinearMap.zero_apply]
· rwa [EMetric.mem_ball, edist_eq_coe_nnnorm_sub, add_comm, add_sub_cancel_right,
← edist_eq_coe_nnnorm, ← EMetric.mem_ball]
/-- If `f` has a formal power series at `x` bounded by `0`, then `f` is equal to `0` in a
neighborhood of `x`. -/
theorem HasFiniteFPowerSeriesAt.eventually_zero_of_bound_zero
(hf : HasFiniteFPowerSeriesAt f pf x 0) : f =ᶠ[𝓝 x] 0 :=
Filter.eventuallyEq_iff_exists_mem.mpr (let ⟨r, hf⟩ := hf; ⟨EMetric.ball x r,
EMetric.ball_mem_nhds x hf.r_pos, fun y hy ↦ hf.eq_zero_of_bound_zero y hy⟩)
/-- If `f` has a formal power series on a ball bounded by `1`, then `f` is constant equal
to `f x` on the ball. -/
| Mathlib/Analysis/Analytic/CPolynomial.lean | 305 | 313 | theorem HasFiniteFPowerSeriesOnBall.eq_const_of_bound_one
(hf : HasFiniteFPowerSeriesOnBall f pf x 1 r) : ∀ y ∈ EMetric.ball x r, f y = f x := by |
intro y hy
rw [hf.eq_partialSum' y hy 1 le_rfl, hf.eq_partialSum' x
(by rw [EMetric.mem_ball, edist_self]; exact hf.r_pos) 1 le_rfl]
simp only [FormalMultilinearSeries.partialSum, Finset.range_one, Finset.sum_singleton]
congr
apply funext
simp only [IsEmpty.forall_iff]
|
/-
Copyright (c) 2018 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Julian Kuelshammer
-/
import Mathlib.Algebra.CharP.Defs
import Mathlib.Algebra.GroupPower.IterateHom
import Mathlib.Algebra.GroupWithZero.Divisibility
import Mathlib.Data.Int.ModEq
import Mathlib.Data.Set.Pointwise.Basic
import Mathlib.Dynamics.PeriodicPts
import Mathlib.GroupTheory.Index
import Mathlib.Order.Interval.Finset.Nat
import Mathlib.Order.Interval.Set.Infinite
#align_import group_theory.order_of_element from "leanprover-community/mathlib"@"d07245fd37786daa997af4f1a73a49fa3b748408"
/-!
# Order of an element
This file defines the order of an element of a finite group. For a finite group `G` the order of
`x ∈ G` is the minimal `n ≥ 1` such that `x ^ n = 1`.
## Main definitions
* `IsOfFinOrder` is a predicate on an element `x` of a monoid `G` saying that `x` is of finite
order.
* `IsOfFinAddOrder` is the additive analogue of `IsOfFinOrder`.
* `orderOf x` defines the order of an element `x` of a monoid `G`, by convention its value is `0`
if `x` has infinite order.
* `addOrderOf` is the additive analogue of `orderOf`.
## Tags
order of an element
-/
open Function Fintype Nat Pointwise Subgroup Submonoid
variable {G H A α β : Type*}
section Monoid
variable [Monoid G] {a b x y : G} {n m : ℕ}
section IsOfFinOrder
-- Porting note(#12129): additional beta reduction needed
@[to_additive]
theorem isPeriodicPt_mul_iff_pow_eq_one (x : G) : IsPeriodicPt (x * ·) n 1 ↔ x ^ n = 1 := by
rw [IsPeriodicPt, IsFixedPt, mul_left_iterate]; beta_reduce; rw [mul_one]
#align is_periodic_pt_mul_iff_pow_eq_one isPeriodicPt_mul_iff_pow_eq_one
#align is_periodic_pt_add_iff_nsmul_eq_zero isPeriodicPt_add_iff_nsmul_eq_zero
/-- `IsOfFinOrder` is a predicate on an element `x` of a monoid to be of finite order, i.e. there
exists `n ≥ 1` such that `x ^ n = 1`. -/
@[to_additive "`IsOfFinAddOrder` is a predicate on an element `a` of an
additive monoid to be of finite order, i.e. there exists `n ≥ 1` such that `n • a = 0`."]
def IsOfFinOrder (x : G) : Prop :=
(1 : G) ∈ periodicPts (x * ·)
#align is_of_fin_order IsOfFinOrder
#align is_of_fin_add_order IsOfFinAddOrder
theorem isOfFinAddOrder_ofMul_iff : IsOfFinAddOrder (Additive.ofMul x) ↔ IsOfFinOrder x :=
Iff.rfl
#align is_of_fin_add_order_of_mul_iff isOfFinAddOrder_ofMul_iff
theorem isOfFinOrder_ofAdd_iff {α : Type*} [AddMonoid α] {x : α} :
IsOfFinOrder (Multiplicative.ofAdd x) ↔ IsOfFinAddOrder x := Iff.rfl
#align is_of_fin_order_of_add_iff isOfFinOrder_ofAdd_iff
@[to_additive]
theorem isOfFinOrder_iff_pow_eq_one : IsOfFinOrder x ↔ ∃ n, 0 < n ∧ x ^ n = 1 := by
simp [IsOfFinOrder, mem_periodicPts, isPeriodicPt_mul_iff_pow_eq_one]
#align is_of_fin_order_iff_pow_eq_one isOfFinOrder_iff_pow_eq_one
#align is_of_fin_add_order_iff_nsmul_eq_zero isOfFinAddOrder_iff_nsmul_eq_zero
@[to_additive] alias ⟨IsOfFinOrder.exists_pow_eq_one, _⟩ := isOfFinOrder_iff_pow_eq_one
@[to_additive]
lemma isOfFinOrder_iff_zpow_eq_one {G} [Group G] {x : G} :
IsOfFinOrder x ↔ ∃ (n : ℤ), n ≠ 0 ∧ x ^ n = 1 := by
rw [isOfFinOrder_iff_pow_eq_one]
refine ⟨fun ⟨n, hn, hn'⟩ ↦ ⟨n, Int.natCast_ne_zero_iff_pos.mpr hn, zpow_natCast x n ▸ hn'⟩,
fun ⟨n, hn, hn'⟩ ↦ ⟨n.natAbs, Int.natAbs_pos.mpr hn, ?_⟩⟩
cases' (Int.natAbs_eq_iff (a := n)).mp rfl with h h
· rwa [h, zpow_natCast] at hn'
· rwa [h, zpow_neg, inv_eq_one, zpow_natCast] at hn'
/-- See also `injective_pow_iff_not_isOfFinOrder`. -/
@[to_additive "See also `injective_nsmul_iff_not_isOfFinAddOrder`."]
theorem not_isOfFinOrder_of_injective_pow {x : G} (h : Injective fun n : ℕ => x ^ n) :
¬IsOfFinOrder x := by
simp_rw [isOfFinOrder_iff_pow_eq_one, not_exists, not_and]
intro n hn_pos hnx
rw [← pow_zero x] at hnx
rw [h hnx] at hn_pos
exact irrefl 0 hn_pos
#align not_is_of_fin_order_of_injective_pow not_isOfFinOrder_of_injective_pow
#align not_is_of_fin_add_order_of_injective_nsmul not_isOfFinAddOrder_of_injective_nsmul
lemma IsOfFinOrder.pow {n : ℕ} : IsOfFinOrder a → IsOfFinOrder (a ^ n) := by
simp_rw [isOfFinOrder_iff_pow_eq_one]
rintro ⟨m, hm, ha⟩
exact ⟨m, hm, by simp [pow_right_comm _ n, ha]⟩
/-- Elements of finite order are of finite order in submonoids. -/
@[to_additive "Elements of finite order are of finite order in submonoids."]
theorem Submonoid.isOfFinOrder_coe {H : Submonoid G} {x : H} :
IsOfFinOrder (x : G) ↔ IsOfFinOrder x := by
rw [isOfFinOrder_iff_pow_eq_one, isOfFinOrder_iff_pow_eq_one]
norm_cast
#align is_of_fin_order_iff_coe Submonoid.isOfFinOrder_coe
#align is_of_fin_add_order_iff_coe AddSubmonoid.isOfFinAddOrder_coe
/-- The image of an element of finite order has finite order. -/
@[to_additive "The image of an element of finite additive order has finite additive order."]
theorem MonoidHom.isOfFinOrder [Monoid H] (f : G →* H) {x : G} (h : IsOfFinOrder x) :
IsOfFinOrder <| f x :=
isOfFinOrder_iff_pow_eq_one.mpr <| by
obtain ⟨n, npos, hn⟩ := h.exists_pow_eq_one
exact ⟨n, npos, by rw [← f.map_pow, hn, f.map_one]⟩
#align monoid_hom.is_of_fin_order MonoidHom.isOfFinOrder
#align add_monoid_hom.is_of_fin_order AddMonoidHom.isOfFinAddOrder
/-- If a direct product has finite order then so does each component. -/
@[to_additive "If a direct product has finite additive order then so does each component."]
theorem IsOfFinOrder.apply {η : Type*} {Gs : η → Type*} [∀ i, Monoid (Gs i)] {x : ∀ i, Gs i}
(h : IsOfFinOrder x) : ∀ i, IsOfFinOrder (x i) := by
obtain ⟨n, npos, hn⟩ := h.exists_pow_eq_one
exact fun _ => isOfFinOrder_iff_pow_eq_one.mpr ⟨n, npos, (congr_fun hn.symm _).symm⟩
#align is_of_fin_order.apply IsOfFinOrder.apply
#align is_of_fin_add_order.apply IsOfFinAddOrder.apply
/-- 1 is of finite order in any monoid. -/
@[to_additive "0 is of finite order in any additive monoid."]
theorem isOfFinOrder_one : IsOfFinOrder (1 : G) :=
isOfFinOrder_iff_pow_eq_one.mpr ⟨1, Nat.one_pos, one_pow 1⟩
#align is_of_fin_order_one isOfFinOrder_one
#align is_of_fin_order_zero isOfFinAddOrder_zero
/-- The submonoid generated by an element is a group if that element has finite order. -/
@[to_additive "The additive submonoid generated by an element is
an additive group if that element has finite order."]
noncomputable abbrev IsOfFinOrder.groupPowers (hx : IsOfFinOrder x) :
Group (Submonoid.powers x) := by
obtain ⟨hpos, hx⟩ := hx.exists_pow_eq_one.choose_spec
exact Submonoid.groupPowers hpos hx
end IsOfFinOrder
/-- `orderOf x` is the order of the element `x`, i.e. the `n ≥ 1`, s.t. `x ^ n = 1` if it exists.
Otherwise, i.e. if `x` is of infinite order, then `orderOf x` is `0` by convention. -/
@[to_additive
"`addOrderOf a` is the order of the element `a`, i.e. the `n ≥ 1`, s.t. `n • a = 0` if it
exists. Otherwise, i.e. if `a` is of infinite order, then `addOrderOf a` is `0` by convention."]
noncomputable def orderOf (x : G) : ℕ :=
minimalPeriod (x * ·) 1
#align order_of orderOf
#align add_order_of addOrderOf
@[simp]
theorem addOrderOf_ofMul_eq_orderOf (x : G) : addOrderOf (Additive.ofMul x) = orderOf x :=
rfl
#align add_order_of_of_mul_eq_order_of addOrderOf_ofMul_eq_orderOf
@[simp]
lemma orderOf_ofAdd_eq_addOrderOf {α : Type*} [AddMonoid α] (a : α) :
orderOf (Multiplicative.ofAdd a) = addOrderOf a := rfl
#align order_of_of_add_eq_add_order_of orderOf_ofAdd_eq_addOrderOf
@[to_additive]
protected lemma IsOfFinOrder.orderOf_pos (h : IsOfFinOrder x) : 0 < orderOf x :=
minimalPeriod_pos_of_mem_periodicPts h
#align order_of_pos' IsOfFinOrder.orderOf_pos
#align add_order_of_pos' IsOfFinAddOrder.addOrderOf_pos
@[to_additive addOrderOf_nsmul_eq_zero]
theorem pow_orderOf_eq_one (x : G) : x ^ orderOf x = 1 := by
convert Eq.trans _ (isPeriodicPt_minimalPeriod (x * ·) 1)
-- Porting note(#12129): additional beta reduction needed in the middle of the rewrite
rw [orderOf, mul_left_iterate]; beta_reduce; rw [mul_one]
#align pow_order_of_eq_one pow_orderOf_eq_one
#align add_order_of_nsmul_eq_zero addOrderOf_nsmul_eq_zero
@[to_additive]
theorem orderOf_eq_zero (h : ¬IsOfFinOrder x) : orderOf x = 0 := by
rwa [orderOf, minimalPeriod, dif_neg]
#align order_of_eq_zero orderOf_eq_zero
#align add_order_of_eq_zero addOrderOf_eq_zero
@[to_additive]
theorem orderOf_eq_zero_iff : orderOf x = 0 ↔ ¬IsOfFinOrder x :=
⟨fun h H ↦ H.orderOf_pos.ne' h, orderOf_eq_zero⟩
#align order_of_eq_zero_iff orderOf_eq_zero_iff
#align add_order_of_eq_zero_iff addOrderOf_eq_zero_iff
@[to_additive]
theorem orderOf_eq_zero_iff' : orderOf x = 0 ↔ ∀ n : ℕ, 0 < n → x ^ n ≠ 1 := by
simp_rw [orderOf_eq_zero_iff, isOfFinOrder_iff_pow_eq_one, not_exists, not_and]
#align order_of_eq_zero_iff' orderOf_eq_zero_iff'
#align add_order_of_eq_zero_iff' addOrderOf_eq_zero_iff'
@[to_additive]
theorem orderOf_eq_iff {n} (h : 0 < n) :
orderOf x = n ↔ x ^ n = 1 ∧ ∀ m, m < n → 0 < m → x ^ m ≠ 1 := by
simp_rw [Ne, ← isPeriodicPt_mul_iff_pow_eq_one, orderOf, minimalPeriod]
split_ifs with h1
· classical
rw [find_eq_iff]
simp only [h, true_and]
push_neg
rfl
· rw [iff_false_left h.ne]
rintro ⟨h', -⟩
exact h1 ⟨n, h, h'⟩
#align order_of_eq_iff orderOf_eq_iff
#align add_order_of_eq_iff addOrderOf_eq_iff
/-- A group element has finite order iff its order is positive. -/
@[to_additive
"A group element has finite additive order iff its order is positive."]
theorem orderOf_pos_iff : 0 < orderOf x ↔ IsOfFinOrder x := by
rw [iff_not_comm.mp orderOf_eq_zero_iff, pos_iff_ne_zero]
#align order_of_pos_iff orderOf_pos_iff
#align add_order_of_pos_iff addOrderOf_pos_iff
@[to_additive]
theorem IsOfFinOrder.mono [Monoid β] {y : β} (hx : IsOfFinOrder x) (h : orderOf y ∣ orderOf x) :
IsOfFinOrder y := by rw [← orderOf_pos_iff] at hx ⊢; exact Nat.pos_of_dvd_of_pos h hx
#align is_of_fin_order.mono IsOfFinOrder.mono
#align is_of_fin_add_order.mono IsOfFinAddOrder.mono
@[to_additive]
theorem pow_ne_one_of_lt_orderOf' (n0 : n ≠ 0) (h : n < orderOf x) : x ^ n ≠ 1 := fun j =>
not_isPeriodicPt_of_pos_of_lt_minimalPeriod n0 h ((isPeriodicPt_mul_iff_pow_eq_one x).mpr j)
#align pow_ne_one_of_lt_order_of' pow_ne_one_of_lt_orderOf'
#align nsmul_ne_zero_of_lt_add_order_of' nsmul_ne_zero_of_lt_addOrderOf'
@[to_additive]
theorem orderOf_le_of_pow_eq_one (hn : 0 < n) (h : x ^ n = 1) : orderOf x ≤ n :=
IsPeriodicPt.minimalPeriod_le hn (by rwa [isPeriodicPt_mul_iff_pow_eq_one])
#align order_of_le_of_pow_eq_one orderOf_le_of_pow_eq_one
#align add_order_of_le_of_nsmul_eq_zero addOrderOf_le_of_nsmul_eq_zero
@[to_additive (attr := simp)]
theorem orderOf_one : orderOf (1 : G) = 1 := by
rw [orderOf, ← minimalPeriod_id (x := (1:G)), ← one_mul_eq_id]
#align order_of_one orderOf_one
#align order_of_zero addOrderOf_zero
@[to_additive (attr := simp) AddMonoid.addOrderOf_eq_one_iff]
theorem orderOf_eq_one_iff : orderOf x = 1 ↔ x = 1 := by
rw [orderOf, minimalPeriod_eq_one_iff_isFixedPt, IsFixedPt, mul_one]
#align order_of_eq_one_iff orderOf_eq_one_iff
#align add_monoid.order_of_eq_one_iff AddMonoid.addOrderOf_eq_one_iff
@[to_additive (attr := simp) mod_addOrderOf_nsmul]
lemma pow_mod_orderOf (x : G) (n : ℕ) : x ^ (n % orderOf x) = x ^ n :=
calc
x ^ (n % orderOf x) = x ^ (n % orderOf x + orderOf x * (n / orderOf x)) := by
simp [pow_add, pow_mul, pow_orderOf_eq_one]
_ = x ^ n := by rw [Nat.mod_add_div]
#align pow_eq_mod_order_of pow_mod_orderOf
#align nsmul_eq_mod_add_order_of mod_addOrderOf_nsmul
@[to_additive]
theorem orderOf_dvd_of_pow_eq_one (h : x ^ n = 1) : orderOf x ∣ n :=
IsPeriodicPt.minimalPeriod_dvd ((isPeriodicPt_mul_iff_pow_eq_one _).mpr h)
#align order_of_dvd_of_pow_eq_one orderOf_dvd_of_pow_eq_one
#align add_order_of_dvd_of_nsmul_eq_zero addOrderOf_dvd_of_nsmul_eq_zero
@[to_additive]
theorem orderOf_dvd_iff_pow_eq_one {n : ℕ} : orderOf x ∣ n ↔ x ^ n = 1 :=
⟨fun h => by rw [← pow_mod_orderOf, Nat.mod_eq_zero_of_dvd h, _root_.pow_zero],
orderOf_dvd_of_pow_eq_one⟩
#align order_of_dvd_iff_pow_eq_one orderOf_dvd_iff_pow_eq_one
#align add_order_of_dvd_iff_nsmul_eq_zero addOrderOf_dvd_iff_nsmul_eq_zero
@[to_additive addOrderOf_smul_dvd]
theorem orderOf_pow_dvd (n : ℕ) : orderOf (x ^ n) ∣ orderOf x := by
rw [orderOf_dvd_iff_pow_eq_one, pow_right_comm, pow_orderOf_eq_one, one_pow]
#align order_of_pow_dvd orderOf_pow_dvd
#align add_order_of_smul_dvd addOrderOf_smul_dvd
@[to_additive]
lemma pow_injOn_Iio_orderOf : (Set.Iio <| orderOf x).InjOn (x ^ ·) := by
simpa only [mul_left_iterate, mul_one]
using iterate_injOn_Iio_minimalPeriod (f := (x * ·)) (x := 1)
#align pow_injective_of_lt_order_of pow_injOn_Iio_orderOf
#align nsmul_injective_of_lt_add_order_of nsmul_injOn_Iio_addOrderOf
@[to_additive]
protected lemma IsOfFinOrder.mem_powers_iff_mem_range_orderOf [DecidableEq G]
(hx : IsOfFinOrder x) :
y ∈ Submonoid.powers x ↔ y ∈ (Finset.range (orderOf x)).image (x ^ ·) :=
Finset.mem_range_iff_mem_finset_range_of_mod_eq' hx.orderOf_pos <| pow_mod_orderOf _
#align mem_powers_iff_mem_range_order_of' IsOfFinOrder.mem_powers_iff_mem_range_orderOf
#align mem_multiples_iff_mem_range_add_order_of' IsOfFinAddOrder.mem_multiples_iff_mem_range_addOrderOf
@[to_additive]
protected lemma IsOfFinOrder.powers_eq_image_range_orderOf [DecidableEq G] (hx : IsOfFinOrder x) :
(Submonoid.powers x : Set G) = (Finset.range (orderOf x)).image (x ^ ·) :=
Set.ext fun _ ↦ hx.mem_powers_iff_mem_range_orderOf
@[deprecated (since := "2024-02-21")]
alias IsOfFinAddOrder.powers_eq_image_range_orderOf :=
IsOfFinAddOrder.multiples_eq_image_range_addOrderOf
@[to_additive]
theorem pow_eq_one_iff_modEq : x ^ n = 1 ↔ n ≡ 0 [MOD orderOf x] := by
rw [modEq_zero_iff_dvd, orderOf_dvd_iff_pow_eq_one]
#align pow_eq_one_iff_modeq pow_eq_one_iff_modEq
#align nsmul_eq_zero_iff_modeq nsmul_eq_zero_iff_modEq
@[to_additive]
| Mathlib/GroupTheory/OrderOfElement.lean | 314 | 318 | theorem orderOf_map_dvd {H : Type*} [Monoid H] (ψ : G →* H) (x : G) :
orderOf (ψ x) ∣ orderOf x := by |
apply orderOf_dvd_of_pow_eq_one
rw [← map_pow, pow_orderOf_eq_one]
apply map_one
|
/-
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.MonoidAlgebra.Degree
import Mathlib.Algebra.Polynomial.Coeff
import Mathlib.Algebra.Polynomial.Monomial
import Mathlib.Data.Fintype.BigOperators
import Mathlib.Data.Nat.WithBot
import Mathlib.Data.Nat.Cast.WithTop
import Mathlib.Data.Nat.SuccPred
#align_import data.polynomial.degree.definitions from "leanprover-community/mathlib"@"808ea4ebfabeb599f21ec4ae87d6dc969597887f"
/-!
# Theory of univariate polynomials
The definitions include
`degree`, `Monic`, `leadingCoeff`
Results include
- `degree_mul` : The degree of the product is the sum of degrees
- `leadingCoeff_add_of_degree_eq` and `leadingCoeff_add_of_degree_lt` :
The leading_coefficient of a sum is determined by the leading coefficients and degrees
-/
-- Porting note: `Mathlib.Data.Nat.Cast.WithTop` should be imported for `Nat.cast_withBot`.
set_option linter.uppercaseLean3 false
noncomputable section
open Finsupp Finset
open Polynomial
namespace Polynomial
universe u v
variable {R : Type u} {S : Type v} {a b c d : R} {n m : ℕ}
section Semiring
variable [Semiring R] {p q r : R[X]}
/-- `degree p` is the degree of the polynomial `p`, i.e. the largest `X`-exponent in `p`.
`degree p = some n` when `p ≠ 0` and `n` is the highest power of `X` that appears in `p`, otherwise
`degree 0 = ⊥`. -/
def degree (p : R[X]) : WithBot ℕ :=
p.support.max
#align polynomial.degree Polynomial.degree
theorem supDegree_eq_degree (p : R[X]) : p.toFinsupp.supDegree WithBot.some = p.degree :=
max_eq_sup_coe
theorem degree_lt_wf : WellFounded fun p q : R[X] => degree p < degree q :=
InvImage.wf degree wellFounded_lt
#align polynomial.degree_lt_wf Polynomial.degree_lt_wf
instance : WellFoundedRelation R[X] :=
⟨_, degree_lt_wf⟩
/-- `natDegree p` forces `degree p` to ℕ, by defining `natDegree 0 = 0`. -/
def natDegree (p : R[X]) : ℕ :=
(degree p).unbot' 0
#align polynomial.nat_degree Polynomial.natDegree
/-- `leadingCoeff p` gives the coefficient of the highest power of `X` in `p`-/
def leadingCoeff (p : R[X]) : R :=
coeff p (natDegree p)
#align polynomial.leading_coeff Polynomial.leadingCoeff
/-- a polynomial is `Monic` if its leading coefficient is 1 -/
def Monic (p : R[X]) :=
leadingCoeff p = (1 : R)
#align polynomial.monic Polynomial.Monic
@[nontriviality]
theorem monic_of_subsingleton [Subsingleton R] (p : R[X]) : Monic p :=
Subsingleton.elim _ _
#align polynomial.monic_of_subsingleton Polynomial.monic_of_subsingleton
theorem Monic.def : Monic p ↔ leadingCoeff p = 1 :=
Iff.rfl
#align polynomial.monic.def Polynomial.Monic.def
instance Monic.decidable [DecidableEq R] : Decidable (Monic p) := by unfold Monic; infer_instance
#align polynomial.monic.decidable Polynomial.Monic.decidable
@[simp]
theorem Monic.leadingCoeff {p : R[X]} (hp : p.Monic) : leadingCoeff p = 1 :=
hp
#align polynomial.monic.leading_coeff Polynomial.Monic.leadingCoeff
theorem Monic.coeff_natDegree {p : R[X]} (hp : p.Monic) : p.coeff p.natDegree = 1 :=
hp
#align polynomial.monic.coeff_nat_degree Polynomial.Monic.coeff_natDegree
@[simp]
theorem degree_zero : degree (0 : R[X]) = ⊥ :=
rfl
#align polynomial.degree_zero Polynomial.degree_zero
@[simp]
theorem natDegree_zero : natDegree (0 : R[X]) = 0 :=
rfl
#align polynomial.nat_degree_zero Polynomial.natDegree_zero
@[simp]
theorem coeff_natDegree : coeff p (natDegree p) = leadingCoeff p :=
rfl
#align polynomial.coeff_nat_degree Polynomial.coeff_natDegree
@[simp]
theorem degree_eq_bot : degree p = ⊥ ↔ p = 0 :=
⟨fun h => support_eq_empty.1 (Finset.max_eq_bot.1 h), fun h => h.symm ▸ rfl⟩
#align polynomial.degree_eq_bot Polynomial.degree_eq_bot
@[nontriviality]
theorem degree_of_subsingleton [Subsingleton R] : degree p = ⊥ := by
rw [Subsingleton.elim p 0, degree_zero]
#align polynomial.degree_of_subsingleton Polynomial.degree_of_subsingleton
@[nontriviality]
theorem natDegree_of_subsingleton [Subsingleton R] : natDegree p = 0 := by
rw [Subsingleton.elim p 0, natDegree_zero]
#align polynomial.nat_degree_of_subsingleton Polynomial.natDegree_of_subsingleton
theorem degree_eq_natDegree (hp : p ≠ 0) : degree p = (natDegree p : WithBot ℕ) := by
let ⟨n, hn⟩ := not_forall.1 (mt Option.eq_none_iff_forall_not_mem.2 (mt degree_eq_bot.1 hp))
have hn : degree p = some n := Classical.not_not.1 hn
rw [natDegree, hn]; rfl
#align polynomial.degree_eq_nat_degree Polynomial.degree_eq_natDegree
theorem supDegree_eq_natDegree (p : R[X]) : p.toFinsupp.supDegree id = p.natDegree := by
obtain rfl|h := eq_or_ne p 0
· simp
apply WithBot.coe_injective
rw [← AddMonoidAlgebra.supDegree_withBot_some_comp, Function.comp_id, supDegree_eq_degree,
degree_eq_natDegree h, Nat.cast_withBot]
rwa [support_toFinsupp, nonempty_iff_ne_empty, Ne, support_eq_empty]
theorem degree_eq_iff_natDegree_eq {p : R[X]} {n : ℕ} (hp : p ≠ 0) :
p.degree = n ↔ p.natDegree = n := by rw [degree_eq_natDegree hp]; exact WithBot.coe_eq_coe
#align polynomial.degree_eq_iff_nat_degree_eq Polynomial.degree_eq_iff_natDegree_eq
theorem degree_eq_iff_natDegree_eq_of_pos {p : R[X]} {n : ℕ} (hn : 0 < n) :
p.degree = n ↔ p.natDegree = n := by
obtain rfl|h := eq_or_ne p 0
· simp [hn.ne]
· exact degree_eq_iff_natDegree_eq h
#align polynomial.degree_eq_iff_nat_degree_eq_of_pos Polynomial.degree_eq_iff_natDegree_eq_of_pos
| Mathlib/Algebra/Polynomial/Degree/Definitions.lean | 157 | 159 | theorem natDegree_eq_of_degree_eq_some {p : R[X]} {n : ℕ} (h : degree p = n) : natDegree p = n := by |
-- Porting note: `Nat.cast_withBot` is required.
rw [natDegree, h, Nat.cast_withBot, WithBot.unbot'_coe]
|
/-
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. -/
| Mathlib/MeasureTheory/Measure/Lebesgue/EqHaar.lean | 179 | 203 | 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
|
/-
Copyright (c) 2021 Yaël Dillies. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Eric Wieser
-/
import Mathlib.Algebra.Order.Module.OrderedSMul
import Mathlib.Algebra.Order.Module.Pointwise
import Mathlib.Data.Real.Archimedean
#align_import data.real.pointwise from "leanprover-community/mathlib"@"dde670c9a3f503647fd5bfdf1037bad526d3397a"
/-!
# Pointwise operations on sets of reals
This file relates `sInf (a • s)`/`sSup (a • s)` with `a • sInf s`/`a • sSup s` for `s : Set ℝ`.
From these, it relates `⨅ i, a • f i` / `⨆ i, a • f i` with `a • (⨅ i, f i)` / `a • (⨆ i, f i)`,
and provides lemmas about distributing `*` over `⨅` and `⨆`.
# TODO
This is true more generally for conditionally complete linear order whose default value is `0`. We
don't have those yet.
-/
open Set
open Pointwise
variable {ι : Sort*} {α : Type*} [LinearOrderedField α]
section MulActionWithZero
variable [MulActionWithZero α ℝ] [OrderedSMul α ℝ] {a : α}
theorem Real.sInf_smul_of_nonneg (ha : 0 ≤ a) (s : Set ℝ) : sInf (a • s) = a • sInf s := by
obtain rfl | hs := s.eq_empty_or_nonempty
· rw [smul_set_empty, Real.sInf_empty, smul_zero]
obtain rfl | ha' := ha.eq_or_lt
· rw [zero_smul_set hs, zero_smul]
exact csInf_singleton 0
by_cases h : BddBelow s
· exact ((OrderIso.smulRight ha').map_csInf' hs h).symm
· rw [Real.sInf_of_not_bddBelow (mt (bddBelow_smul_iff_of_pos ha').1 h),
Real.sInf_of_not_bddBelow h, smul_zero]
#align real.Inf_smul_of_nonneg Real.sInf_smul_of_nonneg
theorem Real.smul_iInf_of_nonneg (ha : 0 ≤ a) (f : ι → ℝ) : (a • ⨅ i, f i) = ⨅ i, a • f i :=
(Real.sInf_smul_of_nonneg ha _).symm.trans <| congr_arg sInf <| (range_comp _ _).symm
#align real.smul_infi_of_nonneg Real.smul_iInf_of_nonneg
| Mathlib/Data/Real/Pointwise.lean | 53 | 62 | theorem Real.sSup_smul_of_nonneg (ha : 0 ≤ a) (s : Set ℝ) : sSup (a • s) = a • sSup s := by |
obtain rfl | hs := s.eq_empty_or_nonempty
· rw [smul_set_empty, Real.sSup_empty, smul_zero]
obtain rfl | ha' := ha.eq_or_lt
· rw [zero_smul_set hs, zero_smul]
exact csSup_singleton 0
by_cases h : BddAbove s
· exact ((OrderIso.smulRight ha').map_csSup' hs h).symm
· rw [Real.sSup_of_not_bddAbove (mt (bddAbove_smul_iff_of_pos ha').1 h),
Real.sSup_of_not_bddAbove h, smul_zero]
|
/-
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.Analysis.SpecialFunctions.Trigonometric.Arctan
import Mathlib.Geometry.Euclidean.Angle.Unoriented.Affine
#align_import geometry.euclidean.angle.unoriented.right_angle from "leanprover-community/mathlib"@"46b633fd842bef9469441c0209906f6dddd2b4f5"
/-!
# Right-angled triangles
This file proves basic geometrical results about distances and angles in (possibly degenerate)
right-angled triangles in real inner product spaces and Euclidean affine spaces.
## Implementation notes
Results in this file are generally given in a form with only those non-degeneracy conditions
needed for the particular result, rather than requiring affine independence of the points of a
triangle unnecessarily.
## References
* https://en.wikipedia.org/wiki/Pythagorean_theorem
-/
noncomputable section
open scoped EuclideanGeometry
open scoped Real
open scoped RealInnerProductSpace
namespace InnerProductGeometry
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℝ V]
/-- Pythagorean theorem, if-and-only-if vector angle form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two (x y : V) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ ↔ angle x y = π / 2 := by
rw [norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero]
exact inner_eq_zero_iff_angle_eq_pi_div_two x y
#align inner_product_geometry.norm_add_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two InnerProductGeometry.norm_add_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two
/-- Pythagorean theorem, vector angle form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq' (x y : V) (h : angle x y = π / 2) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ :=
(norm_add_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two x y).2 h
#align inner_product_geometry.norm_add_sq_eq_norm_sq_add_norm_sq' InnerProductGeometry.norm_add_sq_eq_norm_sq_add_norm_sq'
/-- Pythagorean theorem, subtracting vectors, if-and-only-if vector angle form. -/
theorem norm_sub_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two (x y : V) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ ↔ angle x y = π / 2 := by
rw [norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero]
exact inner_eq_zero_iff_angle_eq_pi_div_two x y
#align inner_product_geometry.norm_sub_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two InnerProductGeometry.norm_sub_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two
/-- Pythagorean theorem, subtracting vectors, vector angle form. -/
theorem norm_sub_sq_eq_norm_sq_add_norm_sq' (x y : V) (h : angle x y = π / 2) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ :=
(norm_sub_sq_eq_norm_sq_add_norm_sq_iff_angle_eq_pi_div_two x y).2 h
#align inner_product_geometry.norm_sub_sq_eq_norm_sq_add_norm_sq' InnerProductGeometry.norm_sub_sq_eq_norm_sq_add_norm_sq'
/-- An angle in a right-angled triangle expressed using `arccos`. -/
theorem angle_add_eq_arccos_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
angle x (x + y) = Real.arccos (‖x‖ / ‖x + y‖) := by
rw [angle, inner_add_right, h, add_zero, real_inner_self_eq_norm_mul_norm]
by_cases hx : ‖x‖ = 0; · simp [hx]
rw [div_mul_eq_div_div, mul_self_div_self]
#align inner_product_geometry.angle_add_eq_arccos_of_inner_eq_zero InnerProductGeometry.angle_add_eq_arccos_of_inner_eq_zero
/-- An angle in a right-angled triangle expressed using `arcsin`. -/
theorem angle_add_eq_arcsin_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0 ∨ y ≠ 0) :
angle x (x + y) = Real.arcsin (‖y‖ / ‖x + y‖) := by
have hxy : ‖x + y‖ ^ 2 ≠ 0 := by
rw [pow_two, norm_add_sq_eq_norm_sq_add_norm_sq_real h, ne_comm]
refine ne_of_lt ?_
rcases h0 with (h0 | h0)
· exact
Left.add_pos_of_pos_of_nonneg (mul_self_pos.2 (norm_ne_zero_iff.2 h0)) (mul_self_nonneg _)
· exact
Left.add_pos_of_nonneg_of_pos (mul_self_nonneg _) (mul_self_pos.2 (norm_ne_zero_iff.2 h0))
rw [angle_add_eq_arccos_of_inner_eq_zero h,
Real.arccos_eq_arcsin (div_nonneg (norm_nonneg _) (norm_nonneg _)), div_pow, one_sub_div hxy]
nth_rw 1 [pow_two]
rw [norm_add_sq_eq_norm_sq_add_norm_sq_real h, pow_two, add_sub_cancel_left, ← pow_two, ← div_pow,
Real.sqrt_sq (div_nonneg (norm_nonneg _) (norm_nonneg _))]
#align inner_product_geometry.angle_add_eq_arcsin_of_inner_eq_zero InnerProductGeometry.angle_add_eq_arcsin_of_inner_eq_zero
/-- An angle in a right-angled triangle expressed using `arctan`. -/
theorem angle_add_eq_arctan_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0) :
angle x (x + y) = Real.arctan (‖y‖ / ‖x‖) := by
rw [angle_add_eq_arcsin_of_inner_eq_zero h (Or.inl h0), Real.arctan_eq_arcsin, ←
div_mul_eq_div_div, norm_add_eq_sqrt_iff_real_inner_eq_zero.2 h]
nth_rw 3 [← Real.sqrt_sq (norm_nonneg x)]
rw_mod_cast [← Real.sqrt_mul (sq_nonneg _), div_pow, pow_two, pow_two, mul_add, mul_one, mul_div,
mul_comm (‖x‖ * ‖x‖), ← mul_div, div_self (mul_self_pos.2 (norm_ne_zero_iff.2 h0)).ne', mul_one]
#align inner_product_geometry.angle_add_eq_arctan_of_inner_eq_zero InnerProductGeometry.angle_add_eq_arctan_of_inner_eq_zero
/-- An angle in a non-degenerate right-angled triangle is positive. -/
theorem angle_add_pos_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x = 0 ∨ y ≠ 0) :
0 < angle x (x + y) := by
rw [angle_add_eq_arccos_of_inner_eq_zero h, Real.arccos_pos,
norm_add_eq_sqrt_iff_real_inner_eq_zero.2 h]
by_cases hx : x = 0; · simp [hx]
rw [div_lt_one (Real.sqrt_pos.2 (Left.add_pos_of_pos_of_nonneg (mul_self_pos.2
(norm_ne_zero_iff.2 hx)) (mul_self_nonneg _))), Real.lt_sqrt (norm_nonneg _), pow_two]
simpa [hx] using h0
#align inner_product_geometry.angle_add_pos_of_inner_eq_zero InnerProductGeometry.angle_add_pos_of_inner_eq_zero
/-- An angle in a right-angled triangle is at most `π / 2`. -/
theorem angle_add_le_pi_div_two_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
angle x (x + y) ≤ π / 2 := by
rw [angle_add_eq_arccos_of_inner_eq_zero h, Real.arccos_le_pi_div_two]
exact div_nonneg (norm_nonneg _) (norm_nonneg _)
#align inner_product_geometry.angle_add_le_pi_div_two_of_inner_eq_zero InnerProductGeometry.angle_add_le_pi_div_two_of_inner_eq_zero
/-- An angle in a non-degenerate right-angled triangle is less than `π / 2`. -/
theorem angle_add_lt_pi_div_two_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0) :
angle x (x + y) < π / 2 := by
rw [angle_add_eq_arccos_of_inner_eq_zero h, Real.arccos_lt_pi_div_two,
norm_add_eq_sqrt_iff_real_inner_eq_zero.2 h]
exact div_pos (norm_pos_iff.2 h0) (Real.sqrt_pos.2 (Left.add_pos_of_pos_of_nonneg
(mul_self_pos.2 (norm_ne_zero_iff.2 h0)) (mul_self_nonneg _)))
#align inner_product_geometry.angle_add_lt_pi_div_two_of_inner_eq_zero InnerProductGeometry.angle_add_lt_pi_div_two_of_inner_eq_zero
/-- The cosine of an angle in a right-angled triangle as a ratio of sides. -/
theorem cos_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
Real.cos (angle x (x + y)) = ‖x‖ / ‖x + y‖ := by
rw [angle_add_eq_arccos_of_inner_eq_zero h,
Real.cos_arccos (le_trans (by norm_num) (div_nonneg (norm_nonneg _) (norm_nonneg _)))
(div_le_one_of_le _ (norm_nonneg _))]
rw [mul_self_le_mul_self_iff (norm_nonneg _) (norm_nonneg _),
norm_add_sq_eq_norm_sq_add_norm_sq_real h]
exact le_add_of_nonneg_right (mul_self_nonneg _)
#align inner_product_geometry.cos_angle_add_of_inner_eq_zero InnerProductGeometry.cos_angle_add_of_inner_eq_zero
/-- The sine of an angle in a right-angled triangle as a ratio of sides. -/
theorem sin_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0 ∨ y ≠ 0) :
Real.sin (angle x (x + y)) = ‖y‖ / ‖x + y‖ := by
rw [angle_add_eq_arcsin_of_inner_eq_zero h h0,
Real.sin_arcsin (le_trans (by norm_num) (div_nonneg (norm_nonneg _) (norm_nonneg _)))
(div_le_one_of_le _ (norm_nonneg _))]
rw [mul_self_le_mul_self_iff (norm_nonneg _) (norm_nonneg _),
norm_add_sq_eq_norm_sq_add_norm_sq_real h]
exact le_add_of_nonneg_left (mul_self_nonneg _)
#align inner_product_geometry.sin_angle_add_of_inner_eq_zero InnerProductGeometry.sin_angle_add_of_inner_eq_zero
/-- The tangent of an angle in a right-angled triangle as a ratio of sides. -/
theorem tan_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
Real.tan (angle x (x + y)) = ‖y‖ / ‖x‖ := by
by_cases h0 : x = 0; · simp [h0]
rw [angle_add_eq_arctan_of_inner_eq_zero h h0, Real.tan_arctan]
#align inner_product_geometry.tan_angle_add_of_inner_eq_zero InnerProductGeometry.tan_angle_add_of_inner_eq_zero
/-- The cosine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
adjacent side. -/
theorem cos_angle_add_mul_norm_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
Real.cos (angle x (x + y)) * ‖x + y‖ = ‖x‖ := by
rw [cos_angle_add_of_inner_eq_zero h]
by_cases hxy : ‖x + y‖ = 0
· have h' := norm_add_sq_eq_norm_sq_add_norm_sq_real h
rw [hxy, zero_mul, eq_comm,
add_eq_zero_iff' (mul_self_nonneg ‖x‖) (mul_self_nonneg ‖y‖), mul_self_eq_zero] at h'
simp [h'.1]
· exact div_mul_cancel₀ _ hxy
#align inner_product_geometry.cos_angle_add_mul_norm_of_inner_eq_zero InnerProductGeometry.cos_angle_add_mul_norm_of_inner_eq_zero
/-- The sine of an angle in a right-angled triangle multiplied by the hypotenuse equals the
opposite side. -/
theorem sin_angle_add_mul_norm_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
Real.sin (angle x (x + y)) * ‖x + y‖ = ‖y‖ := by
by_cases h0 : x = 0 ∧ y = 0; · simp [h0]
rw [not_and_or] at h0
rw [sin_angle_add_of_inner_eq_zero h h0, div_mul_cancel₀]
rw [← mul_self_ne_zero, norm_add_sq_eq_norm_sq_add_norm_sq_real h]
refine (ne_of_lt ?_).symm
rcases h0 with (h0 | h0)
· exact Left.add_pos_of_pos_of_nonneg (mul_self_pos.2 (norm_ne_zero_iff.2 h0)) (mul_self_nonneg _)
· exact Left.add_pos_of_nonneg_of_pos (mul_self_nonneg _) (mul_self_pos.2 (norm_ne_zero_iff.2 h0))
#align inner_product_geometry.sin_angle_add_mul_norm_of_inner_eq_zero InnerProductGeometry.sin_angle_add_mul_norm_of_inner_eq_zero
/-- The tangent of an angle in a right-angled triangle multiplied by the adjacent side equals
the opposite side. -/
theorem tan_angle_add_mul_norm_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0 ∨ y = 0) :
Real.tan (angle x (x + y)) * ‖x‖ = ‖y‖ := by
rw [tan_angle_add_of_inner_eq_zero h]
rcases h0 with (h0 | h0) <;> simp [h0]
#align inner_product_geometry.tan_angle_add_mul_norm_of_inner_eq_zero InnerProductGeometry.tan_angle_add_mul_norm_of_inner_eq_zero
/-- A side of a right-angled triangle divided by the cosine of the adjacent angle equals the
hypotenuse. -/
theorem norm_div_cos_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0 ∨ y = 0) :
‖x‖ / Real.cos (angle x (x + y)) = ‖x + y‖ := by
rw [cos_angle_add_of_inner_eq_zero h]
rcases h0 with (h0 | h0)
· rw [div_div_eq_mul_div, mul_comm, div_eq_mul_inv, mul_inv_cancel_right₀ (norm_ne_zero_iff.2 h0)]
· simp [h0]
#align inner_product_geometry.norm_div_cos_angle_add_of_inner_eq_zero InnerProductGeometry.norm_div_cos_angle_add_of_inner_eq_zero
/-- A side of a right-angled triangle divided by the sine of the opposite angle equals the
hypotenuse. -/
theorem norm_div_sin_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x = 0 ∨ y ≠ 0) :
‖y‖ / Real.sin (angle x (x + y)) = ‖x + y‖ := by
rcases h0 with (h0 | h0); · simp [h0]
rw [sin_angle_add_of_inner_eq_zero h (Or.inr h0), div_div_eq_mul_div, mul_comm, div_eq_mul_inv,
mul_inv_cancel_right₀ (norm_ne_zero_iff.2 h0)]
#align inner_product_geometry.norm_div_sin_angle_add_of_inner_eq_zero InnerProductGeometry.norm_div_sin_angle_add_of_inner_eq_zero
/-- A side of a right-angled triangle divided by the tangent of the opposite angle equals the
adjacent side. -/
theorem norm_div_tan_angle_add_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x = 0 ∨ y ≠ 0) :
‖y‖ / Real.tan (angle x (x + y)) = ‖x‖ := by
rw [tan_angle_add_of_inner_eq_zero h]
rcases h0 with (h0 | h0)
· simp [h0]
· rw [div_div_eq_mul_div, mul_comm, div_eq_mul_inv, mul_inv_cancel_right₀ (norm_ne_zero_iff.2 h0)]
#align inner_product_geometry.norm_div_tan_angle_add_of_inner_eq_zero InnerProductGeometry.norm_div_tan_angle_add_of_inner_eq_zero
/-- An angle in a right-angled triangle expressed using `arccos`, version subtracting vectors. -/
theorem angle_sub_eq_arccos_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) :
angle x (x - y) = Real.arccos (‖x‖ / ‖x - y‖) := by
rw [← neg_eq_zero, ← inner_neg_right] at h
rw [sub_eq_add_neg, angle_add_eq_arccos_of_inner_eq_zero h]
#align inner_product_geometry.angle_sub_eq_arccos_of_inner_eq_zero InnerProductGeometry.angle_sub_eq_arccos_of_inner_eq_zero
/-- An angle in a right-angled triangle expressed using `arcsin`, version subtracting vectors. -/
| Mathlib/Geometry/Euclidean/Angle/Unoriented/RightAngle.lean | 232 | 236 | theorem angle_sub_eq_arcsin_of_inner_eq_zero {x y : V} (h : ⟪x, y⟫ = 0) (h0 : x ≠ 0 ∨ y ≠ 0) :
angle x (x - y) = Real.arcsin (‖y‖ / ‖x - y‖) := by |
rw [← neg_eq_zero, ← inner_neg_right] at h
rw [or_comm, ← neg_ne_zero, or_comm] at h0
rw [sub_eq_add_neg, angle_add_eq_arcsin_of_inner_eq_zero h h0, norm_neg]
|
/-
Copyright (c) 2022 Alexander Bentkamp. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alexander Bentkamp, Eric Wieser, Jeremy Avigad, Johan Commelin
-/
import Mathlib.Data.Matrix.Invertible
import Mathlib.LinearAlgebra.Matrix.NonsingularInverse
import Mathlib.LinearAlgebra.Matrix.PosDef
#align_import linear_algebra.matrix.schur_complement from "leanprover-community/mathlib"@"a176cb1219e300e85793d44583dede42377b51af"
/-! # 2×2 block matrices and the Schur complement
This file proves properties of 2×2 block matrices `[A B; C D]` that relate to the Schur complement
`D - C*A⁻¹*B`.
Some of the results here generalize to 2×2 matrices in a category, rather than just a ring. A few
results in this direction can be found in the file `CateogryTheory.Preadditive.Biproducts`,
especially the declarations `CategoryTheory.Biprod.gaussian` and `CategoryTheory.Biprod.isoElim`.
Compare with `Matrix.invertibleOfFromBlocks₁₁Invertible`.
## Main results
* `Matrix.det_fromBlocks₁₁`, `Matrix.det_fromBlocks₂₂`: determinant of a block matrix in terms of
the Schur complement.
* `Matrix.invOf_fromBlocks_zero₂₁_eq`, `Matrix.invOf_fromBlocks_zero₁₂_eq`: the inverse of a
block triangular matrix.
* `Matrix.isUnit_fromBlocks_zero₂₁`, `Matrix.isUnit_fromBlocks_zero₁₂`: invertibility of a
block triangular matrix.
* `Matrix.det_one_add_mul_comm`: the **Weinstein–Aronszajn identity**.
* `Matrix.PosSemidef.fromBlocks₁₁` and `Matrix.PosSemidef.fromBlocks₂₂`: If a matrix `A` is
positive definite, then `[A B; Bᴴ D]` is postive semidefinite if and only if `D - Bᴴ A⁻¹ B` is
postive semidefinite.
-/
variable {l m n α : Type*}
namespace Matrix
open scoped Matrix
section CommRing
variable [Fintype l] [Fintype m] [Fintype n]
variable [DecidableEq l] [DecidableEq m] [DecidableEq n]
variable [CommRing α]
/-- LDU decomposition of a block matrix with an invertible top-left corner, using the
Schur complement. -/
theorem fromBlocks_eq_of_invertible₁₁ (A : Matrix m m α) (B : Matrix m n α) (C : Matrix l m α)
(D : Matrix l n α) [Invertible A] :
fromBlocks A B C D =
fromBlocks 1 0 (C * ⅟ A) 1 * fromBlocks A 0 0 (D - C * ⅟ A * B) *
fromBlocks 1 (⅟ A * B) 0 1 := by
simp only [fromBlocks_multiply, Matrix.mul_zero, Matrix.zero_mul, add_zero, zero_add,
Matrix.one_mul, Matrix.mul_one, invOf_mul_self, Matrix.mul_invOf_self_assoc,
Matrix.mul_invOf_mul_self_cancel, Matrix.mul_assoc, add_sub_cancel]
#align matrix.from_blocks_eq_of_invertible₁₁ Matrix.fromBlocks_eq_of_invertible₁₁
/-- LDU decomposition of a block matrix with an invertible bottom-right corner, using the
Schur complement. -/
theorem fromBlocks_eq_of_invertible₂₂ (A : Matrix l m α) (B : Matrix l n α) (C : Matrix n m α)
(D : Matrix n n α) [Invertible D] :
fromBlocks A B C D =
fromBlocks 1 (B * ⅟ D) 0 1 * fromBlocks (A - B * ⅟ D * C) 0 0 D *
fromBlocks 1 0 (⅟ D * C) 1 :=
(Matrix.reindex (Equiv.sumComm _ _) (Equiv.sumComm _ _)).injective <| by
simpa [reindex_apply, Equiv.sumComm_symm, ← submatrix_mul_equiv _ _ _ (Equiv.sumComm n m), ←
submatrix_mul_equiv _ _ _ (Equiv.sumComm n l), Equiv.sumComm_apply,
fromBlocks_submatrix_sum_swap_sum_swap] using fromBlocks_eq_of_invertible₁₁ D C B A
#align matrix.from_blocks_eq_of_invertible₂₂ Matrix.fromBlocks_eq_of_invertible₂₂
section Triangular
/-! #### Block triangular matrices -/
/-- An upper-block-triangular matrix is invertible if its diagonal is. -/
def fromBlocksZero₂₁Invertible (A : Matrix m m α) (B : Matrix m n α) (D : Matrix n n α)
[Invertible A] [Invertible D] : Invertible (fromBlocks A B 0 D) :=
invertibleOfLeftInverse _ (fromBlocks (⅟ A) (-(⅟ A * B * ⅟ D)) 0 (⅟ D)) <| by
simp_rw [fromBlocks_multiply, Matrix.mul_zero, Matrix.zero_mul, zero_add, add_zero,
Matrix.neg_mul, invOf_mul_self, Matrix.mul_invOf_mul_self_cancel, add_right_neg,
fromBlocks_one]
#align matrix.from_blocks_zero₂₁_invertible Matrix.fromBlocksZero₂₁Invertible
/-- A lower-block-triangular matrix is invertible if its diagonal is. -/
def fromBlocksZero₁₂Invertible (A : Matrix m m α) (C : Matrix n m α) (D : Matrix n n α)
[Invertible A] [Invertible D] : Invertible (fromBlocks A 0 C D) :=
invertibleOfLeftInverse _
(fromBlocks (⅟ A) 0 (-(⅟ D * C * ⅟ A))
(⅟ D)) <| by -- a symmetry argument is more work than just copying the proof
simp_rw [fromBlocks_multiply, Matrix.mul_zero, Matrix.zero_mul, zero_add, add_zero,
Matrix.neg_mul, invOf_mul_self, Matrix.mul_invOf_mul_self_cancel, add_left_neg,
fromBlocks_one]
#align matrix.from_blocks_zero₁₂_invertible Matrix.fromBlocksZero₁₂Invertible
theorem invOf_fromBlocks_zero₂₁_eq (A : Matrix m m α) (B : Matrix m n α) (D : Matrix n n α)
[Invertible A] [Invertible D] [Invertible (fromBlocks A B 0 D)] :
⅟ (fromBlocks A B 0 D) = fromBlocks (⅟ A) (-(⅟ A * B * ⅟ D)) 0 (⅟ D) := by
letI := fromBlocksZero₂₁Invertible A B D
convert (rfl : ⅟ (fromBlocks A B 0 D) = _)
#align matrix.inv_of_from_blocks_zero₂₁_eq Matrix.invOf_fromBlocks_zero₂₁_eq
| Mathlib/LinearAlgebra/Matrix/SchurComplement.lean | 107 | 111 | theorem invOf_fromBlocks_zero₁₂_eq (A : Matrix m m α) (C : Matrix n m α) (D : Matrix n n α)
[Invertible A] [Invertible D] [Invertible (fromBlocks A 0 C D)] :
⅟ (fromBlocks A 0 C D) = fromBlocks (⅟ A) 0 (-(⅟ D * C * ⅟ A)) (⅟ D) := by |
letI := fromBlocksZero₁₂Invertible A C D
convert (rfl : ⅟ (fromBlocks A 0 C D) = _)
|
/-
Copyright (c) 2020 Jean Lo. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jean Lo
-/
import Mathlib.Topology.Algebra.Group.Basic
import Mathlib.Logic.Function.Iterate
#align_import dynamics.flow from "leanprover-community/mathlib"@"717c073262cd9d59b1a1dcda7e8ab570c5b63370"
/-!
# Flows and invariant sets
This file defines a flow on a topological space `α` by a topological
monoid `τ` as a continuous monoid-action of `τ` on `α`. Anticipating the
cases where `τ` is one of `ℕ`, `ℤ`, `ℝ⁺`, or `ℝ`, we use additive
notation for the monoids, though the definition does not require
commutativity.
A subset `s` of `α` is invariant under a family of maps `ϕₜ : α → α`
if `ϕₜ s ⊆ s` for all `t`. In many cases `ϕ` will be a flow on
`α`. For the cases where `ϕ` is a flow by an ordered (additive,
commutative) monoid, we additionally define forward invariance, where
`t` ranges over those elements which are nonnegative.
Additionally, we define such constructions as the restriction of a
flow onto an invariant subset, and the time-reversal of a flow by a
group.
-/
open Set Function Filter
/-!
### Invariant sets
-/
section Invariant
variable {τ : Type*} {α : Type*}
/-- A set `s ⊆ α` is invariant under `ϕ : τ → α → α` if
`ϕ t s ⊆ s` for all `t` in `τ`. -/
def IsInvariant (ϕ : τ → α → α) (s : Set α) : Prop :=
∀ t, MapsTo (ϕ t) s s
#align is_invariant IsInvariant
variable (ϕ : τ → α → α) (s : Set α)
| Mathlib/Dynamics/Flow.lean | 49 | 50 | theorem isInvariant_iff_image : IsInvariant ϕ s ↔ ∀ t, ϕ t '' s ⊆ s := by |
simp_rw [IsInvariant, mapsTo']
|
/-
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.Algebra.GCDMonoid.Basic
import Mathlib.Data.Multiset.FinsetOps
import Mathlib.Data.Multiset.Fold
#align_import algebra.gcd_monoid.multiset from "leanprover-community/mathlib"@"f694c7dead66f5d4c80f446c796a5aad14707f0e"
/-!
# GCD and LCM operations on multisets
## Main definitions
- `Multiset.gcd` - the greatest common denominator of a `Multiset` of elements of a `GCDMonoid`
- `Multiset.lcm` - the least common multiple of a `Multiset` of elements of a `GCDMonoid`
## Implementation notes
TODO: simplify with a tactic and `Data.Multiset.Lattice`
## Tags
multiset, gcd
-/
namespace Multiset
variable {α : Type*} [CancelCommMonoidWithZero α] [NormalizedGCDMonoid α]
/-! ### LCM -/
section lcm
/-- Least common multiple of a multiset -/
def lcm (s : Multiset α) : α :=
s.fold GCDMonoid.lcm 1
#align multiset.lcm Multiset.lcm
@[simp]
theorem lcm_zero : (0 : Multiset α).lcm = 1 :=
fold_zero _ _
#align multiset.lcm_zero Multiset.lcm_zero
@[simp]
theorem lcm_cons (a : α) (s : Multiset α) : (a ::ₘ s).lcm = GCDMonoid.lcm a s.lcm :=
fold_cons_left _ _ _ _
#align multiset.lcm_cons Multiset.lcm_cons
@[simp]
theorem lcm_singleton {a : α} : ({a} : Multiset α).lcm = normalize a :=
(fold_singleton _ _ _).trans <| lcm_one_right _
#align multiset.lcm_singleton Multiset.lcm_singleton
@[simp]
theorem lcm_add (s₁ s₂ : Multiset α) : (s₁ + s₂).lcm = GCDMonoid.lcm s₁.lcm s₂.lcm :=
Eq.trans (by simp [lcm]) (fold_add _ _ _ _ _)
#align multiset.lcm_add Multiset.lcm_add
theorem lcm_dvd {s : Multiset α} {a : α} : s.lcm ∣ a ↔ ∀ b ∈ s, b ∣ a :=
Multiset.induction_on s (by simp)
(by simp (config := { contextual := true }) [or_imp, forall_and, lcm_dvd_iff])
#align multiset.lcm_dvd Multiset.lcm_dvd
theorem dvd_lcm {s : Multiset α} {a : α} (h : a ∈ s) : a ∣ s.lcm :=
lcm_dvd.1 dvd_rfl _ h
#align multiset.dvd_lcm Multiset.dvd_lcm
theorem lcm_mono {s₁ s₂ : Multiset α} (h : s₁ ⊆ s₂) : s₁.lcm ∣ s₂.lcm :=
lcm_dvd.2 fun _ hb ↦ dvd_lcm (h hb)
#align multiset.lcm_mono Multiset.lcm_mono
/- Porting note: Following `Algebra.GCDMonoid.Basic`'s version of `normalize_gcd`, I'm giving
this lower priority to avoid linter complaints about simp-normal form -/
/- Porting note: Mathport seems to be replacing `Multiset.induction_on s $` with
`(Multiset.induction_on s)`, when it should be `Multiset.induction_on s <|`. -/
@[simp 1100]
theorem normalize_lcm (s : Multiset α) : normalize s.lcm = s.lcm :=
Multiset.induction_on s (by simp) fun a s _ ↦ by simp
#align multiset.normalize_lcm Multiset.normalize_lcm
@[simp]
nonrec theorem lcm_eq_zero_iff [Nontrivial α] (s : Multiset α) : s.lcm = 0 ↔ (0 : α) ∈ s := by
induction' s using Multiset.induction_on with a s ihs
· simp only [lcm_zero, one_ne_zero, not_mem_zero]
· simp only [mem_cons, lcm_cons, lcm_eq_zero_iff, ihs, @eq_comm _ a]
#align multiset.lcm_eq_zero_iff Multiset.lcm_eq_zero_iff
variable [DecidableEq α]
@[simp]
theorem lcm_dedup (s : Multiset α) : (dedup s).lcm = s.lcm :=
Multiset.induction_on s (by simp) fun a s IH ↦ by
by_cases h : a ∈ s <;> simp [IH, h]
unfold lcm
rw [← cons_erase h, fold_cons_left, ← lcm_assoc, lcm_same]
apply lcm_eq_of_associated_left (associated_normalize _)
#align multiset.lcm_dedup Multiset.lcm_dedup
@[simp]
theorem lcm_ndunion (s₁ s₂ : Multiset α) : (ndunion s₁ s₂).lcm = GCDMonoid.lcm s₁.lcm s₂.lcm := by
rw [← lcm_dedup, dedup_ext.2, lcm_dedup, lcm_add]
simp
#align multiset.lcm_ndunion Multiset.lcm_ndunion
@[simp]
theorem lcm_union (s₁ s₂ : Multiset α) : (s₁ ∪ s₂).lcm = GCDMonoid.lcm s₁.lcm s₂.lcm := by
rw [← lcm_dedup, dedup_ext.2, lcm_dedup, lcm_add]
simp
#align multiset.lcm_union Multiset.lcm_union
@[simp]
| Mathlib/Algebra/GCDMonoid/Multiset.lean | 116 | 118 | theorem lcm_ndinsert (a : α) (s : Multiset α) : (ndinsert a s).lcm = GCDMonoid.lcm a s.lcm := by |
rw [← lcm_dedup, dedup_ext.2, lcm_dedup, lcm_cons]
simp
|
/-
Copyright (c) 2021 Martin Zinkevich. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Martin Zinkevich, Rémy Degenne
-/
import Mathlib.Logic.Encodable.Lattice
import Mathlib.MeasureTheory.MeasurableSpace.Defs
#align_import measure_theory.pi_system from "leanprover-community/mathlib"@"98e83c3d541c77cdb7da20d79611a780ff8e7d90"
/-!
# Induction principles for measurable sets, related to π-systems and λ-systems.
## Main statements
* The main theorem of this file is Dynkin's π-λ theorem, which appears
here as an induction principle `induction_on_inter`. Suppose `s` is a
collection of subsets of `α` such that the intersection of two members
of `s` belongs to `s` whenever it is nonempty. Let `m` be the σ-algebra
generated by `s`. In order to check that a predicate `C` holds on every
member of `m`, it suffices to check that `C` holds on the members of `s` and
that `C` is preserved by complementation and *disjoint* countable
unions.
* The proof of this theorem relies on the notion of `IsPiSystem`, i.e., a collection of sets
which is closed under binary non-empty intersections. Note that this is a small variation around
the usual notion in the literature, which often requires that a π-system is non-empty, and closed
also under disjoint intersections. This variation turns out to be convenient for the
formalization.
* The proof of Dynkin's π-λ theorem also requires the notion of `DynkinSystem`, i.e., a collection
of sets which contains the empty set, is closed under complementation and under countable union
of pairwise disjoint sets. The disjointness condition is the only difference with `σ`-algebras.
* `generatePiSystem g` gives the minimal π-system containing `g`.
This can be considered a Galois insertion into both measurable spaces and sets.
* `generateFrom_generatePiSystem_eq` proves that if you start from a collection of sets `g`,
take the generated π-system, and then the generated σ-algebra, you get the same result as
the σ-algebra generated from `g`. This is useful because there are connections between
independent sets that are π-systems and the generated independent spaces.
* `mem_generatePiSystem_iUnion_elim` and `mem_generatePiSystem_iUnion_elim'` show that any
element of the π-system generated from the union of a set of π-systems can be
represented as the intersection of a finite number of elements from these sets.
* `piiUnionInter` defines a new π-system from a family of π-systems `π : ι → Set (Set α)` and a
set of indices `S : Set ι`. `piiUnionInter π S` is the set of sets that can be written
as `⋂ x ∈ t, f x` for some finset `t ∈ S` and sets `f x ∈ π x`.
## Implementation details
* `IsPiSystem` is a predicate, not a type. Thus, we don't explicitly define the galois
insertion, nor do we define a complete lattice. In theory, we could define a complete
lattice and galois insertion on the subtype corresponding to `IsPiSystem`.
-/
open MeasurableSpace Set
open scoped Classical
open MeasureTheory
/-- A π-system is a collection of subsets of `α` that is closed under binary intersection of
non-disjoint sets. Usually it is also required that the collection is nonempty, but we don't do
that here. -/
def IsPiSystem {α} (C : Set (Set α)) : Prop :=
∀ᵉ (s ∈ C) (t ∈ C), (s ∩ t : Set α).Nonempty → s ∩ t ∈ C
#align is_pi_system IsPiSystem
namespace MeasurableSpace
theorem isPiSystem_measurableSet {α : Type*} [MeasurableSpace α] :
IsPiSystem { s : Set α | MeasurableSet s } := fun _ hs _ ht _ => hs.inter ht
#align measurable_space.is_pi_system_measurable_set MeasurableSpace.isPiSystem_measurableSet
end MeasurableSpace
theorem IsPiSystem.singleton {α} (S : Set α) : IsPiSystem ({S} : Set (Set α)) := by
intro s h_s t h_t _
rw [Set.mem_singleton_iff.1 h_s, Set.mem_singleton_iff.1 h_t, Set.inter_self,
Set.mem_singleton_iff]
#align is_pi_system.singleton IsPiSystem.singleton
theorem IsPiSystem.insert_empty {α} {S : Set (Set α)} (h_pi : IsPiSystem S) :
IsPiSystem (insert ∅ S) := by
intro s hs t ht hst
cases' hs with hs hs
· simp [hs]
· cases' ht with ht ht
· simp [ht]
· exact Set.mem_insert_of_mem _ (h_pi s hs t ht hst)
#align is_pi_system.insert_empty IsPiSystem.insert_empty
| Mathlib/MeasureTheory/PiSystem.lean | 95 | 102 | theorem IsPiSystem.insert_univ {α} {S : Set (Set α)} (h_pi : IsPiSystem S) :
IsPiSystem (insert Set.univ S) := by |
intro s hs t ht hst
cases' hs with hs hs
· cases' ht with ht ht <;> simp [hs, ht]
· cases' ht with ht ht
· simp [hs, ht]
· exact Set.mem_insert_of_mem _ (h_pi s hs t ht hst)
|
/-
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]
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]
#align finset.ssubset_singleton_iff Finset.ssubset_singleton_iff
theorem eq_empty_of_ssubset_singleton {s : Finset α} {x : α} (hs : s ⊂ {x}) : s = ∅ :=
ssubset_singleton_iff.1 hs
#align finset.eq_empty_of_ssubset_singleton Finset.eq_empty_of_ssubset_singleton
/-- A finset is nontrivial if it has at least two elements. -/
protected abbrev Nontrivial (s : Finset α) : Prop := (s : Set α).Nontrivial
#align finset.nontrivial Finset.Nontrivial
@[simp]
theorem not_nontrivial_empty : ¬ (∅ : Finset α).Nontrivial := by simp [Finset.Nontrivial]
#align finset.not_nontrivial_empty Finset.not_nontrivial_empty
@[simp]
theorem not_nontrivial_singleton : ¬ ({a} : Finset α).Nontrivial := by simp [Finset.Nontrivial]
#align finset.not_nontrivial_singleton Finset.not_nontrivial_singleton
theorem Nontrivial.ne_singleton (hs : s.Nontrivial) : s ≠ {a} := by
rintro rfl; exact not_nontrivial_singleton hs
#align finset.nontrivial.ne_singleton Finset.Nontrivial.ne_singleton
nonrec lemma Nontrivial.exists_ne (hs : s.Nontrivial) (a : α) : ∃ b ∈ s, b ≠ a := hs.exists_ne _
theorem eq_singleton_or_nontrivial (ha : a ∈ s) : s = {a} ∨ s.Nontrivial := by
rw [← coe_eq_singleton]; exact Set.eq_singleton_or_nontrivial ha
#align finset.eq_singleton_or_nontrivial Finset.eq_singleton_or_nontrivial
theorem nontrivial_iff_ne_singleton (ha : a ∈ s) : s.Nontrivial ↔ s ≠ {a} :=
⟨Nontrivial.ne_singleton, (eq_singleton_or_nontrivial ha).resolve_left⟩
#align finset.nontrivial_iff_ne_singleton Finset.nontrivial_iff_ne_singleton
theorem Nonempty.exists_eq_singleton_or_nontrivial : s.Nonempty → (∃ a, s = {a}) ∨ s.Nontrivial :=
fun ⟨a, ha⟩ => (eq_singleton_or_nontrivial ha).imp_left <| Exists.intro a
#align finset.nonempty.exists_eq_singleton_or_nontrivial Finset.Nonempty.exists_eq_singleton_or_nontrivial
instance instNontrivial [Nonempty α] : Nontrivial (Finset α) :=
‹Nonempty α›.elim fun a => ⟨⟨{a}, ∅, singleton_ne_empty _⟩⟩
#align finset.nontrivial' Finset.instNontrivial
instance [IsEmpty α] : Unique (Finset α) where
default := ∅
uniq _ := eq_empty_of_forall_not_mem isEmptyElim
instance (i : α) : Unique ({i} : Finset α) where
default := ⟨i, mem_singleton_self i⟩
uniq j := Subtype.ext <| mem_singleton.mp j.2
@[simp]
lemma default_singleton (i : α) : ((default : ({i} : Finset α)) : α) = i := rfl
end Singleton
/-! ### cons -/
section Cons
variable {s t : Finset α} {a b : α}
/-- `cons a s h` is the set `{a} ∪ s` containing `a` and the elements of `s`. It is the same as
`insert a s` when it is defined, but unlike `insert a s` it does not require `DecidableEq α`,
and the union is guaranteed to be disjoint. -/
def cons (a : α) (s : Finset α) (h : a ∉ s) : Finset α :=
⟨a ::ₘ s.1, nodup_cons.2 ⟨h, s.2⟩⟩
#align finset.cons Finset.cons
@[simp]
theorem mem_cons {h} : b ∈ s.cons a h ↔ b = a ∨ b ∈ s :=
Multiset.mem_cons
#align finset.mem_cons Finset.mem_cons
theorem mem_cons_of_mem {a b : α} {s : Finset α} {hb : b ∉ s} (ha : a ∈ s) : a ∈ cons b s hb :=
Multiset.mem_cons_of_mem ha
-- Porting note (#10618): @[simp] can prove this
theorem mem_cons_self (a : α) (s : Finset α) {h} : a ∈ cons a s h :=
Multiset.mem_cons_self _ _
#align finset.mem_cons_self Finset.mem_cons_self
@[simp]
theorem cons_val (h : a ∉ s) : (cons a s h).1 = a ::ₘ s.1 :=
rfl
#align finset.cons_val Finset.cons_val
theorem forall_mem_cons (h : a ∉ s) (p : α → Prop) :
(∀ x, x ∈ cons a s h → p x) ↔ p a ∧ ∀ x, x ∈ s → p x := by
simp only [mem_cons, or_imp, forall_and, forall_eq]
#align finset.forall_mem_cons Finset.forall_mem_cons
/-- Useful in proofs by induction. -/
theorem forall_of_forall_cons {p : α → Prop} {h : a ∉ s} (H : ∀ x, x ∈ cons a s h → p x) (x)
(h : x ∈ s) : p x :=
H _ <| mem_cons.2 <| Or.inr h
#align finset.forall_of_forall_cons Finset.forall_of_forall_cons
@[simp]
theorem mk_cons {s : Multiset α} (h : (a ::ₘ s).Nodup) :
(⟨a ::ₘ s, h⟩ : Finset α) = cons a ⟨s, (nodup_cons.1 h).2⟩ (nodup_cons.1 h).1 :=
rfl
#align finset.mk_cons Finset.mk_cons
@[simp]
theorem cons_empty (a : α) : cons a ∅ (not_mem_empty _) = {a} := rfl
#align finset.cons_empty Finset.cons_empty
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem nonempty_cons (h : a ∉ s) : (cons a s h).Nonempty :=
⟨a, mem_cons.2 <| Or.inl rfl⟩
#align finset.nonempty_cons Finset.nonempty_cons
@[simp]
theorem nonempty_mk {m : Multiset α} {hm} : (⟨m, hm⟩ : Finset α).Nonempty ↔ m ≠ 0 := by
induction m using Multiset.induction_on <;> simp
#align finset.nonempty_mk Finset.nonempty_mk
@[simp]
theorem coe_cons {a s h} : (@cons α a s h : Set α) = insert a (s : Set α) := by
ext
simp
#align finset.coe_cons Finset.coe_cons
theorem subset_cons (h : a ∉ s) : s ⊆ s.cons a h :=
Multiset.subset_cons _ _
#align finset.subset_cons Finset.subset_cons
theorem ssubset_cons (h : a ∉ s) : s ⊂ s.cons a h :=
Multiset.ssubset_cons h
#align finset.ssubset_cons Finset.ssubset_cons
theorem cons_subset {h : a ∉ s} : s.cons a h ⊆ t ↔ a ∈ t ∧ s ⊆ t :=
Multiset.cons_subset
#align finset.cons_subset Finset.cons_subset
@[simp]
theorem cons_subset_cons {hs ht} : s.cons a hs ⊆ t.cons a ht ↔ s ⊆ t := by
rwa [← coe_subset, coe_cons, coe_cons, Set.insert_subset_insert_iff, coe_subset]
#align finset.cons_subset_cons Finset.cons_subset_cons
theorem ssubset_iff_exists_cons_subset : s ⊂ t ↔ ∃ (a : _) (h : a ∉ s), s.cons a h ⊆ t := by
refine ⟨fun h => ?_, fun ⟨a, ha, h⟩ => ssubset_of_ssubset_of_subset (ssubset_cons _) h⟩
obtain ⟨a, hs, ht⟩ := not_subset.1 h.2
exact ⟨a, ht, cons_subset.2 ⟨hs, h.subset⟩⟩
#align finset.ssubset_iff_exists_cons_subset Finset.ssubset_iff_exists_cons_subset
end Cons
/-! ### disjoint -/
section Disjoint
variable {f : α → β} {s t u : Finset α} {a b : α}
theorem disjoint_left : Disjoint s t ↔ ∀ ⦃a⦄, a ∈ s → a ∉ t :=
⟨fun h a hs ht => not_mem_empty a <|
singleton_subset_iff.mp (h (singleton_subset_iff.mpr hs) (singleton_subset_iff.mpr ht)),
fun h _ hs ht _ ha => (h (hs ha) (ht ha)).elim⟩
#align finset.disjoint_left Finset.disjoint_left
theorem disjoint_right : Disjoint s t ↔ ∀ ⦃a⦄, a ∈ t → a ∉ s := by
rw [_root_.disjoint_comm, disjoint_left]
#align finset.disjoint_right Finset.disjoint_right
theorem disjoint_iff_ne : Disjoint s t ↔ ∀ a ∈ s, ∀ b ∈ t, a ≠ b := by
simp only [disjoint_left, imp_not_comm, forall_eq']
#align finset.disjoint_iff_ne Finset.disjoint_iff_ne
@[simp]
theorem disjoint_val : s.1.Disjoint t.1 ↔ Disjoint s t :=
disjoint_left.symm
#align finset.disjoint_val Finset.disjoint_val
theorem _root_.Disjoint.forall_ne_finset (h : Disjoint s t) (ha : a ∈ s) (hb : b ∈ t) : a ≠ b :=
disjoint_iff_ne.1 h _ ha _ hb
#align disjoint.forall_ne_finset Disjoint.forall_ne_finset
theorem not_disjoint_iff : ¬Disjoint s t ↔ ∃ a, a ∈ s ∧ a ∈ t :=
disjoint_left.not.trans <| not_forall.trans <| exists_congr fun _ => by
rw [Classical.not_imp, not_not]
#align finset.not_disjoint_iff Finset.not_disjoint_iff
theorem disjoint_of_subset_left (h : s ⊆ u) (d : Disjoint u t) : Disjoint s t :=
disjoint_left.2 fun _x m₁ => (disjoint_left.1 d) (h m₁)
#align finset.disjoint_of_subset_left Finset.disjoint_of_subset_left
theorem disjoint_of_subset_right (h : t ⊆ u) (d : Disjoint s u) : Disjoint s t :=
disjoint_right.2 fun _x m₁ => (disjoint_right.1 d) (h m₁)
#align finset.disjoint_of_subset_right Finset.disjoint_of_subset_right
@[simp]
theorem disjoint_empty_left (s : Finset α) : Disjoint ∅ s :=
disjoint_bot_left
#align finset.disjoint_empty_left Finset.disjoint_empty_left
@[simp]
theorem disjoint_empty_right (s : Finset α) : Disjoint s ∅ :=
disjoint_bot_right
#align finset.disjoint_empty_right Finset.disjoint_empty_right
@[simp]
theorem disjoint_singleton_left : Disjoint (singleton a) s ↔ a ∉ s := by
simp only [disjoint_left, mem_singleton, forall_eq]
#align finset.disjoint_singleton_left Finset.disjoint_singleton_left
@[simp]
theorem disjoint_singleton_right : Disjoint s (singleton a) ↔ a ∉ s :=
disjoint_comm.trans disjoint_singleton_left
#align finset.disjoint_singleton_right Finset.disjoint_singleton_right
-- Porting note: Left-hand side simplifies @[simp]
theorem disjoint_singleton : Disjoint ({a} : Finset α) {b} ↔ a ≠ b := by
rw [disjoint_singleton_left, mem_singleton]
#align finset.disjoint_singleton Finset.disjoint_singleton
theorem disjoint_self_iff_empty (s : Finset α) : Disjoint s s ↔ s = ∅ :=
disjoint_self
#align finset.disjoint_self_iff_empty Finset.disjoint_self_iff_empty
@[simp, norm_cast]
theorem disjoint_coe : Disjoint (s : Set α) t ↔ Disjoint s t := by
simp only [Finset.disjoint_left, Set.disjoint_left, mem_coe]
#align finset.disjoint_coe Finset.disjoint_coe
@[simp, norm_cast]
theorem pairwiseDisjoint_coe {ι : Type*} {s : Set ι} {f : ι → Finset α} :
s.PairwiseDisjoint (fun i => f i : ι → Set α) ↔ s.PairwiseDisjoint f :=
forall₅_congr fun _ _ _ _ _ => disjoint_coe
#align finset.pairwise_disjoint_coe Finset.pairwiseDisjoint_coe
end Disjoint
/-! ### disjoint union -/
/-- `disjUnion s t h` is the set such that `a ∈ disjUnion s t h` iff `a ∈ s` or `a ∈ t`.
It is the same as `s ∪ t`, but it does not require decidable equality on the type. The hypothesis
ensures that the sets are disjoint. -/
def disjUnion (s t : Finset α) (h : Disjoint s t) : Finset α :=
⟨s.1 + t.1, Multiset.nodup_add.2 ⟨s.2, t.2, disjoint_val.2 h⟩⟩
#align finset.disj_union Finset.disjUnion
@[simp]
theorem mem_disjUnion {α s t h a} : a ∈ @disjUnion α s t h ↔ a ∈ s ∨ a ∈ t := by
rcases s with ⟨⟨s⟩⟩; rcases t with ⟨⟨t⟩⟩; apply List.mem_append
#align finset.mem_disj_union Finset.mem_disjUnion
@[simp, norm_cast]
theorem coe_disjUnion {s t : Finset α} (h : Disjoint s t) :
(disjUnion s t h : Set α) = (s : Set α) ∪ t :=
Set.ext <| by simp
theorem disjUnion_comm (s t : Finset α) (h : Disjoint s t) :
disjUnion s t h = disjUnion t s h.symm :=
eq_of_veq <| add_comm _ _
#align finset.disj_union_comm Finset.disjUnion_comm
@[simp]
theorem empty_disjUnion (t : Finset α) (h : Disjoint ∅ t := disjoint_bot_left) :
disjUnion ∅ t h = t :=
eq_of_veq <| zero_add _
#align finset.empty_disj_union Finset.empty_disjUnion
@[simp]
theorem disjUnion_empty (s : Finset α) (h : Disjoint s ∅ := disjoint_bot_right) :
disjUnion s ∅ h = s :=
eq_of_veq <| add_zero _
#align finset.disj_union_empty Finset.disjUnion_empty
theorem singleton_disjUnion (a : α) (t : Finset α) (h : Disjoint {a} t) :
disjUnion {a} t h = cons a t (disjoint_singleton_left.mp h) :=
eq_of_veq <| Multiset.singleton_add _ _
#align finset.singleton_disj_union Finset.singleton_disjUnion
theorem disjUnion_singleton (s : Finset α) (a : α) (h : Disjoint s {a}) :
disjUnion s {a} h = cons a s (disjoint_singleton_right.mp h) := by
rw [disjUnion_comm, singleton_disjUnion]
#align finset.disj_union_singleton Finset.disjUnion_singleton
/-! ### insert -/
section Insert
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
/-- `insert a s` is the set `{a} ∪ s` containing `a` and the elements of `s`. -/
instance : Insert α (Finset α) :=
⟨fun a s => ⟨_, s.2.ndinsert a⟩⟩
theorem insert_def (a : α) (s : Finset α) : insert a s = ⟨_, s.2.ndinsert a⟩ :=
rfl
#align finset.insert_def Finset.insert_def
@[simp]
theorem insert_val (a : α) (s : Finset α) : (insert a s).1 = ndinsert a s.1 :=
rfl
#align finset.insert_val Finset.insert_val
theorem insert_val' (a : α) (s : Finset α) : (insert a s).1 = dedup (a ::ₘ s.1) := by
rw [dedup_cons, dedup_eq_self]; rfl
#align finset.insert_val' Finset.insert_val'
theorem insert_val_of_not_mem {a : α} {s : Finset α} (h : a ∉ s) : (insert a s).1 = a ::ₘ s.1 := by
rw [insert_val, ndinsert_of_not_mem h]
#align finset.insert_val_of_not_mem Finset.insert_val_of_not_mem
@[simp]
theorem mem_insert : a ∈ insert b s ↔ a = b ∨ a ∈ s :=
mem_ndinsert
#align finset.mem_insert Finset.mem_insert
theorem mem_insert_self (a : α) (s : Finset α) : a ∈ insert a s :=
mem_ndinsert_self a s.1
#align finset.mem_insert_self Finset.mem_insert_self
theorem mem_insert_of_mem (h : a ∈ s) : a ∈ insert b s :=
mem_ndinsert_of_mem h
#align finset.mem_insert_of_mem Finset.mem_insert_of_mem
theorem mem_of_mem_insert_of_ne (h : b ∈ insert a s) : b ≠ a → b ∈ s :=
(mem_insert.1 h).resolve_left
#align finset.mem_of_mem_insert_of_ne Finset.mem_of_mem_insert_of_ne
theorem eq_of_not_mem_of_mem_insert (ha : b ∈ insert a s) (hb : b ∉ s) : b = a :=
(mem_insert.1 ha).resolve_right hb
#align finset.eq_of_not_mem_of_mem_insert Finset.eq_of_not_mem_of_mem_insert
/-- A version of `LawfulSingleton.insert_emptyc_eq` that works with `dsimp`. -/
@[simp, nolint simpNF] lemma insert_empty : insert a (∅ : Finset α) = {a} := rfl
@[simp]
theorem cons_eq_insert (a s h) : @cons α a s h = insert a s :=
ext fun a => by simp
#align finset.cons_eq_insert Finset.cons_eq_insert
@[simp, norm_cast]
theorem coe_insert (a : α) (s : Finset α) : ↑(insert a s) = (insert a s : Set α) :=
Set.ext fun x => by simp only [mem_coe, mem_insert, Set.mem_insert_iff]
#align finset.coe_insert Finset.coe_insert
theorem mem_insert_coe {s : Finset α} {x y : α} : x ∈ insert y s ↔ x ∈ insert y (s : Set α) := by
simp
#align finset.mem_insert_coe Finset.mem_insert_coe
instance : LawfulSingleton α (Finset α) :=
⟨fun a => by ext; simp⟩
@[simp]
theorem insert_eq_of_mem (h : a ∈ s) : insert a s = s :=
eq_of_veq <| ndinsert_of_mem h
#align finset.insert_eq_of_mem Finset.insert_eq_of_mem
@[simp]
theorem insert_eq_self : insert a s = s ↔ a ∈ s :=
⟨fun h => h ▸ mem_insert_self _ _, insert_eq_of_mem⟩
#align finset.insert_eq_self Finset.insert_eq_self
theorem insert_ne_self : insert a s ≠ s ↔ a ∉ s :=
insert_eq_self.not
#align finset.insert_ne_self Finset.insert_ne_self
-- Porting note (#10618): @[simp] can prove this
theorem pair_eq_singleton (a : α) : ({a, a} : Finset α) = {a} :=
insert_eq_of_mem <| mem_singleton_self _
#align finset.pair_eq_singleton Finset.pair_eq_singleton
theorem Insert.comm (a b : α) (s : Finset α) : insert a (insert b s) = insert b (insert a s) :=
ext fun x => by simp only [mem_insert, or_left_comm]
#align finset.insert.comm Finset.Insert.comm
-- Porting note (#10618): @[simp] can prove this
@[norm_cast]
theorem coe_pair {a b : α} : (({a, b} : Finset α) : Set α) = {a, b} := by
ext
simp
#align finset.coe_pair Finset.coe_pair
@[simp, norm_cast]
theorem coe_eq_pair {s : Finset α} {a b : α} : (s : Set α) = {a, b} ↔ s = {a, b} := by
rw [← coe_pair, coe_inj]
#align finset.coe_eq_pair Finset.coe_eq_pair
theorem pair_comm (a b : α) : ({a, b} : Finset α) = {b, a} :=
Insert.comm a b ∅
#align finset.pair_comm Finset.pair_comm
-- Porting note (#10618): @[simp] can prove this
theorem insert_idem (a : α) (s : Finset α) : insert a (insert a s) = insert a s :=
ext fun x => by simp only [mem_insert, ← or_assoc, or_self_iff]
#align finset.insert_idem Finset.insert_idem
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem insert_nonempty (a : α) (s : Finset α) : (insert a s).Nonempty :=
⟨a, mem_insert_self a s⟩
#align finset.insert_nonempty Finset.insert_nonempty
@[simp]
theorem insert_ne_empty (a : α) (s : Finset α) : insert a s ≠ ∅ :=
(insert_nonempty a s).ne_empty
#align finset.insert_ne_empty Finset.insert_ne_empty
-- Porting note: explicit universe annotation is no longer required.
instance (i : α) (s : Finset α) : Nonempty ((insert i s : Finset α) : Set α) :=
(Finset.coe_nonempty.mpr (s.insert_nonempty i)).to_subtype
theorem ne_insert_of_not_mem (s t : Finset α) {a : α} (h : a ∉ s) : s ≠ insert a t := by
contrapose! h
simp [h]
#align finset.ne_insert_of_not_mem Finset.ne_insert_of_not_mem
theorem insert_subset_iff : insert a s ⊆ t ↔ a ∈ t ∧ s ⊆ t := by
simp only [subset_iff, mem_insert, forall_eq, or_imp, forall_and]
#align finset.insert_subset Finset.insert_subset_iff
theorem insert_subset (ha : a ∈ t) (hs : s ⊆ t) : insert a s ⊆ t :=
insert_subset_iff.mpr ⟨ha,hs⟩
@[simp] theorem subset_insert (a : α) (s : Finset α) : s ⊆ insert a s := fun _b => mem_insert_of_mem
#align finset.subset_insert Finset.subset_insert
@[gcongr]
theorem insert_subset_insert (a : α) {s t : Finset α} (h : s ⊆ t) : insert a s ⊆ insert a t :=
insert_subset_iff.2 ⟨mem_insert_self _ _, Subset.trans h (subset_insert _ _)⟩
#align finset.insert_subset_insert Finset.insert_subset_insert
@[simp] lemma insert_subset_insert_iff (ha : a ∉ s) : insert a s ⊆ insert a t ↔ s ⊆ t := by
simp_rw [← coe_subset]; simp [-coe_subset, ha]
theorem insert_inj (ha : a ∉ s) : insert a s = insert b s ↔ a = b :=
⟨fun h => eq_of_not_mem_of_mem_insert (h.subst <| mem_insert_self _ _) ha, congr_arg (insert · s)⟩
#align finset.insert_inj Finset.insert_inj
theorem insert_inj_on (s : Finset α) : Set.InjOn (fun a => insert a s) sᶜ := fun _ h _ _ =>
(insert_inj h).1
#align finset.insert_inj_on Finset.insert_inj_on
theorem ssubset_iff : s ⊂ t ↔ ∃ a ∉ s, insert a s ⊆ t := mod_cast @Set.ssubset_iff_insert α s t
#align finset.ssubset_iff Finset.ssubset_iff
theorem ssubset_insert (h : a ∉ s) : s ⊂ insert a s :=
ssubset_iff.mpr ⟨a, h, Subset.rfl⟩
#align finset.ssubset_insert Finset.ssubset_insert
@[elab_as_elim]
theorem cons_induction {α : Type*} {p : Finset α → Prop} (empty : p ∅)
(cons : ∀ (a : α) (s : Finset α) (h : a ∉ s), p s → p (cons a s h)) : ∀ s, p s
| ⟨s, nd⟩ => by
induction s using Multiset.induction with
| empty => exact empty
| cons a s IH =>
rw [mk_cons nd]
exact cons a _ _ (IH _)
#align finset.cons_induction Finset.cons_induction
@[elab_as_elim]
theorem cons_induction_on {α : Type*} {p : Finset α → Prop} (s : Finset α) (h₁ : p ∅)
(h₂ : ∀ ⦃a : α⦄ {s : Finset α} (h : a ∉ s), p s → p (cons a s h)) : p s :=
cons_induction h₁ h₂ s
#align finset.cons_induction_on Finset.cons_induction_on
@[elab_as_elim]
protected theorem induction {α : Type*} {p : Finset α → Prop} [DecidableEq α] (empty : p ∅)
(insert : ∀ ⦃a : α⦄ {s : Finset α}, a ∉ s → p s → p (insert a s)) : ∀ s, p s :=
cons_induction empty fun a s ha => (s.cons_eq_insert a ha).symm ▸ insert ha
#align finset.induction Finset.induction
/-- 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.
-/
@[elab_as_elim]
protected theorem induction_on {α : Type*} {p : Finset α → Prop} [DecidableEq α] (s : Finset α)
(empty : p ∅) (insert : ∀ ⦃a : α⦄ {s : Finset α}, a ∉ s → p s → p (insert a s)) : p s :=
Finset.induction empty insert s
#align finset.induction_on Finset.induction_on
/-- To prove a proposition about `S : Finset α`,
it suffices to prove it for the empty `Finset`,
and to show that if it holds for some `Finset α ⊆ S`,
then it holds for the `Finset` obtained by inserting a new element of `S`.
-/
@[elab_as_elim]
theorem induction_on' {α : Type*} {p : Finset α → Prop} [DecidableEq α] (S : Finset α) (h₁ : p ∅)
(h₂ : ∀ {a s}, a ∈ S → s ⊆ S → a ∉ s → p s → p (insert a s)) : p S :=
@Finset.induction_on α (fun T => T ⊆ S → p T) _ S (fun _ => h₁)
(fun _ _ has hqs hs =>
let ⟨hS, sS⟩ := Finset.insert_subset_iff.1 hs
h₂ hS sS has (hqs sS))
(Finset.Subset.refl S)
#align finset.induction_on' Finset.induction_on'
/-- To prove a proposition about a nonempty `s : Finset α`, it suffices to show it holds for all
singletons and that if it holds for nonempty `t : Finset α`, then it also holds for the `Finset`
obtained by inserting an element in `t`. -/
@[elab_as_elim]
theorem Nonempty.cons_induction {α : Type*} {p : ∀ s : Finset α, s.Nonempty → Prop}
(singleton : ∀ a, p {a} (singleton_nonempty _))
(cons : ∀ a s (h : a ∉ s) (hs), p s hs → p (Finset.cons a s h) (nonempty_cons h))
{s : Finset α} (hs : s.Nonempty) : p s hs := by
induction s using Finset.cons_induction with
| empty => exact (not_nonempty_empty hs).elim
| cons a t ha h =>
obtain rfl | ht := t.eq_empty_or_nonempty
· exact singleton a
· exact cons a t ha ht (h ht)
#align finset.nonempty.cons_induction Finset.Nonempty.cons_induction
lemma Nonempty.exists_cons_eq (hs : s.Nonempty) : ∃ t a ha, cons a t ha = s :=
hs.cons_induction (fun a ↦ ⟨∅, a, _, cons_empty _⟩) fun _ _ _ _ _ ↦ ⟨_, _, _, rfl⟩
/-- Inserting an element to a finite set is equivalent to the option type. -/
def subtypeInsertEquivOption {t : Finset α} {x : α} (h : x ∉ t) :
{ i // i ∈ insert x t } ≃ Option { i // i ∈ t } where
toFun y := if h : ↑y = x then none else some ⟨y, (mem_insert.mp y.2).resolve_left h⟩
invFun y := (y.elim ⟨x, mem_insert_self _ _⟩) fun z => ⟨z, mem_insert_of_mem z.2⟩
left_inv y := by
by_cases h : ↑y = x
· simp only [Subtype.ext_iff, h, Option.elim, dif_pos, Subtype.coe_mk]
· simp only [h, Option.elim, dif_neg, not_false_iff, Subtype.coe_eta, Subtype.coe_mk]
right_inv := by
rintro (_ | y)
· simp only [Option.elim, dif_pos]
· have : ↑y ≠ x := by
rintro ⟨⟩
exact h y.2
simp only [this, Option.elim, Subtype.eta, dif_neg, not_false_iff, Subtype.coe_mk]
#align finset.subtype_insert_equiv_option Finset.subtypeInsertEquivOption
@[simp]
theorem disjoint_insert_left : Disjoint (insert a s) t ↔ a ∉ t ∧ Disjoint s t := by
simp only [disjoint_left, mem_insert, or_imp, forall_and, forall_eq]
#align finset.disjoint_insert_left Finset.disjoint_insert_left
@[simp]
theorem disjoint_insert_right : Disjoint s (insert a t) ↔ a ∉ s ∧ Disjoint s t :=
disjoint_comm.trans <| by rw [disjoint_insert_left, _root_.disjoint_comm]
#align finset.disjoint_insert_right Finset.disjoint_insert_right
end Insert
/-! ### Lattice structure -/
section Lattice
variable [DecidableEq α] {s s₁ s₂ t t₁ t₂ u v : Finset α} {a b : α}
/-- `s ∪ t` is the set such that `a ∈ s ∪ t` iff `a ∈ s` or `a ∈ t`. -/
instance : Union (Finset α) :=
⟨fun s t => ⟨_, t.2.ndunion s.1⟩⟩
/-- `s ∩ t` is the set such that `a ∈ s ∩ t` iff `a ∈ s` and `a ∈ t`. -/
instance : Inter (Finset α) :=
⟨fun s t => ⟨_, s.2.ndinter t.1⟩⟩
instance : Lattice (Finset α) :=
{ Finset.partialOrder with
sup := (· ∪ ·)
sup_le := fun _ _ _ hs ht _ ha => (mem_ndunion.1 ha).elim (fun h => hs h) fun h => ht h
le_sup_left := fun _ _ _ h => mem_ndunion.2 <| Or.inl h
le_sup_right := fun _ _ _ h => mem_ndunion.2 <| Or.inr h
inf := (· ∩ ·)
le_inf := fun _ _ _ ht hu _ h => mem_ndinter.2 ⟨ht h, hu h⟩
inf_le_left := fun _ _ _ h => (mem_ndinter.1 h).1
inf_le_right := fun _ _ _ h => (mem_ndinter.1 h).2 }
@[simp]
theorem sup_eq_union : (Sup.sup : Finset α → Finset α → Finset α) = Union.union :=
rfl
#align finset.sup_eq_union Finset.sup_eq_union
@[simp]
theorem inf_eq_inter : (Inf.inf : Finset α → Finset α → Finset α) = Inter.inter :=
rfl
#align finset.inf_eq_inter Finset.inf_eq_inter
theorem disjoint_iff_inter_eq_empty : Disjoint s t ↔ s ∩ t = ∅ :=
disjoint_iff
#align finset.disjoint_iff_inter_eq_empty Finset.disjoint_iff_inter_eq_empty
instance decidableDisjoint (U V : Finset α) : Decidable (Disjoint U V) :=
decidable_of_iff _ disjoint_left.symm
#align finset.decidable_disjoint Finset.decidableDisjoint
/-! #### union -/
theorem union_val_nd (s t : Finset α) : (s ∪ t).1 = ndunion s.1 t.1 :=
rfl
#align finset.union_val_nd Finset.union_val_nd
@[simp]
theorem union_val (s t : Finset α) : (s ∪ t).1 = s.1 ∪ t.1 :=
ndunion_eq_union s.2
#align finset.union_val Finset.union_val
@[simp]
theorem mem_union : a ∈ s ∪ t ↔ a ∈ s ∨ a ∈ t :=
mem_ndunion
#align finset.mem_union Finset.mem_union
@[simp]
theorem disjUnion_eq_union (s t h) : @disjUnion α s t h = s ∪ t :=
ext fun a => by simp
#align finset.disj_union_eq_union Finset.disjUnion_eq_union
theorem mem_union_left (t : Finset α) (h : a ∈ s) : a ∈ s ∪ t :=
mem_union.2 <| Or.inl h
#align finset.mem_union_left Finset.mem_union_left
theorem mem_union_right (s : Finset α) (h : a ∈ t) : a ∈ s ∪ t :=
mem_union.2 <| Or.inr h
#align finset.mem_union_right Finset.mem_union_right
theorem forall_mem_union {p : α → Prop} : (∀ a ∈ s ∪ t, p a) ↔ (∀ a ∈ s, p a) ∧ ∀ a ∈ t, p a :=
⟨fun h => ⟨fun a => h a ∘ mem_union_left _, fun b => h b ∘ mem_union_right _⟩,
fun h _ab hab => (mem_union.mp hab).elim (h.1 _) (h.2 _)⟩
#align finset.forall_mem_union Finset.forall_mem_union
theorem not_mem_union : a ∉ s ∪ t ↔ a ∉ s ∧ a ∉ t := by rw [mem_union, not_or]
#align finset.not_mem_union Finset.not_mem_union
@[simp, norm_cast]
theorem coe_union (s₁ s₂ : Finset α) : ↑(s₁ ∪ s₂) = (s₁ ∪ s₂ : Set α) :=
Set.ext fun _ => mem_union
#align finset.coe_union Finset.coe_union
theorem union_subset (hs : s ⊆ u) : t ⊆ u → s ∪ t ⊆ u :=
sup_le <| le_iff_subset.2 hs
#align finset.union_subset Finset.union_subset
theorem subset_union_left {s₁ s₂ : Finset α} : s₁ ⊆ s₁ ∪ s₂ := fun _x => mem_union_left _
#align finset.subset_union_left Finset.subset_union_left
theorem subset_union_right {s₁ s₂ : Finset α} : s₂ ⊆ s₁ ∪ s₂ := fun _x => mem_union_right _
#align finset.subset_union_right Finset.subset_union_right
@[gcongr]
theorem union_subset_union (hsu : s ⊆ u) (htv : t ⊆ v) : s ∪ t ⊆ u ∪ v :=
sup_le_sup (le_iff_subset.2 hsu) htv
#align finset.union_subset_union Finset.union_subset_union
@[gcongr]
theorem union_subset_union_left (h : s₁ ⊆ s₂) : s₁ ∪ t ⊆ s₂ ∪ t :=
union_subset_union h Subset.rfl
#align finset.union_subset_union_left Finset.union_subset_union_left
@[gcongr]
theorem union_subset_union_right (h : t₁ ⊆ t₂) : s ∪ t₁ ⊆ s ∪ t₂ :=
union_subset_union Subset.rfl h
#align finset.union_subset_union_right Finset.union_subset_union_right
theorem union_comm (s₁ s₂ : Finset α) : s₁ ∪ s₂ = s₂ ∪ s₁ := sup_comm _ _
#align finset.union_comm Finset.union_comm
instance : Std.Commutative (α := Finset α) (· ∪ ·) :=
⟨union_comm⟩
@[simp]
theorem union_assoc (s₁ s₂ s₃ : Finset α) : s₁ ∪ s₂ ∪ s₃ = s₁ ∪ (s₂ ∪ s₃) := sup_assoc _ _ _
#align finset.union_assoc Finset.union_assoc
instance : Std.Associative (α := Finset α) (· ∪ ·) :=
⟨union_assoc⟩
@[simp]
theorem union_idempotent (s : Finset α) : s ∪ s = s := sup_idem _
#align finset.union_idempotent Finset.union_idempotent
instance : Std.IdempotentOp (α := Finset α) (· ∪ ·) :=
⟨union_idempotent⟩
theorem union_subset_left (h : s ∪ t ⊆ u) : s ⊆ u :=
subset_union_left.trans h
#align finset.union_subset_left Finset.union_subset_left
theorem union_subset_right {s t u : Finset α} (h : s ∪ t ⊆ u) : t ⊆ u :=
Subset.trans subset_union_right h
#align finset.union_subset_right Finset.union_subset_right
theorem union_left_comm (s t u : Finset α) : s ∪ (t ∪ u) = t ∪ (s ∪ u) :=
ext fun _ => by simp only [mem_union, or_left_comm]
#align finset.union_left_comm Finset.union_left_comm
theorem union_right_comm (s t u : Finset α) : s ∪ t ∪ u = s ∪ u ∪ t :=
ext fun x => by simp only [mem_union, or_assoc, @or_comm (x ∈ t)]
#align finset.union_right_comm Finset.union_right_comm
theorem union_self (s : Finset α) : s ∪ s = s :=
union_idempotent s
#align finset.union_self Finset.union_self
@[simp]
theorem union_empty (s : Finset α) : s ∪ ∅ = s :=
ext fun x => mem_union.trans <| by simp
#align finset.union_empty Finset.union_empty
@[simp]
theorem empty_union (s : Finset α) : ∅ ∪ s = s :=
ext fun x => mem_union.trans <| by simp
#align finset.empty_union Finset.empty_union
@[aesop unsafe apply (rule_sets := [finsetNonempty])]
theorem Nonempty.inl {s t : Finset α} (h : s.Nonempty) : (s ∪ t).Nonempty :=
h.mono subset_union_left
@[aesop unsafe apply (rule_sets := [finsetNonempty])]
theorem Nonempty.inr {s t : Finset α} (h : t.Nonempty) : (s ∪ t).Nonempty :=
h.mono subset_union_right
theorem insert_eq (a : α) (s : Finset α) : insert a s = {a} ∪ s :=
rfl
#align finset.insert_eq Finset.insert_eq
@[simp]
theorem insert_union (a : α) (s t : Finset α) : insert a s ∪ t = insert a (s ∪ t) := by
simp only [insert_eq, union_assoc]
#align finset.insert_union Finset.insert_union
@[simp]
theorem union_insert (a : α) (s t : Finset α) : s ∪ insert a t = insert a (s ∪ t) := by
simp only [insert_eq, union_left_comm]
#align finset.union_insert Finset.union_insert
theorem insert_union_distrib (a : α) (s t : Finset α) :
insert a (s ∪ t) = insert a s ∪ insert a t := by
simp only [insert_union, union_insert, insert_idem]
#align finset.insert_union_distrib Finset.insert_union_distrib
@[simp] lemma union_eq_left : s ∪ t = s ↔ t ⊆ s := sup_eq_left
#align finset.union_eq_left_iff_subset Finset.union_eq_left
@[simp] lemma left_eq_union : s = s ∪ t ↔ t ⊆ s := by rw [eq_comm, union_eq_left]
#align finset.left_eq_union_iff_subset Finset.left_eq_union
@[simp] lemma union_eq_right : s ∪ t = t ↔ s ⊆ t := sup_eq_right
#align finset.union_eq_right_iff_subset Finset.union_eq_right
@[simp] lemma right_eq_union : s = t ∪ s ↔ t ⊆ s := by rw [eq_comm, union_eq_right]
#align finset.right_eq_union_iff_subset Finset.right_eq_union
-- Porting note: replaced `⊔` in RHS
theorem union_congr_left (ht : t ⊆ s ∪ u) (hu : u ⊆ s ∪ t) : s ∪ t = s ∪ u :=
sup_congr_left ht hu
#align finset.union_congr_left Finset.union_congr_left
theorem union_congr_right (hs : s ⊆ t ∪ u) (ht : t ⊆ s ∪ u) : s ∪ u = t ∪ u :=
sup_congr_right hs ht
#align finset.union_congr_right Finset.union_congr_right
theorem union_eq_union_iff_left : s ∪ t = s ∪ u ↔ t ⊆ s ∪ u ∧ u ⊆ s ∪ t :=
sup_eq_sup_iff_left
#align finset.union_eq_union_iff_left Finset.union_eq_union_iff_left
theorem union_eq_union_iff_right : s ∪ u = t ∪ u ↔ s ⊆ t ∪ u ∧ t ⊆ s ∪ u :=
sup_eq_sup_iff_right
#align finset.union_eq_union_iff_right Finset.union_eq_union_iff_right
@[simp]
theorem disjoint_union_left : Disjoint (s ∪ t) u ↔ Disjoint s u ∧ Disjoint t u := by
simp only [disjoint_left, mem_union, or_imp, forall_and]
#align finset.disjoint_union_left Finset.disjoint_union_left
@[simp]
theorem disjoint_union_right : Disjoint s (t ∪ u) ↔ Disjoint s t ∧ Disjoint s u := by
simp only [disjoint_right, mem_union, or_imp, forall_and]
#align finset.disjoint_union_right Finset.disjoint_union_right
/-- To prove a relation on pairs of `Finset X`, it suffices to show that it is
* symmetric,
* it holds when one of the `Finset`s is empty,
* it holds for pairs of singletons,
* if it holds for `[a, c]` and for `[b, c]`, then it holds for `[a ∪ b, c]`.
-/
theorem induction_on_union (P : Finset α → Finset α → Prop) (symm : ∀ {a b}, P a b → P b a)
(empty_right : ∀ {a}, P a ∅) (singletons : ∀ {a b}, P {a} {b})
(union_of : ∀ {a b c}, P a c → P b c → P (a ∪ b) c) : ∀ a b, P a b := by
intro a b
refine Finset.induction_on b empty_right fun x s _xs hi => symm ?_
rw [Finset.insert_eq]
apply union_of _ (symm hi)
refine Finset.induction_on a empty_right fun a t _ta hi => symm ?_
rw [Finset.insert_eq]
exact union_of singletons (symm hi)
#align finset.induction_on_union Finset.induction_on_union
/-! #### inter -/
theorem inter_val_nd (s₁ s₂ : Finset α) : (s₁ ∩ s₂).1 = ndinter s₁.1 s₂.1 :=
rfl
#align finset.inter_val_nd Finset.inter_val_nd
@[simp]
theorem inter_val (s₁ s₂ : Finset α) : (s₁ ∩ s₂).1 = s₁.1 ∩ s₂.1 :=
ndinter_eq_inter s₁.2
#align finset.inter_val Finset.inter_val
@[simp]
theorem mem_inter {a : α} {s₁ s₂ : Finset α} : a ∈ s₁ ∩ s₂ ↔ a ∈ s₁ ∧ a ∈ s₂ :=
mem_ndinter
#align finset.mem_inter Finset.mem_inter
theorem mem_of_mem_inter_left {a : α} {s₁ s₂ : Finset α} (h : a ∈ s₁ ∩ s₂) : a ∈ s₁ :=
(mem_inter.1 h).1
#align finset.mem_of_mem_inter_left Finset.mem_of_mem_inter_left
theorem mem_of_mem_inter_right {a : α} {s₁ s₂ : Finset α} (h : a ∈ s₁ ∩ s₂) : a ∈ s₂ :=
(mem_inter.1 h).2
#align finset.mem_of_mem_inter_right Finset.mem_of_mem_inter_right
theorem mem_inter_of_mem {a : α} {s₁ s₂ : Finset α} : a ∈ s₁ → a ∈ s₂ → a ∈ s₁ ∩ s₂ :=
and_imp.1 mem_inter.2
#align finset.mem_inter_of_mem Finset.mem_inter_of_mem
theorem inter_subset_left {s₁ s₂ : Finset α} : s₁ ∩ s₂ ⊆ s₁ := fun _a => mem_of_mem_inter_left
#align finset.inter_subset_left Finset.inter_subset_left
theorem inter_subset_right {s₁ s₂ : Finset α} : s₁ ∩ s₂ ⊆ s₂ := fun _a => mem_of_mem_inter_right
#align finset.inter_subset_right Finset.inter_subset_right
theorem subset_inter {s₁ s₂ u : Finset α} : s₁ ⊆ s₂ → s₁ ⊆ u → s₁ ⊆ s₂ ∩ u := by
simp (config := { contextual := true }) [subset_iff, mem_inter]
#align finset.subset_inter Finset.subset_inter
@[simp, norm_cast]
theorem coe_inter (s₁ s₂ : Finset α) : ↑(s₁ ∩ s₂) = (s₁ ∩ s₂ : Set α) :=
Set.ext fun _ => mem_inter
#align finset.coe_inter Finset.coe_inter
@[simp]
theorem union_inter_cancel_left {s t : Finset α} : (s ∪ t) ∩ s = s := by
rw [← coe_inj, coe_inter, coe_union, Set.union_inter_cancel_left]
#align finset.union_inter_cancel_left Finset.union_inter_cancel_left
@[simp]
theorem union_inter_cancel_right {s t : Finset α} : (s ∪ t) ∩ t = t := by
rw [← coe_inj, coe_inter, coe_union, Set.union_inter_cancel_right]
#align finset.union_inter_cancel_right Finset.union_inter_cancel_right
theorem inter_comm (s₁ s₂ : Finset α) : s₁ ∩ s₂ = s₂ ∩ s₁ :=
ext fun _ => by simp only [mem_inter, and_comm]
#align finset.inter_comm Finset.inter_comm
@[simp]
theorem inter_assoc (s₁ s₂ s₃ : Finset α) : s₁ ∩ s₂ ∩ s₃ = s₁ ∩ (s₂ ∩ s₃) :=
ext fun _ => by simp only [mem_inter, and_assoc]
#align finset.inter_assoc Finset.inter_assoc
theorem inter_left_comm (s₁ s₂ s₃ : Finset α) : s₁ ∩ (s₂ ∩ s₃) = s₂ ∩ (s₁ ∩ s₃) :=
ext fun _ => by simp only [mem_inter, and_left_comm]
#align finset.inter_left_comm Finset.inter_left_comm
theorem inter_right_comm (s₁ s₂ s₃ : Finset α) : s₁ ∩ s₂ ∩ s₃ = s₁ ∩ s₃ ∩ s₂ :=
ext fun _ => by simp only [mem_inter, and_right_comm]
#align finset.inter_right_comm Finset.inter_right_comm
@[simp]
theorem inter_self (s : Finset α) : s ∩ s = s :=
ext fun _ => mem_inter.trans <| and_self_iff
#align finset.inter_self Finset.inter_self
@[simp]
theorem inter_empty (s : Finset α) : s ∩ ∅ = ∅ :=
ext fun _ => mem_inter.trans <| by simp
#align finset.inter_empty Finset.inter_empty
@[simp]
theorem empty_inter (s : Finset α) : ∅ ∩ s = ∅ :=
ext fun _ => mem_inter.trans <| by simp
#align finset.empty_inter Finset.empty_inter
@[simp]
theorem inter_union_self (s t : Finset α) : s ∩ (t ∪ s) = s := by
rw [inter_comm, union_inter_cancel_right]
#align finset.inter_union_self Finset.inter_union_self
@[simp]
theorem insert_inter_of_mem {s₁ s₂ : Finset α} {a : α} (h : a ∈ s₂) :
insert a s₁ ∩ s₂ = insert a (s₁ ∩ s₂) :=
ext fun x => by
have : x = a ∨ x ∈ s₂ ↔ x ∈ s₂ := or_iff_right_of_imp <| by rintro rfl; exact h
simp only [mem_inter, mem_insert, or_and_left, this]
#align finset.insert_inter_of_mem Finset.insert_inter_of_mem
@[simp]
theorem inter_insert_of_mem {s₁ s₂ : Finset α} {a : α} (h : a ∈ s₁) :
s₁ ∩ insert a s₂ = insert a (s₁ ∩ s₂) := by rw [inter_comm, insert_inter_of_mem h, inter_comm]
#align finset.inter_insert_of_mem Finset.inter_insert_of_mem
@[simp]
theorem insert_inter_of_not_mem {s₁ s₂ : Finset α} {a : α} (h : a ∉ s₂) :
insert a s₁ ∩ s₂ = s₁ ∩ s₂ :=
ext fun x => by
have : ¬(x = a ∧ x ∈ s₂) := by rintro ⟨rfl, H⟩; exact h H
simp only [mem_inter, mem_insert, or_and_right, this, false_or_iff]
#align finset.insert_inter_of_not_mem Finset.insert_inter_of_not_mem
@[simp]
theorem inter_insert_of_not_mem {s₁ s₂ : Finset α} {a : α} (h : a ∉ s₁) :
s₁ ∩ insert a s₂ = s₁ ∩ s₂ := by rw [inter_comm, insert_inter_of_not_mem h, inter_comm]
#align finset.inter_insert_of_not_mem Finset.inter_insert_of_not_mem
@[simp]
theorem singleton_inter_of_mem {a : α} {s : Finset α} (H : a ∈ s) : {a} ∩ s = {a} :=
show insert a ∅ ∩ s = insert a ∅ by rw [insert_inter_of_mem H, empty_inter]
#align finset.singleton_inter_of_mem Finset.singleton_inter_of_mem
@[simp]
theorem singleton_inter_of_not_mem {a : α} {s : Finset α} (H : a ∉ s) : {a} ∩ s = ∅ :=
eq_empty_of_forall_not_mem <| by
simp only [mem_inter, mem_singleton]; rintro x ⟨rfl, h⟩; exact H h
#align finset.singleton_inter_of_not_mem Finset.singleton_inter_of_not_mem
@[simp]
theorem inter_singleton_of_mem {a : α} {s : Finset α} (h : a ∈ s) : s ∩ {a} = {a} := by
rw [inter_comm, singleton_inter_of_mem h]
#align finset.inter_singleton_of_mem Finset.inter_singleton_of_mem
@[simp]
theorem inter_singleton_of_not_mem {a : α} {s : Finset α} (h : a ∉ s) : s ∩ {a} = ∅ := by
rw [inter_comm, singleton_inter_of_not_mem h]
#align finset.inter_singleton_of_not_mem Finset.inter_singleton_of_not_mem
@[mono, gcongr]
theorem inter_subset_inter {x y s t : Finset α} (h : x ⊆ y) (h' : s ⊆ t) : x ∩ s ⊆ y ∩ t := by
intro a a_in
rw [Finset.mem_inter] at a_in ⊢
exact ⟨h a_in.1, h' a_in.2⟩
#align finset.inter_subset_inter Finset.inter_subset_inter
@[gcongr]
theorem inter_subset_inter_left (h : t ⊆ u) : s ∩ t ⊆ s ∩ u :=
inter_subset_inter Subset.rfl h
#align finset.inter_subset_inter_left Finset.inter_subset_inter_left
@[gcongr]
theorem inter_subset_inter_right (h : s ⊆ t) : s ∩ u ⊆ t ∩ u :=
inter_subset_inter h Subset.rfl
#align finset.inter_subset_inter_right Finset.inter_subset_inter_right
theorem inter_subset_union : s ∩ t ⊆ s ∪ t :=
le_iff_subset.1 inf_le_sup
#align finset.inter_subset_union Finset.inter_subset_union
instance : DistribLattice (Finset α) :=
{ le_sup_inf := fun a b c => by
simp (config := { contextual := true }) only
[sup_eq_union, inf_eq_inter, le_eq_subset, subset_iff, mem_inter, mem_union, and_imp,
or_imp, true_or_iff, imp_true_iff, true_and_iff, or_true_iff] }
@[simp]
theorem union_left_idem (s t : Finset α) : s ∪ (s ∪ t) = s ∪ t := sup_left_idem _ _
#align finset.union_left_idem Finset.union_left_idem
-- Porting note (#10618): @[simp] can prove this
theorem union_right_idem (s t : Finset α) : s ∪ t ∪ t = s ∪ t := sup_right_idem _ _
#align finset.union_right_idem Finset.union_right_idem
@[simp]
theorem inter_left_idem (s t : Finset α) : s ∩ (s ∩ t) = s ∩ t := inf_left_idem _ _
#align finset.inter_left_idem Finset.inter_left_idem
-- Porting note (#10618): @[simp] can prove this
theorem inter_right_idem (s t : Finset α) : s ∩ t ∩ t = s ∩ t := inf_right_idem _ _
#align finset.inter_right_idem Finset.inter_right_idem
theorem inter_union_distrib_left (s t u : Finset α) : s ∩ (t ∪ u) = s ∩ t ∪ s ∩ u :=
inf_sup_left _ _ _
#align finset.inter_distrib_left Finset.inter_union_distrib_left
theorem union_inter_distrib_right (s t u : Finset α) : (s ∪ t) ∩ u = s ∩ u ∪ t ∩ u :=
inf_sup_right _ _ _
#align finset.inter_distrib_right Finset.union_inter_distrib_right
theorem union_inter_distrib_left (s t u : Finset α) : s ∪ t ∩ u = (s ∪ t) ∩ (s ∪ u) :=
sup_inf_left _ _ _
#align finset.union_distrib_left Finset.union_inter_distrib_left
theorem inter_union_distrib_right (s t u : Finset α) : s ∩ t ∪ u = (s ∪ u) ∩ (t ∪ u) :=
sup_inf_right _ _ _
#align finset.union_distrib_right Finset.inter_union_distrib_right
-- 2024-03-22
@[deprecated] alias inter_distrib_left := inter_union_distrib_left
@[deprecated] alias inter_distrib_right := union_inter_distrib_right
@[deprecated] alias union_distrib_left := union_inter_distrib_left
@[deprecated] alias union_distrib_right := inter_union_distrib_right
theorem union_union_distrib_left (s t u : Finset α) : s ∪ (t ∪ u) = s ∪ t ∪ (s ∪ u) :=
sup_sup_distrib_left _ _ _
#align finset.union_union_distrib_left Finset.union_union_distrib_left
theorem union_union_distrib_right (s t u : Finset α) : s ∪ t ∪ u = s ∪ u ∪ (t ∪ u) :=
sup_sup_distrib_right _ _ _
#align finset.union_union_distrib_right Finset.union_union_distrib_right
theorem inter_inter_distrib_left (s t u : Finset α) : s ∩ (t ∩ u) = s ∩ t ∩ (s ∩ u) :=
inf_inf_distrib_left _ _ _
#align finset.inter_inter_distrib_left Finset.inter_inter_distrib_left
theorem inter_inter_distrib_right (s t u : Finset α) : s ∩ t ∩ u = s ∩ u ∩ (t ∩ u) :=
inf_inf_distrib_right _ _ _
#align finset.inter_inter_distrib_right Finset.inter_inter_distrib_right
theorem union_union_union_comm (s t u v : Finset α) : s ∪ t ∪ (u ∪ v) = s ∪ u ∪ (t ∪ v) :=
sup_sup_sup_comm _ _ _ _
#align finset.union_union_union_comm Finset.union_union_union_comm
theorem inter_inter_inter_comm (s t u v : Finset α) : s ∩ t ∩ (u ∩ v) = s ∩ u ∩ (t ∩ v) :=
inf_inf_inf_comm _ _ _ _
#align finset.inter_inter_inter_comm Finset.inter_inter_inter_comm
lemma union_eq_empty : s ∪ t = ∅ ↔ s = ∅ ∧ t = ∅ := sup_eq_bot_iff
#align finset.union_eq_empty_iff Finset.union_eq_empty
theorem union_subset_iff : s ∪ t ⊆ u ↔ s ⊆ u ∧ t ⊆ u :=
(sup_le_iff : s ⊔ t ≤ u ↔ s ≤ u ∧ t ≤ u)
#align finset.union_subset_iff Finset.union_subset_iff
theorem subset_inter_iff : s ⊆ t ∩ u ↔ s ⊆ t ∧ s ⊆ u :=
(le_inf_iff : s ≤ t ⊓ u ↔ s ≤ t ∧ s ≤ u)
#align finset.subset_inter_iff Finset.subset_inter_iff
@[simp] lemma inter_eq_left : s ∩ t = s ↔ s ⊆ t := inf_eq_left
#align finset.inter_eq_left_iff_subset_iff_subset Finset.inter_eq_left
@[simp] lemma inter_eq_right : t ∩ s = s ↔ s ⊆ t := inf_eq_right
#align finset.inter_eq_right_iff_subset Finset.inter_eq_right
theorem inter_congr_left (ht : s ∩ u ⊆ t) (hu : s ∩ t ⊆ u) : s ∩ t = s ∩ u :=
inf_congr_left ht hu
#align finset.inter_congr_left Finset.inter_congr_left
theorem inter_congr_right (hs : t ∩ u ⊆ s) (ht : s ∩ u ⊆ t) : s ∩ u = t ∩ u :=
inf_congr_right hs ht
#align finset.inter_congr_right Finset.inter_congr_right
theorem inter_eq_inter_iff_left : s ∩ t = s ∩ u ↔ s ∩ u ⊆ t ∧ s ∩ t ⊆ u :=
inf_eq_inf_iff_left
#align finset.inter_eq_inter_iff_left Finset.inter_eq_inter_iff_left
theorem inter_eq_inter_iff_right : s ∩ u = t ∩ u ↔ t ∩ u ⊆ s ∧ s ∩ u ⊆ t :=
inf_eq_inf_iff_right
#align finset.inter_eq_inter_iff_right Finset.inter_eq_inter_iff_right
theorem ite_subset_union (s s' : Finset α) (P : Prop) [Decidable P] : ite P s s' ⊆ s ∪ s' :=
ite_le_sup s s' P
#align finset.ite_subset_union Finset.ite_subset_union
theorem inter_subset_ite (s s' : Finset α) (P : Prop) [Decidable P] : s ∩ s' ⊆ ite P s s' :=
inf_le_ite s s' P
#align finset.inter_subset_ite Finset.inter_subset_ite
theorem not_disjoint_iff_nonempty_inter : ¬Disjoint s t ↔ (s ∩ t).Nonempty :=
not_disjoint_iff.trans <| by simp [Finset.Nonempty]
#align finset.not_disjoint_iff_nonempty_inter Finset.not_disjoint_iff_nonempty_inter
alias ⟨_, Nonempty.not_disjoint⟩ := not_disjoint_iff_nonempty_inter
#align finset.nonempty.not_disjoint Finset.Nonempty.not_disjoint
theorem disjoint_or_nonempty_inter (s t : Finset α) : Disjoint s t ∨ (s ∩ t).Nonempty := by
rw [← not_disjoint_iff_nonempty_inter]
exact em _
#align finset.disjoint_or_nonempty_inter Finset.disjoint_or_nonempty_inter
end Lattice
instance isDirected_le : IsDirected (Finset α) (· ≤ ·) := by classical infer_instance
instance isDirected_subset : IsDirected (Finset α) (· ⊆ ·) := isDirected_le
/-! ### erase -/
section Erase
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
/-- `erase s a` is the set `s - {a}`, that is, the elements of `s` which are
not equal to `a`. -/
def erase (s : Finset α) (a : α) : Finset α :=
⟨_, s.2.erase a⟩
#align finset.erase Finset.erase
@[simp]
theorem erase_val (s : Finset α) (a : α) : (erase s a).1 = s.1.erase a :=
rfl
#align finset.erase_val Finset.erase_val
@[simp]
theorem mem_erase {a b : α} {s : Finset α} : a ∈ erase s b ↔ a ≠ b ∧ a ∈ s :=
s.2.mem_erase_iff
#align finset.mem_erase Finset.mem_erase
theorem not_mem_erase (a : α) (s : Finset α) : a ∉ erase s a :=
s.2.not_mem_erase
#align finset.not_mem_erase Finset.not_mem_erase
-- While this can be solved by `simp`, this lemma is eligible for `dsimp`
@[nolint simpNF, simp]
theorem erase_empty (a : α) : erase ∅ a = ∅ :=
rfl
#align finset.erase_empty Finset.erase_empty
protected lemma Nontrivial.erase_nonempty (hs : s.Nontrivial) : (s.erase a).Nonempty :=
(hs.exists_ne a).imp $ by aesop
@[simp] lemma erase_nonempty (ha : a ∈ s) : (s.erase a).Nonempty ↔ s.Nontrivial := by
simp only [Finset.Nonempty, mem_erase, and_comm (b := _ ∈ _)]
refine ⟨?_, fun hs ↦ hs.exists_ne a⟩
rintro ⟨b, hb, hba⟩
exact ⟨_, hb, _, ha, hba⟩
@[simp]
theorem erase_singleton (a : α) : ({a} : Finset α).erase a = ∅ := by
ext x
simp
#align finset.erase_singleton Finset.erase_singleton
theorem ne_of_mem_erase : b ∈ erase s a → b ≠ a := fun h => (mem_erase.1 h).1
#align finset.ne_of_mem_erase Finset.ne_of_mem_erase
theorem mem_of_mem_erase : b ∈ erase s a → b ∈ s :=
Multiset.mem_of_mem_erase
#align finset.mem_of_mem_erase Finset.mem_of_mem_erase
theorem mem_erase_of_ne_of_mem : a ≠ b → a ∈ s → a ∈ erase s b := by
simp only [mem_erase]; exact And.intro
#align finset.mem_erase_of_ne_of_mem Finset.mem_erase_of_ne_of_mem
/-- An element of `s` that is not an element of `erase s a` must be`a`. -/
theorem eq_of_mem_of_not_mem_erase (hs : b ∈ s) (hsa : b ∉ s.erase a) : b = a := by
rw [mem_erase, not_and] at hsa
exact not_imp_not.mp hsa hs
#align finset.eq_of_mem_of_not_mem_erase Finset.eq_of_mem_of_not_mem_erase
@[simp]
theorem erase_eq_of_not_mem {a : α} {s : Finset α} (h : a ∉ s) : erase s a = s :=
eq_of_veq <| erase_of_not_mem h
#align finset.erase_eq_of_not_mem Finset.erase_eq_of_not_mem
@[simp]
theorem erase_eq_self : s.erase a = s ↔ a ∉ s :=
⟨fun h => h ▸ not_mem_erase _ _, erase_eq_of_not_mem⟩
#align finset.erase_eq_self Finset.erase_eq_self
@[simp]
theorem erase_insert_eq_erase (s : Finset α) (a : α) : (insert a s).erase a = s.erase a :=
ext fun x => by
simp (config := { contextual := true }) only [mem_erase, mem_insert, and_congr_right_iff,
false_or_iff, iff_self_iff, imp_true_iff]
#align finset.erase_insert_eq_erase Finset.erase_insert_eq_erase
theorem erase_insert {a : α} {s : Finset α} (h : a ∉ s) : erase (insert a s) a = s := by
rw [erase_insert_eq_erase, erase_eq_of_not_mem h]
#align finset.erase_insert Finset.erase_insert
theorem erase_insert_of_ne {a b : α} {s : Finset α} (h : a ≠ b) :
erase (insert a s) b = insert a (erase s b) :=
ext fun x => by
have : x ≠ b ∧ x = a ↔ x = a := and_iff_right_of_imp fun hx => hx.symm ▸ h
simp only [mem_erase, mem_insert, and_or_left, this]
#align finset.erase_insert_of_ne Finset.erase_insert_of_ne
theorem erase_cons_of_ne {a b : α} {s : Finset α} (ha : a ∉ s) (hb : a ≠ b) :
erase (cons a s ha) b = cons a (erase s b) fun h => ha <| erase_subset _ _ h := by
simp only [cons_eq_insert, erase_insert_of_ne hb]
#align finset.erase_cons_of_ne Finset.erase_cons_of_ne
@[simp] theorem insert_erase (h : a ∈ s) : insert a (erase s a) = s :=
ext fun x => by
simp only [mem_insert, mem_erase, or_and_left, dec_em, true_and_iff]
apply or_iff_right_of_imp
rintro rfl
exact h
#align finset.insert_erase Finset.insert_erase
lemma erase_eq_iff_eq_insert (hs : a ∈ s) (ht : a ∉ t) : erase s a = t ↔ s = insert a t := by
aesop
lemma insert_erase_invOn :
Set.InvOn (insert a) (fun s ↦ erase s a) {s : Finset α | a ∈ s} {s : Finset α | a ∉ s} :=
⟨fun _s ↦ insert_erase, fun _s ↦ erase_insert⟩
theorem erase_subset_erase (a : α) {s t : Finset α} (h : s ⊆ t) : erase s a ⊆ erase t a :=
val_le_iff.1 <| erase_le_erase _ <| val_le_iff.2 h
#align finset.erase_subset_erase Finset.erase_subset_erase
theorem erase_subset (a : α) (s : Finset α) : erase s a ⊆ s :=
Multiset.erase_subset _ _
#align finset.erase_subset Finset.erase_subset
theorem subset_erase {a : α} {s t : Finset α} : s ⊆ t.erase a ↔ s ⊆ t ∧ a ∉ s :=
⟨fun h => ⟨h.trans (erase_subset _ _), fun ha => not_mem_erase _ _ (h ha)⟩,
fun h _b hb => mem_erase.2 ⟨ne_of_mem_of_not_mem hb h.2, h.1 hb⟩⟩
#align finset.subset_erase Finset.subset_erase
@[simp, norm_cast]
theorem coe_erase (a : α) (s : Finset α) : ↑(erase s a) = (s \ {a} : Set α) :=
Set.ext fun _ => mem_erase.trans <| by rw [and_comm, Set.mem_diff, Set.mem_singleton_iff, mem_coe]
#align finset.coe_erase Finset.coe_erase
theorem erase_ssubset {a : α} {s : Finset α} (h : a ∈ s) : s.erase a ⊂ s :=
calc
s.erase a ⊂ insert a (s.erase a) := ssubset_insert <| not_mem_erase _ _
_ = _ := insert_erase h
#align finset.erase_ssubset Finset.erase_ssubset
theorem ssubset_iff_exists_subset_erase {s t : Finset α} : s ⊂ t ↔ ∃ a ∈ t, s ⊆ t.erase a := by
refine ⟨fun h => ?_, fun ⟨a, ha, h⟩ => ssubset_of_subset_of_ssubset h <| erase_ssubset ha⟩
obtain ⟨a, ht, hs⟩ := not_subset.1 h.2
exact ⟨a, ht, subset_erase.2 ⟨h.1, hs⟩⟩
#align finset.ssubset_iff_exists_subset_erase Finset.ssubset_iff_exists_subset_erase
theorem erase_ssubset_insert (s : Finset α) (a : α) : s.erase a ⊂ insert a s :=
ssubset_iff_exists_subset_erase.2
⟨a, mem_insert_self _ _, erase_subset_erase _ <| subset_insert _ _⟩
#align finset.erase_ssubset_insert Finset.erase_ssubset_insert
theorem erase_ne_self : s.erase a ≠ s ↔ a ∈ s :=
erase_eq_self.not_left
#align finset.erase_ne_self Finset.erase_ne_self
theorem erase_cons {s : Finset α} {a : α} (h : a ∉ s) : (s.cons a h).erase a = s := by
rw [cons_eq_insert, erase_insert_eq_erase, erase_eq_of_not_mem h]
#align finset.erase_cons Finset.erase_cons
theorem erase_idem {a : α} {s : Finset α} : erase (erase s a) a = erase s a := by simp
#align finset.erase_idem Finset.erase_idem
theorem erase_right_comm {a b : α} {s : Finset α} : erase (erase s a) b = erase (erase s b) a := by
ext x
simp only [mem_erase, ← and_assoc]
rw [@and_comm (x ≠ a)]
#align finset.erase_right_comm Finset.erase_right_comm
theorem subset_insert_iff {a : α} {s t : Finset α} : s ⊆ insert a t ↔ erase s a ⊆ t := by
simp only [subset_iff, or_iff_not_imp_left, mem_erase, mem_insert, and_imp]
exact forall_congr' fun x => forall_swap
#align finset.subset_insert_iff Finset.subset_insert_iff
theorem erase_insert_subset (a : α) (s : Finset α) : erase (insert a s) a ⊆ s :=
subset_insert_iff.1 <| Subset.rfl
#align finset.erase_insert_subset Finset.erase_insert_subset
theorem insert_erase_subset (a : α) (s : Finset α) : s ⊆ insert a (erase s a) :=
subset_insert_iff.2 <| Subset.rfl
#align finset.insert_erase_subset Finset.insert_erase_subset
theorem subset_insert_iff_of_not_mem (h : a ∉ s) : s ⊆ insert a t ↔ s ⊆ t := by
rw [subset_insert_iff, erase_eq_of_not_mem h]
#align finset.subset_insert_iff_of_not_mem Finset.subset_insert_iff_of_not_mem
theorem erase_subset_iff_of_mem (h : a ∈ t) : s.erase a ⊆ t ↔ s ⊆ t := by
rw [← subset_insert_iff, insert_eq_of_mem h]
#align finset.erase_subset_iff_of_mem Finset.erase_subset_iff_of_mem
theorem erase_inj {x y : α} (s : Finset α) (hx : x ∈ s) : s.erase x = s.erase y ↔ x = y := by
refine ⟨fun h => eq_of_mem_of_not_mem_erase hx ?_, congr_arg _⟩
rw [← h]
simp
#align finset.erase_inj Finset.erase_inj
theorem erase_injOn (s : Finset α) : Set.InjOn s.erase s := fun _ _ _ _ => (erase_inj s ‹_›).mp
#align finset.erase_inj_on Finset.erase_injOn
theorem erase_injOn' (a : α) : { s : Finset α | a ∈ s }.InjOn fun s => erase s a :=
fun s hs t ht (h : s.erase a = _) => by rw [← insert_erase hs, ← insert_erase ht, h]
#align finset.erase_inj_on' Finset.erase_injOn'
end Erase
lemma Nontrivial.exists_cons_eq {s : Finset α} (hs : s.Nontrivial) :
∃ t a ha b hb hab, (cons b t hb).cons a (mem_cons.not.2 <| not_or_intro hab ha) = s := by
classical
obtain ⟨a, ha, b, hb, hab⟩ := hs
have : b ∈ s.erase a := mem_erase.2 ⟨hab.symm, hb⟩
refine ⟨(s.erase a).erase b, a, ?_, b, ?_, ?_, ?_⟩ <;>
simp [insert_erase this, insert_erase ha, *]
/-! ### sdiff -/
section Sdiff
variable [DecidableEq α] {s t u v : Finset α} {a b : α}
/-- `s \ t` is the set consisting of the elements of `s` that are not in `t`. -/
instance : SDiff (Finset α) :=
⟨fun s₁ s₂ => ⟨s₁.1 - s₂.1, nodup_of_le tsub_le_self s₁.2⟩⟩
@[simp]
theorem sdiff_val (s₁ s₂ : Finset α) : (s₁ \ s₂).val = s₁.val - s₂.val :=
rfl
#align finset.sdiff_val Finset.sdiff_val
@[simp]
theorem mem_sdiff : a ∈ s \ t ↔ a ∈ s ∧ a ∉ t :=
mem_sub_of_nodup s.2
#align finset.mem_sdiff Finset.mem_sdiff
@[simp]
theorem inter_sdiff_self (s₁ s₂ : Finset α) : s₁ ∩ (s₂ \ s₁) = ∅ :=
eq_empty_of_forall_not_mem <| by
simp only [mem_inter, mem_sdiff]; rintro x ⟨h, _, hn⟩; exact hn h
#align finset.inter_sdiff_self Finset.inter_sdiff_self
instance : GeneralizedBooleanAlgebra (Finset α) :=
{ sup_inf_sdiff := fun x y => by
simp only [ext_iff, mem_union, mem_sdiff, inf_eq_inter, sup_eq_union, mem_inter,
← and_or_left, em, and_true, implies_true]
inf_inf_sdiff := fun x y => by
simp only [ext_iff, inter_sdiff_self, inter_empty, inter_assoc, false_iff_iff, inf_eq_inter,
not_mem_empty, bot_eq_empty, not_false_iff, implies_true] }
theorem not_mem_sdiff_of_mem_right (h : a ∈ t) : a ∉ s \ t := by
simp only [mem_sdiff, h, not_true, not_false_iff, and_false_iff]
#align finset.not_mem_sdiff_of_mem_right Finset.not_mem_sdiff_of_mem_right
theorem not_mem_sdiff_of_not_mem_left (h : a ∉ s) : a ∉ s \ t := by simp [h]
#align finset.not_mem_sdiff_of_not_mem_left Finset.not_mem_sdiff_of_not_mem_left
theorem union_sdiff_of_subset (h : s ⊆ t) : s ∪ t \ s = t :=
sup_sdiff_cancel_right h
#align finset.union_sdiff_of_subset Finset.union_sdiff_of_subset
theorem sdiff_union_of_subset {s₁ s₂ : Finset α} (h : s₁ ⊆ s₂) : s₂ \ s₁ ∪ s₁ = s₂ :=
(union_comm _ _).trans (union_sdiff_of_subset h)
#align finset.sdiff_union_of_subset Finset.sdiff_union_of_subset
lemma inter_sdiff_assoc (s t u : Finset α) : (s ∩ t) \ u = s ∩ (t \ u) := by
ext x; simp [and_assoc]
@[deprecated inter_sdiff_assoc (since := "2024-05-01")]
theorem inter_sdiff (s t u : Finset α) : s ∩ (t \ u) = (s ∩ t) \ u := (inter_sdiff_assoc _ _ _).symm
#align finset.inter_sdiff Finset.inter_sdiff
@[simp]
theorem sdiff_inter_self (s₁ s₂ : Finset α) : s₂ \ s₁ ∩ s₁ = ∅ :=
inf_sdiff_self_left
#align finset.sdiff_inter_self Finset.sdiff_inter_self
-- Porting note (#10618): @[simp] can prove this
protected theorem sdiff_self (s₁ : Finset α) : s₁ \ s₁ = ∅ :=
_root_.sdiff_self
#align finset.sdiff_self Finset.sdiff_self
theorem sdiff_inter_distrib_right (s t u : Finset α) : s \ (t ∩ u) = s \ t ∪ s \ u :=
sdiff_inf
#align finset.sdiff_inter_distrib_right Finset.sdiff_inter_distrib_right
@[simp]
theorem sdiff_inter_self_left (s t : Finset α) : s \ (s ∩ t) = s \ t :=
sdiff_inf_self_left _ _
#align finset.sdiff_inter_self_left Finset.sdiff_inter_self_left
@[simp]
theorem sdiff_inter_self_right (s t : Finset α) : s \ (t ∩ s) = s \ t :=
sdiff_inf_self_right _ _
#align finset.sdiff_inter_self_right Finset.sdiff_inter_self_right
@[simp]
theorem sdiff_empty : s \ ∅ = s :=
sdiff_bot
#align finset.sdiff_empty Finset.sdiff_empty
@[mono, gcongr]
theorem sdiff_subset_sdiff (hst : s ⊆ t) (hvu : v ⊆ u) : s \ u ⊆ t \ v :=
sdiff_le_sdiff hst hvu
#align finset.sdiff_subset_sdiff Finset.sdiff_subset_sdiff
@[simp, norm_cast]
theorem coe_sdiff (s₁ s₂ : Finset α) : ↑(s₁ \ s₂) = (s₁ \ s₂ : Set α) :=
Set.ext fun _ => mem_sdiff
#align finset.coe_sdiff Finset.coe_sdiff
@[simp]
theorem union_sdiff_self_eq_union : s ∪ t \ s = s ∪ t :=
sup_sdiff_self_right _ _
#align finset.union_sdiff_self_eq_union Finset.union_sdiff_self_eq_union
@[simp]
theorem sdiff_union_self_eq_union : s \ t ∪ t = s ∪ t :=
sup_sdiff_self_left _ _
#align finset.sdiff_union_self_eq_union Finset.sdiff_union_self_eq_union
theorem union_sdiff_left (s t : Finset α) : (s ∪ t) \ s = t \ s :=
sup_sdiff_left_self
#align finset.union_sdiff_left Finset.union_sdiff_left
theorem union_sdiff_right (s t : Finset α) : (s ∪ t) \ t = s \ t :=
sup_sdiff_right_self
#align finset.union_sdiff_right Finset.union_sdiff_right
theorem union_sdiff_cancel_left (h : Disjoint s t) : (s ∪ t) \ s = t :=
h.sup_sdiff_cancel_left
#align finset.union_sdiff_cancel_left Finset.union_sdiff_cancel_left
theorem union_sdiff_cancel_right (h : Disjoint s t) : (s ∪ t) \ t = s :=
h.sup_sdiff_cancel_right
#align finset.union_sdiff_cancel_right Finset.union_sdiff_cancel_right
theorem union_sdiff_symm : s ∪ t \ s = t ∪ s \ t := by simp [union_comm]
#align finset.union_sdiff_symm Finset.union_sdiff_symm
theorem sdiff_union_inter (s t : Finset α) : s \ t ∪ s ∩ t = s :=
sup_sdiff_inf _ _
#align finset.sdiff_union_inter Finset.sdiff_union_inter
-- Porting note (#10618): @[simp] can prove this
theorem sdiff_idem (s t : Finset α) : (s \ t) \ t = s \ t :=
_root_.sdiff_idem
#align finset.sdiff_idem Finset.sdiff_idem
theorem subset_sdiff : s ⊆ t \ u ↔ s ⊆ t ∧ Disjoint s u :=
le_iff_subset.symm.trans le_sdiff
#align finset.subset_sdiff Finset.subset_sdiff
@[simp]
theorem sdiff_eq_empty_iff_subset : s \ t = ∅ ↔ s ⊆ t :=
sdiff_eq_bot_iff
#align finset.sdiff_eq_empty_iff_subset Finset.sdiff_eq_empty_iff_subset
theorem sdiff_nonempty : (s \ t).Nonempty ↔ ¬s ⊆ t :=
nonempty_iff_ne_empty.trans sdiff_eq_empty_iff_subset.not
#align finset.sdiff_nonempty Finset.sdiff_nonempty
@[simp]
theorem empty_sdiff (s : Finset α) : ∅ \ s = ∅ :=
bot_sdiff
#align finset.empty_sdiff Finset.empty_sdiff
theorem insert_sdiff_of_not_mem (s : Finset α) {t : Finset α} {x : α} (h : x ∉ t) :
insert x s \ t = insert x (s \ t) := by
rw [← coe_inj, coe_insert, coe_sdiff, coe_sdiff, coe_insert]
exact Set.insert_diff_of_not_mem _ h
#align finset.insert_sdiff_of_not_mem Finset.insert_sdiff_of_not_mem
theorem insert_sdiff_of_mem (s : Finset α) {x : α} (h : x ∈ t) : insert x s \ t = s \ t := by
rw [← coe_inj, coe_sdiff, coe_sdiff, coe_insert]
exact Set.insert_diff_of_mem _ h
#align finset.insert_sdiff_of_mem Finset.insert_sdiff_of_mem
@[simp] lemma insert_sdiff_cancel (ha : a ∉ s) : insert a s \ s = {a} := by
rw [insert_sdiff_of_not_mem _ ha, Finset.sdiff_self, insert_emptyc_eq]
@[simp]
theorem insert_sdiff_insert (s t : Finset α) (x : α) : insert x s \ insert x t = s \ insert x t :=
insert_sdiff_of_mem _ (mem_insert_self _ _)
#align finset.insert_sdiff_insert Finset.insert_sdiff_insert
lemma insert_sdiff_insert' (hab : a ≠ b) (ha : a ∉ s) : insert a s \ insert b s = {a} := by
ext; aesop
lemma erase_sdiff_erase (hab : a ≠ b) (hb : b ∈ s) : s.erase a \ s.erase b = {b} := by
ext; aesop
lemma cons_sdiff_cons (hab : a ≠ b) (ha hb) : s.cons a ha \ s.cons b hb = {a} := by
rw [cons_eq_insert, cons_eq_insert, insert_sdiff_insert' hab ha]
theorem sdiff_insert_of_not_mem {x : α} (h : x ∉ s) (t : Finset α) : s \ insert x t = s \ t := by
refine Subset.antisymm (sdiff_subset_sdiff (Subset.refl _) (subset_insert _ _)) fun y hy => ?_
simp only [mem_sdiff, mem_insert, not_or] at hy ⊢
exact ⟨hy.1, fun hxy => h <| hxy ▸ hy.1, hy.2⟩
#align finset.sdiff_insert_of_not_mem Finset.sdiff_insert_of_not_mem
@[simp] theorem sdiff_subset {s t : Finset α} : s \ t ⊆ s := le_iff_subset.mp sdiff_le
#align finset.sdiff_subset Finset.sdiff_subset
theorem sdiff_ssubset (h : t ⊆ s) (ht : t.Nonempty) : s \ t ⊂ s :=
sdiff_lt (le_iff_subset.mpr h) ht.ne_empty
#align finset.sdiff_ssubset Finset.sdiff_ssubset
theorem union_sdiff_distrib (s₁ s₂ t : Finset α) : (s₁ ∪ s₂) \ t = s₁ \ t ∪ s₂ \ t :=
sup_sdiff
#align finset.union_sdiff_distrib Finset.union_sdiff_distrib
theorem sdiff_union_distrib (s t₁ t₂ : Finset α) : s \ (t₁ ∪ t₂) = s \ t₁ ∩ (s \ t₂) :=
sdiff_sup
#align finset.sdiff_union_distrib Finset.sdiff_union_distrib
theorem union_sdiff_self (s t : Finset α) : (s ∪ t) \ t = s \ t :=
sup_sdiff_right_self
#align finset.union_sdiff_self Finset.union_sdiff_self
-- TODO: Do we want to delete this lemma and `Finset.disjUnion_singleton`,
-- or instead add `Finset.union_singleton`/`Finset.singleton_union`?
theorem sdiff_singleton_eq_erase (a : α) (s : Finset α) : s \ singleton a = erase s a := by
ext
rw [mem_erase, mem_sdiff, mem_singleton, and_comm]
#align finset.sdiff_singleton_eq_erase Finset.sdiff_singleton_eq_erase
-- This lemma matches `Finset.insert_eq` in functionality.
theorem erase_eq (s : Finset α) (a : α) : s.erase a = s \ {a} :=
(sdiff_singleton_eq_erase _ _).symm
#align finset.erase_eq Finset.erase_eq
theorem disjoint_erase_comm : Disjoint (s.erase a) t ↔ Disjoint s (t.erase a) := by
simp_rw [erase_eq, disjoint_sdiff_comm]
#align finset.disjoint_erase_comm Finset.disjoint_erase_comm
lemma disjoint_insert_erase (ha : a ∉ t) : Disjoint (s.erase a) (insert a t) ↔ Disjoint s t := by
rw [disjoint_erase_comm, erase_insert ha]
lemma disjoint_erase_insert (ha : a ∉ s) : Disjoint (insert a s) (t.erase a) ↔ Disjoint s t := by
rw [← disjoint_erase_comm, erase_insert ha]
theorem disjoint_of_erase_left (ha : a ∉ t) (hst : Disjoint (s.erase a) t) : Disjoint s t := by
rw [← erase_insert ha, ← disjoint_erase_comm, disjoint_insert_right]
exact ⟨not_mem_erase _ _, hst⟩
#align finset.disjoint_of_erase_left Finset.disjoint_of_erase_left
theorem disjoint_of_erase_right (ha : a ∉ s) (hst : Disjoint s (t.erase a)) : Disjoint s t := by
rw [← erase_insert ha, disjoint_erase_comm, disjoint_insert_left]
exact ⟨not_mem_erase _ _, hst⟩
#align finset.disjoint_of_erase_right Finset.disjoint_of_erase_right
theorem inter_erase (a : α) (s t : Finset α) : s ∩ t.erase a = (s ∩ t).erase a := by
simp only [erase_eq, inter_sdiff_assoc]
#align finset.inter_erase Finset.inter_erase
@[simp]
theorem erase_inter (a : α) (s t : Finset α) : s.erase a ∩ t = (s ∩ t).erase a := by
simpa only [inter_comm t] using inter_erase a t s
#align finset.erase_inter Finset.erase_inter
theorem erase_sdiff_comm (s t : Finset α) (a : α) : s.erase a \ t = (s \ t).erase a := by
simp_rw [erase_eq, sdiff_right_comm]
#align finset.erase_sdiff_comm Finset.erase_sdiff_comm
theorem insert_union_comm (s t : Finset α) (a : α) : insert a s ∪ t = s ∪ insert a t := by
rw [insert_union, union_insert]
#align finset.insert_union_comm Finset.insert_union_comm
theorem erase_inter_comm (s t : Finset α) (a : α) : s.erase a ∩ t = s ∩ t.erase a := by
rw [erase_inter, inter_erase]
#align finset.erase_inter_comm Finset.erase_inter_comm
theorem erase_union_distrib (s t : Finset α) (a : α) : (s ∪ t).erase a = s.erase a ∪ t.erase a := by
simp_rw [erase_eq, union_sdiff_distrib]
#align finset.erase_union_distrib Finset.erase_union_distrib
theorem insert_inter_distrib (s t : Finset α) (a : α) :
insert a (s ∩ t) = insert a s ∩ insert a t := by simp_rw [insert_eq, union_inter_distrib_left]
#align finset.insert_inter_distrib Finset.insert_inter_distrib
theorem erase_sdiff_distrib (s t : Finset α) (a : α) : (s \ t).erase a = s.erase a \ t.erase a := by
simp_rw [erase_eq, sdiff_sdiff, sup_sdiff_eq_sup le_rfl, sup_comm]
#align finset.erase_sdiff_distrib Finset.erase_sdiff_distrib
theorem erase_union_of_mem (ha : a ∈ t) (s : Finset α) : s.erase a ∪ t = s ∪ t := by
rw [← insert_erase (mem_union_right s ha), erase_union_distrib, ← union_insert, insert_erase ha]
#align finset.erase_union_of_mem Finset.erase_union_of_mem
theorem union_erase_of_mem (ha : a ∈ s) (t : Finset α) : s ∪ t.erase a = s ∪ t := by
rw [← insert_erase (mem_union_left t ha), erase_union_distrib, ← insert_union, insert_erase ha]
#align finset.union_erase_of_mem Finset.union_erase_of_mem
@[simp]
theorem sdiff_singleton_eq_self (ha : a ∉ s) : s \ {a} = s :=
sdiff_eq_self_iff_disjoint.2 <| by simp [ha]
#align finset.sdiff_singleton_eq_self Finset.sdiff_singleton_eq_self
| Mathlib/Data/Finset/Basic.lean | 2,369 | 2,373 | theorem Nontrivial.sdiff_singleton_nonempty {c : α} {s : Finset α} (hS : s.Nontrivial) :
(s \ {c}).Nonempty := by |
rw [Finset.sdiff_nonempty, Finset.subset_singleton_iff]
push_neg
exact ⟨by rintro rfl; exact Finset.not_nontrivial_empty hS, hS.ne_singleton⟩
|
/-
Copyright (c) 2022 Xavier Roblot. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Alex J. Best, Xavier Roblot
-/
import Mathlib.Analysis.Complex.Polynomial
import Mathlib.NumberTheory.NumberField.Norm
import Mathlib.NumberTheory.NumberField.Basic
import Mathlib.RingTheory.Norm
import Mathlib.Topology.Instances.Complex
import Mathlib.RingTheory.RootsOfUnity.Basic
#align_import number_theory.number_field.embeddings from "leanprover-community/mathlib"@"caa58cbf5bfb7f81ccbaca4e8b8ac4bc2b39cc1c"
/-!
# Embeddings of number fields
This file defines the embeddings of a number field into an algebraic closed field.
## Main Definitions and Results
* `NumberField.Embeddings.range_eval_eq_rootSet_minpoly`: let `x ∈ K` with `K` number field and
let `A` be an algebraic closed field of char. 0, then the images of `x` by the embeddings of `K`
in `A` are exactly the roots in `A` of the minimal polynomial of `x` over `ℚ`.
* `NumberField.Embeddings.pow_eq_one_of_norm_eq_one`: an algebraic integer whose conjugates are
all of norm one is a root of unity.
* `NumberField.InfinitePlace`: the type of infinite places of a number field `K`.
* `NumberField.InfinitePlace.mk_eq_iff`: two complex embeddings define the same infinite place iff
they are equal or complex conjugates.
* `NumberField.InfinitePlace.prod_eq_abs_norm`: the infinite part of the product formula, that is
for `x ∈ K`, we have `Π_w ‖x‖_w = |norm(x)|` where the product is over the infinite place `w` and
`‖·‖_w` is the normalized absolute value for `w`.
## Tags
number field, embeddings, places, infinite places
-/
open scoped Classical
namespace NumberField.Embeddings
section Fintype
open FiniteDimensional
variable (K : Type*) [Field K] [NumberField K]
variable (A : Type*) [Field A] [CharZero A]
/-- There are finitely many embeddings of a number field. -/
noncomputable instance : Fintype (K →+* A) :=
Fintype.ofEquiv (K →ₐ[ℚ] A) RingHom.equivRatAlgHom.symm
variable [IsAlgClosed A]
/-- The number of embeddings of a number field is equal to its finrank. -/
| Mathlib/NumberTheory/NumberField/Embeddings.lean | 54 | 55 | theorem card : Fintype.card (K →+* A) = finrank ℚ K := by |
rw [Fintype.ofEquiv_card RingHom.equivRatAlgHom.symm, AlgHom.card]
|
/-
Copyright (c) 2021 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca
-/
import Mathlib.Init.Core
import Mathlib.RingTheory.Polynomial.Cyclotomic.Roots
import Mathlib.NumberTheory.NumberField.Basic
import Mathlib.FieldTheory.Galois
#align_import number_theory.cyclotomic.basic from "leanprover-community/mathlib"@"4b05d3f4f0601dca8abf99c4ec99187682ed0bba"
/-!
# Cyclotomic extensions
Let `A` and `B` be commutative rings with `Algebra A B`. For `S : Set ℕ+`, we define a class
`IsCyclotomicExtension S A B` expressing the fact that `B` is obtained from `A` by adding `n`-th
primitive roots of unity, for all `n ∈ S`.
## Main definitions
* `IsCyclotomicExtension S A B` : means that `B` is obtained from `A` by adding `n`-th primitive
roots of unity, for all `n ∈ S`.
* `CyclotomicField`: given `n : ℕ+` and a field `K`, we define `CyclotomicField n K` as the
splitting field of `cyclotomic n K`. If `n` is nonzero in `K`, it has the instance
`IsCyclotomicExtension {n} K (CyclotomicField n K)`.
* `CyclotomicRing` : if `A` is a domain with fraction field `K` and `n : ℕ+`, we define
`CyclotomicRing n A K` as the `A`-subalgebra of `CyclotomicField n K` generated by the roots of
`X ^ n - 1`. If `n` is nonzero in `A`, it has the instance
`IsCyclotomicExtension {n} A (CyclotomicRing n A K)`.
## Main results
* `IsCyclotomicExtension.trans` : if `IsCyclotomicExtension S A B` and
`IsCyclotomicExtension T B C`, then `IsCyclotomicExtension (S ∪ T) A C` if
`Function.Injective (algebraMap B C)`.
* `IsCyclotomicExtension.union_right` : given `IsCyclotomicExtension (S ∪ T) A B`, then
`IsCyclotomicExtension T (adjoin A { b : B | ∃ a : ℕ+, a ∈ S ∧ b ^ (a : ℕ) = 1 }) B`.
* `IsCyclotomicExtension.union_left` : given `IsCyclotomicExtension T A B` and `S ⊆ T`, then
`IsCyclotomicExtension S A (adjoin A { b : B | ∃ a : ℕ+, a ∈ S ∧ b ^ (a : ℕ) = 1 })`.
* `IsCyclotomicExtension.finite` : if `S` is finite and `IsCyclotomicExtension S A B`, then
`B` is a finite `A`-algebra.
* `IsCyclotomicExtension.numberField` : a finite cyclotomic extension of a number field is a
number field.
* `IsCyclotomicExtension.isSplittingField_X_pow_sub_one` : if `IsCyclotomicExtension {n} K L`,
then `L` is the splitting field of `X ^ n - 1`.
* `IsCyclotomicExtension.splitting_field_cyclotomic` : if `IsCyclotomicExtension {n} K L`,
then `L` is the splitting field of `cyclotomic n K`.
## Implementation details
Our definition of `IsCyclotomicExtension` is very general, to allow rings of any characteristic
and infinite extensions, but it will mainly be used in the case `S = {n}` and for integral domains.
All results are in the `IsCyclotomicExtension` namespace.
Note that some results, for example `IsCyclotomicExtension.trans`,
`IsCyclotomicExtension.finite`, `IsCyclotomicExtension.numberField`,
`IsCyclotomicExtension.finiteDimensional`, `IsCyclotomicExtension.isGalois` and
`CyclotomicField.algebraBase` are lemmas, but they can be made local instances. Some of them are
included in the `Cyclotomic` locale.
-/
open Polynomial Algebra FiniteDimensional Set
universe u v w z
variable (n : ℕ+) (S T : Set ℕ+) (A : Type u) (B : Type v) (K : Type w) (L : Type z)
variable [CommRing A] [CommRing B] [Algebra A B]
variable [Field K] [Field L] [Algebra K L]
noncomputable section
/-- Given an `A`-algebra `B` and `S : Set ℕ+`, we define `IsCyclotomicExtension S A B` requiring
that there is an `n`-th primitive root of unity in `B` for all `n ∈ S` and that `B` is generated
over `A` by the roots of `X ^ n - 1`. -/
@[mk_iff]
class IsCyclotomicExtension : Prop where
/-- For all `n ∈ S`, there exists a primitive `n`-th root of unity in `B`. -/
exists_prim_root {n : ℕ+} (ha : n ∈ S) : ∃ r : B, IsPrimitiveRoot r n
/-- The `n`-th roots of unity, for `n ∈ S`, generate `B` as an `A`-algebra. -/
adjoin_roots : ∀ x : B, x ∈ adjoin A {b : B | ∃ n : ℕ+, n ∈ S ∧ b ^ (n : ℕ) = 1}
#align is_cyclotomic_extension IsCyclotomicExtension
namespace IsCyclotomicExtension
section Basic
/-- A reformulation of `IsCyclotomicExtension` that uses `⊤`. -/
theorem iff_adjoin_eq_top :
IsCyclotomicExtension S A B ↔
(∀ n : ℕ+, n ∈ S → ∃ r : B, IsPrimitiveRoot r n) ∧
adjoin A {b : B | ∃ n : ℕ+, n ∈ S ∧ b ^ (n : ℕ) = 1} = ⊤ :=
⟨fun h => ⟨fun _ => h.exists_prim_root, Algebra.eq_top_iff.2 h.adjoin_roots⟩, fun h =>
⟨h.1 _, Algebra.eq_top_iff.1 h.2⟩⟩
#align is_cyclotomic_extension.iff_adjoin_eq_top IsCyclotomicExtension.iff_adjoin_eq_top
/-- A reformulation of `IsCyclotomicExtension` in the case `S` is a singleton. -/
theorem iff_singleton :
IsCyclotomicExtension {n} A B ↔
(∃ r : B, IsPrimitiveRoot r n) ∧ ∀ x, x ∈ adjoin A {b : B | b ^ (n : ℕ) = 1} := by
simp [isCyclotomicExtension_iff]
#align is_cyclotomic_extension.iff_singleton IsCyclotomicExtension.iff_singleton
/-- If `IsCyclotomicExtension ∅ A B`, then the image of `A` in `B` equals `B`. -/
theorem empty [h : IsCyclotomicExtension ∅ A B] : (⊥ : Subalgebra A B) = ⊤ := by
simpa [Algebra.eq_top_iff, isCyclotomicExtension_iff] using h
#align is_cyclotomic_extension.empty IsCyclotomicExtension.empty
/-- If `IsCyclotomicExtension {1} A B`, then the image of `A` in `B` equals `B`. -/
theorem singleton_one [h : IsCyclotomicExtension {1} A B] : (⊥ : Subalgebra A B) = ⊤ :=
Algebra.eq_top_iff.2 fun x => by
simpa [adjoin_singleton_one] using ((isCyclotomicExtension_iff _ _ _).1 h).2 x
#align is_cyclotomic_extension.singleton_one IsCyclotomicExtension.singleton_one
variable {A B}
/-- If `(⊥ : SubAlgebra A B) = ⊤`, then `IsCyclotomicExtension ∅ A B`. -/
| Mathlib/NumberTheory/Cyclotomic/Basic.lean | 120 | 126 | theorem singleton_zero_of_bot_eq_top (h : (⊥ : Subalgebra A B) = ⊤) :
IsCyclotomicExtension ∅ A B := by |
-- Porting note: Lean3 is able to infer `A`.
refine (iff_adjoin_eq_top _ A _).2
⟨fun s hs => by simp at hs, _root_.eq_top_iff.2 fun x hx => ?_⟩
rw [← h] at hx
simpa using hx
|
/-
Copyright (c) 2022 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth
-/
import Mathlib.Analysis.InnerProductSpace.Dual
import Mathlib.Analysis.InnerProductSpace.Orientation
import Mathlib.Data.Complex.Orientation
import Mathlib.Tactic.LinearCombination
#align_import analysis.inner_product_space.two_dim from "leanprover-community/mathlib"@"cd8fafa2fac98e1a67097e8a91ad9901cfde48af"
/-!
# Oriented two-dimensional real inner product spaces
This file defines constructions specific to the geometry of an oriented two-dimensional real inner
product space `E`.
## Main declarations
* `Orientation.areaForm`: an antisymmetric bilinear form `E →ₗ[ℝ] E →ₗ[ℝ] ℝ` (usual notation `ω`).
Morally, when `ω` is evaluated on two vectors, it gives the oriented area of the parallelogram
they span. (But mathlib does not yet have a construction of oriented area, and in fact the
construction of oriented area should pass through `ω`.)
* `Orientation.rightAngleRotation`: an isometric automorphism `E ≃ₗᵢ[ℝ] E` (usual notation `J`).
This automorphism squares to -1. In a later file, rotations (`Orientation.rotation`) are defined,
in such a way that this automorphism is equal to rotation by 90 degrees.
* `Orientation.basisRightAngleRotation`: for a nonzero vector `x` in `E`, the basis `![x, J x]`
for `E`.
* `Orientation.kahler`: a complex-valued real-bilinear map `E →ₗ[ℝ] E →ₗ[ℝ] ℂ`. Its real part is the
inner product and its imaginary part is `Orientation.areaForm`. For vectors `x` and `y` in `E`,
the complex number `o.kahler x y` has modulus `‖x‖ * ‖y‖`. In a later file, oriented angles
(`Orientation.oangle`) are defined, in such a way that the argument of `o.kahler x y` is the
oriented angle from `x` to `y`.
## Main results
* `Orientation.rightAngleRotation_rightAngleRotation`: the identity `J (J x) = - x`
* `Orientation.nonneg_inner_and_areaForm_eq_zero_iff_sameRay`: `x`, `y` are in the same ray, if
and only if `0 ≤ ⟪x, y⟫` and `ω x y = 0`
* `Orientation.kahler_mul`: the identity `o.kahler x a * o.kahler a y = ‖a‖ ^ 2 * o.kahler x y`
* `Complex.areaForm`, `Complex.rightAngleRotation`, `Complex.kahler`: the concrete
interpretations of `areaForm`, `rightAngleRotation`, `kahler` for the oriented real inner
product space `ℂ`
* `Orientation.areaForm_map_complex`, `Orientation.rightAngleRotation_map_complex`,
`Orientation.kahler_map_complex`: given an orientation-preserving isometry from `E` to `ℂ`,
expressions for `areaForm`, `rightAngleRotation`, `kahler` as the pullback of their concrete
interpretations on `ℂ`
## Implementation notes
Notation `ω` for `Orientation.areaForm` and `J` for `Orientation.rightAngleRotation` should be
defined locally in each file which uses them, since otherwise one would need a more cumbersome
notation which mentions the orientation explicitly (something like `ω[o]`). Write
```
local notation "ω" => o.areaForm
local notation "J" => o.rightAngleRotation
```
-/
noncomputable section
open scoped RealInnerProductSpace ComplexConjugate
open FiniteDimensional
lemma FiniteDimensional.of_fact_finrank_eq_two {K V : Type*} [DivisionRing K]
[AddCommGroup V] [Module K V] [Fact (finrank K V = 2)] : FiniteDimensional K V :=
.of_fact_finrank_eq_succ 1
attribute [local instance] FiniteDimensional.of_fact_finrank_eq_two
@[deprecated (since := "2024-02-02")]
alias FiniteDimensional.finiteDimensional_of_fact_finrank_eq_two :=
FiniteDimensional.of_fact_finrank_eq_two
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E] [Fact (finrank ℝ E = 2)]
(o : Orientation ℝ E (Fin 2))
namespace Orientation
/-- An antisymmetric bilinear form on an oriented real inner product space of dimension 2 (usual
notation `ω`). When evaluated on two vectors, it gives the oriented area of the parallelogram they
span. -/
irreducible_def areaForm : E →ₗ[ℝ] E →ₗ[ℝ] ℝ := by
let z : E [⋀^Fin 0]→ₗ[ℝ] ℝ ≃ₗ[ℝ] ℝ :=
AlternatingMap.constLinearEquivOfIsEmpty.symm
let y : E [⋀^Fin 1]→ₗ[ℝ] ℝ →ₗ[ℝ] E →ₗ[ℝ] ℝ :=
LinearMap.llcomp ℝ E (E [⋀^Fin 0]→ₗ[ℝ] ℝ) ℝ z ∘ₗ AlternatingMap.curryLeftLinearMap
exact y ∘ₗ AlternatingMap.curryLeftLinearMap (R' := ℝ) o.volumeForm
#align orientation.area_form Orientation.areaForm
local notation "ω" => o.areaForm
theorem areaForm_to_volumeForm (x y : E) : ω x y = o.volumeForm ![x, y] := by simp [areaForm]
#align orientation.area_form_to_volume_form Orientation.areaForm_to_volumeForm
@[simp]
theorem areaForm_apply_self (x : E) : ω x x = 0 := by
rw [areaForm_to_volumeForm]
refine o.volumeForm.map_eq_zero_of_eq ![x, x] ?_ (?_ : (0 : Fin 2) ≠ 1)
· simp
· norm_num
#align orientation.area_form_apply_self Orientation.areaForm_apply_self
theorem areaForm_swap (x y : E) : ω x y = -ω y x := by
simp only [areaForm_to_volumeForm]
convert o.volumeForm.map_swap ![y, x] (_ : (0 : Fin 2) ≠ 1)
· ext i
fin_cases i <;> rfl
· norm_num
#align orientation.area_form_swap Orientation.areaForm_swap
@[simp]
theorem areaForm_neg_orientation : (-o).areaForm = -o.areaForm := by
ext x y
simp [areaForm_to_volumeForm]
#align orientation.area_form_neg_orientation Orientation.areaForm_neg_orientation
/-- Continuous linear map version of `Orientation.areaForm`, useful for calculus. -/
def areaForm' : E →L[ℝ] E →L[ℝ] ℝ :=
LinearMap.toContinuousLinearMap
(↑(LinearMap.toContinuousLinearMap : (E →ₗ[ℝ] ℝ) ≃ₗ[ℝ] E →L[ℝ] ℝ) ∘ₗ o.areaForm)
#align orientation.area_form' Orientation.areaForm'
@[simp]
theorem areaForm'_apply (x : E) :
o.areaForm' x = LinearMap.toContinuousLinearMap (o.areaForm x) :=
rfl
#align orientation.area_form'_apply Orientation.areaForm'_apply
theorem abs_areaForm_le (x y : E) : |ω x y| ≤ ‖x‖ * ‖y‖ := by
simpa [areaForm_to_volumeForm, Fin.prod_univ_succ] using o.abs_volumeForm_apply_le ![x, y]
#align orientation.abs_area_form_le Orientation.abs_areaForm_le
theorem areaForm_le (x y : E) : ω x y ≤ ‖x‖ * ‖y‖ := by
simpa [areaForm_to_volumeForm, Fin.prod_univ_succ] using o.volumeForm_apply_le ![x, y]
#align orientation.area_form_le Orientation.areaForm_le
theorem abs_areaForm_of_orthogonal {x y : E} (h : ⟪x, y⟫ = 0) : |ω x y| = ‖x‖ * ‖y‖ := by
rw [o.areaForm_to_volumeForm, o.abs_volumeForm_apply_of_pairwise_orthogonal]
· simp [Fin.prod_univ_succ]
intro i j hij
fin_cases i <;> fin_cases j
· simp_all
· simpa using h
· simpa [real_inner_comm] using h
· simp_all
#align orientation.abs_area_form_of_orthogonal Orientation.abs_areaForm_of_orthogonal
theorem areaForm_map {F : Type*} [NormedAddCommGroup F] [InnerProductSpace ℝ F]
[hF : Fact (finrank ℝ F = 2)] (φ : E ≃ₗᵢ[ℝ] F) (x y : F) :
(Orientation.map (Fin 2) φ.toLinearEquiv o).areaForm x y =
o.areaForm (φ.symm x) (φ.symm y) := by
have : φ.symm ∘ ![x, y] = ![φ.symm x, φ.symm y] := by
ext i
fin_cases i <;> rfl
simp [areaForm_to_volumeForm, volumeForm_map, this]
#align orientation.area_form_map Orientation.areaForm_map
/-- The area form is invariant under pullback by a positively-oriented isometric automorphism. -/
theorem areaForm_comp_linearIsometryEquiv (φ : E ≃ₗᵢ[ℝ] E)
(hφ : 0 < LinearMap.det (φ.toLinearEquiv : E →ₗ[ℝ] E)) (x y : E) :
o.areaForm (φ x) (φ y) = o.areaForm x y := by
convert o.areaForm_map φ (φ x) (φ y)
· symm
rwa [← o.map_eq_iff_det_pos φ.toLinearEquiv] at hφ
rw [@Fact.out (finrank ℝ E = 2), Fintype.card_fin]
· simp
· simp
#align orientation.area_form_comp_linear_isometry_equiv Orientation.areaForm_comp_linearIsometryEquiv
/-- Auxiliary construction for `Orientation.rightAngleRotation`, rotation by 90 degrees in an
oriented real inner product space of dimension 2. -/
irreducible_def rightAngleRotationAux₁ : E →ₗ[ℝ] E :=
let to_dual : E ≃ₗ[ℝ] E →ₗ[ℝ] ℝ :=
(InnerProductSpace.toDual ℝ E).toLinearEquiv ≪≫ₗ LinearMap.toContinuousLinearMap.symm
↑to_dual.symm ∘ₗ ω
#align orientation.right_angle_rotation_aux₁ Orientation.rightAngleRotationAux₁
@[simp]
theorem inner_rightAngleRotationAux₁_left (x y : E) : ⟪o.rightAngleRotationAux₁ x, y⟫ = ω x y := by
-- Porting note: split `simp only` for greater proof control
simp only [rightAngleRotationAux₁, LinearEquiv.trans_symm, LinearIsometryEquiv.toLinearEquiv_symm,
LinearMap.coe_comp, LinearEquiv.coe_coe, Function.comp_apply, LinearEquiv.trans_apply,
LinearIsometryEquiv.coe_toLinearEquiv]
rw [InnerProductSpace.toDual_symm_apply]
norm_cast
#align orientation.inner_right_angle_rotation_aux₁_left Orientation.inner_rightAngleRotationAux₁_left
@[simp]
theorem inner_rightAngleRotationAux₁_right (x y : E) :
⟪x, o.rightAngleRotationAux₁ y⟫ = -ω x y := by
rw [real_inner_comm]
simp [o.areaForm_swap y x]
#align orientation.inner_right_angle_rotation_aux₁_right Orientation.inner_rightAngleRotationAux₁_right
/-- Auxiliary construction for `Orientation.rightAngleRotation`, rotation by 90 degrees in an
oriented real inner product space of dimension 2. -/
def rightAngleRotationAux₂ : E →ₗᵢ[ℝ] E :=
{ o.rightAngleRotationAux₁ with
norm_map' := fun x => by
dsimp
refine le_antisymm ?_ ?_
· cases' eq_or_lt_of_le (norm_nonneg (o.rightAngleRotationAux₁ x)) with h h
· rw [← h]
positivity
refine le_of_mul_le_mul_right ?_ h
rw [← real_inner_self_eq_norm_mul_norm, o.inner_rightAngleRotationAux₁_left]
exact o.areaForm_le x (o.rightAngleRotationAux₁ x)
· let K : Submodule ℝ E := ℝ ∙ x
have : Nontrivial Kᗮ := by
apply @FiniteDimensional.nontrivial_of_finrank_pos ℝ
have : finrank ℝ K ≤ Finset.card {x} := by
rw [← Set.toFinset_singleton]
exact finrank_span_le_card ({x} : Set E)
have : Finset.card {x} = 1 := Finset.card_singleton x
have : finrank ℝ K + finrank ℝ Kᗮ = finrank ℝ E := K.finrank_add_finrank_orthogonal
have : finrank ℝ E = 2 := Fact.out
linarith
obtain ⟨w, hw₀⟩ : ∃ w : Kᗮ, w ≠ 0 := exists_ne 0
have hw' : ⟪x, (w : E)⟫ = 0 := Submodule.mem_orthogonal_singleton_iff_inner_right.mp w.2
have hw : (w : E) ≠ 0 := fun h => hw₀ (Submodule.coe_eq_zero.mp h)
refine le_of_mul_le_mul_right ?_ (by rwa [norm_pos_iff] : 0 < ‖(w : E)‖)
rw [← o.abs_areaForm_of_orthogonal hw']
rw [← o.inner_rightAngleRotationAux₁_left x w]
exact abs_real_inner_le_norm (o.rightAngleRotationAux₁ x) w }
#align orientation.right_angle_rotation_aux₂ Orientation.rightAngleRotationAux₂
@[simp]
theorem rightAngleRotationAux₁_rightAngleRotationAux₁ (x : E) :
o.rightAngleRotationAux₁ (o.rightAngleRotationAux₁ x) = -x := by
apply ext_inner_left ℝ
intro y
have : ⟪o.rightAngleRotationAux₁ y, o.rightAngleRotationAux₁ x⟫ = ⟪y, x⟫ :=
LinearIsometry.inner_map_map o.rightAngleRotationAux₂ y x
rw [o.inner_rightAngleRotationAux₁_right, ← o.inner_rightAngleRotationAux₁_left, this,
inner_neg_right]
#align orientation.right_angle_rotation_aux₁_right_angle_rotation_aux₁ Orientation.rightAngleRotationAux₁_rightAngleRotationAux₁
/-- An isometric automorphism of an oriented real inner product space of dimension 2 (usual notation
`J`). This automorphism squares to -1. We will define rotations in such a way that this
automorphism is equal to rotation by 90 degrees. -/
irreducible_def rightAngleRotation : E ≃ₗᵢ[ℝ] E :=
LinearIsometryEquiv.ofLinearIsometry o.rightAngleRotationAux₂ (-o.rightAngleRotationAux₁)
(by ext; simp [rightAngleRotationAux₂]) (by ext; simp [rightAngleRotationAux₂])
#align orientation.right_angle_rotation Orientation.rightAngleRotation
local notation "J" => o.rightAngleRotation
@[simp]
theorem inner_rightAngleRotation_left (x y : E) : ⟪J x, y⟫ = ω x y := by
rw [rightAngleRotation]
exact o.inner_rightAngleRotationAux₁_left x y
#align orientation.inner_right_angle_rotation_left Orientation.inner_rightAngleRotation_left
@[simp]
theorem inner_rightAngleRotation_right (x y : E) : ⟪x, J y⟫ = -ω x y := by
rw [rightAngleRotation]
exact o.inner_rightAngleRotationAux₁_right x y
#align orientation.inner_right_angle_rotation_right Orientation.inner_rightAngleRotation_right
@[simp]
theorem rightAngleRotation_rightAngleRotation (x : E) : J (J x) = -x := by
rw [rightAngleRotation]
exact o.rightAngleRotationAux₁_rightAngleRotationAux₁ x
#align orientation.right_angle_rotation_right_angle_rotation Orientation.rightAngleRotation_rightAngleRotation
@[simp]
theorem rightAngleRotation_symm :
LinearIsometryEquiv.symm J = LinearIsometryEquiv.trans J (LinearIsometryEquiv.neg ℝ) := by
rw [rightAngleRotation]
exact LinearIsometryEquiv.toLinearIsometry_injective rfl
#align orientation.right_angle_rotation_symm Orientation.rightAngleRotation_symm
-- @[simp] -- Porting note (#10618): simp already proves this
theorem inner_rightAngleRotation_self (x : E) : ⟪J x, x⟫ = 0 := by simp
#align orientation.inner_right_angle_rotation_self Orientation.inner_rightAngleRotation_self
theorem inner_rightAngleRotation_swap (x y : E) : ⟪x, J y⟫ = -⟪J x, y⟫ := by simp
#align orientation.inner_right_angle_rotation_swap Orientation.inner_rightAngleRotation_swap
theorem inner_rightAngleRotation_swap' (x y : E) : ⟪J x, y⟫ = -⟪x, J y⟫ := by
simp [o.inner_rightAngleRotation_swap x y]
#align orientation.inner_right_angle_rotation_swap' Orientation.inner_rightAngleRotation_swap'
theorem inner_comp_rightAngleRotation (x y : E) : ⟪J x, J y⟫ = ⟪x, y⟫ :=
LinearIsometryEquiv.inner_map_map J x y
#align orientation.inner_comp_right_angle_rotation Orientation.inner_comp_rightAngleRotation
@[simp]
theorem areaForm_rightAngleRotation_left (x y : E) : ω (J x) y = -⟪x, y⟫ := by
rw [← o.inner_comp_rightAngleRotation, o.inner_rightAngleRotation_right, neg_neg]
#align orientation.area_form_right_angle_rotation_left Orientation.areaForm_rightAngleRotation_left
@[simp]
theorem areaForm_rightAngleRotation_right (x y : E) : ω x (J y) = ⟪x, y⟫ := by
rw [← o.inner_rightAngleRotation_left, o.inner_comp_rightAngleRotation]
#align orientation.area_form_right_angle_rotation_right Orientation.areaForm_rightAngleRotation_right
-- @[simp] -- Porting note (#10618): simp already proves this
theorem areaForm_comp_rightAngleRotation (x y : E) : ω (J x) (J y) = ω x y := by simp
#align orientation.area_form_comp_right_angle_rotation Orientation.areaForm_comp_rightAngleRotation
@[simp]
theorem rightAngleRotation_trans_rightAngleRotation :
LinearIsometryEquiv.trans J J = LinearIsometryEquiv.neg ℝ := by ext; simp
#align orientation.right_angle_rotation_trans_right_angle_rotation Orientation.rightAngleRotation_trans_rightAngleRotation
theorem rightAngleRotation_neg_orientation (x : E) :
(-o).rightAngleRotation x = -o.rightAngleRotation x := by
apply ext_inner_right ℝ
intro y
rw [inner_rightAngleRotation_left]
simp
#align orientation.right_angle_rotation_neg_orientation Orientation.rightAngleRotation_neg_orientation
@[simp]
theorem rightAngleRotation_trans_neg_orientation :
(-o).rightAngleRotation = o.rightAngleRotation.trans (LinearIsometryEquiv.neg ℝ) :=
LinearIsometryEquiv.ext <| o.rightAngleRotation_neg_orientation
#align orientation.right_angle_rotation_trans_neg_orientation Orientation.rightAngleRotation_trans_neg_orientation
theorem rightAngleRotation_map {F : Type*} [NormedAddCommGroup F] [InnerProductSpace ℝ F]
[hF : Fact (finrank ℝ F = 2)] (φ : E ≃ₗᵢ[ℝ] F) (x : F) :
(Orientation.map (Fin 2) φ.toLinearEquiv o).rightAngleRotation x =
φ (o.rightAngleRotation (φ.symm x)) := by
apply ext_inner_right ℝ
intro y
rw [inner_rightAngleRotation_left]
trans ⟪J (φ.symm x), φ.symm y⟫
· simp [o.areaForm_map]
trans ⟪φ (J (φ.symm x)), φ (φ.symm y)⟫
· rw [φ.inner_map_map]
· simp
#align orientation.right_angle_rotation_map Orientation.rightAngleRotation_map
/-- `J` commutes with any positively-oriented isometric automorphism. -/
theorem linearIsometryEquiv_comp_rightAngleRotation (φ : E ≃ₗᵢ[ℝ] E)
(hφ : 0 < LinearMap.det (φ.toLinearEquiv : E →ₗ[ℝ] E)) (x : E) : φ (J x) = J (φ x) := by
convert (o.rightAngleRotation_map φ (φ x)).symm
· simp
· symm
rwa [← o.map_eq_iff_det_pos φ.toLinearEquiv] at hφ
rw [@Fact.out (finrank ℝ E = 2), Fintype.card_fin]
#align orientation.linear_isometry_equiv_comp_right_angle_rotation Orientation.linearIsometryEquiv_comp_rightAngleRotation
theorem rightAngleRotation_map' {F : Type*} [NormedAddCommGroup F] [InnerProductSpace ℝ F]
[Fact (finrank ℝ F = 2)] (φ : E ≃ₗᵢ[ℝ] F) :
(Orientation.map (Fin 2) φ.toLinearEquiv o).rightAngleRotation =
(φ.symm.trans o.rightAngleRotation).trans φ :=
LinearIsometryEquiv.ext <| o.rightAngleRotation_map φ
#align orientation.right_angle_rotation_map' Orientation.rightAngleRotation_map'
/-- `J` commutes with any positively-oriented isometric automorphism. -/
theorem linearIsometryEquiv_comp_rightAngleRotation' (φ : E ≃ₗᵢ[ℝ] E)
(hφ : 0 < LinearMap.det (φ.toLinearEquiv : E →ₗ[ℝ] E)) :
LinearIsometryEquiv.trans J φ = φ.trans J :=
LinearIsometryEquiv.ext <| o.linearIsometryEquiv_comp_rightAngleRotation φ hφ
#align orientation.linear_isometry_equiv_comp_right_angle_rotation' Orientation.linearIsometryEquiv_comp_rightAngleRotation'
/-- For a nonzero vector `x` in an oriented two-dimensional real inner product space `E`,
`![x, J x]` forms an (orthogonal) basis for `E`. -/
def basisRightAngleRotation (x : E) (hx : x ≠ 0) : Basis (Fin 2) ℝ E :=
@basisOfLinearIndependentOfCardEqFinrank ℝ _ _ _ _ _ _ _ ![x, J x]
(linearIndependent_of_ne_zero_of_inner_eq_zero (fun i => by fin_cases i <;> simp [hx])
(by
intro i j hij
fin_cases i <;> fin_cases j <;> simp_all))
(@Fact.out (finrank ℝ E = 2)).symm
#align orientation.basis_right_angle_rotation Orientation.basisRightAngleRotation
@[simp]
theorem coe_basisRightAngleRotation (x : E) (hx : x ≠ 0) :
⇑(o.basisRightAngleRotation x hx) = ![x, J x] :=
coe_basisOfLinearIndependentOfCardEqFinrank _ _
#align orientation.coe_basis_right_angle_rotation Orientation.coe_basisRightAngleRotation
/-- For vectors `a x y : E`, the identity `⟪a, x⟫ * ⟪a, y⟫ + ω a x * ω a y = ‖a‖ ^ 2 * ⟪x, y⟫`. (See
`Orientation.inner_mul_inner_add_areaForm_mul_areaForm` for the "applied" form.)-/
theorem inner_mul_inner_add_areaForm_mul_areaForm' (a x : E) :
⟪a, x⟫ • innerₛₗ ℝ a + ω a x • ω a = ‖a‖ ^ 2 • innerₛₗ ℝ x := by
by_cases ha : a = 0
· simp [ha]
apply (o.basisRightAngleRotation a ha).ext
intro i
fin_cases i
· simp only [Fin.mk_zero, coe_basisRightAngleRotation, Matrix.cons_val_zero, LinearMap.add_apply,
LinearMap.smul_apply, innerₛₗ_apply, real_inner_self_eq_norm_sq, smul_eq_mul,
areaForm_apply_self, mul_zero, add_zero, Real.rpow_two, real_inner_comm]
ring
· simp only [Fin.mk_one, coe_basisRightAngleRotation, Matrix.cons_val_one, Matrix.head_cons,
LinearMap.add_apply, LinearMap.smul_apply, innerₛₗ_apply, inner_rightAngleRotation_right,
areaForm_apply_self, neg_zero, smul_eq_mul, mul_zero, areaForm_rightAngleRotation_right,
real_inner_self_eq_norm_sq, zero_add, Real.rpow_two, mul_neg]
rw [o.areaForm_swap]
ring
#align orientation.inner_mul_inner_add_area_form_mul_area_form' Orientation.inner_mul_inner_add_areaForm_mul_areaForm'
/-- For vectors `a x y : E`, the identity `⟪a, x⟫ * ⟪a, y⟫ + ω a x * ω a y = ‖a‖ ^ 2 * ⟪x, y⟫`. -/
theorem inner_mul_inner_add_areaForm_mul_areaForm (a x y : E) :
⟪a, x⟫ * ⟪a, y⟫ + ω a x * ω a y = ‖a‖ ^ 2 * ⟪x, y⟫ :=
congr_arg (fun f : E →ₗ[ℝ] ℝ => f y) (o.inner_mul_inner_add_areaForm_mul_areaForm' a x)
#align orientation.inner_mul_inner_add_area_form_mul_area_form Orientation.inner_mul_inner_add_areaForm_mul_areaForm
| Mathlib/Analysis/InnerProductSpace/TwoDim.lean | 416 | 417 | theorem inner_sq_add_areaForm_sq (a b : E) : ⟪a, b⟫ ^ 2 + ω a b ^ 2 = ‖a‖ ^ 2 * ‖b‖ ^ 2 := by |
simpa [sq, real_inner_self_eq_norm_sq] using o.inner_mul_inner_add_areaForm_mul_areaForm a b b
|
/-
Copyright (c) 2018 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes, Abhimanyu Pallavi Sudhir, Jean Lo, Calle Sönne, Benjamin Davidson
-/
import Mathlib.Analysis.SpecialFunctions.Exp
import Mathlib.Tactic.Positivity.Core
import Mathlib.Algebra.Ring.NegOnePow
#align_import analysis.special_functions.trigonometric.basic from "leanprover-community/mathlib"@"2c1d8ca2812b64f88992a5294ea3dba144755cd1"
/-!
# Trigonometric functions
## Main definitions
This file contains the definition of `π`.
See also `Analysis.SpecialFunctions.Trigonometric.Inverse` and
`Analysis.SpecialFunctions.Trigonometric.Arctan` for the inverse trigonometric functions.
See also `Analysis.SpecialFunctions.Complex.Arg` and
`Analysis.SpecialFunctions.Complex.Log` for the complex argument function
and the complex logarithm.
## Main statements
Many basic inequalities on the real trigonometric functions are established.
The continuity of the usual trigonometric functions is proved.
Several facts about the real trigonometric functions have the proofs deferred to
`Analysis.SpecialFunctions.Trigonometric.Complex`,
as they are most easily proved by appealing to the corresponding fact for
complex trigonometric functions.
See also `Analysis.SpecialFunctions.Trigonometric.Chebyshev` for the multiple angle formulas
in terms of Chebyshev polynomials.
## Tags
sin, cos, tan, angle
-/
noncomputable section
open scoped Classical
open Topology Filter Set
namespace Complex
@[continuity, fun_prop]
theorem continuous_sin : Continuous sin := by
change Continuous fun z => (exp (-z * I) - exp (z * I)) * I / 2
continuity
#align complex.continuous_sin Complex.continuous_sin
@[fun_prop]
theorem continuousOn_sin {s : Set ℂ} : ContinuousOn sin s :=
continuous_sin.continuousOn
#align complex.continuous_on_sin Complex.continuousOn_sin
@[continuity, fun_prop]
theorem continuous_cos : Continuous cos := by
change Continuous fun z => (exp (z * I) + exp (-z * I)) / 2
continuity
#align complex.continuous_cos Complex.continuous_cos
@[fun_prop]
theorem continuousOn_cos {s : Set ℂ} : ContinuousOn cos s :=
continuous_cos.continuousOn
#align complex.continuous_on_cos Complex.continuousOn_cos
@[continuity, fun_prop]
theorem continuous_sinh : Continuous sinh := by
change Continuous fun z => (exp z - exp (-z)) / 2
continuity
#align complex.continuous_sinh Complex.continuous_sinh
@[continuity, fun_prop]
theorem continuous_cosh : Continuous cosh := by
change Continuous fun z => (exp z + exp (-z)) / 2
continuity
#align complex.continuous_cosh Complex.continuous_cosh
end Complex
namespace Real
variable {x y z : ℝ}
@[continuity, fun_prop]
theorem continuous_sin : Continuous sin :=
Complex.continuous_re.comp (Complex.continuous_sin.comp Complex.continuous_ofReal)
#align real.continuous_sin Real.continuous_sin
@[fun_prop]
theorem continuousOn_sin {s} : ContinuousOn sin s :=
continuous_sin.continuousOn
#align real.continuous_on_sin Real.continuousOn_sin
@[continuity, fun_prop]
theorem continuous_cos : Continuous cos :=
Complex.continuous_re.comp (Complex.continuous_cos.comp Complex.continuous_ofReal)
#align real.continuous_cos Real.continuous_cos
@[fun_prop]
theorem continuousOn_cos {s} : ContinuousOn cos s :=
continuous_cos.continuousOn
#align real.continuous_on_cos Real.continuousOn_cos
@[continuity, fun_prop]
theorem continuous_sinh : Continuous sinh :=
Complex.continuous_re.comp (Complex.continuous_sinh.comp Complex.continuous_ofReal)
#align real.continuous_sinh Real.continuous_sinh
@[continuity, fun_prop]
theorem continuous_cosh : Continuous cosh :=
Complex.continuous_re.comp (Complex.continuous_cosh.comp Complex.continuous_ofReal)
#align real.continuous_cosh Real.continuous_cosh
end Real
namespace Real
theorem exists_cos_eq_zero : 0 ∈ cos '' Icc (1 : ℝ) 2 :=
intermediate_value_Icc' (by norm_num) continuousOn_cos
⟨le_of_lt cos_two_neg, le_of_lt cos_one_pos⟩
#align real.exists_cos_eq_zero Real.exists_cos_eq_zero
/-- The number π = 3.14159265... Defined here using choice as twice a zero of cos in [1,2], from
which one can derive all its properties. For explicit bounds on π, see `Data.Real.Pi.Bounds`. -/
protected noncomputable def pi : ℝ :=
2 * Classical.choose exists_cos_eq_zero
#align real.pi Real.pi
@[inherit_doc]
scoped notation "π" => Real.pi
@[simp]
theorem cos_pi_div_two : cos (π / 2) = 0 := by
rw [Real.pi, mul_div_cancel_left₀ _ (two_ne_zero' ℝ)]
exact (Classical.choose_spec exists_cos_eq_zero).2
#align real.cos_pi_div_two Real.cos_pi_div_two
theorem one_le_pi_div_two : (1 : ℝ) ≤ π / 2 := by
rw [Real.pi, mul_div_cancel_left₀ _ (two_ne_zero' ℝ)]
exact (Classical.choose_spec exists_cos_eq_zero).1.1
#align real.one_le_pi_div_two Real.one_le_pi_div_two
theorem pi_div_two_le_two : π / 2 ≤ 2 := by
rw [Real.pi, mul_div_cancel_left₀ _ (two_ne_zero' ℝ)]
exact (Classical.choose_spec exists_cos_eq_zero).1.2
#align real.pi_div_two_le_two Real.pi_div_two_le_two
theorem two_le_pi : (2 : ℝ) ≤ π :=
(div_le_div_right (show (0 : ℝ) < 2 by norm_num)).1
(by rw [div_self (two_ne_zero' ℝ)]; exact one_le_pi_div_two)
#align real.two_le_pi Real.two_le_pi
theorem pi_le_four : π ≤ 4 :=
(div_le_div_right (show (0 : ℝ) < 2 by norm_num)).1
(calc
π / 2 ≤ 2 := pi_div_two_le_two
_ = 4 / 2 := by norm_num)
#align real.pi_le_four Real.pi_le_four
theorem pi_pos : 0 < π :=
lt_of_lt_of_le (by norm_num) two_le_pi
#align real.pi_pos Real.pi_pos
theorem pi_nonneg : 0 ≤ π :=
pi_pos.le
theorem pi_ne_zero : π ≠ 0 :=
pi_pos.ne'
#align real.pi_ne_zero Real.pi_ne_zero
theorem pi_div_two_pos : 0 < π / 2 :=
half_pos pi_pos
#align real.pi_div_two_pos Real.pi_div_two_pos
theorem two_pi_pos : 0 < 2 * π := by linarith [pi_pos]
#align real.two_pi_pos Real.two_pi_pos
end Real
namespace Mathlib.Meta.Positivity
open Lean.Meta Qq
/-- Extension for the `positivity` tactic: `π` is always positive. -/
@[positivity Real.pi]
def evalRealPi : PositivityExt where eval {u α} _zα _pα e := do
match u, α, e with
| 0, ~q(ℝ), ~q(Real.pi) =>
assertInstancesCommute
pure (.positive q(Real.pi_pos))
| _, _, _ => throwError "not Real.pi"
end Mathlib.Meta.Positivity
namespace NNReal
open Real
open Real NNReal
/-- `π` considered as a nonnegative real. -/
noncomputable def pi : ℝ≥0 :=
⟨π, Real.pi_pos.le⟩
#align nnreal.pi NNReal.pi
@[simp]
theorem coe_real_pi : (pi : ℝ) = π :=
rfl
#align nnreal.coe_real_pi NNReal.coe_real_pi
theorem pi_pos : 0 < pi := mod_cast Real.pi_pos
#align nnreal.pi_pos NNReal.pi_pos
theorem pi_ne_zero : pi ≠ 0 :=
pi_pos.ne'
#align nnreal.pi_ne_zero NNReal.pi_ne_zero
end NNReal
namespace Real
open Real
@[simp]
theorem sin_pi : sin π = 0 := by
rw [← mul_div_cancel_left₀ π (two_ne_zero' ℝ), two_mul, add_div, sin_add, cos_pi_div_two]; simp
#align real.sin_pi Real.sin_pi
@[simp]
theorem cos_pi : cos π = -1 := by
rw [← mul_div_cancel_left₀ π (two_ne_zero' ℝ), mul_div_assoc, cos_two_mul, cos_pi_div_two]
norm_num
#align real.cos_pi Real.cos_pi
@[simp]
theorem sin_two_pi : sin (2 * π) = 0 := by simp [two_mul, sin_add]
#align real.sin_two_pi Real.sin_two_pi
@[simp]
theorem cos_two_pi : cos (2 * π) = 1 := by simp [two_mul, cos_add]
#align real.cos_two_pi Real.cos_two_pi
theorem sin_antiperiodic : Function.Antiperiodic sin π := by simp [sin_add]
#align real.sin_antiperiodic Real.sin_antiperiodic
theorem sin_periodic : Function.Periodic sin (2 * π) :=
sin_antiperiodic.periodic_two_mul
#align real.sin_periodic Real.sin_periodic
@[simp]
theorem sin_add_pi (x : ℝ) : sin (x + π) = -sin x :=
sin_antiperiodic x
#align real.sin_add_pi Real.sin_add_pi
@[simp]
theorem sin_add_two_pi (x : ℝ) : sin (x + 2 * π) = sin x :=
sin_periodic x
#align real.sin_add_two_pi Real.sin_add_two_pi
@[simp]
theorem sin_sub_pi (x : ℝ) : sin (x - π) = -sin x :=
sin_antiperiodic.sub_eq x
#align real.sin_sub_pi Real.sin_sub_pi
@[simp]
theorem sin_sub_two_pi (x : ℝ) : sin (x - 2 * π) = sin x :=
sin_periodic.sub_eq x
#align real.sin_sub_two_pi Real.sin_sub_two_pi
@[simp]
theorem sin_pi_sub (x : ℝ) : sin (π - x) = sin x :=
neg_neg (sin x) ▸ sin_neg x ▸ sin_antiperiodic.sub_eq'
#align real.sin_pi_sub Real.sin_pi_sub
@[simp]
theorem sin_two_pi_sub (x : ℝ) : sin (2 * π - x) = -sin x :=
sin_neg x ▸ sin_periodic.sub_eq'
#align real.sin_two_pi_sub Real.sin_two_pi_sub
@[simp]
theorem sin_nat_mul_pi (n : ℕ) : sin (n * π) = 0 :=
sin_antiperiodic.nat_mul_eq_of_eq_zero sin_zero n
#align real.sin_nat_mul_pi Real.sin_nat_mul_pi
@[simp]
theorem sin_int_mul_pi (n : ℤ) : sin (n * π) = 0 :=
sin_antiperiodic.int_mul_eq_of_eq_zero sin_zero n
#align real.sin_int_mul_pi Real.sin_int_mul_pi
@[simp]
theorem sin_add_nat_mul_two_pi (x : ℝ) (n : ℕ) : sin (x + n * (2 * π)) = sin x :=
sin_periodic.nat_mul n x
#align real.sin_add_nat_mul_two_pi Real.sin_add_nat_mul_two_pi
@[simp]
theorem sin_add_int_mul_two_pi (x : ℝ) (n : ℤ) : sin (x + n * (2 * π)) = sin x :=
sin_periodic.int_mul n x
#align real.sin_add_int_mul_two_pi Real.sin_add_int_mul_two_pi
@[simp]
theorem sin_sub_nat_mul_two_pi (x : ℝ) (n : ℕ) : sin (x - n * (2 * π)) = sin x :=
sin_periodic.sub_nat_mul_eq n
#align real.sin_sub_nat_mul_two_pi Real.sin_sub_nat_mul_two_pi
@[simp]
theorem sin_sub_int_mul_two_pi (x : ℝ) (n : ℤ) : sin (x - n * (2 * π)) = sin x :=
sin_periodic.sub_int_mul_eq n
#align real.sin_sub_int_mul_two_pi Real.sin_sub_int_mul_two_pi
@[simp]
theorem sin_nat_mul_two_pi_sub (x : ℝ) (n : ℕ) : sin (n * (2 * π) - x) = -sin x :=
sin_neg x ▸ sin_periodic.nat_mul_sub_eq n
#align real.sin_nat_mul_two_pi_sub Real.sin_nat_mul_two_pi_sub
@[simp]
theorem sin_int_mul_two_pi_sub (x : ℝ) (n : ℤ) : sin (n * (2 * π) - x) = -sin x :=
sin_neg x ▸ sin_periodic.int_mul_sub_eq n
#align real.sin_int_mul_two_pi_sub Real.sin_int_mul_two_pi_sub
theorem sin_add_int_mul_pi (x : ℝ) (n : ℤ) : sin (x + n * π) = (-1) ^ n * sin x :=
n.coe_negOnePow ℝ ▸ sin_antiperiodic.add_int_mul_eq n
theorem sin_add_nat_mul_pi (x : ℝ) (n : ℕ) : sin (x + n * π) = (-1) ^ n * sin x :=
sin_antiperiodic.add_nat_mul_eq n
theorem sin_sub_int_mul_pi (x : ℝ) (n : ℤ) : sin (x - n * π) = (-1) ^ n * sin x :=
n.coe_negOnePow ℝ ▸ sin_antiperiodic.sub_int_mul_eq n
theorem sin_sub_nat_mul_pi (x : ℝ) (n : ℕ) : sin (x - n * π) = (-1) ^ n * sin x :=
sin_antiperiodic.sub_nat_mul_eq n
theorem sin_int_mul_pi_sub (x : ℝ) (n : ℤ) : sin (n * π - x) = -((-1) ^ n * sin x) := by
simpa only [sin_neg, mul_neg, Int.coe_negOnePow] using sin_antiperiodic.int_mul_sub_eq n
theorem sin_nat_mul_pi_sub (x : ℝ) (n : ℕ) : sin (n * π - x) = -((-1) ^ n * sin x) := by
simpa only [sin_neg, mul_neg] using sin_antiperiodic.nat_mul_sub_eq n
theorem cos_antiperiodic : Function.Antiperiodic cos π := by simp [cos_add]
#align real.cos_antiperiodic Real.cos_antiperiodic
theorem cos_periodic : Function.Periodic cos (2 * π) :=
cos_antiperiodic.periodic_two_mul
#align real.cos_periodic Real.cos_periodic
@[simp]
theorem cos_add_pi (x : ℝ) : cos (x + π) = -cos x :=
cos_antiperiodic x
#align real.cos_add_pi Real.cos_add_pi
@[simp]
theorem cos_add_two_pi (x : ℝ) : cos (x + 2 * π) = cos x :=
cos_periodic x
#align real.cos_add_two_pi Real.cos_add_two_pi
@[simp]
theorem cos_sub_pi (x : ℝ) : cos (x - π) = -cos x :=
cos_antiperiodic.sub_eq x
#align real.cos_sub_pi Real.cos_sub_pi
@[simp]
theorem cos_sub_two_pi (x : ℝ) : cos (x - 2 * π) = cos x :=
cos_periodic.sub_eq x
#align real.cos_sub_two_pi Real.cos_sub_two_pi
@[simp]
theorem cos_pi_sub (x : ℝ) : cos (π - x) = -cos x :=
cos_neg x ▸ cos_antiperiodic.sub_eq'
#align real.cos_pi_sub Real.cos_pi_sub
@[simp]
theorem cos_two_pi_sub (x : ℝ) : cos (2 * π - x) = cos x :=
cos_neg x ▸ cos_periodic.sub_eq'
#align real.cos_two_pi_sub Real.cos_two_pi_sub
@[simp]
theorem cos_nat_mul_two_pi (n : ℕ) : cos (n * (2 * π)) = 1 :=
(cos_periodic.nat_mul_eq n).trans cos_zero
#align real.cos_nat_mul_two_pi Real.cos_nat_mul_two_pi
@[simp]
theorem cos_int_mul_two_pi (n : ℤ) : cos (n * (2 * π)) = 1 :=
(cos_periodic.int_mul_eq n).trans cos_zero
#align real.cos_int_mul_two_pi Real.cos_int_mul_two_pi
@[simp]
theorem cos_add_nat_mul_two_pi (x : ℝ) (n : ℕ) : cos (x + n * (2 * π)) = cos x :=
cos_periodic.nat_mul n x
#align real.cos_add_nat_mul_two_pi Real.cos_add_nat_mul_two_pi
@[simp]
theorem cos_add_int_mul_two_pi (x : ℝ) (n : ℤ) : cos (x + n * (2 * π)) = cos x :=
cos_periodic.int_mul n x
#align real.cos_add_int_mul_two_pi Real.cos_add_int_mul_two_pi
@[simp]
theorem cos_sub_nat_mul_two_pi (x : ℝ) (n : ℕ) : cos (x - n * (2 * π)) = cos x :=
cos_periodic.sub_nat_mul_eq n
#align real.cos_sub_nat_mul_two_pi Real.cos_sub_nat_mul_two_pi
@[simp]
theorem cos_sub_int_mul_two_pi (x : ℝ) (n : ℤ) : cos (x - n * (2 * π)) = cos x :=
cos_periodic.sub_int_mul_eq n
#align real.cos_sub_int_mul_two_pi Real.cos_sub_int_mul_two_pi
@[simp]
theorem cos_nat_mul_two_pi_sub (x : ℝ) (n : ℕ) : cos (n * (2 * π) - x) = cos x :=
cos_neg x ▸ cos_periodic.nat_mul_sub_eq n
#align real.cos_nat_mul_two_pi_sub Real.cos_nat_mul_two_pi_sub
@[simp]
theorem cos_int_mul_two_pi_sub (x : ℝ) (n : ℤ) : cos (n * (2 * π) - x) = cos x :=
cos_neg x ▸ cos_periodic.int_mul_sub_eq n
#align real.cos_int_mul_two_pi_sub Real.cos_int_mul_two_pi_sub
theorem cos_add_int_mul_pi (x : ℝ) (n : ℤ) : cos (x + n * π) = (-1) ^ n * cos x :=
n.coe_negOnePow ℝ ▸ cos_antiperiodic.add_int_mul_eq n
theorem cos_add_nat_mul_pi (x : ℝ) (n : ℕ) : cos (x + n * π) = (-1) ^ n * cos x :=
cos_antiperiodic.add_nat_mul_eq n
theorem cos_sub_int_mul_pi (x : ℝ) (n : ℤ) : cos (x - n * π) = (-1) ^ n * cos x :=
n.coe_negOnePow ℝ ▸ cos_antiperiodic.sub_int_mul_eq n
theorem cos_sub_nat_mul_pi (x : ℝ) (n : ℕ) : cos (x - n * π) = (-1) ^ n * cos x :=
cos_antiperiodic.sub_nat_mul_eq n
theorem cos_int_mul_pi_sub (x : ℝ) (n : ℤ) : cos (n * π - x) = (-1) ^ n * cos x :=
n.coe_negOnePow ℝ ▸ cos_neg x ▸ cos_antiperiodic.int_mul_sub_eq n
theorem cos_nat_mul_pi_sub (x : ℝ) (n : ℕ) : cos (n * π - x) = (-1) ^ n * cos x :=
cos_neg x ▸ cos_antiperiodic.nat_mul_sub_eq n
-- Porting note (#10618): was @[simp], but simp can prove it
theorem cos_nat_mul_two_pi_add_pi (n : ℕ) : cos (n * (2 * π) + π) = -1 := by
simpa only [cos_zero] using (cos_periodic.nat_mul n).add_antiperiod_eq cos_antiperiodic
#align real.cos_nat_mul_two_pi_add_pi Real.cos_nat_mul_two_pi_add_pi
-- Porting note (#10618): was @[simp], but simp can prove it
theorem cos_int_mul_two_pi_add_pi (n : ℤ) : cos (n * (2 * π) + π) = -1 := by
simpa only [cos_zero] using (cos_periodic.int_mul n).add_antiperiod_eq cos_antiperiodic
#align real.cos_int_mul_two_pi_add_pi Real.cos_int_mul_two_pi_add_pi
-- Porting note (#10618): was @[simp], but simp can prove it
theorem cos_nat_mul_two_pi_sub_pi (n : ℕ) : cos (n * (2 * π) - π) = -1 := by
simpa only [cos_zero] using (cos_periodic.nat_mul n).sub_antiperiod_eq cos_antiperiodic
#align real.cos_nat_mul_two_pi_sub_pi Real.cos_nat_mul_two_pi_sub_pi
-- Porting note (#10618): was @[simp], but simp can prove it
theorem cos_int_mul_two_pi_sub_pi (n : ℤ) : cos (n * (2 * π) - π) = -1 := by
simpa only [cos_zero] using (cos_periodic.int_mul n).sub_antiperiod_eq cos_antiperiodic
#align real.cos_int_mul_two_pi_sub_pi Real.cos_int_mul_two_pi_sub_pi
theorem sin_pos_of_pos_of_lt_pi {x : ℝ} (h0x : 0 < x) (hxp : x < π) : 0 < sin x :=
if hx2 : x ≤ 2 then sin_pos_of_pos_of_le_two h0x hx2
else
have : (2 : ℝ) + 2 = 4 := by norm_num
have : π - x ≤ 2 :=
sub_le_iff_le_add.2 (le_trans pi_le_four (this ▸ add_le_add_left (le_of_not_ge hx2) _))
sin_pi_sub x ▸ sin_pos_of_pos_of_le_two (sub_pos.2 hxp) this
#align real.sin_pos_of_pos_of_lt_pi Real.sin_pos_of_pos_of_lt_pi
theorem sin_pos_of_mem_Ioo {x : ℝ} (hx : x ∈ Ioo 0 π) : 0 < sin x :=
sin_pos_of_pos_of_lt_pi hx.1 hx.2
#align real.sin_pos_of_mem_Ioo Real.sin_pos_of_mem_Ioo
theorem sin_nonneg_of_mem_Icc {x : ℝ} (hx : x ∈ Icc 0 π) : 0 ≤ sin x := by
rw [← closure_Ioo pi_ne_zero.symm] at hx
exact
closure_lt_subset_le continuous_const continuous_sin
(closure_mono (fun y => sin_pos_of_mem_Ioo) hx)
#align real.sin_nonneg_of_mem_Icc Real.sin_nonneg_of_mem_Icc
theorem sin_nonneg_of_nonneg_of_le_pi {x : ℝ} (h0x : 0 ≤ x) (hxp : x ≤ π) : 0 ≤ sin x :=
sin_nonneg_of_mem_Icc ⟨h0x, hxp⟩
#align real.sin_nonneg_of_nonneg_of_le_pi Real.sin_nonneg_of_nonneg_of_le_pi
theorem sin_neg_of_neg_of_neg_pi_lt {x : ℝ} (hx0 : x < 0) (hpx : -π < x) : sin x < 0 :=
neg_pos.1 <| sin_neg x ▸ sin_pos_of_pos_of_lt_pi (neg_pos.2 hx0) (neg_lt.1 hpx)
#align real.sin_neg_of_neg_of_neg_pi_lt Real.sin_neg_of_neg_of_neg_pi_lt
theorem sin_nonpos_of_nonnpos_of_neg_pi_le {x : ℝ} (hx0 : x ≤ 0) (hpx : -π ≤ x) : sin x ≤ 0 :=
neg_nonneg.1 <| sin_neg x ▸ sin_nonneg_of_nonneg_of_le_pi (neg_nonneg.2 hx0) (neg_le.1 hpx)
#align real.sin_nonpos_of_nonnpos_of_neg_pi_le Real.sin_nonpos_of_nonnpos_of_neg_pi_le
@[simp]
theorem sin_pi_div_two : sin (π / 2) = 1 :=
have : sin (π / 2) = 1 ∨ sin (π / 2) = -1 := by
simpa [sq, mul_self_eq_one_iff] using sin_sq_add_cos_sq (π / 2)
this.resolve_right fun h =>
show ¬(0 : ℝ) < -1 by norm_num <|
h ▸ sin_pos_of_pos_of_lt_pi pi_div_two_pos (half_lt_self pi_pos)
#align real.sin_pi_div_two Real.sin_pi_div_two
theorem sin_add_pi_div_two (x : ℝ) : sin (x + π / 2) = cos x := by simp [sin_add]
#align real.sin_add_pi_div_two Real.sin_add_pi_div_two
theorem sin_sub_pi_div_two (x : ℝ) : sin (x - π / 2) = -cos x := by simp [sub_eq_add_neg, sin_add]
#align real.sin_sub_pi_div_two Real.sin_sub_pi_div_two
theorem sin_pi_div_two_sub (x : ℝ) : sin (π / 2 - x) = cos x := by simp [sub_eq_add_neg, sin_add]
#align real.sin_pi_div_two_sub Real.sin_pi_div_two_sub
theorem cos_add_pi_div_two (x : ℝ) : cos (x + π / 2) = -sin x := by simp [cos_add]
#align real.cos_add_pi_div_two Real.cos_add_pi_div_two
theorem cos_sub_pi_div_two (x : ℝ) : cos (x - π / 2) = sin x := by simp [sub_eq_add_neg, cos_add]
#align real.cos_sub_pi_div_two Real.cos_sub_pi_div_two
theorem cos_pi_div_two_sub (x : ℝ) : cos (π / 2 - x) = sin x := by
rw [← cos_neg, neg_sub, cos_sub_pi_div_two]
#align real.cos_pi_div_two_sub Real.cos_pi_div_two_sub
theorem cos_pos_of_mem_Ioo {x : ℝ} (hx : x ∈ Ioo (-(π / 2)) (π / 2)) : 0 < cos x :=
sin_add_pi_div_two x ▸ sin_pos_of_mem_Ioo ⟨by linarith [hx.1], by linarith [hx.2]⟩
#align real.cos_pos_of_mem_Ioo Real.cos_pos_of_mem_Ioo
theorem cos_nonneg_of_mem_Icc {x : ℝ} (hx : x ∈ Icc (-(π / 2)) (π / 2)) : 0 ≤ cos x :=
sin_add_pi_div_two x ▸ sin_nonneg_of_mem_Icc ⟨by linarith [hx.1], by linarith [hx.2]⟩
#align real.cos_nonneg_of_mem_Icc Real.cos_nonneg_of_mem_Icc
theorem cos_nonneg_of_neg_pi_div_two_le_of_le {x : ℝ} (hl : -(π / 2) ≤ x) (hu : x ≤ π / 2) :
0 ≤ cos x :=
cos_nonneg_of_mem_Icc ⟨hl, hu⟩
#align real.cos_nonneg_of_neg_pi_div_two_le_of_le Real.cos_nonneg_of_neg_pi_div_two_le_of_le
theorem cos_neg_of_pi_div_two_lt_of_lt {x : ℝ} (hx₁ : π / 2 < x) (hx₂ : x < π + π / 2) :
cos x < 0 :=
neg_pos.1 <| cos_pi_sub x ▸ cos_pos_of_mem_Ioo ⟨by linarith, by linarith⟩
#align real.cos_neg_of_pi_div_two_lt_of_lt Real.cos_neg_of_pi_div_two_lt_of_lt
theorem cos_nonpos_of_pi_div_two_le_of_le {x : ℝ} (hx₁ : π / 2 ≤ x) (hx₂ : x ≤ π + π / 2) :
cos x ≤ 0 :=
neg_nonneg.1 <| cos_pi_sub x ▸ cos_nonneg_of_mem_Icc ⟨by linarith, by linarith⟩
#align real.cos_nonpos_of_pi_div_two_le_of_le Real.cos_nonpos_of_pi_div_two_le_of_le
theorem sin_eq_sqrt_one_sub_cos_sq {x : ℝ} (hl : 0 ≤ x) (hu : x ≤ π) :
sin x = √(1 - cos x ^ 2) := by
rw [← abs_sin_eq_sqrt_one_sub_cos_sq, abs_of_nonneg (sin_nonneg_of_nonneg_of_le_pi hl hu)]
#align real.sin_eq_sqrt_one_sub_cos_sq Real.sin_eq_sqrt_one_sub_cos_sq
theorem cos_eq_sqrt_one_sub_sin_sq {x : ℝ} (hl : -(π / 2) ≤ x) (hu : x ≤ π / 2) :
cos x = √(1 - sin x ^ 2) := by
rw [← abs_cos_eq_sqrt_one_sub_sin_sq, abs_of_nonneg (cos_nonneg_of_mem_Icc ⟨hl, hu⟩)]
#align real.cos_eq_sqrt_one_sub_sin_sq Real.cos_eq_sqrt_one_sub_sin_sq
lemma cos_half {x : ℝ} (hl : -π ≤ x) (hr : x ≤ π) : cos (x / 2) = sqrt ((1 + cos x) / 2) := by
have : 0 ≤ cos (x / 2) := cos_nonneg_of_mem_Icc <| by constructor <;> linarith
rw [← sqrt_sq this, cos_sq, add_div, two_mul, add_halves]
lemma abs_sin_half (x : ℝ) : |sin (x / 2)| = sqrt ((1 - cos x) / 2) := by
rw [← sqrt_sq_eq_abs, sin_sq_eq_half_sub, two_mul, add_halves, sub_div]
lemma sin_half_eq_sqrt {x : ℝ} (hl : 0 ≤ x) (hr : x ≤ 2 * π) :
sin (x / 2) = sqrt ((1 - cos x) / 2) := by
rw [← abs_sin_half, abs_of_nonneg]
apply sin_nonneg_of_nonneg_of_le_pi <;> linarith
lemma sin_half_eq_neg_sqrt {x : ℝ} (hl : -(2 * π) ≤ x) (hr : x ≤ 0) :
sin (x / 2) = -sqrt ((1 - cos x) / 2) := by
rw [← abs_sin_half, abs_of_nonpos, neg_neg]
apply sin_nonpos_of_nonnpos_of_neg_pi_le <;> linarith
theorem sin_eq_zero_iff_of_lt_of_lt {x : ℝ} (hx₁ : -π < x) (hx₂ : x < π) : sin x = 0 ↔ x = 0 :=
⟨fun h => by
contrapose! h
cases h.lt_or_lt with
| inl h0 => exact (sin_neg_of_neg_of_neg_pi_lt h0 hx₁).ne
| inr h0 => exact (sin_pos_of_pos_of_lt_pi h0 hx₂).ne',
fun h => by simp [h]⟩
#align real.sin_eq_zero_iff_of_lt_of_lt Real.sin_eq_zero_iff_of_lt_of_lt
theorem sin_eq_zero_iff {x : ℝ} : sin x = 0 ↔ ∃ n : ℤ, (n : ℝ) * π = x :=
⟨fun h =>
⟨⌊x / π⌋,
le_antisymm (sub_nonneg.1 (Int.sub_floor_div_mul_nonneg _ pi_pos))
(sub_nonpos.1 <|
le_of_not_gt fun h₃ =>
(sin_pos_of_pos_of_lt_pi h₃ (Int.sub_floor_div_mul_lt _ pi_pos)).ne
(by simp [sub_eq_add_neg, sin_add, h, sin_int_mul_pi]))⟩,
fun ⟨n, hn⟩ => hn ▸ sin_int_mul_pi _⟩
#align real.sin_eq_zero_iff Real.sin_eq_zero_iff
theorem sin_ne_zero_iff {x : ℝ} : sin x ≠ 0 ↔ ∀ n : ℤ, (n : ℝ) * π ≠ x := by
rw [← not_exists, not_iff_not, sin_eq_zero_iff]
#align real.sin_ne_zero_iff Real.sin_ne_zero_iff
theorem sin_eq_zero_iff_cos_eq {x : ℝ} : sin x = 0 ↔ cos x = 1 ∨ cos x = -1 := by
rw [← mul_self_eq_one_iff, ← sin_sq_add_cos_sq x, sq, sq, ← sub_eq_iff_eq_add, sub_self]
exact ⟨fun h => by rw [h, mul_zero], eq_zero_of_mul_self_eq_zero ∘ Eq.symm⟩
#align real.sin_eq_zero_iff_cos_eq Real.sin_eq_zero_iff_cos_eq
theorem cos_eq_one_iff (x : ℝ) : cos x = 1 ↔ ∃ n : ℤ, (n : ℝ) * (2 * π) = x :=
⟨fun h =>
let ⟨n, hn⟩ := sin_eq_zero_iff.1 (sin_eq_zero_iff_cos_eq.2 (Or.inl h))
⟨n / 2,
(Int.emod_two_eq_zero_or_one n).elim
(fun hn0 => by
rwa [← mul_assoc, ← @Int.cast_two ℝ, ← Int.cast_mul,
Int.ediv_mul_cancel ((Int.dvd_iff_emod_eq_zero _ _).2 hn0)])
fun hn1 => by
rw [← Int.emod_add_ediv n 2, hn1, Int.cast_add, Int.cast_one, add_mul, one_mul, add_comm,
mul_comm (2 : ℤ), Int.cast_mul, mul_assoc, Int.cast_two] at hn
rw [← hn, cos_int_mul_two_pi_add_pi] at h
exact absurd h (by norm_num)⟩,
fun ⟨n, hn⟩ => hn ▸ cos_int_mul_two_pi _⟩
#align real.cos_eq_one_iff Real.cos_eq_one_iff
theorem cos_eq_one_iff_of_lt_of_lt {x : ℝ} (hx₁ : -(2 * π) < x) (hx₂ : x < 2 * π) :
cos x = 1 ↔ x = 0 :=
⟨fun h => by
rcases (cos_eq_one_iff _).1 h with ⟨n, rfl⟩
rw [mul_lt_iff_lt_one_left two_pi_pos] at hx₂
rw [neg_lt, neg_mul_eq_neg_mul, mul_lt_iff_lt_one_left two_pi_pos] at hx₁
norm_cast at hx₁ hx₂
obtain rfl : n = 0 := le_antisymm (by omega) (by omega)
simp, fun h => by simp [h]⟩
#align real.cos_eq_one_iff_of_lt_of_lt Real.cos_eq_one_iff_of_lt_of_lt
theorem sin_lt_sin_of_lt_of_le_pi_div_two {x y : ℝ} (hx₁ : -(π / 2) ≤ x) (hy₂ : y ≤ π / 2)
(hxy : x < y) : sin x < sin y := by
rw [← sub_pos, sin_sub_sin]
have : 0 < sin ((y - x) / 2) := by apply sin_pos_of_pos_of_lt_pi <;> linarith
have : 0 < cos ((y + x) / 2) := by refine cos_pos_of_mem_Ioo ⟨?_, ?_⟩ <;> linarith
positivity
#align real.sin_lt_sin_of_lt_of_le_pi_div_two Real.sin_lt_sin_of_lt_of_le_pi_div_two
theorem strictMonoOn_sin : StrictMonoOn sin (Icc (-(π / 2)) (π / 2)) := fun _ hx _ hy hxy =>
sin_lt_sin_of_lt_of_le_pi_div_two hx.1 hy.2 hxy
#align real.strict_mono_on_sin Real.strictMonoOn_sin
theorem cos_lt_cos_of_nonneg_of_le_pi {x y : ℝ} (hx₁ : 0 ≤ x) (hy₂ : y ≤ π) (hxy : x < y) :
cos y < cos x := by
rw [← sin_pi_div_two_sub, ← sin_pi_div_two_sub]
apply sin_lt_sin_of_lt_of_le_pi_div_two <;> linarith
#align real.cos_lt_cos_of_nonneg_of_le_pi Real.cos_lt_cos_of_nonneg_of_le_pi
theorem cos_lt_cos_of_nonneg_of_le_pi_div_two {x y : ℝ} (hx₁ : 0 ≤ x) (hy₂ : y ≤ π / 2)
(hxy : x < y) : cos y < cos x :=
cos_lt_cos_of_nonneg_of_le_pi hx₁ (hy₂.trans (by linarith)) hxy
#align real.cos_lt_cos_of_nonneg_of_le_pi_div_two Real.cos_lt_cos_of_nonneg_of_le_pi_div_two
theorem strictAntiOn_cos : StrictAntiOn cos (Icc 0 π) := fun _ hx _ hy hxy =>
cos_lt_cos_of_nonneg_of_le_pi hx.1 hy.2 hxy
#align real.strict_anti_on_cos Real.strictAntiOn_cos
theorem cos_le_cos_of_nonneg_of_le_pi {x y : ℝ} (hx₁ : 0 ≤ x) (hy₂ : y ≤ π) (hxy : x ≤ y) :
cos y ≤ cos x :=
(strictAntiOn_cos.le_iff_le ⟨hx₁.trans hxy, hy₂⟩ ⟨hx₁, hxy.trans hy₂⟩).2 hxy
#align real.cos_le_cos_of_nonneg_of_le_pi Real.cos_le_cos_of_nonneg_of_le_pi
theorem sin_le_sin_of_le_of_le_pi_div_two {x y : ℝ} (hx₁ : -(π / 2) ≤ x) (hy₂ : y ≤ π / 2)
(hxy : x ≤ y) : sin x ≤ sin y :=
(strictMonoOn_sin.le_iff_le ⟨hx₁, hxy.trans hy₂⟩ ⟨hx₁.trans hxy, hy₂⟩).2 hxy
#align real.sin_le_sin_of_le_of_le_pi_div_two Real.sin_le_sin_of_le_of_le_pi_div_two
theorem injOn_sin : InjOn sin (Icc (-(π / 2)) (π / 2)) :=
strictMonoOn_sin.injOn
#align real.inj_on_sin Real.injOn_sin
theorem injOn_cos : InjOn cos (Icc 0 π) :=
strictAntiOn_cos.injOn
#align real.inj_on_cos Real.injOn_cos
theorem surjOn_sin : SurjOn sin (Icc (-(π / 2)) (π / 2)) (Icc (-1) 1) := by
simpa only [sin_neg, sin_pi_div_two] using
intermediate_value_Icc (neg_le_self pi_div_two_pos.le) continuous_sin.continuousOn
#align real.surj_on_sin Real.surjOn_sin
theorem surjOn_cos : SurjOn cos (Icc 0 π) (Icc (-1) 1) := by
simpa only [cos_zero, cos_pi] using intermediate_value_Icc' pi_pos.le continuous_cos.continuousOn
#align real.surj_on_cos Real.surjOn_cos
theorem sin_mem_Icc (x : ℝ) : sin x ∈ Icc (-1 : ℝ) 1 :=
⟨neg_one_le_sin x, sin_le_one x⟩
#align real.sin_mem_Icc Real.sin_mem_Icc
theorem cos_mem_Icc (x : ℝ) : cos x ∈ Icc (-1 : ℝ) 1 :=
⟨neg_one_le_cos x, cos_le_one x⟩
#align real.cos_mem_Icc Real.cos_mem_Icc
theorem mapsTo_sin (s : Set ℝ) : MapsTo sin s (Icc (-1 : ℝ) 1) := fun x _ => sin_mem_Icc x
#align real.maps_to_sin Real.mapsTo_sin
theorem mapsTo_cos (s : Set ℝ) : MapsTo cos s (Icc (-1 : ℝ) 1) := fun x _ => cos_mem_Icc x
#align real.maps_to_cos Real.mapsTo_cos
theorem bijOn_sin : BijOn sin (Icc (-(π / 2)) (π / 2)) (Icc (-1) 1) :=
⟨mapsTo_sin _, injOn_sin, surjOn_sin⟩
#align real.bij_on_sin Real.bijOn_sin
theorem bijOn_cos : BijOn cos (Icc 0 π) (Icc (-1) 1) :=
⟨mapsTo_cos _, injOn_cos, surjOn_cos⟩
#align real.bij_on_cos Real.bijOn_cos
@[simp]
theorem range_cos : range cos = (Icc (-1) 1 : Set ℝ) :=
Subset.antisymm (range_subset_iff.2 cos_mem_Icc) surjOn_cos.subset_range
#align real.range_cos Real.range_cos
@[simp]
theorem range_sin : range sin = (Icc (-1) 1 : Set ℝ) :=
Subset.antisymm (range_subset_iff.2 sin_mem_Icc) surjOn_sin.subset_range
#align real.range_sin Real.range_sin
theorem range_cos_infinite : (range Real.cos).Infinite := by
rw [Real.range_cos]
exact Icc_infinite (by norm_num)
#align real.range_cos_infinite Real.range_cos_infinite
theorem range_sin_infinite : (range Real.sin).Infinite := by
rw [Real.range_sin]
exact Icc_infinite (by norm_num)
#align real.range_sin_infinite Real.range_sin_infinite
section CosDivSq
variable (x : ℝ)
/-- the series `sqrtTwoAddSeries x n` is `sqrt(2 + sqrt(2 + ... ))` with `n` square roots,
starting with `x`. We define it here because `cos (pi / 2 ^ (n+1)) = sqrtTwoAddSeries 0 n / 2`
-/
@[simp]
noncomputable def sqrtTwoAddSeries (x : ℝ) : ℕ → ℝ
| 0 => x
| n + 1 => √(2 + sqrtTwoAddSeries x n)
#align real.sqrt_two_add_series Real.sqrtTwoAddSeries
theorem sqrtTwoAddSeries_zero : sqrtTwoAddSeries x 0 = x := by simp
#align real.sqrt_two_add_series_zero Real.sqrtTwoAddSeries_zero
theorem sqrtTwoAddSeries_one : sqrtTwoAddSeries 0 1 = √2 := by simp
#align real.sqrt_two_add_series_one Real.sqrtTwoAddSeries_one
theorem sqrtTwoAddSeries_two : sqrtTwoAddSeries 0 2 = √(2 + √2) := by simp
#align real.sqrt_two_add_series_two Real.sqrtTwoAddSeries_two
theorem sqrtTwoAddSeries_zero_nonneg : ∀ n : ℕ, 0 ≤ sqrtTwoAddSeries 0 n
| 0 => le_refl 0
| _ + 1 => sqrt_nonneg _
#align real.sqrt_two_add_series_zero_nonneg Real.sqrtTwoAddSeries_zero_nonneg
theorem sqrtTwoAddSeries_nonneg {x : ℝ} (h : 0 ≤ x) : ∀ n : ℕ, 0 ≤ sqrtTwoAddSeries x n
| 0 => h
| _ + 1 => sqrt_nonneg _
#align real.sqrt_two_add_series_nonneg Real.sqrtTwoAddSeries_nonneg
theorem sqrtTwoAddSeries_lt_two : ∀ n : ℕ, sqrtTwoAddSeries 0 n < 2
| 0 => by norm_num
| n + 1 => by
refine lt_of_lt_of_le ?_ (sqrt_sq zero_lt_two.le).le
rw [sqrtTwoAddSeries, sqrt_lt_sqrt_iff, ← lt_sub_iff_add_lt']
· refine (sqrtTwoAddSeries_lt_two n).trans_le ?_
norm_num
· exact add_nonneg zero_le_two (sqrtTwoAddSeries_zero_nonneg n)
#align real.sqrt_two_add_series_lt_two Real.sqrtTwoAddSeries_lt_two
theorem sqrtTwoAddSeries_succ (x : ℝ) :
∀ n : ℕ, sqrtTwoAddSeries x (n + 1) = sqrtTwoAddSeries (√(2 + x)) n
| 0 => rfl
| n + 1 => by rw [sqrtTwoAddSeries, sqrtTwoAddSeries_succ _ _, sqrtTwoAddSeries]
#align real.sqrt_two_add_series_succ Real.sqrtTwoAddSeries_succ
theorem sqrtTwoAddSeries_monotone_left {x y : ℝ} (h : x ≤ y) :
∀ n : ℕ, sqrtTwoAddSeries x n ≤ sqrtTwoAddSeries y n
| 0 => h
| n + 1 => by
rw [sqrtTwoAddSeries, sqrtTwoAddSeries]
exact sqrt_le_sqrt (add_le_add_left (sqrtTwoAddSeries_monotone_left h _) _)
#align real.sqrt_two_add_series_monotone_left Real.sqrtTwoAddSeries_monotone_left
@[simp]
theorem cos_pi_over_two_pow : ∀ n : ℕ, cos (π / 2 ^ (n + 1)) = sqrtTwoAddSeries 0 n / 2
| 0 => by simp
| n + 1 => by
have A : (1 : ℝ) < 2 ^ (n + 1) := one_lt_pow one_lt_two n.succ_ne_zero
have B : π / 2 ^ (n + 1) < π := div_lt_self pi_pos A
have C : 0 < π / 2 ^ (n + 1) := by positivity
rw [pow_succ, div_mul_eq_div_div, cos_half, cos_pi_over_two_pow n, sqrtTwoAddSeries,
add_div_eq_mul_add_div, one_mul, ← div_mul_eq_div_div, sqrt_div, sqrt_mul_self] <;>
linarith [sqrtTwoAddSeries_nonneg le_rfl n]
#align real.cos_pi_over_two_pow Real.cos_pi_over_two_pow
theorem sin_sq_pi_over_two_pow (n : ℕ) :
sin (π / 2 ^ (n + 1)) ^ 2 = 1 - (sqrtTwoAddSeries 0 n / 2) ^ 2 := by
rw [sin_sq, cos_pi_over_two_pow]
#align real.sin_sq_pi_over_two_pow Real.sin_sq_pi_over_two_pow
theorem sin_sq_pi_over_two_pow_succ (n : ℕ) :
sin (π / 2 ^ (n + 2)) ^ 2 = 1 / 2 - sqrtTwoAddSeries 0 n / 4 := by
rw [sin_sq_pi_over_two_pow, sqrtTwoAddSeries, div_pow, sq_sqrt, add_div, ← sub_sub]
· congr
· norm_num
· norm_num
· exact add_nonneg two_pos.le (sqrtTwoAddSeries_zero_nonneg _)
#align real.sin_sq_pi_over_two_pow_succ Real.sin_sq_pi_over_two_pow_succ
@[simp]
theorem sin_pi_over_two_pow_succ (n : ℕ) :
sin (π / 2 ^ (n + 2)) = √(2 - sqrtTwoAddSeries 0 n) / 2 := by
rw [eq_div_iff_mul_eq two_ne_zero, eq_comm, sqrt_eq_iff_sq_eq, mul_pow,
sin_sq_pi_over_two_pow_succ, sub_mul]
· congr <;> norm_num
· rw [sub_nonneg]
exact (sqrtTwoAddSeries_lt_two _).le
refine mul_nonneg (sin_nonneg_of_nonneg_of_le_pi ?_ ?_) zero_le_two
· positivity
· exact div_le_self pi_pos.le <| one_le_pow_of_one_le one_le_two _
#align real.sin_pi_over_two_pow_succ Real.sin_pi_over_two_pow_succ
@[simp]
theorem cos_pi_div_four : cos (π / 4) = √2 / 2 := by
trans cos (π / 2 ^ 2)
· congr
norm_num
· simp
#align real.cos_pi_div_four Real.cos_pi_div_four
@[simp]
theorem sin_pi_div_four : sin (π / 4) = √2 / 2 := by
trans sin (π / 2 ^ 2)
· congr
norm_num
· simp
#align real.sin_pi_div_four Real.sin_pi_div_four
@[simp]
theorem cos_pi_div_eight : cos (π / 8) = √(2 + √2) / 2 := by
trans cos (π / 2 ^ 3)
· congr
norm_num
· simp
#align real.cos_pi_div_eight Real.cos_pi_div_eight
@[simp]
theorem sin_pi_div_eight : sin (π / 8) = √(2 - √2) / 2 := by
trans sin (π / 2 ^ 3)
· congr
norm_num
· simp
#align real.sin_pi_div_eight Real.sin_pi_div_eight
@[simp]
theorem cos_pi_div_sixteen : cos (π / 16) = √(2 + √(2 + √2)) / 2 := by
trans cos (π / 2 ^ 4)
· congr
norm_num
· simp
#align real.cos_pi_div_sixteen Real.cos_pi_div_sixteen
@[simp]
theorem sin_pi_div_sixteen : sin (π / 16) = √(2 - √(2 + √2)) / 2 := by
trans sin (π / 2 ^ 4)
· congr
norm_num
· simp
#align real.sin_pi_div_sixteen Real.sin_pi_div_sixteen
@[simp]
theorem cos_pi_div_thirty_two : cos (π / 32) = √(2 + √(2 + √(2 + √2))) / 2 := by
trans cos (π / 2 ^ 5)
· congr
norm_num
· simp
#align real.cos_pi_div_thirty_two Real.cos_pi_div_thirty_two
@[simp]
theorem sin_pi_div_thirty_two : sin (π / 32) = √(2 - √(2 + √(2 + √2))) / 2 := by
trans sin (π / 2 ^ 5)
· congr
norm_num
· simp
#align real.sin_pi_div_thirty_two Real.sin_pi_div_thirty_two
-- This section is also a convenient location for other explicit values of `sin` and `cos`.
/-- The cosine of `π / 3` is `1 / 2`. -/
@[simp]
theorem cos_pi_div_three : cos (π / 3) = 1 / 2 := by
have h₁ : (2 * cos (π / 3) - 1) ^ 2 * (2 * cos (π / 3) + 2) = 0 := by
have : cos (3 * (π / 3)) = cos π := by
congr 1
ring
linarith [cos_pi, cos_three_mul (π / 3)]
cases' mul_eq_zero.mp h₁ with h h
· linarith [pow_eq_zero h]
· have : cos π < cos (π / 3) := by
refine cos_lt_cos_of_nonneg_of_le_pi ?_ le_rfl ?_ <;> linarith [pi_pos]
linarith [cos_pi]
#align real.cos_pi_div_three Real.cos_pi_div_three
/-- The cosine of `π / 6` is `√3 / 2`. -/
@[simp]
theorem cos_pi_div_six : cos (π / 6) = √3 / 2 := by
rw [show (6 : ℝ) = 3 * 2 by norm_num, div_mul_eq_div_div, cos_half, cos_pi_div_three, one_add_div,
← div_mul_eq_div_div, two_add_one_eq_three, sqrt_div, sqrt_mul_self] <;> linarith [pi_pos]
#align real.cos_pi_div_six Real.cos_pi_div_six
/-- The square of the cosine of `π / 6` is `3 / 4` (this is sometimes more convenient than the
result for cosine itself). -/
| Mathlib/Analysis/SpecialFunctions/Trigonometric/Basic.lean | 907 | 908 | theorem sq_cos_pi_div_six : cos (π / 6) ^ 2 = 3 / 4 := by |
rw [cos_pi_div_six, div_pow, sq_sqrt] <;> norm_num
|
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Sébastien Gouëzel, Frédéric Dupuis
-/
import Mathlib.Algebra.DirectSum.Module
import Mathlib.Analysis.Complex.Basic
import Mathlib.Analysis.Convex.Uniform
import Mathlib.Analysis.NormedSpace.Completion
import Mathlib.Analysis.NormedSpace.BoundedLinearMaps
#align_import analysis.inner_product_space.basic from "leanprover-community/mathlib"@"3f655f5297b030a87d641ad4e825af8d9679eb0b"
/-!
# Inner product space
This file defines inner product spaces and proves the basic properties. We do not formally
define Hilbert spaces, but they can be obtained using the set of assumptions
`[NormedAddCommGroup E] [InnerProductSpace 𝕜 E] [CompleteSpace E]`.
An inner product space is a vector space endowed with an inner product. It generalizes the notion of
dot product in `ℝ^n` and provides the means of defining the length of a vector and the angle between
two vectors. In particular vectors `x` and `y` are orthogonal if their inner product equals zero.
We define both the real and complex cases at the same time using the `RCLike` typeclass.
This file proves general results on inner product spaces. For the specific construction of an inner
product structure on `n → 𝕜` for `𝕜 = ℝ` or `ℂ`, see `EuclideanSpace` in
`Analysis.InnerProductSpace.PiL2`.
## Main results
- We define the class `InnerProductSpace 𝕜 E` extending `NormedSpace 𝕜 E` with a number of basic
properties, most notably the Cauchy-Schwarz inequality. Here `𝕜` is understood to be either `ℝ`
or `ℂ`, through the `RCLike` typeclass.
- We show that the inner product is continuous, `continuous_inner`, and bundle it as the
continuous sesquilinear map `innerSL` (see also `innerₛₗ` for the non-continuous version).
- We define `Orthonormal`, a predicate on a function `v : ι → E`, and prove the existence of a
maximal orthonormal set, `exists_maximal_orthonormal`. Bessel's inequality,
`Orthonormal.tsum_inner_products_le`, states that given an orthonormal set `v` and a vector `x`,
the sum of the norm-squares of the inner products `⟪v i, x⟫` is no more than the norm-square of
`x`. For the existence of orthonormal bases, Hilbert bases, etc., see the file
`Analysis.InnerProductSpace.projection`.
## Notation
We globally denote the real and complex inner products by `⟪·, ·⟫_ℝ` and `⟪·, ·⟫_ℂ` respectively.
We also provide two notation namespaces: `RealInnerProductSpace`, `ComplexInnerProductSpace`,
which respectively introduce the plain notation `⟪·, ·⟫` for the real and complex inner product.
## Implementation notes
We choose the convention that inner products are conjugate linear in the first argument and linear
in the second.
## Tags
inner product space, Hilbert space, norm
## References
* [Clément & Martin, *The Lax-Milgram Theorem. A detailed proof to be formalized in Coq*]
* [Clément & Martin, *A Coq formal proof of the Lax–Milgram theorem*]
The Coq code is available at the following address: <http://www.lri.fr/~sboldo/elfic/index.html>
-/
noncomputable section
open RCLike Real Filter
open Topology ComplexConjugate
open LinearMap (BilinForm)
variable {𝕜 E F : Type*} [RCLike 𝕜]
/-- Syntactic typeclass for types endowed with an inner product -/
class Inner (𝕜 E : Type*) where
/-- The inner product function. -/
inner : E → E → 𝕜
#align has_inner Inner
export Inner (inner)
/-- The inner product with values in `𝕜`. -/
notation3:max "⟪" x ", " y "⟫_" 𝕜:max => @inner 𝕜 _ _ x y
section Notations
/-- The inner product with values in `ℝ`. -/
scoped[RealInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℝ _ _ x y
/-- The inner product with values in `ℂ`. -/
scoped[ComplexInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℂ _ _ x y
end Notations
/-- An inner product space is a vector space with an additional operation called inner product.
The norm could be derived from the inner product, instead we require the existence of a norm and
the fact that `‖x‖^2 = re ⟪x, x⟫` to be able to put instances on `𝕂` or product
spaces.
To construct a norm from an inner product, see `InnerProductSpace.ofCore`.
-/
class InnerProductSpace (𝕜 : Type*) (E : Type*) [RCLike 𝕜] [NormedAddCommGroup E] extends
NormedSpace 𝕜 E, Inner 𝕜 E where
/-- The inner product induces the norm. -/
norm_sq_eq_inner : ∀ x : E, ‖x‖ ^ 2 = re (inner x x)
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space InnerProductSpace
/-!
### Constructing a normed space structure from an inner product
In the definition of an inner product space, we require the existence of a norm, which is equal
(but maybe not defeq) to the square root of the scalar product. This makes it possible to put
an inner product space structure on spaces with a preexisting norm (for instance `ℝ`), with good
properties. However, sometimes, one would like to define the norm starting only from a well-behaved
scalar product. This is what we implement in this paragraph, starting from a structure
`InnerProductSpace.Core` stating that we have a nice scalar product.
Our goal here is not to develop a whole theory with all the supporting API, as this will be done
below for `InnerProductSpace`. Instead, we implement the bare minimum to go as directly as
possible to the construction of the norm and the proof of the triangular inequality.
Warning: Do not use this `Core` structure if the space you are interested in already has a norm
instance defined on it, otherwise this will create a second non-defeq norm instance!
-/
/-- A structure requiring that a scalar product is positive definite and symmetric, from which one
can construct an `InnerProductSpace` instance in `InnerProductSpace.ofCore`. -/
-- @[nolint HasNonemptyInstance] porting note: I don't think we have this linter anymore
structure InnerProductSpace.Core (𝕜 : Type*) (F : Type*) [RCLike 𝕜] [AddCommGroup F]
[Module 𝕜 F] extends Inner 𝕜 F where
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is positive (semi)definite. -/
nonneg_re : ∀ x, 0 ≤ re (inner x x)
/-- The inner product is positive definite. -/
definite : ∀ x, inner x x = 0 → x = 0
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space.core InnerProductSpace.Core
/- We set `InnerProductSpace.Core` to be a class as we will use it as such in the construction
of the normed space structure that it produces. However, all the instances we will use will be
local to this proof. -/
attribute [class] InnerProductSpace.Core
/-- Define `InnerProductSpace.Core` from `InnerProductSpace`. Defined to reuse lemmas about
`InnerProductSpace.Core` for `InnerProductSpace`s. Note that the `Norm` instance provided by
`InnerProductSpace.Core.norm` is propositionally but not definitionally equal to the original
norm. -/
def InnerProductSpace.toCore [NormedAddCommGroup E] [c : InnerProductSpace 𝕜 E] :
InnerProductSpace.Core 𝕜 E :=
{ c with
nonneg_re := fun x => by
rw [← InnerProductSpace.norm_sq_eq_inner]
apply sq_nonneg
definite := fun x hx =>
norm_eq_zero.1 <| pow_eq_zero (n := 2) <| by
rw [InnerProductSpace.norm_sq_eq_inner (𝕜 := 𝕜) x, hx, map_zero] }
#align inner_product_space.to_core InnerProductSpace.toCore
namespace InnerProductSpace.Core
variable [AddCommGroup F] [Module 𝕜 F] [c : InnerProductSpace.Core 𝕜 F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 F _ x y
local notation "normSqK" => @RCLike.normSq 𝕜 _
local notation "reK" => @RCLike.re 𝕜 _
local notation "ext_iff" => @RCLike.ext_iff 𝕜 _
local postfix:90 "†" => starRingEnd _
/-- Inner product defined by the `InnerProductSpace.Core` structure. We can't reuse
`InnerProductSpace.Core.toInner` because it takes `InnerProductSpace.Core` as an explicit
argument. -/
def toInner' : Inner 𝕜 F :=
c.toInner
#align inner_product_space.core.to_has_inner' InnerProductSpace.Core.toInner'
attribute [local instance] toInner'
/-- The norm squared function for `InnerProductSpace.Core` structure. -/
def normSq (x : F) :=
reK ⟪x, x⟫
#align inner_product_space.core.norm_sq InnerProductSpace.Core.normSq
local notation "normSqF" => @normSq 𝕜 F _ _ _ _
theorem inner_conj_symm (x y : F) : ⟪y, x⟫† = ⟪x, y⟫ :=
c.conj_symm x y
#align inner_product_space.core.inner_conj_symm InnerProductSpace.Core.inner_conj_symm
theorem inner_self_nonneg {x : F} : 0 ≤ re ⟪x, x⟫ :=
c.nonneg_re _
#align inner_product_space.core.inner_self_nonneg InnerProductSpace.Core.inner_self_nonneg
theorem inner_self_im (x : F) : im ⟪x, x⟫ = 0 := by
rw [← @ofReal_inj 𝕜, im_eq_conj_sub]
simp [inner_conj_symm]
#align inner_product_space.core.inner_self_im InnerProductSpace.Core.inner_self_im
theorem inner_add_left (x y z : F) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
c.add_left _ _ _
#align inner_product_space.core.inner_add_left InnerProductSpace.Core.inner_add_left
theorem inner_add_right (x y z : F) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]; simp only [inner_conj_symm]
#align inner_product_space.core.inner_add_right InnerProductSpace.Core.inner_add_right
theorem ofReal_normSq_eq_inner_self (x : F) : (normSqF x : 𝕜) = ⟪x, x⟫ := by
rw [ext_iff]
exact ⟨by simp only [ofReal_re]; rfl, by simp only [inner_self_im, ofReal_im]⟩
#align inner_product_space.core.coe_norm_sq_eq_inner_self InnerProductSpace.Core.ofReal_normSq_eq_inner_self
theorem inner_re_symm (x y : F) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
#align inner_product_space.core.inner_re_symm InnerProductSpace.Core.inner_re_symm
theorem inner_im_symm (x y : F) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
#align inner_product_space.core.inner_im_symm InnerProductSpace.Core.inner_im_symm
theorem inner_smul_left (x y : F) {r : 𝕜} : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
c.smul_left _ _ _
#align inner_product_space.core.inner_smul_left InnerProductSpace.Core.inner_smul_left
theorem inner_smul_right (x y : F) {r : 𝕜} : ⟪x, r • y⟫ = r * ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left];
simp only [conj_conj, inner_conj_symm, RingHom.map_mul]
#align inner_product_space.core.inner_smul_right InnerProductSpace.Core.inner_smul_right
theorem inner_zero_left (x : F) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : F), inner_smul_left];
simp only [zero_mul, RingHom.map_zero]
#align inner_product_space.core.inner_zero_left InnerProductSpace.Core.inner_zero_left
theorem inner_zero_right (x : F) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left]; simp only [RingHom.map_zero]
#align inner_product_space.core.inner_zero_right InnerProductSpace.Core.inner_zero_right
theorem inner_self_eq_zero {x : F} : ⟪x, x⟫ = 0 ↔ x = 0 :=
⟨c.definite _, by
rintro rfl
exact inner_zero_left _⟩
#align inner_product_space.core.inner_self_eq_zero InnerProductSpace.Core.inner_self_eq_zero
theorem normSq_eq_zero {x : F} : normSqF x = 0 ↔ x = 0 :=
Iff.trans
(by simp only [normSq, ext_iff, map_zero, inner_self_im, eq_self_iff_true, and_true_iff])
(@inner_self_eq_zero 𝕜 _ _ _ _ _ x)
#align inner_product_space.core.norm_sq_eq_zero InnerProductSpace.Core.normSq_eq_zero
theorem inner_self_ne_zero {x : F} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
#align inner_product_space.core.inner_self_ne_zero InnerProductSpace.Core.inner_self_ne_zero
theorem inner_self_ofReal_re (x : F) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ := by
norm_num [ext_iff, inner_self_im]
set_option linter.uppercaseLean3 false in
#align inner_product_space.core.inner_self_re_to_K InnerProductSpace.Core.inner_self_ofReal_re
theorem norm_inner_symm (x y : F) : ‖⟪x, y⟫‖ = ‖⟪y, x⟫‖ := by rw [← inner_conj_symm, norm_conj]
#align inner_product_space.core.norm_inner_symm InnerProductSpace.Core.norm_inner_symm
theorem inner_neg_left (x y : F) : ⟪-x, y⟫ = -⟪x, y⟫ := by
rw [← neg_one_smul 𝕜 x, inner_smul_left]
simp
#align inner_product_space.core.inner_neg_left InnerProductSpace.Core.inner_neg_left
theorem inner_neg_right (x y : F) : ⟪x, -y⟫ = -⟪x, y⟫ := by
rw [← inner_conj_symm, inner_neg_left]; simp only [RingHom.map_neg, inner_conj_symm]
#align inner_product_space.core.inner_neg_right InnerProductSpace.Core.inner_neg_right
theorem inner_sub_left (x y z : F) : ⟪x - y, z⟫ = ⟪x, z⟫ - ⟪y, z⟫ := by
simp [sub_eq_add_neg, inner_add_left, inner_neg_left]
#align inner_product_space.core.inner_sub_left InnerProductSpace.Core.inner_sub_left
theorem inner_sub_right (x y z : F) : ⟪x, y - z⟫ = ⟪x, y⟫ - ⟪x, z⟫ := by
simp [sub_eq_add_neg, inner_add_right, inner_neg_right]
#align inner_product_space.core.inner_sub_right InnerProductSpace.Core.inner_sub_right
theorem inner_mul_symm_re_eq_norm (x y : F) : re (⟪x, y⟫ * ⟪y, x⟫) = ‖⟪x, y⟫ * ⟪y, x⟫‖ := by
rw [← inner_conj_symm, mul_comm]
exact re_eq_norm_of_mul_conj (inner y x)
#align inner_product_space.core.inner_mul_symm_re_eq_norm InnerProductSpace.Core.inner_mul_symm_re_eq_norm
/-- Expand `inner (x + y) (x + y)` -/
theorem inner_add_add_self (x y : F) : ⟪x + y, x + y⟫ = ⟪x, x⟫ + ⟪x, y⟫ + ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_add_left, inner_add_right]; ring
#align inner_product_space.core.inner_add_add_self InnerProductSpace.Core.inner_add_add_self
-- Expand `inner (x - y) (x - y)`
theorem inner_sub_sub_self (x y : F) : ⟪x - y, x - y⟫ = ⟪x, x⟫ - ⟪x, y⟫ - ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_sub_left, inner_sub_right]; ring
#align inner_product_space.core.inner_sub_sub_self InnerProductSpace.Core.inner_sub_sub_self
/-- An auxiliary equality useful to prove the **Cauchy–Schwarz inequality**: the square of the norm
of `⟪x, y⟫ • x - ⟪x, x⟫ • y` is equal to `‖x‖ ^ 2 * (‖x‖ ^ 2 * ‖y‖ ^ 2 - ‖⟪x, y⟫‖ ^ 2)`. We use
`InnerProductSpace.ofCore.normSq x` etc (defeq to `is_R_or_C.re ⟪x, x⟫`) instead of `‖x‖ ^ 2`
etc to avoid extra rewrites when applying it to an `InnerProductSpace`. -/
theorem cauchy_schwarz_aux (x y : F) :
normSqF (⟪x, y⟫ • x - ⟪x, x⟫ • y) = normSqF x * (normSqF x * normSqF y - ‖⟪x, y⟫‖ ^ 2) := by
rw [← @ofReal_inj 𝕜, ofReal_normSq_eq_inner_self]
simp only [inner_sub_sub_self, inner_smul_left, inner_smul_right, conj_ofReal, mul_sub, ←
ofReal_normSq_eq_inner_self x, ← ofReal_normSq_eq_inner_self y]
rw [← mul_assoc, mul_conj, RCLike.conj_mul, mul_left_comm, ← inner_conj_symm y, mul_conj]
push_cast
ring
#align inner_product_space.core.cauchy_schwarz_aux InnerProductSpace.Core.cauchy_schwarz_aux
/-- **Cauchy–Schwarz inequality**.
We need this for the `Core` structure to prove the triangle inequality below when
showing the core is a normed group.
-/
theorem inner_mul_inner_self_le (x y : F) : ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ := by
rcases eq_or_ne x 0 with (rfl | hx)
· simpa only [inner_zero_left, map_zero, zero_mul, norm_zero] using le_rfl
· have hx' : 0 < normSqF x := inner_self_nonneg.lt_of_ne' (mt normSq_eq_zero.1 hx)
rw [← sub_nonneg, ← mul_nonneg_iff_right_nonneg_of_pos hx', ← normSq, ← normSq,
norm_inner_symm y, ← sq, ← cauchy_schwarz_aux]
exact inner_self_nonneg
#align inner_product_space.core.inner_mul_inner_self_le InnerProductSpace.Core.inner_mul_inner_self_le
/-- Norm constructed from an `InnerProductSpace.Core` structure, defined to be the square root
of the scalar product. -/
def toNorm : Norm F where norm x := √(re ⟪x, x⟫)
#align inner_product_space.core.to_has_norm InnerProductSpace.Core.toNorm
attribute [local instance] toNorm
theorem norm_eq_sqrt_inner (x : F) : ‖x‖ = √(re ⟪x, x⟫) := rfl
#align inner_product_space.core.norm_eq_sqrt_inner InnerProductSpace.Core.norm_eq_sqrt_inner
theorem inner_self_eq_norm_mul_norm (x : F) : re ⟪x, x⟫ = ‖x‖ * ‖x‖ := by
rw [norm_eq_sqrt_inner, ← sqrt_mul inner_self_nonneg (re ⟪x, x⟫), sqrt_mul_self inner_self_nonneg]
#align inner_product_space.core.inner_self_eq_norm_mul_norm InnerProductSpace.Core.inner_self_eq_norm_mul_norm
theorem sqrt_normSq_eq_norm (x : F) : √(normSqF x) = ‖x‖ := rfl
#align inner_product_space.core.sqrt_norm_sq_eq_norm InnerProductSpace.Core.sqrt_normSq_eq_norm
/-- Cauchy–Schwarz inequality with norm -/
theorem norm_inner_le_norm (x y : F) : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ :=
nonneg_le_nonneg_of_sq_le_sq (mul_nonneg (sqrt_nonneg _) (sqrt_nonneg _)) <|
calc
‖⟪x, y⟫‖ * ‖⟪x, y⟫‖ = ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ := by rw [norm_inner_symm]
_ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ := inner_mul_inner_self_le x y
_ = ‖x‖ * ‖y‖ * (‖x‖ * ‖y‖) := by simp only [inner_self_eq_norm_mul_norm]; ring
#align inner_product_space.core.norm_inner_le_norm InnerProductSpace.Core.norm_inner_le_norm
/-- Normed group structure constructed from an `InnerProductSpace.Core` structure -/
def toNormedAddCommGroup : NormedAddCommGroup F :=
AddGroupNorm.toNormedAddCommGroup
{ toFun := fun x => √(re ⟪x, x⟫)
map_zero' := by simp only [sqrt_zero, inner_zero_right, map_zero]
neg' := fun x => by simp only [inner_neg_left, neg_neg, inner_neg_right]
add_le' := fun x y => by
have h₁ : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ := norm_inner_le_norm _ _
have h₂ : re ⟪x, y⟫ ≤ ‖⟪x, y⟫‖ := re_le_norm _
have h₃ : re ⟪x, y⟫ ≤ ‖x‖ * ‖y‖ := h₂.trans h₁
have h₄ : re ⟪y, x⟫ ≤ ‖x‖ * ‖y‖ := by rwa [← inner_conj_symm, conj_re]
have : ‖x + y‖ * ‖x + y‖ ≤ (‖x‖ + ‖y‖) * (‖x‖ + ‖y‖) := by
simp only [← inner_self_eq_norm_mul_norm, inner_add_add_self, mul_add, mul_comm, map_add]
linarith
exact nonneg_le_nonneg_of_sq_le_sq (add_nonneg (sqrt_nonneg _) (sqrt_nonneg _)) this
eq_zero_of_map_eq_zero' := fun x hx =>
normSq_eq_zero.1 <| (sqrt_eq_zero inner_self_nonneg).1 hx }
#align inner_product_space.core.to_normed_add_comm_group InnerProductSpace.Core.toNormedAddCommGroup
attribute [local instance] toNormedAddCommGroup
/-- Normed space structure constructed from an `InnerProductSpace.Core` structure -/
def toNormedSpace : NormedSpace 𝕜 F where
norm_smul_le r x := by
rw [norm_eq_sqrt_inner, inner_smul_left, inner_smul_right, ← mul_assoc]
rw [RCLike.conj_mul, ← ofReal_pow, re_ofReal_mul, sqrt_mul, ← ofReal_normSq_eq_inner_self,
ofReal_re]
· simp [sqrt_normSq_eq_norm, RCLike.sqrt_normSq_eq_norm]
· positivity
#align inner_product_space.core.to_normed_space InnerProductSpace.Core.toNormedSpace
end InnerProductSpace.Core
section
attribute [local instance] InnerProductSpace.Core.toNormedAddCommGroup
/-- Given an `InnerProductSpace.Core` structure on a space, one can use it to turn
the space into an inner product space. The `NormedAddCommGroup` structure is expected
to already be defined with `InnerProductSpace.ofCore.toNormedAddCommGroup`. -/
def InnerProductSpace.ofCore [AddCommGroup F] [Module 𝕜 F] (c : InnerProductSpace.Core 𝕜 F) :
InnerProductSpace 𝕜 F :=
letI : NormedSpace 𝕜 F := @InnerProductSpace.Core.toNormedSpace 𝕜 F _ _ _ c
{ c with
norm_sq_eq_inner := fun x => by
have h₁ : ‖x‖ ^ 2 = √(re (c.inner x x)) ^ 2 := rfl
have h₂ : 0 ≤ re (c.inner x x) := InnerProductSpace.Core.inner_self_nonneg
simp [h₁, sq_sqrt, h₂] }
#align inner_product_space.of_core InnerProductSpace.ofCore
end
/-! ### Properties of inner product spaces -/
variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [NormedAddCommGroup F] [InnerProductSpace ℝ F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
local notation "IK" => @RCLike.I 𝕜 _
local postfix:90 "†" => starRingEnd _
export InnerProductSpace (norm_sq_eq_inner)
section BasicProperties
@[simp]
theorem inner_conj_symm (x y : E) : ⟪y, x⟫† = ⟪x, y⟫ :=
InnerProductSpace.conj_symm _ _
#align inner_conj_symm inner_conj_symm
theorem real_inner_comm (x y : F) : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ :=
@inner_conj_symm ℝ _ _ _ _ x y
#align real_inner_comm real_inner_comm
theorem inner_eq_zero_symm {x y : E} : ⟪x, y⟫ = 0 ↔ ⟪y, x⟫ = 0 := by
rw [← inner_conj_symm]
exact star_eq_zero
#align inner_eq_zero_symm inner_eq_zero_symm
@[simp]
theorem inner_self_im (x : E) : im ⟪x, x⟫ = 0 := by rw [← @ofReal_inj 𝕜, im_eq_conj_sub]; simp
#align inner_self_im inner_self_im
theorem inner_add_left (x y z : E) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
InnerProductSpace.add_left _ _ _
#align inner_add_left inner_add_left
theorem inner_add_right (x y z : E) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]
simp only [inner_conj_symm]
#align inner_add_right inner_add_right
theorem inner_re_symm (x y : E) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
#align inner_re_symm inner_re_symm
theorem inner_im_symm (x y : E) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
#align inner_im_symm inner_im_symm
theorem inner_smul_left (x y : E) (r : 𝕜) : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
InnerProductSpace.smul_left _ _ _
#align inner_smul_left inner_smul_left
theorem real_inner_smul_left (x y : F) (r : ℝ) : ⟪r • x, y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_left _ _ _
#align real_inner_smul_left real_inner_smul_left
theorem inner_smul_real_left (x y : E) (r : ℝ) : ⟪(r : 𝕜) • x, y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_left, conj_ofReal, Algebra.smul_def]
rfl
#align inner_smul_real_left inner_smul_real_left
theorem inner_smul_right (x y : E) (r : 𝕜) : ⟪x, r • y⟫ = r * ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left, RingHom.map_mul, conj_conj, inner_conj_symm]
#align inner_smul_right inner_smul_right
theorem real_inner_smul_right (x y : F) (r : ℝ) : ⟪x, r • y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_right _ _ _
#align real_inner_smul_right real_inner_smul_right
theorem inner_smul_real_right (x y : E) (r : ℝ) : ⟪x, (r : 𝕜) • y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_right, Algebra.smul_def]
rfl
#align inner_smul_real_right inner_smul_real_right
/-- The inner product as a sesquilinear form.
Note that in the case `𝕜 = ℝ` this is a bilinear form. -/
@[simps!]
def sesqFormOfInner : E →ₗ[𝕜] E →ₗ⋆[𝕜] 𝕜 :=
LinearMap.mk₂'ₛₗ (RingHom.id 𝕜) (starRingEnd _) (fun x y => ⟪y, x⟫)
(fun _x _y _z => inner_add_right _ _ _) (fun _r _x _y => inner_smul_right _ _ _)
(fun _x _y _z => inner_add_left _ _ _) fun _r _x _y => inner_smul_left _ _ _
#align sesq_form_of_inner sesqFormOfInner
/-- The real inner product as a bilinear form.
Note that unlike `sesqFormOfInner`, this does not reverse the order of the arguments. -/
@[simps!]
def bilinFormOfRealInner : BilinForm ℝ F := sesqFormOfInner.flip
#align bilin_form_of_real_inner bilinFormOfRealInner
/-- An inner product with a sum on the left. -/
theorem sum_inner {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪∑ i ∈ s, f i, x⟫ = ∑ i ∈ s, ⟪f i, x⟫ :=
map_sum (sesqFormOfInner (𝕜 := 𝕜) (E := E) x) _ _
#align sum_inner sum_inner
/-- An inner product with a sum on the right. -/
theorem inner_sum {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪x, ∑ i ∈ s, f i⟫ = ∑ i ∈ s, ⟪x, f i⟫ :=
map_sum (LinearMap.flip sesqFormOfInner x) _ _
#align inner_sum inner_sum
/-- An inner product with a sum on the left, `Finsupp` version. -/
theorem Finsupp.sum_inner {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪l.sum fun (i : ι) (a : 𝕜) => a • v i, x⟫ = l.sum fun (i : ι) (a : 𝕜) => conj a • ⟪v i, x⟫ := by
convert _root_.sum_inner (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_left, Finsupp.sum, smul_eq_mul]
#align finsupp.sum_inner Finsupp.sum_inner
/-- An inner product with a sum on the right, `Finsupp` version. -/
theorem Finsupp.inner_sum {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪x, l.sum fun (i : ι) (a : 𝕜) => a • v i⟫ = l.sum fun (i : ι) (a : 𝕜) => a • ⟪x, v i⟫ := by
convert _root_.inner_sum (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_right, Finsupp.sum, smul_eq_mul]
#align finsupp.inner_sum Finsupp.inner_sum
theorem DFinsupp.sum_inner {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪l.sum f, x⟫ = l.sum fun i a => ⟪f i a, x⟫ := by
simp (config := { contextual := true }) only [DFinsupp.sum, _root_.sum_inner, smul_eq_mul]
#align dfinsupp.sum_inner DFinsupp.sum_inner
theorem DFinsupp.inner_sum {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪x, l.sum f⟫ = l.sum fun i a => ⟪x, f i a⟫ := by
simp (config := { contextual := true }) only [DFinsupp.sum, _root_.inner_sum, smul_eq_mul]
#align dfinsupp.inner_sum DFinsupp.inner_sum
@[simp]
theorem inner_zero_left (x : E) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : E), inner_smul_left, RingHom.map_zero, zero_mul]
#align inner_zero_left inner_zero_left
theorem inner_re_zero_left (x : E) : re ⟪0, x⟫ = 0 := by
simp only [inner_zero_left, AddMonoidHom.map_zero]
#align inner_re_zero_left inner_re_zero_left
@[simp]
theorem inner_zero_right (x : E) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left, RingHom.map_zero]
#align inner_zero_right inner_zero_right
theorem inner_re_zero_right (x : E) : re ⟪x, 0⟫ = 0 := by
simp only [inner_zero_right, AddMonoidHom.map_zero]
#align inner_re_zero_right inner_re_zero_right
theorem inner_self_nonneg {x : E} : 0 ≤ re ⟪x, x⟫ :=
InnerProductSpace.toCore.nonneg_re x
#align inner_self_nonneg inner_self_nonneg
theorem real_inner_self_nonneg {x : F} : 0 ≤ ⟪x, x⟫_ℝ :=
@inner_self_nonneg ℝ F _ _ _ x
#align real_inner_self_nonneg real_inner_self_nonneg
@[simp]
theorem inner_self_ofReal_re (x : E) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ :=
((RCLike.is_real_TFAE (⟪x, x⟫ : 𝕜)).out 2 3).2 (inner_self_im _)
set_option linter.uppercaseLean3 false in
#align inner_self_re_to_K inner_self_ofReal_re
theorem inner_self_eq_norm_sq_to_K (x : E) : ⟪x, x⟫ = (‖x‖ : 𝕜) ^ 2 := by
rw [← inner_self_ofReal_re, ← norm_sq_eq_inner, ofReal_pow]
set_option linter.uppercaseLean3 false in
#align inner_self_eq_norm_sq_to_K inner_self_eq_norm_sq_to_K
theorem inner_self_re_eq_norm (x : E) : re ⟪x, x⟫ = ‖⟪x, x⟫‖ := by
conv_rhs => rw [← inner_self_ofReal_re]
symm
exact norm_of_nonneg inner_self_nonneg
#align inner_self_re_eq_norm inner_self_re_eq_norm
theorem inner_self_ofReal_norm (x : E) : (‖⟪x, x⟫‖ : 𝕜) = ⟪x, x⟫ := by
rw [← inner_self_re_eq_norm]
exact inner_self_ofReal_re _
set_option linter.uppercaseLean3 false in
#align inner_self_norm_to_K inner_self_ofReal_norm
theorem real_inner_self_abs (x : F) : |⟪x, x⟫_ℝ| = ⟪x, x⟫_ℝ :=
@inner_self_ofReal_norm ℝ F _ _ _ x
#align real_inner_self_abs real_inner_self_abs
@[simp]
theorem inner_self_eq_zero {x : E} : ⟪x, x⟫ = 0 ↔ x = 0 := by
rw [inner_self_eq_norm_sq_to_K, sq_eq_zero_iff, ofReal_eq_zero, norm_eq_zero]
#align inner_self_eq_zero inner_self_eq_zero
theorem inner_self_ne_zero {x : E} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
#align inner_self_ne_zero inner_self_ne_zero
@[simp]
| Mathlib/Analysis/InnerProductSpace/Basic.lean | 607 | 608 | theorem inner_self_nonpos {x : E} : re ⟪x, x⟫ ≤ 0 ↔ x = 0 := by |
rw [← norm_sq_eq_inner, (sq_nonneg _).le_iff_eq, sq_eq_zero_iff, norm_eq_zero]
|
/-
Copyright (c) 2019 Chris Hughes. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Chris Hughes
-/
import Mathlib.Data.Option.Basic
import Mathlib.Data.Set.Basic
#align_import data.pequiv from "leanprover-community/mathlib"@"7c3269ca3fa4c0c19e4d127cd7151edbdbf99ed4"
/-!
# Partial Equivalences
In this file, we define partial equivalences `PEquiv`, which are a bijection between a subset of `α`
and a subset of `β`. Notationally, a `PEquiv` is denoted by "`≃.`" (note that the full stop is part
of the notation). The way we store these internally is with two functions `f : α → Option β` and
the reverse function `g : β → Option α`, with the condition that if `f a` is `some b`,
then `g b` is `some a`.
## Main results
- `PEquiv.ofSet`: creates a `PEquiv` from a set `s`,
which sends an element to itself if it is in `s`.
- `PEquiv.single`: given two elements `a : α` and `b : β`, create a `PEquiv` that sends them to
each other, and ignores all other elements.
- `PEquiv.injective_of_forall_ne_isSome`/`injective_of_forall_isSome`: If the domain of a `PEquiv`
is all of `α` (except possibly one point), its `toFun` is injective.
## Canonical order
`PEquiv` is canonically ordered by inclusion; that is, if a function `f` defined on a subset `s`
is equal to `g` on that subset, but `g` is also defined on a larger set, then `f ≤ g`. We also have
a definition of `⊥`, which is the empty `PEquiv` (sends all to `none`), which in the end gives us a
`SemilatticeInf` with an `OrderBot` instance.
## Tags
pequiv, partial equivalence
-/
universe u v w x
/-- A `PEquiv` is a partial equivalence, a representation of a bijection between a subset
of `α` and a subset of `β`. See also `PartialEquiv` for a version that requires `toFun` and
`invFun` to be globally defined functions and has `source` and `target` sets as extra fields. -/
structure PEquiv (α : Type u) (β : Type v) where
/-- The underlying partial function of a `PEquiv` -/
toFun : α → Option β
/-- The partial inverse of `toFun` -/
invFun : β → Option α
/-- `invFun` is the partial inverse of `toFun` -/
inv : ∀ (a : α) (b : β), a ∈ invFun b ↔ b ∈ toFun a
#align pequiv PEquiv
/-- A `PEquiv` is a partial equivalence, a representation of a bijection between a subset
of `α` and a subset of `β`. See also `PartialEquiv` for a version that requires `toFun` and
`invFun` to be globally defined functions and has `source` and `target` sets as extra fields. -/
infixr:25 " ≃. " => PEquiv
namespace PEquiv
variable {α : Type u} {β : Type v} {γ : Type w} {δ : Type x}
open Function Option
instance : FunLike (α ≃. β) α (Option β) :=
{ coe := toFun
coe_injective' := by
rintro ⟨f₁, f₂, hf⟩ ⟨g₁, g₂, hg⟩ (rfl : f₁ = g₁)
congr with y x
simp only [hf, hg] }
@[simp] theorem coe_mk (f₁ : α → Option β) (f₂ h) : (mk f₁ f₂ h : α → Option β) = f₁ :=
rfl
theorem coe_mk_apply (f₁ : α → Option β) (f₂ : β → Option α) (h) (x : α) :
(PEquiv.mk f₁ f₂ h : α → Option β) x = f₁ x :=
rfl
#align pequiv.coe_mk_apply PEquiv.coe_mk_apply
@[ext] theorem ext {f g : α ≃. β} (h : ∀ x, f x = g x) : f = g :=
DFunLike.ext f g h
#align pequiv.ext PEquiv.ext
theorem ext_iff {f g : α ≃. β} : f = g ↔ ∀ x, f x = g x :=
DFunLike.ext_iff
#align pequiv.ext_iff PEquiv.ext_iff
/-- The identity map as a partial equivalence. -/
@[refl]
protected def refl (α : Type*) : α ≃. α where
toFun := some
invFun := some
inv _ _ := eq_comm
#align pequiv.refl PEquiv.refl
/-- The inverse partial equivalence. -/
@[symm]
protected def symm (f : α ≃. β) : β ≃. α where
toFun := f.2
invFun := f.1
inv _ _ := (f.inv _ _).symm
#align pequiv.symm PEquiv.symm
theorem mem_iff_mem (f : α ≃. β) : ∀ {a : α} {b : β}, a ∈ f.symm b ↔ b ∈ f a :=
f.3 _ _
#align pequiv.mem_iff_mem PEquiv.mem_iff_mem
theorem eq_some_iff (f : α ≃. β) : ∀ {a : α} {b : β}, f.symm b = some a ↔ f a = some b :=
f.3 _ _
#align pequiv.eq_some_iff PEquiv.eq_some_iff
/-- Composition of partial equivalences `f : α ≃. β` and `g : β ≃. γ`. -/
@[trans]
protected def trans (f : α ≃. β) (g : β ≃. γ) :
α ≃. γ where
toFun a := (f a).bind g
invFun a := (g.symm a).bind f.symm
inv a b := by simp_all [and_comm, eq_some_iff f, eq_some_iff g, bind_eq_some]
#align pequiv.trans PEquiv.trans
@[simp]
theorem refl_apply (a : α) : PEquiv.refl α a = some a :=
rfl
#align pequiv.refl_apply PEquiv.refl_apply
@[simp]
theorem symm_refl : (PEquiv.refl α).symm = PEquiv.refl α :=
rfl
#align pequiv.symm_refl PEquiv.symm_refl
@[simp]
theorem symm_symm (f : α ≃. β) : f.symm.symm = f := by cases f; rfl
#align pequiv.symm_symm PEquiv.symm_symm
theorem symm_bijective : Function.Bijective (PEquiv.symm : (α ≃. β) → β ≃. α) :=
Function.bijective_iff_has_inverse.mpr ⟨_, symm_symm, symm_symm⟩
theorem symm_injective : Function.Injective (@PEquiv.symm α β) :=
symm_bijective.injective
#align pequiv.symm_injective PEquiv.symm_injective
theorem trans_assoc (f : α ≃. β) (g : β ≃. γ) (h : γ ≃. δ) :
(f.trans g).trans h = f.trans (g.trans h) :=
ext fun _ => Option.bind_assoc _ _ _
#align pequiv.trans_assoc PEquiv.trans_assoc
theorem mem_trans (f : α ≃. β) (g : β ≃. γ) (a : α) (c : γ) :
c ∈ f.trans g a ↔ ∃ b, b ∈ f a ∧ c ∈ g b :=
Option.bind_eq_some'
#align pequiv.mem_trans PEquiv.mem_trans
theorem trans_eq_some (f : α ≃. β) (g : β ≃. γ) (a : α) (c : γ) :
f.trans g a = some c ↔ ∃ b, f a = some b ∧ g b = some c :=
Option.bind_eq_some'
#align pequiv.trans_eq_some PEquiv.trans_eq_some
theorem trans_eq_none (f : α ≃. β) (g : β ≃. γ) (a : α) :
f.trans g a = none ↔ ∀ b c, b ∉ f a ∨ c ∉ g b := by
simp only [eq_none_iff_forall_not_mem, mem_trans, imp_iff_not_or.symm]
push_neg
exact forall_swap
#align pequiv.trans_eq_none PEquiv.trans_eq_none
@[simp]
theorem refl_trans (f : α ≃. β) : (PEquiv.refl α).trans f = f := by
ext; dsimp [PEquiv.trans]; rfl
#align pequiv.refl_trans PEquiv.refl_trans
@[simp]
| Mathlib/Data/PEquiv.lean | 174 | 175 | theorem trans_refl (f : α ≃. β) : f.trans (PEquiv.refl β) = f := by |
ext; dsimp [PEquiv.trans]; simp
|
/-
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
| Mathlib/SetTheory/Ordinal/NaturalOps.lean | 242 | 244 | 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]
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Algebra.Group.Indicator
import Mathlib.Data.Finset.Piecewise
import Mathlib.Data.Finset.Preimage
#align_import algebra.big_operators.basic from "leanprover-community/mathlib"@"65a1391a0106c9204fe45bc73a039f056558cb83"
/-!
# Big operators
In this file we define products and sums indexed by finite sets (specifically, `Finset`).
## Notation
We introduce the following notation.
Let `s` be a `Finset α`, and `f : α → β` a function.
* `∏ x ∈ s, f x` is notation for `Finset.prod s f` (assuming `β` is a `CommMonoid`)
* `∑ x ∈ s, f x` is notation for `Finset.sum s f` (assuming `β` is an `AddCommMonoid`)
* `∏ x, f x` is notation for `Finset.prod Finset.univ f`
(assuming `α` is a `Fintype` and `β` is a `CommMonoid`)
* `∑ x, f x` is notation for `Finset.sum Finset.univ f`
(assuming `α` is a `Fintype` and `β` is an `AddCommMonoid`)
## Implementation Notes
The first arguments in all definitions and lemmas is the codomain of the function of the big
operator. This is necessary for the heuristic in `@[to_additive]`.
See the documentation of `to_additive.attr` for more information.
-/
-- TODO
-- assert_not_exists AddCommMonoidWithOne
assert_not_exists MonoidWithZero
assert_not_exists MulAction
variable {ι κ α β γ : Type*}
open Fin Function
namespace Finset
/-- `∏ x ∈ s, f x` is the product of `f x`
as `x` ranges over the elements of the finite set `s`.
-/
@[to_additive "`∑ x ∈ s, f x` is the sum of `f x` as `x` ranges over the elements
of the finite set `s`."]
protected def prod [CommMonoid β] (s : Finset α) (f : α → β) : β :=
(s.1.map f).prod
#align finset.prod Finset.prod
#align finset.sum Finset.sum
@[to_additive (attr := simp)]
theorem prod_mk [CommMonoid β] (s : Multiset α) (hs : s.Nodup) (f : α → β) :
(⟨s, hs⟩ : Finset α).prod f = (s.map f).prod :=
rfl
#align finset.prod_mk Finset.prod_mk
#align finset.sum_mk Finset.sum_mk
@[to_additive (attr := simp)]
theorem prod_val [CommMonoid α] (s : Finset α) : s.1.prod = s.prod id := by
rw [Finset.prod, Multiset.map_id]
#align finset.prod_val Finset.prod_val
#align finset.sum_val Finset.sum_val
end Finset
library_note "operator precedence of big operators"/--
There is no established mathematical convention
for the operator precedence of big operators like `∏` and `∑`.
We will have to make a choice.
Online discussions, such as https://math.stackexchange.com/q/185538/30839
seem to suggest that `∏` and `∑` should have the same precedence,
and that this should be somewhere between `*` and `+`.
The latter have precedence levels `70` and `65` respectively,
and we therefore choose the level `67`.
In practice, this means that parentheses should be placed as follows:
```lean
∑ k ∈ K, (a k + b k) = ∑ k ∈ K, a k + ∑ k ∈ K, b k →
∏ k ∈ K, a k * b k = (∏ k ∈ K, a k) * (∏ k ∈ K, b k)
```
(Example taken from page 490 of Knuth's *Concrete Mathematics*.)
-/
namespace BigOperators
open Batteries.ExtendedBinder Lean Meta
-- TODO: contribute this modification back to `extBinder`
/-- A `bigOpBinder` is like an `extBinder` and has the form `x`, `x : ty`, or `x pred`
where `pred` is a `binderPred` like `< 2`.
Unlike `extBinder`, `x` is a term. -/
syntax bigOpBinder := term:max ((" : " term) <|> binderPred)?
/-- A BigOperator binder in parentheses -/
syntax bigOpBinderParenthesized := " (" bigOpBinder ")"
/-- A list of parenthesized binders -/
syntax bigOpBinderCollection := bigOpBinderParenthesized+
/-- A single (unparenthesized) binder, or a list of parenthesized binders -/
syntax bigOpBinders := bigOpBinderCollection <|> (ppSpace bigOpBinder)
/-- Collects additional binder/Finset pairs for the given `bigOpBinder`.
Note: this is not extensible at the moment, unlike the usual `bigOpBinder` expansions. -/
def processBigOpBinder (processed : (Array (Term × Term)))
(binder : TSyntax ``bigOpBinder) : MacroM (Array (Term × Term)) :=
set_option hygiene false in
withRef binder do
match binder with
| `(bigOpBinder| $x:term) =>
match x with
| `(($a + $b = $n)) => -- Maybe this is too cute.
return processed |>.push (← `(⟨$a, $b⟩), ← `(Finset.Nat.antidiagonal $n))
| _ => return processed |>.push (x, ← ``(Finset.univ))
| `(bigOpBinder| $x : $t) => return processed |>.push (x, ← ``((Finset.univ : Finset $t)))
| `(bigOpBinder| $x ∈ $s) => return processed |>.push (x, ← `(finset% $s))
| `(bigOpBinder| $x < $n) => return processed |>.push (x, ← `(Finset.Iio $n))
| `(bigOpBinder| $x ≤ $n) => return processed |>.push (x, ← `(Finset.Iic $n))
| `(bigOpBinder| $x > $n) => return processed |>.push (x, ← `(Finset.Ioi $n))
| `(bigOpBinder| $x ≥ $n) => return processed |>.push (x, ← `(Finset.Ici $n))
| _ => Macro.throwUnsupported
/-- Collects the binder/Finset pairs for the given `bigOpBinders`. -/
def processBigOpBinders (binders : TSyntax ``bigOpBinders) :
MacroM (Array (Term × Term)) :=
match binders with
| `(bigOpBinders| $b:bigOpBinder) => processBigOpBinder #[] b
| `(bigOpBinders| $[($bs:bigOpBinder)]*) => bs.foldlM processBigOpBinder #[]
| _ => Macro.throwUnsupported
/-- Collect the binderIdents into a `⟨...⟩` expression. -/
def bigOpBindersPattern (processed : (Array (Term × Term))) :
MacroM Term := do
let ts := processed.map Prod.fst
if ts.size == 1 then
return ts[0]!
else
`(⟨$ts,*⟩)
/-- Collect the terms into a product of sets. -/
def bigOpBindersProd (processed : (Array (Term × Term))) :
MacroM Term := do
if processed.isEmpty then
`((Finset.univ : Finset Unit))
else if processed.size == 1 then
return processed[0]!.2
else
processed.foldrM (fun s p => `(SProd.sprod $(s.2) $p)) processed.back.2
(start := processed.size - 1)
/--
- `∑ x, f x` is notation for `Finset.sum Finset.univ f`. It is the sum of `f x`,
where `x` ranges over the finite domain of `f`.
- `∑ x ∈ s, f x` is notation for `Finset.sum s f`. It is the sum of `f x`,
where `x` ranges over the finite set `s` (either a `Finset` or a `Set` with a `Fintype` instance).
- `∑ x ∈ s with p x, f x` is notation for `Finset.sum (Finset.filter p s) f`.
- `∑ (x ∈ s) (y ∈ t), f x y` is notation for `Finset.sum (s ×ˢ t) (fun ⟨x, y⟩ ↦ f x y)`.
These support destructuring, for example `∑ ⟨x, y⟩ ∈ s ×ˢ t, f x y`.
Notation: `"∑" bigOpBinders* ("with" term)? "," term` -/
syntax (name := bigsum) "∑ " bigOpBinders ("with " term)? ", " term:67 : term
/--
- `∏ x, f x` is notation for `Finset.prod Finset.univ f`. It is the product of `f x`,
where `x` ranges over the finite domain of `f`.
- `∏ x ∈ s, f x` is notation for `Finset.prod s f`. It is the product of `f x`,
where `x` ranges over the finite set `s` (either a `Finset` or a `Set` with a `Fintype` instance).
- `∏ x ∈ s with p x, f x` is notation for `Finset.prod (Finset.filter p s) f`.
- `∏ (x ∈ s) (y ∈ t), f x y` is notation for `Finset.prod (s ×ˢ t) (fun ⟨x, y⟩ ↦ f x y)`.
These support destructuring, for example `∏ ⟨x, y⟩ ∈ s ×ˢ t, f x y`.
Notation: `"∏" bigOpBinders* ("with" term)? "," term` -/
syntax (name := bigprod) "∏ " bigOpBinders ("with " term)? ", " term:67 : term
macro_rules (kind := bigsum)
| `(∑ $bs:bigOpBinders $[with $p?]?, $v) => do
let processed ← processBigOpBinders bs
let x ← bigOpBindersPattern processed
let s ← bigOpBindersProd processed
match p? with
| some p => `(Finset.sum (Finset.filter (fun $x ↦ $p) $s) (fun $x ↦ $v))
| none => `(Finset.sum $s (fun $x ↦ $v))
macro_rules (kind := bigprod)
| `(∏ $bs:bigOpBinders $[with $p?]?, $v) => do
let processed ← processBigOpBinders bs
let x ← bigOpBindersPattern processed
let s ← bigOpBindersProd processed
match p? with
| some p => `(Finset.prod (Finset.filter (fun $x ↦ $p) $s) (fun $x ↦ $v))
| none => `(Finset.prod $s (fun $x ↦ $v))
/-- (Deprecated, use `∑ x ∈ s, f x`)
`∑ x in s, f x` is notation for `Finset.sum s f`. It is the sum of `f x`,
where `x` ranges over the finite set `s`. -/
syntax (name := bigsumin) "∑ " extBinder " in " term ", " term:67 : term
macro_rules (kind := bigsumin)
| `(∑ $x:ident in $s, $r) => `(∑ $x:ident ∈ $s, $r)
| `(∑ $x:ident : $t in $s, $r) => `(∑ $x:ident ∈ ($s : Finset $t), $r)
/-- (Deprecated, use `∏ x ∈ s, f x`)
`∏ x in s, f x` is notation for `Finset.prod s f`. It is the product of `f x`,
where `x` ranges over the finite set `s`. -/
syntax (name := bigprodin) "∏ " extBinder " in " term ", " term:67 : term
macro_rules (kind := bigprodin)
| `(∏ $x:ident in $s, $r) => `(∏ $x:ident ∈ $s, $r)
| `(∏ $x:ident : $t in $s, $r) => `(∏ $x:ident ∈ ($s : Finset $t), $r)
open Lean Meta Parser.Term PrettyPrinter.Delaborator SubExpr
open Batteries.ExtendedBinder
/-- Delaborator for `Finset.prod`. The `pp.piBinderTypes` option controls whether
to show the domain type when the product is over `Finset.univ`. -/
@[delab app.Finset.prod] def delabFinsetProd : Delab :=
whenPPOption getPPNotation <| withOverApp 5 <| do
let #[_, _, _, s, f] := (← getExpr).getAppArgs | failure
guard <| f.isLambda
let ppDomain ← getPPOption getPPPiBinderTypes
let (i, body) ← withAppArg <| withBindingBodyUnusedName fun i => do
return (i, ← delab)
if s.isAppOfArity ``Finset.univ 2 then
let binder ←
if ppDomain then
let ty ← withNaryArg 0 delab
`(bigOpBinder| $(.mk i):ident : $ty)
else
`(bigOpBinder| $(.mk i):ident)
`(∏ $binder:bigOpBinder, $body)
else
let ss ← withNaryArg 3 <| delab
`(∏ $(.mk i):ident ∈ $ss, $body)
/-- Delaborator for `Finset.sum`. The `pp.piBinderTypes` option controls whether
to show the domain type when the sum is over `Finset.univ`. -/
@[delab app.Finset.sum] def delabFinsetSum : Delab :=
whenPPOption getPPNotation <| withOverApp 5 <| do
let #[_, _, _, s, f] := (← getExpr).getAppArgs | failure
guard <| f.isLambda
let ppDomain ← getPPOption getPPPiBinderTypes
let (i, body) ← withAppArg <| withBindingBodyUnusedName fun i => do
return (i, ← delab)
if s.isAppOfArity ``Finset.univ 2 then
let binder ←
if ppDomain then
let ty ← withNaryArg 0 delab
`(bigOpBinder| $(.mk i):ident : $ty)
else
`(bigOpBinder| $(.mk i):ident)
`(∑ $binder:bigOpBinder, $body)
else
let ss ← withNaryArg 3 <| delab
`(∑ $(.mk i):ident ∈ $ss, $body)
end BigOperators
namespace Finset
variable {s s₁ s₂ : Finset α} {a : α} {f g : α → β}
@[to_additive]
theorem prod_eq_multiset_prod [CommMonoid β] (s : Finset α) (f : α → β) :
∏ x ∈ s, f x = (s.1.map f).prod :=
rfl
#align finset.prod_eq_multiset_prod Finset.prod_eq_multiset_prod
#align finset.sum_eq_multiset_sum Finset.sum_eq_multiset_sum
@[to_additive (attr := simp)]
lemma prod_map_val [CommMonoid β] (s : Finset α) (f : α → β) : (s.1.map f).prod = ∏ a ∈ s, f a :=
rfl
#align finset.prod_map_val Finset.prod_map_val
#align finset.sum_map_val Finset.sum_map_val
@[to_additive]
theorem prod_eq_fold [CommMonoid β] (s : Finset α) (f : α → β) :
∏ x ∈ s, f x = s.fold ((· * ·) : β → β → β) 1 f :=
rfl
#align finset.prod_eq_fold Finset.prod_eq_fold
#align finset.sum_eq_fold Finset.sum_eq_fold
@[simp]
theorem sum_multiset_singleton (s : Finset α) : (s.sum fun x => {x}) = s.val := by
simp only [sum_eq_multiset_sum, Multiset.sum_map_singleton]
#align finset.sum_multiset_singleton Finset.sum_multiset_singleton
end Finset
@[to_additive (attr := simp)]
theorem map_prod [CommMonoid β] [CommMonoid γ] {G : Type*} [FunLike G β γ] [MonoidHomClass G β γ]
(g : G) (f : α → β) (s : Finset α) : g (∏ x ∈ s, f x) = ∏ x ∈ s, g (f x) := by
simp only [Finset.prod_eq_multiset_prod, map_multiset_prod, Multiset.map_map]; rfl
#align map_prod map_prod
#align map_sum map_sum
@[to_additive]
theorem MonoidHom.coe_finset_prod [MulOneClass β] [CommMonoid γ] (f : α → β →* γ) (s : Finset α) :
⇑(∏ x ∈ s, f x) = ∏ x ∈ s, ⇑(f x) :=
map_prod (MonoidHom.coeFn β γ) _ _
#align monoid_hom.coe_finset_prod MonoidHom.coe_finset_prod
#align add_monoid_hom.coe_finset_sum AddMonoidHom.coe_finset_sum
/-- See also `Finset.prod_apply`, with the same conclusion but with the weaker hypothesis
`f : α → β → γ` -/
@[to_additive (attr := simp)
"See also `Finset.sum_apply`, with the same conclusion but with the weaker hypothesis
`f : α → β → γ`"]
theorem MonoidHom.finset_prod_apply [MulOneClass β] [CommMonoid γ] (f : α → β →* γ) (s : Finset α)
(b : β) : (∏ x ∈ s, f x) b = ∏ x ∈ s, f x b :=
map_prod (MonoidHom.eval b) _ _
#align monoid_hom.finset_prod_apply MonoidHom.finset_prod_apply
#align add_monoid_hom.finset_sum_apply AddMonoidHom.finset_sum_apply
variable {s s₁ s₂ : Finset α} {a : α} {f g : α → β}
namespace Finset
section CommMonoid
variable [CommMonoid β]
@[to_additive (attr := simp)]
theorem prod_empty : ∏ x ∈ ∅, f x = 1 :=
rfl
#align finset.prod_empty Finset.prod_empty
#align finset.sum_empty Finset.sum_empty
@[to_additive]
theorem prod_of_empty [IsEmpty α] (s : Finset α) : ∏ i ∈ s, f i = 1 := by
rw [eq_empty_of_isEmpty s, prod_empty]
#align finset.prod_of_empty Finset.prod_of_empty
#align finset.sum_of_empty Finset.sum_of_empty
@[to_additive (attr := simp)]
theorem prod_cons (h : a ∉ s) : ∏ x ∈ cons a s h, f x = f a * ∏ x ∈ s, f x :=
fold_cons h
#align finset.prod_cons Finset.prod_cons
#align finset.sum_cons Finset.sum_cons
@[to_additive (attr := simp)]
theorem prod_insert [DecidableEq α] : a ∉ s → ∏ x ∈ insert a s, f x = f a * ∏ x ∈ s, f x :=
fold_insert
#align finset.prod_insert Finset.prod_insert
#align finset.sum_insert Finset.sum_insert
/-- The product of `f` over `insert a s` is the same as
the product over `s`, as long as `a` is in `s` or `f a = 1`. -/
@[to_additive (attr := simp) "The sum of `f` over `insert a s` is the same as
the sum over `s`, as long as `a` is in `s` or `f a = 0`."]
theorem prod_insert_of_eq_one_if_not_mem [DecidableEq α] (h : a ∉ s → f a = 1) :
∏ x ∈ insert a s, f x = ∏ x ∈ s, f x := by
by_cases hm : a ∈ s
· simp_rw [insert_eq_of_mem hm]
· rw [prod_insert hm, h hm, one_mul]
#align finset.prod_insert_of_eq_one_if_not_mem Finset.prod_insert_of_eq_one_if_not_mem
#align finset.sum_insert_of_eq_zero_if_not_mem Finset.sum_insert_of_eq_zero_if_not_mem
/-- The product of `f` over `insert a s` is the same as
the product over `s`, as long as `f a = 1`. -/
@[to_additive (attr := simp) "The sum of `f` over `insert a s` is the same as
the sum over `s`, as long as `f a = 0`."]
theorem prod_insert_one [DecidableEq α] (h : f a = 1) : ∏ x ∈ insert a s, f x = ∏ x ∈ s, f x :=
prod_insert_of_eq_one_if_not_mem fun _ => h
#align finset.prod_insert_one Finset.prod_insert_one
#align finset.sum_insert_zero Finset.sum_insert_zero
@[to_additive]
theorem prod_insert_div {M : Type*} [CommGroup M] [DecidableEq α] (ha : a ∉ s) {f : α → M} :
(∏ x ∈ insert a s, f x) / f a = ∏ x ∈ s, f x := by simp [ha]
@[to_additive (attr := simp)]
theorem prod_singleton (f : α → β) (a : α) : ∏ x ∈ singleton a, f x = f a :=
Eq.trans fold_singleton <| mul_one _
#align finset.prod_singleton Finset.prod_singleton
#align finset.sum_singleton Finset.sum_singleton
@[to_additive]
theorem prod_pair [DecidableEq α] {a b : α} (h : a ≠ b) :
(∏ x ∈ ({a, b} : Finset α), f x) = f a * f b := by
rw [prod_insert (not_mem_singleton.2 h), prod_singleton]
#align finset.prod_pair Finset.prod_pair
#align finset.sum_pair Finset.sum_pair
@[to_additive (attr := simp)]
theorem prod_const_one : (∏ _x ∈ s, (1 : β)) = 1 := by
simp only [Finset.prod, Multiset.map_const', Multiset.prod_replicate, one_pow]
#align finset.prod_const_one Finset.prod_const_one
#align finset.sum_const_zero Finset.sum_const_zero
@[to_additive (attr := simp)]
theorem prod_image [DecidableEq α] {s : Finset γ} {g : γ → α} :
(∀ x ∈ s, ∀ y ∈ s, g x = g y → x = y) → ∏ x ∈ s.image g, f x = ∏ x ∈ s, f (g x) :=
fold_image
#align finset.prod_image Finset.prod_image
#align finset.sum_image Finset.sum_image
@[to_additive (attr := simp)]
theorem prod_map (s : Finset α) (e : α ↪ γ) (f : γ → β) :
∏ x ∈ s.map e, f x = ∏ x ∈ s, f (e x) := by
rw [Finset.prod, Finset.map_val, Multiset.map_map]; rfl
#align finset.prod_map Finset.prod_map
#align finset.sum_map Finset.sum_map
@[to_additive]
lemma prod_attach (s : Finset α) (f : α → β) : ∏ x ∈ s.attach, f x = ∏ x ∈ s, f x := by
classical rw [← prod_image Subtype.coe_injective.injOn, attach_image_val]
#align finset.prod_attach Finset.prod_attach
#align finset.sum_attach Finset.sum_attach
@[to_additive (attr := congr)]
theorem prod_congr (h : s₁ = s₂) : (∀ x ∈ s₂, f x = g x) → s₁.prod f = s₂.prod g := by
rw [h]; exact fold_congr
#align finset.prod_congr Finset.prod_congr
#align finset.sum_congr Finset.sum_congr
@[to_additive]
theorem prod_eq_one {f : α → β} {s : Finset α} (h : ∀ x ∈ s, f x = 1) : ∏ x ∈ s, f x = 1 :=
calc
∏ x ∈ s, f x = ∏ _x ∈ s, 1 := Finset.prod_congr rfl h
_ = 1 := Finset.prod_const_one
#align finset.prod_eq_one Finset.prod_eq_one
#align finset.sum_eq_zero Finset.sum_eq_zero
@[to_additive]
theorem prod_disjUnion (h) :
∏ x ∈ s₁.disjUnion s₂ h, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x := by
refine Eq.trans ?_ (fold_disjUnion h)
rw [one_mul]
rfl
#align finset.prod_disj_union Finset.prod_disjUnion
#align finset.sum_disj_union Finset.sum_disjUnion
@[to_additive]
theorem prod_disjiUnion (s : Finset ι) (t : ι → Finset α) (h) :
∏ x ∈ s.disjiUnion t h, f x = ∏ i ∈ s, ∏ x ∈ t i, f x := by
refine Eq.trans ?_ (fold_disjiUnion h)
dsimp [Finset.prod, Multiset.prod, Multiset.fold, Finset.disjUnion, Finset.fold]
congr
exact prod_const_one.symm
#align finset.prod_disj_Union Finset.prod_disjiUnion
#align finset.sum_disj_Union Finset.sum_disjiUnion
@[to_additive]
theorem prod_union_inter [DecidableEq α] :
(∏ x ∈ s₁ ∪ s₂, f x) * ∏ x ∈ s₁ ∩ s₂, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x :=
fold_union_inter
#align finset.prod_union_inter Finset.prod_union_inter
#align finset.sum_union_inter Finset.sum_union_inter
@[to_additive]
theorem prod_union [DecidableEq α] (h : Disjoint s₁ s₂) :
∏ x ∈ s₁ ∪ s₂, f x = (∏ x ∈ s₁, f x) * ∏ x ∈ s₂, f x := by
rw [← prod_union_inter, disjoint_iff_inter_eq_empty.mp h]; exact (mul_one _).symm
#align finset.prod_union Finset.prod_union
#align finset.sum_union Finset.sum_union
@[to_additive]
theorem prod_filter_mul_prod_filter_not
(s : Finset α) (p : α → Prop) [DecidablePred p] [∀ x, Decidable (¬p x)] (f : α → β) :
(∏ x ∈ s.filter p, f x) * ∏ x ∈ s.filter fun x => ¬p x, f x = ∏ x ∈ s, f x := by
have := Classical.decEq α
rw [← prod_union (disjoint_filter_filter_neg s s p), filter_union_filter_neg_eq]
#align finset.prod_filter_mul_prod_filter_not Finset.prod_filter_mul_prod_filter_not
#align finset.sum_filter_add_sum_filter_not Finset.sum_filter_add_sum_filter_not
section ToList
@[to_additive (attr := simp)]
theorem prod_to_list (s : Finset α) (f : α → β) : (s.toList.map f).prod = s.prod f := by
rw [Finset.prod, ← Multiset.prod_coe, ← Multiset.map_coe, Finset.coe_toList]
#align finset.prod_to_list Finset.prod_to_list
#align finset.sum_to_list Finset.sum_to_list
end ToList
@[to_additive]
theorem _root_.Equiv.Perm.prod_comp (σ : Equiv.Perm α) (s : Finset α) (f : α → β)
(hs : { a | σ a ≠ a } ⊆ s) : (∏ x ∈ s, f (σ x)) = ∏ x ∈ s, f x := by
convert (prod_map s σ.toEmbedding f).symm
exact (map_perm hs).symm
#align equiv.perm.prod_comp Equiv.Perm.prod_comp
#align equiv.perm.sum_comp Equiv.Perm.sum_comp
@[to_additive]
theorem _root_.Equiv.Perm.prod_comp' (σ : Equiv.Perm α) (s : Finset α) (f : α → α → β)
(hs : { a | σ a ≠ a } ⊆ s) : (∏ x ∈ s, f (σ x) x) = ∏ x ∈ s, f x (σ.symm x) := by
convert σ.prod_comp s (fun x => f x (σ.symm x)) hs
rw [Equiv.symm_apply_apply]
#align equiv.perm.prod_comp' Equiv.Perm.prod_comp'
#align equiv.perm.sum_comp' Equiv.Perm.sum_comp'
/-- A product over all subsets of `s ∪ {x}` is obtained by multiplying the product over all subsets
of `s`, and over all subsets of `s` to which one adds `x`. -/
@[to_additive "A sum over all subsets of `s ∪ {x}` is obtained by summing the sum over all subsets
of `s`, and over all subsets of `s` to which one adds `x`."]
lemma prod_powerset_insert [DecidableEq α] (ha : a ∉ s) (f : Finset α → β) :
∏ t ∈ (insert a s).powerset, f t =
(∏ t ∈ s.powerset, f t) * ∏ t ∈ s.powerset, f (insert a t) := by
rw [powerset_insert, prod_union, prod_image]
· exact insert_erase_invOn.2.injOn.mono fun t ht ↦ not_mem_mono (mem_powerset.1 ht) ha
· aesop (add simp [disjoint_left, insert_subset_iff])
#align finset.prod_powerset_insert Finset.prod_powerset_insert
#align finset.sum_powerset_insert Finset.sum_powerset_insert
/-- A product over all subsets of `s ∪ {x}` is obtained by multiplying the product over all subsets
of `s`, and over all subsets of `s` to which one adds `x`. -/
@[to_additive "A sum over all subsets of `s ∪ {x}` is obtained by summing the sum over all subsets
of `s`, and over all subsets of `s` to which one adds `x`."]
lemma prod_powerset_cons (ha : a ∉ s) (f : Finset α → β) :
∏ t ∈ (s.cons a ha).powerset, f t = (∏ t ∈ s.powerset, f t) *
∏ t ∈ s.powerset.attach, f (cons a t $ not_mem_mono (mem_powerset.1 t.2) ha) := by
classical
simp_rw [cons_eq_insert]
rw [prod_powerset_insert ha, prod_attach _ fun t ↦ f (insert a t)]
/-- A product over `powerset s` is equal to the double product over sets of subsets of `s` with
`card s = k`, for `k = 1, ..., card s`. -/
@[to_additive "A sum over `powerset s` is equal to the double sum over sets of subsets of `s` with
`card s = k`, for `k = 1, ..., card s`"]
lemma prod_powerset (s : Finset α) (f : Finset α → β) :
∏ t ∈ powerset s, f t = ∏ j ∈ range (card s + 1), ∏ t ∈ powersetCard j s, f t := by
rw [powerset_card_disjiUnion, prod_disjiUnion]
#align finset.prod_powerset Finset.prod_powerset
#align finset.sum_powerset Finset.sum_powerset
end CommMonoid
end Finset
section
open Finset
variable [Fintype α] [CommMonoid β]
@[to_additive]
theorem IsCompl.prod_mul_prod {s t : Finset α} (h : IsCompl s t) (f : α → β) :
(∏ i ∈ s, f i) * ∏ i ∈ t, f i = ∏ i, f i :=
(Finset.prod_disjUnion h.disjoint).symm.trans <| by
classical rw [Finset.disjUnion_eq_union, ← Finset.sup_eq_union, h.sup_eq_top]; rfl
#align is_compl.prod_mul_prod IsCompl.prod_mul_prod
#align is_compl.sum_add_sum IsCompl.sum_add_sum
end
namespace Finset
section CommMonoid
variable [CommMonoid β]
/-- Multiplying the products of a function over `s` and over `sᶜ` gives the whole product.
For a version expressed with subtypes, see `Fintype.prod_subtype_mul_prod_subtype`. -/
@[to_additive "Adding the sums of a function over `s` and over `sᶜ` gives the whole sum.
For a version expressed with subtypes, see `Fintype.sum_subtype_add_sum_subtype`. "]
theorem prod_mul_prod_compl [Fintype α] [DecidableEq α] (s : Finset α) (f : α → β) :
(∏ i ∈ s, f i) * ∏ i ∈ sᶜ, f i = ∏ i, f i :=
IsCompl.prod_mul_prod isCompl_compl f
#align finset.prod_mul_prod_compl Finset.prod_mul_prod_compl
#align finset.sum_add_sum_compl Finset.sum_add_sum_compl
@[to_additive]
theorem prod_compl_mul_prod [Fintype α] [DecidableEq α] (s : Finset α) (f : α → β) :
(∏ i ∈ sᶜ, f i) * ∏ i ∈ s, f i = ∏ i, f i :=
(@isCompl_compl _ s _).symm.prod_mul_prod f
#align finset.prod_compl_mul_prod Finset.prod_compl_mul_prod
#align finset.sum_compl_add_sum Finset.sum_compl_add_sum
@[to_additive]
theorem prod_sdiff [DecidableEq α] (h : s₁ ⊆ s₂) :
(∏ x ∈ s₂ \ s₁, f x) * ∏ x ∈ s₁, f x = ∏ x ∈ s₂, f x := by
rw [← prod_union sdiff_disjoint, sdiff_union_of_subset h]
#align finset.prod_sdiff Finset.prod_sdiff
#align finset.sum_sdiff Finset.sum_sdiff
@[to_additive]
theorem prod_subset_one_on_sdiff [DecidableEq α] (h : s₁ ⊆ s₂) (hg : ∀ x ∈ s₂ \ s₁, g x = 1)
(hfg : ∀ x ∈ s₁, f x = g x) : ∏ i ∈ s₁, f i = ∏ i ∈ s₂, g i := by
rw [← prod_sdiff h, prod_eq_one hg, one_mul]
exact prod_congr rfl hfg
#align finset.prod_subset_one_on_sdiff Finset.prod_subset_one_on_sdiff
#align finset.sum_subset_zero_on_sdiff Finset.sum_subset_zero_on_sdiff
@[to_additive]
theorem prod_subset (h : s₁ ⊆ s₂) (hf : ∀ x ∈ s₂, x ∉ s₁ → f x = 1) :
∏ x ∈ s₁, f x = ∏ x ∈ s₂, f x :=
haveI := Classical.decEq α
prod_subset_one_on_sdiff h (by simpa) fun _ _ => rfl
#align finset.prod_subset Finset.prod_subset
#align finset.sum_subset Finset.sum_subset
@[to_additive (attr := simp)]
theorem prod_disj_sum (s : Finset α) (t : Finset γ) (f : Sum α γ → β) :
∏ x ∈ s.disjSum t, f x = (∏ x ∈ s, f (Sum.inl x)) * ∏ x ∈ t, f (Sum.inr x) := by
rw [← map_inl_disjUnion_map_inr, prod_disjUnion, prod_map, prod_map]
rfl
#align finset.prod_disj_sum Finset.prod_disj_sum
#align finset.sum_disj_sum Finset.sum_disj_sum
@[to_additive]
theorem prod_sum_elim (s : Finset α) (t : Finset γ) (f : α → β) (g : γ → β) :
∏ x ∈ s.disjSum t, Sum.elim f g x = (∏ x ∈ s, f x) * ∏ x ∈ t, g x := by simp
#align finset.prod_sum_elim Finset.prod_sum_elim
#align finset.sum_sum_elim Finset.sum_sum_elim
@[to_additive]
theorem prod_biUnion [DecidableEq α] {s : Finset γ} {t : γ → Finset α}
(hs : Set.PairwiseDisjoint (↑s) t) : ∏ x ∈ s.biUnion t, f x = ∏ x ∈ s, ∏ i ∈ t x, f i := by
rw [← disjiUnion_eq_biUnion _ _ hs, prod_disjiUnion]
#align finset.prod_bUnion Finset.prod_biUnion
#align finset.sum_bUnion Finset.sum_biUnion
/-- Product over a sigma type equals the product of fiberwise products. For rewriting
in the reverse direction, use `Finset.prod_sigma'`. -/
@[to_additive "Sum over a sigma type equals the sum of fiberwise sums. For rewriting
in the reverse direction, use `Finset.sum_sigma'`"]
theorem prod_sigma {σ : α → Type*} (s : Finset α) (t : ∀ a, Finset (σ a)) (f : Sigma σ → β) :
∏ x ∈ s.sigma t, f x = ∏ a ∈ s, ∏ s ∈ t a, f ⟨a, s⟩ := by
simp_rw [← disjiUnion_map_sigma_mk, prod_disjiUnion, prod_map, Function.Embedding.sigmaMk_apply]
#align finset.prod_sigma Finset.prod_sigma
#align finset.sum_sigma Finset.sum_sigma
@[to_additive]
theorem prod_sigma' {σ : α → Type*} (s : Finset α) (t : ∀ a, Finset (σ a)) (f : ∀ a, σ a → β) :
(∏ a ∈ s, ∏ s ∈ t a, f a s) = ∏ x ∈ s.sigma t, f x.1 x.2 :=
Eq.symm <| prod_sigma s t fun x => f x.1 x.2
#align finset.prod_sigma' Finset.prod_sigma'
#align finset.sum_sigma' Finset.sum_sigma'
section bij
variable {ι κ α : Type*} [CommMonoid α] {s : Finset ι} {t : Finset κ} {f : ι → α} {g : κ → α}
/-- Reorder a product.
The difference with `Finset.prod_bij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.prod_nbij` is that the bijection is allowed to use membership of the
domain of the product, rather than being a non-dependent function. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_bij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.sum_nbij` is that the bijection is allowed to use membership of the
domain of the sum, rather than being a non-dependent function."]
theorem prod_bij (i : ∀ a ∈ s, κ) (hi : ∀ a ha, i a ha ∈ t)
(i_inj : ∀ a₁ ha₁ a₂ ha₂, i a₁ ha₁ = i a₂ ha₂ → a₁ = a₂)
(i_surj : ∀ b ∈ t, ∃ a ha, i a ha = b) (h : ∀ a ha, f a = g (i a ha)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x :=
congr_arg Multiset.prod (Multiset.map_eq_map_of_bij_of_nodup f g s.2 t.2 i hi i_inj i_surj h)
#align finset.prod_bij Finset.prod_bij
#align finset.sum_bij Finset.sum_bij
/-- Reorder a product.
The difference with `Finset.prod_bij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.prod_nbij'` is that the bijection and its inverse are allowed to use
membership of the domains of the products, rather than being non-dependent functions. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_bij` is that the bijection is specified with an inverse, rather than
as a surjective injection.
The difference with `Finset.sum_nbij'` is that the bijection and its inverse are allowed to use
membership of the domains of the sums, rather than being non-dependent functions."]
theorem prod_bij' (i : ∀ a ∈ s, κ) (j : ∀ a ∈ t, ι) (hi : ∀ a ha, i a ha ∈ t)
(hj : ∀ a ha, j a ha ∈ s) (left_inv : ∀ a ha, j (i a ha) (hi a ha) = a)
(right_inv : ∀ a ha, i (j a ha) (hj a ha) = a) (h : ∀ a ha, f a = g (i a ha)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x := by
refine prod_bij i hi (fun a1 h1 a2 h2 eq ↦ ?_) (fun b hb ↦ ⟨_, hj b hb, right_inv b hb⟩) h
rw [← left_inv a1 h1, ← left_inv a2 h2]
simp only [eq]
#align finset.prod_bij' Finset.prod_bij'
#align finset.sum_bij' Finset.sum_bij'
/-- Reorder a product.
The difference with `Finset.prod_nbij'` is that the bijection is specified as a surjective
injection, rather than by an inverse function.
The difference with `Finset.prod_bij` is that the bijection is a non-dependent function, rather than
being allowed to use membership of the domain of the product. -/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_nbij'` is that the bijection is specified as a surjective injection,
rather than by an inverse function.
The difference with `Finset.sum_bij` is that the bijection is a non-dependent function, rather than
being allowed to use membership of the domain of the sum."]
lemma prod_nbij (i : ι → κ) (hi : ∀ a ∈ s, i a ∈ t) (i_inj : (s : Set ι).InjOn i)
(i_surj : (s : Set ι).SurjOn i t) (h : ∀ a ∈ s, f a = g (i a)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x :=
prod_bij (fun a _ ↦ i a) hi i_inj (by simpa using i_surj) h
/-- Reorder a product.
The difference with `Finset.prod_nbij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.prod_bij'` is that the bijection and its inverse are non-dependent
functions, rather than being allowed to use membership of the domains of the products.
The difference with `Finset.prod_equiv` is that bijectivity is only required to hold on the domains
of the products, rather than on the entire types.
-/
@[to_additive "Reorder a sum.
The difference with `Finset.sum_nbij` is that the bijection is specified with an inverse, rather
than as a surjective injection.
The difference with `Finset.sum_bij'` is that the bijection and its inverse are non-dependent
functions, rather than being allowed to use membership of the domains of the sums.
The difference with `Finset.sum_equiv` is that bijectivity is only required to hold on the domains
of the sums, rather than on the entire types."]
lemma prod_nbij' (i : ι → κ) (j : κ → ι) (hi : ∀ a ∈ s, i a ∈ t) (hj : ∀ a ∈ t, j a ∈ s)
(left_inv : ∀ a ∈ s, j (i a) = a) (right_inv : ∀ a ∈ t, i (j a) = a)
(h : ∀ a ∈ s, f a = g (i a)) : ∏ x ∈ s, f x = ∏ x ∈ t, g x :=
prod_bij' (fun a _ ↦ i a) (fun b _ ↦ j b) hi hj left_inv right_inv h
/-- Specialization of `Finset.prod_nbij'` that automatically fills in most arguments.
See `Fintype.prod_equiv` for the version where `s` and `t` are `univ`. -/
@[to_additive "`Specialization of `Finset.sum_nbij'` that automatically fills in most arguments.
See `Fintype.sum_equiv` for the version where `s` and `t` are `univ`."]
lemma prod_equiv (e : ι ≃ κ) (hst : ∀ i, i ∈ s ↔ e i ∈ t) (hfg : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ i ∈ t, g i := by refine prod_nbij' e e.symm ?_ ?_ ?_ ?_ hfg <;> simp [hst]
#align finset.equiv.prod_comp_finset Finset.prod_equiv
#align finset.equiv.sum_comp_finset Finset.sum_equiv
/-- Specialization of `Finset.prod_bij` that automatically fills in most arguments.
See `Fintype.prod_bijective` for the version where `s` and `t` are `univ`. -/
@[to_additive "`Specialization of `Finset.sum_bij` that automatically fills in most arguments.
See `Fintype.sum_bijective` for the version where `s` and `t` are `univ`."]
lemma prod_bijective (e : ι → κ) (he : e.Bijective) (hst : ∀ i, i ∈ s ↔ e i ∈ t)
(hfg : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ i ∈ t, g i := prod_equiv (.ofBijective e he) hst hfg
@[to_additive]
lemma prod_of_injOn (e : ι → κ) (he : Set.InjOn e s) (hest : Set.MapsTo e s t)
(h' : ∀ i ∈ t, i ∉ e '' s → g i = 1) (h : ∀ i ∈ s, f i = g (e i)) :
∏ i ∈ s, f i = ∏ j ∈ t, g j := by
classical
exact (prod_nbij e (fun a ↦ mem_image_of_mem e) he (by simp [Set.surjOn_image]) h).trans <|
prod_subset (image_subset_iff.2 hest) <| by simpa using h'
variable [DecidableEq κ]
@[to_additive]
lemma prod_fiberwise_eq_prod_filter (s : Finset ι) (t : Finset κ) (g : ι → κ) (f : ι → α) :
∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s.filter fun i ↦ g i ∈ t, f i := by
rw [← prod_disjiUnion, disjiUnion_filter_eq]
@[to_additive]
lemma prod_fiberwise_eq_prod_filter' (s : Finset ι) (t : Finset κ) (g : ι → κ) (f : κ → α) :
∏ j ∈ t, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s.filter fun i ↦ g i ∈ t, f (g i) := by
calc
_ = ∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f (g i) :=
prod_congr rfl fun j _ ↦ prod_congr rfl fun i hi ↦ by rw [(mem_filter.1 hi).2]
_ = _ := prod_fiberwise_eq_prod_filter _ _ _ _
@[to_additive]
lemma prod_fiberwise_of_maps_to {g : ι → κ} (h : ∀ i ∈ s, g i ∈ t) (f : ι → α) :
∏ j ∈ t, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s, f i := by
rw [← prod_disjiUnion, disjiUnion_filter_eq_of_maps_to h]
#align finset.prod_fiberwise_of_maps_to Finset.prod_fiberwise_of_maps_to
#align finset.sum_fiberwise_of_maps_to Finset.sum_fiberwise_of_maps_to
@[to_additive]
lemma prod_fiberwise_of_maps_to' {g : ι → κ} (h : ∀ i ∈ s, g i ∈ t) (f : κ → α) :
∏ j ∈ t, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s, f (g i) := by
calc
_ = ∏ y ∈ t, ∏ x ∈ s.filter fun x ↦ g x = y, f (g x) :=
prod_congr rfl fun y _ ↦ prod_congr rfl fun x hx ↦ by rw [(mem_filter.1 hx).2]
_ = _ := prod_fiberwise_of_maps_to h _
variable [Fintype κ]
@[to_additive]
lemma prod_fiberwise (s : Finset ι) (g : ι → κ) (f : ι → α) :
∏ j, ∏ i ∈ s.filter fun i ↦ g i = j, f i = ∏ i ∈ s, f i :=
prod_fiberwise_of_maps_to (fun _ _ ↦ mem_univ _) _
#align finset.prod_fiberwise Finset.prod_fiberwise
#align finset.sum_fiberwise Finset.sum_fiberwise
@[to_additive]
lemma prod_fiberwise' (s : Finset ι) (g : ι → κ) (f : κ → α) :
∏ j, ∏ _i ∈ s.filter fun i ↦ g i = j, f j = ∏ i ∈ s, f (g i) :=
prod_fiberwise_of_maps_to' (fun _ _ ↦ mem_univ _) _
end bij
/-- Taking a product over `univ.pi t` is the same as taking the product over `Fintype.piFinset t`.
`univ.pi t` and `Fintype.piFinset t` are essentially the same `Finset`, but differ
in the type of their element, `univ.pi t` is a `Finset (Π a ∈ univ, t a)` and
`Fintype.piFinset t` is a `Finset (Π a, t a)`. -/
@[to_additive "Taking a sum over `univ.pi t` is the same as taking the sum over
`Fintype.piFinset t`. `univ.pi t` and `Fintype.piFinset t` are essentially the same `Finset`,
but differ in the type of their element, `univ.pi t` is a `Finset (Π a ∈ univ, t a)` and
`Fintype.piFinset t` is a `Finset (Π a, t a)`."]
lemma prod_univ_pi [DecidableEq ι] [Fintype ι] {κ : ι → Type*} (t : ∀ i, Finset (κ i))
(f : (∀ i ∈ (univ : Finset ι), κ i) → β) :
∏ x ∈ univ.pi t, f x = ∏ x ∈ Fintype.piFinset t, f fun a _ ↦ x a := by
apply prod_nbij' (fun x i ↦ x i $ mem_univ _) (fun x i _ ↦ x i) <;> simp
#align finset.prod_univ_pi Finset.prod_univ_pi
#align finset.sum_univ_pi Finset.sum_univ_pi
@[to_additive (attr := simp)]
lemma prod_diag [DecidableEq α] (s : Finset α) (f : α × α → β) :
∏ i ∈ s.diag, f i = ∏ i ∈ s, f (i, i) := by
apply prod_nbij' Prod.fst (fun i ↦ (i, i)) <;> simp
@[to_additive]
theorem prod_finset_product (r : Finset (γ × α)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : γ × α, p ∈ r ↔ p.1 ∈ s ∧ p.2 ∈ t p.1) {f : γ × α → β} :
∏ p ∈ r, f p = ∏ c ∈ s, ∏ a ∈ t c, f (c, a) := by
refine Eq.trans ?_ (prod_sigma s t fun p => f (p.1, p.2))
apply prod_equiv (Equiv.sigmaEquivProd _ _).symm <;> simp [h]
#align finset.prod_finset_product Finset.prod_finset_product
#align finset.sum_finset_product Finset.sum_finset_product
@[to_additive]
theorem prod_finset_product' (r : Finset (γ × α)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : γ × α, p ∈ r ↔ p.1 ∈ s ∧ p.2 ∈ t p.1) {f : γ → α → β} :
∏ p ∈ r, f p.1 p.2 = ∏ c ∈ s, ∏ a ∈ t c, f c a :=
prod_finset_product r s t h
#align finset.prod_finset_product' Finset.prod_finset_product'
#align finset.sum_finset_product' Finset.sum_finset_product'
@[to_additive]
theorem prod_finset_product_right (r : Finset (α × γ)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : α × γ, p ∈ r ↔ p.2 ∈ s ∧ p.1 ∈ t p.2) {f : α × γ → β} :
∏ p ∈ r, f p = ∏ c ∈ s, ∏ a ∈ t c, f (a, c) := by
refine Eq.trans ?_ (prod_sigma s t fun p => f (p.2, p.1))
apply prod_equiv ((Equiv.prodComm _ _).trans (Equiv.sigmaEquivProd _ _).symm) <;> simp [h]
#align finset.prod_finset_product_right Finset.prod_finset_product_right
#align finset.sum_finset_product_right Finset.sum_finset_product_right
@[to_additive]
theorem prod_finset_product_right' (r : Finset (α × γ)) (s : Finset γ) (t : γ → Finset α)
(h : ∀ p : α × γ, p ∈ r ↔ p.2 ∈ s ∧ p.1 ∈ t p.2) {f : α → γ → β} :
∏ p ∈ r, f p.1 p.2 = ∏ c ∈ s, ∏ a ∈ t c, f a c :=
prod_finset_product_right r s t h
#align finset.prod_finset_product_right' Finset.prod_finset_product_right'
#align finset.sum_finset_product_right' Finset.sum_finset_product_right'
@[to_additive]
theorem prod_image' [DecidableEq α] {s : Finset γ} {g : γ → α} (h : γ → β)
(eq : ∀ c ∈ s, f (g c) = ∏ x ∈ s.filter fun c' => g c' = g c, h x) :
∏ x ∈ s.image g, f x = ∏ x ∈ s, h x :=
calc
∏ x ∈ s.image g, f x = ∏ x ∈ s.image g, ∏ x ∈ s.filter fun c' => g c' = x, h x :=
(prod_congr rfl) fun _x hx =>
let ⟨c, hcs, hc⟩ := mem_image.1 hx
hc ▸ eq c hcs
_ = ∏ x ∈ s, h x := prod_fiberwise_of_maps_to (fun _x => mem_image_of_mem g) _
#align finset.prod_image' Finset.prod_image'
#align finset.sum_image' Finset.sum_image'
@[to_additive]
theorem prod_mul_distrib : ∏ x ∈ s, f x * g x = (∏ x ∈ s, f x) * ∏ x ∈ s, g x :=
Eq.trans (by rw [one_mul]; rfl) fold_op_distrib
#align finset.prod_mul_distrib Finset.prod_mul_distrib
#align finset.sum_add_distrib Finset.sum_add_distrib
@[to_additive]
lemma prod_mul_prod_comm (f g h i : α → β) :
(∏ a ∈ s, f a * g a) * ∏ a ∈ s, h a * i a = (∏ a ∈ s, f a * h a) * ∏ a ∈ s, g a * i a := by
simp_rw [prod_mul_distrib, mul_mul_mul_comm]
@[to_additive]
theorem prod_product {s : Finset γ} {t : Finset α} {f : γ × α → β} :
∏ x ∈ s ×ˢ t, f x = ∏ x ∈ s, ∏ y ∈ t, f (x, y) :=
prod_finset_product (s ×ˢ t) s (fun _a => t) fun _p => mem_product
#align finset.prod_product Finset.prod_product
#align finset.sum_product Finset.sum_product
/-- An uncurried version of `Finset.prod_product`. -/
@[to_additive "An uncurried version of `Finset.sum_product`"]
theorem prod_product' {s : Finset γ} {t : Finset α} {f : γ → α → β} :
∏ x ∈ s ×ˢ t, f x.1 x.2 = ∏ x ∈ s, ∏ y ∈ t, f x y :=
prod_product
#align finset.prod_product' Finset.prod_product'
#align finset.sum_product' Finset.sum_product'
@[to_additive]
theorem prod_product_right {s : Finset γ} {t : Finset α} {f : γ × α → β} :
∏ x ∈ s ×ˢ t, f x = ∏ y ∈ t, ∏ x ∈ s, f (x, y) :=
prod_finset_product_right (s ×ˢ t) t (fun _a => s) fun _p => mem_product.trans and_comm
#align finset.prod_product_right Finset.prod_product_right
#align finset.sum_product_right Finset.sum_product_right
/-- An uncurried version of `Finset.prod_product_right`. -/
@[to_additive "An uncurried version of `Finset.sum_product_right`"]
theorem prod_product_right' {s : Finset γ} {t : Finset α} {f : γ → α → β} :
∏ x ∈ s ×ˢ t, f x.1 x.2 = ∏ y ∈ t, ∏ x ∈ s, f x y :=
prod_product_right
#align finset.prod_product_right' Finset.prod_product_right'
#align finset.sum_product_right' Finset.sum_product_right'
/-- Generalization of `Finset.prod_comm` to the case when the inner `Finset`s depend on the outer
variable. -/
@[to_additive "Generalization of `Finset.sum_comm` to the case when the inner `Finset`s depend on
the outer variable."]
theorem prod_comm' {s : Finset γ} {t : γ → Finset α} {t' : Finset α} {s' : α → Finset γ}
(h : ∀ x y, x ∈ s ∧ y ∈ t x ↔ x ∈ s' y ∧ y ∈ t') {f : γ → α → β} :
(∏ x ∈ s, ∏ y ∈ t x, f x y) = ∏ y ∈ t', ∏ x ∈ s' y, f x y := by
classical
have : ∀ z : γ × α, (z ∈ s.biUnion fun x => (t x).map <| Function.Embedding.sectr x _) ↔
z.1 ∈ s ∧ z.2 ∈ t z.1 := by
rintro ⟨x, y⟩
simp only [mem_biUnion, mem_map, Function.Embedding.sectr_apply, Prod.mk.injEq,
exists_eq_right, ← and_assoc]
exact
(prod_finset_product' _ _ _ this).symm.trans
((prod_finset_product_right' _ _ _) fun ⟨x, y⟩ => (this _).trans ((h x y).trans and_comm))
#align finset.prod_comm' Finset.prod_comm'
#align finset.sum_comm' Finset.sum_comm'
@[to_additive]
theorem prod_comm {s : Finset γ} {t : Finset α} {f : γ → α → β} :
(∏ x ∈ s, ∏ y ∈ t, f x y) = ∏ y ∈ t, ∏ x ∈ s, f x y :=
prod_comm' fun _ _ => Iff.rfl
#align finset.prod_comm Finset.prod_comm
#align finset.sum_comm Finset.sum_comm
@[to_additive]
theorem prod_hom_rel [CommMonoid γ] {r : β → γ → Prop} {f : α → β} {g : α → γ} {s : Finset α}
(h₁ : r 1 1) (h₂ : ∀ a b c, r b c → r (f a * b) (g a * c)) :
r (∏ x ∈ s, f x) (∏ x ∈ s, g x) := by
delta Finset.prod
apply Multiset.prod_hom_rel <;> assumption
#align finset.prod_hom_rel Finset.prod_hom_rel
#align finset.sum_hom_rel Finset.sum_hom_rel
@[to_additive]
theorem prod_filter_of_ne {p : α → Prop} [DecidablePred p] (hp : ∀ x ∈ s, f x ≠ 1 → p x) :
∏ x ∈ s.filter p, f x = ∏ x ∈ s, f x :=
(prod_subset (filter_subset _ _)) fun x => by
classical
rw [not_imp_comm, mem_filter]
exact fun h₁ h₂ => ⟨h₁, by simpa using hp _ h₁ h₂⟩
#align finset.prod_filter_of_ne Finset.prod_filter_of_ne
#align finset.sum_filter_of_ne Finset.sum_filter_of_ne
-- If we use `[DecidableEq β]` here, some rewrites fail because they find a wrong `Decidable`
-- instance first; `{∀ x, Decidable (f x ≠ 1)}` doesn't work with `rw ← prod_filter_ne_one`
@[to_additive]
theorem prod_filter_ne_one (s : Finset α) [∀ x, Decidable (f x ≠ 1)] :
∏ x ∈ s.filter fun x => f x ≠ 1, f x = ∏ x ∈ s, f x :=
prod_filter_of_ne fun _ _ => id
#align finset.prod_filter_ne_one Finset.prod_filter_ne_one
#align finset.sum_filter_ne_zero Finset.sum_filter_ne_zero
@[to_additive]
theorem prod_filter (p : α → Prop) [DecidablePred p] (f : α → β) :
∏ a ∈ s.filter p, f a = ∏ a ∈ s, if p a then f a else 1 :=
calc
∏ a ∈ s.filter p, f a = ∏ a ∈ s.filter p, if p a then f a else 1 :=
prod_congr rfl fun a h => by rw [if_pos]; simpa using (mem_filter.1 h).2
_ = ∏ a ∈ s, if p a then f a else 1 := by
{ refine prod_subset (filter_subset _ s) fun x hs h => ?_
rw [mem_filter, not_and] at h
exact if_neg (by simpa using h hs) }
#align finset.prod_filter Finset.prod_filter
#align finset.sum_filter Finset.sum_filter
@[to_additive]
theorem prod_eq_single_of_mem {s : Finset α} {f : α → β} (a : α) (h : a ∈ s)
(h₀ : ∀ b ∈ s, b ≠ a → f b = 1) : ∏ x ∈ s, f x = f a := by
haveI := Classical.decEq α
calc
∏ x ∈ s, f x = ∏ x ∈ {a}, f x := by
{ refine (prod_subset ?_ ?_).symm
· intro _ H
rwa [mem_singleton.1 H]
· simpa only [mem_singleton] }
_ = f a := prod_singleton _ _
#align finset.prod_eq_single_of_mem Finset.prod_eq_single_of_mem
#align finset.sum_eq_single_of_mem Finset.sum_eq_single_of_mem
@[to_additive]
theorem prod_eq_single {s : Finset α} {f : α → β} (a : α) (h₀ : ∀ b ∈ s, b ≠ a → f b = 1)
(h₁ : a ∉ s → f a = 1) : ∏ x ∈ s, f x = f a :=
haveI := Classical.decEq α
by_cases (prod_eq_single_of_mem a · h₀) fun this =>
(prod_congr rfl fun b hb => h₀ b hb <| by rintro rfl; exact this hb).trans <|
prod_const_one.trans (h₁ this).symm
#align finset.prod_eq_single Finset.prod_eq_single
#align finset.sum_eq_single Finset.sum_eq_single
@[to_additive]
lemma prod_union_eq_left [DecidableEq α] (hs : ∀ a ∈ s₂, a ∉ s₁ → f a = 1) :
∏ a ∈ s₁ ∪ s₂, f a = ∏ a ∈ s₁, f a :=
Eq.symm <|
prod_subset subset_union_left fun _a ha ha' ↦ hs _ ((mem_union.1 ha).resolve_left ha') ha'
@[to_additive]
lemma prod_union_eq_right [DecidableEq α] (hs : ∀ a ∈ s₁, a ∉ s₂ → f a = 1) :
∏ a ∈ s₁ ∪ s₂, f a = ∏ a ∈ s₂, f a := by rw [union_comm, prod_union_eq_left hs]
@[to_additive]
theorem prod_eq_mul_of_mem {s : Finset α} {f : α → β} (a b : α) (ha : a ∈ s) (hb : b ∈ s)
(hn : a ≠ b) (h₀ : ∀ c ∈ s, c ≠ a ∧ c ≠ b → f c = 1) : ∏ x ∈ s, f x = f a * f b := by
haveI := Classical.decEq α; let s' := ({a, b} : Finset α)
have hu : s' ⊆ s := by
refine insert_subset_iff.mpr ?_
apply And.intro ha
apply singleton_subset_iff.mpr hb
have hf : ∀ c ∈ s, c ∉ s' → f c = 1 := by
intro c hc hcs
apply h₀ c hc
apply not_or.mp
intro hab
apply hcs
rw [mem_insert, mem_singleton]
exact hab
rw [← prod_subset hu hf]
exact Finset.prod_pair hn
#align finset.prod_eq_mul_of_mem Finset.prod_eq_mul_of_mem
#align finset.sum_eq_add_of_mem Finset.sum_eq_add_of_mem
@[to_additive]
theorem prod_eq_mul {s : Finset α} {f : α → β} (a b : α) (hn : a ≠ b)
(h₀ : ∀ c ∈ s, c ≠ a ∧ c ≠ b → f c = 1) (ha : a ∉ s → f a = 1) (hb : b ∉ s → f b = 1) :
∏ x ∈ s, f x = f a * f b := by
haveI := Classical.decEq α; by_cases h₁ : a ∈ s <;> by_cases h₂ : b ∈ s
· exact prod_eq_mul_of_mem a b h₁ h₂ hn h₀
· rw [hb h₂, mul_one]
apply prod_eq_single_of_mem a h₁
exact fun c hc hca => h₀ c hc ⟨hca, ne_of_mem_of_not_mem hc h₂⟩
· rw [ha h₁, one_mul]
apply prod_eq_single_of_mem b h₂
exact fun c hc hcb => h₀ c hc ⟨ne_of_mem_of_not_mem hc h₁, hcb⟩
· rw [ha h₁, hb h₂, mul_one]
exact
_root_.trans
(prod_congr rfl fun c hc =>
h₀ c hc ⟨ne_of_mem_of_not_mem hc h₁, ne_of_mem_of_not_mem hc h₂⟩)
prod_const_one
#align finset.prod_eq_mul Finset.prod_eq_mul
#align finset.sum_eq_add Finset.sum_eq_add
-- Porting note: simpNF linter complains that LHS doesn't simplify, but it does
/-- A product over `s.subtype p` equals one over `s.filter p`. -/
@[to_additive (attr := simp, nolint simpNF)
"A sum over `s.subtype p` equals one over `s.filter p`."]
theorem prod_subtype_eq_prod_filter (f : α → β) {p : α → Prop} [DecidablePred p] :
∏ x ∈ s.subtype p, f x = ∏ x ∈ s.filter p, f x := by
conv_lhs => erw [← prod_map (s.subtype p) (Function.Embedding.subtype _) f]
exact prod_congr (subtype_map _) fun x _hx => rfl
#align finset.prod_subtype_eq_prod_filter Finset.prod_subtype_eq_prod_filter
#align finset.sum_subtype_eq_sum_filter Finset.sum_subtype_eq_sum_filter
/-- If all elements of a `Finset` satisfy the predicate `p`, a product
over `s.subtype p` equals that product over `s`. -/
@[to_additive "If all elements of a `Finset` satisfy the predicate `p`, a sum
over `s.subtype p` equals that sum over `s`."]
theorem prod_subtype_of_mem (f : α → β) {p : α → Prop} [DecidablePred p] (h : ∀ x ∈ s, p x) :
∏ x ∈ s.subtype p, f x = ∏ x ∈ s, f x := by
rw [prod_subtype_eq_prod_filter, filter_true_of_mem]
simpa using h
#align finset.prod_subtype_of_mem Finset.prod_subtype_of_mem
#align finset.sum_subtype_of_mem Finset.sum_subtype_of_mem
/-- A product of a function over a `Finset` in a subtype equals a
product in the main type of a function that agrees with the first
function on that `Finset`. -/
@[to_additive "A sum of a function over a `Finset` in a subtype equals a
sum in the main type of a function that agrees with the first
function on that `Finset`."]
theorem prod_subtype_map_embedding {p : α → Prop} {s : Finset { x // p x }} {f : { x // p x } → β}
{g : α → β} (h : ∀ x : { x // p x }, x ∈ s → g x = f x) :
(∏ x ∈ s.map (Function.Embedding.subtype _), g x) = ∏ x ∈ s, f x := by
rw [Finset.prod_map]
exact Finset.prod_congr rfl h
#align finset.prod_subtype_map_embedding Finset.prod_subtype_map_embedding
#align finset.sum_subtype_map_embedding Finset.sum_subtype_map_embedding
variable (f s)
@[to_additive]
theorem prod_coe_sort_eq_attach (f : s → β) : ∏ i : s, f i = ∏ i ∈ s.attach, f i :=
rfl
#align finset.prod_coe_sort_eq_attach Finset.prod_coe_sort_eq_attach
#align finset.sum_coe_sort_eq_attach Finset.sum_coe_sort_eq_attach
@[to_additive]
theorem prod_coe_sort : ∏ i : s, f i = ∏ i ∈ s, f i := prod_attach _ _
#align finset.prod_coe_sort Finset.prod_coe_sort
#align finset.sum_coe_sort Finset.sum_coe_sort
@[to_additive]
theorem prod_finset_coe (f : α → β) (s : Finset α) : (∏ i : (s : Set α), f i) = ∏ i ∈ s, f i :=
prod_coe_sort s f
#align finset.prod_finset_coe Finset.prod_finset_coe
#align finset.sum_finset_coe Finset.sum_finset_coe
variable {f s}
@[to_additive]
theorem prod_subtype {p : α → Prop} {F : Fintype (Subtype p)} (s : Finset α) (h : ∀ x, x ∈ s ↔ p x)
(f : α → β) : ∏ a ∈ s, f a = ∏ a : Subtype p, f a := by
have : (· ∈ s) = p := Set.ext h
subst p
rw [← prod_coe_sort]
congr!
#align finset.prod_subtype Finset.prod_subtype
#align finset.sum_subtype Finset.sum_subtype
@[to_additive]
lemma prod_preimage' (f : ι → κ) [DecidablePred (· ∈ Set.range f)] (s : Finset κ) (hf) (g : κ → β) :
∏ x ∈ s.preimage f hf, g (f x) = ∏ x ∈ s.filter (· ∈ Set.range f), g x := by
classical
calc
∏ x ∈ preimage s f hf, g (f x) = ∏ x ∈ image f (preimage s f hf), g x :=
Eq.symm <| prod_image <| by simpa only [mem_preimage, Set.InjOn] using hf
_ = ∏ x ∈ s.filter fun x => x ∈ Set.range f, g x := by rw [image_preimage]
#align finset.prod_preimage' Finset.prod_preimage'
#align finset.sum_preimage' Finset.sum_preimage'
@[to_additive]
lemma prod_preimage (f : ι → κ) (s : Finset κ) (hf) (g : κ → β)
(hg : ∀ x ∈ s, x ∉ Set.range f → g x = 1) :
∏ x ∈ s.preimage f hf, g (f x) = ∏ x ∈ s, g x := by
classical rw [prod_preimage', prod_filter_of_ne]; exact fun x hx ↦ Not.imp_symm (hg x hx)
#align finset.prod_preimage Finset.prod_preimage
#align finset.sum_preimage Finset.sum_preimage
@[to_additive]
lemma prod_preimage_of_bij (f : ι → κ) (s : Finset κ) (hf : Set.BijOn f (f ⁻¹' ↑s) ↑s) (g : κ → β) :
∏ x ∈ s.preimage f hf.injOn, g (f x) = ∏ x ∈ s, g x :=
prod_preimage _ _ hf.injOn g fun _ hs h_f ↦ (h_f <| hf.subset_range hs).elim
#align finset.prod_preimage_of_bij Finset.prod_preimage_of_bij
#align finset.sum_preimage_of_bij Finset.sum_preimage_of_bij
@[to_additive]
theorem prod_set_coe (s : Set α) [Fintype s] : (∏ i : s, f i) = ∏ i ∈ s.toFinset, f i :=
(Finset.prod_subtype s.toFinset (fun _ ↦ Set.mem_toFinset) f).symm
/-- The product of a function `g` defined only on a set `s` is equal to
the product of a function `f` defined everywhere,
as long as `f` and `g` agree on `s`, and `f = 1` off `s`. -/
@[to_additive "The sum of a function `g` defined only on a set `s` is equal to
the sum of a function `f` defined everywhere,
as long as `f` and `g` agree on `s`, and `f = 0` off `s`."]
theorem prod_congr_set {α : Type*} [CommMonoid α] {β : Type*} [Fintype β] (s : Set β)
[DecidablePred (· ∈ s)] (f : β → α) (g : s → α) (w : ∀ (x : β) (h : x ∈ s), f x = g ⟨x, h⟩)
(w' : ∀ x : β, x ∉ s → f x = 1) : Finset.univ.prod f = Finset.univ.prod g := by
rw [← @Finset.prod_subset _ _ s.toFinset Finset.univ f _ (by simp)]
· rw [Finset.prod_subtype]
· apply Finset.prod_congr rfl
exact fun ⟨x, h⟩ _ => w x h
· simp
· rintro x _ h
exact w' x (by simpa using h)
#align finset.prod_congr_set Finset.prod_congr_set
#align finset.sum_congr_set Finset.sum_congr_set
@[to_additive]
theorem prod_apply_dite {s : Finset α} {p : α → Prop} {hp : DecidablePred p}
[DecidablePred fun x => ¬p x] (f : ∀ x : α, p x → γ) (g : ∀ x : α, ¬p x → γ) (h : γ → β) :
(∏ x ∈ s, h (if hx : p x then f x hx else g x hx)) =
(∏ x ∈ (s.filter p).attach, h (f x.1 <| by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter fun x => ¬p x).attach, h (g x.1 <| by simpa using (mem_filter.mp x.2).2) :=
calc
(∏ x ∈ s, h (if hx : p x then f x hx else g x hx)) =
(∏ x ∈ s.filter p, h (if hx : p x then f x hx else g x hx)) *
∏ x ∈ s.filter (¬p ·), h (if hx : p x then f x hx else g x hx) :=
(prod_filter_mul_prod_filter_not s p _).symm
_ = (∏ x ∈ (s.filter p).attach, h (if hx : p x.1 then f x.1 hx else g x.1 hx)) *
∏ x ∈ (s.filter (¬p ·)).attach, h (if hx : p x.1 then f x.1 hx else g x.1 hx) :=
congr_arg₂ _ (prod_attach _ _).symm (prod_attach _ _).symm
_ = (∏ x ∈ (s.filter p).attach, h (f x.1 <| by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter (¬p ·)).attach, h (g x.1 <| by simpa using (mem_filter.mp x.2).2) :=
congr_arg₂ _ (prod_congr rfl fun x _hx ↦
congr_arg h (dif_pos <| by simpa using (mem_filter.mp x.2).2))
(prod_congr rfl fun x _hx => congr_arg h (dif_neg <| by simpa using (mem_filter.mp x.2).2))
#align finset.prod_apply_dite Finset.prod_apply_dite
#align finset.sum_apply_dite Finset.sum_apply_dite
@[to_additive]
theorem prod_apply_ite {s : Finset α} {p : α → Prop} {_hp : DecidablePred p} (f g : α → γ)
(h : γ → β) :
(∏ x ∈ s, h (if p x then f x else g x)) =
(∏ x ∈ s.filter p, h (f x)) * ∏ x ∈ s.filter fun x => ¬p x, h (g x) :=
(prod_apply_dite _ _ _).trans <| congr_arg₂ _ (prod_attach _ (h ∘ f)) (prod_attach _ (h ∘ g))
#align finset.prod_apply_ite Finset.prod_apply_ite
#align finset.sum_apply_ite Finset.sum_apply_ite
@[to_additive]
theorem prod_dite {s : Finset α} {p : α → Prop} {hp : DecidablePred p} (f : ∀ x : α, p x → β)
(g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) =
(∏ x ∈ (s.filter p).attach, f x.1 (by simpa using (mem_filter.mp x.2).2)) *
∏ x ∈ (s.filter fun x => ¬p x).attach, g x.1 (by simpa using (mem_filter.mp x.2).2) := by
simp [prod_apply_dite _ _ fun x => x]
#align finset.prod_dite Finset.prod_dite
#align finset.sum_dite Finset.sum_dite
@[to_additive]
theorem prod_ite {s : Finset α} {p : α → Prop} {hp : DecidablePred p} (f g : α → β) :
∏ x ∈ s, (if p x then f x else g x) =
(∏ x ∈ s.filter p, f x) * ∏ x ∈ s.filter fun x => ¬p x, g x := by
simp [prod_apply_ite _ _ fun x => x]
#align finset.prod_ite Finset.prod_ite
#align finset.sum_ite Finset.sum_ite
@[to_additive]
theorem prod_ite_of_false {p : α → Prop} {hp : DecidablePred p} (f g : α → β) (h : ∀ x ∈ s, ¬p x) :
∏ x ∈ s, (if p x then f x else g x) = ∏ x ∈ s, g x := by
rw [prod_ite, filter_false_of_mem, filter_true_of_mem]
· simp only [prod_empty, one_mul]
all_goals intros; apply h; assumption
#align finset.prod_ite_of_false Finset.prod_ite_of_false
#align finset.sum_ite_of_false Finset.sum_ite_of_false
@[to_additive]
theorem prod_ite_of_true {p : α → Prop} {hp : DecidablePred p} (f g : α → β) (h : ∀ x ∈ s, p x) :
∏ x ∈ s, (if p x then f x else g x) = ∏ x ∈ s, f x := by
simp_rw [← ite_not (p _)]
apply prod_ite_of_false
simpa
#align finset.prod_ite_of_true Finset.prod_ite_of_true
#align finset.sum_ite_of_true Finset.sum_ite_of_true
@[to_additive]
theorem prod_apply_ite_of_false {p : α → Prop} {hp : DecidablePred p} (f g : α → γ) (k : γ → β)
(h : ∀ x ∈ s, ¬p x) : (∏ x ∈ s, k (if p x then f x else g x)) = ∏ x ∈ s, k (g x) := by
simp_rw [apply_ite k]
exact prod_ite_of_false _ _ h
#align finset.prod_apply_ite_of_false Finset.prod_apply_ite_of_false
#align finset.sum_apply_ite_of_false Finset.sum_apply_ite_of_false
@[to_additive]
theorem prod_apply_ite_of_true {p : α → Prop} {hp : DecidablePred p} (f g : α → γ) (k : γ → β)
(h : ∀ x ∈ s, p x) : (∏ x ∈ s, k (if p x then f x else g x)) = ∏ x ∈ s, k (f x) := by
simp_rw [apply_ite k]
exact prod_ite_of_true _ _ h
#align finset.prod_apply_ite_of_true Finset.prod_apply_ite_of_true
#align finset.sum_apply_ite_of_true Finset.sum_apply_ite_of_true
@[to_additive]
theorem prod_extend_by_one [DecidableEq α] (s : Finset α) (f : α → β) :
∏ i ∈ s, (if i ∈ s then f i else 1) = ∏ i ∈ s, f i :=
(prod_congr rfl) fun _i hi => if_pos hi
#align finset.prod_extend_by_one Finset.prod_extend_by_one
#align finset.sum_extend_by_zero Finset.sum_extend_by_zero
@[to_additive (attr := simp)]
theorem prod_ite_mem [DecidableEq α] (s t : Finset α) (f : α → β) :
∏ i ∈ s, (if i ∈ t then f i else 1) = ∏ i ∈ s ∩ t, f i := by
rw [← Finset.prod_filter, Finset.filter_mem_eq_inter]
#align finset.prod_ite_mem Finset.prod_ite_mem
#align finset.sum_ite_mem Finset.sum_ite_mem
@[to_additive (attr := simp)]
theorem prod_dite_eq [DecidableEq α] (s : Finset α) (a : α) (b : ∀ x : α, a = x → β) :
∏ x ∈ s, (if h : a = x then b x h else 1) = ite (a ∈ s) (b a rfl) 1 := by
split_ifs with h
· rw [Finset.prod_eq_single a, dif_pos rfl]
· intros _ _ h
rw [dif_neg]
exact h.symm
· simp [h]
· rw [Finset.prod_eq_one]
intros
rw [dif_neg]
rintro rfl
contradiction
#align finset.prod_dite_eq Finset.prod_dite_eq
#align finset.sum_dite_eq Finset.sum_dite_eq
@[to_additive (attr := simp)]
theorem prod_dite_eq' [DecidableEq α] (s : Finset α) (a : α) (b : ∀ x : α, x = a → β) :
∏ x ∈ s, (if h : x = a then b x h else 1) = ite (a ∈ s) (b a rfl) 1 := by
split_ifs with h
· rw [Finset.prod_eq_single a, dif_pos rfl]
· intros _ _ h
rw [dif_neg]
exact h
· simp [h]
· rw [Finset.prod_eq_one]
intros
rw [dif_neg]
rintro rfl
contradiction
#align finset.prod_dite_eq' Finset.prod_dite_eq'
#align finset.sum_dite_eq' Finset.sum_dite_eq'
@[to_additive (attr := simp)]
theorem prod_ite_eq [DecidableEq α] (s : Finset α) (a : α) (b : α → β) :
(∏ x ∈ s, ite (a = x) (b x) 1) = ite (a ∈ s) (b a) 1 :=
prod_dite_eq s a fun x _ => b x
#align finset.prod_ite_eq Finset.prod_ite_eq
#align finset.sum_ite_eq Finset.sum_ite_eq
/-- A product taken over a conditional whose condition is an equality test on the index and whose
alternative is `1` has value either the term at that index or `1`.
The difference with `Finset.prod_ite_eq` is that the arguments to `Eq` are swapped. -/
@[to_additive (attr := simp) "A sum taken over a conditional whose condition is an equality
test on the index and whose alternative is `0` has value either the term at that index or `0`.
The difference with `Finset.sum_ite_eq` is that the arguments to `Eq` are swapped."]
theorem prod_ite_eq' [DecidableEq α] (s : Finset α) (a : α) (b : α → β) :
(∏ x ∈ s, ite (x = a) (b x) 1) = ite (a ∈ s) (b a) 1 :=
prod_dite_eq' s a fun x _ => b x
#align finset.prod_ite_eq' Finset.prod_ite_eq'
#align finset.sum_ite_eq' Finset.sum_ite_eq'
@[to_additive]
theorem prod_ite_index (p : Prop) [Decidable p] (s t : Finset α) (f : α → β) :
∏ x ∈ if p then s else t, f x = if p then ∏ x ∈ s, f x else ∏ x ∈ t, f x :=
apply_ite (fun s => ∏ x ∈ s, f x) _ _ _
#align finset.prod_ite_index Finset.prod_ite_index
#align finset.sum_ite_index Finset.sum_ite_index
@[to_additive (attr := simp)]
theorem prod_ite_irrel (p : Prop) [Decidable p] (s : Finset α) (f g : α → β) :
∏ x ∈ s, (if p then f x else g x) = if p then ∏ x ∈ s, f x else ∏ x ∈ s, g x := by
split_ifs with h <;> rfl
#align finset.prod_ite_irrel Finset.prod_ite_irrel
#align finset.sum_ite_irrel Finset.sum_ite_irrel
@[to_additive (attr := simp)]
theorem prod_dite_irrel (p : Prop) [Decidable p] (s : Finset α) (f : p → α → β) (g : ¬p → α → β) :
∏ x ∈ s, (if h : p then f h x else g h x) =
if h : p then ∏ x ∈ s, f h x else ∏ x ∈ s, g h x := by
split_ifs with h <;> rfl
#align finset.prod_dite_irrel Finset.prod_dite_irrel
#align finset.sum_dite_irrel Finset.sum_dite_irrel
@[to_additive (attr := simp)]
theorem prod_pi_mulSingle' [DecidableEq α] (a : α) (x : β) (s : Finset α) :
∏ a' ∈ s, Pi.mulSingle a x a' = if a ∈ s then x else 1 :=
prod_dite_eq' _ _ _
#align finset.prod_pi_mul_single' Finset.prod_pi_mulSingle'
#align finset.sum_pi_single' Finset.sum_pi_single'
@[to_additive (attr := simp)]
theorem prod_pi_mulSingle {β : α → Type*} [DecidableEq α] [∀ a, CommMonoid (β a)] (a : α)
(f : ∀ a, β a) (s : Finset α) :
(∏ a' ∈ s, Pi.mulSingle a' (f a') a) = if a ∈ s then f a else 1 :=
prod_dite_eq _ _ _
#align finset.prod_pi_mul_single Finset.prod_pi_mulSingle
@[to_additive]
lemma mulSupport_prod (s : Finset ι) (f : ι → α → β) :
mulSupport (fun x ↦ ∏ i ∈ s, f i x) ⊆ ⋃ i ∈ s, mulSupport (f i) := by
simp only [mulSupport_subset_iff', Set.mem_iUnion, not_exists, nmem_mulSupport]
exact fun x ↦ prod_eq_one
#align function.mul_support_prod Finset.mulSupport_prod
#align function.support_sum Finset.support_sum
section indicator
open Set
variable {κ : Type*}
/-- Consider a product of `g i (f i)` over a finset. Suppose `g` is a function such as
`n ↦ (· ^ n)`, which maps a second argument of `1` to `1`. Then if `f` is replaced by the
corresponding multiplicative indicator function, the finset may be replaced by a possibly larger
finset without changing the value of the product. -/
@[to_additive "Consider a sum of `g i (f i)` over a finset. Suppose `g` is a function such as
`n ↦ (n • ·)`, which maps a second argument of `0` to `0` (or a weighted sum of `f i * h i` or
`f i • h i`, where `f` gives the weights that are multiplied by some other function `h`). Then if
`f` is replaced by the corresponding indicator function, the finset may be replaced by a possibly
larger finset without changing the value of the sum."]
lemma prod_mulIndicator_subset_of_eq_one [One α] (f : ι → α) (g : ι → α → β) {s t : Finset ι}
(h : s ⊆ t) (hg : ∀ a, g a 1 = 1) :
∏ i ∈ t, g i (mulIndicator ↑s f i) = ∏ i ∈ s, g i (f i) := by
calc
_ = ∏ i ∈ s, g i (mulIndicator ↑s f i) := by rw [prod_subset h fun i _ hn ↦ by simp [hn, hg]]
-- Porting note: This did not use to need the implicit argument
_ = _ := prod_congr rfl fun i hi ↦ congr_arg _ <| mulIndicator_of_mem (α := ι) hi f
#align set.prod_mul_indicator_subset_of_eq_one Finset.prod_mulIndicator_subset_of_eq_one
#align set.sum_indicator_subset_of_eq_zero Finset.sum_indicator_subset_of_eq_zero
/-- Taking the product of an indicator function over a possibly larger finset is the same as
taking the original function over the original finset. -/
@[to_additive "Summing an indicator function over a possibly larger `Finset` is the same as summing
the original function over the original finset."]
lemma prod_mulIndicator_subset (f : ι → β) {s t : Finset ι} (h : s ⊆ t) :
∏ i ∈ t, mulIndicator (↑s) f i = ∏ i ∈ s, f i :=
prod_mulIndicator_subset_of_eq_one _ (fun _ ↦ id) h fun _ ↦ rfl
#align set.prod_mul_indicator_subset Finset.prod_mulIndicator_subset
#align set.sum_indicator_subset Finset.sum_indicator_subset
@[to_additive]
lemma prod_mulIndicator_eq_prod_filter (s : Finset ι) (f : ι → κ → β) (t : ι → Set κ) (g : ι → κ)
[DecidablePred fun i ↦ g i ∈ t i] :
∏ i ∈ s, mulIndicator (t i) (f i) (g i) = ∏ i ∈ s.filter fun i ↦ g i ∈ t i, f i (g i) := by
refine (prod_filter_mul_prod_filter_not s (fun i ↦ g i ∈ t i) _).symm.trans <|
Eq.trans (congr_arg₂ (· * ·) ?_ ?_) (mul_one _)
· exact prod_congr rfl fun x hx ↦ mulIndicator_of_mem (mem_filter.1 hx).2 _
· exact prod_eq_one fun x hx ↦ mulIndicator_of_not_mem (mem_filter.1 hx).2 _
#align finset.prod_mul_indicator_eq_prod_filter Finset.prod_mulIndicator_eq_prod_filter
#align finset.sum_indicator_eq_sum_filter Finset.sum_indicator_eq_sum_filter
@[to_additive]
lemma prod_mulIndicator_eq_prod_inter [DecidableEq ι] (s t : Finset ι) (f : ι → β) :
∏ i ∈ s, (t : Set ι).mulIndicator f i = ∏ i ∈ s ∩ t, f i := by
rw [← filter_mem_eq_inter, prod_mulIndicator_eq_prod_filter]; rfl
@[to_additive]
lemma mulIndicator_prod (s : Finset ι) (t : Set κ) (f : ι → κ → β) :
mulIndicator t (∏ i ∈ s, f i) = ∏ i ∈ s, mulIndicator t (f i) :=
map_prod (mulIndicatorHom _ _) _ _
#align set.mul_indicator_finset_prod Finset.mulIndicator_prod
#align set.indicator_finset_sum Finset.indicator_sum
variable {κ : Type*}
@[to_additive]
lemma mulIndicator_biUnion (s : Finset ι) (t : ι → Set κ) {f : κ → β} :
((s : Set ι).PairwiseDisjoint t) →
mulIndicator (⋃ i ∈ s, t i) f = fun a ↦ ∏ i ∈ s, mulIndicator (t i) f a := by
classical
refine Finset.induction_on s (by simp) fun i s hi ih hs ↦ funext fun j ↦ ?_
rw [prod_insert hi, set_biUnion_insert, mulIndicator_union_of_not_mem_inter,
ih (hs.subset <| subset_insert _ _)]
simp only [not_exists, exists_prop, mem_iUnion, mem_inter_iff, not_and]
exact fun hji i' hi' hji' ↦ (ne_of_mem_of_not_mem hi' hi).symm <|
hs.elim_set (mem_insert_self _ _) (mem_insert_of_mem hi') _ hji hji'
#align set.mul_indicator_finset_bUnion Finset.mulIndicator_biUnion
#align set.indicator_finset_bUnion Finset.indicator_biUnion
@[to_additive]
lemma mulIndicator_biUnion_apply (s : Finset ι) (t : ι → Set κ) {f : κ → β}
(h : (s : Set ι).PairwiseDisjoint t) (x : κ) :
mulIndicator (⋃ i ∈ s, t i) f x = ∏ i ∈ s, mulIndicator (t i) f x := by
rw [mulIndicator_biUnion s t h]
#align set.mul_indicator_finset_bUnion_apply Finset.mulIndicator_biUnion_apply
#align set.indicator_finset_bUnion_apply Finset.indicator_biUnion_apply
end indicator
@[to_additive]
theorem prod_bij_ne_one {s : Finset α} {t : Finset γ} {f : α → β} {g : γ → β}
(i : ∀ a ∈ s, f a ≠ 1 → γ) (hi : ∀ a h₁ h₂, i a h₁ h₂ ∈ t)
(i_inj : ∀ a₁ h₁₁ h₁₂ a₂ h₂₁ h₂₂, i a₁ h₁₁ h₁₂ = i a₂ h₂₁ h₂₂ → a₁ = a₂)
(i_surj : ∀ b ∈ t, g b ≠ 1 → ∃ a h₁ h₂, i a h₁ h₂ = b) (h : ∀ a h₁ h₂, f a = g (i a h₁ h₂)) :
∏ x ∈ s, f x = ∏ x ∈ t, g x := by
classical
calc
∏ x ∈ s, f x = ∏ x ∈ s.filter fun x => f x ≠ 1, f x := by rw [prod_filter_ne_one]
_ = ∏ x ∈ t.filter fun x => g x ≠ 1, g x :=
prod_bij (fun a ha => i a (mem_filter.mp ha).1 <| by simpa using (mem_filter.mp ha).2)
?_ ?_ ?_ ?_
_ = ∏ x ∈ t, g x := prod_filter_ne_one _
· intros a ha
refine (mem_filter.mp ha).elim ?_
intros h₁ h₂
refine (mem_filter.mpr ⟨hi a h₁ _, ?_⟩)
specialize h a h₁ fun H ↦ by rw [H] at h₂; simp at h₂
rwa [← h]
· intros a₁ ha₁ a₂ ha₂
refine (mem_filter.mp ha₁).elim fun _ha₁₁ _ha₁₂ ↦ ?_
refine (mem_filter.mp ha₂).elim fun _ha₂₁ _ha₂₂ ↦ ?_
apply i_inj
· intros b hb
refine (mem_filter.mp hb).elim fun h₁ h₂ ↦ ?_
obtain ⟨a, ha₁, ha₂, eq⟩ := i_surj b h₁ fun H ↦ by rw [H] at h₂; simp at h₂
exact ⟨a, mem_filter.mpr ⟨ha₁, ha₂⟩, eq⟩
· refine (fun a ha => (mem_filter.mp ha).elim fun h₁ h₂ ↦ ?_)
exact h a h₁ fun H ↦ by rw [H] at h₂; simp at h₂
#align finset.prod_bij_ne_one Finset.prod_bij_ne_one
#align finset.sum_bij_ne_zero Finset.sum_bij_ne_zero
@[to_additive]
theorem prod_dite_of_false {p : α → Prop} {hp : DecidablePred p} (h : ∀ x ∈ s, ¬p x)
(f : ∀ x : α, p x → β) (g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) = ∏ x : s, g x.val (h x.val x.property) := by
refine prod_bij' (fun x hx => ⟨x, hx⟩) (fun x _ ↦ x) ?_ ?_ ?_ ?_ ?_ <;> aesop
#align finset.prod_dite_of_false Finset.prod_dite_of_false
#align finset.sum_dite_of_false Finset.sum_dite_of_false
@[to_additive]
theorem prod_dite_of_true {p : α → Prop} {hp : DecidablePred p} (h : ∀ x ∈ s, p x)
(f : ∀ x : α, p x → β) (g : ∀ x : α, ¬p x → β) :
∏ x ∈ s, (if hx : p x then f x hx else g x hx) = ∏ x : s, f x.val (h x.val x.property) := by
refine prod_bij' (fun x hx => ⟨x, hx⟩) (fun x _ ↦ x) ?_ ?_ ?_ ?_ ?_ <;> aesop
#align finset.prod_dite_of_true Finset.prod_dite_of_true
#align finset.sum_dite_of_true Finset.sum_dite_of_true
@[to_additive]
theorem nonempty_of_prod_ne_one (h : ∏ x ∈ s, f x ≠ 1) : s.Nonempty :=
s.eq_empty_or_nonempty.elim (fun H => False.elim <| h <| H.symm ▸ prod_empty) id
#align finset.nonempty_of_prod_ne_one Finset.nonempty_of_prod_ne_one
#align finset.nonempty_of_sum_ne_zero Finset.nonempty_of_sum_ne_zero
@[to_additive]
theorem exists_ne_one_of_prod_ne_one (h : ∏ x ∈ s, f x ≠ 1) : ∃ a ∈ s, f a ≠ 1 := by
classical
rw [← prod_filter_ne_one] at h
rcases nonempty_of_prod_ne_one h with ⟨x, hx⟩
exact ⟨x, (mem_filter.1 hx).1, by simpa using (mem_filter.1 hx).2⟩
#align finset.exists_ne_one_of_prod_ne_one Finset.exists_ne_one_of_prod_ne_one
#align finset.exists_ne_zero_of_sum_ne_zero Finset.exists_ne_zero_of_sum_ne_zero
@[to_additive]
theorem prod_range_succ_comm (f : ℕ → β) (n : ℕ) :
(∏ x ∈ range (n + 1), f x) = f n * ∏ x ∈ range n, f x := by
rw [range_succ, prod_insert not_mem_range_self]
#align finset.prod_range_succ_comm Finset.prod_range_succ_comm
#align finset.sum_range_succ_comm Finset.sum_range_succ_comm
@[to_additive]
theorem prod_range_succ (f : ℕ → β) (n : ℕ) :
(∏ x ∈ range (n + 1), f x) = (∏ x ∈ range n, f x) * f n := by
simp only [mul_comm, prod_range_succ_comm]
#align finset.prod_range_succ Finset.prod_range_succ
#align finset.sum_range_succ Finset.sum_range_succ
@[to_additive]
theorem prod_range_succ' (f : ℕ → β) :
∀ n : ℕ, (∏ k ∈ range (n + 1), f k) = (∏ k ∈ range n, f (k + 1)) * f 0
| 0 => prod_range_succ _ _
| n + 1 => by rw [prod_range_succ _ n, mul_right_comm, ← prod_range_succ' _ n, prod_range_succ]
#align finset.prod_range_succ' Finset.prod_range_succ'
#align finset.sum_range_succ' Finset.sum_range_succ'
@[to_additive]
theorem eventually_constant_prod {u : ℕ → β} {N : ℕ} (hu : ∀ n ≥ N, u n = 1) {n : ℕ} (hn : N ≤ n) :
(∏ k ∈ range n, u k) = ∏ k ∈ range N, u k := by
obtain ⟨m, rfl : n = N + m⟩ := Nat.exists_eq_add_of_le hn
clear hn
induction' m with m hm
· simp
· simp [← add_assoc, prod_range_succ, hm, hu]
#align finset.eventually_constant_prod Finset.eventually_constant_prod
#align finset.eventually_constant_sum Finset.eventually_constant_sum
@[to_additive]
theorem prod_range_add (f : ℕ → β) (n m : ℕ) :
(∏ x ∈ range (n + m), f x) = (∏ x ∈ range n, f x) * ∏ x ∈ range m, f (n + x) := by
induction' m with m hm
· simp
· erw [Nat.add_succ, prod_range_succ, prod_range_succ, hm, mul_assoc]
#align finset.prod_range_add Finset.prod_range_add
#align finset.sum_range_add Finset.sum_range_add
@[to_additive]
theorem prod_range_add_div_prod_range {α : Type*} [CommGroup α] (f : ℕ → α) (n m : ℕ) :
(∏ k ∈ range (n + m), f k) / ∏ k ∈ range n, f k = ∏ k ∈ Finset.range m, f (n + k) :=
div_eq_of_eq_mul' (prod_range_add f n m)
#align finset.prod_range_add_div_prod_range Finset.prod_range_add_div_prod_range
#align finset.sum_range_add_sub_sum_range Finset.sum_range_add_sub_sum_range
@[to_additive]
theorem prod_range_zero (f : ℕ → β) : ∏ k ∈ range 0, f k = 1 := by rw [range_zero, prod_empty]
#align finset.prod_range_zero Finset.prod_range_zero
#align finset.sum_range_zero Finset.sum_range_zero
@[to_additive sum_range_one]
theorem prod_range_one (f : ℕ → β) : ∏ k ∈ range 1, f k = f 0 := by
rw [range_one, prod_singleton]
#align finset.prod_range_one Finset.prod_range_one
#align finset.sum_range_one Finset.sum_range_one
open List
@[to_additive]
theorem prod_list_map_count [DecidableEq α] (l : List α) {M : Type*} [CommMonoid M] (f : α → M) :
(l.map f).prod = ∏ m ∈ l.toFinset, f m ^ l.count m := by
induction' l with a s IH; · simp only [map_nil, prod_nil, count_nil, pow_zero, prod_const_one]
simp only [List.map, List.prod_cons, toFinset_cons, IH]
by_cases has : a ∈ s.toFinset
· rw [insert_eq_of_mem has, ← insert_erase has, prod_insert (not_mem_erase _ _),
prod_insert (not_mem_erase _ _), ← mul_assoc, count_cons_self, pow_succ']
congr 1
refine prod_congr rfl fun x hx => ?_
rw [count_cons_of_ne (ne_of_mem_erase hx)]
rw [prod_insert has, count_cons_self, count_eq_zero_of_not_mem (mt mem_toFinset.2 has), pow_one]
congr 1
refine prod_congr rfl fun x hx => ?_
rw [count_cons_of_ne]
rintro rfl
exact has hx
#align finset.prod_list_map_count Finset.prod_list_map_count
#align finset.sum_list_map_count Finset.sum_list_map_count
@[to_additive]
theorem prod_list_count [DecidableEq α] [CommMonoid α] (s : List α) :
s.prod = ∏ m ∈ s.toFinset, m ^ s.count m := by simpa using prod_list_map_count s id
#align finset.prod_list_count Finset.prod_list_count
#align finset.sum_list_count Finset.sum_list_count
@[to_additive]
theorem prod_list_count_of_subset [DecidableEq α] [CommMonoid α] (m : List α) (s : Finset α)
(hs : m.toFinset ⊆ s) : m.prod = ∏ i ∈ s, i ^ m.count i := by
rw [prod_list_count]
refine prod_subset hs fun x _ hx => ?_
rw [mem_toFinset] at hx
rw [count_eq_zero_of_not_mem hx, pow_zero]
#align finset.prod_list_count_of_subset Finset.prod_list_count_of_subset
#align finset.sum_list_count_of_subset Finset.sum_list_count_of_subset
theorem sum_filter_count_eq_countP [DecidableEq α] (p : α → Prop) [DecidablePred p] (l : List α) :
∑ x ∈ l.toFinset.filter p, l.count x = l.countP p := by
simp [Finset.sum, sum_map_count_dedup_filter_eq_countP p l]
#align finset.sum_filter_count_eq_countp Finset.sum_filter_count_eq_countP
open Multiset
@[to_additive]
theorem prod_multiset_map_count [DecidableEq α] (s : Multiset α) {M : Type*} [CommMonoid M]
(f : α → M) : (s.map f).prod = ∏ m ∈ s.toFinset, f m ^ s.count m := by
refine Quot.induction_on s fun l => ?_
simp [prod_list_map_count l f]
#align finset.prod_multiset_map_count Finset.prod_multiset_map_count
#align finset.sum_multiset_map_count Finset.sum_multiset_map_count
@[to_additive]
theorem prod_multiset_count [DecidableEq α] [CommMonoid α] (s : Multiset α) :
s.prod = ∏ m ∈ s.toFinset, m ^ s.count m := by
convert prod_multiset_map_count s id
rw [Multiset.map_id]
#align finset.prod_multiset_count Finset.prod_multiset_count
#align finset.sum_multiset_count Finset.sum_multiset_count
@[to_additive]
theorem prod_multiset_count_of_subset [DecidableEq α] [CommMonoid α] (m : Multiset α) (s : Finset α)
(hs : m.toFinset ⊆ s) : m.prod = ∏ i ∈ s, i ^ m.count i := by
revert hs
refine Quot.induction_on m fun l => ?_
simp only [quot_mk_to_coe'', prod_coe, coe_count]
apply prod_list_count_of_subset l s
#align finset.prod_multiset_count_of_subset Finset.prod_multiset_count_of_subset
#align finset.sum_multiset_count_of_subset Finset.sum_multiset_count_of_subset
@[to_additive]
theorem prod_mem_multiset [DecidableEq α] (m : Multiset α) (f : { x // x ∈ m } → β) (g : α → β)
(hfg : ∀ x, f x = g x) : ∏ x : { x // x ∈ m }, f x = ∏ x ∈ m.toFinset, g x := by
refine prod_bij' (fun x _ ↦ x) (fun x hx ↦ ⟨x, Multiset.mem_toFinset.1 hx⟩) ?_ ?_ ?_ ?_ ?_ <;>
simp [hfg]
#align finset.prod_mem_multiset Finset.prod_mem_multiset
#align finset.sum_mem_multiset Finset.sum_mem_multiset
/-- To prove a property of a product, it suffices to prove that
the property is multiplicative and holds on factors. -/
@[to_additive "To prove a property of a sum, it suffices to prove that
the property is additive and holds on summands."]
theorem prod_induction {M : Type*} [CommMonoid M] (f : α → M) (p : M → Prop)
(hom : ∀ a b, p a → p b → p (a * b)) (unit : p 1) (base : ∀ x ∈ s, p <| f x) :
p <| ∏ x ∈ s, f x :=
Multiset.prod_induction _ _ hom unit (Multiset.forall_mem_map_iff.mpr base)
#align finset.prod_induction Finset.prod_induction
#align finset.sum_induction Finset.sum_induction
/-- To prove a property of a product, it suffices to prove that
the property is multiplicative and holds on factors. -/
@[to_additive "To prove a property of a sum, it suffices to prove that
the property is additive and holds on summands."]
theorem prod_induction_nonempty {M : Type*} [CommMonoid M] (f : α → M) (p : M → Prop)
(hom : ∀ a b, p a → p b → p (a * b)) (nonempty : s.Nonempty) (base : ∀ x ∈ s, p <| f x) :
p <| ∏ x ∈ s, f x :=
Multiset.prod_induction_nonempty p hom (by simp [nonempty_iff_ne_empty.mp nonempty])
(Multiset.forall_mem_map_iff.mpr base)
#align finset.prod_induction_nonempty Finset.prod_induction_nonempty
#align finset.sum_induction_nonempty Finset.sum_induction_nonempty
/-- For any product along `{0, ..., n - 1}` of a commutative-monoid-valued function, we can verify
that it's equal to a different function just by checking ratios of adjacent terms.
This is a multiplicative discrete analogue of the fundamental theorem of calculus. -/
@[to_additive "For any sum along `{0, ..., n - 1}` of a commutative-monoid-valued function, we can
verify that it's equal to a different function just by checking differences of adjacent terms.
This is a discrete analogue of the fundamental theorem of calculus."]
theorem prod_range_induction (f s : ℕ → β) (base : s 0 = 1)
(step : ∀ n, s (n + 1) = s n * f n) (n : ℕ) :
∏ k ∈ Finset.range n, f k = s n := by
induction' n with k hk
· rw [Finset.prod_range_zero, base]
· simp only [hk, Finset.prod_range_succ, step, mul_comm]
#align finset.prod_range_induction Finset.prod_range_induction
#align finset.sum_range_induction Finset.sum_range_induction
/-- A telescoping product along `{0, ..., n - 1}` of a commutative group valued function reduces to
the ratio of the last and first factors. -/
@[to_additive "A telescoping sum along `{0, ..., n - 1}` of an additive commutative group valued
function reduces to the difference of the last and first terms."]
theorem prod_range_div {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
(∏ i ∈ range n, f (i + 1) / f i) = f n / f 0 := by apply prod_range_induction <;> simp
#align finset.prod_range_div Finset.prod_range_div
#align finset.sum_range_sub Finset.sum_range_sub
@[to_additive]
theorem prod_range_div' {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
(∏ i ∈ range n, f i / f (i + 1)) = f 0 / f n := by apply prod_range_induction <;> simp
#align finset.prod_range_div' Finset.prod_range_div'
#align finset.sum_range_sub' Finset.sum_range_sub'
@[to_additive]
theorem eq_prod_range_div {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
f n = f 0 * ∏ i ∈ range n, f (i + 1) / f i := by rw [prod_range_div, mul_div_cancel]
#align finset.eq_prod_range_div Finset.eq_prod_range_div
#align finset.eq_sum_range_sub Finset.eq_sum_range_sub
@[to_additive]
theorem eq_prod_range_div' {M : Type*} [CommGroup M] (f : ℕ → M) (n : ℕ) :
f n = ∏ i ∈ range (n + 1), if i = 0 then f 0 else f i / f (i - 1) := by
conv_lhs => rw [Finset.eq_prod_range_div f]
simp [Finset.prod_range_succ', mul_comm]
#align finset.eq_prod_range_div' Finset.eq_prod_range_div'
#align finset.eq_sum_range_sub' Finset.eq_sum_range_sub'
/-- A telescoping sum along `{0, ..., n-1}` of an `ℕ`-valued function
reduces to the difference of the last and first terms
when the function we are summing is monotone.
-/
theorem sum_range_tsub [CanonicallyOrderedAddCommMonoid α] [Sub α] [OrderedSub α]
[ContravariantClass α α (· + ·) (· ≤ ·)] {f : ℕ → α} (h : Monotone f) (n : ℕ) :
∑ i ∈ range n, (f (i + 1) - f i) = f n - f 0 := by
apply sum_range_induction
case base => apply tsub_self
case step =>
intro n
have h₁ : f n ≤ f (n + 1) := h (Nat.le_succ _)
have h₂ : f 0 ≤ f n := h (Nat.zero_le _)
rw [tsub_add_eq_add_tsub h₂, add_tsub_cancel_of_le h₁]
#align finset.sum_range_tsub Finset.sum_range_tsub
@[to_additive (attr := simp)]
theorem prod_const (b : β) : ∏ _x ∈ s, b = b ^ s.card :=
(congr_arg _ <| s.val.map_const b).trans <| Multiset.prod_replicate s.card b
#align finset.prod_const Finset.prod_const
#align finset.sum_const Finset.sum_const
@[to_additive sum_eq_card_nsmul]
theorem prod_eq_pow_card {b : β} (hf : ∀ a ∈ s, f a = b) : ∏ a ∈ s, f a = b ^ s.card :=
(prod_congr rfl hf).trans <| prod_const _
#align finset.prod_eq_pow_card Finset.prod_eq_pow_card
#align finset.sum_eq_card_nsmul Finset.sum_eq_card_nsmul
@[to_additive card_nsmul_add_sum]
theorem pow_card_mul_prod {b : β} : b ^ s.card * ∏ a ∈ s, f a = ∏ a ∈ s, b * f a :=
(Finset.prod_const b).symm ▸ prod_mul_distrib.symm
@[to_additive sum_add_card_nsmul]
theorem prod_mul_pow_card {b : β} : (∏ a ∈ s, f a) * b ^ s.card = ∏ a ∈ s, f a * b :=
(Finset.prod_const b).symm ▸ prod_mul_distrib.symm
@[to_additive]
theorem pow_eq_prod_const (b : β) : ∀ n, b ^ n = ∏ _k ∈ range n, b := by simp
#align finset.pow_eq_prod_const Finset.pow_eq_prod_const
#align finset.nsmul_eq_sum_const Finset.nsmul_eq_sum_const
@[to_additive]
theorem prod_pow (s : Finset α) (n : ℕ) (f : α → β) : ∏ x ∈ s, f x ^ n = (∏ x ∈ s, f x) ^ n :=
Multiset.prod_map_pow
#align finset.prod_pow Finset.prod_pow
#align finset.sum_nsmul Finset.sum_nsmul
@[to_additive sum_nsmul_assoc]
lemma prod_pow_eq_pow_sum (s : Finset ι) (f : ι → ℕ) (a : β) :
∏ i ∈ s, a ^ f i = a ^ ∑ i ∈ s, f i :=
cons_induction (by simp) (fun _ _ _ _ ↦ by simp [prod_cons, sum_cons, pow_add, *]) s
#align finset.prod_pow_eq_pow_sum Finset.prod_pow_eq_pow_sum
/-- A product over `Finset.powersetCard` which only depends on the size of the sets is constant. -/
@[to_additive
"A sum over `Finset.powersetCard` which only depends on the size of the sets is constant."]
lemma prod_powersetCard (n : ℕ) (s : Finset α) (f : ℕ → β) :
∏ t ∈ powersetCard n s, f t.card = f n ^ s.card.choose n := by
rw [prod_eq_pow_card, card_powersetCard]; rintro a ha; rw [(mem_powersetCard.1 ha).2]
@[to_additive]
theorem prod_flip {n : ℕ} (f : ℕ → β) :
(∏ r ∈ range (n + 1), f (n - r)) = ∏ k ∈ range (n + 1), f k := by
induction' n with n ih
· rw [prod_range_one, prod_range_one]
· rw [prod_range_succ', prod_range_succ _ (Nat.succ n)]
simp [← ih]
#align finset.prod_flip Finset.prod_flip
#align finset.sum_flip Finset.sum_flip
@[to_additive]
| Mathlib/Algebra/BigOperators/Group/Finset.lean | 1,791 | 1,828 | theorem prod_involution {s : Finset α} {f : α → β} :
∀ (g : ∀ a ∈ s, α) (_ : ∀ a ha, f a * f (g a ha) = 1) (_ : ∀ a ha, f a ≠ 1 → g a ha ≠ a)
(g_mem : ∀ a ha, g a ha ∈ s) (_ : ∀ a ha, g (g a ha) (g_mem a ha) = a),
∏ x ∈ s, f x = 1 := by |
haveI := Classical.decEq α; haveI := Classical.decEq β
exact
Finset.strongInductionOn s fun s ih g h g_ne g_mem g_inv =>
s.eq_empty_or_nonempty.elim (fun hs => hs.symm ▸ rfl) fun ⟨x, hx⟩ =>
have hmem : ∀ y ∈ (s.erase x).erase (g x hx), y ∈ s := fun y hy =>
mem_of_mem_erase (mem_of_mem_erase hy)
have g_inj : ∀ {x hx y hy}, g x hx = g y hy → x = y := fun {x hx y hy} h => by
rw [← g_inv x hx, ← g_inv y hy]; simp [h]
have ih' : (∏ y ∈ erase (erase s x) (g x hx), f y) = (1 : β) :=
ih ((s.erase x).erase (g x hx))
⟨Subset.trans (erase_subset _ _) (erase_subset _ _), fun h =>
not_mem_erase (g x hx) (s.erase x) (h (g_mem x hx))⟩
(fun y hy => g y (hmem y hy)) (fun y hy => h y (hmem y hy))
(fun y hy => g_ne y (hmem y hy))
(fun y hy =>
mem_erase.2
⟨fun h : g y _ = g x hx => by simp [g_inj h] at hy,
mem_erase.2
⟨fun h : g y _ = x => by
have : y = g x hx := g_inv y (hmem y hy) ▸ by simp [h]
simp [this] at hy, g_mem y (hmem y hy)⟩⟩)
fun y hy => g_inv y (hmem y hy)
if hx1 : f x = 1 then
ih' ▸
Eq.symm
(prod_subset hmem fun y hy hy₁ =>
have : y = x ∨ y = g x hx := by
simpa [hy, -not_and, mem_erase, not_and_or, or_comm] using hy₁
this.elim (fun hy => hy.symm ▸ hx1) fun hy =>
h x hx ▸ hy ▸ hx1.symm ▸ (one_mul _).symm)
else by
rw [← insert_erase hx, prod_insert (not_mem_erase _ _), ←
insert_erase (mem_erase.2 ⟨g_ne x hx hx1, g_mem x hx⟩),
prod_insert (not_mem_erase _ _), ih', mul_one, h x hx]
|
/-
Copyright (c) 2020 Joseph Myers. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joseph Myers, Manuel Candales
-/
import Mathlib.Analysis.InnerProductSpace.Projection
import Mathlib.Geometry.Euclidean.PerpBisector
import Mathlib.Algebra.QuadraticDiscriminant
#align_import geometry.euclidean.basic from "leanprover-community/mathlib"@"2de9c37fa71dde2f1c6feff19876dd6a7b1519f0"
/-!
# Euclidean spaces
This file makes some definitions and proves very basic geometrical
results about real inner product spaces and Euclidean affine spaces.
Results about real inner product spaces that involve the norm and
inner product but not angles generally go in
`Analysis.NormedSpace.InnerProduct`. Results with longer
proofs or more geometrical content generally go in separate files.
## Main definitions
* `EuclideanGeometry.orthogonalProjection` is the orthogonal
projection of a point onto an affine subspace.
* `EuclideanGeometry.reflection` is the reflection of a point in an
affine subspace.
## Implementation notes
To declare `P` as the type of points in a Euclidean affine space with
`V` as the type of vectors, use
`[NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P] [NormedAddTorsor V P]`.
This works better with `outParam` to make
`V` implicit in most cases than having a separate type alias for
Euclidean affine spaces.
Rather than requiring Euclidean affine spaces to be finite-dimensional
(as in the definition on Wikipedia), this is specified only for those
theorems that need it.
## References
* https://en.wikipedia.org/wiki/Euclidean_space
-/
noncomputable section
open scoped Classical
open RealInnerProductSpace
namespace EuclideanGeometry
/-!
### Geometrical results on Euclidean affine spaces
This section develops some geometrical definitions and results on
Euclidean affine spaces.
-/
variable {V : Type*} {P : Type*}
variable [NormedAddCommGroup V] [InnerProductSpace ℝ V] [MetricSpace P]
variable [NormedAddTorsor V P]
/-- The midpoint of the segment AB is the same distance from A as it is from B. -/
theorem dist_left_midpoint_eq_dist_right_midpoint (p1 p2 : P) :
dist p1 (midpoint ℝ p1 p2) = dist p2 (midpoint ℝ p1 p2) := by
rw [dist_left_midpoint (𝕜 := ℝ) p1 p2, dist_right_midpoint (𝕜 := ℝ) p1 p2]
#align euclidean_geometry.dist_left_midpoint_eq_dist_right_midpoint EuclideanGeometry.dist_left_midpoint_eq_dist_right_midpoint
/-- The inner product of two vectors given with `weightedVSub`, in
terms of the pairwise distances. -/
theorem inner_weightedVSub {ι₁ : Type*} {s₁ : Finset ι₁} {w₁ : ι₁ → ℝ} (p₁ : ι₁ → P)
(h₁ : ∑ i ∈ s₁, w₁ i = 0) {ι₂ : Type*} {s₂ : Finset ι₂} {w₂ : ι₂ → ℝ} (p₂ : ι₂ → P)
(h₂ : ∑ i ∈ s₂, w₂ i = 0) :
⟪s₁.weightedVSub p₁ w₁, s₂.weightedVSub p₂ w₂⟫ =
(-∑ i₁ ∈ s₁, ∑ i₂ ∈ s₂, w₁ i₁ * w₂ i₂ * (dist (p₁ i₁) (p₂ i₂) * dist (p₁ i₁) (p₂ i₂))) /
2 := by
rw [Finset.weightedVSub_apply, Finset.weightedVSub_apply,
inner_sum_smul_sum_smul_of_sum_eq_zero _ h₁ _ h₂]
simp_rw [vsub_sub_vsub_cancel_right]
rcongr (i₁ i₂) <;> rw [dist_eq_norm_vsub V (p₁ i₁) (p₂ i₂)]
#align euclidean_geometry.inner_weighted_vsub EuclideanGeometry.inner_weightedVSub
/-- The distance between two points given with `affineCombination`,
in terms of the pairwise distances between the points in that
combination. -/
theorem dist_affineCombination {ι : Type*} {s : Finset ι} {w₁ w₂ : ι → ℝ} (p : ι → P)
(h₁ : ∑ i ∈ s, w₁ i = 1) (h₂ : ∑ i ∈ s, w₂ i = 1) : by
have a₁ := s.affineCombination ℝ p w₁
have a₂ := s.affineCombination ℝ p w₂
exact dist a₁ a₂ * dist a₁ a₂ = (-∑ i₁ ∈ s, ∑ i₂ ∈ s,
(w₁ - w₂) i₁ * (w₁ - w₂) i₂ * (dist (p i₁) (p i₂) * dist (p i₁) (p i₂))) / 2 := by
dsimp only
rw [dist_eq_norm_vsub V (s.affineCombination ℝ p w₁) (s.affineCombination ℝ p w₂), ←
@inner_self_eq_norm_mul_norm ℝ, Finset.affineCombination_vsub]
have h : (∑ i ∈ s, (w₁ - w₂) i) = 0 := by
simp_rw [Pi.sub_apply, Finset.sum_sub_distrib, h₁, h₂, sub_self]
exact inner_weightedVSub p h p h
#align euclidean_geometry.dist_affine_combination EuclideanGeometry.dist_affineCombination
-- Porting note: `inner_vsub_vsub_of_dist_eq_of_dist_eq` moved to `PerpendicularBisector`
/-- The squared distance between points on a line (expressed as a
multiple of a fixed vector added to a point) and another point,
expressed as a quadratic. -/
theorem dist_smul_vadd_sq (r : ℝ) (v : V) (p₁ p₂ : P) :
dist (r • v +ᵥ p₁) p₂ * dist (r • v +ᵥ p₁) p₂ =
⟪v, v⟫ * r * r + 2 * ⟪v, p₁ -ᵥ p₂⟫ * r + ⟪p₁ -ᵥ p₂, p₁ -ᵥ p₂⟫ := by
rw [dist_eq_norm_vsub V _ p₂, ← real_inner_self_eq_norm_mul_norm, vadd_vsub_assoc,
real_inner_add_add_self, real_inner_smul_left, real_inner_smul_left, real_inner_smul_right]
ring
#align euclidean_geometry.dist_smul_vadd_sq EuclideanGeometry.dist_smul_vadd_sq
/-- The condition for two points on a line to be equidistant from
another point. -/
theorem dist_smul_vadd_eq_dist {v : V} (p₁ p₂ : P) (hv : v ≠ 0) (r : ℝ) :
dist (r • v +ᵥ p₁) p₂ = dist p₁ p₂ ↔ r = 0 ∨ r = -2 * ⟪v, p₁ -ᵥ p₂⟫ / ⟪v, v⟫ := by
conv_lhs =>
rw [← mul_self_inj_of_nonneg dist_nonneg dist_nonneg, dist_smul_vadd_sq, ← sub_eq_zero,
add_sub_assoc, dist_eq_norm_vsub V p₁ p₂, ← real_inner_self_eq_norm_mul_norm, sub_self]
have hvi : ⟪v, v⟫ ≠ 0 := by simpa using hv
have hd : discrim ⟪v, v⟫ (2 * ⟪v, p₁ -ᵥ p₂⟫) 0 = 2 * ⟪v, p₁ -ᵥ p₂⟫ * (2 * ⟪v, p₁ -ᵥ p₂⟫) := by
rw [discrim]
ring
rw [quadratic_eq_zero_iff hvi hd, add_left_neg, zero_div, neg_mul_eq_neg_mul, ←
mul_sub_right_distrib, sub_eq_add_neg, ← mul_two, mul_assoc, mul_div_assoc, mul_div_mul_left,
mul_div_assoc]
norm_num
#align euclidean_geometry.dist_smul_vadd_eq_dist EuclideanGeometry.dist_smul_vadd_eq_dist
open AffineSubspace FiniteDimensional
/-- Distances `r₁` `r₂` of `p` from two different points `c₁` `c₂` determine at
most two points `p₁` `p₂` in a two-dimensional subspace containing those points
(two circles intersect in at most two points). -/
theorem eq_of_dist_eq_of_dist_eq_of_mem_of_finrank_eq_two {s : AffineSubspace ℝ P}
[FiniteDimensional ℝ s.direction] (hd : finrank ℝ s.direction = 2) {c₁ c₂ p₁ p₂ p : P}
(hc₁s : c₁ ∈ s) (hc₂s : c₂ ∈ s) (hp₁s : p₁ ∈ s) (hp₂s : p₂ ∈ s) (hps : p ∈ s) {r₁ r₂ : ℝ}
(hc : c₁ ≠ c₂) (hp : p₁ ≠ p₂) (hp₁c₁ : dist p₁ c₁ = r₁) (hp₂c₁ : dist p₂ c₁ = r₁)
(hpc₁ : dist p c₁ = r₁) (hp₁c₂ : dist p₁ c₂ = r₂) (hp₂c₂ : dist p₂ c₂ = r₂)
(hpc₂ : dist p c₂ = r₂) : p = p₁ ∨ p = p₂ := by
have ho : ⟪c₂ -ᵥ c₁, p₂ -ᵥ p₁⟫ = 0 :=
inner_vsub_vsub_of_dist_eq_of_dist_eq (hp₁c₁.trans hp₂c₁.symm) (hp₁c₂.trans hp₂c₂.symm)
have hop : ⟪c₂ -ᵥ c₁, p -ᵥ p₁⟫ = 0 :=
inner_vsub_vsub_of_dist_eq_of_dist_eq (hp₁c₁.trans hpc₁.symm) (hp₁c₂.trans hpc₂.symm)
let b : Fin 2 → V := ![c₂ -ᵥ c₁, p₂ -ᵥ p₁]
have hb : LinearIndependent ℝ b := by
refine linearIndependent_of_ne_zero_of_inner_eq_zero ?_ ?_
· intro i
fin_cases i <;> simp [b, hc.symm, hp.symm]
· intro i j hij
fin_cases i <;> fin_cases j <;> try exact False.elim (hij rfl)
· exact ho
· rw [real_inner_comm]
exact ho
have hbs : Submodule.span ℝ (Set.range b) = s.direction := by
refine eq_of_le_of_finrank_eq ?_ ?_
· rw [Submodule.span_le, Set.range_subset_iff]
intro i
fin_cases i
· exact vsub_mem_direction hc₂s hc₁s
· exact vsub_mem_direction hp₂s hp₁s
· rw [finrank_span_eq_card hb, Fintype.card_fin, hd]
have hv : ∀ v ∈ s.direction, ∃ t₁ t₂ : ℝ, v = t₁ • (c₂ -ᵥ c₁) + t₂ • (p₂ -ᵥ p₁) := by
intro v hv
have hr : Set.range b = {c₂ -ᵥ c₁, p₂ -ᵥ p₁} := by
have hu : (Finset.univ : Finset (Fin 2)) = {0, 1} := by decide
rw [← Fintype.coe_image_univ, hu]
simp [b]
rw [← hbs, hr, Submodule.mem_span_insert] at hv
rcases hv with ⟨t₁, v', hv', hv⟩
rw [Submodule.mem_span_singleton] at hv'
rcases hv' with ⟨t₂, rfl⟩
exact ⟨t₁, t₂, hv⟩
rcases hv (p -ᵥ p₁) (vsub_mem_direction hps hp₁s) with ⟨t₁, t₂, hpt⟩
simp only [hpt, inner_add_right, inner_smul_right, ho, mul_zero, add_zero,
mul_eq_zero, inner_self_eq_zero, vsub_eq_zero_iff_eq, hc.symm, or_false_iff] at hop
rw [hop, zero_smul, zero_add, ← eq_vadd_iff_vsub_eq] at hpt
subst hpt
have hp' : (p₂ -ᵥ p₁ : V) ≠ 0 := by simp [hp.symm]
have hp₂ : dist ((1 : ℝ) • (p₂ -ᵥ p₁) +ᵥ p₁) c₁ = r₁ := by simp [hp₂c₁]
rw [← hp₁c₁, dist_smul_vadd_eq_dist _ _ hp'] at hpc₁ hp₂
simp only [one_ne_zero, false_or_iff] at hp₂
rw [hp₂.symm] at hpc₁
cases' hpc₁ with hpc₁ hpc₁ <;> simp [hpc₁]
#align euclidean_geometry.eq_of_dist_eq_of_dist_eq_of_mem_of_finrank_eq_two EuclideanGeometry.eq_of_dist_eq_of_dist_eq_of_mem_of_finrank_eq_two
/-- Distances `r₁` `r₂` of `p` from two different points `c₁` `c₂` determine at
most two points `p₁` `p₂` in two-dimensional space (two circles intersect in at
most two points). -/
theorem eq_of_dist_eq_of_dist_eq_of_finrank_eq_two [FiniteDimensional ℝ V] (hd : finrank ℝ V = 2)
{c₁ c₂ p₁ p₂ p : P} {r₁ r₂ : ℝ} (hc : c₁ ≠ c₂) (hp : p₁ ≠ p₂) (hp₁c₁ : dist p₁ c₁ = r₁)
(hp₂c₁ : dist p₂ c₁ = r₁) (hpc₁ : dist p c₁ = r₁) (hp₁c₂ : dist p₁ c₂ = r₂)
(hp₂c₂ : dist p₂ c₂ = r₂) (hpc₂ : dist p c₂ = r₂) : p = p₁ ∨ p = p₂ :=
haveI hd' : finrank ℝ (⊤ : AffineSubspace ℝ P).direction = 2 := by
rw [direction_top, finrank_top]
exact hd
eq_of_dist_eq_of_dist_eq_of_mem_of_finrank_eq_two hd' (mem_top ℝ V _) (mem_top ℝ V _)
(mem_top ℝ V _) (mem_top ℝ V _) (mem_top ℝ V _) hc hp hp₁c₁ hp₂c₁ hpc₁ hp₁c₂ hp₂c₂ hpc₂
#align euclidean_geometry.eq_of_dist_eq_of_dist_eq_of_finrank_eq_two EuclideanGeometry.eq_of_dist_eq_of_dist_eq_of_finrank_eq_two
/-- The orthogonal projection of a point onto a nonempty affine
subspace, whose direction is complete, as an unbundled function. This
definition is only intended for use in setting up the bundled version
`orthogonalProjection` and should not be used once that is
defined. -/
def orthogonalProjectionFn (s : AffineSubspace ℝ P) [Nonempty s]
[HasOrthogonalProjection s.direction] (p : P) : P :=
Classical.choose <|
inter_eq_singleton_of_nonempty_of_isCompl (nonempty_subtype.mp ‹_›)
(mk'_nonempty p s.directionᗮ)
(by
rw [direction_mk' p s.directionᗮ]
exact Submodule.isCompl_orthogonal_of_completeSpace)
#align euclidean_geometry.orthogonal_projection_fn EuclideanGeometry.orthogonalProjectionFn
/-- The intersection of the subspace and the orthogonal subspace
through the given point is the `orthogonalProjectionFn` of that
point onto the subspace. This lemma is only intended for use in
setting up the bundled version and should not be used once that is
defined. -/
theorem inter_eq_singleton_orthogonalProjectionFn {s : AffineSubspace ℝ P} [Nonempty s]
[HasOrthogonalProjection s.direction] (p : P) :
(s : Set P) ∩ mk' p s.directionᗮ = {orthogonalProjectionFn s p} :=
Classical.choose_spec <|
inter_eq_singleton_of_nonempty_of_isCompl (nonempty_subtype.mp ‹_›)
(mk'_nonempty p s.directionᗮ)
(by
rw [direction_mk' p s.directionᗮ]
exact Submodule.isCompl_orthogonal_of_completeSpace)
#align euclidean_geometry.inter_eq_singleton_orthogonal_projection_fn EuclideanGeometry.inter_eq_singleton_orthogonalProjectionFn
/-- The `orthogonalProjectionFn` lies in the given subspace. This
lemma is only intended for use in setting up the bundled version and
should not be used once that is defined. -/
theorem orthogonalProjectionFn_mem {s : AffineSubspace ℝ P} [Nonempty s]
[HasOrthogonalProjection s.direction] (p : P) : orthogonalProjectionFn s p ∈ s := by
rw [← mem_coe, ← Set.singleton_subset_iff, ← inter_eq_singleton_orthogonalProjectionFn]
exact Set.inter_subset_left
#align euclidean_geometry.orthogonal_projection_fn_mem EuclideanGeometry.orthogonalProjectionFn_mem
/-- The `orthogonalProjectionFn` lies in the orthogonal
subspace. This lemma is only intended for use in setting up the
bundled version and should not be used once that is defined. -/
| Mathlib/Geometry/Euclidean/Basic.lean | 251 | 255 | theorem orthogonalProjectionFn_mem_orthogonal {s : AffineSubspace ℝ P} [Nonempty s]
[HasOrthogonalProjection s.direction] (p : P) :
orthogonalProjectionFn s p ∈ mk' p s.directionᗮ := by |
rw [← mem_coe, ← Set.singleton_subset_iff, ← inter_eq_singleton_orthogonalProjectionFn]
exact Set.inter_subset_right
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Jan-David Salchow, Sébastien Gouëzel, Jean Lo, Yury Kudryashov, Frédéric Dupuis,
Heather Macbeth
-/
import Mathlib.Topology.Algebra.Ring.Basic
import Mathlib.Topology.Algebra.MulAction
import Mathlib.Topology.Algebra.UniformGroup
import Mathlib.Topology.ContinuousFunction.Basic
import Mathlib.Topology.UniformSpace.UniformEmbedding
import Mathlib.Algebra.Algebra.Defs
import Mathlib.LinearAlgebra.Projection
import Mathlib.LinearAlgebra.Pi
import Mathlib.LinearAlgebra.Finsupp
#align_import topology.algebra.module.basic from "leanprover-community/mathlib"@"6285167a053ad0990fc88e56c48ccd9fae6550eb"
/-!
# Theory of topological modules and continuous linear maps.
We use the class `ContinuousSMul` for topological (semi) modules and topological vector spaces.
In this file we define continuous (semi-)linear maps, as semilinear maps between topological
modules which are continuous. The set of continuous semilinear maps between the topological
`R₁`-module `M` and `R₂`-module `M₂` with respect to the `RingHom` `σ` is denoted by `M →SL[σ] M₂`.
Plain linear maps are denoted by `M →L[R] M₂` and star-linear maps by `M →L⋆[R] M₂`.
The corresponding notation for equivalences is `M ≃SL[σ] M₂`, `M ≃L[R] M₂` and `M ≃L⋆[R] M₂`.
-/
open LinearMap (ker range)
open Topology Filter Pointwise
universe u v w u'
section
variable {R : Type*} {M : Type*} [Ring R] [TopologicalSpace R] [TopologicalSpace M]
[AddCommGroup M] [Module R M]
theorem ContinuousSMul.of_nhds_zero [TopologicalRing R] [TopologicalAddGroup M]
(hmul : Tendsto (fun p : R × M => p.1 • p.2) (𝓝 0 ×ˢ 𝓝 0) (𝓝 0))
(hmulleft : ∀ m : M, Tendsto (fun a : R => a • m) (𝓝 0) (𝓝 0))
(hmulright : ∀ a : R, Tendsto (fun m : M => a • m) (𝓝 0) (𝓝 0)) : ContinuousSMul R M where
continuous_smul := by
refine continuous_of_continuousAt_zero₂ (AddMonoidHom.smul : R →+ M →+ M) ?_ ?_ ?_ <;>
simpa [ContinuousAt, nhds_prod_eq]
#align has_continuous_smul.of_nhds_zero ContinuousSMul.of_nhds_zero
end
section
variable {R : Type*} {M : Type*} [Ring R] [TopologicalSpace R] [TopologicalSpace M]
[AddCommGroup M] [ContinuousAdd M] [Module R M] [ContinuousSMul R M]
/-- If `M` is a topological module over `R` and `0` is a limit of invertible elements of `R`, then
`⊤` is the only submodule of `M` with a nonempty interior.
This is the case, e.g., if `R` is a nontrivially normed field. -/
theorem Submodule.eq_top_of_nonempty_interior' [NeBot (𝓝[{ x : R | IsUnit x }] 0)]
(s : Submodule R M) (hs : (interior (s : Set M)).Nonempty) : s = ⊤ := by
rcases hs with ⟨y, hy⟩
refine Submodule.eq_top_iff'.2 fun x => ?_
rw [mem_interior_iff_mem_nhds] at hy
have : Tendsto (fun c : R => y + c • x) (𝓝[{ x : R | IsUnit x }] 0) (𝓝 (y + (0 : R) • x)) :=
tendsto_const_nhds.add ((tendsto_nhdsWithin_of_tendsto_nhds tendsto_id).smul tendsto_const_nhds)
rw [zero_smul, add_zero] at this
obtain ⟨_, hu : y + _ • _ ∈ s, u, rfl⟩ :=
nonempty_of_mem (inter_mem (Filter.mem_map.1 (this hy)) self_mem_nhdsWithin)
have hy' : y ∈ ↑s := mem_of_mem_nhds hy
rwa [s.add_mem_iff_right hy', ← Units.smul_def, s.smul_mem_iff' u] at hu
#align submodule.eq_top_of_nonempty_interior' Submodule.eq_top_of_nonempty_interior'
variable (R M)
/-- Let `R` be a topological ring such that zero is not an isolated point (e.g., a nontrivially
normed field, see `NormedField.punctured_nhds_neBot`). Let `M` be a nontrivial module over `R`
such that `c • x = 0` implies `c = 0 ∨ x = 0`. Then `M` has no isolated points. We formulate this
using `NeBot (𝓝[≠] x)`.
This lemma is not an instance because Lean would need to find `[ContinuousSMul ?m_1 M]` with
unknown `?m_1`. We register this as an instance for `R = ℝ` in `Real.punctured_nhds_module_neBot`.
One can also use `haveI := Module.punctured_nhds_neBot R M` in a proof.
-/
theorem Module.punctured_nhds_neBot [Nontrivial M] [NeBot (𝓝[≠] (0 : R))] [NoZeroSMulDivisors R M]
(x : M) : NeBot (𝓝[≠] x) := by
rcases exists_ne (0 : M) with ⟨y, hy⟩
suffices Tendsto (fun c : R => x + c • y) (𝓝[≠] 0) (𝓝[≠] x) from this.neBot
refine Tendsto.inf ?_ (tendsto_principal_principal.2 <| ?_)
· convert tendsto_const_nhds.add ((@tendsto_id R _).smul_const y)
rw [zero_smul, add_zero]
· intro c hc
simpa [hy] using hc
#align module.punctured_nhds_ne_bot Module.punctured_nhds_neBot
end
section LatticeOps
variable {ι R M₁ M₂ : Type*} [Semiring R] [AddCommMonoid M₁] [AddCommMonoid M₂] [Module R M₁]
[Module R M₂] [u : TopologicalSpace R] {t : TopologicalSpace M₂} [ContinuousSMul R M₂]
(f : M₁ →ₗ[R] M₂)
theorem continuousSMul_induced : @ContinuousSMul R M₁ _ u (t.induced f) :=
let _ : TopologicalSpace M₁ := t.induced f
Inducing.continuousSMul ⟨rfl⟩ continuous_id (map_smul f _ _)
#align has_continuous_smul_induced continuousSMul_induced
end LatticeOps
/-- The span of a separable subset with respect to a separable scalar ring is again separable. -/
lemma TopologicalSpace.IsSeparable.span {R M : Type*} [AddCommMonoid M] [Semiring R] [Module R M]
[TopologicalSpace M] [TopologicalSpace R] [SeparableSpace R]
[ContinuousAdd M] [ContinuousSMul R M] {s : Set M} (hs : IsSeparable s) :
IsSeparable (Submodule.span R s : Set M) := by
rw [span_eq_iUnion_nat]
refine .iUnion fun n ↦ .image ?_ ?_
· have : IsSeparable {f : Fin n → R × M | ∀ (i : Fin n), f i ∈ Set.univ ×ˢ s} := by
apply isSeparable_pi (fun i ↦ .prod (.of_separableSpace Set.univ) hs)
rwa [Set.univ_prod] at this
· apply continuous_finset_sum _ (fun i _ ↦ ?_)
exact (continuous_fst.comp (continuous_apply i)).smul (continuous_snd.comp (continuous_apply i))
namespace Submodule
variable {α β : Type*} [TopologicalSpace β]
#align submodule.has_continuous_smul SMulMemClass.continuousSMul
instance topologicalAddGroup [Ring α] [AddCommGroup β] [Module α β] [TopologicalAddGroup β]
(S : Submodule α β) : TopologicalAddGroup S :=
inferInstanceAs (TopologicalAddGroup S.toAddSubgroup)
#align submodule.topological_add_group Submodule.topologicalAddGroup
end Submodule
section closure
variable {R R' : Type u} {M M' : Type v} [Semiring R] [Ring R']
[TopologicalSpace M] [AddCommMonoid M] [TopologicalSpace M'] [AddCommGroup M'] [Module R M]
[ContinuousConstSMul R M] [Module R' M'] [ContinuousConstSMul R' M']
theorem Submodule.mapsTo_smul_closure (s : Submodule R M) (c : R) :
Set.MapsTo (c • ·) (closure s : Set M) (closure s) :=
have : Set.MapsTo (c • ·) (s : Set M) s := fun _ h ↦ s.smul_mem c h
this.closure (continuous_const_smul c)
theorem Submodule.smul_closure_subset (s : Submodule R M) (c : R) :
c • closure (s : Set M) ⊆ closure (s : Set M) :=
(s.mapsTo_smul_closure c).image_subset
variable [ContinuousAdd M]
/-- The (topological-space) closure of a submodule of a topological `R`-module `M` is itself
a submodule. -/
def Submodule.topologicalClosure (s : Submodule R M) : Submodule R M :=
{ s.toAddSubmonoid.topologicalClosure with
smul_mem' := s.mapsTo_smul_closure }
#align submodule.topological_closure Submodule.topologicalClosure
@[simp]
theorem Submodule.topologicalClosure_coe (s : Submodule R M) :
(s.topologicalClosure : Set M) = closure (s : Set M) :=
rfl
#align submodule.topological_closure_coe Submodule.topologicalClosure_coe
theorem Submodule.le_topologicalClosure (s : Submodule R M) : s ≤ s.topologicalClosure :=
subset_closure
#align submodule.le_topological_closure Submodule.le_topologicalClosure
theorem Submodule.closure_subset_topologicalClosure_span (s : Set M) :
closure s ⊆ (span R s).topologicalClosure := by
rw [Submodule.topologicalClosure_coe]
exact closure_mono subset_span
theorem Submodule.isClosed_topologicalClosure (s : Submodule R M) :
IsClosed (s.topologicalClosure : Set M) := isClosed_closure
#align submodule.is_closed_topological_closure Submodule.isClosed_topologicalClosure
theorem Submodule.topologicalClosure_minimal (s : Submodule R M) {t : Submodule R M} (h : s ≤ t)
(ht : IsClosed (t : Set M)) : s.topologicalClosure ≤ t :=
closure_minimal h ht
#align submodule.topological_closure_minimal Submodule.topologicalClosure_minimal
theorem Submodule.topologicalClosure_mono {s : Submodule R M} {t : Submodule R M} (h : s ≤ t) :
s.topologicalClosure ≤ t.topologicalClosure :=
closure_mono h
#align submodule.topological_closure_mono Submodule.topologicalClosure_mono
/-- The topological closure of a closed submodule `s` is equal to `s`. -/
theorem IsClosed.submodule_topologicalClosure_eq {s : Submodule R M} (hs : IsClosed (s : Set M)) :
s.topologicalClosure = s :=
SetLike.ext' hs.closure_eq
#align is_closed.submodule_topological_closure_eq IsClosed.submodule_topologicalClosure_eq
/-- A subspace is dense iff its topological closure is the entire space. -/
theorem Submodule.dense_iff_topologicalClosure_eq_top {s : Submodule R M} :
Dense (s : Set M) ↔ s.topologicalClosure = ⊤ := by
rw [← SetLike.coe_set_eq, dense_iff_closure_eq]
simp
#align submodule.dense_iff_topological_closure_eq_top Submodule.dense_iff_topologicalClosure_eq_top
instance Submodule.topologicalClosure.completeSpace {M' : Type*} [AddCommMonoid M'] [Module R M']
[UniformSpace M'] [ContinuousAdd M'] [ContinuousConstSMul R M'] [CompleteSpace M']
(U : Submodule R M') : CompleteSpace U.topologicalClosure :=
isClosed_closure.completeSpace_coe
#align submodule.topological_closure.complete_space Submodule.topologicalClosure.completeSpace
/-- A maximal proper subspace of a topological module (i.e a `Submodule` satisfying `IsCoatom`)
is either closed or dense. -/
theorem Submodule.isClosed_or_dense_of_isCoatom (s : Submodule R M) (hs : IsCoatom s) :
IsClosed (s : Set M) ∨ Dense (s : Set M) := by
refine (hs.le_iff.mp s.le_topologicalClosure).symm.imp ?_ dense_iff_topologicalClosure_eq_top.mpr
exact fun h ↦ h ▸ isClosed_closure
#align submodule.is_closed_or_dense_of_is_coatom Submodule.isClosed_or_dense_of_isCoatom
end closure
section Pi
theorem LinearMap.continuous_on_pi {ι : Type*} {R : Type*} {M : Type*} [Finite ι] [Semiring R]
[TopologicalSpace R] [AddCommMonoid M] [Module R M] [TopologicalSpace M] [ContinuousAdd M]
[ContinuousSMul R M] (f : (ι → R) →ₗ[R] M) : Continuous f := by
cases nonempty_fintype ι
classical
-- for the proof, write `f` in the standard basis, and use that each coordinate is a continuous
-- function.
have : (f : (ι → R) → M) = fun x => ∑ i : ι, x i • f fun j => if i = j then 1 else 0 := by
ext x
exact f.pi_apply_eq_sum_univ x
rw [this]
refine continuous_finset_sum _ fun i _ => ?_
exact (continuous_apply i).smul continuous_const
#align linear_map.continuous_on_pi LinearMap.continuous_on_pi
end Pi
/-- Continuous linear maps between modules. We only put the type classes that are necessary for the
definition, although in applications `M` and `M₂` will be topological modules over the topological
ring `R`. -/
structure ContinuousLinearMap {R : Type*} {S : Type*} [Semiring R] [Semiring S] (σ : R →+* S)
(M : Type*) [TopologicalSpace M] [AddCommMonoid M] (M₂ : Type*) [TopologicalSpace M₂]
[AddCommMonoid M₂] [Module R M] [Module S M₂] extends M →ₛₗ[σ] M₂ where
cont : Continuous toFun := by continuity
#align continuous_linear_map ContinuousLinearMap
attribute [inherit_doc ContinuousLinearMap] ContinuousLinearMap.cont
@[inherit_doc]
notation:25 M " →SL[" σ "] " M₂ => ContinuousLinearMap σ M M₂
@[inherit_doc]
notation:25 M " →L[" R "] " M₂ => ContinuousLinearMap (RingHom.id R) M M₂
@[inherit_doc]
notation:25 M " →L⋆[" R "] " M₂ => ContinuousLinearMap (starRingEnd R) M M₂
/-- `ContinuousSemilinearMapClass F σ M M₂` asserts `F` is a type of bundled continuous
`σ`-semilinear maps `M → M₂`. See also `ContinuousLinearMapClass F R M M₂` for the case where
`σ` is the identity map on `R`. A map `f` between an `R`-module and an `S`-module over a ring
homomorphism `σ : R →+* S` is semilinear if it satisfies the two properties `f (x + y) = f x + f y`
and `f (c • x) = (σ c) • f x`. -/
class ContinuousSemilinearMapClass (F : Type*) {R S : outParam Type*} [Semiring R] [Semiring S]
(σ : outParam <| R →+* S) (M : outParam Type*) [TopologicalSpace M] [AddCommMonoid M]
(M₂ : outParam Type*) [TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M]
[Module S M₂] [FunLike F M M₂]
extends SemilinearMapClass F σ M M₂, ContinuousMapClass F M M₂ : Prop
#align continuous_semilinear_map_class ContinuousSemilinearMapClass
-- `σ`, `R` and `S` become metavariables, but they are all outparams so it's OK
-- Porting note(#12094): removed nolint; dangerous_instance linter not ported yet
-- attribute [nolint dangerous_instance] ContinuousSemilinearMapClass.toContinuousMapClass
/-- `ContinuousLinearMapClass F R M M₂` asserts `F` is a type of bundled continuous
`R`-linear maps `M → M₂`. This is an abbreviation for
`ContinuousSemilinearMapClass F (RingHom.id R) M M₂`. -/
abbrev ContinuousLinearMapClass (F : Type*) (R : outParam Type*) [Semiring R]
(M : outParam Type*) [TopologicalSpace M] [AddCommMonoid M] (M₂ : outParam Type*)
[TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M] [Module R M₂] [FunLike F M M₂] :=
ContinuousSemilinearMapClass F (RingHom.id R) M M₂
#align continuous_linear_map_class ContinuousLinearMapClass
/-- Continuous linear equivalences between modules. We only put the type classes that are necessary
for the definition, although in applications `M` and `M₂` will be topological modules over the
topological semiring `R`. -/
-- Porting note (#5171): linter not ported yet; was @[nolint has_nonempty_instance]
structure ContinuousLinearEquiv {R : Type*} {S : Type*} [Semiring R] [Semiring S] (σ : R →+* S)
{σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ] (M : Type*) [TopologicalSpace M]
[AddCommMonoid M] (M₂ : Type*) [TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M]
[Module S M₂] extends M ≃ₛₗ[σ] M₂ where
continuous_toFun : Continuous toFun := by continuity
continuous_invFun : Continuous invFun := by continuity
#align continuous_linear_equiv ContinuousLinearEquiv
attribute [inherit_doc ContinuousLinearEquiv] ContinuousLinearEquiv.continuous_toFun
ContinuousLinearEquiv.continuous_invFun
@[inherit_doc]
notation:50 M " ≃SL[" σ "] " M₂ => ContinuousLinearEquiv σ M M₂
@[inherit_doc]
notation:50 M " ≃L[" R "] " M₂ => ContinuousLinearEquiv (RingHom.id R) M M₂
@[inherit_doc]
notation:50 M " ≃L⋆[" R "] " M₂ => ContinuousLinearEquiv (starRingEnd R) M M₂
/-- `ContinuousSemilinearEquivClass F σ M M₂` asserts `F` is a type of bundled continuous
`σ`-semilinear equivs `M → M₂`. See also `ContinuousLinearEquivClass F R M M₂` for the case
where `σ` is the identity map on `R`. A map `f` between an `R`-module and an `S`-module over a ring
homomorphism `σ : R →+* S` is semilinear if it satisfies the two properties `f (x + y) = f x + f y`
and `f (c • x) = (σ c) • f x`. -/
class ContinuousSemilinearEquivClass (F : Type*) {R : outParam Type*} {S : outParam Type*}
[Semiring R] [Semiring S] (σ : outParam <| R →+* S) {σ' : outParam <| S →+* R}
[RingHomInvPair σ σ'] [RingHomInvPair σ' σ] (M : outParam Type*) [TopologicalSpace M]
[AddCommMonoid M] (M₂ : outParam Type*) [TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M]
[Module S M₂] [EquivLike F M M₂] extends SemilinearEquivClass F σ M M₂ : Prop where
map_continuous : ∀ f : F, Continuous f := by continuity
inv_continuous : ∀ f : F, Continuous (EquivLike.inv f) := by continuity
#align continuous_semilinear_equiv_class ContinuousSemilinearEquivClass
attribute [inherit_doc ContinuousSemilinearEquivClass]
ContinuousSemilinearEquivClass.map_continuous
ContinuousSemilinearEquivClass.inv_continuous
/-- `ContinuousLinearEquivClass F σ M M₂` asserts `F` is a type of bundled continuous
`R`-linear equivs `M → M₂`. This is an abbreviation for
`ContinuousSemilinearEquivClass F (RingHom.id R) M M₂`. -/
abbrev ContinuousLinearEquivClass (F : Type*) (R : outParam Type*) [Semiring R]
(M : outParam Type*) [TopologicalSpace M] [AddCommMonoid M] (M₂ : outParam Type*)
[TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M] [Module R M₂] [EquivLike F M M₂] :=
ContinuousSemilinearEquivClass F (RingHom.id R) M M₂
#align continuous_linear_equiv_class ContinuousLinearEquivClass
namespace ContinuousSemilinearEquivClass
variable (F : Type*) {R : Type*} {S : Type*} [Semiring R] [Semiring S] (σ : R →+* S)
{σ' : S →+* R} [RingHomInvPair σ σ'] [RingHomInvPair σ' σ]
(M : Type*) [TopologicalSpace M] [AddCommMonoid M]
(M₂ : Type*) [TopologicalSpace M₂] [AddCommMonoid M₂]
[Module R M] [Module S M₂]
-- `σ'` becomes a metavariable, but it's OK since it's an outparam
instance (priority := 100) continuousSemilinearMapClass [EquivLike F M M₂]
[s : ContinuousSemilinearEquivClass F σ M M₂] : ContinuousSemilinearMapClass F σ M M₂ :=
{ s with }
#align continuous_semilinear_equiv_class.continuous_semilinear_map_class ContinuousSemilinearEquivClass.continuousSemilinearMapClass
end ContinuousSemilinearEquivClass
section PointwiseLimits
variable {M₁ M₂ α R S : Type*} [TopologicalSpace M₂] [T2Space M₂] [Semiring R] [Semiring S]
[AddCommMonoid M₁] [AddCommMonoid M₂] [Module R M₁] [Module S M₂] [ContinuousConstSMul S M₂]
variable [ContinuousAdd M₂] {σ : R →+* S} {l : Filter α}
/-- Constructs a bundled linear map from a function and a proof that this function belongs to the
closure of the set of linear maps. -/
@[simps (config := .asFn)]
def linearMapOfMemClosureRangeCoe (f : M₁ → M₂)
(hf : f ∈ closure (Set.range ((↑) : (M₁ →ₛₗ[σ] M₂) → M₁ → M₂))) : M₁ →ₛₗ[σ] M₂ :=
{ addMonoidHomOfMemClosureRangeCoe f hf with
map_smul' := (isClosed_setOf_map_smul M₁ M₂ σ).closure_subset_iff.2
(Set.range_subset_iff.2 LinearMap.map_smulₛₗ) hf }
#align linear_map_of_mem_closure_range_coe linearMapOfMemClosureRangeCoe
#align linear_map_of_mem_closure_range_coe_apply linearMapOfMemClosureRangeCoe_apply
/-- Construct a bundled linear map from a pointwise limit of linear maps -/
@[simps! (config := .asFn)]
def linearMapOfTendsto (f : M₁ → M₂) (g : α → M₁ →ₛₗ[σ] M₂) [l.NeBot]
(h : Tendsto (fun a x => g a x) l (𝓝 f)) : M₁ →ₛₗ[σ] M₂ :=
linearMapOfMemClosureRangeCoe f <|
mem_closure_of_tendsto h <| eventually_of_forall fun _ => Set.mem_range_self _
#align linear_map_of_tendsto linearMapOfTendsto
#align linear_map_of_tendsto_apply linearMapOfTendsto_apply
variable (M₁ M₂ σ)
theorem LinearMap.isClosed_range_coe : IsClosed (Set.range ((↑) : (M₁ →ₛₗ[σ] M₂) → M₁ → M₂)) :=
isClosed_of_closure_subset fun f hf => ⟨linearMapOfMemClosureRangeCoe f hf, rfl⟩
#align linear_map.is_closed_range_coe LinearMap.isClosed_range_coe
end PointwiseLimits
namespace ContinuousLinearMap
section Semiring
/-!
### Properties that hold for non-necessarily commutative semirings.
-/
variable {R₁ : Type*} {R₂ : Type*} {R₃ : Type*} [Semiring R₁] [Semiring R₂] [Semiring R₃]
{σ₁₂ : R₁ →+* R₂} {σ₂₃ : R₂ →+* R₃} {σ₁₃ : R₁ →+* R₃} {M₁ : Type*} [TopologicalSpace M₁]
[AddCommMonoid M₁] {M'₁ : Type*} [TopologicalSpace M'₁] [AddCommMonoid M'₁] {M₂ : Type*}
[TopologicalSpace M₂] [AddCommMonoid M₂] {M₃ : Type*} [TopologicalSpace M₃] [AddCommMonoid M₃]
{M₄ : Type*} [TopologicalSpace M₄] [AddCommMonoid M₄] [Module R₁ M₁] [Module R₁ M'₁]
[Module R₂ M₂] [Module R₃ M₃]
attribute [coe] ContinuousLinearMap.toLinearMap
/-- Coerce continuous linear maps to linear maps. -/
instance LinearMap.coe : Coe (M₁ →SL[σ₁₂] M₂) (M₁ →ₛₗ[σ₁₂] M₂) := ⟨toLinearMap⟩
#align continuous_linear_map.linear_map.has_coe ContinuousLinearMap.LinearMap.coe
#noalign continuous_linear_map.to_linear_map_eq_coe
theorem coe_injective : Function.Injective ((↑) : (M₁ →SL[σ₁₂] M₂) → M₁ →ₛₗ[σ₁₂] M₂) := by
intro f g H
cases f
cases g
congr
#align continuous_linear_map.coe_injective ContinuousLinearMap.coe_injective
instance funLike : FunLike (M₁ →SL[σ₁₂] M₂) M₁ M₂ where
coe f := f.toLinearMap
coe_injective' _ _ h := coe_injective (DFunLike.coe_injective h)
instance continuousSemilinearMapClass :
ContinuousSemilinearMapClass (M₁ →SL[σ₁₂] M₂) σ₁₂ M₁ M₂ where
map_add f := map_add f.toLinearMap
map_continuous f := f.2
map_smulₛₗ f := f.toLinearMap.map_smul'
#align continuous_linear_map.continuous_semilinear_map_class ContinuousLinearMap.continuousSemilinearMapClass
-- see Note [function coercion]
/-- Coerce continuous linear maps to functions. -/
--instance toFun' : CoeFun (M₁ →SL[σ₁₂] M₂) fun _ => M₁ → M₂ := ⟨DFunLike.coe⟩
-- porting note (#10618): was `simp`, now `simp only` proves it
theorem coe_mk (f : M₁ →ₛₗ[σ₁₂] M₂) (h) : (mk f h : M₁ →ₛₗ[σ₁₂] M₂) = f :=
rfl
#align continuous_linear_map.coe_mk ContinuousLinearMap.coe_mk
@[simp]
theorem coe_mk' (f : M₁ →ₛₗ[σ₁₂] M₂) (h) : (mk f h : M₁ → M₂) = f :=
rfl
#align continuous_linear_map.coe_mk' ContinuousLinearMap.coe_mk'
@[continuity]
protected theorem continuous (f : M₁ →SL[σ₁₂] M₂) : Continuous f :=
f.2
#align continuous_linear_map.continuous ContinuousLinearMap.continuous
protected theorem uniformContinuous {E₁ E₂ : Type*} [UniformSpace E₁] [UniformSpace E₂]
[AddCommGroup E₁] [AddCommGroup E₂] [Module R₁ E₁] [Module R₂ E₂] [UniformAddGroup E₁]
[UniformAddGroup E₂] (f : E₁ →SL[σ₁₂] E₂) : UniformContinuous f :=
uniformContinuous_addMonoidHom_of_continuous f.continuous
#align continuous_linear_map.uniform_continuous ContinuousLinearMap.uniformContinuous
@[simp, norm_cast]
theorem coe_inj {f g : M₁ →SL[σ₁₂] M₂} : (f : M₁ →ₛₗ[σ₁₂] M₂) = g ↔ f = g :=
coe_injective.eq_iff
#align continuous_linear_map.coe_inj ContinuousLinearMap.coe_inj
theorem coeFn_injective : @Function.Injective (M₁ →SL[σ₁₂] M₂) (M₁ → M₂) (↑) :=
DFunLike.coe_injective
#align continuous_linear_map.coe_fn_injective ContinuousLinearMap.coeFn_injective
/-- See Note [custom simps projection]. We need to specify this projection explicitly in this case,
because it is a composition of multiple projections. -/
def Simps.apply (h : M₁ →SL[σ₁₂] M₂) : M₁ → M₂ :=
h
#align continuous_linear_map.simps.apply ContinuousLinearMap.Simps.apply
/-- See Note [custom simps projection]. -/
def Simps.coe (h : M₁ →SL[σ₁₂] M₂) : M₁ →ₛₗ[σ₁₂] M₂ :=
h
#align continuous_linear_map.simps.coe ContinuousLinearMap.Simps.coe
initialize_simps_projections ContinuousLinearMap (toLinearMap_toFun → apply, toLinearMap → coe)
@[ext]
theorem ext {f g : M₁ →SL[σ₁₂] M₂} (h : ∀ x, f x = g x) : f = g :=
DFunLike.ext f g h
#align continuous_linear_map.ext ContinuousLinearMap.ext
theorem ext_iff {f g : M₁ →SL[σ₁₂] M₂} : f = g ↔ ∀ x, f x = g x :=
DFunLike.ext_iff
#align continuous_linear_map.ext_iff ContinuousLinearMap.ext_iff
/-- Copy of a `ContinuousLinearMap` with a new `toFun` equal to the old one. Useful to fix
definitional equalities. -/
protected def copy (f : M₁ →SL[σ₁₂] M₂) (f' : M₁ → M₂) (h : f' = ⇑f) : M₁ →SL[σ₁₂] M₂ where
toLinearMap := f.toLinearMap.copy f' h
cont := show Continuous f' from h.symm ▸ f.continuous
#align continuous_linear_map.copy ContinuousLinearMap.copy
@[simp]
theorem coe_copy (f : M₁ →SL[σ₁₂] M₂) (f' : M₁ → M₂) (h : f' = ⇑f) : ⇑(f.copy f' h) = f' :=
rfl
#align continuous_linear_map.coe_copy ContinuousLinearMap.coe_copy
theorem copy_eq (f : M₁ →SL[σ₁₂] M₂) (f' : M₁ → M₂) (h : f' = ⇑f) : f.copy f' h = f :=
DFunLike.ext' h
#align continuous_linear_map.copy_eq ContinuousLinearMap.copy_eq
-- make some straightforward lemmas available to `simp`.
protected theorem map_zero (f : M₁ →SL[σ₁₂] M₂) : f (0 : M₁) = 0 :=
map_zero f
#align continuous_linear_map.map_zero ContinuousLinearMap.map_zero
protected theorem map_add (f : M₁ →SL[σ₁₂] M₂) (x y : M₁) : f (x + y) = f x + f y :=
map_add f x y
#align continuous_linear_map.map_add ContinuousLinearMap.map_add
-- @[simp] -- Porting note (#10618): simp can prove this
protected theorem map_smulₛₗ (f : M₁ →SL[σ₁₂] M₂) (c : R₁) (x : M₁) : f (c • x) = σ₁₂ c • f x :=
(toLinearMap _).map_smulₛₗ _ _
#align continuous_linear_map.map_smulₛₗ ContinuousLinearMap.map_smulₛₗ
-- @[simp] -- Porting note (#10618): simp can prove this
protected theorem map_smul [Module R₁ M₂] (f : M₁ →L[R₁] M₂) (c : R₁) (x : M₁) :
f (c • x) = c • f x := by simp only [RingHom.id_apply, ContinuousLinearMap.map_smulₛₗ]
#align continuous_linear_map.map_smul ContinuousLinearMap.map_smul
@[simp]
theorem map_smul_of_tower {R S : Type*} [Semiring S] [SMul R M₁] [Module S M₁] [SMul R M₂]
[Module S M₂] [LinearMap.CompatibleSMul M₁ M₂ R S] (f : M₁ →L[S] M₂) (c : R) (x : M₁) :
f (c • x) = c • f x :=
LinearMap.CompatibleSMul.map_smul (f : M₁ →ₗ[S] M₂) c x
#align continuous_linear_map.map_smul_of_tower ContinuousLinearMap.map_smul_of_tower
@[deprecated _root_.map_sum]
protected theorem map_sum {ι : Type*} (f : M₁ →SL[σ₁₂] M₂) (s : Finset ι) (g : ι → M₁) :
f (∑ i ∈ s, g i) = ∑ i ∈ s, f (g i) :=
map_sum ..
#align continuous_linear_map.map_sum ContinuousLinearMap.map_sum
@[simp, norm_cast]
theorem coe_coe (f : M₁ →SL[σ₁₂] M₂) : ⇑(f : M₁ →ₛₗ[σ₁₂] M₂) = f :=
rfl
#align continuous_linear_map.coe_coe ContinuousLinearMap.coe_coe
@[ext]
theorem ext_ring [TopologicalSpace R₁] {f g : R₁ →L[R₁] M₁} (h : f 1 = g 1) : f = g :=
coe_inj.1 <| LinearMap.ext_ring h
#align continuous_linear_map.ext_ring ContinuousLinearMap.ext_ring
theorem ext_ring_iff [TopologicalSpace R₁] {f g : R₁ →L[R₁] M₁} : f = g ↔ f 1 = g 1 :=
⟨fun h => h ▸ rfl, ext_ring⟩
#align continuous_linear_map.ext_ring_iff ContinuousLinearMap.ext_ring_iff
/-- If two continuous linear maps are equal on a set `s`, then they are equal on the closure
of the `Submodule.span` of this set. -/
theorem eqOn_closure_span [T2Space M₂] {s : Set M₁} {f g : M₁ →SL[σ₁₂] M₂} (h : Set.EqOn f g s) :
Set.EqOn f g (closure (Submodule.span R₁ s : Set M₁)) :=
(LinearMap.eqOn_span' h).closure f.continuous g.continuous
#align continuous_linear_map.eq_on_closure_span ContinuousLinearMap.eqOn_closure_span
/-- If the submodule generated by a set `s` is dense in the ambient module, then two continuous
linear maps equal on `s` are equal. -/
theorem ext_on [T2Space M₂] {s : Set M₁} (hs : Dense (Submodule.span R₁ s : Set M₁))
{f g : M₁ →SL[σ₁₂] M₂} (h : Set.EqOn f g s) : f = g :=
ext fun x => eqOn_closure_span h (hs x)
#align continuous_linear_map.ext_on ContinuousLinearMap.ext_on
/-- Under a continuous linear map, the image of the `TopologicalClosure` of a submodule is
contained in the `TopologicalClosure` of its image. -/
theorem _root_.Submodule.topologicalClosure_map [RingHomSurjective σ₁₂] [TopologicalSpace R₁]
[TopologicalSpace R₂] [ContinuousSMul R₁ M₁] [ContinuousAdd M₁] [ContinuousSMul R₂ M₂]
[ContinuousAdd M₂] (f : M₁ →SL[σ₁₂] M₂) (s : Submodule R₁ M₁) :
s.topologicalClosure.map (f : M₁ →ₛₗ[σ₁₂] M₂) ≤
(s.map (f : M₁ →ₛₗ[σ₁₂] M₂)).topologicalClosure :=
image_closure_subset_closure_image f.continuous
#align submodule.topological_closure_map Submodule.topologicalClosure_map
/-- Under a dense continuous linear map, a submodule whose `TopologicalClosure` is `⊤` is sent to
another such submodule. That is, the image of a dense set under a map with dense range is dense.
-/
theorem _root_.DenseRange.topologicalClosure_map_submodule [RingHomSurjective σ₁₂]
[TopologicalSpace R₁] [TopologicalSpace R₂] [ContinuousSMul R₁ M₁] [ContinuousAdd M₁]
[ContinuousSMul R₂ M₂] [ContinuousAdd M₂] {f : M₁ →SL[σ₁₂] M₂} (hf' : DenseRange f)
{s : Submodule R₁ M₁} (hs : s.topologicalClosure = ⊤) :
(s.map (f : M₁ →ₛₗ[σ₁₂] M₂)).topologicalClosure = ⊤ := by
rw [SetLike.ext'_iff] at hs ⊢
simp only [Submodule.topologicalClosure_coe, Submodule.top_coe, ← dense_iff_closure_eq] at hs ⊢
exact hf'.dense_image f.continuous hs
#align dense_range.topological_closure_map_submodule DenseRange.topologicalClosure_map_submodule
section SMulMonoid
variable {S₂ T₂ : Type*} [Monoid S₂] [Monoid T₂]
variable [DistribMulAction S₂ M₂] [SMulCommClass R₂ S₂ M₂] [ContinuousConstSMul S₂ M₂]
variable [DistribMulAction T₂ M₂] [SMulCommClass R₂ T₂ M₂] [ContinuousConstSMul T₂ M₂]
instance instSMul : SMul S₂ (M₁ →SL[σ₁₂] M₂) where
smul c f := ⟨c • (f : M₁ →ₛₗ[σ₁₂] M₂), (f.2.const_smul _ : Continuous fun x => c • f x)⟩
instance mulAction : MulAction S₂ (M₁ →SL[σ₁₂] M₂) where
one_smul _f := ext fun _x => one_smul _ _
mul_smul _a _b _f := ext fun _x => mul_smul _ _ _
#align continuous_linear_map.mul_action ContinuousLinearMap.mulAction
theorem smul_apply (c : S₂) (f : M₁ →SL[σ₁₂] M₂) (x : M₁) : (c • f) x = c • f x :=
rfl
#align continuous_linear_map.smul_apply ContinuousLinearMap.smul_apply
@[simp, norm_cast]
theorem coe_smul (c : S₂) (f : M₁ →SL[σ₁₂] M₂) :
↑(c • f) = c • (f : M₁ →ₛₗ[σ₁₂] M₂) :=
rfl
#align continuous_linear_map.coe_smul ContinuousLinearMap.coe_smul
@[simp, norm_cast]
theorem coe_smul' (c : S₂) (f : M₁ →SL[σ₁₂] M₂) :
↑(c • f) = c • (f : M₁ → M₂) :=
rfl
#align continuous_linear_map.coe_smul' ContinuousLinearMap.coe_smul'
instance isScalarTower [SMul S₂ T₂] [IsScalarTower S₂ T₂ M₂] :
IsScalarTower S₂ T₂ (M₁ →SL[σ₁₂] M₂) :=
⟨fun a b f => ext fun x => smul_assoc a b (f x)⟩
#align continuous_linear_map.is_scalar_tower ContinuousLinearMap.isScalarTower
instance smulCommClass [SMulCommClass S₂ T₂ M₂] : SMulCommClass S₂ T₂ (M₁ →SL[σ₁₂] M₂) :=
⟨fun a b f => ext fun x => smul_comm a b (f x)⟩
#align continuous_linear_map.smul_comm_class ContinuousLinearMap.smulCommClass
end SMulMonoid
/-- The continuous map that is constantly zero. -/
instance zero : Zero (M₁ →SL[σ₁₂] M₂) :=
⟨⟨0, continuous_zero⟩⟩
#align continuous_linear_map.has_zero ContinuousLinearMap.zero
instance inhabited : Inhabited (M₁ →SL[σ₁₂] M₂) :=
⟨0⟩
#align continuous_linear_map.inhabited ContinuousLinearMap.inhabited
@[simp]
theorem default_def : (default : M₁ →SL[σ₁₂] M₂) = 0 :=
rfl
#align continuous_linear_map.default_def ContinuousLinearMap.default_def
@[simp]
theorem zero_apply (x : M₁) : (0 : M₁ →SL[σ₁₂] M₂) x = 0 :=
rfl
#align continuous_linear_map.zero_apply ContinuousLinearMap.zero_apply
@[simp, norm_cast]
theorem coe_zero : ((0 : M₁ →SL[σ₁₂] M₂) : M₁ →ₛₗ[σ₁₂] M₂) = 0 :=
rfl
#align continuous_linear_map.coe_zero ContinuousLinearMap.coe_zero
/- no simp attribute on the next line as simp does not always simplify `0 x` to `0`
when `0` is the zero function, while it does for the zero continuous linear map,
and this is the most important property we care about. -/
@[norm_cast]
theorem coe_zero' : ⇑(0 : M₁ →SL[σ₁₂] M₂) = 0 :=
rfl
#align continuous_linear_map.coe_zero' ContinuousLinearMap.coe_zero'
instance uniqueOfLeft [Subsingleton M₁] : Unique (M₁ →SL[σ₁₂] M₂) :=
coe_injective.unique
#align continuous_linear_map.unique_of_left ContinuousLinearMap.uniqueOfLeft
instance uniqueOfRight [Subsingleton M₂] : Unique (M₁ →SL[σ₁₂] M₂) :=
coe_injective.unique
#align continuous_linear_map.unique_of_right ContinuousLinearMap.uniqueOfRight
theorem exists_ne_zero {f : M₁ →SL[σ₁₂] M₂} (hf : f ≠ 0) : ∃ x, f x ≠ 0 := by
by_contra! h
exact hf (ContinuousLinearMap.ext h)
#align continuous_linear_map.exists_ne_zero ContinuousLinearMap.exists_ne_zero
section
variable (R₁ M₁)
/-- the identity map as a continuous linear map. -/
def id : M₁ →L[R₁] M₁ :=
⟨LinearMap.id, continuous_id⟩
#align continuous_linear_map.id ContinuousLinearMap.id
end
instance one : One (M₁ →L[R₁] M₁) :=
⟨id R₁ M₁⟩
#align continuous_linear_map.has_one ContinuousLinearMap.one
theorem one_def : (1 : M₁ →L[R₁] M₁) = id R₁ M₁ :=
rfl
#align continuous_linear_map.one_def ContinuousLinearMap.one_def
theorem id_apply (x : M₁) : id R₁ M₁ x = x :=
rfl
#align continuous_linear_map.id_apply ContinuousLinearMap.id_apply
@[simp, norm_cast]
theorem coe_id : (id R₁ M₁ : M₁ →ₗ[R₁] M₁) = LinearMap.id :=
rfl
#align continuous_linear_map.coe_id ContinuousLinearMap.coe_id
@[simp, norm_cast]
theorem coe_id' : ⇑(id R₁ M₁) = _root_.id :=
rfl
#align continuous_linear_map.coe_id' ContinuousLinearMap.coe_id'
@[simp, norm_cast]
theorem coe_eq_id {f : M₁ →L[R₁] M₁} : (f : M₁ →ₗ[R₁] M₁) = LinearMap.id ↔ f = id _ _ := by
rw [← coe_id, coe_inj]
#align continuous_linear_map.coe_eq_id ContinuousLinearMap.coe_eq_id
@[simp]
theorem one_apply (x : M₁) : (1 : M₁ →L[R₁] M₁) x = x :=
rfl
#align continuous_linear_map.one_apply ContinuousLinearMap.one_apply
instance [Nontrivial M₁] : Nontrivial (M₁ →L[R₁] M₁) :=
⟨0, 1, fun e ↦
have ⟨x, hx⟩ := exists_ne (0 : M₁); hx (by simpa using DFunLike.congr_fun e.symm x)⟩
section Add
variable [ContinuousAdd M₂]
instance add : Add (M₁ →SL[σ₁₂] M₂) :=
⟨fun f g => ⟨f + g, f.2.add g.2⟩⟩
#align continuous_linear_map.has_add ContinuousLinearMap.add
@[simp]
theorem add_apply (f g : M₁ →SL[σ₁₂] M₂) (x : M₁) : (f + g) x = f x + g x :=
rfl
#align continuous_linear_map.add_apply ContinuousLinearMap.add_apply
@[simp, norm_cast]
theorem coe_add (f g : M₁ →SL[σ₁₂] M₂) : (↑(f + g) : M₁ →ₛₗ[σ₁₂] M₂) = f + g :=
rfl
#align continuous_linear_map.coe_add ContinuousLinearMap.coe_add
@[norm_cast]
theorem coe_add' (f g : M₁ →SL[σ₁₂] M₂) : ⇑(f + g) = f + g :=
rfl
#align continuous_linear_map.coe_add' ContinuousLinearMap.coe_add'
instance addCommMonoid : AddCommMonoid (M₁ →SL[σ₁₂] M₂) where
zero_add := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
add_zero := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
add_comm := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
add_assoc := by
intros
ext
apply_rules [zero_add, add_assoc, add_zero, add_left_neg, add_comm]
nsmul := (· • ·)
nsmul_zero f := by
ext
simp
nsmul_succ n f := by
ext
simp [add_smul]
#align continuous_linear_map.add_comm_monoid ContinuousLinearMap.addCommMonoid
@[simp, norm_cast]
theorem coe_sum {ι : Type*} (t : Finset ι) (f : ι → M₁ →SL[σ₁₂] M₂) :
↑(∑ d ∈ t, f d) = (∑ d ∈ t, f d : M₁ →ₛₗ[σ₁₂] M₂) :=
map_sum (AddMonoidHom.mk ⟨((↑) : (M₁ →SL[σ₁₂] M₂) → M₁ →ₛₗ[σ₁₂] M₂), rfl⟩ fun _ _ => rfl) _ _
#align continuous_linear_map.coe_sum ContinuousLinearMap.coe_sum
@[simp, norm_cast]
theorem coe_sum' {ι : Type*} (t : Finset ι) (f : ι → M₁ →SL[σ₁₂] M₂) :
⇑(∑ d ∈ t, f d) = ∑ d ∈ t, ⇑(f d) := by simp only [← coe_coe, coe_sum, LinearMap.coeFn_sum]
#align continuous_linear_map.coe_sum' ContinuousLinearMap.coe_sum'
theorem sum_apply {ι : Type*} (t : Finset ι) (f : ι → M₁ →SL[σ₁₂] M₂) (b : M₁) :
(∑ d ∈ t, f d) b = ∑ d ∈ t, f d b := by simp only [coe_sum', Finset.sum_apply]
#align continuous_linear_map.sum_apply ContinuousLinearMap.sum_apply
end Add
variable [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃]
/-- Composition of bounded linear maps. -/
def comp (g : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) : M₁ →SL[σ₁₃] M₃ :=
⟨(g : M₂ →ₛₗ[σ₂₃] M₃).comp (f : M₁ →ₛₗ[σ₁₂] M₂), g.2.comp f.2⟩
#align continuous_linear_map.comp ContinuousLinearMap.comp
@[inherit_doc comp]
infixr:80 " ∘L " =>
@ContinuousLinearMap.comp _ _ _ _ _ _ (RingHom.id _) (RingHom.id _) (RingHom.id _) _ _ _ _ _ _ _ _
_ _ _ _ RingHomCompTriple.ids
@[simp, norm_cast]
theorem coe_comp (h : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) :
(h.comp f : M₁ →ₛₗ[σ₁₃] M₃) = (h : M₂ →ₛₗ[σ₂₃] M₃).comp (f : M₁ →ₛₗ[σ₁₂] M₂) :=
rfl
#align continuous_linear_map.coe_comp ContinuousLinearMap.coe_comp
@[simp, norm_cast]
theorem coe_comp' (h : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) : ⇑(h.comp f) = h ∘ f :=
rfl
#align continuous_linear_map.coe_comp' ContinuousLinearMap.coe_comp'
theorem comp_apply (g : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) (x : M₁) : (g.comp f) x = g (f x) :=
rfl
#align continuous_linear_map.comp_apply ContinuousLinearMap.comp_apply
@[simp]
theorem comp_id (f : M₁ →SL[σ₁₂] M₂) : f.comp (id R₁ M₁) = f :=
ext fun _x => rfl
#align continuous_linear_map.comp_id ContinuousLinearMap.comp_id
@[simp]
theorem id_comp (f : M₁ →SL[σ₁₂] M₂) : (id R₂ M₂).comp f = f :=
ext fun _x => rfl
#align continuous_linear_map.id_comp ContinuousLinearMap.id_comp
@[simp]
theorem comp_zero (g : M₂ →SL[σ₂₃] M₃) : g.comp (0 : M₁ →SL[σ₁₂] M₂) = 0 := by
ext
simp
#align continuous_linear_map.comp_zero ContinuousLinearMap.comp_zero
@[simp]
theorem zero_comp (f : M₁ →SL[σ₁₂] M₂) : (0 : M₂ →SL[σ₂₃] M₃).comp f = 0 := by
ext
simp
#align continuous_linear_map.zero_comp ContinuousLinearMap.zero_comp
@[simp]
theorem comp_add [ContinuousAdd M₂] [ContinuousAdd M₃] (g : M₂ →SL[σ₂₃] M₃)
(f₁ f₂ : M₁ →SL[σ₁₂] M₂) : g.comp (f₁ + f₂) = g.comp f₁ + g.comp f₂ := by
ext
simp
#align continuous_linear_map.comp_add ContinuousLinearMap.comp_add
@[simp]
theorem add_comp [ContinuousAdd M₃] (g₁ g₂ : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) :
(g₁ + g₂).comp f = g₁.comp f + g₂.comp f := by
ext
simp
#align continuous_linear_map.add_comp ContinuousLinearMap.add_comp
theorem comp_assoc {R₄ : Type*} [Semiring R₄] [Module R₄ M₄] {σ₁₄ : R₁ →+* R₄} {σ₂₄ : R₂ →+* R₄}
{σ₃₄ : R₃ →+* R₄} [RingHomCompTriple σ₁₃ σ₃₄ σ₁₄] [RingHomCompTriple σ₂₃ σ₃₄ σ₂₄]
[RingHomCompTriple σ₁₂ σ₂₄ σ₁₄] (h : M₃ →SL[σ₃₄] M₄) (g : M₂ →SL[σ₂₃] M₃) (f : M₁ →SL[σ₁₂] M₂) :
(h.comp g).comp f = h.comp (g.comp f) :=
rfl
#align continuous_linear_map.comp_assoc ContinuousLinearMap.comp_assoc
instance instMul : Mul (M₁ →L[R₁] M₁) :=
⟨comp⟩
#align continuous_linear_map.has_mul ContinuousLinearMap.instMul
theorem mul_def (f g : M₁ →L[R₁] M₁) : f * g = f.comp g :=
rfl
#align continuous_linear_map.mul_def ContinuousLinearMap.mul_def
@[simp]
theorem coe_mul (f g : M₁ →L[R₁] M₁) : ⇑(f * g) = f ∘ g :=
rfl
#align continuous_linear_map.coe_mul ContinuousLinearMap.coe_mul
theorem mul_apply (f g : M₁ →L[R₁] M₁) (x : M₁) : (f * g) x = f (g x) :=
rfl
#align continuous_linear_map.mul_apply ContinuousLinearMap.mul_apply
instance monoidWithZero : MonoidWithZero (M₁ →L[R₁] M₁) where
mul_zero f := ext fun _ => map_zero f
zero_mul _ := ext fun _ => rfl
mul_one _ := ext fun _ => rfl
one_mul _ := ext fun _ => rfl
mul_assoc _ _ _ := ext fun _ => rfl
#align continuous_linear_map.monoid_with_zero ContinuousLinearMap.monoidWithZero
theorem coe_pow (f : M₁ →L[R₁] M₁) (n : ℕ) : ⇑(f ^ n) = f^[n] :=
hom_coe_pow _ rfl (fun _ _ ↦ rfl) _ _
instance instNatCast [ContinuousAdd M₁] : NatCast (M₁ →L[R₁] M₁) where
natCast n := n • (1 : M₁ →L[R₁] M₁)
instance semiring [ContinuousAdd M₁] : Semiring (M₁ →L[R₁] M₁) where
__ := ContinuousLinearMap.monoidWithZero
__ := ContinuousLinearMap.addCommMonoid
left_distrib f g h := ext fun x => map_add f (g x) (h x)
right_distrib _ _ _ := ext fun _ => LinearMap.add_apply _ _ _
toNatCast := instNatCast
natCast_zero := zero_smul ℕ (1 : M₁ →L[R₁] M₁)
natCast_succ n := AddMonoid.nsmul_succ n (1 : M₁ →L[R₁] M₁)
#align continuous_linear_map.semiring ContinuousLinearMap.semiring
/-- `ContinuousLinearMap.toLinearMap` as a `RingHom`. -/
@[simps]
def toLinearMapRingHom [ContinuousAdd M₁] : (M₁ →L[R₁] M₁) →+* M₁ →ₗ[R₁] M₁ where
toFun := toLinearMap
map_zero' := rfl
map_one' := rfl
map_add' _ _ := rfl
map_mul' _ _ := rfl
#align continuous_linear_map.to_linear_map_ring_hom ContinuousLinearMap.toLinearMapRingHom
#align continuous_linear_map.to_linear_map_ring_hom_apply ContinuousLinearMap.toLinearMapRingHom_apply
@[simp]
theorem natCast_apply [ContinuousAdd M₁] (n : ℕ) (m : M₁) : (↑n : M₁ →L[R₁] M₁) m = n • m :=
rfl
@[simp]
theorem ofNat_apply [ContinuousAdd M₁] (n : ℕ) [n.AtLeastTwo] (m : M₁) :
((no_index (OfNat.ofNat n) : M₁ →L[R₁] M₁)) m = OfNat.ofNat n • m :=
rfl
section ApplyAction
variable [ContinuousAdd M₁]
/-- The tautological action by `M₁ →L[R₁] M₁` on `M`.
This generalizes `Function.End.applyMulAction`. -/
instance applyModule : Module (M₁ →L[R₁] M₁) M₁ :=
Module.compHom _ toLinearMapRingHom
#align continuous_linear_map.apply_module ContinuousLinearMap.applyModule
@[simp]
protected theorem smul_def (f : M₁ →L[R₁] M₁) (a : M₁) : f • a = f a :=
rfl
#align continuous_linear_map.smul_def ContinuousLinearMap.smul_def
/-- `ContinuousLinearMap.applyModule` is faithful. -/
instance applyFaithfulSMul : FaithfulSMul (M₁ →L[R₁] M₁) M₁ :=
⟨fun {_ _} => ContinuousLinearMap.ext⟩
#align continuous_linear_map.apply_has_faithful_smul ContinuousLinearMap.applyFaithfulSMul
instance applySMulCommClass : SMulCommClass R₁ (M₁ →L[R₁] M₁) M₁ where
smul_comm r e m := (e.map_smul r m).symm
#align continuous_linear_map.apply_smul_comm_class ContinuousLinearMap.applySMulCommClass
instance applySMulCommClass' : SMulCommClass (M₁ →L[R₁] M₁) R₁ M₁ where
smul_comm := ContinuousLinearMap.map_smul
#align continuous_linear_map.apply_smul_comm_class' ContinuousLinearMap.applySMulCommClass'
instance continuousConstSMul_apply : ContinuousConstSMul (M₁ →L[R₁] M₁) M₁ :=
⟨ContinuousLinearMap.continuous⟩
#align continuous_linear_map.has_continuous_const_smul ContinuousLinearMap.continuousConstSMul_apply
end ApplyAction
/-- The cartesian product of two bounded linear maps, as a bounded linear map. -/
protected def prod [Module R₁ M₂] [Module R₁ M₃] (f₁ : M₁ →L[R₁] M₂) (f₂ : M₁ →L[R₁] M₃) :
M₁ →L[R₁] M₂ × M₃ :=
⟨(f₁ : M₁ →ₗ[R₁] M₂).prod f₂, f₁.2.prod_mk f₂.2⟩
#align continuous_linear_map.prod ContinuousLinearMap.prod
@[simp, norm_cast]
theorem coe_prod [Module R₁ M₂] [Module R₁ M₃] (f₁ : M₁ →L[R₁] M₂) (f₂ : M₁ →L[R₁] M₃) :
(f₁.prod f₂ : M₁ →ₗ[R₁] M₂ × M₃) = LinearMap.prod f₁ f₂ :=
rfl
#align continuous_linear_map.coe_prod ContinuousLinearMap.coe_prod
@[simp, norm_cast]
theorem prod_apply [Module R₁ M₂] [Module R₁ M₃] (f₁ : M₁ →L[R₁] M₂) (f₂ : M₁ →L[R₁] M₃) (x : M₁) :
f₁.prod f₂ x = (f₁ x, f₂ x) :=
rfl
#align continuous_linear_map.prod_apply ContinuousLinearMap.prod_apply
section
variable (R₁ M₁ M₂)
/-- The left injection into a product is a continuous linear map. -/
def inl [Module R₁ M₂] : M₁ →L[R₁] M₁ × M₂ :=
(id R₁ M₁).prod 0
#align continuous_linear_map.inl ContinuousLinearMap.inl
/-- The right injection into a product is a continuous linear map. -/
def inr [Module R₁ M₂] : M₂ →L[R₁] M₁ × M₂ :=
(0 : M₂ →L[R₁] M₁).prod (id R₁ M₂)
#align continuous_linear_map.inr ContinuousLinearMap.inr
end
variable {F : Type*}
@[simp]
theorem inl_apply [Module R₁ M₂] (x : M₁) : inl R₁ M₁ M₂ x = (x, 0) :=
rfl
#align continuous_linear_map.inl_apply ContinuousLinearMap.inl_apply
@[simp]
theorem inr_apply [Module R₁ M₂] (x : M₂) : inr R₁ M₁ M₂ x = (0, x) :=
rfl
#align continuous_linear_map.inr_apply ContinuousLinearMap.inr_apply
@[simp, norm_cast]
theorem coe_inl [Module R₁ M₂] : (inl R₁ M₁ M₂ : M₁ →ₗ[R₁] M₁ × M₂) = LinearMap.inl R₁ M₁ M₂ :=
rfl
#align continuous_linear_map.coe_inl ContinuousLinearMap.coe_inl
@[simp, norm_cast]
theorem coe_inr [Module R₁ M₂] : (inr R₁ M₁ M₂ : M₂ →ₗ[R₁] M₁ × M₂) = LinearMap.inr R₁ M₁ M₂ :=
rfl
#align continuous_linear_map.coe_inr ContinuousLinearMap.coe_inr
theorem isClosed_ker [T1Space M₂] [FunLike F M₁ M₂] [ContinuousSemilinearMapClass F σ₁₂ M₁ M₂]
(f : F) :
IsClosed (ker f : Set M₁) :=
continuous_iff_isClosed.1 (map_continuous f) _ isClosed_singleton
#align continuous_linear_map.is_closed_ker ContinuousLinearMap.isClosed_ker
theorem isComplete_ker {M' : Type*} [UniformSpace M'] [CompleteSpace M'] [AddCommMonoid M']
[Module R₁ M'] [T1Space M₂] [FunLike F M' M₂] [ContinuousSemilinearMapClass F σ₁₂ M' M₂]
(f : F) :
IsComplete (ker f : Set M') :=
(isClosed_ker f).isComplete
#align continuous_linear_map.is_complete_ker ContinuousLinearMap.isComplete_ker
instance completeSpace_ker {M' : Type*} [UniformSpace M'] [CompleteSpace M']
[AddCommMonoid M'] [Module R₁ M'] [T1Space M₂]
[FunLike F M' M₂] [ContinuousSemilinearMapClass F σ₁₂ M' M₂]
(f : F) : CompleteSpace (ker f) :=
(isComplete_ker f).completeSpace_coe
#align continuous_linear_map.complete_space_ker ContinuousLinearMap.completeSpace_ker
instance completeSpace_eqLocus {M' : Type*} [UniformSpace M'] [CompleteSpace M']
[AddCommMonoid M'] [Module R₁ M'] [T2Space M₂]
[FunLike F M' M₂] [ContinuousSemilinearMapClass F σ₁₂ M' M₂]
(f g : F) : CompleteSpace (LinearMap.eqLocus f g) :=
IsClosed.completeSpace_coe <| isClosed_eq (map_continuous f) (map_continuous g)
@[simp]
theorem ker_prod [Module R₁ M₂] [Module R₁ M₃] (f : M₁ →L[R₁] M₂) (g : M₁ →L[R₁] M₃) :
ker (f.prod g) = ker f ⊓ ker g :=
LinearMap.ker_prod (f : M₁ →ₗ[R₁] M₂) (g : M₁ →ₗ[R₁] M₃)
#align continuous_linear_map.ker_prod ContinuousLinearMap.ker_prod
/-- Restrict codomain of a continuous linear map. -/
def codRestrict (f : M₁ →SL[σ₁₂] M₂) (p : Submodule R₂ M₂) (h : ∀ x, f x ∈ p) :
M₁ →SL[σ₁₂] p where
cont := f.continuous.subtype_mk _
toLinearMap := (f : M₁ →ₛₗ[σ₁₂] M₂).codRestrict p h
#align continuous_linear_map.cod_restrict ContinuousLinearMap.codRestrict
@[norm_cast]
theorem coe_codRestrict (f : M₁ →SL[σ₁₂] M₂) (p : Submodule R₂ M₂) (h : ∀ x, f x ∈ p) :
(f.codRestrict p h : M₁ →ₛₗ[σ₁₂] p) = (f : M₁ →ₛₗ[σ₁₂] M₂).codRestrict p h :=
rfl
#align continuous_linear_map.coe_cod_restrict ContinuousLinearMap.coe_codRestrict
@[simp]
theorem coe_codRestrict_apply (f : M₁ →SL[σ₁₂] M₂) (p : Submodule R₂ M₂) (h : ∀ x, f x ∈ p) (x) :
(f.codRestrict p h x : M₂) = f x :=
rfl
#align continuous_linear_map.coe_cod_restrict_apply ContinuousLinearMap.coe_codRestrict_apply
@[simp]
theorem ker_codRestrict (f : M₁ →SL[σ₁₂] M₂) (p : Submodule R₂ M₂) (h : ∀ x, f x ∈ p) :
ker (f.codRestrict p h) = ker f :=
(f : M₁ →ₛₗ[σ₁₂] M₂).ker_codRestrict p h
#align continuous_linear_map.ker_cod_restrict ContinuousLinearMap.ker_codRestrict
/-- Restrict the codomain of a continuous linear map `f` to `f.range`. -/
abbrev rangeRestrict [RingHomSurjective σ₁₂] (f : M₁ →SL[σ₁₂] M₂) :=
f.codRestrict (LinearMap.range f) (LinearMap.mem_range_self f)
@[simp]
theorem coe_rangeRestrict [RingHomSurjective σ₁₂] (f : M₁ →SL[σ₁₂] M₂) :
(f.rangeRestrict : M₁ →ₛₗ[σ₁₂] LinearMap.range f) = (f : M₁ →ₛₗ[σ₁₂] M₂).rangeRestrict :=
rfl
/-- `Submodule.subtype` as a `ContinuousLinearMap`. -/
def _root_.Submodule.subtypeL (p : Submodule R₁ M₁) : p →L[R₁] M₁ where
cont := continuous_subtype_val
toLinearMap := p.subtype
set_option linter.uppercaseLean3 false in
#align submodule.subtypeL Submodule.subtypeL
@[simp, norm_cast]
theorem _root_.Submodule.coe_subtypeL (p : Submodule R₁ M₁) :
(p.subtypeL : p →ₗ[R₁] M₁) = p.subtype :=
rfl
set_option linter.uppercaseLean3 false in
#align submodule.coe_subtypeL Submodule.coe_subtypeL
@[simp]
theorem _root_.Submodule.coe_subtypeL' (p : Submodule R₁ M₁) : ⇑p.subtypeL = p.subtype :=
rfl
set_option linter.uppercaseLean3 false in
#align submodule.coe_subtypeL' Submodule.coe_subtypeL'
@[simp] -- @[norm_cast] -- Porting note: A theorem with this can't have a rhs starting with `↑`.
theorem _root_.Submodule.subtypeL_apply (p : Submodule R₁ M₁) (x : p) : p.subtypeL x = x :=
rfl
set_option linter.uppercaseLean3 false in
#align submodule.subtypeL_apply Submodule.subtypeL_apply
@[simp]
theorem _root_.Submodule.range_subtypeL (p : Submodule R₁ M₁) : range p.subtypeL = p :=
Submodule.range_subtype _
set_option linter.uppercaseLean3 false in
#align submodule.range_subtypeL Submodule.range_subtypeL
@[simp]
theorem _root_.Submodule.ker_subtypeL (p : Submodule R₁ M₁) : ker p.subtypeL = ⊥ :=
Submodule.ker_subtype _
set_option linter.uppercaseLean3 false in
#align submodule.ker_subtypeL Submodule.ker_subtypeL
variable (R₁ M₁ M₂)
/-- `Prod.fst` as a `ContinuousLinearMap`. -/
def fst [Module R₁ M₂] : M₁ × M₂ →L[R₁] M₁ where
cont := continuous_fst
toLinearMap := LinearMap.fst R₁ M₁ M₂
#align continuous_linear_map.fst ContinuousLinearMap.fst
/-- `Prod.snd` as a `ContinuousLinearMap`. -/
def snd [Module R₁ M₂] : M₁ × M₂ →L[R₁] M₂ where
cont := continuous_snd
toLinearMap := LinearMap.snd R₁ M₁ M₂
#align continuous_linear_map.snd ContinuousLinearMap.snd
variable {R₁ M₁ M₂}
@[simp, norm_cast]
theorem coe_fst [Module R₁ M₂] : ↑(fst R₁ M₁ M₂) = LinearMap.fst R₁ M₁ M₂ :=
rfl
#align continuous_linear_map.coe_fst ContinuousLinearMap.coe_fst
@[simp, norm_cast]
theorem coe_fst' [Module R₁ M₂] : ⇑(fst R₁ M₁ M₂) = Prod.fst :=
rfl
#align continuous_linear_map.coe_fst' ContinuousLinearMap.coe_fst'
@[simp, norm_cast]
theorem coe_snd [Module R₁ M₂] : ↑(snd R₁ M₁ M₂) = LinearMap.snd R₁ M₁ M₂ :=
rfl
#align continuous_linear_map.coe_snd ContinuousLinearMap.coe_snd
@[simp, norm_cast]
theorem coe_snd' [Module R₁ M₂] : ⇑(snd R₁ M₁ M₂) = Prod.snd :=
rfl
#align continuous_linear_map.coe_snd' ContinuousLinearMap.coe_snd'
@[simp]
theorem fst_prod_snd [Module R₁ M₂] : (fst R₁ M₁ M₂).prod (snd R₁ M₁ M₂) = id R₁ (M₁ × M₂) :=
ext fun ⟨_x, _y⟩ => rfl
#align continuous_linear_map.fst_prod_snd ContinuousLinearMap.fst_prod_snd
@[simp]
theorem fst_comp_prod [Module R₁ M₂] [Module R₁ M₃] (f : M₁ →L[R₁] M₂) (g : M₁ →L[R₁] M₃) :
(fst R₁ M₂ M₃).comp (f.prod g) = f :=
ext fun _x => rfl
#align continuous_linear_map.fst_comp_prod ContinuousLinearMap.fst_comp_prod
@[simp]
theorem snd_comp_prod [Module R₁ M₂] [Module R₁ M₃] (f : M₁ →L[R₁] M₂) (g : M₁ →L[R₁] M₃) :
(snd R₁ M₂ M₃).comp (f.prod g) = g :=
ext fun _x => rfl
#align continuous_linear_map.snd_comp_prod ContinuousLinearMap.snd_comp_prod
/-- `Prod.map` of two continuous linear maps. -/
def prodMap [Module R₁ M₂] [Module R₁ M₃] [Module R₁ M₄] (f₁ : M₁ →L[R₁] M₂) (f₂ : M₃ →L[R₁] M₄) :
M₁ × M₃ →L[R₁] M₂ × M₄ :=
(f₁.comp (fst R₁ M₁ M₃)).prod (f₂.comp (snd R₁ M₁ M₃))
#align continuous_linear_map.prod_map ContinuousLinearMap.prodMap
@[simp, norm_cast]
theorem coe_prodMap [Module R₁ M₂] [Module R₁ M₃] [Module R₁ M₄] (f₁ : M₁ →L[R₁] M₂)
(f₂ : M₃ →L[R₁] M₄) : ↑(f₁.prodMap f₂) = (f₁ : M₁ →ₗ[R₁] M₂).prodMap (f₂ : M₃ →ₗ[R₁] M₄) :=
rfl
#align continuous_linear_map.coe_prod_map ContinuousLinearMap.coe_prodMap
@[simp, norm_cast]
theorem coe_prodMap' [Module R₁ M₂] [Module R₁ M₃] [Module R₁ M₄] (f₁ : M₁ →L[R₁] M₂)
(f₂ : M₃ →L[R₁] M₄) : ⇑(f₁.prodMap f₂) = Prod.map f₁ f₂ :=
rfl
#align continuous_linear_map.coe_prod_map' ContinuousLinearMap.coe_prodMap'
/-- The continuous linear map given by `(x, y) ↦ f₁ x + f₂ y`. -/
def coprod [Module R₁ M₂] [Module R₁ M₃] [ContinuousAdd M₃] (f₁ : M₁ →L[R₁] M₃)
(f₂ : M₂ →L[R₁] M₃) : M₁ × M₂ →L[R₁] M₃ :=
⟨LinearMap.coprod f₁ f₂, (f₁.cont.comp continuous_fst).add (f₂.cont.comp continuous_snd)⟩
#align continuous_linear_map.coprod ContinuousLinearMap.coprod
@[norm_cast, simp]
theorem coe_coprod [Module R₁ M₂] [Module R₁ M₃] [ContinuousAdd M₃] (f₁ : M₁ →L[R₁] M₃)
(f₂ : M₂ →L[R₁] M₃) : (f₁.coprod f₂ : M₁ × M₂ →ₗ[R₁] M₃) = LinearMap.coprod f₁ f₂ :=
rfl
#align continuous_linear_map.coe_coprod ContinuousLinearMap.coe_coprod
@[simp]
theorem coprod_apply [Module R₁ M₂] [Module R₁ M₃] [ContinuousAdd M₃] (f₁ : M₁ →L[R₁] M₃)
(f₂ : M₂ →L[R₁] M₃) (x) : f₁.coprod f₂ x = f₁ x.1 + f₂ x.2 :=
rfl
#align continuous_linear_map.coprod_apply ContinuousLinearMap.coprod_apply
theorem range_coprod [Module R₁ M₂] [Module R₁ M₃] [ContinuousAdd M₃] (f₁ : M₁ →L[R₁] M₃)
(f₂ : M₂ →L[R₁] M₃) : range (f₁.coprod f₂) = range f₁ ⊔ range f₂ :=
LinearMap.range_coprod _ _
#align continuous_linear_map.range_coprod ContinuousLinearMap.range_coprod
theorem comp_fst_add_comp_snd [Module R₁ M₂] [Module R₁ M₃] [ContinuousAdd M₃] (f : M₁ →L[R₁] M₃)
(g : M₂ →L[R₁] M₃) :
f.comp (ContinuousLinearMap.fst R₁ M₁ M₂) + g.comp (ContinuousLinearMap.snd R₁ M₁ M₂) =
f.coprod g :=
rfl
#align continuous_linear_map.comp_fst_add_comp_snd ContinuousLinearMap.comp_fst_add_comp_snd
theorem coprod_inl_inr [ContinuousAdd M₁] [ContinuousAdd M'₁] :
(ContinuousLinearMap.inl R₁ M₁ M'₁).coprod (ContinuousLinearMap.inr R₁ M₁ M'₁) =
ContinuousLinearMap.id R₁ (M₁ × M'₁) := by
apply coe_injective; apply LinearMap.coprod_inl_inr
#align continuous_linear_map.coprod_inl_inr ContinuousLinearMap.coprod_inl_inr
section
variable {R S : Type*} [Semiring R] [Semiring S] [Module R M₁] [Module R M₂] [Module R S]
[Module S M₂] [IsScalarTower R S M₂] [TopologicalSpace S] [ContinuousSMul S M₂]
/-- The linear map `fun x => c x • f`. Associates to a scalar-valued linear map and an element of
`M₂` the `M₂`-valued linear map obtained by multiplying the two (a.k.a. tensoring by `M₂`).
See also `ContinuousLinearMap.smulRightₗ` and `ContinuousLinearMap.smulRightL`. -/
def smulRight (c : M₁ →L[R] S) (f : M₂) : M₁ →L[R] M₂ :=
{ c.toLinearMap.smulRight f with cont := c.2.smul continuous_const }
#align continuous_linear_map.smul_right ContinuousLinearMap.smulRight
@[simp]
theorem smulRight_apply {c : M₁ →L[R] S} {f : M₂} {x : M₁} :
(smulRight c f : M₁ → M₂) x = c x • f :=
rfl
#align continuous_linear_map.smul_right_apply ContinuousLinearMap.smulRight_apply
end
variable [Module R₁ M₂] [TopologicalSpace R₁] [ContinuousSMul R₁ M₂]
@[simp]
theorem smulRight_one_one (c : R₁ →L[R₁] M₂) : smulRight (1 : R₁ →L[R₁] R₁) (c 1) = c := by
ext
simp [← ContinuousLinearMap.map_smul_of_tower]
#align continuous_linear_map.smul_right_one_one ContinuousLinearMap.smulRight_one_one
@[simp]
theorem smulRight_one_eq_iff {f f' : M₂} :
smulRight (1 : R₁ →L[R₁] R₁) f = smulRight (1 : R₁ →L[R₁] R₁) f' ↔ f = f' := by
simp only [ext_ring_iff, smulRight_apply, one_apply, one_smul]
#align continuous_linear_map.smul_right_one_eq_iff ContinuousLinearMap.smulRight_one_eq_iff
theorem smulRight_comp [ContinuousMul R₁] {x : M₂} {c : R₁} :
(smulRight (1 : R₁ →L[R₁] R₁) x).comp (smulRight (1 : R₁ →L[R₁] R₁) c) =
smulRight (1 : R₁ →L[R₁] R₁) (c • x) := by
ext
simp [mul_smul]
#align continuous_linear_map.smul_right_comp ContinuousLinearMap.smulRight_comp
section ToSpanSingleton
variable (R₁)
variable [ContinuousSMul R₁ M₁]
/-- Given an element `x` of a topological space `M` over a semiring `R`, the natural continuous
linear map from `R` to `M` by taking multiples of `x`. -/
def toSpanSingleton (x : M₁) : R₁ →L[R₁] M₁ where
toLinearMap := LinearMap.toSpanSingleton R₁ M₁ x
cont := continuous_id.smul continuous_const
#align continuous_linear_map.to_span_singleton ContinuousLinearMap.toSpanSingleton
theorem toSpanSingleton_apply (x : M₁) (r : R₁) : toSpanSingleton R₁ x r = r • x :=
rfl
#align continuous_linear_map.to_span_singleton_apply ContinuousLinearMap.toSpanSingleton_apply
theorem toSpanSingleton_add [ContinuousAdd M₁] (x y : M₁) :
toSpanSingleton R₁ (x + y) = toSpanSingleton R₁ x + toSpanSingleton R₁ y := by
ext1; simp [toSpanSingleton_apply]
#align continuous_linear_map.to_span_singleton_add ContinuousLinearMap.toSpanSingleton_add
theorem toSpanSingleton_smul' {α} [Monoid α] [DistribMulAction α M₁] [ContinuousConstSMul α M₁]
[SMulCommClass R₁ α M₁] (c : α) (x : M₁) :
toSpanSingleton R₁ (c • x) = c • toSpanSingleton R₁ x := by
ext1; rw [toSpanSingleton_apply, smul_apply, toSpanSingleton_apply, smul_comm]
#align continuous_linear_map.to_span_singleton_smul' ContinuousLinearMap.toSpanSingleton_smul'
/-- A special case of `to_span_singleton_smul'` for when `R` is commutative. -/
theorem toSpanSingleton_smul (R) {M₁} [CommSemiring R] [AddCommMonoid M₁] [Module R M₁]
[TopologicalSpace R] [TopologicalSpace M₁] [ContinuousSMul R M₁] (c : R) (x : M₁) :
toSpanSingleton R (c • x) = c • toSpanSingleton R x :=
toSpanSingleton_smul' R c x
#align continuous_linear_map.to_span_singleton_smul ContinuousLinearMap.toSpanSingleton_smul
end ToSpanSingleton
end Semiring
section Pi
variable {R : Type*} [Semiring R] {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [Module R M]
{M₂ : Type*} [TopologicalSpace M₂] [AddCommMonoid M₂] [Module R M₂] {ι : Type*} {φ : ι → Type*}
[∀ i, TopologicalSpace (φ i)] [∀ i, AddCommMonoid (φ i)] [∀ i, Module R (φ i)]
/-- `pi` construction for continuous linear functions. From a family of continuous linear functions
it produces a continuous linear function into a family of topological modules. -/
def pi (f : ∀ i, M →L[R] φ i) : M →L[R] ∀ i, φ i :=
⟨LinearMap.pi fun i => f i, continuous_pi fun i => (f i).continuous⟩
#align continuous_linear_map.pi ContinuousLinearMap.pi
@[simp]
theorem coe_pi' (f : ∀ i, M →L[R] φ i) : ⇑(pi f) = fun c i => f i c :=
rfl
#align continuous_linear_map.coe_pi' ContinuousLinearMap.coe_pi'
@[simp]
theorem coe_pi (f : ∀ i, M →L[R] φ i) : (pi f : M →ₗ[R] ∀ i, φ i) = LinearMap.pi fun i => f i :=
rfl
#align continuous_linear_map.coe_pi ContinuousLinearMap.coe_pi
theorem pi_apply (f : ∀ i, M →L[R] φ i) (c : M) (i : ι) : pi f c i = f i c :=
rfl
#align continuous_linear_map.pi_apply ContinuousLinearMap.pi_apply
theorem pi_eq_zero (f : ∀ i, M →L[R] φ i) : pi f = 0 ↔ ∀ i, f i = 0 := by
simp only [ext_iff, pi_apply, Function.funext_iff]
exact forall_swap
#align continuous_linear_map.pi_eq_zero ContinuousLinearMap.pi_eq_zero
theorem pi_zero : pi (fun _ => 0 : ∀ i, M →L[R] φ i) = 0 :=
ext fun _ => rfl
#align continuous_linear_map.pi_zero ContinuousLinearMap.pi_zero
theorem pi_comp (f : ∀ i, M →L[R] φ i) (g : M₂ →L[R] M) :
(pi f).comp g = pi fun i => (f i).comp g :=
rfl
#align continuous_linear_map.pi_comp ContinuousLinearMap.pi_comp
/-- The projections from a family of topological modules are continuous linear maps. -/
def proj (i : ι) : (∀ i, φ i) →L[R] φ i :=
⟨LinearMap.proj i, continuous_apply _⟩
#align continuous_linear_map.proj ContinuousLinearMap.proj
@[simp]
theorem proj_apply (i : ι) (b : ∀ i, φ i) : (proj i : (∀ i, φ i) →L[R] φ i) b = b i :=
rfl
#align continuous_linear_map.proj_apply ContinuousLinearMap.proj_apply
theorem proj_pi (f : ∀ i, M₂ →L[R] φ i) (i : ι) : (proj i).comp (pi f) = f i :=
ext fun _c => rfl
#align continuous_linear_map.proj_pi ContinuousLinearMap.proj_pi
theorem iInf_ker_proj : (⨅ i, ker (proj i : (∀ i, φ i) →L[R] φ i) : Submodule R (∀ i, φ i)) = ⊥ :=
LinearMap.iInf_ker_proj
#align continuous_linear_map.infi_ker_proj ContinuousLinearMap.iInf_ker_proj
variable (R φ)
/-- Given a function `f : α → ι`, it induces a continuous linear function by right composition on
product types. For `f = Subtype.val`, this corresponds to forgetting some set of variables. -/
def _root_.Pi.compRightL {α : Type*} (f : α → ι) : ((i : ι) → φ i) →L[R] ((i : α) → φ (f i)) where
toFun := fun v i ↦ v (f i)
map_add' := by intros; ext; simp
map_smul' := by intros; ext; simp
cont := by continuity
@[simp] lemma _root_.Pi.compRightL_apply {α : Type*} (f : α → ι) (v : (i : ι) → φ i) (i : α) :
Pi.compRightL R φ f v i = v (f i) := rfl
/-- If `I` and `J` are complementary index sets, the product of the kernels of the `J`th projections
of `φ` is linearly equivalent to the product over `I`. -/
def iInfKerProjEquiv {I J : Set ι} [DecidablePred fun i => i ∈ I] (hd : Disjoint I J)
(hu : Set.univ ⊆ I ∪ J) :
(⨅ i ∈ J, ker (proj i : (∀ i, φ i) →L[R] φ i) :
Submodule R (∀ i, φ i)) ≃L[R] ∀ i : I, φ i where
toLinearEquiv := LinearMap.iInfKerProjEquiv R φ hd hu
continuous_toFun :=
continuous_pi fun i => by
have :=
@continuous_subtype_val _ _ fun x =>
x ∈ (⨅ i ∈ J, ker (proj i : (∀ i, φ i) →L[R] φ i) : Submodule R (∀ i, φ i))
have := Continuous.comp (continuous_apply (π := φ) i) this
exact this
continuous_invFun :=
Continuous.subtype_mk
(continuous_pi fun i => by
-- Porting note: Was `dsimp`.
change
Continuous (⇑(if h : i ∈ I then LinearMap.proj (R := R) (ι := ↥I)
(φ := fun i : ↥I => φ i) ⟨i, h⟩ else
(0 : ((i : I) → φ i) →ₗ[R] φ i)))
split_ifs <;> [apply continuous_apply; exact continuous_zero])
_
#align continuous_linear_map.infi_ker_proj_equiv ContinuousLinearMap.iInfKerProjEquiv
end Pi
section Ring
variable {R : Type*} [Ring R] {R₂ : Type*} [Ring R₂] {R₃ : Type*} [Ring R₃] {M : Type*}
[TopologicalSpace M] [AddCommGroup M] {M₂ : Type*} [TopologicalSpace M₂] [AddCommGroup M₂]
{M₃ : Type*} [TopologicalSpace M₃] [AddCommGroup M₃] {M₄ : Type*} [TopologicalSpace M₄]
[AddCommGroup M₄] [Module R M] [Module R₂ M₂] [Module R₃ M₃] {σ₁₂ : R →+* R₂} {σ₂₃ : R₂ →+* R₃}
{σ₁₃ : R →+* R₃}
section
protected theorem map_neg (f : M →SL[σ₁₂] M₂) (x : M) : f (-x) = -f x := by
exact map_neg f x
#align continuous_linear_map.map_neg ContinuousLinearMap.map_neg
protected theorem map_sub (f : M →SL[σ₁₂] M₂) (x y : M) : f (x - y) = f x - f y := by
exact map_sub f x y
#align continuous_linear_map.map_sub ContinuousLinearMap.map_sub
@[simp]
theorem sub_apply' (f g : M →SL[σ₁₂] M₂) (x : M) : ((f : M →ₛₗ[σ₁₂] M₂) - g) x = f x - g x :=
rfl
#align continuous_linear_map.sub_apply' ContinuousLinearMap.sub_apply'
end
section
variable [Module R M₂] [Module R M₃] [Module R M₄]
theorem range_prod_eq {f : M →L[R] M₂} {g : M →L[R] M₃} (h : ker f ⊔ ker g = ⊤) :
range (f.prod g) = (range f).prod (range g) :=
LinearMap.range_prod_eq h
#align continuous_linear_map.range_prod_eq ContinuousLinearMap.range_prod_eq
theorem ker_prod_ker_le_ker_coprod [ContinuousAdd M₃] (f : M →L[R] M₃) (g : M₂ →L[R] M₃) :
(LinearMap.ker f).prod (LinearMap.ker g) ≤ LinearMap.ker (f.coprod g) :=
LinearMap.ker_prod_ker_le_ker_coprod f.toLinearMap g.toLinearMap
#align continuous_linear_map.ker_prod_ker_le_ker_coprod ContinuousLinearMap.ker_prod_ker_le_ker_coprod
theorem ker_coprod_of_disjoint_range [ContinuousAdd M₃] (f : M →L[R] M₃) (g : M₂ →L[R] M₃)
(hd : Disjoint (range f) (range g)) :
LinearMap.ker (f.coprod g) = (LinearMap.ker f).prod (LinearMap.ker g) :=
LinearMap.ker_coprod_of_disjoint_range f.toLinearMap g.toLinearMap hd
#align continuous_linear_map.ker_coprod_of_disjoint_range ContinuousLinearMap.ker_coprod_of_disjoint_range
end
section
variable [TopologicalAddGroup M₂]
instance neg : Neg (M →SL[σ₁₂] M₂) :=
⟨fun f => ⟨-f, f.2.neg⟩⟩
#align continuous_linear_map.has_neg ContinuousLinearMap.neg
@[simp]
theorem neg_apply (f : M →SL[σ₁₂] M₂) (x : M) : (-f) x = -f x :=
rfl
#align continuous_linear_map.neg_apply ContinuousLinearMap.neg_apply
@[simp, norm_cast]
theorem coe_neg (f : M →SL[σ₁₂] M₂) : (↑(-f) : M →ₛₗ[σ₁₂] M₂) = -f :=
rfl
#align continuous_linear_map.coe_neg ContinuousLinearMap.coe_neg
@[norm_cast]
theorem coe_neg' (f : M →SL[σ₁₂] M₂) : ⇑(-f) = -f :=
rfl
#align continuous_linear_map.coe_neg' ContinuousLinearMap.coe_neg'
instance sub : Sub (M →SL[σ₁₂] M₂) :=
⟨fun f g => ⟨f - g, f.2.sub g.2⟩⟩
#align continuous_linear_map.has_sub ContinuousLinearMap.sub
instance addCommGroup : AddCommGroup (M →SL[σ₁₂] M₂) where
__ := ContinuousLinearMap.addCommMonoid
neg := (-·)
sub := (· - ·)
sub_eq_add_neg _ _ := by ext; apply sub_eq_add_neg
nsmul := (· • ·)
zsmul := (· • ·)
zsmul_zero' f := by ext; simp
zsmul_succ' n f := by ext; simp [add_smul, add_comm]
zsmul_neg' n f := by ext; simp [Nat.succ_eq_add_one, add_smul]
add_left_neg _ := by ext; apply add_left_neg
#align continuous_linear_map.add_comm_group ContinuousLinearMap.addCommGroup
theorem sub_apply (f g : M →SL[σ₁₂] M₂) (x : M) : (f - g) x = f x - g x :=
rfl
#align continuous_linear_map.sub_apply ContinuousLinearMap.sub_apply
@[simp, norm_cast]
theorem coe_sub (f g : M →SL[σ₁₂] M₂) : (↑(f - g) : M →ₛₗ[σ₁₂] M₂) = f - g :=
rfl
#align continuous_linear_map.coe_sub ContinuousLinearMap.coe_sub
@[simp, norm_cast]
theorem coe_sub' (f g : M →SL[σ₁₂] M₂) : ⇑(f - g) = f - g :=
rfl
#align continuous_linear_map.coe_sub' ContinuousLinearMap.coe_sub'
end
@[simp]
theorem comp_neg [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] [TopologicalAddGroup M₂] [TopologicalAddGroup M₃]
(g : M₂ →SL[σ₂₃] M₃) (f : M →SL[σ₁₂] M₂) : g.comp (-f) = -g.comp f := by
ext x
simp
#align continuous_linear_map.comp_neg ContinuousLinearMap.comp_neg
@[simp]
theorem neg_comp [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] [TopologicalAddGroup M₃] (g : M₂ →SL[σ₂₃] M₃)
(f : M →SL[σ₁₂] M₂) : (-g).comp f = -g.comp f := by
ext
simp
#align continuous_linear_map.neg_comp ContinuousLinearMap.neg_comp
@[simp]
| Mathlib/Topology/Algebra/Module/Basic.lean | 1,509 | 1,512 | theorem comp_sub [RingHomCompTriple σ₁₂ σ₂₃ σ₁₃] [TopologicalAddGroup M₂] [TopologicalAddGroup M₃]
(g : M₂ →SL[σ₂₃] M₃) (f₁ f₂ : M →SL[σ₁₂] M₂) : g.comp (f₁ - f₂) = g.comp f₁ - g.comp f₂ := by |
ext
simp
|
/-
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.Topology.MetricSpace.PiNat
import Mathlib.Topology.MetricSpace.Isometry
import Mathlib.Topology.MetricSpace.Gluing
import Mathlib.Topology.Sets.Opens
import Mathlib.Analysis.Normed.Field.Basic
#align_import topology.metric_space.polish from "leanprover-community/mathlib"@"bcfa726826abd57587355b4b5b7e78ad6527b7e4"
/-!
# Polish spaces
A topological space is Polish if its topology is second-countable and there exists a compatible
complete metric. This is the class of spaces that is well-behaved with respect to measure theory.
In this file, we establish the basic properties of Polish spaces.
## Main definitions and results
* `PolishSpace α` is a mixin typeclass on a topological space, requiring that the topology is
second-countable and compatible with a complete metric. To endow the space with such a metric,
use in a proof `letI := upgradePolishSpace α`.
We register an instance from complete second-countable metric spaces to Polish spaces, not the
other way around.
* We register that countable products and sums of Polish spaces are Polish.
* `IsClosed.polishSpace`: a closed subset of a Polish space is Polish.
* `IsOpen.polishSpace`: an open subset of a Polish space is Polish.
* `exists_nat_nat_continuous_surjective`: any nonempty Polish space is the continuous image
of the fundamental Polish space `ℕ → ℕ`.
A fundamental property of Polish spaces is that one can put finer topologies, still Polish,
with additional properties:
* `exists_polishSpace_forall_le`: on a topological space, consider countably many topologies
`t n`, all Polish and finer than the original topology. Then there exists another Polish
topology which is finer than all the `t n`.
* `IsClopenable s` is a property of a subset `s` of a topological space, requiring that there
exists a finer topology, which is Polish, for which `s` becomes open and closed. We show that
this property is satisfied for open sets, closed sets, for complements, and for countable unions.
Once Borel-measurable sets are defined in later files, it will follow that any Borel-measurable
set is clopenable. Once the Lusin-Souslin theorem is proved using analytic sets, we will even
show that a set is clopenable if and only if it is Borel-measurable, see
`isClopenable_iff_measurableSet`.
-/
noncomputable section
open scoped Topology Uniformity
open Filter TopologicalSpace Set Metric Function
variable {α : Type*} {β : Type*}
/-! ### Basic properties of Polish spaces -/
/-- A Polish space is a topological space with second countable topology, that can be endowed
with a metric for which it is complete.
We register an instance from complete second countable metric space to polish space, and not the
other way around as this is the most common use case.
To endow a Polish space with a complete metric space structure, do `letI := upgradePolishSpace α`.
-/
class PolishSpace (α : Type*) [h : TopologicalSpace α]
extends SecondCountableTopology α : Prop where
complete : ∃ m : MetricSpace α, m.toUniformSpace.toTopologicalSpace = h ∧
@CompleteSpace α m.toUniformSpace
#align polish_space PolishSpace
/-- A convenience class, for a Polish space endowed with a complete metric. No instance of this
class should be registered: It should be used as `letI := upgradePolishSpace α` to endow a Polish
space with a complete metric. -/
class UpgradedPolishSpace (α : Type*) extends MetricSpace α, SecondCountableTopology α,
CompleteSpace α
#align upgraded_polish_space UpgradedPolishSpace
instance (priority := 100) PolishSpace.of_separableSpace_completeSpace_metrizable [UniformSpace α]
[SeparableSpace α] [CompleteSpace α] [(𝓤 α).IsCountablyGenerated] [T0Space α] :
PolishSpace α where
toSecondCountableTopology := UniformSpace.secondCountable_of_separable α
complete := ⟨UniformSpace.metricSpace α, rfl, ‹_›⟩
#align polish_space_of_complete_second_countable PolishSpace.of_separableSpace_completeSpace_metrizable
/-- Construct on a Polish space a metric (compatible with the topology) which is complete. -/
def polishSpaceMetric (α : Type*) [TopologicalSpace α] [h : PolishSpace α] : MetricSpace α :=
h.complete.choose.replaceTopology h.complete.choose_spec.1.symm
#align polish_space_metric polishSpaceMetric
theorem complete_polishSpaceMetric (α : Type*) [ht : TopologicalSpace α] [h : PolishSpace α] :
@CompleteSpace α (polishSpaceMetric α).toUniformSpace := by
convert h.complete.choose_spec.2
exact MetricSpace.replaceTopology_eq _ _
#align complete_polish_space_metric complete_polishSpaceMetric
/-- This definition endows a Polish space with a complete metric. Use it as:
`letI := upgradePolishSpace α`. -/
def upgradePolishSpace (α : Type*) [TopologicalSpace α] [PolishSpace α] :
UpgradedPolishSpace α :=
letI := polishSpaceMetric α
{ complete_polishSpaceMetric α with }
#align upgrade_polish_space upgradePolishSpace
namespace PolishSpace
instance (priority := 100) instMetrizableSpace (α : Type*) [TopologicalSpace α] [PolishSpace α] :
MetrizableSpace α := by
letI := upgradePolishSpace α
infer_instance
@[deprecated (since := "2024-02-23")]
theorem t2Space (α : Type*) [TopologicalSpace α] [PolishSpace α] : T2Space α := inferInstance
#align polish_space.t2_space PolishSpace.t2Space
/-- A countable product of Polish spaces is Polish. -/
instance pi_countable {ι : Type*} [Countable ι] {E : ι → Type*} [∀ i, TopologicalSpace (E i)]
[∀ i, PolishSpace (E i)] : PolishSpace (∀ i, E i) := by
letI := fun i => upgradePolishSpace (E i)
infer_instance
#align polish_space.pi_countable PolishSpace.pi_countable
/-- A countable disjoint union of Polish spaces is Polish. -/
instance sigma {ι : Type*} [Countable ι] {E : ι → Type*} [∀ n, TopologicalSpace (E n)]
[∀ n, PolishSpace (E n)] : PolishSpace (Σn, E n) :=
letI := fun n => upgradePolishSpace (E n)
letI : MetricSpace (Σn, E n) := Sigma.metricSpace
haveI : CompleteSpace (Σn, E n) := Sigma.completeSpace
inferInstance
#align polish_space.sigma PolishSpace.sigma
/-- The product of two Polish spaces is Polish. -/
instance prod [TopologicalSpace α] [PolishSpace α] [TopologicalSpace β] [PolishSpace β] :
PolishSpace (α × β) :=
letI := upgradePolishSpace α
letI := upgradePolishSpace β
inferInstance
/-- The disjoint union of two Polish spaces is Polish. -/
instance sum [TopologicalSpace α] [PolishSpace α] [TopologicalSpace β] [PolishSpace β] :
PolishSpace (α ⊕ β) :=
letI := upgradePolishSpace α
letI := upgradePolishSpace β
inferInstance
#align polish_space.sum PolishSpace.sum
/-- Any nonempty Polish space is the continuous image of the fundamental space `ℕ → ℕ`. -/
theorem exists_nat_nat_continuous_surjective (α : Type*) [TopologicalSpace α] [PolishSpace α]
[Nonempty α] : ∃ f : (ℕ → ℕ) → α, Continuous f ∧ Surjective f :=
letI := upgradePolishSpace α
exists_nat_nat_continuous_surjective_of_completeSpace α
#align polish_space.exists_nat_nat_continuous_surjective PolishSpace.exists_nat_nat_continuous_surjective
/-- Given a closed embedding into a Polish space, the source space is also Polish. -/
theorem _root_.ClosedEmbedding.polishSpace [TopologicalSpace α] [TopologicalSpace β] [PolishSpace β]
{f : α → β} (hf : ClosedEmbedding f) : PolishSpace α := by
letI := upgradePolishSpace β
letI : MetricSpace α := hf.toEmbedding.comapMetricSpace f
haveI : SecondCountableTopology α := hf.toEmbedding.secondCountableTopology
have : CompleteSpace α := by
rw [completeSpace_iff_isComplete_range hf.toEmbedding.to_isometry.uniformInducing]
exact hf.isClosed_range.isComplete
infer_instance
#align closed_embedding.polish_space ClosedEmbedding.polishSpace
/-- Any countable discrete space is Polish. -/
instance (priority := 50) polish_of_countable [TopologicalSpace α]
[h : Countable α] [DiscreteTopology α] : PolishSpace α := by
obtain ⟨f, hf⟩ := h.exists_injective_nat
have : ClosedEmbedding f := by
apply closedEmbedding_of_continuous_injective_closed continuous_of_discreteTopology hf
exact fun t _ => isClosed_discrete _
exact this.polishSpace
#align polish_of_countable PolishSpace.polish_of_countable
/-- Pulling back a Polish topology under an equiv gives again a Polish topology. -/
theorem _root_.Equiv.polishSpace_induced [t : TopologicalSpace β] [PolishSpace β] (f : α ≃ β) :
@PolishSpace α (t.induced f) :=
letI : TopologicalSpace α := t.induced f
(f.toHomeomorphOfInducing ⟨rfl⟩).closedEmbedding.polishSpace
#align equiv.polish_space_induced Equiv.polishSpace_induced
/-- A closed subset of a Polish space is also Polish. -/
theorem _root_.IsClosed.polishSpace [TopologicalSpace α] [PolishSpace α] {s : Set α}
(hs : IsClosed s) : PolishSpace s :=
(IsClosed.closedEmbedding_subtype_val hs).polishSpace
#align is_closed.polish_space IsClosed.polishSpace
instance instPolishSpaceUniv [TopologicalSpace α] [PolishSpace α] :
PolishSpace (univ : Set α) :=
isClosed_univ.polishSpace
#align measure_theory.set.univ.polish_space PolishSpace.instPolishSpaceUniv
protected theorem _root_.CompletePseudometrizable.iInf {ι : Type*} [Countable ι]
{t : ι → TopologicalSpace α} (ht₀ : ∃ t₀, @T2Space α t₀ ∧ ∀ i, t i ≤ t₀)
(ht : ∀ i, ∃ u : UniformSpace α, CompleteSpace α ∧ 𝓤[u].IsCountablyGenerated ∧
u.toTopologicalSpace = t i) :
∃ u : UniformSpace α, CompleteSpace α ∧
𝓤[u].IsCountablyGenerated ∧ u.toTopologicalSpace = ⨅ i, t i := by
choose u hcomp hcount hut using ht
obtain rfl : t = fun i ↦ (u i).toTopologicalSpace := (funext hut).symm
refine ⟨⨅ i, u i, .iInf hcomp ht₀, ?_, UniformSpace.toTopologicalSpace_iInf⟩
rw [iInf_uniformity]
infer_instance
protected theorem iInf {ι : Type*} [Countable ι] {t : ι → TopologicalSpace α}
(ht₀ : ∃ i₀, ∀ i, t i ≤ t i₀) (ht : ∀ i, @PolishSpace α (t i)) : @PolishSpace α (⨅ i, t i) := by
rcases ht₀ with ⟨i₀, hi₀⟩
rcases CompletePseudometrizable.iInf ⟨t i₀, letI := t i₀; haveI := ht i₀; inferInstance, hi₀⟩
fun i ↦
letI := t i; haveI := ht i; letI := upgradePolishSpace α
⟨inferInstance, inferInstance, inferInstance, rfl⟩
with ⟨u, hcomp, hcount, htop⟩
rw [← htop]
have : @SecondCountableTopology α u.toTopologicalSpace :=
htop.symm ▸ secondCountableTopology_iInf fun i ↦ letI := t i; (ht i).toSecondCountableTopology
have : @T1Space α u.toTopologicalSpace :=
htop.symm ▸ t1Space_antitone (iInf_le _ i₀) (by letI := t i₀; haveI := ht i₀; infer_instance)
infer_instance
#noalign polish_space.aux_copy
/-- Given a Polish space, and countably many finer Polish topologies, there exists another Polish
topology which is finer than all of them. -/
theorem exists_polishSpace_forall_le {ι : Type*} [Countable ι] [t : TopologicalSpace α]
[p : PolishSpace α] (m : ι → TopologicalSpace α) (hm : ∀ n, m n ≤ t)
(h'm : ∀ n, @PolishSpace α (m n)) :
∃ t' : TopologicalSpace α, (∀ n, t' ≤ m n) ∧ t' ≤ t ∧ @PolishSpace α t' :=
⟨⨅ i : Option ι, i.elim t m, fun i ↦ iInf_le _ (some i), iInf_le _ none,
.iInf ⟨none, Option.forall.2 ⟨le_rfl, hm⟩⟩ <| Option.forall.2 ⟨p, h'm⟩⟩
#align polish_space.exists_polish_space_forall_le PolishSpace.exists_polishSpace_forall_le
end PolishSpace
/-!
### An open subset of a Polish space is Polish
To prove this fact, one needs to construct another metric, giving rise to the same topology,
for which the open subset is complete. This is not obvious, as for instance `(0,1) ⊆ ℝ` is not
complete for the usual metric of `ℝ`: one should build a new metric that blows up close to the
boundary.
Porting note: definitions and lemmas in this section now take `(s : Opens α)` instead of
`{s : Set α} (hs : IsOpen s)` so that we can turn various definitions and lemmas into instances.
Also, some lemmas used to assume `Set.Nonempty sᶜ` in Lean 3. In fact, this assumption is not
needed, so it was dropped.
-/
namespace TopologicalSpace.Opens
variable [MetricSpace α] {s : Opens α}
/-- A type synonym for a subset `s` of a metric space, on which we will construct another metric
for which it will be complete. -/
-- Porting note(#5171): was @[nolint has_nonempty_instance]
def CompleteCopy {α : Type*} [MetricSpace α] (s : Opens α) : Type _ := s
#align polish_space.complete_copy TopologicalSpace.Opens.CompleteCopyₓ
namespace CompleteCopy
/-- A distance on an open subset `s` of a metric space, designed to make it complete. It is given
by `dist' x y = dist x y + |1 / dist x sᶜ - 1 / dist y sᶜ|`, where the second term blows up close to
the boundary to ensure that Cauchy sequences for `dist'` remain well inside `s`. -/
-- Porting note: in mathlib3 this was only a local instance.
instance instDist : Dist (CompleteCopy s) where
dist x y := dist x.1 y.1 + abs (1 / infDist x.1 sᶜ - 1 / infDist y.1 sᶜ)
#align polish_space.has_dist_complete_copy TopologicalSpace.Opens.CompleteCopy.instDistₓ
theorem dist_eq (x y : CompleteCopy s) :
dist x y = dist x.1 y.1 + abs (1 / infDist x.1 sᶜ - 1 / infDist y.1 sᶜ) :=
rfl
#align polish_space.dist_complete_copy_eq TopologicalSpace.Opens.CompleteCopy.dist_eqₓ
theorem dist_val_le_dist (x y : CompleteCopy s) : dist x.1 y.1 ≤ dist x y :=
(le_add_iff_nonneg_right _).2 (abs_nonneg _)
#align polish_space.dist_le_dist_complete_copy TopologicalSpace.Opens.CompleteCopy.dist_val_le_distₓ
instance : TopologicalSpace (CompleteCopy s) := inferInstanceAs (TopologicalSpace s)
instance : T0Space (CompleteCopy s) := inferInstanceAs (T0Space s)
/-- A metric space structure on a subset `s` of a metric space, designed to make it complete
if `s` is open. It is given by `dist' x y = dist x y + |1 / dist x sᶜ - 1 / dist y sᶜ|`, where the
second term blows up close to the boundary to ensure that Cauchy sequences for `dist'` remain well
inside `s`.
Porting note: the definition changed to ensure that the `TopologicalSpace` structure on
`TopologicalSpace.Opens.CompleteCopy s` is definitionally equal to the original one. -/
-- Porting note: in mathlib3 this was only a local instance.
instance instMetricSpace : MetricSpace (CompleteCopy s) := by
refine @MetricSpace.ofT0PseudoMetricSpace (CompleteCopy s)
(.ofDistTopology dist (fun _ ↦ ?_) (fun _ _ ↦ ?_) (fun x y z ↦ ?_) fun t ↦ ?_) _
· simp only [dist_eq, dist_self, one_div, sub_self, abs_zero, add_zero]
· simp only [dist_eq, dist_comm, abs_sub_comm]
· calc
dist x z = dist x.1 z.1 + |1 / infDist x.1 sᶜ - 1 / infDist z.1 sᶜ| := rfl
_ ≤ dist x.1 y.1 + dist y.1 z.1 + (|1 / infDist x.1 sᶜ - 1 / infDist y.1 sᶜ| +
|1 / infDist y.1 sᶜ - 1 / infDist z.1 sᶜ|) :=
add_le_add (dist_triangle _ _ _) (dist_triangle (1 / infDist _ _) _ _)
_ = dist x y + dist y z := add_add_add_comm ..
· refine ⟨fun h x hx ↦ ?_, fun h ↦ isOpen_iff_mem_nhds.2 fun x hx ↦ ?_⟩
· rcases (Metric.isOpen_iff (α := s)).1 h x hx with ⟨ε, ε0, hε⟩
exact ⟨ε, ε0, fun y hy ↦ hε <| (dist_comm _ _).trans_lt <| (dist_val_le_dist _ _).trans_lt hy⟩
· rcases h x hx with ⟨ε, ε0, hε⟩
simp only [dist_eq, one_div] at hε
have : Tendsto (fun y : s ↦ dist x.1 y.1 + |(infDist x.1 sᶜ)⁻¹ - (infDist y.1 sᶜ)⁻¹|)
(𝓝 x) (𝓝 (dist x.1 x.1 + |(infDist x.1 sᶜ)⁻¹ - (infDist x.1 sᶜ)⁻¹|)) := by
refine (tendsto_const_nhds.dist continuous_subtype_val.continuousAt).add
(tendsto_const_nhds.sub <| ?_).abs
refine (continuousAt_inv_infDist_pt ?_).comp continuous_subtype_val.continuousAt
rw [s.isOpen.isClosed_compl.closure_eq, mem_compl_iff, not_not]
exact x.2
simp only [dist_self, sub_self, abs_zero, zero_add] at this
exact mem_of_superset (this <| gt_mem_nhds ε0) hε
#align polish_space.complete_copy_metric_space TopologicalSpace.Opens.CompleteCopy.instMetricSpaceₓ
-- Porting note: no longer needed because the topologies are defeq
#noalign polish_space.complete_copy_id_homeo
instance instCompleteSpace [CompleteSpace α] : CompleteSpace (CompleteCopy s) := by
refine Metric.complete_of_convergent_controlled_sequences ((1 / 2) ^ ·) (by simp) fun u hu ↦ ?_
have A : CauchySeq fun n => (u n).1 := by
refine cauchySeq_of_le_tendsto_0 (fun n : ℕ => (1 / 2) ^ n) (fun n m N hNn hNm => ?_) ?_
· exact (dist_val_le_dist (u n) (u m)).trans (hu N n m hNn hNm).le
· exact tendsto_pow_atTop_nhds_zero_of_lt_one (by norm_num) (by norm_num)
obtain ⟨x, xlim⟩ : ∃ x, Tendsto (fun n => (u n).1) atTop (𝓝 x) := cauchySeq_tendsto_of_complete A
by_cases xs : x ∈ s
· exact ⟨⟨x, xs⟩, tendsto_subtype_rng.2 xlim⟩
obtain ⟨C, hC⟩ : ∃ C, ∀ n, 1 / infDist (u n).1 sᶜ < C := by
refine ⟨(1 / 2) ^ 0 + 1 / infDist (u 0).1 sᶜ, fun n ↦ ?_⟩
rw [← sub_lt_iff_lt_add]
calc
_ ≤ |1 / infDist (u n).1 sᶜ - 1 / infDist (u 0).1 sᶜ| := le_abs_self _
_ = |1 / infDist (u 0).1 sᶜ - 1 / infDist (u n).1 sᶜ| := abs_sub_comm _ _
_ ≤ dist (u 0) (u n) := le_add_of_nonneg_left dist_nonneg
_ < (1 / 2) ^ 0 := hu 0 0 n le_rfl n.zero_le
have Cpos : 0 < C := lt_of_le_of_lt (div_nonneg zero_le_one infDist_nonneg) (hC 0)
have Hmem : ∀ {y}, y ∈ s ↔ 0 < infDist y sᶜ := fun {y} ↦ by
rw [← s.isOpen.isClosed_compl.not_mem_iff_infDist_pos ⟨x, xs⟩]; exact not_not.symm
have I : ∀ n, 1 / C ≤ infDist (u n).1 sᶜ := fun n ↦ by
have : 0 < infDist (u n).1 sᶜ := Hmem.1 (u n).2
rw [div_le_iff' Cpos]
exact (div_le_iff this).1 (hC n).le
have I' : 1 / C ≤ infDist x sᶜ :=
have : Tendsto (fun n => infDist (u n).1 sᶜ) atTop (𝓝 (infDist x sᶜ)) :=
((continuous_infDist_pt (sᶜ : Set α)).tendsto x).comp xlim
ge_of_tendsto' this I
exact absurd (Hmem.2 <| lt_of_lt_of_le (div_pos one_pos Cpos) I') xs
#align polish_space.complete_space_complete_copy TopologicalSpace.Opens.CompleteCopy.instCompleteSpaceₓ
/-- An open subset of a Polish space is also Polish. -/
theorem _root_.IsOpen.polishSpace {α : Type*} [TopologicalSpace α] [PolishSpace α] {s : Set α}
(hs : IsOpen s) : PolishSpace s := by
letI := upgradePolishSpace α
lift s to Opens α using hs
have : SecondCountableTopology s.CompleteCopy := inferInstanceAs (SecondCountableTopology s)
exact inferInstanceAs (PolishSpace s.CompleteCopy)
#align is_open.polish_space IsOpen.polishSpace
end CompleteCopy
end TopologicalSpace.Opens
namespace PolishSpace
/-! ### Clopenable sets in Polish spaces -/
/-- A set in a topological space is clopenable if there exists a finer Polish topology for which
this set is open and closed. It turns out that this notion is equivalent to being Borel-measurable,
but this is nontrivial (see `isClopenable_iff_measurableSet`). -/
def IsClopenable [t : TopologicalSpace α] (s : Set α) : Prop :=
∃ t' : TopologicalSpace α, t' ≤ t ∧ @PolishSpace α t' ∧ IsClosed[t'] s ∧ IsOpen[t'] s
#align polish_space.is_clopenable PolishSpace.IsClopenable
/-- Given a closed set `s` in a Polish space, one can construct a finer Polish topology for
which `s` is both open and closed. -/
theorem _root_.IsClosed.isClopenable [TopologicalSpace α] [PolishSpace α] {s : Set α}
(hs : IsClosed s) : IsClopenable s := by
/- Both sets `s` and `sᶜ` admit a Polish topology. So does their disjoint union `s ⊕ sᶜ`.
Pulling back this topology by the canonical bijection with `α` gives the desired Polish
topology in which `s` is both open and closed. -/
classical
haveI : PolishSpace s := hs.polishSpace
let t : Set α := sᶜ
haveI : PolishSpace t := hs.isOpen_compl.polishSpace
let f : s ⊕ t ≃ α := Equiv.Set.sumCompl s
have hle : TopologicalSpace.coinduced f instTopologicalSpaceSum ≤ ‹_› := by
simp only [instTopologicalSpaceSum, coinduced_sup, coinduced_compose, sup_le_iff,
← continuous_iff_coinduced_le]
exact ⟨continuous_subtype_val, continuous_subtype_val⟩
refine ⟨.coinduced f instTopologicalSpaceSum, hle, ?_, hs.mono hle, ?_⟩
· rw [← f.induced_symm]
exact f.symm.polishSpace_induced
· rw [isOpen_coinduced, isOpen_sum_iff]
simp [f, preimage_preimage]
#align is_closed.is_clopenable IsClosed.isClopenable
theorem IsClopenable.compl [TopologicalSpace α] {s : Set α} (hs : IsClopenable s) :
IsClopenable sᶜ := by
rcases hs with ⟨t, t_le, t_polish, h, h'⟩
exact ⟨t, t_le, t_polish, @IsOpen.isClosed_compl α t s h', @IsClosed.isOpen_compl α t s h⟩
#align polish_space.is_clopenable.compl PolishSpace.IsClopenable.compl
| Mathlib/Topology/MetricSpace/Polish.lean | 402 | 404 | theorem _root_.IsOpen.isClopenable [TopologicalSpace α] [PolishSpace α] {s : Set α}
(hs : IsOpen s) : IsClopenable s := by |
simpa using hs.isClosed_compl.isClopenable.compl
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Fintype.Option
import Mathlib.Data.Fintype.Prod
import Mathlib.Data.Fintype.Pi
import Mathlib.Data.Vector.Basic
import Mathlib.Data.PFun
import Mathlib.Logic.Function.Iterate
import Mathlib.Order.Basic
import Mathlib.Tactic.ApplyFun
#align_import computability.turing_machine from "leanprover-community/mathlib"@"4c19a16e4b705bf135cf9a80ac18fcc99c438514"
/-!
# Turing machines
This file defines a sequence of simple machine languages, starting with Turing machines and working
up to more complex languages based on Wang B-machines.
## Naming conventions
Each model of computation in this file shares a naming convention for the elements of a model of
computation. These are the parameters for the language:
* `Γ` is the alphabet on the tape.
* `Λ` is the set of labels, or internal machine states.
* `σ` is the type of internal memory, not on the tape. This does not exist in the TM0 model, and
later models achieve this by mixing it into `Λ`.
* `K` is used in the TM2 model, which has multiple stacks, and denotes the number of such stacks.
All of these variables denote "essentially finite" types, but for technical reasons it is
convenient to allow them to be infinite anyway. When using an infinite type, we will be interested
to prove that only finitely many values of the type are ever interacted with.
Given these parameters, there are a few common structures for the model that arise:
* `Stmt` is the set of all actions that can be performed in one step. For the TM0 model this set is
finite, and for later models it is an infinite inductive type representing "possible program
texts".
* `Cfg` is the set of instantaneous configurations, that is, the state of the machine together with
its environment.
* `Machine` is the set of all machines in the model. Usually this is approximately a function
`Λ → Stmt`, although different models have different ways of halting and other actions.
* `step : Cfg → Option Cfg` is the function that describes how the state evolves over one step.
If `step c = none`, then `c` is a terminal state, and the result of the computation is read off
from `c`. Because of the type of `step`, these models are all deterministic by construction.
* `init : Input → Cfg` sets up the initial state. The type `Input` depends on the model;
in most cases it is `List Γ`.
* `eval : Machine → Input → Part Output`, given a machine `M` and input `i`, starts from
`init i`, runs `step` until it reaches an output, and then applies a function `Cfg → Output` to
the final state to obtain the result. The type `Output` depends on the model.
* `Supports : Machine → Finset Λ → Prop` asserts that a machine `M` starts in `S : Finset Λ`, and
can only ever jump to other states inside `S`. This implies that the behavior of `M` on any input
cannot depend on its values outside `S`. We use this to allow `Λ` to be an infinite set when
convenient, and prove that only finitely many of these states are actually accessible. This
formalizes "essentially finite" mentioned above.
-/
assert_not_exists MonoidWithZero
open Relation
open Nat (iterate)
open Function (update iterate_succ iterate_succ_apply iterate_succ' iterate_succ_apply'
iterate_zero_apply)
namespace Turing
/-- The `BlankExtends` partial order holds of `l₁` and `l₂` if `l₂` is obtained by adding
blanks (`default : Γ`) to the end of `l₁`. -/
def BlankExtends {Γ} [Inhabited Γ] (l₁ l₂ : List Γ) : Prop :=
∃ n, l₂ = l₁ ++ List.replicate n default
#align turing.blank_extends Turing.BlankExtends
@[refl]
theorem BlankExtends.refl {Γ} [Inhabited Γ] (l : List Γ) : BlankExtends l l :=
⟨0, by simp⟩
#align turing.blank_extends.refl Turing.BlankExtends.refl
@[trans]
theorem BlankExtends.trans {Γ} [Inhabited Γ] {l₁ l₂ l₃ : List Γ} :
BlankExtends l₁ l₂ → BlankExtends l₂ l₃ → BlankExtends l₁ l₃ := by
rintro ⟨i, rfl⟩ ⟨j, rfl⟩
exact ⟨i + j, by simp [List.replicate_add]⟩
#align turing.blank_extends.trans Turing.BlankExtends.trans
theorem BlankExtends.below_of_le {Γ} [Inhabited Γ] {l l₁ l₂ : List Γ} :
BlankExtends l l₁ → BlankExtends l l₂ → l₁.length ≤ l₂.length → BlankExtends l₁ l₂ := by
rintro ⟨i, rfl⟩ ⟨j, rfl⟩ h; use j - i
simp only [List.length_append, Nat.add_le_add_iff_left, List.length_replicate] at h
simp only [← List.replicate_add, Nat.add_sub_cancel' h, List.append_assoc]
#align turing.blank_extends.below_of_le Turing.BlankExtends.below_of_le
/-- Any two extensions by blank `l₁,l₂` of `l` have a common join (which can be taken to be the
longer of `l₁` and `l₂`). -/
def BlankExtends.above {Γ} [Inhabited Γ] {l l₁ l₂ : List Γ} (h₁ : BlankExtends l l₁)
(h₂ : BlankExtends l l₂) : { l' // BlankExtends l₁ l' ∧ BlankExtends l₂ l' } :=
if h : l₁.length ≤ l₂.length then ⟨l₂, h₁.below_of_le h₂ h, BlankExtends.refl _⟩
else ⟨l₁, BlankExtends.refl _, h₂.below_of_le h₁ (le_of_not_ge h)⟩
#align turing.blank_extends.above Turing.BlankExtends.above
theorem BlankExtends.above_of_le {Γ} [Inhabited Γ] {l l₁ l₂ : List Γ} :
BlankExtends l₁ l → BlankExtends l₂ l → l₁.length ≤ l₂.length → BlankExtends l₁ l₂ := by
rintro ⟨i, rfl⟩ ⟨j, e⟩ h; use i - j
refine List.append_cancel_right (e.symm.trans ?_)
rw [List.append_assoc, ← List.replicate_add, Nat.sub_add_cancel]
apply_fun List.length at e
simp only [List.length_append, List.length_replicate] at e
rwa [← Nat.add_le_add_iff_left, e, Nat.add_le_add_iff_right]
#align turing.blank_extends.above_of_le Turing.BlankExtends.above_of_le
/-- `BlankRel` is the symmetric closure of `BlankExtends`, turning it into an equivalence
relation. Two lists are related by `BlankRel` if one extends the other by blanks. -/
def BlankRel {Γ} [Inhabited Γ] (l₁ l₂ : List Γ) : Prop :=
BlankExtends l₁ l₂ ∨ BlankExtends l₂ l₁
#align turing.blank_rel Turing.BlankRel
@[refl]
theorem BlankRel.refl {Γ} [Inhabited Γ] (l : List Γ) : BlankRel l l :=
Or.inl (BlankExtends.refl _)
#align turing.blank_rel.refl Turing.BlankRel.refl
@[symm]
theorem BlankRel.symm {Γ} [Inhabited Γ] {l₁ l₂ : List Γ} : BlankRel l₁ l₂ → BlankRel l₂ l₁ :=
Or.symm
#align turing.blank_rel.symm Turing.BlankRel.symm
@[trans]
theorem BlankRel.trans {Γ} [Inhabited Γ] {l₁ l₂ l₃ : List Γ} :
BlankRel l₁ l₂ → BlankRel l₂ l₃ → BlankRel l₁ l₃ := by
rintro (h₁ | h₁) (h₂ | h₂)
· exact Or.inl (h₁.trans h₂)
· rcases le_total l₁.length l₃.length with h | h
· exact Or.inl (h₁.above_of_le h₂ h)
· exact Or.inr (h₂.above_of_le h₁ h)
· rcases le_total l₁.length l₃.length with h | h
· exact Or.inl (h₁.below_of_le h₂ h)
· exact Or.inr (h₂.below_of_le h₁ h)
· exact Or.inr (h₂.trans h₁)
#align turing.blank_rel.trans Turing.BlankRel.trans
/-- Given two `BlankRel` lists, there exists (constructively) a common join. -/
def BlankRel.above {Γ} [Inhabited Γ] {l₁ l₂ : List Γ} (h : BlankRel l₁ l₂) :
{ l // BlankExtends l₁ l ∧ BlankExtends l₂ l } := by
refine
if hl : l₁.length ≤ l₂.length then ⟨l₂, Or.elim h id fun h' ↦ ?_, BlankExtends.refl _⟩
else ⟨l₁, BlankExtends.refl _, Or.elim h (fun h' ↦ ?_) id⟩
· exact (BlankExtends.refl _).above_of_le h' hl
· exact (BlankExtends.refl _).above_of_le h' (le_of_not_ge hl)
#align turing.blank_rel.above Turing.BlankRel.above
/-- Given two `BlankRel` lists, there exists (constructively) a common meet. -/
def BlankRel.below {Γ} [Inhabited Γ] {l₁ l₂ : List Γ} (h : BlankRel l₁ l₂) :
{ l // BlankExtends l l₁ ∧ BlankExtends l l₂ } := by
refine
if hl : l₁.length ≤ l₂.length then ⟨l₁, BlankExtends.refl _, Or.elim h id fun h' ↦ ?_⟩
else ⟨l₂, Or.elim h (fun h' ↦ ?_) id, BlankExtends.refl _⟩
· exact (BlankExtends.refl _).above_of_le h' hl
· exact (BlankExtends.refl _).above_of_le h' (le_of_not_ge hl)
#align turing.blank_rel.below Turing.BlankRel.below
theorem BlankRel.equivalence (Γ) [Inhabited Γ] : Equivalence (@BlankRel Γ _) :=
⟨BlankRel.refl, @BlankRel.symm _ _, @BlankRel.trans _ _⟩
#align turing.blank_rel.equivalence Turing.BlankRel.equivalence
/-- Construct a setoid instance for `BlankRel`. -/
def BlankRel.setoid (Γ) [Inhabited Γ] : Setoid (List Γ) :=
⟨_, BlankRel.equivalence _⟩
#align turing.blank_rel.setoid Turing.BlankRel.setoid
/-- A `ListBlank Γ` is a quotient of `List Γ` by extension by blanks at the end. This is used to
represent half-tapes of a Turing machine, so that we can pretend that the list continues
infinitely with blanks. -/
def ListBlank (Γ) [Inhabited Γ] :=
Quotient (BlankRel.setoid Γ)
#align turing.list_blank Turing.ListBlank
instance ListBlank.inhabited {Γ} [Inhabited Γ] : Inhabited (ListBlank Γ) :=
⟨Quotient.mk'' []⟩
#align turing.list_blank.inhabited Turing.ListBlank.inhabited
instance ListBlank.hasEmptyc {Γ} [Inhabited Γ] : EmptyCollection (ListBlank Γ) :=
⟨Quotient.mk'' []⟩
#align turing.list_blank.has_emptyc Turing.ListBlank.hasEmptyc
/-- A modified version of `Quotient.liftOn'` specialized for `ListBlank`, with the stronger
precondition `BlankExtends` instead of `BlankRel`. -/
-- Porting note: Removed `@[elab_as_elim]`
protected abbrev ListBlank.liftOn {Γ} [Inhabited Γ] {α} (l : ListBlank Γ) (f : List Γ → α)
(H : ∀ a b, BlankExtends a b → f a = f b) : α :=
l.liftOn' f <| by rintro a b (h | h) <;> [exact H _ _ h; exact (H _ _ h).symm]
#align turing.list_blank.lift_on Turing.ListBlank.liftOn
/-- The quotient map turning a `List` into a `ListBlank`. -/
def ListBlank.mk {Γ} [Inhabited Γ] : List Γ → ListBlank Γ :=
Quotient.mk''
#align turing.list_blank.mk Turing.ListBlank.mk
@[elab_as_elim]
protected theorem ListBlank.induction_on {Γ} [Inhabited Γ] {p : ListBlank Γ → Prop}
(q : ListBlank Γ) (h : ∀ a, p (ListBlank.mk a)) : p q :=
Quotient.inductionOn' q h
#align turing.list_blank.induction_on Turing.ListBlank.induction_on
/-- The head of a `ListBlank` is well defined. -/
def ListBlank.head {Γ} [Inhabited Γ] (l : ListBlank Γ) : Γ := by
apply l.liftOn List.headI
rintro a _ ⟨i, rfl⟩
cases a
· cases i <;> rfl
rfl
#align turing.list_blank.head Turing.ListBlank.head
@[simp]
theorem ListBlank.head_mk {Γ} [Inhabited Γ] (l : List Γ) :
ListBlank.head (ListBlank.mk l) = l.headI :=
rfl
#align turing.list_blank.head_mk Turing.ListBlank.head_mk
/-- The tail of a `ListBlank` is well defined (up to the tail of blanks). -/
def ListBlank.tail {Γ} [Inhabited Γ] (l : ListBlank Γ) : ListBlank Γ := by
apply l.liftOn (fun l ↦ ListBlank.mk l.tail)
rintro a _ ⟨i, rfl⟩
refine Quotient.sound' (Or.inl ?_)
cases a
· cases' i with i <;> [exact ⟨0, rfl⟩; exact ⟨i, rfl⟩]
exact ⟨i, rfl⟩
#align turing.list_blank.tail Turing.ListBlank.tail
@[simp]
theorem ListBlank.tail_mk {Γ} [Inhabited Γ] (l : List Γ) :
ListBlank.tail (ListBlank.mk l) = ListBlank.mk l.tail :=
rfl
#align turing.list_blank.tail_mk Turing.ListBlank.tail_mk
/-- We can cons an element onto a `ListBlank`. -/
def ListBlank.cons {Γ} [Inhabited Γ] (a : Γ) (l : ListBlank Γ) : ListBlank Γ := by
apply l.liftOn (fun l ↦ ListBlank.mk (List.cons a l))
rintro _ _ ⟨i, rfl⟩
exact Quotient.sound' (Or.inl ⟨i, rfl⟩)
#align turing.list_blank.cons Turing.ListBlank.cons
@[simp]
theorem ListBlank.cons_mk {Γ} [Inhabited Γ] (a : Γ) (l : List Γ) :
ListBlank.cons a (ListBlank.mk l) = ListBlank.mk (a :: l) :=
rfl
#align turing.list_blank.cons_mk Turing.ListBlank.cons_mk
@[simp]
theorem ListBlank.head_cons {Γ} [Inhabited Γ] (a : Γ) : ∀ l : ListBlank Γ, (l.cons a).head = a :=
Quotient.ind' fun _ ↦ rfl
#align turing.list_blank.head_cons Turing.ListBlank.head_cons
@[simp]
theorem ListBlank.tail_cons {Γ} [Inhabited Γ] (a : Γ) : ∀ l : ListBlank Γ, (l.cons a).tail = l :=
Quotient.ind' fun _ ↦ rfl
#align turing.list_blank.tail_cons Turing.ListBlank.tail_cons
/-- The `cons` and `head`/`tail` functions are mutually inverse, unlike in the case of `List` where
this only holds for nonempty lists. -/
@[simp]
theorem ListBlank.cons_head_tail {Γ} [Inhabited Γ] : ∀ l : ListBlank Γ, l.tail.cons l.head = l := by
apply Quotient.ind'
refine fun l ↦ Quotient.sound' (Or.inr ?_)
cases l
· exact ⟨1, rfl⟩
· rfl
#align turing.list_blank.cons_head_tail Turing.ListBlank.cons_head_tail
/-- The `cons` and `head`/`tail` functions are mutually inverse, unlike in the case of `List` where
this only holds for nonempty lists. -/
theorem ListBlank.exists_cons {Γ} [Inhabited Γ] (l : ListBlank Γ) :
∃ a l', l = ListBlank.cons a l' :=
⟨_, _, (ListBlank.cons_head_tail _).symm⟩
#align turing.list_blank.exists_cons Turing.ListBlank.exists_cons
/-- The n-th element of a `ListBlank` is well defined for all `n : ℕ`, unlike in a `List`. -/
def ListBlank.nth {Γ} [Inhabited Γ] (l : ListBlank Γ) (n : ℕ) : Γ := by
apply l.liftOn (fun l ↦ List.getI l n)
rintro l _ ⟨i, rfl⟩
cases' lt_or_le n _ with h h
· rw [List.getI_append _ _ _ h]
rw [List.getI_eq_default _ h]
rcases le_or_lt _ n with h₂ | h₂
· rw [List.getI_eq_default _ h₂]
rw [List.getI_eq_get _ h₂, List.get_append_right' h, List.get_replicate]
#align turing.list_blank.nth Turing.ListBlank.nth
@[simp]
theorem ListBlank.nth_mk {Γ} [Inhabited Γ] (l : List Γ) (n : ℕ) :
(ListBlank.mk l).nth n = l.getI n :=
rfl
#align turing.list_blank.nth_mk Turing.ListBlank.nth_mk
@[simp]
theorem ListBlank.nth_zero {Γ} [Inhabited Γ] (l : ListBlank Γ) : l.nth 0 = l.head := by
conv => lhs; rw [← ListBlank.cons_head_tail l]
exact Quotient.inductionOn' l.tail fun l ↦ rfl
#align turing.list_blank.nth_zero Turing.ListBlank.nth_zero
@[simp]
theorem ListBlank.nth_succ {Γ} [Inhabited Γ] (l : ListBlank Γ) (n : ℕ) :
l.nth (n + 1) = l.tail.nth n := by
conv => lhs; rw [← ListBlank.cons_head_tail l]
exact Quotient.inductionOn' l.tail fun l ↦ rfl
#align turing.list_blank.nth_succ Turing.ListBlank.nth_succ
@[ext]
theorem ListBlank.ext {Γ} [i : Inhabited Γ] {L₁ L₂ : ListBlank Γ} :
(∀ i, L₁.nth i = L₂.nth i) → L₁ = L₂ := by
refine ListBlank.induction_on L₁ fun l₁ ↦ ListBlank.induction_on L₂ fun l₂ H ↦ ?_
wlog h : l₁.length ≤ l₂.length
· cases le_total l₁.length l₂.length <;> [skip; symm] <;> apply this <;> try assumption
intro
rw [H]
refine Quotient.sound' (Or.inl ⟨l₂.length - l₁.length, ?_⟩)
refine List.ext_get ?_ fun i h h₂ ↦ Eq.symm ?_
· simp only [Nat.add_sub_cancel' h, List.length_append, List.length_replicate]
simp only [ListBlank.nth_mk] at H
cases' lt_or_le i l₁.length with h' h'
· simp only [List.get_append _ h', List.get?_eq_get h, List.get?_eq_get h',
← List.getI_eq_get _ h, ← List.getI_eq_get _ h', H]
· simp only [List.get_append_right' h', List.get_replicate, List.get?_eq_get h,
List.get?_len_le h', ← List.getI_eq_default _ h', H, List.getI_eq_get _ h]
#align turing.list_blank.ext Turing.ListBlank.ext
/-- Apply a function to a value stored at the nth position of the list. -/
@[simp]
def ListBlank.modifyNth {Γ} [Inhabited Γ] (f : Γ → Γ) : ℕ → ListBlank Γ → ListBlank Γ
| 0, L => L.tail.cons (f L.head)
| n + 1, L => (L.tail.modifyNth f n).cons L.head
#align turing.list_blank.modify_nth Turing.ListBlank.modifyNth
theorem ListBlank.nth_modifyNth {Γ} [Inhabited Γ] (f : Γ → Γ) (n i) (L : ListBlank Γ) :
(L.modifyNth f n).nth i = if i = n then f (L.nth i) else L.nth i := by
induction' n with n IH generalizing i L
· cases i <;> simp only [ListBlank.nth_zero, if_true, ListBlank.head_cons, ListBlank.modifyNth,
ListBlank.nth_succ, if_false, ListBlank.tail_cons, Nat.zero_eq]
· cases i
· rw [if_neg (Nat.succ_ne_zero _).symm]
simp only [ListBlank.nth_zero, ListBlank.head_cons, ListBlank.modifyNth, Nat.zero_eq]
· simp only [IH, ListBlank.modifyNth, ListBlank.nth_succ, ListBlank.tail_cons, Nat.succ.injEq]
#align turing.list_blank.nth_modify_nth Turing.ListBlank.nth_modifyNth
/-- A pointed map of `Inhabited` types is a map that sends one default value to the other. -/
structure PointedMap.{u, v} (Γ : Type u) (Γ' : Type v) [Inhabited Γ] [Inhabited Γ'] :
Type max u v where
/-- The map underlying this instance. -/
f : Γ → Γ'
map_pt' : f default = default
#align turing.pointed_map Turing.PointedMap
instance {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] : Inhabited (PointedMap Γ Γ') :=
⟨⟨default, rfl⟩⟩
instance {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] : CoeFun (PointedMap Γ Γ') fun _ ↦ Γ → Γ' :=
⟨PointedMap.f⟩
-- @[simp] -- Porting note (#10685): dsimp can prove this
theorem PointedMap.mk_val {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : Γ → Γ') (pt) :
(PointedMap.mk f pt : Γ → Γ') = f :=
rfl
#align turing.pointed_map.mk_val Turing.PointedMap.mk_val
@[simp]
theorem PointedMap.map_pt {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') :
f default = default :=
PointedMap.map_pt' _
#align turing.pointed_map.map_pt Turing.PointedMap.map_pt
@[simp]
theorem PointedMap.headI_map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ')
(l : List Γ) : (l.map f).headI = f l.headI := by
cases l <;> [exact (PointedMap.map_pt f).symm; rfl]
#align turing.pointed_map.head_map Turing.PointedMap.headI_map
/-- The `map` function on lists is well defined on `ListBlank`s provided that the map is
pointed. -/
def ListBlank.map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (l : ListBlank Γ) :
ListBlank Γ' := by
apply l.liftOn (fun l ↦ ListBlank.mk (List.map f l))
rintro l _ ⟨i, rfl⟩; refine Quotient.sound' (Or.inl ⟨i, ?_⟩)
simp only [PointedMap.map_pt, List.map_append, List.map_replicate]
#align turing.list_blank.map Turing.ListBlank.map
@[simp]
theorem ListBlank.map_mk {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (l : List Γ) :
(ListBlank.mk l).map f = ListBlank.mk (l.map f) :=
rfl
#align turing.list_blank.map_mk Turing.ListBlank.map_mk
@[simp]
theorem ListBlank.head_map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ')
(l : ListBlank Γ) : (l.map f).head = f l.head := by
conv => lhs; rw [← ListBlank.cons_head_tail l]
exact Quotient.inductionOn' l fun a ↦ rfl
#align turing.list_blank.head_map Turing.ListBlank.head_map
@[simp]
theorem ListBlank.tail_map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ')
(l : ListBlank Γ) : (l.map f).tail = l.tail.map f := by
conv => lhs; rw [← ListBlank.cons_head_tail l]
exact Quotient.inductionOn' l fun a ↦ rfl
#align turing.list_blank.tail_map Turing.ListBlank.tail_map
@[simp]
theorem ListBlank.map_cons {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ')
(l : ListBlank Γ) (a : Γ) : (l.cons a).map f = (l.map f).cons (f a) := by
refine (ListBlank.cons_head_tail _).symm.trans ?_
simp only [ListBlank.head_map, ListBlank.head_cons, ListBlank.tail_map, ListBlank.tail_cons]
#align turing.list_blank.map_cons Turing.ListBlank.map_cons
@[simp]
theorem ListBlank.nth_map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ')
(l : ListBlank Γ) (n : ℕ) : (l.map f).nth n = f (l.nth n) := by
refine l.inductionOn fun l ↦ ?_
-- Porting note: Added `suffices` to get `simp` to work.
suffices ((mk l).map f).nth n = f ((mk l).nth n) by exact this
simp only [List.get?_map, ListBlank.map_mk, ListBlank.nth_mk, List.getI_eq_iget_get?]
cases l.get? n
· exact f.2.symm
· rfl
#align turing.list_blank.nth_map Turing.ListBlank.nth_map
/-- The `i`-th projection as a pointed map. -/
def proj {ι : Type*} {Γ : ι → Type*} [∀ i, Inhabited (Γ i)] (i : ι) :
PointedMap (∀ i, Γ i) (Γ i) :=
⟨fun a ↦ a i, rfl⟩
#align turing.proj Turing.proj
theorem proj_map_nth {ι : Type*} {Γ : ι → Type*} [∀ i, Inhabited (Γ i)] (i : ι) (L n) :
(ListBlank.map (@proj ι Γ _ i) L).nth n = L.nth n i := by
rw [ListBlank.nth_map]; rfl
#align turing.proj_map_nth Turing.proj_map_nth
theorem ListBlank.map_modifyNth {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (F : PointedMap Γ Γ')
(f : Γ → Γ) (f' : Γ' → Γ') (H : ∀ x, F (f x) = f' (F x)) (n) (L : ListBlank Γ) :
(L.modifyNth f n).map F = (L.map F).modifyNth f' n := by
induction' n with n IH generalizing L <;>
simp only [*, ListBlank.head_map, ListBlank.modifyNth, ListBlank.map_cons, ListBlank.tail_map]
#align turing.list_blank.map_modify_nth Turing.ListBlank.map_modifyNth
/-- Append a list on the left side of a `ListBlank`. -/
@[simp]
def ListBlank.append {Γ} [Inhabited Γ] : List Γ → ListBlank Γ → ListBlank Γ
| [], L => L
| a :: l, L => ListBlank.cons a (ListBlank.append l L)
#align turing.list_blank.append Turing.ListBlank.append
@[simp]
theorem ListBlank.append_mk {Γ} [Inhabited Γ] (l₁ l₂ : List Γ) :
ListBlank.append l₁ (ListBlank.mk l₂) = ListBlank.mk (l₁ ++ l₂) := by
induction l₁ <;>
simp only [*, ListBlank.append, List.nil_append, List.cons_append, ListBlank.cons_mk]
#align turing.list_blank.append_mk Turing.ListBlank.append_mk
theorem ListBlank.append_assoc {Γ} [Inhabited Γ] (l₁ l₂ : List Γ) (l₃ : ListBlank Γ) :
ListBlank.append (l₁ ++ l₂) l₃ = ListBlank.append l₁ (ListBlank.append l₂ l₃) := by
refine l₃.inductionOn fun l ↦ ?_
-- Porting note: Added `suffices` to get `simp` to work.
suffices append (l₁ ++ l₂) (mk l) = append l₁ (append l₂ (mk l)) by exact this
simp only [ListBlank.append_mk, List.append_assoc]
#align turing.list_blank.append_assoc Turing.ListBlank.append_assoc
/-- The `bind` function on lists is well defined on `ListBlank`s provided that the default element
is sent to a sequence of default elements. -/
def ListBlank.bind {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (l : ListBlank Γ) (f : Γ → List Γ')
(hf : ∃ n, f default = List.replicate n default) : ListBlank Γ' := by
apply l.liftOn (fun l ↦ ListBlank.mk (List.bind l f))
rintro l _ ⟨i, rfl⟩; cases' hf with n e; refine Quotient.sound' (Or.inl ⟨i * n, ?_⟩)
rw [List.append_bind, mul_comm]; congr
induction' i with i IH
· rfl
simp only [IH, e, List.replicate_add, Nat.mul_succ, add_comm, List.replicate_succ, List.cons_bind]
#align turing.list_blank.bind Turing.ListBlank.bind
@[simp]
theorem ListBlank.bind_mk {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (l : List Γ) (f : Γ → List Γ') (hf) :
(ListBlank.mk l).bind f hf = ListBlank.mk (l.bind f) :=
rfl
#align turing.list_blank.bind_mk Turing.ListBlank.bind_mk
@[simp]
theorem ListBlank.cons_bind {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (a : Γ) (l : ListBlank Γ)
(f : Γ → List Γ') (hf) : (l.cons a).bind f hf = (l.bind f hf).append (f a) := by
refine l.inductionOn fun l ↦ ?_
-- Porting note: Added `suffices` to get `simp` to work.
suffices ((mk l).cons a).bind f hf = ((mk l).bind f hf).append (f a) by exact this
simp only [ListBlank.append_mk, ListBlank.bind_mk, ListBlank.cons_mk, List.cons_bind]
#align turing.list_blank.cons_bind Turing.ListBlank.cons_bind
/-- The tape of a Turing machine is composed of a head element (which we imagine to be the
current position of the head), together with two `ListBlank`s denoting the portions of the tape
going off to the left and right. When the Turing machine moves right, an element is pulled from the
right side and becomes the new head, while the head element is `cons`ed onto the left side. -/
structure Tape (Γ : Type*) [Inhabited Γ] where
/-- The current position of the head. -/
head : Γ
/-- The portion of the tape going off to the left. -/
left : ListBlank Γ
/-- The portion of the tape going off to the right. -/
right : ListBlank Γ
#align turing.tape Turing.Tape
instance Tape.inhabited {Γ} [Inhabited Γ] : Inhabited (Tape Γ) :=
⟨by constructor <;> apply default⟩
#align turing.tape.inhabited Turing.Tape.inhabited
/-- A direction for the Turing machine `move` command, either
left or right. -/
inductive Dir
| left
| right
deriving DecidableEq, Inhabited
#align turing.dir Turing.Dir
/-- The "inclusive" left side of the tape, including both `left` and `head`. -/
def Tape.left₀ {Γ} [Inhabited Γ] (T : Tape Γ) : ListBlank Γ :=
T.left.cons T.head
#align turing.tape.left₀ Turing.Tape.left₀
/-- The "inclusive" right side of the tape, including both `right` and `head`. -/
def Tape.right₀ {Γ} [Inhabited Γ] (T : Tape Γ) : ListBlank Γ :=
T.right.cons T.head
#align turing.tape.right₀ Turing.Tape.right₀
/-- Move the tape in response to a motion of the Turing machine. Note that `T.move Dir.left` makes
`T.left` smaller; the Turing machine is moving left and the tape is moving right. -/
def Tape.move {Γ} [Inhabited Γ] : Dir → Tape Γ → Tape Γ
| Dir.left, ⟨a, L, R⟩ => ⟨L.head, L.tail, R.cons a⟩
| Dir.right, ⟨a, L, R⟩ => ⟨R.head, L.cons a, R.tail⟩
#align turing.tape.move Turing.Tape.move
@[simp]
theorem Tape.move_left_right {Γ} [Inhabited Γ] (T : Tape Γ) :
(T.move Dir.left).move Dir.right = T := by
cases T; simp [Tape.move]
#align turing.tape.move_left_right Turing.Tape.move_left_right
@[simp]
theorem Tape.move_right_left {Γ} [Inhabited Γ] (T : Tape Γ) :
(T.move Dir.right).move Dir.left = T := by
cases T; simp [Tape.move]
#align turing.tape.move_right_left Turing.Tape.move_right_left
/-- Construct a tape from a left side and an inclusive right side. -/
def Tape.mk' {Γ} [Inhabited Γ] (L R : ListBlank Γ) : Tape Γ :=
⟨R.head, L, R.tail⟩
#align turing.tape.mk' Turing.Tape.mk'
@[simp]
theorem Tape.mk'_left {Γ} [Inhabited Γ] (L R : ListBlank Γ) : (Tape.mk' L R).left = L :=
rfl
#align turing.tape.mk'_left Turing.Tape.mk'_left
@[simp]
theorem Tape.mk'_head {Γ} [Inhabited Γ] (L R : ListBlank Γ) : (Tape.mk' L R).head = R.head :=
rfl
#align turing.tape.mk'_head Turing.Tape.mk'_head
@[simp]
theorem Tape.mk'_right {Γ} [Inhabited Γ] (L R : ListBlank Γ) : (Tape.mk' L R).right = R.tail :=
rfl
#align turing.tape.mk'_right Turing.Tape.mk'_right
@[simp]
theorem Tape.mk'_right₀ {Γ} [Inhabited Γ] (L R : ListBlank Γ) : (Tape.mk' L R).right₀ = R :=
ListBlank.cons_head_tail _
#align turing.tape.mk'_right₀ Turing.Tape.mk'_right₀
@[simp]
theorem Tape.mk'_left_right₀ {Γ} [Inhabited Γ] (T : Tape Γ) : Tape.mk' T.left T.right₀ = T := by
cases T
simp only [Tape.right₀, Tape.mk', ListBlank.head_cons, ListBlank.tail_cons, eq_self_iff_true,
and_self_iff]
#align turing.tape.mk'_left_right₀ Turing.Tape.mk'_left_right₀
theorem Tape.exists_mk' {Γ} [Inhabited Γ] (T : Tape Γ) : ∃ L R, T = Tape.mk' L R :=
⟨_, _, (Tape.mk'_left_right₀ _).symm⟩
#align turing.tape.exists_mk' Turing.Tape.exists_mk'
@[simp]
theorem Tape.move_left_mk' {Γ} [Inhabited Γ] (L R : ListBlank Γ) :
(Tape.mk' L R).move Dir.left = Tape.mk' L.tail (R.cons L.head) := by
simp only [Tape.move, Tape.mk', ListBlank.head_cons, eq_self_iff_true, ListBlank.cons_head_tail,
and_self_iff, ListBlank.tail_cons]
#align turing.tape.move_left_mk' Turing.Tape.move_left_mk'
@[simp]
theorem Tape.move_right_mk' {Γ} [Inhabited Γ] (L R : ListBlank Γ) :
(Tape.mk' L R).move Dir.right = Tape.mk' (L.cons R.head) R.tail := by
simp only [Tape.move, Tape.mk', ListBlank.head_cons, eq_self_iff_true, ListBlank.cons_head_tail,
and_self_iff, ListBlank.tail_cons]
#align turing.tape.move_right_mk' Turing.Tape.move_right_mk'
/-- Construct a tape from a left side and an inclusive right side. -/
def Tape.mk₂ {Γ} [Inhabited Γ] (L R : List Γ) : Tape Γ :=
Tape.mk' (ListBlank.mk L) (ListBlank.mk R)
#align turing.tape.mk₂ Turing.Tape.mk₂
/-- Construct a tape from a list, with the head of the list at the TM head and the rest going
to the right. -/
def Tape.mk₁ {Γ} [Inhabited Γ] (l : List Γ) : Tape Γ :=
Tape.mk₂ [] l
#align turing.tape.mk₁ Turing.Tape.mk₁
/-- The `nth` function of a tape is integer-valued, with index `0` being the head, negative indexes
on the left and positive indexes on the right. (Picture a number line.) -/
def Tape.nth {Γ} [Inhabited Γ] (T : Tape Γ) : ℤ → Γ
| 0 => T.head
| (n + 1 : ℕ) => T.right.nth n
| -(n + 1 : ℕ) => T.left.nth n
#align turing.tape.nth Turing.Tape.nth
@[simp]
theorem Tape.nth_zero {Γ} [Inhabited Γ] (T : Tape Γ) : T.nth 0 = T.1 :=
rfl
#align turing.tape.nth_zero Turing.Tape.nth_zero
theorem Tape.right₀_nth {Γ} [Inhabited Γ] (T : Tape Γ) (n : ℕ) : T.right₀.nth n = T.nth n := by
cases n <;> simp only [Tape.nth, Tape.right₀, Int.ofNat_zero, ListBlank.nth_zero,
ListBlank.nth_succ, ListBlank.head_cons, ListBlank.tail_cons, Nat.zero_eq]
#align turing.tape.right₀_nth Turing.Tape.right₀_nth
@[simp]
theorem Tape.mk'_nth_nat {Γ} [Inhabited Γ] (L R : ListBlank Γ) (n : ℕ) :
(Tape.mk' L R).nth n = R.nth n := by
rw [← Tape.right₀_nth, Tape.mk'_right₀]
#align turing.tape.mk'_nth_nat Turing.Tape.mk'_nth_nat
@[simp]
theorem Tape.move_left_nth {Γ} [Inhabited Γ] :
∀ (T : Tape Γ) (i : ℤ), (T.move Dir.left).nth i = T.nth (i - 1)
| ⟨_, L, _⟩, -(n + 1 : ℕ) => (ListBlank.nth_succ _ _).symm
| ⟨_, L, _⟩, 0 => (ListBlank.nth_zero _).symm
| ⟨a, L, R⟩, 1 => (ListBlank.nth_zero _).trans (ListBlank.head_cons _ _)
| ⟨a, L, R⟩, (n + 1 : ℕ) + 1 => by
rw [add_sub_cancel_right]
change (R.cons a).nth (n + 1) = R.nth n
rw [ListBlank.nth_succ, ListBlank.tail_cons]
#align turing.tape.move_left_nth Turing.Tape.move_left_nth
@[simp]
theorem Tape.move_right_nth {Γ} [Inhabited Γ] (T : Tape Γ) (i : ℤ) :
(T.move Dir.right).nth i = T.nth (i + 1) := by
conv => rhs; rw [← T.move_right_left]
rw [Tape.move_left_nth, add_sub_cancel_right]
#align turing.tape.move_right_nth Turing.Tape.move_right_nth
@[simp]
theorem Tape.move_right_n_head {Γ} [Inhabited Γ] (T : Tape Γ) (i : ℕ) :
((Tape.move Dir.right)^[i] T).head = T.nth i := by
induction i generalizing T
· rfl
· simp only [*, Tape.move_right_nth, Int.ofNat_succ, iterate_succ, Function.comp_apply]
#align turing.tape.move_right_n_head Turing.Tape.move_right_n_head
/-- Replace the current value of the head on the tape. -/
def Tape.write {Γ} [Inhabited Γ] (b : Γ) (T : Tape Γ) : Tape Γ :=
{ T with head := b }
#align turing.tape.write Turing.Tape.write
@[simp]
theorem Tape.write_self {Γ} [Inhabited Γ] : ∀ T : Tape Γ, T.write T.1 = T := by
rintro ⟨⟩; rfl
#align turing.tape.write_self Turing.Tape.write_self
@[simp]
theorem Tape.write_nth {Γ} [Inhabited Γ] (b : Γ) :
∀ (T : Tape Γ) {i : ℤ}, (T.write b).nth i = if i = 0 then b else T.nth i
| _, 0 => rfl
| _, (_ + 1 : ℕ) => rfl
| _, -(_ + 1 : ℕ) => rfl
#align turing.tape.write_nth Turing.Tape.write_nth
@[simp]
theorem Tape.write_mk' {Γ} [Inhabited Γ] (a b : Γ) (L R : ListBlank Γ) :
(Tape.mk' L (R.cons a)).write b = Tape.mk' L (R.cons b) := by
simp only [Tape.write, Tape.mk', ListBlank.head_cons, ListBlank.tail_cons, eq_self_iff_true,
and_self_iff]
#align turing.tape.write_mk' Turing.Tape.write_mk'
/-- Apply a pointed map to a tape to change the alphabet. -/
def Tape.map {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (T : Tape Γ) : Tape Γ' :=
⟨f T.1, T.2.map f, T.3.map f⟩
#align turing.tape.map Turing.Tape.map
@[simp]
theorem Tape.map_fst {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') :
∀ T : Tape Γ, (T.map f).1 = f T.1 := by
rintro ⟨⟩; rfl
#align turing.tape.map_fst Turing.Tape.map_fst
@[simp]
theorem Tape.map_write {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (b : Γ) :
∀ T : Tape Γ, (T.write b).map f = (T.map f).write (f b) := by
rintro ⟨⟩; rfl
#align turing.tape.map_write Turing.Tape.map_write
-- Porting note: `simpNF` complains about LHS does not simplify when using the simp lemma on
-- itself, but it does indeed.
@[simp, nolint simpNF]
theorem Tape.write_move_right_n {Γ} [Inhabited Γ] (f : Γ → Γ) (L R : ListBlank Γ) (n : ℕ) :
((Tape.move Dir.right)^[n] (Tape.mk' L R)).write (f (R.nth n)) =
(Tape.move Dir.right)^[n] (Tape.mk' L (R.modifyNth f n)) := by
induction' n with n IH generalizing L R
· simp only [ListBlank.nth_zero, ListBlank.modifyNth, iterate_zero_apply, Nat.zero_eq]
rw [← Tape.write_mk', ListBlank.cons_head_tail]
simp only [ListBlank.head_cons, ListBlank.nth_succ, ListBlank.modifyNth, Tape.move_right_mk',
ListBlank.tail_cons, iterate_succ_apply, IH]
#align turing.tape.write_move_right_n Turing.Tape.write_move_right_n
theorem Tape.map_move {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (T : Tape Γ) (d) :
(T.move d).map f = (T.map f).move d := by
cases T
cases d <;> simp only [Tape.move, Tape.map, ListBlank.head_map, eq_self_iff_true,
ListBlank.map_cons, and_self_iff, ListBlank.tail_map]
#align turing.tape.map_move Turing.Tape.map_move
theorem Tape.map_mk' {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (L R : ListBlank Γ) :
(Tape.mk' L R).map f = Tape.mk' (L.map f) (R.map f) := by
simp only [Tape.mk', Tape.map, ListBlank.head_map, eq_self_iff_true, and_self_iff,
ListBlank.tail_map]
#align turing.tape.map_mk' Turing.Tape.map_mk'
theorem Tape.map_mk₂ {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (L R : List Γ) :
(Tape.mk₂ L R).map f = Tape.mk₂ (L.map f) (R.map f) := by
simp only [Tape.mk₂, Tape.map_mk', ListBlank.map_mk]
#align turing.tape.map_mk₂ Turing.Tape.map_mk₂
theorem Tape.map_mk₁ {Γ Γ'} [Inhabited Γ] [Inhabited Γ'] (f : PointedMap Γ Γ') (l : List Γ) :
(Tape.mk₁ l).map f = Tape.mk₁ (l.map f) :=
Tape.map_mk₂ _ _ _
#align turing.tape.map_mk₁ Turing.Tape.map_mk₁
/-- Run a state transition function `σ → Option σ` "to completion". The return value is the last
state returned before a `none` result. If the state transition function always returns `some`,
then the computation diverges, returning `Part.none`. -/
def eval {σ} (f : σ → Option σ) : σ → Part σ :=
PFun.fix fun s ↦ Part.some <| (f s).elim (Sum.inl s) Sum.inr
#align turing.eval Turing.eval
/-- The reflexive transitive closure of a state transition function. `Reaches f a b` means
there is a finite sequence of steps `f a = some a₁`, `f a₁ = some a₂`, ... such that `aₙ = b`.
This relation permits zero steps of the state transition function. -/
def Reaches {σ} (f : σ → Option σ) : σ → σ → Prop :=
ReflTransGen fun a b ↦ b ∈ f a
#align turing.reaches Turing.Reaches
/-- The transitive closure of a state transition function. `Reaches₁ f a b` means there is a
nonempty finite sequence of steps `f a = some a₁`, `f a₁ = some a₂`, ... such that `aₙ = b`.
This relation does not permit zero steps of the state transition function. -/
def Reaches₁ {σ} (f : σ → Option σ) : σ → σ → Prop :=
TransGen fun a b ↦ b ∈ f a
#align turing.reaches₁ Turing.Reaches₁
theorem reaches₁_eq {σ} {f : σ → Option σ} {a b c} (h : f a = f b) :
Reaches₁ f a c ↔ Reaches₁ f b c :=
TransGen.head'_iff.trans (TransGen.head'_iff.trans <| by rw [h]).symm
#align turing.reaches₁_eq Turing.reaches₁_eq
theorem reaches_total {σ} {f : σ → Option σ} {a b c} (hab : Reaches f a b) (hac : Reaches f a c) :
Reaches f b c ∨ Reaches f c b :=
ReflTransGen.total_of_right_unique (fun _ _ _ ↦ Option.mem_unique) hab hac
#align turing.reaches_total Turing.reaches_total
theorem reaches₁_fwd {σ} {f : σ → Option σ} {a b c} (h₁ : Reaches₁ f a c) (h₂ : b ∈ f a) :
Reaches f b c := by
rcases TransGen.head'_iff.1 h₁ with ⟨b', hab, hbc⟩
cases Option.mem_unique hab h₂; exact hbc
#align turing.reaches₁_fwd Turing.reaches₁_fwd
/-- A variation on `Reaches`. `Reaches₀ f a b` holds if whenever `Reaches₁ f b c` then
`Reaches₁ f a c`. This is a weaker property than `Reaches` and is useful for replacing states with
equivalent states without taking a step. -/
def Reaches₀ {σ} (f : σ → Option σ) (a b : σ) : Prop :=
∀ c, Reaches₁ f b c → Reaches₁ f a c
#align turing.reaches₀ Turing.Reaches₀
theorem Reaches₀.trans {σ} {f : σ → Option σ} {a b c : σ} (h₁ : Reaches₀ f a b)
(h₂ : Reaches₀ f b c) : Reaches₀ f a c
| _, h₃ => h₁ _ (h₂ _ h₃)
#align turing.reaches₀.trans Turing.Reaches₀.trans
@[refl]
theorem Reaches₀.refl {σ} {f : σ → Option σ} (a : σ) : Reaches₀ f a a
| _, h => h
#align turing.reaches₀.refl Turing.Reaches₀.refl
theorem Reaches₀.single {σ} {f : σ → Option σ} {a b : σ} (h : b ∈ f a) : Reaches₀ f a b
| _, h₂ => h₂.head h
#align turing.reaches₀.single Turing.Reaches₀.single
theorem Reaches₀.head {σ} {f : σ → Option σ} {a b c : σ} (h : b ∈ f a) (h₂ : Reaches₀ f b c) :
Reaches₀ f a c :=
(Reaches₀.single h).trans h₂
#align turing.reaches₀.head Turing.Reaches₀.head
theorem Reaches₀.tail {σ} {f : σ → Option σ} {a b c : σ} (h₁ : Reaches₀ f a b) (h : c ∈ f b) :
Reaches₀ f a c :=
h₁.trans (Reaches₀.single h)
#align turing.reaches₀.tail Turing.Reaches₀.tail
theorem reaches₀_eq {σ} {f : σ → Option σ} {a b} (e : f a = f b) : Reaches₀ f a b
| _, h => (reaches₁_eq e).2 h
#align turing.reaches₀_eq Turing.reaches₀_eq
theorem Reaches₁.to₀ {σ} {f : σ → Option σ} {a b : σ} (h : Reaches₁ f a b) : Reaches₀ f a b
| _, h₂ => h.trans h₂
#align turing.reaches₁.to₀ Turing.Reaches₁.to₀
theorem Reaches.to₀ {σ} {f : σ → Option σ} {a b : σ} (h : Reaches f a b) : Reaches₀ f a b
| _, h₂ => h₂.trans_right h
#align turing.reaches.to₀ Turing.Reaches.to₀
theorem Reaches₀.tail' {σ} {f : σ → Option σ} {a b c : σ} (h : Reaches₀ f a b) (h₂ : c ∈ f b) :
Reaches₁ f a c :=
h _ (TransGen.single h₂)
#align turing.reaches₀.tail' Turing.Reaches₀.tail'
/-- (co-)Induction principle for `eval`. If a property `C` holds of any point `a` evaluating to `b`
which is either terminal (meaning `a = b`) or where the next point also satisfies `C`, then it
holds of any point where `eval f a` evaluates to `b`. This formalizes the notion that if
`eval f a` evaluates to `b` then it reaches terminal state `b` in finitely many steps. -/
@[elab_as_elim]
def evalInduction {σ} {f : σ → Option σ} {b : σ} {C : σ → Sort*} {a : σ}
(h : b ∈ eval f a) (H : ∀ a, b ∈ eval f a → (∀ a', f a = some a' → C a') → C a) : C a :=
PFun.fixInduction h fun a' ha' h' ↦
H _ ha' fun b' e ↦ h' _ <| Part.mem_some_iff.2 <| by rw [e]; rfl
#align turing.eval_induction Turing.evalInduction
theorem mem_eval {σ} {f : σ → Option σ} {a b} : b ∈ eval f a ↔ Reaches f a b ∧ f b = none := by
refine ⟨fun h ↦ ?_, fun ⟨h₁, h₂⟩ ↦ ?_⟩
· -- Porting note: Explicitly specify `c`.
refine @evalInduction _ _ _ (fun a ↦ Reaches f a b ∧ f b = none) _ h fun a h IH ↦ ?_
cases' e : f a with a'
· rw [Part.mem_unique h
(PFun.mem_fix_iff.2 <| Or.inl <| Part.mem_some_iff.2 <| by rw [e] <;> rfl)]
exact ⟨ReflTransGen.refl, e⟩
· rcases PFun.mem_fix_iff.1 h with (h | ⟨_, h, _⟩) <;> rw [e] at h <;>
cases Part.mem_some_iff.1 h
cases' IH a' e with h₁ h₂
exact ⟨ReflTransGen.head e h₁, h₂⟩
· refine ReflTransGen.head_induction_on h₁ ?_ fun h _ IH ↦ ?_
· refine PFun.mem_fix_iff.2 (Or.inl ?_)
rw [h₂]
apply Part.mem_some
· refine PFun.mem_fix_iff.2 (Or.inr ⟨_, ?_, IH⟩)
rw [h]
apply Part.mem_some
#align turing.mem_eval Turing.mem_eval
theorem eval_maximal₁ {σ} {f : σ → Option σ} {a b} (h : b ∈ eval f a) (c) : ¬Reaches₁ f b c
| bc => by
let ⟨_, b0⟩ := mem_eval.1 h
let ⟨b', h', _⟩ := TransGen.head'_iff.1 bc
cases b0.symm.trans h'
#align turing.eval_maximal₁ Turing.eval_maximal₁
theorem eval_maximal {σ} {f : σ → Option σ} {a b} (h : b ∈ eval f a) {c} : Reaches f b c ↔ c = b :=
let ⟨_, b0⟩ := mem_eval.1 h
reflTransGen_iff_eq fun b' h' ↦ by cases b0.symm.trans h'
#align turing.eval_maximal Turing.eval_maximal
theorem reaches_eval {σ} {f : σ → Option σ} {a b} (ab : Reaches f a b) : eval f a = eval f b := by
refine Part.ext fun _ ↦ ⟨fun h ↦ ?_, fun h ↦ ?_⟩
· have ⟨ac, c0⟩ := mem_eval.1 h
exact mem_eval.2 ⟨(or_iff_left_of_imp fun cb ↦ (eval_maximal h).1 cb ▸ ReflTransGen.refl).1
(reaches_total ab ac), c0⟩
· have ⟨bc, c0⟩ := mem_eval.1 h
exact mem_eval.2 ⟨ab.trans bc, c0⟩
#align turing.reaches_eval Turing.reaches_eval
/-- Given a relation `tr : σ₁ → σ₂ → Prop` between state spaces, and state transition functions
`f₁ : σ₁ → Option σ₁` and `f₂ : σ₂ → Option σ₂`, `Respects f₁ f₂ tr` means that if `tr a₁ a₂` holds
initially and `f₁` takes a step to `a₂` then `f₂` will take one or more steps before reaching a
state `b₂` satisfying `tr a₂ b₂`, and if `f₁ a₁` terminates then `f₂ a₂` also terminates.
Such a relation `tr` is also known as a refinement. -/
def Respects {σ₁ σ₂} (f₁ : σ₁ → Option σ₁) (f₂ : σ₂ → Option σ₂) (tr : σ₁ → σ₂ → Prop) :=
∀ ⦃a₁ a₂⦄, tr a₁ a₂ → (match f₁ a₁ with
| some b₁ => ∃ b₂, tr b₁ b₂ ∧ Reaches₁ f₂ a₂ b₂
| none => f₂ a₂ = none : Prop)
#align turing.respects Turing.Respects
theorem tr_reaches₁ {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ a₂}
(aa : tr a₁ a₂) {b₁} (ab : Reaches₁ f₁ a₁ b₁) : ∃ b₂, tr b₁ b₂ ∧ Reaches₁ f₂ a₂ b₂ := by
induction' ab with c₁ ac c₁ d₁ _ cd IH
· have := H aa
rwa [show f₁ a₁ = _ from ac] at this
· rcases IH with ⟨c₂, cc, ac₂⟩
have := H cc
rw [show f₁ c₁ = _ from cd] at this
rcases this with ⟨d₂, dd, cd₂⟩
exact ⟨_, dd, ac₂.trans cd₂⟩
#align turing.tr_reaches₁ Turing.tr_reaches₁
theorem tr_reaches {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ a₂}
(aa : tr a₁ a₂) {b₁} (ab : Reaches f₁ a₁ b₁) : ∃ b₂, tr b₁ b₂ ∧ Reaches f₂ a₂ b₂ := by
rcases reflTransGen_iff_eq_or_transGen.1 ab with (rfl | ab)
· exact ⟨_, aa, ReflTransGen.refl⟩
· have ⟨b₂, bb, h⟩ := tr_reaches₁ H aa ab
exact ⟨b₂, bb, h.to_reflTransGen⟩
#align turing.tr_reaches Turing.tr_reaches
theorem tr_reaches_rev {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ a₂}
(aa : tr a₁ a₂) {b₂} (ab : Reaches f₂ a₂ b₂) :
∃ c₁ c₂, Reaches f₂ b₂ c₂ ∧ tr c₁ c₂ ∧ Reaches f₁ a₁ c₁ := by
induction' ab with c₂ d₂ _ cd IH
· exact ⟨_, _, ReflTransGen.refl, aa, ReflTransGen.refl⟩
· rcases IH with ⟨e₁, e₂, ce, ee, ae⟩
rcases ReflTransGen.cases_head ce with (rfl | ⟨d', cd', de⟩)
· have := H ee
revert this
cases' eg : f₁ e₁ with g₁ <;> simp only [Respects, and_imp, exists_imp]
· intro c0
cases cd.symm.trans c0
· intro g₂ gg cg
rcases TransGen.head'_iff.1 cg with ⟨d', cd', dg⟩
cases Option.mem_unique cd cd'
exact ⟨_, _, dg, gg, ae.tail eg⟩
· cases Option.mem_unique cd cd'
exact ⟨_, _, de, ee, ae⟩
#align turing.tr_reaches_rev Turing.tr_reaches_rev
theorem tr_eval {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ b₁ a₂}
(aa : tr a₁ a₂) (ab : b₁ ∈ eval f₁ a₁) : ∃ b₂, tr b₁ b₂ ∧ b₂ ∈ eval f₂ a₂ := by
cases' mem_eval.1 ab with ab b0
rcases tr_reaches H aa ab with ⟨b₂, bb, ab⟩
refine ⟨_, bb, mem_eval.2 ⟨ab, ?_⟩⟩
have := H bb; rwa [b0] at this
#align turing.tr_eval Turing.tr_eval
theorem tr_eval_rev {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ b₂ a₂}
(aa : tr a₁ a₂) (ab : b₂ ∈ eval f₂ a₂) : ∃ b₁, tr b₁ b₂ ∧ b₁ ∈ eval f₁ a₁ := by
cases' mem_eval.1 ab with ab b0
rcases tr_reaches_rev H aa ab with ⟨c₁, c₂, bc, cc, ac⟩
cases (reflTransGen_iff_eq (Option.eq_none_iff_forall_not_mem.1 b0)).1 bc
refine ⟨_, cc, mem_eval.2 ⟨ac, ?_⟩⟩
have := H cc
cases' hfc : f₁ c₁ with d₁
· rfl
rw [hfc] at this
rcases this with ⟨d₂, _, bd⟩
rcases TransGen.head'_iff.1 bd with ⟨e, h, _⟩
cases b0.symm.trans h
#align turing.tr_eval_rev Turing.tr_eval_rev
theorem tr_eval_dom {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂ → Prop} (H : Respects f₁ f₂ tr) {a₁ a₂}
(aa : tr a₁ a₂) : (eval f₂ a₂).Dom ↔ (eval f₁ a₁).Dom :=
⟨fun h ↦
let ⟨_, _, h, _⟩ := tr_eval_rev H aa ⟨h, rfl⟩
h,
fun h ↦
let ⟨_, _, h, _⟩ := tr_eval H aa ⟨h, rfl⟩
h⟩
#align turing.tr_eval_dom Turing.tr_eval_dom
/-- A simpler version of `Respects` when the state transition relation `tr` is a function. -/
def FRespects {σ₁ σ₂} (f₂ : σ₂ → Option σ₂) (tr : σ₁ → σ₂) (a₂ : σ₂) : Option σ₁ → Prop
| some b₁ => Reaches₁ f₂ a₂ (tr b₁)
| none => f₂ a₂ = none
#align turing.frespects Turing.FRespects
theorem frespects_eq {σ₁ σ₂} {f₂ : σ₂ → Option σ₂} {tr : σ₁ → σ₂} {a₂ b₂} (h : f₂ a₂ = f₂ b₂) :
∀ {b₁}, FRespects f₂ tr a₂ b₁ ↔ FRespects f₂ tr b₂ b₁
| some b₁ => reaches₁_eq h
| none => by unfold FRespects; rw [h]
#align turing.frespects_eq Turing.frespects_eq
theorem fun_respects {σ₁ σ₂ f₁ f₂} {tr : σ₁ → σ₂} :
(Respects f₁ f₂ fun a b ↦ tr a = b) ↔ ∀ ⦃a₁⦄, FRespects f₂ tr (tr a₁) (f₁ a₁) :=
forall_congr' fun a₁ ↦ by
cases f₁ a₁ <;> simp only [FRespects, Respects, exists_eq_left', forall_eq']
#align turing.fun_respects Turing.fun_respects
theorem tr_eval' {σ₁ σ₂} (f₁ : σ₁ → Option σ₁) (f₂ : σ₂ → Option σ₂) (tr : σ₁ → σ₂)
(H : Respects f₁ f₂ fun a b ↦ tr a = b) (a₁) : eval f₂ (tr a₁) = tr <$> eval f₁ a₁ :=
Part.ext fun b₂ ↦
⟨fun h ↦
let ⟨b₁, bb, hb⟩ := tr_eval_rev H rfl h
(Part.mem_map_iff _).2 ⟨b₁, hb, bb⟩,
fun h ↦ by
rcases (Part.mem_map_iff _).1 h with ⟨b₁, ab, bb⟩
rcases tr_eval H rfl ab with ⟨_, rfl, h⟩
rwa [bb] at h⟩
#align turing.tr_eval' Turing.tr_eval'
/-!
## The TM0 model
A TM0 Turing machine is essentially a Post-Turing machine, adapted for type theory.
A Post-Turing machine with symbol type `Γ` and label type `Λ` is a function
`Λ → Γ → Option (Λ × Stmt)`, where a `Stmt` can be either `move left`, `move right` or `write a`
for `a : Γ`. The machine works over a "tape", a doubly-infinite sequence of elements of `Γ`, and
an instantaneous configuration, `Cfg`, is a label `q : Λ` indicating the current internal state of
the machine, and a `Tape Γ` (which is essentially `ℤ →₀ Γ`). The evolution is described by the
`step` function:
* If `M q T.head = none`, then the machine halts.
* If `M q T.head = some (q', s)`, then the machine performs action `s : Stmt` and then transitions
to state `q'`.
The initial state takes a `List Γ` and produces a `Tape Γ` where the head of the list is the head
of the tape and the rest of the list extends to the right, with the left side all blank. The final
state takes the entire right side of the tape right or equal to the current position of the
machine. (This is actually a `ListBlank Γ`, not a `List Γ`, because we don't know, at this level
of generality, where the output ends. If equality to `default : Γ` is decidable we can trim the list
to remove the infinite tail of blanks.)
-/
namespace TM0
set_option linter.uppercaseLean3 false -- for "TM0"
section
-- type of tape symbols
variable (Γ : Type*) [Inhabited Γ]
-- type of "labels" or TM states
variable (Λ : Type*) [Inhabited Λ]
/-- A Turing machine "statement" is just a command to either move
left or right, or write a symbol on the tape. -/
inductive Stmt
| move : Dir → Stmt
| write : Γ → Stmt
#align turing.TM0.stmt Turing.TM0.Stmt
local notation "Stmt₀" => Stmt Γ -- Porting note (#10750): added this to clean up types.
instance Stmt.inhabited : Inhabited Stmt₀ :=
⟨Stmt.write default⟩
#align turing.TM0.stmt.inhabited Turing.TM0.Stmt.inhabited
/-- A Post-Turing machine with symbol type `Γ` and label type `Λ`
is a function which, given the current state `q : Λ` and
the tape head `a : Γ`, either halts (returns `none`) or returns
a new state `q' : Λ` and a `Stmt` describing what to do,
either a move left or right, or a write command.
Both `Λ` and `Γ` are required to be inhabited; the default value
for `Γ` is the "blank" tape value, and the default value of `Λ` is
the initial state. -/
@[nolint unusedArguments] -- this is a deliberate addition, see comment
def Machine [Inhabited Λ] :=
Λ → Γ → Option (Λ × Stmt₀)
#align turing.TM0.machine Turing.TM0.Machine
local notation "Machine₀" => Machine Γ Λ -- Porting note (#10750): added this to clean up types.
instance Machine.inhabited : Inhabited Machine₀ := by
unfold Machine; infer_instance
#align turing.TM0.machine.inhabited Turing.TM0.Machine.inhabited
/-- The configuration state of a Turing machine during operation
consists of a label (machine state), and a tape.
The tape is represented in the form `(a, L, R)`, meaning the tape looks like `L.rev ++ [a] ++ R`
with the machine currently reading the `a`. The lists are
automatically extended with blanks as the machine moves around. -/
structure Cfg where
/-- The current machine state. -/
q : Λ
/-- The current state of the tape: current symbol, left and right parts. -/
Tape : Tape Γ
#align turing.TM0.cfg Turing.TM0.Cfg
local notation "Cfg₀" => Cfg Γ Λ -- Porting note (#10750): added this to clean up types.
instance Cfg.inhabited : Inhabited Cfg₀ :=
⟨⟨default, default⟩⟩
#align turing.TM0.cfg.inhabited Turing.TM0.Cfg.inhabited
variable {Γ Λ}
/-- Execution semantics of the Turing machine. -/
def step (M : Machine₀) : Cfg₀ → Option Cfg₀ :=
fun ⟨q, T⟩ ↦ (M q T.1).map fun ⟨q', a⟩ ↦ ⟨q', match a with
| Stmt.move d => T.move d
| Stmt.write a => T.write a⟩
#align turing.TM0.step Turing.TM0.step
/-- The statement `Reaches M s₁ s₂` means that `s₂` is obtained
starting from `s₁` after a finite number of steps from `s₂`. -/
def Reaches (M : Machine₀) : Cfg₀ → Cfg₀ → Prop :=
ReflTransGen fun a b ↦ b ∈ step M a
#align turing.TM0.reaches Turing.TM0.Reaches
/-- The initial configuration. -/
def init (l : List Γ) : Cfg₀ :=
⟨default, Tape.mk₁ l⟩
#align turing.TM0.init Turing.TM0.init
/-- Evaluate a Turing machine on initial input to a final state,
if it terminates. -/
def eval (M : Machine₀) (l : List Γ) : Part (ListBlank Γ) :=
(Turing.eval (step M) (init l)).map fun c ↦ c.Tape.right₀
#align turing.TM0.eval Turing.TM0.eval
/-- The raw definition of a Turing machine does not require that
`Γ` and `Λ` are finite, and in practice we will be interested
in the infinite `Λ` case. We recover instead a notion of
"effectively finite" Turing machines, which only make use of a
finite subset of their states. We say that a set `S ⊆ Λ`
supports a Turing machine `M` if `S` is closed under the
transition function and contains the initial state. -/
def Supports (M : Machine₀) (S : Set Λ) :=
default ∈ S ∧ ∀ {q a q' s}, (q', s) ∈ M q a → q ∈ S → q' ∈ S
#align turing.TM0.supports Turing.TM0.Supports
theorem step_supports (M : Machine₀) {S : Set Λ} (ss : Supports M S) :
∀ {c c' : Cfg₀}, c' ∈ step M c → c.q ∈ S → c'.q ∈ S := by
intro ⟨q, T⟩ c' h₁ h₂
rcases Option.map_eq_some'.1 h₁ with ⟨⟨q', a⟩, h, rfl⟩
exact ss.2 h h₂
#align turing.TM0.step_supports Turing.TM0.step_supports
theorem univ_supports (M : Machine₀) : Supports M Set.univ := by
constructor <;> intros <;> apply Set.mem_univ
#align turing.TM0.univ_supports Turing.TM0.univ_supports
end
section
variable {Γ : Type*} [Inhabited Γ]
variable {Γ' : Type*} [Inhabited Γ']
variable {Λ : Type*} [Inhabited Λ]
variable {Λ' : Type*} [Inhabited Λ']
/-- Map a TM statement across a function. This does nothing to move statements and maps the write
values. -/
def Stmt.map (f : PointedMap Γ Γ') : Stmt Γ → Stmt Γ'
| Stmt.move d => Stmt.move d
| Stmt.write a => Stmt.write (f a)
#align turing.TM0.stmt.map Turing.TM0.Stmt.map
/-- Map a configuration across a function, given `f : Γ → Γ'` a map of the alphabets and
`g : Λ → Λ'` a map of the machine states. -/
def Cfg.map (f : PointedMap Γ Γ') (g : Λ → Λ') : Cfg Γ Λ → Cfg Γ' Λ'
| ⟨q, T⟩ => ⟨g q, T.map f⟩
#align turing.TM0.cfg.map Turing.TM0.Cfg.map
variable (M : Machine Γ Λ) (f₁ : PointedMap Γ Γ') (f₂ : PointedMap Γ' Γ) (g₁ : Λ → Λ') (g₂ : Λ' → Λ)
/-- Because the state transition function uses the alphabet and machine states in both the input
and output, to map a machine from one alphabet and machine state space to another we need functions
in both directions, essentially an `Equiv` without the laws. -/
def Machine.map : Machine Γ' Λ'
| q, l => (M (g₂ q) (f₂ l)).map (Prod.map g₁ (Stmt.map f₁))
#align turing.TM0.machine.map Turing.TM0.Machine.map
theorem Machine.map_step {S : Set Λ} (f₂₁ : Function.RightInverse f₁ f₂)
(g₂₁ : ∀ q ∈ S, g₂ (g₁ q) = q) :
∀ c : Cfg Γ Λ,
c.q ∈ S → (step M c).map (Cfg.map f₁ g₁) = step (M.map f₁ f₂ g₁ g₂) (Cfg.map f₁ g₁ c)
| ⟨q, T⟩, h => by
unfold step Machine.map Cfg.map
simp only [Turing.Tape.map_fst, g₂₁ q h, f₂₁ _]
rcases M q T.1 with (_ | ⟨q', d | a⟩); · rfl
· simp only [step, Cfg.map, Option.map_some', Tape.map_move f₁]
rfl
· simp only [step, Cfg.map, Option.map_some', Tape.map_write]
rfl
#align turing.TM0.machine.map_step Turing.TM0.Machine.map_step
theorem map_init (g₁ : PointedMap Λ Λ') (l : List Γ) : (init l).map f₁ g₁ = init (l.map f₁) :=
congr (congr_arg Cfg.mk g₁.map_pt) (Tape.map_mk₁ _ _)
#align turing.TM0.map_init Turing.TM0.map_init
theorem Machine.map_respects (g₁ : PointedMap Λ Λ') (g₂ : Λ' → Λ) {S} (ss : Supports M S)
(f₂₁ : Function.RightInverse f₁ f₂) (g₂₁ : ∀ q ∈ S, g₂ (g₁ q) = q) :
Respects (step M) (step (M.map f₁ f₂ g₁ g₂)) fun a b ↦ a.q ∈ S ∧ Cfg.map f₁ g₁ a = b := by
intro c _ ⟨cs, rfl⟩
cases e : step M c
· rw [← M.map_step f₁ f₂ g₁ g₂ f₂₁ g₂₁ _ cs, e]
rfl
· refine ⟨_, ⟨step_supports M ss e cs, rfl⟩, TransGen.single ?_⟩
rw [← M.map_step f₁ f₂ g₁ g₂ f₂₁ g₂₁ _ cs, e]
rfl
#align turing.TM0.machine.map_respects Turing.TM0.Machine.map_respects
end
end TM0
/-!
## The TM1 model
The TM1 model is a simplification and extension of TM0 (Post-Turing model) in the direction of
Wang B-machines. The machine's internal state is extended with a (finite) store `σ` of variables
that may be accessed and updated at any time.
A machine is given by a `Λ` indexed set of procedures or functions. Each function has a body which
is a `Stmt`. Most of the regular commands are allowed to use the current value `a` of the local
variables and the value `T.head` on the tape to calculate what to write or how to change local
state, but the statements themselves have a fixed structure. The `Stmt`s can be as follows:
* `move d q`: move left or right, and then do `q`
* `write (f : Γ → σ → Γ) q`: write `f a T.head` to the tape, then do `q`
* `load (f : Γ → σ → σ) q`: change the internal state to `f a T.head`
* `branch (f : Γ → σ → Bool) qtrue qfalse`: If `f a T.head` is true, do `qtrue`, else `qfalse`
* `goto (f : Γ → σ → Λ)`: Go to label `f a T.head`
* `halt`: Transition to the halting state, which halts on the following step
Note that here most statements do not have labels; `goto` commands can only go to a new function.
Only the `goto` and `halt` statements actually take a step; the rest is done by recursion on
statements and so take 0 steps. (There is a uniform bound on how many statements can be executed
before the next `goto`, so this is an `O(1)` speedup with the constant depending on the machine.)
The `halt` command has a one step stutter before actually halting so that any changes made before
the halt have a chance to be "committed", since the `eval` relation uses the final configuration
before the halt as the output, and `move` and `write` etc. take 0 steps in this model.
-/
namespace TM1
set_option linter.uppercaseLean3 false -- for "TM1"
section
variable (Γ : Type*) [Inhabited Γ]
-- Type of tape symbols
variable (Λ : Type*)
-- Type of function labels
variable (σ : Type*)
-- Type of variable settings
/-- The TM1 model is a simplification and extension of TM0
(Post-Turing model) in the direction of Wang B-machines. The machine's
internal state is extended with a (finite) store `σ` of variables
that may be accessed and updated at any time.
A machine is given by a `Λ` indexed set of procedures or functions.
Each function has a body which is a `Stmt`, which can either be a
`move` or `write` command, a `branch` (if statement based on the
current tape value), a `load` (set the variable value),
a `goto` (call another function), or `halt`. Note that here
most statements do not have labels; `goto` commands can only
go to a new function. All commands have access to the variable value
and current tape value. -/
inductive Stmt
| move : Dir → Stmt → Stmt
| write : (Γ → σ → Γ) → Stmt → Stmt
| load : (Γ → σ → σ) → Stmt → Stmt
| branch : (Γ → σ → Bool) → Stmt → Stmt → Stmt
| goto : (Γ → σ → Λ) → Stmt
| halt : Stmt
#align turing.TM1.stmt Turing.TM1.Stmt
local notation "Stmt₁" => Stmt Γ Λ σ -- Porting note (#10750): added this to clean up types.
open Stmt
instance Stmt.inhabited : Inhabited Stmt₁ :=
⟨halt⟩
#align turing.TM1.stmt.inhabited Turing.TM1.Stmt.inhabited
/-- The configuration of a TM1 machine is given by the currently
evaluating statement, the variable store value, and the tape. -/
structure Cfg where
/-- The statement (if any) which is currently evaluated -/
l : Option Λ
/-- The current value of the variable store -/
var : σ
/-- The current state of the tape -/
Tape : Tape Γ
#align turing.TM1.cfg Turing.TM1.Cfg
local notation "Cfg₁" => Cfg Γ Λ σ -- Porting note (#10750): added this to clean up types.
instance Cfg.inhabited [Inhabited σ] : Inhabited Cfg₁ :=
⟨⟨default, default, default⟩⟩
#align turing.TM1.cfg.inhabited Turing.TM1.Cfg.inhabited
variable {Γ Λ σ}
/-- The semantics of TM1 evaluation. -/
def stepAux : Stmt₁ → σ → Tape Γ → Cfg₁
| move d q, v, T => stepAux q v (T.move d)
| write a q, v, T => stepAux q v (T.write (a T.1 v))
| load s q, v, T => stepAux q (s T.1 v) T
| branch p q₁ q₂, v, T => cond (p T.1 v) (stepAux q₁ v T) (stepAux q₂ v T)
| goto l, v, T => ⟨some (l T.1 v), v, T⟩
| halt, v, T => ⟨none, v, T⟩
#align turing.TM1.step_aux Turing.TM1.stepAux
/-- The state transition function. -/
def step (M : Λ → Stmt₁) : Cfg₁ → Option Cfg₁
| ⟨none, _, _⟩ => none
| ⟨some l, v, T⟩ => some (stepAux (M l) v T)
#align turing.TM1.step Turing.TM1.step
/-- A set `S` of labels supports the statement `q` if all the `goto`
statements in `q` refer only to other functions in `S`. -/
def SupportsStmt (S : Finset Λ) : Stmt₁ → Prop
| move _ q => SupportsStmt S q
| write _ q => SupportsStmt S q
| load _ q => SupportsStmt S q
| branch _ q₁ q₂ => SupportsStmt S q₁ ∧ SupportsStmt S q₂
| goto l => ∀ a v, l a v ∈ S
| halt => True
#align turing.TM1.supports_stmt Turing.TM1.SupportsStmt
open scoped Classical
/-- The subterm closure of a statement. -/
noncomputable def stmts₁ : Stmt₁ → Finset Stmt₁
| Q@(move _ q) => insert Q (stmts₁ q)
| Q@(write _ q) => insert Q (stmts₁ q)
| Q@(load _ q) => insert Q (stmts₁ q)
| Q@(branch _ q₁ q₂) => insert Q (stmts₁ q₁ ∪ stmts₁ q₂)
| Q => {Q}
#align turing.TM1.stmts₁ Turing.TM1.stmts₁
theorem stmts₁_self {q : Stmt₁} : q ∈ stmts₁ q := by
cases q <;> simp only [stmts₁, Finset.mem_insert_self, Finset.mem_singleton_self]
#align turing.TM1.stmts₁_self Turing.TM1.stmts₁_self
| Mathlib/Computability/TuringMachine.lean | 1,328 | 1,344 | theorem stmts₁_trans {q₁ q₂ : Stmt₁} : q₁ ∈ stmts₁ q₂ → stmts₁ q₁ ⊆ stmts₁ q₂ := by |
intro h₁₂ q₀ h₀₁
induction q₂ with (
simp only [stmts₁] at h₁₂ ⊢
simp only [Finset.mem_insert, Finset.mem_union, Finset.mem_singleton] at h₁₂)
| branch p q₁ q₂ IH₁ IH₂ =>
rcases h₁₂ with (rfl | h₁₂ | h₁₂)
· unfold stmts₁ at h₀₁
exact h₀₁
· exact Finset.mem_insert_of_mem (Finset.mem_union_left _ <| IH₁ h₁₂)
· exact Finset.mem_insert_of_mem (Finset.mem_union_right _ <| IH₂ h₁₂)
| goto l => subst h₁₂; exact h₀₁
| halt => subst h₁₂; exact h₀₁
| _ _ q IH =>
rcases h₁₂ with rfl | h₁₂
· exact h₀₁
· exact Finset.mem_insert_of_mem (IH h₁₂)
|
/-
Copyright (c) 2018 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Reid Barton, Mario Carneiro, Scott Morrison, Floris van Doorn
-/
import Mathlib.CategoryTheory.Adjunction.Basic
import Mathlib.CategoryTheory.Limits.Cones
#align_import category_theory.limits.is_limit from "leanprover-community/mathlib"@"740acc0e6f9adf4423f92a485d0456fc271482da"
/-!
# Limits and colimits
We set up the general theory of limits and colimits in a category.
In this introduction we only describe the setup for limits;
it is repeated, with slightly different names, for colimits.
The main structures defined in this file is
* `IsLimit c`, for `c : Cone F`, `F : J ⥤ C`, expressing that `c` is a limit cone,
See also `CategoryTheory.Limits.HasLimits` which further builds:
* `LimitCone F`, which consists of a choice of cone for `F` and the fact it is a limit cone, and
* `HasLimit F`, asserting the mere existence of some limit cone for `F`.
## Implementation
At present we simply say everything twice, in order to handle both limits and colimits.
It would be highly desirable to have some automation support,
e.g. a `@[dualize]` attribute that behaves similarly to `@[to_additive]`.
## References
* [Stacks: Limits and colimits](https://stacks.math.columbia.edu/tag/002D)
-/
noncomputable section
open CategoryTheory CategoryTheory.Category CategoryTheory.Functor Opposite
namespace CategoryTheory.Limits
-- declare the `v`'s first; see `CategoryTheory.Category` for an explanation
universe v₁ v₂ v₃ v₄ u₁ u₂ u₃ u₄
variable {J : Type u₁} [Category.{v₁} J] {K : Type u₂} [Category.{v₂} K]
variable {C : Type u₃} [Category.{v₃} C]
variable {F : J ⥤ C}
/-- A cone `t` on `F` is a limit cone if each cone on `F` admits a unique
cone morphism to `t`.
See <https://stacks.math.columbia.edu/tag/002E>.
-/
-- porting note (#5171): removed @[nolint has_nonempty_instance]
structure IsLimit (t : Cone F) where
/-- There is a morphism from any cone point to `t.pt` -/
lift : ∀ s : Cone F, s.pt ⟶ t.pt
/-- The map makes the triangle with the two natural transformations commute -/
fac : ∀ (s : Cone F) (j : J), lift s ≫ t.π.app j = s.π.app j := by aesop_cat
/-- It is the unique such map to do this -/
uniq : ∀ (s : Cone F) (m : s.pt ⟶ t.pt) (_ : ∀ j : J, m ≫ t.π.app j = s.π.app j), m = lift s := by
aesop_cat
#align category_theory.limits.is_limit CategoryTheory.Limits.IsLimit
#align category_theory.limits.is_limit.fac' CategoryTheory.Limits.IsLimit.fac
#align category_theory.limits.is_limit.uniq' CategoryTheory.Limits.IsLimit.uniq
-- Porting note (#10618): simp can prove this. Linter complains it still exists
attribute [-simp, nolint simpNF] IsLimit.mk.injEq
attribute [reassoc (attr := simp)] IsLimit.fac
namespace IsLimit
instance subsingleton {t : Cone F} : Subsingleton (IsLimit t) :=
⟨by intro P Q; cases P; cases Q; congr; aesop_cat⟩
#align category_theory.limits.is_limit.subsingleton CategoryTheory.Limits.IsLimit.subsingleton
/-- Given a natural transformation `α : F ⟶ G`, we give a morphism from the cone point
of any cone over `F` to the cone point of a limit cone over `G`. -/
def map {F G : J ⥤ C} (s : Cone F) {t : Cone G} (P : IsLimit t) (α : F ⟶ G) : s.pt ⟶ t.pt :=
P.lift ((Cones.postcompose α).obj s)
#align category_theory.limits.is_limit.map CategoryTheory.Limits.IsLimit.map
@[reassoc (attr := simp)]
theorem map_π {F G : J ⥤ C} (c : Cone F) {d : Cone G} (hd : IsLimit d) (α : F ⟶ G) (j : J) :
hd.map c α ≫ d.π.app j = c.π.app j ≫ α.app j :=
fac _ _ _
#align category_theory.limits.is_limit.map_π CategoryTheory.Limits.IsLimit.map_π
@[simp]
theorem lift_self {c : Cone F} (t : IsLimit c) : t.lift c = 𝟙 c.pt :=
(t.uniq _ _ fun _ => id_comp _).symm
#align category_theory.limits.is_limit.lift_self CategoryTheory.Limits.IsLimit.lift_self
-- Repackaging the definition in terms of cone morphisms.
/-- The universal morphism from any other cone to a limit cone. -/
@[simps]
def liftConeMorphism {t : Cone F} (h : IsLimit t) (s : Cone F) : s ⟶ t where hom := h.lift s
#align category_theory.limits.is_limit.lift_cone_morphism CategoryTheory.Limits.IsLimit.liftConeMorphism
theorem uniq_cone_morphism {s t : Cone F} (h : IsLimit t) {f f' : s ⟶ t} : f = f' :=
have : ∀ {g : s ⟶ t}, g = h.liftConeMorphism s := by
intro g; apply ConeMorphism.ext; exact h.uniq _ _ g.w
this.trans this.symm
#align category_theory.limits.is_limit.uniq_cone_morphism CategoryTheory.Limits.IsLimit.uniq_cone_morphism
/-- Restating the definition of a limit cone in terms of the ∃! operator. -/
theorem existsUnique {t : Cone F} (h : IsLimit t) (s : Cone F) :
∃! l : s.pt ⟶ t.pt, ∀ j, l ≫ t.π.app j = s.π.app j :=
⟨h.lift s, h.fac s, h.uniq s⟩
#align category_theory.limits.is_limit.exists_unique CategoryTheory.Limits.IsLimit.existsUnique
/-- Noncomputably make a limit cone from the existence of unique factorizations. -/
def ofExistsUnique {t : Cone F}
(ht : ∀ s : Cone F, ∃! l : s.pt ⟶ t.pt, ∀ j, l ≫ t.π.app j = s.π.app j) : IsLimit t := by
choose s hs hs' using ht
exact ⟨s, hs, hs'⟩
#align category_theory.limits.is_limit.of_exists_unique CategoryTheory.Limits.IsLimit.ofExistsUnique
/-- Alternative constructor for `isLimit`,
providing a morphism of cones rather than a morphism between the cone points
and separately the factorisation condition.
-/
@[simps]
def mkConeMorphism {t : Cone F} (lift : ∀ s : Cone F, s ⟶ t)
(uniq : ∀ (s : Cone F) (m : s ⟶ t), m = lift s) : IsLimit t where
lift s := (lift s).hom
uniq s m w :=
have : ConeMorphism.mk m w = lift s := by apply uniq
congrArg ConeMorphism.hom this
#align category_theory.limits.is_limit.mk_cone_morphism CategoryTheory.Limits.IsLimit.mkConeMorphism
/-- Limit cones on `F` are unique up to isomorphism. -/
@[simps]
def uniqueUpToIso {s t : Cone F} (P : IsLimit s) (Q : IsLimit t) : s ≅ t where
hom := Q.liftConeMorphism s
inv := P.liftConeMorphism t
hom_inv_id := P.uniq_cone_morphism
inv_hom_id := Q.uniq_cone_morphism
#align category_theory.limits.is_limit.unique_up_to_iso CategoryTheory.Limits.IsLimit.uniqueUpToIso
/-- Any cone morphism between limit cones is an isomorphism. -/
theorem hom_isIso {s t : Cone F} (P : IsLimit s) (Q : IsLimit t) (f : s ⟶ t) : IsIso f :=
⟨⟨P.liftConeMorphism t, ⟨P.uniq_cone_morphism, Q.uniq_cone_morphism⟩⟩⟩
#align category_theory.limits.is_limit.hom_is_iso CategoryTheory.Limits.IsLimit.hom_isIso
/-- Limits of `F` are unique up to isomorphism. -/
def conePointUniqueUpToIso {s t : Cone F} (P : IsLimit s) (Q : IsLimit t) : s.pt ≅ t.pt :=
(Cones.forget F).mapIso (uniqueUpToIso P Q)
#align category_theory.limits.is_limit.cone_point_unique_up_to_iso CategoryTheory.Limits.IsLimit.conePointUniqueUpToIso
@[reassoc (attr := simp)]
theorem conePointUniqueUpToIso_hom_comp {s t : Cone F} (P : IsLimit s) (Q : IsLimit t) (j : J) :
(conePointUniqueUpToIso P Q).hom ≫ t.π.app j = s.π.app j :=
(uniqueUpToIso P Q).hom.w _
#align category_theory.limits.is_limit.cone_point_unique_up_to_iso_hom_comp CategoryTheory.Limits.IsLimit.conePointUniqueUpToIso_hom_comp
@[reassoc (attr := simp)]
theorem conePointUniqueUpToIso_inv_comp {s t : Cone F} (P : IsLimit s) (Q : IsLimit t) (j : J) :
(conePointUniqueUpToIso P Q).inv ≫ s.π.app j = t.π.app j :=
(uniqueUpToIso P Q).inv.w _
#align category_theory.limits.is_limit.cone_point_unique_up_to_iso_inv_comp CategoryTheory.Limits.IsLimit.conePointUniqueUpToIso_inv_comp
@[reassoc (attr := simp)]
theorem lift_comp_conePointUniqueUpToIso_hom {r s t : Cone F} (P : IsLimit s) (Q : IsLimit t) :
P.lift r ≫ (conePointUniqueUpToIso P Q).hom = Q.lift r :=
Q.uniq _ _ (by simp)
#align category_theory.limits.is_limit.lift_comp_cone_point_unique_up_to_iso_hom CategoryTheory.Limits.IsLimit.lift_comp_conePointUniqueUpToIso_hom
@[reassoc (attr := simp)]
theorem lift_comp_conePointUniqueUpToIso_inv {r s t : Cone F} (P : IsLimit s) (Q : IsLimit t) :
Q.lift r ≫ (conePointUniqueUpToIso P Q).inv = P.lift r :=
P.uniq _ _ (by simp)
#align category_theory.limits.is_limit.lift_comp_cone_point_unique_up_to_iso_inv CategoryTheory.Limits.IsLimit.lift_comp_conePointUniqueUpToIso_inv
/-- Transport evidence that a cone is a limit cone across an isomorphism of cones. -/
def ofIsoLimit {r t : Cone F} (P : IsLimit r) (i : r ≅ t) : IsLimit t :=
IsLimit.mkConeMorphism (fun s => P.liftConeMorphism s ≫ i.hom) fun s m => by
rw [← i.comp_inv_eq]; apply P.uniq_cone_morphism
#align category_theory.limits.is_limit.of_iso_limit CategoryTheory.Limits.IsLimit.ofIsoLimit
@[simp]
theorem ofIsoLimit_lift {r t : Cone F} (P : IsLimit r) (i : r ≅ t) (s) :
(P.ofIsoLimit i).lift s = P.lift s ≫ i.hom.hom :=
rfl
#align category_theory.limits.is_limit.of_iso_limit_lift CategoryTheory.Limits.IsLimit.ofIsoLimit_lift
/-- Isomorphism of cones preserves whether or not they are limiting cones. -/
def equivIsoLimit {r t : Cone F} (i : r ≅ t) : IsLimit r ≃ IsLimit t where
toFun h := h.ofIsoLimit i
invFun h := h.ofIsoLimit i.symm
left_inv := by aesop_cat
right_inv := by aesop_cat
#align category_theory.limits.is_limit.equiv_iso_limit CategoryTheory.Limits.IsLimit.equivIsoLimit
@[simp]
theorem equivIsoLimit_apply {r t : Cone F} (i : r ≅ t) (P : IsLimit r) :
equivIsoLimit i P = P.ofIsoLimit i :=
rfl
#align category_theory.limits.is_limit.equiv_iso_limit_apply CategoryTheory.Limits.IsLimit.equivIsoLimit_apply
@[simp]
theorem equivIsoLimit_symm_apply {r t : Cone F} (i : r ≅ t) (P : IsLimit t) :
(equivIsoLimit i).symm P = P.ofIsoLimit i.symm :=
rfl
#align category_theory.limits.is_limit.equiv_iso_limit_symm_apply CategoryTheory.Limits.IsLimit.equivIsoLimit_symm_apply
/-- If the canonical morphism from a cone point to a limiting cone point is an iso, then the
first cone was limiting also.
-/
def ofPointIso {r t : Cone F} (P : IsLimit r) [i : IsIso (P.lift t)] : IsLimit t :=
ofIsoLimit P (by
haveI : IsIso (P.liftConeMorphism t).hom := i
haveI : IsIso (P.liftConeMorphism t) := Cones.cone_iso_of_hom_iso _
symm
apply asIso (P.liftConeMorphism t))
#align category_theory.limits.is_limit.of_point_iso CategoryTheory.Limits.IsLimit.ofPointIso
variable {t : Cone F}
theorem hom_lift (h : IsLimit t) {W : C} (m : W ⟶ t.pt) :
m = h.lift { pt := W, π := { app := fun b => m ≫ t.π.app b } } :=
h.uniq { pt := W, π := { app := fun b => m ≫ t.π.app b } } m fun b => rfl
#align category_theory.limits.is_limit.hom_lift CategoryTheory.Limits.IsLimit.hom_lift
/-- Two morphisms into a limit are equal if their compositions with
each cone morphism are equal. -/
| Mathlib/CategoryTheory/Limits/IsLimit.lean | 228 | 231 | theorem hom_ext (h : IsLimit t) {W : C} {f f' : W ⟶ t.pt}
(w : ∀ j, f ≫ t.π.app j = f' ≫ t.π.app j) :
f = f' := by |
rw [h.hom_lift f, h.hom_lift f']; congr; exact funext w
|
/-
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, Amelia Livingston, Yury Kudryashov,
Neil Strickland, Aaron Anderson
-/
import Mathlib.Algebra.Divisibility.Basic
import Mathlib.Algebra.Group.Units
#align_import algebra.divisibility.units from "leanprover-community/mathlib"@"e574b1a4e891376b0ef974b926da39e05da12a06"
/-!
# Divisibility and units
## Main definition
* `IsRelPrime x y`: that `x` and `y` are relatively prime, defined to mean that the only common
divisors of `x` and `y` are the units.
-/
variable {α : Type*}
namespace Units
section Monoid
variable [Monoid α] {a b : α} {u : αˣ}
/-- Elements of the unit group of a monoid represented as elements of the monoid
divide any element of the monoid. -/
theorem coe_dvd : ↑u ∣ a :=
⟨↑u⁻¹ * a, by simp⟩
#align units.coe_dvd Units.coe_dvd
/-- In a monoid, an element `a` divides an element `b` iff `a` divides all
associates of `b`. -/
theorem dvd_mul_right : a ∣ b * u ↔ a ∣ b :=
Iff.intro (fun ⟨c, Eq⟩ ↦ ⟨c * ↑u⁻¹, by rw [← mul_assoc, ← Eq, Units.mul_inv_cancel_right]⟩)
fun ⟨c, Eq⟩ ↦ Eq.symm ▸ (_root_.dvd_mul_right _ _).mul_right _
#align units.dvd_mul_right Units.dvd_mul_right
/-- In a monoid, an element `a` divides an element `b` iff all associates of `a` divide `b`. -/
theorem mul_right_dvd : a * u ∣ b ↔ a ∣ b :=
Iff.intro (fun ⟨c, Eq⟩ => ⟨↑u * c, Eq.trans (mul_assoc _ _ _)⟩) fun h =>
dvd_trans (Dvd.intro (↑u⁻¹) (by rw [mul_assoc, u.mul_inv, mul_one])) h
#align units.mul_right_dvd Units.mul_right_dvd
end Monoid
section CommMonoid
variable [CommMonoid α] {a b : α} {u : αˣ}
/-- In a commutative monoid, an element `a` divides an element `b` iff `a` divides all left
associates of `b`. -/
theorem dvd_mul_left : a ∣ u * b ↔ a ∣ b := by
rw [mul_comm]
apply dvd_mul_right
#align units.dvd_mul_left Units.dvd_mul_left
/-- In a commutative monoid, an element `a` divides an element `b` iff all
left associates of `a` divide `b`. -/
theorem mul_left_dvd : ↑u * a ∣ b ↔ a ∣ b := by
rw [mul_comm]
apply mul_right_dvd
#align units.mul_left_dvd Units.mul_left_dvd
end CommMonoid
end Units
namespace IsUnit
section Monoid
variable [Monoid α] {a b u : α} (hu : IsUnit u)
/-- Units of a monoid divide any element of the monoid. -/
@[simp]
theorem dvd : u ∣ a := by
rcases hu with ⟨u, rfl⟩
apply Units.coe_dvd
#align is_unit.dvd IsUnit.dvd
@[simp]
theorem dvd_mul_right : a ∣ b * u ↔ a ∣ b := by
rcases hu with ⟨u, rfl⟩
apply Units.dvd_mul_right
#align is_unit.dvd_mul_right IsUnit.dvd_mul_right
/-- In a monoid, an element a divides an element b iff all associates of `a` divide `b`. -/
@[simp]
theorem mul_right_dvd : a * u ∣ b ↔ a ∣ b := by
rcases hu with ⟨u, rfl⟩
apply Units.mul_right_dvd
#align is_unit.mul_right_dvd IsUnit.mul_right_dvd
theorem isPrimal : IsPrimal u := fun _ _ _ ↦ ⟨u, 1, hu.dvd, one_dvd _, (mul_one u).symm⟩
end Monoid
section CommMonoid
variable [CommMonoid α] {a b u : α} (hu : IsUnit u)
/-- In a commutative monoid, an element `a` divides an element `b` iff `a` divides all left
associates of `b`. -/
@[simp]
| Mathlib/Algebra/Divisibility/Units.lean | 110 | 112 | theorem dvd_mul_left : a ∣ u * b ↔ a ∣ b := by |
rcases hu with ⟨u, rfl⟩
apply Units.dvd_mul_left
|
/-
Copyright (c) 2021 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa
-/
import Mathlib.Algebra.Regular.Basic
import Mathlib.GroupTheory.GroupAction.Hom
#align_import algebra.regular.smul from "leanprover-community/mathlib"@"550b58538991c8977703fdeb7c9d51a5aa27df11"
/-!
# Action of regular elements on a module
We introduce `M`-regular elements, in the context of an `R`-module `M`. The corresponding
predicate is called `IsSMulRegular`.
There are very limited typeclass assumptions on `R` and `M`, but the "mathematical" case of interest
is a commutative ring `R` acting on a module `M`. Since the properties are "multiplicative", there
is no actual requirement of having an addition, but there is a zero in both `R` and `M`.
SMultiplications involving `0` are, of course, all trivial.
The defining property is that an element `a ∈ R` is `M`-regular if the smultiplication map
`M → M`, defined by `m ↦ a • m`, is injective.
This property is the direct generalization to modules of the property `IsLeftRegular` defined in
`Algebra/Regular`. Lemma `isLeftRegular_iff` shows that indeed the two notions
coincide.
-/
variable {R S : Type*} (M : Type*) {a b : R} {s : S}
/-- An `M`-regular element is an element `c` such that multiplication on the left by `c` is an
injective map `M → M`. -/
def IsSMulRegular [SMul R M] (c : R) :=
Function.Injective ((c • ·) : M → M)
#align is_smul_regular IsSMulRegular
theorem IsLeftRegular.isSMulRegular [Mul R] {c : R} (h : IsLeftRegular c) : IsSMulRegular R c :=
h
#align is_left_regular.is_smul_regular IsLeftRegular.isSMulRegular
/-- Left-regular multiplication on `R` is equivalent to `R`-regularity of `R` itself. -/
theorem isLeftRegular_iff [Mul R] {a : R} : IsLeftRegular a ↔ IsSMulRegular R a :=
Iff.rfl
#align is_left_regular_iff isLeftRegular_iff
theorem IsRightRegular.isSMulRegular [Mul R] {c : R} (h : IsRightRegular c) :
IsSMulRegular R (MulOpposite.op c) :=
h
#align is_right_regular.is_smul_regular IsRightRegular.isSMulRegular
/-- Right-regular multiplication on `R` is equivalent to `Rᵐᵒᵖ`-regularity of `R` itself. -/
theorem isRightRegular_iff [Mul R] {a : R} :
IsRightRegular a ↔ IsSMulRegular R (MulOpposite.op a) :=
Iff.rfl
#align is_right_regular_iff isRightRegular_iff
namespace IsSMulRegular
variable {M}
section SMul
variable [SMul R M] [SMul R S] [SMul S M] [IsScalarTower R S M]
/-- The product of `M`-regular elements is `M`-regular. -/
theorem smul (ra : IsSMulRegular M a) (rs : IsSMulRegular M s) : IsSMulRegular M (a • s) :=
fun _ _ ab => rs (ra ((smul_assoc _ _ _).symm.trans (ab.trans (smul_assoc _ _ _))))
#align is_smul_regular.smul IsSMulRegular.smul
/-- If an element `b` becomes `M`-regular after multiplying it on the left by an `M`-regular
element, then `b` is `M`-regular. -/
theorem of_smul (a : R) (ab : IsSMulRegular M (a • s)) : IsSMulRegular M s :=
@Function.Injective.of_comp _ _ _ (fun m : M => a • m) _ fun c d cd => by
dsimp only [Function.comp_def] at cd
rw [← smul_assoc, ← smul_assoc] at cd
exact ab cd
#align is_smul_regular.of_smul IsSMulRegular.of_smul
/-- An element is `M`-regular if and only if multiplying it on the left by an `M`-regular element
is `M`-regular. -/
@[simp]
theorem smul_iff (b : S) (ha : IsSMulRegular M a) : IsSMulRegular M (a • b) ↔ IsSMulRegular M b :=
⟨of_smul _, ha.smul⟩
#align is_smul_regular.smul_iff IsSMulRegular.smul_iff
theorem isLeftRegular [Mul R] {a : R} (h : IsSMulRegular R a) : IsLeftRegular a :=
h
#align is_smul_regular.is_left_regular IsSMulRegular.isLeftRegular
theorem isRightRegular [Mul R] {a : R} (h : IsSMulRegular R (MulOpposite.op a)) :
IsRightRegular a :=
h
#align is_smul_regular.is_right_regular IsSMulRegular.isRightRegular
theorem mul [Mul R] [IsScalarTower R R M] (ra : IsSMulRegular M a) (rb : IsSMulRegular M b) :
IsSMulRegular M (a * b) :=
ra.smul rb
#align is_smul_regular.mul IsSMulRegular.mul
theorem of_mul [Mul R] [IsScalarTower R R M] (ab : IsSMulRegular M (a * b)) :
IsSMulRegular M b := by
rw [← smul_eq_mul] at ab
exact ab.of_smul _
#align is_smul_regular.of_mul IsSMulRegular.of_mul
@[simp]
theorem mul_iff_right [Mul R] [IsScalarTower R R M] (ha : IsSMulRegular M a) :
IsSMulRegular M (a * b) ↔ IsSMulRegular M b :=
⟨of_mul, ha.mul⟩
#align is_smul_regular.mul_iff_right IsSMulRegular.mul_iff_right
/-- Two elements `a` and `b` are `M`-regular if and only if both products `a * b` and `b * a`
are `M`-regular. -/
theorem mul_and_mul_iff [Mul R] [IsScalarTower R R M] :
IsSMulRegular M (a * b) ∧ IsSMulRegular M (b * a) ↔ IsSMulRegular M a ∧ IsSMulRegular M b := by
refine ⟨?_, ?_⟩
· rintro ⟨ab, ba⟩
exact ⟨ba.of_mul, ab.of_mul⟩
· rintro ⟨ha, hb⟩
exact ⟨ha.mul hb, hb.mul ha⟩
#align is_smul_regular.mul_and_mul_iff IsSMulRegular.mul_and_mul_iff
lemma of_injective {N F} [SMul R N] [FunLike F M N] [MulActionHomClass F R M N]
(f : F) {r : R} (h1 : Function.Injective f) (h2 : IsSMulRegular N r) :
IsSMulRegular M r := fun x y h3 => h1 <| h2 <|
(map_smulₛₗ f r x).symm.trans ((congrArg f h3).trans (map_smulₛₗ f r y))
end SMul
section Monoid
variable [Monoid R] [MulAction R M]
variable (M)
/-- One is always `M`-regular. -/
@[simp]
theorem one : IsSMulRegular M (1 : R) := fun a b ab => by
dsimp only [Function.comp_def] at ab
rw [one_smul, one_smul] at ab
assumption
#align is_smul_regular.one IsSMulRegular.one
variable {M}
/-- An element of `R` admitting a left inverse is `M`-regular. -/
theorem of_mul_eq_one (h : a * b = 1) : IsSMulRegular M b :=
of_mul
(by
rw [h]
exact one M)
#align is_smul_regular.of_mul_eq_one IsSMulRegular.of_mul_eq_one
/-- Any power of an `M`-regular element is `M`-regular. -/
theorem pow (n : ℕ) (ra : IsSMulRegular M a) : IsSMulRegular M (a ^ n) := by
induction' n with n hn
· rw [pow_zero]; simp only [one]
· rw [pow_succ']
exact (ra.smul_iff (a ^ n)).mpr hn
#align is_smul_regular.pow IsSMulRegular.pow
/-- An element `a` is `M`-regular if and only if a positive power of `a` is `M`-regular. -/
theorem pow_iff {n : ℕ} (n0 : 0 < n) : IsSMulRegular M (a ^ n) ↔ IsSMulRegular M a := by
refine ⟨?_, pow n⟩
rw [← Nat.succ_pred_eq_of_pos n0, pow_succ, ← smul_eq_mul]
exact of_smul _
#align is_smul_regular.pow_iff IsSMulRegular.pow_iff
end Monoid
section MonoidSMul
variable [Monoid S] [SMul R M] [SMul R S] [MulAction S M] [IsScalarTower R S M]
/-- An element of `S` admitting a left inverse in `R` is `M`-regular. -/
theorem of_smul_eq_one (h : a • s = 1) : IsSMulRegular M s :=
of_smul a
(by
rw [h]
exact one M)
#align is_smul_regular.of_smul_eq_one IsSMulRegular.of_smul_eq_one
end MonoidSMul
section MonoidWithZero
variable [MonoidWithZero R] [MonoidWithZero S] [Zero M] [MulActionWithZero R M]
[MulActionWithZero R S] [MulActionWithZero S M] [IsScalarTower R S M]
/-- The element `0` is `M`-regular if and only if `M` is trivial. -/
protected theorem subsingleton (h : IsSMulRegular M (0 : R)) : Subsingleton M :=
⟨fun a b => h (by dsimp only [Function.comp_def]; repeat' rw [MulActionWithZero.zero_smul])⟩
#align is_smul_regular.subsingleton IsSMulRegular.subsingleton
/-- The element `0` is `M`-regular if and only if `M` is trivial. -/
theorem zero_iff_subsingleton : IsSMulRegular M (0 : R) ↔ Subsingleton M :=
⟨fun h => h.subsingleton, fun H a b _ => @Subsingleton.elim _ H a b⟩
#align is_smul_regular.zero_iff_subsingleton IsSMulRegular.zero_iff_subsingleton
/-- The `0` element is not `M`-regular, on a non-trivial module. -/
theorem not_zero_iff : ¬IsSMulRegular M (0 : R) ↔ Nontrivial M := by
rw [nontrivial_iff, not_iff_comm, zero_iff_subsingleton, subsingleton_iff]
push_neg
exact Iff.rfl
#align is_smul_regular.not_zero_iff IsSMulRegular.not_zero_iff
/-- The element `0` is `M`-regular when `M` is trivial. -/
theorem zero [sM : Subsingleton M] : IsSMulRegular M (0 : R) :=
zero_iff_subsingleton.mpr sM
#align is_smul_regular.zero IsSMulRegular.zero
/-- The `0` element is not `M`-regular, on a non-trivial module. -/
theorem not_zero [nM : Nontrivial M] : ¬IsSMulRegular M (0 : R) :=
not_zero_iff.mpr nM
#align is_smul_regular.not_zero IsSMulRegular.not_zero
end MonoidWithZero
section CommSemigroup
variable [CommSemigroup R] [SMul R M] [IsScalarTower R R M]
/-- A product is `M`-regular if and only if the factors are. -/
theorem mul_iff : IsSMulRegular M (a * b) ↔ IsSMulRegular M a ∧ IsSMulRegular M b := by
rw [← mul_and_mul_iff]
exact ⟨fun ab => ⟨ab, by rwa [mul_comm]⟩, fun rab => rab.1⟩
#align is_smul_regular.mul_iff IsSMulRegular.mul_iff
end CommSemigroup
end IsSMulRegular
section Group
variable {G : Type*} [Group G]
/-- An element of a group acting on a Type is regular. This relies on the availability
of the inverse given by groups, since there is no `LeftCancelSMul` typeclass. -/
| Mathlib/Algebra/Regular/SMul.lean | 240 | 242 | theorem isSMulRegular_of_group [MulAction G R] (g : G) : IsSMulRegular R g := by |
intro x y h
convert congr_arg (g⁻¹ • ·) h using 1 <;> simp [← smul_assoc]
|
/-
Copyright (c) 2020 Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Bhavik Mehta, E. W. Ayers
-/
import Mathlib.CategoryTheory.Comma.Over
import Mathlib.CategoryTheory.Limits.Shapes.Pullbacks
import Mathlib.CategoryTheory.Yoneda
import Mathlib.Data.Set.Lattice
import Mathlib.Order.CompleteLattice
#align_import category_theory.sites.sieves from "leanprover-community/mathlib"@"239d882c4fb58361ee8b3b39fb2091320edef10a"
/-!
# Theory of sieves
- For an object `X` of a category `C`, a `Sieve X` is a set of morphisms to `X`
which is closed under left-composition.
- The complete lattice structure on sieves is given, as well as the Galois insertion
given by downward-closing.
- A `Sieve X` (functorially) induces a presheaf on `C` together with a monomorphism to
the yoneda embedding of `X`.
## Tags
sieve, pullback
-/
universe v₁ v₂ v₃ u₁ u₂ u₃
namespace CategoryTheory
open Category Limits
variable {C : Type u₁} [Category.{v₁} C] {D : Type u₂} [Category.{v₂} D] (F : C ⥤ D)
variable {X Y Z : C} (f : Y ⟶ X)
/-- A set of arrows all with codomain `X`. -/
def Presieve (X : C) :=
∀ ⦃Y⦄, Set (Y ⟶ X)-- deriving CompleteLattice
#align category_theory.presieve CategoryTheory.Presieve
instance : CompleteLattice (Presieve X) := by
dsimp [Presieve]
infer_instance
namespace Presieve
noncomputable instance : Inhabited (Presieve X) :=
⟨⊤⟩
/-- The full subcategory of the over category `C/X` consisting of arrows which belong to a
presieve on `X`. -/
abbrev category {X : C} (P : Presieve X) :=
FullSubcategory fun f : Over X => P f.hom
/-- Construct an object of `P.category`. -/
abbrev categoryMk {X : C} (P : Presieve X) {Y : C} (f : Y ⟶ X) (hf : P f) : P.category :=
⟨Over.mk f, hf⟩
/-- Given a sieve `S` on `X : C`, its associated diagram `S.diagram` is defined to be
the natural functor from the full subcategory of the over category `C/X` consisting
of arrows in `S` to `C`. -/
abbrev diagram (S : Presieve X) : S.category ⥤ C :=
fullSubcategoryInclusion _ ⋙ Over.forget X
#align category_theory.presieve.diagram CategoryTheory.Presieve.diagram
/-- Given a sieve `S` on `X : C`, its associated cocone `S.cocone` is defined to be
the natural cocone over the diagram defined above with cocone point `X`. -/
abbrev cocone (S : Presieve X) : Cocone S.diagram :=
(Over.forgetCocone X).whisker (fullSubcategoryInclusion _)
#align category_theory.presieve.cocone CategoryTheory.Presieve.cocone
/-- Given a set of arrows `S` all with codomain `X`, and a set of arrows with codomain `Y` for each
`f : Y ⟶ X` in `S`, produce a set of arrows with codomain `X`:
`{ g ≫ f | (f : Y ⟶ X) ∈ S, (g : Z ⟶ Y) ∈ R f }`.
-/
def bind (S : Presieve X) (R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y) : Presieve X := fun Z h =>
∃ (Y : C) (g : Z ⟶ Y) (f : Y ⟶ X) (H : S f), R H g ∧ g ≫ f = h
#align category_theory.presieve.bind CategoryTheory.Presieve.bind
@[simp]
theorem bind_comp {S : Presieve X} {R : ∀ ⦃Y : C⦄ ⦃f : Y ⟶ X⦄, S f → Presieve Y} {g : Z ⟶ Y}
(h₁ : S f) (h₂ : R h₁ g) : bind S R (g ≫ f) :=
⟨_, _, _, h₁, h₂, rfl⟩
#align category_theory.presieve.bind_comp CategoryTheory.Presieve.bind_comp
-- Porting note: it seems the definition of `Presieve` must be unfolded in order to define
-- this inductive type, it was thus renamed `singleton'`
-- Note we can't make this into `HasSingleton` because of the out-param.
/-- The singleton presieve. -/
inductive singleton' : ⦃Y : C⦄ → (Y ⟶ X) → Prop
| mk : singleton' f
/-- The singleton presieve. -/
def singleton : Presieve X := singleton' f
lemma singleton.mk {f : Y ⟶ X} : singleton f f := singleton'.mk
#align category_theory.presieve.singleton CategoryTheory.Presieve.singleton
@[simp]
theorem singleton_eq_iff_domain (f g : Y ⟶ X) : singleton f g ↔ f = g := by
constructor
· rintro ⟨a, rfl⟩
rfl
· rintro rfl
apply singleton.mk
#align category_theory.presieve.singleton_eq_iff_domain CategoryTheory.Presieve.singleton_eq_iff_domain
theorem singleton_self : singleton f f :=
singleton.mk
#align category_theory.presieve.singleton_self CategoryTheory.Presieve.singleton_self
/-- Pullback a set of arrows with given codomain along a fixed map, by taking the pullback in the
category.
This is not the same as the arrow set of `Sieve.pullback`, but there is a relation between them
in `pullbackArrows_comm`.
-/
inductive pullbackArrows [HasPullbacks C] (R : Presieve X) : Presieve Y
| mk (Z : C) (h : Z ⟶ X) : R h → pullbackArrows _ (pullback.snd : pullback h f ⟶ Y)
#align category_theory.presieve.pullback_arrows CategoryTheory.Presieve.pullbackArrows
theorem pullback_singleton [HasPullbacks C] (g : Z ⟶ X) :
pullbackArrows f (singleton g) = singleton (pullback.snd : pullback g f ⟶ _) := by
funext W
ext h
constructor
· rintro ⟨W, _, _, _⟩
exact singleton.mk
· rintro ⟨_⟩
exact pullbackArrows.mk Z g singleton.mk
#align category_theory.presieve.pullback_singleton CategoryTheory.Presieve.pullback_singleton
/-- Construct the presieve given by the family of arrows indexed by `ι`. -/
inductive ofArrows {ι : Type*} (Y : ι → C) (f : ∀ i, Y i ⟶ X) : Presieve X
| mk (i : ι) : ofArrows _ _ (f i)
#align category_theory.presieve.of_arrows CategoryTheory.Presieve.ofArrows
theorem ofArrows_pUnit : (ofArrows _ fun _ : PUnit => f) = singleton f := by
funext Y
ext g
constructor
· rintro ⟨_⟩
apply singleton.mk
· rintro ⟨_⟩
exact ofArrows.mk PUnit.unit
#align category_theory.presieve.of_arrows_punit CategoryTheory.Presieve.ofArrows_pUnit
theorem ofArrows_pullback [HasPullbacks C] {ι : Type*} (Z : ι → C) (g : ∀ i : ι, Z i ⟶ X) :
(ofArrows (fun i => pullback (g i) f) fun i => pullback.snd) =
pullbackArrows f (ofArrows Z g) := by
funext T
ext h
constructor
· rintro ⟨hk⟩
exact pullbackArrows.mk _ _ (ofArrows.mk hk)
· rintro ⟨W, k, hk₁⟩
cases' hk₁ with i hi
apply ofArrows.mk
#align category_theory.presieve.of_arrows_pullback CategoryTheory.Presieve.ofArrows_pullback
theorem ofArrows_bind {ι : Type*} (Z : ι → C) (g : ∀ i : ι, Z i ⟶ X)
(j : ∀ ⦃Y⦄ (f : Y ⟶ X), ofArrows Z g f → Type*) (W : ∀ ⦃Y⦄ (f : Y ⟶ X) (H), j f H → C)
(k : ∀ ⦃Y⦄ (f : Y ⟶ X) (H i), W f H i ⟶ Y) :
((ofArrows Z g).bind fun Y f H => ofArrows (W f H) (k f H)) =
ofArrows (fun i : Σi, j _ (ofArrows.mk i) => W (g i.1) _ i.2) fun ij =>
k (g ij.1) _ ij.2 ≫ g ij.1 := by
funext Y
ext f
constructor
· rintro ⟨_, _, _, ⟨i⟩, ⟨i'⟩, rfl⟩
exact ofArrows.mk (Sigma.mk _ _)
· rintro ⟨i⟩
exact bind_comp _ (ofArrows.mk _) (ofArrows.mk _)
#align category_theory.presieve.of_arrows_bind CategoryTheory.Presieve.ofArrows_bind
theorem ofArrows_surj {ι : Type*} {Y : ι → C} (f : ∀ i, Y i ⟶ X) {Z : C} (g : Z ⟶ X)
(hg : ofArrows Y f g) : ∃ (i : ι) (h : Y i = Z),
g = eqToHom h.symm ≫ f i := by
cases' hg with i
exact ⟨i, rfl, by simp only [eqToHom_refl, id_comp]⟩
/-- Given a presieve on `F(X)`, we can define a presieve on `X` by taking the preimage via `F`. -/
def functorPullback (R : Presieve (F.obj X)) : Presieve X := fun _ f => R (F.map f)
#align category_theory.presieve.functor_pullback CategoryTheory.Presieve.functorPullback
@[simp]
theorem functorPullback_mem (R : Presieve (F.obj X)) {Y} (f : Y ⟶ X) :
R.functorPullback F f ↔ R (F.map f) :=
Iff.rfl
#align category_theory.presieve.functor_pullback_mem CategoryTheory.Presieve.functorPullback_mem
@[simp]
theorem functorPullback_id (R : Presieve X) : R.functorPullback (𝟭 _) = R :=
rfl
#align category_theory.presieve.functor_pullback_id CategoryTheory.Presieve.functorPullback_id
/-- Given a presieve `R` on `X`, the predicate `R.hasPullbacks` means that for all arrows `f` and
`g` in `R`, the pullback of `f` and `g` exists. -/
class hasPullbacks (R : Presieve X) : Prop where
/-- For all arrows `f` and `g` in `R`, the pullback of `f` and `g` exists. -/
has_pullbacks : ∀ {Y Z} {f : Y ⟶ X} (_ : R f) {g : Z ⟶ X} (_ : R g), HasPullback f g
instance (R : Presieve X) [HasPullbacks C] : R.hasPullbacks := ⟨fun _ _ ↦ inferInstance⟩
instance {α : Type v₂} {X : α → C} {B : C} (π : (a : α) → X a ⟶ B)
[(Presieve.ofArrows X π).hasPullbacks] (a b : α) : HasPullback (π a) (π b) :=
Presieve.hasPullbacks.has_pullbacks (Presieve.ofArrows.mk _) (Presieve.ofArrows.mk _)
section FunctorPushforward
variable {E : Type u₃} [Category.{v₃} E] (G : D ⥤ E)
/-- Given a presieve on `X`, we can define a presieve on `F(X)` (which is actually a sieve)
by taking the sieve generated by the image via `F`.
-/
def functorPushforward (S : Presieve X) : Presieve (F.obj X) := fun Y f =>
∃ (Z : C) (g : Z ⟶ X) (h : Y ⟶ F.obj Z), S g ∧ f = h ≫ F.map g
#align category_theory.presieve.functor_pushforward CategoryTheory.Presieve.functorPushforward
-- Porting note: removed @[nolint hasNonemptyInstance]
/-- An auxiliary definition in order to fix the choice of the preimages between various definitions.
-/
structure FunctorPushforwardStructure (S : Presieve X) {Y} (f : Y ⟶ F.obj X) where
/-- an object in the source category -/
preobj : C
/-- a map in the source category which has to be in the presieve -/
premap : preobj ⟶ X
/-- the morphism which appear in the factorisation -/
lift : Y ⟶ F.obj preobj
/-- the condition that `premap` is in the presieve -/
cover : S premap
/-- the factorisation of the morphism -/
fac : f = lift ≫ F.map premap
#align category_theory.presieve.functor_pushforward_structure CategoryTheory.Presieve.FunctorPushforwardStructure
/-- The fixed choice of a preimage. -/
noncomputable def getFunctorPushforwardStructure {F : C ⥤ D} {S : Presieve X} {Y : D}
{f : Y ⟶ F.obj X} (h : S.functorPushforward F f) : FunctorPushforwardStructure F S f := by
choose Z f' g h₁ h using h
exact ⟨Z, f', g, h₁, h⟩
#align category_theory.presieve.get_functor_pushforward_structure CategoryTheory.Presieve.getFunctorPushforwardStructure
theorem functorPushforward_comp (R : Presieve X) :
R.functorPushforward (F ⋙ G) = (R.functorPushforward F).functorPushforward G := by
funext x
ext f
constructor
· rintro ⟨X, f₁, g₁, h₁, rfl⟩
exact ⟨F.obj X, F.map f₁, g₁, ⟨X, f₁, 𝟙 _, h₁, by simp⟩, rfl⟩
· rintro ⟨X, f₁, g₁, ⟨X', f₂, g₂, h₁, rfl⟩, rfl⟩
exact ⟨X', f₂, g₁ ≫ G.map g₂, h₁, by simp⟩
#align category_theory.presieve.functor_pushforward_comp CategoryTheory.Presieve.functorPushforward_comp
theorem image_mem_functorPushforward (R : Presieve X) {f : Y ⟶ X} (h : R f) :
R.functorPushforward F (F.map f) :=
⟨Y, f, 𝟙 _, h, by simp⟩
#align category_theory.presieve.image_mem_functor_pushforward CategoryTheory.Presieve.image_mem_functorPushforward
end FunctorPushforward
end Presieve
/--
For an object `X` of a category `C`, a `Sieve X` is a set of morphisms to `X` which is closed under
left-composition.
-/
structure Sieve {C : Type u₁} [Category.{v₁} C] (X : C) where
/-- the underlying presieve -/
arrows : Presieve X
/-- stability by precomposition -/
downward_closed : ∀ {Y Z f} (_ : arrows f) (g : Z ⟶ Y), arrows (g ≫ f)
#align category_theory.sieve CategoryTheory.Sieve
namespace Sieve
instance : CoeFun (Sieve X) fun _ => Presieve X :=
⟨Sieve.arrows⟩
initialize_simps_projections Sieve (arrows → apply)
variable {S R : Sieve X}
attribute [simp] downward_closed
theorem arrows_ext : ∀ {R S : Sieve X}, R.arrows = S.arrows → R = S := by
rintro ⟨_, _⟩ ⟨_, _⟩ rfl
rfl
#align category_theory.sieve.arrows_ext CategoryTheory.Sieve.arrows_ext
@[ext]
protected theorem ext {R S : Sieve X} (h : ∀ ⦃Y⦄ (f : Y ⟶ X), R f ↔ S f) : R = S :=
arrows_ext <| funext fun _ => funext fun f => propext <| h f
#align category_theory.sieve.ext CategoryTheory.Sieve.ext
protected theorem ext_iff {R S : Sieve X} : R = S ↔ ∀ ⦃Y⦄ (f : Y ⟶ X), R f ↔ S f :=
⟨fun h _ _ => h ▸ Iff.rfl, Sieve.ext⟩
#align category_theory.sieve.ext_iff CategoryTheory.Sieve.ext_iff
open Lattice
/-- The supremum of a collection of sieves: the union of them all. -/
protected def sup (𝒮 : Set (Sieve X)) : Sieve X where
arrows Y := { f | ∃ S ∈ 𝒮, Sieve.arrows S f }
downward_closed {_ _ f} hf _ := by
obtain ⟨S, hS, hf⟩ := hf
exact ⟨S, hS, S.downward_closed hf _⟩
#align category_theory.sieve.Sup CategoryTheory.Sieve.sup
/-- The infimum of a collection of sieves: the intersection of them all. -/
protected def inf (𝒮 : Set (Sieve X)) : Sieve X where
arrows _ := { f | ∀ S ∈ 𝒮, Sieve.arrows S f }
downward_closed {_ _ _} hf g S H := S.downward_closed (hf S H) g
#align category_theory.sieve.Inf CategoryTheory.Sieve.inf
/-- The union of two sieves is a sieve. -/
protected def union (S R : Sieve X) : Sieve X where
arrows Y f := S f ∨ R f
downward_closed := by rintro _ _ _ (h | h) g <;> simp [h]
#align category_theory.sieve.union CategoryTheory.Sieve.union
/-- The intersection of two sieves is a sieve. -/
protected def inter (S R : Sieve X) : Sieve X where
arrows Y f := S f ∧ R f
downward_closed := by
rintro _ _ _ ⟨h₁, h₂⟩ g
simp [h₁, h₂]
#align category_theory.sieve.inter CategoryTheory.Sieve.inter
/-- Sieves on an object `X` form a complete lattice.
We generate this directly rather than using the galois insertion for nicer definitional properties.
-/
instance : CompleteLattice (Sieve X) where
le S R := ∀ ⦃Y⦄ (f : Y ⟶ X), S f → R f
le_refl S f q := id
le_trans S₁ S₂ S₃ S₁₂ S₂₃ Y f h := S₂₃ _ (S₁₂ _ h)
le_antisymm S R p q := Sieve.ext fun Y f => ⟨p _, q _⟩
top :=
{ arrows := fun _ => Set.univ
downward_closed := fun _ _ => ⟨⟩ }
bot :=
{ arrows := fun _ => ∅
downward_closed := False.elim }
sup := Sieve.union
inf := Sieve.inter
sSup := Sieve.sup
sInf := Sieve.inf
le_sSup 𝒮 S hS Y f hf := ⟨S, hS, hf⟩
sSup_le := fun s a ha Y f ⟨b, hb, hf⟩ => (ha b hb) _ hf
sInf_le _ _ hS _ _ h := h _ hS
le_sInf _ _ hS _ _ hf _ hR := hS _ hR _ hf
le_sup_left _ _ _ _ := Or.inl
le_sup_right _ _ _ _ := Or.inr
sup_le _ _ _ h₁ h₂ _ f := by--ℰ S hS Y f := by
rintro (hf | hf)
· exact h₁ _ hf
· exact h₂ _ hf
inf_le_left _ _ _ _ := And.left
inf_le_right _ _ _ _ := And.right
le_inf _ _ _ p q _ _ z := ⟨p _ z, q _ z⟩
le_top _ _ _ _ := trivial
bot_le _ _ _ := False.elim
/-- The maximal sieve always exists. -/
instance sieveInhabited : Inhabited (Sieve X) :=
⟨⊤⟩
#align category_theory.sieve.sieve_inhabited CategoryTheory.Sieve.sieveInhabited
@[simp]
theorem sInf_apply {Ss : Set (Sieve X)} {Y} (f : Y ⟶ X) :
sInf Ss f ↔ ∀ (S : Sieve X) (_ : S ∈ Ss), S f :=
Iff.rfl
#align category_theory.sieve.Inf_apply CategoryTheory.Sieve.sInf_apply
@[simp]
theorem sSup_apply {Ss : Set (Sieve X)} {Y} (f : Y ⟶ X) :
sSup Ss f ↔ ∃ (S : Sieve X) (_ : S ∈ Ss), S f := by
simp [sSup, Sieve.sup, setOf]
#align category_theory.sieve.Sup_apply CategoryTheory.Sieve.sSup_apply
@[simp]
theorem inter_apply {R S : Sieve X} {Y} (f : Y ⟶ X) : (R ⊓ S) f ↔ R f ∧ S f :=
Iff.rfl
#align category_theory.sieve.inter_apply CategoryTheory.Sieve.inter_apply
@[simp]
theorem union_apply {R S : Sieve X} {Y} (f : Y ⟶ X) : (R ⊔ S) f ↔ R f ∨ S f :=
Iff.rfl
#align category_theory.sieve.union_apply CategoryTheory.Sieve.union_apply
@[simp]
theorem top_apply (f : Y ⟶ X) : (⊤ : Sieve X) f :=
trivial
#align category_theory.sieve.top_apply CategoryTheory.Sieve.top_apply
/-- Generate the smallest sieve containing the given set of arrows. -/
@[simps]
def generate (R : Presieve X) : Sieve X where
arrows Z f := ∃ (Y : _) (h : Z ⟶ Y) (g : Y ⟶ X), R g ∧ h ≫ g = f
downward_closed := by
rintro Y Z _ ⟨W, g, f, hf, rfl⟩ h
exact ⟨_, h ≫ g, _, hf, by simp⟩
#align category_theory.sieve.generate CategoryTheory.Sieve.generate
/-- Given a presieve on `X`, and a sieve on each domain of an arrow in the presieve, we can bind to
produce a sieve on `X`.
-/
@[simps]
def bind (S : Presieve X) (R : ∀ ⦃Y⦄ ⦃f : Y ⟶ X⦄, S f → Sieve Y) : Sieve X where
arrows := S.bind fun Y f h => R h
downward_closed := by
rintro Y Z f ⟨W, f, h, hh, hf, rfl⟩ g
exact ⟨_, g ≫ f, _, hh, by simp [hf]⟩
#align category_theory.sieve.bind CategoryTheory.Sieve.bind
open Order Lattice
theorem sets_iff_generate (R : Presieve X) (S : Sieve X) : generate R ≤ S ↔ R ≤ S :=
⟨fun H Y g hg => H _ ⟨_, 𝟙 _, _, hg, id_comp _⟩, fun ss Y f => by
rintro ⟨Z, f, g, hg, rfl⟩
exact S.downward_closed (ss Z hg) f⟩
#align category_theory.sieve.sets_iff_generate CategoryTheory.Sieve.sets_iff_generate
/-- Show that there is a galois insertion (generate, set_over). -/
def giGenerate : GaloisInsertion (generate : Presieve X → Sieve X) arrows where
gc := sets_iff_generate
choice 𝒢 _ := generate 𝒢
choice_eq _ _ := rfl
le_l_u _ _ _ hf := ⟨_, 𝟙 _, _, hf, id_comp _⟩
#align category_theory.sieve.gi_generate CategoryTheory.Sieve.giGenerate
theorem le_generate (R : Presieve X) : R ≤ generate R :=
giGenerate.gc.le_u_l R
#align category_theory.sieve.le_generate CategoryTheory.Sieve.le_generate
@[simp]
theorem generate_sieve (S : Sieve X) : generate S = S :=
giGenerate.l_u_eq S
#align category_theory.sieve.generate_sieve CategoryTheory.Sieve.generate_sieve
/-- If the identity arrow is in a sieve, the sieve is maximal. -/
theorem id_mem_iff_eq_top : S (𝟙 X) ↔ S = ⊤ :=
⟨fun h => top_unique fun Y f _ => by simpa using downward_closed _ h f, fun h => h.symm ▸ trivial⟩
#align category_theory.sieve.id_mem_iff_eq_top CategoryTheory.Sieve.id_mem_iff_eq_top
/-- If an arrow set contains a split epi, it generates the maximal sieve. -/
theorem generate_of_contains_isSplitEpi {R : Presieve X} (f : Y ⟶ X) [IsSplitEpi f] (hf : R f) :
generate R = ⊤ := by
rw [← id_mem_iff_eq_top]
exact ⟨_, section_ f, f, hf, by simp⟩
#align category_theory.sieve.generate_of_contains_is_split_epi CategoryTheory.Sieve.generate_of_contains_isSplitEpi
@[simp]
theorem generate_of_singleton_isSplitEpi (f : Y ⟶ X) [IsSplitEpi f] :
generate (Presieve.singleton f) = ⊤ :=
generate_of_contains_isSplitEpi f (Presieve.singleton_self _)
#align category_theory.sieve.generate_of_singleton_is_split_epi CategoryTheory.Sieve.generate_of_singleton_isSplitEpi
@[simp]
theorem generate_top : generate (⊤ : Presieve X) = ⊤ :=
generate_of_contains_isSplitEpi (𝟙 _) ⟨⟩
#align category_theory.sieve.generate_top CategoryTheory.Sieve.generate_top
/-- The sieve of `X` generated by family of morphisms `Y i ⟶ X`. -/
abbrev ofArrows {I : Type*} {X : C} (Y : I → C) (f : ∀ i, Y i ⟶ X) :
Sieve X :=
generate (Presieve.ofArrows Y f)
lemma ofArrows_mk {I : Type*} {X : C} (Y : I → C) (f : ∀ i, Y i ⟶ X) (i : I) :
ofArrows Y f (f i) :=
⟨_, 𝟙 _, _, ⟨i⟩, by simp⟩
lemma mem_ofArrows_iff {I : Type*} {X : C} (Y : I → C) (f : ∀ i, Y i ⟶ X)
{W : C} (g : W ⟶ X) :
ofArrows Y f g ↔ ∃ (i : I) (a : W ⟶ Y i), g = a ≫ f i := by
constructor
· rintro ⟨T, a, b, ⟨i⟩, rfl⟩
exact ⟨i, a, rfl⟩
· rintro ⟨i, a, rfl⟩
apply downward_closed _ (ofArrows_mk Y f i)
/-- The sieve of `X : C` that is generated by a family of objects `Y : I → C`:
it consists of morphisms to `X` which factor through at least one of the `Y i`. -/
def ofObjects {I : Type*} (Y : I → C) (X : C) : Sieve X where
arrows Z _ := ∃ (i : I), Nonempty (Z ⟶ Y i)
downward_closed := by
rintro Z₁ Z₂ p ⟨i, ⟨f⟩⟩ g
exact ⟨i, ⟨g ≫ f⟩⟩
lemma mem_ofObjects_iff {I : Type*} (Y : I → C) {Z X : C} (g : Z ⟶ X) :
ofObjects Y X g ↔ ∃ (i : I), Nonempty (Z ⟶ Y i) := by rfl
lemma ofArrows_le_ofObjects
{I : Type*} (Y : I → C) {X : C} (f : ∀ i, Y i ⟶ X) :
Sieve.ofArrows Y f ≤ Sieve.ofObjects Y X := by
intro W g hg
rw [mem_ofArrows_iff] at hg
obtain ⟨i, a, rfl⟩ := hg
exact ⟨i, ⟨a⟩⟩
lemma ofArrows_eq_ofObjects {X : C} (hX : IsTerminal X)
{I : Type*} (Y : I → C) (f : ∀ i, Y i ⟶ X) :
ofArrows Y f = ofObjects Y X := by
refine le_antisymm (ofArrows_le_ofObjects Y f) (fun W g => ?_)
rw [mem_ofArrows_iff, mem_ofObjects_iff]
rintro ⟨i, ⟨h⟩⟩
exact ⟨i, h, hX.hom_ext _ _⟩
/-- Given a morphism `h : Y ⟶ X`, send a sieve S on X to a sieve on Y
as the inverse image of S with `_ ≫ h`.
That is, `Sieve.pullback S h := (≫ h) '⁻¹ S`. -/
@[simps]
def pullback (h : Y ⟶ X) (S : Sieve X) : Sieve Y where
arrows Y sl := S (sl ≫ h)
downward_closed g := by simp [g]
#align category_theory.sieve.pullback CategoryTheory.Sieve.pullback
@[simp]
theorem pullback_id : S.pullback (𝟙 _) = S := by simp [Sieve.ext_iff]
#align category_theory.sieve.pullback_id CategoryTheory.Sieve.pullback_id
@[simp]
theorem pullback_top {f : Y ⟶ X} : (⊤ : Sieve X).pullback f = ⊤ :=
top_unique fun _ _ => id
#align category_theory.sieve.pullback_top CategoryTheory.Sieve.pullback_top
theorem pullback_comp {f : Y ⟶ X} {g : Z ⟶ Y} (S : Sieve X) :
S.pullback (g ≫ f) = (S.pullback f).pullback g := by simp [Sieve.ext_iff]
#align category_theory.sieve.pullback_comp CategoryTheory.Sieve.pullback_comp
@[simp]
theorem pullback_inter {f : Y ⟶ X} (S R : Sieve X) :
(S ⊓ R).pullback f = S.pullback f ⊓ R.pullback f := by simp [Sieve.ext_iff]
#align category_theory.sieve.pullback_inter CategoryTheory.Sieve.pullback_inter
theorem pullback_eq_top_iff_mem (f : Y ⟶ X) : S f ↔ S.pullback f = ⊤ := by
rw [← id_mem_iff_eq_top, pullback_apply, id_comp]
#align category_theory.sieve.pullback_eq_top_iff_mem CategoryTheory.Sieve.pullback_eq_top_iff_mem
theorem pullback_eq_top_of_mem (S : Sieve X) {f : Y ⟶ X} : S f → S.pullback f = ⊤ :=
(pullback_eq_top_iff_mem f).1
#align category_theory.sieve.pullback_eq_top_of_mem CategoryTheory.Sieve.pullback_eq_top_of_mem
lemma pullback_ofObjects_eq_top
{I : Type*} (Y : I → C) {X : C} {i : I} (g : X ⟶ Y i) :
ofObjects Y X = ⊤ := by
ext Z h
simp only [top_apply, iff_true]
rw [mem_ofObjects_iff ]
exact ⟨i, ⟨h ≫ g⟩⟩
/-- Push a sieve `R` on `Y` forward along an arrow `f : Y ⟶ X`: `gf : Z ⟶ X` is in the sieve if `gf`
factors through some `g : Z ⟶ Y` which is in `R`.
-/
@[simps]
def pushforward (f : Y ⟶ X) (R : Sieve Y) : Sieve X where
arrows Z gf := ∃ g, g ≫ f = gf ∧ R g
downward_closed := fun ⟨j, k, z⟩ h => ⟨h ≫ j, by simp [k], by simp [z]⟩
#align category_theory.sieve.pushforward CategoryTheory.Sieve.pushforward
theorem pushforward_apply_comp {R : Sieve Y} {Z : C} {g : Z ⟶ Y} (hg : R g) (f : Y ⟶ X) :
R.pushforward f (g ≫ f) :=
⟨g, rfl, hg⟩
#align category_theory.sieve.pushforward_apply_comp CategoryTheory.Sieve.pushforward_apply_comp
theorem pushforward_comp {f : Y ⟶ X} {g : Z ⟶ Y} (R : Sieve Z) :
R.pushforward (g ≫ f) = (R.pushforward g).pushforward f :=
Sieve.ext fun W h =>
⟨fun ⟨f₁, hq, hf₁⟩ => ⟨f₁ ≫ g, by simpa, f₁, rfl, hf₁⟩, fun ⟨y, hy, z, hR, hz⟩ =>
⟨z, by rw [← Category.assoc, hR]; tauto⟩⟩
#align category_theory.sieve.pushforward_comp CategoryTheory.Sieve.pushforward_comp
theorem galoisConnection (f : Y ⟶ X) : GaloisConnection (Sieve.pushforward f) (Sieve.pullback f) :=
fun _ _ => ⟨fun hR _ g hg => hR _ ⟨g, rfl, hg⟩, fun hS _ _ ⟨h, hg, hh⟩ => hg ▸ hS h hh⟩
#align category_theory.sieve.galois_connection CategoryTheory.Sieve.galoisConnection
theorem pullback_monotone (f : Y ⟶ X) : Monotone (Sieve.pullback f) :=
(galoisConnection f).monotone_u
#align category_theory.sieve.pullback_monotone CategoryTheory.Sieve.pullback_monotone
theorem pushforward_monotone (f : Y ⟶ X) : Monotone (Sieve.pushforward f) :=
(galoisConnection f).monotone_l
#align category_theory.sieve.pushforward_monotone CategoryTheory.Sieve.pushforward_monotone
theorem le_pushforward_pullback (f : Y ⟶ X) (R : Sieve Y) : R ≤ (R.pushforward f).pullback f :=
(galoisConnection f).le_u_l _
#align category_theory.sieve.le_pushforward_pullback CategoryTheory.Sieve.le_pushforward_pullback
theorem pullback_pushforward_le (f : Y ⟶ X) (R : Sieve X) : (R.pullback f).pushforward f ≤ R :=
(galoisConnection f).l_u_le _
#align category_theory.sieve.pullback_pushforward_le CategoryTheory.Sieve.pullback_pushforward_le
theorem pushforward_union {f : Y ⟶ X} (S R : Sieve Y) :
(S ⊔ R).pushforward f = S.pushforward f ⊔ R.pushforward f :=
(galoisConnection f).l_sup
#align category_theory.sieve.pushforward_union CategoryTheory.Sieve.pushforward_union
theorem pushforward_le_bind_of_mem (S : Presieve X) (R : ∀ ⦃Y : C⦄ ⦃f : Y ⟶ X⦄, S f → Sieve Y)
(f : Y ⟶ X) (h : S f) : (R h).pushforward f ≤ bind S R := by
rintro Z _ ⟨g, rfl, hg⟩
exact ⟨_, g, f, h, hg, rfl⟩
#align category_theory.sieve.pushforward_le_bind_of_mem CategoryTheory.Sieve.pushforward_le_bind_of_mem
theorem le_pullback_bind (S : Presieve X) (R : ∀ ⦃Y : C⦄ ⦃f : Y ⟶ X⦄, S f → Sieve Y) (f : Y ⟶ X)
(h : S f) : R h ≤ (bind S R).pullback f := by
rw [← galoisConnection f]
apply pushforward_le_bind_of_mem
#align category_theory.sieve.le_pullback_bind CategoryTheory.Sieve.le_pullback_bind
/-- If `f` is a monomorphism, the pushforward-pullback adjunction on sieves is coreflective. -/
def galoisCoinsertionOfMono (f : Y ⟶ X) [Mono f] :
GaloisCoinsertion (Sieve.pushforward f) (Sieve.pullback f) := by
apply (galoisConnection f).toGaloisCoinsertion
rintro S Z g ⟨g₁, hf, hg₁⟩
rw [cancel_mono f] at hf
rwa [← hf]
#align category_theory.sieve.galois_coinsertion_of_mono CategoryTheory.Sieve.galoisCoinsertionOfMono
/-- If `f` is a split epi, the pushforward-pullback adjunction on sieves is reflective. -/
def galoisInsertionOfIsSplitEpi (f : Y ⟶ X) [IsSplitEpi f] :
GaloisInsertion (Sieve.pushforward f) (Sieve.pullback f) := by
apply (galoisConnection f).toGaloisInsertion
intro S Z g hg
exact ⟨g ≫ section_ f, by simpa⟩
#align category_theory.sieve.galois_insertion_of_is_split_epi CategoryTheory.Sieve.galoisInsertionOfIsSplitEpi
theorem pullbackArrows_comm [HasPullbacks C] {X Y : C} (f : Y ⟶ X) (R : Presieve X) :
Sieve.generate (R.pullbackArrows f) = (Sieve.generate R).pullback f := by
ext W g
constructor
· rintro ⟨_, h, k, hk, rfl⟩
cases' hk with W g hg
change (Sieve.generate R).pullback f (h ≫ pullback.snd)
rw [Sieve.pullback_apply, assoc, ← pullback.condition, ← assoc]
exact Sieve.downward_closed _ (by exact Sieve.le_generate R W hg) (h ≫ pullback.fst)
· rintro ⟨W, h, k, hk, comm⟩
exact ⟨_, _, _, Presieve.pullbackArrows.mk _ _ hk, pullback.lift_snd _ _ comm⟩
#align category_theory.sieve.pullback_arrows_comm CategoryTheory.Sieve.pullbackArrows_comm
section Functor
variable {E : Type u₃} [Category.{v₃} E] (G : D ⥤ E)
/--
If `R` is a sieve, then the `CategoryTheory.Presieve.functorPullback` of `R` is actually a sieve.
-/
@[simps]
def functorPullback (R : Sieve (F.obj X)) : Sieve X where
arrows := Presieve.functorPullback F R
downward_closed := by
intro _ _ f hf g
unfold Presieve.functorPullback
rw [F.map_comp]
exact R.downward_closed hf (F.map g)
#align category_theory.sieve.functor_pullback CategoryTheory.Sieve.functorPullback
@[simp]
theorem functorPullback_arrows (R : Sieve (F.obj X)) :
(R.functorPullback F).arrows = R.arrows.functorPullback F :=
rfl
#align category_theory.sieve.functor_pullback_arrows CategoryTheory.Sieve.functorPullback_arrows
@[simp]
theorem functorPullback_id (R : Sieve X) : R.functorPullback (𝟭 _) = R := by
ext
rfl
#align category_theory.sieve.functor_pullback_id CategoryTheory.Sieve.functorPullback_id
theorem functorPullback_comp (R : Sieve ((F ⋙ G).obj X)) :
R.functorPullback (F ⋙ G) = (R.functorPullback G).functorPullback F := by
ext
rfl
#align category_theory.sieve.functor_pullback_comp CategoryTheory.Sieve.functorPullback_comp
theorem functorPushforward_extend_eq {R : Presieve X} :
(generate R).arrows.functorPushforward F = R.functorPushforward F := by
funext Y
ext f
constructor
· rintro ⟨X', g, f', ⟨X'', g', f'', h₁, rfl⟩, rfl⟩
exact ⟨X'', f'', f' ≫ F.map g', h₁, by simp⟩
· rintro ⟨X', g, f', h₁, h₂⟩
exact ⟨X', g, f', le_generate R _ h₁, h₂⟩
#align category_theory.sieve.functor_pushforward_extend_eq CategoryTheory.Sieve.functorPushforward_extend_eq
/-- The sieve generated by the image of `R` under `F`. -/
@[simps]
def functorPushforward (R : Sieve X) : Sieve (F.obj X) where
arrows := R.arrows.functorPushforward F
downward_closed := by
intro _ _ f h g
obtain ⟨X, α, β, hα, rfl⟩ := h
exact ⟨X, α, g ≫ β, hα, by simp⟩
#align category_theory.sieve.functor_pushforward CategoryTheory.Sieve.functorPushforward
@[simp]
theorem functorPushforward_id (R : Sieve X) : R.functorPushforward (𝟭 _) = R := by
ext X f
constructor
· intro hf
obtain ⟨X, g, h, hg, rfl⟩ := hf
exact R.downward_closed hg h
· intro hf
exact ⟨X, f, 𝟙 _, hf, by simp⟩
#align category_theory.sieve.functor_pushforward_id CategoryTheory.Sieve.functorPushforward_id
theorem functorPushforward_comp (R : Sieve X) :
R.functorPushforward (F ⋙ G) = (R.functorPushforward F).functorPushforward G := by
ext
simp [R.arrows.functorPushforward_comp F G]
#align category_theory.sieve.functor_pushforward_comp CategoryTheory.Sieve.functorPushforward_comp
| Mathlib/CategoryTheory/Sites/Sieves.lean | 716 | 727 | theorem functor_galoisConnection (X : C) :
GaloisConnection (Sieve.functorPushforward F : Sieve X → Sieve (F.obj X))
(Sieve.functorPullback F) := by |
intro R S
constructor
· intro hle X f hf
apply hle
refine ⟨X, f, 𝟙 _, hf, ?_⟩
rw [id_comp]
· rintro hle Y f ⟨X, g, h, hg, rfl⟩
apply Sieve.downward_closed S
exact hle g hg
|
/-
Copyright (c) 2019 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Markus Himmel
-/
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Zero
#align_import category_theory.limits.shapes.kernels from "leanprover-community/mathlib"@"956af7c76589f444f2e1313911bad16366ea476d"
/-!
# Kernels and cokernels
In a category with zero morphisms, the kernel of a morphism `f : X ⟶ Y` is
the equalizer of `f` and `0 : X ⟶ Y`. (Similarly the cokernel is the coequalizer.)
The basic definitions are
* `kernel : (X ⟶ Y) → C`
* `kernel.ι : kernel f ⟶ X`
* `kernel.condition : kernel.ι f ≫ f = 0` and
* `kernel.lift (k : W ⟶ X) (h : k ≫ f = 0) : W ⟶ kernel f` (as well as the dual versions)
## Main statements
Besides the definition and lifts, we prove
* `kernel.ιZeroIsIso`: a kernel map of a zero morphism is an isomorphism
* `kernel.eq_zero_of_epi_kernel`: if `kernel.ι f` is an epimorphism, then `f = 0`
* `kernel.ofMono`: the kernel of a monomorphism is the zero object
* `kernel.liftMono`: the lift of a monomorphism `k : W ⟶ X` such that `k ≫ f = 0`
is still a monomorphism
* `kernel.isLimitConeZeroCone`: if our category has a zero object, then the map from the zero
object is a kernel map of any monomorphism
* `kernel.ιOfZero`: `kernel.ι (0 : X ⟶ Y)` is an isomorphism
and the corresponding dual statements.
## Future work
* TODO: connect this with existing work in the group theory and ring theory libraries.
## Implementation notes
As with the other special shapes in the limits library, all the definitions here are given as
`abbreviation`s of the general statements for limits, so all the `simp` lemmas and theorems about
general limits can be used.
## References
* [F. Borceux, *Handbook of Categorical Algebra 2*][borceux-vol2]
-/
noncomputable section
universe v v₂ u u' u₂
open CategoryTheory
open CategoryTheory.Limits.WalkingParallelPair
namespace CategoryTheory.Limits
variable {C : Type u} [Category.{v} C]
variable [HasZeroMorphisms C]
/-- A morphism `f` has a kernel if the functor `ParallelPair f 0` has a limit. -/
abbrev HasKernel {X Y : C} (f : X ⟶ Y) : Prop :=
HasLimit (parallelPair f 0)
#align category_theory.limits.has_kernel CategoryTheory.Limits.HasKernel
/-- A morphism `f` has a cokernel if the functor `ParallelPair f 0` has a colimit. -/
abbrev HasCokernel {X Y : C} (f : X ⟶ Y) : Prop :=
HasColimit (parallelPair f 0)
#align category_theory.limits.has_cokernel CategoryTheory.Limits.HasCokernel
variable {X Y : C} (f : X ⟶ Y)
section
/-- A kernel fork is just a fork where the second morphism is a zero morphism. -/
abbrev KernelFork :=
Fork f 0
#align category_theory.limits.kernel_fork CategoryTheory.Limits.KernelFork
variable {f}
@[reassoc (attr := simp)]
theorem KernelFork.condition (s : KernelFork f) : Fork.ι s ≫ f = 0 := by
erw [Fork.condition, HasZeroMorphisms.comp_zero]
#align category_theory.limits.kernel_fork.condition CategoryTheory.Limits.KernelFork.condition
-- Porting note (#10618): simp can prove this, removed simp tag
theorem KernelFork.app_one (s : KernelFork f) : s.π.app one = 0 := by
simp [Fork.app_one_eq_ι_comp_right]
#align category_theory.limits.kernel_fork.app_one CategoryTheory.Limits.KernelFork.app_one
/-- A morphism `ι` satisfying `ι ≫ f = 0` determines a kernel fork over `f`. -/
abbrev KernelFork.ofι {Z : C} (ι : Z ⟶ X) (w : ι ≫ f = 0) : KernelFork f :=
Fork.ofι ι <| by rw [w, HasZeroMorphisms.comp_zero]
#align category_theory.limits.kernel_fork.of_ι CategoryTheory.Limits.KernelFork.ofι
@[simp]
theorem KernelFork.ι_ofι {X Y P : C} (f : X ⟶ Y) (ι : P ⟶ X) (w : ι ≫ f = 0) :
Fork.ι (KernelFork.ofι ι w) = ι := rfl
#align category_theory.limits.kernel_fork.ι_of_ι CategoryTheory.Limits.KernelFork.ι_ofι
section
-- attribute [local tidy] tactic.case_bash Porting note: no tidy nor case_bash
/-- Every kernel fork `s` is isomorphic (actually, equal) to `fork.ofι (fork.ι s) _`. -/
def isoOfι (s : Fork f 0) : s ≅ Fork.ofι (Fork.ι s) (Fork.condition s) :=
Cones.ext (Iso.refl _) <| by rintro ⟨j⟩ <;> simp
#align category_theory.limits.iso_of_ι CategoryTheory.Limits.isoOfι
/-- If `ι = ι'`, then `fork.ofι ι _` and `fork.ofι ι' _` are isomorphic. -/
def ofιCongr {P : C} {ι ι' : P ⟶ X} {w : ι ≫ f = 0} (h : ι = ι') :
KernelFork.ofι ι w ≅ KernelFork.ofι ι' (by rw [← h, w]) :=
Cones.ext (Iso.refl _)
#align category_theory.limits.of_ι_congr CategoryTheory.Limits.ofιCongr
/-- If `F` is an equivalence, then applying `F` to a diagram indexing a (co)kernel of `f` yields
the diagram indexing the (co)kernel of `F.map f`. -/
def compNatIso {D : Type u'} [Category.{v} D] [HasZeroMorphisms D] (F : C ⥤ D) [F.IsEquivalence] :
parallelPair f 0 ⋙ F ≅ parallelPair (F.map f) 0 :=
let app (j :WalkingParallelPair) :
(parallelPair f 0 ⋙ F).obj j ≅ (parallelPair (F.map f) 0).obj j :=
match j with
| zero => Iso.refl _
| one => Iso.refl _
NatIso.ofComponents app <| by rintro ⟨i⟩ ⟨j⟩ <;> intro g <;> cases g <;> simp [app]
#align category_theory.limits.comp_nat_iso CategoryTheory.Limits.compNatIso
end
/-- If `s` is a limit kernel fork and `k : W ⟶ X` satisfies `k ≫ f = 0`, then there is some
`l : W ⟶ s.X` such that `l ≫ fork.ι s = k`. -/
def KernelFork.IsLimit.lift' {s : KernelFork f} (hs : IsLimit s) {W : C} (k : W ⟶ X)
(h : k ≫ f = 0) : { l : W ⟶ s.pt // l ≫ Fork.ι s = k } :=
⟨hs.lift <| KernelFork.ofι _ h, hs.fac _ _⟩
#align category_theory.limits.kernel_fork.is_limit.lift' CategoryTheory.Limits.KernelFork.IsLimit.lift'
/-- This is a slightly more convenient method to verify that a kernel fork is a limit cone. It
only asks for a proof of facts that carry any mathematical content -/
def isLimitAux (t : KernelFork f) (lift : ∀ s : KernelFork f, s.pt ⟶ t.pt)
(fac : ∀ s : KernelFork f, lift s ≫ t.ι = s.ι)
(uniq : ∀ (s : KernelFork f) (m : s.pt ⟶ t.pt) (_ : m ≫ t.ι = s.ι), m = lift s) : IsLimit t :=
{ lift
fac := fun s j => by
cases j
· exact fac s
· simp
uniq := fun s m w => uniq s m (w Limits.WalkingParallelPair.zero) }
#align category_theory.limits.is_limit_aux CategoryTheory.Limits.isLimitAux
/-- This is a more convenient formulation to show that a `KernelFork` constructed using
`KernelFork.ofι` is a limit cone.
-/
def KernelFork.IsLimit.ofι {W : C} (g : W ⟶ X) (eq : g ≫ f = 0)
(lift : ∀ {W' : C} (g' : W' ⟶ X) (_ : g' ≫ f = 0), W' ⟶ W)
(fac : ∀ {W' : C} (g' : W' ⟶ X) (eq' : g' ≫ f = 0), lift g' eq' ≫ g = g')
(uniq :
∀ {W' : C} (g' : W' ⟶ X) (eq' : g' ≫ f = 0) (m : W' ⟶ W) (_ : m ≫ g = g'), m = lift g' eq') :
IsLimit (KernelFork.ofι g eq) :=
isLimitAux _ (fun s => lift s.ι s.condition) (fun s => fac s.ι s.condition) fun s =>
uniq s.ι s.condition
#align category_theory.limits.kernel_fork.is_limit.of_ι CategoryTheory.Limits.KernelFork.IsLimit.ofι
/-- This is a more convenient formulation to show that a `KernelFork` of the form
`KernelFork.ofι i _` is a limit cone when we know that `i` is a monomorphism. -/
def KernelFork.IsLimit.ofι' {X Y K : C} {f : X ⟶ Y} (i : K ⟶ X) (w : i ≫ f = 0)
(h : ∀ {A : C} (k : A ⟶ X) (_ : k ≫ f = 0), { l : A ⟶ K // l ≫ i = k}) [hi : Mono i] :
IsLimit (KernelFork.ofι i w) :=
ofι _ _ (fun {A} k hk => (h k hk).1) (fun {A} k hk => (h k hk).2) (fun {A} k hk m hm => by
rw [← cancel_mono i, (h k hk).2, hm])
/-- Every kernel of `f` induces a kernel of `f ≫ g` if `g` is mono. -/
def isKernelCompMono {c : KernelFork f} (i : IsLimit c) {Z} (g : Y ⟶ Z) [hg : Mono g] {h : X ⟶ Z}
(hh : h = f ≫ g) : IsLimit (KernelFork.ofι c.ι (by simp [hh]) : KernelFork h) :=
Fork.IsLimit.mk' _ fun s =>
let s' : KernelFork f := Fork.ofι s.ι (by rw [← cancel_mono g]; simp [← hh, s.condition])
let l := KernelFork.IsLimit.lift' i s'.ι s'.condition
⟨l.1, l.2, fun hm => by
apply Fork.IsLimit.hom_ext i; rw [Fork.ι_ofι] at hm; rw [hm]; exact l.2.symm⟩
#align category_theory.limits.is_kernel_comp_mono CategoryTheory.Limits.isKernelCompMono
theorem isKernelCompMono_lift {c : KernelFork f} (i : IsLimit c) {Z} (g : Y ⟶ Z) [hg : Mono g]
{h : X ⟶ Z} (hh : h = f ≫ g) (s : KernelFork h) :
(isKernelCompMono i g hh).lift s = i.lift (Fork.ofι s.ι (by
rw [← cancel_mono g, Category.assoc, ← hh]
simp)) := rfl
#align category_theory.limits.is_kernel_comp_mono_lift CategoryTheory.Limits.isKernelCompMono_lift
/-- Every kernel of `f ≫ g` is also a kernel of `f`, as long as `c.ι ≫ f` vanishes. -/
def isKernelOfComp {W : C} (g : Y ⟶ W) (h : X ⟶ W) {c : KernelFork h} (i : IsLimit c)
(hf : c.ι ≫ f = 0) (hfg : f ≫ g = h) : IsLimit (KernelFork.ofι c.ι hf) :=
Fork.IsLimit.mk _ (fun s => i.lift (KernelFork.ofι s.ι (by simp [← hfg])))
(fun s => by simp only [KernelFork.ι_ofι, Fork.IsLimit.lift_ι]) fun s m h => by
apply Fork.IsLimit.hom_ext i; simpa using h
#align category_theory.limits.is_kernel_of_comp CategoryTheory.Limits.isKernelOfComp
/-- `X` identifies to the kernel of a zero map `X ⟶ Y`. -/
def KernelFork.IsLimit.ofId {X Y : C} (f : X ⟶ Y) (hf : f = 0) :
IsLimit (KernelFork.ofι (𝟙 X) (show 𝟙 X ≫ f = 0 by rw [hf, comp_zero])) :=
KernelFork.IsLimit.ofι _ _ (fun x _ => x) (fun _ _ => Category.comp_id _)
(fun _ _ _ hb => by simp only [← hb, Category.comp_id])
/-- Any zero object identifies to the kernel of a given monomorphisms. -/
def KernelFork.IsLimit.ofMonoOfIsZero {X Y : C} {f : X ⟶ Y} (c : KernelFork f)
(hf : Mono f) (h : IsZero c.pt) : IsLimit c :=
isLimitAux _ (fun s => 0) (fun s => by rw [zero_comp, ← cancel_mono f, zero_comp, s.condition])
(fun _ _ _ => h.eq_of_tgt _ _)
lemma KernelFork.IsLimit.isIso_ι {X Y : C} {f : X ⟶ Y} (c : KernelFork f)
(hc : IsLimit c) (hf : f = 0) : IsIso c.ι := by
let e : c.pt ≅ X := IsLimit.conePointUniqueUpToIso hc
(KernelFork.IsLimit.ofId (f : X ⟶ Y) hf)
have eq : e.inv ≫ c.ι = 𝟙 X := Fork.IsLimit.lift_ι hc
haveI : IsIso (e.inv ≫ c.ι) := by
rw [eq]
infer_instance
exact IsIso.of_isIso_comp_left e.inv c.ι
end
namespace KernelFork
variable {f} {X' Y' : C} {f' : X' ⟶ Y'}
/-- The morphism between points of kernel forks induced by a morphism
in the category of arrows. -/
def mapOfIsLimit (kf : KernelFork f) {kf' : KernelFork f'} (hf' : IsLimit kf')
(φ : Arrow.mk f ⟶ Arrow.mk f') : kf.pt ⟶ kf'.pt :=
hf'.lift (KernelFork.ofι (kf.ι ≫ φ.left) (by simp))
@[reassoc (attr := simp)]
lemma mapOfIsLimit_ι (kf : KernelFork f) {kf' : KernelFork f'} (hf' : IsLimit kf')
(φ : Arrow.mk f ⟶ Arrow.mk f') :
kf.mapOfIsLimit hf' φ ≫ kf'.ι = kf.ι ≫ φ.left :=
hf'.fac _ _
/-- The isomorphism between points of limit kernel forks induced by an isomorphism
in the category of arrows. -/
@[simps]
def mapIsoOfIsLimit {kf : KernelFork f} {kf' : KernelFork f'}
(hf : IsLimit kf) (hf' : IsLimit kf')
(φ : Arrow.mk f ≅ Arrow.mk f') : kf.pt ≅ kf'.pt where
hom := kf.mapOfIsLimit hf' φ.hom
inv := kf'.mapOfIsLimit hf φ.inv
hom_inv_id := Fork.IsLimit.hom_ext hf (by simp)
inv_hom_id := Fork.IsLimit.hom_ext hf' (by simp)
end KernelFork
section
variable [HasKernel f]
/-- The kernel of a morphism, expressed as the equalizer with the 0 morphism. -/
abbrev kernel (f : X ⟶ Y) [HasKernel f] : C :=
equalizer f 0
#align category_theory.limits.kernel CategoryTheory.Limits.kernel
/-- The map from `kernel f` into the source of `f`. -/
abbrev kernel.ι : kernel f ⟶ X :=
equalizer.ι f 0
#align category_theory.limits.kernel.ι CategoryTheory.Limits.kernel.ι
@[simp]
theorem equalizer_as_kernel : equalizer.ι f 0 = kernel.ι f := rfl
#align category_theory.limits.equalizer_as_kernel CategoryTheory.Limits.equalizer_as_kernel
@[reassoc (attr := simp)]
theorem kernel.condition : kernel.ι f ≫ f = 0 :=
KernelFork.condition _
#align category_theory.limits.kernel.condition CategoryTheory.Limits.kernel.condition
/-- The kernel built from `kernel.ι f` is limiting. -/
def kernelIsKernel : IsLimit (Fork.ofι (kernel.ι f) ((kernel.condition f).trans comp_zero.symm)) :=
IsLimit.ofIsoLimit (limit.isLimit _) (Fork.ext (Iso.refl _) (by aesop_cat))
#align category_theory.limits.kernel_is_kernel CategoryTheory.Limits.kernelIsKernel
/-- Given any morphism `k : W ⟶ X` satisfying `k ≫ f = 0`, `k` factors through `kernel.ι f`
via `kernel.lift : W ⟶ kernel f`. -/
abbrev kernel.lift {W : C} (k : W ⟶ X) (h : k ≫ f = 0) : W ⟶ kernel f :=
(kernelIsKernel f).lift (KernelFork.ofι k h)
#align category_theory.limits.kernel.lift CategoryTheory.Limits.kernel.lift
@[reassoc (attr := simp)]
theorem kernel.lift_ι {W : C} (k : W ⟶ X) (h : k ≫ f = 0) : kernel.lift f k h ≫ kernel.ι f = k :=
(kernelIsKernel f).fac (KernelFork.ofι k h) WalkingParallelPair.zero
#align category_theory.limits.kernel.lift_ι CategoryTheory.Limits.kernel.lift_ι
@[simp]
theorem kernel.lift_zero {W : C} {h} : kernel.lift f (0 : W ⟶ X) h = 0 := by
ext; simp
#align category_theory.limits.kernel.lift_zero CategoryTheory.Limits.kernel.lift_zero
instance kernel.lift_mono {W : C} (k : W ⟶ X) (h : k ≫ f = 0) [Mono k] : Mono (kernel.lift f k h) :=
⟨fun {Z} g g' w => by
replace w := w =≫ kernel.ι f
simp only [Category.assoc, kernel.lift_ι] at w
exact (cancel_mono k).1 w⟩
#align category_theory.limits.kernel.lift_mono CategoryTheory.Limits.kernel.lift_mono
/-- Any morphism `k : W ⟶ X` satisfying `k ≫ f = 0` induces a morphism `l : W ⟶ kernel f` such that
`l ≫ kernel.ι f = k`. -/
def kernel.lift' {W : C} (k : W ⟶ X) (h : k ≫ f = 0) : { l : W ⟶ kernel f // l ≫ kernel.ι f = k } :=
⟨kernel.lift f k h, kernel.lift_ι _ _ _⟩
#align category_theory.limits.kernel.lift' CategoryTheory.Limits.kernel.lift'
/-- A commuting square induces a morphism of kernels. -/
abbrev kernel.map {X' Y' : C} (f' : X' ⟶ Y') [HasKernel f'] (p : X ⟶ X') (q : Y ⟶ Y')
(w : f ≫ q = p ≫ f') : kernel f ⟶ kernel f' :=
kernel.lift f' (kernel.ι f ≫ p) (by simp [← w])
#align category_theory.limits.kernel.map CategoryTheory.Limits.kernel.map
/-- Given a commutative diagram
X --f--> Y --g--> Z
| | |
| | |
v v v
X' -f'-> Y' -g'-> Z'
with horizontal arrows composing to zero,
then we obtain a commutative square
X ---> kernel g
| |
| | kernel.map
| |
v v
X' --> kernel g'
-/
theorem kernel.lift_map {X Y Z X' Y' Z' : C} (f : X ⟶ Y) (g : Y ⟶ Z) [HasKernel g] (w : f ≫ g = 0)
(f' : X' ⟶ Y') (g' : Y' ⟶ Z') [HasKernel g'] (w' : f' ≫ g' = 0) (p : X ⟶ X') (q : Y ⟶ Y')
(r : Z ⟶ Z') (h₁ : f ≫ q = p ≫ f') (h₂ : g ≫ r = q ≫ g') :
kernel.lift g f w ≫ kernel.map g g' q r h₂ = p ≫ kernel.lift g' f' w' := by
ext; simp [h₁]
#align category_theory.limits.kernel.lift_map CategoryTheory.Limits.kernel.lift_map
/-- A commuting square of isomorphisms induces an isomorphism of kernels. -/
@[simps]
def kernel.mapIso {X' Y' : C} (f' : X' ⟶ Y') [HasKernel f'] (p : X ≅ X') (q : Y ≅ Y')
(w : f ≫ q.hom = p.hom ≫ f') : kernel f ≅ kernel f' where
hom := kernel.map f f' p.hom q.hom w
inv :=
kernel.map f' f p.inv q.inv
(by
refine (cancel_mono q.hom).1 ?_
simp [w])
#align category_theory.limits.kernel.map_iso CategoryTheory.Limits.kernel.mapIso
/-- Every kernel of the zero morphism is an isomorphism -/
instance kernel.ι_zero_isIso : IsIso (kernel.ι (0 : X ⟶ Y)) :=
equalizer.ι_of_self _
#align category_theory.limits.kernel.ι_zero_is_iso CategoryTheory.Limits.kernel.ι_zero_isIso
theorem eq_zero_of_epi_kernel [Epi (kernel.ι f)] : f = 0 :=
(cancel_epi (kernel.ι f)).1 (by simp)
#align category_theory.limits.eq_zero_of_epi_kernel CategoryTheory.Limits.eq_zero_of_epi_kernel
/-- The kernel of a zero morphism is isomorphic to the source. -/
def kernelZeroIsoSource : kernel (0 : X ⟶ Y) ≅ X :=
equalizer.isoSourceOfSelf 0
#align category_theory.limits.kernel_zero_iso_source CategoryTheory.Limits.kernelZeroIsoSource
@[simp]
theorem kernelZeroIsoSource_hom : kernelZeroIsoSource.hom = kernel.ι (0 : X ⟶ Y) := rfl
#align category_theory.limits.kernel_zero_iso_source_hom CategoryTheory.Limits.kernelZeroIsoSource_hom
@[simp]
theorem kernelZeroIsoSource_inv :
kernelZeroIsoSource.inv = kernel.lift (0 : X ⟶ Y) (𝟙 X) (by simp) := by
ext
simp [kernelZeroIsoSource]
#align category_theory.limits.kernel_zero_iso_source_inv CategoryTheory.Limits.kernelZeroIsoSource_inv
/-- If two morphisms are known to be equal, then their kernels are isomorphic. -/
def kernelIsoOfEq {f g : X ⟶ Y} [HasKernel f] [HasKernel g] (h : f = g) : kernel f ≅ kernel g :=
HasLimit.isoOfNatIso (by rw [h])
#align category_theory.limits.kernel_iso_of_eq CategoryTheory.Limits.kernelIsoOfEq
@[simp]
theorem kernelIsoOfEq_refl {h : f = f} : kernelIsoOfEq h = Iso.refl (kernel f) := by
ext
simp [kernelIsoOfEq]
#align category_theory.limits.kernel_iso_of_eq_refl CategoryTheory.Limits.kernelIsoOfEq_refl
/- Porting note: induction on Eq is trying instantiate another g... -/
@[reassoc (attr := simp)]
theorem kernelIsoOfEq_hom_comp_ι {f g : X ⟶ Y} [HasKernel f] [HasKernel g] (h : f = g) :
(kernelIsoOfEq h).hom ≫ kernel.ι g = kernel.ι f := by
cases h; simp
#align category_theory.limits.kernel_iso_of_eq_hom_comp_ι CategoryTheory.Limits.kernelIsoOfEq_hom_comp_ι
@[reassoc (attr := simp)]
theorem kernelIsoOfEq_inv_comp_ι {f g : X ⟶ Y} [HasKernel f] [HasKernel g] (h : f = g) :
(kernelIsoOfEq h).inv ≫ kernel.ι _ = kernel.ι _ := by
cases h; simp
#align category_theory.limits.kernel_iso_of_eq_inv_comp_ι CategoryTheory.Limits.kernelIsoOfEq_inv_comp_ι
@[reassoc (attr := simp)]
theorem lift_comp_kernelIsoOfEq_hom {Z} {f g : X ⟶ Y} [HasKernel f] [HasKernel g] (h : f = g)
(e : Z ⟶ X) (he) :
kernel.lift _ e he ≫ (kernelIsoOfEq h).hom = kernel.lift _ e (by simp [← h, he]) := by
cases h; simp
#align category_theory.limits.lift_comp_kernel_iso_of_eq_hom CategoryTheory.Limits.lift_comp_kernelIsoOfEq_hom
@[reassoc (attr := simp)]
theorem lift_comp_kernelIsoOfEq_inv {Z} {f g : X ⟶ Y} [HasKernel f] [HasKernel g] (h : f = g)
(e : Z ⟶ X) (he) :
kernel.lift _ e he ≫ (kernelIsoOfEq h).inv = kernel.lift _ e (by simp [h, he]) := by
cases h; simp
#align category_theory.limits.lift_comp_kernel_iso_of_eq_inv CategoryTheory.Limits.lift_comp_kernelIsoOfEq_inv
@[simp]
theorem kernelIsoOfEq_trans {f g h : X ⟶ Y} [HasKernel f] [HasKernel g] [HasKernel h] (w₁ : f = g)
(w₂ : g = h) : kernelIsoOfEq w₁ ≪≫ kernelIsoOfEq w₂ = kernelIsoOfEq (w₁.trans w₂) := by
cases w₁; cases w₂; ext; simp [kernelIsoOfEq]
#align category_theory.limits.kernel_iso_of_eq_trans CategoryTheory.Limits.kernelIsoOfEq_trans
variable {f}
theorem kernel_not_epi_of_nonzero (w : f ≠ 0) : ¬Epi (kernel.ι f) := fun _ =>
w (eq_zero_of_epi_kernel f)
#align category_theory.limits.kernel_not_epi_of_nonzero CategoryTheory.Limits.kernel_not_epi_of_nonzero
theorem kernel_not_iso_of_nonzero (w : f ≠ 0) : IsIso (kernel.ι f) → False := fun _ =>
kernel_not_epi_of_nonzero w inferInstance
#align category_theory.limits.kernel_not_iso_of_nonzero CategoryTheory.Limits.kernel_not_iso_of_nonzero
instance hasKernel_comp_mono {X Y Z : C} (f : X ⟶ Y) [HasKernel f] (g : Y ⟶ Z) [Mono g] :
HasKernel (f ≫ g) :=
⟨⟨{ cone := _
isLimit := isKernelCompMono (limit.isLimit _) g rfl }⟩⟩
#align category_theory.limits.has_kernel_comp_mono CategoryTheory.Limits.hasKernel_comp_mono
/-- When `g` is a monomorphism, the kernel of `f ≫ g` is isomorphic to the kernel of `f`.
-/
@[simps]
def kernelCompMono {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) [HasKernel f] [Mono g] :
kernel (f ≫ g) ≅ kernel f where
hom :=
kernel.lift _ (kernel.ι _)
(by
rw [← cancel_mono g]
simp)
inv := kernel.lift _ (kernel.ι _) (by simp)
#align category_theory.limits.kernel_comp_mono CategoryTheory.Limits.kernelCompMono
#adaptation_note /-- nightly-2024-04-01 The `symm` wasn't previously necessary. -/
instance hasKernel_iso_comp {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) [IsIso f] [HasKernel g] :
HasKernel (f ≫ g) where
exists_limit :=
⟨{ cone := KernelFork.ofι (kernel.ι g ≫ inv f) (by simp)
isLimit := isLimitAux _ (fun s => kernel.lift _ (s.ι ≫ f) (by aesop_cat))
(by aesop_cat) fun s m w => by
simp_rw [← w]
symm
apply equalizer.hom_ext
simp }⟩
#align category_theory.limits.has_kernel_iso_comp CategoryTheory.Limits.hasKernel_iso_comp
/-- When `f` is an isomorphism, the kernel of `f ≫ g` is isomorphic to the kernel of `g`.
-/
@[simps]
def kernelIsIsoComp {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) [IsIso f] [HasKernel g] :
kernel (f ≫ g) ≅ kernel g where
hom := kernel.lift _ (kernel.ι _ ≫ f) (by simp)
inv := kernel.lift _ (kernel.ι _ ≫ inv f) (by simp)
#align category_theory.limits.kernel_is_iso_comp CategoryTheory.Limits.kernelIsIsoComp
end
section HasZeroObject
variable [HasZeroObject C]
open ZeroObject
/-- The morphism from the zero object determines a cone on a kernel diagram -/
def kernel.zeroKernelFork : KernelFork f where
pt := 0
π := { app := fun j => 0 }
#align category_theory.limits.kernel.zero_kernel_fork CategoryTheory.Limits.kernel.zeroKernelFork
/-- The map from the zero object is a kernel of a monomorphism -/
def kernel.isLimitConeZeroCone [Mono f] : IsLimit (kernel.zeroKernelFork f) :=
Fork.IsLimit.mk _ (fun s => 0)
(fun s => by
erw [zero_comp]
refine (zero_of_comp_mono f ?_).symm
exact KernelFork.condition _)
fun _ _ _ => zero_of_to_zero _
#align category_theory.limits.kernel.is_limit_cone_zero_cone CategoryTheory.Limits.kernel.isLimitConeZeroCone
/-- The kernel of a monomorphism is isomorphic to the zero object -/
def kernel.ofMono [HasKernel f] [Mono f] : kernel f ≅ 0 :=
Functor.mapIso (Cones.forget _) <|
IsLimit.uniqueUpToIso (limit.isLimit (parallelPair f 0)) (kernel.isLimitConeZeroCone f)
#align category_theory.limits.kernel.of_mono CategoryTheory.Limits.kernel.ofMono
/-- The kernel morphism of a monomorphism is a zero morphism -/
theorem kernel.ι_of_mono [HasKernel f] [Mono f] : kernel.ι f = 0 :=
zero_of_source_iso_zero _ (kernel.ofMono f)
#align category_theory.limits.kernel.ι_of_mono CategoryTheory.Limits.kernel.ι_of_mono
/-- If `g ≫ f = 0` implies `g = 0` for all `g`, then `0 : 0 ⟶ X` is a kernel of `f`. -/
def zeroKernelOfCancelZero {X Y : C} (f : X ⟶ Y)
(hf : ∀ (Z : C) (g : Z ⟶ X) (_ : g ≫ f = 0), g = 0) :
IsLimit (KernelFork.ofι (0 : 0 ⟶ X) (show 0 ≫ f = 0 by simp)) :=
Fork.IsLimit.mk _ (fun s => 0) (fun s => by rw [hf _ _ (KernelFork.condition s), zero_comp])
fun s m _ => by dsimp; apply HasZeroObject.to_zero_ext
#align category_theory.limits.zero_kernel_of_cancel_zero CategoryTheory.Limits.zeroKernelOfCancelZero
end HasZeroObject
section Transport
/-- If `i` is an isomorphism such that `l ≫ i.hom = f`, any kernel of `f` is a kernel of `l`. -/
def IsKernel.ofCompIso {Z : C} (l : X ⟶ Z) (i : Z ≅ Y) (h : l ≫ i.hom = f) {s : KernelFork f}
(hs : IsLimit s) :
IsLimit
(KernelFork.ofι (Fork.ι s) <| show Fork.ι s ≫ l = 0 by simp [← i.comp_inv_eq.2 h.symm]) :=
Fork.IsLimit.mk _ (fun s => hs.lift <| KernelFork.ofι (Fork.ι s) <| by simp [← h])
(fun s => by simp) fun s m h => by
apply Fork.IsLimit.hom_ext hs
simpa using h
#align category_theory.limits.is_kernel.of_comp_iso CategoryTheory.Limits.IsKernel.ofCompIso
/-- If `i` is an isomorphism such that `l ≫ i.hom = f`, the kernel of `f` is a kernel of `l`. -/
def kernel.ofCompIso [HasKernel f] {Z : C} (l : X ⟶ Z) (i : Z ≅ Y) (h : l ≫ i.hom = f) :
IsLimit
(KernelFork.ofι (kernel.ι f) <| show kernel.ι f ≫ l = 0 by simp [← i.comp_inv_eq.2 h.symm]) :=
IsKernel.ofCompIso f l i h <| limit.isLimit _
#align category_theory.limits.kernel.of_comp_iso CategoryTheory.Limits.kernel.ofCompIso
/-- If `s` is any limit kernel cone over `f` and if `i` is an isomorphism such that
`i.hom ≫ s.ι = l`, then `l` is a kernel of `f`. -/
def IsKernel.isoKernel {Z : C} (l : Z ⟶ X) {s : KernelFork f} (hs : IsLimit s) (i : Z ≅ s.pt)
(h : i.hom ≫ Fork.ι s = l) : IsLimit (KernelFork.ofι l <| show l ≫ f = 0 by simp [← h]) :=
IsLimit.ofIsoLimit hs <|
Cones.ext i.symm fun j => by
cases j
· exact (Iso.eq_inv_comp i).2 h
· dsimp; rw [← h]; simp
#align category_theory.limits.is_kernel.iso_kernel CategoryTheory.Limits.IsKernel.isoKernel
/-- If `i` is an isomorphism such that `i.hom ≫ kernel.ι f = l`, then `l` is a kernel of `f`. -/
def kernel.isoKernel [HasKernel f] {Z : C} (l : Z ⟶ X) (i : Z ≅ kernel f)
(h : i.hom ≫ kernel.ι f = l) :
IsLimit (@KernelFork.ofι _ _ _ _ _ f _ l <| by simp [← h]) :=
IsKernel.isoKernel f l (limit.isLimit _) i h
#align category_theory.limits.kernel.iso_kernel CategoryTheory.Limits.kernel.isoKernel
end Transport
section
variable (X Y)
/-- The kernel morphism of a zero morphism is an isomorphism -/
theorem kernel.ι_of_zero : IsIso (kernel.ι (0 : X ⟶ Y)) :=
equalizer.ι_of_self _
#align category_theory.limits.kernel.ι_of_zero CategoryTheory.Limits.kernel.ι_of_zero
end
section
/-- A cokernel cofork is just a cofork where the second morphism is a zero morphism. -/
abbrev CokernelCofork :=
Cofork f 0
#align category_theory.limits.cokernel_cofork CategoryTheory.Limits.CokernelCofork
variable {f}
@[reassoc (attr := simp)]
theorem CokernelCofork.condition (s : CokernelCofork f) : f ≫ s.π = 0 := by
rw [Cofork.condition, zero_comp]
#align category_theory.limits.cokernel_cofork.condition CategoryTheory.Limits.CokernelCofork.condition
-- Porting note (#10618): simp can prove this, removed simp tag
theorem CokernelCofork.π_eq_zero (s : CokernelCofork f) : s.ι.app zero = 0 := by
simp [Cofork.app_zero_eq_comp_π_right]
#align category_theory.limits.cokernel_cofork.π_eq_zero CategoryTheory.Limits.CokernelCofork.π_eq_zero
/-- A morphism `π` satisfying `f ≫ π = 0` determines a cokernel cofork on `f`. -/
abbrev CokernelCofork.ofπ {Z : C} (π : Y ⟶ Z) (w : f ≫ π = 0) : CokernelCofork f :=
Cofork.ofπ π <| by rw [w, zero_comp]
#align category_theory.limits.cokernel_cofork.of_π CategoryTheory.Limits.CokernelCofork.ofπ
@[simp]
theorem CokernelCofork.π_ofπ {X Y P : C} (f : X ⟶ Y) (π : Y ⟶ P) (w : f ≫ π = 0) :
Cofork.π (CokernelCofork.ofπ π w) = π :=
rfl
#align category_theory.limits.cokernel_cofork.π_of_π CategoryTheory.Limits.CokernelCofork.π_ofπ
/-- Every cokernel cofork `s` is isomorphic (actually, equal) to `cofork.ofπ (cofork.π s) _`. -/
def isoOfπ (s : Cofork f 0) : s ≅ Cofork.ofπ (Cofork.π s) (Cofork.condition s) :=
Cocones.ext (Iso.refl _) fun j => by cases j <;> aesop_cat
#align category_theory.limits.iso_of_π CategoryTheory.Limits.isoOfπ
/-- If `π = π'`, then `CokernelCofork.of_π π _` and `CokernelCofork.of_π π' _` are isomorphic. -/
def ofπCongr {P : C} {π π' : Y ⟶ P} {w : f ≫ π = 0} (h : π = π') :
CokernelCofork.ofπ π w ≅ CokernelCofork.ofπ π' (by rw [← h, w]) :=
Cocones.ext (Iso.refl _) fun j => by cases j <;> aesop_cat
#align category_theory.limits.of_π_congr CategoryTheory.Limits.ofπCongr
/-- If `s` is a colimit cokernel cofork, then every `k : Y ⟶ W` satisfying `f ≫ k = 0` induces
`l : s.X ⟶ W` such that `cofork.π s ≫ l = k`. -/
def CokernelCofork.IsColimit.desc' {s : CokernelCofork f} (hs : IsColimit s) {W : C} (k : Y ⟶ W)
(h : f ≫ k = 0) : { l : s.pt ⟶ W // Cofork.π s ≫ l = k } :=
⟨hs.desc <| CokernelCofork.ofπ _ h, hs.fac _ _⟩
#align category_theory.limits.cokernel_cofork.is_colimit.desc' CategoryTheory.Limits.CokernelCofork.IsColimit.desc'
/-- This is a slightly more convenient method to verify that a cokernel cofork is a colimit cocone.
It only asks for a proof of facts that carry any mathematical content -/
def isColimitAux (t : CokernelCofork f) (desc : ∀ s : CokernelCofork f, t.pt ⟶ s.pt)
(fac : ∀ s : CokernelCofork f, t.π ≫ desc s = s.π)
(uniq : ∀ (s : CokernelCofork f) (m : t.pt ⟶ s.pt) (_ : t.π ≫ m = s.π), m = desc s) :
IsColimit t :=
{ desc
fac := fun s j => by
cases j
· simp
· exact fac s
uniq := fun s m w => uniq s m (w Limits.WalkingParallelPair.one) }
#align category_theory.limits.is_colimit_aux CategoryTheory.Limits.isColimitAux
/-- This is a more convenient formulation to show that a `CokernelCofork` constructed using
`CokernelCofork.ofπ` is a limit cone.
-/
def CokernelCofork.IsColimit.ofπ {Z : C} (g : Y ⟶ Z) (eq : f ≫ g = 0)
(desc : ∀ {Z' : C} (g' : Y ⟶ Z') (_ : f ≫ g' = 0), Z ⟶ Z')
(fac : ∀ {Z' : C} (g' : Y ⟶ Z') (eq' : f ≫ g' = 0), g ≫ desc g' eq' = g')
(uniq :
∀ {Z' : C} (g' : Y ⟶ Z') (eq' : f ≫ g' = 0) (m : Z ⟶ Z') (_ : g ≫ m = g'), m = desc g' eq') :
IsColimit (CokernelCofork.ofπ g eq) :=
isColimitAux _ (fun s => desc s.π s.condition) (fun s => fac s.π s.condition) fun s =>
uniq s.π s.condition
#align category_theory.limits.cokernel_cofork.is_colimit.of_π CategoryTheory.Limits.CokernelCofork.IsColimit.ofπ
/-- This is a more convenient formulation to show that a `CokernelCofork` of the form
`CokernelCofork.ofπ p _` is a colimit cocone when we know that `p` is an epimorphism. -/
def CokernelCofork.IsColimit.ofπ' {X Y Q : C} {f : X ⟶ Y} (p : Y ⟶ Q) (w : f ≫ p = 0)
(h : ∀ {A : C} (k : Y ⟶ A) (_ : f ≫ k = 0), { l : Q ⟶ A // p ≫ l = k}) [hp : Epi p] :
IsColimit (CokernelCofork.ofπ p w) :=
ofπ _ _ (fun {A} k hk => (h k hk).1) (fun {A} k hk => (h k hk).2) (fun {A} k hk m hm => by
rw [← cancel_epi p, (h k hk).2, hm])
/-- Every cokernel of `f` induces a cokernel of `g ≫ f` if `g` is epi. -/
def isCokernelEpiComp {c : CokernelCofork f} (i : IsColimit c) {W} (g : W ⟶ X) [hg : Epi g]
{h : W ⟶ Y} (hh : h = g ≫ f) :
IsColimit (CokernelCofork.ofπ c.π (by rw [hh]; simp) : CokernelCofork h) :=
Cofork.IsColimit.mk' _ fun s =>
let s' : CokernelCofork f :=
Cofork.ofπ s.π
(by
apply hg.left_cancellation
rw [← Category.assoc, ← hh, s.condition]
simp)
let l := CokernelCofork.IsColimit.desc' i s'.π s'.condition
⟨l.1, l.2, fun hm => by
apply Cofork.IsColimit.hom_ext i; rw [Cofork.π_ofπ] at hm; rw [hm]; exact l.2.symm⟩
#align category_theory.limits.is_cokernel_epi_comp CategoryTheory.Limits.isCokernelEpiComp
@[simp]
theorem isCokernelEpiComp_desc {c : CokernelCofork f} (i : IsColimit c) {W} (g : W ⟶ X) [hg : Epi g]
{h : W ⟶ Y} (hh : h = g ≫ f) (s : CokernelCofork h) :
(isCokernelEpiComp i g hh).desc s =
i.desc
(Cofork.ofπ s.π
(by
rw [← cancel_epi g, ← Category.assoc, ← hh]
simp)) :=
rfl
#align category_theory.limits.is_cokernel_epi_comp_desc CategoryTheory.Limits.isCokernelEpiComp_desc
/-- Every cokernel of `g ≫ f` is also a cokernel of `f`, as long as `f ≫ c.π` vanishes. -/
def isCokernelOfComp {W : C} (g : W ⟶ X) (h : W ⟶ Y) {c : CokernelCofork h} (i : IsColimit c)
(hf : f ≫ c.π = 0) (hfg : g ≫ f = h) : IsColimit (CokernelCofork.ofπ c.π hf) :=
Cofork.IsColimit.mk _ (fun s => i.desc (CokernelCofork.ofπ s.π (by simp [← hfg])))
(fun s => by simp only [CokernelCofork.π_ofπ, Cofork.IsColimit.π_desc]) fun s m h => by
apply Cofork.IsColimit.hom_ext i
simpa using h
#align category_theory.limits.is_cokernel_of_comp CategoryTheory.Limits.isCokernelOfComp
/-- `Y` identifies to the cokernel of a zero map `X ⟶ Y`. -/
def CokernelCofork.IsColimit.ofId {X Y : C} (f : X ⟶ Y) (hf : f = 0) :
IsColimit (CokernelCofork.ofπ (𝟙 Y) (show f ≫ 𝟙 Y = 0 by rw [hf, zero_comp])) :=
CokernelCofork.IsColimit.ofπ _ _ (fun x _ => x) (fun _ _ => Category.id_comp _)
(fun _ _ _ hb => by simp only [← hb, Category.id_comp])
/-- Any zero object identifies to the cokernel of a given epimorphisms. -/
def CokernelCofork.IsColimit.ofEpiOfIsZero {X Y : C} {f : X ⟶ Y} (c : CokernelCofork f)
(hf : Epi f) (h : IsZero c.pt) : IsColimit c :=
isColimitAux _ (fun s => 0) (fun s => by rw [comp_zero, ← cancel_epi f, comp_zero, s.condition])
(fun _ _ _ => h.eq_of_src _ _)
lemma CokernelCofork.IsColimit.isIso_π {X Y : C} {f : X ⟶ Y} (c : CokernelCofork f)
(hc : IsColimit c) (hf : f = 0) : IsIso c.π := by
let e : c.pt ≅ Y := IsColimit.coconePointUniqueUpToIso hc
(CokernelCofork.IsColimit.ofId (f : X ⟶ Y) hf)
have eq : c.π ≫ e.hom = 𝟙 Y := Cofork.IsColimit.π_desc hc
haveI : IsIso (c.π ≫ e.hom) := by
rw [eq]
dsimp
infer_instance
exact IsIso.of_isIso_comp_right c.π e.hom
end
namespace CokernelCofork
variable {f} {X' Y' : C} {f' : X' ⟶ Y'}
/-- The morphism between points of cokernel coforks induced by a morphism
in the category of arrows. -/
def mapOfIsColimit {cc : CokernelCofork f} (hf : IsColimit cc) (cc' : CokernelCofork f')
(φ : Arrow.mk f ⟶ Arrow.mk f') : cc.pt ⟶ cc'.pt :=
hf.desc (CokernelCofork.ofπ (φ.right ≫ cc'.π) (by
erw [← Arrow.w_assoc φ, condition, comp_zero]))
@[reassoc (attr := simp)]
lemma π_mapOfIsColimit {cc : CokernelCofork f} (hf : IsColimit cc) (cc' : CokernelCofork f')
(φ : Arrow.mk f ⟶ Arrow.mk f') :
cc.π ≫ mapOfIsColimit hf cc' φ = φ.right ≫ cc'.π :=
hf.fac _ _
/-- The isomorphism between points of limit cokernel coforks induced by an isomorphism
in the category of arrows. -/
@[simps]
def mapIsoOfIsColimit {cc : CokernelCofork f} {cc' : CokernelCofork f'}
(hf : IsColimit cc) (hf' : IsColimit cc')
(φ : Arrow.mk f ≅ Arrow.mk f') : cc.pt ≅ cc'.pt where
hom := mapOfIsColimit hf cc' φ.hom
inv := mapOfIsColimit hf' cc φ.inv
hom_inv_id := Cofork.IsColimit.hom_ext hf (by simp)
inv_hom_id := Cofork.IsColimit.hom_ext hf' (by simp)
end CokernelCofork
section
variable [HasCokernel f]
/-- The cokernel of a morphism, expressed as the coequalizer with the 0 morphism. -/
abbrev cokernel : C :=
coequalizer f 0
#align category_theory.limits.cokernel CategoryTheory.Limits.cokernel
/-- The map from the target of `f` to `cokernel f`. -/
abbrev cokernel.π : Y ⟶ cokernel f :=
coequalizer.π f 0
#align category_theory.limits.cokernel.π CategoryTheory.Limits.cokernel.π
@[simp]
theorem coequalizer_as_cokernel : coequalizer.π f 0 = cokernel.π f :=
rfl
#align category_theory.limits.coequalizer_as_cokernel CategoryTheory.Limits.coequalizer_as_cokernel
@[reassoc (attr := simp)]
theorem cokernel.condition : f ≫ cokernel.π f = 0 :=
CokernelCofork.condition _
#align category_theory.limits.cokernel.condition CategoryTheory.Limits.cokernel.condition
/-- The cokernel built from `cokernel.π f` is colimiting. -/
def cokernelIsCokernel :
IsColimit (Cofork.ofπ (cokernel.π f) ((cokernel.condition f).trans zero_comp.symm)) :=
IsColimit.ofIsoColimit (colimit.isColimit _) (Cofork.ext (Iso.refl _))
#align category_theory.limits.cokernel_is_cokernel CategoryTheory.Limits.cokernelIsCokernel
/-- Given any morphism `k : Y ⟶ W` such that `f ≫ k = 0`, `k` factors through `cokernel.π f`
via `cokernel.desc : cokernel f ⟶ W`. -/
abbrev cokernel.desc {W : C} (k : Y ⟶ W) (h : f ≫ k = 0) : cokernel f ⟶ W :=
(cokernelIsCokernel f).desc (CokernelCofork.ofπ k h)
#align category_theory.limits.cokernel.desc CategoryTheory.Limits.cokernel.desc
@[reassoc (attr := simp)]
theorem cokernel.π_desc {W : C} (k : Y ⟶ W) (h : f ≫ k = 0) :
cokernel.π f ≫ cokernel.desc f k h = k :=
(cokernelIsCokernel f).fac (CokernelCofork.ofπ k h) WalkingParallelPair.one
#align category_theory.limits.cokernel.π_desc CategoryTheory.Limits.cokernel.π_desc
-- Porting note: added to ease the port of `Abelian.Exact`
@[reassoc (attr := simp)]
lemma colimit_ι_zero_cokernel_desc {C : Type*} [Category C]
[HasZeroMorphisms C] {X Y Z : C} (f : X ⟶ Y) (g : Y ⟶ Z) (h : f ≫ g = 0) [HasCokernel f] :
colimit.ι (parallelPair f 0) WalkingParallelPair.zero ≫ cokernel.desc f g h = 0 := by
rw [(colimit.w (parallelPair f 0) WalkingParallelPairHom.left).symm]
aesop_cat
@[simp]
theorem cokernel.desc_zero {W : C} {h} : cokernel.desc f (0 : Y ⟶ W) h = 0 := by
ext; simp
#align category_theory.limits.cokernel.desc_zero CategoryTheory.Limits.cokernel.desc_zero
instance cokernel.desc_epi {W : C} (k : Y ⟶ W) (h : f ≫ k = 0) [Epi k] :
Epi (cokernel.desc f k h) :=
⟨fun {Z} g g' w => by
replace w := cokernel.π f ≫= w
simp only [cokernel.π_desc_assoc] at w
exact (cancel_epi k).1 w⟩
#align category_theory.limits.cokernel.desc_epi CategoryTheory.Limits.cokernel.desc_epi
/-- Any morphism `k : Y ⟶ W` satisfying `f ≫ k = 0` induces `l : cokernel f ⟶ W` such that
`cokernel.π f ≫ l = k`. -/
def cokernel.desc' {W : C} (k : Y ⟶ W) (h : f ≫ k = 0) :
{ l : cokernel f ⟶ W // cokernel.π f ≫ l = k } :=
⟨cokernel.desc f k h, cokernel.π_desc _ _ _⟩
#align category_theory.limits.cokernel.desc' CategoryTheory.Limits.cokernel.desc'
/-- A commuting square induces a morphism of cokernels. -/
abbrev cokernel.map {X' Y' : C} (f' : X' ⟶ Y') [HasCokernel f'] (p : X ⟶ X') (q : Y ⟶ Y')
(w : f ≫ q = p ≫ f') : cokernel f ⟶ cokernel f' :=
cokernel.desc f (q ≫ cokernel.π f') (by
have : f ≫ q ≫ π f' = p ≫ f' ≫ π f' := by
simp only [← Category.assoc]
apply congrArg (· ≫ π f') w
simp [this])
#align category_theory.limits.cokernel.map CategoryTheory.Limits.cokernel.map
/-- Given a commutative diagram
X --f--> Y --g--> Z
| | |
| | |
v v v
X' -f'-> Y' -g'-> Z'
with horizontal arrows composing to zero,
then we obtain a commutative square
cokernel f ---> Z
| |
| cokernel.map |
| |
v v
cokernel f' --> Z'
-/
theorem cokernel.map_desc {X Y Z X' Y' Z' : C} (f : X ⟶ Y) [HasCokernel f] (g : Y ⟶ Z)
(w : f ≫ g = 0) (f' : X' ⟶ Y') [HasCokernel f'] (g' : Y' ⟶ Z') (w' : f' ≫ g' = 0) (p : X ⟶ X')
(q : Y ⟶ Y') (r : Z ⟶ Z') (h₁ : f ≫ q = p ≫ f') (h₂ : g ≫ r = q ≫ g') :
cokernel.map f f' p q h₁ ≫ cokernel.desc f' g' w' = cokernel.desc f g w ≫ r := by
ext; simp [h₂]
#align category_theory.limits.cokernel.map_desc CategoryTheory.Limits.cokernel.map_desc
/-- A commuting square of isomorphisms induces an isomorphism of cokernels. -/
@[simps]
def cokernel.mapIso {X' Y' : C} (f' : X' ⟶ Y') [HasCokernel f'] (p : X ≅ X') (q : Y ≅ Y')
(w : f ≫ q.hom = p.hom ≫ f') : cokernel f ≅ cokernel f' where
hom := cokernel.map f f' p.hom q.hom w
inv := cokernel.map f' f p.inv q.inv (by
refine (cancel_mono q.hom).1 ?_
simp [w])
#align category_theory.limits.cokernel.map_iso CategoryTheory.Limits.cokernel.mapIso
/-- The cokernel of the zero morphism is an isomorphism -/
instance cokernel.π_zero_isIso : IsIso (cokernel.π (0 : X ⟶ Y)) :=
coequalizer.π_of_self _
#align category_theory.limits.cokernel.π_zero_is_iso CategoryTheory.Limits.cokernel.π_zero_isIso
theorem eq_zero_of_mono_cokernel [Mono (cokernel.π f)] : f = 0 :=
(cancel_mono (cokernel.π f)).1 (by simp)
#align category_theory.limits.eq_zero_of_mono_cokernel CategoryTheory.Limits.eq_zero_of_mono_cokernel
/-- The cokernel of a zero morphism is isomorphic to the target. -/
def cokernelZeroIsoTarget : cokernel (0 : X ⟶ Y) ≅ Y :=
coequalizer.isoTargetOfSelf 0
#align category_theory.limits.cokernel_zero_iso_target CategoryTheory.Limits.cokernelZeroIsoTarget
@[simp]
theorem cokernelZeroIsoTarget_hom :
cokernelZeroIsoTarget.hom = cokernel.desc (0 : X ⟶ Y) (𝟙 Y) (by simp) := by
ext; simp [cokernelZeroIsoTarget]
#align category_theory.limits.cokernel_zero_iso_target_hom CategoryTheory.Limits.cokernelZeroIsoTarget_hom
@[simp]
theorem cokernelZeroIsoTarget_inv : cokernelZeroIsoTarget.inv = cokernel.π (0 : X ⟶ Y) :=
rfl
#align category_theory.limits.cokernel_zero_iso_target_inv CategoryTheory.Limits.cokernelZeroIsoTarget_inv
/-- If two morphisms are known to be equal, then their cokernels are isomorphic. -/
def cokernelIsoOfEq {f g : X ⟶ Y} [HasCokernel f] [HasCokernel g] (h : f = g) :
cokernel f ≅ cokernel g :=
HasColimit.isoOfNatIso (by simp [h]; rfl)
#align category_theory.limits.cokernel_iso_of_eq CategoryTheory.Limits.cokernelIsoOfEq
@[simp]
theorem cokernelIsoOfEq_refl {h : f = f} : cokernelIsoOfEq h = Iso.refl (cokernel f) := by
ext; simp [cokernelIsoOfEq]
#align category_theory.limits.cokernel_iso_of_eq_refl CategoryTheory.Limits.cokernelIsoOfEq_refl
@[reassoc (attr := simp)]
theorem π_comp_cokernelIsoOfEq_hom {f g : X ⟶ Y} [HasCokernel f] [HasCokernel g] (h : f = g) :
cokernel.π f ≫ (cokernelIsoOfEq h).hom = cokernel.π g := by
cases h; simp
#align category_theory.limits.π_comp_cokernel_iso_of_eq_hom CategoryTheory.Limits.π_comp_cokernelIsoOfEq_hom
@[reassoc (attr := simp)]
| Mathlib/CategoryTheory/Limits/Shapes/Kernels.lean | 896 | 898 | theorem π_comp_cokernelIsoOfEq_inv {f g : X ⟶ Y} [HasCokernel f] [HasCokernel g] (h : f = g) :
cokernel.π _ ≫ (cokernelIsoOfEq h).inv = cokernel.π _ := by |
cases h; simp
|
/-
Copyright (c) 2022 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Oleksandr Manzyuk
-/
import Mathlib.CategoryTheory.Bicategory.Basic
import Mathlib.CategoryTheory.Monoidal.Mon_
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Equalizers
#align_import category_theory.monoidal.Bimod from "leanprover-community/mathlib"@"4698e35ca56a0d4fa53aa5639c3364e0a77f4eba"
/-!
# The category of bimodule objects over a pair of monoid objects.
-/
universe v₁ v₂ u₁ u₂
open CategoryTheory
open CategoryTheory.MonoidalCategory
variable {C : Type u₁} [Category.{v₁} C] [MonoidalCategory.{v₁} C]
section
open CategoryTheory.Limits
variable [HasCoequalizers C]
section
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)]
theorem id_tensor_π_preserves_coequalizer_inv_desc {W X Y Z : C} (f g : X ⟶ Y) (h : Z ⊗ Y ⟶ W)
(wh : (Z ◁ f) ≫ h = (Z ◁ g) ≫ h) :
(Z ◁ coequalizer.π f g) ≫
(PreservesCoequalizer.iso (tensorLeft Z) f g).inv ≫ coequalizer.desc h wh =
h :=
map_π_preserves_coequalizer_inv_desc (tensorLeft Z) f g h wh
#align id_tensor_π_preserves_coequalizer_inv_desc id_tensor_π_preserves_coequalizer_inv_desc
theorem id_tensor_π_preserves_coequalizer_inv_colimMap_desc {X Y Z X' Y' Z' : C} (f g : X ⟶ Y)
(f' g' : X' ⟶ Y') (p : Z ⊗ X ⟶ X') (q : Z ⊗ Y ⟶ Y') (wf : (Z ◁ f) ≫ q = p ≫ f')
(wg : (Z ◁ g) ≫ q = p ≫ g') (h : Y' ⟶ Z') (wh : f' ≫ h = g' ≫ h) :
(Z ◁ coequalizer.π f g) ≫
(PreservesCoequalizer.iso (tensorLeft Z) f g).inv ≫
colimMap (parallelPairHom (Z ◁ f) (Z ◁ g) f' g' p q wf wg) ≫ coequalizer.desc h wh =
q ≫ h :=
map_π_preserves_coequalizer_inv_colimMap_desc (tensorLeft Z) f g f' g' p q wf wg h wh
#align id_tensor_π_preserves_coequalizer_inv_colim_map_desc id_tensor_π_preserves_coequalizer_inv_colimMap_desc
end
section
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)]
theorem π_tensor_id_preserves_coequalizer_inv_desc {W X Y Z : C} (f g : X ⟶ Y) (h : Y ⊗ Z ⟶ W)
(wh : (f ▷ Z) ≫ h = (g ▷ Z) ≫ h) :
(coequalizer.π f g ▷ Z) ≫
(PreservesCoequalizer.iso (tensorRight Z) f g).inv ≫ coequalizer.desc h wh =
h :=
map_π_preserves_coequalizer_inv_desc (tensorRight Z) f g h wh
#align π_tensor_id_preserves_coequalizer_inv_desc π_tensor_id_preserves_coequalizer_inv_desc
theorem π_tensor_id_preserves_coequalizer_inv_colimMap_desc {X Y Z X' Y' Z' : C} (f g : X ⟶ Y)
(f' g' : X' ⟶ Y') (p : X ⊗ Z ⟶ X') (q : Y ⊗ Z ⟶ Y') (wf : (f ▷ Z) ≫ q = p ≫ f')
(wg : (g ▷ Z) ≫ q = p ≫ g') (h : Y' ⟶ Z') (wh : f' ≫ h = g' ≫ h) :
(coequalizer.π f g ▷ Z) ≫
(PreservesCoequalizer.iso (tensorRight Z) f g).inv ≫
colimMap (parallelPairHom (f ▷ Z) (g ▷ Z) f' g' p q wf wg) ≫ coequalizer.desc h wh =
q ≫ h :=
map_π_preserves_coequalizer_inv_colimMap_desc (tensorRight Z) f g f' g' p q wf wg h wh
#align π_tensor_id_preserves_coequalizer_inv_colim_map_desc π_tensor_id_preserves_coequalizer_inv_colimMap_desc
end
end
/-- A bimodule object for a pair of monoid objects, all internal to some monoidal category. -/
structure Bimod (A B : Mon_ C) where
X : C
actLeft : A.X ⊗ X ⟶ X
one_actLeft : (A.one ▷ X) ≫ actLeft = (λ_ X).hom := by aesop_cat
left_assoc :
(A.mul ▷ X) ≫ actLeft = (α_ A.X A.X X).hom ≫ (A.X ◁ actLeft) ≫ actLeft := by aesop_cat
actRight : X ⊗ B.X ⟶ X
actRight_one : (X ◁ B.one) ≫ actRight = (ρ_ X).hom := by aesop_cat
right_assoc :
(X ◁ B.mul) ≫ actRight = (α_ X B.X B.X).inv ≫ (actRight ▷ B.X) ≫ actRight := by
aesop_cat
middle_assoc :
(actLeft ▷ B.X) ≫ actRight = (α_ A.X X B.X).hom ≫ (A.X ◁ actRight) ≫ actLeft := by
aesop_cat
set_option linter.uppercaseLean3 false in
#align Bimod Bimod
attribute [reassoc (attr := simp)] Bimod.one_actLeft Bimod.actRight_one Bimod.left_assoc
Bimod.right_assoc Bimod.middle_assoc
namespace Bimod
variable {A B : Mon_ C} (M : Bimod A B)
/-- A morphism of bimodule objects. -/
@[ext]
structure Hom (M N : Bimod A B) where
hom : M.X ⟶ N.X
left_act_hom : M.actLeft ≫ hom = (A.X ◁ hom) ≫ N.actLeft := by aesop_cat
right_act_hom : M.actRight ≫ hom = (hom ▷ B.X) ≫ N.actRight := by aesop_cat
set_option linter.uppercaseLean3 false in
#align Bimod.hom Bimod.Hom
attribute [reassoc (attr := simp)] Hom.left_act_hom Hom.right_act_hom
/-- The identity morphism on a bimodule object. -/
@[simps]
def id' (M : Bimod A B) : Hom M M where hom := 𝟙 M.X
set_option linter.uppercaseLean3 false in
#align Bimod.id' Bimod.id'
instance homInhabited (M : Bimod A B) : Inhabited (Hom M M) :=
⟨id' M⟩
set_option linter.uppercaseLean3 false in
#align Bimod.hom_inhabited Bimod.homInhabited
/-- Composition of bimodule object morphisms. -/
@[simps]
def comp {M N O : Bimod A B} (f : Hom M N) (g : Hom N O) : Hom M O where hom := f.hom ≫ g.hom
set_option linter.uppercaseLean3 false in
#align Bimod.comp Bimod.comp
instance : Category (Bimod A B) where
Hom M N := Hom M N
id := id'
comp f g := comp f g
-- Porting note: added because `Hom.ext` is not triggered automatically
@[ext]
lemma hom_ext {M N : Bimod A B} (f g : M ⟶ N) (h : f.hom = g.hom) : f = g :=
Hom.ext _ _ h
@[simp]
theorem id_hom' (M : Bimod A B) : (𝟙 M : Hom M M).hom = 𝟙 M.X :=
rfl
set_option linter.uppercaseLean3 false in
#align Bimod.id_hom' Bimod.id_hom'
@[simp]
theorem comp_hom' {M N K : Bimod A B} (f : M ⟶ N) (g : N ⟶ K) :
(f ≫ g : Hom M K).hom = f.hom ≫ g.hom :=
rfl
set_option linter.uppercaseLean3 false in
#align Bimod.comp_hom' Bimod.comp_hom'
/-- Construct an isomorphism of bimodules by giving an isomorphism between the underlying objects
and checking compatibility with left and right actions only in the forward direction.
-/
@[simps]
def isoOfIso {X Y : Mon_ C} {P Q : Bimod X Y} (f : P.X ≅ Q.X)
(f_left_act_hom : P.actLeft ≫ f.hom = (X.X ◁ f.hom) ≫ Q.actLeft)
(f_right_act_hom : P.actRight ≫ f.hom = (f.hom ▷ Y.X) ≫ Q.actRight) : P ≅ Q where
hom :=
{ hom := f.hom }
inv :=
{ hom := f.inv
left_act_hom := by
rw [← cancel_mono f.hom, Category.assoc, Category.assoc, Iso.inv_hom_id, Category.comp_id,
f_left_act_hom, ← Category.assoc, ← MonoidalCategory.whiskerLeft_comp, Iso.inv_hom_id,
MonoidalCategory.whiskerLeft_id, Category.id_comp]
right_act_hom := by
rw [← cancel_mono f.hom, Category.assoc, Category.assoc, Iso.inv_hom_id, Category.comp_id,
f_right_act_hom, ← Category.assoc, ← comp_whiskerRight, Iso.inv_hom_id,
MonoidalCategory.id_whiskerRight, Category.id_comp] }
hom_inv_id := by ext; dsimp; rw [Iso.hom_inv_id]
inv_hom_id := by ext; dsimp; rw [Iso.inv_hom_id]
set_option linter.uppercaseLean3 false in
#align Bimod.iso_of_iso Bimod.isoOfIso
variable (A)
/-- A monoid object as a bimodule over itself. -/
@[simps]
def regular : Bimod A A where
X := A.X
actLeft := A.mul
actRight := A.mul
set_option linter.uppercaseLean3 false in
#align Bimod.regular Bimod.regular
instance : Inhabited (Bimod A A) :=
⟨regular A⟩
/-- The forgetful functor from bimodule objects to the ambient category. -/
def forget : Bimod A B ⥤ C where
obj A := A.X
map f := f.hom
set_option linter.uppercaseLean3 false in
#align Bimod.forget Bimod.forget
open CategoryTheory.Limits
variable [HasCoequalizers C]
namespace TensorBimod
variable {R S T : Mon_ C} (P : Bimod R S) (Q : Bimod S T)
/-- The underlying object of the tensor product of two bimodules. -/
noncomputable def X : C :=
coequalizer (P.actRight ▷ Q.X) ((α_ _ _ _).hom ≫ (P.X ◁ Q.actLeft))
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.X Bimod.TensorBimod.X
section
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorLeft X)]
/-- Left action for the tensor product of two bimodules. -/
noncomputable def actLeft : R.X ⊗ X P Q ⟶ X P Q :=
(PreservesCoequalizer.iso (tensorLeft R.X) _ _).inv ≫
colimMap
(parallelPairHom _ _ _ _
((α_ _ _ _).inv ≫ ((α_ _ _ _).inv ▷ _) ≫ (P.actLeft ▷ S.X ▷ Q.X))
((α_ _ _ _).inv ≫ (P.actLeft ▷ Q.X))
(by
dsimp
simp only [Category.assoc]
slice_lhs 1 2 => rw [associator_inv_naturality_middle]
slice_rhs 3 4 => rw [← comp_whiskerRight, middle_assoc, comp_whiskerRight]
coherence)
(by
dsimp
slice_lhs 1 1 => rw [MonoidalCategory.whiskerLeft_comp]
slice_lhs 2 3 => rw [associator_inv_naturality_right]
slice_lhs 3 4 => rw [whisker_exchange]
coherence))
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.act_left Bimod.TensorBimod.actLeft
theorem whiskerLeft_π_actLeft :
(R.X ◁ coequalizer.π _ _) ≫ actLeft P Q =
(α_ _ _ _).inv ≫ (P.actLeft ▷ Q.X) ≫ coequalizer.π _ _ := by
erw [map_π_preserves_coequalizer_inv_colimMap (tensorLeft _)]
simp only [Category.assoc]
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.id_tensor_π_act_left Bimod.TensorBimod.whiskerLeft_π_actLeft
theorem one_act_left' : (R.one ▷ _) ≫ actLeft P Q = (λ_ _).hom := by
refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_
dsimp [X]
-- Porting note: had to replace `rw` by `erw`
slice_lhs 1 2 => erw [whisker_exchange]
slice_lhs 2 3 => rw [whiskerLeft_π_actLeft]
slice_lhs 1 2 => rw [associator_inv_naturality_left]
slice_lhs 2 3 => rw [← comp_whiskerRight, one_actLeft]
slice_rhs 1 2 => rw [leftUnitor_naturality]
coherence
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.one_act_left' Bimod.TensorBimod.one_act_left'
theorem left_assoc' :
(R.mul ▷ _) ≫ actLeft P Q = (α_ R.X R.X _).hom ≫ (R.X ◁ actLeft P Q) ≫ actLeft P Q := by
refine (cancel_epi ((tensorLeft _).map (coequalizer.π _ _))).1 ?_
dsimp [X]
slice_lhs 1 2 => rw [whisker_exchange]
slice_lhs 2 3 => rw [whiskerLeft_π_actLeft]
slice_lhs 1 2 => rw [associator_inv_naturality_left]
slice_lhs 2 3 => rw [← comp_whiskerRight, left_assoc, comp_whiskerRight, comp_whiskerRight]
slice_rhs 1 2 => rw [associator_naturality_right]
slice_rhs 2 3 =>
rw [← MonoidalCategory.whiskerLeft_comp, whiskerLeft_π_actLeft,
MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp]
slice_rhs 4 5 => rw [whiskerLeft_π_actLeft]
slice_rhs 3 4 => rw [associator_inv_naturality_middle]
coherence
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.left_assoc' Bimod.TensorBimod.left_assoc'
end
section
variable [∀ X : C, PreservesColimitsOfSize.{0, 0} (tensorRight X)]
/-- Right action for the tensor product of two bimodules. -/
noncomputable def actRight : X P Q ⊗ T.X ⟶ X P Q :=
(PreservesCoequalizer.iso (tensorRight T.X) _ _).inv ≫
colimMap
(parallelPairHom _ _ _ _
((α_ _ _ _).hom ≫ (α_ _ _ _).hom ≫ (P.X ◁ S.X ◁ Q.actRight) ≫ (α_ _ _ _).inv)
((α_ _ _ _).hom ≫ (P.X ◁ Q.actRight))
(by
dsimp
slice_lhs 1 2 => rw [associator_naturality_left]
slice_lhs 2 3 => rw [← whisker_exchange]
simp)
(by
dsimp
simp only [comp_whiskerRight, whisker_assoc, Category.assoc, Iso.inv_hom_id_assoc]
slice_lhs 3 4 =>
rw [← MonoidalCategory.whiskerLeft_comp, middle_assoc,
MonoidalCategory.whiskerLeft_comp]
simp))
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.act_right Bimod.TensorBimod.actRight
theorem π_tensor_id_actRight :
(coequalizer.π _ _ ▷ T.X) ≫ actRight P Q =
(α_ _ _ _).hom ≫ (P.X ◁ Q.actRight) ≫ coequalizer.π _ _ := by
erw [map_π_preserves_coequalizer_inv_colimMap (tensorRight _)]
simp only [Category.assoc]
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.π_tensor_id_act_right Bimod.TensorBimod.π_tensor_id_actRight
theorem actRight_one' : (_ ◁ T.one) ≫ actRight P Q = (ρ_ _).hom := by
refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_
dsimp [X]
-- Porting note: had to replace `rw` by `erw`
slice_lhs 1 2 =>erw [← whisker_exchange]
slice_lhs 2 3 => rw [π_tensor_id_actRight]
slice_lhs 1 2 => rw [associator_naturality_right]
slice_lhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, actRight_one]
simp
set_option linter.uppercaseLean3 false in
#align Bimod.tensor_Bimod.act_right_one' Bimod.TensorBimod.actRight_one'
| Mathlib/CategoryTheory/Monoidal/Bimod.lean | 329 | 344 | theorem right_assoc' :
(_ ◁ T.mul) ≫ actRight P Q =
(α_ _ T.X T.X).inv ≫ (actRight P Q ▷ T.X) ≫ actRight P Q := by |
refine (cancel_epi ((tensorRight _).map (coequalizer.π _ _))).1 ?_
dsimp [X]
-- Porting note: had to replace some `rw` by `erw`
slice_lhs 1 2 => rw [← whisker_exchange]
slice_lhs 2 3 => rw [π_tensor_id_actRight]
slice_lhs 1 2 => rw [associator_naturality_right]
slice_lhs 2 3 => rw [← MonoidalCategory.whiskerLeft_comp, right_assoc,
MonoidalCategory.whiskerLeft_comp, MonoidalCategory.whiskerLeft_comp]
slice_rhs 1 2 => rw [associator_inv_naturality_left]
slice_rhs 2 3 => rw [← comp_whiskerRight, π_tensor_id_actRight, comp_whiskerRight,
comp_whiskerRight]
slice_rhs 4 5 => rw [π_tensor_id_actRight]
simp
|
/-
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.EuclideanDomain.Basic
import Mathlib.RingTheory.PrincipalIdealDomain
import Mathlib.Algebra.GCDMonoid.Nat
#align_import ring_theory.int.basic from "leanprover-community/mathlib"@"e655e4ea5c6d02854696f97494997ba4c31be802"
/-!
# Divisibility over ℕ and ℤ
This file collects results for the integers and natural numbers that use ring theory in
their proofs or cases of ℕ and ℤ being examples of structures in ring theory.
## Main statements
* `Nat.factors_eq`: the multiset of elements of `Nat.factors` is equal to the factors
given by the `UniqueFactorizationMonoid` instance
## Tags
prime, irreducible, natural numbers, integers, normalization monoid, gcd monoid,
greatest common divisor, prime factorization, prime factors, unique factorization,
unique factors
-/
namespace Int
theorem gcd_eq_one_iff_coprime {a b : ℤ} : Int.gcd a b = 1 ↔ IsCoprime a b := by
constructor
· intro hg
obtain ⟨ua, -, ha⟩ := exists_unit_of_abs a
obtain ⟨ub, -, hb⟩ := exists_unit_of_abs b
use Nat.gcdA (Int.natAbs a) (Int.natAbs b) * ua, Nat.gcdB (Int.natAbs a) (Int.natAbs b) * ub
rw [mul_assoc, ← ha, mul_assoc, ← hb, mul_comm, mul_comm _ (Int.natAbs b : ℤ), ←
Nat.gcd_eq_gcd_ab, ← gcd_eq_natAbs, hg, Int.ofNat_one]
· rintro ⟨r, s, h⟩
by_contra hg
obtain ⟨p, ⟨hp, ha, hb⟩⟩ := Nat.Prime.not_coprime_iff_dvd.mp hg
apply Nat.Prime.not_dvd_one hp
rw [← natCast_dvd_natCast, Int.ofNat_one, ← h]
exact dvd_add ((natCast_dvd.mpr ha).mul_left _) ((natCast_dvd.mpr hb).mul_left _)
#align int.gcd_eq_one_iff_coprime Int.gcd_eq_one_iff_coprime
theorem coprime_iff_nat_coprime {a b : ℤ} : IsCoprime a b ↔ Nat.Coprime a.natAbs b.natAbs := by
rw [← gcd_eq_one_iff_coprime, Nat.coprime_iff_gcd_eq_one, gcd_eq_natAbs]
#align int.coprime_iff_nat_coprime Int.coprime_iff_nat_coprime
/-- If `gcd a (m * n) ≠ 1`, then `gcd a m ≠ 1` or `gcd a n ≠ 1`. -/
theorem gcd_ne_one_iff_gcd_mul_right_ne_one {a : ℤ} {m n : ℕ} :
a.gcd (m * n) ≠ 1 ↔ a.gcd m ≠ 1 ∨ a.gcd n ≠ 1 := by
simp only [gcd_eq_one_iff_coprime, ← not_and_or, not_iff_not, IsCoprime.mul_right_iff]
#align int.gcd_ne_one_iff_gcd_mul_right_ne_one Int.gcd_ne_one_iff_gcd_mul_right_ne_one
theorem sq_of_gcd_eq_one {a b c : ℤ} (h : Int.gcd a b = 1) (heq : a * b = c ^ 2) :
∃ a0 : ℤ, a = a0 ^ 2 ∨ a = -a0 ^ 2 := by
have h' : IsUnit (GCDMonoid.gcd a b) := by
rw [← coe_gcd, h, Int.ofNat_one]
exact isUnit_one
obtain ⟨d, ⟨u, hu⟩⟩ := exists_associated_pow_of_mul_eq_pow h' heq
use d
rw [← hu]
cases' Int.units_eq_one_or u with hu' hu' <;>
· rw [hu']
simp
#align int.sq_of_gcd_eq_one Int.sq_of_gcd_eq_one
theorem sq_of_coprime {a b c : ℤ} (h : IsCoprime a b) (heq : a * b = c ^ 2) :
∃ a0 : ℤ, a = a0 ^ 2 ∨ a = -a0 ^ 2 :=
sq_of_gcd_eq_one (gcd_eq_one_iff_coprime.mpr h) heq
#align int.sq_of_coprime Int.sq_of_coprime
theorem natAbs_euclideanDomain_gcd (a b : ℤ) :
Int.natAbs (EuclideanDomain.gcd a b) = Int.gcd a b := by
apply Nat.dvd_antisymm <;> rw [← Int.natCast_dvd_natCast]
· rw [Int.natAbs_dvd]
exact Int.dvd_gcd (EuclideanDomain.gcd_dvd_left _ _) (EuclideanDomain.gcd_dvd_right _ _)
· rw [Int.dvd_natAbs]
exact EuclideanDomain.dvd_gcd Int.gcd_dvd_left Int.gcd_dvd_right
#align int.nat_abs_euclidean_domain_gcd Int.natAbs_euclideanDomain_gcd
end Int
theorem Int.Prime.dvd_mul {m n : ℤ} {p : ℕ} (hp : Nat.Prime p) (h : (p : ℤ) ∣ m * n) :
p ∣ m.natAbs ∨ p ∣ n.natAbs := by
rwa [← hp.dvd_mul, ← Int.natAbs_mul, ← Int.natCast_dvd]
#align int.prime.dvd_mul Int.Prime.dvd_mul
theorem Int.Prime.dvd_mul' {m n : ℤ} {p : ℕ} (hp : Nat.Prime p) (h : (p : ℤ) ∣ m * n) :
(p : ℤ) ∣ m ∨ (p : ℤ) ∣ n := by
rw [Int.natCast_dvd, Int.natCast_dvd]
exact Int.Prime.dvd_mul hp h
#align int.prime.dvd_mul' Int.Prime.dvd_mul'
theorem Int.Prime.dvd_pow {n : ℤ} {k p : ℕ} (hp : Nat.Prime p) (h : (p : ℤ) ∣ n ^ k) :
p ∣ n.natAbs := by
rw [Int.natCast_dvd, Int.natAbs_pow] at h
exact hp.dvd_of_dvd_pow h
#align int.prime.dvd_pow Int.Prime.dvd_pow
theorem Int.Prime.dvd_pow' {n : ℤ} {k p : ℕ} (hp : Nat.Prime p) (h : (p : ℤ) ∣ n ^ k) :
(p : ℤ) ∣ n := by
rw [Int.natCast_dvd]
exact Int.Prime.dvd_pow hp h
#align int.prime.dvd_pow' Int.Prime.dvd_pow'
theorem prime_two_or_dvd_of_dvd_two_mul_pow_self_two {m : ℤ} {p : ℕ} (hp : Nat.Prime p)
(h : (p : ℤ) ∣ 2 * m ^ 2) : p = 2 ∨ p ∣ Int.natAbs m := by
cases' Int.Prime.dvd_mul hp h with hp2 hpp
· apply Or.intro_left
exact le_antisymm (Nat.le_of_dvd zero_lt_two hp2) (Nat.Prime.two_le hp)
· apply Or.intro_right
rw [sq, Int.natAbs_mul] at hpp
exact or_self_iff.mp ((Nat.Prime.dvd_mul hp).mp hpp)
#align prime_two_or_dvd_of_dvd_two_mul_pow_self_two prime_two_or_dvd_of_dvd_two_mul_pow_self_two
theorem Int.exists_prime_and_dvd {n : ℤ} (hn : n.natAbs ≠ 1) : ∃ p, Prime p ∧ p ∣ n := by
obtain ⟨p, pp, pd⟩ := Nat.exists_prime_and_dvd hn
exact ⟨p, Nat.prime_iff_prime_int.mp pp, Int.natCast_dvd.mpr pd⟩
#align int.exists_prime_and_dvd Int.exists_prime_and_dvd
theorem Int.prime_iff_natAbs_prime {k : ℤ} : Prime k ↔ Nat.Prime k.natAbs :=
(Int.associated_natAbs k).prime_iff.trans Nat.prime_iff_prime_int.symm
#align int.prime_iff_nat_abs_prime Int.prime_iff_natAbs_prime
namespace Int
theorem zmultiples_natAbs (a : ℤ) :
AddSubgroup.zmultiples (a.natAbs : ℤ) = AddSubgroup.zmultiples a :=
le_antisymm (AddSubgroup.zmultiples_le_of_mem (mem_zmultiples_iff.mpr (dvd_natAbs.mpr dvd_rfl)))
(AddSubgroup.zmultiples_le_of_mem (mem_zmultiples_iff.mpr (natAbs_dvd.mpr dvd_rfl)))
#align int.zmultiples_nat_abs Int.zmultiples_natAbs
| Mathlib/RingTheory/Int/Basic.lean | 139 | 141 | theorem span_natAbs (a : ℤ) : Ideal.span ({(a.natAbs : ℤ)} : Set ℤ) = Ideal.span {a} := by |
rw [Ideal.span_singleton_eq_span_singleton]
exact (associated_natAbs _).symm
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Algebra.Order.AbsoluteValue
import Mathlib.Algebra.Order.Field.Basic
import Mathlib.Algebra.Order.Group.MinMax
import Mathlib.Algebra.Ring.Pi
import Mathlib.GroupTheory.GroupAction.Pi
import Mathlib.GroupTheory.GroupAction.Ring
import Mathlib.Init.Align
import Mathlib.Tactic.GCongr
import Mathlib.Tactic.Ring
#align_import data.real.cau_seq from "leanprover-community/mathlib"@"9116dd6709f303dcf781632e15fdef382b0fc579"
/-!
# Cauchy sequences
A basic theory of Cauchy sequences, used in the construction of the reals and p-adic numbers. Where
applicable, lemmas that will be reused in other contexts have been stated in extra generality.
There are other "versions" of Cauchyness in the library, in particular Cauchy filters in topology.
This is a concrete implementation that is useful for simplicity and computability reasons.
## Important definitions
* `IsCauSeq`: a predicate that says `f : ℕ → β` is Cauchy.
* `CauSeq`: the type of Cauchy sequences valued in type `β` with respect to an absolute value
function `abv`.
## Tags
sequence, cauchy, abs val, absolute value
-/
assert_not_exists Finset
assert_not_exists Module
assert_not_exists Submonoid
assert_not_exists FloorRing
variable {α β : Type*}
open IsAbsoluteValue
section
variable [LinearOrderedField α] [Ring β] (abv : β → α) [IsAbsoluteValue abv]
theorem rat_add_continuous_lemma {ε : α} (ε0 : 0 < ε) :
∃ δ > 0, ∀ {a₁ a₂ b₁ b₂ : β}, abv (a₁ - b₁) < δ → abv (a₂ - b₂) < δ →
abv (a₁ + a₂ - (b₁ + b₂)) < ε :=
⟨ε / 2, half_pos ε0, fun {a₁ a₂ b₁ b₂} h₁ h₂ => by
simpa [add_halves, sub_eq_add_neg, add_comm, add_left_comm, add_assoc] using
lt_of_le_of_lt (abv_add abv _ _) (add_lt_add h₁ h₂)⟩
#align rat_add_continuous_lemma rat_add_continuous_lemma
theorem rat_mul_continuous_lemma {ε K₁ K₂ : α} (ε0 : 0 < ε) :
∃ δ > 0, ∀ {a₁ a₂ b₁ b₂ : β}, abv a₁ < K₁ → abv b₂ < K₂ → abv (a₁ - b₁) < δ →
abv (a₂ - b₂) < δ → abv (a₁ * a₂ - b₁ * b₂) < ε := by
have K0 : (0 : α) < max 1 (max K₁ K₂) := lt_of_lt_of_le zero_lt_one (le_max_left _ _)
have εK := div_pos (half_pos ε0) K0
refine ⟨_, εK, fun {a₁ a₂ b₁ b₂} ha₁ hb₂ h₁ h₂ => ?_⟩
replace ha₁ := lt_of_lt_of_le ha₁ (le_trans (le_max_left _ K₂) (le_max_right 1 _))
replace hb₂ := lt_of_lt_of_le hb₂ (le_trans (le_max_right K₁ _) (le_max_right 1 _))
set M := max 1 (max K₁ K₂)
have : abv (a₁ - b₁) * abv b₂ + abv (a₂ - b₂) * abv a₁ < ε / 2 / M * M + ε / 2 / M * M := by
gcongr
rw [← abv_mul abv, mul_comm, div_mul_cancel₀ _ (ne_of_gt K0), ← abv_mul abv, add_halves] at this
simpa [sub_eq_add_neg, mul_add, add_mul, add_left_comm] using
lt_of_le_of_lt (abv_add abv _ _) this
#align rat_mul_continuous_lemma rat_mul_continuous_lemma
theorem rat_inv_continuous_lemma {β : Type*} [DivisionRing β] (abv : β → α) [IsAbsoluteValue abv]
{ε K : α} (ε0 : 0 < ε) (K0 : 0 < K) :
∃ δ > 0, ∀ {a b : β}, K ≤ abv a → K ≤ abv b → abv (a - b) < δ → abv (a⁻¹ - b⁻¹) < ε := by
refine ⟨K * ε * K, mul_pos (mul_pos K0 ε0) K0, fun {a b} ha hb h => ?_⟩
have a0 := K0.trans_le ha
have b0 := K0.trans_le hb
rw [inv_sub_inv' ((abv_pos abv).1 a0) ((abv_pos abv).1 b0), abv_mul abv, abv_mul abv, abv_inv abv,
abv_inv abv, abv_sub abv]
refine lt_of_mul_lt_mul_left (lt_of_mul_lt_mul_right ?_ b0.le) a0.le
rw [mul_assoc, inv_mul_cancel_right₀ b0.ne', ← mul_assoc, mul_inv_cancel a0.ne', one_mul]
refine h.trans_le ?_
gcongr
#align rat_inv_continuous_lemma rat_inv_continuous_lemma
end
/-- A sequence is Cauchy if the distance between its entries tends to zero. -/
def IsCauSeq {α : Type*} [LinearOrderedField α] {β : Type*} [Ring β] (abv : β → α) (f : ℕ → β) :
Prop :=
∀ ε > 0, ∃ i, ∀ j ≥ i, abv (f j - f i) < ε
#align is_cau_seq IsCauSeq
namespace IsCauSeq
variable [LinearOrderedField α] [Ring β] {abv : β → α} [IsAbsoluteValue abv] {f g : ℕ → β}
-- see Note [nolint_ge]
--@[nolint ge_or_gt] -- Porting note: restore attribute
theorem cauchy₂ (hf : IsCauSeq abv f) {ε : α} (ε0 : 0 < ε) :
∃ i, ∀ j ≥ i, ∀ k ≥ i, abv (f j - f k) < ε := by
refine (hf _ (half_pos ε0)).imp fun i hi j ij k ik => ?_
rw [← add_halves ε]
refine lt_of_le_of_lt (abv_sub_le abv _ _ _) (add_lt_add (hi _ ij) ?_)
rw [abv_sub abv]; exact hi _ ik
#align is_cau_seq.cauchy₂ IsCauSeq.cauchy₂
theorem cauchy₃ (hf : IsCauSeq abv f) {ε : α} (ε0 : 0 < ε) :
∃ i, ∀ j ≥ i, ∀ k ≥ j, abv (f k - f j) < ε :=
let ⟨i, H⟩ := hf.cauchy₂ ε0
⟨i, fun _ ij _ jk => H _ (le_trans ij jk) _ ij⟩
#align is_cau_seq.cauchy₃ IsCauSeq.cauchy₃
lemma bounded (hf : IsCauSeq abv f) : ∃ r, ∀ i, abv (f i) < r := by
obtain ⟨i, h⟩ := hf _ zero_lt_one
set R : ℕ → α := @Nat.rec (fun _ => α) (abv (f 0)) fun i c => max c (abv (f i.succ)) with hR
have : ∀ i, ∀ j ≤ i, abv (f j) ≤ R i := by
refine Nat.rec (by simp [hR]) ?_
rintro i hi j (rfl | hj)
· simp [R]
· exact (hi j hj).trans (le_max_left _ _)
refine ⟨R i + 1, fun j ↦ ?_⟩
obtain hji | hij := le_total j i
· exact (this i _ hji).trans_lt (lt_add_one _)
· simpa using (abv_add abv _ _).trans_lt $ add_lt_add_of_le_of_lt (this i _ le_rfl) (h _ hij)
lemma bounded' (hf : IsCauSeq abv f) (x : α) : ∃ r > x, ∀ i, abv (f i) < r :=
let ⟨r, h⟩ := hf.bounded
⟨max r (x + 1), (lt_add_one x).trans_le (le_max_right _ _),
fun i ↦ (h i).trans_le (le_max_left _ _)⟩
lemma const (x : β) : IsCauSeq abv fun _ ↦ x :=
fun ε ε0 ↦ ⟨0, fun j _ => by simpa [abv_zero] using ε0⟩
theorem add (hf : IsCauSeq abv f) (hg : IsCauSeq abv g) : IsCauSeq abv (f + g) := fun _ ε0 =>
let ⟨_, δ0, Hδ⟩ := rat_add_continuous_lemma abv ε0
let ⟨i, H⟩ := exists_forall_ge_and (hf.cauchy₃ δ0) (hg.cauchy₃ δ0)
⟨i, fun _ ij =>
let ⟨H₁, H₂⟩ := H _ le_rfl
Hδ (H₁ _ ij) (H₂ _ ij)⟩
#align is_cau_seq.add IsCauSeq.add
lemma mul (hf : IsCauSeq abv f) (hg : IsCauSeq abv g) : IsCauSeq abv (f * g) := fun _ ε0 =>
let ⟨_, _, hF⟩ := hf.bounded' 0
let ⟨_, _, hG⟩ := hg.bounded' 0
let ⟨_, δ0, Hδ⟩ := rat_mul_continuous_lemma abv ε0
let ⟨i, H⟩ := exists_forall_ge_and (hf.cauchy₃ δ0) (hg.cauchy₃ δ0)
⟨i, fun j ij =>
let ⟨H₁, H₂⟩ := H _ le_rfl
Hδ (hF j) (hG i) (H₁ _ ij) (H₂ _ ij)⟩
@[simp] lemma _root_.isCauSeq_neg : IsCauSeq abv (-f) ↔ IsCauSeq abv f := by
simp only [IsCauSeq, Pi.neg_apply, ← neg_sub', abv_neg]
protected alias ⟨of_neg, neg⟩ := isCauSeq_neg
end IsCauSeq
/-- `CauSeq β abv` is the type of `β`-valued Cauchy sequences, with respect to the absolute value
function `abv`. -/
def CauSeq {α : Type*} [LinearOrderedField α] (β : Type*) [Ring β] (abv : β → α) : Type _ :=
{ f : ℕ → β // IsCauSeq abv f }
#align cau_seq CauSeq
namespace CauSeq
variable [LinearOrderedField α]
section Ring
variable [Ring β] {abv : β → α}
instance : CoeFun (CauSeq β abv) fun _ => ℕ → β :=
⟨Subtype.val⟩
-- Porting note: Remove coeFn theorem
/-@[simp]
theorem mk_to_fun (f) (hf : IsCauSeq abv f) : @coeFn (CauSeq β abv) _ _ ⟨f, hf⟩ = f :=
rfl -/
#noalign cau_seq.mk_to_fun
@[ext]
theorem ext {f g : CauSeq β abv} (h : ∀ i, f i = g i) : f = g := Subtype.eq (funext h)
#align cau_seq.ext CauSeq.ext
theorem isCauSeq (f : CauSeq β abv) : IsCauSeq abv f :=
f.2
#align cau_seq.is_cau CauSeq.isCauSeq
theorem cauchy (f : CauSeq β abv) : ∀ {ε}, 0 < ε → ∃ i, ∀ j ≥ i, abv (f j - f i) < ε := @f.2
#align cau_seq.cauchy CauSeq.cauchy
/-- Given a Cauchy sequence `f`, create a Cauchy sequence from a sequence `g` with
the same values as `f`. -/
def ofEq (f : CauSeq β abv) (g : ℕ → β) (e : ∀ i, f i = g i) : CauSeq β abv :=
⟨g, fun ε => by rw [show g = f from (funext e).symm]; exact f.cauchy⟩
#align cau_seq.of_eq CauSeq.ofEq
variable [IsAbsoluteValue abv]
-- see Note [nolint_ge]
-- @[nolint ge_or_gt] -- Porting note: restore attribute
theorem cauchy₂ (f : CauSeq β abv) {ε} :
0 < ε → ∃ i, ∀ j ≥ i, ∀ k ≥ i, abv (f j - f k) < ε :=
f.2.cauchy₂
#align cau_seq.cauchy₂ CauSeq.cauchy₂
theorem cauchy₃ (f : CauSeq β abv) {ε} : 0 < ε → ∃ i, ∀ j ≥ i, ∀ k ≥ j, abv (f k - f j) < ε :=
f.2.cauchy₃
#align cau_seq.cauchy₃ CauSeq.cauchy₃
theorem bounded (f : CauSeq β abv) : ∃ r, ∀ i, abv (f i) < r := f.2.bounded
#align cau_seq.bounded CauSeq.bounded
theorem bounded' (f : CauSeq β abv) (x : α) : ∃ r > x, ∀ i, abv (f i) < r := f.2.bounded' x
#align cau_seq.bounded' CauSeq.bounded'
instance : Add (CauSeq β abv) :=
⟨fun f g => ⟨f + g, f.2.add g.2⟩⟩
@[simp, norm_cast]
theorem coe_add (f g : CauSeq β abv) : ⇑(f + g) = (f : ℕ → β) + g :=
rfl
#align cau_seq.coe_add CauSeq.coe_add
@[simp, norm_cast]
theorem add_apply (f g : CauSeq β abv) (i : ℕ) : (f + g) i = f i + g i :=
rfl
#align cau_seq.add_apply CauSeq.add_apply
variable (abv)
/-- The constant Cauchy sequence. -/
def const (x : β) : CauSeq β abv := ⟨fun _ ↦ x, IsCauSeq.const _⟩
#align cau_seq.const CauSeq.const
variable {abv}
/-- The constant Cauchy sequence -/
local notation "const" => const abv
@[simp, norm_cast]
theorem coe_const (x : β) : (const x : ℕ → β) = Function.const ℕ x :=
rfl
#align cau_seq.coe_const CauSeq.coe_const
@[simp, norm_cast]
theorem const_apply (x : β) (i : ℕ) : (const x : ℕ → β) i = x :=
rfl
#align cau_seq.const_apply CauSeq.const_apply
theorem const_inj {x y : β} : (const x : CauSeq β abv) = const y ↔ x = y :=
⟨fun h => congr_arg (fun f : CauSeq β abv => (f : ℕ → β) 0) h, congr_arg _⟩
#align cau_seq.const_inj CauSeq.const_inj
instance : Zero (CauSeq β abv) :=
⟨const 0⟩
instance : One (CauSeq β abv) :=
⟨const 1⟩
instance : Inhabited (CauSeq β abv) :=
⟨0⟩
@[simp, norm_cast]
theorem coe_zero : ⇑(0 : CauSeq β abv) = 0 :=
rfl
#align cau_seq.coe_zero CauSeq.coe_zero
@[simp, norm_cast]
theorem coe_one : ⇑(1 : CauSeq β abv) = 1 :=
rfl
#align cau_seq.coe_one CauSeq.coe_one
@[simp, norm_cast]
theorem zero_apply (i) : (0 : CauSeq β abv) i = 0 :=
rfl
#align cau_seq.zero_apply CauSeq.zero_apply
@[simp, norm_cast]
theorem one_apply (i) : (1 : CauSeq β abv) i = 1 :=
rfl
#align cau_seq.one_apply CauSeq.one_apply
@[simp]
theorem const_zero : const 0 = 0 :=
rfl
#align cau_seq.const_zero CauSeq.const_zero
@[simp]
theorem const_one : const 1 = 1 :=
rfl
#align cau_seq.const_one CauSeq.const_one
theorem const_add (x y : β) : const (x + y) = const x + const y :=
rfl
#align cau_seq.const_add CauSeq.const_add
instance : Mul (CauSeq β abv) := ⟨fun f g ↦ ⟨f * g, f.2.mul g.2⟩⟩
@[simp, norm_cast]
theorem coe_mul (f g : CauSeq β abv) : ⇑(f * g) = (f : ℕ → β) * g :=
rfl
#align cau_seq.coe_mul CauSeq.coe_mul
@[simp, norm_cast]
theorem mul_apply (f g : CauSeq β abv) (i : ℕ) : (f * g) i = f i * g i :=
rfl
#align cau_seq.mul_apply CauSeq.mul_apply
theorem const_mul (x y : β) : const (x * y) = const x * const y :=
rfl
#align cau_seq.const_mul CauSeq.const_mul
instance : Neg (CauSeq β abv) := ⟨fun f ↦ ⟨-f, f.2.neg⟩⟩
@[simp, norm_cast]
theorem coe_neg (f : CauSeq β abv) : ⇑(-f) = -f :=
rfl
#align cau_seq.coe_neg CauSeq.coe_neg
@[simp, norm_cast]
theorem neg_apply (f : CauSeq β abv) (i) : (-f) i = -f i :=
rfl
#align cau_seq.neg_apply CauSeq.neg_apply
theorem const_neg (x : β) : const (-x) = -const x :=
rfl
#align cau_seq.const_neg CauSeq.const_neg
instance : Sub (CauSeq β abv) :=
⟨fun f g => ofEq (f + -g) (fun x => f x - g x) fun i => by simp [sub_eq_add_neg]⟩
@[simp, norm_cast]
theorem coe_sub (f g : CauSeq β abv) : ⇑(f - g) = (f : ℕ → β) - g :=
rfl
#align cau_seq.coe_sub CauSeq.coe_sub
@[simp, norm_cast]
theorem sub_apply (f g : CauSeq β abv) (i : ℕ) : (f - g) i = f i - g i :=
rfl
#align cau_seq.sub_apply CauSeq.sub_apply
theorem const_sub (x y : β) : const (x - y) = const x - const y :=
rfl
#align cau_seq.const_sub CauSeq.const_sub
section SMul
variable {G : Type*} [SMul G β] [IsScalarTower G β β]
instance : SMul G (CauSeq β abv) :=
⟨fun a f => (ofEq (const (a • (1 : β)) * f) (a • (f : ℕ → β))) fun _ => smul_one_mul _ _⟩
@[simp, norm_cast]
theorem coe_smul (a : G) (f : CauSeq β abv) : ⇑(a • f) = a • (f : ℕ → β) :=
rfl
#align cau_seq.coe_smul CauSeq.coe_smul
@[simp, norm_cast]
theorem smul_apply (a : G) (f : CauSeq β abv) (i : ℕ) : (a • f) i = a • f i :=
rfl
#align cau_seq.smul_apply CauSeq.smul_apply
theorem const_smul (a : G) (x : β) : const (a • x) = a • const x :=
rfl
#align cau_seq.const_smul CauSeq.const_smul
instance : IsScalarTower G (CauSeq β abv) (CauSeq β abv) :=
⟨fun a f g => Subtype.ext <| smul_assoc a (f : ℕ → β) (g : ℕ → β)⟩
end SMul
instance addGroup : AddGroup (CauSeq β abv) :=
Function.Injective.addGroup Subtype.val Subtype.val_injective rfl coe_add coe_neg coe_sub
(fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _
instance instNatCast : NatCast (CauSeq β abv) := ⟨fun n => const n⟩
instance instIntCast : IntCast (CauSeq β abv) := ⟨fun n => const n⟩
instance addGroupWithOne : AddGroupWithOne (CauSeq β abv) :=
Function.Injective.addGroupWithOne Subtype.val Subtype.val_injective rfl rfl
coe_add coe_neg coe_sub
(by intros; rfl)
(by intros; rfl)
(by intros; rfl)
(by intros; rfl)
instance : Pow (CauSeq β abv) ℕ :=
⟨fun f n =>
(ofEq (npowRec n f) fun i => f i ^ n) <| by induction n <;> simp [*, npowRec, pow_succ]⟩
@[simp, norm_cast]
theorem coe_pow (f : CauSeq β abv) (n : ℕ) : ⇑(f ^ n) = (f : ℕ → β) ^ n :=
rfl
#align cau_seq.coe_pow CauSeq.coe_pow
@[simp, norm_cast]
theorem pow_apply (f : CauSeq β abv) (n i : ℕ) : (f ^ n) i = f i ^ n :=
rfl
#align cau_seq.pow_apply CauSeq.pow_apply
theorem const_pow (x : β) (n : ℕ) : const (x ^ n) = const x ^ n :=
rfl
#align cau_seq.const_pow CauSeq.const_pow
instance ring : Ring (CauSeq β abv) :=
Function.Injective.ring Subtype.val Subtype.val_injective rfl rfl coe_add coe_mul coe_neg coe_sub
(fun _ _ => coe_smul _ _) (fun _ _ => coe_smul _ _) coe_pow (fun _ => rfl) fun _ => rfl
instance {β : Type*} [CommRing β] {abv : β → α} [IsAbsoluteValue abv] : CommRing (CauSeq β abv) :=
{ CauSeq.ring with
mul_comm := fun a b => ext fun n => by simp [mul_left_comm, mul_comm] }
/-- `LimZero f` holds when `f` approaches 0. -/
def LimZero {abv : β → α} (f : CauSeq β abv) : Prop :=
∀ ε > 0, ∃ i, ∀ j ≥ i, abv (f j) < ε
#align cau_seq.lim_zero CauSeq.LimZero
theorem add_limZero {f g : CauSeq β abv} (hf : LimZero f) (hg : LimZero g) : LimZero (f + g)
| ε, ε0 =>
(exists_forall_ge_and (hf _ <| half_pos ε0) (hg _ <| half_pos ε0)).imp fun i H j ij => by
let ⟨H₁, H₂⟩ := H _ ij
simpa [add_halves ε] using lt_of_le_of_lt (abv_add abv _ _) (add_lt_add H₁ H₂)
#align cau_seq.add_lim_zero CauSeq.add_limZero
theorem mul_limZero_right (f : CauSeq β abv) {g} (hg : LimZero g) : LimZero (f * g)
| ε, ε0 =>
let ⟨F, F0, hF⟩ := f.bounded' 0
(hg _ <| div_pos ε0 F0).imp fun i H j ij => by
have := mul_lt_mul' (le_of_lt <| hF j) (H _ ij) (abv_nonneg abv _) F0
rwa [mul_comm F, div_mul_cancel₀ _ (ne_of_gt F0), ← abv_mul] at this
#align cau_seq.mul_lim_zero_right CauSeq.mul_limZero_right
theorem mul_limZero_left {f} (g : CauSeq β abv) (hg : LimZero f) : LimZero (f * g)
| ε, ε0 =>
let ⟨G, G0, hG⟩ := g.bounded' 0
(hg _ <| div_pos ε0 G0).imp fun i H j ij => by
have := mul_lt_mul'' (H _ ij) (hG j) (abv_nonneg abv _) (abv_nonneg abv _)
rwa [div_mul_cancel₀ _ (ne_of_gt G0), ← abv_mul] at this
#align cau_seq.mul_lim_zero_left CauSeq.mul_limZero_left
theorem neg_limZero {f : CauSeq β abv} (hf : LimZero f) : LimZero (-f) := by
rw [← neg_one_mul f]
exact mul_limZero_right _ hf
#align cau_seq.neg_lim_zero CauSeq.neg_limZero
theorem sub_limZero {f g : CauSeq β abv} (hf : LimZero f) (hg : LimZero g) : LimZero (f - g) := by
simpa only [sub_eq_add_neg] using add_limZero hf (neg_limZero hg)
#align cau_seq.sub_lim_zero CauSeq.sub_limZero
theorem limZero_sub_rev {f g : CauSeq β abv} (hfg : LimZero (f - g)) : LimZero (g - f) := by
simpa using neg_limZero hfg
#align cau_seq.lim_zero_sub_rev CauSeq.limZero_sub_rev
theorem zero_limZero : LimZero (0 : CauSeq β abv)
| ε, ε0 => ⟨0, fun j _ => by simpa [abv_zero abv] using ε0⟩
#align cau_seq.zero_lim_zero CauSeq.zero_limZero
theorem const_limZero {x : β} : LimZero (const x) ↔ x = 0 :=
⟨fun H =>
(abv_eq_zero abv).1 <|
(eq_of_le_of_forall_le_of_dense (abv_nonneg abv _)) fun _ ε0 =>
let ⟨_, hi⟩ := H _ ε0
le_of_lt <| hi _ le_rfl,
fun e => e.symm ▸ zero_limZero⟩
#align cau_seq.const_lim_zero CauSeq.const_limZero
instance equiv : Setoid (CauSeq β abv) :=
⟨fun f g => LimZero (f - g),
⟨fun f => by simp [zero_limZero],
fun f ε hε => by simpa using neg_limZero f ε hε,
fun fg gh => by simpa using add_limZero fg gh⟩⟩
#align cau_seq.equiv CauSeq.equiv
theorem add_equiv_add {f1 f2 g1 g2 : CauSeq β abv} (hf : f1 ≈ f2) (hg : g1 ≈ g2) :
f1 + g1 ≈ f2 + g2 := by simpa only [← add_sub_add_comm] using add_limZero hf hg
#align cau_seq.add_equiv_add CauSeq.add_equiv_add
theorem neg_equiv_neg {f g : CauSeq β abv} (hf : f ≈ g) : -f ≈ -g := by
simpa only [neg_sub'] using neg_limZero hf
#align cau_seq.neg_equiv_neg CauSeq.neg_equiv_neg
theorem sub_equiv_sub {f1 f2 g1 g2 : CauSeq β abv} (hf : f1 ≈ f2) (hg : g1 ≈ g2) :
f1 - g1 ≈ f2 - g2 := by simpa only [sub_eq_add_neg] using add_equiv_add hf (neg_equiv_neg hg)
#align cau_seq.sub_equiv_sub CauSeq.sub_equiv_sub
theorem equiv_def₃ {f g : CauSeq β abv} (h : f ≈ g) {ε : α} (ε0 : 0 < ε) :
∃ i, ∀ j ≥ i, ∀ k ≥ j, abv (f k - g j) < ε :=
(exists_forall_ge_and (h _ <| half_pos ε0) (f.cauchy₃ <| half_pos ε0)).imp fun i H j ij k jk => by
let ⟨h₁, h₂⟩ := H _ ij
have := lt_of_le_of_lt (abv_add abv (f j - g j) _) (add_lt_add h₁ (h₂ _ jk))
rwa [sub_add_sub_cancel', add_halves] at this
#align cau_seq.equiv_def₃ CauSeq.equiv_def₃
theorem limZero_congr {f g : CauSeq β abv} (h : f ≈ g) : LimZero f ↔ LimZero g :=
⟨fun l => by simpa using add_limZero (Setoid.symm h) l, fun l => by simpa using add_limZero h l⟩
#align cau_seq.lim_zero_congr CauSeq.limZero_congr
theorem abv_pos_of_not_limZero {f : CauSeq β abv} (hf : ¬LimZero f) :
∃ K > 0, ∃ i, ∀ j ≥ i, K ≤ abv (f j) := by
haveI := Classical.propDecidable
by_contra nk
refine hf fun ε ε0 => ?_
simp? [not_forall] at nk says
simp only [gt_iff_lt, ge_iff_le, not_exists, not_and, not_forall, Classical.not_imp,
not_le] at nk
cases' f.cauchy₃ (half_pos ε0) with i hi
rcases nk _ (half_pos ε0) i with ⟨j, ij, hj⟩
refine ⟨j, fun k jk => ?_⟩
have := lt_of_le_of_lt (abv_add abv _ _) (add_lt_add (hi j ij k jk) hj)
rwa [sub_add_cancel, add_halves] at this
#align cau_seq.abv_pos_of_not_lim_zero CauSeq.abv_pos_of_not_limZero
theorem of_near (f : ℕ → β) (g : CauSeq β abv) (h : ∀ ε > 0, ∃ i, ∀ j ≥ i, abv (f j - g j) < ε) :
IsCauSeq abv f
| ε, ε0 =>
let ⟨i, hi⟩ := exists_forall_ge_and (h _ (half_pos <| half_pos ε0)) (g.cauchy₃ <| half_pos ε0)
⟨i, fun j ij => by
cases' hi _ le_rfl with h₁ h₂; rw [abv_sub abv] at h₁
have := lt_of_le_of_lt (abv_add abv _ _) (add_lt_add (hi _ ij).1 h₁)
have := lt_of_le_of_lt (abv_add abv _ _) (add_lt_add this (h₂ _ ij))
rwa [add_halves, add_halves, add_right_comm, sub_add_sub_cancel, sub_add_sub_cancel] at this⟩
#align cau_seq.of_near CauSeq.of_near
theorem not_limZero_of_not_congr_zero {f : CauSeq _ abv} (hf : ¬f ≈ 0) : ¬LimZero f := by
intro h
have : LimZero (f - 0) := by simp [h]
exact hf this
#align cau_seq.not_lim_zero_of_not_congr_zero CauSeq.not_limZero_of_not_congr_zero
theorem mul_equiv_zero (g : CauSeq _ abv) {f : CauSeq _ abv} (hf : f ≈ 0) : g * f ≈ 0 :=
have : LimZero (f - 0) := hf
have : LimZero (g * f) := mul_limZero_right _ <| by simpa
show LimZero (g * f - 0) by simpa
#align cau_seq.mul_equiv_zero CauSeq.mul_equiv_zero
theorem mul_equiv_zero' (g : CauSeq _ abv) {f : CauSeq _ abv} (hf : f ≈ 0) : f * g ≈ 0 :=
have : LimZero (f - 0) := hf
have : LimZero (f * g) := mul_limZero_left _ <| by simpa
show LimZero (f * g - 0) by simpa
#align cau_seq.mul_equiv_zero' CauSeq.mul_equiv_zero'
theorem mul_not_equiv_zero {f g : CauSeq _ abv} (hf : ¬f ≈ 0) (hg : ¬g ≈ 0) : ¬f * g ≈ 0 :=
fun (this : LimZero (f * g - 0)) => by
have hlz : LimZero (f * g) := by simpa
have hf' : ¬LimZero f := by simpa using show ¬LimZero (f - 0) from hf
have hg' : ¬LimZero g := by simpa using show ¬LimZero (g - 0) from hg
rcases abv_pos_of_not_limZero hf' with ⟨a1, ha1, N1, hN1⟩
rcases abv_pos_of_not_limZero hg' with ⟨a2, ha2, N2, hN2⟩
have : 0 < a1 * a2 := mul_pos ha1 ha2
cases' hlz _ this with N hN
let i := max N (max N1 N2)
have hN' := hN i (le_max_left _ _)
have hN1' := hN1 i (le_trans (le_max_left _ _) (le_max_right _ _))
have hN1' := hN2 i (le_trans (le_max_right _ _) (le_max_right _ _))
apply not_le_of_lt hN'
change _ ≤ abv (_ * _)
rw [abv_mul abv]
gcongr
#align cau_seq.mul_not_equiv_zero CauSeq.mul_not_equiv_zero
theorem const_equiv {x y : β} : const x ≈ const y ↔ x = y :=
show LimZero _ ↔ _ by rw [← const_sub, const_limZero, sub_eq_zero]
#align cau_seq.const_equiv CauSeq.const_equiv
theorem mul_equiv_mul {f1 f2 g1 g2 : CauSeq β abv} (hf : f1 ≈ f2) (hg : g1 ≈ g2) :
f1 * g1 ≈ f2 * g2 := by
change LimZero (f1 * g1 - f2 * g2)
convert add_limZero (mul_limZero_left g1 hf) (mul_limZero_right f2 hg) using 1
rw [mul_sub, sub_mul]
-- Porting note: doesn't work with `rw`, but did in Lean 3
exact (sub_add_sub_cancel (f1*g1) (f2*g1) (f2*g2)).symm
-- Porting note: was
/-
simpa only [mul_sub, sub_mul, sub_add_sub_cancel] using
add_lim_zero (mul_limZero_left g1 hf) (mul_limZero_right f2 hg)
-/
#align cau_seq.mul_equiv_mul CauSeq.mul_equiv_mul
theorem smul_equiv_smul {G : Type*} [SMul G β] [IsScalarTower G β β] {f1 f2 : CauSeq β abv} (c : G)
(hf : f1 ≈ f2) : c • f1 ≈ c • f2 := by
simpa [const_smul, smul_one_mul _ _] using
mul_equiv_mul (const_equiv.mpr <| Eq.refl <| c • (1 : β)) hf
#align cau_seq.smul_equiv_smul CauSeq.smul_equiv_smul
theorem pow_equiv_pow {f1 f2 : CauSeq β abv} (hf : f1 ≈ f2) (n : ℕ) : f1 ^ n ≈ f2 ^ n := by
induction' n with n ih
· simp only [Nat.zero_eq, pow_zero, Setoid.refl]
· simpa only [pow_succ'] using mul_equiv_mul hf ih
#align cau_seq.pow_equiv_pow CauSeq.pow_equiv_pow
end Ring
section IsDomain
variable [Ring β] [IsDomain β] (abv : β → α) [IsAbsoluteValue abv]
theorem one_not_equiv_zero : ¬const abv 1 ≈ const abv 0 := fun h =>
have : ∀ ε > 0, ∃ i, ∀ k, i ≤ k → abv (1 - 0) < ε := h
have h1 : abv 1 ≤ 0 :=
le_of_not_gt fun h2 : 0 < abv 1 =>
(Exists.elim (this _ h2)) fun i hi => lt_irrefl (abv 1) <| by simpa using hi _ le_rfl
have h2 : 0 ≤ abv 1 := abv_nonneg abv _
have : abv 1 = 0 := le_antisymm h1 h2
have : (1 : β) = 0 := (abv_eq_zero abv).mp this
absurd this one_ne_zero
#align cau_seq.one_not_equiv_zero CauSeq.one_not_equiv_zero
end IsDomain
section DivisionRing
variable [DivisionRing β] {abv : β → α} [IsAbsoluteValue abv]
theorem inv_aux {f : CauSeq β abv} (hf : ¬LimZero f) :
∀ ε > 0, ∃ i, ∀ j ≥ i, abv ((f j)⁻¹ - (f i)⁻¹) < ε
| _, ε0 =>
let ⟨_, K0, HK⟩ := abv_pos_of_not_limZero hf
let ⟨_, δ0, Hδ⟩ := rat_inv_continuous_lemma abv ε0 K0
let ⟨i, H⟩ := exists_forall_ge_and HK (f.cauchy₃ δ0)
⟨i, fun _ ij =>
let ⟨iK, H'⟩ := H _ le_rfl
Hδ (H _ ij).1 iK (H' _ ij)⟩
#align cau_seq.inv_aux CauSeq.inv_aux
/-- Given a Cauchy sequence `f` with nonzero limit, create a Cauchy sequence with values equal to
the inverses of the values of `f`. -/
def inv (f : CauSeq β abv) (hf : ¬LimZero f) : CauSeq β abv :=
⟨_, inv_aux hf⟩
#align cau_seq.inv CauSeq.inv
@[simp, norm_cast]
theorem coe_inv {f : CauSeq β abv} (hf) : ⇑(inv f hf) = (f : ℕ → β)⁻¹ :=
rfl
#align cau_seq.coe_inv CauSeq.coe_inv
@[simp, norm_cast]
theorem inv_apply {f : CauSeq β abv} (hf i) : inv f hf i = (f i)⁻¹ :=
rfl
#align cau_seq.inv_apply CauSeq.inv_apply
theorem inv_mul_cancel {f : CauSeq β abv} (hf) : inv f hf * f ≈ 1 := fun ε ε0 =>
let ⟨K, K0, i, H⟩ := abv_pos_of_not_limZero hf
⟨i, fun j ij => by simpa [(abv_pos abv).1 (lt_of_lt_of_le K0 (H _ ij)), abv_zero abv] using ε0⟩
#align cau_seq.inv_mul_cancel CauSeq.inv_mul_cancel
theorem mul_inv_cancel {f : CauSeq β abv} (hf) : f * inv f hf ≈ 1 := fun ε ε0 =>
let ⟨K, K0, i, H⟩ := abv_pos_of_not_limZero hf
⟨i, fun j ij => by simpa [(abv_pos abv).1 (lt_of_lt_of_le K0 (H _ ij)), abv_zero abv] using ε0⟩
#align cau_seq.mul_inv_cancel CauSeq.mul_inv_cancel
theorem const_inv {x : β} (hx : x ≠ 0) :
const abv x⁻¹ = inv (const abv x) (by rwa [const_limZero]) :=
rfl
#align cau_seq.const_inv CauSeq.const_inv
end DivisionRing
section Abs
/-- The constant Cauchy sequence -/
local notation "const" => const abs
/-- The entries of a positive Cauchy sequence eventually have a positive lower bound. -/
def Pos (f : CauSeq α abs) : Prop :=
∃ K > 0, ∃ i, ∀ j ≥ i, K ≤ f j
#align cau_seq.pos CauSeq.Pos
theorem not_limZero_of_pos {f : CauSeq α abs} : Pos f → ¬LimZero f
| ⟨_, F0, hF⟩, H =>
let ⟨_, h⟩ := exists_forall_ge_and hF (H _ F0)
let ⟨h₁, h₂⟩ := h _ le_rfl
not_lt_of_le h₁ (abs_lt.1 h₂).2
#align cau_seq.not_lim_zero_of_pos CauSeq.not_limZero_of_pos
theorem const_pos {x : α} : Pos (const x) ↔ 0 < x :=
⟨fun ⟨_, K0, _, h⟩ => lt_of_lt_of_le K0 (h _ le_rfl), fun h => ⟨x, h, 0, fun _ _ => le_rfl⟩⟩
#align cau_seq.const_pos CauSeq.const_pos
theorem add_pos {f g : CauSeq α abs} : Pos f → Pos g → Pos (f + g)
| ⟨_, F0, hF⟩, ⟨_, G0, hG⟩ =>
let ⟨i, h⟩ := exists_forall_ge_and hF hG
⟨_, _root_.add_pos F0 G0, i, fun _ ij =>
let ⟨h₁, h₂⟩ := h _ ij
add_le_add h₁ h₂⟩
#align cau_seq.add_pos CauSeq.add_pos
theorem pos_add_limZero {f g : CauSeq α abs} : Pos f → LimZero g → Pos (f + g)
| ⟨F, F0, hF⟩, H =>
let ⟨i, h⟩ := exists_forall_ge_and hF (H _ (half_pos F0))
⟨_, half_pos F0, i, fun j ij => by
cases' h j ij with h₁ h₂
have := add_le_add h₁ (le_of_lt (abs_lt.1 h₂).1)
rwa [← sub_eq_add_neg, sub_self_div_two] at this⟩
#align cau_seq.pos_add_lim_zero CauSeq.pos_add_limZero
protected theorem mul_pos {f g : CauSeq α abs} : Pos f → Pos g → Pos (f * g)
| ⟨_, F0, hF⟩, ⟨_, G0, hG⟩ =>
let ⟨i, h⟩ := exists_forall_ge_and hF hG
⟨_, mul_pos F0 G0, i, fun _ ij =>
let ⟨h₁, h₂⟩ := h _ ij
mul_le_mul h₁ h₂ (le_of_lt G0) (le_trans (le_of_lt F0) h₁)⟩
#align cau_seq.mul_pos CauSeq.mul_pos
theorem trichotomy (f : CauSeq α abs) : Pos f ∨ LimZero f ∨ Pos (-f) := by
cases' Classical.em (LimZero f) with h h <;> simp [*]
rcases abv_pos_of_not_limZero h with ⟨K, K0, hK⟩
rcases exists_forall_ge_and hK (f.cauchy₃ K0) with ⟨i, hi⟩
refine (le_total 0 (f i)).imp ?_ ?_ <;>
refine fun h => ⟨K, K0, i, fun j ij => ?_⟩ <;>
have := (hi _ ij).1 <;>
cases' hi _ le_rfl with h₁ h₂
· rwa [abs_of_nonneg] at this
rw [abs_of_nonneg h] at h₁
exact
(le_add_iff_nonneg_right _).1
(le_trans h₁ <| neg_le_sub_iff_le_add'.1 <| le_of_lt (abs_lt.1 <| h₂ _ ij).1)
· rwa [abs_of_nonpos] at this
rw [abs_of_nonpos h] at h₁
rw [← sub_le_sub_iff_right, zero_sub]
exact le_trans (le_of_lt (abs_lt.1 <| h₂ _ ij).2) h₁
#align cau_seq.trichotomy CauSeq.trichotomy
instance : LT (CauSeq α abs) :=
⟨fun f g => Pos (g - f)⟩
instance : LE (CauSeq α abs) :=
⟨fun f g => f < g ∨ f ≈ g⟩
theorem lt_of_lt_of_eq {f g h : CauSeq α abs} (fg : f < g) (gh : g ≈ h) : f < h :=
show Pos (h - f) by
convert pos_add_limZero fg (neg_limZero gh) using 1
simp
#align cau_seq.lt_of_lt_of_eq CauSeq.lt_of_lt_of_eq
| Mathlib/Algebra/Order/CauSeq/Basic.lean | 740 | 742 | theorem lt_of_eq_of_lt {f g h : CauSeq α abs} (fg : f ≈ g) (gh : g < h) : f < h := by |
have := pos_add_limZero gh (neg_limZero fg)
rwa [← sub_eq_add_neg, sub_sub_sub_cancel_right] at this
|
/-
Copyright (c) 2018 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Set.Lattice
import Mathlib.Logic.Small.Basic
import Mathlib.Logic.Function.OfArity
import Mathlib.Order.WellFounded
#align_import set_theory.zfc.basic from "leanprover-community/mathlib"@"f0b3759a8ef0bd8239ecdaa5e1089add5feebe1a"
/-!
# A model of ZFC
In this file, we model Zermelo-Fraenkel set theory (+ Choice) using Lean's underlying type theory.
We do this in four main steps:
* Define pre-sets inductively.
* Define extensional equivalence on pre-sets and give it a `setoid` instance.
* Define ZFC sets by quotienting pre-sets by extensional equivalence.
* Define classes as sets of ZFC sets.
Then the rest is usual set theory.
## The model
* `PSet`: Pre-set. A pre-set is inductively defined by its indexing type and its members, which are
themselves pre-sets.
* `ZFSet`: ZFC set. Defined as `PSet` quotiented by `PSet.Equiv`, the extensional equivalence.
* `Class`: Class. Defined as `Set ZFSet`.
* `ZFSet.choice`: Axiom of choice. Proved from Lean's axiom of choice.
## Other definitions
* `PSet.Type`: Underlying type of a pre-set.
* `PSet.Func`: Underlying family of pre-sets of a pre-set.
* `PSet.Equiv`: Extensional equivalence of pre-sets. Defined inductively.
* `PSet.omega`, `ZFSet.omega`: The von Neumann ordinal `ω` as a `PSet`, as a `Set`.
* `PSet.Arity.Equiv`: Extensional equivalence of `n`-ary `PSet`-valued functions. Extension of
`PSet.Equiv`.
* `PSet.Resp`: Collection of `n`-ary `PSet`-valued functions that respect extensional equivalence.
* `PSet.eval`: Turns a `PSet`-valued function that respect extensional equivalence into a
`ZFSet`-valued function.
* `Classical.allDefinable`: All functions are classically definable.
* `ZFSet.IsFunc` : Predicate that a ZFC set is a subset of `x × y` that can be considered as a ZFC
function `x → y`. That is, each member of `x` is related by the ZFC set to exactly one member of
`y`.
* `ZFSet.funs`: ZFC set of ZFC functions `x → y`.
* `ZFSet.Hereditarily p x`: Predicate that every set in the transitive closure of `x` has property
`p`.
* `Class.iota`: Definite description operator.
## Notes
To avoid confusion between the Lean `Set` and the ZFC `Set`, docstrings in this file refer to them
respectively as "`Set`" and "ZFC set".
## TODO
Prove `ZFSet.mapDefinableAux` computably.
-/
-- Porting note: Lean 3 uses `Set` for `ZFSet`.
set_option linter.uppercaseLean3 false
universe u v
open Function (OfArity)
/-- The type of pre-sets in universe `u`. A pre-set
is a family of pre-sets indexed by a type in `Type u`.
The ZFC universe is defined as a quotient of this
to ensure extensionality. -/
inductive PSet : Type (u + 1)
| mk (α : Type u) (A : α → PSet) : PSet
#align pSet PSet
namespace PSet
/-- The underlying type of a pre-set -/
def «Type» : PSet → Type u
| ⟨α, _⟩ => α
#align pSet.type PSet.Type
/-- The underlying pre-set family of a pre-set -/
def Func : ∀ x : PSet, x.Type → PSet
| ⟨_, A⟩ => A
#align pSet.func PSet.Func
@[simp]
theorem mk_type (α A) : «Type» ⟨α, A⟩ = α :=
rfl
#align pSet.mk_type PSet.mk_type
@[simp]
theorem mk_func (α A) : Func ⟨α, A⟩ = A :=
rfl
#align pSet.mk_func PSet.mk_func
@[simp]
theorem eta : ∀ x : PSet, mk x.Type x.Func = x
| ⟨_, _⟩ => rfl
#align pSet.eta PSet.eta
/-- Two pre-sets are extensionally equivalent if every element of the first family is extensionally
equivalent to some element of the second family and vice-versa. -/
def Equiv : PSet → PSet → Prop
| ⟨_, A⟩, ⟨_, B⟩ => (∀ a, ∃ b, Equiv (A a) (B b)) ∧ (∀ b, ∃ a, Equiv (A a) (B b))
#align pSet.equiv PSet.Equiv
theorem equiv_iff :
∀ {x y : PSet},
Equiv x y ↔ (∀ i, ∃ j, Equiv (x.Func i) (y.Func j)) ∧ ∀ j, ∃ i, Equiv (x.Func i) (y.Func j)
| ⟨_, _⟩, ⟨_, _⟩ => Iff.rfl
#align pSet.equiv_iff PSet.equiv_iff
theorem Equiv.exists_left {x y : PSet} (h : Equiv x y) : ∀ i, ∃ j, Equiv (x.Func i) (y.Func j) :=
(equiv_iff.1 h).1
#align pSet.equiv.exists_left PSet.Equiv.exists_left
theorem Equiv.exists_right {x y : PSet} (h : Equiv x y) : ∀ j, ∃ i, Equiv (x.Func i) (y.Func j) :=
(equiv_iff.1 h).2
#align pSet.equiv.exists_right PSet.Equiv.exists_right
@[refl]
protected theorem Equiv.refl : ∀ x, Equiv x x
| ⟨_, _⟩ => ⟨fun a => ⟨a, Equiv.refl _⟩, fun a => ⟨a, Equiv.refl _⟩⟩
#align pSet.equiv.refl PSet.Equiv.refl
protected theorem Equiv.rfl {x} : Equiv x x :=
Equiv.refl x
#align pSet.equiv.rfl PSet.Equiv.rfl
protected theorem Equiv.euc : ∀ {x y z}, Equiv x y → Equiv z y → Equiv x z
| ⟨_, _⟩, ⟨_, _⟩, ⟨_, _⟩, ⟨αβ, βα⟩, ⟨γβ, βγ⟩ =>
⟨ fun a =>
let ⟨b, ab⟩ := αβ a
let ⟨c, bc⟩ := βγ b
⟨c, Equiv.euc ab bc⟩,
fun c =>
let ⟨b, cb⟩ := γβ c
let ⟨a, ba⟩ := βα b
⟨a, Equiv.euc ba cb⟩ ⟩
#align pSet.equiv.euc PSet.Equiv.euc
@[symm]
protected theorem Equiv.symm {x y} : Equiv x y → Equiv y x :=
(Equiv.refl y).euc
#align pSet.equiv.symm PSet.Equiv.symm
protected theorem Equiv.comm {x y} : Equiv x y ↔ Equiv y x :=
⟨Equiv.symm, Equiv.symm⟩
#align pSet.equiv.comm PSet.Equiv.comm
@[trans]
protected theorem Equiv.trans {x y z} (h1 : Equiv x y) (h2 : Equiv y z) : Equiv x z :=
h1.euc h2.symm
#align pSet.equiv.trans PSet.Equiv.trans
protected theorem equiv_of_isEmpty (x y : PSet) [IsEmpty x.Type] [IsEmpty y.Type] : Equiv x y :=
equiv_iff.2 <| by simp
#align pSet.equiv_of_is_empty PSet.equiv_of_isEmpty
instance setoid : Setoid PSet :=
⟨PSet.Equiv, Equiv.refl, Equiv.symm, Equiv.trans⟩
#align pSet.setoid PSet.setoid
/-- A pre-set is a subset of another pre-set if every element of the first family is extensionally
equivalent to some element of the second family. -/
protected def Subset (x y : PSet) : Prop :=
∀ a, ∃ b, Equiv (x.Func a) (y.Func b)
#align pSet.subset PSet.Subset
instance : HasSubset PSet :=
⟨PSet.Subset⟩
instance : IsRefl PSet (· ⊆ ·) :=
⟨fun _ a => ⟨a, Equiv.refl _⟩⟩
instance : IsTrans PSet (· ⊆ ·) :=
⟨fun x y z hxy hyz a => by
cases' hxy a with b hb
cases' hyz b with c hc
exact ⟨c, hb.trans hc⟩⟩
theorem Equiv.ext : ∀ x y : PSet, Equiv x y ↔ x ⊆ y ∧ y ⊆ x
| ⟨_, _⟩, ⟨_, _⟩ =>
⟨fun ⟨αβ, βα⟩ =>
⟨αβ, fun b =>
let ⟨a, h⟩ := βα b
⟨a, Equiv.symm h⟩⟩,
fun ⟨αβ, βα⟩ =>
⟨αβ, fun b =>
let ⟨a, h⟩ := βα b
⟨a, Equiv.symm h⟩⟩⟩
#align pSet.equiv.ext PSet.Equiv.ext
theorem Subset.congr_left : ∀ {x y z : PSet}, Equiv x y → (x ⊆ z ↔ y ⊆ z)
| ⟨_, _⟩, ⟨_, _⟩, ⟨_, _⟩, ⟨αβ, βα⟩ =>
⟨fun αγ b =>
let ⟨a, ba⟩ := βα b
let ⟨c, ac⟩ := αγ a
⟨c, (Equiv.symm ba).trans ac⟩,
fun βγ a =>
let ⟨b, ab⟩ := αβ a
let ⟨c, bc⟩ := βγ b
⟨c, Equiv.trans ab bc⟩⟩
#align pSet.subset.congr_left PSet.Subset.congr_left
theorem Subset.congr_right : ∀ {x y z : PSet}, Equiv x y → (z ⊆ x ↔ z ⊆ y)
| ⟨_, _⟩, ⟨_, _⟩, ⟨_, _⟩, ⟨αβ, βα⟩ =>
⟨fun γα c =>
let ⟨a, ca⟩ := γα c
let ⟨b, ab⟩ := αβ a
⟨b, ca.trans ab⟩,
fun γβ c =>
let ⟨b, cb⟩ := γβ c
let ⟨a, ab⟩ := βα b
⟨a, cb.trans (Equiv.symm ab)⟩⟩
#align pSet.subset.congr_right PSet.Subset.congr_right
/-- `x ∈ y` as pre-sets if `x` is extensionally equivalent to a member of the family `y`. -/
protected def Mem (x y : PSet.{u}) : Prop :=
∃ b, Equiv x (y.Func b)
#align pSet.mem PSet.Mem
instance : Membership PSet PSet :=
⟨PSet.Mem⟩
theorem Mem.mk {α : Type u} (A : α → PSet) (a : α) : A a ∈ mk α A :=
⟨a, Equiv.refl (A a)⟩
#align pSet.mem.mk PSet.Mem.mk
theorem func_mem (x : PSet) (i : x.Type) : x.Func i ∈ x := by
cases x
apply Mem.mk
#align pSet.func_mem PSet.func_mem
theorem Mem.ext : ∀ {x y : PSet.{u}}, (∀ w : PSet.{u}, w ∈ x ↔ w ∈ y) → Equiv x y
| ⟨_, A⟩, ⟨_, B⟩, h =>
⟨fun a => (h (A a)).1 (Mem.mk A a), fun b =>
let ⟨a, ha⟩ := (h (B b)).2 (Mem.mk B b)
⟨a, ha.symm⟩⟩
#align pSet.mem.ext PSet.Mem.ext
theorem Mem.congr_right : ∀ {x y : PSet.{u}}, Equiv x y → ∀ {w : PSet.{u}}, w ∈ x ↔ w ∈ y
| ⟨_, _⟩, ⟨_, _⟩, ⟨αβ, βα⟩, _ =>
⟨fun ⟨a, ha⟩ =>
let ⟨b, hb⟩ := αβ a
⟨b, ha.trans hb⟩,
fun ⟨b, hb⟩ =>
let ⟨a, ha⟩ := βα b
⟨a, hb.euc ha⟩⟩
#align pSet.mem.congr_right PSet.Mem.congr_right
theorem equiv_iff_mem {x y : PSet.{u}} : Equiv x y ↔ ∀ {w : PSet.{u}}, w ∈ x ↔ w ∈ y :=
⟨Mem.congr_right,
match x, y with
| ⟨_, A⟩, ⟨_, B⟩ => fun h =>
⟨fun a => h.1 (Mem.mk A a), fun b =>
let ⟨a, h⟩ := h.2 (Mem.mk B b)
⟨a, h.symm⟩⟩⟩
#align pSet.equiv_iff_mem PSet.equiv_iff_mem
theorem Mem.congr_left : ∀ {x y : PSet.{u}}, Equiv x y → ∀ {w : PSet.{u}}, x ∈ w ↔ y ∈ w
| _, _, h, ⟨_, _⟩ => ⟨fun ⟨a, ha⟩ => ⟨a, h.symm.trans ha⟩, fun ⟨a, ha⟩ => ⟨a, h.trans ha⟩⟩
#align pSet.mem.congr_left PSet.Mem.congr_left
private theorem mem_wf_aux : ∀ {x y : PSet.{u}}, Equiv x y → Acc (· ∈ ·) y
| ⟨α, A⟩, ⟨β, B⟩, H =>
⟨_, by
rintro ⟨γ, C⟩ ⟨b, hc⟩
cases' H.exists_right b with a ha
have H := ha.trans hc.symm
rw [mk_func] at H
exact mem_wf_aux H⟩
theorem mem_wf : @WellFounded PSet (· ∈ ·) :=
⟨fun x => mem_wf_aux <| Equiv.refl x⟩
#align pSet.mem_wf PSet.mem_wf
instance : WellFoundedRelation PSet :=
⟨_, mem_wf⟩
instance : IsAsymm PSet (· ∈ ·) :=
mem_wf.isAsymm
instance : IsIrrefl PSet (· ∈ ·) :=
mem_wf.isIrrefl
theorem mem_asymm {x y : PSet} : x ∈ y → y ∉ x :=
asymm
#align pSet.mem_asymm PSet.mem_asymm
theorem mem_irrefl (x : PSet) : x ∉ x :=
irrefl x
#align pSet.mem_irrefl PSet.mem_irrefl
/-- Convert a pre-set to a `Set` of pre-sets. -/
def toSet (u : PSet.{u}) : Set PSet.{u} :=
{ x | x ∈ u }
#align pSet.to_set PSet.toSet
@[simp]
theorem mem_toSet (a u : PSet.{u}) : a ∈ u.toSet ↔ a ∈ u :=
Iff.rfl
#align pSet.mem_to_set PSet.mem_toSet
/-- A nonempty set is one that contains some element. -/
protected def Nonempty (u : PSet) : Prop :=
u.toSet.Nonempty
#align pSet.nonempty PSet.Nonempty
theorem nonempty_def (u : PSet) : u.Nonempty ↔ ∃ x, x ∈ u :=
Iff.rfl
#align pSet.nonempty_def PSet.nonempty_def
theorem nonempty_of_mem {x u : PSet} (h : x ∈ u) : u.Nonempty :=
⟨x, h⟩
#align pSet.nonempty_of_mem PSet.nonempty_of_mem
@[simp]
theorem nonempty_toSet_iff {u : PSet} : u.toSet.Nonempty ↔ u.Nonempty :=
Iff.rfl
#align pSet.nonempty_to_set_iff PSet.nonempty_toSet_iff
theorem nonempty_type_iff_nonempty {x : PSet} : Nonempty x.Type ↔ PSet.Nonempty x :=
⟨fun ⟨i⟩ => ⟨_, func_mem _ i⟩, fun ⟨_, j, _⟩ => ⟨j⟩⟩
#align pSet.nonempty_type_iff_nonempty PSet.nonempty_type_iff_nonempty
theorem nonempty_of_nonempty_type (x : PSet) [h : Nonempty x.Type] : PSet.Nonempty x :=
nonempty_type_iff_nonempty.1 h
#align pSet.nonempty_of_nonempty_type PSet.nonempty_of_nonempty_type
/-- Two pre-sets are equivalent iff they have the same members. -/
theorem Equiv.eq {x y : PSet} : Equiv x y ↔ toSet x = toSet y :=
equiv_iff_mem.trans Set.ext_iff.symm
#align pSet.equiv.eq PSet.Equiv.eq
instance : Coe PSet (Set PSet) :=
⟨toSet⟩
/-- The empty pre-set -/
protected def empty : PSet :=
⟨_, PEmpty.elim⟩
#align pSet.empty PSet.empty
instance : EmptyCollection PSet :=
⟨PSet.empty⟩
instance : Inhabited PSet :=
⟨∅⟩
instance : IsEmpty («Type» ∅) :=
⟨PEmpty.elim⟩
@[simp]
theorem not_mem_empty (x : PSet.{u}) : x ∉ (∅ : PSet.{u}) :=
IsEmpty.exists_iff.1
#align pSet.not_mem_empty PSet.not_mem_empty
@[simp]
theorem toSet_empty : toSet ∅ = ∅ := by simp [toSet]
#align pSet.to_set_empty PSet.toSet_empty
@[simp]
theorem empty_subset (x : PSet.{u}) : (∅ : PSet) ⊆ x := fun x => x.elim
#align pSet.empty_subset PSet.empty_subset
@[simp]
theorem not_nonempty_empty : ¬PSet.Nonempty ∅ := by simp [PSet.Nonempty]
#align pSet.not_nonempty_empty PSet.not_nonempty_empty
protected theorem equiv_empty (x : PSet) [IsEmpty x.Type] : Equiv x ∅ :=
PSet.equiv_of_isEmpty x _
#align pSet.equiv_empty PSet.equiv_empty
/-- Insert an element into a pre-set -/
protected def insert (x y : PSet) : PSet :=
⟨Option y.Type, fun o => Option.casesOn o x y.Func⟩
#align pSet.insert PSet.insert
instance : Insert PSet PSet :=
⟨PSet.insert⟩
instance : Singleton PSet PSet :=
⟨fun s => insert s ∅⟩
instance : LawfulSingleton PSet PSet :=
⟨fun _ => rfl⟩
instance (x y : PSet) : Inhabited (insert x y).Type :=
inferInstanceAs (Inhabited <| Option y.Type)
/-- The n-th von Neumann ordinal -/
def ofNat : ℕ → PSet
| 0 => ∅
| n + 1 => insert (ofNat n) (ofNat n)
#align pSet.of_nat PSet.ofNat
/-- The von Neumann ordinal ω -/
def omega : PSet :=
⟨ULift ℕ, fun n => ofNat n.down⟩
#align pSet.omega PSet.omega
/-- The pre-set separation operation `{x ∈ a | p x}` -/
protected def sep (p : PSet → Prop) (x : PSet) : PSet :=
⟨{ a // p (x.Func a) }, fun y => x.Func y.1⟩
#align pSet.sep PSet.sep
instance : Sep PSet PSet :=
⟨PSet.sep⟩
/-- The pre-set powerset operator -/
def powerset (x : PSet) : PSet :=
⟨Set x.Type, fun p => ⟨{ a // p a }, fun y => x.Func y.1⟩⟩
#align pSet.powerset PSet.powerset
@[simp]
theorem mem_powerset : ∀ {x y : PSet}, y ∈ powerset x ↔ y ⊆ x
| ⟨_, A⟩, ⟨_, B⟩ =>
⟨fun ⟨_, e⟩ => (Subset.congr_left e).2 fun ⟨a, _⟩ => ⟨a, Equiv.refl (A a)⟩, fun βα =>
⟨{ a | ∃ b, Equiv (B b) (A a) }, fun b =>
let ⟨a, ba⟩ := βα b
⟨⟨a, b, ba⟩, ba⟩,
fun ⟨_, b, ba⟩ => ⟨b, ba⟩⟩⟩
#align pSet.mem_powerset PSet.mem_powerset
/-- The pre-set union operator -/
def sUnion (a : PSet) : PSet :=
⟨Σx, (a.Func x).Type, fun ⟨x, y⟩ => (a.Func x).Func y⟩
#align pSet.sUnion PSet.sUnion
@[inherit_doc]
prefix:110 "⋃₀ " => sUnion
@[simp]
theorem mem_sUnion : ∀ {x y : PSet.{u}}, y ∈ ⋃₀ x ↔ ∃ z ∈ x, y ∈ z
| ⟨α, A⟩, y =>
⟨fun ⟨⟨a, c⟩, (e : Equiv y ((A a).Func c))⟩ =>
have : Func (A a) c ∈ mk (A a).Type (A a).Func := Mem.mk (A a).Func c
⟨_, Mem.mk _ _, (Mem.congr_left e).2 (by rwa [eta] at this)⟩,
fun ⟨⟨β, B⟩, ⟨a, (e : Equiv (mk β B) (A a))⟩, ⟨b, yb⟩⟩ => by
rw [← eta (A a)] at e
exact
let ⟨βt, _⟩ := e
let ⟨c, bc⟩ := βt b
⟨⟨a, c⟩, yb.trans bc⟩⟩
#align pSet.mem_sUnion PSet.mem_sUnion
@[simp]
theorem toSet_sUnion (x : PSet.{u}) : (⋃₀ x).toSet = ⋃₀ (toSet '' x.toSet) := by
ext
simp
#align pSet.to_set_sUnion PSet.toSet_sUnion
/-- The image of a function from pre-sets to pre-sets. -/
def image (f : PSet.{u} → PSet.{u}) (x : PSet.{u}) : PSet :=
⟨x.Type, f ∘ x.Func⟩
#align pSet.image PSet.image
-- Porting note: H arguments made explicit.
theorem mem_image {f : PSet.{u} → PSet.{u}} (H : ∀ x y, Equiv x y → Equiv (f x) (f y)) :
∀ {x y : PSet.{u}}, y ∈ image f x ↔ ∃ z ∈ x, Equiv y (f z)
| ⟨_, A⟩, _ =>
⟨fun ⟨a, ya⟩ => ⟨A a, Mem.mk A a, ya⟩, fun ⟨_, ⟨a, za⟩, yz⟩ => ⟨a, yz.trans <| H _ _ za⟩⟩
#align pSet.mem_image PSet.mem_image
/-- Universe lift operation -/
protected def Lift : PSet.{u} → PSet.{max u v}
| ⟨α, A⟩ => ⟨ULift.{v, u} α, fun ⟨x⟩ => PSet.Lift (A x)⟩
#align pSet.lift PSet.Lift
-- intended to be used with explicit universe parameters
/-- Embedding of one universe in another -/
@[nolint checkUnivs]
def embed : PSet.{max (u + 1) v} :=
⟨ULift.{v, u + 1} PSet, fun ⟨x⟩ => PSet.Lift.{u, max (u + 1) v} x⟩
#align pSet.embed PSet.embed
theorem lift_mem_embed : ∀ x : PSet.{u}, PSet.Lift.{u, max (u + 1) v} x ∈ embed.{u, v} := fun x =>
⟨⟨x⟩, Equiv.rfl⟩
#align pSet.lift_mem_embed PSet.lift_mem_embed
/-- Function equivalence is defined so that `f ~ g` iff `∀ x y, x ~ y → f x ~ g y`. This extends to
equivalence of `n`-ary functions. -/
def Arity.Equiv : ∀ {n}, OfArity PSet.{u} PSet.{u} n → OfArity PSet.{u} PSet.{u} n → Prop
| 0, a, b => PSet.Equiv a b
| _ + 1, a, b => ∀ x y : PSet, PSet.Equiv x y → Arity.Equiv (a x) (b y)
#align pSet.arity.equiv PSet.Arity.Equiv
theorem Arity.equiv_const {a : PSet.{u}} :
∀ n, Arity.Equiv (OfArity.const PSet.{u} a n) (OfArity.const PSet.{u} a n)
| 0 => Equiv.rfl
| _ + 1 => fun _ _ _ => Arity.equiv_const _
#align pSet.arity.equiv_const PSet.Arity.equiv_const
/-- `resp n` is the collection of n-ary functions on `PSet` that respect
equivalence, i.e. when the inputs are equivalent the output is as well. -/
def Resp (n) :=
{ x : OfArity PSet.{u} PSet.{u} n // Arity.Equiv x x }
#align pSet.resp PSet.Resp
instance Resp.inhabited {n} : Inhabited (Resp n) :=
⟨⟨OfArity.const _ default _, Arity.equiv_const _⟩⟩
#align pSet.resp.inhabited PSet.Resp.inhabited
/-- The `n`-ary image of a `(n + 1)`-ary function respecting equivalence as a function respecting
equivalence. -/
def Resp.f {n} (f : Resp (n + 1)) (x : PSet) : Resp n :=
⟨f.1 x, f.2 _ _ <| Equiv.refl x⟩
#align pSet.resp.f PSet.Resp.f
/-- Function equivalence for functions respecting equivalence. See `PSet.Arity.Equiv`. -/
def Resp.Equiv {n} (a b : Resp n) : Prop :=
Arity.Equiv a.1 b.1
#align pSet.resp.equiv PSet.Resp.Equiv
@[refl]
protected theorem Resp.Equiv.refl {n} (a : Resp n) : Resp.Equiv a a :=
a.2
#align pSet.resp.equiv.refl PSet.Resp.Equiv.refl
protected theorem Resp.Equiv.euc :
∀ {n} {a b c : Resp n}, Resp.Equiv a b → Resp.Equiv c b → Resp.Equiv a c
| 0, _, _, _, hab, hcb => PSet.Equiv.euc hab hcb
| n + 1, a, b, c, hab, hcb => fun x y h =>
@Resp.Equiv.euc n (a.f x) (b.f y) (c.f y) (hab _ _ h) (hcb _ _ <| PSet.Equiv.refl y)
#align pSet.resp.equiv.euc PSet.Resp.Equiv.euc
@[symm]
protected theorem Resp.Equiv.symm {n} {a b : Resp n} : Resp.Equiv a b → Resp.Equiv b a :=
(Resp.Equiv.refl b).euc
#align pSet.resp.equiv.symm PSet.Resp.Equiv.symm
@[trans]
protected theorem Resp.Equiv.trans {n} {x y z : Resp n} (h1 : Resp.Equiv x y)
(h2 : Resp.Equiv y z) : Resp.Equiv x z :=
h1.euc h2.symm
#align pSet.resp.equiv.trans PSet.Resp.Equiv.trans
instance Resp.setoid {n} : Setoid (Resp n) :=
⟨Resp.Equiv, Resp.Equiv.refl, Resp.Equiv.symm, Resp.Equiv.trans⟩
#align pSet.resp.setoid PSet.Resp.setoid
end PSet
/-- The ZFC universe of sets consists of the type of pre-sets,
quotiented by extensional equivalence. -/
def ZFSet : Type (u + 1) :=
Quotient PSet.setoid.{u}
#align Set ZFSet
namespace PSet
namespace Resp
/-- Helper function for `PSet.eval`. -/
def evalAux :
∀ {n},
{ f : Resp n → OfArity ZFSet.{u} ZFSet.{u} n // ∀ a b : Resp n, Resp.Equiv a b → f a = f b }
| 0 => ⟨fun a => ⟦a.1⟧, fun _ _ h => Quotient.sound h⟩
| n + 1 =>
let F : Resp (n + 1) → OfArity ZFSet ZFSet (n + 1) := fun a =>
@Quotient.lift _ _ PSet.setoid (fun x => evalAux.1 (a.f x)) fun _ _ h =>
evalAux.2 _ _ (a.2 _ _ h)
⟨F, fun b c h =>
funext <|
(@Quotient.ind _ _ fun q => F b q = F c q) fun z =>
evalAux.2 (Resp.f b z) (Resp.f c z) (h _ _ (PSet.Equiv.refl z))⟩
#align pSet.resp.eval_aux PSet.Resp.evalAux
/-- An equivalence-respecting function yields an n-ary ZFC set function. -/
def eval (n) : Resp n → OfArity ZFSet.{u} ZFSet.{u} n :=
evalAux.1
#align pSet.resp.eval PSet.Resp.eval
theorem eval_val {n f x} :
(@eval (n + 1) f : ZFSet → OfArity ZFSet ZFSet n) ⟦x⟧ = eval n (Resp.f f x) :=
rfl
#align pSet.resp.eval_val PSet.Resp.eval_val
end Resp
/-- A set function is "definable" if it is the image of some n-ary pre-set
function. This isn't exactly definability, but is useful as a sufficient
condition for functions that have a computable image. -/
class inductive Definable (n) : OfArity ZFSet.{u} ZFSet.{u} n → Type (u + 1)
| mk (f) : Definable n (Resp.eval n f)
#align pSet.definable PSet.Definable
attribute [instance] Definable.mk
/-- The evaluation of a function respecting equivalence is definable, by that same function. -/
def Definable.EqMk {n} (f) :
∀ {s : OfArity ZFSet.{u} ZFSet.{u} n} (_ : Resp.eval _ f = s), Definable n s
| _, rfl => ⟨f⟩
#align pSet.definable.eq_mk PSet.Definable.EqMk
/-- Turns a definable function into a function that respects equivalence. -/
def Definable.Resp {n} : ∀ (s : OfArity ZFSet.{u} ZFSet.{u} n) [Definable n s], Resp n
| _, ⟨f⟩ => f
#align pSet.definable.resp PSet.Definable.Resp
theorem Definable.eq {n} :
∀ (s : OfArity ZFSet.{u} ZFSet.{u} n) [H : Definable n s], (@Definable.Resp n s H).eval _ = s
| _, ⟨_⟩ => rfl
#align pSet.definable.eq PSet.Definable.eq
end PSet
namespace Classical
open PSet
/-- All functions are classically definable. -/
noncomputable def allDefinable : ∀ {n} (F : OfArity ZFSet ZFSet n), Definable n F
| 0, F =>
let p := @Quotient.exists_rep PSet _ F
@Definable.EqMk 0 ⟨choose p, Equiv.rfl⟩ _ (choose_spec p)
| n + 1, (F : OfArity ZFSet ZFSet (n + 1)) => by
have I : (x : ZFSet) → Definable n (F x) := fun x => allDefinable (F x)
refine @Definable.EqMk (n + 1) ⟨fun x : PSet => (@Definable.Resp _ _ (I ⟦x⟧)).1, ?_⟩ _ ?_
· dsimp [Arity.Equiv]
intro x y h
rw [@Quotient.sound PSet _ _ _ h]
exact (Definable.Resp (F ⟦y⟧)).2
refine funext fun q => Quotient.inductionOn q fun x => ?_
simp_rw [Resp.eval_val, Resp.f]
exact @Definable.eq _ (F ⟦x⟧) (I ⟦x⟧)
#align classical.all_definable Classical.allDefinable
end Classical
namespace ZFSet
open PSet
/-- Turns a pre-set into a ZFC set. -/
def mk : PSet → ZFSet :=
Quotient.mk''
#align Set.mk ZFSet.mk
@[simp]
theorem mk_eq (x : PSet) : @Eq ZFSet ⟦x⟧ (mk x) :=
rfl
#align Set.mk_eq ZFSet.mk_eq
@[simp]
theorem mk_out : ∀ x : ZFSet, mk x.out = x :=
Quotient.out_eq
#align Set.mk_out ZFSet.mk_out
theorem eq {x y : PSet} : mk x = mk y ↔ Equiv x y :=
Quotient.eq
#align Set.eq ZFSet.eq
theorem sound {x y : PSet} (h : PSet.Equiv x y) : mk x = mk y :=
Quotient.sound h
#align Set.sound ZFSet.sound
theorem exact {x y : PSet} : mk x = mk y → PSet.Equiv x y :=
Quotient.exact
#align Set.exact ZFSet.exact
@[simp]
theorem eval_mk {n f x} :
(@Resp.eval (n + 1) f : ZFSet → OfArity ZFSet ZFSet n) (mk x) = Resp.eval n (Resp.f f x) :=
rfl
#align Set.eval_mk ZFSet.eval_mk
/-- The membership relation for ZFC sets is inherited from the membership relation for pre-sets. -/
protected def Mem : ZFSet → ZFSet → Prop :=
Quotient.lift₂ PSet.Mem fun _ _ _ _ hx hy =>
propext ((Mem.congr_left hx).trans (Mem.congr_right hy))
#align Set.mem ZFSet.Mem
instance : Membership ZFSet ZFSet :=
⟨ZFSet.Mem⟩
@[simp]
theorem mk_mem_iff {x y : PSet} : mk x ∈ mk y ↔ x ∈ y :=
Iff.rfl
#align Set.mk_mem_iff ZFSet.mk_mem_iff
/-- Convert a ZFC set into a `Set` of ZFC sets -/
def toSet (u : ZFSet.{u}) : Set ZFSet.{u} :=
{ x | x ∈ u }
#align Set.to_set ZFSet.toSet
@[simp]
theorem mem_toSet (a u : ZFSet.{u}) : a ∈ u.toSet ↔ a ∈ u :=
Iff.rfl
#align Set.mem_to_set ZFSet.mem_toSet
instance small_toSet (x : ZFSet.{u}) : Small.{u} x.toSet :=
Quotient.inductionOn x fun a => by
let f : a.Type → (mk a).toSet := fun i => ⟨mk <| a.Func i, func_mem a i⟩
suffices Function.Surjective f by exact small_of_surjective this
rintro ⟨y, hb⟩
induction y using Quotient.inductionOn
cases' hb with i h
exact ⟨i, Subtype.coe_injective (Quotient.sound h.symm)⟩
#align Set.small_to_set ZFSet.small_toSet
/-- A nonempty set is one that contains some element. -/
protected def Nonempty (u : ZFSet) : Prop :=
u.toSet.Nonempty
#align Set.nonempty ZFSet.Nonempty
theorem nonempty_def (u : ZFSet) : u.Nonempty ↔ ∃ x, x ∈ u :=
Iff.rfl
#align Set.nonempty_def ZFSet.nonempty_def
theorem nonempty_of_mem {x u : ZFSet} (h : x ∈ u) : u.Nonempty :=
⟨x, h⟩
#align Set.nonempty_of_mem ZFSet.nonempty_of_mem
@[simp]
theorem nonempty_toSet_iff {u : ZFSet} : u.toSet.Nonempty ↔ u.Nonempty :=
Iff.rfl
#align Set.nonempty_to_set_iff ZFSet.nonempty_toSet_iff
/-- `x ⊆ y` as ZFC sets means that all members of `x` are members of `y`. -/
protected def Subset (x y : ZFSet.{u}) :=
∀ ⦃z⦄, z ∈ x → z ∈ y
#align Set.subset ZFSet.Subset
instance hasSubset : HasSubset ZFSet :=
⟨ZFSet.Subset⟩
#align Set.has_subset ZFSet.hasSubset
theorem subset_def {x y : ZFSet.{u}} : x ⊆ y ↔ ∀ ⦃z⦄, z ∈ x → z ∈ y :=
Iff.rfl
#align Set.subset_def ZFSet.subset_def
instance : IsRefl ZFSet (· ⊆ ·) :=
⟨fun _ _ => id⟩
instance : IsTrans ZFSet (· ⊆ ·) :=
⟨fun _ _ _ hxy hyz _ ha => hyz (hxy ha)⟩
@[simp]
theorem subset_iff : ∀ {x y : PSet}, mk x ⊆ mk y ↔ x ⊆ y
| ⟨_, A⟩, ⟨_, _⟩ =>
⟨fun h a => @h ⟦A a⟧ (Mem.mk A a), fun h z =>
Quotient.inductionOn z fun _ ⟨a, za⟩ =>
let ⟨b, ab⟩ := h a
⟨b, za.trans ab⟩⟩
#align Set.subset_iff ZFSet.subset_iff
@[simp]
theorem toSet_subset_iff {x y : ZFSet} : x.toSet ⊆ y.toSet ↔ x ⊆ y := by
simp [subset_def, Set.subset_def]
#align Set.to_set_subset_iff ZFSet.toSet_subset_iff
@[ext]
theorem ext {x y : ZFSet.{u}} : (∀ z : ZFSet.{u}, z ∈ x ↔ z ∈ y) → x = y :=
Quotient.inductionOn₂ x y fun _ _ h => Quotient.sound (Mem.ext fun w => h ⟦w⟧)
#align Set.ext ZFSet.ext
theorem ext_iff {x y : ZFSet.{u}} : x = y ↔ ∀ z : ZFSet.{u}, z ∈ x ↔ z ∈ y :=
⟨fun h => by simp [h], ext⟩
#align Set.ext_iff ZFSet.ext_iff
theorem toSet_injective : Function.Injective toSet := fun _ _ h => ext <| Set.ext_iff.1 h
#align Set.to_set_injective ZFSet.toSet_injective
@[simp]
theorem toSet_inj {x y : ZFSet} : x.toSet = y.toSet ↔ x = y :=
toSet_injective.eq_iff
#align Set.to_set_inj ZFSet.toSet_inj
instance : IsAntisymm ZFSet (· ⊆ ·) :=
⟨fun _ _ hab hba => ext fun c => ⟨@hab c, @hba c⟩⟩
/-- The empty ZFC set -/
protected def empty : ZFSet :=
mk ∅
#align Set.empty ZFSet.empty
instance : EmptyCollection ZFSet :=
⟨ZFSet.empty⟩
instance : Inhabited ZFSet :=
⟨∅⟩
@[simp]
theorem not_mem_empty (x) : x ∉ (∅ : ZFSet.{u}) :=
Quotient.inductionOn x PSet.not_mem_empty
#align Set.not_mem_empty ZFSet.not_mem_empty
@[simp]
theorem toSet_empty : toSet ∅ = ∅ := by simp [toSet]
#align Set.to_set_empty ZFSet.toSet_empty
@[simp]
theorem empty_subset (x : ZFSet.{u}) : (∅ : ZFSet) ⊆ x :=
Quotient.inductionOn x fun y => subset_iff.2 <| PSet.empty_subset y
#align Set.empty_subset ZFSet.empty_subset
@[simp]
theorem not_nonempty_empty : ¬ZFSet.Nonempty ∅ := by simp [ZFSet.Nonempty]
#align Set.not_nonempty_empty ZFSet.not_nonempty_empty
@[simp]
theorem nonempty_mk_iff {x : PSet} : (mk x).Nonempty ↔ x.Nonempty := by
refine ⟨?_, fun ⟨a, h⟩ => ⟨mk a, h⟩⟩
rintro ⟨a, h⟩
induction a using Quotient.inductionOn
exact ⟨_, h⟩
#align Set.nonempty_mk_iff ZFSet.nonempty_mk_iff
theorem eq_empty (x : ZFSet.{u}) : x = ∅ ↔ ∀ y : ZFSet.{u}, y ∉ x := by
rw [ext_iff]
simp
#align Set.eq_empty ZFSet.eq_empty
theorem eq_empty_or_nonempty (u : ZFSet) : u = ∅ ∨ u.Nonempty := by
rw [eq_empty, ← not_exists]
apply em'
#align Set.eq_empty_or_nonempty ZFSet.eq_empty_or_nonempty
/-- `Insert x y` is the set `{x} ∪ y` -/
protected def Insert : ZFSet → ZFSet → ZFSet :=
Resp.eval 2
⟨PSet.insert, fun _ _ uv ⟨_, _⟩ ⟨_, _⟩ ⟨αβ, βα⟩ =>
⟨fun o =>
match o with
| some a =>
let ⟨b, hb⟩ := αβ a
⟨some b, hb⟩
| none => ⟨none, uv⟩,
fun o =>
match o with
| some b =>
let ⟨a, ha⟩ := βα b
⟨some a, ha⟩
| none => ⟨none, uv⟩⟩⟩
#align Set.insert ZFSet.Insert
instance : Insert ZFSet ZFSet :=
⟨ZFSet.Insert⟩
instance : Singleton ZFSet ZFSet :=
⟨fun x => insert x ∅⟩
instance : LawfulSingleton ZFSet ZFSet :=
⟨fun _ => rfl⟩
@[simp]
theorem mem_insert_iff {x y z : ZFSet.{u}} : x ∈ insert y z ↔ x = y ∨ x ∈ z :=
Quotient.inductionOn₃ x y z fun x y ⟨α, A⟩ =>
show (x ∈ PSet.mk (Option α) fun o => Option.rec y A o) ↔ mk x = mk y ∨ x ∈ PSet.mk α A from
⟨fun m =>
match m with
| ⟨some a, ha⟩ => Or.inr ⟨a, ha⟩
| ⟨none, h⟩ => Or.inl (Quotient.sound h),
fun m =>
match m with
| Or.inr ⟨a, ha⟩ => ⟨some a, ha⟩
| Or.inl h => ⟨none, Quotient.exact h⟩⟩
#align Set.mem_insert_iff ZFSet.mem_insert_iff
theorem mem_insert (x y : ZFSet) : x ∈ insert x y :=
mem_insert_iff.2 <| Or.inl rfl
#align Set.mem_insert ZFSet.mem_insert
theorem mem_insert_of_mem {y z : ZFSet} (x) (h : z ∈ y) : z ∈ insert x y :=
mem_insert_iff.2 <| Or.inr h
#align Set.mem_insert_of_mem ZFSet.mem_insert_of_mem
@[simp]
theorem toSet_insert (x y : ZFSet) : (insert x y).toSet = insert x y.toSet := by
ext
simp
#align Set.to_set_insert ZFSet.toSet_insert
@[simp]
theorem mem_singleton {x y : ZFSet.{u}} : x ∈ @singleton ZFSet.{u} ZFSet.{u} _ y ↔ x = y :=
Iff.trans mem_insert_iff
⟨fun o => Or.rec (fun h => h) (fun n => absurd n (not_mem_empty _)) o, Or.inl⟩
#align Set.mem_singleton ZFSet.mem_singleton
@[simp]
theorem toSet_singleton (x : ZFSet) : ({x} : ZFSet).toSet = {x} := by
ext
simp
#align Set.to_set_singleton ZFSet.toSet_singleton
theorem insert_nonempty (u v : ZFSet) : (insert u v).Nonempty :=
⟨u, mem_insert u v⟩
#align Set.insert_nonempty ZFSet.insert_nonempty
theorem singleton_nonempty (u : ZFSet) : ZFSet.Nonempty {u} :=
insert_nonempty u ∅
#align Set.singleton_nonempty ZFSet.singleton_nonempty
theorem mem_pair {x y z : ZFSet.{u}} : x ∈ ({y, z} : ZFSet) ↔ x = y ∨ x = z := by
simp
#align Set.mem_pair ZFSet.mem_pair
/-- `omega` is the first infinite von Neumann ordinal -/
def omega : ZFSet :=
mk PSet.omega
#align Set.omega ZFSet.omega
@[simp]
theorem omega_zero : ∅ ∈ omega :=
⟨⟨0⟩, Equiv.rfl⟩
#align Set.omega_zero ZFSet.omega_zero
@[simp]
theorem omega_succ {n} : n ∈ omega.{u} → insert n n ∈ omega.{u} :=
Quotient.inductionOn n fun x ⟨⟨n⟩, h⟩ =>
⟨⟨n + 1⟩,
ZFSet.exact <|
show insert (mk x) (mk x) = insert (mk <| ofNat n) (mk <| ofNat n) by
rw [ZFSet.sound h]
rfl⟩
#align Set.omega_succ ZFSet.omega_succ
/-- `{x ∈ a | p x}` is the set of elements in `a` satisfying `p` -/
protected def sep (p : ZFSet → Prop) : ZFSet → ZFSet :=
Resp.eval 1
⟨PSet.sep fun y => p (mk y), fun ⟨α, A⟩ ⟨β, B⟩ ⟨αβ, βα⟩ =>
⟨fun ⟨a, pa⟩ =>
let ⟨b, hb⟩ := αβ a
⟨⟨b, by simpa only [mk_func, ← ZFSet.sound hb]⟩, hb⟩,
fun ⟨b, pb⟩ =>
let ⟨a, ha⟩ := βα b
⟨⟨a, by simpa only [mk_func, ZFSet.sound ha]⟩, ha⟩⟩⟩
#align Set.sep ZFSet.sep
-- Porting note: the { x | p x } notation appears to be disabled in Lean 4.
instance : Sep ZFSet ZFSet :=
⟨ZFSet.sep⟩
@[simp]
theorem mem_sep {p : ZFSet.{u} → Prop} {x y : ZFSet.{u}} :
y ∈ ZFSet.sep p x ↔ y ∈ x ∧ p y :=
Quotient.inductionOn₂ x y fun ⟨α, A⟩ y =>
⟨fun ⟨⟨a, pa⟩, h⟩ => ⟨⟨a, h⟩, by rwa [@Quotient.sound PSet _ _ _ h]⟩, fun ⟨⟨a, h⟩, pa⟩ =>
⟨⟨a, by
rw [mk_func] at h
rwa [mk_func, ← ZFSet.sound h]⟩,
h⟩⟩
#align Set.mem_sep ZFSet.mem_sep
@[simp]
theorem toSet_sep (a : ZFSet) (p : ZFSet → Prop) :
(ZFSet.sep p a).toSet = { x ∈ a.toSet | p x } := by
ext
simp
#align Set.to_set_sep ZFSet.toSet_sep
/-- The powerset operation, the collection of subsets of a ZFC set -/
def powerset : ZFSet → ZFSet :=
Resp.eval 1
⟨PSet.powerset, fun ⟨_, A⟩ ⟨_, B⟩ ⟨αβ, βα⟩ =>
⟨fun p =>
⟨{ b | ∃ a, p a ∧ Equiv (A a) (B b) }, fun ⟨a, pa⟩ =>
let ⟨b, ab⟩ := αβ a
⟨⟨b, a, pa, ab⟩, ab⟩,
fun ⟨_, a, pa, ab⟩ => ⟨⟨a, pa⟩, ab⟩⟩,
fun q =>
⟨{ a | ∃ b, q b ∧ Equiv (A a) (B b) }, fun ⟨_, b, qb, ab⟩ => ⟨⟨b, qb⟩, ab⟩, fun ⟨b, qb⟩ =>
let ⟨a, ab⟩ := βα b
⟨⟨a, b, qb, ab⟩, ab⟩⟩⟩⟩
#align Set.powerset ZFSet.powerset
@[simp]
theorem mem_powerset {x y : ZFSet.{u}} : y ∈ powerset x ↔ y ⊆ x :=
Quotient.inductionOn₂ x y fun ⟨α, A⟩ ⟨β, B⟩ =>
show (⟨β, B⟩ : PSet.{u}) ∈ PSet.powerset.{u} ⟨α, A⟩ ↔ _ by simp [mem_powerset, subset_iff]
#align Set.mem_powerset ZFSet.mem_powerset
theorem sUnion_lem {α β : Type u} (A : α → PSet) (B : β → PSet) (αβ : ∀ a, ∃ b, Equiv (A a) (B b)) :
∀ a, ∃ b, Equiv ((sUnion ⟨α, A⟩).Func a) ((sUnion ⟨β, B⟩).Func b)
| ⟨a, c⟩ => by
let ⟨b, hb⟩ := αβ a
induction' ea : A a with γ Γ
induction' eb : B b with δ Δ
rw [ea, eb] at hb
cases' hb with γδ δγ
let c : (A a).Type := c
let ⟨d, hd⟩ := γδ (by rwa [ea] at c)
use ⟨b, Eq.ndrec d (Eq.symm eb)⟩
change PSet.Equiv ((A a).Func c) ((B b).Func (Eq.ndrec d eb.symm))
match A a, B b, ea, eb, c, d, hd with
| _, _, rfl, rfl, _, _, hd => exact hd
#align Set.sUnion_lem ZFSet.sUnion_lem
/-- The union operator, the collection of elements of elements of a ZFC set -/
def sUnion : ZFSet → ZFSet :=
Resp.eval 1
⟨PSet.sUnion, fun ⟨_, A⟩ ⟨_, B⟩ ⟨αβ, βα⟩ =>
⟨sUnion_lem A B αβ, fun a =>
Exists.elim
(sUnion_lem B A (fun b => Exists.elim (βα b) fun c hc => ⟨c, PSet.Equiv.symm hc⟩) a)
fun b hb => ⟨b, PSet.Equiv.symm hb⟩⟩⟩
#align Set.sUnion ZFSet.sUnion
@[inherit_doc]
prefix:110 "⋃₀ " => ZFSet.sUnion
/-- The intersection operator, the collection of elements in all of the elements of a ZFC set. We
special-case `⋂₀ ∅ = ∅`. -/
noncomputable def sInter (x : ZFSet) : ZFSet := by
classical exact if h : x.Nonempty then ZFSet.sep (fun y => ∀ z ∈ x, y ∈ z) h.some else ∅
#align Set.sInter ZFSet.sInter
@[inherit_doc]
prefix:110 "⋂₀ " => ZFSet.sInter
@[simp]
theorem mem_sUnion {x y : ZFSet.{u}} : y ∈ ⋃₀ x ↔ ∃ z ∈ x, y ∈ z :=
Quotient.inductionOn₂ x y fun _ _ =>
Iff.trans PSet.mem_sUnion
⟨fun ⟨z, h⟩ => ⟨⟦z⟧, h⟩, fun ⟨z, h⟩ => Quotient.inductionOn z (fun z h => ⟨z, h⟩) h⟩
#align Set.mem_sUnion ZFSet.mem_sUnion
theorem mem_sInter {x y : ZFSet} (h : x.Nonempty) : y ∈ ⋂₀ x ↔ ∀ z ∈ x, y ∈ z := by
rw [sInter, dif_pos h]
simp only [mem_toSet, mem_sep, and_iff_right_iff_imp]
exact fun H => H _ h.some_mem
#align Set.mem_sInter ZFSet.mem_sInter
@[simp]
theorem sUnion_empty : ⋃₀ (∅ : ZFSet.{u}) = ∅ := by
ext
simp
#align Set.sUnion_empty ZFSet.sUnion_empty
@[simp]
theorem sInter_empty : ⋂₀ (∅ : ZFSet) = ∅ := dif_neg <| by simp
#align Set.sInter_empty ZFSet.sInter_empty
theorem mem_of_mem_sInter {x y z : ZFSet} (hy : y ∈ ⋂₀ x) (hz : z ∈ x) : y ∈ z := by
rcases eq_empty_or_nonempty x with (rfl | hx)
· exact (not_mem_empty z hz).elim
· exact (mem_sInter hx).1 hy z hz
#align Set.mem_of_mem_sInter ZFSet.mem_of_mem_sInter
theorem mem_sUnion_of_mem {x y z : ZFSet} (hy : y ∈ z) (hz : z ∈ x) : y ∈ ⋃₀ x :=
mem_sUnion.2 ⟨z, hz, hy⟩
#align Set.mem_sUnion_of_mem ZFSet.mem_sUnion_of_mem
theorem not_mem_sInter_of_not_mem {x y z : ZFSet} (hy : ¬y ∈ z) (hz : z ∈ x) : ¬y ∈ ⋂₀ x :=
fun hx => hy <| mem_of_mem_sInter hx hz
#align Set.not_mem_sInter_of_not_mem ZFSet.not_mem_sInter_of_not_mem
@[simp]
theorem sUnion_singleton {x : ZFSet.{u}} : ⋃₀ ({x} : ZFSet) = x :=
ext fun y => by simp_rw [mem_sUnion, mem_singleton, exists_eq_left]
#align Set.sUnion_singleton ZFSet.sUnion_singleton
@[simp]
theorem sInter_singleton {x : ZFSet.{u}} : ⋂₀ ({x} : ZFSet) = x :=
ext fun y => by simp_rw [mem_sInter (singleton_nonempty x), mem_singleton, forall_eq]
#align Set.sInter_singleton ZFSet.sInter_singleton
@[simp]
theorem toSet_sUnion (x : ZFSet.{u}) : (⋃₀ x).toSet = ⋃₀ (toSet '' x.toSet) := by
ext
simp
#align Set.to_set_sUnion ZFSet.toSet_sUnion
theorem toSet_sInter {x : ZFSet.{u}} (h : x.Nonempty) : (⋂₀ x).toSet = ⋂₀ (toSet '' x.toSet) := by
ext
simp [mem_sInter h]
#align Set.to_set_sInter ZFSet.toSet_sInter
theorem singleton_injective : Function.Injective (@singleton ZFSet ZFSet _) := fun x y H => by
let this := congr_arg sUnion H
rwa [sUnion_singleton, sUnion_singleton] at this
#align Set.singleton_injective ZFSet.singleton_injective
@[simp]
theorem singleton_inj {x y : ZFSet} : ({x} : ZFSet) = {y} ↔ x = y :=
singleton_injective.eq_iff
#align Set.singleton_inj ZFSet.singleton_inj
/-- The binary union operation -/
protected def union (x y : ZFSet.{u}) : ZFSet.{u} :=
⋃₀ {x, y}
#align Set.union ZFSet.union
/-- The binary intersection operation -/
protected def inter (x y : ZFSet.{u}) : ZFSet.{u} :=
ZFSet.sep (fun z => z ∈ y) x -- { z ∈ x | z ∈ y }
#align Set.inter ZFSet.inter
/-- The set difference operation -/
protected def diff (x y : ZFSet.{u}) : ZFSet.{u} :=
ZFSet.sep (fun z => z ∉ y) x -- { z ∈ x | z ∉ y }
#align Set.diff ZFSet.diff
instance : Union ZFSet :=
⟨ZFSet.union⟩
instance : Inter ZFSet :=
⟨ZFSet.inter⟩
instance : SDiff ZFSet :=
⟨ZFSet.diff⟩
@[simp]
theorem toSet_union (x y : ZFSet.{u}) : (x ∪ y).toSet = x.toSet ∪ y.toSet := by
change (⋃₀ {x, y}).toSet = _
simp
#align Set.to_set_union ZFSet.toSet_union
@[simp]
theorem toSet_inter (x y : ZFSet.{u}) : (x ∩ y).toSet = x.toSet ∩ y.toSet := by
change (ZFSet.sep (fun z => z ∈ y) x).toSet = _
ext
simp
#align Set.to_set_inter ZFSet.toSet_inter
@[simp]
theorem toSet_sdiff (x y : ZFSet.{u}) : (x \ y).toSet = x.toSet \ y.toSet := by
change (ZFSet.sep (fun z => z ∉ y) x).toSet = _
ext
simp
#align Set.to_set_sdiff ZFSet.toSet_sdiff
@[simp]
theorem mem_union {x y z : ZFSet.{u}} : z ∈ x ∪ y ↔ z ∈ x ∨ z ∈ y := by
rw [← mem_toSet]
simp
#align Set.mem_union ZFSet.mem_union
@[simp]
theorem mem_inter {x y z : ZFSet.{u}} : z ∈ x ∩ y ↔ z ∈ x ∧ z ∈ y :=
@mem_sep (fun z : ZFSet.{u} => z ∈ y) x z
#align Set.mem_inter ZFSet.mem_inter
@[simp]
theorem mem_diff {x y z : ZFSet.{u}} : z ∈ x \ y ↔ z ∈ x ∧ z ∉ y :=
@mem_sep (fun z : ZFSet.{u} => z ∉ y) x z
#align Set.mem_diff ZFSet.mem_diff
@[simp]
theorem sUnion_pair {x y : ZFSet.{u}} : ⋃₀ ({x, y} : ZFSet.{u}) = x ∪ y :=
rfl
#align Set.sUnion_pair ZFSet.sUnion_pair
theorem mem_wf : @WellFounded ZFSet (· ∈ ·) :=
(wellFounded_lift₂_iff (H := fun a b c d hx hy =>
propext ((@Mem.congr_left a c hx).trans (@Mem.congr_right b d hy _)))).mpr PSet.mem_wf
#align Set.mem_wf ZFSet.mem_wf
/-- Induction on the `∈` relation. -/
@[elab_as_elim]
theorem inductionOn {p : ZFSet → Prop} (x) (h : ∀ x, (∀ y ∈ x, p y) → p x) : p x :=
mem_wf.induction x h
#align Set.induction_on ZFSet.inductionOn
instance : WellFoundedRelation ZFSet :=
⟨_, mem_wf⟩
instance : IsAsymm ZFSet (· ∈ ·) :=
mem_wf.isAsymm
-- Porting note: this can't be inferred automatically for some reason.
instance : IsIrrefl ZFSet (· ∈ ·) :=
mem_wf.isIrrefl
theorem mem_asymm {x y : ZFSet} : x ∈ y → y ∉ x :=
asymm
#align Set.mem_asymm ZFSet.mem_asymm
theorem mem_irrefl (x : ZFSet) : x ∉ x :=
irrefl x
#align Set.mem_irrefl ZFSet.mem_irrefl
theorem regularity (x : ZFSet.{u}) (h : x ≠ ∅) : ∃ y ∈ x, x ∩ y = ∅ :=
by_contradiction fun ne =>
h <| (eq_empty x).2 fun y =>
@inductionOn (fun z => z ∉ x) y fun z IH zx =>
ne ⟨z, zx, (eq_empty _).2 fun w wxz =>
let ⟨wx, wz⟩ := mem_inter.1 wxz
IH w wz wx⟩
#align Set.regularity ZFSet.regularity
/-- The image of a (definable) ZFC set function -/
def image (f : ZFSet → ZFSet) [Definable 1 f] : ZFSet → ZFSet :=
let ⟨r, hr⟩ := @Definable.Resp 1 f _
Resp.eval 1
⟨PSet.image r, fun _ _ e =>
Mem.ext fun _ =>
(mem_image hr).trans <|
Iff.trans
⟨fun ⟨w, h1, h2⟩ => ⟨w, (Mem.congr_right e).1 h1, h2⟩, fun ⟨w, h1, h2⟩ =>
⟨w, (Mem.congr_right e).2 h1, h2⟩⟩ <|
(mem_image hr).symm⟩
#align Set.image ZFSet.image
theorem image.mk :
∀ (f : ZFSet.{u} → ZFSet.{u}) [H : Definable 1 f] (x) {y} (_ : y ∈ x), f y ∈ @image f H x
| _, ⟨F⟩, x, y => Quotient.inductionOn₂ x y fun ⟨_, _⟩ _ ⟨a, ya⟩ => ⟨a, F.2 _ _ ya⟩
#align Set.image.mk ZFSet.image.mk
@[simp]
theorem mem_image :
∀ {f : ZFSet.{u} → ZFSet.{u}} [H : Definable 1 f] {x y : ZFSet.{u}},
y ∈ @image f H x ↔ ∃ z ∈ x, f z = y
| _, ⟨_⟩, x, y =>
Quotient.inductionOn₂ x y fun ⟨_, A⟩ _ =>
⟨fun ⟨a, ya⟩ => ⟨⟦A a⟧, Mem.mk A a, Eq.symm <| Quotient.sound ya⟩, fun ⟨_, hz, e⟩ =>
e ▸ image.mk _ _ hz⟩
#align Set.mem_image ZFSet.mem_image
@[simp]
theorem toSet_image (f : ZFSet → ZFSet) [H : Definable 1 f] (x : ZFSet) :
(image f x).toSet = f '' x.toSet := by
ext
simp
#align Set.to_set_image ZFSet.toSet_image
/-- The range of an indexed family of sets. The universes allow for a more general index type
without manual use of `ULift`. -/
noncomputable def range {α : Type u} (f : α → ZFSet.{max u v}) : ZFSet.{max u v} :=
⟦⟨ULift.{v} α, Quotient.out ∘ f ∘ ULift.down⟩⟧
#align Set.range ZFSet.range
@[simp]
theorem mem_range {α : Type u} {f : α → ZFSet.{max u v}} {x : ZFSet.{max u v}} :
x ∈ range.{u, v} f ↔ x ∈ Set.range f :=
Quotient.inductionOn x fun y => by
constructor
· rintro ⟨z, hz⟩
exact ⟨z.down, Quotient.eq_mk_iff_out.2 hz.symm⟩
· rintro ⟨z, hz⟩
use ULift.up z
simpa [hz] using PSet.Equiv.symm (Quotient.mk_out y)
#align Set.mem_range ZFSet.mem_range
@[simp]
theorem toSet_range {α : Type u} (f : α → ZFSet.{max u v}) :
(range.{u, v} f).toSet = Set.range f := by
ext
simp
#align Set.to_set_range ZFSet.toSet_range
/-- Kuratowski ordered pair -/
def pair (x y : ZFSet.{u}) : ZFSet.{u} :=
{{x}, {x, y}}
#align Set.pair ZFSet.pair
@[simp]
theorem toSet_pair (x y : ZFSet.{u}) : (pair x y).toSet = {{x}, {x, y}} := by simp [pair]
#align Set.to_set_pair ZFSet.toSet_pair
/-- A subset of pairs `{(a, b) ∈ x × y | p a b}` -/
def pairSep (p : ZFSet.{u} → ZFSet.{u} → Prop) (x y : ZFSet.{u}) : ZFSet.{u} :=
ZFSet.sep (fun z => ∃ a ∈ x, ∃ b ∈ y, z = pair a b ∧ p a b) (powerset (powerset (x ∪ y)))
#align Set.pair_sep ZFSet.pairSep
@[simp]
theorem mem_pairSep {p} {x y z : ZFSet.{u}} :
z ∈ pairSep p x y ↔ ∃ a ∈ x, ∃ b ∈ y, z = pair a b ∧ p a b := by
refine mem_sep.trans ⟨And.right, fun e => ⟨?_, e⟩⟩
rcases e with ⟨a, ax, b, bY, rfl, pab⟩
simp only [mem_powerset, subset_def, mem_union, pair, mem_pair]
rintro u (rfl | rfl) v <;> simp only [mem_singleton, mem_pair]
· rintro rfl
exact Or.inl ax
· rintro (rfl | rfl) <;> [left; right] <;> assumption
#align Set.mem_pair_sep ZFSet.mem_pairSep
theorem pair_injective : Function.Injective2 pair := fun x x' y y' H => by
have ae := ext_iff.1 H
simp only [pair, mem_pair] at ae
obtain rfl : x = x' := by
cases' (ae {x}).1 (by simp) with h h
· exact singleton_injective h
· have m : x' ∈ ({x} : ZFSet) := by simp [h]
rw [mem_singleton.mp m]
have he : x = y → y = y' := by
rintro rfl
cases' (ae {x, y'}).2 (by simp only [eq_self_iff_true, or_true_iff]) with xy'x xy'xx
· rw [eq_comm, ← mem_singleton, ← xy'x, mem_pair]
exact Or.inr rfl
· simpa [eq_comm] using (ext_iff.1 xy'xx y').1 (by simp)
obtain xyx | xyy' := (ae {x, y}).1 (by simp)
· obtain rfl := mem_singleton.mp ((ext_iff.1 xyx y).1 <| by simp)
simp [he rfl]
· obtain rfl | yy' := mem_pair.mp ((ext_iff.1 xyy' y).1 <| by simp)
· simp [he rfl]
· simp [yy']
#align Set.pair_injective ZFSet.pair_injective
@[simp]
theorem pair_inj {x y x' y' : ZFSet} : pair x y = pair x' y' ↔ x = x' ∧ y = y' :=
pair_injective.eq_iff
#align Set.pair_inj ZFSet.pair_inj
/-- The cartesian product, `{(a, b) | a ∈ x, b ∈ y}` -/
def prod : ZFSet.{u} → ZFSet.{u} → ZFSet.{u} :=
pairSep fun _ _ => True
#align Set.prod ZFSet.prod
@[simp]
| Mathlib/SetTheory/ZFC/Basic.lean | 1,305 | 1,306 | theorem mem_prod {x y z : ZFSet.{u}} : z ∈ prod x y ↔ ∃ a ∈ x, ∃ b ∈ y, z = pair a b := by |
simp [prod]
|
/-
Copyright (c) 2019 Sébastien Gouëzel. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Analysis.Calculus.FDeriv.Equiv
import Mathlib.Analysis.Calculus.FormalMultilinearSeries
#align_import analysis.calculus.cont_diff_def from "leanprover-community/mathlib"@"3a69562db5a458db8322b190ec8d9a8bbd8a5b14"
/-!
# Higher differentiability
A function is `C^1` on a domain if it is differentiable there, and its derivative is continuous.
By induction, it is `C^n` if it is `C^{n-1}` and its (n-1)-th derivative is `C^1` there or,
equivalently, if it is `C^1` and its derivative is `C^{n-1}`.
Finally, it is `C^∞` if it is `C^n` for all n.
We formalize these notions by defining iteratively the `n+1`-th derivative of a function as the
derivative of the `n`-th derivative. It is called `iteratedFDeriv 𝕜 n f x` where `𝕜` is the
field, `n` is the number of iterations, `f` is the function and `x` is the point, and it is given
as an `n`-multilinear map. We also define a version `iteratedFDerivWithin` relative to a domain,
as well as predicates `ContDiffWithinAt`, `ContDiffAt`, `ContDiffOn` and
`ContDiff` saying that the function is `C^n` within a set at a point, at a point, on a set
and on the whole space respectively.
To avoid the issue of choice when choosing a derivative in sets where the derivative is not
necessarily unique, `ContDiffOn` is not defined directly in terms of the
regularity of the specific choice `iteratedFDerivWithin 𝕜 n f s` inside `s`, but in terms of the
existence of a nice sequence of derivatives, expressed with a predicate
`HasFTaylorSeriesUpToOn`.
We prove basic properties of these notions.
## Main definitions and results
Let `f : E → F` be a map between normed vector spaces over a nontrivially normed field `𝕜`.
* `HasFTaylorSeriesUpTo n f p`: expresses that the formal multilinear series `p` is a sequence
of iterated derivatives of `f`, up to the `n`-th term (where `n` is a natural number or `∞`).
* `HasFTaylorSeriesUpToOn n f p s`: same thing, but inside a set `s`. The notion of derivative
is now taken inside `s`. In particular, derivatives don't have to be unique.
* `ContDiff 𝕜 n f`: expresses that `f` is `C^n`, i.e., it admits a Taylor series up to
rank `n`.
* `ContDiffOn 𝕜 n f s`: expresses that `f` is `C^n` in `s`.
* `ContDiffAt 𝕜 n f x`: expresses that `f` is `C^n` around `x`.
* `ContDiffWithinAt 𝕜 n f s x`: expresses that `f` is `C^n` around `x` within the set `s`.
* `iteratedFDerivWithin 𝕜 n f s x` is an `n`-th derivative of `f` over the field `𝕜` on the
set `s` at the point `x`. It is a continuous multilinear map from `E^n` to `F`, defined as a
derivative within `s` of `iteratedFDerivWithin 𝕜 (n-1) f s` if one exists, and `0` otherwise.
* `iteratedFDeriv 𝕜 n f x` is the `n`-th derivative of `f` over the field `𝕜` at the point `x`.
It is a continuous multilinear map from `E^n` to `F`, defined as a derivative of
`iteratedFDeriv 𝕜 (n-1) f` if one exists, and `0` otherwise.
In sets of unique differentiability, `ContDiffOn 𝕜 n f s` can be expressed in terms of the
properties of `iteratedFDerivWithin 𝕜 m f s` for `m ≤ n`. In the whole space,
`ContDiff 𝕜 n f` can be expressed in terms of the properties of `iteratedFDeriv 𝕜 m f`
for `m ≤ n`.
## Implementation notes
The definitions in this file are designed to work on any field `𝕜`. They are sometimes slightly more
complicated than the naive definitions one would guess from the intuition over the real or complex
numbers, but they are designed to circumvent the lack of gluing properties and partitions of unity
in general. In the usual situations, they coincide with the usual definitions.
### Definition of `C^n` functions in domains
One could define `C^n` functions in a domain `s` by fixing an arbitrary choice of derivatives (this
is what we do with `iteratedFDerivWithin`) and requiring that all these derivatives up to `n` are
continuous. If the derivative is not unique, this could lead to strange behavior like two `C^n`
functions `f` and `g` on `s` whose sum is not `C^n`. A better definition is thus to say that a
function is `C^n` inside `s` if it admits a sequence of derivatives up to `n` inside `s`.
This definition still has the problem that a function which is locally `C^n` would not need to
be `C^n`, as different choices of sequences of derivatives around different points might possibly
not be glued together to give a globally defined sequence of derivatives. (Note that this issue
can not happen over reals, thanks to partition of unity, but the behavior over a general field is
not so clear, and we want a definition for general fields). Also, there are locality
problems for the order parameter: one could image a function which, for each `n`, has a nice
sequence of derivatives up to order `n`, but they do not coincide for varying `n` and can therefore
not be glued to give rise to an infinite sequence of derivatives. This would give a function
which is `C^n` for all `n`, but not `C^∞`. We solve this issue by putting locality conditions
in space and order in our definition of `ContDiffWithinAt` and `ContDiffOn`.
The resulting definition is slightly more complicated to work with (in fact not so much), but it
gives rise to completely satisfactory theorems.
For instance, with this definition, a real function which is `C^m` (but not better) on `(-1/m, 1/m)`
for each natural `m` is by definition `C^∞` at `0`.
There is another issue with the definition of `ContDiffWithinAt 𝕜 n f s x`. We can
require the existence and good behavior of derivatives up to order `n` on a neighborhood of `x`
within `s`. However, this does not imply continuity or differentiability within `s` of the function
at `x` when `x` does not belong to `s`. Therefore, we require such existence and good behavior on
a neighborhood of `x` within `s ∪ {x}` (which appears as `insert x s` in this file).
### Side of the composition, and universe issues
With a naïve direct definition, the `n`-th derivative of a function belongs to the space
`E →L[𝕜] (E →L[𝕜] (E ... F)...)))` where there are n iterations of `E →L[𝕜]`. This space
may also be seen as the space of continuous multilinear functions on `n` copies of `E` with
values in `F`, by uncurrying. This is the point of view that is usually adopted in textbooks,
and that we also use. This means that the definition and the first proofs are slightly involved,
as one has to keep track of the uncurrying operation. The uncurrying can be done from the
left or from the right, amounting to defining the `n+1`-th derivative either as the derivative of
the `n`-th derivative, or as the `n`-th derivative of the derivative.
For proofs, it would be more convenient to use the latter approach (from the right),
as it means to prove things at the `n+1`-th step we only need to understand well enough the
derivative in `E →L[𝕜] F` (contrary to the approach from the left, where one would need to know
enough on the `n`-th derivative to deduce things on the `n+1`-th derivative).
However, the definition from the right leads to a universe polymorphism problem: if we define
`iteratedFDeriv 𝕜 (n + 1) f x = iteratedFDeriv 𝕜 n (fderiv 𝕜 f) x` by induction, we need to
generalize over all spaces (as `f` and `fderiv 𝕜 f` don't take values in the same space). It is
only possible to generalize over all spaces in some fixed universe in an inductive definition.
For `f : E → F`, then `fderiv 𝕜 f` is a map `E → (E →L[𝕜] F)`. Therefore, the definition will only
work if `F` and `E →L[𝕜] F` are in the same universe.
This issue does not appear with the definition from the left, where one does not need to generalize
over all spaces. Therefore, we use the definition from the left. This means some proofs later on
become a little bit more complicated: to prove that a function is `C^n`, the most efficient approach
is to exhibit a formula for its `n`-th derivative and prove it is continuous (contrary to the
inductive approach where one would prove smoothness statements without giving a formula for the
derivative). In the end, this approach is still satisfactory as it is good to have formulas for the
iterated derivatives in various constructions.
One point where we depart from this explicit approach is in the proof of smoothness of a
composition: there is a formula for the `n`-th derivative of a composition (Faà di Bruno's formula),
but it is very complicated and barely usable, while the inductive proof is very simple. Thus, we
give the inductive proof. As explained above, it works by generalizing over the target space, hence
it only works well if all spaces belong to the same universe. To get the general version, we lift
things to a common universe using a trick.
### Variables management
The textbook definitions and proofs use various identifications and abuse of notations, for instance
when saying that the natural space in which the derivative lives, i.e.,
`E →L[𝕜] (E →L[𝕜] ( ... →L[𝕜] F))`, is the same as a space of multilinear maps. When doing things
formally, we need to provide explicit maps for these identifications, and chase some diagrams to see
everything is compatible with the identifications. In particular, one needs to check that taking the
derivative and then doing the identification, or first doing the identification and then taking the
derivative, gives the same result. The key point for this is that taking the derivative commutes
with continuous linear equivalences. Therefore, we need to implement all our identifications with
continuous linear equivs.
## Notations
We use the notation `E [×n]→L[𝕜] F` for the space of continuous multilinear maps on `E^n` with
values in `F`. This is the space in which the `n`-th derivative of a function from `E` to `F` lives.
In this file, we denote `⊤ : ℕ∞` with `∞`.
## Tags
derivative, differentiability, higher derivative, `C^n`, multilinear, Taylor series, formal series
-/
noncomputable section
open scoped Classical
open NNReal Topology Filter
local notation "∞" => (⊤ : ℕ∞)
/-
Porting note: These lines are not required in Mathlib4.
attribute [local instance 1001]
NormedAddCommGroup.toAddCommGroup NormedSpace.toModule' AddCommGroup.toAddCommMonoid
-/
open Set Fin Filter Function
universe u uE uF uG uX
variable {𝕜 : Type u} [NontriviallyNormedField 𝕜] {E : Type uE} [NormedAddCommGroup E]
[NormedSpace 𝕜 E] {F : Type uF} [NormedAddCommGroup F] [NormedSpace 𝕜 F] {G : Type uG}
[NormedAddCommGroup G] [NormedSpace 𝕜 G] {X : Type uX} [NormedAddCommGroup X] [NormedSpace 𝕜 X]
{s s₁ t u : Set E} {f f₁ : E → F} {g : F → G} {x x₀ : E} {c : F} {m n : ℕ∞}
{p : E → FormalMultilinearSeries 𝕜 E F}
/-! ### Functions with a Taylor series on a domain -/
/-- `HasFTaylorSeriesUpToOn n f p s` registers the fact that `p 0 = f` and `p (m+1)` is a
derivative of `p m` for `m < n`, and is continuous for `m ≤ n`. This is a predicate analogous to
`HasFDerivWithinAt` but for higher order derivatives.
Notice that `p` does not sum up to `f` on the diagonal (`FormalMultilinearSeries.sum`), even if
`f` is analytic and `n = ∞`: an additional `1/m!` factor on the `m`th term is necessary for that. -/
structure HasFTaylorSeriesUpToOn (n : ℕ∞) (f : E → F) (p : E → FormalMultilinearSeries 𝕜 E F)
(s : Set E) : Prop where
zero_eq : ∀ x ∈ s, (p x 0).uncurry0 = f x
protected fderivWithin : ∀ m : ℕ, (m : ℕ∞) < n → ∀ x ∈ s,
HasFDerivWithinAt (p · m) (p x m.succ).curryLeft s x
cont : ∀ m : ℕ, (m : ℕ∞) ≤ n → ContinuousOn (p · m) s
#align has_ftaylor_series_up_to_on HasFTaylorSeriesUpToOn
theorem HasFTaylorSeriesUpToOn.zero_eq' (h : HasFTaylorSeriesUpToOn n f p s) {x : E} (hx : x ∈ s) :
p x 0 = (continuousMultilinearCurryFin0 𝕜 E F).symm (f x) := by
rw [← h.zero_eq x hx]
exact (p x 0).uncurry0_curry0.symm
#align has_ftaylor_series_up_to_on.zero_eq' HasFTaylorSeriesUpToOn.zero_eq'
/-- If two functions coincide on a set `s`, then a Taylor series for the first one is as well a
Taylor series for the second one. -/
theorem HasFTaylorSeriesUpToOn.congr (h : HasFTaylorSeriesUpToOn n f p s)
(h₁ : ∀ x ∈ s, f₁ x = f x) : HasFTaylorSeriesUpToOn n f₁ p s := by
refine ⟨fun x hx => ?_, h.fderivWithin, h.cont⟩
rw [h₁ x hx]
exact h.zero_eq x hx
#align has_ftaylor_series_up_to_on.congr HasFTaylorSeriesUpToOn.congr
theorem HasFTaylorSeriesUpToOn.mono (h : HasFTaylorSeriesUpToOn n f p s) {t : Set E} (hst : t ⊆ s) :
HasFTaylorSeriesUpToOn n f p t :=
⟨fun x hx => h.zero_eq x (hst hx), fun m hm x hx => (h.fderivWithin m hm x (hst hx)).mono hst,
fun m hm => (h.cont m hm).mono hst⟩
#align has_ftaylor_series_up_to_on.mono HasFTaylorSeriesUpToOn.mono
theorem HasFTaylorSeriesUpToOn.of_le (h : HasFTaylorSeriesUpToOn n f p s) (hmn : m ≤ n) :
HasFTaylorSeriesUpToOn m f p s :=
⟨h.zero_eq, fun k hk x hx => h.fderivWithin k (lt_of_lt_of_le hk hmn) x hx, fun k hk =>
h.cont k (le_trans hk hmn)⟩
#align has_ftaylor_series_up_to_on.of_le HasFTaylorSeriesUpToOn.of_le
theorem HasFTaylorSeriesUpToOn.continuousOn (h : HasFTaylorSeriesUpToOn n f p s) :
ContinuousOn f s := by
have := (h.cont 0 bot_le).congr fun x hx => (h.zero_eq' hx).symm
rwa [← (continuousMultilinearCurryFin0 𝕜 E F).symm.comp_continuousOn_iff]
#align has_ftaylor_series_up_to_on.continuous_on HasFTaylorSeriesUpToOn.continuousOn
theorem hasFTaylorSeriesUpToOn_zero_iff :
HasFTaylorSeriesUpToOn 0 f p s ↔ ContinuousOn f s ∧ ∀ x ∈ s, (p x 0).uncurry0 = f x := by
refine ⟨fun H => ⟨H.continuousOn, H.zero_eq⟩, fun H =>
⟨H.2, fun m hm => False.elim (not_le.2 hm bot_le), fun m hm ↦ ?_⟩⟩
obtain rfl : m = 0 := mod_cast hm.antisymm (zero_le _)
have : EqOn (p · 0) ((continuousMultilinearCurryFin0 𝕜 E F).symm ∘ f) s := fun x hx ↦
(continuousMultilinearCurryFin0 𝕜 E F).eq_symm_apply.2 (H.2 x hx)
rw [continuousOn_congr this, LinearIsometryEquiv.comp_continuousOn_iff]
exact H.1
#align has_ftaylor_series_up_to_on_zero_iff hasFTaylorSeriesUpToOn_zero_iff
theorem hasFTaylorSeriesUpToOn_top_iff :
HasFTaylorSeriesUpToOn ∞ f p s ↔ ∀ n : ℕ, HasFTaylorSeriesUpToOn n f p s := by
constructor
· intro H n; exact H.of_le le_top
· intro H
constructor
· exact (H 0).zero_eq
· intro m _
apply (H m.succ).fderivWithin m (WithTop.coe_lt_coe.2 (lt_add_one m))
· intro m _
apply (H m).cont m le_rfl
#align has_ftaylor_series_up_to_on_top_iff hasFTaylorSeriesUpToOn_top_iff
/-- In the case that `n = ∞` we don't need the continuity assumption in
`HasFTaylorSeriesUpToOn`. -/
theorem hasFTaylorSeriesUpToOn_top_iff' :
HasFTaylorSeriesUpToOn ∞ f p s ↔
(∀ x ∈ s, (p x 0).uncurry0 = f x) ∧
∀ m : ℕ, ∀ x ∈ s, HasFDerivWithinAt (fun y => p y m) (p x m.succ).curryLeft s x :=
-- Everything except for the continuity is trivial:
⟨fun h => ⟨h.1, fun m => h.2 m (WithTop.coe_lt_top m)⟩, fun h =>
⟨h.1, fun m _ => h.2 m, fun m _ x hx =>
-- The continuity follows from the existence of a derivative:
(h.2 m x hx).continuousWithinAt⟩⟩
#align has_ftaylor_series_up_to_on_top_iff' hasFTaylorSeriesUpToOn_top_iff'
/-- If a function has a Taylor series at order at least `1`, then the term of order `1` of this
series is a derivative of `f`. -/
theorem HasFTaylorSeriesUpToOn.hasFDerivWithinAt (h : HasFTaylorSeriesUpToOn n f p s) (hn : 1 ≤ n)
(hx : x ∈ s) : HasFDerivWithinAt f (continuousMultilinearCurryFin1 𝕜 E F (p x 1)) s x := by
have A : ∀ y ∈ s, f y = (continuousMultilinearCurryFin0 𝕜 E F) (p y 0) := fun y hy ↦
(h.zero_eq y hy).symm
suffices H : HasFDerivWithinAt (continuousMultilinearCurryFin0 𝕜 E F ∘ (p · 0))
(continuousMultilinearCurryFin1 𝕜 E F (p x 1)) s x from H.congr A (A x hx)
rw [LinearIsometryEquiv.comp_hasFDerivWithinAt_iff']
have : ((0 : ℕ) : ℕ∞) < n := zero_lt_one.trans_le hn
convert h.fderivWithin _ this x hx
ext y v
change (p x 1) (snoc 0 y) = (p x 1) (cons y v)
congr with i
rw [Unique.eq_default (α := Fin 1) i]
rfl
#align has_ftaylor_series_up_to_on.has_fderiv_within_at HasFTaylorSeriesUpToOn.hasFDerivWithinAt
theorem HasFTaylorSeriesUpToOn.differentiableOn (h : HasFTaylorSeriesUpToOn n f p s) (hn : 1 ≤ n) :
DifferentiableOn 𝕜 f s := fun _x hx => (h.hasFDerivWithinAt hn hx).differentiableWithinAt
#align has_ftaylor_series_up_to_on.differentiable_on HasFTaylorSeriesUpToOn.differentiableOn
/-- If a function has a Taylor series at order at least `1` on a neighborhood of `x`, then the term
of order `1` of this series is a derivative of `f` at `x`. -/
theorem HasFTaylorSeriesUpToOn.hasFDerivAt (h : HasFTaylorSeriesUpToOn n f p s) (hn : 1 ≤ n)
(hx : s ∈ 𝓝 x) : HasFDerivAt f (continuousMultilinearCurryFin1 𝕜 E F (p x 1)) x :=
(h.hasFDerivWithinAt hn (mem_of_mem_nhds hx)).hasFDerivAt hx
#align has_ftaylor_series_up_to_on.has_fderiv_at HasFTaylorSeriesUpToOn.hasFDerivAt
/-- If a function has a Taylor series at order at least `1` on a neighborhood of `x`, then
in a neighborhood of `x`, the term of order `1` of this series is a derivative of `f`. -/
theorem HasFTaylorSeriesUpToOn.eventually_hasFDerivAt (h : HasFTaylorSeriesUpToOn n f p s)
(hn : 1 ≤ n) (hx : s ∈ 𝓝 x) :
∀ᶠ y in 𝓝 x, HasFDerivAt f (continuousMultilinearCurryFin1 𝕜 E F (p y 1)) y :=
(eventually_eventually_nhds.2 hx).mono fun _y hy => h.hasFDerivAt hn hy
#align has_ftaylor_series_up_to_on.eventually_has_fderiv_at HasFTaylorSeriesUpToOn.eventually_hasFDerivAt
/-- If a function has a Taylor series at order at least `1` on a neighborhood of `x`, then
it is differentiable at `x`. -/
theorem HasFTaylorSeriesUpToOn.differentiableAt (h : HasFTaylorSeriesUpToOn n f p s) (hn : 1 ≤ n)
(hx : s ∈ 𝓝 x) : DifferentiableAt 𝕜 f x :=
(h.hasFDerivAt hn hx).differentiableAt
#align has_ftaylor_series_up_to_on.differentiable_at HasFTaylorSeriesUpToOn.differentiableAt
/-- `p` is a Taylor series of `f` up to `n+1` if and only if `p` is a Taylor series up to `n`, and
`p (n + 1)` is a derivative of `p n`. -/
theorem hasFTaylorSeriesUpToOn_succ_iff_left {n : ℕ} :
HasFTaylorSeriesUpToOn (n + 1) f p s ↔
HasFTaylorSeriesUpToOn n f p s ∧
(∀ x ∈ s, HasFDerivWithinAt (fun y => p y n) (p x n.succ).curryLeft s x) ∧
ContinuousOn (fun x => p x (n + 1)) s := by
constructor
· exact fun h ↦ ⟨h.of_le (WithTop.coe_le_coe.2 (Nat.le_succ n)),
h.fderivWithin _ (WithTop.coe_lt_coe.2 (lt_add_one n)), h.cont (n + 1) le_rfl⟩
· intro h
constructor
· exact h.1.zero_eq
· intro m hm
by_cases h' : m < n
· exact h.1.fderivWithin m (WithTop.coe_lt_coe.2 h')
· have : m = n := Nat.eq_of_lt_succ_of_not_lt (WithTop.coe_lt_coe.1 hm) h'
rw [this]
exact h.2.1
· intro m hm
by_cases h' : m ≤ n
· apply h.1.cont m (WithTop.coe_le_coe.2 h')
· have : m = n + 1 := le_antisymm (WithTop.coe_le_coe.1 hm) (not_le.1 h')
rw [this]
exact h.2.2
#align has_ftaylor_series_up_to_on_succ_iff_left hasFTaylorSeriesUpToOn_succ_iff_left
#adaptation_note
/--
After https://github.com/leanprover/lean4/pull/4119,
without `set_option maxSynthPendingDepth 2` this proof needs substantial repair.
-/
set_option maxSynthPendingDepth 2 in
-- Porting note: this was split out from `hasFTaylorSeriesUpToOn_succ_iff_right` to avoid a timeout.
theorem HasFTaylorSeriesUpToOn.shift_of_succ
{n : ℕ} (H : HasFTaylorSeriesUpToOn (n + 1 : ℕ) f p s) :
(HasFTaylorSeriesUpToOn n (fun x => continuousMultilinearCurryFin1 𝕜 E F (p x 1))
(fun x => (p x).shift)) s := by
constructor
· intro x _
rfl
· intro m (hm : (m : ℕ∞) < n) x (hx : x ∈ s)
have A : (m.succ : ℕ∞) < n.succ := by
rw [Nat.cast_lt] at hm ⊢
exact Nat.succ_lt_succ hm
change HasFDerivWithinAt ((continuousMultilinearCurryRightEquiv' 𝕜 m E F).symm ∘ (p · m.succ))
(p x m.succ.succ).curryRight.curryLeft s x
rw [((continuousMultilinearCurryRightEquiv' 𝕜 m E F).symm).comp_hasFDerivWithinAt_iff']
convert H.fderivWithin _ A x hx
ext y v
change p x (m + 2) (snoc (cons y (init v)) (v (last _))) = p x (m + 2) (cons y v)
rw [← cons_snoc_eq_snoc_cons, snoc_init_self]
· intro m (hm : (m : ℕ∞) ≤ n)
suffices A : ContinuousOn (p · (m + 1)) s from
((continuousMultilinearCurryRightEquiv' 𝕜 m E F).symm).continuous.comp_continuousOn A
refine H.cont _ ?_
rw [Nat.cast_le] at hm ⊢
exact Nat.succ_le_succ hm
/-- `p` is a Taylor series of `f` up to `n+1` if and only if `p.shift` is a Taylor series up to `n`
for `p 1`, which is a derivative of `f`. -/
theorem hasFTaylorSeriesUpToOn_succ_iff_right {n : ℕ} :
HasFTaylorSeriesUpToOn (n + 1 : ℕ) f p s ↔
(∀ x ∈ s, (p x 0).uncurry0 = f x) ∧
(∀ x ∈ s, HasFDerivWithinAt (fun y => p y 0) (p x 1).curryLeft s x) ∧
HasFTaylorSeriesUpToOn n (fun x => continuousMultilinearCurryFin1 𝕜 E F (p x 1))
(fun x => (p x).shift) s := by
constructor
· intro H
refine ⟨H.zero_eq, H.fderivWithin 0 (Nat.cast_lt.2 (Nat.succ_pos n)), ?_⟩
exact H.shift_of_succ
· rintro ⟨Hzero_eq, Hfderiv_zero, Htaylor⟩
constructor
· exact Hzero_eq
· intro m (hm : (m : ℕ∞) < n.succ) x (hx : x ∈ s)
cases' m with m
· exact Hfderiv_zero x hx
· have A : (m : ℕ∞) < n := by
rw [Nat.cast_lt] at hm ⊢
exact Nat.lt_of_succ_lt_succ hm
have :
HasFDerivWithinAt ((continuousMultilinearCurryRightEquiv' 𝕜 m E F).symm ∘ (p · m.succ))
((p x).shift m.succ).curryLeft s x := Htaylor.fderivWithin _ A x hx
rw [LinearIsometryEquiv.comp_hasFDerivWithinAt_iff'] at this
convert this
ext y v
change
(p x (Nat.succ (Nat.succ m))) (cons y v) =
(p x m.succ.succ) (snoc (cons y (init v)) (v (last _)))
rw [← cons_snoc_eq_snoc_cons, snoc_init_self]
· intro m (hm : (m : ℕ∞) ≤ n.succ)
cases' m with m
· have : DifferentiableOn 𝕜 (fun x => p x 0) s := fun x hx =>
(Hfderiv_zero x hx).differentiableWithinAt
exact this.continuousOn
· refine (continuousMultilinearCurryRightEquiv' 𝕜 m E F).symm.comp_continuousOn_iff.mp ?_
refine Htaylor.cont _ ?_
rw [Nat.cast_le] at hm ⊢
exact Nat.lt_succ_iff.mp hm
#align has_ftaylor_series_up_to_on_succ_iff_right hasFTaylorSeriesUpToOn_succ_iff_right
/-! ### Smooth functions within a set around a point -/
variable (𝕜)
/-- A function is continuously differentiable up to order `n` within a set `s` at a point `x` if
it admits continuous derivatives up to order `n` in a neighborhood of `x` in `s ∪ {x}`.
For `n = ∞`, we only require that this holds up to any finite order (where the neighborhood may
depend on the finite order we consider).
For instance, a real function which is `C^m` on `(-1/m, 1/m)` for each natural `m`, but not
better, is `C^∞` at `0` within `univ`.
-/
def ContDiffWithinAt (n : ℕ∞) (f : E → F) (s : Set E) (x : E) : Prop :=
∀ m : ℕ, (m : ℕ∞) ≤ n → ∃ u ∈ 𝓝[insert x s] x,
∃ p : E → FormalMultilinearSeries 𝕜 E F, HasFTaylorSeriesUpToOn m f p u
#align cont_diff_within_at ContDiffWithinAt
variable {𝕜}
theorem contDiffWithinAt_nat {n : ℕ} :
ContDiffWithinAt 𝕜 n f s x ↔ ∃ u ∈ 𝓝[insert x s] x,
∃ p : E → FormalMultilinearSeries 𝕜 E F, HasFTaylorSeriesUpToOn n f p u :=
⟨fun H => H n le_rfl, fun ⟨u, hu, p, hp⟩ _m hm => ⟨u, hu, p, hp.of_le hm⟩⟩
#align cont_diff_within_at_nat contDiffWithinAt_nat
theorem ContDiffWithinAt.of_le (h : ContDiffWithinAt 𝕜 n f s x) (hmn : m ≤ n) :
ContDiffWithinAt 𝕜 m f s x := fun k hk => h k (le_trans hk hmn)
#align cont_diff_within_at.of_le ContDiffWithinAt.of_le
theorem contDiffWithinAt_iff_forall_nat_le :
ContDiffWithinAt 𝕜 n f s x ↔ ∀ m : ℕ, ↑m ≤ n → ContDiffWithinAt 𝕜 m f s x :=
⟨fun H _m hm => H.of_le hm, fun H m hm => H m hm _ le_rfl⟩
#align cont_diff_within_at_iff_forall_nat_le contDiffWithinAt_iff_forall_nat_le
theorem contDiffWithinAt_top : ContDiffWithinAt 𝕜 ∞ f s x ↔ ∀ n : ℕ, ContDiffWithinAt 𝕜 n f s x :=
contDiffWithinAt_iff_forall_nat_le.trans <| by simp only [forall_prop_of_true, le_top]
#align cont_diff_within_at_top contDiffWithinAt_top
theorem ContDiffWithinAt.continuousWithinAt (h : ContDiffWithinAt 𝕜 n f s x) :
ContinuousWithinAt f s x := by
rcases h 0 bot_le with ⟨u, hu, p, H⟩
rw [mem_nhdsWithin_insert] at hu
exact (H.continuousOn.continuousWithinAt hu.1).mono_of_mem hu.2
#align cont_diff_within_at.continuous_within_at ContDiffWithinAt.continuousWithinAt
theorem ContDiffWithinAt.congr_of_eventuallyEq (h : ContDiffWithinAt 𝕜 n f s x)
(h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) : ContDiffWithinAt 𝕜 n f₁ s x := fun m hm =>
let ⟨u, hu, p, H⟩ := h m hm
⟨{ x ∈ u | f₁ x = f x }, Filter.inter_mem hu (mem_nhdsWithin_insert.2 ⟨hx, h₁⟩), p,
(H.mono (sep_subset _ _)).congr fun _ => And.right⟩
#align cont_diff_within_at.congr_of_eventually_eq ContDiffWithinAt.congr_of_eventuallyEq
theorem ContDiffWithinAt.congr_of_eventuallyEq_insert (h : ContDiffWithinAt 𝕜 n f s x)
(h₁ : f₁ =ᶠ[𝓝[insert x s] x] f) : ContDiffWithinAt 𝕜 n f₁ s x :=
h.congr_of_eventuallyEq (nhdsWithin_mono x (subset_insert x s) h₁)
(mem_of_mem_nhdsWithin (mem_insert x s) h₁ : _)
#align cont_diff_within_at.congr_of_eventually_eq_insert ContDiffWithinAt.congr_of_eventuallyEq_insert
theorem ContDiffWithinAt.congr_of_eventually_eq' (h : ContDiffWithinAt 𝕜 n f s x)
(h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : x ∈ s) : ContDiffWithinAt 𝕜 n f₁ s x :=
h.congr_of_eventuallyEq h₁ <| h₁.self_of_nhdsWithin hx
#align cont_diff_within_at.congr_of_eventually_eq' ContDiffWithinAt.congr_of_eventually_eq'
theorem Filter.EventuallyEq.contDiffWithinAt_iff (h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) :
ContDiffWithinAt 𝕜 n f₁ s x ↔ ContDiffWithinAt 𝕜 n f s x :=
⟨fun H => ContDiffWithinAt.congr_of_eventuallyEq H h₁.symm hx.symm, fun H =>
H.congr_of_eventuallyEq h₁ hx⟩
#align filter.eventually_eq.cont_diff_within_at_iff Filter.EventuallyEq.contDiffWithinAt_iff
theorem ContDiffWithinAt.congr (h : ContDiffWithinAt 𝕜 n f s x) (h₁ : ∀ y ∈ s, f₁ y = f y)
(hx : f₁ x = f x) : ContDiffWithinAt 𝕜 n f₁ s x :=
h.congr_of_eventuallyEq (Filter.eventuallyEq_of_mem self_mem_nhdsWithin h₁) hx
#align cont_diff_within_at.congr ContDiffWithinAt.congr
theorem ContDiffWithinAt.congr' (h : ContDiffWithinAt 𝕜 n f s x) (h₁ : ∀ y ∈ s, f₁ y = f y)
(hx : x ∈ s) : ContDiffWithinAt 𝕜 n f₁ s x :=
h.congr h₁ (h₁ _ hx)
#align cont_diff_within_at.congr' ContDiffWithinAt.congr'
| Mathlib/Analysis/Calculus/ContDiff/Defs.lean | 490 | 494 | theorem ContDiffWithinAt.mono_of_mem (h : ContDiffWithinAt 𝕜 n f s x) {t : Set E}
(hst : s ∈ 𝓝[t] x) : ContDiffWithinAt 𝕜 n f t x := by |
intro m hm
rcases h m hm with ⟨u, hu, p, H⟩
exact ⟨u, nhdsWithin_le_of_mem (insert_mem_nhdsWithin_insert hst) hu, p, H⟩
|
/-
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, Floris van Doorn
-/
import Mathlib.Data.Fintype.BigOperators
import Mathlib.Data.Finsupp.Defs
import Mathlib.Data.Nat.Cast.Order
import Mathlib.Data.Set.Countable
import Mathlib.Logic.Small.Set
import Mathlib.Order.SuccPred.CompleteLinearOrder
import Mathlib.SetTheory.Cardinal.SchroederBernstein
#align_import set_theory.cardinal.basic from "leanprover-community/mathlib"@"3ff3f2d6a3118b8711063de7111a0d77a53219a8"
/-!
# Cardinal Numbers
We define cardinal numbers as a quotient of types under the equivalence relation of equinumerity.
## Main definitions
* `Cardinal` is the type of cardinal numbers (in a given universe).
* `Cardinal.mk α` or `#α` is the cardinality of `α`. The notation `#` lives in the locale
`Cardinal`.
* Addition `c₁ + c₂` is defined by `Cardinal.add_def α β : #α + #β = #(α ⊕ β)`.
* Multiplication `c₁ * c₂` is defined by `Cardinal.mul_def : #α * #β = #(α × β)`.
* The order `c₁ ≤ c₂` is defined by `Cardinal.le_def α β : #α ≤ #β ↔ Nonempty (α ↪ β)`.
* Exponentiation `c₁ ^ c₂` is defined by `Cardinal.power_def α β : #α ^ #β = #(β → α)`.
* `Cardinal.isLimit c` means that `c` is a (weak) limit cardinal: `c ≠ 0 ∧ ∀ x < c, succ x < c`.
* `Cardinal.aleph0` or `ℵ₀` is the cardinality of `ℕ`. This definition is universe polymorphic:
`Cardinal.aleph0.{u} : Cardinal.{u}` (contrast with `ℕ : Type`, which lives in a specific
universe). In some cases the universe level has to be given explicitly.
* `Cardinal.sum` is the sum of an indexed family of cardinals, i.e. the cardinality of the
corresponding sigma type.
* `Cardinal.prod` is the product of an indexed family of cardinals, i.e. the cardinality of the
corresponding pi type.
* `Cardinal.powerlt a b` or `a ^< b` is defined as the supremum of `a ^ c` for `c < b`.
## Main instances
* Cardinals form a `CanonicallyOrderedCommSemiring` with the aforementioned sum and product.
* Cardinals form a `SuccOrder`. Use `Order.succ c` for the smallest cardinal greater than `c`.
* The less than relation on cardinals forms a well-order.
* Cardinals form a `ConditionallyCompleteLinearOrderBot`. Bounded sets for cardinals in universe
`u` are precisely the sets indexed by some type in universe `u`, see
`Cardinal.bddAbove_iff_small`. One can use `sSup` for the cardinal supremum, and `sInf` for the
minimum of a set of cardinals.
## Main Statements
* Cantor's theorem: `Cardinal.cantor c : c < 2 ^ c`.
* König's theorem: `Cardinal.sum_lt_prod`
## Implementation notes
* There is a type of cardinal numbers in every universe level:
`Cardinal.{u} : Type (u + 1)` is the quotient of types in `Type u`.
The operation `Cardinal.lift` lifts cardinal numbers to a higher level.
* Cardinal arithmetic specifically for infinite cardinals (like `κ * κ = κ`) is in the file
`Mathlib/SetTheory/Cardinal/Ordinal.lean`.
* There is an instance `Pow Cardinal`, but this will only fire if Lean already knows that both
the base and the exponent live in the same universe. As a workaround, you can add
```
local infixr:80 " ^' " => @HPow.hPow Cardinal Cardinal Cardinal _
```
to a file. This notation will work even if Lean doesn't know yet that the base and the exponent
live in the same universe (but no exponents in other types can be used).
(Porting note: This last point might need to be updated.)
## References
* <https://en.wikipedia.org/wiki/Cardinal_number>
## Tags
cardinal number, cardinal arithmetic, cardinal exponentiation, aleph,
Cantor's theorem, König's theorem, Konig's theorem
-/
assert_not_exists Field
assert_not_exists Module
open scoped Classical
open Function Set Order
noncomputable section
universe u v w
variable {α β : Type u}
/-- The equivalence relation on types given by equivalence (bijective correspondence) of types.
Quotienting by this equivalence relation gives the cardinal numbers.
-/
instance Cardinal.isEquivalent : Setoid (Type u) where
r α β := Nonempty (α ≃ β)
iseqv := ⟨
fun α => ⟨Equiv.refl α⟩,
fun ⟨e⟩ => ⟨e.symm⟩,
fun ⟨e₁⟩ ⟨e₂⟩ => ⟨e₁.trans e₂⟩⟩
#align cardinal.is_equivalent Cardinal.isEquivalent
/-- `Cardinal.{u}` is the type of cardinal numbers in `Type u`,
defined as the quotient of `Type u` by existence of an equivalence
(a bijection with explicit inverse). -/
@[pp_with_univ]
def Cardinal : Type (u + 1) :=
Quotient Cardinal.isEquivalent
#align cardinal Cardinal
namespace Cardinal
/-- The cardinal number of a type -/
def mk : Type u → Cardinal :=
Quotient.mk'
#align cardinal.mk Cardinal.mk
@[inherit_doc]
scoped prefix:max "#" => Cardinal.mk
instance canLiftCardinalType : CanLift Cardinal.{u} (Type u) mk fun _ => True :=
⟨fun c _ => Quot.inductionOn c fun α => ⟨α, rfl⟩⟩
#align cardinal.can_lift_cardinal_Type Cardinal.canLiftCardinalType
@[elab_as_elim]
theorem inductionOn {p : Cardinal → Prop} (c : Cardinal) (h : ∀ α, p #α) : p c :=
Quotient.inductionOn c h
#align cardinal.induction_on Cardinal.inductionOn
@[elab_as_elim]
theorem inductionOn₂ {p : Cardinal → Cardinal → Prop} (c₁ : Cardinal) (c₂ : Cardinal)
(h : ∀ α β, p #α #β) : p c₁ c₂ :=
Quotient.inductionOn₂ c₁ c₂ h
#align cardinal.induction_on₂ Cardinal.inductionOn₂
@[elab_as_elim]
theorem inductionOn₃ {p : Cardinal → Cardinal → Cardinal → Prop} (c₁ : Cardinal) (c₂ : Cardinal)
(c₃ : Cardinal) (h : ∀ α β γ, p #α #β #γ) : p c₁ c₂ c₃ :=
Quotient.inductionOn₃ c₁ c₂ c₃ h
#align cardinal.induction_on₃ Cardinal.inductionOn₃
protected theorem eq : #α = #β ↔ Nonempty (α ≃ β) :=
Quotient.eq'
#align cardinal.eq Cardinal.eq
@[simp]
theorem mk'_def (α : Type u) : @Eq Cardinal ⟦α⟧ #α :=
rfl
#align cardinal.mk_def Cardinal.mk'_def
@[simp]
theorem mk_out (c : Cardinal) : #c.out = c :=
Quotient.out_eq _
#align cardinal.mk_out Cardinal.mk_out
/-- The representative of the cardinal of a type is equivalent to the original type. -/
def outMkEquiv {α : Type v} : (#α).out ≃ α :=
Nonempty.some <| Cardinal.eq.mp (by simp)
#align cardinal.out_mk_equiv Cardinal.outMkEquiv
theorem mk_congr (e : α ≃ β) : #α = #β :=
Quot.sound ⟨e⟩
#align cardinal.mk_congr Cardinal.mk_congr
alias _root_.Equiv.cardinal_eq := mk_congr
#align equiv.cardinal_eq Equiv.cardinal_eq
/-- Lift a function between `Type*`s to a function between `Cardinal`s. -/
def map (f : Type u → Type v) (hf : ∀ α β, α ≃ β → f α ≃ f β) : Cardinal.{u} → Cardinal.{v} :=
Quotient.map f fun α β ⟨e⟩ => ⟨hf α β e⟩
#align cardinal.map Cardinal.map
@[simp]
theorem map_mk (f : Type u → Type v) (hf : ∀ α β, α ≃ β → f α ≃ f β) (α : Type u) :
map f hf #α = #(f α) :=
rfl
#align cardinal.map_mk Cardinal.map_mk
/-- Lift a binary operation `Type* → Type* → Type*` to a binary operation on `Cardinal`s. -/
def map₂ (f : Type u → Type v → Type w) (hf : ∀ α β γ δ, α ≃ β → γ ≃ δ → f α γ ≃ f β δ) :
Cardinal.{u} → Cardinal.{v} → Cardinal.{w} :=
Quotient.map₂ f fun α β ⟨e₁⟩ γ δ ⟨e₂⟩ => ⟨hf α β γ δ e₁ e₂⟩
#align cardinal.map₂ Cardinal.map₂
/-- The universe lift operation on cardinals. You can specify the universes explicitly with
`lift.{u v} : Cardinal.{v} → Cardinal.{max v u}` -/
@[pp_with_univ]
def lift (c : Cardinal.{v}) : Cardinal.{max v u} :=
map ULift.{u, v} (fun _ _ e => Equiv.ulift.trans <| e.trans Equiv.ulift.symm) c
#align cardinal.lift Cardinal.lift
@[simp]
theorem mk_uLift (α) : #(ULift.{v, u} α) = lift.{v} #α :=
rfl
#align cardinal.mk_ulift Cardinal.mk_uLift
-- Porting note: simpNF is not happy with universe levels, but this is needed as simp lemma
-- further down in this file
/-- `lift.{max u v, u}` equals `lift.{v, u}`. -/
@[simp, nolint simpNF]
theorem lift_umax : lift.{max u v, u} = lift.{v, u} :=
funext fun a => inductionOn a fun _ => (Equiv.ulift.trans Equiv.ulift.symm).cardinal_eq
#align cardinal.lift_umax Cardinal.lift_umax
-- Porting note: simpNF is not happy with universe levels, but this is needed as simp lemma
-- further down in this file
/-- `lift.{max v u, u}` equals `lift.{v, u}`. -/
@[simp, nolint simpNF]
theorem lift_umax' : lift.{max v u, u} = lift.{v, u} :=
lift_umax
#align cardinal.lift_umax' Cardinal.lift_umax'
-- Porting note: simpNF is not happy with universe levels, but this is needed as simp lemma
-- further down in this file
/-- A cardinal lifted to a lower or equal universe equals itself. -/
@[simp, nolint simpNF]
theorem lift_id' (a : Cardinal.{max u v}) : lift.{u} a = a :=
inductionOn a fun _ => mk_congr Equiv.ulift
#align cardinal.lift_id' Cardinal.lift_id'
/-- A cardinal lifted to the same universe equals itself. -/
@[simp]
theorem lift_id (a : Cardinal) : lift.{u, u} a = a :=
lift_id'.{u, u} a
#align cardinal.lift_id Cardinal.lift_id
/-- A cardinal lifted to the zero universe equals itself. -/
-- porting note (#10618): simp can prove this
-- @[simp]
theorem lift_uzero (a : Cardinal.{u}) : lift.{0} a = a :=
lift_id'.{0, u} a
#align cardinal.lift_uzero Cardinal.lift_uzero
@[simp]
theorem lift_lift.{u_1} (a : Cardinal.{u_1}) : lift.{w} (lift.{v} a) = lift.{max v w} a :=
inductionOn a fun _ => (Equiv.ulift.trans <| Equiv.ulift.trans Equiv.ulift.symm).cardinal_eq
#align cardinal.lift_lift Cardinal.lift_lift
/-- We define the order on cardinal numbers by `#α ≤ #β` if and only if
there exists an embedding (injective function) from α to β. -/
instance : LE Cardinal.{u} :=
⟨fun q₁ q₂ =>
Quotient.liftOn₂ q₁ q₂ (fun α β => Nonempty <| α ↪ β) fun _ _ _ _ ⟨e₁⟩ ⟨e₂⟩ =>
propext ⟨fun ⟨e⟩ => ⟨e.congr e₁ e₂⟩, fun ⟨e⟩ => ⟨e.congr e₁.symm e₂.symm⟩⟩⟩
instance partialOrder : PartialOrder Cardinal.{u} where
le := (· ≤ ·)
le_refl := by
rintro ⟨α⟩
exact ⟨Embedding.refl _⟩
le_trans := by
rintro ⟨α⟩ ⟨β⟩ ⟨γ⟩ ⟨e₁⟩ ⟨e₂⟩
exact ⟨e₁.trans e₂⟩
le_antisymm := by
rintro ⟨α⟩ ⟨β⟩ ⟨e₁⟩ ⟨e₂⟩
exact Quotient.sound (e₁.antisymm e₂)
instance linearOrder : LinearOrder Cardinal.{u} :=
{ Cardinal.partialOrder with
le_total := by
rintro ⟨α⟩ ⟨β⟩
apply Embedding.total
decidableLE := Classical.decRel _ }
theorem le_def (α β : Type u) : #α ≤ #β ↔ Nonempty (α ↪ β) :=
Iff.rfl
#align cardinal.le_def Cardinal.le_def
theorem mk_le_of_injective {α β : Type u} {f : α → β} (hf : Injective f) : #α ≤ #β :=
⟨⟨f, hf⟩⟩
#align cardinal.mk_le_of_injective Cardinal.mk_le_of_injective
theorem _root_.Function.Embedding.cardinal_le {α β : Type u} (f : α ↪ β) : #α ≤ #β :=
⟨f⟩
#align function.embedding.cardinal_le Function.Embedding.cardinal_le
theorem mk_le_of_surjective {α β : Type u} {f : α → β} (hf : Surjective f) : #β ≤ #α :=
⟨Embedding.ofSurjective f hf⟩
#align cardinal.mk_le_of_surjective Cardinal.mk_le_of_surjective
theorem le_mk_iff_exists_set {c : Cardinal} {α : Type u} : c ≤ #α ↔ ∃ p : Set α, #p = c :=
⟨inductionOn c fun _ ⟨⟨f, hf⟩⟩ => ⟨Set.range f, (Equiv.ofInjective f hf).cardinal_eq.symm⟩,
fun ⟨_, e⟩ => e ▸ ⟨⟨Subtype.val, fun _ _ => Subtype.eq⟩⟩⟩
#align cardinal.le_mk_iff_exists_set Cardinal.le_mk_iff_exists_set
theorem mk_subtype_le {α : Type u} (p : α → Prop) : #(Subtype p) ≤ #α :=
⟨Embedding.subtype p⟩
#align cardinal.mk_subtype_le Cardinal.mk_subtype_le
theorem mk_set_le (s : Set α) : #s ≤ #α :=
mk_subtype_le s
#align cardinal.mk_set_le Cardinal.mk_set_le
@[simp]
lemma mk_preimage_down {s : Set α} : #(ULift.down.{v} ⁻¹' s) = lift.{v} (#s) := by
rw [← mk_uLift, Cardinal.eq]
constructor
let f : ULift.down ⁻¹' s → ULift s := fun x ↦ ULift.up (restrictPreimage s ULift.down x)
have : Function.Bijective f :=
ULift.up_bijective.comp (restrictPreimage_bijective _ (ULift.down_bijective))
exact Equiv.ofBijective f this
theorem out_embedding {c c' : Cardinal} : c ≤ c' ↔ Nonempty (c.out ↪ c'.out) := by
trans
· rw [← Quotient.out_eq c, ← Quotient.out_eq c']
· rw [mk'_def, mk'_def, le_def]
#align cardinal.out_embedding Cardinal.out_embedding
theorem lift_mk_le {α : Type v} {β : Type w} :
lift.{max u w} #α ≤ lift.{max u v} #β ↔ Nonempty (α ↪ β) :=
⟨fun ⟨f⟩ => ⟨Embedding.congr Equiv.ulift Equiv.ulift f⟩, fun ⟨f⟩ =>
⟨Embedding.congr Equiv.ulift.symm Equiv.ulift.symm f⟩⟩
#align cardinal.lift_mk_le Cardinal.lift_mk_le
/-- A variant of `Cardinal.lift_mk_le` with specialized universes.
Because Lean often can not realize it should use this specialization itself,
we provide this statement separately so you don't have to solve the specialization problem either.
-/
theorem lift_mk_le' {α : Type u} {β : Type v} : lift.{v} #α ≤ lift.{u} #β ↔ Nonempty (α ↪ β) :=
lift_mk_le.{0}
#align cardinal.lift_mk_le' Cardinal.lift_mk_le'
theorem lift_mk_eq {α : Type u} {β : Type v} :
lift.{max v w} #α = lift.{max u w} #β ↔ Nonempty (α ≃ β) :=
Quotient.eq'.trans
⟨fun ⟨f⟩ => ⟨Equiv.ulift.symm.trans <| f.trans Equiv.ulift⟩, fun ⟨f⟩ =>
⟨Equiv.ulift.trans <| f.trans Equiv.ulift.symm⟩⟩
#align cardinal.lift_mk_eq Cardinal.lift_mk_eq
/-- A variant of `Cardinal.lift_mk_eq` with specialized universes.
Because Lean often can not realize it should use this specialization itself,
we provide this statement separately so you don't have to solve the specialization problem either.
-/
theorem lift_mk_eq' {α : Type u} {β : Type v} : lift.{v} #α = lift.{u} #β ↔ Nonempty (α ≃ β) :=
lift_mk_eq.{u, v, 0}
#align cardinal.lift_mk_eq' Cardinal.lift_mk_eq'
@[simp]
theorem lift_le {a b : Cardinal.{v}} : lift.{u, v} a ≤ lift.{u, v} b ↔ a ≤ b :=
inductionOn₂ a b fun α β => by
rw [← lift_umax]
exact lift_mk_le.{u}
#align cardinal.lift_le Cardinal.lift_le
-- Porting note: changed `simps` to `simps!` because the linter told to do so.
/-- `Cardinal.lift` as an `OrderEmbedding`. -/
@[simps! (config := .asFn)]
def liftOrderEmbedding : Cardinal.{v} ↪o Cardinal.{max v u} :=
OrderEmbedding.ofMapLEIff lift.{u, v} fun _ _ => lift_le
#align cardinal.lift_order_embedding Cardinal.liftOrderEmbedding
theorem lift_injective : Injective lift.{u, v} :=
liftOrderEmbedding.injective
#align cardinal.lift_injective Cardinal.lift_injective
@[simp]
theorem lift_inj {a b : Cardinal.{u}} : lift.{v, u} a = lift.{v, u} b ↔ a = b :=
lift_injective.eq_iff
#align cardinal.lift_inj Cardinal.lift_inj
@[simp]
theorem lift_lt {a b : Cardinal.{u}} : lift.{v, u} a < lift.{v, u} b ↔ a < b :=
liftOrderEmbedding.lt_iff_lt
#align cardinal.lift_lt Cardinal.lift_lt
theorem lift_strictMono : StrictMono lift := fun _ _ => lift_lt.2
#align cardinal.lift_strict_mono Cardinal.lift_strictMono
theorem lift_monotone : Monotone lift :=
lift_strictMono.monotone
#align cardinal.lift_monotone Cardinal.lift_monotone
instance : Zero Cardinal.{u} :=
-- `PEmpty` might be more canonical, but this is convenient for defeq with natCast
⟨lift #(Fin 0)⟩
instance : Inhabited Cardinal.{u} :=
⟨0⟩
@[simp]
theorem mk_eq_zero (α : Type u) [IsEmpty α] : #α = 0 :=
(Equiv.equivOfIsEmpty α (ULift (Fin 0))).cardinal_eq
#align cardinal.mk_eq_zero Cardinal.mk_eq_zero
@[simp]
theorem lift_zero : lift 0 = 0 := mk_eq_zero _
#align cardinal.lift_zero Cardinal.lift_zero
@[simp]
theorem lift_eq_zero {a : Cardinal.{v}} : lift.{u} a = 0 ↔ a = 0 :=
lift_injective.eq_iff' lift_zero
#align cardinal.lift_eq_zero Cardinal.lift_eq_zero
theorem mk_eq_zero_iff {α : Type u} : #α = 0 ↔ IsEmpty α :=
⟨fun e =>
let ⟨h⟩ := Quotient.exact e
h.isEmpty,
@mk_eq_zero α⟩
#align cardinal.mk_eq_zero_iff Cardinal.mk_eq_zero_iff
theorem mk_ne_zero_iff {α : Type u} : #α ≠ 0 ↔ Nonempty α :=
(not_iff_not.2 mk_eq_zero_iff).trans not_isEmpty_iff
#align cardinal.mk_ne_zero_iff Cardinal.mk_ne_zero_iff
@[simp]
theorem mk_ne_zero (α : Type u) [Nonempty α] : #α ≠ 0 :=
mk_ne_zero_iff.2 ‹_›
#align cardinal.mk_ne_zero Cardinal.mk_ne_zero
instance : One Cardinal.{u} :=
-- `PUnit` might be more canonical, but this is convenient for defeq with natCast
⟨lift #(Fin 1)⟩
instance : Nontrivial Cardinal.{u} :=
⟨⟨1, 0, mk_ne_zero _⟩⟩
theorem mk_eq_one (α : Type u) [Unique α] : #α = 1 :=
(Equiv.equivOfUnique α (ULift (Fin 1))).cardinal_eq
#align cardinal.mk_eq_one Cardinal.mk_eq_one
theorem le_one_iff_subsingleton {α : Type u} : #α ≤ 1 ↔ Subsingleton α :=
⟨fun ⟨f⟩ => ⟨fun _ _ => f.injective (Subsingleton.elim _ _)⟩, fun ⟨h⟩ =>
⟨fun _ => ULift.up 0, fun _ _ _ => h _ _⟩⟩
#align cardinal.le_one_iff_subsingleton Cardinal.le_one_iff_subsingleton
@[simp]
theorem mk_le_one_iff_set_subsingleton {s : Set α} : #s ≤ 1 ↔ s.Subsingleton :=
le_one_iff_subsingleton.trans s.subsingleton_coe
#align cardinal.mk_le_one_iff_set_subsingleton Cardinal.mk_le_one_iff_set_subsingleton
alias ⟨_, _root_.Set.Subsingleton.cardinal_mk_le_one⟩ := mk_le_one_iff_set_subsingleton
#align set.subsingleton.cardinal_mk_le_one Set.Subsingleton.cardinal_mk_le_one
instance : Add Cardinal.{u} :=
⟨map₂ Sum fun _ _ _ _ => Equiv.sumCongr⟩
theorem add_def (α β : Type u) : #α + #β = #(Sum α β) :=
rfl
#align cardinal.add_def Cardinal.add_def
instance : NatCast Cardinal.{u} :=
⟨fun n => lift #(Fin n)⟩
@[simp]
theorem mk_sum (α : Type u) (β : Type v) : #(α ⊕ β) = lift.{v, u} #α + lift.{u, v} #β :=
mk_congr (Equiv.ulift.symm.sumCongr Equiv.ulift.symm)
#align cardinal.mk_sum Cardinal.mk_sum
@[simp]
theorem mk_option {α : Type u} : #(Option α) = #α + 1 := by
rw [(Equiv.optionEquivSumPUnit.{u, u} α).cardinal_eq, mk_sum, mk_eq_one PUnit, lift_id, lift_id]
#align cardinal.mk_option Cardinal.mk_option
@[simp]
theorem mk_psum (α : Type u) (β : Type v) : #(PSum α β) = lift.{v} #α + lift.{u} #β :=
(mk_congr (Equiv.psumEquivSum α β)).trans (mk_sum α β)
#align cardinal.mk_psum Cardinal.mk_psum
@[simp]
theorem mk_fintype (α : Type u) [h : Fintype α] : #α = Fintype.card α :=
mk_congr (Fintype.equivOfCardEq (by simp))
protected theorem cast_succ (n : ℕ) : ((n + 1 : ℕ) : Cardinal.{u}) = n + 1 := by
change #(ULift.{u} (Fin (n+1))) = # (ULift.{u} (Fin n)) + 1
rw [← mk_option, mk_fintype, mk_fintype]
simp only [Fintype.card_ulift, Fintype.card_fin, Fintype.card_option]
instance : Mul Cardinal.{u} :=
⟨map₂ Prod fun _ _ _ _ => Equiv.prodCongr⟩
theorem mul_def (α β : Type u) : #α * #β = #(α × β) :=
rfl
#align cardinal.mul_def Cardinal.mul_def
@[simp]
theorem mk_prod (α : Type u) (β : Type v) : #(α × β) = lift.{v, u} #α * lift.{u, v} #β :=
mk_congr (Equiv.ulift.symm.prodCongr Equiv.ulift.symm)
#align cardinal.mk_prod Cardinal.mk_prod
private theorem mul_comm' (a b : Cardinal.{u}) : a * b = b * a :=
inductionOn₂ a b fun α β => mk_congr <| Equiv.prodComm α β
/-- The cardinal exponential. `#α ^ #β` is the cardinal of `β → α`. -/
instance instPowCardinal : Pow Cardinal.{u} Cardinal.{u} :=
⟨map₂ (fun α β => β → α) fun _ _ _ _ e₁ e₂ => e₂.arrowCongr e₁⟩
theorem power_def (α β : Type u) : #α ^ #β = #(β → α) :=
rfl
#align cardinal.power_def Cardinal.power_def
theorem mk_arrow (α : Type u) (β : Type v) : #(α → β) = (lift.{u} #β^lift.{v} #α) :=
mk_congr (Equiv.ulift.symm.arrowCongr Equiv.ulift.symm)
#align cardinal.mk_arrow Cardinal.mk_arrow
@[simp]
theorem lift_power (a b : Cardinal.{u}) : lift.{v} (a ^ b) = lift.{v} a ^ lift.{v} b :=
inductionOn₂ a b fun _ _ =>
mk_congr <| Equiv.ulift.trans (Equiv.ulift.arrowCongr Equiv.ulift).symm
#align cardinal.lift_power Cardinal.lift_power
@[simp]
theorem power_zero {a : Cardinal} : a ^ (0 : Cardinal) = 1 :=
inductionOn a fun _ => mk_eq_one _
#align cardinal.power_zero Cardinal.power_zero
@[simp]
theorem power_one {a : Cardinal.{u}} : a ^ (1 : Cardinal) = a :=
inductionOn a fun α => mk_congr (Equiv.funUnique (ULift.{u} (Fin 1)) α)
#align cardinal.power_one Cardinal.power_one
theorem power_add {a b c : Cardinal} : a ^ (b + c) = a ^ b * a ^ c :=
inductionOn₃ a b c fun α β γ => mk_congr <| Equiv.sumArrowEquivProdArrow β γ α
#align cardinal.power_add Cardinal.power_add
instance commSemiring : CommSemiring Cardinal.{u} where
zero := 0
one := 1
add := (· + ·)
mul := (· * ·)
zero_add a := inductionOn a fun α => mk_congr <| Equiv.emptySum (ULift (Fin 0)) α
add_zero a := inductionOn a fun α => mk_congr <| Equiv.sumEmpty α (ULift (Fin 0))
add_assoc a b c := inductionOn₃ a b c fun α β γ => mk_congr <| Equiv.sumAssoc α β γ
add_comm a b := inductionOn₂ a b fun α β => mk_congr <| Equiv.sumComm α β
zero_mul a := inductionOn a fun α => mk_eq_zero _
mul_zero a := inductionOn a fun α => mk_eq_zero _
one_mul a := inductionOn a fun α => mk_congr <| Equiv.uniqueProd α (ULift (Fin 1))
mul_one a := inductionOn a fun α => mk_congr <| Equiv.prodUnique α (ULift (Fin 1))
mul_assoc a b c := inductionOn₃ a b c fun α β γ => mk_congr <| Equiv.prodAssoc α β γ
mul_comm := mul_comm'
left_distrib a b c := inductionOn₃ a b c fun α β γ => mk_congr <| Equiv.prodSumDistrib α β γ
right_distrib a b c := inductionOn₃ a b c fun α β γ => mk_congr <| Equiv.sumProdDistrib α β γ
nsmul := nsmulRec
npow n c := c ^ (n : Cardinal)
npow_zero := @power_zero
npow_succ n c := show c ^ (↑(n + 1) : Cardinal) = c ^ (↑n : Cardinal) * c
by rw [Cardinal.cast_succ, power_add, power_one, mul_comm']
natCast := (fun n => lift.{u} #(Fin n) : ℕ → Cardinal.{u})
natCast_zero := rfl
natCast_succ := Cardinal.cast_succ
/-! Porting note (#11229): Deprecated section. Remove. -/
section deprecated
set_option linter.deprecated false
@[deprecated (since := "2023-02-11")]
theorem power_bit0 (a b : Cardinal) : a ^ bit0 b = a ^ b * a ^ b :=
power_add
#align cardinal.power_bit0 Cardinal.power_bit0
@[deprecated (since := "2023-02-11")]
| Mathlib/SetTheory/Cardinal/Basic.lean | 552 | 553 | theorem power_bit1 (a b : Cardinal) : a ^ bit1 b = a ^ b * a ^ b * a := by |
rw [bit1, ← power_bit0, power_add, power_one]
|
/-
Copyright (c) 2022 Kevin H. Wilson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kevin H. Wilson
-/
import Mathlib.Analysis.Calculus.MeanValue
import Mathlib.Analysis.NormedSpace.RCLike
import Mathlib.Order.Filter.Curry
#align_import analysis.calculus.uniform_limits_deriv from "leanprover-community/mathlib"@"3f655f5297b030a87d641ad4e825af8d9679eb0b"
/-!
# Swapping limits and derivatives via uniform convergence
The purpose of this file is to prove that the derivative of the pointwise limit of a sequence of
functions is the pointwise limit of the functions' derivatives when the derivatives converge
_uniformly_. The formal statement appears as `hasFDerivAt_of_tendstoLocallyUniformlyOn`.
## Main statements
* `uniformCauchySeqOnFilter_of_fderiv`: If
1. `f : ℕ → E → G` is a sequence of functions which have derivatives
`f' : ℕ → E → (E →L[𝕜] G)` on a neighborhood of `x`,
2. the functions `f` converge at `x`, and
3. the derivatives `f'` form a Cauchy sequence uniformly on a neighborhood of `x`,
then the `f` form a Cauchy sequence _uniformly_ on a neighborhood of `x`
* `hasFDerivAt_of_tendstoUniformlyOnFilter` : Suppose (1), (2), and (3) above are true. Let
`g` (resp. `g'`) be the limiting function of the `f` (resp. `g'`). Then `f'` is the derivative of
`g` on a neighborhood of `x`
* `hasFDerivAt_of_tendstoUniformlyOn`: An often-easier-to-use version of the above theorem when
*all* the derivatives exist and functions converge on a common open set and the derivatives
converge uniformly there.
Each of the above statements also has variations that support `deriv` instead of `fderiv`.
## Implementation notes
Our technique for proving the main result is the famous "`ε / 3` proof." In words, you can find it
explained, for instance, at [this StackExchange post](https://math.stackexchange.com/questions/214218/uniform-convergence-of-derivatives-tao-14-2-7).
The subtlety is that we want to prove that the difference quotients of the `g` converge to the `g'`.
That is, we want to prove something like:
```
∀ ε > 0, ∃ δ > 0, ∀ y ∈ B_δ(x), |y - x|⁻¹ * |(g y - g x) - g' x (y - x)| < ε.
```
To do so, we will need to introduce a pair of quantifiers
```lean
∀ ε > 0, ∃ N, ∀ n ≥ N, ∃ δ > 0, ∀ y ∈ B_δ(x), |y - x|⁻¹ * |(g y - g x) - g' x (y - x)| < ε.
```
So how do we write this in terms of filters? Well, the initial definition of the derivative is
```lean
tendsto (|y - x|⁻¹ * |(g y - g x) - g' x (y - x)|) (𝓝 x) (𝓝 0)
```
There are two ways we might introduce `n`. We could do:
```lean
∀ᶠ (n : ℕ) in atTop, Tendsto (|y - x|⁻¹ * |(g y - g x) - g' x (y - x)|) (𝓝 x) (𝓝 0)
```
but this is equivalent to the quantifier order `∃ N, ∀ n ≥ N, ∀ ε > 0, ∃ δ > 0, ∀ y ∈ B_δ(x)`,
which _implies_ our desired `∀ ∃ ∀ ∃ ∀` but is _not_ equivalent to it. On the other hand, we might
try
```lean
Tendsto (|y - x|⁻¹ * |(g y - g x) - g' x (y - x)|) (atTop ×ˢ 𝓝 x) (𝓝 0)
```
but this is equivalent to the quantifier order `∀ ε > 0, ∃ N, ∃ δ > 0, ∀ n ≥ N, ∀ y ∈ B_δ(x)`, which
again _implies_ our desired `∀ ∃ ∀ ∃ ∀` but is not equivalent to it.
So to get the quantifier order we want, we need to introduce a new filter construction, which we
call a "curried filter"
```lean
Tendsto (|y - x|⁻¹ * |(g y - g x) - g' x (y - x)|) (atTop.curry (𝓝 x)) (𝓝 0)
```
Then the above implications are `Filter.Tendsto.curry` and
`Filter.Tendsto.mono_left Filter.curry_le_prod`. We will use both of these deductions as part of
our proof.
We note that if you loosen the assumptions of the main theorem then the proof becomes quite a bit
easier. In particular, if you assume there is a common neighborhood `s` where all of the three
assumptions of `hasFDerivAt_of_tendstoUniformlyOnFilter` hold and that the `f'` are
continuous, then you can avoid the mean value theorem and much of the work around curried filters.
## Tags
uniform convergence, limits of derivatives
-/
open Filter
open scoped uniformity Filter Topology
section LimitsOfDerivatives
variable {ι : Type*} {l : Filter ι} {E : Type*} [NormedAddCommGroup E] {𝕜 : Type*} [RCLike 𝕜]
[NormedSpace 𝕜 E] {G : Type*} [NormedAddCommGroup G] [NormedSpace 𝕜 G] {f : ι → E → G}
{g : E → G} {f' : ι → E → E →L[𝕜] G} {g' : E → E →L[𝕜] G} {x : E}
/-- If a sequence of functions real or complex functions are eventually differentiable on a
neighborhood of `x`, they are Cauchy _at_ `x`, and their derivatives
are a uniform Cauchy sequence in a neighborhood of `x`, then the functions form a uniform Cauchy
sequence in a neighborhood of `x`. -/
theorem uniformCauchySeqOnFilter_of_fderiv (hf' : UniformCauchySeqOnFilter f' l (𝓝 x))
(hf : ∀ᶠ n : ι × E in l ×ˢ 𝓝 x, HasFDerivAt (f n.1) (f' n.1 n.2) n.2)
(hfg : Cauchy (map (fun n => f n x) l)) : UniformCauchySeqOnFilter f l (𝓝 x) := by
letI : NormedSpace ℝ E := NormedSpace.restrictScalars ℝ 𝕜 _
rw [SeminormedAddGroup.uniformCauchySeqOnFilter_iff_tendstoUniformlyOnFilter_zero] at hf' ⊢
suffices
TendstoUniformlyOnFilter (fun (n : ι × ι) (z : E) => f n.1 z - f n.2 z - (f n.1 x - f n.2 x)) 0
(l ×ˢ l) (𝓝 x) ∧
TendstoUniformlyOnFilter (fun (n : ι × ι) (_ : E) => f n.1 x - f n.2 x) 0 (l ×ˢ l) (𝓝 x) by
have := this.1.add this.2
rw [add_zero] at this
exact this.congr (by simp)
constructor
· -- This inequality follows from the mean value theorem. To apply it, we will need to shrink our
-- neighborhood to small enough ball
rw [Metric.tendstoUniformlyOnFilter_iff] at hf' ⊢
intro ε hε
have := (tendsto_swap4_prod.eventually (hf.prod_mk hf)).diag_of_prod_right
obtain ⟨a, b, c, d, e⟩ := eventually_prod_iff.1 ((hf' ε hε).and this)
obtain ⟨R, hR, hR'⟩ := Metric.nhds_basis_ball.eventually_iff.mp d
let r := min 1 R
have hr : 0 < r := by simp [r, hR]
have hr' : ∀ ⦃y : E⦄, y ∈ Metric.ball x r → c y := fun y hy =>
hR' (lt_of_lt_of_le (Metric.mem_ball.mp hy) (min_le_right _ _))
have hxy : ∀ y : E, y ∈ Metric.ball x r → ‖y - x‖ < 1 := by
intro y hy
rw [Metric.mem_ball, dist_eq_norm] at hy
exact lt_of_lt_of_le hy (min_le_left _ _)
have hxyε : ∀ y : E, y ∈ Metric.ball x r → ε * ‖y - x‖ < ε := by
intro y hy
exact (mul_lt_iff_lt_one_right hε.lt).mpr (hxy y hy)
-- With a small ball in hand, apply the mean value theorem
refine
eventually_prod_iff.mpr
⟨_, b, fun e : E => Metric.ball x r e,
eventually_mem_set.mpr (Metric.nhds_basis_ball.mem_of_mem hr), fun {n} hn {y} hy => ?_⟩
simp only [Pi.zero_apply, dist_zero_left] at e ⊢
refine lt_of_le_of_lt ?_ (hxyε y hy)
exact
Convex.norm_image_sub_le_of_norm_hasFDerivWithin_le
(fun y hy => ((e hn (hr' hy)).2.1.sub (e hn (hr' hy)).2.2).hasFDerivWithinAt)
(fun y hy => (e hn (hr' hy)).1.le) (convex_ball x r) (Metric.mem_ball_self hr) hy
· -- This is just `hfg` run through `eventually_prod_iff`
refine Metric.tendstoUniformlyOnFilter_iff.mpr fun ε hε => ?_
obtain ⟨t, ht, ht'⟩ := (Metric.cauchy_iff.mp hfg).2 ε hε
exact
eventually_prod_iff.mpr
⟨fun n : ι × ι => f n.1 x ∈ t ∧ f n.2 x ∈ t,
eventually_prod_iff.mpr ⟨_, ht, _, ht, fun {n} hn {n'} hn' => ⟨hn, hn'⟩⟩,
fun _ => True,
by simp,
fun {n} hn {y} _ => by simpa [norm_sub_rev, dist_eq_norm] using ht' _ hn.1 _ hn.2⟩
#align uniform_cauchy_seq_on_filter_of_fderiv uniformCauchySeqOnFilter_of_fderiv
/-- A variant of the second fundamental theorem of calculus (FTC-2): If a sequence of functions
between real or complex normed spaces are differentiable on a ball centered at `x`, they
form a Cauchy sequence _at_ `x`, and their derivatives are Cauchy uniformly on the ball, then the
functions form a uniform Cauchy sequence on the ball.
NOTE: The fact that we work on a ball is typically all that is necessary to work with power series
and Dirichlet series (our primary use case). However, this can be generalized by replacing the ball
with any connected, bounded, open set and replacing uniform convergence with local uniform
convergence. See `cauchy_map_of_uniformCauchySeqOn_fderiv`.
-/
theorem uniformCauchySeqOn_ball_of_fderiv {r : ℝ} (hf' : UniformCauchySeqOn f' l (Metric.ball x r))
(hf : ∀ n : ι, ∀ y : E, y ∈ Metric.ball x r → HasFDerivAt (f n) (f' n y) y)
(hfg : Cauchy (map (fun n => f n x) l)) : UniformCauchySeqOn f l (Metric.ball x r) := by
letI : NormedSpace ℝ E := NormedSpace.restrictScalars ℝ 𝕜 _
have : NeBot l := (cauchy_map_iff.1 hfg).1
rcases le_or_lt r 0 with (hr | hr)
· simp only [Metric.ball_eq_empty.2 hr, UniformCauchySeqOn, Set.mem_empty_iff_false,
IsEmpty.forall_iff, eventually_const, imp_true_iff]
rw [SeminormedAddGroup.uniformCauchySeqOn_iff_tendstoUniformlyOn_zero] at hf' ⊢
suffices
TendstoUniformlyOn (fun (n : ι × ι) (z : E) => f n.1 z - f n.2 z - (f n.1 x - f n.2 x)) 0
(l ×ˢ l) (Metric.ball x r) ∧
TendstoUniformlyOn (fun (n : ι × ι) (_ : E) => f n.1 x - f n.2 x) 0
(l ×ˢ l) (Metric.ball x r) by
have := this.1.add this.2
rw [add_zero] at this
refine this.congr ?_
filter_upwards with n z _ using (by simp)
constructor
· -- This inequality follows from the mean value theorem
rw [Metric.tendstoUniformlyOn_iff] at hf' ⊢
intro ε hε
obtain ⟨q, hqpos, hq⟩ : ∃ q : ℝ, 0 < q ∧ q * r < ε := by
simp_rw [mul_comm]
exact exists_pos_mul_lt hε.lt r
apply (hf' q hqpos.gt).mono
intro n hn y hy
simp_rw [dist_eq_norm, Pi.zero_apply, zero_sub, norm_neg] at hn ⊢
have mvt :=
Convex.norm_image_sub_le_of_norm_hasFDerivWithin_le
(fun z hz => ((hf n.1 z hz).sub (hf n.2 z hz)).hasFDerivWithinAt) (fun z hz => (hn z hz).le)
(convex_ball x r) (Metric.mem_ball_self hr) hy
refine lt_of_le_of_lt mvt ?_
have : q * ‖y - x‖ < q * r :=
mul_lt_mul' rfl.le (by simpa only [dist_eq_norm] using Metric.mem_ball.mp hy) (norm_nonneg _)
hqpos
exact this.trans hq
· -- This is just `hfg` run through `eventually_prod_iff`
refine Metric.tendstoUniformlyOn_iff.mpr fun ε hε => ?_
obtain ⟨t, ht, ht'⟩ := (Metric.cauchy_iff.mp hfg).2 ε hε
rw [eventually_prod_iff]
refine ⟨fun n => f n x ∈ t, ht, fun n => f n x ∈ t, ht, ?_⟩
intro n hn n' hn' z _
rw [dist_eq_norm, Pi.zero_apply, zero_sub, norm_neg, ← dist_eq_norm]
exact ht' _ hn _ hn'
#align uniform_cauchy_seq_on_ball_of_fderiv uniformCauchySeqOn_ball_of_fderiv
/-- If a sequence of functions between real or complex normed spaces are differentiable on a
preconnected open set, they form a Cauchy sequence _at_ `x`, and their derivatives are Cauchy
uniformly on the set, then the functions form a Cauchy sequence at any point in the set. -/
theorem cauchy_map_of_uniformCauchySeqOn_fderiv {s : Set E} (hs : IsOpen s) (h's : IsPreconnected s)
(hf' : UniformCauchySeqOn f' l s) (hf : ∀ n : ι, ∀ y : E, y ∈ s → HasFDerivAt (f n) (f' n y) y)
{x₀ x : E} (hx₀ : x₀ ∈ s) (hx : x ∈ s) (hfg : Cauchy (map (fun n => f n x₀) l)) :
Cauchy (map (fun n => f n x) l) := by
have : NeBot l := (cauchy_map_iff.1 hfg).1
let t := { y | y ∈ s ∧ Cauchy (map (fun n => f n y) l) }
suffices H : s ⊆ t from (H hx).2
have A : ∀ x ε, x ∈ t → Metric.ball x ε ⊆ s → Metric.ball x ε ⊆ t := fun x ε xt hx y hy =>
⟨hx hy,
(uniformCauchySeqOn_ball_of_fderiv (hf'.mono hx) (fun n y hy => hf n y (hx hy))
xt.2).cauchy_map
hy⟩
have open_t : IsOpen t := by
rw [Metric.isOpen_iff]
intro x hx
rcases Metric.isOpen_iff.1 hs x hx.1 with ⟨ε, εpos, hε⟩
exact ⟨ε, εpos, A x ε hx hε⟩
have st_nonempty : (s ∩ t).Nonempty := ⟨x₀, hx₀, ⟨hx₀, hfg⟩⟩
suffices H : closure t ∩ s ⊆ t from h's.subset_of_closure_inter_subset open_t st_nonempty H
rintro x ⟨xt, xs⟩
obtain ⟨ε, εpos, hε⟩ : ∃ (ε : ℝ), ε > 0 ∧ Metric.ball x ε ⊆ s := Metric.isOpen_iff.1 hs x xs
obtain ⟨y, yt, hxy⟩ : ∃ (y : E), y ∈ t ∧ dist x y < ε / 2 :=
Metric.mem_closure_iff.1 xt _ (half_pos εpos)
have B : Metric.ball y (ε / 2) ⊆ Metric.ball x ε := by
apply Metric.ball_subset_ball'; rw [dist_comm]; linarith
exact A y (ε / 2) yt (B.trans hε) (Metric.mem_ball.2 hxy)
#align cauchy_map_of_uniform_cauchy_seq_on_fderiv cauchy_map_of_uniformCauchySeqOn_fderiv
/-- If `f_n → g` pointwise and the derivatives `(f_n)' → h` _uniformly_ converge, then
in fact for a fixed `y`, the difference quotients `‖z - y‖⁻¹ • (f_n z - f_n y)` converge
_uniformly_ to `‖z - y‖⁻¹ • (g z - g y)` -/
theorem difference_quotients_converge_uniformly (hf' : TendstoUniformlyOnFilter f' g' l (𝓝 x))
(hf : ∀ᶠ n : ι × E in l ×ˢ 𝓝 x, HasFDerivAt (f n.1) (f' n.1 n.2) n.2)
(hfg : ∀ᶠ y : E in 𝓝 x, Tendsto (fun n => f n y) l (𝓝 (g y))) :
TendstoUniformlyOnFilter (fun n : ι => fun y : E => (‖y - x‖⁻¹ : 𝕜) • (f n y - f n x))
(fun y : E => (‖y - x‖⁻¹ : 𝕜) • (g y - g x)) l (𝓝 x) := by
let A : NormedSpace ℝ E := NormedSpace.restrictScalars ℝ 𝕜 _
rcases eq_or_ne l ⊥ with (hl | hl)
· simp only [hl, TendstoUniformlyOnFilter, bot_prod, eventually_bot, imp_true_iff]
haveI : NeBot l := ⟨hl⟩
refine
UniformCauchySeqOnFilter.tendstoUniformlyOnFilter_of_tendsto ?_
((hfg.and (eventually_const.mpr hfg.self_of_nhds)).mono fun y hy =>
(hy.1.sub hy.2).const_smul _)
rw [SeminormedAddGroup.uniformCauchySeqOnFilter_iff_tendstoUniformlyOnFilter_zero]
rw [Metric.tendstoUniformlyOnFilter_iff]
have hfg' := hf'.uniformCauchySeqOnFilter
rw [SeminormedAddGroup.uniformCauchySeqOnFilter_iff_tendstoUniformlyOnFilter_zero] at hfg'
rw [Metric.tendstoUniformlyOnFilter_iff] at hfg'
intro ε hε
obtain ⟨q, hqpos, hqε⟩ := exists_pos_rat_lt hε
specialize hfg' (q : ℝ) (by simp [hqpos])
have := (tendsto_swap4_prod.eventually (hf.prod_mk hf)).diag_of_prod_right
obtain ⟨a, b, c, d, e⟩ := eventually_prod_iff.1 (hfg'.and this)
obtain ⟨r, hr, hr'⟩ := Metric.nhds_basis_ball.eventually_iff.mp d
rw [eventually_prod_iff]
refine
⟨_, b, fun e : E => Metric.ball x r e,
eventually_mem_set.mpr (Metric.nhds_basis_ball.mem_of_mem hr), fun {n} hn {y} hy => ?_⟩
simp only [Pi.zero_apply, dist_zero_left]
rw [← smul_sub, norm_smul, norm_inv, RCLike.norm_coe_norm]
refine lt_of_le_of_lt ?_ hqε
by_cases hyz' : x = y; · simp [hyz', hqpos.le]
have hyz : 0 < ‖y - x‖ := by rw [norm_pos_iff]; intro hy'; exact hyz' (eq_of_sub_eq_zero hy').symm
rw [inv_mul_le_iff hyz, mul_comm, sub_sub_sub_comm]
simp only [Pi.zero_apply, dist_zero_left] at e
refine
Convex.norm_image_sub_le_of_norm_hasFDerivWithin_le
(fun y hy => ((e hn (hr' hy)).2.1.sub (e hn (hr' hy)).2.2).hasFDerivWithinAt)
(fun y hy => (e hn (hr' hy)).1.le) (convex_ball x r) (Metric.mem_ball_self hr) hy
#align difference_quotients_converge_uniformly difference_quotients_converge_uniformly
/-- `(d/dx) lim_{n → ∞} f n x = lim_{n → ∞} f' n x` when the `f' n` converge
_uniformly_ to their limit at `x`.
In words the assumptions mean the following:
* `hf'`: The `f'` converge "uniformly at" `x` to `g'`. This does not mean that the `f' n` even
converge away from `x`!
* `hf`: For all `(y, n)` with `y` sufficiently close to `x` and `n` sufficiently large, `f' n` is
the derivative of `f n`
* `hfg`: The `f n` converge pointwise to `g` on a neighborhood of `x` -/
theorem hasFDerivAt_of_tendstoUniformlyOnFilter [NeBot l]
(hf' : TendstoUniformlyOnFilter f' g' l (𝓝 x))
(hf : ∀ᶠ n : ι × E in l ×ˢ 𝓝 x, HasFDerivAt (f n.1) (f' n.1 n.2) n.2)
(hfg : ∀ᶠ y in 𝓝 x, Tendsto (fun n => f n y) l (𝓝 (g y))) : HasFDerivAt g (g' x) x := by
-- The proof strategy follows several steps:
-- 1. The quantifiers in the definition of the derivative are
-- `∀ ε > 0, ∃δ > 0, ∀y ∈ B_δ(x)`. We will introduce a quantifier in the middle:
-- `∀ ε > 0, ∃N, ∀n ≥ N, ∃δ > 0, ∀y ∈ B_δ(x)` which will allow us to introduce the `f(') n`
-- 2. The order of the quantifiers `hfg` are opposite to what we need. We will be able to swap
-- the quantifiers using the uniform convergence assumption
rw [hasFDerivAt_iff_tendsto]
-- Introduce extra quantifier via curried filters
suffices
Tendsto (fun y : ι × E => ‖y.2 - x‖⁻¹ * ‖g y.2 - g x - (g' x) (y.2 - x)‖)
(l.curry (𝓝 x)) (𝓝 0) by
rw [Metric.tendsto_nhds] at this ⊢
intro ε hε
specialize this ε hε
rw [eventually_curry_iff] at this
simp only at this
exact (eventually_const.mp this).mono (by simp only [imp_self, forall_const])
-- With the new quantifier in hand, we can perform the famous `ε/3` proof. Specifically,
-- we will break up the limit (the difference functions minus the derivative go to 0) into 3:
-- * The difference functions of the `f n` converge *uniformly* to the difference functions
-- of the `g n`
-- * The `f' n` are the derivatives of the `f n`
-- * The `f' n` converge to `g'` at `x`
conv =>
congr
ext
rw [← abs_norm, ← abs_inv, ← @RCLike.norm_ofReal 𝕜 _ _, RCLike.ofReal_inv, ← norm_smul]
rw [← tendsto_zero_iff_norm_tendsto_zero]
have :
(fun a : ι × E => (‖a.2 - x‖⁻¹ : 𝕜) • (g a.2 - g x - (g' x) (a.2 - x))) =
((fun a : ι × E => (‖a.2 - x‖⁻¹ : 𝕜) • (g a.2 - g x - (f a.1 a.2 - f a.1 x))) +
fun a : ι × E =>
(‖a.2 - x‖⁻¹ : 𝕜) • (f a.1 a.2 - f a.1 x - ((f' a.1 x) a.2 - (f' a.1 x) x))) +
fun a : ι × E => (‖a.2 - x‖⁻¹ : 𝕜) • (f' a.1 x - g' x) (a.2 - x) := by
ext; simp only [Pi.add_apply]; rw [← smul_add, ← smul_add]; congr
simp only [map_sub, sub_add_sub_cancel, ContinuousLinearMap.coe_sub', Pi.sub_apply]
-- Porting note: added
abel
simp_rw [this]
have : 𝓝 (0 : G) = 𝓝 (0 + 0 + 0) := by simp only [add_zero]
rw [this]
refine Tendsto.add (Tendsto.add ?_ ?_) ?_
· simp only
have := difference_quotients_converge_uniformly hf' hf hfg
rw [Metric.tendstoUniformlyOnFilter_iff] at this
rw [Metric.tendsto_nhds]
intro ε hε
apply ((this ε hε).filter_mono curry_le_prod).mono
intro n hn
rw [dist_eq_norm] at hn ⊢
rw [← smul_sub] at hn
rwa [sub_zero]
· -- (Almost) the definition of the derivatives
rw [Metric.tendsto_nhds]
intro ε hε
rw [eventually_curry_iff]
refine hf.curry.mono fun n hn => ?_
have := hn.self_of_nhds
rw [hasFDerivAt_iff_tendsto, Metric.tendsto_nhds] at this
refine (this ε hε).mono fun y hy => ?_
rw [dist_eq_norm] at hy ⊢
simp only [sub_zero, map_sub, norm_mul, norm_inv, norm_norm] at hy ⊢
rw [norm_smul, norm_inv, RCLike.norm_coe_norm]
exact hy
· -- hfg' after specializing to `x` and applying the definition of the operator norm
refine Tendsto.mono_left ?_ curry_le_prod
have h1 : Tendsto (fun n : ι × E => g' n.2 - f' n.1 n.2) (l ×ˢ 𝓝 x) (𝓝 0) := by
rw [Metric.tendstoUniformlyOnFilter_iff] at hf'
exact Metric.tendsto_nhds.mpr fun ε hε => by simpa using hf' ε hε
have h2 : Tendsto (fun n : ι => g' x - f' n x) l (𝓝 0) := by
rw [Metric.tendsto_nhds] at h1 ⊢
exact fun ε hε => (h1 ε hε).curry.mono fun n hn => hn.self_of_nhds
refine squeeze_zero_norm ?_
(tendsto_zero_iff_norm_tendsto_zero.mp (tendsto_fst.comp (h2.prod_map tendsto_id)))
intro n
simp_rw [norm_smul, norm_inv, RCLike.norm_coe_norm]
by_cases hx : x = n.2; · simp [hx]
have hnx : 0 < ‖n.2 - x‖ := by
rw [norm_pos_iff]; intro hx'; exact hx (eq_of_sub_eq_zero hx').symm
rw [inv_mul_le_iff hnx, mul_comm]
simp only [Function.comp_apply, Prod.map_apply]
rw [norm_sub_rev]
exact (f' n.1 x - g' x).le_opNorm (n.2 - x)
#align has_fderiv_at_of_tendsto_uniformly_on_filter hasFDerivAt_of_tendstoUniformlyOnFilter
theorem hasFDerivAt_of_tendstoLocallyUniformlyOn [NeBot l] {s : Set E} (hs : IsOpen s)
(hf' : TendstoLocallyUniformlyOn f' g' l s) (hf : ∀ n, ∀ x ∈ s, HasFDerivAt (f n) (f' n x) x)
(hfg : ∀ x ∈ s, Tendsto (fun n => f n x) l (𝓝 (g x))) (hx : x ∈ s) :
HasFDerivAt g (g' x) x := by
have h1 : s ∈ 𝓝 x := hs.mem_nhds hx
have h3 : Set.univ ×ˢ s ∈ l ×ˢ 𝓝 x := by simp only [h1, prod_mem_prod_iff, univ_mem, and_self_iff]
have h4 : ∀ᶠ n : ι × E in l ×ˢ 𝓝 x, HasFDerivAt (f n.1) (f' n.1 n.2) n.2 :=
eventually_of_mem h3 fun ⟨n, z⟩ ⟨_, hz⟩ => hf n z hz
refine hasFDerivAt_of_tendstoUniformlyOnFilter ?_ h4 (eventually_of_mem h1 hfg)
simpa [IsOpen.nhdsWithin_eq hs hx] using tendstoLocallyUniformlyOn_iff_filter.mp hf' x hx
#align has_fderiv_at_of_tendsto_locally_uniformly_on hasFDerivAt_of_tendstoLocallyUniformlyOn
/-- A slight variant of `hasFDerivAt_of_tendstoLocallyUniformlyOn` with the assumption stated
in terms of `DifferentiableOn` rather than `HasFDerivAt`. This makes a few proofs nicer in
complex analysis where holomorphicity is assumed but the derivative is not known a priori. -/
| Mathlib/Analysis/Calculus/UniformLimitsDeriv.lean | 411 | 416 | theorem hasFDerivAt_of_tendsto_locally_uniformly_on' [NeBot l] {s : Set E} (hs : IsOpen s)
(hf' : TendstoLocallyUniformlyOn (fderiv 𝕜 ∘ f) g' l s) (hf : ∀ n, DifferentiableOn 𝕜 (f n) s)
(hfg : ∀ x ∈ s, Tendsto (fun n => f n x) l (𝓝 (g x))) (hx : x ∈ s) :
HasFDerivAt g (g' x) x := by |
refine hasFDerivAt_of_tendstoLocallyUniformlyOn hs hf' (fun n z hz => ?_) hfg hx
exact ((hf n z hz).differentiableAt (hs.mem_nhds hz)).hasFDerivAt
|
/-
Copyright (c) 2020 Thomas Browning, Patrick Lutz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Thomas Browning, Patrick Lutz
-/
import Mathlib.FieldTheory.Fixed
import Mathlib.FieldTheory.NormalClosure
import Mathlib.FieldTheory.PrimitiveElement
import Mathlib.GroupTheory.GroupAction.FixingSubgroup
#align_import field_theory.galois from "leanprover-community/mathlib"@"9fb8964792b4237dac6200193a0d533f1b3f7423"
/-!
# Galois Extensions
In this file we define Galois extensions as extensions which are both separable and normal.
## Main definitions
- `IsGalois F E` where `E` is an extension of `F`
- `fixedField H` where `H : Subgroup (E ≃ₐ[F] E)`
- `fixingSubgroup K` where `K : IntermediateField F E`
- `intermediateFieldEquivSubgroup` where `E/F` is finite dimensional and Galois
## Main results
- `IntermediateField.fixingSubgroup_fixedField` : If `E/F` is finite dimensional (but not
necessarily Galois) then `fixingSubgroup (fixedField H) = H`
- `IntermediateField.fixedField_fixingSubgroup`: If `E/F` is finite dimensional and Galois
then `fixedField (fixingSubgroup K) = K`
Together, these two results prove the Galois correspondence.
- `IsGalois.tfae` : Equivalent characterizations of a Galois extension of finite degree
-/
open scoped Polynomial IntermediateField
open FiniteDimensional AlgEquiv
section
variable (F : Type*) [Field F] (E : Type*) [Field E] [Algebra F E]
/-- A field extension E/F is Galois if it is both separable and normal. Note that in mathlib
a separable extension of fields is by definition algebraic. -/
class IsGalois : Prop where
[to_isSeparable : IsSeparable F E]
[to_normal : Normal F E]
#align is_galois IsGalois
variable {F E}
theorem isGalois_iff : IsGalois F E ↔ IsSeparable F E ∧ Normal F E :=
⟨fun h => ⟨h.1, h.2⟩, fun h =>
{ to_isSeparable := h.1
to_normal := h.2 }⟩
#align is_galois_iff isGalois_iff
attribute [instance 100] IsGalois.to_isSeparable IsGalois.to_normal
-- see Note [lower instance priority]
variable (F E)
namespace IsGalois
instance self : IsGalois F F :=
⟨⟩
#align is_galois.self IsGalois.self
variable {E}
theorem integral [IsGalois F E] (x : E) : IsIntegral F x :=
to_normal.isIntegral x
#align is_galois.integral IsGalois.integral
theorem separable [IsGalois F E] (x : E) : (minpoly F x).Separable :=
IsSeparable.separable F x
#align is_galois.separable IsGalois.separable
theorem splits [IsGalois F E] (x : E) : (minpoly F x).Splits (algebraMap F E) :=
Normal.splits' x
#align is_galois.splits IsGalois.splits
variable (E)
instance of_fixed_field (G : Type*) [Group G] [Finite G] [MulSemiringAction G E] :
IsGalois (FixedPoints.subfield G E) E :=
⟨⟩
#align is_galois.of_fixed_field IsGalois.of_fixed_field
theorem IntermediateField.AdjoinSimple.card_aut_eq_finrank [FiniteDimensional F E] {α : E}
(hα : IsIntegral F α) (h_sep : (minpoly F α).Separable)
(h_splits : (minpoly F α).Splits (algebraMap F F⟮α⟯)) :
Fintype.card (F⟮α⟯ ≃ₐ[F] F⟮α⟯) = finrank F F⟮α⟯ := by
letI : Fintype (F⟮α⟯ →ₐ[F] F⟮α⟯) := IntermediateField.fintypeOfAlgHomAdjoinIntegral F hα
rw [IntermediateField.adjoin.finrank hα]
rw [← IntermediateField.card_algHom_adjoin_integral F hα h_sep h_splits]
exact Fintype.card_congr (algEquivEquivAlgHom F F⟮α⟯)
#align is_galois.intermediate_field.adjoin_simple.card_aut_eq_finrank IsGalois.IntermediateField.AdjoinSimple.card_aut_eq_finrank
| Mathlib/FieldTheory/Galois.lean | 103 | 125 | theorem card_aut_eq_finrank [FiniteDimensional F E] [IsGalois F E] :
Fintype.card (E ≃ₐ[F] E) = finrank F E := by |
cases' Field.exists_primitive_element F E with α hα
let iso : F⟮α⟯ ≃ₐ[F] E :=
{ toFun := fun e => e.val
invFun := fun e => ⟨e, by rw [hα]; exact IntermediateField.mem_top⟩
left_inv := fun _ => by ext; rfl
right_inv := fun _ => rfl
map_mul' := fun _ _ => rfl
map_add' := fun _ _ => rfl
commutes' := fun _ => rfl }
have H : IsIntegral F α := IsGalois.integral F α
have h_sep : (minpoly F α).Separable := IsGalois.separable F α
have h_splits : (minpoly F α).Splits (algebraMap F E) := IsGalois.splits F α
replace h_splits : Polynomial.Splits (algebraMap F F⟮α⟯) (minpoly F α) := by
simpa using
Polynomial.splits_comp_of_splits (algebraMap F E) iso.symm.toAlgHom.toRingHom h_splits
rw [← LinearEquiv.finrank_eq iso.toLinearEquiv]
rw [← IntermediateField.AdjoinSimple.card_aut_eq_finrank F E H h_sep h_splits]
apply Fintype.card_congr
apply Equiv.mk (fun ϕ => iso.trans (ϕ.trans iso.symm)) fun ϕ => iso.symm.trans (ϕ.trans iso)
· intro ϕ; ext1; simp only [trans_apply, apply_symm_apply]
· intro ϕ; ext1; simp only [trans_apply, symm_apply_apply]
|
/-
Copyright (c) 2022 Riccardo Brasca. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Riccardo Brasca
-/
import Mathlib.Data.Nat.Choose.Dvd
import Mathlib.RingTheory.IntegrallyClosed
import Mathlib.RingTheory.Norm
import Mathlib.RingTheory.Polynomial.Cyclotomic.Expand
#align_import ring_theory.polynomial.eisenstein.is_integral from "leanprover-community/mathlib"@"5bfbcca0a7ffdd21cf1682e59106d6c942434a32"
/-!
# Eisenstein polynomials
In this file we gather more miscellaneous results about Eisenstein polynomials
## Main results
* `mem_adjoin_of_smul_prime_pow_smul_of_minpoly_isEisensteinAt`: let `K` be the field of fraction
of an integrally closed domain `R` and let `L` be a separable extension of `K`, generated by an
integral power basis `B` such that the minimal polynomial of `B.gen` is Eisenstein at `p`. Given
`z : L` integral over `R`, if `p ^ n • z ∈ adjoin R {B.gen}`, then `z ∈ adjoin R {B.gen}`.
Together with `Algebra.discr_mul_isIntegral_mem_adjoin` this result often allows to compute the
ring of integers of `L`.
-/
universe u v w z
variable {R : Type u}
open Ideal Algebra Finset
open scoped Polynomial
section Cyclotomic
variable (p : ℕ)
local notation "𝓟" => Submodule.span ℤ {(p : ℤ)}
open Polynomial
theorem cyclotomic_comp_X_add_one_isEisensteinAt [hp : Fact p.Prime] :
((cyclotomic p ℤ).comp (X + 1)).IsEisensteinAt 𝓟 := by
refine Monic.isEisensteinAt_of_mem_of_not_mem ?_
(Ideal.IsPrime.ne_top <| (Ideal.span_singleton_prime (mod_cast hp.out.ne_zero)).2 <|
Nat.prime_iff_prime_int.1 hp.out) (fun {i hi} => ?_) ?_
· rw [show (X + 1 : ℤ[X]) = X + C 1 by simp]
refine (cyclotomic.monic p ℤ).comp (monic_X_add_C 1) fun h => ?_
rw [natDegree_X_add_C] at h
exact zero_ne_one h.symm
· rw [cyclotomic_prime, geom_sum_X_comp_X_add_one_eq_sum, ← lcoeff_apply, map_sum]
conv =>
congr
congr
next => skip
ext
rw [lcoeff_apply, ← C_eq_natCast, C_mul_X_pow_eq_monomial, coeff_monomial]
rw [natDegree_comp, show (X + 1 : ℤ[X]) = X + C 1 by simp, natDegree_X_add_C, mul_one,
natDegree_cyclotomic, Nat.totient_prime hp.out] at hi
simp only [hi.trans_le (Nat.sub_le _ _), sum_ite_eq', mem_range, if_true,
Ideal.submodule_span_eq, Ideal.mem_span_singleton, Int.natCast_dvd_natCast]
exact hp.out.dvd_choose_self i.succ_ne_zero (lt_tsub_iff_right.1 hi)
· rw [coeff_zero_eq_eval_zero, eval_comp, cyclotomic_prime, eval_add, eval_X, eval_one, zero_add,
eval_geom_sum, one_geom_sum, Ideal.submodule_span_eq, Ideal.span_singleton_pow,
Ideal.mem_span_singleton]
intro h
obtain ⟨k, hk⟩ := Int.natCast_dvd_natCast.1 h
rw [mul_assoc, mul_comm 1, mul_one] at hk
nth_rw 1 [← Nat.mul_one p] at hk
rw [mul_right_inj' hp.out.ne_zero] at hk
exact Nat.Prime.not_dvd_one hp.out (Dvd.intro k hk.symm)
set_option linter.uppercaseLean3 false in
#align cyclotomic_comp_X_add_one_is_eisenstein_at cyclotomic_comp_X_add_one_isEisensteinAt
| Mathlib/RingTheory/Polynomial/Eisenstein/IsIntegral.lean | 77 | 117 | theorem cyclotomic_prime_pow_comp_X_add_one_isEisensteinAt [hp : Fact p.Prime] (n : ℕ) :
((cyclotomic (p ^ (n + 1)) ℤ).comp (X + 1)).IsEisensteinAt 𝓟 := by |
refine Monic.isEisensteinAt_of_mem_of_not_mem ?_
(Ideal.IsPrime.ne_top <| (Ideal.span_singleton_prime (mod_cast hp.out.ne_zero)).2 <|
Nat.prime_iff_prime_int.1 hp.out) ?_ ?_
· rw [show (X + 1 : ℤ[X]) = X + C 1 by simp]
refine (cyclotomic.monic _ ℤ).comp (monic_X_add_C 1) fun h => ?_
rw [natDegree_X_add_C] at h
exact zero_ne_one h.symm
· induction' n with n hn
· intro i hi
rw [Nat.zero_add, pow_one] at hi ⊢
exact (cyclotomic_comp_X_add_one_isEisensteinAt p).mem hi
· intro i hi
rw [Ideal.submodule_span_eq, Ideal.mem_span_singleton, ← ZMod.intCast_zmod_eq_zero_iff_dvd,
show ↑(_ : ℤ) = Int.castRingHom (ZMod p) _ by rfl, ← coeff_map, map_comp, map_cyclotomic,
Polynomial.map_add, map_X, Polynomial.map_one, pow_add, pow_one,
cyclotomic_mul_prime_dvd_eq_pow, pow_comp, ← ZMod.expand_card, coeff_expand hp.out.pos]
· simp only [ite_eq_right_iff]
rintro ⟨k, hk⟩
rw [natDegree_comp, show (X + 1 : ℤ[X]) = X + C 1 by simp, natDegree_X_add_C, mul_one,
natDegree_cyclotomic, Nat.totient_prime_pow hp.out (Nat.succ_pos _), Nat.add_one_sub_one]
at hn hi
rw [hk, pow_succ', mul_assoc] at hi
rw [hk, mul_comm, Nat.mul_div_cancel _ hp.out.pos]
replace hn := hn (lt_of_mul_lt_mul_left' hi)
rw [Ideal.submodule_span_eq, Ideal.mem_span_singleton, ← ZMod.intCast_zmod_eq_zero_iff_dvd,
show ↑(_ : ℤ) = Int.castRingHom (ZMod p) _ by rfl, ← coeff_map] at hn
simpa [map_comp] using hn
· exact ⟨p ^ n, by rw [pow_succ']⟩
· rw [coeff_zero_eq_eval_zero, eval_comp, cyclotomic_prime_pow_eq_geom_sum hp.out, eval_add,
eval_X, eval_one, zero_add, eval_finset_sum]
simp only [eval_pow, eval_X, one_pow, sum_const, card_range, Nat.smul_one_eq_cast,
submodule_span_eq, Ideal.submodule_span_eq, Ideal.span_singleton_pow,
Ideal.mem_span_singleton]
intro h
obtain ⟨k, hk⟩ := Int.natCast_dvd_natCast.1 h
rw [mul_assoc, mul_comm 1, mul_one] at hk
nth_rw 1 [← Nat.mul_one p] at hk
rw [mul_right_inj' hp.out.ne_zero] at hk
exact Nat.Prime.not_dvd_one hp.out (Dvd.intro k hk.symm)
|
/-
Copyright (c) 2023 Rémy Degenne. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Rémy Degenne
-/
import Mathlib.MeasureTheory.Constructions.Pi
import Mathlib.Probability.Kernel.Basic
/-!
# Independence with respect to a kernel and a measure
A family of sets of sets `π : ι → Set (Set Ω)` is independent with respect to a kernel
`κ : kernel α Ω` and a measure `μ` on `α` if for any finite set of indices `s = {i_1, ..., i_n}`,
for any sets `f i_1 ∈ π i_1, ..., f i_n ∈ π i_n`, then for `μ`-almost every `a : α`,
`κ a (⋂ i in s, f i) = ∏ i ∈ s, κ a (f i)`.
This notion of independence is a generalization of both independence and conditional independence.
For conditional independence, `κ` is the conditional kernel `ProbabilityTheory.condexpKernel` and
`μ` is the ambiant measure. For (non-conditional) independence, `κ = kernel.const Unit μ` and the
measure is the Dirac measure on `Unit`.
The main purpose of this file is to prove only once the properties that hold for both conditional
and non-conditional independence.
## Main definitions
* `ProbabilityTheory.kernel.iIndepSets`: independence of a family of sets of sets.
Variant for two sets of sets: `ProbabilityTheory.kernel.IndepSets`.
* `ProbabilityTheory.kernel.iIndep`: independence of a family of σ-algebras. Variant for two
σ-algebras: `Indep`.
* `ProbabilityTheory.kernel.iIndepSet`: independence of a family of sets. Variant for two sets:
`ProbabilityTheory.kernel.IndepSet`.
* `ProbabilityTheory.kernel.iIndepFun`: independence of a family of functions (random variables).
Variant for two functions: `ProbabilityTheory.kernel.IndepFun`.
See the file `Mathlib/Probability/Kernel/Basic.lean` for a more detailed discussion of these
definitions in the particular case of the usual independence notion.
## Main statements
* `ProbabilityTheory.kernel.iIndepSets.iIndep`: if π-systems are independent as sets of sets,
then the measurable space structures they generate are independent.
* `ProbabilityTheory.kernel.IndepSets.Indep`: variant with two π-systems.
-/
open MeasureTheory MeasurableSpace
open scoped MeasureTheory ENNReal
namespace ProbabilityTheory.kernel
variable {α Ω ι : Type*}
section Definitions
variable {_mα : MeasurableSpace α}
/-- A family of sets of sets `π : ι → Set (Set Ω)` is independent with respect to a kernel `κ` and
a measure `μ` if for any finite set of indices `s = {i_1, ..., i_n}`, for any sets
`f i_1 ∈ π i_1, ..., f i_n ∈ π i_n`, then `∀ᵐ a ∂μ, κ a (⋂ i in s, f i) = ∏ i ∈ s, κ a (f i)`.
It will be used for families of pi_systems. -/
def iIndepSets {_mΩ : MeasurableSpace Ω}
(π : ι → Set (Set Ω)) (κ : kernel α Ω) (μ : Measure α := by volume_tac) : Prop :=
∀ (s : Finset ι) {f : ι → Set Ω} (_H : ∀ i, i ∈ s → f i ∈ π i),
∀ᵐ a ∂μ, κ a (⋂ i ∈ s, f i) = ∏ i ∈ s, κ a (f i)
/-- Two sets of sets `s₁, s₂` are independent with respect to a kernel `κ` and a measure `μ` if for
any sets `t₁ ∈ s₁, t₂ ∈ s₂`, then `∀ᵐ a ∂μ, κ a (t₁ ∩ t₂) = κ a (t₁) * κ a (t₂)` -/
def IndepSets {_mΩ : MeasurableSpace Ω}
(s1 s2 : Set (Set Ω)) (κ : kernel α Ω) (μ : Measure α := by volume_tac) : Prop :=
∀ t1 t2 : Set Ω, t1 ∈ s1 → t2 ∈ s2 → (∀ᵐ a ∂μ, κ a (t1 ∩ t2) = κ a t1 * κ a t2)
/-- A family of measurable space structures (i.e. of σ-algebras) is independent with respect to a
kernel `κ` and a measure `μ` if the family of sets of measurable sets they define is independent. -/
def iIndep (m : ι → MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω} (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
iIndepSets (fun x ↦ {s | MeasurableSet[m x] s}) κ μ
/-- Two measurable space structures (or σ-algebras) `m₁, m₂` are independent with respect to a
kernel `κ` and a measure `μ` if for any sets `t₁ ∈ m₁, t₂ ∈ m₂`,
`∀ᵐ a ∂μ, κ a (t₁ ∩ t₂) = κ a (t₁) * κ a (t₂)` -/
def Indep (m₁ m₂ : MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω} (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
IndepSets {s | MeasurableSet[m₁] s} {s | MeasurableSet[m₂] s} κ μ
/-- A family of sets is independent if the family of measurable space structures they generate is
independent. For a set `s`, the generated measurable space has measurable sets `∅, s, sᶜ, univ`. -/
def iIndepSet {_mΩ : MeasurableSpace Ω} (s : ι → Set Ω) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
iIndep (fun i ↦ generateFrom {s i}) κ μ
/-- Two sets are independent if the two measurable space structures they generate are independent.
For a set `s`, the generated measurable space structure has measurable sets `∅, s, sᶜ, univ`. -/
def IndepSet {_mΩ : MeasurableSpace Ω} (s t : Set Ω) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
Indep (generateFrom {s}) (generateFrom {t}) κ μ
/-- A family of functions defined on the same space `Ω` and taking values in possibly different
spaces, each with a measurable space structure, is independent if the family of measurable space
structures they generate on `Ω` is independent. For a function `g` with codomain having measurable
space structure `m`, the generated measurable space structure is `MeasurableSpace.comap g m`. -/
def iIndepFun {_mΩ : MeasurableSpace Ω} {β : ι → Type*} (m : ∀ x : ι, MeasurableSpace (β x))
(f : ∀ x : ι, Ω → β x) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
iIndep (fun x ↦ MeasurableSpace.comap (f x) (m x)) κ μ
/-- Two functions are independent if the two measurable space structures they generate are
independent. For a function `f` with codomain having measurable space structure `m`, the generated
measurable space structure is `MeasurableSpace.comap f m`. -/
def IndepFun {β γ} {_mΩ : MeasurableSpace Ω} [mβ : MeasurableSpace β] [mγ : MeasurableSpace γ]
(f : Ω → β) (g : Ω → γ) (κ : kernel α Ω)
(μ : Measure α := by volume_tac) : Prop :=
Indep (MeasurableSpace.comap f mβ) (MeasurableSpace.comap g mγ) κ μ
end Definitions
section ByDefinition
variable {β : ι → Type*} {mβ : ∀ i, MeasurableSpace (β i)}
{_mα : MeasurableSpace α} {m : ι → MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α}
{π : ι → Set (Set Ω)} {s : ι → Set Ω} {S : Finset ι} {f : ∀ x : ι, Ω → β x}
lemma iIndepSets.meas_biInter (h : iIndepSets π κ μ) (s : Finset ι)
{f : ι → Set Ω} (hf : ∀ i, i ∈ s → f i ∈ π i) :
∀ᵐ a ∂μ, κ a (⋂ i ∈ s, f i) = ∏ i ∈ s, κ a (f i) := h s hf
lemma iIndepSets.meas_iInter [Fintype ι] (h : iIndepSets π κ μ) (hs : ∀ i, s i ∈ π i) :
∀ᵐ a ∂μ, κ a (⋂ i, s i) = ∏ i, κ a (s i) := by
filter_upwards [h.meas_biInter Finset.univ (fun _i _ ↦ hs _)] with a ha using by simp [← ha]
lemma iIndep.iIndepSets' (hμ : iIndep m κ μ) :
iIndepSets (fun x ↦ {s | MeasurableSet[m x] s}) κ μ := hμ
lemma iIndep.meas_biInter (hμ : iIndep m κ μ) (hs : ∀ i, i ∈ S → MeasurableSet[m i] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i ∈ S, s i) = ∏ i ∈ S, κ a (s i) := hμ _ hs
lemma iIndep.meas_iInter [Fintype ι] (h : iIndep m κ μ) (hs : ∀ i, MeasurableSet[m i] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i, s i) = ∏ i, κ a (s i) := by
filter_upwards [h.meas_biInter (fun i (_ : i ∈ Finset.univ) ↦ hs _)] with a ha
simp [← ha]
protected lemma iIndepFun.iIndep (hf : iIndepFun mβ f κ μ) :
iIndep (fun x ↦ (mβ x).comap (f x)) κ μ := hf
lemma iIndepFun.meas_biInter (hf : iIndepFun mβ f κ μ)
(hs : ∀ i, i ∈ S → MeasurableSet[(mβ i).comap (f i)] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i ∈ S, s i) = ∏ i ∈ S, κ a (s i) := hf.iIndep.meas_biInter hs
lemma iIndepFun.meas_iInter [Fintype ι] (hf : iIndepFun mβ f κ μ)
(hs : ∀ i, MeasurableSet[(mβ i).comap (f i)] (s i)) :
∀ᵐ a ∂μ, κ a (⋂ i, s i) = ∏ i, κ a (s i) := hf.iIndep.meas_iInter hs
lemma IndepFun.meas_inter {β γ : Type*} [mβ : MeasurableSpace β] [mγ : MeasurableSpace γ]
{f : Ω → β} {g : Ω → γ} (hfg : IndepFun f g κ μ)
{s t : Set Ω} (hs : MeasurableSet[mβ.comap f] s) (ht : MeasurableSet[mγ.comap g] t) :
∀ᵐ a ∂μ, κ a (s ∩ t) = κ a s * κ a t := hfg _ _ hs ht
end ByDefinition
section Indep
variable {_mα : MeasurableSpace α}
@[symm]
theorem IndepSets.symm {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α}
{s₁ s₂ : Set (Set Ω)} (h : IndepSets s₁ s₂ κ μ) :
IndepSets s₂ s₁ κ μ := by
intros t1 t2 ht1 ht2
filter_upwards [h t2 t1 ht2 ht1] with a ha
rwa [Set.inter_comm, mul_comm]
@[symm]
theorem Indep.symm {m₁ m₂ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω}
{μ : Measure α} (h : Indep m₁ m₂ κ μ) :
Indep m₂ m₁ κ μ :=
IndepSets.symm h
theorem indep_bot_right (m' : MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] :
Indep m' ⊥ κ μ := by
intros s t _ ht
rw [Set.mem_setOf_eq, MeasurableSpace.measurableSet_bot_iff] at ht
refine Filter.eventually_of_forall (fun a ↦ ?_)
cases' ht with ht ht
· rw [ht, Set.inter_empty, measure_empty, mul_zero]
· rw [ht, Set.inter_univ, measure_univ, mul_one]
theorem indep_bot_left (m' : MeasurableSpace Ω) {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] :
Indep ⊥ m' κ μ := (indep_bot_right m').symm
theorem indepSet_empty_right {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] (s : Set Ω) :
IndepSet s ∅ κ μ := by
simp only [IndepSet, generateFrom_singleton_empty];
exact indep_bot_right _
theorem indepSet_empty_left {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω}
{μ : Measure α} [IsMarkovKernel κ] (s : Set Ω) :
IndepSet ∅ s κ μ :=
(indepSet_empty_right s).symm
theorem indepSets_of_indepSets_of_le_left {s₁ s₂ s₃ : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : IndepSets s₁ s₂ κ μ) (h31 : s₃ ⊆ s₁) :
IndepSets s₃ s₂ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 (Set.mem_of_subset_of_mem h31 ht1) ht2
theorem indepSets_of_indepSets_of_le_right {s₁ s₂ s₃ : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : IndepSets s₁ s₂ κ μ) (h32 : s₃ ⊆ s₂) :
IndepSets s₁ s₃ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 ht1 (Set.mem_of_subset_of_mem h32 ht2)
theorem indep_of_indep_of_le_left {m₁ m₂ m₃ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : Indep m₁ m₂ κ μ) (h31 : m₃ ≤ m₁) :
Indep m₃ m₂ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 (h31 _ ht1) ht2
theorem indep_of_indep_of_le_right {m₁ m₂ m₃ : MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : Indep m₁ m₂ κ μ) (h32 : m₃ ≤ m₂) :
Indep m₁ m₃ κ μ :=
fun t1 t2 ht1 ht2 => h_indep t1 t2 ht1 (h32 _ ht2)
theorem IndepSets.union {s₁ s₂ s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α}
(h₁ : IndepSets s₁ s' κ μ) (h₂ : IndepSets s₂ s' κ μ) :
IndepSets (s₁ ∪ s₂) s' κ μ := by
intro t1 t2 ht1 ht2
cases' (Set.mem_union _ _ _).mp ht1 with ht1₁ ht1₂
· exact h₁ t1 t2 ht1₁ ht2
· exact h₂ t1 t2 ht1₂ ht2
@[simp]
theorem IndepSets.union_iff {s₁ s₂ s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
IndepSets (s₁ ∪ s₂) s' κ μ ↔ IndepSets s₁ s' κ μ ∧ IndepSets s₂ s' κ μ :=
⟨fun h =>
⟨indepSets_of_indepSets_of_le_left h Set.subset_union_left,
indepSets_of_indepSets_of_le_left h Set.subset_union_right⟩,
fun h => IndepSets.union h.left h.right⟩
theorem IndepSets.iUnion {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (hyp : ∀ n, IndepSets (s n) s' κ μ) :
IndepSets (⋃ n, s n) s' κ μ := by
intro t1 t2 ht1 ht2
rw [Set.mem_iUnion] at ht1
cases' ht1 with n ht1
exact hyp n t1 t2 ht1 ht2
theorem IndepSets.bUnion {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {u : Set ι} (hyp : ∀ n ∈ u, IndepSets (s n) s' κ μ) :
IndepSets (⋃ n ∈ u, s n) s' κ μ := by
intro t1 t2 ht1 ht2
simp_rw [Set.mem_iUnion] at ht1
rcases ht1 with ⟨n, hpn, ht1⟩
exact hyp n hpn t1 t2 ht1 ht2
theorem IndepSets.inter {s₁ s' : Set (Set Ω)} (s₂ : Set (Set Ω)) {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h₁ : IndepSets s₁ s' κ μ) :
IndepSets (s₁ ∩ s₂) s' κ μ :=
fun t1 t2 ht1 ht2 => h₁ t1 t2 ((Set.mem_inter_iff _ _ _).mp ht1).left ht2
theorem IndepSets.iInter {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h : ∃ n, IndepSets (s n) s' κ μ) :
IndepSets (⋂ n, s n) s' κ μ := by
intro t1 t2 ht1 ht2; cases' h with n h; exact h t1 t2 (Set.mem_iInter.mp ht1 n) ht2
theorem IndepSets.bInter {s : ι → Set (Set Ω)} {s' : Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {u : Set ι} (h : ∃ n ∈ u, IndepSets (s n) s' κ μ) :
IndepSets (⋂ n ∈ u, s n) s' κ μ := by
intro t1 t2 ht1 ht2
rcases h with ⟨n, hn, h⟩
exact h t1 t2 (Set.biInter_subset_of_mem hn ht1) ht2
theorem iIndep_comap_mem_iff {f : ι → Set Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
iIndep (fun i => MeasurableSpace.comap (· ∈ f i) ⊤) κ μ ↔ iIndepSet f κ μ := by
simp_rw [← generateFrom_singleton, iIndepSet]
theorem iIndepSets_singleton_iff {s : ι → Set Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
iIndepSets (fun i ↦ {s i}) κ μ ↔
∀ S : Finset ι, ∀ᵐ a ∂μ, κ a (⋂ i ∈ S, s i) = ∏ i ∈ S, κ a (s i) := by
refine ⟨fun h S ↦ h S (fun i _ ↦ rfl), fun h S f hf ↦ ?_⟩
filter_upwards [h S] with a ha
have : ∀ i ∈ S, κ a (f i) = κ a (s i) := fun i hi ↦ by rw [hf i hi]
rwa [Finset.prod_congr rfl this, Set.iInter₂_congr hf]
theorem indepSets_singleton_iff {s t : Set Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} :
IndepSets {s} {t} κ μ ↔ ∀ᵐ a ∂μ, κ a (s ∩ t) = κ a s * κ a t :=
⟨fun h ↦ h s t rfl rfl,
fun h s1 t1 hs1 ht1 ↦ by rwa [Set.mem_singleton_iff.mp hs1, Set.mem_singleton_iff.mp ht1]⟩
end Indep
/-! ### Deducing `Indep` from `iIndep` -/
section FromiIndepToIndep
variable {_mα : MeasurableSpace α}
theorem iIndepSets.indepSets {s : ι → Set (Set Ω)} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} (h_indep : iIndepSets s κ μ) {i j : ι} (hij : i ≠ j) :
IndepSets (s i) (s j) κ μ := by
classical
intro t₁ t₂ ht₁ ht₂
have hf_m : ∀ x : ι, x ∈ ({i, j} : Finset ι) → ite (x = i) t₁ t₂ ∈ s x := by
intro x hx
cases' Finset.mem_insert.mp hx with hx hx
· simp [hx, ht₁]
· simp [Finset.mem_singleton.mp hx, hij.symm, ht₂]
have h1 : t₁ = ite (i = i) t₁ t₂ := by simp only [if_true, eq_self_iff_true]
have h2 : t₂ = ite (j = i) t₁ t₂ := by simp only [hij.symm, if_false]
have h_inter : ⋂ (t : ι) (_ : t ∈ ({i, j} : Finset ι)), ite (t = i) t₁ t₂ =
ite (i = i) t₁ t₂ ∩ ite (j = i) t₁ t₂ := by
simp only [Finset.set_biInter_singleton, Finset.set_biInter_insert]
filter_upwards [h_indep {i, j} hf_m] with a h_indep'
have h_prod : (∏ t ∈ ({i, j} : Finset ι), κ a (ite (t = i) t₁ t₂))
= κ a (ite (i = i) t₁ t₂) * κ a (ite (j = i) t₁ t₂) := by
simp only [hij, Finset.prod_singleton, Finset.prod_insert, not_false_iff,
Finset.mem_singleton]
rw [h1]
nth_rw 2 [h2]
nth_rw 4 [h2]
rw [← h_inter, ← h_prod, h_indep']
theorem iIndep.indep {m : ι → MeasurableSpace Ω} {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α}
(h_indep : iIndep m κ μ) {i j : ι} (hij : i ≠ j) : Indep (m i) (m j) κ μ :=
iIndepSets.indepSets h_indep hij
theorem iIndepFun.indepFun {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {β : ι → Type*}
{m : ∀ x, MeasurableSpace (β x)} {f : ∀ i, Ω → β i} (hf_Indep : iIndepFun m f κ μ) {i j : ι}
(hij : i ≠ j) : IndepFun (f i) (f j) κ μ :=
hf_Indep.indep hij
end FromiIndepToIndep
/-!
## π-system lemma
Independence of measurable spaces is equivalent to independence of generating π-systems.
-/
section FromMeasurableSpacesToSetsOfSets
/-! ### Independence of measurable space structures implies independence of generating π-systems -/
variable {_mα : MeasurableSpace α}
theorem iIndep.iIndepSets {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {m : ι → MeasurableSpace Ω}
{s : ι → Set (Set Ω)} (hms : ∀ n, m n = generateFrom (s n)) (h_indep : iIndep m κ μ) :
iIndepSets s κ μ :=
fun S f hfs =>
h_indep S fun x hxS =>
((hms x).symm ▸ measurableSet_generateFrom (hfs x hxS) : MeasurableSet[m x] (f x))
theorem Indep.indepSets {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} {s1 s2 : Set (Set Ω)}
(h_indep : Indep (generateFrom s1) (generateFrom s2) κ μ) :
IndepSets s1 s2 κ μ :=
fun t1 t2 ht1 ht2 =>
h_indep t1 t2 (measurableSet_generateFrom ht1) (measurableSet_generateFrom ht2)
end FromMeasurableSpacesToSetsOfSets
section FromPiSystemsToMeasurableSpaces
/-! ### Independence of generating π-systems implies independence of measurable space structures -/
variable {_mα : MeasurableSpace α}
theorem IndepSets.indep_aux {m₂ m : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ] {p1 p2 : Set (Set Ω)} (h2 : m₂ ≤ m)
(hp2 : IsPiSystem p2) (hpm2 : m₂ = generateFrom p2) (hyp : IndepSets p1 p2 κ μ) {t1 t2 : Set Ω}
(ht1 : t1 ∈ p1) (ht1m : MeasurableSet[m] t1) (ht2m : MeasurableSet[m₂] t2) :
∀ᵐ a ∂μ, κ a (t1 ∩ t2) = κ a t1 * κ a t2 := by
refine @induction_on_inter _ (fun t ↦ ∀ᵐ a ∂μ, κ a (t1 ∩ t) = κ a t1 * κ a t) _
m₂ hpm2 hp2 ?_ ?_ ?_ ?_ t2 ht2m
· simp only [Set.inter_empty, measure_empty, mul_zero, eq_self_iff_true,
Filter.eventually_true]
· exact fun t ht_mem_p2 ↦ hyp t1 t ht1 ht_mem_p2
· intros t ht h
filter_upwards [h] with a ha
have : t1 ∩ tᶜ = t1 \ (t1 ∩ t) := by
rw [Set.diff_self_inter, Set.diff_eq_compl_inter, Set.inter_comm]
rw [this,
measure_diff Set.inter_subset_left (ht1m.inter (h2 _ ht)) (measure_ne_top (κ a) _),
measure_compl (h2 _ ht) (measure_ne_top (κ a) t), measure_univ,
ENNReal.mul_sub (fun _ _ ↦ measure_ne_top (κ a) _), mul_one, ha]
· intros f hf_disj hf_meas h
rw [← ae_all_iff] at h
filter_upwards [h] with a ha
rw [Set.inter_iUnion, measure_iUnion]
· rw [measure_iUnion hf_disj (fun i ↦ h2 _ (hf_meas i))]
rw [← ENNReal.tsum_mul_left]
congr with i
rw [ha i]
· intros i j hij
rw [Function.onFun, Set.inter_comm t1, Set.inter_comm t1]
exact Disjoint.inter_left _ (Disjoint.inter_right _ (hf_disj hij))
· exact fun i ↦ ht1m.inter (h2 _ (hf_meas i))
/-- The measurable space structures generated by independent pi-systems are independent. -/
theorem IndepSets.indep {m1 m2 m : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α}
[IsMarkovKernel κ] {p1 p2 : Set (Set Ω)} (h1 : m1 ≤ m) (h2 : m2 ≤ m) (hp1 : IsPiSystem p1)
(hp2 : IsPiSystem p2) (hpm1 : m1 = generateFrom p1) (hpm2 : m2 = generateFrom p2)
(hyp : IndepSets p1 p2 κ μ) :
Indep m1 m2 κ μ := by
intros t1 t2 ht1 ht2
refine @induction_on_inter _ (fun t ↦ ∀ᵐ (a : α) ∂μ, κ a (t ∩ t2) = κ a t * κ a t2) _ m1 hpm1 hp1
?_ ?_ ?_ ?_ _ ht1
· simp only [Set.empty_inter, measure_empty, zero_mul, eq_self_iff_true,
Filter.eventually_true]
· intros t ht_mem_p1
have ht1 : MeasurableSet[m] t := by
refine h1 _ ?_
rw [hpm1]
exact measurableSet_generateFrom ht_mem_p1
exact IndepSets.indep_aux h2 hp2 hpm2 hyp ht_mem_p1 ht1 ht2
· intros t ht h
filter_upwards [h] with a ha
have : tᶜ ∩ t2 = t2 \ (t ∩ t2) := by
rw [Set.inter_comm t, Set.diff_self_inter, Set.diff_eq_compl_inter]
rw [this, Set.inter_comm t t2,
measure_diff Set.inter_subset_left ((h2 _ ht2).inter (h1 _ ht))
(measure_ne_top (κ a) _),
Set.inter_comm, ha, measure_compl (h1 _ ht) (measure_ne_top (κ a) t), measure_univ,
mul_comm (1 - κ a t), ENNReal.mul_sub (fun _ _ ↦ measure_ne_top (κ a) _), mul_one, mul_comm]
· intros f hf_disj hf_meas h
rw [← ae_all_iff] at h
filter_upwards [h] with a ha
rw [Set.inter_comm, Set.inter_iUnion, measure_iUnion]
· rw [measure_iUnion hf_disj (fun i ↦ h1 _ (hf_meas i))]
rw [← ENNReal.tsum_mul_right]
congr 1 with i
rw [Set.inter_comm t2, ha i]
· intros i j hij
rw [Function.onFun, Set.inter_comm t2, Set.inter_comm t2]
exact Disjoint.inter_left _ (Disjoint.inter_right _ (hf_disj hij))
· exact fun i ↦ (h2 _ ht2).inter (h1 _ (hf_meas i))
theorem IndepSets.indep' {_mΩ : MeasurableSpace Ω}
{κ : kernel α Ω} {μ : Measure α} [IsMarkovKernel κ]
{p1 p2 : Set (Set Ω)} (hp1m : ∀ s ∈ p1, MeasurableSet s) (hp2m : ∀ s ∈ p2, MeasurableSet s)
(hp1 : IsPiSystem p1) (hp2 : IsPiSystem p2) (hyp : IndepSets p1 p2 κ μ) :
Indep (generateFrom p1) (generateFrom p2) κ μ :=
hyp.indep (generateFrom_le hp1m) (generateFrom_le hp2m) hp1 hp2 rfl rfl
variable {_mΩ : MeasurableSpace Ω} {κ : kernel α Ω} {μ : Measure α}
theorem indepSets_piiUnionInter_of_disjoint [IsMarkovKernel κ] {s : ι → Set (Set Ω)}
{S T : Set ι} (h_indep : iIndepSets s κ μ) (hST : Disjoint S T) :
IndepSets (piiUnionInter s S) (piiUnionInter s T) κ μ := by
rintro t1 t2 ⟨p1, hp1, f1, ht1_m, ht1_eq⟩ ⟨p2, hp2, f2, ht2_m, ht2_eq⟩
classical
let g i := ite (i ∈ p1) (f1 i) Set.univ ∩ ite (i ∈ p2) (f2 i) Set.univ
have h_P_inter : ∀ᵐ a ∂μ, κ a (t1 ∩ t2) = ∏ n ∈ p1 ∪ p2, κ a (g n) := by
have hgm : ∀ i ∈ p1 ∪ p2, g i ∈ s i := by
intro i hi_mem_union
rw [Finset.mem_union] at hi_mem_union
cases' hi_mem_union with hi1 hi2
· have hi2 : i ∉ p2 := fun hip2 => Set.disjoint_left.mp hST (hp1 hi1) (hp2 hip2)
simp_rw [g, if_pos hi1, if_neg hi2, Set.inter_univ]
exact ht1_m i hi1
· have hi1 : i ∉ p1 := fun hip1 => Set.disjoint_right.mp hST (hp2 hi2) (hp1 hip1)
simp_rw [g, if_neg hi1, if_pos hi2, Set.univ_inter]
exact ht2_m i hi2
have h_p1_inter_p2 :
((⋂ x ∈ p1, f1 x) ∩ ⋂ x ∈ p2, f2 x) =
⋂ i ∈ p1 ∪ p2, ite (i ∈ p1) (f1 i) Set.univ ∩ ite (i ∈ p2) (f2 i) Set.univ := by
ext1 x
simp only [Set.mem_ite_univ_right, Set.mem_inter_iff, Set.mem_iInter, Finset.mem_union]
exact
⟨fun h i _ => ⟨h.1 i, h.2 i⟩, fun h =>
⟨fun i hi => (h i (Or.inl hi)).1 hi, fun i hi => (h i (Or.inr hi)).2 hi⟩⟩
filter_upwards [h_indep _ hgm] with a ha
rw [ht1_eq, ht2_eq, h_p1_inter_p2, ← ha]
filter_upwards [h_P_inter, h_indep p1 ht1_m, h_indep p2 ht2_m] with a h_P_inter ha1 ha2
have h_μg : ∀ n, κ a (g n) = (ite (n ∈ p1) (κ a (f1 n)) 1) * (ite (n ∈ p2) (κ a (f2 n)) 1) := by
intro n
dsimp only [g]
split_ifs with h1 h2
· exact absurd rfl (Set.disjoint_iff_forall_ne.mp hST (hp1 h1) (hp2 h2))
all_goals simp only [measure_univ, one_mul, mul_one, Set.inter_univ, Set.univ_inter]
simp_rw [h_P_inter, h_μg, Finset.prod_mul_distrib,
Finset.prod_ite_mem (p1 ∪ p2) p1 (fun x ↦ κ a (f1 x)), Finset.union_inter_cancel_left,
Finset.prod_ite_mem (p1 ∪ p2) p2 (fun x => κ a (f2 x)), Finset.union_inter_cancel_right, ht1_eq,
← ha1, ht2_eq, ← ha2]
| Mathlib/Probability/Independence/Kernel.lean | 496 | 508 | theorem iIndepSet.indep_generateFrom_of_disjoint [IsMarkovKernel κ] {s : ι → Set Ω}
(hsm : ∀ n, MeasurableSet (s n)) (hs : iIndepSet s κ μ) (S T : Set ι) (hST : Disjoint S T) :
Indep (generateFrom { t | ∃ n ∈ S, s n = t }) (generateFrom { t | ∃ k ∈ T, s k = t }) κ μ := by |
rw [← generateFrom_piiUnionInter_singleton_left, ← generateFrom_piiUnionInter_singleton_left]
refine
IndepSets.indep'
(fun t ht => generateFrom_piiUnionInter_le _ ?_ _ _ (measurableSet_generateFrom ht))
(fun t ht => generateFrom_piiUnionInter_le _ ?_ _ _ (measurableSet_generateFrom ht)) ?_ ?_ ?_
· exact fun k => generateFrom_le fun t ht => (Set.mem_singleton_iff.1 ht).symm ▸ hsm k
· exact fun k => generateFrom_le fun t ht => (Set.mem_singleton_iff.1 ht).symm ▸ hsm k
· exact isPiSystem_piiUnionInter _ (fun k => IsPiSystem.singleton _) _
· exact isPiSystem_piiUnionInter _ (fun k => IsPiSystem.singleton _) _
· classical exact indepSets_piiUnionInter_of_disjoint (iIndep.iIndepSets (fun n => rfl) hs) hST
|
/-
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]
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]
#align measure_theory.integrable_with_density_iff_integrable_coe_smul MeasureTheory.integrable_withDensity_iff_integrable_coe_smul
theorem integrable_withDensity_iff_integrable_smul {f : α → ℝ≥0} (hf : Measurable f) {g : α → E} :
Integrable g (μ.withDensity fun x => f x) ↔ Integrable (fun x => f x • g x) μ :=
integrable_withDensity_iff_integrable_coe_smul hf
#align measure_theory.integrable_with_density_iff_integrable_smul MeasureTheory.integrable_withDensity_iff_integrable_smul
theorem integrable_withDensity_iff_integrable_smul' {f : α → ℝ≥0∞} (hf : Measurable f)
(hflt : ∀ᵐ x ∂μ, f x < ∞) {g : α → E} :
Integrable g (μ.withDensity f) ↔ Integrable (fun x => (f x).toReal • g x) μ := by
rw [← withDensity_congr_ae (coe_toNNReal_ae_eq hflt),
integrable_withDensity_iff_integrable_smul]
· simp_rw [NNReal.smul_def, ENNReal.toReal]
· exact hf.ennreal_toNNReal
#align measure_theory.integrable_with_density_iff_integrable_smul' MeasureTheory.integrable_withDensity_iff_integrable_smul'
theorem integrable_withDensity_iff_integrable_coe_smul₀ {f : α → ℝ≥0} (hf : AEMeasurable f μ)
{g : α → E} :
Integrable g (μ.withDensity fun x => f x) ↔ Integrable (fun x => (f x : ℝ) • g x) μ :=
calc
Integrable g (μ.withDensity fun x => f x) ↔
Integrable g (μ.withDensity fun x => (hf.mk f x : ℝ≥0)) := by
suffices (fun x => (f x : ℝ≥0∞)) =ᵐ[μ] (fun x => (hf.mk f x : ℝ≥0)) by
rw [withDensity_congr_ae this]
filter_upwards [hf.ae_eq_mk] with x hx
simp [hx]
_ ↔ Integrable (fun x => ((hf.mk f x : ℝ≥0) : ℝ) • g x) μ :=
integrable_withDensity_iff_integrable_coe_smul hf.measurable_mk
_ ↔ Integrable (fun x => (f x : ℝ) • g x) μ := by
apply integrable_congr
filter_upwards [hf.ae_eq_mk] with x hx
simp [hx]
#align measure_theory.integrable_with_density_iff_integrable_coe_smul₀ MeasureTheory.integrable_withDensity_iff_integrable_coe_smul₀
theorem integrable_withDensity_iff_integrable_smul₀ {f : α → ℝ≥0} (hf : AEMeasurable f μ)
{g : α → E} : Integrable g (μ.withDensity fun x => f x) ↔ Integrable (fun x => f x • g x) μ :=
integrable_withDensity_iff_integrable_coe_smul₀ hf
#align measure_theory.integrable_with_density_iff_integrable_smul₀ MeasureTheory.integrable_withDensity_iff_integrable_smul₀
end
theorem integrable_withDensity_iff {f : α → ℝ≥0∞} (hf : Measurable f) (hflt : ∀ᵐ x ∂μ, f x < ∞)
{g : α → ℝ} : Integrable g (μ.withDensity f) ↔ Integrable (fun x => g x * (f x).toReal) μ := by
have : (fun x => g x * (f x).toReal) = fun x => (f x).toReal • g x := by simp [mul_comm]
rw [this]
exact integrable_withDensity_iff_integrable_smul' hf hflt
#align measure_theory.integrable_with_density_iff MeasureTheory.integrable_withDensity_iff
section
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
theorem memℒ1_smul_of_L1_withDensity {f : α → ℝ≥0} (f_meas : Measurable f)
(u : Lp E 1 (μ.withDensity fun x => f x)) : Memℒp (fun x => f x • u x) 1 μ :=
memℒp_one_iff_integrable.2 <|
(integrable_withDensity_iff_integrable_smul f_meas).1 <| memℒp_one_iff_integrable.1 (Lp.memℒp u)
set_option linter.uppercaseLean3 false in
#align measure_theory.mem_ℒ1_smul_of_L1_with_density MeasureTheory.memℒ1_smul_of_L1_withDensity
variable (μ)
/-- The map `u ↦ f • u` is an isometry between the `L^1` spaces for `μ.withDensity f` and `μ`. -/
noncomputable def withDensitySMulLI {f : α → ℝ≥0} (f_meas : Measurable f) :
Lp E 1 (μ.withDensity fun x => f x) →ₗᵢ[ℝ] Lp E 1 μ where
toFun u := (memℒ1_smul_of_L1_withDensity f_meas u).toLp _
map_add' := by
intro u v
ext1
filter_upwards [(memℒ1_smul_of_L1_withDensity f_meas u).coeFn_toLp,
(memℒ1_smul_of_L1_withDensity f_meas v).coeFn_toLp,
(memℒ1_smul_of_L1_withDensity f_meas (u + v)).coeFn_toLp,
Lp.coeFn_add ((memℒ1_smul_of_L1_withDensity f_meas u).toLp _)
((memℒ1_smul_of_L1_withDensity f_meas v).toLp _),
(ae_withDensity_iff f_meas.coe_nnreal_ennreal).1 (Lp.coeFn_add u v)]
intro x hu hv huv h' h''
rw [huv, h', Pi.add_apply, hu, hv]
rcases eq_or_ne (f x) 0 with (hx | hx)
· simp only [hx, zero_smul, add_zero]
· rw [h'' _, Pi.add_apply, smul_add]
simpa only [Ne, ENNReal.coe_eq_zero] using hx
map_smul' := by
intro r u
ext1
filter_upwards [(ae_withDensity_iff f_meas.coe_nnreal_ennreal).1 (Lp.coeFn_smul r u),
(memℒ1_smul_of_L1_withDensity f_meas (r • u)).coeFn_toLp,
Lp.coeFn_smul r ((memℒ1_smul_of_L1_withDensity f_meas u).toLp _),
(memℒ1_smul_of_L1_withDensity f_meas u).coeFn_toLp]
intro x h h' h'' h'''
rw [RingHom.id_apply, h', h'', Pi.smul_apply, h''']
rcases eq_or_ne (f x) 0 with (hx | hx)
· simp only [hx, zero_smul, smul_zero]
· rw [h _, smul_comm, Pi.smul_apply]
simpa only [Ne, ENNReal.coe_eq_zero] using hx
norm_map' := by
intro u
-- Porting note: Lean can't infer types of `AddHom.coe_mk`.
simp only [snorm, LinearMap.coe_mk,
AddHom.coe_mk (M := Lp E 1 (μ.withDensity fun x => f x)) (N := Lp E 1 μ), Lp.norm_toLp,
one_ne_zero, ENNReal.one_ne_top, ENNReal.one_toReal, if_false, snorm', ENNReal.rpow_one,
_root_.div_one, Lp.norm_def]
rw [lintegral_withDensity_eq_lintegral_mul_non_measurable _ f_meas.coe_nnreal_ennreal
(Filter.eventually_of_forall fun x => ENNReal.coe_lt_top)]
congr 1
apply lintegral_congr_ae
filter_upwards [(memℒ1_smul_of_L1_withDensity f_meas u).coeFn_toLp] with x hx
rw [hx, Pi.mul_apply]
change (‖(f x : ℝ) • u x‖₊ : ℝ≥0∞) = (f x : ℝ≥0∞) * (‖u x‖₊ : ℝ≥0∞)
simp only [nnnorm_smul, NNReal.nnnorm_eq, ENNReal.coe_mul]
#align measure_theory.with_density_smul_li MeasureTheory.withDensitySMulLI
@[simp]
theorem withDensitySMulLI_apply {f : α → ℝ≥0} (f_meas : Measurable f)
(u : Lp E 1 (μ.withDensity fun x => f x)) :
withDensitySMulLI μ (E := E) f_meas u =
(memℒ1_smul_of_L1_withDensity f_meas u).toLp fun x => f x • u x :=
rfl
#align measure_theory.with_density_smul_li_apply MeasureTheory.withDensitySMulLI_apply
end
theorem mem_ℒ1_toReal_of_lintegral_ne_top {f : α → ℝ≥0∞} (hfm : AEMeasurable f μ)
(hfi : (∫⁻ x, f x ∂μ) ≠ ∞) : Memℒp (fun x => (f x).toReal) 1 μ := by
rw [Memℒp, snorm_one_eq_lintegral_nnnorm]
exact
⟨(AEMeasurable.ennreal_toReal hfm).aestronglyMeasurable,
hasFiniteIntegral_toReal_of_lintegral_ne_top hfi⟩
#align measure_theory.mem_ℒ1_to_real_of_lintegral_ne_top MeasureTheory.mem_ℒ1_toReal_of_lintegral_ne_top
theorem integrable_toReal_of_lintegral_ne_top {f : α → ℝ≥0∞} (hfm : AEMeasurable f μ)
(hfi : (∫⁻ x, f x ∂μ) ≠ ∞) : Integrable (fun x => (f x).toReal) μ :=
memℒp_one_iff_integrable.1 <| mem_ℒ1_toReal_of_lintegral_ne_top hfm hfi
#align measure_theory.integrable_to_real_of_lintegral_ne_top MeasureTheory.integrable_toReal_of_lintegral_ne_top
section PosPart
/-! ### Lemmas used for defining the positive part of an `L¹` function -/
theorem Integrable.pos_part {f : α → ℝ} (hf : Integrable f μ) :
Integrable (fun a => max (f a) 0) μ :=
⟨(hf.aestronglyMeasurable.aemeasurable.max aemeasurable_const).aestronglyMeasurable,
hf.hasFiniteIntegral.max_zero⟩
#align measure_theory.integrable.pos_part MeasureTheory.Integrable.pos_part
theorem Integrable.neg_part {f : α → ℝ} (hf : Integrable f μ) :
Integrable (fun a => max (-f a) 0) μ :=
hf.neg.pos_part
#align measure_theory.integrable.neg_part MeasureTheory.Integrable.neg_part
end PosPart
section BoundedSMul
variable {𝕜 : Type*}
theorem Integrable.smul [NormedAddCommGroup 𝕜] [SMulZeroClass 𝕜 β] [BoundedSMul 𝕜 β] (c : 𝕜)
{f : α → β} (hf : Integrable f μ) : Integrable (c • f) μ :=
⟨hf.aestronglyMeasurable.const_smul c, hf.hasFiniteIntegral.smul c⟩
#align measure_theory.integrable.smul MeasureTheory.Integrable.smul
theorem _root_.IsUnit.integrable_smul_iff [NormedRing 𝕜] [Module 𝕜 β] [BoundedSMul 𝕜 β] {c : 𝕜}
(hc : IsUnit c) (f : α → β) : Integrable (c • f) μ ↔ Integrable f μ :=
and_congr hc.aestronglyMeasurable_const_smul_iff (hasFiniteIntegral_smul_iff hc f)
#align measure_theory.is_unit.integrable_smul_iff IsUnit.integrable_smul_iff
theorem integrable_smul_iff [NormedDivisionRing 𝕜] [Module 𝕜 β] [BoundedSMul 𝕜 β] {c : 𝕜}
(hc : c ≠ 0) (f : α → β) : Integrable (c • f) μ ↔ Integrable f μ :=
(IsUnit.mk0 _ hc).integrable_smul_iff f
#align measure_theory.integrable_smul_iff MeasureTheory.integrable_smul_iff
variable [NormedRing 𝕜] [Module 𝕜 β] [BoundedSMul 𝕜 β]
theorem Integrable.smul_of_top_right {f : α → β} {φ : α → 𝕜} (hf : Integrable f μ)
(hφ : Memℒp φ ∞ μ) : Integrable (φ • f) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact Memℒp.smul_of_top_right hf hφ
#align measure_theory.integrable.smul_of_top_right MeasureTheory.Integrable.smul_of_top_right
theorem Integrable.smul_of_top_left {f : α → β} {φ : α → 𝕜} (hφ : Integrable φ μ)
(hf : Memℒp f ∞ μ) : Integrable (φ • f) μ := by
rw [← memℒp_one_iff_integrable] at hφ ⊢
exact Memℒp.smul_of_top_left hf hφ
#align measure_theory.integrable.smul_of_top_left MeasureTheory.Integrable.smul_of_top_left
theorem Integrable.smul_const {f : α → 𝕜} (hf : Integrable f μ) (c : β) :
Integrable (fun x => f x • c) μ :=
hf.smul_of_top_left (memℒp_top_const c)
#align measure_theory.integrable.smul_const MeasureTheory.Integrable.smul_const
end BoundedSMul
section NormedSpaceOverCompleteField
variable {𝕜 : Type*} [NontriviallyNormedField 𝕜] [CompleteSpace 𝕜]
variable {E : Type*} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
theorem integrable_smul_const {f : α → 𝕜} {c : E} (hc : c ≠ 0) :
Integrable (fun x => f x • c) μ ↔ Integrable f μ := by
simp_rw [Integrable, aestronglyMeasurable_smul_const_iff (f := f) hc, and_congr_right_iff,
HasFiniteIntegral, nnnorm_smul, ENNReal.coe_mul]
intro _; rw [lintegral_mul_const' _ _ ENNReal.coe_ne_top, ENNReal.mul_lt_top_iff]
have : ∀ x : ℝ≥0∞, x = 0 → x < ∞ := by simp
simp [hc, or_iff_left_of_imp (this _)]
#align measure_theory.integrable_smul_const MeasureTheory.integrable_smul_const
end NormedSpaceOverCompleteField
section NormedRing
variable {𝕜 : Type*} [NormedRing 𝕜] {f : α → 𝕜}
theorem Integrable.const_mul {f : α → 𝕜} (h : Integrable f μ) (c : 𝕜) :
Integrable (fun x => c * f x) μ :=
h.smul c
#align measure_theory.integrable.const_mul MeasureTheory.Integrable.const_mul
theorem Integrable.const_mul' {f : α → 𝕜} (h : Integrable f μ) (c : 𝕜) :
Integrable ((fun _ : α => c) * f) μ :=
Integrable.const_mul h c
#align measure_theory.integrable.const_mul' MeasureTheory.Integrable.const_mul'
theorem Integrable.mul_const {f : α → 𝕜} (h : Integrable f μ) (c : 𝕜) :
Integrable (fun x => f x * c) μ :=
h.smul (MulOpposite.op c)
#align measure_theory.integrable.mul_const MeasureTheory.Integrable.mul_const
theorem Integrable.mul_const' {f : α → 𝕜} (h : Integrable f μ) (c : 𝕜) :
Integrable (f * fun _ : α => c) μ :=
Integrable.mul_const h c
#align measure_theory.integrable.mul_const' MeasureTheory.Integrable.mul_const'
theorem integrable_const_mul_iff {c : 𝕜} (hc : IsUnit c) (f : α → 𝕜) :
Integrable (fun x => c * f x) μ ↔ Integrable f μ :=
hc.integrable_smul_iff f
#align measure_theory.integrable_const_mul_iff MeasureTheory.integrable_const_mul_iff
theorem integrable_mul_const_iff {c : 𝕜} (hc : IsUnit c) (f : α → 𝕜) :
Integrable (fun x => f x * c) μ ↔ Integrable f μ :=
hc.op.integrable_smul_iff f
#align measure_theory.integrable_mul_const_iff MeasureTheory.integrable_mul_const_iff
theorem Integrable.bdd_mul' {f g : α → 𝕜} {c : ℝ} (hg : Integrable g μ)
(hf : AEStronglyMeasurable f μ) (hf_bound : ∀ᵐ x ∂μ, ‖f x‖ ≤ c) :
Integrable (fun x => f x * g x) μ := by
refine Integrable.mono' (hg.norm.smul c) (hf.mul hg.1) ?_
filter_upwards [hf_bound] with x hx
rw [Pi.smul_apply, smul_eq_mul]
exact (norm_mul_le _ _).trans (mul_le_mul_of_nonneg_right hx (norm_nonneg _))
#align measure_theory.integrable.bdd_mul' MeasureTheory.Integrable.bdd_mul'
end NormedRing
section NormedDivisionRing
variable {𝕜 : Type*} [NormedDivisionRing 𝕜] {f : α → 𝕜}
theorem Integrable.div_const {f : α → 𝕜} (h : Integrable f μ) (c : 𝕜) :
Integrable (fun x => f x / c) μ := by simp_rw [div_eq_mul_inv, h.mul_const]
#align measure_theory.integrable.div_const MeasureTheory.Integrable.div_const
end NormedDivisionRing
section RCLike
variable {𝕜 : Type*} [RCLike 𝕜] {f : α → 𝕜}
theorem Integrable.ofReal {f : α → ℝ} (hf : Integrable f μ) :
Integrable (fun x => (f x : 𝕜)) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact hf.ofReal
#align measure_theory.integrable.of_real MeasureTheory.Integrable.ofReal
theorem Integrable.re_im_iff :
Integrable (fun x => RCLike.re (f x)) μ ∧ Integrable (fun x => RCLike.im (f x)) μ ↔
Integrable f μ := by
simp_rw [← memℒp_one_iff_integrable]
exact memℒp_re_im_iff
#align measure_theory.integrable.re_im_iff MeasureTheory.Integrable.re_im_iff
theorem Integrable.re (hf : Integrable f μ) : Integrable (fun x => RCLike.re (f x)) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact hf.re
#align measure_theory.integrable.re MeasureTheory.Integrable.re
theorem Integrable.im (hf : Integrable f μ) : Integrable (fun x => RCLike.im (f x)) μ := by
rw [← memℒp_one_iff_integrable] at hf ⊢
exact hf.im
#align measure_theory.integrable.im MeasureTheory.Integrable.im
end RCLike
section Trim
variable {H : Type*} [NormedAddCommGroup H] {m0 : MeasurableSpace α} {μ' : Measure α} {f : α → H}
theorem Integrable.trim (hm : m ≤ m0) (hf_int : Integrable f μ') (hf : StronglyMeasurable[m] f) :
Integrable f (μ'.trim hm) := by
refine ⟨hf.aestronglyMeasurable, ?_⟩
rw [HasFiniteIntegral, lintegral_trim hm _]
· exact hf_int.2
· exact @StronglyMeasurable.ennnorm _ m _ _ f hf
#align measure_theory.integrable.trim MeasureTheory.Integrable.trim
theorem integrable_of_integrable_trim (hm : m ≤ m0) (hf_int : Integrable f (μ'.trim hm)) :
Integrable f μ' := by
obtain ⟨hf_meas_ae, hf⟩ := hf_int
refine ⟨aestronglyMeasurable_of_aestronglyMeasurable_trim hm hf_meas_ae, ?_⟩
rw [HasFiniteIntegral] at hf ⊢
rwa [lintegral_trim_ae hm _] at hf
exact AEStronglyMeasurable.ennnorm hf_meas_ae
#align measure_theory.integrable_of_integrable_trim MeasureTheory.integrable_of_integrable_trim
end Trim
section SigmaFinite
variable {E : Type*} {m0 : MeasurableSpace α} [NormedAddCommGroup E]
theorem integrable_of_forall_fin_meas_le' {μ : Measure α} (hm : m ≤ m0) [SigmaFinite (μ.trim hm)]
(C : ℝ≥0∞) (hC : C < ∞) {f : α → E} (hf_meas : AEStronglyMeasurable f μ)
(hf : ∀ s, MeasurableSet[m] s → μ s ≠ ∞ → (∫⁻ x in s, ‖f x‖₊ ∂μ) ≤ C) : Integrable f μ :=
⟨hf_meas, (lintegral_le_of_forall_fin_meas_le' hm C hf_meas.ennnorm hf).trans_lt hC⟩
#align measure_theory.integrable_of_forall_fin_meas_le' MeasureTheory.integrable_of_forall_fin_meas_le'
theorem integrable_of_forall_fin_meas_le [SigmaFinite μ] (C : ℝ≥0∞) (hC : C < ∞) {f : α → E}
(hf_meas : AEStronglyMeasurable f μ)
(hf : ∀ s : Set α, MeasurableSet[m] s → μ s ≠ ∞ → (∫⁻ x in s, ‖f x‖₊ ∂μ) ≤ C) :
Integrable f μ :=
@integrable_of_forall_fin_meas_le' _ m _ m _ _ _ (by rwa [@trim_eq_self _ m]) C hC _ hf_meas hf
#align measure_theory.integrable_of_forall_fin_meas_le MeasureTheory.integrable_of_forall_fin_meas_le
end SigmaFinite
/-! ### The predicate `Integrable` on measurable functions modulo a.e.-equality -/
namespace AEEqFun
section
/-- A class of almost everywhere equal functions is `Integrable` if its function representative
is integrable. -/
def Integrable (f : α →ₘ[μ] β) : Prop :=
MeasureTheory.Integrable f μ
#align measure_theory.ae_eq_fun.integrable MeasureTheory.AEEqFun.Integrable
theorem integrable_mk {f : α → β} (hf : AEStronglyMeasurable f μ) :
Integrable (mk f hf : α →ₘ[μ] β) ↔ MeasureTheory.Integrable f μ := by
simp only [Integrable]
apply integrable_congr
exact coeFn_mk f hf
#align measure_theory.ae_eq_fun.integrable_mk MeasureTheory.AEEqFun.integrable_mk
theorem integrable_coeFn {f : α →ₘ[μ] β} : MeasureTheory.Integrable f μ ↔ Integrable f := by
rw [← integrable_mk, mk_coeFn]
#align measure_theory.ae_eq_fun.integrable_coe_fn MeasureTheory.AEEqFun.integrable_coeFn
theorem integrable_zero : Integrable (0 : α →ₘ[μ] β) :=
(MeasureTheory.integrable_zero α β μ).congr (coeFn_mk _ _).symm
#align measure_theory.ae_eq_fun.integrable_zero MeasureTheory.AEEqFun.integrable_zero
end
section
theorem Integrable.neg {f : α →ₘ[μ] β} : Integrable f → Integrable (-f) :=
induction_on f fun _f hfm hfi => (integrable_mk _).2 ((integrable_mk hfm).1 hfi).neg
#align measure_theory.ae_eq_fun.integrable.neg MeasureTheory.AEEqFun.Integrable.neg
section
theorem integrable_iff_mem_L1 {f : α →ₘ[μ] β} : Integrable f ↔ f ∈ (α →₁[μ] β) := by
rw [← integrable_coeFn, ← memℒp_one_iff_integrable, Lp.mem_Lp_iff_memℒp]
set_option linter.uppercaseLean3 false in
#align measure_theory.ae_eq_fun.integrable_iff_mem_L1 MeasureTheory.AEEqFun.integrable_iff_mem_L1
theorem Integrable.add {f g : α →ₘ[μ] β} : Integrable f → Integrable g → Integrable (f + g) := by
refine induction_on₂ f g fun f hf g hg hfi hgi => ?_
simp only [integrable_mk, mk_add_mk] at hfi hgi ⊢
exact hfi.add hgi
#align measure_theory.ae_eq_fun.integrable.add MeasureTheory.AEEqFun.Integrable.add
theorem Integrable.sub {f g : α →ₘ[μ] β} (hf : Integrable f) (hg : Integrable g) :
Integrable (f - g) :=
(sub_eq_add_neg f g).symm ▸ hf.add hg.neg
#align measure_theory.ae_eq_fun.integrable.sub MeasureTheory.AEEqFun.Integrable.sub
end
section BoundedSMul
variable {𝕜 : Type*} [NormedRing 𝕜] [Module 𝕜 β] [BoundedSMul 𝕜 β]
theorem Integrable.smul {c : 𝕜} {f : α →ₘ[μ] β} : Integrable f → Integrable (c • f) :=
induction_on f fun _f hfm hfi => (integrable_mk _).2 <|
by simpa using ((integrable_mk hfm).1 hfi).smul c
#align measure_theory.ae_eq_fun.integrable.smul MeasureTheory.AEEqFun.Integrable.smul
end BoundedSMul
end
end AEEqFun
namespace L1
set_option linter.uppercaseLean3 false
theorem integrable_coeFn (f : α →₁[μ] β) : Integrable f μ := by
rw [← memℒp_one_iff_integrable]
exact Lp.memℒp f
#align measure_theory.L1.integrable_coe_fn MeasureTheory.L1.integrable_coeFn
theorem hasFiniteIntegral_coeFn (f : α →₁[μ] β) : HasFiniteIntegral f μ :=
(integrable_coeFn f).hasFiniteIntegral
#align measure_theory.L1.has_finite_integral_coe_fn MeasureTheory.L1.hasFiniteIntegral_coeFn
theorem stronglyMeasurable_coeFn (f : α →₁[μ] β) : StronglyMeasurable f :=
Lp.stronglyMeasurable f
#align measure_theory.L1.strongly_measurable_coe_fn MeasureTheory.L1.stronglyMeasurable_coeFn
theorem measurable_coeFn [MeasurableSpace β] [BorelSpace β] (f : α →₁[μ] β) : Measurable f :=
(Lp.stronglyMeasurable f).measurable
#align measure_theory.L1.measurable_coe_fn MeasureTheory.L1.measurable_coeFn
theorem aestronglyMeasurable_coeFn (f : α →₁[μ] β) : AEStronglyMeasurable f μ :=
Lp.aestronglyMeasurable f
#align measure_theory.L1.ae_strongly_measurable_coe_fn MeasureTheory.L1.aestronglyMeasurable_coeFn
theorem aemeasurable_coeFn [MeasurableSpace β] [BorelSpace β] (f : α →₁[μ] β) : AEMeasurable f μ :=
(Lp.stronglyMeasurable f).measurable.aemeasurable
#align measure_theory.L1.ae_measurable_coe_fn MeasureTheory.L1.aemeasurable_coeFn
theorem edist_def (f g : α →₁[μ] β) : edist f g = ∫⁻ a, edist (f a) (g a) ∂μ := by
simp only [Lp.edist_def, snorm, one_ne_zero, snorm', Pi.sub_apply, one_toReal, ENNReal.rpow_one,
ne_eq, not_false_eq_true, div_self, ite_false]
simp [edist_eq_coe_nnnorm_sub]
#align measure_theory.L1.edist_def MeasureTheory.L1.edist_def
theorem dist_def (f g : α →₁[μ] β) : dist f g = (∫⁻ a, edist (f a) (g a) ∂μ).toReal := by
simp only [Lp.dist_def, snorm, one_ne_zero, snorm', Pi.sub_apply, one_toReal, ENNReal.rpow_one,
ne_eq, not_false_eq_true, div_self, ite_false]
simp [edist_eq_coe_nnnorm_sub]
#align measure_theory.L1.dist_def MeasureTheory.L1.dist_def
theorem norm_def (f : α →₁[μ] β) : ‖f‖ = (∫⁻ a, ‖f a‖₊ ∂μ).toReal := by
simp [Lp.norm_def, snorm, snorm']
#align measure_theory.L1.norm_def MeasureTheory.L1.norm_def
/-- Computing the norm of a difference between two L¹-functions. Note that this is not a
special case of `norm_def` since `(f - g) x` and `f x - g x` are not equal
(but only a.e.-equal). -/
theorem norm_sub_eq_lintegral (f g : α →₁[μ] β) :
‖f - g‖ = (∫⁻ x, (‖f x - g x‖₊ : ℝ≥0∞) ∂μ).toReal := by
rw [norm_def]
congr 1
rw [lintegral_congr_ae]
filter_upwards [Lp.coeFn_sub f g] with _ ha
simp only [ha, Pi.sub_apply]
#align measure_theory.L1.norm_sub_eq_lintegral MeasureTheory.L1.norm_sub_eq_lintegral
theorem ofReal_norm_eq_lintegral (f : α →₁[μ] β) :
ENNReal.ofReal ‖f‖ = ∫⁻ x, (‖f x‖₊ : ℝ≥0∞) ∂μ := by
rw [norm_def, ENNReal.ofReal_toReal]
exact ne_of_lt (hasFiniteIntegral_coeFn f)
#align measure_theory.L1.of_real_norm_eq_lintegral MeasureTheory.L1.ofReal_norm_eq_lintegral
/-- Computing the norm of a difference between two L¹-functions. Note that this is not a
special case of `ofReal_norm_eq_lintegral` since `(f - g) x` and `f x - g x` are not equal
(but only a.e.-equal). -/
| Mathlib/MeasureTheory/Function/L1Space.lean | 1,431 | 1,436 | theorem ofReal_norm_sub_eq_lintegral (f g : α →₁[μ] β) :
ENNReal.ofReal ‖f - g‖ = ∫⁻ x, (‖f x - g x‖₊ : ℝ≥0∞) ∂μ := by |
simp_rw [ofReal_norm_eq_lintegral, ← edist_eq_coe_nnnorm]
apply lintegral_congr_ae
filter_upwards [Lp.coeFn_sub f g] with _ ha
simp only [ha, Pi.sub_apply]
|
/-
Copyright (c) 2022 Floris van Doorn, Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Floris van Doorn, Heather Macbeth
-/
import Mathlib.Geometry.Manifold.ContMDiff.NormedSpace
#align_import geometry.manifold.vector_bundle.fiberwise_linear from "leanprover-community/mathlib"@"be2c24f56783935652cefffb4bfca7e4b25d167e"
/-! # The groupoid of smooth, fiberwise-linear maps
This file contains preliminaries for the definition of a smooth vector bundle: an associated
`StructureGroupoid`, the groupoid of `smoothFiberwiseLinear` functions.
-/
noncomputable section
open Set TopologicalSpace
open scoped Manifold Topology
/-! ### The groupoid of smooth, fiberwise-linear maps -/
variable {𝕜 B F : Type*} [TopologicalSpace B]
variable [NontriviallyNormedField 𝕜] [NormedAddCommGroup F] [NormedSpace 𝕜 F]
namespace FiberwiseLinear
variable {φ φ' : B → F ≃L[𝕜] F} {U U' : Set B}
/-- For `B` a topological space and `F` a `𝕜`-normed space, a map from `U : Set B` to `F ≃L[𝕜] F`
determines a partial homeomorphism from `B × F` to itself by its action fiberwise. -/
def partialHomeomorph (φ : B → F ≃L[𝕜] F) (hU : IsOpen U)
(hφ : ContinuousOn (fun x => φ x : B → F →L[𝕜] F) U)
(h2φ : ContinuousOn (fun x => (φ x).symm : B → F →L[𝕜] F) U) :
PartialHomeomorph (B × F) (B × F) where
toFun x := (x.1, φ x.1 x.2)
invFun x := (x.1, (φ x.1).symm x.2)
source := U ×ˢ univ
target := U ×ˢ univ
map_source' _x hx := mk_mem_prod hx.1 (mem_univ _)
map_target' _x hx := mk_mem_prod hx.1 (mem_univ _)
left_inv' _ _ := Prod.ext rfl (ContinuousLinearEquiv.symm_apply_apply _ _)
right_inv' _ _ := Prod.ext rfl (ContinuousLinearEquiv.apply_symm_apply _ _)
open_source := hU.prod isOpen_univ
open_target := hU.prod isOpen_univ
continuousOn_toFun :=
have : ContinuousOn (fun p : B × F => ((φ p.1 : F →L[𝕜] F), p.2)) (U ×ˢ univ) :=
hφ.prod_map continuousOn_id
continuousOn_fst.prod (isBoundedBilinearMap_apply.continuous.comp_continuousOn this)
continuousOn_invFun :=
haveI : ContinuousOn (fun p : B × F => (((φ p.1).symm : F →L[𝕜] F), p.2)) (U ×ˢ univ) :=
h2φ.prod_map continuousOn_id
continuousOn_fst.prod (isBoundedBilinearMap_apply.continuous.comp_continuousOn this)
#align fiberwise_linear.local_homeomorph FiberwiseLinear.partialHomeomorph
/-- Compute the composition of two partial homeomorphisms induced by fiberwise linear
equivalences. -/
theorem trans_partialHomeomorph_apply (hU : IsOpen U)
(hφ : ContinuousOn (fun x => φ x : B → F →L[𝕜] F) U)
(h2φ : ContinuousOn (fun x => (φ x).symm : B → F →L[𝕜] F) U) (hU' : IsOpen U')
(hφ' : ContinuousOn (fun x => φ' x : B → F →L[𝕜] F) U')
(h2φ' : ContinuousOn (fun x => (φ' x).symm : B → F →L[𝕜] F) U') (b : B) (v : F) :
(FiberwiseLinear.partialHomeomorph φ hU hφ h2φ ≫ₕ
FiberwiseLinear.partialHomeomorph φ' hU' hφ' h2φ')
⟨b, v⟩ =
⟨b, φ' b (φ b v)⟩ :=
rfl
#align fiberwise_linear.trans_local_homeomorph_apply FiberwiseLinear.trans_partialHomeomorph_apply
/-- Compute the source of the composition of two partial homeomorphisms induced by fiberwise linear
equivalences. -/
| Mathlib/Geometry/Manifold/VectorBundle/FiberwiseLinear.lean | 74 | 82 | theorem source_trans_partialHomeomorph (hU : IsOpen U)
(hφ : ContinuousOn (fun x => φ x : B → F →L[𝕜] F) U)
(h2φ : ContinuousOn (fun x => (φ x).symm : B → F →L[𝕜] F) U) (hU' : IsOpen U')
(hφ' : ContinuousOn (fun x => φ' x : B → F →L[𝕜] F) U')
(h2φ' : ContinuousOn (fun x => (φ' x).symm : B → F →L[𝕜] F) U') :
(FiberwiseLinear.partialHomeomorph φ hU hφ h2φ ≫ₕ
FiberwiseLinear.partialHomeomorph φ' hU' hφ' h2φ').source =
(U ∩ U') ×ˢ univ := by |
dsimp only [FiberwiseLinear.partialHomeomorph]; mfld_set_tac
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Finset.Image
import Mathlib.Data.List.FinRange
#align_import data.fintype.basic from "leanprover-community/mathlib"@"d78597269638367c3863d40d45108f52207e03cf"
/-!
# Finite types
This file defines a typeclass to state that a type is finite.
## Main declarations
* `Fintype α`: Typeclass saying that a type is finite. It takes as fields a `Finset` and a proof
that all terms of type `α` are in it.
* `Finset.univ`: The finset of all elements of a fintype.
See `Data.Fintype.Card` for the cardinality of a fintype,
the equivalence with `Fin (Fintype.card α)`, and pigeonhole principles.
## Instances
Instances for `Fintype` for
* `{x // p x}` are in this file as `Fintype.subtype`
* `Option α` are in `Data.Fintype.Option`
* `α × β` are in `Data.Fintype.Prod`
* `α ⊕ β` are in `Data.Fintype.Sum`
* `Σ (a : α), β a` are in `Data.Fintype.Sigma`
These files also contain appropriate `Infinite` instances for these types.
`Infinite` instances for `ℕ`, `ℤ`, `Multiset α`, and `List α` are in `Data.Fintype.Lattice`.
Types which have a surjection from/an injection to a `Fintype` are themselves fintypes.
See `Fintype.ofInjective` and `Fintype.ofSurjective`.
-/
assert_not_exists MonoidWithZero
assert_not_exists MulAction
open Function
open Nat
universe u v
variable {α β γ : Type*}
/-- `Fintype α` means that `α` is finite, i.e. there are only
finitely many distinct elements of type `α`. The evidence of this
is a finset `elems` (a list up to permutation without duplicates),
together with a proof that everything of type `α` is in the list. -/
class Fintype (α : Type*) where
/-- The `Finset` containing all elements of a `Fintype` -/
elems : Finset α
/-- A proof that `elems` contains every element of the type -/
complete : ∀ x : α, x ∈ elems
#align fintype Fintype
namespace Finset
variable [Fintype α] {s t : Finset α}
/-- `univ` is the universal finite set of type `Finset α` implied from
the assumption `Fintype α`. -/
def univ : Finset α :=
@Fintype.elems α _
#align finset.univ Finset.univ
@[simp]
theorem mem_univ (x : α) : x ∈ (univ : Finset α) :=
Fintype.complete x
#align finset.mem_univ Finset.mem_univ
-- Porting note: removing @[simp], simp can prove it
theorem mem_univ_val : ∀ x, x ∈ (univ : Finset α).1 :=
mem_univ
#align finset.mem_univ_val Finset.mem_univ_val
theorem eq_univ_iff_forall : s = univ ↔ ∀ x, x ∈ s := by simp [ext_iff]
#align finset.eq_univ_iff_forall Finset.eq_univ_iff_forall
theorem eq_univ_of_forall : (∀ x, x ∈ s) → s = univ :=
eq_univ_iff_forall.2
#align finset.eq_univ_of_forall Finset.eq_univ_of_forall
@[simp, norm_cast]
theorem coe_univ : ↑(univ : Finset α) = (Set.univ : Set α) := by ext; simp
#align finset.coe_univ Finset.coe_univ
@[simp, norm_cast]
theorem coe_eq_univ : (s : Set α) = Set.univ ↔ s = univ := by rw [← coe_univ, coe_inj]
#align finset.coe_eq_univ Finset.coe_eq_univ
theorem Nonempty.eq_univ [Subsingleton α] : s.Nonempty → s = univ := by
rintro ⟨x, hx⟩
exact eq_univ_of_forall fun y => by rwa [Subsingleton.elim y x]
#align finset.nonempty.eq_univ Finset.Nonempty.eq_univ
theorem univ_nonempty_iff : (univ : Finset α).Nonempty ↔ Nonempty α := by
rw [← coe_nonempty, coe_univ, Set.nonempty_iff_univ_nonempty]
#align finset.univ_nonempty_iff Finset.univ_nonempty_iff
@[aesop unsafe apply (rule_sets := [finsetNonempty])]
theorem univ_nonempty [Nonempty α] : (univ : Finset α).Nonempty :=
univ_nonempty_iff.2 ‹_›
#align finset.univ_nonempty Finset.univ_nonempty
theorem univ_eq_empty_iff : (univ : Finset α) = ∅ ↔ IsEmpty α := by
rw [← not_nonempty_iff, ← univ_nonempty_iff, not_nonempty_iff_eq_empty]
#align finset.univ_eq_empty_iff Finset.univ_eq_empty_iff
@[simp]
theorem univ_eq_empty [IsEmpty α] : (univ : Finset α) = ∅ :=
univ_eq_empty_iff.2 ‹_›
#align finset.univ_eq_empty Finset.univ_eq_empty
@[simp]
theorem univ_unique [Unique α] : (univ : Finset α) = {default} :=
Finset.ext fun x => iff_of_true (mem_univ _) <| mem_singleton.2 <| Subsingleton.elim x default
#align finset.univ_unique Finset.univ_unique
@[simp]
theorem subset_univ (s : Finset α) : s ⊆ univ := fun a _ => mem_univ a
#align finset.subset_univ Finset.subset_univ
instance boundedOrder : BoundedOrder (Finset α) :=
{ inferInstanceAs (OrderBot (Finset α)) with
top := univ
le_top := subset_univ }
#align finset.bounded_order Finset.boundedOrder
@[simp]
theorem top_eq_univ : (⊤ : Finset α) = univ :=
rfl
#align finset.top_eq_univ Finset.top_eq_univ
theorem ssubset_univ_iff {s : Finset α} : s ⊂ univ ↔ s ≠ univ :=
@lt_top_iff_ne_top _ _ _ s
#align finset.ssubset_univ_iff Finset.ssubset_univ_iff
@[simp]
theorem univ_subset_iff {s : Finset α} : univ ⊆ s ↔ s = univ :=
@top_le_iff _ _ _ s
theorem codisjoint_left : Codisjoint s t ↔ ∀ ⦃a⦄, a ∉ s → a ∈ t := by
classical simp [codisjoint_iff, eq_univ_iff_forall, or_iff_not_imp_left]
#align finset.codisjoint_left Finset.codisjoint_left
theorem codisjoint_right : Codisjoint s t ↔ ∀ ⦃a⦄, a ∉ t → a ∈ s :=
Codisjoint_comm.trans codisjoint_left
#align finset.codisjoint_right Finset.codisjoint_right
section BooleanAlgebra
variable [DecidableEq α] {a : α}
instance booleanAlgebra : BooleanAlgebra (Finset α) :=
GeneralizedBooleanAlgebra.toBooleanAlgebra
#align finset.boolean_algebra Finset.booleanAlgebra
theorem sdiff_eq_inter_compl (s t : Finset α) : s \ t = s ∩ tᶜ :=
sdiff_eq
#align finset.sdiff_eq_inter_compl Finset.sdiff_eq_inter_compl
theorem compl_eq_univ_sdiff (s : Finset α) : sᶜ = univ \ s :=
rfl
#align finset.compl_eq_univ_sdiff Finset.compl_eq_univ_sdiff
@[simp]
theorem mem_compl : a ∈ sᶜ ↔ a ∉ s := by simp [compl_eq_univ_sdiff]
#align finset.mem_compl Finset.mem_compl
theorem not_mem_compl : a ∉ sᶜ ↔ a ∈ s := by rw [mem_compl, not_not]
#align finset.not_mem_compl Finset.not_mem_compl
@[simp, norm_cast]
theorem coe_compl (s : Finset α) : ↑sᶜ = (↑s : Set α)ᶜ :=
Set.ext fun _ => mem_compl
#align finset.coe_compl Finset.coe_compl
@[simp] lemma compl_subset_compl : sᶜ ⊆ tᶜ ↔ t ⊆ s := @compl_le_compl_iff_le (Finset α) _ _ _
@[simp] lemma compl_ssubset_compl : sᶜ ⊂ tᶜ ↔ t ⊂ s := @compl_lt_compl_iff_lt (Finset α) _ _ _
lemma subset_compl_comm : s ⊆ tᶜ ↔ t ⊆ sᶜ := le_compl_iff_le_compl (α := Finset α)
@[simp] lemma subset_compl_singleton : s ⊆ {a}ᶜ ↔ a ∉ s := by
rw [subset_compl_comm, singleton_subset_iff, mem_compl]
@[simp]
theorem compl_empty : (∅ : Finset α)ᶜ = univ :=
compl_bot
#align finset.compl_empty Finset.compl_empty
@[simp]
theorem compl_univ : (univ : Finset α)ᶜ = ∅ :=
compl_top
#align finset.compl_univ Finset.compl_univ
@[simp]
theorem compl_eq_empty_iff (s : Finset α) : sᶜ = ∅ ↔ s = univ :=
compl_eq_bot
#align finset.compl_eq_empty_iff Finset.compl_eq_empty_iff
@[simp]
theorem compl_eq_univ_iff (s : Finset α) : sᶜ = univ ↔ s = ∅ :=
compl_eq_top
#align finset.compl_eq_univ_iff Finset.compl_eq_univ_iff
@[simp]
theorem union_compl (s : Finset α) : s ∪ sᶜ = univ :=
sup_compl_eq_top
#align finset.union_compl Finset.union_compl
@[simp]
theorem inter_compl (s : Finset α) : s ∩ sᶜ = ∅ :=
inf_compl_eq_bot
#align finset.inter_compl Finset.inter_compl
@[simp]
theorem compl_union (s t : Finset α) : (s ∪ t)ᶜ = sᶜ ∩ tᶜ :=
compl_sup
#align finset.compl_union Finset.compl_union
@[simp]
theorem compl_inter (s t : Finset α) : (s ∩ t)ᶜ = sᶜ ∪ tᶜ :=
compl_inf
#align finset.compl_inter Finset.compl_inter
@[simp]
theorem compl_erase : (s.erase a)ᶜ = insert a sᶜ := by
ext
simp only [or_iff_not_imp_left, mem_insert, not_and, mem_compl, mem_erase]
#align finset.compl_erase Finset.compl_erase
@[simp]
theorem compl_insert : (insert a s)ᶜ = sᶜ.erase a := by
ext
simp only [not_or, mem_insert, iff_self_iff, mem_compl, mem_erase]
#align finset.compl_insert Finset.compl_insert
theorem insert_compl_insert (ha : a ∉ s) : insert a (insert a s)ᶜ = sᶜ := by
simp_rw [compl_insert, insert_erase (mem_compl.2 ha)]
@[simp]
theorem insert_compl_self (x : α) : insert x ({x}ᶜ : Finset α) = univ := by
rw [← compl_erase, erase_singleton, compl_empty]
#align finset.insert_compl_self Finset.insert_compl_self
@[simp]
theorem compl_filter (p : α → Prop) [DecidablePred p] [∀ x, Decidable ¬p x] :
(univ.filter p)ᶜ = univ.filter fun x => ¬p x :=
ext <| by simp
#align finset.compl_filter Finset.compl_filter
theorem compl_ne_univ_iff_nonempty (s : Finset α) : sᶜ ≠ univ ↔ s.Nonempty := by
simp [eq_univ_iff_forall, Finset.Nonempty]
#align finset.compl_ne_univ_iff_nonempty Finset.compl_ne_univ_iff_nonempty
theorem compl_singleton (a : α) : ({a} : Finset α)ᶜ = univ.erase a := by
rw [compl_eq_univ_sdiff, sdiff_singleton_eq_erase]
#align finset.compl_singleton Finset.compl_singleton
theorem insert_inj_on' (s : Finset α) : Set.InjOn (fun a => insert a s) (sᶜ : Finset α) := by
rw [coe_compl]
exact s.insert_inj_on
#align finset.insert_inj_on' Finset.insert_inj_on'
theorem image_univ_of_surjective [Fintype β] {f : β → α} (hf : Surjective f) :
univ.image f = univ :=
eq_univ_of_forall <| hf.forall.2 fun _ => mem_image_of_mem _ <| mem_univ _
#align finset.image_univ_of_surjective Finset.image_univ_of_surjective
@[simp]
theorem image_univ_equiv [Fintype β] (f : β ≃ α) : univ.image f = univ :=
Finset.image_univ_of_surjective f.surjective
@[simp] lemma univ_inter (s : Finset α) : univ ∩ s = s := by ext a; simp
#align finset.univ_inter Finset.univ_inter
@[simp] lemma inter_univ (s : Finset α) : s ∩ univ = s := by rw [inter_comm, univ_inter]
#align finset.inter_univ Finset.inter_univ
@[simp] lemma inter_eq_univ : s ∩ t = univ ↔ s = univ ∧ t = univ := inf_eq_top_iff
end BooleanAlgebra
-- @[simp] --Note this would loop with `Finset.univ_unique`
lemma singleton_eq_univ [Subsingleton α] (a : α) : ({a} : Finset α) = univ := by
ext b; simp [Subsingleton.elim a b]
theorem map_univ_of_surjective [Fintype β] {f : β ↪ α} (hf : Surjective f) : univ.map f = univ :=
eq_univ_of_forall <| hf.forall.2 fun _ => mem_map_of_mem _ <| mem_univ _
#align finset.map_univ_of_surjective Finset.map_univ_of_surjective
@[simp]
theorem map_univ_equiv [Fintype β] (f : β ≃ α) : univ.map f.toEmbedding = univ :=
map_univ_of_surjective f.surjective
#align finset.map_univ_equiv Finset.map_univ_equiv
theorem univ_map_equiv_to_embedding {α β : Type*} [Fintype α] [Fintype β] (e : α ≃ β) :
univ.map e.toEmbedding = univ :=
eq_univ_iff_forall.mpr fun b => mem_map.mpr ⟨e.symm b, mem_univ _, by simp⟩
#align finset.univ_map_equiv_to_embedding Finset.univ_map_equiv_to_embedding
@[simp]
theorem univ_filter_exists (f : α → β) [Fintype β] [DecidablePred fun y => ∃ x, f x = y]
[DecidableEq β] : (Finset.univ.filter fun y => ∃ x, f x = y) = Finset.univ.image f := by
ext
simp
#align finset.univ_filter_exists Finset.univ_filter_exists
/-- Note this is a special case of `(Finset.image_preimage f univ _).symm`. -/
theorem univ_filter_mem_range (f : α → β) [Fintype β] [DecidablePred fun y => y ∈ Set.range f]
[DecidableEq β] : (Finset.univ.filter fun y => y ∈ Set.range f) = Finset.univ.image f := by
letI : DecidablePred (fun y => ∃ x, f x = y) := by simpa using ‹_›
exact univ_filter_exists f
#align finset.univ_filter_mem_range Finset.univ_filter_mem_range
theorem coe_filter_univ (p : α → Prop) [DecidablePred p] :
(univ.filter p : Set α) = { x | p x } := by simp
#align finset.coe_filter_univ Finset.coe_filter_univ
@[simp] lemma subtype_eq_univ {p : α → Prop} [DecidablePred p] [Fintype {a // p a}] :
s.subtype p = univ ↔ ∀ ⦃a⦄, p a → a ∈ s := by simp [ext_iff]
@[simp] lemma subtype_univ [Fintype α] (p : α → Prop) [DecidablePred p] [Fintype {a // p a}] :
univ.subtype p = univ := by simp
end Finset
open Finset Function
namespace Fintype
instance decidablePiFintype {α} {β : α → Type*} [∀ a, DecidableEq (β a)] [Fintype α] :
DecidableEq (∀ a, β a) := fun f g =>
decidable_of_iff (∀ a ∈ @Fintype.elems α _, f a = g a)
(by simp [Function.funext_iff, Fintype.complete])
#align fintype.decidable_pi_fintype Fintype.decidablePiFintype
instance decidableForallFintype {p : α → Prop} [DecidablePred p] [Fintype α] :
Decidable (∀ a, p a) :=
decidable_of_iff (∀ a ∈ @univ α _, p a) (by simp)
#align fintype.decidable_forall_fintype Fintype.decidableForallFintype
instance decidableExistsFintype {p : α → Prop} [DecidablePred p] [Fintype α] :
Decidable (∃ a, p a) :=
decidable_of_iff (∃ a ∈ @univ α _, p a) (by simp)
#align fintype.decidable_exists_fintype Fintype.decidableExistsFintype
instance decidableMemRangeFintype [Fintype α] [DecidableEq β] (f : α → β) :
DecidablePred (· ∈ Set.range f) := fun _ => Fintype.decidableExistsFintype
#align fintype.decidable_mem_range_fintype Fintype.decidableMemRangeFintype
instance decidableSubsingleton [Fintype α] [DecidableEq α] {s : Set α} [DecidablePred (· ∈ s)] :
Decidable s.Subsingleton := decidable_of_iff (∀ a ∈ s, ∀ b ∈ s, a = b) Iff.rfl
section BundledHoms
instance decidableEqEquivFintype [DecidableEq β] [Fintype α] : DecidableEq (α ≃ β) := fun a b =>
decidable_of_iff (a.1 = b.1) Equiv.coe_fn_injective.eq_iff
#align fintype.decidable_eq_equiv_fintype Fintype.decidableEqEquivFintype
instance decidableEqEmbeddingFintype [DecidableEq β] [Fintype α] : DecidableEq (α ↪ β) := fun a b =>
decidable_of_iff ((a : α → β) = b) Function.Embedding.coe_injective.eq_iff
#align fintype.decidable_eq_embedding_fintype Fintype.decidableEqEmbeddingFintype
end BundledHoms
instance decidableInjectiveFintype [DecidableEq α] [DecidableEq β] [Fintype α] :
DecidablePred (Injective : (α → β) → Prop) := fun x => by unfold Injective; infer_instance
#align fintype.decidable_injective_fintype Fintype.decidableInjectiveFintype
instance decidableSurjectiveFintype [DecidableEq β] [Fintype α] [Fintype β] :
DecidablePred (Surjective : (α → β) → Prop) := fun x => by unfold Surjective; infer_instance
#align fintype.decidable_surjective_fintype Fintype.decidableSurjectiveFintype
instance decidableBijectiveFintype [DecidableEq α] [DecidableEq β] [Fintype α] [Fintype β] :
DecidablePred (Bijective : (α → β) → Prop) := fun x => by unfold Bijective; infer_instance
#align fintype.decidable_bijective_fintype Fintype.decidableBijectiveFintype
instance decidableRightInverseFintype [DecidableEq α] [Fintype α] (f : α → β) (g : β → α) :
Decidable (Function.RightInverse f g) :=
show Decidable (∀ x, g (f x) = x) by infer_instance
#align fintype.decidable_right_inverse_fintype Fintype.decidableRightInverseFintype
instance decidableLeftInverseFintype [DecidableEq β] [Fintype β] (f : α → β) (g : β → α) :
Decidable (Function.LeftInverse f g) :=
show Decidable (∀ x, f (g x) = x) by infer_instance
#align fintype.decidable_left_inverse_fintype Fintype.decidableLeftInverseFintype
/-- Construct a proof of `Fintype α` from a universal multiset -/
def ofMultiset [DecidableEq α] (s : Multiset α) (H : ∀ x : α, x ∈ s) : Fintype α :=
⟨s.toFinset, by simpa using H⟩
#align fintype.of_multiset Fintype.ofMultiset
/-- Construct a proof of `Fintype α` from a universal list -/
def ofList [DecidableEq α] (l : List α) (H : ∀ x : α, x ∈ l) : Fintype α :=
⟨l.toFinset, by simpa using H⟩
#align fintype.of_list Fintype.ofList
instance subsingleton (α : Type*) : Subsingleton (Fintype α) :=
⟨fun ⟨s₁, h₁⟩ ⟨s₂, h₂⟩ => by congr; simp [Finset.ext_iff, h₁, h₂]⟩
#align fintype.subsingleton Fintype.subsingleton
instance (α : Type*) : Lean.Meta.FastSubsingleton (Fintype α) := {}
/-- Given a predicate that can be represented by a finset, the subtype
associated to the predicate is a fintype. -/
protected def subtype {p : α → Prop} (s : Finset α) (H : ∀ x : α, x ∈ s ↔ p x) :
Fintype { x // p x } :=
⟨⟨s.1.pmap Subtype.mk fun x => (H x).1, s.nodup.pmap fun _ _ _ _ => congr_arg Subtype.val⟩,
fun ⟨x, px⟩ => Multiset.mem_pmap.2 ⟨x, (H x).2 px, rfl⟩⟩
#align fintype.subtype Fintype.subtype
/-- Construct a fintype from a finset with the same elements. -/
def ofFinset {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) : Fintype p :=
Fintype.subtype s H
#align fintype.of_finset Fintype.ofFinset
/-- If `f : α → β` is a bijection and `α` is a fintype, then `β` is also a fintype. -/
def ofBijective [Fintype α] (f : α → β) (H : Function.Bijective f) : Fintype β :=
⟨univ.map ⟨f, H.1⟩, fun b =>
let ⟨_, e⟩ := H.2 b
e ▸ mem_map_of_mem _ (mem_univ _)⟩
#align fintype.of_bijective Fintype.ofBijective
/-- If `f : α → β` is a surjection and `α` is a fintype, then `β` is also a fintype. -/
def ofSurjective [DecidableEq β] [Fintype α] (f : α → β) (H : Function.Surjective f) : Fintype β :=
⟨univ.image f, fun b =>
let ⟨_, e⟩ := H b
e ▸ mem_image_of_mem _ (mem_univ _)⟩
#align fintype.of_surjective Fintype.ofSurjective
end Fintype
namespace Finset
variable [Fintype α] [DecidableEq α] {s t : Finset α}
@[simp]
lemma filter_univ_mem (s : Finset α) : univ.filter (· ∈ s) = s := by simp [filter_mem_eq_inter]
instance decidableCodisjoint : Decidable (Codisjoint s t) :=
decidable_of_iff _ codisjoint_left.symm
#align finset.decidable_codisjoint Finset.decidableCodisjoint
instance decidableIsCompl : Decidable (IsCompl s t) :=
decidable_of_iff' _ isCompl_iff
#align finset.decidable_is_compl Finset.decidableIsCompl
end Finset
section Inv
namespace Function
variable [Fintype α] [DecidableEq β]
namespace Injective
variable {f : α → β} (hf : Function.Injective f)
/-- The inverse of an `hf : injective` function `f : α → β`, of the type `↥(Set.range f) → α`.
This is the computable version of `Function.invFun` that requires `Fintype α` and `DecidableEq β`,
or the function version of applying `(Equiv.ofInjective f hf).symm`.
This function should not usually be used for actual computation because for most cases,
an explicit inverse can be stated that has better computational properties.
This function computes by checking all terms `a : α` to find the `f a = b`, so it is O(N) where
`N = Fintype.card α`.
-/
def invOfMemRange : Set.range f → α := fun b =>
Finset.choose (fun a => f a = b) Finset.univ
((exists_unique_congr (by simp)).mp (hf.exists_unique_of_mem_range b.property))
#align function.injective.inv_of_mem_range Function.Injective.invOfMemRange
theorem left_inv_of_invOfMemRange (b : Set.range f) : f (hf.invOfMemRange b) = b :=
(Finset.choose_spec (fun a => f a = b) _ _).right
#align function.injective.left_inv_of_inv_of_mem_range Function.Injective.left_inv_of_invOfMemRange
@[simp]
theorem right_inv_of_invOfMemRange (a : α) : hf.invOfMemRange ⟨f a, Set.mem_range_self a⟩ = a :=
hf (Finset.choose_spec (fun a' => f a' = f a) _ _).right
#align function.injective.right_inv_of_inv_of_mem_range Function.Injective.right_inv_of_invOfMemRange
theorem invFun_restrict [Nonempty α] : (Set.range f).restrict (invFun f) = hf.invOfMemRange := by
ext ⟨b, h⟩
apply hf
simp [hf.left_inv_of_invOfMemRange, @invFun_eq _ _ _ f b (Set.mem_range.mp h)]
#align function.injective.inv_fun_restrict Function.Injective.invFun_restrict
theorem invOfMemRange_surjective : Function.Surjective hf.invOfMemRange := fun a =>
⟨⟨f a, Set.mem_range_self a⟩, by simp⟩
#align function.injective.inv_of_mem_range_surjective Function.Injective.invOfMemRange_surjective
end Injective
namespace Embedding
variable (f : α ↪ β) (b : Set.range f)
/-- The inverse of an embedding `f : α ↪ β`, of the type `↥(Set.range f) → α`.
This is the computable version of `Function.invFun` that requires `Fintype α` and `DecidableEq β`,
or the function version of applying `(Equiv.ofInjective f f.injective).symm`.
This function should not usually be used for actual computation because for most cases,
an explicit inverse can be stated that has better computational properties.
This function computes by checking all terms `a : α` to find the `f a = b`, so it is O(N) where
`N = Fintype.card α`.
-/
def invOfMemRange : α :=
f.injective.invOfMemRange b
#align function.embedding.inv_of_mem_range Function.Embedding.invOfMemRange
@[simp]
theorem left_inv_of_invOfMemRange : f (f.invOfMemRange b) = b :=
f.injective.left_inv_of_invOfMemRange b
#align function.embedding.left_inv_of_inv_of_mem_range Function.Embedding.left_inv_of_invOfMemRange
@[simp]
theorem right_inv_of_invOfMemRange (a : α) : f.invOfMemRange ⟨f a, Set.mem_range_self a⟩ = a :=
f.injective.right_inv_of_invOfMemRange a
#align function.embedding.right_inv_of_inv_of_mem_range Function.Embedding.right_inv_of_invOfMemRange
theorem invFun_restrict [Nonempty α] : (Set.range f).restrict (invFun f) = f.invOfMemRange := by
ext ⟨b, h⟩
apply f.injective
simp [f.left_inv_of_invOfMemRange, @invFun_eq _ _ _ f b (Set.mem_range.mp h)]
#align function.embedding.inv_fun_restrict Function.Embedding.invFun_restrict
theorem invOfMemRange_surjective : Function.Surjective f.invOfMemRange := fun a =>
⟨⟨f a, Set.mem_range_self a⟩, by simp⟩
#align function.embedding.inv_of_mem_range_surjective Function.Embedding.invOfMemRange_surjective
end Embedding
end Function
end Inv
namespace Fintype
/-- Given an injective function to a fintype, the domain is also a
fintype. This is noncomputable because injectivity alone cannot be
used to construct preimages. -/
noncomputable def ofInjective [Fintype β] (f : α → β) (H : Function.Injective f) : Fintype α :=
letI := Classical.dec
if hα : Nonempty α then
letI := Classical.inhabited_of_nonempty hα
ofSurjective (invFun f) (invFun_surjective H)
else ⟨∅, fun x => (hα ⟨x⟩).elim⟩
#align fintype.of_injective Fintype.ofInjective
/-- If `f : α ≃ β` and `α` is a fintype, then `β` is also a fintype. -/
def ofEquiv (α : Type*) [Fintype α] (f : α ≃ β) : Fintype β :=
ofBijective _ f.bijective
#align fintype.of_equiv Fintype.ofEquiv
/-- Any subsingleton type with a witness is a fintype (with one term). -/
def ofSubsingleton (a : α) [Subsingleton α] : Fintype α :=
⟨{a}, fun _ => Finset.mem_singleton.2 (Subsingleton.elim _ _)⟩
#align fintype.of_subsingleton Fintype.ofSubsingleton
@[simp]
theorem univ_ofSubsingleton (a : α) [Subsingleton α] : @univ _ (ofSubsingleton a) = {a} :=
rfl
#align fintype.univ_of_subsingleton Fintype.univ_ofSubsingleton
/-- An empty type is a fintype. Not registered as an instance, to make sure that there aren't two
conflicting `Fintype ι` instances around when casing over whether a fintype `ι` is empty or not. -/
def ofIsEmpty [IsEmpty α] : Fintype α :=
⟨∅, isEmptyElim⟩
#align fintype.of_is_empty Fintype.ofIsEmpty
/-- Note: this lemma is specifically about `Fintype.ofIsEmpty`. For a statement about
arbitrary `Fintype` instances, use `Finset.univ_eq_empty`. -/
theorem univ_ofIsEmpty [IsEmpty α] : @univ α Fintype.ofIsEmpty = ∅ :=
rfl
#align fintype.univ_of_is_empty Fintype.univ_ofIsEmpty
instance : Fintype Empty := Fintype.ofIsEmpty
instance : Fintype PEmpty := Fintype.ofIsEmpty
end Fintype
namespace Set
variable {s t : Set α}
/-- Construct a finset enumerating a set `s`, given a `Fintype` instance. -/
def toFinset (s : Set α) [Fintype s] : Finset α :=
(@Finset.univ s _).map <| Function.Embedding.subtype _
#align set.to_finset Set.toFinset
@[congr]
theorem toFinset_congr {s t : Set α} [Fintype s] [Fintype t] (h : s = t) :
toFinset s = toFinset t := by subst h; congr; exact Subsingleton.elim _ _
#align set.to_finset_congr Set.toFinset_congr
@[simp]
theorem mem_toFinset {s : Set α} [Fintype s] {a : α} : a ∈ s.toFinset ↔ a ∈ s := by
simp [toFinset]
#align set.mem_to_finset Set.mem_toFinset
/-- Many `Fintype` instances for sets are defined using an extensionally equal `Finset`.
Rewriting `s.toFinset` with `Set.toFinset_ofFinset` replaces the term with such a `Finset`. -/
theorem toFinset_ofFinset {p : Set α} (s : Finset α) (H : ∀ x, x ∈ s ↔ x ∈ p) :
@Set.toFinset _ p (Fintype.ofFinset s H) = s :=
Finset.ext fun x => by rw [@mem_toFinset _ _ (id _), H]
#align set.to_finset_of_finset Set.toFinset_ofFinset
/-- Membership of a set with a `Fintype` instance is decidable.
Using this as an instance leads to potential loops with `Subtype.fintype` under certain decidability
assumptions, so it should only be declared a local instance. -/
def decidableMemOfFintype [DecidableEq α] (s : Set α) [Fintype s] (a) : Decidable (a ∈ s) :=
decidable_of_iff _ mem_toFinset
#align set.decidable_mem_of_fintype Set.decidableMemOfFintype
@[simp]
theorem coe_toFinset (s : Set α) [Fintype s] : (↑s.toFinset : Set α) = s :=
Set.ext fun _ => mem_toFinset
#align set.coe_to_finset Set.coe_toFinset
@[simp, aesop safe apply (rule_sets := [finsetNonempty])]
theorem toFinset_nonempty {s : Set α} [Fintype s] : s.toFinset.Nonempty ↔ s.Nonempty := by
rw [← Finset.coe_nonempty, coe_toFinset]
#align set.to_finset_nonempty Set.toFinset_nonempty
@[simp]
theorem toFinset_inj {s t : Set α} [Fintype s] [Fintype t] : s.toFinset = t.toFinset ↔ s = t :=
⟨fun h => by rw [← s.coe_toFinset, h, t.coe_toFinset], fun h => by simp [h]⟩
#align set.to_finset_inj Set.toFinset_inj
@[mono]
theorem toFinset_subset_toFinset [Fintype s] [Fintype t] : s.toFinset ⊆ t.toFinset ↔ s ⊆ t := by
simp [Finset.subset_iff, Set.subset_def]
#align set.to_finset_subset_to_finset Set.toFinset_subset_toFinset
@[simp]
theorem toFinset_ssubset [Fintype s] {t : Finset α} : s.toFinset ⊂ t ↔ s ⊂ t := by
rw [← Finset.coe_ssubset, coe_toFinset]
#align set.to_finset_ssubset Set.toFinset_ssubset
@[simp]
theorem subset_toFinset {s : Finset α} [Fintype t] : s ⊆ t.toFinset ↔ ↑s ⊆ t := by
rw [← Finset.coe_subset, coe_toFinset]
#align set.subset_to_finset Set.subset_toFinset
@[simp]
theorem ssubset_toFinset {s : Finset α} [Fintype t] : s ⊂ t.toFinset ↔ ↑s ⊂ t := by
rw [← Finset.coe_ssubset, coe_toFinset]
#align set.ssubset_to_finset Set.ssubset_toFinset
@[mono]
theorem toFinset_ssubset_toFinset [Fintype s] [Fintype t] : s.toFinset ⊂ t.toFinset ↔ s ⊂ t := by
simp only [Finset.ssubset_def, toFinset_subset_toFinset, ssubset_def]
#align set.to_finset_ssubset_to_finset Set.toFinset_ssubset_toFinset
@[simp]
theorem toFinset_subset [Fintype s] {t : Finset α} : s.toFinset ⊆ t ↔ s ⊆ t := by
rw [← Finset.coe_subset, coe_toFinset]
#align set.to_finset_subset Set.toFinset_subset
alias ⟨_, toFinset_mono⟩ := toFinset_subset_toFinset
#align set.to_finset_mono Set.toFinset_mono
alias ⟨_, toFinset_strict_mono⟩ := toFinset_ssubset_toFinset
#align set.to_finset_strict_mono Set.toFinset_strict_mono
@[simp]
theorem disjoint_toFinset [Fintype s] [Fintype t] :
Disjoint s.toFinset t.toFinset ↔ Disjoint s t := by simp only [← disjoint_coe, coe_toFinset]
#align set.disjoint_to_finset Set.disjoint_toFinset
section DecidableEq
variable [DecidableEq α] (s t) [Fintype s] [Fintype t]
@[simp]
theorem toFinset_inter [Fintype (s ∩ t : Set _)] : (s ∩ t).toFinset = s.toFinset ∩ t.toFinset := by
ext
simp
#align set.to_finset_inter Set.toFinset_inter
@[simp]
| Mathlib/Data/Fintype/Basic.lean | 692 | 694 | theorem toFinset_union [Fintype (s ∪ t : Set _)] : (s ∪ t).toFinset = s.toFinset ∪ t.toFinset := by |
ext
simp
|
/-
Copyright (c) 2022 Joël Riou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Joël Riou
-/
import Mathlib.CategoryTheory.Equivalence
#align_import algebraic_topology.dold_kan.compatibility from "leanprover-community/mathlib"@"32a7e535287f9c73f2e4d2aef306a39190f0b504"
/-! Tools for compatibilities between Dold-Kan equivalences
The purpose of this file is to introduce tools which will enable the
construction of the Dold-Kan equivalence `SimplicialObject C ≌ ChainComplex C ℕ`
for a pseudoabelian category `C` from the equivalence
`Karoubi (SimplicialObject C) ≌ Karoubi (ChainComplex C ℕ)` and the two
equivalences `simplicial_object C ≅ Karoubi (SimplicialObject C)` and
`ChainComplex C ℕ ≅ Karoubi (ChainComplex C ℕ)`.
It is certainly possible to get an equivalence `SimplicialObject C ≌ ChainComplex C ℕ`
using a compositions of the three equivalences above, but then neither the functor
nor the inverse would have good definitional properties. For example, it would be better
if the inverse functor of the equivalence was exactly the functor
`Γ₀ : SimplicialObject C ⥤ ChainComplex C ℕ` which was constructed in `FunctorGamma.lean`.
In this file, given four categories `A`, `A'`, `B`, `B'`, equivalences `eA : A ≅ A'`,
`eB : B ≅ B'`, `e' : A' ≅ B'`, functors `F : A ⥤ B'`, `G : B ⥤ A` equipped with certain
compatibilities, we construct successive equivalences:
- `equivalence₀` from `A` to `B'`, which is the composition of `eA` and `e'`.
- `equivalence₁` from `A` to `B'`, with the same inverse functor as `equivalence₀`,
but whose functor is `F`.
- `equivalence₂` from `A` to `B`, which is the composition of `equivalence₁` and the
inverse of `eB`:
- `equivalence` from `A` to `B`, which has the same functor `F ⋙ eB.inverse` as `equivalence₂`,
but whose inverse functor is `G`.
When extra assumptions are given, we shall also provide simplification lemmas for the
unit and counit isomorphisms of `equivalence`.
(See `Equivalence.lean` for the general strategy of proof of the Dold-Kan equivalence.)
-/
open CategoryTheory CategoryTheory.Category
namespace AlgebraicTopology
namespace DoldKan
namespace Compatibility
variable {A A' B B' : Type*} [Category A] [Category A'] [Category B] [Category B'] (eA : A ≌ A')
(eB : B ≌ B') (e' : A' ≌ B') {F : A ⥤ B'} (hF : eA.functor ⋙ e'.functor ≅ F) {G : B ⥤ A}
(hG : eB.functor ⋙ e'.inverse ≅ G ⋙ eA.functor)
/-- A basic equivalence `A ≅ B'` obtained by composing `eA : A ≅ A'` and `e' : A' ≅ B'`. -/
@[simps! functor inverse unitIso_hom_app]
def equivalence₀ : A ≌ B' :=
eA.trans e'
#align algebraic_topology.dold_kan.compatibility.equivalence₀ AlgebraicTopology.DoldKan.Compatibility.equivalence₀
variable {eA} {e'}
/-- An intermediate equivalence `A ≅ B'` whose functor is `F` and whose inverse is
`e'.inverse ⋙ eA.inverse`. -/
@[simps! functor]
def equivalence₁ : A ≌ B' := (equivalence₀ eA e').changeFunctor hF
#align algebraic_topology.dold_kan.compatibility.equivalence₁ AlgebraicTopology.DoldKan.Compatibility.equivalence₁
theorem equivalence₁_inverse : (equivalence₁ hF).inverse = e'.inverse ⋙ eA.inverse :=
rfl
#align algebraic_topology.dold_kan.compatibility.equivalence₁_inverse AlgebraicTopology.DoldKan.Compatibility.equivalence₁_inverse
/-- The counit isomorphism of the equivalence `equivalence₁` between `A` and `B'`. -/
@[simps!]
def equivalence₁CounitIso : (e'.inverse ⋙ eA.inverse) ⋙ F ≅ 𝟭 B' :=
calc
(e'.inverse ⋙ eA.inverse) ⋙ F ≅ (e'.inverse ⋙ eA.inverse) ⋙ eA.functor ⋙ e'.functor :=
isoWhiskerLeft _ hF.symm
_ ≅ e'.inverse ⋙ (eA.inverse ⋙ eA.functor) ⋙ e'.functor := Iso.refl _
_ ≅ e'.inverse ⋙ 𝟭 _ ⋙ e'.functor := isoWhiskerLeft _ (isoWhiskerRight eA.counitIso _)
_ ≅ e'.inverse ⋙ e'.functor := Iso.refl _
_ ≅ 𝟭 B' := e'.counitIso
#align algebraic_topology.dold_kan.compatibility.equivalence₁_counit_iso AlgebraicTopology.DoldKan.Compatibility.equivalence₁CounitIso
theorem equivalence₁CounitIso_eq : (equivalence₁ hF).counitIso = equivalence₁CounitIso hF := by
ext Y
simp [equivalence₁, equivalence₀]
#align algebraic_topology.dold_kan.compatibility.equivalence₁_counit_iso_eq AlgebraicTopology.DoldKan.Compatibility.equivalence₁CounitIso_eq
/-- The unit isomorphism of the equivalence `equivalence₁` between `A` and `B'`. -/
@[simps!]
def equivalence₁UnitIso : 𝟭 A ≅ F ⋙ e'.inverse ⋙ eA.inverse :=
calc
𝟭 A ≅ eA.functor ⋙ eA.inverse := eA.unitIso
_ ≅ eA.functor ⋙ 𝟭 A' ⋙ eA.inverse := Iso.refl _
_ ≅ eA.functor ⋙ (e'.functor ⋙ e'.inverse) ⋙ eA.inverse :=
isoWhiskerLeft _ (isoWhiskerRight e'.unitIso _)
_ ≅ (eA.functor ⋙ e'.functor) ⋙ e'.inverse ⋙ eA.inverse := Iso.refl _
_ ≅ F ⋙ e'.inverse ⋙ eA.inverse := isoWhiskerRight hF _
#align algebraic_topology.dold_kan.compatibility.equivalence₁_unit_iso AlgebraicTopology.DoldKan.Compatibility.equivalence₁UnitIso
theorem equivalence₁UnitIso_eq : (equivalence₁ hF).unitIso = equivalence₁UnitIso hF := by
ext X
simp [equivalence₁]
#align algebraic_topology.dold_kan.compatibility.equivalence₁_unit_iso_eq AlgebraicTopology.DoldKan.Compatibility.equivalence₁UnitIso_eq
/-- An intermediate equivalence `A ≅ B` obtained as the composition of `equivalence₁` and
the inverse of `eB : B ≌ B'`. -/
@[simps! functor]
def equivalence₂ : A ≌ B :=
(equivalence₁ hF).trans eB.symm
#align algebraic_topology.dold_kan.compatibility.equivalence₂ AlgebraicTopology.DoldKan.Compatibility.equivalence₂
theorem equivalence₂_inverse :
(equivalence₂ eB hF).inverse = eB.functor ⋙ e'.inverse ⋙ eA.inverse :=
rfl
#align algebraic_topology.dold_kan.compatibility.equivalence₂_inverse AlgebraicTopology.DoldKan.Compatibility.equivalence₂_inverse
/-- The counit isomorphism of the equivalence `equivalence₂` between `A` and `B`. -/
@[simps!]
def equivalence₂CounitIso : (eB.functor ⋙ e'.inverse ⋙ eA.inverse) ⋙ F ⋙ eB.inverse ≅ 𝟭 B :=
calc
(eB.functor ⋙ e'.inverse ⋙ eA.inverse) ⋙ F ⋙ eB.inverse ≅
eB.functor ⋙ (e'.inverse ⋙ eA.inverse ⋙ F) ⋙ eB.inverse :=
Iso.refl _
_ ≅ eB.functor ⋙ 𝟭 _ ⋙ eB.inverse :=
isoWhiskerLeft _ (isoWhiskerRight (equivalence₁CounitIso hF) _)
_ ≅ eB.functor ⋙ eB.inverse := Iso.refl _
_ ≅ 𝟭 B := eB.unitIso.symm
#align algebraic_topology.dold_kan.compatibility.equivalence₂_counit_iso AlgebraicTopology.DoldKan.Compatibility.equivalence₂CounitIso
theorem equivalence₂CounitIso_eq :
(equivalence₂ eB hF).counitIso = equivalence₂CounitIso eB hF := by
ext Y'
dsimp [equivalence₂, Iso.refl]
simp only [equivalence₁CounitIso_eq, equivalence₂CounitIso_hom_app,
equivalence₁CounitIso_hom_app, Functor.map_comp, assoc]
#align algebraic_topology.dold_kan.compatibility.equivalence₂_counit_iso_eq AlgebraicTopology.DoldKan.Compatibility.equivalence₂CounitIso_eq
/-- The unit isomorphism of the equivalence `equivalence₂` between `A` and `B`. -/
@[simps!]
def equivalence₂UnitIso : 𝟭 A ≅ (F ⋙ eB.inverse) ⋙ eB.functor ⋙ e'.inverse ⋙ eA.inverse :=
calc
𝟭 A ≅ F ⋙ e'.inverse ⋙ eA.inverse := equivalence₁UnitIso hF
_ ≅ F ⋙ 𝟭 B' ⋙ e'.inverse ⋙ eA.inverse := Iso.refl _
_ ≅ F ⋙ (eB.inverse ⋙ eB.functor) ⋙ e'.inverse ⋙ eA.inverse :=
isoWhiskerLeft _ (isoWhiskerRight eB.counitIso.symm _)
_ ≅ (F ⋙ eB.inverse) ⋙ eB.functor ⋙ e'.inverse ⋙ eA.inverse := Iso.refl _
#align algebraic_topology.dold_kan.compatibility.equivalence₂_unit_iso AlgebraicTopology.DoldKan.Compatibility.equivalence₂UnitIso
| Mathlib/AlgebraicTopology/DoldKan/Compatibility.lean | 152 | 157 | theorem equivalence₂UnitIso_eq : (equivalence₂ eB hF).unitIso = equivalence₂UnitIso eB hF := by |
ext X
dsimp [equivalence₂]
simp only [equivalence₂UnitIso_hom_app, equivalence₁UnitIso_eq, equivalence₁UnitIso_hom_app,
assoc, NatIso.cancel_natIso_hom_left]
rfl
|
/-
Copyright (c) 2021 Kexing Ying. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kexing Ying
-/
import Mathlib.MeasureTheory.Measure.Typeclasses
import Mathlib.Analysis.Complex.Basic
#align_import measure_theory.measure.vector_measure from "leanprover-community/mathlib"@"70a4f2197832bceab57d7f41379b2592d1110570"
/-!
# Vector valued measures
This file defines vector valued measures, which are σ-additive functions from a set to an add monoid
`M` such that it maps the empty set and non-measurable sets to zero. In the case
that `M = ℝ`, we called the vector measure a signed measure and write `SignedMeasure α`.
Similarly, when `M = ℂ`, we call the measure a complex measure and write `ComplexMeasure α`.
## Main definitions
* `MeasureTheory.VectorMeasure` is a vector valued, σ-additive function that maps the empty
and non-measurable set to zero.
* `MeasureTheory.VectorMeasure.map` is the pushforward of a vector measure along a function.
* `MeasureTheory.VectorMeasure.restrict` is the restriction of a vector measure on some set.
## Notation
* `v ≤[i] w` means that the vector measure `v` restricted on the set `i` is less than or equal
to the vector measure `w` restricted on `i`, i.e. `v.restrict i ≤ w.restrict i`.
## Implementation notes
We require all non-measurable sets to be mapped to zero in order for the extensionality lemma
to only compare the underlying functions for measurable sets.
We use `HasSum` instead of `tsum` in the definition of vector measures in comparison to `Measure`
since this provides summability.
## Tags
vector measure, signed measure, complex measure
-/
noncomputable section
open scoped Classical
open NNReal ENNReal MeasureTheory
namespace MeasureTheory
variable {α β : Type*} {m : MeasurableSpace α}
/-- A vector measure on a measurable space `α` is a σ-additive `M`-valued function (for some `M`
an add monoid) such that the empty set and non-measurable sets are mapped to zero. -/
structure VectorMeasure (α : Type*) [MeasurableSpace α] (M : Type*) [AddCommMonoid M]
[TopologicalSpace M] where
measureOf' : Set α → M
empty' : measureOf' ∅ = 0
not_measurable' ⦃i : Set α⦄ : ¬MeasurableSet i → measureOf' i = 0
m_iUnion' ⦃f : ℕ → Set α⦄ : (∀ i, MeasurableSet (f i)) → Pairwise (Disjoint on f) →
HasSum (fun i => measureOf' (f i)) (measureOf' (⋃ i, f i))
#align measure_theory.vector_measure MeasureTheory.VectorMeasure
#align measure_theory.vector_measure.measure_of' MeasureTheory.VectorMeasure.measureOf'
#align measure_theory.vector_measure.empty' MeasureTheory.VectorMeasure.empty'
#align measure_theory.vector_measure.not_measurable' MeasureTheory.VectorMeasure.not_measurable'
#align measure_theory.vector_measure.m_Union' MeasureTheory.VectorMeasure.m_iUnion'
/-- A `SignedMeasure` is an `ℝ`-vector measure. -/
abbrev SignedMeasure (α : Type*) [MeasurableSpace α] :=
VectorMeasure α ℝ
#align measure_theory.signed_measure MeasureTheory.SignedMeasure
/-- A `ComplexMeasure` is a `ℂ`-vector measure. -/
abbrev ComplexMeasure (α : Type*) [MeasurableSpace α] :=
VectorMeasure α ℂ
#align measure_theory.complex_measure MeasureTheory.ComplexMeasure
open Set MeasureTheory
namespace VectorMeasure
section
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
attribute [coe] VectorMeasure.measureOf'
instance instCoeFun : CoeFun (VectorMeasure α M) fun _ => Set α → M :=
⟨VectorMeasure.measureOf'⟩
#align measure_theory.vector_measure.has_coe_to_fun MeasureTheory.VectorMeasure.instCoeFun
initialize_simps_projections VectorMeasure (measureOf' → apply)
#noalign measure_theory.vector_measure.measure_of_eq_coe
@[simp]
theorem empty (v : VectorMeasure α M) : v ∅ = 0 :=
v.empty'
#align measure_theory.vector_measure.empty MeasureTheory.VectorMeasure.empty
theorem not_measurable (v : VectorMeasure α M) {i : Set α} (hi : ¬MeasurableSet i) : v i = 0 :=
v.not_measurable' hi
#align measure_theory.vector_measure.not_measurable MeasureTheory.VectorMeasure.not_measurable
theorem m_iUnion (v : VectorMeasure α M) {f : ℕ → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : HasSum (fun i => v (f i)) (v (⋃ i, f i)) :=
v.m_iUnion' hf₁ hf₂
#align measure_theory.vector_measure.m_Union MeasureTheory.VectorMeasure.m_iUnion
theorem of_disjoint_iUnion_nat [T2Space M] (v : VectorMeasure α M) {f : ℕ → Set α}
(hf₁ : ∀ i, MeasurableSet (f i)) (hf₂ : Pairwise (Disjoint on f)) :
v (⋃ i, f i) = ∑' i, v (f i) :=
(v.m_iUnion hf₁ hf₂).tsum_eq.symm
#align measure_theory.vector_measure.of_disjoint_Union_nat MeasureTheory.VectorMeasure.of_disjoint_iUnion_nat
theorem coe_injective : @Function.Injective (VectorMeasure α M) (Set α → M) (⇑) := fun v w h => by
cases v
cases w
congr
#align measure_theory.vector_measure.coe_injective MeasureTheory.VectorMeasure.coe_injective
theorem ext_iff' (v w : VectorMeasure α M) : v = w ↔ ∀ i : Set α, v i = w i := by
rw [← coe_injective.eq_iff, Function.funext_iff]
#align measure_theory.vector_measure.ext_iff' MeasureTheory.VectorMeasure.ext_iff'
theorem ext_iff (v w : VectorMeasure α M) : v = w ↔ ∀ i : Set α, MeasurableSet i → v i = w i := by
constructor
· rintro rfl _ _
rfl
· rw [ext_iff']
intro h i
by_cases hi : MeasurableSet i
· exact h i hi
· simp_rw [not_measurable _ hi]
#align measure_theory.vector_measure.ext_iff MeasureTheory.VectorMeasure.ext_iff
@[ext]
theorem ext {s t : VectorMeasure α M} (h : ∀ i : Set α, MeasurableSet i → s i = t i) : s = t :=
(ext_iff s t).2 h
#align measure_theory.vector_measure.ext MeasureTheory.VectorMeasure.ext
variable [T2Space M] {v : VectorMeasure α M} {f : ℕ → Set α}
theorem hasSum_of_disjoint_iUnion [Countable β] {f : β → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : HasSum (fun i => v (f i)) (v (⋃ i, f i)) := by
cases nonempty_encodable β
set g := fun i : ℕ => ⋃ (b : β) (_ : b ∈ Encodable.decode₂ β i), f b with hg
have hg₁ : ∀ i, MeasurableSet (g i) :=
fun _ => MeasurableSet.iUnion fun b => MeasurableSet.iUnion fun _ => hf₁ b
have hg₂ : Pairwise (Disjoint on g) := Encodable.iUnion_decode₂_disjoint_on hf₂
have := v.of_disjoint_iUnion_nat hg₁ hg₂
rw [hg, Encodable.iUnion_decode₂] at this
have hg₃ : (fun i : β => v (f i)) = fun i => v (g (Encodable.encode i)) := by
ext x
rw [hg]
simp only
congr
ext y
simp only [exists_prop, Set.mem_iUnion, Option.mem_def]
constructor
· intro hy
exact ⟨x, (Encodable.decode₂_is_partial_inv _ _).2 rfl, hy⟩
· rintro ⟨b, hb₁, hb₂⟩
rw [Encodable.decode₂_is_partial_inv _ _] at hb₁
rwa [← Encodable.encode_injective hb₁]
rw [Summable.hasSum_iff, this, ← tsum_iUnion_decode₂]
· exact v.empty
· rw [hg₃]
change Summable ((fun i => v (g i)) ∘ Encodable.encode)
rw [Function.Injective.summable_iff Encodable.encode_injective]
· exact (v.m_iUnion hg₁ hg₂).summable
· intro x hx
convert v.empty
simp only [g, Set.iUnion_eq_empty, Option.mem_def, not_exists, Set.mem_range] at hx ⊢
intro i hi
exact False.elim ((hx i) ((Encodable.decode₂_is_partial_inv _ _).1 hi))
#align measure_theory.vector_measure.has_sum_of_disjoint_Union MeasureTheory.VectorMeasure.hasSum_of_disjoint_iUnion
theorem of_disjoint_iUnion [Countable β] {f : β → Set α} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) : v (⋃ i, f i) = ∑' i, v (f i) :=
(hasSum_of_disjoint_iUnion hf₁ hf₂).tsum_eq.symm
#align measure_theory.vector_measure.of_disjoint_Union MeasureTheory.VectorMeasure.of_disjoint_iUnion
theorem of_union {A B : Set α} (h : Disjoint A B) (hA : MeasurableSet A) (hB : MeasurableSet B) :
v (A ∪ B) = v A + v B := by
rw [Set.union_eq_iUnion, of_disjoint_iUnion, tsum_fintype, Fintype.sum_bool, cond, cond]
exacts [fun b => Bool.casesOn b hB hA, pairwise_disjoint_on_bool.2 h]
#align measure_theory.vector_measure.of_union MeasureTheory.VectorMeasure.of_union
theorem of_add_of_diff {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B) (h : A ⊆ B) :
v A + v (B \ A) = v B := by
rw [← of_union (@Set.disjoint_sdiff_right _ A B) hA (hB.diff hA), Set.union_diff_cancel h]
#align measure_theory.vector_measure.of_add_of_diff MeasureTheory.VectorMeasure.of_add_of_diff
theorem of_diff {M : Type*} [AddCommGroup M] [TopologicalSpace M] [T2Space M]
{v : VectorMeasure α M} {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B)
(h : A ⊆ B) : v (B \ A) = v B - v A := by
rw [← of_add_of_diff hA hB h, add_sub_cancel_left]
#align measure_theory.vector_measure.of_diff MeasureTheory.VectorMeasure.of_diff
theorem of_diff_of_diff_eq_zero {A B : Set α} (hA : MeasurableSet A) (hB : MeasurableSet B)
(h' : v (B \ A) = 0) : v (A \ B) + v B = v A := by
symm
calc
v A = v (A \ B ∪ A ∩ B) := by simp only [Set.diff_union_inter]
_ = v (A \ B) + v (A ∩ B) := by
rw [of_union]
· rw [disjoint_comm]
exact Set.disjoint_of_subset_left A.inter_subset_right disjoint_sdiff_self_right
· exact hA.diff hB
· exact hA.inter hB
_ = v (A \ B) + v (A ∩ B ∪ B \ A) := by
rw [of_union, h', add_zero]
· exact Set.disjoint_of_subset_left A.inter_subset_left disjoint_sdiff_self_right
· exact hA.inter hB
· exact hB.diff hA
_ = v (A \ B) + v B := by rw [Set.union_comm, Set.inter_comm, Set.diff_union_inter]
#align measure_theory.vector_measure.of_diff_of_diff_eq_zero MeasureTheory.VectorMeasure.of_diff_of_diff_eq_zero
theorem of_iUnion_nonneg {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
[OrderClosedTopology M] {v : VectorMeasure α M} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) (hf₃ : ∀ i, 0 ≤ v (f i)) : 0 ≤ v (⋃ i, f i) :=
(v.of_disjoint_iUnion_nat hf₁ hf₂).symm ▸ tsum_nonneg hf₃
#align measure_theory.vector_measure.of_Union_nonneg MeasureTheory.VectorMeasure.of_iUnion_nonneg
theorem of_iUnion_nonpos {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
[OrderClosedTopology M] {v : VectorMeasure α M} (hf₁ : ∀ i, MeasurableSet (f i))
(hf₂ : Pairwise (Disjoint on f)) (hf₃ : ∀ i, v (f i) ≤ 0) : v (⋃ i, f i) ≤ 0 :=
(v.of_disjoint_iUnion_nat hf₁ hf₂).symm ▸ tsum_nonpos hf₃
#align measure_theory.vector_measure.of_Union_nonpos MeasureTheory.VectorMeasure.of_iUnion_nonpos
theorem of_nonneg_disjoint_union_eq_zero {s : SignedMeasure α} {A B : Set α} (h : Disjoint A B)
(hA₁ : MeasurableSet A) (hB₁ : MeasurableSet B) (hA₂ : 0 ≤ s A) (hB₂ : 0 ≤ s B)
(hAB : s (A ∪ B) = 0) : s A = 0 := by
rw [of_union h hA₁ hB₁] at hAB
linarith
#align measure_theory.vector_measure.of_nonneg_disjoint_union_eq_zero MeasureTheory.VectorMeasure.of_nonneg_disjoint_union_eq_zero
theorem of_nonpos_disjoint_union_eq_zero {s : SignedMeasure α} {A B : Set α} (h : Disjoint A B)
(hA₁ : MeasurableSet A) (hB₁ : MeasurableSet B) (hA₂ : s A ≤ 0) (hB₂ : s B ≤ 0)
(hAB : s (A ∪ B) = 0) : s A = 0 := by
rw [of_union h hA₁ hB₁] at hAB
linarith
#align measure_theory.vector_measure.of_nonpos_disjoint_union_eq_zero MeasureTheory.VectorMeasure.of_nonpos_disjoint_union_eq_zero
end
section SMul
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
/-- Given a real number `r` and a signed measure `s`, `smul r s` is the signed
measure corresponding to the function `r • s`. -/
def smul (r : R) (v : VectorMeasure α M) : VectorMeasure α M where
measureOf' := r • ⇑v
empty' := by rw [Pi.smul_apply, empty, smul_zero]
not_measurable' _ hi := by rw [Pi.smul_apply, v.not_measurable hi, smul_zero]
m_iUnion' _ hf₁ hf₂ := by exact HasSum.const_smul _ (v.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.smul MeasureTheory.VectorMeasure.smul
instance instSMul : SMul R (VectorMeasure α M) :=
⟨smul⟩
#align measure_theory.vector_measure.has_smul MeasureTheory.VectorMeasure.instSMul
@[simp]
theorem coe_smul (r : R) (v : VectorMeasure α M) : ⇑(r • v) = r • ⇑v := rfl
#align measure_theory.vector_measure.coe_smul MeasureTheory.VectorMeasure.coe_smul
theorem smul_apply (r : R) (v : VectorMeasure α M) (i : Set α) : (r • v) i = r • v i := rfl
#align measure_theory.vector_measure.smul_apply MeasureTheory.VectorMeasure.smul_apply
end SMul
section AddCommMonoid
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
instance instZero : Zero (VectorMeasure α M) :=
⟨⟨0, rfl, fun _ _ => rfl, fun _ _ _ => hasSum_zero⟩⟩
#align measure_theory.vector_measure.has_zero MeasureTheory.VectorMeasure.instZero
instance instInhabited : Inhabited (VectorMeasure α M) :=
⟨0⟩
#align measure_theory.vector_measure.inhabited MeasureTheory.VectorMeasure.instInhabited
@[simp]
theorem coe_zero : ⇑(0 : VectorMeasure α M) = 0 := rfl
#align measure_theory.vector_measure.coe_zero MeasureTheory.VectorMeasure.coe_zero
theorem zero_apply (i : Set α) : (0 : VectorMeasure α M) i = 0 := rfl
#align measure_theory.vector_measure.zero_apply MeasureTheory.VectorMeasure.zero_apply
variable [ContinuousAdd M]
/-- The sum of two vector measure is a vector measure. -/
def add (v w : VectorMeasure α M) : VectorMeasure α M where
measureOf' := v + w
empty' := by simp
not_measurable' _ hi := by rw [Pi.add_apply, v.not_measurable hi, w.not_measurable hi, add_zero]
m_iUnion' f hf₁ hf₂ := HasSum.add (v.m_iUnion hf₁ hf₂) (w.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.add MeasureTheory.VectorMeasure.add
instance instAdd : Add (VectorMeasure α M) :=
⟨add⟩
#align measure_theory.vector_measure.has_add MeasureTheory.VectorMeasure.instAdd
@[simp]
theorem coe_add (v w : VectorMeasure α M) : ⇑(v + w) = v + w := rfl
#align measure_theory.vector_measure.coe_add MeasureTheory.VectorMeasure.coe_add
theorem add_apply (v w : VectorMeasure α M) (i : Set α) : (v + w) i = v i + w i := rfl
#align measure_theory.vector_measure.add_apply MeasureTheory.VectorMeasure.add_apply
instance instAddCommMonoid : AddCommMonoid (VectorMeasure α M) :=
Function.Injective.addCommMonoid _ coe_injective coe_zero coe_add fun _ _ => coe_smul _ _
#align measure_theory.vector_measure.add_comm_monoid MeasureTheory.VectorMeasure.instAddCommMonoid
/-- `(⇑)` is an `AddMonoidHom`. -/
@[simps]
def coeFnAddMonoidHom : VectorMeasure α M →+ Set α → M where
toFun := (⇑)
map_zero' := coe_zero
map_add' := coe_add
#align measure_theory.vector_measure.coe_fn_add_monoid_hom MeasureTheory.VectorMeasure.coeFnAddMonoidHom
end AddCommMonoid
section AddCommGroup
variable {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
/-- The negative of a vector measure is a vector measure. -/
def neg (v : VectorMeasure α M) : VectorMeasure α M where
measureOf' := -v
empty' := by simp
not_measurable' _ hi := by rw [Pi.neg_apply, neg_eq_zero, v.not_measurable hi]
m_iUnion' f hf₁ hf₂ := HasSum.neg <| v.m_iUnion hf₁ hf₂
#align measure_theory.vector_measure.neg MeasureTheory.VectorMeasure.neg
instance instNeg : Neg (VectorMeasure α M) :=
⟨neg⟩
#align measure_theory.vector_measure.has_neg MeasureTheory.VectorMeasure.instNeg
@[simp]
theorem coe_neg (v : VectorMeasure α M) : ⇑(-v) = -v := rfl
#align measure_theory.vector_measure.coe_neg MeasureTheory.VectorMeasure.coe_neg
theorem neg_apply (v : VectorMeasure α M) (i : Set α) : (-v) i = -v i := rfl
#align measure_theory.vector_measure.neg_apply MeasureTheory.VectorMeasure.neg_apply
/-- The difference of two vector measure is a vector measure. -/
def sub (v w : VectorMeasure α M) : VectorMeasure α M where
measureOf' := v - w
empty' := by simp
not_measurable' _ hi := by rw [Pi.sub_apply, v.not_measurable hi, w.not_measurable hi, sub_zero]
m_iUnion' f hf₁ hf₂ := HasSum.sub (v.m_iUnion hf₁ hf₂) (w.m_iUnion hf₁ hf₂)
#align measure_theory.vector_measure.sub MeasureTheory.VectorMeasure.sub
instance instSub : Sub (VectorMeasure α M) :=
⟨sub⟩
#align measure_theory.vector_measure.has_sub MeasureTheory.VectorMeasure.instSub
@[simp]
theorem coe_sub (v w : VectorMeasure α M) : ⇑(v - w) = v - w := rfl
#align measure_theory.vector_measure.coe_sub MeasureTheory.VectorMeasure.coe_sub
theorem sub_apply (v w : VectorMeasure α M) (i : Set α) : (v - w) i = v i - w i := rfl
#align measure_theory.vector_measure.sub_apply MeasureTheory.VectorMeasure.sub_apply
instance instAddCommGroup : AddCommGroup (VectorMeasure α M) :=
Function.Injective.addCommGroup _ coe_injective coe_zero coe_add coe_neg coe_sub
(fun _ _ => coe_smul _ _) fun _ _ => coe_smul _ _
#align measure_theory.vector_measure.add_comm_group MeasureTheory.VectorMeasure.instAddCommGroup
end AddCommGroup
section DistribMulAction
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
instance instDistribMulAction [ContinuousAdd M] : DistribMulAction R (VectorMeasure α M) :=
Function.Injective.distribMulAction coeFnAddMonoidHom coe_injective coe_smul
#align measure_theory.vector_measure.distrib_mul_action MeasureTheory.VectorMeasure.instDistribMulAction
end DistribMulAction
section Module
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [Module R M] [ContinuousConstSMul R M]
instance instModule [ContinuousAdd M] : Module R (VectorMeasure α M) :=
Function.Injective.module R coeFnAddMonoidHom coe_injective coe_smul
#align measure_theory.vector_measure.module MeasureTheory.VectorMeasure.instModule
end Module
end VectorMeasure
namespace Measure
/-- A finite measure coerced into a real function is a signed measure. -/
@[simps]
def toSignedMeasure (μ : Measure α) [hμ : IsFiniteMeasure μ] : SignedMeasure α where
measureOf' := fun s : Set α => if MeasurableSet s then (μ s).toReal else 0
empty' := by simp [μ.empty]
not_measurable' _ hi := if_neg hi
m_iUnion' f hf₁ hf₂ := by
simp only [*, MeasurableSet.iUnion hf₁, if_true, measure_iUnion hf₂ hf₁]
rw [ENNReal.tsum_toReal_eq]
exacts [(summable_measure_toReal hf₁ hf₂).hasSum, fun _ ↦ measure_ne_top _ _]
#align measure_theory.measure.to_signed_measure MeasureTheory.Measure.toSignedMeasure
theorem toSignedMeasure_apply_measurable {μ : Measure α} [IsFiniteMeasure μ] {i : Set α}
(hi : MeasurableSet i) : μ.toSignedMeasure i = (μ i).toReal :=
if_pos hi
#align measure_theory.measure.to_signed_measure_apply_measurable MeasureTheory.Measure.toSignedMeasure_apply_measurable
-- Without this lemma, `singularPart_neg` in `MeasureTheory.Decomposition.Lebesgue` is
-- extremely slow
theorem toSignedMeasure_congr {μ ν : Measure α} [IsFiniteMeasure μ] [IsFiniteMeasure ν]
(h : μ = ν) : μ.toSignedMeasure = ν.toSignedMeasure := by
congr
#align measure_theory.measure.to_signed_measure_congr MeasureTheory.Measure.toSignedMeasure_congr
theorem toSignedMeasure_eq_toSignedMeasure_iff {μ ν : Measure α} [IsFiniteMeasure μ]
[IsFiniteMeasure ν] : μ.toSignedMeasure = ν.toSignedMeasure ↔ μ = ν := by
refine ⟨fun h => ?_, fun h => ?_⟩
· ext1 i hi
have : μ.toSignedMeasure i = ν.toSignedMeasure i := by rw [h]
rwa [toSignedMeasure_apply_measurable hi, toSignedMeasure_apply_measurable hi,
ENNReal.toReal_eq_toReal] at this
<;> exact measure_ne_top _ _
· congr
#align measure_theory.measure.to_signed_measure_eq_to_signed_measure_iff MeasureTheory.Measure.toSignedMeasure_eq_toSignedMeasure_iff
@[simp]
theorem toSignedMeasure_zero : (0 : Measure α).toSignedMeasure = 0 := by
ext i
simp
#align measure_theory.measure.to_signed_measure_zero MeasureTheory.Measure.toSignedMeasure_zero
@[simp]
theorem toSignedMeasure_add (μ ν : Measure α) [IsFiniteMeasure μ] [IsFiniteMeasure ν] :
(μ + ν).toSignedMeasure = μ.toSignedMeasure + ν.toSignedMeasure := by
ext i hi
rw [toSignedMeasure_apply_measurable hi, add_apply,
ENNReal.toReal_add (ne_of_lt (measure_lt_top _ _)) (ne_of_lt (measure_lt_top _ _)),
VectorMeasure.add_apply, toSignedMeasure_apply_measurable hi,
toSignedMeasure_apply_measurable hi]
#align measure_theory.measure.to_signed_measure_add MeasureTheory.Measure.toSignedMeasure_add
@[simp]
theorem toSignedMeasure_smul (μ : Measure α) [IsFiniteMeasure μ] (r : ℝ≥0) :
(r • μ).toSignedMeasure = r • μ.toSignedMeasure := by
ext i hi
rw [toSignedMeasure_apply_measurable hi, VectorMeasure.smul_apply,
toSignedMeasure_apply_measurable hi, coe_smul, Pi.smul_apply, ENNReal.toReal_smul]
#align measure_theory.measure.to_signed_measure_smul MeasureTheory.Measure.toSignedMeasure_smul
/-- A measure is a vector measure over `ℝ≥0∞`. -/
@[simps]
def toENNRealVectorMeasure (μ : Measure α) : VectorMeasure α ℝ≥0∞ where
measureOf' := fun i : Set α => if MeasurableSet i then μ i else 0
empty' := by simp [μ.empty]
not_measurable' _ hi := if_neg hi
m_iUnion' _ hf₁ hf₂ := by
simp only
rw [Summable.hasSum_iff ENNReal.summable, if_pos (MeasurableSet.iUnion hf₁),
MeasureTheory.measure_iUnion hf₂ hf₁]
exact tsum_congr fun n => if_pos (hf₁ n)
#align measure_theory.measure.to_ennreal_vector_measure MeasureTheory.Measure.toENNRealVectorMeasure
theorem toENNRealVectorMeasure_apply_measurable {μ : Measure α} {i : Set α} (hi : MeasurableSet i) :
μ.toENNRealVectorMeasure i = μ i :=
if_pos hi
#align measure_theory.measure.to_ennreal_vector_measure_apply_measurable MeasureTheory.Measure.toENNRealVectorMeasure_apply_measurable
@[simp]
theorem toENNRealVectorMeasure_zero : (0 : Measure α).toENNRealVectorMeasure = 0 := by
ext i
simp
#align measure_theory.measure.to_ennreal_vector_measure_zero MeasureTheory.Measure.toENNRealVectorMeasure_zero
@[simp]
theorem toENNRealVectorMeasure_add (μ ν : Measure α) :
(μ + ν).toENNRealVectorMeasure = μ.toENNRealVectorMeasure + ν.toENNRealVectorMeasure := by
refine MeasureTheory.VectorMeasure.ext fun i hi => ?_
rw [toENNRealVectorMeasure_apply_measurable hi, add_apply, VectorMeasure.add_apply,
toENNRealVectorMeasure_apply_measurable hi, toENNRealVectorMeasure_apply_measurable hi]
#align measure_theory.measure.to_ennreal_vector_measure_add MeasureTheory.Measure.toENNRealVectorMeasure_add
theorem toSignedMeasure_sub_apply {μ ν : Measure α} [IsFiniteMeasure μ] [IsFiniteMeasure ν]
{i : Set α} (hi : MeasurableSet i) :
(μ.toSignedMeasure - ν.toSignedMeasure) i = (μ i).toReal - (ν i).toReal := by
rw [VectorMeasure.sub_apply, toSignedMeasure_apply_measurable hi,
Measure.toSignedMeasure_apply_measurable hi]
#align measure_theory.measure.to_signed_measure_sub_apply MeasureTheory.Measure.toSignedMeasure_sub_apply
end Measure
namespace VectorMeasure
open Measure
section
/-- A vector measure over `ℝ≥0∞` is a measure. -/
def ennrealToMeasure {_ : MeasurableSpace α} (v : VectorMeasure α ℝ≥0∞) : Measure α :=
ofMeasurable (fun s _ => v s) v.empty fun _ hf₁ hf₂ => v.of_disjoint_iUnion_nat hf₁ hf₂
#align measure_theory.vector_measure.ennreal_to_measure MeasureTheory.VectorMeasure.ennrealToMeasure
theorem ennrealToMeasure_apply {m : MeasurableSpace α} {v : VectorMeasure α ℝ≥0∞} {s : Set α}
(hs : MeasurableSet s) : ennrealToMeasure v s = v s := by
rw [ennrealToMeasure, ofMeasurable_apply _ hs]
#align measure_theory.vector_measure.ennreal_to_measure_apply MeasureTheory.VectorMeasure.ennrealToMeasure_apply
@[simp]
theorem _root_.MeasureTheory.Measure.toENNRealVectorMeasure_ennrealToMeasure
(μ : VectorMeasure α ℝ≥0∞) :
toENNRealVectorMeasure (ennrealToMeasure μ) = μ := ext fun s hs => by
rw [toENNRealVectorMeasure_apply_measurable hs, ennrealToMeasure_apply hs]
@[simp]
theorem ennrealToMeasure_toENNRealVectorMeasure (μ : Measure α) :
ennrealToMeasure (toENNRealVectorMeasure μ) = μ := Measure.ext fun s hs => by
rw [ennrealToMeasure_apply hs, toENNRealVectorMeasure_apply_measurable hs]
/-- The equiv between `VectorMeasure α ℝ≥0∞` and `Measure α` formed by
`MeasureTheory.VectorMeasure.ennrealToMeasure` and
`MeasureTheory.Measure.toENNRealVectorMeasure`. -/
@[simps]
def equivMeasure [MeasurableSpace α] : VectorMeasure α ℝ≥0∞ ≃ Measure α where
toFun := ennrealToMeasure
invFun := toENNRealVectorMeasure
left_inv := toENNRealVectorMeasure_ennrealToMeasure
right_inv := ennrealToMeasure_toENNRealVectorMeasure
#align measure_theory.vector_measure.equiv_measure MeasureTheory.VectorMeasure.equivMeasure
end
section
variable [MeasurableSpace α] [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable (v : VectorMeasure α M)
/-- The pushforward of a vector measure along a function. -/
def map (v : VectorMeasure α M) (f : α → β) : VectorMeasure β M :=
if hf : Measurable f then
{ measureOf' := fun s => if MeasurableSet s then v (f ⁻¹' s) else 0
empty' := by simp
not_measurable' := fun i hi => if_neg hi
m_iUnion' := by
intro g hg₁ hg₂
simp only
convert v.m_iUnion (fun i => hf (hg₁ i)) fun i j hij => (hg₂ hij).preimage _
· rw [if_pos (hg₁ _)]
· rw [Set.preimage_iUnion, if_pos (MeasurableSet.iUnion hg₁)] }
else 0
#align measure_theory.vector_measure.map MeasureTheory.VectorMeasure.map
theorem map_not_measurable {f : α → β} (hf : ¬Measurable f) : v.map f = 0 :=
dif_neg hf
#align measure_theory.vector_measure.map_not_measurable MeasureTheory.VectorMeasure.map_not_measurable
theorem map_apply {f : α → β} (hf : Measurable f) {s : Set β} (hs : MeasurableSet s) :
v.map f s = v (f ⁻¹' s) := by
rw [map, dif_pos hf]
exact if_pos hs
#align measure_theory.vector_measure.map_apply MeasureTheory.VectorMeasure.map_apply
@[simp]
theorem map_id : v.map id = v :=
ext fun i hi => by rw [map_apply v measurable_id hi, Set.preimage_id]
#align measure_theory.vector_measure.map_id MeasureTheory.VectorMeasure.map_id
@[simp]
theorem map_zero (f : α → β) : (0 : VectorMeasure α M).map f = 0 := by
by_cases hf : Measurable f
· ext i hi
rw [map_apply _ hf hi, zero_apply, zero_apply]
· exact dif_neg hf
#align measure_theory.vector_measure.map_zero MeasureTheory.VectorMeasure.map_zero
section
variable {N : Type*} [AddCommMonoid N] [TopologicalSpace N]
/-- Given a vector measure `v` on `M` and a continuous `AddMonoidHom` `f : M → N`, `f ∘ v` is a
vector measure on `N`. -/
def mapRange (v : VectorMeasure α M) (f : M →+ N) (hf : Continuous f) : VectorMeasure α N where
measureOf' s := f (v s)
empty' := by simp only; rw [empty, AddMonoidHom.map_zero]
not_measurable' i hi := by simp only; rw [not_measurable v hi, AddMonoidHom.map_zero]
m_iUnion' g hg₁ hg₂ := HasSum.map (v.m_iUnion hg₁ hg₂) f hf
#align measure_theory.vector_measure.map_range MeasureTheory.VectorMeasure.mapRange
@[simp]
theorem mapRange_apply {f : M →+ N} (hf : Continuous f) {s : Set α} : v.mapRange f hf s = f (v s) :=
rfl
#align measure_theory.vector_measure.map_range_apply MeasureTheory.VectorMeasure.mapRange_apply
@[simp]
theorem mapRange_id : v.mapRange (AddMonoidHom.id M) continuous_id = v := by
ext
rfl
#align measure_theory.vector_measure.map_range_id MeasureTheory.VectorMeasure.mapRange_id
@[simp]
theorem mapRange_zero {f : M →+ N} (hf : Continuous f) :
mapRange (0 : VectorMeasure α M) f hf = 0 := by
ext
simp
#align measure_theory.vector_measure.map_range_zero MeasureTheory.VectorMeasure.mapRange_zero
section ContinuousAdd
variable [ContinuousAdd M] [ContinuousAdd N]
@[simp]
theorem mapRange_add {v w : VectorMeasure α M} {f : M →+ N} (hf : Continuous f) :
(v + w).mapRange f hf = v.mapRange f hf + w.mapRange f hf := by
ext
simp
#align measure_theory.vector_measure.map_range_add MeasureTheory.VectorMeasure.mapRange_add
/-- Given a continuous `AddMonoidHom` `f : M → N`, `mapRangeHom` is the `AddMonoidHom` mapping the
vector measure `v` on `M` to the vector measure `f ∘ v` on `N`. -/
def mapRangeHom (f : M →+ N) (hf : Continuous f) : VectorMeasure α M →+ VectorMeasure α N where
toFun v := v.mapRange f hf
map_zero' := mapRange_zero hf
map_add' _ _ := mapRange_add hf
#align measure_theory.vector_measure.map_range_hom MeasureTheory.VectorMeasure.mapRangeHom
end ContinuousAdd
section Module
variable {R : Type*} [Semiring R] [Module R M] [Module R N]
variable [ContinuousAdd M] [ContinuousAdd N] [ContinuousConstSMul R M] [ContinuousConstSMul R N]
/-- Given a continuous linear map `f : M → N`, `mapRangeₗ` is the linear map mapping the
vector measure `v` on `M` to the vector measure `f ∘ v` on `N`. -/
def mapRangeₗ (f : M →ₗ[R] N) (hf : Continuous f) : VectorMeasure α M →ₗ[R] VectorMeasure α N where
toFun v := v.mapRange f.toAddMonoidHom hf
map_add' _ _ := mapRange_add hf
map_smul' := by
intros
ext
simp
#align measure_theory.vector_measure.map_rangeₗ MeasureTheory.VectorMeasure.mapRangeₗ
end Module
end
/-- The restriction of a vector measure on some set. -/
def restrict (v : VectorMeasure α M) (i : Set α) : VectorMeasure α M :=
if hi : MeasurableSet i then
{ measureOf' := fun s => if MeasurableSet s then v (s ∩ i) else 0
empty' := by simp
not_measurable' := fun i hi => if_neg hi
m_iUnion' := by
intro f hf₁ hf₂
simp only
convert v.m_iUnion (fun n => (hf₁ n).inter hi)
(hf₂.mono fun i j => Disjoint.mono inf_le_left inf_le_left)
· rw [if_pos (hf₁ _)]
· rw [Set.iUnion_inter, if_pos (MeasurableSet.iUnion hf₁)] }
else 0
#align measure_theory.vector_measure.restrict MeasureTheory.VectorMeasure.restrict
theorem restrict_not_measurable {i : Set α} (hi : ¬MeasurableSet i) : v.restrict i = 0 :=
dif_neg hi
#align measure_theory.vector_measure.restrict_not_measurable MeasureTheory.VectorMeasure.restrict_not_measurable
theorem restrict_apply {i : Set α} (hi : MeasurableSet i) {j : Set α} (hj : MeasurableSet j) :
v.restrict i j = v (j ∩ i) := by
rw [restrict, dif_pos hi]
exact if_pos hj
#align measure_theory.vector_measure.restrict_apply MeasureTheory.VectorMeasure.restrict_apply
theorem restrict_eq_self {i : Set α} (hi : MeasurableSet i) {j : Set α} (hj : MeasurableSet j)
(hij : j ⊆ i) : v.restrict i j = v j := by
rw [restrict_apply v hi hj, Set.inter_eq_left.2 hij]
#align measure_theory.vector_measure.restrict_eq_self MeasureTheory.VectorMeasure.restrict_eq_self
@[simp]
theorem restrict_empty : v.restrict ∅ = 0 :=
ext fun i hi => by
rw [restrict_apply v MeasurableSet.empty hi, Set.inter_empty, v.empty, zero_apply]
#align measure_theory.vector_measure.restrict_empty MeasureTheory.VectorMeasure.restrict_empty
@[simp]
theorem restrict_univ : v.restrict Set.univ = v :=
ext fun i hi => by rw [restrict_apply v MeasurableSet.univ hi, Set.inter_univ]
#align measure_theory.vector_measure.restrict_univ MeasureTheory.VectorMeasure.restrict_univ
@[simp]
theorem restrict_zero {i : Set α} : (0 : VectorMeasure α M).restrict i = 0 := by
by_cases hi : MeasurableSet i
· ext j hj
rw [restrict_apply 0 hi hj, zero_apply, zero_apply]
· exact dif_neg hi
#align measure_theory.vector_measure.restrict_zero MeasureTheory.VectorMeasure.restrict_zero
section ContinuousAdd
variable [ContinuousAdd M]
theorem map_add (v w : VectorMeasure α M) (f : α → β) : (v + w).map f = v.map f + w.map f := by
by_cases hf : Measurable f
· ext i hi
simp [map_apply _ hf hi]
· simp [map, dif_neg hf]
#align measure_theory.vector_measure.map_add MeasureTheory.VectorMeasure.map_add
/-- `VectorMeasure.map` as an additive monoid homomorphism. -/
@[simps]
def mapGm (f : α → β) : VectorMeasure α M →+ VectorMeasure β M where
toFun v := v.map f
map_zero' := map_zero f
map_add' _ _ := map_add _ _ f
#align measure_theory.vector_measure.map_gm MeasureTheory.VectorMeasure.mapGm
theorem restrict_add (v w : VectorMeasure α M) (i : Set α) :
(v + w).restrict i = v.restrict i + w.restrict i := by
by_cases hi : MeasurableSet i
· ext j hj
simp [restrict_apply _ hi hj]
· simp [restrict_not_measurable _ hi]
#align measure_theory.vector_measure.restrict_add MeasureTheory.VectorMeasure.restrict_add
/-- `VectorMeasure.restrict` as an additive monoid homomorphism. -/
@[simps]
def restrictGm (i : Set α) : VectorMeasure α M →+ VectorMeasure α M where
toFun v := v.restrict i
map_zero' := restrict_zero
map_add' _ _ := restrict_add _ _ i
#align measure_theory.vector_measure.restrict_gm MeasureTheory.VectorMeasure.restrictGm
end ContinuousAdd
end
section
variable [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M]
@[simp]
theorem map_smul {v : VectorMeasure α M} {f : α → β} (c : R) : (c • v).map f = c • v.map f := by
by_cases hf : Measurable f
· ext i hi
simp [map_apply _ hf hi]
· simp only [map, dif_neg hf]
-- `smul_zero` does not work since we do not require `ContinuousAdd`
ext i
simp
#align measure_theory.vector_measure.map_smul MeasureTheory.VectorMeasure.map_smul
@[simp]
theorem restrict_smul {v : VectorMeasure α M} {i : Set α} (c : R) :
(c • v).restrict i = c • v.restrict i := by
by_cases hi : MeasurableSet i
· ext j hj
simp [restrict_apply _ hi hj]
· simp only [restrict_not_measurable _ hi]
-- `smul_zero` does not work since we do not require `ContinuousAdd`
ext j
simp
#align measure_theory.vector_measure.restrict_smul MeasureTheory.VectorMeasure.restrict_smul
end
section
variable [MeasurableSpace β]
variable {M : Type*} [AddCommMonoid M] [TopologicalSpace M]
variable {R : Type*} [Semiring R] [Module R M] [ContinuousConstSMul R M] [ContinuousAdd M]
/-- `VectorMeasure.map` as a linear map. -/
@[simps]
def mapₗ (f : α → β) : VectorMeasure α M →ₗ[R] VectorMeasure β M where
toFun v := v.map f
map_add' _ _ := map_add _ _ f
map_smul' _ _ := map_smul _
#align measure_theory.vector_measure.mapₗ MeasureTheory.VectorMeasure.mapₗ
/-- `VectorMeasure.restrict` as an additive monoid homomorphism. -/
@[simps]
def restrictₗ (i : Set α) : VectorMeasure α M →ₗ[R] VectorMeasure α M where
toFun v := v.restrict i
map_add' _ _ := restrict_add _ _ i
map_smul' _ _ := restrict_smul _
#align measure_theory.vector_measure.restrictₗ MeasureTheory.VectorMeasure.restrictₗ
end
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
/-- Vector measures over a partially ordered monoid is partially ordered.
This definition is consistent with `Measure.instPartialOrder`. -/
instance instPartialOrder : PartialOrder (VectorMeasure α M) where
le v w := ∀ i, MeasurableSet i → v i ≤ w i
le_refl v i _ := le_rfl
le_trans u v w h₁ h₂ i hi := le_trans (h₁ i hi) (h₂ i hi)
le_antisymm v w h₁ h₂ := ext fun i hi => le_antisymm (h₁ i hi) (h₂ i hi)
variable {u v w : VectorMeasure α M}
theorem le_iff : v ≤ w ↔ ∀ i, MeasurableSet i → v i ≤ w i := Iff.rfl
#align measure_theory.vector_measure.le_iff MeasureTheory.VectorMeasure.le_iff
theorem le_iff' : v ≤ w ↔ ∀ i, v i ≤ w i := by
refine ⟨fun h i => ?_, fun h i _ => h i⟩
by_cases hi : MeasurableSet i
· exact h i hi
· rw [v.not_measurable hi, w.not_measurable hi]
#align measure_theory.vector_measure.le_iff' MeasureTheory.VectorMeasure.le_iff'
end
set_option quotPrecheck false in -- Porting note: error message suggested to do this
scoped[MeasureTheory]
notation:50 v " ≤[" i:50 "] " w:50 =>
MeasureTheory.VectorMeasure.restrict v i ≤ MeasureTheory.VectorMeasure.restrict w i
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
variable (v w : VectorMeasure α M)
theorem restrict_le_restrict_iff {i : Set α} (hi : MeasurableSet i) :
v ≤[i] w ↔ ∀ ⦃j⦄, MeasurableSet j → j ⊆ i → v j ≤ w j :=
⟨fun h j hj₁ hj₂ => restrict_eq_self v hi hj₁ hj₂ ▸ restrict_eq_self w hi hj₁ hj₂ ▸ h j hj₁,
fun h => le_iff.1 fun _ hj =>
(restrict_apply v hi hj).symm ▸ (restrict_apply w hi hj).symm ▸
h (hj.inter hi) Set.inter_subset_right⟩
#align measure_theory.vector_measure.restrict_le_restrict_iff MeasureTheory.VectorMeasure.restrict_le_restrict_iff
theorem subset_le_of_restrict_le_restrict {i : Set α} (hi : MeasurableSet i) (hi₂ : v ≤[i] w)
{j : Set α} (hj : j ⊆ i) : v j ≤ w j := by
by_cases hj₁ : MeasurableSet j
· exact (restrict_le_restrict_iff _ _ hi).1 hi₂ hj₁ hj
· rw [v.not_measurable hj₁, w.not_measurable hj₁]
#align measure_theory.vector_measure.subset_le_of_restrict_le_restrict MeasureTheory.VectorMeasure.subset_le_of_restrict_le_restrict
theorem restrict_le_restrict_of_subset_le {i : Set α}
(h : ∀ ⦃j⦄, MeasurableSet j → j ⊆ i → v j ≤ w j) : v ≤[i] w := by
by_cases hi : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi).2 h
· rw [restrict_not_measurable v hi, restrict_not_measurable w hi]
#align measure_theory.vector_measure.restrict_le_restrict_of_subset_le MeasureTheory.VectorMeasure.restrict_le_restrict_of_subset_le
theorem restrict_le_restrict_subset {i j : Set α} (hi₁ : MeasurableSet i) (hi₂ : v ≤[i] w)
(hij : j ⊆ i) : v ≤[j] w :=
restrict_le_restrict_of_subset_le v w fun _ _ hk₂ =>
subset_le_of_restrict_le_restrict v w hi₁ hi₂ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.restrict_le_restrict_subset MeasureTheory.VectorMeasure.restrict_le_restrict_subset
theorem le_restrict_empty : v ≤[∅] w := by
intro j _
rw [restrict_empty, restrict_empty]
#align measure_theory.vector_measure.le_restrict_empty MeasureTheory.VectorMeasure.le_restrict_empty
theorem le_restrict_univ_iff_le : v ≤[Set.univ] w ↔ v ≤ w := by
constructor
· intro h s hs
have := h s hs
rwa [restrict_apply _ MeasurableSet.univ hs, Set.inter_univ,
restrict_apply _ MeasurableSet.univ hs, Set.inter_univ] at this
· intro h s hs
rw [restrict_apply _ MeasurableSet.univ hs, Set.inter_univ,
restrict_apply _ MeasurableSet.univ hs, Set.inter_univ]
exact h s hs
#align measure_theory.vector_measure.le_restrict_univ_iff_le MeasureTheory.VectorMeasure.le_restrict_univ_iff_le
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommGroup M] [TopologicalAddGroup M]
variable (v w : VectorMeasure α M)
nonrec theorem neg_le_neg {i : Set α} (hi : MeasurableSet i) (h : v ≤[i] w) : -w ≤[i] -v := by
intro j hj₁
rw [restrict_apply _ hi hj₁, restrict_apply _ hi hj₁, neg_apply, neg_apply]
refine neg_le_neg ?_
rw [← restrict_apply _ hi hj₁, ← restrict_apply _ hi hj₁]
exact h j hj₁
#align measure_theory.vector_measure.neg_le_neg MeasureTheory.VectorMeasure.neg_le_neg
@[simp]
theorem neg_le_neg_iff {i : Set α} (hi : MeasurableSet i) : -w ≤[i] -v ↔ v ≤[i] w :=
⟨fun h => neg_neg v ▸ neg_neg w ▸ neg_le_neg _ _ hi h, fun h => neg_le_neg _ _ hi h⟩
#align measure_theory.vector_measure.neg_le_neg_iff MeasureTheory.VectorMeasure.neg_le_neg_iff
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M] [OrderClosedTopology M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem restrict_le_restrict_iUnion {f : ℕ → Set α} (hf₁ : ∀ n, MeasurableSet (f n))
(hf₂ : ∀ n, v ≤[f n] w) : v ≤[⋃ n, f n] w := by
refine restrict_le_restrict_of_subset_le v w fun a ha₁ ha₂ => ?_
have ha₃ : ⋃ n, a ∩ disjointed f n = a := by
rwa [← Set.inter_iUnion, iUnion_disjointed, Set.inter_eq_left]
have ha₄ : Pairwise (Disjoint on fun n => a ∩ disjointed f n) :=
(disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
rw [← ha₃, v.of_disjoint_iUnion_nat _ ha₄, w.of_disjoint_iUnion_nat _ ha₄]
· refine tsum_le_tsum (fun n => (restrict_le_restrict_iff v w (hf₁ n)).1 (hf₂ n) ?_ ?_) ?_ ?_
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact Set.Subset.trans Set.inter_subset_right (disjointed_subset _ _)
· refine (v.m_iUnion (fun n => ?_) ?_).summable
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact (disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
· refine (w.m_iUnion (fun n => ?_) ?_).summable
· exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact (disjoint_disjointed _).mono fun i j => Disjoint.mono inf_le_right inf_le_right
· intro n
exact ha₁.inter (MeasurableSet.disjointed hf₁ n)
· exact fun n => ha₁.inter (MeasurableSet.disjointed hf₁ n)
#align measure_theory.vector_measure.restrict_le_restrict_Union MeasureTheory.VectorMeasure.restrict_le_restrict_iUnion
theorem restrict_le_restrict_countable_iUnion [Countable β] {f : β → Set α}
(hf₁ : ∀ b, MeasurableSet (f b)) (hf₂ : ∀ b, v ≤[f b] w) : v ≤[⋃ b, f b] w := by
cases nonempty_encodable β
rw [← Encodable.iUnion_decode₂]
refine restrict_le_restrict_iUnion v w ?_ ?_
· intro n
measurability
· intro n
cases' Encodable.decode₂ β n with b
· simp
· simp [hf₂ b]
#align measure_theory.vector_measure.restrict_le_restrict_countable_Union MeasureTheory.VectorMeasure.restrict_le_restrict_countable_iUnion
theorem restrict_le_restrict_union (hi₁ : MeasurableSet i) (hi₂ : v ≤[i] w) (hj₁ : MeasurableSet j)
(hj₂ : v ≤[j] w) : v ≤[i ∪ j] w := by
rw [Set.union_eq_iUnion]
refine restrict_le_restrict_countable_iUnion v w ?_ ?_
· measurability
· rintro (_ | _) <;> simpa
#align measure_theory.vector_measure.restrict_le_restrict_union MeasureTheory.VectorMeasure.restrict_le_restrict_union
end
section
variable {M : Type*} [TopologicalSpace M] [OrderedAddCommMonoid M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem nonneg_of_zero_le_restrict (hi₂ : 0 ≤[i] v) : 0 ≤ v i := by
by_cases hi₁ : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi₁).1 hi₂ hi₁ Set.Subset.rfl
· rw [v.not_measurable hi₁]
#align measure_theory.vector_measure.nonneg_of_zero_le_restrict MeasureTheory.VectorMeasure.nonneg_of_zero_le_restrict
theorem nonpos_of_restrict_le_zero (hi₂ : v ≤[i] 0) : v i ≤ 0 := by
by_cases hi₁ : MeasurableSet i
· exact (restrict_le_restrict_iff _ _ hi₁).1 hi₂ hi₁ Set.Subset.rfl
· rw [v.not_measurable hi₁]
#align measure_theory.vector_measure.nonpos_of_restrict_le_zero MeasureTheory.VectorMeasure.nonpos_of_restrict_le_zero
theorem zero_le_restrict_not_measurable (hi : ¬MeasurableSet i) : 0 ≤[i] v := by
rw [restrict_zero, restrict_not_measurable _ hi]
#align measure_theory.vector_measure.zero_le_restrict_not_measurable MeasureTheory.VectorMeasure.zero_le_restrict_not_measurable
theorem restrict_le_zero_of_not_measurable (hi : ¬MeasurableSet i) : v ≤[i] 0 := by
rw [restrict_zero, restrict_not_measurable _ hi]
#align measure_theory.vector_measure.restrict_le_zero_of_not_measurable MeasureTheory.VectorMeasure.restrict_le_zero_of_not_measurable
theorem measurable_of_not_zero_le_restrict (hi : ¬0 ≤[i] v) : MeasurableSet i :=
Not.imp_symm (zero_le_restrict_not_measurable _) hi
#align measure_theory.vector_measure.measurable_of_not_zero_le_restrict MeasureTheory.VectorMeasure.measurable_of_not_zero_le_restrict
theorem measurable_of_not_restrict_le_zero (hi : ¬v ≤[i] 0) : MeasurableSet i :=
Not.imp_symm (restrict_le_zero_of_not_measurable _) hi
#align measure_theory.vector_measure.measurable_of_not_restrict_le_zero MeasureTheory.VectorMeasure.measurable_of_not_restrict_le_zero
theorem zero_le_restrict_subset (hi₁ : MeasurableSet i) (hij : j ⊆ i) (hi₂ : 0 ≤[i] v) : 0 ≤[j] v :=
restrict_le_restrict_of_subset_le _ _ fun _ hk₁ hk₂ =>
(restrict_le_restrict_iff _ _ hi₁).1 hi₂ hk₁ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.zero_le_restrict_subset MeasureTheory.VectorMeasure.zero_le_restrict_subset
theorem restrict_le_zero_subset (hi₁ : MeasurableSet i) (hij : j ⊆ i) (hi₂ : v ≤[i] 0) : v ≤[j] 0 :=
restrict_le_restrict_of_subset_le _ _ fun _ hk₁ hk₂ =>
(restrict_le_restrict_iff _ _ hi₁).1 hi₂ hk₁ (Set.Subset.trans hk₂ hij)
#align measure_theory.vector_measure.restrict_le_zero_subset MeasureTheory.VectorMeasure.restrict_le_zero_subset
end
section
variable {M : Type*} [TopologicalSpace M] [LinearOrderedAddCommMonoid M]
variable (v w : VectorMeasure α M) {i j : Set α}
theorem exists_pos_measure_of_not_restrict_le_zero (hi : ¬v ≤[i] 0) :
∃ j : Set α, MeasurableSet j ∧ j ⊆ i ∧ 0 < v j := by
have hi₁ : MeasurableSet i := measurable_of_not_restrict_le_zero _ hi
rw [restrict_le_restrict_iff _ _ hi₁] at hi
push_neg at hi
exact hi
#align measure_theory.vector_measure.exists_pos_measure_of_not_restrict_le_zero MeasureTheory.VectorMeasure.exists_pos_measure_of_not_restrict_le_zero
end
section
variable {M : Type*} [TopologicalSpace M] [AddCommMonoid M] [PartialOrder M]
[CovariantClass M M (· + ·) (· ≤ ·)] [ContinuousAdd M]
instance covariant_add_le :
CovariantClass (VectorMeasure α M) (VectorMeasure α M) (· + ·) (· ≤ ·) :=
⟨fun _ _ _ h i hi => add_le_add_left (h i hi) _⟩
#align measure_theory.vector_measure.covariant_add_le MeasureTheory.VectorMeasure.covariant_add_le
end
section
variable {L M N : Type*}
variable [AddCommMonoid L] [TopologicalSpace L] [AddCommMonoid M] [TopologicalSpace M]
[AddCommMonoid N] [TopologicalSpace N]
/-- A vector measure `v` is absolutely continuous with respect to a measure `μ` if for all sets
`s`, `μ s = 0`, we have `v s = 0`. -/
def AbsolutelyContinuous (v : VectorMeasure α M) (w : VectorMeasure α N) :=
∀ ⦃s : Set α⦄, w s = 0 → v s = 0
#align measure_theory.vector_measure.absolutely_continuous MeasureTheory.VectorMeasure.AbsolutelyContinuous
@[inherit_doc VectorMeasure.AbsolutelyContinuous]
scoped[MeasureTheory] infixl:50 " ≪ᵥ " => MeasureTheory.VectorMeasure.AbsolutelyContinuous
open MeasureTheory
namespace AbsolutelyContinuous
variable {v : VectorMeasure α M} {w : VectorMeasure α N}
theorem mk (h : ∀ ⦃s : Set α⦄, MeasurableSet s → w s = 0 → v s = 0) : v ≪ᵥ w := by
intro s hs
by_cases hmeas : MeasurableSet s
· exact h hmeas hs
· exact not_measurable v hmeas
#align measure_theory.vector_measure.absolutely_continuous.mk MeasureTheory.VectorMeasure.AbsolutelyContinuous.mk
theorem eq {w : VectorMeasure α M} (h : v = w) : v ≪ᵥ w :=
fun _ hs => h.symm ▸ hs
#align measure_theory.vector_measure.absolutely_continuous.eq MeasureTheory.VectorMeasure.AbsolutelyContinuous.eq
@[refl]
theorem refl (v : VectorMeasure α M) : v ≪ᵥ v :=
eq rfl
#align measure_theory.vector_measure.absolutely_continuous.refl MeasureTheory.VectorMeasure.AbsolutelyContinuous.refl
@[trans]
theorem trans {u : VectorMeasure α L} {v : VectorMeasure α M} {w : VectorMeasure α N} (huv : u ≪ᵥ v)
(hvw : v ≪ᵥ w) : u ≪ᵥ w :=
fun _ hs => huv <| hvw hs
#align measure_theory.vector_measure.absolutely_continuous.trans MeasureTheory.VectorMeasure.AbsolutelyContinuous.trans
theorem zero (v : VectorMeasure α N) : (0 : VectorMeasure α M) ≪ᵥ v :=
fun s _ => VectorMeasure.zero_apply s
#align measure_theory.vector_measure.absolutely_continuous.zero MeasureTheory.VectorMeasure.AbsolutelyContinuous.zero
theorem neg_left {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : -v ≪ᵥ w := by
intro s hs
rw [neg_apply, h hs, neg_zero]
#align measure_theory.vector_measure.absolutely_continuous.neg_left MeasureTheory.VectorMeasure.AbsolutelyContinuous.neg_left
theorem neg_right {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : v ≪ᵥ -w := by
intro s hs
rw [neg_apply, neg_eq_zero] at hs
exact h hs
#align measure_theory.vector_measure.absolutely_continuous.neg_right MeasureTheory.VectorMeasure.AbsolutelyContinuous.neg_right
theorem add [ContinuousAdd M] {v₁ v₂ : VectorMeasure α M} {w : VectorMeasure α N} (hv₁ : v₁ ≪ᵥ w)
(hv₂ : v₂ ≪ᵥ w) : v₁ + v₂ ≪ᵥ w := by
intro s hs
rw [add_apply, hv₁ hs, hv₂ hs, zero_add]
#align measure_theory.vector_measure.absolutely_continuous.add MeasureTheory.VectorMeasure.AbsolutelyContinuous.add
theorem sub {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v₁ v₂ : VectorMeasure α M} {w : VectorMeasure α N} (hv₁ : v₁ ≪ᵥ w) (hv₂ : v₂ ≪ᵥ w) :
v₁ - v₂ ≪ᵥ w := by
intro s hs
rw [sub_apply, hv₁ hs, hv₂ hs, zero_sub, neg_zero]
#align measure_theory.vector_measure.absolutely_continuous.sub MeasureTheory.VectorMeasure.AbsolutelyContinuous.sub
theorem smul {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M] {r : R}
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ≪ᵥ w) : r • v ≪ᵥ w := by
intro s hs
rw [smul_apply, h hs, smul_zero]
#align measure_theory.vector_measure.absolutely_continuous.smul MeasureTheory.VectorMeasure.AbsolutelyContinuous.smul
theorem map [MeasureSpace β] (h : v ≪ᵥ w) (f : α → β) : v.map f ≪ᵥ w.map f := by
by_cases hf : Measurable f
· refine mk fun s hs hws => ?_
rw [map_apply _ hf hs] at hws ⊢
exact h hws
· intro s _
rw [map_not_measurable v hf, zero_apply]
#align measure_theory.vector_measure.absolutely_continuous.map MeasureTheory.VectorMeasure.AbsolutelyContinuous.map
theorem ennrealToMeasure {μ : VectorMeasure α ℝ≥0∞} :
(∀ ⦃s : Set α⦄, μ.ennrealToMeasure s = 0 → v s = 0) ↔ v ≪ᵥ μ := by
constructor <;> intro h
· refine mk fun s hmeas hs => h ?_
rw [← hs, ennrealToMeasure_apply hmeas]
· intro s hs
by_cases hmeas : MeasurableSet s
· rw [ennrealToMeasure_apply hmeas] at hs
exact h hs
· exact not_measurable v hmeas
#align measure_theory.vector_measure.absolutely_continuous.ennreal_to_measure MeasureTheory.VectorMeasure.AbsolutelyContinuous.ennrealToMeasure
end AbsolutelyContinuous
/-- Two vector measures `v` and `w` are said to be mutually singular if there exists a measurable
set `s`, such that for all `t ⊆ s`, `v t = 0` and for all `t ⊆ sᶜ`, `w t = 0`.
We note that we do not require the measurability of `t` in the definition since this makes it easier
to use. This is equivalent to the definition which requires measurability. To prove
`MutuallySingular` with the measurability condition, use
`MeasureTheory.VectorMeasure.MutuallySingular.mk`. -/
def MutuallySingular (v : VectorMeasure α M) (w : VectorMeasure α N) : Prop :=
∃ s : Set α, MeasurableSet s ∧ (∀ t ⊆ s, v t = 0) ∧ ∀ t ⊆ sᶜ, w t = 0
#align measure_theory.vector_measure.mutually_singular MeasureTheory.VectorMeasure.MutuallySingular
@[inherit_doc VectorMeasure.MutuallySingular]
scoped[MeasureTheory] infixl:60 " ⟂ᵥ " => MeasureTheory.VectorMeasure.MutuallySingular
namespace MutuallySingular
variable {v v₁ v₂ : VectorMeasure α M} {w w₁ w₂ : VectorMeasure α N}
theorem mk (s : Set α) (hs : MeasurableSet s) (h₁ : ∀ t ⊆ s, MeasurableSet t → v t = 0)
(h₂ : ∀ t ⊆ sᶜ, MeasurableSet t → w t = 0) : v ⟂ᵥ w := by
refine ⟨s, hs, fun t hst => ?_, fun t hst => ?_⟩ <;> by_cases ht : MeasurableSet t
· exact h₁ t hst ht
· exact not_measurable v ht
· exact h₂ t hst ht
· exact not_measurable w ht
#align measure_theory.vector_measure.mutually_singular.mk MeasureTheory.VectorMeasure.MutuallySingular.mk
theorem symm (h : v ⟂ᵥ w) : w ⟂ᵥ v :=
let ⟨s, hmeas, hs₁, hs₂⟩ := h
⟨sᶜ, hmeas.compl, hs₂, fun t ht => hs₁ _ (compl_compl s ▸ ht : t ⊆ s)⟩
#align measure_theory.vector_measure.mutually_singular.symm MeasureTheory.VectorMeasure.MutuallySingular.symm
theorem zero_right : v ⟂ᵥ (0 : VectorMeasure α N) :=
⟨∅, MeasurableSet.empty, fun _ ht => (Set.subset_empty_iff.1 ht).symm ▸ v.empty,
fun _ _ => zero_apply _⟩
#align measure_theory.vector_measure.mutually_singular.zero_right MeasureTheory.VectorMeasure.MutuallySingular.zero_right
theorem zero_left : (0 : VectorMeasure α M) ⟂ᵥ w :=
zero_right.symm
#align measure_theory.vector_measure.mutually_singular.zero_left MeasureTheory.VectorMeasure.MutuallySingular.zero_left
theorem add_left [T2Space N] [ContinuousAdd M] (h₁ : v₁ ⟂ᵥ w) (h₂ : v₂ ⟂ᵥ w) : v₁ + v₂ ⟂ᵥ w := by
obtain ⟨u, hmu, hu₁, hu₂⟩ := h₁
obtain ⟨v, hmv, hv₁, hv₂⟩ := h₂
refine mk (u ∩ v) (hmu.inter hmv) (fun t ht _ => ?_) fun t ht hmt => ?_
· rw [add_apply, hu₁ _ (Set.subset_inter_iff.1 ht).1, hv₁ _ (Set.subset_inter_iff.1 ht).2,
zero_add]
· rw [Set.compl_inter] at ht
rw [(_ : t = uᶜ ∩ t ∪ vᶜ \ uᶜ ∩ t),
of_union _ (hmu.compl.inter hmt) ((hmv.compl.diff hmu.compl).inter hmt), hu₂, hv₂, add_zero]
· exact Set.Subset.trans Set.inter_subset_left diff_subset
· exact Set.inter_subset_left
· exact disjoint_sdiff_self_right.mono Set.inter_subset_left Set.inter_subset_left
· apply Set.Subset.antisymm <;> intro x hx
· by_cases hxu' : x ∈ uᶜ
· exact Or.inl ⟨hxu', hx⟩
rcases ht hx with (hxu | hxv)
exacts [False.elim (hxu' hxu), Or.inr ⟨⟨hxv, hxu'⟩, hx⟩]
· cases' hx with hx hx <;> exact hx.2
#align measure_theory.vector_measure.mutually_singular.add_left MeasureTheory.VectorMeasure.MutuallySingular.add_left
theorem add_right [T2Space M] [ContinuousAdd N] (h₁ : v ⟂ᵥ w₁) (h₂ : v ⟂ᵥ w₂) : v ⟂ᵥ w₁ + w₂ :=
(add_left h₁.symm h₂.symm).symm
#align measure_theory.vector_measure.mutually_singular.add_right MeasureTheory.VectorMeasure.MutuallySingular.add_right
theorem smul_right {R : Type*} [Semiring R] [DistribMulAction R N] [ContinuousConstSMul R N]
(r : R) (h : v ⟂ᵥ w) : v ⟂ᵥ r • w :=
let ⟨s, hmeas, hs₁, hs₂⟩ := h
⟨s, hmeas, hs₁, fun t ht => by simp only [coe_smul, Pi.smul_apply, hs₂ t ht, smul_zero]⟩
#align measure_theory.vector_measure.mutually_singular.smul_right MeasureTheory.VectorMeasure.MutuallySingular.smul_right
theorem smul_left {R : Type*} [Semiring R] [DistribMulAction R M] [ContinuousConstSMul R M] (r : R)
(h : v ⟂ᵥ w) : r • v ⟂ᵥ w :=
(smul_right r h.symm).symm
#align measure_theory.vector_measure.mutually_singular.smul_left MeasureTheory.VectorMeasure.MutuallySingular.smul_left
theorem neg_left {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ⟂ᵥ w) : -v ⟂ᵥ w := by
obtain ⟨u, hmu, hu₁, hu₂⟩ := h
refine ⟨u, hmu, fun s hs => ?_, hu₂⟩
rw [neg_apply v s, neg_eq_zero]
exact hu₁ s hs
#align measure_theory.vector_measure.mutually_singular.neg_left MeasureTheory.VectorMeasure.MutuallySingular.neg_left
theorem neg_right {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} (h : v ⟂ᵥ w) : v ⟂ᵥ -w :=
h.symm.neg_left.symm
#align measure_theory.vector_measure.mutually_singular.neg_right MeasureTheory.VectorMeasure.MutuallySingular.neg_right
@[simp]
theorem neg_left_iff {M : Type*} [AddCommGroup M] [TopologicalSpace M] [TopologicalAddGroup M]
{v : VectorMeasure α M} {w : VectorMeasure α N} : -v ⟂ᵥ w ↔ v ⟂ᵥ w :=
⟨fun h => neg_neg v ▸ h.neg_left, neg_left⟩
#align measure_theory.vector_measure.mutually_singular.neg_left_iff MeasureTheory.VectorMeasure.MutuallySingular.neg_left_iff
@[simp]
theorem neg_right_iff {N : Type*} [AddCommGroup N] [TopologicalSpace N] [TopologicalAddGroup N]
{v : VectorMeasure α M} {w : VectorMeasure α N} : v ⟂ᵥ -w ↔ v ⟂ᵥ w :=
⟨fun h => neg_neg w ▸ h.neg_right, neg_right⟩
#align measure_theory.vector_measure.mutually_singular.neg_right_iff MeasureTheory.VectorMeasure.MutuallySingular.neg_right_iff
end MutuallySingular
section Trim
/-- Restriction of a vector measure onto a sub-σ-algebra. -/
@[simps]
def trim {m n : MeasurableSpace α} (v : VectorMeasure α M) (hle : m ≤ n) :
@VectorMeasure α m M _ _ :=
@VectorMeasure.mk α m M _ _
(fun i => if MeasurableSet[m] i then v i else 0)
(by dsimp only; rw [if_pos (@MeasurableSet.empty _ m), v.empty])
(fun i hi => by dsimp only; rw [if_neg hi])
(fun f hf₁ hf₂ => by
dsimp only
have hf₁' : ∀ k, MeasurableSet[n] (f k) := fun k => hle _ (hf₁ k)
convert v.m_iUnion hf₁' hf₂ using 1
· ext n
rw [if_pos (hf₁ n)]
· rw [if_pos (@MeasurableSet.iUnion _ _ m _ _ hf₁)])
#align measure_theory.vector_measure.trim MeasureTheory.VectorMeasure.trim
variable {n : MeasurableSpace α} {v : VectorMeasure α M}
| Mathlib/MeasureTheory/Measure/VectorMeasure.lean | 1,258 | 1,260 | theorem trim_eq_self : v.trim le_rfl = v := by |
ext i hi
exact if_pos hi
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Yury G. Kudryashov
-/
import Mathlib.Logic.Function.Basic
import Mathlib.Tactic.MkIffOfInductiveProp
#align_import data.sum.basic from "leanprover-community/mathlib"@"bd9851ca476957ea4549eb19b40e7b5ade9428cc"
/-!
# Additional lemmas about sum types
Most of the former contents of this file have been moved to Batteries.
-/
universe u v w x
variable {α : Type u} {α' : Type w} {β : Type v} {β' : Type x} {γ δ : Type*}
namespace Sum
#align sum.forall Sum.forall
#align sum.exists Sum.exists
theorem exists_sum {γ : α ⊕ β → Sort*} (p : (∀ ab, γ ab) → Prop) :
(∃ fab, p fab) ↔ (∃ fa fb, p (Sum.rec fa fb)) := by
rw [← not_forall_not, forall_sum]
simp
theorem inl_injective : Function.Injective (inl : α → Sum α β) := fun _ _ ↦ inl.inj
#align sum.inl_injective Sum.inl_injective
theorem inr_injective : Function.Injective (inr : β → Sum α β) := fun _ _ ↦ inr.inj
#align sum.inr_injective Sum.inr_injective
theorem sum_rec_congr (P : α ⊕ β → Sort*) (f : ∀ i, P (inl i)) (g : ∀ i, P (inr i))
{x y : α ⊕ β} (h : x = y) :
@Sum.rec _ _ _ f g x = cast (congr_arg P h.symm) (@Sum.rec _ _ _ f g y) := by cases h; rfl
section get
#align sum.is_left Sum.isLeft
#align sum.is_right Sum.isRight
#align sum.get_left Sum.getLeft?
#align sum.get_right Sum.getRight?
variable {x y : Sum α β}
#align sum.get_left_eq_none_iff Sum.getLeft?_eq_none_iff
#align sum.get_right_eq_none_iff Sum.getRight?_eq_none_iff
theorem eq_left_iff_getLeft_eq {a : α} : x = inl a ↔ ∃ h, x.getLeft h = a := by
cases x <;> simp
theorem eq_right_iff_getRight_eq {b : β} : x = inr b ↔ ∃ h, x.getRight h = b := by
cases x <;> simp
#align sum.get_left_eq_some_iff Sum.getLeft?_eq_some_iff
#align sum.get_right_eq_some_iff Sum.getRight?_eq_some_iff
theorem getLeft_eq_getLeft? (h₁ : x.isLeft) (h₂ : x.getLeft?.isSome) :
x.getLeft h₁ = x.getLeft?.get h₂ := by simp [← getLeft?_eq_some_iff]
theorem getRight_eq_getRight? (h₁ : x.isRight) (h₂ : x.getRight?.isSome) :
x.getRight h₁ = x.getRight?.get h₂ := by simp [← getRight?_eq_some_iff]
#align sum.bnot_is_left Sum.bnot_isLeft
#align sum.is_left_eq_ff Sum.isLeft_eq_false
#align sum.not_is_left Sum.not_isLeft
#align sum.bnot_is_right Sum.bnot_isRight
#align sum.is_right_eq_ff Sum.isRight_eq_false
#align sum.not_is_right Sum.not_isRight
#align sum.is_left_iff Sum.isLeft_iff
#align sum.is_right_iff Sum.isRight_iff
@[simp] theorem isSome_getLeft?_iff_isLeft : x.getLeft?.isSome ↔ x.isLeft := by
rw [isLeft_iff, Option.isSome_iff_exists]; simp
@[simp] theorem isSome_getRight?_iff_isRight : x.getRight?.isSome ↔ x.isRight := by
rw [isRight_iff, Option.isSome_iff_exists]; simp
end get
#align sum.inl.inj_iff Sum.inl.inj_iff
#align sum.inr.inj_iff Sum.inr.inj_iff
#align sum.inl_ne_inr Sum.inl_ne_inr
#align sum.inr_ne_inl Sum.inr_ne_inl
#align sum.elim Sum.elim
#align sum.elim_inl Sum.elim_inl
#align sum.elim_inr Sum.elim_inr
#align sum.elim_comp_inl Sum.elim_comp_inl
#align sum.elim_comp_inr Sum.elim_comp_inr
#align sum.elim_inl_inr Sum.elim_inl_inr
#align sum.comp_elim Sum.comp_elim
#align sum.elim_comp_inl_inr Sum.elim_comp_inl_inr
#align sum.map Sum.map
#align sum.map_inl Sum.map_inl
#align sum.map_inr Sum.map_inr
#align sum.map_map Sum.map_map
#align sum.map_comp_map Sum.map_comp_map
#align sum.map_id_id Sum.map_id_id
#align sum.elim_map Sum.elim_map
#align sum.elim_comp_map Sum.elim_comp_map
#align sum.is_left_map Sum.isLeft_map
#align sum.is_right_map Sum.isRight_map
#align sum.get_left_map Sum.getLeft?_map
#align sum.get_right_map Sum.getRight?_map
open Function (update update_eq_iff update_comp_eq_of_injective update_comp_eq_of_forall_ne)
@[simp]
theorem update_elim_inl [DecidableEq α] [DecidableEq (Sum α β)] {f : α → γ} {g : β → γ} {i : α}
{x : γ} : update (Sum.elim f g) (inl i) x = Sum.elim (update f i x) g :=
update_eq_iff.2 ⟨by simp, by simp (config := { contextual := true })⟩
#align sum.update_elim_inl Sum.update_elim_inl
@[simp]
theorem update_elim_inr [DecidableEq β] [DecidableEq (Sum α β)] {f : α → γ} {g : β → γ} {i : β}
{x : γ} : update (Sum.elim f g) (inr i) x = Sum.elim f (update g i x) :=
update_eq_iff.2 ⟨by simp, by simp (config := { contextual := true })⟩
#align sum.update_elim_inr Sum.update_elim_inr
@[simp]
theorem update_inl_comp_inl [DecidableEq α] [DecidableEq (Sum α β)] {f : Sum α β → γ} {i : α}
{x : γ} : update f (inl i) x ∘ inl = update (f ∘ inl) i x :=
update_comp_eq_of_injective _ inl_injective _ _
#align sum.update_inl_comp_inl Sum.update_inl_comp_inl
@[simp]
theorem update_inl_apply_inl [DecidableEq α] [DecidableEq (Sum α β)] {f : Sum α β → γ} {i j : α}
{x : γ} : update f (inl i) x (inl j) = update (f ∘ inl) i x j := by
rw [← update_inl_comp_inl, Function.comp_apply]
#align sum.update_inl_apply_inl Sum.update_inl_apply_inl
@[simp]
theorem update_inl_comp_inr [DecidableEq (Sum α β)] {f : Sum α β → γ} {i : α} {x : γ} :
update f (inl i) x ∘ inr = f ∘ inr :=
(update_comp_eq_of_forall_ne _ _) fun _ ↦ inr_ne_inl
#align sum.update_inl_comp_inr Sum.update_inl_comp_inr
theorem update_inl_apply_inr [DecidableEq (Sum α β)] {f : Sum α β → γ} {i : α} {j : β} {x : γ} :
update f (inl i) x (inr j) = f (inr j) :=
Function.update_noteq inr_ne_inl _ _
#align sum.update_inl_apply_inr Sum.update_inl_apply_inr
@[simp]
theorem update_inr_comp_inl [DecidableEq (Sum α β)] {f : Sum α β → γ} {i : β} {x : γ} :
update f (inr i) x ∘ inl = f ∘ inl :=
(update_comp_eq_of_forall_ne _ _) fun _ ↦ inl_ne_inr
#align sum.update_inr_comp_inl Sum.update_inr_comp_inl
theorem update_inr_apply_inl [DecidableEq (Sum α β)] {f : Sum α β → γ} {i : α} {j : β} {x : γ} :
update f (inr j) x (inl i) = f (inl i) :=
Function.update_noteq inl_ne_inr _ _
#align sum.update_inr_apply_inl Sum.update_inr_apply_inl
@[simp]
theorem update_inr_comp_inr [DecidableEq β] [DecidableEq (Sum α β)] {f : Sum α β → γ} {i : β}
{x : γ} : update f (inr i) x ∘ inr = update (f ∘ inr) i x :=
update_comp_eq_of_injective _ inr_injective _ _
#align sum.update_inr_comp_inr Sum.update_inr_comp_inr
@[simp]
theorem update_inr_apply_inr [DecidableEq β] [DecidableEq (Sum α β)] {f : Sum α β → γ} {i j : β}
{x : γ} : update f (inr i) x (inr j) = update (f ∘ inr) i x j := by
rw [← update_inr_comp_inr, Function.comp_apply]
#align sum.update_inr_apply_inr Sum.update_inr_apply_inr
#align sum.swap Sum.swap
#align sum.swap_inl Sum.swap_inl
#align sum.swap_inr Sum.swap_inr
#align sum.swap_swap Sum.swap_swap
#align sum.swap_swap_eq Sum.swap_swap_eq
@[simp]
theorem swap_leftInverse : Function.LeftInverse (@swap α β) swap :=
swap_swap
#align sum.swap_left_inverse Sum.swap_leftInverse
@[simp]
theorem swap_rightInverse : Function.RightInverse (@swap α β) swap :=
swap_swap
#align sum.swap_right_inverse Sum.swap_rightInverse
#align sum.is_left_swap Sum.isLeft_swap
#align sum.is_right_swap Sum.isRight_swap
#align sum.get_left_swap Sum.getLeft?_swap
#align sum.get_right_swap Sum.getRight?_swap
mk_iff_of_inductive_prop Sum.LiftRel Sum.liftRel_iff
namespace LiftRel
#align sum.lift_rel Sum.LiftRel
#align sum.lift_rel_inl_inl Sum.liftRel_inl_inl
#align sum.not_lift_rel_inl_inr Sum.not_liftRel_inl_inr
#align sum.not_lift_rel_inr_inl Sum.not_liftRel_inr_inl
#align sum.lift_rel_inr_inr Sum.liftRel_inr_inr
#align sum.lift_rel.mono Sum.LiftRel.mono
#align sum.lift_rel.mono_left Sum.LiftRel.mono_left
#align sum.lift_rel.mono_right Sum.LiftRel.mono_right
#align sum.lift_rel.swap Sum.LiftRel.swap
#align sum.lift_rel_swap_iff Sum.liftRel_swap_iff
variable {r : α → γ → Prop} {s : β → δ → Prop} {x : Sum α β} {y : Sum γ δ}
{a : α} {b : β} {c : γ} {d : δ}
theorem isLeft_congr (h : LiftRel r s x y) : x.isLeft ↔ y.isLeft := by cases h <;> rfl
theorem isRight_congr (h : LiftRel r s x y) : x.isRight ↔ y.isRight := by cases h <;> rfl
theorem isLeft_left (h : LiftRel r s x (inl c)) : x.isLeft := by cases h; rfl
theorem isLeft_right (h : LiftRel r s (inl a) y) : y.isLeft := by cases h; rfl
theorem isRight_left (h : LiftRel r s x (inr d)) : x.isRight := by cases h; rfl
theorem isRight_right (h : LiftRel r s (inr b) y) : y.isRight := by cases h; rfl
theorem exists_of_isLeft_left (h₁ : LiftRel r s x y) (h₂ : x.isLeft) :
∃ a c, r a c ∧ x = inl a ∧ y = inl c := by
rcases isLeft_iff.mp h₂ with ⟨_, rfl⟩
simp only [liftRel_iff, false_and, and_false, exists_false, or_false] at h₁
exact h₁
theorem exists_of_isLeft_right (h₁ : LiftRel r s x y) (h₂ : y.isLeft) :
∃ a c, r a c ∧ x = inl a ∧ y = inl c := exists_of_isLeft_left h₁ ((isLeft_congr h₁).mpr h₂)
| Mathlib/Data/Sum/Basic.lean | 227 | 231 | theorem exists_of_isRight_left (h₁ : LiftRel r s x y) (h₂ : x.isRight) :
∃ b d, s b d ∧ x = inr b ∧ y = inr d := by |
rcases isRight_iff.mp h₂ with ⟨_, rfl⟩
simp only [liftRel_iff, false_and, and_false, exists_false, false_or] at h₁
exact h₁
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.Algebra.BigOperators.Fin
import Mathlib.Algebra.GeomSum
import Mathlib.LinearAlgebra.Matrix.Block
import Mathlib.LinearAlgebra.Matrix.Determinant.Basic
import Mathlib.LinearAlgebra.Matrix.Nondegenerate
#align_import linear_algebra.vandermonde from "leanprover-community/mathlib"@"70fd9563a21e7b963887c9360bd29b2393e6225a"
/-!
# Vandermonde matrix
This file defines the `vandermonde` matrix and gives its determinant.
## Main definitions
- `vandermonde v`: a square matrix with the `i, j`th entry equal to `v i ^ j`.
## Main results
- `det_vandermonde`: `det (vandermonde v)` is the product of `v i - v j`, where
`(i, j)` ranges over the unordered pairs.
-/
variable {R : Type*} [CommRing R]
open Equiv Finset
open Matrix
namespace Matrix
/-- `vandermonde v` is the square matrix with `i`th row equal to `1, v i, v i ^ 2, v i ^ 3, ...`.
-/
def vandermonde {n : ℕ} (v : Fin n → R) : Matrix (Fin n) (Fin n) R := fun i j => v i ^ (j : ℕ)
#align matrix.vandermonde Matrix.vandermonde
@[simp]
theorem vandermonde_apply {n : ℕ} (v : Fin n → R) (i j) : vandermonde v i j = v i ^ (j : ℕ) :=
rfl
#align matrix.vandermonde_apply Matrix.vandermonde_apply
@[simp]
theorem vandermonde_cons {n : ℕ} (v0 : R) (v : Fin n → R) :
vandermonde (Fin.cons v0 v : Fin n.succ → R) =
Fin.cons (fun (j : Fin n.succ) => v0 ^ (j : ℕ)) fun i => Fin.cons 1
fun j => v i * vandermonde v i j := by
ext i j
refine Fin.cases (by simp) (fun i => ?_) i
refine Fin.cases (by simp) (fun j => ?_) j
simp [pow_succ']
#align matrix.vandermonde_cons Matrix.vandermonde_cons
theorem vandermonde_succ {n : ℕ} (v : Fin n.succ → R) :
vandermonde v =
Fin.cons (fun (j : Fin n.succ) => v 0 ^ (j : ℕ)) fun i =>
Fin.cons 1 fun j => v i.succ * vandermonde (Fin.tail v) i j := by
conv_lhs => rw [← Fin.cons_self_tail v, vandermonde_cons]
rfl
#align matrix.vandermonde_succ Matrix.vandermonde_succ
theorem vandermonde_mul_vandermonde_transpose {n : ℕ} (v w : Fin n → R) (i j) :
(vandermonde v * (vandermonde w)ᵀ) i j = ∑ k : Fin n, (v i * w j) ^ (k : ℕ) := by
simp only [vandermonde_apply, Matrix.mul_apply, Matrix.transpose_apply, mul_pow]
#align matrix.vandermonde_mul_vandermonde_transpose Matrix.vandermonde_mul_vandermonde_transpose
theorem vandermonde_transpose_mul_vandermonde {n : ℕ} (v : Fin n → R) (i j) :
((vandermonde v)ᵀ * vandermonde v) i j = ∑ k : Fin n, v k ^ (i + j : ℕ) := by
simp only [vandermonde_apply, Matrix.mul_apply, Matrix.transpose_apply, pow_add]
#align matrix.vandermonde_transpose_mul_vandermonde Matrix.vandermonde_transpose_mul_vandermonde
theorem det_vandermonde {n : ℕ} (v : Fin n → R) :
det (vandermonde v) = ∏ i : Fin n, ∏ j ∈ Ioi i, (v j - v i) := by
unfold vandermonde
induction' n with n ih
· exact det_eq_one_of_card_eq_zero (Fintype.card_fin 0)
calc
det (of fun i j : Fin n.succ => v i ^ (j : ℕ)) =
det
(of fun i j : Fin n.succ =>
Matrix.vecCons (v 0 ^ (j : ℕ)) (fun i => v (Fin.succ i) ^ (j : ℕ) - v 0 ^ (j : ℕ)) i) :=
det_eq_of_forall_row_eq_smul_add_const (Matrix.vecCons 0 1) 0 (Fin.cons_zero _ _) ?_
_ =
det
(of fun i j : Fin n =>
Matrix.vecCons (v 0 ^ (j.succ : ℕ))
(fun i : Fin n => v (Fin.succ i) ^ (j.succ : ℕ) - v 0 ^ (j.succ : ℕ))
(Fin.succAbove 0 i)) := by
simp_rw [det_succ_column_zero, Fin.sum_univ_succ, of_apply, Matrix.cons_val_zero, submatrix,
of_apply, Matrix.cons_val_succ, Fin.val_zero, pow_zero, one_mul, sub_self,
mul_zero, zero_mul, Finset.sum_const_zero, add_zero]
_ =
det
(of fun i j : Fin n =>
(v (Fin.succ i) - v 0) *
∑ k ∈ Finset.range (j + 1 : ℕ), v i.succ ^ k * v 0 ^ (j - k : ℕ) :
Matrix _ _ R) := by
congr
ext i j
rw [Fin.succAbove_zero, Matrix.cons_val_succ, Fin.val_succ, mul_comm]
exact (geom_sum₂_mul (v i.succ) (v 0) (j + 1 : ℕ)).symm
_ =
(∏ i ∈ Finset.univ, (v (Fin.succ i) - v 0)) *
det fun i j : Fin n =>
∑ k ∈ Finset.range (j + 1 : ℕ), v i.succ ^ k * v 0 ^ (j - k : ℕ) :=
(det_mul_column (fun i => v (Fin.succ i) - v 0) _)
_ = (∏ i ∈ Finset.univ, (v (Fin.succ i) - v 0)) *
det fun i j : Fin n => v (Fin.succ i) ^ (j : ℕ) := congr_arg _ ?_
_ = ∏ i : Fin n.succ, ∏ j ∈ Ioi i, (v j - v i) := by
simp_rw [Fin.prod_univ_succ, Fin.prod_Ioi_zero, Fin.prod_Ioi_succ]
have h := ih (v ∘ Fin.succ)
unfold Function.comp at h
rw [h]
· intro i j
simp_rw [of_apply]
rw [Matrix.cons_val_zero]
refine Fin.cases ?_ (fun i => ?_) i
· simp
rw [Matrix.cons_val_succ, Matrix.cons_val_succ, Pi.one_apply]
ring
· cases n
· rw [det_eq_one_of_card_eq_zero (Fintype.card_fin 0),
det_eq_one_of_card_eq_zero (Fintype.card_fin 0)]
apply det_eq_of_forall_col_eq_smul_add_pred fun _ => v 0
· intro j
simp
· intro i j
simp only [smul_eq_mul, Pi.add_apply, Fin.val_succ, Fin.coe_castSucc, Pi.smul_apply]
rw [Finset.sum_range_succ, add_comm, tsub_self, pow_zero, mul_one, Finset.mul_sum]
congr 1
refine Finset.sum_congr rfl fun i' hi' => ?_
rw [mul_left_comm (v 0), Nat.succ_sub, pow_succ']
exact Nat.lt_succ_iff.mp (Finset.mem_range.mp hi')
#align matrix.det_vandermonde Matrix.det_vandermonde
theorem det_vandermonde_eq_zero_iff [IsDomain R] {n : ℕ} {v : Fin n → R} :
det (vandermonde v) = 0 ↔ ∃ i j : Fin n, v i = v j ∧ i ≠ j := by
constructor
· simp only [det_vandermonde v, Finset.prod_eq_zero_iff, sub_eq_zero, forall_exists_index]
rintro i ⟨_, j, h₁, h₂⟩
exact ⟨j, i, h₂, (mem_Ioi.mp h₁).ne'⟩
· simp only [Ne, forall_exists_index, and_imp]
refine fun i j h₁ h₂ => Matrix.det_zero_of_row_eq h₂ (funext fun k => ?_)
rw [vandermonde_apply, vandermonde_apply, h₁]
#align matrix.det_vandermonde_eq_zero_iff Matrix.det_vandermonde_eq_zero_iff
theorem det_vandermonde_ne_zero_iff [IsDomain R] {n : ℕ} {v : Fin n → R} :
det (vandermonde v) ≠ 0 ↔ Function.Injective v := by
unfold Function.Injective
simp only [det_vandermonde_eq_zero_iff, Ne, not_exists, not_and, Classical.not_not]
#align matrix.det_vandermonde_ne_zero_iff Matrix.det_vandermonde_ne_zero_iff
@[simp]
| Mathlib/LinearAlgebra/Vandermonde.lean | 160 | 162 | theorem det_vandermonde_add {n : ℕ} (v : Fin n → R) (a : R) :
(Matrix.vandermonde fun i ↦ v i + a).det = (Matrix.vandermonde v).det := by |
simp [Matrix.det_vandermonde]
|
/-
Copyright (c) 2020 Thomas Browning and Patrick Lutz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Thomas Browning, Patrick Lutz
-/
import Mathlib.GroupTheory.Solvable
import Mathlib.FieldTheory.PolynomialGaloisGroup
import Mathlib.RingTheory.RootsOfUnity.Basic
#align_import field_theory.abel_ruffini from "leanprover-community/mathlib"@"e3f4be1fcb5376c4948d7f095bec45350bfb9d1a"
/-!
# The Abel-Ruffini Theorem
This file proves one direction of the Abel-Ruffini theorem, namely that if an element is solvable
by radicals, then its minimal polynomial has solvable Galois group.
## Main definitions
* `solvableByRad F E` : the intermediate field of solvable-by-radicals elements
## Main results
* the Abel-Ruffini Theorem `solvableByRad.isSolvable'` : An irreducible polynomial with a root
that is solvable by radicals has a solvable Galois group.
-/
noncomputable section
open scoped Classical Polynomial IntermediateField
open Polynomial IntermediateField
section AbelRuffini
variable {F : Type*} [Field F] {E : Type*} [Field E] [Algebra F E]
theorem gal_zero_isSolvable : IsSolvable (0 : F[X]).Gal := by infer_instance
#align gal_zero_is_solvable gal_zero_isSolvable
theorem gal_one_isSolvable : IsSolvable (1 : F[X]).Gal := by infer_instance
#align gal_one_is_solvable gal_one_isSolvable
| Mathlib/FieldTheory/AbelRuffini.lean | 45 | 45 | theorem gal_C_isSolvable (x : F) : IsSolvable (C x).Gal := by | infer_instance
|
/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Geometry.Manifold.SmoothManifoldWithCorners
import Mathlib.Topology.Compactness.Paracompact
import Mathlib.Topology.Metrizable.Urysohn
#align_import geometry.manifold.metrizable from "leanprover-community/mathlib"@"d1bd9c5df2867c1cb463bc6364446d57bdd9f7f1"
/-!
# Metrizability of a σ-compact manifold
In this file we show that a σ-compact Hausdorff topological manifold over a finite dimensional real
vector space is metrizable.
-/
open TopologicalSpace
/-- A σ-compact Hausdorff topological manifold over a finite dimensional real vector space is
metrizable. -/
| Mathlib/Geometry/Manifold/Metrizable.lean | 24 | 31 | theorem ManifoldWithCorners.metrizableSpace {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
[FiniteDimensional ℝ E] {H : Type*} [TopologicalSpace H] (I : ModelWithCorners ℝ E H)
(M : Type*) [TopologicalSpace M] [ChartedSpace H M] [SigmaCompactSpace M] [T2Space M] :
MetrizableSpace M := by |
haveI := I.locallyCompactSpace; haveI := ChartedSpace.locallyCompactSpace H M
haveI := I.secondCountableTopology
haveI := ChartedSpace.secondCountable_of_sigma_compact H M
exact metrizableSpace_of_t3_second_countable M
|
/-
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.Aut
import Mathlib.Algebra.Group.Invertible.Basic
import Mathlib.Algebra.GroupWithZero.Units.Basic
import Mathlib.GroupTheory.GroupAction.Units
#align_import group_theory.group_action.group from "leanprover-community/mathlib"@"3b52265189f3fb43aa631edffce5d060fafaf82f"
/-!
# Group actions applied to various types of group
This file contains lemmas about `SMul` on `GroupWithZero`, and `Group`.
-/
universe u v w
variable {α : Type u} {β : Type v} {γ : Type w}
section MulAction
section Group
variable [Group α] [MulAction α β]
@[to_additive (attr := simp)]
theorem inv_smul_smul (c : α) (x : β) : c⁻¹ • c • x = x := by rw [smul_smul, mul_left_inv, one_smul]
#align inv_smul_smul inv_smul_smul
#align neg_vadd_vadd neg_vadd_vadd
@[to_additive (attr := simp)]
theorem smul_inv_smul (c : α) (x : β) : c • c⁻¹ • x = x := by
rw [smul_smul, mul_right_inv, one_smul]
#align smul_inv_smul smul_inv_smul
#align vadd_neg_vadd vadd_neg_vadd
/-- Given an action of a group `α` on `β`, each `g : α` defines a permutation of `β`. -/
@[to_additive (attr := simps)]
def MulAction.toPerm (a : α) : Equiv.Perm β :=
⟨fun x => a • x, fun x => a⁻¹ • x, inv_smul_smul a, smul_inv_smul a⟩
#align mul_action.to_perm MulAction.toPerm
#align add_action.to_perm AddAction.toPerm
#align add_action.to_perm_apply AddAction.toPerm_apply
#align mul_action.to_perm_apply MulAction.toPerm_apply
#align add_action.to_perm_symm_apply AddAction.toPerm_symm_apply
#align mul_action.to_perm_symm_apply MulAction.toPerm_symm_apply
/-- Given an action of an additive group `α` on `β`, each `g : α` defines a permutation of `β`. -/
add_decl_doc AddAction.toPerm
/-- `MulAction.toPerm` is injective on faithful actions. -/
@[to_additive "`AddAction.toPerm` is injective on faithful actions."]
theorem MulAction.toPerm_injective [FaithfulSMul α β] :
Function.Injective (MulAction.toPerm : α → Equiv.Perm β) :=
(show Function.Injective (Equiv.toFun ∘ MulAction.toPerm) from smul_left_injective').of_comp
#align mul_action.to_perm_injective MulAction.toPerm_injective
#align add_action.to_perm_injective AddAction.toPerm_injective
variable (α) (β)
/-- Given an action of a group `α` on a set `β`, each `g : α` defines a permutation of `β`. -/
@[simps]
def MulAction.toPermHom : α →* Equiv.Perm β where
toFun := MulAction.toPerm
map_one' := Equiv.ext <| one_smul α
map_mul' u₁ u₂ := Equiv.ext <| mul_smul (u₁ : α) u₂
#align mul_action.to_perm_hom MulAction.toPermHom
#align mul_action.to_perm_hom_apply MulAction.toPermHom_apply
/-- Given an action of an additive group `α` on a set `β`, each `g : α` defines a permutation of
`β`. -/
@[simps!]
def AddAction.toPermHom (α : Type*) [AddGroup α] [AddAction α β] :
α →+ Additive (Equiv.Perm β) :=
MonoidHom.toAdditive'' <| MulAction.toPermHom (Multiplicative α) β
#align add_action.to_perm_hom AddAction.toPermHom
/-- The tautological action by `Equiv.Perm α` on `α`.
This generalizes `Function.End.applyMulAction`. -/
instance Equiv.Perm.applyMulAction (α : Type*) : MulAction (Equiv.Perm α) α where
smul f a := f a
one_smul _ := rfl
mul_smul _ _ _ := rfl
#align equiv.perm.apply_mul_action Equiv.Perm.applyMulAction
@[simp]
protected theorem Equiv.Perm.smul_def {α : Type*} (f : Equiv.Perm α) (a : α) : f • a = f a :=
rfl
#align equiv.perm.smul_def Equiv.Perm.smul_def
/-- `Equiv.Perm.applyMulAction` is faithful. -/
instance Equiv.Perm.applyFaithfulSMul (α : Type*) : FaithfulSMul (Equiv.Perm α) α :=
⟨Equiv.ext⟩
#align equiv.perm.apply_has_faithful_smul Equiv.Perm.applyFaithfulSMul
variable {α} {β}
@[to_additive]
theorem inv_smul_eq_iff {a : α} {x y : β} : a⁻¹ • x = y ↔ x = a • y :=
(MulAction.toPerm a).symm_apply_eq
#align inv_smul_eq_iff inv_smul_eq_iff
#align neg_vadd_eq_iff neg_vadd_eq_iff
@[to_additive]
theorem eq_inv_smul_iff {a : α} {x y : β} : x = a⁻¹ • y ↔ a • x = y :=
(MulAction.toPerm a).eq_symm_apply
#align eq_inv_smul_iff eq_inv_smul_iff
#align eq_neg_vadd_iff eq_neg_vadd_iff
theorem smul_inv [Group β] [SMulCommClass α β β] [IsScalarTower α β β] (c : α) (x : β) :
(c • x)⁻¹ = c⁻¹ • x⁻¹ := by
rw [inv_eq_iff_mul_eq_one, smul_mul_smul, mul_right_inv, mul_right_inv, one_smul]
#align smul_inv smul_inv
theorem smul_zpow [Group β] [SMulCommClass α β β] [IsScalarTower α β β] (c : α) (x : β) (p : ℤ) :
(c • x) ^ p = c ^ p • x ^ p := by
cases p <;>
simp [smul_pow, smul_inv]
#align smul_zpow smul_zpow
@[simp]
theorem Commute.smul_right_iff [Mul β] [SMulCommClass α β β] [IsScalarTower α β β] {a b : β}
(r : α) : Commute a (r • b) ↔ Commute a b :=
⟨fun h => inv_smul_smul r b ▸ h.smul_right r⁻¹, fun h => h.smul_right r⟩
#align commute.smul_right_iff Commute.smul_right_iff
@[simp]
| Mathlib/GroupTheory/GroupAction/Group.lean | 132 | 134 | theorem Commute.smul_left_iff [Mul β] [SMulCommClass α β β] [IsScalarTower α β β] {a b : β}
(r : α) : Commute (r • a) b ↔ Commute a b := by |
rw [Commute.symm_iff, Commute.smul_right_iff, Commute.symm_iff]
|
/-
Copyright (c) 2020 Thomas Browning. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Thomas Browning
-/
import Mathlib.Algebra.GCDMonoid.Multiset
import Mathlib.Combinatorics.Enumerative.Partition
import Mathlib.Data.List.Rotate
import Mathlib.GroupTheory.Perm.Cycle.Factors
import Mathlib.GroupTheory.Perm.Closure
import Mathlib.Algebra.GCDMonoid.Nat
import Mathlib.Tactic.NormNum.GCD
#align_import group_theory.perm.cycle.type from "leanprover-community/mathlib"@"47adfab39a11a072db552f47594bf8ed2cf8a722"
/-!
# Cycle Types
In this file we define the cycle type of a permutation.
## Main definitions
- `Equiv.Perm.cycleType σ` where `σ` is a permutation of a `Fintype`
- `Equiv.Perm.partition σ` where `σ` is a permutation of a `Fintype`
## Main results
- `sum_cycleType` : The sum of `σ.cycleType` equals `σ.support.card`
- `lcm_cycleType` : The lcm of `σ.cycleType` equals `orderOf σ`
- `isConj_iff_cycleType_eq` : Two permutations are conjugate if and only if they have the same
cycle type.
- `exists_prime_orderOf_dvd_card`: For every prime `p` dividing the order of a finite group `G`
there exists an element of order `p` in `G`. This is known as Cauchy's theorem.
-/
namespace Equiv.Perm
open Equiv List Multiset
variable {α : Type*} [Fintype α]
section CycleType
variable [DecidableEq α]
/-- The cycle type of a permutation -/
def cycleType (σ : Perm α) : Multiset ℕ :=
σ.cycleFactorsFinset.1.map (Finset.card ∘ support)
#align equiv.perm.cycle_type Equiv.Perm.cycleType
theorem cycleType_def (σ : Perm α) :
σ.cycleType = σ.cycleFactorsFinset.1.map (Finset.card ∘ support) :=
rfl
#align equiv.perm.cycle_type_def Equiv.Perm.cycleType_def
theorem cycleType_eq' {σ : Perm α} (s : Finset (Perm α)) (h1 : ∀ f : Perm α, f ∈ s → f.IsCycle)
(h2 : (s : Set (Perm α)).Pairwise Disjoint)
(h0 : s.noncommProd id (h2.imp fun _ _ => Disjoint.commute) = σ) :
σ.cycleType = s.1.map (Finset.card ∘ support) := by
rw [cycleType_def]
congr
rw [cycleFactorsFinset_eq_finset]
exact ⟨h1, h2, h0⟩
#align equiv.perm.cycle_type_eq' Equiv.Perm.cycleType_eq'
theorem cycleType_eq {σ : Perm α} (l : List (Perm α)) (h0 : l.prod = σ)
(h1 : ∀ σ : Perm α, σ ∈ l → σ.IsCycle) (h2 : l.Pairwise Disjoint) :
σ.cycleType = l.map (Finset.card ∘ support) := by
have hl : l.Nodup := nodup_of_pairwise_disjoint_cycles h1 h2
rw [cycleType_eq' l.toFinset]
· simp [List.dedup_eq_self.mpr hl, (· ∘ ·)]
· simpa using h1
· simpa [hl] using h2
· simp [hl, h0]
#align equiv.perm.cycle_type_eq Equiv.Perm.cycleType_eq
@[simp] -- Porting note: new attr
theorem cycleType_eq_zero {σ : Perm α} : σ.cycleType = 0 ↔ σ = 1 := by
simp [cycleType_def, cycleFactorsFinset_eq_empty_iff]
#align equiv.perm.cycle_type_eq_zero Equiv.Perm.cycleType_eq_zero
@[simp] -- Porting note: new attr
theorem cycleType_one : (1 : Perm α).cycleType = 0 := cycleType_eq_zero.2 rfl
#align equiv.perm.cycle_type_one Equiv.Perm.cycleType_one
theorem card_cycleType_eq_zero {σ : Perm α} : Multiset.card σ.cycleType = 0 ↔ σ = 1 := by
rw [card_eq_zero, cycleType_eq_zero]
#align equiv.perm.card_cycle_type_eq_zero Equiv.Perm.card_cycleType_eq_zero
theorem card_cycleType_pos {σ : Perm α} : 0 < Multiset.card σ.cycleType ↔ σ ≠ 1 :=
pos_iff_ne_zero.trans card_cycleType_eq_zero.not
theorem two_le_of_mem_cycleType {σ : Perm α} {n : ℕ} (h : n ∈ σ.cycleType) : 2 ≤ n := by
simp only [cycleType_def, ← Finset.mem_def, Function.comp_apply, Multiset.mem_map,
mem_cycleFactorsFinset_iff] at h
obtain ⟨_, ⟨hc, -⟩, rfl⟩ := h
exact hc.two_le_card_support
#align equiv.perm.two_le_of_mem_cycle_type Equiv.Perm.two_le_of_mem_cycleType
theorem one_lt_of_mem_cycleType {σ : Perm α} {n : ℕ} (h : n ∈ σ.cycleType) : 1 < n :=
two_le_of_mem_cycleType h
#align equiv.perm.one_lt_of_mem_cycle_type Equiv.Perm.one_lt_of_mem_cycleType
theorem IsCycle.cycleType {σ : Perm α} (hσ : IsCycle σ) : σ.cycleType = [σ.support.card] :=
cycleType_eq [σ] (mul_one σ) (fun _τ hτ => (congr_arg IsCycle (List.mem_singleton.mp hτ)).mpr hσ)
(List.pairwise_singleton Disjoint σ)
#align equiv.perm.is_cycle.cycle_type Equiv.Perm.IsCycle.cycleType
theorem card_cycleType_eq_one {σ : Perm α} : Multiset.card σ.cycleType = 1 ↔ σ.IsCycle := by
rw [card_eq_one]
simp_rw [cycleType_def, Multiset.map_eq_singleton, ← Finset.singleton_val, Finset.val_inj,
cycleFactorsFinset_eq_singleton_iff]
constructor
· rintro ⟨_, _, ⟨h, -⟩, -⟩
exact h
· intro h
use σ.support.card, σ
simp [h]
#align equiv.perm.card_cycle_type_eq_one Equiv.Perm.card_cycleType_eq_one
| Mathlib/GroupTheory/Perm/Cycle/Type.lean | 122 | 126 | theorem Disjoint.cycleType {σ τ : Perm α} (h : Disjoint σ τ) :
(σ * τ).cycleType = σ.cycleType + τ.cycleType := by |
rw [cycleType_def, cycleType_def, cycleType_def, h.cycleFactorsFinset_mul_eq_union, ←
Multiset.map_add, Finset.union_val, Multiset.add_eq_union_iff_disjoint.mpr _]
exact Finset.disjoint_val.2 h.disjoint_cycleFactorsFinset
|
/-
Copyright (c) 2017 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Patrick Massot, Yury Kudryashov, Rémy Degenne
-/
import Mathlib.Order.MinMax
import Mathlib.Data.Set.Subsingleton
import Mathlib.Tactic.Says
#align_import data.set.intervals.basic from "leanprover-community/mathlib"@"3ba15165bd6927679be7c22d6091a87337e3cd0c"
/-!
# Intervals
In any preorder `α`, we define intervals (which on each side can be either infinite, open, or
closed) using the following naming conventions:
- `i`: infinite
- `o`: open
- `c`: closed
Each interval has the name `I` + letter for left side + letter for right side. For instance,
`Ioc a b` denotes the interval `(a, b]`.
This file contains these definitions, and basic facts on inclusion, intersection, difference of
intervals (where the precise statements may depend on the properties of the order, in particular
for some statements it should be `LinearOrder` or `DenselyOrdered`).
TODO: This is just the beginning; a lot of rules are missing
-/
open Function
open OrderDual (toDual ofDual)
variable {α β : Type*}
namespace Set
section Preorder
variable [Preorder α] {a a₁ a₂ b b₁ b₂ c x : α}
/-- Left-open right-open interval -/
def Ioo (a b : α) :=
{ x | a < x ∧ x < b }
#align set.Ioo Set.Ioo
/-- Left-closed right-open interval -/
def Ico (a b : α) :=
{ x | a ≤ x ∧ x < b }
#align set.Ico Set.Ico
/-- Left-infinite right-open interval -/
def Iio (a : α) :=
{ x | x < a }
#align set.Iio Set.Iio
/-- Left-closed right-closed interval -/
def Icc (a b : α) :=
{ x | a ≤ x ∧ x ≤ b }
#align set.Icc Set.Icc
/-- Left-infinite right-closed interval -/
def Iic (b : α) :=
{ x | x ≤ b }
#align set.Iic Set.Iic
/-- Left-open right-closed interval -/
def Ioc (a b : α) :=
{ x | a < x ∧ x ≤ b }
#align set.Ioc Set.Ioc
/-- Left-closed right-infinite interval -/
def Ici (a : α) :=
{ x | a ≤ x }
#align set.Ici Set.Ici
/-- Left-open right-infinite interval -/
def Ioi (a : α) :=
{ x | a < x }
#align set.Ioi Set.Ioi
theorem Ioo_def (a b : α) : { x | a < x ∧ x < b } = Ioo a b :=
rfl
#align set.Ioo_def Set.Ioo_def
theorem Ico_def (a b : α) : { x | a ≤ x ∧ x < b } = Ico a b :=
rfl
#align set.Ico_def Set.Ico_def
theorem Iio_def (a : α) : { x | x < a } = Iio a :=
rfl
#align set.Iio_def Set.Iio_def
theorem Icc_def (a b : α) : { x | a ≤ x ∧ x ≤ b } = Icc a b :=
rfl
#align set.Icc_def Set.Icc_def
theorem Iic_def (b : α) : { x | x ≤ b } = Iic b :=
rfl
#align set.Iic_def Set.Iic_def
theorem Ioc_def (a b : α) : { x | a < x ∧ x ≤ b } = Ioc a b :=
rfl
#align set.Ioc_def Set.Ioc_def
theorem Ici_def (a : α) : { x | a ≤ x } = Ici a :=
rfl
#align set.Ici_def Set.Ici_def
theorem Ioi_def (a : α) : { x | a < x } = Ioi a :=
rfl
#align set.Ioi_def Set.Ioi_def
@[simp]
theorem mem_Ioo : x ∈ Ioo a b ↔ a < x ∧ x < b :=
Iff.rfl
#align set.mem_Ioo Set.mem_Ioo
@[simp]
theorem mem_Ico : x ∈ Ico a b ↔ a ≤ x ∧ x < b :=
Iff.rfl
#align set.mem_Ico Set.mem_Ico
@[simp]
theorem mem_Iio : x ∈ Iio b ↔ x < b :=
Iff.rfl
#align set.mem_Iio Set.mem_Iio
@[simp]
theorem mem_Icc : x ∈ Icc a b ↔ a ≤ x ∧ x ≤ b :=
Iff.rfl
#align set.mem_Icc Set.mem_Icc
@[simp]
theorem mem_Iic : x ∈ Iic b ↔ x ≤ b :=
Iff.rfl
#align set.mem_Iic Set.mem_Iic
@[simp]
theorem mem_Ioc : x ∈ Ioc a b ↔ a < x ∧ x ≤ b :=
Iff.rfl
#align set.mem_Ioc Set.mem_Ioc
@[simp]
theorem mem_Ici : x ∈ Ici a ↔ a ≤ x :=
Iff.rfl
#align set.mem_Ici Set.mem_Ici
@[simp]
theorem mem_Ioi : x ∈ Ioi a ↔ a < x :=
Iff.rfl
#align set.mem_Ioi Set.mem_Ioi
instance decidableMemIoo [Decidable (a < x ∧ x < b)] : Decidable (x ∈ Ioo a b) := by assumption
#align set.decidable_mem_Ioo Set.decidableMemIoo
instance decidableMemIco [Decidable (a ≤ x ∧ x < b)] : Decidable (x ∈ Ico a b) := by assumption
#align set.decidable_mem_Ico Set.decidableMemIco
instance decidableMemIio [Decidable (x < b)] : Decidable (x ∈ Iio b) := by assumption
#align set.decidable_mem_Iio Set.decidableMemIio
instance decidableMemIcc [Decidable (a ≤ x ∧ x ≤ b)] : Decidable (x ∈ Icc a b) := by assumption
#align set.decidable_mem_Icc Set.decidableMemIcc
instance decidableMemIic [Decidable (x ≤ b)] : Decidable (x ∈ Iic b) := by assumption
#align set.decidable_mem_Iic Set.decidableMemIic
instance decidableMemIoc [Decidable (a < x ∧ x ≤ b)] : Decidable (x ∈ Ioc a b) := by assumption
#align set.decidable_mem_Ioc Set.decidableMemIoc
instance decidableMemIci [Decidable (a ≤ x)] : Decidable (x ∈ Ici a) := by assumption
#align set.decidable_mem_Ici Set.decidableMemIci
instance decidableMemIoi [Decidable (a < x)] : Decidable (x ∈ Ioi a) := by assumption
#align set.decidable_mem_Ioi Set.decidableMemIoi
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem left_mem_Ioo : a ∈ Ioo a b ↔ False := by simp [lt_irrefl]
#align set.left_mem_Ioo Set.left_mem_Ioo
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem left_mem_Ico : a ∈ Ico a b ↔ a < b := by simp [le_refl]
#align set.left_mem_Ico Set.left_mem_Ico
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem left_mem_Icc : a ∈ Icc a b ↔ a ≤ b := by simp [le_refl]
#align set.left_mem_Icc Set.left_mem_Icc
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem left_mem_Ioc : a ∈ Ioc a b ↔ False := by simp [lt_irrefl]
#align set.left_mem_Ioc Set.left_mem_Ioc
theorem left_mem_Ici : a ∈ Ici a := by simp
#align set.left_mem_Ici Set.left_mem_Ici
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem right_mem_Ioo : b ∈ Ioo a b ↔ False := by simp [lt_irrefl]
#align set.right_mem_Ioo Set.right_mem_Ioo
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem right_mem_Ico : b ∈ Ico a b ↔ False := by simp [lt_irrefl]
#align set.right_mem_Ico Set.right_mem_Ico
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem right_mem_Icc : b ∈ Icc a b ↔ a ≤ b := by simp [le_refl]
#align set.right_mem_Icc Set.right_mem_Icc
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem right_mem_Ioc : b ∈ Ioc a b ↔ a < b := by simp [le_refl]
#align set.right_mem_Ioc Set.right_mem_Ioc
theorem right_mem_Iic : a ∈ Iic a := by simp
#align set.right_mem_Iic Set.right_mem_Iic
@[simp]
theorem dual_Ici : Ici (toDual a) = ofDual ⁻¹' Iic a :=
rfl
#align set.dual_Ici Set.dual_Ici
@[simp]
theorem dual_Iic : Iic (toDual a) = ofDual ⁻¹' Ici a :=
rfl
#align set.dual_Iic Set.dual_Iic
@[simp]
theorem dual_Ioi : Ioi (toDual a) = ofDual ⁻¹' Iio a :=
rfl
#align set.dual_Ioi Set.dual_Ioi
@[simp]
theorem dual_Iio : Iio (toDual a) = ofDual ⁻¹' Ioi a :=
rfl
#align set.dual_Iio Set.dual_Iio
@[simp]
theorem dual_Icc : Icc (toDual a) (toDual b) = ofDual ⁻¹' Icc b a :=
Set.ext fun _ => and_comm
#align set.dual_Icc Set.dual_Icc
@[simp]
theorem dual_Ioc : Ioc (toDual a) (toDual b) = ofDual ⁻¹' Ico b a :=
Set.ext fun _ => and_comm
#align set.dual_Ioc Set.dual_Ioc
@[simp]
theorem dual_Ico : Ico (toDual a) (toDual b) = ofDual ⁻¹' Ioc b a :=
Set.ext fun _ => and_comm
#align set.dual_Ico Set.dual_Ico
@[simp]
theorem dual_Ioo : Ioo (toDual a) (toDual b) = ofDual ⁻¹' Ioo b a :=
Set.ext fun _ => and_comm
#align set.dual_Ioo Set.dual_Ioo
@[simp]
theorem nonempty_Icc : (Icc a b).Nonempty ↔ a ≤ b :=
⟨fun ⟨_, hx⟩ => hx.1.trans hx.2, fun h => ⟨a, left_mem_Icc.2 h⟩⟩
#align set.nonempty_Icc Set.nonempty_Icc
@[simp]
theorem nonempty_Ico : (Ico a b).Nonempty ↔ a < b :=
⟨fun ⟨_, hx⟩ => hx.1.trans_lt hx.2, fun h => ⟨a, left_mem_Ico.2 h⟩⟩
#align set.nonempty_Ico Set.nonempty_Ico
@[simp]
theorem nonempty_Ioc : (Ioc a b).Nonempty ↔ a < b :=
⟨fun ⟨_, hx⟩ => hx.1.trans_le hx.2, fun h => ⟨b, right_mem_Ioc.2 h⟩⟩
#align set.nonempty_Ioc Set.nonempty_Ioc
@[simp]
theorem nonempty_Ici : (Ici a).Nonempty :=
⟨a, left_mem_Ici⟩
#align set.nonempty_Ici Set.nonempty_Ici
@[simp]
theorem nonempty_Iic : (Iic a).Nonempty :=
⟨a, right_mem_Iic⟩
#align set.nonempty_Iic Set.nonempty_Iic
@[simp]
theorem nonempty_Ioo [DenselyOrdered α] : (Ioo a b).Nonempty ↔ a < b :=
⟨fun ⟨_, ha, hb⟩ => ha.trans hb, exists_between⟩
#align set.nonempty_Ioo Set.nonempty_Ioo
@[simp]
theorem nonempty_Ioi [NoMaxOrder α] : (Ioi a).Nonempty :=
exists_gt a
#align set.nonempty_Ioi Set.nonempty_Ioi
@[simp]
theorem nonempty_Iio [NoMinOrder α] : (Iio a).Nonempty :=
exists_lt a
#align set.nonempty_Iio Set.nonempty_Iio
theorem nonempty_Icc_subtype (h : a ≤ b) : Nonempty (Icc a b) :=
Nonempty.to_subtype (nonempty_Icc.mpr h)
#align set.nonempty_Icc_subtype Set.nonempty_Icc_subtype
theorem nonempty_Ico_subtype (h : a < b) : Nonempty (Ico a b) :=
Nonempty.to_subtype (nonempty_Ico.mpr h)
#align set.nonempty_Ico_subtype Set.nonempty_Ico_subtype
theorem nonempty_Ioc_subtype (h : a < b) : Nonempty (Ioc a b) :=
Nonempty.to_subtype (nonempty_Ioc.mpr h)
#align set.nonempty_Ioc_subtype Set.nonempty_Ioc_subtype
/-- An interval `Ici a` is nonempty. -/
instance nonempty_Ici_subtype : Nonempty (Ici a) :=
Nonempty.to_subtype nonempty_Ici
#align set.nonempty_Ici_subtype Set.nonempty_Ici_subtype
/-- An interval `Iic a` is nonempty. -/
instance nonempty_Iic_subtype : Nonempty (Iic a) :=
Nonempty.to_subtype nonempty_Iic
#align set.nonempty_Iic_subtype Set.nonempty_Iic_subtype
theorem nonempty_Ioo_subtype [DenselyOrdered α] (h : a < b) : Nonempty (Ioo a b) :=
Nonempty.to_subtype (nonempty_Ioo.mpr h)
#align set.nonempty_Ioo_subtype Set.nonempty_Ioo_subtype
/-- In an order without maximal elements, the intervals `Ioi` are nonempty. -/
instance nonempty_Ioi_subtype [NoMaxOrder α] : Nonempty (Ioi a) :=
Nonempty.to_subtype nonempty_Ioi
#align set.nonempty_Ioi_subtype Set.nonempty_Ioi_subtype
/-- In an order without minimal elements, the intervals `Iio` are nonempty. -/
instance nonempty_Iio_subtype [NoMinOrder α] : Nonempty (Iio a) :=
Nonempty.to_subtype nonempty_Iio
#align set.nonempty_Iio_subtype Set.nonempty_Iio_subtype
instance [NoMinOrder α] : NoMinOrder (Iio a) :=
⟨fun a =>
let ⟨b, hb⟩ := exists_lt (a : α)
⟨⟨b, lt_trans hb a.2⟩, hb⟩⟩
instance [NoMinOrder α] : NoMinOrder (Iic a) :=
⟨fun a =>
let ⟨b, hb⟩ := exists_lt (a : α)
⟨⟨b, hb.le.trans a.2⟩, hb⟩⟩
instance [NoMaxOrder α] : NoMaxOrder (Ioi a) :=
OrderDual.noMaxOrder (α := Iio (toDual a))
instance [NoMaxOrder α] : NoMaxOrder (Ici a) :=
OrderDual.noMaxOrder (α := Iic (toDual a))
@[simp]
theorem Icc_eq_empty (h : ¬a ≤ b) : Icc a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ ⟨ha, hb⟩ => h (ha.trans hb)
#align set.Icc_eq_empty Set.Icc_eq_empty
@[simp]
theorem Ico_eq_empty (h : ¬a < b) : Ico a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ ⟨ha, hb⟩ => h (ha.trans_lt hb)
#align set.Ico_eq_empty Set.Ico_eq_empty
@[simp]
theorem Ioc_eq_empty (h : ¬a < b) : Ioc a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ ⟨ha, hb⟩ => h (ha.trans_le hb)
#align set.Ioc_eq_empty Set.Ioc_eq_empty
@[simp]
theorem Ioo_eq_empty (h : ¬a < b) : Ioo a b = ∅ :=
eq_empty_iff_forall_not_mem.2 fun _ ⟨ha, hb⟩ => h (ha.trans hb)
#align set.Ioo_eq_empty Set.Ioo_eq_empty
@[simp]
theorem Icc_eq_empty_of_lt (h : b < a) : Icc a b = ∅ :=
Icc_eq_empty h.not_le
#align set.Icc_eq_empty_of_lt Set.Icc_eq_empty_of_lt
@[simp]
theorem Ico_eq_empty_of_le (h : b ≤ a) : Ico a b = ∅ :=
Ico_eq_empty h.not_lt
#align set.Ico_eq_empty_of_le Set.Ico_eq_empty_of_le
@[simp]
theorem Ioc_eq_empty_of_le (h : b ≤ a) : Ioc a b = ∅ :=
Ioc_eq_empty h.not_lt
#align set.Ioc_eq_empty_of_le Set.Ioc_eq_empty_of_le
@[simp]
theorem Ioo_eq_empty_of_le (h : b ≤ a) : Ioo a b = ∅ :=
Ioo_eq_empty h.not_lt
#align set.Ioo_eq_empty_of_le Set.Ioo_eq_empty_of_le
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem Ico_self (a : α) : Ico a a = ∅ :=
Ico_eq_empty <| lt_irrefl _
#align set.Ico_self Set.Ico_self
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem Ioc_self (a : α) : Ioc a a = ∅ :=
Ioc_eq_empty <| lt_irrefl _
#align set.Ioc_self Set.Ioc_self
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem Ioo_self (a : α) : Ioo a a = ∅ :=
Ioo_eq_empty <| lt_irrefl _
#align set.Ioo_self Set.Ioo_self
theorem Ici_subset_Ici : Ici a ⊆ Ici b ↔ b ≤ a :=
⟨fun h => h <| left_mem_Ici, fun h _ hx => h.trans hx⟩
#align set.Ici_subset_Ici Set.Ici_subset_Ici
@[gcongr] alias ⟨_, _root_.GCongr.Ici_subset_Ici_of_le⟩ := Ici_subset_Ici
theorem Iic_subset_Iic : Iic a ⊆ Iic b ↔ a ≤ b :=
@Ici_subset_Ici αᵒᵈ _ _ _
#align set.Iic_subset_Iic Set.Iic_subset_Iic
@[gcongr] alias ⟨_, _root_.GCongr.Iic_subset_Iic_of_le⟩ := Iic_subset_Iic
theorem Ici_subset_Ioi : Ici a ⊆ Ioi b ↔ b < a :=
⟨fun h => h left_mem_Ici, fun h _ hx => h.trans_le hx⟩
#align set.Ici_subset_Ioi Set.Ici_subset_Ioi
theorem Iic_subset_Iio : Iic a ⊆ Iio b ↔ a < b :=
⟨fun h => h right_mem_Iic, fun h _ hx => lt_of_le_of_lt hx h⟩
#align set.Iic_subset_Iio Set.Iic_subset_Iio
@[gcongr]
theorem Ioo_subset_Ioo (h₁ : a₂ ≤ a₁) (h₂ : b₁ ≤ b₂) : Ioo a₁ b₁ ⊆ Ioo a₂ b₂ := fun _ ⟨hx₁, hx₂⟩ =>
⟨h₁.trans_lt hx₁, hx₂.trans_le h₂⟩
#align set.Ioo_subset_Ioo Set.Ioo_subset_Ioo
@[gcongr]
theorem Ioo_subset_Ioo_left (h : a₁ ≤ a₂) : Ioo a₂ b ⊆ Ioo a₁ b :=
Ioo_subset_Ioo h le_rfl
#align set.Ioo_subset_Ioo_left Set.Ioo_subset_Ioo_left
@[gcongr]
theorem Ioo_subset_Ioo_right (h : b₁ ≤ b₂) : Ioo a b₁ ⊆ Ioo a b₂ :=
Ioo_subset_Ioo le_rfl h
#align set.Ioo_subset_Ioo_right Set.Ioo_subset_Ioo_right
@[gcongr]
theorem Ico_subset_Ico (h₁ : a₂ ≤ a₁) (h₂ : b₁ ≤ b₂) : Ico a₁ b₁ ⊆ Ico a₂ b₂ := fun _ ⟨hx₁, hx₂⟩ =>
⟨h₁.trans hx₁, hx₂.trans_le h₂⟩
#align set.Ico_subset_Ico Set.Ico_subset_Ico
@[gcongr]
theorem Ico_subset_Ico_left (h : a₁ ≤ a₂) : Ico a₂ b ⊆ Ico a₁ b :=
Ico_subset_Ico h le_rfl
#align set.Ico_subset_Ico_left Set.Ico_subset_Ico_left
@[gcongr]
theorem Ico_subset_Ico_right (h : b₁ ≤ b₂) : Ico a b₁ ⊆ Ico a b₂ :=
Ico_subset_Ico le_rfl h
#align set.Ico_subset_Ico_right Set.Ico_subset_Ico_right
@[gcongr]
theorem Icc_subset_Icc (h₁ : a₂ ≤ a₁) (h₂ : b₁ ≤ b₂) : Icc a₁ b₁ ⊆ Icc a₂ b₂ := fun _ ⟨hx₁, hx₂⟩ =>
⟨h₁.trans hx₁, le_trans hx₂ h₂⟩
#align set.Icc_subset_Icc Set.Icc_subset_Icc
@[gcongr]
theorem Icc_subset_Icc_left (h : a₁ ≤ a₂) : Icc a₂ b ⊆ Icc a₁ b :=
Icc_subset_Icc h le_rfl
#align set.Icc_subset_Icc_left Set.Icc_subset_Icc_left
@[gcongr]
theorem Icc_subset_Icc_right (h : b₁ ≤ b₂) : Icc a b₁ ⊆ Icc a b₂ :=
Icc_subset_Icc le_rfl h
#align set.Icc_subset_Icc_right Set.Icc_subset_Icc_right
theorem Icc_subset_Ioo (ha : a₂ < a₁) (hb : b₁ < b₂) : Icc a₁ b₁ ⊆ Ioo a₂ b₂ := fun _ hx =>
⟨ha.trans_le hx.1, hx.2.trans_lt hb⟩
#align set.Icc_subset_Ioo Set.Icc_subset_Ioo
theorem Icc_subset_Ici_self : Icc a b ⊆ Ici a := fun _ => And.left
#align set.Icc_subset_Ici_self Set.Icc_subset_Ici_self
theorem Icc_subset_Iic_self : Icc a b ⊆ Iic b := fun _ => And.right
#align set.Icc_subset_Iic_self Set.Icc_subset_Iic_self
theorem Ioc_subset_Iic_self : Ioc a b ⊆ Iic b := fun _ => And.right
#align set.Ioc_subset_Iic_self Set.Ioc_subset_Iic_self
@[gcongr]
theorem Ioc_subset_Ioc (h₁ : a₂ ≤ a₁) (h₂ : b₁ ≤ b₂) : Ioc a₁ b₁ ⊆ Ioc a₂ b₂ := fun _ ⟨hx₁, hx₂⟩ =>
⟨h₁.trans_lt hx₁, hx₂.trans h₂⟩
#align set.Ioc_subset_Ioc Set.Ioc_subset_Ioc
@[gcongr]
theorem Ioc_subset_Ioc_left (h : a₁ ≤ a₂) : Ioc a₂ b ⊆ Ioc a₁ b :=
Ioc_subset_Ioc h le_rfl
#align set.Ioc_subset_Ioc_left Set.Ioc_subset_Ioc_left
@[gcongr]
theorem Ioc_subset_Ioc_right (h : b₁ ≤ b₂) : Ioc a b₁ ⊆ Ioc a b₂ :=
Ioc_subset_Ioc le_rfl h
#align set.Ioc_subset_Ioc_right Set.Ioc_subset_Ioc_right
theorem Ico_subset_Ioo_left (h₁ : a₁ < a₂) : Ico a₂ b ⊆ Ioo a₁ b := fun _ =>
And.imp_left h₁.trans_le
#align set.Ico_subset_Ioo_left Set.Ico_subset_Ioo_left
theorem Ioc_subset_Ioo_right (h : b₁ < b₂) : Ioc a b₁ ⊆ Ioo a b₂ := fun _ =>
And.imp_right fun h' => h'.trans_lt h
#align set.Ioc_subset_Ioo_right Set.Ioc_subset_Ioo_right
theorem Icc_subset_Ico_right (h₁ : b₁ < b₂) : Icc a b₁ ⊆ Ico a b₂ := fun _ =>
And.imp_right fun h₂ => h₂.trans_lt h₁
#align set.Icc_subset_Ico_right Set.Icc_subset_Ico_right
theorem Ioo_subset_Ico_self : Ioo a b ⊆ Ico a b := fun _ => And.imp_left le_of_lt
#align set.Ioo_subset_Ico_self Set.Ioo_subset_Ico_self
theorem Ioo_subset_Ioc_self : Ioo a b ⊆ Ioc a b := fun _ => And.imp_right le_of_lt
#align set.Ioo_subset_Ioc_self Set.Ioo_subset_Ioc_self
theorem Ico_subset_Icc_self : Ico a b ⊆ Icc a b := fun _ => And.imp_right le_of_lt
#align set.Ico_subset_Icc_self Set.Ico_subset_Icc_self
theorem Ioc_subset_Icc_self : Ioc a b ⊆ Icc a b := fun _ => And.imp_left le_of_lt
#align set.Ioc_subset_Icc_self Set.Ioc_subset_Icc_self
theorem Ioo_subset_Icc_self : Ioo a b ⊆ Icc a b :=
Subset.trans Ioo_subset_Ico_self Ico_subset_Icc_self
#align set.Ioo_subset_Icc_self Set.Ioo_subset_Icc_self
theorem Ico_subset_Iio_self : Ico a b ⊆ Iio b := fun _ => And.right
#align set.Ico_subset_Iio_self Set.Ico_subset_Iio_self
theorem Ioo_subset_Iio_self : Ioo a b ⊆ Iio b := fun _ => And.right
#align set.Ioo_subset_Iio_self Set.Ioo_subset_Iio_self
theorem Ioc_subset_Ioi_self : Ioc a b ⊆ Ioi a := fun _ => And.left
#align set.Ioc_subset_Ioi_self Set.Ioc_subset_Ioi_self
theorem Ioo_subset_Ioi_self : Ioo a b ⊆ Ioi a := fun _ => And.left
#align set.Ioo_subset_Ioi_self Set.Ioo_subset_Ioi_self
theorem Ioi_subset_Ici_self : Ioi a ⊆ Ici a := fun _ hx => le_of_lt hx
#align set.Ioi_subset_Ici_self Set.Ioi_subset_Ici_self
theorem Iio_subset_Iic_self : Iio a ⊆ Iic a := fun _ hx => le_of_lt hx
#align set.Iio_subset_Iic_self Set.Iio_subset_Iic_self
theorem Ico_subset_Ici_self : Ico a b ⊆ Ici a := fun _ => And.left
#align set.Ico_subset_Ici_self Set.Ico_subset_Ici_self
theorem Ioi_ssubset_Ici_self : Ioi a ⊂ Ici a :=
⟨Ioi_subset_Ici_self, fun h => lt_irrefl a (h le_rfl)⟩
#align set.Ioi_ssubset_Ici_self Set.Ioi_ssubset_Ici_self
theorem Iio_ssubset_Iic_self : Iio a ⊂ Iic a :=
@Ioi_ssubset_Ici_self αᵒᵈ _ _
#align set.Iio_ssubset_Iic_self Set.Iio_ssubset_Iic_self
theorem Icc_subset_Icc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Icc a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ :=
⟨fun h => ⟨(h ⟨le_rfl, h₁⟩).1, (h ⟨h₁, le_rfl⟩).2⟩, fun ⟨h, h'⟩ _ ⟨hx, hx'⟩ =>
⟨h.trans hx, hx'.trans h'⟩⟩
#align set.Icc_subset_Icc_iff Set.Icc_subset_Icc_iff
theorem Icc_subset_Ioo_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioo a₂ b₂ ↔ a₂ < a₁ ∧ b₁ < b₂ :=
⟨fun h => ⟨(h ⟨le_rfl, h₁⟩).1, (h ⟨h₁, le_rfl⟩).2⟩, fun ⟨h, h'⟩ _ ⟨hx, hx'⟩ =>
⟨h.trans_le hx, hx'.trans_lt h'⟩⟩
#align set.Icc_subset_Ioo_iff Set.Icc_subset_Ioo_iff
theorem Icc_subset_Ico_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ico a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ < b₂ :=
⟨fun h => ⟨(h ⟨le_rfl, h₁⟩).1, (h ⟨h₁, le_rfl⟩).2⟩, fun ⟨h, h'⟩ _ ⟨hx, hx'⟩ =>
⟨h.trans hx, hx'.trans_lt h'⟩⟩
#align set.Icc_subset_Ico_iff Set.Icc_subset_Ico_iff
theorem Icc_subset_Ioc_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioc a₂ b₂ ↔ a₂ < a₁ ∧ b₁ ≤ b₂ :=
⟨fun h => ⟨(h ⟨le_rfl, h₁⟩).1, (h ⟨h₁, le_rfl⟩).2⟩, fun ⟨h, h'⟩ _ ⟨hx, hx'⟩ =>
⟨h.trans_le hx, hx'.trans h'⟩⟩
#align set.Icc_subset_Ioc_iff Set.Icc_subset_Ioc_iff
theorem Icc_subset_Iio_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Iio b₂ ↔ b₁ < b₂ :=
⟨fun h => h ⟨h₁, le_rfl⟩, fun h _ ⟨_, hx'⟩ => hx'.trans_lt h⟩
#align set.Icc_subset_Iio_iff Set.Icc_subset_Iio_iff
theorem Icc_subset_Ioi_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ioi a₂ ↔ a₂ < a₁ :=
⟨fun h => h ⟨le_rfl, h₁⟩, fun h _ ⟨hx, _⟩ => h.trans_le hx⟩
#align set.Icc_subset_Ioi_iff Set.Icc_subset_Ioi_iff
theorem Icc_subset_Iic_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Iic b₂ ↔ b₁ ≤ b₂ :=
⟨fun h => h ⟨h₁, le_rfl⟩, fun h _ ⟨_, hx'⟩ => hx'.trans h⟩
#align set.Icc_subset_Iic_iff Set.Icc_subset_Iic_iff
theorem Icc_subset_Ici_iff (h₁ : a₁ ≤ b₁) : Icc a₁ b₁ ⊆ Ici a₂ ↔ a₂ ≤ a₁ :=
⟨fun h => h ⟨le_rfl, h₁⟩, fun h _ ⟨hx, _⟩ => h.trans hx⟩
#align set.Icc_subset_Ici_iff Set.Icc_subset_Ici_iff
theorem Icc_ssubset_Icc_left (hI : a₂ ≤ b₂) (ha : a₂ < a₁) (hb : b₁ ≤ b₂) : Icc a₁ b₁ ⊂ Icc a₂ b₂ :=
(ssubset_iff_of_subset (Icc_subset_Icc (le_of_lt ha) hb)).mpr
⟨a₂, left_mem_Icc.mpr hI, not_and.mpr fun f _ => lt_irrefl a₂ (ha.trans_le f)⟩
#align set.Icc_ssubset_Icc_left Set.Icc_ssubset_Icc_left
theorem Icc_ssubset_Icc_right (hI : a₂ ≤ b₂) (ha : a₂ ≤ a₁) (hb : b₁ < b₂) :
Icc a₁ b₁ ⊂ Icc a₂ b₂ :=
(ssubset_iff_of_subset (Icc_subset_Icc ha (le_of_lt hb))).mpr
⟨b₂, right_mem_Icc.mpr hI, fun f => lt_irrefl b₁ (hb.trans_le f.2)⟩
#align set.Icc_ssubset_Icc_right Set.Icc_ssubset_Icc_right
/-- If `a ≤ b`, then `(b, +∞) ⊆ (a, +∞)`. In preorders, this is just an implication. If you need
the equivalence in linear orders, use `Ioi_subset_Ioi_iff`. -/
@[gcongr]
theorem Ioi_subset_Ioi (h : a ≤ b) : Ioi b ⊆ Ioi a := fun _ hx => h.trans_lt hx
#align set.Ioi_subset_Ioi Set.Ioi_subset_Ioi
/-- If `a ≤ b`, then `(b, +∞) ⊆ [a, +∞)`. In preorders, this is just an implication. If you need
the equivalence in dense linear orders, use `Ioi_subset_Ici_iff`. -/
theorem Ioi_subset_Ici (h : a ≤ b) : Ioi b ⊆ Ici a :=
Subset.trans (Ioi_subset_Ioi h) Ioi_subset_Ici_self
#align set.Ioi_subset_Ici Set.Ioi_subset_Ici
/-- If `a ≤ b`, then `(-∞, a) ⊆ (-∞, b)`. In preorders, this is just an implication. If you need
the equivalence in linear orders, use `Iio_subset_Iio_iff`. -/
@[gcongr]
theorem Iio_subset_Iio (h : a ≤ b) : Iio a ⊆ Iio b := fun _ hx => lt_of_lt_of_le hx h
#align set.Iio_subset_Iio Set.Iio_subset_Iio
/-- If `a ≤ b`, then `(-∞, a) ⊆ (-∞, b]`. In preorders, this is just an implication. If you need
the equivalence in dense linear orders, use `Iio_subset_Iic_iff`. -/
theorem Iio_subset_Iic (h : a ≤ b) : Iio a ⊆ Iic b :=
Subset.trans (Iio_subset_Iio h) Iio_subset_Iic_self
#align set.Iio_subset_Iic Set.Iio_subset_Iic
theorem Ici_inter_Iic : Ici a ∩ Iic b = Icc a b :=
rfl
#align set.Ici_inter_Iic Set.Ici_inter_Iic
theorem Ici_inter_Iio : Ici a ∩ Iio b = Ico a b :=
rfl
#align set.Ici_inter_Iio Set.Ici_inter_Iio
theorem Ioi_inter_Iic : Ioi a ∩ Iic b = Ioc a b :=
rfl
#align set.Ioi_inter_Iic Set.Ioi_inter_Iic
theorem Ioi_inter_Iio : Ioi a ∩ Iio b = Ioo a b :=
rfl
#align set.Ioi_inter_Iio Set.Ioi_inter_Iio
theorem Iic_inter_Ici : Iic a ∩ Ici b = Icc b a :=
inter_comm _ _
#align set.Iic_inter_Ici Set.Iic_inter_Ici
theorem Iio_inter_Ici : Iio a ∩ Ici b = Ico b a :=
inter_comm _ _
#align set.Iio_inter_Ici Set.Iio_inter_Ici
theorem Iic_inter_Ioi : Iic a ∩ Ioi b = Ioc b a :=
inter_comm _ _
#align set.Iic_inter_Ioi Set.Iic_inter_Ioi
theorem Iio_inter_Ioi : Iio a ∩ Ioi b = Ioo b a :=
inter_comm _ _
#align set.Iio_inter_Ioi Set.Iio_inter_Ioi
theorem mem_Icc_of_Ioo (h : x ∈ Ioo a b) : x ∈ Icc a b :=
Ioo_subset_Icc_self h
#align set.mem_Icc_of_Ioo Set.mem_Icc_of_Ioo
theorem mem_Ico_of_Ioo (h : x ∈ Ioo a b) : x ∈ Ico a b :=
Ioo_subset_Ico_self h
#align set.mem_Ico_of_Ioo Set.mem_Ico_of_Ioo
theorem mem_Ioc_of_Ioo (h : x ∈ Ioo a b) : x ∈ Ioc a b :=
Ioo_subset_Ioc_self h
#align set.mem_Ioc_of_Ioo Set.mem_Ioc_of_Ioo
theorem mem_Icc_of_Ico (h : x ∈ Ico a b) : x ∈ Icc a b :=
Ico_subset_Icc_self h
#align set.mem_Icc_of_Ico Set.mem_Icc_of_Ico
theorem mem_Icc_of_Ioc (h : x ∈ Ioc a b) : x ∈ Icc a b :=
Ioc_subset_Icc_self h
#align set.mem_Icc_of_Ioc Set.mem_Icc_of_Ioc
theorem mem_Ici_of_Ioi (h : x ∈ Ioi a) : x ∈ Ici a :=
Ioi_subset_Ici_self h
#align set.mem_Ici_of_Ioi Set.mem_Ici_of_Ioi
theorem mem_Iic_of_Iio (h : x ∈ Iio a) : x ∈ Iic a :=
Iio_subset_Iic_self h
#align set.mem_Iic_of_Iio Set.mem_Iic_of_Iio
theorem Icc_eq_empty_iff : Icc a b = ∅ ↔ ¬a ≤ b := by
rw [← not_nonempty_iff_eq_empty, not_iff_not, nonempty_Icc]
#align set.Icc_eq_empty_iff Set.Icc_eq_empty_iff
theorem Ico_eq_empty_iff : Ico a b = ∅ ↔ ¬a < b := by
rw [← not_nonempty_iff_eq_empty, not_iff_not, nonempty_Ico]
#align set.Ico_eq_empty_iff Set.Ico_eq_empty_iff
theorem Ioc_eq_empty_iff : Ioc a b = ∅ ↔ ¬a < b := by
rw [← not_nonempty_iff_eq_empty, not_iff_not, nonempty_Ioc]
#align set.Ioc_eq_empty_iff Set.Ioc_eq_empty_iff
theorem Ioo_eq_empty_iff [DenselyOrdered α] : Ioo a b = ∅ ↔ ¬a < b := by
rw [← not_nonempty_iff_eq_empty, not_iff_not, nonempty_Ioo]
#align set.Ioo_eq_empty_iff Set.Ioo_eq_empty_iff
theorem _root_.IsTop.Iic_eq (h : IsTop a) : Iic a = univ :=
eq_univ_of_forall h
#align is_top.Iic_eq IsTop.Iic_eq
theorem _root_.IsBot.Ici_eq (h : IsBot a) : Ici a = univ :=
eq_univ_of_forall h
#align is_bot.Ici_eq IsBot.Ici_eq
theorem _root_.IsMax.Ioi_eq (h : IsMax a) : Ioi a = ∅ :=
eq_empty_of_subset_empty fun _ => h.not_lt
#align is_max.Ioi_eq IsMax.Ioi_eq
theorem _root_.IsMin.Iio_eq (h : IsMin a) : Iio a = ∅ :=
eq_empty_of_subset_empty fun _ => h.not_lt
#align is_min.Iio_eq IsMin.Iio_eq
theorem Iic_inter_Ioc_of_le (h : a ≤ c) : Iic a ∩ Ioc b c = Ioc b a :=
ext fun _ => ⟨fun H => ⟨H.2.1, H.1⟩, fun H => ⟨H.2, H.1, H.2.trans h⟩⟩
#align set.Iic_inter_Ioc_of_le Set.Iic_inter_Ioc_of_le
theorem not_mem_Icc_of_lt (ha : c < a) : c ∉ Icc a b := fun h => ha.not_le h.1
#align set.not_mem_Icc_of_lt Set.not_mem_Icc_of_lt
theorem not_mem_Icc_of_gt (hb : b < c) : c ∉ Icc a b := fun h => hb.not_le h.2
#align set.not_mem_Icc_of_gt Set.not_mem_Icc_of_gt
theorem not_mem_Ico_of_lt (ha : c < a) : c ∉ Ico a b := fun h => ha.not_le h.1
#align set.not_mem_Ico_of_lt Set.not_mem_Ico_of_lt
theorem not_mem_Ioc_of_gt (hb : b < c) : c ∉ Ioc a b := fun h => hb.not_le h.2
#align set.not_mem_Ioc_of_gt Set.not_mem_Ioc_of_gt
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem not_mem_Ioi_self : a ∉ Ioi a := lt_irrefl _
#align set.not_mem_Ioi_self Set.not_mem_Ioi_self
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem not_mem_Iio_self : b ∉ Iio b := lt_irrefl _
#align set.not_mem_Iio_self Set.not_mem_Iio_self
theorem not_mem_Ioc_of_le (ha : c ≤ a) : c ∉ Ioc a b := fun h => lt_irrefl _ <| h.1.trans_le ha
#align set.not_mem_Ioc_of_le Set.not_mem_Ioc_of_le
theorem not_mem_Ico_of_ge (hb : b ≤ c) : c ∉ Ico a b := fun h => lt_irrefl _ <| h.2.trans_le hb
#align set.not_mem_Ico_of_ge Set.not_mem_Ico_of_ge
theorem not_mem_Ioo_of_le (ha : c ≤ a) : c ∉ Ioo a b := fun h => lt_irrefl _ <| h.1.trans_le ha
#align set.not_mem_Ioo_of_le Set.not_mem_Ioo_of_le
theorem not_mem_Ioo_of_ge (hb : b ≤ c) : c ∉ Ioo a b := fun h => lt_irrefl _ <| h.2.trans_le hb
#align set.not_mem_Ioo_of_ge Set.not_mem_Ioo_of_ge
end Preorder
section PartialOrder
variable [PartialOrder α] {a b c : α}
@[simp]
theorem Icc_self (a : α) : Icc a a = {a} :=
Set.ext <| by simp [Icc, le_antisymm_iff, and_comm]
#align set.Icc_self Set.Icc_self
instance instIccUnique : Unique (Set.Icc a a) where
default := ⟨a, by simp⟩
uniq y := Subtype.ext <| by simpa using y.2
@[simp]
theorem Icc_eq_singleton_iff : Icc a b = {c} ↔ a = c ∧ b = c := by
refine ⟨fun h => ?_, ?_⟩
· have hab : a ≤ b := nonempty_Icc.1 (h.symm.subst <| singleton_nonempty c)
exact
⟨eq_of_mem_singleton <| h.subst <| left_mem_Icc.2 hab,
eq_of_mem_singleton <| h.subst <| right_mem_Icc.2 hab⟩
· rintro ⟨rfl, rfl⟩
exact Icc_self _
#align set.Icc_eq_singleton_iff Set.Icc_eq_singleton_iff
lemma subsingleton_Icc_of_ge (hba : b ≤ a) : Set.Subsingleton (Icc a b) :=
fun _x ⟨hax, hxb⟩ _y ⟨hay, hyb⟩ ↦ le_antisymm
(le_implies_le_of_le_of_le hxb hay hba) (le_implies_le_of_le_of_le hyb hax hba)
#align set.subsingleton_Icc_of_ge Set.subsingleton_Icc_of_ge
@[simp] lemma subsingleton_Icc_iff {α : Type*} [LinearOrder α] {a b : α} :
Set.Subsingleton (Icc a b) ↔ b ≤ a := by
refine ⟨fun h ↦ ?_, subsingleton_Icc_of_ge⟩
contrapose! h
simp only [ge_iff_le, gt_iff_lt, not_subsingleton_iff]
exact ⟨a, ⟨le_refl _, h.le⟩, b, ⟨h.le, le_refl _⟩, h.ne⟩
@[simp]
theorem Icc_diff_left : Icc a b \ {a} = Ioc a b :=
ext fun x => by simp [lt_iff_le_and_ne, eq_comm, and_right_comm]
#align set.Icc_diff_left Set.Icc_diff_left
@[simp]
theorem Icc_diff_right : Icc a b \ {b} = Ico a b :=
ext fun x => by simp [lt_iff_le_and_ne, and_assoc]
#align set.Icc_diff_right Set.Icc_diff_right
@[simp]
theorem Ico_diff_left : Ico a b \ {a} = Ioo a b :=
ext fun x => by simp [and_right_comm, ← lt_iff_le_and_ne, eq_comm]
#align set.Ico_diff_left Set.Ico_diff_left
@[simp]
theorem Ioc_diff_right : Ioc a b \ {b} = Ioo a b :=
ext fun x => by simp [and_assoc, ← lt_iff_le_and_ne]
#align set.Ioc_diff_right Set.Ioc_diff_right
@[simp]
theorem Icc_diff_both : Icc a b \ {a, b} = Ioo a b := by
rw [insert_eq, ← diff_diff, Icc_diff_left, Ioc_diff_right]
#align set.Icc_diff_both Set.Icc_diff_both
@[simp]
theorem Ici_diff_left : Ici a \ {a} = Ioi a :=
ext fun x => by simp [lt_iff_le_and_ne, eq_comm]
#align set.Ici_diff_left Set.Ici_diff_left
@[simp]
theorem Iic_diff_right : Iic a \ {a} = Iio a :=
ext fun x => by simp [lt_iff_le_and_ne]
#align set.Iic_diff_right Set.Iic_diff_right
@[simp]
theorem Ico_diff_Ioo_same (h : a < b) : Ico a b \ Ioo a b = {a} := by
rw [← Ico_diff_left, diff_diff_cancel_left (singleton_subset_iff.2 <| left_mem_Ico.2 h)]
#align set.Ico_diff_Ioo_same Set.Ico_diff_Ioo_same
@[simp]
theorem Ioc_diff_Ioo_same (h : a < b) : Ioc a b \ Ioo a b = {b} := by
rw [← Ioc_diff_right, diff_diff_cancel_left (singleton_subset_iff.2 <| right_mem_Ioc.2 h)]
#align set.Ioc_diff_Ioo_same Set.Ioc_diff_Ioo_same
@[simp]
theorem Icc_diff_Ico_same (h : a ≤ b) : Icc a b \ Ico a b = {b} := by
rw [← Icc_diff_right, diff_diff_cancel_left (singleton_subset_iff.2 <| right_mem_Icc.2 h)]
#align set.Icc_diff_Ico_same Set.Icc_diff_Ico_same
@[simp]
theorem Icc_diff_Ioc_same (h : a ≤ b) : Icc a b \ Ioc a b = {a} := by
rw [← Icc_diff_left, diff_diff_cancel_left (singleton_subset_iff.2 <| left_mem_Icc.2 h)]
#align set.Icc_diff_Ioc_same Set.Icc_diff_Ioc_same
@[simp]
theorem Icc_diff_Ioo_same (h : a ≤ b) : Icc a b \ Ioo a b = {a, b} := by
rw [← Icc_diff_both, diff_diff_cancel_left]
simp [insert_subset_iff, h]
#align set.Icc_diff_Ioo_same Set.Icc_diff_Ioo_same
@[simp]
theorem Ici_diff_Ioi_same : Ici a \ Ioi a = {a} := by
rw [← Ici_diff_left, diff_diff_cancel_left (singleton_subset_iff.2 left_mem_Ici)]
#align set.Ici_diff_Ioi_same Set.Ici_diff_Ioi_same
@[simp]
theorem Iic_diff_Iio_same : Iic a \ Iio a = {a} := by
rw [← Iic_diff_right, diff_diff_cancel_left (singleton_subset_iff.2 right_mem_Iic)]
#align set.Iic_diff_Iio_same Set.Iic_diff_Iio_same
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem Ioi_union_left : Ioi a ∪ {a} = Ici a :=
ext fun x => by simp [eq_comm, le_iff_eq_or_lt]
#align set.Ioi_union_left Set.Ioi_union_left
-- Porting note (#10618): `simp` can prove this
-- @[simp]
theorem Iio_union_right : Iio a ∪ {a} = Iic a :=
ext fun _ => le_iff_lt_or_eq.symm
#align set.Iio_union_right Set.Iio_union_right
theorem Ioo_union_left (hab : a < b) : Ioo a b ∪ {a} = Ico a b := by
rw [← Ico_diff_left, diff_union_self,
union_eq_self_of_subset_right (singleton_subset_iff.2 <| left_mem_Ico.2 hab)]
#align set.Ioo_union_left Set.Ioo_union_left
theorem Ioo_union_right (hab : a < b) : Ioo a b ∪ {b} = Ioc a b := by
simpa only [dual_Ioo, dual_Ico] using Ioo_union_left hab.dual
#align set.Ioo_union_right Set.Ioo_union_right
theorem Ioo_union_both (h : a ≤ b) : Ioo a b ∪ {a, b} = Icc a b := by
have : (Icc a b \ {a, b}) ∪ {a, b} = Icc a b := diff_union_of_subset fun
| x, .inl rfl => left_mem_Icc.mpr h
| x, .inr rfl => right_mem_Icc.mpr h
rw [← this, Icc_diff_both]
theorem Ioc_union_left (hab : a ≤ b) : Ioc a b ∪ {a} = Icc a b := by
rw [← Icc_diff_left, diff_union_self,
union_eq_self_of_subset_right (singleton_subset_iff.2 <| left_mem_Icc.2 hab)]
#align set.Ioc_union_left Set.Ioc_union_left
theorem Ico_union_right (hab : a ≤ b) : Ico a b ∪ {b} = Icc a b := by
simpa only [dual_Ioc, dual_Icc] using Ioc_union_left hab.dual
#align set.Ico_union_right Set.Ico_union_right
@[simp]
theorem Ico_insert_right (h : a ≤ b) : insert b (Ico a b) = Icc a b := by
rw [insert_eq, union_comm, Ico_union_right h]
#align set.Ico_insert_right Set.Ico_insert_right
@[simp]
theorem Ioc_insert_left (h : a ≤ b) : insert a (Ioc a b) = Icc a b := by
rw [insert_eq, union_comm, Ioc_union_left h]
#align set.Ioc_insert_left Set.Ioc_insert_left
@[simp]
theorem Ioo_insert_left (h : a < b) : insert a (Ioo a b) = Ico a b := by
rw [insert_eq, union_comm, Ioo_union_left h]
#align set.Ioo_insert_left Set.Ioo_insert_left
@[simp]
theorem Ioo_insert_right (h : a < b) : insert b (Ioo a b) = Ioc a b := by
rw [insert_eq, union_comm, Ioo_union_right h]
#align set.Ioo_insert_right Set.Ioo_insert_right
@[simp]
theorem Iio_insert : insert a (Iio a) = Iic a :=
ext fun _ => le_iff_eq_or_lt.symm
#align set.Iio_insert Set.Iio_insert
@[simp]
theorem Ioi_insert : insert a (Ioi a) = Ici a :=
ext fun _ => (or_congr_left eq_comm).trans le_iff_eq_or_lt.symm
#align set.Ioi_insert Set.Ioi_insert
theorem mem_Ici_Ioi_of_subset_of_subset {s : Set α} (ho : Ioi a ⊆ s) (hc : s ⊆ Ici a) :
s ∈ ({Ici a, Ioi a} : Set (Set α)) :=
by_cases
(fun h : a ∈ s =>
Or.inl <| Subset.antisymm hc <| by rw [← Ioi_union_left, union_subset_iff]; simp [*])
fun h =>
Or.inr <| Subset.antisymm (fun x hx => lt_of_le_of_ne (hc hx) fun heq => h <| heq.symm ▸ hx) ho
#align set.mem_Ici_Ioi_of_subset_of_subset Set.mem_Ici_Ioi_of_subset_of_subset
theorem mem_Iic_Iio_of_subset_of_subset {s : Set α} (ho : Iio a ⊆ s) (hc : s ⊆ Iic a) :
s ∈ ({Iic a, Iio a} : Set (Set α)) :=
@mem_Ici_Ioi_of_subset_of_subset αᵒᵈ _ a s ho hc
#align set.mem_Iic_Iio_of_subset_of_subset Set.mem_Iic_Iio_of_subset_of_subset
theorem mem_Icc_Ico_Ioc_Ioo_of_subset_of_subset {s : Set α} (ho : Ioo a b ⊆ s) (hc : s ⊆ Icc a b) :
s ∈ ({Icc a b, Ico a b, Ioc a b, Ioo a b} : Set (Set α)) := by
classical
by_cases ha : a ∈ s <;> by_cases hb : b ∈ s
· refine Or.inl (Subset.antisymm hc ?_)
rwa [← Ico_diff_left, diff_singleton_subset_iff, insert_eq_of_mem ha, ← Icc_diff_right,
diff_singleton_subset_iff, insert_eq_of_mem hb] at ho
· refine Or.inr <| Or.inl <| Subset.antisymm ?_ ?_
· rw [← Icc_diff_right]
exact subset_diff_singleton hc hb
· rwa [← Ico_diff_left, diff_singleton_subset_iff, insert_eq_of_mem ha] at ho
· refine Or.inr <| Or.inr <| Or.inl <| Subset.antisymm ?_ ?_
· rw [← Icc_diff_left]
exact subset_diff_singleton hc ha
· rwa [← Ioc_diff_right, diff_singleton_subset_iff, insert_eq_of_mem hb] at ho
· refine Or.inr <| Or.inr <| Or.inr <| Subset.antisymm ?_ ho
rw [← Ico_diff_left, ← Icc_diff_right]
apply_rules [subset_diff_singleton]
#align set.mem_Icc_Ico_Ioc_Ioo_of_subset_of_subset Set.mem_Icc_Ico_Ioc_Ioo_of_subset_of_subset
theorem eq_left_or_mem_Ioo_of_mem_Ico {x : α} (hmem : x ∈ Ico a b) : x = a ∨ x ∈ Ioo a b :=
hmem.1.eq_or_gt.imp_right fun h => ⟨h, hmem.2⟩
#align set.eq_left_or_mem_Ioo_of_mem_Ico Set.eq_left_or_mem_Ioo_of_mem_Ico
theorem eq_right_or_mem_Ioo_of_mem_Ioc {x : α} (hmem : x ∈ Ioc a b) : x = b ∨ x ∈ Ioo a b :=
hmem.2.eq_or_lt.imp_right <| And.intro hmem.1
#align set.eq_right_or_mem_Ioo_of_mem_Ioc Set.eq_right_or_mem_Ioo_of_mem_Ioc
theorem eq_endpoints_or_mem_Ioo_of_mem_Icc {x : α} (hmem : x ∈ Icc a b) :
x = a ∨ x = b ∨ x ∈ Ioo a b :=
hmem.1.eq_or_gt.imp_right fun h => eq_right_or_mem_Ioo_of_mem_Ioc ⟨h, hmem.2⟩
#align set.eq_endpoints_or_mem_Ioo_of_mem_Icc Set.eq_endpoints_or_mem_Ioo_of_mem_Icc
theorem _root_.IsMax.Ici_eq (h : IsMax a) : Ici a = {a} :=
eq_singleton_iff_unique_mem.2 ⟨left_mem_Ici, fun _ => h.eq_of_ge⟩
#align is_max.Ici_eq IsMax.Ici_eq
theorem _root_.IsMin.Iic_eq (h : IsMin a) : Iic a = {a} :=
h.toDual.Ici_eq
#align is_min.Iic_eq IsMin.Iic_eq
theorem Ici_injective : Injective (Ici : α → Set α) := fun _ _ =>
eq_of_forall_ge_iff ∘ Set.ext_iff.1
#align set.Ici_injective Set.Ici_injective
theorem Iic_injective : Injective (Iic : α → Set α) := fun _ _ =>
eq_of_forall_le_iff ∘ Set.ext_iff.1
#align set.Iic_injective Set.Iic_injective
theorem Ici_inj : Ici a = Ici b ↔ a = b :=
Ici_injective.eq_iff
#align set.Ici_inj Set.Ici_inj
theorem Iic_inj : Iic a = Iic b ↔ a = b :=
Iic_injective.eq_iff
#align set.Iic_inj Set.Iic_inj
end PartialOrder
section OrderTop
@[simp]
theorem Ici_top [PartialOrder α] [OrderTop α] : Ici (⊤ : α) = {⊤} :=
isMax_top.Ici_eq
#align set.Ici_top Set.Ici_top
variable [Preorder α] [OrderTop α] {a : α}
@[simp]
theorem Ioi_top : Ioi (⊤ : α) = ∅ :=
isMax_top.Ioi_eq
#align set.Ioi_top Set.Ioi_top
@[simp]
theorem Iic_top : Iic (⊤ : α) = univ :=
isTop_top.Iic_eq
#align set.Iic_top Set.Iic_top
@[simp]
theorem Icc_top : Icc a ⊤ = Ici a := by simp [← Ici_inter_Iic]
#align set.Icc_top Set.Icc_top
@[simp]
theorem Ioc_top : Ioc a ⊤ = Ioi a := by simp [← Ioi_inter_Iic]
#align set.Ioc_top Set.Ioc_top
end OrderTop
section OrderBot
@[simp]
theorem Iic_bot [PartialOrder α] [OrderBot α] : Iic (⊥ : α) = {⊥} :=
isMin_bot.Iic_eq
#align set.Iic_bot Set.Iic_bot
variable [Preorder α] [OrderBot α] {a : α}
@[simp]
theorem Iio_bot : Iio (⊥ : α) = ∅ :=
isMin_bot.Iio_eq
#align set.Iio_bot Set.Iio_bot
@[simp]
theorem Ici_bot : Ici (⊥ : α) = univ :=
isBot_bot.Ici_eq
#align set.Ici_bot Set.Ici_bot
@[simp]
theorem Icc_bot : Icc ⊥ a = Iic a := by simp [← Ici_inter_Iic]
#align set.Icc_bot Set.Icc_bot
@[simp]
theorem Ico_bot : Ico ⊥ a = Iio a := by simp [← Ici_inter_Iio]
#align set.Ico_bot Set.Ico_bot
end OrderBot
theorem Icc_bot_top [PartialOrder α] [BoundedOrder α] : Icc (⊥ : α) ⊤ = univ := by simp
#align set.Icc_bot_top Set.Icc_bot_top
section LinearOrder
variable [LinearOrder α] {a a₁ a₂ b b₁ b₂ c d : α}
theorem not_mem_Ici : c ∉ Ici a ↔ c < a :=
not_le
#align set.not_mem_Ici Set.not_mem_Ici
theorem not_mem_Iic : c ∉ Iic b ↔ b < c :=
not_le
#align set.not_mem_Iic Set.not_mem_Iic
theorem not_mem_Ioi : c ∉ Ioi a ↔ c ≤ a :=
not_lt
#align set.not_mem_Ioi Set.not_mem_Ioi
theorem not_mem_Iio : c ∉ Iio b ↔ b ≤ c :=
not_lt
#align set.not_mem_Iio Set.not_mem_Iio
@[simp]
theorem compl_Iic : (Iic a)ᶜ = Ioi a :=
ext fun _ => not_le
#align set.compl_Iic Set.compl_Iic
@[simp]
theorem compl_Ici : (Ici a)ᶜ = Iio a :=
ext fun _ => not_le
#align set.compl_Ici Set.compl_Ici
@[simp]
theorem compl_Iio : (Iio a)ᶜ = Ici a :=
ext fun _ => not_lt
#align set.compl_Iio Set.compl_Iio
@[simp]
theorem compl_Ioi : (Ioi a)ᶜ = Iic a :=
ext fun _ => not_lt
#align set.compl_Ioi Set.compl_Ioi
@[simp]
theorem Ici_diff_Ici : Ici a \ Ici b = Ico a b := by rw [diff_eq, compl_Ici, Ici_inter_Iio]
#align set.Ici_diff_Ici Set.Ici_diff_Ici
@[simp]
theorem Ici_diff_Ioi : Ici a \ Ioi b = Icc a b := by rw [diff_eq, compl_Ioi, Ici_inter_Iic]
#align set.Ici_diff_Ioi Set.Ici_diff_Ioi
@[simp]
theorem Ioi_diff_Ioi : Ioi a \ Ioi b = Ioc a b := by rw [diff_eq, compl_Ioi, Ioi_inter_Iic]
#align set.Ioi_diff_Ioi Set.Ioi_diff_Ioi
@[simp]
theorem Ioi_diff_Ici : Ioi a \ Ici b = Ioo a b := by rw [diff_eq, compl_Ici, Ioi_inter_Iio]
#align set.Ioi_diff_Ici Set.Ioi_diff_Ici
@[simp]
theorem Iic_diff_Iic : Iic b \ Iic a = Ioc a b := by
rw [diff_eq, compl_Iic, inter_comm, Ioi_inter_Iic]
#align set.Iic_diff_Iic Set.Iic_diff_Iic
@[simp]
theorem Iio_diff_Iic : Iio b \ Iic a = Ioo a b := by
rw [diff_eq, compl_Iic, inter_comm, Ioi_inter_Iio]
#align set.Iio_diff_Iic Set.Iio_diff_Iic
@[simp]
theorem Iic_diff_Iio : Iic b \ Iio a = Icc a b := by
rw [diff_eq, compl_Iio, inter_comm, Ici_inter_Iic]
#align set.Iic_diff_Iio Set.Iic_diff_Iio
@[simp]
theorem Iio_diff_Iio : Iio b \ Iio a = Ico a b := by
rw [diff_eq, compl_Iio, inter_comm, Ici_inter_Iio]
#align set.Iio_diff_Iio Set.Iio_diff_Iio
theorem Ioi_injective : Injective (Ioi : α → Set α) := fun _ _ =>
eq_of_forall_gt_iff ∘ Set.ext_iff.1
#align set.Ioi_injective Set.Ioi_injective
theorem Iio_injective : Injective (Iio : α → Set α) := fun _ _ =>
eq_of_forall_lt_iff ∘ Set.ext_iff.1
#align set.Iio_injective Set.Iio_injective
theorem Ioi_inj : Ioi a = Ioi b ↔ a = b :=
Ioi_injective.eq_iff
#align set.Ioi_inj Set.Ioi_inj
theorem Iio_inj : Iio a = Iio b ↔ a = b :=
Iio_injective.eq_iff
#align set.Iio_inj Set.Iio_inj
theorem Ico_subset_Ico_iff (h₁ : a₁ < b₁) : Ico a₁ b₁ ⊆ Ico a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ :=
⟨fun h =>
have : a₂ ≤ a₁ ∧ a₁ < b₂ := h ⟨le_rfl, h₁⟩
⟨this.1, le_of_not_lt fun h' => lt_irrefl b₂ (h ⟨this.2.le, h'⟩).2⟩,
fun ⟨h₁, h₂⟩ => Ico_subset_Ico h₁ h₂⟩
#align set.Ico_subset_Ico_iff Set.Ico_subset_Ico_iff
theorem Ioc_subset_Ioc_iff (h₁ : a₁ < b₁) : Ioc a₁ b₁ ⊆ Ioc a₂ b₂ ↔ b₁ ≤ b₂ ∧ a₂ ≤ a₁ := by
convert @Ico_subset_Ico_iff αᵒᵈ _ b₁ b₂ a₁ a₂ h₁ using 2 <;> exact (@dual_Ico α _ _ _).symm
#align set.Ioc_subset_Ioc_iff Set.Ioc_subset_Ioc_iff
theorem Ioo_subset_Ioo_iff [DenselyOrdered α] (h₁ : a₁ < b₁) :
Ioo a₁ b₁ ⊆ Ioo a₂ b₂ ↔ a₂ ≤ a₁ ∧ b₁ ≤ b₂ :=
⟨fun h => by
rcases exists_between h₁ with ⟨x, xa, xb⟩
constructor <;> refine le_of_not_lt fun h' => ?_
· have ab := (h ⟨xa, xb⟩).1.trans xb
exact lt_irrefl _ (h ⟨h', ab⟩).1
· have ab := xa.trans (h ⟨xa, xb⟩).2
exact lt_irrefl _ (h ⟨ab, h'⟩).2,
fun ⟨h₁, h₂⟩ => Ioo_subset_Ioo h₁ h₂⟩
#align set.Ioo_subset_Ioo_iff Set.Ioo_subset_Ioo_iff
theorem Ico_eq_Ico_iff (h : a₁ < b₁ ∨ a₂ < b₂) : Ico a₁ b₁ = Ico a₂ b₂ ↔ a₁ = a₂ ∧ b₁ = b₂ :=
⟨fun e => by
simp only [Subset.antisymm_iff] at e
simp only [le_antisymm_iff]
cases' h with h h <;>
simp only [gt_iff_lt, not_lt, ge_iff_le, Ico_subset_Ico_iff h] at e <;>
[ rcases e with ⟨⟨h₁, h₂⟩, e'⟩; rcases e with ⟨e', ⟨h₁, h₂⟩⟩ ] <;>
-- Porting note: restore `tauto`
have hab := (Ico_subset_Ico_iff <| h₁.trans_lt <| h.trans_le h₂).1 e' <;>
[ exact ⟨⟨hab.left, h₁⟩, ⟨h₂, hab.right⟩⟩; exact ⟨⟨h₁, hab.left⟩, ⟨hab.right, h₂⟩⟩ ],
fun ⟨h₁, h₂⟩ => by rw [h₁, h₂]⟩
#align set.Ico_eq_Ico_iff Set.Ico_eq_Ico_iff
lemma Ici_eq_singleton_iff_isTop {x : α} : (Ici x = {x}) ↔ IsTop x := by
refine ⟨fun h y ↦ ?_, fun h ↦ by ext y; simp [(h y).ge_iff_eq]⟩
by_contra! H
have : y ∈ Ici x := H.le
rw [h, mem_singleton_iff] at this
exact lt_irrefl y (this.le.trans_lt H)
open scoped Classical
@[simp]
theorem Ioi_subset_Ioi_iff : Ioi b ⊆ Ioi a ↔ a ≤ b := by
refine ⟨fun h => ?_, fun h => Ioi_subset_Ioi h⟩
by_contra ba
exact lt_irrefl _ (h (not_le.mp ba))
#align set.Ioi_subset_Ioi_iff Set.Ioi_subset_Ioi_iff
@[simp]
theorem Ioi_subset_Ici_iff [DenselyOrdered α] : Ioi b ⊆ Ici a ↔ a ≤ b := by
refine ⟨fun h => ?_, fun h => Ioi_subset_Ici h⟩
by_contra ba
obtain ⟨c, bc, ca⟩ : ∃ c, b < c ∧ c < a := exists_between (not_le.mp ba)
exact lt_irrefl _ (ca.trans_le (h bc))
#align set.Ioi_subset_Ici_iff Set.Ioi_subset_Ici_iff
@[simp]
theorem Iio_subset_Iio_iff : Iio a ⊆ Iio b ↔ a ≤ b := by
refine ⟨fun h => ?_, fun h => Iio_subset_Iio h⟩
by_contra ab
exact lt_irrefl _ (h (not_le.mp ab))
#align set.Iio_subset_Iio_iff Set.Iio_subset_Iio_iff
@[simp]
theorem Iio_subset_Iic_iff [DenselyOrdered α] : Iio a ⊆ Iic b ↔ a ≤ b := by
rw [← diff_eq_empty, Iio_diff_Iic, Ioo_eq_empty_iff, not_lt]
#align set.Iio_subset_Iic_iff Set.Iio_subset_Iic_iff
/-! ### Unions of adjacent intervals -/
/-! #### Two infinite intervals -/
theorem Iic_union_Ioi_of_le (h : a ≤ b) : Iic b ∪ Ioi a = univ :=
eq_univ_of_forall fun x => (h.lt_or_le x).symm
#align set.Iic_union_Ioi_of_le Set.Iic_union_Ioi_of_le
theorem Iio_union_Ici_of_le (h : a ≤ b) : Iio b ∪ Ici a = univ :=
eq_univ_of_forall fun x => (h.le_or_lt x).symm
#align set.Iio_union_Ici_of_le Set.Iio_union_Ici_of_le
theorem Iic_union_Ici_of_le (h : a ≤ b) : Iic b ∪ Ici a = univ :=
eq_univ_of_forall fun x => (h.le_or_le x).symm
#align set.Iic_union_Ici_of_le Set.Iic_union_Ici_of_le
theorem Iio_union_Ioi_of_lt (h : a < b) : Iio b ∪ Ioi a = univ :=
eq_univ_of_forall fun x => (h.lt_or_lt x).symm
#align set.Iio_union_Ioi_of_lt Set.Iio_union_Ioi_of_lt
@[simp]
theorem Iic_union_Ici : Iic a ∪ Ici a = univ :=
Iic_union_Ici_of_le le_rfl
#align set.Iic_union_Ici Set.Iic_union_Ici
@[simp]
theorem Iio_union_Ici : Iio a ∪ Ici a = univ :=
Iio_union_Ici_of_le le_rfl
#align set.Iio_union_Ici Set.Iio_union_Ici
@[simp]
theorem Iic_union_Ioi : Iic a ∪ Ioi a = univ :=
Iic_union_Ioi_of_le le_rfl
#align set.Iic_union_Ioi Set.Iic_union_Ioi
@[simp]
theorem Iio_union_Ioi : Iio a ∪ Ioi a = {a}ᶜ :=
ext fun _ => lt_or_lt_iff_ne
#align set.Iio_union_Ioi Set.Iio_union_Ioi
/-! #### A finite and an infinite interval -/
theorem Ioo_union_Ioi' (h₁ : c < b) : Ioo a b ∪ Ioi c = Ioi (min a c) := by
ext1 x
simp_rw [mem_union, mem_Ioo, mem_Ioi, min_lt_iff]
by_cases hc : c < x
· simp only [hc, or_true] -- Porting note: restore `tauto`
· have hxb : x < b := (le_of_not_gt hc).trans_lt h₁
simp only [hxb, and_true] -- Porting note: restore `tauto`
#align set.Ioo_union_Ioi' Set.Ioo_union_Ioi'
theorem Ioo_union_Ioi (h : c < max a b) : Ioo a b ∪ Ioi c = Ioi (min a c) := by
rcases le_total a b with hab | hab <;> simp [hab] at h
· exact Ioo_union_Ioi' h
· rw [min_comm]
simp [*, min_eq_left_of_lt]
#align set.Ioo_union_Ioi Set.Ioo_union_Ioi
theorem Ioi_subset_Ioo_union_Ici : Ioi a ⊆ Ioo a b ∪ Ici b := fun x hx =>
(lt_or_le x b).elim (fun hxb => Or.inl ⟨hx, hxb⟩) fun hxb => Or.inr hxb
#align set.Ioi_subset_Ioo_union_Ici Set.Ioi_subset_Ioo_union_Ici
@[simp]
theorem Ioo_union_Ici_eq_Ioi (h : a < b) : Ioo a b ∪ Ici b = Ioi a :=
Subset.antisymm (fun _ hx => hx.elim And.left h.trans_le) Ioi_subset_Ioo_union_Ici
#align set.Ioo_union_Ici_eq_Ioi Set.Ioo_union_Ici_eq_Ioi
theorem Ici_subset_Ico_union_Ici : Ici a ⊆ Ico a b ∪ Ici b := fun x hx =>
(lt_or_le x b).elim (fun hxb => Or.inl ⟨hx, hxb⟩) fun hxb => Or.inr hxb
#align set.Ici_subset_Ico_union_Ici Set.Ici_subset_Ico_union_Ici
@[simp]
theorem Ico_union_Ici_eq_Ici (h : a ≤ b) : Ico a b ∪ Ici b = Ici a :=
Subset.antisymm (fun _ hx => hx.elim And.left h.trans) Ici_subset_Ico_union_Ici
#align set.Ico_union_Ici_eq_Ici Set.Ico_union_Ici_eq_Ici
theorem Ico_union_Ici' (h₁ : c ≤ b) : Ico a b ∪ Ici c = Ici (min a c) := by
ext1 x
simp_rw [mem_union, mem_Ico, mem_Ici, min_le_iff]
by_cases hc : c ≤ x
· simp only [hc, or_true] -- Porting note: restore `tauto`
· have hxb : x < b := (lt_of_not_ge hc).trans_le h₁
simp only [hxb, and_true] -- Porting note: restore `tauto`
#align set.Ico_union_Ici' Set.Ico_union_Ici'
theorem Ico_union_Ici (h : c ≤ max a b) : Ico a b ∪ Ici c = Ici (min a c) := by
rcases le_total a b with hab | hab <;> simp [hab] at h
· exact Ico_union_Ici' h
· simp [*]
#align set.Ico_union_Ici Set.Ico_union_Ici
theorem Ioi_subset_Ioc_union_Ioi : Ioi a ⊆ Ioc a b ∪ Ioi b := fun x hx =>
(le_or_lt x b).elim (fun hxb => Or.inl ⟨hx, hxb⟩) fun hxb => Or.inr hxb
#align set.Ioi_subset_Ioc_union_Ioi Set.Ioi_subset_Ioc_union_Ioi
@[simp]
theorem Ioc_union_Ioi_eq_Ioi (h : a ≤ b) : Ioc a b ∪ Ioi b = Ioi a :=
Subset.antisymm (fun _ hx => hx.elim And.left h.trans_lt) Ioi_subset_Ioc_union_Ioi
#align set.Ioc_union_Ioi_eq_Ioi Set.Ioc_union_Ioi_eq_Ioi
theorem Ioc_union_Ioi' (h₁ : c ≤ b) : Ioc a b ∪ Ioi c = Ioi (min a c) := by
ext1 x
simp_rw [mem_union, mem_Ioc, mem_Ioi, min_lt_iff]
by_cases hc : c < x
· simp only [hc, or_true] -- Porting note: restore `tauto`
· have hxb : x ≤ b := (le_of_not_gt hc).trans h₁
simp only [hxb, and_true] -- Porting note: restore `tauto`
#align set.Ioc_union_Ioi' Set.Ioc_union_Ioi'
theorem Ioc_union_Ioi (h : c ≤ max a b) : Ioc a b ∪ Ioi c = Ioi (min a c) := by
rcases le_total a b with hab | hab <;> simp [hab] at h
· exact Ioc_union_Ioi' h
· simp [*]
#align set.Ioc_union_Ioi Set.Ioc_union_Ioi
theorem Ici_subset_Icc_union_Ioi : Ici a ⊆ Icc a b ∪ Ioi b := fun x hx =>
(le_or_lt x b).elim (fun hxb => Or.inl ⟨hx, hxb⟩) fun hxb => Or.inr hxb
#align set.Ici_subset_Icc_union_Ioi Set.Ici_subset_Icc_union_Ioi
@[simp]
theorem Icc_union_Ioi_eq_Ici (h : a ≤ b) : Icc a b ∪ Ioi b = Ici a :=
Subset.antisymm (fun _ hx => (hx.elim And.left) fun hx' => h.trans <| le_of_lt hx')
Ici_subset_Icc_union_Ioi
#align set.Icc_union_Ioi_eq_Ici Set.Icc_union_Ioi_eq_Ici
theorem Ioi_subset_Ioc_union_Ici : Ioi a ⊆ Ioc a b ∪ Ici b :=
Subset.trans Ioi_subset_Ioo_union_Ici (union_subset_union_left _ Ioo_subset_Ioc_self)
#align set.Ioi_subset_Ioc_union_Ici Set.Ioi_subset_Ioc_union_Ici
@[simp]
theorem Ioc_union_Ici_eq_Ioi (h : a < b) : Ioc a b ∪ Ici b = Ioi a :=
Subset.antisymm (fun _ hx => hx.elim And.left h.trans_le) Ioi_subset_Ioc_union_Ici
#align set.Ioc_union_Ici_eq_Ioi Set.Ioc_union_Ici_eq_Ioi
theorem Ici_subset_Icc_union_Ici : Ici a ⊆ Icc a b ∪ Ici b :=
Subset.trans Ici_subset_Ico_union_Ici (union_subset_union_left _ Ico_subset_Icc_self)
#align set.Ici_subset_Icc_union_Ici Set.Ici_subset_Icc_union_Ici
@[simp]
theorem Icc_union_Ici_eq_Ici (h : a ≤ b) : Icc a b ∪ Ici b = Ici a :=
Subset.antisymm (fun _ hx => hx.elim And.left h.trans) Ici_subset_Icc_union_Ici
#align set.Icc_union_Ici_eq_Ici Set.Icc_union_Ici_eq_Ici
theorem Icc_union_Ici' (h₁ : c ≤ b) : Icc a b ∪ Ici c = Ici (min a c) := by
ext1 x
simp_rw [mem_union, mem_Icc, mem_Ici, min_le_iff]
by_cases hc : c ≤ x
· simp only [hc, or_true] -- Porting note: restore `tauto`
· have hxb : x ≤ b := (le_of_not_ge hc).trans h₁
simp only [hxb, and_true] -- Porting note: restore `tauto`
#align set.Icc_union_Ici' Set.Icc_union_Ici'
theorem Icc_union_Ici (h : c ≤ max a b) : Icc a b ∪ Ici c = Ici (min a c) := by
rcases le_or_lt a b with hab | hab <;> simp [hab] at h
· exact Icc_union_Ici' h
· cases' h with h h
· simp [*]
· have hca : c ≤ a := h.trans hab.le
simp [*]
#align set.Icc_union_Ici Set.Icc_union_Ici
/-! #### An infinite and a finite interval -/
theorem Iic_subset_Iio_union_Icc : Iic b ⊆ Iio a ∪ Icc a b := fun x hx =>
(lt_or_le x a).elim (fun hxa => Or.inl hxa) fun hxa => Or.inr ⟨hxa, hx⟩
#align set.Iic_subset_Iio_union_Icc Set.Iic_subset_Iio_union_Icc
@[simp]
theorem Iio_union_Icc_eq_Iic (h : a ≤ b) : Iio a ∪ Icc a b = Iic b :=
Subset.antisymm (fun _ hx => hx.elim (fun hx => (le_of_lt hx).trans h) And.right)
Iic_subset_Iio_union_Icc
#align set.Iio_union_Icc_eq_Iic Set.Iio_union_Icc_eq_Iic
theorem Iio_subset_Iio_union_Ico : Iio b ⊆ Iio a ∪ Ico a b := fun x hx =>
(lt_or_le x a).elim (fun hxa => Or.inl hxa) fun hxa => Or.inr ⟨hxa, hx⟩
#align set.Iio_subset_Iio_union_Ico Set.Iio_subset_Iio_union_Ico
@[simp]
theorem Iio_union_Ico_eq_Iio (h : a ≤ b) : Iio a ∪ Ico a b = Iio b :=
Subset.antisymm (fun _ hx => hx.elim (fun hx' => lt_of_lt_of_le hx' h) And.right)
Iio_subset_Iio_union_Ico
#align set.Iio_union_Ico_eq_Iio Set.Iio_union_Ico_eq_Iio
theorem Iio_union_Ico' (h₁ : c ≤ b) : Iio b ∪ Ico c d = Iio (max b d) := by
ext1 x
simp_rw [mem_union, mem_Iio, mem_Ico, lt_max_iff]
by_cases hc : c ≤ x
· simp only [hc, true_and] -- Porting note: restore `tauto`
· have hxb : x < b := (lt_of_not_ge hc).trans_le h₁
simp only [hxb, true_or] -- Porting note: restore `tauto`
#align set.Iio_union_Ico' Set.Iio_union_Ico'
theorem Iio_union_Ico (h : min c d ≤ b) : Iio b ∪ Ico c d = Iio (max b d) := by
rcases le_total c d with hcd | hcd <;> simp [hcd] at h
· exact Iio_union_Ico' h
· simp [*]
#align set.Iio_union_Ico Set.Iio_union_Ico
theorem Iic_subset_Iic_union_Ioc : Iic b ⊆ Iic a ∪ Ioc a b := fun x hx =>
(le_or_lt x a).elim (fun hxa => Or.inl hxa) fun hxa => Or.inr ⟨hxa, hx⟩
#align set.Iic_subset_Iic_union_Ioc Set.Iic_subset_Iic_union_Ioc
@[simp]
theorem Iic_union_Ioc_eq_Iic (h : a ≤ b) : Iic a ∪ Ioc a b = Iic b :=
Subset.antisymm (fun _ hx => hx.elim (fun hx' => le_trans hx' h) And.right)
Iic_subset_Iic_union_Ioc
#align set.Iic_union_Ioc_eq_Iic Set.Iic_union_Ioc_eq_Iic
theorem Iic_union_Ioc' (h₁ : c < b) : Iic b ∪ Ioc c d = Iic (max b d) := by
ext1 x
simp_rw [mem_union, mem_Iic, mem_Ioc, le_max_iff]
by_cases hc : c < x
· simp only [hc, true_and] -- Porting note: restore `tauto`
· have hxb : x ≤ b := (le_of_not_gt hc).trans h₁.le
simp only [hxb, true_or] -- Porting note: restore `tauto`
#align set.Iic_union_Ioc' Set.Iic_union_Ioc'
theorem Iic_union_Ioc (h : min c d < b) : Iic b ∪ Ioc c d = Iic (max b d) := by
rcases le_total c d with hcd | hcd <;> simp [hcd] at h
· exact Iic_union_Ioc' h
· rw [max_comm]
simp [*, max_eq_right_of_lt h]
#align set.Iic_union_Ioc Set.Iic_union_Ioc
theorem Iio_subset_Iic_union_Ioo : Iio b ⊆ Iic a ∪ Ioo a b := fun x hx =>
(le_or_lt x a).elim (fun hxa => Or.inl hxa) fun hxa => Or.inr ⟨hxa, hx⟩
#align set.Iio_subset_Iic_union_Ioo Set.Iio_subset_Iic_union_Ioo
@[simp]
theorem Iic_union_Ioo_eq_Iio (h : a < b) : Iic a ∪ Ioo a b = Iio b :=
Subset.antisymm (fun _ hx => hx.elim (fun hx' => lt_of_le_of_lt hx' h) And.right)
Iio_subset_Iic_union_Ioo
#align set.Iic_union_Ioo_eq_Iio Set.Iic_union_Ioo_eq_Iio
theorem Iio_union_Ioo' (h₁ : c < b) : Iio b ∪ Ioo c d = Iio (max b d) := by
ext x
cases' lt_or_le x b with hba hba
· simp [hba, h₁]
· simp only [mem_Iio, mem_union, mem_Ioo, lt_max_iff]
refine or_congr Iff.rfl ⟨And.right, ?_⟩
exact fun h₂ => ⟨h₁.trans_le hba, h₂⟩
#align set.Iio_union_Ioo' Set.Iio_union_Ioo'
| Mathlib/Order/Interval/Set/Basic.lean | 1,486 | 1,490 | theorem Iio_union_Ioo (h : min c d < b) : Iio b ∪ Ioo c d = Iio (max b d) := by |
rcases le_total c d with hcd | hcd <;> simp [hcd] at h
· exact Iio_union_Ioo' h
· rw [max_comm]
simp [*, max_eq_right_of_lt h]
|
/-
Copyright (c) 2021 Stuart Presnell. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Stuart Presnell
-/
import Mathlib.Data.Finsupp.Multiset
import Mathlib.Data.Nat.GCD.BigOperators
import Mathlib.Data.Nat.PrimeFin
import Mathlib.NumberTheory.Padics.PadicVal
import Mathlib.Order.Interval.Finset.Nat
#align_import data.nat.factorization.basic from "leanprover-community/mathlib"@"f694c7dead66f5d4c80f446c796a5aad14707f0e"
/-!
# Prime factorizations
`n.factorization` is the finitely supported function `ℕ →₀ ℕ`
mapping each prime factor of `n` to its multiplicity in `n`. For example, since 2000 = 2^4 * 5^3,
* `factorization 2000 2` is 4
* `factorization 2000 5` is 3
* `factorization 2000 k` is 0 for all other `k : ℕ`.
## TODO
* As discussed in this Zulip thread:
https://leanprover.zulipchat.com/#narrow/stream/217875/topic/Multiplicity.20in.20the.20naturals
We have lots of disparate ways of talking about the multiplicity of a prime
in a natural number, including `factors.count`, `padicValNat`, `multiplicity`,
and the material in `Data/PNat/Factors`. Move some of this material to this file,
prove results about the relationships between these definitions,
and (where appropriate) choose a uniform canonical way of expressing these ideas.
* Moreover, the results here should be generalised to an arbitrary unique factorization monoid
with a normalization function, and then deduplicated. The basics of this have been started in
`RingTheory/UniqueFactorizationDomain`.
* Extend the inductions to any `NormalizationMonoid` with unique factorization.
-/
-- Workaround for lean4#2038
attribute [-instance] instBEqNat
open Nat Finset List Finsupp
namespace Nat
variable {a b m n p : ℕ}
/-- `n.factorization` is the finitely supported function `ℕ →₀ ℕ`
mapping each prime factor of `n` to its multiplicity in `n`. -/
def factorization (n : ℕ) : ℕ →₀ ℕ where
support := n.primeFactors
toFun p := if p.Prime then padicValNat p n else 0
mem_support_toFun := by simp [not_or]; aesop
#align nat.factorization Nat.factorization
/-- The support of `n.factorization` is exactly `n.primeFactors`. -/
@[simp] lemma support_factorization (n : ℕ) : (factorization n).support = n.primeFactors := rfl
theorem factorization_def (n : ℕ) {p : ℕ} (pp : p.Prime) : n.factorization p = padicValNat p n := by
simpa [factorization] using absurd pp
#align nat.factorization_def Nat.factorization_def
/-- We can write both `n.factorization p` and `n.factors.count p` to represent the power
of `p` in the factorization of `n`: we declare the former to be the simp-normal form. -/
@[simp]
theorem factors_count_eq {n p : ℕ} : n.factors.count p = n.factorization p := by
rcases n.eq_zero_or_pos with (rfl | hn0)
· simp [factorization, count]
if pp : p.Prime then ?_ else
rw [count_eq_zero_of_not_mem (mt prime_of_mem_factors pp)]
simp [factorization, pp]
simp only [factorization_def _ pp]
apply _root_.le_antisymm
· rw [le_padicValNat_iff_replicate_subperm_factors pp hn0.ne']
exact List.le_count_iff_replicate_sublist.mp le_rfl |>.subperm
· rw [← lt_add_one_iff, lt_iff_not_ge, ge_iff_le,
le_padicValNat_iff_replicate_subperm_factors pp hn0.ne']
intro h
have := h.count_le p
simp at this
#align nat.factors_count_eq Nat.factors_count_eq
theorem factorization_eq_factors_multiset (n : ℕ) :
n.factorization = Multiset.toFinsupp (n.factors : Multiset ℕ) := by
ext p
simp
#align nat.factorization_eq_factors_multiset Nat.factorization_eq_factors_multiset
theorem multiplicity_eq_factorization {n p : ℕ} (pp : p.Prime) (hn : n ≠ 0) :
multiplicity p n = n.factorization p := by
simp [factorization, pp, padicValNat_def' pp.ne_one hn.bot_lt]
#align nat.multiplicity_eq_factorization Nat.multiplicity_eq_factorization
/-! ### Basic facts about factorization -/
@[simp]
theorem factorization_prod_pow_eq_self {n : ℕ} (hn : n ≠ 0) : n.factorization.prod (· ^ ·) = n := by
rw [factorization_eq_factors_multiset n]
simp only [← prod_toMultiset, factorization, Multiset.prod_coe, Multiset.toFinsupp_toMultiset]
exact prod_factors hn
#align nat.factorization_prod_pow_eq_self Nat.factorization_prod_pow_eq_self
theorem eq_of_factorization_eq {a b : ℕ} (ha : a ≠ 0) (hb : b ≠ 0)
(h : ∀ p : ℕ, a.factorization p = b.factorization p) : a = b :=
eq_of_perm_factors ha hb (by simpa only [List.perm_iff_count, factors_count_eq] using h)
#align nat.eq_of_factorization_eq Nat.eq_of_factorization_eq
/-- Every nonzero natural number has a unique prime factorization -/
theorem factorization_inj : Set.InjOn factorization { x : ℕ | x ≠ 0 } := fun a ha b hb h =>
eq_of_factorization_eq ha hb fun p => by simp [h]
#align nat.factorization_inj Nat.factorization_inj
@[simp]
theorem factorization_zero : factorization 0 = 0 := by ext; simp [factorization]
#align nat.factorization_zero Nat.factorization_zero
@[simp]
theorem factorization_one : factorization 1 = 0 := by ext; simp [factorization]
#align nat.factorization_one Nat.factorization_one
#noalign nat.support_factorization
#align nat.factor_iff_mem_factorization Nat.mem_primeFactors_iff_mem_factors
#align nat.prime_of_mem_factorization Nat.prime_of_mem_primeFactors
#align nat.pos_of_mem_factorization Nat.pos_of_mem_primeFactors
#align nat.le_of_mem_factorization Nat.le_of_mem_primeFactors
/-! ## Lemmas characterising when `n.factorization p = 0` -/
theorem factorization_eq_zero_iff (n p : ℕ) :
n.factorization p = 0 ↔ ¬p.Prime ∨ ¬p ∣ n ∨ n = 0 := by
simp_rw [← not_mem_support_iff, support_factorization, mem_primeFactors, not_and_or, not_ne_iff]
#align nat.factorization_eq_zero_iff Nat.factorization_eq_zero_iff
@[simp]
theorem factorization_eq_zero_of_non_prime (n : ℕ) {p : ℕ} (hp : ¬p.Prime) :
n.factorization p = 0 := by simp [factorization_eq_zero_iff, hp]
#align nat.factorization_eq_zero_of_non_prime Nat.factorization_eq_zero_of_non_prime
theorem factorization_eq_zero_of_not_dvd {n p : ℕ} (h : ¬p ∣ n) : n.factorization p = 0 := by
simp [factorization_eq_zero_iff, h]
#align nat.factorization_eq_zero_of_not_dvd Nat.factorization_eq_zero_of_not_dvd
theorem factorization_eq_zero_of_lt {n p : ℕ} (h : n < p) : n.factorization p = 0 :=
Finsupp.not_mem_support_iff.mp (mt le_of_mem_primeFactors (not_le_of_lt h))
#align nat.factorization_eq_zero_of_lt Nat.factorization_eq_zero_of_lt
@[simp]
theorem factorization_zero_right (n : ℕ) : n.factorization 0 = 0 :=
factorization_eq_zero_of_non_prime _ not_prime_zero
#align nat.factorization_zero_right Nat.factorization_zero_right
@[simp]
theorem factorization_one_right (n : ℕ) : n.factorization 1 = 0 :=
factorization_eq_zero_of_non_prime _ not_prime_one
#align nat.factorization_one_right Nat.factorization_one_right
theorem dvd_of_factorization_pos {n p : ℕ} (hn : n.factorization p ≠ 0) : p ∣ n :=
dvd_of_mem_factors <| mem_primeFactors_iff_mem_factors.1 <| mem_support_iff.2 hn
#align nat.dvd_of_factorization_pos Nat.dvd_of_factorization_pos
theorem Prime.factorization_pos_of_dvd {n p : ℕ} (hp : p.Prime) (hn : n ≠ 0) (h : p ∣ n) :
0 < n.factorization p := by
rwa [← factors_count_eq, count_pos_iff_mem, mem_factors_iff_dvd hn hp]
#align nat.prime.factorization_pos_of_dvd Nat.Prime.factorization_pos_of_dvd
theorem factorization_eq_zero_of_remainder {p r : ℕ} (i : ℕ) (hr : ¬p ∣ r) :
(p * i + r).factorization p = 0 := by
apply factorization_eq_zero_of_not_dvd
rwa [← Nat.dvd_add_iff_right (Dvd.intro i rfl)]
#align nat.factorization_eq_zero_of_remainder Nat.factorization_eq_zero_of_remainder
theorem factorization_eq_zero_iff_remainder {p r : ℕ} (i : ℕ) (pp : p.Prime) (hr0 : r ≠ 0) :
¬p ∣ r ↔ (p * i + r).factorization p = 0 := by
refine ⟨factorization_eq_zero_of_remainder i, fun h => ?_⟩
rw [factorization_eq_zero_iff] at h
contrapose! h
refine ⟨pp, ?_, ?_⟩
· rwa [← Nat.dvd_add_iff_right (dvd_mul_right p i)]
· contrapose! hr0
exact (add_eq_zero_iff.mp hr0).2
#align nat.factorization_eq_zero_iff_remainder Nat.factorization_eq_zero_iff_remainder
/-- The only numbers with empty prime factorization are `0` and `1` -/
theorem factorization_eq_zero_iff' (n : ℕ) : n.factorization = 0 ↔ n = 0 ∨ n = 1 := by
rw [factorization_eq_factors_multiset n]
simp [factorization, AddEquiv.map_eq_zero_iff, Multiset.coe_eq_zero]
#align nat.factorization_eq_zero_iff' Nat.factorization_eq_zero_iff'
/-! ## Lemmas about factorizations of products and powers -/
/-- For nonzero `a` and `b`, the power of `p` in `a * b` is the sum of the powers in `a` and `b` -/
@[simp]
theorem factorization_mul {a b : ℕ} (ha : a ≠ 0) (hb : b ≠ 0) :
(a * b).factorization = a.factorization + b.factorization := by
ext p
simp only [add_apply, ← factors_count_eq, perm_iff_count.mp (perm_factors_mul ha hb) p,
count_append]
#align nat.factorization_mul Nat.factorization_mul
#align nat.factorization_mul_support Nat.primeFactors_mul
/-- A product over `n.factorization` can be written as a product over `n.primeFactors`; -/
lemma prod_factorization_eq_prod_primeFactors {β : Type*} [CommMonoid β] (f : ℕ → ℕ → β) :
n.factorization.prod f = ∏ p ∈ n.primeFactors, f p (n.factorization p) := rfl
#align nat.prod_factorization_eq_prod_factors Nat.prod_factorization_eq_prod_primeFactors
/-- A product over `n.primeFactors` can be written as a product over `n.factorization`; -/
lemma prod_primeFactors_prod_factorization {β : Type*} [CommMonoid β] (f : ℕ → β) :
∏ p ∈ n.primeFactors, f p = n.factorization.prod (fun p _ ↦ f p) := rfl
/-- For any `p : ℕ` and any function `g : α → ℕ` that's non-zero on `S : Finset α`,
the power of `p` in `S.prod g` equals the sum over `x ∈ S` of the powers of `p` in `g x`.
Generalises `factorization_mul`, which is the special case where `S.card = 2` and `g = id`. -/
theorem factorization_prod {α : Type*} {S : Finset α} {g : α → ℕ} (hS : ∀ x ∈ S, g x ≠ 0) :
(S.prod g).factorization = S.sum fun x => (g x).factorization := by
classical
ext p
refine Finset.induction_on' S ?_ ?_
· simp
· intro x T hxS hTS hxT IH
have hT : T.prod g ≠ 0 := prod_ne_zero_iff.mpr fun x hx => hS x (hTS hx)
simp [prod_insert hxT, sum_insert hxT, ← IH, factorization_mul (hS x hxS) hT]
#align nat.factorization_prod Nat.factorization_prod
/-- For any `p`, the power of `p` in `n^k` is `k` times the power in `n` -/
@[simp]
theorem factorization_pow (n k : ℕ) : factorization (n ^ k) = k • n.factorization := by
induction' k with k ih; · simp
rcases eq_or_ne n 0 with (rfl | hn)
· simp
rw [Nat.pow_succ, mul_comm, factorization_mul hn (pow_ne_zero _ hn), ih,
add_smul, one_smul, add_comm]
#align nat.factorization_pow Nat.factorization_pow
/-! ## Lemmas about factorizations of primes and prime powers -/
/-- The only prime factor of prime `p` is `p` itself, with multiplicity `1` -/
@[simp]
protected theorem Prime.factorization {p : ℕ} (hp : Prime p) : p.factorization = single p 1 := by
ext q
rw [← factors_count_eq, factors_prime hp, single_apply, count_singleton', if_congr eq_comm] <;>
rfl
#align nat.prime.factorization Nat.Prime.factorization
/-- The multiplicity of prime `p` in `p` is `1` -/
@[simp]
theorem Prime.factorization_self {p : ℕ} (hp : Prime p) : p.factorization p = 1 := by simp [hp]
#align nat.prime.factorization_self Nat.Prime.factorization_self
/-- For prime `p` the only prime factor of `p^k` is `p` with multiplicity `k` -/
theorem Prime.factorization_pow {p k : ℕ} (hp : Prime p) : (p ^ k).factorization = single p k := by
simp [hp]
#align nat.prime.factorization_pow Nat.Prime.factorization_pow
/-- If the factorization of `n` contains just one number `p` then `n` is a power of `p` -/
theorem eq_pow_of_factorization_eq_single {n p k : ℕ} (hn : n ≠ 0)
(h : n.factorization = Finsupp.single p k) : n = p ^ k := by
-- Porting note: explicitly added `Finsupp.prod_single_index`
rw [← Nat.factorization_prod_pow_eq_self hn, h, Finsupp.prod_single_index]
simp
#align nat.eq_pow_of_factorization_eq_single Nat.eq_pow_of_factorization_eq_single
/-- The only prime factor of prime `p` is `p` itself. -/
theorem Prime.eq_of_factorization_pos {p q : ℕ} (hp : Prime p) (h : p.factorization q ≠ 0) :
p = q := by simpa [hp.factorization, single_apply] using h
#align nat.prime.eq_of_factorization_pos Nat.Prime.eq_of_factorization_pos
/-! ### Equivalence between `ℕ+` and `ℕ →₀ ℕ` with support in the primes. -/
/-- Any Finsupp `f : ℕ →₀ ℕ` whose support is in the primes is equal to the factorization of
the product `∏ (a : ℕ) ∈ f.support, a ^ f a`. -/
theorem prod_pow_factorization_eq_self {f : ℕ →₀ ℕ} (hf : ∀ p : ℕ, p ∈ f.support → Prime p) :
(f.prod (· ^ ·)).factorization = f := by
have h : ∀ x : ℕ, x ∈ f.support → x ^ f x ≠ 0 := fun p hp =>
pow_ne_zero _ (Prime.ne_zero (hf p hp))
simp only [Finsupp.prod, factorization_prod h]
conv =>
rhs
rw [(sum_single f).symm]
exact sum_congr rfl fun p hp => Prime.factorization_pow (hf p hp)
#align nat.prod_pow_factorization_eq_self Nat.prod_pow_factorization_eq_self
theorem eq_factorization_iff {n : ℕ} {f : ℕ →₀ ℕ} (hn : n ≠ 0) (hf : ∀ p ∈ f.support, Prime p) :
f = n.factorization ↔ f.prod (· ^ ·) = n :=
⟨fun h => by rw [h, factorization_prod_pow_eq_self hn], fun h => by
rw [← h, prod_pow_factorization_eq_self hf]⟩
#align nat.eq_factorization_iff Nat.eq_factorization_iff
/-- The equiv between `ℕ+` and `ℕ →₀ ℕ` with support in the primes. -/
def factorizationEquiv : ℕ+ ≃ { f : ℕ →₀ ℕ | ∀ p ∈ f.support, Prime p } where
toFun := fun ⟨n, _⟩ => ⟨n.factorization, fun _ => prime_of_mem_primeFactors⟩
invFun := fun ⟨f, hf⟩ =>
⟨f.prod _, prod_pow_pos_of_zero_not_mem_support fun H => not_prime_zero (hf 0 H)⟩
left_inv := fun ⟨_, hx⟩ => Subtype.ext <| factorization_prod_pow_eq_self hx.ne.symm
right_inv := fun ⟨_, hf⟩ => Subtype.ext <| prod_pow_factorization_eq_self hf
#align nat.factorization_equiv Nat.factorizationEquiv
theorem factorizationEquiv_apply (n : ℕ+) : (factorizationEquiv n).1 = n.1.factorization := by
cases n
rfl
#align nat.factorization_equiv_apply Nat.factorizationEquiv_apply
theorem factorizationEquiv_inv_apply {f : ℕ →₀ ℕ} (hf : ∀ p ∈ f.support, Prime p) :
(factorizationEquiv.symm ⟨f, hf⟩).1 = f.prod (· ^ ·) :=
rfl
#align nat.factorization_equiv_inv_apply Nat.factorizationEquiv_inv_apply
/-! ### Generalisation of the "even part" and "odd part" of a natural number
We introduce the notations `ord_proj[p] n` for the largest power of the prime `p` that
divides `n` and `ord_compl[p] n` for the complementary part. The `ord` naming comes from
the $p$-adic order/valuation of a number, and `proj` and `compl` are for the projection and
complementary projection. The term `n.factorization p` is the $p$-adic order itself.
For example, `ord_proj[2] n` is the even part of `n` and `ord_compl[2] n` is the odd part. -/
-- Porting note: Lean 4 thinks we need `HPow` without this
set_option quotPrecheck false in
notation "ord_proj[" p "] " n:arg => p ^ Nat.factorization n p
notation "ord_compl[" p "] " n:arg => n / ord_proj[p] n
@[simp]
theorem ord_proj_of_not_prime (n p : ℕ) (hp : ¬p.Prime) : ord_proj[p] n = 1 := by
simp [factorization_eq_zero_of_non_prime n hp]
#align nat.ord_proj_of_not_prime Nat.ord_proj_of_not_prime
@[simp]
theorem ord_compl_of_not_prime (n p : ℕ) (hp : ¬p.Prime) : ord_compl[p] n = n := by
simp [factorization_eq_zero_of_non_prime n hp]
#align nat.ord_compl_of_not_prime Nat.ord_compl_of_not_prime
theorem ord_proj_dvd (n p : ℕ) : ord_proj[p] n ∣ n := by
if hp : p.Prime then ?_ else simp [hp]
rw [← factors_count_eq]
apply dvd_of_factors_subperm (pow_ne_zero _ hp.ne_zero)
rw [hp.factors_pow, List.subperm_ext_iff]
intro q hq
simp [List.eq_of_mem_replicate hq]
#align nat.ord_proj_dvd Nat.ord_proj_dvd
theorem ord_compl_dvd (n p : ℕ) : ord_compl[p] n ∣ n :=
div_dvd_of_dvd (ord_proj_dvd n p)
#align nat.ord_compl_dvd Nat.ord_compl_dvd
theorem ord_proj_pos (n p : ℕ) : 0 < ord_proj[p] n := by
if pp : p.Prime then simp [pow_pos pp.pos] else simp [pp]
#align nat.ord_proj_pos Nat.ord_proj_pos
theorem ord_proj_le {n : ℕ} (p : ℕ) (hn : n ≠ 0) : ord_proj[p] n ≤ n :=
le_of_dvd hn.bot_lt (Nat.ord_proj_dvd n p)
#align nat.ord_proj_le Nat.ord_proj_le
theorem ord_compl_pos {n : ℕ} (p : ℕ) (hn : n ≠ 0) : 0 < ord_compl[p] n := by
if pp : p.Prime then
exact Nat.div_pos (ord_proj_le p hn) (ord_proj_pos n p)
else
simpa [Nat.factorization_eq_zero_of_non_prime n pp] using hn.bot_lt
#align nat.ord_compl_pos Nat.ord_compl_pos
theorem ord_compl_le (n p : ℕ) : ord_compl[p] n ≤ n :=
Nat.div_le_self _ _
#align nat.ord_compl_le Nat.ord_compl_le
theorem ord_proj_mul_ord_compl_eq_self (n p : ℕ) : ord_proj[p] n * ord_compl[p] n = n :=
Nat.mul_div_cancel' (ord_proj_dvd n p)
#align nat.ord_proj_mul_ord_compl_eq_self Nat.ord_proj_mul_ord_compl_eq_self
theorem ord_proj_mul {a b : ℕ} (p : ℕ) (ha : a ≠ 0) (hb : b ≠ 0) :
ord_proj[p] (a * b) = ord_proj[p] a * ord_proj[p] b := by
simp [factorization_mul ha hb, pow_add]
#align nat.ord_proj_mul Nat.ord_proj_mul
theorem ord_compl_mul (a b p : ℕ) : ord_compl[p] (a * b) = ord_compl[p] a * ord_compl[p] b := by
if ha : a = 0 then simp [ha] else
if hb : b = 0 then simp [hb] else
simp only [ord_proj_mul p ha hb]
rw [div_mul_div_comm (ord_proj_dvd a p) (ord_proj_dvd b p)]
#align nat.ord_compl_mul Nat.ord_compl_mul
/-! ### Factorization and divisibility -/
#align nat.dvd_of_mem_factorization Nat.dvd_of_mem_primeFactors
/-- A crude upper bound on `n.factorization p` -/
theorem factorization_lt {n : ℕ} (p : ℕ) (hn : n ≠ 0) : n.factorization p < n := by
by_cases pp : p.Prime
· exact (pow_lt_pow_iff_right pp.one_lt).1 <| (ord_proj_le p hn).trans_lt <|
lt_pow_self pp.one_lt _
· simpa only [factorization_eq_zero_of_non_prime n pp] using hn.bot_lt
#align nat.factorization_lt Nat.factorization_lt
/-- An upper bound on `n.factorization p` -/
theorem factorization_le_of_le_pow {n p b : ℕ} (hb : n ≤ p ^ b) : n.factorization p ≤ b := by
if hn : n = 0 then simp [hn] else
if pp : p.Prime then
exact (pow_le_pow_iff_right pp.one_lt).1 ((ord_proj_le p hn).trans hb)
else
simp [factorization_eq_zero_of_non_prime n pp]
#align nat.factorization_le_of_le_pow Nat.factorization_le_of_le_pow
theorem factorization_le_iff_dvd {d n : ℕ} (hd : d ≠ 0) (hn : n ≠ 0) :
d.factorization ≤ n.factorization ↔ d ∣ n := by
constructor
· intro hdn
set K := n.factorization - d.factorization with hK
use K.prod (· ^ ·)
rw [← factorization_prod_pow_eq_self hn, ← factorization_prod_pow_eq_self hd,
← Finsupp.prod_add_index' pow_zero pow_add, hK, add_tsub_cancel_of_le hdn]
· rintro ⟨c, rfl⟩
rw [factorization_mul hd (right_ne_zero_of_mul hn)]
simp
#align nat.factorization_le_iff_dvd Nat.factorization_le_iff_dvd
theorem factorization_prime_le_iff_dvd {d n : ℕ} (hd : d ≠ 0) (hn : n ≠ 0) :
(∀ p : ℕ, p.Prime → d.factorization p ≤ n.factorization p) ↔ d ∣ n := by
rw [← factorization_le_iff_dvd hd hn]
refine ⟨fun h p => (em p.Prime).elim (h p) fun hp => ?_, fun h p _ => h p⟩
simp_rw [factorization_eq_zero_of_non_prime _ hp]
rfl
#align nat.factorization_prime_le_iff_dvd Nat.factorization_prime_le_iff_dvd
theorem pow_succ_factorization_not_dvd {n p : ℕ} (hn : n ≠ 0) (hp : p.Prime) :
¬p ^ (n.factorization p + 1) ∣ n := by
intro h
rw [← factorization_le_iff_dvd (pow_pos hp.pos _).ne' hn] at h
simpa [hp.factorization] using h p
#align nat.pow_succ_factorization_not_dvd Nat.pow_succ_factorization_not_dvd
theorem factorization_le_factorization_mul_left {a b : ℕ} (hb : b ≠ 0) :
a.factorization ≤ (a * b).factorization := by
rcases eq_or_ne a 0 with (rfl | ha)
· simp
rw [factorization_le_iff_dvd ha <| mul_ne_zero ha hb]
exact Dvd.intro b rfl
#align nat.factorization_le_factorization_mul_left Nat.factorization_le_factorization_mul_left
theorem factorization_le_factorization_mul_right {a b : ℕ} (ha : a ≠ 0) :
b.factorization ≤ (a * b).factorization := by
rw [mul_comm]
apply factorization_le_factorization_mul_left ha
#align nat.factorization_le_factorization_mul_right Nat.factorization_le_factorization_mul_right
theorem Prime.pow_dvd_iff_le_factorization {p k n : ℕ} (pp : Prime p) (hn : n ≠ 0) :
p ^ k ∣ n ↔ k ≤ n.factorization p := by
rw [← factorization_le_iff_dvd (pow_pos pp.pos k).ne' hn, pp.factorization_pow, single_le_iff]
#align nat.prime.pow_dvd_iff_le_factorization Nat.Prime.pow_dvd_iff_le_factorization
theorem Prime.pow_dvd_iff_dvd_ord_proj {p k n : ℕ} (pp : Prime p) (hn : n ≠ 0) :
p ^ k ∣ n ↔ p ^ k ∣ ord_proj[p] n := by
rw [pow_dvd_pow_iff_le_right pp.one_lt, pp.pow_dvd_iff_le_factorization hn]
#align nat.prime.pow_dvd_iff_dvd_ord_proj Nat.Prime.pow_dvd_iff_dvd_ord_proj
theorem Prime.dvd_iff_one_le_factorization {p n : ℕ} (pp : Prime p) (hn : n ≠ 0) :
p ∣ n ↔ 1 ≤ n.factorization p :=
Iff.trans (by simp) (pp.pow_dvd_iff_le_factorization hn)
#align nat.prime.dvd_iff_one_le_factorization Nat.Prime.dvd_iff_one_le_factorization
theorem exists_factorization_lt_of_lt {a b : ℕ} (ha : a ≠ 0) (hab : a < b) :
∃ p : ℕ, a.factorization p < b.factorization p := by
have hb : b ≠ 0 := (ha.bot_lt.trans hab).ne'
contrapose! hab
rw [← Finsupp.le_def, factorization_le_iff_dvd hb ha] at hab
exact le_of_dvd ha.bot_lt hab
#align nat.exists_factorization_lt_of_lt Nat.exists_factorization_lt_of_lt
@[simp]
theorem factorization_div {d n : ℕ} (h : d ∣ n) :
(n / d).factorization = n.factorization - d.factorization := by
rcases eq_or_ne d 0 with (rfl | hd); · simp [zero_dvd_iff.mp h]
rcases eq_or_ne n 0 with (rfl | hn); · simp
apply add_left_injective d.factorization
simp only
rw [tsub_add_cancel_of_le <| (Nat.factorization_le_iff_dvd hd hn).mpr h, ←
Nat.factorization_mul (Nat.div_pos (Nat.le_of_dvd hn.bot_lt h) hd.bot_lt).ne' hd,
Nat.div_mul_cancel h]
#align nat.factorization_div Nat.factorization_div
theorem dvd_ord_proj_of_dvd {n p : ℕ} (hn : n ≠ 0) (pp : p.Prime) (h : p ∣ n) : p ∣ ord_proj[p] n :=
dvd_pow_self p (Prime.factorization_pos_of_dvd pp hn h).ne'
#align nat.dvd_ord_proj_of_dvd Nat.dvd_ord_proj_of_dvd
theorem not_dvd_ord_compl {n p : ℕ} (hp : Prime p) (hn : n ≠ 0) : ¬p ∣ ord_compl[p] n := by
rw [Nat.Prime.dvd_iff_one_le_factorization hp (ord_compl_pos p hn).ne']
rw [Nat.factorization_div (Nat.ord_proj_dvd n p)]
simp [hp.factorization]
#align nat.not_dvd_ord_compl Nat.not_dvd_ord_compl
theorem coprime_ord_compl {n p : ℕ} (hp : Prime p) (hn : n ≠ 0) : Coprime p (ord_compl[p] n) :=
(or_iff_left (not_dvd_ord_compl hp hn)).mp <| coprime_or_dvd_of_prime hp _
#align nat.coprime_ord_compl Nat.coprime_ord_compl
theorem factorization_ord_compl (n p : ℕ) :
(ord_compl[p] n).factorization = n.factorization.erase p := by
if hn : n = 0 then simp [hn] else
if pp : p.Prime then ?_ else
-- Porting note: needed to solve side goal explicitly
rw [Finsupp.erase_of_not_mem_support] <;> simp [pp]
ext q
rcases eq_or_ne q p with (rfl | hqp)
· simp only [Finsupp.erase_same, factorization_eq_zero_iff, not_dvd_ord_compl pp hn]
simp
· rw [Finsupp.erase_ne hqp, factorization_div (ord_proj_dvd n p)]
simp [pp.factorization, hqp.symm]
#align nat.factorization_ord_compl Nat.factorization_ord_compl
-- `ord_compl[p] n` is the largest divisor of `n` not divisible by `p`.
theorem dvd_ord_compl_of_dvd_not_dvd {p d n : ℕ} (hdn : d ∣ n) (hpd : ¬p ∣ d) :
d ∣ ord_compl[p] n := by
if hn0 : n = 0 then simp [hn0] else
if hd0 : d = 0 then simp [hd0] at hpd else
rw [← factorization_le_iff_dvd hd0 (ord_compl_pos p hn0).ne', factorization_ord_compl]
intro q
if hqp : q = p then
simp [factorization_eq_zero_iff, hqp, hpd]
else
simp [hqp, (factorization_le_iff_dvd hd0 hn0).2 hdn q]
#align nat.dvd_ord_compl_of_dvd_not_dvd Nat.dvd_ord_compl_of_dvd_not_dvd
/-- If `n` is a nonzero natural number and `p ≠ 1`, then there are natural numbers `e`
and `n'` such that `n'` is not divisible by `p` and `n = p^e * n'`. -/
theorem exists_eq_pow_mul_and_not_dvd {n : ℕ} (hn : n ≠ 0) (p : ℕ) (hp : p ≠ 1) :
∃ e n' : ℕ, ¬p ∣ n' ∧ n = p ^ e * n' :=
let ⟨a', h₁, h₂⟩ :=
multiplicity.exists_eq_pow_mul_and_not_dvd
(multiplicity.finite_nat_iff.mpr ⟨hp, Nat.pos_of_ne_zero hn⟩)
⟨_, a', h₂, h₁⟩
#align nat.exists_eq_pow_mul_and_not_dvd Nat.exists_eq_pow_mul_and_not_dvd
theorem dvd_iff_div_factorization_eq_tsub {d n : ℕ} (hd : d ≠ 0) (hdn : d ≤ n) :
d ∣ n ↔ (n / d).factorization = n.factorization - d.factorization := by
refine ⟨factorization_div, ?_⟩
rcases eq_or_lt_of_le hdn with (rfl | hd_lt_n); · simp
have h1 : n / d ≠ 0 := fun H => Nat.lt_asymm hd_lt_n ((Nat.div_eq_zero_iff hd.bot_lt).mp H)
intro h
rw [dvd_iff_le_div_mul n d]
by_contra h2
cases' exists_factorization_lt_of_lt (mul_ne_zero h1 hd) (not_le.mp h2) with p hp
rwa [factorization_mul h1 hd, add_apply, ← lt_tsub_iff_right, h, tsub_apply,
lt_self_iff_false] at hp
#align nat.dvd_iff_div_factorization_eq_tsub Nat.dvd_iff_div_factorization_eq_tsub
theorem ord_proj_dvd_ord_proj_of_dvd {a b : ℕ} (hb0 : b ≠ 0) (hab : a ∣ b) (p : ℕ) :
ord_proj[p] a ∣ ord_proj[p] b := by
rcases em' p.Prime with (pp | pp); · simp [pp]
rcases eq_or_ne a 0 with (rfl | ha0); · simp
rw [pow_dvd_pow_iff_le_right pp.one_lt]
exact (factorization_le_iff_dvd ha0 hb0).2 hab p
#align nat.ord_proj_dvd_ord_proj_of_dvd Nat.ord_proj_dvd_ord_proj_of_dvd
theorem ord_proj_dvd_ord_proj_iff_dvd {a b : ℕ} (ha0 : a ≠ 0) (hb0 : b ≠ 0) :
(∀ p : ℕ, ord_proj[p] a ∣ ord_proj[p] b) ↔ a ∣ b := by
refine ⟨fun h => ?_, fun hab p => ord_proj_dvd_ord_proj_of_dvd hb0 hab p⟩
rw [← factorization_le_iff_dvd ha0 hb0]
intro q
rcases le_or_lt q 1 with (hq_le | hq1)
· interval_cases q <;> simp
exact (pow_dvd_pow_iff_le_right hq1).1 (h q)
#align nat.ord_proj_dvd_ord_proj_iff_dvd Nat.ord_proj_dvd_ord_proj_iff_dvd
theorem ord_compl_dvd_ord_compl_of_dvd {a b : ℕ} (hab : a ∣ b) (p : ℕ) :
ord_compl[p] a ∣ ord_compl[p] b := by
rcases em' p.Prime with (pp | pp)
· simp [pp, hab]
rcases eq_or_ne b 0 with (rfl | hb0)
· simp
rcases eq_or_ne a 0 with (rfl | ha0)
· cases hb0 (zero_dvd_iff.1 hab)
have ha := (Nat.div_pos (ord_proj_le p ha0) (ord_proj_pos a p)).ne'
have hb := (Nat.div_pos (ord_proj_le p hb0) (ord_proj_pos b p)).ne'
rw [← factorization_le_iff_dvd ha hb, factorization_ord_compl a p, factorization_ord_compl b p]
intro q
rcases eq_or_ne q p with (rfl | hqp)
· simp
simp_rw [erase_ne hqp]
exact (factorization_le_iff_dvd ha0 hb0).2 hab q
#align nat.ord_compl_dvd_ord_compl_of_dvd Nat.ord_compl_dvd_ord_compl_of_dvd
theorem ord_compl_dvd_ord_compl_iff_dvd (a b : ℕ) :
(∀ p : ℕ, ord_compl[p] a ∣ ord_compl[p] b) ↔ a ∣ b := by
refine ⟨fun h => ?_, fun hab p => ord_compl_dvd_ord_compl_of_dvd hab p⟩
rcases eq_or_ne b 0 with (rfl | hb0)
· simp
if pa : a.Prime then ?_ else simpa [pa] using h a
if pb : b.Prime then ?_ else simpa [pb] using h b
rw [prime_dvd_prime_iff_eq pa pb]
by_contra hab
apply pa.ne_one
rw [← Nat.dvd_one, ← Nat.mul_dvd_mul_iff_left hb0.bot_lt, mul_one]
simpa [Prime.factorization_self pb, Prime.factorization pa, hab] using h b
#align nat.ord_compl_dvd_ord_compl_iff_dvd Nat.ord_compl_dvd_ord_compl_iff_dvd
theorem dvd_iff_prime_pow_dvd_dvd (n d : ℕ) :
d ∣ n ↔ ∀ p k : ℕ, Prime p → p ^ k ∣ d → p ^ k ∣ n := by
rcases eq_or_ne n 0 with (rfl | hn)
· simp
rcases eq_or_ne d 0 with (rfl | hd)
· simp only [zero_dvd_iff, hn, false_iff_iff, not_forall]
exact ⟨2, n, prime_two, dvd_zero _, mt (le_of_dvd hn.bot_lt) (lt_two_pow n).not_le⟩
refine ⟨fun h p k _ hpkd => dvd_trans hpkd h, ?_⟩
rw [← factorization_prime_le_iff_dvd hd hn]
intro h p pp
simp_rw [← pp.pow_dvd_iff_le_factorization hn]
exact h p _ pp (ord_proj_dvd _ _)
#align nat.dvd_iff_prime_pow_dvd_dvd Nat.dvd_iff_prime_pow_dvd_dvd
theorem prod_primeFactors_dvd (n : ℕ) : ∏ p ∈ n.primeFactors, p ∣ n := by
by_cases hn : n = 0
· subst hn
simp
simpa [prod_factors hn] using Multiset.toFinset_prod_dvd_prod (n.factors : Multiset ℕ)
#align nat.prod_prime_factors_dvd Nat.prod_primeFactors_dvd
theorem factorization_gcd {a b : ℕ} (ha_pos : a ≠ 0) (hb_pos : b ≠ 0) :
(gcd a b).factorization = a.factorization ⊓ b.factorization := by
let dfac := a.factorization ⊓ b.factorization
let d := dfac.prod (· ^ ·)
have dfac_prime : ∀ p : ℕ, p ∈ dfac.support → Prime p := by
intro p hp
have : p ∈ a.factors ∧ p ∈ b.factors := by simpa [dfac] using hp
exact prime_of_mem_factors this.1
have h1 : d.factorization = dfac := prod_pow_factorization_eq_self dfac_prime
have hd_pos : d ≠ 0 := (factorizationEquiv.invFun ⟨dfac, dfac_prime⟩).2.ne'
suffices d = gcd a b by rwa [← this]
apply gcd_greatest
· rw [← factorization_le_iff_dvd hd_pos ha_pos, h1]
exact inf_le_left
· rw [← factorization_le_iff_dvd hd_pos hb_pos, h1]
exact inf_le_right
· intro e hea heb
rcases Decidable.eq_or_ne e 0 with (rfl | he_pos)
· simp only [zero_dvd_iff] at hea
contradiction
have hea' := (factorization_le_iff_dvd he_pos ha_pos).mpr hea
have heb' := (factorization_le_iff_dvd he_pos hb_pos).mpr heb
simp [dfac, ← factorization_le_iff_dvd he_pos hd_pos, h1, hea', heb']
#align nat.factorization_gcd Nat.factorization_gcd
theorem factorization_lcm {a b : ℕ} (ha : a ≠ 0) (hb : b ≠ 0) :
(a.lcm b).factorization = a.factorization ⊔ b.factorization := by
rw [← add_right_inj (a.gcd b).factorization, ←
factorization_mul (mt gcd_eq_zero_iff.1 fun h => ha h.1) (lcm_ne_zero ha hb), gcd_mul_lcm,
factorization_gcd ha hb, factorization_mul ha hb]
ext1
exact (min_add_max _ _).symm
#align nat.factorization_lcm Nat.factorization_lcm
/-- If `a = ∏ pᵢ ^ nᵢ` and `b = ∏ pᵢ ^ mᵢ`, then `factorizationLCMLeft = ∏ pᵢ ^ kᵢ`, where
`kᵢ = nᵢ` if `mᵢ ≤ nᵢ` and `0` otherwise. Note that the product is over the divisors of `lcm a b`,
so if one of `a` or `b` is `0` then the result is `1`. -/
def factorizationLCMLeft (a b : ℕ) : ℕ :=
(Nat.lcm a b).factorization.prod fun p n ↦
if b.factorization p ≤ a.factorization p then p ^ n else 1
/-- If `a = ∏ pᵢ ^ nᵢ` and `b = ∏ pᵢ ^ mᵢ`, then `factorizationLCMRight = ∏ pᵢ ^ kᵢ`, where
`kᵢ = mᵢ` if `nᵢ < mᵢ` and `0` otherwise. Note that the product is over the divisors of `lcm a b`,
so if one of `a` or `b` is `0` then the result is `1`.
Note that `factorizationLCMRight a b` is *not* `factorizationLCMLeft b a`: the difference is
that in `factorizationLCMLeft a b` there are the primes whose exponent in `a` is bigger or equal
than the exponent in `b`, while in `factorizationLCMRight a b` there are the primes whose
exponent in `b` is strictly bigger than in `a`. For example `factorizationLCMLeft 2 2 = 2`, but
`factorizationLCMRight 2 2 = 1`. -/
def factorizationLCMRight (a b : ℕ) :=
(Nat.lcm a b).factorization.prod fun p n ↦
if b.factorization p ≤ a.factorization p then 1 else p ^ n
variable (a b)
@[simp]
lemma factorizationLCMLeft_zero_left : factorizationLCMLeft 0 b = 1 := by
simp [factorizationLCMLeft]
@[simp]
lemma factorizationLCMLeft_zero_right : factorizationLCMLeft a 0 = 1 := by
simp [factorizationLCMLeft]
@[simp]
lemma factorizationLCRight_zero_left : factorizationLCMRight 0 b = 1 := by
simp [factorizationLCMRight]
@[simp]
lemma factorizationLCMRight_zero_right : factorizationLCMRight a 0 = 1 := by
simp [factorizationLCMRight]
lemma factorizationLCMLeft_pos :
0 < factorizationLCMLeft a b := by
apply Nat.pos_of_ne_zero
rw [factorizationLCMLeft, Finsupp.prod_ne_zero_iff]
intro p _ H
by_cases h : b.factorization p ≤ a.factorization p
· simp only [h, reduceIte, pow_eq_zero_iff', ne_eq] at H
simpa [H.1] using H.2
· simp only [h, reduceIte, one_ne_zero] at H
lemma factorizationLCMRight_pos :
0 < factorizationLCMRight a b := by
apply Nat.pos_of_ne_zero
rw [factorizationLCMRight, Finsupp.prod_ne_zero_iff]
intro p _ H
by_cases h : b.factorization p ≤ a.factorization p
· simp only [h, reduceIte, pow_eq_zero_iff', ne_eq] at H
· simp only [h, ↓reduceIte, pow_eq_zero_iff', ne_eq] at H
simpa [H.1] using H.2
lemma coprime_factorizationLCMLeft_factorizationLCMRight :
(factorizationLCMLeft a b).Coprime (factorizationLCMRight a b) := by
rw [factorizationLCMLeft, factorizationLCMRight]
refine coprime_prod_left_iff.mpr fun p hp ↦ coprime_prod_right_iff.mpr fun q hq ↦ ?_
dsimp only; split_ifs with h h'
any_goals simp only [coprime_one_right_eq_true, coprime_one_left_eq_true]
refine coprime_pow_primes _ _ (prime_of_mem_primeFactors hp) (prime_of_mem_primeFactors hq) ?_
contrapose! h'; rwa [← h']
variable {a b}
lemma factorizationLCMLeft_mul_factorizationLCMRight (ha : a ≠ 0) (hb : b ≠ 0) :
(factorizationLCMLeft a b) * (factorizationLCMRight a b) = lcm a b := by
rw [← factorization_prod_pow_eq_self (lcm_ne_zero ha hb), factorizationLCMLeft,
factorizationLCMRight, ← prod_mul]
congr; ext p n; split_ifs <;> simp
variable (a b)
lemma factorizationLCMLeft_dvd_left : factorizationLCMLeft a b ∣ a := by
rcases eq_or_ne a 0 with rfl | ha
· simp only [dvd_zero]
rcases eq_or_ne b 0 with rfl | hb
· simp [factorizationLCMLeft]
nth_rewrite 2 [← factorization_prod_pow_eq_self ha]
rw [prod_of_support_subset (s := (lcm a b).factorization.support)]
· apply prod_dvd_prod_of_dvd; rintro p -; dsimp only; split_ifs with le
· rw [factorization_lcm ha hb]; apply pow_dvd_pow; exact sup_le le_rfl le
· apply one_dvd
· intro p hp; rw [mem_support_iff] at hp ⊢
rw [factorization_lcm ha hb]; exact (lt_sup_iff.mpr <| .inl <| Nat.pos_of_ne_zero hp).ne'
· intros; rw [pow_zero]
lemma factorizationLCMRight_dvd_right : factorizationLCMRight a b ∣ b := by
rcases eq_or_ne a 0 with rfl | ha
· simp [factorizationLCMRight]
rcases eq_or_ne b 0 with rfl | hb
· simp only [dvd_zero]
nth_rewrite 2 [← factorization_prod_pow_eq_self hb]
rw [prod_of_support_subset (s := (lcm a b).factorization.support)]
· apply Finset.prod_dvd_prod_of_dvd; rintro p -; dsimp only; split_ifs with le
· apply one_dvd
· rw [factorization_lcm ha hb]; apply pow_dvd_pow; exact sup_le (not_le.1 le).le le_rfl
· intro p hp; rw [mem_support_iff] at hp ⊢
rw [factorization_lcm ha hb]; exact (lt_sup_iff.mpr <| .inr <| Nat.pos_of_ne_zero hp).ne'
· intros; rw [pow_zero]
@[to_additive sum_primeFactors_gcd_add_sum_primeFactors_mul]
theorem prod_primeFactors_gcd_mul_prod_primeFactors_mul {β : Type*} [CommMonoid β] (m n : ℕ)
(f : ℕ → β) :
(m.gcd n).primeFactors.prod f * (m * n).primeFactors.prod f =
m.primeFactors.prod f * n.primeFactors.prod f := by
obtain rfl | hm₀ := eq_or_ne m 0
· simp
obtain rfl | hn₀ := eq_or_ne n 0
· simp
· rw [primeFactors_mul hm₀ hn₀, primeFactors_gcd hm₀ hn₀, mul_comm, Finset.prod_union_inter]
#align nat.prod_factors_gcd_mul_prod_factors_mul Nat.prod_primeFactors_gcd_mul_prod_primeFactors_mul
#align nat.sum_factors_gcd_add_sum_factors_mul Nat.sum_primeFactors_gcd_add_sum_primeFactors_mul
theorem setOf_pow_dvd_eq_Icc_factorization {n p : ℕ} (pp : p.Prime) (hn : n ≠ 0) :
{ i : ℕ | i ≠ 0 ∧ p ^ i ∣ n } = Set.Icc 1 (n.factorization p) := by
ext
simp [Nat.lt_succ_iff, one_le_iff_ne_zero, pp.pow_dvd_iff_le_factorization hn]
#align nat.set_of_pow_dvd_eq_Icc_factorization Nat.setOf_pow_dvd_eq_Icc_factorization
/-- The set of positive powers of prime `p` that divide `n` is exactly the set of
positive natural numbers up to `n.factorization p`. -/
theorem Icc_factorization_eq_pow_dvd (n : ℕ) {p : ℕ} (pp : Prime p) :
Icc 1 (n.factorization p) = (Ico 1 n).filter fun i : ℕ => p ^ i ∣ n := by
rcases eq_or_ne n 0 with (rfl | hn)
· simp
ext x
simp only [mem_Icc, Finset.mem_filter, mem_Ico, and_assoc, and_congr_right_iff,
pp.pow_dvd_iff_le_factorization hn, iff_and_self]
exact fun _ H => lt_of_le_of_lt H (factorization_lt p hn)
#align nat.Icc_factorization_eq_pow_dvd Nat.Icc_factorization_eq_pow_dvd
theorem factorization_eq_card_pow_dvd (n : ℕ) {p : ℕ} (pp : p.Prime) :
n.factorization p = ((Ico 1 n).filter fun i => p ^ i ∣ n).card := by
simp [← Icc_factorization_eq_pow_dvd n pp]
#align nat.factorization_eq_card_pow_dvd Nat.factorization_eq_card_pow_dvd
theorem Ico_filter_pow_dvd_eq {n p b : ℕ} (pp : p.Prime) (hn : n ≠ 0) (hb : n ≤ p ^ b) :
((Ico 1 n).filter fun i => p ^ i ∣ n) = (Icc 1 b).filter fun i => p ^ i ∣ n := by
ext x
simp only [Finset.mem_filter, mem_Ico, mem_Icc, and_congr_left_iff, and_congr_right_iff]
rintro h1 -
exact iff_of_true (lt_of_pow_dvd_right hn pp.two_le h1) <|
(pow_le_pow_iff_right pp.one_lt).1 <| (le_of_dvd hn.bot_lt h1).trans hb
#align nat.Ico_filter_pow_dvd_eq Nat.Ico_filter_pow_dvd_eq
/-! ### Factorization and coprimes -/
/-- For coprime `a` and `b`, the power of `p` in `a * b` is the sum of the powers in `a` and `b` -/
theorem factorization_mul_apply_of_coprime {p a b : ℕ} (hab : Coprime a b) :
(a * b).factorization p = a.factorization p + b.factorization p := by
simp only [← factors_count_eq, perm_iff_count.mp (perm_factors_mul_of_coprime hab), count_append]
#align nat.factorization_mul_apply_of_coprime Nat.factorization_mul_apply_of_coprime
/-- For coprime `a` and `b`, the power of `p` in `a * b` is the sum of the powers in `a` and `b` -/
| Mathlib/Data/Nat/Factorization/Basic.lean | 814 | 817 | theorem factorization_mul_of_coprime {a b : ℕ} (hab : Coprime a b) :
(a * b).factorization = a.factorization + b.factorization := by |
ext q
rw [Finsupp.add_apply, factorization_mul_apply_of_coprime hab]
|
/-
Copyright (c) 2022 Yury Kudryashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudryashov
-/
import Mathlib.Topology.EMetricSpace.Paracompact
import Mathlib.Topology.Instances.ENNReal
import Mathlib.Analysis.Convex.PartitionOfUnity
#align_import topology.metric_space.partition_of_unity from "leanprover-community/mathlib"@"f2ce6086713c78a7f880485f7917ea547a215982"
/-!
# Lemmas about (e)metric spaces that need partition of unity
The main lemma in this file (see `Metric.exists_continuous_real_forall_closedBall_subset`) says the
following. Let `X` be a metric space. Let `K : ι → Set X` be a locally finite family of closed sets,
let `U : ι → Set X` be a family of open sets such that `K i ⊆ U i` for all `i`. Then there exists a
positive continuous function `δ : C(X, → ℝ)` such that for any `i` and `x ∈ K i`, we have
`Metric.closedBall x (δ x) ⊆ U i`. We also formulate versions of this lemma for extended metric
spaces and for different codomains (`ℝ`, `ℝ≥0`, and `ℝ≥0∞`).
We also prove a few auxiliary lemmas to be used later in a proof of the smooth version of this
lemma.
## Tags
metric space, partition of unity, locally finite
-/
open Topology ENNReal NNReal Filter Set Function TopologicalSpace
variable {ι X : Type*}
namespace EMetric
variable [EMetricSpace X] {K : ι → Set X} {U : ι → Set X}
/-- Let `K : ι → Set X` be a locally finite family of closed sets in an emetric space. Let
`U : ι → Set X` be a family of open sets such that `K i ⊆ U i` for all `i`. Then for any point
`x : X`, for sufficiently small `r : ℝ≥0∞` and for `y` sufficiently close to `x`, for all `i`, if
`y ∈ K i`, then `EMetric.closedBall y r ⊆ U i`. -/
theorem eventually_nhds_zero_forall_closedBall_subset (hK : ∀ i, IsClosed (K i))
(hU : ∀ i, IsOpen (U i)) (hKU : ∀ i, K i ⊆ U i) (hfin : LocallyFinite K) (x : X) :
∀ᶠ p : ℝ≥0∞ × X in 𝓝 0 ×ˢ 𝓝 x, ∀ i, p.2 ∈ K i → closedBall p.2 p.1 ⊆ U i := by
suffices ∀ i, x ∈ K i → ∀ᶠ p : ℝ≥0∞ × X in 𝓝 0 ×ˢ 𝓝 x, closedBall p.2 p.1 ⊆ U i by
apply mp_mem ((eventually_all_finite (hfin.point_finite x)).2 this)
(mp_mem (@tendsto_snd ℝ≥0∞ _ (𝓝 0) _ _ (hfin.iInter_compl_mem_nhds hK x)) _)
apply univ_mem'
rintro ⟨r, y⟩ hxy hyU i hi
simp only [mem_iInter, mem_compl_iff, not_imp_not, mem_preimage] at hxy
exact hyU _ (hxy _ hi)
intro i hi
rcases nhds_basis_closed_eball.mem_iff.1 ((hU i).mem_nhds <| hKU i hi) with ⟨R, hR₀, hR⟩
rcases ENNReal.lt_iff_exists_nnreal_btwn.mp hR₀ with ⟨r, hr₀, hrR⟩
filter_upwards [prod_mem_prod (eventually_lt_nhds hr₀)
(closedBall_mem_nhds x (tsub_pos_iff_lt.2 hrR))] with p hp z hz
apply hR
calc
edist z x ≤ edist z p.2 + edist p.2 x := edist_triangle _ _ _
_ ≤ p.1 + (R - p.1) := add_le_add hz <| le_trans hp.2 <| tsub_le_tsub_left hp.1.out.le _
_ = R := add_tsub_cancel_of_le (lt_trans (by exact hp.1) hrR).le
#align emetric.eventually_nhds_zero_forall_closed_ball_subset EMetric.eventually_nhds_zero_forall_closedBall_subset
theorem exists_forall_closedBall_subset_aux₁ (hK : ∀ i, IsClosed (K i)) (hU : ∀ i, IsOpen (U i))
(hKU : ∀ i, K i ⊆ U i) (hfin : LocallyFinite K) (x : X) :
∃ r : ℝ, ∀ᶠ y in 𝓝 x,
r ∈ Ioi (0 : ℝ) ∩ ENNReal.ofReal ⁻¹' ⋂ (i) (_ : y ∈ K i), { r | closedBall y r ⊆ U i } := by
have := (ENNReal.continuous_ofReal.tendsto' 0 0 ENNReal.ofReal_zero).eventually
(eventually_nhds_zero_forall_closedBall_subset hK hU hKU hfin x).curry
rcases this.exists_gt with ⟨r, hr0, hr⟩
refine ⟨r, hr.mono fun y hy => ⟨hr0, ?_⟩⟩
rwa [mem_preimage, mem_iInter₂]
#align emetric.exists_forall_closed_ball_subset_aux₁ EMetric.exists_forall_closedBall_subset_aux₁
theorem exists_forall_closedBall_subset_aux₂ (y : X) :
Convex ℝ
(Ioi (0 : ℝ) ∩ ENNReal.ofReal ⁻¹' ⋂ (i) (_ : y ∈ K i), { r | closedBall y r ⊆ U i }) :=
(convex_Ioi _).inter <| OrdConnected.convex <| OrdConnected.preimage_ennreal_ofReal <|
ordConnected_iInter fun i => ordConnected_iInter fun (_ : y ∈ K i) =>
ordConnected_setOf_closedBall_subset y (U i)
#align emetric.exists_forall_closed_ball_subset_aux₂ EMetric.exists_forall_closedBall_subset_aux₂
/-- Let `X` be an extended metric space. Let `K : ι → Set X` be a locally finite family of closed
sets, let `U : ι → Set X` be a family of open sets such that `K i ⊆ U i` for all `i`. Then there
exists a positive continuous function `δ : C(X, ℝ)` such that for any `i` and `x ∈ K i`,
we have `EMetric.closedBall x (ENNReal.ofReal (δ x)) ⊆ U i`. -/
theorem exists_continuous_real_forall_closedBall_subset (hK : ∀ i, IsClosed (K i))
(hU : ∀ i, IsOpen (U i)) (hKU : ∀ i, K i ⊆ U i) (hfin : LocallyFinite K) :
∃ δ : C(X, ℝ), (∀ x, 0 < δ x) ∧
∀ (i), ∀ x ∈ K i, closedBall x (ENNReal.ofReal <| δ x) ⊆ U i := by
simpa only [mem_inter_iff, forall_and, mem_preimage, mem_iInter, @forall_swap ι X] using
exists_continuous_forall_mem_convex_of_local_const exists_forall_closedBall_subset_aux₂
(exists_forall_closedBall_subset_aux₁ hK hU hKU hfin)
#align emetric.exists_continuous_real_forall_closed_ball_subset EMetric.exists_continuous_real_forall_closedBall_subset
/-- Let `X` be an extended metric space. Let `K : ι → Set X` be a locally finite family of closed
sets, let `U : ι → Set X` be a family of open sets such that `K i ⊆ U i` for all `i`. Then there
exists a positive continuous function `δ : C(X, ℝ≥0)` such that for any `i` and `x ∈ K i`,
we have `EMetric.closedBall x (δ x) ⊆ U i`. -/
| Mathlib/Topology/MetricSpace/PartitionOfUnity.lean | 100 | 106 | theorem exists_continuous_nnreal_forall_closedBall_subset (hK : ∀ i, IsClosed (K i))
(hU : ∀ i, IsOpen (U i)) (hKU : ∀ i, K i ⊆ U i) (hfin : LocallyFinite K) :
∃ δ : C(X, ℝ≥0), (∀ x, 0 < δ x) ∧ ∀ (i), ∀ x ∈ K i, closedBall x (δ x) ⊆ U i := by |
rcases exists_continuous_real_forall_closedBall_subset hK hU hKU hfin with ⟨δ, hδ₀, hδ⟩
lift δ to C(X, ℝ≥0) using fun x => (hδ₀ x).le
refine ⟨δ, hδ₀, fun i x hi => ?_⟩
simpa only [← ENNReal.ofReal_coe_nnreal] using hδ i x hi
|
/-
Copyright (c) 2022 Adam Topaz. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Adam Topaz, Amelia Livingston
-/
import Mathlib.Algebra.Homology.Additive
import Mathlib.CategoryTheory.Abelian.Pseudoelements
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Kernels
import Mathlib.CategoryTheory.Limits.Preserves.Shapes.Images
#align_import category_theory.abelian.homology from "leanprover-community/mathlib"@"956af7c76589f444f2e1313911bad16366ea476d"
/-!
The object `homology' f g w`, where `w : f ≫ g = 0`, can be identified with either a
cokernel or a kernel. The isomorphism with a cokernel is `homology'IsoCokernelLift`, which
was obtained elsewhere. In the case of an abelian category, this file shows the isomorphism
with a kernel as well.
We use these isomorphisms to obtain the analogous api for `homology'`:
- `homology'.ι` is the map from `homology' f g w` into the cokernel of `f`.
- `homology'.π'` is the map from `kernel g` to `homology' f g w`.
- `homology'.desc'` constructs a morphism from `homology' f g w`, when it is viewed as a cokernel.
- `homology'.lift` constructs a morphism to `homology' f g w`, when it is viewed as a kernel.
- Various small lemmas are proved as well, mimicking the API for (co)kernels.
With these definitions and lemmas, the isomorphisms between homology and a (co)kernel need not
be used directly.
Note: As part of the homology refactor, it is planned to remove the definitions in this file,
because it can be replaced by the content of `Algebra.Homology.ShortComplex.Homology`.
-/
open CategoryTheory.Limits
open CategoryTheory
noncomputable section
universe v u
variable {A : Type u} [Category.{v} A] [Abelian A]
variable {X Y Z : A} (f : X ⟶ Y) (g : Y ⟶ Z) (w : f ≫ g = 0)
namespace CategoryTheory.Abelian
/-- The cokernel of `kernel.lift g f w`. This is isomorphic to `homology f g w`.
See `homologyIsoCokernelLift`. -/
abbrev homologyC : A :=
cokernel (kernel.lift g f w)
#align category_theory.abelian.homology_c CategoryTheory.Abelian.homologyC
/-- The kernel of `cokernel.desc f g w`. This is isomorphic to `homology f g w`.
See `homologyIsoKernelDesc`. -/
abbrev homologyK : A :=
kernel (cokernel.desc f g w)
#align category_theory.abelian.homology_k CategoryTheory.Abelian.homologyK
/-- The canonical map from `homologyC` to `homologyK`.
This is an isomorphism, and it is used in obtaining the API for `homology f g w`
in the bottom of this file. -/
abbrev homologyCToK : homologyC f g w ⟶ homologyK f g w :=
cokernel.desc _ (kernel.lift _ (kernel.ι _ ≫ cokernel.π _) (by simp)) (by ext; simp)
#align category_theory.abelian.homology_c_to_k CategoryTheory.Abelian.homologyCToK
attribute [local instance] Pseudoelement.homToFun Pseudoelement.hasZero
instance : Mono (homologyCToK f g w) := by
apply Pseudoelement.mono_of_zero_of_map_zero
intro a ha
obtain ⟨a, rfl⟩ := Pseudoelement.pseudo_surjective_of_epi (cokernel.π (kernel.lift g f w)) a
apply_fun kernel.ι (cokernel.desc f g w) at ha
simp only [← Pseudoelement.comp_apply, cokernel.π_desc, kernel.lift_ι,
Pseudoelement.apply_zero] at ha
simp only [Pseudoelement.comp_apply] at ha
obtain ⟨b, hb⟩ : ∃ b, f b = _ := (Pseudoelement.pseudo_exact_of_exact (exact_cokernel f)).2 _ ha
rsuffices ⟨c, rfl⟩ : ∃ c, kernel.lift g f w c = a
· simp [← Pseudoelement.comp_apply]
use b
apply_fun kernel.ι g
swap; · apply Pseudoelement.pseudo_injective_of_mono
simpa [← Pseudoelement.comp_apply]
instance : Epi (homologyCToK f g w) := by
apply Pseudoelement.epi_of_pseudo_surjective
intro a
let b := kernel.ι (cokernel.desc f g w) a
obtain ⟨c, hc⟩ : ∃ c, cokernel.π f c = b := by
apply Pseudoelement.pseudo_surjective_of_epi (cokernel.π f)
have : g c = 0 := by
rw [show g = cokernel.π f ≫ cokernel.desc f g w by simp, Pseudoelement.comp_apply, hc]
simp [b, ← Pseudoelement.comp_apply]
obtain ⟨d, hd⟩ : ∃ d, kernel.ι g d = c := by
apply (Pseudoelement.pseudo_exact_of_exact exact_kernel_ι).2 _ this
use cokernel.π (kernel.lift g f w) d
apply_fun kernel.ι (cokernel.desc f g w)
swap
· apply Pseudoelement.pseudo_injective_of_mono
simp only [← Pseudoelement.comp_apply, cokernel.π_desc, kernel.lift_ι]
simp only [Pseudoelement.comp_apply, hd, hc]
instance (w : f ≫ g = 0) : IsIso (homologyCToK f g w) :=
isIso_of_mono_of_epi _
end CategoryTheory.Abelian
/-- The homology associated to `f` and `g` is isomorphic to a kernel. -/
def homology'IsoKernelDesc : homology' f g w ≅ kernel (cokernel.desc f g w) :=
homology'IsoCokernelLift _ _ _ ≪≫ asIso (CategoryTheory.Abelian.homologyCToK _ _ _)
#align homology_iso_kernel_desc homology'IsoKernelDesc
namespace homology'
-- `homology'.π` is taken
/-- The canonical map from the kernel of `g` to the homology of `f` and `g`. -/
def π' : kernel g ⟶ homology' f g w :=
cokernel.π _ ≫ (homology'IsoCokernelLift _ _ _).inv
#align homology.π' homology'.π'
/-- The canonical map from the homology of `f` and `g` to the cokernel of `f`. -/
def ι : homology' f g w ⟶ cokernel f :=
(homology'IsoKernelDesc _ _ _).hom ≫ kernel.ι _
#align homology.ι homology'.ι
/-- Obtain a morphism from the homology, given a morphism from the kernel. -/
def desc' {W : A} (e : kernel g ⟶ W) (he : kernel.lift g f w ≫ e = 0) : homology' f g w ⟶ W :=
(homology'IsoCokernelLift _ _ _).hom ≫ cokernel.desc _ e he
#align homology.desc' homology'.desc'
/-- Obtain a morphism to the homology, given a morphism to the kernel. -/
def lift {W : A} (e : W ⟶ cokernel f) (he : e ≫ cokernel.desc f g w = 0) : W ⟶ homology' f g w :=
kernel.lift _ e he ≫ (homology'IsoKernelDesc _ _ _).inv
#align homology.lift homology'.lift
@[reassoc (attr := simp)]
theorem π'_desc' {W : A} (e : kernel g ⟶ W) (he : kernel.lift g f w ≫ e = 0) :
π' f g w ≫ desc' f g w e he = e := by
dsimp [π', desc']
simp
#align homology.π'_desc' homology'.π'_desc'
@[reassoc (attr := simp)]
theorem lift_ι {W : A} (e : W ⟶ cokernel f) (he : e ≫ cokernel.desc f g w = 0) :
lift f g w e he ≫ ι _ _ _ = e := by
dsimp [ι, lift]
simp
#align homology.lift_ι homology'.lift_ι
@[reassoc (attr := simp)]
| Mathlib/CategoryTheory/Abelian/Homology.lean | 151 | 153 | theorem condition_π' : kernel.lift g f w ≫ π' f g w = 0 := by |
dsimp [π']
simp
|
/-
Copyright (c) 2020 Fox Thomson. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Fox Thomson
-/
import Mathlib.Computability.DFA
import Mathlib.Data.Fintype.Powerset
#align_import computability.NFA from "leanprover-community/mathlib"@"32253a1a1071173b33dc7d6a218cf722c6feb514"
/-!
# Nondeterministic Finite Automata
This file contains the definition of a Nondeterministic Finite Automaton (NFA), a state machine
which determines whether a string (implemented as a list over an arbitrary alphabet) is in a regular
set by evaluating the string over every possible path.
We show that DFA's are equivalent to NFA's however the construction from NFA to DFA uses an
exponential number of states.
Note that this definition allows for Automaton with infinite states; a `Fintype` instance must be
supplied for true NFA's.
-/
open Set
open Computability
universe u v
-- Porting note: Required as `NFA` is used in mathlib3
set_option linter.uppercaseLean3 false
/-- An NFA is a set of states (`σ`), a transition function from state to state labelled by the
alphabet (`step`), a set of starting states (`start`) and a set of acceptance states (`accept`).
Note the transition function sends a state to a `Set` of states. These are the states that it
may be sent to. -/
structure NFA (α : Type u) (σ : Type v) where
step : σ → α → Set σ
start : Set σ
accept : Set σ
#align NFA NFA
variable {α : Type u} {σ σ' : Type v} (M : NFA α σ)
namespace NFA
instance : Inhabited (NFA α σ) :=
⟨NFA.mk (fun _ _ => ∅) ∅ ∅⟩
/-- `M.stepSet S a` is the union of `M.step s a` for all `s ∈ S`. -/
def stepSet (S : Set σ) (a : α) : Set σ :=
⋃ s ∈ S, M.step s a
#align NFA.step_set NFA.stepSet
theorem mem_stepSet (s : σ) (S : Set σ) (a : α) : s ∈ M.stepSet S a ↔ ∃ t ∈ S, s ∈ M.step t a := by
simp [stepSet]
#align NFA.mem_step_set NFA.mem_stepSet
@[simp]
theorem stepSet_empty (a : α) : M.stepSet ∅ a = ∅ := by simp [stepSet]
#align NFA.step_set_empty NFA.stepSet_empty
/-- `M.evalFrom S x` computes all possible paths though `M` with input `x` starting at an element
of `S`. -/
def evalFrom (start : Set σ) : List α → Set σ :=
List.foldl M.stepSet start
#align NFA.eval_from NFA.evalFrom
@[simp]
theorem evalFrom_nil (S : Set σ) : M.evalFrom S [] = S :=
rfl
#align NFA.eval_from_nil NFA.evalFrom_nil
@[simp]
theorem evalFrom_singleton (S : Set σ) (a : α) : M.evalFrom S [a] = M.stepSet S a :=
rfl
#align NFA.eval_from_singleton NFA.evalFrom_singleton
@[simp]
theorem evalFrom_append_singleton (S : Set σ) (x : List α) (a : α) :
M.evalFrom S (x ++ [a]) = M.stepSet (M.evalFrom S x) a := by
simp only [evalFrom, List.foldl_append, List.foldl_cons, List.foldl_nil]
#align NFA.eval_from_append_singleton NFA.evalFrom_append_singleton
/-- `M.eval x` computes all possible paths though `M` with input `x` starting at an element of
`M.start`. -/
def eval : List α → Set σ :=
M.evalFrom M.start
#align NFA.eval NFA.eval
@[simp]
theorem eval_nil : M.eval [] = M.start :=
rfl
#align NFA.eval_nil NFA.eval_nil
@[simp]
theorem eval_singleton (a : α) : M.eval [a] = M.stepSet M.start a :=
rfl
#align NFA.eval_singleton NFA.eval_singleton
@[simp]
theorem eval_append_singleton (x : List α) (a : α) : M.eval (x ++ [a]) = M.stepSet (M.eval x) a :=
evalFrom_append_singleton _ _ _ _
#align NFA.eval_append_singleton NFA.eval_append_singleton
/-- `M.accepts` is the language of `x` such that there is an accept state in `M.eval x`. -/
def accepts : Language α := {x | ∃ S ∈ M.accept, S ∈ M.eval x}
#align NFA.accepts NFA.accepts
theorem mem_accepts {x : List α} : x ∈ M.accepts ↔ ∃ S ∈ M.accept, S ∈ M.evalFrom M.start x := by
rfl
/-- `M.toDFA` is a `DFA` constructed from an `NFA` `M` using the subset construction. The
states is the type of `Set`s of `M.state` and the step function is `M.stepSet`. -/
def toDFA : DFA α (Set σ) where
step := M.stepSet
start := M.start
accept := { S | ∃ s ∈ S, s ∈ M.accept }
#align NFA.to_DFA NFA.toDFA
@[simp]
theorem toDFA_correct : M.toDFA.accepts = M.accepts := by
ext x
rw [mem_accepts, DFA.mem_accepts]
constructor <;> · exact fun ⟨w, h2, h3⟩ => ⟨w, h3, h2⟩
#align NFA.to_DFA_correct NFA.toDFA_correct
theorem pumping_lemma [Fintype σ] {x : List α} (hx : x ∈ M.accepts)
(hlen : Fintype.card (Set σ) ≤ List.length x) :
∃ a b c,
x = a ++ b ++ c ∧
a.length + b.length ≤ Fintype.card (Set σ) ∧ b ≠ [] ∧ {a} * {b}∗ * {c} ≤ M.accepts := by
rw [← toDFA_correct] at hx ⊢
exact M.toDFA.pumping_lemma hx hlen
#align NFA.pumping_lemma NFA.pumping_lemma
end NFA
namespace DFA
/-- `M.toNFA` is an `NFA` constructed from a `DFA` `M` by using the same start and accept
states and a transition function which sends `s` with input `a` to the singleton `M.step s a`. -/
@[simps] def toNFA (M : DFA α σ') : NFA α σ' where
step s a := {M.step s a}
start := {M.start}
accept := M.accept
#align DFA.to_NFA DFA.toNFA
@[simp]
| Mathlib/Computability/NFA.lean | 148 | 155 | theorem toNFA_evalFrom_match (M : DFA α σ) (start : σ) (s : List α) :
M.toNFA.evalFrom {start} s = {M.evalFrom start s} := by |
change List.foldl M.toNFA.stepSet {start} s = {List.foldl M.step start s}
induction' s with a s ih generalizing start
· tauto
· rw [List.foldl, List.foldl,
show M.toNFA.stepSet {start} a = {M.step start a} by simp [NFA.stepSet] ]
tauto
|
/-
Copyright (c) 2019 Reid Barton. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sébastien Gouëzel
-/
import Mathlib.Topology.Constructions
#align_import topology.continuous_on from "leanprover-community/mathlib"@"d4f691b9e5f94cfc64639973f3544c95f8d5d494"
/-!
# Neighborhoods and continuity relative to a subset
This file defines relative versions
* `nhdsWithin` of `nhds`
* `ContinuousOn` of `Continuous`
* `ContinuousWithinAt` of `ContinuousAt`
and proves their basic properties, including the relationships between
these restricted notions and the corresponding notions for the subtype
equipped with the subspace topology.
## Notation
* `𝓝 x`: the filter of neighborhoods of a point `x`;
* `𝓟 s`: the principal filter of a set `s`;
* `𝓝[s] x`: the filter `nhdsWithin x s` of neighborhoods of a point `x` within a set `s`.
-/
open Set Filter Function Topology Filter
variable {α : Type*} {β : Type*} {γ : Type*} {δ : Type*}
variable [TopologicalSpace α]
@[simp]
theorem nhds_bind_nhdsWithin {a : α} {s : Set α} : ((𝓝 a).bind fun x => 𝓝[s] x) = 𝓝[s] a :=
bind_inf_principal.trans <| congr_arg₂ _ nhds_bind_nhds rfl
#align nhds_bind_nhds_within nhds_bind_nhdsWithin
@[simp]
theorem eventually_nhds_nhdsWithin {a : α} {s : Set α} {p : α → Prop} :
(∀ᶠ y in 𝓝 a, ∀ᶠ x in 𝓝[s] y, p x) ↔ ∀ᶠ x in 𝓝[s] a, p x :=
Filter.ext_iff.1 nhds_bind_nhdsWithin { x | p x }
#align eventually_nhds_nhds_within eventually_nhds_nhdsWithin
theorem eventually_nhdsWithin_iff {a : α} {s : Set α} {p : α → Prop} :
(∀ᶠ x in 𝓝[s] a, p x) ↔ ∀ᶠ x in 𝓝 a, x ∈ s → p x :=
eventually_inf_principal
#align eventually_nhds_within_iff eventually_nhdsWithin_iff
theorem frequently_nhdsWithin_iff {z : α} {s : Set α} {p : α → Prop} :
(∃ᶠ x in 𝓝[s] z, p x) ↔ ∃ᶠ x in 𝓝 z, p x ∧ x ∈ s :=
frequently_inf_principal.trans <| by simp only [and_comm]
#align frequently_nhds_within_iff frequently_nhdsWithin_iff
theorem mem_closure_ne_iff_frequently_within {z : α} {s : Set α} :
z ∈ closure (s \ {z}) ↔ ∃ᶠ x in 𝓝[≠] z, x ∈ s := by
simp [mem_closure_iff_frequently, frequently_nhdsWithin_iff]
#align mem_closure_ne_iff_frequently_within mem_closure_ne_iff_frequently_within
@[simp]
theorem eventually_nhdsWithin_nhdsWithin {a : α} {s : Set α} {p : α → Prop} :
(∀ᶠ y in 𝓝[s] a, ∀ᶠ x in 𝓝[s] y, p x) ↔ ∀ᶠ x in 𝓝[s] a, p x := by
refine ⟨fun h => ?_, fun h => (eventually_nhds_nhdsWithin.2 h).filter_mono inf_le_left⟩
simp only [eventually_nhdsWithin_iff] at h ⊢
exact h.mono fun x hx hxs => (hx hxs).self_of_nhds hxs
#align eventually_nhds_within_nhds_within eventually_nhdsWithin_nhdsWithin
theorem nhdsWithin_eq (a : α) (s : Set α) :
𝓝[s] a = ⨅ t ∈ { t : Set α | a ∈ t ∧ IsOpen t }, 𝓟 (t ∩ s) :=
((nhds_basis_opens a).inf_principal s).eq_biInf
#align nhds_within_eq nhdsWithin_eq
theorem nhdsWithin_univ (a : α) : 𝓝[Set.univ] a = 𝓝 a := by
rw [nhdsWithin, principal_univ, inf_top_eq]
#align nhds_within_univ nhdsWithin_univ
theorem nhdsWithin_hasBasis {p : β → Prop} {s : β → Set α} {a : α} (h : (𝓝 a).HasBasis p s)
(t : Set α) : (𝓝[t] a).HasBasis p fun i => s i ∩ t :=
h.inf_principal t
#align nhds_within_has_basis nhdsWithin_hasBasis
theorem nhdsWithin_basis_open (a : α) (t : Set α) :
(𝓝[t] a).HasBasis (fun u => a ∈ u ∧ IsOpen u) fun u => u ∩ t :=
nhdsWithin_hasBasis (nhds_basis_opens a) t
#align nhds_within_basis_open nhdsWithin_basis_open
theorem mem_nhdsWithin {t : Set α} {a : α} {s : Set α} :
t ∈ 𝓝[s] a ↔ ∃ u, IsOpen u ∧ a ∈ u ∧ u ∩ s ⊆ t := by
simpa only [and_assoc, and_left_comm] using (nhdsWithin_basis_open a s).mem_iff
#align mem_nhds_within mem_nhdsWithin
theorem mem_nhdsWithin_iff_exists_mem_nhds_inter {t : Set α} {a : α} {s : Set α} :
t ∈ 𝓝[s] a ↔ ∃ u ∈ 𝓝 a, u ∩ s ⊆ t :=
(nhdsWithin_hasBasis (𝓝 a).basis_sets s).mem_iff
#align mem_nhds_within_iff_exists_mem_nhds_inter mem_nhdsWithin_iff_exists_mem_nhds_inter
theorem diff_mem_nhdsWithin_compl {x : α} {s : Set α} (hs : s ∈ 𝓝 x) (t : Set α) :
s \ t ∈ 𝓝[tᶜ] x :=
diff_mem_inf_principal_compl hs t
#align diff_mem_nhds_within_compl diff_mem_nhdsWithin_compl
theorem diff_mem_nhdsWithin_diff {x : α} {s t : Set α} (hs : s ∈ 𝓝[t] x) (t' : Set α) :
s \ t' ∈ 𝓝[t \ t'] x := by
rw [nhdsWithin, diff_eq, diff_eq, ← inf_principal, ← inf_assoc]
exact inter_mem_inf hs (mem_principal_self _)
#align diff_mem_nhds_within_diff diff_mem_nhdsWithin_diff
theorem nhds_of_nhdsWithin_of_nhds {s t : Set α} {a : α} (h1 : s ∈ 𝓝 a) (h2 : t ∈ 𝓝[s] a) :
t ∈ 𝓝 a := by
rcases mem_nhdsWithin_iff_exists_mem_nhds_inter.mp h2 with ⟨_, Hw, hw⟩
exact (𝓝 a).sets_of_superset ((𝓝 a).inter_sets Hw h1) hw
#align nhds_of_nhds_within_of_nhds nhds_of_nhdsWithin_of_nhds
theorem mem_nhdsWithin_iff_eventually {s t : Set α} {x : α} :
t ∈ 𝓝[s] x ↔ ∀ᶠ y in 𝓝 x, y ∈ s → y ∈ t :=
eventually_inf_principal
#align mem_nhds_within_iff_eventually mem_nhdsWithin_iff_eventually
theorem mem_nhdsWithin_iff_eventuallyEq {s t : Set α} {x : α} :
t ∈ 𝓝[s] x ↔ s =ᶠ[𝓝 x] (s ∩ t : Set α) := by
simp_rw [mem_nhdsWithin_iff_eventually, eventuallyEq_set, mem_inter_iff, iff_self_and]
#align mem_nhds_within_iff_eventually_eq mem_nhdsWithin_iff_eventuallyEq
theorem nhdsWithin_eq_iff_eventuallyEq {s t : Set α} {x : α} : 𝓝[s] x = 𝓝[t] x ↔ s =ᶠ[𝓝 x] t :=
set_eventuallyEq_iff_inf_principal.symm
#align nhds_within_eq_iff_eventually_eq nhdsWithin_eq_iff_eventuallyEq
theorem nhdsWithin_le_iff {s t : Set α} {x : α} : 𝓝[s] x ≤ 𝓝[t] x ↔ t ∈ 𝓝[s] x :=
set_eventuallyLE_iff_inf_principal_le.symm.trans set_eventuallyLE_iff_mem_inf_principal
#align nhds_within_le_iff nhdsWithin_le_iff
-- Porting note: golfed, dropped an unneeded assumption
theorem preimage_nhdsWithin_coinduced' {π : α → β} {s : Set β} {t : Set α} {a : α} (h : a ∈ t)
(hs : s ∈ @nhds β (.coinduced (fun x : t => π x) inferInstance) (π a)) :
π ⁻¹' s ∈ 𝓝[t] a := by
lift a to t using h
replace hs : (fun x : t => π x) ⁻¹' s ∈ 𝓝 a := preimage_nhds_coinduced hs
rwa [← map_nhds_subtype_val, mem_map]
#align preimage_nhds_within_coinduced' preimage_nhdsWithin_coinduced'ₓ
theorem mem_nhdsWithin_of_mem_nhds {s t : Set α} {a : α} (h : s ∈ 𝓝 a) : s ∈ 𝓝[t] a :=
mem_inf_of_left h
#align mem_nhds_within_of_mem_nhds mem_nhdsWithin_of_mem_nhds
theorem self_mem_nhdsWithin {a : α} {s : Set α} : s ∈ 𝓝[s] a :=
mem_inf_of_right (mem_principal_self s)
#align self_mem_nhds_within self_mem_nhdsWithin
theorem eventually_mem_nhdsWithin {a : α} {s : Set α} : ∀ᶠ x in 𝓝[s] a, x ∈ s :=
self_mem_nhdsWithin
#align eventually_mem_nhds_within eventually_mem_nhdsWithin
theorem inter_mem_nhdsWithin (s : Set α) {t : Set α} {a : α} (h : t ∈ 𝓝 a) : s ∩ t ∈ 𝓝[s] a :=
inter_mem self_mem_nhdsWithin (mem_inf_of_left h)
#align inter_mem_nhds_within inter_mem_nhdsWithin
theorem nhdsWithin_mono (a : α) {s t : Set α} (h : s ⊆ t) : 𝓝[s] a ≤ 𝓝[t] a :=
inf_le_inf_left _ (principal_mono.mpr h)
#align nhds_within_mono nhdsWithin_mono
theorem pure_le_nhdsWithin {a : α} {s : Set α} (ha : a ∈ s) : pure a ≤ 𝓝[s] a :=
le_inf (pure_le_nhds a) (le_principal_iff.2 ha)
#align pure_le_nhds_within pure_le_nhdsWithin
theorem mem_of_mem_nhdsWithin {a : α} {s t : Set α} (ha : a ∈ s) (ht : t ∈ 𝓝[s] a) : a ∈ t :=
pure_le_nhdsWithin ha ht
#align mem_of_mem_nhds_within mem_of_mem_nhdsWithin
theorem Filter.Eventually.self_of_nhdsWithin {p : α → Prop} {s : Set α} {x : α}
(h : ∀ᶠ y in 𝓝[s] x, p y) (hx : x ∈ s) : p x :=
mem_of_mem_nhdsWithin hx h
#align filter.eventually.self_of_nhds_within Filter.Eventually.self_of_nhdsWithin
theorem tendsto_const_nhdsWithin {l : Filter β} {s : Set α} {a : α} (ha : a ∈ s) :
Tendsto (fun _ : β => a) l (𝓝[s] a) :=
tendsto_const_pure.mono_right <| pure_le_nhdsWithin ha
#align tendsto_const_nhds_within tendsto_const_nhdsWithin
theorem nhdsWithin_restrict'' {a : α} (s : Set α) {t : Set α} (h : t ∈ 𝓝[s] a) :
𝓝[s] a = 𝓝[s ∩ t] a :=
le_antisymm (le_inf inf_le_left (le_principal_iff.mpr (inter_mem self_mem_nhdsWithin h)))
(inf_le_inf_left _ (principal_mono.mpr Set.inter_subset_left))
#align nhds_within_restrict'' nhdsWithin_restrict''
theorem nhdsWithin_restrict' {a : α} (s : Set α) {t : Set α} (h : t ∈ 𝓝 a) : 𝓝[s] a = 𝓝[s ∩ t] a :=
nhdsWithin_restrict'' s <| mem_inf_of_left h
#align nhds_within_restrict' nhdsWithin_restrict'
theorem nhdsWithin_restrict {a : α} (s : Set α) {t : Set α} (h₀ : a ∈ t) (h₁ : IsOpen t) :
𝓝[s] a = 𝓝[s ∩ t] a :=
nhdsWithin_restrict' s (IsOpen.mem_nhds h₁ h₀)
#align nhds_within_restrict nhdsWithin_restrict
theorem nhdsWithin_le_of_mem {a : α} {s t : Set α} (h : s ∈ 𝓝[t] a) : 𝓝[t] a ≤ 𝓝[s] a :=
nhdsWithin_le_iff.mpr h
#align nhds_within_le_of_mem nhdsWithin_le_of_mem
theorem nhdsWithin_le_nhds {a : α} {s : Set α} : 𝓝[s] a ≤ 𝓝 a := by
rw [← nhdsWithin_univ]
apply nhdsWithin_le_of_mem
exact univ_mem
#align nhds_within_le_nhds nhdsWithin_le_nhds
theorem nhdsWithin_eq_nhdsWithin' {a : α} {s t u : Set α} (hs : s ∈ 𝓝 a) (h₂ : t ∩ s = u ∩ s) :
𝓝[t] a = 𝓝[u] a := by rw [nhdsWithin_restrict' t hs, nhdsWithin_restrict' u hs, h₂]
#align nhds_within_eq_nhds_within' nhdsWithin_eq_nhdsWithin'
theorem nhdsWithin_eq_nhdsWithin {a : α} {s t u : Set α} (h₀ : a ∈ s) (h₁ : IsOpen s)
(h₂ : t ∩ s = u ∩ s) : 𝓝[t] a = 𝓝[u] a := by
rw [nhdsWithin_restrict t h₀ h₁, nhdsWithin_restrict u h₀ h₁, h₂]
#align nhds_within_eq_nhds_within nhdsWithin_eq_nhdsWithin
@[simp] theorem nhdsWithin_eq_nhds {a : α} {s : Set α} : 𝓝[s] a = 𝓝 a ↔ s ∈ 𝓝 a :=
inf_eq_left.trans le_principal_iff
#align nhds_within_eq_nhds nhdsWithin_eq_nhds
theorem IsOpen.nhdsWithin_eq {a : α} {s : Set α} (h : IsOpen s) (ha : a ∈ s) : 𝓝[s] a = 𝓝 a :=
nhdsWithin_eq_nhds.2 <| h.mem_nhds ha
#align is_open.nhds_within_eq IsOpen.nhdsWithin_eq
theorem preimage_nhds_within_coinduced {π : α → β} {s : Set β} {t : Set α} {a : α} (h : a ∈ t)
(ht : IsOpen t)
(hs : s ∈ @nhds β (.coinduced (fun x : t => π x) inferInstance) (π a)) :
π ⁻¹' s ∈ 𝓝 a := by
rw [← ht.nhdsWithin_eq h]
exact preimage_nhdsWithin_coinduced' h hs
#align preimage_nhds_within_coinduced preimage_nhds_within_coinduced
@[simp]
theorem nhdsWithin_empty (a : α) : 𝓝[∅] a = ⊥ := by rw [nhdsWithin, principal_empty, inf_bot_eq]
#align nhds_within_empty nhdsWithin_empty
theorem nhdsWithin_union (a : α) (s t : Set α) : 𝓝[s ∪ t] a = 𝓝[s] a ⊔ 𝓝[t] a := by
delta nhdsWithin
rw [← inf_sup_left, sup_principal]
#align nhds_within_union nhdsWithin_union
theorem nhdsWithin_biUnion {ι} {I : Set ι} (hI : I.Finite) (s : ι → Set α) (a : α) :
𝓝[⋃ i ∈ I, s i] a = ⨆ i ∈ I, 𝓝[s i] a :=
Set.Finite.induction_on hI (by simp) fun _ _ hT ↦ by
simp only [hT, nhdsWithin_union, iSup_insert, biUnion_insert]
#align nhds_within_bUnion nhdsWithin_biUnion
theorem nhdsWithin_sUnion {S : Set (Set α)} (hS : S.Finite) (a : α) :
𝓝[⋃₀ S] a = ⨆ s ∈ S, 𝓝[s] a := by
rw [sUnion_eq_biUnion, nhdsWithin_biUnion hS]
#align nhds_within_sUnion nhdsWithin_sUnion
theorem nhdsWithin_iUnion {ι} [Finite ι] (s : ι → Set α) (a : α) :
𝓝[⋃ i, s i] a = ⨆ i, 𝓝[s i] a := by
rw [← sUnion_range, nhdsWithin_sUnion (finite_range s), iSup_range]
#align nhds_within_Union nhdsWithin_iUnion
theorem nhdsWithin_inter (a : α) (s t : Set α) : 𝓝[s ∩ t] a = 𝓝[s] a ⊓ 𝓝[t] a := by
delta nhdsWithin
rw [inf_left_comm, inf_assoc, inf_principal, ← inf_assoc, inf_idem]
#align nhds_within_inter nhdsWithin_inter
theorem nhdsWithin_inter' (a : α) (s t : Set α) : 𝓝[s ∩ t] a = 𝓝[s] a ⊓ 𝓟 t := by
delta nhdsWithin
rw [← inf_principal, inf_assoc]
#align nhds_within_inter' nhdsWithin_inter'
theorem nhdsWithin_inter_of_mem {a : α} {s t : Set α} (h : s ∈ 𝓝[t] a) : 𝓝[s ∩ t] a = 𝓝[t] a := by
rw [nhdsWithin_inter, inf_eq_right]
exact nhdsWithin_le_of_mem h
#align nhds_within_inter_of_mem nhdsWithin_inter_of_mem
theorem nhdsWithin_inter_of_mem' {a : α} {s t : Set α} (h : t ∈ 𝓝[s] a) : 𝓝[s ∩ t] a = 𝓝[s] a := by
rw [inter_comm, nhdsWithin_inter_of_mem h]
#align nhds_within_inter_of_mem' nhdsWithin_inter_of_mem'
@[simp]
theorem nhdsWithin_singleton (a : α) : 𝓝[{a}] a = pure a := by
rw [nhdsWithin, principal_singleton, inf_eq_right.2 (pure_le_nhds a)]
#align nhds_within_singleton nhdsWithin_singleton
@[simp]
theorem nhdsWithin_insert (a : α) (s : Set α) : 𝓝[insert a s] a = pure a ⊔ 𝓝[s] a := by
rw [← singleton_union, nhdsWithin_union, nhdsWithin_singleton]
#align nhds_within_insert nhdsWithin_insert
theorem mem_nhdsWithin_insert {a : α} {s t : Set α} : t ∈ 𝓝[insert a s] a ↔ a ∈ t ∧ t ∈ 𝓝[s] a := by
simp
#align mem_nhds_within_insert mem_nhdsWithin_insert
theorem insert_mem_nhdsWithin_insert {a : α} {s t : Set α} (h : t ∈ 𝓝[s] a) :
insert a t ∈ 𝓝[insert a s] a := by simp [mem_of_superset h]
#align insert_mem_nhds_within_insert insert_mem_nhdsWithin_insert
theorem insert_mem_nhds_iff {a : α} {s : Set α} : insert a s ∈ 𝓝 a ↔ s ∈ 𝓝[≠] a := by
simp only [nhdsWithin, mem_inf_principal, mem_compl_iff, mem_singleton_iff, or_iff_not_imp_left,
insert_def]
#align insert_mem_nhds_iff insert_mem_nhds_iff
@[simp]
theorem nhdsWithin_compl_singleton_sup_pure (a : α) : 𝓝[≠] a ⊔ pure a = 𝓝 a := by
rw [← nhdsWithin_singleton, ← nhdsWithin_union, compl_union_self, nhdsWithin_univ]
#align nhds_within_compl_singleton_sup_pure nhdsWithin_compl_singleton_sup_pure
theorem nhdsWithin_prod {α : Type*} [TopologicalSpace α] {β : Type*} [TopologicalSpace β]
{s u : Set α} {t v : Set β} {a : α} {b : β} (hu : u ∈ 𝓝[s] a) (hv : v ∈ 𝓝[t] b) :
u ×ˢ v ∈ 𝓝[s ×ˢ t] (a, b) := by
rw [nhdsWithin_prod_eq]
exact prod_mem_prod hu hv
#align nhds_within_prod nhdsWithin_prod
theorem nhdsWithin_pi_eq' {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {I : Set ι}
(hI : I.Finite) (s : ∀ i, Set (α i)) (x : ∀ i, α i) :
𝓝[pi I s] x = ⨅ i, comap (fun x => x i) (𝓝 (x i) ⊓ ⨅ (_ : i ∈ I), 𝓟 (s i)) := by
simp only [nhdsWithin, nhds_pi, Filter.pi, comap_inf, comap_iInf, pi_def, comap_principal, ←
iInf_principal_finite hI, ← iInf_inf_eq]
#align nhds_within_pi_eq' nhdsWithin_pi_eq'
theorem nhdsWithin_pi_eq {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {I : Set ι}
(hI : I.Finite) (s : ∀ i, Set (α i)) (x : ∀ i, α i) :
𝓝[pi I s] x =
(⨅ i ∈ I, comap (fun x => x i) (𝓝[s i] x i)) ⊓
⨅ (i) (_ : i ∉ I), comap (fun x => x i) (𝓝 (x i)) := by
simp only [nhdsWithin, nhds_pi, Filter.pi, pi_def, ← iInf_principal_finite hI, comap_inf,
comap_principal, eval]
rw [iInf_split _ fun i => i ∈ I, inf_right_comm]
simp only [iInf_inf_eq]
#align nhds_within_pi_eq nhdsWithin_pi_eq
theorem nhdsWithin_pi_univ_eq {ι : Type*} {α : ι → Type*} [Finite ι] [∀ i, TopologicalSpace (α i)]
(s : ∀ i, Set (α i)) (x : ∀ i, α i) :
𝓝[pi univ s] x = ⨅ i, comap (fun x => x i) (𝓝[s i] x i) := by
simpa [nhdsWithin] using nhdsWithin_pi_eq finite_univ s x
#align nhds_within_pi_univ_eq nhdsWithin_pi_univ_eq
theorem nhdsWithin_pi_eq_bot {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {I : Set ι}
{s : ∀ i, Set (α i)} {x : ∀ i, α i} : 𝓝[pi I s] x = ⊥ ↔ ∃ i ∈ I, 𝓝[s i] x i = ⊥ := by
simp only [nhdsWithin, nhds_pi, pi_inf_principal_pi_eq_bot]
#align nhds_within_pi_eq_bot nhdsWithin_pi_eq_bot
theorem nhdsWithin_pi_neBot {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {I : Set ι}
{s : ∀ i, Set (α i)} {x : ∀ i, α i} : (𝓝[pi I s] x).NeBot ↔ ∀ i ∈ I, (𝓝[s i] x i).NeBot := by
simp [neBot_iff, nhdsWithin_pi_eq_bot]
#align nhds_within_pi_ne_bot nhdsWithin_pi_neBot
theorem Filter.Tendsto.piecewise_nhdsWithin {f g : α → β} {t : Set α} [∀ x, Decidable (x ∈ t)]
{a : α} {s : Set α} {l : Filter β} (h₀ : Tendsto f (𝓝[s ∩ t] a) l)
(h₁ : Tendsto g (𝓝[s ∩ tᶜ] a) l) : Tendsto (piecewise t f g) (𝓝[s] a) l := by
apply Tendsto.piecewise <;> rwa [← nhdsWithin_inter']
#align filter.tendsto.piecewise_nhds_within Filter.Tendsto.piecewise_nhdsWithin
theorem Filter.Tendsto.if_nhdsWithin {f g : α → β} {p : α → Prop} [DecidablePred p] {a : α}
{s : Set α} {l : Filter β} (h₀ : Tendsto f (𝓝[s ∩ { x | p x }] a) l)
(h₁ : Tendsto g (𝓝[s ∩ { x | ¬p x }] a) l) :
Tendsto (fun x => if p x then f x else g x) (𝓝[s] a) l :=
h₀.piecewise_nhdsWithin h₁
#align filter.tendsto.if_nhds_within Filter.Tendsto.if_nhdsWithin
theorem map_nhdsWithin (f : α → β) (a : α) (s : Set α) :
map f (𝓝[s] a) = ⨅ t ∈ { t : Set α | a ∈ t ∧ IsOpen t }, 𝓟 (f '' (t ∩ s)) :=
((nhdsWithin_basis_open a s).map f).eq_biInf
#align map_nhds_within map_nhdsWithin
theorem tendsto_nhdsWithin_mono_left {f : α → β} {a : α} {s t : Set α} {l : Filter β} (hst : s ⊆ t)
(h : Tendsto f (𝓝[t] a) l) : Tendsto f (𝓝[s] a) l :=
h.mono_left <| nhdsWithin_mono a hst
#align tendsto_nhds_within_mono_left tendsto_nhdsWithin_mono_left
theorem tendsto_nhdsWithin_mono_right {f : β → α} {l : Filter β} {a : α} {s t : Set α} (hst : s ⊆ t)
(h : Tendsto f l (𝓝[s] a)) : Tendsto f l (𝓝[t] a) :=
h.mono_right (nhdsWithin_mono a hst)
#align tendsto_nhds_within_mono_right tendsto_nhdsWithin_mono_right
theorem tendsto_nhdsWithin_of_tendsto_nhds {f : α → β} {a : α} {s : Set α} {l : Filter β}
(h : Tendsto f (𝓝 a) l) : Tendsto f (𝓝[s] a) l :=
h.mono_left inf_le_left
#align tendsto_nhds_within_of_tendsto_nhds tendsto_nhdsWithin_of_tendsto_nhds
theorem eventually_mem_of_tendsto_nhdsWithin {f : β → α} {a : α} {s : Set α} {l : Filter β}
(h : Tendsto f l (𝓝[s] a)) : ∀ᶠ i in l, f i ∈ s := by
simp_rw [nhdsWithin_eq, tendsto_iInf, mem_setOf_eq, tendsto_principal, mem_inter_iff,
eventually_and] at h
exact (h univ ⟨mem_univ a, isOpen_univ⟩).2
#align eventually_mem_of_tendsto_nhds_within eventually_mem_of_tendsto_nhdsWithin
theorem tendsto_nhds_of_tendsto_nhdsWithin {f : β → α} {a : α} {s : Set α} {l : Filter β}
(h : Tendsto f l (𝓝[s] a)) : Tendsto f l (𝓝 a) :=
h.mono_right nhdsWithin_le_nhds
#align tendsto_nhds_of_tendsto_nhds_within tendsto_nhds_of_tendsto_nhdsWithin
theorem nhdsWithin_neBot_of_mem {s : Set α} {x : α} (hx : x ∈ s) : NeBot (𝓝[s] x) :=
mem_closure_iff_nhdsWithin_neBot.1 <| subset_closure hx
#align nhds_within_ne_bot_of_mem nhdsWithin_neBot_of_mem
theorem IsClosed.mem_of_nhdsWithin_neBot {s : Set α} (hs : IsClosed s) {x : α}
(hx : NeBot <| 𝓝[s] x) : x ∈ s :=
hs.closure_eq ▸ mem_closure_iff_nhdsWithin_neBot.2 hx
#align is_closed.mem_of_nhds_within_ne_bot IsClosed.mem_of_nhdsWithin_neBot
theorem DenseRange.nhdsWithin_neBot {ι : Type*} {f : ι → α} (h : DenseRange f) (x : α) :
NeBot (𝓝[range f] x) :=
mem_closure_iff_clusterPt.1 (h x)
#align dense_range.nhds_within_ne_bot DenseRange.nhdsWithin_neBot
theorem mem_closure_pi {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {I : Set ι}
{s : ∀ i, Set (α i)} {x : ∀ i, α i} : x ∈ closure (pi I s) ↔ ∀ i ∈ I, x i ∈ closure (s i) := by
simp only [mem_closure_iff_nhdsWithin_neBot, nhdsWithin_pi_neBot]
#align mem_closure_pi mem_closure_pi
theorem closure_pi_set {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] (I : Set ι)
(s : ∀ i, Set (α i)) : closure (pi I s) = pi I fun i => closure (s i) :=
Set.ext fun _ => mem_closure_pi
#align closure_pi_set closure_pi_set
theorem dense_pi {ι : Type*} {α : ι → Type*} [∀ i, TopologicalSpace (α i)] {s : ∀ i, Set (α i)}
(I : Set ι) (hs : ∀ i ∈ I, Dense (s i)) : Dense (pi I s) := by
simp only [dense_iff_closure_eq, closure_pi_set, pi_congr rfl fun i hi => (hs i hi).closure_eq,
pi_univ]
#align dense_pi dense_pi
theorem eventuallyEq_nhdsWithin_iff {f g : α → β} {s : Set α} {a : α} :
f =ᶠ[𝓝[s] a] g ↔ ∀ᶠ x in 𝓝 a, x ∈ s → f x = g x :=
mem_inf_principal
#align eventually_eq_nhds_within_iff eventuallyEq_nhdsWithin_iff
theorem eventuallyEq_nhdsWithin_of_eqOn {f g : α → β} {s : Set α} {a : α} (h : EqOn f g s) :
f =ᶠ[𝓝[s] a] g :=
mem_inf_of_right h
#align eventually_eq_nhds_within_of_eq_on eventuallyEq_nhdsWithin_of_eqOn
theorem Set.EqOn.eventuallyEq_nhdsWithin {f g : α → β} {s : Set α} {a : α} (h : EqOn f g s) :
f =ᶠ[𝓝[s] a] g :=
eventuallyEq_nhdsWithin_of_eqOn h
#align set.eq_on.eventually_eq_nhds_within Set.EqOn.eventuallyEq_nhdsWithin
theorem tendsto_nhdsWithin_congr {f g : α → β} {s : Set α} {a : α} {l : Filter β}
(hfg : ∀ x ∈ s, f x = g x) (hf : Tendsto f (𝓝[s] a) l) : Tendsto g (𝓝[s] a) l :=
(tendsto_congr' <| eventuallyEq_nhdsWithin_of_eqOn hfg).1 hf
#align tendsto_nhds_within_congr tendsto_nhdsWithin_congr
theorem eventually_nhdsWithin_of_forall {s : Set α} {a : α} {p : α → Prop} (h : ∀ x ∈ s, p x) :
∀ᶠ x in 𝓝[s] a, p x :=
mem_inf_of_right h
#align eventually_nhds_within_of_forall eventually_nhdsWithin_of_forall
theorem tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within {a : α} {l : Filter β} {s : Set α}
(f : β → α) (h1 : Tendsto f l (𝓝 a)) (h2 : ∀ᶠ x in l, f x ∈ s) : Tendsto f l (𝓝[s] a) :=
tendsto_inf.2 ⟨h1, tendsto_principal.2 h2⟩
#align tendsto_nhds_within_of_tendsto_nhds_of_eventually_within tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within
theorem tendsto_nhdsWithin_iff {a : α} {l : Filter β} {s : Set α} {f : β → α} :
Tendsto f l (𝓝[s] a) ↔ Tendsto f l (𝓝 a) ∧ ∀ᶠ n in l, f n ∈ s :=
⟨fun h => ⟨tendsto_nhds_of_tendsto_nhdsWithin h, eventually_mem_of_tendsto_nhdsWithin h⟩, fun h =>
tendsto_nhdsWithin_of_tendsto_nhds_of_eventually_within _ h.1 h.2⟩
#align tendsto_nhds_within_iff tendsto_nhdsWithin_iff
@[simp]
theorem tendsto_nhdsWithin_range {a : α} {l : Filter β} {f : β → α} :
Tendsto f l (𝓝[range f] a) ↔ Tendsto f l (𝓝 a) :=
⟨fun h => h.mono_right inf_le_left, fun h =>
tendsto_inf.2 ⟨h, tendsto_principal.2 <| eventually_of_forall mem_range_self⟩⟩
#align tendsto_nhds_within_range tendsto_nhdsWithin_range
theorem Filter.EventuallyEq.eq_of_nhdsWithin {s : Set α} {f g : α → β} {a : α} (h : f =ᶠ[𝓝[s] a] g)
(hmem : a ∈ s) : f a = g a :=
h.self_of_nhdsWithin hmem
#align filter.eventually_eq.eq_of_nhds_within Filter.EventuallyEq.eq_of_nhdsWithin
theorem eventually_nhdsWithin_of_eventually_nhds {α : Type*} [TopologicalSpace α] {s : Set α}
{a : α} {p : α → Prop} (h : ∀ᶠ x in 𝓝 a, p x) : ∀ᶠ x in 𝓝[s] a, p x :=
mem_nhdsWithin_of_mem_nhds h
#align eventually_nhds_within_of_eventually_nhds eventually_nhdsWithin_of_eventually_nhds
/-!
### `nhdsWithin` and subtypes
-/
theorem mem_nhdsWithin_subtype {s : Set α} {a : { x // x ∈ s }} {t u : Set { x // x ∈ s }} :
t ∈ 𝓝[u] a ↔ t ∈ comap ((↑) : s → α) (𝓝[(↑) '' u] a) := by
rw [nhdsWithin, nhds_subtype, principal_subtype, ← comap_inf, ← nhdsWithin]
#align mem_nhds_within_subtype mem_nhdsWithin_subtype
theorem nhdsWithin_subtype (s : Set α) (a : { x // x ∈ s }) (t : Set { x // x ∈ s }) :
𝓝[t] a = comap ((↑) : s → α) (𝓝[(↑) '' t] a) :=
Filter.ext fun _ => mem_nhdsWithin_subtype
#align nhds_within_subtype nhdsWithin_subtype
theorem nhdsWithin_eq_map_subtype_coe {s : Set α} {a : α} (h : a ∈ s) :
𝓝[s] a = map ((↑) : s → α) (𝓝 ⟨a, h⟩) :=
(map_nhds_subtype_val ⟨a, h⟩).symm
#align nhds_within_eq_map_subtype_coe nhdsWithin_eq_map_subtype_coe
theorem mem_nhds_subtype_iff_nhdsWithin {s : Set α} {a : s} {t : Set s} :
t ∈ 𝓝 a ↔ (↑) '' t ∈ 𝓝[s] (a : α) := by
rw [← map_nhds_subtype_val, image_mem_map_iff Subtype.val_injective]
#align mem_nhds_subtype_iff_nhds_within mem_nhds_subtype_iff_nhdsWithin
theorem preimage_coe_mem_nhds_subtype {s t : Set α} {a : s} : (↑) ⁻¹' t ∈ 𝓝 a ↔ t ∈ 𝓝[s] ↑a := by
rw [← map_nhds_subtype_val, mem_map]
#align preimage_coe_mem_nhds_subtype preimage_coe_mem_nhds_subtype
theorem eventually_nhds_subtype_iff (s : Set α) (a : s) (P : α → Prop) :
(∀ᶠ x : s in 𝓝 a, P x) ↔ ∀ᶠ x in 𝓝[s] a, P x :=
preimage_coe_mem_nhds_subtype
theorem frequently_nhds_subtype_iff (s : Set α) (a : s) (P : α → Prop) :
(∃ᶠ x : s in 𝓝 a, P x) ↔ ∃ᶠ x in 𝓝[s] a, P x :=
eventually_nhds_subtype_iff s a (¬ P ·) |>.not
theorem tendsto_nhdsWithin_iff_subtype {s : Set α} {a : α} (h : a ∈ s) (f : α → β) (l : Filter β) :
Tendsto f (𝓝[s] a) l ↔ Tendsto (s.restrict f) (𝓝 ⟨a, h⟩) l := by
rw [nhdsWithin_eq_map_subtype_coe h, tendsto_map'_iff]; rfl
#align tendsto_nhds_within_iff_subtype tendsto_nhdsWithin_iff_subtype
variable [TopologicalSpace β] [TopologicalSpace γ] [TopologicalSpace δ]
/-- If a function is continuous within `s` at `x`, then it tends to `f x` within `s` by definition.
We register this fact for use with the dot notation, especially to use `Filter.Tendsto.comp` as
`ContinuousWithinAt.comp` will have a different meaning. -/
theorem ContinuousWithinAt.tendsto {f : α → β} {s : Set α} {x : α} (h : ContinuousWithinAt f s x) :
Tendsto f (𝓝[s] x) (𝓝 (f x)) :=
h
#align continuous_within_at.tendsto ContinuousWithinAt.tendsto
theorem ContinuousOn.continuousWithinAt {f : α → β} {s : Set α} {x : α} (hf : ContinuousOn f s)
(hx : x ∈ s) : ContinuousWithinAt f s x :=
hf x hx
#align continuous_on.continuous_within_at ContinuousOn.continuousWithinAt
theorem continuousWithinAt_univ (f : α → β) (x : α) :
ContinuousWithinAt f Set.univ x ↔ ContinuousAt f x := by
rw [ContinuousAt, ContinuousWithinAt, nhdsWithin_univ]
#align continuous_within_at_univ continuousWithinAt_univ
theorem continuous_iff_continuousOn_univ {f : α → β} : Continuous f ↔ ContinuousOn f univ := by
simp [continuous_iff_continuousAt, ContinuousOn, ContinuousAt, ContinuousWithinAt,
nhdsWithin_univ]
#align continuous_iff_continuous_on_univ continuous_iff_continuousOn_univ
theorem continuousWithinAt_iff_continuousAt_restrict (f : α → β) {x : α} {s : Set α} (h : x ∈ s) :
ContinuousWithinAt f s x ↔ ContinuousAt (s.restrict f) ⟨x, h⟩ :=
tendsto_nhdsWithin_iff_subtype h f _
#align continuous_within_at_iff_continuous_at_restrict continuousWithinAt_iff_continuousAt_restrict
theorem ContinuousWithinAt.tendsto_nhdsWithin {f : α → β} {x : α} {s : Set α} {t : Set β}
(h : ContinuousWithinAt f s x) (ht : MapsTo f s t) : Tendsto f (𝓝[s] x) (𝓝[t] f x) :=
tendsto_inf.2 ⟨h, tendsto_principal.2 <| mem_inf_of_right <| mem_principal.2 <| ht⟩
#align continuous_within_at.tendsto_nhds_within ContinuousWithinAt.tendsto_nhdsWithin
theorem ContinuousWithinAt.tendsto_nhdsWithin_image {f : α → β} {x : α} {s : Set α}
(h : ContinuousWithinAt f s x) : Tendsto f (𝓝[s] x) (𝓝[f '' s] f x) :=
h.tendsto_nhdsWithin (mapsTo_image _ _)
#align continuous_within_at.tendsto_nhds_within_image ContinuousWithinAt.tendsto_nhdsWithin_image
theorem ContinuousWithinAt.prod_map {f : α → γ} {g : β → δ} {s : Set α} {t : Set β} {x : α} {y : β}
(hf : ContinuousWithinAt f s x) (hg : ContinuousWithinAt g t y) :
ContinuousWithinAt (Prod.map f g) (s ×ˢ t) (x, y) := by
unfold ContinuousWithinAt at *
rw [nhdsWithin_prod_eq, Prod.map, nhds_prod_eq]
exact hf.prod_map hg
#align continuous_within_at.prod_map ContinuousWithinAt.prod_map
theorem continuousWithinAt_prod_of_discrete_left [DiscreteTopology α]
{f : α × β → γ} {s : Set (α × β)} {x : α × β} :
ContinuousWithinAt f s x ↔ ContinuousWithinAt (f ⟨x.1, ·⟩) {b | (x.1, b) ∈ s} x.2 := by
rw [← x.eta]; simp_rw [ContinuousWithinAt, nhdsWithin, nhds_prod_eq, nhds_discrete, pure_prod,
← map_inf_principal_preimage]; rfl
theorem continuousWithinAt_prod_of_discrete_right [DiscreteTopology β]
{f : α × β → γ} {s : Set (α × β)} {x : α × β} :
ContinuousWithinAt f s x ↔ ContinuousWithinAt (f ⟨·, x.2⟩) {a | (a, x.2) ∈ s} x.1 := by
rw [← x.eta]; simp_rw [ContinuousWithinAt, nhdsWithin, nhds_prod_eq, nhds_discrete, prod_pure,
← map_inf_principal_preimage]; rfl
theorem continuousAt_prod_of_discrete_left [DiscreteTopology α] {f : α × β → γ} {x : α × β} :
ContinuousAt f x ↔ ContinuousAt (f ⟨x.1, ·⟩) x.2 := by
simp_rw [← continuousWithinAt_univ]; exact continuousWithinAt_prod_of_discrete_left
theorem continuousAt_prod_of_discrete_right [DiscreteTopology β] {f : α × β → γ} {x : α × β} :
ContinuousAt f x ↔ ContinuousAt (f ⟨·, x.2⟩) x.1 := by
simp_rw [← continuousWithinAt_univ]; exact continuousWithinAt_prod_of_discrete_right
theorem continuousOn_prod_of_discrete_left [DiscreteTopology α] {f : α × β → γ} {s : Set (α × β)} :
ContinuousOn f s ↔ ∀ a, ContinuousOn (f ⟨a, ·⟩) {b | (a, b) ∈ s} := by
simp_rw [ContinuousOn, Prod.forall, continuousWithinAt_prod_of_discrete_left]; rfl
theorem continuousOn_prod_of_discrete_right [DiscreteTopology β] {f : α × β → γ} {s : Set (α × β)} :
ContinuousOn f s ↔ ∀ b, ContinuousOn (f ⟨·, b⟩) {a | (a, b) ∈ s} := by
simp_rw [ContinuousOn, Prod.forall, continuousWithinAt_prod_of_discrete_right]; apply forall_swap
/-- If a function `f a b` is such that `y ↦ f a b` is continuous for all `a`, and `a` lives in a
discrete space, then `f` is continuous, and vice versa. -/
theorem continuous_prod_of_discrete_left [DiscreteTopology α] {f : α × β → γ} :
Continuous f ↔ ∀ a, Continuous (f ⟨a, ·⟩) := by
simp_rw [continuous_iff_continuousOn_univ]; exact continuousOn_prod_of_discrete_left
theorem continuous_prod_of_discrete_right [DiscreteTopology β] {f : α × β → γ} :
Continuous f ↔ ∀ b, Continuous (f ⟨·, b⟩) := by
simp_rw [continuous_iff_continuousOn_univ]; exact continuousOn_prod_of_discrete_right
theorem isOpenMap_prod_of_discrete_left [DiscreteTopology α] {f : α × β → γ} :
IsOpenMap f ↔ ∀ a, IsOpenMap (f ⟨a, ·⟩) := by
simp_rw [isOpenMap_iff_nhds_le, Prod.forall, nhds_prod_eq, nhds_discrete, pure_prod, map_map]
rfl
theorem isOpenMap_prod_of_discrete_right [DiscreteTopology β] {f : α × β → γ} :
IsOpenMap f ↔ ∀ b, IsOpenMap (f ⟨·, b⟩) := by
simp_rw [isOpenMap_iff_nhds_le, Prod.forall, forall_swap (α := α) (β := β), nhds_prod_eq,
nhds_discrete, prod_pure, map_map]; rfl
theorem continuousWithinAt_pi {ι : Type*} {π : ι → Type*} [∀ i, TopologicalSpace (π i)]
{f : α → ∀ i, π i} {s : Set α} {x : α} :
ContinuousWithinAt f s x ↔ ∀ i, ContinuousWithinAt (fun y => f y i) s x :=
tendsto_pi_nhds
#align continuous_within_at_pi continuousWithinAt_pi
theorem continuousOn_pi {ι : Type*} {π : ι → Type*} [∀ i, TopologicalSpace (π i)]
{f : α → ∀ i, π i} {s : Set α} : ContinuousOn f s ↔ ∀ i, ContinuousOn (fun y => f y i) s :=
⟨fun h i x hx => tendsto_pi_nhds.1 (h x hx) i, fun h x hx => tendsto_pi_nhds.2 fun i => h i x hx⟩
#align continuous_on_pi continuousOn_pi
@[fun_prop]
theorem continuousOn_pi' {ι : Type*} {π : ι → Type*} [∀ i, TopologicalSpace (π i)]
{f : α → ∀ i, π i} {s : Set α} (hf : ∀ i, ContinuousOn (fun y => f y i) s) :
ContinuousOn f s :=
continuousOn_pi.2 hf
theorem ContinuousWithinAt.fin_insertNth {n} {π : Fin (n + 1) → Type*}
[∀ i, TopologicalSpace (π i)] (i : Fin (n + 1)) {f : α → π i} {a : α} {s : Set α}
(hf : ContinuousWithinAt f s a) {g : α → ∀ j : Fin n, π (i.succAbove j)}
(hg : ContinuousWithinAt g s a) : ContinuousWithinAt (fun a => i.insertNth (f a) (g a)) s a :=
hf.tendsto.fin_insertNth i hg
#align continuous_within_at.fin_insert_nth ContinuousWithinAt.fin_insertNth
nonrec theorem ContinuousOn.fin_insertNth {n} {π : Fin (n + 1) → Type*}
[∀ i, TopologicalSpace (π i)] (i : Fin (n + 1)) {f : α → π i} {s : Set α}
(hf : ContinuousOn f s) {g : α → ∀ j : Fin n, π (i.succAbove j)} (hg : ContinuousOn g s) :
ContinuousOn (fun a => i.insertNth (f a) (g a)) s := fun a ha =>
(hf a ha).fin_insertNth i (hg a ha)
#align continuous_on.fin_insert_nth ContinuousOn.fin_insertNth
theorem continuousOn_iff {f : α → β} {s : Set α} :
ContinuousOn f s ↔
∀ x ∈ s, ∀ t : Set β, IsOpen t → f x ∈ t → ∃ u, IsOpen u ∧ x ∈ u ∧ u ∩ s ⊆ f ⁻¹' t := by
simp only [ContinuousOn, ContinuousWithinAt, tendsto_nhds, mem_nhdsWithin]
#align continuous_on_iff continuousOn_iff
theorem continuousOn_iff_continuous_restrict {f : α → β} {s : Set α} :
ContinuousOn f s ↔ Continuous (s.restrict f) := by
rw [ContinuousOn, continuous_iff_continuousAt]; constructor
· rintro h ⟨x, xs⟩
exact (continuousWithinAt_iff_continuousAt_restrict f xs).mp (h x xs)
intro h x xs
exact (continuousWithinAt_iff_continuousAt_restrict f xs).mpr (h ⟨x, xs⟩)
#align continuous_on_iff_continuous_restrict continuousOn_iff_continuous_restrict
-- Porting note: 2 new lemmas
alias ⟨ContinuousOn.restrict, _⟩ := continuousOn_iff_continuous_restrict
theorem ContinuousOn.restrict_mapsTo {f : α → β} {s : Set α} {t : Set β} (hf : ContinuousOn f s)
(ht : MapsTo f s t) : Continuous (ht.restrict f s t) :=
hf.restrict.codRestrict _
theorem continuousOn_iff' {f : α → β} {s : Set α} :
ContinuousOn f s ↔ ∀ t : Set β, IsOpen t → ∃ u, IsOpen u ∧ f ⁻¹' t ∩ s = u ∩ s := by
have : ∀ t, IsOpen (s.restrict f ⁻¹' t) ↔ ∃ u : Set α, IsOpen u ∧ f ⁻¹' t ∩ s = u ∩ s := by
intro t
rw [isOpen_induced_iff, Set.restrict_eq, Set.preimage_comp]
simp only [Subtype.preimage_coe_eq_preimage_coe_iff]
constructor <;>
· rintro ⟨u, ou, useq⟩
exact ⟨u, ou, by simpa only [Set.inter_comm, eq_comm] using useq⟩
rw [continuousOn_iff_continuous_restrict, continuous_def]; simp only [this]
#align continuous_on_iff' continuousOn_iff'
/-- If a function is continuous on a set for some topologies, then it is
continuous on the same set with respect to any finer topology on the source space. -/
theorem ContinuousOn.mono_dom {α β : Type*} {t₁ t₂ : TopologicalSpace α} {t₃ : TopologicalSpace β}
(h₁ : t₂ ≤ t₁) {s : Set α} {f : α → β} (h₂ : @ContinuousOn α β t₁ t₃ f s) :
@ContinuousOn α β t₂ t₃ f s := fun x hx _u hu =>
map_mono (inf_le_inf_right _ <| nhds_mono h₁) (h₂ x hx hu)
#align continuous_on.mono_dom ContinuousOn.mono_dom
/-- If a function is continuous on a set for some topologies, then it is
continuous on the same set with respect to any coarser topology on the target space. -/
theorem ContinuousOn.mono_rng {α β : Type*} {t₁ : TopologicalSpace α} {t₂ t₃ : TopologicalSpace β}
(h₁ : t₂ ≤ t₃) {s : Set α} {f : α → β} (h₂ : @ContinuousOn α β t₁ t₂ f s) :
@ContinuousOn α β t₁ t₃ f s := fun x hx _u hu =>
h₂ x hx <| nhds_mono h₁ hu
#align continuous_on.mono_rng ContinuousOn.mono_rng
theorem continuousOn_iff_isClosed {f : α → β} {s : Set α} :
ContinuousOn f s ↔ ∀ t : Set β, IsClosed t → ∃ u, IsClosed u ∧ f ⁻¹' t ∩ s = u ∩ s := by
have : ∀ t, IsClosed (s.restrict f ⁻¹' t) ↔ ∃ u : Set α, IsClosed u ∧ f ⁻¹' t ∩ s = u ∩ s := by
intro t
rw [isClosed_induced_iff, Set.restrict_eq, Set.preimage_comp]
simp only [Subtype.preimage_coe_eq_preimage_coe_iff, eq_comm, Set.inter_comm s]
rw [continuousOn_iff_continuous_restrict, continuous_iff_isClosed]; simp only [this]
#align continuous_on_iff_is_closed continuousOn_iff_isClosed
theorem ContinuousOn.prod_map {f : α → γ} {g : β → δ} {s : Set α} {t : Set β}
(hf : ContinuousOn f s) (hg : ContinuousOn g t) : ContinuousOn (Prod.map f g) (s ×ˢ t) :=
fun ⟨x, y⟩ ⟨hx, hy⟩ => ContinuousWithinAt.prod_map (hf x hx) (hg y hy)
#align continuous_on.prod_map ContinuousOn.prod_map
theorem continuous_of_cover_nhds {ι : Sort*} {f : α → β} {s : ι → Set α}
(hs : ∀ x : α, ∃ i, s i ∈ 𝓝 x) (hf : ∀ i, ContinuousOn f (s i)) :
Continuous f :=
continuous_iff_continuousAt.mpr fun x ↦ let ⟨i, hi⟩ := hs x; by
rw [ContinuousAt, ← nhdsWithin_eq_nhds.2 hi]
exact hf _ _ (mem_of_mem_nhds hi)
#align continuous_of_cover_nhds continuous_of_cover_nhds
theorem continuousOn_empty (f : α → β) : ContinuousOn f ∅ := fun _ => False.elim
#align continuous_on_empty continuousOn_empty
@[simp]
theorem continuousOn_singleton (f : α → β) (a : α) : ContinuousOn f {a} :=
forall_eq.2 <| by
simpa only [ContinuousWithinAt, nhdsWithin_singleton, tendsto_pure_left] using fun s =>
mem_of_mem_nhds
#align continuous_on_singleton continuousOn_singleton
theorem Set.Subsingleton.continuousOn {s : Set α} (hs : s.Subsingleton) (f : α → β) :
ContinuousOn f s :=
hs.induction_on (continuousOn_empty f) (continuousOn_singleton f)
#align set.subsingleton.continuous_on Set.Subsingleton.continuousOn
theorem nhdsWithin_le_comap {x : α} {s : Set α} {f : α → β} (ctsf : ContinuousWithinAt f s x) :
𝓝[s] x ≤ comap f (𝓝[f '' s] f x) :=
ctsf.tendsto_nhdsWithin_image.le_comap
#align nhds_within_le_comap nhdsWithin_le_comap
@[simp]
theorem comap_nhdsWithin_range {α} (f : α → β) (y : β) : comap f (𝓝[range f] y) = comap f (𝓝 y) :=
comap_inf_principal_range
#align comap_nhds_within_range comap_nhdsWithin_range
theorem ContinuousWithinAt.mono {f : α → β} {s t : Set α} {x : α} (h : ContinuousWithinAt f t x)
(hs : s ⊆ t) : ContinuousWithinAt f s x :=
h.mono_left (nhdsWithin_mono x hs)
#align continuous_within_at.mono ContinuousWithinAt.mono
theorem ContinuousWithinAt.mono_of_mem {f : α → β} {s t : Set α} {x : α}
(h : ContinuousWithinAt f t x) (hs : t ∈ 𝓝[s] x) : ContinuousWithinAt f s x :=
h.mono_left (nhdsWithin_le_of_mem hs)
#align continuous_within_at.mono_of_mem ContinuousWithinAt.mono_of_mem
theorem continuousWithinAt_congr_nhds {f : α → β} {s t : Set α} {x : α} (h : 𝓝[s] x = 𝓝[t] x) :
ContinuousWithinAt f s x ↔ ContinuousWithinAt f t x := by
simp only [ContinuousWithinAt, h]
theorem continuousWithinAt_inter' {f : α → β} {s t : Set α} {x : α} (h : t ∈ 𝓝[s] x) :
ContinuousWithinAt f (s ∩ t) x ↔ ContinuousWithinAt f s x := by
simp [ContinuousWithinAt, nhdsWithin_restrict'' s h]
#align continuous_within_at_inter' continuousWithinAt_inter'
theorem continuousWithinAt_inter {f : α → β} {s t : Set α} {x : α} (h : t ∈ 𝓝 x) :
ContinuousWithinAt f (s ∩ t) x ↔ ContinuousWithinAt f s x := by
simp [ContinuousWithinAt, nhdsWithin_restrict' s h]
#align continuous_within_at_inter continuousWithinAt_inter
theorem continuousWithinAt_union {f : α → β} {s t : Set α} {x : α} :
ContinuousWithinAt f (s ∪ t) x ↔ ContinuousWithinAt f s x ∧ ContinuousWithinAt f t x := by
simp only [ContinuousWithinAt, nhdsWithin_union, tendsto_sup]
#align continuous_within_at_union continuousWithinAt_union
theorem ContinuousWithinAt.union {f : α → β} {s t : Set α} {x : α} (hs : ContinuousWithinAt f s x)
(ht : ContinuousWithinAt f t x) : ContinuousWithinAt f (s ∪ t) x :=
continuousWithinAt_union.2 ⟨hs, ht⟩
#align continuous_within_at.union ContinuousWithinAt.union
theorem ContinuousWithinAt.mem_closure_image {f : α → β} {s : Set α} {x : α}
(h : ContinuousWithinAt f s x) (hx : x ∈ closure s) : f x ∈ closure (f '' s) :=
haveI := mem_closure_iff_nhdsWithin_neBot.1 hx
mem_closure_of_tendsto h <| mem_of_superset self_mem_nhdsWithin (subset_preimage_image f s)
#align continuous_within_at.mem_closure_image ContinuousWithinAt.mem_closure_image
theorem ContinuousWithinAt.mem_closure {f : α → β} {s : Set α} {x : α} {A : Set β}
(h : ContinuousWithinAt f s x) (hx : x ∈ closure s) (hA : MapsTo f s A) : f x ∈ closure A :=
closure_mono (image_subset_iff.2 hA) (h.mem_closure_image hx)
#align continuous_within_at.mem_closure ContinuousWithinAt.mem_closure
theorem Set.MapsTo.closure_of_continuousWithinAt {f : α → β} {s : Set α} {t : Set β}
(h : MapsTo f s t) (hc : ∀ x ∈ closure s, ContinuousWithinAt f s x) :
MapsTo f (closure s) (closure t) := fun x hx => (hc x hx).mem_closure hx h
#align set.maps_to.closure_of_continuous_within_at Set.MapsTo.closure_of_continuousWithinAt
theorem Set.MapsTo.closure_of_continuousOn {f : α → β} {s : Set α} {t : Set β} (h : MapsTo f s t)
(hc : ContinuousOn f (closure s)) : MapsTo f (closure s) (closure t) :=
h.closure_of_continuousWithinAt fun x hx => (hc x hx).mono subset_closure
#align set.maps_to.closure_of_continuous_on Set.MapsTo.closure_of_continuousOn
theorem ContinuousWithinAt.image_closure {f : α → β} {s : Set α}
(hf : ∀ x ∈ closure s, ContinuousWithinAt f s x) : f '' closure s ⊆ closure (f '' s) :=
((mapsTo_image f s).closure_of_continuousWithinAt hf).image_subset
#align continuous_within_at.image_closure ContinuousWithinAt.image_closure
theorem ContinuousOn.image_closure {f : α → β} {s : Set α} (hf : ContinuousOn f (closure s)) :
f '' closure s ⊆ closure (f '' s) :=
ContinuousWithinAt.image_closure fun x hx => (hf x hx).mono subset_closure
#align continuous_on.image_closure ContinuousOn.image_closure
@[simp]
theorem continuousWithinAt_singleton {f : α → β} {x : α} : ContinuousWithinAt f {x} x := by
simp only [ContinuousWithinAt, nhdsWithin_singleton, tendsto_pure_nhds]
#align continuous_within_at_singleton continuousWithinAt_singleton
@[simp]
theorem continuousWithinAt_insert_self {f : α → β} {x : α} {s : Set α} :
ContinuousWithinAt f (insert x s) x ↔ ContinuousWithinAt f s x := by
simp only [← singleton_union, continuousWithinAt_union, continuousWithinAt_singleton,
true_and_iff]
#align continuous_within_at_insert_self continuousWithinAt_insert_self
alias ⟨_, ContinuousWithinAt.insert_self⟩ := continuousWithinAt_insert_self
#align continuous_within_at.insert_self ContinuousWithinAt.insert_self
theorem ContinuousWithinAt.diff_iff {f : α → β} {s t : Set α} {x : α}
(ht : ContinuousWithinAt f t x) : ContinuousWithinAt f (s \ t) x ↔ ContinuousWithinAt f s x :=
⟨fun h => (h.union ht).mono <| by simp only [diff_union_self, subset_union_left], fun h =>
h.mono diff_subset⟩
#align continuous_within_at.diff_iff ContinuousWithinAt.diff_iff
@[simp]
theorem continuousWithinAt_diff_self {f : α → β} {s : Set α} {x : α} :
ContinuousWithinAt f (s \ {x}) x ↔ ContinuousWithinAt f s x :=
continuousWithinAt_singleton.diff_iff
#align continuous_within_at_diff_self continuousWithinAt_diff_self
@[simp]
theorem continuousWithinAt_compl_self {f : α → β} {a : α} :
ContinuousWithinAt f {a}ᶜ a ↔ ContinuousAt f a := by
rw [compl_eq_univ_diff, continuousWithinAt_diff_self, continuousWithinAt_univ]
#align continuous_within_at_compl_self continuousWithinAt_compl_self
@[simp]
theorem continuousWithinAt_update_same [DecidableEq α] {f : α → β} {s : Set α} {x : α} {y : β} :
ContinuousWithinAt (update f x y) s x ↔ Tendsto f (𝓝[s \ {x}] x) (𝓝 y) :=
calc
ContinuousWithinAt (update f x y) s x ↔ Tendsto (update f x y) (𝓝[s \ {x}] x) (𝓝 y) := by
{ rw [← continuousWithinAt_diff_self, ContinuousWithinAt, update_same] }
_ ↔ Tendsto f (𝓝[s \ {x}] x) (𝓝 y) :=
tendsto_congr' <| eventually_nhdsWithin_iff.2 <| eventually_of_forall
fun z hz => update_noteq hz.2 _ _
#align continuous_within_at_update_same continuousWithinAt_update_same
@[simp]
theorem continuousAt_update_same [DecidableEq α] {f : α → β} {x : α} {y : β} :
ContinuousAt (Function.update f x y) x ↔ Tendsto f (𝓝[≠] x) (𝓝 y) := by
rw [← continuousWithinAt_univ, continuousWithinAt_update_same, compl_eq_univ_diff]
#align continuous_at_update_same continuousAt_update_same
theorem IsOpenMap.continuousOn_image_of_leftInvOn {f : α → β} {s : Set α}
(h : IsOpenMap (s.restrict f)) {finv : β → α} (hleft : LeftInvOn finv f s) :
ContinuousOn finv (f '' s) := by
refine continuousOn_iff'.2 fun t ht => ⟨f '' (t ∩ s), ?_, ?_⟩
· rw [← image_restrict]
exact h _ (ht.preimage continuous_subtype_val)
· rw [inter_eq_self_of_subset_left (image_subset f inter_subset_right), hleft.image_inter']
#align is_open_map.continuous_on_image_of_left_inv_on IsOpenMap.continuousOn_image_of_leftInvOn
theorem IsOpenMap.continuousOn_range_of_leftInverse {f : α → β} (hf : IsOpenMap f) {finv : β → α}
(hleft : Function.LeftInverse finv f) : ContinuousOn finv (range f) := by
rw [← image_univ]
exact (hf.restrict isOpen_univ).continuousOn_image_of_leftInvOn fun x _ => hleft x
#align is_open_map.continuous_on_range_of_left_inverse IsOpenMap.continuousOn_range_of_leftInverse
theorem ContinuousOn.congr_mono {f g : α → β} {s s₁ : Set α} (h : ContinuousOn f s)
(h' : EqOn g f s₁) (h₁ : s₁ ⊆ s) : ContinuousOn g s₁ := by
intro x hx
unfold ContinuousWithinAt
have A := (h x (h₁ hx)).mono h₁
unfold ContinuousWithinAt at A
rw [← h' hx] at A
exact A.congr' h'.eventuallyEq_nhdsWithin.symm
#align continuous_on.congr_mono ContinuousOn.congr_mono
theorem ContinuousOn.congr {f g : α → β} {s : Set α} (h : ContinuousOn f s) (h' : EqOn g f s) :
ContinuousOn g s :=
h.congr_mono h' (Subset.refl _)
#align continuous_on.congr ContinuousOn.congr
theorem continuousOn_congr {f g : α → β} {s : Set α} (h' : EqOn g f s) :
ContinuousOn g s ↔ ContinuousOn f s :=
⟨fun h => ContinuousOn.congr h h'.symm, fun h => h.congr h'⟩
#align continuous_on_congr continuousOn_congr
theorem ContinuousAt.continuousWithinAt {f : α → β} {s : Set α} {x : α} (h : ContinuousAt f x) :
ContinuousWithinAt f s x :=
ContinuousWithinAt.mono ((continuousWithinAt_univ f x).2 h) (subset_univ _)
#align continuous_at.continuous_within_at ContinuousAt.continuousWithinAt
theorem continuousWithinAt_iff_continuousAt {f : α → β} {s : Set α} {x : α} (h : s ∈ 𝓝 x) :
ContinuousWithinAt f s x ↔ ContinuousAt f x := by
rw [← univ_inter s, continuousWithinAt_inter h, continuousWithinAt_univ]
#align continuous_within_at_iff_continuous_at continuousWithinAt_iff_continuousAt
theorem ContinuousWithinAt.continuousAt {f : α → β} {s : Set α} {x : α}
(h : ContinuousWithinAt f s x) (hs : s ∈ 𝓝 x) : ContinuousAt f x :=
(continuousWithinAt_iff_continuousAt hs).mp h
#align continuous_within_at.continuous_at ContinuousWithinAt.continuousAt
theorem IsOpen.continuousOn_iff {f : α → β} {s : Set α} (hs : IsOpen s) :
ContinuousOn f s ↔ ∀ ⦃a⦄, a ∈ s → ContinuousAt f a :=
forall₂_congr fun _ => continuousWithinAt_iff_continuousAt ∘ hs.mem_nhds
#align is_open.continuous_on_iff IsOpen.continuousOn_iff
theorem ContinuousOn.continuousAt {f : α → β} {s : Set α} {x : α} (h : ContinuousOn f s)
(hx : s ∈ 𝓝 x) : ContinuousAt f x :=
(h x (mem_of_mem_nhds hx)).continuousAt hx
#align continuous_on.continuous_at ContinuousOn.continuousAt
theorem ContinuousAt.continuousOn {f : α → β} {s : Set α} (hcont : ∀ x ∈ s, ContinuousAt f x) :
ContinuousOn f s := fun x hx => (hcont x hx).continuousWithinAt
#align continuous_at.continuous_on ContinuousAt.continuousOn
theorem ContinuousWithinAt.comp {g : β → γ} {f : α → β} {s : Set α} {t : Set β} {x : α}
(hg : ContinuousWithinAt g t (f x)) (hf : ContinuousWithinAt f s x) (h : MapsTo f s t) :
ContinuousWithinAt (g ∘ f) s x :=
hg.tendsto.comp (hf.tendsto_nhdsWithin h)
#align continuous_within_at.comp ContinuousWithinAt.comp
theorem ContinuousWithinAt.comp' {g : β → γ} {f : α → β} {s : Set α} {t : Set β} {x : α}
(hg : ContinuousWithinAt g t (f x)) (hf : ContinuousWithinAt f s x) :
ContinuousWithinAt (g ∘ f) (s ∩ f ⁻¹' t) x :=
hg.comp (hf.mono inter_subset_left) inter_subset_right
#align continuous_within_at.comp' ContinuousWithinAt.comp'
theorem ContinuousAt.comp_continuousWithinAt {g : β → γ} {f : α → β} {s : Set α} {x : α}
(hg : ContinuousAt g (f x)) (hf : ContinuousWithinAt f s x) : ContinuousWithinAt (g ∘ f) s x :=
hg.continuousWithinAt.comp hf (mapsTo_univ _ _)
#align continuous_at.comp_continuous_within_at ContinuousAt.comp_continuousWithinAt
theorem ContinuousOn.comp {g : β → γ} {f : α → β} {s : Set α} {t : Set β} (hg : ContinuousOn g t)
(hf : ContinuousOn f s) (h : MapsTo f s t) : ContinuousOn (g ∘ f) s := fun x hx =>
ContinuousWithinAt.comp (hg _ (h hx)) (hf x hx) h
#align continuous_on.comp ContinuousOn.comp
@[fun_prop]
theorem ContinuousOn.comp'' {g : β → γ} {f : α → β} {s : Set α} {t : Set β} (hg : ContinuousOn g t)
(hf : ContinuousOn f s) (h : Set.MapsTo f s t) : ContinuousOn (fun x => g (f x)) s :=
ContinuousOn.comp hg hf h
theorem ContinuousOn.mono {f : α → β} {s t : Set α} (hf : ContinuousOn f s) (h : t ⊆ s) :
ContinuousOn f t := fun x hx => (hf x (h hx)).mono_left (nhdsWithin_mono _ h)
#align continuous_on.mono ContinuousOn.mono
theorem antitone_continuousOn {f : α → β} : Antitone (ContinuousOn f) := fun _s _t hst hf =>
hf.mono hst
#align antitone_continuous_on antitone_continuousOn
@[fun_prop]
theorem ContinuousOn.comp' {g : β → γ} {f : α → β} {s : Set α} {t : Set β} (hg : ContinuousOn g t)
(hf : ContinuousOn f s) : ContinuousOn (g ∘ f) (s ∩ f ⁻¹' t) :=
hg.comp (hf.mono inter_subset_left) inter_subset_right
#align continuous_on.comp' ContinuousOn.comp'
@[fun_prop]
theorem Continuous.continuousOn {f : α → β} {s : Set α} (h : Continuous f) : ContinuousOn f s := by
rw [continuous_iff_continuousOn_univ] at h
exact h.mono (subset_univ _)
#align continuous.continuous_on Continuous.continuousOn
theorem Continuous.continuousWithinAt {f : α → β} {s : Set α} {x : α} (h : Continuous f) :
ContinuousWithinAt f s x :=
h.continuousAt.continuousWithinAt
#align continuous.continuous_within_at Continuous.continuousWithinAt
theorem Continuous.comp_continuousOn {g : β → γ} {f : α → β} {s : Set α} (hg : Continuous g)
(hf : ContinuousOn f s) : ContinuousOn (g ∘ f) s :=
hg.continuousOn.comp hf (mapsTo_univ _ _)
#align continuous.comp_continuous_on Continuous.comp_continuousOn
@[fun_prop]
theorem Continuous.comp_continuousOn'
{α β γ : Type*} [TopologicalSpace α] [TopologicalSpace β] [TopologicalSpace γ] {g : β → γ}
{f : α → β} {s : Set α} (hg : Continuous g) (hf : ContinuousOn f s) :
ContinuousOn (fun x ↦ g (f x)) s :=
hg.comp_continuousOn hf
theorem ContinuousOn.comp_continuous {g : β → γ} {f : α → β} {s : Set β} (hg : ContinuousOn g s)
(hf : Continuous f) (hs : ∀ x, f x ∈ s) : Continuous (g ∘ f) := by
rw [continuous_iff_continuousOn_univ] at *
exact hg.comp hf fun x _ => hs x
#align continuous_on.comp_continuous ContinuousOn.comp_continuous
@[fun_prop]
theorem continuousOn_apply {ι : Type*} {π : ι → Type*} [∀ i, TopologicalSpace (π i)]
(i : ι) (s) : ContinuousOn (fun p : ∀ i, π i => p i) s :=
Continuous.continuousOn (continuous_apply i)
theorem ContinuousWithinAt.preimage_mem_nhdsWithin {f : α → β} {x : α} {s : Set α} {t : Set β}
(h : ContinuousWithinAt f s x) (ht : t ∈ 𝓝 (f x)) : f ⁻¹' t ∈ 𝓝[s] x :=
h ht
#align continuous_within_at.preimage_mem_nhds_within ContinuousWithinAt.preimage_mem_nhdsWithin
theorem Set.LeftInvOn.map_nhdsWithin_eq {f : α → β} {g : β → α} {x : β} {s : Set β}
(h : LeftInvOn f g s) (hx : f (g x) = x) (hf : ContinuousWithinAt f (g '' s) (g x))
(hg : ContinuousWithinAt g s x) : map g (𝓝[s] x) = 𝓝[g '' s] g x := by
apply le_antisymm
· exact hg.tendsto_nhdsWithin (mapsTo_image _ _)
· have A : g ∘ f =ᶠ[𝓝[g '' s] g x] id :=
h.rightInvOn_image.eqOn.eventuallyEq_of_mem self_mem_nhdsWithin
refine le_map_of_right_inverse A ?_
simpa only [hx] using hf.tendsto_nhdsWithin (h.mapsTo (surjOn_image _ _))
#align set.left_inv_on.map_nhds_within_eq Set.LeftInvOn.map_nhdsWithin_eq
theorem Function.LeftInverse.map_nhds_eq {f : α → β} {g : β → α} {x : β}
(h : Function.LeftInverse f g) (hf : ContinuousWithinAt f (range g) (g x))
(hg : ContinuousAt g x) : map g (𝓝 x) = 𝓝[range g] g x := by
simpa only [nhdsWithin_univ, image_univ] using
(h.leftInvOn univ).map_nhdsWithin_eq (h x) (by rwa [image_univ]) hg.continuousWithinAt
#align function.left_inverse.map_nhds_eq Function.LeftInverse.map_nhds_eq
theorem ContinuousWithinAt.preimage_mem_nhdsWithin' {f : α → β} {x : α} {s : Set α} {t : Set β}
(h : ContinuousWithinAt f s x) (ht : t ∈ 𝓝[f '' s] f x) : f ⁻¹' t ∈ 𝓝[s] x :=
h.tendsto_nhdsWithin (mapsTo_image _ _) ht
#align continuous_within_at.preimage_mem_nhds_within' ContinuousWithinAt.preimage_mem_nhdsWithin'
theorem ContinuousWithinAt.preimage_mem_nhdsWithin''
{f : α → β} {x : α} {y : β} {s t : Set β}
(h : ContinuousWithinAt f (f ⁻¹' s) x) (ht : t ∈ 𝓝[s] y) (hxy : y = f x) :
f ⁻¹' t ∈ 𝓝[f ⁻¹' s] x := by
rw [hxy] at ht
exact h.preimage_mem_nhdsWithin' (nhdsWithin_mono _ (image_preimage_subset f s) ht)
theorem Filter.EventuallyEq.congr_continuousWithinAt {f g : α → β} {s : Set α} {x : α}
(h : f =ᶠ[𝓝[s] x] g) (hx : f x = g x) :
ContinuousWithinAt f s x ↔ ContinuousWithinAt g s x := by
rw [ContinuousWithinAt, hx, tendsto_congr' h, ContinuousWithinAt]
#align filter.eventually_eq.congr_continuous_within_at Filter.EventuallyEq.congr_continuousWithinAt
theorem ContinuousWithinAt.congr_of_eventuallyEq {f f₁ : α → β} {s : Set α} {x : α}
(h : ContinuousWithinAt f s x) (h₁ : f₁ =ᶠ[𝓝[s] x] f) (hx : f₁ x = f x) :
ContinuousWithinAt f₁ s x :=
(h₁.congr_continuousWithinAt hx).2 h
#align continuous_within_at.congr_of_eventually_eq ContinuousWithinAt.congr_of_eventuallyEq
theorem ContinuousWithinAt.congr {f f₁ : α → β} {s : Set α} {x : α} (h : ContinuousWithinAt f s x)
(h₁ : ∀ y ∈ s, f₁ y = f y) (hx : f₁ x = f x) : ContinuousWithinAt f₁ s x :=
h.congr_of_eventuallyEq (mem_of_superset self_mem_nhdsWithin h₁) hx
#align continuous_within_at.congr ContinuousWithinAt.congr
theorem ContinuousWithinAt.congr_mono {f g : α → β} {s s₁ : Set α} {x : α}
(h : ContinuousWithinAt f s x) (h' : EqOn g f s₁) (h₁ : s₁ ⊆ s) (hx : g x = f x) :
ContinuousWithinAt g s₁ x :=
(h.mono h₁).congr h' hx
#align continuous_within_at.congr_mono ContinuousWithinAt.congr_mono
@[fun_prop]
theorem continuousOn_const {s : Set α} {c : β} : ContinuousOn (fun _ => c) s :=
continuous_const.continuousOn
#align continuous_on_const continuousOn_const
theorem continuousWithinAt_const {b : β} {s : Set α} {x : α} :
ContinuousWithinAt (fun _ : α => b) s x :=
continuous_const.continuousWithinAt
#align continuous_within_at_const continuousWithinAt_const
theorem continuousOn_id {s : Set α} : ContinuousOn id s :=
continuous_id.continuousOn
#align continuous_on_id continuousOn_id
@[fun_prop]
theorem continuousOn_id' (s : Set α) : ContinuousOn (fun x : α => x) s := continuousOn_id
theorem continuousWithinAt_id {s : Set α} {x : α} : ContinuousWithinAt id s x :=
continuous_id.continuousWithinAt
#align continuous_within_at_id continuousWithinAt_id
theorem continuousOn_open_iff {f : α → β} {s : Set α} (hs : IsOpen s) :
ContinuousOn f s ↔ ∀ t, IsOpen t → IsOpen (s ∩ f ⁻¹' t) := by
rw [continuousOn_iff']
constructor
· intro h t ht
rcases h t ht with ⟨u, u_open, hu⟩
rw [inter_comm, hu]
apply IsOpen.inter u_open hs
· intro h t ht
refine ⟨s ∩ f ⁻¹' t, h t ht, ?_⟩
rw [@inter_comm _ s (f ⁻¹' t), inter_assoc, inter_self]
#align continuous_on_open_iff continuousOn_open_iff
theorem ContinuousOn.isOpen_inter_preimage {f : α → β} {s : Set α} {t : Set β}
(hf : ContinuousOn f s) (hs : IsOpen s) (ht : IsOpen t) : IsOpen (s ∩ f ⁻¹' t) :=
(continuousOn_open_iff hs).1 hf t ht
#align continuous_on.preimage_open_of_open ContinuousOn.isOpen_inter_preimage
theorem ContinuousOn.isOpen_preimage {f : α → β} {s : Set α} {t : Set β} (h : ContinuousOn f s)
(hs : IsOpen s) (hp : f ⁻¹' t ⊆ s) (ht : IsOpen t) : IsOpen (f ⁻¹' t) := by
convert (continuousOn_open_iff hs).mp h t ht
rw [inter_comm, inter_eq_self_of_subset_left hp]
#align continuous_on.is_open_preimage ContinuousOn.isOpen_preimage
theorem ContinuousOn.preimage_isClosed_of_isClosed {f : α → β} {s : Set α} {t : Set β}
(hf : ContinuousOn f s) (hs : IsClosed s) (ht : IsClosed t) : IsClosed (s ∩ f ⁻¹' t) := by
rcases continuousOn_iff_isClosed.1 hf t ht with ⟨u, hu⟩
rw [inter_comm, hu.2]
apply IsClosed.inter hu.1 hs
#align continuous_on.preimage_closed_of_closed ContinuousOn.preimage_isClosed_of_isClosed
theorem ContinuousOn.preimage_interior_subset_interior_preimage {f : α → β} {s : Set α} {t : Set β}
(hf : ContinuousOn f s) (hs : IsOpen s) : s ∩ f ⁻¹' interior t ⊆ s ∩ interior (f ⁻¹' t) :=
calc
s ∩ f ⁻¹' interior t ⊆ interior (s ∩ f ⁻¹' t) :=
interior_maximal (inter_subset_inter (Subset.refl _) (preimage_mono interior_subset))
(hf.isOpen_inter_preimage hs isOpen_interior)
_ = s ∩ interior (f ⁻¹' t) := by rw [interior_inter, hs.interior_eq]
#align continuous_on.preimage_interior_subset_interior_preimage ContinuousOn.preimage_interior_subset_interior_preimage
theorem continuousOn_of_locally_continuousOn {f : α → β} {s : Set α}
(h : ∀ x ∈ s, ∃ t, IsOpen t ∧ x ∈ t ∧ ContinuousOn f (s ∩ t)) : ContinuousOn f s := by
intro x xs
rcases h x xs with ⟨t, open_t, xt, ct⟩
have := ct x ⟨xs, xt⟩
rwa [ContinuousWithinAt, ← nhdsWithin_restrict _ xt open_t] at this
#align continuous_on_of_locally_continuous_on continuousOn_of_locally_continuousOn
-- Porting note (#10756): new lemma
theorem continuousOn_to_generateFrom_iff {s : Set α} {T : Set (Set β)} {f : α → β} :
@ContinuousOn α β _ (.generateFrom T) f s ↔ ∀ x ∈ s, ∀ t ∈ T, f x ∈ t → f ⁻¹' t ∈ 𝓝[s] x :=
forall₂_congr fun x _ => by
delta ContinuousWithinAt
simp only [TopologicalSpace.nhds_generateFrom, tendsto_iInf, tendsto_principal, mem_setOf_eq,
and_imp]
exact forall_congr' fun t => forall_swap
-- Porting note: dropped an unneeded assumption
theorem continuousOn_isOpen_of_generateFrom {β : Type*} {s : Set α} {T : Set (Set β)} {f : α → β}
(h : ∀ t ∈ T, IsOpen (s ∩ f ⁻¹' t)) :
@ContinuousOn α β _ (.generateFrom T) f s :=
continuousOn_to_generateFrom_iff.2 fun _x hx t ht hxt => mem_nhdsWithin.2
⟨_, h t ht, ⟨hx, hxt⟩, fun _y hy => hy.1.2⟩
#align continuous_on_open_of_generate_from continuousOn_isOpen_of_generateFromₓ
theorem ContinuousWithinAt.prod {f : α → β} {g : α → γ} {s : Set α} {x : α}
(hf : ContinuousWithinAt f s x) (hg : ContinuousWithinAt g s x) :
ContinuousWithinAt (fun x => (f x, g x)) s x :=
hf.prod_mk_nhds hg
#align continuous_within_at.prod ContinuousWithinAt.prod
@[fun_prop]
theorem ContinuousOn.prod {f : α → β} {g : α → γ} {s : Set α} (hf : ContinuousOn f s)
(hg : ContinuousOn g s) : ContinuousOn (fun x => (f x, g x)) s := fun x hx =>
ContinuousWithinAt.prod (hf x hx) (hg x hx)
#align continuous_on.prod ContinuousOn.prod
theorem ContinuousAt.comp₂_continuousWithinAt {f : β × γ → δ} {g : α → β} {h : α → γ} {x : α}
{s : Set α} (hf : ContinuousAt f (g x, h x)) (hg : ContinuousWithinAt g s x)
(hh : ContinuousWithinAt h s x) :
ContinuousWithinAt (fun x ↦ f (g x, h x)) s x :=
ContinuousAt.comp_continuousWithinAt hf (hg.prod hh)
theorem ContinuousAt.comp₂_continuousWithinAt_of_eq {f : β × γ → δ} {g : α → β}
{h : α → γ} {x : α} {s : Set α} {y : β × γ} (hf : ContinuousAt f y)
(hg : ContinuousWithinAt g s x) (hh : ContinuousWithinAt h s x) (e : (g x, h x) = y) :
ContinuousWithinAt (fun x ↦ f (g x, h x)) s x := by
rw [← e] at hf
exact hf.comp₂_continuousWithinAt hg hh
theorem Inducing.continuousWithinAt_iff {f : α → β} {g : β → γ} (hg : Inducing g) {s : Set α}
{x : α} : ContinuousWithinAt f s x ↔ ContinuousWithinAt (g ∘ f) s x := by
simp_rw [ContinuousWithinAt, Inducing.tendsto_nhds_iff hg]; rfl
#align inducing.continuous_within_at_iff Inducing.continuousWithinAt_iff
theorem Inducing.continuousOn_iff {f : α → β} {g : β → γ} (hg : Inducing g) {s : Set α} :
ContinuousOn f s ↔ ContinuousOn (g ∘ f) s := by
simp_rw [ContinuousOn, hg.continuousWithinAt_iff]
#align inducing.continuous_on_iff Inducing.continuousOn_iff
theorem Embedding.continuousOn_iff {f : α → β} {g : β → γ} (hg : Embedding g) {s : Set α} :
ContinuousOn f s ↔ ContinuousOn (g ∘ f) s :=
Inducing.continuousOn_iff hg.1
#align embedding.continuous_on_iff Embedding.continuousOn_iff
theorem Embedding.map_nhdsWithin_eq {f : α → β} (hf : Embedding f) (s : Set α) (x : α) :
map f (𝓝[s] x) = 𝓝[f '' s] f x := by
rw [nhdsWithin, Filter.map_inf hf.inj, hf.map_nhds_eq, map_principal, ← nhdsWithin_inter',
inter_eq_self_of_subset_right (image_subset_range _ _)]
#align embedding.map_nhds_within_eq Embedding.map_nhdsWithin_eq
theorem OpenEmbedding.map_nhdsWithin_preimage_eq {f : α → β} (hf : OpenEmbedding f) (s : Set β)
(x : α) : map f (𝓝[f ⁻¹' s] x) = 𝓝[s] f x := by
rw [hf.toEmbedding.map_nhdsWithin_eq, image_preimage_eq_inter_range]
apply nhdsWithin_eq_nhdsWithin (mem_range_self _) hf.isOpen_range
rw [inter_assoc, inter_self]
#align open_embedding.map_nhds_within_preimage_eq OpenEmbedding.map_nhdsWithin_preimage_eq
| Mathlib/Topology/ContinuousOn.lean | 1,188 | 1,192 | theorem continuousWithinAt_of_not_mem_closure {f : α → β} {s : Set α} {x : α} (hx : x ∉ closure s) :
ContinuousWithinAt f s x := by |
rw [mem_closure_iff_nhdsWithin_neBot, not_neBot] at hx
rw [ContinuousWithinAt, hx]
exact tendsto_bot
|
/-
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, Violeta Hernández Palacios
-/
import Mathlib.SetTheory.Ordinal.Basic
import Mathlib.Data.Nat.SuccPred
#align_import set_theory.ordinal.arithmetic from "leanprover-community/mathlib"@"31b269b60935483943542d547a6dd83a66b37dc7"
/-!
# Ordinal arithmetic
Ordinals have an addition (corresponding to disjoint union) that turns them into an additive
monoid, and a multiplication (corresponding to the lexicographic order on the product) that turns
them into a monoid. One can also define correspondingly a subtraction, a division, a successor
function, a power function and a logarithm function.
We also define limit ordinals and prove the basic induction principle on ordinals separating
successor ordinals and limit ordinals, in `limitRecOn`.
## Main definitions and results
* `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`.
* `o₁ - o₂` is the unique ordinal `o` such that `o₂ + o = o₁`, when `o₂ ≤ o₁`.
* `o₁ * o₂` is the lexicographic order on `o₂ × o₁`.
* `o₁ / o₂` is the ordinal `o` such that `o₁ = o₂ * o + o'` with `o' < o₂`. We also define the
divisibility predicate, and a modulo operation.
* `Order.succ o = o + 1` is the successor of `o`.
* `pred o` if the predecessor of `o`. If `o` is not a successor, we set `pred o = o`.
We discuss the properties of casts of natural numbers of and of `ω` with respect to these
operations.
Some properties of the operations are also used to discuss general tools on ordinals:
* `IsLimit o`: an ordinal is a limit ordinal if it is neither `0` nor a successor.
* `limitRecOn` is the main induction principle of ordinals: if one can prove a property by
induction at successor ordinals and at limit ordinals, then it holds for all ordinals.
* `IsNormal`: a function `f : Ordinal → Ordinal` satisfies `IsNormal` if it is strictly increasing
and order-continuous, i.e., the image `f o` of a limit ordinal `o` is the sup of `f a` for
`a < o`.
* `enumOrd`: enumerates an unbounded set of ordinals by the ordinals themselves.
* `sup`, `lsub`: the supremum / least strict upper bound of an indexed family of ordinals in
`Type u`, as an ordinal in `Type u`.
* `bsup`, `blsub`: the supremum / least strict upper bound of a set of ordinals indexed by ordinals
less than a given ordinal `o`.
Various other basic arithmetic results are given in `Principal.lean` instead.
-/
assert_not_exists Field
assert_not_exists Module
noncomputable section
open Function Cardinal Set Equiv Order
open scoped Classical
open Cardinal Ordinal
universe u v w
namespace Ordinal
variable {α : Type*} {β : Type*} {γ : Type*} {r : α → α → Prop} {s : β → β → Prop}
{t : γ → γ → Prop}
/-! ### Further properties of addition on ordinals -/
@[simp]
theorem lift_add (a b : Ordinal.{v}) : lift.{u} (a + b) = lift.{u} a + lift.{u} b :=
Quotient.inductionOn₂ a b fun ⟨_α, _r, _⟩ ⟨_β, _s, _⟩ =>
Quotient.sound
⟨(RelIso.preimage Equiv.ulift _).trans
(RelIso.sumLexCongr (RelIso.preimage Equiv.ulift _) (RelIso.preimage Equiv.ulift _)).symm⟩
#align ordinal.lift_add Ordinal.lift_add
@[simp]
theorem lift_succ (a : Ordinal.{v}) : lift.{u} (succ a) = succ (lift.{u} a) := by
rw [← add_one_eq_succ, lift_add, lift_one]
rfl
#align ordinal.lift_succ Ordinal.lift_succ
instance add_contravariantClass_le : ContravariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· ≤ ·) :=
⟨fun a b c =>
inductionOn a fun α r hr =>
inductionOn b fun β₁ s₁ hs₁ =>
inductionOn c fun β₂ s₂ hs₂ ⟨f⟩ =>
⟨have fl : ∀ a, f (Sum.inl a) = Sum.inl a := fun a => by
simpa only [InitialSeg.trans_apply, InitialSeg.leAdd_apply] using
@InitialSeg.eq _ _ _ _ _
((InitialSeg.leAdd r s₁).trans f) (InitialSeg.leAdd r s₂) a
have : ∀ b, { b' // f (Sum.inr b) = Sum.inr b' } := by
intro b; cases e : f (Sum.inr b)
· rw [← fl] at e
have := f.inj' e
contradiction
· exact ⟨_, rfl⟩
let g (b) := (this b).1
have fr : ∀ b, f (Sum.inr b) = Sum.inr (g b) := fun b => (this b).2
⟨⟨⟨g, fun x y h => by
injection f.inj' (by rw [fr, fr, h] : f (Sum.inr x) = f (Sum.inr y))⟩,
@fun a b => by
-- Porting note:
-- `relEmbedding.coe_fn_to_embedding` & `initial_seg.coe_fn_to_rel_embedding`
-- → `InitialSeg.coe_coe_fn`
simpa only [Sum.lex_inr_inr, fr, InitialSeg.coe_coe_fn, Embedding.coeFn_mk] using
@RelEmbedding.map_rel_iff _ _ _ _ f.toRelEmbedding (Sum.inr a) (Sum.inr b)⟩,
fun a b H => by
rcases f.init (by rw [fr] <;> exact Sum.lex_inr_inr.2 H) with ⟨a' | a', h⟩
· rw [fl] at h
cases h
· rw [fr] at h
exact ⟨a', Sum.inr.inj h⟩⟩⟩⟩
#align ordinal.add_contravariant_class_le Ordinal.add_contravariantClass_le
theorem add_left_cancel (a) {b c : Ordinal} : a + b = a + c ↔ b = c := by
simp only [le_antisymm_iff, add_le_add_iff_left]
#align ordinal.add_left_cancel Ordinal.add_left_cancel
private theorem add_lt_add_iff_left' (a) {b c : Ordinal} : a + b < a + c ↔ b < c := by
rw [← not_le, ← not_le, add_le_add_iff_left]
instance add_covariantClass_lt : CovariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· < ·) :=
⟨fun a _b _c => (add_lt_add_iff_left' a).2⟩
#align ordinal.add_covariant_class_lt Ordinal.add_covariantClass_lt
instance add_contravariantClass_lt : ContravariantClass Ordinal.{u} Ordinal.{u} (· + ·) (· < ·) :=
⟨fun a _b _c => (add_lt_add_iff_left' a).1⟩
#align ordinal.add_contravariant_class_lt Ordinal.add_contravariantClass_lt
instance add_swap_contravariantClass_lt :
ContravariantClass Ordinal.{u} Ordinal.{u} (swap (· + ·)) (· < ·) :=
⟨fun _a _b _c => lt_imp_lt_of_le_imp_le fun h => add_le_add_right h _⟩
#align ordinal.add_swap_contravariant_class_lt Ordinal.add_swap_contravariantClass_lt
theorem add_le_add_iff_right {a b : Ordinal} : ∀ n : ℕ, a + n ≤ b + n ↔ a ≤ b
| 0 => by simp
| n + 1 => by
simp only [natCast_succ, add_succ, add_succ, succ_le_succ_iff, add_le_add_iff_right]
#align ordinal.add_le_add_iff_right Ordinal.add_le_add_iff_right
theorem add_right_cancel {a b : Ordinal} (n : ℕ) : a + n = b + n ↔ a = b := by
simp only [le_antisymm_iff, add_le_add_iff_right]
#align ordinal.add_right_cancel Ordinal.add_right_cancel
theorem add_eq_zero_iff {a b : Ordinal} : a + b = 0 ↔ a = 0 ∧ b = 0 :=
inductionOn a fun α r _ =>
inductionOn b fun β s _ => by
simp_rw [← type_sum_lex, type_eq_zero_iff_isEmpty]
exact isEmpty_sum
#align ordinal.add_eq_zero_iff Ordinal.add_eq_zero_iff
theorem left_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : a = 0 :=
(add_eq_zero_iff.1 h).1
#align ordinal.left_eq_zero_of_add_eq_zero Ordinal.left_eq_zero_of_add_eq_zero
theorem right_eq_zero_of_add_eq_zero {a b : Ordinal} (h : a + b = 0) : b = 0 :=
(add_eq_zero_iff.1 h).2
#align ordinal.right_eq_zero_of_add_eq_zero Ordinal.right_eq_zero_of_add_eq_zero
/-! ### The predecessor of an ordinal -/
/-- The ordinal predecessor of `o` is `o'` if `o = succ o'`,
and `o` otherwise. -/
def pred (o : Ordinal) : Ordinal :=
if h : ∃ a, o = succ a then Classical.choose h else o
#align ordinal.pred Ordinal.pred
@[simp]
theorem pred_succ (o) : pred (succ o) = o := by
have h : ∃ a, succ o = succ a := ⟨_, rfl⟩;
simpa only [pred, dif_pos h] using (succ_injective <| Classical.choose_spec h).symm
#align ordinal.pred_succ Ordinal.pred_succ
theorem pred_le_self (o) : pred o ≤ o :=
if h : ∃ a, o = succ a then by
let ⟨a, e⟩ := h
rw [e, pred_succ]; exact le_succ a
else by rw [pred, dif_neg h]
#align ordinal.pred_le_self Ordinal.pred_le_self
theorem pred_eq_iff_not_succ {o} : pred o = o ↔ ¬∃ a, o = succ a :=
⟨fun e ⟨a, e'⟩ => by rw [e', pred_succ] at e; exact (lt_succ a).ne e, fun h => dif_neg h⟩
#align ordinal.pred_eq_iff_not_succ Ordinal.pred_eq_iff_not_succ
theorem pred_eq_iff_not_succ' {o} : pred o = o ↔ ∀ a, o ≠ succ a := by
simpa using pred_eq_iff_not_succ
#align ordinal.pred_eq_iff_not_succ' Ordinal.pred_eq_iff_not_succ'
theorem pred_lt_iff_is_succ {o} : pred o < o ↔ ∃ a, o = succ a :=
Iff.trans (by simp only [le_antisymm_iff, pred_le_self, true_and_iff, not_le])
(iff_not_comm.1 pred_eq_iff_not_succ).symm
#align ordinal.pred_lt_iff_is_succ Ordinal.pred_lt_iff_is_succ
@[simp]
theorem pred_zero : pred 0 = 0 :=
pred_eq_iff_not_succ'.2 fun a => (succ_ne_zero a).symm
#align ordinal.pred_zero Ordinal.pred_zero
theorem succ_pred_iff_is_succ {o} : succ (pred o) = o ↔ ∃ a, o = succ a :=
⟨fun e => ⟨_, e.symm⟩, fun ⟨a, e⟩ => by simp only [e, pred_succ]⟩
#align ordinal.succ_pred_iff_is_succ Ordinal.succ_pred_iff_is_succ
theorem succ_lt_of_not_succ {o b : Ordinal} (h : ¬∃ a, o = succ a) : succ b < o ↔ b < o :=
⟨(lt_succ b).trans, fun l => lt_of_le_of_ne (succ_le_of_lt l) fun e => h ⟨_, e.symm⟩⟩
#align ordinal.succ_lt_of_not_succ Ordinal.succ_lt_of_not_succ
theorem lt_pred {a b} : a < pred b ↔ succ a < b :=
if h : ∃ a, b = succ a then by
let ⟨c, e⟩ := h
rw [e, pred_succ, succ_lt_succ_iff]
else by simp only [pred, dif_neg h, succ_lt_of_not_succ h]
#align ordinal.lt_pred Ordinal.lt_pred
theorem pred_le {a b} : pred a ≤ b ↔ a ≤ succ b :=
le_iff_le_iff_lt_iff_lt.2 lt_pred
#align ordinal.pred_le Ordinal.pred_le
@[simp]
theorem lift_is_succ {o : Ordinal.{v}} : (∃ a, lift.{u} o = succ a) ↔ ∃ a, o = succ a :=
⟨fun ⟨a, h⟩ =>
let ⟨b, e⟩ := lift_down <| show a ≤ lift.{u} o from le_of_lt <| h.symm ▸ lt_succ a
⟨b, lift_inj.1 <| by rw [h, ← e, lift_succ]⟩,
fun ⟨a, h⟩ => ⟨lift.{u} a, by simp only [h, lift_succ]⟩⟩
#align ordinal.lift_is_succ Ordinal.lift_is_succ
@[simp]
theorem lift_pred (o : Ordinal.{v}) : lift.{u} (pred o) = pred (lift.{u} o) :=
if h : ∃ a, o = succ a then by cases' h with a e; simp only [e, pred_succ, lift_succ]
else by rw [pred_eq_iff_not_succ.2 h, pred_eq_iff_not_succ.2 (mt lift_is_succ.1 h)]
#align ordinal.lift_pred Ordinal.lift_pred
/-! ### Limit ordinals -/
/-- A limit ordinal is an ordinal which is not zero and not a successor. -/
def IsLimit (o : Ordinal) : Prop :=
o ≠ 0 ∧ ∀ a < o, succ a < o
#align ordinal.is_limit Ordinal.IsLimit
theorem IsLimit.isSuccLimit {o} (h : IsLimit o) : IsSuccLimit o := isSuccLimit_iff_succ_lt.mpr h.2
theorem IsLimit.succ_lt {o a : Ordinal} (h : IsLimit o) : a < o → succ a < o :=
h.2 a
#align ordinal.is_limit.succ_lt Ordinal.IsLimit.succ_lt
theorem isSuccLimit_zero : IsSuccLimit (0 : Ordinal) := isSuccLimit_bot
theorem not_zero_isLimit : ¬IsLimit 0
| ⟨h, _⟩ => h rfl
#align ordinal.not_zero_is_limit Ordinal.not_zero_isLimit
theorem not_succ_isLimit (o) : ¬IsLimit (succ o)
| ⟨_, h⟩ => lt_irrefl _ (h _ (lt_succ o))
#align ordinal.not_succ_is_limit Ordinal.not_succ_isLimit
theorem not_succ_of_isLimit {o} (h : IsLimit o) : ¬∃ a, o = succ a
| ⟨a, e⟩ => not_succ_isLimit a (e ▸ h)
#align ordinal.not_succ_of_is_limit Ordinal.not_succ_of_isLimit
theorem succ_lt_of_isLimit {o a : Ordinal} (h : IsLimit o) : succ a < o ↔ a < o :=
⟨(lt_succ a).trans, h.2 _⟩
#align ordinal.succ_lt_of_is_limit Ordinal.succ_lt_of_isLimit
theorem le_succ_of_isLimit {o} (h : IsLimit o) {a} : o ≤ succ a ↔ o ≤ a :=
le_iff_le_iff_lt_iff_lt.2 <| succ_lt_of_isLimit h
#align ordinal.le_succ_of_is_limit Ordinal.le_succ_of_isLimit
theorem limit_le {o} (h : IsLimit o) {a} : o ≤ a ↔ ∀ x < o, x ≤ a :=
⟨fun h _x l => l.le.trans h, fun H =>
(le_succ_of_isLimit h).1 <| le_of_not_lt fun hn => not_lt_of_le (H _ hn) (lt_succ a)⟩
#align ordinal.limit_le Ordinal.limit_le
theorem lt_limit {o} (h : IsLimit o) {a} : a < o ↔ ∃ x < o, a < x := by
-- Porting note: `bex_def` is required.
simpa only [not_forall₂, not_le, bex_def] using not_congr (@limit_le _ h a)
#align ordinal.lt_limit Ordinal.lt_limit
@[simp]
theorem lift_isLimit (o) : IsLimit (lift o) ↔ IsLimit o :=
and_congr (not_congr <| by simpa only [lift_zero] using @lift_inj o 0)
⟨fun H a h => lift_lt.1 <| by simpa only [lift_succ] using H _ (lift_lt.2 h), fun H a h => by
obtain ⟨a', rfl⟩ := lift_down h.le
rw [← lift_succ, lift_lt]
exact H a' (lift_lt.1 h)⟩
#align ordinal.lift_is_limit Ordinal.lift_isLimit
theorem IsLimit.pos {o : Ordinal} (h : IsLimit o) : 0 < o :=
lt_of_le_of_ne (Ordinal.zero_le _) h.1.symm
#align ordinal.is_limit.pos Ordinal.IsLimit.pos
theorem IsLimit.one_lt {o : Ordinal} (h : IsLimit o) : 1 < o := by
simpa only [succ_zero] using h.2 _ h.pos
#align ordinal.is_limit.one_lt Ordinal.IsLimit.one_lt
theorem IsLimit.nat_lt {o : Ordinal} (h : IsLimit o) : ∀ n : ℕ, (n : Ordinal) < o
| 0 => h.pos
| n + 1 => h.2 _ (IsLimit.nat_lt h n)
#align ordinal.is_limit.nat_lt Ordinal.IsLimit.nat_lt
theorem zero_or_succ_or_limit (o : Ordinal) : o = 0 ∨ (∃ a, o = succ a) ∨ IsLimit o :=
if o0 : o = 0 then Or.inl o0
else
if h : ∃ a, o = succ a then Or.inr (Or.inl h)
else Or.inr <| Or.inr ⟨o0, fun _a => (succ_lt_of_not_succ h).2⟩
#align ordinal.zero_or_succ_or_limit Ordinal.zero_or_succ_or_limit
/-- Main induction principle of ordinals: if one can prove a property by
induction at successor ordinals and at limit ordinals, then it holds for all ordinals. -/
@[elab_as_elim]
def limitRecOn {C : Ordinal → Sort*} (o : Ordinal) (H₁ : C 0) (H₂ : ∀ o, C o → C (succ o))
(H₃ : ∀ o, IsLimit o → (∀ o' < o, C o') → C o) : C o :=
SuccOrder.limitRecOn o (fun o _ ↦ H₂ o) fun o hl ↦
if h : o = 0 then fun _ ↦ h ▸ H₁ else H₃ o ⟨h, fun _ ↦ hl.succ_lt⟩
#align ordinal.limit_rec_on Ordinal.limitRecOn
@[simp]
theorem limitRecOn_zero {C} (H₁ H₂ H₃) : @limitRecOn C 0 H₁ H₂ H₃ = H₁ := by
rw [limitRecOn, SuccOrder.limitRecOn_limit _ _ isSuccLimit_zero, dif_pos rfl]
#align ordinal.limit_rec_on_zero Ordinal.limitRecOn_zero
@[simp]
theorem limitRecOn_succ {C} (o H₁ H₂ H₃) :
@limitRecOn C (succ o) H₁ H₂ H₃ = H₂ o (@limitRecOn C o H₁ H₂ H₃) := by
simp_rw [limitRecOn, SuccOrder.limitRecOn_succ _ _ (not_isMax _)]
#align ordinal.limit_rec_on_succ Ordinal.limitRecOn_succ
@[simp]
theorem limitRecOn_limit {C} (o H₁ H₂ H₃ h) :
@limitRecOn C o H₁ H₂ H₃ = H₃ o h fun x _h => @limitRecOn C x H₁ H₂ H₃ := by
simp_rw [limitRecOn, SuccOrder.limitRecOn_limit _ _ h.isSuccLimit, dif_neg h.1]
#align ordinal.limit_rec_on_limit Ordinal.limitRecOn_limit
instance orderTopOutSucc (o : Ordinal) : OrderTop (succ o).out.α :=
@OrderTop.mk _ _ (Top.mk _) le_enum_succ
#align ordinal.order_top_out_succ Ordinal.orderTopOutSucc
theorem enum_succ_eq_top {o : Ordinal} :
enum (· < ·) o
(by
rw [type_lt]
exact lt_succ o) =
(⊤ : (succ o).out.α) :=
rfl
#align ordinal.enum_succ_eq_top Ordinal.enum_succ_eq_top
theorem has_succ_of_type_succ_lt {α} {r : α → α → Prop} [wo : IsWellOrder α r]
(h : ∀ a < type r, succ a < type r) (x : α) : ∃ y, r x y := by
use enum r (succ (typein r x)) (h _ (typein_lt_type r x))
convert (enum_lt_enum (typein_lt_type r x)
(h _ (typein_lt_type r x))).mpr (lt_succ _); rw [enum_typein]
#align ordinal.has_succ_of_type_succ_lt Ordinal.has_succ_of_type_succ_lt
theorem out_no_max_of_succ_lt {o : Ordinal} (ho : ∀ a < o, succ a < o) : NoMaxOrder o.out.α :=
⟨has_succ_of_type_succ_lt (by rwa [type_lt])⟩
#align ordinal.out_no_max_of_succ_lt Ordinal.out_no_max_of_succ_lt
theorem bounded_singleton {r : α → α → Prop} [IsWellOrder α r] (hr : (type r).IsLimit) (x) :
Bounded r {x} := by
refine ⟨enum r (succ (typein r x)) (hr.2 _ (typein_lt_type r x)), ?_⟩
intro b hb
rw [mem_singleton_iff.1 hb]
nth_rw 1 [← enum_typein r x]
rw [@enum_lt_enum _ r]
apply lt_succ
#align ordinal.bounded_singleton Ordinal.bounded_singleton
-- Porting note: `· < ·` requires a type ascription for an `IsWellOrder` instance.
theorem type_subrel_lt (o : Ordinal.{u}) :
type (Subrel ((· < ·) : Ordinal → Ordinal → Prop) { o' : Ordinal | o' < o })
= Ordinal.lift.{u + 1} o := by
refine Quotient.inductionOn o ?_
rintro ⟨α, r, wo⟩; apply Quotient.sound
-- Porting note: `symm; refine' [term]` → `refine' [term].symm`
constructor; refine ((RelIso.preimage Equiv.ulift r).trans (enumIso r).symm).symm
#align ordinal.type_subrel_lt Ordinal.type_subrel_lt
theorem mk_initialSeg (o : Ordinal.{u}) :
#{ o' : Ordinal | o' < o } = Cardinal.lift.{u + 1} o.card := by
rw [lift_card, ← type_subrel_lt, card_type]
#align ordinal.mk_initial_seg Ordinal.mk_initialSeg
/-! ### Normal ordinal functions -/
/-- A normal ordinal function is a strictly increasing function which is
order-continuous, i.e., the image `f o` of a limit ordinal `o` is the sup of `f a` for
`a < o`. -/
def IsNormal (f : Ordinal → Ordinal) : Prop :=
(∀ o, f o < f (succ o)) ∧ ∀ o, IsLimit o → ∀ a, f o ≤ a ↔ ∀ b < o, f b ≤ a
#align ordinal.is_normal Ordinal.IsNormal
theorem IsNormal.limit_le {f} (H : IsNormal f) :
∀ {o}, IsLimit o → ∀ {a}, f o ≤ a ↔ ∀ b < o, f b ≤ a :=
@H.2
#align ordinal.is_normal.limit_le Ordinal.IsNormal.limit_le
theorem IsNormal.limit_lt {f} (H : IsNormal f) {o} (h : IsLimit o) {a} :
a < f o ↔ ∃ b < o, a < f b :=
not_iff_not.1 <| by simpa only [exists_prop, not_exists, not_and, not_lt] using H.2 _ h a
#align ordinal.is_normal.limit_lt Ordinal.IsNormal.limit_lt
theorem IsNormal.strictMono {f} (H : IsNormal f) : StrictMono f := fun a b =>
limitRecOn b (Not.elim (not_lt_of_le <| Ordinal.zero_le _))
(fun _b IH h =>
(lt_or_eq_of_le (le_of_lt_succ h)).elim (fun h => (IH h).trans (H.1 _)) fun e => e ▸ H.1 _)
fun _b l _IH h => lt_of_lt_of_le (H.1 a) ((H.2 _ l _).1 le_rfl _ (l.2 _ h))
#align ordinal.is_normal.strict_mono Ordinal.IsNormal.strictMono
theorem IsNormal.monotone {f} (H : IsNormal f) : Monotone f :=
H.strictMono.monotone
#align ordinal.is_normal.monotone Ordinal.IsNormal.monotone
theorem isNormal_iff_strictMono_limit (f : Ordinal → Ordinal) :
IsNormal f ↔ StrictMono f ∧ ∀ o, IsLimit o → ∀ a, (∀ b < o, f b ≤ a) → f o ≤ a :=
⟨fun hf => ⟨hf.strictMono, fun a ha c => (hf.2 a ha c).2⟩, fun ⟨hs, hl⟩ =>
⟨fun a => hs (lt_succ a), fun a ha c =>
⟨fun hac _b hba => ((hs hba).trans_le hac).le, hl a ha c⟩⟩⟩
#align ordinal.is_normal_iff_strict_mono_limit Ordinal.isNormal_iff_strictMono_limit
theorem IsNormal.lt_iff {f} (H : IsNormal f) {a b} : f a < f b ↔ a < b :=
StrictMono.lt_iff_lt <| H.strictMono
#align ordinal.is_normal.lt_iff Ordinal.IsNormal.lt_iff
theorem IsNormal.le_iff {f} (H : IsNormal f) {a b} : f a ≤ f b ↔ a ≤ b :=
le_iff_le_iff_lt_iff_lt.2 H.lt_iff
#align ordinal.is_normal.le_iff Ordinal.IsNormal.le_iff
theorem IsNormal.inj {f} (H : IsNormal f) {a b} : f a = f b ↔ a = b := by
simp only [le_antisymm_iff, H.le_iff]
#align ordinal.is_normal.inj Ordinal.IsNormal.inj
theorem IsNormal.self_le {f} (H : IsNormal f) (a) : a ≤ f a :=
lt_wf.self_le_of_strictMono H.strictMono a
#align ordinal.is_normal.self_le Ordinal.IsNormal.self_le
theorem IsNormal.le_set {f o} (H : IsNormal f) (p : Set Ordinal) (p0 : p.Nonempty) (b)
(H₂ : ∀ o, b ≤ o ↔ ∀ a ∈ p, a ≤ o) : f b ≤ o ↔ ∀ a ∈ p, f a ≤ o :=
⟨fun h a pa => (H.le_iff.2 ((H₂ _).1 le_rfl _ pa)).trans h, fun h => by
-- Porting note: `refine'` didn't work well so `induction` is used
induction b using limitRecOn with
| H₁ =>
cases' p0 with x px
have := Ordinal.le_zero.1 ((H₂ _).1 (Ordinal.zero_le _) _ px)
rw [this] at px
exact h _ px
| H₂ S _ =>
rcases not_forall₂.1 (mt (H₂ S).2 <| (lt_succ S).not_le) with ⟨a, h₁, h₂⟩
exact (H.le_iff.2 <| succ_le_of_lt <| not_le.1 h₂).trans (h _ h₁)
| H₃ S L _ =>
refine (H.2 _ L _).2 fun a h' => ?_
rcases not_forall₂.1 (mt (H₂ a).2 h'.not_le) with ⟨b, h₁, h₂⟩
exact (H.le_iff.2 <| (not_le.1 h₂).le).trans (h _ h₁)⟩
#align ordinal.is_normal.le_set Ordinal.IsNormal.le_set
theorem IsNormal.le_set' {f o} (H : IsNormal f) (p : Set α) (p0 : p.Nonempty) (g : α → Ordinal) (b)
(H₂ : ∀ o, b ≤ o ↔ ∀ a ∈ p, g a ≤ o) : f b ≤ o ↔ ∀ a ∈ p, f (g a) ≤ o := by
simpa [H₂] using H.le_set (g '' p) (p0.image g) b
#align ordinal.is_normal.le_set' Ordinal.IsNormal.le_set'
theorem IsNormal.refl : IsNormal id :=
⟨lt_succ, fun _o l _a => Ordinal.limit_le l⟩
#align ordinal.is_normal.refl Ordinal.IsNormal.refl
theorem IsNormal.trans {f g} (H₁ : IsNormal f) (H₂ : IsNormal g) : IsNormal (f ∘ g) :=
⟨fun _x => H₁.lt_iff.2 (H₂.1 _), fun o l _a =>
H₁.le_set' (· < o) ⟨0, l.pos⟩ g _ fun _c => H₂.2 _ l _⟩
#align ordinal.is_normal.trans Ordinal.IsNormal.trans
theorem IsNormal.isLimit {f} (H : IsNormal f) {o} (l : IsLimit o) : IsLimit (f o) :=
⟨ne_of_gt <| (Ordinal.zero_le _).trans_lt <| H.lt_iff.2 l.pos, fun _ h =>
let ⟨_b, h₁, h₂⟩ := (H.limit_lt l).1 h
(succ_le_of_lt h₂).trans_lt (H.lt_iff.2 h₁)⟩
#align ordinal.is_normal.is_limit Ordinal.IsNormal.isLimit
theorem IsNormal.le_iff_eq {f} (H : IsNormal f) {a} : f a ≤ a ↔ f a = a :=
(H.self_le a).le_iff_eq
#align ordinal.is_normal.le_iff_eq Ordinal.IsNormal.le_iff_eq
theorem add_le_of_limit {a b c : Ordinal} (h : IsLimit b) : a + b ≤ c ↔ ∀ b' < b, a + b' ≤ c :=
⟨fun h b' l => (add_le_add_left l.le _).trans h, fun H =>
le_of_not_lt <| by
-- Porting note: `induction` tactics are required because of the parser bug.
induction a using inductionOn with
| H α r =>
induction b using inductionOn with
| H β s =>
intro l
suffices ∀ x : β, Sum.Lex r s (Sum.inr x) (enum _ _ l) by
-- Porting note: `revert` & `intro` is required because `cases'` doesn't replace
-- `enum _ _ l` in `this`.
revert this; cases' enum _ _ l with x x <;> intro this
· cases this (enum s 0 h.pos)
· exact irrefl _ (this _)
intro x
rw [← typein_lt_typein (Sum.Lex r s), typein_enum]
have := H _ (h.2 _ (typein_lt_type s x))
rw [add_succ, succ_le_iff] at this
refine
(RelEmbedding.ofMonotone (fun a => ?_) fun a b => ?_).ordinal_type_le.trans_lt this
· rcases a with ⟨a | b, h⟩
· exact Sum.inl a
· exact Sum.inr ⟨b, by cases h; assumption⟩
· rcases a with ⟨a | a, h₁⟩ <;> rcases b with ⟨b | b, h₂⟩ <;> cases h₁ <;> cases h₂ <;>
rintro ⟨⟩ <;> constructor <;> assumption⟩
#align ordinal.add_le_of_limit Ordinal.add_le_of_limit
theorem add_isNormal (a : Ordinal) : IsNormal (a + ·) :=
⟨fun b => (add_lt_add_iff_left a).2 (lt_succ b), fun _b l _c => add_le_of_limit l⟩
#align ordinal.add_is_normal Ordinal.add_isNormal
theorem add_isLimit (a) {b} : IsLimit b → IsLimit (a + b) :=
(add_isNormal a).isLimit
#align ordinal.add_is_limit Ordinal.add_isLimit
alias IsLimit.add := add_isLimit
#align ordinal.is_limit.add Ordinal.IsLimit.add
/-! ### Subtraction on ordinals-/
/-- The set in the definition of subtraction is nonempty. -/
theorem sub_nonempty {a b : Ordinal} : { o | a ≤ b + o }.Nonempty :=
⟨a, le_add_left _ _⟩
#align ordinal.sub_nonempty Ordinal.sub_nonempty
/-- `a - b` is the unique ordinal satisfying `b + (a - b) = a` when `b ≤ a`. -/
instance sub : Sub Ordinal :=
⟨fun a b => sInf { o | a ≤ b + o }⟩
theorem le_add_sub (a b : Ordinal) : a ≤ b + (a - b) :=
csInf_mem sub_nonempty
#align ordinal.le_add_sub Ordinal.le_add_sub
theorem sub_le {a b c : Ordinal} : a - b ≤ c ↔ a ≤ b + c :=
⟨fun h => (le_add_sub a b).trans (add_le_add_left h _), fun h => csInf_le' h⟩
#align ordinal.sub_le Ordinal.sub_le
theorem lt_sub {a b c : Ordinal} : a < b - c ↔ c + a < b :=
lt_iff_lt_of_le_iff_le sub_le
#align ordinal.lt_sub Ordinal.lt_sub
theorem add_sub_cancel (a b : Ordinal) : a + b - a = b :=
le_antisymm (sub_le.2 <| le_rfl) ((add_le_add_iff_left a).1 <| le_add_sub _ _)
#align ordinal.add_sub_cancel Ordinal.add_sub_cancel
theorem sub_eq_of_add_eq {a b c : Ordinal} (h : a + b = c) : c - a = b :=
h ▸ add_sub_cancel _ _
#align ordinal.sub_eq_of_add_eq Ordinal.sub_eq_of_add_eq
theorem sub_le_self (a b : Ordinal) : a - b ≤ a :=
sub_le.2 <| le_add_left _ _
#align ordinal.sub_le_self Ordinal.sub_le_self
protected theorem add_sub_cancel_of_le {a b : Ordinal} (h : b ≤ a) : b + (a - b) = a :=
(le_add_sub a b).antisymm'
(by
rcases zero_or_succ_or_limit (a - b) with (e | ⟨c, e⟩ | l)
· simp only [e, add_zero, h]
· rw [e, add_succ, succ_le_iff, ← lt_sub, e]
exact lt_succ c
· exact (add_le_of_limit l).2 fun c l => (lt_sub.1 l).le)
#align ordinal.add_sub_cancel_of_le Ordinal.add_sub_cancel_of_le
theorem le_sub_of_le {a b c : Ordinal} (h : b ≤ a) : c ≤ a - b ↔ b + c ≤ a := by
rw [← add_le_add_iff_left b, Ordinal.add_sub_cancel_of_le h]
#align ordinal.le_sub_of_le Ordinal.le_sub_of_le
theorem sub_lt_of_le {a b c : Ordinal} (h : b ≤ a) : a - b < c ↔ a < b + c :=
lt_iff_lt_of_le_iff_le (le_sub_of_le h)
#align ordinal.sub_lt_of_le Ordinal.sub_lt_of_le
instance existsAddOfLE : ExistsAddOfLE Ordinal :=
⟨fun h => ⟨_, (Ordinal.add_sub_cancel_of_le h).symm⟩⟩
@[simp]
theorem sub_zero (a : Ordinal) : a - 0 = a := by simpa only [zero_add] using add_sub_cancel 0 a
#align ordinal.sub_zero Ordinal.sub_zero
@[simp]
theorem zero_sub (a : Ordinal) : 0 - a = 0 := by rw [← Ordinal.le_zero]; apply sub_le_self
#align ordinal.zero_sub Ordinal.zero_sub
@[simp]
theorem sub_self (a : Ordinal) : a - a = 0 := by simpa only [add_zero] using add_sub_cancel a 0
#align ordinal.sub_self Ordinal.sub_self
protected theorem sub_eq_zero_iff_le {a b : Ordinal} : a - b = 0 ↔ a ≤ b :=
⟨fun h => by simpa only [h, add_zero] using le_add_sub a b, fun h => by
rwa [← Ordinal.le_zero, sub_le, add_zero]⟩
#align ordinal.sub_eq_zero_iff_le Ordinal.sub_eq_zero_iff_le
theorem sub_sub (a b c : Ordinal) : a - b - c = a - (b + c) :=
eq_of_forall_ge_iff fun d => by rw [sub_le, sub_le, sub_le, add_assoc]
#align ordinal.sub_sub Ordinal.sub_sub
@[simp]
theorem add_sub_add_cancel (a b c : Ordinal) : a + b - (a + c) = b - c := by
rw [← sub_sub, add_sub_cancel]
#align ordinal.add_sub_add_cancel Ordinal.add_sub_add_cancel
theorem sub_isLimit {a b} (l : IsLimit a) (h : b < a) : IsLimit (a - b) :=
⟨ne_of_gt <| lt_sub.2 <| by rwa [add_zero], fun c h => by
rw [lt_sub, add_succ]; exact l.2 _ (lt_sub.1 h)⟩
#align ordinal.sub_is_limit Ordinal.sub_isLimit
-- @[simp] -- Porting note (#10618): simp can prove this
theorem one_add_omega : 1 + ω = ω := by
refine le_antisymm ?_ (le_add_left _ _)
rw [omega, ← lift_one.{_, 0}, ← lift_add, lift_le, ← type_unit, ← type_sum_lex]
refine ⟨RelEmbedding.collapse (RelEmbedding.ofMonotone ?_ ?_)⟩
· apply Sum.rec
· exact fun _ => 0
· exact Nat.succ
· intro a b
cases a <;> cases b <;> intro H <;> cases' H with _ _ H _ _ H <;>
[exact H.elim; exact Nat.succ_pos _; exact Nat.succ_lt_succ H]
#align ordinal.one_add_omega Ordinal.one_add_omega
@[simp]
theorem one_add_of_omega_le {o} (h : ω ≤ o) : 1 + o = o := by
rw [← Ordinal.add_sub_cancel_of_le h, ← add_assoc, one_add_omega]
#align ordinal.one_add_of_omega_le Ordinal.one_add_of_omega_le
/-! ### Multiplication of ordinals-/
/-- The multiplication of ordinals `o₁` and `o₂` is the (well founded) lexicographic order on
`o₂ × o₁`. -/
instance monoid : Monoid Ordinal.{u} where
mul a b :=
Quotient.liftOn₂ a b
(fun ⟨α, r, wo⟩ ⟨β, s, wo'⟩ => ⟦⟨β × α, Prod.Lex s r, inferInstance⟩⟧ :
WellOrder → WellOrder → Ordinal)
fun ⟨α₁, r₁, o₁⟩ ⟨α₂, r₂, o₂⟩ ⟨β₁, s₁, p₁⟩ ⟨β₂, s₂, p₂⟩ ⟨f⟩ ⟨g⟩ =>
Quot.sound ⟨RelIso.prodLexCongr g f⟩
one := 1
mul_assoc a b c :=
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ =>
Eq.symm <|
Quotient.sound
⟨⟨prodAssoc _ _ _, @fun a b => by
rcases a with ⟨⟨a₁, a₂⟩, a₃⟩
rcases b with ⟨⟨b₁, b₂⟩, b₃⟩
simp [Prod.lex_def, and_or_left, or_assoc, and_assoc]⟩⟩
mul_one a :=
inductionOn a fun α r _ =>
Quotient.sound
⟨⟨punitProd _, @fun a b => by
rcases a with ⟨⟨⟨⟩⟩, a⟩; rcases b with ⟨⟨⟨⟩⟩, b⟩
simp only [Prod.lex_def, EmptyRelation, false_or_iff]
simp only [eq_self_iff_true, true_and_iff]
rfl⟩⟩
one_mul a :=
inductionOn a fun α r _ =>
Quotient.sound
⟨⟨prodPUnit _, @fun a b => by
rcases a with ⟨a, ⟨⟨⟩⟩⟩; rcases b with ⟨b, ⟨⟨⟩⟩⟩
simp only [Prod.lex_def, EmptyRelation, and_false_iff, or_false_iff]
rfl⟩⟩
@[simp]
theorem type_prod_lex {α β : Type u} (r : α → α → Prop) (s : β → β → Prop) [IsWellOrder α r]
[IsWellOrder β s] : type (Prod.Lex s r) = type r * type s :=
rfl
#align ordinal.type_prod_lex Ordinal.type_prod_lex
private theorem mul_eq_zero' {a b : Ordinal} : a * b = 0 ↔ a = 0 ∨ b = 0 :=
inductionOn a fun α _ _ =>
inductionOn b fun β _ _ => by
simp_rw [← type_prod_lex, type_eq_zero_iff_isEmpty]
rw [or_comm]
exact isEmpty_prod
instance monoidWithZero : MonoidWithZero Ordinal :=
{ Ordinal.monoid with
zero := 0
mul_zero := fun _a => mul_eq_zero'.2 <| Or.inr rfl
zero_mul := fun _a => mul_eq_zero'.2 <| Or.inl rfl }
instance noZeroDivisors : NoZeroDivisors Ordinal :=
⟨fun {_ _} => mul_eq_zero'.1⟩
@[simp]
theorem lift_mul (a b : Ordinal.{v}) : lift.{u} (a * b) = lift.{u} a * lift.{u} b :=
Quotient.inductionOn₂ a b fun ⟨_α, _r, _⟩ ⟨_β, _s, _⟩ =>
Quotient.sound
⟨(RelIso.preimage Equiv.ulift _).trans
(RelIso.prodLexCongr (RelIso.preimage Equiv.ulift _)
(RelIso.preimage Equiv.ulift _)).symm⟩
#align ordinal.lift_mul Ordinal.lift_mul
@[simp]
theorem card_mul (a b) : card (a * b) = card a * card b :=
Quotient.inductionOn₂ a b fun ⟨α, _r, _⟩ ⟨β, _s, _⟩ => mul_comm #β #α
#align ordinal.card_mul Ordinal.card_mul
instance leftDistribClass : LeftDistribClass Ordinal.{u} :=
⟨fun a b c =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ =>
Quotient.sound
⟨⟨sumProdDistrib _ _ _, by
rintro ⟨a₁ | a₁, a₂⟩ ⟨b₁ | b₁, b₂⟩ <;>
simp only [Prod.lex_def, Sum.lex_inl_inl, Sum.Lex.sep, Sum.lex_inr_inl,
Sum.lex_inr_inr, sumProdDistrib_apply_left, sumProdDistrib_apply_right] <;>
-- Porting note: `Sum.inr.inj_iff` is required.
simp only [Sum.inl.inj_iff, Sum.inr.inj_iff,
true_or_iff, false_and_iff, false_or_iff]⟩⟩⟩
theorem mul_succ (a b : Ordinal) : a * succ b = a * b + a :=
mul_add_one a b
#align ordinal.mul_succ Ordinal.mul_succ
instance mul_covariantClass_le : CovariantClass Ordinal.{u} Ordinal.{u} (· * ·) (· ≤ ·) :=
⟨fun c a b =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ ⟨f⟩ => by
refine
(RelEmbedding.ofMonotone (fun a : α × γ => (f a.1, a.2)) fun a b h => ?_).ordinal_type_le
cases' h with a₁ b₁ a₂ b₂ h' a b₁ b₂ h'
· exact Prod.Lex.left _ _ (f.toRelEmbedding.map_rel_iff.2 h')
· exact Prod.Lex.right _ h'⟩
#align ordinal.mul_covariant_class_le Ordinal.mul_covariantClass_le
instance mul_swap_covariantClass_le :
CovariantClass Ordinal.{u} Ordinal.{u} (swap (· * ·)) (· ≤ ·) :=
⟨fun c a b =>
Quotient.inductionOn₃ a b c fun ⟨α, r, _⟩ ⟨β, s, _⟩ ⟨γ, t, _⟩ ⟨f⟩ => by
refine
(RelEmbedding.ofMonotone (fun a : γ × α => (a.1, f a.2)) fun a b h => ?_).ordinal_type_le
cases' h with a₁ b₁ a₂ b₂ h' a b₁ b₂ h'
· exact Prod.Lex.left _ _ h'
· exact Prod.Lex.right _ (f.toRelEmbedding.map_rel_iff.2 h')⟩
#align ordinal.mul_swap_covariant_class_le Ordinal.mul_swap_covariantClass_le
theorem le_mul_left (a : Ordinal) {b : Ordinal} (hb : 0 < b) : a ≤ a * b := by
convert mul_le_mul_left' (one_le_iff_pos.2 hb) a
rw [mul_one a]
#align ordinal.le_mul_left Ordinal.le_mul_left
theorem le_mul_right (a : Ordinal) {b : Ordinal} (hb : 0 < b) : a ≤ b * a := by
convert mul_le_mul_right' (one_le_iff_pos.2 hb) a
rw [one_mul a]
#align ordinal.le_mul_right Ordinal.le_mul_right
private theorem mul_le_of_limit_aux {α β r s} [IsWellOrder α r] [IsWellOrder β s] {c}
(h : IsLimit (type s)) (H : ∀ b' < type s, type r * b' ≤ c) (l : c < type r * type s) :
False := by
suffices ∀ a b, Prod.Lex s r (b, a) (enum _ _ l) by
cases' enum _ _ l with b a
exact irrefl _ (this _ _)
intro a b
rw [← typein_lt_typein (Prod.Lex s r), typein_enum]
have := H _ (h.2 _ (typein_lt_type s b))
rw [mul_succ] at this
have := ((add_lt_add_iff_left _).2 (typein_lt_type _ a)).trans_le this
refine (RelEmbedding.ofMonotone (fun a => ?_) fun a b => ?_).ordinal_type_le.trans_lt this
· rcases a with ⟨⟨b', a'⟩, h⟩
by_cases e : b = b'
· refine Sum.inr ⟨a', ?_⟩
subst e
cases' h with _ _ _ _ h _ _ _ h
· exact (irrefl _ h).elim
· exact h
· refine Sum.inl (⟨b', ?_⟩, a')
cases' h with _ _ _ _ h _ _ _ h
· exact h
· exact (e rfl).elim
· rcases a with ⟨⟨b₁, a₁⟩, h₁⟩
rcases b with ⟨⟨b₂, a₂⟩, h₂⟩
intro h
by_cases e₁ : b = b₁ <;> by_cases e₂ : b = b₂
· substs b₁ b₂
simpa only [subrel_val, Prod.lex_def, @irrefl _ s _ b, true_and_iff, false_or_iff,
eq_self_iff_true, dif_pos, Sum.lex_inr_inr] using h
· subst b₁
simp only [subrel_val, Prod.lex_def, e₂, Prod.lex_def, dif_pos, subrel_val, eq_self_iff_true,
or_false_iff, dif_neg, not_false_iff, Sum.lex_inr_inl, false_and_iff] at h ⊢
cases' h₂ with _ _ _ _ h₂_h h₂_h <;> [exact asymm h h₂_h; exact e₂ rfl]
-- Porting note: `cc` hadn't ported yet.
· simp [e₂, dif_neg e₁, show b₂ ≠ b₁ from e₂ ▸ e₁]
· simpa only [dif_neg e₁, dif_neg e₂, Prod.lex_def, subrel_val, Subtype.mk_eq_mk,
Sum.lex_inl_inl] using h
theorem mul_le_of_limit {a b c : Ordinal} (h : IsLimit b) : a * b ≤ c ↔ ∀ b' < b, a * b' ≤ c :=
⟨fun h b' l => (mul_le_mul_left' l.le _).trans h, fun H =>
-- Porting note: `induction` tactics are required because of the parser bug.
le_of_not_lt <| by
induction a using inductionOn with
| H α r =>
induction b using inductionOn with
| H β s =>
exact mul_le_of_limit_aux h H⟩
#align ordinal.mul_le_of_limit Ordinal.mul_le_of_limit
theorem mul_isNormal {a : Ordinal} (h : 0 < a) : IsNormal (a * ·) :=
-- Porting note(#12129): additional beta reduction needed
⟨fun b => by
beta_reduce
rw [mul_succ]
simpa only [add_zero] using (add_lt_add_iff_left (a * b)).2 h,
fun b l c => mul_le_of_limit l⟩
#align ordinal.mul_is_normal Ordinal.mul_isNormal
theorem lt_mul_of_limit {a b c : Ordinal} (h : IsLimit c) : a < b * c ↔ ∃ c' < c, a < b * c' := by
-- Porting note: `bex_def` is required.
simpa only [not_forall₂, not_le, bex_def] using not_congr (@mul_le_of_limit b c a h)
#align ordinal.lt_mul_of_limit Ordinal.lt_mul_of_limit
theorem mul_lt_mul_iff_left {a b c : Ordinal} (a0 : 0 < a) : a * b < a * c ↔ b < c :=
(mul_isNormal a0).lt_iff
#align ordinal.mul_lt_mul_iff_left Ordinal.mul_lt_mul_iff_left
theorem mul_le_mul_iff_left {a b c : Ordinal} (a0 : 0 < a) : a * b ≤ a * c ↔ b ≤ c :=
(mul_isNormal a0).le_iff
#align ordinal.mul_le_mul_iff_left Ordinal.mul_le_mul_iff_left
theorem mul_lt_mul_of_pos_left {a b c : Ordinal} (h : a < b) (c0 : 0 < c) : c * a < c * b :=
(mul_lt_mul_iff_left c0).2 h
#align ordinal.mul_lt_mul_of_pos_left Ordinal.mul_lt_mul_of_pos_left
theorem mul_pos {a b : Ordinal} (h₁ : 0 < a) (h₂ : 0 < b) : 0 < a * b := by
simpa only [mul_zero] using mul_lt_mul_of_pos_left h₂ h₁
#align ordinal.mul_pos Ordinal.mul_pos
theorem mul_ne_zero {a b : Ordinal} : a ≠ 0 → b ≠ 0 → a * b ≠ 0 := by
simpa only [Ordinal.pos_iff_ne_zero] using mul_pos
#align ordinal.mul_ne_zero Ordinal.mul_ne_zero
theorem le_of_mul_le_mul_left {a b c : Ordinal} (h : c * a ≤ c * b) (h0 : 0 < c) : a ≤ b :=
le_imp_le_of_lt_imp_lt (fun h' => mul_lt_mul_of_pos_left h' h0) h
#align ordinal.le_of_mul_le_mul_left Ordinal.le_of_mul_le_mul_left
theorem mul_right_inj {a b c : Ordinal} (a0 : 0 < a) : a * b = a * c ↔ b = c :=
(mul_isNormal a0).inj
#align ordinal.mul_right_inj Ordinal.mul_right_inj
theorem mul_isLimit {a b : Ordinal} (a0 : 0 < a) : IsLimit b → IsLimit (a * b) :=
(mul_isNormal a0).isLimit
#align ordinal.mul_is_limit Ordinal.mul_isLimit
theorem mul_isLimit_left {a b : Ordinal} (l : IsLimit a) (b0 : 0 < b) : IsLimit (a * b) := by
rcases zero_or_succ_or_limit b with (rfl | ⟨b, rfl⟩ | lb)
· exact b0.false.elim
· rw [mul_succ]
exact add_isLimit _ l
· exact mul_isLimit l.pos lb
#align ordinal.mul_is_limit_left Ordinal.mul_isLimit_left
theorem smul_eq_mul : ∀ (n : ℕ) (a : Ordinal), n • a = a * n
| 0, a => by rw [zero_nsmul, Nat.cast_zero, mul_zero]
| n + 1, a => by rw [succ_nsmul, Nat.cast_add, mul_add, Nat.cast_one, mul_one, smul_eq_mul n]
#align ordinal.smul_eq_mul Ordinal.smul_eq_mul
/-! ### Division on ordinals -/
/-- The set in the definition of division is nonempty. -/
theorem div_nonempty {a b : Ordinal} (h : b ≠ 0) : { o | a < b * succ o }.Nonempty :=
⟨a, (succ_le_iff (a := a) (b := b * succ a)).1 <| by
simpa only [succ_zero, one_mul] using
mul_le_mul_right' (succ_le_of_lt (Ordinal.pos_iff_ne_zero.2 h)) (succ a)⟩
#align ordinal.div_nonempty Ordinal.div_nonempty
/-- `a / b` is the unique ordinal `o` satisfying `a = b * o + o'` with `o' < b`. -/
instance div : Div Ordinal :=
⟨fun a b => if _h : b = 0 then 0 else sInf { o | a < b * succ o }⟩
@[simp]
theorem div_zero (a : Ordinal) : a / 0 = 0 :=
dif_pos rfl
#align ordinal.div_zero Ordinal.div_zero
theorem div_def (a) {b : Ordinal} (h : b ≠ 0) : a / b = sInf { o | a < b * succ o } :=
dif_neg h
#align ordinal.div_def Ordinal.div_def
theorem lt_mul_succ_div (a) {b : Ordinal} (h : b ≠ 0) : a < b * succ (a / b) := by
rw [div_def a h]; exact csInf_mem (div_nonempty h)
#align ordinal.lt_mul_succ_div Ordinal.lt_mul_succ_div
theorem lt_mul_div_add (a) {b : Ordinal} (h : b ≠ 0) : a < b * (a / b) + b := by
simpa only [mul_succ] using lt_mul_succ_div a h
#align ordinal.lt_mul_div_add Ordinal.lt_mul_div_add
theorem div_le {a b c : Ordinal} (b0 : b ≠ 0) : a / b ≤ c ↔ a < b * succ c :=
⟨fun h => (lt_mul_succ_div a b0).trans_le (mul_le_mul_left' (succ_le_succ_iff.2 h) _), fun h => by
rw [div_def a b0]; exact csInf_le' h⟩
#align ordinal.div_le Ordinal.div_le
theorem lt_div {a b c : Ordinal} (h : c ≠ 0) : a < b / c ↔ c * succ a ≤ b := by
rw [← not_le, div_le h, not_lt]
#align ordinal.lt_div Ordinal.lt_div
theorem div_pos {b c : Ordinal} (h : c ≠ 0) : 0 < b / c ↔ c ≤ b := by simp [lt_div h]
#align ordinal.div_pos Ordinal.div_pos
theorem le_div {a b c : Ordinal} (c0 : c ≠ 0) : a ≤ b / c ↔ c * a ≤ b := by
induction a using limitRecOn with
| H₁ => simp only [mul_zero, Ordinal.zero_le]
| H₂ _ _ => rw [succ_le_iff, lt_div c0]
| H₃ _ h₁ h₂ =>
revert h₁ h₂
simp (config := { contextual := true }) only [mul_le_of_limit, limit_le, iff_self_iff,
forall_true_iff]
#align ordinal.le_div Ordinal.le_div
theorem div_lt {a b c : Ordinal} (b0 : b ≠ 0) : a / b < c ↔ a < b * c :=
lt_iff_lt_of_le_iff_le <| le_div b0
#align ordinal.div_lt Ordinal.div_lt
theorem div_le_of_le_mul {a b c : Ordinal} (h : a ≤ b * c) : a / b ≤ c :=
if b0 : b = 0 then by simp only [b0, div_zero, Ordinal.zero_le]
else
(div_le b0).2 <| h.trans_lt <| mul_lt_mul_of_pos_left (lt_succ c) (Ordinal.pos_iff_ne_zero.2 b0)
#align ordinal.div_le_of_le_mul Ordinal.div_le_of_le_mul
theorem mul_lt_of_lt_div {a b c : Ordinal} : a < b / c → c * a < b :=
lt_imp_lt_of_le_imp_le div_le_of_le_mul
#align ordinal.mul_lt_of_lt_div Ordinal.mul_lt_of_lt_div
@[simp]
theorem zero_div (a : Ordinal) : 0 / a = 0 :=
Ordinal.le_zero.1 <| div_le_of_le_mul <| Ordinal.zero_le _
#align ordinal.zero_div Ordinal.zero_div
theorem mul_div_le (a b : Ordinal) : b * (a / b) ≤ a :=
if b0 : b = 0 then by simp only [b0, zero_mul, Ordinal.zero_le] else (le_div b0).1 le_rfl
#align ordinal.mul_div_le Ordinal.mul_div_le
theorem mul_add_div (a) {b : Ordinal} (b0 : b ≠ 0) (c) : (b * a + c) / b = a + c / b := by
apply le_antisymm
· apply (div_le b0).2
rw [mul_succ, mul_add, add_assoc, add_lt_add_iff_left]
apply lt_mul_div_add _ b0
· rw [le_div b0, mul_add, add_le_add_iff_left]
apply mul_div_le
#align ordinal.mul_add_div Ordinal.mul_add_div
theorem div_eq_zero_of_lt {a b : Ordinal} (h : a < b) : a / b = 0 := by
rw [← Ordinal.le_zero, div_le <| Ordinal.pos_iff_ne_zero.1 <| (Ordinal.zero_le _).trans_lt h]
simpa only [succ_zero, mul_one] using h
#align ordinal.div_eq_zero_of_lt Ordinal.div_eq_zero_of_lt
@[simp]
theorem mul_div_cancel (a) {b : Ordinal} (b0 : b ≠ 0) : b * a / b = a := by
simpa only [add_zero, zero_div] using mul_add_div a b0 0
#align ordinal.mul_div_cancel Ordinal.mul_div_cancel
@[simp]
theorem div_one (a : Ordinal) : a / 1 = a := by
simpa only [one_mul] using mul_div_cancel a Ordinal.one_ne_zero
#align ordinal.div_one Ordinal.div_one
@[simp]
theorem div_self {a : Ordinal} (h : a ≠ 0) : a / a = 1 := by
simpa only [mul_one] using mul_div_cancel 1 h
#align ordinal.div_self Ordinal.div_self
theorem mul_sub (a b c : Ordinal) : a * (b - c) = a * b - a * c :=
if a0 : a = 0 then by simp only [a0, zero_mul, sub_self]
else
eq_of_forall_ge_iff fun d => by rw [sub_le, ← le_div a0, sub_le, ← le_div a0, mul_add_div _ a0]
#align ordinal.mul_sub Ordinal.mul_sub
theorem isLimit_add_iff {a b} : IsLimit (a + b) ↔ IsLimit b ∨ b = 0 ∧ IsLimit a := by
constructor <;> intro h
· by_cases h' : b = 0
· rw [h', add_zero] at h
right
exact ⟨h', h⟩
left
rw [← add_sub_cancel a b]
apply sub_isLimit h
suffices a + 0 < a + b by simpa only [add_zero] using this
rwa [add_lt_add_iff_left, Ordinal.pos_iff_ne_zero]
rcases h with (h | ⟨rfl, h⟩)
· exact add_isLimit a h
· simpa only [add_zero]
#align ordinal.is_limit_add_iff Ordinal.isLimit_add_iff
theorem dvd_add_iff : ∀ {a b c : Ordinal}, a ∣ b → (a ∣ b + c ↔ a ∣ c)
| a, _, c, ⟨b, rfl⟩ =>
⟨fun ⟨d, e⟩ => ⟨d - b, by rw [mul_sub, ← e, add_sub_cancel]⟩, fun ⟨d, e⟩ => by
rw [e, ← mul_add]
apply dvd_mul_right⟩
#align ordinal.dvd_add_iff Ordinal.dvd_add_iff
theorem div_mul_cancel : ∀ {a b : Ordinal}, a ≠ 0 → a ∣ b → a * (b / a) = b
| a, _, a0, ⟨b, rfl⟩ => by rw [mul_div_cancel _ a0]
#align ordinal.div_mul_cancel Ordinal.div_mul_cancel
theorem le_of_dvd : ∀ {a b : Ordinal}, b ≠ 0 → a ∣ b → a ≤ b
-- Porting note: `⟨b, rfl⟩ => by` → `⟨b, e⟩ => by subst e`
| a, _, b0, ⟨b, e⟩ => by
subst e
-- Porting note: `Ne` is required.
simpa only [mul_one] using
mul_le_mul_left'
(one_le_iff_ne_zero.2 fun h : b = 0 => by
simp only [h, mul_zero, Ne, not_true_eq_false] at b0) a
#align ordinal.le_of_dvd Ordinal.le_of_dvd
theorem dvd_antisymm {a b : Ordinal} (h₁ : a ∣ b) (h₂ : b ∣ a) : a = b :=
if a0 : a = 0 then by subst a; exact (eq_zero_of_zero_dvd h₁).symm
else
if b0 : b = 0 then by subst b; exact eq_zero_of_zero_dvd h₂
else (le_of_dvd b0 h₁).antisymm (le_of_dvd a0 h₂)
#align ordinal.dvd_antisymm Ordinal.dvd_antisymm
instance isAntisymm : IsAntisymm Ordinal (· ∣ ·) :=
⟨@dvd_antisymm⟩
/-- `a % b` is the unique ordinal `o'` satisfying
`a = b * o + o'` with `o' < b`. -/
instance mod : Mod Ordinal :=
⟨fun a b => a - b * (a / b)⟩
theorem mod_def (a b : Ordinal) : a % b = a - b * (a / b) :=
rfl
#align ordinal.mod_def Ordinal.mod_def
theorem mod_le (a b : Ordinal) : a % b ≤ a :=
sub_le_self a _
#align ordinal.mod_le Ordinal.mod_le
@[simp]
theorem mod_zero (a : Ordinal) : a % 0 = a := by simp only [mod_def, div_zero, zero_mul, sub_zero]
#align ordinal.mod_zero Ordinal.mod_zero
theorem mod_eq_of_lt {a b : Ordinal} (h : a < b) : a % b = a := by
simp only [mod_def, div_eq_zero_of_lt h, mul_zero, sub_zero]
#align ordinal.mod_eq_of_lt Ordinal.mod_eq_of_lt
@[simp]
theorem zero_mod (b : Ordinal) : 0 % b = 0 := by simp only [mod_def, zero_div, mul_zero, sub_self]
#align ordinal.zero_mod Ordinal.zero_mod
theorem div_add_mod (a b : Ordinal) : b * (a / b) + a % b = a :=
Ordinal.add_sub_cancel_of_le <| mul_div_le _ _
#align ordinal.div_add_mod Ordinal.div_add_mod
theorem mod_lt (a) {b : Ordinal} (h : b ≠ 0) : a % b < b :=
(add_lt_add_iff_left (b * (a / b))).1 <| by rw [div_add_mod]; exact lt_mul_div_add a h
#align ordinal.mod_lt Ordinal.mod_lt
@[simp]
theorem mod_self (a : Ordinal) : a % a = 0 :=
if a0 : a = 0 then by simp only [a0, zero_mod]
else by simp only [mod_def, div_self a0, mul_one, sub_self]
#align ordinal.mod_self Ordinal.mod_self
@[simp]
theorem mod_one (a : Ordinal) : a % 1 = 0 := by simp only [mod_def, div_one, one_mul, sub_self]
#align ordinal.mod_one Ordinal.mod_one
theorem dvd_of_mod_eq_zero {a b : Ordinal} (H : a % b = 0) : b ∣ a :=
⟨a / b, by simpa [H] using (div_add_mod a b).symm⟩
#align ordinal.dvd_of_mod_eq_zero Ordinal.dvd_of_mod_eq_zero
theorem mod_eq_zero_of_dvd {a b : Ordinal} (H : b ∣ a) : a % b = 0 := by
rcases H with ⟨c, rfl⟩
rcases eq_or_ne b 0 with (rfl | hb)
· simp
· simp [mod_def, hb]
#align ordinal.mod_eq_zero_of_dvd Ordinal.mod_eq_zero_of_dvd
theorem dvd_iff_mod_eq_zero {a b : Ordinal} : b ∣ a ↔ a % b = 0 :=
⟨mod_eq_zero_of_dvd, dvd_of_mod_eq_zero⟩
#align ordinal.dvd_iff_mod_eq_zero Ordinal.dvd_iff_mod_eq_zero
@[simp]
theorem mul_add_mod_self (x y z : Ordinal) : (x * y + z) % x = z % x := by
rcases eq_or_ne x 0 with rfl | hx
· simp
· rwa [mod_def, mul_add_div, mul_add, ← sub_sub, add_sub_cancel, mod_def]
#align ordinal.mul_add_mod_self Ordinal.mul_add_mod_self
@[simp]
theorem mul_mod (x y : Ordinal) : x * y % x = 0 := by
simpa using mul_add_mod_self x y 0
#align ordinal.mul_mod Ordinal.mul_mod
theorem mod_mod_of_dvd (a : Ordinal) {b c : Ordinal} (h : c ∣ b) : a % b % c = a % c := by
nth_rw 2 [← div_add_mod a b]
rcases h with ⟨d, rfl⟩
rw [mul_assoc, mul_add_mod_self]
#align ordinal.mod_mod_of_dvd Ordinal.mod_mod_of_dvd
@[simp]
theorem mod_mod (a b : Ordinal) : a % b % b = a % b :=
mod_mod_of_dvd a dvd_rfl
#align ordinal.mod_mod Ordinal.mod_mod
/-! ### Families of ordinals
There are two kinds of indexed families that naturally arise when dealing with ordinals: those
indexed by some type in the appropriate universe, and those indexed by ordinals less than another.
The following API allows one to convert from one kind of family to the other.
In many cases, this makes it easy to prove claims about one kind of family via the corresponding
claim on the other. -/
/-- Converts a family indexed by a `Type u` to one indexed by an `Ordinal.{u}` using a specified
well-ordering. -/
def bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) :
∀ a < type r, α := fun a ha => f (enum r a ha)
#align ordinal.bfamily_of_family' Ordinal.bfamilyOfFamily'
/-- Converts a family indexed by a `Type u` to one indexed by an `Ordinal.{u}` using a well-ordering
given by the axiom of choice. -/
def bfamilyOfFamily {ι : Type u} : (ι → α) → ∀ a < type (@WellOrderingRel ι), α :=
bfamilyOfFamily' WellOrderingRel
#align ordinal.bfamily_of_family Ordinal.bfamilyOfFamily
/-- Converts a family indexed by an `Ordinal.{u}` to one indexed by a `Type u` using a specified
well-ordering. -/
def familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o} (ho : type r = o)
(f : ∀ a < o, α) : ι → α := fun i =>
f (typein r i)
(by
rw [← ho]
exact typein_lt_type r i)
#align ordinal.family_of_bfamily' Ordinal.familyOfBFamily'
/-- Converts a family indexed by an `Ordinal.{u}` to one indexed by a `Type u` using a well-ordering
given by the axiom of choice. -/
def familyOfBFamily (o : Ordinal) (f : ∀ a < o, α) : o.out.α → α :=
familyOfBFamily' (· < ·) (type_lt o) f
#align ordinal.family_of_bfamily Ordinal.familyOfBFamily
@[simp]
theorem bfamilyOfFamily'_typein {ι} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) (i) :
bfamilyOfFamily' r f (typein r i) (typein_lt_type r i) = f i := by
simp only [bfamilyOfFamily', enum_typein]
#align ordinal.bfamily_of_family'_typein Ordinal.bfamilyOfFamily'_typein
@[simp]
theorem bfamilyOfFamily_typein {ι} (f : ι → α) (i) :
bfamilyOfFamily f (typein _ i) (typein_lt_type _ i) = f i :=
bfamilyOfFamily'_typein _ f i
#align ordinal.bfamily_of_family_typein Ordinal.bfamilyOfFamily_typein
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem familyOfBFamily'_enum {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) (i hi) :
familyOfBFamily' r ho f (enum r i (by rwa [ho])) = f i hi := by
simp only [familyOfBFamily', typein_enum]
#align ordinal.family_of_bfamily'_enum Ordinal.familyOfBFamily'_enum
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem familyOfBFamily_enum (o : Ordinal) (f : ∀ a < o, α) (i hi) :
familyOfBFamily o f
(enum (· < ·) i
(by
convert hi
exact type_lt _)) =
f i hi :=
familyOfBFamily'_enum _ (type_lt o) f _ _
#align ordinal.family_of_bfamily_enum Ordinal.familyOfBFamily_enum
/-- The range of a family indexed by ordinals. -/
def brange (o : Ordinal) (f : ∀ a < o, α) : Set α :=
{ a | ∃ i hi, f i hi = a }
#align ordinal.brange Ordinal.brange
theorem mem_brange {o : Ordinal} {f : ∀ a < o, α} {a} : a ∈ brange o f ↔ ∃ i hi, f i hi = a :=
Iff.rfl
#align ordinal.mem_brange Ordinal.mem_brange
theorem mem_brange_self {o} (f : ∀ a < o, α) (i hi) : f i hi ∈ brange o f :=
⟨i, hi, rfl⟩
#align ordinal.mem_brange_self Ordinal.mem_brange_self
@[simp]
theorem range_familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) : range (familyOfBFamily' r ho f) = brange o f := by
refine Set.ext fun a => ⟨?_, ?_⟩
· rintro ⟨b, rfl⟩
apply mem_brange_self
· rintro ⟨i, hi, rfl⟩
exact ⟨_, familyOfBFamily'_enum _ _ _ _ _⟩
#align ordinal.range_family_of_bfamily' Ordinal.range_familyOfBFamily'
@[simp]
theorem range_familyOfBFamily {o} (f : ∀ a < o, α) : range (familyOfBFamily o f) = brange o f :=
range_familyOfBFamily' _ _ f
#align ordinal.range_family_of_bfamily Ordinal.range_familyOfBFamily
@[simp]
theorem brange_bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α) :
brange _ (bfamilyOfFamily' r f) = range f := by
refine Set.ext fun a => ⟨?_, ?_⟩
· rintro ⟨i, hi, rfl⟩
apply mem_range_self
· rintro ⟨b, rfl⟩
exact ⟨_, _, bfamilyOfFamily'_typein _ _ _⟩
#align ordinal.brange_bfamily_of_family' Ordinal.brange_bfamilyOfFamily'
@[simp]
theorem brange_bfamilyOfFamily {ι : Type u} (f : ι → α) : brange _ (bfamilyOfFamily f) = range f :=
brange_bfamilyOfFamily' _ _
#align ordinal.brange_bfamily_of_family Ordinal.brange_bfamilyOfFamily
@[simp]
theorem brange_const {o : Ordinal} (ho : o ≠ 0) {c : α} : (brange o fun _ _ => c) = {c} := by
rw [← range_familyOfBFamily]
exact @Set.range_const _ o.out.α (out_nonempty_iff_ne_zero.2 ho) c
#align ordinal.brange_const Ordinal.brange_const
theorem comp_bfamilyOfFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → α)
(g : α → β) : (fun i hi => g (bfamilyOfFamily' r f i hi)) = bfamilyOfFamily' r (g ∘ f) :=
rfl
#align ordinal.comp_bfamily_of_family' Ordinal.comp_bfamilyOfFamily'
theorem comp_bfamilyOfFamily {ι : Type u} (f : ι → α) (g : α → β) :
(fun i hi => g (bfamilyOfFamily f i hi)) = bfamilyOfFamily (g ∘ f) :=
rfl
#align ordinal.comp_bfamily_of_family Ordinal.comp_bfamilyOfFamily
theorem comp_familyOfBFamily' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o}
(ho : type r = o) (f : ∀ a < o, α) (g : α → β) :
g ∘ familyOfBFamily' r ho f = familyOfBFamily' r ho fun i hi => g (f i hi) :=
rfl
#align ordinal.comp_family_of_bfamily' Ordinal.comp_familyOfBFamily'
theorem comp_familyOfBFamily {o} (f : ∀ a < o, α) (g : α → β) :
g ∘ familyOfBFamily o f = familyOfBFamily o fun i hi => g (f i hi) :=
rfl
#align ordinal.comp_family_of_bfamily Ordinal.comp_familyOfBFamily
/-! ### Supremum of a family of ordinals -/
-- Porting note: Universes should be specified in `sup`s.
/-- The supremum of a family of ordinals -/
def sup {ι : Type u} (f : ι → Ordinal.{max u v}) : Ordinal.{max u v} :=
iSup f
#align ordinal.sup Ordinal.sup
@[simp]
theorem sSup_eq_sup {ι : Type u} (f : ι → Ordinal.{max u v}) : sSup (Set.range f) = sup.{_, v} f :=
rfl
#align ordinal.Sup_eq_sup Ordinal.sSup_eq_sup
/-- The range of an indexed ordinal function, whose outputs live in a higher universe than the
inputs, is always bounded above. See `Ordinal.lsub` for an explicit bound. -/
theorem bddAbove_range {ι : Type u} (f : ι → Ordinal.{max u v}) : BddAbove (Set.range f) :=
⟨(iSup (succ ∘ card ∘ f)).ord, by
rintro a ⟨i, rfl⟩
exact le_of_lt (Cardinal.lt_ord.2 ((lt_succ _).trans_le
(le_ciSup (Cardinal.bddAbove_range.{_, v} _) _)))⟩
#align ordinal.bdd_above_range Ordinal.bddAbove_range
theorem le_sup {ι : Type u} (f : ι → Ordinal.{max u v}) : ∀ i, f i ≤ sup.{_, v} f := fun i =>
le_csSup (bddAbove_range.{_, v} f) (mem_range_self i)
#align ordinal.le_sup Ordinal.le_sup
theorem sup_le_iff {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : sup.{_, v} f ≤ a ↔ ∀ i, f i ≤ a :=
(csSup_le_iff' (bddAbove_range.{_, v} f)).trans (by simp)
#align ordinal.sup_le_iff Ordinal.sup_le_iff
theorem sup_le {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : (∀ i, f i ≤ a) → sup.{_, v} f ≤ a :=
sup_le_iff.2
#align ordinal.sup_le Ordinal.sup_le
theorem lt_sup {ι : Type u} {f : ι → Ordinal.{max u v}} {a} : a < sup.{_, v} f ↔ ∃ i, a < f i := by
simpa only [not_forall, not_le] using not_congr (@sup_le_iff.{_, v} _ f a)
#align ordinal.lt_sup Ordinal.lt_sup
theorem ne_sup_iff_lt_sup {ι : Type u} {f : ι → Ordinal.{max u v}} :
(∀ i, f i ≠ sup.{_, v} f) ↔ ∀ i, f i < sup.{_, v} f :=
⟨fun hf _ => lt_of_le_of_ne (le_sup _ _) (hf _), fun hf _ => ne_of_lt (hf _)⟩
#align ordinal.ne_sup_iff_lt_sup Ordinal.ne_sup_iff_lt_sup
theorem sup_not_succ_of_ne_sup {ι : Type u} {f : ι → Ordinal.{max u v}}
(hf : ∀ i, f i ≠ sup.{_, v} f) {a} (hao : a < sup.{_, v} f) : succ a < sup.{_, v} f := by
by_contra! hoa
exact
hao.not_le (sup_le fun i => le_of_lt_succ <| (lt_of_le_of_ne (le_sup _ _) (hf i)).trans_le hoa)
#align ordinal.sup_not_succ_of_ne_sup Ordinal.sup_not_succ_of_ne_sup
@[simp]
theorem sup_eq_zero_iff {ι : Type u} {f : ι → Ordinal.{max u v}} :
sup.{_, v} f = 0 ↔ ∀ i, f i = 0 := by
refine
⟨fun h i => ?_, fun h =>
le_antisymm (sup_le fun i => Ordinal.le_zero.2 (h i)) (Ordinal.zero_le _)⟩
rw [← Ordinal.le_zero, ← h]
exact le_sup f i
#align ordinal.sup_eq_zero_iff Ordinal.sup_eq_zero_iff
theorem IsNormal.sup {f : Ordinal.{max u v} → Ordinal.{max u w}} (H : IsNormal f) {ι : Type u}
(g : ι → Ordinal.{max u v}) [Nonempty ι] : f (sup.{_, v} g) = sup.{_, w} (f ∘ g) :=
eq_of_forall_ge_iff fun a => by
rw [sup_le_iff]; simp only [comp]; rw [H.le_set' Set.univ Set.univ_nonempty g] <;>
simp [sup_le_iff]
#align ordinal.is_normal.sup Ordinal.IsNormal.sup
@[simp]
theorem sup_empty {ι} [IsEmpty ι] (f : ι → Ordinal) : sup f = 0 :=
ciSup_of_empty f
#align ordinal.sup_empty Ordinal.sup_empty
@[simp]
theorem sup_const {ι} [_hι : Nonempty ι] (o : Ordinal) : (sup fun _ : ι => o) = o :=
ciSup_const
#align ordinal.sup_const Ordinal.sup_const
@[simp]
theorem sup_unique {ι} [Unique ι] (f : ι → Ordinal) : sup f = f default :=
ciSup_unique
#align ordinal.sup_unique Ordinal.sup_unique
theorem sup_le_of_range_subset {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f ⊆ Set.range g) : sup.{u, max v w} f ≤ sup.{v, max u w} g :=
sup_le fun i =>
match h (mem_range_self i) with
| ⟨_j, hj⟩ => hj ▸ le_sup _ _
#align ordinal.sup_le_of_range_subset Ordinal.sup_le_of_range_subset
theorem sup_eq_of_range_eq {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f = Set.range g) : sup.{u, max v w} f = sup.{v, max u w} g :=
(sup_le_of_range_subset.{u, v, w} h.le).antisymm (sup_le_of_range_subset.{v, u, w} h.ge)
#align ordinal.sup_eq_of_range_eq Ordinal.sup_eq_of_range_eq
@[simp]
theorem sup_sum {α : Type u} {β : Type v} (f : Sum α β → Ordinal) :
sup.{max u v, w} f =
max (sup.{u, max v w} fun a => f (Sum.inl a)) (sup.{v, max u w} fun b => f (Sum.inr b)) := by
apply (sup_le_iff.2 _).antisymm (max_le_iff.2 ⟨_, _⟩)
· rintro (i | i)
· exact le_max_of_le_left (le_sup _ i)
· exact le_max_of_le_right (le_sup _ i)
all_goals
apply sup_le_of_range_subset.{_, max u v, w}
rintro i ⟨a, rfl⟩
apply mem_range_self
#align ordinal.sup_sum Ordinal.sup_sum
theorem unbounded_range_of_sup_ge {α β : Type u} (r : α → α → Prop) [IsWellOrder α r] (f : β → α)
(h : type r ≤ sup.{u, u} (typein r ∘ f)) : Unbounded r (range f) :=
(not_bounded_iff _).1 fun ⟨x, hx⟩ =>
not_lt_of_le h <|
lt_of_le_of_lt
(sup_le fun y => le_of_lt <| (typein_lt_typein r).2 <| hx _ <| mem_range_self y)
(typein_lt_type r x)
#align ordinal.unbounded_range_of_sup_ge Ordinal.unbounded_range_of_sup_ge
theorem le_sup_shrink_equiv {s : Set Ordinal.{u}} (hs : Small.{u} s) (a) (ha : a ∈ s) :
a ≤ sup.{u, u} fun x => ((@equivShrink s hs).symm x).val := by
convert le_sup.{u, u} (fun x => ((@equivShrink s hs).symm x).val) ((@equivShrink s hs) ⟨a, ha⟩)
rw [symm_apply_apply]
#align ordinal.le_sup_shrink_equiv Ordinal.le_sup_shrink_equiv
instance small_Iio (o : Ordinal.{u}) : Small.{u} (Set.Iio o) :=
let f : o.out.α → Set.Iio o :=
fun x => ⟨typein ((· < ·) : o.out.α → o.out.α → Prop) x, typein_lt_self x⟩
let hf : Surjective f := fun b =>
⟨enum (· < ·) b.val
(by
rw [type_lt]
exact b.prop),
Subtype.ext (typein_enum _ _)⟩
small_of_surjective hf
#align ordinal.small_Iio Ordinal.small_Iio
instance small_Iic (o : Ordinal.{u}) : Small.{u} (Set.Iic o) := by
rw [← Iio_succ]
infer_instance
#align ordinal.small_Iic Ordinal.small_Iic
theorem bddAbove_iff_small {s : Set Ordinal.{u}} : BddAbove s ↔ Small.{u} s :=
⟨fun ⟨a, h⟩ => small_subset <| show s ⊆ Iic a from fun _x hx => h hx, fun h =>
⟨sup.{u, u} fun x => ((@equivShrink s h).symm x).val, le_sup_shrink_equiv h⟩⟩
#align ordinal.bdd_above_iff_small Ordinal.bddAbove_iff_small
theorem bddAbove_of_small (s : Set Ordinal.{u}) [h : Small.{u} s] : BddAbove s :=
bddAbove_iff_small.2 h
#align ordinal.bdd_above_of_small Ordinal.bddAbove_of_small
theorem sup_eq_sSup {s : Set Ordinal.{u}} (hs : Small.{u} s) :
(sup.{u, u} fun x => (@equivShrink s hs).symm x) = sSup s :=
let hs' := bddAbove_iff_small.2 hs
((csSup_le_iff' hs').2 (le_sup_shrink_equiv hs)).antisymm'
(sup_le fun _x => le_csSup hs' (Subtype.mem _))
#align ordinal.sup_eq_Sup Ordinal.sup_eq_sSup
theorem sSup_ord {s : Set Cardinal.{u}} (hs : BddAbove s) : (sSup s).ord = sSup (ord '' s) :=
eq_of_forall_ge_iff fun a => by
rw [csSup_le_iff'
(bddAbove_iff_small.2 (@small_image _ _ _ s (Cardinal.bddAbove_iff_small.1 hs))),
ord_le, csSup_le_iff' hs]
simp [ord_le]
#align ordinal.Sup_ord Ordinal.sSup_ord
theorem iSup_ord {ι} {f : ι → Cardinal} (hf : BddAbove (range f)) :
(iSup f).ord = ⨆ i, (f i).ord := by
unfold iSup
convert sSup_ord hf
-- Porting note: `change` is required.
conv_lhs => change range (ord ∘ f)
rw [range_comp]
#align ordinal.supr_ord Ordinal.iSup_ord
private theorem sup_le_sup {ι ι' : Type u} (r : ι → ι → Prop) (r' : ι' → ι' → Prop)
[IsWellOrder ι r] [IsWellOrder ι' r'] {o} (ho : type r = o) (ho' : type r' = o)
(f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily' r ho f) ≤ sup.{_, v} (familyOfBFamily' r' ho' f) :=
sup_le fun i => by
cases'
typein_surj r'
(by
rw [ho', ← ho]
exact typein_lt_type r i) with
j hj
simp_rw [familyOfBFamily', ← hj]
apply le_sup
theorem sup_eq_sup {ι ι' : Type u} (r : ι → ι → Prop) (r' : ι' → ι' → Prop) [IsWellOrder ι r]
[IsWellOrder ι' r'] {o : Ordinal.{u}} (ho : type r = o) (ho' : type r' = o)
(f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily' r ho f) = sup.{_, v} (familyOfBFamily' r' ho' f) :=
sup_eq_of_range_eq.{u, u, v} (by simp)
#align ordinal.sup_eq_sup Ordinal.sup_eq_sup
/-- The supremum of a family of ordinals indexed by the set of ordinals less than some
`o : Ordinal.{u}`. This is a special case of `sup` over the family provided by
`familyOfBFamily`. -/
def bsup (o : Ordinal.{u}) (f : ∀ a < o, Ordinal.{max u v}) : Ordinal.{max u v} :=
sup.{_, v} (familyOfBFamily o f)
#align ordinal.bsup Ordinal.bsup
@[simp]
theorem sup_eq_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
sup.{_, v} (familyOfBFamily o f) = bsup.{_, v} o f :=
rfl
#align ordinal.sup_eq_bsup Ordinal.sup_eq_bsup
@[simp]
theorem sup_eq_bsup' {o : Ordinal.{u}} {ι} (r : ι → ι → Prop) [IsWellOrder ι r] (ho : type r = o)
(f : ∀ a < o, Ordinal.{max u v}) : sup.{_, v} (familyOfBFamily' r ho f) = bsup.{_, v} o f :=
sup_eq_sup r _ ho _ f
#align ordinal.sup_eq_bsup' Ordinal.sup_eq_bsup'
@[simp, nolint simpNF] -- Porting note (#10959): simp cannot prove this
theorem sSup_eq_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
sSup (brange o f) = bsup.{_, v} o f := by
congr
rw [range_familyOfBFamily]
#align ordinal.Sup_eq_bsup Ordinal.sSup_eq_bsup
@[simp]
theorem bsup_eq_sup' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] (f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily' r f) = sup.{_, v} f := by
simp (config := { unfoldPartialApp := true }) only [← sup_eq_bsup' r, enum_typein,
familyOfBFamily', bfamilyOfFamily']
#align ordinal.bsup_eq_sup' Ordinal.bsup_eq_sup'
theorem bsup_eq_bsup {ι : Type u} (r r' : ι → ι → Prop) [IsWellOrder ι r] [IsWellOrder ι r']
(f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily' r f) = bsup.{_, v} _ (bfamilyOfFamily' r' f) := by
rw [bsup_eq_sup', bsup_eq_sup']
#align ordinal.bsup_eq_bsup Ordinal.bsup_eq_bsup
@[simp]
theorem bsup_eq_sup {ι : Type u} (f : ι → Ordinal.{max u v}) :
bsup.{_, v} _ (bfamilyOfFamily f) = sup.{_, v} f :=
bsup_eq_sup' _ f
#align ordinal.bsup_eq_sup Ordinal.bsup_eq_sup
@[congr]
theorem bsup_congr {o₁ o₂ : Ordinal.{u}} (f : ∀ a < o₁, Ordinal.{max u v}) (ho : o₁ = o₂) :
bsup.{_, v} o₁ f = bsup.{_, v} o₂ fun a h => f a (h.trans_eq ho.symm) := by
subst ho
-- Porting note: `rfl` is required.
rfl
#align ordinal.bsup_congr Ordinal.bsup_congr
theorem bsup_le_iff {o f a} : bsup.{u, v} o f ≤ a ↔ ∀ i h, f i h ≤ a :=
sup_le_iff.trans
⟨fun h i hi => by
rw [← familyOfBFamily_enum o f]
exact h _, fun h i => h _ _⟩
#align ordinal.bsup_le_iff Ordinal.bsup_le_iff
theorem bsup_le {o : Ordinal} {f : ∀ b < o, Ordinal} {a} :
(∀ i h, f i h ≤ a) → bsup.{u, v} o f ≤ a :=
bsup_le_iff.2
#align ordinal.bsup_le Ordinal.bsup_le
theorem le_bsup {o} (f : ∀ a < o, Ordinal) (i h) : f i h ≤ bsup o f :=
bsup_le_iff.1 le_rfl _ _
#align ordinal.le_bsup Ordinal.le_bsup
theorem lt_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) {a} :
a < bsup.{_, v} o f ↔ ∃ i hi, a < f i hi := by
simpa only [not_forall, not_le] using not_congr (@bsup_le_iff.{_, v} _ f a)
#align ordinal.lt_bsup Ordinal.lt_bsup
theorem IsNormal.bsup {f : Ordinal.{max u v} → Ordinal.{max u w}} (H : IsNormal f)
{o : Ordinal.{u}} :
∀ (g : ∀ a < o, Ordinal), o ≠ 0 → f (bsup.{_, v} o g) = bsup.{_, w} o fun a h => f (g a h) :=
inductionOn o fun α r _ g h => by
haveI := type_ne_zero_iff_nonempty.1 h
rw [← sup_eq_bsup' r, IsNormal.sup.{_, v, w} H, ← sup_eq_bsup' r] <;> rfl
#align ordinal.is_normal.bsup Ordinal.IsNormal.bsup
theorem lt_bsup_of_ne_bsup {o : Ordinal.{u}} {f : ∀ a < o, Ordinal.{max u v}} :
(∀ i h, f i h ≠ bsup.{_, v} o f) ↔ ∀ i h, f i h < bsup.{_, v} o f :=
⟨fun hf _ _ => lt_of_le_of_ne (le_bsup _ _ _) (hf _ _), fun hf _ _ => ne_of_lt (hf _ _)⟩
#align ordinal.lt_bsup_of_ne_bsup Ordinal.lt_bsup_of_ne_bsup
theorem bsup_not_succ_of_ne_bsup {o : Ordinal.{u}} {f : ∀ a < o, Ordinal.{max u v}}
(hf : ∀ {i : Ordinal} (h : i < o), f i h ≠ bsup.{_, v} o f) (a) :
a < bsup.{_, v} o f → succ a < bsup.{_, v} o f := by
rw [← sup_eq_bsup] at *
exact sup_not_succ_of_ne_sup fun i => hf _
#align ordinal.bsup_not_succ_of_ne_bsup Ordinal.bsup_not_succ_of_ne_bsup
@[simp]
theorem bsup_eq_zero_iff {o} {f : ∀ a < o, Ordinal} : bsup o f = 0 ↔ ∀ i hi, f i hi = 0 := by
refine
⟨fun h i hi => ?_, fun h =>
le_antisymm (bsup_le fun i hi => Ordinal.le_zero.2 (h i hi)) (Ordinal.zero_le _)⟩
rw [← Ordinal.le_zero, ← h]
exact le_bsup f i hi
#align ordinal.bsup_eq_zero_iff Ordinal.bsup_eq_zero_iff
theorem lt_bsup_of_limit {o : Ordinal} {f : ∀ a < o, Ordinal}
(hf : ∀ {a a'} (ha : a < o) (ha' : a' < o), a < a' → f a ha < f a' ha')
(ho : ∀ a < o, succ a < o) (i h) : f i h < bsup o f :=
(hf _ _ <| lt_succ i).trans_le (le_bsup f (succ i) <| ho _ h)
#align ordinal.lt_bsup_of_limit Ordinal.lt_bsup_of_limit
theorem bsup_succ_of_mono {o : Ordinal} {f : ∀ a < succ o, Ordinal}
(hf : ∀ {i j} (hi hj), i ≤ j → f i hi ≤ f j hj) : bsup _ f = f o (lt_succ o) :=
le_antisymm (bsup_le fun _i hi => hf _ _ <| le_of_lt_succ hi) (le_bsup _ _ _)
#align ordinal.bsup_succ_of_mono Ordinal.bsup_succ_of_mono
@[simp]
theorem bsup_zero (f : ∀ a < (0 : Ordinal), Ordinal) : bsup 0 f = 0 :=
bsup_eq_zero_iff.2 fun i hi => (Ordinal.not_lt_zero i hi).elim
#align ordinal.bsup_zero Ordinal.bsup_zero
theorem bsup_const {o : Ordinal.{u}} (ho : o ≠ 0) (a : Ordinal.{max u v}) :
(bsup.{_, v} o fun _ _ => a) = a :=
le_antisymm (bsup_le fun _ _ => le_rfl) (le_bsup _ 0 (Ordinal.pos_iff_ne_zero.2 ho))
#align ordinal.bsup_const Ordinal.bsup_const
@[simp]
theorem bsup_one (f : ∀ a < (1 : Ordinal), Ordinal) : bsup 1 f = f 0 zero_lt_one := by
simp_rw [← sup_eq_bsup, sup_unique, familyOfBFamily, familyOfBFamily', typein_one_out]
#align ordinal.bsup_one Ordinal.bsup_one
theorem bsup_le_of_brange_subset {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : brange o f ⊆ brange o' g) : bsup.{u, max v w} o f ≤ bsup.{v, max u w} o' g :=
bsup_le fun i hi => by
obtain ⟨j, hj, hj'⟩ := h ⟨i, hi, rfl⟩
rw [← hj']
apply le_bsup
#align ordinal.bsup_le_of_brange_subset Ordinal.bsup_le_of_brange_subset
theorem bsup_eq_of_brange_eq {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : brange o f = brange o' g) : bsup.{u, max v w} o f = bsup.{v, max u w} o' g :=
(bsup_le_of_brange_subset.{u, v, w} h.le).antisymm (bsup_le_of_brange_subset.{v, u, w} h.ge)
#align ordinal.bsup_eq_of_brange_eq Ordinal.bsup_eq_of_brange_eq
/-- The least strict upper bound of a family of ordinals. -/
def lsub {ι} (f : ι → Ordinal) : Ordinal :=
sup (succ ∘ f)
#align ordinal.lsub Ordinal.lsub
@[simp]
theorem sup_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} (succ ∘ f) = lsub.{_, v} f :=
rfl
#align ordinal.sup_eq_lsub Ordinal.sup_eq_lsub
theorem lsub_le_iff {ι : Type u} {f : ι → Ordinal.{max u v}} {a} :
lsub.{_, v} f ≤ a ↔ ∀ i, f i < a := by
convert sup_le_iff.{_, v} (f := succ ∘ f) (a := a) using 2
-- Porting note: `comp_apply` is required.
simp only [comp_apply, succ_le_iff]
#align ordinal.lsub_le_iff Ordinal.lsub_le_iff
theorem lsub_le {ι} {f : ι → Ordinal} {a} : (∀ i, f i < a) → lsub f ≤ a :=
lsub_le_iff.2
#align ordinal.lsub_le Ordinal.lsub_le
theorem lt_lsub {ι} (f : ι → Ordinal) (i) : f i < lsub f :=
succ_le_iff.1 (le_sup _ i)
#align ordinal.lt_lsub Ordinal.lt_lsub
theorem lt_lsub_iff {ι : Type u} {f : ι → Ordinal.{max u v}} {a} :
a < lsub.{_, v} f ↔ ∃ i, a ≤ f i := by
simpa only [not_forall, not_lt, not_le] using not_congr (@lsub_le_iff.{_, v} _ f a)
#align ordinal.lt_lsub_iff Ordinal.lt_lsub_iff
theorem sup_le_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) : sup.{_, v} f ≤ lsub.{_, v} f :=
sup_le fun i => (lt_lsub f i).le
#align ordinal.sup_le_lsub Ordinal.sup_le_lsub
theorem lsub_le_sup_succ {ι : Type u} (f : ι → Ordinal.{max u v}) :
lsub.{_, v} f ≤ succ (sup.{_, v} f) :=
lsub_le fun i => lt_succ_iff.2 (le_sup f i)
#align ordinal.lsub_le_sup_succ Ordinal.lsub_le_sup_succ
theorem sup_eq_lsub_or_sup_succ_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} f = lsub.{_, v} f ∨ succ (sup.{_, v} f) = lsub.{_, v} f := by
cases' eq_or_lt_of_le (sup_le_lsub.{_, v} f) with h h
· exact Or.inl h
· exact Or.inr ((succ_le_of_lt h).antisymm (lsub_le_sup_succ f))
#align ordinal.sup_eq_lsub_or_sup_succ_eq_lsub Ordinal.sup_eq_lsub_or_sup_succ_eq_lsub
theorem sup_succ_le_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
succ (sup.{_, v} f) ≤ lsub.{_, v} f ↔ ∃ i, f i = sup.{_, v} f := by
refine ⟨fun h => ?_, ?_⟩
· by_contra! hf
exact (succ_le_iff.1 h).ne ((sup_le_lsub f).antisymm (lsub_le (ne_sup_iff_lt_sup.1 hf)))
rintro ⟨_, hf⟩
rw [succ_le_iff, ← hf]
exact lt_lsub _ _
#align ordinal.sup_succ_le_lsub Ordinal.sup_succ_le_lsub
theorem sup_succ_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
succ (sup.{_, v} f) = lsub.{_, v} f ↔ ∃ i, f i = sup.{_, v} f :=
(lsub_le_sup_succ f).le_iff_eq.symm.trans (sup_succ_le_lsub f)
#align ordinal.sup_succ_eq_lsub Ordinal.sup_succ_eq_lsub
theorem sup_eq_lsub_iff_succ {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} f = lsub.{_, v} f ↔ ∀ a < lsub.{_, v} f, succ a < lsub.{_, v} f := by
refine ⟨fun h => ?_, fun hf => le_antisymm (sup_le_lsub f) (lsub_le fun i => ?_)⟩
· rw [← h]
exact fun a => sup_not_succ_of_ne_sup fun i => (lsub_le_iff.1 (le_of_eq h.symm) i).ne
by_contra! hle
have heq := (sup_succ_eq_lsub f).2 ⟨i, le_antisymm (le_sup _ _) hle⟩
have :=
hf _
(by
rw [← heq]
exact lt_succ (sup f))
rw [heq] at this
exact this.false
#align ordinal.sup_eq_lsub_iff_succ Ordinal.sup_eq_lsub_iff_succ
theorem sup_eq_lsub_iff_lt_sup {ι : Type u} (f : ι → Ordinal.{max u v}) :
sup.{_, v} f = lsub.{_, v} f ↔ ∀ i, f i < sup.{_, v} f :=
⟨fun h i => by
rw [h]
apply lt_lsub, fun h => le_antisymm (sup_le_lsub f) (lsub_le h)⟩
#align ordinal.sup_eq_lsub_iff_lt_sup Ordinal.sup_eq_lsub_iff_lt_sup
@[simp]
theorem lsub_empty {ι} [h : IsEmpty ι] (f : ι → Ordinal) : lsub f = 0 := by
rw [← Ordinal.le_zero, lsub_le_iff]
exact h.elim
#align ordinal.lsub_empty Ordinal.lsub_empty
theorem lsub_pos {ι : Type u} [h : Nonempty ι] (f : ι → Ordinal.{max u v}) : 0 < lsub.{_, v} f :=
h.elim fun i => (Ordinal.zero_le _).trans_lt (lt_lsub f i)
#align ordinal.lsub_pos Ordinal.lsub_pos
@[simp]
theorem lsub_eq_zero_iff {ι : Type u} (f : ι → Ordinal.{max u v}) :
lsub.{_, v} f = 0 ↔ IsEmpty ι := by
refine ⟨fun h => ⟨fun i => ?_⟩, fun h => @lsub_empty _ h _⟩
have := @lsub_pos.{_, v} _ ⟨i⟩ f
rw [h] at this
exact this.false
#align ordinal.lsub_eq_zero_iff Ordinal.lsub_eq_zero_iff
@[simp]
theorem lsub_const {ι} [Nonempty ι] (o : Ordinal) : (lsub fun _ : ι => o) = succ o :=
sup_const (succ o)
#align ordinal.lsub_const Ordinal.lsub_const
@[simp]
theorem lsub_unique {ι} [Unique ι] (f : ι → Ordinal) : lsub f = succ (f default) :=
sup_unique _
#align ordinal.lsub_unique Ordinal.lsub_unique
theorem lsub_le_of_range_subset {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f ⊆ Set.range g) : lsub.{u, max v w} f ≤ lsub.{v, max u w} g :=
sup_le_of_range_subset.{u, v, w} (by convert Set.image_subset succ h <;> apply Set.range_comp)
#align ordinal.lsub_le_of_range_subset Ordinal.lsub_le_of_range_subset
theorem lsub_eq_of_range_eq {ι ι'} {f : ι → Ordinal} {g : ι' → Ordinal}
(h : Set.range f = Set.range g) : lsub.{u, max v w} f = lsub.{v, max u w} g :=
(lsub_le_of_range_subset.{u, v, w} h.le).antisymm (lsub_le_of_range_subset.{v, u, w} h.ge)
#align ordinal.lsub_eq_of_range_eq Ordinal.lsub_eq_of_range_eq
@[simp]
theorem lsub_sum {α : Type u} {β : Type v} (f : Sum α β → Ordinal) :
lsub.{max u v, w} f =
max (lsub.{u, max v w} fun a => f (Sum.inl a)) (lsub.{v, max u w} fun b => f (Sum.inr b)) :=
sup_sum _
#align ordinal.lsub_sum Ordinal.lsub_sum
theorem lsub_not_mem_range {ι : Type u} (f : ι → Ordinal.{max u v}) :
lsub.{_, v} f ∉ Set.range f := fun ⟨i, h⟩ =>
h.not_lt (lt_lsub f i)
#align ordinal.lsub_not_mem_range Ordinal.lsub_not_mem_range
theorem nonempty_compl_range {ι : Type u} (f : ι → Ordinal.{max u v}) : (Set.range f)ᶜ.Nonempty :=
⟨_, lsub_not_mem_range.{_, v} f⟩
#align ordinal.nonempty_compl_range Ordinal.nonempty_compl_range
@[simp]
theorem lsub_typein (o : Ordinal) : lsub.{u, u} (typein ((· < ·) : o.out.α → o.out.α → Prop)) = o :=
(lsub_le.{u, u} typein_lt_self).antisymm
(by
by_contra! h
-- Porting note: `nth_rw` → `conv_rhs` & `rw`
conv_rhs at h => rw [← type_lt o]
simpa [typein_enum] using lt_lsub.{u, u} (typein (· < ·)) (enum (· < ·) _ h))
#align ordinal.lsub_typein Ordinal.lsub_typein
theorem sup_typein_limit {o : Ordinal} (ho : ∀ a, a < o → succ a < o) :
sup.{u, u} (typein ((· < ·) : o.out.α → o.out.α → Prop)) = o := by
-- Porting note: `rwa` → `rw` & `assumption`
rw [(sup_eq_lsub_iff_succ.{u, u} (typein (· < ·))).2] <;> rw [lsub_typein o]; assumption
#align ordinal.sup_typein_limit Ordinal.sup_typein_limit
@[simp]
theorem sup_typein_succ {o : Ordinal} :
sup.{u, u} (typein ((· < ·) : (succ o).out.α → (succ o).out.α → Prop)) = o := by
cases'
sup_eq_lsub_or_sup_succ_eq_lsub.{u, u}
(typein ((· < ·) : (succ o).out.α → (succ o).out.α → Prop)) with
h h
· rw [sup_eq_lsub_iff_succ] at h
simp only [lsub_typein] at h
exact (h o (lt_succ o)).false.elim
rw [← succ_eq_succ_iff, h]
apply lsub_typein
#align ordinal.sup_typein_succ Ordinal.sup_typein_succ
/-- The least strict upper bound of a family of ordinals indexed by the set of ordinals less than
some `o : Ordinal.{u}`.
This is to `lsub` as `bsup` is to `sup`. -/
def blsub (o : Ordinal.{u}) (f : ∀ a < o, Ordinal.{max u v}) : Ordinal.{max u v} :=
bsup.{_, v} o fun a ha => succ (f a ha)
#align ordinal.blsub Ordinal.blsub
@[simp]
theorem bsup_eq_blsub (o : Ordinal.{u}) (f : ∀ a < o, Ordinal.{max u v}) :
(bsup.{_, v} o fun a ha => succ (f a ha)) = blsub.{_, v} o f :=
rfl
#align ordinal.bsup_eq_blsub Ordinal.bsup_eq_blsub
theorem lsub_eq_blsub' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r] {o} (ho : type r = o)
(f : ∀ a < o, Ordinal.{max u v}) : lsub.{_, v} (familyOfBFamily' r ho f) = blsub.{_, v} o f :=
sup_eq_bsup'.{_, v} r ho fun a ha => succ (f a ha)
#align ordinal.lsub_eq_blsub' Ordinal.lsub_eq_blsub'
theorem lsub_eq_lsub {ι ι' : Type u} (r : ι → ι → Prop) (r' : ι' → ι' → Prop) [IsWellOrder ι r]
[IsWellOrder ι' r'] {o} (ho : type r = o) (ho' : type r' = o)
(f : ∀ a < o, Ordinal.{max u v}) :
lsub.{_, v} (familyOfBFamily' r ho f) = lsub.{_, v} (familyOfBFamily' r' ho' f) := by
rw [lsub_eq_blsub', lsub_eq_blsub']
#align ordinal.lsub_eq_lsub Ordinal.lsub_eq_lsub
@[simp]
theorem lsub_eq_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
lsub.{_, v} (familyOfBFamily o f) = blsub.{_, v} o f :=
lsub_eq_blsub' _ _ _
#align ordinal.lsub_eq_blsub Ordinal.lsub_eq_blsub
@[simp]
theorem blsub_eq_lsub' {ι : Type u} (r : ι → ι → Prop) [IsWellOrder ι r]
(f : ι → Ordinal.{max u v}) : blsub.{_, v} _ (bfamilyOfFamily' r f) = lsub.{_, v} f :=
bsup_eq_sup'.{_, v} r (succ ∘ f)
#align ordinal.blsub_eq_lsub' Ordinal.blsub_eq_lsub'
theorem blsub_eq_blsub {ι : Type u} (r r' : ι → ι → Prop) [IsWellOrder ι r] [IsWellOrder ι r']
(f : ι → Ordinal.{max u v}) :
blsub.{_, v} _ (bfamilyOfFamily' r f) = blsub.{_, v} _ (bfamilyOfFamily' r' f) := by
rw [blsub_eq_lsub', blsub_eq_lsub']
#align ordinal.blsub_eq_blsub Ordinal.blsub_eq_blsub
@[simp]
theorem blsub_eq_lsub {ι : Type u} (f : ι → Ordinal.{max u v}) :
blsub.{_, v} _ (bfamilyOfFamily f) = lsub.{_, v} f :=
blsub_eq_lsub' _ _
#align ordinal.blsub_eq_lsub Ordinal.blsub_eq_lsub
@[congr]
theorem blsub_congr {o₁ o₂ : Ordinal.{u}} (f : ∀ a < o₁, Ordinal.{max u v}) (ho : o₁ = o₂) :
blsub.{_, v} o₁ f = blsub.{_, v} o₂ fun a h => f a (h.trans_eq ho.symm) := by
subst ho
-- Porting note: `rfl` is required.
rfl
#align ordinal.blsub_congr Ordinal.blsub_congr
theorem blsub_le_iff {o : Ordinal.{u}} {f : ∀ a < o, Ordinal.{max u v}} {a} :
blsub.{_, v} o f ≤ a ↔ ∀ i h, f i h < a := by
convert bsup_le_iff.{_, v} (f := fun a ha => succ (f a ha)) (a := a) using 2
simp_rw [succ_le_iff]
#align ordinal.blsub_le_iff Ordinal.blsub_le_iff
theorem blsub_le {o : Ordinal} {f : ∀ b < o, Ordinal} {a} : (∀ i h, f i h < a) → blsub o f ≤ a :=
blsub_le_iff.2
#align ordinal.blsub_le Ordinal.blsub_le
theorem lt_blsub {o} (f : ∀ a < o, Ordinal) (i h) : f i h < blsub o f :=
blsub_le_iff.1 le_rfl _ _
#align ordinal.lt_blsub Ordinal.lt_blsub
theorem lt_blsub_iff {o : Ordinal.{u}} {f : ∀ b < o, Ordinal.{max u v}} {a} :
a < blsub.{_, v} o f ↔ ∃ i hi, a ≤ f i hi := by
simpa only [not_forall, not_lt, not_le] using not_congr (@blsub_le_iff.{_, v} _ f a)
#align ordinal.lt_blsub_iff Ordinal.lt_blsub_iff
theorem bsup_le_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f ≤ blsub.{_, v} o f :=
bsup_le fun i h => (lt_blsub f i h).le
#align ordinal.bsup_le_blsub Ordinal.bsup_le_blsub
theorem blsub_le_bsup_succ {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
blsub.{_, v} o f ≤ succ (bsup.{_, v} o f) :=
blsub_le fun i h => lt_succ_iff.2 (le_bsup f i h)
#align ordinal.blsub_le_bsup_succ Ordinal.blsub_le_bsup_succ
theorem bsup_eq_blsub_or_succ_bsup_eq_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f = blsub.{_, v} o f ∨ succ (bsup.{_, v} o f) = blsub.{_, v} o f := by
rw [← sup_eq_bsup, ← lsub_eq_blsub]
exact sup_eq_lsub_or_sup_succ_eq_lsub _
#align ordinal.bsup_eq_blsub_or_succ_bsup_eq_blsub Ordinal.bsup_eq_blsub_or_succ_bsup_eq_blsub
theorem bsup_succ_le_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
succ (bsup.{_, v} o f) ≤ blsub.{_, v} o f ↔ ∃ i hi, f i hi = bsup.{_, v} o f := by
refine ⟨fun h => ?_, ?_⟩
· by_contra! hf
exact
ne_of_lt (succ_le_iff.1 h)
(le_antisymm (bsup_le_blsub f) (blsub_le (lt_bsup_of_ne_bsup.1 hf)))
rintro ⟨_, _, hf⟩
rw [succ_le_iff, ← hf]
exact lt_blsub _ _ _
#align ordinal.bsup_succ_le_blsub Ordinal.bsup_succ_le_blsub
theorem bsup_succ_eq_blsub {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
succ (bsup.{_, v} o f) = blsub.{_, v} o f ↔ ∃ i hi, f i hi = bsup.{_, v} o f :=
(blsub_le_bsup_succ f).le_iff_eq.symm.trans (bsup_succ_le_blsub f)
#align ordinal.bsup_succ_eq_blsub Ordinal.bsup_succ_eq_blsub
theorem bsup_eq_blsub_iff_succ {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f = blsub.{_, v} o f ↔ ∀ a < blsub.{_, v} o f, succ a < blsub.{_, v} o f := by
rw [← sup_eq_bsup, ← lsub_eq_blsub]
apply sup_eq_lsub_iff_succ
#align ordinal.bsup_eq_blsub_iff_succ Ordinal.bsup_eq_blsub_iff_succ
theorem bsup_eq_blsub_iff_lt_bsup {o : Ordinal.{u}} (f : ∀ a < o, Ordinal.{max u v}) :
bsup.{_, v} o f = blsub.{_, v} o f ↔ ∀ i hi, f i hi < bsup.{_, v} o f :=
⟨fun h i => by
rw [h]
apply lt_blsub, fun h => le_antisymm (bsup_le_blsub f) (blsub_le h)⟩
#align ordinal.bsup_eq_blsub_iff_lt_bsup Ordinal.bsup_eq_blsub_iff_lt_bsup
theorem bsup_eq_blsub_of_lt_succ_limit {o : Ordinal.{u}} (ho : IsLimit o)
{f : ∀ a < o, Ordinal.{max u v}} (hf : ∀ a ha, f a ha < f (succ a) (ho.2 a ha)) :
bsup.{_, v} o f = blsub.{_, v} o f := by
rw [bsup_eq_blsub_iff_lt_bsup]
exact fun i hi => (hf i hi).trans_le (le_bsup f _ _)
#align ordinal.bsup_eq_blsub_of_lt_succ_limit Ordinal.bsup_eq_blsub_of_lt_succ_limit
theorem blsub_succ_of_mono {o : Ordinal.{u}} {f : ∀ a < succ o, Ordinal.{max u v}}
(hf : ∀ {i j} (hi hj), i ≤ j → f i hi ≤ f j hj) : blsub.{_, v} _ f = succ (f o (lt_succ o)) :=
bsup_succ_of_mono fun {_ _} hi hj h => succ_le_succ (hf hi hj h)
#align ordinal.blsub_succ_of_mono Ordinal.blsub_succ_of_mono
@[simp]
theorem blsub_eq_zero_iff {o} {f : ∀ a < o, Ordinal} : blsub o f = 0 ↔ o = 0 := by
rw [← lsub_eq_blsub, lsub_eq_zero_iff]
exact out_empty_iff_eq_zero
#align ordinal.blsub_eq_zero_iff Ordinal.blsub_eq_zero_iff
-- Porting note: `rwa` → `rw`
@[simp]
theorem blsub_zero (f : ∀ a < (0 : Ordinal), Ordinal) : blsub 0 f = 0 := by rw [blsub_eq_zero_iff]
#align ordinal.blsub_zero Ordinal.blsub_zero
theorem blsub_pos {o : Ordinal} (ho : 0 < o) (f : ∀ a < o, Ordinal) : 0 < blsub o f :=
(Ordinal.zero_le _).trans_lt (lt_blsub f 0 ho)
#align ordinal.blsub_pos Ordinal.blsub_pos
theorem blsub_type {α : Type u} (r : α → α → Prop) [IsWellOrder α r]
(f : ∀ a < type r, Ordinal.{max u v}) :
blsub.{_, v} (type r) f = lsub.{_, v} fun a => f (typein r a) (typein_lt_type _ _) :=
eq_of_forall_ge_iff fun o => by
rw [blsub_le_iff, lsub_le_iff];
exact ⟨fun H b => H _ _, fun H i h => by simpa only [typein_enum] using H (enum r i h)⟩
#align ordinal.blsub_type Ordinal.blsub_type
theorem blsub_const {o : Ordinal} (ho : o ≠ 0) (a : Ordinal) :
(blsub.{u, v} o fun _ _ => a) = succ a :=
bsup_const.{u, v} ho (succ a)
#align ordinal.blsub_const Ordinal.blsub_const
@[simp]
theorem blsub_one (f : ∀ a < (1 : Ordinal), Ordinal) : blsub 1 f = succ (f 0 zero_lt_one) :=
bsup_one _
#align ordinal.blsub_one Ordinal.blsub_one
@[simp]
theorem blsub_id : ∀ o, (blsub.{u, u} o fun x _ => x) = o :=
lsub_typein
#align ordinal.blsub_id Ordinal.blsub_id
theorem bsup_id_limit {o : Ordinal} : (∀ a < o, succ a < o) → (bsup.{u, u} o fun x _ => x) = o :=
sup_typein_limit
#align ordinal.bsup_id_limit Ordinal.bsup_id_limit
@[simp]
theorem bsup_id_succ (o) : (bsup.{u, u} (succ o) fun x _ => x) = o :=
sup_typein_succ
#align ordinal.bsup_id_succ Ordinal.bsup_id_succ
theorem blsub_le_of_brange_subset {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : brange o f ⊆ brange o' g) : blsub.{u, max v w} o f ≤ blsub.{v, max u w} o' g :=
bsup_le_of_brange_subset.{u, v, w} fun a ⟨b, hb, hb'⟩ => by
obtain ⟨c, hc, hc'⟩ := h ⟨b, hb, rfl⟩
simp_rw [← hc'] at hb'
exact ⟨c, hc, hb'⟩
#align ordinal.blsub_le_of_brange_subset Ordinal.blsub_le_of_brange_subset
theorem blsub_eq_of_brange_eq {o o'} {f : ∀ a < o, Ordinal} {g : ∀ a < o', Ordinal}
(h : { o | ∃ i hi, f i hi = o } = { o | ∃ i hi, g i hi = o }) :
blsub.{u, max v w} o f = blsub.{v, max u w} o' g :=
(blsub_le_of_brange_subset.{u, v, w} h.le).antisymm (blsub_le_of_brange_subset.{v, u, w} h.ge)
#align ordinal.blsub_eq_of_brange_eq Ordinal.blsub_eq_of_brange_eq
theorem bsup_comp {o o' : Ordinal.{max u v}} {f : ∀ a < o, Ordinal.{max u v w}}
(hf : ∀ {i j} (hi) (hj), i ≤ j → f i hi ≤ f j hj) {g : ∀ a < o', Ordinal.{max u v}}
(hg : blsub.{_, u} o' g = o) :
(bsup.{_, w} o' fun a ha => f (g a ha) (by rw [← hg]; apply lt_blsub)) = bsup.{_, w} o f := by
apply le_antisymm <;> refine bsup_le fun i hi => ?_
· apply le_bsup
· rw [← hg, lt_blsub_iff] at hi
rcases hi with ⟨j, hj, hj'⟩
exact (hf _ _ hj').trans (le_bsup _ _ _)
#align ordinal.bsup_comp Ordinal.bsup_comp
theorem blsub_comp {o o' : Ordinal.{max u v}} {f : ∀ a < o, Ordinal.{max u v w}}
(hf : ∀ {i j} (hi) (hj), i ≤ j → f i hi ≤ f j hj) {g : ∀ a < o', Ordinal.{max u v}}
(hg : blsub.{_, u} o' g = o) :
(blsub.{_, w} o' fun a ha => f (g a ha) (by rw [← hg]; apply lt_blsub)) = blsub.{_, w} o f :=
@bsup_comp.{u, v, w} o _ (fun a ha => succ (f a ha))
(fun {_ _} _ _ h => succ_le_succ_iff.2 (hf _ _ h)) g hg
#align ordinal.blsub_comp Ordinal.blsub_comp
theorem IsNormal.bsup_eq {f : Ordinal.{u} → Ordinal.{max u v}} (H : IsNormal f) {o : Ordinal.{u}}
(h : IsLimit o) : (Ordinal.bsup.{_, v} o fun x _ => f x) = f o := by
rw [← IsNormal.bsup.{u, u, v} H (fun x _ => x) h.1, bsup_id_limit h.2]
#align ordinal.is_normal.bsup_eq Ordinal.IsNormal.bsup_eq
theorem IsNormal.blsub_eq {f : Ordinal.{u} → Ordinal.{max u v}} (H : IsNormal f) {o : Ordinal.{u}}
(h : IsLimit o) : (blsub.{_, v} o fun x _ => f x) = f o := by
rw [← IsNormal.bsup_eq.{u, v} H h, bsup_eq_blsub_of_lt_succ_limit h]
exact fun a _ => H.1 a
#align ordinal.is_normal.blsub_eq Ordinal.IsNormal.blsub_eq
theorem isNormal_iff_lt_succ_and_bsup_eq {f : Ordinal.{u} → Ordinal.{max u v}} :
IsNormal f ↔ (∀ a, f a < f (succ a)) ∧ ∀ o, IsLimit o → (bsup.{_, v} o fun x _ => f x) = f o :=
⟨fun h => ⟨h.1, @IsNormal.bsup_eq f h⟩, fun ⟨h₁, h₂⟩ =>
⟨h₁, fun o ho a => by
rw [← h₂ o ho]
exact bsup_le_iff⟩⟩
#align ordinal.is_normal_iff_lt_succ_and_bsup_eq Ordinal.isNormal_iff_lt_succ_and_bsup_eq
theorem isNormal_iff_lt_succ_and_blsub_eq {f : Ordinal.{u} → Ordinal.{max u v}} :
IsNormal f ↔ (∀ a, f a < f (succ a)) ∧
∀ o, IsLimit o → (blsub.{_, v} o fun x _ => f x) = f o := by
rw [isNormal_iff_lt_succ_and_bsup_eq.{u, v}, and_congr_right_iff]
intro h
constructor <;> intro H o ho <;> have := H o ho <;>
rwa [← bsup_eq_blsub_of_lt_succ_limit ho fun a _ => h a] at *
#align ordinal.is_normal_iff_lt_succ_and_blsub_eq Ordinal.isNormal_iff_lt_succ_and_blsub_eq
theorem IsNormal.eq_iff_zero_and_succ {f g : Ordinal.{u} → Ordinal.{u}} (hf : IsNormal f)
(hg : IsNormal g) : f = g ↔ f 0 = g 0 ∧ ∀ a, f a = g a → f (succ a) = g (succ a) :=
⟨fun h => by simp [h], fun ⟨h₁, h₂⟩ =>
funext fun a => by
induction' a using limitRecOn with _ _ _ ho H
any_goals solve_by_elim
rw [← IsNormal.bsup_eq.{u, u} hf ho, ← IsNormal.bsup_eq.{u, u} hg ho]
congr
ext b hb
exact H b hb⟩
#align ordinal.is_normal.eq_iff_zero_and_succ Ordinal.IsNormal.eq_iff_zero_and_succ
/-- A two-argument version of `Ordinal.blsub`.
We don't develop a full API for this, since it's only used in a handful of existence results. -/
def blsub₂ (o₁ o₂ : Ordinal) (op : {a : Ordinal} → (a < o₁) → {b : Ordinal} → (b < o₂) → Ordinal) :
Ordinal :=
lsub (fun x : o₁.out.α × o₂.out.α => op (typein_lt_self x.1) (typein_lt_self x.2))
#align ordinal.blsub₂ Ordinal.blsub₂
theorem lt_blsub₂ {o₁ o₂ : Ordinal}
(op : {a : Ordinal} → (a < o₁) → {b : Ordinal} → (b < o₂) → Ordinal) {a b : Ordinal}
(ha : a < o₁) (hb : b < o₂) : op ha hb < blsub₂ o₁ o₂ op := by
convert lt_lsub _ (Prod.mk (enum (· < ·) a (by rwa [type_lt]))
(enum (· < ·) b (by rwa [type_lt])))
simp only [typein_enum]
#align ordinal.lt_blsub₂ Ordinal.lt_blsub₂
/-! ### Minimum excluded ordinals -/
/-- The minimum excluded ordinal in a family of ordinals. -/
def mex {ι : Type u} (f : ι → Ordinal.{max u v}) : Ordinal :=
sInf (Set.range f)ᶜ
#align ordinal.mex Ordinal.mex
theorem mex_not_mem_range {ι : Type u} (f : ι → Ordinal.{max u v}) : mex.{_, v} f ∉ Set.range f :=
csInf_mem (nonempty_compl_range.{_, v} f)
#align ordinal.mex_not_mem_range Ordinal.mex_not_mem_range
| Mathlib/SetTheory/Ordinal/Arithmetic.lean | 2,025 | 2,028 | theorem le_mex_of_forall {ι : Type u} {f : ι → Ordinal.{max u v}} {a : Ordinal}
(H : ∀ b < a, ∃ i, f i = b) : a ≤ mex.{_, v} f := by |
by_contra! h
exact mex_not_mem_range f (H _ h)
|
/-
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. -/
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
#align measurable.measurable_set_preimage_iff_of_surjective Measurable.measurableSet_preimage_iff_of_surjective
theorem map_measurableSpace_eq [CountablySeparated Z]
{f : X → Z} (hf : Measurable f)
(hsurj : Surjective f) : MeasurableSpace.map f ‹MeasurableSpace X› = ‹MeasurableSpace Z› :=
MeasurableSpace.ext fun _ => hf.measurableSet_preimage_iff_of_surjective hsurj
#align measurable.map_measurable_space_eq Measurable.map_measurableSpace_eq
theorem map_measurableSpace_eq_borel [SecondCountableTopology Y] {f : X → Y} (hf : Measurable f)
(hsurj : Surjective f) : MeasurableSpace.map f ‹MeasurableSpace X› = borel Y := by
have d := hf.mono le_rfl OpensMeasurableSpace.borel_le
letI := borel Y; haveI : BorelSpace Y := ⟨rfl⟩
exact d.map_measurableSpace_eq hsurj
#align measurable.map_measurable_space_eq_borel Measurable.map_measurableSpace_eq_borel
theorem borelSpace_codomain [SecondCountableTopology Y] {f : X → Y} (hf : Measurable f)
(hsurj : Surjective f) : BorelSpace Y :=
⟨(hf.map_measurableSpace_eq hsurj).symm.trans <| hf.map_measurableSpace_eq_borel hsurj⟩
#align measurable.borel_space_codomain Measurable.borelSpace_codomain
/-- If `f : X → Z` is a 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 in `Set.range f`. -/
theorem measurableSet_preimage_iff_preimage_val {f : X → Z} [CountablySeparated (range f)]
(hf : Measurable f) {s : Set Z} :
MeasurableSet (f ⁻¹' s) ↔ MeasurableSet ((↑) ⁻¹' s : Set (range f)) :=
have hf' : Measurable (rangeFactorization f) := hf.subtype_mk
hf'.measurableSet_preimage_iff_of_surjective (s := Subtype.val ⁻¹' s) surjective_onto_range
#align measurable.measurable_set_preimage_iff_preimage_coe Measurable.measurableSet_preimage_iff_preimage_val
/-- If `f : X → Z` is a Borel measurable map from a standard Borel space to a
countably separated measurable space and the range of `f` is measurable,
then the preimage of a set `s` is measurable
if and only if the intesection with `Set.range f` is measurable. -/
theorem measurableSet_preimage_iff_inter_range {f : X → Z} [CountablySeparated (range f)]
(hf : Measurable f) (hr : MeasurableSet (range f)) {s : Set Z} :
MeasurableSet (f ⁻¹' s) ↔ MeasurableSet (s ∩ range f) := by
rw [hf.measurableSet_preimage_iff_preimage_val, inter_comm,
← (MeasurableEmbedding.subtype_coe hr).measurableSet_image, Subtype.image_preimage_coe]
#align measurable.measurable_set_preimage_iff_inter_range Measurable.measurableSet_preimage_iff_inter_range
/-- If `f : X → Z` is a Borel measurable map from a standard Borel space
to a countably separated measurable space,
then for any measurable space `β` and `g : Z → β`, the composition `g ∘ f` is
measurable if and only if the restriction of `g` to the range of `f` is measurable. -/
theorem measurable_comp_iff_restrict {f : X → Z}
[CountablySeparated (range f)]
(hf : Measurable f) {g : Z → β} : Measurable (g ∘ f) ↔ Measurable (restrict (range f) g) :=
forall₂_congr fun s _ => measurableSet_preimage_iff_preimage_val hf (s := g ⁻¹' s)
#align measurable.measurable_comp_iff_restrict Measurable.measurable_comp_iff_restrict
/-- If `f : X → Z` is a surjective Borel measurable map from a standard Borel space
to a countably separated measurable space,
then for any measurable space `α` and `g : Z → α`, the composition
`g ∘ f` is measurable if and only if `g` is measurable. -/
theorem measurable_comp_iff_of_surjective [CountablySeparated Z]
{f : X → Z} (hf : Measurable f) (hsurj : Surjective f)
{g : Z → β} : Measurable (g ∘ f) ↔ Measurable g :=
forall₂_congr fun s _ => measurableSet_preimage_iff_of_surjective hf hsurj (s := g ⁻¹' s)
#align measurable.measurable_comp_iff_of_surjective Measurable.measurable_comp_iff_of_surjective
end Measurable
theorem Continuous.map_eq_borel {X Y : Type*} [TopologicalSpace X] [PolishSpace X]
[MeasurableSpace X] [BorelSpace X] [TopologicalSpace Y] [T0Space Y] [SecondCountableTopology Y]
{f : X → Y} (hf : Continuous f) (hsurj : Surjective f) :
MeasurableSpace.map f ‹MeasurableSpace X› = borel Y := by
borelize Y
exact hf.measurable.map_measurableSpace_eq hsurj
#align continuous.map_eq_borel Continuous.map_eq_borel
theorem Continuous.map_borel_eq {X Y : Type*} [TopologicalSpace X] [PolishSpace X]
[TopologicalSpace Y] [T0Space Y] [SecondCountableTopology Y] {f : X → Y} (hf : Continuous f)
(hsurj : Surjective f) : MeasurableSpace.map f (borel X) = borel Y := by
borelize X
exact hf.map_eq_borel hsurj
#align continuous.map_borel_eq Continuous.map_borel_eq
instance Quotient.borelSpace {X : Type*} [TopologicalSpace X] [PolishSpace X] [MeasurableSpace X]
[BorelSpace X] {s : Setoid X} [T0Space (Quotient s)] [SecondCountableTopology (Quotient s)] :
BorelSpace (Quotient s) :=
⟨continuous_quotient_mk'.map_eq_borel (surjective_quotient_mk' _)⟩
#align quotient.borel_space Quotient.borelSpace
/-- When the subgroup `N < G` is not necessarily `Normal`, we have a `CosetSpace` as opposed
to `QuotientGroup` (the next `instance`).
TODO: typeclass inference should normally find this, but currently doesn't.
E.g., `MeasurableSMul G (G ⧸ Γ)` fails to synthesize, even though `G ⧸ Γ` is the quotient
of `G` by the action of `Γ`; it seems unable to pick up the `BorelSpace` instance. -/
@[to_additive AddCosetSpace.borelSpace]
instance CosetSpace.borelSpace {G : Type*} [TopologicalSpace G] [PolishSpace G] [Group G]
[MeasurableSpace G] [BorelSpace G] {N : Subgroup G} [T2Space (G ⧸ N)]
[SecondCountableTopology (G ⧸ N)] : BorelSpace (G ⧸ N) := Quotient.borelSpace
@[to_additive]
instance QuotientGroup.borelSpace {G : Type*} [TopologicalSpace G] [PolishSpace G] [Group G]
[TopologicalGroup G] [MeasurableSpace G] [BorelSpace G] {N : Subgroup G} [N.Normal]
[IsClosed (N : Set G)] : BorelSpace (G ⧸ N) :=
-- Porting note: 1st and 3rd `haveI`s were not needed in Lean 3
haveI := Subgroup.t3_quotient_of_isClosed N
haveI := QuotientGroup.secondCountableTopology (Γ := N)
Quotient.borelSpace
#align quotient_group.borel_space QuotientGroup.borelSpace
#align quotient_add_group.borel_space QuotientAddGroup.borelSpace
namespace MeasureTheory
/-! ### Injective images of Borel sets -/
variable {γ : Type*}
/-- The **Lusin-Souslin theorem**: the range of a continuous injective function defined on a Polish
space is Borel-measurable. -/
theorem measurableSet_range_of_continuous_injective {β : Type*} [TopologicalSpace γ]
[PolishSpace γ] [TopologicalSpace β] [T2Space β] [MeasurableSpace β] [OpensMeasurableSpace β]
{f : γ → β} (f_cont : Continuous f) (f_inj : Injective f) :
MeasurableSet (range f) := by
/- We follow [Fremlin, *Measure Theory* (volume 4, 423I)][fremlin_vol4].
Let `b = {s i}` be a countable basis for `α`. When `s i` and `s j` are disjoint, their images
are disjoint analytic sets, hence by the separation theorem one can find a Borel-measurable set
`q i j` separating them.
Let `E i = closure (f '' s i) ∩ ⋂ j, q i j \ q j i`. It contains `f '' (s i)` and it is
measurable. Let `F n = ⋃ E i`, where the union is taken over those `i` for which `diam (s i)`
is bounded by some number `u n` tending to `0` with `n`.
We claim that `range f = ⋂ F n`, from which the measurability is obvious. The inclusion `⊆` is
straightforward. To show `⊇`, consider a point `x` in the intersection. For each `n`, it belongs
to some `E i` with `diam (s i) ≤ u n`. Pick a point `y i ∈ s i`. We claim that for such `i`
and `j`, the intersection `s i ∩ s j` is nonempty: if it were empty, then thanks to the
separating set `q i j` in the definition of `E i` one could not have `x ∈ E i ∩ E j`.
Since these two sets have small diameter, it follows that `y i` and `y j` are close.
Thus, `y` is a Cauchy sequence, converging to a limit `z`. We claim that `f z = x`, completing
the proof.
Otherwise, one could find open sets `v` and `w` separating `f z` from `x`. Then, for large `n`,
the image `f '' (s i)` would be included in `v` by continuity of `f`, so its closure would be
contained in the closure of `v`, and therefore it would be disjoint from `w`. This is a
contradiction since `x` belongs both to this closure and to `w`. -/
letI := upgradePolishSpace γ
obtain ⟨b, b_count, b_nonempty, hb⟩ :
∃ b : Set (Set γ), b.Countable ∧ ∅ ∉ b ∧ IsTopologicalBasis b := exists_countable_basis γ
haveI : Encodable b := b_count.toEncodable
let A := { p : b × b // Disjoint (p.1 : Set γ) p.2 }
-- for each pair of disjoint sets in the topological basis `b`, consider Borel sets separating
-- their images, by injectivity of `f` and the Lusin separation theorem.
have : ∀ p : A, ∃ q : Set β,
f '' (p.1.1 : Set γ) ⊆ q ∧ Disjoint (f '' (p.1.2 : Set γ)) q ∧ MeasurableSet q := by
intro p
apply
AnalyticSet.measurablySeparable ((hb.isOpen p.1.1.2).analyticSet_image f_cont)
((hb.isOpen p.1.2.2).analyticSet_image f_cont)
exact Disjoint.image p.2 f_inj.injOn (subset_univ _) (subset_univ _)
choose q hq1 hq2 q_meas using this
-- define sets `E i` and `F n` as in the proof sketch above
let E : b → Set β := fun s =>
closure (f '' s) ∩ ⋂ (t : b) (ht : Disjoint s.1 t.1), q ⟨(s, t), ht⟩ \ q ⟨(t, s), ht.symm⟩
obtain ⟨u, u_anti, u_pos, u_lim⟩ :
∃ u : ℕ → ℝ, StrictAnti u ∧ (∀ n : ℕ, 0 < u n) ∧ Tendsto u atTop (𝓝 0) :=
exists_seq_strictAnti_tendsto (0 : ℝ)
let F : ℕ → Set β := fun n => ⋃ (s : b) (_ : IsBounded s.1 ∧ diam s.1 ≤ u n), E s
-- it is enough to show that `range f = ⋂ F n`, as the latter set is obviously measurable.
suffices range f = ⋂ n, F n by
have E_meas : ∀ s : b, MeasurableSet (E s) := by
intro b
refine isClosed_closure.measurableSet.inter ?_
refine MeasurableSet.iInter fun s => ?_
exact MeasurableSet.iInter fun hs => (q_meas _).diff (q_meas _)
have F_meas : ∀ n, MeasurableSet (F n) := by
intro n
refine MeasurableSet.iUnion fun s => ?_
exact MeasurableSet.iUnion fun _ => E_meas _
rw [this]
exact MeasurableSet.iInter fun n => F_meas n
-- we check both inclusions.
apply Subset.antisymm
-- we start with the easy inclusion `range f ⊆ ⋂ F n`. One just needs to unfold the definitions.
· rintro x ⟨y, rfl⟩
refine mem_iInter.2 fun n => ?_
obtain ⟨s, sb, ys, hs⟩ : ∃ (s : Set γ), s ∈ b ∧ y ∈ s ∧ s ⊆ ball y (u n / 2) := by
apply hb.mem_nhds_iff.1
exact ball_mem_nhds _ (half_pos (u_pos n))
have diam_s : diam s ≤ u n := by
apply (diam_mono hs isBounded_ball).trans
convert diam_ball (x := y) (half_pos (u_pos n)).le
ring
refine mem_iUnion.2 ⟨⟨s, sb⟩, ?_⟩
refine mem_iUnion.2 ⟨⟨isBounded_ball.subset hs, diam_s⟩, ?_⟩
apply mem_inter (subset_closure (mem_image_of_mem _ ys))
refine mem_iInter.2 fun t => mem_iInter.2 fun ht => ⟨?_, ?_⟩
· apply hq1
exact mem_image_of_mem _ ys
· apply disjoint_left.1 (hq2 ⟨(t, ⟨s, sb⟩), ht.symm⟩)
exact mem_image_of_mem _ ys
-- Now, let us prove the harder inclusion `⋂ F n ⊆ range f`.
· intro x hx
-- pick for each `n` a good set `s n` of small diameter for which `x ∈ E (s n)`.
have C1 : ∀ n, ∃ (s : b) (_ : IsBounded s.1 ∧ diam s.1 ≤ u n), x ∈ E s := fun n => by
simpa only [F, mem_iUnion] using mem_iInter.1 hx n
choose s hs hxs using C1
have C2 : ∀ n, (s n).1.Nonempty := by
intro n
rw [nonempty_iff_ne_empty]
intro hn
have := (s n).2
rw [hn] at this
exact b_nonempty this
-- choose a point `y n ∈ s n`.
choose y hy using C2
have I : ∀ m n, ((s m).1 ∩ (s n).1).Nonempty := by
intro m n
rw [← not_disjoint_iff_nonempty_inter]
by_contra! h
have A : x ∈ q ⟨(s m, s n), h⟩ \ q ⟨(s n, s m), h.symm⟩ :=
haveI := mem_iInter.1 (hxs m).2 (s n)
(mem_iInter.1 this h : _)
have B : x ∈ q ⟨(s n, s m), h.symm⟩ \ q ⟨(s m, s n), h⟩ :=
haveI := mem_iInter.1 (hxs n).2 (s m)
(mem_iInter.1 this h.symm : _)
exact A.2 B.1
-- the points `y n` are nearby, and therefore they form a Cauchy sequence.
have cauchy_y : CauchySeq y := by
have : Tendsto (fun n => 2 * u n) atTop (𝓝 0) := by
simpa only [mul_zero] using u_lim.const_mul 2
refine cauchySeq_of_le_tendsto_0' (fun n => 2 * u n) (fun m n hmn => ?_) this
rcases I m n with ⟨z, zsm, zsn⟩
calc
dist (y m) (y n) ≤ dist (y m) z + dist z (y n) := dist_triangle _ _ _
_ ≤ u m + u n :=
(add_le_add ((dist_le_diam_of_mem (hs m).1 (hy m) zsm).trans (hs m).2)
((dist_le_diam_of_mem (hs n).1 zsn (hy n)).trans (hs n).2))
_ ≤ 2 * u m := by linarith [u_anti.antitone hmn]
haveI : Nonempty γ := ⟨y 0⟩
-- let `z` be its limit.
let z := limUnder atTop y
have y_lim : Tendsto y atTop (𝓝 z) := cauchy_y.tendsto_limUnder
suffices f z = x by
rw [← this]
exact mem_range_self _
-- assume for a contradiction that `f z ≠ x`.
by_contra! hne
-- introduce disjoint open sets `v` and `w` separating `f z` from `x`.
obtain ⟨v, w, v_open, w_open, fzv, xw, hvw⟩ := t2_separation hne
obtain ⟨δ, δpos, hδ⟩ : ∃ δ > (0 : ℝ), ball z δ ⊆ f ⁻¹' v := by
apply Metric.mem_nhds_iff.1
exact f_cont.continuousAt.preimage_mem_nhds (v_open.mem_nhds fzv)
obtain ⟨n, hn⟩ : ∃ n, u n + dist (y n) z < δ :=
haveI : Tendsto (fun n => u n + dist (y n) z) atTop (𝓝 0) := by
simpa only [add_zero] using u_lim.add (tendsto_iff_dist_tendsto_zero.1 y_lim)
((tendsto_order.1 this).2 _ δpos).exists
-- for large enough `n`, the image of `s n` is contained in `v`, by continuity of `f`.
have fsnv : f '' s n ⊆ v := by
rw [image_subset_iff]
apply Subset.trans _ hδ
intro a ha
calc
dist a z ≤ dist a (y n) + dist (y n) z := dist_triangle _ _ _
_ ≤ u n + dist (y n) z :=
(add_le_add_right ((dist_le_diam_of_mem (hs n).1 ha (hy n)).trans (hs n).2) _)
_ < δ := hn
-- as `x` belongs to the closure of `f '' (s n)`, it belongs to the closure of `v`.
have : x ∈ closure v := closure_mono fsnv (hxs n).1
-- this is a contradiction, as `x` is supposed to belong to `w`, which is disjoint from
-- the closure of `v`.
exact disjoint_left.1 (hvw.closure_left w_open) this xw
#align measure_theory.measurable_set_range_of_continuous_injective MeasureTheory.measurableSet_range_of_continuous_injective
theorem _root_.IsClosed.measurableSet_image_of_continuousOn_injOn
[TopologicalSpace γ] [PolishSpace γ] {β : Type*} [TopologicalSpace β] [T2Space β]
[MeasurableSpace β] [OpensMeasurableSpace β] {s : Set γ} (hs : IsClosed s) {f : γ → β}
(f_cont : ContinuousOn f s) (f_inj : InjOn f s) : MeasurableSet (f '' s) := by
rw [image_eq_range]
haveI : PolishSpace s := IsClosed.polishSpace hs
apply measurableSet_range_of_continuous_injective
· rwa [continuousOn_iff_continuous_restrict] at f_cont
· rwa [injOn_iff_injective] at f_inj
#align is_closed.measurable_set_image_of_continuous_on_inj_on IsClosed.measurableSet_image_of_continuousOn_injOn
variable {α β : Type*} [tβ : TopologicalSpace β] [T2Space β] [MeasurableSpace β]
[MeasurableSpace α]
{s : Set γ} {f : γ → β}
/-- The Lusin-Souslin theorem: if `s` is Borel-measurable in a Polish space, then its image under
a continuous injective map is also Borel-measurable. -/
theorem _root_.MeasurableSet.image_of_continuousOn_injOn [OpensMeasurableSpace β]
[tγ : TopologicalSpace γ] [PolishSpace γ] [MeasurableSpace γ] [BorelSpace γ]
(hs : MeasurableSet s)
(f_cont : ContinuousOn f s) (f_inj : InjOn f s) : MeasurableSet (f '' s) := by
obtain ⟨t', t't, t'_polish, s_closed, _⟩ :
∃ t' : TopologicalSpace γ, t' ≤ tγ ∧ @PolishSpace γ t' ∧ IsClosed[t'] s ∧ IsOpen[t'] s :=
hs.isClopenable
exact
@IsClosed.measurableSet_image_of_continuousOn_injOn γ t' t'_polish β _ _ _ _ s s_closed f
(f_cont.mono_dom t't) f_inj
#align measurable_set.image_of_continuous_on_inj_on MeasurableSet.image_of_continuousOn_injOn
/-- The Lusin-Souslin theorem: if `s` is Borel-measurable in a standard Borel space,
then its image under a measurable injective map taking values in a
countably separate measurable space is also Borel-measurable. -/
theorem _root_.MeasurableSet.image_of_measurable_injOn {f : γ → α}
[MeasurableSpace.CountablySeparated α]
[MeasurableSpace γ] [StandardBorelSpace γ]
(hs : MeasurableSet s) (f_meas : Measurable f) (f_inj : InjOn f s) :
MeasurableSet (f '' s) := by
letI := upgradeStandardBorel γ
let tγ : TopologicalSpace γ := inferInstance
rcases exists_opensMeasurableSpace_of_countablySeparated α with ⟨τ, _, _, _⟩
-- for a finer Polish topology, `f` is continuous. Therefore, one may apply the corresponding
-- result for continuous maps.
obtain ⟨t', t't, f_cont, t'_polish⟩ :
∃ t' : TopologicalSpace γ, t' ≤ tγ ∧ @Continuous γ _ t' _ f ∧ @PolishSpace γ t' :=
f_meas.exists_continuous
have M : MeasurableSet[@borel γ t'] s :=
@Continuous.measurable γ γ t' (@borel γ t')
(@BorelSpace.opensMeasurable γ t' (@borel γ t') (@BorelSpace.mk _ _ (borel γ) rfl))
tγ _ _ _ (continuous_id_of_le t't) s hs
exact
@MeasurableSet.image_of_continuousOn_injOn γ
_ _ _ _ s f _ t' t'_polish (@borel γ t') (@BorelSpace.mk _ _ (borel γ) rfl)
M (@Continuous.continuousOn γ _ t' _ f s f_cont) f_inj
#align measurable_set.image_of_measurable_inj_on MeasurableSet.image_of_measurable_injOn
/-- An injective continuous function on a Polish space is a measurable embedding. -/
theorem _root_.Continuous.measurableEmbedding [BorelSpace β]
[TopologicalSpace γ] [PolishSpace γ] [MeasurableSpace γ] [BorelSpace γ]
(f_cont : Continuous f) (f_inj : Injective f) :
MeasurableEmbedding f :=
{ injective := f_inj
measurable := f_cont.measurable
measurableSet_image' := fun _u hu =>
hu.image_of_continuousOn_injOn f_cont.continuousOn f_inj.injOn }
#align continuous.measurable_embedding Continuous.measurableEmbedding
/-- If `s` is Borel-measurable in a Polish space and `f` is continuous injective on `s`, then
the restriction of `f` to `s` is a measurable embedding. -/
| Mathlib/MeasureTheory/Constructions/Polish.lean | 890 | 903 | theorem _root_.ContinuousOn.measurableEmbedding [BorelSpace β]
[TopologicalSpace γ] [PolishSpace γ] [MeasurableSpace γ] [BorelSpace γ]
(hs : MeasurableSet s) (f_cont : ContinuousOn f s)
(f_inj : InjOn f s) : MeasurableEmbedding (s.restrict f) :=
{ injective := injOn_iff_injective.1 f_inj
measurable := (continuousOn_iff_continuous_restrict.1 f_cont).measurable
measurableSet_image' := by |
intro u hu
have A : MeasurableSet (((↑) : s → γ) '' u) :=
(MeasurableEmbedding.subtype_coe hs).measurableSet_image.2 hu
have B : MeasurableSet (f '' (((↑) : s → γ) '' u)) :=
A.image_of_continuousOn_injOn (f_cont.mono (Subtype.coe_image_subset s u))
(f_inj.mono (Subtype.coe_image_subset s u))
rwa [← image_comp] at B }
|
/-
Copyright (c) 2022 Yaël Dillies, Bhavik Mehta. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yaël Dillies, Bhavik Mehta
-/
import Mathlib.Combinatorics.SimpleGraph.Connectivity
import Mathlib.Combinatorics.SimpleGraph.Operations
import Mathlib.Data.Finset.Pairwise
#align_import combinatorics.simple_graph.clique from "leanprover-community/mathlib"@"3365b20c2ffa7c35e47e5209b89ba9abdddf3ffe"
/-!
# Graph cliques
This file defines cliques in simple graphs. A clique is a set of vertices that are pairwise
adjacent.
## Main declarations
* `SimpleGraph.IsClique`: Predicate for a set of vertices to be a clique.
* `SimpleGraph.IsNClique`: Predicate for a set of vertices to be an `n`-clique.
* `SimpleGraph.cliqueFinset`: Finset of `n`-cliques of a graph.
* `SimpleGraph.CliqueFree`: Predicate for a graph to have no `n`-cliques.
## TODO
* Clique numbers
* Dualise all the API to get independent sets
-/
open Finset Fintype Function SimpleGraph.Walk
namespace SimpleGraph
variable {α β : Type*} (G H : SimpleGraph α)
/-! ### Cliques -/
section Clique
variable {s t : Set α}
/-- A clique in a graph is a set of vertices that are pairwise adjacent. -/
abbrev IsClique (s : Set α) : Prop :=
s.Pairwise G.Adj
#align simple_graph.is_clique SimpleGraph.IsClique
theorem isClique_iff : G.IsClique s ↔ s.Pairwise G.Adj :=
Iff.rfl
#align simple_graph.is_clique_iff SimpleGraph.isClique_iff
/-- A clique is a set of vertices whose induced graph is complete. -/
theorem isClique_iff_induce_eq : G.IsClique s ↔ G.induce s = ⊤ := by
rw [isClique_iff]
constructor
· intro h
ext ⟨v, hv⟩ ⟨w, hw⟩
simp only [comap_adj, Subtype.coe_mk, top_adj, Ne, Subtype.mk_eq_mk]
exact ⟨Adj.ne, h hv hw⟩
· intro h v hv w hw hne
have h2 : (G.induce s).Adj ⟨v, hv⟩ ⟨w, hw⟩ = _ := rfl
conv_lhs at h2 => rw [h]
simp only [top_adj, ne_eq, Subtype.mk.injEq, eq_iff_iff] at h2
exact h2.1 hne
#align simple_graph.is_clique_iff_induce_eq SimpleGraph.isClique_iff_induce_eq
instance [DecidableEq α] [DecidableRel G.Adj] {s : Finset α} : Decidable (G.IsClique s) :=
decidable_of_iff' _ G.isClique_iff
variable {G H} {a b : α}
lemma isClique_empty : G.IsClique ∅ := by simp
#align simple_graph.is_clique_empty SimpleGraph.isClique_empty
lemma isClique_singleton (a : α) : G.IsClique {a} := by simp
#align simple_graph.is_clique_singleton SimpleGraph.isClique_singleton
lemma isClique_pair : G.IsClique {a, b} ↔ a ≠ b → G.Adj a b := Set.pairwise_pair_of_symmetric G.symm
#align simple_graph.is_clique_pair SimpleGraph.isClique_pair
@[simp]
lemma isClique_insert : G.IsClique (insert a s) ↔ G.IsClique s ∧ ∀ b ∈ s, a ≠ b → G.Adj a b :=
Set.pairwise_insert_of_symmetric G.symm
#align simple_graph.is_clique_insert SimpleGraph.isClique_insert
lemma isClique_insert_of_not_mem (ha : a ∉ s) :
G.IsClique (insert a s) ↔ G.IsClique s ∧ ∀ b ∈ s, G.Adj a b :=
Set.pairwise_insert_of_symmetric_of_not_mem G.symm ha
#align simple_graph.is_clique_insert_of_not_mem SimpleGraph.isClique_insert_of_not_mem
lemma IsClique.insert (hs : G.IsClique s) (h : ∀ b ∈ s, a ≠ b → G.Adj a b) :
G.IsClique (insert a s) := hs.insert_of_symmetric G.symm h
#align simple_graph.is_clique.insert SimpleGraph.IsClique.insert
theorem IsClique.mono (h : G ≤ H) : G.IsClique s → H.IsClique s := Set.Pairwise.mono' h
#align simple_graph.is_clique.mono SimpleGraph.IsClique.mono
theorem IsClique.subset (h : t ⊆ s) : G.IsClique s → G.IsClique t := Set.Pairwise.mono h
#align simple_graph.is_clique.subset SimpleGraph.IsClique.subset
protected theorem IsClique.map {s : Set α} (h : G.IsClique s) {f : α ↪ β} :
(G.map f).IsClique (f '' s) := by
rintro _ ⟨a, ha, rfl⟩ _ ⟨b, hb, rfl⟩ hab
exact ⟨a, b, h ha hb <| ne_of_apply_ne _ hab, rfl, rfl⟩
#align simple_graph.is_clique.map SimpleGraph.IsClique.map
@[simp]
theorem isClique_bot_iff : (⊥ : SimpleGraph α).IsClique s ↔ (s : Set α).Subsingleton :=
Set.pairwise_bot_iff
#align simple_graph.is_clique_bot_iff SimpleGraph.isClique_bot_iff
alias ⟨IsClique.subsingleton, _⟩ := isClique_bot_iff
#align simple_graph.is_clique.subsingleton SimpleGraph.IsClique.subsingleton
end Clique
/-! ### `n`-cliques -/
section NClique
variable {n : ℕ} {s : Finset α}
/-- An `n`-clique in a graph is a set of `n` vertices which are pairwise connected. -/
structure IsNClique (n : ℕ) (s : Finset α) : Prop where
clique : G.IsClique s
card_eq : s.card = n
#align simple_graph.is_n_clique SimpleGraph.IsNClique
theorem isNClique_iff : G.IsNClique n s ↔ G.IsClique s ∧ s.card = n :=
⟨fun h ↦ ⟨h.1, h.2⟩, fun h ↦ ⟨h.1, h.2⟩⟩
#align simple_graph.is_n_clique_iff SimpleGraph.isNClique_iff
instance [DecidableEq α] [DecidableRel G.Adj] {n : ℕ} {s : Finset α} :
Decidable (G.IsNClique n s) :=
decidable_of_iff' _ G.isNClique_iff
variable {G H} {a b c : α}
@[simp] lemma isNClique_empty : G.IsNClique n ∅ ↔ n = 0 := by simp [isNClique_iff, eq_comm]
#align simple_graph.is_n_clique_empty SimpleGraph.isNClique_empty
@[simp]
lemma isNClique_singleton : G.IsNClique n {a} ↔ n = 1 := by simp [isNClique_iff, eq_comm]
#align simple_graph.is_n_clique_singleton SimpleGraph.isNClique_singleton
theorem IsNClique.mono (h : G ≤ H) : G.IsNClique n s → H.IsNClique n s := by
simp_rw [isNClique_iff]
exact And.imp_left (IsClique.mono h)
#align simple_graph.is_n_clique.mono SimpleGraph.IsNClique.mono
protected theorem IsNClique.map (h : G.IsNClique n s) {f : α ↪ β} :
(G.map f).IsNClique n (s.map f) :=
⟨by rw [coe_map]; exact h.1.map, (card_map _).trans h.2⟩
#align simple_graph.is_n_clique.map SimpleGraph.IsNClique.map
@[simp]
theorem isNClique_bot_iff : (⊥ : SimpleGraph α).IsNClique n s ↔ n ≤ 1 ∧ s.card = n := by
rw [isNClique_iff, isClique_bot_iff]
refine and_congr_left ?_
rintro rfl
exact card_le_one.symm
#align simple_graph.is_n_clique_bot_iff SimpleGraph.isNClique_bot_iff
@[simp]
theorem isNClique_zero : G.IsNClique 0 s ↔ s = ∅ := by
simp only [isNClique_iff, Finset.card_eq_zero, and_iff_right_iff_imp]; rintro rfl; simp
#align simple_graph.is_n_clique_zero SimpleGraph.isNClique_zero
@[simp]
theorem isNClique_one : G.IsNClique 1 s ↔ ∃ a, s = {a} := by
simp only [isNClique_iff, card_eq_one, and_iff_right_iff_imp]; rintro ⟨a, rfl⟩; simp
#align simple_graph.is_n_clique_one SimpleGraph.isNClique_one
section DecidableEq
variable [DecidableEq α]
theorem IsNClique.insert (hs : G.IsNClique n s) (h : ∀ b ∈ s, G.Adj a b) :
G.IsNClique (n + 1) (insert a s) := by
constructor
· push_cast
exact hs.1.insert fun b hb _ => h _ hb
· rw [card_insert_of_not_mem fun ha => (h _ ha).ne rfl, hs.2]
#align simple_graph.is_n_clique.insert SimpleGraph.IsNClique.insert
theorem is3Clique_triple_iff : G.IsNClique 3 {a, b, c} ↔ G.Adj a b ∧ G.Adj a c ∧ G.Adj b c := by
simp only [isNClique_iff, isClique_iff, Set.pairwise_insert_of_symmetric G.symm, coe_insert]
by_cases hab : a = b <;> by_cases hbc : b = c <;> by_cases hac : a = c <;> subst_vars <;>
simp [G.ne_of_adj, and_rotate, *]
#align simple_graph.is_3_clique_triple_iff SimpleGraph.is3Clique_triple_iff
theorem is3Clique_iff :
G.IsNClique 3 s ↔ ∃ a b c, G.Adj a b ∧ G.Adj a c ∧ G.Adj b c ∧ s = {a, b, c} := by
refine ⟨fun h ↦ ?_, ?_⟩
· obtain ⟨a, b, c, -, -, -, hs⟩ := card_eq_three.1 h.card_eq
refine ⟨a, b, c, ?_⟩
rwa [hs, eq_self_iff_true, and_true, is3Clique_triple_iff.symm, ← hs]
· rintro ⟨a, b, c, hab, hbc, hca, rfl⟩
exact is3Clique_triple_iff.2 ⟨hab, hbc, hca⟩
#align simple_graph.is_3_clique_iff SimpleGraph.is3Clique_iff
end DecidableEq
theorem is3Clique_iff_exists_cycle_length_three :
(∃ s : Finset α, G.IsNClique 3 s) ↔ ∃ (u : α) (w : G.Walk u u), w.IsCycle ∧ w.length = 3 := by
classical
simp_rw [is3Clique_iff, isCycle_def]
exact
⟨(fun ⟨_, a, _, _, hab, hac, hbc, _⟩ => ⟨a, cons hab (cons hbc (cons hac.symm nil)), by aesop⟩),
(fun ⟨_, .cons hab (.cons hbc (.cons hca nil)), _, _⟩ => ⟨_, _, _, _, hab, hca.symm, hbc, rfl⟩)⟩
end NClique
/-! ### Graphs without cliques -/
section CliqueFree
variable {m n : ℕ}
/-- `G.CliqueFree n` means that `G` has no `n`-cliques. -/
def CliqueFree (n : ℕ) : Prop :=
∀ t, ¬G.IsNClique n t
#align simple_graph.clique_free SimpleGraph.CliqueFree
variable {G H} {s : Finset α}
theorem IsNClique.not_cliqueFree (hG : G.IsNClique n s) : ¬G.CliqueFree n :=
fun h ↦ h _ hG
#align simple_graph.is_n_clique.not_clique_free SimpleGraph.IsNClique.not_cliqueFree
theorem not_cliqueFree_of_top_embedding {n : ℕ} (f : (⊤ : SimpleGraph (Fin n)) ↪g G) :
¬G.CliqueFree n := by
simp only [CliqueFree, isNClique_iff, isClique_iff_induce_eq, not_forall, Classical.not_not]
use Finset.univ.map f.toEmbedding
simp only [card_map, Finset.card_fin, eq_self_iff_true, and_true_iff]
ext ⟨v, hv⟩ ⟨w, hw⟩
simp only [coe_map, Set.mem_image, coe_univ, Set.mem_univ, true_and_iff] at hv hw
obtain ⟨v', rfl⟩ := hv
obtain ⟨w', rfl⟩ := hw
simp only [coe_sort_coe, RelEmbedding.coe_toEmbedding, comap_adj, Function.Embedding.coe_subtype,
f.map_adj_iff, top_adj, ne_eq, Subtype.mk.injEq, RelEmbedding.inj]
-- This used to be the end of the proof before leanprover/lean4#2644
erw [Function.Embedding.coe_subtype, f.map_adj_iff]
simp
#align simple_graph.not_clique_free_of_top_embedding SimpleGraph.not_cliqueFree_of_top_embedding
/-- An embedding of a complete graph that witnesses the fact that the graph is not clique-free. -/
noncomputable def topEmbeddingOfNotCliqueFree {n : ℕ} (h : ¬G.CliqueFree n) :
(⊤ : SimpleGraph (Fin n)) ↪g G := by
simp only [CliqueFree, isNClique_iff, isClique_iff_induce_eq, not_forall, Classical.not_not] at h
obtain ⟨ha, hb⟩ := h.choose_spec
have : (⊤ : SimpleGraph (Fin h.choose.card)) ≃g (⊤ : SimpleGraph h.choose) := by
apply Iso.completeGraph
simpa using (Fintype.equivFin h.choose).symm
rw [← ha] at this
convert (Embedding.induce ↑h.choose.toSet).comp this.toEmbedding
exact hb.symm
#align simple_graph.top_embedding_of_not_clique_free SimpleGraph.topEmbeddingOfNotCliqueFree
theorem not_cliqueFree_iff (n : ℕ) : ¬G.CliqueFree n ↔ Nonempty ((⊤ : SimpleGraph (Fin n)) ↪g G) :=
⟨fun h ↦ ⟨topEmbeddingOfNotCliqueFree h⟩, fun ⟨f⟩ ↦ not_cliqueFree_of_top_embedding f⟩
#align simple_graph.not_clique_free_iff SimpleGraph.not_cliqueFree_iff
theorem cliqueFree_iff {n : ℕ} : G.CliqueFree n ↔ IsEmpty ((⊤ : SimpleGraph (Fin n)) ↪g G) := by
rw [← not_iff_not, not_cliqueFree_iff, not_isEmpty_iff]
#align simple_graph.clique_free_iff SimpleGraph.cliqueFree_iff
theorem not_cliqueFree_card_of_top_embedding [Fintype α] (f : (⊤ : SimpleGraph α) ↪g G) :
¬G.CliqueFree (card α) := by
rw [not_cliqueFree_iff]
exact ⟨(Iso.completeGraph (Fintype.equivFin α)).symm.toEmbedding.trans f⟩
#align simple_graph.not_clique_free_card_of_top_embedding SimpleGraph.not_cliqueFree_card_of_top_embedding
@[simp]
theorem cliqueFree_bot (h : 2 ≤ n) : (⊥ : SimpleGraph α).CliqueFree n := by
intro t ht
have := le_trans h (isNClique_bot_iff.1 ht).1
contradiction
#align simple_graph.clique_free_bot SimpleGraph.cliqueFree_bot
theorem CliqueFree.mono (h : m ≤ n) : G.CliqueFree m → G.CliqueFree n := by
intro hG s hs
obtain ⟨t, hts, ht⟩ := s.exists_smaller_set _ (h.trans hs.card_eq.ge)
exact hG _ ⟨hs.clique.subset hts, ht⟩
#align simple_graph.clique_free.mono SimpleGraph.CliqueFree.mono
theorem CliqueFree.anti (h : G ≤ H) : H.CliqueFree n → G.CliqueFree n :=
forall_imp fun _ ↦ mt <| IsNClique.mono h
#align simple_graph.clique_free.anti SimpleGraph.CliqueFree.anti
/-- If a graph is cliquefree, any graph that embeds into it is also cliquefree. -/
theorem CliqueFree.comap {H : SimpleGraph β} (f : H ↪g G) : G.CliqueFree n → H.CliqueFree n := by
intro h; contrapose h
exact not_cliqueFree_of_top_embedding <| f.comp (topEmbeddingOfNotCliqueFree h)
/-- See `SimpleGraph.cliqueFree_of_chromaticNumber_lt` for a tighter bound. -/
| Mathlib/Combinatorics/SimpleGraph/Clique.lean | 301 | 305 | theorem cliqueFree_of_card_lt [Fintype α] (hc : card α < n) : G.CliqueFree n := by |
by_contra h
refine Nat.lt_le_asymm hc ?_
rw [cliqueFree_iff, not_isEmpty_iff] at h
simpa only [Fintype.card_fin] using Fintype.card_le_of_embedding h.some.toEmbedding
|
/-
Copyright (c) 2022 Andrew Yang. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Andrew Yang
-/
import Mathlib.RingTheory.Ideal.Cotangent
import Mathlib.RingTheory.QuotientNilpotent
import Mathlib.RingTheory.TensorProduct.Basic
import Mathlib.RingTheory.FinitePresentation
import Mathlib.RingTheory.Localization.Away.Basic
import Mathlib.RingTheory.Localization.Away.AdjoinRoot
#align_import ring_theory.etale from "leanprover-community/mathlib"@"73f96237417835f148a1f7bc1ff55f67119b7166"
/-!
# Smooth morphisms
An `R`-algebra `A` is formally smooth if for every `R`-algebra,
every square-zero ideal `I : Ideal B` and `f : A →ₐ[R] B ⧸ I`, there exists
at least one lift `A →ₐ[R] B`.
It is smooth if it is formally smooth and of finite presentation.
We show that the property of being formally smooth extends onto nilpotent ideals,
and that it is stable under `R`-algebra homomorphisms and compositions.
We show that smooth is stable under algebra isomorphisms, composition and
localization at an element.
# TODO
- Show that smooth is stable under base change.
-/
-- Porting note: added to make the syntax work below.
open scoped TensorProduct
universe u
namespace Algebra
section
variable (R : Type u) [CommSemiring R]
variable (A : Type u) [Semiring A] [Algebra R A]
/-- An `R` algebra `A` is formally smooth if for every `R`-algebra, every square-zero ideal
`I : Ideal B` and `f : A →ₐ[R] B ⧸ I`, there exists at least one lift `A →ₐ[R] B`. -/
@[mk_iff]
class FormallySmooth : Prop where
comp_surjective :
∀ ⦃B : Type u⦄ [CommRing B],
∀ [Algebra R B] (I : Ideal B) (_ : I ^ 2 = ⊥),
Function.Surjective ((Ideal.Quotient.mkₐ R I).comp : (A →ₐ[R] B) → A →ₐ[R] B ⧸ I)
#align algebra.formally_smooth Algebra.FormallySmooth
end
namespace FormallySmooth
section
variable {R : Type u} [CommSemiring R]
variable {A : Type u} [Semiring A] [Algebra R A]
variable {B : Type u} [CommRing B] [Algebra R B] (I : Ideal B)
theorem exists_lift {B : Type u} [CommRing B] [_RB : Algebra R B]
[FormallySmooth R A] (I : Ideal B) (hI : IsNilpotent I) (g : A →ₐ[R] B ⧸ I) :
∃ f : A →ₐ[R] B, (Ideal.Quotient.mkₐ R I).comp f = g := by
revert g
change Function.Surjective (Ideal.Quotient.mkₐ R I).comp
revert _RB
apply Ideal.IsNilpotent.induction_on (R := B) I hI
· intro B _ I hI _; exact FormallySmooth.comp_surjective I hI
· intro B _ I J hIJ h₁ h₂ _ g
let this : ((B ⧸ I) ⧸ J.map (Ideal.Quotient.mk I)) ≃ₐ[R] B ⧸ J :=
{
(DoubleQuot.quotQuotEquivQuotSup I J).trans
(Ideal.quotEquivOfEq (sup_eq_right.mpr hIJ)) with
commutes' := fun x => rfl }
obtain ⟨g', e⟩ := h₂ (this.symm.toAlgHom.comp g)
obtain ⟨g', rfl⟩ := h₁ g'
replace e := congr_arg this.toAlgHom.comp e
conv_rhs at e =>
rw [← AlgHom.comp_assoc, AlgEquiv.toAlgHom_eq_coe, AlgEquiv.toAlgHom_eq_coe,
AlgEquiv.comp_symm, AlgHom.id_comp]
exact ⟨g', e⟩
#align algebra.formally_smooth.exists_lift Algebra.FormallySmooth.exists_lift
/-- For a formally smooth `R`-algebra `A` and a map `f : A →ₐ[R] B ⧸ I` with `I` square-zero,
this is an arbitrary lift `A →ₐ[R] B`. -/
noncomputable def lift [FormallySmooth R A] (I : Ideal B) (hI : IsNilpotent I)
(g : A →ₐ[R] B ⧸ I) : A →ₐ[R] B :=
(FormallySmooth.exists_lift I hI g).choose
#align algebra.formally_smooth.lift Algebra.FormallySmooth.lift
@[simp]
theorem comp_lift [FormallySmooth R A] (I : Ideal B) (hI : IsNilpotent I)
(g : A →ₐ[R] B ⧸ I) : (Ideal.Quotient.mkₐ R I).comp (FormallySmooth.lift I hI g) = g :=
(FormallySmooth.exists_lift I hI g).choose_spec
#align algebra.formally_smooth.comp_lift Algebra.FormallySmooth.comp_lift
@[simp]
theorem mk_lift [FormallySmooth R A] (I : Ideal B) (hI : IsNilpotent I)
(g : A →ₐ[R] B ⧸ I) (x : A) : Ideal.Quotient.mk I (FormallySmooth.lift I hI g x) = g x :=
AlgHom.congr_fun (FormallySmooth.comp_lift I hI g : _) x
#align algebra.formally_smooth.mk_lift Algebra.FormallySmooth.mk_lift
variable {C : Type u} [CommRing C] [Algebra R C]
/-- For a formally smooth `R`-algebra `A` and a map `f : A →ₐ[R] B ⧸ I` with `I` nilpotent,
this is an arbitrary lift `A →ₐ[R] B`. -/
noncomputable def liftOfSurjective [FormallySmooth R A] (f : A →ₐ[R] C)
(g : B →ₐ[R] C) (hg : Function.Surjective g) (hg' : IsNilpotent <| RingHom.ker (g : B →+* C)) :
A →ₐ[R] B :=
FormallySmooth.lift _ hg' ((Ideal.quotientKerAlgEquivOfSurjective hg).symm.toAlgHom.comp f)
#align algebra.formally_smooth.lift_of_surjective Algebra.FormallySmooth.liftOfSurjective
@[simp]
theorem liftOfSurjective_apply [FormallySmooth R A] (f : A →ₐ[R] C) (g : B →ₐ[R] C)
(hg : Function.Surjective g) (hg' : IsNilpotent <| RingHom.ker (g : B →+* C)) (x : A) :
g (FormallySmooth.liftOfSurjective f g hg hg' x) = f x := by
apply (Ideal.quotientKerAlgEquivOfSurjective hg).symm.injective
change _ = ((Ideal.quotientKerAlgEquivOfSurjective hg).symm.toAlgHom.comp f) x
-- This used to be `rw`, but we need `erw` after leanprover/lean4#2644
erw [← FormallySmooth.mk_lift _ hg'
((Ideal.quotientKerAlgEquivOfSurjective hg).symm.toAlgHom.comp f)]
apply (Ideal.quotientKerAlgEquivOfSurjective hg).injective
simp only [liftOfSurjective, AlgEquiv.apply_symm_apply, AlgEquiv.toAlgHom_eq_coe,
Ideal.quotientKerAlgEquivOfSurjective_apply, RingHom.kerLift_mk, RingHom.coe_coe]
#align algebra.formally_smooth.lift_of_surjective_apply Algebra.FormallySmooth.liftOfSurjective_apply
@[simp]
theorem comp_liftOfSurjective [FormallySmooth R A] (f : A →ₐ[R] C) (g : B →ₐ[R] C)
(hg : Function.Surjective g) (hg' : IsNilpotent <| RingHom.ker (g : B →+* C)) :
g.comp (FormallySmooth.liftOfSurjective f g hg hg') = f :=
AlgHom.ext (FormallySmooth.liftOfSurjective_apply f g hg hg')
#align algebra.formally_smooth.comp_lift_of_surjective Algebra.FormallySmooth.comp_liftOfSurjective
end
section OfEquiv
variable {R : Type u} [CommSemiring R]
variable {A B : Type u} [Semiring A] [Algebra R A] [Semiring B] [Algebra R B]
theorem of_equiv [FormallySmooth R A] (e : A ≃ₐ[R] B) : FormallySmooth R B := by
constructor
intro C _ _ I hI f
use (FormallySmooth.lift I ⟨2, hI⟩ (f.comp e : A →ₐ[R] C ⧸ I)).comp e.symm
rw [← AlgHom.comp_assoc, FormallySmooth.comp_lift, AlgHom.comp_assoc, AlgEquiv.comp_symm,
AlgHom.comp_id]
#align algebra.formally_smooth.of_equiv Algebra.FormallySmooth.of_equiv
end OfEquiv
section Polynomial
open scoped Polynomial
variable (R : Type u) [CommSemiring R]
instance mvPolynomial (σ : Type u) : FormallySmooth R (MvPolynomial σ R) := by
constructor
intro C _ _ I _ f
have : ∀ s : σ, ∃ c : C, Ideal.Quotient.mk I c = f (MvPolynomial.X s) := fun s =>
Ideal.Quotient.mk_surjective _
choose g hg using this
refine ⟨MvPolynomial.aeval g, ?_⟩
ext s
rw [← hg, AlgHom.comp_apply, MvPolynomial.aeval_X]
rfl
#align algebra.formally_smooth.mv_polynomial Algebra.FormallySmooth.mvPolynomial
instance polynomial : FormallySmooth R R[X] :=
FormallySmooth.of_equiv (MvPolynomial.pUnitAlgEquiv R)
#align algebra.formally_smooth.polynomial Algebra.FormallySmooth.polynomial
end Polynomial
section Comp
variable (R : Type u) [CommSemiring R]
variable (A : Type u) [CommSemiring A] [Algebra R A]
variable (B : Type u) [Semiring B] [Algebra R B] [Algebra A B] [IsScalarTower R A B]
theorem comp [FormallySmooth R A] [FormallySmooth A B] : FormallySmooth R B := by
constructor
intro C _ _ I hI f
obtain ⟨f', e⟩ := FormallySmooth.comp_surjective I hI (f.comp (IsScalarTower.toAlgHom R A B))
letI := f'.toRingHom.toAlgebra
obtain ⟨f'', e'⟩ :=
FormallySmooth.comp_surjective I hI { f.toRingHom with commutes' := AlgHom.congr_fun e.symm }
apply_fun AlgHom.restrictScalars R at e'
exact ⟨f''.restrictScalars _, e'.trans (AlgHom.ext fun _ => rfl)⟩
#align algebra.formally_smooth.comp Algebra.FormallySmooth.comp
end Comp
section OfSurjective
variable {R S : Type u} [CommRing R] [CommSemiring S]
variable {P A : Type u} [CommRing A] [Algebra R A] [CommRing P] [Algebra R P]
variable (I : Ideal P) (f : P →ₐ[R] A) (hf : Function.Surjective f)
set_option backward.isDefEq.lazyWhnfCore false in -- See https://github.com/leanprover-community/mathlib4/issues/12534
theorem of_split [FormallySmooth R P] (g : A →ₐ[R] P ⧸ (RingHom.ker f.toRingHom) ^ 2)
(hg : f.kerSquareLift.comp g = AlgHom.id R A) : FormallySmooth R A := by
constructor
intro C _ _ I hI i
let l : P ⧸ (RingHom.ker f.toRingHom) ^ 2 →ₐ[R] C := by
refine Ideal.Quotient.liftₐ _ (FormallySmooth.lift I ⟨2, hI⟩ (i.comp f)) ?_
have : RingHom.ker f ≤ I.comap (FormallySmooth.lift I ⟨2, hI⟩ (i.comp f)) := by
rintro x (hx : f x = 0)
have : _ = i (f x) := (FormallySmooth.mk_lift I ⟨2, hI⟩ (i.comp f) x : _)
rwa [hx, map_zero, ← Ideal.Quotient.mk_eq_mk, Submodule.Quotient.mk_eq_zero] at this
intro x hx
have := (Ideal.pow_right_mono this 2).trans (Ideal.le_comap_pow _ 2) hx
rwa [hI] at this
have : i.comp f.kerSquareLift = (Ideal.Quotient.mkₐ R _).comp l := by
apply AlgHom.coe_ringHom_injective
apply Ideal.Quotient.ringHom_ext
ext x
exact (FormallySmooth.mk_lift I ⟨2, hI⟩ (i.comp f) x).symm
exact ⟨l.comp g, by rw [← AlgHom.comp_assoc, ← this, AlgHom.comp_assoc, hg, AlgHom.comp_id]⟩
#align algebra.formally_smooth.of_split Algebra.FormallySmooth.of_split
/-- Let `P →ₐ[R] A` be a surjection with kernel `J`, and `P` a formally smooth `R`-algebra,
then `A` is formally smooth over `R` iff the surjection `P ⧸ J ^ 2 →ₐ[R] A` has a section.
Geometric intuition: we require that a first-order thickening of `Spec A` inside `Spec P` admits
a retraction. -/
| Mathlib/RingTheory/Smooth/Basic.lean | 235 | 266 | theorem iff_split_surjection [FormallySmooth R P] :
FormallySmooth R A ↔ ∃ g, f.kerSquareLift.comp g = AlgHom.id R A := by |
constructor
· intro
have surj : Function.Surjective f.kerSquareLift := fun x =>
⟨Submodule.Quotient.mk (hf x).choose, (hf x).choose_spec⟩
have sqz : RingHom.ker f.kerSquareLift.toRingHom ^ 2 = 0 := by
rw [AlgHom.ker_kerSquareLift, Ideal.cotangentIdeal_square, Ideal.zero_eq_bot]
refine
⟨FormallySmooth.lift _ ⟨2, sqz⟩ (Ideal.quotientKerAlgEquivOfSurjective surj).symm.toAlgHom,
?_⟩
ext x
have :=
(Ideal.quotientKerAlgEquivOfSurjective surj).toAlgHom.congr_arg
(FormallySmooth.mk_lift _ ⟨2, sqz⟩
(Ideal.quotientKerAlgEquivOfSurjective surj).symm.toAlgHom x)
-- Porting note: was
-- dsimp at this
-- rw [AlgEquiv.apply_symm_apply] at this
erw [AlgEquiv.apply_symm_apply] at this
conv_rhs => rw [← this, AlgHom.id_apply]
rfl
-- Porting note: lean3 was not finished here:
-- obtain ⟨y, e⟩ :=
-- Ideal.Quotient.mk_surjective
-- (FormallySmooth.lift _ ⟨2, sqz⟩
-- (Ideal.quotientKerAlgEquivOfSurjective surj).symm.toAlgHom
-- x)
-- dsimp at e ⊢
-- rw [← e]
-- rfl
· rintro ⟨g, hg⟩; exact FormallySmooth.of_split f g hg
|
/-
Copyright (c) 2019 Yury Kudriashov. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yury Kudriashov
-/
import Mathlib.Algebra.Order.BigOperators.Ring.Finset
import Mathlib.Analysis.Convex.Hull
import Mathlib.LinearAlgebra.AffineSpace.Basis
#align_import analysis.convex.combination from "leanprover-community/mathlib"@"92bd7b1ffeb306a89f450bee126ddd8a284c259d"
/-!
# Convex combinations
This file defines convex combinations of points in a vector space.
## Main declarations
* `Finset.centerMass`: Center of mass of a finite family of points.
## Implementation notes
We divide by the sum of the weights in the definition of `Finset.centerMass` because of the way
mathematical arguments go: one doesn't change weights, but merely adds some. This also makes a few
lemmas unconditional on the sum of the weights being `1`.
-/
open Set Function
open scoped Classical
open Pointwise
universe u u'
variable {R R' E F ι ι' α : Type*} [LinearOrderedField R] [LinearOrderedField R'] [AddCommGroup E]
[AddCommGroup F] [LinearOrderedAddCommGroup α] [Module R E] [Module R F] [Module R α]
[OrderedSMul R α] {s : Set E}
/-- Center of mass of a finite collection of points with prescribed weights.
Note that we require neither `0 ≤ w i` nor `∑ w = 1`. -/
def Finset.centerMass (t : Finset ι) (w : ι → R) (z : ι → E) : E :=
(∑ i ∈ t, w i)⁻¹ • ∑ i ∈ t, w i • z i
#align finset.center_mass Finset.centerMass
variable (i j : ι) (c : R) (t : Finset ι) (w : ι → R) (z : ι → E)
open Finset
theorem Finset.centerMass_empty : (∅ : Finset ι).centerMass w z = 0 := by
simp only [centerMass, sum_empty, smul_zero]
#align finset.center_mass_empty Finset.centerMass_empty
theorem Finset.centerMass_pair (hne : i ≠ j) :
({i, j} : Finset ι).centerMass w z = (w i / (w i + w j)) • z i + (w j / (w i + w j)) • z j := by
simp only [centerMass, sum_pair hne, smul_add, (mul_smul _ _ _).symm, div_eq_inv_mul]
#align finset.center_mass_pair Finset.centerMass_pair
variable {w}
theorem Finset.centerMass_insert (ha : i ∉ t) (hw : ∑ j ∈ t, w j ≠ 0) :
(insert i t).centerMass w z =
(w i / (w i + ∑ j ∈ t, w j)) • z i +
((∑ j ∈ t, w j) / (w i + ∑ j ∈ t, w j)) • t.centerMass w z := by
simp only [centerMass, sum_insert ha, smul_add, (mul_smul _ _ _).symm, ← div_eq_inv_mul]
congr 2
rw [div_mul_eq_mul_div, mul_inv_cancel hw, one_div]
#align finset.center_mass_insert Finset.centerMass_insert
theorem Finset.centerMass_singleton (hw : w i ≠ 0) : ({i} : Finset ι).centerMass w z = z i := by
rw [centerMass, sum_singleton, sum_singleton, ← mul_smul, inv_mul_cancel hw, one_smul]
#align finset.center_mass_singleton Finset.centerMass_singleton
@[simp] lemma Finset.centerMass_neg_left : t.centerMass (-w) z = t.centerMass w z := by
simp [centerMass, inv_neg]
lemma Finset.centerMass_smul_left {c : R'} [Module R' R] [Module R' E] [SMulCommClass R' R R]
[IsScalarTower R' R R] [SMulCommClass R R' E] [IsScalarTower R' R E] (hc : c ≠ 0) :
t.centerMass (c • w) z = t.centerMass w z := by
simp [centerMass, -smul_assoc, smul_assoc c, ← smul_sum, smul_inv₀, smul_smul_smul_comm, hc]
theorem Finset.centerMass_eq_of_sum_1 (hw : ∑ i ∈ t, w i = 1) :
t.centerMass w z = ∑ i ∈ t, w i • z i := by
simp only [Finset.centerMass, hw, inv_one, one_smul]
#align finset.center_mass_eq_of_sum_1 Finset.centerMass_eq_of_sum_1
theorem Finset.centerMass_smul : (t.centerMass w fun i => c • z i) = c • t.centerMass w z := by
simp only [Finset.centerMass, Finset.smul_sum, (mul_smul _ _ _).symm, mul_comm c, mul_assoc]
#align finset.center_mass_smul Finset.centerMass_smul
/-- A convex combination of two centers of mass is a center of mass as well. This version
deals with two different index types. -/
theorem Finset.centerMass_segment' (s : Finset ι) (t : Finset ι') (ws : ι → R) (zs : ι → E)
(wt : ι' → R) (zt : ι' → E) (hws : ∑ i ∈ s, ws i = 1) (hwt : ∑ i ∈ t, wt i = 1) (a b : R)
(hab : a + b = 1) : a • s.centerMass ws zs + b • t.centerMass wt zt = (s.disjSum t).centerMass
(Sum.elim (fun i => a * ws i) fun j => b * wt j) (Sum.elim zs zt) := by
rw [s.centerMass_eq_of_sum_1 _ hws, t.centerMass_eq_of_sum_1 _ hwt, smul_sum, smul_sum, ←
Finset.sum_sum_elim, Finset.centerMass_eq_of_sum_1]
· congr with ⟨⟩ <;> simp only [Sum.elim_inl, Sum.elim_inr, mul_smul]
· rw [sum_sum_elim, ← mul_sum, ← mul_sum, hws, hwt, mul_one, mul_one, hab]
#align finset.center_mass_segment' Finset.centerMass_segment'
/-- A convex combination of two centers of mass is a center of mass as well. This version
works if two centers of mass share the set of original points. -/
theorem Finset.centerMass_segment (s : Finset ι) (w₁ w₂ : ι → R) (z : ι → E)
(hw₁ : ∑ i ∈ s, w₁ i = 1) (hw₂ : ∑ i ∈ s, w₂ i = 1) (a b : R) (hab : a + b = 1) :
a • s.centerMass w₁ z + b • s.centerMass w₂ z =
s.centerMass (fun i => a * w₁ i + b * w₂ i) z := by
have hw : (∑ i ∈ s, (a * w₁ i + b * w₂ i)) = 1 := by
simp only [← mul_sum, sum_add_distrib, mul_one, *]
simp only [Finset.centerMass_eq_of_sum_1, Finset.centerMass_eq_of_sum_1 _ _ hw,
smul_sum, sum_add_distrib, add_smul, mul_smul, *]
#align finset.center_mass_segment Finset.centerMass_segment
theorem Finset.centerMass_ite_eq (hi : i ∈ t) :
t.centerMass (fun j => if i = j then (1 : R) else 0) z = z i := by
rw [Finset.centerMass_eq_of_sum_1]
· trans ∑ j ∈ t, if i = j then z i else 0
· congr with i
split_ifs with h
exacts [h ▸ one_smul _ _, zero_smul _ _]
· rw [sum_ite_eq, if_pos hi]
· rw [sum_ite_eq, if_pos hi]
#align finset.center_mass_ite_eq Finset.centerMass_ite_eq
variable {t}
theorem Finset.centerMass_subset {t' : Finset ι} (ht : t ⊆ t') (h : ∀ i ∈ t', i ∉ t → w i = 0) :
t.centerMass w z = t'.centerMass w z := by
rw [centerMass, sum_subset ht h, smul_sum, centerMass, smul_sum]
apply sum_subset ht
intro i hit' hit
rw [h i hit' hit, zero_smul, smul_zero]
#align finset.center_mass_subset Finset.centerMass_subset
theorem Finset.centerMass_filter_ne_zero :
(t.filter fun i => w i ≠ 0).centerMass w z = t.centerMass w z :=
Finset.centerMass_subset z (filter_subset _ _) fun i hit hit' => by
simpa only [hit, mem_filter, true_and_iff, Ne, Classical.not_not] using hit'
#align finset.center_mass_filter_ne_zero Finset.centerMass_filter_ne_zero
namespace Finset
theorem centerMass_le_sup {s : Finset ι} {f : ι → α} {w : ι → R} (hw₀ : ∀ i ∈ s, 0 ≤ w i)
(hw₁ : 0 < ∑ i ∈ s, w i) :
s.centerMass w f ≤ s.sup' (nonempty_of_ne_empty <| by rintro rfl; simp at hw₁) f := by
rw [centerMass, inv_smul_le_iff_of_pos hw₁, sum_smul]
exact sum_le_sum fun i hi => smul_le_smul_of_nonneg_left (le_sup' _ hi) <| hw₀ i hi
#align finset.center_mass_le_sup Finset.centerMass_le_sup
theorem inf_le_centerMass {s : Finset ι} {f : ι → α} {w : ι → R} (hw₀ : ∀ i ∈ s, 0 ≤ w i)
(hw₁ : 0 < ∑ i ∈ s, w i) :
s.inf' (nonempty_of_ne_empty <| by rintro rfl; simp at hw₁) f ≤ s.centerMass w f :=
@centerMass_le_sup R _ αᵒᵈ _ _ _ _ _ _ _ hw₀ hw₁
#align finset.inf_le_center_mass Finset.inf_le_centerMass
end Finset
variable {z}
lemma Finset.centerMass_of_sum_add_sum_eq_zero {s t : Finset ι}
(hw : ∑ i ∈ s, w i + ∑ i ∈ t, w i = 0) (hz : ∑ i ∈ s, w i • z i + ∑ i ∈ t, w i • z i = 0) :
s.centerMass w z = t.centerMass w z := by
simp [centerMass, eq_neg_of_add_eq_zero_right hw, eq_neg_of_add_eq_zero_left hz, ← neg_inv]
/-- The center of mass of a finite subset of a convex set belongs to the set
provided that all weights are non-negative, and the total weight is positive. -/
theorem Convex.centerMass_mem (hs : Convex R s) :
(∀ i ∈ t, 0 ≤ w i) → (0 < ∑ i ∈ t, w i) → (∀ i ∈ t, z i ∈ s) → t.centerMass w z ∈ s := by
induction' t using Finset.induction with i t hi ht
· simp [lt_irrefl]
intro h₀ hpos hmem
have zi : z i ∈ s := hmem _ (mem_insert_self _ _)
have hs₀ : ∀ j ∈ t, 0 ≤ w j := fun j hj => h₀ j <| mem_insert_of_mem hj
rw [sum_insert hi] at hpos
by_cases hsum_t : ∑ j ∈ t, w j = 0
· have ws : ∀ j ∈ t, w j = 0 := (sum_eq_zero_iff_of_nonneg hs₀).1 hsum_t
have wz : ∑ j ∈ t, w j • z j = 0 := sum_eq_zero fun i hi => by simp [ws i hi]
simp only [centerMass, sum_insert hi, wz, hsum_t, add_zero]
simp only [hsum_t, add_zero] at hpos
rw [← mul_smul, inv_mul_cancel (ne_of_gt hpos), one_smul]
exact zi
· rw [Finset.centerMass_insert _ _ _ hi hsum_t]
refine convex_iff_div.1 hs zi (ht hs₀ ?_ ?_) ?_ (sum_nonneg hs₀) hpos
· exact lt_of_le_of_ne (sum_nonneg hs₀) (Ne.symm hsum_t)
· intro j hj
exact hmem j (mem_insert_of_mem hj)
· exact h₀ _ (mem_insert_self _ _)
#align convex.center_mass_mem Convex.centerMass_mem
theorem Convex.sum_mem (hs : Convex R s) (h₀ : ∀ i ∈ t, 0 ≤ w i) (h₁ : ∑ i ∈ t, w i = 1)
(hz : ∀ i ∈ t, z i ∈ s) : (∑ i ∈ t, w i • z i) ∈ s := by
simpa only [h₁, centerMass, inv_one, one_smul] using
hs.centerMass_mem h₀ (h₁.symm ▸ zero_lt_one) hz
#align convex.sum_mem Convex.sum_mem
/-- A version of `Convex.sum_mem` for `finsum`s. If `s` is a convex set, `w : ι → R` is a family of
nonnegative weights with sum one and `z : ι → E` is a family of elements of a module over `R` such
that `z i ∈ s` whenever `w i ≠ 0`, then the sum `∑ᶠ i, w i • z i` belongs to `s`. See also
`PartitionOfUnity.finsum_smul_mem_convex`. -/
theorem Convex.finsum_mem {ι : Sort*} {w : ι → R} {z : ι → E} {s : Set E} (hs : Convex R s)
(h₀ : ∀ i, 0 ≤ w i) (h₁ : ∑ᶠ i, w i = 1) (hz : ∀ i, w i ≠ 0 → z i ∈ s) :
(∑ᶠ i, w i • z i) ∈ s := by
have hfin_w : (support (w ∘ PLift.down)).Finite := by
by_contra H
rw [finsum, dif_neg H] at h₁
exact zero_ne_one h₁
have hsub : support ((fun i => w i • z i) ∘ PLift.down) ⊆ hfin_w.toFinset :=
(support_smul_subset_left _ _).trans hfin_w.coe_toFinset.ge
rw [finsum_eq_sum_plift_of_support_subset hsub]
refine hs.sum_mem (fun _ _ => h₀ _) ?_ fun i hi => hz _ ?_
· rwa [finsum, dif_pos hfin_w] at h₁
· rwa [hfin_w.mem_toFinset] at hi
#align convex.finsum_mem Convex.finsum_mem
theorem convex_iff_sum_mem : Convex R s ↔ ∀ (t : Finset E) (w : E → R),
(∀ i ∈ t, 0 ≤ w i) → ∑ i ∈ t, w i = 1 → (∀ x ∈ t, x ∈ s) → (∑ x ∈ t, w x • x) ∈ s := by
refine ⟨fun hs t w hw₀ hw₁ hts => hs.sum_mem hw₀ hw₁ hts, ?_⟩
intro h x hx y hy a b ha hb hab
by_cases h_cases : x = y
· rw [h_cases, ← add_smul, hab, one_smul]
exact hy
· convert h {x, y} (fun z => if z = y then b else a) _ _ _
-- Porting note: Original proof had 2 `simp_intro i hi`
· simp only [sum_pair h_cases, if_neg h_cases, if_pos trivial]
· intro i _
simp only
split_ifs <;> assumption
· simp only [sum_pair h_cases, if_neg h_cases, if_pos trivial, hab]
· intro i hi
simp only [Finset.mem_singleton, Finset.mem_insert] at hi
cases hi <;> subst i <;> assumption
#align convex_iff_sum_mem convex_iff_sum_mem
theorem Finset.centerMass_mem_convexHull (t : Finset ι) {w : ι → R} (hw₀ : ∀ i ∈ t, 0 ≤ w i)
(hws : 0 < ∑ i ∈ t, w i) {z : ι → E} (hz : ∀ i ∈ t, z i ∈ s) :
t.centerMass w z ∈ convexHull R s :=
(convex_convexHull R s).centerMass_mem hw₀ hws fun i hi => subset_convexHull R s <| hz i hi
#align finset.center_mass_mem_convex_hull Finset.centerMass_mem_convexHull
/-- A version of `Finset.centerMass_mem_convexHull` for when the weights are nonpositive. -/
lemma Finset.centerMass_mem_convexHull_of_nonpos (t : Finset ι) (hw₀ : ∀ i ∈ t, w i ≤ 0)
(hws : ∑ i ∈ t, w i < 0) (hz : ∀ i ∈ t, z i ∈ s) : t.centerMass w z ∈ convexHull R s := by
rw [← centerMass_neg_left]
exact Finset.centerMass_mem_convexHull _ (fun _i hi ↦ neg_nonneg.2 <| hw₀ _ hi) (by simpa) hz
/-- A refinement of `Finset.centerMass_mem_convexHull` when the indexed family is a `Finset` of
the space. -/
theorem Finset.centerMass_id_mem_convexHull (t : Finset E) {w : E → R} (hw₀ : ∀ i ∈ t, 0 ≤ w i)
(hws : 0 < ∑ i ∈ t, w i) : t.centerMass w id ∈ convexHull R (t : Set E) :=
t.centerMass_mem_convexHull hw₀ hws fun _ => mem_coe.2
#align finset.center_mass_id_mem_convex_hull Finset.centerMass_id_mem_convexHull
/-- A version of `Finset.centerMass_mem_convexHull` for when the weights are nonpositive. -/
lemma Finset.centerMass_id_mem_convexHull_of_nonpos (t : Finset E) {w : E → R}
(hw₀ : ∀ i ∈ t, w i ≤ 0) (hws : ∑ i ∈ t, w i < 0) :
t.centerMass w id ∈ convexHull R (t : Set E) :=
t.centerMass_mem_convexHull_of_nonpos hw₀ hws fun _ ↦ mem_coe.2
theorem affineCombination_eq_centerMass {ι : Type*} {t : Finset ι} {p : ι → E} {w : ι → R}
(hw₂ : ∑ i ∈ t, w i = 1) : t.affineCombination R p w = centerMass t w p := by
rw [affineCombination_eq_weightedVSubOfPoint_vadd_of_sum_eq_one _ w _ hw₂ (0 : E),
Finset.weightedVSubOfPoint_apply, vadd_eq_add, add_zero, t.centerMass_eq_of_sum_1 _ hw₂]
simp_rw [vsub_eq_sub, sub_zero]
#align affine_combination_eq_center_mass affineCombination_eq_centerMass
theorem affineCombination_mem_convexHull {s : Finset ι} {v : ι → E} {w : ι → R}
(hw₀ : ∀ i ∈ s, 0 ≤ w i) (hw₁ : s.sum w = 1) :
s.affineCombination R v w ∈ convexHull R (range v) := by
rw [affineCombination_eq_centerMass hw₁]
apply s.centerMass_mem_convexHull hw₀
· simp [hw₁]
· simp
#align affine_combination_mem_convex_hull affineCombination_mem_convexHull
/-- The centroid can be regarded as a center of mass. -/
@[simp]
theorem Finset.centroid_eq_centerMass (s : Finset ι) (hs : s.Nonempty) (p : ι → E) :
s.centroid R p = s.centerMass (s.centroidWeights R) p :=
affineCombination_eq_centerMass (s.sum_centroidWeights_eq_one_of_nonempty R hs)
#align finset.centroid_eq_center_mass Finset.centroid_eq_centerMass
theorem Finset.centroid_mem_convexHull (s : Finset E) (hs : s.Nonempty) :
s.centroid R id ∈ convexHull R (s : Set E) := by
rw [s.centroid_eq_centerMass hs]
apply s.centerMass_id_mem_convexHull
· simp only [inv_nonneg, imp_true_iff, Nat.cast_nonneg, Finset.centroidWeights_apply]
· have hs_card : (s.card : R) ≠ 0 := by simp [Finset.nonempty_iff_ne_empty.mp hs]
simp only [hs_card, Finset.sum_const, nsmul_eq_mul, mul_inv_cancel, Ne, not_false_iff,
Finset.centroidWeights_apply, zero_lt_one]
#align finset.centroid_mem_convex_hull Finset.centroid_mem_convexHull
| Mathlib/Analysis/Convex/Combination.lean | 293 | 321 | theorem convexHull_range_eq_exists_affineCombination (v : ι → E) : convexHull R (range v) =
{ x | ∃ (s : Finset ι) (w : ι → R), (∀ i ∈ s, 0 ≤ w i) ∧ s.sum w = 1 ∧
s.affineCombination R v w = x } := by |
refine Subset.antisymm (convexHull_min ?_ ?_) ?_
· intro x hx
obtain ⟨i, hi⟩ := Set.mem_range.mp hx
exact ⟨{i}, Function.const ι (1 : R), by simp, by simp, by simp [hi]⟩
· rintro x ⟨s, w, hw₀, hw₁, rfl⟩ y ⟨s', w', hw₀', hw₁', rfl⟩ a b ha hb hab
let W : ι → R := fun i => (if i ∈ s then a * w i else 0) + if i ∈ s' then b * w' i else 0
have hW₁ : (s ∪ s').sum W = 1 := by
rw [sum_add_distrib, ← sum_subset subset_union_left,
← sum_subset subset_union_right, sum_ite_of_true _ _ fun i hi => hi,
sum_ite_of_true _ _ fun i hi => hi, ← mul_sum, ← mul_sum, hw₁, hw₁', ← add_mul, hab,
mul_one] <;> intro i _ hi' <;> simp [hi']
refine ⟨s ∪ s', W, ?_, hW₁, ?_⟩
· rintro i -
by_cases hi : i ∈ s <;> by_cases hi' : i ∈ s' <;>
simp [W, hi, hi', add_nonneg, mul_nonneg ha (hw₀ i _), mul_nonneg hb (hw₀' i _)]
· simp_rw [affineCombination_eq_linear_combination (s ∪ s') v _ hW₁,
affineCombination_eq_linear_combination s v w hw₁,
affineCombination_eq_linear_combination s' v w' hw₁', add_smul, sum_add_distrib]
rw [← sum_subset subset_union_left, ← sum_subset subset_union_right]
· simp only [ite_smul, sum_ite_of_true _ _ fun _ hi => hi, mul_smul, ← smul_sum]
· intro i _ hi'
simp [hi']
· intro i _ hi'
simp [hi']
· rintro x ⟨s, w, hw₀, hw₁, rfl⟩
exact affineCombination_mem_convexHull hw₀ hw₁
|
/-
Copyright (c) 2023 Antoine Chambert-Loir and María Inés de Frutos-Fernández. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Antoine Chambert-Loir, María Inés de Frutos-Fernández, Eric Wieser, Bhavik Mehta
-/
import Mathlib.Data.Finset.Antidiagonal
import Mathlib.Data.Finsupp.Defs
import Mathlib.Data.Finsupp.Basic
/-!
# Partial HasAntidiagonal for functions with finite support
For an `AddCommMonoid` `μ`,
`Finset.HasAntidiagonal μ` provides a function `antidiagonal : μ → Finset (μ × μ)`
which maps `n : μ` to a `Finset` of pairs `(a, b)` such that `a + b = n`.
In this file, we provide an analogous definition for `ι →₀ μ`,
with an explicit finiteness condition on the support,
assuming `AddCommMonoid μ`, `HasAntidiagonal μ`,
For computability reasons, we also need `DecidableEq ι` and `DecidableEq μ`.
This Finset could be viewed inside `ι → μ`,
but the `Finsupp` condition provides a natural `DecidableEq` instance.
## Main definitions
* `Finset.finsuppAntidiag s n` is the finite set of all functions `f : ι →₀ μ`
with finite support contained in `s` and such that the sum of its values equals `n : μ`
That condition is expressed by `Finset.mem_finsuppAntidiag`
* `Finset.mem_finsuppAntidiag'` rewrites the `Finsupp.sum` condition as a `Finset.sum`.
* `Finset.finAntidiagonal`, a more general case of `Finset.Nat.antidiagonalTuple`
(TODO: deduplicate).
-/
namespace Finset
variable {ι μ μ' : Type*}
open Function Finsupp
section Fin
variable [AddCommMonoid μ] [DecidableEq μ] [HasAntidiagonal μ]
/-- `finAntidiagonal d n` is the type of `d`-tuples with sum `n`.
TODO: deduplicate with the less general `Finset.Nat.antidiagonalTuple`. -/
def finAntidiagonal (d : ℕ) (n : μ) : Finset (Fin d → μ) :=
aux d n
where
/-- Auxiliary construction for `finAntidiagonal` that bundles a proof of lawfulness
(`mem_finAntidiagonal`), as this is needed to invoke `disjiUnion`. Using `Finset.disjiUnion` makes
this computationally much more efficient than using `Finset.biUnion`. -/
aux (d : ℕ) (n : μ) : {s : Finset (Fin d → μ) // ∀ f, f ∈ s ↔ ∑ i, f i = n} :=
match d with
| 0 =>
if h : n = 0 then
⟨{0}, by simp [h, Subsingleton.elim finZeroElim ![]]⟩
else
⟨∅, by simp [Ne.symm h]⟩
| d + 1 =>
{ val := (antidiagonal n).disjiUnion
(fun ab => (aux d ab.2).1.map {
toFun := Fin.cons (ab.1)
inj' := Fin.cons_right_injective _ })
(fun i _hi j _hj hij => Finset.disjoint_left.2 fun t hti htj => hij <| by
simp_rw [Finset.mem_map, Embedding.coeFn_mk] at hti htj
obtain ⟨ai, hai, hij'⟩ := hti
obtain ⟨aj, haj, rfl⟩ := htj
rw [Fin.cons_eq_cons] at hij'
ext
· exact hij'.1
· obtain ⟨-, rfl⟩ := hij'
rw [← (aux d i.2).prop ai |>.mp hai, ← (aux d j.2).prop ai |>.mp haj])
property := fun f => by
simp_rw [mem_disjiUnion, mem_antidiagonal, mem_map, Embedding.coeFn_mk, Prod.exists,
(aux d _).prop, Fin.sum_univ_succ]
constructor
· rintro ⟨a, b, rfl, g, rfl, rfl⟩
simp only [Fin.cons_zero, Fin.cons_succ]
· intro hf
exact ⟨_, _, hf, _, rfl, Fin.cons_self_tail f⟩ }
lemma mem_finAntidiagonal (d : ℕ) (n : μ) (f : Fin d → μ) :
f ∈ finAntidiagonal d n ↔ ∑ i, f i = n :=
(finAntidiagonal.aux d n).prop f
/-- `finAntidiagonal₀ d n` is the type of d-tuples with sum `n` -/
def finAntidiagonal₀ (d : ℕ) (n : μ) : Finset (Fin d →₀ μ) :=
(finAntidiagonal d n).map
{ toFun := fun f =>
-- this is `Finsupp.onFinset`, but computable
{ toFun := f, support := univ.filter (f · ≠ 0), mem_support_toFun := fun x => by simp }
inj' := fun _ _ h => DFunLike.coe_fn_eq.mpr h }
lemma mem_finAntidiagonal₀' (d : ℕ) (n : μ) (f : Fin d →₀ μ) :
f ∈ finAntidiagonal₀ d n ↔ ∑ i, f i = n := by
simp only [finAntidiagonal₀, mem_map, Embedding.coeFn_mk, ← mem_finAntidiagonal,
← DFunLike.coe_injective.eq_iff, Finsupp.coe_mk, exists_eq_right]
lemma mem_finAntidiagonal₀ (d : ℕ) (n : μ) (f : Fin d →₀ μ) :
f ∈ finAntidiagonal₀ d n ↔ sum f (fun _ x => x) = n := by
rw [mem_finAntidiagonal₀', sum_of_support_subset f (subset_univ _) _ (fun _ _ => rfl)]
end Fin
section finsuppAntidiag
variable [DecidableEq ι]
variable [AddCommMonoid μ] [HasAntidiagonal μ] [DecidableEq μ]
/-- The Finset of functions `ι →₀ μ` with support contained in `s` and sum `n`. -/
def finsuppAntidiag (s : Finset ι) (n : μ) : Finset (ι →₀ μ) :=
let x : Finset (s →₀ μ) :=
-- any ordering of elements of `s` will do, the result is the same
(Fintype.truncEquivFinOfCardEq <| Fintype.card_coe s).lift
(fun e => (finAntidiagonal₀ s.card n).map (equivCongrLeft e.symm).toEmbedding)
(fun e1 e2 => Finset.ext fun x => by
simp only [mem_map_equiv, equivCongrLeft_symm, Equiv.symm_symm, equivCongrLeft_apply,
mem_finAntidiagonal₀, sum_equivMapDomain])
x.map
⟨Finsupp.extendDomain, Function.LeftInverse.injective subtypeDomain_extendDomain⟩
/-- A function belongs to `finsuppAntidiag s n`
iff its support is contained in `s` and the sum of its components is equal to `n` -/
lemma mem_finsuppAntidiag {s : Finset ι} {n : μ} {f : ι →₀ μ} :
f ∈ finsuppAntidiag s n ↔ f.support ⊆ s ∧ Finsupp.sum f (fun _ x => x) = n := by
simp only [finsuppAntidiag, mem_map, Embedding.coeFn_mk, mem_finAntidiagonal₀]
induction' (Fintype.truncEquivFinOfCardEq <| Fintype.card_coe s) using Trunc.ind with e'
simp_rw [Trunc.lift_mk, mem_map_equiv, equivCongrLeft_symm, Equiv.symm_symm, equivCongrLeft_apply,
mem_finAntidiagonal₀, sum_equivMapDomain]
constructor
· rintro ⟨f, rfl, rfl⟩
dsimp [sum]
constructor
· exact Finset.coe_subset.mpr (support_extendDomain_subset _)
· simp
· rintro ⟨hsupp, rfl⟩
refine (Function.RightInverse.surjective subtypeDomain_extendDomain).exists.mpr ⟨f, ?_⟩
constructor
· simp_rw [sum, support_subtypeDomain, subtypeDomain_apply, sum_subtype_of_mem _ hsupp]
· rw [extendDomain_subtypeDomain _ hsupp]
end finsuppAntidiag
section
variable [DecidableEq ι]
variable [AddCommMonoid μ] [HasAntidiagonal μ] [DecidableEq μ]
variable [AddCommMonoid μ'] [HasAntidiagonal μ'] [DecidableEq μ']
lemma mem_finsuppAntidiag' (s : Finset ι) (n : μ) (f) :
f ∈ finsuppAntidiag s n ↔ f.support ⊆ s ∧ s.sum f = n := by
rw [mem_finsuppAntidiag, and_congr_right_iff]
intro hs
rw [sum_of_support_subset _ hs]
exact fun _ _ => rfl
@[simp]
theorem finsuppAntidiag_empty_zero :
finsuppAntidiag (∅ : Finset ι) (0 : μ) = {0} := by
ext f
rw [mem_finsuppAntidiag]
simp only [mem_singleton, subset_empty]
rw [support_eq_empty, and_iff_left_iff_imp]
intro hf
rw [hf, sum_zero_index]
theorem finsuppAntidiag_empty_of_ne_zero {n : μ} (hn : n ≠ 0) :
finsuppAntidiag (∅ : Finset ι) n = ∅ := by
ext f
rw [mem_finsuppAntidiag]
simp only [subset_empty, support_eq_empty, sum_empty,
not_mem_empty, iff_false, not_and]
intro hf
rw [hf, sum_zero_index]
exact Ne.symm hn
| Mathlib/Data/Finset/PiAntidiagonal.lean | 180 | 185 | theorem finsuppAntidiag_empty [DecidableEq μ] (n : μ) :
finsuppAntidiag (∅ : Finset ι) n = if n = 0 then {0} else ∅ := by |
split_ifs with hn
· rw [hn]
apply finsuppAntidiag_empty_zero
· apply finsuppAntidiag_empty_of_ne_zero hn
|
/-
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.Caratheodory
/-!
# Induced Outer Measure
We can extend a function defined on a subset of `Set α` to an outer measure.
The underlying function is called `extend`, and the measure it induces is called
`inducedOuterMeasure`.
Some lemmas below are proven twice, once in the general case, and one where the function `m`
is only defined on measurable sets (i.e. when `P = MeasurableSet`). In the latter cases, we can
remove some hypotheses in the statement. The general version has the same name, but with a prime
at the end.
## Tags
outer measure
-/
#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
open OuterMeasure
section Extend
variable {α : Type*} {P : α → Prop}
variable (m : ∀ s : α, P s → ℝ≥0∞)
/-- We can trivially extend a function defined on a subclass of objects (with codomain `ℝ≥0∞`)
to all objects by defining it to be `∞` on the objects not in the class. -/
def extend (s : α) : ℝ≥0∞ :=
⨅ h : P s, m s h
#align measure_theory.extend MeasureTheory.extend
theorem extend_eq {s : α} (h : P s) : extend m s = m s h := by simp [extend, h]
#align measure_theory.extend_eq MeasureTheory.extend_eq
theorem extend_eq_top {s : α} (h : ¬P s) : extend m s = ∞ := by simp [extend, h]
#align measure_theory.extend_eq_top MeasureTheory.extend_eq_top
theorem smul_extend {R} [Zero R] [SMulWithZero R ℝ≥0∞] [IsScalarTower R ℝ≥0∞ ℝ≥0∞]
[NoZeroSMulDivisors R ℝ≥0∞] {c : R} (hc : c ≠ 0) :
c • extend m = extend fun s h => c • m s h := by
ext1 s
dsimp [extend]
by_cases h : P s
· simp [h]
· simp [h, ENNReal.smul_top, hc]
#align measure_theory.smul_extend MeasureTheory.smul_extend
theorem le_extend {s : α} (h : P s) : m s h ≤ extend m s := by
simp only [extend, le_iInf_iff]
intro
rfl
#align measure_theory.le_extend MeasureTheory.le_extend
-- TODO: why this is a bad `congr` lemma?
theorem extend_congr {β : Type*} {Pb : β → Prop} {mb : ∀ s : β, Pb s → ℝ≥0∞} {sa : α} {sb : β}
(hP : P sa ↔ Pb sb) (hm : ∀ (ha : P sa) (hb : Pb sb), m sa ha = mb sb hb) :
extend m sa = extend mb sb :=
iInf_congr_Prop hP fun _h => hm _ _
#align measure_theory.extend_congr MeasureTheory.extend_congr
@[simp]
theorem extend_top {α : Type*} {P : α → Prop} : extend (fun _ _ => ∞ : ∀ s : α, P s → ℝ≥0∞) = ⊤ :=
funext fun _ => iInf_eq_top.mpr fun _ => rfl
#align measure_theory.extend_top MeasureTheory.extend_top
end Extend
section ExtendSet
variable {α : Type*} {P : Set α → Prop}
variable {m : ∀ s : Set α, P s → ℝ≥0∞}
variable (P0 : P ∅) (m0 : m ∅ P0 = 0)
variable (PU : ∀ ⦃f : ℕ → Set α⦄ (_hm : ∀ i, P (f i)), P (⋃ i, f i))
variable
(mU :
∀ ⦃f : ℕ → Set α⦄ (hm : ∀ i, P (f i)),
Pairwise (Disjoint on f) → m (⋃ i, f i) (PU hm) = ∑' i, m (f i) (hm i))
variable (msU : ∀ ⦃f : ℕ → Set α⦄ (hm : ∀ i, P (f i)), m (⋃ i, f i) (PU hm) ≤ ∑' i, m (f i) (hm i))
variable (m_mono : ∀ ⦃s₁ s₂ : Set α⦄ (hs₁ : P s₁) (hs₂ : P s₂), s₁ ⊆ s₂ → m s₁ hs₁ ≤ m s₂ hs₂)
theorem extend_empty : extend m ∅ = 0 :=
(extend_eq _ P0).trans m0
#align measure_theory.extend_empty MeasureTheory.extend_empty
theorem extend_iUnion_nat {f : ℕ → Set α} (hm : ∀ i, P (f i))
(mU : m (⋃ i, f i) (PU hm) = ∑' i, m (f i) (hm i)) :
extend m (⋃ i, f i) = ∑' i, extend m (f i) :=
(extend_eq _ _).trans <|
mU.trans <| by
congr with i
rw [extend_eq]
#align measure_theory.extend_Union_nat MeasureTheory.extend_iUnion_nat
section Subadditive
theorem extend_iUnion_le_tsum_nat' (s : ℕ → Set α) :
extend m (⋃ i, s i) ≤ ∑' i, extend m (s i) := by
by_cases h : ∀ i, P (s i)
· rw [extend_eq _ (PU h), congr_arg tsum _]
· apply msU h
funext i
apply extend_eq _ (h i)
· cases' not_forall.1 h with i hi
exact le_trans (le_iInf fun h => hi.elim h) (ENNReal.le_tsum i)
#align measure_theory.extend_Union_le_tsum_nat' MeasureTheory.extend_iUnion_le_tsum_nat'
end Subadditive
section Mono
theorem extend_mono' ⦃s₁ s₂ : Set α⦄ (h₁ : P s₁) (hs : s₁ ⊆ s₂) : extend m s₁ ≤ extend m s₂ := by
refine le_iInf ?_
intro h₂
rw [extend_eq m h₁]
exact m_mono h₁ h₂ hs
#align measure_theory.extend_mono' MeasureTheory.extend_mono'
end Mono
section Unions
| Mathlib/MeasureTheory/OuterMeasure/Induced.lean | 140 | 147 | theorem extend_iUnion {β} [Countable β] {f : β → Set α} (hd : Pairwise (Disjoint on f))
(hm : ∀ i, P (f i)) : extend m (⋃ i, f i) = ∑' i, extend m (f i) := by |
cases nonempty_encodable β
rw [← Encodable.iUnion_decode₂, ← tsum_iUnion_decode₂]
· exact
extend_iUnion_nat PU (fun n => Encodable.iUnion_decode₂_cases P0 hm)
(mU _ (Encodable.iUnion_decode₂_disjoint_on hd))
· exact extend_empty P0 m0
|
/-
Copyright (c) 2022 Yakov Pechersky. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Yakov Pechersky
-/
import Mathlib.Data.List.Infix
#align_import data.list.rdrop from "leanprover-community/mathlib"@"26f081a2fb920140ed5bc5cc5344e84bcc7cb2b2"
/-!
# Dropping or taking from lists on the right
Taking or removing element from the tail end of a list
## Main definitions
- `rdrop n`: drop `n : ℕ` elements from the tail
- `rtake n`: take `n : ℕ` elements from the tail
- `rdropWhile p`: remove all the elements from the tail of a list until it finds the first element
for which `p : α → Bool` returns false. This element and everything before is returned.
- `rtakeWhile p`: Returns the longest terminal segment of a list for which `p : α → Bool` returns
true.
## Implementation detail
The two predicate-based methods operate by performing the regular "from-left" operation on
`List.reverse`, followed by another `List.reverse`, so they are not the most performant.
The other two rely on `List.length l` so they still traverse the list twice. One could construct
another function that takes a `L : ℕ` and use `L - n`. Under a proof condition that
`L = l.length`, the function would do the right thing.
-/
-- Make sure we don't import algebra
assert_not_exists Monoid
variable {α : Type*} (p : α → Bool) (l : List α) (n : ℕ)
namespace List
/-- Drop `n` elements from the tail end of a list. -/
def rdrop : List α :=
l.take (l.length - n)
#align list.rdrop List.rdrop
@[simp]
theorem rdrop_nil : rdrop ([] : List α) n = [] := by simp [rdrop]
#align list.rdrop_nil List.rdrop_nil
@[simp]
theorem rdrop_zero : rdrop l 0 = l := by simp [rdrop]
#align list.rdrop_zero List.rdrop_zero
theorem rdrop_eq_reverse_drop_reverse : l.rdrop n = reverse (l.reverse.drop n) := by
rw [rdrop]
induction' l using List.reverseRecOn with xs x IH generalizing n
· simp
· cases n
· simp [take_append]
· simp [take_append_eq_append_take, IH]
#align list.rdrop_eq_reverse_drop_reverse List.rdrop_eq_reverse_drop_reverse
@[simp]
theorem rdrop_concat_succ (x : α) : rdrop (l ++ [x]) (n + 1) = rdrop l n := by
simp [rdrop_eq_reverse_drop_reverse]
#align list.rdrop_concat_succ List.rdrop_concat_succ
/-- Take `n` elements from the tail end of a list. -/
def rtake : List α :=
l.drop (l.length - n)
#align list.rtake List.rtake
@[simp]
theorem rtake_nil : rtake ([] : List α) n = [] := by simp [rtake]
#align list.rtake_nil List.rtake_nil
@[simp]
theorem rtake_zero : rtake l 0 = [] := by simp [rtake]
#align list.rtake_zero List.rtake_zero
theorem rtake_eq_reverse_take_reverse : l.rtake n = reverse (l.reverse.take n) := by
rw [rtake]
induction' l using List.reverseRecOn with xs x IH generalizing n
· simp
· cases n
· exact drop_length _
· simp [drop_append_eq_append_drop, IH]
#align list.rtake_eq_reverse_take_reverse List.rtake_eq_reverse_take_reverse
@[simp]
theorem rtake_concat_succ (x : α) : rtake (l ++ [x]) (n + 1) = rtake l n ++ [x] := by
simp [rtake_eq_reverse_take_reverse]
#align list.rtake_concat_succ List.rtake_concat_succ
/-- Drop elements from the tail end of a list that satisfy `p : α → Bool`.
Implemented naively via `List.reverse` -/
def rdropWhile : List α :=
reverse (l.reverse.dropWhile p)
#align list.rdrop_while List.rdropWhile
@[simp]
theorem rdropWhile_nil : rdropWhile p ([] : List α) = [] := by simp [rdropWhile, dropWhile]
#align list.rdrop_while_nil List.rdropWhile_nil
theorem rdropWhile_concat (x : α) :
rdropWhile p (l ++ [x]) = if p x then rdropWhile p l else l ++ [x] := by
simp only [rdropWhile, dropWhile, reverse_append, reverse_singleton, singleton_append]
split_ifs with h <;> simp [h]
#align list.rdrop_while_concat List.rdropWhile_concat
@[simp]
theorem rdropWhile_concat_pos (x : α) (h : p x) : rdropWhile p (l ++ [x]) = rdropWhile p l := by
rw [rdropWhile_concat, if_pos h]
#align list.rdrop_while_concat_pos List.rdropWhile_concat_pos
@[simp]
theorem rdropWhile_concat_neg (x : α) (h : ¬p x) : rdropWhile p (l ++ [x]) = l ++ [x] := by
rw [rdropWhile_concat, if_neg h]
#align list.rdrop_while_concat_neg List.rdropWhile_concat_neg
theorem rdropWhile_singleton (x : α) : rdropWhile p [x] = if p x then [] else [x] := by
rw [← nil_append [x], rdropWhile_concat, rdropWhile_nil]
#align list.rdrop_while_singleton List.rdropWhile_singleton
theorem rdropWhile_last_not (hl : l.rdropWhile p ≠ []) : ¬p ((rdropWhile p l).getLast hl) := by
simp_rw [rdropWhile]
rw [getLast_reverse]
exact dropWhile_nthLe_zero_not _ _ _
#align list.rdrop_while_last_not List.rdropWhile_last_not
theorem rdropWhile_prefix : l.rdropWhile p <+: l := by
rw [← reverse_suffix, rdropWhile, reverse_reverse]
exact dropWhile_suffix _
#align list.rdrop_while_prefix List.rdropWhile_prefix
variable {p} {l}
@[simp]
| Mathlib/Data/List/DropRight.lean | 139 | 139 | theorem rdropWhile_eq_nil_iff : rdropWhile p l = [] ↔ ∀ x ∈ l, p x := by | simp [rdropWhile]
|
/-
Copyright (c) 2021 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth
-/
import Mathlib.Analysis.Calculus.Deriv.Inv
import Mathlib.Analysis.NormedSpace.BallAction
import Mathlib.Analysis.SpecialFunctions.ExpDeriv
import Mathlib.Analysis.InnerProductSpace.Calculus
import Mathlib.Analysis.InnerProductSpace.PiL2
import Mathlib.Geometry.Manifold.Algebra.LieGroup
import Mathlib.Geometry.Manifold.Instances.Real
import Mathlib.Geometry.Manifold.MFDeriv.Basic
#align_import geometry.manifold.instances.sphere from "leanprover-community/mathlib"@"0dc4079202c28226b2841a51eb6d3cc2135bb80f"
/-!
# Manifold structure on the sphere
This file defines stereographic projection from the sphere in an inner product space `E`, and uses
it to put a smooth manifold structure on the sphere.
## Main results
For a unit vector `v` in `E`, the definition `stereographic` gives the stereographic projection
centred at `v`, a partial homeomorphism from the sphere to `(ℝ ∙ v)ᗮ` (the orthogonal complement of
`v`).
For finite-dimensional `E`, we then construct a smooth manifold instance on the sphere; the charts
here are obtained by composing the partial homeomorphisms `stereographic` with arbitrary isometries
from `(ℝ ∙ v)ᗮ` to Euclidean space.
We prove two lemmas about smooth maps:
* `contMDiff_coe_sphere` states that the coercion map from the sphere into `E` is smooth;
this is a useful tool for constructing smooth maps *from* the sphere.
* `contMDiff.codRestrict_sphere` states that a map from a manifold into the sphere is
smooth if its lift to a map to `E` is smooth; this is a useful tool for constructing smooth maps
*to* the sphere.
As an application we prove `contMdiffNegSphere`, that the antipodal map is smooth.
Finally, we equip the `circle` (defined in `Analysis.Complex.Circle` to be the sphere in `ℂ`
centred at `0` of radius `1`) with the following structure:
* a charted space with model space `EuclideanSpace ℝ (Fin 1)` (inherited from `Metric.Sphere`)
* a Lie group with model with corners `𝓡 1`
We furthermore show that `expMapCircle` (defined in `Analysis.Complex.Circle` to be the natural
map `fun t ↦ exp (t * I)` from `ℝ` to `circle`) is smooth.
## Implementation notes
The model space for the charted space instance is `EuclideanSpace ℝ (Fin n)`, where `n` is a
natural number satisfying the typeclass assumption `[Fact (finrank ℝ E = n + 1)]`. This may seem a
little awkward, but it is designed to circumvent the problem that the literal expression for the
dimension of the model space (up to definitional equality) determines the type. If one used the
naive expression `EuclideanSpace ℝ (Fin (finrank ℝ E - 1))` for the model space, then the sphere in
`ℂ` would be a manifold with model space `EuclideanSpace ℝ (Fin (2 - 1))` but not with model space
`EuclideanSpace ℝ (Fin 1)`.
## TODO
Relate the stereographic projection to the inversion of the space.
-/
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
noncomputable section
open Metric FiniteDimensional Function
open scoped Manifold
section StereographicProjection
variable (v : E)
/-! ### Construction of the stereographic projection -/
/-- Stereographic projection, forward direction. This is a map from an inner product space `E` to
the orthogonal complement of an element `v` of `E`. It is smooth away from the affine hyperplane
through `v` parallel to the orthogonal complement. It restricts on the sphere to the stereographic
projection. -/
def stereoToFun (x : E) : (ℝ ∙ v)ᗮ :=
(2 / ((1 : ℝ) - innerSL ℝ v x)) • orthogonalProjection (ℝ ∙ v)ᗮ x
#align stereo_to_fun stereoToFun
variable {v}
@[simp]
theorem stereoToFun_apply (x : E) :
stereoToFun v x = (2 / ((1 : ℝ) - innerSL ℝ v x)) • orthogonalProjection (ℝ ∙ v)ᗮ x :=
rfl
#align stereo_to_fun_apply stereoToFun_apply
theorem contDiffOn_stereoToFun :
ContDiffOn ℝ ⊤ (stereoToFun v) {x : E | innerSL _ v x ≠ (1 : ℝ)} := by
refine ContDiffOn.smul ?_ (orthogonalProjection (ℝ ∙ v)ᗮ).contDiff.contDiffOn
refine contDiff_const.contDiffOn.div ?_ ?_
· exact (contDiff_const.sub (innerSL ℝ v).contDiff).contDiffOn
· intro x h h'
exact h (sub_eq_zero.mp h').symm
#align cont_diff_on_stereo_to_fun contDiffOn_stereoToFun
theorem continuousOn_stereoToFun :
ContinuousOn (stereoToFun v) {x : E | innerSL _ v x ≠ (1 : ℝ)} :=
contDiffOn_stereoToFun.continuousOn
#align continuous_on_stereo_to_fun continuousOn_stereoToFun
variable (v)
/-- Auxiliary function for the construction of the reverse direction of the stereographic
projection. This is a map from the orthogonal complement of a unit vector `v` in an inner product
space `E` to `E`; we will later prove that it takes values in the unit sphere.
For most purposes, use `stereoInvFun`, not `stereoInvFunAux`. -/
def stereoInvFunAux (w : E) : E :=
(‖w‖ ^ 2 + 4)⁻¹ • ((4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v)
#align stereo_inv_fun_aux stereoInvFunAux
variable {v}
@[simp]
theorem stereoInvFunAux_apply (w : E) :
stereoInvFunAux v w = (‖w‖ ^ 2 + 4)⁻¹ • ((4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v) :=
rfl
#align stereo_inv_fun_aux_apply stereoInvFunAux_apply
theorem stereoInvFunAux_mem (hv : ‖v‖ = 1) {w : E} (hw : w ∈ (ℝ ∙ v)ᗮ) :
stereoInvFunAux v w ∈ sphere (0 : E) 1 := by
have h₁ : (0 : ℝ) < ‖w‖ ^ 2 + 4 := by positivity
suffices ‖(4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v‖ = ‖w‖ ^ 2 + 4 by
simp only [mem_sphere_zero_iff_norm, norm_smul, Real.norm_eq_abs, abs_inv, this,
abs_of_pos h₁, stereoInvFunAux_apply, inv_mul_cancel h₁.ne']
suffices ‖(4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v‖ ^ 2 = (‖w‖ ^ 2 + 4) ^ 2 by
simpa [sq_eq_sq_iff_abs_eq_abs, abs_of_pos h₁] using this
rw [Submodule.mem_orthogonal_singleton_iff_inner_left] at hw
simp [norm_add_sq_real, norm_smul, inner_smul_left, inner_smul_right, hw, mul_pow,
Real.norm_eq_abs, hv]
ring
#align stereo_inv_fun_aux_mem stereoInvFunAux_mem
theorem hasFDerivAt_stereoInvFunAux (v : E) :
HasFDerivAt (stereoInvFunAux v) (ContinuousLinearMap.id ℝ E) 0 := by
have h₀ : HasFDerivAt (fun w : E => ‖w‖ ^ 2) (0 : E →L[ℝ] ℝ) 0 := by
convert (hasStrictFDerivAt_norm_sq (0 : E)).hasFDerivAt
simp
have h₁ : HasFDerivAt (fun w : E => (‖w‖ ^ 2 + 4)⁻¹) (0 : E →L[ℝ] ℝ) 0 := by
convert (hasFDerivAt_inv _).comp _ (h₀.add (hasFDerivAt_const 4 0)) <;> simp
have h₂ : HasFDerivAt (fun w => (4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v)
((4 : ℝ) • ContinuousLinearMap.id ℝ E) 0 := by
convert ((hasFDerivAt_const (4 : ℝ) 0).smul (hasFDerivAt_id 0)).add
((h₀.sub (hasFDerivAt_const (4 : ℝ) 0)).smul (hasFDerivAt_const v 0)) using 1
ext w
simp
convert h₁.smul h₂ using 1
ext w
simp
#align has_fderiv_at_stereo_inv_fun_aux hasFDerivAt_stereoInvFunAux
theorem hasFDerivAt_stereoInvFunAux_comp_coe (v : E) :
HasFDerivAt (stereoInvFunAux v ∘ ((↑) : (ℝ ∙ v)ᗮ → E)) (ℝ ∙ v)ᗮ.subtypeL 0 := by
have : HasFDerivAt (stereoInvFunAux v) (ContinuousLinearMap.id ℝ E) ((ℝ ∙ v)ᗮ.subtypeL 0) :=
hasFDerivAt_stereoInvFunAux v
convert this.comp (0 : (ℝ ∙ v)ᗮ) (by apply ContinuousLinearMap.hasFDerivAt)
#align has_fderiv_at_stereo_inv_fun_aux_comp_coe hasFDerivAt_stereoInvFunAux_comp_coe
theorem contDiff_stereoInvFunAux : ContDiff ℝ ⊤ (stereoInvFunAux v) := by
have h₀ : ContDiff ℝ ⊤ fun w : E => ‖w‖ ^ 2 := contDiff_norm_sq ℝ
have h₁ : ContDiff ℝ ⊤ fun w : E => (‖w‖ ^ 2 + 4)⁻¹ := by
refine (h₀.add contDiff_const).inv ?_
intro x
nlinarith
have h₂ : ContDiff ℝ ⊤ fun w => (4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v := by
refine (contDiff_const.smul contDiff_id).add ?_
exact (h₀.sub contDiff_const).smul contDiff_const
exact h₁.smul h₂
#align cont_diff_stereo_inv_fun_aux contDiff_stereoInvFunAux
/-- Stereographic projection, reverse direction. This is a map from the orthogonal complement of a
unit vector `v` in an inner product space `E` to the unit sphere in `E`. -/
def stereoInvFun (hv : ‖v‖ = 1) (w : (ℝ ∙ v)ᗮ) : sphere (0 : E) 1 :=
⟨stereoInvFunAux v (w : E), stereoInvFunAux_mem hv w.2⟩
#align stereo_inv_fun stereoInvFun
@[simp]
theorem stereoInvFun_apply (hv : ‖v‖ = 1) (w : (ℝ ∙ v)ᗮ) :
(stereoInvFun hv w : E) = (‖w‖ ^ 2 + 4)⁻¹ • ((4 : ℝ) • w + (‖w‖ ^ 2 - 4) • v) :=
rfl
#align stereo_inv_fun_apply stereoInvFun_apply
theorem stereoInvFun_ne_north_pole (hv : ‖v‖ = 1) (w : (ℝ ∙ v)ᗮ) :
stereoInvFun hv w ≠ (⟨v, by simp [hv]⟩ : sphere (0 : E) 1) := by
refine Subtype.coe_ne_coe.1 ?_
rw [← inner_lt_one_iff_real_of_norm_one _ hv]
· have hw : ⟪v, w⟫_ℝ = 0 := Submodule.mem_orthogonal_singleton_iff_inner_right.mp w.2
have hw' : (‖(w : E)‖ ^ 2 + 4)⁻¹ * (‖(w : E)‖ ^ 2 - 4) < 1 := by
refine (inv_mul_lt_iff' ?_).mpr ?_
· nlinarith
linarith
simpa [real_inner_comm, inner_add_right, inner_smul_right, real_inner_self_eq_norm_mul_norm, hw,
hv] using hw'
· simpa using stereoInvFunAux_mem hv w.2
#align stereo_inv_fun_ne_north_pole stereoInvFun_ne_north_pole
theorem continuous_stereoInvFun (hv : ‖v‖ = 1) : Continuous (stereoInvFun hv) :=
continuous_induced_rng.2 (contDiff_stereoInvFunAux.continuous.comp continuous_subtype_val)
#align continuous_stereo_inv_fun continuous_stereoInvFun
theorem stereo_left_inv (hv : ‖v‖ = 1) {x : sphere (0 : E) 1} (hx : (x : E) ≠ v) :
stereoInvFun hv (stereoToFun v x) = x := by
ext
simp only [stereoToFun_apply, stereoInvFun_apply, smul_add]
-- name two frequently-occuring quantities and write down their basic properties
set a : ℝ := innerSL _ v x
set y := orthogonalProjection (ℝ ∙ v)ᗮ x
have split : ↑x = a • v + ↑y := by
convert (orthogonalProjection_add_orthogonalProjection_orthogonal (ℝ ∙ v) x).symm
exact (orthogonalProjection_unit_singleton ℝ hv x).symm
have hvy : ⟪v, y⟫_ℝ = 0 := Submodule.mem_orthogonal_singleton_iff_inner_right.mp y.2
have pythag : 1 = a ^ 2 + ‖y‖ ^ 2 := by
have hvy' : ⟪a • v, y⟫_ℝ = 0 := by simp only [inner_smul_left, hvy, mul_zero]
convert norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero _ _ hvy' using 2
· simp [← split]
· simp [norm_smul, hv, ← sq, sq_abs]
· exact sq _
-- two facts which will be helpful for clearing denominators in the main calculation
have ha : 1 - a ≠ 0 := by
have : a < 1 := (inner_lt_one_iff_real_of_norm_one hv (by simp)).mpr hx.symm
linarith
-- the core of the problem is these two algebraic identities:
have h₁ : (2 ^ 2 / (1 - a) ^ 2 * ‖y‖ ^ 2 + 4)⁻¹ * 4 * (2 / (1 - a)) = 1 := by
field_simp; simp only [Submodule.coe_norm] at *; nlinarith
have h₂ : (2 ^ 2 / (1 - a) ^ 2 * ‖y‖ ^ 2 + 4)⁻¹ * (2 ^ 2 / (1 - a) ^ 2 * ‖y‖ ^ 2 - 4) = a := by
field_simp
transitivity (1 - a) ^ 2 * (a * (2 ^ 2 * ‖y‖ ^ 2 + 4 * (1 - a) ^ 2))
· congr
simp only [Submodule.coe_norm] at *
nlinarith
ring!
convert
congr_arg₂ Add.add (congr_arg (fun t => t • (y : E)) h₁) (congr_arg (fun t => t • v) h₂) using 1
· simp [a, inner_add_right, inner_smul_right, hvy, real_inner_self_eq_norm_mul_norm, hv, mul_smul,
mul_pow, Real.norm_eq_abs, sq_abs, norm_smul]
-- Porting note: used to be simp only [split, add_comm] but get maxRec errors
rw [split, add_comm]
ac_rfl
-- Porting note: this branch did not exit in ml3
· rw [split, add_comm]
congr!
dsimp
rw [one_smul]
#align stereo_left_inv stereo_left_inv
theorem stereo_right_inv (hv : ‖v‖ = 1) (w : (ℝ ∙ v)ᗮ) : stereoToFun v (stereoInvFun hv w) = w := by
have : 2 / (1 - (‖(w : E)‖ ^ 2 + 4)⁻¹ * (‖(w : E)‖ ^ 2 - 4)) * (‖(w : E)‖ ^ 2 + 4)⁻¹ * 4 = 1 := by
field_simp; ring
convert congr_arg (· • w) this
· have h₁ : orthogonalProjection (ℝ ∙ v)ᗮ v = 0 :=
orthogonalProjection_orthogonalComplement_singleton_eq_zero v
-- Porting note: was innerSL _ and now just inner
have h₃ : inner v w = (0 : ℝ) := Submodule.mem_orthogonal_singleton_iff_inner_right.mp w.2
-- Porting note: was innerSL _ and now just inner
have h₄ : inner v v = (1 : ℝ) := by simp [real_inner_self_eq_norm_mul_norm, hv]
simp [h₁, h₃, h₄, ContinuousLinearMap.map_add, ContinuousLinearMap.map_smul, mul_smul]
· simp
#align stereo_right_inv stereo_right_inv
/-- Stereographic projection from the unit sphere in `E`, centred at a unit vector `v` in `E`;
this is the version as a partial homeomorphism. -/
def stereographic (hv : ‖v‖ = 1) : PartialHomeomorph (sphere (0 : E) 1) (ℝ ∙ v)ᗮ where
toFun := stereoToFun v ∘ (↑)
invFun := stereoInvFun hv
source := {⟨v, by simp [hv]⟩}ᶜ
target := Set.univ
map_source' := by simp
map_target' {w} _ := fun h => (stereoInvFun_ne_north_pole hv w) (Set.eq_of_mem_singleton h)
left_inv' x hx := stereo_left_inv hv fun h => hx (by
rw [← h] at hv
apply Subtype.ext
dsimp
exact h)
right_inv' w _ := stereo_right_inv hv w
open_source := isOpen_compl_singleton
open_target := isOpen_univ
continuousOn_toFun :=
continuousOn_stereoToFun.comp continuous_subtype_val.continuousOn fun w h => by
dsimp
exact
h ∘ Subtype.ext ∘ Eq.symm ∘ (inner_eq_one_iff_of_norm_one hv (by simp)).mp
continuousOn_invFun := (continuous_stereoInvFun hv).continuousOn
#align stereographic stereographic
theorem stereographic_apply (hv : ‖v‖ = 1) (x : sphere (0 : E) 1) :
stereographic hv x = (2 / ((1 : ℝ) - inner v x)) • orthogonalProjection (ℝ ∙ v)ᗮ x :=
rfl
#align stereographic_apply stereographic_apply
@[simp]
theorem stereographic_source (hv : ‖v‖ = 1) : (stereographic hv).source = {⟨v, by simp [hv]⟩}ᶜ :=
rfl
#align stereographic_source stereographic_source
@[simp]
theorem stereographic_target (hv : ‖v‖ = 1) : (stereographic hv).target = Set.univ :=
rfl
#align stereographic_target stereographic_target
@[simp]
theorem stereographic_apply_neg (v : sphere (0 : E) 1) :
stereographic (norm_eq_of_mem_sphere v) (-v) = 0 := by
simp [stereographic_apply, orthogonalProjection_orthogonalComplement_singleton_eq_zero]
#align stereographic_apply_neg stereographic_apply_neg
@[simp]
theorem stereographic_neg_apply (v : sphere (0 : E) 1) :
stereographic (norm_eq_of_mem_sphere (-v)) v = 0 := by
convert stereographic_apply_neg (-v)
ext1
simp
#align stereographic_neg_apply stereographic_neg_apply
end StereographicProjection
section ChartedSpace
/-!
### Charted space structure on the sphere
In this section we construct a charted space structure on the unit sphere in a finite-dimensional
real inner product space `E`; that is, we show that it is locally homeomorphic to the Euclidean
space of dimension one less than `E`.
The restriction to finite dimension is for convenience. The most natural `ChartedSpace`
structure for the sphere uses the stereographic projection from the antipodes of a point as the
canonical chart at this point. However, the codomain of the stereographic projection constructed
in the previous section is `(ℝ ∙ v)ᗮ`, the orthogonal complement of the vector `v` in `E` which is
the "north pole" of the projection, so a priori these charts all have different codomains.
So it is necessary to prove that these codomains are all continuously linearly equivalent to a
fixed normed space. This could be proved in general by a simple case of Gram-Schmidt
orthogonalization, but in the finite-dimensional case it follows more easily by dimension-counting.
-/
-- Porting note: unnecessary in Lean 3
private theorem findim (n : ℕ) [Fact (finrank ℝ E = n + 1)] : FiniteDimensional ℝ E :=
.of_fact_finrank_eq_succ n
/-- Variant of the stereographic projection, for the sphere in an `n + 1`-dimensional inner product
space `E`. This version has codomain the Euclidean space of dimension `n`, and is obtained by
composing the original sterographic projection (`stereographic`) with an arbitrary linear isometry
from `(ℝ ∙ v)ᗮ` to the Euclidean space. -/
def stereographic' (n : ℕ) [Fact (finrank ℝ E = n + 1)] (v : sphere (0 : E) 1) :
PartialHomeomorph (sphere (0 : E) 1) (EuclideanSpace ℝ (Fin n)) :=
stereographic (norm_eq_of_mem_sphere v) ≫ₕ
(OrthonormalBasis.fromOrthogonalSpanSingleton n
(ne_zero_of_mem_unit_sphere v)).repr.toHomeomorph.toPartialHomeomorph
#align stereographic' stereographic'
@[simp]
theorem stereographic'_source {n : ℕ} [Fact (finrank ℝ E = n + 1)] (v : sphere (0 : E) 1) :
(stereographic' n v).source = {v}ᶜ := by simp [stereographic']
#align stereographic'_source stereographic'_source
@[simp]
theorem stereographic'_target {n : ℕ} [Fact (finrank ℝ E = n + 1)] (v : sphere (0 : E) 1) :
(stereographic' n v).target = Set.univ := by simp [stereographic']
#align stereographic'_target stereographic'_target
/-- The unit sphere in an `n + 1`-dimensional inner product space `E` is a charted space
modelled on the Euclidean space of dimension `n`. -/
instance EuclideanSpace.instChartedSpaceSphere {n : ℕ} [Fact (finrank ℝ E = n + 1)] :
ChartedSpace (EuclideanSpace ℝ (Fin n)) (sphere (0 : E) 1) where
atlas := {f | ∃ v : sphere (0 : E) 1, f = stereographic' n v}
chartAt v := stereographic' n (-v)
mem_chart_source v := by simpa using ne_neg_of_mem_unit_sphere ℝ v
chart_mem_atlas v := ⟨-v, rfl⟩
end ChartedSpace
section SmoothManifold
theorem sphere_ext_iff (u v : sphere (0 : E) 1) : u = v ↔ ⟪(u : E), v⟫_ℝ = 1 := by
simp [Subtype.ext_iff, inner_eq_one_iff_of_norm_one]
#align sphere_ext_iff sphere_ext_iff
theorem stereographic'_symm_apply {n : ℕ} [Fact (finrank ℝ E = n + 1)] (v : sphere (0 : E) 1)
(x : EuclideanSpace ℝ (Fin n)) :
((stereographic' n v).symm x : E) =
let U : (ℝ ∙ (v : E))ᗮ ≃ₗᵢ[ℝ] EuclideanSpace ℝ (Fin n) :=
(OrthonormalBasis.fromOrthogonalSpanSingleton n (ne_zero_of_mem_unit_sphere v)).repr
(‖(U.symm x : E)‖ ^ 2 + 4)⁻¹ • (4 : ℝ) • (U.symm x : E) +
(‖(U.symm x : E)‖ ^ 2 + 4)⁻¹ • (‖(U.symm x : E)‖ ^ 2 - 4) • v.val := by
simp [real_inner_comm, stereographic, stereographic', ← Submodule.coe_norm]
#align stereographic'_symm_apply stereographic'_symm_apply
/-! ### Smooth manifold structure on the sphere -/
/-- The unit sphere in an `n + 1`-dimensional inner product space `E` is a smooth manifold,
modelled on the Euclidean space of dimension `n`. -/
instance EuclideanSpace.instSmoothManifoldWithCornersSphere {n : ℕ} [Fact (finrank ℝ E = n + 1)] :
SmoothManifoldWithCorners (𝓡 n) (sphere (0 : E) 1) :=
smoothManifoldWithCorners_of_contDiffOn (𝓡 n) (sphere (0 : E) 1)
(by
rintro _ _ ⟨v, rfl⟩ ⟨v', rfl⟩
let U :=
(-- Removed type ascription, and this helped for some reason with timeout issues?
OrthonormalBasis.fromOrthogonalSpanSingleton (𝕜 := ℝ)
n (ne_zero_of_mem_unit_sphere v)).repr
let U' :=
(-- Removed type ascription, and this helped for some reason with timeout issues?
OrthonormalBasis.fromOrthogonalSpanSingleton (𝕜 := ℝ)
n (ne_zero_of_mem_unit_sphere v')).repr
have H₁ := U'.contDiff.comp_contDiffOn contDiffOn_stereoToFun
-- Porting note: need to help with implicit variables again
have H₂ := (contDiff_stereoInvFunAux (v := v.val)|>.comp
(ℝ ∙ (v : E))ᗮ.subtypeL.contDiff).comp U.symm.contDiff
convert H₁.comp' (H₂.contDiffOn : ContDiffOn ℝ ⊤ _ Set.univ) using 1
-- -- squeezed from `ext, simp [sphere_ext_iff, stereographic'_symm_apply, real_inner_comm]`
simp only [PartialHomeomorph.trans_toPartialEquiv, PartialHomeomorph.symm_toPartialEquiv,
PartialEquiv.trans_source, PartialEquiv.symm_source, stereographic'_target,
stereographic'_source]
simp only [modelWithCornersSelf_coe, modelWithCornersSelf_coe_symm, Set.preimage_id,
Set.range_id, Set.inter_univ, Set.univ_inter, Set.compl_singleton_eq, Set.preimage_setOf_eq]
simp only [id, comp_apply, Submodule.subtypeL_apply, PartialHomeomorph.coe_coe_symm,
innerSL_apply, Ne, sphere_ext_iff, real_inner_comm (v' : E)]
rfl)
/-- The inclusion map (i.e., `coe`) from the sphere in `E` to `E` is smooth. -/
theorem contMDiff_coe_sphere {n : ℕ} [Fact (finrank ℝ E = n + 1)] :
ContMDiff (𝓡 n) 𝓘(ℝ, E) ∞ ((↑) : sphere (0 : E) 1 → E) := by
-- Porting note: trouble with filling these implicit variables in the instance
have := EuclideanSpace.instSmoothManifoldWithCornersSphere (E := E) (n := n)
rw [contMDiff_iff]
constructor
· exact continuous_subtype_val
· intro v _
let U : _ ≃ₗᵢ[ℝ] _ :=
(-- Again, partially removing type ascription...
OrthonormalBasis.fromOrthogonalSpanSingleton
n (ne_zero_of_mem_unit_sphere (-v))).repr
exact
((contDiff_stereoInvFunAux.comp (ℝ ∙ (-v : E))ᗮ.subtypeL.contDiff).comp
U.symm.contDiff).contDiffOn
#align cont_mdiff_coe_sphere contMDiff_coe_sphere
variable {F : Type*} [NormedAddCommGroup F] [NormedSpace ℝ F]
variable {H : Type*} [TopologicalSpace H] {I : ModelWithCorners ℝ F H}
variable {M : Type*} [TopologicalSpace M] [ChartedSpace H M] [SmoothManifoldWithCorners I M]
/-- If a `ContMDiff` function `f : M → E`, where `M` is some manifold, takes values in the
sphere, then it restricts to a `ContMDiff` function from `M` to the sphere. -/
| Mathlib/Geometry/Manifold/Instances/Sphere.lean | 455 | 476 | theorem ContMDiff.codRestrict_sphere {n : ℕ} [Fact (finrank ℝ E = n + 1)] {m : ℕ∞} {f : M → E}
(hf : ContMDiff I 𝓘(ℝ, E) m f) (hf' : ∀ x, f x ∈ sphere (0 : E) 1) :
ContMDiff I (𝓡 n) m (Set.codRestrict _ _ hf' : M → sphere (0 : E) 1) := by |
rw [contMDiff_iff_target]
refine ⟨continuous_induced_rng.2 hf.continuous, ?_⟩
intro v
let U : _ ≃ₗᵢ[ℝ] _ :=
(-- Again, partially removing type ascription... Weird that this helps!
OrthonormalBasis.fromOrthogonalSpanSingleton
n (ne_zero_of_mem_unit_sphere (-v))).repr
have h : ContDiffOn ℝ ⊤ _ Set.univ := U.contDiff.contDiffOn
have H₁ := (h.comp' contDiffOn_stereoToFun).contMDiffOn
have H₂ : ContMDiffOn _ _ _ _ Set.univ := hf.contMDiffOn
convert (H₁.of_le le_top).comp' H₂ using 1
ext x
have hfxv : f x = -↑v ↔ ⟪f x, -↑v⟫_ℝ = 1 := by
have hfx : ‖f x‖ = 1 := by simpa using hf' x
rw [inner_eq_one_iff_of_norm_one hfx]
exact norm_eq_of_mem_sphere (-v)
-- Porting note: unfold more
dsimp [chartAt, Set.codRestrict, ChartedSpace.chartAt]
simp [not_iff_not, Subtype.ext_iff, hfxv, real_inner_comm]
|
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import Mathlib.Algebra.CharP.Two
import Mathlib.Algebra.CharP.Reduced
import Mathlib.Algebra.NeZero
import Mathlib.Algebra.Polynomial.RingDivision
import Mathlib.GroupTheory.SpecificGroups.Cyclic
import Mathlib.NumberTheory.Divisors
import Mathlib.RingTheory.IntegralDomain
import Mathlib.Tactic.Zify
#align_import ring_theory.roots_of_unity.basic from "leanprover-community/mathlib"@"7fdeecc0d03cd40f7a165e6cf00a4d2286db599f"
/-!
# Roots of unity and primitive roots of unity
We define roots of unity in the context of an arbitrary commutative monoid,
as a subgroup of the group of units. We also define a predicate `IsPrimitiveRoot` on commutative
monoids, expressing that an element is a primitive root of unity.
## Main definitions
* `rootsOfUnity n M`, for `n : ℕ+` is the subgroup of the units of a commutative monoid `M`
consisting of elements `x` that satisfy `x ^ n = 1`.
* `IsPrimitiveRoot ζ k`: an element `ζ` is a primitive `k`-th root of unity if `ζ ^ k = 1`,
and if `l` satisfies `ζ ^ l = 1` then `k ∣ l`.
* `primitiveRoots k R`: the finset of primitive `k`-th roots of unity in an integral domain `R`.
* `IsPrimitiveRoot.autToPow`: the monoid hom that takes an automorphism of a ring to the power
it sends that specific primitive root, as a member of `(ZMod n)ˣ`.
## Main results
* `rootsOfUnity.isCyclic`: the roots of unity in an integral domain form a cyclic group.
* `IsPrimitiveRoot.zmodEquivZPowers`: `ZMod k` is equivalent to
the subgroup generated by a primitive `k`-th root of unity.
* `IsPrimitiveRoot.zpowers_eq`: in an integral domain, the subgroup generated by
a primitive `k`-th root of unity is equal to the `k`-th roots of unity.
* `IsPrimitiveRoot.card_primitiveRoots`: if an integral domain
has a primitive `k`-th root of unity, then it has `φ k` of them.
## Implementation details
It is desirable that `rootsOfUnity` is a subgroup,
and it will mainly be applied to rings (e.g. the ring of integers in a number field) and fields.
We therefore implement it as a subgroup of the units of a commutative monoid.
We have chosen to define `rootsOfUnity n` for `n : ℕ+`, instead of `n : ℕ`,
because almost all lemmas need the positivity assumption,
and in particular the type class instances for `Fintype` and `IsCyclic`.
On the other hand, for primitive roots of unity, it is desirable to have a predicate
not just on units, but directly on elements of the ring/field.
For example, we want to say that `exp (2 * pi * I / n)` is a primitive `n`-th root of unity
in the complex numbers, without having to turn that number into a unit first.
This creates a little bit of friction, but lemmas like `IsPrimitiveRoot.isUnit` and
`IsPrimitiveRoot.coe_units_iff` should provide the necessary glue.
-/
open scoped Classical Polynomial
noncomputable section
open Polynomial
open Finset
variable {M N G R S F : Type*}
variable [CommMonoid M] [CommMonoid N] [DivisionCommMonoid G]
section rootsOfUnity
variable {k l : ℕ+}
/-- `rootsOfUnity k M` is the subgroup of elements `m : Mˣ` that satisfy `m ^ k = 1`. -/
def rootsOfUnity (k : ℕ+) (M : Type*) [CommMonoid M] : Subgroup Mˣ where
carrier := {ζ | ζ ^ (k : ℕ) = 1}
one_mem' := one_pow _
mul_mem' _ _ := by simp_all only [Set.mem_setOf_eq, mul_pow, one_mul]
inv_mem' _ := by simp_all only [Set.mem_setOf_eq, inv_pow, inv_one]
#align roots_of_unity rootsOfUnity
@[simp]
theorem mem_rootsOfUnity (k : ℕ+) (ζ : Mˣ) : ζ ∈ rootsOfUnity k M ↔ ζ ^ (k : ℕ) = 1 :=
Iff.rfl
#align mem_roots_of_unity mem_rootsOfUnity
theorem mem_rootsOfUnity' (k : ℕ+) (ζ : Mˣ) : ζ ∈ rootsOfUnity k M ↔ (ζ : M) ^ (k : ℕ) = 1 := by
rw [mem_rootsOfUnity]; norm_cast
#align mem_roots_of_unity' mem_rootsOfUnity'
@[simp]
theorem rootsOfUnity_one (M : Type*) [CommMonoid M] : rootsOfUnity 1 M = ⊥ := by ext; simp
theorem rootsOfUnity.coe_injective {n : ℕ+} :
Function.Injective (fun x : rootsOfUnity n M ↦ x.val.val) :=
Units.ext.comp fun _ _ => Subtype.eq
#align roots_of_unity.coe_injective rootsOfUnity.coe_injective
/-- Make an element of `rootsOfUnity` from a member of the base ring, and a proof that it has
a positive power equal to one. -/
@[simps! coe_val]
def rootsOfUnity.mkOfPowEq (ζ : M) {n : ℕ+} (h : ζ ^ (n : ℕ) = 1) : rootsOfUnity n M :=
⟨Units.ofPowEqOne ζ n h n.ne_zero, Units.pow_ofPowEqOne _ _⟩
#align roots_of_unity.mk_of_pow_eq rootsOfUnity.mkOfPowEq
#align roots_of_unity.mk_of_pow_eq_coe_coe rootsOfUnity.val_mkOfPowEq_coe
@[simp]
theorem rootsOfUnity.coe_mkOfPowEq {ζ : M} {n : ℕ+} (h : ζ ^ (n : ℕ) = 1) :
((rootsOfUnity.mkOfPowEq _ h : Mˣ) : M) = ζ :=
rfl
#align roots_of_unity.coe_mk_of_pow_eq rootsOfUnity.coe_mkOfPowEq
theorem rootsOfUnity_le_of_dvd (h : k ∣ l) : rootsOfUnity k M ≤ rootsOfUnity l M := by
obtain ⟨d, rfl⟩ := h
intro ζ h
simp_all only [mem_rootsOfUnity, PNat.mul_coe, pow_mul, one_pow]
#align roots_of_unity_le_of_dvd rootsOfUnity_le_of_dvd
theorem map_rootsOfUnity (f : Mˣ →* Nˣ) (k : ℕ+) : (rootsOfUnity k M).map f ≤ rootsOfUnity k N := by
rintro _ ⟨ζ, h, rfl⟩
simp_all only [← map_pow, mem_rootsOfUnity, SetLike.mem_coe, MonoidHom.map_one]
#align map_roots_of_unity map_rootsOfUnity
@[norm_cast]
theorem rootsOfUnity.coe_pow [CommMonoid R] (ζ : rootsOfUnity k R) (m : ℕ) :
(((ζ ^ m :) : Rˣ) : R) = ((ζ : Rˣ) : R) ^ m := by
rw [Subgroup.coe_pow, Units.val_pow_eq_pow_val]
#align roots_of_unity.coe_pow rootsOfUnity.coe_pow
section CommMonoid
variable [CommMonoid R] [CommMonoid S] [FunLike F R S]
/-- Restrict a ring homomorphism to the nth roots of unity. -/
def restrictRootsOfUnity [MonoidHomClass F R S] (σ : F) (n : ℕ+) :
rootsOfUnity n R →* rootsOfUnity n S :=
let h : ∀ ξ : rootsOfUnity n R, (σ (ξ : Rˣ)) ^ (n : ℕ) = 1 := fun ξ => by
rw [← map_pow, ← Units.val_pow_eq_pow_val, show (ξ : Rˣ) ^ (n : ℕ) = 1 from ξ.2, Units.val_one,
map_one σ]
{ toFun := fun ξ =>
⟨@unitOfInvertible _ _ _ (invertibleOfPowEqOne _ _ (h ξ) n.ne_zero), by
ext; rw [Units.val_pow_eq_pow_val]; exact h ξ⟩
map_one' := by ext; exact map_one σ
map_mul' := fun ξ₁ ξ₂ => by ext; rw [Subgroup.coe_mul, Units.val_mul]; exact map_mul σ _ _ }
#align restrict_roots_of_unity restrictRootsOfUnity
@[simp]
theorem restrictRootsOfUnity_coe_apply [MonoidHomClass F R S] (σ : F) (ζ : rootsOfUnity k R) :
(restrictRootsOfUnity σ k ζ : Sˣ) = σ (ζ : Rˣ) :=
rfl
#align restrict_roots_of_unity_coe_apply restrictRootsOfUnity_coe_apply
/-- Restrict a monoid isomorphism to the nth roots of unity. -/
nonrec def MulEquiv.restrictRootsOfUnity (σ : R ≃* S) (n : ℕ+) :
rootsOfUnity n R ≃* rootsOfUnity n S where
toFun := restrictRootsOfUnity σ n
invFun := restrictRootsOfUnity σ.symm n
left_inv ξ := by ext; exact σ.symm_apply_apply (ξ : Rˣ)
right_inv ξ := by ext; exact σ.apply_symm_apply (ξ : Sˣ)
map_mul' := (restrictRootsOfUnity _ n).map_mul
#align ring_equiv.restrict_roots_of_unity MulEquiv.restrictRootsOfUnity
@[simp]
theorem MulEquiv.restrictRootsOfUnity_coe_apply (σ : R ≃* S) (ζ : rootsOfUnity k R) :
(σ.restrictRootsOfUnity k ζ : Sˣ) = σ (ζ : Rˣ) :=
rfl
#align ring_equiv.restrict_roots_of_unity_coe_apply MulEquiv.restrictRootsOfUnity_coe_apply
@[simp]
theorem MulEquiv.restrictRootsOfUnity_symm (σ : R ≃* S) :
(σ.restrictRootsOfUnity k).symm = σ.symm.restrictRootsOfUnity k :=
rfl
#align ring_equiv.restrict_roots_of_unity_symm MulEquiv.restrictRootsOfUnity_symm
end CommMonoid
section IsDomain
variable [CommRing R] [IsDomain R]
theorem mem_rootsOfUnity_iff_mem_nthRoots {ζ : Rˣ} :
ζ ∈ rootsOfUnity k R ↔ (ζ : R) ∈ nthRoots k (1 : R) := by
simp only [mem_rootsOfUnity, mem_nthRoots k.pos, Units.ext_iff, Units.val_one,
Units.val_pow_eq_pow_val]
#align mem_roots_of_unity_iff_mem_nth_roots mem_rootsOfUnity_iff_mem_nthRoots
variable (k R)
/-- Equivalence between the `k`-th roots of unity in `R` and the `k`-th roots of `1`.
This is implemented as equivalence of subtypes,
because `rootsOfUnity` is a subgroup of the group of units,
whereas `nthRoots` is a multiset. -/
def rootsOfUnityEquivNthRoots : rootsOfUnity k R ≃ { x // x ∈ nthRoots k (1 : R) } where
toFun x := ⟨(x : Rˣ), mem_rootsOfUnity_iff_mem_nthRoots.mp x.2⟩
invFun x := by
refine ⟨⟨x, ↑x ^ (k - 1 : ℕ), ?_, ?_⟩, ?_⟩
all_goals
rcases x with ⟨x, hx⟩; rw [mem_nthRoots k.pos] at hx
simp only [Subtype.coe_mk, ← pow_succ, ← pow_succ', hx,
tsub_add_cancel_of_le (show 1 ≤ (k : ℕ) from k.one_le)]
show (_ : Rˣ) ^ (k : ℕ) = 1
simp only [Units.ext_iff, hx, Units.val_mk, Units.val_one, Subtype.coe_mk,
Units.val_pow_eq_pow_val]
left_inv := by rintro ⟨x, hx⟩; ext; rfl
right_inv := by rintro ⟨x, hx⟩; ext; rfl
#align roots_of_unity_equiv_nth_roots rootsOfUnityEquivNthRoots
variable {k R}
@[simp]
theorem rootsOfUnityEquivNthRoots_apply (x : rootsOfUnity k R) :
(rootsOfUnityEquivNthRoots R k x : R) = ((x : Rˣ) : R) :=
rfl
#align roots_of_unity_equiv_nth_roots_apply rootsOfUnityEquivNthRoots_apply
@[simp]
theorem rootsOfUnityEquivNthRoots_symm_apply (x : { x // x ∈ nthRoots k (1 : R) }) :
(((rootsOfUnityEquivNthRoots R k).symm x : Rˣ) : R) = (x : R) :=
rfl
#align roots_of_unity_equiv_nth_roots_symm_apply rootsOfUnityEquivNthRoots_symm_apply
variable (k R)
instance rootsOfUnity.fintype : Fintype (rootsOfUnity k R) :=
Fintype.ofEquiv { x // x ∈ nthRoots k (1 : R) } <| (rootsOfUnityEquivNthRoots R k).symm
#align roots_of_unity.fintype rootsOfUnity.fintype
instance rootsOfUnity.isCyclic : IsCyclic (rootsOfUnity k R) :=
isCyclic_of_subgroup_isDomain ((Units.coeHom R).comp (rootsOfUnity k R).subtype)
(Units.ext.comp Subtype.val_injective)
#align roots_of_unity.is_cyclic rootsOfUnity.isCyclic
theorem card_rootsOfUnity : Fintype.card (rootsOfUnity k R) ≤ k :=
calc
Fintype.card (rootsOfUnity k R) = Fintype.card { x // x ∈ nthRoots k (1 : R) } :=
Fintype.card_congr (rootsOfUnityEquivNthRoots R k)
_ ≤ Multiset.card (nthRoots k (1 : R)).attach := Multiset.card_le_card (Multiset.dedup_le _)
_ = Multiset.card (nthRoots k (1 : R)) := Multiset.card_attach
_ ≤ k := card_nthRoots k 1
#align card_roots_of_unity card_rootsOfUnity
variable {k R}
theorem map_rootsOfUnity_eq_pow_self [FunLike F R R] [RingHomClass F R R] (σ : F)
(ζ : rootsOfUnity k R) :
∃ m : ℕ, σ (ζ : Rˣ) = ((ζ : Rˣ) : R) ^ m := by
obtain ⟨m, hm⟩ := MonoidHom.map_cyclic (restrictRootsOfUnity σ k)
rw [← restrictRootsOfUnity_coe_apply, hm, ← zpow_mod_orderOf, ← Int.toNat_of_nonneg
(m.emod_nonneg (Int.natCast_ne_zero.mpr (pos_iff_ne_zero.mp (orderOf_pos ζ)))),
zpow_natCast, rootsOfUnity.coe_pow]
exact ⟨(m % orderOf ζ).toNat, rfl⟩
#align map_root_of_unity_eq_pow_self map_rootsOfUnity_eq_pow_self
end IsDomain
section Reduced
variable (R) [CommRing R] [IsReduced R]
-- @[simp] -- Porting note: simp normal form is `mem_rootsOfUnity_prime_pow_mul_iff'`
theorem mem_rootsOfUnity_prime_pow_mul_iff (p k : ℕ) (m : ℕ+) [ExpChar R p]
{ζ : Rˣ} : ζ ∈ rootsOfUnity (⟨p, expChar_pos R p⟩ ^ k * m) R ↔ ζ ∈ rootsOfUnity m R := by
simp only [mem_rootsOfUnity', PNat.mul_coe, PNat.pow_coe, PNat.mk_coe,
ExpChar.pow_prime_pow_mul_eq_one_iff]
#align mem_roots_of_unity_prime_pow_mul_iff mem_rootsOfUnity_prime_pow_mul_iff
@[simp]
theorem mem_rootsOfUnity_prime_pow_mul_iff' (p k : ℕ) (m : ℕ+) [ExpChar R p]
{ζ : Rˣ} : ζ ^ (p ^ k * ↑m) = 1 ↔ ζ ∈ rootsOfUnity m R := by
rw [← PNat.mk_coe p (expChar_pos R p), ← PNat.pow_coe, ← PNat.mul_coe, ← mem_rootsOfUnity,
mem_rootsOfUnity_prime_pow_mul_iff]
end Reduced
end rootsOfUnity
/-- An element `ζ` is a primitive `k`-th root of unity if `ζ ^ k = 1`,
and if `l` satisfies `ζ ^ l = 1` then `k ∣ l`. -/
@[mk_iff IsPrimitiveRoot.iff_def]
structure IsPrimitiveRoot (ζ : M) (k : ℕ) : Prop where
pow_eq_one : ζ ^ (k : ℕ) = 1
dvd_of_pow_eq_one : ∀ l : ℕ, ζ ^ l = 1 → k ∣ l
#align is_primitive_root IsPrimitiveRoot
#align is_primitive_root.iff_def IsPrimitiveRoot.iff_def
/-- Turn a primitive root μ into a member of the `rootsOfUnity` subgroup. -/
@[simps!]
def IsPrimitiveRoot.toRootsOfUnity {μ : M} {n : ℕ+} (h : IsPrimitiveRoot μ n) : rootsOfUnity n M :=
rootsOfUnity.mkOfPowEq μ h.pow_eq_one
#align is_primitive_root.to_roots_of_unity IsPrimitiveRoot.toRootsOfUnity
#align is_primitive_root.coe_to_roots_of_unity_coe IsPrimitiveRoot.val_toRootsOfUnity_coe
#align is_primitive_root.coe_inv_to_roots_of_unity_coe IsPrimitiveRoot.val_inv_toRootsOfUnity_coe
section primitiveRoots
variable {k : ℕ}
/-- `primitiveRoots k R` is the finset of primitive `k`-th roots of unity
in the integral domain `R`. -/
def primitiveRoots (k : ℕ) (R : Type*) [CommRing R] [IsDomain R] : Finset R :=
(nthRoots k (1 : R)).toFinset.filter fun ζ => IsPrimitiveRoot ζ k
#align primitive_roots primitiveRoots
variable [CommRing R] [IsDomain R]
@[simp]
theorem mem_primitiveRoots {ζ : R} (h0 : 0 < k) : ζ ∈ primitiveRoots k R ↔ IsPrimitiveRoot ζ k := by
rw [primitiveRoots, mem_filter, Multiset.mem_toFinset, mem_nthRoots h0, and_iff_right_iff_imp]
exact IsPrimitiveRoot.pow_eq_one
#align mem_primitive_roots mem_primitiveRoots
@[simp]
theorem primitiveRoots_zero : primitiveRoots 0 R = ∅ := by
rw [primitiveRoots, nthRoots_zero, Multiset.toFinset_zero, Finset.filter_empty]
#align primitive_roots_zero primitiveRoots_zero
theorem isPrimitiveRoot_of_mem_primitiveRoots {ζ : R} (h : ζ ∈ primitiveRoots k R) :
IsPrimitiveRoot ζ k :=
k.eq_zero_or_pos.elim (fun hk => by simp [hk] at h) fun hk => (mem_primitiveRoots hk).1 h
#align is_primitive_root_of_mem_primitive_roots isPrimitiveRoot_of_mem_primitiveRoots
end primitiveRoots
namespace IsPrimitiveRoot
variable {k l : ℕ}
theorem mk_of_lt (ζ : M) (hk : 0 < k) (h1 : ζ ^ k = 1) (h : ∀ l : ℕ, 0 < l → l < k → ζ ^ l ≠ 1) :
IsPrimitiveRoot ζ k := by
refine ⟨h1, fun l hl => ?_⟩
suffices k.gcd l = k by exact this ▸ k.gcd_dvd_right l
rw [eq_iff_le_not_lt]
refine ⟨Nat.le_of_dvd hk (k.gcd_dvd_left l), ?_⟩
intro h'; apply h _ (Nat.gcd_pos_of_pos_left _ hk) h'
exact pow_gcd_eq_one _ h1 hl
#align is_primitive_root.mk_of_lt IsPrimitiveRoot.mk_of_lt
section CommMonoid
variable {ζ : M} {f : F} (h : IsPrimitiveRoot ζ k)
@[nontriviality]
theorem of_subsingleton [Subsingleton M] (x : M) : IsPrimitiveRoot x 1 :=
⟨Subsingleton.elim _ _, fun _ _ => one_dvd _⟩
#align is_primitive_root.of_subsingleton IsPrimitiveRoot.of_subsingleton
theorem pow_eq_one_iff_dvd (l : ℕ) : ζ ^ l = 1 ↔ k ∣ l :=
⟨h.dvd_of_pow_eq_one l, by
rintro ⟨i, rfl⟩; simp only [pow_mul, h.pow_eq_one, one_pow, PNat.mul_coe]⟩
#align is_primitive_root.pow_eq_one_iff_dvd IsPrimitiveRoot.pow_eq_one_iff_dvd
theorem isUnit (h : IsPrimitiveRoot ζ k) (h0 : 0 < k) : IsUnit ζ := by
apply isUnit_of_mul_eq_one ζ (ζ ^ (k - 1))
rw [← pow_succ', tsub_add_cancel_of_le h0.nat_succ_le, h.pow_eq_one]
#align is_primitive_root.is_unit IsPrimitiveRoot.isUnit
theorem pow_ne_one_of_pos_of_lt (h0 : 0 < l) (hl : l < k) : ζ ^ l ≠ 1 :=
mt (Nat.le_of_dvd h0 ∘ h.dvd_of_pow_eq_one _) <| not_le_of_lt hl
#align is_primitive_root.pow_ne_one_of_pos_of_lt IsPrimitiveRoot.pow_ne_one_of_pos_of_lt
theorem ne_one (hk : 1 < k) : ζ ≠ 1 :=
h.pow_ne_one_of_pos_of_lt zero_lt_one hk ∘ (pow_one ζ).trans
#align is_primitive_root.ne_one IsPrimitiveRoot.ne_one
theorem pow_inj (h : IsPrimitiveRoot ζ k) ⦃i j : ℕ⦄ (hi : i < k) (hj : j < k) (H : ζ ^ i = ζ ^ j) :
i = j := by
wlog hij : i ≤ j generalizing i j
· exact (this hj hi H.symm (le_of_not_le hij)).symm
apply le_antisymm hij
rw [← tsub_eq_zero_iff_le]
apply Nat.eq_zero_of_dvd_of_lt _ (lt_of_le_of_lt tsub_le_self hj)
apply h.dvd_of_pow_eq_one
rw [← ((h.isUnit (lt_of_le_of_lt (Nat.zero_le _) hi)).pow i).mul_left_inj, ← pow_add,
tsub_add_cancel_of_le hij, H, one_mul]
#align is_primitive_root.pow_inj IsPrimitiveRoot.pow_inj
theorem one : IsPrimitiveRoot (1 : M) 1 :=
{ pow_eq_one := pow_one _
dvd_of_pow_eq_one := fun _ _ => one_dvd _ }
#align is_primitive_root.one IsPrimitiveRoot.one
@[simp]
theorem one_right_iff : IsPrimitiveRoot ζ 1 ↔ ζ = 1 := by
clear h
constructor
· intro h; rw [← pow_one ζ, h.pow_eq_one]
· rintro rfl; exact one
#align is_primitive_root.one_right_iff IsPrimitiveRoot.one_right_iff
@[simp]
theorem coe_submonoidClass_iff {M B : Type*} [CommMonoid M] [SetLike B M] [SubmonoidClass B M]
{N : B} {ζ : N} : IsPrimitiveRoot (ζ : M) k ↔ IsPrimitiveRoot ζ k := by
simp_rw [iff_def]
norm_cast
#align is_primitive_root.coe_submonoid_class_iff IsPrimitiveRoot.coe_submonoidClass_iff
@[simp]
theorem coe_units_iff {ζ : Mˣ} : IsPrimitiveRoot (ζ : M) k ↔ IsPrimitiveRoot ζ k := by
simp only [iff_def, Units.ext_iff, Units.val_pow_eq_pow_val, Units.val_one]
#align is_primitive_root.coe_units_iff IsPrimitiveRoot.coe_units_iff
lemma isUnit_unit {ζ : M} {n} (hn) (hζ : IsPrimitiveRoot ζ n) :
IsPrimitiveRoot (hζ.isUnit hn).unit n := coe_units_iff.mp hζ
lemma isUnit_unit' {ζ : G} {n} (hn) (hζ : IsPrimitiveRoot ζ n) :
IsPrimitiveRoot (hζ.isUnit hn).unit' n := coe_units_iff.mp hζ
-- Porting note `variable` above already contains `(h : IsPrimitiveRoot ζ k)`
theorem pow_of_coprime (i : ℕ) (hi : i.Coprime k) : IsPrimitiveRoot (ζ ^ i) k := by
by_cases h0 : k = 0
· subst k; simp_all only [pow_one, Nat.coprime_zero_right]
rcases h.isUnit (Nat.pos_of_ne_zero h0) with ⟨ζ, rfl⟩
rw [← Units.val_pow_eq_pow_val]
rw [coe_units_iff] at h ⊢
refine
{ pow_eq_one := by rw [← pow_mul', pow_mul, h.pow_eq_one, one_pow]
dvd_of_pow_eq_one := ?_ }
intro l hl
apply h.dvd_of_pow_eq_one
rw [← pow_one ζ, ← zpow_natCast ζ, ← hi.gcd_eq_one, Nat.gcd_eq_gcd_ab, zpow_add, mul_pow,
← zpow_natCast, ← zpow_mul, mul_right_comm]
simp only [zpow_mul, hl, h.pow_eq_one, one_zpow, one_pow, one_mul, zpow_natCast]
#align is_primitive_root.pow_of_coprime IsPrimitiveRoot.pow_of_coprime
theorem pow_of_prime (h : IsPrimitiveRoot ζ k) {p : ℕ} (hprime : Nat.Prime p) (hdiv : ¬p ∣ k) :
IsPrimitiveRoot (ζ ^ p) k :=
h.pow_of_coprime p (hprime.coprime_iff_not_dvd.2 hdiv)
#align is_primitive_root.pow_of_prime IsPrimitiveRoot.pow_of_prime
theorem pow_iff_coprime (h : IsPrimitiveRoot ζ k) (h0 : 0 < k) (i : ℕ) :
IsPrimitiveRoot (ζ ^ i) k ↔ i.Coprime k := by
refine ⟨?_, h.pow_of_coprime i⟩
intro hi
obtain ⟨a, ha⟩ := i.gcd_dvd_left k
obtain ⟨b, hb⟩ := i.gcd_dvd_right k
suffices b = k by
-- Porting note: was `rwa [this, ← one_mul k, mul_left_inj' h0.ne', eq_comm] at hb`
rw [this, eq_comm, Nat.mul_left_eq_self_iff h0] at hb
rwa [Nat.Coprime]
rw [ha] at hi
rw [mul_comm] at hb
apply Nat.dvd_antisymm ⟨i.gcd k, hb⟩ (hi.dvd_of_pow_eq_one b _)
rw [← pow_mul', ← mul_assoc, ← hb, pow_mul, h.pow_eq_one, one_pow]
#align is_primitive_root.pow_iff_coprime IsPrimitiveRoot.pow_iff_coprime
protected theorem orderOf (ζ : M) : IsPrimitiveRoot ζ (orderOf ζ) :=
⟨pow_orderOf_eq_one ζ, fun _ => orderOf_dvd_of_pow_eq_one⟩
#align is_primitive_root.order_of IsPrimitiveRoot.orderOf
theorem unique {ζ : M} (hk : IsPrimitiveRoot ζ k) (hl : IsPrimitiveRoot ζ l) : k = l :=
Nat.dvd_antisymm (hk.2 _ hl.1) (hl.2 _ hk.1)
#align is_primitive_root.unique IsPrimitiveRoot.unique
theorem eq_orderOf : k = orderOf ζ :=
h.unique (IsPrimitiveRoot.orderOf ζ)
#align is_primitive_root.eq_order_of IsPrimitiveRoot.eq_orderOf
protected theorem iff (hk : 0 < k) :
IsPrimitiveRoot ζ k ↔ ζ ^ k = 1 ∧ ∀ l : ℕ, 0 < l → l < k → ζ ^ l ≠ 1 := by
refine ⟨fun h => ⟨h.pow_eq_one, fun l hl' hl => ?_⟩,
fun ⟨hζ, hl⟩ => IsPrimitiveRoot.mk_of_lt ζ hk hζ hl⟩
rw [h.eq_orderOf] at hl
exact pow_ne_one_of_lt_orderOf' hl'.ne' hl
#align is_primitive_root.iff IsPrimitiveRoot.iff
protected theorem not_iff : ¬IsPrimitiveRoot ζ k ↔ orderOf ζ ≠ k :=
⟨fun h hk => h <| hk ▸ IsPrimitiveRoot.orderOf ζ,
fun h hk => h.symm <| hk.unique <| IsPrimitiveRoot.orderOf ζ⟩
#align is_primitive_root.not_iff IsPrimitiveRoot.not_iff
theorem pow_mul_pow_lcm {ζ' : M} {k' : ℕ} (hζ : IsPrimitiveRoot ζ k) (hζ' : IsPrimitiveRoot ζ' k')
(hk : k ≠ 0) (hk' : k' ≠ 0) :
IsPrimitiveRoot
(ζ ^ (k / Nat.factorizationLCMLeft k k') * ζ' ^ (k' / Nat.factorizationLCMRight k k'))
(Nat.lcm k k') := by
convert IsPrimitiveRoot.orderOf _
convert ((Commute.all ζ ζ').orderOf_mul_pow_eq_lcm
(by simpa [← hζ.eq_orderOf]) (by simpa [← hζ'.eq_orderOf])).symm using 2
all_goals simp [hζ.eq_orderOf, hζ'.eq_orderOf]
theorem pow_of_dvd (h : IsPrimitiveRoot ζ k) {p : ℕ} (hp : p ≠ 0) (hdiv : p ∣ k) :
IsPrimitiveRoot (ζ ^ p) (k / p) := by
suffices orderOf (ζ ^ p) = k / p by exact this ▸ IsPrimitiveRoot.orderOf (ζ ^ p)
rw [orderOf_pow' _ hp, ← eq_orderOf h, Nat.gcd_eq_right hdiv]
#align is_primitive_root.pow_of_dvd IsPrimitiveRoot.pow_of_dvd
protected theorem mem_rootsOfUnity {ζ : Mˣ} {n : ℕ+} (h : IsPrimitiveRoot ζ n) :
ζ ∈ rootsOfUnity n M :=
h.pow_eq_one
#align is_primitive_root.mem_roots_of_unity IsPrimitiveRoot.mem_rootsOfUnity
/-- If there is an `n`-th primitive root of unity in `R` and `b` divides `n`,
then there is a `b`-th primitive root of unity in `R`. -/
theorem pow {n : ℕ} {a b : ℕ} (hn : 0 < n) (h : IsPrimitiveRoot ζ n) (hprod : n = a * b) :
IsPrimitiveRoot (ζ ^ a) b := by
subst n
simp only [iff_def, ← pow_mul, h.pow_eq_one, eq_self_iff_true, true_and_iff]
intro l hl
-- Porting note: was `by rintro rfl; simpa only [Nat.not_lt_zero, zero_mul] using hn`
have ha0 : a ≠ 0 := left_ne_zero_of_mul hn.ne'
rw [← mul_dvd_mul_iff_left ha0]
exact h.dvd_of_pow_eq_one _ hl
#align is_primitive_root.pow IsPrimitiveRoot.pow
lemma injOn_pow {n : ℕ} {ζ : M} (hζ : IsPrimitiveRoot ζ n) :
Set.InjOn (ζ ^ ·) (Finset.range n) := by
obtain (rfl|hn) := n.eq_zero_or_pos; · simp
intros i hi j hj e
rw [Finset.coe_range, Set.mem_Iio] at hi hj
have : (hζ.isUnit hn).unit ^ i = (hζ.isUnit hn).unit ^ j := Units.ext (by simpa using e)
rw [pow_inj_mod, ← orderOf_injective ⟨⟨Units.val, Units.val_one⟩, Units.val_mul⟩
Units.ext (hζ.isUnit hn).unit] at this
simpa [← hζ.eq_orderOf, Nat.mod_eq_of_lt, hi, hj] using this
section Maps
open Function
variable [FunLike F M N]
theorem map_of_injective [MonoidHomClass F M N] (h : IsPrimitiveRoot ζ k) (hf : Injective f) :
IsPrimitiveRoot (f ζ) k where
pow_eq_one := by rw [← map_pow, h.pow_eq_one, _root_.map_one]
dvd_of_pow_eq_one := by
rw [h.eq_orderOf]
intro l hl
rw [← map_pow, ← map_one f] at hl
exact orderOf_dvd_of_pow_eq_one (hf hl)
#align is_primitive_root.map_of_injective IsPrimitiveRoot.map_of_injective
theorem of_map_of_injective [MonoidHomClass F M N] (h : IsPrimitiveRoot (f ζ) k)
(hf : Injective f) : IsPrimitiveRoot ζ k where
pow_eq_one := by apply_fun f; rw [map_pow, _root_.map_one, h.pow_eq_one]
dvd_of_pow_eq_one := by
rw [h.eq_orderOf]
intro l hl
apply_fun f at hl
rw [map_pow, _root_.map_one] at hl
exact orderOf_dvd_of_pow_eq_one hl
#align is_primitive_root.of_map_of_injective IsPrimitiveRoot.of_map_of_injective
theorem map_iff_of_injective [MonoidHomClass F M N] (hf : Injective f) :
IsPrimitiveRoot (f ζ) k ↔ IsPrimitiveRoot ζ k :=
⟨fun h => h.of_map_of_injective hf, fun h => h.map_of_injective hf⟩
#align is_primitive_root.map_iff_of_injective IsPrimitiveRoot.map_iff_of_injective
end Maps
end CommMonoid
section CommMonoidWithZero
variable {M₀ : Type*} [CommMonoidWithZero M₀]
theorem zero [Nontrivial M₀] : IsPrimitiveRoot (0 : M₀) 0 :=
⟨pow_zero 0, fun l hl => by
simpa [zero_pow_eq, show ∀ p, ¬p → False ↔ p from @Classical.not_not] using hl⟩
#align is_primitive_root.zero IsPrimitiveRoot.zero
protected theorem ne_zero [Nontrivial M₀] {ζ : M₀} (h : IsPrimitiveRoot ζ k) : k ≠ 0 → ζ ≠ 0 :=
mt fun hn => h.unique (hn.symm ▸ IsPrimitiveRoot.zero)
#align is_primitive_root.ne_zero IsPrimitiveRoot.ne_zero
end CommMonoidWithZero
section CancelCommMonoidWithZero
variable {M₀ : Type*} [CancelCommMonoidWithZero M₀]
lemma injOn_pow_mul {n : ℕ} {ζ : M₀} (hζ : IsPrimitiveRoot ζ n)
{α : M₀} (hα : α ≠ 0) :
Set.InjOn (ζ ^ · * α) (Finset.range n) := fun i hi j hj e ↦
hζ.injOn_pow hi hj (by simpa [mul_eq_mul_right_iff, or_iff_left hα] using e)
end CancelCommMonoidWithZero
section DivisionCommMonoid
variable {ζ : G}
theorem zpow_eq_one (h : IsPrimitiveRoot ζ k) : ζ ^ (k : ℤ) = 1 := by
rw [zpow_natCast]; exact h.pow_eq_one
#align is_primitive_root.zpow_eq_one IsPrimitiveRoot.zpow_eq_one
theorem zpow_eq_one_iff_dvd (h : IsPrimitiveRoot ζ k) (l : ℤ) : ζ ^ l = 1 ↔ (k : ℤ) ∣ l := by
by_cases h0 : 0 ≤ l
· lift l to ℕ using h0; rw [zpow_natCast]; norm_cast; exact h.pow_eq_one_iff_dvd l
· have : 0 ≤ -l := by simp only [not_le, neg_nonneg] at h0 ⊢; exact le_of_lt h0
lift -l to ℕ using this with l' hl'
rw [← dvd_neg, ← hl']
norm_cast
rw [← h.pow_eq_one_iff_dvd, ← inv_inj, ← zpow_neg, ← hl', zpow_natCast, inv_one]
#align is_primitive_root.zpow_eq_one_iff_dvd IsPrimitiveRoot.zpow_eq_one_iff_dvd
theorem inv (h : IsPrimitiveRoot ζ k) : IsPrimitiveRoot ζ⁻¹ k :=
{ pow_eq_one := by simp only [h.pow_eq_one, inv_one, eq_self_iff_true, inv_pow]
dvd_of_pow_eq_one := by
intro l hl
apply h.dvd_of_pow_eq_one l
rw [← inv_inj, ← inv_pow, hl, inv_one] }
#align is_primitive_root.inv IsPrimitiveRoot.inv
@[simp]
theorem inv_iff : IsPrimitiveRoot ζ⁻¹ k ↔ IsPrimitiveRoot ζ k := by
refine ⟨?_, fun h => inv h⟩; intro h; rw [← inv_inv ζ]; exact inv h
#align is_primitive_root.inv_iff IsPrimitiveRoot.inv_iff
theorem zpow_of_gcd_eq_one (h : IsPrimitiveRoot ζ k) (i : ℤ) (hi : i.gcd k = 1) :
IsPrimitiveRoot (ζ ^ i) k := by
by_cases h0 : 0 ≤ i
· lift i to ℕ using h0
rw [zpow_natCast]
exact h.pow_of_coprime i hi
have : 0 ≤ -i := by simp only [not_le, neg_nonneg] at h0 ⊢; exact le_of_lt h0
lift -i to ℕ using this with i' hi'
rw [← inv_iff, ← zpow_neg, ← hi', zpow_natCast]
apply h.pow_of_coprime
rw [Int.gcd, ← Int.natAbs_neg, ← hi'] at hi
exact hi
#align is_primitive_root.zpow_of_gcd_eq_one IsPrimitiveRoot.zpow_of_gcd_eq_one
end DivisionCommMonoid
section CommRing
variable [CommRing R] {n : ℕ} (hn : 1 < n) {ζ : R} (hζ : IsPrimitiveRoot ζ n)
theorem sub_one_ne_zero : ζ - 1 ≠ 0 := sub_ne_zero.mpr <| hζ.ne_one hn
end CommRing
section IsDomain
variable {ζ : R}
variable [CommRing R] [IsDomain R]
@[simp]
theorem primitiveRoots_one : primitiveRoots 1 R = {(1 : R)} := by
apply Finset.eq_singleton_iff_unique_mem.2
constructor
· simp only [IsPrimitiveRoot.one_right_iff, mem_primitiveRoots zero_lt_one]
· intro x hx
rw [mem_primitiveRoots zero_lt_one, IsPrimitiveRoot.one_right_iff] at hx
exact hx
#align is_primitive_root.primitive_roots_one IsPrimitiveRoot.primitiveRoots_one
theorem neZero' {n : ℕ+} (hζ : IsPrimitiveRoot ζ n) : NeZero ((n : ℕ) : R) := by
let p := ringChar R
have hfin := multiplicity.finite_nat_iff.2 ⟨CharP.char_ne_one R p, n.pos⟩
obtain ⟨m, hm⟩ := multiplicity.exists_eq_pow_mul_and_not_dvd hfin
by_cases hp : p ∣ n
· obtain ⟨k, hk⟩ := Nat.exists_eq_succ_of_ne_zero (multiplicity.pos_of_dvd hfin hp).ne'
haveI : NeZero p := NeZero.of_pos (Nat.pos_of_dvd_of_pos hp n.pos)
haveI hpri : Fact p.Prime := CharP.char_is_prime_of_pos R p
have := hζ.pow_eq_one
rw [hm.1, hk, pow_succ', mul_assoc, pow_mul', ← frobenius_def, ← frobenius_one p] at this
exfalso
have hpos : 0 < p ^ k * m := by
refine mul_pos (pow_pos hpri.1.pos _) (Nat.pos_of_ne_zero fun h => ?_)
have H := hm.1
rw [h] at H
simp at H
refine hζ.pow_ne_one_of_pos_of_lt hpos ?_ (frobenius_inj R p this)
rw [hm.1, hk, pow_succ', mul_assoc, mul_comm p]
exact lt_mul_of_one_lt_right hpos hpri.1.one_lt
· exact NeZero.of_not_dvd R hp
#align is_primitive_root.ne_zero' IsPrimitiveRoot.neZero'
nonrec theorem mem_nthRootsFinset (hζ : IsPrimitiveRoot ζ k) (hk : 0 < k) :
ζ ∈ nthRootsFinset k R :=
(mem_nthRootsFinset hk).2 hζ.pow_eq_one
#align is_primitive_root.mem_nth_roots_finset IsPrimitiveRoot.mem_nthRootsFinset
end IsDomain
section IsDomain
variable [CommRing R]
variable {ζ : Rˣ} (h : IsPrimitiveRoot ζ k)
theorem eq_neg_one_of_two_right [NoZeroDivisors R] {ζ : R} (h : IsPrimitiveRoot ζ 2) : ζ = -1 := by
apply (eq_or_eq_neg_of_sq_eq_sq ζ 1 _).resolve_left
· rw [← pow_one ζ]; apply h.pow_ne_one_of_pos_of_lt <;> decide
· simp only [h.pow_eq_one, one_pow]
#align is_primitive_root.eq_neg_one_of_two_right IsPrimitiveRoot.eq_neg_one_of_two_right
theorem neg_one (p : ℕ) [Nontrivial R] [h : CharP R p] (hp : p ≠ 2) :
IsPrimitiveRoot (-1 : R) 2 := by
convert IsPrimitiveRoot.orderOf (-1 : R)
rw [orderOf_neg_one, if_neg]
rwa [ringChar.eq_iff.mpr h]
#align is_primitive_root.neg_one IsPrimitiveRoot.neg_one
/-- If `1 < k` then `(∑ i ∈ range k, ζ ^ i) = 0`. -/
theorem geom_sum_eq_zero [IsDomain R] {ζ : R} (hζ : IsPrimitiveRoot ζ k) (hk : 1 < k) :
∑ i ∈ range k, ζ ^ i = 0 := by
refine eq_zero_of_ne_zero_of_mul_left_eq_zero (sub_ne_zero_of_ne (hζ.ne_one hk).symm) ?_
rw [mul_neg_geom_sum, hζ.pow_eq_one, sub_self]
#align is_primitive_root.geom_sum_eq_zero IsPrimitiveRoot.geom_sum_eq_zero
/-- If `1 < k`, then `ζ ^ k.pred = -(∑ i ∈ range k.pred, ζ ^ i)`. -/
| Mathlib/RingTheory/RootsOfUnity/Basic.lean | 709 | 712 | theorem pow_sub_one_eq [IsDomain R] {ζ : R} (hζ : IsPrimitiveRoot ζ k) (hk : 1 < k) :
ζ ^ k.pred = -∑ i ∈ range k.pred, ζ ^ i := by |
rw [eq_neg_iff_add_eq_zero, add_comm, ← sum_range_succ, ← Nat.succ_eq_add_one,
Nat.succ_pred_eq_of_pos (pos_of_gt hk), hζ.geom_sum_eq_zero hk]
|
/-
Copyright (c) 2019 Zhouhang Zhou. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Zhouhang Zhou, Sébastien Gouëzel, Frédéric Dupuis
-/
import Mathlib.Algebra.DirectSum.Module
import Mathlib.Analysis.Complex.Basic
import Mathlib.Analysis.Convex.Uniform
import Mathlib.Analysis.NormedSpace.Completion
import Mathlib.Analysis.NormedSpace.BoundedLinearMaps
#align_import analysis.inner_product_space.basic from "leanprover-community/mathlib"@"3f655f5297b030a87d641ad4e825af8d9679eb0b"
/-!
# Inner product space
This file defines inner product spaces and proves the basic properties. We do not formally
define Hilbert spaces, but they can be obtained using the set of assumptions
`[NormedAddCommGroup E] [InnerProductSpace 𝕜 E] [CompleteSpace E]`.
An inner product space is a vector space endowed with an inner product. It generalizes the notion of
dot product in `ℝ^n` and provides the means of defining the length of a vector and the angle between
two vectors. In particular vectors `x` and `y` are orthogonal if their inner product equals zero.
We define both the real and complex cases at the same time using the `RCLike` typeclass.
This file proves general results on inner product spaces. For the specific construction of an inner
product structure on `n → 𝕜` for `𝕜 = ℝ` or `ℂ`, see `EuclideanSpace` in
`Analysis.InnerProductSpace.PiL2`.
## Main results
- We define the class `InnerProductSpace 𝕜 E` extending `NormedSpace 𝕜 E` with a number of basic
properties, most notably the Cauchy-Schwarz inequality. Here `𝕜` is understood to be either `ℝ`
or `ℂ`, through the `RCLike` typeclass.
- We show that the inner product is continuous, `continuous_inner`, and bundle it as the
continuous sesquilinear map `innerSL` (see also `innerₛₗ` for the non-continuous version).
- We define `Orthonormal`, a predicate on a function `v : ι → E`, and prove the existence of a
maximal orthonormal set, `exists_maximal_orthonormal`. Bessel's inequality,
`Orthonormal.tsum_inner_products_le`, states that given an orthonormal set `v` and a vector `x`,
the sum of the norm-squares of the inner products `⟪v i, x⟫` is no more than the norm-square of
`x`. For the existence of orthonormal bases, Hilbert bases, etc., see the file
`Analysis.InnerProductSpace.projection`.
## Notation
We globally denote the real and complex inner products by `⟪·, ·⟫_ℝ` and `⟪·, ·⟫_ℂ` respectively.
We also provide two notation namespaces: `RealInnerProductSpace`, `ComplexInnerProductSpace`,
which respectively introduce the plain notation `⟪·, ·⟫` for the real and complex inner product.
## Implementation notes
We choose the convention that inner products are conjugate linear in the first argument and linear
in the second.
## Tags
inner product space, Hilbert space, norm
## References
* [Clément & Martin, *The Lax-Milgram Theorem. A detailed proof to be formalized in Coq*]
* [Clément & Martin, *A Coq formal proof of the Lax–Milgram theorem*]
The Coq code is available at the following address: <http://www.lri.fr/~sboldo/elfic/index.html>
-/
noncomputable section
open RCLike Real Filter
open Topology ComplexConjugate
open LinearMap (BilinForm)
variable {𝕜 E F : Type*} [RCLike 𝕜]
/-- Syntactic typeclass for types endowed with an inner product -/
class Inner (𝕜 E : Type*) where
/-- The inner product function. -/
inner : E → E → 𝕜
#align has_inner Inner
export Inner (inner)
/-- The inner product with values in `𝕜`. -/
notation3:max "⟪" x ", " y "⟫_" 𝕜:max => @inner 𝕜 _ _ x y
section Notations
/-- The inner product with values in `ℝ`. -/
scoped[RealInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℝ _ _ x y
/-- The inner product with values in `ℂ`. -/
scoped[ComplexInnerProductSpace] notation "⟪" x ", " y "⟫" => @inner ℂ _ _ x y
end Notations
/-- An inner product space is a vector space with an additional operation called inner product.
The norm could be derived from the inner product, instead we require the existence of a norm and
the fact that `‖x‖^2 = re ⟪x, x⟫` to be able to put instances on `𝕂` or product
spaces.
To construct a norm from an inner product, see `InnerProductSpace.ofCore`.
-/
class InnerProductSpace (𝕜 : Type*) (E : Type*) [RCLike 𝕜] [NormedAddCommGroup E] extends
NormedSpace 𝕜 E, Inner 𝕜 E where
/-- The inner product induces the norm. -/
norm_sq_eq_inner : ∀ x : E, ‖x‖ ^ 2 = re (inner x x)
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space InnerProductSpace
/-!
### Constructing a normed space structure from an inner product
In the definition of an inner product space, we require the existence of a norm, which is equal
(but maybe not defeq) to the square root of the scalar product. This makes it possible to put
an inner product space structure on spaces with a preexisting norm (for instance `ℝ`), with good
properties. However, sometimes, one would like to define the norm starting only from a well-behaved
scalar product. This is what we implement in this paragraph, starting from a structure
`InnerProductSpace.Core` stating that we have a nice scalar product.
Our goal here is not to develop a whole theory with all the supporting API, as this will be done
below for `InnerProductSpace`. Instead, we implement the bare minimum to go as directly as
possible to the construction of the norm and the proof of the triangular inequality.
Warning: Do not use this `Core` structure if the space you are interested in already has a norm
instance defined on it, otherwise this will create a second non-defeq norm instance!
-/
/-- A structure requiring that a scalar product is positive definite and symmetric, from which one
can construct an `InnerProductSpace` instance in `InnerProductSpace.ofCore`. -/
-- @[nolint HasNonemptyInstance] porting note: I don't think we have this linter anymore
structure InnerProductSpace.Core (𝕜 : Type*) (F : Type*) [RCLike 𝕜] [AddCommGroup F]
[Module 𝕜 F] extends Inner 𝕜 F where
/-- The inner product is *hermitian*, taking the `conj` swaps the arguments. -/
conj_symm : ∀ x y, conj (inner y x) = inner x y
/-- The inner product is positive (semi)definite. -/
nonneg_re : ∀ x, 0 ≤ re (inner x x)
/-- The inner product is positive definite. -/
definite : ∀ x, inner x x = 0 → x = 0
/-- The inner product is additive in the first coordinate. -/
add_left : ∀ x y z, inner (x + y) z = inner x z + inner y z
/-- The inner product is conjugate linear in the first coordinate. -/
smul_left : ∀ x y r, inner (r • x) y = conj r * inner x y
#align inner_product_space.core InnerProductSpace.Core
/- We set `InnerProductSpace.Core` to be a class as we will use it as such in the construction
of the normed space structure that it produces. However, all the instances we will use will be
local to this proof. -/
attribute [class] InnerProductSpace.Core
/-- Define `InnerProductSpace.Core` from `InnerProductSpace`. Defined to reuse lemmas about
`InnerProductSpace.Core` for `InnerProductSpace`s. Note that the `Norm` instance provided by
`InnerProductSpace.Core.norm` is propositionally but not definitionally equal to the original
norm. -/
def InnerProductSpace.toCore [NormedAddCommGroup E] [c : InnerProductSpace 𝕜 E] :
InnerProductSpace.Core 𝕜 E :=
{ c with
nonneg_re := fun x => by
rw [← InnerProductSpace.norm_sq_eq_inner]
apply sq_nonneg
definite := fun x hx =>
norm_eq_zero.1 <| pow_eq_zero (n := 2) <| by
rw [InnerProductSpace.norm_sq_eq_inner (𝕜 := 𝕜) x, hx, map_zero] }
#align inner_product_space.to_core InnerProductSpace.toCore
namespace InnerProductSpace.Core
variable [AddCommGroup F] [Module 𝕜 F] [c : InnerProductSpace.Core 𝕜 F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 F _ x y
local notation "normSqK" => @RCLike.normSq 𝕜 _
local notation "reK" => @RCLike.re 𝕜 _
local notation "ext_iff" => @RCLike.ext_iff 𝕜 _
local postfix:90 "†" => starRingEnd _
/-- Inner product defined by the `InnerProductSpace.Core` structure. We can't reuse
`InnerProductSpace.Core.toInner` because it takes `InnerProductSpace.Core` as an explicit
argument. -/
def toInner' : Inner 𝕜 F :=
c.toInner
#align inner_product_space.core.to_has_inner' InnerProductSpace.Core.toInner'
attribute [local instance] toInner'
/-- The norm squared function for `InnerProductSpace.Core` structure. -/
def normSq (x : F) :=
reK ⟪x, x⟫
#align inner_product_space.core.norm_sq InnerProductSpace.Core.normSq
local notation "normSqF" => @normSq 𝕜 F _ _ _ _
theorem inner_conj_symm (x y : F) : ⟪y, x⟫† = ⟪x, y⟫ :=
c.conj_symm x y
#align inner_product_space.core.inner_conj_symm InnerProductSpace.Core.inner_conj_symm
theorem inner_self_nonneg {x : F} : 0 ≤ re ⟪x, x⟫ :=
c.nonneg_re _
#align inner_product_space.core.inner_self_nonneg InnerProductSpace.Core.inner_self_nonneg
theorem inner_self_im (x : F) : im ⟪x, x⟫ = 0 := by
rw [← @ofReal_inj 𝕜, im_eq_conj_sub]
simp [inner_conj_symm]
#align inner_product_space.core.inner_self_im InnerProductSpace.Core.inner_self_im
theorem inner_add_left (x y z : F) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
c.add_left _ _ _
#align inner_product_space.core.inner_add_left InnerProductSpace.Core.inner_add_left
theorem inner_add_right (x y z : F) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]; simp only [inner_conj_symm]
#align inner_product_space.core.inner_add_right InnerProductSpace.Core.inner_add_right
theorem ofReal_normSq_eq_inner_self (x : F) : (normSqF x : 𝕜) = ⟪x, x⟫ := by
rw [ext_iff]
exact ⟨by simp only [ofReal_re]; rfl, by simp only [inner_self_im, ofReal_im]⟩
#align inner_product_space.core.coe_norm_sq_eq_inner_self InnerProductSpace.Core.ofReal_normSq_eq_inner_self
theorem inner_re_symm (x y : F) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
#align inner_product_space.core.inner_re_symm InnerProductSpace.Core.inner_re_symm
theorem inner_im_symm (x y : F) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
#align inner_product_space.core.inner_im_symm InnerProductSpace.Core.inner_im_symm
theorem inner_smul_left (x y : F) {r : 𝕜} : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
c.smul_left _ _ _
#align inner_product_space.core.inner_smul_left InnerProductSpace.Core.inner_smul_left
theorem inner_smul_right (x y : F) {r : 𝕜} : ⟪x, r • y⟫ = r * ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left];
simp only [conj_conj, inner_conj_symm, RingHom.map_mul]
#align inner_product_space.core.inner_smul_right InnerProductSpace.Core.inner_smul_right
theorem inner_zero_left (x : F) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : F), inner_smul_left];
simp only [zero_mul, RingHom.map_zero]
#align inner_product_space.core.inner_zero_left InnerProductSpace.Core.inner_zero_left
theorem inner_zero_right (x : F) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left]; simp only [RingHom.map_zero]
#align inner_product_space.core.inner_zero_right InnerProductSpace.Core.inner_zero_right
theorem inner_self_eq_zero {x : F} : ⟪x, x⟫ = 0 ↔ x = 0 :=
⟨c.definite _, by
rintro rfl
exact inner_zero_left _⟩
#align inner_product_space.core.inner_self_eq_zero InnerProductSpace.Core.inner_self_eq_zero
theorem normSq_eq_zero {x : F} : normSqF x = 0 ↔ x = 0 :=
Iff.trans
(by simp only [normSq, ext_iff, map_zero, inner_self_im, eq_self_iff_true, and_true_iff])
(@inner_self_eq_zero 𝕜 _ _ _ _ _ x)
#align inner_product_space.core.norm_sq_eq_zero InnerProductSpace.Core.normSq_eq_zero
theorem inner_self_ne_zero {x : F} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
#align inner_product_space.core.inner_self_ne_zero InnerProductSpace.Core.inner_self_ne_zero
theorem inner_self_ofReal_re (x : F) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ := by
norm_num [ext_iff, inner_self_im]
set_option linter.uppercaseLean3 false in
#align inner_product_space.core.inner_self_re_to_K InnerProductSpace.Core.inner_self_ofReal_re
theorem norm_inner_symm (x y : F) : ‖⟪x, y⟫‖ = ‖⟪y, x⟫‖ := by rw [← inner_conj_symm, norm_conj]
#align inner_product_space.core.norm_inner_symm InnerProductSpace.Core.norm_inner_symm
theorem inner_neg_left (x y : F) : ⟪-x, y⟫ = -⟪x, y⟫ := by
rw [← neg_one_smul 𝕜 x, inner_smul_left]
simp
#align inner_product_space.core.inner_neg_left InnerProductSpace.Core.inner_neg_left
theorem inner_neg_right (x y : F) : ⟪x, -y⟫ = -⟪x, y⟫ := by
rw [← inner_conj_symm, inner_neg_left]; simp only [RingHom.map_neg, inner_conj_symm]
#align inner_product_space.core.inner_neg_right InnerProductSpace.Core.inner_neg_right
theorem inner_sub_left (x y z : F) : ⟪x - y, z⟫ = ⟪x, z⟫ - ⟪y, z⟫ := by
simp [sub_eq_add_neg, inner_add_left, inner_neg_left]
#align inner_product_space.core.inner_sub_left InnerProductSpace.Core.inner_sub_left
theorem inner_sub_right (x y z : F) : ⟪x, y - z⟫ = ⟪x, y⟫ - ⟪x, z⟫ := by
simp [sub_eq_add_neg, inner_add_right, inner_neg_right]
#align inner_product_space.core.inner_sub_right InnerProductSpace.Core.inner_sub_right
theorem inner_mul_symm_re_eq_norm (x y : F) : re (⟪x, y⟫ * ⟪y, x⟫) = ‖⟪x, y⟫ * ⟪y, x⟫‖ := by
rw [← inner_conj_symm, mul_comm]
exact re_eq_norm_of_mul_conj (inner y x)
#align inner_product_space.core.inner_mul_symm_re_eq_norm InnerProductSpace.Core.inner_mul_symm_re_eq_norm
/-- Expand `inner (x + y) (x + y)` -/
theorem inner_add_add_self (x y : F) : ⟪x + y, x + y⟫ = ⟪x, x⟫ + ⟪x, y⟫ + ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_add_left, inner_add_right]; ring
#align inner_product_space.core.inner_add_add_self InnerProductSpace.Core.inner_add_add_self
-- Expand `inner (x - y) (x - y)`
theorem inner_sub_sub_self (x y : F) : ⟪x - y, x - y⟫ = ⟪x, x⟫ - ⟪x, y⟫ - ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_sub_left, inner_sub_right]; ring
#align inner_product_space.core.inner_sub_sub_self InnerProductSpace.Core.inner_sub_sub_self
/-- An auxiliary equality useful to prove the **Cauchy–Schwarz inequality**: the square of the norm
of `⟪x, y⟫ • x - ⟪x, x⟫ • y` is equal to `‖x‖ ^ 2 * (‖x‖ ^ 2 * ‖y‖ ^ 2 - ‖⟪x, y⟫‖ ^ 2)`. We use
`InnerProductSpace.ofCore.normSq x` etc (defeq to `is_R_or_C.re ⟪x, x⟫`) instead of `‖x‖ ^ 2`
etc to avoid extra rewrites when applying it to an `InnerProductSpace`. -/
theorem cauchy_schwarz_aux (x y : F) :
normSqF (⟪x, y⟫ • x - ⟪x, x⟫ • y) = normSqF x * (normSqF x * normSqF y - ‖⟪x, y⟫‖ ^ 2) := by
rw [← @ofReal_inj 𝕜, ofReal_normSq_eq_inner_self]
simp only [inner_sub_sub_self, inner_smul_left, inner_smul_right, conj_ofReal, mul_sub, ←
ofReal_normSq_eq_inner_self x, ← ofReal_normSq_eq_inner_self y]
rw [← mul_assoc, mul_conj, RCLike.conj_mul, mul_left_comm, ← inner_conj_symm y, mul_conj]
push_cast
ring
#align inner_product_space.core.cauchy_schwarz_aux InnerProductSpace.Core.cauchy_schwarz_aux
/-- **Cauchy–Schwarz inequality**.
We need this for the `Core` structure to prove the triangle inequality below when
showing the core is a normed group.
-/
theorem inner_mul_inner_self_le (x y : F) : ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ := by
rcases eq_or_ne x 0 with (rfl | hx)
· simpa only [inner_zero_left, map_zero, zero_mul, norm_zero] using le_rfl
· have hx' : 0 < normSqF x := inner_self_nonneg.lt_of_ne' (mt normSq_eq_zero.1 hx)
rw [← sub_nonneg, ← mul_nonneg_iff_right_nonneg_of_pos hx', ← normSq, ← normSq,
norm_inner_symm y, ← sq, ← cauchy_schwarz_aux]
exact inner_self_nonneg
#align inner_product_space.core.inner_mul_inner_self_le InnerProductSpace.Core.inner_mul_inner_self_le
/-- Norm constructed from an `InnerProductSpace.Core` structure, defined to be the square root
of the scalar product. -/
def toNorm : Norm F where norm x := √(re ⟪x, x⟫)
#align inner_product_space.core.to_has_norm InnerProductSpace.Core.toNorm
attribute [local instance] toNorm
theorem norm_eq_sqrt_inner (x : F) : ‖x‖ = √(re ⟪x, x⟫) := rfl
#align inner_product_space.core.norm_eq_sqrt_inner InnerProductSpace.Core.norm_eq_sqrt_inner
theorem inner_self_eq_norm_mul_norm (x : F) : re ⟪x, x⟫ = ‖x‖ * ‖x‖ := by
rw [norm_eq_sqrt_inner, ← sqrt_mul inner_self_nonneg (re ⟪x, x⟫), sqrt_mul_self inner_self_nonneg]
#align inner_product_space.core.inner_self_eq_norm_mul_norm InnerProductSpace.Core.inner_self_eq_norm_mul_norm
theorem sqrt_normSq_eq_norm (x : F) : √(normSqF x) = ‖x‖ := rfl
#align inner_product_space.core.sqrt_norm_sq_eq_norm InnerProductSpace.Core.sqrt_normSq_eq_norm
/-- Cauchy–Schwarz inequality with norm -/
theorem norm_inner_le_norm (x y : F) : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ :=
nonneg_le_nonneg_of_sq_le_sq (mul_nonneg (sqrt_nonneg _) (sqrt_nonneg _)) <|
calc
‖⟪x, y⟫‖ * ‖⟪x, y⟫‖ = ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ := by rw [norm_inner_symm]
_ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ := inner_mul_inner_self_le x y
_ = ‖x‖ * ‖y‖ * (‖x‖ * ‖y‖) := by simp only [inner_self_eq_norm_mul_norm]; ring
#align inner_product_space.core.norm_inner_le_norm InnerProductSpace.Core.norm_inner_le_norm
/-- Normed group structure constructed from an `InnerProductSpace.Core` structure -/
def toNormedAddCommGroup : NormedAddCommGroup F :=
AddGroupNorm.toNormedAddCommGroup
{ toFun := fun x => √(re ⟪x, x⟫)
map_zero' := by simp only [sqrt_zero, inner_zero_right, map_zero]
neg' := fun x => by simp only [inner_neg_left, neg_neg, inner_neg_right]
add_le' := fun x y => by
have h₁ : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ := norm_inner_le_norm _ _
have h₂ : re ⟪x, y⟫ ≤ ‖⟪x, y⟫‖ := re_le_norm _
have h₃ : re ⟪x, y⟫ ≤ ‖x‖ * ‖y‖ := h₂.trans h₁
have h₄ : re ⟪y, x⟫ ≤ ‖x‖ * ‖y‖ := by rwa [← inner_conj_symm, conj_re]
have : ‖x + y‖ * ‖x + y‖ ≤ (‖x‖ + ‖y‖) * (‖x‖ + ‖y‖) := by
simp only [← inner_self_eq_norm_mul_norm, inner_add_add_self, mul_add, mul_comm, map_add]
linarith
exact nonneg_le_nonneg_of_sq_le_sq (add_nonneg (sqrt_nonneg _) (sqrt_nonneg _)) this
eq_zero_of_map_eq_zero' := fun x hx =>
normSq_eq_zero.1 <| (sqrt_eq_zero inner_self_nonneg).1 hx }
#align inner_product_space.core.to_normed_add_comm_group InnerProductSpace.Core.toNormedAddCommGroup
attribute [local instance] toNormedAddCommGroup
/-- Normed space structure constructed from an `InnerProductSpace.Core` structure -/
def toNormedSpace : NormedSpace 𝕜 F where
norm_smul_le r x := by
rw [norm_eq_sqrt_inner, inner_smul_left, inner_smul_right, ← mul_assoc]
rw [RCLike.conj_mul, ← ofReal_pow, re_ofReal_mul, sqrt_mul, ← ofReal_normSq_eq_inner_self,
ofReal_re]
· simp [sqrt_normSq_eq_norm, RCLike.sqrt_normSq_eq_norm]
· positivity
#align inner_product_space.core.to_normed_space InnerProductSpace.Core.toNormedSpace
end InnerProductSpace.Core
section
attribute [local instance] InnerProductSpace.Core.toNormedAddCommGroup
/-- Given an `InnerProductSpace.Core` structure on a space, one can use it to turn
the space into an inner product space. The `NormedAddCommGroup` structure is expected
to already be defined with `InnerProductSpace.ofCore.toNormedAddCommGroup`. -/
def InnerProductSpace.ofCore [AddCommGroup F] [Module 𝕜 F] (c : InnerProductSpace.Core 𝕜 F) :
InnerProductSpace 𝕜 F :=
letI : NormedSpace 𝕜 F := @InnerProductSpace.Core.toNormedSpace 𝕜 F _ _ _ c
{ c with
norm_sq_eq_inner := fun x => by
have h₁ : ‖x‖ ^ 2 = √(re (c.inner x x)) ^ 2 := rfl
have h₂ : 0 ≤ re (c.inner x x) := InnerProductSpace.Core.inner_self_nonneg
simp [h₁, sq_sqrt, h₂] }
#align inner_product_space.of_core InnerProductSpace.ofCore
end
/-! ### Properties of inner product spaces -/
variable [NormedAddCommGroup E] [InnerProductSpace 𝕜 E]
variable [NormedAddCommGroup F] [InnerProductSpace ℝ F]
local notation "⟪" x ", " y "⟫" => @inner 𝕜 _ _ x y
local notation "IK" => @RCLike.I 𝕜 _
local postfix:90 "†" => starRingEnd _
export InnerProductSpace (norm_sq_eq_inner)
section BasicProperties
@[simp]
theorem inner_conj_symm (x y : E) : ⟪y, x⟫† = ⟪x, y⟫ :=
InnerProductSpace.conj_symm _ _
#align inner_conj_symm inner_conj_symm
theorem real_inner_comm (x y : F) : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ :=
@inner_conj_symm ℝ _ _ _ _ x y
#align real_inner_comm real_inner_comm
theorem inner_eq_zero_symm {x y : E} : ⟪x, y⟫ = 0 ↔ ⟪y, x⟫ = 0 := by
rw [← inner_conj_symm]
exact star_eq_zero
#align inner_eq_zero_symm inner_eq_zero_symm
@[simp]
theorem inner_self_im (x : E) : im ⟪x, x⟫ = 0 := by rw [← @ofReal_inj 𝕜, im_eq_conj_sub]; simp
#align inner_self_im inner_self_im
theorem inner_add_left (x y z : E) : ⟪x + y, z⟫ = ⟪x, z⟫ + ⟪y, z⟫ :=
InnerProductSpace.add_left _ _ _
#align inner_add_left inner_add_left
theorem inner_add_right (x y z : E) : ⟪x, y + z⟫ = ⟪x, y⟫ + ⟪x, z⟫ := by
rw [← inner_conj_symm, inner_add_left, RingHom.map_add]
simp only [inner_conj_symm]
#align inner_add_right inner_add_right
theorem inner_re_symm (x y : E) : re ⟪x, y⟫ = re ⟪y, x⟫ := by rw [← inner_conj_symm, conj_re]
#align inner_re_symm inner_re_symm
theorem inner_im_symm (x y : E) : im ⟪x, y⟫ = -im ⟪y, x⟫ := by rw [← inner_conj_symm, conj_im]
#align inner_im_symm inner_im_symm
theorem inner_smul_left (x y : E) (r : 𝕜) : ⟪r • x, y⟫ = r† * ⟪x, y⟫ :=
InnerProductSpace.smul_left _ _ _
#align inner_smul_left inner_smul_left
theorem real_inner_smul_left (x y : F) (r : ℝ) : ⟪r • x, y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_left _ _ _
#align real_inner_smul_left real_inner_smul_left
theorem inner_smul_real_left (x y : E) (r : ℝ) : ⟪(r : 𝕜) • x, y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_left, conj_ofReal, Algebra.smul_def]
rfl
#align inner_smul_real_left inner_smul_real_left
theorem inner_smul_right (x y : E) (r : 𝕜) : ⟪x, r • y⟫ = r * ⟪x, y⟫ := by
rw [← inner_conj_symm, inner_smul_left, RingHom.map_mul, conj_conj, inner_conj_symm]
#align inner_smul_right inner_smul_right
theorem real_inner_smul_right (x y : F) (r : ℝ) : ⟪x, r • y⟫_ℝ = r * ⟪x, y⟫_ℝ :=
inner_smul_right _ _ _
#align real_inner_smul_right real_inner_smul_right
theorem inner_smul_real_right (x y : E) (r : ℝ) : ⟪x, (r : 𝕜) • y⟫ = r • ⟪x, y⟫ := by
rw [inner_smul_right, Algebra.smul_def]
rfl
#align inner_smul_real_right inner_smul_real_right
/-- The inner product as a sesquilinear form.
Note that in the case `𝕜 = ℝ` this is a bilinear form. -/
@[simps!]
def sesqFormOfInner : E →ₗ[𝕜] E →ₗ⋆[𝕜] 𝕜 :=
LinearMap.mk₂'ₛₗ (RingHom.id 𝕜) (starRingEnd _) (fun x y => ⟪y, x⟫)
(fun _x _y _z => inner_add_right _ _ _) (fun _r _x _y => inner_smul_right _ _ _)
(fun _x _y _z => inner_add_left _ _ _) fun _r _x _y => inner_smul_left _ _ _
#align sesq_form_of_inner sesqFormOfInner
/-- The real inner product as a bilinear form.
Note that unlike `sesqFormOfInner`, this does not reverse the order of the arguments. -/
@[simps!]
def bilinFormOfRealInner : BilinForm ℝ F := sesqFormOfInner.flip
#align bilin_form_of_real_inner bilinFormOfRealInner
/-- An inner product with a sum on the left. -/
theorem sum_inner {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪∑ i ∈ s, f i, x⟫ = ∑ i ∈ s, ⟪f i, x⟫ :=
map_sum (sesqFormOfInner (𝕜 := 𝕜) (E := E) x) _ _
#align sum_inner sum_inner
/-- An inner product with a sum on the right. -/
theorem inner_sum {ι : Type*} (s : Finset ι) (f : ι → E) (x : E) :
⟪x, ∑ i ∈ s, f i⟫ = ∑ i ∈ s, ⟪x, f i⟫ :=
map_sum (LinearMap.flip sesqFormOfInner x) _ _
#align inner_sum inner_sum
/-- An inner product with a sum on the left, `Finsupp` version. -/
theorem Finsupp.sum_inner {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪l.sum fun (i : ι) (a : 𝕜) => a • v i, x⟫ = l.sum fun (i : ι) (a : 𝕜) => conj a • ⟪v i, x⟫ := by
convert _root_.sum_inner (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_left, Finsupp.sum, smul_eq_mul]
#align finsupp.sum_inner Finsupp.sum_inner
/-- An inner product with a sum on the right, `Finsupp` version. -/
theorem Finsupp.inner_sum {ι : Type*} (l : ι →₀ 𝕜) (v : ι → E) (x : E) :
⟪x, l.sum fun (i : ι) (a : 𝕜) => a • v i⟫ = l.sum fun (i : ι) (a : 𝕜) => a • ⟪x, v i⟫ := by
convert _root_.inner_sum (𝕜 := 𝕜) l.support (fun a => l a • v a) x
simp only [inner_smul_right, Finsupp.sum, smul_eq_mul]
#align finsupp.inner_sum Finsupp.inner_sum
theorem DFinsupp.sum_inner {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪l.sum f, x⟫ = l.sum fun i a => ⟪f i a, x⟫ := by
simp (config := { contextual := true }) only [DFinsupp.sum, _root_.sum_inner, smul_eq_mul]
#align dfinsupp.sum_inner DFinsupp.sum_inner
theorem DFinsupp.inner_sum {ι : Type*} [DecidableEq ι] {α : ι → Type*}
[∀ i, AddZeroClass (α i)] [∀ (i) (x : α i), Decidable (x ≠ 0)] (f : ∀ i, α i → E)
(l : Π₀ i, α i) (x : E) : ⟪x, l.sum f⟫ = l.sum fun i a => ⟪x, f i a⟫ := by
simp (config := { contextual := true }) only [DFinsupp.sum, _root_.inner_sum, smul_eq_mul]
#align dfinsupp.inner_sum DFinsupp.inner_sum
@[simp]
theorem inner_zero_left (x : E) : ⟪0, x⟫ = 0 := by
rw [← zero_smul 𝕜 (0 : E), inner_smul_left, RingHom.map_zero, zero_mul]
#align inner_zero_left inner_zero_left
theorem inner_re_zero_left (x : E) : re ⟪0, x⟫ = 0 := by
simp only [inner_zero_left, AddMonoidHom.map_zero]
#align inner_re_zero_left inner_re_zero_left
@[simp]
theorem inner_zero_right (x : E) : ⟪x, 0⟫ = 0 := by
rw [← inner_conj_symm, inner_zero_left, RingHom.map_zero]
#align inner_zero_right inner_zero_right
theorem inner_re_zero_right (x : E) : re ⟪x, 0⟫ = 0 := by
simp only [inner_zero_right, AddMonoidHom.map_zero]
#align inner_re_zero_right inner_re_zero_right
theorem inner_self_nonneg {x : E} : 0 ≤ re ⟪x, x⟫ :=
InnerProductSpace.toCore.nonneg_re x
#align inner_self_nonneg inner_self_nonneg
theorem real_inner_self_nonneg {x : F} : 0 ≤ ⟪x, x⟫_ℝ :=
@inner_self_nonneg ℝ F _ _ _ x
#align real_inner_self_nonneg real_inner_self_nonneg
@[simp]
theorem inner_self_ofReal_re (x : E) : (re ⟪x, x⟫ : 𝕜) = ⟪x, x⟫ :=
((RCLike.is_real_TFAE (⟪x, x⟫ : 𝕜)).out 2 3).2 (inner_self_im _)
set_option linter.uppercaseLean3 false in
#align inner_self_re_to_K inner_self_ofReal_re
theorem inner_self_eq_norm_sq_to_K (x : E) : ⟪x, x⟫ = (‖x‖ : 𝕜) ^ 2 := by
rw [← inner_self_ofReal_re, ← norm_sq_eq_inner, ofReal_pow]
set_option linter.uppercaseLean3 false in
#align inner_self_eq_norm_sq_to_K inner_self_eq_norm_sq_to_K
theorem inner_self_re_eq_norm (x : E) : re ⟪x, x⟫ = ‖⟪x, x⟫‖ := by
conv_rhs => rw [← inner_self_ofReal_re]
symm
exact norm_of_nonneg inner_self_nonneg
#align inner_self_re_eq_norm inner_self_re_eq_norm
theorem inner_self_ofReal_norm (x : E) : (‖⟪x, x⟫‖ : 𝕜) = ⟪x, x⟫ := by
rw [← inner_self_re_eq_norm]
exact inner_self_ofReal_re _
set_option linter.uppercaseLean3 false in
#align inner_self_norm_to_K inner_self_ofReal_norm
theorem real_inner_self_abs (x : F) : |⟪x, x⟫_ℝ| = ⟪x, x⟫_ℝ :=
@inner_self_ofReal_norm ℝ F _ _ _ x
#align real_inner_self_abs real_inner_self_abs
@[simp]
theorem inner_self_eq_zero {x : E} : ⟪x, x⟫ = 0 ↔ x = 0 := by
rw [inner_self_eq_norm_sq_to_K, sq_eq_zero_iff, ofReal_eq_zero, norm_eq_zero]
#align inner_self_eq_zero inner_self_eq_zero
theorem inner_self_ne_zero {x : E} : ⟪x, x⟫ ≠ 0 ↔ x ≠ 0 :=
inner_self_eq_zero.not
#align inner_self_ne_zero inner_self_ne_zero
@[simp]
theorem inner_self_nonpos {x : E} : re ⟪x, x⟫ ≤ 0 ↔ x = 0 := by
rw [← norm_sq_eq_inner, (sq_nonneg _).le_iff_eq, sq_eq_zero_iff, norm_eq_zero]
#align inner_self_nonpos inner_self_nonpos
theorem real_inner_self_nonpos {x : F} : ⟪x, x⟫_ℝ ≤ 0 ↔ x = 0 :=
@inner_self_nonpos ℝ F _ _ _ x
#align real_inner_self_nonpos real_inner_self_nonpos
theorem norm_inner_symm (x y : E) : ‖⟪x, y⟫‖ = ‖⟪y, x⟫‖ := by rw [← inner_conj_symm, norm_conj]
#align norm_inner_symm norm_inner_symm
@[simp]
theorem inner_neg_left (x y : E) : ⟪-x, y⟫ = -⟪x, y⟫ := by
rw [← neg_one_smul 𝕜 x, inner_smul_left]
simp
#align inner_neg_left inner_neg_left
@[simp]
theorem inner_neg_right (x y : E) : ⟪x, -y⟫ = -⟪x, y⟫ := by
rw [← inner_conj_symm, inner_neg_left]; simp only [RingHom.map_neg, inner_conj_symm]
#align inner_neg_right inner_neg_right
theorem inner_neg_neg (x y : E) : ⟪-x, -y⟫ = ⟪x, y⟫ := by simp
#align inner_neg_neg inner_neg_neg
-- Porting note: removed `simp` because it can prove it using `inner_conj_symm`
theorem inner_self_conj (x : E) : ⟪x, x⟫† = ⟪x, x⟫ := inner_conj_symm _ _
#align inner_self_conj inner_self_conj
theorem inner_sub_left (x y z : E) : ⟪x - y, z⟫ = ⟪x, z⟫ - ⟪y, z⟫ := by
simp [sub_eq_add_neg, inner_add_left]
#align inner_sub_left inner_sub_left
theorem inner_sub_right (x y z : E) : ⟪x, y - z⟫ = ⟪x, y⟫ - ⟪x, z⟫ := by
simp [sub_eq_add_neg, inner_add_right]
#align inner_sub_right inner_sub_right
theorem inner_mul_symm_re_eq_norm (x y : E) : re (⟪x, y⟫ * ⟪y, x⟫) = ‖⟪x, y⟫ * ⟪y, x⟫‖ := by
rw [← inner_conj_symm, mul_comm]
exact re_eq_norm_of_mul_conj (inner y x)
#align inner_mul_symm_re_eq_norm inner_mul_symm_re_eq_norm
/-- Expand `⟪x + y, x + y⟫` -/
theorem inner_add_add_self (x y : E) : ⟪x + y, x + y⟫ = ⟪x, x⟫ + ⟪x, y⟫ + ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_add_left, inner_add_right]; ring
#align inner_add_add_self inner_add_add_self
/-- Expand `⟪x + y, x + y⟫_ℝ` -/
theorem real_inner_add_add_self (x y : F) :
⟪x + y, x + y⟫_ℝ = ⟪x, x⟫_ℝ + 2 * ⟪x, y⟫_ℝ + ⟪y, y⟫_ℝ := by
have : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ := by rw [← inner_conj_symm]; rfl
simp only [inner_add_add_self, this, add_left_inj]
ring
#align real_inner_add_add_self real_inner_add_add_self
-- Expand `⟪x - y, x - y⟫`
theorem inner_sub_sub_self (x y : E) : ⟪x - y, x - y⟫ = ⟪x, x⟫ - ⟪x, y⟫ - ⟪y, x⟫ + ⟪y, y⟫ := by
simp only [inner_sub_left, inner_sub_right]; ring
#align inner_sub_sub_self inner_sub_sub_self
/-- Expand `⟪x - y, x - y⟫_ℝ` -/
theorem real_inner_sub_sub_self (x y : F) :
⟪x - y, x - y⟫_ℝ = ⟪x, x⟫_ℝ - 2 * ⟪x, y⟫_ℝ + ⟪y, y⟫_ℝ := by
have : ⟪y, x⟫_ℝ = ⟪x, y⟫_ℝ := by rw [← inner_conj_symm]; rfl
simp only [inner_sub_sub_self, this, add_left_inj]
ring
#align real_inner_sub_sub_self real_inner_sub_sub_self
variable (𝕜)
theorem ext_inner_left {x y : E} (h : ∀ v, ⟪v, x⟫ = ⟪v, y⟫) : x = y := by
rw [← sub_eq_zero, ← @inner_self_eq_zero 𝕜, inner_sub_right, sub_eq_zero, h (x - y)]
#align ext_inner_left ext_inner_left
theorem ext_inner_right {x y : E} (h : ∀ v, ⟪x, v⟫ = ⟪y, v⟫) : x = y := by
rw [← sub_eq_zero, ← @inner_self_eq_zero 𝕜, inner_sub_left, sub_eq_zero, h (x - y)]
#align ext_inner_right ext_inner_right
variable {𝕜}
/-- Parallelogram law -/
theorem parallelogram_law {x y : E} : ⟪x + y, x + y⟫ + ⟪x - y, x - y⟫ = 2 * (⟪x, x⟫ + ⟪y, y⟫) := by
simp only [inner_add_add_self, inner_sub_sub_self]
ring
#align parallelogram_law parallelogram_law
/-- **Cauchy–Schwarz inequality**. -/
theorem inner_mul_inner_self_le (x y : E) : ‖⟪x, y⟫‖ * ‖⟪y, x⟫‖ ≤ re ⟪x, x⟫ * re ⟪y, y⟫ :=
letI c : InnerProductSpace.Core 𝕜 E := InnerProductSpace.toCore
InnerProductSpace.Core.inner_mul_inner_self_le x y
#align inner_mul_inner_self_le inner_mul_inner_self_le
/-- Cauchy–Schwarz inequality for real inner products. -/
theorem real_inner_mul_inner_self_le (x y : F) : ⟪x, y⟫_ℝ * ⟪x, y⟫_ℝ ≤ ⟪x, x⟫_ℝ * ⟪y, y⟫_ℝ :=
calc
⟪x, y⟫_ℝ * ⟪x, y⟫_ℝ ≤ ‖⟪x, y⟫_ℝ‖ * ‖⟪y, x⟫_ℝ‖ := by
rw [real_inner_comm y, ← norm_mul]
exact le_abs_self _
_ ≤ ⟪x, x⟫_ℝ * ⟪y, y⟫_ℝ := @inner_mul_inner_self_le ℝ _ _ _ _ x y
#align real_inner_mul_inner_self_le real_inner_mul_inner_self_le
/-- A family of vectors is linearly independent if they are nonzero
and orthogonal. -/
theorem linearIndependent_of_ne_zero_of_inner_eq_zero {ι : Type*} {v : ι → E} (hz : ∀ i, v i ≠ 0)
(ho : Pairwise fun i j => ⟪v i, v j⟫ = 0) : LinearIndependent 𝕜 v := by
rw [linearIndependent_iff']
intro s g hg i hi
have h' : g i * inner (v i) (v i) = inner (v i) (∑ j ∈ s, g j • v j) := by
rw [inner_sum]
symm
convert Finset.sum_eq_single (β := 𝕜) i ?_ ?_
· rw [inner_smul_right]
· intro j _hj hji
rw [inner_smul_right, ho hji.symm, mul_zero]
· exact fun h => False.elim (h hi)
simpa [hg, hz] using h'
#align linear_independent_of_ne_zero_of_inner_eq_zero linearIndependent_of_ne_zero_of_inner_eq_zero
end BasicProperties
section OrthonormalSets
variable {ι : Type*} (𝕜)
/-- An orthonormal set of vectors in an `InnerProductSpace` -/
def Orthonormal (v : ι → E) : Prop :=
(∀ i, ‖v i‖ = 1) ∧ Pairwise fun i j => ⟪v i, v j⟫ = 0
#align orthonormal Orthonormal
variable {𝕜}
/-- `if ... then ... else` characterization of an indexed set of vectors being orthonormal. (Inner
product equals Kronecker delta.) -/
theorem orthonormal_iff_ite [DecidableEq ι] {v : ι → E} :
Orthonormal 𝕜 v ↔ ∀ i j, ⟪v i, v j⟫ = if i = j then (1 : 𝕜) else (0 : 𝕜) := by
constructor
· intro hv i j
split_ifs with h
· simp [h, inner_self_eq_norm_sq_to_K, hv.1]
· exact hv.2 h
· intro h
constructor
· intro i
have h' : ‖v i‖ ^ 2 = 1 ^ 2 := by simp [@norm_sq_eq_inner 𝕜, h i i]
have h₁ : 0 ≤ ‖v i‖ := norm_nonneg _
have h₂ : (0 : ℝ) ≤ 1 := zero_le_one
rwa [sq_eq_sq h₁ h₂] at h'
· intro i j hij
simpa [hij] using h i j
#align orthonormal_iff_ite orthonormal_iff_ite
/-- `if ... then ... else` characterization of a set of vectors being orthonormal. (Inner product
equals Kronecker delta.) -/
theorem orthonormal_subtype_iff_ite [DecidableEq E] {s : Set E} :
Orthonormal 𝕜 (Subtype.val : s → E) ↔ ∀ v ∈ s, ∀ w ∈ s, ⟪v, w⟫ = if v = w then 1 else 0 := by
rw [orthonormal_iff_ite]
constructor
· intro h v hv w hw
convert h ⟨v, hv⟩ ⟨w, hw⟩ using 1
simp
· rintro h ⟨v, hv⟩ ⟨w, hw⟩
convert h v hv w hw using 1
simp
#align orthonormal_subtype_iff_ite orthonormal_subtype_iff_ite
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_right_finsupp {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι →₀ 𝕜) (i : ι) :
⟪v i, Finsupp.total ι E 𝕜 v l⟫ = l i := by
classical
simpa [Finsupp.total_apply, Finsupp.inner_sum, orthonormal_iff_ite.mp hv] using Eq.symm
#align orthonormal.inner_right_finsupp Orthonormal.inner_right_finsupp
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_right_sum {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜) {s : Finset ι}
{i : ι} (hi : i ∈ s) : ⟪v i, ∑ i ∈ s, l i • v i⟫ = l i := by
classical
simp [inner_sum, inner_smul_right, orthonormal_iff_ite.mp hv, hi]
#align orthonormal.inner_right_sum Orthonormal.inner_right_sum
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_right_fintype [Fintype ι] {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜)
(i : ι) : ⟪v i, ∑ i : ι, l i • v i⟫ = l i :=
hv.inner_right_sum l (Finset.mem_univ _)
#align orthonormal.inner_right_fintype Orthonormal.inner_right_fintype
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_left_finsupp {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι →₀ 𝕜) (i : ι) :
⟪Finsupp.total ι E 𝕜 v l, v i⟫ = conj (l i) := by rw [← inner_conj_symm, hv.inner_right_finsupp]
#align orthonormal.inner_left_finsupp Orthonormal.inner_left_finsupp
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_left_sum {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜) {s : Finset ι}
{i : ι} (hi : i ∈ s) : ⟪∑ i ∈ s, l i • v i, v i⟫ = conj (l i) := by
classical
simp only [sum_inner, inner_smul_left, orthonormal_iff_ite.mp hv, hi, mul_boole,
Finset.sum_ite_eq', if_true]
#align orthonormal.inner_left_sum Orthonormal.inner_left_sum
/-- The inner product of a linear combination of a set of orthonormal vectors with one of those
vectors picks out the coefficient of that vector. -/
theorem Orthonormal.inner_left_fintype [Fintype ι] {v : ι → E} (hv : Orthonormal 𝕜 v) (l : ι → 𝕜)
(i : ι) : ⟪∑ i : ι, l i • v i, v i⟫ = conj (l i) :=
hv.inner_left_sum l (Finset.mem_univ _)
#align orthonormal.inner_left_fintype Orthonormal.inner_left_fintype
/-- The inner product of two linear combinations of a set of orthonormal vectors, expressed as
a sum over the first `Finsupp`. -/
theorem Orthonormal.inner_finsupp_eq_sum_left {v : ι → E} (hv : Orthonormal 𝕜 v) (l₁ l₂ : ι →₀ 𝕜) :
⟪Finsupp.total ι E 𝕜 v l₁, Finsupp.total ι E 𝕜 v l₂⟫ = l₁.sum fun i y => conj y * l₂ i := by
simp only [l₁.total_apply _, Finsupp.sum_inner, hv.inner_right_finsupp, smul_eq_mul]
#align orthonormal.inner_finsupp_eq_sum_left Orthonormal.inner_finsupp_eq_sum_left
/-- The inner product of two linear combinations of a set of orthonormal vectors, expressed as
a sum over the second `Finsupp`. -/
theorem Orthonormal.inner_finsupp_eq_sum_right {v : ι → E} (hv : Orthonormal 𝕜 v) (l₁ l₂ : ι →₀ 𝕜) :
⟪Finsupp.total ι E 𝕜 v l₁, Finsupp.total ι E 𝕜 v l₂⟫ = l₂.sum fun i y => conj (l₁ i) * y := by
simp only [l₂.total_apply _, Finsupp.inner_sum, hv.inner_left_finsupp, mul_comm, smul_eq_mul]
#align orthonormal.inner_finsupp_eq_sum_right Orthonormal.inner_finsupp_eq_sum_right
/-- The inner product of two linear combinations of a set of orthonormal vectors, expressed as
a sum. -/
theorem Orthonormal.inner_sum {v : ι → E} (hv : Orthonormal 𝕜 v) (l₁ l₂ : ι → 𝕜) (s : Finset ι) :
⟪∑ i ∈ s, l₁ i • v i, ∑ i ∈ s, l₂ i • v i⟫ = ∑ i ∈ s, conj (l₁ i) * l₂ i := by
simp_rw [sum_inner, inner_smul_left]
refine Finset.sum_congr rfl fun i hi => ?_
rw [hv.inner_right_sum l₂ hi]
#align orthonormal.inner_sum Orthonormal.inner_sum
/--
The double sum of weighted inner products of pairs of vectors from an orthonormal sequence is the
sum of the weights.
-/
theorem Orthonormal.inner_left_right_finset {s : Finset ι} {v : ι → E} (hv : Orthonormal 𝕜 v)
{a : ι → ι → 𝕜} : (∑ i ∈ s, ∑ j ∈ s, a i j • ⟪v j, v i⟫) = ∑ k ∈ s, a k k := by
classical
simp [orthonormal_iff_ite.mp hv, Finset.sum_ite_of_true]
#align orthonormal.inner_left_right_finset Orthonormal.inner_left_right_finset
/-- An orthonormal set is linearly independent. -/
theorem Orthonormal.linearIndependent {v : ι → E} (hv : Orthonormal 𝕜 v) :
LinearIndependent 𝕜 v := by
rw [linearIndependent_iff]
intro l hl
ext i
have key : ⟪v i, Finsupp.total ι E 𝕜 v l⟫ = ⟪v i, 0⟫ := by rw [hl]
simpa only [hv.inner_right_finsupp, inner_zero_right] using key
#align orthonormal.linear_independent Orthonormal.linearIndependent
/-- A subfamily of an orthonormal family (i.e., a composition with an injective map) is an
orthonormal family. -/
theorem Orthonormal.comp {ι' : Type*} {v : ι → E} (hv : Orthonormal 𝕜 v) (f : ι' → ι)
(hf : Function.Injective f) : Orthonormal 𝕜 (v ∘ f) := by
classical
rw [orthonormal_iff_ite] at hv ⊢
intro i j
convert hv (f i) (f j) using 1
simp [hf.eq_iff]
#align orthonormal.comp Orthonormal.comp
/-- An injective family `v : ι → E` is orthonormal if and only if `Subtype.val : (range v) → E` is
orthonormal. -/
theorem orthonormal_subtype_range {v : ι → E} (hv : Function.Injective v) :
Orthonormal 𝕜 (Subtype.val : Set.range v → E) ↔ Orthonormal 𝕜 v := by
let f : ι ≃ Set.range v := Equiv.ofInjective v hv
refine ⟨fun h => h.comp f f.injective, fun h => ?_⟩
rw [← Equiv.self_comp_ofInjective_symm hv]
exact h.comp f.symm f.symm.injective
#align orthonormal_subtype_range orthonormal_subtype_range
/-- If `v : ι → E` is an orthonormal family, then `Subtype.val : (range v) → E` is an orthonormal
family. -/
theorem Orthonormal.toSubtypeRange {v : ι → E} (hv : Orthonormal 𝕜 v) :
Orthonormal 𝕜 (Subtype.val : Set.range v → E) :=
(orthonormal_subtype_range hv.linearIndependent.injective).2 hv
#align orthonormal.to_subtype_range Orthonormal.toSubtypeRange
/-- A linear combination of some subset of an orthonormal set is orthogonal to other members of the
set. -/
theorem Orthonormal.inner_finsupp_eq_zero {v : ι → E} (hv : Orthonormal 𝕜 v) {s : Set ι} {i : ι}
(hi : i ∉ s) {l : ι →₀ 𝕜} (hl : l ∈ Finsupp.supported 𝕜 𝕜 s) :
⟪Finsupp.total ι E 𝕜 v l, v i⟫ = 0 := by
rw [Finsupp.mem_supported'] at hl
simp only [hv.inner_left_finsupp, hl i hi, map_zero]
#align orthonormal.inner_finsupp_eq_zero Orthonormal.inner_finsupp_eq_zero
/-- Given an orthonormal family, a second family of vectors is orthonormal if every vector equals
the corresponding vector in the original family or its negation. -/
theorem Orthonormal.orthonormal_of_forall_eq_or_eq_neg {v w : ι → E} (hv : Orthonormal 𝕜 v)
(hw : ∀ i, w i = v i ∨ w i = -v i) : Orthonormal 𝕜 w := by
classical
rw [orthonormal_iff_ite] at *
intro i j
cases' hw i with hi hi <;> cases' hw j with hj hj <;>
replace hv := hv i j <;> split_ifs at hv ⊢ with h <;>
simpa only [hi, hj, h, inner_neg_right, inner_neg_left, neg_neg, eq_self_iff_true,
neg_eq_zero] using hv
#align orthonormal.orthonormal_of_forall_eq_or_eq_neg Orthonormal.orthonormal_of_forall_eq_or_eq_neg
/- The material that follows, culminating in the existence of a maximal orthonormal subset, is
adapted from the corresponding development of the theory of linearly independents sets. See
`exists_linearIndependent` in particular. -/
variable (𝕜 E)
theorem orthonormal_empty : Orthonormal 𝕜 (fun x => x : (∅ : Set E) → E) := by
classical
simp [orthonormal_subtype_iff_ite]
#align orthonormal_empty orthonormal_empty
variable {𝕜 E}
theorem orthonormal_iUnion_of_directed {η : Type*} {s : η → Set E} (hs : Directed (· ⊆ ·) s)
(h : ∀ i, Orthonormal 𝕜 (fun x => x : s i → E)) :
Orthonormal 𝕜 (fun x => x : (⋃ i, s i) → E) := by
classical
rw [orthonormal_subtype_iff_ite]
rintro x ⟨_, ⟨i, rfl⟩, hxi⟩ y ⟨_, ⟨j, rfl⟩, hyj⟩
obtain ⟨k, hik, hjk⟩ := hs i j
have h_orth : Orthonormal 𝕜 (fun x => x : s k → E) := h k
rw [orthonormal_subtype_iff_ite] at h_orth
exact h_orth x (hik hxi) y (hjk hyj)
#align orthonormal_Union_of_directed orthonormal_iUnion_of_directed
theorem orthonormal_sUnion_of_directed {s : Set (Set E)} (hs : DirectedOn (· ⊆ ·) s)
(h : ∀ a ∈ s, Orthonormal 𝕜 (fun x => ((x : a) : E))) :
Orthonormal 𝕜 (fun x => x : ⋃₀ s → E) := by
rw [Set.sUnion_eq_iUnion]; exact orthonormal_iUnion_of_directed hs.directed_val (by simpa using h)
#align orthonormal_sUnion_of_directed orthonormal_sUnion_of_directed
/-- Given an orthonormal set `v` of vectors in `E`, there exists a maximal orthonormal set
containing it. -/
theorem exists_maximal_orthonormal {s : Set E} (hs : Orthonormal 𝕜 (Subtype.val : s → E)) :
∃ w ⊇ s, Orthonormal 𝕜 (Subtype.val : w → E) ∧
∀ u ⊇ w, Orthonormal 𝕜 (Subtype.val : u → E) → u = w := by
have := zorn_subset_nonempty { b | Orthonormal 𝕜 (Subtype.val : b → E) } ?_ _ hs
· obtain ⟨b, bi, sb, h⟩ := this
refine ⟨b, sb, bi, ?_⟩
exact fun u hus hu => h u hu hus
· refine fun c hc cc _c0 => ⟨⋃₀ c, ?_, ?_⟩
· exact orthonormal_sUnion_of_directed cc.directedOn fun x xc => hc xc
· exact fun _ => Set.subset_sUnion_of_mem
#align exists_maximal_orthonormal exists_maximal_orthonormal
theorem Orthonormal.ne_zero {v : ι → E} (hv : Orthonormal 𝕜 v) (i : ι) : v i ≠ 0 := by
have : ‖v i‖ ≠ 0 := by
rw [hv.1 i]
norm_num
simpa using this
#align orthonormal.ne_zero Orthonormal.ne_zero
open FiniteDimensional
/-- A family of orthonormal vectors with the correct cardinality forms a basis. -/
def basisOfOrthonormalOfCardEqFinrank [Fintype ι] [Nonempty ι] {v : ι → E} (hv : Orthonormal 𝕜 v)
(card_eq : Fintype.card ι = finrank 𝕜 E) : Basis ι 𝕜 E :=
basisOfLinearIndependentOfCardEqFinrank hv.linearIndependent card_eq
#align basis_of_orthonormal_of_card_eq_finrank basisOfOrthonormalOfCardEqFinrank
@[simp]
theorem coe_basisOfOrthonormalOfCardEqFinrank [Fintype ι] [Nonempty ι] {v : ι → E}
(hv : Orthonormal 𝕜 v) (card_eq : Fintype.card ι = finrank 𝕜 E) :
(basisOfOrthonormalOfCardEqFinrank hv card_eq : ι → E) = v :=
coe_basisOfLinearIndependentOfCardEqFinrank _ _
#align coe_basis_of_orthonormal_of_card_eq_finrank coe_basisOfOrthonormalOfCardEqFinrank
end OrthonormalSets
section Norm
theorem norm_eq_sqrt_inner (x : E) : ‖x‖ = √(re ⟪x, x⟫) :=
calc
‖x‖ = √(‖x‖ ^ 2) := (sqrt_sq (norm_nonneg _)).symm
_ = √(re ⟪x, x⟫) := congr_arg _ (norm_sq_eq_inner _)
#align norm_eq_sqrt_inner norm_eq_sqrt_inner
theorem norm_eq_sqrt_real_inner (x : F) : ‖x‖ = √⟪x, x⟫_ℝ :=
@norm_eq_sqrt_inner ℝ _ _ _ _ x
#align norm_eq_sqrt_real_inner norm_eq_sqrt_real_inner
theorem inner_self_eq_norm_mul_norm (x : E) : re ⟪x, x⟫ = ‖x‖ * ‖x‖ := by
rw [@norm_eq_sqrt_inner 𝕜, ← sqrt_mul inner_self_nonneg (re ⟪x, x⟫),
sqrt_mul_self inner_self_nonneg]
#align inner_self_eq_norm_mul_norm inner_self_eq_norm_mul_norm
theorem inner_self_eq_norm_sq (x : E) : re ⟪x, x⟫ = ‖x‖ ^ 2 := by
rw [pow_two, inner_self_eq_norm_mul_norm]
#align inner_self_eq_norm_sq inner_self_eq_norm_sq
theorem real_inner_self_eq_norm_mul_norm (x : F) : ⟪x, x⟫_ℝ = ‖x‖ * ‖x‖ := by
have h := @inner_self_eq_norm_mul_norm ℝ F _ _ _ x
simpa using h
#align real_inner_self_eq_norm_mul_norm real_inner_self_eq_norm_mul_norm
theorem real_inner_self_eq_norm_sq (x : F) : ⟪x, x⟫_ℝ = ‖x‖ ^ 2 := by
rw [pow_two, real_inner_self_eq_norm_mul_norm]
#align real_inner_self_eq_norm_sq real_inner_self_eq_norm_sq
-- Porting note: this was present in mathlib3 but seemingly didn't do anything.
-- variable (𝕜)
/-- Expand the square -/
theorem norm_add_sq (x y : E) : ‖x + y‖ ^ 2 = ‖x‖ ^ 2 + 2 * re ⟪x, y⟫ + ‖y‖ ^ 2 := by
repeat' rw [sq (M := ℝ), ← @inner_self_eq_norm_mul_norm 𝕜]
rw [inner_add_add_self, two_mul]
simp only [add_assoc, add_left_inj, add_right_inj, AddMonoidHom.map_add]
rw [← inner_conj_symm, conj_re]
#align norm_add_sq norm_add_sq
alias norm_add_pow_two := norm_add_sq
#align norm_add_pow_two norm_add_pow_two
/-- Expand the square -/
theorem norm_add_sq_real (x y : F) : ‖x + y‖ ^ 2 = ‖x‖ ^ 2 + 2 * ⟪x, y⟫_ℝ + ‖y‖ ^ 2 := by
have h := @norm_add_sq ℝ _ _ _ _ x y
simpa using h
#align norm_add_sq_real norm_add_sq_real
alias norm_add_pow_two_real := norm_add_sq_real
#align norm_add_pow_two_real norm_add_pow_two_real
/-- Expand the square -/
theorem norm_add_mul_self (x y : E) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + 2 * re ⟪x, y⟫ + ‖y‖ * ‖y‖ := by
repeat' rw [← sq (M := ℝ)]
exact norm_add_sq _ _
#align norm_add_mul_self norm_add_mul_self
/-- Expand the square -/
theorem norm_add_mul_self_real (x y : F) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + 2 * ⟪x, y⟫_ℝ + ‖y‖ * ‖y‖ := by
have h := @norm_add_mul_self ℝ _ _ _ _ x y
simpa using h
#align norm_add_mul_self_real norm_add_mul_self_real
/-- Expand the square -/
theorem norm_sub_sq (x y : E) : ‖x - y‖ ^ 2 = ‖x‖ ^ 2 - 2 * re ⟪x, y⟫ + ‖y‖ ^ 2 := by
rw [sub_eq_add_neg, @norm_add_sq 𝕜 _ _ _ _ x (-y), norm_neg, inner_neg_right, map_neg, mul_neg,
sub_eq_add_neg]
#align norm_sub_sq norm_sub_sq
alias norm_sub_pow_two := norm_sub_sq
#align norm_sub_pow_two norm_sub_pow_two
/-- Expand the square -/
theorem norm_sub_sq_real (x y : F) : ‖x - y‖ ^ 2 = ‖x‖ ^ 2 - 2 * ⟪x, y⟫_ℝ + ‖y‖ ^ 2 :=
@norm_sub_sq ℝ _ _ _ _ _ _
#align norm_sub_sq_real norm_sub_sq_real
alias norm_sub_pow_two_real := norm_sub_sq_real
#align norm_sub_pow_two_real norm_sub_pow_two_real
/-- Expand the square -/
theorem norm_sub_mul_self (x y : E) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ - 2 * re ⟪x, y⟫ + ‖y‖ * ‖y‖ := by
repeat' rw [← sq (M := ℝ)]
exact norm_sub_sq _ _
#align norm_sub_mul_self norm_sub_mul_self
/-- Expand the square -/
theorem norm_sub_mul_self_real (x y : F) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ - 2 * ⟪x, y⟫_ℝ + ‖y‖ * ‖y‖ := by
have h := @norm_sub_mul_self ℝ _ _ _ _ x y
simpa using h
#align norm_sub_mul_self_real norm_sub_mul_self_real
/-- Cauchy–Schwarz inequality with norm -/
theorem norm_inner_le_norm (x y : E) : ‖⟪x, y⟫‖ ≤ ‖x‖ * ‖y‖ := by
rw [norm_eq_sqrt_inner (𝕜 := 𝕜) x, norm_eq_sqrt_inner (𝕜 := 𝕜) y]
letI : InnerProductSpace.Core 𝕜 E := InnerProductSpace.toCore
exact InnerProductSpace.Core.norm_inner_le_norm x y
#align norm_inner_le_norm norm_inner_le_norm
theorem nnnorm_inner_le_nnnorm (x y : E) : ‖⟪x, y⟫‖₊ ≤ ‖x‖₊ * ‖y‖₊ :=
norm_inner_le_norm x y
#align nnnorm_inner_le_nnnorm nnnorm_inner_le_nnnorm
theorem re_inner_le_norm (x y : E) : re ⟪x, y⟫ ≤ ‖x‖ * ‖y‖ :=
le_trans (re_le_norm (inner x y)) (norm_inner_le_norm x y)
#align re_inner_le_norm re_inner_le_norm
/-- Cauchy–Schwarz inequality with norm -/
theorem abs_real_inner_le_norm (x y : F) : |⟪x, y⟫_ℝ| ≤ ‖x‖ * ‖y‖ :=
(Real.norm_eq_abs _).ge.trans (norm_inner_le_norm x y)
#align abs_real_inner_le_norm abs_real_inner_le_norm
/-- Cauchy–Schwarz inequality with norm -/
theorem real_inner_le_norm (x y : F) : ⟪x, y⟫_ℝ ≤ ‖x‖ * ‖y‖ :=
le_trans (le_abs_self _) (abs_real_inner_le_norm _ _)
#align real_inner_le_norm real_inner_le_norm
variable (𝕜)
theorem parallelogram_law_with_norm (x y : E) :
‖x + y‖ * ‖x + y‖ + ‖x - y‖ * ‖x - y‖ = 2 * (‖x‖ * ‖x‖ + ‖y‖ * ‖y‖) := by
simp only [← @inner_self_eq_norm_mul_norm 𝕜]
rw [← re.map_add, parallelogram_law, two_mul, two_mul]
simp only [re.map_add]
#align parallelogram_law_with_norm parallelogram_law_with_norm
theorem parallelogram_law_with_nnnorm (x y : E) :
‖x + y‖₊ * ‖x + y‖₊ + ‖x - y‖₊ * ‖x - y‖₊ = 2 * (‖x‖₊ * ‖x‖₊ + ‖y‖₊ * ‖y‖₊) :=
Subtype.ext <| parallelogram_law_with_norm 𝕜 x y
#align parallelogram_law_with_nnnorm parallelogram_law_with_nnnorm
variable {𝕜}
/-- Polarization identity: The real part of the inner product, in terms of the norm. -/
theorem re_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two (x y : E) :
re ⟪x, y⟫ = (‖x + y‖ * ‖x + y‖ - ‖x‖ * ‖x‖ - ‖y‖ * ‖y‖) / 2 := by
rw [@norm_add_mul_self 𝕜]
ring
#align re_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two re_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two
/-- Polarization identity: The real part of the inner product, in terms of the norm. -/
theorem re_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two (x y : E) :
re ⟪x, y⟫ = (‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ - ‖x - y‖ * ‖x - y‖) / 2 := by
rw [@norm_sub_mul_self 𝕜]
ring
#align re_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two re_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two
/-- Polarization identity: The real part of the inner product, in terms of the norm. -/
theorem re_inner_eq_norm_add_mul_self_sub_norm_sub_mul_self_div_four (x y : E) :
re ⟪x, y⟫ = (‖x + y‖ * ‖x + y‖ - ‖x - y‖ * ‖x - y‖) / 4 := by
rw [@norm_add_mul_self 𝕜, @norm_sub_mul_self 𝕜]
ring
#align re_inner_eq_norm_add_mul_self_sub_norm_sub_mul_self_div_four re_inner_eq_norm_add_mul_self_sub_norm_sub_mul_self_div_four
/-- Polarization identity: The imaginary part of the inner product, in terms of the norm. -/
theorem im_inner_eq_norm_sub_i_smul_mul_self_sub_norm_add_i_smul_mul_self_div_four (x y : E) :
im ⟪x, y⟫ = (‖x - IK • y‖ * ‖x - IK • y‖ - ‖x + IK • y‖ * ‖x + IK • y‖) / 4 := by
simp only [@norm_add_mul_self 𝕜, @norm_sub_mul_self 𝕜, inner_smul_right, I_mul_re]
ring
set_option linter.uppercaseLean3 false in
#align im_inner_eq_norm_sub_I_smul_mul_self_sub_norm_add_I_smul_mul_self_div_four im_inner_eq_norm_sub_i_smul_mul_self_sub_norm_add_i_smul_mul_self_div_four
/-- Polarization identity: The inner product, in terms of the norm. -/
theorem inner_eq_sum_norm_sq_div_four (x y : E) :
⟪x, y⟫ = ((‖x + y‖ : 𝕜) ^ 2 - (‖x - y‖ : 𝕜) ^ 2 +
((‖x - IK • y‖ : 𝕜) ^ 2 - (‖x + IK • y‖ : 𝕜) ^ 2) * IK) / 4 := by
rw [← re_add_im ⟪x, y⟫, re_inner_eq_norm_add_mul_self_sub_norm_sub_mul_self_div_four,
im_inner_eq_norm_sub_i_smul_mul_self_sub_norm_add_i_smul_mul_self_div_four]
push_cast
simp only [sq, ← mul_div_right_comm, ← add_div]
#align inner_eq_sum_norm_sq_div_four inner_eq_sum_norm_sq_div_four
/-- Formula for the distance between the images of two nonzero points under an inversion with center
zero. See also `EuclideanGeometry.dist_inversion_inversion` for inversions around a general
point. -/
theorem dist_div_norm_sq_smul {x y : F} (hx : x ≠ 0) (hy : y ≠ 0) (R : ℝ) :
dist ((R / ‖x‖) ^ 2 • x) ((R / ‖y‖) ^ 2 • y) = R ^ 2 / (‖x‖ * ‖y‖) * dist x y :=
have hx' : ‖x‖ ≠ 0 := norm_ne_zero_iff.2 hx
have hy' : ‖y‖ ≠ 0 := norm_ne_zero_iff.2 hy
calc
dist ((R / ‖x‖) ^ 2 • x) ((R / ‖y‖) ^ 2 • y) =
√(‖(R / ‖x‖) ^ 2 • x - (R / ‖y‖) ^ 2 • y‖ ^ 2) := by
rw [dist_eq_norm, sqrt_sq (norm_nonneg _)]
_ = √((R ^ 2 / (‖x‖ * ‖y‖)) ^ 2 * ‖x - y‖ ^ 2) :=
congr_arg sqrt <| by
field_simp [sq, norm_sub_mul_self_real, norm_smul, real_inner_smul_left, inner_smul_right,
Real.norm_of_nonneg (mul_self_nonneg _)]
ring
_ = R ^ 2 / (‖x‖ * ‖y‖) * dist x y := by
rw [sqrt_mul, sqrt_sq, sqrt_sq, dist_eq_norm] <;> positivity
#align dist_div_norm_sq_smul dist_div_norm_sq_smul
-- See note [lower instance priority]
instance (priority := 100) InnerProductSpace.toUniformConvexSpace : UniformConvexSpace F :=
⟨fun ε hε => by
refine
⟨2 - √(4 - ε ^ 2), sub_pos_of_lt <| (sqrt_lt' zero_lt_two).2 ?_, fun x hx y hy hxy => ?_⟩
· norm_num
exact pow_pos hε _
rw [sub_sub_cancel]
refine le_sqrt_of_sq_le ?_
rw [sq, eq_sub_iff_add_eq.2 (parallelogram_law_with_norm ℝ x y), ← sq ‖x - y‖, hx, hy]
ring_nf
exact sub_le_sub_left (pow_le_pow_left hε.le hxy _) 4⟩
#align inner_product_space.to_uniform_convex_space InnerProductSpace.toUniformConvexSpace
section Complex
variable {V : Type*} [NormedAddCommGroup V] [InnerProductSpace ℂ V]
/-- A complex polarization identity, with a linear map
-/
theorem inner_map_polarization (T : V →ₗ[ℂ] V) (x y : V) :
⟪T y, x⟫_ℂ =
(⟪T (x + y), x + y⟫_ℂ - ⟪T (x - y), x - y⟫_ℂ +
Complex.I * ⟪T (x + Complex.I • y), x + Complex.I • y⟫_ℂ -
Complex.I * ⟪T (x - Complex.I • y), x - Complex.I • y⟫_ℂ) /
4 := by
simp only [map_add, map_sub, inner_add_left, inner_add_right, LinearMap.map_smul, inner_smul_left,
inner_smul_right, Complex.conj_I, ← pow_two, Complex.I_sq, inner_sub_left, inner_sub_right,
mul_add, ← mul_assoc, mul_neg, neg_neg, sub_neg_eq_add, one_mul, neg_one_mul, mul_sub, sub_sub]
ring
#align inner_map_polarization inner_map_polarization
theorem inner_map_polarization' (T : V →ₗ[ℂ] V) (x y : V) :
⟪T x, y⟫_ℂ =
(⟪T (x + y), x + y⟫_ℂ - ⟪T (x - y), x - y⟫_ℂ -
Complex.I * ⟪T (x + Complex.I • y), x + Complex.I • y⟫_ℂ +
Complex.I * ⟪T (x - Complex.I • y), x - Complex.I • y⟫_ℂ) /
4 := by
simp only [map_add, map_sub, inner_add_left, inner_add_right, LinearMap.map_smul, inner_smul_left,
inner_smul_right, Complex.conj_I, ← pow_two, Complex.I_sq, inner_sub_left, inner_sub_right,
mul_add, ← mul_assoc, mul_neg, neg_neg, sub_neg_eq_add, one_mul, neg_one_mul, mul_sub, sub_sub]
ring
#align inner_map_polarization' inner_map_polarization'
/-- A linear map `T` is zero, if and only if the identity `⟪T x, x⟫_ℂ = 0` holds for all `x`.
-/
theorem inner_map_self_eq_zero (T : V →ₗ[ℂ] V) : (∀ x : V, ⟪T x, x⟫_ℂ = 0) ↔ T = 0 := by
constructor
· intro hT
ext x
rw [LinearMap.zero_apply, ← @inner_self_eq_zero ℂ V, inner_map_polarization]
simp only [hT]
norm_num
· rintro rfl x
simp only [LinearMap.zero_apply, inner_zero_left]
#align inner_map_self_eq_zero inner_map_self_eq_zero
/--
Two linear maps `S` and `T` are equal, if and only if the identity `⟪S x, x⟫_ℂ = ⟪T x, x⟫_ℂ` holds
for all `x`.
-/
theorem ext_inner_map (S T : V →ₗ[ℂ] V) : (∀ x : V, ⟪S x, x⟫_ℂ = ⟪T x, x⟫_ℂ) ↔ S = T := by
rw [← sub_eq_zero, ← inner_map_self_eq_zero]
refine forall_congr' fun x => ?_
rw [LinearMap.sub_apply, inner_sub_left, sub_eq_zero]
#align ext_inner_map ext_inner_map
end Complex
section
variable {ι : Type*} {ι' : Type*} {ι'' : Type*}
variable {E' : Type*} [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E']
variable {E'' : Type*} [NormedAddCommGroup E''] [InnerProductSpace 𝕜 E'']
/-- A linear isometry preserves the inner product. -/
@[simp]
theorem LinearIsometry.inner_map_map (f : E →ₗᵢ[𝕜] E') (x y : E) : ⟪f x, f y⟫ = ⟪x, y⟫ := by
simp [inner_eq_sum_norm_sq_div_four, ← f.norm_map]
#align linear_isometry.inner_map_map LinearIsometry.inner_map_map
/-- A linear isometric equivalence preserves the inner product. -/
@[simp]
theorem LinearIsometryEquiv.inner_map_map (f : E ≃ₗᵢ[𝕜] E') (x y : E) : ⟪f x, f y⟫ = ⟪x, y⟫ :=
f.toLinearIsometry.inner_map_map x y
#align linear_isometry_equiv.inner_map_map LinearIsometryEquiv.inner_map_map
/-- The adjoint of a linear isometric equivalence is its inverse. -/
theorem LinearIsometryEquiv.inner_map_eq_flip (f : E ≃ₗᵢ[𝕜] E') (x : E) (y : E') :
⟪f x, y⟫_𝕜 = ⟪x, f.symm y⟫_𝕜 := by
conv_lhs => rw [← f.apply_symm_apply y, f.inner_map_map]
/-- A linear map that preserves the inner product is a linear isometry. -/
def LinearMap.isometryOfInner (f : E →ₗ[𝕜] E') (h : ∀ x y, ⟪f x, f y⟫ = ⟪x, y⟫) : E →ₗᵢ[𝕜] E' :=
⟨f, fun x => by simp only [@norm_eq_sqrt_inner 𝕜, h]⟩
#align linear_map.isometry_of_inner LinearMap.isometryOfInner
@[simp]
theorem LinearMap.coe_isometryOfInner (f : E →ₗ[𝕜] E') (h) : ⇑(f.isometryOfInner h) = f :=
rfl
#align linear_map.coe_isometry_of_inner LinearMap.coe_isometryOfInner
@[simp]
theorem LinearMap.isometryOfInner_toLinearMap (f : E →ₗ[𝕜] E') (h) :
(f.isometryOfInner h).toLinearMap = f :=
rfl
#align linear_map.isometry_of_inner_to_linear_map LinearMap.isometryOfInner_toLinearMap
/-- A linear equivalence that preserves the inner product is a linear isometric equivalence. -/
def LinearEquiv.isometryOfInner (f : E ≃ₗ[𝕜] E') (h : ∀ x y, ⟪f x, f y⟫ = ⟪x, y⟫) : E ≃ₗᵢ[𝕜] E' :=
⟨f, ((f : E →ₗ[𝕜] E').isometryOfInner h).norm_map⟩
#align linear_equiv.isometry_of_inner LinearEquiv.isometryOfInner
@[simp]
theorem LinearEquiv.coe_isometryOfInner (f : E ≃ₗ[𝕜] E') (h) : ⇑(f.isometryOfInner h) = f :=
rfl
#align linear_equiv.coe_isometry_of_inner LinearEquiv.coe_isometryOfInner
@[simp]
theorem LinearEquiv.isometryOfInner_toLinearEquiv (f : E ≃ₗ[𝕜] E') (h) :
(f.isometryOfInner h).toLinearEquiv = f :=
rfl
#align linear_equiv.isometry_of_inner_to_linear_equiv LinearEquiv.isometryOfInner_toLinearEquiv
/-- A linear map is an isometry if and it preserves the inner product. -/
theorem LinearMap.norm_map_iff_inner_map_map {F : Type*} [FunLike F E E'] [LinearMapClass F 𝕜 E E']
(f : F) : (∀ x, ‖f x‖ = ‖x‖) ↔ (∀ x y, ⟪f x, f y⟫_𝕜 = ⟪x, y⟫_𝕜) :=
⟨({ toLinearMap := LinearMapClass.linearMap f, norm_map' := · : E →ₗᵢ[𝕜] E' }.inner_map_map),
(LinearMapClass.linearMap f |>.isometryOfInner · |>.norm_map)⟩
/-- A linear isometry preserves the property of being orthonormal. -/
theorem LinearIsometry.orthonormal_comp_iff {v : ι → E} (f : E →ₗᵢ[𝕜] E') :
Orthonormal 𝕜 (f ∘ v) ↔ Orthonormal 𝕜 v := by
classical simp_rw [orthonormal_iff_ite, Function.comp_apply, LinearIsometry.inner_map_map]
#align linear_isometry.orthonormal_comp_iff LinearIsometry.orthonormal_comp_iff
/-- A linear isometry preserves the property of being orthonormal. -/
theorem Orthonormal.comp_linearIsometry {v : ι → E} (hv : Orthonormal 𝕜 v) (f : E →ₗᵢ[𝕜] E') :
Orthonormal 𝕜 (f ∘ v) := by rwa [f.orthonormal_comp_iff]
#align orthonormal.comp_linear_isometry Orthonormal.comp_linearIsometry
/-- A linear isometric equivalence preserves the property of being orthonormal. -/
theorem Orthonormal.comp_linearIsometryEquiv {v : ι → E} (hv : Orthonormal 𝕜 v) (f : E ≃ₗᵢ[𝕜] E') :
Orthonormal 𝕜 (f ∘ v) :=
hv.comp_linearIsometry f.toLinearIsometry
#align orthonormal.comp_linear_isometry_equiv Orthonormal.comp_linearIsometryEquiv
/-- A linear isometric equivalence, applied with `Basis.map`, preserves the property of being
orthonormal. -/
theorem Orthonormal.mapLinearIsometryEquiv {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v)
(f : E ≃ₗᵢ[𝕜] E') : Orthonormal 𝕜 (v.map f.toLinearEquiv) :=
hv.comp_linearIsometryEquiv f
#align orthonormal.map_linear_isometry_equiv Orthonormal.mapLinearIsometryEquiv
/-- A linear map that sends an orthonormal basis to orthonormal vectors is a linear isometry. -/
def LinearMap.isometryOfOrthonormal (f : E →ₗ[𝕜] E') {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v)
(hf : Orthonormal 𝕜 (f ∘ v)) : E →ₗᵢ[𝕜] E' :=
f.isometryOfInner fun x y => by
classical rw [← v.total_repr x, ← v.total_repr y, Finsupp.apply_total, Finsupp.apply_total,
hv.inner_finsupp_eq_sum_left, hf.inner_finsupp_eq_sum_left]
#align linear_map.isometry_of_orthonormal LinearMap.isometryOfOrthonormal
@[simp]
theorem LinearMap.coe_isometryOfOrthonormal (f : E →ₗ[𝕜] E') {v : Basis ι 𝕜 E}
(hv : Orthonormal 𝕜 v) (hf : Orthonormal 𝕜 (f ∘ v)) : ⇑(f.isometryOfOrthonormal hv hf) = f :=
rfl
#align linear_map.coe_isometry_of_orthonormal LinearMap.coe_isometryOfOrthonormal
@[simp]
theorem LinearMap.isometryOfOrthonormal_toLinearMap (f : E →ₗ[𝕜] E') {v : Basis ι 𝕜 E}
(hv : Orthonormal 𝕜 v) (hf : Orthonormal 𝕜 (f ∘ v)) :
(f.isometryOfOrthonormal hv hf).toLinearMap = f :=
rfl
#align linear_map.isometry_of_orthonormal_to_linear_map LinearMap.isometryOfOrthonormal_toLinearMap
/-- A linear equivalence that sends an orthonormal basis to orthonormal vectors is a linear
isometric equivalence. -/
def LinearEquiv.isometryOfOrthonormal (f : E ≃ₗ[𝕜] E') {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v)
(hf : Orthonormal 𝕜 (f ∘ v)) : E ≃ₗᵢ[𝕜] E' :=
f.isometryOfInner fun x y => by
rw [← LinearEquiv.coe_coe] at hf
classical rw [← v.total_repr x, ← v.total_repr y, ← LinearEquiv.coe_coe f, Finsupp.apply_total,
Finsupp.apply_total, hv.inner_finsupp_eq_sum_left, hf.inner_finsupp_eq_sum_left]
#align linear_equiv.isometry_of_orthonormal LinearEquiv.isometryOfOrthonormal
@[simp]
theorem LinearEquiv.coe_isometryOfOrthonormal (f : E ≃ₗ[𝕜] E') {v : Basis ι 𝕜 E}
(hv : Orthonormal 𝕜 v) (hf : Orthonormal 𝕜 (f ∘ v)) : ⇑(f.isometryOfOrthonormal hv hf) = f :=
rfl
#align linear_equiv.coe_isometry_of_orthonormal LinearEquiv.coe_isometryOfOrthonormal
@[simp]
theorem LinearEquiv.isometryOfOrthonormal_toLinearEquiv (f : E ≃ₗ[𝕜] E') {v : Basis ι 𝕜 E}
(hv : Orthonormal 𝕜 v) (hf : Orthonormal 𝕜 (f ∘ v)) :
(f.isometryOfOrthonormal hv hf).toLinearEquiv = f :=
rfl
#align linear_equiv.isometry_of_orthonormal_to_linear_equiv LinearEquiv.isometryOfOrthonormal_toLinearEquiv
/-- A linear isometric equivalence that sends an orthonormal basis to a given orthonormal basis. -/
def Orthonormal.equiv {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v) {v' : Basis ι' 𝕜 E'}
(hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') : E ≃ₗᵢ[𝕜] E' :=
(v.equiv v' e).isometryOfOrthonormal hv
(by
have h : v.equiv v' e ∘ v = v' ∘ e := by
ext i
simp
rw [h]
classical exact hv'.comp _ e.injective)
#align orthonormal.equiv Orthonormal.equiv
@[simp]
theorem Orthonormal.equiv_toLinearEquiv {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v)
{v' : Basis ι' 𝕜 E'} (hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') :
(hv.equiv hv' e).toLinearEquiv = v.equiv v' e :=
rfl
#align orthonormal.equiv_to_linear_equiv Orthonormal.equiv_toLinearEquiv
@[simp]
theorem Orthonormal.equiv_apply {ι' : Type*} {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v)
{v' : Basis ι' 𝕜 E'} (hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') (i : ι) :
hv.equiv hv' e (v i) = v' (e i) :=
Basis.equiv_apply _ _ _ _
#align orthonormal.equiv_apply Orthonormal.equiv_apply
@[simp]
theorem Orthonormal.equiv_refl {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v) :
hv.equiv hv (Equiv.refl ι) = LinearIsometryEquiv.refl 𝕜 E :=
v.ext_linearIsometryEquiv fun i => by
simp only [Orthonormal.equiv_apply, Equiv.coe_refl, id, LinearIsometryEquiv.coe_refl]
#align orthonormal.equiv_refl Orthonormal.equiv_refl
@[simp]
theorem Orthonormal.equiv_symm {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v) {v' : Basis ι' 𝕜 E'}
(hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') : (hv.equiv hv' e).symm = hv'.equiv hv e.symm :=
v'.ext_linearIsometryEquiv fun i =>
(hv.equiv hv' e).injective <| by
simp only [LinearIsometryEquiv.apply_symm_apply, Orthonormal.equiv_apply, e.apply_symm_apply]
#align orthonormal.equiv_symm Orthonormal.equiv_symm
@[simp]
theorem Orthonormal.equiv_trans {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v) {v' : Basis ι' 𝕜 E'}
(hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') {v'' : Basis ι'' 𝕜 E''} (hv'' : Orthonormal 𝕜 v'')
(e' : ι' ≃ ι'') : (hv.equiv hv' e).trans (hv'.equiv hv'' e') = hv.equiv hv'' (e.trans e') :=
v.ext_linearIsometryEquiv fun i => by
simp only [LinearIsometryEquiv.trans_apply, Orthonormal.equiv_apply, e.coe_trans,
Function.comp_apply]
#align orthonormal.equiv_trans Orthonormal.equiv_trans
theorem Orthonormal.map_equiv {v : Basis ι 𝕜 E} (hv : Orthonormal 𝕜 v) {v' : Basis ι' 𝕜 E'}
(hv' : Orthonormal 𝕜 v') (e : ι ≃ ι') :
v.map (hv.equiv hv' e).toLinearEquiv = v'.reindex e.symm :=
v.map_equiv _ _
#align orthonormal.map_equiv Orthonormal.map_equiv
end
/-- Polarization identity: The real inner product, in terms of the norm. -/
theorem real_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two (x y : F) :
⟪x, y⟫_ℝ = (‖x + y‖ * ‖x + y‖ - ‖x‖ * ‖x‖ - ‖y‖ * ‖y‖) / 2 :=
re_to_real.symm.trans <|
re_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two x y
#align real_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two real_inner_eq_norm_add_mul_self_sub_norm_mul_self_sub_norm_mul_self_div_two
/-- Polarization identity: The real inner product, in terms of the norm. -/
theorem real_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two (x y : F) :
⟪x, y⟫_ℝ = (‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ - ‖x - y‖ * ‖x - y‖) / 2 :=
re_to_real.symm.trans <|
re_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two x y
#align real_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two real_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two
/-- Pythagorean theorem, if-and-only-if vector inner product form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero (x y : F) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ ↔ ⟪x, y⟫_ℝ = 0 := by
rw [@norm_add_mul_self ℝ, add_right_cancel_iff, add_right_eq_self, mul_eq_zero]
norm_num
#align norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero
/-- Pythagorean theorem, if-and-if vector inner product form using square roots. -/
theorem norm_add_eq_sqrt_iff_real_inner_eq_zero {x y : F} :
‖x + y‖ = √(‖x‖ * ‖x‖ + ‖y‖ * ‖y‖) ↔ ⟪x, y⟫_ℝ = 0 := by
rw [← norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero, eq_comm,
sqrt_eq_iff_mul_self_eq (add_nonneg (mul_self_nonneg _) (mul_self_nonneg _)) (norm_nonneg _)]
#align norm_add_eq_sqrt_iff_real_inner_eq_zero norm_add_eq_sqrt_iff_real_inner_eq_zero
/-- Pythagorean theorem, vector inner product form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero (x y : E) (h : ⟪x, y⟫ = 0) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ := by
rw [@norm_add_mul_self 𝕜, add_right_cancel_iff, add_right_eq_self, mul_eq_zero]
apply Or.inr
simp only [h, zero_re']
#align norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero norm_add_sq_eq_norm_sq_add_norm_sq_of_inner_eq_zero
/-- Pythagorean theorem, vector inner product form. -/
theorem norm_add_sq_eq_norm_sq_add_norm_sq_real {x y : F} (h : ⟪x, y⟫_ℝ = 0) :
‖x + y‖ * ‖x + y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ :=
(norm_add_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero x y).2 h
#align norm_add_sq_eq_norm_sq_add_norm_sq_real norm_add_sq_eq_norm_sq_add_norm_sq_real
/-- Pythagorean theorem, subtracting vectors, if-and-only-if vector
inner product form. -/
theorem norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero (x y : F) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ ↔ ⟪x, y⟫_ℝ = 0 := by
rw [@norm_sub_mul_self ℝ, add_right_cancel_iff, sub_eq_add_neg, add_right_eq_self, neg_eq_zero,
mul_eq_zero]
norm_num
#align norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero
/-- Pythagorean theorem, subtracting vectors, if-and-if vector inner product form using square
roots. -/
theorem norm_sub_eq_sqrt_iff_real_inner_eq_zero {x y : F} :
‖x - y‖ = √(‖x‖ * ‖x‖ + ‖y‖ * ‖y‖) ↔ ⟪x, y⟫_ℝ = 0 := by
rw [← norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero, eq_comm,
sqrt_eq_iff_mul_self_eq (add_nonneg (mul_self_nonneg _) (mul_self_nonneg _)) (norm_nonneg _)]
#align norm_sub_eq_sqrt_iff_real_inner_eq_zero norm_sub_eq_sqrt_iff_real_inner_eq_zero
/-- Pythagorean theorem, subtracting vectors, vector inner product
form. -/
theorem norm_sub_sq_eq_norm_sq_add_norm_sq_real {x y : F} (h : ⟪x, y⟫_ℝ = 0) :
‖x - y‖ * ‖x - y‖ = ‖x‖ * ‖x‖ + ‖y‖ * ‖y‖ :=
(norm_sub_sq_eq_norm_sq_add_norm_sq_iff_real_inner_eq_zero x y).2 h
#align norm_sub_sq_eq_norm_sq_add_norm_sq_real norm_sub_sq_eq_norm_sq_add_norm_sq_real
/-- The sum and difference of two vectors are orthogonal if and only
if they have the same norm. -/
theorem real_inner_add_sub_eq_zero_iff (x y : F) : ⟪x + y, x - y⟫_ℝ = 0 ↔ ‖x‖ = ‖y‖ := by
conv_rhs => rw [← mul_self_inj_of_nonneg (norm_nonneg _) (norm_nonneg _)]
simp only [← @inner_self_eq_norm_mul_norm ℝ, inner_add_left, inner_sub_right, real_inner_comm y x,
sub_eq_zero, re_to_real]
constructor
· intro h
rw [add_comm] at h
linarith
· intro h
linarith
#align real_inner_add_sub_eq_zero_iff real_inner_add_sub_eq_zero_iff
/-- Given two orthogonal vectors, their sum and difference have equal norms. -/
theorem norm_sub_eq_norm_add {v w : E} (h : ⟪v, w⟫ = 0) : ‖w - v‖ = ‖w + v‖ := by
rw [← mul_self_inj_of_nonneg (norm_nonneg _) (norm_nonneg _)]
simp only [h, ← @inner_self_eq_norm_mul_norm 𝕜, sub_neg_eq_add, sub_zero, map_sub, zero_re',
zero_sub, add_zero, map_add, inner_add_right, inner_sub_left, inner_sub_right, inner_re_symm,
zero_add]
#align norm_sub_eq_norm_add norm_sub_eq_norm_add
/-- The real inner product of two vectors, divided by the product of their
norms, has absolute value at most 1. -/
theorem abs_real_inner_div_norm_mul_norm_le_one (x y : F) : |⟪x, y⟫_ℝ / (‖x‖ * ‖y‖)| ≤ 1 := by
rw [abs_div, abs_mul, abs_norm, abs_norm]
exact div_le_one_of_le (abs_real_inner_le_norm x y) (by positivity)
#align abs_real_inner_div_norm_mul_norm_le_one abs_real_inner_div_norm_mul_norm_le_one
/-- The inner product of a vector with a multiple of itself. -/
theorem real_inner_smul_self_left (x : F) (r : ℝ) : ⟪r • x, x⟫_ℝ = r * (‖x‖ * ‖x‖) := by
rw [real_inner_smul_left, ← real_inner_self_eq_norm_mul_norm]
#align real_inner_smul_self_left real_inner_smul_self_left
/-- The inner product of a vector with a multiple of itself. -/
theorem real_inner_smul_self_right (x : F) (r : ℝ) : ⟪x, r • x⟫_ℝ = r * (‖x‖ * ‖x‖) := by
rw [inner_smul_right, ← real_inner_self_eq_norm_mul_norm]
#align real_inner_smul_self_right real_inner_smul_self_right
/-- The inner product of a nonzero vector with a nonzero multiple of
itself, divided by the product of their norms, has absolute value
1. -/
theorem norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul {x : E} {r : 𝕜} (hx : x ≠ 0)
(hr : r ≠ 0) : ‖⟪x, r • x⟫‖ / (‖x‖ * ‖r • x‖) = 1 := by
have hx' : ‖x‖ ≠ 0 := by simp [hx]
have hr' : ‖r‖ ≠ 0 := by simp [hr]
rw [inner_smul_right, norm_mul, ← inner_self_re_eq_norm, inner_self_eq_norm_mul_norm, norm_smul]
rw [← mul_assoc, ← div_div, mul_div_cancel_right₀ _ hx', ← div_div, mul_comm,
mul_div_cancel_right₀ _ hr', div_self hx']
#align norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul
/-- The inner product of a nonzero vector with a nonzero multiple of
itself, divided by the product of their norms, has absolute value
1. -/
theorem abs_real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul {x : F} {r : ℝ}
(hx : x ≠ 0) (hr : r ≠ 0) : |⟪x, r • x⟫_ℝ| / (‖x‖ * ‖r • x‖) = 1 :=
norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul hx hr
#align abs_real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul abs_real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul
/-- The inner product of a nonzero vector with a positive multiple of
itself, divided by the product of their norms, has value 1. -/
theorem real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_pos_mul {x : F} {r : ℝ} (hx : x ≠ 0)
(hr : 0 < r) : ⟪x, r • x⟫_ℝ / (‖x‖ * ‖r • x‖) = 1 := by
rw [real_inner_smul_self_right, norm_smul, Real.norm_eq_abs, ← mul_assoc ‖x‖, mul_comm _ |r|,
mul_assoc, abs_of_nonneg hr.le, div_self]
exact mul_ne_zero hr.ne' (mul_self_ne_zero.2 (norm_ne_zero_iff.2 hx))
#align real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_pos_mul real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_pos_mul
/-- The inner product of a nonzero vector with a negative multiple of
itself, divided by the product of their norms, has value -1. -/
theorem real_inner_div_norm_mul_norm_eq_neg_one_of_ne_zero_of_neg_mul {x : F} {r : ℝ} (hx : x ≠ 0)
(hr : r < 0) : ⟪x, r • x⟫_ℝ / (‖x‖ * ‖r • x‖) = -1 := by
rw [real_inner_smul_self_right, norm_smul, Real.norm_eq_abs, ← mul_assoc ‖x‖, mul_comm _ |r|,
mul_assoc, abs_of_neg hr, neg_mul, div_neg_eq_neg_div, div_self]
exact mul_ne_zero hr.ne (mul_self_ne_zero.2 (norm_ne_zero_iff.2 hx))
#align real_inner_div_norm_mul_norm_eq_neg_one_of_ne_zero_of_neg_mul real_inner_div_norm_mul_norm_eq_neg_one_of_ne_zero_of_neg_mul
theorem norm_inner_eq_norm_tfae (x y : E) :
List.TFAE [‖⟪x, y⟫‖ = ‖x‖ * ‖y‖,
x = 0 ∨ y = (⟪x, y⟫ / ⟪x, x⟫) • x,
x = 0 ∨ ∃ r : 𝕜, y = r • x,
x = 0 ∨ y ∈ 𝕜 ∙ x] := by
tfae_have 1 → 2
· refine fun h => or_iff_not_imp_left.2 fun hx₀ => ?_
have : ‖x‖ ^ 2 ≠ 0 := pow_ne_zero _ (norm_ne_zero_iff.2 hx₀)
rw [← sq_eq_sq, mul_pow, ← mul_right_inj' this, eq_comm, ← sub_eq_zero, ← mul_sub] at h <;>
try positivity
simp only [@norm_sq_eq_inner 𝕜] at h
letI : InnerProductSpace.Core 𝕜 E := InnerProductSpace.toCore
erw [← InnerProductSpace.Core.cauchy_schwarz_aux, InnerProductSpace.Core.normSq_eq_zero,
sub_eq_zero] at h
rw [div_eq_inv_mul, mul_smul, h, inv_smul_smul₀]
rwa [inner_self_ne_zero]
tfae_have 2 → 3
· exact fun h => h.imp_right fun h' => ⟨_, h'⟩
tfae_have 3 → 1
· rintro (rfl | ⟨r, rfl⟩) <;>
simp [inner_smul_right, norm_smul, inner_self_eq_norm_sq_to_K, inner_self_eq_norm_mul_norm,
sq, mul_left_comm]
tfae_have 3 ↔ 4; · simp only [Submodule.mem_span_singleton, eq_comm]
tfae_finish
#align norm_inner_eq_norm_tfae norm_inner_eq_norm_tfae
/-- If the inner product of two vectors is equal to the product of their norms, then the two vectors
are multiples of each other. One form of the equality case for Cauchy-Schwarz.
Compare `inner_eq_norm_mul_iff`, which takes the stronger hypothesis `⟪x, y⟫ = ‖x‖ * ‖y‖`. -/
theorem norm_inner_eq_norm_iff {x y : E} (hx₀ : x ≠ 0) (hy₀ : y ≠ 0) :
‖⟪x, y⟫‖ = ‖x‖ * ‖y‖ ↔ ∃ r : 𝕜, r ≠ 0 ∧ y = r • x :=
calc
‖⟪x, y⟫‖ = ‖x‖ * ‖y‖ ↔ x = 0 ∨ ∃ r : 𝕜, y = r • x :=
(@norm_inner_eq_norm_tfae 𝕜 _ _ _ _ x y).out 0 2
_ ↔ ∃ r : 𝕜, y = r • x := or_iff_right hx₀
_ ↔ ∃ r : 𝕜, r ≠ 0 ∧ y = r • x :=
⟨fun ⟨r, h⟩ => ⟨r, fun hr₀ => hy₀ <| h.symm ▸ smul_eq_zero.2 <| Or.inl hr₀, h⟩,
fun ⟨r, _hr₀, h⟩ => ⟨r, h⟩⟩
#align norm_inner_eq_norm_iff norm_inner_eq_norm_iff
/-- The inner product of two vectors, divided by the product of their
norms, has absolute value 1 if and only if they are nonzero and one is
a multiple of the other. One form of equality case for Cauchy-Schwarz. -/
theorem norm_inner_div_norm_mul_norm_eq_one_iff (x y : E) :
‖⟪x, y⟫ / (‖x‖ * ‖y‖)‖ = 1 ↔ x ≠ 0 ∧ ∃ r : 𝕜, r ≠ 0 ∧ y = r • x := by
constructor
· intro h
have hx₀ : x ≠ 0 := fun h₀ => by simp [h₀] at h
have hy₀ : y ≠ 0 := fun h₀ => by simp [h₀] at h
refine ⟨hx₀, (norm_inner_eq_norm_iff hx₀ hy₀).1 <| eq_of_div_eq_one ?_⟩
simpa using h
· rintro ⟨hx, ⟨r, ⟨hr, rfl⟩⟩⟩
simp only [norm_div, norm_mul, norm_ofReal, abs_norm]
exact norm_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_ne_zero_mul hx hr
#align norm_inner_div_norm_mul_norm_eq_one_iff norm_inner_div_norm_mul_norm_eq_one_iff
/-- The inner product of two vectors, divided by the product of their
norms, has absolute value 1 if and only if they are nonzero and one is
a multiple of the other. One form of equality case for Cauchy-Schwarz. -/
theorem abs_real_inner_div_norm_mul_norm_eq_one_iff (x y : F) :
|⟪x, y⟫_ℝ / (‖x‖ * ‖y‖)| = 1 ↔ x ≠ 0 ∧ ∃ r : ℝ, r ≠ 0 ∧ y = r • x :=
@norm_inner_div_norm_mul_norm_eq_one_iff ℝ F _ _ _ x y
#align abs_real_inner_div_norm_mul_norm_eq_one_iff abs_real_inner_div_norm_mul_norm_eq_one_iff
theorem inner_eq_norm_mul_iff_div {x y : E} (h₀ : x ≠ 0) :
⟪x, y⟫ = (‖x‖ : 𝕜) * ‖y‖ ↔ (‖y‖ / ‖x‖ : 𝕜) • x = y := by
have h₀' := h₀
rw [← norm_ne_zero_iff, Ne, ← @ofReal_eq_zero 𝕜] at h₀'
constructor <;> intro h
· have : x = 0 ∨ y = (⟪x, y⟫ / ⟪x, x⟫ : 𝕜) • x :=
((@norm_inner_eq_norm_tfae 𝕜 _ _ _ _ x y).out 0 1).1 (by simp [h])
rw [this.resolve_left h₀, h]
simp [norm_smul, inner_self_ofReal_norm, mul_div_cancel_right₀ _ h₀']
· conv_lhs => rw [← h, inner_smul_right, inner_self_eq_norm_sq_to_K]
field_simp [sq, mul_left_comm]
#align inner_eq_norm_mul_iff_div inner_eq_norm_mul_iff_div
/-- If the inner product of two vectors is equal to the product of their norms (i.e.,
`⟪x, y⟫ = ‖x‖ * ‖y‖`), then the two vectors are nonnegative real multiples of each other. One form
of the equality case for Cauchy-Schwarz.
Compare `norm_inner_eq_norm_iff`, which takes the weaker hypothesis `abs ⟪x, y⟫ = ‖x‖ * ‖y‖`. -/
theorem inner_eq_norm_mul_iff {x y : E} :
⟪x, y⟫ = (‖x‖ : 𝕜) * ‖y‖ ↔ (‖y‖ : 𝕜) • x = (‖x‖ : 𝕜) • y := by
rcases eq_or_ne x 0 with (rfl | h₀)
· simp
· rw [inner_eq_norm_mul_iff_div h₀, div_eq_inv_mul, mul_smul, inv_smul_eq_iff₀]
rwa [Ne, ofReal_eq_zero, norm_eq_zero]
#align inner_eq_norm_mul_iff inner_eq_norm_mul_iff
/-- If the inner product of two vectors is equal to the product of their norms (i.e.,
`⟪x, y⟫ = ‖x‖ * ‖y‖`), then the two vectors are nonnegative real multiples of each other. One form
of the equality case for Cauchy-Schwarz.
Compare `norm_inner_eq_norm_iff`, which takes the weaker hypothesis `abs ⟪x, y⟫ = ‖x‖ * ‖y‖`. -/
theorem inner_eq_norm_mul_iff_real {x y : F} : ⟪x, y⟫_ℝ = ‖x‖ * ‖y‖ ↔ ‖y‖ • x = ‖x‖ • y :=
inner_eq_norm_mul_iff
#align inner_eq_norm_mul_iff_real inner_eq_norm_mul_iff_real
/-- The inner product of two vectors, divided by the product of their
norms, has value 1 if and only if they are nonzero and one is
a positive multiple of the other. -/
theorem real_inner_div_norm_mul_norm_eq_one_iff (x y : F) :
⟪x, y⟫_ℝ / (‖x‖ * ‖y‖) = 1 ↔ x ≠ 0 ∧ ∃ r : ℝ, 0 < r ∧ y = r • x := by
constructor
· intro h
have hx₀ : x ≠ 0 := fun h₀ => by simp [h₀] at h
have hy₀ : y ≠ 0 := fun h₀ => by simp [h₀] at h
refine ⟨hx₀, ‖y‖ / ‖x‖, div_pos (norm_pos_iff.2 hy₀) (norm_pos_iff.2 hx₀), ?_⟩
exact ((inner_eq_norm_mul_iff_div hx₀).1 (eq_of_div_eq_one h)).symm
· rintro ⟨hx, ⟨r, ⟨hr, rfl⟩⟩⟩
exact real_inner_div_norm_mul_norm_eq_one_of_ne_zero_of_pos_mul hx hr
#align real_inner_div_norm_mul_norm_eq_one_iff real_inner_div_norm_mul_norm_eq_one_iff
/-- The inner product of two vectors, divided by the product of their
norms, has value -1 if and only if they are nonzero and one is
a negative multiple of the other. -/
theorem real_inner_div_norm_mul_norm_eq_neg_one_iff (x y : F) :
⟪x, y⟫_ℝ / (‖x‖ * ‖y‖) = -1 ↔ x ≠ 0 ∧ ∃ r : ℝ, r < 0 ∧ y = r • x := by
rw [← neg_eq_iff_eq_neg, ← neg_div, ← inner_neg_right, ← norm_neg y,
real_inner_div_norm_mul_norm_eq_one_iff, (@neg_surjective ℝ _).exists]
refine Iff.rfl.and (exists_congr fun r => ?_)
rw [neg_pos, neg_smul, neg_inj]
#align real_inner_div_norm_mul_norm_eq_neg_one_iff real_inner_div_norm_mul_norm_eq_neg_one_iff
/-- If the inner product of two unit vectors is `1`, then the two vectors are equal. One form of
the equality case for Cauchy-Schwarz. -/
theorem inner_eq_one_iff_of_norm_one {x y : E} (hx : ‖x‖ = 1) (hy : ‖y‖ = 1) :
⟪x, y⟫ = 1 ↔ x = y := by
convert inner_eq_norm_mul_iff (𝕜 := 𝕜) (E := E) using 2 <;> simp [hx, hy]
#align inner_eq_one_iff_of_norm_one inner_eq_one_iff_of_norm_one
theorem inner_lt_norm_mul_iff_real {x y : F} : ⟪x, y⟫_ℝ < ‖x‖ * ‖y‖ ↔ ‖y‖ • x ≠ ‖x‖ • y :=
calc
⟪x, y⟫_ℝ < ‖x‖ * ‖y‖ ↔ ⟪x, y⟫_ℝ ≠ ‖x‖ * ‖y‖ :=
⟨ne_of_lt, lt_of_le_of_ne (real_inner_le_norm _ _)⟩
_ ↔ ‖y‖ • x ≠ ‖x‖ • y := not_congr inner_eq_norm_mul_iff_real
#align inner_lt_norm_mul_iff_real inner_lt_norm_mul_iff_real
/-- If the inner product of two unit vectors is strictly less than `1`, then the two vectors are
distinct. One form of the equality case for Cauchy-Schwarz. -/
theorem inner_lt_one_iff_real_of_norm_one {x y : F} (hx : ‖x‖ = 1) (hy : ‖y‖ = 1) :
⟪x, y⟫_ℝ < 1 ↔ x ≠ y := by convert inner_lt_norm_mul_iff_real (F := F) <;> simp [hx, hy]
#align inner_lt_one_iff_real_of_norm_one inner_lt_one_iff_real_of_norm_one
/-- The sphere of radius `r = ‖y‖` is tangent to the plane `⟪x, y⟫ = ‖y‖ ^ 2` at `x = y`. -/
theorem eq_of_norm_le_re_inner_eq_norm_sq {x y : E} (hle : ‖x‖ ≤ ‖y‖) (h : re ⟪x, y⟫ = ‖y‖ ^ 2) :
x = y := by
suffices H : re ⟪x - y, x - y⟫ ≤ 0 by rwa [inner_self_nonpos, sub_eq_zero] at H
have H₁ : ‖x‖ ^ 2 ≤ ‖y‖ ^ 2 := by gcongr
have H₂ : re ⟪y, x⟫ = ‖y‖ ^ 2 := by rwa [← inner_conj_symm, conj_re]
simpa [inner_sub_left, inner_sub_right, ← norm_sq_eq_inner, h, H₂] using H₁
/-- The inner product of two weighted sums, where the weights in each
sum add to 0, in terms of the norms of pairwise differences. -/
theorem inner_sum_smul_sum_smul_of_sum_eq_zero {ι₁ : Type*} {s₁ : Finset ι₁} {w₁ : ι₁ → ℝ}
(v₁ : ι₁ → F) (h₁ : ∑ i ∈ s₁, w₁ i = 0) {ι₂ : Type*} {s₂ : Finset ι₂} {w₂ : ι₂ → ℝ}
(v₂ : ι₂ → F) (h₂ : ∑ i ∈ s₂, w₂ i = 0) :
⟪∑ i₁ ∈ s₁, w₁ i₁ • v₁ i₁, ∑ i₂ ∈ s₂, w₂ i₂ • v₂ i₂⟫_ℝ =
(-∑ i₁ ∈ s₁, ∑ i₂ ∈ s₂, w₁ i₁ * w₂ i₂ * (‖v₁ i₁ - v₂ i₂‖ * ‖v₁ i₁ - v₂ i₂‖)) / 2 := by
simp_rw [sum_inner, inner_sum, real_inner_smul_left, real_inner_smul_right,
real_inner_eq_norm_mul_self_add_norm_mul_self_sub_norm_sub_mul_self_div_two, ← div_sub_div_same,
← div_add_div_same, mul_sub_left_distrib, left_distrib, Finset.sum_sub_distrib,
Finset.sum_add_distrib, ← Finset.mul_sum, ← Finset.sum_mul, h₁, h₂, zero_mul,
mul_zero, Finset.sum_const_zero, zero_add, zero_sub, Finset.mul_sum, neg_div,
Finset.sum_div, mul_div_assoc, mul_assoc]
#align inner_sum_smul_sum_smul_of_sum_eq_zero inner_sum_smul_sum_smul_of_sum_eq_zero
variable (𝕜)
/-- The inner product as a sesquilinear map. -/
def innerₛₗ : E →ₗ⋆[𝕜] E →ₗ[𝕜] 𝕜 :=
LinearMap.mk₂'ₛₗ _ _ (fun v w => ⟪v, w⟫) inner_add_left (fun _ _ _ => inner_smul_left _ _ _)
inner_add_right fun _ _ _ => inner_smul_right _ _ _
#align innerₛₗ innerₛₗ
@[simp]
theorem innerₛₗ_apply_coe (v : E) : ⇑(innerₛₗ 𝕜 v) = fun w => ⟪v, w⟫ :=
rfl
#align innerₛₗ_apply_coe innerₛₗ_apply_coe
@[simp]
theorem innerₛₗ_apply (v w : E) : innerₛₗ 𝕜 v w = ⟪v, w⟫ :=
rfl
#align innerₛₗ_apply innerₛₗ_apply
variable (F)
/-- The inner product as a bilinear map in the real case. -/
def innerₗ : F →ₗ[ℝ] F →ₗ[ℝ] ℝ := innerₛₗ ℝ
@[simp] lemma flip_innerₗ : (innerₗ F).flip = innerₗ F := by
ext v w
exact real_inner_comm v w
variable {F}
@[simp] lemma innerₗ_apply (v w : F) : innerₗ F v w = ⟪v, w⟫_ℝ := rfl
/-- The inner product as a continuous sesquilinear map. Note that `toDualMap` (resp. `toDual`)
in `InnerProductSpace.Dual` is a version of this given as a linear isometry (resp. linear
isometric equivalence). -/
def innerSL : E →L⋆[𝕜] E →L[𝕜] 𝕜 :=
LinearMap.mkContinuous₂ (innerₛₗ 𝕜) 1 fun x y => by
simp only [norm_inner_le_norm, one_mul, innerₛₗ_apply]
set_option linter.uppercaseLean3 false in
#align innerSL innerSL
@[simp]
theorem innerSL_apply_coe (v : E) : ⇑(innerSL 𝕜 v) = fun w => ⟪v, w⟫ :=
rfl
set_option linter.uppercaseLean3 false in
#align innerSL_apply_coe innerSL_apply_coe
@[simp]
theorem innerSL_apply (v w : E) : innerSL 𝕜 v w = ⟪v, w⟫ :=
rfl
set_option linter.uppercaseLean3 false in
#align innerSL_apply innerSL_apply
/-- `innerSL` is an isometry. Note that the associated `LinearIsometry` is defined in
`InnerProductSpace.Dual` as `toDualMap`. -/
@[simp]
theorem innerSL_apply_norm (x : E) : ‖innerSL 𝕜 x‖ = ‖x‖ := by
refine
le_antisymm ((innerSL 𝕜 x).opNorm_le_bound (norm_nonneg _) fun y => norm_inner_le_norm _ _) ?_
rcases eq_or_ne x 0 with (rfl | h)
· simp
· refine (mul_le_mul_right (norm_pos_iff.2 h)).mp ?_
calc
‖x‖ * ‖x‖ = ‖(⟪x, x⟫ : 𝕜)‖ := by
rw [← sq, inner_self_eq_norm_sq_to_K, norm_pow, norm_ofReal, abs_norm]
_ ≤ ‖innerSL 𝕜 x‖ * ‖x‖ := (innerSL 𝕜 x).le_opNorm _
set_option linter.uppercaseLean3 false in
#align innerSL_apply_norm innerSL_apply_norm
lemma norm_innerSL_le : ‖innerSL 𝕜 (E := E)‖ ≤ 1 :=
ContinuousLinearMap.opNorm_le_bound _ zero_le_one (by simp)
/-- The inner product as a continuous sesquilinear map, with the two arguments flipped. -/
def innerSLFlip : E →L[𝕜] E →L⋆[𝕜] 𝕜 :=
@ContinuousLinearMap.flipₗᵢ' 𝕜 𝕜 𝕜 E E 𝕜 _ _ _ _ _ _ _ _ _ (RingHom.id 𝕜) (starRingEnd 𝕜) _ _
(innerSL 𝕜)
set_option linter.uppercaseLean3 false in
#align innerSL_flip innerSLFlip
@[simp]
theorem innerSLFlip_apply (x y : E) : innerSLFlip 𝕜 x y = ⟪y, x⟫ :=
rfl
set_option linter.uppercaseLean3 false in
#align innerSL_flip_apply innerSLFlip_apply
variable (F) in
@[simp] lemma innerSL_real_flip : (innerSL ℝ (E := F)).flip = innerSL ℝ := by
ext v w
exact real_inner_comm _ _
variable {𝕜}
namespace ContinuousLinearMap
variable {E' : Type*} [NormedAddCommGroup E'] [InnerProductSpace 𝕜 E']
-- Note: odd and expensive build behavior is explicitly turned off using `noncomputable`
/-- Given `f : E →L[𝕜] E'`, construct the continuous sesquilinear form `fun x y ↦ ⟪x, A y⟫`, given
as a continuous linear map. -/
noncomputable def toSesqForm : (E →L[𝕜] E') →L[𝕜] E' →L⋆[𝕜] E →L[𝕜] 𝕜 :=
(ContinuousLinearMap.flipₗᵢ' E E' 𝕜 (starRingEnd 𝕜) (RingHom.id 𝕜)).toContinuousLinearEquiv ∘L
ContinuousLinearMap.compSL E E' (E' →L⋆[𝕜] 𝕜) (RingHom.id 𝕜) (RingHom.id 𝕜) (innerSLFlip 𝕜)
#align continuous_linear_map.to_sesq_form ContinuousLinearMap.toSesqForm
@[simp]
theorem toSesqForm_apply_coe (f : E →L[𝕜] E') (x : E') : toSesqForm f x = (innerSL 𝕜 x).comp f :=
rfl
#align continuous_linear_map.to_sesq_form_apply_coe ContinuousLinearMap.toSesqForm_apply_coe
theorem toSesqForm_apply_norm_le {f : E →L[𝕜] E'} {v : E'} : ‖toSesqForm f v‖ ≤ ‖f‖ * ‖v‖ := by
refine opNorm_le_bound _ (by positivity) fun x ↦ ?_
have h₁ : ‖f x‖ ≤ ‖f‖ * ‖x‖ := le_opNorm _ _
have h₂ := @norm_inner_le_norm 𝕜 E' _ _ _ v (f x)
calc
‖⟪v, f x⟫‖ ≤ ‖v‖ * ‖f x‖ := h₂
_ ≤ ‖v‖ * (‖f‖ * ‖x‖) := mul_le_mul_of_nonneg_left h₁ (norm_nonneg v)
_ = ‖f‖ * ‖v‖ * ‖x‖ := by ring
#align continuous_linear_map.to_sesq_form_apply_norm_le ContinuousLinearMap.toSesqForm_apply_norm_le
end ContinuousLinearMap
/-- When an inner product space `E` over `𝕜` is considered as a real normed space, its inner
product satisfies `IsBoundedBilinearMap`.
In order to state these results, we need a `NormedSpace ℝ E` instance. We will later establish
such an instance by restriction-of-scalars, `InnerProductSpace.rclikeToReal 𝕜 E`, but this
instance may be not definitionally equal to some other “natural” instance. So, we assume
`[NormedSpace ℝ E]`.
-/
theorem _root_.isBoundedBilinearMap_inner [NormedSpace ℝ E] :
IsBoundedBilinearMap ℝ fun p : E × E => ⟪p.1, p.2⟫ :=
{ add_left := inner_add_left
smul_left := fun r x y => by
simp only [← algebraMap_smul 𝕜 r x, algebraMap_eq_ofReal, inner_smul_real_left]
add_right := inner_add_right
smul_right := fun r x y => by
simp only [← algebraMap_smul 𝕜 r y, algebraMap_eq_ofReal, inner_smul_real_right]
bound :=
⟨1, zero_lt_one, fun x y => by
rw [one_mul]
exact norm_inner_le_norm x y⟩ }
#align is_bounded_bilinear_map_inner isBoundedBilinearMap_inner
end Norm
section BesselsInequality
variable {ι : Type*} (x : E) {v : ι → E}
/-- Bessel's inequality for finite sums. -/
theorem Orthonormal.sum_inner_products_le {s : Finset ι} (hv : Orthonormal 𝕜 v) :
∑ i ∈ s, ‖⟪v i, x⟫‖ ^ 2 ≤ ‖x‖ ^ 2 := by
have h₂ :
(∑ i ∈ s, ∑ j ∈ s, ⟪v i, x⟫ * ⟪x, v j⟫ * ⟪v j, v i⟫) = (∑ k ∈ s, ⟪v k, x⟫ * ⟪x, v k⟫ : 𝕜) := by
classical exact hv.inner_left_right_finset
have h₃ : ∀ z : 𝕜, re (z * conj z) = ‖z‖ ^ 2 := by
intro z
simp only [mul_conj, normSq_eq_def']
norm_cast
suffices hbf : ‖x - ∑ i ∈ s, ⟪v i, x⟫ • v i‖ ^ 2 = ‖x‖ ^ 2 - ∑ i ∈ s, ‖⟪v i, x⟫‖ ^ 2 by
rw [← sub_nonneg, ← hbf]
simp only [norm_nonneg, pow_nonneg]
rw [@norm_sub_sq 𝕜, sub_add]
simp only [@InnerProductSpace.norm_sq_eq_inner 𝕜, _root_.inner_sum, _root_.sum_inner]
simp only [inner_smul_right, two_mul, inner_smul_left, inner_conj_symm, ← mul_assoc, h₂,
add_sub_cancel_right, sub_right_inj]
simp only [map_sum, ← inner_conj_symm x, ← h₃]
#align orthonormal.sum_inner_products_le Orthonormal.sum_inner_products_le
/-- Bessel's inequality. -/
theorem Orthonormal.tsum_inner_products_le (hv : Orthonormal 𝕜 v) :
∑' i, ‖⟪v i, x⟫‖ ^ 2 ≤ ‖x‖ ^ 2 := by
refine tsum_le_of_sum_le' ?_ fun s => hv.sum_inner_products_le x
simp only [norm_nonneg, pow_nonneg]
#align orthonormal.tsum_inner_products_le Orthonormal.tsum_inner_products_le
/-- The sum defined in Bessel's inequality is summable. -/
theorem Orthonormal.inner_products_summable (hv : Orthonormal 𝕜 v) :
Summable fun i => ‖⟪v i, x⟫‖ ^ 2 := by
use ⨆ s : Finset ι, ∑ i ∈ s, ‖⟪v i, x⟫‖ ^ 2
apply hasSum_of_isLUB_of_nonneg
· intro b
simp only [norm_nonneg, pow_nonneg]
· refine isLUB_ciSup ?_
use ‖x‖ ^ 2
rintro y ⟨s, rfl⟩
exact hv.sum_inner_products_le x
#align orthonormal.inner_products_summable Orthonormal.inner_products_summable
end BesselsInequality
/-- A field `𝕜` satisfying `RCLike` is itself a `𝕜`-inner product space. -/
instance RCLike.innerProductSpace : InnerProductSpace 𝕜 𝕜 where
inner x y := conj x * y
norm_sq_eq_inner x := by simp only [inner, conj_mul, ← ofReal_pow, ofReal_re]
conj_symm x y := by simp only [mul_comm, map_mul, starRingEnd_self_apply]
add_left x y z := by simp only [add_mul, map_add]
smul_left x y z := by simp only [mul_assoc, smul_eq_mul, map_mul]
#align is_R_or_C.inner_product_space RCLike.innerProductSpace
@[simp]
theorem RCLike.inner_apply (x y : 𝕜) : ⟪x, y⟫ = conj x * y :=
rfl
#align is_R_or_C.inner_apply RCLike.inner_apply
/-! ### Inner product space structure on subspaces -/
/-- Induced inner product on a submodule. -/
instance Submodule.innerProductSpace (W : Submodule 𝕜 E) : InnerProductSpace 𝕜 W :=
{ Submodule.normedSpace W with
inner := fun x y => ⟪(x : E), (y : E)⟫
conj_symm := fun _ _ => inner_conj_symm _ _
norm_sq_eq_inner := fun x => norm_sq_eq_inner (x : E)
add_left := fun _ _ _ => inner_add_left _ _ _
smul_left := fun _ _ _ => inner_smul_left _ _ _ }
#align submodule.inner_product_space Submodule.innerProductSpace
/-- The inner product on submodules is the same as on the ambient space. -/
@[simp]
theorem Submodule.coe_inner (W : Submodule 𝕜 E) (x y : W) : ⟪x, y⟫ = ⟪(x : E), ↑y⟫ :=
rfl
#align submodule.coe_inner Submodule.coe_inner
theorem Orthonormal.codRestrict {ι : Type*} {v : ι → E} (hv : Orthonormal 𝕜 v) (s : Submodule 𝕜 E)
(hvs : ∀ i, v i ∈ s) : @Orthonormal 𝕜 s _ _ _ ι (Set.codRestrict v s hvs) :=
s.subtypeₗᵢ.orthonormal_comp_iff.mp hv
#align orthonormal.cod_restrict Orthonormal.codRestrict
theorem orthonormal_span {ι : Type*} {v : ι → E} (hv : Orthonormal 𝕜 v) :
@Orthonormal 𝕜 (Submodule.span 𝕜 (Set.range v)) _ _ _ ι fun i : ι =>
⟨v i, Submodule.subset_span (Set.mem_range_self i)⟩ :=
hv.codRestrict (Submodule.span 𝕜 (Set.range v)) fun i =>
Submodule.subset_span (Set.mem_range_self i)
#align orthonormal_span orthonormal_span
/-! ### Families of mutually-orthogonal subspaces of an inner product space -/
section OrthogonalFamily
variable {ι : Type*} (𝕜)
open DirectSum
/-- An indexed family of mutually-orthogonal subspaces of an inner product space `E`.
The simple way to express this concept would be as a condition on `V : ι → Submodule 𝕜 E`. We
instead implement it as a condition on a family of inner product spaces each equipped with an
isometric embedding into `E`, thus making it a property of morphisms rather than subobjects.
The connection to the subobject spelling is shown in `orthogonalFamily_iff_pairwise`.
This definition is less lightweight, but allows for better definitional properties when the inner
product space structure on each of the submodules is important -- for example, when considering
their Hilbert sum (`PiLp V 2`). For example, given an orthonormal set of vectors `v : ι → E`,
we have an associated orthogonal family of one-dimensional subspaces of `E`, which it is convenient
to be able to discuss using `ι → 𝕜` rather than `Π i : ι, span 𝕜 (v i)`. -/
def OrthogonalFamily (G : ι → Type*) [∀ i, NormedAddCommGroup (G i)]
[∀ i, InnerProductSpace 𝕜 (G i)] (V : ∀ i, G i →ₗᵢ[𝕜] E) : Prop :=
Pairwise fun i j => ∀ v : G i, ∀ w : G j, ⟪V i v, V j w⟫ = 0
#align orthogonal_family OrthogonalFamily
variable {𝕜}
variable {G : ι → Type*} [∀ i, NormedAddCommGroup (G i)] [∀ i, InnerProductSpace 𝕜 (G i)]
{V : ∀ i, G i →ₗᵢ[𝕜] E} (hV : OrthogonalFamily 𝕜 G V) [dec_V : ∀ (i) (x : G i), Decidable (x ≠ 0)]
theorem Orthonormal.orthogonalFamily {v : ι → E} (hv : Orthonormal 𝕜 v) :
OrthogonalFamily 𝕜 (fun _i : ι => 𝕜) fun i => LinearIsometry.toSpanSingleton 𝕜 E (hv.1 i) :=
fun i j hij a b => by simp [inner_smul_left, inner_smul_right, hv.2 hij]
#align orthonormal.orthogonal_family Orthonormal.orthogonalFamily
theorem OrthogonalFamily.eq_ite [DecidableEq ι] {i j : ι} (v : G i) (w : G j) :
⟪V i v, V j w⟫ = ite (i = j) ⟪V i v, V j w⟫ 0 := by
split_ifs with h
· rfl
· exact hV h v w
#align orthogonal_family.eq_ite OrthogonalFamily.eq_ite
| Mathlib/Analysis/InnerProductSpace/Basic.lean | 2,021 | 2,033 | theorem OrthogonalFamily.inner_right_dfinsupp [DecidableEq ι] (l : ⨁ i, G i) (i : ι) (v : G i) :
⟪V i v, l.sum fun j => V j⟫ = ⟪v, l i⟫ :=
calc
⟪V i v, l.sum fun j => V j⟫ = l.sum fun j => fun w => ⟪V i v, V j w⟫ :=
DFinsupp.inner_sum (fun j => V j) l (V i v)
_ = l.sum fun j => fun w => ite (i = j) ⟪V i v, V j w⟫ 0 :=
(congr_arg l.sum <| funext fun j => funext <| hV.eq_ite v)
_ = ⟪v, l i⟫ := by |
simp only [DFinsupp.sum, Submodule.coe_inner, Finset.sum_ite_eq, ite_eq_left_iff,
DFinsupp.mem_support_toFun]
split_ifs with h
· simp only [LinearIsometry.inner_map_map]
· simp only [of_not_not h, inner_zero_right]
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Data.Fintype.Card
import Mathlib.Data.Finset.Sum
import Mathlib.Logic.Embedding.Set
#align_import data.fintype.sum from "leanprover-community/mathlib"@"6623e6af705e97002a9054c1c05a980180276fc1"
/-!
## Instances
We provide the `Fintype` instance for the sum of two fintypes.
-/
universe u v
variable {α β : Type*}
open Finset
instance (α : Type u) (β : Type v) [Fintype α] [Fintype β] : Fintype (Sum α β) where
elems := univ.disjSum univ
complete := by rintro (_ | _) <;> simp
@[simp]
theorem Finset.univ_disjSum_univ {α β : Type*} [Fintype α] [Fintype β] :
univ.disjSum univ = (univ : Finset (Sum α β)) :=
rfl
#align finset.univ_disj_sum_univ Finset.univ_disjSum_univ
@[simp]
theorem Fintype.card_sum [Fintype α] [Fintype β] :
Fintype.card (Sum α β) = Fintype.card α + Fintype.card β :=
card_disjSum _ _
#align fintype.card_sum Fintype.card_sum
/-- If the subtype of all-but-one elements is a `Fintype` then the type itself is a `Fintype`. -/
def fintypeOfFintypeNe (a : α) (h : Fintype { b // b ≠ a }) : Fintype α :=
Fintype.ofBijective (Sum.elim ((↑) : { b // b = a } → α) ((↑) : { b // b ≠ a } → α)) <| by
classical exact (Equiv.sumCompl (· = a)).bijective
#align fintype_of_fintype_ne fintypeOfFintypeNe
theorem image_subtype_ne_univ_eq_image_erase [Fintype α] [DecidableEq β] (k : β) (b : α → β) :
image (fun i : { a // b a ≠ k } => b ↑i) univ = (image b univ).erase k := by
apply subset_antisymm
· rw [image_subset_iff]
intro i _
apply mem_erase_of_ne_of_mem i.2 (mem_image_of_mem _ (mem_univ _))
· intro i hi
rw [mem_image]
rcases mem_image.1 (erase_subset _ _ hi) with ⟨a, _, ha⟩
subst ha
exact ⟨⟨a, ne_of_mem_erase hi⟩, mem_univ _, rfl⟩
#align image_subtype_ne_univ_eq_image_erase image_subtype_ne_univ_eq_image_erase
theorem image_subtype_univ_ssubset_image_univ [Fintype α] [DecidableEq β] (k : β) (b : α → β)
(hk : k ∈ Finset.image b univ) (p : β → Prop) [DecidablePred p] (hp : ¬p k) :
image (fun i : { a // p (b a) } => b ↑i) univ ⊂ image b univ := by
constructor
· intro x hx
rcases mem_image.1 hx with ⟨y, _, hy⟩
exact hy ▸ mem_image_of_mem b (mem_univ (y : α))
· intro h
rw [mem_image] at hk
rcases hk with ⟨k', _, hk'⟩
subst hk'
have := h (mem_image_of_mem b (mem_univ k'))
rw [mem_image] at this
rcases this with ⟨j, _, hj'⟩
exact hp (hj' ▸ j.2)
#align image_subtype_univ_ssubset_image_univ image_subtype_univ_ssubset_image_univ
/-- Any injection from a finset `s` in a fintype `α` to a finset `t` of the same cardinality as `α`
can be extended to a bijection between `α` and `t`. -/
theorem Finset.exists_equiv_extend_of_card_eq [Fintype α] [DecidableEq β] {t : Finset β}
(hαt : Fintype.card α = t.card) {s : Finset α} {f : α → β} (hfst : Finset.image f s ⊆ t)
(hfs : Set.InjOn f s) : ∃ g : α ≃ t, ∀ i ∈ s, (g i : β) = f i := by
classical
induction' s using Finset.induction with a s has H generalizing f
· obtain ⟨e⟩ : Nonempty (α ≃ ↥t) := by rwa [← Fintype.card_eq, Fintype.card_coe]
use e
simp
have hfst' : Finset.image f s ⊆ t := (Finset.image_mono _ (s.subset_insert a)).trans hfst
have hfs' : Set.InjOn f s := hfs.mono (s.subset_insert a)
obtain ⟨g', hg'⟩ := H hfst' hfs'
have hfat : f a ∈ t := hfst (mem_image_of_mem _ (s.mem_insert_self a))
use g'.trans (Equiv.swap (⟨f a, hfat⟩ : t) (g' a))
simp_rw [mem_insert]
rintro i (rfl | hi)
· simp
rw [Equiv.trans_apply, Equiv.swap_apply_of_ne_of_ne, hg' _ hi]
· exact
ne_of_apply_ne Subtype.val
(ne_of_eq_of_ne (hg' _ hi) <|
hfs.ne (subset_insert _ _ hi) (mem_insert_self _ _) <| ne_of_mem_of_not_mem hi has)
· exact g'.injective.ne (ne_of_mem_of_not_mem hi has)
#align finset.exists_equiv_extend_of_card_eq Finset.exists_equiv_extend_of_card_eq
/-- Any injection from a set `s` in a fintype `α` to a finset `t` of the same cardinality as `α`
can be extended to a bijection between `α` and `t`. -/
theorem Set.MapsTo.exists_equiv_extend_of_card_eq [Fintype α] {t : Finset β}
(hαt : Fintype.card α = t.card) {s : Set α} {f : α → β} (hfst : s.MapsTo f t)
(hfs : Set.InjOn f s) : ∃ g : α ≃ t, ∀ i ∈ s, (g i : β) = f i := by
classical
let s' : Finset α := s.toFinset
have hfst' : s'.image f ⊆ t := by simpa [s', ← Finset.coe_subset] using hfst
have hfs' : Set.InjOn f s' := by simpa [s'] using hfs
obtain ⟨g, hg⟩ := Finset.exists_equiv_extend_of_card_eq hαt hfst' hfs'
refine ⟨g, fun i hi => ?_⟩
apply hg
simpa [s'] using hi
#align set.maps_to.exists_equiv_extend_of_card_eq Set.MapsTo.exists_equiv_extend_of_card_eq
theorem Fintype.card_subtype_or (p q : α → Prop) [Fintype { x // p x }] [Fintype { x // q x }]
[Fintype { x // p x ∨ q x }] :
Fintype.card { x // p x ∨ q x } ≤ Fintype.card { x // p x } + Fintype.card { x // q x } := by
classical
convert Fintype.card_le_of_embedding (subtypeOrLeftEmbedding p q)
rw [Fintype.card_sum]
#align fintype.card_subtype_or Fintype.card_subtype_or
| Mathlib/Data/Fintype/Sum.lean | 126 | 131 | theorem Fintype.card_subtype_or_disjoint (p q : α → Prop) (h : Disjoint p q) [Fintype { x // p x }]
[Fintype { x // q x }] [Fintype { x // p x ∨ q x }] :
Fintype.card { x // p x ∨ q x } = Fintype.card { x // p x } + Fintype.card { x // q x } := by |
classical
convert Fintype.card_congr (subtypeOrEquiv p q h)
simp
|
/-
Copyright (c) 2022 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa, Yuyang Zhao
-/
import Mathlib.Algebra.GroupWithZero.Defs
import Mathlib.Algebra.Order.Monoid.Unbundled.Defs
import Mathlib.Tactic.GCongr.Core
#align_import algebra.order.ring.lemmas from "leanprover-community/mathlib"@"44e29dbcff83ba7114a464d592b8c3743987c1e5"
/-!
# Monotonicity of multiplication by positive elements
This file defines typeclasses to reason about monotonicity of the operations
* `b ↦ a * b`, "left multiplication"
* `a ↦ a * b`, "right multiplication"
We use eight typeclasses to encode the various properties we care about for those two operations.
These typeclasses are meant to be mostly internal to this file, to set up each lemma in the
appropriate generality.
Less granular typeclasses like `OrderedAddCommMonoid`, `LinearOrderedField` should be enough for
most purposes, and the system is set up so that they imply the correct granular typeclasses here.
If those are enough for you, you may stop reading here! Else, beware that what follows is a bit
technical.
## Definitions
In all that follows, `α` is an orders which has a `0` and a multiplication. Note however that we do
not use lawfulness of this action in most of the file. Hence `*` should be considered here as a
mostly arbitrary function `α → α → α`.
We use the following four typeclasses to reason about left multiplication (`b ↦ a * b`):
* `PosMulMono`: If `a ≥ 0`, then `b₁ ≤ b₂ → a * b₁ ≤ a * b₂`.
* `PosMulStrictMono`: If `a > 0`, then `b₁ < b₂ → a * b₁ < a * b₂`.
* `PosMulReflectLT`: If `a ≥ 0`, then `a * b₁ < a * b₂ → b₁ < b₂`.
* `PosMulReflectLE`: If `a > 0`, then `a * b₁ ≤ a * b₂ → b₁ ≤ b₂`.
We use the following four typeclasses to reason about right multiplication (`a ↦ a * b`):
* `MulPosMono`: If `b ≥ 0`, then `a₁ ≤ a₂ → a₁ * b ≤ a₂ * b`.
* `MulPosStrictMono`: If `b > 0`, then `a₁ < a₂ → a₁ * b < a₂ * b`.
* `MulPosReflectLT`: If `b ≥ 0`, then `a₁ * b < a₂ * b → a₁ < a₂`.
* `MulPosReflectLE`: If `b > 0`, then `a₁ * b ≤ a₂ * b → a₁ ≤ a₂`.
## Implications
As `α` gets more and more structure, those typeclasses end up being equivalent. The commonly used
implications are:
* When `α` is a partial order:
* `PosMulStrictMono → PosMulMono`
* `MulPosStrictMono → MulPosMono`
* `PosMulReflectLE → PosMulReflectLT`
* `MulPosReflectLE → MulPosReflectLT`
* When `α` is a linear order:
* `PosMulStrictMono → PosMulReflectLE`
* `MulPosStrictMono → MulPosReflectLE` .
* When the multiplication of `α` is commutative:
* `PosMulMono → MulPosMono`
* `PosMulStrictMono → MulPosStrictMono`
* `PosMulReflectLE → MulPosReflectLE`
* `PosMulReflectLT → MulPosReflectLT`
Further, the bundled non-granular typeclasses imply the granular ones like so:
* `OrderedSemiring → PosMulMono`
* `OrderedSemiring → MulPosMono`
* `StrictOrderedSemiring → PosMulStrictMono`
* `StrictOrderedSemiring → MulPosStrictMono`
All these are registered as instances, which means that in practice you should not worry about these
implications. However, if you encounter a case where you think a statement is true but not covered
by the current implications, please bring it up on Zulip!
## Notation
The following is local notation in this file:
* `α≥0`: `{x : α // 0 ≤ x}`
* `α>0`: `{x : α // 0 < x}`
See https://leanprover.zulipchat.com/#narrow/stream/113488-general/topic/notation.20for.20positive.20elements
for a discussion about this notation, and whether to enable it globally (note that the notation is
currently global but broken, hence actually only works locally).
-/
variable (α : Type*)
set_option quotPrecheck false in
/-- Local notation for the nonnegative elements of a type `α`. TODO: actually make local. -/
notation "α≥0" => { x : α // 0 ≤ x }
set_option quotPrecheck false in
/-- Local notation for the positive elements of a type `α`. TODO: actually make local. -/
notation "α>0" => { x : α // 0 < x }
section Abbreviations
variable [Mul α] [Zero α] [Preorder α]
/-- Typeclass for monotonicity of multiplication by nonnegative elements on the left,
namely `b₁ ≤ b₂ → a * b₁ ≤ a * b₂` if `0 ≤ a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`OrderedSemiring`. -/
abbrev PosMulMono : Prop :=
CovariantClass α≥0 α (fun x y => x * y) (· ≤ ·)
#align pos_mul_mono PosMulMono
/-- Typeclass for monotonicity of multiplication by nonnegative elements on the right,
namely `a₁ ≤ a₂ → a₁ * b ≤ a₂ * b` if `0 ≤ b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`OrderedSemiring`. -/
abbrev MulPosMono : Prop :=
CovariantClass α≥0 α (fun x y => y * x) (· ≤ ·)
#align mul_pos_mono MulPosMono
/-- Typeclass for strict monotonicity of multiplication by positive elements on the left,
namely `b₁ < b₂ → a * b₁ < a * b₂` if `0 < a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`StrictOrderedSemiring`. -/
abbrev PosMulStrictMono : Prop :=
CovariantClass α>0 α (fun x y => x * y) (· < ·)
#align pos_mul_strict_mono PosMulStrictMono
/-- Typeclass for strict monotonicity of multiplication by positive elements on the right,
namely `a₁ < a₂ → a₁ * b < a₂ * b` if `0 < b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`StrictOrderedSemiring`. -/
abbrev MulPosStrictMono : Prop :=
CovariantClass α>0 α (fun x y => y * x) (· < ·)
#align mul_pos_strict_mono MulPosStrictMono
/-- Typeclass for strict reverse monotonicity of multiplication by nonnegative elements on
the left, namely `a * b₁ < a * b₂ → b₁ < b₂` if `0 ≤ a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev PosMulReflectLT : Prop :=
ContravariantClass α≥0 α (fun x y => x * y) (· < ·)
#align pos_mul_reflect_lt PosMulReflectLT
/-- Typeclass for strict reverse monotonicity of multiplication by nonnegative elements on
the right, namely `a₁ * b < a₂ * b → a₁ < a₂` if `0 ≤ b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev MulPosReflectLT : Prop :=
ContravariantClass α≥0 α (fun x y => y * x) (· < ·)
#align mul_pos_reflect_lt MulPosReflectLT
/-- Typeclass for reverse monotonicity of multiplication by positive elements on the left,
namely `a * b₁ ≤ a * b₂ → b₁ ≤ b₂` if `0 < a`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev PosMulReflectLE : Prop :=
ContravariantClass α>0 α (fun x y => x * y) (· ≤ ·)
#align pos_mul_mono_rev PosMulReflectLE
/-- Typeclass for reverse monotonicity of multiplication by positive elements on the right,
namely `a₁ * b ≤ a₂ * b → a₁ ≤ a₂` if `0 < b`.
You should usually not use this very granular typeclass directly, but rather a typeclass like
`LinearOrderedSemiring`. -/
abbrev MulPosReflectLE : Prop :=
ContravariantClass α>0 α (fun x y => y * x) (· ≤ ·)
#align mul_pos_mono_rev MulPosReflectLE
end Abbreviations
variable {α} {a b c d : α}
section MulZero
variable [Mul α] [Zero α]
section Preorder
variable [Preorder α]
instance PosMulMono.to_covariantClass_pos_mul_le [PosMulMono α] :
CovariantClass α>0 α (fun x y => x * y) (· ≤ ·) :=
⟨fun a _ _ bc => @CovariantClass.elim α≥0 α (fun x y => x * y) (· ≤ ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align pos_mul_mono.to_covariant_class_pos_mul_le PosMulMono.to_covariantClass_pos_mul_le
instance MulPosMono.to_covariantClass_pos_mul_le [MulPosMono α] :
CovariantClass α>0 α (fun x y => y * x) (· ≤ ·) :=
⟨fun a _ _ bc => @CovariantClass.elim α≥0 α (fun x y => y * x) (· ≤ ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align mul_pos_mono.to_covariant_class_pos_mul_le MulPosMono.to_covariantClass_pos_mul_le
instance PosMulReflectLT.to_contravariantClass_pos_mul_lt [PosMulReflectLT α] :
ContravariantClass α>0 α (fun x y => x * y) (· < ·) :=
⟨fun a _ _ bc => @ContravariantClass.elim α≥0 α (fun x y => x * y) (· < ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align pos_mul_reflect_lt.to_contravariant_class_pos_mul_lt PosMulReflectLT.to_contravariantClass_pos_mul_lt
instance MulPosReflectLT.to_contravariantClass_pos_mul_lt [MulPosReflectLT α] :
ContravariantClass α>0 α (fun x y => y * x) (· < ·) :=
⟨fun a _ _ bc => @ContravariantClass.elim α≥0 α (fun x y => y * x) (· < ·) _ ⟨_, a.2.le⟩ _ _ bc⟩
#align mul_pos_reflect_lt.to_contravariant_class_pos_mul_lt MulPosReflectLT.to_contravariantClass_pos_mul_lt
@[gcongr]
theorem mul_le_mul_of_nonneg_left [PosMulMono α] (h : b ≤ c) (a0 : 0 ≤ a) : a * b ≤ a * c :=
@CovariantClass.elim α≥0 α (fun x y => x * y) (· ≤ ·) _ ⟨a, a0⟩ _ _ h
#align mul_le_mul_of_nonneg_left mul_le_mul_of_nonneg_left
@[gcongr]
theorem mul_le_mul_of_nonneg_right [MulPosMono α] (h : b ≤ c) (a0 : 0 ≤ a) : b * a ≤ c * a :=
@CovariantClass.elim α≥0 α (fun x y => y * x) (· ≤ ·) _ ⟨a, a0⟩ _ _ h
#align mul_le_mul_of_nonneg_right mul_le_mul_of_nonneg_right
@[gcongr]
theorem mul_lt_mul_of_pos_left [PosMulStrictMono α] (bc : b < c) (a0 : 0 < a) : a * b < a * c :=
@CovariantClass.elim α>0 α (fun x y => x * y) (· < ·) _ ⟨a, a0⟩ _ _ bc
#align mul_lt_mul_of_pos_left mul_lt_mul_of_pos_left
@[gcongr]
theorem mul_lt_mul_of_pos_right [MulPosStrictMono α] (bc : b < c) (a0 : 0 < a) : b * a < c * a :=
@CovariantClass.elim α>0 α (fun x y => y * x) (· < ·) _ ⟨a, a0⟩ _ _ bc
#align mul_lt_mul_of_pos_right mul_lt_mul_of_pos_right
theorem lt_of_mul_lt_mul_left [PosMulReflectLT α] (h : a * b < a * c) (a0 : 0 ≤ a) : b < c :=
@ContravariantClass.elim α≥0 α (fun x y => x * y) (· < ·) _ ⟨a, a0⟩ _ _ h
#align lt_of_mul_lt_mul_left lt_of_mul_lt_mul_left
theorem lt_of_mul_lt_mul_right [MulPosReflectLT α] (h : b * a < c * a) (a0 : 0 ≤ a) : b < c :=
@ContravariantClass.elim α≥0 α (fun x y => y * x) (· < ·) _ ⟨a, a0⟩ _ _ h
#align lt_of_mul_lt_mul_right lt_of_mul_lt_mul_right
theorem le_of_mul_le_mul_left [PosMulReflectLE α] (bc : a * b ≤ a * c) (a0 : 0 < a) : b ≤ c :=
@ContravariantClass.elim α>0 α (fun x y => x * y) (· ≤ ·) _ ⟨a, a0⟩ _ _ bc
#align le_of_mul_le_mul_left le_of_mul_le_mul_left
theorem le_of_mul_le_mul_right [MulPosReflectLE α] (bc : b * a ≤ c * a) (a0 : 0 < a) : b ≤ c :=
@ContravariantClass.elim α>0 α (fun x y => y * x) (· ≤ ·) _ ⟨a, a0⟩ _ _ bc
#align le_of_mul_le_mul_right le_of_mul_le_mul_right
alias lt_of_mul_lt_mul_of_nonneg_left := lt_of_mul_lt_mul_left
#align lt_of_mul_lt_mul_of_nonneg_left lt_of_mul_lt_mul_of_nonneg_left
alias lt_of_mul_lt_mul_of_nonneg_right := lt_of_mul_lt_mul_right
#align lt_of_mul_lt_mul_of_nonneg_right lt_of_mul_lt_mul_of_nonneg_right
alias le_of_mul_le_mul_of_pos_left := le_of_mul_le_mul_left
#align le_of_mul_le_mul_of_pos_left le_of_mul_le_mul_of_pos_left
alias le_of_mul_le_mul_of_pos_right := le_of_mul_le_mul_right
#align le_of_mul_le_mul_of_pos_right le_of_mul_le_mul_of_pos_right
@[simp]
theorem mul_lt_mul_left [PosMulStrictMono α] [PosMulReflectLT α] (a0 : 0 < a) :
a * b < a * c ↔ b < c :=
@rel_iff_cov α>0 α (fun x y => x * y) (· < ·) _ _ ⟨a, a0⟩ _ _
#align mul_lt_mul_left mul_lt_mul_left
@[simp]
theorem mul_lt_mul_right [MulPosStrictMono α] [MulPosReflectLT α] (a0 : 0 < a) :
b * a < c * a ↔ b < c :=
@rel_iff_cov α>0 α (fun x y => y * x) (· < ·) _ _ ⟨a, a0⟩ _ _
#align mul_lt_mul_right mul_lt_mul_right
@[simp]
theorem mul_le_mul_left [PosMulMono α] [PosMulReflectLE α] (a0 : 0 < a) : a * b ≤ a * c ↔ b ≤ c :=
@rel_iff_cov α>0 α (fun x y => x * y) (· ≤ ·) _ _ ⟨a, a0⟩ _ _
#align mul_le_mul_left mul_le_mul_left
@[simp]
theorem mul_le_mul_right [MulPosMono α] [MulPosReflectLE α] (a0 : 0 < a) : b * a ≤ c * a ↔ b ≤ c :=
@rel_iff_cov α>0 α (fun x y => y * x) (· ≤ ·) _ _ ⟨a, a0⟩ _ _
#align mul_le_mul_right mul_le_mul_right
alias mul_le_mul_iff_of_pos_left := mul_le_mul_left
alias mul_le_mul_iff_of_pos_right := mul_le_mul_right
alias mul_lt_mul_iff_of_pos_left := mul_lt_mul_left
alias mul_lt_mul_iff_of_pos_right := mul_lt_mul_right
theorem mul_lt_mul_of_pos_of_nonneg [PosMulStrictMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c < d)
(a0 : 0 < a) (d0 : 0 ≤ d) : a * c < b * d :=
(mul_lt_mul_of_pos_left h₂ a0).trans_le (mul_le_mul_of_nonneg_right h₁ d0)
#align mul_lt_mul_of_pos_of_nonneg mul_lt_mul_of_pos_of_nonneg
theorem mul_lt_mul_of_le_of_le' [PosMulStrictMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c < d)
(b0 : 0 < b) (c0 : 0 ≤ c) : a * c < b * d :=
(mul_le_mul_of_nonneg_right h₁ c0).trans_lt (mul_lt_mul_of_pos_left h₂ b0)
#align mul_lt_mul_of_le_of_le' mul_lt_mul_of_le_of_le'
theorem mul_lt_mul_of_nonneg_of_pos [PosMulMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c ≤ d)
(a0 : 0 ≤ a) (d0 : 0 < d) : a * c < b * d :=
(mul_le_mul_of_nonneg_left h₂ a0).trans_lt (mul_lt_mul_of_pos_right h₁ d0)
#align mul_lt_mul_of_nonneg_of_pos mul_lt_mul_of_nonneg_of_pos
theorem mul_lt_mul_of_le_of_lt' [PosMulMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c ≤ d)
(b0 : 0 ≤ b) (c0 : 0 < c) : a * c < b * d :=
(mul_lt_mul_of_pos_right h₁ c0).trans_le (mul_le_mul_of_nonneg_left h₂ b0)
#align mul_lt_mul_of_le_of_lt' mul_lt_mul_of_le_of_lt'
theorem mul_lt_mul_of_pos_of_pos [PosMulStrictMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c < d)
(a0 : 0 < a) (d0 : 0 < d) : a * c < b * d :=
(mul_lt_mul_of_pos_left h₂ a0).trans (mul_lt_mul_of_pos_right h₁ d0)
#align mul_lt_mul_of_pos_of_pos mul_lt_mul_of_pos_of_pos
theorem mul_lt_mul_of_lt_of_lt' [PosMulStrictMono α] [MulPosStrictMono α] (h₁ : a < b) (h₂ : c < d)
(b0 : 0 < b) (c0 : 0 < c) : a * c < b * d :=
(mul_lt_mul_of_pos_right h₁ c0).trans (mul_lt_mul_of_pos_left h₂ b0)
#align mul_lt_mul_of_lt_of_lt' mul_lt_mul_of_lt_of_lt'
theorem mul_lt_of_mul_lt_of_nonneg_left [PosMulMono α] (h : a * b < c) (hdb : d ≤ b) (ha : 0 ≤ a) :
a * d < c :=
(mul_le_mul_of_nonneg_left hdb ha).trans_lt h
#align mul_lt_of_mul_lt_of_nonneg_left mul_lt_of_mul_lt_of_nonneg_left
theorem lt_mul_of_lt_mul_of_nonneg_left [PosMulMono α] (h : a < b * c) (hcd : c ≤ d) (hb : 0 ≤ b) :
a < b * d :=
h.trans_le <| mul_le_mul_of_nonneg_left hcd hb
#align lt_mul_of_lt_mul_of_nonneg_left lt_mul_of_lt_mul_of_nonneg_left
theorem mul_lt_of_mul_lt_of_nonneg_right [MulPosMono α] (h : a * b < c) (hda : d ≤ a) (hb : 0 ≤ b) :
d * b < c :=
(mul_le_mul_of_nonneg_right hda hb).trans_lt h
#align mul_lt_of_mul_lt_of_nonneg_right mul_lt_of_mul_lt_of_nonneg_right
theorem lt_mul_of_lt_mul_of_nonneg_right [MulPosMono α] (h : a < b * c) (hbd : b ≤ d) (hc : 0 ≤ c) :
a < d * c :=
h.trans_le <| mul_le_mul_of_nonneg_right hbd hc
#align lt_mul_of_lt_mul_of_nonneg_right lt_mul_of_lt_mul_of_nonneg_right
end Preorder
section LinearOrder
variable [LinearOrder α]
-- see Note [lower instance priority]
instance (priority := 100) PosMulStrictMono.toPosMulReflectLE [PosMulStrictMono α] :
PosMulReflectLE α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).1 CovariantClass.elim⟩
-- see Note [lower instance priority]
instance (priority := 100) MulPosStrictMono.toMulPosReflectLE [MulPosStrictMono α] :
MulPosReflectLE α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).1 CovariantClass.elim⟩
theorem PosMulReflectLE.toPosMulStrictMono [PosMulReflectLE α] : PosMulStrictMono α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).2 ContravariantClass.elim⟩
#align pos_mul_mono_rev.to_pos_mul_strict_mono PosMulReflectLE.toPosMulStrictMono
theorem MulPosReflectLE.toMulPosStrictMono [MulPosReflectLE α] : MulPosStrictMono α :=
⟨(covariant_lt_iff_contravariant_le _ _ _).2 ContravariantClass.elim⟩
#align mul_pos_mono_rev.to_mul_pos_strict_mono MulPosReflectLE.toMulPosStrictMono
theorem posMulStrictMono_iff_posMulReflectLE : PosMulStrictMono α ↔ PosMulReflectLE α :=
⟨@PosMulStrictMono.toPosMulReflectLE _ _ _ _, @PosMulReflectLE.toPosMulStrictMono _ _ _ _⟩
#align pos_mul_strict_mono_iff_pos_mul_mono_rev posMulStrictMono_iff_posMulReflectLE
theorem mulPosStrictMono_iff_mulPosReflectLE : MulPosStrictMono α ↔ MulPosReflectLE α :=
⟨@MulPosStrictMono.toMulPosReflectLE _ _ _ _, @MulPosReflectLE.toMulPosStrictMono _ _ _ _⟩
#align mul_pos_strict_mono_iff_mul_pos_mono_rev mulPosStrictMono_iff_mulPosReflectLE
theorem PosMulReflectLT.toPosMulMono [PosMulReflectLT α] : PosMulMono α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).2 ContravariantClass.elim⟩
#align pos_mul_reflect_lt.to_pos_mul_mono PosMulReflectLT.toPosMulMono
theorem MulPosReflectLT.toMulPosMono [MulPosReflectLT α] : MulPosMono α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).2 ContravariantClass.elim⟩
#align mul_pos_reflect_lt.to_mul_pos_mono MulPosReflectLT.toMulPosMono
theorem PosMulMono.toPosMulReflectLT [PosMulMono α] : PosMulReflectLT α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).1 CovariantClass.elim⟩
#align pos_mul_mono.to_pos_mul_reflect_lt PosMulMono.toPosMulReflectLT
theorem MulPosMono.toMulPosReflectLT [MulPosMono α] : MulPosReflectLT α :=
⟨(covariant_le_iff_contravariant_lt _ _ _).1 CovariantClass.elim⟩
#align mul_pos_mono.to_mul_pos_reflect_lt MulPosMono.toMulPosReflectLT
/- TODO: Currently, only one in four of the above are made instances; we could consider making
both directions of `covariant_le_iff_contravariant_lt` and `covariant_lt_iff_contravariant_le`
instances, then all of the above become redundant instances, but there are performance issues. -/
theorem posMulMono_iff_posMulReflectLT : PosMulMono α ↔ PosMulReflectLT α :=
⟨@PosMulMono.toPosMulReflectLT _ _ _ _, @PosMulReflectLT.toPosMulMono _ _ _ _⟩
#align pos_mul_mono_iff_pos_mul_reflect_lt posMulMono_iff_posMulReflectLT
theorem mulPosMono_iff_mulPosReflectLT : MulPosMono α ↔ MulPosReflectLT α :=
⟨@MulPosMono.toMulPosReflectLT _ _ _ _, @MulPosReflectLT.toMulPosMono _ _ _ _⟩
#align mul_pos_mono_iff_mul_pos_reflect_lt mulPosMono_iff_mulPosReflectLT
end LinearOrder
end MulZero
section MulZeroClass
variable [MulZeroClass α]
section Preorder
variable [Preorder α]
/-- Assumes left covariance. -/
theorem Left.mul_pos [PosMulStrictMono α] (ha : 0 < a) (hb : 0 < b) : 0 < a * b := by
simpa only [mul_zero] using mul_lt_mul_of_pos_left hb ha
#align left.mul_pos Left.mul_pos
alias mul_pos := Left.mul_pos
#align mul_pos mul_pos
theorem mul_neg_of_pos_of_neg [PosMulStrictMono α] (ha : 0 < a) (hb : b < 0) : a * b < 0 := by
simpa only [mul_zero] using mul_lt_mul_of_pos_left hb ha
#align mul_neg_of_pos_of_neg mul_neg_of_pos_of_neg
@[simp]
theorem mul_pos_iff_of_pos_left [PosMulStrictMono α] [PosMulReflectLT α] (h : 0 < a) :
0 < a * b ↔ 0 < b := by simpa using mul_lt_mul_left (b := 0) h
#align zero_lt_mul_left mul_pos_iff_of_pos_left
/-- Assumes right covariance. -/
theorem Right.mul_pos [MulPosStrictMono α] (ha : 0 < a) (hb : 0 < b) : 0 < a * b := by
simpa only [zero_mul] using mul_lt_mul_of_pos_right ha hb
#align right.mul_pos Right.mul_pos
theorem mul_neg_of_neg_of_pos [MulPosStrictMono α] (ha : a < 0) (hb : 0 < b) : a * b < 0 := by
simpa only [zero_mul] using mul_lt_mul_of_pos_right ha hb
#align mul_neg_of_neg_of_pos mul_neg_of_neg_of_pos
@[simp]
theorem mul_pos_iff_of_pos_right [MulPosStrictMono α] [MulPosReflectLT α] (h : 0 < b) :
0 < a * b ↔ 0 < a := by simpa using mul_lt_mul_right (b := 0) h
#align zero_lt_mul_right mul_pos_iff_of_pos_right
/-- Assumes left covariance. -/
theorem Left.mul_nonneg [PosMulMono α] (ha : 0 ≤ a) (hb : 0 ≤ b) : 0 ≤ a * b := by
simpa only [mul_zero] using mul_le_mul_of_nonneg_left hb ha
#align left.mul_nonneg Left.mul_nonneg
alias mul_nonneg := Left.mul_nonneg
#align mul_nonneg mul_nonneg
theorem mul_nonpos_of_nonneg_of_nonpos [PosMulMono α] (ha : 0 ≤ a) (hb : b ≤ 0) : a * b ≤ 0 := by
simpa only [mul_zero] using mul_le_mul_of_nonneg_left hb ha
#align mul_nonpos_of_nonneg_of_nonpos mul_nonpos_of_nonneg_of_nonpos
/-- Assumes right covariance. -/
theorem Right.mul_nonneg [MulPosMono α] (ha : 0 ≤ a) (hb : 0 ≤ b) : 0 ≤ a * b := by
simpa only [zero_mul] using mul_le_mul_of_nonneg_right ha hb
#align right.mul_nonneg Right.mul_nonneg
theorem mul_nonpos_of_nonpos_of_nonneg [MulPosMono α] (ha : a ≤ 0) (hb : 0 ≤ b) : a * b ≤ 0 := by
simpa only [zero_mul] using mul_le_mul_of_nonneg_right ha hb
#align mul_nonpos_of_nonpos_of_nonneg mul_nonpos_of_nonpos_of_nonneg
theorem pos_of_mul_pos_right [PosMulReflectLT α] (h : 0 < a * b) (ha : 0 ≤ a) : 0 < b :=
lt_of_mul_lt_mul_left ((mul_zero a).symm ▸ h : a * 0 < a * b) ha
#align pos_of_mul_pos_right pos_of_mul_pos_right
theorem pos_of_mul_pos_left [MulPosReflectLT α] (h : 0 < a * b) (hb : 0 ≤ b) : 0 < a :=
lt_of_mul_lt_mul_right ((zero_mul b).symm ▸ h : 0 * b < a * b) hb
#align pos_of_mul_pos_left pos_of_mul_pos_left
theorem pos_iff_pos_of_mul_pos [PosMulReflectLT α] [MulPosReflectLT α] (hab : 0 < a * b) :
0 < a ↔ 0 < b :=
⟨pos_of_mul_pos_right hab ∘ le_of_lt, pos_of_mul_pos_left hab ∘ le_of_lt⟩
#align pos_iff_pos_of_mul_pos pos_iff_pos_of_mul_pos
theorem mul_le_mul_of_le_of_le [PosMulMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c ≤ d) (a0 : 0 ≤ a)
(d0 : 0 ≤ d) : a * c ≤ b * d :=
(mul_le_mul_of_nonneg_left h₂ a0).trans <| mul_le_mul_of_nonneg_right h₁ d0
#align mul_le_mul_of_le_of_le mul_le_mul_of_le_of_le
@[gcongr]
theorem mul_le_mul [PosMulMono α] [MulPosMono α] (h₁ : a ≤ b) (h₂ : c ≤ d) (c0 : 0 ≤ c)
(b0 : 0 ≤ b) : a * c ≤ b * d :=
(mul_le_mul_of_nonneg_right h₁ c0).trans <| mul_le_mul_of_nonneg_left h₂ b0
#align mul_le_mul mul_le_mul
theorem mul_self_le_mul_self [PosMulMono α] [MulPosMono α] (ha : 0 ≤ a) (hab : a ≤ b) :
a * a ≤ b * b :=
mul_le_mul hab hab ha <| ha.trans hab
#align mul_self_le_mul_self mul_self_le_mul_self
theorem mul_le_of_mul_le_of_nonneg_left [PosMulMono α] (h : a * b ≤ c) (hle : d ≤ b)
(a0 : 0 ≤ a) : a * d ≤ c :=
(mul_le_mul_of_nonneg_left hle a0).trans h
#align mul_le_of_mul_le_of_nonneg_left mul_le_of_mul_le_of_nonneg_left
theorem le_mul_of_le_mul_of_nonneg_left [PosMulMono α] (h : a ≤ b * c) (hle : c ≤ d)
(b0 : 0 ≤ b) : a ≤ b * d :=
h.trans (mul_le_mul_of_nonneg_left hle b0)
#align le_mul_of_le_mul_of_nonneg_left le_mul_of_le_mul_of_nonneg_left
theorem mul_le_of_mul_le_of_nonneg_right [MulPosMono α] (h : a * b ≤ c) (hle : d ≤ a)
(b0 : 0 ≤ b) : d * b ≤ c :=
(mul_le_mul_of_nonneg_right hle b0).trans h
#align mul_le_of_mul_le_of_nonneg_right mul_le_of_mul_le_of_nonneg_right
theorem le_mul_of_le_mul_of_nonneg_right [MulPosMono α] (h : a ≤ b * c) (hle : b ≤ d)
(c0 : 0 ≤ c) : a ≤ d * c :=
h.trans (mul_le_mul_of_nonneg_right hle c0)
#align le_mul_of_le_mul_of_nonneg_right le_mul_of_le_mul_of_nonneg_right
end Preorder
section PartialOrder
variable [PartialOrder α]
theorem posMulMono_iff_covariant_pos :
PosMulMono α ↔ CovariantClass α>0 α (fun x y => x * y) (· ≤ ·) :=
⟨@PosMulMono.to_covariantClass_pos_mul_le _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha]
· exact @CovariantClass.elim α>0 α (fun x y => x * y) (· ≤ ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align pos_mul_mono_iff_covariant_pos posMulMono_iff_covariant_pos
theorem mulPosMono_iff_covariant_pos :
MulPosMono α ↔ CovariantClass α>0 α (fun x y => y * x) (· ≤ ·) :=
⟨@MulPosMono.to_covariantClass_pos_mul_le _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha]
· exact @CovariantClass.elim α>0 α (fun x y => y * x) (· ≤ ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align mul_pos_mono_iff_covariant_pos mulPosMono_iff_covariant_pos
theorem posMulReflectLT_iff_contravariant_pos :
PosMulReflectLT α ↔ ContravariantClass α>0 α (fun x y => x * y) (· < ·) :=
⟨@PosMulReflectLT.to_contravariantClass_pos_mul_lt _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha] at h
· exact @ContravariantClass.elim α>0 α (fun x y => x * y) (· < ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align pos_mul_reflect_lt_iff_contravariant_pos posMulReflectLT_iff_contravariant_pos
theorem mulPosReflectLT_iff_contravariant_pos :
MulPosReflectLT α ↔ ContravariantClass α>0 α (fun x y => y * x) (· < ·) :=
⟨@MulPosReflectLT.to_contravariantClass_pos_mul_lt _ _ _ _, fun h =>
⟨fun a b c h => by
obtain ha | ha := a.prop.eq_or_lt
· simp [← ha] at h
· exact @ContravariantClass.elim α>0 α (fun x y => y * x) (· < ·) _ ⟨_, ha⟩ _ _ h ⟩⟩
#align mul_pos_reflect_lt_iff_contravariant_pos mulPosReflectLT_iff_contravariant_pos
-- Porting note: mathlib3 proofs would look like `StrictMono.monotone <| @CovariantClass.elim ..`
-- but implicit argument handling causes that to break
-- see Note [lower instance priority]
instance (priority := 100) PosMulStrictMono.toPosMulMono [PosMulStrictMono α] : PosMulMono α :=
posMulMono_iff_covariant_pos.2 (covariantClass_le_of_lt _ _ _)
#align pos_mul_strict_mono.to_pos_mul_mono PosMulStrictMono.toPosMulMono
-- Porting note: mathlib3 proofs would look like `StrictMono.monotone <| @CovariantClass.elim ..`
-- but implicit argument handling causes that to break
-- see Note [lower instance priority]
instance (priority := 100) MulPosStrictMono.toMulPosMono [MulPosStrictMono α] : MulPosMono α :=
mulPosMono_iff_covariant_pos.2 (covariantClass_le_of_lt _ _ _)
#align mul_pos_strict_mono.to_mul_pos_mono MulPosStrictMono.toMulPosMono
-- see Note [lower instance priority]
instance (priority := 100) PosMulReflectLE.toPosMulReflectLT [PosMulReflectLE α] :
PosMulReflectLT α :=
posMulReflectLT_iff_contravariant_pos.2
⟨fun a b c h =>
(le_of_mul_le_mul_of_pos_left h.le a.2).lt_of_ne <| by
rintro rfl
simp at h⟩
#align pos_mul_mono_rev.to_pos_mul_reflect_lt PosMulReflectLE.toPosMulReflectLT
-- see Note [lower instance priority]
instance (priority := 100) MulPosReflectLE.toMulPosReflectLT [MulPosReflectLE α] :
MulPosReflectLT α :=
mulPosReflectLT_iff_contravariant_pos.2
⟨fun a b c h =>
(le_of_mul_le_mul_of_pos_right h.le a.2).lt_of_ne <| by
rintro rfl
simp at h⟩
#align mul_pos_mono_rev.to_mul_pos_reflect_lt MulPosReflectLE.toMulPosReflectLT
theorem mul_left_cancel_iff_of_pos [PosMulReflectLE α] (a0 : 0 < a) : a * b = a * c ↔ b = c :=
⟨fun h => (le_of_mul_le_mul_of_pos_left h.le a0).antisymm <|
le_of_mul_le_mul_of_pos_left h.ge a0, congr_arg _⟩
#align mul_left_cancel_iff_of_pos mul_left_cancel_iff_of_pos
theorem mul_right_cancel_iff_of_pos [MulPosReflectLE α] (b0 : 0 < b) : a * b = c * b ↔ a = c :=
⟨fun h => (le_of_mul_le_mul_of_pos_right h.le b0).antisymm <|
le_of_mul_le_mul_of_pos_right h.ge b0, congr_arg (· * b)⟩
#align mul_right_cancel_iff_of_pos mul_right_cancel_iff_of_pos
theorem mul_eq_mul_iff_eq_and_eq_of_pos [PosMulStrictMono α] [MulPosStrictMono α]
(hab : a ≤ b) (hcd : c ≤ d) (a0 : 0 < a) (d0 : 0 < d) :
a * c = b * d ↔ a = b ∧ c = d := by
refine ⟨fun h ↦ ?_, by rintro ⟨rfl, rfl⟩; rfl⟩
simp only [eq_iff_le_not_lt, hab, hcd, true_and]
refine ⟨fun hab ↦ h.not_lt ?_, fun hcd ↦ h.not_lt ?_⟩
· exact (mul_le_mul_of_nonneg_left hcd a0.le).trans_lt (mul_lt_mul_of_pos_right hab d0)
· exact (mul_lt_mul_of_pos_left hcd a0).trans_le (mul_le_mul_of_nonneg_right hab d0.le)
#align mul_eq_mul_iff_eq_and_eq_of_pos mul_eq_mul_iff_eq_and_eq_of_pos
| Mathlib/Algebra/Order/GroupWithZero/Unbundled.lean | 598 | 605 | theorem mul_eq_mul_iff_eq_and_eq_of_pos' [PosMulStrictMono α] [MulPosStrictMono α]
(hab : a ≤ b) (hcd : c ≤ d) (b0 : 0 < b) (c0 : 0 < c) :
a * c = b * d ↔ a = b ∧ c = d := by |
refine ⟨fun h ↦ ?_, by rintro ⟨rfl, rfl⟩; rfl⟩
simp only [eq_iff_le_not_lt, hab, hcd, true_and]
refine ⟨fun hab ↦ h.not_lt ?_, fun hcd ↦ h.not_lt ?_⟩
· exact (mul_lt_mul_of_pos_right hab c0).trans_le (mul_le_mul_of_nonneg_left hcd b0.le)
· exact (mul_le_mul_of_nonneg_right hab c0.le).trans_lt (mul_lt_mul_of_pos_left hcd b0)
|
/-
Copyright (c) 2017 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Floris van Doorn, Violeta Hernández Palacios
-/
import Mathlib.SetTheory.Ordinal.Arithmetic
#align_import set_theory.ordinal.exponential from "leanprover-community/mathlib"@"b67044ba53af18680e1dd246861d9584e968495d"
/-! # Ordinal exponential
In this file we define the power function and the logarithm function on ordinals. The two are
related by the lemma `Ordinal.opow_le_iff_le_log : b ^ c ≤ x ↔ c ≤ log b x` for nontrivial inputs
`b`, `c`.
-/
noncomputable section
open Function Cardinal Set Equiv Order
open scoped Classical
open Cardinal Ordinal
universe u v w
namespace Ordinal
/-- The ordinal exponential, defined by transfinite recursion. -/
instance pow : Pow Ordinal Ordinal :=
⟨fun a b => if a = 0 then 1 - b else limitRecOn b 1 (fun _ IH => IH * a) fun b _ => bsup.{u, u} b⟩
-- Porting note: Ambiguous notations.
-- local infixr:0 "^" => @Pow.pow Ordinal Ordinal Ordinal.instPowOrdinalOrdinal
theorem opow_def (a b : Ordinal) :
a ^ b = if a = 0 then 1 - b else limitRecOn b 1 (fun _ IH => IH * a) fun b _ => bsup.{u, u} b :=
rfl
#align ordinal.opow_def Ordinal.opow_def
-- Porting note: `if_pos rfl` → `if_true`
theorem zero_opow' (a : Ordinal) : 0 ^ a = 1 - a := by simp only [opow_def, if_true]
#align ordinal.zero_opow' Ordinal.zero_opow'
@[simp]
theorem zero_opow {a : Ordinal} (a0 : a ≠ 0) : (0 : Ordinal) ^ a = 0 := by
rwa [zero_opow', Ordinal.sub_eq_zero_iff_le, one_le_iff_ne_zero]
#align ordinal.zero_opow Ordinal.zero_opow
@[simp]
theorem opow_zero (a : Ordinal) : a ^ (0 : Ordinal) = 1 := by
by_cases h : a = 0
· simp only [opow_def, if_pos h, sub_zero]
· simp only [opow_def, if_neg h, limitRecOn_zero]
#align ordinal.opow_zero Ordinal.opow_zero
@[simp]
theorem opow_succ (a b : Ordinal) : a ^ succ b = a ^ b * a :=
if h : a = 0 then by subst a; simp only [zero_opow (succ_ne_zero _), mul_zero]
else by simp only [opow_def, limitRecOn_succ, if_neg h]
#align ordinal.opow_succ Ordinal.opow_succ
theorem opow_limit {a b : Ordinal} (a0 : a ≠ 0) (h : IsLimit b) :
a ^ b = bsup.{u, u} b fun c _ => a ^ c := by
simp only [opow_def, if_neg a0]; rw [limitRecOn_limit _ _ _ _ h]
#align ordinal.opow_limit Ordinal.opow_limit
theorem opow_le_of_limit {a b c : Ordinal} (a0 : a ≠ 0) (h : IsLimit b) :
a ^ b ≤ c ↔ ∀ b' < b, a ^ b' ≤ c := by rw [opow_limit a0 h, bsup_le_iff]
#align ordinal.opow_le_of_limit Ordinal.opow_le_of_limit
theorem lt_opow_of_limit {a b c : Ordinal} (b0 : b ≠ 0) (h : IsLimit c) :
a < b ^ c ↔ ∃ c' < c, a < b ^ c' := by
rw [← not_iff_not, not_exists]; simp only [not_lt, opow_le_of_limit b0 h, exists_prop, not_and]
#align ordinal.lt_opow_of_limit Ordinal.lt_opow_of_limit
@[simp]
theorem opow_one (a : Ordinal) : a ^ (1 : Ordinal) = a := by
rw [← succ_zero, opow_succ]; simp only [opow_zero, one_mul]
#align ordinal.opow_one Ordinal.opow_one
@[simp]
theorem one_opow (a : Ordinal) : (1 : Ordinal) ^ a = 1 := by
induction a using limitRecOn with
| H₁ => simp only [opow_zero]
| H₂ _ ih =>
simp only [opow_succ, ih, mul_one]
| H₃ b l IH =>
refine eq_of_forall_ge_iff fun c => ?_
rw [opow_le_of_limit Ordinal.one_ne_zero l]
exact ⟨fun H => by simpa only [opow_zero] using H 0 l.pos, fun H b' h => by rwa [IH _ h]⟩
#align ordinal.one_opow Ordinal.one_opow
theorem opow_pos {a : Ordinal} (b : Ordinal) (a0 : 0 < a) : 0 < a ^ b := by
have h0 : 0 < a ^ (0 : Ordinal) := by simp only [opow_zero, zero_lt_one]
induction b using limitRecOn with
| H₁ => exact h0
| H₂ b IH =>
rw [opow_succ]
exact mul_pos IH a0
| H₃ b l _ =>
exact (lt_opow_of_limit (Ordinal.pos_iff_ne_zero.1 a0) l).2 ⟨0, l.pos, h0⟩
#align ordinal.opow_pos Ordinal.opow_pos
theorem opow_ne_zero {a : Ordinal} (b : Ordinal) (a0 : a ≠ 0) : a ^ b ≠ 0 :=
Ordinal.pos_iff_ne_zero.1 <| opow_pos b <| Ordinal.pos_iff_ne_zero.2 a0
#align ordinal.opow_ne_zero Ordinal.opow_ne_zero
theorem opow_isNormal {a : Ordinal} (h : 1 < a) : IsNormal (a ^ ·) :=
have a0 : 0 < a := zero_lt_one.trans h
⟨fun b => by simpa only [mul_one, opow_succ] using (mul_lt_mul_iff_left (opow_pos b a0)).2 h,
fun b l c => opow_le_of_limit (ne_of_gt a0) l⟩
#align ordinal.opow_is_normal Ordinal.opow_isNormal
theorem opow_lt_opow_iff_right {a b c : Ordinal} (a1 : 1 < a) : a ^ b < a ^ c ↔ b < c :=
(opow_isNormal a1).lt_iff
#align ordinal.opow_lt_opow_iff_right Ordinal.opow_lt_opow_iff_right
theorem opow_le_opow_iff_right {a b c : Ordinal} (a1 : 1 < a) : a ^ b ≤ a ^ c ↔ b ≤ c :=
(opow_isNormal a1).le_iff
#align ordinal.opow_le_opow_iff_right Ordinal.opow_le_opow_iff_right
theorem opow_right_inj {a b c : Ordinal} (a1 : 1 < a) : a ^ b = a ^ c ↔ b = c :=
(opow_isNormal a1).inj
#align ordinal.opow_right_inj Ordinal.opow_right_inj
theorem opow_isLimit {a b : Ordinal} (a1 : 1 < a) : IsLimit b → IsLimit (a ^ b) :=
(opow_isNormal a1).isLimit
#align ordinal.opow_is_limit Ordinal.opow_isLimit
theorem opow_isLimit_left {a b : Ordinal} (l : IsLimit a) (hb : b ≠ 0) : IsLimit (a ^ b) := by
rcases zero_or_succ_or_limit b with (e | ⟨b, rfl⟩ | l')
· exact absurd e hb
· rw [opow_succ]
exact mul_isLimit (opow_pos _ l.pos) l
· exact opow_isLimit l.one_lt l'
#align ordinal.opow_is_limit_left Ordinal.opow_isLimit_left
theorem opow_le_opow_right {a b c : Ordinal} (h₁ : 0 < a) (h₂ : b ≤ c) : a ^ b ≤ a ^ c := by
rcases lt_or_eq_of_le (one_le_iff_pos.2 h₁) with h₁ | h₁
· exact (opow_le_opow_iff_right h₁).2 h₂
· subst a
-- Porting note: `le_refl` is required.
simp only [one_opow, le_refl]
#align ordinal.opow_le_opow_right Ordinal.opow_le_opow_right
theorem opow_le_opow_left {a b : Ordinal} (c : Ordinal) (ab : a ≤ b) : a ^ c ≤ b ^ c := by
by_cases a0 : a = 0
-- Porting note: `le_refl` is required.
· subst a
by_cases c0 : c = 0
· subst c
simp only [opow_zero, le_refl]
· simp only [zero_opow c0, Ordinal.zero_le]
· induction c using limitRecOn with
| H₁ => simp only [opow_zero, le_refl]
| H₂ c IH =>
simpa only [opow_succ] using mul_le_mul' IH ab
| H₃ c l IH =>
exact
(opow_le_of_limit a0 l).2 fun b' h =>
(IH _ h).trans (opow_le_opow_right ((Ordinal.pos_iff_ne_zero.2 a0).trans_le ab) h.le)
#align ordinal.opow_le_opow_left Ordinal.opow_le_opow_left
theorem left_le_opow (a : Ordinal) {b : Ordinal} (b1 : 0 < b) : a ≤ a ^ b := by
nth_rw 1 [← opow_one a]
cases' le_or_gt a 1 with a1 a1
· rcases lt_or_eq_of_le a1 with a0 | a1
· rw [lt_one_iff_zero] at a0
rw [a0, zero_opow Ordinal.one_ne_zero]
exact Ordinal.zero_le _
rw [a1, one_opow, one_opow]
rwa [opow_le_opow_iff_right a1, one_le_iff_pos]
#align ordinal.left_le_opow Ordinal.left_le_opow
theorem right_le_opow {a : Ordinal} (b : Ordinal) (a1 : 1 < a) : b ≤ a ^ b :=
(opow_isNormal a1).self_le _
#align ordinal.right_le_opow Ordinal.right_le_opow
theorem opow_lt_opow_left_of_succ {a b c : Ordinal} (ab : a < b) : a ^ succ c < b ^ succ c := by
rw [opow_succ, opow_succ]
exact
(mul_le_mul_right' (opow_le_opow_left c ab.le) a).trans_lt
(mul_lt_mul_of_pos_left ab (opow_pos c ((Ordinal.zero_le a).trans_lt ab)))
#align ordinal.opow_lt_opow_left_of_succ Ordinal.opow_lt_opow_left_of_succ
theorem opow_add (a b c : Ordinal) : a ^ (b + c) = a ^ b * a ^ c := by
rcases eq_or_ne a 0 with (rfl | a0)
· rcases eq_or_ne c 0 with (rfl | c0)
· simp
have : b + c ≠ 0 := ((Ordinal.pos_iff_ne_zero.2 c0).trans_le (le_add_left _ _)).ne'
simp only [zero_opow c0, zero_opow this, mul_zero]
rcases eq_or_lt_of_le (one_le_iff_ne_zero.2 a0) with (rfl | a1)
· simp only [one_opow, mul_one]
induction c using limitRecOn with
| H₁ => simp
| H₂ c IH =>
rw [add_succ, opow_succ, IH, opow_succ, mul_assoc]
| H₃ c l IH =>
refine
eq_of_forall_ge_iff fun d =>
(((opow_isNormal a1).trans (add_isNormal b)).limit_le l).trans ?_
dsimp only [Function.comp_def]
simp (config := { contextual := true }) only [IH]
exact
(((mul_isNormal <| opow_pos b (Ordinal.pos_iff_ne_zero.2 a0)).trans
(opow_isNormal a1)).limit_le
l).symm
#align ordinal.opow_add Ordinal.opow_add
theorem opow_one_add (a b : Ordinal) : a ^ (1 + b) = a * a ^ b := by rw [opow_add, opow_one]
#align ordinal.opow_one_add Ordinal.opow_one_add
theorem opow_dvd_opow (a : Ordinal) {b c : Ordinal} (h : b ≤ c) : a ^ b ∣ a ^ c :=
⟨a ^ (c - b), by rw [← opow_add, Ordinal.add_sub_cancel_of_le h]⟩
#align ordinal.opow_dvd_opow Ordinal.opow_dvd_opow
theorem opow_dvd_opow_iff {a b c : Ordinal} (a1 : 1 < a) : a ^ b ∣ a ^ c ↔ b ≤ c :=
⟨fun h =>
le_of_not_lt fun hn =>
not_le_of_lt ((opow_lt_opow_iff_right a1).2 hn) <|
le_of_dvd (opow_ne_zero _ <| one_le_iff_ne_zero.1 <| a1.le) h,
opow_dvd_opow _⟩
#align ordinal.opow_dvd_opow_iff Ordinal.opow_dvd_opow_iff
theorem opow_mul (a b c : Ordinal) : a ^ (b * c) = (a ^ b) ^ c := by
by_cases b0 : b = 0; · simp only [b0, zero_mul, opow_zero, one_opow]
by_cases a0 : a = 0
· subst a
by_cases c0 : c = 0
· simp only [c0, mul_zero, opow_zero]
simp only [zero_opow b0, zero_opow c0, zero_opow (mul_ne_zero b0 c0)]
cases' eq_or_lt_of_le (one_le_iff_ne_zero.2 a0) with a1 a1
· subst a1
simp only [one_opow]
induction c using limitRecOn with
| H₁ => simp only [mul_zero, opow_zero]
| H₂ c IH =>
rw [mul_succ, opow_add, IH, opow_succ]
| H₃ c l IH =>
refine
eq_of_forall_ge_iff fun d =>
(((opow_isNormal a1).trans (mul_isNormal (Ordinal.pos_iff_ne_zero.2 b0))).limit_le
l).trans
?_
dsimp only [Function.comp_def]
simp (config := { contextual := true }) only [IH]
exact (opow_le_of_limit (opow_ne_zero _ a0) l).symm
#align ordinal.opow_mul Ordinal.opow_mul
/-! ### Ordinal logarithm -/
/-- The ordinal logarithm is the solution `u` to the equation `x = b ^ u * v + w` where `v < b` and
`w < b ^ u`. -/
-- @[pp_nodot] -- Porting note: Unknown attribute.
def log (b : Ordinal) (x : Ordinal) : Ordinal :=
if _h : 1 < b then pred (sInf { o | x < b ^ o }) else 0
#align ordinal.log Ordinal.log
/-- The set in the definition of `log` is nonempty. -/
theorem log_nonempty {b x : Ordinal} (h : 1 < b) : { o : Ordinal | x < b ^ o }.Nonempty :=
⟨_, succ_le_iff.1 (right_le_opow _ h)⟩
#align ordinal.log_nonempty Ordinal.log_nonempty
theorem log_def {b : Ordinal} (h : 1 < b) (x : Ordinal) :
log b x = pred (sInf { o | x < b ^ o }) := by simp only [log, dif_pos h]
#align ordinal.log_def Ordinal.log_def
theorem log_of_not_one_lt_left {b : Ordinal} (h : ¬1 < b) (x : Ordinal) : log b x = 0 := by
simp only [log, dif_neg h]
#align ordinal.log_of_not_one_lt_left Ordinal.log_of_not_one_lt_left
theorem log_of_left_le_one {b : Ordinal} (h : b ≤ 1) : ∀ x, log b x = 0 :=
log_of_not_one_lt_left h.not_lt
#align ordinal.log_of_left_le_one Ordinal.log_of_left_le_one
@[simp]
theorem log_zero_left : ∀ b, log 0 b = 0 :=
log_of_left_le_one zero_le_one
#align ordinal.log_zero_left Ordinal.log_zero_left
@[simp]
theorem log_zero_right (b : Ordinal) : log b 0 = 0 :=
if b1 : 1 < b then by
rw [log_def b1, ← Ordinal.le_zero, pred_le]
apply csInf_le'
dsimp
rw [succ_zero, opow_one]
exact zero_lt_one.trans b1
else by simp only [log_of_not_one_lt_left b1]
#align ordinal.log_zero_right Ordinal.log_zero_right
@[simp]
theorem log_one_left : ∀ b, log 1 b = 0 :=
log_of_left_le_one le_rfl
#align ordinal.log_one_left Ordinal.log_one_left
theorem succ_log_def {b x : Ordinal} (hb : 1 < b) (hx : x ≠ 0) :
succ (log b x) = sInf { o : Ordinal | x < b ^ o } := by
let t := sInf { o : Ordinal | x < b ^ o }
have : x < (b^t) := csInf_mem (log_nonempty hb)
rcases zero_or_succ_or_limit t with (h | h | h)
· refine ((one_le_iff_ne_zero.2 hx).not_lt ?_).elim
simpa only [h, opow_zero] using this
· rw [show log b x = pred t from log_def hb x, succ_pred_iff_is_succ.2 h]
· rcases (lt_opow_of_limit (zero_lt_one.trans hb).ne' h).1 this with ⟨a, h₁, h₂⟩
exact h₁.not_le.elim ((le_csInf_iff'' (log_nonempty hb)).1 le_rfl a h₂)
#align ordinal.succ_log_def Ordinal.succ_log_def
theorem lt_opow_succ_log_self {b : Ordinal} (hb : 1 < b) (x : Ordinal) :
x < b ^ succ (log b x) := by
rcases eq_or_ne x 0 with (rfl | hx)
· apply opow_pos _ (zero_lt_one.trans hb)
· rw [succ_log_def hb hx]
exact csInf_mem (log_nonempty hb)
#align ordinal.lt_opow_succ_log_self Ordinal.lt_opow_succ_log_self
theorem opow_log_le_self (b : Ordinal) {x : Ordinal} (hx : x ≠ 0) : b ^ log b x ≤ x := by
rcases eq_or_ne b 0 with (rfl | b0)
· rw [zero_opow']
exact (sub_le_self _ _).trans (one_le_iff_ne_zero.2 hx)
rcases lt_or_eq_of_le (one_le_iff_ne_zero.2 b0) with (hb | rfl)
· refine le_of_not_lt fun h => (lt_succ (log b x)).not_le ?_
have := @csInf_le' _ _ { o | x < b ^ o } _ h
rwa [← succ_log_def hb hx] at this
· rwa [one_opow, one_le_iff_ne_zero]
#align ordinal.opow_log_le_self Ordinal.opow_log_le_self
/-- `opow b` and `log b` (almost) form a Galois connection. -/
theorem opow_le_iff_le_log {b x c : Ordinal} (hb : 1 < b) (hx : x ≠ 0) : b ^ c ≤ x ↔ c ≤ log b x :=
⟨fun h =>
le_of_not_lt fun hn =>
(lt_opow_succ_log_self hb x).not_le <|
((opow_le_opow_iff_right hb).2 (succ_le_of_lt hn)).trans h,
fun h => ((opow_le_opow_iff_right hb).2 h).trans (opow_log_le_self b hx)⟩
#align ordinal.opow_le_iff_le_log Ordinal.opow_le_iff_le_log
theorem lt_opow_iff_log_lt {b x c : Ordinal} (hb : 1 < b) (hx : x ≠ 0) : x < b ^ c ↔ log b x < c :=
lt_iff_lt_of_le_iff_le (opow_le_iff_le_log hb hx)
#align ordinal.lt_opow_iff_log_lt Ordinal.lt_opow_iff_log_lt
| Mathlib/SetTheory/Ordinal/Exponential.lean | 343 | 344 | theorem log_pos {b o : Ordinal} (hb : 1 < b) (ho : o ≠ 0) (hbo : b ≤ o) : 0 < log b o := by |
rwa [← succ_le_iff, succ_zero, ← opow_le_iff_le_log hb ho, opow_one]
|
/-
Copyright (c) 2017 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro
-/
import Mathlib.Logic.Relation
import Mathlib.Data.Option.Basic
import Mathlib.Data.Seq.Seq
#align_import data.seq.wseq from "leanprover-community/mathlib"@"a7e36e48519ab281320c4d192da6a7b348ce40ad"
/-!
# Partially defined possibly infinite lists
This file provides a `WSeq α` type representing partially defined possibly infinite lists
(referred here as weak sequences).
-/
namespace Stream'
open Function
universe u v w
/-
coinductive WSeq (α : Type u) : Type u
| nil : WSeq α
| cons : α → WSeq α → WSeq α
| think : WSeq α → WSeq α
-/
/-- Weak sequences.
While the `Seq` structure allows for lists which may not be finite,
a weak sequence also allows the computation of each element to
involve an indeterminate amount of computation, including possibly
an infinite loop. This is represented as a regular `Seq` interspersed
with `none` elements to indicate that computation is ongoing.
This model is appropriate for Haskell style lazy lists, and is closed
under most interesting computation patterns on infinite lists,
but conversely it is difficult to extract elements from it. -/
def WSeq (α) :=
Seq (Option α)
#align stream.wseq Stream'.WSeq
/-
coinductive WSeq (α : Type u) : Type u
| nil : WSeq α
| cons : α → WSeq α → WSeq α
| think : WSeq α → WSeq α
-/
namespace WSeq
variable {α : Type u} {β : Type v} {γ : Type w}
/-- Turn a sequence into a weak sequence -/
@[coe]
def ofSeq : Seq α → WSeq α :=
(· <$> ·) some
#align stream.wseq.of_seq Stream'.WSeq.ofSeq
/-- Turn a list into a weak sequence -/
@[coe]
def ofList (l : List α) : WSeq α :=
ofSeq l
#align stream.wseq.of_list Stream'.WSeq.ofList
/-- Turn a stream into a weak sequence -/
@[coe]
def ofStream (l : Stream' α) : WSeq α :=
ofSeq l
#align stream.wseq.of_stream Stream'.WSeq.ofStream
instance coeSeq : Coe (Seq α) (WSeq α) :=
⟨ofSeq⟩
#align stream.wseq.coe_seq Stream'.WSeq.coeSeq
instance coeList : Coe (List α) (WSeq α) :=
⟨ofList⟩
#align stream.wseq.coe_list Stream'.WSeq.coeList
instance coeStream : Coe (Stream' α) (WSeq α) :=
⟨ofStream⟩
#align stream.wseq.coe_stream Stream'.WSeq.coeStream
/-- The empty weak sequence -/
def nil : WSeq α :=
Seq.nil
#align stream.wseq.nil Stream'.WSeq.nil
instance inhabited : Inhabited (WSeq α) :=
⟨nil⟩
#align stream.wseq.inhabited Stream'.WSeq.inhabited
/-- Prepend an element to a weak sequence -/
def cons (a : α) : WSeq α → WSeq α :=
Seq.cons (some a)
#align stream.wseq.cons Stream'.WSeq.cons
/-- Compute for one tick, without producing any elements -/
def think : WSeq α → WSeq α :=
Seq.cons none
#align stream.wseq.think Stream'.WSeq.think
/-- Destruct a weak sequence, to (eventually possibly) produce either
`none` for `nil` or `some (a, s)` if an element is produced. -/
def destruct : WSeq α → Computation (Option (α × WSeq α)) :=
Computation.corec fun s =>
match Seq.destruct s with
| none => Sum.inl none
| some (none, s') => Sum.inr s'
| some (some a, s') => Sum.inl (some (a, s'))
#align stream.wseq.destruct Stream'.WSeq.destruct
/-- Recursion principle for weak sequences, compare with `List.recOn`. -/
def recOn {C : WSeq α → Sort v} (s : WSeq α) (h1 : C nil) (h2 : ∀ x s, C (cons x s))
(h3 : ∀ s, C (think s)) : C s :=
Seq.recOn s h1 fun o => Option.recOn o h3 h2
#align stream.wseq.rec_on Stream'.WSeq.recOn
/-- membership for weak sequences-/
protected def Mem (a : α) (s : WSeq α) :=
Seq.Mem (some a) s
#align stream.wseq.mem Stream'.WSeq.Mem
instance membership : Membership α (WSeq α) :=
⟨WSeq.Mem⟩
#align stream.wseq.has_mem Stream'.WSeq.membership
theorem not_mem_nil (a : α) : a ∉ @nil α :=
Seq.not_mem_nil (some a)
#align stream.wseq.not_mem_nil Stream'.WSeq.not_mem_nil
/-- Get the head of a weak sequence. This involves a possibly
infinite computation. -/
def head (s : WSeq α) : Computation (Option α) :=
Computation.map (Prod.fst <$> ·) (destruct s)
#align stream.wseq.head Stream'.WSeq.head
/-- Encode a computation yielding a weak sequence into additional
`think` constructors in a weak sequence -/
def flatten : Computation (WSeq α) → WSeq α :=
Seq.corec fun c =>
match Computation.destruct c with
| Sum.inl s => Seq.omap (return ·) (Seq.destruct s)
| Sum.inr c' => some (none, c')
#align stream.wseq.flatten Stream'.WSeq.flatten
/-- Get the tail of a weak sequence. This doesn't need a `Computation`
wrapper, unlike `head`, because `flatten` allows us to hide this
in the construction of the weak sequence itself. -/
def tail (s : WSeq α) : WSeq α :=
flatten <| (fun o => Option.recOn o nil Prod.snd) <$> destruct s
#align stream.wseq.tail Stream'.WSeq.tail
/-- drop the first `n` elements from `s`. -/
def drop (s : WSeq α) : ℕ → WSeq α
| 0 => s
| n + 1 => tail (drop s n)
#align stream.wseq.drop Stream'.WSeq.drop
/-- Get the nth element of `s`. -/
def get? (s : WSeq α) (n : ℕ) : Computation (Option α) :=
head (drop s n)
#align stream.wseq.nth Stream'.WSeq.get?
/-- Convert `s` to a list (if it is finite and completes in finite time). -/
def toList (s : WSeq α) : Computation (List α) :=
@Computation.corec (List α) (List α × WSeq α)
(fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => Sum.inl l.reverse
| some (none, s') => Sum.inr (l, s')
| some (some a, s') => Sum.inr (a::l, s'))
([], s)
#align stream.wseq.to_list Stream'.WSeq.toList
/-- Get the length of `s` (if it is finite and completes in finite time). -/
def length (s : WSeq α) : Computation ℕ :=
@Computation.corec ℕ (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s with
| none => Sum.inl n
| some (none, s') => Sum.inr (n, s')
| some (some _, s') => Sum.inr (n + 1, s'))
(0, s)
#align stream.wseq.length Stream'.WSeq.length
/-- A weak sequence is finite if `toList s` terminates. Equivalently,
it is a finite number of `think` and `cons` applied to `nil`. -/
class IsFinite (s : WSeq α) : Prop where
out : (toList s).Terminates
#align stream.wseq.is_finite Stream'.WSeq.IsFinite
instance toList_terminates (s : WSeq α) [h : IsFinite s] : (toList s).Terminates :=
h.out
#align stream.wseq.to_list_terminates Stream'.WSeq.toList_terminates
/-- Get the list corresponding to a finite weak sequence. -/
def get (s : WSeq α) [IsFinite s] : List α :=
(toList s).get
#align stream.wseq.get Stream'.WSeq.get
/-- A weak sequence is *productive* if it never stalls forever - there are
always a finite number of `think`s between `cons` constructors.
The sequence itself is allowed to be infinite though. -/
class Productive (s : WSeq α) : Prop where
get?_terminates : ∀ n, (get? s n).Terminates
#align stream.wseq.productive Stream'.WSeq.Productive
#align stream.wseq.productive.nth_terminates Stream'.WSeq.Productive.get?_terminates
theorem productive_iff (s : WSeq α) : Productive s ↔ ∀ n, (get? s n).Terminates :=
⟨fun h => h.1, fun h => ⟨h⟩⟩
#align stream.wseq.productive_iff Stream'.WSeq.productive_iff
instance get?_terminates (s : WSeq α) [h : Productive s] : ∀ n, (get? s n).Terminates :=
h.get?_terminates
#align stream.wseq.nth_terminates Stream'.WSeq.get?_terminates
instance head_terminates (s : WSeq α) [Productive s] : (head s).Terminates :=
s.get?_terminates 0
#align stream.wseq.head_terminates Stream'.WSeq.head_terminates
/-- Replace the `n`th element of `s` with `a`. -/
def updateNth (s : WSeq α) (n : ℕ) (a : α) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s, n with
| none, _ => none
| some (none, s'), n => some (none, n, s')
| some (some a', s'), 0 => some (some a', 0, s')
| some (some _, s'), 1 => some (some a, 0, s')
| some (some a', s'), n + 2 => some (some a', n + 1, s'))
(n + 1, s)
#align stream.wseq.update_nth Stream'.WSeq.updateNth
/-- Remove the `n`th element of `s`. -/
def removeNth (s : WSeq α) (n : ℕ) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match Seq.destruct s, n with
| none, _ => none
| some (none, s'), n => some (none, n, s')
| some (some a', s'), 0 => some (some a', 0, s')
| some (some _, s'), 1 => some (none, 0, s')
| some (some a', s'), n + 2 => some (some a', n + 1, s'))
(n + 1, s)
#align stream.wseq.remove_nth Stream'.WSeq.removeNth
/-- Map the elements of `s` over `f`, removing any values that yield `none`. -/
def filterMap (f : α → Option β) : WSeq α → WSeq β :=
Seq.corec fun s =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, s')
| some (some a, s') => some (f a, s')
#align stream.wseq.filter_map Stream'.WSeq.filterMap
/-- Select the elements of `s` that satisfy `p`. -/
def filter (p : α → Prop) [DecidablePred p] : WSeq α → WSeq α :=
filterMap fun a => if p a then some a else none
#align stream.wseq.filter Stream'.WSeq.filter
-- example of infinite list manipulations
/-- Get the first element of `s` satisfying `p`. -/
def find (p : α → Prop) [DecidablePred p] (s : WSeq α) : Computation (Option α) :=
head <| filter p s
#align stream.wseq.find Stream'.WSeq.find
/-- Zip a function over two weak sequences -/
def zipWith (f : α → β → γ) (s1 : WSeq α) (s2 : WSeq β) : WSeq γ :=
@Seq.corec (Option γ) (WSeq α × WSeq β)
(fun ⟨s1, s2⟩ =>
match Seq.destruct s1, Seq.destruct s2 with
| some (none, s1'), some (none, s2') => some (none, s1', s2')
| some (some _, _), some (none, s2') => some (none, s1, s2')
| some (none, s1'), some (some _, _) => some (none, s1', s2)
| some (some a1, s1'), some (some a2, s2') => some (some (f a1 a2), s1', s2')
| _, _ => none)
(s1, s2)
#align stream.wseq.zip_with Stream'.WSeq.zipWith
/-- Zip two weak sequences into a single sequence of pairs -/
def zip : WSeq α → WSeq β → WSeq (α × β) :=
zipWith Prod.mk
#align stream.wseq.zip Stream'.WSeq.zip
/-- Get the list of indexes of elements of `s` satisfying `p` -/
def findIndexes (p : α → Prop) [DecidablePred p] (s : WSeq α) : WSeq ℕ :=
(zip s (Stream'.nats : WSeq ℕ)).filterMap fun ⟨a, n⟩ => if p a then some n else none
#align stream.wseq.find_indexes Stream'.WSeq.findIndexes
/-- Get the index of the first element of `s` satisfying `p` -/
def findIndex (p : α → Prop) [DecidablePred p] (s : WSeq α) : Computation ℕ :=
(fun o => Option.getD o 0) <$> head (findIndexes p s)
#align stream.wseq.find_index Stream'.WSeq.findIndex
/-- Get the index of the first occurrence of `a` in `s` -/
def indexOf [DecidableEq α] (a : α) : WSeq α → Computation ℕ :=
findIndex (Eq a)
#align stream.wseq.index_of Stream'.WSeq.indexOf
/-- Get the indexes of occurrences of `a` in `s` -/
def indexesOf [DecidableEq α] (a : α) : WSeq α → WSeq ℕ :=
findIndexes (Eq a)
#align stream.wseq.indexes_of Stream'.WSeq.indexesOf
/-- `union s1 s2` is a weak sequence which interleaves `s1` and `s2` in
some order (nondeterministically). -/
def union (s1 s2 : WSeq α) : WSeq α :=
@Seq.corec (Option α) (WSeq α × WSeq α)
(fun ⟨s1, s2⟩ =>
match Seq.destruct s1, Seq.destruct s2 with
| none, none => none
| some (a1, s1'), none => some (a1, s1', nil)
| none, some (a2, s2') => some (a2, nil, s2')
| some (none, s1'), some (none, s2') => some (none, s1', s2')
| some (some a1, s1'), some (none, s2') => some (some a1, s1', s2')
| some (none, s1'), some (some a2, s2') => some (some a2, s1', s2')
| some (some a1, s1'), some (some a2, s2') => some (some a1, cons a2 s1', s2'))
(s1, s2)
#align stream.wseq.union Stream'.WSeq.union
/-- Returns `true` if `s` is `nil` and `false` if `s` has an element -/
def isEmpty (s : WSeq α) : Computation Bool :=
Computation.map Option.isNone <| head s
#align stream.wseq.is_empty Stream'.WSeq.isEmpty
/-- Calculate one step of computation -/
def compute (s : WSeq α) : WSeq α :=
match Seq.destruct s with
| some (none, s') => s'
| _ => s
#align stream.wseq.compute Stream'.WSeq.compute
/-- Get the first `n` elements of a weak sequence -/
def take (s : WSeq α) (n : ℕ) : WSeq α :=
@Seq.corec (Option α) (ℕ × WSeq α)
(fun ⟨n, s⟩ =>
match n, Seq.destruct s with
| 0, _ => none
| _ + 1, none => none
| m + 1, some (none, s') => some (none, m + 1, s')
| m + 1, some (some a, s') => some (some a, m, s'))
(n, s)
#align stream.wseq.take Stream'.WSeq.take
/-- Split the sequence at position `n` into a finite initial segment
and the weak sequence tail -/
def splitAt (s : WSeq α) (n : ℕ) : Computation (List α × WSeq α) :=
@Computation.corec (List α × WSeq α) (ℕ × List α × WSeq α)
(fun ⟨n, l, s⟩ =>
match n, Seq.destruct s with
| 0, _ => Sum.inl (l.reverse, s)
| _ + 1, none => Sum.inl (l.reverse, s)
| _ + 1, some (none, s') => Sum.inr (n, l, s')
| m + 1, some (some a, s') => Sum.inr (m, a::l, s'))
(n, [], s)
#align stream.wseq.split_at Stream'.WSeq.splitAt
/-- Returns `true` if any element of `s` satisfies `p` -/
def any (s : WSeq α) (p : α → Bool) : Computation Bool :=
Computation.corec
(fun s : WSeq α =>
match Seq.destruct s with
| none => Sum.inl false
| some (none, s') => Sum.inr s'
| some (some a, s') => if p a then Sum.inl true else Sum.inr s')
s
#align stream.wseq.any Stream'.WSeq.any
/-- Returns `true` if every element of `s` satisfies `p` -/
def all (s : WSeq α) (p : α → Bool) : Computation Bool :=
Computation.corec
(fun s : WSeq α =>
match Seq.destruct s with
| none => Sum.inl true
| some (none, s') => Sum.inr s'
| some (some a, s') => if p a then Sum.inr s' else Sum.inl false)
s
#align stream.wseq.all Stream'.WSeq.all
/-- Apply a function to the elements of the sequence to produce a sequence
of partial results. (There is no `scanr` because this would require
working from the end of the sequence, which may not exist.) -/
def scanl (f : α → β → α) (a : α) (s : WSeq β) : WSeq α :=
cons a <|
@Seq.corec (Option α) (α × WSeq β)
(fun ⟨a, s⟩ =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, a, s')
| some (some b, s') =>
let a' := f a b
some (some a', a', s'))
(a, s)
#align stream.wseq.scanl Stream'.WSeq.scanl
/-- Get the weak sequence of initial segments of the input sequence -/
def inits (s : WSeq α) : WSeq (List α) :=
cons [] <|
@Seq.corec (Option (List α)) (Batteries.DList α × WSeq α)
(fun ⟨l, s⟩ =>
match Seq.destruct s with
| none => none
| some (none, s') => some (none, l, s')
| some (some a, s') =>
let l' := l.push a
some (some l'.toList, l', s'))
(Batteries.DList.empty, s)
#align stream.wseq.inits Stream'.WSeq.inits
/-- Like take, but does not wait for a result. Calculates `n` steps of
computation and returns the sequence computed so far -/
def collect (s : WSeq α) (n : ℕ) : List α :=
(Seq.take n s).filterMap id
#align stream.wseq.collect Stream'.WSeq.collect
/-- Append two weak sequences. As with `Seq.append`, this may not use
the second sequence if the first one takes forever to compute -/
def append : WSeq α → WSeq α → WSeq α :=
Seq.append
#align stream.wseq.append Stream'.WSeq.append
/-- Map a function over a weak sequence -/
def map (f : α → β) : WSeq α → WSeq β :=
Seq.map (Option.map f)
#align stream.wseq.map Stream'.WSeq.map
/-- Flatten a sequence of weak sequences. (Note that this allows
empty sequences, unlike `Seq.join`.) -/
def join (S : WSeq (WSeq α)) : WSeq α :=
Seq.join
((fun o : Option (WSeq α) =>
match o with
| none => Seq1.ret none
| some s => (none, s)) <$>
S)
#align stream.wseq.join Stream'.WSeq.join
/-- Monadic bind operator for weak sequences -/
def bind (s : WSeq α) (f : α → WSeq β) : WSeq β :=
join (map f s)
#align stream.wseq.bind Stream'.WSeq.bind
/-- lift a relation to a relation over weak sequences -/
@[simp]
def LiftRelO (R : α → β → Prop) (C : WSeq α → WSeq β → Prop) :
Option (α × WSeq α) → Option (β × WSeq β) → Prop
| none, none => True
| some (a, s), some (b, t) => R a b ∧ C s t
| _, _ => False
#align stream.wseq.lift_rel_o Stream'.WSeq.LiftRelO
theorem LiftRelO.imp {R S : α → β → Prop} {C D : WSeq α → WSeq β → Prop} (H1 : ∀ a b, R a b → S a b)
(H2 : ∀ s t, C s t → D s t) : ∀ {o p}, LiftRelO R C o p → LiftRelO S D o p
| none, none, _ => trivial
| some (_, _), some (_, _), h => And.imp (H1 _ _) (H2 _ _) h
| none, some _, h => False.elim h
| some (_, _), none, h => False.elim h
#align stream.wseq.lift_rel_o.imp Stream'.WSeq.LiftRelO.imp
theorem LiftRelO.imp_right (R : α → β → Prop) {C D : WSeq α → WSeq β → Prop}
(H : ∀ s t, C s t → D s t) {o p} : LiftRelO R C o p → LiftRelO R D o p :=
LiftRelO.imp (fun _ _ => id) H
#align stream.wseq.lift_rel_o.imp_right Stream'.WSeq.LiftRelO.imp_right
/-- Definition of bisimilarity for weak sequences-/
@[simp]
def BisimO (R : WSeq α → WSeq α → Prop) : Option (α × WSeq α) → Option (α × WSeq α) → Prop :=
LiftRelO (· = ·) R
#align stream.wseq.bisim_o Stream'.WSeq.BisimO
theorem BisimO.imp {R S : WSeq α → WSeq α → Prop} (H : ∀ s t, R s t → S s t) {o p} :
BisimO R o p → BisimO S o p :=
LiftRelO.imp_right _ H
#align stream.wseq.bisim_o.imp Stream'.WSeq.BisimO.imp
/-- Two weak sequences are `LiftRel R` related if they are either both empty,
or they are both nonempty and the heads are `R` related and the tails are
`LiftRel R` related. (This is a coinductive definition.) -/
def LiftRel (R : α → β → Prop) (s : WSeq α) (t : WSeq β) : Prop :=
∃ C : WSeq α → WSeq β → Prop,
C s t ∧ ∀ {s t}, C s t → Computation.LiftRel (LiftRelO R C) (destruct s) (destruct t)
#align stream.wseq.lift_rel Stream'.WSeq.LiftRel
/-- If two sequences are equivalent, then they have the same values and
the same computational behavior (i.e. if one loops forever then so does
the other), although they may differ in the number of `think`s needed to
arrive at the answer. -/
def Equiv : WSeq α → WSeq α → Prop :=
LiftRel (· = ·)
#align stream.wseq.equiv Stream'.WSeq.Equiv
theorem liftRel_destruct {R : α → β → Prop} {s : WSeq α} {t : WSeq β} :
LiftRel R s t → Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t)
| ⟨R, h1, h2⟩ => by
refine Computation.LiftRel.imp ?_ _ _ (h2 h1)
apply LiftRelO.imp_right
exact fun s' t' h' => ⟨R, h', @h2⟩
#align stream.wseq.lift_rel_destruct Stream'.WSeq.liftRel_destruct
theorem liftRel_destruct_iff {R : α → β → Prop} {s : WSeq α} {t : WSeq β} :
LiftRel R s t ↔ Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t) :=
⟨liftRel_destruct, fun h =>
⟨fun s t =>
LiftRel R s t ∨ Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t),
Or.inr h, fun {s t} h => by
have h : Computation.LiftRel (LiftRelO R (LiftRel R)) (destruct s) (destruct t) := by
cases' h with h h
· exact liftRel_destruct h
· assumption
apply Computation.LiftRel.imp _ _ _ h
intro a b
apply LiftRelO.imp_right
intro s t
apply Or.inl⟩⟩
#align stream.wseq.lift_rel_destruct_iff Stream'.WSeq.liftRel_destruct_iff
-- Porting note: To avoid ambiguous notation, `~` became `~ʷ`.
infixl:50 " ~ʷ " => Equiv
theorem destruct_congr {s t : WSeq α} :
s ~ʷ t → Computation.LiftRel (BisimO (· ~ʷ ·)) (destruct s) (destruct t) :=
liftRel_destruct
#align stream.wseq.destruct_congr Stream'.WSeq.destruct_congr
theorem destruct_congr_iff {s t : WSeq α} :
s ~ʷ t ↔ Computation.LiftRel (BisimO (· ~ʷ ·)) (destruct s) (destruct t) :=
liftRel_destruct_iff
#align stream.wseq.destruct_congr_iff Stream'.WSeq.destruct_congr_iff
theorem LiftRel.refl (R : α → α → Prop) (H : Reflexive R) : Reflexive (LiftRel R) := fun s => by
refine ⟨(· = ·), rfl, fun {s t} (h : s = t) => ?_⟩
rw [← h]
apply Computation.LiftRel.refl
intro a
cases' a with a
· simp
· cases a
simp only [LiftRelO, and_true]
apply H
#align stream.wseq.lift_rel.refl Stream'.WSeq.LiftRel.refl
| Mathlib/Data/Seq/WSeq.lean | 546 | 549 | theorem LiftRelO.swap (R : α → β → Prop) (C) :
swap (LiftRelO R C) = LiftRelO (swap R) (swap C) := by |
funext x y
rcases x with ⟨⟩ | ⟨hx, jx⟩ <;> rcases y with ⟨⟩ | ⟨hy, jy⟩ <;> 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.Topology.Separation
#align_import topology.sober from "leanprover-community/mathlib"@"0a0ec35061ed9960bf0e7ffb0335f44447b58977"
/-!
# Sober spaces
A quasi-sober space is a topological space where every
irreducible closed subset has a generic point.
A sober space is a quasi-sober space where every irreducible closed subset
has a *unique* generic point. This is if and only if the space is T0, and thus sober spaces can be
stated via `[QuasiSober α] [T0Space α]`.
## Main definition
* `IsGenericPoint` : `x` is the generic point of `S` if `S` is the closure of `x`.
* `QuasiSober` : A space is quasi-sober if every irreducible closed subset has a generic point.
-/
open Set
variable {α β : Type*} [TopologicalSpace α] [TopologicalSpace β]
section genericPoint
/-- `x` is a generic point of `S` if `S` is the closure of `x`. -/
def IsGenericPoint (x : α) (S : Set α) : Prop :=
closure ({x} : Set α) = S
#align is_generic_point IsGenericPoint
theorem isGenericPoint_def {x : α} {S : Set α} : IsGenericPoint x S ↔ closure ({x} : Set α) = S :=
Iff.rfl
#align is_generic_point_def isGenericPoint_def
theorem IsGenericPoint.def {x : α} {S : Set α} (h : IsGenericPoint x S) :
closure ({x} : Set α) = S :=
h
#align is_generic_point.def IsGenericPoint.def
theorem isGenericPoint_closure {x : α} : IsGenericPoint x (closure ({x} : Set α)) :=
refl _
#align is_generic_point_closure isGenericPoint_closure
variable {x y : α} {S U Z : Set α}
theorem isGenericPoint_iff_specializes : IsGenericPoint x S ↔ ∀ y, x ⤳ y ↔ y ∈ S := by
simp only [specializes_iff_mem_closure, IsGenericPoint, Set.ext_iff]
#align is_generic_point_iff_specializes isGenericPoint_iff_specializes
namespace IsGenericPoint
theorem specializes_iff_mem (h : IsGenericPoint x S) : x ⤳ y ↔ y ∈ S :=
isGenericPoint_iff_specializes.1 h y
#align is_generic_point.specializes_iff_mem IsGenericPoint.specializes_iff_mem
protected theorem specializes (h : IsGenericPoint x S) (h' : y ∈ S) : x ⤳ y :=
h.specializes_iff_mem.2 h'
#align is_generic_point.specializes IsGenericPoint.specializes
protected theorem mem (h : IsGenericPoint x S) : x ∈ S :=
h.specializes_iff_mem.1 specializes_rfl
#align is_generic_point.mem IsGenericPoint.mem
protected theorem isClosed (h : IsGenericPoint x S) : IsClosed S :=
h.def ▸ isClosed_closure
#align is_generic_point.is_closed IsGenericPoint.isClosed
protected theorem isIrreducible (h : IsGenericPoint x S) : IsIrreducible S :=
h.def ▸ isIrreducible_singleton.closure
#align is_generic_point.is_irreducible IsGenericPoint.isIrreducible
protected theorem inseparable (h : IsGenericPoint x S) (h' : IsGenericPoint y S) :
Inseparable x y :=
(h.specializes h'.mem).antisymm (h'.specializes h.mem)
/-- In a T₀ space, each set has at most one generic point. -/
protected theorem eq [T0Space α] (h : IsGenericPoint x S) (h' : IsGenericPoint y S) : x = y :=
(h.inseparable h').eq
#align is_generic_point.eq IsGenericPoint.eq
theorem mem_open_set_iff (h : IsGenericPoint x S) (hU : IsOpen U) : x ∈ U ↔ (S ∩ U).Nonempty :=
⟨fun h' => ⟨x, h.mem, h'⟩, fun ⟨_y, hyS, hyU⟩ => (h.specializes hyS).mem_open hU hyU⟩
#align is_generic_point.mem_open_set_iff IsGenericPoint.mem_open_set_iff
| Mathlib/Topology/Sober.lean | 92 | 93 | theorem disjoint_iff (h : IsGenericPoint x S) (hU : IsOpen U) : Disjoint S U ↔ x ∉ U := by |
rw [h.mem_open_set_iff hU, ← not_disjoint_iff_nonempty_inter, Classical.not_not]
|
/-
Copyright (c) 2019 Mario Carneiro. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Mario Carneiro, Scott Morrison
-/
import Mathlib.Algebra.Order.Hom.Monoid
import Mathlib.SetTheory.Game.Ordinal
#align_import set_theory.surreal.basic from "leanprover-community/mathlib"@"8900d545017cd21961daa2a1734bb658ef52c618"
/-!
# Surreal numbers
The basic theory of surreal numbers, built on top of the theory of combinatorial (pre-)games.
A pregame is `Numeric` if all the Left options are strictly smaller than all the Right options, and
all those options are themselves numeric. In terms of combinatorial games, the numeric games have
"frozen"; you can only make your position worse by playing, and Left is some definite "number" of
moves ahead (or behind) Right.
A surreal number is an equivalence class of numeric pregames.
In fact, the surreals form a complete ordered field, containing a copy of the reals (and much else
besides!) but we do not yet have a complete development.
## Order properties
Surreal numbers inherit the relations `≤` and `<` from games (`Surreal.instLE` and
`Surreal.instLT`), and these relations satisfy the axioms of a partial order.
## Algebraic operations
We show that the surreals form a linear ordered commutative group.
One can also map all the ordinals into the surreals!
### Multiplication of surreal numbers
The proof that multiplication lifts to surreal numbers is surprisingly difficult and is currently
missing in the library. A sample proof can be found in Theorem 3.8 in the second reference below.
The difficulty lies in the length of the proof and the number of theorems that need to proven
simultaneously. This will make for a fun and challenging project.
The branch `surreal_mul` contains some progress on this proof.
### Todo
- Define the field structure on the surreals.
## References
* [Conway, *On numbers and games*][conway2001]
* [Schleicher, Stoll, *An introduction to Conway's games and numbers*][schleicher_stoll]
-/
universe u
namespace SetTheory
open scoped PGame
namespace PGame
/-- A pre-game is numeric if everything in the L set is less than everything in the R set,
and all the elements of L and R are also numeric. -/
def Numeric : PGame → Prop
| ⟨_, _, L, R⟩ => (∀ i j, L i < R j) ∧ (∀ i, Numeric (L i)) ∧ ∀ j, Numeric (R j)
#align pgame.numeric SetTheory.PGame.Numeric
theorem numeric_def {x : PGame} :
Numeric x ↔
(∀ i j, x.moveLeft i < x.moveRight j) ∧
(∀ i, Numeric (x.moveLeft i)) ∧ ∀ j, Numeric (x.moveRight j) := by
cases x; rfl
#align pgame.numeric_def SetTheory.PGame.numeric_def
namespace Numeric
theorem mk {x : PGame} (h₁ : ∀ i j, x.moveLeft i < x.moveRight j) (h₂ : ∀ i, Numeric (x.moveLeft i))
(h₃ : ∀ j, Numeric (x.moveRight j)) : Numeric x :=
numeric_def.2 ⟨h₁, h₂, h₃⟩
#align pgame.numeric.mk SetTheory.PGame.Numeric.mk
theorem left_lt_right {x : PGame} (o : Numeric x) (i : x.LeftMoves) (j : x.RightMoves) :
x.moveLeft i < x.moveRight j := by cases x; exact o.1 i j
#align pgame.numeric.left_lt_right SetTheory.PGame.Numeric.left_lt_right
theorem moveLeft {x : PGame} (o : Numeric x) (i : x.LeftMoves) : Numeric (x.moveLeft i) := by
cases x; exact o.2.1 i
#align pgame.numeric.move_left SetTheory.PGame.Numeric.moveLeft
theorem moveRight {x : PGame} (o : Numeric x) (j : x.RightMoves) : Numeric (x.moveRight j) := by
cases x; exact o.2.2 j
#align pgame.numeric.move_right SetTheory.PGame.Numeric.moveRight
end Numeric
@[elab_as_elim]
theorem numeric_rec {C : PGame → Prop}
(H : ∀ (l r) (L : l → PGame) (R : r → PGame), (∀ i j, L i < R j) →
(∀ i, Numeric (L i)) → (∀ i, Numeric (R i)) → (∀ i, C (L i)) → (∀ i, C (R i)) →
C ⟨l, r, L, R⟩) :
∀ x, Numeric x → C x
| ⟨_, _, _, _⟩, ⟨h, hl, hr⟩ =>
H _ _ _ _ h hl hr (fun i => numeric_rec H _ (hl i)) fun i => numeric_rec H _ (hr i)
#align pgame.numeric_rec SetTheory.PGame.numeric_rec
theorem Relabelling.numeric_imp {x y : PGame} (r : x ≡r y) (ox : Numeric x) : Numeric y := by
induction' x using PGame.moveRecOn with x IHl IHr generalizing y
apply Numeric.mk (fun i j => ?_) (fun i => ?_) fun j => ?_
· rw [← lt_congr (r.moveLeftSymm i).equiv (r.moveRightSymm j).equiv]
apply ox.left_lt_right
· exact IHl _ (r.moveLeftSymm i) (ox.moveLeft _)
· exact IHr _ (r.moveRightSymm j) (ox.moveRight _)
#align pgame.relabelling.numeric_imp SetTheory.PGame.Relabelling.numeric_imp
/-- Relabellings preserve being numeric. -/
theorem Relabelling.numeric_congr {x y : PGame} (r : x ≡r y) : Numeric x ↔ Numeric y :=
⟨r.numeric_imp, r.symm.numeric_imp⟩
#align pgame.relabelling.numeric_congr SetTheory.PGame.Relabelling.numeric_congr
theorem lf_asymm {x y : PGame} (ox : Numeric x) (oy : Numeric y) : x ⧏ y → ¬y ⧏ x := by
refine numeric_rec (C := fun x => ∀ z (_oz : Numeric z), x ⧏ z → ¬z ⧏ x)
(fun xl xr xL xR hx _oxl _oxr IHxl IHxr => ?_) x ox y oy
refine numeric_rec fun yl yr yL yR hy oyl oyr _IHyl _IHyr => ?_
rw [mk_lf_mk, mk_lf_mk]; rintro (⟨i, h₁⟩ | ⟨j, h₁⟩) (⟨i, h₂⟩ | ⟨j, h₂⟩)
· exact IHxl _ _ (oyl _) (h₁.moveLeft_lf _) (h₂.moveLeft_lf _)
· exact (le_trans h₂ h₁).not_gf (lf_of_lt (hy _ _))
· exact (le_trans h₁ h₂).not_gf (lf_of_lt (hx _ _))
· exact IHxr _ _ (oyr _) (h₁.lf_moveRight _) (h₂.lf_moveRight _)
#align pgame.lf_asymm SetTheory.PGame.lf_asymm
theorem le_of_lf {x y : PGame} (h : x ⧏ y) (ox : Numeric x) (oy : Numeric y) : x ≤ y :=
not_lf.1 (lf_asymm ox oy h)
#align pgame.le_of_lf SetTheory.PGame.le_of_lf
alias LF.le := le_of_lf
#align pgame.lf.le SetTheory.PGame.LF.le
theorem lt_of_lf {x y : PGame} (h : x ⧏ y) (ox : Numeric x) (oy : Numeric y) : x < y :=
(lt_or_fuzzy_of_lf h).resolve_right (not_fuzzy_of_le (h.le ox oy))
#align pgame.lt_of_lf SetTheory.PGame.lt_of_lf
alias LF.lt := lt_of_lf
#align pgame.lf.lt SetTheory.PGame.LF.lt
theorem lf_iff_lt {x y : PGame} (ox : Numeric x) (oy : Numeric y) : x ⧏ y ↔ x < y :=
⟨fun h => h.lt ox oy, lf_of_lt⟩
#align pgame.lf_iff_lt SetTheory.PGame.lf_iff_lt
/-- Definition of `x ≤ y` on numeric pre-games, in terms of `<` -/
theorem le_iff_forall_lt {x y : PGame} (ox : x.Numeric) (oy : y.Numeric) :
x ≤ y ↔ (∀ i, x.moveLeft i < y) ∧ ∀ j, x < y.moveRight j := by
refine le_iff_forall_lf.trans (and_congr ?_ ?_) <;>
refine forall_congr' fun i => lf_iff_lt ?_ ?_ <;>
apply_rules [Numeric.moveLeft, Numeric.moveRight]
#align pgame.le_iff_forall_lt SetTheory.PGame.le_iff_forall_lt
/-- Definition of `x < y` on numeric pre-games, in terms of `≤` -/
theorem lt_iff_exists_le {x y : PGame} (ox : x.Numeric) (oy : y.Numeric) :
x < y ↔ (∃ i, x ≤ y.moveLeft i) ∨ ∃ j, x.moveRight j ≤ y := by
rw [← lf_iff_lt ox oy, lf_iff_exists_le]
#align pgame.lt_iff_exists_le SetTheory.PGame.lt_iff_exists_le
theorem lt_of_exists_le {x y : PGame} (ox : x.Numeric) (oy : y.Numeric) :
((∃ i, x ≤ y.moveLeft i) ∨ ∃ j, x.moveRight j ≤ y) → x < y :=
(lt_iff_exists_le ox oy).2
#align pgame.lt_of_exists_le SetTheory.PGame.lt_of_exists_le
/-- The definition of `x < y` on numeric pre-games, in terms of `<` two moves later. -/
theorem lt_def {x y : PGame} (ox : x.Numeric) (oy : y.Numeric) :
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_lt ox oy, lf_def]
refine or_congr ?_ ?_ <;> refine exists_congr fun x_1 => ?_ <;> refine and_congr ?_ ?_ <;>
refine forall_congr' fun i => lf_iff_lt ?_ ?_ <;>
apply_rules [Numeric.moveLeft, Numeric.moveRight]
#align pgame.lt_def SetTheory.PGame.lt_def
theorem not_fuzzy {x y : PGame} (ox : Numeric x) (oy : Numeric y) : ¬Fuzzy x y :=
fun h => not_lf.2 ((lf_of_fuzzy h).le ox oy) h.2
#align pgame.not_fuzzy SetTheory.PGame.not_fuzzy
theorem lt_or_equiv_or_gt {x y : PGame} (ox : Numeric x) (oy : Numeric y) :
x < y ∨ (x ≈ y) ∨ y < x :=
((lf_or_equiv_or_gf x y).imp fun h => h.lt ox oy) <| Or.imp_right fun h => h.lt oy ox
#align pgame.lt_or_equiv_or_gt SetTheory.PGame.lt_or_equiv_or_gt
theorem numeric_of_isEmpty (x : PGame) [IsEmpty x.LeftMoves] [IsEmpty x.RightMoves] : Numeric x :=
Numeric.mk isEmptyElim isEmptyElim isEmptyElim
#align pgame.numeric_of_is_empty SetTheory.PGame.numeric_of_isEmpty
theorem numeric_of_isEmpty_leftMoves (x : PGame) [IsEmpty x.LeftMoves] :
(∀ j, Numeric (x.moveRight j)) → Numeric x :=
Numeric.mk isEmptyElim isEmptyElim
#align pgame.numeric_of_is_empty_left_moves SetTheory.PGame.numeric_of_isEmpty_leftMoves
theorem numeric_of_isEmpty_rightMoves (x : PGame) [IsEmpty x.RightMoves]
(H : ∀ i, Numeric (x.moveLeft i)) : Numeric x :=
Numeric.mk (fun _ => isEmptyElim) H isEmptyElim
#align pgame.numeric_of_is_empty_right_moves SetTheory.PGame.numeric_of_isEmpty_rightMoves
theorem numeric_zero : Numeric 0 :=
numeric_of_isEmpty 0
#align pgame.numeric_zero SetTheory.PGame.numeric_zero
theorem numeric_one : Numeric 1 :=
numeric_of_isEmpty_rightMoves 1 fun _ => numeric_zero
#align pgame.numeric_one SetTheory.PGame.numeric_one
theorem Numeric.neg : ∀ {x : PGame} (_ : Numeric x), Numeric (-x)
| ⟨_, _, _, _⟩, o =>
⟨fun j i => neg_lt_neg_iff.2 (o.1 i j), fun j => (o.2.2 j).neg, fun i => (o.2.1 i).neg⟩
#align pgame.numeric.neg SetTheory.PGame.Numeric.neg
namespace Numeric
theorem moveLeft_lt {x : PGame} (o : Numeric x) (i) : x.moveLeft i < x :=
(moveLeft_lf i).lt (o.moveLeft i) o
#align pgame.numeric.move_left_lt SetTheory.PGame.Numeric.moveLeft_lt
theorem moveLeft_le {x : PGame} (o : Numeric x) (i) : x.moveLeft i ≤ x :=
(o.moveLeft_lt i).le
#align pgame.numeric.move_left_le SetTheory.PGame.Numeric.moveLeft_le
theorem lt_moveRight {x : PGame} (o : Numeric x) (j) : x < x.moveRight j :=
(lf_moveRight j).lt o (o.moveRight j)
#align pgame.numeric.lt_move_right SetTheory.PGame.Numeric.lt_moveRight
theorem le_moveRight {x : PGame} (o : Numeric x) (j) : x ≤ x.moveRight j :=
(o.lt_moveRight j).le
#align pgame.numeric.le_move_right SetTheory.PGame.Numeric.le_moveRight
theorem add : ∀ {x y : PGame} (_ : Numeric x) (_ : Numeric y), Numeric (x + y)
| ⟨xl, xr, xL, xR⟩, ⟨yl, yr, yL, yR⟩, ox, oy =>
⟨by
rintro (ix | iy) (jx | jy)
· exact add_lt_add_right (ox.1 ix jx) _
· exact (add_lf_add_of_lf_of_le (lf_mk _ _ ix) (oy.le_moveRight jy)).lt
((ox.moveLeft ix).add oy) (ox.add (oy.moveRight jy))
· exact (add_lf_add_of_lf_of_le (mk_lf _ _ jx) (oy.moveLeft_le iy)).lt
(ox.add (oy.moveLeft iy)) ((ox.moveRight jx).add oy)
· exact add_lt_add_left (oy.1 iy jy) ⟨xl, xr, xL, xR⟩, by
constructor
· rintro (ix | iy)
· exact (ox.moveLeft ix).add oy
· exact ox.add (oy.moveLeft iy)
· rintro (jx | jy)
· apply (ox.moveRight jx).add oy
· apply ox.add (oy.moveRight jy)⟩
termination_by x y => (x, y) -- Porting note: Added `termination_by`
#align pgame.numeric.add SetTheory.PGame.Numeric.add
theorem sub {x y : PGame} (ox : Numeric x) (oy : Numeric y) : Numeric (x - y) :=
ox.add oy.neg
#align pgame.numeric.sub SetTheory.PGame.Numeric.sub
end Numeric
/-- Pre-games defined by natural numbers are numeric. -/
theorem numeric_nat : ∀ n : ℕ, Numeric n
| 0 => numeric_zero
| n + 1 => (numeric_nat n).add numeric_one
#align pgame.numeric_nat SetTheory.PGame.numeric_nat
/-- Ordinal games are numeric. -/
| Mathlib/SetTheory/Surreal/Basic.lean | 269 | 272 | theorem numeric_toPGame (o : Ordinal) : o.toPGame.Numeric := by |
induction' o using Ordinal.induction with o IH
apply numeric_of_isEmpty_rightMoves
simpa using fun i => IH _ (Ordinal.toLeftMovesToPGame_symm_lt i)
|
/-
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
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
#align measure_theory.crossing_eq_crossing_of_upper_crossing_time_lt MeasureTheory.crossing_eq_crossing_of_upperCrossingTime_lt
theorem upperCrossingTime_eq_upperCrossingTime_of_lt {M : ℕ} (hNM : N ≤ M)
(h : upperCrossingTime a b f N n ω < N) :
upperCrossingTime a b f M n ω = upperCrossingTime a b f N n ω := by
cases n
· simp
· exact (crossing_eq_crossing_of_upperCrossingTime_lt hNM h).1
#align measure_theory.upper_crossing_time_eq_upper_crossing_time_of_lt MeasureTheory.upperCrossingTime_eq_upperCrossingTime_of_lt
theorem upcrossingsBefore_mono (hab : a < b) : Monotone fun N ω => upcrossingsBefore a b f N ω := by
intro N M hNM ω
simp only [upcrossingsBefore]
by_cases hemp : {n : ℕ | upperCrossingTime a b f N n ω < N}.Nonempty
· refine csSup_le_csSup (upperCrossingTime_lt_bddAbove hab) hemp fun n hn => ?_
rw [Set.mem_setOf_eq, upperCrossingTime_eq_upperCrossingTime_of_lt hNM hn]
exact lt_of_lt_of_le hn hNM
· rw [Set.not_nonempty_iff_eq_empty] at hemp
simp [hemp, csSup_empty, bot_eq_zero', zero_le']
#align measure_theory.upcrossings_before_mono MeasureTheory.upcrossingsBefore_mono
theorem upcrossingsBefore_lt_of_exists_upcrossing (hab : a < b) {N₁ N₂ : ℕ} (hN₁ : N ≤ N₁)
(hN₁' : f N₁ ω < a) (hN₂ : N₁ ≤ N₂) (hN₂' : b < f N₂ ω) :
upcrossingsBefore a b f N ω < upcrossingsBefore a b f (N₂ + 1) ω := by
refine lt_of_lt_of_le (Nat.lt_succ_self _) (le_csSup (upperCrossingTime_lt_bddAbove hab) ?_)
rw [Set.mem_setOf_eq, upperCrossingTime_succ_eq, hitting_lt_iff _ le_rfl]
refine ⟨N₂, ⟨?_, Nat.lt_succ_self _⟩, hN₂'.le⟩
rw [lowerCrossingTime, hitting_le_iff_of_lt _ (Nat.lt_succ_self _)]
refine ⟨N₁, ⟨le_trans ?_ hN₁, hN₂⟩, hN₁'.le⟩
by_cases hN : 0 < N
· have : upperCrossingTime a b f N (upcrossingsBefore a b f N ω) ω < N :=
Nat.sSup_mem (upperCrossingTime_lt_nonempty hN) (upperCrossingTime_lt_bddAbove hab)
rw [upperCrossingTime_eq_upperCrossingTime_of_lt (hN₁.trans (hN₂.trans <| Nat.le_succ _))
this]
exact this.le
· rw [not_lt, Nat.le_zero] at hN
rw [hN, upcrossingsBefore_zero, upperCrossingTime_zero]
rfl
#align measure_theory.upcrossings_before_lt_of_exists_upcrossing MeasureTheory.upcrossingsBefore_lt_of_exists_upcrossing
theorem lowerCrossingTime_lt_of_lt_upcrossingsBefore (hN : 0 < N) (hab : a < b)
(hn : n < upcrossingsBefore a b f N ω) : lowerCrossingTime a b f N n ω < N :=
lt_of_le_of_lt lowerCrossingTime_le_upperCrossingTime_succ
(upperCrossingTime_lt_of_le_upcrossingsBefore hN hab hn)
#align measure_theory.lower_crossing_time_lt_of_lt_upcrossings_before MeasureTheory.lowerCrossingTime_lt_of_lt_upcrossingsBefore
theorem le_sub_of_le_upcrossingsBefore (hN : 0 < N) (hab : a < b)
(hn : n < upcrossingsBefore a b f N ω) :
b - a ≤ stoppedValue f (upperCrossingTime a b f N (n + 1)) ω -
stoppedValue f (lowerCrossingTime a b f N n) ω :=
sub_le_sub
(stoppedValue_upperCrossingTime (upperCrossingTime_lt_of_le_upcrossingsBefore hN hab hn).ne)
(stoppedValue_lowerCrossingTime (lowerCrossingTime_lt_of_lt_upcrossingsBefore hN hab hn).ne)
#align measure_theory.le_sub_of_le_upcrossings_before MeasureTheory.le_sub_of_le_upcrossingsBefore
theorem sub_eq_zero_of_upcrossingsBefore_lt (hab : a < b) (hn : upcrossingsBefore a b f N ω < n) :
stoppedValue f (upperCrossingTime a b f N (n + 1)) ω -
stoppedValue f (lowerCrossingTime a b f N n) ω = 0 := by
have : N ≤ upperCrossingTime a b f N n ω := by
rw [upcrossingsBefore] at hn
rw [← not_lt]
exact fun h => not_le.2 hn (le_csSup (upperCrossingTime_lt_bddAbove hab) h)
simp [stoppedValue, upperCrossingTime_stabilize' (Nat.le_succ n) this,
lowerCrossingTime_stabilize' le_rfl (le_trans this upperCrossingTime_le_lowerCrossingTime)]
#align measure_theory.sub_eq_zero_of_upcrossings_before_lt MeasureTheory.sub_eq_zero_of_upcrossingsBefore_lt
theorem mul_upcrossingsBefore_le (hf : a ≤ f N ω) (hab : a < b) :
(b - a) * upcrossingsBefore a b f N ω ≤
∑ k ∈ Finset.range N, upcrossingStrat a b f N k ω * (f (k + 1) - f k) ω := by
classical
by_cases hN : N = 0
· simp [hN]
simp_rw [upcrossingStrat, Finset.sum_mul, ←
Set.indicator_mul_left _ _ (fun x ↦ (f (x + 1) - f x) ω), Pi.one_apply, Pi.sub_apply, one_mul]
rw [Finset.sum_comm]
have h₁ : ∀ k, ∑ n ∈ Finset.range N, (Set.Ico (lowerCrossingTime a b f N k ω)
(upperCrossingTime a b f N (k + 1) ω)).indicator (fun m => f (m + 1) ω - f m ω) n =
stoppedValue f (upperCrossingTime a b f N (k + 1)) ω -
stoppedValue f (lowerCrossingTime a b f N k) ω := by
intro k
rw [Finset.sum_indicator_eq_sum_filter, (_ : Finset.filter (fun i => i ∈ Set.Ico
(lowerCrossingTime a b f N k ω) (upperCrossingTime a b f N (k + 1) ω)) (Finset.range N) =
Finset.Ico (lowerCrossingTime a b f N k ω) (upperCrossingTime a b f N (k + 1) ω)),
Finset.sum_Ico_eq_add_neg _ lowerCrossingTime_le_upperCrossingTime_succ,
Finset.sum_range_sub fun n => f n ω, Finset.sum_range_sub fun n => f n ω, neg_sub,
sub_add_sub_cancel]
· rfl
· ext i
simp only [Set.mem_Ico, Finset.mem_filter, Finset.mem_range, Finset.mem_Ico,
and_iff_right_iff_imp, and_imp]
exact fun _ h => lt_of_lt_of_le h upperCrossingTime_le
simp_rw [h₁]
have h₂ : ∑ _k ∈ Finset.range (upcrossingsBefore a b f N ω), (b - a) ≤
∑ k ∈ Finset.range N, (stoppedValue f (upperCrossingTime a b f N (k + 1)) ω -
stoppedValue f (lowerCrossingTime a b f N k) ω) := by
calc
∑ _k ∈ Finset.range (upcrossingsBefore a b f N ω), (b - a) ≤
∑ k ∈ Finset.range (upcrossingsBefore a b f N ω),
(stoppedValue f (upperCrossingTime a b f N (k + 1)) ω -
stoppedValue f (lowerCrossingTime a b f N k) ω) := by
refine Finset.sum_le_sum fun i hi =>
le_sub_of_le_upcrossingsBefore (zero_lt_iff.2 hN) hab ?_
rwa [Finset.mem_range] at hi
_ ≤ ∑ k ∈ Finset.range N, (stoppedValue f (upperCrossingTime a b f N (k + 1)) ω -
stoppedValue f (lowerCrossingTime a b f N k) ω) := by
refine Finset.sum_le_sum_of_subset_of_nonneg
(Finset.range_subset.2 (upcrossingsBefore_le f ω hab)) fun i _ hi => ?_
by_cases hi' : i = upcrossingsBefore a b f N ω
· subst hi'
simp only [stoppedValue]
rw [upperCrossingTime_eq_of_upcrossingsBefore_lt hab (Nat.lt_succ_self _)]
by_cases heq : lowerCrossingTime a b f N (upcrossingsBefore a b f N ω) ω = N
· rw [heq, sub_self]
· rw [sub_nonneg]
exact le_trans (stoppedValue_lowerCrossingTime heq) hf
· rw [sub_eq_zero_of_upcrossingsBefore_lt hab]
rw [Finset.mem_range, not_lt] at hi
exact lt_of_le_of_ne hi (Ne.symm hi')
refine le_trans ?_ h₂
rw [Finset.sum_const, Finset.card_range, nsmul_eq_mul, mul_comm]
#align measure_theory.mul_upcrossings_before_le MeasureTheory.mul_upcrossingsBefore_le
theorem integral_mul_upcrossingsBefore_le_integral [IsFiniteMeasure μ] (hf : Submartingale f ℱ μ)
(hfN : ∀ ω, a ≤ f N ω) (hfzero : 0 ≤ f 0) (hab : a < b) :
(b - a) * μ[upcrossingsBefore a b f N] ≤ μ[f N] :=
calc
(b - a) * μ[upcrossingsBefore a b f N] ≤
μ[∑ k ∈ Finset.range N, upcrossingStrat a b f N k * (f (k + 1) - f k)] := by
rw [← integral_mul_left]
refine integral_mono_of_nonneg ?_ ((hf.sum_upcrossingStrat_mul a b N).integrable N) ?_
· exact eventually_of_forall fun ω => mul_nonneg (sub_nonneg.2 hab.le) (Nat.cast_nonneg _)
· filter_upwards with ω
simpa using mul_upcrossingsBefore_le (hfN ω) hab
_ ≤ μ[f N] - μ[f 0] := hf.sum_mul_upcrossingStrat_le
_ ≤ μ[f N] := (sub_le_self_iff _).2 (integral_nonneg hfzero)
#align measure_theory.integral_mul_upcrossings_before_le_integral MeasureTheory.integral_mul_upcrossingsBefore_le_integral
| Mathlib/Probability/Martingale/Upcrossing.lean | 672 | 719 | theorem crossing_pos_eq (hab : a < b) :
upperCrossingTime 0 (b - a) (fun n ω => (f n ω - a)⁺) N n = upperCrossingTime a b f N n ∧
lowerCrossingTime 0 (b - a) (fun n ω => (f n ω - a)⁺) N n = lowerCrossingTime a b f N n := by |
have hab' : 0 < b - a := sub_pos.2 hab
have hf : ∀ ω i, b - a ≤ (f i ω - a)⁺ ↔ b ≤ f i ω := by
intro i ω
refine ⟨fun h => ?_, fun h => ?_⟩
· rwa [← sub_le_sub_iff_right a, ←
posPart_eq_of_posPart_pos (lt_of_lt_of_le hab' h)]
· rw [← sub_le_sub_iff_right a] at h
rwa [posPart_eq_self.2 (le_trans hab'.le h)]
have hf' (ω i) : (f i ω - a)⁺ ≤ 0 ↔ f i ω ≤ a := by rw [posPart_nonpos, sub_nonpos]
induction' n with k ih
· refine ⟨rfl, ?_⟩
#adaptation_note /-- nightly-2024-03-16: simp was
simp (config := { unfoldPartialApp := true }) only [lowerCrossingTime_zero, hitting,
Set.mem_Icc, Set.mem_Iic, Nat.zero_eq] -/
simp (config := { unfoldPartialApp := true }) only [lowerCrossingTime_zero, hitting_def,
Set.mem_Icc, Set.mem_Iic, Nat.zero_eq]
ext ω
split_ifs with h₁ h₂ h₂
· simp_rw [hf']
· simp_rw [Set.mem_Iic, ← hf' _ _] at h₂
exact False.elim (h₂ h₁)
· simp_rw [Set.mem_Iic, hf' _ _] at h₁
exact False.elim (h₁ h₂)
· rfl
· have : upperCrossingTime 0 (b - a) (fun n ω => (f n ω - a)⁺) N (k + 1) =
upperCrossingTime a b f N (k + 1) := by
ext ω
simp only [upperCrossingTime_succ_eq, ← ih.2, hitting, Set.mem_Ici, tsub_le_iff_right]
split_ifs with h₁ h₂ h₂
· simp_rw [← sub_le_iff_le_add, hf ω]
· refine False.elim (h₂ ?_)
simp_all only [Set.mem_Ici, not_true_eq_false]
· refine False.elim (h₁ ?_)
simp_all only [Set.mem_Ici]
· rfl
refine ⟨this, ?_⟩
ext ω
simp only [lowerCrossingTime, this, hitting, Set.mem_Iic]
split_ifs with h₁ h₂ h₂
· simp_rw [hf' ω]
· refine False.elim (h₂ ?_)
simp_all only [Set.mem_Iic, not_true_eq_false]
· refine False.elim (h₁ ?_)
simp_all only [Set.mem_Iic]
· rfl
|
/-
Copyright (c) 2018 Sean Leather. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Sean Leather, Mario Carneiro
-/
import Mathlib.Data.List.AList
import Mathlib.Data.Finset.Sigma
import Mathlib.Data.Part
#align_import data.finmap from "leanprover-community/mathlib"@"cea83e192eae2d368ab2b500a0975667da42c920"
/-!
# Finite maps over `Multiset`
-/
universe u v w
open List
variable {α : Type u} {β : α → Type v}
/-! ### Multisets of sigma types-/
namespace Multiset
/-- Multiset of keys of an association multiset. -/
def keys (s : Multiset (Sigma β)) : Multiset α :=
s.map Sigma.fst
#align multiset.keys Multiset.keys
@[simp]
theorem coe_keys {l : List (Sigma β)} : keys (l : Multiset (Sigma β)) = (l.keys : Multiset α) :=
rfl
#align multiset.coe_keys Multiset.coe_keys
-- Porting note: Fixed Nodupkeys -> NodupKeys
/-- `NodupKeys s` means that `s` has no duplicate keys. -/
def NodupKeys (s : Multiset (Sigma β)) : Prop :=
Quot.liftOn s List.NodupKeys fun _ _ p => propext <| perm_nodupKeys p
#align multiset.nodupkeys Multiset.NodupKeys
@[simp]
theorem coe_nodupKeys {l : List (Sigma β)} : @NodupKeys α β l ↔ l.NodupKeys :=
Iff.rfl
#align multiset.coe_nodupkeys Multiset.coe_nodupKeys
lemma nodup_keys {m : Multiset (Σ a, β a)} : m.keys.Nodup ↔ m.NodupKeys := by
rcases m with ⟨l⟩; rfl
alias ⟨_, NodupKeys.nodup_keys⟩ := nodup_keys
protected lemma NodupKeys.nodup {m : Multiset (Σ a, β a)} (h : m.NodupKeys) : m.Nodup :=
h.nodup_keys.of_map _
end Multiset
/-! ### Finmap -/
/-- `Finmap β` is the type of finite maps over a multiset. It is effectively
a quotient of `AList β` by permutation of the underlying list. -/
structure Finmap (β : α → Type v) : Type max u v where
/-- The underlying `Multiset` of a `Finmap` -/
entries : Multiset (Sigma β)
/-- There are no duplicate keys in `entries` -/
nodupKeys : entries.NodupKeys
#align finmap Finmap
/-- The quotient map from `AList` to `Finmap`. -/
def AList.toFinmap (s : AList β) : Finmap β :=
⟨s.entries, s.nodupKeys⟩
#align alist.to_finmap AList.toFinmap
local notation:arg "⟦" a "⟧" => AList.toFinmap a
theorem AList.toFinmap_eq {s₁ s₂ : AList β} :
toFinmap s₁ = toFinmap s₂ ↔ s₁.entries ~ s₂.entries := by
cases s₁
cases s₂
simp [AList.toFinmap]
#align alist.to_finmap_eq AList.toFinmap_eq
@[simp]
theorem AList.toFinmap_entries (s : AList β) : ⟦s⟧.entries = s.entries :=
rfl
#align alist.to_finmap_entries AList.toFinmap_entries
/-- Given `l : List (Sigma β)`, create a term of type `Finmap β` by removing
entries with duplicate keys. -/
def List.toFinmap [DecidableEq α] (s : List (Sigma β)) : Finmap β :=
s.toAList.toFinmap
#align list.to_finmap List.toFinmap
namespace Finmap
open AList
lemma nodup_entries (f : Finmap β) : f.entries.Nodup := f.nodupKeys.nodup
/-! ### Lifting from AList -/
/-- Lift a permutation-respecting function on `AList` to `Finmap`. -/
-- @[elab_as_elim] Porting note: we can't add `elab_as_elim` attr in this type
def liftOn {γ} (s : Finmap β) (f : AList β → γ)
(H : ∀ a b : AList β, a.entries ~ b.entries → f a = f b) : γ := by
refine
(Quotient.liftOn s.entries
(fun (l : List (Sigma β)) => (⟨_, fun nd => f ⟨l, nd⟩⟩ : Part γ))
(fun l₁ l₂ p => Part.ext' (perm_nodupKeys p) ?_) : Part γ).get ?_
· exact fun h1 h2 => H _ _ p
· have := s.nodupKeys
-- Porting note: `revert` required because `rcases` behaves differently
revert this
rcases s.entries with ⟨l⟩
exact id
#align finmap.lift_on Finmap.liftOn
@[simp]
theorem liftOn_toFinmap {γ} (s : AList β) (f : AList β → γ) (H) : liftOn ⟦s⟧ f H = f s := by
cases s
rfl
#align finmap.lift_on_to_finmap Finmap.liftOn_toFinmap
/-- Lift a permutation-respecting function on 2 `AList`s to 2 `Finmap`s. -/
-- @[elab_as_elim] Porting note: we can't add `elab_as_elim` attr in this type
def liftOn₂ {γ} (s₁ s₂ : Finmap β) (f : AList β → AList β → γ)
(H : ∀ a₁ b₁ a₂ b₂ : AList β,
a₁.entries ~ a₂.entries → b₁.entries ~ b₂.entries → f a₁ b₁ = f a₂ b₂) : γ :=
liftOn s₁ (fun l₁ => liftOn s₂ (f l₁) fun b₁ b₂ p => H _ _ _ _ (Perm.refl _) p) fun a₁ a₂ p => by
have H' : f a₁ = f a₂ := funext fun _ => H _ _ _ _ p (Perm.refl _)
simp only [H']
#align finmap.lift_on₂ Finmap.liftOn₂
@[simp]
theorem liftOn₂_toFinmap {γ} (s₁ s₂ : AList β) (f : AList β → AList β → γ) (H) :
liftOn₂ ⟦s₁⟧ ⟦s₂⟧ f H = f s₁ s₂ := by
cases s₁; cases s₂; rfl
#align finmap.lift_on₂_to_finmap Finmap.liftOn₂_toFinmap
/-! ### Induction -/
@[elab_as_elim]
theorem induction_on {C : Finmap β → Prop} (s : Finmap β) (H : ∀ a : AList β, C ⟦a⟧) : C s := by
rcases s with ⟨⟨a⟩, h⟩; exact H ⟨a, h⟩
#align finmap.induction_on Finmap.induction_on
@[elab_as_elim]
theorem induction_on₂ {C : Finmap β → Finmap β → Prop} (s₁ s₂ : Finmap β)
(H : ∀ a₁ a₂ : AList β, C ⟦a₁⟧ ⟦a₂⟧) : C s₁ s₂ :=
induction_on s₁ fun l₁ => induction_on s₂ fun l₂ => H l₁ l₂
#align finmap.induction_on₂ Finmap.induction_on₂
@[elab_as_elim]
theorem induction_on₃ {C : Finmap β → Finmap β → Finmap β → Prop} (s₁ s₂ s₃ : Finmap β)
(H : ∀ a₁ a₂ a₃ : AList β, C ⟦a₁⟧ ⟦a₂⟧ ⟦a₃⟧) : C s₁ s₂ s₃ :=
induction_on₂ s₁ s₂ fun l₁ l₂ => induction_on s₃ fun l₃ => H l₁ l₂ l₃
#align finmap.induction_on₃ Finmap.induction_on₃
/-! ### extensionality -/
@[ext]
theorem ext : ∀ {s t : Finmap β}, s.entries = t.entries → s = t
| ⟨l₁, h₁⟩, ⟨l₂, _⟩, H => by congr
#align finmap.ext Finmap.ext
@[simp]
theorem ext_iff {s t : Finmap β} : s.entries = t.entries ↔ s = t :=
⟨ext, congr_arg _⟩
#align finmap.ext_iff Finmap.ext_iff
/-! ### mem -/
/-- The predicate `a ∈ s` means that `s` has a value associated to the key `a`. -/
instance : Membership α (Finmap β) :=
⟨fun a s => a ∈ s.entries.keys⟩
theorem mem_def {a : α} {s : Finmap β} : a ∈ s ↔ a ∈ s.entries.keys :=
Iff.rfl
#align finmap.mem_def Finmap.mem_def
@[simp]
theorem mem_toFinmap {a : α} {s : AList β} : a ∈ toFinmap s ↔ a ∈ s :=
Iff.rfl
#align finmap.mem_to_finmap Finmap.mem_toFinmap
/-! ### keys -/
/-- The set of keys of a finite map. -/
def keys (s : Finmap β) : Finset α :=
⟨s.entries.keys, s.nodupKeys.nodup_keys⟩
#align finmap.keys Finmap.keys
@[simp]
theorem keys_val (s : AList β) : (keys ⟦s⟧).val = s.keys :=
rfl
#align finmap.keys_val Finmap.keys_val
@[simp]
theorem keys_ext {s₁ s₂ : AList β} : keys ⟦s₁⟧ = keys ⟦s₂⟧ ↔ s₁.keys ~ s₂.keys := by
simp [keys, AList.keys]
#align finmap.keys_ext Finmap.keys_ext
theorem mem_keys {a : α} {s : Finmap β} : a ∈ s.keys ↔ a ∈ s :=
induction_on s fun _ => AList.mem_keys
#align finmap.mem_keys Finmap.mem_keys
/-! ### empty -/
/-- The empty map. -/
instance : EmptyCollection (Finmap β) :=
⟨⟨0, nodupKeys_nil⟩⟩
instance : Inhabited (Finmap β) :=
⟨∅⟩
@[simp]
theorem empty_toFinmap : (⟦∅⟧ : Finmap β) = ∅ :=
rfl
#align finmap.empty_to_finmap Finmap.empty_toFinmap
@[simp]
theorem toFinmap_nil [DecidableEq α] : ([].toFinmap : Finmap β) = ∅ :=
rfl
#align finmap.to_finmap_nil Finmap.toFinmap_nil
theorem not_mem_empty {a : α} : a ∉ (∅ : Finmap β) :=
Multiset.not_mem_zero a
#align finmap.not_mem_empty Finmap.not_mem_empty
@[simp]
theorem keys_empty : (∅ : Finmap β).keys = ∅ :=
rfl
#align finmap.keys_empty Finmap.keys_empty
/-! ### singleton -/
/-- The singleton map. -/
def singleton (a : α) (b : β a) : Finmap β :=
⟦AList.singleton a b⟧
#align finmap.singleton Finmap.singleton
@[simp]
theorem keys_singleton (a : α) (b : β a) : (singleton a b).keys = {a} :=
rfl
#align finmap.keys_singleton Finmap.keys_singleton
@[simp]
theorem mem_singleton (x y : α) (b : β y) : x ∈ singleton y b ↔ x = y := by
simp only [singleton]; erw [mem_cons, mem_nil_iff, or_false_iff]
#align finmap.mem_singleton Finmap.mem_singleton
section
variable [DecidableEq α]
instance decidableEq [∀ a, DecidableEq (β a)] : DecidableEq (Finmap β)
| _, _ => decidable_of_iff _ ext_iff
#align finmap.has_decidable_eq Finmap.decidableEq
/-! ### lookup -/
/-- Look up the value associated to a key in a map. -/
def lookup (a : α) (s : Finmap β) : Option (β a) :=
liftOn s (AList.lookup a) fun _ _ => perm_lookup
#align finmap.lookup Finmap.lookup
@[simp]
theorem lookup_toFinmap (a : α) (s : AList β) : lookup a ⟦s⟧ = s.lookup a :=
rfl
#align finmap.lookup_to_finmap Finmap.lookup_toFinmap
-- Porting note: renaming to `List.dlookup` since `List.lookup` already exists
@[simp]
theorem dlookup_list_toFinmap (a : α) (s : List (Sigma β)) : lookup a s.toFinmap = s.dlookup a := by
rw [List.toFinmap, lookup_toFinmap, lookup_to_alist]
#align finmap.lookup_list_to_finmap Finmap.dlookup_list_toFinmap
@[simp]
theorem lookup_empty (a) : lookup a (∅ : Finmap β) = none :=
rfl
#align finmap.lookup_empty Finmap.lookup_empty
theorem lookup_isSome {a : α} {s : Finmap β} : (s.lookup a).isSome ↔ a ∈ s :=
induction_on s fun _ => AList.lookup_isSome
#align finmap.lookup_is_some Finmap.lookup_isSome
theorem lookup_eq_none {a} {s : Finmap β} : lookup a s = none ↔ a ∉ s :=
induction_on s fun _ => AList.lookup_eq_none
#align finmap.lookup_eq_none Finmap.lookup_eq_none
lemma mem_lookup_iff {s : Finmap β} {a : α} {b : β a} :
b ∈ s.lookup a ↔ Sigma.mk a b ∈ s.entries := by
rcases s with ⟨⟨l⟩, hl⟩; exact List.mem_dlookup_iff hl
lemma lookup_eq_some_iff {s : Finmap β} {a : α} {b : β a} :
s.lookup a = b ↔ Sigma.mk a b ∈ s.entries := mem_lookup_iff
@[simp] lemma sigma_keys_lookup (s : Finmap β) :
s.keys.sigma (fun i => (s.lookup i).toFinset) = ⟨s.entries, s.nodup_entries⟩ := by
ext x
have : x ∈ s.entries → x.1 ∈ s.keys := Multiset.mem_map_of_mem _
simpa [lookup_eq_some_iff]
@[simp]
theorem lookup_singleton_eq {a : α} {b : β a} : (singleton a b).lookup a = some b := by
rw [singleton, lookup_toFinmap, AList.singleton, AList.lookup, dlookup_cons_eq]
#align finmap.lookup_singleton_eq Finmap.lookup_singleton_eq
instance (a : α) (s : Finmap β) : Decidable (a ∈ s) :=
decidable_of_iff _ lookup_isSome
theorem mem_iff {a : α} {s : Finmap β} : a ∈ s ↔ ∃ b, s.lookup a = some b :=
induction_on s fun s =>
Iff.trans List.mem_keys <| exists_congr fun _ => (mem_dlookup_iff s.nodupKeys).symm
#align finmap.mem_iff Finmap.mem_iff
theorem mem_of_lookup_eq_some {a : α} {b : β a} {s : Finmap β} (h : s.lookup a = some b) : a ∈ s :=
mem_iff.mpr ⟨_, h⟩
#align finmap.mem_of_lookup_eq_some Finmap.mem_of_lookup_eq_some
theorem ext_lookup {s₁ s₂ : Finmap β} : (∀ x, s₁.lookup x = s₂.lookup x) → s₁ = s₂ :=
induction_on₂ s₁ s₂ fun s₁ s₂ h => by
simp only [AList.lookup, lookup_toFinmap] at h
rw [AList.toFinmap_eq]
apply lookup_ext s₁.nodupKeys s₂.nodupKeys
intro x y
rw [h]
#align finmap.ext_lookup Finmap.ext_lookup
/-- An equivalence between `Finmap β` and pairs `(keys : Finset α, lookup : ∀ a, Option (β a))` such
that `(lookup a).isSome ↔ a ∈ keys`. -/
@[simps apply_coe_fst apply_coe_snd]
def keysLookupEquiv :
Finmap β ≃ { f : Finset α × (∀ a, Option (β a)) // ∀ i, (f.2 i).isSome ↔ i ∈ f.1 } where
toFun s := ⟨(s.keys, fun i => s.lookup i), fun _ => lookup_isSome⟩
invFun f := mk (f.1.1.sigma fun i => (f.1.2 i).toFinset).val <| by
refine Multiset.nodup_keys.1 ((Finset.nodup _).map_on ?_)
simp only [Finset.mem_val, Finset.mem_sigma, Option.mem_toFinset, Option.mem_def]
rintro ⟨i, x⟩ ⟨_, hx⟩ ⟨j, y⟩ ⟨_, hy⟩ (rfl : i = j)
simpa using hx.symm.trans hy
left_inv f := ext <| by simp
right_inv := fun ⟨(s, f), hf⟩ => by
dsimp only at hf
ext
· simp [keys, Multiset.keys, ← hf, Option.isSome_iff_exists]
· simp (config := { contextual := true }) [lookup_eq_some_iff, ← hf]
@[simp] lemma keysLookupEquiv_symm_apply_keys :
∀ f : {f : Finset α × (∀ a, Option (β a)) // ∀ i, (f.2 i).isSome ↔ i ∈ f.1},
(keysLookupEquiv.symm f).keys = f.1.1 :=
keysLookupEquiv.surjective.forall.2 fun _ => by
simp only [Equiv.symm_apply_apply, keysLookupEquiv_apply_coe_fst]
@[simp] lemma keysLookupEquiv_symm_apply_lookup :
∀ (f : {f : Finset α × (∀ a, Option (β a)) // ∀ i, (f.2 i).isSome ↔ i ∈ f.1}) a,
(keysLookupEquiv.symm f).lookup a = f.1.2 a :=
keysLookupEquiv.surjective.forall.2 fun _ _ => by
simp only [Equiv.symm_apply_apply, keysLookupEquiv_apply_coe_snd]
/-! ### replace -/
/-- Replace a key with a given value in a finite map.
If the key is not present it does nothing. -/
def replace (a : α) (b : β a) (s : Finmap β) : Finmap β :=
(liftOn s fun t => AList.toFinmap (AList.replace a b t))
fun _ _ p => toFinmap_eq.2 <| perm_replace p
#align finmap.replace Finmap.replace
-- Porting note: explicit type required because of the ambiguity
@[simp]
theorem replace_toFinmap (a : α) (b : β a) (s : AList β) :
replace a b ⟦s⟧ = (⟦s.replace a b⟧ : Finmap β) := by
simp [replace]
#align finmap.replace_to_finmap Finmap.replace_toFinmap
@[simp]
theorem keys_replace (a : α) (b : β a) (s : Finmap β) : (replace a b s).keys = s.keys :=
induction_on s fun s => by simp
#align finmap.keys_replace Finmap.keys_replace
@[simp]
theorem mem_replace {a a' : α} {b : β a} {s : Finmap β} : a' ∈ replace a b s ↔ a' ∈ s :=
induction_on s fun s => by simp
#align finmap.mem_replace Finmap.mem_replace
end
/-! ### foldl -/
/-- Fold a commutative function over the key-value pairs in the map -/
def foldl {δ : Type w} (f : δ → ∀ a, β a → δ)
(H : ∀ d a₁ b₁ a₂ b₂, f (f d a₁ b₁) a₂ b₂ = f (f d a₂ b₂) a₁ b₁) (d : δ) (m : Finmap β) : δ :=
m.entries.foldl (fun d s => f d s.1 s.2) (fun _ _ _ => H _ _ _ _ _) d
#align finmap.foldl Finmap.foldl
/-- `any f s` returns `true` iff there exists a value `v` in `s` such that `f v = true`. -/
def any (f : ∀ x, β x → Bool) (s : Finmap β) : Bool :=
s.foldl (fun x y z => x || f y z)
(fun _ _ _ _ => by simp_rw [Bool.or_assoc, Bool.or_comm, imp_true_iff]) false
#align finmap.any Finmap.any
/-- `all f s` returns `true` iff `f v = true` for all values `v` in `s`. -/
def all (f : ∀ x, β x → Bool) (s : Finmap β) : Bool :=
s.foldl (fun x y z => x && f y z)
(fun _ _ _ _ => by simp_rw [Bool.and_assoc, Bool.and_comm, imp_true_iff]) true
#align finmap.all Finmap.all
/-! ### erase -/
section
variable [DecidableEq α]
/-- Erase a key from the map. If the key is not present it does nothing. -/
def erase (a : α) (s : Finmap β) : Finmap β :=
(liftOn s fun t => AList.toFinmap (AList.erase a t)) fun _ _ p => toFinmap_eq.2 <| perm_erase p
#align finmap.erase Finmap.erase
@[simp]
theorem erase_toFinmap (a : α) (s : AList β) : erase a ⟦s⟧ = AList.toFinmap (s.erase a) := by
simp [erase]
#align finmap.erase_to_finmap Finmap.erase_toFinmap
@[simp]
theorem keys_erase_toFinset (a : α) (s : AList β) : keys ⟦s.erase a⟧ = (keys ⟦s⟧).erase a := by
simp [Finset.erase, keys, AList.erase, keys_kerase]
#align finmap.keys_erase_to_finset Finmap.keys_erase_toFinset
@[simp]
theorem keys_erase (a : α) (s : Finmap β) : (erase a s).keys = s.keys.erase a :=
induction_on s fun s => by simp
#align finmap.keys_erase Finmap.keys_erase
@[simp]
theorem mem_erase {a a' : α} {s : Finmap β} : a' ∈ erase a s ↔ a' ≠ a ∧ a' ∈ s :=
induction_on s fun s => by simp
#align finmap.mem_erase Finmap.mem_erase
theorem not_mem_erase_self {a : α} {s : Finmap β} : ¬a ∈ erase a s := by
rw [mem_erase, not_and_or, not_not]
left
rfl
#align finmap.not_mem_erase_self Finmap.not_mem_erase_self
@[simp]
theorem lookup_erase (a) (s : Finmap β) : lookup a (erase a s) = none :=
induction_on s <| AList.lookup_erase a
#align finmap.lookup_erase Finmap.lookup_erase
@[simp]
theorem lookup_erase_ne {a a'} {s : Finmap β} (h : a ≠ a') : lookup a (erase a' s) = lookup a s :=
induction_on s fun _ => AList.lookup_erase_ne h
#align finmap.lookup_erase_ne Finmap.lookup_erase_ne
theorem erase_erase {a a' : α} {s : Finmap β} : erase a (erase a' s) = erase a' (erase a s) :=
induction_on s fun s => ext (by simp only [AList.erase_erase, erase_toFinmap])
#align finmap.erase_erase Finmap.erase_erase
/-! ### sdiff -/
/-- `sdiff s s'` consists of all key-value pairs from `s` and `s'` where the keys are in `s` or
`s'` but not both. -/
def sdiff (s s' : Finmap β) : Finmap β :=
s'.foldl (fun s x _ => s.erase x) (fun _ _ _ _ _ => erase_erase) s
#align finmap.sdiff Finmap.sdiff
instance : SDiff (Finmap β) :=
⟨sdiff⟩
/-! ### insert -/
/-- Insert a key-value pair into a finite map, replacing any existing pair with
the same key. -/
def insert (a : α) (b : β a) (s : Finmap β) : Finmap β :=
(liftOn s fun t => AList.toFinmap (AList.insert a b t)) fun _ _ p =>
toFinmap_eq.2 <| perm_insert p
#align finmap.insert Finmap.insert
@[simp]
theorem insert_toFinmap (a : α) (b : β a) (s : AList β) :
insert a b (AList.toFinmap s) = AList.toFinmap (s.insert a b) := by
simp [insert]
#align finmap.insert_to_finmap Finmap.insert_toFinmap
theorem insert_entries_of_neg {a : α} {b : β a} {s : Finmap β} :
a ∉ s → (insert a b s).entries = ⟨a, b⟩ ::ₘ s.entries :=
induction_on s fun s h => by
-- Porting note: `-insert_entries` required
simp [AList.insert_entries_of_neg (mt mem_toFinmap.1 h), -insert_entries]
#align finmap.insert_entries_of_neg Finmap.insert_entries_of_neg
@[simp]
theorem mem_insert {a a' : α} {b' : β a'} {s : Finmap β} : a ∈ insert a' b' s ↔ a = a' ∨ a ∈ s :=
induction_on s AList.mem_insert
#align finmap.mem_insert Finmap.mem_insert
@[simp]
theorem lookup_insert {a} {b : β a} (s : Finmap β) : lookup a (insert a b s) = some b :=
induction_on s fun s => by simp only [insert_toFinmap, lookup_toFinmap, AList.lookup_insert]
#align finmap.lookup_insert Finmap.lookup_insert
@[simp]
theorem lookup_insert_of_ne {a a'} {b : β a} (s : Finmap β) (h : a' ≠ a) :
lookup a' (insert a b s) = lookup a' s :=
induction_on s fun s => by simp only [insert_toFinmap, lookup_toFinmap, lookup_insert_ne h]
#align finmap.lookup_insert_of_ne Finmap.lookup_insert_of_ne
@[simp]
theorem insert_insert {a} {b b' : β a} (s : Finmap β) :
(s.insert a b).insert a b' = s.insert a b' :=
induction_on s fun s => by simp only [insert_toFinmap, AList.insert_insert]
#align finmap.insert_insert Finmap.insert_insert
theorem insert_insert_of_ne {a a'} {b : β a} {b' : β a'} (s : Finmap β) (h : a ≠ a') :
(s.insert a b).insert a' b' = (s.insert a' b').insert a b :=
induction_on s fun s => by
simp only [insert_toFinmap, AList.toFinmap_eq, AList.insert_insert_of_ne _ h]
#align finmap.insert_insert_of_ne Finmap.insert_insert_of_ne
theorem toFinmap_cons (a : α) (b : β a) (xs : List (Sigma β)) :
List.toFinmap (⟨a, b⟩ :: xs) = insert a b xs.toFinmap :=
rfl
#align finmap.to_finmap_cons Finmap.toFinmap_cons
| Mathlib/Data/Finmap.lean | 524 | 534 | theorem mem_list_toFinmap (a : α) (xs : List (Sigma β)) :
a ∈ xs.toFinmap ↔ ∃ b : β a, Sigma.mk a b ∈ xs := by |
-- Porting note: golfed
induction' xs with x xs
· simp only [toFinmap_nil, not_mem_empty, find?, not_mem_nil, exists_false]
cases' x with fst_i snd_i
-- Porting note: `Sigma.mk.inj_iff` required because `simp` behaves differently
simp only [toFinmap_cons, *, exists_or, mem_cons, mem_insert, exists_and_left, Sigma.mk.inj_iff]
refine (or_congr_left <| and_iff_left_of_imp ?_).symm
rintro rfl
simp only [exists_eq, heq_iff_eq]
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Kenny Lau
-/
import Mathlib.Algebra.BigOperators.GroupWithZero.Finset
import Mathlib.Algebra.Group.Submonoid.Membership
import Mathlib.Algebra.Module.LinearMap.Basic
import Mathlib.Data.Finset.Preimage
import Mathlib.Data.Set.Finite
import Mathlib.GroupTheory.GroupAction.BigOperators
#align_import data.dfinsupp.basic from "leanprover-community/mathlib"@"6623e6af705e97002a9054c1c05a980180276fc1"
/-!
# Dependent functions with finite support
For a non-dependent version see `data/finsupp.lean`.
## Notation
This file introduces the notation `Π₀ a, β a` as notation for `DFinsupp β`, mirroring the `α →₀ β`
notation used for `Finsupp`. This works for nested binders too, with `Π₀ a b, γ a b` as notation
for `DFinsupp (fun a ↦ DFinsupp (γ a))`.
## Implementation notes
The support is internally represented (in the primed `DFinsupp.support'`) as a `Multiset` that
represents a superset of the true support of the function, quotiented by the always-true relation so
that this does not impact equality. This approach has computational benefits over storing a
`Finset`; it allows us to add together two finitely-supported functions without
having to evaluate the resulting function to recompute its support (which would required
decidability of `b = 0` for `b : β i`).
The true support of the function can still be recovered with `DFinsupp.support`; but these
decidability obligations are now postponed to when the support is actually needed. As a consequence,
there are two ways to sum a `DFinsupp`: with `DFinsupp.sum` which works over an arbitrary function
but requires recomputation of the support and therefore a `Decidable` argument; and with
`DFinsupp.sumAddHom` which requires an additive morphism, using its properties to show that
summing over a superset of the support is sufficient.
`Finsupp` takes an altogether different approach here; it uses `Classical.Decidable` and declares
the `Add` instance as noncomputable. This design difference is independent of the fact that
`DFinsupp` is dependently-typed and `Finsupp` is not; in future, we may want to align these two
definitions, or introduce two more definitions for the other combinations of decisions.
-/
universe u u₁ u₂ v v₁ v₂ v₃ w x y l
variable {ι : Type u} {γ : Type w} {β : ι → Type v} {β₁ : ι → Type v₁} {β₂ : ι → Type v₂}
variable (β)
/-- A dependent function `Π i, β i` with finite support, with notation `Π₀ i, β i`.
Note that `DFinsupp.support` is the preferred API for accessing the support of the function,
`DFinsupp.support'` is an implementation detail that aids computability; see the implementation
notes in this file for more information. -/
structure DFinsupp [∀ i, Zero (β i)] : Type max u v where mk' ::
/-- The underlying function of a dependent function with finite support (aka `DFinsupp`). -/
toFun : ∀ i, β i
/-- The support of a dependent function with finite support (aka `DFinsupp`). -/
support' : Trunc { s : Multiset ι // ∀ i, i ∈ s ∨ toFun i = 0 }
#align dfinsupp DFinsupp
variable {β}
/-- `Π₀ i, β i` denotes the type of dependent functions with finite support `DFinsupp β`. -/
notation3 "Π₀ "(...)", "r:(scoped f => DFinsupp f) => r
namespace DFinsupp
section Basic
variable [∀ i, Zero (β i)] [∀ i, Zero (β₁ i)] [∀ i, Zero (β₂ i)]
instance instDFunLike : DFunLike (Π₀ i, β i) ι β :=
⟨fun f => f.toFun, fun ⟨f₁, s₁⟩ ⟨f₂, s₁⟩ ↦ fun (h : f₁ = f₂) ↦ by
subst h
congr
apply Subsingleton.elim ⟩
#align dfinsupp.fun_like DFinsupp.instDFunLike
/-- Helper instance for when there are too many metavariables to apply `DFunLike.coeFunForall`
directly. -/
instance : CoeFun (Π₀ i, β i) fun _ => ∀ i, β i :=
inferInstance
@[simp]
theorem toFun_eq_coe (f : Π₀ i, β i) : f.toFun = f :=
rfl
#align dfinsupp.to_fun_eq_coe DFinsupp.toFun_eq_coe
@[ext]
theorem ext {f g : Π₀ i, β i} (h : ∀ i, f i = g i) : f = g :=
DFunLike.ext _ _ h
#align dfinsupp.ext DFinsupp.ext
#align dfinsupp.ext_iff DFunLike.ext_iff
#align dfinsupp.coe_fn_injective DFunLike.coe_injective
lemma ne_iff {f g : Π₀ i, β i} : f ≠ g ↔ ∃ i, f i ≠ g i := DFunLike.ne_iff
instance : Zero (Π₀ i, β i) :=
⟨⟨0, Trunc.mk <| ⟨∅, fun _ => Or.inr rfl⟩⟩⟩
instance : Inhabited (Π₀ i, β i) :=
⟨0⟩
@[simp, norm_cast] lemma coe_mk' (f : ∀ i, β i) (s) : ⇑(⟨f, s⟩ : Π₀ i, β i) = f := rfl
#align dfinsupp.coe_mk' DFinsupp.coe_mk'
@[simp, norm_cast] lemma coe_zero : ⇑(0 : Π₀ i, β i) = 0 := rfl
#align dfinsupp.coe_zero DFinsupp.coe_zero
theorem zero_apply (i : ι) : (0 : Π₀ i, β i) i = 0 :=
rfl
#align dfinsupp.zero_apply DFinsupp.zero_apply
/-- The composition of `f : β₁ → β₂` and `g : Π₀ i, β₁ i` is
`mapRange f hf g : Π₀ i, β₂ i`, well defined when `f 0 = 0`.
This preserves the structure on `f`, and exists in various bundled forms for when `f` is itself
bundled:
* `DFinsupp.mapRange.addMonoidHom`
* `DFinsupp.mapRange.addEquiv`
* `dfinsupp.mapRange.linearMap`
* `dfinsupp.mapRange.linearEquiv`
-/
def mapRange (f : ∀ i, β₁ i → β₂ i) (hf : ∀ i, f i 0 = 0) (x : Π₀ i, β₁ i) : Π₀ i, β₂ i :=
⟨fun i => f i (x i),
x.support'.map fun s => ⟨s.1, fun i => (s.2 i).imp_right fun h : x i = 0 => by
rw [← hf i, ← h]⟩⟩
#align dfinsupp.map_range DFinsupp.mapRange
@[simp]
theorem mapRange_apply (f : ∀ i, β₁ i → β₂ i) (hf : ∀ i, f i 0 = 0) (g : Π₀ i, β₁ i) (i : ι) :
mapRange f hf g i = f i (g i) :=
rfl
#align dfinsupp.map_range_apply DFinsupp.mapRange_apply
@[simp]
theorem mapRange_id (h : ∀ i, id (0 : β₁ i) = 0 := fun i => rfl) (g : Π₀ i : ι, β₁ i) :
mapRange (fun i => (id : β₁ i → β₁ i)) h g = g := by
ext
rfl
#align dfinsupp.map_range_id DFinsupp.mapRange_id
theorem mapRange_comp (f : ∀ i, β₁ i → β₂ i) (f₂ : ∀ i, β i → β₁ i) (hf : ∀ i, f i 0 = 0)
(hf₂ : ∀ i, f₂ i 0 = 0) (h : ∀ i, (f i ∘ f₂ i) 0 = 0) (g : Π₀ i : ι, β i) :
mapRange (fun i => f i ∘ f₂ i) h g = mapRange f hf (mapRange f₂ hf₂ g) := by
ext
simp only [mapRange_apply]; rfl
#align dfinsupp.map_range_comp DFinsupp.mapRange_comp
@[simp]
theorem mapRange_zero (f : ∀ i, β₁ i → β₂ i) (hf : ∀ i, f i 0 = 0) :
mapRange f hf (0 : Π₀ i, β₁ i) = 0 := by
ext
simp only [mapRange_apply, coe_zero, Pi.zero_apply, hf]
#align dfinsupp.map_range_zero DFinsupp.mapRange_zero
/-- Let `f i` be a binary operation `β₁ i → β₂ i → β i` such that `f i 0 0 = 0`.
Then `zipWith f hf` is a binary operation `Π₀ i, β₁ i → Π₀ i, β₂ i → Π₀ i, β i`. -/
def zipWith (f : ∀ i, β₁ i → β₂ i → β i) (hf : ∀ i, f i 0 0 = 0) (x : Π₀ i, β₁ i) (y : Π₀ i, β₂ i) :
Π₀ i, β i :=
⟨fun i => f i (x i) (y i), by
refine x.support'.bind fun xs => ?_
refine y.support'.map fun ys => ?_
refine ⟨xs + ys, fun i => ?_⟩
obtain h1 | (h1 : x i = 0) := xs.prop i
· left
rw [Multiset.mem_add]
left
exact h1
obtain h2 | (h2 : y i = 0) := ys.prop i
· left
rw [Multiset.mem_add]
right
exact h2
right; rw [← hf, ← h1, ← h2]⟩
#align dfinsupp.zip_with DFinsupp.zipWith
@[simp]
theorem zipWith_apply (f : ∀ i, β₁ i → β₂ i → β i) (hf : ∀ i, f i 0 0 = 0) (g₁ : Π₀ i, β₁ i)
(g₂ : Π₀ i, β₂ i) (i : ι) : zipWith f hf g₁ g₂ i = f i (g₁ i) (g₂ i) :=
rfl
#align dfinsupp.zip_with_apply DFinsupp.zipWith_apply
section Piecewise
variable (x y : Π₀ i, β i) (s : Set ι) [∀ i, Decidable (i ∈ s)]
/-- `x.piecewise y s` is the finitely supported function equal to `x` on the set `s`,
and to `y` on its complement. -/
def piecewise : Π₀ i, β i :=
zipWith (fun i x y => if i ∈ s then x else y) (fun _ => ite_self 0) x y
#align dfinsupp.piecewise DFinsupp.piecewise
theorem piecewise_apply (i : ι) : x.piecewise y s i = if i ∈ s then x i else y i :=
zipWith_apply _ _ x y i
#align dfinsupp.piecewise_apply DFinsupp.piecewise_apply
@[simp, norm_cast]
theorem coe_piecewise : ⇑(x.piecewise y s) = s.piecewise x y := by
ext
apply piecewise_apply
#align dfinsupp.coe_piecewise DFinsupp.coe_piecewise
end Piecewise
end Basic
section Algebra
instance [∀ i, AddZeroClass (β i)] : Add (Π₀ i, β i) :=
⟨zipWith (fun _ => (· + ·)) fun _ => add_zero 0⟩
theorem add_apply [∀ i, AddZeroClass (β i)] (g₁ g₂ : Π₀ i, β i) (i : ι) :
(g₁ + g₂) i = g₁ i + g₂ i :=
rfl
#align dfinsupp.add_apply DFinsupp.add_apply
@[simp, norm_cast]
theorem coe_add [∀ i, AddZeroClass (β i)] (g₁ g₂ : Π₀ i, β i) : ⇑(g₁ + g₂) = g₁ + g₂ :=
rfl
#align dfinsupp.coe_add DFinsupp.coe_add
instance addZeroClass [∀ i, AddZeroClass (β i)] : AddZeroClass (Π₀ i, β i) :=
DFunLike.coe_injective.addZeroClass _ coe_zero coe_add
instance instIsLeftCancelAdd [∀ i, AddZeroClass (β i)] [∀ i, IsLeftCancelAdd (β i)] :
IsLeftCancelAdd (Π₀ i, β i) where
add_left_cancel _ _ _ h := ext fun x => add_left_cancel <| DFunLike.congr_fun h x
instance instIsRightCancelAdd [∀ i, AddZeroClass (β i)] [∀ i, IsRightCancelAdd (β i)] :
IsRightCancelAdd (Π₀ i, β i) where
add_right_cancel _ _ _ h := ext fun x => add_right_cancel <| DFunLike.congr_fun h x
instance instIsCancelAdd [∀ i, AddZeroClass (β i)] [∀ i, IsCancelAdd (β i)] :
IsCancelAdd (Π₀ i, β i) where
/-- Note the general `SMul` instance doesn't apply as `ℕ` is not distributive
unless `β i`'s addition is commutative. -/
instance hasNatScalar [∀ i, AddMonoid (β i)] : SMul ℕ (Π₀ i, β i) :=
⟨fun c v => v.mapRange (fun _ => (c • ·)) fun _ => nsmul_zero _⟩
#align dfinsupp.has_nat_scalar DFinsupp.hasNatScalar
theorem nsmul_apply [∀ i, AddMonoid (β i)] (b : ℕ) (v : Π₀ i, β i) (i : ι) : (b • v) i = b • v i :=
rfl
#align dfinsupp.nsmul_apply DFinsupp.nsmul_apply
@[simp, norm_cast]
theorem coe_nsmul [∀ i, AddMonoid (β i)] (b : ℕ) (v : Π₀ i, β i) : ⇑(b • v) = b • ⇑v :=
rfl
#align dfinsupp.coe_nsmul DFinsupp.coe_nsmul
instance [∀ i, AddMonoid (β i)] : AddMonoid (Π₀ i, β i) :=
DFunLike.coe_injective.addMonoid _ coe_zero coe_add fun _ _ => coe_nsmul _ _
/-- Coercion from a `DFinsupp` to a pi type is an `AddMonoidHom`. -/
def coeFnAddMonoidHom [∀ i, AddZeroClass (β i)] : (Π₀ i, β i) →+ ∀ i, β i where
toFun := (⇑)
map_zero' := coe_zero
map_add' := coe_add
#align dfinsupp.coe_fn_add_monoid_hom DFinsupp.coeFnAddMonoidHom
/-- Evaluation at a point is an `AddMonoidHom`. This is the finitely-supported version of
`Pi.evalAddMonoidHom`. -/
def evalAddMonoidHom [∀ i, AddZeroClass (β i)] (i : ι) : (Π₀ i, β i) →+ β i :=
(Pi.evalAddMonoidHom β i).comp coeFnAddMonoidHom
#align dfinsupp.eval_add_monoid_hom DFinsupp.evalAddMonoidHom
instance addCommMonoid [∀ i, AddCommMonoid (β i)] : AddCommMonoid (Π₀ i, β i) :=
DFunLike.coe_injective.addCommMonoid _ coe_zero coe_add fun _ _ => coe_nsmul _ _
@[simp, norm_cast]
theorem coe_finset_sum {α} [∀ i, AddCommMonoid (β i)] (s : Finset α) (g : α → Π₀ i, β i) :
⇑(∑ a ∈ s, g a) = ∑ a ∈ s, ⇑(g a) :=
map_sum coeFnAddMonoidHom g s
#align dfinsupp.coe_finset_sum DFinsupp.coe_finset_sum
@[simp]
theorem finset_sum_apply {α} [∀ i, AddCommMonoid (β i)] (s : Finset α) (g : α → Π₀ i, β i) (i : ι) :
(∑ a ∈ s, g a) i = ∑ a ∈ s, g a i :=
map_sum (evalAddMonoidHom i) g s
#align dfinsupp.finset_sum_apply DFinsupp.finset_sum_apply
instance [∀ i, AddGroup (β i)] : Neg (Π₀ i, β i) :=
⟨fun f => f.mapRange (fun _ => Neg.neg) fun _ => neg_zero⟩
theorem neg_apply [∀ i, AddGroup (β i)] (g : Π₀ i, β i) (i : ι) : (-g) i = -g i :=
rfl
#align dfinsupp.neg_apply DFinsupp.neg_apply
@[simp, norm_cast] lemma coe_neg [∀ i, AddGroup (β i)] (g : Π₀ i, β i) : ⇑(-g) = -g := rfl
#align dfinsupp.coe_neg DFinsupp.coe_neg
instance [∀ i, AddGroup (β i)] : Sub (Π₀ i, β i) :=
⟨zipWith (fun _ => Sub.sub) fun _ => sub_zero 0⟩
theorem sub_apply [∀ i, AddGroup (β i)] (g₁ g₂ : Π₀ i, β i) (i : ι) : (g₁ - g₂) i = g₁ i - g₂ i :=
rfl
#align dfinsupp.sub_apply DFinsupp.sub_apply
@[simp, norm_cast]
theorem coe_sub [∀ i, AddGroup (β i)] (g₁ g₂ : Π₀ i, β i) : ⇑(g₁ - g₂) = g₁ - g₂ :=
rfl
#align dfinsupp.coe_sub DFinsupp.coe_sub
/-- Note the general `SMul` instance doesn't apply as `ℤ` is not distributive
unless `β i`'s addition is commutative. -/
instance hasIntScalar [∀ i, AddGroup (β i)] : SMul ℤ (Π₀ i, β i) :=
⟨fun c v => v.mapRange (fun _ => (c • ·)) fun _ => zsmul_zero _⟩
#align dfinsupp.has_int_scalar DFinsupp.hasIntScalar
theorem zsmul_apply [∀ i, AddGroup (β i)] (b : ℤ) (v : Π₀ i, β i) (i : ι) : (b • v) i = b • v i :=
rfl
#align dfinsupp.zsmul_apply DFinsupp.zsmul_apply
@[simp, norm_cast]
theorem coe_zsmul [∀ i, AddGroup (β i)] (b : ℤ) (v : Π₀ i, β i) : ⇑(b • v) = b • ⇑v :=
rfl
#align dfinsupp.coe_zsmul DFinsupp.coe_zsmul
instance [∀ i, AddGroup (β i)] : AddGroup (Π₀ i, β i) :=
DFunLike.coe_injective.addGroup _ coe_zero coe_add coe_neg coe_sub (fun _ _ => coe_nsmul _ _)
fun _ _ => coe_zsmul _ _
instance addCommGroup [∀ i, AddCommGroup (β i)] : AddCommGroup (Π₀ i, β i) :=
DFunLike.coe_injective.addCommGroup _ coe_zero coe_add coe_neg coe_sub (fun _ _ => coe_nsmul _ _)
fun _ _ => coe_zsmul _ _
/-- Dependent functions with finite support inherit a semiring action from an action on each
coordinate. -/
instance [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)] : SMul γ (Π₀ i, β i) :=
⟨fun c v => v.mapRange (fun _ => (c • ·)) fun _ => smul_zero _⟩
theorem smul_apply [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)] (b : γ)
(v : Π₀ i, β i) (i : ι) : (b • v) i = b • v i :=
rfl
#align dfinsupp.smul_apply DFinsupp.smul_apply
@[simp, norm_cast]
theorem coe_smul [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)] (b : γ)
(v : Π₀ i, β i) : ⇑(b • v) = b • ⇑v :=
rfl
#align dfinsupp.coe_smul DFinsupp.coe_smul
instance smulCommClass {δ : Type*} [Monoid γ] [Monoid δ] [∀ i, AddMonoid (β i)]
[∀ i, DistribMulAction γ (β i)] [∀ i, DistribMulAction δ (β i)] [∀ i, SMulCommClass γ δ (β i)] :
SMulCommClass γ δ (Π₀ i, β i) where
smul_comm r s m := ext fun i => by simp only [smul_apply, smul_comm r s (m i)]
instance isScalarTower {δ : Type*} [Monoid γ] [Monoid δ] [∀ i, AddMonoid (β i)]
[∀ i, DistribMulAction γ (β i)] [∀ i, DistribMulAction δ (β i)] [SMul γ δ]
[∀ i, IsScalarTower γ δ (β i)] : IsScalarTower γ δ (Π₀ i, β i) where
smul_assoc r s m := ext fun i => by simp only [smul_apply, smul_assoc r s (m i)]
instance isCentralScalar [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)]
[∀ i, DistribMulAction γᵐᵒᵖ (β i)] [∀ i, IsCentralScalar γ (β i)] :
IsCentralScalar γ (Π₀ i, β i) where
op_smul_eq_smul r m := ext fun i => by simp only [smul_apply, op_smul_eq_smul r (m i)]
/-- Dependent functions with finite support inherit a `DistribMulAction` structure from such a
structure on each coordinate. -/
instance distribMulAction [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)] :
DistribMulAction γ (Π₀ i, β i) :=
Function.Injective.distribMulAction coeFnAddMonoidHom DFunLike.coe_injective coe_smul
/-- Dependent functions with finite support inherit a module structure from such a structure on
each coordinate. -/
instance module [Semiring γ] [∀ i, AddCommMonoid (β i)] [∀ i, Module γ (β i)] :
Module γ (Π₀ i, β i) :=
{ inferInstanceAs (DistribMulAction γ (Π₀ i, β i)) with
zero_smul := fun c => ext fun i => by simp only [smul_apply, zero_smul, zero_apply]
add_smul := fun c x y => ext fun i => by simp only [add_apply, smul_apply, add_smul] }
#align dfinsupp.module DFinsupp.module
end Algebra
section FilterAndSubtypeDomain
/-- `Filter p f` is the function which is `f i` if `p i` is true and 0 otherwise. -/
def filter [∀ i, Zero (β i)] (p : ι → Prop) [DecidablePred p] (x : Π₀ i, β i) : Π₀ i, β i :=
⟨fun i => if p i then x i else 0,
x.support'.map fun xs =>
⟨xs.1, fun i => (xs.prop i).imp_right fun H : x i = 0 => by simp only [H, ite_self]⟩⟩
#align dfinsupp.filter DFinsupp.filter
@[simp]
theorem filter_apply [∀ i, Zero (β i)] (p : ι → Prop) [DecidablePred p] (i : ι) (f : Π₀ i, β i) :
f.filter p i = if p i then f i else 0 :=
rfl
#align dfinsupp.filter_apply DFinsupp.filter_apply
theorem filter_apply_pos [∀ i, Zero (β i)] {p : ι → Prop} [DecidablePred p] (f : Π₀ i, β i) {i : ι}
(h : p i) : f.filter p i = f i := by simp only [filter_apply, if_pos h]
#align dfinsupp.filter_apply_pos DFinsupp.filter_apply_pos
theorem filter_apply_neg [∀ i, Zero (β i)] {p : ι → Prop} [DecidablePred p] (f : Π₀ i, β i) {i : ι}
(h : ¬p i) : f.filter p i = 0 := by simp only [filter_apply, if_neg h]
#align dfinsupp.filter_apply_neg DFinsupp.filter_apply_neg
theorem filter_pos_add_filter_neg [∀ i, AddZeroClass (β i)] (f : Π₀ i, β i) (p : ι → Prop)
[DecidablePred p] : (f.filter p + f.filter fun i => ¬p i) = f :=
ext fun i => by
simp only [add_apply, filter_apply]; split_ifs <;> simp only [add_zero, zero_add]
#align dfinsupp.filter_pos_add_filter_neg DFinsupp.filter_pos_add_filter_neg
@[simp]
theorem filter_zero [∀ i, Zero (β i)] (p : ι → Prop) [DecidablePred p] :
(0 : Π₀ i, β i).filter p = 0 := by
ext
simp
#align dfinsupp.filter_zero DFinsupp.filter_zero
@[simp]
theorem filter_add [∀ i, AddZeroClass (β i)] (p : ι → Prop) [DecidablePred p] (f g : Π₀ i, β i) :
(f + g).filter p = f.filter p + g.filter p := by
ext
simp [ite_add_zero]
#align dfinsupp.filter_add DFinsupp.filter_add
@[simp]
theorem filter_smul [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)] (p : ι → Prop)
[DecidablePred p] (r : γ) (f : Π₀ i, β i) : (r • f).filter p = r • f.filter p := by
ext
simp [smul_apply, smul_ite]
#align dfinsupp.filter_smul DFinsupp.filter_smul
variable (γ β)
/-- `DFinsupp.filter` as an `AddMonoidHom`. -/
@[simps]
def filterAddMonoidHom [∀ i, AddZeroClass (β i)] (p : ι → Prop) [DecidablePred p] :
(Π₀ i, β i) →+ Π₀ i, β i where
toFun := filter p
map_zero' := filter_zero p
map_add' := filter_add p
#align dfinsupp.filter_add_monoid_hom DFinsupp.filterAddMonoidHom
#align dfinsupp.filter_add_monoid_hom_apply DFinsupp.filterAddMonoidHom_apply
/-- `DFinsupp.filter` as a `LinearMap`. -/
@[simps]
def filterLinearMap [Semiring γ] [∀ i, AddCommMonoid (β i)] [∀ i, Module γ (β i)] (p : ι → Prop)
[DecidablePred p] : (Π₀ i, β i) →ₗ[γ] Π₀ i, β i where
toFun := filter p
map_add' := filter_add p
map_smul' := filter_smul p
#align dfinsupp.filter_linear_map DFinsupp.filterLinearMap
#align dfinsupp.filter_linear_map_apply DFinsupp.filterLinearMap_apply
variable {γ β}
@[simp]
theorem filter_neg [∀ i, AddGroup (β i)] (p : ι → Prop) [DecidablePred p] (f : Π₀ i, β i) :
(-f).filter p = -f.filter p :=
(filterAddMonoidHom β p).map_neg f
#align dfinsupp.filter_neg DFinsupp.filter_neg
@[simp]
theorem filter_sub [∀ i, AddGroup (β i)] (p : ι → Prop) [DecidablePred p] (f g : Π₀ i, β i) :
(f - g).filter p = f.filter p - g.filter p :=
(filterAddMonoidHom β p).map_sub f g
#align dfinsupp.filter_sub DFinsupp.filter_sub
/-- `subtypeDomain p f` is the restriction of the finitely supported function
`f` to the subtype `p`. -/
def subtypeDomain [∀ i, Zero (β i)] (p : ι → Prop) [DecidablePred p] (x : Π₀ i, β i) :
Π₀ i : Subtype p, β i :=
⟨fun i => x (i : ι),
x.support'.map fun xs =>
⟨(Multiset.filter p xs.1).attach.map fun j => ⟨j.1, (Multiset.mem_filter.1 j.2).2⟩, fun i =>
(xs.prop i).imp_left fun H =>
Multiset.mem_map.2
⟨⟨i, Multiset.mem_filter.2 ⟨H, i.2⟩⟩, Multiset.mem_attach _ _, Subtype.eta _ _⟩⟩⟩
#align dfinsupp.subtype_domain DFinsupp.subtypeDomain
@[simp]
theorem subtypeDomain_zero [∀ i, Zero (β i)] {p : ι → Prop} [DecidablePred p] :
subtypeDomain p (0 : Π₀ i, β i) = 0 :=
rfl
#align dfinsupp.subtype_domain_zero DFinsupp.subtypeDomain_zero
@[simp]
theorem subtypeDomain_apply [∀ i, Zero (β i)] {p : ι → Prop} [DecidablePred p] {i : Subtype p}
{v : Π₀ i, β i} : (subtypeDomain p v) i = v i :=
rfl
#align dfinsupp.subtype_domain_apply DFinsupp.subtypeDomain_apply
@[simp]
theorem subtypeDomain_add [∀ i, AddZeroClass (β i)] {p : ι → Prop} [DecidablePred p]
(v v' : Π₀ i, β i) : (v + v').subtypeDomain p = v.subtypeDomain p + v'.subtypeDomain p :=
DFunLike.coe_injective rfl
#align dfinsupp.subtype_domain_add DFinsupp.subtypeDomain_add
@[simp]
theorem subtypeDomain_smul [Monoid γ] [∀ i, AddMonoid (β i)] [∀ i, DistribMulAction γ (β i)]
{p : ι → Prop} [DecidablePred p] (r : γ) (f : Π₀ i, β i) :
(r • f).subtypeDomain p = r • f.subtypeDomain p :=
DFunLike.coe_injective rfl
#align dfinsupp.subtype_domain_smul DFinsupp.subtypeDomain_smul
variable (γ β)
/-- `subtypeDomain` but as an `AddMonoidHom`. -/
@[simps]
def subtypeDomainAddMonoidHom [∀ i, AddZeroClass (β i)] (p : ι → Prop) [DecidablePred p] :
(Π₀ i : ι, β i) →+ Π₀ i : Subtype p, β i where
toFun := subtypeDomain p
map_zero' := subtypeDomain_zero
map_add' := subtypeDomain_add
#align dfinsupp.subtype_domain_add_monoid_hom DFinsupp.subtypeDomainAddMonoidHom
#align dfinsupp.subtype_domain_add_monoid_hom_apply DFinsupp.subtypeDomainAddMonoidHom_apply
/-- `DFinsupp.subtypeDomain` as a `LinearMap`. -/
@[simps]
def subtypeDomainLinearMap [Semiring γ] [∀ i, AddCommMonoid (β i)] [∀ i, Module γ (β i)]
(p : ι → Prop) [DecidablePred p] : (Π₀ i, β i) →ₗ[γ] Π₀ i : Subtype p, β i where
toFun := subtypeDomain p
map_add' := subtypeDomain_add
map_smul' := subtypeDomain_smul
#align dfinsupp.subtype_domain_linear_map DFinsupp.subtypeDomainLinearMap
#align dfinsupp.subtype_domain_linear_map_apply DFinsupp.subtypeDomainLinearMap_apply
variable {γ β}
@[simp]
theorem subtypeDomain_neg [∀ i, AddGroup (β i)] {p : ι → Prop} [DecidablePred p] {v : Π₀ i, β i} :
(-v).subtypeDomain p = -v.subtypeDomain p :=
DFunLike.coe_injective rfl
#align dfinsupp.subtype_domain_neg DFinsupp.subtypeDomain_neg
@[simp]
theorem subtypeDomain_sub [∀ i, AddGroup (β i)] {p : ι → Prop} [DecidablePred p]
{v v' : Π₀ i, β i} : (v - v').subtypeDomain p = v.subtypeDomain p - v'.subtypeDomain p :=
DFunLike.coe_injective rfl
#align dfinsupp.subtype_domain_sub DFinsupp.subtypeDomain_sub
end FilterAndSubtypeDomain
variable [DecidableEq ι]
section Basic
variable [∀ i, Zero (β i)]
theorem finite_support (f : Π₀ i, β i) : Set.Finite { i | f i ≠ 0 } :=
Trunc.induction_on f.support' fun xs ↦
xs.1.finite_toSet.subset fun i H ↦ ((xs.prop i).resolve_right H)
#align dfinsupp.finite_support DFinsupp.finite_support
/-- Create an element of `Π₀ i, β i` from a finset `s` and a function `x`
defined on this `Finset`. -/
def mk (s : Finset ι) (x : ∀ i : (↑s : Set ι), β (i : ι)) : Π₀ i, β i :=
⟨fun i => if H : i ∈ s then x ⟨i, H⟩ else 0,
Trunc.mk ⟨s.1, fun i => if H : i ∈ s then Or.inl H else Or.inr <| dif_neg H⟩⟩
#align dfinsupp.mk DFinsupp.mk
variable {s : Finset ι} {x : ∀ i : (↑s : Set ι), β i} {i : ι}
@[simp]
theorem mk_apply : (mk s x : ∀ i, β i) i = if H : i ∈ s then x ⟨i, H⟩ else 0 :=
rfl
#align dfinsupp.mk_apply DFinsupp.mk_apply
theorem mk_of_mem (hi : i ∈ s) : (mk s x : ∀ i, β i) i = x ⟨i, hi⟩ :=
dif_pos hi
#align dfinsupp.mk_of_mem DFinsupp.mk_of_mem
theorem mk_of_not_mem (hi : i ∉ s) : (mk s x : ∀ i, β i) i = 0 :=
dif_neg hi
#align dfinsupp.mk_of_not_mem DFinsupp.mk_of_not_mem
theorem mk_injective (s : Finset ι) : Function.Injective (@mk ι β _ _ s) := by
intro x y H
ext i
have h1 : (mk s x : ∀ i, β i) i = (mk s y : ∀ i, β i) i := by rw [H]
obtain ⟨i, hi : i ∈ s⟩ := i
dsimp only [mk_apply, Subtype.coe_mk] at h1
simpa only [dif_pos hi] using h1
#align dfinsupp.mk_injective DFinsupp.mk_injective
instance unique [∀ i, Subsingleton (β i)] : Unique (Π₀ i, β i) :=
DFunLike.coe_injective.unique
#align dfinsupp.unique DFinsupp.unique
instance uniqueOfIsEmpty [IsEmpty ι] : Unique (Π₀ i, β i) :=
DFunLike.coe_injective.unique
#align dfinsupp.unique_of_is_empty DFinsupp.uniqueOfIsEmpty
/-- Given `Fintype ι`, `equivFunOnFintype` is the `Equiv` between `Π₀ i, β i` and `Π i, β i`.
(All dependent functions on a finite type are finitely supported.) -/
@[simps apply]
def equivFunOnFintype [Fintype ι] : (Π₀ i, β i) ≃ ∀ i, β i where
toFun := (⇑)
invFun f := ⟨f, Trunc.mk ⟨Finset.univ.1, fun _ => Or.inl <| Finset.mem_univ_val _⟩⟩
left_inv _ := DFunLike.coe_injective rfl
right_inv _ := rfl
#align dfinsupp.equiv_fun_on_fintype DFinsupp.equivFunOnFintype
#align dfinsupp.equiv_fun_on_fintype_apply DFinsupp.equivFunOnFintype_apply
@[simp]
theorem equivFunOnFintype_symm_coe [Fintype ι] (f : Π₀ i, β i) : equivFunOnFintype.symm f = f :=
Equiv.symm_apply_apply _ _
#align dfinsupp.equiv_fun_on_fintype_symm_coe DFinsupp.equivFunOnFintype_symm_coe
/-- The function `single i b : Π₀ i, β i` sends `i` to `b`
and all other points to `0`. -/
def single (i : ι) (b : β i) : Π₀ i, β i :=
⟨Pi.single i b,
Trunc.mk ⟨{i}, fun j => (Decidable.eq_or_ne j i).imp (by simp) fun h => Pi.single_eq_of_ne h _⟩⟩
#align dfinsupp.single DFinsupp.single
theorem single_eq_pi_single {i b} : ⇑(single i b : Π₀ i, β i) = Pi.single i b :=
rfl
#align dfinsupp.single_eq_pi_single DFinsupp.single_eq_pi_single
@[simp]
theorem single_apply {i i' b} :
(single i b : Π₀ i, β i) i' = if h : i = i' then Eq.recOn h b else 0 := by
rw [single_eq_pi_single, Pi.single, Function.update]
simp [@eq_comm _ i i']
#align dfinsupp.single_apply DFinsupp.single_apply
@[simp]
theorem single_zero (i) : (single i 0 : Π₀ i, β i) = 0 :=
DFunLike.coe_injective <| Pi.single_zero _
#align dfinsupp.single_zero DFinsupp.single_zero
-- @[simp] -- Porting note (#10618): simp can prove this
theorem single_eq_same {i b} : (single i b : Π₀ i, β i) i = b := by
simp only [single_apply, dite_eq_ite, ite_true]
#align dfinsupp.single_eq_same DFinsupp.single_eq_same
theorem single_eq_of_ne {i i' b} (h : i ≠ i') : (single i b : Π₀ i, β i) i' = 0 := by
simp only [single_apply, dif_neg h]
#align dfinsupp.single_eq_of_ne DFinsupp.single_eq_of_ne
theorem single_injective {i} : Function.Injective (single i : β i → Π₀ i, β i) := fun _ _ H =>
Pi.single_injective β i <| DFunLike.coe_injective.eq_iff.mpr H
#align dfinsupp.single_injective DFinsupp.single_injective
/-- Like `Finsupp.single_eq_single_iff`, but with a `HEq` due to dependent types -/
theorem single_eq_single_iff (i j : ι) (xi : β i) (xj : β j) :
DFinsupp.single i xi = DFinsupp.single j xj ↔ i = j ∧ HEq xi xj ∨ xi = 0 ∧ xj = 0 := by
constructor
· intro h
by_cases hij : i = j
· subst hij
exact Or.inl ⟨rfl, heq_of_eq (DFinsupp.single_injective h)⟩
· have h_coe : ⇑(DFinsupp.single i xi) = DFinsupp.single j xj := congr_arg (⇑) h
have hci := congr_fun h_coe i
have hcj := congr_fun h_coe j
rw [DFinsupp.single_eq_same] at hci hcj
rw [DFinsupp.single_eq_of_ne (Ne.symm hij)] at hci
rw [DFinsupp.single_eq_of_ne hij] at hcj
exact Or.inr ⟨hci, hcj.symm⟩
· rintro (⟨rfl, hxi⟩ | ⟨hi, hj⟩)
· rw [eq_of_heq hxi]
· rw [hi, hj, DFinsupp.single_zero, DFinsupp.single_zero]
#align dfinsupp.single_eq_single_iff DFinsupp.single_eq_single_iff
/-- `DFinsupp.single a b` is injective in `a`. For the statement that it is injective in `b`, see
`DFinsupp.single_injective` -/
theorem single_left_injective {b : ∀ i : ι, β i} (h : ∀ i, b i ≠ 0) :
Function.Injective (fun i => single i (b i) : ι → Π₀ i, β i) := fun _ _ H =>
(((single_eq_single_iff _ _ _ _).mp H).resolve_right fun hb => h _ hb.1).left
#align dfinsupp.single_left_injective DFinsupp.single_left_injective
@[simp]
theorem single_eq_zero {i : ι} {xi : β i} : single i xi = 0 ↔ xi = 0 := by
rw [← single_zero i, single_eq_single_iff]
simp
#align dfinsupp.single_eq_zero DFinsupp.single_eq_zero
theorem filter_single (p : ι → Prop) [DecidablePred p] (i : ι) (x : β i) :
(single i x).filter p = if p i then single i x else 0 := by
ext j
have := apply_ite (fun x : Π₀ i, β i => x j) (p i) (single i x) 0
dsimp at this
rw [filter_apply, this]
obtain rfl | hij := Decidable.eq_or_ne i j
· rfl
· rw [single_eq_of_ne hij, ite_self, ite_self]
#align dfinsupp.filter_single DFinsupp.filter_single
@[simp]
theorem filter_single_pos {p : ι → Prop} [DecidablePred p] (i : ι) (x : β i) (h : p i) :
(single i x).filter p = single i x := by rw [filter_single, if_pos h]
#align dfinsupp.filter_single_pos DFinsupp.filter_single_pos
@[simp]
theorem filter_single_neg {p : ι → Prop} [DecidablePred p] (i : ι) (x : β i) (h : ¬p i) :
(single i x).filter p = 0 := by rw [filter_single, if_neg h]
#align dfinsupp.filter_single_neg DFinsupp.filter_single_neg
/-- Equality of sigma types is sufficient (but not necessary) to show equality of `DFinsupp`s. -/
theorem single_eq_of_sigma_eq {i j} {xi : β i} {xj : β j} (h : (⟨i, xi⟩ : Sigma β) = ⟨j, xj⟩) :
DFinsupp.single i xi = DFinsupp.single j xj := by
cases h
rfl
#align dfinsupp.single_eq_of_sigma_eq DFinsupp.single_eq_of_sigma_eq
@[simp]
theorem equivFunOnFintype_single [Fintype ι] (i : ι) (m : β i) :
(@DFinsupp.equivFunOnFintype ι β _ _) (DFinsupp.single i m) = Pi.single i m := by
ext x
dsimp [Pi.single, Function.update]
simp [DFinsupp.single_eq_pi_single, @eq_comm _ i]
#align dfinsupp.equiv_fun_on_fintype_single DFinsupp.equivFunOnFintype_single
@[simp]
theorem equivFunOnFintype_symm_single [Fintype ι] (i : ι) (m : β i) :
(@DFinsupp.equivFunOnFintype ι β _ _).symm (Pi.single i m) = DFinsupp.single i m := by
ext i'
simp only [← single_eq_pi_single, equivFunOnFintype_symm_coe]
#align dfinsupp.equiv_fun_on_fintype_symm_single DFinsupp.equivFunOnFintype_symm_single
section SingleAndZipWith
variable [∀ i, Zero (β₁ i)] [∀ i, Zero (β₂ i)]
@[simp]
theorem zipWith_single_single (f : ∀ i, β₁ i → β₂ i → β i) (hf : ∀ i, f i 0 0 = 0)
{i} (b₁ : β₁ i) (b₂ : β₂ i) :
zipWith f hf (single i b₁) (single i b₂) = single i (f i b₁ b₂) := by
ext j
rw [zipWith_apply]
obtain rfl | hij := Decidable.eq_or_ne i j
· rw [single_eq_same, single_eq_same, single_eq_same]
· rw [single_eq_of_ne hij, single_eq_of_ne hij, single_eq_of_ne hij, hf]
end SingleAndZipWith
/-- Redefine `f i` to be `0`. -/
def erase (i : ι) (x : Π₀ i, β i) : Π₀ i, β i :=
⟨fun j ↦ if j = i then 0 else x.1 j,
x.support'.map fun xs ↦ ⟨xs.1, fun j ↦ (xs.prop j).imp_right (by simp only [·, ite_self])⟩⟩
#align dfinsupp.erase DFinsupp.erase
@[simp]
theorem erase_apply {i j : ι} {f : Π₀ i, β i} : (f.erase i) j = if j = i then 0 else f j :=
rfl
#align dfinsupp.erase_apply DFinsupp.erase_apply
-- @[simp] -- Porting note (#10618): simp can prove this
theorem erase_same {i : ι} {f : Π₀ i, β i} : (f.erase i) i = 0 := by simp
#align dfinsupp.erase_same DFinsupp.erase_same
theorem erase_ne {i i' : ι} {f : Π₀ i, β i} (h : i' ≠ i) : (f.erase i) i' = f i' := by simp [h]
#align dfinsupp.erase_ne DFinsupp.erase_ne
theorem piecewise_single_erase (x : Π₀ i, β i) (i : ι)
[∀ i' : ι, Decidable <| (i' ∈ ({i} : Set ι))] : -- Porting note: added Decidable hypothesis
(single i (x i)).piecewise (x.erase i) {i} = x := by
ext j; rw [piecewise_apply]; split_ifs with h
· rw [(id h : j = i), single_eq_same]
· exact erase_ne h
#align dfinsupp.piecewise_single_erase DFinsupp.piecewise_single_erase
theorem erase_eq_sub_single {β : ι → Type*} [∀ i, AddGroup (β i)] (f : Π₀ i, β i) (i : ι) :
f.erase i = f - single i (f i) := by
ext j
rcases eq_or_ne i j with (rfl | h)
· simp
· simp [erase_ne h.symm, single_eq_of_ne h, @eq_comm _ j, h]
#align dfinsupp.erase_eq_sub_single DFinsupp.erase_eq_sub_single
@[simp]
theorem erase_zero (i : ι) : erase i (0 : Π₀ i, β i) = 0 :=
ext fun _ => ite_self _
#align dfinsupp.erase_zero DFinsupp.erase_zero
@[simp]
theorem filter_ne_eq_erase (f : Π₀ i, β i) (i : ι) : f.filter (· ≠ i) = f.erase i := by
ext1 j
simp only [DFinsupp.filter_apply, DFinsupp.erase_apply, ite_not]
#align dfinsupp.filter_ne_eq_erase DFinsupp.filter_ne_eq_erase
@[simp]
theorem filter_ne_eq_erase' (f : Π₀ i, β i) (i : ι) : f.filter (i ≠ ·) = f.erase i := by
rw [← filter_ne_eq_erase f i]
congr with j
exact ne_comm
#align dfinsupp.filter_ne_eq_erase' DFinsupp.filter_ne_eq_erase'
theorem erase_single (j : ι) (i : ι) (x : β i) :
(single i x).erase j = if i = j then 0 else single i x := by
rw [← filter_ne_eq_erase, filter_single, ite_not]
#align dfinsupp.erase_single DFinsupp.erase_single
@[simp]
theorem erase_single_same (i : ι) (x : β i) : (single i x).erase i = 0 := by
rw [erase_single, if_pos rfl]
#align dfinsupp.erase_single_same DFinsupp.erase_single_same
@[simp]
theorem erase_single_ne {i j : ι} (x : β i) (h : i ≠ j) : (single i x).erase j = single i x := by
rw [erase_single, if_neg h]
#align dfinsupp.erase_single_ne DFinsupp.erase_single_ne
section Update
variable (f : Π₀ i, β i) (i) (b : β i)
/-- Replace the value of a `Π₀ i, β i` at a given point `i : ι` by a given value `b : β i`.
If `b = 0`, this amounts to removing `i` from the support.
Otherwise, `i` is added to it.
This is the (dependent) finitely-supported version of `Function.update`. -/
def update : Π₀ i, β i :=
⟨Function.update f i b,
f.support'.map fun s =>
⟨i ::ₘ s.1, fun j => by
rcases eq_or_ne i j with (rfl | hi)
· simp
· obtain hj | (hj : f j = 0) := s.prop j
· exact Or.inl (Multiset.mem_cons_of_mem hj)
· exact Or.inr ((Function.update_noteq hi.symm b _).trans hj)⟩⟩
#align dfinsupp.update DFinsupp.update
variable (j : ι)
@[simp, norm_cast] lemma coe_update : (f.update i b : ∀ i : ι, β i) = Function.update f i b := rfl
#align dfinsupp.coe_update DFinsupp.coe_update
@[simp]
theorem update_self : f.update i (f i) = f := by
ext
simp
#align dfinsupp.update_self DFinsupp.update_self
@[simp]
theorem update_eq_erase : f.update i 0 = f.erase i := by
ext j
rcases eq_or_ne i j with (rfl | hi)
· simp
· simp [hi.symm]
#align dfinsupp.update_eq_erase DFinsupp.update_eq_erase
theorem update_eq_single_add_erase {β : ι → Type*} [∀ i, AddZeroClass (β i)] (f : Π₀ i, β i)
(i : ι) (b : β i) : f.update i b = single i b + f.erase i := by
ext j
rcases eq_or_ne i j with (rfl | h)
· simp
· simp [Function.update_noteq h.symm, h, erase_ne, h.symm]
#align dfinsupp.update_eq_single_add_erase DFinsupp.update_eq_single_add_erase
theorem update_eq_erase_add_single {β : ι → Type*} [∀ i, AddZeroClass (β i)] (f : Π₀ i, β i)
(i : ι) (b : β i) : f.update i b = f.erase i + single i b := by
ext j
rcases eq_or_ne i j with (rfl | h)
· simp
· simp [Function.update_noteq h.symm, h, erase_ne, h.symm]
#align dfinsupp.update_eq_erase_add_single DFinsupp.update_eq_erase_add_single
theorem update_eq_sub_add_single {β : ι → Type*} [∀ i, AddGroup (β i)] (f : Π₀ i, β i) (i : ι)
(b : β i) : f.update i b = f - single i (f i) + single i b := by
rw [update_eq_erase_add_single f i b, erase_eq_sub_single f i]
#align dfinsupp.update_eq_sub_add_single DFinsupp.update_eq_sub_add_single
end Update
end Basic
section AddMonoid
variable [∀ i, AddZeroClass (β i)]
@[simp]
theorem single_add (i : ι) (b₁ b₂ : β i) : single i (b₁ + b₂) = single i b₁ + single i b₂ :=
(zipWith_single_single (fun _ => (· + ·)) _ b₁ b₂).symm
#align dfinsupp.single_add DFinsupp.single_add
@[simp]
theorem erase_add (i : ι) (f₁ f₂ : Π₀ i, β i) : erase i (f₁ + f₂) = erase i f₁ + erase i f₂ :=
ext fun _ => by simp [ite_zero_add]
#align dfinsupp.erase_add DFinsupp.erase_add
variable (β)
/-- `DFinsupp.single` as an `AddMonoidHom`. -/
@[simps]
def singleAddHom (i : ι) : β i →+ Π₀ i, β i where
toFun := single i
map_zero' := single_zero i
map_add' := single_add i
#align dfinsupp.single_add_hom DFinsupp.singleAddHom
#align dfinsupp.single_add_hom_apply DFinsupp.singleAddHom_apply
/-- `DFinsupp.erase` as an `AddMonoidHom`. -/
@[simps]
def eraseAddHom (i : ι) : (Π₀ i, β i) →+ Π₀ i, β i where
toFun := erase i
map_zero' := erase_zero i
map_add' := erase_add i
#align dfinsupp.erase_add_hom DFinsupp.eraseAddHom
#align dfinsupp.erase_add_hom_apply DFinsupp.eraseAddHom_apply
variable {β}
@[simp]
theorem single_neg {β : ι → Type v} [∀ i, AddGroup (β i)] (i : ι) (x : β i) :
single i (-x) = -single i x :=
(singleAddHom β i).map_neg x
#align dfinsupp.single_neg DFinsupp.single_neg
@[simp]
theorem single_sub {β : ι → Type v} [∀ i, AddGroup (β i)] (i : ι) (x y : β i) :
single i (x - y) = single i x - single i y :=
(singleAddHom β i).map_sub x y
#align dfinsupp.single_sub DFinsupp.single_sub
@[simp]
theorem erase_neg {β : ι → Type v} [∀ i, AddGroup (β i)] (i : ι) (f : Π₀ i, β i) :
(-f).erase i = -f.erase i :=
(eraseAddHom β i).map_neg f
#align dfinsupp.erase_neg DFinsupp.erase_neg
@[simp]
theorem erase_sub {β : ι → Type v} [∀ i, AddGroup (β i)] (i : ι) (f g : Π₀ i, β i) :
(f - g).erase i = f.erase i - g.erase i :=
(eraseAddHom β i).map_sub f g
#align dfinsupp.erase_sub DFinsupp.erase_sub
theorem single_add_erase (i : ι) (f : Π₀ i, β i) : single i (f i) + f.erase i = f :=
ext fun i' =>
if h : i = i' then by
subst h; simp only [add_apply, single_apply, erase_apply, add_zero, dite_eq_ite, if_true]
else by
simp only [add_apply, single_apply, erase_apply, dif_neg h, if_neg (Ne.symm h), zero_add]
#align dfinsupp.single_add_erase DFinsupp.single_add_erase
theorem erase_add_single (i : ι) (f : Π₀ i, β i) : f.erase i + single i (f i) = f :=
ext fun i' =>
if h : i = i' then by
subst h; simp only [add_apply, single_apply, erase_apply, zero_add, dite_eq_ite, if_true]
else by
simp only [add_apply, single_apply, erase_apply, dif_neg h, if_neg (Ne.symm h), add_zero]
#align dfinsupp.erase_add_single DFinsupp.erase_add_single
protected theorem induction {p : (Π₀ i, β i) → Prop} (f : Π₀ i, β i) (h0 : p 0)
(ha : ∀ (i b) (f : Π₀ i, β i), f i = 0 → b ≠ 0 → p f → p (single i b + f)) : p f := by
cases' f with f s
induction' s using Trunc.induction_on with s
cases' s with s H
induction' s using Multiset.induction_on with i s ih generalizing f
· have : f = 0 := funext fun i => (H i).resolve_left (Multiset.not_mem_zero _)
subst this
exact h0
have H2 : p (erase i ⟨f, Trunc.mk ⟨i ::ₘ s, H⟩⟩) := by
dsimp only [erase, Trunc.map, Trunc.bind, Trunc.liftOn, Trunc.lift_mk,
Function.comp, Subtype.coe_mk]
have H2 : ∀ j, j ∈ s ∨ ite (j = i) 0 (f j) = 0 := by
intro j
cases' H j with H2 H2
· cases' Multiset.mem_cons.1 H2 with H3 H3
· right; exact if_pos H3
· left; exact H3
right
split_ifs <;> [rfl; exact H2]
have H3 : ∀ aux, (⟨fun j : ι => ite (j = i) 0 (f j), Trunc.mk ⟨i ::ₘ s, aux⟩⟩ : Π₀ i, β i) =
⟨fun j : ι => ite (j = i) 0 (f j), Trunc.mk ⟨s, H2⟩⟩ :=
fun _ ↦ ext fun _ => rfl
rw [H3]
apply ih
have H3 : single i _ + _ = (⟨f, Trunc.mk ⟨i ::ₘ s, H⟩⟩ : Π₀ i, β i) := single_add_erase _ _
rw [← H3]
change p (single i (f i) + _)
cases' Classical.em (f i = 0) with h h
· rw [h, single_zero, zero_add]
exact H2
refine ha _ _ _ ?_ h H2
rw [erase_same]
#align dfinsupp.induction DFinsupp.induction
| Mathlib/Data/DFinsupp/Basic.lean | 980 | 988 | theorem induction₂ {p : (Π₀ i, β i) → Prop} (f : Π₀ i, β i) (h0 : p 0)
(ha : ∀ (i b) (f : Π₀ i, β i), f i = 0 → b ≠ 0 → p f → p (f + single i b)) : p f :=
DFinsupp.induction f h0 fun i b f h1 h2 h3 =>
have h4 : f + single i b = single i b + f := by |
ext j; by_cases H : i = j
· subst H
simp [h1]
· simp [H]
Eq.recOn h4 <| ha i b f h1 h2 h3
|
/-
Copyright (c) 2019 Johannes Hölzl. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl
-/
import Mathlib.Data.Finsupp.Encodable
import Mathlib.LinearAlgebra.Pi
import Mathlib.LinearAlgebra.Span
import Mathlib.Data.Set.Countable
#align_import linear_algebra.finsupp from "leanprover-community/mathlib"@"9d684a893c52e1d6692a504a118bfccbae04feeb"
/-!
# Properties of the module `α →₀ M`
Given an `R`-module `M`, the `R`-module structure on `α →₀ M` is defined in
`Data.Finsupp.Basic`.
In this file we define `Finsupp.supported s` to be the set `{f : α →₀ M | f.support ⊆ s}`
interpreted as a submodule of `α →₀ M`. We also define `LinearMap` versions of various maps:
* `Finsupp.lsingle a : M →ₗ[R] ι →₀ M`: `Finsupp.single a` as a linear map;
* `Finsupp.lapply a : (ι →₀ M) →ₗ[R] M`: the map `fun f ↦ f a` as a linear map;
* `Finsupp.lsubtypeDomain (s : Set α) : (α →₀ M) →ₗ[R] (s →₀ M)`: restriction to a subtype as a
linear map;
* `Finsupp.restrictDom`: `Finsupp.filter` as a linear map to `Finsupp.supported s`;
* `Finsupp.lsum`: `Finsupp.sum` or `Finsupp.liftAddHom` as a `LinearMap`;
* `Finsupp.total α M R (v : ι → M)`: sends `l : ι → R` to the linear combination of `v i` with
coefficients `l i`;
* `Finsupp.totalOn`: a restricted version of `Finsupp.total` with domain `Finsupp.supported R R s`
and codomain `Submodule.span R (v '' s)`;
* `Finsupp.supportedEquivFinsupp`: a linear equivalence between the functions `α →₀ M` supported
on `s` and the functions `s →₀ M`;
* `Finsupp.lmapDomain`: a linear map version of `Finsupp.mapDomain`;
* `Finsupp.domLCongr`: a `LinearEquiv` version of `Finsupp.domCongr`;
* `Finsupp.congr`: if the sets `s` and `t` are equivalent, then `supported M R s` is equivalent to
`supported M R t`;
* `Finsupp.lcongr`: a `LinearEquiv`alence between `α →₀ M` and `β →₀ N` constructed using
`e : α ≃ β` and `e' : M ≃ₗ[R] N`.
## Tags
function with finite support, module, linear algebra
-/
noncomputable section
open Set LinearMap Submodule
namespace Finsupp
section SMul
variable {α : Type*} {β : Type*} {R : Type*} {M : Type*} {M₂ : Type*}
theorem smul_sum [Zero β] [AddCommMonoid M] [DistribSMul R M] {v : α →₀ β} {c : R} {h : α → β → M} :
c • v.sum h = v.sum fun a b => c • h a b :=
Finset.smul_sum
#align finsupp.smul_sum Finsupp.smul_sum
@[simp]
theorem sum_smul_index_linearMap' [Semiring R] [AddCommMonoid M] [Module R M] [AddCommMonoid M₂]
[Module R M₂] {v : α →₀ M} {c : R} {h : α → M →ₗ[R] M₂} :
((c • v).sum fun a => h a) = c • v.sum fun a => h a := by
rw [Finsupp.sum_smul_index', Finsupp.smul_sum]
· simp only [map_smul]
· intro i
exact (h i).map_zero
#align finsupp.sum_smul_index_linear_map' Finsupp.sum_smul_index_linearMap'
end SMul
section LinearEquivFunOnFinite
variable (R : Type*) {S : Type*} (M : Type*) (α : Type*)
variable [Finite α] [AddCommMonoid M] [Semiring R] [Module R M]
/-- Given `Finite α`, `linearEquivFunOnFinite R` is the natural `R`-linear equivalence between
`α →₀ β` and `α → β`. -/
@[simps apply]
noncomputable def linearEquivFunOnFinite : (α →₀ M) ≃ₗ[R] α → M :=
{ equivFunOnFinite with
toFun := (⇑)
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
#align finsupp.linear_equiv_fun_on_finite Finsupp.linearEquivFunOnFinite
@[simp]
theorem linearEquivFunOnFinite_single [DecidableEq α] (x : α) (m : M) :
(linearEquivFunOnFinite R M α) (single x m) = Pi.single x m :=
equivFunOnFinite_single x m
#align finsupp.linear_equiv_fun_on_finite_single Finsupp.linearEquivFunOnFinite_single
@[simp]
theorem linearEquivFunOnFinite_symm_single [DecidableEq α] (x : α) (m : M) :
(linearEquivFunOnFinite R M α).symm (Pi.single x m) = single x m :=
equivFunOnFinite_symm_single x m
#align finsupp.linear_equiv_fun_on_finite_symm_single Finsupp.linearEquivFunOnFinite_symm_single
@[simp]
theorem linearEquivFunOnFinite_symm_coe (f : α →₀ M) : (linearEquivFunOnFinite R M α).symm f = f :=
(linearEquivFunOnFinite R M α).symm_apply_apply f
#align finsupp.linear_equiv_fun_on_finite_symm_coe Finsupp.linearEquivFunOnFinite_symm_coe
end LinearEquivFunOnFinite
section LinearEquiv.finsuppUnique
variable (R : Type*) {S : Type*} (M : Type*)
variable [AddCommMonoid M] [Semiring R] [Module R M]
variable (α : Type*) [Unique α]
/-- If `α` has a unique term, then the type of finitely supported functions `α →₀ M` is
`R`-linearly equivalent to `M`. -/
noncomputable def LinearEquiv.finsuppUnique : (α →₀ M) ≃ₗ[R] M :=
{ Finsupp.equivFunOnFinite.trans (Equiv.funUnique α M) with
map_add' := fun _ _ => rfl
map_smul' := fun _ _ => rfl }
#align finsupp.linear_equiv.finsupp_unique Finsupp.LinearEquiv.finsuppUnique
variable {R M}
@[simp]
theorem LinearEquiv.finsuppUnique_apply (f : α →₀ M) :
LinearEquiv.finsuppUnique R M α f = f default :=
rfl
#align finsupp.linear_equiv.finsupp_unique_apply Finsupp.LinearEquiv.finsuppUnique_apply
variable {α}
@[simp]
theorem LinearEquiv.finsuppUnique_symm_apply [Unique α] (m : M) :
(LinearEquiv.finsuppUnique R M α).symm m = Finsupp.single default m := by
ext; simp [LinearEquiv.finsuppUnique, Equiv.funUnique, single, Pi.single,
equivFunOnFinite, Function.update]
#align finsupp.linear_equiv.finsupp_unique_symm_apply Finsupp.LinearEquiv.finsuppUnique_symm_apply
end LinearEquiv.finsuppUnique
variable {α : Type*} {M : Type*} {N : Type*} {P : Type*} {R : Type*} {S : Type*}
variable [Semiring R] [Semiring S] [AddCommMonoid M] [Module R M]
variable [AddCommMonoid N] [Module R N]
variable [AddCommMonoid P] [Module R P]
/-- Interpret `Finsupp.single a` as a linear map. -/
def lsingle (a : α) : M →ₗ[R] α →₀ M :=
{ Finsupp.singleAddHom a with map_smul' := fun _ _ => (smul_single _ _ _).symm }
#align finsupp.lsingle Finsupp.lsingle
/-- Two `R`-linear maps from `Finsupp X M` which agree on each `single x y` agree everywhere. -/
theorem lhom_ext ⦃φ ψ : (α →₀ M) →ₗ[R] N⦄ (h : ∀ a b, φ (single a b) = ψ (single a b)) : φ = ψ :=
LinearMap.toAddMonoidHom_injective <| addHom_ext h
#align finsupp.lhom_ext Finsupp.lhom_ext
/-- Two `R`-linear maps from `Finsupp X M` which agree on each `single x y` agree everywhere.
We formulate this fact using equality of linear maps `φ.comp (lsingle a)` and `ψ.comp (lsingle a)`
so that the `ext` tactic can apply a type-specific extensionality lemma to prove equality of these
maps. E.g., if `M = R`, then it suffices to verify `φ (single a 1) = ψ (single a 1)`. -/
-- Porting note: The priority should be higher than `LinearMap.ext`.
@[ext high]
theorem lhom_ext' ⦃φ ψ : (α →₀ M) →ₗ[R] N⦄ (h : ∀ a, φ.comp (lsingle a) = ψ.comp (lsingle a)) :
φ = ψ :=
lhom_ext fun a => LinearMap.congr_fun (h a)
#align finsupp.lhom_ext' Finsupp.lhom_ext'
/-- Interpret `fun f : α →₀ M ↦ f a` as a linear map. -/
def lapply (a : α) : (α →₀ M) →ₗ[R] M :=
{ Finsupp.applyAddHom a with map_smul' := fun _ _ => rfl }
#align finsupp.lapply Finsupp.lapply
section CompatibleSMul
variable (R S M N ι : Type*)
variable [Semiring S] [AddCommMonoid M] [AddCommMonoid N] [Module S M] [Module S N]
instance _root_.LinearMap.CompatibleSMul.finsupp_dom [SMulZeroClass R M] [DistribSMul R N]
[LinearMap.CompatibleSMul M N R S] : LinearMap.CompatibleSMul (ι →₀ M) N R S where
map_smul f r m := by
conv_rhs => rw [← sum_single m, map_finsupp_sum, smul_sum]
erw [← sum_single (r • m), sum_mapRange_index single_zero, map_finsupp_sum]
congr; ext i m; exact (f.comp <| lsingle i).map_smul_of_tower r m
instance _root_.LinearMap.CompatibleSMul.finsupp_cod [SMul R M] [SMulZeroClass R N]
[LinearMap.CompatibleSMul M N R S] : LinearMap.CompatibleSMul M (ι →₀ N) R S where
map_smul f r m := by ext i; apply ((lapply i).comp f).map_smul_of_tower
end CompatibleSMul
/-- Forget that a function is finitely supported.
This is the linear version of `Finsupp.toFun`. -/
@[simps]
def lcoeFun : (α →₀ M) →ₗ[R] α → M where
toFun := (⇑)
map_add' x y := by
ext
simp
map_smul' x y := by
ext
simp
#align finsupp.lcoe_fun Finsupp.lcoeFun
section LSubtypeDomain
variable (s : Set α)
/-- Interpret `Finsupp.subtypeDomain s` as a linear map. -/
def lsubtypeDomain : (α →₀ M) →ₗ[R] s →₀ M where
toFun := subtypeDomain fun x => x ∈ s
map_add' _ _ := subtypeDomain_add
map_smul' _ _ := ext fun _ => rfl
#align finsupp.lsubtype_domain Finsupp.lsubtypeDomain
theorem lsubtypeDomain_apply (f : α →₀ M) :
(lsubtypeDomain s : (α →₀ M) →ₗ[R] s →₀ M) f = subtypeDomain (fun x => x ∈ s) f :=
rfl
#align finsupp.lsubtype_domain_apply Finsupp.lsubtypeDomain_apply
end LSubtypeDomain
@[simp]
theorem lsingle_apply (a : α) (b : M) : (lsingle a : M →ₗ[R] α →₀ M) b = single a b :=
rfl
#align finsupp.lsingle_apply Finsupp.lsingle_apply
@[simp]
theorem lapply_apply (a : α) (f : α →₀ M) : (lapply a : (α →₀ M) →ₗ[R] M) f = f a :=
rfl
#align finsupp.lapply_apply Finsupp.lapply_apply
@[simp]
theorem lapply_comp_lsingle_same (a : α) : lapply a ∘ₗ lsingle a = (.id : M →ₗ[R] M) := by ext; simp
@[simp]
theorem lapply_comp_lsingle_of_ne (a a' : α) (h : a ≠ a') :
lapply a ∘ₗ lsingle a' = (0 : M →ₗ[R] M) := by ext; simp [h.symm]
@[simp]
theorem ker_lsingle (a : α) : ker (lsingle a : M →ₗ[R] α →₀ M) = ⊥ :=
ker_eq_bot_of_injective (single_injective a)
#align finsupp.ker_lsingle Finsupp.ker_lsingle
theorem lsingle_range_le_ker_lapply (s t : Set α) (h : Disjoint s t) :
⨆ a ∈ s, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M) ≤
⨅ a ∈ t, ker (lapply a : (α →₀ M) →ₗ[R] M) := by
refine iSup_le fun a₁ => iSup_le fun h₁ => range_le_iff_comap.2 ?_
simp only [(ker_comp _ _).symm, eq_top_iff, SetLike.le_def, mem_ker, comap_iInf, mem_iInf]
intro b _ a₂ h₂
have : a₁ ≠ a₂ := fun eq => h.le_bot ⟨h₁, eq.symm ▸ h₂⟩
exact single_eq_of_ne this
#align finsupp.lsingle_range_le_ker_lapply Finsupp.lsingle_range_le_ker_lapply
theorem iInf_ker_lapply_le_bot : ⨅ a, ker (lapply a : (α →₀ M) →ₗ[R] M) ≤ ⊥ := by
simp only [SetLike.le_def, mem_iInf, mem_ker, mem_bot, lapply_apply]
exact fun a h => Finsupp.ext h
#align finsupp.infi_ker_lapply_le_bot Finsupp.iInf_ker_lapply_le_bot
theorem iSup_lsingle_range : ⨆ a, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M) = ⊤ := by
refine eq_top_iff.2 <| SetLike.le_def.2 fun f _ => ?_
rw [← sum_single f]
exact sum_mem fun a _ => Submodule.mem_iSup_of_mem a ⟨_, rfl⟩
#align finsupp.supr_lsingle_range Finsupp.iSup_lsingle_range
theorem disjoint_lsingle_lsingle (s t : Set α) (hs : Disjoint s t) :
Disjoint (⨆ a ∈ s, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M))
(⨆ a ∈ t, LinearMap.range (lsingle a : M →ₗ[R] α →₀ M)) := by
-- Porting note: 2 placeholders are added to prevent timeout.
refine
(Disjoint.mono
(lsingle_range_le_ker_lapply s sᶜ ?_)
(lsingle_range_le_ker_lapply t tᶜ ?_))
?_
· apply disjoint_compl_right
· apply disjoint_compl_right
rw [disjoint_iff_inf_le]
refine le_trans (le_iInf fun i => ?_) iInf_ker_lapply_le_bot
classical
by_cases his : i ∈ s
· by_cases hit : i ∈ t
· exact (hs.le_bot ⟨his, hit⟩).elim
exact inf_le_of_right_le (iInf_le_of_le i <| iInf_le _ hit)
exact inf_le_of_left_le (iInf_le_of_le i <| iInf_le _ his)
#align finsupp.disjoint_lsingle_lsingle Finsupp.disjoint_lsingle_lsingle
theorem span_single_image (s : Set M) (a : α) :
Submodule.span R (single a '' s) = (Submodule.span R s).map (lsingle a : M →ₗ[R] α →₀ M) := by
rw [← span_image]; rfl
#align finsupp.span_single_image Finsupp.span_single_image
variable (M R)
/-- `Finsupp.supported M R s` is the `R`-submodule of all `p : α →₀ M` such that `p.support ⊆ s`. -/
def supported (s : Set α) : Submodule R (α →₀ M) where
carrier := { p | ↑p.support ⊆ s }
add_mem' {p q} hp hq := by
classical
refine Subset.trans (Subset.trans (Finset.coe_subset.2 support_add) ?_) (union_subset hp hq)
rw [Finset.coe_union]
zero_mem' := by
simp only [subset_def, Finset.mem_coe, Set.mem_setOf_eq, mem_support_iff, zero_apply]
intro h ha
exact (ha rfl).elim
smul_mem' a p hp := Subset.trans (Finset.coe_subset.2 support_smul) hp
#align finsupp.supported Finsupp.supported
variable {M}
theorem mem_supported {s : Set α} (p : α →₀ M) : p ∈ supported M R s ↔ ↑p.support ⊆ s :=
Iff.rfl
#align finsupp.mem_supported Finsupp.mem_supported
theorem mem_supported' {s : Set α} (p : α →₀ M) :
p ∈ supported M R s ↔ ∀ x ∉ s, p x = 0 := by
haveI := Classical.decPred fun x : α => x ∈ s; simp [mem_supported, Set.subset_def, not_imp_comm]
#align finsupp.mem_supported' Finsupp.mem_supported'
theorem mem_supported_support (p : α →₀ M) : p ∈ Finsupp.supported M R (p.support : Set α) := by
rw [Finsupp.mem_supported]
#align finsupp.mem_supported_support Finsupp.mem_supported_support
theorem single_mem_supported {s : Set α} {a : α} (b : M) (h : a ∈ s) :
single a b ∈ supported M R s :=
Set.Subset.trans support_single_subset (Finset.singleton_subset_set_iff.2 h)
#align finsupp.single_mem_supported Finsupp.single_mem_supported
theorem supported_eq_span_single (s : Set α) :
supported R R s = span R ((fun i => single i 1) '' s) := by
refine (span_eq_of_le _ ?_ (SetLike.le_def.2 fun l hl => ?_)).symm
· rintro _ ⟨_, hp, rfl⟩
exact single_mem_supported R 1 hp
· rw [← l.sum_single]
refine sum_mem fun i il => ?_
-- Porting note: Needed to help this convert quite a bit replacing underscores
convert smul_mem (M := α →₀ R) (x := single i 1) (span R ((fun i => single i 1) '' s)) (l i) ?_
· simp [span]
· apply subset_span
apply Set.mem_image_of_mem _ (hl il)
#align finsupp.supported_eq_span_single Finsupp.supported_eq_span_single
variable (M)
/-- Interpret `Finsupp.filter s` as a linear map from `α →₀ M` to `supported M R s`. -/
def restrictDom (s : Set α) [DecidablePred (· ∈ s)] : (α →₀ M) →ₗ[R] supported M R s :=
LinearMap.codRestrict _
{ toFun := filter (· ∈ s)
map_add' := fun _ _ => filter_add
map_smul' := fun _ _ => filter_smul } fun l =>
(mem_supported' _ _).2 fun _ => filter_apply_neg (· ∈ s) l
#align finsupp.restrict_dom Finsupp.restrictDom
variable {M R}
section
@[simp]
theorem restrictDom_apply (s : Set α) (l : α →₀ M) [DecidablePred (· ∈ s)]:
(restrictDom M R s l : α →₀ M) = Finsupp.filter (· ∈ s) l := rfl
#align finsupp.restrict_dom_apply Finsupp.restrictDom_apply
end
theorem restrictDom_comp_subtype (s : Set α) [DecidablePred (· ∈ s)] :
(restrictDom M R s).comp (Submodule.subtype _) = LinearMap.id := by
ext l a
by_cases h : a ∈ s <;> simp [h]
exact ((mem_supported' R l.1).1 l.2 a h).symm
#align finsupp.restrict_dom_comp_subtype Finsupp.restrictDom_comp_subtype
theorem range_restrictDom (s : Set α) [DecidablePred (· ∈ s)] :
LinearMap.range (restrictDom M R s) = ⊤ :=
range_eq_top.2 <|
Function.RightInverse.surjective <| LinearMap.congr_fun (restrictDom_comp_subtype s)
#align finsupp.range_restrict_dom Finsupp.range_restrictDom
theorem supported_mono {s t : Set α} (st : s ⊆ t) : supported M R s ≤ supported M R t := fun _ h =>
Set.Subset.trans h st
#align finsupp.supported_mono Finsupp.supported_mono
@[simp]
theorem supported_empty : supported M R (∅ : Set α) = ⊥ :=
eq_bot_iff.2 fun l h => (Submodule.mem_bot R).2 <| by ext; simp_all [mem_supported']
#align finsupp.supported_empty Finsupp.supported_empty
@[simp]
theorem supported_univ : supported M R (Set.univ : Set α) = ⊤ :=
eq_top_iff.2 fun _ _ => Set.subset_univ _
#align finsupp.supported_univ Finsupp.supported_univ
theorem supported_iUnion {δ : Type*} (s : δ → Set α) :
supported M R (⋃ i, s i) = ⨆ i, supported M R (s i) := by
refine le_antisymm ?_ (iSup_le fun i => supported_mono <| Set.subset_iUnion _ _)
haveI := Classical.decPred fun x => x ∈ ⋃ i, s i
suffices
LinearMap.range ((Submodule.subtype _).comp (restrictDom M R (⋃ i, s i))) ≤
⨆ i, supported M R (s i) by
rwa [LinearMap.range_comp, range_restrictDom, Submodule.map_top, range_subtype] at this
rw [range_le_iff_comap, eq_top_iff]
rintro l ⟨⟩
-- Porting note: Was ported as `induction l using Finsupp.induction`
refine Finsupp.induction l ?_ ?_
· exact zero_mem _
· refine fun x a l _ _ => add_mem ?_
by_cases h : ∃ i, x ∈ s i <;> simp [h]
cases' h with i hi
exact le_iSup (fun i => supported M R (s i)) i (single_mem_supported R _ hi)
#align finsupp.supported_Union Finsupp.supported_iUnion
theorem supported_union (s t : Set α) :
supported M R (s ∪ t) = supported M R s ⊔ supported M R t := by
erw [Set.union_eq_iUnion, supported_iUnion, iSup_bool_eq]; rfl
#align finsupp.supported_union Finsupp.supported_union
theorem supported_iInter {ι : Type*} (s : ι → Set α) :
supported M R (⋂ i, s i) = ⨅ i, supported M R (s i) :=
Submodule.ext fun x => by simp [mem_supported, subset_iInter_iff]
#align finsupp.supported_Inter Finsupp.supported_iInter
theorem supported_inter (s t : Set α) :
supported M R (s ∩ t) = supported M R s ⊓ supported M R t := by
rw [Set.inter_eq_iInter, supported_iInter, iInf_bool_eq]; rfl
#align finsupp.supported_inter Finsupp.supported_inter
theorem disjoint_supported_supported {s t : Set α} (h : Disjoint s t) :
Disjoint (supported M R s) (supported M R t) :=
disjoint_iff.2 <| by rw [← supported_inter, disjoint_iff_inter_eq_empty.1 h, supported_empty]
#align finsupp.disjoint_supported_supported Finsupp.disjoint_supported_supported
theorem disjoint_supported_supported_iff [Nontrivial M] {s t : Set α} :
Disjoint (supported M R s) (supported M R t) ↔ Disjoint s t := by
refine ⟨fun h => Set.disjoint_left.mpr fun x hx1 hx2 => ?_, disjoint_supported_supported⟩
rcases exists_ne (0 : M) with ⟨y, hy⟩
have := h.le_bot ⟨single_mem_supported R y hx1, single_mem_supported R y hx2⟩
rw [mem_bot, single_eq_zero] at this
exact hy this
#align finsupp.disjoint_supported_supported_iff Finsupp.disjoint_supported_supported_iff
/-- Interpret `Finsupp.restrictSupportEquiv` as a linear equivalence between
`supported M R s` and `s →₀ M`. -/
def supportedEquivFinsupp (s : Set α) : supported M R s ≃ₗ[R] s →₀ M := by
let F : supported M R s ≃ (s →₀ M) := restrictSupportEquiv s M
refine F.toLinearEquiv ?_
have :
(F : supported M R s → ↥s →₀ M) =
(lsubtypeDomain s : (α →₀ M) →ₗ[R] s →₀ M).comp (Submodule.subtype (supported M R s)) :=
rfl
rw [this]
exact LinearMap.isLinear _
#align finsupp.supported_equiv_finsupp Finsupp.supportedEquivFinsupp
section LSum
variable (S)
variable [Module S N] [SMulCommClass R S N]
/-- Lift a family of linear maps `M →ₗ[R] N` indexed by `x : α` to a linear map from `α →₀ M` to
`N` using `Finsupp.sum`. This is an upgraded version of `Finsupp.liftAddHom`.
See note [bundled maps over different rings] for why separate `R` and `S` semirings are used.
-/
def lsum : (α → M →ₗ[R] N) ≃ₗ[S] (α →₀ M) →ₗ[R] N where
toFun F :=
{ toFun := fun d => d.sum fun i => F i
map_add' := (liftAddHom (α := α) (M := M) (N := N) fun x => (F x).toAddMonoidHom).map_add
map_smul' := fun c f => by simp [sum_smul_index', smul_sum] }
invFun F x := F.comp (lsingle x)
left_inv F := by
ext x y
simp
right_inv F := by
ext x y
simp
map_add' F G := by
ext x y
simp
map_smul' F G := by
ext x y
simp
#align finsupp.lsum Finsupp.lsum
@[simp]
theorem coe_lsum (f : α → M →ₗ[R] N) : (lsum S f : (α →₀ M) → N) = fun d => d.sum fun i => f i :=
rfl
#align finsupp.coe_lsum Finsupp.coe_lsum
theorem lsum_apply (f : α → M →ₗ[R] N) (l : α →₀ M) : Finsupp.lsum S f l = l.sum fun b => f b :=
rfl
#align finsupp.lsum_apply Finsupp.lsum_apply
theorem lsum_single (f : α → M →ₗ[R] N) (i : α) (m : M) :
Finsupp.lsum S f (Finsupp.single i m) = f i m :=
Finsupp.sum_single_index (f i).map_zero
#align finsupp.lsum_single Finsupp.lsum_single
@[simp] theorem lsum_comp_lsingle (f : α → M →ₗ[R] N) (i : α) :
Finsupp.lsum S f ∘ₗ lsingle i = f i := by ext; simp
theorem lsum_symm_apply (f : (α →₀ M) →ₗ[R] N) (x : α) : (lsum S).symm f x = f.comp (lsingle x) :=
rfl
#align finsupp.lsum_symm_apply Finsupp.lsum_symm_apply
end LSum
section
variable (M) (R) (X : Type*) (S)
variable [Module S M] [SMulCommClass R S M]
/-- A slight rearrangement from `lsum` gives us
the bijection underlying the free-forgetful adjunction for R-modules.
-/
noncomputable def lift : (X → M) ≃+ ((X →₀ R) →ₗ[R] M) :=
(AddEquiv.arrowCongr (Equiv.refl X) (ringLmapEquivSelf R ℕ M).toAddEquiv.symm).trans
(lsum _ : _ ≃ₗ[ℕ] _).toAddEquiv
#align finsupp.lift Finsupp.lift
@[simp]
theorem lift_symm_apply (f) (x) : ((lift M R X).symm f) x = f (single x 1) :=
rfl
#align finsupp.lift_symm_apply Finsupp.lift_symm_apply
@[simp]
theorem lift_apply (f) (g) : ((lift M R X) f) g = g.sum fun x r => r • f x :=
rfl
#align finsupp.lift_apply Finsupp.lift_apply
/-- Given compatible `S` and `R`-module structures on `M` and a type `X`, the set of functions
`X → M` is `S`-linearly equivalent to the `R`-linear maps from the free `R`-module
on `X` to `M`. -/
noncomputable def llift : (X → M) ≃ₗ[S] (X →₀ R) →ₗ[R] M :=
{ lift M R X with
map_smul' := by
intros
dsimp
ext
simp only [coe_comp, Function.comp_apply, lsingle_apply, lift_apply, Pi.smul_apply,
sum_single_index, zero_smul, one_smul, LinearMap.smul_apply] }
#align finsupp.llift Finsupp.llift
@[simp]
theorem llift_apply (f : X → M) (x : X →₀ R) : llift M R S X f x = lift M R X f x :=
rfl
#align finsupp.llift_apply Finsupp.llift_apply
@[simp]
theorem llift_symm_apply (f : (X →₀ R) →ₗ[R] M) (x : X) :
(llift M R S X).symm f x = f (single x 1) :=
rfl
#align finsupp.llift_symm_apply Finsupp.llift_symm_apply
end
section LMapDomain
variable {α' : Type*} {α'' : Type*} (M R)
/-- Interpret `Finsupp.mapDomain` as a linear map. -/
def lmapDomain (f : α → α') : (α →₀ M) →ₗ[R] α' →₀ M where
toFun := mapDomain f
map_add' _ _ := mapDomain_add
map_smul' := mapDomain_smul
#align finsupp.lmap_domain Finsupp.lmapDomain
@[simp]
theorem lmapDomain_apply (f : α → α') (l : α →₀ M) :
(lmapDomain M R f : (α →₀ M) →ₗ[R] α' →₀ M) l = mapDomain f l :=
rfl
#align finsupp.lmap_domain_apply Finsupp.lmapDomain_apply
@[simp]
theorem lmapDomain_id : (lmapDomain M R _root_.id : (α →₀ M) →ₗ[R] α →₀ M) = LinearMap.id :=
LinearMap.ext fun _ => mapDomain_id
#align finsupp.lmap_domain_id Finsupp.lmapDomain_id
theorem lmapDomain_comp (f : α → α') (g : α' → α'') :
lmapDomain M R (g ∘ f) = (lmapDomain M R g).comp (lmapDomain M R f) :=
LinearMap.ext fun _ => mapDomain_comp
#align finsupp.lmap_domain_comp Finsupp.lmapDomain_comp
theorem supported_comap_lmapDomain (f : α → α') (s : Set α') :
supported M R (f ⁻¹' s) ≤ (supported M R s).comap (lmapDomain M R f) := by
classical
intro l (hl : (l.support : Set α) ⊆ f ⁻¹' s)
show ↑(mapDomain f l).support ⊆ s
rw [← Set.image_subset_iff, ← Finset.coe_image] at hl
exact Set.Subset.trans mapDomain_support hl
#align finsupp.supported_comap_lmap_domain Finsupp.supported_comap_lmapDomain
theorem lmapDomain_supported (f : α → α') (s : Set α) :
(supported M R s).map (lmapDomain M R f) = supported M R (f '' s) := by
classical
cases isEmpty_or_nonempty α
· simp [s.eq_empty_of_isEmpty]
refine
le_antisymm
(map_le_iff_le_comap.2 <|
le_trans (supported_mono <| Set.subset_preimage_image _ _)
(supported_comap_lmapDomain M R _ _))
?_
intro l hl
refine ⟨(lmapDomain M R (Function.invFunOn f s) : (α' →₀ M) →ₗ[R] α →₀ M) l, fun x hx => ?_, ?_⟩
· rcases Finset.mem_image.1 (mapDomain_support hx) with ⟨c, hc, rfl⟩
exact Function.invFunOn_mem (by simpa using hl hc)
· rw [← LinearMap.comp_apply, ← lmapDomain_comp]
refine (mapDomain_congr fun c hc => ?_).trans mapDomain_id
exact Function.invFunOn_eq (by simpa using hl hc)
#align finsupp.lmap_domain_supported Finsupp.lmapDomain_supported
theorem lmapDomain_disjoint_ker (f : α → α') {s : Set α}
(H : ∀ a ∈ s, ∀ b ∈ s, f a = f b → a = b) :
Disjoint (supported M R s) (ker (lmapDomain M R f)) := by
rw [disjoint_iff_inf_le]
rintro l ⟨h₁, h₂⟩
rw [SetLike.mem_coe, mem_ker, lmapDomain_apply, mapDomain] at h₂
simp; ext x
haveI := Classical.decPred fun x => x ∈ s
by_cases xs : x ∈ s
· have : Finsupp.sum l (fun a => Finsupp.single (f a)) (f x) = 0 := by
rw [h₂]
rfl
rw [Finsupp.sum_apply, Finsupp.sum_eq_single x, single_eq_same] at this
· simpa
· intro y hy xy
simp only [SetLike.mem_coe, mem_supported, subset_def, Finset.mem_coe, mem_support_iff] at h₁
simp [mt (H _ (h₁ _ hy) _ xs) xy]
· simp (config := { contextual := true })
· by_contra h
exact xs (h₁ <| Finsupp.mem_support_iff.2 h)
#align finsupp.lmap_domain_disjoint_ker Finsupp.lmapDomain_disjoint_ker
end LMapDomain
section LComapDomain
variable {β : Type*}
/-- Given `f : α → β` and a proof `hf` that `f` is injective, `lcomapDomain f hf` is the linear map
sending `l : β →₀ M` to the finitely supported function from `α` to `M` given by composing
`l` with `f`.
This is the linear version of `Finsupp.comapDomain`. -/
def lcomapDomain (f : α → β) (hf : Function.Injective f) : (β →₀ M) →ₗ[R] α →₀ M where
toFun l := Finsupp.comapDomain f l hf.injOn
map_add' x y := by ext; simp
map_smul' c x := by ext; simp
#align finsupp.lcomap_domain Finsupp.lcomapDomain
end LComapDomain
section Total
variable (α) (M) (R)
variable {α' : Type*} {M' : Type*} [AddCommMonoid M'] [Module R M'] (v : α → M) {v' : α' → M'}
/-- Interprets (l : α →₀ R) as linear combination of the elements in the family (v : α → M) and
evaluates this linear combination. -/
protected def total : (α →₀ R) →ₗ[R] M :=
Finsupp.lsum ℕ fun i => LinearMap.id.smulRight (v i)
#align finsupp.total Finsupp.total
variable {α M v}
theorem total_apply (l : α →₀ R) : Finsupp.total α M R v l = l.sum fun i a => a • v i :=
rfl
#align finsupp.total_apply Finsupp.total_apply
theorem total_apply_of_mem_supported {l : α →₀ R} {s : Finset α}
(hs : l ∈ supported R R (↑s : Set α)) : Finsupp.total α M R v l = s.sum fun i => l i • v i :=
Finset.sum_subset hs fun x _ hxg =>
show l x • v x = 0 by rw [not_mem_support_iff.1 hxg, zero_smul]
#align finsupp.total_apply_of_mem_supported Finsupp.total_apply_of_mem_supported
@[simp]
| Mathlib/LinearAlgebra/Finsupp.lean | 675 | 676 | theorem total_single (c : R) (a : α) : Finsupp.total α M R v (single a c) = c • v a := by |
simp [total_apply, sum_single_index]
|
/-
Copyright (c) 2019 Gabriel Ebner. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Gabriel Ebner, Anatole Dedecker, Yury Kudryashov
-/
import Mathlib.Analysis.Calculus.Deriv.Basic
import Mathlib.Analysis.Calculus.FDeriv.Mul
import Mathlib.Analysis.Calculus.FDeriv.Add
#align_import analysis.calculus.deriv.mul from "leanprover-community/mathlib"@"3bce8d800a6f2b8f63fe1e588fd76a9ff4adcebe"
/-!
# Derivative of `f x * g x`
In this file we prove formulas for `(f x * g x)'` and `(f x • g x)'`.
For a more detailed overview of one-dimensional derivatives in mathlib, see the module docstring of
`Analysis/Calculus/Deriv/Basic`.
## Keywords
derivative, multiplication
-/
universe u v w
noncomputable section
open scoped Classical Topology Filter ENNReal
open Filter Asymptotics Set
open ContinuousLinearMap (smulRight smulRight_one_eq_iff)
variable {𝕜 : Type u} [NontriviallyNormedField 𝕜]
variable {F : Type v} [NormedAddCommGroup F] [NormedSpace 𝕜 F]
variable {E : Type w} [NormedAddCommGroup E] [NormedSpace 𝕜 E]
variable {G : Type*} [NormedAddCommGroup G] [NormedSpace 𝕜 G]
variable {f f₀ f₁ g : 𝕜 → F}
variable {f' f₀' f₁' g' : F}
variable {x : 𝕜}
variable {s t : Set 𝕜}
variable {L L₁ L₂ : Filter 𝕜}
/-! ### Derivative of bilinear maps -/
namespace ContinuousLinearMap
variable {B : E →L[𝕜] F →L[𝕜] G} {u : 𝕜 → E} {v : 𝕜 → F} {u' : E} {v' : F}
theorem hasDerivWithinAt_of_bilinear
(hu : HasDerivWithinAt u u' s x) (hv : HasDerivWithinAt v v' s x) :
HasDerivWithinAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) s x := by
simpa using (B.hasFDerivWithinAt_of_bilinear
hu.hasFDerivWithinAt hv.hasFDerivWithinAt).hasDerivWithinAt
theorem hasDerivAt_of_bilinear (hu : HasDerivAt u u' x) (hv : HasDerivAt v v' x) :
HasDerivAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) x := by
simpa using (B.hasFDerivAt_of_bilinear hu.hasFDerivAt hv.hasFDerivAt).hasDerivAt
theorem hasStrictDerivAt_of_bilinear (hu : HasStrictDerivAt u u' x) (hv : HasStrictDerivAt v v' x) :
HasStrictDerivAt (fun x ↦ B (u x) (v x)) (B (u x) v' + B u' (v x)) x := by
simpa using
(B.hasStrictFDerivAt_of_bilinear hu.hasStrictFDerivAt hv.hasStrictFDerivAt).hasStrictDerivAt
theorem derivWithin_of_bilinear (hxs : UniqueDiffWithinAt 𝕜 s x)
(hu : DifferentiableWithinAt 𝕜 u s x) (hv : DifferentiableWithinAt 𝕜 v s x) :
derivWithin (fun y => B (u y) (v y)) s x =
B (u x) (derivWithin v s x) + B (derivWithin u s x) (v x) :=
(B.hasDerivWithinAt_of_bilinear hu.hasDerivWithinAt hv.hasDerivWithinAt).derivWithin hxs
theorem deriv_of_bilinear (hu : DifferentiableAt 𝕜 u x) (hv : DifferentiableAt 𝕜 v x) :
deriv (fun y => B (u y) (v y)) x = B (u x) (deriv v x) + B (deriv u x) (v x) :=
(B.hasDerivAt_of_bilinear hu.hasDerivAt hv.hasDerivAt).deriv
end ContinuousLinearMap
section SMul
/-! ### Derivative of the multiplication of a scalar function and a vector function -/
variable {𝕜' : Type*} [NontriviallyNormedField 𝕜'] [NormedAlgebra 𝕜 𝕜'] [NormedSpace 𝕜' F]
[IsScalarTower 𝕜 𝕜' F] {c : 𝕜 → 𝕜'} {c' : 𝕜'}
theorem HasDerivWithinAt.smul (hc : HasDerivWithinAt c c' s x) (hf : HasDerivWithinAt f f' s x) :
HasDerivWithinAt (fun y => c y • f y) (c x • f' + c' • f x) s x := by
simpa using (HasFDerivWithinAt.smul hc hf).hasDerivWithinAt
#align has_deriv_within_at.smul HasDerivWithinAt.smul
theorem HasDerivAt.smul (hc : HasDerivAt c c' x) (hf : HasDerivAt f f' x) :
HasDerivAt (fun y => c y • f y) (c x • f' + c' • f x) x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.smul hf
#align has_deriv_at.smul HasDerivAt.smul
nonrec theorem HasStrictDerivAt.smul (hc : HasStrictDerivAt c c' x) (hf : HasStrictDerivAt f f' x) :
HasStrictDerivAt (fun y => c y • f y) (c x • f' + c' • f x) x := by
simpa using (hc.smul hf).hasStrictDerivAt
#align has_strict_deriv_at.smul HasStrictDerivAt.smul
theorem derivWithin_smul (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(hf : DifferentiableWithinAt 𝕜 f s x) :
derivWithin (fun y => c y • f y) s x = c x • derivWithin f s x + derivWithin c s x • f x :=
(hc.hasDerivWithinAt.smul hf.hasDerivWithinAt).derivWithin hxs
#align deriv_within_smul derivWithin_smul
theorem deriv_smul (hc : DifferentiableAt 𝕜 c x) (hf : DifferentiableAt 𝕜 f x) :
deriv (fun y => c y • f y) x = c x • deriv f x + deriv c x • f x :=
(hc.hasDerivAt.smul hf.hasDerivAt).deriv
#align deriv_smul deriv_smul
theorem HasStrictDerivAt.smul_const (hc : HasStrictDerivAt c c' x) (f : F) :
HasStrictDerivAt (fun y => c y • f) (c' • f) x := by
have := hc.smul (hasStrictDerivAt_const x f)
rwa [smul_zero, zero_add] at this
#align has_strict_deriv_at.smul_const HasStrictDerivAt.smul_const
theorem HasDerivWithinAt.smul_const (hc : HasDerivWithinAt c c' s x) (f : F) :
HasDerivWithinAt (fun y => c y • f) (c' • f) s x := by
have := hc.smul (hasDerivWithinAt_const x s f)
rwa [smul_zero, zero_add] at this
#align has_deriv_within_at.smul_const HasDerivWithinAt.smul_const
theorem HasDerivAt.smul_const (hc : HasDerivAt c c' x) (f : F) :
HasDerivAt (fun y => c y • f) (c' • f) x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.smul_const f
#align has_deriv_at.smul_const HasDerivAt.smul_const
theorem derivWithin_smul_const (hxs : UniqueDiffWithinAt 𝕜 s x)
(hc : DifferentiableWithinAt 𝕜 c s x) (f : F) :
derivWithin (fun y => c y • f) s x = derivWithin c s x • f :=
(hc.hasDerivWithinAt.smul_const f).derivWithin hxs
#align deriv_within_smul_const derivWithin_smul_const
theorem deriv_smul_const (hc : DifferentiableAt 𝕜 c x) (f : F) :
deriv (fun y => c y • f) x = deriv c x • f :=
(hc.hasDerivAt.smul_const f).deriv
#align deriv_smul_const deriv_smul_const
end SMul
section ConstSMul
variable {R : Type*} [Semiring R] [Module R F] [SMulCommClass 𝕜 R F] [ContinuousConstSMul R F]
nonrec theorem HasStrictDerivAt.const_smul (c : R) (hf : HasStrictDerivAt f f' x) :
HasStrictDerivAt (fun y => c • f y) (c • f') x := by
simpa using (hf.const_smul c).hasStrictDerivAt
#align has_strict_deriv_at.const_smul HasStrictDerivAt.const_smul
nonrec theorem HasDerivAtFilter.const_smul (c : R) (hf : HasDerivAtFilter f f' x L) :
HasDerivAtFilter (fun y => c • f y) (c • f') x L := by
simpa using (hf.const_smul c).hasDerivAtFilter
#align has_deriv_at_filter.const_smul HasDerivAtFilter.const_smul
nonrec theorem HasDerivWithinAt.const_smul (c : R) (hf : HasDerivWithinAt f f' s x) :
HasDerivWithinAt (fun y => c • f y) (c • f') s x :=
hf.const_smul c
#align has_deriv_within_at.const_smul HasDerivWithinAt.const_smul
nonrec theorem HasDerivAt.const_smul (c : R) (hf : HasDerivAt f f' x) :
HasDerivAt (fun y => c • f y) (c • f') x :=
hf.const_smul c
#align has_deriv_at.const_smul HasDerivAt.const_smul
theorem derivWithin_const_smul (hxs : UniqueDiffWithinAt 𝕜 s x) (c : R)
(hf : DifferentiableWithinAt 𝕜 f s x) :
derivWithin (fun y => c • f y) s x = c • derivWithin f s x :=
(hf.hasDerivWithinAt.const_smul c).derivWithin hxs
#align deriv_within_const_smul derivWithin_const_smul
theorem deriv_const_smul (c : R) (hf : DifferentiableAt 𝕜 f x) :
deriv (fun y => c • f y) x = c • deriv f x :=
(hf.hasDerivAt.const_smul c).deriv
#align deriv_const_smul deriv_const_smul
/-- A variant of `deriv_const_smul` without differentiability assumption when the scalar
multiplication is by field elements. -/
lemma deriv_const_smul' {f : 𝕜 → F} {x : 𝕜} {R : Type*} [Field R] [Module R F] [SMulCommClass 𝕜 R F]
[ContinuousConstSMul R F] (c : R) :
deriv (fun y ↦ c • f y) x = c • deriv f x := by
by_cases hf : DifferentiableAt 𝕜 f x
· exact deriv_const_smul c hf
· rcases eq_or_ne c 0 with rfl | hc
· simp only [zero_smul, deriv_const']
· have H : ¬DifferentiableAt 𝕜 (fun y ↦ c • f y) x := by
contrapose! hf
change DifferentiableAt 𝕜 (fun y ↦ f y) x
conv => enter [2, y]; rw [← inv_smul_smul₀ hc (f y)]
exact DifferentiableAt.const_smul hf c⁻¹
rw [deriv_zero_of_not_differentiableAt hf, deriv_zero_of_not_differentiableAt H, smul_zero]
end ConstSMul
section Mul
/-! ### Derivative of the multiplication of two functions -/
variable {𝕜' 𝔸 : Type*} [NormedField 𝕜'] [NormedRing 𝔸] [NormedAlgebra 𝕜 𝕜'] [NormedAlgebra 𝕜 𝔸]
{c d : 𝕜 → 𝔸} {c' d' : 𝔸} {u v : 𝕜 → 𝕜'}
theorem HasDerivWithinAt.mul (hc : HasDerivWithinAt c c' s x) (hd : HasDerivWithinAt d d' s x) :
HasDerivWithinAt (fun y => c y * d y) (c' * d x + c x * d') s x := by
have := (HasFDerivWithinAt.mul' hc hd).hasDerivWithinAt
rwa [ContinuousLinearMap.add_apply, ContinuousLinearMap.smul_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.smulRight_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.one_apply, one_smul, one_smul,
add_comm] at this
#align has_deriv_within_at.mul HasDerivWithinAt.mul
theorem HasDerivAt.mul (hc : HasDerivAt c c' x) (hd : HasDerivAt d d' x) :
HasDerivAt (fun y => c y * d y) (c' * d x + c x * d') x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.mul hd
#align has_deriv_at.mul HasDerivAt.mul
theorem HasStrictDerivAt.mul (hc : HasStrictDerivAt c c' x) (hd : HasStrictDerivAt d d' x) :
HasStrictDerivAt (fun y => c y * d y) (c' * d x + c x * d') x := by
have := (HasStrictFDerivAt.mul' hc hd).hasStrictDerivAt
rwa [ContinuousLinearMap.add_apply, ContinuousLinearMap.smul_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.smulRight_apply,
ContinuousLinearMap.smulRight_apply, ContinuousLinearMap.one_apply, one_smul, one_smul,
add_comm] at this
#align has_strict_deriv_at.mul HasStrictDerivAt.mul
theorem derivWithin_mul (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(hd : DifferentiableWithinAt 𝕜 d s x) :
derivWithin (fun y => c y * d y) s x = derivWithin c s x * d x + c x * derivWithin d s x :=
(hc.hasDerivWithinAt.mul hd.hasDerivWithinAt).derivWithin hxs
#align deriv_within_mul derivWithin_mul
@[simp]
theorem deriv_mul (hc : DifferentiableAt 𝕜 c x) (hd : DifferentiableAt 𝕜 d x) :
deriv (fun y => c y * d y) x = deriv c x * d x + c x * deriv d x :=
(hc.hasDerivAt.mul hd.hasDerivAt).deriv
#align deriv_mul deriv_mul
theorem HasDerivWithinAt.mul_const (hc : HasDerivWithinAt c c' s x) (d : 𝔸) :
HasDerivWithinAt (fun y => c y * d) (c' * d) s x := by
convert hc.mul (hasDerivWithinAt_const x s d) using 1
rw [mul_zero, add_zero]
#align has_deriv_within_at.mul_const HasDerivWithinAt.mul_const
theorem HasDerivAt.mul_const (hc : HasDerivAt c c' x) (d : 𝔸) :
HasDerivAt (fun y => c y * d) (c' * d) x := by
rw [← hasDerivWithinAt_univ] at *
exact hc.mul_const d
#align has_deriv_at.mul_const HasDerivAt.mul_const
theorem hasDerivAt_mul_const (c : 𝕜) : HasDerivAt (fun x => x * c) c x := by
simpa only [one_mul] using (hasDerivAt_id' x).mul_const c
#align has_deriv_at_mul_const hasDerivAt_mul_const
theorem HasStrictDerivAt.mul_const (hc : HasStrictDerivAt c c' x) (d : 𝔸) :
HasStrictDerivAt (fun y => c y * d) (c' * d) x := by
convert hc.mul (hasStrictDerivAt_const x d) using 1
rw [mul_zero, add_zero]
#align has_strict_deriv_at.mul_const HasStrictDerivAt.mul_const
theorem derivWithin_mul_const (hxs : UniqueDiffWithinAt 𝕜 s x) (hc : DifferentiableWithinAt 𝕜 c s x)
(d : 𝔸) : derivWithin (fun y => c y * d) s x = derivWithin c s x * d :=
(hc.hasDerivWithinAt.mul_const d).derivWithin hxs
#align deriv_within_mul_const derivWithin_mul_const
theorem deriv_mul_const (hc : DifferentiableAt 𝕜 c x) (d : 𝔸) :
deriv (fun y => c y * d) x = deriv c x * d :=
(hc.hasDerivAt.mul_const d).deriv
#align deriv_mul_const deriv_mul_const
theorem deriv_mul_const_field (v : 𝕜') : deriv (fun y => u y * v) x = deriv u x * v := by
by_cases hu : DifferentiableAt 𝕜 u x
· exact deriv_mul_const hu v
· rw [deriv_zero_of_not_differentiableAt hu, zero_mul]
rcases eq_or_ne v 0 with (rfl | hd)
· simp only [mul_zero, deriv_const]
· refine deriv_zero_of_not_differentiableAt (mt (fun H => ?_) hu)
simpa only [mul_inv_cancel_right₀ hd] using H.mul_const v⁻¹
#align deriv_mul_const_field deriv_mul_const_field
@[simp]
theorem deriv_mul_const_field' (v : 𝕜') : (deriv fun x => u x * v) = fun x => deriv u x * v :=
funext fun _ => deriv_mul_const_field v
#align deriv_mul_const_field' deriv_mul_const_field'
theorem HasDerivWithinAt.const_mul (c : 𝔸) (hd : HasDerivWithinAt d d' s x) :
HasDerivWithinAt (fun y => c * d y) (c * d') s x := by
convert (hasDerivWithinAt_const x s c).mul hd using 1
rw [zero_mul, zero_add]
#align has_deriv_within_at.const_mul HasDerivWithinAt.const_mul
theorem HasDerivAt.const_mul (c : 𝔸) (hd : HasDerivAt d d' x) :
HasDerivAt (fun y => c * d y) (c * d') x := by
rw [← hasDerivWithinAt_univ] at *
exact hd.const_mul c
#align has_deriv_at.const_mul HasDerivAt.const_mul
theorem HasStrictDerivAt.const_mul (c : 𝔸) (hd : HasStrictDerivAt d d' x) :
HasStrictDerivAt (fun y => c * d y) (c * d') x := by
convert (hasStrictDerivAt_const _ _).mul hd using 1
rw [zero_mul, zero_add]
#align has_strict_deriv_at.const_mul HasStrictDerivAt.const_mul
theorem derivWithin_const_mul (hxs : UniqueDiffWithinAt 𝕜 s x) (c : 𝔸)
(hd : DifferentiableWithinAt 𝕜 d s x) :
derivWithin (fun y => c * d y) s x = c * derivWithin d s x :=
(hd.hasDerivWithinAt.const_mul c).derivWithin hxs
#align deriv_within_const_mul derivWithin_const_mul
theorem deriv_const_mul (c : 𝔸) (hd : DifferentiableAt 𝕜 d x) :
deriv (fun y => c * d y) x = c * deriv d x :=
(hd.hasDerivAt.const_mul c).deriv
#align deriv_const_mul deriv_const_mul
theorem deriv_const_mul_field (u : 𝕜') : deriv (fun y => u * v y) x = u * deriv v x := by
simp only [mul_comm u, deriv_mul_const_field]
#align deriv_const_mul_field deriv_const_mul_field
@[simp]
theorem deriv_const_mul_field' (u : 𝕜') : (deriv fun x => u * v x) = fun x => u * deriv v x :=
funext fun _ => deriv_const_mul_field u
#align deriv_const_mul_field' deriv_const_mul_field'
end Mul
section Prod
section HasDeriv
variable {ι : Type*} [DecidableEq ι] {𝔸' : Type*} [NormedCommRing 𝔸'] [NormedAlgebra 𝕜 𝔸']
{u : Finset ι} {f : ι → 𝕜 → 𝔸'} {f' : ι → 𝔸'}
theorem HasDerivAt.finset_prod (hf : ∀ i ∈ u, HasDerivAt (f i) (f' i) x) :
HasDerivAt (∏ i ∈ u, f i ·) (∑ i ∈ u, (∏ j ∈ u.erase i, f j x) • f' i) x := by
simpa [ContinuousLinearMap.sum_apply, ContinuousLinearMap.smul_apply] using
(HasFDerivAt.finset_prod (fun i hi ↦ (hf i hi).hasFDerivAt)).hasDerivAt
theorem HasDerivWithinAt.finset_prod (hf : ∀ i ∈ u, HasDerivWithinAt (f i) (f' i) s x) :
HasDerivWithinAt (∏ i ∈ u, f i ·) (∑ i ∈ u, (∏ j ∈ u.erase i, f j x) • f' i) s x := by
simpa [ContinuousLinearMap.sum_apply, ContinuousLinearMap.smul_apply] using
(HasFDerivWithinAt.finset_prod (fun i hi ↦ (hf i hi).hasFDerivWithinAt)).hasDerivWithinAt
theorem HasStrictDerivAt.finset_prod (hf : ∀ i ∈ u, HasStrictDerivAt (f i) (f' i) x) :
HasStrictDerivAt (∏ i ∈ u, f i ·) (∑ i ∈ u, (∏ j ∈ u.erase i, f j x) • f' i) x := by
simpa [ContinuousLinearMap.sum_apply, ContinuousLinearMap.smul_apply] using
(HasStrictFDerivAt.finset_prod (fun i hi ↦ (hf i hi).hasStrictFDerivAt)).hasStrictDerivAt
theorem deriv_finset_prod (hf : ∀ i ∈ u, DifferentiableAt 𝕜 (f i) x) :
deriv (∏ i ∈ u, f i ·) x = ∑ i ∈ u, (∏ j ∈ u.erase i, f j x) • deriv (f i) x :=
(HasDerivAt.finset_prod fun i hi ↦ (hf i hi).hasDerivAt).deriv
theorem derivWithin_finset_prod (hxs : UniqueDiffWithinAt 𝕜 s x)
(hf : ∀ i ∈ u, DifferentiableWithinAt 𝕜 (f i) s x) :
derivWithin (∏ i ∈ u, f i ·) s x =
∑ i ∈ u, (∏ j ∈ u.erase i, f j x) • derivWithin (f i) s x :=
(HasDerivWithinAt.finset_prod fun i hi ↦ (hf i hi).hasDerivWithinAt).derivWithin hxs
end HasDeriv
variable {ι : Type*} {𝔸' : Type*} [NormedCommRing 𝔸'] [NormedAlgebra 𝕜 𝔸']
{u : Finset ι} {f : ι → 𝕜 → 𝔸'} {f' : ι → 𝔸'}
theorem DifferentiableAt.finset_prod (hd : ∀ i ∈ u, DifferentiableAt 𝕜 (f i) x) :
DifferentiableAt 𝕜 (∏ i ∈ u, f i ·) x :=
(HasDerivAt.finset_prod (fun i hi ↦ DifferentiableAt.hasDerivAt (hd i hi))).differentiableAt
theorem DifferentiableWithinAt.finset_prod (hd : ∀ i ∈ u, DifferentiableWithinAt 𝕜 (f i) s x) :
DifferentiableWithinAt 𝕜 (∏ i ∈ u, f i ·) s x :=
(HasDerivWithinAt.finset_prod (fun i hi ↦
DifferentiableWithinAt.hasDerivWithinAt (hd i hi))).differentiableWithinAt
theorem DifferentiableOn.finset_prod (hd : ∀ i ∈ u, DifferentiableOn 𝕜 (f i) s) :
DifferentiableOn 𝕜 (∏ i ∈ u, f i ·) s :=
fun x hx ↦ .finset_prod (fun i hi ↦ hd i hi x hx)
theorem Differentiable.finset_prod (hd : ∀ i ∈ u, Differentiable 𝕜 (f i)) :
Differentiable 𝕜 (∏ i ∈ u, f i ·) :=
fun x ↦ .finset_prod (fun i hi ↦ hd i hi x)
end Prod
section Div
variable {𝕜' : Type*} [NontriviallyNormedField 𝕜'] [NormedAlgebra 𝕜 𝕜'] {c d : 𝕜 → 𝕜'} {c' d' : 𝕜'}
theorem HasDerivAt.div_const (hc : HasDerivAt c c' x) (d : 𝕜') :
HasDerivAt (fun x => c x / d) (c' / d) x := by
simpa only [div_eq_mul_inv] using hc.mul_const d⁻¹
#align has_deriv_at.div_const HasDerivAt.div_const
theorem HasDerivWithinAt.div_const (hc : HasDerivWithinAt c c' s x) (d : 𝕜') :
HasDerivWithinAt (fun x => c x / d) (c' / d) s x := by
simpa only [div_eq_mul_inv] using hc.mul_const d⁻¹
#align has_deriv_within_at.div_const HasDerivWithinAt.div_const
theorem HasStrictDerivAt.div_const (hc : HasStrictDerivAt c c' x) (d : 𝕜') :
HasStrictDerivAt (fun x => c x / d) (c' / d) x := by
simpa only [div_eq_mul_inv] using hc.mul_const d⁻¹
#align has_strict_deriv_at.div_const HasStrictDerivAt.div_const
theorem DifferentiableWithinAt.div_const (hc : DifferentiableWithinAt 𝕜 c s x) (d : 𝕜') :
DifferentiableWithinAt 𝕜 (fun x => c x / d) s x :=
(hc.hasDerivWithinAt.div_const _).differentiableWithinAt
#align differentiable_within_at.div_const DifferentiableWithinAt.div_const
@[simp]
theorem DifferentiableAt.div_const (hc : DifferentiableAt 𝕜 c x) (d : 𝕜') :
DifferentiableAt 𝕜 (fun x => c x / d) x :=
(hc.hasDerivAt.div_const _).differentiableAt
#align differentiable_at.div_const DifferentiableAt.div_const
theorem DifferentiableOn.div_const (hc : DifferentiableOn 𝕜 c s) (d : 𝕜') :
DifferentiableOn 𝕜 (fun x => c x / d) s := fun x hx => (hc x hx).div_const d
#align differentiable_on.div_const DifferentiableOn.div_const
@[simp]
theorem Differentiable.div_const (hc : Differentiable 𝕜 c) (d : 𝕜') :
Differentiable 𝕜 fun x => c x / d := fun x => (hc x).div_const d
#align differentiable.div_const Differentiable.div_const
| Mathlib/Analysis/Calculus/Deriv/Mul.lean | 424 | 427 | theorem derivWithin_div_const (hc : DifferentiableWithinAt 𝕜 c s x)
(d : 𝕜') (hxs : UniqueDiffWithinAt 𝕜 s x) :
derivWithin (fun x => c x / d) s x = derivWithin c s x / d := by |
simp [div_eq_inv_mul, derivWithin_const_mul, hc, hxs]
|
/-
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
| Mathlib/MeasureTheory/Integral/SetIntegral.lean | 288 | 293 | 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
|
/-
Copyright (c) 2021 Eric Wieser. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Eric Wieser
-/
import Mathlib.Algebra.Group.Submonoid.Membership
import Mathlib.Algebra.Order.BigOperators.Group.List
import Mathlib.Data.Set.Pointwise.SMul
import Mathlib.Order.WellFoundedSet
#align_import group_theory.submonoid.pointwise from "leanprover-community/mathlib"@"2bbc7e3884ba234309d2a43b19144105a753292e"
/-! # Pointwise instances on `Submonoid`s and `AddSubmonoid`s
This file provides:
* `Submonoid.inv`
* `AddSubmonoid.neg`
and the actions
* `Submonoid.pointwiseMulAction`
* `AddSubmonoid.pointwiseMulAction`
which matches the action of `Set.mulActionSet`.
These are all available in the `Pointwise` locale.
Additionally, it provides various degrees of monoid structure:
* `AddSubmonoid.one`
* `AddSubmonoid.mul`
* `AddSubmonoid.mulOneClass`
* `AddSubmonoid.semigroup`
* `AddSubmonoid.monoid`
which is available globally to match the monoid structure implied by `Submodule.idemSemiring`.
## Implementation notes
Most of the lemmas in this file are direct copies of lemmas from `Algebra/Pointwise.lean`.
While the statements of these lemmas are defeq, we repeat them here due to them not being
syntactically equal. Before adding new lemmas here, consider if they would also apply to the action
on `Set`s.
-/
open Set Pointwise
variable {α : Type*} {G : Type*} {M : Type*} {R : Type*} {A : Type*}
variable [Monoid M] [AddMonoid A]
/-! Some lemmas about pointwise multiplication and submonoids. Ideally we put these in
`GroupTheory.Submonoid.Basic`, but currently we cannot because that file is imported by this. -/
namespace Submonoid
variable {s t u : Set M}
@[to_additive]
theorem mul_subset {S : Submonoid M} (hs : s ⊆ S) (ht : t ⊆ S) : s * t ⊆ S :=
mul_subset_iff.2 fun _x hx _y hy ↦ mul_mem (hs hx) (ht hy)
#align submonoid.mul_subset Submonoid.mul_subset
#align add_submonoid.add_subset AddSubmonoid.add_subset
@[to_additive]
theorem mul_subset_closure (hs : s ⊆ u) (ht : t ⊆ u) : s * t ⊆ Submonoid.closure u :=
mul_subset (Subset.trans hs Submonoid.subset_closure) (Subset.trans ht Submonoid.subset_closure)
#align submonoid.mul_subset_closure Submonoid.mul_subset_closure
#align add_submonoid.add_subset_closure AddSubmonoid.add_subset_closure
@[to_additive]
theorem coe_mul_self_eq (s : Submonoid M) : (s : Set M) * s = s := by
ext x
refine ⟨?_, fun h => ⟨x, h, 1, s.one_mem, mul_one x⟩⟩
rintro ⟨a, ha, b, hb, rfl⟩
exact s.mul_mem ha hb
#align submonoid.coe_mul_self_eq Submonoid.coe_mul_self_eq
#align add_submonoid.coe_add_self_eq AddSubmonoid.coe_add_self_eq
@[to_additive]
theorem closure_mul_le (S T : Set M) : closure (S * T) ≤ closure S ⊔ closure T :=
sInf_le fun _x ⟨_s, hs, _t, ht, hx⟩ => hx ▸
(closure S ⊔ closure T).mul_mem (SetLike.le_def.mp le_sup_left <| subset_closure hs)
(SetLike.le_def.mp le_sup_right <| subset_closure ht)
#align submonoid.closure_mul_le Submonoid.closure_mul_le
#align add_submonoid.closure_add_le AddSubmonoid.closure_add_le
@[to_additive]
theorem sup_eq_closure_mul (H K : Submonoid M) : H ⊔ K = closure ((H : Set M) * (K : Set M)) :=
le_antisymm
(sup_le (fun h hh => subset_closure ⟨h, hh, 1, K.one_mem, mul_one h⟩) fun k hk =>
subset_closure ⟨1, H.one_mem, k, hk, one_mul k⟩)
((closure_mul_le _ _).trans <| by rw [closure_eq, closure_eq])
#align submonoid.sup_eq_closure Submonoid.sup_eq_closure_mul
#align add_submonoid.sup_eq_closure AddSubmonoid.sup_eq_closure_add
@[to_additive]
| Mathlib/Algebra/Group/Submonoid/Pointwise.lean | 98 | 107 | theorem pow_smul_mem_closure_smul {N : Type*} [CommMonoid N] [MulAction M N] [IsScalarTower M N N]
(r : M) (s : Set N) {x : N} (hx : x ∈ closure s) : ∃ n : ℕ, r ^ n • x ∈ closure (r • s) := by |
refine @closure_induction N _ s (fun x : N => ∃ n : ℕ, r ^ n • x ∈ closure (r • s)) _ hx ?_ ?_ ?_
· intro x hx
exact ⟨1, subset_closure ⟨_, hx, by rw [pow_one]⟩⟩
· exact ⟨0, by simpa using one_mem _⟩
· rintro x y ⟨nx, hx⟩ ⟨ny, hy⟩
use ny + nx
rw [pow_add, mul_smul, ← smul_mul_assoc, mul_comm, ← smul_mul_assoc]
exact mul_mem hy hx
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen
-/
import Mathlib.LinearAlgebra.Matrix.BilinearForm
import Mathlib.LinearAlgebra.Matrix.Charpoly.Minpoly
import Mathlib.LinearAlgebra.Determinant
import Mathlib.LinearAlgebra.FiniteDimensional
import Mathlib.LinearAlgebra.Vandermonde
import Mathlib.LinearAlgebra.Trace
import Mathlib.FieldTheory.IsAlgClosed.AlgebraicClosure
import Mathlib.FieldTheory.PrimitiveElement
import Mathlib.FieldTheory.Galois
import Mathlib.RingTheory.PowerBasis
import Mathlib.FieldTheory.Minpoly.MinpolyDiv
#align_import ring_theory.trace from "leanprover-community/mathlib"@"3e068ece210655b7b9a9477c3aff38a492400aa1"
/-!
# Trace for (finite) ring extensions.
Suppose we have an `R`-algebra `S` with a finite basis. For each `s : S`,
the trace of the linear map given by multiplying by `s` gives information about
the roots of the minimal polynomial of `s` over `R`.
## Main definitions
* `Algebra.trace R S x`: the trace of an element `s` of an `R`-algebra `S`
* `Algebra.traceForm R S`: bilinear form sending `x`, `y` to the trace of `x * y`
* `Algebra.traceMatrix R b`: the matrix whose `(i j)`-th element is the trace of `b i * b j`.
* `Algebra.embeddingsMatrix A C b : Matrix κ (B →ₐ[A] C) C` is the matrix whose
`(i, σ)` coefficient is `σ (b i)`.
* `Algebra.embeddingsMatrixReindex A C b e : Matrix κ κ C` is the matrix whose `(i, j)`
coefficient is `σⱼ (b i)`, where `σⱼ : B →ₐ[A] C` is the embedding corresponding to `j : κ`
given by a bijection `e : κ ≃ (B →ₐ[A] C)`.
## Main results
* `trace_algebraMap_of_basis`, `trace_algebraMap`: if `x : K`, then `Tr_{L/K} x = [L : K] x`
* `trace_trace_of_basis`, `trace_trace`: `Tr_{L/K} (Tr_{F/L} x) = Tr_{F/K} x`
* `trace_eq_sum_roots`: the trace of `x : K(x)` is the sum of all conjugate roots of `x`
* `trace_eq_sum_embeddings`: the trace of `x : K(x)` is the sum of all embeddings of `x` into an
algebraically closed field
* `traceForm_nondegenerate`: the trace form over a separable extension is a nondegenerate
bilinear form
* `traceForm_dualBasis_powerBasis_eq`: The dual basis of a powerbasis `{1, x, x²...}` under the
trace form is `aᵢ / f'(x)`, with `f` being the minpoly of `x` and `f / (X - x) = ∑ aᵢxⁱ`.
## Implementation notes
Typically, the trace is defined specifically for finite field extensions.
The definition is as general as possible and the assumption that we have
fields or that the extension is finite is added to the lemmas as needed.
We only define the trace for left multiplication (`Algebra.leftMulMatrix`,
i.e. `LinearMap.mulLeft`).
For now, the definitions assume `S` is commutative, so the choice doesn't matter anyway.
## References
* https://en.wikipedia.org/wiki/Field_trace
-/
universe u v w z
variable {R S T : Type*} [CommRing R] [CommRing S] [CommRing T]
variable [Algebra R S] [Algebra R T]
variable {K L : Type*} [Field K] [Field L] [Algebra K L]
variable {ι κ : Type w} [Fintype ι]
open FiniteDimensional
open LinearMap (BilinForm)
open LinearMap
open Matrix
open scoped Matrix
namespace Algebra
variable (b : Basis ι R S)
variable (R S)
/-- The trace of an element `s` of an `R`-algebra is the trace of `(s * ·)`,
as an `R`-linear map. -/
noncomputable def trace : S →ₗ[R] R :=
(LinearMap.trace R S).comp (lmul R S).toLinearMap
#align algebra.trace Algebra.trace
variable {S}
-- Not a `simp` lemma since there are more interesting ways to rewrite `trace R S x`,
-- for example `trace_trace`
theorem trace_apply (x) : trace R S x = LinearMap.trace R S (lmul R S x) :=
rfl
#align algebra.trace_apply Algebra.trace_apply
theorem trace_eq_zero_of_not_exists_basis (h : ¬∃ s : Finset S, Nonempty (Basis s R S)) :
trace R S = 0 := by ext s; simp [trace_apply, LinearMap.trace, h]
#align algebra.trace_eq_zero_of_not_exists_basis Algebra.trace_eq_zero_of_not_exists_basis
variable {R}
-- Can't be a `simp` lemma because it depends on a choice of basis
theorem trace_eq_matrix_trace [DecidableEq ι] (b : Basis ι R S) (s : S) :
trace R S s = Matrix.trace (Algebra.leftMulMatrix b s) := by
rw [trace_apply, LinearMap.trace_eq_matrix_trace _ b, ← toMatrix_lmul_eq]; rfl
#align algebra.trace_eq_matrix_trace Algebra.trace_eq_matrix_trace
/-- If `x` is in the base field `K`, then the trace is `[L : K] * x`. -/
theorem trace_algebraMap_of_basis (x : R) : trace R S (algebraMap R S x) = Fintype.card ι • x := by
haveI := Classical.decEq ι
rw [trace_apply, LinearMap.trace_eq_matrix_trace R b, Matrix.trace]
convert Finset.sum_const x
simp [-coe_lmul_eq_mul]
#align algebra.trace_algebra_map_of_basis Algebra.trace_algebraMap_of_basis
/-- If `x` is in the base field `K`, then the trace is `[L : K] * x`.
(If `L` is not finite-dimensional over `K`, then `trace` and `finrank` return `0`.)
-/
@[simp]
theorem trace_algebraMap (x : K) : trace K L (algebraMap K L x) = finrank K L • x := by
by_cases H : ∃ s : Finset L, Nonempty (Basis s K L)
· rw [trace_algebraMap_of_basis H.choose_spec.some, finrank_eq_card_basis H.choose_spec.some]
· simp [trace_eq_zero_of_not_exists_basis K H, finrank_eq_zero_of_not_exists_basis_finset H]
#align algebra.trace_algebra_map Algebra.trace_algebraMap
theorem trace_trace_of_basis [Algebra S T] [IsScalarTower R S T] {ι κ : Type*} [Finite ι]
[Finite κ] (b : Basis ι R S) (c : Basis κ S T) (x : T) :
trace R S (trace S T x) = trace R T x := by
haveI := Classical.decEq ι
haveI := Classical.decEq κ
cases nonempty_fintype ι
cases nonempty_fintype κ
rw [trace_eq_matrix_trace (b.smul c), trace_eq_matrix_trace b, trace_eq_matrix_trace c,
Matrix.trace, Matrix.trace, Matrix.trace, ← Finset.univ_product_univ, Finset.sum_product]
refine Finset.sum_congr rfl fun i _ ↦ ?_
simp only [AlgHom.map_sum, smul_leftMulMatrix, Finset.sum_apply,
Matrix.diag, Finset.sum_apply
i (Finset.univ : Finset κ) fun y => leftMulMatrix b (leftMulMatrix c x y y)]
#align algebra.trace_trace_of_basis Algebra.trace_trace_of_basis
theorem trace_comp_trace_of_basis [Algebra S T] [IsScalarTower R S T] {ι κ : Type*} [Finite ι]
[Finite κ] (b : Basis ι R S) (c : Basis κ S T) :
(trace R S).comp ((trace S T).restrictScalars R) = trace R T := by
ext
rw [LinearMap.comp_apply, LinearMap.restrictScalars_apply, trace_trace_of_basis b c]
#align algebra.trace_comp_trace_of_basis Algebra.trace_comp_trace_of_basis
@[simp]
theorem trace_trace [Algebra K T] [Algebra L T] [IsScalarTower K L T] [FiniteDimensional K L]
[FiniteDimensional L T] (x : T) : trace K L (trace L T x) = trace K T x :=
trace_trace_of_basis (Basis.ofVectorSpace K L) (Basis.ofVectorSpace L T) x
#align algebra.trace_trace Algebra.trace_trace
@[simp]
theorem trace_comp_trace [Algebra K T] [Algebra L T] [IsScalarTower K L T] [FiniteDimensional K L]
[FiniteDimensional L T] : (trace K L).comp ((trace L T).restrictScalars K) = trace K T := by
ext; rw [LinearMap.comp_apply, LinearMap.restrictScalars_apply, trace_trace]
#align algebra.trace_comp_trace Algebra.trace_comp_trace
@[simp]
theorem trace_prod_apply [Module.Free R S] [Module.Free R T] [Module.Finite R S] [Module.Finite R T]
(x : S × T) : trace R (S × T) x = trace R S x.fst + trace R T x.snd := by
nontriviality R
let f := (lmul R S).toLinearMap.prodMap (lmul R T).toLinearMap
have : (lmul R (S × T)).toLinearMap = (prodMapLinear R S T S T R).comp f :=
LinearMap.ext₂ Prod.mul_def
simp_rw [trace, this]
exact trace_prodMap' _ _
#align algebra.trace_prod_apply Algebra.trace_prod_apply
theorem trace_prod [Module.Free R S] [Module.Free R T] [Module.Finite R S] [Module.Finite R T] :
trace R (S × T) = (trace R S).coprod (trace R T) :=
LinearMap.ext fun p => by rw [coprod_apply, trace_prod_apply]
#align algebra.trace_prod Algebra.trace_prod
section TraceForm
variable (R S)
/-- The `traceForm` maps `x y : S` to the trace of `x * y`.
It is a symmetric bilinear form and is nondegenerate if the extension is separable. -/
noncomputable def traceForm : BilinForm R S :=
LinearMap.compr₂ (lmul R S).toLinearMap (trace R S)
#align algebra.trace_form Algebra.traceForm
variable {S}
-- This is a nicer lemma than the one produced by `@[simps] def traceForm`.
@[simp]
theorem traceForm_apply (x y : S) : traceForm R S x y = trace R S (x * y) :=
rfl
#align algebra.trace_form_apply Algebra.traceForm_apply
theorem traceForm_isSymm : (traceForm R S).IsSymm := fun _ _ => congr_arg (trace R S) (mul_comm _ _)
#align algebra.trace_form_is_symm Algebra.traceForm_isSymm
theorem traceForm_toMatrix [DecidableEq ι] (i j) :
BilinForm.toMatrix b (traceForm R S) i j = trace R S (b i * b j) := by
rw [BilinForm.toMatrix_apply, traceForm_apply]
#align algebra.trace_form_to_matrix Algebra.traceForm_toMatrix
theorem traceForm_toMatrix_powerBasis (h : PowerBasis R S) :
BilinForm.toMatrix h.basis (traceForm R S) = of fun i j => trace R S (h.gen ^ (i.1 + j.1)) := by
ext; rw [traceForm_toMatrix, of_apply, pow_add, h.basis_eq_pow, h.basis_eq_pow]
#align algebra.trace_form_to_matrix_power_basis Algebra.traceForm_toMatrix_powerBasis
end TraceForm
end Algebra
section EqSumRoots
open Algebra Polynomial
variable {F : Type*} [Field F]
variable [Algebra K S] [Algebra K F]
/-- Given `pb : PowerBasis K S`, the trace of `pb.gen` is `-(minpoly K pb.gen).nextCoeff`. -/
| Mathlib/RingTheory/Trace.lean | 227 | 233 | theorem PowerBasis.trace_gen_eq_nextCoeff_minpoly [Nontrivial S] (pb : PowerBasis K S) :
Algebra.trace K S pb.gen = -(minpoly K pb.gen).nextCoeff := by |
have d_pos : 0 < pb.dim := PowerBasis.dim_pos pb
have d_pos' : 0 < (minpoly K pb.gen).natDegree := by simpa
haveI : Nonempty (Fin pb.dim) := ⟨⟨0, d_pos⟩⟩
rw [trace_eq_matrix_trace pb.basis, trace_eq_neg_charpoly_coeff, charpoly_leftMulMatrix, ←
pb.natDegree_minpoly, Fintype.card_fin, ← nextCoeff_of_natDegree_pos d_pos']
|
/-
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]
| Mathlib/Data/ZMod/Basic.lean | 176 | 180 | theorem cast_zero : (cast (0 : ZMod n) : R) = 0 := by |
delta ZMod.cast
cases n
· exact Int.cast_zero
· simp
|
/-
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]
| Mathlib/Algebra/Polynomial/Eval.lean | 58 | 61 | 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]
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Mario Carneiro
-/
import Mathlib.Algebra.Module.Submodule.Bilinear
import Mathlib.GroupTheory.Congruence.Basic
import Mathlib.LinearAlgebra.Basic
import Mathlib.Tactic.SuppressCompilation
#align_import linear_algebra.tensor_product from "leanprover-community/mathlib"@"88fcdc3da43943f5b01925deddaa5bf0c0e85e4e"
/-!
# Tensor product of modules over commutative semirings.
This file constructs the tensor product of modules over commutative semirings. Given a semiring
`R` and modules over it `M` and `N`, the standard construction of the tensor product is
`TensorProduct R M N`. It is also a module over `R`.
It comes with a canonical bilinear map `M → N → TensorProduct R M N`.
Given any bilinear map `M → N → P`, there is a unique linear map `TensorProduct R M N → P` whose
composition with the canonical bilinear map `M → N → TensorProduct R M N` is the given bilinear
map `M → N → P`.
We start by proving basic lemmas about bilinear maps.
## Notations
This file uses the localized notation `M ⊗ N` and `M ⊗[R] N` for `TensorProduct R M N`, as well
as `m ⊗ₜ n` and `m ⊗ₜ[R] n` for `TensorProduct.tmul R m n`.
## Tags
bilinear, tensor, tensor product
-/
suppress_compilation
section Semiring
variable {R : Type*} [CommSemiring R]
variable {R' : Type*} [Monoid R']
variable {R'' : Type*} [Semiring R'']
variable {M : Type*} {N : Type*} {P : Type*} {Q : Type*} {S : Type*} {T : Type*}
variable [AddCommMonoid M] [AddCommMonoid N] [AddCommMonoid P]
variable [AddCommMonoid Q] [AddCommMonoid S] [AddCommMonoid T]
variable [Module R M] [Module R N] [Module R P] [Module R Q] [Module R S] [Module R T]
variable [DistribMulAction R' M]
variable [Module R'' M]
variable (M N)
namespace TensorProduct
section
variable (R)
/-- The relation on `FreeAddMonoid (M × N)` that generates a congruence whose quotient is
the tensor product. -/
inductive Eqv : FreeAddMonoid (M × N) → FreeAddMonoid (M × N) → Prop
| of_zero_left : ∀ n : N, Eqv (.of (0, n)) 0
| of_zero_right : ∀ m : M, Eqv (.of (m, 0)) 0
| of_add_left : ∀ (m₁ m₂ : M) (n : N), Eqv (.of (m₁, n) + .of (m₂, n)) (.of (m₁ + m₂, n))
| of_add_right : ∀ (m : M) (n₁ n₂ : N), Eqv (.of (m, n₁) + .of (m, n₂)) (.of (m, n₁ + n₂))
| of_smul : ∀ (r : R) (m : M) (n : N), Eqv (.of (r • m, n)) (.of (m, r • n))
| add_comm : ∀ x y, Eqv (x + y) (y + x)
#align tensor_product.eqv TensorProduct.Eqv
end
end TensorProduct
variable (R)
/-- The tensor product of two modules `M` and `N` over the same commutative semiring `R`.
The localized notations are `M ⊗ N` and `M ⊗[R] N`, accessed by `open scoped TensorProduct`. -/
def TensorProduct : Type _ :=
(addConGen (TensorProduct.Eqv R M N)).Quotient
#align tensor_product TensorProduct
variable {R}
set_option quotPrecheck false in
@[inherit_doc TensorProduct] scoped[TensorProduct] infixl:100 " ⊗ " => TensorProduct _
@[inherit_doc] scoped[TensorProduct] notation:100 M " ⊗[" R "] " N:100 => TensorProduct R M N
namespace TensorProduct
section Module
protected instance add : Add (M ⊗[R] N) :=
(addConGen (TensorProduct.Eqv R M N)).hasAdd
instance addZeroClass : AddZeroClass (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with
/- The `toAdd` field is given explicitly as `TensorProduct.add` for performance reasons.
This avoids any need to unfold `Con.addMonoid` when the type checker is checking
that instance diagrams commute -/
toAdd := TensorProduct.add _ _ }
instance addSemigroup : AddSemigroup (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with
toAdd := TensorProduct.add _ _ }
instance addCommSemigroup : AddCommSemigroup (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with
toAddSemigroup := TensorProduct.addSemigroup _ _
add_comm := fun x y =>
AddCon.induction_on₂ x y fun _ _ =>
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.add_comm _ _ }
instance : Inhabited (M ⊗[R] N) :=
⟨0⟩
variable (R) {M N}
/-- The canonical function `M → N → M ⊗ N`. The localized notations are `m ⊗ₜ n` and `m ⊗ₜ[R] n`,
accessed by `open scoped TensorProduct`. -/
def tmul (m : M) (n : N) : M ⊗[R] N :=
AddCon.mk' _ <| FreeAddMonoid.of (m, n)
#align tensor_product.tmul TensorProduct.tmul
variable {R}
/-- The canonical function `M → N → M ⊗ N`. -/
infixl:100 " ⊗ₜ " => tmul _
/-- The canonical function `M → N → M ⊗ N`. -/
notation:100 x " ⊗ₜ[" R "] " y:100 => tmul R x y
-- Porting note: make the arguments of induction_on explicit
@[elab_as_elim]
protected theorem induction_on {motive : M ⊗[R] N → Prop} (z : M ⊗[R] N)
(zero : motive 0)
(tmul : ∀ x y, motive <| x ⊗ₜ[R] y)
(add : ∀ x y, motive x → motive y → motive (x + y)) : motive z :=
AddCon.induction_on z fun x =>
FreeAddMonoid.recOn x zero fun ⟨m, n⟩ y ih => by
rw [AddCon.coe_add]
exact add _ _ (tmul ..) ih
#align tensor_product.induction_on TensorProduct.induction_on
/-- Lift an `R`-balanced map to the tensor product.
A map `f : M →+ N →+ P` additive in both components is `R`-balanced, or middle linear with respect
to `R`, if scalar multiplication in either argument is equivalent, `f (r • m) n = f m (r • n)`.
Note that strictly the first action should be a right-action by `R`, but for now `R` is commutative
so it doesn't matter. -/
-- TODO: use this to implement `lift` and `SMul.aux`. For now we do not do this as it causes
-- performance issues elsewhere.
def liftAddHom (f : M →+ N →+ P)
(hf : ∀ (r : R) (m : M) (n : N), f (r • m) n = f m (r • n)) :
M ⊗[R] N →+ P :=
(addConGen (TensorProduct.Eqv R M N)).lift (FreeAddMonoid.lift (fun mn : M × N => f mn.1 mn.2)) <|
AddCon.addConGen_le fun x y hxy =>
match x, y, hxy with
| _, _, .of_zero_left n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, FreeAddMonoid.lift_eval_of, map_zero,
AddMonoidHom.zero_apply]
| _, _, .of_zero_right m =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, FreeAddMonoid.lift_eval_of, map_zero]
| _, _, .of_add_left m₁ m₂ n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, FreeAddMonoid.lift_eval_of, map_add,
AddMonoidHom.add_apply]
| _, _, .of_add_right m n₁ n₂ =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, FreeAddMonoid.lift_eval_of, map_add]
| _, _, .of_smul s m n =>
(AddCon.ker_rel _).2 <| by rw [FreeAddMonoid.lift_eval_of, FreeAddMonoid.lift_eval_of, hf]
| _, _, .add_comm x y =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, add_comm]
@[simp]
theorem liftAddHom_tmul (f : M →+ N →+ P)
(hf : ∀ (r : R) (m : M) (n : N), f (r • m) n = f m (r • n)) (m : M) (n : N) :
liftAddHom f hf (m ⊗ₜ n) = f m n :=
rfl
variable (M)
@[simp]
theorem zero_tmul (n : N) : (0 : M) ⊗ₜ[R] n = 0 :=
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_zero_left _
#align tensor_product.zero_tmul TensorProduct.zero_tmul
variable {M}
theorem add_tmul (m₁ m₂ : M) (n : N) : (m₁ + m₂) ⊗ₜ n = m₁ ⊗ₜ n + m₂ ⊗ₜ[R] n :=
Eq.symm <| Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_add_left _ _ _
#align tensor_product.add_tmul TensorProduct.add_tmul
variable (N)
@[simp]
theorem tmul_zero (m : M) : m ⊗ₜ[R] (0 : N) = 0 :=
Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_zero_right _
#align tensor_product.tmul_zero TensorProduct.tmul_zero
variable {N}
theorem tmul_add (m : M) (n₁ n₂ : N) : m ⊗ₜ (n₁ + n₂) = m ⊗ₜ n₁ + m ⊗ₜ[R] n₂ :=
Eq.symm <| Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_add_right _ _ _
#align tensor_product.tmul_add TensorProduct.tmul_add
instance uniqueLeft [Subsingleton M] : Unique (M ⊗[R] N) where
default := 0
uniq z := z.induction_on rfl (fun x y ↦ by rw [Subsingleton.elim x 0, zero_tmul]; rfl) <| by
rintro _ _ rfl rfl; apply add_zero
instance uniqueRight [Subsingleton N] : Unique (M ⊗[R] N) where
default := 0
uniq z := z.induction_on rfl (fun x y ↦ by rw [Subsingleton.elim y 0, tmul_zero]; rfl) <| by
rintro _ _ rfl rfl; apply add_zero
section
variable (R R' M N)
/-- A typeclass for `SMul` structures which can be moved across a tensor product.
This typeclass is generated automatically from an `IsScalarTower` instance, but exists so that
we can also add an instance for `AddCommGroup.intModule`, allowing `z •` to be moved even if
`R` does not support negation.
Note that `Module R' (M ⊗[R] N)` is available even without this typeclass on `R'`; it's only
needed if `TensorProduct.smul_tmul`, `TensorProduct.smul_tmul'`, or `TensorProduct.tmul_smul` is
used.
-/
class CompatibleSMul [DistribMulAction R' N] : Prop where
smul_tmul : ∀ (r : R') (m : M) (n : N), (r • m) ⊗ₜ n = m ⊗ₜ[R] (r • n)
#align tensor_product.compatible_smul TensorProduct.CompatibleSMul
end
/-- Note that this provides the default `compatible_smul R R M N` instance through
`IsScalarTower.left`. -/
instance (priority := 100) CompatibleSMul.isScalarTower [SMul R' R] [IsScalarTower R' R M]
[DistribMulAction R' N] [IsScalarTower R' R N] : CompatibleSMul R R' M N :=
⟨fun r m n => by
conv_lhs => rw [← one_smul R m]
conv_rhs => rw [← one_smul R n]
rw [← smul_assoc, ← smul_assoc]
exact Quotient.sound' <| AddConGen.Rel.of _ _ <| Eqv.of_smul _ _ _⟩
#align tensor_product.compatible_smul.is_scalar_tower TensorProduct.CompatibleSMul.isScalarTower
/-- `smul` can be moved from one side of the product to the other . -/
theorem smul_tmul [DistribMulAction R' N] [CompatibleSMul R R' M N] (r : R') (m : M) (n : N) :
(r • m) ⊗ₜ n = m ⊗ₜ[R] (r • n) :=
CompatibleSMul.smul_tmul _ _ _
#align tensor_product.smul_tmul TensorProduct.smul_tmul
-- Porting note: This is added as a local instance for `SMul.aux`.
-- For some reason type-class inference in Lean 3 unfolded this definition.
private def addMonoidWithWrongNSMul : AddMonoid (M ⊗[R] N) :=
{ (addConGen (TensorProduct.Eqv R M N)).addMonoid with }
attribute [local instance] addMonoidWithWrongNSMul in
/-- Auxiliary function to defining scalar multiplication on tensor product. -/
def SMul.aux {R' : Type*} [SMul R' M] (r : R') : FreeAddMonoid (M × N) →+ M ⊗[R] N :=
FreeAddMonoid.lift fun p : M × N => (r • p.1) ⊗ₜ p.2
#align tensor_product.smul.aux TensorProduct.SMul.aux
theorem SMul.aux_of {R' : Type*} [SMul R' M] (r : R') (m : M) (n : N) :
SMul.aux r (.of (m, n)) = (r • m) ⊗ₜ[R] n :=
rfl
#align tensor_product.smul.aux_of TensorProduct.SMul.aux_of
variable [SMulCommClass R R' M] [SMulCommClass R R'' M]
/-- Given two modules over a commutative semiring `R`, if one of the factors carries a
(distributive) action of a second type of scalars `R'`, which commutes with the action of `R`, then
the tensor product (over `R`) carries an action of `R'`.
This instance defines this `R'` action in the case that it is the left module which has the `R'`
action. Two natural ways in which this situation arises are:
* Extension of scalars
* A tensor product of a group representation with a module not carrying an action
Note that in the special case that `R = R'`, since `R` is commutative, we just get the usual scalar
action on a tensor product of two modules. This special case is important enough that, for
performance reasons, we define it explicitly below. -/
instance leftHasSMul : SMul R' (M ⊗[R] N) :=
⟨fun r =>
(addConGen (TensorProduct.Eqv R M N)).lift (SMul.aux r : _ →+ M ⊗[R] N) <|
AddCon.addConGen_le fun x y hxy =>
match x, y, hxy with
| _, _, .of_zero_left n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, SMul.aux_of, smul_zero, zero_tmul]
| _, _, .of_zero_right m =>
(AddCon.ker_rel _).2 <| by simp_rw [map_zero, SMul.aux_of, tmul_zero]
| _, _, .of_add_left m₁ m₂ n =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, SMul.aux_of, smul_add, add_tmul]
| _, _, .of_add_right m n₁ n₂ =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, SMul.aux_of, tmul_add]
| _, _, .of_smul s m n =>
(AddCon.ker_rel _).2 <| by rw [SMul.aux_of, SMul.aux_of, ← smul_comm, smul_tmul]
| _, _, .add_comm x y =>
(AddCon.ker_rel _).2 <| by simp_rw [map_add, add_comm]⟩
#align tensor_product.left_has_smul TensorProduct.leftHasSMul
instance : SMul R (M ⊗[R] N) :=
TensorProduct.leftHasSMul
protected theorem smul_zero (r : R') : r • (0 : M ⊗[R] N) = 0 :=
AddMonoidHom.map_zero _
#align tensor_product.smul_zero TensorProduct.smul_zero
protected theorem smul_add (r : R') (x y : M ⊗[R] N) : r • (x + y) = r • x + r • y :=
AddMonoidHom.map_add _ _ _
#align tensor_product.smul_add TensorProduct.smul_add
protected theorem zero_smul (x : M ⊗[R] N) : (0 : R'') • x = 0 :=
have : ∀ (r : R'') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
x.induction_on (by rw [TensorProduct.smul_zero])
(fun m n => by rw [this, zero_smul, zero_tmul]) fun x y ihx ihy => by
rw [TensorProduct.smul_add, ihx, ihy, add_zero]
#align tensor_product.zero_smul TensorProduct.zero_smul
protected theorem one_smul (x : M ⊗[R] N) : (1 : R') • x = x :=
have : ∀ (r : R') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
x.induction_on (by rw [TensorProduct.smul_zero])
(fun m n => by rw [this, one_smul])
fun x y ihx ihy => by rw [TensorProduct.smul_add, ihx, ihy]
#align tensor_product.one_smul TensorProduct.one_smul
protected theorem add_smul (r s : R'') (x : M ⊗[R] N) : (r + s) • x = r • x + s • x :=
have : ∀ (r : R'') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
x.induction_on (by simp_rw [TensorProduct.smul_zero, add_zero])
(fun m n => by simp_rw [this, add_smul, add_tmul]) fun x y ihx ihy => by
simp_rw [TensorProduct.smul_add]
rw [ihx, ihy, add_add_add_comm]
#align tensor_product.add_smul TensorProduct.add_smul
instance addMonoid : AddMonoid (M ⊗[R] N) :=
{ TensorProduct.addZeroClass _ _ with
toAddSemigroup := TensorProduct.addSemigroup _ _
toZero := (TensorProduct.addZeroClass _ _).toZero
nsmul := fun n v => n • v
nsmul_zero := by simp [TensorProduct.zero_smul]
nsmul_succ := by simp only [TensorProduct.one_smul, TensorProduct.add_smul, add_comm,
forall_const] }
instance addCommMonoid : AddCommMonoid (M ⊗[R] N) :=
{ TensorProduct.addCommSemigroup _ _ with
toAddMonoid := TensorProduct.addMonoid }
instance leftDistribMulAction : DistribMulAction R' (M ⊗[R] N) :=
have : ∀ (r : R') (m : M) (n : N), r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n := fun _ _ _ => rfl
{ smul_add := fun r x y => TensorProduct.smul_add r x y
mul_smul := fun r s x =>
x.induction_on (by simp_rw [TensorProduct.smul_zero])
(fun m n => by simp_rw [this, mul_smul]) fun x y ihx ihy => by
simp_rw [TensorProduct.smul_add]
rw [ihx, ihy]
one_smul := TensorProduct.one_smul
smul_zero := TensorProduct.smul_zero }
#align tensor_product.left_distrib_mul_action TensorProduct.leftDistribMulAction
instance : DistribMulAction R (M ⊗[R] N) :=
TensorProduct.leftDistribMulAction
theorem smul_tmul' (r : R') (m : M) (n : N) : r • m ⊗ₜ[R] n = (r • m) ⊗ₜ n :=
rfl
#align tensor_product.smul_tmul' TensorProduct.smul_tmul'
@[simp]
theorem tmul_smul [DistribMulAction R' N] [CompatibleSMul R R' M N] (r : R') (x : M) (y : N) :
x ⊗ₜ (r • y) = r • x ⊗ₜ[R] y :=
(smul_tmul _ _ _).symm
#align tensor_product.tmul_smul TensorProduct.tmul_smul
theorem smul_tmul_smul (r s : R) (m : M) (n : N) : (r • m) ⊗ₜ[R] (s • n) = (r * s) • m ⊗ₜ[R] n := by
simp_rw [smul_tmul, tmul_smul, mul_smul]
#align tensor_product.smul_tmul_smul TensorProduct.smul_tmul_smul
instance leftModule : Module R'' (M ⊗[R] N) :=
{ add_smul := TensorProduct.add_smul
zero_smul := TensorProduct.zero_smul }
#align tensor_product.left_module TensorProduct.leftModule
instance : Module R (M ⊗[R] N) :=
TensorProduct.leftModule
instance [Module R''ᵐᵒᵖ M] [IsCentralScalar R'' M] : IsCentralScalar R'' (M ⊗[R] N) where
op_smul_eq_smul r x :=
x.induction_on (by rw [smul_zero, smul_zero])
(fun x y => by rw [smul_tmul', smul_tmul', op_smul_eq_smul]) fun x y hx hy => by
rw [smul_add, smul_add, hx, hy]
section
-- Like `R'`, `R'₂` provides a `DistribMulAction R'₂ (M ⊗[R] N)`
variable {R'₂ : Type*} [Monoid R'₂] [DistribMulAction R'₂ M]
variable [SMulCommClass R R'₂ M]
/-- `SMulCommClass R' R'₂ M` implies `SMulCommClass R' R'₂ (M ⊗[R] N)` -/
instance smulCommClass_left [SMulCommClass R' R'₂ M] : SMulCommClass R' R'₂ (M ⊗[R] N) where
smul_comm r' r'₂ x :=
TensorProduct.induction_on x (by simp_rw [TensorProduct.smul_zero])
(fun m n => by simp_rw [smul_tmul', smul_comm]) fun x y ihx ihy => by
simp_rw [TensorProduct.smul_add]; rw [ihx, ihy]
#align tensor_product.smul_comm_class_left TensorProduct.smulCommClass_left
variable [SMul R'₂ R']
/-- `IsScalarTower R'₂ R' M` implies `IsScalarTower R'₂ R' (M ⊗[R] N)` -/
instance isScalarTower_left [IsScalarTower R'₂ R' M] : IsScalarTower R'₂ R' (M ⊗[R] N) :=
⟨fun s r x =>
x.induction_on (by simp)
(fun m n => by rw [smul_tmul', smul_tmul', smul_tmul', smul_assoc]) fun x y ihx ihy => by
rw [smul_add, smul_add, smul_add, ihx, ihy]⟩
#align tensor_product.is_scalar_tower_left TensorProduct.isScalarTower_left
variable [DistribMulAction R'₂ N] [DistribMulAction R' N]
variable [CompatibleSMul R R'₂ M N] [CompatibleSMul R R' M N]
/-- `IsScalarTower R'₂ R' N` implies `IsScalarTower R'₂ R' (M ⊗[R] N)` -/
instance isScalarTower_right [IsScalarTower R'₂ R' N] : IsScalarTower R'₂ R' (M ⊗[R] N) :=
⟨fun s r x =>
x.induction_on (by simp)
(fun m n => by rw [← tmul_smul, ← tmul_smul, ← tmul_smul, smul_assoc]) fun x y ihx ihy => by
rw [smul_add, smul_add, smul_add, ihx, ihy]⟩
#align tensor_product.is_scalar_tower_right TensorProduct.isScalarTower_right
end
/-- A short-cut instance for the common case, where the requirements for the `compatible_smul`
instances are sufficient. -/
instance isScalarTower [SMul R' R] [IsScalarTower R' R M] : IsScalarTower R' R (M ⊗[R] N) :=
TensorProduct.isScalarTower_left
#align tensor_product.is_scalar_tower TensorProduct.isScalarTower
-- or right
variable (R M N)
/-- The canonical bilinear map `M → N → M ⊗[R] N`. -/
def mk : M →ₗ[R] N →ₗ[R] M ⊗[R] N :=
LinearMap.mk₂ R (· ⊗ₜ ·) add_tmul (fun c m n => by simp_rw [smul_tmul, tmul_smul])
tmul_add tmul_smul
#align tensor_product.mk TensorProduct.mk
variable {R M N}
@[simp]
theorem mk_apply (m : M) (n : N) : mk R M N m n = m ⊗ₜ n :=
rfl
#align tensor_product.mk_apply TensorProduct.mk_apply
theorem ite_tmul (x₁ : M) (x₂ : N) (P : Prop) [Decidable P] :
(if P then x₁ else 0) ⊗ₜ[R] x₂ = if P then x₁ ⊗ₜ x₂ else 0 := by split_ifs <;> simp
#align tensor_product.ite_tmul TensorProduct.ite_tmul
theorem tmul_ite (x₁ : M) (x₂ : N) (P : Prop) [Decidable P] :
(x₁ ⊗ₜ[R] if P then x₂ else 0) = if P then x₁ ⊗ₜ x₂ else 0 := by split_ifs <;> simp
#align tensor_product.tmul_ite TensorProduct.tmul_ite
section
theorem sum_tmul {α : Type*} (s : Finset α) (m : α → M) (n : N) :
(∑ a ∈ s, m a) ⊗ₜ[R] n = ∑ a ∈ s, m a ⊗ₜ[R] n := by
classical
induction' s using Finset.induction with a s has ih h
· simp
· simp [Finset.sum_insert has, add_tmul, ih]
#align tensor_product.sum_tmul TensorProduct.sum_tmul
theorem tmul_sum (m : M) {α : Type*} (s : Finset α) (n : α → N) :
(m ⊗ₜ[R] ∑ a ∈ s, n a) = ∑ a ∈ s, m ⊗ₜ[R] n a := by
classical
induction' s using Finset.induction with a s has ih h
· simp
· simp [Finset.sum_insert has, tmul_add, ih]
#align tensor_product.tmul_sum TensorProduct.tmul_sum
end
variable (R M N)
/-- The simple (aka pure) elements span the tensor product. -/
| Mathlib/LinearAlgebra/TensorProduct/Basic.lean | 482 | 490 | theorem span_tmul_eq_top : Submodule.span R { t : M ⊗[R] N | ∃ m n, m ⊗ₜ n = t } = ⊤ := by |
ext t; simp only [Submodule.mem_top, iff_true_iff]
refine t.induction_on ?_ ?_ ?_
· exact Submodule.zero_mem _
· intro m n
apply Submodule.subset_span
use m, n
· intro t₁ t₂ ht₁ ht₂
exact Submodule.add_mem _ ht₁ ht₂
|
/-
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.Set.Card
import Mathlib.Order.Minimal
import Mathlib.Data.Matroid.Init
/-!
# Matroids
A `Matroid` is a structure that combinatorially abstracts
the notion of linear independence and dependence;
matroids have connections with graph theory, discrete optimization,
additive combinatorics and algebraic geometry.
Mathematically, a matroid `M` is a structure on a set `E` comprising a
collection of subsets of `E` called the bases of `M`,
where the bases are required to obey certain axioms.
This file gives a definition of a matroid `M` in terms of its bases,
and some API relating independent sets (subsets of bases) and the notion of a
basis of a set `X` (a maximal independent subset of `X`).
## Main definitions
* a `Matroid α` on a type `α` is a structure comprising a 'ground set'
and a suitably behaved 'base' predicate.
Given `M : Matroid α` ...
* `M.E` denotes the ground set of `M`, which has type `Set α`
* For `B : Set α`, `M.Base B` means that `B` is a base of `M`.
* For `I : Set α`, `M.Indep I` means that `I` is independent in `M`
(that is, `I` is contained in a base of `M`).
* For `D : Set α`, `M.Dep D` means that `D` is contained in the ground set of `M`
but isn't independent.
* For `I : Set α` and `X : Set α`, `M.Basis I X` means that `I` is a maximal independent
subset of `X`.
* `M.Finite` means that `M` has finite ground set.
* `M.Nonempty` means that the ground set of `M` is nonempty.
* `FiniteRk M` means that the bases of `M` are finite.
* `InfiniteRk M` means that the bases of `M` are infinite.
* `RkPos M` means that the bases of `M` are nonempty.
* `Finitary M` means that a set is independent if and only if all its finite subsets are
independent.
* `aesop_mat` : a tactic designed to prove `X ⊆ M.E` for some set `X` and matroid `M`.
## Implementation details
There are a few design decisions worth discussing.
### Finiteness
The first is that our matroids are allowed to be infinite.
Unlike with many mathematical structures, this isn't such an obvious choice.
Finite matroids have been studied since the 1930's,
and there was never controversy as to what is and isn't an example of a finite matroid -
in fact, surprisingly many apparently different definitions of a matroid
give rise to the same class of objects.
However, generalizing different definitions of a finite matroid
to the infinite in the obvious way (i.e. by simply allowing the ground set to be infinite)
gives a number of different notions of 'infinite matroid' that disagree with each other,
and that all lack nice properties.
Many different competing notions of infinite matroid were studied through the years;
in fact, the problem of which definition is the best was only really solved in 2013,
when Bruhn et al. [2] showed that there is a unique 'reasonable' notion of an infinite matroid
(these objects had previously defined by Higgs under the name 'B-matroid').
These are defined by adding one carefully chosen axiom to the standard set,
and adapting existing axioms to not mention set cardinalities;
they enjoy nearly all the nice properties of standard finite matroids.
Even though at least 90% of the literature is on finite matroids,
B-matroids are the definition we use, because they allow for additional generality,
nearly all theorems are still true and just as easy to state,
and (hopefully) the more general definition will prevent the need for a costly future refactor.
The disadvantage is that developing API for the finite case is harder work
(for instance, it is harder to prove that something is a matroid in the first place,
and one must deal with `ℕ∞` rather than `ℕ`).
For serious work on finite matroids, we provide the typeclasses
`[M.Finite]` and `[FiniteRk M]` and associated API.
### Cardinality
Just as with bases of a vector space,
all bases of a finite matroid `M` are finite and have the same cardinality;
this cardinality is an important invariant known as the 'rank' of `M`.
For infinite matroids, bases are not in general equicardinal;
in fact the equicardinality of bases of infinite matroids is independent of ZFC [3].
What is still true is that either all bases are finite and equicardinal,
or all bases are infinite. This means that the natural notion of 'size'
for a set in matroid theory is given by the function `Set.encard`, which
is the cardinality as a term in `ℕ∞`. We use this function extensively
in building the API; it is preferable to both `Set.ncard` and `Finset.card`
because it allows infinite sets to be handled without splitting into cases.
### The ground `Set`
A last place where we make a consequential choice is making the ground set of a matroid
a structure field of type `Set α` (where `α` is the type of 'possible matroid elements')
rather than just having a type `α` of all the matroid elements.
This is because of how common it is to simultaneously consider
a number of matroids on different but related ground sets.
For example, a matroid `M` on ground set `E` can have its structure
'restricted' to some subset `R ⊆ E` to give a smaller matroid `M ↾ R` with ground set `R`.
A statement like `(M ↾ R₁) ↾ R₂ = M ↾ R₂` is mathematically obvious.
But if the ground set of a matroid is a type, this doesn't typecheck,
and is only true up to canonical isomorphism.
Restriction is just the tip of the iceberg here;
one can also 'contract' and 'delete' elements and sets of elements
in a matroid to give a smaller matroid,
and in practice it is common to make statements like `M₁.E = M₂.E ∩ M₃.E` and
`((M ⟋ e) ↾ R) ⟋ C = M ⟋ (C ∪ {e}) ↾ R`.
Such things are a nightmare to work with unless `=` is actually propositional equality
(especially because the relevant coercions are usually between sets and not just elements).
So the solution is that the ground set `M.E` has type `Set α`,
and there are elements of type `α` that aren't in the matroid.
The tradeoff is that for many statements, one now has to add
hypotheses of the form `X ⊆ M.E` to make sure than `X` is actually 'in the matroid',
rather than letting a 'type of matroid elements' take care of this invisibly.
It still seems that this is worth it.
The tactic `aesop_mat` exists specifically to discharge such goals
with minimal fuss (using default values).
The tactic works fairly well, but has room for improvement.
Even though the carrier set is written `M.E`,
A related decision is to not have matroids themselves be a typeclass.
This would make things be notationally simpler
(having `Base` in the presence of `[Matroid α]` rather than `M.Base` for a term `M : Matroid α`)
but is again just too awkward when one has multiple matroids on the same type.
In fact, in regular written mathematics,
it is normal to explicitly indicate which matroid something is happening in,
so our notation mirrors common practice.
### Notation
We use a couple of nonstandard conventions in theorem names that are related to the above.
First, we mirror common informal practice by referring explicitly to the `ground` set rather
than the notation `E`. (Writing `ground` everywhere in a proof term would be unwieldy, and
writing `E` in theorem names would be unnatural to read.)
Second, because we are typically interested in subsets of the ground set `M.E`,
using `Set.compl` is inconvenient, since `Xᶜ ⊆ M.E` is typically false for `X ⊆ M.E`.
On the other hand (especially when duals arise), it is common to complement
a set `X ⊆ M.E` *within* the ground set, giving `M.E \ X`.
For this reason, we use the term `compl` in theorem names to refer to taking a set difference
with respect to the ground set, rather than a complement within a type. The lemma
`compl_base_dual` is one of the many examples of this.
## References
[1] The standard text on matroid theory
[J. G. Oxley, Matroid Theory, Oxford University Press, New York, 2011.]
[2] The robust axiomatic definition of infinite matroids
[H. Bruhn, R. Diestel, M. Kriesell, R. Pendavingh, P. Wollan, Axioms for infinite matroids,
Adv. Math 239 (2013), 18-46]
[3] Equicardinality of matroid bases is independent of ZFC.
[N. Bowler, S. Geschke, Self-dual uniform matroids on infinite sets,
Proc. Amer. Math. Soc. 144 (2016), 459-471]
-/
set_option autoImplicit true
open Set
/-- A predicate `P` on sets satisfies the **exchange property** if,
for all `X` and `Y` satisfying `P` and all `a ∈ X \ Y`, there exists `b ∈ Y \ X` so that
swapping `a` for `b` in `X` maintains `P`. -/
def Matroid.ExchangeProperty {α : Type _} (P : Set α → Prop) : Prop :=
∀ X Y, P X → P Y → ∀ a ∈ X \ Y, ∃ b ∈ Y \ X, P (insert b (X \ {a}))
/-- A set `X` has the maximal subset property for a predicate `P` if every subset of `X` satisfying
`P` is contained in a maximal subset of `X` satisfying `P`. -/
def Matroid.ExistsMaximalSubsetProperty {α : Type _} (P : Set α → Prop) (X : Set α) : Prop :=
∀ I, P I → I ⊆ X → (maximals (· ⊆ ·) {Y | P Y ∧ I ⊆ Y ∧ Y ⊆ X}).Nonempty
/-- A `Matroid α` is a ground set `E` of type `Set α`, and a nonempty collection of its subsets
satisfying the exchange property and the maximal subset property. Each such set is called a
`Base` of `M`. An `Indep`endent set is just a set contained in a base, but we include this
predicate as a structure field for better definitional properties.
In most cases, using this definition directly is not the best way to construct a matroid,
since it requires specifying both the bases and independent sets. If the bases are known,
use `Matroid.ofBase` or a variant. If just the independent sets are known,
define an `IndepMatroid`, and then use `IndepMatroid.matroid`.
-/
@[ext] structure Matroid (α : Type _) where
/-- `M` has a ground set `E`. -/
(E : Set α)
/-- `M` has a predicate `Base` definining its bases. -/
(Base : Set α → Prop)
/-- `M` has a predicate `Indep` defining its independent sets. -/
(Indep : Set α → Prop)
/-- The `Indep`endent sets are those contained in `Base`s. -/
(indep_iff' : ∀ ⦃I⦄, Indep I ↔ ∃ B, Base B ∧ I ⊆ B)
/-- There is at least one `Base`. -/
(exists_base : ∃ B, Base B)
/-- For any bases `B`, `B'` and `e ∈ B \ B'`, there is some `f ∈ B' \ B` for which `B-e+f`
is a base. -/
(base_exchange : Matroid.ExchangeProperty Base)
/-- Every independent subset `I` of a set `X` for is contained in a maximal independent
subset of `X`. -/
(maximality : ∀ X, X ⊆ E → Matroid.ExistsMaximalSubsetProperty Indep X)
/-- Every base is contained in the ground set. -/
(subset_ground : ∀ B, Base B → B ⊆ E)
namespace Matroid
variable {α : Type*} {M : Matroid α}
/-- Typeclass for a matroid having finite ground set. Just a wrapper for `M.E.Finite`-/
protected class Finite (M : Matroid α) : Prop where
/-- The ground set is finite -/
(ground_finite : M.E.Finite)
/-- Typeclass for a matroid having nonempty ground set. Just a wrapper for `M.E.Nonempty`-/
protected class Nonempty (M : Matroid α) : Prop where
/-- The ground set is nonempty -/
(ground_nonempty : M.E.Nonempty)
theorem ground_nonempty (M : Matroid α) [M.Nonempty] : M.E.Nonempty :=
Nonempty.ground_nonempty
theorem ground_nonempty_iff (M : Matroid α) : M.E.Nonempty ↔ M.Nonempty :=
⟨fun h ↦ ⟨h⟩, fun ⟨h⟩ ↦ h⟩
theorem ground_finite (M : Matroid α) [M.Finite] : M.E.Finite :=
Finite.ground_finite
theorem set_finite (M : Matroid α) [M.Finite] (X : Set α) (hX : X ⊆ M.E := by aesop) : X.Finite :=
M.ground_finite.subset hX
instance finite_of_finite [Finite α] {M : Matroid α} : M.Finite :=
⟨Set.toFinite _⟩
/-- A `FiniteRk` matroid is one whose bases are finite -/
class FiniteRk (M : Matroid α) : Prop where
/-- There is a finite base -/
exists_finite_base : ∃ B, M.Base B ∧ B.Finite
instance finiteRk_of_finite (M : Matroid α) [M.Finite] : FiniteRk M :=
⟨M.exists_base.imp (fun B hB ↦ ⟨hB, M.set_finite B (M.subset_ground _ hB)⟩)⟩
/-- An `InfiniteRk` matroid is one whose bases are infinite. -/
class InfiniteRk (M : Matroid α) : Prop where
/-- There is an infinite base -/
exists_infinite_base : ∃ B, M.Base B ∧ B.Infinite
/-- A `RkPos` matroid is one whose bases are nonempty. -/
class RkPos (M : Matroid α) : Prop where
/-- The empty set isn't a base -/
empty_not_base : ¬M.Base ∅
theorem rkPos_iff_empty_not_base : M.RkPos ↔ ¬M.Base ∅ :=
⟨fun ⟨h⟩ ↦ h, fun h ↦ ⟨h⟩⟩
section exchange
namespace ExchangeProperty
variable {Base : Set α → Prop} (exch : ExchangeProperty Base)
/-- A family of sets with the exchange property is an antichain. -/
theorem antichain (hB : Base B) (hB' : Base B') (h : B ⊆ B') : B = B' :=
h.antisymm (fun x hx ↦ by_contra
(fun hxB ↦ let ⟨_, hy, _⟩ := exch B' B hB' hB x ⟨hx, hxB⟩; hy.2 <| h hy.1))
theorem encard_diff_le_aux (exch : ExchangeProperty Base) (hB₁ : Base B₁) (hB₂ : Base B₂) :
(B₁ \ B₂).encard ≤ (B₂ \ B₁).encard := by
obtain (he | hinf | ⟨e, he, hcard⟩) :=
(B₂ \ B₁).eq_empty_or_encard_eq_top_or_encard_diff_singleton_lt
· rw [exch.antichain hB₂ hB₁ (diff_eq_empty.mp he)]
· exact le_top.trans_eq hinf.symm
obtain ⟨f, hf, hB'⟩ := exch B₂ B₁ hB₂ hB₁ e he
have : encard (insert f (B₂ \ {e}) \ B₁) < encard (B₂ \ B₁) := by
rw [insert_diff_of_mem _ hf.1, diff_diff_comm]; exact hcard
have hencard := encard_diff_le_aux exch hB₁ hB'
rw [insert_diff_of_mem _ hf.1, diff_diff_comm, ← union_singleton, ← diff_diff, diff_diff_right,
inter_singleton_eq_empty.mpr he.2, union_empty] at hencard
rw [← encard_diff_singleton_add_one he, ← encard_diff_singleton_add_one hf]
exact add_le_add_right hencard 1
termination_by (B₂ \ B₁).encard
/-- For any two sets `B₁`, `B₂` in a family with the exchange property, the differences `B₁ \ B₂`
and `B₂ \ B₁` have the same `ℕ∞`-cardinality. -/
theorem encard_diff_eq (hB₁ : Base B₁) (hB₂ : Base B₂) : (B₁ \ B₂).encard = (B₂ \ B₁).encard :=
(encard_diff_le_aux exch hB₁ hB₂).antisymm (encard_diff_le_aux exch hB₂ hB₁)
/-- Any two sets `B₁`, `B₂` in a family with the exchange property have the same
`ℕ∞`-cardinality. -/
theorem encard_base_eq (hB₁ : Base B₁) (hB₂ : Base B₂) : B₁.encard = B₂.encard := by
rw [← encard_diff_add_encard_inter B₁ B₂, exch.encard_diff_eq hB₁ hB₂, inter_comm,
encard_diff_add_encard_inter]
end ExchangeProperty
end exchange
section aesop
/-- The `aesop_mat` tactic attempts to prove a set is contained in the ground set of a matroid.
It uses a `[Matroid]` ruleset, and is allowed to fail. -/
macro (name := aesop_mat) "aesop_mat" c:Aesop.tactic_clause* : tactic =>
`(tactic|
aesop $c* (config := { terminal := true })
(rule_sets := [$(Lean.mkIdent `Matroid):ident]))
/- We add a number of trivial lemmas (deliberately specialized to statements in terms of the
ground set of a matroid) to the ruleset `Matroid` for `aesop`. -/
@[aesop unsafe 5% (rule_sets := [Matroid])]
private theorem inter_right_subset_ground (hX : X ⊆ M.E) :
X ∩ Y ⊆ M.E := inter_subset_left.trans hX
@[aesop unsafe 5% (rule_sets := [Matroid])]
private theorem inter_left_subset_ground (hX : X ⊆ M.E) :
Y ∩ X ⊆ M.E := inter_subset_right.trans hX
@[aesop unsafe 5% (rule_sets := [Matroid])]
private theorem diff_subset_ground (hX : X ⊆ M.E) : X \ Y ⊆ M.E :=
diff_subset.trans hX
@[aesop unsafe 10% (rule_sets := [Matroid])]
private theorem ground_diff_subset_ground : M.E \ X ⊆ M.E :=
diff_subset_ground rfl.subset
@[aesop unsafe 10% (rule_sets := [Matroid])]
private theorem singleton_subset_ground (he : e ∈ M.E) : {e} ⊆ M.E :=
singleton_subset_iff.mpr he
@[aesop unsafe 5% (rule_sets := [Matroid])]
private theorem subset_ground_of_subset (hXY : X ⊆ Y) (hY : Y ⊆ M.E) : X ⊆ M.E :=
hXY.trans hY
@[aesop unsafe 5% (rule_sets := [Matroid])]
private theorem mem_ground_of_mem_of_subset (hX : X ⊆ M.E) (heX : e ∈ X) : e ∈ M.E :=
hX heX
@[aesop safe (rule_sets := [Matroid])]
private theorem insert_subset_ground {e : α} {X : Set α} {M : Matroid α}
(he : e ∈ M.E) (hX : X ⊆ M.E) : insert e X ⊆ M.E :=
insert_subset he hX
@[aesop safe (rule_sets := [Matroid])]
private theorem ground_subset_ground {M : Matroid α} : M.E ⊆ M.E :=
rfl.subset
attribute [aesop safe (rule_sets := [Matroid])] empty_subset union_subset iUnion_subset
end aesop
section Base
@[aesop unsafe 10% (rule_sets := [Matroid])]
theorem Base.subset_ground (hB : M.Base B) : B ⊆ M.E :=
M.subset_ground B hB
theorem Base.exchange (hB₁ : M.Base B₁) (hB₂ : M.Base B₂) (hx : e ∈ B₁ \ B₂) :
∃ y ∈ B₂ \ B₁, M.Base (insert y (B₁ \ {e})) :=
M.base_exchange B₁ B₂ hB₁ hB₂ _ hx
theorem Base.exchange_mem (hB₁ : M.Base B₁) (hB₂ : M.Base B₂) (hxB₁ : e ∈ B₁) (hxB₂ : e ∉ B₂) :
∃ y, (y ∈ B₂ ∧ y ∉ B₁) ∧ M.Base (insert y (B₁ \ {e})) := by
simpa using hB₁.exchange hB₂ ⟨hxB₁, hxB₂⟩
theorem Base.eq_of_subset_base (hB₁ : M.Base B₁) (hB₂ : M.Base B₂) (hB₁B₂ : B₁ ⊆ B₂) :
B₁ = B₂ :=
M.base_exchange.antichain hB₁ hB₂ hB₁B₂
theorem Base.not_base_of_ssubset (hB : M.Base B) (hX : X ⊂ B) : ¬ M.Base X :=
fun h ↦ hX.ne (h.eq_of_subset_base hB hX.subset)
theorem Base.insert_not_base (hB : M.Base B) (heB : e ∉ B) : ¬ M.Base (insert e B) :=
fun h ↦ h.not_base_of_ssubset (ssubset_insert heB) hB
theorem Base.encard_diff_comm (hB₁ : M.Base B₁) (hB₂ : M.Base B₂) :
(B₁ \ B₂).encard = (B₂ \ B₁).encard :=
M.base_exchange.encard_diff_eq hB₁ hB₂
theorem Base.ncard_diff_comm (hB₁ : M.Base B₁) (hB₂ : M.Base B₂) :
(B₁ \ B₂).ncard = (B₂ \ B₁).ncard := by
rw [ncard_def, hB₁.encard_diff_comm hB₂, ← ncard_def]
theorem Base.card_eq_card_of_base (hB₁ : M.Base B₁) (hB₂ : M.Base B₂) :
B₁.encard = B₂.encard := by
rw [M.base_exchange.encard_base_eq hB₁ hB₂]
theorem Base.ncard_eq_ncard_of_base (hB₁ : M.Base B₁) (hB₂ : M.Base B₂) : B₁.ncard = B₂.ncard := by
rw [ncard_def B₁, hB₁.card_eq_card_of_base hB₂, ← ncard_def]
theorem Base.finite_of_finite (hB : M.Base B) (h : B.Finite) (hB' : M.Base B') : B'.Finite :=
(finite_iff_finite_of_encard_eq_encard (hB.card_eq_card_of_base hB')).mp h
theorem Base.infinite_of_infinite (hB : M.Base B) (h : B.Infinite) (hB₁ : M.Base B₁) :
B₁.Infinite :=
by_contra (fun hB_inf ↦ (hB₁.finite_of_finite (not_infinite.mp hB_inf) hB).not_infinite h)
theorem Base.finite [FiniteRk M] (hB : M.Base B) : B.Finite :=
let ⟨B₀,hB₀⟩ := ‹FiniteRk M›.exists_finite_base
hB₀.1.finite_of_finite hB₀.2 hB
theorem Base.infinite [InfiniteRk M] (hB : M.Base B) : B.Infinite :=
let ⟨B₀,hB₀⟩ := ‹InfiniteRk M›.exists_infinite_base
hB₀.1.infinite_of_infinite hB₀.2 hB
theorem empty_not_base [h : RkPos M] : ¬M.Base ∅ :=
h.empty_not_base
theorem Base.nonempty [RkPos M] (hB : M.Base B) : B.Nonempty := by
rw [nonempty_iff_ne_empty]; rintro rfl; exact M.empty_not_base hB
theorem Base.rkPos_of_nonempty (hB : M.Base B) (h : B.Nonempty) : M.RkPos := by
rw [rkPos_iff_empty_not_base]
intro he
obtain rfl := he.eq_of_subset_base hB (empty_subset B)
simp at h
theorem Base.finiteRk_of_finite (hB : M.Base B) (hfin : B.Finite) : FiniteRk M :=
⟨⟨B, hB, hfin⟩⟩
theorem Base.infiniteRk_of_infinite (hB : M.Base B) (h : B.Infinite) : InfiniteRk M :=
⟨⟨B, hB, h⟩⟩
theorem not_finiteRk (M : Matroid α) [InfiniteRk M] : ¬ FiniteRk M := by
intro h; obtain ⟨B,hB⟩ := M.exists_base; exact hB.infinite hB.finite
theorem not_infiniteRk (M : Matroid α) [FiniteRk M] : ¬ InfiniteRk M := by
intro h; obtain ⟨B,hB⟩ := M.exists_base; exact hB.infinite hB.finite
theorem finite_or_infiniteRk (M : Matroid α) : FiniteRk M ∨ InfiniteRk M :=
let ⟨B, hB⟩ := M.exists_base
B.finite_or_infinite.elim
(Or.inl ∘ hB.finiteRk_of_finite) (Or.inr ∘ hB.infiniteRk_of_infinite)
theorem Base.diff_finite_comm (hB₁ : M.Base B₁) (hB₂ : M.Base B₂) :
(B₁ \ B₂).Finite ↔ (B₂ \ B₁).Finite :=
finite_iff_finite_of_encard_eq_encard (hB₁.encard_diff_comm hB₂)
theorem Base.diff_infinite_comm (hB₁ : M.Base B₁) (hB₂ : M.Base B₂) :
(B₁ \ B₂).Infinite ↔ (B₂ \ B₁).Infinite :=
infinite_iff_infinite_of_encard_eq_encard (hB₁.encard_diff_comm hB₂)
theorem eq_of_base_iff_base_forall {M₁ M₂ : Matroid α} (hE : M₁.E = M₂.E)
(h : ∀ ⦃B⦄, B ⊆ M₁.E → (M₁.Base B ↔ M₂.Base B)) : M₁ = M₂ := by
have h' : ∀ B, M₁.Base B ↔ M₂.Base B :=
fun B ↦ ⟨fun hB ↦ (h hB.subset_ground).1 hB,
fun hB ↦ (h <| hB.subset_ground.trans_eq hE.symm).2 hB⟩
ext <;> simp [hE, M₁.indep_iff', M₂.indep_iff', h']
theorem base_compl_iff_mem_maximals_disjoint_base (hB : B ⊆ M.E := by aesop_mat) :
M.Base (M.E \ B) ↔ B ∈ maximals (· ⊆ ·) {I | I ⊆ M.E ∧ ∃ B, M.Base B ∧ Disjoint I B} := by
simp_rw [mem_maximals_setOf_iff, and_iff_right hB, and_imp, forall_exists_index]
refine ⟨fun h ↦ ⟨⟨_, h, disjoint_sdiff_right⟩,
fun I hI B' ⟨hB', hIB'⟩ hBI ↦ hBI.antisymm ?_⟩, fun ⟨⟨B', hB', hBB'⟩,h⟩ ↦ ?_⟩
· rw [hB'.eq_of_subset_base h, ← subset_compl_iff_disjoint_right, diff_eq, compl_inter,
compl_compl] at hIB'
· exact fun e he ↦ (hIB' he).elim (fun h' ↦ (h' (hI he)).elim) id
rw [subset_diff, and_iff_right hB'.subset_ground, disjoint_comm]
exact disjoint_of_subset_left hBI hIB'
rw [h diff_subset B' ⟨hB', disjoint_sdiff_left⟩]
· simpa [hB'.subset_ground]
simp [subset_diff, hB, hBB']
end Base
section dep_indep
/-- A subset of `M.E` is `Dep`endent if it is not `Indep`endent . -/
def Dep (M : Matroid α) (D : Set α) : Prop := ¬M.Indep D ∧ D ⊆ M.E
theorem indep_iff : M.Indep I ↔ ∃ B, M.Base B ∧ I ⊆ B :=
M.indep_iff' (I := I)
theorem setOf_indep_eq (M : Matroid α) : {I | M.Indep I} = lowerClosure ({B | M.Base B}) := by
simp_rw [indep_iff]
rfl
theorem Indep.exists_base_superset (hI : M.Indep I) : ∃ B, M.Base B ∧ I ⊆ B :=
indep_iff.1 hI
theorem dep_iff : M.Dep D ↔ ¬M.Indep D ∧ D ⊆ M.E := Iff.rfl
theorem setOf_dep_eq (M : Matroid α) : {D | M.Dep D} = {I | M.Indep I}ᶜ ∩ Iic M.E := rfl
@[aesop unsafe 30% (rule_sets := [Matroid])]
theorem Indep.subset_ground (hI : M.Indep I) : I ⊆ M.E := by
obtain ⟨B, hB, hIB⟩ := hI.exists_base_superset
exact hIB.trans hB.subset_ground
@[aesop unsafe 20% (rule_sets := [Matroid])]
theorem Dep.subset_ground (hD : M.Dep D) : D ⊆ M.E :=
hD.2
theorem indep_or_dep (hX : X ⊆ M.E := by aesop_mat) : M.Indep X ∨ M.Dep X := by
rw [Dep, and_iff_left hX]
apply em
theorem Indep.not_dep (hI : M.Indep I) : ¬ M.Dep I :=
fun h ↦ h.1 hI
theorem Dep.not_indep (hD : M.Dep D) : ¬ M.Indep D :=
hD.1
theorem dep_of_not_indep (hD : ¬ M.Indep D) (hDE : D ⊆ M.E := by aesop_mat) : M.Dep D :=
⟨hD, hDE⟩
theorem indep_of_not_dep (hI : ¬ M.Dep I) (hIE : I ⊆ M.E := by aesop_mat) : M.Indep I :=
by_contra (fun h ↦ hI ⟨h, hIE⟩)
@[simp] theorem not_dep_iff (hX : X ⊆ M.E := by aesop_mat) : ¬ M.Dep X ↔ M.Indep X := by
rw [Dep, and_iff_left hX, not_not]
@[simp] theorem not_indep_iff (hX : X ⊆ M.E := by aesop_mat) : ¬ M.Indep X ↔ M.Dep X := by
rw [Dep, and_iff_left hX]
theorem indep_iff_not_dep : M.Indep I ↔ ¬M.Dep I ∧ I ⊆ M.E := by
rw [dep_iff, not_and, not_imp_not]
exact ⟨fun h ↦ ⟨fun _ ↦ h, h.subset_ground⟩, fun h ↦ h.1 h.2⟩
theorem Indep.subset (hJ : M.Indep J) (hIJ : I ⊆ J) : M.Indep I := by
obtain ⟨B, hB, hJB⟩ := hJ.exists_base_superset
exact indep_iff.2 ⟨B, hB, hIJ.trans hJB⟩
theorem Dep.superset (hD : M.Dep D) (hDX : D ⊆ X) (hXE : X ⊆ M.E := by aesop_mat) : M.Dep X :=
dep_of_not_indep (fun hI ↦ (hI.subset hDX).not_dep hD)
theorem Base.indep (hB : M.Base B) : M.Indep B :=
indep_iff.2 ⟨B, hB, subset_rfl⟩
@[simp] theorem empty_indep (M : Matroid α) : M.Indep ∅ :=
Exists.elim M.exists_base (fun _ hB ↦ hB.indep.subset (empty_subset _))
theorem Dep.nonempty (hD : M.Dep D) : D.Nonempty := by
rw [nonempty_iff_ne_empty]; rintro rfl; exact hD.not_indep M.empty_indep
theorem Indep.finite [FiniteRk M] (hI : M.Indep I) : I.Finite :=
let ⟨_, hB, hIB⟩ := hI.exists_base_superset
hB.finite.subset hIB
theorem Indep.rkPos_of_nonempty (hI : M.Indep I) (hne : I.Nonempty) : M.RkPos := by
obtain ⟨B, hB, hIB⟩ := hI.exists_base_superset
exact hB.rkPos_of_nonempty (hne.mono hIB)
theorem Indep.inter_right (hI : M.Indep I) (X : Set α) : M.Indep (I ∩ X) :=
hI.subset inter_subset_left
theorem Indep.inter_left (hI : M.Indep I) (X : Set α) : M.Indep (X ∩ I) :=
hI.subset inter_subset_right
theorem Indep.diff (hI : M.Indep I) (X : Set α) : M.Indep (I \ X) :=
hI.subset diff_subset
theorem Base.eq_of_subset_indep (hB : M.Base B) (hI : M.Indep I) (hBI : B ⊆ I) : B = I :=
let ⟨B', hB', hB'I⟩ := hI.exists_base_superset
hBI.antisymm (by rwa [hB.eq_of_subset_base hB' (hBI.trans hB'I)])
theorem base_iff_maximal_indep : M.Base B ↔ M.Indep B ∧ ∀ I, M.Indep I → B ⊆ I → B = I := by
refine ⟨fun h ↦ ⟨h.indep, fun _ ↦ h.eq_of_subset_indep ⟩, fun ⟨h, h'⟩ ↦ ?_⟩
obtain ⟨B', hB', hBB'⟩ := h.exists_base_superset
rwa [h' _ hB'.indep hBB']
theorem setOf_base_eq_maximals_setOf_indep : {B | M.Base B} = maximals (· ⊆ ·) {I | M.Indep I} := by
ext B; rw [mem_maximals_setOf_iff, mem_setOf, base_iff_maximal_indep]
theorem Indep.base_of_maximal (hI : M.Indep I) (h : ∀ J, M.Indep J → I ⊆ J → I = J) : M.Base I :=
base_iff_maximal_indep.mpr ⟨hI,h⟩
theorem Base.dep_of_ssubset (hB : M.Base B) (h : B ⊂ X) (hX : X ⊆ M.E := by aesop_mat) : M.Dep X :=
⟨fun hX ↦ h.ne (hB.eq_of_subset_indep hX h.subset), hX⟩
theorem Base.dep_of_insert (hB : M.Base B) (heB : e ∉ B) (he : e ∈ M.E := by aesop_mat) :
M.Dep (insert e B) := hB.dep_of_ssubset (ssubset_insert heB) (insert_subset he hB.subset_ground)
theorem Base.mem_of_insert_indep (hB : M.Base B) (heB : M.Indep (insert e B)) : e ∈ B :=
by_contra fun he ↦ (hB.dep_of_insert he (heB.subset_ground (mem_insert _ _))).not_indep heB
/-- If the difference of two Bases is a singleton, then they differ by an insertion/removal -/
theorem Base.eq_exchange_of_diff_eq_singleton (hB : M.Base B) (hB' : M.Base B') (h : B \ B' = {e}) :
∃ f ∈ B' \ B, B' = (insert f B) \ {e} := by
obtain ⟨f, hf, hb⟩ := hB.exchange hB' (h.symm.subset (mem_singleton e))
have hne : f ≠ e := by rintro rfl; exact hf.2 (h.symm.subset (mem_singleton f)).1
rw [insert_diff_singleton_comm hne] at hb
refine ⟨f, hf, (hb.eq_of_subset_base hB' ?_).symm⟩
rw [diff_subset_iff, insert_subset_iff, union_comm, ← diff_subset_iff, h, and_iff_left rfl.subset]
exact Or.inl hf.1
theorem Base.exchange_base_of_indep (hB : M.Base B) (hf : f ∉ B)
(hI : M.Indep (insert f (B \ {e}))) : M.Base (insert f (B \ {e})) := by
obtain ⟨B', hB', hIB'⟩ := hI.exists_base_superset
have hcard := hB'.encard_diff_comm hB
rw [insert_subset_iff, ← diff_eq_empty, diff_diff_comm, diff_eq_empty, subset_singleton_iff_eq]
at hIB'
obtain ⟨hfB, (h | h)⟩ := hIB'
· rw [h, encard_empty, encard_eq_zero, eq_empty_iff_forall_not_mem] at hcard
exact (hcard f ⟨hfB, hf⟩).elim
rw [h, encard_singleton, encard_eq_one] at hcard
obtain ⟨x, hx⟩ := hcard
obtain (rfl : f = x) := hx.subset ⟨hfB, hf⟩
simp_rw [← h, ← singleton_union, ← hx, sdiff_sdiff_right_self, inf_eq_inter, inter_comm B,
diff_union_inter]
exact hB'
theorem Base.exchange_base_of_indep' (hB : M.Base B) (he : e ∈ B) (hf : f ∉ B)
(hI : M.Indep (insert f B \ {e})) : M.Base (insert f B \ {e}) := by
have hfe : f ≠ e := by rintro rfl; exact hf he
rw [← insert_diff_singleton_comm hfe] at *
exact hB.exchange_base_of_indep hf hI
theorem Base.insert_dep (hB : M.Base B) (h : e ∈ M.E \ B) : M.Dep (insert e B) := by
rw [← not_indep_iff (insert_subset h.1 hB.subset_ground)]
exact h.2 ∘ (fun hi ↦ insert_eq_self.mp (hB.eq_of_subset_indep hi (subset_insert e B)).symm)
theorem Indep.exists_insert_of_not_base (hI : M.Indep I) (hI' : ¬M.Base I) (hB : M.Base B) :
∃ e ∈ B \ I, M.Indep (insert e I) := by
obtain ⟨B', hB', hIB'⟩ := hI.exists_base_superset
obtain ⟨x, hxB', hx⟩ := exists_of_ssubset (hIB'.ssubset_of_ne (by (rintro rfl; exact hI' hB')))
obtain (hxB | hxB) := em (x ∈ B)
· exact ⟨x, ⟨hxB, hx⟩, hB'.indep.subset (insert_subset hxB' hIB') ⟩
obtain ⟨e,he, hBase⟩ := hB'.exchange hB ⟨hxB',hxB⟩
exact ⟨e, ⟨he.1, not_mem_subset hIB' he.2⟩,
indep_iff.2 ⟨_, hBase, insert_subset_insert (subset_diff_singleton hIB' hx)⟩⟩
/-- This is the same as `Indep.exists_insert_of_not_base`, but phrased so that
it is defeq to the augmentation axiom for independent sets. -/
theorem Indep.exists_insert_of_not_mem_maximals (M : Matroid α) ⦃I B : Set α⦄ (hI : M.Indep I)
(hInotmax : I ∉ maximals (· ⊆ ·) {I | M.Indep I}) (hB : B ∈ maximals (· ⊆ ·) {I | M.Indep I}) :
∃ x ∈ B \ I, M.Indep (insert x I) := by
simp only [mem_maximals_iff, mem_setOf_eq, not_and, not_forall, exists_prop,
exists_and_left, iff_true_intro hI, true_imp_iff] at hB hInotmax
refine hI.exists_insert_of_not_base (fun hIb ↦ ?_) ?_
· obtain ⟨I', hII', hI', hne⟩ := hInotmax
exact hne <| hIb.eq_of_subset_indep hII' hI'
exact hB.1.base_of_maximal fun J hJ hBJ ↦ hB.2 hJ hBJ
theorem ground_indep_iff_base : M.Indep M.E ↔ M.Base M.E :=
⟨fun h ↦ h.base_of_maximal (fun _ hJ hEJ ↦ hEJ.antisymm hJ.subset_ground), Base.indep⟩
theorem Base.exists_insert_of_ssubset (hB : M.Base B) (hIB : I ⊂ B) (hB' : M.Base B') :
∃ e ∈ B' \ I, M.Indep (insert e I) :=
(hB.indep.subset hIB.subset).exists_insert_of_not_base
(fun hI ↦ hIB.ne (hI.eq_of_subset_base hB hIB.subset)) hB'
theorem eq_of_indep_iff_indep_forall {M₁ M₂ : Matroid α} (hE : M₁.E = M₂.E)
(h : ∀ I, I ⊆ M₁.E → (M₁.Indep I ↔ M₂.Indep I)) : M₁ = M₂ :=
let h' : ∀ I, M₁.Indep I ↔ M₂.Indep I := fun I ↦
(em (I ⊆ M₁.E)).elim (h I) (fun h' ↦ iff_of_false (fun hi ↦ h' (hi.subset_ground))
(fun hi ↦ h' (hi.subset_ground.trans_eq hE.symm)))
eq_of_base_iff_base_forall hE (fun B _ ↦ by simp_rw [base_iff_maximal_indep, h'])
theorem eq_iff_indep_iff_indep_forall {M₁ M₂ : Matroid α} :
M₁ = M₂ ↔ (M₁.E = M₂.E) ∧ ∀ I, I ⊆ M₁.E → (M₁.Indep I ↔ M₂.Indep I) :=
⟨fun h ↦ by (subst h; simp), fun h ↦ eq_of_indep_iff_indep_forall h.1 h.2⟩
/-- A `Finitary` matroid is one where a set is independent if and only if it all
its finite subsets are independent, or equivalently a matroid whose circuits are finite. -/
class Finitary (M : Matroid α) : Prop where
/-- `I` is independent if all its finite subsets are independent. -/
indep_of_forall_finite : ∀ I, (∀ J, J ⊆ I → J.Finite → M.Indep J) → M.Indep I
theorem indep_of_forall_finite_subset_indep {M : Matroid α} [Finitary M] (I : Set α)
(h : ∀ J, J ⊆ I → J.Finite → M.Indep J) : M.Indep I :=
Finitary.indep_of_forall_finite I h
theorem indep_iff_forall_finite_subset_indep {M : Matroid α} [Finitary M] :
M.Indep I ↔ ∀ J, J ⊆ I → J.Finite → M.Indep J :=
⟨fun h _ hJI _ ↦ h.subset hJI, Finitary.indep_of_forall_finite I⟩
instance finitary_of_finiteRk {M : Matroid α} [FiniteRk M] : Finitary M :=
⟨ by
refine fun I hI ↦ I.finite_or_infinite.elim (hI _ Subset.rfl) (fun h ↦ False.elim ?_)
obtain ⟨B, hB⟩ := M.exists_base
obtain ⟨I₀, hI₀I, hI₀fin, hI₀card⟩ := h.exists_subset_ncard_eq (B.ncard + 1)
obtain ⟨B', hB', hI₀B'⟩ := (hI _ hI₀I hI₀fin).exists_base_superset
have hle := ncard_le_ncard hI₀B' hB'.finite
rw [hI₀card, hB'.ncard_eq_ncard_of_base hB, Nat.add_one_le_iff] at hle
exact hle.ne rfl ⟩
/-- Matroids obey the maximality axiom -/
theorem existsMaximalSubsetProperty_indep (M : Matroid α) :
∀ X, X ⊆ M.E → ExistsMaximalSubsetProperty M.Indep X :=
M.maximality
end dep_indep
section Basis
/-- A Basis for a set `X ⊆ M.E` is a maximal independent subset of `X`
(Often in the literature, the word 'Basis' is used to refer to what we call a 'Base'). -/
def Basis (M : Matroid α) (I X : Set α) : Prop :=
I ∈ maximals (· ⊆ ·) {A | M.Indep A ∧ A ⊆ X} ∧ X ⊆ M.E
/-- A `Basis'` is a basis without the requirement that `X ⊆ M.E`. This is convenient for some
API building, especially when working with rank and closure. -/
def Basis' (M : Matroid α) (I X : Set α) : Prop :=
I ∈ maximals (· ⊆ ·) {A | M.Indep A ∧ A ⊆ X}
theorem Basis'.indep (hI : M.Basis' I X) : M.Indep I :=
hI.1.1
theorem Basis.indep (hI : M.Basis I X) : M.Indep I :=
hI.1.1.1
theorem Basis.subset (hI : M.Basis I X) : I ⊆ X :=
hI.1.1.2
theorem Basis.basis' (hI : M.Basis I X) : M.Basis' I X :=
hI.1
theorem Basis'.basis (hI : M.Basis' I X) (hX : X ⊆ M.E := by aesop_mat) : M.Basis I X :=
⟨hI, hX⟩
theorem Basis'.subset (hI : M.Basis' I X) : I ⊆ X :=
hI.1.2
theorem setOf_basis_eq (M : Matroid α) (hX : X ⊆ M.E := by aesop_mat) :
{I | M.Basis I X} = maximals (· ⊆ ·) ({I | M.Indep I} ∩ Iic X) := by
ext I; simp [Matroid.Basis, maximals, iff_true_intro hX]
@[aesop unsafe 15% (rule_sets := [Matroid])]
theorem Basis.subset_ground (hI : M.Basis I X) : X ⊆ M.E :=
hI.2
theorem Basis.basis_inter_ground (hI : M.Basis I X) : M.Basis I (X ∩ M.E) := by
convert hI
rw [inter_eq_self_of_subset_left hI.subset_ground]
@[aesop unsafe 15% (rule_sets := [Matroid])]
theorem Basis.left_subset_ground (hI : M.Basis I X) : I ⊆ M.E :=
hI.indep.subset_ground
theorem Basis.eq_of_subset_indep (hI : M.Basis I X) (hJ : M.Indep J) (hIJ : I ⊆ J) (hJX : J ⊆ X) :
I = J :=
hIJ.antisymm (hI.1.2 ⟨hJ, hJX⟩ hIJ)
theorem Basis.Finite (hI : M.Basis I X) [FiniteRk M] : I.Finite := hI.indep.finite
theorem basis_iff' :
M.Basis I X ↔ (M.Indep I ∧ I ⊆ X ∧ ∀ J, M.Indep J → I ⊆ J → J ⊆ X → I = J) ∧ X ⊆ M.E := by
simp [Basis, mem_maximals_setOf_iff, and_assoc, and_congr_left_iff, and_imp,
and_congr_left_iff, and_congr_right_iff, @Imp.swap (_ ⊆ X)]
theorem basis_iff (hX : X ⊆ M.E := by aesop_mat) :
M.Basis I X ↔ (M.Indep I ∧ I ⊆ X ∧ ∀ J, M.Indep J → I ⊆ J → J ⊆ X → I = J) := by
rw [basis_iff', and_iff_left hX]
theorem basis'_iff_basis_inter_ground : M.Basis' I X ↔ M.Basis I (X ∩ M.E) := by
rw [Basis', Basis, and_iff_left inter_subset_right]
convert Iff.rfl using 3
ext I
simp only [subset_inter_iff, mem_setOf_eq, and_congr_right_iff, and_iff_left_iff_imp]
exact fun h _ ↦ h.subset_ground
theorem basis'_iff_basis (hX : X ⊆ M.E := by aesop_mat) : M.Basis' I X ↔ M.Basis I X := by
rw [basis'_iff_basis_inter_ground, inter_eq_self_of_subset_left hX]
theorem basis_iff_basis'_subset_ground : M.Basis I X ↔ M.Basis' I X ∧ X ⊆ M.E :=
⟨fun h ↦ ⟨h.basis', h.subset_ground⟩, fun h ↦ (basis'_iff_basis h.2).mp h.1⟩
theorem Basis'.basis_inter_ground (hIX : M.Basis' I X) : M.Basis I (X ∩ M.E) :=
basis'_iff_basis_inter_ground.mp hIX
theorem Basis'.eq_of_subset_indep (hI : M.Basis' I X) (hJ : M.Indep J) (hIJ : I ⊆ J)
(hJX : J ⊆ X) : I = J :=
hIJ.antisymm (hI.2 ⟨hJ, hJX⟩ hIJ)
theorem Basis'.insert_not_indep (hI : M.Basis' I X) (he : e ∈ X \ I) : ¬ M.Indep (insert e I) :=
fun hi ↦ he.2 <| insert_eq_self.1 <| Eq.symm <|
hI.eq_of_subset_indep hi (subset_insert _ _) (insert_subset he.1 hI.subset)
theorem basis_iff_mem_maximals (hX : X ⊆ M.E := by aesop_mat):
M.Basis I X ↔ I ∈ maximals (· ⊆ ·) {I | M.Indep I ∧ I ⊆ X} := by
rw [Basis, and_iff_left hX]
theorem basis_iff_mem_maximals_Prop (hX : X ⊆ M.E := by aesop_mat):
M.Basis I X ↔ I ∈ maximals (· ⊆ ·) (fun I ↦ M.Indep I ∧ I ⊆ X) :=
basis_iff_mem_maximals
theorem Indep.basis_of_maximal_subset (hI : M.Indep I) (hIX : I ⊆ X)
(hmax : ∀ ⦃J⦄, M.Indep J → I ⊆ J → J ⊆ X → J ⊆ I) (hX : X ⊆ M.E := by aesop_mat) :
M.Basis I X := by
rw [basis_iff (by aesop_mat : X ⊆ M.E), and_iff_right hI, and_iff_right hIX]
exact fun J hJ hIJ hJX ↦ hIJ.antisymm (hmax hJ hIJ hJX)
theorem Basis.basis_subset (hI : M.Basis I X) (hIY : I ⊆ Y) (hYX : Y ⊆ X) : M.Basis I Y := by
rw [basis_iff (hYX.trans hI.subset_ground), and_iff_right hI.indep, and_iff_right hIY]
exact fun J hJ hIJ hJY ↦ hI.eq_of_subset_indep hJ hIJ (hJY.trans hYX)
@[simp] theorem basis_self_iff_indep : M.Basis I I ↔ M.Indep I := by
rw [basis_iff', and_iff_right rfl.subset, and_assoc, and_iff_left_iff_imp]
exact fun hi ↦ ⟨fun _ _ ↦ subset_antisymm, hi.subset_ground⟩
theorem Indep.basis_self (h : M.Indep I) : M.Basis I I :=
basis_self_iff_indep.mpr h
@[simp] theorem basis_empty_iff (M : Matroid α) : M.Basis I ∅ ↔ I = ∅ :=
⟨fun h ↦ subset_empty_iff.mp h.subset, fun h ↦ by (rw [h]; exact M.empty_indep.basis_self)⟩
theorem Basis.dep_of_ssubset (hI : M.Basis I X) (hIY : I ⊂ Y) (hYX : Y ⊆ X) : M.Dep Y := by
have : X ⊆ M.E := hI.subset_ground
rw [← not_indep_iff]
exact fun hY ↦ hIY.ne (hI.eq_of_subset_indep hY hIY.subset hYX)
theorem Basis.insert_dep (hI : M.Basis I X) (he : e ∈ X \ I) : M.Dep (insert e I) :=
hI.dep_of_ssubset (ssubset_insert he.2) (insert_subset he.1 hI.subset)
theorem Basis.mem_of_insert_indep (hI : M.Basis I X) (he : e ∈ X) (hIe : M.Indep (insert e I)) :
e ∈ I :=
by_contra (fun heI ↦ (hI.insert_dep ⟨he, heI⟩).not_indep hIe)
theorem Basis'.mem_of_insert_indep (hI : M.Basis' I X) (he : e ∈ X) (hIe : M.Indep (insert e I)) :
e ∈ I :=
hI.basis_inter_ground.mem_of_insert_indep ⟨he, hIe.subset_ground (mem_insert _ _)⟩ hIe
theorem Basis.not_basis_of_ssubset (hI : M.Basis I X) (hJI : J ⊂ I) : ¬ M.Basis J X :=
fun h ↦ hJI.ne (h.eq_of_subset_indep hI.indep hJI.subset hI.subset)
theorem Indep.subset_basis_of_subset (hI : M.Indep I) (hIX : I ⊆ X) (hX : X ⊆ M.E := by aesop_mat) :
∃ J, M.Basis J X ∧ I ⊆ J := by
obtain ⟨J, ⟨(hJ : M.Indep J),hIJ,hJX⟩, hJmax⟩ := M.maximality X hX I hI hIX
use J
rw [and_iff_left hIJ, basis_iff, and_iff_right hJ, and_iff_right hJX]
exact fun K hK hJK hKX ↦ hJK.antisymm (hJmax ⟨hK, hIJ.trans hJK, hKX⟩ hJK)
theorem Indep.subset_basis'_of_subset (hI : M.Indep I) (hIX : I ⊆ X) :
∃ J, M.Basis' J X ∧ I ⊆ J := by
simp_rw [basis'_iff_basis_inter_ground]
exact hI.subset_basis_of_subset (subset_inter hIX hI.subset_ground)
theorem exists_basis (M : Matroid α) (X : Set α) (hX : X ⊆ M.E := by aesop_mat) :
∃ I, M.Basis I X :=
let ⟨_, hI, _⟩ := M.empty_indep.subset_basis_of_subset (empty_subset X)
⟨_,hI⟩
theorem exists_basis' (M : Matroid α) (X : Set α) : ∃ I, M.Basis' I X :=
let ⟨_, hI, _⟩ := M.empty_indep.subset_basis'_of_subset (empty_subset X)
⟨_,hI⟩
theorem exists_basis_subset_basis (M : Matroid α) (hXY : X ⊆ Y) (hY : Y ⊆ M.E := by aesop_mat) :
∃ I J, M.Basis I X ∧ M.Basis J Y ∧ I ⊆ J := by
obtain ⟨I, hI⟩ := M.exists_basis X (hXY.trans hY)
obtain ⟨J, hJ, hIJ⟩ := hI.indep.subset_basis_of_subset (hI.subset.trans hXY)
exact ⟨_, _, hI, hJ, hIJ⟩
theorem Basis.exists_basis_inter_eq_of_superset (hI : M.Basis I X) (hXY : X ⊆ Y)
(hY : Y ⊆ M.E := by aesop_mat) : ∃ J, M.Basis J Y ∧ J ∩ X = I := by
obtain ⟨J, hJ, hIJ⟩ := hI.indep.subset_basis_of_subset (hI.subset.trans hXY)
refine ⟨J, hJ, subset_antisymm ?_ (subset_inter hIJ hI.subset)⟩
exact fun e he ↦ hI.mem_of_insert_indep he.2 (hJ.indep.subset (insert_subset he.1 hIJ))
theorem exists_basis_union_inter_basis (M : Matroid α) (X Y : Set α) (hX : X ⊆ M.E := by aesop_mat)
(hY : Y ⊆ M.E := by aesop_mat) : ∃ I, M.Basis I (X ∪ Y) ∧ M.Basis (I ∩ Y) Y :=
let ⟨J, hJ⟩ := M.exists_basis Y
(hJ.exists_basis_inter_eq_of_superset subset_union_right).imp
(fun I hI ↦ ⟨hI.1, by rwa [hI.2]⟩)
theorem Indep.eq_of_basis (hI : M.Indep I) (hJ : M.Basis J I) : J = I :=
hJ.eq_of_subset_indep hI hJ.subset rfl.subset
theorem Basis.exists_base (hI : M.Basis I X) : ∃ B, M.Base B ∧ I = B ∩ X :=
let ⟨B,hB, hIB⟩ := hI.indep.exists_base_superset
⟨B, hB, subset_antisymm (subset_inter hIB hI.subset)
(by rw [hI.eq_of_subset_indep (hB.indep.inter_right X) (subset_inter hIB hI.subset)
inter_subset_right])⟩
@[simp] theorem basis_ground_iff : M.Basis B M.E ↔ M.Base B := by
rw [base_iff_maximal_indep, basis_iff', and_assoc, and_congr_right]
rw [and_iff_left (rfl.subset : M.E ⊆ M.E)]
exact fun h ↦ ⟨fun h' I hI hBI ↦ h'.2 _ hI hBI hI.subset_ground,
fun h' ↦ ⟨h.subset_ground,fun J hJ hBJ _ ↦ h' J hJ hBJ⟩⟩
theorem Base.basis_ground (hB : M.Base B) : M.Basis B M.E :=
basis_ground_iff.mpr hB
theorem Indep.basis_iff_forall_insert_dep (hI : M.Indep I) (hIX : I ⊆ X) :
M.Basis I X ↔ ∀ e ∈ X \ I, M.Dep (insert e I) := by
rw [basis_iff', and_iff_right hIX, and_iff_right hI]
refine ⟨fun h e he ↦ ⟨fun hi ↦ he.2 ?_, insert_subset (h.2 he.1) hI.subset_ground⟩,
fun h ↦ ⟨fun J hJ hIJ hJX ↦ hIJ.antisymm (fun e heJ ↦ by_contra (fun heI ↦ ?_)), ?_⟩⟩
· exact (h.1 _ hi (subset_insert _ _) (insert_subset he.1 hIX)).symm.subset (mem_insert e I)
· exact (h e ⟨hJX heJ, heI⟩).not_indep (hJ.subset (insert_subset heJ hIJ))
rw [← diff_union_of_subset hIX, union_subset_iff, and_iff_left hI.subset_ground]
exact fun e he ↦ (h e he).subset_ground (mem_insert _ _)
theorem Indep.basis_of_forall_insert (hI : M.Indep I) (hIX : I ⊆ X)
(he : ∀ e ∈ X \ I, M.Dep (insert e I)) : M.Basis I X :=
(hI.basis_iff_forall_insert_dep hIX).mpr he
theorem Indep.basis_insert_iff (hI : M.Indep I) :
M.Basis I (insert e I) ↔ M.Dep (insert e I) ∨ e ∈ I := by
simp_rw [hI.basis_iff_forall_insert_dep (subset_insert _ _), dep_iff, insert_subset_iff,
and_iff_left hI.subset_ground, mem_diff, mem_insert_iff, or_and_right, and_not_self,
or_false, and_imp, forall_eq]
tauto
theorem Basis.iUnion_basis_iUnion {ι : Type _} (X I : ι → Set α) (hI : ∀ i, M.Basis (I i) (X i))
(h_ind : M.Indep (⋃ i, I i)) : M.Basis (⋃ i, I i) (⋃ i, X i) := by
refine h_ind.basis_of_forall_insert
(iUnion_subset (fun i ↦ (hI i).subset.trans (subset_iUnion _ _))) ?_
rintro e ⟨⟨_, ⟨⟨i, hi, rfl⟩, (hes : e ∈ X i)⟩⟩, he'⟩
rw [mem_iUnion, not_exists] at he'
refine ((hI i).insert_dep ⟨hes, he' _⟩).superset (insert_subset_insert (subset_iUnion _ _)) ?_
rw [insert_subset_iff, iUnion_subset_iff, and_iff_left (fun i ↦ (hI i).indep.subset_ground)]
exact (hI i).subset_ground hes
theorem Basis.basis_iUnion {ι : Type _} [Nonempty ι] (X : ι → Set α)
(hI : ∀ i, M.Basis I (X i)) : M.Basis I (⋃ i, X i) := by
convert Basis.iUnion_basis_iUnion X (fun _ ↦ I) (fun i ↦ hI i) _ <;> rw [iUnion_const]
exact (hI (Classical.arbitrary ι)).indep
theorem Basis.basis_sUnion {Xs : Set (Set α)} (hne : Xs.Nonempty) (h : ∀ X ∈ Xs, M.Basis I X) :
M.Basis I (⋃₀ Xs) := by
rw [sUnion_eq_iUnion]
have := Iff.mpr nonempty_coe_sort hne
exact Basis.basis_iUnion _ fun X ↦ (h X X.prop)
theorem Indep.basis_setOf_insert_basis (hI : M.Indep I) :
M.Basis I {x | M.Basis I (insert x I)} := by
refine hI.basis_of_forall_insert (fun e he ↦ (?_ : M.Basis _ _))
(fun e he ↦ ⟨fun hu ↦ he.2 ?_, he.1.subset_ground⟩)
· rw [insert_eq_of_mem he]; exact hI.basis_self
simpa using (hu.eq_of_basis he.1).symm
| Mathlib/Data/Matroid/Basic.lean | 925 | 930 | theorem Basis.union_basis_union (hIX : M.Basis I X) (hJY : M.Basis J Y) (h : M.Indep (I ∪ J)) :
M.Basis (I ∪ J) (X ∪ Y) := by |
rw [union_eq_iUnion, union_eq_iUnion]
refine Basis.iUnion_basis_iUnion _ _ ?_ ?_
· simp only [Bool.forall_bool, cond_false, cond_true]; exact ⟨hJY, hIX⟩
rwa [← union_eq_iUnion]
|
/-
Copyright (c) 2020 Anne Baanen. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Anne Baanen, Filippo A. E. Nuccio
-/
import Mathlib.RingTheory.IntegralClosure
import Mathlib.RingTheory.FractionalIdeal.Basic
#align_import ring_theory.fractional_ideal from "leanprover-community/mathlib"@"ed90a7d327c3a5caf65a6faf7e8a0d63c4605df7"
/-!
# More operations on fractional ideals
## Main definitions
* `map` is the pushforward of a fractional ideal along an algebra morphism
Let `K` be the localization of `R` at `R⁰ = R \ {0}` (i.e. the field of fractions).
* `FractionalIdeal R⁰ K` is the type of fractional ideals in the field of fractions
* `Div (FractionalIdeal R⁰ K)` instance:
the ideal quotient `I / J` (typically written $I : J$, but a `:` operator cannot be defined)
## Main statement
* `isNoetherian` states that every fractional ideal of a noetherian integral domain is noetherian
## References
* https://en.wikipedia.org/wiki/Fractional_ideal
## Tags
fractional ideal, fractional ideals, invertible ideal
-/
open IsLocalization Pointwise nonZeroDivisors
namespace FractionalIdeal
open Set Submodule
variable {R : Type*} [CommRing R] {S : Submonoid R} {P : Type*} [CommRing P]
variable [Algebra R P] [loc : IsLocalization S P]
section
variable {P' : Type*} [CommRing P'] [Algebra R P'] [loc' : IsLocalization S P']
variable {P'' : Type*} [CommRing P''] [Algebra R P''] [loc'' : IsLocalization S P'']
theorem _root_.IsFractional.map (g : P →ₐ[R] P') {I : Submodule R P} :
IsFractional S I → IsFractional S (Submodule.map g.toLinearMap I)
| ⟨a, a_nonzero, hI⟩ =>
⟨a, a_nonzero, fun b hb => by
obtain ⟨b', b'_mem, hb'⟩ := Submodule.mem_map.mp hb
rw [AlgHom.toLinearMap_apply] at hb'
obtain ⟨x, hx⟩ := hI b' b'_mem
use x
rw [← g.commutes, hx, g.map_smul, hb']⟩
#align is_fractional.map IsFractional.map
/-- `I.map g` is the pushforward of the fractional ideal `I` along the algebra morphism `g` -/
def map (g : P →ₐ[R] P') : FractionalIdeal S P → FractionalIdeal S P' := fun I =>
⟨Submodule.map g.toLinearMap I, I.isFractional.map g⟩
#align fractional_ideal.map FractionalIdeal.map
@[simp, norm_cast]
theorem coe_map (g : P →ₐ[R] P') (I : FractionalIdeal S P) :
↑(map g I) = Submodule.map g.toLinearMap I :=
rfl
#align fractional_ideal.coe_map FractionalIdeal.coe_map
@[simp]
theorem mem_map {I : FractionalIdeal S P} {g : P →ₐ[R] P'} {y : P'} :
y ∈ I.map g ↔ ∃ x, x ∈ I ∧ g x = y :=
Submodule.mem_map
#align fractional_ideal.mem_map FractionalIdeal.mem_map
variable (I J : FractionalIdeal S P) (g : P →ₐ[R] P')
@[simp]
theorem map_id : I.map (AlgHom.id _ _) = I :=
coeToSubmodule_injective (Submodule.map_id (I : Submodule R P))
#align fractional_ideal.map_id FractionalIdeal.map_id
@[simp]
theorem map_comp (g' : P' →ₐ[R] P'') : I.map (g'.comp g) = (I.map g).map g' :=
coeToSubmodule_injective (Submodule.map_comp g.toLinearMap g'.toLinearMap I)
#align fractional_ideal.map_comp FractionalIdeal.map_comp
@[simp, norm_cast]
theorem map_coeIdeal (I : Ideal R) : (I : FractionalIdeal S P).map g = I := by
ext x
simp only [mem_coeIdeal]
constructor
· rintro ⟨_, ⟨y, hy, rfl⟩, rfl⟩
exact ⟨y, hy, (g.commutes y).symm⟩
· rintro ⟨y, hy, rfl⟩
exact ⟨_, ⟨y, hy, rfl⟩, g.commutes y⟩
#align fractional_ideal.map_coe_ideal FractionalIdeal.map_coeIdeal
@[simp]
theorem map_one : (1 : FractionalIdeal S P).map g = 1 :=
map_coeIdeal g ⊤
#align fractional_ideal.map_one FractionalIdeal.map_one
@[simp]
theorem map_zero : (0 : FractionalIdeal S P).map g = 0 :=
map_coeIdeal g 0
#align fractional_ideal.map_zero FractionalIdeal.map_zero
@[simp]
theorem map_add : (I + J).map g = I.map g + J.map g :=
coeToSubmodule_injective (Submodule.map_sup _ _ _)
#align fractional_ideal.map_add FractionalIdeal.map_add
@[simp]
theorem map_mul : (I * J).map g = I.map g * J.map g := by
simp only [mul_def]
exact coeToSubmodule_injective (Submodule.map_mul _ _ _)
#align fractional_ideal.map_mul FractionalIdeal.map_mul
@[simp]
theorem map_map_symm (g : P ≃ₐ[R] P') : (I.map (g : P →ₐ[R] P')).map (g.symm : P' →ₐ[R] P) = I := by
rw [← map_comp, g.symm_comp, map_id]
#align fractional_ideal.map_map_symm FractionalIdeal.map_map_symm
@[simp]
theorem map_symm_map (I : FractionalIdeal S P') (g : P ≃ₐ[R] P') :
(I.map (g.symm : P' →ₐ[R] P)).map (g : P →ₐ[R] P') = I := by
rw [← map_comp, g.comp_symm, map_id]
#align fractional_ideal.map_symm_map FractionalIdeal.map_symm_map
theorem map_mem_map {f : P →ₐ[R] P'} (h : Function.Injective f) {x : P} {I : FractionalIdeal S P} :
f x ∈ map f I ↔ x ∈ I :=
mem_map.trans ⟨fun ⟨_, hx', x'_eq⟩ => h x'_eq ▸ hx', fun h => ⟨x, h, rfl⟩⟩
#align fractional_ideal.map_mem_map FractionalIdeal.map_mem_map
theorem map_injective (f : P →ₐ[R] P') (h : Function.Injective f) :
Function.Injective (map f : FractionalIdeal S P → FractionalIdeal S P') := fun _ _ hIJ =>
ext fun _ => (map_mem_map h).symm.trans (hIJ.symm ▸ map_mem_map h)
#align fractional_ideal.map_injective FractionalIdeal.map_injective
/-- If `g` is an equivalence, `map g` is an isomorphism -/
def mapEquiv (g : P ≃ₐ[R] P') : FractionalIdeal S P ≃+* FractionalIdeal S P' where
toFun := map g
invFun := map g.symm
map_add' I J := map_add I J _
map_mul' I J := map_mul I J _
left_inv I := by rw [← map_comp, AlgEquiv.symm_comp, map_id]
right_inv I := by rw [← map_comp, AlgEquiv.comp_symm, map_id]
#align fractional_ideal.map_equiv FractionalIdeal.mapEquiv
@[simp]
theorem coeFun_mapEquiv (g : P ≃ₐ[R] P') :
(mapEquiv g : FractionalIdeal S P → FractionalIdeal S P') = map g :=
rfl
#align fractional_ideal.coe_fun_map_equiv FractionalIdeal.coeFun_mapEquiv
@[simp]
theorem mapEquiv_apply (g : P ≃ₐ[R] P') (I : FractionalIdeal S P) : mapEquiv g I = map (↑g) I :=
rfl
#align fractional_ideal.map_equiv_apply FractionalIdeal.mapEquiv_apply
@[simp]
theorem mapEquiv_symm (g : P ≃ₐ[R] P') :
((mapEquiv g).symm : FractionalIdeal S P' ≃+* _) = mapEquiv g.symm :=
rfl
#align fractional_ideal.map_equiv_symm FractionalIdeal.mapEquiv_symm
@[simp]
theorem mapEquiv_refl : mapEquiv AlgEquiv.refl = RingEquiv.refl (FractionalIdeal S P) :=
RingEquiv.ext fun x => by simp
#align fractional_ideal.map_equiv_refl FractionalIdeal.mapEquiv_refl
theorem isFractional_span_iff {s : Set P} :
IsFractional S (span R s) ↔ ∃ a ∈ S, ∀ b : P, b ∈ s → IsInteger R (a • b) :=
⟨fun ⟨a, a_mem, h⟩ => ⟨a, a_mem, fun b hb => h b (subset_span hb)⟩, fun ⟨a, a_mem, h⟩ =>
⟨a, a_mem, fun b hb =>
span_induction hb h
(by
rw [smul_zero]
exact isInteger_zero)
(fun x y hx hy => by
rw [smul_add]
exact isInteger_add hx hy)
fun s x hx => by
rw [smul_comm]
exact isInteger_smul hx⟩⟩
#align fractional_ideal.is_fractional_span_iff FractionalIdeal.isFractional_span_iff
theorem isFractional_of_fg {I : Submodule R P} (hI : I.FG) : IsFractional S I := by
rcases hI with ⟨I, rfl⟩
rcases exist_integer_multiples_of_finset S I with ⟨⟨s, hs1⟩, hs⟩
rw [isFractional_span_iff]
exact ⟨s, hs1, hs⟩
#align fractional_ideal.is_fractional_of_fg FractionalIdeal.isFractional_of_fg
theorem mem_span_mul_finite_of_mem_mul {I J : FractionalIdeal S P} {x : P} (hx : x ∈ I * J) :
∃ T T' : Finset P, (T : Set P) ⊆ I ∧ (T' : Set P) ⊆ J ∧ x ∈ span R (T * T' : Set P) :=
Submodule.mem_span_mul_finite_of_mem_mul (by simpa using mem_coe.mpr hx)
#align fractional_ideal.mem_span_mul_finite_of_mem_mul FractionalIdeal.mem_span_mul_finite_of_mem_mul
variable (S)
theorem coeIdeal_fg (inj : Function.Injective (algebraMap R P)) (I : Ideal R) :
FG ((I : FractionalIdeal S P) : Submodule R P) ↔ I.FG :=
coeSubmodule_fg _ inj _
#align fractional_ideal.coe_ideal_fg FractionalIdeal.coeIdeal_fg
variable {S}
theorem fg_unit (I : (FractionalIdeal S P)ˣ) : FG (I : Submodule R P) :=
Submodule.fg_unit <| Units.map (coeSubmoduleHom S P).toMonoidHom I
#align fractional_ideal.fg_unit FractionalIdeal.fg_unit
theorem fg_of_isUnit (I : FractionalIdeal S P) (h : IsUnit I) : FG (I : Submodule R P) :=
fg_unit h.unit
#align fractional_ideal.fg_of_is_unit FractionalIdeal.fg_of_isUnit
theorem _root_.Ideal.fg_of_isUnit (inj : Function.Injective (algebraMap R P)) (I : Ideal R)
(h : IsUnit (I : FractionalIdeal S P)) : I.FG := by
rw [← coeIdeal_fg S inj I]
exact FractionalIdeal.fg_of_isUnit I h
#align ideal.fg_of_is_unit Ideal.fg_of_isUnit
variable (S P P')
/-- `canonicalEquiv f f'` is the canonical equivalence between the fractional
ideals in `P` and in `P'`, which are both localizations of `R` at `S`. -/
noncomputable irreducible_def canonicalEquiv : FractionalIdeal S P ≃+* FractionalIdeal S P' :=
mapEquiv
{ ringEquivOfRingEquiv P P' (RingEquiv.refl R)
(show S.map _ = S by rw [RingEquiv.toMonoidHom_refl, Submonoid.map_id]) with
commutes' := fun r => ringEquivOfRingEquiv_eq _ _ }
#align fractional_ideal.canonical_equiv FractionalIdeal.canonicalEquiv
@[simp]
theorem mem_canonicalEquiv_apply {I : FractionalIdeal S P} {x : P'} :
x ∈ canonicalEquiv S P P' I ↔
∃ y ∈ I,
IsLocalization.map P' (RingHom.id R) (fun y (hy : y ∈ S) => show RingHom.id R y ∈ S from hy)
(y : P) =
x := by
rw [canonicalEquiv, mapEquiv_apply, mem_map]
exact ⟨fun ⟨y, mem, Eq⟩ => ⟨y, mem, Eq⟩, fun ⟨y, mem, Eq⟩ => ⟨y, mem, Eq⟩⟩
#align fractional_ideal.mem_canonical_equiv_apply FractionalIdeal.mem_canonicalEquiv_apply
@[simp]
theorem canonicalEquiv_symm : (canonicalEquiv S P P').symm = canonicalEquiv S P' P :=
RingEquiv.ext fun I =>
SetLike.ext_iff.mpr fun x => by
rw [mem_canonicalEquiv_apply, canonicalEquiv, mapEquiv_symm, mapEquiv_apply,
mem_map]
exact ⟨fun ⟨y, mem, Eq⟩ => ⟨y, mem, Eq⟩, fun ⟨y, mem, Eq⟩ => ⟨y, mem, Eq⟩⟩
#align fractional_ideal.canonical_equiv_symm FractionalIdeal.canonicalEquiv_symm
theorem canonicalEquiv_flip (I) : canonicalEquiv S P P' (canonicalEquiv S P' P I) = I := by
rw [← canonicalEquiv_symm]; erw [RingEquiv.apply_symm_apply]
#align fractional_ideal.canonical_equiv_flip FractionalIdeal.canonicalEquiv_flip
@[simp]
theorem canonicalEquiv_canonicalEquiv (P'' : Type*) [CommRing P''] [Algebra R P'']
[IsLocalization S P''] (I : FractionalIdeal S P) :
canonicalEquiv S P' P'' (canonicalEquiv S P P' I) = canonicalEquiv S P P'' I := by
ext
simp only [IsLocalization.map_map, RingHomInvPair.comp_eq₂, mem_canonicalEquiv_apply,
exists_prop, exists_exists_and_eq_and]
#align fractional_ideal.canonical_equiv_canonical_equiv FractionalIdeal.canonicalEquiv_canonicalEquiv
theorem canonicalEquiv_trans_canonicalEquiv (P'' : Type*) [CommRing P''] [Algebra R P'']
[IsLocalization S P''] :
(canonicalEquiv S P P').trans (canonicalEquiv S P' P'') = canonicalEquiv S P P'' :=
RingEquiv.ext (canonicalEquiv_canonicalEquiv S P P' P'')
#align fractional_ideal.canonical_equiv_trans_canonical_equiv FractionalIdeal.canonicalEquiv_trans_canonicalEquiv
@[simp]
theorem canonicalEquiv_coeIdeal (I : Ideal R) : canonicalEquiv S P P' I = I := by
ext
simp [IsLocalization.map_eq]
#align fractional_ideal.canonical_equiv_coe_ideal FractionalIdeal.canonicalEquiv_coeIdeal
@[simp]
theorem canonicalEquiv_self : canonicalEquiv S P P = RingEquiv.refl _ := by
rw [← canonicalEquiv_trans_canonicalEquiv S P P]
convert (canonicalEquiv S P P).symm_trans_self
exact (canonicalEquiv_symm S P P).symm
#align fractional_ideal.canonical_equiv_self FractionalIdeal.canonicalEquiv_self
end
section IsFractionRing
/-!
### `IsFractionRing` section
This section concerns fractional ideals in the field of fractions,
i.e. the type `FractionalIdeal R⁰ K` where `IsFractionRing R K`.
-/
variable {K K' : Type*} [Field K] [Field K']
variable [Algebra R K] [IsFractionRing R K] [Algebra R K'] [IsFractionRing R K']
variable {I J : FractionalIdeal R⁰ K} (h : K →ₐ[R] K')
/-- Nonzero fractional ideals contain a nonzero integer. -/
theorem exists_ne_zero_mem_isInteger [Nontrivial R] (hI : I ≠ 0) :
∃ x, x ≠ 0 ∧ algebraMap R K x ∈ I := by
obtain ⟨y : K, y_mem, y_not_mem⟩ :=
SetLike.exists_of_lt (by simpa only using bot_lt_iff_ne_bot.mpr hI)
have y_ne_zero : y ≠ 0 := by simpa using y_not_mem
obtain ⟨z, ⟨x, hx⟩⟩ := exists_integer_multiple R⁰ y
refine ⟨x, ?_, ?_⟩
· rw [Ne, ← @IsFractionRing.to_map_eq_zero_iff R _ K, hx, Algebra.smul_def]
exact mul_ne_zero (IsFractionRing.to_map_ne_zero_of_mem_nonZeroDivisors z.2) y_ne_zero
· rw [hx]
exact smul_mem _ _ y_mem
#align fractional_ideal.exists_ne_zero_mem_is_integer FractionalIdeal.exists_ne_zero_mem_isInteger
theorem map_ne_zero [Nontrivial R] (hI : I ≠ 0) : I.map h ≠ 0 := by
obtain ⟨x, x_ne_zero, hx⟩ := exists_ne_zero_mem_isInteger hI
contrapose! x_ne_zero with map_eq_zero
refine IsFractionRing.to_map_eq_zero_iff.mp (eq_zero_iff.mp map_eq_zero _ (mem_map.mpr ?_))
exact ⟨algebraMap R K x, hx, h.commutes x⟩
#align fractional_ideal.map_ne_zero FractionalIdeal.map_ne_zero
@[simp]
theorem map_eq_zero_iff [Nontrivial R] : I.map h = 0 ↔ I = 0 :=
⟨not_imp_not.mp (map_ne_zero _), fun hI => hI.symm ▸ map_zero h⟩
#align fractional_ideal.map_eq_zero_iff FractionalIdeal.map_eq_zero_iff
theorem coeIdeal_injective : Function.Injective (fun (I : Ideal R) ↦ (I : FractionalIdeal R⁰ K)) :=
coeIdeal_injective' le_rfl
#align fractional_ideal.coe_ideal_injective FractionalIdeal.coeIdeal_injective
theorem coeIdeal_inj {I J : Ideal R} :
(I : FractionalIdeal R⁰ K) = (J : FractionalIdeal R⁰ K) ↔ I = J :=
coeIdeal_inj' le_rfl
#align fractional_ideal.coe_ideal_inj FractionalIdeal.coeIdeal_inj
@[simp]
theorem coeIdeal_eq_zero {I : Ideal R} : (I : FractionalIdeal R⁰ K) = 0 ↔ I = ⊥ :=
coeIdeal_eq_zero' le_rfl
#align fractional_ideal.coe_ideal_eq_zero FractionalIdeal.coeIdeal_eq_zero
theorem coeIdeal_ne_zero {I : Ideal R} : (I : FractionalIdeal R⁰ K) ≠ 0 ↔ I ≠ ⊥ :=
coeIdeal_ne_zero' le_rfl
#align fractional_ideal.coe_ideal_ne_zero FractionalIdeal.coeIdeal_ne_zero
@[simp]
theorem coeIdeal_eq_one {I : Ideal R} : (I : FractionalIdeal R⁰ K) = 1 ↔ I = 1 := by
simpa only [Ideal.one_eq_top] using coeIdeal_inj
#align fractional_ideal.coe_ideal_eq_one FractionalIdeal.coeIdeal_eq_one
theorem coeIdeal_ne_one {I : Ideal R} : (I : FractionalIdeal R⁰ K) ≠ 1 ↔ I ≠ 1 :=
not_iff_not.mpr coeIdeal_eq_one
#align fractional_ideal.coe_ideal_ne_one FractionalIdeal.coeIdeal_ne_one
theorem num_eq_zero_iff [Nontrivial R] {I : FractionalIdeal R⁰ K} : I.num = 0 ↔ I = 0 :=
⟨fun h ↦ zero_of_num_eq_bot zero_not_mem_nonZeroDivisors h,
fun h ↦ h ▸ num_zero_eq (IsFractionRing.injective R K)⟩
end IsFractionRing
section Quotient
/-!
### `quotient` section
This section defines the ideal quotient of fractional ideals.
In this section we need that each non-zero `y : R` has an inverse in
the localization, i.e. that the localization is a field. We satisfy this
assumption by taking `S = nonZeroDivisors R`, `R`'s localization at which
is a field because `R` is a domain.
-/
open scoped Classical
variable {R₁ : Type*} [CommRing R₁] {K : Type*} [Field K]
variable [Algebra R₁ K] [frac : IsFractionRing R₁ K]
instance : Nontrivial (FractionalIdeal R₁⁰ K) :=
⟨⟨0, 1, fun h =>
have this : (1 : K) ∈ (0 : FractionalIdeal R₁⁰ K) := by
rw [← (algebraMap R₁ K).map_one]
simpa only [h] using coe_mem_one R₁⁰ 1
one_ne_zero ((mem_zero_iff _).mp this)⟩⟩
theorem ne_zero_of_mul_eq_one (I J : FractionalIdeal R₁⁰ K) (h : I * J = 1) : I ≠ 0 := fun hI =>
zero_ne_one' (FractionalIdeal R₁⁰ K)
(by
convert h
simp [hI])
#align fractional_ideal.ne_zero_of_mul_eq_one FractionalIdeal.ne_zero_of_mul_eq_one
variable [IsDomain R₁]
theorem _root_.IsFractional.div_of_nonzero {I J : Submodule R₁ K} :
IsFractional R₁⁰ I → IsFractional R₁⁰ J → J ≠ 0 → IsFractional R₁⁰ (I / J)
| ⟨aI, haI, hI⟩, ⟨aJ, haJ, hJ⟩, h => by
obtain ⟨y, mem_J, not_mem_zero⟩ :=
SetLike.exists_of_lt (show 0 < J by simpa only using bot_lt_iff_ne_bot.mpr h)
obtain ⟨y', hy'⟩ := hJ y mem_J
use aI * y'
constructor
· apply (nonZeroDivisors R₁).mul_mem haI (mem_nonZeroDivisors_iff_ne_zero.mpr _)
intro y'_eq_zero
have : algebraMap R₁ K aJ * y = 0 := by
rw [← Algebra.smul_def, ← hy', y'_eq_zero, RingHom.map_zero]
have y_zero :=
(mul_eq_zero.mp this).resolve_left
(mt ((injective_iff_map_eq_zero (algebraMap R₁ K)).1 (IsFractionRing.injective _ _) _)
(mem_nonZeroDivisors_iff_ne_zero.mp haJ))
apply not_mem_zero
simpa
intro b hb
convert hI _ (hb _ (Submodule.smul_mem _ aJ mem_J)) using 1
rw [← hy', mul_comm b, ← Algebra.smul_def, mul_smul]
#align is_fractional.div_of_nonzero IsFractional.div_of_nonzero
theorem fractional_div_of_nonzero {I J : FractionalIdeal R₁⁰ K} (h : J ≠ 0) :
IsFractional R₁⁰ (I / J : Submodule R₁ K) :=
I.isFractional.div_of_nonzero J.isFractional fun H =>
h <| coeToSubmodule_injective <| H.trans coe_zero.symm
#align fractional_ideal.fractional_div_of_nonzero FractionalIdeal.fractional_div_of_nonzero
noncomputable instance : Div (FractionalIdeal R₁⁰ K) :=
⟨fun I J => if h : J = 0 then 0 else ⟨I / J, fractional_div_of_nonzero h⟩⟩
variable {I J : FractionalIdeal R₁⁰ K}
@[simp]
theorem div_zero {I : FractionalIdeal R₁⁰ K} : I / 0 = 0 :=
dif_pos rfl
#align fractional_ideal.div_zero FractionalIdeal.div_zero
theorem div_nonzero {I J : FractionalIdeal R₁⁰ K} (h : J ≠ 0) :
I / J = ⟨I / J, fractional_div_of_nonzero h⟩ :=
dif_neg h
#align fractional_ideal.div_nonzero FractionalIdeal.div_nonzero
@[simp]
theorem coe_div {I J : FractionalIdeal R₁⁰ K} (hJ : J ≠ 0) :
(↑(I / J) : Submodule R₁ K) = ↑I / (↑J : Submodule R₁ K) :=
congr_arg _ (dif_neg hJ)
#align fractional_ideal.coe_div FractionalIdeal.coe_div
theorem mem_div_iff_of_nonzero {I J : FractionalIdeal R₁⁰ K} (h : J ≠ 0) {x} :
x ∈ I / J ↔ ∀ y ∈ J, x * y ∈ I := by
rw [div_nonzero h]
exact Submodule.mem_div_iff_forall_mul_mem
#align fractional_ideal.mem_div_iff_of_nonzero FractionalIdeal.mem_div_iff_of_nonzero
theorem mul_one_div_le_one {I : FractionalIdeal R₁⁰ K} : I * (1 / I) ≤ 1 := by
by_cases hI : I = 0
· rw [hI, div_zero, mul_zero]
exact zero_le 1
· rw [← coe_le_coe, coe_mul, coe_div hI, coe_one]
apply Submodule.mul_one_div_le_one
#align fractional_ideal.mul_one_div_le_one FractionalIdeal.mul_one_div_le_one
theorem le_self_mul_one_div {I : FractionalIdeal R₁⁰ K} (hI : I ≤ (1 : FractionalIdeal R₁⁰ K)) :
I ≤ I * (1 / I) := by
by_cases hI_nz : I = 0
· rw [hI_nz, div_zero, mul_zero]
· rw [← coe_le_coe, coe_mul, coe_div hI_nz, coe_one]
rw [← coe_le_coe, coe_one] at hI
exact Submodule.le_self_mul_one_div hI
#align fractional_ideal.le_self_mul_one_div FractionalIdeal.le_self_mul_one_div
theorem le_div_iff_of_nonzero {I J J' : FractionalIdeal R₁⁰ K} (hJ' : J' ≠ 0) :
I ≤ J / J' ↔ ∀ x ∈ I, ∀ y ∈ J', x * y ∈ J :=
⟨fun h _ hx => (mem_div_iff_of_nonzero hJ').mp (h hx), fun h x hx =>
(mem_div_iff_of_nonzero hJ').mpr (h x hx)⟩
#align fractional_ideal.le_div_iff_of_nonzero FractionalIdeal.le_div_iff_of_nonzero
theorem le_div_iff_mul_le {I J J' : FractionalIdeal R₁⁰ K} (hJ' : J' ≠ 0) :
I ≤ J / J' ↔ I * J' ≤ J := by
rw [div_nonzero hJ']
-- Porting note: this used to be { convert; rw }, flipped the order.
rw [← coe_le_coe (I := I * J') (J := J), coe_mul]
exact Submodule.le_div_iff_mul_le
#align fractional_ideal.le_div_iff_mul_le FractionalIdeal.le_div_iff_mul_le
@[simp]
theorem div_one {I : FractionalIdeal R₁⁰ K} : I / 1 = I := by
rw [div_nonzero (one_ne_zero' (FractionalIdeal R₁⁰ K))]
ext
constructor <;> intro h
· simpa using mem_div_iff_forall_mul_mem.mp h 1 ((algebraMap R₁ K).map_one ▸ coe_mem_one R₁⁰ 1)
· apply mem_div_iff_forall_mul_mem.mpr
rintro y ⟨y', _, rfl⟩
-- Porting note: this used to be { convert; rw }, flipped the order.
rw [mul_comm, Algebra.linearMap_apply, ← Algebra.smul_def]
exact Submodule.smul_mem _ y' h
#align fractional_ideal.div_one FractionalIdeal.div_one
theorem eq_one_div_of_mul_eq_one_right (I J : FractionalIdeal R₁⁰ K) (h : I * J = 1) :
J = 1 / I := by
have hI : I ≠ 0 := ne_zero_of_mul_eq_one I J h
suffices h' : I * (1 / I) = 1 from
congr_arg Units.inv <| @Units.ext _ _ (Units.mkOfMulEqOne _ _ h) (Units.mkOfMulEqOne _ _ h') rfl
apply le_antisymm
· apply mul_le.mpr _
intro x hx y hy
rw [mul_comm]
exact (mem_div_iff_of_nonzero hI).mp hy x hx
rw [← h]
apply mul_left_mono I
apply (le_div_iff_of_nonzero hI).mpr _
intro y hy x hx
rw [mul_comm]
exact mul_mem_mul hx hy
#align fractional_ideal.eq_one_div_of_mul_eq_one_right FractionalIdeal.eq_one_div_of_mul_eq_one_right
theorem mul_div_self_cancel_iff {I : FractionalIdeal R₁⁰ K} : I * (1 / I) = 1 ↔ ∃ J, I * J = 1 :=
⟨fun h => ⟨1 / I, h⟩, fun ⟨J, hJ⟩ => by rwa [← eq_one_div_of_mul_eq_one_right I J hJ]⟩
#align fractional_ideal.mul_div_self_cancel_iff FractionalIdeal.mul_div_self_cancel_iff
variable {K' : Type*} [Field K'] [Algebra R₁ K'] [IsFractionRing R₁ K']
@[simp]
theorem map_div (I J : FractionalIdeal R₁⁰ K) (h : K ≃ₐ[R₁] K') :
(I / J).map (h : K →ₐ[R₁] K') = I.map h / J.map h := by
by_cases H : J = 0
· rw [H, div_zero, map_zero, div_zero]
· -- Porting note: `simp` wouldn't apply these lemmas so do them manually using `rw`
rw [← coeToSubmodule_inj, div_nonzero H, div_nonzero (map_ne_zero _ H)]
simp [Submodule.map_div]
#align fractional_ideal.map_div FractionalIdeal.map_div
-- Porting note: doesn't need to be @[simp] because this follows from `map_one` and `map_div`
theorem map_one_div (I : FractionalIdeal R₁⁰ K) (h : K ≃ₐ[R₁] K') :
(1 / I).map (h : K →ₐ[R₁] K') = 1 / I.map h := by rw [map_div, map_one]
#align fractional_ideal.map_one_div FractionalIdeal.map_one_div
end Quotient
section Field
variable {R₁ K L : Type*} [CommRing R₁] [Field K] [Field L]
variable [Algebra R₁ K] [IsFractionRing R₁ K] [Algebra K L] [IsFractionRing K L]
theorem eq_zero_or_one (I : FractionalIdeal K⁰ L) : I = 0 ∨ I = 1 := by
rw [or_iff_not_imp_left]
intro hI
simp_rw [@SetLike.ext_iff _ _ _ I 1, mem_one_iff]
intro x
constructor
· intro x_mem
obtain ⟨n, d, rfl⟩ := IsLocalization.mk'_surjective K⁰ x
refine ⟨n / d, ?_⟩
rw [map_div₀, IsFractionRing.mk'_eq_div]
· rintro ⟨x, rfl⟩
obtain ⟨y, y_ne, y_mem⟩ := exists_ne_zero_mem_isInteger hI
rw [← div_mul_cancel₀ x y_ne, RingHom.map_mul, ← Algebra.smul_def]
exact smul_mem (M := L) I (x / y) y_mem
#align fractional_ideal.eq_zero_or_one FractionalIdeal.eq_zero_or_one
theorem eq_zero_or_one_of_isField (hF : IsField R₁) (I : FractionalIdeal R₁⁰ K) : I = 0 ∨ I = 1 :=
letI : Field R₁ := hF.toField
eq_zero_or_one I
#align fractional_ideal.eq_zero_or_one_of_is_field FractionalIdeal.eq_zero_or_one_of_isField
end Field
section PrincipalIdeal
variable {R₁ : Type*} [CommRing R₁] {K : Type*} [Field K]
variable [Algebra R₁ K] [IsFractionRing R₁ K]
open scoped Classical
variable (R₁)
/-- `FractionalIdeal.span_finset R₁ s f` is the fractional ideal of `R₁` generated by `f '' s`. -/
-- Porting note: `@[simps]` generated a `Subtype.val` coercion instead of a
-- `FractionalIdeal.coeToSubmodule` coercion
def spanFinset {ι : Type*} (s : Finset ι) (f : ι → K) : FractionalIdeal R₁⁰ K :=
⟨Submodule.span R₁ (f '' s), by
obtain ⟨a', ha'⟩ := IsLocalization.exist_integer_multiples R₁⁰ s f
refine ⟨a', a'.2, fun x hx => Submodule.span_induction hx ?_ ?_ ?_ ?_⟩
· rintro _ ⟨i, hi, rfl⟩
exact ha' i hi
· rw [smul_zero]
exact IsLocalization.isInteger_zero
· intro x y hx hy
rw [smul_add]
exact IsLocalization.isInteger_add hx hy
· intro c x hx
rw [smul_comm]
exact IsLocalization.isInteger_smul hx⟩
#align fractional_ideal.span_finset FractionalIdeal.spanFinset
@[simp] lemma spanFinset_coe {ι : Type*} (s : Finset ι) (f : ι → K) :
(spanFinset R₁ s f : Submodule R₁ K) = Submodule.span R₁ (f '' s) :=
rfl
variable {R₁}
@[simp]
theorem spanFinset_eq_zero {ι : Type*} {s : Finset ι} {f : ι → K} :
spanFinset R₁ s f = 0 ↔ ∀ j ∈ s, f j = 0 := by
simp only [← coeToSubmodule_inj, spanFinset_coe, coe_zero, Submodule.span_eq_bot,
Set.mem_image, Finset.mem_coe, forall_exists_index, and_imp, forall_apply_eq_imp_iff₂]
#align fractional_ideal.span_finset_eq_zero FractionalIdeal.spanFinset_eq_zero
theorem spanFinset_ne_zero {ι : Type*} {s : Finset ι} {f : ι → K} :
spanFinset R₁ s f ≠ 0 ↔ ∃ j ∈ s, f j ≠ 0 := by simp
#align fractional_ideal.span_finset_ne_zero FractionalIdeal.spanFinset_ne_zero
open Submodule.IsPrincipal
theorem isFractional_span_singleton (x : P) : IsFractional S (span R {x} : Submodule R P) :=
let ⟨a, ha⟩ := exists_integer_multiple S x
isFractional_span_iff.mpr ⟨a, a.2, fun _ hx' => (Set.mem_singleton_iff.mp hx').symm ▸ ha⟩
#align fractional_ideal.is_fractional_span_singleton FractionalIdeal.isFractional_span_singleton
variable (S)
/-- `spanSingleton x` is the fractional ideal generated by `x` if `0 ∉ S` -/
irreducible_def spanSingleton (x : P) : FractionalIdeal S P :=
⟨span R {x}, isFractional_span_singleton x⟩
#align fractional_ideal.span_singleton FractionalIdeal.spanSingleton
-- local attribute [semireducible] span_singleton
@[simp]
theorem coe_spanSingleton (x : P) : (spanSingleton S x : Submodule R P) = span R {x} := by
rw [spanSingleton]
rfl
#align fractional_ideal.coe_span_singleton FractionalIdeal.coe_spanSingleton
@[simp]
theorem mem_spanSingleton {x y : P} : x ∈ spanSingleton S y ↔ ∃ z : R, z • y = x := by
rw [spanSingleton]
exact Submodule.mem_span_singleton
#align fractional_ideal.mem_span_singleton FractionalIdeal.mem_spanSingleton
theorem mem_spanSingleton_self (x : P) : x ∈ spanSingleton S x :=
(mem_spanSingleton S).mpr ⟨1, one_smul _ _⟩
#align fractional_ideal.mem_span_singleton_self FractionalIdeal.mem_spanSingleton_self
variable (P) in
/-- A version of `FractionalIdeal.den_mul_self_eq_num` in terms of fractional ideals. -/
theorem den_mul_self_eq_num' (I : FractionalIdeal S P) :
spanSingleton S (algebraMap R P I.den) * I = I.num := by
apply coeToSubmodule_injective
dsimp only
rw [coe_mul, ← smul_eq_mul, coe_spanSingleton, smul_eq_mul, Submodule.span_singleton_mul]
convert I.den_mul_self_eq_num using 1
ext
erw [Set.mem_smul_set, Set.mem_smul_set]
simp [Algebra.smul_def]
variable {S}
@[simp]
theorem spanSingleton_le_iff_mem {x : P} {I : FractionalIdeal S P} :
spanSingleton S x ≤ I ↔ x ∈ I := by
rw [← coe_le_coe, coe_spanSingleton, Submodule.span_singleton_le_iff_mem, mem_coe]
#align fractional_ideal.span_singleton_le_iff_mem FractionalIdeal.spanSingleton_le_iff_mem
theorem spanSingleton_eq_spanSingleton [NoZeroSMulDivisors R P] {x y : P} :
spanSingleton S x = spanSingleton S y ↔ ∃ z : Rˣ, z • x = y := by
rw [← Submodule.span_singleton_eq_span_singleton, spanSingleton, spanSingleton]
exact Subtype.mk_eq_mk
#align fractional_ideal.span_singleton_eq_span_singleton FractionalIdeal.spanSingleton_eq_spanSingleton
theorem eq_spanSingleton_of_principal (I : FractionalIdeal S P) [IsPrincipal (I : Submodule R P)] :
I = spanSingleton S (generator (I : Submodule R P)) := by
-- Porting note: this used to be `coeToSubmodule_injective (span_singleton_generator ↑I).symm`
-- but Lean 4 struggled to unify everything. Turned it into an explicit `rw`.
rw [spanSingleton, ← coeToSubmodule_inj, coe_mk, span_singleton_generator]
#align fractional_ideal.eq_span_singleton_of_principal FractionalIdeal.eq_spanSingleton_of_principal
theorem isPrincipal_iff (I : FractionalIdeal S P) :
IsPrincipal (I : Submodule R P) ↔ ∃ x, I = spanSingleton S x :=
⟨fun h => ⟨@generator _ _ _ _ _ (↑I) h, @eq_spanSingleton_of_principal _ _ _ _ _ _ _ I h⟩,
fun ⟨x, hx⟩ => { principal' := ⟨x, Eq.trans (congr_arg _ hx) (coe_spanSingleton _ x)⟩ }⟩
#align fractional_ideal.is_principal_iff FractionalIdeal.isPrincipal_iff
@[simp]
theorem spanSingleton_zero : spanSingleton S (0 : P) = 0 := by
ext
simp [Submodule.mem_span_singleton, eq_comm]
#align fractional_ideal.span_singleton_zero FractionalIdeal.spanSingleton_zero
theorem spanSingleton_eq_zero_iff {y : P} : spanSingleton S y = 0 ↔ y = 0 :=
⟨fun h =>
span_eq_bot.mp (by simpa using congr_arg Subtype.val h : span R {y} = ⊥) y (mem_singleton y),
fun h => by simp [h]⟩
#align fractional_ideal.span_singleton_eq_zero_iff FractionalIdeal.spanSingleton_eq_zero_iff
theorem spanSingleton_ne_zero_iff {y : P} : spanSingleton S y ≠ 0 ↔ y ≠ 0 :=
not_congr spanSingleton_eq_zero_iff
#align fractional_ideal.span_singleton_ne_zero_iff FractionalIdeal.spanSingleton_ne_zero_iff
@[simp]
theorem spanSingleton_one : spanSingleton S (1 : P) = 1 := by
ext
refine (mem_spanSingleton S).trans ((exists_congr ?_).trans (mem_one_iff S).symm)
intro x'
rw [Algebra.smul_def, mul_one]
#align fractional_ideal.span_singleton_one FractionalIdeal.spanSingleton_one
@[simp]
theorem spanSingleton_mul_spanSingleton (x y : P) :
spanSingleton S x * spanSingleton S y = spanSingleton S (x * y) := by
apply coeToSubmodule_injective
simp only [coe_mul, coe_spanSingleton, span_mul_span, singleton_mul_singleton]
#align fractional_ideal.span_singleton_mul_span_singleton FractionalIdeal.spanSingleton_mul_spanSingleton
@[simp]
theorem spanSingleton_pow (x : P) (n : ℕ) : spanSingleton S x ^ n = spanSingleton S (x ^ n) := by
induction' n with n hn
· rw [pow_zero, pow_zero, spanSingleton_one]
· rw [pow_succ, hn, spanSingleton_mul_spanSingleton, pow_succ]
#align fractional_ideal.span_singleton_pow FractionalIdeal.spanSingleton_pow
@[simp]
theorem coeIdeal_span_singleton (x : R) :
(↑(Ideal.span {x} : Ideal R) : FractionalIdeal S P) = spanSingleton S (algebraMap R P x) := by
ext y
refine (mem_coeIdeal S).trans (Iff.trans ?_ (mem_spanSingleton S).symm)
constructor
· rintro ⟨y', hy', rfl⟩
obtain ⟨x', rfl⟩ := Submodule.mem_span_singleton.mp hy'
use x'
rw [smul_eq_mul, RingHom.map_mul, Algebra.smul_def]
· rintro ⟨y', rfl⟩
refine ⟨y' * x, Submodule.mem_span_singleton.mpr ⟨y', rfl⟩, ?_⟩
rw [RingHom.map_mul, Algebra.smul_def]
#align fractional_ideal.coe_ideal_span_singleton FractionalIdeal.coeIdeal_span_singleton
@[simp]
| Mathlib/RingTheory/FractionalIdeal/Operations.lean | 737 | 755 | theorem canonicalEquiv_spanSingleton {P'} [CommRing P'] [Algebra R P'] [IsLocalization S P']
(x : P) :
canonicalEquiv S P P' (spanSingleton S x) =
spanSingleton S
(IsLocalization.map P' (RingHom.id R)
(fun y (hy : y ∈ S) => show RingHom.id R y ∈ S from hy) x) := by |
apply SetLike.ext_iff.mpr
intro y
constructor <;> intro h
· rw [mem_spanSingleton]
obtain ⟨x', hx', rfl⟩ := (mem_canonicalEquiv_apply _ _ _).mp h
obtain ⟨z, rfl⟩ := (mem_spanSingleton _).mp hx'
use z
rw [IsLocalization.map_smul, RingHom.id_apply]
· rw [mem_canonicalEquiv_apply]
obtain ⟨z, rfl⟩ := (mem_spanSingleton _).mp h
use z • x
use (mem_spanSingleton _).mpr ⟨z, rfl⟩
simp [IsLocalization.map_smul]
|
/-
Copyright (c) 2022 David Kurniadi Angdinata. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: David Kurniadi Angdinata
-/
import Mathlib.Algebra.Polynomial.Splits
#align_import algebra.cubic_discriminant from "leanprover-community/mathlib"@"930133160e24036d5242039fe4972407cd4f1222"
/-!
# Cubics and discriminants
This file defines cubic polynomials over a semiring and their discriminants over a splitting field.
## Main definitions
* `Cubic`: the structure representing a cubic polynomial.
* `Cubic.disc`: the discriminant of a cubic polynomial.
## Main statements
* `Cubic.disc_ne_zero_iff_roots_nodup`: the cubic discriminant is not equal to zero if and only if
the cubic has no duplicate roots.
## References
* https://en.wikipedia.org/wiki/Cubic_equation
* https://en.wikipedia.org/wiki/Discriminant
## Tags
cubic, discriminant, polynomial, root
-/
noncomputable section
/-- The structure representing a cubic polynomial. -/
@[ext]
structure Cubic (R : Type*) where
(a b c d : R)
#align cubic Cubic
namespace Cubic
open Cubic Polynomial
open Polynomial
variable {R S F K : Type*}
instance [Inhabited R] : Inhabited (Cubic R) :=
⟨⟨default, default, default, default⟩⟩
instance [Zero R] : Zero (Cubic R) :=
⟨⟨0, 0, 0, 0⟩⟩
section Basic
variable {P Q : Cubic R} {a b c d a' b' c' d' : R} [Semiring R]
/-- Convert a cubic polynomial to a polynomial. -/
def toPoly (P : Cubic R) : R[X] :=
C P.a * X ^ 3 + C P.b * X ^ 2 + C P.c * X + C P.d
#align cubic.to_poly Cubic.toPoly
theorem C_mul_prod_X_sub_C_eq [CommRing S] {w x y z : S} :
C w * (X - C x) * (X - C y) * (X - C z) =
toPoly ⟨w, w * -(x + y + z), w * (x * y + x * z + y * z), w * -(x * y * z)⟩ := by
simp only [toPoly, C_neg, C_add, C_mul]
ring1
set_option linter.uppercaseLean3 false in
#align cubic.C_mul_prod_X_sub_C_eq Cubic.C_mul_prod_X_sub_C_eq
theorem prod_X_sub_C_eq [CommRing S] {x y z : S} :
(X - C x) * (X - C y) * (X - C z) =
toPoly ⟨1, -(x + y + z), x * y + x * z + y * z, -(x * y * z)⟩ := by
rw [← one_mul <| X - C x, ← C_1, C_mul_prod_X_sub_C_eq, one_mul, one_mul, one_mul]
set_option linter.uppercaseLean3 false in
#align cubic.prod_X_sub_C_eq Cubic.prod_X_sub_C_eq
/-! ### Coefficients -/
section Coeff
private theorem coeffs : (∀ n > 3, P.toPoly.coeff n = 0) ∧ P.toPoly.coeff 3 = P.a ∧
P.toPoly.coeff 2 = P.b ∧ P.toPoly.coeff 1 = P.c ∧ P.toPoly.coeff 0 = P.d := by
simp only [toPoly, coeff_add, coeff_C, coeff_C_mul_X, coeff_C_mul_X_pow]
set_option tactic.skipAssignedInstances false in norm_num
intro n hn
repeat' rw [if_neg]
any_goals linarith only [hn]
repeat' rw [zero_add]
@[simp]
theorem coeff_eq_zero {n : ℕ} (hn : 3 < n) : P.toPoly.coeff n = 0 :=
coeffs.1 n hn
#align cubic.coeff_eq_zero Cubic.coeff_eq_zero
@[simp]
theorem coeff_eq_a : P.toPoly.coeff 3 = P.a :=
coeffs.2.1
#align cubic.coeff_eq_a Cubic.coeff_eq_a
@[simp]
theorem coeff_eq_b : P.toPoly.coeff 2 = P.b :=
coeffs.2.2.1
#align cubic.coeff_eq_b Cubic.coeff_eq_b
@[simp]
theorem coeff_eq_c : P.toPoly.coeff 1 = P.c :=
coeffs.2.2.2.1
#align cubic.coeff_eq_c Cubic.coeff_eq_c
@[simp]
theorem coeff_eq_d : P.toPoly.coeff 0 = P.d :=
coeffs.2.2.2.2
#align cubic.coeff_eq_d Cubic.coeff_eq_d
theorem a_of_eq (h : P.toPoly = Q.toPoly) : P.a = Q.a := by rw [← coeff_eq_a, h, coeff_eq_a]
#align cubic.a_of_eq Cubic.a_of_eq
theorem b_of_eq (h : P.toPoly = Q.toPoly) : P.b = Q.b := by rw [← coeff_eq_b, h, coeff_eq_b]
#align cubic.b_of_eq Cubic.b_of_eq
theorem c_of_eq (h : P.toPoly = Q.toPoly) : P.c = Q.c := by rw [← coeff_eq_c, h, coeff_eq_c]
#align cubic.c_of_eq Cubic.c_of_eq
theorem d_of_eq (h : P.toPoly = Q.toPoly) : P.d = Q.d := by rw [← coeff_eq_d, h, coeff_eq_d]
#align cubic.d_of_eq Cubic.d_of_eq
theorem toPoly_injective (P Q : Cubic R) : P.toPoly = Q.toPoly ↔ P = Q :=
⟨fun h ↦ Cubic.ext P Q (a_of_eq h) (b_of_eq h) (c_of_eq h) (d_of_eq h), congr_arg toPoly⟩
#align cubic.to_poly_injective Cubic.toPoly_injective
theorem of_a_eq_zero (ha : P.a = 0) : P.toPoly = C P.b * X ^ 2 + C P.c * X + C P.d := by
rw [toPoly, ha, C_0, zero_mul, zero_add]
#align cubic.of_a_eq_zero Cubic.of_a_eq_zero
theorem of_a_eq_zero' : toPoly ⟨0, b, c, d⟩ = C b * X ^ 2 + C c * X + C d :=
of_a_eq_zero rfl
#align cubic.of_a_eq_zero' Cubic.of_a_eq_zero'
theorem of_b_eq_zero (ha : P.a = 0) (hb : P.b = 0) : P.toPoly = C P.c * X + C P.d := by
rw [of_a_eq_zero ha, hb, C_0, zero_mul, zero_add]
#align cubic.of_b_eq_zero Cubic.of_b_eq_zero
theorem of_b_eq_zero' : toPoly ⟨0, 0, c, d⟩ = C c * X + C d :=
of_b_eq_zero rfl rfl
#align cubic.of_b_eq_zero' Cubic.of_b_eq_zero'
theorem of_c_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) : P.toPoly = C P.d := by
rw [of_b_eq_zero ha hb, hc, C_0, zero_mul, zero_add]
#align cubic.of_c_eq_zero Cubic.of_c_eq_zero
theorem of_c_eq_zero' : toPoly ⟨0, 0, 0, d⟩ = C d :=
of_c_eq_zero rfl rfl rfl
#align cubic.of_c_eq_zero' Cubic.of_c_eq_zero'
theorem of_d_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) (hd : P.d = 0) :
P.toPoly = 0 := by
rw [of_c_eq_zero ha hb hc, hd, C_0]
#align cubic.of_d_eq_zero Cubic.of_d_eq_zero
theorem of_d_eq_zero' : (⟨0, 0, 0, 0⟩ : Cubic R).toPoly = 0 :=
of_d_eq_zero rfl rfl rfl rfl
#align cubic.of_d_eq_zero' Cubic.of_d_eq_zero'
theorem zero : (0 : Cubic R).toPoly = 0 :=
of_d_eq_zero'
#align cubic.zero Cubic.zero
theorem toPoly_eq_zero_iff (P : Cubic R) : P.toPoly = 0 ↔ P = 0 := by
rw [← zero, toPoly_injective]
#align cubic.to_poly_eq_zero_iff Cubic.toPoly_eq_zero_iff
private theorem ne_zero (h0 : P.a ≠ 0 ∨ P.b ≠ 0 ∨ P.c ≠ 0 ∨ P.d ≠ 0) : P.toPoly ≠ 0 := by
contrapose! h0
rw [(toPoly_eq_zero_iff P).mp h0]
exact ⟨rfl, rfl, rfl, rfl⟩
theorem ne_zero_of_a_ne_zero (ha : P.a ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp ne_zero).1 ha
#align cubic.ne_zero_of_a_ne_zero Cubic.ne_zero_of_a_ne_zero
theorem ne_zero_of_b_ne_zero (hb : P.b ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp (or_imp.mp ne_zero).2).1 hb
#align cubic.ne_zero_of_b_ne_zero Cubic.ne_zero_of_b_ne_zero
theorem ne_zero_of_c_ne_zero (hc : P.c ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp (or_imp.mp (or_imp.mp ne_zero).2).2).1 hc
#align cubic.ne_zero_of_c_ne_zero Cubic.ne_zero_of_c_ne_zero
theorem ne_zero_of_d_ne_zero (hd : P.d ≠ 0) : P.toPoly ≠ 0 :=
(or_imp.mp (or_imp.mp (or_imp.mp ne_zero).2).2).2 hd
#align cubic.ne_zero_of_d_ne_zero Cubic.ne_zero_of_d_ne_zero
@[simp]
theorem leadingCoeff_of_a_ne_zero (ha : P.a ≠ 0) : P.toPoly.leadingCoeff = P.a :=
leadingCoeff_cubic ha
#align cubic.leading_coeff_of_a_ne_zero Cubic.leadingCoeff_of_a_ne_zero
@[simp]
theorem leadingCoeff_of_a_ne_zero' (ha : a ≠ 0) : (toPoly ⟨a, b, c, d⟩).leadingCoeff = a :=
leadingCoeff_of_a_ne_zero ha
#align cubic.leading_coeff_of_a_ne_zero' Cubic.leadingCoeff_of_a_ne_zero'
@[simp]
theorem leadingCoeff_of_b_ne_zero (ha : P.a = 0) (hb : P.b ≠ 0) : P.toPoly.leadingCoeff = P.b := by
rw [of_a_eq_zero ha, leadingCoeff_quadratic hb]
#align cubic.leading_coeff_of_b_ne_zero Cubic.leadingCoeff_of_b_ne_zero
@[simp]
theorem leadingCoeff_of_b_ne_zero' (hb : b ≠ 0) : (toPoly ⟨0, b, c, d⟩).leadingCoeff = b :=
leadingCoeff_of_b_ne_zero rfl hb
#align cubic.leading_coeff_of_b_ne_zero' Cubic.leadingCoeff_of_b_ne_zero'
@[simp]
theorem leadingCoeff_of_c_ne_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c ≠ 0) :
P.toPoly.leadingCoeff = P.c := by
rw [of_b_eq_zero ha hb, leadingCoeff_linear hc]
#align cubic.leading_coeff_of_c_ne_zero Cubic.leadingCoeff_of_c_ne_zero
@[simp]
theorem leadingCoeff_of_c_ne_zero' (hc : c ≠ 0) : (toPoly ⟨0, 0, c, d⟩).leadingCoeff = c :=
leadingCoeff_of_c_ne_zero rfl rfl hc
#align cubic.leading_coeff_of_c_ne_zero' Cubic.leadingCoeff_of_c_ne_zero'
@[simp]
theorem leadingCoeff_of_c_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) :
P.toPoly.leadingCoeff = P.d := by
rw [of_c_eq_zero ha hb hc, leadingCoeff_C]
#align cubic.leading_coeff_of_c_eq_zero Cubic.leadingCoeff_of_c_eq_zero
-- @[simp] -- porting note (#10618): simp can prove this
theorem leadingCoeff_of_c_eq_zero' : (toPoly ⟨0, 0, 0, d⟩).leadingCoeff = d :=
leadingCoeff_of_c_eq_zero rfl rfl rfl
#align cubic.leading_coeff_of_c_eq_zero' Cubic.leadingCoeff_of_c_eq_zero'
theorem monic_of_a_eq_one (ha : P.a = 1) : P.toPoly.Monic := by
nontriviality R
rw [Monic, leadingCoeff_of_a_ne_zero (ha ▸ one_ne_zero), ha]
#align cubic.monic_of_a_eq_one Cubic.monic_of_a_eq_one
theorem monic_of_a_eq_one' : (toPoly ⟨1, b, c, d⟩).Monic :=
monic_of_a_eq_one rfl
#align cubic.monic_of_a_eq_one' Cubic.monic_of_a_eq_one'
theorem monic_of_b_eq_one (ha : P.a = 0) (hb : P.b = 1) : P.toPoly.Monic := by
nontriviality R
rw [Monic, leadingCoeff_of_b_ne_zero ha (hb ▸ one_ne_zero), hb]
#align cubic.monic_of_b_eq_one Cubic.monic_of_b_eq_one
theorem monic_of_b_eq_one' : (toPoly ⟨0, 1, c, d⟩).Monic :=
monic_of_b_eq_one rfl rfl
#align cubic.monic_of_b_eq_one' Cubic.monic_of_b_eq_one'
theorem monic_of_c_eq_one (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 1) : P.toPoly.Monic := by
nontriviality R
rw [Monic, leadingCoeff_of_c_ne_zero ha hb (hc ▸ one_ne_zero), hc]
#align cubic.monic_of_c_eq_one Cubic.monic_of_c_eq_one
theorem monic_of_c_eq_one' : (toPoly ⟨0, 0, 1, d⟩).Monic :=
monic_of_c_eq_one rfl rfl rfl
#align cubic.monic_of_c_eq_one' Cubic.monic_of_c_eq_one'
theorem monic_of_d_eq_one (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) (hd : P.d = 1) :
P.toPoly.Monic := by
rw [Monic, leadingCoeff_of_c_eq_zero ha hb hc, hd]
#align cubic.monic_of_d_eq_one Cubic.monic_of_d_eq_one
theorem monic_of_d_eq_one' : (toPoly ⟨0, 0, 0, 1⟩).Monic :=
monic_of_d_eq_one rfl rfl rfl rfl
#align cubic.monic_of_d_eq_one' Cubic.monic_of_d_eq_one'
end Coeff
/-! ### Degrees -/
section Degree
/-- The equivalence between cubic polynomials and polynomials of degree at most three. -/
@[simps]
def equiv : Cubic R ≃ { p : R[X] // p.degree ≤ 3 } where
toFun P := ⟨P.toPoly, degree_cubic_le⟩
invFun f := ⟨coeff f 3, coeff f 2, coeff f 1, coeff f 0⟩
left_inv P := by ext <;> simp only [Subtype.coe_mk, coeffs]
right_inv f := by
-- Porting note: Added `simp only [Nat.zero_eq, Nat.succ_eq_add_one] <;> ring_nf`
-- There's probably a better way to do this.
ext (_ | _ | _ | _ | n) <;> simp only [Nat.zero_eq, Nat.succ_eq_add_one] <;> ring_nf
<;> try simp only [coeffs]
have h3 : 3 < 4 + n := by linarith only
rw [coeff_eq_zero h3,
(degree_le_iff_coeff_zero (f : R[X]) 3).mp f.2 _ <| WithBot.coe_lt_coe.mpr (by exact h3)]
#align cubic.equiv Cubic.equiv
@[simp]
theorem degree_of_a_ne_zero (ha : P.a ≠ 0) : P.toPoly.degree = 3 :=
degree_cubic ha
#align cubic.degree_of_a_ne_zero Cubic.degree_of_a_ne_zero
@[simp]
theorem degree_of_a_ne_zero' (ha : a ≠ 0) : (toPoly ⟨a, b, c, d⟩).degree = 3 :=
degree_of_a_ne_zero ha
#align cubic.degree_of_a_ne_zero' Cubic.degree_of_a_ne_zero'
theorem degree_of_a_eq_zero (ha : P.a = 0) : P.toPoly.degree ≤ 2 := by
simpa only [of_a_eq_zero ha] using degree_quadratic_le
#align cubic.degree_of_a_eq_zero Cubic.degree_of_a_eq_zero
theorem degree_of_a_eq_zero' : (toPoly ⟨0, b, c, d⟩).degree ≤ 2 :=
degree_of_a_eq_zero rfl
#align cubic.degree_of_a_eq_zero' Cubic.degree_of_a_eq_zero'
@[simp]
theorem degree_of_b_ne_zero (ha : P.a = 0) (hb : P.b ≠ 0) : P.toPoly.degree = 2 := by
rw [of_a_eq_zero ha, degree_quadratic hb]
#align cubic.degree_of_b_ne_zero Cubic.degree_of_b_ne_zero
@[simp]
theorem degree_of_b_ne_zero' (hb : b ≠ 0) : (toPoly ⟨0, b, c, d⟩).degree = 2 :=
degree_of_b_ne_zero rfl hb
#align cubic.degree_of_b_ne_zero' Cubic.degree_of_b_ne_zero'
theorem degree_of_b_eq_zero (ha : P.a = 0) (hb : P.b = 0) : P.toPoly.degree ≤ 1 := by
simpa only [of_b_eq_zero ha hb] using degree_linear_le
#align cubic.degree_of_b_eq_zero Cubic.degree_of_b_eq_zero
theorem degree_of_b_eq_zero' : (toPoly ⟨0, 0, c, d⟩).degree ≤ 1 :=
degree_of_b_eq_zero rfl rfl
#align cubic.degree_of_b_eq_zero' Cubic.degree_of_b_eq_zero'
@[simp]
theorem degree_of_c_ne_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c ≠ 0) : P.toPoly.degree = 1 := by
rw [of_b_eq_zero ha hb, degree_linear hc]
#align cubic.degree_of_c_ne_zero Cubic.degree_of_c_ne_zero
@[simp]
theorem degree_of_c_ne_zero' (hc : c ≠ 0) : (toPoly ⟨0, 0, c, d⟩).degree = 1 :=
degree_of_c_ne_zero rfl rfl hc
#align cubic.degree_of_c_ne_zero' Cubic.degree_of_c_ne_zero'
theorem degree_of_c_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) : P.toPoly.degree ≤ 0 := by
simpa only [of_c_eq_zero ha hb hc] using degree_C_le
#align cubic.degree_of_c_eq_zero Cubic.degree_of_c_eq_zero
theorem degree_of_c_eq_zero' : (toPoly ⟨0, 0, 0, d⟩).degree ≤ 0 :=
degree_of_c_eq_zero rfl rfl rfl
#align cubic.degree_of_c_eq_zero' Cubic.degree_of_c_eq_zero'
@[simp]
theorem degree_of_d_ne_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) (hd : P.d ≠ 0) :
P.toPoly.degree = 0 := by
rw [of_c_eq_zero ha hb hc, degree_C hd]
#align cubic.degree_of_d_ne_zero Cubic.degree_of_d_ne_zero
@[simp]
theorem degree_of_d_ne_zero' (hd : d ≠ 0) : (toPoly ⟨0, 0, 0, d⟩).degree = 0 :=
degree_of_d_ne_zero rfl rfl rfl hd
#align cubic.degree_of_d_ne_zero' Cubic.degree_of_d_ne_zero'
@[simp]
theorem degree_of_d_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) (hd : P.d = 0) :
P.toPoly.degree = ⊥ := by
rw [of_d_eq_zero ha hb hc hd, degree_zero]
#align cubic.degree_of_d_eq_zero Cubic.degree_of_d_eq_zero
-- @[simp] -- porting note (#10618): simp can prove this
theorem degree_of_d_eq_zero' : (⟨0, 0, 0, 0⟩ : Cubic R).toPoly.degree = ⊥ :=
degree_of_d_eq_zero rfl rfl rfl rfl
#align cubic.degree_of_d_eq_zero' Cubic.degree_of_d_eq_zero'
@[simp]
theorem degree_of_zero : (0 : Cubic R).toPoly.degree = ⊥ :=
degree_of_d_eq_zero'
#align cubic.degree_of_zero Cubic.degree_of_zero
@[simp]
theorem natDegree_of_a_ne_zero (ha : P.a ≠ 0) : P.toPoly.natDegree = 3 :=
natDegree_cubic ha
#align cubic.nat_degree_of_a_ne_zero Cubic.natDegree_of_a_ne_zero
@[simp]
theorem natDegree_of_a_ne_zero' (ha : a ≠ 0) : (toPoly ⟨a, b, c, d⟩).natDegree = 3 :=
natDegree_of_a_ne_zero ha
#align cubic.nat_degree_of_a_ne_zero' Cubic.natDegree_of_a_ne_zero'
theorem natDegree_of_a_eq_zero (ha : P.a = 0) : P.toPoly.natDegree ≤ 2 := by
simpa only [of_a_eq_zero ha] using natDegree_quadratic_le
#align cubic.nat_degree_of_a_eq_zero Cubic.natDegree_of_a_eq_zero
theorem natDegree_of_a_eq_zero' : (toPoly ⟨0, b, c, d⟩).natDegree ≤ 2 :=
natDegree_of_a_eq_zero rfl
#align cubic.nat_degree_of_a_eq_zero' Cubic.natDegree_of_a_eq_zero'
@[simp]
theorem natDegree_of_b_ne_zero (ha : P.a = 0) (hb : P.b ≠ 0) : P.toPoly.natDegree = 2 := by
rw [of_a_eq_zero ha, natDegree_quadratic hb]
#align cubic.nat_degree_of_b_ne_zero Cubic.natDegree_of_b_ne_zero
@[simp]
theorem natDegree_of_b_ne_zero' (hb : b ≠ 0) : (toPoly ⟨0, b, c, d⟩).natDegree = 2 :=
natDegree_of_b_ne_zero rfl hb
#align cubic.nat_degree_of_b_ne_zero' Cubic.natDegree_of_b_ne_zero'
theorem natDegree_of_b_eq_zero (ha : P.a = 0) (hb : P.b = 0) : P.toPoly.natDegree ≤ 1 := by
simpa only [of_b_eq_zero ha hb] using natDegree_linear_le
#align cubic.nat_degree_of_b_eq_zero Cubic.natDegree_of_b_eq_zero
theorem natDegree_of_b_eq_zero' : (toPoly ⟨0, 0, c, d⟩).natDegree ≤ 1 :=
natDegree_of_b_eq_zero rfl rfl
#align cubic.nat_degree_of_b_eq_zero' Cubic.natDegree_of_b_eq_zero'
@[simp]
theorem natDegree_of_c_ne_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c ≠ 0) :
P.toPoly.natDegree = 1 := by
rw [of_b_eq_zero ha hb, natDegree_linear hc]
#align cubic.nat_degree_of_c_ne_zero Cubic.natDegree_of_c_ne_zero
@[simp]
theorem natDegree_of_c_ne_zero' (hc : c ≠ 0) : (toPoly ⟨0, 0, c, d⟩).natDegree = 1 :=
natDegree_of_c_ne_zero rfl rfl hc
#align cubic.nat_degree_of_c_ne_zero' Cubic.natDegree_of_c_ne_zero'
@[simp]
| Mathlib/Algebra/CubicDiscriminant.lean | 429 | 431 | theorem natDegree_of_c_eq_zero (ha : P.a = 0) (hb : P.b = 0) (hc : P.c = 0) :
P.toPoly.natDegree = 0 := by |
rw [of_c_eq_zero ha hb hc, natDegree_C]
|
/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Mario Carneiro, Johan Commelin, Amelia Livingston, Anne Baanen
-/
import Mathlib.Algebra.GroupWithZero.NonZeroDivisors
import Mathlib.Algebra.Polynomial.Lifts
import Mathlib.GroupTheory.MonoidLocalization
import Mathlib.RingTheory.Algebraic
import Mathlib.RingTheory.Ideal.LocalRing
import Mathlib.RingTheory.IntegralClosure
import Mathlib.RingTheory.Localization.FractionRing
import Mathlib.RingTheory.Localization.Integer
#align_import ring_theory.localization.integral from "leanprover-community/mathlib"@"831c494092374cfe9f50591ed0ac81a25efc5b86"
/-!
# Integral and algebraic elements of a fraction field
## Implementation notes
See `RingTheory/Localization/Basic.lean` for a design overview.
## Tags
localization, ring localization, commutative ring localization, characteristic predicate,
commutative ring, field of fractions
-/
variable {R : Type*} [CommRing R] (M : Submonoid R) {S : Type*} [CommRing S]
variable [Algebra R S] {P : Type*} [CommRing P]
open Polynomial
namespace IsLocalization
section IntegerNormalization
open Polynomial
variable [IsLocalization M S]
open scoped Classical
/-- `coeffIntegerNormalization p` gives the coefficients of the polynomial
`integerNormalization p` -/
noncomputable def coeffIntegerNormalization (p : S[X]) (i : ℕ) : R :=
if hi : i ∈ p.support then
Classical.choose
(Classical.choose_spec (exist_integer_multiples_of_finset M (p.support.image p.coeff))
(p.coeff i) (Finset.mem_image.mpr ⟨i, hi, rfl⟩))
else 0
#align is_localization.coeff_integer_normalization IsLocalization.coeffIntegerNormalization
theorem coeffIntegerNormalization_of_not_mem_support (p : S[X]) (i : ℕ) (h : coeff p i = 0) :
coeffIntegerNormalization M p i = 0 := by
simp only [coeffIntegerNormalization, h, mem_support_iff, eq_self_iff_true, not_true, Ne,
dif_neg, not_false_iff]
#align is_localization.coeff_integer_normalization_of_not_mem_support IsLocalization.coeffIntegerNormalization_of_not_mem_support
theorem coeffIntegerNormalization_mem_support (p : S[X]) (i : ℕ)
(h : coeffIntegerNormalization M p i ≠ 0) : i ∈ p.support := by
contrapose h
rw [Ne, Classical.not_not, coeffIntegerNormalization, dif_neg h]
#align is_localization.coeff_integer_normalization_mem_support IsLocalization.coeffIntegerNormalization_mem_support
/-- `integerNormalization g` normalizes `g` to have integer coefficients
by clearing the denominators -/
noncomputable def integerNormalization (p : S[X]) : R[X] :=
∑ i ∈ p.support, monomial i (coeffIntegerNormalization M p i)
#align is_localization.integer_normalization IsLocalization.integerNormalization
@[simp]
theorem integerNormalization_coeff (p : S[X]) (i : ℕ) :
(integerNormalization M p).coeff i = coeffIntegerNormalization M p i := by
simp (config := { contextual := true }) [integerNormalization, coeff_monomial,
coeffIntegerNormalization_of_not_mem_support]
#align is_localization.integer_normalization_coeff IsLocalization.integerNormalization_coeff
theorem integerNormalization_spec (p : S[X]) :
∃ b : M, ∀ i, algebraMap R S ((integerNormalization M p).coeff i) = (b : R) • p.coeff i := by
use Classical.choose (exist_integer_multiples_of_finset M (p.support.image p.coeff))
intro i
rw [integerNormalization_coeff, coeffIntegerNormalization]
split_ifs with hi
· exact
Classical.choose_spec
(Classical.choose_spec (exist_integer_multiples_of_finset M (p.support.image p.coeff))
(p.coeff i) (Finset.mem_image.mpr ⟨i, hi, rfl⟩))
· rw [RingHom.map_zero, not_mem_support_iff.mp hi, smul_zero]
-- Porting note: was `convert (smul_zero _).symm, ...`
#align is_localization.integer_normalization_spec IsLocalization.integerNormalization_spec
theorem integerNormalization_map_to_map (p : S[X]) :
∃ b : M, (integerNormalization M p).map (algebraMap R S) = (b : R) • p :=
let ⟨b, hb⟩ := integerNormalization_spec M p
⟨b,
Polynomial.ext fun i => by
rw [coeff_map, coeff_smul]
exact hb i⟩
#align is_localization.integer_normalization_map_to_map IsLocalization.integerNormalization_map_to_map
variable {R' : Type*} [CommRing R']
theorem integerNormalization_eval₂_eq_zero (g : S →+* R') (p : S[X]) {x : R'}
(hx : eval₂ g x p = 0) : eval₂ (g.comp (algebraMap R S)) x (integerNormalization M p) = 0 :=
let ⟨b, hb⟩ := integerNormalization_map_to_map M p
_root_.trans (eval₂_map (algebraMap R S) g x).symm
(by rw [hb, ← IsScalarTower.algebraMap_smul S (b : R) p, eval₂_smul, hx, mul_zero])
#align is_localization.integer_normalization_eval₂_eq_zero IsLocalization.integerNormalization_eval₂_eq_zero
theorem integerNormalization_aeval_eq_zero [Algebra R R'] [Algebra S R'] [IsScalarTower R S R']
(p : S[X]) {x : R'} (hx : aeval x p = 0) : aeval x (integerNormalization M p) = 0 := by
rw [aeval_def, IsScalarTower.algebraMap_eq R S R',
integerNormalization_eval₂_eq_zero _ (algebraMap _ _) _ hx]
#align is_localization.integer_normalization_aeval_eq_zero IsLocalization.integerNormalization_aeval_eq_zero
end IntegerNormalization
end IsLocalization
namespace IsFractionRing
open IsLocalization
variable {A K C : Type*} [CommRing A] [IsDomain A] [Field K] [Algebra A K] [IsFractionRing A K]
variable [CommRing C]
theorem integerNormalization_eq_zero_iff {p : K[X]} :
integerNormalization (nonZeroDivisors A) p = 0 ↔ p = 0 := by
refine Polynomial.ext_iff.trans (Polynomial.ext_iff.trans ?_).symm
obtain ⟨⟨b, nonzero⟩, hb⟩ := integerNormalization_spec (nonZeroDivisors A) p
constructor <;> intro h i
· -- Porting note: avoided some defeq abuse
rw [coeff_zero, ← to_map_eq_zero_iff (K := K), hb i, h i, coeff_zero, smul_zero]
· have hi := h i
rw [Polynomial.coeff_zero, ← @to_map_eq_zero_iff A _ K, hb i, Algebra.smul_def] at hi
apply Or.resolve_left (eq_zero_or_eq_zero_of_mul_eq_zero hi)
intro h
apply mem_nonZeroDivisors_iff_ne_zero.mp nonzero
exact to_map_eq_zero_iff.mp h
#align is_fraction_ring.integer_normalization_eq_zero_iff IsFractionRing.integerNormalization_eq_zero_iff
variable (A K C)
/-- An element of a ring is algebraic over the ring `A` iff it is algebraic
over the field of fractions of `A`.
-/
theorem isAlgebraic_iff [Algebra A C] [Algebra K C] [IsScalarTower A K C] {x : C} :
IsAlgebraic A x ↔ IsAlgebraic K x := by
constructor <;> rintro ⟨p, hp, px⟩
· refine ⟨p.map (algebraMap A K), fun h => hp (Polynomial.ext fun i => ?_), ?_⟩
· have : algebraMap A K (p.coeff i) = 0 :=
_root_.trans (Polynomial.coeff_map _ _).symm (by simp [h])
exact to_map_eq_zero_iff.mp this
· exact (Polynomial.aeval_map_algebraMap K _ _).trans px
· exact
⟨integerNormalization _ p, mt integerNormalization_eq_zero_iff.mp hp,
integerNormalization_aeval_eq_zero _ p px⟩
#align is_fraction_ring.is_algebraic_iff IsFractionRing.isAlgebraic_iff
variable {A K C}
/-- A ring is algebraic over the ring `A` iff it is algebraic over the field of fractions of `A`.
-/
theorem comap_isAlgebraic_iff [Algebra A C] [Algebra K C] [IsScalarTower A K C] :
Algebra.IsAlgebraic A C ↔ Algebra.IsAlgebraic K C :=
⟨fun h => ⟨fun x => (isAlgebraic_iff A K C).mp (h.isAlgebraic x)⟩,
fun h => ⟨fun x => (isAlgebraic_iff A K C).mpr (h.isAlgebraic x)⟩⟩
#align is_fraction_ring.comap_is_algebraic_iff IsFractionRing.comap_isAlgebraic_iff
end IsFractionRing
open IsLocalization
section IsIntegral
variable {Rₘ Sₘ : Type*} [CommRing Rₘ] [CommRing Sₘ]
variable [Algebra R Rₘ] [IsLocalization M Rₘ]
variable [Algebra S Sₘ] [IsLocalization (Algebra.algebraMapSubmonoid S M) Sₘ]
variable {M}
open Polynomial
| Mathlib/RingTheory/Localization/Integral.lean | 185 | 201 | theorem RingHom.isIntegralElem_localization_at_leadingCoeff {R S : Type*} [CommRing R] [CommRing S]
(f : R →+* S) (x : S) (p : R[X]) (hf : p.eval₂ f x = 0) (M : Submonoid R)
(hM : p.leadingCoeff ∈ M) {Rₘ Sₘ : Type*} [CommRing Rₘ] [CommRing Sₘ] [Algebra R Rₘ]
[IsLocalization M Rₘ] [Algebra S Sₘ] [IsLocalization (M.map f : Submonoid S) Sₘ] :
(map Sₘ f M.le_comap_map : Rₘ →+* _).IsIntegralElem (algebraMap S Sₘ x) := by |
by_cases triv : (1 : Rₘ) = 0
· exact ⟨0, ⟨_root_.trans leadingCoeff_zero triv.symm, eval₂_zero _ _⟩⟩
haveI : Nontrivial Rₘ := nontrivial_of_ne 1 0 triv
obtain ⟨b, hb⟩ := isUnit_iff_exists_inv.mp (map_units Rₘ ⟨p.leadingCoeff, hM⟩)
refine ⟨p.map (algebraMap R Rₘ) * C b, ⟨?_, ?_⟩⟩
· refine monic_mul_C_of_leadingCoeff_mul_eq_one ?_
rwa [leadingCoeff_map_of_leadingCoeff_ne_zero (algebraMap R Rₘ)]
refine fun hfp => zero_ne_one
(_root_.trans (zero_mul b).symm (hfp ▸ hb) : (0 : Rₘ) = 1)
· refine eval₂_mul_eq_zero_of_left _ _ _ ?_
erw [eval₂_map, IsLocalization.map_comp, ← hom_eval₂ _ f (algebraMap S Sₘ) x]
exact _root_.trans (congr_arg (algebraMap S Sₘ) hf) (RingHom.map_zero _)
|
/-
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.Order.SuccPred.Basic
import Mathlib.Order.BoundedOrder
#align_import order.succ_pred.limit from "leanprover-community/mathlib"@"1e05171a5e8cf18d98d9cf7b207540acb044acae"
/-!
# Successor and predecessor limits
We define the predicate `Order.IsSuccLimit` for "successor limits", values that don't cover any
others. They are so named since they can't be the successors of anything smaller. We define
`Order.IsPredLimit` analogously, and prove basic results.
## Todo
The plan is to eventually replace `Ordinal.IsLimit` and `Cardinal.IsLimit` with the common
predicate `Order.IsSuccLimit`.
-/
variable {α : Type*}
namespace Order
open Function Set OrderDual
/-! ### Successor limits -/
section LT
variable [LT α]
/-- A successor limit is a value that doesn't cover any other.
It's so named because in a successor order, a successor limit can't be the successor of anything
smaller. -/
def IsSuccLimit (a : α) : Prop :=
∀ b, ¬b ⋖ a
#align order.is_succ_limit Order.IsSuccLimit
theorem not_isSuccLimit_iff_exists_covBy (a : α) : ¬IsSuccLimit a ↔ ∃ b, b ⋖ a := by
simp [IsSuccLimit]
#align order.not_is_succ_limit_iff_exists_covby Order.not_isSuccLimit_iff_exists_covBy
@[simp]
theorem isSuccLimit_of_dense [DenselyOrdered α] (a : α) : IsSuccLimit a := fun _ => not_covBy
#align order.is_succ_limit_of_dense Order.isSuccLimit_of_dense
end LT
section Preorder
variable [Preorder α] {a : α}
protected theorem _root_.IsMin.isSuccLimit : IsMin a → IsSuccLimit a := fun h _ hab =>
not_isMin_of_lt hab.lt h
#align is_min.is_succ_limit IsMin.isSuccLimit
theorem isSuccLimit_bot [OrderBot α] : IsSuccLimit (⊥ : α) :=
IsMin.isSuccLimit isMin_bot
#align order.is_succ_limit_bot Order.isSuccLimit_bot
variable [SuccOrder α]
protected theorem IsSuccLimit.isMax (h : IsSuccLimit (succ a)) : IsMax a := by
by_contra H
exact h a (covBy_succ_of_not_isMax H)
#align order.is_succ_limit.is_max Order.IsSuccLimit.isMax
theorem not_isSuccLimit_succ_of_not_isMax (ha : ¬IsMax a) : ¬IsSuccLimit (succ a) := by
contrapose! ha
exact ha.isMax
#align order.not_is_succ_limit_succ_of_not_is_max Order.not_isSuccLimit_succ_of_not_isMax
section NoMaxOrder
variable [NoMaxOrder α]
theorem IsSuccLimit.succ_ne (h : IsSuccLimit a) (b : α) : succ b ≠ a := by
rintro rfl
exact not_isMax _ h.isMax
#align order.is_succ_limit.succ_ne Order.IsSuccLimit.succ_ne
@[simp]
theorem not_isSuccLimit_succ (a : α) : ¬IsSuccLimit (succ a) := fun h => h.succ_ne _ rfl
#align order.not_is_succ_limit_succ Order.not_isSuccLimit_succ
end NoMaxOrder
section IsSuccArchimedean
variable [IsSuccArchimedean α]
theorem IsSuccLimit.isMin_of_noMax [NoMaxOrder α] (h : IsSuccLimit a) : IsMin a := fun b hb => by
rcases hb.exists_succ_iterate with ⟨_ | n, rfl⟩
· exact le_rfl
· rw [iterate_succ_apply'] at h
exact (not_isSuccLimit_succ _ h).elim
#align order.is_succ_limit.is_min_of_no_max Order.IsSuccLimit.isMin_of_noMax
@[simp]
theorem isSuccLimit_iff_of_noMax [NoMaxOrder α] : IsSuccLimit a ↔ IsMin a :=
⟨IsSuccLimit.isMin_of_noMax, IsMin.isSuccLimit⟩
#align order.is_succ_limit_iff_of_no_max Order.isSuccLimit_iff_of_noMax
theorem not_isSuccLimit_of_noMax [NoMinOrder α] [NoMaxOrder α] : ¬IsSuccLimit a := by simp
#align order.not_is_succ_limit_of_no_max Order.not_isSuccLimit_of_noMax
end IsSuccArchimedean
end Preorder
section PartialOrder
variable [PartialOrder α] [SuccOrder α] {a b : α} {C : α → Sort*}
theorem isSuccLimit_of_succ_ne (h : ∀ b, succ b ≠ a) : IsSuccLimit a := fun b hba =>
h b (CovBy.succ_eq hba)
#align order.is_succ_limit_of_succ_ne Order.isSuccLimit_of_succ_ne
theorem not_isSuccLimit_iff : ¬IsSuccLimit a ↔ ∃ b, ¬IsMax b ∧ succ b = a := by
rw [not_isSuccLimit_iff_exists_covBy]
refine exists_congr fun b => ⟨fun hba => ⟨hba.lt.not_isMax, (CovBy.succ_eq hba)⟩, ?_⟩
rintro ⟨h, rfl⟩
exact covBy_succ_of_not_isMax h
#align order.not_is_succ_limit_iff Order.not_isSuccLimit_iff
/-- See `not_isSuccLimit_iff` for a version that states that `a` is a successor of a value other
than itself. -/
theorem mem_range_succ_of_not_isSuccLimit (h : ¬IsSuccLimit a) : a ∈ range (@succ α _ _) := by
cases' not_isSuccLimit_iff.1 h with b hb
exact ⟨b, hb.2⟩
#align order.mem_range_succ_of_not_is_succ_limit Order.mem_range_succ_of_not_isSuccLimit
theorem isSuccLimit_of_succ_lt (H : ∀ a < b, succ a < b) : IsSuccLimit b := fun a hab =>
(H a hab.lt).ne (CovBy.succ_eq hab)
#align order.is_succ_limit_of_succ_lt Order.isSuccLimit_of_succ_lt
| Mathlib/Order/SuccPred/Limit.lean | 144 | 150 | theorem IsSuccLimit.succ_lt (hb : IsSuccLimit b) (ha : a < b) : succ a < b := by |
by_cases h : IsMax a
· rwa [h.succ_eq]
· rw [lt_iff_le_and_ne, succ_le_iff_of_not_isMax h]
refine ⟨ha, fun hab => ?_⟩
subst hab
exact (h hb.isMax).elim
|
/-
Copyright (c) 2020 Devon Tuma. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Devon Tuma
-/
import Mathlib.RingTheory.Ideal.IsPrimary
import Mathlib.RingTheory.Ideal.Quotient
import Mathlib.RingTheory.Polynomial.Quotient
#align_import ring_theory.jacobson_ideal from "leanprover-community/mathlib"@"da420a8c6dd5bdfb85c4ced85c34388f633bc6ff"
/-!
# Jacobson radical
The Jacobson radical of a ring `R` is defined to be the intersection of all maximal ideals of `R`.
This is similar to how the nilradical is equal to the intersection of all prime ideals of `R`.
We can extend the idea of the nilradical to ideals of `R`,
by letting the radical of an ideal `I` be the intersection of prime ideals containing `I`.
Under this extension, the original nilradical is the radical of the zero ideal `⊥`.
Here we define the Jacobson radical of an ideal `I` in a similar way,
as the intersection of maximal ideals containing `I`.
## Main definitions
Let `R` be a commutative ring, and `I` be an ideal of `R`
* `Ideal.jacobson I` is the jacobson radical, i.e. the infimum of all maximal ideals containing I.
* `Ideal.IsLocal I` is the proposition that the jacobson radical of `I` is itself a maximal ideal
## Main statements
* `mem_jacobson_iff` gives a characterization of members of the jacobson of I
* `Ideal.isLocal_of_isMaximal_radical`: if the radical of I is maximal then so is the jacobson
radical
## Tags
Jacobson, Jacobson radical, Local Ideal
-/
universe u v
namespace Ideal
variable {R : Type u} {S : Type v}
open Polynomial
section Jacobson
section Ring
variable [Ring R] [Ring S] {I : Ideal R}
/-- The Jacobson radical of `I` is the infimum of all maximal (left) ideals containing `I`. -/
def jacobson (I : Ideal R) : Ideal R :=
sInf { J : Ideal R | I ≤ J ∧ IsMaximal J }
#align ideal.jacobson Ideal.jacobson
theorem le_jacobson : I ≤ jacobson I := fun _ hx => mem_sInf.mpr fun _ hJ => hJ.left hx
#align ideal.le_jacobson Ideal.le_jacobson
@[simp]
theorem jacobson_idem : jacobson (jacobson I) = jacobson I :=
le_antisymm (sInf_le_sInf fun _ hJ => ⟨sInf_le hJ, hJ.2⟩) le_jacobson
#align ideal.jacobson_idem Ideal.jacobson_idem
@[simp]
theorem jacobson_top : jacobson (⊤ : Ideal R) = ⊤ :=
eq_top_iff.2 le_jacobson
#align ideal.jacobson_top Ideal.jacobson_top
@[simp]
theorem jacobson_eq_top_iff : jacobson I = ⊤ ↔ I = ⊤ :=
⟨fun H =>
by_contradiction fun hi => let ⟨M, hm, him⟩ := exists_le_maximal I hi
lt_top_iff_ne_top.1
(lt_of_le_of_lt (show jacobson I ≤ M from sInf_le ⟨him, hm⟩) <|
lt_top_iff_ne_top.2 hm.ne_top) H,
fun H => eq_top_iff.2 <| le_sInf fun _ ⟨hij, _⟩ => H ▸ hij⟩
#align ideal.jacobson_eq_top_iff Ideal.jacobson_eq_top_iff
theorem jacobson_eq_bot : jacobson I = ⊥ → I = ⊥ := fun h => eq_bot_iff.mpr (h ▸ le_jacobson)
#align ideal.jacobson_eq_bot Ideal.jacobson_eq_bot
theorem jacobson_eq_self_of_isMaximal [H : IsMaximal I] : I.jacobson = I :=
le_antisymm (sInf_le ⟨le_of_eq rfl, H⟩) le_jacobson
#align ideal.jacobson_eq_self_of_is_maximal Ideal.jacobson_eq_self_of_isMaximal
instance (priority := 100) jacobson.isMaximal [H : IsMaximal I] : IsMaximal (jacobson I) :=
⟨⟨fun htop => H.1.1 (jacobson_eq_top_iff.1 htop), fun _ hJ =>
H.1.2 _ (lt_of_le_of_lt le_jacobson hJ)⟩⟩
#align ideal.jacobson.is_maximal Ideal.jacobson.isMaximal
theorem mem_jacobson_iff {x : R} : x ∈ jacobson I ↔ ∀ y, ∃ z, z * y * x + z - 1 ∈ I :=
⟨fun hx y =>
by_cases
(fun hxy : I ⊔ span {y * x + 1} = ⊤ =>
let ⟨p, hpi, q, hq, hpq⟩ := Submodule.mem_sup.1 ((eq_top_iff_one _).1 hxy)
let ⟨r, hr⟩ := mem_span_singleton'.1 hq
⟨r, by
-- Porting note: supply `mul_add_one` with explicit variables
rw [mul_assoc, ← mul_add_one r (y * x), hr, ← hpq, ← neg_sub, add_sub_cancel_right]
exact I.neg_mem hpi⟩)
fun hxy : I ⊔ span {y * x + 1} ≠ ⊤ => let ⟨M, hm1, hm2⟩ := exists_le_maximal _ hxy
suffices x ∉ M from (this <| mem_sInf.1 hx ⟨le_trans le_sup_left hm2, hm1⟩).elim
fun hxm => hm1.1.1 <| (eq_top_iff_one _).2 <| add_sub_cancel_left (y * x) 1 ▸
M.sub_mem (le_sup_right.trans hm2 <| subset_span rfl) (M.mul_mem_left _ hxm),
fun hx => mem_sInf.2 fun M ⟨him, hm⟩ => by_contradiction fun hxm =>
let ⟨y, i, hi, df⟩ := hm.exists_inv hxm
let ⟨z, hz⟩ := hx (-y)
hm.1.1 <| (eq_top_iff_one _).2 <| sub_sub_cancel (z * -y * x + z) 1 ▸
M.sub_mem (by
-- Porting note: supply `mul_add_one` with explicit variables
rw [mul_assoc, ← mul_add_one z, neg_mul, ← sub_eq_iff_eq_add.mpr df.symm, neg_sub,
sub_add_cancel]
exact M.mul_mem_left _ hi) <| him hz⟩
#align ideal.mem_jacobson_iff Ideal.mem_jacobson_iff
theorem exists_mul_sub_mem_of_sub_one_mem_jacobson {I : Ideal R} (r : R) (h : r - 1 ∈ jacobson I) :
∃ s, s * r - 1 ∈ I := by
cases' mem_jacobson_iff.1 h 1 with s hs
use s
simpa [mul_sub] using hs
#align ideal.exists_mul_sub_mem_of_sub_one_mem_jacobson Ideal.exists_mul_sub_mem_of_sub_one_mem_jacobson
/-- An ideal equals its Jacobson radical iff it is the intersection of a set of maximal ideals.
Allowing the set to include ⊤ is equivalent, and is included only to simplify some proofs. -/
theorem eq_jacobson_iff_sInf_maximal :
I.jacobson = I ↔ ∃ M : Set (Ideal R), (∀ J ∈ M, IsMaximal J ∨ J = ⊤) ∧ I = sInf M := by
use fun hI => ⟨{ J : Ideal R | I ≤ J ∧ J.IsMaximal }, ⟨fun _ hJ => Or.inl hJ.right, hI.symm⟩⟩
rintro ⟨M, hM, hInf⟩
refine le_antisymm (fun x hx => ?_) le_jacobson
rw [hInf, mem_sInf]
intro I hI
cases' hM I hI with is_max is_top
· exact (mem_sInf.1 hx) ⟨le_sInf_iff.1 (le_of_eq hInf) I hI, is_max⟩
· exact is_top.symm ▸ Submodule.mem_top
#align ideal.eq_jacobson_iff_Inf_maximal Ideal.eq_jacobson_iff_sInf_maximal
theorem eq_jacobson_iff_sInf_maximal' :
I.jacobson = I ↔ ∃ M : Set (Ideal R), (∀ J ∈ M, ∀ (K : Ideal R), J < K → K = ⊤) ∧ I = sInf M :=
eq_jacobson_iff_sInf_maximal.trans
⟨fun h =>
let ⟨M, hM⟩ := h
⟨M,
⟨fun J hJ K hK =>
Or.recOn (hM.1 J hJ) (fun h => h.1.2 K hK) fun h => eq_top_iff.2 (le_of_lt (h ▸ hK)),
hM.2⟩⟩,
fun h =>
let ⟨M, hM⟩ := h
⟨M,
⟨fun J hJ =>
Or.recOn (Classical.em (J = ⊤)) (fun h => Or.inr h) fun h => Or.inl ⟨⟨h, hM.1 J hJ⟩⟩,
hM.2⟩⟩⟩
#align ideal.eq_jacobson_iff_Inf_maximal' Ideal.eq_jacobson_iff_sInf_maximal'
/-- An ideal `I` equals its Jacobson radical if and only if every element outside `I`
also lies outside of a maximal ideal containing `I`. -/
| Mathlib/RingTheory/JacobsonIdeal.lean | 165 | 176 | theorem eq_jacobson_iff_not_mem :
I.jacobson = I ↔ ∀ (x) (_ : x ∉ I), ∃ M : Ideal R, (I ≤ M ∧ M.IsMaximal) ∧ x ∉ M := by |
constructor
· intro h x hx
erw [← h, mem_sInf] at hx
push_neg at hx
exact hx
· refine fun h => le_antisymm (fun x hx => ?_) le_jacobson
contrapose hx
erw [mem_sInf]
push_neg
exact h x hx
|
/-
Copyright (c) 2020 Heather Macbeth. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Heather Macbeth
-/
import Mathlib.Topology.Algebra.Ring.Ideal
import Mathlib.Analysis.SpecificLimits.Normed
#align_import analysis.normed_space.units from "leanprover-community/mathlib"@"9a59dcb7a2d06bf55da57b9030169219980660cd"
/-!
# The group of units of a complete normed ring
This file contains the basic theory for the group of units (invertible elements) of a complete
normed ring (Banach algebras being a notable special case).
## Main results
The constructions `Units.oneSub`, `Units.add`, and `Units.ofNearby` state, in varying forms, that
perturbations of a unit are units. The latter two are not stated in their optimal form; more precise
versions would use the spectral radius.
The first main result is `Units.isOpen`: the group of units of a complete normed ring is an open
subset of the ring.
The function `Ring.inverse` (defined elsewhere), for a ring `R`, sends `a : R` to `a⁻¹` if `a` is a
unit and `0` if not. The other major results of this file (notably `NormedRing.inverse_add`,
`NormedRing.inverse_add_norm` and `NormedRing.inverse_add_norm_diff_nth_order`) cover the asymptotic
properties of `Ring.inverse (x + t)` as `t → 0`.
-/
noncomputable section
open Topology
variable {R : Type*} [NormedRing R] [CompleteSpace R]
namespace Units
/-- In a complete normed ring, a perturbation of `1` by an element `t` of distance less than `1`
from `1` is a unit. Here we construct its `Units` structure. -/
@[simps val]
def oneSub (t : R) (h : ‖t‖ < 1) : Rˣ where
val := 1 - t
inv := ∑' n : ℕ, t ^ n
val_inv := mul_neg_geom_series t h
inv_val := geom_series_mul_neg t h
#align units.one_sub Units.oneSub
#align units.coe_one_sub Units.val_oneSub
/-- In a complete normed ring, a perturbation of a unit `x` by an element `t` of distance less than
`‖x⁻¹‖⁻¹` from `x` is a unit. Here we construct its `Units` structure. -/
@[simps! val]
def add (x : Rˣ) (t : R) (h : ‖t‖ < ‖(↑x⁻¹ : R)‖⁻¹) : Rˣ :=
Units.copy -- to make `add_val` true definitionally, for convenience
(x * Units.oneSub (-((x⁻¹).1 * t)) (by
nontriviality R using zero_lt_one
have hpos : 0 < ‖(↑x⁻¹ : R)‖ := Units.norm_pos x⁻¹
calc
‖-(↑x⁻¹ * t)‖ = ‖↑x⁻¹ * t‖ := by rw [norm_neg]
_ ≤ ‖(↑x⁻¹ : R)‖ * ‖t‖ := norm_mul_le (x⁻¹).1 _
_ < ‖(↑x⁻¹ : R)‖ * ‖(↑x⁻¹ : R)‖⁻¹ := by nlinarith only [h, hpos]
_ = 1 := mul_inv_cancel (ne_of_gt hpos)))
(x + t) (by simp [mul_add]) _ rfl
#align units.add Units.add
#align units.coe_add Units.val_add
/-- In a complete normed ring, an element `y` of distance less than `‖x⁻¹‖⁻¹` from `x` is a unit.
Here we construct its `Units` structure. -/
@[simps! val]
def ofNearby (x : Rˣ) (y : R) (h : ‖y - x‖ < ‖(↑x⁻¹ : R)‖⁻¹) : Rˣ :=
(x.add (y - x : R) h).copy y (by simp) _ rfl
#align units.unit_of_nearby Units.ofNearby
#align units.coe_unit_of_nearby Units.val_ofNearby
/-- The group of units of a complete normed ring is an open subset of the ring. -/
protected theorem isOpen : IsOpen { x : R | IsUnit x } := by
nontriviality R
rw [Metric.isOpen_iff]
rintro _ ⟨x, rfl⟩
refine ⟨‖(↑x⁻¹ : R)‖⁻¹, _root_.inv_pos.mpr (Units.norm_pos x⁻¹), fun y hy ↦ ?_⟩
rw [mem_ball_iff_norm] at hy
exact (x.ofNearby y hy).isUnit
#align units.is_open Units.isOpen
protected theorem nhds (x : Rˣ) : { x : R | IsUnit x } ∈ 𝓝 (x : R) :=
IsOpen.mem_nhds Units.isOpen x.isUnit
#align units.nhds Units.nhds
end Units
namespace nonunits
/-- The `nonunits` in a complete normed ring are contained in the complement of the ball of radius
`1` centered at `1 : R`. -/
theorem subset_compl_ball : nonunits R ⊆ (Metric.ball (1 : R) 1)ᶜ := fun x hx h₁ ↦ hx <|
sub_sub_self 1 x ▸ (Units.oneSub (1 - x) (by rwa [mem_ball_iff_norm'] at h₁)).isUnit
#align nonunits.subset_compl_ball nonunits.subset_compl_ball
-- The `nonunits` in a complete normed ring are a closed set
protected theorem isClosed : IsClosed (nonunits R) :=
Units.isOpen.isClosed_compl
#align nonunits.is_closed nonunits.isClosed
end nonunits
namespace NormedRing
open scoped Classical
open Asymptotics Filter Metric Finset Ring
theorem inverse_one_sub (t : R) (h : ‖t‖ < 1) : inverse (1 - t) = ↑(Units.oneSub t h)⁻¹ := by
rw [← inverse_unit (Units.oneSub t h), Units.val_oneSub]
#align normed_ring.inverse_one_sub NormedRing.inverse_one_sub
/-- The formula `Ring.inverse (x + t) = Ring.inverse (1 + x⁻¹ * t) * x⁻¹` holds for `t` sufficiently
small. -/
theorem inverse_add (x : Rˣ) :
∀ᶠ t in 𝓝 0, inverse ((x : R) + t) = inverse (1 + ↑x⁻¹ * t) * ↑x⁻¹ := by
nontriviality R
rw [Metric.eventually_nhds_iff]
refine ⟨‖(↑x⁻¹ : R)‖⁻¹, by cancel_denoms, fun t ht ↦ ?_⟩
rw [dist_zero_right] at ht
rw [← x.val_add t ht, inverse_unit, Units.add, Units.copy_eq, mul_inv_rev, Units.val_mul,
← inverse_unit, Units.val_oneSub, sub_neg_eq_add]
#align normed_ring.inverse_add NormedRing.inverse_add
theorem inverse_one_sub_nth_order' (n : ℕ) {t : R} (ht : ‖t‖ < 1) :
inverse ((1 : R) - t) = (∑ i ∈ range n, t ^ i) + t ^ n * inverse (1 - t) :=
have := NormedRing.summable_geometric_of_norm_lt_one t ht
calc inverse (1 - t) = ∑' i : ℕ, t ^ i := inverse_one_sub t ht
_ = ∑ i ∈ range n, t ^ i + ∑' i : ℕ, t ^ (i + n) := (sum_add_tsum_nat_add _ this).symm
_ = (∑ i ∈ range n, t ^ i) + t ^ n * inverse (1 - t) := by
simp only [inverse_one_sub t ht, add_comm _ n, pow_add, this.tsum_mul_left]; rfl
theorem inverse_one_sub_nth_order (n : ℕ) :
∀ᶠ t in 𝓝 0, inverse ((1 : R) - t) = (∑ i ∈ range n, t ^ i) + t ^ n * inverse (1 - t) :=
Metric.eventually_nhds_iff.2 ⟨1, one_pos, fun t ht ↦ inverse_one_sub_nth_order' n <| by
rwa [← dist_zero_right]⟩
#align normed_ring.inverse_one_sub_nth_order NormedRing.inverse_one_sub_nth_order
/-- The formula
`Ring.inverse (x + t) =
(∑ i ∈ Finset.range n, (- x⁻¹ * t) ^ i) * x⁻¹ + (- x⁻¹ * t) ^ n * Ring.inverse (x + t)`
holds for `t` sufficiently small. -/
theorem inverse_add_nth_order (x : Rˣ) (n : ℕ) :
∀ᶠ t in 𝓝 0, inverse ((x : R) + t) =
(∑ i ∈ range n, (-↑x⁻¹ * t) ^ i) * ↑x⁻¹ + (-↑x⁻¹ * t) ^ n * inverse (x + t) := by
have hzero : Tendsto (-(↑x⁻¹ : R) * ·) (𝓝 0) (𝓝 0) :=
(mulLeft_continuous _).tendsto' _ _ <| mul_zero _
filter_upwards [inverse_add x, hzero.eventually (inverse_one_sub_nth_order n)] with t ht ht'
rw [neg_mul, sub_neg_eq_add] at ht'
conv_lhs => rw [ht, ht', add_mul, ← neg_mul, mul_assoc]
rw [ht]
#align normed_ring.inverse_add_nth_order NormedRing.inverse_add_nth_order
theorem inverse_one_sub_norm : (fun t : R => inverse (1 - t)) =O[𝓝 0] (fun _t => 1 : R → ℝ) := by
simp only [IsBigO, IsBigOWith, Metric.eventually_nhds_iff]
refine ⟨‖(1 : R)‖ + 1, (2 : ℝ)⁻¹, by norm_num, fun t ht ↦ ?_⟩
rw [dist_zero_right] at ht
have ht' : ‖t‖ < 1 := by
have : (2 : ℝ)⁻¹ < 1 := by cancel_denoms
linarith
simp only [inverse_one_sub t ht', norm_one, mul_one, Set.mem_setOf_eq]
change ‖∑' n : ℕ, t ^ n‖ ≤ _
have := NormedRing.tsum_geometric_of_norm_lt_one t ht'
have : (1 - ‖t‖)⁻¹ ≤ 2 := by
rw [← inv_inv (2 : ℝ)]
refine inv_le_inv_of_le (by norm_num) ?_
have : (2 : ℝ)⁻¹ + (2 : ℝ)⁻¹ = 1 := by ring
linarith
linarith
#align normed_ring.inverse_one_sub_norm NormedRing.inverse_one_sub_norm
/-- The function `fun t ↦ inverse (x + t)` is O(1) as `t → 0`. -/
theorem inverse_add_norm (x : Rˣ) : (fun t : R => inverse (↑x + t)) =O[𝓝 0] fun _t => (1 : ℝ) := by
refine EventuallyEq.trans_isBigO (inverse_add x) (one_mul (1 : ℝ) ▸ ?_)
simp only [← sub_neg_eq_add, ← neg_mul]
have hzero : Tendsto (-(↑x⁻¹ : R) * ·) (𝓝 0) (𝓝 0) :=
(mulLeft_continuous _).tendsto' _ _ <| mul_zero _
exact (inverse_one_sub_norm.comp_tendsto hzero).mul (isBigO_const_const _ one_ne_zero _)
#align normed_ring.inverse_add_norm NormedRing.inverse_add_norm
/-- The function
`fun t ↦ Ring.inverse (x + t) - (∑ i ∈ Finset.range n, (- x⁻¹ * t) ^ i) * x⁻¹`
is `O(t ^ n)` as `t → 0`. -/
theorem inverse_add_norm_diff_nth_order (x : Rˣ) (n : ℕ) :
(fun t : R => inverse (↑x + t) - (∑ i ∈ range n, (-↑x⁻¹ * t) ^ i) * ↑x⁻¹) =O[𝓝 (0 : R)]
fun t => ‖t‖ ^ n := by
refine EventuallyEq.trans_isBigO (.sub (inverse_add_nth_order x n) (.refl _ _)) ?_
simp only [add_sub_cancel_left]
refine ((isBigO_refl _ _).norm_right.mul (inverse_add_norm x)).trans ?_
simp only [mul_one, isBigO_norm_left]
exact ((isBigO_refl _ _).norm_right.const_mul_left _).pow _
#align normed_ring.inverse_add_norm_diff_nth_order NormedRing.inverse_add_norm_diff_nth_order
/-- The function `fun t ↦ Ring.inverse (x + t) - x⁻¹` is `O(t)` as `t → 0`. -/
theorem inverse_add_norm_diff_first_order (x : Rˣ) :
(fun t : R => inverse (↑x + t) - ↑x⁻¹) =O[𝓝 0] fun t => ‖t‖ := by
simpa using inverse_add_norm_diff_nth_order x 1
#align normed_ring.inverse_add_norm_diff_first_order NormedRing.inverse_add_norm_diff_first_order
/-- The function `fun t ↦ Ring.inverse (x + t) - x⁻¹ + x⁻¹ * t * x⁻¹` is `O(t ^ 2)` as `t → 0`. -/
| Mathlib/Analysis/NormedSpace/Units.lean | 206 | 210 | theorem inverse_add_norm_diff_second_order (x : Rˣ) :
(fun t : R => inverse (↑x + t) - ↑x⁻¹ + ↑x⁻¹ * t * ↑x⁻¹) =O[𝓝 0] fun t => ‖t‖ ^ 2 := by |
convert inverse_add_norm_diff_nth_order x 2 using 2
simp only [sum_range_succ, sum_range_zero, zero_add, pow_zero, pow_one, add_mul, one_mul,
← sub_sub, neg_mul, sub_neg_eq_add]
|
/-
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
| Mathlib/Probability/Martingale/Upcrossing.lean | 242 | 249 | 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)
|
/-
Copyright (c) 2024 Josha Dekker. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Josha Dekker, Devon Tuma, Kexing Ying
-/
import Mathlib.Probability.Notation
import Mathlib.Probability.Density
import Mathlib.Probability.ConditionalProbability
import Mathlib.Probability.ProbabilityMassFunction.Constructions
/-!
# Uniform distributions and probability mass functions
This file defines two related notions of uniform distributions, which will be unified in the future.
# Uniform distributions
Defines the uniform distribution for any set with finite measure.
## Main definitions
* `IsUniform X s ℙ μ` : A random variable `X` has uniform distribution on `s` under `ℙ` if the
push-forward measure agrees with the rescaled restricted measure `μ`.
# Uniform probability mass functions
This file defines a number of uniform `PMF` distributions from various inputs,
uniformly drawing from the corresponding object.
## Main definitions
`PMF.uniformOfFinset` gives each element in the set equal probability,
with `0` probability for elements not in the set.
`PMF.uniformOfFintype` gives all elements equal probability,
equal to the inverse of the size of the `Fintype`.
`PMF.ofMultiset` draws randomly from the given `Multiset`, treating duplicate values as distinct.
Each probability is given by the count of the element divided by the size of the `Multiset`
# To Do:
* Refactor the `PMF` definitions to come from a `uniformMeasure` on a `Finset`/`Fintype`/`Multiset`.
-/
open scoped Classical MeasureTheory NNReal ENNReal
-- TODO: We can't `open ProbabilityTheory` without opening the `ProbabilityTheory` locale :(
open TopologicalSpace MeasureTheory.Measure PMF
noncomputable section
namespace MeasureTheory
variable {E : Type*} [MeasurableSpace E] {m : Measure E} {μ : Measure E}
namespace pdf
variable {Ω : Type*}
variable {_ : MeasurableSpace Ω} {ℙ : Measure Ω}
/-- A random variable `X` has uniform distribution on `s` if its push-forward measure is
`(μ s)⁻¹ • μ.restrict s`. -/
def IsUniform (X : Ω → E) (s : Set E) (ℙ : Measure Ω) (μ : Measure E := by volume_tac) :=
map X ℙ = ProbabilityTheory.cond μ s
#align measure_theory.pdf.is_uniform MeasureTheory.pdf.IsUniform
namespace IsUniform
theorem aemeasurable {X : Ω → E} {s : Set E} (hns : μ s ≠ 0) (hnt : μ s ≠ ∞)
(hu : IsUniform X s ℙ μ) : AEMeasurable X ℙ := by
dsimp [IsUniform, ProbabilityTheory.cond] at hu
by_contra h
rw [map_of_not_aemeasurable h] at hu
apply zero_ne_one' ℝ≥0∞
calc
0 = (0 : Measure E) Set.univ := rfl
_ = _ := by rw [hu, smul_apply, restrict_apply MeasurableSet.univ,
Set.univ_inter, smul_eq_mul, ENNReal.inv_mul_cancel hns hnt]
theorem absolutelyContinuous {X : Ω → E} {s : Set E} (hu : IsUniform X s ℙ μ) : map X ℙ ≪ μ := by
rw [hu]; exact ProbabilityTheory.cond_absolutelyContinuous
theorem measure_preimage {X : Ω → E} {s : Set E} (hns : μ s ≠ 0) (hnt : μ s ≠ ∞)
(hu : IsUniform X s ℙ μ) {A : Set E} (hA : MeasurableSet A) :
ℙ (X ⁻¹' A) = μ (s ∩ A) / μ s := by
rwa [← map_apply_of_aemeasurable (hu.aemeasurable hns hnt) hA, hu, ProbabilityTheory.cond_apply',
ENNReal.div_eq_inv_mul]
#align measure_theory.pdf.is_uniform.measure_preimage MeasureTheory.pdf.IsUniform.measure_preimage
theorem isProbabilityMeasure {X : Ω → E} {s : Set E} (hns : μ s ≠ 0) (hnt : μ s ≠ ∞)
(hu : IsUniform X s ℙ μ) : IsProbabilityMeasure ℙ :=
⟨by
have : X ⁻¹' Set.univ = Set.univ := Set.preimage_univ
rw [← this, hu.measure_preimage hns hnt MeasurableSet.univ, Set.inter_univ,
ENNReal.div_self hns hnt]⟩
#align measure_theory.pdf.is_uniform.is_probability_measure MeasureTheory.pdf.IsUniform.isProbabilityMeasure
theorem toMeasurable_iff {X : Ω → E} {s : Set E} :
IsUniform X (toMeasurable μ s) ℙ μ ↔ IsUniform X s ℙ μ := by
unfold IsUniform
rw [ProbabilityTheory.cond_toMeasurable_eq]
protected theorem toMeasurable {X : Ω → E} {s : Set E} (hu : IsUniform X s ℙ μ) :
IsUniform X (toMeasurable μ s) ℙ μ := by
unfold IsUniform at *
rwa [ProbabilityTheory.cond_toMeasurable_eq]
| Mathlib/Probability/Distributions/Uniform.lean | 105 | 111 | theorem hasPDF {X : Ω → E} {s : Set E} (hns : μ s ≠ 0) (hnt : μ s ≠ ∞)
(hu : IsUniform X s ℙ μ) : HasPDF X ℙ μ := by |
let t := toMeasurable μ s
apply hasPDF_of_map_eq_withDensity (hu.aemeasurable hns hnt) (t.indicator ((μ t)⁻¹ • 1)) <|
(measurable_one.aemeasurable.const_smul (μ t)⁻¹).indicator (measurableSet_toMeasurable μ s)
rw [hu, withDensity_indicator (measurableSet_toMeasurable μ s), withDensity_smul _ measurable_one,
withDensity_one, restrict_toMeasurable hnt, measure_toMeasurable, ProbabilityTheory.cond]
|
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